Dual-coding Contrastive Learning Based on the ConvNeXt and ViT Models for Morphological Classification of Galaxies in COSMOS-Web by Shiwei Zhu, Guanwen Fang, Chichun Zhou, Jie Song, Zesen Lin, Yao Dai, Xu Kong

“…Benefiting from its higher efficiency, this updated algorithm is well suited for application in future China Space Station Telescope missions.…”
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Predictors of food insecurity among older persons in selected cash-grant communities in Ghana: application of social-ecological model by Doris Ottie-Boakye, Sandra Ayivor, Margaret Appiah, Jesse Sey Ayivor

“…Data were analysed using descriptive and logistic regression. …”
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Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone by Yuyu Sun, Yuchen Zhang, Zhiguo Zhao

“…Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years. Practical implications – The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. …”
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Assessment of soil erosion and sediment transport index in the Awash River Basin, Ethiopia: an application of the USLE model and GIS techniques by Abayneh Gebremichael, Ephrem Gebremariam, Hayal Desta

“…The result of annual average soil loss shows a significant range from 0–31,049,739 t/h/y after analyzing of various soil, DEM, topographical and meteorological data, obtained from USGS and EMA. The broader implications of this finding are highlights the significant capacity of land management potential in study area. …”
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Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder by Yilu Zhao, Zhao Fu, Eric J. Barnett, Ning Wang, Kangfuxi Zhang, Xuping Gao, Xiangyu Zheng, Junbin Tian, Hui Zhang, XueTong Ding, Shaoxian Li, Shuyu Li, Qingjiu Cao, Suhua Chang, Yufeng Wang, Stephen V. Faraone, Li Yang

“…Furthermore, our CNN model exhibited good performance in an independent dataset, encouraged future studies and implied potential clinical applications.…”
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A comparative study of ultra-massive MIMO intelligent receivers with adversarial robustness and energy efficiency for 6G applications by Pushkar Nidagundi, Advesh Darvekar, Malik Amber, Ramesh R

“…Ultra-Massive Multiple Input Multiple Output (UM-MIMO) systems are pivotal for 6G wireless networks, enabling unprecedented data rates and spectral efficiency. However, optimizing these systems requires a careful balance between energy efficiency, spectral efficiency, and Bit Error Rate (BER) performance. …”
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Maximum-likelihood Regression with Systematic Errors for Astronomy and the Physical Sciences. II. Hypothesis Testing of Nested Model Components for Poisson Data by Massimiliano Bonamente, Dale Zimmerman, Yang Chen

“…A novel model of systematic errors for the regression of Poisson data is applied to hypothesis testing of nested model components with the introduction of a generalization of the Δ C statistic that applies in the presence of systematic errors. …”
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A Novel Hybridized Cluster-Based Geographical Opportunistic Routing Protocol for Effective Data Routing in Underwater Wireless Sensor Networks by B. Ragavi, V. Baranidharan, K. Ramash Kumar

“…These networks are employed to transmit the data with enhanced quality of service (QoS). However, efficient data routing is the most challenging obstacle in many underwater applications. …”
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Phylogenetic Relations and High-Altitude Adaptation in Wild Boar (<i>Sus scrofa</i>), Identified Using Genome-Wide Data by Shiyong Fang, Haoyuan Zhang, Haoyuan Long, Dongjie Zhang, Hongyue Chen, Xiuqin Yang, Hongmei Pan, Xiao Pan, Di Liu, Guangxin E

“…In this study, we analyzed genome-wide data from 93 wild boars compiled from various studies worldwide, including the QTP, southern and northern regions of China, Europe, Northeast Asia, and Southeast Asia, to explore their phylogenetic patterns and high-altitude adaptation based on genome-wide selection signal analysis and run of homozygosity (ROH) estimation. …”
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Integrative multi-omics data from early development to identify the genes and cell types underlying attention-deficit/hyperactivity disorder by Shufen Jiao, Li Bao, Xiaowen Lu, Yong Wu, Yichen Li

“…Additionally, we performed cell-type enrichment analysis to identify specific cell types implicated in ADHD. Results Our integrative analysis identified LSM6 and RPS26 as significantly associated with ADHD, based on eQTL data from fetal brain and iPSC-derived neurons. …”
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Harmonizing ground and UAV hyperspectral data: A novel spectral correction method for maximizing estimation models and datasets of ground hyperspectral by Zhonglin Wang, Pengxin Deng, Kairui Chen, Ying Xiong, Feng Yang, Cheng Wang, Zhixin Li, Biao Li, Yongjian Sun, Zongkui Chen, Zhiyuan Yang, Jun Ma

“…Importantly, the applicability and effectiveness of the CNC estimation models and the dataset of corrected hyperspectral were explored for hyperspectral images. …”
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An iteration-free approach for determining the average reservoir pressure and original gas in place by production data analysis: Methodology and field cases by Yang Wang, Shilong Yang, Hang Xie, Naichao Feng, Haiyang Yu

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Robust Synthetic Data Generation for Sequential Financial Models Using Hybrid Variational Autoencoder–Markov Chain Monte Carlo Architectures by Francesco Bruni Prenestino, Enrico Barbierato, Alice Gatti

“…Generating high-quality synthetic data is essential for advancing machine learning applications in financial time series, where data scarcity and privacy concerns often pose significant challenges. …”
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Transforming Quality Management with Industry 4.0 Technologies: A Meta-Analytic Review of AI, Blockchain, IoT, and Big Data by SOUAD LAHMINE, FATIMA BENNOUNA

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Digitalization of the Legal System: Opportunities and Challenges for Indonesia by Mochammad Tanzil Multazam, Aan Eko Widiarto

“…This study aims to analyze the impact and challenges of digitalization in the Indonesian legal system, focusing on its implications for legal education, data security, and professional readiness. …”
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Enhanced large-scale building extraction evaluation: developing a two-level framework using proxy data and building matching by Shenglong Chen, Yoshiki Ogawa, Chenbo Zhao, Yoshihide Sekimoto

“…Deep learning-based building extraction methods have widespread applications in diverse fields. However, the evaluation of large-scale extraction results remains challenging, due to traditional evaluation metrics rely on manually created ground-truth samples and the lack of comprehensive reference-building data for developing countries. …”
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Enhancing image security via chaotic maps, Fibonacci, Tribonacci transformations, and DWT diffusion: a robust data encryption approach by Mohammad Mazyad Hazzazi, Mujeeb Ur Rehman, Arslan Shafique, Amer Aljaedi, Zaid Bassfar, Aminu Bello Usman

“…Abstract In recent years, numerous image encryption schemes have been developed that demonstrate different levels of effectiveness in terms of robust security and real-time applications. While a few of them outperform in terms of robust security, others perform well for real-time applications where less processing time is required. …”
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Lentil plant disease and quality assessment: A detailed dataset of high-resolution images for deep learning researchMendeley Data by Eram Mahamud, Md Assaduzzaman, Shayla Sharmin

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CSTFNet: A CNN and Dual Swin-Transformer Fusion Network for Remote Sensing Hyperspectral Data Fusion and Classification of Coastal Areas by Dekai Li, Harold Neira-Molina, Mengxing Huang, Syam M.S., Yu Zhang, Zhang Junfeng, Uzair Aslam Bhatti, Muhammad Asif, Nadia Sarhan, Emad Mahrous Awwad

“…However, due to the high dimensionality of HSI data and the complexity of spectral-spatial feature extraction, achieving accurate results in coastal areas remains challenging. …”
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