Signatures of Rapidly Rotating Stars with Chemically Homogeneous Evolution in the First Galaxies by Boyuan Liu, Yves Sibony, Georges Meynet, Volker Bromm

“…We find that the rest-frame UV luminosity of star-forming galaxies can be significantly enhanced by a factor of  ∼3−6 when CHE stars above a minimum initial mass of ${m}_{\star ,\min }^{\mathrm{CHE}}\sim 2-10\,{M}_{\odot }$ account for more than half of the total stellar mass following a Salpeter initial mass function. As a result, the UV luminosity functions observed at z  ∼ 12−16 can be reproduced with less extreme values of star formation efficiency and UV luminosity stochastic variability. …”
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Root‐Zone Water‐Storage Capacity and Uncertainty: An Intrinsic Factor Affecting Agroecosystem Resilience to Drought by Nunzio Romano, Caterina Mazzitelli, Paolo Nasta

“…Root‐zone water‐storage capacity (SR) is a commonly used variable of agroecosystem functioning, representing the maximum value of water stored within the root zone and accessible to vegetation for its productive growth. …”
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Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

“…This has motivated a shift towards semi-supervised learning (SSL), which leverages labeled and unlabeled data to improve learning efficiency and reduce annotation costs. This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions. …”
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Principal networks. by Jonathan D Clayden, Michael Dayan, Chris A Clark

“…This is an important problem because most cognitive functions would be expected to involve some but not all brain regions. …”
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Removal of caffeine from aqueous solution by green approach using Ficus Benjamina zero-valent iron/copper nanoparticles by Hossam Mohammed Abdel-Aziz, Rabie Saad Farag, Soha Ali Abdel-Gawad

“…Overall, FB-Fe/Cu is a committed green substance for removal Caffeine from aqueous solutions. Functional parameters affect investigated using the Linear regression analysis, we found them to account for over 98% of the variables affecting the removal procedure.…”
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Beyond Collaboration: The Impact of Partner Knowledge, Relational Skills, and Internal Communication on SME’s Performance by Marsiana Setiarini

“…Meanwhile, Internal Communication functions as a routine interaction mechanism that improves collaborative competence and accelerates organizational performance. …”
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Slow and Quick Flow Models Explain the Temporal Dynamics of Daily Salinity in Streams by Thomas G. Westfall, Tim J. Peterson, Anna Lintern, Andrew W. Western

“…However, significant variability within high‐frequency data sets can result in poor explanation of temporal dynamics using the simple C‐Q equation. …”
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Accurate Sugarcane Detection and Row Fitting Using SugarRow-YOLO and Clustering-Based Spline Methods for Autonomous Agricultural Operations by Guiqing Deng, Fangyue Zhou, Huan Dong, Zhihao Xu, Yanzhou Li

“…This model introduces the WTConv convolutional modules to expand the sensory field and improve computational efficiency, adopts the iRMB inverted residual block attention mechanism to enhance the modeling capability of crop spatial structure, and uses the UIOU loss function to effectively mitigate the misdetection and omission problem in the region of dense and overlapping targets. …”
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Biomechanical Analysis of <i>Camellia oleifera</i> Branches for Optimized Vibratory Harvesting by Rui Pan, Ziping Wan, Mingliang Wu, Shikui Lu, Lewei Tang

“…The nonlinear least squares method, based on the hyperbolic tangent function, was employed to fit the bending load–deflection curves of the branches. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…Timely identification is crucial for efficient intervention, as untreated diabetic retinopathy can progress to irreversible vision loss. …”
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Experiments in globalisation, food security and land use decision making. by Calum Brown, Dave Murray-Rust, Jasper van Vliet, Shah Jamal Alam, Peter H Verburg, Mark D Rounsevell

“…Both outcomes are subject to the responses of individual land managers to economic and environmental stimuli, and these responses are known to be variable and often (economically) irrational. We investigate the consequences of stylised food security policies and globalisation of agricultural markets on land use patterns under a variety of modelled forms of land manager behaviour, including variation in production levels, tenacity, land use intensity and multi-functionality. …”
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Predictive model of small choroidal melanoma progression after eye-saving treatment based on clinical, morphometric and immunological parameters by E. B. Myakoshina, I. G. Kulikova, N. V. Balatskaya, L. A. Katargina, S. V. Saakyan

“…A formula was calculated where P (z) is the value of the logistic function; Z, linear combination of symptoms; bo , intercept (free term), bi – regression coefficients for parameters Zi.P (z) = 1 : 1 + e – b0– b1z1– b2z2– b3z3– b4z4The logistic function increases monotonically and takes the values from 0 to 1 for any b and Z values [P∈ (0;1)]. …”
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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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Fast Möbius transform: An algebraic approach to information decomposition by Abel Jansma, Pedro A. M. Mediano, Fernando E. Rosas

“…The partial information decomposition (PID) and its extension integrated information decomposition (ΦID) are promising frameworks to investigate information phenomena involving multiple variables. An important limitation of these approaches is the high computational cost involved in their calculation. …”
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Predicting the onset of chronic kidney disease (CKD) for diabetic patients with aggregated longitudinal EMR data. by Neda Aminnejad, Michelle Greiver, Huaxiong Huang

“…This research focuses on developing a predictive model to classify diabetic patients showing signs of kidney function impairment based on their CKD development risk. …”
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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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Assessment of RBFs Based Meshfree Method for the Vibration Response of FGM Rectangular Plate Using HSDT Model by Manish Srivastava, Jeeoot Singh

“…Radial basis functions (RBFs) with modified radial distance are proposed for vibration analysis of functionally graded materials (FGM) rectangular plates. …”
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Physics-augmented deep learning models for improving evapotranspiration estimation in global land regions by Binrui Liu, Xinguang He, Wenkai Lyu, Lizhi Tao

“…A Physics-Data Learning (PDL) model is first formed by adding a complementary physical variable generated by Penman–Monteith (PM) equation to a deep learning (DL) model along with driving variables to regress latent heat flux. …”
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Decomposed Linear Dynamical Systems (dLDS) models reveal instantaneous, context-dependent dynamic connectivity in C. elegans by Eva Yezerets, Noga Mudrik, Adam S. Charles

“…Abstract Mounting evidence indicates that neural “tuning” can be highly variable within an individual across time and across individuals. …”
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Monitoring Abiotic Stressors in Rainfed Vineyards Involves Combining UAV and Field Monitoring Techniques to Enhance Precision Management by Federico Valerio Moresi, Pasquale Cirigliano, Andrea Rengo, Elena Brunori, Rita Biasi, Giuseppe Scarascia Mugnozza, Mauro Maesano

“…However, precise vineyard management is a crucial component of adaptation strategies aimed at optimizing resource efficiency, which is essential for sustainable farming practices. …”
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