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    Research from Henan University of Science and Technology Yields New Data on Artificial Intelligence (Artificial Intelligence Technology Enabling Innovation in Museum Public Cultural Service Models)

    20-20页
    查看更多>>摘要：Current study results on artificial intelligence have been published. According to news reporting from Henan, People’s Republic of China, by NewsRx journalists, research stated, “In this paper, we constructed an artificial intelligence model of environment perception and human body perception, and after filtering the irrelevant information in the environment, we collected and analyzed the three-dimensional information of the environment to realize the intelligent perception of the environment.” Our news reporters obtained a quote from the research from Henan University of Science and Technology: “Aiming at the transient noise that may occur in the robot’s operating environment, a time threshold is added on the basis of the traditional double threshold endpoint detection algorithm, which effectively eliminates the influence of transient noise on endpoint detection and realizes non-contact continuous speech recognition. Then the data of the perceived human body was analyzed to understand the perception of the human body by artificial intelligence.”
      原文链接:
    • NETL
    • NSTL

    Universite Paris Cite Reports Findings in Heart Attack (Patterns of left ventricular remodeling post-myocardial infarction, determinants, and outcome)

    21-22页
    查看更多>>摘要：New research on Heart Disorders and Diseases Heart Attack is the subject of a report. According to news reporting originating from Paris, France, by NewsRx correspondents, research stated, “Left ventricular remodeling (LVR) after myocardial infarction (MI) can lead to heart failure, arrhythmia, and death. We aim to describe adverse LVR patterns at 6 months post-MI and their relationships with subsequent outcomes and to determine baseline.” Our news editors obtained a quote from the research from Universite Paris Cite, “A multicenter cohort of 410 patients (median age 57 years, 87% male) with reperfused MI and at least 3 akinetic LV segments on admission was analyzed. All patients had transthoracic echocardiography performed 4 days and 6 months post-MI, and 214 also had cardiac magnetic resonance imaging performed on day 4. To predict LVR, machine learning methods were employed in order to handle many variables, some of which may have complex interactions. Six months post-MI, echocardiographic increases in LV end-diastolic volume (LVEDV), LV end-systolic volume (LVESV), and LV ejection fraction (LVEF) were 14.1% [interquartile range 0.0, 32.0], 5.0% [-14.0, 25.8], and 8.7% [0.0, 19.4], respectively. At 6 months, 15% or 20% increases in LVEDV were observed in 49% and 42% of patients, respectively, and 37% had an LVEF <50%. The rate of death or new-onset HF at the end of 5-year follow-up was 8.8%. Baseline variables associated with adverse LVR were determined best by random forest analysis and included stroke volume, stroke work, necrosis size, LVEDV, LVEF, and LV afterload, the latter assessed by Ea or Ea/Ees. In contrast, baseline clinical and biological characteristics were poorly predictive of LVR. After adjustment for predictive baseline variables, LV dilation >20% and 6-month LVEF <50% were significantly associated with the risk of death and/or heart failure: hazard ratio (HR) 2.12 (95% confidence interval (CI) 1.05-4.43; p = 0.04) and HR 2.68 (95% CI 1.20-6.00; p = 0.016) respectively. Despite early reperfusion and cardioprotective therapy, adverse LVR remains frequent after acute MI and is associated with a risk of death and HF.”
      原文链接:
    • NETL
    • NSTL

    Study Data from Yunnan Normal University Update Understanding of Machine Learning (Optimization of an Eco-friendly Municipal Solid Waste-to-multi-generation Energy Scheme Integrated By Msw Gasification and Hsofc: Regression Analysis and Machine ...)

    22-23页
    查看更多>>摘要：A new study on Machine Learning is now available. According to news reporting originating from Yunnan, People’s Republic of China, by NewsRx correspondents, research stated, “The utilization of regression models and machine learning algorithms in waste-to-energy systems has the potential to enhance the efficiency and effectiveness of these systems. The predictive capacity to ascertain energy production and optimize operational methodologies can contribute to increased efficacy and proficiency of waste-to-energy systems, thereby diminishing waste generation and fostering the generation of sustainable energy.” Our news editors obtained a quote from the research from Yunnan Normal University, “The gasification technology for Municipal Solid Waste (MSW) provides a multitude of environmental advantages and holds significant importance in safeguarding the environment. This approach entails the use of sustainable and environmentally friendly practices in waste management, which effectively mitigates the release of greenhouse gases while also preserving finite natural resources. Considering the plethora of benefits it offers, it is anticipated that the utilization of MSW gasification as a waste management technique will experience a noticeable surge in popularity in the near future. This study presents a modeling approach for a multigeneration energy system that utilizes municipal solid waste (MSW) gasification technology integrated with a proton conducting solid oxide fuel cell (SOFC). Machine learning algorithms have been devised for the purposes of predicting and optimizing the performance of systems. The heating generation, power generation, electrical efficiency, exergy efficiency, and emission levels of the system have been accurately predicted, exhibiting a substantial level of precision as indicated by R2 values predominantly exceeding 94%.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    New Machine Learning Study Findings Have Been Reported by Researchers at Sichuan Agricultural University (Asset Pricing Via Fused Deep Learning With Visual Clues)

