Duke Research Blog

Following the people and events that make up the research community at Duke.

Category: Visualization (Page 1 of 7)

Durham Traffic Data Reveal Clues to Safer Streets

Ghost bikes are a haunting site. The white-painted bicycles, often decorated with flowers or photographs, mark the locations where cyclists have been hit and killed on the street.

A white-painted bike next to a street.

A Ghost Bike located in Chapel Hill, NC.

Four of these memorials currently line the streets of Durham, and the statistics on non-fatal crashes in the community are equally sobering. According to data gathered by the North Carolina Department of Transportation, Durham county averaged 23 bicycle and 116 pedestrian crashes per year between 2011 and 2015.

But a team of Duke researchers say these grim crash data may also reveal clues for how to make Durham’s streets safer for bikers, walkers, and drivers.

This summer, a team of Duke students partnered with Durham’s Department of Transportation to analyze and map pedestrian, bicycle and motor vehicle crash data as part of the 10-week Data+ summer research program.

In the Ghost Bikes project, the team created an interactive website that allows users to explore how different factors such as the time-of-day, weather conditions, and sociodemographics affect crash risk. Insights from the data also allowed the team to develop policy recommendations for improving the safety of Durham’s streets.

“Ideally this could help make things safer, help people stay out of hospitals and save lives,” said Lauren Fox, a Duke cultural anthropology major who graduated this spring, and a member of the DATA+ Ghost Bikes team.

A map of Durham county with dots showing the locations of bicycle crashes

A heat map from the team’s interactive website shows areas with the highest density of bicycle crashes, overlaid with the locations of individual bicycle crashes.

The final analysis showed some surprising trends.

“For pedestrians the most common crash isn’t actually happening at intersections, it is happening at what is called mid-block crossings, which happen when someone is crossing in the middle of the road,” Fox said.

To mitigate the risks, the team’s Executive Summary includes recommendations to install crosswalks, median islands and bike lanes to roads with a high density of crashes.

They also found that males, who make up about two-thirds of bicycle commuters over the age of 16, are involved in 75% of bicycle crashes.

“We found that male cyclists over age 16 actually are hit at a statistically higher rate,” said Elizabeth Ratliff, a junior majoring in statistical science. “But we don’t know why. We don’t know if this is because males are riskier bikers, if it is because they are physically bigger objects to hit, or if it just happens to be a statistical coincidence of a very unlikely nature.”

To build their website, the team integrated more than 20 sets of crash data from a wide variety of different sources, including city, county, regional and state reports, and in an array of formats, from maps to Excel spreadsheets.

“They had to fit together many different data sources that don’t necessarily speak to each other,” said faculty advisor Harris Solomon, an associate professor of cultural anthropology and global health at Duke.  The Ghost Bikes project arose out of Solomon’s research on traffic accidents in India, supported by the National Science Foundation Cultural Anthropology Program.

In Solomon’s Spring 2017 anthropology and global health seminar, students explored the role of the ghost bikes as memorials in the Durham community. The Data+ team approached the same issues from a more quantitative angle, Solomon said.

“The bikes are a very concrete reminder that the data are about lives and deaths,” Solomon said. “By visiting the bikes, the team was able to think about the very human aspects of data work.”

“I was surprised to see how many stakeholders there are in biking,” Fox said. For example, she added, the simple act of adding a bike lane requires balancing the needs of bicyclists, nearby residents concerned with home values or parking spots, and buses or ambulances who require access to the road.

“I hadn’t seen policy work that closely in my classes, so it was interesting to see that there aren’t really simple solutions,” Fox said.

[youtube https://www.youtube.com/watch?v=YHIRqhdb7YQ&w=629&h=354]

 

Data+ is sponsored by Bass Connections, the Information Initiative at Duke, the Social Science Research Institute, the departments of Mathematics and Statistical Science and MEDx.

Other Duke sponsors include DTECH, Duke Health, Sanford School of Public Policy, Nicholas School of the Environment, Development and Alumni Affairs, Energy Initiative, Franklin Humanities Institute, Duke Institute for Brain Sciences, Office for Information Technology and the Office of the Provost, as well as the departments of Electrical & Computer Engineering, Computer Science, Biomedical Engineering, Biostatistics & Bioinformatics and Biology.

Government funding comes from the National Science Foundation. Outside funding comes from Accenture, Academic Analytics, Counter Tools and an anonymous donation.

Community partnerships, data and interesting problems come from the Durham Police Department, Durham Neighborhood Compass, Cary Institute of Ecosystem Studies, Duke Marine Lab, Center for Child and Family Policy, Northeast Ohio Medical University, TD Bank, Epsilon, Duke School of Nursing, University of Southern California, Durham Bicycle and Pedestrian Advisory Commission, Duke Surgery, MyHealth Teams, North Carolina Museum of Art and Scholars@Duke.

Writing by Kara Manke; video by Lauren Mueller and Summer Dunsmore

Pinpointing Where Durham’s Nicotine Addicts Get Their Fix

DURHAM, N.C. — It’s been five years since Durham expanded its smoking ban beyond bars and restaurants to include public parks, bus stops, even sidewalks.

