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Discourse UNIVERSITY OF REGINA RESEARCH MAGAZINE FALL 2017 / WINTER 2018

Sandra Zilles, CRC in Computational Learning Theory, is driving change.

Dugouts: A new player in the fight against climate change | 06 Loaded Dice: How Sandeep Mishra is unlocking the links between risktaking and inequality | 08 Projecting future climate change to help keep Canadians safe | 17

Photos by Risa Horowitz, associate professor in the Department of Visual Arts. In June 2017, Horowitz attended the Summer Solstice Arctic Expedition, an artist residency devoted to art and science, with a focus on the environment. The works in this layout are the results of her sun-tracking marathon.

FALL 2017 / WINTER 2018 | VOLUME 3 | NO. 2

Discourse Editor Krista Baliko Manager, Strategic Communications Katherine Cormack Vice-President (Research) David Malloy Contributors Jocelyn Carriere Everett Dorma Rae Graham Trevor Hopkin Dale Johnson Costa Maragos Dave Oswald Mitchell Devin Pacholik Colette Schlamp Deborah Sproat All photos by The University of Regina Photography Department unless otherwise noted. Original design by Bravo Tango Advertising Firm Inc. Discourse is published twice a year by the office of the Vice-President (Research) and External Relations at the University of Regina. The magazine is emailed or mailed to internal and external stakeholders of the University. Ideas and opinions published in Discourse do not necessarily reflect those of the editor, the office of the Vice-President (Research) or the University of Regina. Letters and editorial contributions are welcome. To reach us: Discourse, External Relations 210 Paskwaˉw Tower, University of Regina 3737 Wascana Parkway Regina, SK S4S 0A2 Ph: 306-585-4024 Fax: 306-585-4997 E-mail: discourse.magazine@uregina.ca www.uregina.ca Return undeliverable magazines to: External Relations 210 Paskwaˉw Tower, University of Regina 3737 Wascana Parkway Regina, SK S4S 0A2

Inside

DISCOURSE: THE RESEARCH MAGAZINE OF THE UNIVERSITY OF REGINA.

FEATURES

08 Loaded Dice: How Sandeep Mishra is unlocking the links between risk-taking and inequality Sandeep Mishra’s research is shedding light on the reasons behind risk-taking behaviour.

PROFILES

12 Machine Learning: How algorithms, pure mathematics and creativity are driving change Sandra Zilles and her collaborators are helping drive the future of machine learning.

06 Dugouts: A new player in the fight against climate change Kerri Finlay explores the role of dugouts in helping to mitigate greenhouse gas emissions and offset the carbon tax.

17 Projecting future climate change to help keep Canadians safe Gordon Huang launches a new tool that projects future climate change to the year 2100.

DISCOURSE SUBMISSIONS

DEPARTMENTS

Discourse is a bi-annual publication. The call for submissions is sent out through the University research listserv. The call will be open from January 3 to January 12, 2018, for the Spring/Summer 2018 publication and from September 6 to September 14, 2018, for the Fall 2018/Winter 2019 publication.

02 Vice-President (Research) Message 03 Student Focus 07 Accolades 18 By the Book 20 Funding 22 Collaborate

Discourse's mission is to profile new and ongoing research projects by faculty, staff and students, and to showcase the breadth and depth of research being conducted at our University. If you have a research project, recent achievement, award, funding update, have written or edited a book or have been included in a world-class publication and would like to see your work profiled in Discourse, or if you are working with or supervising students conducting interesting research, please send submissions to: discourse.magazine@uregina.ca.

Vice-President(Research)Message

Welcome to the third edition of Discourse. In this issue you’ll find a number of articles that describe the great research our scholars are conducting and the impact that it’s having locally and globally. The research culture at the University of Regina continues to focus on quality, as national and international measures confirm. For example, the 2017 Essential Science Indicators report, from Thomson Reuters’s InCites analytics tool, tracks highly cited academic papers all over the world. The statistics, gathered from the previous ten years, ranked the University of Regina within the top one per cent in the world in physics, environment/ecology, engineering, psychiatry/psychology and social sciences.

“While we rightfully feature some of our lead researchers in this magazine, it is important that we acknowledge the amazing teams, units and individuals behind the scenes that make this outstanding research possible.”

The Average Relative Citation Factor (ARC), an international standardized measure of citations, shows that the University’s ARC value has steadily improved over the last decade, from under one in 2008 to almost 1.6 in 2017. An ARC value greater than one means that the paper or the group of papers received more citations than the world average. Our 1.6 rating places the University in a noticeably higher position than many larger comprehensive universities across the country. In October, Research Infosource ranked the University of Regina one of the top 50 research universities in Canada and placed us first in research revenue growth (12.6 per cent!) in the comprehensive university category for the 2016 fiscal year. This announcement dovetailed nicely with the two exciting funding announcements made earlier in the semester regarding several successful NSERC and CIHR grants, cumulatively worth more than $5.5 million dollars. While we rightfully feature some of our lead researchers in this magazine, it is important that we acknowledge the amazing teams, units and individuals behind the scenes that make this outstanding research possible. This turns out to be a rather challenging task, because what office on the University of Regina campus is not directly or indirectly connected with supporting faculty and students to achieve their research goals?

2 DISCOURSE | FALL 2017 / WINTER 2018

A researcher with a lab has Facilities Management to thank for its design and maintenance; a researcher hiring a student works with Human Resources to ensure all employment policies and procedures are followed and that the student and the professor are protected; a researcher relies on campus libraries to find current literature and scholarly news; a researcher needing a proposal read, a budget designed or ethics approval heads to the Research Office; Supply Management Services helps a researcher buy equipment; UR International supports a researcher who is travelling to an international destination or seeking to recruit international students; a researcher with graduate students works with the Faculty of Graduate Studies and Research; a researcher who has been featured in a story or magazine (like Discourse), or has received philanthropic research funds from an external source has External Relations to thank. And while the list goes on and on, the bottom line is that for every successful University of Regina researcher we celebrate, there are scores of individuals behind the scenes doing their work with passion and dedication. So with all that we have to celebrate regarding our research impact stature domestically and globally, and the awards that we have received and will continue to receive, I would like to offer my sincere thanks to the University staff that support our efforts – quite simply, we could not do what we do without you. DAVID MALLOY

Vice-President (Research)

StudentFocus Herbs and spices may be the key to natural anti-fungal medications Zinnat Shahina says she is hopeful that one day her research will help HIV and cancer patients overcome their vulnerability to fungal infections.

The end goal is to determine if these natural products can be used instead of, or in combination with, antifungal drugs.

“I grew up in Bangladesh, where the abundance of medicinal plants means that we reach for natural remedies before pharmaceuticals,” says Shahina, a University of Regina PhD student in chemistry and biochemistry.

Every day fungi grow more resistant to pharmaceuticals, says Shahina, so this research could be a game-changer, especially for those susceptible to fungal infections.

Working with her advisor Tanya Dahms, professor in the Department of Chemistry and Biochemistry, along with research associate Taranum Sultana, Shahina is putting cinnamon bark, cinnamon leaf, clove and rosemary oil under the microscope to see how they work against Candida, a common opportunistic pathogen that causes fungal infections.

“Through science we are trying to provide evidence for something that many people have known for generations: essential oils work.”

“By comparing and combining each herb and spice’s essential oils, our research team is seeking to find out which constituents inhibit virulence and cell division in fungal infections,” says Shahina.

Zinnat Shahina’s research is supported by the Natural Sciences and Engineering Research Council (NSERC) and the Canada Foundation for Innovation (CFI).

“Through science we are trying to provide evidence for something that many people have known for generations: essential oils work.” DISCOURSE | FALL 2017 / WINTER 2018

StudentFocus

How victims of bullying can help in treatment research Bullying is a traumatic experience associated with a range of psychological and adjustment difficulties, such as PTSD, anxiety, depression and unstable interpersonal relationships, says Audur Thorisdottir, a third-year PhD student in clinical psychology. “Bullying is a concept that describes a wide array of direct and indirect behaviours, including physical aggression, verbal aggression – like intimidation and teasing – and social manipulation, including spreading rumours or sending hurtful messages online,” says Thorisdottir, an international student from Iceland. While many adults carry around the negative consequences of being bullied early in life, it’s not only children and adolescents who are bullied, says Thorisdottir. “The prevalence of bullying among adults in the workplace is also high, but often it’s a hidden problem that causes significant burden on the employee’s health and productivity.” Thorisdottir explains that adults may have a harder time coming to terms with being victimized.

