Implementation of a Digital Model of Thermal Characteristics Based on the Temperature Field by V. V. Pozevalkin, A. N. Polyakov

“…The implementation of digital twin technology in the process of designing technical facilities is the current direction of scientific research and development. …”
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Analysis of the most influential factors affecting outcomes of lung transplant recipients: a multivariate prediction model based on UNOS Data by Reza Safdari, Marsa Gholamzadeh, Hamidreza Abtahi, Mehrnaz Asadi Gharabaghi

“…Our primary objective was to identify the key factors that influence the allocation of priorities in LTx using machine learning (ML) techniques to enhance the process of prioritising patients.Design Developing a prediction model.Setting and participants Our data were retrieved from the United Network for Organ Sharing (UNOS) open-source database of transplant patients between 2005 and 2023.Interventions After the preprocessing process, a feature engineering technique was employed to select the most relevant features. …”
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Enhancing Healthcare With WBAN and Digital Twins: A Machine Learning Approach for Predictive Health Monitoring by Rishit Mahapatra, Deepak Sethi, Kaushik Mishra

“…The collected data undergoes processing and is then sent to a remote medical server over the Internet. …”
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Computational Intelligence-Based Structural Health Monitoring of Corroded and Eccentrically Loaded Reinforced Concrete Columns by Somain Sharma, Harish Chandra Arora, Aman Kumar, Denise-Penelope N. Kontoni, Nishant Raj Kapoor, Krishna Kumar, Arshdeep Singh

“…In this article, an ML-based artificial neural network (ANN), Gaussian process regression (GPR), and support vector machine (SVM) algorithms have been applied to estimate the residual strength of corroded and eccentrically loaded RC columns. …”
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SCM-DL: Split-Combine-Merge Deep Learning Model Integrated With Feature Selection in Sports for Talent Identification by Didem Abidin, Muhammed G. Erdem

“…In the literature, this process is called Talent Identification (TID) and is defined as “to know the players participating in the sport with the potential to be perfect.…”
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Highly efficient stacking ensemble learning model for automated keratoconus screening by Zahra J. Muhsin, Rami Qahwaji, Ibrahim Ghafir, Mo’ath AlShawabkeh, Muawyah Al Bdour, Saif Aldeen AlRyalat, Majid Al-Taee

“…A novel stacking ensemble model is developed using the selected features to improve corneal classification into NKC, SCKC, and CKC by integrating top tree-based classifiers (random forest, gradient boosting, decision trees) with a support vector machine meta-classifier. Results The pre-processing and feature selection techniques reduced the model's parameters to just 6.33% of the original dataset, improving classification performance, and cutting over 85% of the training time. …”
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Fine-Grained Feature Extraction in Key Sentence Selection for Explainable Sentiment Classification Using BERT and CNN by Thennakoon Mudiyanselage Anupama Udayangani Gunathilaka, Jinglan Zhang, Yuefeng Li

“…These models rely on sequential processing of text rather than parallel processing, which can lead to missed important fine-grained features and long-range dependencies spread across sentences. …”
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Cryptocurrency forensics automation: a deep learning and NLP-based approach for mobile platforms by Abhishek Bhattarai, Abdulhadi Sahin, Maryna Veksler, Ahmet Kurt, Devrim Aras, Carlos Imery, Kemal Akkaya

“…Therefore, in this paper, we present a comprehensive framework that incorporates various machine learning (ML), image processing, and natural language processing (NLP) approaches to enable fast and automated extraction/triage of crypto-related artifacts from Android and iOS devices. …”
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Quantum-enhanced beetle swarm optimized ELM for high-dimensional smart grid intrusion detection by Na Cheng, Shuqing Wang, Lihong Zhao, Yan Hu

“…With regard to the efficiency of training, QBOA-ELM demonstrates a substantial advantage, processing large-scale datasets in a training time of 120 s, which is considerably less than the 180 s required by BOA-ELM and the 300 s required by SVM. …”
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Neurophysiological Approaches to Lie Detection: A Systematic Review by Bewar Neamat Taha, Muhammet Baykara, Talha Burak Alakuş

“…Among classification algorithms, Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Convolutional Neural Networks (CNN) were frequently utilized. …”
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Hyperactive Repeating Fast Radio Bursts from Rotation-modulated Starquakes on Magnetars by Jia-Wei Luo, Jia-Rui Niu, Wei-Yang Wang, Yong-Kun Zhang, De-Jiang Zhou, Heng Xu, Pei Wang, Chen-Hui Niu, Zhen-Hui Zhang, Shuai Zhang, Ce Cai, Jin-Lin Han, Di Li, Ke-Jia Lee, Wei-Wei Zhu, Bing Zhang

“…Moreover, a bimodal distribution of the burst waiting times is widely observed in hyperactive FRBs, a significant deviation from the exponential distribution expected from stationary Poisson processes. By combining the epidemic-type aftershock sequence earthquake model and the rotating vector model involving the rotation of the magnetar and orientations of the spin and magnetic axes, we find that starquake events modulated by the rotation of FRB-emitting magnetar can explain the bimodal distribution of FRB waiting times, as well as the nondetection of periodicity in hyperactive repeating FRBs. …”
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Exploring the predictive value of structural covariance networks for the diagnosis of schizophrenia by Clara S. Vetter, Clara S. Vetter, Clara S. Vetter, Annika Bender, Dominic B. Dwyer, Dominic B. Dwyer, Dominic B. Dwyer, Max Montembeault, Anne Ruef, Katharine Chisholm, Lana Kambeitz-Ilankovic, Linda A. Antonucci, Stephan Ruhrmann, Joseph Kambeitz, Marlene Rosen, Theresa Lichtenstein, Anita Riecher-Rössler, Rachel Upthegrove, Raimo K. R. Salokangas, Jarmo Hietala, Christos Pantelis, Christos Pantelis, Rebekka Lencer, Rebekka Lencer, Eva Meisenzahl, Stephen J. Wood, Stephen J. Wood, Paolo Brambilla, Paolo Brambilla, Stefan Borgwardt, Peter Falkai, Peter Falkai, Alessandro Bertolino, Nikolaos Koutsouleris, Nikolaos Koutsouleris, Nikolaos Koutsouleris, PRONIA Consortium

