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Welcome to the June 18, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.

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U.S., EU Establish Trade, Technology Council to Compete with China U.S., EU Establish Trade, Technology Council to Compete with China
The Hill
Maggie Miller
June 15, 2021

A Trade and Technology Council (TTC) established by the U.S. and the EU this week will help to coordinate on critical technology issues and support their competition with China. An official statement from a U.S.-EU summit in Brussels read, "We plan to cooperate on the development and deployment of new technologies based on our shared democratic values, including respect for human rights, and that encourages compatible standards and regulations." Among other things, the TTC will address the semiconductor shortage, the creation of standards for artificial intelligence and Internet-connected technologies, and the securing of critical telecommunications systems. Also established at the summit was a Joint Technology Competition Policy Dialogue to foster cooperation on issues like biotechnology and genomics, and to increase U.S.-EU sharing of information on cybersecurity threats.

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Workers tending IBM Quantum System One. Germany Unveils Quantum Computer to Keep Europe in Global Tech Race
Clothilde Goujard
June 15, 2021

Germany unveiled a quantum computer this week. Under construction by IBM, the device will be managed by German research organization Fraunhofer-Gesellschaft, for use by researchers and companies developing and testing quantum algorithms. Germany announced last year a €2-billion (U.S.$2.37-billion) investment in quantum over the ensuing five years, supplemented by the European Commission's €1-billion (U.S.$1.19-billion) fund for quantum technologies. Chancellor Angela Merkel indicated that it is time for Europe to catch up to the U.S. and China, which hold the greatest number of patents related to quantum computing. Fraunhofer-Gesellschaft's Reimund Neugebauer said partnerships have been forged with companies and universities to use the computer, although he declined to name them.

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Malicious Content Exploits Pathways Between Platforms to Thrive Online, Subvert Moderation
George Washington University Today
June 16, 2021

New research indicates that malicious COVID-19 content circumvents social media platforms' moderation initiatives to prosper online. George Washington University (GW) investigators combined machine learning with network data science to detail malicious content's exploitation of pathways between platforms. The team mapped the interconnection of hate clusters to spread their narratives across Facebook, VKontakte, Instagram, Gab, Telegram, and 4Chan. They found the COVID-19 discussion solidified in the early phases of the pandemic, with hate clusters subverting moderation via adaptive methods to regroup on other platforms and/or re-infiltrate a platform. GW's Yonatan Lupu said, "Our study demonstrates a similarity between the spread of online hate and the spread of a virus. Individual social media platforms have had difficulty controlling the spread of online hate, which mirrors the difficulty individual countries around the world have had in stopping the spread of the COVID-19 virus."

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The Mayflower Autonomous Ship at dock. Robotic Ship Sets Off to Retrace the Mayflower's Journey
Associated Press
Urooba Jamal
June 15, 2021

The Mayflower Autonomous Ship set off this week to retrace the journey of its 1620 namesake across the Atlantic Ocean. The robotic ship, piloted by artificial intelligence (AI) technology and carrying no human crew or passengers, will make the trans-Atlantic crossing from Plymouth, U.K., to Provincetown, MA, and then to Plymouth, MA, in three weeks or less. Built by IBM and the nonprofit marine research organization ProMare, the 50-foot trimaran is propelled by a solar-powered hybrid electric motor and will gather data as it goes on ocean acidification, microplastics, and marine mammal conservation using AI-powered cameras and onboard sensors. The $1.3-million ship's journey can be followed online at

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Mehrdad Nojoumian in Florida Atlantic University’s autonomous vehicle lab Invention Uses Machine-Learned Human Emotions to 'Drive' Autonomous Vehicles
Florida Atlantic University
Gisele Galoustian
June 16, 2021

Florida Atlantic University (FAU)'s Mehrdad Nojoumian has designed and patented new technology for autonomous systems that uses machine-learned human moods to respond to human emotions. Nojoumian's adaptive mood control system employs non-intrusive sensory solutions in semi- or fully autonomous vehicles to read the mood of drivers and passengers. In-vehicle sensors collect data based on facial expressions and other emotional cues of the vehicle's occupants, then use real-time machine learning mechanisms to identify occupants' moods over time. The vehicle responds to perceived emotions by selecting a suitable driving mode (normal, cautious, or alert). FAU's Stella Batalama said Nojoumian's system overcomes self-driving vehicles' inability to accurately forecast the behavior of other self-driving and human-driven vehicles.

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A narwhal swimming. Algorithm Reveals Mysterious Foraging Habits of Narwhals
University of Copenhagen (Denmark)
June 16, 2021

Researchers at Denmark's University of Copenhagen and the Greenland Institute of Natural Resources utilized algorithms in their study of the foraging habits of narwhals, and how they may be affected by human disturbances and global warming. The researchers used artificial intelligence to detect patterns in the way narwhals move and the sounds they emit. Among their findings was that certain sounds indicate when narwhals are hunting prey. University of Copenhagen’s Raghavendra Selvan said, “The major challenge was that these whales have very complex movement patterns, which can be tough to analyze. This becomes possible only with the use of deep learning, which could learn to recognize both the various swimming patterns of whales, as well as their buzzing sounds. The algorithm then discovered connections between the two.”

