Calculation and Forecast of Glacial Feeding in River Basins by V. G. Konovalov

“…Index δ for the upper reaches of the Rhone River turned out to be not only a representative characteristic of changes in the vegetation period and annual runoff of the river, but also an efficient argument for the super-long-range prediction of these variables for 2025–2054 years.…”
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Development characteristics and potential of fault-fracture reservoir in southwest margin of Ordos Basin by HE Faqi, LI Junlu, GAO Yilong, WU Jinwei, BAI Xingying, GAO Dun

“…The induced fracture zone's proximity to the fault correlates with higher production capacity, demonstrating the spatial impact of fault structures on reservoir productivity. 3） The production characteristics of fracture wells are categorized into three stages: ① the fracture system acts as the high yield stage; ② the fracture system serves as the storage stage and plays the role of diversion; ③ the fracture's primarily function in diversion. This research significantly increases the proportion of high-yield wells in the fault-fracture reservoir, providing crucial insights for guiding efficient, ongoing exploration and development activities in the Mesozoic reservoirs on the southwest margin of the basin. …”
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SCIENTIFIC APPROACH TO A COMPLEX ASSESSMENT OF DETERMINANTS OF THE INSURANCE MARKET DEVELOPMENT OF UKRAINE by L. V. Popova, N. O. Kovalchuk, D. D. Polagnyn

“…The developed model contains a clear list and sequence of stages of the insurance market analysis and a specific methodology for assessing the impact of key factors, characteristic for changing conditions of management, on the efficiency of its functioning. Practical application allows to take into consideration the influence of individual determinants of the insurance market development on its condition, to increase the efficiency of managerial decisions in this area. …”
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An FPGA-accelerated multi-level AI-integrated simulation framework for multi-time domain power systems with high penetration of power converters by Chen Liu, Peng Su, Hao Bai, Xizheng Guo, Alber Filbà Martínez, Jose Luis Dominguez Garcia

“…By integrating AI techniques, such as back propagation neural networks, the framework predicts variables with high computational complexity, improving accuracy and simulation efficiency. …”
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Predicting the Permeability of Pervious Concrete Based on the Beetle Antennae Search Algorithm and Random Forest Model by Jiandong Huang, Tianhong Duan, Yi Zhang, Jiandong Liu, Jia Zhang, Yawei Lei

“…The results showed that the hyperparameters of RF can be tuned by the BAS efficiently; the BAS can combine the conventional RF algorithm to construct the evolved model to predict the permeability of pervious concrete; the cement/aggregate ratio was the most significant variable to determine the permeability, followed by the coarse aggregate proportions.…”
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Optimization of medium components for the production of exopolysaccharide by Lycoperdon pyriforme Schaeff.: Pers. using response surface methodology by MA Xiaokui, JIANG Hua, LI Junzhi, CHEN Yong, HE Xiaojing

“….: Pers. is one of medicinal macro-fungi, which has become an attractive topic as a functional food and as a source for the development of drugs and nutraceuticals. …”
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Causal relationships of vegetation productivity with root zone water availability and atmospheric dryness at the catchment scale by G. W. Abeshu, H.-Y. Li, M. Shi, L. R. Leung

“…These findings underscore the need for a comprehensive functional framework that integrates catchment water supply, atmospheric demand, and vegetation productivity to enhance our understanding and predictive capabilities with regard to ecosystem responses to climate change.…”
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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…In this method, the number of membership functions is 5 functions representing very low, low, medium, high and very high. …”
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Multi-objective optimization of a novel control algorithm and scheduling procedure for optimal use of energy storage systems by Amirhossein Hamzeiyan, Armin Ebrahimi

“…Peak shaving with energy storage systems (ESSs) is a promising approach to optimize energy use, reduce costs, and ensure a more reliable power grid.This paper aims to improve the performance of a novel control algorithm for efficient peak shaving by using sensitivity analysis and multi-objective optimization techniques. …”
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Cognitive Agent-Based Modeling to Optimize Complex Project Management Under Uncertainty by Liliana M. Pantoja-Rojas, Marco A. Alzate-Monroy, Vactor H. Medina-Garcaa, Luis G. Moreno-Sandoval

“…Methodologically, the model integrates mechanisms for distributing tasks, rules for agent assignment, adjustable collaboration ranges, and decision-making based on utility functions. Cognitive aspects are addressed through decentralized decision processes and adaptive behaviors that evolve during the simulation. …”
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Review: roles of mycorrhizal symbioses and associated soil microbiomes in ecological restoration by Christine Lethielleux-Juge

