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LETTER FROM THE EDITOR-IN-CHIEF Dear Reader, I am elated to present to you with Volume V, Issue II of the Journal of Undergraduate Science and Technology (JUST). JUST is truly a campus wide effort and a celebration of not only the extraordinary research that takes place on this campus, but the work conducted by undergraduates specifically. I would like to extend my sincerest thanks to the undergraduate researchers who submitted their work along with the faculty and staff who supported them. I would also like to express my gratitude for the JUST staff that have chosen to make JUST a part of their undergraduate experience and worked diligently to bring you this publication. Additionally, without the generous support of the Wisconsin Institute for Discovery, the Holtz Center for Science and Technology Studies, the College of Agriculture and Life Sciences, and Associated Students of Madison, the publication of this journal would not have been possible. JUST’s mission has always been to support undergraduate researchers and make science accessible to broader audiences. At UW-Madison, we have been uniquely able to provide the opportunity for undergraduates to publish their work in a peer-reviewed journal and give students a glimpse into the publication process of an academic journal. On the other hand, our staff gain exceptional skills and experience the publication process from the perspective of a producer in a scholarly journal. We believe that these experiences are an invaluable supplement to a traditional undergraduate education, especially for those students who wish to continue research.
UW-Madison's only undergraduate STEM research & communication journal
is RECRUITING for Fall 2020! editors | staff writers | designers and accepting submissions for: research reports | editorials | photographs
As for the second part of our mission, I believe that scientific literacy is more important than ever in today’s advancing society. STEM topics have immersed themselves in all aspects of daily life, and all of our lives can only be enriched by a solid understanding of scientific thought. Effective communication of research and science is key to this. We are honored to be a small part in a much larger effort to make research and scientific achievement more accessible to non-expert communities beyond academia. In many ways, the space we occupy on campus mirrors the tenets of the Wisconsin Idea: that the influence of the university should better people’s lives outside of the classroom and across the state. We believe that by helping to train the next generation of researchers and assisting in the dissemination of scientific knowledge, JUST is helping to realize and advance the Wisconsin Idea. This issue serves as my final after two years as the Editor-in-Chief of JUST and four years of involvement in this organization. JUST has brought me incredible opportunities to work with and support talented peers. It has truly been an honor to be a part of this organization and continue to forward its mission. In this issue of JUST, you will find a wide range of scientific disciplines represented both by our peer reviewed reports and our shorter editorials as well as the visual pleasure of scientific imagery. Please join us in making it a tradition to recognize the incredible research and thoughtful written pieces presented by UW-Madison undergraduates, and in our larger pursuit to support science literacy.
Sincerely,
www.justjournal.org | contact@justjournal.org Helen Heo JUST Editor-in-Chief JUST VOL V // ISSUE II // SPRING 2020
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TABLE OF CONTENTS
SPONSORS & PARTNERS
EDITORIALS
EDITOR-IN-CHIEF Helen Heo MANAGING EDITORS Haley Dagenais Stephen Halada
We would like to sincerely thank the Integrated Studies in Science, Engineering, and Society Undergraduate Certificate Program [ISSuES] at UW-Madison; The College of Agriculture and Life Sciences [CALS]; The Wisconsin Institute for Discovery; the Associated Students of Madison (ASM) and Wisconsin Alumni Research Foundation for financially supporting the production of JUST’s Spring 2020 issue. Thank you!
A Gut Feeling: The Connection Between Brain Health and the Gut Microbiota...................6 Jaret Schroeder
And Oh What a Big If: Researchers Investigate Life's Primordial Form..........9 Alex Plum
Microbial Dark Matter........12 DIRECTOR OF FINANCE Aditya Singh
Cate Wilkinson
RNAi: A Novel Approach for Pest Management.....15
DIRECTOR OF MARKETING Tammy Zhong
Timmy Davenport
DIRECTOR OF DESIGN Ashley Harris
PIXELS
WEBMASTER Cayman McKee
Catherine Nguyen...........................................................................18-19
MARKETING ASSISTANT Jenny Lee
Evan Douglas.........19
EDITORS OF CONTENT Ben Fordyce Haley Van Beek Jaitri Joshi Luke Zangl Mary Magnuson
REPORTS Evaluating Solutions to Overcoming Mars Rover Limitations for Autonomous Navigation to Increase Exploration Rate ......22 Victor Freire
COPY EDITOR Mary Magnuson STAFF WRITERS Aadhishre Kasat, Head Staff Writer Aislen Kelly Ryan Brown Anna Feldman Parabhjot Singh
Fear Conditioning and TBI in a Unique Pair of Inbred Rat Strains......30 Justin Magnus
The Journal of Undergraduate Science and Technology (JUST) is an interdisciplinary journal for the publication and dissemination of undergraduate research conducted at the University of Wisconsin-Madison. Encompassing all areas of research in science and technology, JUST aims to provide an open-access platform for undergraduates to share their research with the university and the Madison community at large.
Political, Economic, and Environmental Indicators of the Rick of Polybrominated Diphenyl Ether Exposure in the United States.....36 Evan Douglas
PERSPECTIVES Can They Deliver......................................................................46 Logan Krishka
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SCIENCE + SOCIETY: How to be creative and effective in a rapidly changing environment
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J PHYSIOLOGY
A Gut Feeling: The Connection Between Brain Health and the Gut Microbiota By Jaret Schroeder
It has been said: you are what you eat. This common colloquium is quickly becoming a scientific fact thanks to researchers on the UW-Madison campus. Researchers at UW involved in the Microbiome Initiative, a collective interested in the microbes that live in the human gut, have uncovered links between brain health and the gut microbiota. The gut microbiota refers to the tens of trillions of microorganisms currently living inside of the human gut. These bacteria are influenced by more than 3 million genes and are required for regular tasks inside the intestines, and regulate processes across the entire body [1].
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The exciting role of microbiota as it relates to the human brain has gone unstudied for years, but could now shed light on our understanding of Alzheimer’s Disease. For decades, the two most common pathologies associated with Alzheimer’s Disease have been neurofibrillary tau tangles and the accumulation of the amyloid beta peptide into amyloid plaques, which place oxidative stress on neurons and create inflammation in the brain [2][3]. These tangles and plaques were the only observable phenotypes of Alzheimer’s Disease at a histological level [4]. Recently, the role of gut microbiota has taken
Understanding how the human microbiota influences Alzheimer’s could open new avenues for understanding previous research as well. UW Physician Robert Pryzbelski found a link between decreased Vitamin D metabolism and cognitive decline in older adults in 2007 [11]. Only now are scientists beginning to understand how Vitamin D influences the gut microbiome to change the microbiota of patients suffering from Alzheimer’s Disease. Vitamin D acts as a hormone synthesizer [12]. Its role is to help the intestines absorb other vitamins and nutrients, including Calcium, Magnesium, and Zinc [13]. These nutrients influence brain development, but their effect is variable and can be modulated by intestinal microbiota [12]. Many drugs require microbes to metabolize them into the active form. The lack of microbiota diversity in Alzheimer’s Disease patients jeopardizes their ability to metabolize certain drugs which can also influence treatment options, furthering the need for more research into the connection between the gut and the brain. As the prevalence of Alzheimer’s Disease increases, this interdisciplinary research is highly necessary. A 2016 report from the Alzheimer’s Association predicts that in 2050, one new case of Alzheimer’s Disease will develop every 33 seconds in the United States [14]. Currently, more than 5 million cases are diagnosed every year around the world [15]. With this number quickly rising, research into the complex world of microbiota is necessary to understand the high variability behind Alzheimer’s Disease. This could lead to new preventative treatments. Currently, there is no silver bullet approach to preventing cognitive decline. Alzheimer’s Disease is still a complex issue. However, research into the connection between microbiota and brain health does provide hope for those affected; hope in the form of a gut feeling.
EDITORIAL
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"The microbes that live in the human gut, have uncovered links between brain health and the gut microbiota."
the scientific community by storm for their role in neuronal disease regulation. In a paper from the lab of John Denu, in collaboration with the lab of Frederico Ray, gut microbiota was shown to influence epigenetic states within the host species. In a mouse host model, a group of peptides exhibited altered regulation due to changing gut microbiota. In the study, altering the gut microbiota of mice resulted in the methylation of a post-mitotic histone, leading to a transcriptional response [5]. There is evidence that this molecular response at the level of transcribing proteins could lead to neuroinflammation and to play a role in Alzheimer’s Disease [4]. Inflammation and adaptive immune responses are an area of research that is becoming more heavily studied in relation to Alzheimer’s Disease. The pathology of inflammation from micro- and astro-glial activation offers more insights into the formation of tau tangles and amyloid plaques [6]. Being the defense system of the human body, glial cells patrol the central nervous system and respond to the inflammation caused by amyloid plaques in Alzheimer’s patients [5]. This epigenetic regulation of the immune system and mental disease by gut microbiota offers a new molecular mechanism for understanding Alzheimer’s Disease, but still needs to be researched further. This epigenetic regulation also extends to eukaryotic models other than mice, including human patient models. The lab of Barbara Bendlin has found that the gut microbiota of patients with Alzheimer’s Disease can profoundly affect the severity and progression of the disease. The microbiota signatures of individuals completing a clinical study through the Wisconsin Registry for Alzheimer’s Prevention (WRAP) were examined by performing DNA sequencing on fecal samples. The study found that people living with Alzheimer’s Disease share a unique microbiome signature that is depleted of many of the microbes that reside in the gut of a healthy individual. One of these signatures is a decrease in the microbe Bifidobacterium [7]. This lactic acid bacteria plays a role in decreasing oxidative stress within the intestines [8]. This could correlate to the oxidative stress mechanism caused by amyloid precursor protein cleavage of plaques in the brain [7]. More research is needed. A separate 2018 study utilizing mice showed that three probiotics improved spatial memory and lessened that oxidative stress when administered by intrahippocampal injection [9]. One of these probiotics is Bifidobacterium, confirming the role of these microbes on the human brain. Studies by Bendlin and others show that gut microbiota could act as a manipulatable biomarker for Alzheimer’s Disease [10]. This offers great promise for the development of new preventative treatments against the negative effects of Alzheimer's Disease on cognition.
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J REFERENCES 1. Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, Manichanh C, et al. A human gut microbial gene catalog established by metagenomic sequencing. Nature. 2010;464: 59–65. doi:10.1038/nature08821 2. Markesbery WR. The Role of Oxidative Stress in Alzheimer Disease. Archives of Neurology. 1999;56: 1449– 1452. doi:10.1001/archneur.56.12.1449 3. Akiyama H, Barger S, Barnum S, Bradt B, Bauer J, Cole GM, et al. Inflammation and Alzheimer’s disease. Neurobiol Aging. 2000;21: 383–421. doi:10.1016/s01974580(00)00124-x 4. Kinney JW, Bemiller SM, Murtishaw AS, Leisgang AM, Salazar AM, Lamb BT. Inflammation as a central mechanism in Alzheimer’s Disease. Alzheimer’s & Dementia: Translational Research & Clinical Interventions. 2018;4: 575–590. doi:10.1016/j.trci.2018.06.014 5. Krautkramer KA, Kreznar JH, Romano KA, Vivas EI, Barrett-Wilt GA, Rabaglia ME, et al. Diet-Microbiota Interactions Mediate Global Epigenetic Programming in Multiple Host Tissues. Mol Cell. 2016/11/23. 2016;64: 982– 992. doi:10.1016/j.molcel.2016.10.025 6. Cerovic M, Forloni G, Balducci C. Neuroinflammation and the Gut Microbiota: Possible Alternative Therapeutic Targets to Counteract Alzheimer’s Disease? Frontiers in Aging Neuroscience. 2019;11: 284. doi:10.3389/ fnagi.2019.00284 7. Vogt NM, Kerby RL, Dill-McFarland KA, Harding SJ, Merluzzi AP, Johnson SC, et al. Gut microbiome alterations in Alzheimer’s Disease. Scientific Reports. 2017;7: 1–11. doi:10.1038/s41598-017-13601-y
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EVOLUTION
10. Agahi A, Hamidi GA, Daneshvar R, Hamdieh M, Soheili M, Alinaghipour A, et al. Does Severity of Alzheimer’s Disease Contribute to Its Responsiveness to Modifying Gut Microbiota? A Double Blind Clinical Trial. Front Neurol. 2018;9: 662. doi:10.3389/fneur.2018.00662 11. Przybelski RJ, Binkley NC. Is vitamin D important for preserving cognition? A positive correlation of serum 25-hydroxyvitamin D concentration with cognitive function. Arch Biochem Biophys. 2007;460: 202–205. doi:10.1016/j. abb.2006.12.018 12. Kang MJ, Kim HG, Kim JS, Oh DG, Um YJ, Seo CS, et al. The effect of gut microbiota on drug metabolism. Expert Opin Drug Metab Toxicol. 2013;9: 1295–1308. doi:10.1517/1 7425255.2013.807798 13. Jamilian M, Mirhosseini N, Eslahi M, Bahmani F, Shokrpour M, Chamani M, et al. The effects of magnesium-zinc-calcium-vitamin D co-supplementation on biomarkers of inflammation, oxidative stress and pregnancy outcomes in gestational diabetes. BMC Pregnancy Childbirth. 2019;19. doi:10.1186/s12884-019-2258-y 14. Alzheimer’s Association. 2016 Alzheimer’s Disease facts and figures. Alzheimers Dement. 2016;12: 459–509. doi:10.1016/j.jalz.2016.03.001 15. Qiu C, Kivipelto M, von Strauss E. Epidemiology of Alzheimer’s Disease: occurrence, determinants, and strategies toward intervention. Dialogues Clin Neurosci. 2009;11: 111–128.
And Oh What a Big If: Researchers Investigate Life's Primordial Form By Alex Plum "But if (and oh what a big if) we could conceive in some warm little pond with all sorts of ammonia & phosphoric salts, light, heat, electricity etc. present, that a protein compound was chemically formed, ready to undergo still more complex changes” -Charles Darwin, in a letter to Joseph Hooker (1871) How can life emerge from nonlife? This phenomenon, termed abiogenesis, is perhaps the single most important event in our history. Nearly four billion years ago, it animated Earth, and, although this process may be ubiquitous in the Universe, we only have evidence it happened once. Biology provides the flawed but effective metaphor of a tree of life. Tracing life’s rich evolutionary history over the tree’s buds, bark, and branches, we work our way all the way down to its base, where life began.
