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    Data on Robotics Detailed by Researchers at Jilin University (Research On Gait S witching Method Based On Speed Requirement)

    12-13页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Robotics is now availab le. According to news reporting originating in Changchun, People’s Republic of C hina, by NewsRx journalists, research stated, “Real-time gait switching of quadr uped robot with speed change is a difficult problem in the field of robot resear ch. It is a novel solution to apply reinforcement learning method to the quadrup ed robot problem.” Funders for this research include Science and Technology Development Program of Jilin Province, China, National Natural Science Foundation of China (NSFC).
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    Findings from Hohai University Provides New Data on Machine Learning (Intelligen t Mixture Optimization for Stabilized Soil Containing Solid Waste Based On Machi ne Learning and Evolutionary Algorithms)

    13-14页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Researchers detail new data in Machine Learning. According to news reporting from Nanjing, People’s Republic of China, by NewsRx journalists, research stated, “The usage of industrial solid waste to improve so il for road materials has attracted widespread attention. In addition to mechani cal performance, economic and environmental factors gain increasing concern duri ng road construction.” Funders for this research include National Natural Science Foundation of China ( NSFC), Water Conservancy Science and Technology Program of Suzhou, Science and T echnology Program of Suzhou.
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    Data from University of Southampton Broaden Understanding of Machine Learning (I ntegrating LSTM Networks with Mean- Variance Optimization for Enhanced Portfolio Construction: An Empirical Study on UK Stock Market)

    14-14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 artificial intelligence. According to news originating from Southampton, United Kingdom, by NewsRx correspondents, research stated, “Portfolio optimization has long been a central theme in finance.” Our news reporters obtained a quote from the research from University of Southam pton: “With ongoing advancements in machine learning, there is a significant opp ortunity to integrate predictive methods into portfolio optimization. This paper proposes leveraging Long Short-Term Memory (LSTM) networks alongside the establ ished Mean-Variance (MV) optimization framework to construct optimal portfolios. These portfolios aim to help financial investors effectively manage and mitigat e risk while maximizing returns. The study meticulously screened the leading sto cks of 12 prominent UK companies listed on the London Stock Exchange (LSE), know n for their influence and visibility. Initially, the study applies the LSTM netw orks to predict stock price volatility and integrates these predictions into the MV model to allocate portfolio weights effectively. To underscore the superiori ty of the proposed approach, the study compares cumulative returns from portfoli os optimized for maximum and minimum variance Sharpe ratios with real data again st the FTSE100 index over the same period.”
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    Department of Chemical Sciences Reports Findings in Machine Learning (A Mode Evo lution Metric to Extract Reaction Coordinates for Biomolecular Conformational Tr ansitions)

    15-15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 Mumbai, India, by News Rx editors, research stated, “The complex, multidimensional energy landscape of biomolecules makes the extraction of suitable, nonintuitive collective variables (CVs) that describe their conformational transitions challenging. At present, d imensionality reduction approaches and machine learning (ML) schemes are employe d to obtain CVs from molecular dynamics (MD)/Monte Carlo (MC) trajectories or st ructural databanks for biomolecules.” Our news journalists obtained a quote from the research from the Department of C hemical Sciences, “However, minimum sampling conditions to generate reliable CVs that accurately describe the underlying energy landscape remain unclear. Here, we address this issue by developing a ode volution Metric (MeM) to extract CVs t hat can pinpoint new states and describe local transitions in the vicinity of a reference minimum from nonequilibrated MD/MC trajectories. We present a general mathematical formulation of MeM for both statistical dimensionality reduction an d machine learning approaches. Application of MeM to MC trajectories of model po tential energy landscapes and MD trajectories of solvated alanine dipeptide reve als that the principal components which locate new states in the vicinity of a r eference minimum emerge well before the trajectories locally equilibrate between the associated states. Finally, we demonstrate a possible application of MeM in designing efficient biased sampling schemes to construct accurate energy landsc ape slices that link transitions between states.”
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    Guizhou Provincial People’s Hospital Reports Findings in Pancreatoduodenectomy ( Clinical efficacy of enhanced recovery surgery in Da Vinci robot-assisted pancre atoduodenectomy)

