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    Beijing Hospital Reports Findings in Bladder Cancer (Dynamic landscapeof m6A mo difications and related post-transcriptional eventsin muscle-invasive bladder c ancer)

    40-41页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Oncology - Bladder Can cer is the subject of a report. According tonews reporting originating from Bei jing, People’s Republic of China, by NewsRx correspondents, researchstated, “Mu scle-invasive bladder carcinoma (MIBC) is a serious and more advanced stage of b laddercarcinoma. N6-Methyladenosine (m6A) is a dynamic and reversible modificat ions that primarily affectsRNA stability and alternative splicing.”Our news editors obtained a quote from the research from Beijing Hospital, “The dysregulation of m6Ain MIBC can be potential target for clinical interventions, but there have been limited studies on m6Amodifications in MIBC and their asso ciations with post-transcriptional regulatory processes. Paired tumorand adjace nt-normal tissues were obtained from three patients with MIBC following radical cystectomy.The additional paired tissues for validation were obtained from pati ents underwent transurethral resection.Utilizing Nanopore direct-RNA sequencing , we characterized the m6A RNA methylation landscape in MIBC, with a focus on id entifying post-transcriptional events potentially affected by changes in m6A sites. This included an examination of differential transcript usage, polyadenylati on signal sites, and variationsin poly(A) tail length, providing insights into the broader impact of m6A alterations on RNA processing inMIBC. The prognostic- related m6A genes and m6A-risk model constructed by machine learning enablesthe stratification of high and low-risk patients with precision. A novel m6A modifi cation site in the 3’untranslated region (3’UTR) of IGLL5 gene were identified, characterized by a lower m6A methylationratio, elongated poly(A) tails, and a notable bias in transcript usage. Furthermore, we discovered twoparticular tran scripts, VWA1-203 and CEBPB-201. VWA1-203 displayed diminished m6A methylation levels, a truncated 3’UTR, and an elongated poly(A) tail, whereas CEBPB-201 showe d opposite trends,highlighting the complex interplay between m6A modifications and RNA processing.
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    Studies from School of Intelligent Manufacturing Further Understandingof Roboti cs (Research on automatic control and servocontrol technology of industrial rob ots for high-precision assemblyrequirements)

    41-42页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on robotics is the subjec t of a new report. According to news originatingfrom Jiangsu, People’s Republic of China, by NewsRx editors, the research stated, “Industrial robots findwides pread application in machining, part assembly, and welding processes.”Our news editors obtained a quote from the research from School of Intelligent M anufacturing: “Thispaper focuses on the precise control of industrial robots, u sing the permanent magnet synchronous motor(PMSM) as the driving device of the manipulator. By constructing a mathematical model of the PMSMand implementing a vector control strategy, we design an adaptive control algorithm based on the f eaturemodel. We also introduce the golden section adaptive control and the posi tion outer-loop control, which are based on the nonlinear proportional regulator . This approach enables the creation of industrial robotsthat utilize high-prec ision servo control technology. After analyzing the response speed and positiona laccuracy of the servo control technology through testing experiments, we integ rated this technology intothe design of the automatic control system for indust rial robots and conducted simulation tests to exploreits performance in various applications. The results demonstrate the superior speed response speed andpos ition control accuracy of the servo control technology; the response times for s peed and position areapproximately 0.2 seconds and 1 second, respectively, with a maximum deviation of 31.75 rpm when thespeed remains constant.”
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    Reports from Karunya Institute of Technology and Sciences AddNew Study Findings to Research in Artificial Intelligence (Precisionin motion: enhancing autonomo us driving with advanced lanerecognition using high resolution network)

