Macro and mesoscopic mechanical behavior of concrete with actual aggregate segmented by hybrid Transformers and convolutional neural networks by Dong Wang, Junxing Zheng, Jichen Zhong, Lin Gao, Shuling Huang, Jiajia Zheng

“…Comparative analyses are performed utilizing models with circular aggregates and randomly distributed irregular aggregates, providing further insights into the influence of actual aggregate morphology and distribution on concrete mechanical behavior. …”
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Development of a Hyperspectral Imaging Protocol for Painting Applications at the University of Seville by Giovanna Vasco, Hélène Aureli, Isabel Fernández-Lizaranzu, Javier Moreno-Soto, Anabelle Križnar, Rubén Parrilla-Giraldez, Emilio Gómez-González, Miguel Angel Respaldiza Galisteo

“…In the last decade, the hyperspectral imaging (HSI) method allowed performing non-invasive analysis in the field of cultural heritage. …”
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Applications of tunable-Q factor wavelet transform and AdaBoost classier for identification of high impedance faults: Towards the reliability of electrical distribution systems by S. Ramana Kumar Joga, Pampa Sinha, Vasupalli Manoj, Srinivasa Rao Sura, Vasudeva Naidu Pudi, Nagwa F. Ibrahim, Abdulaziz Alkuhayli, Mahmoud M. Hussein, Usama Khaled, Daniel Eutyche Mbadjoun Wapet, Abderrahmane Beroual, Mohamed Metwally Mahmoud

“…Traditional overcurrent protection relays frequently have lower fault current levels than normal current, making it exceedingly difficult to detect this HIF problem with the necessity to use a quick and effective approach to find HIF problems. Since the TQWT performs better with signals that exhibit oscillatory behavior, it has been utilized to extract special features for the training of the improved AdaBoost model. …”
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Trajectories of medical students’ empathy nowadays: a longitudinal study using a comprehensive framework of empathy by Valerie Carrard, Céline Bourquin, Sylvie Berney, Setareh Ranjbar, Katja Schlegel, Jacques Gaume, Pierre-Alexandre Bart, Marianne Schmid Mast, Martin Preisig, Alexandre Berney

“…Cognitive, affective, and behavioral empathy were measured with three validated instruments, and emotion recognition was assessed with a performance test. For each measure, linear mixed models including an array of psychosocial and health-related potential covariates were modelled. …”
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Contribution of Scalp Regions to Machine Learning-Based Classification of Dementia Utilizing Resting-State qEEG Signals by Simfukwe C, An SSA, Youn YC

“…The EO rEEG achieved the highest performance metrics across various models. For HC vs MCI (combined hemisphere), the accuracy, sensitivity, specificity, and AUC were 92%, 99%, 83%, and 96%, respectively. …”
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Self-Isolation in MIMO Array Using Mode Diversity by Manzoor Elahi, Slawomir Koziel, Leifur Leifsson

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Predicting real-time traffic restoration time based on the estimated traffic state by Md Rakibul Islam, Zaheen E Muktadi Syed, Mohamed Abdel-Aty, Samiul Hasan

“…Traffic, crash, weather, and emergency facility data from 2017 to 2019 were collected recording 24,448 events (4,939 crashes and 19,509 non-crash events) and 65 real-time features. A total of eight traffic state prediction models with high accuracy were developed using the XGBoost machine learning technique. …”
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Natural training tools of informatics in conditions of embodied and mental approach realization by Daria A. Barkhatova, Elmira A. Nigmatulina, Tatyana A. Stepanova

“…The instrument of realization of this idea is offered to use natural tools in informatics, what is actualized by age features of cognitive abilities of students and individual requirements to ways of perception and mastering of the material, matched according to the level of their knowledge.The research results describe the models of natural tools, developed by students and lecturers of the basic Department of Informatics and Information Technologies in Education of Krasnoyarsk State Pedagogical University named after V. …”
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Translating high-precision mixed reality navigation from lab to operating room: design and clinical evaluation by Zhongjie Shi, Yilong Peng, Xin Gao, Sifang Chen, Gang Chen, Gaojian Pan, Zhirong Liang, Zhanxiang Wang

“…Results In laboratory evaluations, the MRN system demonstrated consistent and reliable performance. The fiducial registration error (FRE), which reflects the alignment accuracy between corresponding anatomical fiducial points on the physical and virtual models, ranged from 1.70 to 2.20 mm. …”
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Predictive analysis of total organic carbon (TOC) in shale targets: example from the Lower Cretaceous of the Austral Basin (Patagonia, Argentina) using machine learning on outcrop... by Sebastian M. Richiano, Federico Ares

“…Dimensionality reduction improved model performance, with SVC achieving the most robust results. …”
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Removal of LiDAR Negative Outliers Based on Retroreflective Surface by Haolong Gao, Shaobo Li, Zhouyi Kang, Fan Zhang, Yi Zhang, Yunlong Wu

