Principal networks. by Jonathan D Clayden, Michael Dayan, Chris A Clark

“…This is an important problem because most cognitive functions would be expected to involve some but not all brain regions. …”
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Removal of caffeine from aqueous solution by green approach using Ficus Benjamina zero-valent iron/copper nanoparticles by Hossam Mohammed Abdel-Aziz, Rabie Saad Farag, Soha Ali Abdel-Gawad

“…Overall, FB-Fe/Cu is a committed green substance for removal Caffeine from aqueous solutions. Functional parameters affect investigated using the Linear regression analysis, we found them to account for over 98% of the variables affecting the removal procedure.…”
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Beyond Collaboration: The Impact of Partner Knowledge, Relational Skills, and Internal Communication on SME’s Performance by Marsiana Setiarini

“…Meanwhile, Internal Communication functions as a routine interaction mechanism that improves collaborative competence and accelerates organizational performance. …”
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Signatures of Rapidly Rotating Stars with Chemically Homogeneous Evolution in the First Galaxies by Boyuan Liu, Yves Sibony, Georges Meynet, Volker Bromm

“…We find that the rest-frame UV luminosity of star-forming galaxies can be significantly enhanced by a factor of  ∼3−6 when CHE stars above a minimum initial mass of ${m}_{\star ,\min }^{\mathrm{CHE}}\sim 2-10\,{M}_{\odot }$ account for more than half of the total stellar mass following a Salpeter initial mass function. As a result, the UV luminosity functions observed at z  ∼ 12−16 can be reproduced with less extreme values of star formation efficiency and UV luminosity stochastic variability. …”
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Optimization of household medical waste recycling logistics routes: Considering contamination risks. by Jihui Hu, Ying Zhang, Yanqiu Liu, Jiaqi Hou, Aobei Zhang

“…To enhance the realism of the simulation, traffic congestion is integrated into the vehicle speed function, reflecting the urban roads' variability. …”
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The modern concept of cognitive reserve by N. N. Koberskaya, G. R. Tabeeva

“…The main forms of cognitive impairment (CI) are characterized by a significant variability in the relationship between morphological changes and clinical manifestations. …”
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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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Slow and Quick Flow Models Explain the Temporal Dynamics of Daily Salinity in Streams by Thomas G. Westfall, Tim J. Peterson, Anna Lintern, Andrew W. Western

“…However, significant variability within high‐frequency data sets can result in poor explanation of temporal dynamics using the simple C‐Q equation. …”
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Accurate Sugarcane Detection and Row Fitting Using SugarRow-YOLO and Clustering-Based Spline Methods for Autonomous Agricultural Operations by Guiqing Deng, Fangyue Zhou, Huan Dong, Zhihao Xu, Yanzhou Li

“…This model introduces the WTConv convolutional modules to expand the sensory field and improve computational efficiency, adopts the iRMB inverted residual block attention mechanism to enhance the modeling capability of crop spatial structure, and uses the UIOU loss function to effectively mitigate the misdetection and omission problem in the region of dense and overlapping targets. …”
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Biomechanical Analysis of <i>Camellia oleifera</i> Branches for Optimized Vibratory Harvesting by Rui Pan, Ziping Wan, Mingliang Wu, Shikui Lu, Lewei Tang

“…The nonlinear least squares method, based on the hyperbolic tangent function, was employed to fit the bending load–deflection curves of the branches. …”
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Experiments in globalisation, food security and land use decision making. by Calum Brown, Dave Murray-Rust, Jasper van Vliet, Shah Jamal Alam, Peter H Verburg, Mark D Rounsevell

“…Both outcomes are subject to the responses of individual land managers to economic and environmental stimuli, and these responses are known to be variable and often (economically) irrational. We investigate the consequences of stylised food security policies and globalisation of agricultural markets on land use patterns under a variety of modelled forms of land manager behaviour, including variation in production levels, tenacity, land use intensity and multi-functionality. …”
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Assessment of RBFs Based Meshfree Method for the Vibration Response of FGM Rectangular Plate Using HSDT Model by Manish Srivastava, Jeeoot Singh

“…Radial basis functions (RBFs) with modified radial distance are proposed for vibration analysis of functionally graded materials (FGM) rectangular plates. …”
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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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Developing a machine learning model for fast economic optimization of solar power plants using the hybrid method of firefly and genetic algorithms, case study: optimizing solar the... by Ali Omidkar, Razieh Es'haghian, Hua Song

“…The objective functions were to optimize the exergy efficiency and the heat cost. …”
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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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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

“…In recent years, marine bacteria have emerged as a valuable and diverse source of these enzymes, owing to their unique adaptations to extreme marine conditions such as high salinity, variable potential of hydrogen, and fluctuating temperatures. …”
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The Design and Analysis of a Lightweight Robotic Arm Based on a Load-Adaptive Hoisting Mechanism by Ruchao Wang, Zhiguo Lu, Yiru Wang, Zhongqing Li

“…The proposed design integrates a spring-loaded rope and a variable radius reel into the gripper, enabling efficient load adaptability with minimal structural complexity. …”
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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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Impact of Product, Process, Organisational, and Marketing Innovation on Micro, Small and Medium Scale Enterprises' Sustainability by Erna Listyaningsih, Yuliansyah Yuliansyah, Rissa A. Martinouva, Febrianty Febrianty, Muazza Muazza, Shofia Amin, Etty Puji Lestari, Amirul Mukminin

“… Background: Rapid and efficient adoption of new business models is a key lever for improving an organisation's sustainable performance and one of the most important sources of enduring competitive edge. …”
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