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    Affiliated Hospital of Inner Mongolia Medical University Reports Findings in Gli omas (Construction and validation of a machine learning-based immune-related pro gnostic model for glioma)

    76-77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 Oncology - Gliomas is the subject of a report. According to news reporting out of Hohhot, People’s Rep ublic of China, by NewsRx editors, research stated, “Glioma stands as the most p revalent primary brain tumor found within the central nervous system, characteri zed by high invasiveness and treatment resistance. Although immunotherapy has sh own potential in various tumors, it still faces challenges in gliomas.” Our news journalists obtained a quote from the research from the Affiliated Hosp ital of Inner Mongolia Medical University, “This study seeks to develop and vali date a prognostic model for glioma based on immune-related genes, to provide new tools for precision medicine. Glioma samples were obtained from a database that includes the ImmPort database. Additionally, we incorporated ten machine learni ng algorithms to assess the model’s performance using evaluation metrics like th e Harrell concordance index (C-index). The model genes were further studied usin g GSCA, TISCH2, and HPA databases to understand their role in glioma pathology a t the genomic, molecular, and single-cell levels, and validate the biological fu nction of IKBKE in vitro experiments. In this study, a total of 199 genes associ ated with prognosis were identified using univariate Cox analysis. Subsequently, a consensus prognostic model was developed through the application of machine l earning algorithms. In which the Lasso + plsRcox algorithm demonstrated the best predictive performance. The model showed a good ability to distinguish two grou ps in both the training and test sets. Additionally, the model genes were closel y related to immunity (oligodendrocytes and macrophages), and mutation burden. T he results of in vitro experiments showed that the expression level of the IKBKE gene had a significant effect on the apoptosis and migration of GL261 glioma ce lls. Western blot analysis showed that down-regulation of IKBKE resulted in incr eased expression of pro-apoptotic protein Bax and decreased expression of anti-a poptotic protein Bcl-2, which was consistent with increased apoptosis rate. On t he contrary, IKBKE overexpression caused a decrease in Bax expression an increas e in Bcl-2 expression, and a decrease in apoptosis rate. Tunel results further c onfirmed that down-regulation of IKBKE promoted apoptosis, while overexpression of IKBKE reduced apoptosis. In addition, cells with down-regulated IKBKE had red uced migration in scratch experiments, while cells with overexpression of IKBKE had increased migration. This study successfully constructed a glioma prognosis model based on immune-related genes.”
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    Reports Summarize Robotics Research from Technical University of Sofia (Programm ing Industrial Robots in the Fanuc ROBOGUIDE Environment)

    77-78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 originating from Sofia, Bulgaria, by NewsRx correspond ents, research stated, “Descriptions of the main CARC environments for programmi ng industrial robots are given, describing the main used programming environment s for various robot manufacturers such as ROBOGUIDE developed by FANUC Robotics, KUKA Sim and Kuka Work Visual developed by KUKA ROBOTICS, Robot Studio develope d by ABB Robotics, K-ROSET and K-ROSET LITE developed by Kawasaki Robotics, Visu al Component, DELMIA ROBOTICS of Dassault Systems, Tecnomatix Robotics & Automation Simulation of SIEMENS PLM Software/Simatic Robot Integrator, Visual C omponents, etc.”
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    Studies in the Area of Artificial Intelligence Reported from Rzeszow University of Technology (Predictive Artificial Intelligence Models for Energy Efficiency i n Hybrid and Electric Vehicles: Analysis for Enna, Sicily)

