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    Study Results from University of Bucharest Provide New Insights into Artificial Intelligence (Using generative Artificial Intelligence tools in Public Relations : Ethical concerns and the impact on the profession in the Romanian context)

    29-29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 artificial intelligence are presented in a new report. According to news reporting out of the University of Bucharest by NewsRx editors, research stated, "The controversy surrounding C hatGPT has reopened the debate about the impact of new technologies in many fiel ds of activities, including communication and PR. This study mapped Romanian PR practitioners' use of generative AI and their perception of it, placing a specia l focus on the ethical concerns involved and the implications for the profession itself." Our news correspondents obtained a quote from the research from University of Bu charest: "We took a quantitative-qualitative approach by using both a survey and semi-structured interviews. Our goal was to determine the impact of generative artificial intelligence (AI) in the Romanian PR industry and to understand the r easons and challenges behind integrating generative AI in PR practice. The surve y findings revealed a substantial adoption (73.5%) of AI within the Romanian PR community, with an overwhelming 91.6% of them using C hatGPT. The satisfaction level was remarkably high, with 92% expre ssing satisfaction with generative AI application efficacy. Benefits included ti mesaving, work simplification, and the reduction of repetitive tasks. Surprising ly, not only did 67.3% of respondents not perceive AI as an immedi ate threat to PR jobs, but 80.5% believed AI represents an opportu nity for the industry. Indeed, almost all our interviewees admitted relief and s atisfaction when using generative AI tools to complete their tasks."
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    University of Toronto Reports Findings in Robotics (Robotic microinjection enabl es large-scale transgenic studies of Caenorhabditis elegans)

    30-30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 Toronto, Canada, by Ne wsRx journalists, research stated, "The nematode Caenorhabditis elegans is widely employed as a model organism to study basic biological mechanisms. Ho wever, transgenic C. elegans are generated by manual injection, which remains lo w-throughput and labor-intensive, limiting the scope of approaches benefitting f rom large-scale transgenesis. Here, we report a robotic microinjection system, i ntegrating a microfluidic device capable of reliable worm immobilization, transf er, and rotation, for high-speed injection of C. elegans." The news reporters obtained a quote from the research from the University of Tor onto, "The robotic system provides an injection speed 2-3 times faster than that of experts with 7-22 years of experience while maintaining comparable injection quality and only limited trials needed by users to become proficient. We furthe r employ our system in a large-scale reverse genetic screen using multiplexed al ternative splicing reporters, and find that the TDP-1 RNA-binding protein regula tes alternative splicing of zoo-1 mRNA, which encodes variants of the zonula occ ludens tight junction proteins."
      原文链接:
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    University of Texas Austin Reports Findings in Machine Learning (Complex Emotion Dynamics Contribute to the Prediction of Depression: A Machine Learning and Tim e Series Feature Extraction Approach)

    31-31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 Austin, Texas, by NewsRx journalists, research stated, "Emotion dynamics have demonstrated mix ed ability to predict depressive symptoms and outperform traditional metrics lik e the mean and standard deviation of emotion reports. Here, we expand the types of emotion dynamic features used in prior work and apply a machine learning algo rithm to predict depression symptoms." The news reporters obtained a quote from the research from the University of Tex as Austin, "We obtained seven ecological momentary assessment (EMA) studies from previous work on depression and emotion dynamics ( = 890). These studies measur ed self-reported sadness, positive affect, and negative affect 5 to 10 times per day for 7 to 21 days (schedule varied across studies). These data were fed thro ugh a feature extraction routine to generate hundreds of emotion dynamic feature s. A gradient boosting machine (GBM) using all available emotion dynamics featur es was the best of all models assessed. This model's out-of-sample prediction ( ) for depression severity ranged from .20 to .44 depending on EMA interpolation method and samples included in the analysis. It also explained significantly mor e variance than a benchmark model of individuals' mean emotion ratings over the assessment period, = .089."
      原文链接:
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    Studies from University of Michigan Add New Findings in the Area of Robotics (Te aching Motor Skills Without a Motor: a Semipassive Robot To Facilitate Learning )

    31-32页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Researchers detail new data in Robotic s. According to news reporting originating in Ann Arbor, Michigan, by NewsRx jou rnalists, research stated, "Semi-passive rehabilitation robots resist and steer a patient's motion using only controllable passive force elements (e.g., control lable brakes). Contrarily, passive robots use uncontrollable passive force eleme nts (e.g., springs), while active robots use controllable active force elements (e.g., motors)." Financial supporters for this research include Disability and Rehabilitation Eng ineering Program of the National Science Foundation, National Science Foundation Graduate Research Program through DGE, National Institutes of Health (NIH) - US A.
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    Research Findings from Southern University at New Orleans Update Understanding o f Machine Learning (Comparison of Machine Learning-Based Predictive Models of th e Nutrient Loads Delivered from the Mississippi/Atchafalaya River Basin to the G ulf ...)