While smoking in the state overall may be down, 19 percent of North Carolinians still light up, particularly the poor and those without a high school or college diploma.

Among North Carolina teens, consumption of electronic cigarettes in particular more than doubled between 2013 and 2015.

Now, new maps created by students in the Data+ summer research program show where nicotine addicts can get their fix.

Studies suggest that tobacco retailers are disproportionately located in low-income neighborhoods.

Living in a neighborhood with easy access to stores that sell tobacco makes it easier to start young and harder to quit.

The end result is that smoking, secondhand smoke exposure, and smoking-related diseases such as lung cancer, are concentrated among the most socially disadvantaged communities.

If you’re poor and lack a high school or college diploma, you’re more likely to live near a store that sells tobacco.

If you’re poor and lack a high school or college diploma, you’re more likely to live near a store that sells tobacco. Photo from Pixabay.

Where stores that sell tobacco are located matters for health, but for many states such data are hard to come by, said Duke statistics major James Wang.

Tobacco products bring in more than a third of in-store sales revenue at U.S. convenience stores — more than food, beverages, candy, snacks or beer. Despite big profits, more than a dozen states don’t require businesses to get a special license or permit to sell tobacco. North Carolina is one of them.

For these states, there is no convenient spreadsheet from the local licensing agency identifying all the businesses that sell tobacco, said Duke undergraduate Nikhil Pulimood. Previous attempts to collect such data in Virginia involved searching for tobacco retail stores by car.

“They had people physically drive across every single road in the state to collect the data. It took three years,” said team member and Duke undergraduate Felicia Chen.

Led by UNC PhD student in epidemiology Mike Dolan Fliss, the Duke team tried to come up with an easier way.

Instead of collecting data on the ground, they wrote an automated web-crawler program to extract the data from the Yellow Pages websites, using a technique called Web scraping.

By telling the software the type of business and location, they were able to create a database that included the names, addresses, phone numbers and other information for 266 potential tobacco retailers in Durham County and more than 15,500 statewide, including chains such as Family Fare, Circle K and others.

Map showing the locations of tobacco retail stores in Durham County, North Carolina.

Map showing the locations of tobacco retail stores in Durham County, North Carolina.

When they compared their web-scraped data with a pre-existing dataset for Durham County, compiled by a nonprofit called Counter Tools, hundreds of previously hidden retailers emerged on the map.

To determine which stores actually sold tobacco, they fed a computer algorithm data from more than 19,000 businesses outside North Carolina so it could learn how to distinguish say, convenience stores from grocery stores. When the algorithm received store names from North Carolina, it predicted tobacco retailers correctly 85 percent of the time.

“For example we could predict that if a store has the word “7-Eleven” in it, it probably sells tobacco,” Chen said.

As a final step, they also crosschecked their results by paying people a small fee to search for the stores online to verify that they exist, and call them to ask if they actually sell tobacco, using a crowdsourcing service called Amazon Mechanical Turk.

Ultimately, the team hopes their methods will help map the more than 336,000 tobacco retailers nationwide.

“With a complete dataset for tobacco retailers around the nation, public health experts will be able to see where tobacco retailers are located relative to parks and schools, and how store density changes from one neighborhood to another,” Wang said.

The team presented their work at the Data+ Final Symposium on July 28 in Gross Hall.

Data+ is sponsored by Bass Connections, the Information Initiative at Duke, the Social Science Research Institute, the departments of mathematics and statistical science and MEDx. This project team was also supported by Counter Tools, a non-profit based in Carrboro, NC.

Writing by Robin Smith; video by Lauren Mueller and Summer Dunsmore

Sizing Up Hollywood's Gender Gap

DURHAM, N.C. — A mere seven-plus decades after she first appeared in comic books in the early 1940s, Wonder Woman finally has her own movie.

In the two months since it premiered, the film has brought in more than $785 million worldwide, making it the highest grossing movie of the summer.

But if Hollywood has seen a number of recent hits with strong female leads, from “Wonder Woman” and “Atomic Blonde” to “Hidden Figures,” it doesn’t signal a change in how women are depicted on screen — at least not yet.

Those are the conclusions of three students who spent ten weeks this summer compiling and analyzing data on women’s roles in American film, through the Data+ summer research program.

The team relied on a measure called the Bechdel test, first depicted by the cartoonist Alison Bechdel in 1985.

Bechdel test

The “Bechdel test” asks whether a movie features at least two women who talk to each other about anything besides a man. Surprisingly, a lot of films fail. Art by Srravya [CC0], via Wikimedia Commons.

To pass the Bechdel test, a movie must satisfy three basic requirements: it must have at least two named women in it, they must talk to each other, and their conversation must be about something other than a man.

It’s a low bar. The female characters don’t have to have power, or purpose, or buck gender stereotypes.

Even a movie in which two women only speak to each other briefly in one scene, about nail polish — as was the case with “American Hustle” —  gets a passing grade.

