A novel deep reinforcement learning‐based algorithm for multi‐objective energy‐efficient flow‐shop scheduling by Peng Liang, Pengfei Xiao, Zeya Li, Min Luo, Chaoyong Zhang

“…Considering the global and local features of NFSP, a set of 15 state features is extracted. …”
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A cutting-edge ensemble model for enhanced underwater image restoration and quality improvement by A. Sarala, C. Vinoth kumar

“…In this paper, we propose an ensemble model, Ensemble Pyramid-based Convolutional Neural Network and Deep Channel Prior Dehazing Network (EPCNN-DCPDN), which combines Pyramid-based Convolutional Neural Networks (CNNs) and the Deep Channel Prior Dehazing Network (DCPDN) to address these challenges. …”
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Object detection in motion management scenarios based on deep learning. by Baocheng Pei, Yanan Sun, Yebiao Fu, Ting Ren

“…The accuracy of target detection in this scenario is greatly. To evaluate the effectiveness of our designed network and proposed methodology, we conduct experiments on open-source datasets. …”
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MiR-485-3p/MELK cascade mediates tumor progression in pancreatic cancer by Yishan Huang, Ting Yang, Chen Yang, Bo Tang, Bo Su, Xiaojun Yang

“…Tumor migration, invasion, and angiogenesis were evaluated using transwell and tube formation assays, respectively. …”
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A method for detecting the rate of tobacco leaf loosening in tobacco leaf sorting scenarios by Yansong Wang, Yansong Wang, Chunjie Zhang, Chunjie Zhang, Mingjie Wu, Mingjie Wu, Ruilin Luo, Lin Lu, Zaiqing Chen, Zaiqing Chen, Lijun Yun, Lijun Yun

“…This was achieved by adding layers for detecting smaller objects and integrating a weighted bi-directional feature pyramid structure to reconstruct the feature fusion network. …”
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Identifying liver cirrhosis in patients with chronic hepatitis B: an interpretable machine learning algorithm based on LSM by Xueting Bai, Chunwen Pu, Wenchong Zhen, Yushuang Huang, Qian Zhang, Zihan Li, Yixin Zhang, Rongxuan Xu, Zhihan Yao, Wei Wu, Mei Sun, Xiaofeng Li

“…Employing the least absolute shrinkage and selection operator (LASSO) and random forest-recursive feature elimination (RF-RFE) for feature selection, we developed both traditional logistic regression and five machine learning models (k-nearest neighbors, random forest (RF), artificial neural network, support vector machine and eXtreme Gradient Boosting). …”
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Experimental assessment and data-driven hybrid machine learning quantification with parametric optimization of compressive strength of ceramic waste concrete by Mihir Mishra, Md. Habibur Rahman Sobuz, Md. Kawsarul Islam Kabbo, M Jameel, Turki S. Alahmari, Naim Ahmad, Md. Munir Hayet Khan

“…CWC samples were prepared for experimental evaluation by replacing cement with 5 % SF and 5 %, 10 %, 15 %, and 20 % CW. …”
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Exploring the Influence of Environmental Characteristics on Emotional Perceptions in Metro Station Spaces by Hedi Shi, Jianfei Chen, Zuhan Feng, Tong Liu, Donghui Sun, Xiaolu Zhou

“…This study adopts an innovative approach by integrating deep learning-based affective computing methods with semantic segmentation techniques in computer vision to systematically evaluate the impact of various physical environmental features and functional spaces on users’ emotional perceptions across multiple dimensions. …”
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Artificial Intelligence Models for Pediatric Lung Sound Analysis: Systematic Review and Meta-Analysis by Ji Soo Park, Sa-Yoon Park, Jae Won Moon, Kwangsoo Kim, Dong In Suh

“…Convolutional neural networks were the predominant ML model, often combined with recurrent neural networks or residual network architectures. …”
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Insect-specific virus platforms for arbovirus vaccine development by Roy A. Hall, Roy A. Hall, Wilson Nguyen, Alexander A. Khromykh, Alexander A. Khromykh, Andreas Suhrbier, Andreas Suhrbier

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Characteristics of cancer mycobiome in patients with acral melanoma by Lin Li, Qi Sun, Rong Huang, Zhengyun Zou, Jiayu Wang, Lianjun Zhao, Donglin Kang, Xinyu Su, Yirong Wu, Ziyao Xie

