Quest 15.3 by questonlineza

VOLUME 15 | NUMBER 3 | 2019 ISSN 1729-830X

Machine learning for astronomy

Standing up for clean air ACADEMY OF SCIENCE OF SOUTH AFRICA

Mathâ&#x20AC;&#x201C;Art steams ahead

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CONTENTS Volume 15 | Number 3 | 2019

THEME

FEATURES

Machine learning

Benjamin Rosman gives us an introductory overview

The rise of the machines in our quest to understand the universe Michelle Lochner explains how machine learning is used in astronomy and cosmology

Quantum machine learning

Betony Adams, Francesco Petruccione and Maria Schuld explain what it is and how it can help us

Machine learning for biomedical engineering A Stellenbosch University research group shares its machine learning experience

Seeing spots and counting chirps Ian Durbach tells us how machine learning can be used in ecological surveys

#LINO19

Katekani Shingange and Francis Otieno tell us about their Lindau Nobel Laureate Meeting experience

Building new forms of matter, brick by LEGO® brick Ben Skuse reports on the #LINO19 lecture by Wolfgang Ketterle

Fifth centenary of world’s fi rst circumnavigation Helen Swingler reports on an exhibition to mark the quincentenary

Scientific repercussions of the fi rst circumnavigation Álvaro de la Cruz-Dombriz shows how discoveries made 500 years ago remain relevant today

Shark!

Standing up for clean air Danielle Millar and Caradee Wright highlight the need for action on air pollution

Machine learning for beach safety

NEWS

REGULARS

ASSAf reaches out for National Science Week

Books

Wood-munching fungus has genome decoded

Puzzles

Subscription

Body of work on Basotho medicinal plants

My science fair journey

Math-Art steams ahead

Nectar-lapping lizards pollinate hidden flowers

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FEATURE | DETERMINED Editor Sue Matthews

Editorial Board

Himla Soodyall (EO: ASSAf) (Chair) John Butler-Adam (South African Journal of Science) Debra Meyer (University of Johannesburg) Kevin Govender (SAAO) Caradee Wright (MRC)

Correspondence and enquiries

The Editor e-mail: Quest-Editor@assaf.org.za e-copies: https://questonline.org.za/publications/ @questSa1 - Twitter Quest: Science for South Africa - Facebook

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EDITOR’S NOTE

Machine learning for everyone It’s how YouTube is able to suggest videos for you, based on others you’ve watched or liked, and why you’re shown particular adverts online, after googling for similar products. It’s why you get a call from the bank if an unusual transaction on your account indicates you might have been the victim of fraud, and how certain email gets flagged as spam. It’s why Google Maps and Waze can recommend driving routes and provide estimated travel times at diﬀerent times of day, and how Google Assistant and Siri can interpret what you’re saying. Machine learning is part of our everyday lives, and is increasingly being used in new and innovative ways as various industries recognise its potential. It has already been widely adopted by sports analytics companies, for example, to predict outcomes of each game and overall match winners for betting organisations, and to help team managers recruit promising players or tweak game strategy based on past performance. SciSports’ BallJames system even allows real-time analysis of soccer games, because every movement on the pitch is captured from three or four angles by 14 video cameras around the stadium and automatically processed into 3D data. In recognition of the advances made in this field, the January 2019 issue of the Springer US journal Machine Learning was devoted entirely to machine learning in soccer. More recently, the prestigious New England Journal of Medicine published an article on 4 April by scientists at Harvard Medical School and Google, oﬀering a blueprint for integrating machine learning into the practice of medicine. In an accompanying press release, lead author Dr Isaac Kohane noted that machine learning models can be trained on tens of millions of

Every care is taken in compiling the contents of this publication, but we assume no responsibility for effects arising therefrom. The views expressed in this magazine are not necessarily those of the publisher. Content may be copied or shared with acknowledgement to Quest as well as the author where stated. Copyright of republished material and images remains with the original source.

Quest Vol. 15 No. 3 | 2019

electronic medical records, while a human physician would not see more than a few tens of thousands of patients in an entire career. He stressed, however, that the models would only be as good as the data inputted, and that physicians need to understand the models’ limitations and not rely on them at the expense of their own vigilance in diagnosing disease and recommending treatment protocols. Google is doing much to advance the uptake of machine learning, oﬀering free courses online and making its software library TensorFlow available as an opensource platform to build and deploy machine learning models. The TensorFlow website features a number of excellent videos showing how the platform has been used, from transcribing and interpreting medieval manuscripts in the Vatican archives, to predicting extreme weather events globally and identifying diseases of cassava crops in Tanzania. Google has also opened a research centre for artificial intelligence in Ghana to take on Africa-specific challenges, such as those in healthcare, education and agriculture, and supports the African Master’s in Machine Intelligence, a fully funded graduate programme at Rwanda’s branch of the African Institute of Mathematical Sciences (AIMS). In this issue, we highlight some machine learning applications from the South African science and engineering community.

Quest now has its own website! Visit https://questonline.org.za/ or scan the QR code for current and previous issues of Quest, as well as additional resources. QUESTONLINE.ORG.ZA

NATIONAL SCIENCE WEEK | ASSAF NEWS

ASSAf reaches out for

National Science Week The Academy of Science of South Africa (ASSAf) pulled out all the stops for this year’s National Science Week, celebrated from 29 July to 3 August 2019. It received a grant from the South African Agency for Science and Technology Advancement (SAASTA) to implement a programme in three provinces – the Eastern Cape, the Northern Cape and the North West. Although the main theme for 2019 was ‘Facing the harsh realities of climate change’, grant-holders were asked to incorporate material and activities addressing the United Nations International Year of the Periodic Table and International Year of Indigenous Languages too. Two lectures on climate change, aimed at students and academics, were presented at Sol Plaatjie University in the Northern Cape and the North-West University’s Mafikeng Campus. But the main focus was on the Eastern Cape component of the programme, which took place in Humansdorp and Jeffreys Bay. From Monday to Friday the ASSAf team presented a full morning programme at five different schools. This included a lecture on climate change relevant to the science curriculum, a webinar with the South African Weather Service (SAWS) on the country’s weather and climate, an information session on career development, a virtual engagement using technology with learners across the globe, and the launch of the Quest website. During the virtual engagement, learners in South Africa exchanged ideas with other learners and young environmental activists in several parts of the world on issues such as signs of climate change they’d seen in their area, what they were doing to combat climate change and create awareness around it, how they could get involved in supporting international initiatives around climate change, and measures they could implement in their schools to off set the effects of climate change. Information contributed by Tsepo Majake, ASSAf Education Liaison Officer

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Quest Vol. 15 No. 3 | 2019

What

N a ti o n al Science Week? The National Science Week is an annual countrywide celebration of science. It is an initiative of the Department of Science and Innovation and implemented by the South African Agency for Science and Technology Advancement. Learners, educators, journalists, decision-makers, industry leaders and other members of society get involved in the celebrations and are able to engage directly with scientists, research organisations and local innovations in science and technology. &RQGXFWHG XQGHU D GHVLJQDWHG VFLHQWLÂż F WKHPH and sub-themes, this massive initiative uses a variety of exciting and stimulating activities to popularise science. It also serves as a vehicle for showcasing local innovations, researcher programmes and technology development initiatives.

Facing up to climate change The theme for National Science Week 2019 was â&#x20AC;&#x153;Facing the harsh realities of climate changeâ&#x20AC;?. South Africa, like many other parts of the world, is experiencing severe weather, which the South AfULFDQ :HDWKHU 6HUYLFH GHÂż QHV DV DQ H[WUHPH PH teorological event or phenomenon that represents a real hazard to human life and property and has the potential to cause damage, serious social disUXSWLRQ RU ORVV RI KXPDQ OLIH 7KH VFLHQWLÂż F FRP munity has since warned that climate change is OLNHO\ WR LQĂ&#x20AC; XHQFH PRUH H[WUHPH ZHDWKHU SDWWHUQV in the country in the coming years.

The National Science Week theme aimed to raise public awareness of what scientists are predicting about the future of climate changes and, more importantly, what we can do to help reduce the negative impacts of climate change.

Who are we? The South Africa Agency for Science and Technology Advancement is a business unit of the National Research Foundation with the mandate to advance public awareness, appreciation and engagement of science, engineering, innovation and technology in South Africa. Science, through research, has a crucial role to play in the growth of South Africaâ&#x20AC;&#x2122;s economy. Active dialogue and engagement between VFLHQFH DQG VRFLHW\ HQVXUHV WKDW VFLHQWLÂż F UHVHDUFK Âż QGLQJV DUH HDVLO\ WUDQVODWHG LQWR UHOHYDQW DSSURSUL DWH DQG EHQHÂż FLDO LQQRYDWLRQ DQG HQWUHSUHQHXULDO RSSRUWXQLWLHV 5HVHDUFK Âż QGLQJV VKRXOG DOVR KDYH DQ impact on policy and social conditions in a country. For more details, please visit our website www.saasta.ac.za or connect with us on Facebook: NRFSAASTA Twitter: @NRF_SAASTA

Is climate change bad for your health? - Sabeehah Vawda Sabeehah is a medical doctor who has specialised in medical virology. She was a participant of SAASTAâ&#x20AC;&#x2122;s Young Science Communicators Competition, which is one of various programmes at SAASTA aiming to nurture science communication skills in young scientists. To facilitate engagement during National Science Week 2019, we asked these young scientists to write an article or create any form of communication piece on a topic of their choice that relates to the theme.

â&#x20AC;&#x153;Sjoe! This has got to be the hottest summer I have ever experienced, and mind you, I have been living here since I was born. Iâ&#x20AC;&#x2122;m telling you - this climate change is bad.â&#x20AC;? We all have conversations about the weather, primarily because a discussion on the weather is the perfect conversation starter and what better ZD\ LV WKHUH WR Âż OO XS WKDW DZNZDUG conversation gap, right? As mundane as the weather may seem, everyone experiences it on a daily basis, and so a weather discussion can result in quite lively exchanges. Nowadays, the term climate change is sure to pop up in casual weather conversation, almost proportionally to the level of discomfort experienced, and is generally used as the concluding point. One that no one can argue with. The JUDQG Âż QDOH WR WKH ZHDWKHU GLVFXV sion. The ultimate explanation for subjective weather ratings. In reality, while the term climate change has become quite popular in casual conversations, the print media and social media, very few individuals actually understand the tremendous, multidimensional impact of climate change.

Climate c h a n g e is about more than the weather. For example, has it ever occurred to you that climate change may have a huge impact on oneâ&#x20AC;&#x2122;s health? Possibly not; you may have had to think a bit about that one. So how does climate change affect your health? Extremes of temperatures are obviously not good, and with climate change causing an increase in the average global temperatures, itâ&#x20AC;&#x2122;s GHÂż QLWHO\ JRLQJ WR EHFRPH PXFK warmer. Prolonged exposure to hot conditions can result in many heat-related illnesses ranging from sunburn to heat exhaustion,heat cramps, and the more sinister, sun stroke. While these may occur to literally anyone, the very young, the very old, individuals with underlying medical conditions, those with weakened immune systems, and those lacking proper clothing and/or housing, are particularly at risk. Higher temperatures also result in an increase in air pollutants and pollen, which could trigger asthma and worsen other cardiovascular and respiratory diseases. Believe it or not, but temperature extremes can have effects on your mental health

too, which in turn, may impact on your work and relationships. It already sounds pretty dreary right? Unfortunately, thereâ&#x20AC;&#x2122;s more. There are many indirect health effects of climate change as well. Weather-related natural disasters are on the rise. An increase in droughts will lead to instability in food production, hence hunger and famine. Increase in Ă&#x20AC; RRGV ZLOO OHDG WR ORFDO GHYDVWDWLRQ DQG disruption, with injuries and death, and affected individuals will be exposed to unclean water sources. This will lead to an escalation in infectious water-borne diseases. The recent cholera outbreak in Mozambique, following Cyclone Idai, is just one, close-tohome example. Insect and snail populations are also sensitive to climate change. Increasing temperatures would mean a wider distribution of these vector-borne diseases and possibly an escalation in the number of people infected. 6R \HV FOLPDWH FKDQJH ZLOO GHÂż QLWHO\ LP pact on health. According to the World Health Organisation, climate change will result in approximately 250 000 additional deaths per year, between 2030 and 2050. These would be as a result of heat stress, malaria, diarrhoea, and malnutrition. So the next time you are having one of those infamous weather conversations, donâ&#x20AC;&#x2122;t forget about all the serious health effects of climate change. Try to steer the conversation to ways that we as individuals can impact climate change â&#x20AC;&#x201C; waste less food, switch to a more plant-rich diet, make our homes PRUH HQHUJ\ HIÂż FLHQW DQG FRPPXWLQJ RQ public transport or carpooling, are just some examples. The collective effort RI VHHPLQJO\ LQVLJQLÂż FDQW FKDQJHV FDQ make an impact. Letâ&#x20AC;&#x2122;s do our part to hinder the stride towards climate change.

THEME | MACHINE LEARNING

Benjamin Rosman gives us an introductory overview It is diﬃcult to imagine what the modern world would look like without computers. We have come to rely on them for everything, from handling our financial transactions to maintaining our social lives.

