The Hydrodynamic Performance of a Vertical-Axis Hydro Turbine with an Airfoil Designed Based on the Outline of a Sailfish by Aiping Wu, Shiming Wang, Chenglin Ding

“…Through Latin hypercube experimental design combined with optimization algorithms, four key geometric variables governing the airfoil’s hydrodynamic characteristics were systematically analyzed. …”
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The operational municipal solid waste management policy focuses on identifying waste generation behavior across multiple levels in mega cities, a case study by Hamed Alimoradiyan, Ahmad Hajinezhad, Hossein Yousefi, Mario Giampietro

“…This study demonstrates how impact indicators other than income, like district size, financial types, and economic activity, can be identified as explanatory variables when employing Python software and the K-means method to analyze MSW generation behavior across multiple organizational levels. …”
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Swarm Intelligence Integrated Graph-Cut for Liver Segmentation from 3D-CT Volumes by Maya Eapen, Reeba Korah, G. Geetha

“…In this paper, we focus on liver segmentation from contrast-enhanced abdominal CT volumes, a challenging task due to intensity overlapping, blurred edges, large variability in liver shape, and complex background with cluttered features. …”
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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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A Fractional Time–Space Stochastic Advection–Diffusion Equation for Modeling Atmospheric Moisture Transport at Ocean–Atmosphere Interfaces by Behrouz Parsa Moghaddam, Mahmoud A. Zaky, António Mendes Lopes, Alexandra Galhano

“…The framework employs the Caputo fractional derivative to represent temporal persistence and the fractional Laplacian to model non-local turbulent diffusion, and incorporates a stochastic term with a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mo>/</mo><mi>f</mi></mrow></semantics></math></inline-formula> power spectral density to simulate environmental variability. An efficient numerical solution methodology is derived utilizing complementary Fourier and Laplace transforms, which elegantly converts spatial fractional operators into algebraic expressions and yields closed-form solutions via Mittag–Leffler functions. …”
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Estimation of carbon sequestration capacity of urban green infrastructure by fusing multi-source remote sensing data by Jiahui Chang, Zhenfeng Shao, Jinyang Wang, Zhu Mao, Tao Cheng, Xiaodi Xu, Qingwei Zhuang

“…Urban green infrastructure significantly contributes to the carbon storage functions of urban ecosystems. Accurate selection and efficiently integrating remote sensing data are paramount for evaluating carbon storage at the small-scale of urban green infrastructure. …”
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TheraVision: Engineering platform technology for the development of oncolytic viruses based on herpes simplex virus type 1 by Christina Funk, Nadja Uhlig, Zsolt Ruzsics, Florentin Baur, Matthias Peindl, Sarah Nietzer, Karina Epting, Gabriele Vacun, Gudrun Dandekar, Catherine Botteron, Christian Werno, Thomas Grunwald, Susanne M. Bailer

“…Viruses are able to efficiently penetrate cells, multiply, and eventually kill infected cells, release tumor antigens, and activate the immune system. …”
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Changes in white matter predict efficacy of repetitive transcranial magnetic stimulation in Parkinson's disease by Jinying Han, Lingling Lv, Xin Chen, Mengqi Wang, Lili Hu, Fengbo Xing, Pingping Liu, Liuzhenxiong Yu, Ziye Zhao, Jinmei Sun, Tingting Liu, Jingjing Cheng, Minhao Zhu, Manman Gao, Gongjun Ji, Rong Ye, Kai Wang, Panpan Hu

“…Background: The efficacy of continuous theta burst stimulation (cTBS) in Parkinson's disease (PD) exhibits considerable variability. Emerging evidence links changes in brain white matter (WM) activity to the onset and progression of PD, offering novel insights into its pathophysiology. …”
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Emerging Role of Mesenchymal Stromal Cell and Exosome Therapies in Treating Cognitive Impairment by Vick Key Tew, Muttiah Barathan, Fazlina Nordin, Jia Xian Law, Min Hwei Ng

“…Cognitive aging, characterized by the gradual decline in cognitive functions such as memory, attention, and problem-solving, significantly impacts daily life. …”
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Decellularized adipose-derived matrix from Superficial layers of abdominal adipose tissue exhibits superior capacity of adipogenesis compared to deep layers by Xiaomu Ma, Qiang Yue, Su Fu, Chunjun Liu, Jie Luan

