Multi-model MCDM framework for sustainable renewable energy selection in India: integrating CRITIC-EDAS-CODAS-CoCoSo by Shankha Shubhra Goswami, T. Tapankumar, N. Channa Keshava Naik, J. Gowrishankar, Nilesh Bhosle, Amrita Singh, G. Sanyasi Raju, D. Nagesh, A. Johnson Santhosh

“…Abstract The global boom in the importance of renewable energy (RE) resources has accelerated the transition from traditional energy sources to sustainable alternatives. Selecting an optimum RE power plant is a complex task influenced by geographical factors, climatic differences, and regional peculiarities. …”
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Optimal Industrial Waste Management Strategy for Pakistan Steel Mill Corporation Using Complex Spherical Fuzzy Einstein Aggregation Information by Ijaz Ur Rahman, Shahzaib Ashraf, Bushra Batool, K. C. Gokul

“…Applying greater generality in the dimensions of the abovementioned applications could potentially enhance a lot of their efficiency. Einstein norms/application of Einstein operations have not been effectively applied within the complex spherical fuzzy sets (CSFSs) framework as such; this study now advances the application of Einstein operators in CSFS which would provide an adiaphorous approach to solving issues related to decision-making problems (DMPs). …”
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Identification of PET/CT radiomic signature for classification of locally recurrent rectal cancer: A network-based feature selection approach by Sara Dalmonte, Maria Adriana Cocozza, Dajana Cuicchi, Daniel Remondini, Lorenzo Faggioni, Paolo Castellucci, Andrea Farolfi, Emilia Fortunati, Alberta Cappelli, Riccardo Biondi, Arrigo Cattabriga, Gilberto Poggioli, Stefano Fanti, Gastone Castellani, Francesca Coppola, Nico Curti

“…Identifying LRRC through imaging is complex, due to the mismatch between fibrosis and inflammatory pelvic tissue. …”
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A novel sodium Iron silicate composite with chitosan for efficient removal of Cd(II) ions from water by Mohamed S. Kamel, Ehab A. Abdelrahman, Zinab M. Anwar, Samir M. El Rayes, Mortaga M. Abou-Krisha, Raed M. Hegazey, Hanan Alhussain

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π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing by Xiang Zhang, Tianze Ling, Zhi Jin, Sheng Xu, Zhiqiang Gao, Boyan Sun, Zijie Qiu, Jiaqi Wei, Nanqing Dong, Guangshuai Wang, Guibin Wang, Leyuan Li, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan, Fuchu He, Wanli Ouyang, Cheng Chang, Siqi Sun

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Selective disruption of aurora C kinase reveals distinct functions from aurora B kinase during meiosis in mouse oocytes. by Ahmed Z Balboula, Karen Schindler

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CD-STMamba: Toward Remote Sensing Image Change Detection With Spatio-Temporal Interaction Mamba Model by Shanwei Liu, Shuaipeng Wang, Wei Zhang, Tao Zhang, Mingming Xu, Muhammad Yasir, Shiqing Wei

“…Change detection (CD) is a critical Earth observation task. …”
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Distributed Denial of Services (DDoS) attack detection in SDN using Optimizer-equipped CNN-MLP. by Sajid Mehmood, Rashid Amin, Jamal Mustafa, Mudassar Hussain, Faisal S Alsubaei, Muhammad D Zakaria

“…We propose to implement both MLP (Multilayer Perceptron) and CNN (Convolutional Neural Networks) based on conventional methods to detect the Denial of Services (DDoS) attack. These models have got a complex optimizer installed on them to decrease the false positive or DDoS case detection efficiency. …”
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Efficiency of Therapeutic Use and Mechanisms of Therapeutic Effect of "Essentuki" and "Narzan" Mineral Waters in Various Diseases: a Review by Tatiana V. Konchugova, Tatiana V. Apkhanova, Tatyana V. Marfina, Detelina B. Kulchitskaya, Larisa A. Marchenkova, Valeriia A. Vasileva, Maxim Yu. Yakovlev, Olga M. Musaeva

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A feature selection method utilizing path accumulation cost, redundancy minimization, and interaction maximization for the diagnosis of coronary heart disease by Jiayao Jiang, Zheng Yue, Hongling Zhu, Yan Wang, Hongsen Cai, Wenguang Hou