And yet more than 40 percent of all U.S. films fail.

The team used data from the bechdeltest.com website, a user-compiled database of over 7,000 movies where volunteers rate films based on the Bechdel criteria. The number of criteria a film passes adds up to its Bechdel score.

“Spider Man,” “The Jungle Book,” “Star Trek Beyond” and “The Hobbit” all fail by at least one of the criteria.

Films are more likely to pass today than they were in the 1970s, according to a 2014 study by FiveThirtyEight, the data journalism site created by Nate Silver.

The authors of that study analyzed 1,794 movies released between 1970 and 2013. They found that the number of passing films rose steadily from 1970 to 1995 but then began to stall.

In the past two decades, the proportion of passing films hasn’t budged.

Since the mid-1990s, the proportion of films that pass the Bechdel test has flatlined at about 50 percent.

Since the mid-1990s, the proportion of films that pass the Bechdel test has flatlined at about 50 percent.

The Duke team was also able to obtain data from a 2016 study of the gender breakdown of movie dialogue in roughly 2,000 screenplays.

Men played two out of three top speaking roles in more than 80 percent of films, according to that study.

Using data from the screenplay study, the students plotted the relationship between a movie’s Bechdel score and the number of words spoken by female characters. Perhaps not surprisingly, films with higher Bechdel scores were also more likely to achieve gender parity in terms of speaking roles.

“The Bechdel test doesn’t really tell you if a film is feminist,” but it’s a good indicator of how much women speak, said team member Sammy Garland, a Duke sophomore majoring in statistics and Chinese.

Previous studies suggest that men do twice as much talking in most films — a proportion that has remained largely unchanged since 1995. The reason, researchers say, is not because male characters are more talkative individually, but because there are simply more male roles.

“To close the gap of speaking time, we just need more female characters,” said team member Selen Berkman, a sophomore majoring in math and computer science.

Achieving that, they say, ultimately comes down to who writes the script and chooses the cast.

The team did a network analysis of patterns of collaboration among 10,000 directors, writers and producers. Two people are joined whenever they worked together on the same movie. The 13 most influential and well-connected people in the American film industry were all men, whose films had average Bechdel scores ranging from 1.5 to 2.6 — meaning no top producer is regularly making films that pass the Bechdel test.

“What this tells us is there is no one big influential producer who is moving the needle. We have no champion,” Garland said.

Men and women were equally represented in fewer than 10 percent of production crews.

But assembling a more gender-balanced production team in the early stages of a film can make a difference, research shows. Films with more women in top production roles have female characters who speak more too.

“To better represent women on screen you need more women behind the scenes,” Garland said.

Dollar for dollar, making an effort to close the Hollywood gender gap can mean better returns at the box office too. Films that pass the Bechdel test earn $2.68 for every dollar spent, compared with $2.45 for films that fail — a 23-cent better return on investment, according to FiveThirtyEight.

Other versions of the Bechdel test have been proposed to measure race and gender in film more broadly. The advantage of analyzing the Bechdel data is that thousands of films have already been scored, said English major and Data+ team member Aaron VanSteinberg.

“We tried to watch a movie a week, but we just didn’t have time to watch thousands of movies,” VanSteinberg said.

A new report on diversity in Hollywood from the University of Southern California suggests the same lack of progress is true for other groups as well. In nearly 900 top-grossing films from 2007 to 2016, disabled, Latino and LGBTQ characters were consistently underrepresented relative to their makeup in the U.S. population.

Berkman, Garland and VanSteinberg were among more than 70 students selected for the 2017 Data+ program, which included data-driven projects on photojournalism, art restoration, public policy and more.

They presented their work at the Data+ Final Symposium on July 28 in Gross Hall.

Data+ is sponsored by Bass Connections, the Information Initiative at Duke, the Social Science Research Institute, the departments of mathematics and statistical science and MEDx. 

Writing by Robin Smith; video by Lauren Mueller and Summer Dunsmore

Mapping Electricity Access for a Sixth of the World's People

DURHAM, N.C. — Most Americans can charge their cell phones, raid the fridge or boot up their laptops at any time without a second thought.

Not so for the 1.2 billion people — roughly 16 percent of the world’s population — with no access to electricity.

Despite improvements over the past two decades, an estimated 780 million people will still be without power by 2030, especially in rural parts of sub-Saharan Africa, Asia and the Pacific.

To get power to these people, first officials need to locate them. But for much of the developing world, reliable, up-to-date data on electricity access is hard to come by.

Researchers say remote sensing can help.

For ten weeks from May through July, a team of Duke students in the Data+ summer research program worked on developing ways to assess electricity access automatically, using satellite imagery.

“Ground surveys take a lot of time, money and manpower,” said Data+ team member Ben Brigman. “As it is now, the only way to figure out if a village has electricity is to send someone out there to check. You can’t call them up or put out an online poll, because they won’t be able to answer.”

