Natural assets, changes, and variations of the socioeconomic-environmental systems along the Asian drylands belt by Jiquan Chen, Ranjeet John, Venkatesh Kolluru, Elizabeth A Mack, Peilei Fan, Jing Yuan, Zutao Ouyang, Jingyan Chen, Pavel Groisman, Changliang Shao, Amarjargal Amartuvshin, Garik Gutman

“…We found increased variability as well as spikes in extreme values in each of these three measures of SES function among the 23 PEs over the study period. …”
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Exploration design for Q-learning-based adaptive linear quadratic optimal regulators under stochastic disturbances by Vina Putri Virgiani, Shiro Masuda

“…Q-learning optimizes the state-action policy by estimating the Q-function iteratively. This study proposes exploration signal design for the bias-free Q-learning algorithm that modifies the recursively defined Q-function by adding a disturbance-influenced term and utilizes an Instrumental Variable (IV) technique to resolve the bias-error issue. …”
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Study on Operation Control Strategy for Campus Public Building Heating Systems in Severe Cold Areas by Chuntian Lu, Shourui Xue, Yuetong Zhang, Songqing Wang

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Jump around: Selecting Markov Chain Monte Carlo parameters and diagnostics for improved food web model quality and ecosystem representation by Gemma Gerber, Ursula M. Scharler

“…However, little information exists on how each LIM-MCMC algorithm parameter affects the degree of empirical data variability introduced into the ensemble. Further, post hoc algorithm quality diagnostics with commonly used trace plots and the coefficient of variation (CoV) rarely address critical aspects of algorithm quality, such as (1) if the returned ensemble successfully targeted the solution space distribution (stationarity), (2) correlation between ensemble solutions (mixing), and (3) if the ensemble contains enough solutions to adequately capture input data variability (sampling efficiency). …”
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Rolling Bearing Fault Diagnosis Method Based on SWT and Improved Vision Transformer by Saihao Ren, Xiaoping Lou

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An asymmetric fuzzy-based self-tuned PSO-Optimized MPPT controller for grid-connected solar photovoltaic system by Md. Naiem-Ur-Rahman, Md. Mahmudul Hasan, Afsana Mimi Raka, Md. Fayzur Rahman, Md. Masud Rana, Ahmed Al Mansur, Md. Abdur Razzak

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An Improved Adaptive Car-Following Model Based on the Unscented Kalman Filter for Vehicle Platoons’ Speed Control by Caixia Huang, Wu Tang, Jiande Wang, Zhiyong Zhang

“…Traditional models generally assume a fixed maximum speed within the optimal velocity function, which constrains effective platoon speed regulation across road segments with varying speed limits and lacks adaptability to dynamic scenarios such as changes in the platoon leader’s speed or substitution of the lead vehicle. …”
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Research on Small-Target Detection of Flax Pests and Diseases in Natural Environment by Integrating Similarity-Aware Activation Module and Bidirectional Feature Pyramid Network Mod... by Manxi Zhong, Yue Li, Yuhong Gao

“…Additionally, this paper adopts the EIOU loss function to further optimize the model’s bounding box regression, reducing the distortion of bounding boxes caused by high sample variability. …”
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Effects of stand age and soil microbial communities on soil respiration throughout the growth cycle of poplar plantations in northeastern China by Xiangrong Liu, Xiangrong Liu, Lingyu Hou, Lingyu Hou, Changjun Ding, Changjun Ding, Xiaohua Su, Xiaohua Su, Weixi Zhang, Weixi Zhang, Zhongyi Pang, Yanlin Zhang, Yanlin Zhang, Qiwu Sun, Qiwu Sun

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Mathematical modeling describing the performance of open loop multivariable vapor compression chiller model: implications for sustainable HVAC in social housing development by Basim Touqan, Basim Touqan, Muna Salameh

“…IntroductionThis study introduces a simplified multi-variable state-space model of a vapour compression chiller system, focusing on key components such as the condenser and evaporator.MethodsThe model is based on a previously validated state-space framework and has been further developed to generate a transfer function matrix with two inputs (refrigerant and cold carrier flow rates) and two outputs (cooling capacity and outlet temperature). …”
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Development and evaluation of the organization`s logistics strategy based on the application of bifurcation theory by M. Yu. Uchirova, L. A. Ilin, S. V. Khudyakov

