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    University of the Chinese Academy of Sciences Reports Findings in Artificial Int elligence (Next-Generation Patient-Based Real-Time Quality Control Models)

    66-67页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news originating from Beijing, People 's Republic of China, by NewsRx correspondents, research stated, "Patient-based real-time QC (PBRTQC) uses patient-derived data to assess assay performance. PBR TQC algorithms have advanced in parallel with developments in computer science a nd the increased availability of more powerful computers." Our news journalists obtained a quote from the research from the University of t he Chinese Academy of Sciences, "The uptake of Artificial Intelligence in PBRTQC has been rapid, with many stated advantages over conventional approaches. Howev er, until this review, there has been no critical comparison of these. The PBRTQ C algorithms based on moving averages, regression-adjusted real-time QC, neural networks and anomaly detection are described and contrasted."
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    Central South University Reports Findings in Osteosarcomas (Machine learning sur vival prediction using tumor lipid metabolism genes for osteosarcoma)

    67-68页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Oncology - Osteosarcom as is the subject of a report. According to news originating from Hunan, People' s Republic of China, by NewsRx correspondents, research stated, "Osteosarcoma is a primary malignant tumor that commonly affects children and adolescents, with a poor prognosis. The existence of tumor heterogeneity leads to different molecu lar subtypes and survival outcomes." Financial support for this research came from National Natural Science Foundatio n of China. Our news journalists obtained a quote from the research from Central South Unive rsity, "Recently, lipid metabolism has been identified as a critical characteris tic of cancer. Therefore, our study aims to identify osteosarcoma's lipid metabo lism molecular subtype and develop a signature for survival outcome prediction. Four multicenter cohorts-TARGET-OS, GSE21257, GSE39058, and GSE16091-were amalga mated into a unified Meta-Cohort. Through consensus clustering, novel molecular subtypes within Meta-Cohort patients were delineated. Subsequent feature selecti on processes, encompassing analyses of differentially expressed genes between su btypes, univariate Cox analysis, and StepAIC, were employed to pinpoint biomarke rs related to lipid metabolism in TARGET-OS. We selected the most effective algo rithm for constructing a Lipid Metabolism-Related Signature (LMRS) by utilizing four machine-learning algorithms reconfigured into ten unique combinations. This selection was based on achieving the highest concordance index (Cindex) in the test cohort of GSE21257, GSE39058, and GSE16091. We identified two distinct lip id metabolism molecular subtypes in osteosarcoma patients, C1 and C2, with signi ficantly different survival rates. C1 is characterized by increased cholesterol, fatty acid synthesis, and ketone metabolism. In contrast, C2 focuses on steroid hormone biosynthesis, arachidonic acid, and glycerolipid and linoleic acid meta bolism. Feature selection in the TARGET-OS identified 12 lipid metabolism genes, leading to a model predicting osteosarcoma patient survival. The LMRS, based on the 12 identified genes, consistently accurately predicted prognosis across TAR GET-OS, testing cohorts, and Meta-Cohort. Incorporating 12 published signatures, LMRS showed robust and significantly superior predictive capability."
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    Wuhan Institute of Technology Researcher Has Published New Data on Support Vecto r Machines (Early Warning for Continuous Rigid Frame Bridges Based on Nonlinear Modeling for Temperature- Induced Deflection)

    68-69页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on support vector machines are presented in a new report. According to news reporting from Wuhan, People's Republic of China, by NewsRx journalists, research stated, "Bridge early warning based on structural health monitoring (SHM) system is of significant importance for ensuring bridge safe operation." Financial supporters for this research include National Natural Science Foundati on of China; Open Projects Foundation of Engineering Research Center of Disaster Prevention And Mitigation of Southeast Coastal Engineering Structures of Fujian Province University; Construction Science And Technology Plan Projects of Hubei Province.
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    Reports Outline Robotics Study Findings from Ningbo University (A Spatiotemporal Graphical Attention Navigation Algorithm Based On Limited State Information)

    69-70页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators publish new report on Robotics. Acc ording to news originating from Ningbo, People's Republic of China, by NewsRx co rrespondents, research stated, "Safe and efficient navigation of a robot in a hi gh-density and dynamic crowd is a challenging task. Most of existing navigation algorithms need to acquire the full dynamics of neighboring humans at all times, making them heavily dependent on a complex upper level information state estima tion process." Funders for this research include Natural Science Foundation of Zhejiang Provinc e, Ningbo Science Technology Plan projects of China.
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    Studies from Saarland University Yield New Information about Machine Learning (I mproved Carbide Volume Fraction Estimation In As-cast Hcci Alloys Using Machine Learning Techniques)

    70-71页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ma chine Learning. According to news originating from Saarbrucken, Germany, by News Rx correspondents, research stated, "An improved approach is presented for the e stimation of carbide volume fraction (CVF) in as-cast High Chromium Cast Iron (H CCI) alloys using Machine Learning (ML) techniques." Financial supporters for this research include German Research Foundation (DFG), EFRE Funds of the European Commission, State Chancellery of Saarland. Our news journalists obtained a quote from the research from Saarland University , "The limitations of existing formulae for CVF estimation in HCCI alloys, which relied on a limited number of alloy compositions, are addressed."
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    Studies from Lawrence Livermore National Laboratory Have Provided New Informatio n about Machine Learning (Integrating Machine Learning Potential and X-ray Absor ption Spectroscopy for Predicting the Chemical Speciation of Disordered Carbon . ..)

