Collaborating Authors


The Legend of Zelda, 'Dinky,' and a Bridge to My Daughter


When winter made its second pandemic appearance here in Montana, I found myself pining to relive my first experience with The Legend of Zelda: Breath of the Wild. To my dismay, the sequel, Hyrule Warriors: Age of Calamity, the bash-fest Nintendo released in November, didn't scratch my itch for sweeping, soothing landscapes and low-stakes puzzle solving during a year of high-stakes reality. I've been home with toddlers for 11 months straight, my every lockdown minute a battle against darkness and chaos, replete with my own two tiny red Bokoblins perpetually swinging their Boko Clubs at my weakened defenses. I wondered daily: Are there even enough stamella shrooms in the entire gaming universe to get us through this year? When we first hunkered down last spring, my kids were 18 months and 4 years old.

Heart Disease Prediction using Machine Learning with Python


This database contains 14 attributes, but all published experiments refer to using a subset of 14 of them. In particular, the Cleveland database is the only one that has been used by ML researchers to this date. The "target" field refers to the presence of heart disease in the patient. It is integer-valued from 0 and 1. To get the information about the data set.

Health-behaviors associated with the growing risk of adolescent suicide attempts: A data-driven cross-sectional study Machine Learning

Purpose: Identify and examine the associations between health behaviors and increased risk of adolescent suicide attempts, while controlling for socioeconomic and demographic differences. Design: A data-driven analysis using cross-sectional data. Setting: Communities in the state of Montana from 1999 to 2017. Subjects: Selected 22,447 adolescents of whom 1,631 adolescents attempted suicide at least once. Measures: Overall 29 variables (predictors) accounting for psychological behaviors, illegal substances consumption, daily activities at schools and demographic backgrounds, were considered. Analysis: A library of machine learning algorithms along with the traditionally-used logistic regression were used to model and predict suicide attempt risk. Model performances (goodness-of-fit and predictive accuracy) were measured using accuracy, precision, recall and F-score metrics. Results: The non-parametric Bayesian tree ensemble model outperformed all other models, with 80.0% accuracy in goodness-of-fit (F-score:0.802) and 78.2% in predictive accuracy (F-score:0.785). Key health-behaviors identified include: being sad/hopeless, followed by safety concerns at school, physical fighting, inhalant usage, illegal drugs consumption at school, current cigarette usage, and having first sex at an early age (below 15 years of age). Additionally, the minority groups (American Indian/Alaska Natives, Hispanics/Latinos), and females are also found to be highly vulnerable to attempting suicides. Conclusion: Significant contribution of this work is understanding the key health-behaviors and health disparities that lead to higher frequency of suicide attempts among adolescents, while accounting for the non-linearity and complex interactions among the outcome and the exposure variables.

Twins, Pirates game delayed by drone flying over Target Field

FOX News

How can teams protect players and staff? A drone flew over Target Field prior to the start of a Minnesota Twins and Pittsburgh Pirates game on Tuesday, which forced a delay. According to The Athletic, players were trying to throw baseballs at the drone, but they were unable to hit it. Eventually, it flew out of the stadium, and around one of the parking lots. The umpires made the players get off the field because the drone presents a safety issue.