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Forecasting Industrial Electricity Consumption in Iran: A Novel Hybrid Approach for Sustainable Energy Management by Mohsen Rezaei

“…Accurately predicting industrial electricity consumption is essential for optimizing energy efficiency, and reducing costs in industrial operations. …”
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CLINICAL SIGNIFICANCE OF ASPIRIN RESISTANCE IN PATIENTS WITH CARDIO-VASCULAR DISEASES by P. J. Dovgalevsky, N. V. Furman, N. F. Puchinian

“…Possible reasons for this are discussed: low compliance with treatment, peculiarities of functional condition of platelets, genetically given variability of platelet receptors etc. …”
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Comparative Evaluation of Feed-Forward Neural Networks for Predicting Uniaxial Compressive Strength of Seybaplaya Carbonate Rock Cores by Jose W. Naal-Pech, Leonardo Palemón-Arcos, Youness El Hamzaoui

“…This work presents a comprehensive evaluation of four feed-forward artificial neural network (ANN) architectures—radial basis function (RBF), Bayesian regularized (BR), scaled conjugate gradient (SCG), and Levenberg–Marquardt (LM)—to predict UCS from three readily measured variables: water content, interconnected porosity, and real density. …”
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Sol–gel auto-combustion synthesis of a novel ternary magnetic-recyclable ZnFe2O4/ZnO/CeO2 nano-photocatalyst for highly efficient visible-light-induced degradation of organic conta... by Saba Roostaei, Hanieh Ansarinejad, Elmuez A. Dawi, Forat H. Alsultany, Salman Khalaf Issa, Mina Ahmadi-Kashani, Masoud Salavati-Niasari

“…Abstract The creation and design of highly efficient photocatalysts responsive to visible light are critically required to address pressing environmental challenges. …”
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Morpho‐Physiological Traits and Dehydration Tolerance of High‐Altitude Andean Wetland Vegetation in the Chilean Atacama Region by Dariel López, Patricia L. Sáez, Lohengrin A. Cavieres, Fernanda C. Beveridge, Felipe Saavedra‐Mella, León A. Bravo

“…In this study, we characterized the functional trait spectrum of dominant plant species within the Salar de Pedernales, Quebrada Leoncito (Leoncito) and Río Negro HAWAs and explored the relationships between these traits and key environmental variables. …”
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In-depth characterization of accessory gene regulator loci and associated virulence factors in tcdA+B+ Clostridioides difficile isolates by Mansoor Kodori, Zohreh Ghalavand, Abbas Yadegar, Gita Eslami, Masoumeh Azimirad, Mohammad Reza Zali

“…The study uncovered significant variability in sporulation efficiency among isolates, with high efficiency correlating with tcdC-A genotype. …”
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Association mapping for root system architecture under varying levels of phosphorus application in Brassica juncea L. Czern & Coss by Priyanka Upadhyay, Mehak Gupta, Simarjeet Kaur Sra, Gurdeep Cheema, Virender K. Sardana, Rakesh Sharda, Nitika Sandhu, Javed Akhatar, Gurpreet Kaur

“…Root system architecture (RSAr) plays a crucial role in Pi uptake from soil and thereby improving phosphorus use efficiency (PUE) of plants. Studying the genetic variability of RSAr traits across various Pi levels offers insights for enhancing crop resilience to Pi deficiency. …”
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Economic Analysis of Innovation Development Processes in Agriculture of the Republic of Uzbekistan by I. B. Rustamova, M. M. Babadjanova

“…The article provides econometric analysis of agricultural production efficiency in the Republic of Uzbekistan. As methodology for identifying the impact of land, labour resources and capital on the net output of agriculture Kobba - Douglas production function was used. …”
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A Novel Method for Inverting Deep-Sea Sound-Speed Profiles Based on Hybrid Data Fusion Combined with Surface Sound Speed by Qiang Yuan, Weiming Xu, Shaohua Jin, Xiaohan Yu, Xiaodong Ma, Tong Sun

“…By constructing a high-resolution regional sound speed field through WOA23 and historical SSP fusion, this method effectively mitigates spatiotemporal heterogeneity and seasonal variability. The artificial lemming algorithm (ALA) is introduced to optimize the inversion of empirical orthogonal function (EOF) coefficients, enhancing global search efficiency while avoiding local optimization. …”
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