Entering the Emperor’s Villa: an integrated methodology to enrich cognitive accessibility of an archaeological site by Silvia Bertacchi, Benedetta Adembri

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A Reanalysis Precipitation Integration Method Utilizing the Generalized Three-Cornered Hat Approach and High-Resolution, Gauge-Based Datasets by Lilan Zhang, Xiaohong Chen, Bensheng Huang, Jie Liu, Daoyi Chen, Liangxiong Chen, Rouyi Lai, Yanhui Zheng

“…The development of high-precision, long-term, hourly-scale precipitation data is essential for understanding extreme precipitation events. …”
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3-D UXSE-Net for Seismic Channel Detection Based on Satellite Image Enhanced Synthetic Datasets by Xinke Zhang, Yihuai Lou, Naihao Liu, Daosheng Ling, Yunmin Chen

“…However, insufficient labeled training data remains a key challenge for refining DL models. …”
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Credit Scoring Prediction Using Deep Learning Models in the Financial Sector by Xi Shi, Dingfen Tang, Yike Yu

“…The increasing complexity and volume of financial and behavioral data in modern credit scoring and risk assessment present significant challenges to traditional modeling methods. …”
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Estimating reference intervals from an IPD meta-analysis using quantile regression by Ziren Jiang, Haitao Chu, Zhen Wang, M. Hassan Murad, Lianne K. Siegel

“…Methods With the availability of individual participant data (IPD), non-parametric methods can be used to estimate reference intervals without any distributional assumptions. …”
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The role of mathematics in transdisciplinarity content of modern education by V. A. Testov, E. A. Perminov

“…The result is transdisciplinary branches of science such as cybernetics, disaster theory, synergetics, artificial intelligence, big data, etc. All these concepts have been developed on the basis of the achievements of mathematics over the past 70-80 years, the era of mathematical sciences. …”
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Enabling scalable single-cell transcriptomic analysis through distributed computing with Apache spark by Asif Adil, Namrata Bhattacharya, Aadam, Naveed Jeelani Khan, Mohammed Asger

“…We demonstrate the utility of our framework and algorithms through a series of experiments on real-world scRNA-seq data. Overall, our results suggest that scSPARKL represents a powerful and flexible tool for the analysis of single-cell transcriptomic data, with broad applications across the fields of biology and medicine.…”
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Redefining customer connections in the UAE’s digital era: A study on emerging technological synergies by Hussam Ali, Ehab Haikal

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Graph-Based Radiomics Feature Extraction From 2D Retina Images by Ofelio Jorreia, Nuno Goncalves, Rui Cortesao

“…The radiomics approach addresses this need by combining quantitative image analysis with Machine Learning (ML) techniques, further enhancing Explainable Artificial Intelligence (XAI) for clinical applications. While working with two-dimensional (2D) images derived from volumetric data offers computational advantages, accurately estimating structural properties within these images remains challenging. …”
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Prediction of the Next Solar Rotation Synoptic Maps Using an Artificial Intelligence–based Surface Flux Transport Model by Hyun-Jin Jeong, Mingyu Jeon, Daeil Kim, Youngjae Kim, Ji-Hye Baek, Yong-Jae Moon, Seonghwan Choi

“…Using synthetic input data with bipolar structures, we confirm that our model successfully reproduces differential rotation and meridional flow. …”
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Dataset Construction Using Item Response Theory for Educational Machine Learning Competitions by Takeaki Sakabe, Yuko Sakurai, Emiko Tsutsumi, Satoshi Oyama

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AlzheimerViT: harnessing lightweight vision transformer architecture for proactive Alzheimer’s screening by C. Kishor Kumar Reddy, Hafsa Ihteshamuddin Ahmed, Muhammad Mohzary, Muhammad Mohzary, T. Monika Singh, Mohammed Shuaib, Shadab Alam, Hani Mohammed Alnami, Hani Mohammed Alnami

