Improvement of electrospark deposition technology of steel units for drilling rigs and mining equipment by D. N. Korotaev, E. V. Ivanova

“…Tribological tests were carried out on a 2070-СМТ-1 standard friction machine according to the “disk-shoe” scheme.Results. …”
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Neural signatures of STEM learning and interest in youth by Milton O. Candela-Leal, Myriam Alanis-Espinosa, Jorge Murrieta-González, Jorge de-J. Lozoya-Santos, Mauricio A. Ramírez-Moreno

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Multiparametric MRI for the improved diagnostic accuracy of Alzheimer's disease and mild cognitive impairment: Research protocol of a case-control study design. by Albert Dayor Piersson, Buhari Ibrahim, Subapriya Suppiah, Mazlyfarina Mohamad, Hasyma Abu Hassan, Nur Farhayu Omar, Mohd Izuan Ibrahim, Ahmad Nazlim Yusoff, Normala Ibrahim, M Iqbal Saripan, Rizah Mazzuin Razali

“…Accurate imaging can decide on the frequency of follow-up at memory clinics and select classifiers for machine learning that may aid in the disease identification and prognostication. …”
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COVID-19 Public Health Communication on X (Formerly Twitter): Cross-Sectional Study of Message Type, Sentiment, and Source by Sana Parveen, Agustin Garcia Pereira, Nathaly Garzon-Orjuela, Patricia McHugh, Aswathi Surendran, Heike Vornhagen, Akke Vellinga

“…A combination of manual content analysis with abductive coding and machine learning models were used to categorize sentiment, user category and message type for every tweet. …”
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Association Between COVID-19 During Pregnancy and Preterm Birth by Trimester of Infection: Retrospective Cohort Study Using Large-Scale Social Media Data by Ari Z Klein, Shriya Kunatharaju, Su Golder, Lisa D Levine, Jane C Figueiredo, Graciela Gonzalez-Hernandez

“…ObjectiveThe objective of this study was to use self-reports in large-scale social media data to assess the association between the trimester of COVID-19 infection and preterm birth. MethodsIn this retrospective cohort study, we used natural language processing and machine learning, followed by manual validation, to identify self-reports of pregnancy on Twitter and to search these users’ collection of publicly available tweets for self-reports of COVID-19 infection during pregnancy and, subsequently, a preterm birth or term birth outcome. …”
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Comprehensive Analysis of the Biomechanical Research of Pelvic Organ Prolapse: A Scientometric Approach by Du H, Yang M, Qi X, Yang L, Wang Z, Yang T, Xu S, Fu L

“…Notably, the journal Int Urogynecol J has the highest publication rate and citation frequency, making a significant contribution and demonstrating considerable academic influence in the field. …”
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Postimplementation Evaluation in Assisted Living Facilities of an eHealth Medical Device Developed to Predict and Avoid Unplanned Hospitalizations: Pragmatic Trial by Jacques-Henri Veyron, François Deparis, Marie Noel Al Zayat, Joël Belmin, Charlotte Havreng-Théry

“…Due to their vulnerability, there is a higher frequency of unplanned hospitalizations in this population, leading to adverse events. …”
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GEM-CRAP: a fusion architecture for focal seizure detection by Jianwei Shi, Yuanyuan Zhang, Ziang Song, Hang Xu, Yanfeng Yang, Lei Jin, Hengxin Dong, Zhaoying Li, Penghu Wei, Yongzhi Shan, Guoguang Zhao

“…Abstract Background Identification of seizures is essential for the treatment of epilepsy. Current machine-learning and deep-learning models often perform well on public datasets when classifying generalized seizures with prominent features. …”
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Effect of Periodic Fluctuations of Cutting Mode Parameters on the Temperature of the Front Face of a Turning Tool by E. V. Fominov, V. E. Gvindjiliya, A. A. Marchenko, C. G. Shuchev

“…However, few works consider uncontrolled periodic disturbances, whose sources are spindle units and the supporting system of the machine. These disturbances also have a significant impact on the final quality indicators of the cutting process. …”
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Design and Development of Gorilla Optimized Deep Resilient Architecture for Prediction of Agro-Climatic Changes to Increase the Crop–Yield Production by Deepa Devarashetti, S. S. Aravinth

