Exploring the decentralized science ecosystem: insights on organizational structures, technologies, and funding by Francisco Díaz, Carolina Menchaca, Lukas Weidener

“…By identifying key patterns and areas for improvement, this study contributes to a deeper understanding of the factors driving success and sustainability in DeSci.…”
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Federated-Learning-Based Strategy for Enhancing Orbit Prediction of Satellites by Jiayi Tang, Wenxin Li, Qinchen Zhao, Hongmei Chi

“…Each satellite uses a Convolutional Neural Network (CNN) model to extract features from historical prediction error data. The server optimizes the global model through the Federated Averaging algorithm, learning more orbital patterns and enhancing accuracy. …”
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Enhancing prediction of crop yield and soil health assessment for sustainable agriculture using machine learning approach by Kapil Netaji Vhatkar, Shweta Ashish Koparde, Sonali Kothari, Jayesh Sarwade, Kishor Sakur

“…Back-propagation Neural Network (BPNN) is an SL algorithm applied for predicting complex patterns, especially in crop yield and soil health assessments. …”
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Ependymosarcoma presenting as recurrence in a primary left parieto-occipital ependymoma by Pallavi Prasad, Harshita Baranwal, Neelima Gupta

“…Gliosarcoma is described as a variant of IDH-wildtype glioblastoma, comprising a biphasic tissue pattern with alternating areas displaying glial and mesenchymal differentiation. …”
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Acute Liver Injury Is Independent of B Cells or Immunoglobulin M. by James A Richards, Martina Bucsaiova, Emily E Hesketh, Chiara Ventre, Neil C Henderson, Kenneth Simpson, Christopher O C Bellamy, Sarah E M Howie, Stephen M Anderton, Jeremy Hughes, Stephen J Wigmore

“…<h4>Background & aims</h4>Acute liver injury is a clinically important pathology and results in the release of Danger Associated Molecular Patterns, which initiate an immune response. Withdrawal of the injurious agent and curtailing any pathogenic secondary immune response may allow spontaneous resolution of injury. …”
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Forecasting Temperature Time Series Data Using Combined Statistical and Deep Learning Methods: A Case Study of Nairobi County Daily Temperature by John Kamwele Mutinda, Amos Kipkorir Langat, Samuel Musili Mwalili

“…In addition, the high R-squared value of 0.779234 indicates that approximately 77.92% of the variance in the observed data is explained by the model, showcasing its robustness and effectiveness in capturing the underlying patterns in temperature time series data. Overall, this study underscores the importance of VMD in preprocessing data to enhance feature representation and forecasting accuracy. …”
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Surface Damage Detection in Hydraulic Structures from UAV Images Using Lightweight Neural Networks by Feng Han, Chongshi Gu

“…The developed DL-based model integrates an enhanced Fast-SCNN backbone for efficient feature extraction, a Lightweight Feature Pyramid Attention (LFPA) module for multi-scale context enhancement, and an Edge Attention Module (EAM) for refined boundary localization. …”
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Clinical characteristics and epilepsy in genomic imprinting disorders: Angelman syndrome and Prader–Willi syndrome by Tzong-Shi Wang, Wen-Hsin Tsai, Li-Ping Tsai, Shi-Bing Wong

“…The distinctive gait pattern, excessive laughter, and characteristic electroencephalography features, which contain anterior-dominated, high-voltage triphasic delta waves intermixed with epileptic spikes, result in early suspicion of AS. …”
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Modeling Short-Term Drought for SPEI in Mainland China Using the XGBoost Model by Fanchao Zeng, Qing Gao, Lifeng Wu, Zhilong Rao, Zihan Wang, Xinjian Zhang, Fuqi Yao, Jinwei Sun

