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    Southern Federal University Reports Findings in Machine Learning (Machine Learning for Quantitative Structural Information from Infrared Spectra: The Case of Palladium Hydride)

    76-77页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news originating from Rostov on Don, Russia, by NewsRx correspondents, research stated, “Infrared spectroscopy (IR) is a widely used technique enabling to identify specific functional groups in the molecule of interest based on their characteristic vibrational modes or the presence of a specific adsorption site based on the characteristic vibrational mode of an adsorbed probe molecule. The interpretation of an IR spectrum is generally carried out within a fingerprint paradigm by comparing the observed spectral features with the features of known references or theoretical calculations.” Our news journalists obtained a quote from the research from Southern Federal University, “This work demonstrates a method for extracting quantitative structural information beyond this approach by application of machine learning (ML) algorithms. Taking palladium hydride formation as an example, Pd-H pressure-composition isotherms are reconstructed using IR data collected in situ in diffuse reflectance using CO molecule as a probe.”
      原文链接:
    • NETL
    • NSTL
    • Wiley

    Council of Scientific and Industrial Research (CSIR) Researchers Provide New Insights into Robotics (Modular robotic arm for automation of SMME industrial press)

    77-77页
    查看更多>>摘要：New research on robotics is the subject of a new report. According to news reporting from the Council of Scientific and Industrial Research (CSIR) by NewsRx journalists, research stated, “Small South African manufacturing companies, endeavouring to benefit from Fourth Industrial Revolution (4IR) technologies, specifically automation, are restricted by exorbitant costs and the lack of know-how associated with automation.” The news editors obtained a quote from the research from Council of Scientific and Industrial Research (CSIR): “This project aims to develop affordable modular automation blocks that can couple with each other, using the OpenStructures grid, to provide customisable degrees of freedom tailored for specific automation applications. The cost of development is recovered, and the cost of maintenance is reduced through the reuse of these blocks over different automation applications.” According to the news editors, the research concluded: “A key measure of effectiveness is a standardised mechanical and electrical interface for each block.”
      原文链接:
    • NETL
    • NSTL

    Tsinghua University Reports Findings in Nephrolithotomy (Machine learning algorithm to predict postoperative bleeding complications after lateral decubitus percutaneous nephrolithotomy)

    78-78页
    查看更多>>摘要：New research on Surgery - Nephrolithotomy is the subject of a report. According to news reporting from Beijing, People's Republic of China, by NewsRx journalists, research stated, “Bleeding is a serious complication following percutaneous nephrolithotomy (PCNL). This study establishes a predictive model based on machine learning algorithms to forecast the occurrence of postoperative bleeding complications in patients with renal and upper ureteral stones undergoing lateral decubitus PCNL.” The news correspondents obtained a quote from the research from Tsinghua University, “We retrospectively collected data from 356 patients with renal stones and upper ureteral stones who underwent lateral decubitus PCNL in the Department of Urology at Peking University First Hospital-Miyun Hospital, between January 2015 and August 2022. Among them, 290 patients had complete baseline data. The data was randomly divided into a training group (n = 232) and a test group (n = 58) in an 8:2 ratio. Predictive models were constructed using Logistic Regression, Random Forest, and Extreme Gradient Boosting (XGBoost). The performance of each model was evaluated using Accuracy, Precision, F1-Score, Receiver Operating Characteristic curves, and Area Under the Curve (AUC). Among the 290 patients, 35 (12.07%) experienced postoperative bleeding complications after lateral decubitus PCNL. Using postoperative bleeding as the outcome, the Logistic model achieved an accuracy of 73.2%, AUC of 0.605, and F1 score of 0.732. The Random Forest model achieved an accuracy of 74.5%, AUC of 0.679, and F1 score of 0.732. The XGBoost model achieved an accuracy of 68.3%, AUC of 0.513, and F1 score of 0.644. The predictive model for postoperative bleeding after lateral decubitus PCNL, established based on machine learning algorithms, is reasonably accurate.”
      原文链接:
    • NETL
    • NSTL

