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    Shengjing Hospital Affiliated to China Medical University Reports Findings in Bi oinformatics (Potential therapeutic targets for COVID-19 complicated with pulmon ary hypertension: a bioinformatics and early validation study)

    104-105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 Biotechnology - Bioinf ormatics is the subject of a report. According to news reporting out of Shenyang , People’s Republic of China, by NewsRx editors, research stated, “Coronavirus d isease (COVID-19) and pulmonary hypertension (PH) are closely correlated. Howeve r, the mechanism is still poorly understood.” Funders for this research include National Natural Science Foundation of China, Liaoning science and technology project. Our news journalists obtained a quote from the research from Shengjing Hospital Affiliated to China Medical University, “In this article, we analyzed the molecu lar action network driving the emergence of this event. Two datasets (GSE113439 and GSE147507) from the GEO database were used for the identification of differe ntially expressed genes (DEGs).Common DEGs were selected by VennDiagram and thei r enrichment in biological pathways was analyzed. Candidate gene biomarkers were selected using three different machine-learning algorithms (SVM-RFE, LASSO, RF) .The diagnostic efficacy of these foundational genes was validated using indepen dent datasets. Eventually, we validated molecular docking and medication predict ion. We found 62 common DEGs, including several ones that could be enriched for Immune Response and Inflammation. Two DEGs (SELE and CCL20) could be identified by machinelearning algorithms. They performed well in diagnostic tests on indep endent datasets. In particular,we observed an upregulation of functions associa ted with the adaptive immune response, the leukocytelymphocyte- driven immunolog ical response, and the proinflammatory response. Moreover, by ssGSEA, natural ki ller T cells, activated dendritic cells, activated CD4 T cells, neutrophils, and plasmacytoid dendritic cells were correlated with COVID-19 and PH, with SELE an d CCL20 showing the strongest correlation with dendritic cells. Potential therap eutic compounds like FENRETI-NIDE, AFLATOXIN B1 and 1-nitropyrene were predicted .”
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    University of Wisconsin Madison Reports Findings in Machine Learning (Phase Tran sition in Silicon from Machine Learning Informed Metadynamics)

    105-106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 in Madison, Unite d States, by NewsRx journalists, research stated, “Investigating reconstructive phase transitions in large-sized systems requires a highly efficient computation al framework with computational cost proportional to the system size. Traditiona lly, widely used frameworks such as density functional theory (DFT) have been pr ohibitively expensive for extensive simulations on large systems that require lo ng-time scales.”The news reporters obtained a quote from the research from the University of Wis consin Madison, “To address this challenge, this study employed well-trained mac hine learning potential to simulate phase transitions in a large-size system. Th is work integrates the metadynamics simulation approach with machine learning po tential, specifically deep potential, to enhance computational efficiency and ac celerate the study of phase transition and consequent development of grains and dislocation defects in a system. The new method is demonstrated using the phase transitions of bulk silicon under high pressure.”
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    Sun Yat-sen University Reports Findings in Artificial Intelligence (Validation o f Artificial Intelligence-based Bowel Preparation Assessment in Screening Colono scopy)

    106-107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 reporting originating in Shenzhe n, People’s Republic of China, by NewsRx journalists, research stated, “Accurate bowel preparation assessment is essential for determining colonoscopy screening intervals. Patients with suboptimal bowel preparation are at a high risk of mis sing >5mm adenomas, and should undergo an early repeat c olonoscopy.” The news reporters obtained a quote from the research from Sun Yat-sen Universit y, “In this study, we employed artificial intelligence (AI) to evaluate bowel pr eparation and validated the ability of the system in accurately identifying pati ents who are at high risk of missing >5mm adenoma due to inadequate bowel preparation. This prospective, single-center, observational st udy was conducted at the Eighth Affiliated Hospital, Sun Yat-sen University from October 8, 2021, to November 9, 2022. Eligible patients underwent screening col onoscopy were consecutively enrolled. The AI assessed bowel preparation using e- Boston Bowel Preparation Scale (BBPS) while endoscopists evaluated using BBPS. I f both BBPS and e-BBPS deemed preparation adequate, the patient immediately unde rwent a second colonoscopy, otherwise the patient underwent bowel re-cleansing b efore the second colonoscopy. Among the 393 patients, 72 > 5mm adenomas were detected, while 27 >5mm adenomas were missed. In unqualified-AI patients, the >5mm AMR was sig nificantly higher than in qualified-AI patients (35.71% vs 13.19% , p=0.0056, OR 0.2734, 95% CI 0.1139, 0.6565), as were the AMR (50 .89% vs 20.79%, p<0.001, OR 0.25 32, 95% CI 0.1583, 0.4052) and >5mm PMR (3 5.82% vs 19.48%, p=0.0152, OR 0.4335, 95% CI 0.2288, 0.8213).”
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    Data on Robotics and Automation Described by Researchers at Beijing Institute of Technology (Macim: Multi-agent Collaborative Implicit Mapping)

    107-108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 Robotics - Robotics an d Automation is the subject of a report. According to news reporting from Beijin g, People’s Republic of China, by NewsRx journalists, research stated, “Collabor ative mapping aids agents in achieving an efficient and comprehensive understand ing of their environment. Recently, there has been growing interest in using neu ral networks as maps to represent functions that implicitly define the geometric features of a scene.” Financial support for this research came from National Natural Science Foundatio n of China (NSFC).
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    New Robotics Study Findings Have Been Published by a Researcher at Iqra Universi ty (On-line task allocation for multi-robot teams under dynamic scenarios)