Courses bring field sites and labs to the small screen


> Science's COVID-19 coverage is supported by the Pulitzer Center. In a normal summer, Appledore Island, a 39-hectare outcrop 12 kilometers off the coast of Maine and New Hampshire, becomes a classroom. Students from high school to graduate level live in close quarters, eat in a communal dining hall, and work shoulder to shoulder to explore the biology of the shore and waters in 18 courses organized by the Shoals Marine Laboratory. But this summer, with the pandemic surging, students have stayed home. Instead, a skeleton staff on Appledore is streaming field trips and dissections of fish and invertebrates and setting up cameras to gather data for students. Rather than leading students around the island, coastal restoration ecologist Gregg Moore from the University of New Hampshire (UNH), Durham, hauls a backpack full of equipment: “a dual modem with two different cellular carriers, a signal-boosting directional antenna, and a large DC power source,” he says. The equipment allows him to teach 12 remote students—twice the course's usual enrollment—basic techniques of coastal ecology. Moore's is just one of hundreds of lab and field courses forced online by COVID-19—“a seismic shift for those who were not already involved in distance or online education,” says Martin Storksdieck, a science education researcher at Oregon State University, Corvallis. Some researchers worry students will miss out on certain practical and problem-solving skills and won't be able to judge whether the hands-on work of a scientist is a good fit for them. But instructors are developing high-tech ways to simulate the field and lab experiences. “I would say [these courses] are not virtual,” says Jennifer Seavey, director of the Shoals lab. “They are real.” And some advantages are emerging. By lowering geographical and financial barriers, Seavey says, “Virtual field courses are democratizing fieldwork.” The shift has taken ingenuity. “Professors must get creative and use a combination of what is available,” including online videos and free or commercially available online labs, says Mildred Pointer, a physiologist at Howard University who is working on a fall course in general biology. No single tool meets all their needs, Pointer says. As the pandemic gained momentum, emails flew among the leaders of the National Association of Geoscience Teachers. Many U.S. geology majors must take a “capstone” field course to graduate. The cancellation of more than three-quarters of these courses jeopardized graduation for many majors. So the association invited instructors to develop learning objectives that did not depend on students doing fieldwork. It also compiled online exercises to help the 29 field courses that have moved online this summer. Lessons range from “Orienteering in Minecraft” to “Geology of Yosemite Valley,” which includes a 43-stop Google Earth tour with photos and embedded text. Like Moore, geoscientist Jim Handschy wanted to give remote students “as close to the real experience as possible.” He runs Indiana University's Judson Mead Geologic Field Station in Montana, which had enrolled 60 students before classes were canceled in March. He and a few instructors visited each outcrop in their course plan, filmed the rocks and landscape, and captured magnified views of samples. Each week, the class delves deeper into the rock layers and their history. For their final project, students digitally map a 3100-hectare landscape. Shannon Dulin, a geologist at the University of Oklahoma, Norman, who just finished teaching a field course, sees the value of learning how to survey a landscape without setting foot on it. On their class evaluations, her students said they gained unexpected skills. “And these are skills they are going to need on the job,” she adds, as geologists are increasingly being asked to evaluate sites they don't visit. In other fields, hands-on learning takes place in labs. Typically, students work in pairs and share equipment, “so there are a lot of issues about virus transmission,” says Heather Lewandowski, a physicist at the University of Colorado (CU), Boulder. At her university this fall, lab exercises as diverse as building an electrical circuit or analyzing solar flare data will most likely be completely remote. Luckily, physics already had a foot in the virtual lab world—especially at CU. There, back in 2002, Nobel laureate Carl Wieman developed the Physics Education Technology (PhET) Interactive Simulations project to provide “games” that teach students basic physics concepts. The PhET web portal now has 106 physics-based simulations and another 50 or so for other disciplines. It became a go-to place this spring for faculty shifting to online teaching; traffic increased fivefold, says Director Katherine Perkins. In addition, several universities have adopted a handheld device called the iOLab that rents for $50 a semester. With it, students can measure magnetism, light intensity, acceleration, temperature, gravity, and atmospheric pressure, and do basic physics experiments at home. “They like that we trust them and are not just giving them instructions,” says iOLab inventor and physicist Mats Selen at the University of Illinois, Urbana-Champaign. Lewandowski and her colleagues surveyed physics instructors and students about their experiences and posted their findings on arXiv, the physics preprint server, on 2 July. Respondents said online labs work best when projects are open-ended, and online class meetings are kept small. They complained about technical difficulties, students having unequal access to the internet and materials, and longer prep times for both students and instructors. But they reported they could meet most key learning objectives, Lewandowski says, even though “there are lots of things we can't replicate in remote experiments,” such as such as building vacuum chambers or troubleshooting equipment. Some institutions decided this spring that virtual just wouldn't do. The Marine Biological Laboratory (MBL) in Woods Hole, Massachusetts, simply canceled its summer courses. “MBL courses are world-renowned for the intensity of the hands-on nature of the lab work,” says Director Nipam Patel. Students spend long hours with famous faculty and do their own projects using organisms collected locally. “We felt that it would be exceedingly difficult to replicate these experiences as a virtual lab course.” Other institutions will try for a mix of in-person and virtual labs. Suely Black, chemistry chair at Norfolk State University, expects only half of his students will be in lab each week this fall, while the other half will be in online classes analyzing data and writing reports. “The crisis has caused us to more critically evaluate what activities students must experience in the lab setting,” he says. Similarly, this fall, organic chemistry students at the University of Michigan (UM), Ann Arbor, will rotate into the lab in small groups, giving each a taste of the hands-on experience. Personal protection equipment is standard for this course and all the work is done in hoods with excellent air exchange, so “they are really fully protected,” says UM biochemist Kathleen Nolta. Storksdieck, an advocate of online learning, questions the value of smelling fumes or using a pipette. “We have to ask whether all the hands-on taught so far was all that great,” he says. Dominique Durand, a biomedical engineer at Case Western Reserve University, says after he put a master's program in biomedical engineering completely online 5 years ago, he concluded that solving problems was more important than hands-on experience. And University of California, Santa Cruz, ecologist Erika Zavaleta thinks virtual courses will open fieldwork to far more students. “There are things you can do online that you can't do in person,” she adds, such as visiting more places than possible by driving. Even so, Handschy laments that his geology students will not have the 12-hour-a-day immersive interactions with each other and faculty that past classes have had. Natalie White, a rising junior at UNH who took Moore's course on Appledore last year, agrees: “You don't have all the time in between when you walk around the island and can ask impromptu questions.” Appledore Island is the source of some her fondest memories. “I think they are missing out on the community.”

