A Gradient Boosting Crash Prediction Approach for Highway-Rail Grade Crossing Crash Analysis by Pan Lu, Zijian Zheng, Yihao Ren, Xiaoyi Zhou, Amin Keramati, Denver Tolliver, Ying Huang

“…Moreover, contributors’ importance and partial-dependent relations are generated to further understand the relationship of identified contributors and HRGC crash likelihood to concur “black box” issues that most machine learning methods face. Furthermore, to fully demonstrate the model’s prediction performance, a comprehensive model prediction power assessment based on six measurements is conducted, and the prediction performance of the GB model is verified and compared with a decision tree model as a reference due to their popularity and comparable data availability. …”
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Unleashing the potential of chatbots in mental health: bibliometric analysis by Qing Han, Chenyang Zhao

“…The keyword co-occurrence network highlights the prominent techniques in this multidisciplinary area and reveals 5 research topics, showing a significant overlap between clusters. High-frequency terms such as “ChatGPT”, “machine learning”, and “large language models” underscore the current state of research, highlighting the cutting-edge advancements and frontiers in this field.ConclusionsThis study provides an in-depth analysis of the most prominent countries, institutions, publications, collaboration status, and research topics associated with utilization of chatbots in mental health over the last decade. …”
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Mechanical Behaviors of Electrostatic Microbeams with Nonideal Supports by Yunxia Chang, Qichang Zhang, Wei Wang, Jianxin Han

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Two-dimensional cooling without repump laser beams through ion motional heating by Yue Xiao, Yongxu Peng, Linfeng Chen, Chunhui Li, Zongao Song, Xin Wang, Tao Wang, Yurun Xie, Bin Zhao, Tiangang Yang

“…This work provides a robust method to control micromotion velocity of ions and demonstrates the potential of micromotion-assisted laser cooling to simplify setups for systems requiring multiple repumping frequencies.…”
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AI-based tool wear prediction with feature selection from sound signal analysis by Viet Q. Vu, Tien-Ninh Bui, Minh-Quang Tran

“…In automated production systems, the condition of tools greatly influences production efficiency, cutting stability, and the quality of machined surfaces. The present study proposes an effective tool condition monitoring system based on cutting sound signature analysis and a machine learning model for milling processes. …”
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Robust and Adaptive Tuning of PI Current Controllers for Grid-Forming Inverters by Florian Reisner, George Weiss

“…To enable automatic tuning online, we employ a method for measuring the grid impedance by injecting a small probing current into the grid, at a frequency that is close but different from the grid frequency.…”
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Artificial Intelligence Models for Pediatric Lung Sound Analysis: Systematic Review and Meta-Analysis by Ji Soo Park, Sa-Yoon Park, Jae Won Moon, Kwangsoo Kim, Dong In Suh

“…The most frequently used feature extraction methods were Mel-spectrogram, Mel-frequency cepstral coefficients, and short-time Fourier transform. …”
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Impedance-Based Stability Analysis of a Low-Inertia AC Grid Connected to a DC Grid by a VSC With Virtual Inertia Controllers by Ahmed M.E.I. Mohamad, Hassanien Ramadan A. Mohamed, Yasser Abdel-Rady I. Mohamed

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Energy and Spectral Efficiency Analysis for UAV-to-UAV Communication in Dynamic Networks for Smart Cities by Mfonobong Uko, Sunday Ekpo, Ubong Ukommi, Unwana Iwok, Stephen Alabi

“…Similarly, sub-6 GHz spectral efficiency can attain <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>4</mn><mo>×</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>12</mn></mrow></msup><mspace width="0.166667em"></mspace><mrow><mi>bps</mi><mo>/</mo><mi>Hz</mi></mrow></mrow></semantics></math></inline-formula> in near-line-of-sight scenarios, whereas 60 GHz lines encounter significant attenuation at distances above 200–300 m without sophisticated beamforming techniques. Polynomial-fitting methods indicate that the projected <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mi>η</mi><mi>e</mi></msub></semantics></math></inline-formula> diverges from actual performance by less than 5% after 10 s of flight, highlighting the feasibility of machine-learning-based techniques for real-time power regulation, beam steering, or multi-band switching. …”
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Spatiospectral dynamics of electroencephalography patterns during propofol-induced alterations of consciousness states by Xuan Li, Dezhao Liu, Zheng Li, Rui Wang, Xiaoli Li, Tianyi Zhou

“…Our methods yielded six dynamical patterns that continuously reflect the neural activity changes in specific brain regions and frequency bands under propofol sedation. …”
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Bidirectional Long Short-Term Memory–Based Detection of Adverse Drug Reaction Posts Using Korean Social Networking Services Data: Deep Learning Approaches by Chung-Chun Lee, Seunghee Lee, Mi-Hwa Song, Jong-Yeup Kim, Suehyun Lee

“…Based on this information, we aimed to develop a deep learning model that classifies drug ADR posts based on a recurrent neural network. MethodsIn previous studies, ketoprofen, which has a high prescription frequency and, thus, was referred to the most in posts secured from SNS data, was selected as the target drug. …”
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Heuristic modeling of the process of milling aviation parts with opposed end mills by synthesis of a predictive model by E. A. Shestakova, V. O. Ievlev, R. M. Yanbaev

“…The resulting model allows predicting the results of machining by the proposed method with an error of 10…15%.…”
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Processing ambient noise using wavelet analysis tools: the Iraqi Seismological broadband Network Data at Iraqi Meteorological Organization and seismology (IMOS) by Hasanain Jasim Mohammed, Ali M. Al-Rahim

“…The outcomes seem that ways compared with other denoising methods, using the Continuous Wavelet Transform has many natural translation-invariant and time-frequency properties and improve considerably the results compared to those using traditional filters. …”
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Investigation of factors affecting the sound absorption behaviour of 3D printed hexagonal prism lattice polyamide structures by Martin Vašina, Jakub Měsíček, Martin Mánek, Quoc-Phu Ma, Jiří Hajnyš, Jana Petrů

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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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