    78-79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 artificial intelligen ce have been presented. According to news originating from Rzeszow, Poland, by N ewsRx editors, the research stated, “Developments in artificial intelligence tec hniques allow for an improvement in sustainable mobility strategies with particu lar reference to energy consumption estimates of electric vehicles (EVs).” Our news reporters obtained a quote from the research from Rzeszow University of Technology: “This research proposes a vehicle energy model developed on the bas is of deep neural network (DNN) technology. This study also explores the potenti al application of the model developed for the movement data of new vehicles in t he province of Enna, Sicily, Italy, which are characterized by numerous attracto rs and the increasing number of hybrid and electric cars circulating. The energy model for electric vehicles shows high accuracy and versatility, requiring vehi cle velocity and acceleration as input data to predict energy consumption. This research article also provides recommendations for the energy modeling of electr ic vehicles and outlines additional steps for model development.”
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    Study Findings on Robotics Detailed by Researchers at Department of Electronics and Computer Engineering (Design and Implementation of Versatile Delivery Robot)

    79-79页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Research findings on robotics are disc ussed in a new report. According to news reporting out of Visakhapatnam, India, by NewsRx editors, research stated, “This paper focuses on the design and implem entation of a versatile delivery robot which integrates a secure locking system, GPS navigation, customer authentication, and a camera system for real-time moni toring.” The news correspondents obtained a quote from the research from Department of El ectronics and Computer Engineering: “The advanced locking system ensures the pro tection of delivered goods during transit, addressing security concerns. GPS nav igation optimizes routes for efficient last-mile deliveries, reducing overall de livery times. Customer authentication adds an extra layer of security, allowing only the designated customer, equipped with a unique authentication method, to u nlock and retrieve their parcel. The integrated camera system provides continuou s monitoring throughout the delivery process. The combination of these features showcases technological innovation and also addresses critical aspects of securi ty and customer trust in autonomous deliveries.”
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    Researchers from University of Cote d’Azur Report Details of New Studies and Fin dings in the Area of Machine Learning (Optically Accelerated Extreme Learning Ma chine Using Hot Atomic Vapors)

    80-81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 Machine Learn ing have been published. According to news reporting from Nice, France, by NewsR x journalists, research stated, “Machine learning is becoming a widely used tech nique with impressive growth due to the diversity of problems of societal intere st for which it can offer practical solutions. This increase of applications and required resources start to become limited by present-day hardware technologies .”Funders for this research include CNRS Innovation via the prematuration project SQVAC, Provence- Alpes-Cote d’Azur region via a “Jeune docteur innovant” project.
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    Researchers at Department of Electrical and Electronics Engineering Zero in on M achine Learning (Machine Learning Models for Predicting and Managing Electric Ve hicle Load in Smart Grids)

    80-80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 the Department of El ectrical and Electronics Engineering by NewsRx correspondents, research stated, “The integration of electric vehicles (EVs) into smart grids provides major issu es and prospects for effective energy management.” The news reporters obtained a quote from the research from Department of Electri cal and Electronics Engineering: “This research examines the actual utilization of machine learning models to forecast and manage EV demand in smart grids, inte nded to increase grid effectiveness and dependable operation. We acquire and pre process different datasets, considering elements such as time of usage, characte ristics of the environment, and user behaviors. Multiple machine learning models , combining neural networks, support vector machines, and forests that are rando m, are developed and rated for their projected accuracy. Our results imply that enhanced prediction algorithms may considerably raise all the level of detail of EV load forecasts. Furthermore, we recommend load management systems based on r eal-time forecasts to enhance energy distribution and lower peak demand.”
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    European Bioinformatics Institute Reports Findings in Machine Learning (Dataset from a human-in-the-loop approach to identify functionally important protein res idues from literature)

    81-82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 Cambridge, United King dom, by NewsRx editors, research stated, “We present a novel system that leverag es curators in the loop to develop a dataset and model for detecting structure f eatures and functional annotations at residue-level from standard publication te xt. Our approach involves the integration of data from multiple resources, inclu ding PDBe, EuropePMC, PubMedCentral, and PubMed, combined with annotation guidel ines from UniProt, and LitSuggest and HuggingFace models as tools in the annotat ion process.”
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    Chinese Academy of Medical Sciences Reports Findings in Bioinformatics (Unveilin g the glycolysis in sepsis: Integrated bioinformatics and machine learning analy sis identifies crucial roles for IER3, DSC2, and PPARG in disease pathogenesis)