“…These findings not only deepen our comprehension of the structural and functional heterogeneity of adipose tissues but also become one of the reason for the large variability between batches of DAM products, providing guidance for constructing more efficient and stable bio-scaffolds.…”
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Reducing Building Energy Performance Gap: Integrating Agent-Based Modelling and Building Performance Simulation by Chi-Li Chiang, John Calautit

“…Focusing on a multi-functional office building at the University of Nottingham, the study used empirical data to validate the model. …”
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Motor Imagery during Action Observation of Locomotor Tasks Improves Rehabilitation Outcome in Older Adults after Total Hip Arthroplasty by Uros Marusic, Sidney Grosprêtre, Armin Paravlic, Simon Kovač, Rado Pišot, Wolfgang Taube

“…These results demonstrate that AO + MI is efficient to improve motor-cognitive performance after hip surgery. …”
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Assessment of upper limb motor control: establishing normative benchmarks for clinical applications by Pablo Martín-Sierra, Cristina Sanchez, Eloy Urendes, Rafael Raya

“…A combination of clinical functional scales with the quantitative metrics presented here is expected to enable better evaluation of motor control. …”
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Synergistic co-metabolism enhancing the crude oil degradation by Acinetobacter oleivorans DR1 and its metabolic potential by Lairenjam Paikhomba Singha, Renuka Kumari, Keisam Malabika Singha, Piyush Pandey, Pratyoosh Shukla

“…ABSTRACT Bacterial degradation of hydrocarbons during co-metabolism with glucose often resulted in variable degradation efficiency. This study explored the mechanistic understanding of the metabolic response during co-metabolism in Acinetobacter oleivorans DR1 using a metabolomics approach. …”
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Linear Interpolation on a Euclidean Ball in Rⁿ by Mikhail V. Nevskii, Alexey Yu. Ukhalov

“…We mean by \(C(B)\) the space of continuous functions \(f:B\to{\mathbb R}\) with the norm \(\|f\|_{C(B)}:=\max_{x\in B}|f(x)|\) and by \(\Pi_1\left({\mathbb R}^n\right)\) the set of polynomials in \(n\) variables of degree \(\leq 1\), i.e. linear functions on \({\mathbb R}^n\). …”
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Estimativa das temperaturas máximas e mínimas do ar para a região do Circuito das Frutas, SP Estimation of maximum and minimum air temperatures for the "Circuito das Frutas" region... by Ludmila Bardin, Mário J. Pedro Júnior, Jener F. L. de Moraes

“…Also, maps with the spacial variability of the maximum and minimum mean monthly and annual temperatures are presented for the region.…”
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Achievement motivation and attitude of medical laboratory assistants to continuing education by K. S. Kichukova, T. G. Taneva

“…The applicability of the results is very clearly visible in the formulated thesis of the necessary change in the educational policy in the country through new forms of continuous education of medical laboratory assistants which would update their achievement motivation and would result in increase in the efficiency of their professional functioning.…”
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Optimization of Fused Deposition Modeling Parameters for Mechanical Properties of Polylactic Acid Parts Based on Kriging and Cuckoo Search by Yuan Yang, Yiyang Wang, Bowen Xue, Changxu Wang, Bo Yang

“…As an emerging rapid manufacturing technology, 3D printing has been widely applied in numerous fields such as aerospace, shipbuilding, and wind power, by virtue of its advantage in efficiently fabricating components with complex structures and integrated functions. …”
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A self-powered millifluidic device driven by triboelectric generator for the label-free and real-time detection of DNA hybridization by Tara Ghafouri, Sheida Bagherzadeh‑Nobari, Negin Manavizadeh

“…In line with the heterogeneous genoassay modeling, flow variables are tuned to attain the optimal hybridization efficiency equal to 92%. …”
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On Robustness of the Explanatory Power of Machine Learning Models: Insights From a New Explainable AI Approach Using Sensitivity Analysis by Banamali Panigrahi, Saman Razavi, Lorne E. Doig, Blanchard Cordell, Hoshin V. Gupta, Karsten Liber

“…Unlike many methods for explainable artificial intelligence (XAI), this method (a) accounts for complex multi‐variate distributional properties of data, common in environmental systems, (b) offers a global assessment of the input‐output response surface formed by ML, rather than focusing solely on local regions around existing data points, and (c) is scalable and data‐size independent, ensuring computational efficiency with large data sets. We apply this method to a suite of ML models predicting various water quality variables in a pilot‐scale experimental pit lake. …”
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