Molecular and genetic features of a bla NDM−1 and bla SHV−12 coharboring hypermucoviscous Klebsiella pneumoniae of serotype K2 and ST65 by Yuting Kang, Qiujie Li, Wanting Ma, Chao Xu, Zhuoran Qiu, Wei Jia, Pengtao Wang

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Impact of Corrugated Fins on Flow and Heat Transfer Performance in Medium-Deep Coaxial Underground Heat Exchangers by Yan Shi, Chengcheng Liu, Hongxu Chen, Yaoshuai Yue, Mingqi Li

“…The optimal configuration, featuring a fin width of 15 mm, a spacing of 60 mm, and a thickness of 15 mm, achieves a maximum PEC value of 1.34 at Re = 12,000, indicating a substantial improvement in heat transfer performance within acceptable pressure drop limits. …”
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Effect of the trap/divergent flow channel on the performance of open-cathode proton exchange membrane fuel cells by Minyuan Du, Yi Liu, Jilin Lei, Shiyao Zhao, Hu Peng, Shuchao He, Rui Mo

“…This study explores PEMFC models featuring various trap configurations, varying in factors such as the quantity and length of traps employed. …”
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Performance evaluation of operating freight cars with improved technical characteristics for JSC “Russian Railways” on the testing basis by G. A. Granovskaya, R. V. Murzin, O. A. Suslov

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Explainable Supervised Learning Models for Aviation Predictions in Australia by Aziida Nanyonga, Hassan Wasswa, Keith Joiner, Ugur Turhan, Graham Wild

“…This study investigates the classification performance of multiple supervised machine learning models and employs SHapley Additive exPlanations (SHAPs) to provide global model explanations, identifying key features that influence decision boundaries. …”
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Meta-analysis to determine the effects of supplementation of niacin during the transition or lactation period on performance in dairy cows by U. Arshad, S. Bagaria, C.M. Ncho, M. Sagheer, K. Krogstad, M. Niu

“…This meta-analysis aimed to evaluate the effects of niacin supplementation on lactational performance in dairy cows. We hypothesized that niacin supplementation during the transition or lactation period would enhance the productive performance of dairy cows. …”
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A Spatio-Temporal Joint Diagnosis Framework for Bearing Faults via Graph Convolution and Attention-Enhanced Bidirectional Gated Networks by Zhiguo Xiao, Xinyao Cao, Huihui Hao, Siwen Liang, Junli Liu, Dongni Li

“…Subsequently, we design an end-to-end spatio-temporal joint learning architecture by implementing a global attention-enhanced BiGRU temporal modeling module. This architecture achieves the deep fusion of spatio-temporal features through the graph-structural transformation of vibration signals and a feature cascading strategy, thereby improving overall model performance. …”
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Predictive modeling for rework detection in sustainable building projects by AbdulLateef Olanrewaju, Kafayat Shobowale

“…Model performance was evaluated using k-fold cross-validation to ensure generalizability. …”
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Weather identification using models based on deep learning by Afroza Nahar, Rifat Al Mamun Rudro, Bakhtiar Atiq Faisal, Md. Faruk Abdullah Al Sohan, Laveet Kumar

“…Predictions, extraction of features, and fine-tuning of models were achieved with an accuracy of up to 83.39%. …”
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Deep Learning Model for Analyzing EEG Signal Analysis by Varun Gupta, Vivek Kumar, Prince, Saurabh Singh, Young-Seok Lee, In-Ho Ra

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Network-Based Bag-of-Words Model for Text Classification by Dongyang Yan, Keping Li, Shuang Gu, Liu Yang

“…Because the structural and semantic information of a network reflects the relationship between nodes, the proposed model can distinguish the relation of words. We apply the proposed model to text classification and compare the performance of the proposed model with different text representation methods on four document datasets. …”
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Dynamic convolution models for cross-frontend keyword spotting by Rongqi Liu, Wenkang Chen, Xuejun Zhang

“…The dynamic convolution model enables the adaptive capture of diverse and time-varying acoustic patterns, while the mutual learning strategy effectively leverages complementary features extracted from multiple audio frontends to enhance the model’s generalization across different input conditions. …”
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Model-Based Dynamic Structural Modification of Machine Tools by Mateusz Wąsik, Krzysztof Lis, Krzysztof Lehrich, Łukasz Mucha

“…It is based on the results of experimental research and allows for the prediction of dynamic features of individual bodies and complete structures on the basis of the described modal model. …”
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Detection of circulating tumor cells in peripheral blood of patients with tongue squamous cell carcinoma and its relationship with clinical features and prognosis: a retrospective... by Ningbo Geng, Weiyi Lin, Dandan Zhang, Wei Cao, Chongjin Feng, Shan Chen

“…Methods 85 with TSCC and 30 tongues with benign disease who underwent surgical treatment from May 2016 to May 2023 were retrospectively analysed. CTC testing was performed twice for TSCC group before and after surgery and only before the surgery for the benign disease group, only one test was performed before surgery.The association of CTCs with clinical features and progression-free survival (PFS) was also analyzed. …”
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The TERT promoter mutation status and MGMT promoter methylation status, combined with dichotomized MRI‐derived and clinical features, predict adult primary glioblastoma survival by Chang Shu, Qiong Wang, Xiaoling Yan, Jinhuan Wang

“…Abstract Purpose This study aimed to integrate the TERT promoter mutation status, MGMT promoter methylation status, MRI‐derived features, and clinical features into a survival analysis model to better understand adult primary glioblastoma prognosis‐related markers. …”
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“VTMine for Visio”: Graphical Tool for Modeling in Process Mining by Sergey A. Shershakov

“…The subject area of the process analysis involves the work of an analyst with a large number of graphical models. Such work will be more efficient with a convenient graphical modeling tool. …”
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Tabular Data Models for Predicting Art Auction Results by Patryk Mauer, Szczepan Paszkiel

“…Additionally, we address the interpretability of models, which is crucial for understanding the influence of various features on predictions. …”
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Association of [¹⁸F]-FDG PET/CT-Derived Radiomic Features with Clinical Outcomes and Genomic Profiles in Patients with Chronic Lymphocytic Leukemia by Fabiana Esposito, Luigi Manco, Guglielmo Manenti, Livio Pupo, Andrea Nunzi, Roberta Laureana, Luca Guarnera, Massimiliano Marinoni, Elisa Buzzatti, Paola Elda Gigliotti, Andrea Micillo, Giovanni Scribano, Adriano Venditti, Massimiliano Postorino, Maria Ilaria Del Principe

“…The IGVH models showed poorer performance. <b>Conclusions:</b> ML models based on PET/CT radiomic features effectively predict outcomes and genetic profiles in CLL patients.…”
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S2-IFNet: A spatial-semantic information fusion network integrated with boundary feature enhancement for forest land extraction from Sentinel-2 data by Junyang Xie, Mengyao Zhang, Hao Wu, Anqi Lin, Marcos Adami, Abdul Rashid Mohamed Shariff, Yahui Guo

“…Compared to the different forest land extraction models, S2-IFNet shows a superior performance, with ablation experiments confirming the effectiveness of each module. …”
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Lightweight Deep Learning Model for Fire Classification in Tunnels by Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho

“…The experimental results demonstrate that the proposed model achieves an accuracy of 96.5%, a precision of 95.7%, and a recall of 97.2%, significantly outperforming state-of-the-art (SOTA) models such as ResNet50 and YOLOv5 in both accuracy and real-time performance. …”
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