Multi-Objective Routing and Categorization of Urban Network Segments for Cyclists by Konstantinos Theodoreskos, Konstantinos Gkiotsalitis

“…Data collection methods include GPS tracking, field measurements, and qualitative approaches to understand cyclists’ behavior and preferences. Nine objective functions are constructed based on criteria related to safety and comfort, incorporating decision variables related to cyclists riding on sidewalks, capturing the complexity of urban cycling infrastructure. …”
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Antigenic characterization of the human immunodeficiency virus (HIV-1) envelope glycoprotein precursor incorporated into nanodiscs. by Kristen C Witt, Luis Castillo-Menendez, Haitao Ding, Nicole Espy, Shijian Zhang, John C Kappes, Joseph Sodroski

“…These results indicate that Env-NDs represent a potentially useful platform for investigating the structural, functional and antigenic properties of the HIV-1 Env trimer in a membrane context.…”
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Fault Estimation for Semi-Markov Jump Neural Networks Based on the Extended State Method by Lihong Rong, Yuexin Pan, Zhimin Tong

“…To alleviate network congestion and optimize communication resources, the Round-Robin protocol is adopted to schedule data transmission efficiently. By constructing a Lyapunov–Krasovskii functional and applying the discrete Wirtinger inequality, sufficient conditions are derived to ensure the mean square exponential stability and dissipative performance of the system. …”
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Agricultural Waste–Derived Biochar for Antibiotics Removal in Aqueous Environment: A Comprehensive Outlook by Varalakshmi Varatharajan, Karthik V., Selvakumar Periyasamy

“…The key elements influencing antibiotic adsorption on biochar, including surface chemistry, pyrolysis conditions, and environmental variables, were discussed in detail. This review focuses specifically on the functional modification of the biochar, the mechanism involved in antibiotic adsorption, and the scalability of this process. …”
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Bioactive compounds from tropical fruit by-products: Extraction, characterization and therapeutic potential by Niza Otero-Guzman, Ricardo Andrade-Pizarro

“…However, there are several challenges associted with the efficient extraction and accurate characterization of these compounds, including the complexity of plant matrices, variability in compound polarity, and the need for scalable, eco-friendly methods that preserve their bioactivity. …”
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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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