SOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizer by Sameh I. Selem, Attia A. El-Fergany, Eid A. Gouda, Mohamed F. Kotb, Islam Ismael

“…As a result, the polarization principal curves of the measured and estimated voltage datasets are checked and verified with very close matching. …”
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Pilot study: Initial investigation suggests differences in EMT-associated gene expression in breast tumor regions by Kylie L. King, Hamed Abdollahi, Zoe Dinkel, Alannah Akins, Homayoun Valafar, Heather Dunn

“…ML enables the analysis of complex datasets and the extraction of useful information from small datasets. …”
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Prostate Cancer Detection from MRI Using Efficient Feature Extraction with Transfer Learning by Rafiqul Islam, Al Imran, Md. Fazle Rabbi

“…The random forest classifier, a powerful ensemble learning method renowned for its adaptability and ability to handle intricate datasets, then uses the collected characteristics as input. …”
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Skeleton-Based Data Augmentation for Sign Language Recognition Using Adversarial Learning by Yuriya Nakamura, Lei Jing

“…However, it is difficult to collect sign language data, and many datasets suffer from data lack and imbalance, leading to overfitting and reduced accuracy in machine learning. …”
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Application of Gene Expression Programming to Evaluate Strength Characteristics of Hydrated-Lime-Activated Rice Husk Ash-Treated Expansive Soil by Kennedy C. Onyelowe, Fazal E. Jalal, Michael E. Onyia, Ifeanyichukwu C. Onuoha, George U. Alaneme

“…A multiple linear regression (MLR) was also conducted on the datasets in addition to GEP to serve as a check mechanism. …”
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An Attention-Based Residual U-Net for Tumour Segmentation Using Multi-Modal MRI Brain Images by Najme Zehra Naqvi, K. R. Seeja

“…The performance of proposed model is evaluated on two datasets BraTS 2020 and BraTS 2018. The experiments on both datasets demonstrate that the proposed framework enhances multi-modal MRI brain tumour segmentation performance on all metrics evaluated. …”
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IL1RN and PRRX1 as a Prognostic Biomarker Correlated with Immune Infiltrates in Colorectal Cancer: Evidence from Bioinformatic Analysis by Qi Wang, Xufeng Huang, Shujing Zhou, Yuntao Ding, Huizhi Wang, Weiye Jiang, Min Xu

“…For this, we identified 704 differentially expressed genes (DEGs) by intersecting three datasets, GSE41328, GSE37364, and GSE15960 from Gene Expression Omnibus database, to maximize the accuracy of the results. …”
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The Prognostic Significance of TRs in Hepatocellular Carcinoma: Insights from TCGA and GEO Databases by Hao Zhou, Weijie Wang, Ruopeng Liang, Rongtao Zhu, Jiahui Cao, Chenguang Sun, Yuling Sun

“…Expression levels of TRs in HCC and immune single cells were assessed using datasets from the Gene Expression Omnibus (GEO) and TCGA, analyzed with R software. …”
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A composite improved attention convolutional network for motor imagery EEG classification by Wenzhe Liao, Zipeng Miao, Shuaibo Liang, Linyan Zhang, Chen Li

“…CIACNet utilizes a dual-branch convolutional neural network (CNN) to extract rich temporal features, an improved convolutional block attention module (CBAM) to enhance feature extraction, temporal convolutional network (TCN) to capture advanced temporal features, and multi-level feature concatenation for more comprehensive feature representation.ResultsThe CIACNet model performs well on both the BCI IV-2a and BCI IV-2b datasets, achieving accuracies of 85.15 and 90.05%, respectively, with a kappa score of 0.80 on both datasets. …”
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Classifying IoT Botnet Attacks With Kolmogorov-Arnold Networks: A Comparative Analysis of Architectural Variations by Phuc Hao do, Tran Duc Le, Truong Duy Dinh, van Dai Pham

“…The evaluation was performed on three IoT botnet datasets: N-BaIoT, IoT23, and IoT-BotNet, using metrics such as accuracy, precision, recall, F1-score, training time, and model complexity. …”
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A Review on Person Re-Identification Techniques and Its Analysis by C. Selvan, H. Anwar Basha, K. Meenakshi, Soumyalatha Naveen