“…It also achieves a Kappa Score of 97.2% and an AUC ROC Score of 99%.ConclusionThis paper, along with comprehensive data pre-processing and augmentation, represents one of the major steps toward achieving more robust and clinically applicable models for Alzheimer’s disease prediction. …”
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Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure by Luis Martí-Bonmatí, Ignacio Blanquer, Manolis Tsiknakis, Gianna Tsakou, Ricard Martinez, Salvador Capella-Gutierrez, Sara Zullino, Janos Meszaros, Esther E. Bron, Jose Luis Gelpi, Katrine Riklund, Linda Chaabane, Heinz-Peter Schlemmer, Mario Aznar, Patricia Serrano Candelas, Peter Gordebeke, Monika Hierath, the EUCAIM Consortium, European Society of Radiology

“…In summer 2024, the EUCAIM project released the first prototype of an EU-wide infrastructure, with a comprehensive dashboard integrating applications for dataset discovery, federated search, data access request, metadata harvesting, annotation, secure processing environments and federated processing. …”
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qPRF: A system to accelerate population receptive field modeling by Sebastian Waz, Yalin Wang, Zhong-Lin Lu

“…., 2013) on a benchmark of data from the Human Connectome Project (HCP; Van Essen et al. (2013). …”
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A recurrent YOLOv8-based framework for event-based object detection by Diego A. Silva, Kamilya Smagulova, Ahmed Elsheikh, Mohammed E. Fouda, Ahmed M. Eltawil

“…ReYOLOv8 incorporates a low-latency, memory-efficient method for encoding event data called Volume of Ternary Event Images (VTEI) and introduces a novel data augmentation technique based on Random Polarity Suppression (RPS) optimized for event-based sensors and tailored to leverage the unique attributes of event data. …”
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MOLUNGN: a multi-omics graph neural network for biomarker discovery and accurate lung cancer classification by Daifeng Zhang, Daifeng Zhang, Daifeng Zhang, Guoqiang Bian, Guoqiang Bian, Guoqiang Bian, Yuanbin Zhang, Yuanbin Zhang, Jiadong Xie, Jiadong Xie, Chenjun Hu, Chenjun Hu, Chenjun Hu

“…This study aimed to systematically integrate biomedical datasets, particularly incorporating traditional Chinese medicine (TCM)-associated multi-omics data, employing advanced deep-learning methods enhanced by graph attention mechanisms. …”
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Assessing the Efficiency of Transformer Models with Varying Sizes for Text Classification: A Study of Rule-Based Annotation with DistilBERT and Other Transformers by Arafet Sbei, Khaoula ElBedoui, Walid Barhoumi

“…The proposed hybrid method offers a robust and adaptable solution for sentence annotation pipelines, enhancing performance in diverse natural language processing applications with limited labeled data. Code is available at https://github.com/arafet/Text-annotation-using-rule-based-method-and-Transformers.…”
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DeepAptamer: Advancing high-affinity aptamer discovery with a hybrid deep learning model by Xin Yang, Chi Ho Chan, Shanshan Yao, Hang Yin Chu, Minchuan Lyu, Ziqi Chen, Huan Xiao, Yuan Ma, Sifan Yu, Fangfei Li, Jin Liu, Luyao Wang, Zongkang Zhang, Bao-Ting Zhang, Lu Zhang, Aiping Lu, Yaofeng Wang, Ge Zhang, Yuanyuan Yu

“…Trained on comprehensive SELEX data, DeepAptamer outperformed existing models in accuracy as substantiated by experimental evidence. …”
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Googling Patients by Emily Beer

“…Despite this, misunderstandings about HIPAA abound, even among clinicians.[11] It has even been reported that some inaccurately claim that PTG violates HIPAA .[12] Other statutes also protect health data in a variety of ways. For example, the FTC Act creates an obligation to maintain appropriate security of health data and requires entities to keep promises they make about privacy.[13] The Health Breach Notification Rule contains notice requirements for data breaches involving certain health information.[14] Additionally, the doctor-patient privilege protects confidential information from disclosure, and the exact confines of the privilege depend on the applicable statutes.[15] As these examples demonstrate, there are many different legal requirements that concern privacy and confidentiality in the health sphere. …”
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Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm by Roozbeh Moazenzadeh, Okan Mert Katipoğlu, Ahmadreza Shateri, Hamid Nasiri, Mohammed Abdallah

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