Welcome to the May 28, 2021 edition of ACM TechNews, providing timely information for IT professionals three times a week.

Please note: In observance of the U.S. Memorial Day holiday, TechNews will not be published on Monday, May 31. Publication will resume Wednesday, June 2.

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Google, Hospital Chain Partner in Push to Boost Efficiency
The Hill
Lexi Lonas
May 26, 2021

Google Cloud and national hospital chain HCA Healthcare announced an alliance to upgrade medical care efficiency by producing "a secure and dynamic data analytics platform for HCA Healthcare and [enabling] the development of next-generation operational models focused on actionable insights and improved workflows." The partners said they will strive to store medical devices and digital health records with Google Data. The companies also said they aim to design more effective algorithms that will "empower physicians, nurses, and others with workflow tools, analysis, and alerts on their mobile devices to help clinicians respond quickly to changes in a patient's condition."

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Artificial Neurons Recognize Biosignals in Real Time
University of Zurich (Switzerland)
May 27, 2021

A chip built from artificial neurons can decode brainwaves in real time, and can determine which brain regions trigger epileptic seizures. Researchers at Switzerland's University of Zurich, ETH Zurich, and University Hospital Zurich (UHZ) developed the chip using neuromorphic engineering, to enable the detection of previously recorded high-frequency oscillations (HFOs). The team first developed an algorithm to detect HFOs by modeling the brain's spiking neural network (SNN), then deployed the SNN in an energy-efficient device that receives neural signals via electrodes; the hardware executes calculations with a high temporal resolution, without requiring the Internet or cloud computing. UHZ's Johannes Sarnthein said, "A portable or implantable chip such as this could identify periods with a higher or lower rate of incidence of seizures, which would enable us to deliver personalized medicine."

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The Kargu-2 quadcopter armed with an explosive charge. Drones May Have Attacked Humans Fully Autonomously for the First Time
New Scientist
David Hambling
May 27, 2021

A recent report by the United Nations Security Council's Panel of Experts reveals that an incident in Libya last year may have marked the first time military drones autonomously attacked humans. Full details of the incident have not been released, but the report said retreating forces affiliated with Khalifa Haftar, commander of the Libyan National Army, were "hunted down" by Kargu-2 quadcopters during a civil war conflict in March 2020. The drones, produced by the Turkish firm STM, locate and identify targets in autonomous mode using on-board cameras with artificial intelligence, and attack by flying into the target and detonating. The report called the attack "highly effective" and said the drones did not require data connectivity with an operator.

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An old pipeline warning sign. Pipelines Now Must Report Cybersecurity Breaches
Brian Naylor
May 27, 2021

The U.S. Department of Homeland Security (DHS)' Transportation Security Administration (TSA) has announced new reporting mandates for pipeline operators following the ransomware attack on the Colonial Pipeline. Operators are required to report any cyberattacks on their systems to the federal government within 12 hours; they also must appoint a round-the-clock, on-call cybersecurity coordinator to work with the government in the event of an attack, and then have 30 days to evaluate their cyber practices. Pipeline operators must report cyberattacks to the Cybersecurity and Infrastructure Security Agency, or face fines starting at $7,000 a day. DHS says roughly 100 pipelines have been deemed critical and subject to the new directive; a DHS official said additional actions will be taken "in the not-too-distant future."

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Archaeologists vs. Computers: Study Tests Who's Best at Sifting the Past
The New York Times
Heather Murphy
May 25, 2021

Computers can sort pottery shards into subtypes at least as accurately as human archaeologists, as demonstrated by Northern Arizona University researchers. The researchers pitted a deep learning neural network against four expert archaeologists in classifying thousands of images of Tusayan White Ware pottery among nine known types; the networks outperformed two experts and equaled the other two. The network also sifted through all 3,000 photos in minutes, while each expert's analysis took three to four months. The network also could more specifically communicate its reasoning for certain categorizations than its human counterparts, and offered a single answer for each classification.

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Dr. Rickmer Braren (left) and Daniel Rueckert explore diagnostic possibilities using artificial intelligence for medical image data. AI Technology Protects Privacy
Technical University of Munich (Germany)
May 24, 2021

Technology developed by researchers at Germany's Technical University of Munich (TUM) ensures that the training of artificial intelligence (AI) algorithms does not infringe on patients' personal data. The team, collaborating with researchers at the U.K.'s Imperial College London and the OpenMined private AI technology nonprofit, integrated AI-based diagnostic processes for radiological image data that preserve privacy. TUM's Alexander Ziller said the models were trained in various hospitals on local data, so "data owners did not have to share their data and retained complete control." The researchers also used data aggregation to block the identification of institutions where the algorithm was trained, while a third technique was utilized to guarantee differential privacy. TUM's Rickmer Braren said, "It is often claimed that data protection and the utilization of data must always be in conflict. But we are now proving that this does not have to be true."

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An image from Microsoft’s Minecraft video game. You'll Soon be Able to Use Your Apple Watch Without Touching the Screen
The Wall Street Journal
Katie Deighton
May 21, 2021

Apple will launch features later this year that enable hand gesture-based control of Apple Watches and eye-motion control of iPads. The AssistiveTouch hand-movement control feature was developed to facilitate touch-free smartwatch control for users with upper-body limb differences; an Apple spokesman said it will be available to all users at launch. Apple also plans to update the iPad operating system to support third-party eye-tracking devices, and to introduce "background sounds" that iPhone users can use to minimize distractions and maintain calm. Jonathan Hassell at U.K.-based accessibility consultancy Hassell Inclusion said, "The big guys tend to do the right thing. The thing that now needs to be done is for everybody to follow their lead."