    42-43页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on artificial intelligenc e is the subject of a new report. Accordingto news reporting out of Coimbatore, India, by NewsRx editors, research stated, “Autonomous cars arerevolutionizing transportation by navigating roadways without human intervention using digital technologyand artificial intelligence.”The news journalists obtained a quote from the research from Karunya Institute o f Technology andSciences: “However, reliable lane recognition is a big barrier in this endeavor. Lane identification isa complex topic that presents significa nt challenges to computer vision and machine learning systems.Accurate lane lin e detection can be challenging due to real-world driving conditions, resulting i n negativelyimpacts steering angle prediction. In response to this difficulty, our research proposes a novel strategy toimproving lane detection and steering control accuracy. To recognize lanes with better precision, we usecomputer visi on techniques, namely semantic segmentation. Semantic segmentation allows the ve hicle’sinternal artificial intelligence system to classify each pixel in an ima ge as belonging to a given object class,such as road lanes.”
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    Researchers from Persian Gulf University Detail Research in MachineLearning (In vestigation of wettability and IFT alteration duringhydrogen storage using mach ine learning)

    43-44页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on artificial intelligence is now available. According to news reporting fromBushehr, Iran, by NewsRx jou rnalists, research stated, “Reducing the environmental impact caused by theprod uction or use of carbon dioxide (CO2) and other greenhouse gases (GHG) has recen tly attracted theattention of scientific, research, and industrial communities. In this context, oil production and enhancedoil recovery (EOR) have also focus ed on using environmentally friendly methods.”Our news editors obtained a quote from the research from Persian Gulf University : “CO2 has beenstudied as a significant gas in reducing harmful environmental e ffects and preventing its release into theatmosphere. This gas, along with meth ane (CH4) and nitrogen (N2), is recognized as a ‘cushion gas’.Given that hydrog en (H2) is considered a green and environmentally friendly gas, its storage for alteringwettability (contact angle (CA) and interfacial tension (IFT)) has rece ntly become an intriguing topic.This study examines how H2 can be utilized as a novel cushion gas in EOR systems. In this research,the role of H2 and its stor age in altering wettability in the presence of other cushion gases has been investigated. The performance of H2 in changing the CA and IFT with other gases has also been comparedusing machine learning (ML) models. During this process, ML a nd experimental data were used to predictand report the values of IFT and CA. T he data used underwent statistical and quantitative preprocessing,processing, e valuation, and validation, with outliers and skewed data removed. Subsequently, ML modelssuch as Random Forest (RF), Random Tree, and LSBoost were implemented on training and testing data.”
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    Ankara Yildirim Beyazit University Reports Findings in Artificial Intelligence( Patients’ attitudes toward artificial intelligence in dentistryand their trust in dentists)

    44-45页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Artificial Intelligenc e is the subject of a report. According to newsoriginating from Ankara, Turkey, by NewsRx correspondents, research stated, “This study intended toevaluate pat ients’ attitudes toward the use of AI in dental radiographic detection of occlus al caries andthe impact of AI-based diagnosis on their trust in dentists. A tot al of 272 completed questionnaires wereincluded in this study.”Our news journalists obtained a quote from the research from Ankara Yildirim Bey azit University, “Inthe first part of the study, approval was obtained from the patients, and data were collected about theirsocio-demographic characteristics . In the second part the 11-item Dentist Trust Scale was applied. Inthe third a nd fourth parts, there were questions about two clinical scenarios, the patients ’ knowledge ofattitudes toward AI, and how the AI-based diagnosis had affected their trust. Evaluation was performedusing a Likert-type scale. Data were analy zed with the Chi-square, one-way ANOVA, and ordinal logisticregression tests (p <0.05). The patients believed that ‘AI is useful’ (3.86 ± 1.03) and were not afraidof the use of AI in dentistry (2.40 ± 1.05). Educatio nal level was considerably related to the patients’attitudes to the use of AI f or dental diagnostics (p <0.05). The patients stated that ‘dentists are extremelythorough and careful’ (4.39 ± 0.77). The patients displa yed a positive attitude to AI-based diagnosis inthe dental field and appear to exhibit trust in dentists.”
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    New Kidney Disease Study Findings Have Been Reported by Researchersat SRM Unive rsity (Enhancing Machine Learning-basedForecasting of Chronic Renal Disease Wit h Ai)

