Welcome to the November 12, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.
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COVID e-Gate Combines Contact Tracing Information, Temperature Screens
University of Sydney (Australia)
November 9, 2021
A COVID-19 e-Gate integrated entry screening system developed by Australia's University of Sydney, Sydney Children's Hospitals Network, and The Children's Hospital at Westmead provides screening and contact tracing before people enter the hospital. The real-time system uses a personalized QR code for physical gate-enabled access based on COVID-19 screening questions and temperature checks. More than 1,500 staff and regular visitors took part in a trial of the system over the past eight months. Sydney Children's Hospitals Network's Michael Dickinson said, "Not only does the e-Gate have the ability to be easily expanded to other hospitals, but the Internet of Things smart approach to health screening could be useful in other large locations—such as airports and major sports or entertainment venues."
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Nuclear Radiation Used to Transmit Digital Data Wirelessly
Lancaster University (U.K.)
November 10, 2021
Digitally encoded information has been transmitted wirelessly using nuclear radiation, thanks to engineers at the U.K.'s Lancaster University and Slovenia's Jožef Stefan Institute. The researchers transmitted the data using fast neutrons spontaneously emitted from the radioactive isotope californium-252. A detector measured the emissions, which were recorded on a laptop; the researchers serially encoded data including a word, the alphabet, and a blindly-chosen random number into the modulation of the neutron field, and decoded the output on a laptop that retrieved the encoded information. Lancaster's Malcolm Joyce said, "We demonstrate the potential of fast neutron radiation as a medium for wireless communications for applications where conventional electromagnetic transmission is either not feasible or is inherently limited."
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Computer Program Can Read Any Genome Sequence, Decipher Its Genetic Code
News-Medical Life Sciences
November 9, 2021
Researchers at Harvard University have developed a program that can read an organism's genome sequence and determine its genetic code, which could help scientists understand the evolution of genetic code. While most organisms use the same genetic code, some organisms have been discovered that use alternative genetic codes. The new program, Codetta, can be used to identify organisms that use alternative genetic codes. The researchers used Codetta to analyze the genome sequences of more than 250,000 bacteria and other single-celled organisms, and found five organisms in which the code for the amino acid arginine was reassigned to a different amino acid, the first time this swap has been seen in bacteria.
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When Algorithms Get Creative
University of Bern (Switzerland)
November 10, 2021
An international team of scientists led by Switzerland's University of Bern has developed evolutionary algorithms that can learn creatively. Such algorithms determine the "fitness" of a candidate solution based on how well it solves the underlying problem. The researchers' evolving-to-learn (E2L) or "becoming adaptive" approach was applied to three typical learning scenarios. The first was to detect a repeating pattern in a continuous input stream without performance feedback; the second virtually rewarded the computer for behaving in a desired manner; and the third guided the computer on how much its behavior diverged from a desired pattern. “In all these scenarios,” Bern's Jakob Jordan said, "The evolutionary algorithms were able to discover mechanisms of synaptic plasticity, and thereby successfully solved a new task."
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Dexterous Robotic Hands Manipulate Objects with Ease
MIT Computer Science and Artificial Intelligence Laboratory
Rachel Gordon
November 5, 2021
Scientists at the Massachusetts Institute of Technology's Computer Science and Artificial Intelligence Laboratory (CSAIL) have designed a system to enable robotic hands to handle more than 2,000 different objects. The researchers used a simulated hand with 24 degrees of freedom, and demonstrated that the framework could be adapted to a real robotic system. The framework employs a model-free reinforcement learning algorithm that formulates value functions from environmental interactions, deep learning, and "teacher-student" training. The "teacher" network is fed data about the object and robot in simulation, which it distills into observations similar to those found in the real world.
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How an RF Control System Enhances Quantum Computers
Berkeley Lab Computing Sciences
November 9, 2021
Researchers at Lawrence Berkeley National Laboratory (LBNL) have developed compact radio frequency (RF) modules that mix signals to improve control system reliability for superconducting quantum processors. They replaced a bulky RF system controlling superconducting qubits via analog circuits with a smaller modular system that delivers high-resolution, low-noise RF signals to manipulate and measure superconducting qubits at room temperature. Said LBNL’s Gang Huang, “The new module exhibits low-noise, high-reliability operation and is now becoming our laboratory standard for microwave frequency modulation/demodulation across many different experimental configurations” in the Advanced Quantum Testbed at Berkeley Lab, a collaborative research program funded by the U.S. Department of Energy’s Office of Science.