“…Differences in fungal communities between the two tissues, as well as the prognostic and diagnostic potential of intratumoral fungi, and their associations with the tumor microenvironment and clinicopathologic features, were evaluated through bioinformatics and biostatistical analyses.Results Although some intratumoral fungi originated from adjacent tissues, AM tumors exhibited a distinct fungal composition characterized by altered species richness, community structure, and an increased Ascomycota-to-Basidiomycota ratio. …”
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A Hybrid Speech Enhancement Technique Based on Discrete Wavelet Transform and Spectral Subtraction by Yasir Iqbal, Tao Zhang, Teddy Surya Gunawan, Agus Pratondo, Xin Zhao, Yanzhang Geng, Mira Kartiwi, Nasir Saleem, Sami Bourouis

“…Proposed speech enhancement network evaluated and experimental results show that the hybrid SS-DWT method outperforms existing systems, achieving up to 34.15 dB in SDR, 0.98 in STOI, and 3.84 in PESQ, demonstrating significant improvements in speech quality under various noisy conditions.…”
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Earth Observation Data to Support Environmental Justice: Linking Non‐Permitted Poultry Operations to Social Vulnerability Indices by Mirela G. Tulbure, Júlio Caineta, Brooke Cox, Stephen V. Stehman, Ayse Ercumen, Rebecca Witter, Ryan Emanuel, Dana E. Powell, Kemp Burdette, Sherri White‐Williamson, Shea Tuberty

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Research on leaf identification of table grape varieties based on deep learning by PAN Bowen, LIN Meiling, JU Yanlun, SU Baofeng, SUN Lei, FAN Xiucai, ZHANG Ying, ZHANG Yonghui, LIU Chonghuai, JIANG Jianfu, FANG Yulin

“…The Grad-CAM algorithm was used to evaluate the classification effect of four convolutional neural networks, and all of them could accurately identify the main features of the leaves. …”
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Recurrence-Based Techniques for Data-Driven Fault Diagnosis and Monitoring in Neutral-Point-Clamped Inverters by Lincoln Moura De Oliveira, Menaouar Berrehil El Kattel, Esio Eloi Dos Santos Filho, Juan C. Vasquez, Josep M. Guerrero, Fernando Luiz Marcelo Antunes

“…Three operating conditions were evaluated: an RL load, an induction motor, and an open-circuit fault scenario. …”
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SbD4Skin by EosCloud: Integrating multi-view molecular representation for predicting skin sensitization, irritation, and acute dermal toxicity by Nikoletta-Maria Koutroumpa, Dimitra-Danai Varsou, Panagiotis D. Kolokathis, Maria Antoniou, Konstantinos D. Papavasileiou, Eleni Papadopoulou, Anastasios G. Papadiamantis, Andreas Tsoumanis, Georgia Melagraki, Milica Velimirovic, Antreas Afantitis

“…Different molecular representations for skin toxicity-related endpoints were first evaluated using three machine learning algorithms (Random Forest, Support Vector Machine, and k-Nearest Neighbors), then combined into a unified input space for training a fully connected neural network (FCNN). …”
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Progressive Cluster-Guided Knowledge Distillation for Remote Sensing Image Scene Classification by Zhaopeng Deng, Zheng Zhou, Haoran Zhao, Xiaolin Chen, Danfeng Hong, Xin Sun

“…Specifically, we devise an optimal clustering module that adaptively selects informative samples and dynamically updates cluster centers to alleviate intraclass and interclass discrepancies. Subsequently, a feature selection module is introduced to evaluate feature confidence levels, enabling smooth separation of features with varying difficulty and resolving feature imbalance. …”
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Expanded Design by Roberto Bottazzi

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Identification of anti-fibrotic compounds from Piper longum L via hollow fiber cell fishing and high-performance liquid chromatography with in vivo and in vitro validation by Jie Tian, Nan Zhou, Heng Wang, Wanghui Jing, Guoping Zheng

“…This model was integrated with network pharmacology and molecular biology techniques to screen and validate active anti-fibrotic compounds in Piper longum L. …”
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Clinical relevance of macromolecular complexes involving integrins, potassium and sodium ion channels and the sodium/proton antiporter in human breast cancer by Elena Lastraioli, Jessica Iorio, Francesco Piazza, Chiara Capitani, Michele Santillo, Claudia Duranti, Simonetta Bianchi, Icro Meattini, Scott P. Fraser, Mustafa B. A. Djamgoz, Andrea Becchetti, Annarosa Arcangeli

“…Interestingly, hERG1, nNav1.5 and the hERG1/β1 integrin complex associated with several clinical features, including molecular subtype and hormone receptor status. …”
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