    108-109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 from Karachi, Pakistan, by NewsRx jo urnalists, research stated, “Multi-Robot Task Allocation (MRTA) is a complex pro blem domain with the majority of problem representations categorized as NP-hard. ” Our news journalists obtained a quote from the research from Iqra University: “E xisting solution approaches handling dynamic MRTA scenarios do not consider the problem structure changes as a possible system dynamic. RoSTAM (Robust and Self- adaptive Task Allocation for Multi-robot teams) presents a novel approach to han dle a variety of MRTA problem representations without any alterations to the tas k allocation framework. RoSTAM’s capabilities against a range of MRTA problem di stributions have already been established. This paper further validates RoSTAM’s performance against the more conventional dynamics, such as robot failure and n ew task arrival, while performing allocations against two of the most frequently faced problem representations.”
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    Findings from Beijing University of Technology Yields New Findings on Androids ( Asymmetric Integral Barrier Lyapunov Function-based Human-robot Interaction Cont rol for Human-compliant Spaceconstrained Muscle Strength Training)

    109-110页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on Robotics - Androi ds are discussed in a new report. According to news reporting originating in Bei jing, People’s Republic of China, by NewsRx journalists, research stated, “In th is article, an asymmetric integral barrier Lyapunov function (AIBLF)-based contr ol scheme is proposed for human-robot interaction (HRI), with which robot-aided human-compliant space-constrained muscle strength training can be achieved. Firs t, an admittance model is exploited to generate compliant desired trajectory wit h the input of human-robot interaction torque.” Financial support for this research came from China Postdoctoral Science Foundat ion.
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    Research on Robotics Detailed by Researchers at Anhalt University of Applied Sci ences (Modular Robotic Reinforcement Learning Platform for Object Manipulation)

    110-110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 originating from Kothen, Germany, by NewsRx co rrespondents, research stated, “The field of robotics and autonomous systems has witnessed significant advancements in recent years, with an increasing focus on enhancing the capabilities of robotic agents through RL.” The news correspondents obtained a quote from the research from Anhalt Universit y of Applied Sciences: “This project centres around applying Reinforcement Learn ing (RL) techniques to do object manipulation tasks with a specific focus on mak ing a robot arm reach a target object. Using a combination of Gazebo and Robot O perating System (ROS) environments, the robot arm is trained using custom OpenAI Gym environments to simulate the task. The primary objective involves positioni ng the endeffector of the robot arm close to a designated object and overcoming challenges such as self-collisions during movements. Various iterations of RL t raining, including different reward logics, curriculum learning approaches, and fine-tuning parameters, are explored to refine the decision-making capabilities of the agent. The training process of Curriculum Learning involves a phased appr oach, starting with basic movements and progressing to more complex tasks, demon strating improved performance. However, challenges such as prolonged training ti mes and uncertainties in arm behaviour persist.”
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    Data from University of Padua Provide New Insights into Robotics and Automation (Kvn: Keypoints Voting Network With Differentiable Ransac for Stereo Pose Estima tion)

    111-111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 Robotics - Robotics an d Automation is the subject of a report. According to news reporting out of Padu a, Italy, by NewsRx editors, research stated, “Object pose estimation is a funda mental computer vision task exploited in several robotics and augmented reality applications. Many established approaches rely on predicting 2D-3D keypoint corr espondences using RANSAC (Random sample consensus) and estimating the object pos e using the PnP (Perspective-n- Point) algorithm.” Financial support for this research came from University of Padova.
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    Georgia Institute of Technology & Emory University Reports Finding s in Machine Learning (BiliQML: A supervised machine-learning model to quantify biliary forms from digitized whole-slide liver histopathological images)

    112-113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 out of Atlanta, Georgia, by N ewsRx editors, research stated, “The progress of research focused on cholangiocy tes and the biliary tree during development and following injury is hindered by limited available quantitative methodologies. Current techniques include two-dim ensional standard histological cell-counting approaches, which are rapidly perfo rmed error-prone and lack architectural context; or threedimensional analysis o f the biliary tree in opacified livers, which introduce technical issues along w ith minimal quantitation.” Financial supporters for this research include HHS | NIH | National Institute of Diabetes and Digestive and Kidney Diseases, HHS | NIH | National Institute of D iabetes and Digestive and Kidney Diseases, HHS | NIH | National Institute of Dia betes and Digestive and Kidney Diseases, HHS | NIH | National Institute of Diabe tes and Digestive and Kidney Diseases, Chan Zuckerberg Initiative, HHS | NIH | N ational Institute of Allergy and Infectious Diseases, HHS | NIH | National Insti tute of Allergy and Infectious Diseases, HHS | NIH | National Institute of Aller gy and Infectious Diseases, HHS | NIH | National Institute of Allergy and Infect ious Diseases, HHS | NIH | National Heart, Lung, and Blood Institute, HHS | NIH | National Institute of Biomedical Imaging and Bioengineering, Deutsche Forschun gsgemeinschaft, HHS | NIH | National Institute of Diabetes and Digestive and Kid ney Diseases, HHS | NIH | National Institute of General Medical Sciences.
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    Dalian University Reports Findings in Robotics (Dual modality prompt learning fo r visual question-grounded answering in robotic surgery)

    113-114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 Robotics is the subjec t of a report. According to news reporting originating in Liaoning, People’s Rep ublic of China, by NewsRx journalists, research stated, “With recent advancement s in robotic surgery, notable strides have been made in visual question answerin g (VQA). Existing VQA systems typically generate textual answers to questions bu t fail to indicate the location of the relevant content within the image.” Financial supporters for this research include 111 Project, National Key Researc h and Development Program of China.
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