The human gut microbiota contributes to type-2 diabetes non-resolution 5-years after Roux-en-Y gastric bypass by Jean Debédat, Tiphaine Le Roy, Lise Voland, Eugeni Belda, Rohia Alili, Solia Adriouch, Pierre Bel Lassen, Kazuyuki Kasahara, Evan Hutchison, Laurent Genser, Licia Torres, Camille Gamblin, Christine Rouault, Jean-Daniel Zucker, Nathalie Kapel, Christine Poitou, Geneviève Marcelin, Federico E. Rey, Judith Aron-Wisnewsky, Karine Clément

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Parametric-modeling-based multi-objective thermoelastic optimization of rudder structures by Shi Guanghui, Bao Yuhao, Wu Wenhua, Guo Guiqiang, Lin Ye, Zhang Xiaopeng, Tao Ran

“…To efficiently analyze and optimize the structural performance of rudder structures, a parametric optimization model for the radial configuration of reinforcement ribs is constructed. …”
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AER-Net: Attention-Enhanced Residual Refinement Network for Nuclei Segmentation and Classification in Histology Images by Ruifen Cao, Qingbin Meng, Dayu Tan, Pijing Wei, Yun Ding, Chunhou Zheng

“…Moreover, the coarse predictions and refined predictions are combined by using a loss function that employs cross-entropy loss and generalized dice loss to efficiently tackle the challenge of class imbalance among nuclei in histology images. …”
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Optimization of Adaptive I²H ∞ Control Method Based on Multiple Input Sensors by Yu Gu, Hanyang Li, Zeting Mei, Hao Wen, Yuanxiong Jin, Wenxuan Dong

“…The core contributions of this study include: 1) Designing a multi-sensor current reference estimator to dynamically generate the optimal electromagnetic torque through state variables such as wheel speed, acceleration, slope, and human factor database (heart rate, subjective score, fatigue index) to achieve real-time prediction of rider demand; 2) Proposing an adaptive current reference value estimation algorithm that integrates feedforward compensation and error feedback to ensure smooth switching of assistance modes and suppress sensor noise; 3) Developing an intention-induced H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> robust current tracking controller that significantly enhances the system&#x2019;s robustness to parameter fluctuations and external disturbances by optimizing the H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> norm of the closed-loop transfer function, while supporting personalized riding assistance.…”
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Cognitive ability and motor performances in the elderly by Jovanović Stevan S., Stojanović-Jovanović Biljana N., Pavlović Aleksandra M., Milošević Radovan Lj., Pavlović Dragan M.

“…Clinicians should consider the association between cognitive function and physical-motor performances when dealing with functioning improvement in the elderly. …”
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Pilot study evaluating lipoma reduction with injected physiologic ice slurry by Kristen K. Arango, Cheryl A. London, William M. Karlin, Jacqueline Milton Hicks

“…Future studies could explore using coolants with more sustained coolant function and multiple injections to promote more efficient tumor reduction.…”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. …”
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Prediction of Biogas Yield from Codigestion of Lignocellulosic Biomass Using Adaptive Neuro-Fuzzy Inference System (ANFIS) Model by Moses Oluwatobi Fajobi, Olumuyiwa Ajani Lasode, Adekunle Akanni Adeleke, Peter Pelumi Ikubanni, Ayokunle Olubusayo Balogun, Prabhu Paramasivam

“…The Gaussian membership function (Gauss-mf) was implemented for the fuzzification of input variables, while the hybrid algorithm was selected for the learning and mapping of the input-output dataset. …”
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Triangular Fuzzy Finite Element Solution for Drought Flow of Horizontal Unconfined Aquifers by Christos Tzimopoulos, Nikiforos Samarinas, Kyriakos Papadopoulos, Christos Evangelides

“…The initial water table is assumed to be curvilinear, following the form of an inverse incomplete beta function. To account for uncertainties in the system, the hydraulic parameters—hydraulic conductivity (K) and porosity (S)—are treated as fuzzy variables, considering sources of imprecision such as measurement errors and human-induced uncertainties. …”
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The impact of digital economy on urban-rural income gap under government intervention by LE Yang, GAO Dongxi, ZHANG Yi, GUO Wei, CHEN Yi

