NavBLIP: a visual-language model for enhancing unmanned aerial vehicles navigation and object detection by Ye Li, Li Yang, Meifang Yang, Fei Yan, Tonghua Liu, Chensi Guo, Rufeng Chen

“…Furthermore, NavBLIP employs a multimodal control strategy that dynamically selects context-specific features to optimize real-time performance, ensuring efficiency in high-stakes operations.Results and discussionExtensive experiments on benchmark datasets such as RefCOCO, CC12M, and Openlmages reveal that NavBLIP outperforms existing state-of-the-art models in terms of accuracy, recall, and computational efficiency. …”
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Investigating the correlation of hip circumference to cardiovascular disease and type‐2 diabetes using Mendelian randomization by Hongtao Liu, Zhaoyu Li, Su Yan, Shaopeng Ming

“…Main Outcome Measures Publicly available summary statistics datasets from GWAS meta‐analyses were used, with HC and HC adjusted for body mass index (BMI) as exposures. …”
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Identification of GPD1L as a Potential Prognosis Biomarker and Associated with Immune Infiltrates in Lung Adenocarcinoma by Zhengyang Fan, Song Wu, Hongyang Sang, Qianping Li, Shaofei Cheng, Hongling Zhu

“…In this study, following an examination of the TGCA datasets, we found that GPD1L displayed a dysregulated state in a wide variety of cancers; this led us to believe that GPD1L is an essential regulator in the progression of malignancies. …”
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High Expression of Ten Eleven Translocation 1 Is Associated with Poor Prognosis in Hepatocellular Carcinoma by Haopeng Wen, Tengfei Ji, Liteng Lin, Nan Cheng, Kangshun Zhu, Liangqi Cao

“…Materials and Methods. Four independent datasets with gene expression data and clinical data of HCC samples were downloaded from public databases. …”
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Factors associated with, and variations in, COVID-19 hospital death rates in England’s first two waves: observational study by Alex Bottle, Paul Aylin, Stephen Brett, Puji Faitna

“…To quantify the correlation between hospitals’ first and second wave death rates.Design Observational study using administrative data.Setting Acute non-specialist hospitals in England.Participants All patients admitted with a primary diagnosis of COVID-19.Primary and secondary outcomes In-hospital death.Results Hospital Episode Statistics (HES) data were extracted for all acute hospitals in England for COVID-19 admissions from March 2020 to March 2021. …”
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A foundation systematic review of natural language processing applied to gastroenterology & hepatology by Matthew Stammers, Balasubramanian Ramgopal, Abigail Owusu Nimako, Anand Vyas, Reza Nouraei, Cheryl Metcalf, James Batchelor, Jonathan Shepherd, Markus Gwiggner

“…Therefore, greater clinical engagement, collaboration, and open sharing of appropriate datasets and code are needed.…”
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Identification and Validation of the Pyroptosis-Related Hub Gene Signature and the Associated Regulation Axis in Diabetic Keratopathy by Yi Cui, Li Wang, Wentao Liang, Li Huang, Shuting Zhuang, Hong Shi, Nuo Xu, Jianzhang Hu

“…Intersection of DEGs and pyroptosis-related datasets showed 33 differentially expressed pyroptosis-related genes (DEPRGs) associated with pathways such as IL-17, NOD-like receptor, TNF, and Toll-like receptor signaling. …”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…As environmental sciences increasingly rely on complex datasets, machine learning (ML) has become crucial for identifying patterns and relationships. …”
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DGL-STFA: Predicting lithium-ion battery health with dynamic graph learning and spatial–temporal fusion attention by Zheng Chen, Quan Qian

“…Extensive experiments were conducted on the NASA and CALCE battery datasets, comparing this framework with traditional time-series prediction methods and other graph-based prediction methods. …”
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EPRNG: Effective Pseudo-Random Number Generator on the Internet of Vehicles Using Deep Convolution Generative Adversarial Network by Chenyang Fei, Xiaomei Zhang, Dayu Wang, Haomin Hu, Rong Huang, Zejie Wang

“…In this paper, we propose an Effective Pseudo-Random Number Generator (EPRNG) which exploits a deep convolution generative adversarial network (DCGAN)-based approach using our processed vehicle datasets and entropy-driven stopping method-based training processes for the generation of pseudo-random numbers. …”
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Impacts of Strategic Mobility Restrictions Policies during 2020 COVID-19 Outbreak on Brazil’s Regional Air Quality by Anderson P. Rudke, Daniela S. de Almeida, Ronaldo A. Alves, Alexandra Beal, Leila D. Martins, Jorge A. Martins, Ricardo Hallak, Taciana T. de Almeida Albuquerque