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8. Butterfield DA, Swomley AM, Sultana R. Amyloid β-Peptide (1–42)-Induced Oxidative Stress in Alzheimer Disease: Importance in Disease Pathogenesis and Progression. Antioxid Redox Signal. 2013;19: 823–835. doi:10.1089/ars.2012.5027
9. Athari Nik Azm S, Djazayeri A, Safa M, Azami K, Ahmadvand B, Sabbaghziarani F, et al. Lactobacilli and bifidobacteria ameliorate memory and learning deficits and oxidative stress in β-amyloid (1-42) injected rats. Appl Physiol Nutr Metab. 2018;43: 718–726. doi:10.1139/apnm-20170648
But for all that we understand about how life evolved, about the magnificent tree above the soil, we understand relatively about life’s origins, the mysterious root system below. Traced back in time, these roots map the makings of life’s most primitive mechanisms. Their junctions indicate not speciation but rather self-organization, not common descent but rather a creative ascent culminating in the first sprout of life that broke through. Beneath this metaphorical soil, the types of JUST VOL V // ISSUE II // SPRING 2020
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J Countless autocatalytic processes exist in chemistry, and any number of them could play a role in abiogenesis, so researchers in the Baum lab take an eclectic approach to experimentation. Operating without the a priori assumption of any chemical pathway, researchers prepare a highly complex prebiotic environment, one that might give rise to many autocatalytic processes [4,7]. This prebiotic soup contains organic compounds and sources of chemical free energy that might have existed on the early Earth. Pyrite mineral grains are also mixed into the soup as their surfaces provide [AP21] for the more stable [AP22] propagation of some autocatalytic processes. The researchers incubate their model prebiotic soup at room temperature in vials flushed with Nitrogen gas. Theoretical work suggests populations of autocatalytic processes can undergo neighborhood selection on the surface of mineral pyrites, adaptively evolving to [AP23] better compete in [AP24] mineral surface colonization [8,9]. After several days of incubation, researchers extract a fraction of the mineral grains and solution in each vial and inject it into a new vial with freshly prepared contents. By periodically diluting each prebiotic environment in these serial transfers, they expect autocatalytic processes to be selected for their ability to self-propagate and reestablish themselves faster than the imposed dilution rate can eliminate them [6]. Between transfers, the lab uses a diverse array of chemical assays to assess compositional changes in the chemical ecosystem. They then attempt to ascertain whether the observed dynamics match the anticipated life-like dynamics of interacting autocatalytic processes. Preliminary CES experiments have already produced dynamics consistent with life-like chemistry. Consistent oscillations in the concentrations of certain chemicals over time suggest a boom-bust phenomenon similar to that observed in many biological ecosystems [10]. Future work may automate aspects of CES procedures and analyses, enabling researchers to efficiently explore the space of possible parameters that might be conducive to the emergence of life-like dynamics. Complementing their wet-lab experiments, the Baum lab has begun a new line of theoretical work using computational models to simulate the dynamics of autocatalytic processes. By relaxing the constraints of particular chemicals or conditions, they simulate artificial chemistry, treating chemicals and their respective properties entirely in the abstract. With distinct autocatalyt-
EDITORIAL
"Life might be best understood not as a state, but as a process or a pattern in time. "
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ic processes acting like populations of distinct biological species, this approach has demonstrated that competitive, predator-prey, and mutualistic relationships can readily emerge between them [11]. As ongoing work assesses the abundance of autocatalytic cycles within known databases of chemical reactions, researchers may soon apply this approach to evaluate the dynamics of real autocatalytic processes within Earth’s known biochemistry. Furthermore, as researchers apply more powerful analyses to the CES experimental soups, they may use computational models to evaluate candidate autocatalytic processes that are suspected to be present. Beyond contributing to a historical account of our earliest origins, the Baum lab’s work may help researchers to predict the prevalence of life elsewhere in the Universe by clarifying the conditions under which life’s emergence might be possible. Studying the nature of life in its most primitive forms may lead us to understand life as a general process of which life as we know it is just one instance among many. As we uproot the tree of life to analyze the soil, we may come to find that all along we’ve been missing the forest for a tree.
plates: theory of surface metabolism. Microbiological reviews. 1988; 52 (4): 452. 10. Vincent L, et al. Chemical Ecosystem Selection on Mineral Surfaces Reveals Long-Term Dynamics Consistent with the Spontaneous Emergence of Mutual Catalysis. Life. 2019; 9(4): 80. 11. Peng Z, Plum A, Gagrani P, Baum DA. An ecological framework for the analysis of prebiotic chemical reaction networks and their dynamical behavior. arXiv preprint arXiv:2001.02533. 2020 Jan 8.
REFERENCES 1. Fry I. The role of natural selection in the origin of life. Origins of Life and Evolution of Biospheres. 2011; 41 (1): 3-16. 2. Krakauer D, Bertschinger N, Olbrich E, Ay N, Flack JC. The information theory of individuality. arXiv preprint arXiv:1412.2447. 2014. 3. Baum DA. The origin and early evolution of life in chemical composition space. Journal of theoretical biology. 2018; (456): 295-304. 4. Kauffman SA. Autocatalytic sets of proteins. Journal of theoretical biology. 1986; 119 (1): 1-24. 5. Pross A, Pascal R. How and why kinetics, thermodynamics, and chemistry induce the logic of biological evolution. Beilstein journal of organic chemistry. 2017; 13 (1): 665-74. 6. Baum DA, Vetsigian K. An experimental framework for generating evolvable chemical systems in the laboratory. Origins of Life and Evolution of Biospheres. 2017; 47 (4): 481-97.
EDITORIAL
systems eventually giving rise to life remain shrouded in mystery. The complex chemical systems which underlie life’s first replicating cell and last universal common ancestor did not likely arise spontaneously, but complexified from humble beginnings. In this simpler epoch, lifelike chemical systems would have lacked complex structures like DNA and ribosomes for encoding and interpreting genetic information. These structures potentially even lacked membranes to clearly distinguish them from their environments [1]. As the boundaries of these analog amorphous assemblages blur so too do the definitions that would ordinarily distinguish them. We are forced to consider life reduced to its bare essence. Life might be best understood not as a state, but as a process or a pattern in time [2]. This process persists out of thermodynamic equilibrium, consuming free energy to maintain a low entropy relative to its surroundings. Other vital characteristics include an ability to self-propagate, and a capacity for open-ended evolution [3]. None of these characteristics prove easy to achieve or maintain. To self-propagate, a chemical system needs to react both internally and with its environment to constituent chemicals. This recursive chemistry is captured in a phenomenon called autocatalysis. Represented as cycles in chemical reaction networks, simple autocatalytic processes manifest a crude form of self-propagation, their constituents collectively catalyzing their own continuous reaction [4]. They must reckon with diffusive processes and side reactions that tend to tug them back into a more thermodynamically stable chemical equilibrium. However, when a source of free energy drives them to propagate the pattern, they serve faster than they decay into equilibrium, they can achieve a dynamic kinetic stability that outpaces the dissolutive drive of the second law of thermodynamics [5]. As a result, autocatalytic processes may be responsible for rooting life’s primordial possibility firmly in reality. While theories on life’s origins abound, procedures to test their predictions have been in short supply. To address this need and extend the tried-and-true principles of natural selection from evolutionary biology to prebiotic chemistry, an interdisciplinary team of researchers in the lab of Professor David Baum has developed the Chemical Ecosystem Selection (CES) paradigm for studying the origins of life. In CES experiments, a complex but lifeless chemical soup is constructed, then subjected to selective pressures to drive the development of a chemical ecosystem whose constituents exhibit lifelike behaviors [6].
7. Virgo N, Ikegami T. Autocatalysis before enzymes: The emergence of prebiotic chain reactions. InArtificial Life Conference Proceedings 2013 (pp. 240 247). 8. Baum DA. Selection and the origin of cells. Bioscience. 2015; 65 (7): 678-84. Sourced from Publicdomainimages.net 9.
Wächtershäuser G. Before enzymes and temJUST VOL V // ISSUE II // SPRING 2020
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J consider the total number of microbial species to be one trillion, and a recent study figures that only 0.5% of microbes can be cultured, there are about 5 billion culturable microbial species and 995 billion unculturable microbial species [4;1]. Why are those billions of tiny beings import-
MICROBIOLOGY
Figure 1. This picture depicts microscopes on a laboratory bench. Photo by Ousa Chea from Unsplash.
Microbial Dark Matter By Catherine Wilkinson
"Microbial dark matter, a term popularized in recent years, describes a population of microbes that have never been grown in a lab before."
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uncultured microorganisms can be studied through modern sequencing technologies that survey the DNA of environmental samples, species that fall into the “microbial dark matter” category have never been physically grown and studied in a defined medium [2]. In 1985, a similar phenomenon was referred to as “the great plate count anomaly”, which described that less than one percent of microbial cells from certain environments can be cultured with standard methods [3]. As estimates of the number of microbial species that inhabit Earth constantly increase, a 2016 study predicted that one trillion microbes call the world around us, home [4]. So, if we
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EDITORIAL
When you hear the words “dark matter”, you mind probably wanders to black holes somewhere amongst the stars, Einstein, and a whir of physics equations seeking to solve the unanswered questions of space, time and the galaxies. But, what if instead of unknown matter and strange worlds far away from our home, there was a largely undiscovered one all around us, within us, and embedded in our everyday lives? Microbial dark matter, a term popularized in recent years, describes a population of microbes that have never been grown in a lab before [1]. Though some
ant to us? Scientists continue to study already isolated model organisms, such as Escherichia coli, that provide a detailed understanding of much of the microbial world. And, since all of life shares many essential components, these microbial model organisms have expanded our knowledge about human biology and other life forms. For example, E. coli have a small genome that is completely known and much less complex than a human’s [5]. E. coli also grows quickly in a controlled laboratory setting on well-defined media. These characteristics make E. coli a perfect subject for molecular studies, and so much of our basic understanding of molecular biology (i.e. DNA replication, the genetic code, and the expression of genes) comes from studying this organism [5]. Another interesting model organism is Dictyostelium discoideum, a “social amoeba” and phagocyte that is easily cultured [6]. Though you might not expect it, D. discoideum has proved to be a useful model for understanding the treatment and development of certain human diseases [6]. More recently, this model amoeba has provided insight into the cytopathology, or the cellular study, of mitochondrial and neurodegenerative diseases [6]. Microorganisms have a remarkably diverse array of applications due to their wide variety of capabilities, allowing us to uncover so much about the fundamentals of biology! Through years of study scientists have come to realize that microorganisms are extremely diverse; their ability to persist in both accessible and unthinkable environments is extraordinary. Scientists have uncovered microbes that thrive in hot springs, the arctic tundra, the human skin, an animal’s stomach, and many other unique niches. Another way to think about the expanse of microbial diversity is by understanding that the differences between an E. coli’s biological processes and those of other bacteria, could be more vast than the differenc-
es between a zebra and a pine tree! With this range of capabilities discovered in already known bacteria, there is undoubtedly a great amount of biological potential buried within microbial dark matter and uncultured species. Using innovative techniques, we can, and are, beginning to tap into it. Technologies such as metagenomics, invented right here at UW Madison in Dr. Jo Handelsman’s lab, have recently taken us to great heights in understanding the uncultured microbial realm. Metagenomics, or “the genomic analysis of a population of microorganisms,” is done by extracting genomic DNA directly from environmental samples and cloning it to make many copies of the DNA so that it can be sequenced and analyzed [2]. This process allows microbiologists to learn about the genetics and physiology of microbial systems while bypassing the limitations surrounding physical growth in a lab. And, since so many microorganisms are elusive and tricky to culture, metagenomics empowers discoveries about otherwise completely mysterious microbial beings [2]. For example, metagenomics in concert with other techniques has proven to be a useful tool for uncovering metabolic capabilities of unculturable bacteria, specifically, the production of novel enzymes. These naturally produced biocatalysts initiate or speed up chemical reactions that are relevant to a variety of industries [7]. For instance, naturally sourced biocatalysts can be used to breakdown biomass, a necessary step in the production of biofuels. They can also be used to carry out reactions that allow for flavor development in baked goods [7]. Metagenomics has been used in a variety of studies to make important contributions to understanding the world around us. Scientists have harnessed this technology to understand how microbial communities in the deep sea were impacted by the Deepwater Horizon oil spill in the Gulf of Mexico [8]. Researchers have also applied metagenomics to study microorganisms that inhabit the surfaces of New York City, ultimately creating a “baseline metagenomic map of NYC.” [9]. So, even without direct cultivation of microorganisms we’ve been able to extract novel and useful information from them. But this hasn’t always been the case. Pure culture studies dominated the world of microbiology for many years. This approach involves the isolation of a single microbial species using selective methods in a laboratory setting. Because the focus is on one organism alone, some extraneous factors that could make results cloudy and error prone are eliminated. The “power and precision,” of these studies have given scientists a way of diving deep into the world of culturable microorganisms [2]. Researchers have found, though, that this approach is not fully representative of microbial diversity. Some microorganisms occupy a niche so specific and complex that it becomes extremely difficult to replicate in a laboratory setting. For example, interactions with other organisms might be an essential part of a microbe’s ability to gain necessary nutrients for survival in its ecosystem. As the name suggests, a pure culture study would eliminate the possibility of these
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J interactions altogether and so organisms that require cooperation wouldn’t be represented. While this culturing of microbes has already deepened our understanding of the microbial world, being able to expand this technique to study previously unculturable organisms would extend our knowledge so much further! In order to culture microbes with such particular growth requirements, we need new perspectives and innovation. Researchers at UW Madison and beyond are already diving into this new era of microbial cultivation with novel and creative solutions. These range from the construction of bioreactors designed to simulate a natural soil environment, to co-culturing microorganisms that are known to cooperate, ultimately creating an environment where novel antibiotics can be produced [10; 11].
Figure 2. "File:Dictyostelium discoideum fb 2.jpg" by Tyler Larsen is licensed under CC BY-SA 4.0
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1. Lloyd KG, et al. Phylogenetically Novel Uncultured Microbial Cells Dominate Earth Microbiomes. mSystems. 2018 Sep-Oct;3(5): e00055-18. doi: 10.1128/ mSystems.00055-18 2. Handelsman J. Metagenomics: Application of Genomics to Uncultured Microorganisms. Microbiol Mol Biol Rev. 2004 Dec;68(4): 669-685. 3. Staley JT, Konopka A. Measurement of in situ activities of nonphotosynthetic microorganisms in aquatic and terrestrial habitats. Annu Rev Microbiol. 1985;39:321–346. doi:10.1146/annurev. mi.39.100185.001541 4. Locey KJ, Lennon JT. Scaling Laws Predict Global Microbial Diversity. PNAS. 2016; 113(21): 59705975. 5. Cooper GM. Cells as Experimental Models. In: The Cell: A Molecular Approach. 2nd edition. Sunderland (MA): Sinauer Associates; 2000. 6. Annesley SJ, Fisher PR Dictyostelium discoideum—a model for many reasons. Mol Cell Biochem. 2009; 329:73–91. 7. Madhavan A, et al. Metagenome Analysis: a Powerful Tool for Enzyme Bioprospecting. Appl Biochem Biotechnol. 2017 Oct;183(2): 636-651. 8. Mason OU, Scott NM, Gonzalez A, et al. Metagenomics reveals sediment microbial community response to Deepwater Horizon oil spill. ISME J. 2014;8(7):1464–1475. 9. Afshinnekoo E, Meydan C, Chowdhury S, et al. Geospatial Resolution of Human and Bacterial Diversity with City-Scale Metagenomics. Cell Syst. 2015;1(1):72–87. 10. Chaudhary DK, Khulan A, Kim J. Development of a Novel Cultivation Technique for Uncultured Soil Bacteria. Scientific Reports. 2019 April;9(1): 6666. 11. Adnani N, et al. Investigation of Interspecies Interactions within Marine Micromonosporaceae Using an Improved Co-Culture Approach. Mar Drugs. 2015 Oct;13(10): 6082–6098.
ENVIRONMENT
RNAi: A Novel Approach to Pest Management By Timothy Davenport "The need for holistically understanding the ecological risks associated with pest management techniques is vital for environmentally conscious decision making." The Modern Plague of Chemicides From the dawn of agriculture, farmers have relied on the resources at their disposal to optimize the growth of their crops. In recent times, synthetic pesticides have proven to be an efficient and effective way of mitigating the destruction of crops by pests, and chemical pesticides have become standard practice for ridding fields of organismal nuisances. The affordability and effectiveness of chemical pesticides have contributed to their widespread use in pest management. With this, the need for sustainable pest treatment methods that do not threaten the viability of surrounding ecosystems is important for environmentally conscious farming practices.
A History of Environmental Neglect Although farmers and consumers receive the shortterm benefits of pesticides, synthetic chemicals have long term consequences on ecosystems which may outweigh their convenience. These synthetic pesticides can lead to a biomagnification effect on ecosystems when an accumulation of typically toxic substances in plants and animals increases in abundance moving up the food chain. Biomagnification of toxic commercial pesticides can derail the stability of ecological communities and threaten the overall surrounding ecosystems. The use of dichlorodiphenyltrichloroethane (DDT) in the 20th century is a classic example of chemical pesticide toxicity through ecosystem biomagnification. JUST VOL V // ISSUE II // SPRING 2020
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Whatever the case, uncovering the diverse array of biological processes performed by microbes can provide great insights into the microscopic world and ultimately uncover answers to questions already being posed, while prompting questions we never thought to ask. With the development of novel culturing techniques and the utilization of sequencing technologies such as metagenomics, microbiologists are well on their way to tapping the potential of those microorganisms that once seemed unreachable. Just as physicists will continue to explore and discover the implications of dark matter, microbiologists will strive to investigate the fascinating, mighty microbes that inhabit the world that is within and around us.
REFERENCES
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J In the 1940s, DDT was introduced to the world [2]. This aerosol-based chemical pesticide was effective at eradi cating unwanted organisms such as mosquitoes and was deployed throughout the United States and around the world [2]. The pesticide became woven into 1950s American culture as being a harbinger for summer as beach-wide sprays were a common practice to keep mosquitoes off fellow beachgoers (Fig. 1).
These insects can infect crops and extract nutrients from the plants [8]. This feeding process starves the plant of nutrients and can be lethal. Soybean aphids have short life spans but high reproductive rates such that a single aphid can have hundreds of offspring at a time [8]. Thousands of these insects can inhabit a single leaf of the soybean crop, posing a substantial threat to soybean fields (Fig. 3) [7]. Fig. 4. Sketch of the general mouthpiece morphology of a common aphid [1].
encoded for a desired trait [5]. Each method holds the potential to revolutionize the way agribusinesses protect their crops against invasive species. However, the prospective ecological and economic costs of RNAi question whether this practice will be truly suitable for addressing environmental and monetary burdens proposed by farmers and environmentalists at scale.
