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Welcome to the May 21, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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A fist bump between a human and a robot. Scientists Bring Sense of Touch to a Robotic Arm
Jon Hamilton
May 20, 2021

Scientists at the University of Pittsburgh, the University of Texas at Austin, and the University of Chicago have conferred a sense of touch to a robotic arm that provides tactile feedback directly to a paralyzed man's brain. The team planted electrodes in a region of the man’s brain that processes sensory input, then developed a method of generating signals from the robotic arm/hand that the brain would recognize as making contact with something. Testing showed the patient was able to perform some manual tasks with the robotic arm and hand as quickly as a person using their own hand could.

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An infographic showing a computational model of mutations on SARS-CoV-2’s spike protein. Computer-Based Modeling Can Predict Mutation 'Hotspots,' Antibody Escapers in the SARS-CoV-2 Spike Protein
New York University
May 19, 2021

Computational modeling by researchers at New York University (NYU) and NYU Abu Dhabi in the United Arab Emirates characterized the biological significance of SARS-CoV-2 spike protein mutations. The researchers simulated the mechanism by which the coronavirus' spike protein recognizes the ACE2 receptor to invade host cells. They evaluated 1,003 mutation combinations in the spike and ACE2 proteins, including those leading to rapidly transmitted variants originating in Brazil, South Africa, Britain, and India. This showed that mutations that bind tightly to the ACE2 receptor happen in two clusters or mutation hotspots on the binding interface, while certain variants also confer antibody resistance. NYU's Kristin C. Gunsalus said the computational modeling method “allows for a more timely response to emerging outbreaks and could be used to guide the development of new vaccines."

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U.S. Has Almost 500,000 Job Openings in Cybersecurity
CBS News
Khristopher J. Brooks
May 19, 2021

The U.S. Commerce Department's Cyber Seek technology job-tracking database and the trade group CompTIA count about 465,000 current U.S. cybersecurity jobs openings. Experts said private businesses and government agencies' need for more cybersecurity staff has unlocked a prime opportunity for anyone considering a job in that field. The University of San Diego's Michelle Moore suggested switching to a cybersecurity career could be as simple as obtaining a Network+ or Security+ certification, while an eight-week online course could help someone gain an entry-level job earning $60,000 to $90,000 a year as a penetration tester, network security engineer, or incident response analyst. Moore cited a lack of skilled cybersecurity personnel as a problem, while CompTIA's Tim Herbert said only a small percentage of computer science graduates pursue cybersecurity careers.

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An illustration of a physical aircraft co-developed by researchers to test digital twin technology. Advanced Technique for Developing Digital Twins Makes Tech Universally Applicable
UT News
May 20, 2021

Researchers at the University of Texas at Austin (UT Austin), the Massachusetts Institute of Technology (MIT), and industry partner The Jessara Group have developed what they’re calling a universally applicable digital twin mathematical model. The framework was designed to facilitate predictive digital twins at scale. MIT's Michael Kapteyn said, "Using probabilistic graphical models, we create a mathematical model of the digital twin that applies broadly across application domains." The researchers used this technique to generate a structural digital twin of a custom-built unmanned aerial vehicle equipped with state-of-the-art sensors. Said Jacob Pretorius of the Jessara Group, “The value of integrated sensing solutions has been recognized for some time, but combining them with the digital twin concept takes that to a new level. We are on the cusp of an exciting future for intelligent engineering systems.”

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Protein Simulation, Experiments Unveil Clues on Origins of Parkinson's Disease
Penn State News
Zachary Sweger
May 19, 2021

Researchers at Pennsylvania State University (Penn State) and Israel's Hebrew University of Jerusalem blended experimental and computational methods to explore how individual proteins may form aggregates that play into the development of Parkinson's disease. Penn State's Nikolay Dokholyan said, "Using experiments performed in professor Eitan Lerner's laboratory at the Biological Chemistry Department at The Hebrew University of Jerusalem, a series of algorithms accounts for effective forces acting in and upon a specific protein and can identify the various conformations it will take based on those forces." The researchers used data from earlier experiments to feed the molecular dynamics of the alpha-synuclein protein into their calculations, which exposed conformations that in some instances persisted longer than previously estimated. Penn State's Jiaxing Chen said these findings unlock "possibilities for the development of drugs that can regulate the function of this protein."

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Illustration of a DNA string. Novel Approach Identifies Genes Linked to Autism, Patient IQ
Baylor College of Medicine
Molly Chiu
May 19, 2021

A study led by Baylor College of Medicine researchers identified a novel computational approach for identifying genes most likely associated with autism spectrum disorders (ASD), and predicting the severity of intellectual disability in ASD patients as a result. The team fed a massive volume of evolutionary data to their analyses on mutations' contribution to protein evolution, and on the impact of human variants on protein function. Researchers concentrated on de novo missense variants in particular, to identify mutations that differentiate ASD patients and unaffected siblings. The Baylor researchers used the Evolutionary Action equation to assess the impact of each missense mutation on a corresponding protein. Baylor’s Young Won Kim said the results suggest new genes to study, and “a path forward to advise parents of children with these mutations of the potential outcomes in their child and how to best involve external support in early development intervention, which has shown to make a huge difference in outcome as well.”

