Bioactive compounds in blackberry fruits under the conditions of Central Russia by М. A. Мakarkina, О. A. Vetrova, L. A. Gruner, B. B. Kornilov

“…‘Black Satin’, ‘Cacanska Bestrna’, ‘Chester’, ‘Natchez’ and ‘Triple Crown’, plus hybrid seedlings LN-14, LN-1 and LN-7, were identified according to a set of indicators (ascorbic acid and phenolics) and recommended for breeding to improve the quality of blackberry fruits.…”
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<inline-formula><tex-math notation="LaTeX">$\mathrm{D}^{3}$</tex-math></inline-formula>T: Deep Denoising Dictionary Tensor for Hyperspectral Anomaly Detection by Qiangqiang Shen, Zonglin Liu, Hanzhang Wang, Yanhui Xu, Yongyong Chen, Yongsheng Liang

“…Numerous experimental results from various real-world datasets validate the effectiveness of our <inline-formula><tex-math notation="LaTeX">$\mathrm{D}^{3}$</tex-math></inline-formula>T.…”
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Hybrid Prophet-NAR Model for Short-Term Electricity Load Forecasting by Winita Sulandari, Yudho Yudhanto, Etik Zukhronah, Isnandar Slamet, Hilman Ferdinandus Pardede, Paulo Canas Rodrigues, Muhammad Hisyam Lee

“…On the Malaysian electricity load datasets, the PropNAR model achieved MAE values ranging from 527.26 to 1023.78, RMSE values from 752.70 to 1498.54, and MAPE values from 1.12% to 2.04%. …”
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Molecular characterization of EBV-associated primary pulmonary lymphoepithelial carcinoma by multiomics analysis by Meiling Yang, Guixian Zheng, Fukun Chen, Haijuan Tang, Yaoyao Liu, Xuan Gao, Yu Huang, Zili Lv, Benhua Li, Maolin Yang, Qing Bu, Lixia Zhu, Pengli Yu, Zengyu Huo, Xinyan Wei, Xiaoli Chen, Yanbing Huang, Zhiyi He, Xuefeng Xia, Jing Bai

“…Methods In this study, we explored pLEC using whole-exome sequencing (WES) and RNA-whole-transcriptome sequencing (RNA-seq) technologies. Datasets of normal lung tissue, other types of NSCLC, and EBV-positive nasopharyngeal carcinoma (EBV+-NPC) were obtained from public databases. …”
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An AI recognition method for children's clinical operative pain by skin potential (SP) signal by Mingxuan Huang, Cangcang Fu, Linbo Chui, Jiadong He, Xiaozhi Wang, Jikui Luo, Bin Wu, Yonggang Chen, Shaohua Hu, Jihua Zhu, Yubo Li

“…Initially, we preprocessed SP signals and built datasets for pain and non-pain conditions, including 195 pain and 97 non-pain samples. …”
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Cetacean feeding modelling using machine learning: A case study of the Central-Eastern Mediterranean Sea by Carla Cherubini, Giulia Cipriano, Leonardo Saccotelli, Giovanni Dimauro, Giovanni Coppini, Roberto Carlucci, Carmelo Fanizza, Rosalia Maglietta

“…Behavioural data from April 2016 to October 2023, coupled with 20 environmental variables from Copernicus Marine Service and EMODnet-bathymetry datasets, were used to build Cetacean Feeding Models (CFMs) for the target species using Random Forest and RUSBoost algorithms. …”
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Zero-Shot Remote Sensing Scene Classification Based on Automatic Knowledge Graph and Dual-Branch Semantic Correlation Supervision by Chao Wang, Jiajun Yang, Tanvir Ahmed, Yang Zhao, Tong Zhang, Bing Sun, Tao Xie, Jie Wang, Tianyu Chen