You may be eligible to be part of this research if you have a history of bullying victimization and still feel bothered by that experience (either recently or early in life) or are currently being bullied in your workplace, are 18 years or older, live in Saskatchewan and have access to a computer and the internet. You will receive 12 sessions of online therapy, as well as questionnaires and assignments between sessions. For more information, please contact the Anxiety and Illness Behaviours Laboratory at 306-337-2473 or bullying.treatment@gmail.com. 4 DISCOURSE | FALL 2017 / WINTER 2018

“They may feel ashamed and blame themselves for what happened, or think they should be able to stop it,” she says. Her research into treating the effects of bullying centres on providing online therapy to victims of bullying. “Internet-delivered therapy has been proven to be an effective and convenient therapy that increases client accessibility – especially for those living in rural areas,” Thorisdottir says. Her interest in bullying was piqued through her research and clinical practice in the field of trauma, where she learned about the pronounced and prolonged effects bullying can have on victims. “We often treat symptoms – like anxiety and depression – but not the traumatic impact of the victimization experience itself,” says Thorisdottir. “This is the first victim-tailored treatment that focuses specifically on the traumatic impact of bullying victimization.” Thorisdottir says her goal is to discover whether treating bullying victimization as trauma, using an adapted version of a specific trauma-focused treatment, helps victims of bullying. Audur Thorisdottir’s research is supported by Delta Kappa Gamma. This year she was one of only five recipients in Canada to be awarded the 2017-2018 World Fellowship, a fund established to provide opportunities for women from foreign countries to pursue graduate studies in Canada and the United States.

“I made the documentary because women are still disappearing. While I was producing the film, in May 2017, a woman from Prince George went missing. How and why does this phenomenon continue?”

Highway of Tears Tennessa Wild grew up surrounded by the pain and sorrow associated with the area commonly referred to as the "Highway of Tears" in northern British Columbia. This 720-kilometre section of Highway 16, between Prince Rupert and Prince George, is where 19 women have dissappeared over the span of more than 30 years. Of those cases, 18 remain unsolved. To help tell the stories of those affected by these missing and murdered women, and to ensure the memories of the women live on, Wild made a documentary called Highway of Lost Years as part of her journalism master’s thesis. Wild says that when she was young, there wasn’t a lot of fear around travelling the highway. “In part, the lack of fear was because hitchhiking was a part of the community culture and was how most people got around.” Wild explains that this is for a number of reasons, including necessity. “Poverty means people don’t have cars or can’t afford gas. Thumbing

a ride was an easy way to get from place to place in communities without public transportation.”

knows that while her story is one of many, numerous women have not lived to tell about it.

Growing up on the outskirts of Houston, British Columbia, living adjacent to Highway 16, Wild had her own experience with this infamous stretch of road.

“I made the documentary because women are still disappearing. While I was producing the film, in May 2017, a woman from Prince George went missing. How and why does this phenomenon continue?”

One night, when she was about 13 years old, Wild was walking home from work along Highway 16 when a passing car pulled over and yelled for her to jump in. Wild recognized the driver as a family friend. Only once safe inside did she learn she was being followed. “The driver pointed out the silhouette of a man about 20 feet behind me. As the car pulled away, I watched him dart into the brush and further into the trees.” Wild says a police report was never filed. She believes it’s because at that time many people in the community came to normalize these incidents – and the violence.

Because Wild is from the area, she says she gained a lot of trust from the locals who she says gave graciously of their time and energy to speak with her and appear on camera. She has also learned a lot of troubling information from them. “Because the RCMP can’t talk about open cases, the trauma continues for those who don’t recover their loved ones. In many cases the families haven’t had updates on their daughters’ cases for years. They live with no answers.”

“But there’s nothing normal about missing and murdered women.”

She adds that many reports about what needs to be done have been written and recommendations have been made. What is absent is implementation.

Looking back, Wild now sees the severity of her incident. She also

Wild points to public transportation as one example.

She says an initial proposal for public transportation along the entire interchange was made in 2006, but only got up and running in the summer of 2017, adding that it will take years to know if it has any effect on reducing the numbers of new missing and murdered women. “The losses have been traumatic for so many people and everyone I spoke with is somehow connected to one case or another, so my focus has been to keep the women’s memories alive, ensuring these tragedies are not forgotten and remembering that there is still more to be done to find answers for the friends and families of these women.” She says her hope is that the documentary will help others to be proactive. “I want to inspire others to ask questions and think more critically about the issue of missing and murdered women,” she says. “While acknowledgement is appreciated, real change occurs when action is taken.” D Tennessa Wild’s documentary will be shown in local theatres in Northern B.C. She has also applied for entry into several film festivals. DISCOURSE | FALL 2017 / WINTER 2018

Profile

Dugouts: A new player in the fight against climate change Dugouts, large holes used to catch and hold rain or runoff, are ubiquitous on the prairies. These bodies of water that dot the landscape may also prove to be a game changer in the fight against climate change. A University of Regina research team, led by biologist Kerri Finlay, has found that the pH levels in many of Saskatchewanâ€™s algaefilled agricultural dugouts are optimal for quickly processing and sequestering carbon dioxide (CO 2). Not only could they help mitigate greenhouse gas emissions, dugouts may also offset the carbon tax. Furthermore, the team is using results from their prairie dugout research to help develop water management processes that could combat harmful CO2 emissions across the country. And thatâ€™s a winner. This research is supported by the Saskatchewan Ministry of Agriculture.

Biology professor Kerri Finlay with Corey McCowan, a fourth-year honours student in the Department of Biology, taking samples from a dugout near Regina, Saskatchewan. 6 DISCOURSE | FALL 2017 / WINTER 2018

Accolades

1. Christine Chan, professor and Canada Research Chair (Tier 1) in Energy and Environmental Informatics, was inducted as a new Fellow in the Canadian Academy of Engineering (CAE) in June 2017. Chan is the first female Fellow of the Academy at the University of Regina. The Academy praised Chan for her “major contributions to the education of engineers and research in information technology and applied artificial intelligence. She is an international researcher who has done pioneering work in engineering applications of artificial intelligence.” The CAE is an independent, self-governing and not-for-profit organization through which Canada’s most distinguished and experienced engineers provide strategic advice on matters of critical importance to Canada.

Fellows are nominated and elected by their peers on the basis of their distinguished achievements and career-long service to the engineering profession. 2. According to a national study released in August, a significant percentage of Canada’s public safety personnel self-report symptoms consistent with one or more mental disorders, proportions that appear much higher than found in previous diagnostic research with the general public. “Mental Disorder Symptoms Among Public Safety Personnel in Canada” was released by a team of researchers with the Canadian Institute for Public Safety Research and Treatment, led by University of Regina psychology professor Nick Carleton. The first study

Photo credit: Charles Schelle, Frostburg State University

3 3

4 4 of its kind published in Canada, the report has been downloaded more than 4,600 times, placing it in the top five per cent of all research tracked by Altmetric, a company that monitors and analyses online engagement with scholarly research. 3. In November, Pamela Osmond-Johnson received the Canadian Education Association’s (CEA) Pat Clifford Award for emerging education researchers. The award recognizes scholars who are challenging commonly held assumptions in Canadian education policy, practice or theory. Osmond-Johnson, assistant professor of educational administration, has made a significant and critical contribution to the CEA’s mission to transform public education through her

innovative leadership research, which positions classroom teachers as both leaders and learners. 4. This fall the University welcomed to campus the institution’s inaugural Fulbright Canada Research Chair. As part of the prestigious Fulbright Canada program, Richard Russo, associate professor of geography from Frostburg State University in Maryland, is conducting research on campus and across Saskatchewan to understand the role of books and written language in creating places and spaces of Fransaskois(e)/ francophone identity. He hopes his research can serve the Fransaskois community – and other small linguistic groups – by analyzing how the textual environment of a minority language can better support its community of speakers. DISCOURSE | FALL 2017 / WINTER 2018

"What we do know, on an aggregate level, is that income inequality is one of the best predictors of things like gambling rates, property crimes, violent crimes, teen pregnancy â€” any kind of risk you can imagine."

