Welcome to the June 8, 2022, edition of ACM TechNews, providing timely information for IT professionals three times a week.

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The new technique boosts the speeds of programs that run in the Unix shell by parallelizing the programs. Faster Computing Results Without Fear of Errors
MIT News
Adam Zewe
June 7, 2022

A multi-institutional team of researchers has developed PaSh, a system that can dramatically speed up certain types of computer programs while ensuring the accuracy of results. The system accelerates programs or scripts that run in the Unix shell, parsing their components into segments that can be run on multiple processors. PaSh parallelizes program components "just in time" to predict program behavior, speeding up more elements than traditional methods that attempt to parallelize in advance while still returning accurate results. The researchers tested PaSh on hundreds of scripts without breaking one; the system also ran programs an average six times faster than unparallelized scripts, and realized a nearly 34-fold maximum speed increase.

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How 'Trustless' Is Bitcoin, Really?
The New York Times
Siobhan Roberts
June 6, 2022

Rice University's Alyssa Blackburn and colleagues have dissected the anonymity of bitcoin, reporting in a paper that "information leakage erodes the once-impenetrable blocks, carving out a new landscape of socioeconomic data." The researchers aggregated multiple leakages and bitcoin addresses, determining 64 key agents mined most of the existing bitcoin in the first two years since the cryptocurrency's launch. Blackburn devised hacks for this period, and tapped human lapses like insecure user behavior, operational features innate to bitcoin's software, and methods for connecting pseudonymous addresses. She said very few people serve as network arbiters, "which is not the ethos of decentralized trustless crypto." Blackburn also noted that the concentration of resources undercut the network's security, with a miner's computing resources found to be commensurate to their mining income.

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Using a deep neural network of optical waveguides, the chip can detect and classify an image in less than a nanosecond. Chip Processes, Classifies Nearly Two Billion Images per Second
Penn Engineering Today
Melissa Pappas
June 1, 2022

University of Pennsylvania (Penn) engineers have designed a 9.3-square-millimeter chip that can detect and classify images in less than a nanosecond. The chip directly processes light received from objects of interest using an optical deep neural network. "Our chip processes information through what we call 'computation-by-propagation,' meaning that unlike clock-based systems, computations occur as light propagates through the chip," explained Penn's Firooz Aflatouni. "We are also skipping the step of converting optical signals to electrical signals because our chip can read and process optical signals directly, and both of these changes make our chip a significantly faster technology." Penn's Farshid Ashtiani said direct processing of optical signals makes a large memory unit unnecessary.

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A researcher deploys a hydrophone, which helps to record underwater soundscapes, for a pilot project using artificial intelligence system to identify reef health. Crackling or Desolate? AI Trained to Hear Coral's Sounds of Life
Angie Teo
June 6, 2022

U.K. and Indonesian scientists have trained an artificial intelligence (AI) system to monitor the sounds of a coral reef off islands in central Indonesia to assess its health. Ben Williams at the U.K.'s University of Exeter said a healthy reef has a "crackling, campfire-like" sound produced by the organisms living on and in it, while a degraded reef sounds more desolate. The AI system parses data points like the frequency and loudness of the sound from audio clips, and can determine whether the reef is healthy or deteriorated with at least 92% accuracy. The researchers hope the system will help conservation groups track reef health with greater efficiency.

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Scientists Use Robots to Reveal How Predatory Fish Cope with Unpredictable Prey
University of Bristol News (U.K.)
June 6, 2022

Researchers at the U.K.'s University of Bristol used robots to demonstrate how predators adapt to overcome unpredictable behavior by their prey. Using real predatory fish (blue acara cichlids) and robotic prey, the researchers found that predators that adjust their own behavior to neutralize prey’s erratic behavior. The researchers programmed the robotic prey to act predictably by escaping in the same direction in every interaction with the predator, and to act unpredictably by escaping in random directions. They found predators adjusted their speed of approach when dealing with predictable prey in a way that showed they anticipated the prey's behavior based on previous encounters. Although predators did not adjust their approach speed when dealing with unpredictable prey, the researchers found they compensated by increasing their speed during the hunt.

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Making Blockchain Stop Wasting Energy by Getting It to Manage Energy
Ars Technica
John Timmer
June 5, 2022

A group of researchers from China's Shanghai Jiao Tong and Tsinghua universities identified an optimization calculation that could make blockchain systems more energy-efficient. The researchers concentrated on the energy supply other blockchains consume, noting optimization is needed in instances like matching supply with demand, and formulating the most economic mix of generating sources. They also proposed small sub-grids could self-manage through proof-of-solution (PoSo)-based optimizations, and used energy systems at the U.K.'s University of Manchester and the city of Suzhou, China, to test the concept. In both cases, the system quickly produced optimal solutions for resource distribution, which competed with centralized management. Although the system still demands multiple computers to execute calculations and verification, the researchers contend the PoSo blockchain solution is tougher to manipulate.