    32-33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 artificial intelligence are presented in a new report. According to news originating from New Orleans, L ouisiana, by NewsRx correspondents, research stated, "Predicting nutrient loads is essential to understanding and managing one of the environmental issues faced by the northern Gulf of Mexico hypoxic zone, which poses a severe threat to the Gulf's healthy ecosystem and economy. The development of hypoxia in the Gulf of Mexico is strongly associated with the eutrophication process initiated by exce ssive nutrient loads."
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    Data on Machine Learning Discussed by Researchers at National Institute of Techn ology Silchar (Sensor Fusion Model for Weld Quality Monitoring In Friction Stir Welding Process Using Machine Learning Technique)

    33-34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 reporting originating in Assam, India, by News Rx journalists, research stated, "Weld quality monitoring in welding processes i s not new and many research works have been carried in this area. Sensor informa tion based methodologies have been developed to an appreciable extent and many f ound its recognition in many industrial applications." Financial support for this research came from Department of Science and Technolo gy and Science and Engineering Research Board.
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    Selcuk University Researcher Highlights Recent Research in Machine Learning (Cla ssification of Garlic Varieties with Fluorescent Spectroscopy Using Machine Lear ning)

    34-35页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on artificial in telligence have been published. According to news reporting out of Selcuk Univer sity by NewsRx editors, research stated, "Machine learning techniques can produc e fast, accurate and objective results in the analysis of agricultural products. " The news correspondents obtained a quote from the research from Selcuk Universit y: "These artificial intelligence-based systems are frequently encountered in st udies on agriculture in the literature. This study reveals the usability of mach ine learning algorithms in classification of garlic cultivars using fluorescent spectroscopic data. For this, six types of garlic were used: Razgradski-11, Razg radski-12, Razgradski-115, Plovdivski-120, Yambolski-99 and Topolovgradski. In t he first stage, the parsing analysis made from the fluorescent spectroscopic dat a of the garlics was carried out with seven different machine learning. The clas sification results of these seven types of machine learning algorithms were obta ined. In the second stage, the classification results were obtained by adjusting the hyperparameters of each Machine Learning (ML) algorithm in order to control the improvability of the classification accuracy rates."
      原文链接:
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    Study Findings on Machine Learning Published by Researchers at European Space Ag ency (2024 ESA-ECMWF workshop report: current status, progress and opportunities in machine learning for Earth system observation and prediction)

    35-36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 originating from the European Space Age ncy by NewsRx editors, the research stated, "This report summarises the main out comes of the 4th edition of the workshop on Machine Learning (ML) for Earth Syst em Observation and Prediction (ESOP / ML4ESOP) co-organised by the European Spac e Agency (ESA) and the European Centre for Medium-Range Weather Forecasts (ECMWF )." Our news reporters obtained a quote from the research from European Space Agency : "The 4-day workshop was held on 7-10 May 2024 in a hybrid format at the ESA Fr ascati site with an interactive online component, featuring over 46 expert talks with a record number of submissions and about 800 registrations. The workshop o ffered leading experts a platform to exchange on the current opportunities, chal lenges and future directions for applying ML methodology to ESOP. To structure t he presentations and discussions, the workshop featured five main thematic areas covering key topics and emerging trends."
      原文链接:
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    Researcher at Northwest University Discusses Research in Artificial Intelligence (Enhancing Supply Chain Management Through Artificial Intelligence: A Case Stud y of JD Logistics)

    36-36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 artificial intelligence is now available. According to news reporting out of Northwest University by Ne wsRx editors, research stated, "With the intensification of global economic comp etition, enterprises face the challenge of improving the supply chain management efficiency, and AI technology, as an emerging field in computer science, can pr ovide effective solutions." The news correspondents obtained a quote from the research from Northwest Univer sity: "As a leading e-commerce logistics service provider in China, JD Logistics has accumulated a wealth of logistics technology capabilities and digital trans formation experience within and outside the JD Group. Using JD Logistics as a ca se study, this paper discusses the application of AI technology in supply chain management and its impact on enterprise responsiveness and operational efficienc y."
      原文链接:
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    Second Hospital of Jilin University Reports Findings in Personalized Medicine (D evelopment of a COVID-19 early risk assessment system based on multiple machine learning algorithms and routine blood tests: a real-world study)

    37-38页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Drugs and Therapies - Personalize d Medicine is the subject of a report. According to news originating from Jilin, People's Republic of China, by NewsRx correspondents, research stated, "During the Coronavirus Disease 2019 (COVID-19) epidemic, the massive spread of the dise ase has placed an enormous burden on the world's healthcare and economy. The ear ly risk assessment system based on a variety of machine learning (ML) algorithms may be able to provide more accurate advice on the classification of COVID-19 p atients, offering predictive, preventive, and personalized medicine (PPPM) solut ions in the future." Our news journalists obtained a quote from the research from the Second Hospital of Jilin University, "In this retrospective study, we divided a portion of the data into training and validation cohorts in a 7:3 ratio and established a model based on a combination of two ML algorithms first. Then, we used another portio n of the data as an independent testing cohort to determine the most accurate an d stable model and compared it with other scoring systems. Finally, patients wer e categorized according to risk scores and then the correlation between their cl inical data and risk scores was studied. The elderly accounted for the majority of hospitalized patients with COVID-19. The C-index of the model constructed by combining the stepcox[both] and survivalSV M algorithms was 0.840 in the training cohort and 0.815 in the validation cohort , which was calculated to have the highest C-index in the testing cohort compare d to the other 119 ML model combinations. Compared with current scoring systems, including the CURB-65 and several reported prognosis models previously, our mod el had the highest AUC value of 0.778, representing an even higher predictive pe rformance. In addition, the model's AUC values for specific time intervals, incl uding days 7,14 and 28, demonstrate excellent predictive performance. Most impor tantly, we stratified patients according to the model's risk score and demonstra ted a difference in survival status between the high-risk, median-risk, and low- risk groups, which means a new and stable risk assessment system was built. Fina lly, we found that COVID-19 patients with a history of cerebral infarction had a significantly higher risk of death. This novel risk assessment system is highly accurate in predicting the prognosis of patients with COVID-19, especially elde rly patients with COVID-19, and can be well applied within the PPPM framework."
      原文链接:
    • NETL
    • NSTL