Force Reduction Factor R for Shear Dominated Low-Rise Brick Masonry Structures by N. Ahmad, Q. Ali, M. Javed

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Design and implementation of a cost-effective, safe, and precise lean-rich generating system for the evaluation of NOX storage reduction catalysts: performance analysis, statistica... by Javad Sajedifar, Seyyed Bagher Mortazavi, Hasan Asilian Mahabadi, Ali Khavanin, Mohammad Sharif Hosseini

“…This research presents a simple, safe, and cost-effective gas generation system for laboratory applications, including evaluating adsorbents and catalysts, particularly NOx storage reduction catalysts, and for toxicological studies using precise dynamic methods like gas stream mixing and evaporation. …”
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Tropospheric ozone trends and attributions over East and Southeast Asia in 1995–2019: an integrated assessment using statistical methods, machine learning models, and multiple chem... by X. Lu, X. Lu, Y. Liu, Y. Liu, J. Su, J. Su, X. Weng, X. Weng, X. Weng, T. Ansari, Y. Zhang, G. He, G. He, Y. Zhu, Y. Zhu, H. Wang, H. Wang, G. Zeng, G. Zeng, J. Li, J. Li, C. He, C. He, S. Li, S. Li, T. Amnuaylojaroen, T. Butler, Q. Fan, Q. Fan, S. Fan, S. Fan, G. L. Forster, G. L. Forster, M. Gao, J. Hu, Y. Kanaya, M. T. Latif, K. Lu, P. Nédélec, P. Nowack, P. Nowack, B. Sauvage, X. Xu, L. Zhang, K. Li, J.-H. Koo, T. Nagashima

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Analysis of selectional preference for grassland ecological compensation methods under the perspective of herders differentiation by Juanjuan Hu, Yuchen Liu, Xinling Zhang, Jianjun Zhang

“…IntroductionExploring herders’ preferences for grassland ecological compensation methods provides a decision-making basis for strengthening the incentive effects of grassland ecological compensation policies.MethodsThe research utilized survey data of 372 herders from three prefecture-level cities in Inner Mongolia, and comprehensively applied grey relational analysis (GRA) and multinomial logit (MNL) model to empirically analyze herders’ selectional preferences for grassland ecological compensation methods and influencing factors from the perspective of herders differentiation.ResultsThe findings revealed: (1) More than two thirds (69.28%) of the herders preferred simple and convenient “financial compensation” in addition to existing forms of compensation; 10.22%, 10.48%, and 11.02% of the herders preferred in-kind compensation, technological compensation, and policy-based compensation, respectively. (2) Compared with individual and livestock operation characteristics, herders’ differentiated behavioral attitudes and family characteristics were more strongly associated with their preferences for compensation methods. (3) Compared with direct financial compensation, herders’ gender and transport distance to the nearest marketplace significantly influenced the choice of in-kind compensation; herders’ age, livestock numbers, grazing area, and dependence on subsidy and reward policies significantly influenced the choice of technological compensation; herders’ gender, age, number of family laborers, level of part-time income, willingness for professional transformation, and perception of the rationality of compensation types significantly influenced the choice of policy-based compensation.DiscussionTo optimize compensation modes for grassland ecological conservation, a “diversified & differentiated” positive incentive system should be constructed according to herders’ preferences and differentiated characteristics in order to facilitate voluntary livestock reduction, meanwhile a negative incentive should be incorporated to constrain herders’ overgrazing behavior.…”
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Flash Flood Regionalization for the Hengduan Mountains Region, China, Combining GNN and SHAP Methods by Yifan Li, Chendi Zhang, Peng Cui, Marwan Hassan, Zhongjie Duan, Suman Bhattacharyya, Shunyu Yao, Yang Zhao

“…The performances of two classic machine learning methods (K-means and Self-organizing feature map) and three GNN methods (Deep Graph Infomax (DGI), Deep Modularity Networks (DMoN), and Dilation shrink Network (Dink-Net)) were compared for flash-flood regionalization, and the Dink-Net model outperformed the others. …”
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Methods and Algorithms for Decision-Making in Agro-Industrial Environmental Management by Olga Ivashchuk, Vyacheslav Fedorov, Zhanat Kenzhebayeva, Oleg Ivashchuk, Moldir Allaniyazova, Kaiyrbek Makulov, Gulnar Kaziyeva

“…Field experiments conducted in the Belgorod Region, Russia, on 50-hectare test sites demonstrated a 27% improvement in forecasting accuracy compared to conventional methods. Key findings reveal that implementing optimized land-use scenarios resulted in: 19% reduction in pollutant accumulation in soil, 27% increase in agricultural productivity, 25% decrease in public health risks. …”
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Modeling processes for preparing high-tech production using the virtual enterprise concept by Liudmyla Lutai