“…Extensive experiments on the UCM, AID, and NWPU datasets demonstrate that AKG-DBSS achieves class average accuracy and overall accuracy of up to 98&#x0025;, and 59.56&#x0025;, respectively, for the classification of unseen class scenes, with standard deviations below 6.91&#x0025;, significantly outperforming four other advanced comparative methods. …”
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Morphological Neuroimaging Biomarkers for Tinnitus: Evidence Obtained by Applying Machine Learning by Yawen Liu, Haijun Niu, Jianming Zhu, Pengfei Zhao, Hongxia Yin, Heyu Ding, Shusheng Gong, Zhenghan Yang, Han Lv, Zhenchang Wang

“…The accuracy in the training and test datasets was 80.49% and 80.00%, respectively, and the AUC was 0.8586. …”
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E-MAC: Enhanced In-SRAM MAC Accuracy via Digital-to-Time Modulation by Saeed Seyedfaraji, Salar Shakibhamedan, Amire Seyedfaraji, Baset Mesgari, Nima Taherinejad, Axel Jantsch, Semeen Rehman

“…., a 0.1% and 0.17% reduction for LeNet5-based CNN and VGG16, respectively, when trained on the MNIST and ImageNet datasets.…”
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Evidence for the replication of a plant rhabdovirus in its arthropod mite vector by Hideki Kondo, Miki Fujita, Paul Telengech, Kazuyuki Maruyam, Kiwamu Hyodo, Aline Daniele Tassi, Ronald Ochoa, Ida Bagus Andika, Nobuhiro Suzuki

“…In the mite and plant datasets, a large number of sequence reads were aligned to genomic regions of OFV RNA1 and RNA2 corresponding to transcribed viral gene mRNAs. …”
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Machine Learning Diagnostic Model for Hepatocellular Carcinoma Based on Liquid–Liquid Phase Separation and Ferroptosis-Related Genes by Wenchao Chen, Ting Zhu, Xiaofan Pu, Linlin Zhao, Senhao Zhou, Xin Zhong, Suihan Wang, Tianyu Lin

“…Materials and Methods: The differentially expressed genes (DEGs) were identified based on 3 GEO datasets, followed by overlapping with LLPS-related and ferroptosis-related genes. …”
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Single‐cell dissection reveals immunosuppressive F13A1+ macrophage as a hallmark for multiple primary lung cancers by Chenglin Yang, Jiahao Qu, Jingting Wu, Songhua Cai, Wenyi Liu, Youjun Deng, Yiran Meng, Liuqing Zheng, Lishen Zhang, Li Wang, Xiaotong Guo

“…Methods We performed a comparative single‐cell RNAsequencing (scRNA‐seq) analysis on tumour and adjacent para‐tumour tissues fromMPLC and SPLC patients to comparatively evaluate their immunological landscapes.Additionally, multiplex immunofluorescence (mIF) staining and independentvalidation datasets were used to confirm findings. Results MPLCs and SPLCs share significant similarities in genetic, transcriptomic and immune profiles, suggesting common therapeutic strategies such as EGFR‐TKIs andICIs. …”
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Prediction of clinical efficacy of acupuncture intervention on upper limb dysfunction after ischemic stroke based on machine learning: a study driven by DSA diagnostic reports data by Yaning Liu, Yuqi Tang, Zechen Li, Pei Yu, Jing Yuan, Lichuan Zeng, Can Wang, Su Li, Ling Zhao, Ling Zhao, Ling Zhao

“…After screening, 616 datasets were selected for analysis. A prediction model was developed using the AutoGluon framework, with three outcome measures as endpoints: the National Institutes of Health Stroke Scale (NIHSS), Fugl-Meyer Assessment for Upper Extremity (FMA-UE), and the Modified Barthel Index (MBI).ResultsThe prediction model demonstrated high accuracy for the three endpoints, with prediction accuracies of 84.3% for NIHSS, 77.8% for FMA-UE, and 88.1% for MBI. …”
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Contaminant-degrading bacteria are super carriers of antibiotic resistance genes in municipal landfills: A metagenomics-based study by Fang-Zhou Gao, Wei-Li Jia, Bing Li, Min Zhang, Liang-Ying He, Hong Bai, You-Sheng Liu, Guang-Guo Ying