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Integration Leads to Leap in Tech for Forest Inventory, Management
Purdue University News
Elizabeth K. Gardner
June 6, 2022

Purdue University researchers located, tallied, and measured more than 1,000 trees in just hours by combining aerial and ground-based mobile mapping sensors and systems. The project, part of Purdue's Digital Forestry Initiative, employs manned aircraft, unmanned aerial drones, and backpack-mounted systems that integrate cameras with light detection and ranging (LiDAR) units, along with sensors including global navigation satellite systems and inertial navigation systems. The researchers also created a machine learning algorithm to analyze the data. Purdue's Songlin Fei called the scheme "a groundbreaking development on our path to using technology for a quick, accurate inventory of the global forest ecosystem, which will improve our ability to prevent forest fires, detect disease, perform accurate carbon counting, and make informed forest management decisions."

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The researchers can monitor an entire system, such as a server, with simple radio antennas (pink). Radio Waves for the Detection of Hardware Tampering
Ruhr-Universitat Bochum
June 7, 2022

Scientists at Germany's Ruhr-Universitat Bochum (RUB), the Max Planck Institute for Security and Privacy, and information technology company PHYSEC have developed a technique that uses radio waves to monitor hardware for tampering. The radio waves can be used to detect the slightest changes in ambient conditions via a system with a sender and a receiver antenna. The transmitter emits a special signal that is reflected by walls and computer components; these reflected signals have a unique signature when they reach the receiver, which even the smallest of tampering can disrupt. RUB's Johannes Tobisch said the antennas should be placed "as close as possible to the components that require a high degree of protection," because the source of tampering is easier to identify when it is closer to the receiving antenna.

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A simulation of a galaxy cluster forming and evolving. Simulation Charts Early Universe's Development Seconds After Big Bang
Elizabeth Howell
June 6, 2022

A new simulation delineates the intergalactic medium (the gas and dust between galaxies) in the first few seconds following the Big Bang. A team of researchers led by Spain's Institute of Astrophysics of the Canary Islands used the Hydro-BAM algorithm to conduct 100,000 hours of computation. The researchers said Hydro-BAM incorporates probability, machine learning, and cosmology, and "has made it possible to obtain very accurate predictions in just a few tens of seconds." The team mapped phenomena including dark matter, energized gas, neutral hydrogen, and other cosmic elements, and also replicated spectral line patterns indicative of objects formed by hydrogen gas clouds absorbing galactic light. The researchers learned the location of these clouds by charting absorption lines in the galactic spectra.

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Scientists Develop Computational Model for Aptamer Generation
Waseda University (Japan)
June 7, 2022

The RaptGen model developed by Japanese researchers can identify new single-stranded oligonucleotides, or aptamers, not in the high-throughput systematic evolution of ligands by exponential enrichment (HT-SELEX) dataset. RaptGen's variational autoencoder uses a profile hidden Markov Model decoder to create latent spaces where nucleotide sequences can cluster, fostering the production of aptamers outside the original sequencing data or HT-SELEX library. The researchers showed the model could generate aptamer derivatives in an activity-guided process, and offer optimization opportunities. Said Waseda University's Michiaki Hamada, "It means that RaptGen can generate sequences having desired properties, such as the inhibition of certain enzymes or protein-protein interactions.”

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Model Finds Best Sites for Electric Vehicle Charging Stations
NC State University News
Matt Shipman
June 6, 2022

North Carolina State University (NC State) researchers have developed a computational model that finds the best sites for electric vehicle (EV) charging stations, and the amount of power they can use without straining the local grid. The model's power system component factors in the limitations of the local power distribution network, while its transportation component considers number of travelers, the routes they take, and how far their vehicles can go before they must recharge. The model also attempts to identify locations that will minimize travel times, in order to account for user decision-making. NC State's Leila Hajibabai said, "Ultimately, we feel the model can be used to inform the development of EV charging infrastructure at multiple levels, from projects aimed at supporting local commuters to charging facilities that serve interstate highway travel."

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The beam-steering antenna technology was developed to increase the efficiency of fixed 5G and 6G base station antennas. 'Beam-Steering' Technology Takes Mobile Communications Beyond 5G
University of Birmingham (U.K.)
June 3, 2022

A beam-steering antenna developed by researchers at the U.K.'s University of Birmingham can boost the efficiency of data transmission across the millimeter wave spectrum. The device offers continuous "wide-angle" beam steering that enables it to track a mobile phone user in motion more efficiently. Fully compatible with existing 5G specifications and comprised of a metamaterial, the antenna can control the deflection of a radio wave beam, concentrating the beam into a highly directive signal and redirecting the energy while boosting transmission efficiency. Said Birmingham's James Churm, "Our current models show that our beam-steering technology may be capable of 94% efficiency at 300 GHz.” Churm added that the technology is suitable for “next-generation use in automotive, radar, space, and defense applications."

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AI Translates Math Problems into Code to Make Them Easier to Solve
New Scientist
Alex Wilkins
June 6, 2022

Google's Yuhuai Wu and colleagues used the Codex neural network of artificial intelligence (AI) research company OpenAI to translate mathematical problems from plain English into formal code. Codex correctly translated 25% of 12,500 secondary-school math competition problems into a format compatible with a formal proof-solver program called Isabelle. Wu said the system's inability to understand certain mathematical concepts was responsible for many of the unsuccessful translations. The team then tested the process by applying Codex to problems pre-formalized by humans. The network produced its own formal versions, and the researchers used the MiniF2F AI to solve both versions; the auto-formalized versions raised MiniF2F's success rate from 29% to 35%, suggesting Codex's formalization was superior to that of humans.

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Hardness of Approximation Between P and NP
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