India at night

Satellite image of India at night. Large parts of the Indian countryside still aren’t connected to the grid, but remote sensing, machine learning could help pinpoint people living without power. Credits: NASA Earth Observatory images by Joshua Stevens, using Suomi NPP VIIRS data from Miguel Román, NASA’s Goddard Space Flight Center

Led by researchers in the Energy Data Analytics Lab and the Sustainable Energy Transitions Initiative, “the initial goal was to create a map of India, showing every village or town that does or does not have access to electricity,” said team member Trishul Nagenalli.

Electricity makes it possible to pump groundwater for crops, refrigerate food and medicines, and study or work after dark. But in parts of rural India, where Nagenalli’s parents grew up, many households use kerosene lamps to light homes at night, and wood or animal dung as cooking fuel.

Fires from overturned kerosene lamps are not uncommon, and indoor air pollution from cooking with solid fuels contributes to low birth weight, pneumonia and other health problems.

In 2005, the Indian government set out to provide electricity to all households within five years. Yet a quarter of India’s population still lives without power.

Ultimately, the goal is to create a machine learning algorithm — basically a set of instructions for a computer to follow — that can recognize power plants, irrigated fields and other indicators of electricity in satellite images, much like the algorithms that recognize your face on Facebook.

Rather than being programmed with specific instructions, machine learning algorithms “learn” from large amounts of data.

This summer the researchers focused on the unsung first step in the process: preparing the training data.

Phoenix power plant

Satellite image of a power plant in Phoenix, Arizona

Fellow Duke students Gouttham Chandrasekar, Shamikh Hossain and Boning Li were also part of the effort. First they compiled publicly available satellite images of U.S. power plants. Rather than painstakingly framing and labeling the plants in each photo themselves, they tapped the powers of the Internet to outsource the task and hired other people to annotate the images for them, using a crowdsourcing service called Amazon Mechanical Turk.

So far, they have collected more than 8,500 image annotations of different kinds of power plants, including oil, natural gas, hydroelectric and solar.

The team also compiled firsthand observations of the electrification rate for more than 36,000 villages in the Indian state of Bihar, which has one of the lowest electrification rates in the country. For each village, they also gathered satellite images showing light intensity at night, along with density of green land and other indicators of irrigated farms, as proxies for electricity consumption.

Using these data sets, the goal is to develop a computer algorithm which, through machine learning, teaches itself to detect similar features in unlabeled images, and distinguishes towns and villages that are connected to the grid from those that aren’t.

“We would like to develop our final algorithm to essentially go into a developing country and analyze whether or not a community there has access to electricity, and if so what kind,” Chandrasekar said.

Electrification map of Bihar, India

The proportion of households connected to the grid in more than 36,000 villages in Bihar, India

The project is far from finished. During the 2017-2018 school year, a Bass Connections team will continue to build on their work.

The summer team presented their research at the Data+ Final Symposium on July 28 in Gross Hall.

Data+ is sponsored by Bass Connections, the Information Initiative at Duke, the Social Science Research Institute, the departments of mathematics and statistical science and MEDx. This project team was also supported by the Duke University Energy Initiative.

Writing by Robin Smith; video by Lauren Mueller and Summer Dunsmore

From Solid to Liquid and Back Again

A black and white moving image of a ball being pulled out from under a pile of circular discs

Force chains erupt as an “intruder” is yanked from beneath a pile of circular discs, which are designed to simulate a granular material. The entire process takes less than one second. Credit: Yue Zhang, Duke University.

You can easily walk across the sand on a beach. But step into a ball pit, and chances are you’ll fall right through.

Sand and ball pits are both granular materials, or materials that are made of collections of much smaller particles or grains. Depending on their density and how much force they experience, granular materials sometimes behave like liquids — something you fall right through — and sometimes “jam” into solids, making them something you can stand on.

“In some cases, these little particles have figured out how to actually form solid-like structures,” said Robert P. Behringer, James B. Duke Professor of Physics. “So why don’t they always just go squirting sideways and relax all the stress?”

Physicists do not yet understand exactly when and how jamming occurs, but Behringer’s team at Duke is on the case. The group squishes, stretches, hits, and pulls at granular materials to get a better picture of how and why they behave like they do. The team recently presented a whopping 10 papers at the 2017 Powders and Grains Conference, which occurred from July 3-7, 2017 in Montpellier, France.

Many of these studies use one of the lab’s favorite techniques, which is to create granular materials from small transparent discs that are about half an inch to an inch in diameter. These discs are made of a material which, thanks to the special way it interacts with light, changes color when squished. This effect allows the team to watch how the stress within the material changes as various forces are applied.

A blue and green moving image of spinning discs

As the wheels turn, shear strain between the discs creates a dense web of inter-particle forces. Credit: Yiqiu Zhao, Duke University.

In one experiment, graduate student Yue Zhang used a high-speed camera to catch the stress patterns as a ball on a string is yanked out from a pile of these discs. In the video, the ball first appears to be stuck under the pile, and then suddenly gives way after enough force is applied — not unlike what you might experience pulling a tent stake out of the ground, or opening the lid on a pesky pickle jar.