“…Therefore, air quality (CO, NO2, PM10, PM2.5, and O3) and urban mobility datasets available in five populous Brazilian states (São Paulo, Rio de Janeiro, Espírito Santo, Paraná, and Rio Grande do Sul) were analyzed. …”
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A Lightweight CNN-Transformer Implemented via Structural Re-Parameterization and Hybrid Attention for Remote Sensing Image Super-Resolution by Jie Wang, Hongwei Li, Yifan Li, Zilong Qin

“…Moreover, the distinctive architectures of transformers, their extensive parameter counts, and their reliance on large-scale training datasets impose constraints on transformer applications in remote sensing image feature extraction tasks. …”
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LAMB1 promotes proliferation and metastasis in nasopharyngeal carcinoma and shapes the immune-suppressive tumor microenvironment by Enzi Feng, Xinyu Yang, Jie Yang, Qianqian Qu, Xiaojiang Li

“…However, the role of LAMB1 in Nasopharyngeal Carcinoma (NPC) remains unknown. Methods: Three NPC datasets were utilized to identify LAMB1 as a targeted gene. …”
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The complete mitochondrial genomes of five critical phytopathogenic Bipolaris species: features, evolution, and phylogeny by Xinzheng Song, Yuehua Geng, Chao Xu, Jiaxin Li, Yashuang Guo, Yan Shi, Qingzhou Ma, Qiang Li, Meng Zhang

“…Phylogenetic analysis based on combined mitochondrial gene datasets showed that the five Bipolaris species formed well-supported topologies. …”
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A novel graph neural network based approach for influenza-like illness nowcasting: exploring the interplay of temporal, geographical, and functional spatial features by Jiajia Luo, Xuan Wang, Xiaomao Fan, Yuxin He, Xiangjun Du, Yao-Qing Chen, Yang Zhao

“…Results Our approach for predicting influenza outbreaks achieves competitive performance on real-world datasets (Corr = 0.8202; RMSE = 0.0017; MAE = 0.0013; MAPE = 0.0966), surpassing established baselines. …”
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A systematic review of the impact of artificial intelligence on educational outcomes in health professions education by Eva Feigerlova, Hind Hani, Ellie Hothersall-Davies

“…There was insufficient information on training datasets and copyright issues. Conclusions The results of the analysis show that the current evidence regarding measurable educational outcomes of AI-powered interventions in health professions education is poor. …”
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Efficient and Secure Traffic Scheduling Based on Private Sketch by Yang Chen, Huishu Wu, Xuhao Ren

“…Experimental evaluations on real and synthetic datasets demonstrate that ESTS significantly improves the accuracy of feature distribution estimation and privacy preservation. …”
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Geospatial Modelling for Estimation of PM2.5 Concentrations in Two Megacities in Peninsular India by V. P. Lavanyaa, S. Varshini, Souvik Sankar Mitra, Kiran M. Hungund, Rudrodip Majumdar, R. Srikanth

“…This model is based on covariates such as aerosol optical depth (AOD), meteorological parameters, and Land-use-Land-cover (LULC) variables and is validated with extensive datasets from continuous and manual air quality monitoring stations through a 10-fold cross-validation process. …”
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The Tasmanian Estuary Perch Population—A Threatened Species? by Jonah L. Yick, Bryan Van Wyk, James Haddy

“…This study also confirms this population has a delayed spawning season in comparison to mainland populations, with growth models and tag recaptures (32 fish) demonstrating a very slow but sexually dimorphic growth rate. By combining the datasets of the 2014/15 and 2023 survey, we present an updated understanding of the biology and population dynamics of this unique Tasmanian population, which has previously never been published. …”
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Association of objective and subjective socioeconomic markers with cognitive impairment among older adults: cross-sectional evidence from a developing country by Shobhit Srivastava, T Muhammad, TV Sekher

“…Objective This study explored how various markers of objective and subjective socioeconomic status (SES) are associated with cognitive impairment among older Indian adults.Design A cross-sectional study was conducted using large nationally representative survey data.Setting and participant This study used data from the Longitudinal Ageing Study in India (2017–2018). …”
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