“…A similar recovery period was observed for fungal communities in forest restoration, where ectomycorrhizal mycorrhizal fungi (EMF) species dominate, and diversity increased with time post-revegetation, influenced by edaphic variables and tree species. Under heavy metal (HM) contamination, microorganism classes, enzymes, and AMF efficiency vary with time, soil parameters, restoration treatments, plant species, and levels of soil contamination, with Proteobacteria and Actinobacteria being often predominant. …”
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An enhanced buck-boost converter for photovoltaic diagnosis application: Accurate MPP tracker and I-V tracer by Yassine Chouay, Mohammed Ouassaid

“…In normal operation, the converter is controlled by neural network (NN) controller to efficiently extract maximum power point (MPP). However, in the event of a system failure, the converter automatically transitions to variable load mode to capture different points on the current-voltage (I-V) curve. …”
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Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development by Yurun Wang, Yi Huang, Dongsheng Chen, Longyan Wang, Lingjian Ye, Feifan Shen

“…For deep learning based soft sensors, the spatiotemporal attention (STA)-LSTM is a newly emerged technique which provides efficient predictions for quality variables of industrial processes. …”
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MCL-SWT: Mirror Contrastive Learning with Sliding Window Transformer for Subject-Independent EEG Recognition by Qi Mao, Hongke Zhu, Wenyao Yan, Yu Zhao, Xinhong Hei, Jing Luo

“…Inspired by left/right hand motor imagery inducing event-related desynchronization (ERD) in the contralateral sensorimotor cortex, we develop a mirror contrastive loss function. It segregates feature spaces of EEG signals from contralateral ERD locations while curtailing variability in signals sharing similar ERD locations. …”
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Improved Sliding Mode Active Disturbance Rejection Control for Single-inductance Dual-output Buck Converter by HUANG Jinfeng, ZHOU Jie

“…ObjectiveThe single-inductance dual-output (SIDO) converter has gained increasing attention due to its reduced magnetic component count, compact size, low cost, and high efficiency. However, because both output branches share a single inductor, significant cross-coupling arises during input voltage transients and load disturbances, degrading output voltage performance. …”
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Active RIS-NOMA Uplink in URLLC, Jamming Mitigation via Surrogate and Deep Learning by Ghazal Asemian, Mohammadreza Amini, Burak Kantarci

“…The complexity of the optimization problem, involving numerous interacting variables, leads us to develop a deep regression model to predict optimal network configurations, providing a computationally efficient approach as well as reducing the signaling overhead. …”
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SSR loci potentially associated with high amylopectine content in maize kernel endosperm by S. I. Vakula, O. A. Orlovskaya, L. V. Khotyleva, A. V. Kilchevsky

“…As a component of functional nutrition, maize cultivars with “non-traditional” kernel composition (waxy, oilbearing, sugar, opaque, etc. phenotypic variants) are promising. …”
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Interpretable machine learning for predicting isolated basal septal hypertrophy. by Lei Gao, Boyan Tian, Qiqi Jia, Xingyu He, Guannan Zhao, Yueheng Wang

“…This is a common echocardiographic finding with a prevalence of approximately 7-20%, which may indicate early structural and functional remodeling of the left ventricle in certain pathologies. …”
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Fuzzy System for the Quality Assessment of Educational Multimedia Edition Design by Vsevolod Senkivskyy, Liubomyr Sikora, Nataliia Lysa, Alona Kudriashova, Iryna Pikh

“…A multilevel model of fuzzy logical inference is constructed, representing the dependency between quality factors. Membership functions for linguistic variables are formed and their weight coefficients are determined using pairwise comparison matrices. …”
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Explainable AI-driven assessment of hydro climatic interactions shaping river discharge dynamics in a monsoonal basin by Prashant Parasar, Akhouri Pramod Krishna

“…The main findings of this study are (1) KAN demonstrated high predictive performance with root mean squared error (RMSE) values ranging from 42.7 to 58.3 m3/s, Nash–Sutcliffe efficiency (NSE) between 0.80 and 0.87, mean absolute error (MAE) between 28.9 to 52.7 and R2 values between 0.84 and 0.90 across stations. (2) SHAP based feature contribution analysis identified Relative humidity (hurs), specific humidity (huss), and temperature (tas) as key predictors, while (pr) showed limited contribution due to spatial inherent inconsistencies in GCM precipitation data. (3) The bootstrapped SHAP distributions highlighted substantial variability in feature importance, particularly for humidity variables, revealing station specific uncertainty patterns in model interpretation. (4) The KAN framework results indicate strong temporal alignment and physical realism, confirming KAN’s robustness in capturing seasonal discharge dynamics and extreme flow events under monsoon influence environments. (5) In this study KAN with SHAP (SHapley additive exPlanations) is implemented for hydrological modeling under monsoon-influenced and data-limited regions such as SRB, offering improved accuracy, functional precision and efficiency compared to traditional models. …”
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