Fig. 1. Clouds of DDT are dispersed into the air engulfing fellow beachgoers during a spray along a beach [2].
However, the environmental impacts of this ‘miracle pesticide’ were still unknown. After application, the DDT would run off from fields into surrounding bodies of water where fish and other aquatic organisms would ingest them [2]. Bird populations that fed off the poisoned fish suffered rapid population loss as eggs were softened by DDT and embryos were left more susceptible to premature death [2]. This example of DDT serves as a lesson for understanding the consequences of artificially constructed substances on native ecosystems. Interestingly, despite the current ban of DDT in countries such as the United States, some countries still use this chemical to reduce the transmission of mosquito-borne diseases, which demonstrates governments balancing healthcare security needs over environmental protectionism [2].
Fig. 2. Photography of a soybean aphid, an organism invasive to North America [7].
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Farmers continually battle the soybean aphids to maintain the viability of the soybean harvest, and chemical pesticides prove effective, but toxic solutions to controlling this pest. One emerging treatment method for countering the infestation of soybean aphids is the use of RNAi biomolecules as a species-specific biological control method [11]. This practice eliminates the broad range of chemical toxins that are released onto fields and surrounding environments that threaten surrounding ecosystems. RNAi technology highlights a new era of pest management solutions that aim to relieve farmers of soybean aphid infestation while minimizing harm to non-target wildlife. RNAi - How it works In terms of how RNAi works on a molecular level, the biomolecule suppresses the production of proteins [11]. RNAi is bioengineered to be complementary to mRNA, which normally makes proteins [4]. When RNAi pairs with the mRNA before protein synthesis, the mRNA is destroyed and levels of the associated protein remain low [4]. This technique can be used as a pesticide by targeting the production of viral proteins. Engineering of RNAi to target specific proteins is critical to the versatility of this biotechnology. Current RNAi target virus proteins located in the mouthpiece of the soybean aphid (Fig. 4). This virus governs the feeding capabilities of the soybean aphid, so inhibiting the replication process of the virus can be lethal to the aphid [11]. Currently, RNAi can be applied to soybean plants in two main methods. One is through the application of an RNAi aerosol spray which is directly applied onto the leaves of the soybean plant [9]. The second is the development of transgenic soybean plants which contain the capability of self-producing RNAi biomolecules [10]. Transgenic plants contain genetically engineered DNA
The Bottom Line Due to high initial adoption costs and unforeseen environmental damages, the practicality of pest management with RNAi comes into scrutiny. If it were to be assured that RNAi biomolecules do not pose a reasonable environmental threat, government subsidies to cover the prospective high costs of RNAi could stimulate the interest of local farmers to adopt this practice. Yet, even if RNAi
REFERENCES 1. Dixon A. Aphids and Translocation. Transport in Plants. 1975; 1: 154-170. 2. Environmental Protection Agency (EPA). 2017. DDT - A Brief History and Status. https://www.epa.gov/ingredients-used-pesticide-products/ddt-brief-history-and-status 3. Friederici P. (2012). Is DDT Here to Stay? Audubon. https://www.audubon.org/magazine/may-june-2012/is-ddthere-stay 4. Hardin J. and Bertoni G. Becker’s World of the Cell. Pearson. 2016; 9: 608. 5. Jhansi Rani S. and Usha R. Transgenic plants: Types, benefits, public concerns and future. Journal of Pharmacy Research. 2013; 6: 879-883. 6. National Oceanic and Atmospheric Administration (NOAA). 2019. What is an invasive species? https://oceanservice.noaa.gov/facts/invasive.html 7. Purdue University (2009). Soybean Aphid. Purdue University. https://extension.entm.purdue.edu/fieldcropsipm/insects/soybean-aphid.php 8. University of Nebraska-Lincoln. 2019. Managing Soybean Aphids. https://cropwatch.unl.edu/managing-soybean-aphids 9. Yan S, Qian J, Cai C, Ma Z, Li J, et al. Spray method application of transdermal dsRNA delivery system for efficient gene silencing and pest control on soybean aphid Aphis glycines. Journal of Pest Science. 2019; 1-11. 10. Yang X., Niu L., Zhang W., He H., Yang J, et al. Increased multiple virus resistance in transgenic soybean overexpressing the double-strand RNA-specific ribonuclease gene PAC1. Transgenic Research. 2018; 28: 129-140. 11. Yu X., Liu Z., Huang S., Chen Z., Sun Y, et al. RNAi-mediated plant protection against aphids. Pest Management Science. 2016; 72: 1090-1098. JUST VOL V // ISSUE II // SPRING 2020 17
EDITORIAL
EDITORIAL
The Aphid Attack and RNAi Soybean aphids (Aphis glycines) are an invasive species that consume the soybean plant (Glycine max) (Fig. 2). Invasive species are organisms that cause ecological or economic damages in an introduced non-native environment [6]. The accidental introduction of soybean aphids into the United States from Eastern Asia in the early 2000s has created a sizable threat for soybean farmers across the Midwest, where most American soybeans are grown.
Fig. 3. A cluster of soybean aphids feeding off the leaf of a soybean crop (Purdue University, 2009).
Notes of Concern Although RNAi appears a promising novel solution for curbing chemical pesticide use, this method is still unavailable for public use. This is due to ongoing investigations on the long-term effects of RNAi molecules, which may pose potential environmental damages akin to ones seen with DDT. RNAi has emerged within the past five years which is an insufficient time period for thorough environmental studies to prove this solution is of best interest for ecosystems [9]. Nevertheless, the sequence-specificity of the product itself would, in theory, only affect the soybean aphid [9]. Additionally, if this product, whether in aerosol or transgenic plant form, were to be newly introduced in a market, the initial monetary cost for effective use may be too high for the practical adoption by local farmers. This is a problem for working towards a holistic solution to combating the toxic chemical pesticides, as farmers who cannot feasibly afford the cost of RNAi treatment would continue to use environmentally damaging pesticides. This raises the opportunity for government subsidies to stipend soybean farmers in RNAi adoption since providing a monetary reward for changing farming practices would incentivize farmers to invest in the new technology once it becomes available. Despite the prospective drawbacks of RNAi, sustainable pest management strategies should be a priority for farming in the modern era. As demonstrated through the catastrophes of past unsustainable pest management, the need for holistically understanding the ecological risks associated with pest management techniques is vital for environmentally conscious decision making.
imposes threats to local ecosystems, the efforts to pursue sustainable pest management is the mindset innovators must hold to reach effective solutions against ecological degradation. Farmers work under the common value of providing food security domestically and abroad. With this, the means by which this goal is accomplished may be through unsustainable pest management strategies. Humans also bear the moral obligation to protect the longevity of species, which further drives the idea that agribusinesses should adopt ecologically conscious management practices in order to progress global ecological conservation. Whether RNAi is the best solution for solving the damaging pesticide practices currently used by the soybean industry cannot be concluded. Yet, the strategies used to tackle soybean aphid infestation, or any infestation of an invasive organism, must consider the ecological risks associated with a given treatment. As exemplified through the mistakes learned through the popularization of DDT, the externalities of non-specific synthetic pesticides are too great of a risk to ignore. Neglecting to acknowledge the potential damage to ecosystems caused by any pesticide is negligence to a shared duty for ensuring the vitality of the environment for the generations to come.
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Evan Douglas: Giants Among Giants
where science and art collide
Catherine Nguyen: Hawaiian bobtail squid (Euprymna scolopes) hatchlings viewed under a Leica M60 stereo microscope (Mandel Lab).
Catherine Nguyen: An African Buffalo ((Syncerus caffer) resting in a waterhole located in Hluhluwe-Imfolozi game reserve within South Africa.
Catherine Nguyen: Herbivores stick together in Hluhluwe-Imfolozi game reserve located in South Africa. A herd of zebras and giraffes grazing together.
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Evaluating Solutions to Overcoming Mars Rovers Limitations for Autonnomous Navigation to Increase Exploration Rate.............................22 As resources on Earth are depleted, extraterrestrial resources become increasingly appealing as a way of sustaining life. Mars rovers help this cause by exploring that which lies beyond the confines of Earth. The last remaining rover operating on Mars is NASA’s Curiosity [3]. The robot has exceeded mission expectations for days survived and terrain covered, however efficiency fell behind projections (Figure 1) early on [4]. By assessing the limitations of technology that underlie the diminished efficiency of Mars rovers and considering the advances in research on automation, we can revolutionize rover design to more effectively explore other planets.
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Fear Conditioning and TBI in a Unique Pair of Inbred Rat Strains.........................................30 Post-traumatic stress disorder (PTSD) and traumatic brain injuries (TBI) increase the chance of suicidal tendencies and neuropsychiatric disorders in military veterans. If left untreated and misunderstood, thousands of returning veterans will struggle to adjust to civilian life and could, in some cases, go as far as taking their own life. Therefore, it is important to understand how PTSD and TBI affect veterans. Using a rat model, fear conditioning and mTBI (mild traumatic brain injury) are analyzed to understand why different responses were recorded for rats of different genetic backgrounds, Perforant Path Kindling Susceptible (PPKS) and Perforant Path Kindling Resistant (PPKR). A fast kindling (FK) rat with the PPKS strand is more susceptible to seizure-induced plasticity, than a slow kindling (SK) rat with the PPKR strand (Langberg, 2016). Our preliminary studies show that TBI by controlled cortical impact results in more frequent seizures in FK rats compared to SK rats. Injured, TBI, FK rats in this study were found to have recorded freezing times similar to those of uninjured, SHAM (faked surgical intervention), FK rats. Our results suggest that FK rats are genetically dispositioned to respond better to injury and fear stimulus than SK rats.
Political, Economic and Enviornmental Indicators of the Risk of Polybrominated Diphenyl Ether Exposure in the United States ............................36 PBDEs, or polybrominated diphenyl ethers, have yet to be disbanded in the United States, as there has been little political intervention on a national scale despite the danger posed to humans and the environment from exposure. PBDE exposure has been shown to negatively impact the health of animals in experimental studies, so understanding potential risk factors that correlate to high exposure can give humans a better understanding of their risk in a given area. The purpose of this study was to investigate the correlation between political, economic, and environmental factors and risk of PBDE exposure, and to then create an index that consolidates these indicators into a score that can be used to evaluate levels of risk in a given location. We quantified potential risk indicating variables for nine U.S. states, and then combined assigned values into an index score representative of each state’s level of risk of exposure. We then evaluated the relationship of these index scores to PBDE dumping on site, infant mortality rates and cancer incidence rates for each state in this study. Our results suggest that the index can predict risk of exposure based on these categorical variables because risk scores were proportional to levels of pollution and related to the ramifications of exposure shown in animal studies for humans. By using this index, states can assess their current status of PBDE risk of exposure based on political associations, economic conditions and relative environment instead of levels of pollution to evaluate policy directed at PBDE usage in a more comprehensive manner.
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Evaluating Solutions to Overcominng Mars Rovers Limitations for Autonomous navigation to Increase Exploration Rate Victor Freire Department of Mechanical Engineering University of Wisconsin - Madison
INTRODUCTION As resources on Earth are depleted, extraterrestrial resources become increasingly appealing as a way of sustaining life. Mars rovers help this cause by exploring that which lies beyond the confines of Earth. The last remaining rover operating on Mars is NASA’s Curiosity [3]. The robot has exceeded mission expectations for days survived and terrain covered, however efficiency fell behind projections (Figure 1) early on [4]. By assessing the limitations of technology that underlie the diminished efficiency of Mars rovers and considering the advances in research on automation, we can revolutionize rover design to more effectively explore other planets.
Autonomous rovers don’t need instructions from Earth, but they can’t survive on Mars. Recently, research efforts towards production of self-driving cars, smart delivery drones, and other autonomous systems have increased. Technology behind these advances can serve as a foundation for improving rovers by introducing autonomous navigation as a solution to the communication delay problem [8]. However, environmental factors specific to Mars make it challenging to implement [4]. Table 1 highlights some of these limitations. The distance between Mars and Earth puts an upper limit on the amount of data sent back and forth in a reasonable time. When sending many instructions at once, data travels slow and some can get lost or obscured along the way [7]. This limitation can be addressed by implementing machine learning algorithms. Machine learning is a nov-
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How can current research overcome Mars limitations for autonomous navigation? This report describes and evaluates four research studies that identify solutions to the limitations introduced. Unsupervised machine learning increases exploration rate by reducing amount of data sent to Mars. I recommend computer vision classification of terrain as the most promising technology. Thermal inertia measurements can enhance this terrain classification. Efficient slope ascent helps sustain CPU intensive algorithms such as image processing. Despite surpassing mission projections for total duration and terrain covered, Curiosity has been inefficient in exploring the Red Planet. Data shown is from NASA and Lamarre [1, 4].
This section describes and analyzes research studies that overcome Mars-specific limitations to autonomy. The analysis critiques each technology on its ability to increase a rover’s exploration rate. 2.1 Unsupervised machine learning to reduce amount of data transferred When NASA sends commands to Curiosity, they are specific. For instance: “rotate front-right wheel half a degree clockwise” [9]. This degree of command specialization compounds, resulting in large amounts of data sent to Mars. The more data sent, the more delay in the message [7]. Whenever data is in transit, the Mars rover sits idle and is not exploring. A research group led by Jones at North Dakota State University, funded by The Boeing Company, proposed unsupervised machine learning to reduce the number of commands sent [9]. Their model would allow NASA rover operators to send more general goals to the Mars rover [9]. For example: “traverse forward 20 meters and then setup for science cache collection.” With this model, the rover makes all small-scale decisions autonomously to accomplish the specified broader goal. This reduces the amount of data sent through space and increases exploration efficiency. Trends in sensor data guide the rover to make the appropriate small-scale decision at any time [9]. For example, after a few days’ worth of temperature logging, the rover would know around what time it starts getting cold. The rover then optimizes heater control by predicting when temperature is about to drop. Unsupervised learning identifies data trends without human input [9]. This opposes supervised learning, which requires a training set [9]. This approach is especially useful in unknown environments such as that of Mars. One drawback to this technology is that it requires high computational power to process data and identify trends [8]. It is also prone to making mistakes that could be mission-ending [8]. This happens because it does not account for certain external conditions that make data appear trend- like when it is not. For example, a dust storm passing by may lead the rover to interpret its surroundings as though it’s getting dark, forcing it into hibernation mode as if it were nighttime. Despite these drawbacks, unsupervised machine learning could be the first step towards a fully autonomous rover. By abstracting rover control and reducing the amount of data sent to Mars, the exploration efficiency increases. 2.2 Computer vision terrain classification to avoid rocky terrain Mars terrain is difficult to categorize by sight. Early in Curiosity’s mission, NASA operators misread the terrain and drove the rover over jagged rocks that damaged its wheels [4]. Operators use static black and white images to judge an uneven surface and they face the pressure of time when plotting a path for the rover [4,10]. As
Robotics expert from Carnegie Mellon University and California Institute of Technology’s (Caltech’s) Jet Propulsion Lab collaborated to develop the Soil Property and Object Classification (SPOC) software package [10]. This program classifies features like rock size, contrast, and brightness in terrain pictures. To train the program, developers feed it with a set of images having some of these features in common to calibrate it [10]. The SPOC program will then classify any future images according to the learned patterns [10]. For example, the developers ran pre-labeled sand images through SPOC [10]. The program was then able to find sand in unlabeled images that contained a mixture of terrain types. The success of SPOC was only possible because of advances in image processing techniques. Traditional computer vision relies on labeling each individual pixel and finding patterns [11]. Recent advances in the field allow algorithms to account for the color of neighboring pixels [10]. SPOC benefited from these advances to find boundaries between terrain classes [10]. The group developing SPOC collaborated with Curiosity’s team to test the algorithm. Figure 2 shows actual footage of Mars taken by Curiosity and passed through SPOC. One drawback of SPOC is the computational complexity; image processing programs demand high performance computers [11]. Another disadvantage is that it requires a training set. The uncalibrated algorithm will not work in the early stages of a mission when traversing virgin land. The program may also need new terrain classes defined as the mission progresses and the planet is explored. This will require NASA operators to alter SPOC’s source code and delay the mission. Despite these drawbacks, computer vision is still a promising technology. The greatest advantage of image processing is that it is fast, about 2-3 minutes [12]. This short delay outweighs the alternative of sending the image to earth and awaiting commands (up to 1-hour total delay). The rover can then avoid traversing large rocks to prevent damaging its wheels. It can also prioritize traversing dunes that are more spaced apart. These time-saving benefits have the potential to increase exploration efficiency. Because of this, I consider computer vision one of the most promising immerging technologies for Mars rover autonomy. 2.3 Thermal inertia measurements to predict wheel slip Hills of loose sand are commonplace on Mars [13]. This type of terrain is hard to traverse for wheeled robots, like Mars rovers, because they tend to slip and lose traction. When wheels slip, the rover thinks it’s farther along a path than it actually is [14]. This is the case because rovers keep mileage like a normal car: based on wheel rtations and assuming no-slip [14]. Mars rovers combat wheel slip with the help of computer vision. The rover takes sequences of images as it drives to track disJUST VOL V // ISSUE II // SPRING 2020
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Signal delays are responsible for Curiosity’s low exploration efficiency Remote control is the primary navigation mode for all Mars rovers [5, 6]. In this mode, operators send commands from Earth to direct the robot. Interplanetary communications are slow due to the long distance that signals must travel [7]. It can take up to 30 minutes to send a drive command to Curiosity [7]. These delays limit the speed with which NASA is able to communicate with its rovers.
el technique that aims to reduce amount of commands a robotic system needs to receive, abstracting control as much as possible. Rocky terrain can damage rover wheels as it traverses the Martian landscape. This means autonomous navigation programs must identify the terrain ahead of the vehicle in order to avoid the most dangerous routes. To this end, computer vision identifies patterns in pictures to provide a layer of environment awareness. The sandy nature of Mars makes rovers prone to wheel slippage. This issue is concerning on two fronts because in addition to potentially getting permanently stuck, it renders the rover’s odometer useless. When the wheels slip, the rover’s position estimator changes while its actual location does not. The concept of terrain thermal inertia is explored as a predictor for wheel slip. The cold temperatures and low energy availability of Mars force space-approved computers to be slow by design. Saving energy while traversing is crucial to ensure the computer has enough energy available. One proposed way to reduce excess energy usage is efficient slope ascension.