    Universidad de Alcala Reports Findings in Machine Learning (An explainable machine learning approach for hospital emergency department visits forecasting using continuous training and multi-model regression)

    79-79页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting from Alcala de Henares, Spain, by NewsRx journalists, research stated, “In the last years, the Emergency Department (ED) has become an important source of admissions for hospitals. Since late 90s, the number of ED visits has been steadily increasing, and since Covid19 pandemic this trend has been much stronger.” The news correspondents obtained a quote from the research from Universidad de Alcala, “Accurate prediction of ED visits, even for moderate forecasting time-horizons, can definitively improve operational efficiency, quality of care, and patient outcomes in hospitals. In this paper we propose two different interpretable approaches, based on Machine Learning algorithms, to accurately forecast hospital emergency visits. The proposed approaches involve a first step of data segmentation based on two different criteria, depending on the approach considered: first, a threshold-based strategy is adopted, where data is divided depending on the value of specific predictor variables. In a second approach, a cluster-based ensemble learning is proposed, in such a way that a clustering algorithm is applied to the training dataset, and ML models are then trained for each cluster. The two proposed methodologies have been evaluated in real data from two hospital ED visits datasets in Spain. We have shown that the proposed approaches are able to obtain accurate ED visits forecasting, in short-term and also long-term prediction time-horizons up to one week, improving the efficiency of alternative prediction methods for this problem. The proposed forecasting approaches have a strong emphasis on providing explainability to the problem.”
      原文链接:
    • NETL
    • NSTL

    Nanchang Institute of Technology Researcher Focuses on Artificial Intelligence (Research and Practical Exploration of New Models of Social Governance in the Age of Artificial Intelligence)

    80-80页
    查看更多>>摘要：Current study results on artificial intelligence have been published. According to news originating from the Nanchang Institute of Technology by NewsRx correspondents, research stated, “With the rapid development of artificial intelligence, social governance is facing new challenges and opportunities.” The news editors obtained a quote from the research from Nanchang Institute of Technology: “This study aims to explore new models of social governance in the era of artificial intelligence, in order to contribute to social stability and development. Through literature review and empirical research, this paper first reviews the rapid application of artificial intelligence technology and the emergence of artificial intelligence. literature review and empirical research, this paper first reviews the rapid application of artificial intelligence technology and the emergence of Through literature review and empirical research, this paper first reviews the rapid application of artificial intelligence technology and the emergence of related issues, and then explores the new situations and challenges faced by social governance in the era of artificial intelligence. Based on in-depth analysis of various governance practices, this paper proposes an innovative new model of social governance, namely the co-governance model supported by artificial intelligence. By fully utilising artificial intelligence technology and establishing an intelligent social governance system, it promotes collaboration and interaction between government and the private sector. By fully utilising artificial intelligence technology and establishing an intelligent social governance system, it promotes collaboration and interaction between government and the public, as well as between enterprises and individuals, thereby achieving By fully utilising artificial intelligence technology and establishing an intelligent social governance system, it promotes collaboration and interaction between government and the public, as well as between enterprises and individuals, thereby achieving rationalization, efficiency, and sustainable development of social governance. Finally, through case studies and practical exploration, the implementation and effects of the proposed new model of social governance are demonstrated.”
      原文链接:
    • NETL
    • NSTL

    Recent Studies from National Institute of Technology Add New Data to Machine Learning (Simplified discrimination method and systematically threshold setting for pipe inspection using vibrationsensing- actuation device)