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Massive Phishing Campaign Delivers Password-Stealing Malware Disguised as Ransomware
Danny Palmer
May 24, 2021

Microsoft cybersecurity researchers said the latest version of the Java-based STRRAT malware is being distributed as part of a massive phishing campaign. The messages, sent via compromised email accounts, claim to be related to payments and contain an image that looks like a PDF attachment with information about the transfer; when opened, the file connects users to a malicious domain that downloads the malware. The addition of a .crimson file name extension aims to make the attack appear like ransomware, but actually a remote access trojan is placed on the PC to steal usernames, passwords, and other information through a backdoor into Windows systems. Victims' email accounts could be used by the attackers in new phishing emails to spread the STRRAT malware. Users can protect themselves by using antivirus software and exerting caution when opening emails and attachments from unknown senders.

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An intricate 3D-printed biomedical structure at the tip of a gloved finger. Technique Breaks the Mold for 3D-Printing Medical Implants
Royal Melbourne Institute of Technology (Australia)
Gosia Kaszubska
May 26, 2021

The development of three-dimensionally (3D)-printed molds by researchers at Australia's Royal Melbourne Institute of Technology (RMIT) invert the traditional 3D printing of medical implants. The Negative Embodied Sacrificial Template 3D (NEST3D) printing method generates molds featuring intricately patterned cavities filled with biocompatible materials; these are dissolved in water and leave behind fingernail-sized bioscaffolds with elaborate structures that standard 3D printers could not previously produce. The RMIT researchers developed NEST3D with collaborators at the University of Melbourne and St. Vincent's Hospital Melbourne. RMIT's Cathal O'Connell said, "We essentially draw the structure we want in the empty space inside our 3D-printed mold. This allows us to create the tiny, complex microstructures where cells will flourish." RMIT's Stephanie Doyle said the technique's versatility allowed the production of dozens of trial bioscaffolds using a range of materials.

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A Volkswagen commercial vehicle. Germany Greenlights Driverless Vehicles on Public Roads
Tech Crunch
Rebecca Bellan
May 24, 2021

Legislation passed by the lower house of Germany's parliament would permit driverless vehicles on that nation’s public roads by 2022. The bill specifically addresses vehicles with the Society of Automobile Engineers' Level 4 autonomy designation, which means all driving is handled by the vehicle’s computer in certain conditions. The legislation also details possible initial applications for self-driving cars, including public passenger transport, business and supply trips, logistics, company shuttles, and trips between medical centers and retirement homes. Commercial driverless vehicle operators would have to carry liability insurance and be able to stop autonomous operations remotely, among other requirements. The bill still needs the approval of the upper chamber of parliament to be enacted into law.

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UVA Develops Tools to Battle Cancer, Advance Genomics Research
UVA Health Newsroom
May 24, 2021

A computational method that maps the folding patterns of human chromosomes from experimental data could help combat cancer while furthering genomics science. Developed by scientists at the University of Virginia (UVA) School of Medicine, the BART3D technique compares available three-dimensional (3D) configuration data about a chromosomal region with that of neighboring regions, then uses the Binding Analysis for Regulation of Transcription (BART) algorithm to fill in gaps in the genetic template with information from the comparison. The resulting map yields unprecedented insights about genetic interaction with transcriptional regulators. The UVA researchers also built the BARTweb server to offer free access to the BART tool. UVA's Chongzhi Zang said, "We hope that the tools and resources we develop can benefit the whole biomedical research community by accelerating scientific discoveries and future therapeutic development."

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Digger finger robots, as they dig through granular material like sand and gravel Slender Robotic Finger Senses Buried Items
MIT News
Daniel Ackerman
May 26, 2021

Massachusetts Institute of Technology (MIT) researchers have developed a slender robot finger with a sharp tip and tactile sensing capabilities that can help identify buried objects. Dubbed "Digger Finger," the robot can sense the shape of items submerged within granular materials like sand or rice. The researchers adapted their GelSight tactile sensor for the Digger Finger, and added vibration to make it easier for the robot to clear jams in the granular media that occur when particles lock together. MIT’s Radhen Patel said the Digger Finger's motion pattern must be adjusted based on the type of media in which it is searching, and the size and shape of its grains. MIT’s Edward Adelson said the Digger Finger “would be helpful if you’re trying to find and disable buried bombs, for example.”

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An ultrasound image of a normal fetus showing heart structures. Fetal Heart Defect Detection Improved by Using ML
University of California, San Francisco News
Elizabeth Fernandez
May 26, 2021

University of California, San Francisco (UCSF) researchers doubled the accuracy of doctors in detecting fetal heart defects in unborn children by integrating ultrasound imaging with machine learning (ML). The researchers trained ML models to mimic tasks that doctors conduct in diagnosing congenital heart disease (CHD). The technique employs neural networks to find five views of the heart, then uses neural networks again to decide whether each view is normal; finally, a third algorithm combines the results of the first two into a diagnosis of fetal-heart normality or abnormality. Humans typically detect 30% to 50% of CHD cases in utero, while the UCSF system detected 95% of CHD cases in the test dataset. UCSF's Rima Arnaout said, "Our goal is to help forge a path toward using machine learning to solve diagnostic challenges for the many diseases where ultrasound is used in screening and diagnosis."

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