RESEARCH
this occurs, Curiosity sits idle and is unable to continue its exploration [10]. One aspect of analyzing images includes determining the distance between sand dune crests [10]. Curiosity traverses dunes best when crests lie farther apart [10].
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J 2.4 Energy efficient slope ascent to reduce rover power usage Cold temperatures on Mars force rovers to keep electronics warm, using a lot of power [18]. Additionally, since the atmosphere on Mars is a lot thinner than on Earth, daily temperature swings are greater [18]. On any given day, Mars surface temperature can vary up to 200 degrees Fahrenheit [18]. Electronic equipment performs best when temperature is warm and steady [17]. Curiosity uses heaters, radioactive decay, and cooling fins to maintain the electronics at a constant, mild temperature [18]. This temperature regulation equipment consumes a lot of energy. When computers perform intense work and process large amounts of data, they heat up quickly. Heat sinks are aluminum structures that extend the surface area of a CPU in contact with air. Curiosity’s heat sinks, aided by fans, dissipate heat and cool down the electronics [17]. This cooling technique works well on Earth. However, the thin Martian atmosphere limits the performance of heat sinks [16]. These limitations make space-approved computers even slower than those available to the public [17]. Sakayori and Ishigami, funded by the Institute of Electrical and Electronics Engineers (IEEE), found the most energy efficient ways to traverse a slope [19]. They used a soil-wheel interaction simulation on slopes of varying angles [19]. A separate researcher reinforced the accuracy of the simulation model used [20]. Figure 4 shows the simulation result for a 6-degree incline. Sakayori and Ishigami found the ideal way to ascend a 6-degree slope is with an angle that is 30 degrees offset from the direct path [19]. Approaching the slope head-on, without offset, requires a burst of power that lowers wheel motor efficiency [19]. Between 45 and 60 degrees, a single wheel supports much of the rover’s weight, reducing overall traction. This increases slippage, thus wasting energy [19]. Beyond 60 degrees, the rover will not ascend the incline enough to be worth the low power usage. A rover’s computer can make use of this model to estimate required power before ascending a slope. The rover will then choose the most efficient route to save energy. However, not all terrain on Mars behaves the same way. Packed or rocky slopes will have different power requirements than the loose-soil model developed by the researchers. Another limitation to this solution is that simulation work demands high performance computers [17]. Lookup tables eliminate the need to solve the mathematical model each time the rover encounters a new slope. Because Mars rovers have low-grade CPUs, an expert on energy optimization distilled the model results into lookup tables [17, 21]. His team computed these tables for three common Mars terrain types and a range of slope angles [21]. These tables are a good start but additional work to characterize other terrain types is needed before implementation. The main advantage of efficiently ascending slopes is that batteries will last longer and the rover will cover more distance before needing to recharge.
CONCLUSION AND RECOMMENDATIONS By allowing Mars rovers to understand broader, more vague commands, unsupervised machine learning reduces the amount of data transferred to Mars [9]. This ensures signal speed and integrity while abstracting low-level control commands. Additionally, a sense of autonomy is introduced when sensor data trends are analyzed by the rover in its low-level decision making. Until trends are identified, the rover decisions may be error prone. While requiring high-performance onboard computers, this is still a promising technology to implement in rovers and begin the transition towards autonomy. Image processing consists of taking camera video feed and analyzing it on a pixel-wise basis. Computer vision algorithms can then classify terrain near the rover in discrete types [10]. This enables Mars rovers to avoid rocky terrain and prevent damage to their wheels. The image processing can happen onboard the rover and is rapid [11]. This technology removes the need for operators on Earth to characterize the terrain around the rover as it travels. The short image processing time onboard the rover, 2-3 minutes, makes this technology viable to increase exploration rate. If implemented alone, image processing would be the most promising technology discussed. Thermal inertia measurements can add a deeper layer of terrain classification. An example of this becomes apparent when forced to traverse through sandy terrain. Thermal inertia can determine shallower sand banks to minimize the chance of becoming trapped [16]. This is otherwise impossible using only image processing [10]. The slow nature of measuring thermal inertia can be coupled with exploring other locations in the meantime. For example, if the rover encounters a sand bank area it must travel through, it should take a temperature measurement of the surrounding terrain. Then it should return where it came from and explore somewhere else. After a span of eight hours, return to the sand bank location and take another temperature measurement to estimate thermal inertia. Then progress through the shallowest sand bank. This way, thermal inertia complements image processing and enhances it. The computer vision algorithms can be very exhausting for the rover’s CPU. Mars rovers can implement energy-efficient slope ascent while navigating to increase power availability to the CPU [19]. By using lookup tables to find the optimal ascent angle, the rover can optimize the way it traverses uneven terrain and save battery. This energy saved can be routed towards a longer journey before recharging, or towards image processing to safely traverse dangerous terrain. There is no single technology to overcome all the limitations Mars presents to autonomous navigation. The strengths of some technologies complement the weaknesses of others. In this fashion, space agencies can combine them to develop more autonomous rovers, thus boosting the rate of space exploration.
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placement [14]. Features in the images move backwards as the robot drives forward [14]. Imagery not changing for many wheel rotations signals that wheel slip is happening. After a certain threshold, the rover stops operating until commands from Earth provide a solution [15]. One issue with this approach is that detection happens only after wheel slip. It does not prevent, only corrects. Spirit, a Mars rover that operated in 2004, got trapped in a sand bank because it was not able to predict wheel slip [16]. By the time the imagery alerted of wheel slipping, it had already dug itself too far down. A study conducted by Cunningham at Caltech, funded by NASA, proposed measuring how well terrain near the rover holds temperature to predict wheel slippage [16]. Packed terrain is easier to traverse with wheeled robots, and it holds temperature better than loose soil [14, 16]. The researchers exploited this relationship to find suitable terrain for a Mars rover. Packed terrain holds temperature well because of the same reason baking a cake takes longer than baking cookies: Heating up one large item takes longer than many smaller pieces. The same holds true for cooling. Thermal inertia is the resistance to changes in temperature [16]. Packed terrain changes temperature slower than loose soil giving it a higher thermal inertia than loose terrain [16]. With this idea, thermal inertia can be used to determine how deep a sand bank is. Deep sand traps will have lower thermal inertia than shallow ones [16]. Figure 3 illustrates how the researchers used this property. To measure thermal inertia, they used infrared scanning over time [16]. Measuring how long terrain takes to change temperature provides an estimate of its thermal inertia. Longer times required for temperature change result in higher magnitude thermal inertia. In their study, the Caltech researchers used infrared measurements taken at dawn and after mid-day by Curiosity [16]. The change in temperature between the two measurements estimates the local thermal inertia. Since the program is only comparing temperature changes over time, low-performance computers can support it [17]. One downside of this technology is that it is slow, requiring a minimum time lapse between infrared measurements. The researchers used an 8-hour window between their measurements. This delay is counterproductive to increasing exploration rate. Thermal inertia measurements also require the rovers to include additional hardware to support infrared measurements that might otherwise not be present. The main advantage of using thermal inertia is the ability to characterize terrain before contact. When terrain has low thermal inertia, the rover can then decide to avoid it before even traversing it. With this approach, the rover will not get stuck from wheel slip, and odometry errors are avoided altogether. This makes for a more accurate navigation path and eliminates the need for NASA operators to intervene and override the planned path. The reduction in communications with Earth will ultimately increase exploration efficiency.
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[1] mars.nasa.gov, “Where is Curiosity?” [Online]. Available: https://mars.nasa.gov/msl/mission/whereistherovernow/. [Accessed: 23-Sep-2019]. [2] “Average Annual Miles per Driver by Age Group.” [Online]. Available: https://www.fhwa.dot.gov/ohim/onh00/ bar8.htm. [Accessed: 08-Oct-2019]. [3] K. Northon, “NASA’s Record-Setting Opportunity Rover Mission on Mars Comes to End,” NASA, 13-Feb-2019. [Online]. Available: http://www.nasa.gov/press-release/ nasas-record- setting-opportunity-rover-mission-on-marscomes-to-end. [Accessed: 02-Oct-2019]. [4] O. Lamarre and J. Kelly, “Overcoming the Challenges of Solar Rover Autonomy: Enabling Long-Duration Planetary Navigation,” arXiv:1805.05451 [cs], May 2018. [5] M. Ai-Chang et al., “MAPGEN: mixed-initiative planning and scheduling for the Mars Exploration Rover mission,” IEEE Intell. Syst., vol. 19, no. 1, pp. 8–12, Jan. 2004. [6] J. P. Grotzinger et al., “Mars Science Laboratory Mission and Science Investigation,” Space Sci Rev, vol. 170, no. 1, pp. 5–56, Sep. 2012. [7] P. Wan and Y. Zhan, “A structured Solar System satellite relay constellation network topology design for Earth‐Mars deep space communications,” International Journal of Satellite Communications and Networking, vol. 37, no. 3, pp. 292–313, May 2019. [8] A. Medina, G. Binet, and P. Colmenarejo, “An integrated autonomous navigation and decision-making architecture for planetary exploration rovers,” Intelligent Systems, Control and Automation: Science and Engineering, vol. 70, pp. 97–112, 2014. [9] A. Jones and D. J. Straub, “UNSUPERVISED LEARNING TO COMPENSATE FOR HIGH LATENCY IN INTERSTELLAR AND OTHER PLANETARY EXPLORATION,” th International Astronautical Congress, p. 6, 2017. [10] B. Rothrock, J. Papon, R. Kennedy, M. Ono, M. Heverly, and C. Cunningham, “SPOC: Deep learning-based terrain classification for Mars rover missions,” presented at the AIAA Space and Astronautics Forum and Exposition, SPACE 2016, 2016. [11] L. Matthies et al., “Computer vision on Mars,” International Journal of Computer Vision, vol. 75, no. 1, pp. 67–92, 2007. [12] J. J. Biesiadecki, C. Leger, and M. W. Maimone, “Tradeoffs between directed and autonomous driving on the mars exploration rovers,” Springer Tracts in Advanced Robotics, vol. 28, 2007. [13] S. Shekhtman, “How Global Dust Storms Affect Martian Water, Winds, and Climate,” NASA, 29-Apr2019. [Online]. Available: http://www.nasa.gov/feature/ goddard/2019/martian-dust-could-help-explain-planet-swater-loss-plus-other-learnings-from-recent-global. [Accessed: 01-Oct-2019].
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FIGURES AND TABLES [14] C. Cunningham, M. Ono, I. Nesnas, J. Yen, and W. L. Whittaker, “Locally-adaptive slip prediction for planetary rovers using Gaussian processes,” presented at the Proceedings - IEEE International Conference on Robotics and Automation, 2017, pp. 5487–5494. [15] M. Maimone, Y. Cheng, and L. Matthies, “Two years of Visual Odometry on the Mars Exploration Rovers,” Journal of Field Robotics, vol. 24, no. 3, pp. 169–186, 2007. [16] C. Cunningham, I. A. Nesnas, and W. L. Whittaker, “Improving slip prediction on Mars using thermal inertia measurements,” Autonomous Robots, vol. 43, no. 2, pp. 503–521, 2019. [17] B. Bornstein, T. Estlin, B. Clement, and P. Springer, “Using a multicore processor for rover autonomous science,” in 2011 Aerospace Conference, 2011, pp. 1–9. [18] mars.nasa.gov, “The Rover’s Temperature Controls.” [Online]. Available: https://mars.nasa.gov/mer/mission/ rover/temperature/. [Accessed: 26-Oct-2019]. [19] G. Sakayori and G. Ishigami, “Energy efficient slope traversability planning for mobile robot in loose soil,” presented at the Proceedings - 2017 IEEE International Conference on Mechatronics, ICM 2017, 2017, pp. 99–104. [20] K. Yoshida, T. Watanabe, N. Mizuno, and G. Ishigami, “Terramechanics-based analysis and traction control of a lunar/planetary rover,” Springer Tracts in Advanced Robotics, vol. 24, pp. 225–234, 2006. [21] S. Fallah, B. Yue, O. Vahid-Araghi, and A. Khajepour, “Energy management of planetary rovers using a fast feature-based path planning and hardware-in-the-loop experiments,” IEEE Transactions on Vehicular Technology, vol. 62, no. 6, pp. 2389–2401, 2013.
Mars Limitation
Impact
Large amounts of data cannot be sent at once
Low - communications with Earth must be concise
Rocky terrain damages wheels
Medium - limits viable navigation paths
Wheel slip on loose sand
High - stuck in sand, wrong position estimate
Low-performance computers
Medium - algorithms must be simple
Table 1. Mars limitation to autonomy and their impact on implementation
Figure 1. Exploration performance of Mars rover Curiosity. Despite surpassing mission projections for total duration and terrain covered, Curiosity has been inefficient in exploring the Red Planet. Data shown is from NASA and Lamarre [1, 4].
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Figure 3. Thermal inertia measurements translated to wheel slip probability. High thermal inertia terrain is easier to traverse. Figure modified from [16]. Figure 4. The most energy efficient way to traverse a 6-degree slope is with a 30-degree, offset angle. Data from Sakayori and Ishigami [19].
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Figure 2. Automatic terrain classification of Mars footage taken by curiosity. The pre-trained SPOC algorithm can recognize patterns in images of Mars soil. Figure has been modified from Rothrock, et al. [10]
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Fear Conditioning and TBI in a Unique Pair of Inbred Rat Strains Justin Magnus1, Robert Kotloski2 Universiyty of Wisconsin - Madison Department of Neurology, University of Wisconsin School of Medicine and Public Health
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ABSTRACT Post-traumatic stress disorder (PTSD) and traumatic brain injuries (TBI) increase the chance of suicidal tendencies and neuropsychiatric disorders in military veterans. If left untreated and misunderstood, thousands of returning veterans will struggle to adjust to civilian life and could, in some cases, go as far as taking their own life. Therefore, it is important to understand how PTSD and TBI affect veterans. Using a rat model, fear conditioning and mTBI (mild traumatic brain injury) are analyzed to understand why different responses were recorded for rats of different genetic backgrounds, Perforant Path Kindling Susceptible (PPKS) and Perforant Path Kindling Resistant (PPKR). A fast kindling (FK) rat with the PPKS strand is more susceptible to seizure-induced plasticity, than a slow kindling (SK) rat with the PPKR strand (Langberg, 2016). Our preliminary studies show that TBI by controlled cortical impact results in more frequent seizures in FK rats compared to SK rats. Injured, TBI, FK rats in this study were found to have recorded freezing times similar to those of uninjured, SHAM (faked surgical intervention), FK rats. Our results suggest that FK rats are genetically dispositioned to respond better to injury and fear stimulus than SK rats.
