Welcome to the November 15, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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High-Tech Approaches to America's Sewer Problem
The Wall Street Journal
Christopher Mims
November 13, 2021
U.S. cities and service contractors use sophisticated technology like flying drones, crawling robots, and remote-operated swimming machines to more affordably and effectively explore, diagnose, and fix municipal sewer systems. Such tools boast cameras, sonar, and lasers, and in some instances can clear obstructions with high-powered water-jet cutters, or repair pipes using ultraviolet-cured plastics. The solutions also employ artificial intelligence (AI) systems to catalog defects automatically, and to prioritize certain repairs. Robotic sewer inspection company Sewer AI uses a vast video archive of sewer pipe exploration to update its defect-identifying computer-vision system continually. Water/wastewater infrastructure consultant Gregory Baird said the water and sewer industry can transform itself with software capable of extracting data from tunnel-exploring robots and flagging defects, combined with failure-prediction algorithms.
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AI Predicts Eye Movements
Max Planck Institute for Human Cognitive and Brain Sciences (Germany)
November 8, 2021
Scientists at Germany's Max Planck Institute for Human Cognitive and Brain Sciences and Norway's Kavli Institute for Systems Neuroscience have developed software to predict eye movements from magnetic resonance imaging (MRI) scans, via artificial intelligence. The open source DeepMReye software can track individual viewing behavior without cameras by detecting patterns of eye movement during an MRI scan. The researchers have trained a neural network with their own and publicly available data from participants so DeepMReye can track eye movements even in data on which it has not been trained. The software can forecast when eyes are open or closed, and tracks eye movements even when the eyes stay closed.
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Scientists Employ Digital Esophagus to Battle Barrett's
Oak Ridge National Laboratory
November 11, 2021
Researchers at the U.S. Department of Energy's Oak Ridge National Laboratory (ORNL) helped design a digital tool to monitor Barrett's esophagus, a deterioration of the lower esophagus' mucosal lining, less invasively. Working with scientists at Columbia University's Irving Medical Center, Mount Sinai's Icahn School of Medicine, and Massachusetts General Hospital's Institute for Technology Assessment, the team built a computational esophageal model based on real-world data. The process was enabled through parallelization across multicore servers, and the model has been released into the public domain. ORNL's Jim Nutaro said, "The ultimate goal was to strike a balance between physically poking a patient and how often you find something that may be concerning."
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True, Untrue Viral News Move Equally Through Twitter
Cornell Chronicle
Louis DiPietro
November 10, 2021
A study found both true and untrue viral news spread through Twitter at the same speed, breadth, and depth, highlighting why attempts to stop disinformation on the platform have had limited success. Cornell University's Jonas Juul and Stanford University's Johan Ugander focused on the structure of Twitter "cascades," a quantification of viral tweets' paths from the original poster through the network via retweets. More popular tweets have bigger cascades, and the researchers analyzed cascades of the same size, implying that true and untrue tweets reached about the same number of users. Cascades of equally shared true and untrue tweets were virtually identical, changing the prevailing notion that untrue tweets travel faster. The researchers said this would limit disinformation countermeasures like flagging viral tweets with long diffusion patterns, or deprioritizing major hubs in news feeds; they suggested better digital literacy among users would be more effective.
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3D Printing, ML Unite in Research to Improve Cochlear Implants
University of Cambridge (U.K.)
November 12, 2021
Improving cochlear implants (CIs) by combining three-dimensional (3D) printing and machine learning (ML) was the goal of a British-Chinese research team of engineers and clinicians. The researchers 3D-printed replicas of human cochleae to examine how the models' shapes and “current spread,” the electrical properties of the highly conductive fluids inside cochlear ducts, affect current or electrical stimulus spread in the ear. Adding ML to the process enabled the prediction of current spread in CI users, which could be used to extrapolate the range of patient cochlear tissue resistivity. Shery Juang at the U.K.'s University of Cambridge said 3D printing "is a powerful tool to create physical models which might provide a well-characterized training dataset as a purpose-built surrogate to clinical data for machine learning. The co-modelling principle demonstrated in this study could be useful to address other areas of clinical modelling and healthcare applications."