“…Climatic data and services are crucial for agriculturalists to withstand the rising frequency of strong meteorological conditions, which negatively impact crop yields. …”
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Enhanced SVM-based model for predicting cyberspace vulnerabilities: Analyzing the role of user group dynamics and capital influx. by Yicheng Long

“…To address the limited adaptability of traditional support vector machine (SVM) models in identifying nonlinear attacks, this study introduces a distribution-driven, dynamically adaptive kernel optimization approach. …”
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Evaluating landslide susceptibility: the impact of resolution and hybrid integration approaches by Xia Zhao, Wei Chen, Paraskevas Tsangaratos, Ioanna Ilia

“…The study reveals that finer spatial resolutions significantly enhance the accuracy of landslide predictions and that integrated models have superior performance over single models. The Frequency Ratio method identified elevation, slope, and hydrological factors as the key predictors concerning landslide occurrences. …”
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Design and Optimization of a Robust Wide‐Area Damping Controller for Mitigating Inter‐Area Oscillations in Wind‐Integrated Power Systems by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Sun‐Kyoung Kang, Ilhami Colak, El Manaa Barhoumi

“…ABSTRACT In power networks, low‐frequency oscillations—particularly inter‐area oscillations—pose a serious threat to system stability because of disruptions like short‐circuit faults and the increasing use of renewable energy sources like wind farms. …”
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Using Hybrid Feature and Classifier Fusion for an Asynchronous Brain–Computer Interface Framework Based on Steady-State Motion Visual Evoked Potentials by Bo Hu, Jun Xie, Huanqing Zhang, Junjie Liu, Hu Wang

“…This study proposes an asynchronous brain–computer interface (BCI) framework based on steady-state motion visual evoked potentials (SSMVEPs), designed to enhance the accuracy and robustness of control state recognition. The method integrates filter bank common spatial patterns (FBCSPs) and filter bank canonical correlation analysis (FBCCA) to extract complementary spatial and frequency domain features from EEG signals. …”
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Feasibility of Conoscopic Holography Measurement in the Stereolithography (SLA) Process with Alumina by Lorenzo Meana, Víctor Meana, Eduardo Cuesta, Pedro Fernández, Gonzalo Valiño, Braulio J. Álvarez

“…The investigation shows that conoscopic holography does not ensure an accurate measurement method for this additive process and ceramic material, making it impossible to achieve power and frequency settings that would allow signal-to-noise ratios above 50%.…”
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Heuristic Binary Search for Modulated Predictive Control by Rafael FIgueiredo, Igor Oliani, Angelo Lunardi, Alfeu J. Sguarezi Filho

“…This paper introduces the Heuristic Binary Search, an intelligent search algorithm that efficiently explores the solution space, accommodating arbitrary cost function constraints similar to Finite Control Set, while maintaining a fixed switching frequency. Applicable to various machine and inverter topologies, the proposed method is experimentally validated on a two-level voltage source inverter driving an induction motor using Predictive Torque Control and Deadbeat Robust Predictive Control. …”
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A discrete element simulation study of paver screed and hot mix asphalt interaction by Leandro Harries, Stefan Böhm, Jia Liu

“…This study addresses these challenges by employing a full-scale simulation using a calibrated Discrete Element Method (DEM) model to analyze HMA’s flow and pre-compaction behavior. …”
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A Dual Band Slotted Patch Antenna on Dielectric Material Substrate by M. Habib Ullah, M. T. Islam, M. R. Ahsan, J. S. Mandeep, N. Misran

“…A low profile, compact dual band slotted patch antenna has been designed using finite element method-based high frequency full-wave electromagnetic simulator. …”
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PROPER: Personality Recognition Based on Public Speaking Using Electroencephalography Recordings by Muhammad Majid, Amna Rauf Butt, Imran Fareed Nizami, Aamir Arsalan, Jihyoung Ryu

“…Five feature groups are extracted from the frequency bands of EEG data of each channel. Feature selection is applied to the extracted features via the wrapper method. …”
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Multi-modal denoised data-driven milling chatter detection using an optimized hybrid neural network architecture by Haining Gao, Haoyu Wang, Hongdan Shen, Shule Xing, Yong Yang, Yinlin Wang, Wenfu Liu, Lei Yu, Mazhar Ali, Imran Ali Khan

“…Multi-modal data features of different machining states are then obtained using time–frequency domain methods and Markov transition field methods. …”
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