DISCOURSE | FALL 2017 / WINTER 2018

Feature

Loaded Dice: How Sandeep Mishra is unlocking the links between risk-taking and inequality Imagine a football team is down six points. Stuck at their 10-yard line as the final seconds of the game count down, their only chance is to throw a Hail Mary pass for a touchdown. The obvious choice for the team is to go for the risky play to close the gap. Unfortunately, that sense of desperation and inevitability might be the same feeling motivating a problem gambler on the brink of homelessness to spend their paycheque at the craps table. As the old saying goes, and as new research seems to confirm, desperate times call for desperate measures.

BY DEVIN PACHOLIK

Sandeep Mishra’s research is shedding light on the reasons behind risk-taking behaviour. According to him, people take risks based on many variables, real and perceived. Real variables like inequality increase the likelihood that people will take risks, but the craps player may also feel a stronger urge to put it all on the line after seeing a nearby table hit the jackpot. While “desperate times call for desperate measures” is a rational line of thinking for down-and-out football teams in a controlled game, a problem gambler’s sense of reality might be distorted. “How do people deal with gaps between where they are and where they want to be, and choose risky options accordingly?” Mishra summarizes during an interview. “That’s risk sensitivity theory.” His work on the topic may help describe the mindset behind things like gambling addiction, crime and other antisocial behaviour. The associate professor of organizational behaviour studies the psychology of risk through his work with the Paul J. Hill School of Business at the University of Regina. He is particularly interested in understanding how aspects of environment, such as income inequality, motivate risk-taking behaviour. One experiment from 2014 demonstrates that people tend to take more risks when they believe they are at a disadvantage. Mishra and his team put pairs of people in a lab and gave one of them $10 and the other nothing. Later, they had both participants gamble. The results showed, simply put, “you find that people gamble way more where they’re victims of inequality,” Mishra says.

In another experiment, he had participants play a reactiontime game involving clicking targets on a computer screen. Mishra’s team gave false feedback to the participants showing they were either well above or well below the average reaction time. The researchers then told the test takers their results were related to intelligence. Essentially, participants who believed they weren’t as intelligent as their peers clicked more erratically on the screen to try to improve their score. The experiment showed that people who believed they were competitively disadvantaged engaged in riskier behaviour. One key factor linking these two studies is that both place participants in a situation of relative deprivation. Mishra explains, “It’s basically feeling anger, resentment and frustration to a perceived unfair gap between you and other people.” He underscores that the two studies are simplified instances of relative deprivation, emphasizing that the “real world is messier than that,” but the data may illuminate the damaging effects of social and economic inequality, whether real or believed. “What these studies translate to in the real world is an open question. What we do know, on an aggregate level, is that income inequality is one of the best predictors of things like gambling rates, property crimes, violent crimes, teen pregnancy — any kind of risk you can imagine. This research has led to offshoots where I’m interested in inequality and how disparity affects not only risks and gambling, but also wellbeing and health.” DISCOURSE | FALL 2017 / WINTER 2018

Feature Shadi Beshai

“This is where my theory comes in: People who are vulnerable to psychopathology are going to engage in social comparisons, and it will fuel the fire and become a vicious cycle.” This line of thinking has developed into a collaboration between Mishra and University of Regina assistant professor Shadi Beshai. Beshai works in clinical psychology and is particularly interested in depression. “Work coming out of Mishra’s lab seems to show you don’t have to actually be disadvantaged for you to feel relatively deprived,” Beshai says. “This is where my theory comes in: People who are vulnerable to psychopathology are going to engage in social comparisons, and it will fuel the fire and become a vicious cycle.” He is hoping to test the link between mental illness and false social comparisons. Beshai’s lab is only just beginning to research such theories, but he says their initial findings show a relationship between relative deprivation and mental health issues. “If people compare themselves, and find themselves wanting in an important domain, our work shows that this particular process is detrimental to mental health. It’s associated with an increase in anxiety and depression symptoms.” 10 DISCOURSE | FALL 2017 / WINTER 2018

The relationship between social comparison and depression then becomes a chicken-and-egg problem. According to Beshai, “We know that people who suffer from depression process the world in a negative and skewed way, which may lead to more negative comparisons and thoughts about themselves, which leads to more depressive symptoms.” He says that while work on this complicated relationship is in the early stages, Mishra’s findings have changed how he thinks about mental health in general. “It appears that selfcomparison has a large effect on mental health symptoms. The data seems to explain a big chunk of variance in depression symptoms. It’s not just depression; this process is transdiagnostic across many disorders. This is maybe an important process for treatment.” Of course, risk-taking can be healthy, from a football team opting to run the ball on a third-down play, to an entrepreneur starting a new venture, risk can lead to innovation. Sometimes the best motivator is competition. “How am I doing compared to everyone else?” Mishra says, “If you think on a psychological level, that is the human condition. It’s about comparison. Relative deprivation is an interesting problem because it summarizes the emotional mechanism that leads us to taking risks.” “I’m interested in looking at different kinds of risk-taking,” says Pat Barclay, an associate professor working in psychology, neuroscience and behaviour at the University of Guelph. “There are some kinds of risk-taking that are done by those who are desperate, the competitively disadvantaged, but there are other forms of risk-taking where people will take risks because they can succeed.”

Barclay co-authored risk-taking studies with Mishra on gambling, relative deprivation and competitive disadvantage in 2014. Now, the two want to find out what separates risktaking motivated by desperation and risk-taking motivated by skill or having the means to reduce the chances of failure. In a study that is not yet published, the researchers are testing a theoretical model to mathematically predict risk-taking from “those who are likely to succeed versus those who are competitively disadvantaged.” Even though all models are simplified, when it comes to negative risks that can harm others, perhaps Barclay’s work in conjunction with Mishra’s findings on relative deprivation could help reduce harmful behaviour, such as problem gambling or crime. When asked if the goal is to create a system to predict crime, like something out of science fiction, Barclay says with a laugh, “There are lots of examples in fiction of people trying to predict human behaviour. My favourite is Isaac Asimov's Foundation series, where there is a mathematical science of history. They are able to predict the major forces going on — economics, religious powers, trade.” While the idea is fantastic, if not a bit creepy, Barclay says their current research will help us understand the forces that cause different kinds of risk-taking, which in turn could help reduce the likelihood of antisocial behaviour by addressing those forces. “Humans are obviously very complex, and a model like this is a simplification in the same way a hand-scrawled map is a simplification of the real world,” Barclay says. “There are a lot of features that aren’t on the map, but at the same

“If you have a gap between where you are and where you want to be with a safe option, you have to take a risk,” Mishra says. “It’s simple, but it’s incredibly evocative because that’s how most of life works.” time, a hand-drawn map can be really useful to help you get somewhere. It’s the same thing with using mathematical models to predict human behaviour. We might be able to make generalizations through this model and determine which factors hold more weight when it comes to risktaking behaviour.” For Mishra and his colleagues, one of their key objectives remains to understand relative deprivation in relation to risk-taking. Whether it’s crime, mental health or the performance of sports teams, perhaps our willingness to roll the dice really does hinge on our sense that times are desperate. “If you have a gap between where you are and where you want to be with a safe option, you have to take a risk,” he says. “It’s simple, but it’s incredibly evocative because that’s how most of life works.” Sandeep Mishra’s research is supported by the Social Sciences and Humanities Research Council (SSHRC). Photo Credit: Martin Schwalbe

Pat Barclay in his office at the University of Guelph.

