Study on Intelligent Classing of Public Welfare Forestland in Kunyu City by Meng Sha, Hua Yang, Jianwei Wu, Jianning Qi

“…The main contributions of this work are as follows: A machine learning model was developed using integrated data from the Third National Land Survey of China, including forestry, grassland, and wetland datasets. Unlike previous approaches, the SVM model is optimized with Grid Search (GS), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) to automatically determine classification parameters, overcoming the limitations of manual rule-based methods. …”
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Causal Effects of Sleep Traits on Angina Pectoris: Mediation by Cardiovascular Risk Factors by Zeng C, Ke Y, Li H, Zhang C, Chen J, Chen M

“…Our study aims to declare the causality of sleep traits on AP by Mendelian randomization (MR) analyses.Methods: Genome-wide association study (GWAS) data of sleep traits (sleep duration, insomnia, nap during day, chronotype, getting up in morning, narcolepsy, snoring) were obtained from the UK Biobank. The AP datasets came from an analysis containing samples from the UK biobank, FinnGen, and BioBank Japan. …”
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Balancing Privacy and Utility in Split Learning: An Adversarial Channel Pruning-Based Approach by Afnan Alhindi, Saad Al-Ahmadi, Mohamed Maher Ben Ismail

“…The contributions of this research were validated and assessed using benchmark datasets. The experiments demonstrated the superior defense ability, against data reconstruction attacks, of the proposed approach in comparison with relevant state-of-the-art approaches. …”
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Revisiting ‘revisiting supervised methods for effort‐aware cross‐project defect prediction’ by Fuyang Li, Peixin Yang, Jacky Wai Keung, Wenhua Hu, Haoyu Luo, Xiao Yu

“…The authors use three classification evaluation metrics and seven effort‐aware metrics to assess the performance of methods on 11 PROMISE datasets comprehensively. The results show that (1) The classification before sorting (CBS+) defect density calculation strategy achieves the best overall performance. (2) Using balanced distribution adaption (BDA) and joint distribution adaptation (JDA) with the K‐nearest neighbour classifier to build the EACPDP model can find 15% and 14.3% more defective modules and 11.6% and 8.9% more defects while achieving the acceptable initial false alarms (IFA). (3) Better comprehensive classification performance of the methods can bring better EACPDP performance to some extent. (4) A flexible adjustment of the defect threshold λ of the CBS+ strategy contribute to different goals. …”
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Making sense of the L-shaped pore pressure ramps in Brunei: Compression-induced vertical fluid flow in the basin and its impact on the petroleum system by Udai Bhan Rai, Aminul Islam, Nick Hogg Mascall, Mohamed Ragab Shalaby

“…Overpressure prediction for exploratory drilling has become robust in most basins with increasing well control, high-quality seismic datasets, and proactive real-time overpressure monitoring while drilling. …”
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In Praise of Diversity in Participatory Heritage Planning Empowered by Artificial Intelligence: Windcatchers in Yazd by Mahda Foroughi, Tong Wang, Ana Pereira Roders

“…However, effectively involving diverse stakeholders and capturing the cultural significance they attribute to heritage remains a challenge, particularly when dealing with extensive datasets and multiple stakeholders. Although automated methods have shown potential in fields like digital humanities, their application in heritage planning is still limited. …”
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Key wound healing genes as diagnostic biomarkers and therapeutic targets in uterine corpus endometrial carcinoma: an integrated in silico and in vitro study by Fuchuan Jiang, Sajjad Ahmad, Sadia kanwal, Yasir Hameed, Qian Tang

“…Validation using TCGA datasets revealed consistent downregulation of these genes in UCEC samples, corroborated by immunohistochemical staining. …”
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An Investigation of Infrared Small Target Detection by Using the SPT–YOLO Technique by Yongjun Qi, Shaohua Yang, Zhengzheng Jia, Yuanmeng Song, Jie Zhu, Xin Liu, Hongxing Zheng

“…Some experiments on datasets such as infrared small object detection (IR-SOD) and infrared small target detection 1K(IRSTD-1K), etc. have been executed to verify the proposed algorithm; and the mean average precision of 94.0% and 69% under the condition of threshold at 0.5 and over a range from 0.5 to 0.95 is obtained, respectively. …”
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Advances in Light Field Spatial Super-Resolution: A Comprehensive Literature Survey by Wenqi Lyu, Hao Sheng, Wei Ke, Xiao Ma

“…We present a systematic review of 17 mainstream light field spatial super-resolution techniques, evaluating their performance across seven public datasets. Integrating experimental results, we specifically analyze the performance of deep learning-based super-resolution algorithms at various magnification levels. …”
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QAR Data Imputation Using Generative Adversarial Network with Self-Attention Mechanism by Jingqi Zhao, Chuitian Rong, Xin Dang, Huabo Sun

“…Experimental results on real datasets demonstrate that the model can reasonably impute the missing values in QAR data with excellent results.…”
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MFCEN: A lightweight multi-scale feature cooperative enhancement network for single-image super-resolution by Jiange Liu, Yu Chen, Xin Dai, Li Cao, Qingwu Li

