Optimal Design Method of Integrated Energy Systems Considering Staged Planning and Equipment Replacement by Lei ZOU, Yiming TANG, Zhuping LIU, Zhengyong WU, Chao FANG, Chaoqun WANG, Fushuan WEN

“…Then, with the whole project cycle as the optimization time scale, the relationship between the equipment installation year and the current remaining life is modeled by introducing the equipment selection and operation decision variables. Finally, considering the influence of economic factors such as nominal interest rates and inflation rates, an objective function, involving investment costs, operating costs, and equipment residual value income, is constructed, with the optimal economical performance as the goal. …”
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Interval Economic Dispatch for Commercial Campus Integrated Energy System with Demand Response Considering Multiple Uncertainties by Xuan Sheng, Shunjiang Lin, Weikun Liang, Yue Pan, Mingbo Liu

“…Test results from actual CCIES demonstrate that the DR can improve the economy and reduce the uncertain fluctuation range of both the objective function and state variables. The ED result can maintain an economical and secure operation under multiple uncertain fluctuations.…”
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Decoding the role of serum cholinesterase among type 2 diabetes mellitus patients at RIMS, Ranchi – A hospital-based study by Avijit Saha, Abha Kumari, Santosh Kumar, Abhay Kumar, Chandrakanta Munni

“…This condition is characterized by variable levels of insulin resistance, impaired insulin secretion, and elevated glucose production. …”
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Association between Oral Health Status and Diabetic Nephropathy-Related Indices in Japanese Middle-Aged Men by Masami Yoshioka, Yoshifumi Okamoto, Masahiro Murata, Makoto Fukui, Shizuko Yanagisawa, Yasuhiko Shirayama, Kojiro Nagai, Daisuke Hinode

“…Logistic regression analysis using eGFR as a dependent variable and age, CPI score, body mass index, HbA1c, and neutral fat as independent variables suggested that low eGFR (<60) could be attributed to CPI score (OR=3.169, 95% CI: 1.031–9.742, p=0.044). …”
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Androgen receptor co-regulation in prostate cancer by Dhirodatta Senapati, Sangeeta Kumari, Hannelore V. Heemers

“…Novel therapeutic strategies are being explored that involve targeting other critical AR domains such as those that mediate its constitutively active transactivation function, its DNA binding ability, or its interaction with co-operating transcriptional regulators. …”
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Construction Concrete Price Prediction Based on a Double-Branch Physics-Informed Neural Network by Kaier Shi, Ruiqing Han, Zhipeng Li, Pan Guo

“…Traditional price prediction of construction material concrete often adopts macroeconomic indicators as independent variables. However, since there is often a closer relationship between the raw materials of construction concrete and the production of construction materials, the price prediction of construction concrete based on raw material prices can more directly ensure the prediction accuracy. …”
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Peak Arm Current Reduction of Modular Multilevel Converter Based on Particle Swarm Optimizer for Circulating Current Injections by Riyadh Toman Thahab, Tahani Hamodi Al-Mhana

“…The magnitude and phase of the injected components are treated as variables in the optimisation process, with the goal of minimising the peak arm current as the cost function. …”
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Selection of Superior Lentil (Lens esculenta M.) Genotypes by Assessing Character Association and Genetic Diversity by U. K. Nath, Santona Rani, M. R. Paul, M. N. Alam, B. Horneburg

“…However, discriminant function analysis revealed a progressive increase in the efficiency of selection and BM-70 ranked as the best followed by the genotypes BM-739, BM-680, BM-185, and BM-513. …”
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A study of the effects of situational strength on self-efficacy and happiness: comparing individualist and collectivist cultures by Young Hyun Yeo, Ju Ho Lee, Keon-Hyung Lee

“…While this may enhance organizational efficiency by minimizing variability in individual performance, it can also suppress self-expression and elevate stress—particularly for individuals in collectivist cultures who face stronger normative control. …”
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L-arginine Supplementation in Endurance Athletes: A Systematic Review of Recovery Mechanisms and Performance Enhancement by Łukasz Karoń, Anna Ewa Zygmunt, Karolina Karoń, Wojciech Grabowski, Grzegorz Drapała, Emilia Pedrycz, Daria Pedrycz

“…Recognized for its multifaceted roles in cardiovascular, immune, and metabolic functions, L-arginine serves as a precursor to biologically active molecules, including nitric oxide (NO), creatine, and polyamines, which are integral to muscle function and recovery. …”
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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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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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Developing data driven framework to model earthquake induced liquefaction potential of granular terrain by machine learning classification models by Kennedy C. Onyelowe, Viroon Kamchoom, Tammineni Gnananandarao, Krishna P. Arunachalam

“…The high precision and Phi Correlation Coefficient further affirm the reliability and accuracy of the model’s predictions. …”
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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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Non-Iterative Estimation of Multiscale Geographically and Temporally Weighted Regression Model by Ya-Di Dai, Hui-Guo Zhang

“…The results demonstrate that the non-iterative estimation method for MGTWR significantly enhances computational efficiency while effectively capturing the scale effects of spatiotemporal variation in the regression coefficient functions for each predictor.…”
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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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