“…Ordinary least squares (OLS) and instrumental variables-two stage least squares (IV-2SLS) estimation methods are used to empirically test the above mentioned-theoretical inferences from the empirical level based on the mediation effect model. …”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. …”
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Implementation of Fuzzy Logic Scheme for Assessment of Power Transformer Oil Deterioration Using Imprecise Information by Zuhaib Nishter, Fangzong Wang

“…This research aims to analyze the implementation of a fuzzy logic-based approach in improving the diagnosis of power transformer oil deterioration, which is critical for maintaining the efficient performance and operational life of transformers. …”
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Reconstruction of reservoir rock using attention-based convolutional recurrent neural network by Indrajeet Kumar, Anugrah Singh

“…This deep learning method is computationally efficient, fast, and reliable for synthetic image realizations. …”
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Good Governance and Seigniorage in a Selected OPEC Countries and Iran by ALI Rashid Shamkhal, Kambiz Paykarjou, beitollah Akbari Moghaddam

“…Therefore, based on the results obtained from the analysis of responce functions in empirical analysis, it is essential to pay attention to changing and improving the methods of governance and administration of the country. …”
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Speciation and mobilization of ultra-trace Hg(II) in groundwater by Kunfu PI, Yanxin WANG, Juewen LIU, Ya’nan YANG, Van Cappellen PHILIPPE

“…Applying tests to hydrogeochemically diverse groundwaters from the Grand River Watershed, Canada, the results indicate that the DNA-functionalized hydrogel is able to quickly detect dissolved Hg(II) but inapplicable to low Hg(II) concentrations (<1.60 μg/L), whereas the DNA-DGT sensor can capture variably ultra-trace Hg(II) species depending on the deployment time. …”
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Influence of Migratory Strategy, Group Size, and Environmental Conditions on the Movements of Caribou in Eastern Alaska by Kyle Joly

“…Migration is a diverse behavior exhibited by a wide array of organisms. Variability in the type of movements is rooted in their purpose, environmental factors, demographics, and individual physiological condition. …”
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Supplier Selection and Order Allocation in A Pharmaceutical Wholesaler by Ryan Hikmah Fadilla, Cucuk Nur Rosyidi, Wakhid Ahmad Jauhari

“…As part of the system modeling, a sensitivity analysis was performed to explore the effects of specific parameters on the objective function and decision variables, assessing variations in inventory costs, shortage costs, and demand. …”
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Calculation and Forecast of Glacial Feeding in River Basins by V. G. Konovalov

“…Index δ for the upper reaches of the Rhone River turned out to be not only a representative characteristic of changes in the vegetation period and annual runoff of the river, but also an efficient argument for the super-long-range prediction of these variables for 2025–2054 years.…”
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Development characteristics and potential of fault-fracture reservoir in southwest margin of Ordos Basin by HE Faqi, LI Junlu, GAO Yilong, WU Jinwei, BAI Xingying, GAO Dun

“…The induced fracture zone's proximity to the fault correlates with higher production capacity, demonstrating the spatial impact of fault structures on reservoir productivity. 3） The production characteristics of fracture wells are categorized into three stages: ① the fracture system acts as the high yield stage; ② the fracture system serves as the storage stage and plays the role of diversion; ③ the fracture's primarily function in diversion. This research significantly increases the proportion of high-yield wells in the fault-fracture reservoir, providing crucial insights for guiding efficient, ongoing exploration and development activities in the Mesozoic reservoirs on the southwest margin of the basin. …”
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An FPGA-accelerated multi-level AI-integrated simulation framework for multi-time domain power systems with high penetration of power converters by Chen Liu, Peng Su, Hao Bai, Xizheng Guo, Alber Filbà Martínez, Jose Luis Dominguez Garcia

“…By integrating AI techniques, such as back propagation neural networks, the framework predicts variables with high computational complexity, improving accuracy and simulation efficiency. …”
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