DISCOURSE | FALL 2017 / WINTER 2018

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Machine Learning: How algorithms, pure mathematics and creativity are driving change

defeated the world’s top players in the online multiplayer game Dota 2 after only two weeks of learning. The list of uses for machine learning is long and will continue to grow.

It’s not surprising, then, that machine learning is the subject of ongoing research all over the world. Among those researchers is University of Regina computer scientist Sandra Zilles, Canada Research Chair in Computational Learning Theory and the recipient of several awards for her work in this area. She was named a member of the Royal Society of Canada’s College of New Scholars, Artists and Scientists in 2016, and was recognized as an Outstanding Young Computer Science Researcher by the Canadian Association of Computer Science in 2014.

student Elham Parhizkar, she is envisioning scenarios where cars would exchange information. “The basic idea of a trust model is to let agents, or in this project cars, rate each other and decide whether or not to interact with a specific car in the future,” Parhizkar says. “The goal of this project is to improve communication between self-driving cars.” Zilles says the information one car receives from another might be manipulated by a malicious source, could be “noisy” because information gets lost in transmission or might be wrong because the car sending the information has faulty sensors. DISCOURSE | FALL 2017 / WINTER 2018

i l I acti cted t x 2, th ns jc n o i a e t r 6= g ↵ . assej a i a 2 ecutin The a and j 1 x i a 1a 2 hen e ected. i 6= x 1 W una↵ g . If nd 3. ain rem , e, f a nce is d e b, c, n sequ o acti

(l to r) Elham Parhizkar and Ashwani Kumar

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r h ce t =e i d W Sauer bound) Corollary 8 (Generalized (Gurvits, , 1  i  m, be a ! e1997)⇥ ·Let rou = :X x !1{0, 1}, and = ··= ⇥ b . If VCD (C) = d spanning family of mappings c = ps g then |C| Φ (N , . . . , N ). . i 1 x 2 ! x 1) ! only =b of a we con = e f l j − families, b r , and are of spanning this bound and the sfollowing Since ! side 2.productsapplies ring (a 1 to them. os i he fou general definition of maximum classes= 2) p x r s i i − s rin o is ht 3. itfamily (a 2 , 1  i dm,cabesea spanning w g, c f ↵ num based Let Definition 9 (VCD -maximum class) = e r u -maximum ofif er co . j= ⇥ · · · ⇥e th. i C is called trVCD onta as t mappings : X ! {0, 1}. Let 4 o s b h i n h ered e the VCD (C) = d and |C|= Φ (N , . . . , N ). t t wo i e ot m n a h a Kumar says his primary goal is to solve biological problems, t i s h n s t tican isomething g ngle d ac actio hegreat les learn from The class of but e doof of a VCD- = e Twhich ottoe VCD(C), machine learning has been “a tool for me to nexample all sets of size up is the standard ( o N i ns. x“Iftilwe . n l n tion l p maximum class in the He binary case, straightforward extension to abiologists VCD -maximum =d es, and easy-to-work-with that.” sees his has job providing tools that ndother weaas c a ( s is to Thea cheap can ↵ poss layer p(VCD -maximum) a multi-label class, namely the class of concepts that have at most , x. 1 x example of this=is his x2 use in their research projects. first ible erm(C) (VCDcan (C)) many non-zero elements. intuitivejexample of a maxiVCD i =AsAnanother b If a c f 2 th I e h use of machine learning to develop a scale to help biologists d / a n fl mum multi-label class, consider the following geometric example of a class that is maximum • u p 1 nx resource or organism, and we can a a a n taquantify 1 genetic interaction. tVCD 2 and 2. results of experiments on x ion the + 1 i is in p ge the ction ipped. osioftVCD x1 = i o i= − n f i I s 2 s 1 transfer that information to p is sh − i. 15 osipartially .T • +1 X a 1/ =a tion ositio to ro h = 1 own x e tate it’s a i = −1 a morei sophisticated − x1 +1 f for ns of torganism, in F c I 1 a a X • 1 he t ll ↵ igur great achievement −1 x 1 = 3. t for science.” = i e i i les a les 8 2. =a If i bf )) = • 1 x x 1 , , e c 7 . (( thesome “The car receiving the information would need model. . , a 1 − ((id) n = , c x1 i j ) = of what information to trust and what information nota tof +1 t = e i a2 r j −1 X If trust. We’re using machine learning to come up with this 6 i a 2a 1 • kind of trust model.” (a 1 i

⇤

Figure 1: The geometric class described in Example 2 forto m apply = 3. He says machine learning also makes it possible Zilles is also excited by her work with graduate student knowledge gained from research on one organism to Ashwani Kumar, whom she co-supervises with a faculty another. gives researchers head startposition because Example 2 Suppose thatThis X corresponds to m linesa in general on itthe plane, i.e., member from the Department of Chemistry and no two lines arereduces parallel and three lines share a common Then (i) the number of the no number of interactions they point. have to consider, 2 ; (iii) the number Biochemistry. Kumar is a biologist and a PhD student in is 1 + m + regions m(m −time 1)/2;and (ii)money. the number segmentshe and rays is mare saving For of example, and Zilles intersection points is m(m−1)/2. Summing these numbers yields 1+2m2 = Φ2 (2, . . . , 2). computer science, and is using machine learning of methods working on a project that involves determining if knowledge All regions, segments, rays and intersection points form a natural multi-label concept class to analyze data in the systems biology lab. about genetic interactions in E. coli can be2. applied to other and VCD -maximum of dimension Each instance takes values that is VCD ⇤ -maximum G

↵=

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in {−1, 0, +1}, depending on such whichas side of the line the concept is on (and 0 if the concept pathogens, Mycobacterium tuberculosis. “The nice thing is he’s a trained biologist so he really knows is contained within the line itself ). Each region is a concept with instance values −1 or +1. what makes sense and what doesn’t make sense Each when segment/ray “If is weacan learnwith something from cheap and easy-to-workconcept value 0 in oneaparticular instance and values −1 or +1 intoall the other intersection point a concept value 0 on exactly he does his data analysis,” she says. “He knows what withinstances. resourceEach or organism, and we is can partiallywith transfer two instances. One can verify that no set of three instances is shattered using any label look for and that’s really valuable. It’s exciting to work with that information to a more sophisticated organism, it’s a mapping to a binary class. Figure 1 illustrates such a class for m = 3, and Table 2 shows someone who has that domain knowledge.” great achievement for science,” he says. the corresponding concepts.

13 a nd x= 4. / WINTER 2018 14 DISCOURSE | FALL 2017

grou

|SF |+|SB | is lower-bounded by the size of the smallest vertex u we c these sAmong p u f↵n p cover for GMX (I). o o r g g n ed a ri cocost ntaic(n relat is1ts of smallest -Theorem G Proof. Let (uF , vB ) be an edge sin n e i l MX (I). Then , p z g z s p u ocon rin smallest Toto coninput thiswith requires the state pair6.(u, be laexpanded Aeon actith s of p by 1. v) s m o f a (U, V ) from w o g c t s s t n the r has is I, i.e., A must expand u inAthe firsforward Thi sitvioin e and Vac(lines tion 16 n. direction oor y i p a p l s x p p d backward direction. Thus the set by o of states st con theA on If a firexpanded me Tcover ific, . The se to,guarantee , x. tha1 thofe G c . (I). input I corresponds to agavertex f e . MX o . p n its 1 heuristics re sreason tionThat’s5)m x +ar othat wide variety problems another Zilles enjoys the applied research because it is tangible, and We awill eclater. nefficie show ofbelow this lower ions used.An oI sitio bound s(Theorem o t i p i e t s i b e o s o on bidirectional po Tworld.” thisattained abstract mathematical it’s therefore much easier to see and explain to others whycannotlikebe yDXBB s sho in p is in pair by any admissible i b y e l g t n selection is m i ren an it might be useful. It’s easy to see why self-driving cars need e rarea n, a i f this ga front-to-end search algorithm. However, we admishthe urdevise t o c t i Zilles’ theoretical research is in of interactive t h n e i c r g The pseudoc a i some way to know what information can bem trusted. Similarly, no at a thesfinds sible algorithm, NBS, machine learning. Shewhich is tryingefficiently to question of tratio thanswer conad near-optimal lesbased on lab results e 9 t i it is analogous t a x s it’s easy to explain how a research paper e u l necessary th work ilof vertexwhether cover aand thuslearning is near-optimal in terms 10 ese machine algorithm will with less g c h i n t i t all obtained by machine learning ak ma say by of might be useful to others. node expansions. 1 1 problem inst data if that data is chosen “int a very helpful scheway,” me o A included here b s of the domain. But she is salso claimwithofknowledge near-optimality is Further, only does withit respect to es, happy when she has a chance to return to Thea human a c are very similar 2 1 n makepairs a difference the machine knows that the data it will to Theotheoretical research, to the pure mathematics that forms a state the that ifmust be expanded according le: 2 rtai b efoundation i c s 1 receive has been specially selected? on which to build the algorithms and models for s n j. I 13 rem 1, it does not take into account state pairs of the form o p e

