A Novel Multi-Dynamic Coupled Neural Mass Model of SSVEP by Hongqi Li, Yujuan Wang, Peirong Fu

“…Steady-state visual evoked potential (SSVEP)-based brain—computer interfaces (BCIs) leverage high-speed neural synchronization to visual flicker stimuli for efficient device control. While SSVEP-BCIs minimize user training requirements, their dependence on physical EEG recordings introduces challenges, such as inter-subject variability, signal instability, and experimental complexity. …”
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Improving Monitoring of Indoor RF-EMF Exposure Using IoT-Embedded Sensors and Kriging Techniques by Randa Jabeur, Alaa Alaerjan

“…These networks consist of numerous sensor nodes, often deployed in challenging terrains where maintenance is difficult. Efficient monitoring approaches are essential to maximize the functionality and lifespan of each sensor node, thereby improving the overall performance of the WSN. …”
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“Why would I bother?” Understanding prosumer motivations and engagement in renewable energy communities: a qualitative study of polish photovoltaic installation owners by Maksymilian Bielecki, Ewa Neska, Anna Kowalska-Pyzalska

“…The development and efficient functioning of RECs depend not only on technical or economic factors but also on numerous socio-psychological variables deeply rooted in local historical, political, economic, and cultural contexts. …”
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Effects of curing age and magnesium slag grinding time on mechanical properties and hydration characteristics of magnesium slag-based backfill materials by Xiaobing Yang, Jian Yang, Xi Wang, Shenghua Yin, Zepeng Yan, Xizhi Zhang, Gongcheng Li, Xun Chen, Yaobin Qi, Wei Chen

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Dimensions-Reduced Volterra Digital Pre-Distortion Based On Orthogonal Basis for Band-Limited Nonlinear Opto-Electronic Components by Hananel Faig, Yaron Yoffe, Eyal Wohlgemuth, Dan Sadot

“…Here, we propose the use of orthogonal polynomial basis functions for efficient DPD implementation. The orthogonal basis enables the estimation of each coefficient separately, which provides a significant computational gain. …”
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Mathematical crystal chemistry II: Random search for ionic crystals and analysis on oxide crystals registered in ICSD by Ryotaro Koshoji

“…Additionally, discrete variables and constraint functions, which give a choice of creatable types of geometrical constraints depending on the spatial order of atoms, are implemented to formalize the feasible atomic environment, such as the composition of coordination polyhedra, resulting in acceleration of structure search and decrease of the number of local minima. …”
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Land-Cover Semantic Segmentation for Very-High-Resolution Remote Sensing Imagery Using Deep Transfer Learning and Active Contour Loss by Miguel Chicchon, Francisco James Leon Trujillo, Ivan Sipiran, Ricardo Madrid

“…We assessed the U-Net-scSE, FT-U-NetFormer, and DC-Swin architectures, incorporating transfer learning and active contour loss functions to improve performance on semantic segmentation tasks. …”
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Removal of <i>para</i>-Phenylenediamine (PPD) Dye from Its Aqueous Solution by Adsorption Using the Activated Carbon Nanoparticles by Shabaa Fayyad Bdewi, Hanaa Hassan Hussein, Shireen Abdulmohsin Azeez

“…This study focused on the development of an efficient preparation method of activated carbon for the removal of para-phenylenediamine (PPD) dye in an aqueous solution. …”
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Complementing Dynamical Downscaling With Super‐Resolution Convolutional Neural Networks by Deeksha Rastogi, Haoran Niu, Linsey Passarella, Salil Mahajan, Shih‐Chieh Kao, Pouya Vahmani, Andrew D. Jones

“…Modifications, such as incorporating elevation data and data pre‐processing enhances overall model performance, while using exponential and quantile loss functions improve the simulation of extremes. Our findings show SRCNN models efficiently and skillfully downscale precipitation from GCMs. …”
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Agronomic Information Extraction from UAV-Based Thermal Photogrammetry Using MATLAB by Francesco Paciolla, Giovanni Popeo, Alessia Farella, Simone Pascuzzi

“…Nowadays, these sensors can be integrated as payloads on unmanned aerial vehicles, providing high spatial and temporal resolution, to deeply understand the variability of crop and soil conditions. However, few commercial software programs, such as PIX4D Mapper, can process thermal images, and their functionalities are very limited. …”
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Multimodality Data Integration in Epilepsy by Otto Muzik, Diane C. Chugani, Guangyu Zou, Jing Hua, Yi Lu, Shiyong Lu, Eishi Asano, Harry T. Chugani