The military is a very stressful environment with many traumatizing events. These traumatizing events have been linked to post traumatic stress disorder (PTSD) in 19% of all United States military veterans (Dohrenwend, 2019). PTSD occurs when a person, in this case a veteran, is exposed to death, near death experiences, serious injury, or other prolonged traumatic experiences (Krasowska, 2018). A person with PTSD experiences symptoms such as: an increase in negative thoughts or feelings, irritability, aggression, difficulty concentrating, and a heightened startle reaction (Bryan, 2019). The person also re-experiences the trauma through flashbacks or nightmares causing the individual to experience emotional distress (Russell, 2018). These symptoms and experiences cause distress or functional impairment for the person suffering from PTSD (Krasowska, 2018). PTSD is one disease among the multitude of medical problems veterans experience after their involvement in traumatic war experiences. Other medical problems veterans have reportedly experienced are concussions and traumatic brain injuries (TBI). 11-23% of veterans experience a mild traumatic brain injury (mTBI) (Lindquist, 2019). TBI occur when a person experiences an impact to the head or another mechanism of rapid movement that displaces the brain within the skull. It results in a loss of consciousness, posttraumatic amnesia, disorientation, or confusion (Krasowska, 2018). Individuals diagnosed with an mTBI experience short term personality
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change, irritability, tension, anxiety, headache, fatigue, or sleep disorder (Bryan, 2019). They also experience long term symptoms such as: vertigo (spinning dizziness), anosmia (loss of smell), tinnitus (ringing in ears), seizures (convulsions), or cranial nerve deficits (nerve damage) (Bryan, 2019). 7% of veterans have both mTBI and PTSD (Combs, 2019). Veterans with PTSD and mTBI struggle with visual scanning, visual attention, immediate and long delay recall, and the ability to quickly process information (Combs, 2019). These veterans with PTSD and mTBI experience impaired semantic fluency and verbal memory, yet little research has been conducted to help understand these cognitive deficits (Combs, 2019). Research on the effects of stress and traumatic injury on the returning military will yield data that will help the scientific community better understand their issues and how to best help them live a higher quality of life by understanding and helping them adapt to their cognitive deficits. This study examined mTBI and fear conditioning in Perforant Path Kindling Susceptible (PPKS) and Perforant Path Kindling Resistant (PPKR) rats as a model to elucidate their effects. For over 15 years in the laboratory of Dr. Thomas Sutula’s, a unique inbred strain of rate has undergone genetic selection with the goal of breeding an increased rate of perforant path kindling, PPKS genetic background. The two genetic background resulting in this genetic selection are PPKS, plasticity-susceptible, and PPKR, plasticity-resistant. Two different genetic background are used because preliminary studies suggest that PPKS rats are more
prone to neurological disorders and diseases following a mTBI. In this study, fear conditioning in a rat model was conducted to simulate the neurological disorder PTSD with and without a TBI. Conducting a study with two genetic backgrounds and two groups, TBI and control, will demonstrate what factors effect fear conditioning in a rat model.. This study uses the Startle and Fear Combined System by Harvard Apparatus to fear condition the rats because the Corinna Burger’s laboratory owns the product and recommended it for the purposes of this study. This study hypothesizes that different rat strains will demonstrate divergent responses to both treatments, TBI and fear conditioning, because of differences in genetic background.
METHODS Twelve 4-month-old male rats were chosen for this study. Six of these rats were identified as fast kindling (FK, genetically seizure prone) and six as slow kindling (SK, genetically seizure resistant) (Stefan, 2012). The fear conditioning apparatus used was the Startle and Fear Combined System (Panlab) and the Packwin software is sold by Harvard Apparatus. Burger Lab at UW Madison purchased the equipment for their research studies and was gracious enough to allow Kotloski Lab access. Day 1: Initial Fear Conditioning Rats were prepared for the initial two-shock fear conditioning program. Rats are individually put inside a cage with a wire floor. That cage is then put in a soundproof box. A six-minute program ran on the computer that signals a high-pitched sound in the box, two times during the program and for the same duration. The sound intervals are succeeded by a two-second shock. Packwin software records the time duration of rat movement, Day 2: Surgery Three of the FK rats and three of SK rats are given a TBI during the surgery. The other six are subjected to a sham surgery. The surgical procedure consists of a moderate TBI to the temporo-parietal cortex and underlying dorsal hippocampus by controlled cortical impact. Isoflurane was used to sedate the animals as they were placed in a stereotaxic frame to perform the craniotomy5 mm posterior and 3 mm lateral from the sagittal-coronal suture junction. The exposed hippocampus is then impacted by a Leica Impact One Stereotaxic Impactor. Following the controlled cortical impact, the incision on the skin is stapled together. The rat is placed in a heated cage for monitoring before being returned to its . Day 3: Context and Cued Fear Conditioning All the rats repeated the protocol from day 1 in the wire cage, except no shock is administered after the high-pitched sound. Context fear condition is complete and the Packwin software records activity levels. Once all the rats completed the program, a new cage is prepped to
go in the soundproof box. The rats are individually put in a cage with a metal bottom and the scent of vanilla, to further distinguish the cued cage from the context cage. The protocol from day 1 is repeated, except a burst of light followed the high-pitched sounds, instead of a shock. Context fear conditioning is complete and the Packwin software records activity levels. All the data regarding the seconds of freezing, the absence of movement except for breathing, for each session of each rat are then organized by mean freezing time and graphed using excel. Results: The data recorded are preliminary results. Therefore, more trials need to be conducted to accurately determine statistical significance. Day 1: Initial Fear Conditioning Initial fear conditioning data illustrate that all the SK rats are above the 100 seconds freezing line, while only half of the FK are above the 100 seconds freezing line (Figure 1). As shown in Figure 2, SK rats have a higher mean freezing time than FK rats. Therefore, SK rats freeze either more often or over longer intervals than FK rats. It is also worth noting that FK rats have roughly similar freezing times (Figure 1). SK rats also have similar freezing times (Figure 1). Day 3: Context Fear Conditioning Results Context fear conditioning data illustrates that SK TBI rats appear to be resistant to fear condition since a majority, other than the outlier, recorded very little freezing (Figure 3). Figure 3 also illustrates that FK TBI rats seem to respond/act the same as FK SHAM rats to context fear conditioning. Therefore, going against the pattern that FK TBI and FK SHAM rats have similar freezing times. SK TBI and SK SHAM still follow that pattern (Figure 3). Another pattern found in the data is that SK rats continue to have a higher freezing time when compared to FK rats (Figure 4). Day 3: Cued Fear Conditioning Results Cued fear conditioning data illustrates that there was increased freezing time for all rats and that it follows the pattern of FK TBI and FK SHAM rats have roughly the same freezing time (Figure 5). In addition, SK TBI and SK SHAM have roughly the same freezing time (Figure 5). The freezing time has increase noticeably across all subjects, which is to be expected (Figure 6). However, the pattern follows that SK rats have a longer freezing time than FK rats.
DISCUSSION/CONCLUSION
The first phase to discover how to heal veterans with PTSD and TBI is the replication phase. The replication phase consists of reproducing PTSD and TBI. In this study, fear conditioning in a rat model replicates PTSD in humans because they follow similar mechanisms and a moderate TBI in temporo-parietal cortex and underlying
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dorsal hippocampus of a rat replicates TBI in humans. Fear conditioning is measured based on the amount of freezing time, more freezing time means that the rats remember the shock. The specific aim of this research is to determine the effect of genetic background on TBI-associated changes in fear conditioning. Initial fear conditioning demonstrates that there is a difference in initial response between the two genetic backgrounds. Before TBIs or SHAMs are administered, SK rats have a noticeably higher mean freezing time than FK rats (Figure 2). This finding does not further the understanding of how TBIs and fear conditioning affect rats, however it should be further examined in order to highlight the phenotypic differences between these two genetic backgrounds. Following fear conditioning, noticeable variations in freezing times between groups occur during the 48-hour context that are not as apparent during the 48-hour cued. During the 48-hour cued, there is a slight indication that the FK TBI rats are responding the same as an FK SHAM would, but that behavior is more noticeable during the 48-hour context (Figure 5). During the 48-hour context, FK TBI rats have similar freezing times compared to FK SHAM rats (Figure 3). Therefore, the injured, TBI, FK rats are acting like the uninjured, SHAM, FK rats. Demonstrating that the PPKS strain of rat gene responds more positively to injury and fear stimulus than the PPKR strain of rat gene. This study proves that it is possible to replicate PTSD using fear conditioning in a rat model. By successfully replicating the mechanism of PTSD, scientists can conduct further experiments to understand and heal fear conditioning in rats and PTSD in humans. Additonally, this study demonstrates that the difference in genetic background does produce different responses to TBI-associated changes in fear conditioning. Using this difference between the FK genetic background and SK genetic background, future experiments, such as a radial arm maze, can be conducted to see if the FK rats will have a higher cognitive function than the SK rats following a round of fear conditioning. The results of the radial arm maze should illustrate how fear conditioning and TBI effect cognitive ability in the rat model.
JM would like to gratefully acknowledge the help of the Sutula lab for breeding and supplying the 12 rats for this experiment and the Burger lab for allowing JM to use their fear conditioning setup. JM acknowledges Dr. Robert Kotloski for assisting JM with understanding how to work the fear conditioning system, assisting with data collection, organizing the data in excel, assisting with analysis of the data, and insightful conversations about neurology, his lab work, and his lab goal. Finally, a special thanks to Rachel Jordan and Jaitri Joshi for assisting with the formatting of this paper.
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Dohrenwend, B.P. et al. The Psychological Risks of Vietnam for U.S. Veterans: A Revisit with New Data and Methods. Science. 2006; 313:979-983 Krasowska D, Rolinska A, Mazurkiewicz A. To what extent are genetic and environmental factors linked with the development of posttraumatic stress disorder? Postepy Psychiatrii I Neurologii. 2018; 27(1):64-71. Bryant, R. Post-traumatic stress disorder vs traumatic brain injury. Dialogues in clinical neuroscience. 2011; 13(3):251-262. Russell MC, Schaubel SR, Figley CR. The darker side of military mental healthcare part one: Understanding the military's mental health dilemma. Psychological Injury & Law. 2018; 11(1):22-36. Lindquist, L.K. et al. Traumatic Brain Injury in Iraq and Afghanistan Veterans: New Results From a National Random Sample Study. J. Neuropsychiatry Clin. Neurosci. 2018; 29:254-259 Combs, H. et al. The Effects of Mild Traumatic Traumatic Brain Injury, Post-Traumatic Stress Disorder, and Combined Mild Traumatic Brain Injury/Post-Traumatic Stress Disorder on Returning Veterans. J Neurotrauma. 2015; 1;32(13):956-66
Figure 1: Illustrates the freezing time in seconds for each rat during the initial fear conditioning session.
Stefan, H. Theodore, W.H. Epilepsy. Edinburgh: Elsevier. Teutsch, P. et al. 2018 Gait and Conditioned Fear Impairments in Mouse Model for Comorbid TBI and PTSD. Behav. Neurol. 2012; 2018:6037015 Langberg T, Dashek R, Mulvey B, Miller KA, Osting S, Stafstrom CE, Sutula TP. Distinct behavioral phenotypes in novel "fast" kindling-susceptible and "slow" kindling-resistant rat strains selected by stimulation of the hippocampal perforant path. Neurobiology of Disease. 2016; 85:122-129.
Figure 2. illustrates the mean freezing time in seconds for the four categories of rat (FK SHAM, FK TBI, SK SHAM, and SK TBI) during the initial fear conditioning session.
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Figure 4. illustrates the mean freezing time in seconds for the four categories of rat (FK SHAM, FK TBI, SK SHAM, and SK TBI) during the 48-hour context fear conditioning session
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Figure 5. illustrates the freezing time in seconds for each rat during the 48-hour cued fear conditioning session.
Figure 6. illustrates the mean freezing time in seconds for the four categories of rat (FK SHAM, FK TBI, SK SHAM, and SK TBI) during the 48-hour cued fear conditioning session.
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Figure 3. illustrates the freezing time in seconds for each rat during the 48-hour context fear conditioning session.
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Political, Economic and Enviornmental Indicators of the Risk of Polybrominated Diphenyl Ether Exposure in the United States Michael B. Basovi, Evan C. Douglas, Thomas P. Stamatakos ABSTRACT PBDEs, or polybrominated diphenyl ethers, have yet to be disbanded in the United States, as there has been little political intervention on a national scale despite the danger posed to humans and the environment from exposure. PBDE exposure has been shown to negatively impact the health of animals in experimental studies, so understanding potential risk factors that correlate to high exposure can give humans a better understanding of their risk in a given area. The purpose of this study was to investigate the correlation between political, economic, and environmental factors and risk of PBDE exposure, and to then create an index that consolidates these indicators into a score that can be used to evaluate levels of risk in a given location. We quantified potential risk indicating variables for nine U.S. states, and then combined assigned values into an index score representative of each state’s level of risk of exposure. We then evaluated the relationship of these index scores to PBDE dumping on site, infant mortality rates and cancer incidence rates for each state in this study. Our results suggest that the index can predict risk of exposure based on these categorical variables because risk scores were proportional to levels of pollution and related to the ramifications of exposure shown in animal studies for humans. By using this index, states can assess their current status of PBDE risk of exposure based on political associations, economic conditions and relative environment instead of levels of pollution to evaluate policy directed at PBDE usage in a more comprehensive manner.