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machine intelligence. Zilles likes the theoretical research because it’s wholly mathematical, and the results can be broadly applied.

s nce e d i inc

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“That’s still my main direction in research,” she says. “And it’s not always with specific applications in mind. The nice thing about the theory is the ideas generalize to a whole class of applications.

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1 1 the you will do a “When you work on an application t directly, . c e a res 5 h 1 t h = 1 h F F=0 lot of specific things thatsare tailored to that one specific ) = e rep b e ) i n l e a hB = 0 hB = 1 p at a new application, a lotbofcftheg ca application. If you imlook ning1 N ame Algorithm ( t fi g i e ( d n i work you have done for that other application is going to p or C ← ∞ f1: j)= and That’s Figure 1: A sample problem instance.e Tops .) not the samei with ters 2: OpenF ← {λ the theory. With the e “It has actually been proven already, both in theory and e /2useless. h s m a T a 2 1be a a andF j c trying to model N par = theory, dI am 3: Closed a1 whole class of problems, so in practice, that if I feed the machine good data, then the F ← ∅ i a 2a s 2 n . a 1 o 2 x x x c left right ra ↵,while Open if (a 1up with are hopefully I come Let 4: d sewhatever results gen←eF O̸= )) = applicable to machine needs less data to learn something. aButndwhat has n . g n 5: at iPsairs e 6 a f 2 h ( t h lbmin ← m d:0, fB d:0, f:2 j f:2 = aF rth (be) ition of S ↵ t6: old ( n i a2 ) h fi 7: if lbmin e s p d ≥C j = j Dd:1, f:2 bgrou nce eB d:2, f:6 bF i a 2a 1 8: ↵),endan if e i a2 ) u d s . i . 2 j . .9: the (a 1 minset ← . oinc i a 2a 1 )= 1 2 10: n ( ) e U set c d:1, f:2 d:2, f:2 e d F B = −←1){X a h b 1 n ( t xmin ( e a ↵ ( ) h 2 11: U ← • b ( t 1)m ⇢ (1 12: x) Choose j)= = b)f:2 dF hen −any t g x c d:2, d:2, f:2 i , = B ) e 2 e ( V set ← {YU g ) j a a2 13: x = = c 1 i (114: V min ← tm = e, f d= eF bB d:5, f:6 • b x d:2, f:2 e (a 1a 2 ( = 15: Choose 2 d provany V o 2/ t a = hen 16: Forward-Exp c rd th fF aB d:3, f:3 d:3, f:3 x 2 6= earn ot ha17:an lBackward-E /2 ( n 2 2 = s a i 8 c end while j It x18: x2 = and and 19: return C Figure 2: The Must-Expand Graph for Figure 1, where C ∗s=3. 1 9 ↵ − 3 eter tion 12. = a2 10 2 x class efini 14 4 e = D h T j 27. 5 nd :2 a m e 2 b x} r 11 , / o e 13 a ↵ 1 a Th t to {{ 1. 6 c = se ) ) respe 491 t of a

Over the last decade, Zilles has collaborated with academic colleagues and people in industry across the globe, including at the University of Regina, the University of British Columbia, the University of Alberta, and in various places in the United States, Germany, Japan, Israel, Brazil and beyond.

u n inp be defin O f o can Pro ntly e i he c effi ine t m r e t e 1. D

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gi e ori 15 In th 1. Vancouver

7. Vicosa (Brazil)

10. Bern (Switzerland)

2. Edmonton

8. Copenhagen (Denmark)

11. Be’er Sheva (Israel)

3. Toronto

9. Bochum (Germany)

12. Singapore (Singapore)

4. Denver (USA)

Darmstadt (Germany)

13. Jinhua (China)

5. Sunnyvale (USA)

Kaiserslautern (Germany)

14. Sapporo (Japan)

6. Manoa, Hawaii (USA)

Munich (Germany)

DISCOURSE | FALL 2017 / WINTER 2018

we ha sup T every ve tha L1 , L2 , L , 01 D L, i≥1 L 2 3 ...f t for L L , di is L \ [ i−1 ⌘ i or w.r.t. t he sup j L = [ 1 j i Lj ), t . hen S j ≥i Lj (and d remum ove is said r positiv to be i = 1 if so all L 2 L e teac a posi me L i of th hi ing di e sma tive te 2 (4) mensi ng sequenc L l l a e d i c s o h o e t e i n s ng s not wanted toizfind S for L. of L ( e ofthe have a a pshortest More possib (possibly 1 sequence f “If you ositive p o forma ly 1) o r ) Simila s L i i sequence of moves to get from s t teachi i . v d The o e teac efined is defi rly, R + lly, RTD ng r h d i n a T er ofstate n s e Note ( g D d L o s r ) your scrambled-up to the goal a e d ( s a teac t w.r.t = inf L (S ) = that th the or hing s . d e follo ) = inf S o S ord( s e u r t or d ( p of thyou e S ) wh q state, can’t afford to look at rd(S ) u wing i ≥ e d S) = e nce teachi Mo1 i . The ere S , whe RTD( 0 holds fo n r r e n r g e a c o n all possible routes. Your s computer u S ran L ): r ever ges ov ges over a is saequteonncieciotyf rsive 0 y L ll tnot RTD( ✓La er anever be a eaicdinhtioan blong, . low would Aecsto ll posfinish,  m, L i≥ n t d ) d  e h g = 1 i ) a f t m , s C o i ( t e v i R r qouneontc mpl e twe t Tcneed everlong D e f VCD TD(L 0 I a 97) Le long, time. So some . y oensic hinisg m teachi )≥o ··· ⇥ m s o if L e 1⇥ n n q r g d u o ( e t sesearching.” S) ≥ n o pth of c q smarter methods of n e wi n g u o l i s l e c o L f . It is d1 = emm nce S f L and the sup T o 0 f a r nlieis,nth(isLbound2 L w.r.t. not been done systematically is to model Lwhether L 6 there D(L,“But for it makes them to be able to figure that out, P needs to B 0 a 2 , ≺) th f L T s o trictif pthe machine just receives the helpfully 1 chosen beL D an )≥T somebody to offer them these ideas, these theories difference e teac a spananitngefnamdmisulymadata a A if r d PB D t s i a and algorithms.” and processes it the way it processes any pile of data, h i l orde eg ax mina(nLa0 in L ( m, ibn D -m TD p r i VC ) r m or whether the machine knows the data it receives has been p e i  i  s cal led d mpose s e p n . She says in her mind it’s like building.laic bigatower, with the s i a i o C s t nchosen iononowhich 1 if t d on Ltheoretical research forming a strong foundation is helpfully.” m. 5) h f(that VCD-related e a L r m i f s e o e e l i onot d t other research is built. “If you want to have something p s o m e m m She is also investigating whether there’s a way the machine u n a fi t x m o h i e m n x e d e b onic d -ma a p o ndar r u a leads up to a peak, you can’t build it on something that’s a t e t D 7 s n s s could interact with its environment, requesting more f C o e d erence t h o F e n h is th nsion to a V have at m io t l r thin; it will break apart.” he len engtheve information in areas where it’s needed and less in-areas based xte s that a max g ward e ofrythfien t oncept example of where h P t c m e it already has sufficient information. If scientists can f u o o r a m i f c o Zilles also uses machine learning in research on searching t h ite su h o max itive class i u s e n i t f n t s i g a r e interact with the machine 5 in that way, she says, it can save a in large “state spaces,” d t he ss t h i orTlarge networks,cwhich involves h m h bcla a e t e i As ano ple of a cla ns).a he fapathnfrom fiarsstart sioangiven lot of effort collecting data. finding the shortest position to xam t c i s t et r i c e n foleloqw that goal position. of ≺ uasl:it Machine learning algorithms currently require large quantities a fi , 0 n L i t e parto try y holds of data; algorithms that can solve problems with less data “In that area, you can also machine learning mapply +1 X 3 u st co of the network bec tiaand could make using machine learning more efficient. This would to learn something about the structure lly o n t a r i −1 be a welcome development for researchers such as Zilles’ then speed up the search. Again, it’s about reducing dere n a the o colleagues in biology and biochemistry who, for example, amount of data I need to look at, to find a short pathcfrom a n P c ept L 0 d B goalDposition.” given position to a T now spend a lot of time and money collecting data by doing (L 0, su experiments in the lab. Computer scientists try out their ≺ approaches to these ) S ≥ incein toy domains such as Rubik’s Cube, c4 PB problems she says, t TD( 0 h i s noting that “all the possible holdconfigurations of the Rubik’s L , L0 Cube make a huge network. s If you wanted to find the f , ≺) o r anyour +1 shortest sequence of moves to get from y cscrambledhoaticall up state to the goal state, you can’t afford to look −1 X 2 e 3. = m possible routes. Your computer would never finish, not of ≺ for 2 e l , we p xam 3. inPa long, long, long time. So we need some smarter g , ed i n E . b e i . i r c r , s e of searching.” methods s de plane G