“…Extensive experiments on commonly used image super-resolution datasets further validated the effectiveness of the network.…”
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Inpatient service utilization amongst infants diagnosed with Respiratory Syncytial Virus infection (RSV) in the United States. by Jason R Gantenberg, Kathryn D Thompson, Robertus van Aalst, David M Smith, Megan Richards, Christopher B Nelson, William V La Via, Sandra S Chaves, Angela M Bengtson, David A Savitz, Andrew R Zullo

“…<h4>Methods</h4>In this retrospective observational study, we analyzed three different administrative claims datasets to examine healthcare service utilization during RSV hospitalizations among infants. …”
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Crotonylation-Related Prognostic Model of Esophageal Squamous Cell Carcinoma Based on Transcriptome Analysis and Single-Cell Sequencing Analysis by Lin RY, Chen RP, Lin FQ

“…This study aimed to investigate the role of crotonylation-related genes (CRGs) in ESCC using bioinformatics approaches.Methods: We included three ESCC datasets and 24 CRGs. Differentially expressed genes (DEGs) from TCGA-ESCA were intersected with key module genes related to CRGs to identify candidate genes. …”
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Transgenerational epigenetic heritability for growth, body composition, and reproductive traits in Landrace pigs by Andre C. Araujo, Jay S. Johnson, Jason R. Graham, Jeremy Howard, Yijian Huang, Hinayah R. Oliveira, Luiz F. Brito

“…Therefore, we aimed to estimate transgenerational epigenetic heritability, percentage of resetting epigenetic marks, genetic parameters, and predicting breeding values using genetic and epigenetic models for growth, body composition, and reproductive traits in Landrace pigs using routinely recorded datasets. Birth and weaning weight, backfat thickness, total number of piglets born, and number of piglets born alive (BW, WW, BF, TNB, and NBA, respectively) were investigated. …”
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Plant-based diets and total and cause-specific mortality: a meta-analysis of prospective studies by Qiwang Mo, Jizhongrong Wu, Yi Lu, Xiao Zhang

“…Dose–response meta-analysis was also performed for studies reporting categorical risk estimates for at least three quantitative levels of PDIs, hPDIs and uPDIs.ResultsA total of 11 eligible cohort studies (13 datasets) were eventually included in this meta-analysis. …”
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Seasonal and Regional Differences in Extreme Rainfall Events and Their Contribution to the World’s Precipitation: GPM Observations by Shailendra Kumar, Yamina Silva, Aldo S. Moya-Álvarez, Daniel Martínez-Castro

“…In the present study, five-year of precipitation features (PFs) datasets, based on Global Precipitation Measurement (GPM), are used to investigate the global and regional characteristics of extreme rainfall events (EREs). …”
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GS-DTA: integrating graph and sequence models for predicting drug-target binding affinity by Junwei Luo, Ziguang Zhu, Zhenhan Xu, Chuanle Xiao, Jingjing Wei, Jiquan Shen

“…Conclusions The results show that GS-DTA achieves good performance in terms of MSE, CI, and r2 m on the Davis and KIBA datasets, improving the accuracy of DTA prediction.…”
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Advanced characterization of deforestation frontiers in Nigeria utilizing deep learning and Bayesian approaches with sentinel-1 SAR imagery by Isiaka Lukman Alage, Yumin Tan, Ahmed Wasiu Akande, Agus Suprijanto

“…Our method includes: (1) evaluating a spatiotemporal deep learning algorithm, particularly U-Net and DeepLab3, with various ResNet backbones across eight temporal datasets for delineating deforestation; (2) employing a Bayesian temporal advancing approach to combine deforestation detection from the Sentinel-1 and (3) conducting frontier analysis based on biannual results to assess patch size distribution and formation speed from 2020 to 2023. …”
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Use of 18F-NaF PET in the staging of skeletal metastases of newly diagnosed, high-risk prostate cancer patients: a nationwide cohort study by Christian Torp-Pedersen, Mette Nørgaard, Helle D Zacho, Lars J Petersen, Anna Winther Mogensen, Marie T Pank

“…Objective To determine whether preoperative staging of high-risk prostate cancer with 18F-sodium-fluoride (18F-NaF) positron emission tomography (PET) reduces the risk of skeletal metastases.Design Nationwide, population-based cohort study using real-world data.Setting The study used national health registries, including all sites in Denmark from 2011 to 2018.Participants Newly diagnosed high-risk prostate cancer patients who underwent radical prostatectomy from 2011 to 2018. …”
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Psychological and Behavioral Insights From Social Media Users: Natural Language Processing–Based Quantitative Study on Mental Well-Being by Xingwei Yang, Guang Li

“…We empirically evaluated the effectiveness of our framework by applying machine learning models to detect depression, reporting accuracy, recall, precision, and F1-score using social media status updates from 1047 users along with their associated depression diagnosis questionnaire scores. These datasets also include user postings, network connections, and personality responses. …”
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