    45-45页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Research findings on Kidney Diseases a nd Conditions - Kidney Disease are discussedin a new report. According to news reporting out of Andhra Pradesh, India, by NewsRx editors, researchstated, “Chr onic renal disease (CRD) is a significant concern in the field of healthcare, hi ghlighting thecrucial need of early and accurate prediction in order to provide prompt treatments and enhance patientoutcomes. This article presents an end-to - end predictive model for the binary classification of CRD inhealthcare, addre ssing the crucial need for early and accurate predictions to enhance patient out comes.”Our news journalists obtained a quote from the research from SRM University, “Th rough hyperparameteroptimization using GridSearchCV, we significantly improve m odel performance. Leveraging a rangeof machine learning (ML) techniques, our ap proach achieves a high predictive accuracy of 99.07% forrandom fo rest, extra trees classifier, logistic regression with L2 penalty, and artificia l neural networks(ANN). Through rigorous evaluation, the logistic regression wi th L2 penalty emerges as the top performer,demonstrating consistent performance . Moreover, integration of Explainable Artificial Intelligence(XAI) techniques, such as Local Interpretable Model- agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP), enhances interpretability and reveals insights into m odel decision-making. Byemphasizing an end-to-end model development process, fr om data collection to deployment, our systemenables real-time predictions and i nformed healthcare decisions.”
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    University of Science and Technology Beijing Reports Findingsin Machine Learnin g (First-Principles Calculations and MachineLearning of Hydrogen Evolution Reac tion Activity of NonmetallicDoped b-Mo2C Support Pt Single-Atom Catalysts)

    46-46页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsoriginating from Beijing, People’s Repu blic of China, by NewsRx correspondents, research stated, “Themost widely used catalyst for the hydrogen evolution reaction (HER) is Pt, but the high cost and lowabundance of Pt need to be urgently addressed. Single-atom catalysts (SACs) have been an effectivemeans of improving the utilization of Pt atoms.”Our news journalists obtained a quote from the research from the University of S cience and TechnologyBeijing, “In this work, we used a nonmetal (NM = B, N, O, F, Si, P, S, Cl, As, Se, Br, Te, and I) dopedb-MoC (100) C-termination surface as the support, with Pt atoms dispersed on the support surface toconstruct Pt@N M-MoC. Using density functional theory (DFT) calculations, we selected catalysts withexcellent HER activity. Among 117 candidate catalysts, 49 catalysts exhibi ted ideal catalytic performancewith Gibbs free energy of hydrogen intermediate (H*) adsorption (D) values less than 0.2 eV. The D valuesof 16 catalysts were e ven lower than that of Pt (D 0.09 eV), with Pt@N-MoC demonstrating the best performance (D = -0.01 eV). Combined with electronic structure analysis, we could un derstand the impactof charge transfer between Pt and the underlying NM atoms on the strength of the Pt-H bond, therebypromoting HER activity.”
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    Icahn School of Medicine at Mount Sinai Reports Findings inCOVID-19 (An assessm ent of PET and CMR radiomic featuresfor the detection of cardiac sarcoidosis)