Unfortunately, there are many problems that are just too hard to solve in this way. Think of the challenge of detecting if there is a face in an image. To do this, a programmer would describe an algorithm – or set of instructions – to identify two eyes, placed above a nose, which in turn is above a mouth. But how should the computer recognise these eyes, noses and mouths? And what happens if the face is seen from the side so only one eye is visible, or the image is upside down? And how do we make sure this works for anyone, of any age or race, even if they have hats, glasses or beards?

Machine learning is an area of artificial intelligence that focuses on learning patterns from data, rather than being programmed by humans. The insight of machine learning is that even though solutions to problems like these are very diﬃcult for a human to specify, it is easy to collect examples of images that do and don’t contain faces. If this can be done, a computer should be able to write the program or algorithm itself using these examples. It does this by trying to learn the rules that would distinguish the examples of ‘faces’ that it has been given from the examples of ‘not faces’, using the underlying data such as the pixels in the images. This is a specific case of machine learning, known as supervised learning, because the algorithm is supervised by a human, training it with a set of examples with faces 8

Quest Vol. 15 No. 3 | 2019

Nicolas Buenaventura, CC BY-SA 3.0

Having computers assist in all these tasks requires a way of giving them instructions. For this we traditionally use programming, where programs are written as sequences of steps that should be followed by a computer to perform some function. The programmer here has to think carefully about any situation that the computer may find itself in, and explain to it how that problem should be dealt with.

Machine learning is used in biometric facial recognition software, which analyses nodal points on the face.

(the positive examples) and a set of examples without faces (the negative examples). Technically, the algorithm tries to optimise, or find the best set of mathematical rules, to be able to divide the positive and negative examples as well as the human did. This same basic methodology can be used anywhere that a human can provide samples of what the machine is required to learn. This approach has been used for everything from handwriting recognition, to detecting fraudulent bank transactions, performing medical diagnoses from x-rays, and recognising and translating speech. Ukufunda kwemishini kusewolunye uphiko lwe artificial intelligence olumayelana nokuthi imishini izifundele yona ngokwayo iphethini yedatha ngaphandle kokuthi kungenelele noma kuhlelwe ngabantu.

Translation by Zamantimande Kunene

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MACHINE LEARNING | THEME Machine learning is at the core of artificial intelligence: the science of building intelligent machines. This sits at the intersection of computer science, mathematics and statistics, but also draws on many other fields, such as psychology and neuroscience. Many of the exciting new ideas in machine learning come from knowledge of how the brain works, or how young babies and children learn about their environments. Another area of machine learning that has seen considerable advances in recent years is reinforcement learning. This involves having a computer learn to make sequences of decisions towards some desired goal. For example, a chess-playing algorithm would need to learn to take a whole sequence of actions to win a game, where each move it makes may not by itself be good or bad, but sets the game up for a later win. This kind of algorithm has recently been used to learn to beat expert human players in games as diverse as the board game Go and the computer game StarCraft II. These techniques are also used for robots to learn new skills and for autonomous cars to learn to drive.

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Artificial intelligence: The creation of computers and computer software capable of intelligent behaviour.

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Machine learning: The subfield of artificial intelligence involving the scientific study of computational and statistical models and algorithms that can learn from and make predictions on data. Machine learning is often divided into the three areas of supervised, unsupervised and reinforcement learning.

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Deep learning: A family of machine learning methods based on artificial neural networks, a class of model very loosely inspired by information processing in the brain.

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Supervised learning: A type of machine learning task that involves training on a set of known inputs (data) and outputs (targets) in order to make predictions from new inputs.

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Unsupervised learning: An area of machine learning concerned with finding structure and patterns in data, where no targets are specified.

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Reinforcement learning: The area of machine learning that studies how an agent, or decision maker, can choose a sequence of actions in some environment so as to maximise a long-term payoﬀ.

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Google’s DeepMind artificial intelligence (AI) program, called AphaStar, used machine learning to beat some of the world’s top Starcraft II players in January.

Cburnett, CC BY-SA 3.0

With the current frenzy of research in this area, machine learning is touching every sphere of society, from medicine to education, with significant implications for ethics and society. Global advancements here will aﬀect everything from the law to our relationship with work. It is likely that, in the coming years, every profession will have artificial intelligence and machine learning playing a greater role in how it operates, and every person will be influenced by it to a much greater extent, in virtually every aspect of life.

Artificial neural networks are inspired by the neural network of the brain, where nerve calls called neurons transmit information for processing. Dr Benjamin Rosman is a principal researcher in the Mobile Intelligent Autonomous Systems group at the CSIR, and is also a senior lecturer in the School of Computer Science and Applied Mathematics at the University of the Witwatersrand, where he leads the Robotics, Autonomous Intelligence and Learning (RAIL) laboratory. Quest Vol. 15 No. 3 | 2019

THEME | ASTRONOMY

The rise of the machines NASA/ESA/CXC/SSC/STScI

in our quest to understand the universe Michelle Lochner explains how machine learning is used in astronomy and cosmology In 1967 Jocelyn Bell, a young PhD student at the University of Cambridge, discovered something no one had ever seen before. She had been tasked with building a radio telescope, an instrument designed to pick up radio waves (as opposed to visible light) to study the universe. While looking at the data from her telescope, which in those days was in the form of long sheets of paper with lines on them, she observed something that looked like a pulse repeating with astonishing regularity from a distant corner of our galaxy. It was initially dismissed as noise, but Jocelyn persisted that she had discovered a true cosmic anomaly. Eventually, it was realised she had made one of the most important discoveries of the 20 th century. Jocelyn had discovered pulsars, incredibly dense stars that emit radio waves as they rapidly rotate. Pulsars are now some of the most well-studied objects in astronomy. The important thing to note is that it required a human being to look at the data to spot something weird. Fast forward 52 years into the future: over 10 000 km away from Cambridge – in our backyard in the Karoo – another radio telescope is being built. With half a century of technological advancement, this telescope, the Square Kilometre Array (SKA), is significantly bigger and more powerful than Jocelyn’s telescope. In fact, when finished the SKA will be the biggest telescope (of any kind) in the world. The SKA is an array, meaning it will consist of hundreds of telescopes working together to make radio images of the sky. The SKA will be split in two, with one component being built in South Africa and the other in Australia. Currently, there is a precursor for the SKA in the Karoo, called MeerKAT. It is made up of 64 individual antennas, 10

Quest Vol. 15 No. 3 | 2019

and is already one of the world’s most sensitive telescopes.. MeerKAT was proudly designed and built by South Africans, and is already in high demand in the scientific community. As well as being much bigger and more sensitive than Jocelyn’s telescope of 1967, the SKA will also produce dramatically more data – as much as 100 PB (petabytes; 1 PB = 1 million GB) a day even in its first phase of construction. If you could convert all that data into a song and listen to the universe singing to you, it would take approximately two million years to play back the data collected in a single day. The universe is a busy and complicated place! Across the ocean in Chile, another marvellous telescope is under construction, called the Large Synoptic Survey Telescope (LSST). This big project is led by the United States, but several South African researchers are also involved. Unlike MeerKAT, LSST looks more like a traditional telescope that sees the universe in visible light. It is made up of huge mirrors as well as what will be the world’s largest CCD camera (charge-coupled device, the type of sensor found in most digital cameras). LSST has clever optics that will allow it to observe almost the entire southern sky every three nights. What this means is that over its 10-year survey LSST will be able to make a movie of the universe. QUESTONLINE.ORG.ZA

ASTRONOMY | THEME When you look up at the sky at night, I’m sure you’ll agree that it doesn’t look like it changes much. Apart from the constellations appearing to move on their steady path throughout the night and the year, not much seems to happen in the sky. But if your eyes were bigger, like a telescope’s eye, you’d be able to see fainter things – and then you’d realise that the universe is changing all the time. Often the changing sky is associated with dramatic or explosive events. When a big star runs out of fuel, it blows up in a massive explosion called a supernova. Now the death of a star may be a rare event, but if you observe the whole sky you end up catching a lot of supernovae! There are other dramatic events like supermassive black holes devouring nearby stars, or when pairs of the same incredibly dense stars that form pulsars merge in an explosive fashion. LSST will find everything that changes in the sky, from nearby rocks hurtling through space to distant exploding stars.

Enter machine learning

Machine learning has revolutionised the modern world, and astronomy is no diﬀerent. Not only can it automate tedious tasks once left to the astronomer, like detecting artefacts in images (think satellite trails and cosmic rays), but it can also be used to automate discovery and seek out unknown unknowns – things we don’t know we don’t know, being so unexpected that we would not consider or predict them. With the imminent arrival of these two telescopes, the SKA and the LSST, astronomy is undergoing the same revolution as every other field. We are rapidly finding we have more data than we know how to handle! We have no choice but to automate many of the tasks that would

traditionally be done by astronomers. Machine learning is becoming a key tool in smart automation. Here’s an example of the data deluge that we’ll need machine learning to handle: LSST will detect 10 million transient events every night. That means 10 million things will have changed from the previous night. As much as half of these won’t be real events, they will be things like problems with the CCD or aeroplanes flying past. But that still leaves millions of events that are real astrophysical sources. Most of these will be classes of objects we’ve seen before, like exploding stars (supernovae) or supermassive black holes swallowing stars (active galactic nuclei). How do we automatically classify these objects so that astronomers can just study the types of objects they’re interested in? Or the bigger question, what if one of those 10 million transients is something we’ve never seen before, like pulsars in 1967? How do we find them when there just isn’t enough time in the world to look through all the data with human eyes? Our Data Science group, which is a mix of collaborative groups at the African Institute for Mathematical Sciences (AIMS) and the South African Radio Astronomy Observatory (SARAO), led by Professor Bruce Bassett, is engaged in a number of projects to make use of machine learning for astronomy. We have teams working on classifying types of transients for LSST, MeerKAT and other telescopes. We have a large team focusing on automatically detecting radio frequency interference in data, which can be caused by satellites, aeroplanes and electronic devices near the MeerKAT telescope site. And Prof. Bassett and I lead a team focusing on anomaly detection in astronomy, one of the most exciting areas of machine learning.

SARAO

MeerKAT, near Carnarvon in the Northern Cape, consists of 64 radio antennas.

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Quest Vol. 15 No. 3 | 2019

SARAO

THEME | ASTRONOMY

Cutouts from a MeerKAT radio image showing (top row) point sources, representing radio galaxies too distant for MeerKAT to resolve, and (bottom row) anomalies, representing rare objects that might turn out to be new discoveries.

Anomaly detection

Anomaly detection is all about finding a needle in a haystack: finding that one rare or even never-before-seen object in a dataset of thousands of ordinary things. Let’s illustrate anomalies with a real example. Above are some cutouts from a MeerKAT radio image. MeerKAT stared at a relatively empty patch of sky to make a large radio image that I chopped up into thousands of smaller cutouts (each cutout is a piece of sky 0.04 degrees across, which is around 10 times smaller than the moon). The sensitivity is turned up so that empty sky shows up as orange

patchy noise, much like the white noise of a detuned television. If we examine these cutouts, we find that most of them look like the ones in the top row: pretty boring, noisy images. We also see some cutouts with point sources – radio galaxies too distant for MeerKAT to resolve them clearly, so they just look like blobs. While lots of important science can be done with point sources, they’re not anomalies. What we want to find automatically are things like those in the bottom row. The problem with images is that they are actually very complicated for computers to understand. While even a three-year-old can tell the diﬀerence between an elephant and a mouse, it’s taken decades of research and a revolution in machine learning to get a computer to be able to do the same thing. So we have to extract features from the images to be able to reduce them down to a simple set of numbers a computer can understand.

Michelle Lochner

For this problem, we made use of an advanced school of machine learning called deep learning. Deep learning tries to emulate the way the human brain works by building a network of ‘neurons’ – a neural network – to map inputs (such as images) to outputs (such as the animal’s name). We used a type of neural network called an autoencoder, which finds a small set of numbers that represents the image. We can then take a look at these numbers on a plot. We used a second stage of machine learning to do the actual anomaly detection. The algorithm we used works by trying to isolate points that are diﬀerent from the others.

The machine learning algorithm for anomaly detection isolates points that are diﬀerent from others. Each dot is a representation of one of the cutout images above; the brighter the dot, the more anomalous the image.

Quest Vol. 15 No. 3 | 2019

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SARAO

ASTRONOMY | THEME

One scientist may be curious about how this anomalous artefact was produced...

But another will be more interested in astronomical objects like these.

