Predictor Importance for Hydrological Fluxes of Global Hydrological and Land Surface Models by João Paulo L. F. Brêda, Lieke A. Melsen, Ioannis Athanasiadis, Albert VanDijk, Vinícius A. Siqueira, Anne Verhoef, Yijian Zeng, Martine van derPloeg

“…We analyzed the JULES, ORCHIDEE, HTESSEL, SURFEX, and PCR‐GLOBWB models for the relative importance of precipitation, climate, soil, land cover and topographic slope as predictors of simulated average evaporation, runoff, and surface and subsurface runoff. RF models functioned as a metamodel and could reproduce GHM/LSMs outputs with a coefficient of determination (R2) over 0.85 in all cases and often considerably better. …”
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Immunological Avalanches in Renal Immune Diseases by Davide Viggiano, Pietro Iulianiello, Antonio Mancini, Candida Iacuzzo, Luca Apicella, Renata Angela Di Pietro, Sarah Hamzeh, Giovanna Cacciola, Eugenio Lippiello, Andrea Gigliotti, Carmine Secondulfo, Giancarlo Bilancio, Giuseppe Gigliotti

“…Two distinct dynamic patterns emerged: large oscillations in eGFR, proteinuria, or biological age predicted declining function, while small oscillations indicated stability. …”
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Non-Similar Analysis of Boundary Layer Flow and Heat Transfer in Non-Newtonian Hybrid Nanofluid over a Cylinder with Viscous Dissipation Effects by Ahmed Zeeshan, Majeed Ahmad Yousif, Muhammad Imran Khan, Muhammad Amer Latif, Syed Shahzad Ali, Pshtiwan Othman Mohammed

“…Non-similar system of PDEs are obtained with efficient conversion variables. The dimensionless PDEs are truncated using a local non-similarity approach up to third level and numerical solution is evaluated using MATLAB built-in-function bvp4c. …”
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Estimation of Fuzzy Measures Using Covariance Matrices in Gaussian Mixtures by Nishchal K. Verma

“…The mixture components of GMM provide the membership functions for the input-output fuzzy sets. By treating consequent part as a function of fuzzy measures, we derived its coefficients from the covariance matrices found directly from GMM and the defuzzified output constructed from both the premise and consequent parts of the nonadditive fuzzy rules that takes the form of Choquet integral. …”
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Analysis of Surface Roughness and Machine Learning-Based Modeling in Dry Turning of Super Duplex Stainless Steel Using Textured Tools by Shailendra Pawanr, Kapil Gupta

“…One of the most critical aspects of turning, and machining in general, is the surface roughness of the finished product, which directly influences the performance, functionality, and longevity of machined components. …”
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Incorporating stand parameters in nonlinear height-diameter mixed-effects model for uneven-aged Larix gmelinii forests by Muhammad Junaid Ismail, Tika Ram Poudel, Akber Ali, Lingbo Dong

“…Model performance was assessed using root mean square error (RMSE), mean absolute error (MAE), and the coefficient of determination (R2). Results identified the Ratkowsky model (M8) as the best performer, achieving the highest R2 (0.74), the lowest RMSE (16.47%) and MAE (12.50%), at statistically significant regression coefficients (p < 0.05). …”
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AngleCam: Predicting the temporal variation of leaf angle distributions from image series with deep learning by Teja Kattenborn, Ronny Richter, Claudia Guimarães‐Steinicke, Hannes Feilhauer, Christian Wirth

“…The plausibility of the predicted leaf angle time series was underlined by its close relationship with environmental variables related to transpiration. The evaluations confirm that AngleCam is a robust and efficient method to track leaf angles under field conditions. …”
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Adsorption of Cd (II) Using Chemically Modified Rice Husk: Characterization, Equilibrium, and Kinetic Studies by Javier Montalvo-Andía, Warren Reátegui-Romero, Alexis D. Peña-Contreras, Walter F. Zaldivar Alvarez, María E. King-Santos, Víctor Fernández-Guzmán, José Luis Guerrero-Guevara, Jhon E. Puris-Naupay

“…In optimal experimental conditions, the maximum adsorption efficiency was 92.65%. Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM) were used allowing the identification of the main functional groups and morphology of rice husk and treated rice husk, and the results showed an improvement of adsorption characteristics after rice husk treatment with NaOH. …”
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Evaluating Sensitivity of the Ranking of Forest Fuel Treatments to Manager’s Risk Attitudes and the Importance of Treatment Objectives, Montana, USA by Tony Prato, Travis Paveglio

“…The conceptual framework involves (1) defining a utility function on an index that is a weighted average of fuel treatment objectives and incorporates a manager’s risk attitude; (2) using the utility function to calculate utility values for FTSs; (3) applying the stochastic efficiency with respect to a function method to utility values to obtain certainty equivalents (CEs); and (4) ranking FTSs based on statistically significant differences in median CEs for pairs of FTSs. …”
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Evaluasi Kinerja Aplikasi Penelusuran Online Cerah Informasi Pustaka (CIP) Perpustakaan Universitas Tridinanti Palembang Berdasarkan Persepsi Pustakwan by Rusmiatiningsih Rusmiatiningsih, Indah Solehati, Sagiman Sagiman, Marleni Marleni

