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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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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Analysis of Surface Roughness and Machine Learning-Based Modeling in Dry Turning of Super Duplex Stainless Steel Using Textured Tools by Shailendra Pawanr, Kapil Gupta

“…One of the most critical aspects of turning, and machining in general, is the surface roughness of the finished product, which directly influences the performance, functionality, and longevity of machined components. …”
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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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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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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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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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On a Solution of a Third Kind Mixed Integro-Differential Equation with Singular Kernel Using Orthogonal Polynomial Method by Ahmad Alalyani, M. A. Abdou, M. Basseem

“…The singular kernel is modified to take a logarithmic form, while the kernels of time are continuous and positive functions. Using the separation of variables technique, we have a system of Fredholm integral equations (FIEs) that can be transformed into an algebraic system after using orthogonal polynomials. …”
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Using Fuzzy Feed-Forward Neural Network for Linguistic Processing by AbdulRahim K. Rah, Sozan S. Haydar

“…To determine the costs associated with fuzzy calculations and fuzzy objectives, developed a cost function. At that point, created a learning algorithm from the cost capacity to align the four variables of each trapezoidal fuzzy weight. …”
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Impact of Wall Material Composition (Maltodextrin vs. Inulin vs. Nutriose) and Emulsion Preparation System (Nano- vs. Microemulsion) on Properties of Spray-Dried Linseed Oil by Dorota Ogrodowska, Iwona Zofia Konopka, Grzegorz Dąbrowski, Beata Piłat, Józef Warechowski, Fabian Dajnowiec, Małgorzata Tańska

“…For these independent variables, the properties of the prepared emulsions (flow curves and viscosity) and the resulting powders (encapsulation efficiency, particle size distribution, water activity, bulk and tapped density, Carr’s index, color parameters, and thermal stability) were determined. …”
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Role of physical activity on the maintenance of cognition and activities of daily living in elderly with Alzheimer's disease Papel da atividade física na manutenção da cognição e a... by Cynthia Arcoverde, Andréa Deslandes, Aryce Rangel, Andreza Rangel, Robson Pavão, Fortunée Nigri, Eliasz Engelhardt, Jerson Laks

“…BACKGROUND: The practice of physical activities has proved to be an efficient strategy in the improvement of independency and cognitive functions in the elderly with Alzheimer's disease (AD). …”
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Gross Tonnage-Based Statistical Modeling and Calculation of Shipping Emissions for the Bosphorus Strait by Kaan Ünlügençoğlu

“…These EPA-estimated values served as dependent variables in the modeling process. The modeling framework followed a three-step strategy: (1) outlier detection using Rosner’s test to reduce the influence of outliers on model accuracy, (2) curve fitting with 12 regression models representing four curve types—polynomial (e.g., linear, quadratic), concave/convex (e.g., exponential, logarithmic), sigmoidal (e.g., logistic, Gompertz, Weibull), and spline-based (e.g., cubic spline, natural spline)—to capture diverse functional relationships between GT and emissions, and (3) model comparison using difference performance metrics to ensure a comprehensive assessment of predictive accuracy, consistency, and bias. …”
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Improved representation of soil moisture processes through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model by E. Fatima, E. Fatima, R. Kumar, S. Attinger, S. Attinger, M. Kaluza, O. Rakovec, O. Rakovec, C. Rebmann, C. Rebmann, R. Rosolem, R. Rosolem, S. E. Oswald, L. Samaniego, L. Samaniego, S. Zacharias, M. Schrön

“…<p>Profound knowledge of soil moisture and its variability plays a crucial role in hydrological modelling to support agricultural management, flood and drought monitoring and forecasting, and groundwater recharge estimation. …”
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Assessing the stability of indoor farming systems using data outlier detection by Jean Pompeo, Ziwen Yu, Chi Zhang, Songzi Wu, Ying Zhang, Celina Gomez, Melanie Correll

“…Ensuring data quality in CEA systems is essential, as it affects system stability and operational efficiency. This research aims to assess system stability by analyzing the correlation between cumulative agricultural operations (Agr.Ops) and air temperature data variability.MethodsThe methodology involved collecting air temperature data from IoT sensors in the CEA system throughout lettuce cultivation trials. …”
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