Each dot in the bottom left image is actually a representation of one of the cutouts seen earlier. The brighter the dot, the more anomalous the machine learning algorithm thinks the image is. In this way, we can turn quite a complicated thing (an image) into a simple set of numbers that a computer can understand. The entire set of 2 500 cutouts, which would take a human hours to go through looking for interesting objects, is processed in under two minutes on a normal desktop. Finally, there is still a subtle distinction between what is anomalous and what is interesting. For instance, someone responsible for producing the left image above might be interested in this source. It looks a little strange because of the dark spot on its side and could be an artefact. However, a scientist looking for active galaxies would not be interested. So we build a final layer to turn our anomaly detection algorithm into an astronomical recommendation engine – an algorithm capable of learning users’ interests and showing them more sources that it thinks they will be interested in. This application of machine learning could be a massive time saver in astronomy. Indeed, it will be the only way to explore datasets that are too large to sift through manually. We hope our framework will be an entirely new way of working with data, and perhaps allow us to make the next big discovery, just like Jocelyn Bell did more than 50 years ago. Some people are (quite understandably) afraid of machine learning and how it is impacting our society. Like any technological advancement, it can be used to help or harm. But by combining next-generation telescopes with machine learning tools, astronomers are finding new ways to unlock the mysteries of the universe.

Dr Michelle Lochner is a researcher in a position shared between the African Institute for Mathematical Sciences and South African Radio Astronomy Observatory. She did her undergraduate degree in Physics and Electronics at Rhodes University, before moving on to postgraduate studies at the University of Cape Town, where she obtained her PhD in Mathematics and Applied Mathematics.

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Jocelyn Bell, now Dame Jocelyn Bell Burnell, was awarded the US$3 million Special Breakthrough Prize in Fundamental Physics in November 2018 in recognition of her ‘fundamental contributions to the discovery of pulsars, and a lifetime of inspiring leadership in the scientific community’. The award comes five decades after her discovery of pulsars, for which her PhD supervisor Antony Hewish and his collaborator Sir Martin Ryle were awarded the 1974 Nobel Prize in Physics. She has remained deeply engaged in astronomy, teaching at multiple research institutes and taking on leadership roles such as project manager of the James Clerk Maxwell Telescope in Hawaii. She has been President of the Royal Astronomical Society, the Institute of Physics and the Royal Society of Edinburgh, and is currently a Visiting Professor of Astrophysics at the University of Oxford and Chancellor of the University of Dundee. She received a CBE in 1999 and a DBE in 2007 for her services to astronomy. Bell Burnell announced that she would donate the prize money to establish research studentships or scholarships for people from under-represented groups in physics. This is in keeping with her instrumental role in the creation of the Athena SWAN (Scientific Women’s Academic Network) Charter and awards, established in 2005 to advance the careers of women in science, technology, engineering, maths and medicine. Bell Burnell is the fourth recipient of the prize, which was previously awarded to Stephen Hawking, seven CERN scientists whose leadership led to the discovery of the Higgs boson, and the entire LIGO collaboration that detected gravitational waves. For an entertaining account of Bell Burnell’s life, see: https://physicsworld.com/a/look-happy-dear-youve-just-madea-discovery/

Quest Vol. 15 No. 3 | 2019

THEME | QUANTUM TECHNOLOGY

EXPLAINER:

what is quantum machine learning and how can it help us? By Betony Adams, Francesco Petruccione and Maria Schuld

Artificial intelligence refers, among other things, to machines’ capacity to demonstrate some degree of what humans consider ‘intelligence’. This process is being driven by the rapid advancement of machine learning: getting machines to think for themselves rather than preprogramming them with an absolute concept. Take image recognition. Humans excel at this task, but it’s proved difficult to simulate artificially. Training a machine to recognise a cat doesn’t mean inputting a set definition of what a cat looks like. Instead, many different images of cats are inputted; the aim is that the computer learns to distil the underlying ‘cat-like’ pattern of pixels. This dependence on data is a powerful training tool. But it comes with potential pitfalls. If machines are trained to find and exploit patterns in data, in certain instances they only perpetuate the race, gender or class prejudices specific to current human intelligence. But the data-processing facility inherent to machine learning also has the potential to generate applications that can improve human lives. ‘Intelligent’ machines could help scientists to more efficiently detect cancer or better understand mental health. Most of the progress in machine learning so far has been classical: the techniques that machines use to learn follow the laws of classical physics. The data they learn from has a classical form. The machines on which the algorithms run are also classical. We work in the emerging field of quantum machine learning, which is exploring whether the branch of physics called quantum mechanics might improve machine learning. Quantum mechanics is different to classical physics on a fundamental level: it deals in

probabilities and makes a principle out of uncertainty. Quantum mechanics also expands physics to include interesting phenomena that cannot be explained using classical intuition.

From classical to quantum

Quantum mechanics is a branch of physics that attempts to understand and apply mathematical, verifiable rules to the behaviour of nature at the smallest end of the spectrum – on the scale of atoms, electrons and photons. It was first developed at the beginning of the 20 th century, and has been very successful in describing systems on the microscopic level. The fundamental divide between the quantum and classical worlds has been popularised by the Schrödinger’s cat thought-experiment. In it, a cat is sealed in a box along with a vial of poison and a radioactive atom. The release of the poison – and the cat’s life – depends on the decay of the atom. Quantum mechanics allows the atom to be described as simultaneously decayed or undecayed until a measurement forces it into an exact state. But it then should follow that the cat can be described as both dead and alive at the same time, until the box is opened and the state of the cat made certain. The paradox illustrates the diﬃculty of applying quantum rules to classical objects. This is one of the more fascinating possibilities inherent in quantum theory: that it is possible for a quantum system to be in more than one state at the same time – a phenomenon described as a superposition – until that system is measured.

Quantum computing

There are several ways in which machine learning might be made quantum. Of these, it’s the race to create a quantum computer that’s dominated the popular press and seen the development of contenders like the D-Wave computer and the IBM Quantum Experience.

Dhatfield, Wikimedia

Quantum computers’ value would lie in their ability to process information and perform computational tasks diﬀerently, and in some instances more quickly, than classical computers.

The Schrödinger’s cat paradox is a thought-experiment devised in 1935 by Erwin Schrödinger, who was awarded the Nobel Prize for Physics in 1933 for his work relating to quantum mechanics. The scenario presents a hypothetical cat that may be simultaneously dead and alive inside a sealed box, until the box is opened and the cat’s state observed. 14

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Despite commercial interest, none of the contenders are an outright success yet. That’s because the phenomena they’re drawing from in quantum mechanics, such as superposition states, are delicate and prone to destruction. Other branches of quantum machine learning focus on how quantum theory might inform the methods that computers use to learn, or the data QUESTONLINE.ORG.ZA

QUANTUM TECHNOLOGY | THEME they learn from, as well as fine-tuning the tools and techniques of classical machine learning in a quantum framework. While measurable outcomes are still mostly in the realm of theory, quantum machine learning does have everyday implications for ordinary people. It has long been predicted that the processing power of quantum computers could render current encryption techniques used in banking or other online transactions ineﬀective. More recently, quantum machine learning techniques such as annealing have shown business promise by optimising the yields of financial assets or the calculation of credit ratings. Quantum techniques in machine learning are also likely to become important in medical technology or drug design, as the principles that underpin chemistry are fundamentally quantum. ProteinQure, a biotech company founded in 2017, already uses elements of quantum computation to engineer new therapies. Quantum machine learning techniques are likely to have far-reaching eﬀects on many of the technologies we have become accustomed to, from aviation to agriculture, with companies such as Lockheed Martin, NASA and Google already on board.

Quantum machine learning in Africa

Quantum machine learning is an exciting, rapidly growing field. A number of start-ups have been established that aim to perfect the process and deliver scalable quantum devices. Academics and university researchers are also working to harness the potential of quantum machine learning. We are among them. The University of KwaZulu-Natal’s quantum research group investigates both how quantum theory might improve machine learning and how machine learning techniques can inform quantum theory. Dr Maria Schuld, who is part of the group, recently shared headlines with IBM and US university MIT for an important advancement in the quantum enhancement of kernel-based machine learning methods. See: https:// singularityhub.com/2019/03/17/finally-proof-thatquantum-computing-can-boost-machine-learning/. The authors are from the Centre for Quantum Technology, a research group within the School of Chemistry and Physics at the University of KwaZulu-Natal, headed by Prof. Francesco Petruccione. Betony Adams is a Physics PhD student and Dr Maria Schuld is a researcher. This article was originally published in The Conversation. https://theconversation.com/explainer-what-is-quantum-machinelearning-and-how-can-it-help-us-114627

IBM – Wits quantum computing partnership

IBM first made quantum computers available to the public in May 2016 through its IBM Q Experience quantum cloud service, and has doubled the power of its quantum computers annually since 2017. It also established the IBM Q Network, a community of Fortune 500 companies, start-ups, academic institutions and research labs working with IBM to advance quantum computing and explore practical applications for business and science.

As part of the partnership, academics from the 15 universities that are part of the African Research Universities Alliance (ARUA) will have the opportunity to apply for access to IBM Q’s most advanced quantum computing systems and software for teaching quantum information science and exploring early applications. To gain access to the IBM Q quantum cloud service, ARUA scholars will be required to submit quality research proposals to a scientific committee of Wits and IBM experts for approval.

In April 2019, IBM signed an agreement with the University of the Witwatersrand (Wits) as the first African partner on the IBM Q Network. Researchers at Wits will investigate the use of quantum computing and machine learning in the fields of cosmology and molecular biology with a specific focus on HIV drug discovery.

The University of KwaZulu-Natal, University of Cape Town, University of Pretoria, University of Stellenbosch and Rhodes University are the five South African members of ARUA, and the remaining 10 are universities in Ethiopia, Ghana, Kenya, Nigeria, Rwanda, Senegal, Issued by Wits Tanzania and Uganda.

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Quest Vol. 15 No. 3 | 2019

THEME | BIOMEDICAL ENGINEERING

Machine learning for BIOMEDICAL ENGINEERING There’s a very active machine learning community at Stellenbosch University, to the extent that a Maties Machine Learning event is held every second Friday lunchtime, with short talks or open discussions to bring people together and strengthen machine learning research at the university. Recently, it was the turn of Professor Dawie van den Heever, head of the Biomedical Engineering Research Group (BERG) in the Department of Mechanical and Mechatronic Engineering, to share information on projects involving machine learning. Here, Quest gives a brief summary of a few of these.

Drawing on the acronym of its name ‘Paediatric Attention-Deficit/Hyperactivity Disorder Application Software’ – PANDAS – the game uses a panda bear as its main character, which has to perform tasks and deal with various obstacles at increasing speed. Two diﬀerent games to cater for each of the ADHD sub-types were developed. Data is recorded while the learner plays the game, and machine learning is then used to identify patterns in the data that discriminate between players with and without the condition. Prof. Dawie van den Heever with Sophia, the humanoid robot.

Attention-Deficit/Hyperactivity Disorder

An estimated 5% of learners in South Africa have Attention-Deficit/Hyperactivity Disorder (ADHD), which occurs as two sub-types – inattentive and hyperactive – and is associated with a lack of concentration, no sense of time, poor memory, low self-esteem and poor social skills. Typically, teachers or parents notice these problems in a learner, who is then referred to a specialist, such as a child psychiatrist or educational psychologist, for a proper diagnosis. This involves interviews with the family and the completion by the parents and teachers of questionnaires called rating scales, as well as a series of psychometric tests for the learner. Many learners, especially in rural settings, do not have access to advanced healthcare services, so they may never get the diagnosis and hence the treatment and

The PANDAS game developed by BERG researchers as a screening tool for ADHD. 16

support they need. To address this, researchers at BERG developed a tablet-based game that can be used as a rapid screening tool for ADHD. Final diagnosis would still need to be done by a specialist, but the tool could be used by teachers or nurses before referral, as a diagnostic aid by specialists, or even to monitor response to treatment.

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Knee replacements

The knee is the largest joint in the human body. It is prone to injury, especially through rigorous sport, and to disease, particularly osteoarthritis in the elderly, when cartilage wears away and the underlying bones rub against one another, causing pain and a loss of function. Patients requiring a ‘knee An X-ray showing a knee implant. replacement’ usually have to rely on an artificial implant that comes in standard sizes from a variety of manufacturers. Where an implant does not match the geometry of the patient’s healthy knee, the surgeon tries to make the implant ‘fit’ by shaving away more bone. Often, the mismatch means that normal motion is not fully restored, or that the patient experiences more pain and discomfort during the rehabilitation process. The BERG researchers obtained a large database of CT scans of normal knees from the United States, and used it to model knee geometry – examining, for example, the relationship between the width of the femur and tibia, and the size and curvature of the condyles. They could then use machine learning to estimate the knee geometry of a patient’s healthy knee from CT scans of the damaged knee, well before surgery. This would help in ordering the ‘best fit’ standard implant, but could also be used to custom-make patient-specific knee parts by metal 3D printing, also known as additive manufacturing. QUESTONLINE.ORG.ZA

BIOMEDICAL ENGINEERING | THEME

The portable ECG device developed by BERG researchers could be used in rural areas to detect heart problems.

Cardiovascular disease

Worldwide, cardiovascular disease is a leading cause of death, but diagnosing it requires expensive medical equipment, operated by trained technicians. For this reason, an electrocardiogram (ECG) can only be done at larger hospitals in major cities in South Africa. A standard 12-lead ECG makes use of 10 electrodes attached in specific places on the chest and limbs to record the heart’s electrical activity, represented as a graph of voltage versus time. The BERG researchers developed a portable ECG device that could be used in rural areas to screen for cardiovascular disease, allowing patients with potential heart problems to be referred to hospital for further examination if necessary. The device has a reduced number of leads and electrodes, as well as an electronic stethoscope that records heart sounds, with all data saved to a tablet for instant display and replay.