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Supercomputers Join Fight Against Antibiotic Resistance
Ruhr-Universität Bochum (Germany)
Yvonne Kasper
November 8, 2021
An international research team has developed a method to address the threat of antibiotic-resistant bacteria using supercomputers. The simulation strategies devised by researchers at Germany's Ruhr-Universität Bochum (RUB) and University of Duisburg-Essen, the U.K.'s University of Portsmouth, Australia's University of Queensland, and Israel's Weizmann Institute could help develop new antibiotic variants more quickly. Their approach involves modifying existing antibiotics based on simulations of the antibiotic's solubility, its effectiveness in penetrating the bacterial membrane, and its efficiency in blocking the pathogen's protein production. RUB's Frank Schulz explained, "The computational evaluation of whether a chemical compound will be active before it is actually synthesized avoids chemical waste."
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Energy Companies Turn to 3D Printing to Bypass Snarled Supply Chains
The Wall Street Journal
Stuart Condie
November 11, 2021
Energy companies are using three-dimensional (3D) printing to overcome pandemic-related supply-chain bottlenecks. Chevron tapped Australian 3D printing company AdditiveNow to supply parts needed for maintenance at an Australian gas-export project, and was sufficiently impressed to acquire the company's intellectual property for future projects. Matthew Waterhouse at 3D printing firm 3D Metalforge said some clients view additive manufacturing as a tool to eliminate the need to buy replacement parts for their equipment, as their storage and obsolescence can be costly. Chevron's Robert Rettew said, "We've shown that this flexible, right part, right time digital supply-chain approach can be successful, and it can meet our needs in a sort of reactive mode."
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AI Brings Power of NLP to African Languages
Waterloo News (Canada)
November 9, 2021
A neural network model developed by researchers at Canada's University of Waterloo enables computer-based analysis of text in 11 African languages. The AfriBERTa model achieved output quality similar to that of existing models while requiring significantly less data to train the model, just a gigabyte of text. The African languages covered by the model are considered low-resource, meaning there is a lack of data to feed to neural networks. University of Waterloo's Jimmy Lin explained that requiring less training data results in “lower carbon emissions associated with operating massive data centers.” Lin added that using smaller datasets also makes data curation more practical, “which is one approach to reduce the biases present in the models.”
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Algorithmic Tracking ‘Damaging Mental Health’ of U.K. Workers
The Guardian
Dan Milmo
November 11, 2021
A report by the U.K. Parliament's All-Party Parliamentary Group (AAPG) calls for new legislation to control the use of algorithms to monitor workers and set performance targets for them. The report said pervasive monitoring and target-setting technologies in particular “are associated with pronounced negative impacts on mental and physical well-being as workers experience the extreme pressure of constant, real-time micro-management and automated assessment." The group is calling for an "accountability for algorithms act" to ensure performance-driven regimes are evaluated to assess their impact, and that workers participate in the design and use of algorithm-driven systems.
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Computer Model a Key Step Toward Low-Temperature Preservation of 3D Tissues, Organs
Oregon State University News
Steve Lundeberg
November 9, 2021
A mathematical model developed by researchers at Oregon State University (OSU), Augusta University, and Canada's University of Saskatchewan can forecast changes in tissue size during cryopreservation. Inducing cells to swell by initial exposure to a low cryoprotectant (CPA) concentration could prevent destructive ice formation in tissues after rapidly adding a high CPA level while reducing toxicity. OSU's Adam Higgins said, "Our new paper extends this line of research by presenting a new model of mass transfer in tissue; a key feature is that it allows for the prediction of tissue size changes."
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Can Electric Cars Help Strengthen Electrical Grids?
University of Rochester NewsCenter
November 8, 2021
A computational model developed by researchers at the University of Rochester shows how using vehicle-to-grid (V2G) technology to store electricity in electric vehicle batteries, selling it back to the utility as needed, can result in local electric grid stability. Rochester's Heta Gandhi said, "An electric vehicle is already connected to the grid when you use a public charger, or any charger for that matter. If you make [a charger] bidirectional it can also transfer energy from the vehicle to the grid." The model takes into account historic electricity rates, battery degradation, commuter driving times, distances, and other scenarios. It was used to develop a cost-benefit analysis for V2G participants in six U.S. cities—Boston, Chicago, Phoenix, New York City, Washington DC, and San Francisco—which found potential annual savings for vehicle owners ranged from $120 to $150.
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