    47-78页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Coronavirus - COVID-19 is the subject of a report. According to newsreporting out of New York City, N ew York, by NewsRx editors, research stated, “Visual interpretationof PET and C MR may fail to identify cardiac sarcoidosis (CS) with high specificity. This stu dy aimedto evaluate the role of [F]FDG PE T and late gadolinium enhancement (LGE)-CMR radiomic features indifferentiating CS from another cause of myocardial inflammation, in this case patients with ca rdiac-relatedclinical symptoms following COVID-19.”Our news journalists obtained a quote from the research from the Icahn School of Medicine at MountSinai, “[F]FDG PET and LGE-CMR were treated separately in this work. There were 35 post-COVID-19(PC) a nd 40 CS datasets. Regions of interest were delineated manually around the entir e left ventricle forthe PET and LGE-CMR datasets. Radiomic features were then e xtracted. The ability of individual featuresto correctly identify image data as CS or PC was tested to predict the clinical classification of CS vs. PCusing M ann-Whitney -tests and logistic regression. Features were retained if the -value was <0.00053, theAUC was >0.5, an d the accuracy was >0.7. After applying the correlation test, uncorrelated features wereused as a signature (joint features) to train m achine learning classifiers. For LGE-CMR analysis, to furtherimprove the result s, different classifiers were used for individual features besides logistic regr ession, and theresults of individual features of each classifier were screened to create a signature that included all featuresthat followed the previously me ntioned criteria and used it them as input for machine learning classifiers.The Mann-Whitney -tests and logistic regression were trained on individual features to build a collectionof features. For [F] FDG PET analysis, the maximum target-to-background ratio ( ) showed a high areaunder the curve (AUC) and accuracy with small -values (<0.0 0053), but the signature performed better(AUC 0.98 and accuracy 0.91). For LGE- CMR analysis, the showed good results with small error bars(accuracy 0.75 and A UC 0.87). However, by applying a Support Vector Machine classifier to individualLGE-CMR features and creating a signature, a Random Forest classifier displayed better AUC and accuracy(0.91 and 0.84, respectively). Using radiomic features may prove useful in identifying individuals with CS.Some features showed promis ing results in differentiating between PC and CS.”
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    Study Findings from Florida International University Update Knowledgein Machine Learning (Precision Calibration in Wire-Arc-Directed Energy Deposition Simulati ons Using a Machine-Learning-Based Multi-Fidelity Model)

    48-49页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Investigators discuss new findings in artificial intelligence. According to news reportingoriginating from Miami, Flo rida, by NewsRx correspondents, research stated, “Thermal simulation isessentia l in wire-arc-directed energy deposition (W-DED) to accurately estimate temperat ure distributions,impacting residual stress and distortion in components.”Funders for this research include Devcom-army Research Laboratory.Our news journalists obtained a quote from the research from Florida Internation al University: “Propercalibration of simulation models minimizes inaccuracies c aused by varying material properties, machinesettings, and environmental condit ions. The lack of standardized calibration methods further complicatesthermal p redictions. This paper introduces a novel calibration method integrating both ma chine learning,as the high-fidelity (HF) model, and response surface modeling, as the low-fidelity (LF) model, withina multi-fidelity (MF) framework. The appr oach utilizes Bayesian optimization to effectively explore thesearch space for optimal solutions. A two-tiered model employs the LF model to identify feasible regions,followed by the HF model to refine calibration parameters, such as ther mal efficiency (e), convectioncoefficient (h), and emissivity (e), which are di fficult to determine experimentally. A three-factor Box-Behnken design (BBD) is applied to explore the design space, requiring only thirteen parameter configurations, conserving resources and enabling robust model training.”
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    Study Findings on Machine Learning Are Outlined in Reports fromFederal Universi ty Rio Grande do Sul (Enhancing AutoencoderbasedMachine Learning Through the U se of Process Control Gainand Relative Gain Arrays As Cost Functions)

    49-49页
    查看更多>>摘要：By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Current study results on Machine Learn ing have been published. According to newsreporting from Porto Alegre, Brazil, by NewsRx journalists, research stated, “Autoencoders are neuralnetworks utiliz ed for unsupervised learning and reconstructing input data, making them helpful in foranalyzing industrial process data. To enhance their effectiveness, we int roduce two cost functions basedon the Gain Matrix and Relative Gain Array (RGA) concepts, referred to in this paper as Gain Autoencoder(GAE) and Relative Gain Autoencoder (RGAE).”Financial support for this research came from Coordenacao de Aperfeicoamento de Pessoal de NivelSuperior (CAPES).The news correspondents obtained a quote from the research from Federal Universi ty Rio Grandedo Sul, “These cost functions aid in reducing dimensionality and i mproving the model’s performance inindustrial settings. This article delves int o applying of these functions in machine learning, particularly inautoencoders, to predict Mooney viscosity in styrene butadiene rubber (SBR) production. The f indingsindicate that the proposed GAE and RGAE models outperform traditional li near (linear regression) andnonlinear models (SVR), as evidenced by an increase d explained variance of up to 10% and a decrease inmean square er ror of up to 13%.”
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