    81-81页
    查看更多>>摘要：Investigators discuss new findings in artificial intelligence. According to news originating from the National Institute of Technology by NewsRx correspondents, research stated, “Water pipes have exceeded their service life, and the number of leakage and burst accidents is increasing. These accidents cause economic losses due to the interruption of operations and supply.” Our news journalists obtained a quote from the research from National Institute of Technology: “However, replacing all the deteriorated pipes is difficult, as this would involve a huge cost and long time. Therefore, the condition of water pipes must be quantified, and an efficient maintenance management is required. Current sensors for detecting water leakage have many problems because their measurement principle is a passive system, and thus they are susceptible to external noise. In our previous study, we proposed an active vibration sensing-actuation device to improve the measurement reliability for a water pipe deterioration diagnosis. The principle of deterioration diagnosis was based on the detection of the frequency change of the in-plane bending mode. In that study, the thresholds of discrimination were determined by the amplitude of the response based on empirical knowledge, which did not allow for theoretical or systematic discrimination. In this study, we focused on a simplified discrimination method of deterioration of a water pipe and its implementation with an IoT sensor module. The following three methods were considered in terms of implementation cost: an absolute threshold method based on theoretical random vibration analysis (based on a physical model), a linear discrimination method, and a support vector machine (based on a machine learning model), and the most appropriate discrimination method was determined. Furthermore, we considered the discrimination accuracy of models based on physics and machine learning. The results show that the support vector machine has the best accuracy, followed by the absolute threshold method, which has good accuracy. However, when compared in terms of computational complexity, the absolute threshold method is superior from both perspectives in terms of implementation.”
      原文链接:
    • NETL
    • NSTL

    New Machine Learning Study Results Reported from Shanghai University (Water-tolerant and Anti-dust Ceco-mno2 Membrane Catalysts for Low Temperature Selective Catalytic Reduction of Nitrogen Oxides)

    82-82页
    查看更多>>摘要：Investigators discuss new findings in Machine Learning. According to news reporting out of Shanghai, People's Republic of China, by NewsRx editors, research stated, “The present work successfully proposes a domain knowledge-guided Machine Learning (ML) strategy, which successes the development of a water-tolerant anti-dust catalyst for Low-Temperature (LT) Selective Catalytic Reduction (SCR) of nitrogen oxides (NOx) from catalyst discovery to industrial deployment. The discovered catalyst is able to convert 99 % of NOx at 150 degrees C in the standard waste gas, even in the waste gas containing 7 vol % of water vapors, the efficiency is still retained at 97 %. The superior LT activity and water-tolerance are attributed to abundant surface-active oxygen, Bronsted acid and microcellular structure.” Financial support for this research came from Introduced Jointed Research and Development Institution of Jiangxi. Our news journalists obtained a quote from the research from Shanghai University, “The SCR reaction mainly follows the Eley-Rideal (E-R) pathway driven by Bronsted acid and the Langmuir-Hinshelwood (LH) pathway maintained by abundant reactive oxygen species in moisture waste gases. And then, catalyst is synthesized on a polyphenylene sulfide filter to render the membrane configuration in order to have the anti-dust ability. The final membrane catalyst has the capacity of converting 95 % NOx in the waste gas containing 7 vol% of moisture at 150 degrees C and the dedusting, and denitrification ability.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    University of Chicago Reports Findings in Machine Learning (Classifying Protein-Protein Binding Affinity with Free-Energy Calculations and Machine Learning Approaches)

    83-83页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting originating from Chicago, Illinois, by NewsRx correspondents, research stated, “Understanding the intricate phenomenon of neuronal wiring in the brain is of great interest in neuroscience. In the fruit fly, the Dpr-DIP interactome has been identified to play an important role in this process.” Our news editors obtained a quote from the research from the University of Chicago, “However, experimental data suggest that a merely limited subset of complexes, essentially 57 out of a total of 231, exhibit strong binding affinity. In this work, we sought to identify the residue-level molecular basis underlying the difference in binding affinity using a state-of-the-art methodology consisting of standard binding free-energy calculations with a geometrical route and machine learning (ML) techniques. We determined the binding affinity for two complexes using statistical mechanics simulations, achieving an excellent reproduction of the experimental data. Moreover, we predicted the binding free energy for two additional low-affinity complexes, devoid of experimental estimation, while simultaneously identifying key residues for the binding. Furthermore, through the use of ML algorithms, linear discriminant analysis, and random forest, we achieved remarkable accuracy, as high as 0.99, in discerning between strong (cognate) and weak (noncognate) binders. The presented ML approach encompasses easily transferable input features, enabling its broad application to any interactome while facilitating the identification of pivotal residues critical for binding interactions. The predictive power of the generated model was probed on similar protein families from 13 diverse species.”
      原文链接:
    • NETL
    • NSTL

