An Accelerated FPGA-Based Parallel CNN-LSTM Computing Device by Xin Zhou, Wei Xie, Han Zhou, Yongjing Cheng, Ximing Wang, Yun Ren, Shandong Yuan, Liuwen Li

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Neural Network Ensemble to Detect Dicentric Chromosomes in Metaphase Images by Ignacio Atencia-Jiménez, Adayabalam S. Balajee, Miguel J. Ruiz-Gómez, Francisco Sendra-Portero, Alegría Montoro, Miguel A. Molina-Cabello

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SFD-YOLO: A novel framework for subsidence funnels detection in China based on large-scale SAR interferograms by Jing Guo, Zhengjia Zhang, Peifeng Ma, Mengmeng Wang, Xuefei Zhang, Dongdong Li, Bing Sui

“…To address these challenges, this study proposes a deep learning network based on the YOLO architecture—SFD-YOLO (Sinking Funnel Detection-YOLO). …”
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Integrating multi-dimensional data to reveal the mechanisms and molecular targets of baikening granules for treatment of pediatric influenza by Zhaoyuan Gong, Qianzi Che, Mingzhi Hu, Tian Song, Lin Chen, Haili Zhang, Ning Liang, Huizhen Li, Guozhen Zhao, Lijiao Yan, Xuefei Zhang, Bin Liu, Jing Guo, Nannan Shi

“…Target networks were built with the purpose of screening both targets and key components. Pathway and function enrichment were conducted on the relevant targets of BKN for treating pediatric influenza. …”
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CacPred: a cascaded convolutional neural network for TF-DNA binding prediction by Shuangquan Zhang, Anjun Ma, Xuping Xie, Zhichao Lian, Yan Wang

“…In recent years, convolutional neural networks (CNNs) have succeeded in TF-DNA binding prediction, but existing DL methods’ accuracy needs to be improved and convolution function in TF-DNA binding prediction should be further explored. …”
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A Universal Tire Detection Method Based on Improved YOLOv8 by Chi Guo, Mingxia Chen, Junjie Wu, Haipeng Hu, Luobing Huang, Junjie Li

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BESW-YOLO: A Lightweight SAR Image Detection Model Based on YOLOv8n for Complex Scenarios by Xiao Tang, Kun Cao, Yunzhi Xia, Enkun Cui, Weining Zhao, Qiong Chen

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Overexpression of MMP14 is associated with poor prognosis and immune cell infiltration in colon cancer by Na Li, Nan Zhang, Guanghui Wang

“…This study investigated the regulatory role of Matrix metalloproteinase-14 (MMP14) in immune function and its impact on CRC prognosis.Methodswe performed transcriptome sequencing on tumor and adjacent non-cancerous samples from four pairs of patients diagnosed with colorectal cancer. …”
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Alleviating small sample problem in continuous forest monitoring with remote sensing-assisted Copulas by Xinjie Cheng, Zhengyang Hou, Annika Kangas, Jean-Pierre Renaud, Hao Tang, Weisheng Zeng, Qing Xu

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Validation of the inadequate delivery of oxygen index in an adult cardiovascular intensive care unitCentral MessagePerspective by Heather Holman, BS, Dimitar Baronov, PhD, Jeff McMurray, MD, Arman Kilic, MD, Marc Katz, MD, Sanford Zeigler, MD

“…Objective: Machine learning (ML) may allow for improved discernment of hemodynamics and oxygen delivery compared to standard invasive monitoring. …”
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DIRECTIONS FOR IMPROVING THE QUALITY OF POSTGRADUATE EDUCATION OF PHYSICIANS by Н. Каспрук, С. Батрановська, С. Мельничук, Т. Унгурян, Т. Копчук, А. Петрюк

“…Contemporary higher medical education must cultivate a learning environment capable of preparing competitive and competent healthcare professionals who can function effectively, make rapid decisions under wartime and other challenging conditions, and engage in lifelong professional development. …”
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Changes in soil pH on the Tibetan Plateau from the 1980 s to 2020 s by Lirong Zhao, Bo Pang, Jiangtao Hong, Xinxin Zhang, Jinmei Li, Xiaodan Wang

“…Soil pH, as a crucial variable in the soil environment, has a significant impact on the structure and function of terrestrial ecosystems. The Tibetan Plateau is recognized as one of the most sensitive regions to global climate change. …”
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Association between Alzheimer's disease pathologic products and age and a pathologic product-based diagnostic model for Alzheimer's disease by Weizhe Zhen, Yu Wang, Hongjun Zhen, Weihe Zhang, Wen Shao, Yu Sun, Yanan Qiao, Shuhong Jia, Zhi Zhou, Yuye Wang, Leian Chen, Jiali Zhang, Dantao Peng, Dantao Peng

