Homogenization in Sobolev Spaces with Nonstandard Growth: Brief Review of Methods and Applications by Brahim Amaziane, Leonid Pankratov

“…We review recent results on the homogenization in Sobolev spaces with variable exponents. In particular, we are dealing with the Γ-convergence of variational functionals with rapidly oscillating coefficients, the homogenization of the Dirichlet and Neumann variational problems in strongly perforated domains, as well as double porosity type problems. …”
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Modelagem da produtividade e gestão da qualidade acadêmica by Annibal Parracho Sant'Anna

“…It is a hierarchical model because technical coefficients of the academic production function are modeled as function of second level explanatory variables in such a way that such production function is allowed to change coherently from one department to another. …”
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Skin hyperspectral imaging and machine learning to accurately predict the muscular poly-unsaturated fatty acids contents in fish by Yi-Ming Cao, Yan Zhang, Qi Wang, Ran Zhao, Mingxi Hou, Shuang-Ting Yu, Kai-Kuo Wang, Ying-Jie Chen, Xiao-Qing Sun, Shijing Liu, Jiong-Tang Li

“…With the skin spectra of fish, five ML methods, including the extreme learning machine (ELM), random forest (RF), radial basis function (RBF), back propagation (BP), and least squares support vector machine (LS-SVM) methods, were used to predict the PUFAs and EPA + DHA contents. …”
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Unraveling novel variants in the NF1 gene and investigating potential therapeutic strategies by Jianmei Huang, Ke Yang, Yaoping Wang, Xinrui Ma, Wenke Yang, Xiaodong Huo, Jie Bai, Hongjie Zhu, Jinming Wang, Yibing Lv, Shixiu Liao

“…A retrospective analysis of 49 clinical trials over the past 20 years revealed that NF1 therapies predominantly target neurofibromin’s GTPase function. Gene therapies aiming to restore neurofibromin by transducing the truncated NF1-GRD gene have been developed but faced pre-clinical challenges, including cloning capacity, transduction efficiency, and immunogenicity caused by gene delivery. …”
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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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Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

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Optimisation of the performance and structure of soluble ball seat metal sealing rings based on response surface by CHEN Zhen, RAN Qingjie, CHEN Nengpeng, WANG Qiaomu

“…The increase of groove parameters (groove width and depth) can enhance the contact pressure, and at the same time, increase the equivalent stress, which may lead to local strength deficiency.Through the sensitivity analysis, the sensitivity coefficients of the radius of the metal seal ring to the equivalent force and contact pressure were found to reach 0.67 and 0.82, which were the dominant variables affecting the sealing performance; the width and depth of the grooves regulated the stress distribution through the geometric compensation mechanism. …”
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Machine learning-driven benchmarking of China's wastewater treatment plant electricity consumption by Minjian Li, Chongqiao Tang, Junhan Gu, Nianchu Li, Ahemaide Zhou, Kunlin Wu, Zhibo Zhang, Hui Huang, Hongqiang Ren

“…To overcome the complexity of wastewater compositions, an unsupervised machine learning algorithm, spectral clustering, is introduced to analyze 2,576 WWTPs across China, effectively characterizing influent quality as a single variable and contributing to robust benchmarks with 75 % of the fittings achieving coefficients of determination (R2) >0.85. …”
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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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Ammonia Gas Adsorption in Fixed Bed and Fluidized Bed Using Bentonite Particles by Gabriela Muntianu, Ana-Maria Georgescu, Ana-Maria Rosu, Nicoleta Platon, Vasilica Alisa Arus, Cosmin Valeriu Jinescu, Ileana Denisa Nistor

“…Fluidized bed adsorption can be an efficient technique to accelerate mass transfer between ammonia from air and adsorbent particles.…”
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Neuro-fuzzy inference system and white shark optimization of coagulation-flocculation of aquaculture wastewater treatment by A.F. Mohamed, H. Rezk