“The amusing thing is that you start trying to pull, you add more force, you add more force, and then at some point you pull so hard that you hit yourself in the head,” Behringer said.

The team was surprised to find that the stress patterns created by the ball, which Behringer says look “like hair all standing on end,” are almost identical to the stress of impact, only in reverse.

“What you see is even though you are just gradually gradually pulling harder and harder, the final dynamics are in some sense the same dynamics that you get on impact,” Behringer said.

In another experiment, the team examined what happens in granular materials under shear strain, which is similar to the force your fingers exert on one another when you rub them together.

Graduate student Yiqiu Zhao placed hundreds of these discs onto a circular platform made of a series of flat, concentric rings, each of which is controlled by a separate motor. As the rings turn at different speeds, the particles rub against one another, creating a shear stress.

An image of an experimental set up in a lab

Beneath the small transparent discs lie a series of concentric wheels, each attached to its own motor. By turning these platforms at different speeds, Yiqiu Zhao can observe how shear strain affects the discs.

“We have about twenty stepper motors here, so that we can rotate all the rings to apply a shear not only from the outside boundary, but also from everywhere inside the bulk of the material,” Zhao said. This ensures that each particle in the circle experiences a similar amount of shear.

“One of the key intents of this new experiment was to find a way that we could shear until the cows come home,” Behringer said. “And if it takes a hundred times more shear than I could get with older experiments, well we’ll get it.”

As the rings turn, videos of the material show forces snaking out from the inner circle like lightning bolts. They found that by applying enough shear, it is possible to make the material like a solid at much lower densities than had been seen before.

“You can actually turn a granular fluid into a granular solid by shearing it,” Behringer said. “So it is like you don’t put your ice in the refrigerator, you put it in one of these trays and you shear the tray and it turns into ice.”

Kara J. Manke, PhDPost by Kara Manke

3D Virus Cam Catches Germs Red-Handed

A 3D plot of a virus wiggling around

The Duke team used their 3D virus cam to spy on this small lentivirus as it danced through a salt water solution.

Before germs like viruses can make you sick, they first have to make a landing on one of your cells — Mars Rover style — and then punch their way inside.

A team of physical chemists at Duke is building a microscope so powerful that it can spot these minuscule germs in the act of infection.

The team has created a new 3D “virus cam” that can spy on tiny viral germs as they wriggle around in real time. In a video caught by the microscope, you can watch as a lentivirus bounces and jitters through an area a little wider that a human hair.

Next, they hope to develop this technique into a multi-functional “magic camera” that will let them see not only the dancing viruses, but also the much larger cell membranes they are trying breech.

“Really what we are trying to investigate is the very first contacts of the virus with the cell surface — how it calls receptors, and how it sheds its envelope,” said group leader Kevin Welsher, assistant professor of chemistry at Duke. “We want to watch that process in real time, and to do that, we need to be able to lock on to the virus right from the first moment.”

A 3D plot spells out the name "Duke"

To test out the microscope, the team attached a fluorescent bead to a motion controller and tracked its movements as it spelled out a familiar name.

This isn’t the first microscope that can track real-time, 3D motions of individual particles. In fact, as a postdoctoral researcher at Princeton, Welsher built an earlier model and used it to track a bright fluorescent bead as it gets stuck in the membrane of a cell.

But the new virus cam, built by Duke postdoc Shangguo Hou, can track particles that are faster-moving and dimmer compared to earlier microscopes. “We were trying to overcome a speed limit, and we were trying to do so with the fewest number of photons collected possible,” Welsher said.

The ability to spot dimmer particles is particularly important when tracking viruses, Welsher said. These small bundles of proteins and DNA don’t naturally give off any light, so to see them under a microscope, researchers first have to stick something fluorescent on them. But many bright fluorescent particles, such as quantum dots, are pretty big compared to the size of most viruses. Attaching one is kind of like sticking a baseball onto a basketball – there is a good chance it might affect how the virus moves and interacts with cells.

The new microscope can detect the fainter light given off by much smaller fluorescent proteins – which, if the virus is a basketball, are approximately the size of a pea. Fluorescent proteins can also be inserted to the viral genome, which allows them to be incorporated into the virus as it is being assembled.

“That was the big move for us,” Welsher said, “We didn’t need to use a quantum dot, we didn’t need to use an artificial fluorescent bead. As long as the fluorescent protein was somewhere in the virus, we could spot it.” To create their viral video, Welsher’s team enlisted Duke’s Viral Vector Core to insert a yellow fluorescent protein into their lentivirus.

Now that the virus-tracking microscope is up-and-running, the team is busy building a laser scanning microscope that will also be able to map cell surfaces nearby. “So if we know where the particle is, we can also image around it and reconstruct where the particle is going,” Welsher said. “We hope to adapt this to capturing viral infection in real time.”