“…Here, we collected metagenomic datasets of 32 raw leachate and 45 solid waste samples in 22 municipal landfills of China. …”
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Temporal and habitat-specific variations in drivers of aboveground biomass dynamics in a Chinese subtropical forest by Yuxuan Bian, Qi Wu, Rong Zheng, Jiaqin Fu, Jianhua Chen, Xiangcheng Mi, Mingjian Yu, Yunquan Wang, Yunquan Wang, Yunquan Wang

“…To address this gap, we evaluated changes in aboveground biomass across a decade and various habitats, disentangling the relative influences of topography and multidimensional diversity on ΔAGB through datasets from forest inventories conducted between 2007 and 2017, along with phylogenetic relatedness, functional traits, and environmental variables from a subtropical forest in China. …”
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Exploring the influence of pre-analytical variables on gene expression measurements and relative expression orderings in cancer research by Tian Tian, Guie Lai, Ming He, Xiaofang Liu, Yun Luo, You Guo, Guini Hong, Hongdong Li, Kai Song, Hao Cai

“…Systematic evaluating effects of these variables on gene expression measurements and relative expression orderings (REOs) of gene pairs, is necessary. A total of 18 datasets were collected, comprising over 800 paired samples. …”
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Sphingosine kinase 1 promotes M2 macrophage infiltration and enhances glioma cell migration via the JAK2/STAT3 pathway by Zihan Song, Zijun Zhao, Xuehua Liu, Yiran Song, Siyu Zhu, Ziyang Jia, Yijie Li, Zairan Wang, Boyu Sun, Qianxu Jin, Shiyang Zhang, Zongmao Zhao, Liqiang Liu

“…We comprehensively examined SPHK1 and investigated its correlation with glioma survival time using different datasets. The correlation between SPHK1 and various cancer pathways was analyzed using the Kyoto encyclopedia of genes and genomes (KEGG) analysis. …”
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Dual Fine-Grained network with frequency Transformer for change detection on remote sensing images by Zhen Li, Zhenxin Zhang, Mengmeng Li, Liqiang Zhang, Xueli Peng, Rixing He, Leidong Shi

“…Our comparative experiments across four publicly available datasets demonstrate that FTransDF-Net reaches advanced results. …”
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Deciphering the generation of heterogeneity in esophageal squamous cell carcinoma metastasis via single-cell multiomics analysis by Kaiwen Sheng, Jun Chen, Ruitang Xu, Haoqiang Sun, Ran Liu, Yongjie Wang, Wenwen Xu, Jiao Guo, Miao Zhang, Shuai Liu, Juan Lei, Yawen Sun, Yang Jia, Dianhao Guo

“…In conjunction, we integrated these data with 55 scRNA-seq datasets, ChIP-seq or CUT&Tag sequencing data, Hi-C sequencing data, bulk RNA-seq data, and bulk ATAC-seq data from ESCC cell lines to dissect the mechanisms underlying the heterogeneity of ESCC and tumor microenvironment (TME). …”
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Targeting TCMR-associated cytokine genes for drug screening identifies PPARγ agonists as novel immunomodulatory agents in transplantation by Lu Hu, Lu Hu, Xiaohan Zhang, Xiaohan Zhang, Weiqi Zhang, Weiqi Zhang, Shuai Jin, Shuai Jin, Jie Zhao, Jianming Zheng, Wenli Song, Zhongyang Shen, Zhongyang Shen, Zhongyang Shen

“…To evaluate the effectiveness of this gene set, a diagnostic predictive model was constructed using Lasso regression and multivariate logistic regression, with validation in independent datasets. Connectivity Map (CMap) analysis was employed to screen drugs targeting TCMR-Cs. …”
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