“…Moreover, an effort was made to derive quantitative variables (such as the spatial proximity index, SPI) characterizing the relationship between complementing modalities on a more generic level as a prerequisite for efficient data mining strategies. …”
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AngleCam: Predicting the temporal variation of leaf angle distributions from image series with deep learning by Teja Kattenborn, Ronny Richter, Claudia Guimarães‐Steinicke, Hannes Feilhauer, Christian Wirth

“…The plausibility of the predicted leaf angle time series was underlined by its close relationship with environmental variables related to transpiration. The evaluations confirm that AngleCam is a robust and efficient method to track leaf angles under field conditions. …”
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Orientation reversal and the Chern-Simons natural boundary by Griffen Adams, Ovidiu Costin, Gerald V. Dunne, Sergei Gukov, Oğuz Öner

“…Resurgence analysis identifies as primary objects Mordell integrals: up to changes of variables, they are Laplace transforms of resurgent functions. …”
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Estimation of carbon sequestration capacity of urban green infrastructure by fusing multi-source remote sensing data by Jiahui Chang, Zhenfeng Shao, Jinyang Wang, Zhu Mao, Tao Cheng, Xiaodi Xu, Qingwei Zhuang

“…Urban green infrastructure significantly contributes to the carbon storage functions of urban ecosystems. Accurate selection and efficiently integrating remote sensing data are paramount for evaluating carbon storage at the small-scale of urban green infrastructure. …”
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EEGUnity: Open-Source Tool in Facilitating Unified EEG Datasets Toward Large-Scale EEG Model by Chengxuan Qin, Rui Yang, Wenlong You, Zhige Chen, Longsheng Zhu, Mengjie Huang, Zidong Wang

“…To tackle the challenges, this paper introduces EEGUnity, an open-source tool that incorporates modules of "EEG Parser", "Correction", "Batch Processing", and "Large Language Model Boost". Leveraging the functionality of such modules, EEGUnity facilitates the efficient management of multiple EEG datasets, such as intelligent data structure inference, data cleaning, and data unification. …”
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Optimization of Mangiferin extraction from Mangifera Indica leaves Peruvian Criollo variation using ultrasound assisted surface response methodology by Elena Sofia Espinoza Rodríguez, Stephanie Elena Sosa Pulcha, Naysha Y. M․ Elguera, Abdel Alejandro Portocarrero Banda, Hugo Guillermo Jiménez Pacheco

“…Additionally, FTIR analysis demonstrated that the extracted mangiferin preserved key functional groups such as hydroxyl (-OH), carbonyl (C = O), and aromatic C = C bonds. …”
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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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A Fractional Time–Space Stochastic Advection–Diffusion Equation for Modeling Atmospheric Moisture Transport at Ocean–Atmosphere Interfaces by Behrouz Parsa Moghaddam, Mahmoud A. Zaky, António Mendes Lopes, Alexandra Galhano

“…The framework employs the Caputo fractional derivative to represent temporal persistence and the fractional Laplacian to model non-local turbulent diffusion, and incorporates a stochastic term with a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1</mn><mo>/</mo><mi>f</mi></mrow></semantics></math></inline-formula> power spectral density to simulate environmental variability. An efficient numerical solution methodology is derived utilizing complementary Fourier and Laplace transforms, which elegantly converts spatial fractional operators into algebraic expressions and yields closed-form solutions via Mittag–Leffler functions. …”
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Enhancing epidemic preparedness: a data-driven system for managing respiratory infections by Moslem Sarani, Katayoun Jahangiri, Manoochehr Karami, Mohammadreza Honarvar

“…Results Key data categories include individual-level variables, such as age, symptoms, and vaccination records, alongside population-level metrics like infection rates and regional vaccination coverage enabling functionalities such as identifying high-risk individuals, tracking infection dynamics, and optimizing resource allocation. …”
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Prediction of suicidal attempts among Chinese adolescents with mood disorders: a clinical study using a machine learning approach by Jianbing Li, Yinqiu Zhao, Chi Yang, Wenqing Li, Zhihao Huang, Changhe Fan

“…However, there is a need for studies of accurate and efficient SA models specifically for use in adolescents with mood disorders due to a lack of existing research integrating risk variables when predicting clinical SA. …”
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