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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No significant links between somatognosia, stereognosia, and hypermobility: sensory processing unlikely to drive common complaints in hypermobile population by Ivana Hanzlíková, Aneta Ruská, Kristýna Jančíková, Kim Hébert-Losier

“…These sensory processing functions are unlikely to contribute to the common complaints reported by hypermobile individuals. …”
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The effect of water soluble pentosanes on baking properties of winter rye by E. N. Shabolkina, A. A. Bisharev, N. V. Anisimkina, M. V. Belyaeva

“…Estimation of the variation coefficients showed that non-starch polysaccharides influence by genotypic and environmental factors are characterized by low variability CVf = 8.2%. …”
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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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Reconstruction of U.S. Regional-Scale Soybean SIF Based on MODIS Data and BP Neural Network by YAO Jianen, LIU Haiqiu, YANG Man, FENG Jinying, CHEN Xiu, ZHANG Peipei

“…The Pearson correlation coefficient between the original OCO-2 SIF data and MODIS GPP stood were at a modest 0.53. …”
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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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Interaction of integral parameters of physical state and biological age of students aged 17-19 years old in the process of adaptation to standard and experimental physical educatio... by Oleksandr Pryimakov, Marek Sawczuk, Stanislav Prysiazhniuk, Georgiy Korobeynikov, Nataliya Mazurok

“…The degree of BA reduction under the influence of the studied factors is most pronounced in the EG of girls and boys. The variability of the group of PD and PF indices is accompanied by the variability of most of the BA parameters’ dispersion in all studied groups of students. …”
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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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Impact of Body Image Perception on Behavioral Outcomes in Chinese Adolescent and Young Adult Survivors of Sarcoma by Yihui Wei, Chung Tin Ma, Michael Can Heng Li, Keary Rui Zhou, Herbert Ho Fung Loong, Kwok Chuen Wong, Chi Kong Li, Yin Ting Cheung

“…The significant risk factors associated with body image dissatisfaction were being female (standardized coefficient estimate [Est] = 0.21, SE = 0.10; p = 0.047), surgery treatment (Est = 0.19, SE = 0.09; p = 0.046), and worse family functioning (Est = 0.27, SE = 0.10, p = 0.013). …”
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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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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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Animal welfare and biosecurity correlation in buffalo farm evaluated by ClassyFarm system by Domenico Vecchio

“…The two variables were positively correlated (Spearman’s Rho=0.501; p<0.001). …”
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