Background PBDEs, or polybrominated diphenyl ethers, are more commonly known as flame retardants. These chemicals are commercially produced and utilized as a safety product in the textile and technology industries, which include companies that produce wire insulation, rugs, and small appliances like computers. The first commercial productions of PBDEs began in the 1970s in Germany and its production has continued for almost half a century. There are three different types of commercial PBDE products: pentaBDE, octaBDE, and decaBDE. DecaBDE and octaBDE are colorless to offwhite solids while pentaBDE exists as a thick liquid (“Tox Town,” 2017). DecaBDE makes up 82 percent of PBDE products manufactured globally but its sale was scheduled to end by December 31, 2012 and for all uses by December 31, 2013 (“Polybrominated Diphenyl,” 2017). According to the EPA, 0.007 (mg/kg/day) exposure of decaPBDE is considered carcinogenic, with less brominated congeners needing even less exposure per day to be carcinogenic. In water, 2 x10¬¬¬-8micrograms per liter is considered carcinogenic. The EPA has reported that 440 mg/kg of residential soil, 3300 mg/kg of industrial soil, and 110 micrograms/liter are considered toxic levels for decaPBDE, and even less for
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less brominated congeners (“Technical Fact Sheet,” 2017). Based on these valuations, very little amounts of PBDE exposure can be carcinogenic and impact human health negatively. Although many people have never heard of PBDEs, this category of chemical is still commonly being used in the United States today despite evidence of a wide variety of health issues in organisms exposed over time. For example, they have been shown to deform progeny of researched wildlife populations, such as birds and rodents. The effects on adult animal subjects have ranged from deformities in thyroid development to the growth of tumors in the liver and the thyroid, as well as other issues (“Toxic Substances Portal,” 2015). Although there is no definitive understanding of the relative effects on humans, the negative effects studied in these animal populations may be of concern for human populations also being exposed. Exposure to PBDEs may have serious consequences for humans and our environment in areas where pollution is high. These chemicals are present in our natural environment as particles during the manufacturing processes. PBDEs are not very biodegradable, so they suspend in air, sediment, and water as particulates for long periods without dissociating, leading to bioaccumulation in humans and wildlife (“Toxicological Profile,” 2016). PBDEs mainly enter
Understanding Risk of Exposure While it is known how PBDE exposure impacts other organisms, questions regarding the effects on humans are still largely unanswered, and the risk of exposure in a given location is even less defined. A basis for risk evaluation based on current knowledge is crucial because little political intervention has occurred in the United States, and citizens in areas of high exposure continue to blindly be at risk to health complications down the road. We believe that there are six political, economic and environmental indicators that correlate to presence of PBDEs in a community and ultimately risk of exposure (two indicators for each profile). These factors are more prominent in communities of high exposure in contrast to others, so quantifying these variables in a given state can be used to create an index that predicts the risk of exposure that state may face. Consolidating these valuations into a risk score can be compared to reported values of PBDE pollution like the amount of dumping on site to assess the accuracy of the index and can then be related to consequences of PBDE exposure in animal studies for humans like infant mortality rates to investigate potential correlations. The creation of this index is based on three communities with high risk of exposure, and three com-
munities at low risk of exposure compared to data on PBDE pollution by state from the EPA. We then evaluated and quantified our variables in the index to calculate a risk score for each state that was consistent with relative levels of pollution. We then evaluated the factors for three other states that were randomly selected in order to eliminate selection bias in creating and evaluating the index, and to have a larger sample for graphing relationships between scores and negative effects of PBDEs. A score of 0-1 is defined as a not at-risk community of PBDE exposure, while a score of 1-2 is defined as an at-risk community. A score of 1 is inconclusive as there would be factors indicating high risk, and other factors indicating low risk. The political profile consists of the Liberal vs. Conservative factor, and the Age Demographic factor in each state. Our rationale for the Liberal vs. Conservative factor is that conservative states are often thought of to be in favor of smaller governments, less regulation, and free market economics. Because of this, we hypothesize that more conservative states will regulate PBDEs less than liberal states, and as a result have a higher risk of exposure to PBDEs. Our rationale for the Age Demographic factor is that we believe that since younger generations are more recently educated, and that they more recently entered the workforce, they are consequently more sensitive and proactive towards issues that are affecting the state/nation. Older populations are retired/retiring and not as directly in touch or impacted by working class issues. We believe that younger states would pay greater attention to pollution in general, and as a result would have less PBDE pollution and less risk of exposure. The economic profile consists of the Change in GDP factor, and Service vs Industrialized Economy factor. Our rationale for the Change in GDP factor is that if a state has lower change in GDP, there is less spending, development, and innovation, and a slower expansion of industry would yield less waste than a growing industry, so a state with a lower change in GDP would have less risk of PBDE pollution. Our rationale for the Service vs Industrialized Economy factor is that a larger percentage of GDP coming from manufacturing intuitively means that more products (textiles, electronics…) are being produced and there is more industrial waste, higher amounts of PBDE pollution, and therefore greater risk of exposure. The environmental profile consists of the Dry vs Wet Environment factor and the Rural vs Urban population factor. Our rationale for the Dry vs Wet Environment factor is that a wetter climate means that there is more rainfall to wash off PBDE particulates from the wide range of products in which PBDEs reside. Therefore, higher amounts of rainfall indicate that there is a greater risk of PBDE runoff polluting water and soil and causing harm to the ecosystem, which leads to greater risk of exposure. Our rationale for the Rural
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the body through consumption of foods being exposed near sites of application and by humans exposed to the chemical in their own preparation. When consumed, PBDEs can be broken down and passed through the body as metabolites or can be stored in areas of high fat content in humans. Lower chemical constituents of PBDEs like penta and octa PBDE have the tendency to concentrate in breast milk and can be passed on to infants through breastfeeding (“Toxicological Profile,” 2016) which may negatively impact infant survivability. Suspended particulates in water from waste run off in electronics and dumping sites are another common pathway of exposure for humans, as they have been shown to expose aquatic organisms often consumed by humans in the area (“Toxicological Profile,” 2016). With small amounts of exposure considered to be carcinogenic and many pathways present for PBDEs to enter the human body, the danger of continued exposure is apparent. An initiative has been proposed by the Environmental Protection Agency (EPA) to help transition manufacturing agencies from the toxic congeners of PBDEs being commonly used to safer alternatives. Industry in a capitalist country like the U.S. has a large influence on policy especially in regard to pollution, and these proposed alternatives by the EPA are not cost effective for these markets, so little real change has been observed. With the resistance to change, more exposure and consequences of PBDEs on humans will continue to arise in areas of risk in the United States.
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J vs Urban factor is that it can be assumed that states that are more urbanized will have more PBDE in the environment than one would find in rural/agricultural areas because there are generally more buildings and products in which PBDEs would be found. In other words, more urbanized communities indicate a greater risk of exposure to PBDEs. Each profile was weighted differently to account for what is more likely to have a bigger impact on communities being at risk for PBDE exposure. The political profile was given a weight of 40% because we believe the political views of a state will determine policies/ attitudes towards protecting the environment, thus directly impacting the amount of PBDEs being manufactured, used and disposed of improperly in a given area. The economic profile was also given a weight of 40% because we believe it is the economic demand for higher production levels that is ultimately determining if more or less PBDE containing products are being manufactured, as well as PBDE treated products being consumed and dumped in the environment as waste. The environmental profile was given a weight of 20% because the environment is not necessarily a direct cause for an increase in PBDE exposure but is more of a proxy that exacerbates the effects of PBDE exposure on communities. An example would be the hydrologic cycle with PBDE particulates exposing local food sources consumed by the populations in the area. The presence of PBDEs in the environment is a consequence of the different factors that we mentioned in creating the index like exposure to PBDEs by more industrialized workforces. If a state has a score indicating risk of exposure, health issues such as infant mortality rates and cancer incidence rates should be higher. An accurate index will not only allow states to assess their current status of PBDE exposure risk, but also use the assessment to evaluate policy directed at PBDE usage in states without reported pollution data to make the appropriate changes to effectively decrease risk of exposure. With the ability of PBDEs to remain in the environment, as well as its presence in commercial products, states that may not currently have PBDE manufacturing may still be continually exposed and these factors should indicate the risk of said exposure. Each state’s score will then be compared to pounds of PBDEs dumped on site by state to assess the accuracy of the index (“Toxic Substances Portal,” 2015). On site dumping means PBDE waste that is directly disposed of into the local environment at the manufacturing site, as opposed to off-site dumping which transports waste to processing agencies. These scores will then be compared to potential correlates of exposure for humans like increased infant mortality rates and cancer incidence rates which were observed in studied animal populations exposed to PBDEs.
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METHODS Study Selection We selected studies that were peer reviewed and documented the effects of PBDEs and PBDE levels in the environment. Reference sheets, such as the toxicological profile of PBDEs by the EPA, detailed reported amounts of PBDE pollution by state, dangerous levels of PBDEs for humans, local and federal health standards, as well as other technical facts regarding PBDEs. State Selection We chose to evaluate the following states: Pennsylvania, Ohio, Georgia, Illinois, New York, Connecticut, Virginia, California and Massachusetts. These states were chosen because of the availability of data on PBDE pollution, infant mortality rates, cancer incidence rates and the statistics available to evaluate our variables like partisan leanings over the last 10 elections. Evaluation of Variables Liberal vs. Conservative factor: When looking at presidential election voting history from the last 10 elections (1980-2016), if a state voted 7 or more times for a Democrat, it will receive a 0. If it voted 4, 5 or 6 times for either a Democrat or Republican it will receive a 1. If it voted 7 or more times for a Republican, it will receive a 2. Young population vs. Old population factor: Looking at median age per state (Johnson, 2017), states in the top 15 oldest will receive a 2, states 16-34 will receive a 1, and states 35-50 will receive a 0. Low change in GDP vs. High change in GDP factor: States with -0.7-1.5 % change in GDP in the second quarter of 2017 will receive a 0, states with 1.5-3.0 % change in GDP will receive a 1, and states with 3.0-8.3 % change in GDP will received a 2 (BEA GDP by State, 2017). Service economy vs. Industrialized economy factor: States within 1-15 of % of state manufacturing in terms of GDP in state ranking will receive a 0, states within 16-35 % of state manufacturing in terms of GDP in state ranking will receive a 1, and states within 35-50 % of state manufacturing in terms of GDP in state ranking will receive a 2. Dry environment vs. Wet environment factor: Using the average annual precipitation by USA state chart (“Average Annual Precipitation”), states that receive a rainfall level in the top 15 will receive a rank of 2, 16-34 will receive a rank of 1, and 35-50 will receive a rank of 0 Rural landscape vs. Urbanized landscape factor: Using a ranking of states based on how much urban area has been built up as of 2010 (“America's Most Urban”), states that qualify in the top 15 will receive a
rank of 2, 16-34 will receive a rank of 1 and 35-50 will receive a rank of 0. Statistical Analysis We used a one tailed and two tailed T test to compare our created risk scores for the selected states to amount of PBDE dumping on site, infant mortality rates, and cancer incidence rates. We used these tests to check whether the true mean of our scores was related to the given rates within a confidence interval of 95% indicating significance or lack thereof. This analysis would check the accuracy of our evaluating methods of generating a score to the comparisons we believed would be correlated.
RESULTS Evaluation of Variables For the Liberal/Conservative factor Pennsylvania received a 1, Ohio received a 1, Georgia received a 2, Illinois received a 0, New York received a 0, Connecticut received a 0, Virginia received a 1, California received a 0 and Massachusetts received a 0. For the Demographic factor Pennsylvania received a 2, Ohio received a 2, Georgia received a 0, Illinois received a 1, New York received a 1, Connecticut received a 2, Virginia received a 1, California received a 0, and Massachusetts received a 2. For the Change in GDP factor Pennsylvania received a 2, Ohio received a 0, Georgia received a 2, Illinois received a 0, New York received a 0, Connecticut received a 0, Virginia received a 0, California received a 0 and Massachusetts received a 0. For the Service/Industrialized Economy factor Pennsylvania received a 2, Ohio received a 2, Georgia received a 2, Illinois received a 2, New York received a 1, Connecticut received a 0, Virginia received a 0, California received a 2 and Massachusetts received a 0. For the Dry/Wet Climate factor Pennsylvania received a 1, Ohio received a 1, Georgia received a 1, Illinois received a 1, New York received a 1, Connecticut received a 1, Virginia received a 1, California received a 1 and Massachusetts received a 1. For the Rural/Urban Landscape factor Pennsylvania received a 2, Ohio received a 2, Georgia received a 2, Illinois received a 2, New York received a 2, Connecticut received a 2, Virginia received a 1, California received a 1 and Massachusetts received a 2.
ANALYSIS Our generated risk scores are indicated in Table 1. One and two tailed T tests for Risk Scores vs. PBDE dumping on site in a given state were 0.053 and 0.107 respectively, indicating a lack of significance. The R-squared value was 0.738, indicating a strong correlation. One and two tailed T tests for Risk Scores vs. Infant Mortality Rate in a given state were 0.0001
and 0.0001 respectively, indicating significance. The R-squared value was 0.568, indicating a moderate correlation. One and two tailed T tests for Risk Scores vs. Cancer Incidence Rates in a given state were 0.0001 and 0.0001, indicating significance. The R-squared value was 0.253, indicating a weak correlation. Index Scores and Correlation to Risk of Exposure The created index seems to correctly predict PBDE risk of exposure for the evaluated states. Scores that indicated risk of exposure correlated with high on site dumping and scores that indicated no risk of exposure correlated with little to no on site dumping (Figure 1). Though a p-value of 0.053 indicates the data is not statistically significant, it is incredibly close to significance within our accepted confidence interval. There was also a positive correlation between index scores and rates of infant mortality rates (Figure 2). Given a p-value less than 0.0001, the data is statistically significant. However, index scores were more strongly correlated with on-site dumping with an R² value of 0.738, while index scores were less correlated with infant mortality rate with an R² value of 0.5681. There was no correlation between index scores and cancer incidence rates given an R² value of 0.253 and the data is statistically significant given a p-value less than 0.0001 (Figure 3). The communities’ economic profile scores in service vs. industrialized economy and change in state GDP had the strongest influence on a state’s index scores as the lone inconclusive valuation for a state was New York for the Service vs. Industrialized economy factor.
DISCUSSION The created index was found to be accurate in consolidating these qualitative factors into a valuation for risk of PBDE exposure. Risk scores were proportional to levels of PBDE pollution in the evaluated states, which is crucial to understand levels of exposure in areas without pollution data. There is a complex combination of factors that correlate with risk of PBDE exposure and, by using this style of index, states can assess their current status in regard to risk of exposure and this assessment can then be used to evaluate policy directed at PBDE usage more effectively. Understanding that political, economic and environmental distinctions between states are indicative of the levels of risk of PBDE exposure illustrates the relationship between these qualitative variables and amount of risk of exposure. The scores were influenced differently by each factor, and this illuminated more detail on the relationship between our defined categories and risk of exposure. The biggest influence on index scores were the economic variables because most of the evaluated states either fell exclusively under high risk or low risk for both factors. This is validated when considering
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J the United States as a market that has driven and is still driving PBDE production and use because of the importance of these chemicals in high value industries. Despite intervention attempts by the EPA to transition PBDE producers to safer alternatives, it is not cost effective for capitalistic markets in industries like electronics to compete with countries like China who have not yet banned PBDEs, and do not have agencies attempting to limit use and exposure (Ni et al., 2012). Companies in these industries have to make their products fire safe, so PBDE use or an alternative must be factored into production costs. Economic competition on an international level influences what is being used nationally, and PBDEs make American products in relevant industries cheaper, so it is consistent that risk of PBDE exposure is more greatly influenced by economic factors in a state. These economic factors also played a crucial role when considering the environment as a buffer and the indicated risk factors. PBDE exposure has been primarily attributed to consumption of exposed foods primarily in aquatic life, and exposure to dust and air particles in areas of exposure (Axelrad, 2009). Personal and commercial consumption (purchase and usage) of commercial products such as sofas, insulated wires, insulation, hardware in electronics, and a variety of PBDE treated products in the last four decades have been treated as regular waste, dumped in landfills, and were consequently exposed to bodies of water through landfill runoff, contaminating aquaculture. In addition to this, the products treated are still being used in the residential areas and are settling in the dust of households, thus exposing the inhabitants. The economic factors were a strong determinant of PBDE risk of exposure as they indicate more pollution, whereas the environmental factors were not as strongly correlated which was indicated by the lack of minimal risk valuations for those factors. This is because high risk environmental conditions exacerbate the effects of PBDE presence but will have minimal impact if PBDEs are not prominently used. The political factors serve a greater purpose in considering the future of exposure as opposed to the present. The partisan leanings of a state and country ultimately determine potential economic policies, environmental initiative, and overall pathway to risk exposure, serving as a mechanism to direct exposure. In general, politics influence current and future risk, whereas economics solely influence current risk, and the environment serves as a proxy for direct exposure. The EPA has tried to transition PBDE producers and users in the United States to alternative waste management practices over the last decade that are safer, but states leaning right like Georgia have not implemented such change over this time. This includes Pennsylvania and Ohio as well: areas of considerably high risk of PBDE exposure (Safer States, 2018). The
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index scores were consistent with the fact these states are at high risk of exposure showing the partisan leanings influencing policy in the past correlates to risk of exposure in the present and future. Considering the analysis of our operationalized negative effects, and though the correlations of infant mortality rates and cancer incidence rates were not strong in regard to PBDE exposure being the direct influence, the economic and environmental landscapes served as a strong indicator of higher rates in general. This shows that the index might also be an indicator of the health of a community in general as a function of these three profiles. Expanding the index to include more specific indicators may highlight a more direct pathway to PBDE exposure since it would show other possible important factors that contribute to it, thus allowing for more effective management. Additionally, including more than just two specific indicators for each profile would bolster the index values and potentially be more accurate. Use of better data to evaluate specifically highlighted causes of PBDE exposure would give us a better scope of the relationship between index scores and these negative consequences on humans, but actual diseases shown to be caused in humans due to PBDE exposure are not well understood. Looking at the relationship with a specific cancer incidence rate that is shown to be a potential result of PBDE exposure could give us stronger correlation than generalized incidence rates based on specific findings in animal research. Potentially correlating the risk score to studied mice populations could have yielded a strong correlation, but the concern would be the significance of the sets of data to those in humans, since animal trials do not necessarily directly indicate the same effect in humans. In addition to a need for more specific data to validate direct effects of risk of exposure, using more specific metrics could make the risk score more accurate. Considering a metric like percentage of electronic waste each year by state in the US paired with percentage of consumption as part of GDP by state in the US could be a strong indicator to risk of exposure based on our current understanding. Percentage change in GDP and annual precipitation do not encapsulate the exact proxies to direct influences as well as those potential metrics. The specific products need to be directly in the environment to then contribute to PBDE pollution and how many products are present in waste indicates level of exposure and therefore risk of being exposed. Using the aforementioned metrics in evaluation could yield more accurate results that could be strongly correlated with levels of pollution, risk of exposure and potential health implications from exposure. Future research on PBDE risk of exposure and use of this style of index should focus on finding the best metrics that encapsulate the relationships of interest, as well as specific data that presents specific
consequences to potential negative effects. This concept of identifying social constructs that are a proxy to exposure of carcinogens can be illustrated with this style of index and can be useful when actual levels of carcinogenic exposure are not known in a given area. This will yield more concrete findings that illustrate or nullify relationships of political, economic, and environmental factors influencing exposure to any carcinogen still being produced, used and unsafely disposed of in the United States.
