An Improved Dynamic Matrix Control Algorithm and Its Application in Cold Helium Temperature Control of a Modular High-Temperature Gas-Cooled Reactor (mHTGR) by Zhendong Wu, Zhe Dong, Jilan Zhang

“…As a model predictive control (MPC) technique, dynamic matrix control (DMC) has gained widespread industrial adoption due to its straightforward model construction and clear physical interpretation. …”
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THE METHODS OF FORMATION OF VISUAL AND INFORMATION CULTURE OF PRE-SERVICE MATHEMATICS AND COMPUTER SCIENCE TEACHERS by Maryna H. Drushliak

“…The use of the task method allows to form the ability of rational choice of CVM in accordance with the chosen method of solution, rational choice of CVM computer tools; construction of a cognitive and visual model, interpretation of the obtained computer solution. …”
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Embodied Feeling and Reason in Decision-Making: Assessing the Somatic-Marker Hypothesis by Warren TenHouten

“…However, if task-performance is motivated by potentially large rewards, with high demands on short-term memory and on concentration, the dorsolateral prefrontal cortexcan inhibit affects manifested in the medial prefrontal cortex in order to carry out the necessary cognitive operations. We interpret these two different mental task situations using dual process models. …”
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Explainable Artificial Intelligence to Unveil Intrinsic Characteristics of Conditioning Factors Governing Forest Fire Susceptibility by A. Teke, T. Kavzoglu

“…The internal mechanisms of these models were then interpreted using global and local XAI techniques. …”
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Med-DGTN: Dynamic Graph Transformer with Adaptive Wavelet Fusion for multi-label medical image classification by Guanyu Zhang, Yan Li, Tingting Wang, Guokun Shi, Li Jin, Zongyun Gu, Zongyun Gu

“…Med-DGTN’s architecture demonstrates clinical translatability by revealing disease interaction patterns through interpretable graph structures, potentially informing precision diagnostics in multi-morbidity scenarios.…”
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SIG-ShapeFormer: A Multi-Scale Spatiotemporal Feature Fusion Network for Satellite Cloud Image Classification by Xuan Liu, Zhenyu Lu, Bingjian Lu, Zhuang Li, Zhongfeng Chen, Yongjie Ma

“…SIG-Shapeformer consists of three core components: (1) a Shapelet-based module that captures discriminative and interpretable local temporal patterns; (2) a multi-scale Inception module combining 1D convolutions and Transformer encoders to extract temporal features across different scales; and (3) a differentially enhanced Gramian Angular Summation Field (GASF) module that converts time series into 2D texture representations, significantly improving the recognition of cloud internal structures. …”
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Wheat Soil-Borne Mosaic Virus Disease Detection: A Perspective of Agricultural Decision-Making via Spectral Clustering and Multi-Indicator Feedback by Xue Hou, Chao Zhang, Yunsheng Song, Turki Alghamdi, Majed Aborokbah, Hui Zhang, Haoyue La, Yizhen Wang

“…To address this, the problem is formulated as large-scale group decision-making process (LSGDM), where each planting plot is treated as an independent virtual decision maker, providing its own severity assessments. This modeling approach reflects the spatial heterogeneity of the disease and enables a structured mechanism to reconcile divergent evaluations. …”
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Magnetic Induction Spectroscopy-Based Non-Contact Assessment of Avocado Fruit Condition by Tianyang Lu, Adam D. Fletcher, Richard John Colgan, Michael D. O’Toole

“…The equivalent circuit model, which is both physically interpretable and fitted to experimental data, revealed that the ripening process of avocado fruits is characterized by a weakening of capacitive structures and an increase in extracellular solution conductivity, suggesting changes in cellular integrity and extracellular composition, respectively. …”
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Explainability in machine learning: a pedagogical perspective by Andreas Bueff, Ioannis Papantonis, Auste Simkute, Vaishak Belle

“…Students particularly valued the balance between theoretical concepts and hands-on implementation, though evaluation of XAI outputs remained the most challenging aspect, suggesting future courses should include more structured interpretation exercises and analysis templates.…”
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Evaluating organic carbon in living and dead trees using GLCM features and explainable machine learning: insights from Italian national forest by Mehdi Fasihi, Alex Falcon, Giorgio Alberti, Luca Cadez, Francesca Giannetti, Antonio Tomao, Giuseppe Serra