“…Structural covariance networks (SCN) describe the shared variation in morphological properties emerging from coordinated neurodevelopmental processes, This study evaluates the potential of SCNs as diagnostic biomarker for schizophrenia.MethodsWe compared the diagnostic value of two SCN computation methods derived from regional gray matter volume (GMV) in 154 patients with a diagnosis of first episode psychosis or recurrent schizophrenia (PAT) and 366 healthy control individuals (HC). …”
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Emotion Recognition in a Closed-Cabin Environment: An Exploratory Study Using Millimeter-Wave Radar and Respiration Signals by Hanyu Wang, Dengkai Chen, Sen Gu, Yao Zhou, Jianghao Xiao, Yiwei Sun, Jianhua Sun, Yuexin Huang, Xian Zhang, Hao Fan

“…An automatic sparse encoder was used to extract features from respiration signals, and two support vector machines were employed for emotion classification. …”
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Machine learning analysis of gene expression profiles of pyroptosis-related differentially expressed genes in ischemic stroke revealed potential targets for drug repurposing by Changchun Hei, Xiaowen Li, Ruochen Wang, Jiahui Peng, Ping Liu, Xialan Dong, P. Andy Li, Weifan Zheng, Jianguo Niu, Xiao Yang

“…The primary objective was to develop classification models to identify crucial PRDEGs integral to the ischemic stroke process. Leveraging three distinct machine learning algorithms (LASSO, Random Forest, and Support Vector Machine), models were developed to differentiate between the Control and the IS patient samples. …”
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Investigating the relationship between the monetary policy shock through the exchange rate channel on the management quality index in the banking system: by examining the productiv... by Farhad Sharifi Bagha, Jafar Haqiqat, Zahra Karimi Takanloo

“…Therefore, first, the following equation was estimated without considering the Yt vector, based on which the number of optimal factors was selected. …”
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Same data, different results? Machine learning approaches in bioacoustics by Kaja Wierucka, Derek Murphy, Stuart K. Watson, Nikola Falk, Claudia Fichtel, Julian León, Stephan T. Leu, Peter M. Kappeler, Elodie F. Briefer, Marta B. Manser, Nikhil Phaniraj, Marina Scheumann, Judith M. Burkart

“…We offer guidelines for processing and analysing mammalian vocalisations, fostering greater comparability and advancing our understanding of the evolutionary significance of acoustic communication in diverse mammalian species.…”
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Dataset of observables for small modular lead-cooled fast reactor MOX spent nuclear fuelMendeley Data by Victor J. Casas-Molina, Pablo Romojaro, Gwennaelle Nourry, Gert Van den Eynde, Luca Fiorito, Ivan Merino-Rodríguez, Tom Dhaene, Ivo Couckuyt

“…This data article introduces a comprehensive dataset of isotopic mass densities, spanning 152 nuclides present in irradiated LFR-MOX fuel, additionally providing insights into fuel characteristics such as activity, decay heat rates, photon emission rates, spontaneous fission rates, and radiotoxicity values across various decay steps.Using the Serpent2 Monte Carlo code for fuel depletion calculations, and processed with SerpentTools, the dataset captures inventory data as a function of reactor power, fuel burnup, plutonium vector in the fresh MOX, and decay time at the end of irradiation, enabling analyses of SNF properties. …”
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A novel fault location method for multi-terminal transmission lines based on composite analysis of time-frequency fault traveling waves by Jupeng Zeng, Xiangjun Zeng, Hao Bai, Kun Yu, Min Xu, Xiaolong She, Feng Liu

“…According to the characteristic that the FTW natural frequency (NF) is inversely proportional to the transmission distance, the fault branch determination vector is defined, and the corresponding principle is proposed to determine the fault branch. …”
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Stomatal State Identification and Classification in Quinoa Microscopic Imprints through Deep Learning by Abdul Razzaq, Sharaiz Shahid, Muhammad Akram, Muhammad Ashraf, Shahid Iqbal, Aamir Hussain, M. Azam Zia, Sulman Qadri, Najia Saher, Faisal Shahzad, Ali Nawaz Shah, Aziz-ur Rehman, Sven-Erik Jacobsen

“…Stomata are the main medium of plants for the trade of water, regulate the gas exchange, and are responsible for the process of photosynthesis and transpiration. The stomata are surrounded by guard cells, which help to control the rate of transpiration by opening and closing the stomata. …”
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Unusual topological polar texture in moiré ferroelectrics by Yuhao Li, Yuanhao Wei, Ruiping Guo, Yifei Wang, Hanhao Zhang, Takashi Taniguchi, Kenji Watanabe, Yan Shi, Yi Shi, Chong Wang, Zaiyao Fei

“…However, experimental observation of these polar textures within twisted two-dimensional van der Waals materials remains elusive. Here, we utilize vector piezoresponse force microscopy to reconstruct the polarization fields in R-type marginally twisted hexagonal boron nitride. …”
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