Robust real-time 3D single-particle tracking using a dynamically moving laser spot,” Shangguo Hou, Xiaoqi Lang and Kevin Welsher. Optics Letters, June 15, 2017. DOI: 10.1364/OL.42.002390

Kara J. Manke, PhDPost by Kara Manke

Immerse Yourself in Virtual Reality on the Quad

Open since September 2016, the Virtual Reality Room on the first floor lounge of Edens 1C allows students to experience virtual reality using the HTC Vive headset and controllers.

DURHAM, N.C. — The virtual reality headset looked like something out of a science fiction film. It was tethered by a long cable to a glass-encased PC, which in turn was connected to thick hoses filled with glowing blue coolant.

I slipped the mask over my head and was literally transported to another world.

In real life, I was in the lower level of Edens residence hall testing out the recently opened BoltVR gaming room during an event hosted by the Duke Digital Initiative (DDI). Virtual reality is one of the technologies that DDI is exploring for its potential in teaching and learning.

Rebekkah Huss shoots invaders with a virtual bow and arrow in Duke's newest virtual reality space.

Rebekkah Huss shoots invaders with a virtual bow and arrow in Duke’s newest virtual reality space. Open to students 4 p.m. to 10 p.m. on weekdays, noon to midnight on weekends.

BoltVR is a virtual reality space outfitted with the immersive room-scale technology of the HTC Vive, an $800 gaming system consisting of the headset, hand-held controllers and motion sensors in the room. The VR experience is a new addition to the Bolt gaming suite that opened in 2015 for Duke students.

Once I had the headset on, suddenly the bare walls and carpet were replaced by the yellow lined grid of the Holodeck from Star Trek. It was like nothing I’d ever seen. This is like the home screen for the gaming system, explained  Mark-Everett McGill the designer of the BoltVR game room, as he scrolled through the more than 70 downloaded VR experiences on the BoltVR online account at Steam.

McGill chose a story experience so that I could adjust to being able to move around physical objects in a virtual space.

It was like the floor melted away. On a tiny asteroid in front of me The Little Prince and his rose played out their drama from the cover of the classic children’s book. The stars surrounded me and I tilted my head back to watch a giant planet fly over.

I could walk around the prince’s tiny asteroid and inspect the little world from all angles, but I found it disorienting to walk with normal stability while my eyes told me that I was floating in space. The HTC Vive has a built-in  guidance system called the Chaperone that used a map of the room to keep me from crashing into the walls, I still somehow managed to bump a spectator.

“A lot of people get motion sickness when they use VR because your eyes are sensing the movement but your ears are telling you, you aren’t doing anything.” said, McGill.

Lucky for me, I have a strong stomach and suffered no ill effects while wearing the headset. The HTC Vive also helps counteract motion sickness because is room scale design allows for normal walking and movement.

There was however, one part of the experience that felt very odd, and that was the handheld controllers. The controllers  are tracked by wall-mounted sensors so they show up really well in the VR headset. The problem was that in the titles I played my hands and body were invisible to me.

The headset and controller themselves are incredibly sensitive and accurate. I think most people would intuitively understand how to use them, especially if they have a gaming background, but I missed having the comfort of my own arms. So while the VR worlds are visually believable and the technology powering them is absolutely fascinating, there is still lots of room for new innovations.

Once I started playing games though, I no longer cared about the limitations of the tech because I was having so much fun!

The most popular student choice in the BoltVR is a subgame of The Lab by Valve, it’s a simple tower defense game where the player uses a bow and arrow to shoot little 2D stickmen and stop their attack.

Everything about using the bow felt pretty realistic like loading arrows, and using angles to control the trajectory of a shot. There was even a torch that I used to light my arrow on fire before launching it at an attacker. With unlimited ammunition, I happily guarded my tower from waves of baddies until I finally had to let someone else have a turn.

To learn more about VR experiences for teaching and learning at Duke, join the listserv at https://lists.duke.edu/sympa/subscribe/vr2learn.

Post by Rebekkah Huss

Post by Rebekkah Huss

Cooking Up “Frustrated” Magnets in Search of Superconductivity

Sara Haravifard

A simplified version of Sara Haravifard’s recipe for new superconductors, by the National High Magnetic Field Laboratory

Duke physics professor Sara Haravifard is mixing, cooking, squishing and freezing “frustrated” magnetic crystals in search of the origins of superconductivity.

Superconductivity refers to the ability of electrons to travel endlessly through certain materials, called superconductors, without adding any energy — think of a car that can drive forever with no gas or electricity. And just the way gas-less, charge-less cars would make travel vastly cheaper, superconductivity has the potential to revolutionize electronics and energy industry.

But superconductors are extremely rare, and are usually only superconductive at extremely cold temperatures — too cold for any but a few highly specialized applications. A few “high-temperature” superconductors have been discovered, but scientists are still flummoxed at why and how these superconductors exist.

Haravifard hopes that her magnet experiments will reveal the origins of high-temperature superconductivity so that researchers can design and build new materials with this amazing property. In the process, her team may also discover materials that are useful in quantum computing, or even entirely new states of matter.

Learn more about their journey on this fascinating infographic by The National High Magnetic Field Laboratory.

