Identification of natural inhibitors targeting trehalase of Anopheles funestus in the management of malaria: A Biocomputational assessment by Amer Al Ali, Abdulaziz Asiri, Mohammed H Abu-Alghayth, Maryam Musleh Althobiti, Bandar Ali Al Hader, Zain Alhindi

“…Methods: A collection of 1900 natural compounds from the ZINC database were screened against the 3D modeled structure of An. funestus trehalase protein using in silico tools. …”
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Soviet Socio-Cultural Practices from Perspective of Genres in <i>Pioneer</i> Magazine by T. V. Dubrovskaya

“…This paper focuses on its structure and contents, as well as typical genres that construct the representations of the Soviet society and socio-cultural practices. …”
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Real-time human gaze target estimation in 360-degree vision via integration of human gaze direction and scene saliency analysis by Jialin Tu, Yusuke Tamura, Yasuhisa Hirata

“…We have improved the network structure by leveraging the gaze heatmap as an interpretable network component, combined with the scene saliency heatmap, to estimate people’s gaze targets. …”
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From Postdramatic Heterogeneity to New Reflections on Noise: The House of Extreme Music Theater and the Schachtophonia Accenni for Kamov by Anamarija Žugić Borić

“…But precisely because of its apparently chaotic, noisy manifestation, it is easy to miss the structure and concept that is undoubtedly in the background of every performance. …”
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Assessing Measurement Invariance of Achievement Emotions Questionnaire for Teachers in Prospective Teacher Sample by Sevilay Kilmen

“…Although configural invariance suggests that the three-factor structure of the AEQT is the same across the teacher training programs, the lack of metric invariance indicates that the relationship between the items and the underlying latent variable the AEQT factors is not the same across these groups. …”
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Simple Fermionic backflow states via a systematically improvable tensor decomposition by Massimo Bortone, Yannic Rath, George H. Booth

“…By considering controllable truncations in the rank and range of the backflow correlations, as well as screening the local energy contributions for realistic Coulomb interactions, we obtain a scalable and interpretable approach to strongly correlated electronic structure problems that bridges tensor factorizations and machine learning-based representations.…”
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Component-Element Composition of National Economy Forecasting and Planning Methodology by Yu. I. Busheneva

“…The aim of the study is to determine the complex of key components and elements of the methodology based on the understanding of foresight and design of the future as creative and transformative activity and to test the element-byelement structure using the example of forecasting and planning in Russia. …”
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The psychometric properties of interpersonal support evaluation list-short form (ISEL-16) on College Students by Septian Wahyu Rahmanto

“…Theoretically, the adaptation reinforces the four-dimensional structure of social support previously established. …”
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An explainable AI-based framework for predicting and optimizing blast-induced ground vibrations in surface mining by Charan Kumar Ala, Zefree Lazarus Mayaluri, Aman Kaushik, Nikhat Parveen, Surabhi Saxena, Abu Taha Zamani, Debendra Muduli

“…Crucially, the framework incorporates Explainable AI (XAI) techniques such as Shapley Additive Explanations (SHAP) and Local Interpretable Model Agnostic Explanations (LIME) and uncertainty quantification (UQ) methods based on Bayesian Neural Networks to provide insight into model decisions and confidence in predictions. …”
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FROM PIXELS TO DIAGNOSIS: A DEEP LEARNING FRAMEWORK FOR HISTOPATHOLOGICAL IMAGE ANALYSIS IN CANINE TESTICULAR PATHOLOGY

“…This computational approach is based on a deep learning pipeline that integrates convolutional neural networks, multi-class histological segmentation, and spatial attention via Grad-CAM maps to acquire and interpret complex morphological structures in haematoxylin-eosin-stained slides.1 We created a histological whole-slide image dataset (N=400 slides) by collecting samples of healthy, pathological non-neoplastic and neoplastic testes from the archive of DIPSA laboratory of University of Naples Federico II. …”
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Cyclic Reformulation-Based System Identification for Periodically Time-Varying Systems by Hiroshi Okajima, Yusuke Fujimoto, Hiroshi Oku, Haruto Kondo

“…Specifically, subspace identification methods are applied to the cycled signals, allowing the extraction of Markov parameters, which form the basis for constructing the state-space model. Furthermore, the sparsity properties of the matrices derived from these Markov parameters are analyzed and utilized to design the coordinate transformation matrix, enhancing the representation and interpretability of the identified LPTV model. …”
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Temporal Fusion Transformer-Based Trading Strategy for Multi-Crypto Assets Using On-Chain and Technical Indicators by Ming Che Lee