Machine learning was used in two ways. Firstly, it allowed ‘lead reconstruction’ – in other words, the device is able to reproduce the results of a standard 12-lead ECG that doctors are accustomed to using when making a diagnosis. Secondly, by training the neural network on ‘normal’ ECGs and ECGs representing diﬀerent heart abnormalities, the device was able to diagnose abnormal heart activity with 90% accuracy when tested on 70 subjects in a clinical study at Tygerberg Hospital. It is expected that this would improve with an increased number of training sets.

Brain waves

An electroencephalogram (EEG) is a test usually used by doctors to diagnose problems with the electrical activity of the brain. Electrodes placed on the scalp allow patterns in electrical activity, or brain waves, to be recorded. The main use of EEGs is to investigate epileptic seizures, but also head injuries, sleep disorders, coma, dementia, and brain inflammation or tumours. Researchers at BERG have used EEGs and machine learning to do ‘mind-reading’! Test subjects were shown pictures, words or sentences on a computer screen while brain activity was recorded, and neural networks were then trained to identify what the subject was thinking about. Good results were obtained for training on the EEG data of a specific person, but the neural network did not generalise well to other people, especially to people it did not train upon at all. “But this is still cool,” concludes Dawie. “It tells us that people’s brains work diﬀerently, and that it is possible to train AI to know what object or concept someone is thinking about, based just on brain activity”.

More information can be found on the websites of BERG (https://berg. sun.ac.za/) or Maties Machine Learning (https://mml.sun.ac.za/). A student wears an EEG cap to measure patterns of electrical activity in the brain. QUESTONLINE.ORG.ZA

Quest Vol. 15 No. 3 | 2019

THEME | ECOLOGY

Seeing spots and counting chirps Ian Durbach tells us how machine learning can be used in ecological surveys

Counting animals is an important part of many kinds of ecological problems. Ecologists are often interested in what makes one area better for some animals than others, a question that can only be answered after counting how many animals live in each area. And to assess whether a conservation project in a national park is working, managers would need to know if the number of animals in the park is going up or down. The two main ways animals are counted is by seeing or hearing them. Both of these are diﬃcult jobs, requiring a lot of training and many hours of fieldwork. Up until a few years ago, the most common way of doing this surveying work would be to have highly trained specialists go out and try to see or hear animals. Naturally, there were only so many of these specialists, which meant that the number of studies that could be done was fairly small.

Sifting through all this data can be very time-consuming, and these days data is being captured faster than it can be manually processed. Machine learning plays an important role in ecology, by developing models that can automatically recognise animals in photographs and audio recordings. These are models that recognise patterns – like a leopard’s spots, a giraﬀe’s long neck, or a frog’s croak or chirp – that distinguish what we are interested in (the animal) from the rest of the background. There are a number of diﬀerent kinds of identification problem that can be assisted by machine learning. One is individual animal identification. Some animals have unique markings that allow individual members of the same species to be told apart. The most famous example is the leopard, but many species of frogs and toads also have unique markings. This is important when counting animals from photographs because there might be

Alex Rebelo

Recent advances in digital camera and audio recording technology oﬀer a diﬀerent way of collecting data. Instead of people doing the counts, it is now possible to set up cameras or microphones, and let these do the work. But normally someone still needs to sort through the photographs, or listen to the recordings, to identify which ones contain the animals that are being studied. For example, the cameras that are used are usually motion-sensitive, and will take a photograph whenever

any kind of motion is detected. This can include the species of interest, but also other species, or even motion that is of no interest at all, such as leaves moving in the wind. Audio recording equipment is usually set to switch on for certain hours of the day, and will record all sounds in the nearby environment, whether the animal is there or not.

Distinctive patterns on western leopard toads allow individuals to be identified and counted. 18

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Alex Rebelo

ECOLOGY | THEME

The Cape Peninsula moss frog lives in moist habitats near streams and seeps. Adults don’t grow much larger than 2 cm.

more than one photograph for some of the animals, so population sizes will be overestimated if this is not noted. We work with one species of toad like this, the western leopard toad. The toads have striking patterns on their backs that are unique to each toad. We use a special model called a Siamese convolutional neural network to predict whether two photographs are from the same individual or two different individuals. The model is built by first feeding it pairs of images that come from the same individual, and then feeding it pairs of images from different individuals. From these examples, the model learns which features to pay attention to, and which can be ignored. For example, the model would learn that it is a toad’s spots that make it different from any other toad, rather than – say – the number of legs it has. Cape Peninsula moss frogs present a different kind of challenge. These frogs are extremely difficult to find. Despite being common on Cape Town’s peninsula, very few people have seen one. They are only 2 cm long, live in thick vegetation around mountain seeps or streams, and stop calling as soon as approached. The only possible way of counting the frogs is by setting up microphones and recording how many individual chirps there are. To get from a count of chirps to a count of frogs, we need to divide by the average number of calls made by each frog – fortunately something that is reasonably well known. Machine learning helps here by providing a model that is able to ‘listen’ to thousands of hours of recordings and very rapidly count how many chirps are present. It QUESTONLINE.ORG.ZA

does this by taking one tiny slice of recording at a time – roughly 1/1000 of a second – and predicting whether there is a chirp in that segment or not. It learns, like the western leopard toad model, by example. We first need to feed the model lots of segments that do contain a chirp. Then we feed it segments that do not. Over time, the model learns to recognise what makes the two types of segment diﬀerent. These are just two examples where machine learning is allowing ecologists to focus on the more important scientific questions arising from their research, rather than spending many hours on mundane tasks like sifting through photographs or listening to recordings. As drone technology and high-resolution video and audio recorders become more aﬀordable, ecological monitoring programmes are collecting more data than ever before. Machine learning is almost certain to play an increasingly important role in ecology in the years to come.

Dr Ian Durbach spends half the year in Scotland, where he is a research fellow at the Centre for Research into Ecological and Environmental Modelling at the University of St Andrews. For the other half, he is an associate professor in the University of Cape Town’s Department of Statistical Sciences and an associate research fellow at AIMS. The research reported here was done by two UCT Master’s students he supervised, Emmanuel Kabuga (leopard toads) and Jenicca Poongavanan (moss frogs). Quest Vol. 15 No. 3 | 2019

THEME | BEACH SAFETY

Shark!

Olga Ernst, CC BY-SA 4.0

Machine learning for beach safety The Shark Spotters programme operating at eight of Cape Town’s beaches has improved the safety of water users since its inception in 2004. The programme deploys lookouts at elevated positions near the beaches to keep watch for sharks as well as other marine activity that may indicate the presence of sharks, such as large shoals of fish or ‘feeding frenzies’ by seabirds and dolphins. Equipped with binoculars, polarised sunglasses and two-way radios, these ‘mountain spotters’ contact ‘beach-based spotters’ if they see a shark, so that a white flag can be raised and a siren set oﬀ to warn beachgoers to leave the water immediately. To date, over 2 300 shark sightings have been recorded by the programme, which is funded by the City of Cape Town and Save Our Seas Foundation. Recently, the Shark Spotters programme has embarked on a research project to create an automated sharkspotting system, with the aim of enhancing the beach safety service. The project came about after Dr Krzysztof Kryszczuk – a keen kitesurfer and the cofounder of PatternLab, a scientific consulting company in Switzerland with expertise in machine learning – approached the Shark Spotters team while visiting Cape Town. The Institute for Communities and Wildlife in Africa, based at the University of Cape Town (UCT), subsequently became involved too, and a project to research and develop an automated system using fixed cameras above beaches was designed. 20

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At a public event in February to launch the project, Shark Spotters CEO Sarah Waries explained that there is no intention to replace human ‘spotters’ with robotic ones. Currently, the programme can only operate at beaches where the required elevation is available (usually in the form of a mountain slope), and human fatigue can inevitably set in after some time scanning the sea, increasing the ever-present possibility of the spotters missing a shark. Being able to monitor beaches remotely using cameras fixed to a pole or tower would not only allow the programme to be extended to other beaches, but could also increase the accuracy of shark detection at the existing ones. The initial fieldwork for the project, which involved collecting video footage of sharks in order to build the automated detection algorithm, took place at Fish Hoek beach. Since shark sightings are sporadic and unreliable, a realistically sized shark decoy was also constructed for towing behind a boat. This allowed footage to be collected under a wide range of conditions. Krzysztof reported that wind and glare on the sea surface, cloud cover and particular sun positions all created challenges, sometimes to the extent that neither an automated system nor a human spotter would be able to rule out the presence of a shark. The footage will be analysed to diﬀerentiate how sharks move compared to other marine life or objects, such as a piece of floating kelp, in a process known as heuristic filtering. QUESTONLINE.ORG.ZA

Shark Spotters

BEACH SAFETY | THEME

Construction of a decoy shark for towing behind a boat ensured that enough data could be collected for development of the automated shark-spotting system’s machine learning algorithm, without having to rely on sporadic sightings of real sharks.

Shark Spotters

The concept of automated shark detection is not a new one. In 2018 the Australian Information Industry Association’s National iAward in the category ‘Artificial Intelligence or Machine Learning Innovation of the Year’ was won by the University of Technology Sydney (UTS) and the Ripper Group for their SharkSpotter© technology. In this case, the video surveillance is done using drones, which were deployed at more than 50 locations across Australia last summer. According to the Ripper Group, which own and operate the drones, the AI algorithm developed by UTS can differentiate between sharks and 16 different objects: rays, dolphins, whales, turtles, large fish, swimmers, surfers, other humans, various different boat types, drones and beach tents. The system’s advanced machine learning techniques ensure shark detection accuracy of 90%, compared to conventional techniques such as helicopters with human spotters (18%), fixed-wing aircraft spotters (12% accuracy) and humans analysing aerial imagery (20–30%).

A member of the Shark Spotters team waits at an elevated location above Fish Hoek bay to collect footage of sharks and the towed decoy. QUESTONLINE.ORG.ZA

At the launch of the Cape Town-based project, however, Sarah pointed out that drones are compromised by short battery life and cannot operate in strong wind, they have a relatively small field of view, they are not used continuously and they are expensive, plus the legislative restrictions controlling drone use and the strict certification requirements in South Africa means that they aren’t feasible for use in the local Shark Spotter programme. Four of the beaches in Cape Town are monitored by human spotters from 8 am to 5 or 6 pm for 365 days per year, while the other four only operate during spring and summer. With the added benefit of the so-called ‘computer vision’ currently being developed by PatternLab for the automated shark-detection system, beachgoers should in future be able to enjoy a swim in the sea in more spots along the coastline, safe in the knowledge that the Shark Spotters programme is looking out for them. The project is due to be completed during 2020.

The project is funded by Eurostars, which aims to support innovative projects by small- and medium-sized enterprises working in the research and development arena (R&D-performing SMEs). Eurostars is a joint programme between EUREKA – an intergovernmental organisation for panEuropean R&D funding and coordination – and the European Commission. Eurostars funding for the South African partners in the project, Shark Spotters and UCT, is administered by the Department of Science and Innovation (DSI). South Africa is a EUREKA Associate country, and the DSI had already administered funding for six EUREKA projects, but the Automated Shark Spotting project is its first under the Eurostars programme. The Swiss counterpart of DSI, Innosuisse, administers Eurostars funding for PatternLab’s involvement in the project.

Quest Vol. 15 No. 3 | 2019

Agricultural Research Council offers farmers biogas alternative The Agricultural Research Council recently acquired the state-of-the-art Automatic Methane Potential Test System (AMPTS II) at its engineering research campus. The AMPTS II is one of the instruments used by scientists and engineers to conduct tests in biogas production from organic waste, agricultural residues and animal manure. The AMPTS II performs with ease several tasks including analysis, recording, sample analysis and report generation. The usage of biogas is a response to the growing amount of agricultural waste in modern-day society and, the impact it has on the environment. Many modern farmers are using electricity generated from their farms. Biogas can be used as an alternative source of energy a reduce power reliance on the power grid. The Agricultural Research Council’s engineering research campus oﬀers its services to existing and start-up biogas ventures. The institution oﬀers technical and expertise for biogas generation and maximisation at client’s facilities. Before the construction of biogas facilities, the Agricultural Research Council will conduct a feasibility study on the client’s farm to determine if production of the gas will be sustained.