Z ILLES , L ANGE , H OLTE AND Z INKEVICH

concept 0/ {x3 } {x2 } {x2 , x4 } {x1 } {x1 , x5 } {x1 , x2 } {x1 , x2 , x6 }

x1 [−] − [−] − [+] + [+] +

x2 [−] − [+] + [−] − [+] +

x3 [−] [+] − − − − − −

x4 − − [−] [+] − − − −

x5 − − − − [−] [+] − −

x6 − − − − − − [−] [+]

STS0 {(x1 , −), (x2 , −), (x3 , −)} {(x3 , +)} {(x1 , −), (x2 , +), (x4 , −)} {(x4 , +)} {(x1 , +), (x2 , −), (x5 , −)} {(x5 , +)} {(x1 , +), (x2 , +), (x6 , −)} {(x6 , +)} u

STS1 {(x3 , −)} {(x3 , +)} {(x4 , −)} {(x4 , +)} {(x5 , −)} {(x5 , +)} {(x6 , −)} {(x6 , +)} u

Proof. Let m ∈ N, m ≥ 2 and s = (s1 , . . . , sm ), s′ = (s′1 , . . . , s′m ) elements in {0, 1}m . Let ∆(s, s′ ) denote the Hamming distance of s and s′ , that is, ∆(s, s′ ) = ∑1≤i≤m |s(i) − s′ (i)|. We distinguish the following types of monomials M over m variables. DISCOURSE | FALL 2017 / WINTER 2018 Type 1: M is the empty monomial (i.e., the always true concept). Type 2: M involves m variables, M ̸≡ v1 ∧ v1 .5 Type 3: M involves k variables, 1 ≤ k < m, M ̸≡ v1 ∧ v1 .

feren

TheShe says the need forcethis-btypeasof research is growing as pr andfemore data is collected,eanddnetworks more kinds get ersofuofallsearching rbigger, both biggereand enceso much so that the v methods s n tio ten years-bagoascan’t necessarily cope now.Re e recu thatoworked d n sandcomany teach finding time forcursive rsWith i other commitments, iveteaching n itonwork cbutidZilles T g donimboth teisaacchallenge, e ocontinues n h A tresearch i e fi napplied nsion nitlearning, g disides machine building eatheoretical e clproblems chinasg and a par the menofaway is a foundations well as hammering at practical a sseofs, si ndrive the future titiasonshe and her many seqcollaborators helpoto u a a e s we o L – whereverncitemayf take them.nd of machineflearning or L into s o me r w nonis a s ela em by the Natural eSciences Sandra Zilles’ research is supported p ty su quence te and Engineering Research Council (NSERC) andbthe -cCanada lasse of the well in practice, which need revision, which may not work well. Foundation for Innovation (CFI). s and If, fo , fo r eve d r set f i = ⇣ sup or L y i ≥ 1, TD w. d [ L2

Table 2: Iterated for the class Cpair with u = 2, where Cpair = the subset. , cbteaching f sets / c−−,1 = {x3 }, c−+,0 = {x2 }, c−+,1 = } with c−−,0 = 0, {c−−,0 , c−−,1 . .m er, co++,1 ++,0 n Ifon o i t u Zilles is successful in coming up with a model that i n s o e {x }, c+−,1 1 , x5 }, c++,0 = {x1 , x2 }, c++,1 = {x1 , x2 , x6 }. All labels ) 2t, xh4 }, c+−,0 =n{xu1m er = {xsets ral p icontributing bteaching e ( n n e e g to minimal are highlighted by square brackets. h n e T i works well in theory, her hope is that she can transfer her h . t s t e ) n 2 ; (iii lin poi , 2). . . m . , s s to m a common i 2 theoretical findings into concrete algorithms that are usable ( s y 2 Φ 2 a r =concept x1 t x2clax3ss x4 x5 nd are TS (equal to STS) e+p − − − “That nes sh f segments a ields 1 +in2m a concrete goal,” she says. “Of (x3 , −), (x4 , −), (x5 , −)} {x l 1c}oncapplication. s − {(x2is, −),my y e o e b s r lu r la e e a i b b v lt s m u e {x } − + − − − {(x , −), (x , −), (x (x5 , −)} u k 2 1 3 4 , −), course, it might also happen that others do this kind of m num n a l t p−t − {(x1 , −), (x2 , −), (x4 , −), (x5 , −)} g these − − natura ch instan{xc3e} oI ndoc+epublish c e transfer because my research.” a h ummin ints form a t E − − − 1+. − {(x1 , −), (x2 , −), (x3 , −), (x5 , −)} {x } f + po ion 2. nd 0 45 }i − − 1 −or − − + {(x1 , −), (x2 , −), (x3 , −), (x4 , −)} ection m of dimens ept is on (a {x e}stime, lu a o−r −part of doing {x , x + +she−1says, {(x1 , +),fundamental, (x2 , +)} v c 1 2 u At the same e n m c o − i c n x s a a e t e -m {x1 , x3v } alu + − + − − {(x1 , +), (x3 , +)} ins h ne th t li i d ly t n w e c a t h theoretical research is understanding that not all of it ends up a t {(x1 , +), (x f 4 , +)} ncep ance {x1 , x4e} 0 +on− ex− + l− side o {x , x5in } an + actual − − la −be + {(x1 , +), (x5 ,that +)} is normal. is a co ticular inst being 1lu a n v o used application, and that i g h t {x2 , x3 } n−g a+ ny+ − − e r {(x2 , +), (x3 , +)} ept wi i Each r 0 in one pa {(x2 , +), (x4 , +)} a conc shattere{xd2 , xu4 }s − le+ 2−sh+ow−s s e i lu t a n v b i know. h {x2 , d x5 }point − − + is we don’t {(x2 , +), (x5 , +)}So what we Ta− of+ research s is “The3whole n po e o n c i a t n c , a e t s s r {x3 , x4 } − − + + − 3 , +), (x4 , +)} e in mdo=as theorists is offer a−wide variety{(x of results, a coherent, e r h inte r h o t f f {x , x } − − + + {(x , +), (x5 , +)} s 3 5 3 clas set o a o n h {x , x } − − − + + {(x , +), (x , +)} consistent theory, and then people at the next level can try out c 4 5 4 5 t u a s strates lu u and l i which of these theories, models, algorithms ideas work Table 3: Iterated subset teaching sets for the class C with u = 4. 1 1/2 e

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Projecting future climate change to help keep Canadians safe It sounds like science fiction. But it's scientific fact. Gordon Huang, executive director of the University of Regina’s Institute for Energy, R Eand Environment Communities and a professor of engineering, has launched a F ESustainable R E Nprojections about future climate change. unique tool that houses

CE-

SED The Canada Climate Change Data Portal (CCCDP) is the first coordinated effort for EA systematically sharing projected climate change consequences in Canada using highCHI NG resolution regional climate simulations.

