Welcome to the August 16, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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Electrical workers check solar panels at a photovoltaic power station in a fishpond in Haian, in China's Jiangsu province. Computer Models of Civilization Offer Routes to Ending Global Warming
Dan Charles
August 14, 2021

Some climate scientists believe massive computer simulations of the world economy could be harnessed to establish a path forward to prevent the worst effects of global warming. There are six major integrated assessment models—four in Europe, one in Japan, and one in the U.S.—and the Netherlands Environmental Assessment Agency's Detlef van Vuuren said they are being used to investigate what is required to meet the Paris goals of slashing greenhouse gas emissions to zero within about 40 years. Each model incorporates data about current greenhouse emission sources like cars, power plants, and home furnaces, as well as assumptions about international trade, prices, and the costs of new technologies. The scientists then impose greenhouse emission limits, and the models formulate the most cost-efficient strategies for meeting those limits, provided they are technologically feasible and do not infringe on natural resources.

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Farmers Help Create 'Virtual Safe Space' to Save Bumblebees
University of Exeter (U.K.)
August 13, 2021

Land-management strategies to save bumblebees can be tested in a "virtual safe space" developed by scientists at the U.K.'s University of Exeter, who collaborated with farmers and landowners on its development. The freely available Bee-Steward decision-support tool offers a computer model of bumblebee colony survival in a given landscape. The Bumblebee Conservation Trust is using Bee-Steward to test and direct land management to help bumblebees and farm businesses prosper in Cornwall county. The Trust's Richard Comont said, "The Bee-Steward model will be fantastic for conservation planning—it lets us time-travel to see the long-term results of changing management and compare all the possible options to see which one will work out best for bumblebees."

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A molecular geneticist evaluates genetic data in a hospital lab in Germany’s Rhineland region. Autocorrect Errors in Excel Still Creating Genomics Headache
Dyani Lewis
August 13, 2021

Autocorrect errors in spreadsheet programs like Microsoft Excel or Google Sheets continue to dog academic genomics literature, according to a study of published gene lists. This often happens when the abbreviated form of a gene's name, or symbol, is wrongly identified and autocorrected as a date, which means the gene is lost when the data is imported into gene-network-analysis software. Five years after Australian researchers brought attention to the problem, analysis by a team at Australia's Deakin University confirmed such errors remain widespread. Deakin's Mark Ziemann said simple checks can detect autocorrect errors, while not using spreadsheets is another suggestion. He also said researchers can trace errors by using scripted computer languages like Python and R, which do not autocorrect gene symbols.

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Quantum Computing Breakthrough May Be Key to Large-Scale Quantum Chips
John Loeffler
August 13, 2021

Researchers at Australia's University of New South Wales (UNSW) say a new method could enable engineers to reliably control millions of quantum bits (qubits), a critical step toward commercially practical full-scale quantum computing. Qubit control up to now has relied on delivering microwave magnetic fields via heat-producing wires next to the qubits. The UNSW team has forgone the wires and applied the fields using a dielectric resonator over the quantum chip. This facilitates simultaneous control over all qubits, which UNSW's Jarryd Pla said could provide control fields of up to 4 million qubits. Explained Pla, “The trick is to cleverly design your algorithm so that the correct answer that you’re looking for reveals itself at the end of the calculation, still making use of the parallelism."

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A robotic eel leverages sensory feedback from the water it swims through to coordinate its motion without the need for central control. Robot Shows How Simple Swimming Can Be
IEEE Spectrum
Evan Ackerman
August 11, 2021

A robotic eel designed by researchers at the Swiss Federal Institute of Technology Lausanne (EPFL) can swim through water, receiving sensory data while in motion. The AgnathaX robot does not employ centralized programming, relying instead on skin sensors that can detect pressure changes in the surrounding water. The sensors are connected to the robot's motorized segments, enabling AgnathaX to produce swimming motions even if its segments are unconnected. This mechanism supports a peripheral control system for robots, and EPFL's Robin Thandiackal and Kamilo Melo said, “Robots that have our complete control architecture, with both peripheral and central components, are remarkably fault-tolerant and robust against damage in their sensors, communication buses, and control circuits.”

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Cornell Researchers Discover 'Code-Poisoning' Attack
Jonathan Greig
August 12, 2021

A backdoor attack discovered by researchers at Cornell University Tech has the potential to compromise algorithmic training and email accounts, among other things. The researchers said the "code poisoning" attack can "manipulate natural-language modeling systems to produce incorrect outputs and evade any known defense" without "any access to the original code or model by uploading malicious code to open-source sites that are frequently used by many companies and programmers." Cornell's Vitaly Shmatikov explained, "With this new attack, the attack can be done in advance, before the model even exists or before the data is even collected — and a single attack can actually target multiple victims." As a defense, the researchers recommend using a system able to identify deviations from the model's original code. Said Shmatikov, non-expert users building models using code they do not understand "can have devastating security consequences."