PRE - & FEASIBILITY STUDY This is the ﬁrst stage, which determines whether there is a possibility for biogas production in a given proposed project. A pre-feasibility study is related to the desktop analysis of the potential of anaerobic digestion process using client’s data. • Raw material-related data quality and quantity assessment • Yield calculations • Sample analysis • Flowsheet development • Assessment of Environmental standards, water pollution issues and resolutions • Estimation of preliminary capital and other operating equipment requirements. Agricultural Research Council’s feasibility study services are related to the stage after a successful feasibility study. The stage encompasses on site visits of anaerobic digestion and the biogas facility, and involves the following: • Provision of raw material data quality requirements • Biomethane potential analysis (grades of biogas, residence time, loading rates and operation temperature) • Process stability analysis (pH, ammonia formation, COD, BOD, volatile fatty acids accumulation, and FOS/TAC) • Infrastructure requirements for a biogas plant, including water consumption and optimisation studies • Assessment of all legal and legislation requirements

ECONOMIC FEASIBILITY The Agricultural Research Council’s economic feasibility services will focus on minimizing costs and optimising returns on investment. Important considerations for economic feasibility include capital and operating equipment costs, quality and prices of biogas and digestate (green fertilizer). ARC oﬀers: • Resource and reserve calculations, process modelling, variability assessment and optimization • Production forecasting and reviews.

CONSTRUCTION OF DIGESTERS The Agricultural Research Council is involved in the design and construction of the digester, development of mathematical equation for the design of a biogas digester system and the fabrication of biogas digester facilities using high-density polyethene plastic, steel or bricks. The Agricultural Research Council ensures that pre-feasibility, feasibility and economic feasibility studies are complete, comprehensive and accurate. The Agricultural Research Council is one of the few institutions which farmers can partner with to reduce risk associated with the development of biogas facilities.

www.arc.agric.za | Telephone: 012 427 9700 | enquiry@arc.agric.za

FEATURE | #LINO19

#LINO19 The Lindau Nobel Laureate Meeting, held annually in the German town of Lindau since 1951, is done and dusted for another year The 2019 meeting – known by its Twitter hashtag #LINO19 – was dedicated to physics, and was attended by 39 Nobel laureates and 580 young scientists from 89 countries. It was particularly meaningful for the South African contingent, because South Africa hosted the International Day this year. The day began with a breakfast panel discussion, titled ‘Global Science in Reaching for the Stars’, which highlighted the diverse opportunities presented by the Square Kilometre Array (SKA), MeerKAT and South African Large Telescope (SALT) astronomy projects. It ended with a get-together over dinner, with some home-grown Mzansi entertainment that was enjoyed by all.

FO: The trip preparations were full of optimism but also nervousness, since I truly didn’t see myself with Nobel laureates in physics, let alone discussing my research eﬀorts. Although ASSAf made me feel relaxed by organising a pre-Lindau meeting, where all nominated individuals were briefed of the expectations, I still felt uneasy. But we arrived as a team and I was taken in by my host, Petra Wissmann, an incredible lady with a golden heart quite rare to find. We had the best time, full of wide-ranging discussions about previous laureate meetings, the history of Lindau, giving back to the community, etc. So on the day of registration I was feeling quite at home, anticipating meeting the Nobel laureates.

Here, two of the 20 young scientists from South Africa who attended this year tell us about their #LINO19 experience.

Which of the laureates’ talks made a particular impression on you?

•

Ms Katekani Shingange (KS) is a physics PhD candidate registered at the University of the Free State, but based at the CSIR in Pretoria. Her research focuses on the design of advanced nanostructured perovskite oxides for application in gas sensors.

•

Dr Francis (Frank) Otieno (FO) is a postdoctoral fellow at the University of the Witwatersrand, where he conducts research on condensed matter physics relating to thin films, and their application to photovoltaics.

What were your feelings before the meeting?

FO: I was fascinated by how most of the speakers had many years of investigations and only realised a breakthrough later, often at the least expected moments.

Patrick Kunkel/Lindau Nobel Laureate Meetings

KS: Leaving South Africa for the meeting, I had my expectations, and they were all met and even exceeded! I experienced an overwhelming excitement. The Lindau meeting was filled with positive vibes, smiley faces and very motivated people – and all of this was pretty contagious!

KS: The keynote address by Brian Schmidt was a personal highlight. He said that we are completely interdependent in the work that we do, and although it is easy to feel isolated in our research, and that our little piece doesn’t matter, more often than not it does, or it will, but in ways we cannot predict in advance. And it’s not just through academic journals – it can manifest in all sorts of unexpected ways. He gave an example of our smartphones, which contain diﬀerent pieces of research done by diﬀerent people, and relied on a history of discoveries. He said: “It is this interconnected world where each of us does our bit that makes us powerful and strong”. From these words, I felt I was important, and it hit me that actually I was amongst the most beautiful brains in the world – it made me blush!

The South African delegation of young scientists in culturally inspired fashion for the get-together dinner. 24

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#LINO19 | FEATURE

Patrick Kunkel/Lindau Nobel Laureate Meetings

Left: Young scientists work up an appetite with Xhosa dancers before the dinner. Right: Katekani Shingange with Donna Strickland (2018 Nobel laureate) Below: Frank Otieno with William D. Phillips (1997 Nobel laureate)

They had kept working, never giving up. This was well illustrated by Joseph H. Taylor in his talk titled ‘Long tortuous path to gravitational waves’. Although not my field of study, he compared his experience to Einstein’s conversation with the editor of his paper about whether gravitational waves exist. It was not a smooth ride but with errors, disappointments and a feeling of not being taken seriously for the much-celebrated Einstein. His disappointments mirror so well my current struggle to publish, and was a true motivation to keep going.

Apart from the talks, what were some of the other highlights?

KS: I enjoyed the student exchange sessions, as well as the science walk with the laureates. During these sessions, the young scientists had opportunities to ask as many questions as they wanted. The panel discussions were stimulating too, such as the one titled ‘Student, Postdoc and then? Aiming for a career in science’. This discussion made me realise that I am the driver of my own career and I should take this into consideration when planning it. Other take-home points from the discussion were: it is all right to fail, the value of perseverance and knowing when to quit.

Reflecting on your experience, what is your lasting impression?

KS: Most of the talks and activities provoked self-analysis within me to find my own ideas, thoughts and feelings about my path in science and my contribution to society. The Lindau meeting is an attitude-changing experience, and I regard myself as very fortunate to have been given the opportunity to attend. FO: I was struck by the simplicity and humbleness of the laureates, and my previous perception that the Nobel Prize was something unattainable was proved otherwise. We also had lots of interactions with fellow researchers, sharing our ideas, disappointments, ambitions and current conditions, as well as general talks that I found so encouraging. It was a great experience!

Julia Nimke/Lindau Nobel Laureate Meetings

FO: I wish all conferences could be done in a similar way. The talks and discussions were quite engaging – I felt heard and to have heard a lot too. One session in particular was the Master class I attended on teaching physics. After a short presentation, we had a wonderful engaging session of discussions, guided by one of the Nobel laureates, and I felt quite inspired since I love teaching so much.

And the social highlights?

KS: For the international get-together hosted by South Africa, all the South African delegates were dressed in our diverse cultural attires – and we looked so fine! Another aspect that made the whole Lindau experience enjoyable for me was the hospitality of my wonderful hosts, Diana and Stephan Förbs. Instead of just focusing on the meeting alone, I got to learn about their culture as well. FO: The hospitality at the meeting was amazing, culminating in a boat ride to Mainau Island – very beautiful scenery, with wonderful people. QUESTONLINE.ORG.ZA

Afro-Soul singer Nomfusi performing at the get-together dinner, hosted by South Africa. Quest Vol. 15 No. 3 | 2019

Alan Chia, CC BY-SA 2.0

FEATURE | #LINO19

Building new forms of matter,

brick by LEGO brick ®

Ben Skuse, a guest blogger at #LINO19, reports on the lecture by Wolfgang Ketterle, who was awarded the Nobel Prize for Physics in 2001

Christian Flemming/Lindau Nobel Laureate Meetings

To build new matter, Ketterle says that the key is not just extremely low temperature but also the need for each atom, like an individual LEGO brick, to be isolated. “A lot of people think the field of ultracold atoms is characterised by ultracold temperature, nano-kelvin temperature. This is correct,” he said. “However… what is much more important is that the materials we create from ultracold atoms are extremely dilute – the density is a billion times lower than ordinary matter. If we put these materials together, we can then focus on the special phenomena of these materials and not their complicated interactions.”

Wolfgang Ketterle emphasised the need for a playful attitude to physics.

“I loved to play with LEGO,” recalled Nobel laureate Wolfgang Ketterle during his lecture on the fifth day of the 69 th Lindau Nobel Laureate Meeting. “In my days, LEGO was just a box of bricks and you had to use your imagination to build very complicated things out of very few building blocks – and this is what we do in my research.” Today, his LEGO bricks are ultracold atoms (and molecules) and his playmat consists of a tabletop covered with extremely complicated equipment. But his playful spirit remains. He applies it to finding new forms of matter near absolute zero temperature. 26

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Ketterle applied this understanding in 1995, when he (together with Nobel laureates Eric Cornell and Carl Wieman) discovered Bose-Einstein condensates (BECs) – a new state of matter observed at ultracold temperatures. At less than a millionth of a degree above absolute zero, Ketterle and his fellow laureates demonstrated that distinct atoms meld into a single quantum state to form a quantum gas. Individual particles can no longer be distinguished because they have formed a single macroscopic matter wave. Not one to rest on his laurels, Ketterle has continued his pursuit of new forms of matter. He does so by shining between five and 10 laser beams on ultracold atoms and then gradually making the system more complex. “You start with a simple system which you can immediately understand just as a stepping stone, but eventually you want to add more complexity and create a situation where even the best supercomputers cannot solve the Hamiltonian,” he revealed. “You want to build the

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#LINO19 | FEATURE complexity step-by-step and hopefully be able to test every single step… like a computer code.” Recently, this technique bore fruit, when Ketterle and his team observed a supersolid. Supersolids are a bizarre form of matter combining properties of a solid and a superfluid at the same time. In a solid, every atom is localised and therefore you can distinguish them by location, whereas in a BEC or a superfluid all the atoms have to be delocalised, by definition, and form one single matter wave. The two should therefore be mutually exclusive. Ketterle found a way to bring the two together: “What we were able to create was a shape, in this case a density modulation with a striped phase [in a BEC], but those stripes were not imprinted with laser beams,” he explained. “And this contained continuous symmetry-breaking properties, which is the defining feature of a solid.” “What we created was a supersolid that I could explain to you in one slide,” he said. But this is exactly what he wanted to achieve. “When people would later say ‘This is trivial’, I would say, ‘Thank you, this is actually a compliment’… we want to show the simplest possible way to realise a phenomenon.” Even more recently – in fact, just a few weeks ago in unpublished work – Ketterle made another key breakthrough in ultracold physics. His team discovered a method to ultracool molecules. Ultracold molecules would provide fundamental new insights into molecular interactions in the quantum regime.

Patrick Kunkel/Lindau Nobel Laureate Meetings

However, for over a decade, physicists have struggled to cool an ensemble close to absolute zero, a major source

Ketterle surrounded by young scientists during the boat trip to Mainau Island.

of frustration for Ketterle: “In my research I really want more LEGO pieces”. Though numerous techniques have been applied, all have so far failed. The most promising of these options is collisional cooling. Yet all previous attempts at collisioncooling ended with unstable molecules that didn’t survive collisions. To surmount this impasse, Ketterle’s team played with a system nobody expected would allow collisional cooling: sodium-lithium molecules. “People told us this would not work, but I told my group we just have to try it,” he recalled. Sodium-lithium molecules are normally reactive, but by aligning all the spins in the system, they became non-reactive. Doing so allowed the team to reduce the temperature by more than an order of magnitude. Ketterle said that the breakthrough means that for the first time, there is a system of molecules that can be collision-cooled, bringing ultracold molecules a huge step closer to reality. Most importantly, it means Ketterle may soon have a completely new playground in which to probe fundamental physics and even perhaps find more new forms of matter. Benjamin Skuse is a professional freelance writer of all things science. In a previous life, he was an academic, earning a PhD in Applied Mathematics from the University of Edinburgh and an MSc in Science Communication. Now based in England’s south-western region, he aims to craft understandable, absorbing and persuasive narratives for all audiences – no matter how complex the subject matter. His work has appeared in New Scientist, Sky & Telescope, BBC Sky at Night Magazine, Physics World and many more.

To find out more about Wolfgang Ketterle’s path to his Nobel Prize, read his autobiographical profile: https://www.nobelprize.org/prizes/physics/2001/ketterle/biographical/ He shares his other interests in this 2009 interview with Runner’s World magazine: https://www.runnersworld.com/runners-stories/a20837391/im-a-runner-wolfgang-ketterle-ph-d/ QUESTONLINE.ORG.ZA

Quest Vol. 15 No. 3 | 2019

FEATURE | FIRST CIRCUMNAVIGATION

Fifth centenary of world’s first circumnavigation The first trip around the globe in the 1500s lasted just over a thousand days longer than the time it took Phileas Fogg in Jules Verne’s classic novel Around the World in 80 Days. By Helen Swingler

Wikimedia (CC BY-SA 3.0)

The circumnavigation of the globe by the Spanish ship Victoria 500 years ago was akin to the first moon landing, 50 years ago. The repercussions of that historic voyage are still felt today in science, mathematics and astronomy, says University of Cape Town (UCT) scholar Dr Álvaro de la Cruz-Dombriz. De la Cruz-Dombriz – of the UCT Cosmology and Gravity Group in the Department of Mathematics and Applied Mathematics – was speaking at the opening of an exhibition to mark the quincentenary. The month-long exhibition, ‘Elcano Crosses the Cape’, opened at the Castle of Good Hope on 12 June 2019. “The event is indeed linked to my academic research, as the circumnavigation was a milestone, among others, in the scientific realisation of the roundness of Earth and the use of southern hemisphere stars to navigate,” he explained. The exhibition was a joint venture by the Iziko Castle of Good Hope, the SA Naval Museum, the South African Astronomical Observatory, the General Consulate of Spain in Cape Town and the Embassy of Spain in South Africa. De la Cruz-Dombriz was its co-organiser.