    Reports Summarize Machine Learning Research from 'Dunarea de Jos' University (A Machine Learning Algorithm That Experiences the Evolutionary Algorithm's Predictions-An Application to Optimal Control)

    84-84页
    查看更多>>摘要：Research findings on artificial intelligence are discussed in a new report. According to news originating from Galati, Romania, by NewsRx correspondents, research stated, “Using metaheuristics such as the Evolutionary Algorithm (EA) within control structures is a realistic approach for certain optimal control problems. They often predict the optimal control values over a prediction horizon using a process model (PM).” The news reporters obtained a quote from the research from “Dunarea de Jos” University: “The computational effort sometimes causes the execution time to exceed the sampling period. Our work addresses a new issue: whether a machine learning (ML) algorithm could 'learn' the optimal behaviour of the couple (EA and PM). A positive answer is given by proposing datasets apprehending this couple's optimal behaviour and appropriate ML models. Following a design procedure, a number of closed-loop simulations will provide the sequences of optimal control and state values, which are collected and aggregated in a data structure. For each sampling period, datasets are extracted from the aggregated data. The ML algorithm experiencing these datasets will produce a set of regression functions. Replacing the EA predictor with the ML model, new simulations are carried out, proving that the state evolution is almost identical. The execution time decreases drastically because the PM's numerical integrations are totally avoided.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    New Machine Learning Findings from Swiss Federal Institute of Technology Lausanne (EPFL) Described (Remapping Wetness Perception In Upper Limb Amputees)

    84-85页
    查看更多>>摘要：Current study results on Machine Learning have been published. According to news reporting from Lausanne, Switzerland, by NewsRx journalists, research stated, “Recent research has made remarkable strides in restoring sensory feedback for prosthetic users, including tactile, proprioceptive, and thermal feedback. Herein, a sensory modality that has been largely neglected is explored: the ability to perceive wetness.” Financial support for this research came from H2020 European Research Council. The news correspondents obtained a quote from the research from the Swiss Federal Institute of Technology Lausanne (EPFL), “Providing moisture-related information to prosthesis users can increase their overall sensory palette toward a more natural sensory experience. A rapid decrease in skin temperature is found to trigger the illusion of contact with something wet. Two body parts were tested, the upper arm and the lateral abdomen, in a group of non amputated participants, and it was found that a wetness sensation can be elicited and maintained for at least 10 s in 86% and 93% of participants, respectively. It is then demonstrated how to mediate the wetness sensation in real-time using a thermal wearable device that mimics the thermal properties of the skin. Finally, two upper limb amputee individuals used their prosthetic arm, sensorized with the device, to discriminate between three levels of moisture; their detection accuracy was similar to one they had with their intact hands. The current study is a stepping stone for future prostheses aimed at restoring the richness of sensory experience in upper limb amputees. A new generation of prostheses aims to restore the rich sensory feedback of amputated people, but one modality is often neglected: wetness perception. Ploumitsakou and colleagues present an approach to detect and mediate moisture information: a cold, dry skin stimulation created the vivid sensation of touching something wet.” According to the news reporters, the research concluded: “Blindfolded amputees could scan objects and discriminate three levels of moisture.i.”
      原文链接:
    • NETL
    • NSTL
    • Wiley