Infographic describing magnetic crystal research

Infographic courtesy of the National High Magnetic Field Laboratory

Kara J. Manke, PhD

Post by Kara Manke

Visualizing the Fourth Dimension

Living in a 3-dimensional world, we can easily visualize objects in 2 and 3 dimensions. But as a mathematician, playing with only 3 dimensions is limiting, Dr. Henry Segerman laments.  An Assistant Professor in Mathematics at Oklahoma State University, Segerman spoke to Duke students and faculty on visualizing 4-dimensional space as part of the PLUM lecture series on April 18.

What exactly is the 4th dimension?

Let’s break down spatial dimensions into what we know. We can describe a point in 2-dimensional space with two numbers x and y, visualizing an object in the xy plane, and a point in 3D space with 3 numbers in the xyz coordinate system.

Plotting three dimensions in the xyz coordinate system.

While the green right-angle markers are not actually 90 degrees, we are able to infer the 3-dimensional geometry as shown on a 2-dimensional screen.

Likewise, we can describe a point in 4-dimensional space with four numbers – x, y, z, and w – where the purple w-axis is at a right angle to the other regions; in other words, we can visualize 4 dimensions by squishing it down to three.

Plotting four dimensions in the xyzw coordinate system.

One commonly explored 4D object we can attempt to visualize is known as a hypercube. A hypercube is analogous to a cube in 3 dimensions, just as a cube is to a square.

How do we make a hypercube?

To create a 1D line, we take a point, make a copy, move the copied point parallely to some distance away, and then connect the two points with a line.

Similarly, a square can be formed by making a copy of a line and connecting them to add the second dimension.

So, to create a hypercube, we move identical 3D cubes parallel to each other, and then connect them with four lines, as depicted in the image below.

To create an n–dimensional cube, we take 2 copies of the (n−1)–dimensional cube and connecting corresponding corners.

Even with a 3D-printed model, trying to visualize the hypercube can get confusing. 

How can we make a better picture of a hypercube? “You sort of cheat,” Dr. Segerman explained. One way to cheat is by casting shadows.

Parallel projection shadows, depicted in the figure below, are caused by rays of light falling at a  right angle to the plane of the table. We can see that some of the edges of the shadow are parallel, which is also true of the physical object. However, some of the edges that collide in the 2D cast don’t actually collide in the 3D object, making the projection more complicated to map back to the 3D object.

Parallel projection of a cube on a transparent sheet of plastic above the table.

One way to cast shadows with no collisions is through stereographic projection as depicted below.

The stereographic projection is a mapping (function) that projects a sphere onto a plane. The projection is defined on the entire sphere, except the point at the top of the sphere.

For the object below, the curves on the sphere cast shadows, mapping them to a straight line grid on the plane. With stereographic projection, each side of the 3D object maps to a different point on the plane so that we can view all sides of the original object.

Stereographic projection of a grid pattern onto the plane. 3D print the model at Duke’s Co-Lab!

Just as shadows of 3D objects are images formed on a 2D surface, our retina has only a 2D surface area to detect light entering the eye, so we actually see a 2D projection of our 3D world. Our minds are computationally able to reconstruct the 3D world around us by using previous experience and information from the 2D images such as light, shade, and parallax.

Projection of a 3D object on a 2D surface.

Projection of a 4D object on a 3D world

How can we visualize the 4-dimensional hypercube?

To use stereographic projection, we radially project the edges of a 3D cube (left of the image below) to the surface of a sphere to form a “beach ball cube” (right).

The faces of the cube radially projected onto the sphere.

Placing a point light source at the north pole of the bloated cube, we can obtain the projection onto a 2D plane as shown below.

Stereographic projection of the “beach ball cube” pattern to the plane. View the 3D model here.

Applied to one dimension higher, we can theoretically blow a 4-dimensional shape up into a ball, and then place a light at the top of the object, and project the image down into 3 dimensions.

Left: 3D print of the stereographic projection of a “beach ball hypercube” to 3-dimensional space. Right: computer render of the same, including the 2-dimensional square faces.

Forming n–dimensional cubes from (n−1)–dimensional renderings.

Thus, the constructed 3D model of the “beach ball cube” shadow is the projection of the hypercube into 3-dimensional space. Here the 4-dimensional edges of the hypercube become distorted cubes instead of strips.

Just as the edges of the top object in the figure can be connected together by folding the squares through the 3rd dimension to form a cube, the edges of the bottom object can be connected through the 4th dimension

Why are we trying to understand things in 4 dimensions?

As far as we know, the space around us consists of only 3 dimensions. Mathematically, however, there is no reason to limit our understanding of higher-dimensional geometry and space to only 3, since there is nothing special about the number 3 that makes it the only possible number of dimensions space can have.