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Round the world in three years

The 1519 to 1522 expedition culminating in the historic milestone, led by Ferdinand Magellan and Juan Sebastián Elcano, passed by the Cape of Good Hope. Magellan was the Portuguese explorer who organised the Spanish expedition, although it was completed by Elcano, a Spaniard. The voyage’s primary aim was to find the passage of spices between Asia, America and Europe through the Pacific. Making history was not their main intention when they set out for the East Indies in 1519, said Spanish historian Dr Ángel Tordesillas, who delivered the opening address. They had other things on their minds, commodities more precious than gold: spices. “They had wanted to take control of the Eastern spices, and just happened to sail around the globe,” he said. Vying with the Portuguese for the spice wealth of the East, and to avoid conflict, Spain agreed with Portugal to establish two zones of influence, under the bilateral Treaty of Tordesillas of 1494. The fleet that set out employed the best ships and navigation devices of the time: 23 navigation charts, 35 compasses, six pairs of compasses, 21 quadrants, seven astrolabes and 18 sandglasses, among other instruments. QUESTONLINE.ORG.ZA

FIRST CIRCUMNAVIGATION | FEATURE

Logistics and logs

Among the supplies they carried for the grand voyage were 253 wine barrels, 417 wineskins, 21 000 pounds (9 525 kg) of biscuits, 2 800 pounds (1 270 kg) of cheese, seven cows and other livestock, bacon, dried meat and fish, ham, rice, lentils, beans, chickpeas, plums, marmalade, jam, sugar, honey, dried fruit, quinces and garlic. Under the auspices of the Spanish Crown (Carlos I was on the throne), the trade expedition embarked from the river port of Seville: five ships and 250 men from 10 nations. Three years later, after a journey of 40 000 miles (64 400 km), only one ship, the Victoria, and 18 men remained. One of the survivors was Elcano, who completed the round-the-world voyage after Magellan was killed during the Battle of Mactan in the Philippines in 1521. “The voyage provided the first empirical proof of at least four important facts,” De la Cruz-Dombriz said. “First, that America was a diﬀerent continent from Asia; second, the existence of a southernmost pass in America; third, the character of the Pacific as an ocean, not a sea; and finally, the roundness of the Earth. The latter could have been proved by indirect scientific measurements throughout human history,” he added. “But the fact [that] this expedition, just navigating west, returned to the same point [from which it had started], proved indeed the roundness of the Earth, and helped to establish its diameter – much bigger than … it was thought to be before.”

famous Magellanic Clouds – named after Magellan, to commemorate the expedition achievement – although known by several civilisations in southern America and Africa, were unknown in the western astronomical knowledge of the time. Thus, the expedition served to join knowledge of diﬀerent parts of the globe. The exhibition displays an original Nicolas de Lacaille book dating back to 1763 (on loan from the South African Astronomical Observatory) showing how these ‘clouds’ (indeed, two irregular dwarf galaxies) were since then depicted in the most important catalogues of astronomy – a research field which has become a national priority in South Africa.” In summary, De la Cruz-Dombriz said the expedition had helped to integrate the southern hemisphere on an equal footing in the development of sciences in modern history, also beginning an epoch of transnational enterprises, global trade and exchange of human knowledge between four continents. Helen Swingler is senior writer in the University of Cape Town newsroom. This article is republished from UCT News under a Creative Commons Licence (CC BY-ND 4.0).

Pedrik, CC BY-SA 2.0

Also, the expedition was instrumental in the use of southern hemisphere stars for navigation. “The very

A replica of the Victoria, the only one of five ships that set out from Spain in 1519 to complete the circumnavigation. QUESTONLINE.ORG.ZA

Quest Vol. 15 No. 3 | 2019

FEATURE | FIRST CIRCUMNAVIGATION

Scientific repercussions of the first circumnavigation Wikimedia, CC BY-SA 3.0

Nowadays, when intercontinental trips take place every day from airports and ports around the world, it is hard to imagine the difficulties faced during the expedition led by Magellan and Elcano 500 years ago, resulting in the world’s first circumnavigation. The years at sea gave rise to scientific discoveries and technical applications that are still relevant today. By Álvaro de la Cruz-Dombriz State secrets

First, the expedition served to dismiss the old portulan charts that for centuries were useful for a closed sea, such as the Mediterranean, but useless for the vast oceans. Astronomical observation and the study of ocean currents had by then made more distant navigations possible, so 24 nautical charts were used in this historic voyage, containing all the knowledge that both the Spanish and Portuguese had accumulated about the Eastern and Western Indies. The information gathered by the expedition allowed Nuño García de Toreno to show the location of the Moluccan and Philippines Islands in his chart, dated 1522,

Information gathered during the circumnavigation was used in the Padrón Real, the Spanish master map completed in 1527 and used as a template for the maps carried by all Spanish ships during the 16th century.

of Spanish territory in southern Asia. The same year, Pedro Reinel released a southern polar (or azimuthal) projection chart depicting the coast of South America. In 1527 Diego Ribero finished the Padrón Real, the oﬃcial and secret Spanish master map used as a template for the maps carried by all Spanish ships during the 16th century. Its layout was strongly influenced by the information obtained during the Magellan-Elcano circumnavigation, and is considered the first scientific world map. Cartography thus became an essential tool at the service of the Hispanic Monarchy. The King was able to furnish his powerful network of diplomats with the authority conferred by discoveries represented on the maps.

Instruments

The use of all the available technology at the time, including quadrants, astrolabes, magnetic compasses, sandglasses (hourglasses) and pairs of compasses (drawing tools), eased the enormous task of the expedition. For instance, compasses could be used to measure distances based on angles marked on the maps, while astrolabes were used to measure the height of stars above the horizon so that latitude could be determined. It seems that Elcano noticed how magnetic compasses lost precision once the North Star could no longer be seen as the ships approached the southern hemisphere.

NASA

Three oceans and the American continent

The Strait of Magellan near the tip of South America was named after Ferdinand Magellan after he proved the existence of this passage between the Atlantic and Pacific Oceans. 30

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On 1 November 1520, the expedition entered a 565-km long labyrinth of islands and channels at the tip of South America. By finding the way through and emerging on the other side of the continent, the existence of a southernmost passage, subsequently named the Strait of Magellan, was confirmed. It took Magellan and his crew three months to cross the ocean beyond, which they named the Pacific Ocean for its calm waters and bright skies. It thus became obvious that Asia and America were diﬀerent continents, a fact that QUESTONLINE.ORG.ZA

FIRST CIRCUMNAVIGATION |FEATURE

ESO/Y. Beletsky

The Magellanic Clouds can be seen with the naked eye, but high-ISO, long-exposure photography allows them to be captured here as two bright areas between telescopes at the Paranal Observatory in Chile, South America, while the Milky Way arches overhead. Visible only from the southern hemisphere, the Magellanic Clouds were known by indigenous people of Africa, South America and Australasia long before they were documented during the Magellan circumnavigation.

had remained unclear since 1492, when Christopher Columbus claimed to have arrived in the East Indies. The expedition also marked the first crossing of the southern Indian Ocean. Consequently, Europeans abandoned the idea that the Atlantic Ocean was the sole ocean, and America achieved the status of being another continent.

The southern skies

Once through the Strait of Magellan, the voyage chronicler, Antonio de Pigafetta, reported two features of the southern skies. First, he remarked on the presence of ‘clouds’ in the heavens – these two dwarf galaxies, neighbouring the Milky Way and visible without a telescope, were duly named the Magellanic Clouds. Second, Pigafetta described the Southern Cross, probably making him the first to record this set of five stars.

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They are the subject of ongoing research, both in South Africa and abroad, to be discussed at a dedicated scientific workshop hosted by the European Southern Observatory (ESO) in Germany in September 2019. These two dwarf galaxies – the Large Magellanic Cloud (LMC) approximately 163 000 light years away, and the Small Magellanic Cloud (SMC) some 200 000 light years away – may eventually merge with our own galaxy, the Milky Way, but not for another two billion years at least!

Around the world

Although both Aristharcus and Eratosthenes theorised about the roundness of the Earth in the 2nd century BC, it was Elcano’s team who proved it because the expedition returned to the same point from which it had started, just by navigating west. In fact, they also realised that their logbooks were one day behind, although they had kept meticulous records, marking each day as the sun rose. Since the Earth rotates eastwards, by navigating west and returning to the same point they had spent one less day under the sun than those who had stayed at that point. Now, a realistic world map was indeed feasible. Dr Álvaro de la Cruz-Dombriz is a researcher in cosmology and a senior lecturer in UCT’s Department of Mathematics and Applied Mathematics.

Quest Vol. 15 No. 3 | 2019

FEATURE | AIR POLLUTION

#Be

atA #Br irPol lu eat heL tion ife

Standing up for clean air By Danielle Millar and Caradee Wright

Clean air is as vital to life on earth as clean water, and the suffering and deaths from polluted air are preventable. Air pollution reduction and control must become a priority for everyone. Industrialisation, rural-urban migration and urban planning under apartheid have all played a role in contributing to air pollution in South Africa. Historically, low-cost residential areas were designated close to industrial zones, and the continued influx of people to these urban and industrial areas gave rise to informal dwellings in their vicinity. Poor service delivery in these settlements means that people living there may still rely on traditional solid fuels such as wood, coal and paraﬃn for cooking and heating, and often dispose of waste by burning it. These practices generate smoke that results in household air pollution. Poor air quality has long been known to have a negative impact on human health. According to World Health Organisation (WHO) statistics, the death rate attributed to household air pollution in South Africa in 2016 was 34 per 100 000 people. This estimate was calculated considering acute (short-term) and chronic (long-term) respiratory diseases linked to air pollution exposure, such as lower respiratory infections, respiratory cancers and Chronic Obstructive Pulmonary Disease, as well as cardiovascular diseases – ischaemic heart disease and stroke – for which air pollution is a risk factor. Apart from household air pollution, people living in urban areas may also be exposed to high levels of ambient air pollution, generated by outdoor fires, vehicles, coalUmoya ohlanzekile ubalulekile kwizinto eziphila emhlabeni njengoba kubaluleke amanzi, futhi ukuhlupheka nokufa okubangelwa umoya oncolile kunga vimbeka. Ukunciphisa nokuvimbela umoya oncolile kufanele kube yinto ehamba phambili kuwo wonke umuntu. Translation by Zamantimande Kunene 32

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fired power plants, industrial facilities and waste sites. But ambient air pollution can also occur in rural areas, due to natural sources such as dust storms and veld fires. In an eﬀort to address ambient air pollution in South Africa, National Ambient Air Quality Standards for pollutant levels were set in accordance with the National Environmental Management: Air Quality Act (NEMAQA). Many areas currently exceed the standards, however, with air pollution hotspots typically coinciding with centres of industry and large populations. These areas include three National Air Quality Priority Areas – Vaal Triangle Airshed, Highveld and Waterberg-Bojanala – that were declared because they exceed the standards and also cross provincial boundaries. Ambient monitoring data collected by national, provincial and municipal authorities to assess compliance with the standards is made publicly available through the South African Air Quality Information System (SAAQIS). The SAAQIS website (https://saaqis.environment.gov.za/), as well as its associated Android and iOS apps, includes a simplified Air Quality Index that allows members of the public to understand how measured concentrations of pollutants translate to air quality and health eﬀects. QUESTONLINE.ORG.ZA

AIR POLLUTION | FEATURE South Africa’s standards are not as strict as the WHO’s air quality guidelines; in fact, 91% of the world’s population lived in places that did not meet the WHO guidelines in 2016. Globally, the main source of air pollution is caused by the utilisation and burning of biomass and fossil fuels for power, heat, transport and food production. One air pollutant of major concern is particulate matter (PM), a complex combination of tiny solid particles and liquid droplets of organic and inorganic substances suspended in the air. The key components of PM are nitrates, ammonia, sulphates, sodium chloride, black carbon, water and mineral dust. Particles with a diameter of 10 micrometres (equivalent to 0.01 mm) or less are known as PM10 and can aﬀect human health as their small size means they easily penetrate and lodge in the lungs. Even more dangerous are particles with a diameter of 2.5 micrometres or less – known as PM2.5 – as they can penetrate the lung barrier and enter the bloodstream. Chronic exposure to these particles increases the risk of developing multiple respiratory and cardiovascular diseases and conditions.

