Profiling the diversity of the village chicken faecal microbiota using 16S rRNA gene and metagenomic sequencing data to reveal patterns of gut microbiome signatures by Mxolisi Nene, Mxolisi Nene, Nokuthula Winfred Kunene, Rian Pierneef, Rian Pierneef, Rian Pierneef, Khanyisile Hadebe

“…This study aimed to investigate the diversity and functional capacities of the faecal microbiome in village chickens from Limpopo and KwaZulu-Natal provinces of South Africa.MethodsUsing a combination of 16S rRNA gene sequencing and shotgun metagenomic sequencing technologies, we analysed 98 16S rRNA and 72 metagenomic datasets. Taxonomic profiles and functional gene annotations were derived, focusing on microbial diversity, antibiotic resistance genes (ARGs), and potential zoonotic pathogens.ResultsTaxonomic analysis showed that the predominant phyla in both provinces were Firmicutes, Bacteroidota, Proteobacteria, and Actinobacteria. …”
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Assessing the impact of climate and land use change on flood vulnerability: a machine learning approach in coastal region of Tamil Nadu, India by Devanantham Abijith, Subbarayan Saravanan, K S S Parthasarathy, Nagireddy Masthan Reddy, Janardhanam Niraimathi, Ahmed Ali Bindajam, Javed Mallick, Maged Muteb Alharbi, Hazem Ghassan Abdo

“…To identify flooded areas, the study utilised Google Earth Engine (GEE), Sentinel-1 data, and 12 geospatial datasets from multiple sources. A random forest algorithm was used for LULC change and flood susceptibility mapping. …”
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Depression Detection in Social Media: A Comprehensive Review of Machine Learning and Deep Learning Techniques by Waleed Bin Tahir, Shah Khalid, Sulaiman Almutairi, Mohammed Abohashrh, Sufyan Ali Memon, Jawad Khan

“…We propose a generic architecture for these systems and present a detailed analysis of methodologies and datasets used for evaluation in this field. In addition, we highlight key open research areas, providing a useful starting point for further research and development. …”
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Multi-channel spatio-temporal graph attention contrastive network for brain disease diagnosis by Chaojun Li, Kai Ma, Shengrong Li, Xiangshui Meng, Ran Wang, Daoqiang Zhang, Qi Zhu

“…Experiments on epilepsy and ADNI datasets show that our method outperforms several state-of-the-art approaches in diagnosing performance, and it provides discriminative graph features for related brain diseases.…”
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Integrated analysis of chromatin and transcriptomic profiling of the striatum after cerebral hypoperfusion in mice by Shijia Le, Fengyiyang Xu, Zhi Luo, Weihao Shi, Shuangshuang Lu, Zengyu Zhang, Zimin Guo, Wenshi Xu, Mingqi Yang, Tianyi Li, Xu Li, Kun Liang, Lei Zhu

“…The integration of these datasets allowed us to correlate chromatin accessibility with transcriptional activity and to identify key transcription factors driving the observed gene expression changes. …”
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Prognostic Significance and Therapeutic Potential of SERPINE1 in Head and Neck Squamous Cell Carcinoma by Changyu Zhu, Heshu Liu, Zhixin Li, Yijun Shi, Jingyang Zhao, Yuping Bai, Qian Chen, Wei Li

“…Methods and Results In this study, we delved into the variations in gene mutation, methylation patterns, and expression levels of SERPINE1 in head and neck squamous cell carcinoma (HNSCC) and normal tissues, leveraging comprehensive analyses of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. The connection between the biological function of the gene and prognosis was scrutinized through immune infiltration and enrichment analyses. …”
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Infrared Image Enhancement: A Review by Qingwang Wang, Pengcheng Jin, Yuhang Wu, Liyao Zhou, Tao Shen

“…Therefore, we have conducted a systematic investigation of the research advancements in the field of infrared image enhancement, encompassing infrared image enhancement methods, related datasets, and evaluation metrics, with the aim of exploring a research solution that could potentially break through current technological limitations. …”
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A Deep Learning-Based Approach for the Detection of Various Internet of Things Intrusion Attacks Through Optical Networks by Nouman Imtiaz, Abdul Wahid, Syed Zain Ul Abideen, Mian Muhammad Kamal, Nabila Sehito, Salahuddin Khan, Bal S. Virdee, Lida Kouhalvandi, Mohammad Alibakhshikenari

“…Comprehensive experiments on benchmark datasets, including KDD CUP99, UNSW NB15, and Bot-IoT, demonstrate XIoT’s exceptional accuracy rates of 99.34%, 99.61%, and 99.21%, respectively, significantly surpassing existing methods in both accuracy and interpretability. …”
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Comprehensive Evaluation of Bankruptcy Prediction in Taiwanese Firms Using Multiple Machine Learning Models by Hung V. Pham, Tuan Chu, Tuan M. Le, Hieu M. Tran, Huong T.K. Tran, Khanh N. Yen, Son V. T. Dao

“…This study developed an advanced bankruptcy prediction model using Support Vector Machines (SVM), Random Forest (RF), and Artificial Neural Network (ANN) algorithms based on datasets from the UCI machine learning repository. …”
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Extracting Regular Building Footprints Using Projection Histogram Method from UAV-Based 3D Models by Yaoyao Ren, Xing Li, Fangyuqing Jin, Chunmei Li, Wei Liu, Erzhu Li, Lianpeng Zhang