“…Third, a terrain mesh model is constructed to approximate the retroreflective surface, enabling a feature-based comparison between negative outliers and their preliminary reflection points. …”
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Long-term tracking of neural and oligodendroglial development in large-scale human cerebral organoids by noninvasive volumetric imaging by Sangjun Park, Cheol Hong Min, Eunjin Choi, Jeong-Sun Choi, Kyungjin Park, Seokyoung Han, Wonjun Choi, Hyun-Jong Jang, Kyung-Ok Cho, Moonseok Kim

“…The integration of deconvolution and compressive sensing has improved image contrast by 6-fold, elucidating fine features of the neurites. Thus, noninvasive imaging enabled us to perform long-term tracking of neural and oligodendroglial development in the large-scale human cerebral organoid. …”
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Profiling of Metabolome in the Plasma Following a circH19 Knockdown Intervention in Diet-Induced Obese Mice by Hanxin Zhao, Dike Shi, Weiwei Gui, Xihua Lin, Jionghuang Chen, Weihua Yu

“…Metabolic profiling was performed to identify and quantify metabolites, followed by multivariate statistical analysis to discern differential metabolic signatures. …”
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Rapid Mapping: Unmanned Aerial Vehicles and Mobile-Based Remote Sensing for Flash Flood Consequence Monitoring (A Case Study of Tsarevo Municipality, South Bulgarian Black Sea Coas... by Stelian Dimitrov, Bilyana Borisova, Ivo Ihtimanski, Kalina Radeva, Martin Iliev, Lidiya Semerdzhieva, Stefan Petrov

“…Flood simulation using UAV data and a digital elevation model was performed. The appropriateness of contemporary land use forms and infrastructure location in catchments is discussed. …”
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Prediction of tuberculosis treatment outcomes using biochemical makers with machine learning by Zheyue Wang, Zhenpeng Guo, Weijia Wang, Qiang Zhang, Suya Song, Yuan Xue, Zhixin Zhang, Jianming Wang

“…SHapley Additive exPlanations (SHAP) were applied to evaluate feature importance in top-performing models. Results Analysis of 1,086 TB cases showed that a K-Nearest Neighbor classifier with Mutual Information feature selection achieved an area under the receiver operation curve (AUC) of 0.87 (95% CI: 0.83–0.92). …”
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Imaging the Solar Corona from “Within”: A Cutting-edge Approach to Enhance PSP/WISPR Imagery by Guillermo Stenborg, Angelos Vourlidas, Russell A. Howard

“…In this paper, we introduce a new, heuristic approach to model the evolution of the F-corona background as a function of the observer’s location. …”
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Coastal Eddy Detection in the Balearic Sea: SWOT Capabilities by Laura Fortunato, Laura Gómez-Navarro, Vincent Combes, Yuri Cotroneo, Giuseppe Aulicino, Ananda Pascual

“…Furthermore, Lagrangian transport simulations reveal how altimetric resolution influences modeled transport pathways and retention patterns. …”
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A statistical and machine learning approach for monthly precipitation forecasting in an Amazon city by Ewerton Cristhian Lima de Oliveira, Eduardo Costa de Carvalho, Edmir dos Santos Jesus, Rafael de Lima Rocha, Rafael de Lima Rocha, Helder Moreira Arruda, Ronnie Cley de Oliveira Alves, Ronnie Cley de Oliveira Alves, Renata Gonçalves Tedeschi

“…Additionally, we use meteorological data from a set of sensors installed at a meteorological station located in Belém to train multivariate statistical and machine learning (ML) models to predict precipitation. Besides the use of algorithms, another evaluation was conducted on Feature Composition based on statistical methods to investigate the impact of variables on the prediction.ResultsThe results obtained in our investigation indicate that the vector autoregressive moving average with exogenous regressors (VARMAX) model achieved the best performance in rainfall forecasting, with an average root mean square error (RMSE) of 9.1833 in time series cross-validation, outperforming the other models.DiscussionThe climate-driven patterns directly influenced the performance of the rainfall forecasting models evaluated in this study. …”
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NeXtMD: a new generation of machine learning and deep learning stacked hybrid framework for accurate identification of anti-inflammatory peptides by Chengzhi Xie, Yijie Wei, Xinwei Luo, Huan Yang, Hongyan Lai, Fuying Dao, Juan Feng, Hao Lv

“…While various machine learning and deep learning approaches have been explored, their limitations in feature representation and model integration hinder the effective discovery of novel AIPs. …”
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Effective Estimation of Hourly Global Solar Radiation Using Machine Learning Algorithms by Abdurrahman Burak Guher, Sakir Tasdemir, Bulent Yaniktepe

“…The performance of the estimation models was evaluated by comparing each model with different statistical indicators and with previous studies. …”
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