    16-16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 Surgery - Pancreatoduo denectomy is the subject of a report. According to news reporting originating in Guizhou, People’s Republic of China, by NewsRx journalists, research stated, “D a Vinci robot-assisted pancreaticoduodenectomy offers advantages, including mini mal invasiveness, precise, and safe procedures. This study aimed to investigate the clinical effectiveness of implementing enhanced recovery after surgery (ERAS ) concepts in Da Vinci robot-assisted pancreaticoduodenectomy.” The news reporters obtained a quote from the research from Guizhou Provincial Pe ople’s Hospital, “A retrospective analysis was conducted on clinical data from 6 2 patients who underwent Da Vinci robotassisted pancreaticoduodenectomy between January 2018 and December 2022. Among these patients, 30 were managed with ERAS principles, while 32 were managed using traditional perioperative management pr otocols. Surgical time, intraoperative blood loss, postoperative oral intake tim e, time to return of bowel function, time to ambulation, visual analog scale (VA S) pain scores, fluid replacement volume, length of hospital stay, total hospita l expenses, complications, and patient satisfaction were recorded and compared b etween the two groups. Postoperative follow-up included assessment of postoperat ive functional scores, reoperation rates, SF-36 quality of life scores, and surv ival rates. The average follow-up time was 35.6 months (range: 12-56 months). Th ere were no statistically significant differences in general characteristics, in cluding age, surgical time, intraoperative blood loss, and preoperative medical history between the two groups (P > 0.05). Compared to t he control group, the intervention group had an earlier postoperative oral intak e time, faster return of bowel function, rapid ambulation, and shorter hospital stays (P <0.05). The intervention group also had lower pos toperative VAS scores, lower fluid replacement volume, lower total hospital expe nses, and a lower rate of complications (P <0.05). Patient satisfaction was higher in the intervention group (P <0.0 5). There were no statistically significant differences between the two groups i n two-year functional scores, reoperation rates, quality of life scores, and sur vival rates (P > 0.05). Implementing ERAS principles in Da Vinci robot-assisted pancreaticoduodenectomy substantially expedited postoper ative recovery, lowered pain scores, and diminished complications.”
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    New Machine Learning Study Findings Have Been Published by Researchers at Sohar University (Determinates of investor opinion gap around IPOs: A machine learning approach)

    17-17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 ar tificial intelligence. According to news reporting out of Sohar University by Ne wsRx editors, research stated, “The current study examines the factors influenci ng investor opinions on issues related to listed firms during the first day of I nitial Public Offerings (IPOs), focusing on a sample of 350 fixed-priced IPOs li sted on the Malaysian stock exchange (Bursa Malaysia) from 2004 to 2021.” Our news journalists obtained a quote from the research from Sohar University: “ This research contributes to existing literature by employing various machine le arning methods, which address the limitations of traditional linear regression m odels commonly used in previous studies. Specifically, five methods-extra tree r egressor (ETR), single feature selection (SFS), reverse single feature (RSF), re cursive feature elimination (RFE), and sequential modelling feature adding (SMFA )-are utilized to assess the importance of features in predicting the investor o pinion gap within the dataset. The study’s experiments indicate that these metho ds effectively mitigate noisy data, enhancing their reliability for this type of analysis.”
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    Researchers from Vytautas Magnus University Report Details of New Studies and Fi ndings in the Area of Robotics (Investigation of Dynamics of the Manipulator Wit h Self-stopping Mechanism and Vibration Drive Based On Centrifugal Forces)

    17-18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 from Kaunas, Lithuania, by NewsRx journalist s, research stated, “Manipulators of this type can be used as constituent parts of robots of several dimensions. Vibration drive based on centrifugal forces is often used in elements of manipulators and robots.” The news correspondents obtained a quote from the research from Vytautas Magnus University, “In this paper manipulator with vibration drive based on centrifugal forces and with the self-stopping mechanism is investigated. The model of the i nvestigated manipulator is described and equations determining the motion of the manipulator are obtained. The conservative system is investigated. Then the ful l dynamic model is investigated. Also, the model with excitation of unlimited po wer is investigated. Numerical solution of the obtained equations is performed. First the results for the conservative system are described and investigated. Th en the full dynamic model is investigated in detail. Also, the model with excita tion of unlimited power is described and investigated. Various typical graphical relationships determining the dynamic behavior of the investigated manipulator with vibration drive based on centrifugal forces in steady state regimes of moti on are presented. Experimental investigations are performed.”
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    Capital Medical University Reports Findings in Artificial Intelligence (Prelimin ary experiments on interpretable ChatGPT-assisted diagnosis for breast ultrasoun d radiologists)