“…Conclusion The proposed approach offers an efficient solution for early detection of CHD by identifying critical indicators, reducing diagnostic complexity, and improving predictive accuracy, thus potentially leading to more effective CHD management.…”
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Detection of disease on nasal breath sound by new lightweight architecture: Using COVID-19 as an example by Jiayuan She, Lin Shi, Peiqi Li, Ziling Dong, Renxing Li, Shengkai Li, Liping Gu, Zhao Tong, Zhuochang Yang, Yajie Ji, Liang Feng, Jiangang Chen

“…Our Dense-ReLU-Dropout model, using RF and PCA for feature selection, achieves high accuracy with greater computational efficiency compared to existing methods that require more complex models or larger datasets. …”
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Trade-offs between machine learning and deep learning for mental illness detection on social media by Zhanyi Ding, Zhongyan Wang, Yeyubei Zhang, Yuchen Cao, Yunchong Liu, Xiaorui Shen, Yexin Tian, Jianglai Dai

“…Machine learning (ML) and deep learning (DL) models have been increasingly applied to classify mental health conditions from textual data, but selecting the most effective model involves trade-offs in accuracy, interpretability, and computational efficiency. …”
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A novel approach to skin disease segmentation using a visual selective state spatial model with integrated spatial constraints by Yu Bai, Hai Zhou, Hongjie Zhu, Shimin Wen, Binbin Hu, Haotian Li, Huazhang Wang, Daji Ergu, Fangyao Liu

“…To address limitations in existing approaches, we introduce a novel U-shaped segmentation architecture based on our Residual Space State Block. This efficient model, termed ‘SSR-UNet,’ leverages bidirectional scanning to capture both global and local features in image data, achieving strong performance with low computational complexity. …”
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A new scheme for boosting in situ Fenton-like reaction in plant pathogenic tissues for selective structural degradation of capsid proteins by Jun Ma, Ming Chen, Yujie Wang, Jiaying Li, Jian Tang, Shengjun Wu, Chi He, J. Paul Chen

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Method on Efficient Operation of Multiple Models for Vision-Based In-Flight Risky Behavior Recognition in UAM Safety and Security by Byeonghun Kim, Byeongjoon Noh, Kyowon Song

“…It can effectively perform roles such as detecting prohibited items and recognition of dangerous/abnormal behavior. …”
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Multifunctional RNA-binding proteins influence mRNA abundance and translational efficiency of distinct sets of target genes. by Valentin Schneider-Lunitz, Jorge Ruiz-Orera, Norbert Hubner, Sebastiaan van Heesch

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Detection of Stator Faults in Three-Phase Induction Motors Using Stray Flux and Machine Learning by Ailton O. Louzada, Wesley A. Souza, Avyner L. O. Vitor, Marcelo F. Castoldi, Alessandro Goedtel

“…Despite advancements in non-invasive sensing, challenges remain in balancing fault detection accuracy, computational efficiency, and adaptability to real-world conditions. …”
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A Lightweight Deep Learning Network with an Optimized Attention Module for Aluminum Surface Defect Detection by Yizhe Li, Yidong Xie, Hu He

“…Additionally, we introduced an optimized Convolutional Block Attention Module (CBAM) to further enhance network efficiency. Furthermore, we employed the genetic K-means algorithm to optimize prior region selection, and a lightweight Ghost model to reduce network complexity by 14.3%, demonstrating the superior performance of the Ghost model in terms of loss function optimization during training and validation as well as in terms of detection accuracy, speed, and stability. …”
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Coverage, Throughput, and Energy Efficiency Enhancement in Beamspace Massive MIMO System Using Rate-Splitting and Orthogonal Precoding by David Alimo, Masanori Hamamura, Saifur Rahman Sabuj

“…Following that, we offer an alternating method to solve the approximate optimization issue and select an optimal solution. Furthermore, we deduce an analytic expression for the downlink cell coverage percentage and evaluate the effectiveness of the suggested method in terms of total throughput, energy efficiency, and cell coverage percentage. …”
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A method for detecting abnormal electricity prices at charging stations based on two rounds of clustering by XUE Xiaohui, ZHANG Wen, ZHANG Jing, CHEN Yan, ZHOU Chun, CHEN Liang, CAO Zengwei

“…Due to the complexity of electricity pricing policies, multiple implementation steps, and difficulty in regulation, errors in electricity pricing implementation occur from time to time. …”
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