Modeling the contribution of micronekton diel vertical migrations to carbon export in the mesopelagic zone by H. Thibault, F. Ménard, J. Abitbol-Spangaro, J.-C. Poggiale, S. Martini

“…Several metabolic parameters accounted for most of the variability in micronekton biomass, organic carbon production, and transport efficiency, mostly linked to respiration rates and capture efficiency. …”
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Decarbonisation pathways for industrial clusters through multi-energy systems by Ugochukwu Ngwaka, Yousaf Khalid, Janie Ling-Chin, John Counsell, Ruben Pinedo-Cuenca, Huda Dawood, Andrew J. Smallbone, Nashwan Dawood, Anthony P. Roskilly

“…Given the complex and nonlinear interconnections among systems within a multi-energy cluster, this study extends the dynamic multi-vector methodology to multi-energy system clusters, representing variables as nodes and converting them into transfer functions for system integration. …”
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Optimization of stope dimensions using response surface method coupling a hybrid chaos-genetic algorithm by Ming lan, Hanwen Jia, Ju Ma

“…The interaction between variables within this framework was carefully considered when defining the objective functions for optimization. …”
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Optimizing the Spectrum and Power Allocation for D2D-Enabled Communication Systems Using DC Programming by Guomei Gan, Yanhu Huang, Qiang Wang

“…Indeed, the devices can communicate with each other in a D2D system, and the base station (BS) can share the spectrum with D2D users, which can efficiently improve the spectrum and energy efficiency. …”
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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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Building electrical consumption patterns forecasting based on a novel hybrid deep learning model by Nasser Shahsavari-Pour, Azim Heydari, Farshid Keynia, Afef Fekih, Aylar Shahsavari-Pour

“…Specifically, the proposed model comprises three key components: (i) a mutual information-based feature selection method to identify the most significant input variables influencing energy consumption; (ii) a variational mode decomposition (VMD) approach to decompose the original energy consumption signal into intrinsic mode functions (IMFs), capturing relevant trends and eliminating noise; and (iii) a long short-term memory (LSTM) neural network to perform time-series forecasting of the target energy consumption values. …”
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The Relationship between the Reorganization of Higher Education Institutions' Operations in Poland During the COVID-19 Pandemic and Student Loyalty by Sojkin Bogdan, Bartkowiak Paweł, Michalak Szymon

“…Using exploratory factor analysis (EFA), the main components were identified for various variables pertaining to the functioning, organization, and delivery of online classes, as well as for aspects associated with university operations during the COVID-19 pandemic. …”
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Decentralized queue control with delay shifting in edge-IoT using reinforcement learning by Viacheslav Kovtun

“…Analytical expressions for key QoS indicators (delay, variability, loss, energy consumption) as functions of the shift parameter are derived, and a multi-factor reward function is constructed. …”
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Reliability optimization methods: A systematic literature review by Singla Shakuntla, Mangla Diksha, Kumar Malik Ajender, Muhammad Modibbo Umar

“…Additionally, which variables influence the primary reliability metrics in their work and how? …”
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Stress Estimation Based on Stochastic Method for Strength Evaluation of Floating Wind Turbines by Byungmo Kim, Beomil Kim

“…Next, each time series was stochastically fitted to Weibull distribution function. The most probable maximum (MPM) von-Mises stresses were estimated according to the probability level corresponding to the design life of the platform on the fitted curves. …”
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Large live biomass carbon losses from droughts in the northern temperate ecosystems during 2016-2022 by Xiaojun Li, Philippe Ciais, Rasmus Fensholt, Jérome Chave, Stephen Sitch, Josep G. Canadell, Martin Brandt, Lei Fan, Xiangming Xiao, Shengli Tao, Huan Wang, Clément Albergel, Hui Yang, Frédéric Frappart, Mengjia Wang, Ana Bastos, Philippe Maisongrande, Yuanwei Qin, Zanpin Xing, Tianxiang Cui, Ling Yu, Lei He, Yi Zheng, Xiangzhuo Liu, Yuqing Liu, Aurelien De Truchis, Jean-Pierre Wigneron