“…Accurate drought prediction is crucial for optimizing water resource allocation, safeguarding agricultural productivity, and maintaining ecosystem stability. This study develops a methodological framework for short-term drought forecasting using SPEI time series (1979–2020) and evaluates three predictive models: (1) a baseline XGBoost model (XGBoost1), (2) a feature-optimized XGBoost variant incorporating Pearson correlation analysis (XGBoost2), and (3) an enhanced CPSO-XGBoost model integrating hybrid particle swarm optimization with dual mechanisms of binary feature selection and parameter tuning. …”
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SPECIFIC TRAITS OF HUNGARIAN-UKRAINIAN POETRY TRANSLATION (BASED ON YURII SHKROBYNETS’ TRANSLATIONS) by Oksana Yu. Talabirchuk

“…Neither significant language differences nor national versification systems and related rhyming features become an obstacle, if the translator is well knowledgeable of them. …”
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Landscapes of Trade by Merten Nefs

“…The Dutch logistics complex since 1980 offers a critical European case for the analysis, due to the clear shifts in its spatial pattern and planning system, as well as a fierce and well-documented planning discourse featuring various information sources and actor networks. …”
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Topic modeling analysis of the Allen Human Brain Atlas by Letizia Pizzini, Filippo Valle, Matteo Osella, Michele Caselle

“…It is composed of many regions that exhibit specific distributions of cell types and distinct patterns of functional connections. This complexity is rooted in differential transcription. …”
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CONSTITUTIVE MODEL FOR TIMBER FRACTURE USED FOR FE SIMULATION OF LVL ARCH by Eliška Šmídová, Petr Kabele

“…Furthermore, the model can capture the most distinctive features of the crack pattern.…”
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Methylmap: visualization of modified nucleotides for large cohort sizes by Elise Coopman, Svenn D’Hert, Rosa Rademakers, Wouter De Coster

“…Understanding methylation patterns at the nucleotide level has become pivotal for advancing this field. …”
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Detection and location of EEG events using deep learning visual inspection. by Mohammad Amin Fraiwan

“…This signal contains a number of distinctive waveform patterns that reflect the subject's health state in relation to sleep, neurological disorders, memory functions, and more. …”
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Neuronal adaptation translates stimulus gaps into a population code. by Chun-Wei Yuan, Leila Khouri, Benedikt Grothe, Christian Leibold

“…Neurons in sensory pathways exhibit a vast multitude of adaptation behaviors, which are assumed to aid the encoding of temporal stimulus features and provide the basis for a population code in higher brain areas. …”
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Ecological portraits: Mapping functional spectra and space characteristics of birds in China by Fei Duan, Ming Gao, Shuyi Zhu, Xiaoli Shen, Sheng Li

“…The results showed that birds in China exhibited a clustered distribution pattern within the functional spectra and spaces. …”
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Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation by Zongqi Xia, Prerna Chikersal, Shruthi Venkatesh, Elizabeth Walker, Anind K Dey, Mayank Goel

“…Smartphone sensors recorded call activity, location, and screen use, while fitness trackers captured heart rate, sleep patterns, and step count. We extracted patient-level behavioral features and categorized them into 2 feature sets: one from the prediction period (called action) and one from the preceding period (called context). …”
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Addressing the emerging threat of Oropouche virus: implications and public health responses for healthcare systems by Olalekan John Okesanya, Blessing Olawumi Amisu, Olaniyi Abideen Adigun, Mohamed Mustaf Ahmed, Abdulmajeed Opeyemi Agboola, Tolga Kab, Gilbert Eshun, Bonaventure Michael Ukoaka, Tolutope Adebimpe Oso, Jerico Bautista Ogaya, Don Eliseo Lucero-Prisno

“…This paper delves into the epidemiology, clinical features, and transmission patterns of OROV, shedding light on the difficulties in diagnosing and managing the disease. …”
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Comparative evaluation of machine learning models for extreme river water level forecasting in Bangladesh: Implications for flood and drought resilience by Md Touhidul Islam, Sujan Chandra Roy, Nusrat Jahan, Al-Mahmud, Md Mazharul Islam, Abdullah Al Ferdaus, Kazunori Fujisawa, A.K.M. Adham

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