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Exact Symbolic AI for Better Assessment of AI Fairness
MIT News
Rachel Paiste
August 9, 2021

A new artificial intelligence programming language can evaluate algorithmic fairness faster and more precisely than other available tools, thanks to the work of Massachusetts Institute of Technology researchers. The Sum-Product Probabilistic Language (SPPL) returns fast, precise answers to probabilistic inference questions, and only permits users to write probabilistic algorithms for which it can automatically provide exact probabilistic inference outcomes; users also can check inference's expected speed to avoid writing slow programs. Boston College's Jean-Baptiste Tristan said, "SPPL offers improved flexibility and trustworthiness over other PPLs on this challenging and important class of problems due to the expressiveness of the language, its precise and simple semantics, and the speed and soundness of the exact symbolic inference engine."

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Oak Ridge National Laboratory’s AutoBEM software suite creates a digital twin of the nation’s 129 million buildings. ORNL's Simulation Tool Creates Digital Twins of Buildings From Coast to Coast
Oak Ridge National Laboratory
August 11, 2021

Modeling software designed by researchers at the U.S. Department of Energy's Oak Ridge National Laboratory (ORNL) can simulate the energy profiles of all 129 million buildings in the U.S. The researchers developed the Automatic Building Energy Modeling (AutoBEM) software suite to realize ORNL's five-year Model America vision of producing digital twins for all U.S. buildings. AutoBEM uses high-performance computing to collect publicly available data like satellite imagery and street views, then generates a building energy model to forecast which energy-saving technologies could be implemented. ORNL's Joshua New said, "Before this program, no one had the capability to perform that analysis with detailed, building-specific energy modeling at this scale. Individual utilities now have the capability to perform modeling to show the potential of reducing demand and greenhouse gas emissions."

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NIST Study on Kids' Passwords Shows Gap Between Knowledge of Password Best Practices, Behavior
August 11, 2021

A survey of more than 1,500 U.S. students between the ages of eight and 18 by the National Institute of Standards and Technology revealed a gap between children's knowledge of good password practices and their behavior. The survey found that children are learning password best practices, like memorizing them and logging out after sessions. Their passwords often mentioned sports, video games, names, animals, movies, titles like "princess," numbers, and colors, and the strength of these passwords increased with grade level. However, the researchers found that children typically reuse passwords and share them with friends. When asked about the reason for passwords, elementary students primarily cited safety; middle and high school students more often cited privacy. Among other things, the survey found that younger children used their families for help in creating and maintaining home passwords.

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Blood Test Spots Biological Markers for Schizophrenia
HealthDay News
Robert Preidt
August 12, 2021

A team of U.K. and U.S. scientists has developed a blood test that can detect biological or epigenetic markers of early-stage schizophrenia with 80% accuracy. The researchers used a machine learning algorithm to search for DNA methylation patterns in the human genome's CoRSIV regions. Baylor College of Medicine's Chathura Gunasekara said the findings "not only suggest the possibility of predicting risk of schizophrenia early in life, but also outline a new approach that may be applicable to other diseases." The research accounts for major variables impacting methylation patterns in blood, like smoking and taking antipsychotic drugs. Baylor's Robert Waterland said this "indicates that the epigenetic differences we identified between schizophrenia patients and healthy individuals were there before the disease was diagnosed, suggesting they may contribute to the condition."

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A two-armed mobile manipulator rolls across a steep incline, using the new approach to identify placements for its arms. Faster Path Planning for Rubble-Roving Robots
University of Michigan News
August 13, 2021

A new algorithm designed by University of Michigan (U-M) scientists could enhance the performance of robots traversing treacherous terrain. The algorithm can accelerate path planning for robots that use arm-like appendages to maintain balance on rough ground like disaster areas or construction sites. U-M's Yu-Chi Lin said, "First, we used machine learning to train the robot on the different ways it can place its hands and feet to maintain balance and make progress. Then, when placed in a new, complex environment, the robot can use what it learned to determine how traversable a path is, allowing it to find a path to the goal much faster." In a virtual experiment, a humanoid robot using the new algorithm outperformed previous methods in negotiating a corridor of rubble.

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Is Your Mobile Provider Tracking Your Location? This Technology Could Stop It.
USC Viterbi School of Engineering
Caitlin Dawson
August 12, 2021

A new system devised by researchers at the University of Southern California Viterbi School of Engineering (USC Viterbi) and Princeton University can thwart the tracking of cellphone users by network operators while maintaining seamless connectivity. The Pretty Good Phone Privacy software architecture anonymizes personal identifiers sent to cell towers, effectively severing phone connectivity from authentication and billing without altering network hardware. The system transmits an anonymous, cryptographically signed token in place of a personally identifiable signal to the tower, using a mobile virtual network operator like Cricket or Boost as a substitute or intermediary. USC Viterbi's Barath Raghavan said, "Now the identity in a specific location is separated from the fact that there is a phone at that location." The system also ensures that location-based services still function normally.

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Event Mining for Explanatory Modeling
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