REFERENCES 1. America's Most Urban States. America's Most Urban States | Newgeography.com. Available: http:// www.newgeography.com/content/005187-america-smost-urban-states 2. Archive. Archive | US Bureau of Economic Analysis (BEA). Available: https://www.bea.gov/newsreleases/regional/gdp_state/qgsp_newsrelease.htm 3. Average Annual Precipitation by State. Average Annual Precipitation by USA State - Current Results. Available: https://www.currentresults.com/Weather/US/average-annual-state-precipitation.php 4. Axelrad D. Brominated Flame Retardants: Regulatory Actions and EPA ... Available: https://www. nist.gov/document/1-axelradpdf 5. Cancer Prevention and Control. Centers for Disease Control and Prevention. Centers for Disease Control and Prevention; Available: https://www.cdc.gov/ cancer/dcpc/data/state.htm 6. Crawford M. The States Leading the U.S. Manufacturing Resurgence. Area Development. 2014. Available: http://www.areadevelopment.com/RegionalReports/Q1-2013/states-leading-US-manufacturing-resurgence-2665542.shtml?Page=1 7. Guigueno MF, Fernie KJ. Birds and flame retardants: A review of the toxic effects on birds of historical and novel flame retardants. Environmental Research. Academic Press; 2017. Available: https://www.sciencedirect.com/science/article/pii/ S0013935116303942 8. Health risks of PBDEs. EWG. Available: https:// www.ewg.org/research/mothers-milk/health-riskspbdes#.Wuq439Pwa35 9. Historical Presidential Election Information by State. 270toWincom. Available: https://www.270towin.com/states/ 10. Johnson D. The Youngest and Oldest States in America: Map. Time. Time; 2017. Available: http:// time.com/5000792/youngest-oldest-us-states/ 11. Ni K, Lu Y, Wang T, Shi Y, Kannan K, Xu L, et al. Polybrominated diphenyl ethers (PBDEs) in China: Policies and recommendations for sound management of plastics from electronic wastes. Journal of Environmental Management. 2013;115: 114–123. doi:10.1016/j.jenvman.2012.09.031
12. Polybrominated Diphenyl Ethers (PBDEs). EPA. Environmental Protection Agency; 2017. Available: http://www.epa.gov/assessing-and-managing-chemicals-under-tsca/polybrominated-diphenyl-ethers-pbdes 13. Stats of the States - Infant Mortality. Centers for Disease Control and Prevention. Centers for Disease Control and Prevention; 2018. Available: https:// www.cdc.gov/nchs/pressroom/sosmap/infant_mortality_rates/infant_mortality.htm 14. Technical Fact Sheet – Polybrominated Diphenyl Ethers (PBDEs). EPA. Available: https://www.epa. gov/sites/production/files/2014-03/documents/ffrrofactsheet_contaminant_perchlorate_january2014_ final_0.pdf 15. The People's Republic of China. United States Trade Representative. Available: https://ustr.gov/ countries-regions/china-mongolia-taiwan/peoples-republic-china 16. Tox Town - Polybrominated Diphenyl Ethers Ethers (PBDEs). US National Library of Medicine. National Institutes of Health; Available: https://toxtown.nlm.nih.gov/text_version/chemicals.php?id=79 17. Toxic Flame Retardants. Safer States. Available: http://www.saferstates.com/toxic-chemicals/ toxic-flame-retardants/ 18. Toxic Substances Portal - Polybrominated Biphenyls (PBBs). Centers for Disease Control and Prevention. Centers for Disease Control and Prevention; Available: https://www.atsdr.cdc.gov/PHS/PHS.asp?id=899&tid=94 19. Toxicological Profile for Polybrominated Diphenyl Ethers (PBDEs). Centers for Disease Control and Prevention. 2016. Available: https://www.atsdr.cdc. gov/toxprofiles/tp207-c6.pdf
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Figure 2. Risk Score vs. Infant Mortality Rate by State. The graph plots the index scores of each state against their infant mortality rate and shows that there is a positive correlation between the two and the data is statistically significant. This means the states more at risk for PBDE exposure can expect to have higher levels of infant mortality. R2 = 0.56841; T-test: one-tailed = <0.0001, two-tailed = <0.0001.
Figure 1. Risk Score vs. On-site Dumping by State. The graph analyzes the relationship between the index scores of each state in comparison to their actual level of PBDE pollution. A positive correlation is shown indicating that states more at risk for PBDE exposure are the states that are dumping more PBDE waste, showing the index scores were proportional. R² = 0.73808; T test: one-tailed = 0.053292, two-tailed = 0.106584.
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Figure 3. Risk Score vs. Cancer Incidence Rate by State. This graph plots the index score of each state against their cancer rates and shows that there is a positive correlation between the two and the data is statistically significant. This means that the states more at risk for PBDE pollution can expect to have higher cancer rates. R2 = 0.25338; T-test: one-tailed = <0.0001, two-tailed = < 0.0001.
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Table 1. Index on three states with high level on site PBDE pollution, three states with no on-site PBDE pollution, and three randomly selected states. These three states were randomly selected to test index scores without considering levels of PBDE pollution. Each factor was given a score of 0, 1, or 2 based on data collected and interpreted from several sources1, 2, 3, 6, 9, 10. We ranked all 50 states for each set of data related to a factor, and defined three ranges from these rankings to assign a value. Final scores were calculated by taking the average for each category, multiplying each category by their respective weights, and then summing the values. Scores greater than 1 indicate high risk of PBDE exposure whereas scores less than 1 indicates low risk of PBDE exposure.
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Can They Deliver?.............................46 Since the debut of Starship’s food delivery robots on the UW–Madison campus, students have been grappling with how to interpret them. This social study seeks to understand how students have come to understand the robots and, subsequently, their selves. Through a short, small-scale survey conducted by analyzing memes and comments on an unofficial university Facebook meme page, I have determined that students actually reify already-held moral perceptions both of themselves and of the role certain technologies should play in everyday life. These already-held beliefs, however, are not always factually substantiated. Further, the robots, which may be designated “disruptive technologies,” transform social relations within a “micro-Commons,” – a small, bounded domain with particular ways of engagement within it – and force an “adjustment period,” in which students must figure out how to share a common space. The comic relief provided by memes are a means by which students mitigate new anxieties surrounding the robots and by which they forge a new technoscape within the micro-Commons. Limitations to this study are the number of people surveyed, the scope of theoretical analysis, and the novelty of the robots themselves. In fact, the following pages represent a particular moment of an emerging social transformation.
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Can They Deliver? Logan Krishka
ABSTRACT Since the debut of Starship’s food delivery robots on the UW–Madison campus, students have been grappling with how to interpret them. This social study seeks to understand how students have come to understand the robots and, subsequently, their selves. Through a short, small-scale survey conducted by analyzing memes and comments on an unofficial university Facebook meme page, I have determined that students actually reify already-held moral perceptions both of themselves and of the role certain technologies should play in everyday life. These already-held beliefs, however, are not always factually substantiated. Further, the robots, which may be designated “disruptive technologies,” transform social relations within a “micro-Commons,” – a small, bounded domain with particular ways of engagement within it – and force an “adjustment period,” in which students must figure out how to share a common space. The comic relief provided by memes are a means by which students mitigate new anxieties surrounding the robots and by which they forge a new technoscape within the micro-Commons. Limitations to this study are the number of people surveyed, the scope of theoretical analysis, and the novelty of the robots themselves. In fact, the following pages represent a particular moment of an emerging social transformation.
In a 1985 volume edited by Marvin Minsky rife with historical reflections and curious predictions of the future of robotics, Joseph Engelberger ponders the ways in which artificial intelligence (AI) and robotics will eventually forge “the ultimate worker.” Fast food preparation and delivery do not fail to make the list; he speaks of: the Pizza Time restaurants, a chain of pizza parlors with automated entertainers, robots are the only motorized mannequins that entertain customers with taped routines, but maybe this is a harbinger of the future. A working robot could be backstage making hamburgers, French fries, and cherry pies; a fellow robot would then deliver the goodies to the waiting customers. Wouldn’t it be nice in that circumstance to have real, live, talented young folks to do the entertaining? [1]. I open with this image due to its demonstration that humans have been both dealing with the social implications of technology, specifically robots, as well as hypothesizing about their – and our – future for decades. It is not within the scope of this paper to take up thoroughly the myriad of manners in which humans and robots construct and adapt to each other but rather to put into question promises that certain technologies solely “free us up” with little work on our part, and make our lives easier. The recent food delivery robots that have found themselves on the UW–Madison campus allow for a fascinating point of departure. The principle intention of this inquiry is to determine how students have reacted to the robots and to give insight as to how technology can alter social relations and preconceived notions students hold about themselves and technology. Before delving in, two foundational points must be discussed. First, what is a robot? Following Jenni-
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fer Robertson’s definition, a robot is “an aggregation of different technologies, sensors, lenses, software, telecommunication tools, actuators, batteries, synthetic materials and fabrics that make it capable of interacting with its environment, with some human supervision (through teleoperation) or autonomously” [2]. Second, referring to “robots” as a singular category may be disingenuous as it homogenizes different types of robots and their applications in local contexts [2]. Throughout this paper, I will at times refer to the food delivery robots simply as “robots” for the sake of space; however, this stipulation shall be kept in mind. These robots, manufactured by San Francisco-based company Starship, are marketed to “improve everyday life” [3]; however, as I will argue, they more importantly reify students’ already-present moral perceptions both of themselves and the role the robots should or should not play in everyday life. My discussion will be made clear by responses to a short, informal survey I conducted as well as by the plurivocal sentiments of those in the university’s unofficial meme page on Facebook. Seemingly unscientific, this latter source of information provides a specialized glance into students’ social interactions and is an extension of what will be deemed a local “technoscape” or newly emerging hybridized realm of private technology, online interaction and mediation, and the public commons. What I’ve discerned is that, despite the assurance of their usefulness, students are worried about the potential social costs of the food delivery robots regardless of whether these perceived implications are actually present or not. These anxieties respond to a shift in social and labor relations between the students and the robots, and the discourse that students construct and within which they operate not only shapes but also
METHODS Despite several shortcomings of the robots (such as trouble in the snow and delayed delivery), what is most pertinent is how people actually interact – or don’t – with them. On top of analyzing the reactions to and comments on dozens of memes found on the UW meme page (a uniquely 21st century fieldsite), I also conducted a short, open-ended survey of 15 people (time constraints limited the number of people I could ask and whose opinions I could analyze). I asked for their general reactions, if they would ever use one and why, if they thought the robots would help give students more time, and if they saw any potential problems with their presence on campus. Not only was every person against them – sometimes adamantly – or indifferent towards them, but their aversion towards the robots reveals how they think people should interact with such technologies and how they think about themselves.
RESULTS Before addressing their concerns, certain potential benefits were acknowledged by the students interviewed. In line with Peter Testory’s claims that “students are juggling more than they ever have before” [5] is one student’s recognition that using a robot means that one doesn’t have to wait in line for food. Another student highlights that added convenience may generate extra revenue for the dining halls. However, the most recurrent positive attribute is their “cuteness.” At least four people I surveyed and many more on the Facebook group mentioned how the robots are cute; as well, there is a great deal of anthropomorphization surrounding the robots. Generally understood as the human tendency to attribute human traits to non-human entities, or to treat non-human behaviors as motivated by human feelings and mental states [7], anthropomorphism is one characterization of an “adjustment period” to which Sally Applin and Michael Fischer refer. Students have uploaded pictures of robots with hats on, have remarked that “if you’re cold, they’re cold: bring them inside,” and have even created fake Tinder accounts for the robots. Moreover, the discourse surrounding them humanizes the robots and frequently genders them as he/him. “He’s trying his best,” commented one member of the group after another posted that she had been waiting an hour for it to deliver her food. Three memes referred to groups of them as soldiers, ascribing to them a particular automated task while imputing a human-like agency: Another comment stated, “Celebrities get 1000s of likes, let’s see how many our troops can get.” Humorous parodies of an armada of robots disclose both the human tendency to personify as well as offer comic JUST VOL V // ISSUE II // SPRING 2020
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limits their interactions with the modish machines. Before exploring the still-developing presence of the food delivery robots on the UW–Madison campus, it is necessary to determine their origins. Skype co-founders Ahti Heinla and Janus Friis launched Starship Technologies in 2014 with the goal to “revolutionize food delivery” through a “convenient new service that improves everyday life” [3]. By August of 2019, over 100,000 autonomous deliveries had been completed, and, according to Forbes, the company has recently raised $40 million to expand its services to 100 college campuses, adding several each month until this goal is achieved in 2021 [4]. Starship’s robots currently operate at George Mason University, Northern Arizona University, Purdue, Pittsburgh, several Houston University campuses, and the University of Wisconsin at Madison, according to its official Facebook page. The robots made their debut on the UW campus on November 4 of 2019. The robots operate around the globe and have traveled over 350,000 miles, completing over 150,000 autonomous deliveries [5]. Operating at a maximum of four miles-per-hour, CEO of Starship Technologies Lex Bayer says “by design, they are unintimidating; they are smart and cute and polite” [4]. At least four students I surveyed along with many other voices participating on the student-led university Facebook meme page concurred that they are, in fact, cute. This will prove relavent in the discussion of student-robot interactions. The robots have six wheels and use sophisticated machine learning (AI) and sensors (including nine cameras) to cross streets, climb curbs, travel at night, and operate in both rain and snow [5]. However, Director of University Housing Dining & Culinary Services Peter Testory explains that, even though they are manufactured in Estonia and thus “used to a dark, cold, and snowy environment,” there will be days the robots will not be able to deliver food [6]. At UW, the curious critters operate out of Carson’s Market, Four Lakes Market, Liz’s Market, and the Gordon Dining Hall, can carry up to 20 pounds of food, and are maintained through a delivery cost of $1.99. Students use the Starship app to drop a pin where they’d like to pick up the food and it is delivered, supposedly, within minutes. At first, their domain was restricted to the Lakeshore area of campus and the Eagle Heights neighborhood, but service has since expanded to part of the Southeast neighborhood. The following investigages how – partially through digital interaction and partially through their physical presence on campus – the food delivery robots not only reshape both social relations and students’ beliefs about themselves and technology but how they also foster certain anxieties. The anxieties stoked by the social reshuffling are present explicitly in students’ responses to me and implicitly through the evocation of humor in a considerable number of memes and discussions.
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relief from the anxieties that are more strongly expressed. In fact, anthropomorphic projections rely on the tacit recognition that one is dealing with an en-
what fashions a “good” student. Even more interesting is the fact that many of the perceived problems cannot be factually supported, yet these understandings, faulty though they may be, still corroborate certain beliefs. This is not novel and in fact speaks broadly to how humans tend to substantiate already-held beliefs when presented with something new. In fact, what we likely have is an instance of cognitive penetration, where students’ interpretation of their experiences, in this case with the food delivery robots, arises from already present knowledge and beliefs. These understandings are
Fig 1: An entertaining example of anthropomorphism demonstrates one way of navigating the adjusgment period.
Fig 2: Students comment on an ostensible future scenario with comic relief.
followed up with a stipulation. “They don’t displace jobs, but they don’t provide a ton of benefits,” “they are innovative, but don’t belong on this campus,” “they are cute, but could lead to laziness” and so on. What is particularly noteworthy is that the students’ quandaries regarding the robots reaffirm moral perceptions of themselves, of technologies like the food delivery robots, and how college life should be, according to them. From a moral point of view, students generally felt that the robots unnecessary and also that familiarity with food preparation and the need to be social are part of
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Fig 3: Anthropomorphism and humor mitigate the anxieties of sharing space
due not only to a lack of communication on the part of the university to the student body but also due to predispositions that help fashion a student who believes he or she doesn’t need to use the robots. Several examples of these not-quite-true assumptions are that the robots are a waste of funds (in purchasing and in maintenance fees), that they eliminate the job of a delivery person/driver, and that these funds could be allocated more appropriately to other areas, such as an anonymous sexual assault reporting app specific to the university. Although these are valid concerns on various levels, the university did not pay for the robots; the 30 on campus are part of a pilot program and, as stated earlier, their incorporation to this campus was due in part to the $40 million fundraising by Starship. Importantly, there currently are not any student delivery services; in this sense, the robots are not ersatz stand-ins. In fact, the reported troubles with the robots resembles one person’s recollection of when there was a student delivery service: I worked dining for 4 years (Gordon’s), and we did delivery my freshman year back in 2015. We had students walk to the nearby dorms (so all of Southeast and none of Lakeshore, at least at my location). It was such a cluster and my freshman year was the last year for delivery. This robot stuff is a total joke. They underpay the student employees because they don’t have the money to properly compensate them, but they have the money for robots? The money could’ve been better used in so many places. It seems here that the robots are not creating a unique problem but rather represent a more consistent one UW Dining has had, albeit in a different form. Further, as Peter Testory remarked, the university actually plans on creating jobs: “[Students] will be keeping track
in a line than to have food delivered vis-à-vis the robots. Many people also cited the problem of their interference with people and surroundings, like making it difficult to maneuver the already-crowded sidewalks and getting stuck. When I asked those surveyed if they would ever use one of the robots, all said they would not, often with qualifiers of “I have no interest” or “I would feel awkward if people saw me using one in public.” However, five of them included that if they were to use one, it would be out of irony or simply for the novelty of having used one. This in its entirety highlights how, as Maria Chiara Carrozza puts it, “technologies … may very well upset our model of society, transform or eliminate jobs, and enter into contact with our cognitive intimacy” [9]. My main argument here is that, even if the negative circumstances outlined by students do not actually occur, the lay student may perceive them as legitimate and reaffirm parts of his/her moral identity that work against the implied imposition of ease, flexibility, and convenience offered by the robots.
