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    Researchers from China Agricultural University Report Details of New Studies and Findings in the Area of Machine Learning (Multifrequency Bioimpedance Combined With Machine Learning for Frozen-thawed Quality Evaluation of Atlantic Salmon)

    146-147页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Research findings on Machine Learning are discussed in a new report. According tonews reporting out of Beijing, Peopl e’s Republic of China, by NewsRx editors, research stated, “Ensuring the freshne ss of salmon in the face of freezing and thawing cycles during cold chain transp ortation is acritical challenge, particularly as some merchants may mislabel fr ozen-thawed salmon as fresh for higherprofits. In this study, we developed an a dvanced monitoring system to track changes in bioimpedancesignals and quality p arameters of salmon.”

    Jiangnan University Reports Findings in Adenocarcinoma (Preoperative Prediction of Perineural Invasion in Pancreatic Ductal Adenocarcinoma Using Machine Learnin g Radiomics Based on Contrast-Enhanced CT Imaging)

    147-148页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Oncology - Adenocarcin oma is the subject of a report. Accordingto news reporting from Jiangsu, People ’s Republic of China, by NewsRx journalists, research stated, “Theobjective of the study is to assess the clinical value of machine learning radiomics based on contrastenhancedcomputed tomography (CECT) images in preoperative prediction of perineural invasion (PNI)status in pancreatic ductal adenocarcinoma (PDAC). A total of 143 patients with PDAC were enrolled inthis retrospective study (tra ining group, n = 100; test group, n = 43).”

    Recent Findings from Xi’an Jiaotong University Provides New Insights into Roboti cs (Rigid-soft Hybrid Suction Cups for Enhanced Anti-torque and Energy-efficient Attachment)

    148-149页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on Robotics have been pr esented. According to news reporting originatingfrom Xi’an, People’s Republic o f China, by NewsRx correspondents, research stated, “In the realm ofrobotics, s uction-based adhesion plays a pivotal role in applications ranging from object t ransfer towall-climbing robots. To improve the sealing and attachment stability of suction cups, researchers have employed state-of-the-art techniques, includi ng the use of soft materials with better conformal propertiesor jamming mechani sms.”

    Liaoning University of Traditional Chinese Medicine Reports Findings in Atherosc lerosis (Identification of key genes for cuproptosis in carotid atherosclerosis)

    149-150页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Cardiovascular Disease s and Conditions - Atherosclerosis is the subjectof a report. According to news reporting from Liaoning, People’s Republic of China, by NewsRx journalists,res earch stated, “Atherosclerosis is a leading cause of cardiovascular disease worl dwide, while carotidatherosclerosis (CAS) is more likely to cause ischemic cere brovascular events. Emerging evidence suggeststhat cuproptosis may be associate d with an increased risk of atherosclerotic cardiovascular disease.”

    Reports Outline Artificial Intelligence Findings from Biomedical University of R ome (Combining Fiber Bragg Grating and Artificial Intelligence Technologies for Supporting Epidural Procedures)

    150-151页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on Ar tificial Intelligence. According to news reportingoriginating in Rome, Italy, b y NewsRx journalists, research stated, “Loss of resistance (LOR) is a widely accepted method for performing epidural punctures in clinical settings. However, th e risk of failure associatedwith LOR is still high.”

    Tongji University Reports Findings in Machine Learning (A novel hybrid variable cross layer-based machine learning model improves the accuracy and interpretatio n of energy intensity prediction of wastewater treatment plant)

    151-152页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Machine Learning is th e subject of a report. According to newsreporting out of Shanghai, People’s Rep ublic of China, by NewsRx editors, research stated, “Energyintensity (EI) predi ction in wastewater treatment plants (WWTPs) suffers from inaccuracy and non-interpretability due to poor data quality, complex mechanisms and various confoundi ng variables. In thisstudy, the novel hybrid variable cross layer-based machine learning (VCL-ML) model was devised, which generates new knowledge with monitor ing indicators (e.g., COD, etc.) and then embeds both domainknowledge and monit oring indicators into the ML model.”

    New Machine Learning Findings from University of Texas Austin Discussed [Machine-learning-assisted Seismic Prediction of Massive (Up To 500 M) Sands and Their Geologic Meaning: Lower Wilcox Intraslope Basins, South-central Texas, Usa ]

    152-153页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - A new study on Machine Learning is now available. According to news reportingoriginating in Austin, Texas, by NewsRx journalists, research stated, “We studied deep (up to 6000 m)Lower Wilcox strat a (Guadalupe A) immediately above the Midway shale using a 1000-km2 3D seismicv olume and sparse six deep-well, wireline-log data in south-central Texas. Althou gh some of the wells encounter sandstones collectively as thick as 500 m, tradit ional seismic attributes and seismic inversionare unable to reveal the sign and extent of the massive sand distribution in the intraslope minibasins.”

    Researchers from Xi’an Technological University Report on Findings in Artificial Intelligence (Research On Numerical Simulation and Prediction of Tool Wear In C utting Ultra-high-strength Aluminum Alloys)

    153-154页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews - Research findings on Artificial Intelligence are discussed in a new report. According to newsreporting from Shaanxi, People’s Re public of China, by NewsRx journalists, research stated, “The objectiveof this research is to predict tool wear by quickly and accurately analyzing the cutting parameters range ofthe machinable area that the typical hard-to-machine materi al, 7075 ultra-high-strength aluminum alloy.Firstly, the four-factor and four-l evel cutting finite element simulation model is established, and the rangeanaly sis of the orthogonal experiment results is carried out.”

    Data from National Institute of Standards and Technology Provide New Insights in to Robotics (Toward a Digital Twin of a Robot Workcell: Standards and Methods)

    154-155页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Current study results on Robotics have been published. According to news reportingout of Gaithersburg, Maryland, by N ewsRx editors, research stated, “Digital twins are poised to improvethe enginee ring, operation, and management of manufacturing facilities. However, implementi ng digitaltwins has been a challenge primarily due to a lack of resources and t he absence of standardized digitaltwin frameworks and methods.”

    First Affiliated Hospital of Chongqing Medical University Reports Findings in Su pport Vector Machines (Resting-state functional magnetic resonance imaging and s upport vector machines for the diagnosis of major depressive disorder in adolesc ents)

    155-156页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - New research on Support Vector Machine s is the subject of a report. Accordingto news reporting originating from Chong qing, People’s Republic of China, by NewsRx correspondents,research stated, “Re search has found that the amygdala plays a significant role in underlying pathol ogy ofmajor depressive disorder (MDD). However, few studies have explored machi ne learning-assisted diagnosticbiomarkers based on amygdala functional connecti vity (FC).”