    71-72页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators discuss new findings in Machine Learning. According to news originating from Livermore, California, by N ewsRx correspondents, research stated, "Precise determination of atomic structur al information in functional materials holds transformative potential and broad implications for emerging technologies. Spectroscopic techniques, such as X-ray absorption near-edge structure (XANES), have been widely used for material chara cterization; however, extracting chemical information from experimental probes r emains a significant challenge, particularly for disordered materials." Financial supporters for this research include United States Department of Energ y (DOE), United States Department of Energy (DOE), Laboratory Directed Research and Development (LDRD) program, United States Department of Energy (DOE).
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    Findings on Robotics Detailed by Investigators at Obuda University (Electric Veh icle Charging Socket Detection Using Yolov8s Model)

    72-72页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ro botics. According to news reporting originating in Budapest, Hungary, by NewsRx journalists, research stated, "This paper introduces the utilization of the late st small You Only Look Once version 8 - YOLOv8s convolutional neural network in an automatic electric vehicle charging application study." Financial supporters for this research include Obuda University, University of D unaujvaros. The news reporters obtained a quote from the research from Obuda University, "Th e employment of a deep learning -based object detector is a novel and significan t aspect in robotic applications, since it is both, the initial and the fundamen tal step in a series of robotic operations, where the intent is to detect and lo cate the charging socket on the vehicle's body surface. The aim was to use a ren owned and reliable object detector to ensure the reliable and smooth functioning of the deployed robotic vision system in an industrial environment."
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    New Robotics Study Findings Recently Were Reported by Researchers at Xiamen Univ ersity of Technology (Model-free Visual Servoing Based On Active Disturbance Rej ection Control and Adaptive Estimator for Robotic Manipulation Without Calibrati on)

    73-74页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Investigators publish new report on Ro botics. According to news reporting out of Xiamen, People's Republic of China, b y NewsRx editors, research stated, "PurposeVisual feedback control is a promisin g solution for robots work in unstructured environments, and this is accomplishe d by estimation of the time derivative relationship between the image features a nd the robot moving. While some of the drawbacks associated with most visual ser voing (VS) approaches include the vision-motor mapping computation and the robot s' dynamic performance, the problem of designing optimal and more effective VS s ystems still remains challenging." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Natural Science Foundation of Fujian Province.
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    Reports Summarize Robotics Study Results from Shandong University of Science and Technology (Adaptive Admittance Tracking Control for Interactive Robot With Pre scribed Performance)

    74-74页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Fresh data on Robotics are presented i n a new report. According to news reporting originating in Qingdao, People's Rep ublic of China, by NewsRx journalists, research stated, "An adaptive control app roach is presented in this paper for tracking desired trajectories in interactiv e manipulators. The controller design incorporates prescribed performance functi ons (PPFs) to improve dynamic performance." Financial support for this research came from National Natural Science Foundatio n of China (NSFC). The news reporters obtained a quote from the research from the Shandong Universi ty of Science and Technology, "Notably, the performance of the output error is c onfined in an envelope characterized by exponential convergence, leading to conv ergence to zero. This feature ensures a prompt response from admittance control and establishes a reliable safety framework for interactions." According to the news reporters, the research concluded: "Simulation results pro vide practical insights, demonstrating the viability of the control scheme propo sed in this paper."
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    Massachusetts General Hospital and Harvard Medical School Reports Findings in Ma chine Learning (No code machine learning: validating the approach on use-case fo r classifying clavicle fractures)

    75-75页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Machine Learning is th e subject of a report. According to news reporting originating from Boston, Unit ed States, by NewsRx correspondents, research stated, "We created an infrastruct ure for no code machine learning (NML) platform for non-programming physicians t o create NML model. We tested the platform by creating an NML model for classify ing radiographs for the presence and absence of clavicle fractures." Our news editors obtained a quote from the research from Massachusetts General H ospital and Harvard Medical School, "Our IRB-approved retrospective study includ ed 4135 clavicle radiographs from 2039 patients (mean age 52 ± 20 years, F:M 102 2:1017) from 13 hospitals. Each patient had two-view clavicle radiographs with a xial and anterior-posterior projections. The positive radiographs had either dis placed or non-displaced clavicle fractures. We configured the NML platform to au tomatically retrieve the eligible exams using the series' unique identification from the hospital virtual network archive via web access to DICOM Objects. The p latform trained a model until the validation loss plateaus. Once the testing was complete, the platform provided the receiver operating characteristics curve an d confusion matrix for estimating sensitivity, specificity, and accuracy. The NM L platform successfully retrieved 3917 radiographs (3917/4135, 94.7 % ) and parsed them for creating a ML classifier with 2151 radiographs in the trai ning, 100 radiographs for validation, and 1666 radiographs in testing datasets ( 772 radiographs with clavicle fracture, 894 without clavicle fracture). The netw ork identified clavicle fracture with 90 % sensitivity, 87 % specificity, and 88 % accuracy with AUC of 0.95 (confidence interv al 0.94-0.96)."
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