“…During the optimization process, these controlling parameters are used as a design variable whereas the objective function required to me be a maximum is the summation of turbidity removal and salinity removal. …”
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Application of marine bacterial alginate lyases in wastewater treatment, biofilm removal and green technology by M.U.K. Anjung, H. Nursyam, A.A. Prihanto, E. Chasanah

“…Despite notable progress, challenges remain in achieving efficient large-scale production, enhancing enzyme robustness, and fine-tuning catalytic properties. …”
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Intelligent hybrid method to predict generated power of solar PV system by Prashant Singh, Navneet Kumar Singh, Asheesh Kumar Singh

“…The input solar PV power data are broken down into intrinsic mode functions (IMFs) using EMD technique is fed into the PSO-ANFIS, along with important meteorological variables. …”
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Engineering safe anti-CD19-CD28ζ CAR T cells with CD8a hinge domain in serum-free media for adoptive immunotherapy by Muthuganesh Muthuvel, Muthuganesh Muthuvel, Thamizhselvi Ganapathy, Trent Spencer, Sunil S. Raikar, Saravanabhavan Thangavel, Alok Srivastava, Alok Srivastava, Alok Srivastava, Sunil Martin

“…CARs are modular synthetic antigen receptors integrating the single-chain variable fragment (scFv) of an immunoglobulin molecule to the TCR signaling. …”
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A Fusion Method Based on Physical Modes and Satellite Remote Sensing for 3D Ocean State Reconstruction by Yingxiang Hong, Xuan Wang, Bin Wang, Wei Li, Guijun Han

“…This study developed an operational-oriented lightweight framework for three-dimensional ocean state reconstruction by integrating multi-source observations through a computationally efficient multivariate empirical orthogonal function (MEOF) method. …”
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A New Multi-Parametric MRI-Based Scoring System for Degenerative Cervical Myelopathy: The Severity on Imaging Myelopathy Score (SIMS) by Alexis Morgado, Julien Berthiller, Fabien Subtil, Donato Creatura, Gildas Patet, Nathalie André-Obadia, Cédric Yves Barrey

“…<b>Background/Objectives:</b> Degenerative cervical myelopathy (DCM) is the leading cause of functional disabilities of spinal origin in people over 50 years old. …”
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Positive Invertibility of Matrices and Exponential Stability of Linear Stochastic Systems with Delay by Ramazan Kadiev, Arcady Ponosov

“…The work addresses the exponential moment stability of solutions of large systems of linear differential Itô equations with variable delays by means of a modified regularization method, which can be viewed as an alternative to the technique based on Lyapunov or Lyapunov-like functionals. …”
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On Complex Singularity Analysis for Some Linear Partial Differential Equations in by A. Lastra, S. Malek, C. Stenger

“…We construct these solutions with the help of series of functions with infinitely many variables which involve derivatives of all orders of X in one variable. …”
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Cost-effective process design for methanol synthesis from carbon dioxide hydrogenation by Sheng-Zhong Huang, Chih-Yao Lin, Chianghui Wang, Akhmat Fauzan Saputra, Henggar Yudha Hananto, Nicolas Justin Sutanto, Anggit Raksajati, Vincentius Surya Kurnia Adi

“…Accordingly, this research introduces an optimization framework capable of handling diverse process configurations, operating variables, and their interactions. This approach enables effective optimization using total annual cost (TAC) as the objective function and significantly enhances process design efficiency. …”
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Multi-Objective Optimal Design of 200 kW Permanent Magnet Synchronous Motor Based on NSGA-II by Chengxu Sun, Qi Li, Tao Fan, Xuhui Wen, Ye Li, Hongyang Li

“…Interior permanent magnet synchronous motors (IPMSMs) are widely applied as drive motors in electric vehicles because they have the advantages of high power density, high efficiency, and excellent dynamic performance. This paper introduces a framework for multi-objective optimization, tailored for the demands of V-Shaped IPMSMs, which involves high-dimensional variables. …”
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