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BytheBook

18 DISCOURSE | FALL 2017 / WINTER 2018

2 1. Romantic writers frequently invoked prophecy in their work, seemingly undeterred by its failure, time and again, to materialize. Why, then, did they persist? The answer at the heart of English professor Christopher Bundock’s book, Romantic Prophecy and the Resistance to Historicism (University of Toronto Press, 2016), is that creativity stemmed from the repeated failure of prophecy in Romantic thought. 2. Canada has a reputation for being one of the most queer-friendly nations on earth – a pioneer in legalizing same-sex marriage and home to enormously popular Pride parades. Yet Canada was not always so hospitable to its queer citizens. Homosexuality was only decriminalized in Canada in 1969 and remained socially stigmatized for many years. In Queers Were Here: Heroes & Icons of Queer Canada (Biblioasis, 2016), Robin Ganev, assistant professor in the Department of History, and RJ Gilmour, an independent scholar, have co-edited a collection of personal stories that illuminate the social changes that have transformed sexuality in Canada. 3. Stigmas, Work and Organizations (Palgrave Macmillan, 2018), co-edited by Gina Grandy, associate dean in the Faulty of Business Administration, brings together current research on stigma as applied to business and management. Covering wide-ranging topics like religion, obesity, sexual preference, and what the editors call “tainted work” – sex work, garbage collection and hospice work – Stigmas challenges readers to ask why and how, in our everyday working lives, we categorize by markers of difference, and how such “marking” has far-reaching negative implications for individuals, groups and organizations.

Shuana Niessenâ€™s Shattering the Silence is an online resource developed to facilitate teaching and learning about the history of Indian residential schools in Saskatchewan.

4&5. Canadian history has always been marked by cleavages and conflicts. While negotiations and compromises have arguably enabled Canada to develop into one of the most successful, pluralistic countries in the world, invariably some grievances are still left unresolved. Conflict and Compromise (University of Toronto Press, 2017), a two-volume history of Canada co-authored by history professor Raymond Blake, was written to help Canadian students make sense of their own past. 6. Shattering the Silence: The Hidden History of Indian Residential Schools in Saskatchewan (Faculty of Education, University of Regina, 2017), is an online resource by Shuana Niessen, communications officer and publications manager in the Faculty of Education. Developed to facilitate teaching and learning about the history of Indian residential schools in Saskatchewan, this free ebook graphically lays out Saskatchewan school-specific information extracted from the National Centre for Truth and Reconciliation reports, archived school files and photographs, as well as incorporating links to survivor stories, news clippings, scanned historical documents, and artistic and commemorative projects.

5 6

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Funding

1 1. Joan Wagner, associate professor in the Faculty of Nursing, in collaboration with the University of Saskatchewan, the Saskatchewan Union of Nurses and the Regina Qu’Appelle Health Region (RQHR), was awarded a Saskatchewan Health Research Foundation (SHRF) Collaborative Innovation Development Grant for a project focused on the use of a synergy tool in Regina’s two emergency departments. The synergy tool is used to assess patient priority needs, which are then used to more accurately determine the resources, including numbers and types of nurses, required to provide quality care. The synergy tool has never been used in a Canadian emergency department context, making this research the first of its kind in Canada to systematically and collaboratively explore best approaches to promote quality nursing care, while also reducing emergency department wait times. 2. Saskatchewan has especially high rates of deaths caused by impaired driving. Yet there is little research into how the families of individuals killed are impacted and supported throughout their experience – including their time in hospitals and their contact with the justice system. The Community Safety Knowledge Alliance (CSKA) has provided funding to Nick Jones, associate professor in the Department of Justice Studies, to look into the range of pressures placed on these families. Through interviews with family members, Jones and CSKA clinical 20 DISCOURSE | FALL 2017 / WINTER 2018

psychologist Jody Burnett are examining the available systems of support, from the beginning of the event onwards, and are working to identify any existing gaps to better understand what is working and what needs to change. 3. On September 8, 2017, the Honourable Ralph Goodale, speaking on behalf of the Minister of Science, Kristy Duncan, announced more than $2 million in Natural Sciences and Engineering Research Council (NSERC) funding for 16 University of Regina researchers. Goodale, the Minister of Public Safety and Emergency Preparedness, stated to the packed house, “It’s incredible to witness the promise of the next generation of Canada’s scientists, doctors, researchers and innovators. Our government is proud to be able to support the recipients recognized today. And the Government of Canada is proud to partner with the University of Regina.” At the event, award recipient Orland Hoeber from computer science discussed his primary research interest as being at the intersection of interactive information retrieval and information visualization, focusing on the design, development and study of novel search interfaces that support complex search tasks.

(l to r) Pierre Charest, NSERC vice-president, research grants and schloraships; Orland Hoeber; Honourable Ralph Goodale and David Malloy.

2 "The NSERC Discovery Program is critical to the pursuit of a longterm research agenda that seeks to develop an understanding of, and novel solutions to, important problems. It allows researchers to not only support graduate students in developing knowledge, skills and solutions to these problems, but also guide them in becoming the next generation of thinkers, problem solvers and researchers," said Hoeber. Discovery Grants recipients: Mark Brigham (Faculty of Science), Ecological and Physiological Convergence in Thermoregulation by Caprimulgid Birds and Vespertilionid Bats. Cory Butz (Faculty of Science), Optimizing Inference in Deep Learning Models. Allan East (Faculty of Science), Theoretical Studies of Ion Processes in the Liquid State. Kerri Finlay (Faculty of Science), Carbon-climate Interactions in Hard-water Lakes.

Allen Herman (Faculty of Science), Realization Problems in Representation Theory and Algebraic Combinatorics. Orland Hoeber (Faculty of Science), Studying Visual Analytics Support for Interactive Information Retrieval within Complex Search Settings. Yee-Chung Jin (Faculty of Engineering and Applied Science), Improvement of Mesh-free Particle Method for Free Surface Flow Simulation. Mehran Mehrandezh (Faculty of Engineering and Applied Science), Photometry and Radiometrybased Metrology for Design and Development of High-precision Fully-autonomous Robotic Inspection Systems. Chris Oriet (Faculty of Arts), The Role of Statistical Summary Representations in Visual Learning. Farshid Torabi (Faculty of Engineering and Applied Science), Utilization of Percolation Theory and Multiphysics’ Concept to

Minister Goodale meeting with researchers, including graduate students and postdoctoral fellows, in Mohan Babu’s proteomics and genomics facility

Develop Dynamic Modeling and Accurate Upscaling Approaches for Two-phase Flow during Immiscible Displacement of Heavy Oil in Porous Media. Andrei Volodin (Faculty of Science), Asymptotic Analysis for Point and Interval Estimation in Some Statistical Models. Peng Wu (Faculty of Engineering and Applied Science), Scour at Culvert Outlets under Ice Cover and Ice Jam Conditions. JingTao Yao (Faculty of Science), Multi-criteria Intelligent Decision-making Approaches and Applications. Yiyu Yao (Faculty of Science), Theory and Applications of Three-way Decisions in Intelligent Information Systems. Sandra Zilles (Faculty of Science), Models and Algorithms for Interactive Machine Learning Applied to Formal Languages and Geometric Concepts. Discovery Development Grants recipients: Renata Raina-Fulton (Faculty of Science), Agricultural Pesticides: Occurrence in the Atmosphere and Identification of Atmospheric Transport and Transformations.