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Canadian Regulators Seek Policy Amendments for Facial Recognition
The Wall Street Journal
Jared Council
June 14, 2021

Canada's Office of the Privacy Commissioner has cited the Royal Canadian Mounted Police (RCMP) for breaking federal privacy law by using facial recognition software from Clearview AI. Regulators said Clearview compiled biometric information without the knowledge or consent of individuals; the company has a database of roughly 3 billion photos harvested from the Internet. Canadian Privacy Commissioner Daniel Therrien also requested clarification from Canada's Parliament on the treatment of online images of people's faces, and said police must ensure third-party data providers' information collection practices comply with privacy statutes. Therrien said Canadian laws should stipulate that the concept of publicly available personal information "does not apply to information where an individual has a reasonable expectation of privacy."

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McAfee Finds Security Vulnerability in Peloton Products
NBC News
Liat Weinstein; Vicky Nguyen
June 15, 2021

Researchers at software security company McAfee discovered a vulnerability in the Peloton Bike+ that could enable attackers to install malware in the system through a USB port. The flaw, which the researchers said was associated with the Android attachment accompanying the Bike+, could allow attackers to access its webcam and spy on riders and their surroundings. It also could allow them to install fake versions of popular apps like Netflix and Spotify, and capture riders' personal information. McAfee's Steve Povolny said, "The flaw was that Peloton actually failed to validate that the operating system loaded. And ultimately what that means then is they can install malicious software, they can create Trojan horses and give themselves back doors into the bike, and even access the webcam." Peloton confirmed it was working with McAfee to fix the issue, adding that it recently pushed a mandatory update to affected devices to address the vulnerability.

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Researchers Identify 16 Medicines That Could Be Used to Treat COVID-19
RUVID (Spain)
June 16, 2021

Researchers from the ESI International Chair of the CEU Cardenal Herrera University and ESI Group used a new computational topology strategy to determine which existing medicines could be used to treat COVID-19. The model uses topologic data analysis to compare the three-dimensional structure of the target proteins of known medicines to SARS-CoV-2 coronavirus proteins, such as protein NSP12. The researchers studied 1,825 medicines approved by the U.S. Food and Drug Administration, which are connected to 27,830 protein structures. In comparing the topological structure of the proteins available in the Protein Data Bank with the 23 proteins of the SARS-CoV-2 coronavirus, they identified 16 medicines that act against the three viral proteins found to have highly significant topological similarities to target protein structures of the known medicines. These drugs can now be studied to determine the most effective combination of them to treat COVID-19 symptoms.

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An infographic showing the screening procedure to maximize the success rate of materials discovery for the solar generation of hydrogen fuels. Computers Help Researchers Find Materials to Turn Solar Power into Hydrogen
Pennsylvania State University News
Matt Swayne
June 16, 2021

A team led by Pennsylvania State University (Penn State) researchers has shown how supercomputers can identify materials that could help separate hydrogen from water using solar energy. The researchers developed an algorithm to identify materials in the online open access Materials Project database that have the properties of suitable photocatalysts, which can enable the solar hydrogen production process when added to water. They examined such things as the band gap, or the ideal energy range for the materials to absorb sunlight, as well as which materials can dissociate water effectively and which have good chemical stability. Penn State's Yihuang Xiong said, "We believe the integrated computational-experimental workflow that we have developed can considerably accelerate the discovery of efficient photocatalysts."

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An infographic of the model parsing flow. MSU, Facebook Develop Research Model to Fight Deepfakes
Michigan State University
June 16, 2021

A new reverse-engineering approach developed by artificial intelligence experts at Michigan State University (MSU) and Facebook aims to identify and attribute "deepfakes." Facebook's Tal Hassner said, "With model parsing, we can estimate properties of the generative models used to create each deepfake, and even associate multiple deepfakes to the model that possibly produced them. This provides information about each deepfake, even ones where no prior information existed." The researchers tested their approach using a dataset of 100,000 synthetic images produced by 100 publicly available generative models, and found that it outperformed the random baselines of previous detection models. MSU's Xiaoming Liu said, "Our framework can not only perform model parsing, but also extend to deepfake detection and image attribution."

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An artistic rendering showing what happens when a high-energy cosmic ray hits a qubit chip. Correlated Errors in Quantum Computers Emphasize Need for Design Changes
University of Wisconsin-Madison News
Sarah Perdue
June 16, 2021

A team led by researchers at the University of Wisconsin–Madison found clues that errors correlate across an entire superconducting quantum computing chip, which must be addressed to develop fault-tolerant quantum computers. After observing in previous experiments that multiple qubits were flipping at the same time, the researchers set out to determine whether the flips were independent or correlated. The team designed a four-qubit superconducting chip and measured fluctuations in offset charge for each qubit; they found sudden increases in offset charge following long periods of relative stability, and that the closer together two qubits were, the more likely they were to jump simultaneously. The researchers said the qubit flips were correlated across the entire chip as the energy spread.

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A photo from 2009 shows German Chancellor Angela Merkel holding a cellphone with a photo of her on the screen. Security Flaw Found in 2G Mobile Data Encryption Standard
Associated Press
June 16, 2021

Cybersecurity researchers from Germany, France, and Norway have identified a flaw in the GEA-1 encryption algorithm that affects the GPRS or 2G mobile data standard. The vulnerability may have enabled attackers to eavesdrop on some data traffic for decades. The researchers said it likely was created intentionally as a "backdoor" for law enforcement agencies. Germany-based Ruhr University Bochum's Christof Beierle said, "According to our experimental analysis, having six correct numbers in the German lottery twice in a row is about as likely as having these properties of the key occur by chance." The GEA-1 algorithm was found in current Android and iOS smartphones, though it was supposed to have been phased out starting in 2013. Most current phones use 4G or 5G mobile data standards, but GPRS remains a fallback for data connections in some countries.

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