查看更多>>摘要：Current study results on Machine Learn ing have been published. According to news reporting originating in Wuhan, Peopl e's Republic of China, by NewsRx journalists, research stated, "Ultra-high perfo rmance concrete (UHPC) is an advanced material in construction. Porous lightweig ht aggregates (PLWA) could reduce the self-shrinkage risk of UHPC by maintaining internal relative humidity." Financial supporters for this research include National Natural Science Foundati on of China (NSFC), Guangdong Basic and Applied Basic Research Foundation, Syste matic Project of Guangxi Key Laboratory of Disaster Prevention and Engineering S afety.
查看更多>>摘要：Investigators publish new report on Ma chine Learning. According to news originating from Montreal, Canada, by NewsRx e ditors, the research stated, "This paper assesses the utility of machine learnin g (ML) techniques combined with comprehensive macroeconomic and microeconomic da tasets in enhancing risk analysis during stress tests. The analysis unfolds in t wo stages." Financial supporters for this research include Fonds de recherche sur la societe et la culture (Quebec), Canadian chair in Macroeconomy and Forecasting (UQAM). Our news journalists obtained a quote from the research from the University of Q uebec Montreal, "I initially benchmark ML's efficacy in forecasting two pivotal banking variables, net charge-off (NCO) and pre-provision net revenue (PPNR), ag ainst traditional linear models. Results underscore the superiority of Random Fo rest and Adaptive Lasso models in this context. Subsequently, I use these models to project PPNR and NCO for selected bank holding companies under adverse stres s scenarios. This exercise feeds into the Tier 1 common equity capital (T1CR) de nsities simulation. T1CR is the equity capital ratio corrected by some regulator y adjustments to risk-weighted assets. Crucially, findings reveal a pronounced l eft skew in the T1CR distribution for globally systemically important banks vis- & agrave;-vis linear models."
查看更多>>摘要：Current study results on Machine Learn ing have been published. According to news originating from West Lafayette, Indi ana, by NewsRx correspondents, research stated, "Smart systems such as data-driv en machine health monitoring are emerging as powerful technology for advanced ma nufacturing as a result of the availability of low-cost sensors, wireless commun ication, and advances in Machine Learning (ML) and Artificial Intelligence (AI). Predictive maintenance (PdM) has become increasingly popular in manufacturing, which can identify approaching failures, determine root causes of operation anom alies, estimate the current health state of a system, and predict the future sta te and time when a component will fail in the absence of an intervention." Financial support for this research came from Wabash Heartland Innovative Networ k. Our news journalists obtained a quote from the research from Purdue University, "One weakness of many past studies is the lack of run-to-failure data from an ac tual production environment. This paper presents run-to-failure data for the air compressor of an injection molding machine. A Long Short-Term Memory (LSTM) Rec urrent Neural Network (RNN) is proposed to detect bearing faults in the air comp ressor, which can capture the long-term dependencies without losing the capabili ty to identify local dependencies. The model achieves a 97.4% of p rediction accuracy (95.3% of overall accuracy)."
查看更多>>摘要：2024 OCT 08 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Investigators discuss new findings in Machine Lea rning. According to news reporting from Cam-bridge, Massachusetts, by NewsRx jour nalists, research stated, "The mass assembly history (MAH) of dark matter haloes plays a crucial role in shaping the formation and evolution of galaxies. MAHs are used extensively in semi-analytic and empirical models of galaxy formation, y et current analytic methods to generate them are inaccurate and unable to captur e their relationship with the halo internal structure and large-scale environmen t." Funders for this research include Center for Computational Astrophysics at the F latiron Institute, Simons Foundation, National Science Foundation (NSF), NASA Po stdoctoral Program (NPP) at NASA Goddard Space Flight Center, Gauss Centre for S upercomputing e.V., Partnership for Advanced Supercomputing in Europe (PRACE).
查看更多>>摘要：New research on Drugs and Therapies-Antibiotics is the subject of a report. According to news reporting out of Qingd ao, People's Republic of China, by NewsRx editors, research stated, "Marine anti microbial peptides (AMPs) represent a promising source for combating infections, especially against antibiotic-resistant pathogens and traditionally challenging infections. However, traditional drug discovery methods face challenges such as time-consuming processes and high costs." Funders for this research include Strategic Priority Research Program of the Chi nese Academy of Sciences, National Key Research and Development Program of China , National Science Foundation of China, Young Elite Scientists Sponsorship Progr am, Science and Technology Program of Guangzhou, China, Science and Technology P lanning Project of Guangdong Province, China.
