Bayesian joint-regression analysis of unbalanced series of on-farm trials by Turbet Delof, Michel, Rivière, Pierre, Dawson, Julie C, Gauffreteau, Arnaud, Goldringer, Isabelle, van Frank, Gaëlle, David, Olivier

“…The methods developed could be used for evaluation and/or selection within networks of various stakeholders such as farmers, gardeners, plant breeders or managers of genetic resource centres.…”
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Mobile Accelerometer Applications in Core Muscle Rehabilitation and Pre-Operative Assessment by Aleš Procházka, Daniel Martynek, Marie Vitujová, Daniela Janáková, Hana Charvátová, Oldřich Vyšata

“…The study employs a range of machine learning methods, including support vector machines, Bayesian analysis, and neural networks, to evaluate the balance of various physical activities. …”
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Identifying Disinformation on the Extended Impacts of COVID-19: Methodological Investigation Using a Fuzzy Ranking Ensemble of Natural Language Processing Models by Jian-An Chen, Wu-Chun Chung, Che-Lun Hung, Chun-Ying Wu

“…The dataset was randomly split using the scikit-learn package to facilitate both training and evaluation. Deep learning models were trained for 20 epochs on a Tesla T4 for hierarchical attention networks (HANs) and an RTX A5000 (for the other models). …”
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Thinking- Skins by Jens Böke

“…The influence is particularly evident in the transformation of the industrial sector to Industry 4.0, where formerly mechatronic production plants are networked into intelligent technical systems with the aim of achieving higher and more flexible productivity. …”
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Oxidative Phosphorylation-Related Signature Participates in Cancer Development, and PTPRG Overexpression Suppresses the Cancer Progression in Clear Cell Renal Cell Carcinoma by Liang Huang, Yu Xie, Weiqing Han, Shusuan Jiang, Lingfeng Zeng

“…Also, the cell cycle and apoptosis level were evaluated by flow cytometry. As a result, we discovered that both the C1 cluster and high-risk group predicted patient survival with high accuracy and characterized lower survival rates, lower oxidative phosphorylation levels, higher immune infiltration, and malignant clinical features. …”
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Analyzing execution path non-determinism of the Linux kernel in different scenarios by Yucong Chen, Xianzhi Tang, Shuaixin Xu, Fangfang Zhu, Qingguo Zhou, Tien-Hsiung Weng

“…Therefore, an online data collection system for system call execution paths was constructed based on Ftrace, network file system (NFS), and MD5 hash function, uniquely identifying the system call execution path. …”
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Unveiling Pharmacological Mechanisms of <i>Bombyx mori</i> (Abresham), a Traditional Arabic Unani Medicine for Ischemic Heart Disease: An Integrative Molecular Simulation Study by Doni Dermawan, Nasser Alotaiq

“…Pharmacophore modeling identified key structural features critical for bioactivity, while in silico toxicity assessments evaluated the safety profiles of the compounds. …”
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Application of deep learning in malware detection: a review by Yafei Song, Dandan Zhang, Jian Wang, Yanan Wang, Yang Wang, Peng Ding

“…The review includes common methods such as convolutional neural networks, recurrent neural networks and generative adversarial networks, focusing on feature extraction techniques such as sequence features, image visualization and data enhancement. …”
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BiLSTM-Based Parallel CNN Models With Attention and Ensemble Mechanism for Twitter Sentiment Analysis by Anas W. Abulfaraj

“…When used together, models like the Convolutional Neural Networks (CNN) and LSTM networks have significant high-performance results for text feature extraction and semantic relationship of the word. …”
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Homotherapy for heteropathy of chronic kidney disease and oligoasthenozoospermia through regulating SIRT1/NF-κB pathway by Shenqi pills by Shuo Huang, Qihan Luo, Xinyue Li, Yiming Liu, Jiale Wei, Sichen Wang, Ping Qiu, Changyu Li, Changyu Li

“…Both conditions share features of yang deficiency, including fatigue, cold intolerance, and weakness. …”
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Research Progress on Information Model of Urban Green Space by Wei ZHANG, Yahan YAN

“…By summarizing and analyzing the green space-related components of existing digital information model standards both domestically and internationally, this research explores different expression methods suitable for green space information modeling by focusing on three aspects: model composition, data relationship, and analytical evaluation applications. To meet the practical needs of urban green space planning and management, this research conducts digital simulations of the geometric forms and attribute information of green space plants, and proposes directions for further improvement of green space information models, including the construction of modeling standards, the development of sharing platforms, and the research on generative algorithms.ResultsThe structures and characteristics of green space plants differ from those of other urban components, and their digital representation methods need to be explored based on the spatial morphological features of the vegetation in green spaces. …”
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Scientific objectives of research on road machines life cycle in modern conditions by S. A. Evtiukov, S. V. Repin, S. M. Grushetskii, G. A. Kаrro