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Algorithm Provides Better Way to Search, Build Nanoporous Materials
WSU Insider
Tina Hilding
November 10, 2021
Washington State University (WSU) and Oregon State University researchers have developed an algorithm that can winnow down thousands of nanoporous material candidates to the best option, at minimal cost. The researchers used the algorithm to find the best candidate for a methane-absorbent nanoporous material, identifying it from a library of 70,000 materials after assessing just 120 candidates. The algorithm examines the material's three-dimensional structures, and conducts virtual experiments when encountering new iterations to update its structural and property knowledge before choosing another nanoporous material. WSU's Aryan Deshwal said, "We explicitly build statistical models, which allowed us to predict the properties for unknown materials and have well-calibrated uncertainty, which means you know what you don't know, so when we explored the space, we explored it in a much smarter way rather than randomly."
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Canadian Researchers Achieve First Quantum Simulation of Baryons
Waterloo News (Canada)
November 11, 2021
Researchers at Canada's University of Waterloo and York University achieved the first simulation of the quantum particles called baryons on a quantum computer. The research focused on the quantum simulation of lattice gauge theory, which describes the physics of reality, including the Standard Theory of particle physics. The researchers developed a resource-efficient quantum algorithm that enabled them to model a system within a non-Abelian gauge theory on a cloud quantum computer coupled to a classical computer. Said Waterloo's Jinglei Zhang, "What’s exciting about these results for us is that the theory can be made so much more complicated. We can consider simulating matter at higher densities, which is beyond the capability of classical computers."
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Unique Robotic Hand Can Rotate Objects Without Releasing Grasp
New Atlas
Ben Coxworth
November 10, 2021
A novel robotic hand can change a grasped object's orientation without letting go. Built by researchers at Spain's University of Malaga (UMA) and the U.K.'s University College London, the Rolling Fingers hand's three articulated fingers close in on objects from three sides, while bending to conform to the object's shape. Rubber gripping surfaces on the fingers can rotate left or right relative to the underlying structure, and when rotated in the same direction simultaneously, can turn objects around while maintaining their grip. UMA's Jesús M. Gómez said, "With at least three fingers providing two active degrees of freedom [grasping and axial rotation], we can create robotic graspers that are capable of moving objects in a controlled way during a single grasp."
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More Than a Third of Women in Tech Eyeing the Exit in Next Two Years
CNet
Erin Carson
November 12, 2021
A survey by business management consulting firm New View Strategies found 38% of women in the technology sector intend to quit in the next two years, driven by the pandemic and gender inequality. More than a quarter (27%) of 1,000 survey respondents said they were now less positive about their careers than they were before the pandemic, and more than half (52%) said their workload had grown since COVID-19 started. Moreover, 43% perceive a gender pay gap at their workplace, and 38% reported having experienced gender bias. Respondents cited few advancement opportunities, female role models, or mentorship as among the biggest challenges for women in technology.
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What's in the Water?
The Current (University of California, Santa Barbara)
Sonia Fernandez
November 10, 2021
University of California, Santa Barbara (UCSB) researchers have mapped the global pathways of nitrogen and pathogens from human wastewater. Their data visualization plots the sources and destinations of nitrogen, common to agricultural and wastewater, which causes offshore phytoplankton blooms that strip the waters of oxygen. UCSB's Ben Halpern said, "Our work here helps map where nutrients from wastewater are likely putting [coastal] ecosystems at greatest risk." UCSB's Cascade Tuholske said the research indicates that diets rich in animal-based proteins, typical of wealthy nations, increase nitrogen concentrations in wastewater. The researchers hope the mapping model will inform local remediation efforts.
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CMU Opens AI Maker Space to Let Students 'Sharpen the Cutting Edge of AI'
Pittsburgh Post-Gazette
Lauren Rosenblatt
November 10, 2021
Carnegie Mellon University (CMU) last week unveiled its first artificial intelligence (AI) maker space for students and researchers to advance computer vision, speech recognition, and other AI applications. "Our students will use hands-on tools and open environments to further sharpen the cutting edge of AI," said CMU president Farnam Jahanian. Unlike other maker spaces at CMU, which have been mostly in the engineering department or with a focus on hardware, the new one is devoted to software. Slated to open for students in January, the JPMorgan Chase AI Maker Space is funded via donations from the bank. Said Jahanian, “By putting critical AI tools directly into the hands of CMU students and researchers at the forefront of innovation, the [maker space] will empower our students to become the next generation of AI leaders.”
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