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The influence of fitness mobile apps on workout behavior intention among Chinese young adults. by Mengyu Li, Shujie Wang, Abdul Rahim Ahmed Soliman Darweesh

“…Three components of belief were examined: self-efficiency, perceived barriers, and perceived benefits. …”
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A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition by Mokhtar Ali, Abdelkerim Souahlia, Abdelhalim Rabehi, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem

“…Three feature selection methods---ReliefF, Minimum Correlation, and Minimum Redundancy Maximum Relevance (MRMR)---are employed to identify the most relevant input variables from a dataset collected in the Ghardaia region. …”
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Theoretical and technical concept of cemented backfill material for flexible enhanced thermal energy storage in coal underground space by Chao LYU, Wenyu LYU, Qiang SUN, Panshi XIE, Ding LANG, Songtao JI, Jianjun HU

“…The research status of backfill mining is analyzed based on the current coal mining technology and the scientific concept of "cemented backfill material for flexible enhanced thermal energy storage (CBM–FETES)" is proposed by integrating the idea of functional filling. The core of CBM–FETES is to ensure the four essential conditions: the suitability of geological conditions, the feasibility of thermal storage and extraction technologies, high efficiency in heat and mass transfer, and the safety and stability of the operational cycle. …”
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Optimizing the Construction Supply Chain Network Considering the Flow of Materials, Equipment, Manpower, Drawings and Technical Documents by Seyed Saeid Helli, Hadi Mokhtari, Saeed Dehnavi

“…All indices, parameters, decision variables, objective functions and constraints have been introduced and presented in the proposed model. …”
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Double and integer multi-objective optimization of solar HDH desalination system with bubble column dehumidifier: An artificial neural network approach by Alireza Naeini, Alireza Jalali, Ehsan Houshfar

“…A neural network model is utilized to predict how the objective functions vary with six decision variables. The chosen optimization approach utilizes the genetic algorithm (GA) method. …”
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Adaptive neighbourhood for locally and globally tuned biogeography based optimization algorithm by Parimal Kumar Giri, Sagar S. De, Satchidananda Dehuri

“…BBO has demonstrated good performance on various unconstrained and constrained benchmark functions. It has also been applied to real world optimization problems of type linear or nonlinear, nominal or ordinal as well as mixed variables. …”
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Application of a novel metaheuristic algorithm inspired by connected banking system in truss size and layout optimum design problems and optimization problems by Mehrdad Nemati, Yousef Zandi, Jamshid Sabouri

“…Abstract Optimum design of truss structures can be a challenging and difficult field of study specially if an optimum design problem is comprised of continuous and discrete decision variables such as in truss size and layout optimization problems. …”
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Comparing machine learning approaches for estimating soil saturated hydraulic conductivity. by Ali Akbar Moosavi, Mohammad Amin Nematollahi, Mohammad Omidifard

“…Results revealed that all NN models particularly PSO-NNs were efficient in prediction of Kfs. However, further evaluations may be recommended for other soil conditions and input variables to quantify their potential uncertainties and wider potential and versatility before they are used in other geographical locations/soil conditions.…”
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Comparing the Effect of Beractant (Beraksurf™) with That of Poractant Alfa (Curosurf®) on the Need for Intermittent Positive Pressure Ventilation in Neonatal Respiratory Distress S... by Yosra Khazani, Sirous Fathi Manesh, Elnaz Shaseb, Parvin Sarbakhsh

“…Performing appropriate adjusted analysis leads to a more interpretable and efficient estimation of treatment effects. Semiparametric adjustment approach modifies the estimating equations solved by the marginal treatment effect estimator by adding an augmentation function, which makes use of the baseline covariates and estimate the unbiased marginal treatment effect with improved precision. …”
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