DISCUSSION In working toward a more complex discussion, it is useful to embrace several insights. Jennifer Robertson, in her recent study of the robotization of Japan, informs us that robots, being incredibly sophisticated and expensive, reflect the “values” of those who fund them. In this sense we see a dissonance within the “micro-Commons” of Starship and UW Dining’s aim to bring about a more “freed up” student and the students’ perceptions that, for the most part, go against this, whether they actively realize it or not. Robertson tells us that we should not assume technology per se is liberating, that it can provide certain freedoms but also be experienced as “repressive” and even “alarming” [2]. We can now establish a theoretical approach that will aid the discussion to follow. Considering the food delivery robot as an actor on the same plane as human invites us to understand how we inscribe practices into our technologies while also questioning the practices themselves and reifying our perceptions of them. The fact that we inscribe practices into technologies implies that there is a certain way we believe we ought to do something; our routines become our cultural practices, and the relationship between material object and cultural practice allows us to view the former as not just a benign object but something that conveys, in a broad sense, meaning. Eating/food preparation is an excellent example of this. Although there are of course differences throughout human history in the types of food we eat, at what times, and for what reasons, there tends to be some consistencies, such as the act of gathering together, use of certain utensils, and culturally distinct social arrangements. Being something with which we cannot dispense, food’s ontological quality and our cultural beliefs regularly inform each other and mark the act of eating as a conspicuous site of culJUST VOL V // ISSUE II // SPRING 2020
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tity that acts; a change in relations that requires the coordination of two agents to achieve any given goal unveils anthropomorphism at its essence as a recognition of intersubjectivity [7]. It is partially this that underpins the fear of a transformation from the bizarre to the banal, a fear of moving from a period of negotiation to one in which robots are accepted unequivocally. This is evidenced in several of the memes (Figures 2 and 3) present in the Facebook group: Here we see how humor and anthropomorphism are utilized to alleviate certain anxieties, namely, having to share space with robots with whom students are not intimately familiar. The comic relief brought by memes such as in Figures 2 and 3 parallels how almost all of the positive feedback I received from surveyees was
of the delivery and getting the orders for the different venues and putting them in the robots and sending them off to their final locations” [6]. However, Forbes reports that the command-and-control center is located in Washington D.C. [4], and NPR adds that the human that might get the robot back on track may even be all the way in Estonia [8]. The discussion of an anonymous sexual assault reporting app dominated the comments of several memes in the groups, and two people with whom I spoke voiced the same concern: Why spend money on robots when this potential app could help people in a more useful way? As is now clear, the university did not pay for the robots, but the deflection of the issue toward the potential for this app illuminates that, unsurprisingly, students are not against technology; rather, the desire of some for a sexual assault reporting app over the desire for the food delivery robots exhibits the opinion that the university should be helping students in ways students deem applicable and necessary. This idea is found in almost every anxiety displayed by students. Several students commented on the importance of the social aspect of food and sharing a meal. Our relationship with food offers insight to who we are and what we think. Recognizing it as one of the most intimate things we can do – nourish ourselves – two people I surveyed commented on their worries around knowledge of food preparation and sociability. “Knowing how to cook is a life skill, and the convenience of the robots could reduce the desire/need to learn how to cook your own food,” remarked one student. Another said that going to the dining halls with friends is an important part of the college experience. In these two observations we see a reaffirmation of personal beliefs already held by those contemplating the food delivery robots; the former student, along with several others, holds that the robots may disincentivize learning to cook for oneself and lead to a fostering of lazy behavior and perhaps even a certain level of social alienation. It is doubtful that this is entirely true; after all, the robots can deliver up to 20 pounds of food, enough to feed a small group of people, and it would be misguided to assume students would rely on the robots for every meal. The latter student recognizes the potential for people to get so swept up in their work (a point Starship and university partners advertise under the guise of “productivity”) that they miss out on an important aspect of the American College Experience. The fear of fostering a way of life where one doesn’t have to interact with people is compounded, in the students’ eyes, by the fact that the robots simply aren’t “efficient” enough. Operating at a maximum of four miles-per-hour and having to navigate a labyrinth of ongoing construction on campus makes it difficult for “delivery in minutes,” as is promised. “3000 minutes maybe,” commented one person in the Facebook page. The memes included above are but a few of the many that illustrate some of the problems students associate with the robots. Further, most people recognized that it would take less time to walk to a dining hall and wait
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Through analyzing the food delivery robots and the effects they have already had in the mere few months of their habitation on this campus, it is clear that they are beginning to shape a new technoscape, both physical and virtual, in what anthropologist Sally Applin calls a “micro-Commons” [13], which is a small, bounded domain with particular ways of engagement within it. Interested in the ways humans and algorithm-driven machines interact, Applin and Fischer discuss “disruptive technologies” – which include food delivery robots – that: a) expect humans to adapt to a transformation in their social sphere that now integrates robots into this micro-Commons, b) force an “adjustment period” in which humans have to figure out how to organize themselves in a physical space with the robots that were not previously there, and c) shift the labor model of maintenance to those within the micro-Commons, fostering the assumption that a given technology functions properly and blends seamlessly into an emerging technoscape [14]. From the UW memepage we see an example where these three issues coalesce. A video depicts one of the robots stuck on a curb; a man approaches, restabilizes it on the sidewalk, and is jovially thanked by the robot who continues its delivery journey. In my own observations during the winter months, I have seen the robots get stuck in snowy conditions. I have also witnessed quite a few students help them get back on track. In regard to the rearrangement of labor, that there are command-and-control centers in Washington D.C. and Estonia goes hand-in-hand with Applin’s characterization of a shifting of social and labor relations within the micro-Commons. As the robots are now, they cannot open doors or control elevators, so they require human cooperation both in the official sense of loading and retrieving food and in the unrecognized sense of invisible (to Starship) human helpers that fill in the gaps of a sometimes-faulty automation [13]. This reference to the “adjustment period,” as well as the varying concerns voiced by multiple students, confirm that we cannot understand robots in a universal way because of varying levels of social impact and the local context of the micro-Commons that intertwine and inform the culture and technology within this specific geographic location. The use of humor through memes exemplifies a mitigation of the anxieties that characterize this particular adjustment period. The assumptions mentioned above, and the robots themselves, illustrate what Maria Chiara Carrozza labels the fourth industrial revolution, one that offers a world around and within which intelligent machines roam [9]. She envisions the driverless car as the symbolic hallmark of this revolution as it embodies the implications and meanings of the revolution itself: robots among us, the replacement of a human driver, control systems that automatize driving, and legislative intervention [9]. Indeed, Starship has played a substantial role in altering legislation to favor their autonomous robots [5, 8, 15]; currently, nine states, including Wisconsin, allow them to operate on sidewalks. Carrozza
interestingly remarks: “I think when we get to the point where the robot will also choose the food we like best and deliver it to us at the time we want to eat, we will have reached perhaps the top (or bottom?) of this industrial revolution” [9]. This concern complements some of Applin’s. Both Carrozza’s consideration of the not-yetwritten scenarios of the fourth industrial revolution – including social and human concerns, laws and rights, ethics and civil responsibility, and time and space – and Applin’s apprehension of shifting relations of human labor and disruptions in the micro-Commons aptly reflect students’ own anxieties. In viewing the food delivery robots as what Marcel Mauss would label a “total social phenomenon,” we are able to see broadly how material culture, the product of technology, is more than a practical instrument [10]. The anthropologist’s uniquely privileged perspective allows one to think about the robots’ physical and technical aspects while necessarily examining how they socially shape, limit, and inform our selves. Viewed as “actors” within constantly changing networks of interaction and interdependence, we are able to see how behaviors and practices are embedded in the technologies we use and how these same technologies also reflect our ontologies. I have shown that students are mostly against what they could validly label an “intrusion” of these robots into their space – and their creation of a technospace – for reasons both factually founded and not. What is most important, however, is not whether the information they use to reflect on the robots is per se correct but that, regardless of this, they use the presence of the robots themselves and their discourse surrounding them: a) to question the purported ease and flexibility of the robots, and, b) to reaffirm strongly-held moral and cultural beliefs about their own place on this campus and their personal lives. It is most appropriate to consider this discussion of Starship’s food delivery robots as a unique snapshot at a given moment. They are relatively new to the campus, and students’ views are likely to evolve as the kinks of the technology are worked out. Considering this, I have laid out a social analysis of the robots, primarily through the lens of Actor-Network Theory. Constraints don’t allow for a full discussion of Marx’s four conceptualizations of alienation and how each could apply to the topic at hand, but that analysis, which would focus more on labor, could and should be taken up in the future and compared to an analysis proposed here by Actor-Network Theory. A future study with a larger number of people interviewed would provide more nuance and complexity to my argument; however, that which is described here provides a point of departure for studying the robots within the specific domain of the UW–Madison campus.
ACKNOWLEDGEMENTS I wish to express my sincere gratitude to Dr. Vijayanka Nair for her comments and guidance throughout this project.
REFERENCES 1. Engelberger, J.F. The Ultimate Worker. In Marvin Minsky. Robotics. Garden City, NY: Anchor Press/Doubleday; 1985. p. [206-207]. 2. Robertson, J. Robo Sapiens Japanicus: Robots, Gender, Family, and the Japanese Nation. Oakland, CA: University of California Press; 2018. 3. Starship Technologies. We are a company building a network of robots ready to serve you anytime, anywhere [Internet]. [Place unknown]. [cited 2019 Nov 27]. Available from https://www.starship.xyz/ 4. Forbes [Internet]. [Place unknown]. Forbes; 2019. Starship Technologies Raises $40 Million To Expand Its Food-Delivery Robots On College Campuses; 2019. [cited 2019 Nov 27]. Available from: https://www.forbes. com/sites/amyfeldman/2019/08/20/starship-technologies-raises-40m-to-expand-its-food-delivery-robots-on-college-campuses/#2dae63981cec. 5. University Housing [Internet]. Madison, Wisconsin: University of Wisconsin – Madison; 2019. University Housing Launches New Starship Robot Delivery Service; 2019 [cited 2019 Nov 26].. Available from: https://www. housing.wisc.edu/2019/11/robot-delivery/. 6. WKOW [Internet]. Madison, Wisconsin.: WKOW; 2019. Delivery robots hit UW-Madison’s campus; 2019 [cited 2019 Nov 27]. Available from: https://wkow.com/ news/2019/11/04/delivery-robots-hit-uw-madisons-campus/?fbclid=IwAR3uzvspA4wI6XgzIy3l40lmBUdPU1a0i6knAzODm12fpR4VPBdJEWRM3aU. 7. Damiano, L, Dumouchel, P. Anthropomorphism in Human-Robot Co-evolution. Front. Psychol [Internet]. 2018 Mar [cited Dec 2019 Nov 28]; 9: :1-9. Available from https://www.frontiersin.org/articles/10.3389/ fpsyg.2018.00468/full. DOI: 10.3389/fpsyg.2018.00468 8. NPR [Internet]. [Place unknown]: NPR; 2017. Hungry? Call your Neighborhood Delivery Robot; [cited 2019 Dec 3]. Available from: https://www.npr.org/sections/alltechconsidered/2017/03/23/520848983/hungry-call-your-neighborhood-delivery-robot. 9. Carrozza, MC. The Robot and Us: An Antidisciplinary Perspective on the Scientific and Social Impacts of Robotics. Rome: Springer; 2019. 10. Pfaffenberger, B. Fetishised Objects and Humanised Nature: Towards an Anthropology of Technology. Man. 1988; 23(2): 236-252. 11. Latour, Bruno. Reassembling the Social: An Introduction to Actor-Network Theory. New York, NY: Oxford University Press; 2005. 12. Khong, L. Actants and Enframing: Heidegger and Latour on Technology. Stud. Hist. Philos. Sci. A. 2003; 34: 693-704. 13. Vice [Internet]. [Place unknown]: Vice; 2018. Delivery Robots Will Rely on Human Kindness and Labor; 2018 [cited 2019 Nov 26]. Available from: https://www. vice.com/en_us/article/ne98x7/delivery-robots-will-relyon-human-kindness-and-labor 14. Applin, S, Fischer, MD. New Technologies and Mixed-Use Convergence: How Humans and Algorithms are Adapting to Each Other. In Proceedings of the 21st IEEE International Symposium on Technology and Society; 2015; Dublin, Ireland. p. 1-6. Available from: http:// ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7439436&isnumber=7439393. DOI: 10.1109/ISTAS.2015.7439436 15. Inc [Internet]. [Place unknown]. Inc; 2017. Robot Delivery Company Influencing Laws That Favor Its Autonomous Bots; 2017 [cited 2019 Nov 29]. Available from: https://www.inc.com/will-yakowicz/starship-technologies-virginia-idaho-florida-wisconsin.html
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tural contestation. The food delivery robots make visible, or at least prompt contemplation of, the invisible; they present, through a distinguishable artefact of material culture, the symbolic categories through which we organize the world. Mapping how technologies and artifacts participate in our everyday lives permits us to see how technology is not merely an application of science to technical matters but also that technology, through dealing with economic constraints and surmounting legal roadblocks, is derived from the interaction of particular elements and shaped into a network of interrelated components [10]. This approach may be labeled Actor-Network Theory (ANT), a theoretical framework applied widely throughout Science and Technology Studies. Developed principally by Michel Callon, John Law, and Bruno Latour, ANT examines the relations and associations between human and non-human entities to understand how certain actors emerge. It is also useful in that it encorporates these entities into an ontologically symmetrical framework, enabling us to discern how “objective” knowledge and “subjective” beliefs forge and validate certain claims. Most importantly, by considering both technology and the social as part of a process of ever-changing relations and becomings, we are better able to understand the robots, and students’ relationships with them, as much less clear-cut than may commonly be believed. However, as Latour tells us, these associations are not immeidately recognizable as social until the moment they are “reshuffled” together [11]. The social, then, is not a discreet category or arrangement nor is it neutral; rather, it comes about through the interactions of mutually influencing entities. In this case, the robots result from a potential market for Starship and the cooperation between their parent corporation and the university, manifesting in an insertion, or intrusion, of the robots into student spaces. We cannot in fact, as ANT dictates, separate society from that which it comprises. Bryan Pfaffenberger’s call to view any technology as a system both of tools and related social behaviors and techniques [10] is mirrored in Lynnette Khong’s critical reflection of Martin Heidegger’s and Bruno Latour’s philosophies of technology. She stresses the limitations of each philosophy – for example, that Latour does not succeed in surpassing the subject-object dichotomy that characterizes Enlightenment thinking and that Heidegger’s account maintains human ontological mastery over non-humans [12]. However, Khong also reveals a commonality between the two: Latour’s aim is to reframe artefacts as not solely objects that are acted upon where Heidegger’s is to move beyond an exclusively human way of knowing the world [12]. Each revolves around a central thesis that has as its foundation the idea that a new technology is not merely a new material artefact but also one that forges new milieux of social relations and alters conceptions that are constructed by the same relations the technology engenders [10].
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The Journal of Undergraduate Science and Technology (JUST) is an interdisciplinary journal for the publication and dissemination of undergraduate research conducted at the University of Wisconsin-Madison. Encompassing all areas of research in science and technology, JUST aims to provide an open-access platform for undergraduates to share their research with the university and the Madison community at large.