Science-policy statement on air pollution and health The National Academies of Sciences and Medicine from South Africa, Brazil, Germany and the United States have joined forces to issue an urgent call to action on harmful air pollution. At a ceremony at the United Nations (UN) headquarters in New York on 19 June 2019, the academies handed over a sciencepolicy statement, titled Air Pollution and Health, to senior UN representatives and high-level diplomats from the four countries. In the statement, the five academies call for a new global compact – or agreement – to improve collaboration on the growing problem, and for governments, businesses and citizens to take action to reduce air pollution. They appeal for emissions controls in all countries, as well as proper monitoring of key pollutants, especially PM2.5 .

Scientific evidence shows that air pollution aﬀects human health at every stage in our lifespan, including as unborn babies. The most vulnerable to pollutioninduced damage are the young, elderly and otherwise health-compromised individuals. In children and adolescents, lung growth and brain development is slowed because of air pollution. In adults, there is increasing evidence of pollution contributing to dementia and neurodegeneration. Apart from the previously mentioned respiratory and cardiovascular eﬀects, air pollution aggravates or increases susceptibility to conditions such as asthma, allergies, diabetes, eczema and skin ageing. Indeed, evidence is mounting that air pollution causes premature deaths of at least five million people per year.

The global economic burden of disease caused by air pollution across 176 countries in 2015 was estimated to be US$3.8 trillion. The academies note that public and private investments in measures to reduce air pollution do not match the scale of the problem, and highlight the need for increased funding to confront the issue. The measures could also help to reduce climate change and contribute to meeting the goal of limiting average global warming to 1.5°C.

•

The statement is available online at: www.air-pollution.health.

For more information on air pollution, see the World Health Organisation’s online portal: https://www.who.int/airpollution/en/

The academies invite other science academies, research institutes, universities and individual scientists worldwide to join the initiative and to strengthen research and science-policy activities in the area of air pollution and health.

Danielle Millar is an MSc graduate in medical physiology and a research intern in the Environment and Health Research Unit of the South African Medical Research Council (MRC). Dr Caradee Wright is a Senior Specialist Scientist in the same unit and is also a lecturer in the Department of Geography, Geoinformatics and Meteorology at the University of Pretoria.

CURRICULUM CORNER LIFE SCIENCES: GRADE 10-12 Environmental studies

GEOGRAPHY: GRADE 10 Population movements

GEOGRAPHY: GRADE 12 Urban settlement issues

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ASSAf Executive Oﬃcer, Prof. Himla Soodyall (left), and MRC scientist Dr Caradee Wright (right) with Prof. Jacqueline McGlade, former Chief Scientist to the UN Environment Programme, at the handover ceremony for the Air Pollution and Health science-policy statement at the UN headquarters in New York. Quest Vol. 15 No. 3 | 2019

NEWS | MICROBIOLOGY

Wood-munching fungus has genome decoded

The research team: Prof. Alf Botha, MSc student CJ Borstlap, Dr Heinrich Volschenk and Dr Riaan de Witt.

A relatively unknown fungus, found by chance on an acacia tree in the Northern Cape, has emerged as a voracious wood-munching organism with enormous potential for industries that use biomass as a renewable resource. The first time someone took note of Coniochaeta pulveracea was more than 200 years ago, when the South African-born mycologist Dr Christiaan Hendrik Persoon mentioned it in his 1797 book on the classification of fungi. Now C. pulveracea has had its whole genome sequenced by microbiologists at Stellenbosch University (SU), and henceforth made its debut in cyberspace with a few tweets and a hashtag. All because this relatively unknown fungus has an extraordinary ability to degrade wood – hence the species name ‘pulveracea’, reflecting its ability to render something powdery. In the age of biotechnology, biofuels and the use of renewable raw materials, this is an important fungus to take note of, says Professor Alf Botha, from SU’s Department of Microbiology. While the ability of species in the Coniochaeta genus to rapidly degrade lignocellulose into fermentable simple sugars has been reported over the past 25 years, thus far Prof. Botha’s lab is the only one working on C. pulveracea. The work started in 2011, when he quite randomly snapped a brittle twig, covered in lichen, from a decaying acacia tree while holidaying on a farm in the Northern Cape. “At the time we were looking for fungi and yeasts that can break down wood, so I knew this was something special when I decided to keep the twig,” Cells of the wood-eating fungus Coniochaeta pulveracea exhibit both unicellular yeast- and filamentous fungus-type characteristics while breaking down twigs from an acacia tree.

he explains. To date, despite numerous attempts, they have not been able to find the fungus in the field again. However, back in the lab there was great excitement when they observed that the fungus, in culture, was literally munching its way through birchwood toothpicks. Even more astounding was its ability to change form between a filamentous fungus and a unicellular yeast, depending on the environment – an unusual behaviour typically associated with fungal pathogens. Prof. Botha and his postgraduate students began investigating the fungus more closely, and in 2011 Dr Andrea van Heerden found that it produced enzymes that degraded the complex structures of wood into simple sugars, such as glucose and cellobiose. In 2016 she published the results of her research on its ability to switch to a yeast-like growth. Understanding this process would be important to the potential use of this fungi in industrial processes. In the latest study, MSc student CJ Borstlap worked with Dr Heinrich Volschenk, an expert molecular biologist, and Dr Riaan de Witt from the Centre for Bioinformatics and Computational Biology at SU, to produce the first draft genome sequence of C. pulveracea. With a genome size of 30 million nucleotides and 10 053 genes, this was no easy task. Genes responsible for the wood-degrading character of the fungus were identified, but the next step is to understand the mechanisms on a molecular level. “With the genetic blueprint now available, we can study the network of genes and proteins the fungus employs to convert wood and other similar renewable resources into more valuable products,” explains Dr Volschenk. The sequence data for C. pulveracea have been deposited at the DNA Data Bank of Japan (DDBJ), the European Nucleotide Archive (ENA) at Cambridge, and GenBank in the United States, and is freely available to all researchers in this field. More information is available online at: https://mra.asm.org/content/8/1/e01429-18. Article by Wiida Fourie-Basson, media oﬃcer for the Faculty of Science, Stellenbosch University QUESTONLINE.ORG.ZA

MICROBIOLOGY | NEWS

Body of work on

Basotho medicinal plants

So says the principal investigator of the University of the Free State’s Phytomedicine and Phytopharmacology Research Programme (PPRP), Professor Anofi Ashafa. Based in the Department of Plant Sciences on the Qwaqwa Campus, the PPRP studies the biological effects of medicinal plants used in the traditional medicine of the eastern Free State. “Our research is mainly aimed at documenting plants used by the Basotho in the management of different ailments and to further discover, isolate and purify active phytoconstituents that are responsible for disease curation or amelioration, thereby assisting in the global promotion of accessible and affordable medication in developing countries,” said Prof. Ashafa.

The group is also investigating some threatened species on the Red List of South African Plants, compiled QUESTONLINE.ORG.ZA

Issued by Thabo Kessah, communication specialist for UFS: Qwaqua Campus

Alexey Yakovlev, CC BY-SA 3.0

Peganum, CC BY-SA 3.0

“Our research informs teaching and the development of expertise in ethnobotany, phytomedicine and phytopharmacology in order to contribute to the National Development Plan (NDP) through human capacity development, skills and knowledge transfer,” says Prof. Ashafa.

by the South African National Biodiversity Institute (SANBI), through micropropagation and field trials, and is proposing conservation strategies for the species’ protection. Research is done in collaboration with several local and international universities, as well as the Agricultural Research Council (ARC).

Paul Venter, CC BY-SA 3.0

These activities have led to the discovery of four potent antidiabetic biomolecules that are awaiting the processes of patency and commercialisation. Additional outputs include 104 published peer-reviewed articles, seven postdoctoral fellows, six PhDs, nine Master’s and 16 Honours graduates.

Prof. Anofi Ashafa heads the Phytomedicine and Phytopharmacology Research Programme (PPRP) at the University of the Free State.

Andrey Sochivko, CC BY-SA 3.0

Phytoconstituents are chemical compounds that occur naturally in plants, and since 2012 the PPRP has investigated numerous Basotho medicinal plants used as antimicrobials, antioxidants, antidiabetics, antitubercular, anticancer, anthelmintic and antidiarrheal agents. Apart from studying their biological activity, the researchers have evaluated toxicity to kidney, liver and heart functions in order to establish safe dosage parameters.

Tsepo Moeketsi

By conducting research on traditional medicine, the values and contribution of indigenous knowledge systems (IKS) towards broader scientific research can be explored.

Clockwise from top left: Dicoma anomala, Pentanisia prunelloides, Lessertia (formerly Sutherlandia) montana and Gazania krebsiana are just some of the plants that have been investigated by PPRP researchers. Quest Vol. 15 No. 3 | 2019

NEWS | SCIENCE FAIR

My science fair journey

Hritik Mitha, a Grade 10 learner from Bryanston High School in Johannesburg, was sponsored by Eskom Expo for Young Scientists to attend the Intel International Science and Engineering Fair (ISEF) in Phoenix, Arizona, in the United States in May 2019. He was one of eight learners representing South Africa at the high school science fair, having been awarded a gold medal for his science project at the Eskom International Science Fair in Johannesburg in September 2018. Intel ISEF featured more than 1 800 high school students from 80 countries and regions around the world. Hritik walked away with a USAID Science for Development Second Place Award, winning US$3 000 in prize money! Quest asked him about his USA experience, the opportunities presented to him since his return, his future plans and his other interests.

The trip

“The trip to Intel ISEF was my first time overseas, so merely going to another country was already amazing for me. It was an adventure getting to Phoenix, with connecting flights via Dubai, Seattle and New York. After over 20 hours of flying time to get there, it was great to arrive in Phoenix, passing the Grand Canyon on the flight’s descent and then viewing the city by night, illuminated by all the lights. Phoenix was a beautiful city, although stiflingly hot, being in the Sonoran Desert.” 36

Quest Vol. 15 No. 3 | 2019

“Highlights of my trip included meeting people of so many diﬀerent cultures from all over the world. Getting to converse with people with similar visions to my own of helping the world was both enlightening and inspiring.” “Apart from the science fair, I went to my first baseball game, featuring the Phoenix team, the Arizona Diamondbacks. That was a really interesting experience, watching a new sport whilst enjoying the energy of the evening. We were also able to explore more of the city independently during our free time. We either went shopping or did some leisure activities such as ice-skating (also a first for me).” “Eating out at multiple American restaurants was a refreshing experience, although I cannot lie – I went to Starbucks about six times! The city had such a buzz, so overall it was an epic excursion!”

Opportunities back home

“Since arriving back from the USA, I’ve had so many opportunities to discuss my project and attend scienceor engineering-oriented events. I was invited to attend and speak at the Green Youth Indaba, an annual event that promotes sustainable development in technology and skills development for the future. I spoke about my project, as it promoted green energy and sustainable development.” “Then I was interviewed on Caps Radio a few weeks later, where I was asked questions regarding my project QUESTONLINE.ORG.ZA

SCIENCE FAIR | NEWS journey. I really enjoyed knowing that my story of resilience and dedication could inspire many others with similar goals. The #MillionYoungMinds event was focused around robotics and AI, and I was selected as a school ambassador due to my past achievements. It was a great experience. I never knew that something as simple as a science fair project could yield so many opportunities in the future. Even after winning, I still continued to reap the rewards of my work.”

Future plans

“At this stage, I’m not certain what profession I’ll pursue in the future, but currently I’m looking into studying physics or engineering. This expo made me aware, more than anything else, of all the possibilities there are, and that there’s no need to make a hasty decision when there are so many career fields out there. I may even consider going into entrepreneurship – people like Elon Musk and Bill Gates are transforming the world and saving it from problems such as climate change, and I wish to contribute to this. I feel proud knowing my project has the potential to contribute and help mitigate the current problems the world faces. I feel satisfied knowing that my high school project is already contributing to cleaner, sustainable energy production, and I hope to focus on goals that benefit people and the world at large in the future.”

Proudly South African winners at the Intel International Science and Engineering Fair in Phoenix, Arizona.

Other interests

“Science is a major part of my life, but it’s always healthy to maintain a balance in your life. I have quite a few other interests. I enjoy long-distance running, as well as sports like cricket and tennis, mainly because they really help me to clear my mind and think better. I enjoy activities that stimulate my brain mentally, such as reading, playing chess and playing the piano. One of my favourite hobbies, though, is astrophotography. I’ve had a love for space and astronomy ever since I could comprehend what it was. The time and patience it requires is well worth it, considering you can eventually capture images of the moon, stars and planets and share it with the world. I also do this in the hope that I can arouse interest in others about the marvels of space and astronomy that we ignore in our day-to-day lives.”

Hritik Mitha won a USAID Science for Development Second Place Award of US$3 000 for his project ‘Improving the harnessing of solar energy using a hybrid photovoltaic thermal system’. Hritik modified lab-scale solar panels by adding front and back water cooling, using low-cost commercially available materials, to extract the thermal energy that would otherwise be dissipated as waste heat. Since this heat has an adverse impact on the solar panel’s electrical performance and lifespan, the overall energy efficiency of the solar panels was significantly increased. Runè Edeling (left), from Eunice High School in the Free State, won a Fourth Place Award of US$500 in the physics and astronomy category for her project ‘Using dimple technology to optimise the aerodynamics of heavy motor vehicles’. The project investigates how golf-ball style dents, or dimples, applied on certain areas of the bodywork of a truck can be used to decrease aerodynamic drag so as to increase fuel efficiency and cost-effectiveness. Chris Ayers/Society for Science & the Public)

Congratulations Hritik, and all the best for your future endeavours!

