Eco-engineered remediation: Microbial and rhizosphere-based strategies for heavy metal detoxification by Arun Karnwal, Gaurav Kumar, Alaa El Din Mahmoud, Joydeep Dutta, Rattandeep Singh, Abdel Rahman Mohammad Said Al-Tawaha, Tabarak Malik

“…Moreover, a detailed understanding of plant–microbe interactions and the role of secondary metabolite signalling in the rhizosphere is essential to improve remediation efficiency. Future strategies should prioritize the application of functional genomics, developing bioinoculants tailored to specific environmental conditions, and implementing robust ecological risk assessments for GEMs. …”
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A New Legendre Collocation Method for Solving a Two-Dimensional Fractional Diffusion Equation by A. H. Bhrawy

“…A new spectral shifted Legendre Gauss-Lobatto collocation (SL-GL-C) method is developed and analyzed to solve a class of two-dimensional initial-boundary fractional diffusion equations with variable coefficients. The method depends basically on the fact that an expansion in a series of shifted Legendre polynomials PL,n(x)PL,m(y), for the function and its space-fractional derivatives occurring in the partial fractional differential equation (PFDE), is assumed; the expansion coefficients are then determined by reducing the PFDE with its boundary and initial conditions to a system of ordinary differential equations (SODEs) for these coefficients. …”
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Analysis of Hydrological and Meteorological Conditions in the Southern Baltic Sea for the Purpose of Using LNG as Bunkering Fuel by Ewelina Orysiak, Jakub Figas, Maciej Prygiel, Maksymilian Ziółek, Bartosz Ryłko

“…The southern Baltic Sea is characterized by highly variable weather conditions, particularly in autumn and winter, when storms, strong westerly winds, and temporary sea ice formation disrupt maritime operations. …”
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Smart technique for calculating fault current model parameters using short circuit current measurements by R. A. Mahmoud, O. P. Malik, W. M. Fayek

“…The difference concept can be utilized to obtain precise mathematical formulas for evaluating the parameters of the fault current model. This is for efficient implementation of multiple functions that include digital protective relay, fault locator, digital filter, CT saturation detector and compensator. …”
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Machine learning projection of climate and technology impacts on crops key to food security by Dan Li, Vassili Kitsios, David Newth, Terence John O’Kane

“…Our model is designed to capture the relationships between technology, climate variables and the annual growth rate in crop yield across the world’s producing regions. …”
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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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Production of Cyanobacterial Microscale Adsorbent by Hydrothermal Method for Pre-concentration of Cadmium from Water by T. Mohammadi Arian, G. Rahimi, R. Khavari Farid

“…The absorbent surface was rich in oxygen and nitrogen functional groups, such as hydroxyl, isothiocyanate, and carbonyl. …”
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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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RL-Cervix.Net: A Hybrid Lightweight Model Integrating Reinforcement Learning for Cervical Cell Classification by Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho

“…A novel application of RL for dynamic feature refinement and adjustment based on reward functions was employed to optimize the detection capabilities of the model. …”
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Development of a High-Cell-Density Production Process for a Biotherapeutic Yeast, <i>Saccharomyces cerevisiae</i> var. <i>boulardii</i>, for Use as a Human Probiotic by Ghaneshree Moonsamy, Sarisha Singh, Yrielle Roets-Dlamini, Koketso Kenneth Baikgaki, Santosh Omrajah Ramchuran

“…Once the optimised batch was validated in the replicate batches, the statistical analysis indicated a high level of reproducibility, with low variability across key performance indicators such as biomass concentration (unit), CFU production (CFU.mL⁻¹), and substrate utilization efficiency (g.g⁻¹). …”
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Application of Polylogarithms to the Approximate Solution of the Inhomogeneous Telegraph Equation for the Distortionless Line by P. G. Lasy, I. N. Meleshko

“…Solutions to both problems can be found by separating the variables in the form of a series of trigonometric functions of the line point with time-dependent coefficients. …”
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Blind deconvolution estimation by multi-exponential models and alternated least squares approximations: Free-form and sparse approach. by Daniel U Campos-Delgado, Omar Gutierrez-Navarro, Ricardo Salinas-Martinez, Elvis Duran, Aldo R Mejia-Rodriguez, Miguel J Velazquez-Duran, Javier A Jo

“…On the other hand, the same exponential functions are used in the whole dataset in the global perspective, and just the scaling coefficients are updated for each spatial point. …”
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Optimization of the encapsulation of arazá pulp by spray drying: Physicochemical, morphological and in vitro digestion studies by Greilis Quintero-Gamero, Francis S. Sánchez-Garzón, Aureliano Rodríguez-Cortina, María Hernández-Carrión, Luz Stella Nerio

“…Yield (Y), moisture (M), water activity (aw), water solubility index (WSI), hygroscopicity, ascorbic acid and phenolics encapsulation efficiency (EEAA, EEP), and the retention efficiency of DPPH and radical scavenging capacity (DPPH, ABTS) were studied as response variables; being Y, M, aw, WSI and EAA the ones considered for optimization purposes. …”
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DC Performance Variations of SOI FinFETs with Different Silicide Thickness by Jun-Sik Yoon

“…DC parameters including threshold voltage, low-field-mobility-related coefficient, and parasitic resistance are extracted from Y-function method for the comparison of DC performance and variability, and the correlation analysis. …”
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Integrating UAV-Based RGB Imagery with Semi-Supervised Learning for Tree Species Identification in Heterogeneous Forests by Bingru Hou, Chenfeng Lin, Mengyuan Chen, Mostafa M. Gouda, Yunpeng Zhao, Yuefeng Chen, Fei Liu, Xuping Feng

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Spatial Analysis of the Relationship between Ecological Factors and Housing Prices in Tehran by Atefeh Kolyaei, Tahir Prizadi, Habibollah Fasihi

“…Among the independent variables, the average annual temperature, distance from river valleys, distance from fault lines, and green coverage showed the highest correlation coefficients; however, these relationships were negative, indicating an inverse correlation. …”
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Comparative studies of Taguchi dynamic analysis, statistical, and artificial neural networks for low-carbon steel corrosion inhibition in acidic media by Aprael S. Yaro, Anees A. Khadom, Saeed Rajab Yassen

“…The highest correlation coefficient (0.996) and lower absolute error (0.126) were achieved by MLP 2:2-9-4-1:1.…”
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Optimized Control of Hybrid Energy Storage Systems Using Whale Optimization Algorithm for Enhanced Battery Longevity and Stability in Microgrids by Nouman Alam Siddiqui, Hira Tahir, Muhammad Akram, Habib Ullah Manzoor

“…The method optimizes two key variables: current sharing coefficients and the smoothing constant, enabling continuous HESS functionality. …”
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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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Physically-based constitutive model and dynamic recrystallization behavior of AISI 4330V mod. Alloy steel under hot working conditions by Jungmin Lee, Sungryul Kim, Byoungkoo Kim, Donghwan Kim

“…To enhance prediction accuracy, key variables such as characteristic stresses, strains, and material constants used in the model were expressed not only as functions of the Zener–Hollomon parameter (Z), but also as functions of forming temperature and strain rate. …”
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