“…The methodology is structured into five key steps. First, we extract Gray-Level Co-occurrence Matrix (GLCM) texture features from LiDAR-derived canopy height models to quantify spatial heterogeneity in forest structure. …”
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Artificial intelligence in human immunodeficiency virus mutation prediction and drug design: Advancing personalized treatment and prevention by Karamot O. Oyediran, Peace-Ofonabasi O. Bassey, Deborah A. Ogundemuren, Abdullahi Abdulraheem, Chukwuemeka P. Azubuike, Andrew N. Amenaghawon, Margaret O. Ilomunaya

“…However, challenges such as limited access to diverse datasets, ethical concerns, and model interpretability hinder the full potential of AI in HIV research. …”
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Characterization of Anisotropy in Additively Manufactured Materials through Instrumented Indentation Testing by Zhuoshao Cai, Zhiwei Yang, Liang Meng, Kaijie Lin, Yuliang Hou, Thaneshan Sapanathan, Jihong Zhu, Weihong Zhang

“…Abstract The accurate characterization of anisotropy for additively manufactured materials is of vital importance for both high-performance structural design and printing processing optimization. …”
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Analysis of volumetric properties of liquid mixtures: I. method of binary additive quasi-solvates by Pavel Efimov

“…Quasi-solvate Qij is a hypothetical two-particle structure in which one particle i is the ‘solute’ and the other particle j is the ‘solvent’. …”
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Comparison of different neurite density metrics with brain asymmetry evaluation by Ivan I. Maximov, Lars T. Westlye

“…Advanced diffusion approaches allow for estimation of intra-axonal water fraction (AWF), describing a key structural characteristic of brain tissue. AWF can be interpreted as an indirect measure or proxy of neurite density and has a potential as useful clinical biomarker. …”
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Resources, Potentials and Academic Achievements of Students. Part 1. Differentiation of Resources and Potentials by L. Ya. Dorfman, A. Yu. Kalugin

“…There is no consistency in the interpretations and criteria of personal learning resources and potentials, and the numerous models are inaccurate in most cases.The aim of the present research is to conceptually harmonise and systematise disjointed scientific data on the internal resources and potentials of students as prerequisites for their academic success in higher education.Methodology and research methods. …”
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Graph Kolmogorov–Arnold Convolutional Network for Hyperspectral Image Classification by Hengyi Zheng, Hongjun Su, Zhaoyue Wu, Yiping Chen, Qian Du

“…As a new network architecture designed to replace the traditional MLP, KAN addresses the model scaling and interpretability limitations of MLP by using learnable spline-based functions in lieu of weights, resulting that GKACN fully exploits the potential of the KAN and GNN structures to facilitate the mining of more representative features. …”
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Formal Verification of Spatio-Temporal Rules Guided Safe Reinforcement Learning for CPS by YIN Chan, ZHU Yi, WANG Jinyong, CHEN Xiaoying, HAO Guosheng

“…Secondly, the structure of the reward state machine is formalized by abstracting the system environment model to propose the spatio-temporal rule reward machine (STR-RM) which can guide the setting of reward functions in reinforcement learning. …”
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Seismic data denoising based on attention dual dilated CNN by Haixia Hu, Youhua Wei, Hui Chen, Xingan Fu, Ji Zhang, Quan Wang, Shiwei Cai

“…Abstract Seismic data denoising is essential for accurate seismic-exploration data processing and interpretation. Traditional noise suppression methods often result in the loss of critical signals, affecting subsurface structure characterization. …”
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Benchmarking universal machine learning interatomic potentials for rapid analysis of inelastic neutron scattering data by Bowen Han, Yongqiang Cheng

“…Traditional methods based on the quantum description of the electronic structure, while widely used, are computationally expensive and demand substantial expertise. …”
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The Sun’s Dark Core: Helioseismic and Neutrino Flux Constraints on a Compact Solar Center by Earl P. Bellinger, Matt E. Caplan

“…We consider the effects on the solar structure arising from a general class of macroscopic dark matter candidates that include strange quark matter, compact dark objects, and others. …”
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