Lie detectors have always been suspect. AI has made the problem worse.


A Montana-based company called Neuro-ID conducts AI analysis of mouse movements and keystrokes to help banks and insurance companies assess fraud risk, assigning loan applicants a "confidence score" of 1 to 100. In a video the company showed me, when a customer making an online loan application takes extra time to fill out the field for household income, moving the mouse around while doing so, the system factors that into its credibility score. It's based on research by the company's founding scientists that claims to show a correlation between mouse movements and emotional arousal: one paper that asserts that "being deceptive may increase the normalized distance of movement, decrease the speed of movement, increase the response time, and result in more left clicks." The company's own tests, though, reveal that the software generates a high number of false positives: in one case study where Neuro-ID processed 20,000 applications for an e-commerce website, fewer than half the applicants who got the lowest scores (5 to 10) turned out to be fraudulent, and only 10% of the those who received scores from 20 to 30 represented a fraud risk. By the company's own admission, the software flags applicants who may turn out to be innocent and lets the company use that information to follow up how it pleases.

CAESAR source finder: recent developments and testing Machine Learning

A new era in radioastronomy will begin with the upcoming large-scale surveys planned at the Australian Square Kilometre Array Pathfinder (ASKAP). ASKAP started its Early Science program in October 2017 and several target fields were observed during the array commissioning phase. The SCORPIO field was the first observed in the Galactic Plane in Band 1 (792-1032 MHz) using 15 commissioned antennas. The achieved sensitivity and large field of view already allow to discover new sources and survey thousands of existing ones with improved precision with respect to previous surveys. Data analysis is currently ongoing to deliver the first source catalogue. Given the increased scale of the data, source extraction and characterization, even in this Early Science phase, have to be carried out in a mostly automated way. This process presents significant challenges due to the presence of extended objects and diffuse emission close to the Galactic Plane. In this context we have extended and optimized a novel source finding tool, named CAESAR , to allow extraction of both compact and extended sources from radio maps. A number of developments have been done driven by the analysis of the SCORPIO map and in view of the future ASKAP Galactic Plane survey. The main goals are the improvement of algorithm performances and scalability as well as of software maintainability and usability within the radio community. In this paper we present the current status of CAESAR and report a first systematic characterization of its performance for both compact and extended sources using simulated maps. Future prospects are discussed in light of the obtained results.

Artificial Intelligence with Catalytic Predict Catalytic


Train your machine learning model to make predictions for target fields of your choice. Catalytic Predict automatically selects the appropriate classification or model to train based on your selected data sets, each rooted in a logistic regression machine learning algorithm. Example: Invoice approval You tell Catalytic to predict whether it should approve or deny an invoice based on the set of rules you choose. Then, you tell it what actions you want it to take after the decision is made, whether it's processing an approved payment, or automatically reaching out to a vendor for a new invoice after a denial.

Former Google car project Waymo to build self-driving cars at Detroit factory

USATODAY - Tech Top Stories

Stephen Crouch of Montana-based Blackmore explains how the company's lidar technology would help a robot car see what's ahead. Waymo will build self-driving vehicles in Detroit. The company, once known as Google's self-driving car project and now a leader in the push to develop autonomous vehicles, had previously said it was scouting locations in southeast Michigan but did not name a specific city. CEO John Krafcik revealed Detroit as the company's choice in a blog post Tuesday titled, "Making Waymos in Motor City." It refers to being "up and running" this year.

Most people think sex with a machine IS morally acceptable (but only if you are single)

Daily Mail - Science & tech

Robot brothels could soon be accepted by society after research revealed people think that sex with machines is morally acceptable - as long as you're single. The University of Helsinki found that respondents to a survey are less okay with those in committed relationships having sex with robots. It comes as manufacturers in China are using artificial intelligence to create'smart' sex dolls capable of holding basic conversation using an embedded chatbot. Academic Mika Koverol surveyed hundreds of people on their moral code when it comes to sex and relationships and will present his findings at the International Congress on Love and Sex with Robots in Montana. Research has found that people think it's morally acceptable to have sex with robots as scientists develop'smart' sex dolls in China He asked respondents in two separate studies to judge the moral character and actions of characters in a science fiction scenario, New Scientist reports.