“…The evaluation model used is the PIECES evaluation model by making a questionnaire based on 6 variables, namely Performance, Information, Economy, Control, Efficiency and Service and each variable is made into indicators. …”
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Pulley ring suture increases shoulder stability after biceps tendon transposition by Duzheng Zhang, Jiezhou Wu, Liyun Zhang, Qiyun Chen, Chao Wang, Ming Cai, Ruijun Cong

“…These statistically significant variables and their coefficients were used to build a generalized linear equation and selected to build the final model including Grouping information (OR:1.61E + 01;95% CI:5.8854–52.5200), Mean T value of bone mineral density (OR:6.95E + 00;95% CI:2.4695–25.6797) and 3 Months post operation UCLA score (OR:1.77E + 00;95% CI:1.4810–2.2539).ConclusionsCompared with the traditional MDBT, the modified MDBT is more effective in improving the long-term function of the glenohumeral joint and better restoring the biological state of the glenohumeral joint.…”
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No significant links between somatognosia, stereognosia, and hypermobility: sensory processing unlikely to drive common complaints in hypermobile population by Ivana Hanzlíková, Aneta Ruská, Kristýna Jančíková, Kim Hébert-Losier

“…Spearman’s rank correlation coefficient was examined the relationship between the Beighton score and measures of somatognosia and stereognosia. …”
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Machine learning-based model for acute asthma exacerbation detection using routine blood parameters by Youpeng Chen, Junquan Sun, Yabang Chen, Enzhong Li, Jiancai Lu, Huanhua Tang, Yifei Xie, Jiana Zhang, Lesi Peng, Haojie Wu, Zhangkai J. Cheng, Baoqing Sun

“…Background: Acute asthma exacerbations (AAEs) are a leading cause of asthma-related morbidity and mortality, especially in resource-limited settings where pulmonary function tests are unavailable or when patients are unable to cooperate with testing. …”
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Optimization of the flow guiding fins configuration and tube arrangements in a shell and tube heat exchanger: coupling response surface methodology and CFD by Xiangmin Shao, Ali Marzban, Farzad Pourfattah, Omid Ali Akbari, Gholamreza Ahmadi, Nafiseh Emami, Soheil Salahshour

“…In both laminar and turbulent flow regimes, the objective functions include the maximum heat transfer and the minimum pressure drop. …”
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Identifying and Validating Indicators of Ritualism in the Iranian Higher Education System: A Mixed-Methods Study by Seyed Hedayat Davarpanah, Reza Hoveida, Mostafa Bagherian Far

“…Neglecting its indicators in the core functions of the university—teaching, research, and services—can lead to institutions that lack quality and fail to make a significant impact on society, both formally and functionally.  …”
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Reconstruction of U.S. Regional-Scale Soybean SIF Based on MODIS Data and BP Neural Network by YAO Jianen, LIU Haiqiu, YANG Man, FENG Jinying, CHEN Xiu, ZHANG Peipei

“…The Pearson correlation coefficient between the original OCO-2 SIF data and MODIS GPP stood were at a modest 0.53. …”
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Polynomial Chaos Expansion Approach to Interest Rate Models by Luca Di Persio, Gregorio Pellegrini, Michele Bonollo

“…The Polynomial Chaos Expansion (PCE) technique allows us to recover a finite second-order random variable exploiting suitable linear combinations of orthogonal polynomials which are functions of a given stochastic quantity ξ, hence acting as a kind of random basis. …”
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Distributed generation plants multi-agent controlling system by YU. N. Bulatov, A. V. Kryukov

“…The adaptability of the system against variable conditions and applicability of the multi-agent technologies during creation of electric power supply smart grids was demonstrated.…”
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An improved statistical bias correction method for Global Climate Model (GCM) precipitation projection: A case study on the CMCC-CM2-SR5 model projection in China’s Huaihe River Ba... by Yuning Luo, Ke Zhang, Wen Wang, Xinyu Chen, Jin Feng, Haijun Wang, Wei Liu, Cheng Guo, Cuiying Chen, Xiaozhong Wang

“…We applied this and three other methods—EquiDistant Cumulative Distribution Function matching method (EDCDF), combined Linear Scaling and Cumulative Distribution Function matching method (LS-CDF) and Quantile-quantile mapping method (QUANT)—to correct biases in the CMCC-CM2-SR5 model. …”
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Research on digital matching methods integrating user intent and patent technology characteristics by Jianwei Yang, Yi Wang, Bonan Zang, Min Peng, George Torrens

“…Abstract The hierarchical analysis of user needs, function mapping, and the intelligent extraction and matching of related product patent technical features are crucial for seeking innovative design solutions and improving design efficiency. …”
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