查看更多>>摘要：New research on Artificial Intelligenc e is the subject of a report. According to news reporting originating from Xi'an , People's Republic of China, by NewsRx correspondents, research stated, "The wi despread use of Artificial Intelligence (AI) in language education contexts has motivated several scholars around the world to uncover the advantages and disadv antages of AI and AI-powered instruments in different language classrooms. Yet, as the review of earlier investigations revealed, few inquiries have been carrie d out to divulge the pros and cons of leveraging AI in EFL classes." Financial support for this research came from Research and Practice Project of C omprehensive Reform of Postgraduate Education in Shaanxi Province in the Second Round. Our news editors obtained a quote from the research from Shaanxi Normal Universi ty, "To narrow this gap, using the phenomenological approach, this inquiry inves tigated the opportunities and challenges of implementing AI in EFL classes from the perspective of Chinese EFL students. To do so, through the criterion samplin g technique, a total of 45 EFL students was recruited from different educational institutions in China. To collect the dataset, participants were asked to compl ete an open-ended questionnaire. For the sake of triangulation, among the 45 par ticipants, 15 were randomly selected to engage in a follow-up interview session. With the aid of MAXQDA software (version 2023), participants' perceptions of AI opportunities and challenges were carefully analyzed. Overall, the analysis fin dings uncovered that leveraging AI in EFL classes can bring numerous opportuniti es for EFL students, including individualized learning, timely and immediate fee dback, rich educational resources, and an interactive learning atmosphere. Howev er, as demonstrated by the analysis outcomes, implementing AI in EFL courses may also face students with a range of challenges and problems."
查看更多>>摘要：Data detailed on Machine Learning-Co mputational Intelligence have been presented. According to news reporting origin ating in Shenyang, People's Republic of China, by NewsRx journalists, research s tated, "Medical knowledge graph (KG) is sparse KG that contains insufficient inf ormation and missing paths. Multi-hop reasoning is an effective approach of medi cal KG completion, since it offers logical insights of the underlying KG and sho ws more direct interpretability." Financial supporters for this research include Guangdong Basic and Applied Basic Research Foundation, Key Technologies R&D Program of Liaoning Prov ince, Key Project of Science and Technology Innovation and Entrepreneurship of T DTEC.
查看更多>>摘要：New research on Gram-Negative Bacteria-Serratia marcescens is the subject of a report. According to news reporting o riginating in Burgos, Spain, by NewsRx journalists, research stated, "Metal cont amination in soil poses environmental and health risks requiring effective remed iation strategies. This study introduces an innovative approach of synergistical ly employing biochar and bacterial inoculum of Serratia marcescens to address toxic metal ™ contamination." The news reporters obtained a quote from the research from the University of Bur gos, "Physicochemical, enzymatic, and microbial analyses were conducted, employi ng integrated biomarker response (IBR) and machine-learning approaches for toxic ity estimation. The combined application significantly reduced the Cd, Cr, and P b concentrations by 71.6, 31.2, and 57.1%, respectively, while the Cu concentration increased by 85% in the individual Serratia marcescens treatment. Biochar enhanced microbial biomass by 33-44% after 25 days. Noteworthy physicochemical improvements included a 44.7% inc rease in organic content and a decrease in pH and electrical conductivity. The K and Ca concentrations increased by 196.9 and 21.6%, respectively, while the Mg content decreased by 86.4%. Network analysis revealed intricate relationships, displaying direct and indirect negative correlations be tween metals and soil physicochemical parameters. The IBR index values indicated effective mitigation of TM toxicity in Serratia marcescens and biochar with individual and combined treatments. Binary classification demo nstrated high sensitivity (80.1 %) and specificity (80.5% ) in identifying TM-contaminated soil."
查看更多>>摘要：Researchers detail new data in robotic s. According to news reporting originating from Beijing, People's Republic of Ch ina, by NewsRx correspondents, research stated, "Birds have remarkable flight ca pabilities due to their adaptive wing morphology." Funders for this research include National Natural Science Foundation of China. The news journalists obtained a quote from the research from Beijing Institute o f Technology: "However, studying live birds is time-consuming and laborious, and obtaining information about the complete wingbeat cycle is difficult. To addres s this issue and provide a complete dataset, we recorded comprehensive motion ca pture wing trajectory data from five free-flying pigeons (Columba livia). Five k ey motion parameters are used to quantitatively characterize wing kinematics: fl apping, sweeping, twisting, folding and bending. In addition, the forelimb skele ton is mapped using an open-chain three-bar mechanism model. By systematically e valuating the relationship of joint degrees of freedom (DOFs), we configured the model as a 3-DOF shoulder, 1-DOF elbow and 2-DOF wrist. Based on the correlatio n analysis between wingbeat kinematics and joint movement, we found that the str ongly correlated shoulder and wrist roll within the stroke plane cause wing flap and bending."
查看更多>>摘要：Data detailed on Machine Learning have been presented. According to news reporting originating in Stavanger, Norway, b y NewsRx journalists, research stated, "Mud gas data from drilling operations pr ovide the first indication of hydrocarbons in the reservoir. It has been a dream for decades in the oil industry to predict reservoir gas and oil properties fro m mud gas data because it would provide knowledge of the reservoir fluid propert ies in an early stage, continuously for all reservoir zones, and at low costs." Funders for this research include Equinor's Digital Subsurface, Equinor's Resear ch and Technology (RT) division.
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