    82-83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 Biotechnology - Bioinf ormatics is the subject of a report. According to news originating from Beijing, People’s Republic of China, by NewsRx correspondents, research stated, “Sepsis, a multifaceted syndrome driven by an imbalanced host response to infection, rem ains a significant medical challenge. At its core lies the pivotal role of glyco lysis, orchestrating immune responses especially in severe sepsis.” Our news journalists obtained a quote from the research from the Chinese Academy of Medical Sciences, “The intertwined dynamics between glycolysis, sepsis, and immunity, however, have gaps in knowledge with several Crucial genes still shrou ded in ambiguity. We harvested transcriptomic profiles from the peripheral blood of 107 septic patients juxtaposed against 29 healthy controls. Delving into thi s dataset, differential expression analysis shed light on genes distinctly linke d to glycolysis in both cohorts. Harnessing the prowess of LASSO regression and SVM-RFE, we isolated Crucial genes, paving the way for a sepsis risk prediction model, subsequently vetted via Calibration and decision curve analysis. Using th e CIBERSORT algorithm, we further mapped 22 immune cell subtypes within the sept ic samples, establishing potential interactions with the delineated Crucial gene s. Our efforts unveiled 21 genes intricately tied to glycolysis that exhibited d ifferential expression patterns. Gene set enrichment analysis (GSEA) and Kyoto E ncyclopedia of Genes and Genomes (KEGG) pathway analyses offered insights, spotl ighting pathways predominantly associated with oxidative phosphorylation, PPAR s ignaling pathway, Glycolysis/Gluconeogenesis and HIF-1 signaling pathway. Among the myriad genes, IER3, DSC2, and PPARG emerged as linchpins, their prominence i n sepsis further validated through ROC analytics. These sentinel genes demonstra ted profound affiliations with various immune cell facets, bridging the complex terrain of glycolysis, sepsis, and immune responses. In line with our endeavor t o ‘unveil the glycolysis in sepsis,’ the discovery of IER3, DSC2, and PPARG rein forces their cardinal roles in sepsis pathogenesis.”
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    Study Results from University of Malaysia Perlis Broaden Understanding of Machin e Learning (Integration of Dual Band Radio Waves and Ensemble-based Approach for Rice Moisture Content Determination and Localisation)

    83-84页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – Fresh data on Machine Learning are presented in a new report. According to news reporting originating from Arau, Malaysia, by New sRx correspondents, research stated, “Maintaining optimal moisture content in gr ain storage is critical to ensuring adequate supply throughout the year, but it presents a significant challenge. Current moisture measurement methods often nec essitate sophisticated and costly equipment.” Financial supporters for this research include Ministry of Higher Education (MOH E) Malaysia under grant Transdisciplinary Research Grant Scheme, Universiti Mala ysia Perlis (UniMAP).
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    Research Reports on Artificial Intelligence from Tokat Gaziosmanpasa Universites i Provide New Insights (Does ChatGPT provide comprehensive and accurate informat ion regarding the effects, types and programming of core exercises?)

    84-85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 the Tokat Gazi osmanpasa Universitesi by NewsRx correspondents, research stated, “The objective of this study is to assess the accuracy of ChatGPT’s responses regarding core e xercises.” The news journalists obtained a quote from the research from Tokat Gaziosmanpasa Universitesi: “A total of 23 questions were asked to ChatGPT 3.5 about core exe rcises. Nine physiotherapists assessed the accuracy of the answers provided by C hatGPT for these questions using a 5-point Likert scale (5: strongly agree, 1: s trongly disagree). The maximum possible score achievable through Likert scoring is 115, while the minimum score is 23. The answers of the artificial intelligenc e received an average of 3.93±0.46 (minimum: 3.48, maximum: 4.91) points. The lo west score obtained from the responses of ChatGPT was 3.22 ± 0.97 (question 21), whereas the highest score was 4.56 ± 0.53 (questions 12 and 18).”
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