From a physics perspective, Einstein’s theory of Special Relativity suggests a connection between space and time, so the space-time continuum consists of 3 spatial dimensions and 1 temporal dimension. For example, consider a blooming flower. The flower’s position it not changing: it is not moving up or sideways. Yet, we can observe the transformation, which is proof that an additional dimension exists. Equating time with the 4th dimension is one example, but the 4th dimension can also be positional like the first 3. While it is possible to visualize space-time by examining snapshots of the flower with time as a constant, it is also useful to understand how space and time interrelate geometrically.

Explore more in the 4th dimension with Hypernom or Dr. Segerman’s book “Visualizing Mathematics with 3D Printing“!

Post by Anika Radiya-Dixit.

 

 

Data Geeks Go Head to Head

For North Carolina college students, “big data” is becoming a big deal. The proof: signups for DataFest, a 48-hour number-crunching competition held at Duke last weekend, set a record for the third time in a row this year.

DataFest 2017

More than 350 data geeks swarmed Bostock Library this weekend for a 48-hour number-crunching competition called DataFest. Photo by Loreanne Oh, Duke University.

Expected turnout was so high that event organizer and Duke statistics professor Mine Cetinkaya-Rundel was even required by state fire code to sign up for “crowd manager” safety training — her certificate of completion is still proudly displayed on her Twitter feed.

Nearly 350 students from 10 schools across North Carolina, California and elsewhere flocked to Duke’s West Campus from Friday, March 31 to Sunday, April 2 to compete in the annual event.

Teams of two to five students worked around the clock over the weekend to make sense of a single real-world data set. “It’s an incredible opportunity to apply the modeling and computing skills we learn in class to actual business problems,” said Duke junior Angie Shen, who participated in DataFest for the second time this year.

The surprise dataset was revealed Friday night. Just taming it into a form that could be analyzed was a challenge. Containing millions of data points from an online booking site, it was too large to open in Excel. “It was bigger than anything I’ve worked with before,” said NC State statistics major Michael Burton.

DataFest 2017

The mystery data set was revealed Friday night in Gross Hall. Photo by Loreanne Oh.

Because of its size, even simple procedures took a long time to run. “The dataset was so large that we actually spent the first half of the competition fixing our crushed software and did not arrive at any concrete finding until late afternoon on Saturday,” said Duke junior Tianlin Duan.

The organizers of DataFest don’t specify research questions in advance. Participants are given free rein to analyze the data however they choose.

“We were overwhelmed with the possibilities. There was so much data and so little time,” said NCSU psychology major Chandani Kumar.

“While for the most part data analysis was decided by our teachers before now, this time we had to make all of the decisions ourselves,” said Kumar’s teammate Aleksey Fayuk, a statistics major at NCSU.

As a result, these budding data scientists don’t just write code. They form theories, find patterns, test hunches. Before the weekend is over they also visualize their findings, make recommendations and communicate them to stakeholders.

This year’s participants came from more than 10 schools, including Duke, UNC, NC State and North Carolina A&T. Students from UC Davis and UC Berkeley also made the trek. Photo by Loreanne Oh.

“The most memorable moment was when we finally got our model to start generating predictions,” said Duke neuroscience and computer science double major Luke Farrell. “It was really exciting to see all of our work come together a few hours before the presentations were due.”

Consultants are available throughout the weekend to help with any questions participants might have. Recruiters from both start-ups and well-established companies were also on site for participants looking to network or share their resumes.

“Even as late as 11 p.m. on Saturday we were still able to find a professor from the Duke statistics department at the Edge to help us,” said Duke junior Yuqi Yun, whose team presented their results in a winning interactive visualization. “The organizers treat the event not merely as a contest but more of a learning experience for everyone.”

Caffeine was critical. “By 3 a.m. on Sunday morning, we ended initial analysis with what we had, hoped for the best, and went for a five-hour sleep in the library,” said NCSU’s Fayuk, whose team DataWolves went on to win best use of outside data.

By Sunday afternoon, every surface of The Edge in Bostock Library was littered with coffee cups, laptops, nacho crumbs, pizza boxes and candy wrappers. White boards were covered in scribbles from late-night brainstorming sessions.

“My team encouraged everyone to contribute ideas. I loved how everyone was treated as a valuable team member,” said Duke computer science and political science major Pim Chuaylua. She decided to sign up when a friend asked if she wanted to join their team. “I was hesitant at first because I’m the only non-stats major in the team, but I encouraged myself to get out of my comfort zone,” Chuaylua said.

“I learned so much from everyone since we all have different expertise and skills that we contributed to the discussion,” said Shen, whose teammates were majors in statistics, computer science and engineering. Students majoring in math, economics and biology were also well represented.

At the end, each team was allowed four minutes and at most three slides to present their findings to a panel of judges. Prizes were awarded in several categories, including “best insight,” “best visualization” and “best use of outside data.”

Duke is among more than 30 schools hosting similar events this year, coordinated by the American Statistical Association (ASA). The winning presentations and mystery data source will be posted on the DataFest website in May after all events are over.

The registration deadline for the next Duke DataFest will be March 2018.

DataFest 2017

Bleary-eyed contestants pose for a group photo at Duke DataFest 2017. Photo by Loreanne Oh.

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Post by Robin Smith

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