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Development of a Novel Real-Time Weighted Surrogate Model for Wind Turbine-Based on DFIG: Enhancing Computational Efficiency in Power Systems With Error Bound by Muhammad Latif, Hira Ambreen, Tang Diyin, Farrukh Hassan, Muhammad Imran, Saddam Hussain Abbasi, Muhammad Imran

“…In the realm of modern wind turbine engineering, where precision is paramount for stability, control, and observability, this article introduces a groundbreaking method leveraging time-weighted Gramians. The focal point of this work is the reduction of model order in wind turbines featuring a double-fed induction generator with time-varying rotational speeds. …”
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Decoding Chemical Profiles, Biological Functions, and Medicinal Properties of Liquidambar orientalis Extracts Through Molecular Modeling and Bioinformatic Methods by Mehmet Cengiz Baloglu, Lutfiye Yildiz Ozer, Buket Pirci, Yasemin Celik Altunoglu, Sanam Iram Soomro, Gokhan Zengin, Mehmet Veysi Cetiz, Simone Carradori, Zoltán Cziáky, József Jekő

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Research and Experimental Verification of an Efficient Subframe Lightweighting Method Integrating SIMP Topology and Size Optimization by Jihui Zhuang, Fan Zeng

“…A topology optimization model was established using the Solid Isotropic Material with Penalization (SIMP) method and solved using the Method of Moving Asymptotes (MMA) algorithm. …”
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Long-term trajectory prediction method based on highway vehicle-following behavior patterns by Zhichao An, Yimin Wu, Fan Zhang, Dong Zhang, Bolin Gao, Suying Zhang, Guang Zhou, Aoning Jia

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Reducing Computational and Memory Cost of Substructuring Technique in Finite Element Models by M H. Kadkhodaee, H. Moslemi

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Machine learning method based on radiomics help differentiate posterior pituitary tumors from pituitary neuroendocrine tumors and craniopharyngioma by Yukun Liu, Yanpeng Zhou, Chunyao Zhou, Zhenmin Wang, Ziwen Fan, Kai Tang, Siyuan Chen

“…Predictive models were successfully established, and models based on CE features had the best performance with an accuracy of 0.786, precision of 0.929, specificity of 0.778, sensitivity of 0.788, and area under the curve of 0.818 in validation. …”
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MATHEMATICAL MODELING OF A DISTANCE DEPENDENCE OF A SCANNING KELVIN PROBE LATERAL RESOLUTION by A. K. Tyavlovsky

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Landslide hazard early warning method for rock slopes using a hybrid LSTM-SARIMA data-driven model. by Yongxin Dai, Zijian Li, Jingbiao Lu

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Optimization of bulk carrier hull design through CAD modelling and FEM structural analysis – a case study by Alexandru Pintilie, Mihaela-Greti Manea, Daniel Mărăşescu, Ovidiu Cristea, Paul Burlacu, Cătălin-Paul Clinci, Nicolae Silviu Popa

“…Recording of frequent structural damage to the hull of bulk carriers (some of it serious) motivates the need to use the concept of computer-based rational design through advanced analysis methods. The aim of this paper was to optimize - through structural and dimensional modeling - the mid ship section of the 165,000 dwt bulk carriers, under the effect of general combined stresses (longitudinal-vertical bending, transverse-vertical bending and longitudinal torsion) also considering specific local stresses. …”
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Advances in the pilot point inverse method: Où En Sommes-Nous maintenant? by White, Jeremy, Lavenue, Marsh

“…Since Ghislain de Marsily first developed the Pilot Point Method (PPM) in 1978, its development and use has grown significantly in applied decision-support modeling settings including hydrogeology, as well as in other industries, e.g., petroleum reservoir engineering. …”
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Using artificial intelligence methods for the optimal synthesis of reversible networks by Taras Kyryliuk, Mykhailo Palahuta, Vitaly Deibuk

“…According to Moore's Law, the reduction of transistor sizes to the atomic scale faces physical limits, which complicate further development. …”
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YOLO-Ginseng: a detection method for ginseng fruit in natural agricultural environment by Zhedong Xie, Zhuang Yang, Chao Li, Zhen Zhang, Jiazhuo Jiang, Hongyu Guo

“…The inference time of the model reaches 7.4ms. The compressed model exhibits reductions of 76.4%, 79.3%, and 74.2% in terms of model weight size, parameter count, and computational load, respectively.DiscussionCompared to other models, YOLO-Ginseng demonstrates superior overall detection performance. …”
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An Ensemble Learning Method for the Kernel-Based Nonlinear Multivariate Grey Model and its Application in Forecasting Greenhouse Gas Emissions by Lan Wang, Nan Li, Ming Xie

“…In order to give policy makers more power to set the specific target of GHG emission reduction, we propose an ensemble learning method with the least squares boosting (LSBoost) algorithm for the kernel-based nonlinear multivariate grey model (KGM) (1, N), and it is abbreviated as BKGM (1, N). …”
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