“…In addition, the active implementation of CALS-technologies; modern monitoring systems for road machines; the commitment to automate and robotic work processes; change in the volume and pace of road construction; increasing requirements for the quality of work performed; extension of the warranty period of road service; the existence of mega road organizations; the absence to date of generally accepted criteria for evaluating the effectiveness of one form or another of organizing maintenance and repair work (unscheduled repairs) of road machines; active development of a network of toll roads, etc. they require a radical review and systematization of issues related to the formulation of scientific problems in the study of the life cycle system of road vehicles in modern conditions.Materials and methods. …”
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RSDCNet: An efficient and lightweight deep learning model for benign and malignant pathology detection in breast cancer by Yuan Liu, Haipeng Li, Zhu Zhu, Chen Chen, Xiaojing Zhang, Gongsheng Jin, Hongtao Li

“…Methods This study introduces RSDCNet, an enhanced lightweight neural network architecture designed for the automatic detection of benign and malignant breast cancer pathology. …”
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A hybrid framework for classifying and detecting aircraft cabin anomalous sounds under heavy background noise by Jiaan Chen, Tian Gan, Chenyi Zhao, Huayong Zhao, Ci Song, Xiaole Wang, Zhenyu Huang

“…And in the second stage for anomalous sound identification, a lightweight convolutional neural network, trained with ArcFace loss and aided by an anomalous feature decomposition method, detects those labeled anomalous sounds even when the signal-to-noise ratio (SNR) is very low. …”
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A Study on the Oxidative Functionalization of a Poplar Biochar by Antonella Di Vincenzo, Ettore Madonia, Calogero Librici, Paola Bambina, Delia Chillura Martino, Susanna Guernelli, Paolo Lo Meo, Pellegrino Conte

“…The results clarify the relationship between oxidative treatment conditions and biochar properties, highlighting their impact on both structural modifications and water dynamics within the porous network, and enabling us to identify the best reaction conditions for optimizing the features of the oxidized product.…”
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Deep learning helps discriminate between autoimmune hepatitis and primary biliary cholangitis by Alessio Gerussi, Oliver Lester Saldanha, Giorgio Cazzaniga, Damiano Verda, Zunamys I. Carrero, Bastian Engel, Richard Taubert, Francesca Bolis, Laura Cristoferi, Federica Malinverno, Francesca Colapietro, Reha Akpinar, Luca Di Tommaso, Luigi Terracciano, Ana Lleo, Mauro Viganó, Cristina Rigamonti, Daniela Cabibi, Vincenza Calvaruso, Fabio Gibilisco, Nicoló Caldonazzi, Alessandro Valentino, Stefano Ceola, Valentina Canini, Eugenia Nofit, Marco Muselli, Julien Calderaro, Dina Tiniakos, Vincenzo L’Imperio, Fabio Pagni, Nicola Zucchini, Pietro Invernizzi, Marco Carbone, Jakob Nikolas Kather

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Visibility Graph Investigation of the Shallow Seismicity of Lai Chau Area (Vietnam) by Luciano Telesca, Anh Tuan Thai, Dinh Trong Cao, Thanh Hai Dang

“…Analyzing the variation of the seismological and topological parameters of the seismicity relative to the distance from the center of the Lai Chau reservoir revealed the following features: (1) the <i>b</i>-value fluctuates around a mean value of 1.21 at distances of up to 10–11 km, while, for distances larger than 25–30 km, it tends to the value of 0.86; (2) the maximum IMI between the monthly number of earthquakes and the monthly mean water level occurs at a distance of 9–11 km, showing a distance evolution similar to that of the <i>b</i>-value; (3) at these distances from the center of the reservoir, the time lag between the earthquake monthly counts and the monthly water level mean is 9–10 months; (4) the relationship between the <i>b</i>-value and the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>k</mi><mo>−</mo><mi>M</mi></mrow></semantics></math></inline-formula> slope suggests that the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>k</mi><mo>−</mo><mi>M</mi></mrow></semantics></math></inline-formula> slope depends on the number of earthquakes within a 22 km radius from the center of the dam. …”
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3D reconstruction for unconstrained image collections using Gaussian Splatting with foundation model by Shuowen Huang, Qingwu Hu, Pengcheng Zhao, Mingyao Ai, Xujie Zhang, Wenwu Ou, Linze Li

“…Specifically, we develop a multi-scale tri-plane feature encoding module that integrates scene features across multiple scales and predicts Gaussian attributes. …”
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Research on Arthroscopic Images Bleeding Detection Algorithm Based on ViT-ResNet50 Integrated Model and Transfer Learning by Zewen Liu, Shaoyi Zhou, Jianqiao Chu, Zhiyuan Chai, Dongdong Chang, Yi Yuan, Jinling Qin, Xiancheng Wang

“…Finally, the two sub-network models are integrated through weighted soft voting method to realize bleeding detection in arthroscopic images. …”
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Relating satellite NO2 tropospheric columns to near-surface concentrations: implications from ground-based MAX-DOAS NO2 vertical profile observations by Bowen Chang, Haoran Liu, Chengxin Zhang, Chengzhi Xing, Wei Tan, Cheng Liu

“…In this study, the correlation between CNO2 and SNO2 is examined using vertical profile observations from China’s MAX-DOAS network. Cloud cover and air convection substantially weaken (R = −0.68) and strengthen (R = 0.71) the CNO2-SNO2 correlation, respectively. …”
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