4. Substantial federal funding for University health research was announced on October 11, 2017, by the Honourable Ralph Goodale, speaking on behalf of the Honourable Ginette Petitpas Taylor, Canada’s Minister of Health. Three research projects geared towards helping address the challenges facing Indigenous youth, people living with neurodegenerative disorders and people who receive mental health care, secured more than $3.7 million from the Canadian Institutes of Health Research (CIHR). "The work of health researchers across Canada elevates the standard of science and health care delivery from coast to coast to coast,” said Petitpas Taylor. “By supporting these three teams of innovative researchers in Regina, the Government of Canada will help address the health challenges facing Indigenous youth, as well as people living with Parkinson’s disease and mental health injuries. We will deliver on our commitment to research today, so that our scientists will achieve health care breakthroughs tomorrow." As part of the announcement, Goodale spent time touring award recipient Mohan Babu's research facility at the University.

"Saskatchewan is home to some of Canada's leading health researchers. This project is an example of the leading-edge research being done in the province. It also highlights the strong support for research and innovation at the University of Regina,” said Goodale. Mohan Babu, associate professor in the Faculty of Science, will use his more than $1.9 million grant to shed light on the genes linked to Parkinson’s disease. “Mitochondrial dysfunction contributes to neurodegenerative disorders, such as Parkinson’s disease, for which no effective longterm cure currently exists,” says Babu. “This CIHR funding will help to facilitate the discovery of potential new therapeutic targets for patients suffering with debilitating disorders, and inspire further research into novel treatments for sustainable health care.” Heather Hadjistavropoulos, psychology professor and director of the Online Therapy Unit, will use internet-delivered cognitive behavioural therapy (ICBT) to make accessing mental health care easier for all Canadians. "I am delighted to have secured this CIHR award. These funds will allow our team to advance

4 how ICBT is offered by therapists in diverse mental health care settings to ensure we are meeting the mental health care needs of Canadians who have difficulties accessing care for various reasons, such as rural and remote location, time, mobility, costs, lack of providers or concerns about stigma,” says Hadjistavropoulos, whose work is supported by a grant of more than $971,000. Tarun Katapally, assistant professor at the University’s Johnson Shoyama Graduate School of Public Policy, will use his more than $772,000 grant to study how to adopt culturally appropriate ways to integrate physical activity into the daily lives of Indigenous youth to foster better physical, mental and emotional health. “This investment will allow me and my team to embark on a five-year research project to implement a land-based, culturally appropriate, active living intervention to help improve mental health among Indigenous youth,” says Katapally. “The CIHR award will also help to extend this project to schools in different communities across Saskatchewan, ultimately informing school physical activity policies and programs throughout the province.” DISCOURSE | FALL 2017 / WINTER 2018

Collaborate

“The support I receive, as well as the opportunities I’ve had to participate in interdisciplinary international climate change projects with Harry Diaz and David Sauchyn from the University, allowed me to gain the experience and skills to make this international contribution to solving the problem of climate change.”

MAKING A MARK ON CLIMATE CHANGE Margot Hurlbert is part of an international team of writers and editors crafting a document on climate change. Hurlbert, a professor at the Centre for the Study of Science and Innovation Policy at the Johnson Shoyama Graduate School of Public Policy, was appointed to the prestigious position of Coordinating Lead Author by the Intergovernmental Panel on Climate Change (IPCC) for its Special Report on Land and Climate. Established in 1988, the IPCC provides periodic scientific assessments regarding climate change to governments at all levels and informs the UN Climate Conference – the United Nations Framework Convention on Climate Change (UNFCCC). Across the globe, only 104 people have been selected as Coordinating Lead Authors and Lead Authors from the 640 names proposed by governments. As a scientist with a background in climate change and the energy sector, her contribution to the Special 22 DISCOURSE | FALL 2017 / WINTER 2018

Report is a chapter centred on risk, decision making and sustainable development. Hurlbert’s previous work on climate adaptation, agricultural producers and drought will also prove helpful, particularly in relation to the issues of greenhouse gas emissions, desertification, land degradation, food security and the integrated responses to these issues. Over the next two years, Hurlbert will work with an author from a developing country in leading a team of 11 Lead Authors and future contributing authors to produce this content on the basis of the best scientific information available. Hurlbert credits working at the University of Regina as key to this appointment. “The support I receive, as well as the opportunities I’ve had to participate in interdisciplinary international climate change projects with Harry Diaz and David Sauchyn from the University, allowed me to gain the experience and skills to make this international contribution to solving the problem of climate change.”

"The importance of our study is that we were able to place global warming, and recent weather observations, in the context of the past 2,000 years,” explains David Sauchyn. TRACKING TEMPERATURE CHANGES THROUGH TREE RINGS A group of international scientists has new evidence that the Earth is warming at an unprecedented rate. The new data were compiled from 648 sites across the planet and provides the most complete look at climate change over the past 2,000 years.

Left: Okimaw Wally Burns shows oil debris collected on James Smith CreeNation territory, in a still from the student documentary Crude Power.

In all, 98 scientists from around the world are taking part in the research project – including geography professor David Sauchyn.

Photo Credit: School of Journalism

“The data clearly show a long-term cooling trend until the 19th century, which is then followed by a sharp warming. This recent rapid warming is consistent with the large body of scientific evidence of anthropogenic global warming. The importance of our study is that we were able to place global warming, and recent weather observations, in the context of the past 2,000 years,” explains Sauchyn. This summer the international team published their findings in the journal Nature Scientific Data. Sauchyn’s tree-ring data used in the journal article were gathered from two locations in the Rocky Mountains. “The width of tree rings is directly related to growing season temperatures,” Sauchyn says. “Trees often grow more in warmer years than in cooler ones, which creates rings of different widths depending on the weather they encounter.” He’s been collecting tree samples for years as part of his research into climate change. “In our Tree-Ring Lab at the University we have more than 6,000 samples of old wood. It has taken my grad students and me about 25 years to collect this wood and extract information about the annual climate of the past millennium. But this effort has paid off since we are able to reconstruct the past climate of the Canadian prairies and contribute to global studies of climate change,” he says.

CRUDE POWER The University of Regina’s School of Journalism recently participated in the largest journalism collaboration in Canadian history. Our J-School was part of a year-long national investigation into the Saskatchewan oil industry that brought together media outlets and journalism schools from across the country – including the Toronto Star, the National Observer, Global News, Concordia University, Ryerson University and the University of British Columbia. Coverage of the first articles in an ongoing series titled The Price of Oil has been extensive and is ongoing. One element of the project is a hard-hitting documentary called Crude Power: An Investigation into Oil, Money and Influence in Saskatchewan, produced by University of Regina journalism student Janelle Blakley, along with field producers Madina Azizi, Katie Doke Sawatzky, Brenna Engel and Celine Grimard, with help from journalism faculty members Patricia Elliott and Trevor Grant. This investigative current affairs program shines a light on the oil industry's substantial influence on government policy and reveals who benefits and who is hurt. Filmed in communities across the province, Crude Power exposes the tight connection between government and the oil industry and investigates the substantial impact of this connection on the citizens of the province. The documentary aired on campus on October 4, 2017. This investigation was undertaken with assistance from the Michener Awards Foundation and the Corporate Mapping Project (CMP). The CMP is studying the power of the fossil fuel industry in Western Canada, and is jointly led by the University of Victoria, the Canadian Centre for Policy Alternatives and the Parkland Institute. This research is supported by the Social Science and Humanities Research Council (SSHRC).

Bottom left: David Sauchyn

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IN RESEARCH REVENUE GROWTH I N T H E C O M P R E H E N S I V E C AT E G O R Y

The University of Regina is #1 in research revenue growth (up 12.6 %) and is one of Canadaâ€™s top 50 research universities among the nationâ€™s comprehensive universities for FY 2016. (Research Infosource)

Not bad for the little university on the prairie, huh?

CONTACT US Discourse 210 PaskwaË‰w Tower University of Regina 3737 Wascana Parkway Regina, SK S4S 0A2 Ph: 306-585-4024 discourse.magazine@uregina.ca