“…Using correlation analysis method like cor function, we analyzed the pathology products (t-Tau, p-Tau, and Aβ proteins), age, gender, and Minimum Mental State Examination (MMSE) scores in the ADNI data. …”
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Identification of tryptophan metabolism-related biomarkers for nonalcoholic fatty liver disease through network analysis by Cuihua Jiang, Jianqi Liang, Kaibo Hu, Yanqing Ye, Jiajia Yang, Xiaozhi Zhang, Guilin Ye, Jing Zhang, Deju Zhang, Bin Zhong, Peng Yu, Liefeng Wang, Bin Zeng

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Rice-SVBDete: a detection algorithm for small vascular bundles in rice stem’s cross-sections by Xiaoying Zhu, Weiyu Zhou, Jianguo Li, Jianguo Li, Mingchong Yang, Mingchong Yang, Haiyu Zhou, Haiyu Zhou, Jiada Huang, Jiada Huang, Jiahua Shi, Jun Shen, Guangyao Pang, Lingqiang Wang, Lingqiang Wang, Lingqiang Wang

“…A new Powerful Intersection over Union (PIoU) loss function that emphasizes spatial consistency and positional accuracy, replacing the standard CIoU loss.ResultsExperimental evaluations show that Rice-SVBDete achieves a precision of 0.789, recall of 0.771, and mean Average Precision (mAP@.5) of 0.728 at an IoU threshold of 0.50. …”
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International Natural Uranium Price Prediction Based on TF-CNN-BiLSTM Model by YANG Jingzhe, XUE Xiaogang

“…The study meticulously constructed and trained the TF-CNN-BiLSTM model using TensorFlow with the Adam optimizer and mean squared error loss function. The training process was optimized with learning rate reduction and early stopping callbacks to prevent overfitting. …”

Cellular hierarchy framework based on single-cell and bulk RNA sequencing reveals fatty acid metabolic biomarker MYDGF as a therapeutic target for ccRCC by Ning Wang, Ziyu Xu, Lina Zhang, Lina Zhang, Yanfang Lu, Yanfang Lu, Yanliang Wang, Yanliang Wang, Lei Yan, Lei Yan, Huixia Cao, Huixia Cao, Limeng Wang, Limeng Wang, Fengmin Shao, Fengmin Shao

“…The function of the selected genes in FAM was validated through clinical samples and cellular functional experiments.ResultsThe results revealed significant upregulation of FAM in malignant epithelial cells. …”
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UP3: Unsupervised Predictive Path Planner for Mobile Robots in Unknown Environment by Jianing Luo, Jiwei Zhu, Ruopeng Cui, Gaoxiong Lu, Wei Li

“…In this article, UP3, a novel unsupervised learning‐based predictive path planning framework for mobile robot navigation in partially observable environments is proposed. …”
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Predicting Interplanetary Shock Occurrence for Solar Cycle 25: Opportunities and Challenges in Space Weather Research by Denny M. Oliveira, Robert C. Allen, Livia R. Alves, Séan P. Blake, Brett A. Carter, Dibyendu Chakrabarty, Giulia D’Angelo, Kevin Delano, Ezequiel Echer, Cristian P. Ferradas, Matt G. Finley, Bea Gallardo‐Lacourt, Dan Gershman, Jesper W. Gjerloev, John Bosco Habarulema, Michael D. Hartinger, Rajkumar Hajra, Hisashi Hayakawa, Liisa Juusola, Karl M. Laundal, Robert J. Leamon, Michael Madelaire, Miguel Martínez‐Ledesma, Scott M. McIntosh, Yoshizumi Miyoshi, Mark B. Moldwin, Emmanuel Nahayo, Dibyendu Nandy, Bhosale Nilam, Katariina Nykyri, William R. Paterson, Mirko Piersanti, Ermanno Pietropaolo, Craig J. Rodger, Trunali Shah, Andy W. Smith, Nandita Srivastava, Bruce T. Tsurutani, S. Tulasi Ram, Lisa A. Upton, Bhaskara Veenadhari, Sergio Vidal‐Luengo, Ari Viljanen, Sarah K. Vines, Vipin K. Yadav, Jeng‐Hwa Yee, James W. Weygand, Eftyhia Zesta

“…Thus, it is of great interest to the space weather community to (a) keep an accurate catalog of shocks observed near Earth, and (b) be able to forecast shock occurrence as a function of the solar cycle (SC). In this work, we use a supervised machine learning regression model to predict the number of shocks expected in SC25 using three previously published sunspot predictions for the same cycle. …”
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Stochastic and deterministic processes in Asymmetric Tsetlin Machine by Negar Elmisadr, Mohamed-Bachir Belaid, Anis Yazidi

“…We incorporate stochasticity and asymmetry into the TM's process, along with a decaying normal distribution function that improves adaptability as it converges toward zero over time. …”
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