“…Over the past few years, the realm of deep learning applied to video re-ID has consistently delivered remarkable outcomes on public datasets, showcasing a range of innovative strategies devised to tackle the array of issues encountered in video re-ID. …”
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Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore Regions by Mohamad Alkhalidi, Abdullah Al-Dabbous, Shoug Al-Dabbous, Dalal Alzaid

“…Accurate wind speed and direction data are vital for coastal engineering, renewable energy, and climate resilience, particularly in regions with sparse observational datasets. This study evaluates the ERA5 reanalysis model’s performance in predicting wind speeds and directions at ten coastal and offshore stations in Kuwait from 2010 to 2017. …”
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PPARD May Play a Protective Role for Major Depressive Disorder by Tao Yang, Juhua Li, Liyuan Li, Xuehua Huang, Jiajun Xu, Xia Huang, Lijuan Huang, Kamil Can Kural

“…PPARG presented significant within- and between-study variations in the 18 MDD datasets (p value = 0.97), which were significantly associated with the population region (country) and sample source (p<2.67e−5). …”
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The role of passive surveillance and citizen science in plant health by Nathan Brown, Ana Pérez-Sierra, Peter Crow, Stephen Parnell

“…There are already many working examples of passive surveillance programmes and the suite of options to interpret the resulting datasets is growing rapidly.…”
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Integrative analysis of single-cell and transcriptome sequencing with experimental validation reveals PKHD1L1 as a novel biomarker in lung adenocarcinoma by Xiangqian Zhang, Jie Wang, Hanyang Su, Xiaojin Liu

“…Through meticulous analysis of immune cell infiltrates and single-cell datasets, we discerned a notable correlation between the expression of PKHD1L1 and the presence of B cells, with a particularly strong association observed in plasma cells. …”
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Modeling Soil Behavior with Machine Learning: Static and Cyclic Properties of High Plasticity Clays Treated with Lime and Fly Ash by Gebrail Bekdaş, Yaren Aydın, Sinan Melih Nigdeli, İnci Süt Ünver, Wook-Won Kim, Zong Woo Geem

“…These results highlight the general applicability of the used ML models on different datasets containing soil properties.…”
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Multi-omics approaches for understanding gene-environment interactions in noncommunicable diseases: techniques, translation, and equity issues by Robel Alemu, Nigussie T. Sharew, Yodit Y. Arsano, Muktar Ahmed, Fasil Tekola-Ayele, Tesfaye B. Mersha, Azmeraw T. Amare

“…These challenges include the inherent complexity and heterogeneity of multi-omic datasets, limitations in analytical approaches, and severe underrepresentation of non-European genetic ancestries in most omics datasets, which restricts the generalizability of findings and exacerbates health disparities. …”
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Development of an m6A-Related lncRNAs Signature Predicts Tumor Stemness and Prognosis for Low-Grade Glioma Patients by Dahua Xu, Peihu Li, Chunrui Zhang, Yutong Shen, Jiale Cai, Qingchen Wei, Meng Cao, Zhizhou Xu, Deng Wu, Hong Wang, Xiaoman Bi, Bo Wang, Kongning Li

“…A risk score model based on m6A-related lncRNAs was constructed and validated in external LGG datasets. Results. Based on the expression of LINC02984, PFKP-DT, and CRNDE, a risk model and nomogram were constructed; they successfully predicted the survival of patients and were extended to external datasets. …”
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Evaluation of Satellite Precipitation Products and Their Potential Influence on Hydrological Modeling over the Ganzi River Basin of the Tibetan Plateau by Alaa Alden Alazzy, Haishen Lü, Rensheng Chen, Abubaker B. Ali, Yonghua Zhu, Jianbin Su

“…In the last few years, satellite-based precipitation datasets are believed to be a potential source for forcing inputs in driving hydrological models, which are important especially in complex terrain areas or ungauged basins where ground gauges are generally sparse or nonexistent. …”
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CENPN contributes to pancreatic carcinoma progression through the MDM2-mediated p53 signaling pathway by Ming Xu, Jie Tang, Qiong Sun, Jing Meng, Guoyu Chen, Yunli Chang, Yao Yao, Jieru Ji, Hao Luo, Lingling Chen, Minxue Lu, Weiwei Shi

“…Results Following a comprehensive bioinformatic analysis of 161 concordant differentially expressed genes (DEGs) across three microarray datasets, CENPN emerged as the central gene under investigation. …”
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