    23-24页
    查看更多>>摘要：Current study results on Machine Learning have been published. According to news reporting originating from Chengdu, People’s Republic of China, by NewsRx correspondents, research stated, “Asset pricing via machine learning provides a promising way to capture price trends by fusing heterogeneous market factors to analyze their joint impact on stock movements rather than relying on statistical and econometric models in finance to explore the causality between a market indicator and stock returns. However, the fusion nature of machine learning also hides the way to unveil the internal mechanism of stock movements.” Financial supporters for this research include National Natural Science Foundation of China (NSFC), China Postdoctoral Science Foundation, Fintech Innovation Center of South-western University of Finance and Economics, Key Laboratory of Financial Intelligence and Financial Engineering of Sichuan Province. Our news editors obtained a quote from the research from Sichuan Agricultural University, “In this study, a deep learning framework with visual clues is presented to unveil the entangled factors and their function on stock movements. In particular, a context-aware hierarchical attention mechanism (CHARM) is first proposed to encode unstructured textual media information to trace the literal power of news on such media-aware stock movements. The encoded media and other structured market factors are further fused via tensor-based learning to infer and visualize their interactions on stock fluctuations. Last, a preestimating method for locating turning points as trading clues is utilized to improve the efficiency of each investment opportunity.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Reports Outline Robotics Study Findings from Hefei University of Technology (Design and Implementation of a 7-dof Cable-driven Serial Spray-painting Robot With Motion-decoupling Mechanisms)

    24-25页
    查看更多>>摘要：Data detailed on Robotics have been presented. According to news reporting originating in Anhui, People’s Republic of China, by NewsRx journalists, research stated, “This paper presents the design and implementation of a 7-DOF cable-driven serial spray-painting robot (CDSSR) featuring motiondecoupling mechanisms and introduces an improved nonsingular inverse kinematics method for redundant serial robots. In the study, first, the motioncoupling characteristics of cable-driven joints and motiondecoupling methods based on translational and rotational compensation were examined.” Financial support for this research came from National Natural Science Foundation of China (NSFC). The news reporters obtained a quote from the research from the Hefei University of Technology, “Next, the mechanical structure of the CDSSR was designed, including motion-decoupling mechanisms, cable-driven differential wrists, and tension-amplification mechanisms. In addition, an improved nonsingular inverse kinematics approach incorporating dual-arm angles and configuration control parameters was developed. Finally, an experimentally scaled prototype of the proposed robot was constructed, and motion decoupling and spray trajectory planning experiments were conducted. The experimental and simulation results demonstrate the effectiveness of the non-singular inverse kinematics method in achieving efficient inverse kinematics solutions under global configuration control.”
      原文链接:
    • NETL
    • NSTL

    New Robotics Study Findings Have Been Reported from Faculty of Engineering (Dynamics Analysis and Control of a Two-Link Manipulator)

    24-24页
    查看更多>>摘要：New research on robotics is the subject of a new report. According to news reporting originating from Cairo, Egypt, by NewsRx correspondents, research stated, “This article develops a practicable, efficient, and robust PID controller for the traditional double pendulum system.” The news journalists obtained a quote from the research from Faculty of Engineering: “Utilizing the Lagrangian method, the equations of motion for the two-link robot manipulator are initially derived. The system of ordinary differential equations for this nonlinearity describes these equations. As closed-form solutions for the equations of motion are absent, we approximate the solution of the initial-value problem. Securing precise user-defined positions while controlling the motion of the two-link robot manipulator proves to be a formidable challenge due to its non-linear behavior. The primary objective is to achieve the intended position of the robot manipulator by implementing the computed torque control method. Once the equation of motion has been derived, MATLAB is utilized to represent the control simulation.” According to the news reporters, the research concluded: “Several computational simulations are employed to validate the controller performance. Specifically, we implement a PID controller to simulate the balancing of the two links on a mobile robot at any given angle, including inverted.”
      原文链接:
    • NETL
    • NSTL

    University of Cambridge Reports Findings in Robotics (A dynamic knowledge graph approach to distributed self-driving laboratories)