“…By combining multi-source features—such as Spent Output Profit Ratio (SOPR), Total Value Locked (TVL), active addresses (AA), exchange net flow (ENF), Realized Cap HODL Waves, and the Crypto Fear and Greed Index—with classical signals like Relative Strength Index (RSI) and moving average convergence divergence (MACD), the model captures behavioral patterns, investor sentiment, and price dynamics in a unified structure. …”
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Nonparametric Bayesian Networks as a Tool of Multiscale Time Series Analysis and Remote Sensing Data Integration by Nikita S. Pyko, Denis V. Tishin, Pavel Yu. Iskandirov, Artur M. Gafurov, Bulat M. Usmanov, Mikhail I. Bogachev

“…Nonparametric Bayesian networks are a promising tool for analyzing, visualizing, interpreting and predicting the structural and dynamic characteristics of complex systems. …”
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Transmutation Methodology + Neural Networks: A Philological and Didactic Project by Golev Nikolay

“…By becoming authors, students assume an active speech position as they formulate the promt for the AI program, i.e., a description (model, structure) of the original text. The functional unity of the transmutation approach and AI programs demonstrate good prospects for linguistic didactics.…”
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Predicting cardiovascular risk with hybrid ensemble learning and explainable AI by Pooja Shah, Madhu Shukla, Neel H. Dholakia, Himanshu Gupta

“…Using a range of publicly accessible datasets, the suggested structure incorporates Gradient Boosting, CatBoost, and Neural Networks using a stacked ensemble architecture, resulting in more robust predictive performance than the constituent models. …”
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OPERATIONAL RESEARCH IN ACCESSIBILITY ASSESSMENT: A MULTI-CRITERIA EVALUATION FRAMEWORK FOR OLD COMMUNITY REFURBISHMENT ACCEPTANCE UNDER ENVIRONMENTAL CONSTRAINTS by Wu Wei, Md Azree Othuman Mydin, Farhana Mohd Razif

“…A structured questionnaire survey was conducted with local residents to gather insights on public space performance, particularly under emergency conditions. …”
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Influence of Multisensory Perceptions on Thermal Comfort in Heat Wave Weather with Different Heat Pressures by Chang Liu, Wei Wu, Jingyi Ouyang, Jinshan Yan, Lina Tang

“…In this study, we used the structural equation model technique to construct a multisensory modality model for interpreting the pathways and mechanisms by which visual, auditory, and olfactory perceptions (VAO perceptions) affect thermal comfort and help identify the key perceptual indicators that affect people’s thermal comfort under weather with different heat pressures. …”
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A UNet++-Based Approach for Delamination Imaging in CFRP Laminates Using Full Wavefield by Yitian Yan, Kang Yang, Yaxun Gou, Zhifeng Tang, Fuzai Lv, Zhoumo Zeng, Jian Li, Yang Liu

“…Full wavefields in CFRP encapsulate extensive information on the interaction between guided waves and structural damage, making them a widely utilized tool for damage mapping. …”
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A tied-weight autoencoder for the linear dimensionality reduction of sample data by Sunhee Kim, Sang-Ho Chu, Yong-Jin Park, Chang-Yong Lee

“…Our results show that the proposed model performs comparably to the nonlinear model of a similar autoencoder structure to the proposed model. …”
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Research on the relationship between key risk factors of university emergencies based on ISM-MICMAC. by Yufei Li, Xiaoyun Liu, Nanyan Hu, Xuexue Li

“…In order to accurately analyze the interaction among the risk factors of university emergencies, firstly, based on the key performance indicator (KPI) concept, by initially extracting risk factors, identifying initial risk factors, and correcting initial risk factors, and the risk factors of emergencies in universities were divided into three categories: human factors, environmental factors, and management factors, and 18 key risk factors of emergencies in universities, including psychological problems, weak legal awareness and lack of safety awareness, were subdivided and determined. Secondly, the interpretive structure model (ISM) was used to construct a multi-layer hierarchical model of the relationship between university emergencies risk factors, clarified the hierarchical affiliation between the risk factors of university emergencies, divided the risk factors of university emergencies into surface direct factors, middle indirect factors and deep fundamental factors, and analyzed the coupling effect of various risk factors on university emergencies. …”
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