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Cheap, User-Friendly Smartphone App Predicts Vineyard Yields
Cornell Chronicle
Krishna Ramanujan
May 17, 2021

Cornell University engineers and plant scientists have developed an inexpensive machine learning application to predict vineyard yields earlier in the season and with greater accuracy than costlier manual counting techniques. Growers can use a smartphone to record video of their grapevines, then upload the footage to a server to process; the system uses computer vision to improve yield estimates. Cornell's Kirstin Petersen said, "Compared to the technology, a farmer would have to manually count 70% of their vineyard to gain the same level of confidence in their yield prediction, and no one would do that." As a result, Petersen said, “This could be a real game-changer for small and medium-sized farms in the Northeast.”

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Digital Nose Stimulation Enables Smelling in Stereo
IEEE Spectrum
Evan Ackerman
May 13, 2021

Researchers at the University of Chicago (UChicago) have developed a wireless, nose-worn device that can enable directional smell using tiny electrical impulses. The battery-powered hardware has magnets to keep itself attached to the inside of the nose; it can detect inhalation, and employs electrodes to stimulate the septum and trigger the trigeminal nerve. The model, which connects with external sensors, works well enough that completely untrained people can use it to localize electrically-triggered virtual odors. UChicago's Jas Brooks said, "The sensation our device produces can feel like a 'tickling' or 'sting,' not far from that of wasabi or the smell of white vinegar, except it is clearly directional." The stimulator could be used as an assistive device for people suffering loss of olfactory function.

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A woman wearing virtual reality goggles. Locomotion Vault Will Help Guide Innovations in VR Locomotion
University of Birmingham (U.K.)
May 13, 2021

Researchers at the University of Birmingham in the U.K., the University of Copenhagen in Denmark, and Microsoft Research have developed Locomotion Vault, a central and freely available resource that analyzes currently available techniques for virtual reality (VR) locomotion. Locomotion Vault aims to help developers choose the best technique for their application, as well as identifying gaps to target in future research. The interactive database allows for contributions from researchers and practitioners. Microsoft Research's Mar Gonzalez-Franco said, "As new and existing technologies progress and become a more regular part of our lives, new challenges and opportunities around accessibility and inclusivity will present themselves. [VR] is a great example. We need to consider how VR can be designed to accommodate the variety of capabilities represented by those who want to use it."

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Envisioning Safer Cities with AI
Texas Advanced Computing Center
Aaron Dubrow
May 19, 2021

University of California, Berkeley (UC Berkeley) researchers have designed an artificial intelligence toolkit for automatically identifying building properties, and for gauging urban structures' resilience. BRAILS (Building Recognition using AI at Large-Scale) applies machine learning, deep learning, and computer vision on data about the built environment as a tool for more efficient urban planning, design, and management of buildings and infrastructure. The basic BRAILS framework derives building characteristics from satellite and ground-level images drawn from Google Maps, combining them with data from sources like Microsoft Footprint Data and OpenStreetMap. The researchers trained the BRAILS modules and ran simulations using supercomputers at the Texas Advanced Computing Center. UC Berkeley's Charles Wang said the research aims "to create a more resilient built environment."

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Photo of a bipedal robot going down a set of stairs. 'Blind' Robot Successfully Navigates Stairs
Steve Dent
May 19, 2021

A "blind" bipedal robot trained in a simulator by Oregon State University (OSU) researchers can negotiate varying terrain, including the climbing of stairs. The researchers applied sim-to-real Reinforcement Learning to establish how Agility Robotics' Cassie robot would ambulate. The OSU team taught Cassie virtually to manage various situations, including stairs and flat surfaces. In real-world tests, the robot could handle curbs, logs, and other uneven terrain it had never encountered before, and ascended and descended stairs with 80% and 100% efficiency, respectively. According to the researchers, "This work has demonstrated surprising capabilities for blind locomotion and leaves open the question of where the limits lie."

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Illustration of a lung cancer scan. Deep Learning Enables Dual Screening for Cancer, Cardiovascular Disease
Rensselaer Polytechnic Institute News
May 20, 2021

A new deep learning algorithm shows promise for screening patients for both cardiovascular disease and lung cancer. Engineers at Rensselaer Polytechnic Institute (RPI) used data from over 30,000 low-dose computed tomography (CT) scans to develop, train, and validate the algorithm, which weeded out unwanted artifacts and noise and extracted diagnostic features. Massachusetts General Hospital (MGH) researchers then tested the algorithm on state-of-the-art scans, and found it was as effective in analyzing those images as the hospital’s radiologists. RPI's Deepak Vashishth said, “ This innovative research is a prime example of the ways in which bioimaging and artificial intelligence can be combined to improve and deliver patient care with greater precision and safety.”

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