    25-26页
    查看更多>>摘要：New research on Robotics is the subject of a report. According to news reporting from Cambridge, United Kingdom, by NewsRx journalists, research stated, “The ability to integrate resources and share knowledge across organisations empowers scientists to expedite the scientific discovery process. This is especially crucial in addressing emerging global challenges that require global solutions.” Financial supporters for this research include RCUK | Engineering and Physical Sciences Research Council, Alexander von Humboldt-Stiftung, Pharma Innovation Platform Singapore (PIPS) via grant to CARES 5 Ltd “Data2Knowledge, C12”, Cambridge Commonwealth, European and International Trust, China Scholarship Council. The news correspondents obtained a quote from the research from the University of Cambridge, “In this work, we develop an architecture for distributed self-driving laboratories within The World Avatar project, which seeks to create an all-encompassing digital twin based on a dynamic knowledge graph. We employ ontologies to capture data and material flows in design-make-test-analyse cycles, utilising autonomous agents as executable knowledge components to carry out the experimentation workflow. Data provenance is recorded to ensure its findability, accessibility, interoperability, and reusability. We demonstrate the practical application of our framework by linking two robots in Cambridge and Singapore for a collaborative closed-loop optimisation for a pharmaceutically-relevant aldol condensation reaction in real-time.”
      原文链接:
    • NETL
    • NSTL

    Researchers from Faculty of Applied Sciences Report Recent Findings in Artificial Intelligence (Navigating the perils of artificial intelligence: a focused review on ChatGPT and responsible research and innovation)

    26-27页
    查看更多>>摘要：Researchers detail new data in artificial intelligence. According to news originating from the Faculty of Applied Sciences by NewsRx correspondents, research stated, “While the rise of artificial intelligence (AI) tools holds promise for delivering benefits, it is important to acknowledge the associated risks of their deployment.” The news journalists obtained a quote from the research from Faculty of Applied Sciences: “In this article, we conduct a focused literature review to address two central research inquiries concerning ChatGPT and similar AI tools. Firstly, we examine the potential pitfalls linked with the development and implementation of ChatGPT across the individual, organizational, and societal levels. Secondly, we explore the role of a multi-stakeholder responsible research and innovation framework in guiding chatbots’ sustainable development and utilization. Drawing inspiration from responsible research and innovation and stakeholder theory principles, we underscore the necessity of comprehensive ethical guidelines to navigate the design, inception, and utilization of emerging AI innovations. The findings of the focused review shed light on the potential perils of ChatGPT implementation across various societal levels, including issues such as devaluation of relationships, unemployment, privacy concerns, bias, misinformation, and digital inequities.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    New Machine Learning Research Has Been Reported by a Researcher at National Institute of Technology (Experimental Investigation of the Influence of Various Wear Parameters on the Tribological Characteristics of AZ91 Hybrid Composites and Their ...)

    27-28页
    查看更多>>摘要：New study results on artificial intelligence have been published. According to news originating from Tamil Nadu, India, by NewsRx editors, the research stated, “In the current work, the AZ91 hybrid composites are fabricated through the utilization of the stir casting technique, incorporating aluminum oxide (Al2O3) and graphene (Gr) as reinforcing elements.” Our news journalists obtained a quote from the research from National Institute of Technology: “Wear behavior of the AZ91/Gr/Al2O3 composites was examined with the pin-on-disc setup under dry conditions. In this study, the factors such as reinforcement percentage ®, load (L), velocity (Ⅴ), and sliding distance (D) have been chosen to investigate their impact on the wear-rate (WR) and coefficient of friction (COF). This study utilizes a full factorial design to conduct experiments. The experimental data was critically analyzed to examine the impact of each wear parameter (i.e., R, L, V, and D) on the WR and COF of composites. The wear mechanisms at the extreme conditions of maximum and minimum wear rates are also investigated by utilizing the scanning electron microscope (SEM) images of specimen’s surface. The SEM study revealed the presence of delamination, abrasion, oxidation, and adhesion mechanisms on the surface experiencing wear.”
      原文链接:
    • NETL
    • NSTL
    • Asme

    Northeast Agricultural University Reports Findings in Machine Learning (Machine Learning Combined With Molecular Simulations To Screen A-amylase Inhibitors As Compounds That Regulate Blood Sugar)

    28-29页
    查看更多>>摘要：Investigators publish new report on Machine Learning. According to news reporting from Harbin, People’s Republic of China, by NewsRx journalists, research stated, “Diabetes, a metabolic disease characterized by hyperglycemia, seriously endangers the health and the lives of people. alpha-Amylase inhibitors have become effective substances to control blood glucose, and attracted extensive attention. In this study, a database of alpha-amylase inhibitors derived from naturally active small molecules in food was created and a quantitative structure-activity relationship model was developed by combining three machine learning methods (SVM, RF, and LDA) with four descriptors (MOE, ChemoPy, Mordred, and Rdkit).” Financial support for this research came from National Center of Technology Innovation for Dairy. The news correspondents obtained a quote from the research from Northeast Agricultural University, “Hydrogen bond and hydrophobic interaction in the inhibition of alpha-amylase activity was confirmed by molecular docking. Enzyme inhibition experiments showed that the predicted compound had alpha-amylase inhibitory activity. Nevadensin was identified as a promising candidate of alpha-amylase inhibitors. The stability of alpha-amylase binding reaction was verified by molecular dynamics simulation. Optimal process conditions for the extraction of nevadensin from L. pauciflorus maxim were derived from single-factor experiments and response surface modeling.”
      原文链接:
    • NETL
    • NSTL