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Shaziyah Laher (right) from Nizamiye Al Azhar Institute in the Eastern Cape, won a Fourth Place Award of US$500 in the chemistry category for her project ‘Organic biodegradable alternative to plastic’. The project investigated a more eﬃcient way of making and disposing of plastic that is less harmful towards humans, animals and the environment. The results of the experiment produced a transparent, strong, biodegradable polymer.

Quest Vol. 15 No. 3 | 2019

NEWS | MATH-ART

Math-Art

steams ahead You’ve probably heard of STEM – the acronym for Science, Technology, Engineering and Maths – but what about STEAM? It’s the Arts that put the A into the acronym, and STEAM is part of a global trend in education to encourage learners to seek creative solutions to realworld problems. The Govan Mbeki Mathematics Development Centre (GMMDC) at Nelson Mandela University is promoting STEAM in South African classrooms, and recently held its second annual Math-Art Competition to encourage learners to recognise mathematics in the world around them. “Through this competition, we wanted learners to discover the links between maths and art, as this will form a major part of future careers in this Fourth Industrial Revolution, where digital innovation is changing how we do things,” said competition coordinator Carine Steyn. The competition, which was launched and run in the Eastern Cape in 2018, was extended to include all provinces in 2019. It was open to learners from Grade 8 to 12, who could enter artworks in two categories – Maths in Nature or Maths in Manmade Designs.

Winner, Maths in Manmade Designs (Grade 8 and 9): Caitlin Wilde of Fish Hoek High in Cape Town for Heritage Mandala, depicting traditional Zulu patterns.

The artworks could incorporate any visual medium, including photography, drawing, painting, collage or mixed media, and each had to be accompanied by a written explanation, describing how it linked to maths. Some 600 entries were received from high schools across the country. The top three entrants in each category were announced at a prize-giving at the Nelson Mandela Metropolitan Art Museum in June, and all received cash vouchers and book prizes. Partnering with GMMDC for the 2019 competition were the Department of Basic Education (Eastern Cape), Umalusi (the Council for Quality Assurance in General and Further Education and Training), the South African Mathematics Foundation (SAMF), the Centre for the Advancement of Science and Mathematics Education (CASME), the University of the Free State, Kutlwanong Centre for Maths, Science and Technology, the Independent Schools Association of South Africa (Isasa) and Curro Schools.

The winners in the GMMDC National Math-Art competition were from schools in Johannesburg, Bloemfontein, Durban, East London, Cape Town, Paarl, Port Elizabeth and Makhanda (Grahamstown). 38

Quest Vol. 15 No. 3 | 2019

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MATH-ART | NEWS

Top left: Winner, Maths in Nature (Grade 10 to 12): Lauren Damstra from Eunice Girls High in Bloemfontein for her artwork Infinity, which used the vastness of outer space to represent “the terror of things we don’t know”. Above: Winner, Maths in Nature (Grade 8 and 9): Luke Ferreira from Redhill High in Johannesburg, for his exploration of mathematical tessellations and symmetry in his artwork Pale Face. Left: Winner, Maths in Manmade Designs (Grade 10 to 12): Morgan Durrheim from Beaconhurst High in East London. Her mixed-media artwork Hidden Mathematics showed “many examples of applying mathematics for our own benefit” in famous ancient and modern landmarks, from the Pyramids of Giza to Disneyland’s famous castle. Bottom left: Runner-up, Maths in Nature (Grade 10 to 12): Kara van Heerden from Framesby High in Port Elizabeth, for her artwork The functions of a zebra. She wrote: “Nature is filled with mathematics and the zebra’s body has always fascinated me with all its shapes and patterns. As I drew the zebra, I also noticed the mathematical functions. The Golden Ratio is also very visible in nature and I saw it in the hind part of the zebra. Mathematics sometimes seem impossible to do but as the feet of my zebra illustrate….a person must just start to unravel the problem. It then becomes easier and clearer and directs you on the right path.” Bottom right: Runner-up, Maths in Manmade Designs (Grade 10 to 12): Sibangani Matsa from the University of Johannesburg Metropolitan Academy, who chose to draw attention to the pending extinction of rhinos through poaching in his pencil sketch of a rhino constructed out of metal, titled Same Diﬀerence.

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Quest Vol. 15 No. 3 | 2019

Nectar-lapping lizards pollinate hidden flowers

Ruth Cozien & Steve Johnson

NEWS | POLLINATION

The flowers of Guthriea capensis, which grows at high elevation and in rocky terrain along the Drakensberg and Karoo escarpments, are strongly scented and produce copious nectar. But they are inconspicuous because they are green, like the leaves, plus they are borne at ground level, tucked away beneath the leaves – hence the plant’s common name, ‘hidden flower’. Researchers from the University of KwaZulu-Natal’s School of Life Sciences and the University of the Free State’s Afromontane Research Unit set out to identify the plant’s pollinator. They suspected that the ‘secret agent’ was a mouse, because a number of other plant species with flowers borne near ground level have been found to be pollinated by mice, rats, gerbils or elephant shrews. But they were proved wrong when footage from their motion-activated cameras – set up among a population of the plants below Sentinel Peak in the northern Drakensberg – revealed that mice displayed no interest in the flowers. Instead, the videos showed that Drakensberg crag lizards, Pseudocordylus subviridis, were the main

CURRICULUM CORNER LIFE SCIENCES: GRADE 11 Reproduction in plants: Pollination

Quest Vol. 15 No. 3 | 2019

Wikimedia Commons

Almost 90% of flowering plants are pollinated by animals, rather than wind or (very rarely) water. Most of this biotic pollination is by flying insects, although the other types of flying animals – birds and bats – are important pollinators of certain species. Plants that rely on insect pollinators typically attract them with brightly coloured and strongly scented flowers. By contrast, those that depend on birds have brightly coloured but odourless flowers, while those that seek to attract bats have strong odours and large, pale-coloured flowers that stand out from their dark surroundings at night.

visitors, lapping nectar for up to 40 seconds per flower. In the process, pollen stuck to their snouts, with some inevitably transferred to other flowers. Experimentally excluding lizards by caging the plants resulted in a 95% decline in the number of seeds produced. Internationally, the first records of lizards visiting flowers date back to the 1970s, from Madeira Island, and more than 40 reptile species have since been shown to engage in the practice, mainly on other oceanic islands. Most lizards are primarily insectivorous, but energy-rich nectar would be a valuable ‘dietary supplement’ in harsh environments. The Drakensberg crag lizard is likely attracted to the hidden flowers by their strong scent, found through chemical analysis to contain compounds that are highly unusual in the plant kingdom. These may account for the nectar’s bitter taste, which is probably why mice show no interest in the flowers. • Cozien RJ, Van der Niet T, Johnson SD, Steenhuisen S-L. Saurian surprise: lizards pollinate South Africa’s enigmatic Hidden Flower. Ecology. Doi: 10.1002/ecy.2670 QUESTONLINE.ORG.ZA

DETERMINED |FEATURE

Books Field Guide to the Frogs & oth other Amphibians of Afric Africa By Alan Channing & Ma Mark-Oliver Rödel. 407 pp. Struik Nature. R400 This book represents an extraordinary feat, because it covers all 815 species of amphibians – 788 frogs, 23 caecilians and four salamanders – that have been described from the African continent, the first guide ever to do so. Depicting all these species was made possible by the more than 100 friends and colleagues of the authors who contributed photographs. These reveal a fascinating variety of frogs and toads, from the cute and colourful to rather ugly, warty specimens that even the most desperate handsome prince-seeker would not want to kiss! The book adheres to the classic field guide format, with species entries on the left and colour plates of photographs on the right. Each species is described in terms of its common and species name, identifying features, distribution, habitat, advertisement call, biology and conservation status. There is also an introductory section, covering the biology and ecology of amphibians, and tips on finding and handling them.

Field Guide to Mushrooms & other Fungi of South Africa Gary B Goldman & Marieka Gryzenhout. 360 pp. Struik Nature. R370 For thos those who want to gather ‘w ‘wild’ mushrooms to eat, bein being able to identify accurately is vital, species a because getting it wrong could b be deadly, given the toxicity of some examples. But there are many naturalists who just want to be able to put names to the interesting fungi they might see or photograph on their favourite walking trails. This book caters for both target groups, covering everything from fairy ring-forming mushrooms to brackets, puﬀ balls, stinkhorns, corals, jellies and more. It features 200 of South Africa’s most distinctive and conspicuous fungal species, each described in detail with notes on its ecology, distribution, habitat, edibility and any similar species with which it might be confused. Many of the species have an entire double-page spread devoted to them, with photographs taken from a number of diﬀerent angles to aid identification. Apart from these species accounts, there is an introduction outlining the basic anatomy and biology of mushrooms and their role in nature, as well as guidelines to foraging for and photographing them.

A Guide to Dragonflies & Damselflies of South Africa By Warwick & Michèle Tarboton. 224 pp. Struik Nature. R310 310 Dragonflies dart about so quickly that it would be impossible for most of us to identify them in flight, butt fortunately they often settle in one spot long enough for us to photograph. Then, with the help of this book, t, putting a name to the species shouldn’t be too diﬃcult, because clear photographs are provided of the 164 uth dragonfly and damselfly species known to occur in South Africa, Lesotho and Swaziland, along with information on their size, identifying features and occurrence. Apart from photographs of each species in its natural environment, there are colour plates showing key ng diagnostic features for identification, and distinguishing y characteristics for males and females. An introductory y section covers aspects like life cycle, behaviour, biology and breeding, and includes some useful guidelines to make identification easier.

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Overall, the guide – a revised and updated e edition of a book first p published in 2015 – is b both attractive and userfr friendly. And who knew tha that these insects had suc such evocative and lyrical nam names, such as Dancing Jewe Jewel, Springwater Sprite, Frien Friendly Hawker, Gracious Wisp Wisp, Deceptive Widow, Phant Phantom Flutterer, Smoky Duskd Duskdarter, Denim Dropwing and El Elusive Skimmer?

Quest Vol. 15 No. 3 | 2019

PUZZLES

Test your knowledge 1

Most of the answers can be found in this issue of Quest.

QUEST MATHS PUZZLE NO. 50

2 3 5

9 5

Fudge pieces R2.00

Chocolate cake slices R3.00

Large bubblegum block R0.48

8 10 9

12 14

Answer to Maths Puzzle no. 49: 2688 15

19 20

1. One of the National Air Quality Priority Areas 2. Something that is unusual or not normal 3. List of threatened species 4. On the scale of atoms, electrons and photons 5. Glucose is one 6. His thought-experiment involves a cat 7. Describes our galaxy 8. Name for someone awarded the Nobel Prize 9. Gives cell walls their strength 10. The Padrón …. was a map made in the 1500s 11. Term used to describe genetic code 12. An acronym that represents art and science 13. South Africa’s air pollution law 14. Rotating stars that emit radio waves 15. He completed the first global circumnavigation 16. Indigenous knowledge abbreviation 17. A reptile pollinator 18. The direction Magellan sailed from Spain 19. The prefix describing extremely cold atoms 20. A type of toad 21. A data and memory unit 22. A global health organisation 42

Quest Vol. 15 No. 3 | 2019

WIN A PRIZE! Send us your answer (fax, e-mail or snail-mail) together with your name and contact details by 15:00 on 31 October 2019.

Across

More chocolate cake slices were sold than fudge.

How many large bubblegum blocks were sold?

At a market, 500 items were sold for a total of R500. The prices were as follows:

Down 1. The Lindau meetings end with a boat trip to this island 2. A kind of telescope 3. This ship completed the first global circumnavigation 4. A stand-in for a real shark 5. The theme of this issue of Quest 6. The mathematical term for an instruction 7. A radio telescope with an animal’s name 8. Opposite of indigenous 9. AI refers to this 10. Plants do this together to attract pollinators 11. A network that emulates the brain 12. Prefix for solid matter with liquid properties 13. A unicellular fungus 14. Refers to outside air quality 15. A passage connecting two seas 16. South Africa’s largest telescope project 17. A super ___ is an exploding star 18. Magellanic Clouds are these galaxy types 19. Ecologists do this in surveys 20. Lindau meeting acronym 21. A device to measure cardiovascular health

THE FIRST CORRECT ENTRY THAT WE OPEN WILL BE THE LUCKY WINNER. WE’LL SEND YOU A COOL ‘TRULY SCIENTIFIC’ CALCULATOR! Mark your answer ‘Quest Maths Puzzle no. 50’ and send it to: Fax: 0866 710 953 E-mail: livmath@ iafrica.com. Snailmail: Quest Maths Puzzle, Living Maths, P.O. Box 195, Bergvliet, 7864, Cape Town, South Africa

For more on Living Maths phone 083 308 3883 and visit www.livingmaths.com

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