“…Extensive experiments conducted on datasets from Nanjing and Wuhan demonstrate the remarkable accuracy of our approach. …”
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Refined Urban Functional Zones Identification via Empirical Bayesian Kriging: A POI-Weighted Scoring Innovation by Xuan Du, Yisha Pan, Xiaoyan Yang, Longgao Chen, Liangchen Liu, Ying Lin

“…The rapid proliferation and open accessibility of multi-source data, such as remote sensing imagery and socio-economic datasets, have introduced new opportunities for the dynamic identification of UFZs. …”
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New Evaluation Method for Fuzzy Cluster Validity Indices by Ismay Perez-Sanchez, Miguel Angel Medina-Perez, Raul Monroy, Octavio Loyola-Gonzalez, Andres Eduardo Gutierrez-Rodriguez

“…The experiments are conducted evaluating the partitions generated by the fuzzy c-means clustering algorithm over 84 UCI datasets with 31 fuzzy CVIs. Experimental results evidenced the need for bigger experimental setups compared to previous studies. …”
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Unraveling the interplay between NDVI, soil moisture, and snowmelt: A comprehensive analysis of the Tibetan Plateau agroecosystem by Di Wei, Lin Yan, Ziqi Zhang, Jia Yu, Xue’er Luo, Yun Zhang, Bo Wang

“…This study integrates MODIS remote sensing images and ERA5-Land meteorological reanalysis datasets to establish a ternary system encompassing NDVI, soil moisture, and snowmelt. …”
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A proposed methodology for the definition of background and reference values for trace elements in fluvial sediments by F. Barrio-Parra, R. Álvarez, H. Serrano-García, M. Izquierdo-Díaz, A. Ordóñez, C.C. García-Fernández, E. De Miguel

“…The methodology proved particularly effective in datasets with a limited sample size and highly skewed data distributions. …”
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Forecasting insect abundance using time series embedding and machine learning by Gabriel R. Palma, Rodrigo F. Mello, Wesley A.C. Godoy, Eduardo Engel, Douglas Lau, Charles Markham, Rafael A. Moral

“…Therefore, we propose a new approach to address this problem by combining statistics, machine learning, and time series embedding. We used two datasets containing a time series of aphids and climate data collected weekly in two municipalities in Southern Brazil for eight years. …”
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Complementary Non‐invasive Fish Monitoring Distinguishes Depth‐Dependent Fish Communities by Ewan Burns, Vijini Mallawaarachchi, Thomas M. Clarke, Belinda Martin, Joseph D. DiBattista, Jamie Hicks, Danny Brock, Elizabeth A. Dinsdale, Charlie Huveneers, Michael P. Doane

“…Only 17 of the 102 species recorded were detected by both methods and combining these two datasets resulted in a 40% increase in species‐level detections compared to either method alone. …”
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Integrating social narratives of flood events into a text network analysis-based decision support framework to reduce vulnerability to climate change in Africa by Thomas E. O’Shea, Lena C. Grobusch, Mary Zhang, Jeff Neal, Joseph Daron, Richard G. Jones, Christopher Jack, Alice McClure, Gilbert Siame, Dorothy Ndhlovu, Sukaina Bharwani

“…Local flood inundation maps were created using global rainfall and GIS datasets and then analysed across two interactive “Learning Labs” with local stakeholders. …”
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Multiscale Adaptively Spatial Feature Fusion Network for Spacecraft Component Recognition by Wuxia Zhang, Xiaoxiao Shao, Chao Mei, Xiaoying Pan, Xiaoqiang Lu

“…The proposed method has been validated on the UESD and URSO datasets, and the experimental results demonstrate the superiority of MASFFN over existing spacecraft component recognition methods.…”
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Endoplasmic reticulum stress-related super enhancer promotes epithelial-mesenchymal transformation in hepatocellular carcinoma through CREB5 mediated activation of TNC by Anqi Wang, Sitong Yan, Jiatao Liu, Xiang Chen, Mengyao Hu, Xiao Du, Weijia Jiang, Zhipeng Pan, Lulu Fan, Guoping Sun

“…CRISPR-Cas9 and RT-qPCR identified CAMP responsive element binding protein 5 (CREB5) as a key target of ERS-related SE. Analyses of TCGA datasets and tissue arrays showed that CREB5 mRNA and protein expression levels were higher in liver cancer tissues than in paired normal tissues. …”
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Prognostic prediction for inflammatory breast cancer patients using random survival forest modeling by Yiwei Jia, Chaofan Li, Cong Feng, Shiyu Sun, Yifan Cai, Peizhuo Yao, Xinyu Wei, Zeyao Feng, Yanbin Liu, Wei Lv, Huizi Wu, Fei Wu, Lu Zhang, Shuqun Zhang, Xingcong Ma

“…The C-index of RSF model was 0.7704 and the area under curve (AUC) values for 1, 3, 5 years in training and validation datasets were 0.879–0.955, suggesting the excellent predictive performance of RSF model. …”
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