    18-19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 Beijing , People’s Republic of China, by NewsRx journalists, research stated, “Ultrasoun d is essential for detecting breast lesions. The American College of Radiology’s Breast Imaging Reporting and Data System (BI-RADS) classification system is wid ely used, but its subjectivity can lead to inconsistency in diagnostic outcomes. ” The news reporters obtained a quote from the research from Capital Medical Unive rsity, “Artificial intelligence (AI) models, such as ChatGPT-3.5, may potentiall y enhance diagnostic accuracy and efficiency in medical settings. This study aim ed to assess the utility of the ChatGPT-3.5 model in generating BI-RADS classifi cations for breast ultrasound reports and its ability to replicate the ‘chain of thought’ (CoT) in clinical decision-making to improve model interpretability. B reast ultrasound reports were collected, and ChatGPT-3.5 was used to generate di agnoses and treatment plans. We evaluated GPT-4’s performance by comparing its g enerated reports to those from doctors with various levels of experience. We als o conducted a Turing test and a consistency analysis. To enhance the interpretab ility of the model, we applied the CoT method to deconstruct the decision-making chain of the GPT model. A total of 131 patients were evaluated, with 57 doctors participating in the experiment. ChatGPT-3.5 showed promising performance in st ructure and organization (S&O), professional terminology and expres sion (PTE), treatment recommendations (TR), and clarity and comprehensibility (C &C). However, improvements are needed in BI-RADS classification, ma lignancy diagnosis (MD), likelihood of being written by a physician (LWBP), and ultrasound doctor artificial intelligence acceptance (UDAIA). Turing test result s indicated that AI-generated reports convincingly resembled human-authored repo rts. Reproducibility experiments displayed consistent performance. Erroneous rep ort analysis revealed issues related to incorrect diagnosis, inconsistencies, an d overdiagnosis. The CoT investigation supports the potential of ChatGPT to repl icate the clinical decision-making process and offers insights into AI interpret ability.”
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    Recep Tayyip Erdogan University Training and Research Hospital Reports Findings in Telemedicine [The development of point-ofcare ultrasound (POCUS): Worldwide contributions and publication trends]

    19-20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 Telemedicine is the su bject of a report. According to news reporting originating from Rize, Turkey, by NewsRx correspondents, research stated, “Point-of-care ultrasound (POCUS) conce pt is widely used in both emergency medicine (EM) and intensive care medicine (I CM). This study aimed to analyze the scientific articles on POCUS published by s tatistical methods and to evaluate the subject holistically.” Our news editors obtained a quote from the research from Recep Tayyip Erdogan Un iversity Training and Research Hospital, “This study is bibliographical, descrip tive, and analytical in nature. POCUS-related publications published were downlo aded from the Web of Science (WoS) database and analyzed using statistical metho ds. Network visualization maps were used to identify trending topics. The litera ture search revealed 5714 publications on POCUS in the WoS database. According t o the WoS categorization of publications, the most common categories were emerge ncy medicine (1751; 30.6%). The topics studied in recent years were deep learning, artificial intelligence, COVID-19, acute kidney injury, heart fa ilure, and telemedicine. This study on POCUS, we summarized 5714 publications pu blished. According to our results, the trending topics in POCUS research in rece nt years include deep learning, artificial intelligence, COVID-19, acute kidney injury, heart failure and telemedicine.”
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    Data on Machine Learning Reported by Researchers at Jamia Millia Islamia (Effect iveness of Hybrid Ensemble Machine Learning Models for Landslide Susceptibility Analysis: Evidence From Shimla District of North-west Indian Himalayan Region)

    20-21页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Data detailed on Machine Learning have been presented. According to news reporting out of New Delhi, India, by NewsRx editors, research stated, “The Indian Himalayan region is frequently experiencin g climate change-induced landslides. Thus, landslide susceptibility assessment a ssumes greater significance for lessening the impact of a landslide hazard.” Financial supporters for this research include Indian Council of Social Science Research (ICSSR), New Delhi, United States Geological Survey.
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