A study on the prediction of mountain slope displacement using a hybrid deep learning model by Yuyang Ma, Xiangxiang Hu, Yuhang Liu, Yaya Shi, Zhiyuan Yu, Xinmin Wang, Liangbai Hu, Shuailing Liu, Dongdong Pang

“…Unlike conventional models, this hybrid framework effectively mitigates large errors and improves reliability by leveraging a multi-stage approach. …”
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Advancing bridge resilience: a review of monitoring technologies for flood-prone infrastructure [version 2; peer review: 2 approved] by Vanni Nicoletti, Karina Buka-Vaivade, Fabrizio Gara

“…This review examines state-of-the-art Structural Health Monitoring (SHM) technologies tailored to mitigate flood risks, focusing on their real-world applications in flood-prone bridges. …”
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SUNet: Coffee Leaf Disease Detection Using Hybrid Deep Learning Model by Deepak Thakur, Tanya Gera, Ambika Aggarwal, Madhushi Verma, Manjit Kaur, Dilbag Singh, Mohammed Amoon

“…SUNet integrates U-Net with Segnet’s encoding system, using VGG16 for robust feature extraction. A decoder with skip connections is used to preserve spatial details. …”
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Dynamic Real-Time Anchor Selection for Accurate UWB Indoor Positioning-Based Deep Neural Networks by Ammar Fahem Majeed, Rashidah Arsat, Muhammad Ariff Baharudin, Nurul Mu'Azzah Abdul Latiff, Abbas Albaidhani

“…The model effectively mitigates non-line-of-sight (NLOS) ranging errors, evaluates anchor channel quality online, and selects optimal anchor combinations, ensuring scalability and adaptability for diverse deployment scenarios. …”
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Inhibiting inter-layer gliding in transition metal layered oxides through interphase engineering for sodium-ion batteries by Xing Zhou, Chao Yang, Xiaowei Liu, Xin Peng, Yongyuan Zhou, Liguang Wang, Tongchao Liu, Ya You, Jun Lu

“…Building upon this insight, we propose interphase engineering as an effective approach to mitigate phase transitions. The resulting P2/P3-Na0.46Mn0.9Ni0.1O2 material, featuring dense and uniform P2/P3 interphases, exhibits notable enhancements in both cycling stability and rate capability. …”
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Elevated ubiquitin phosphorylation by PINK1 contributes to proteasomal impairment and promotes neurodegeneration by Cong Chen, Tong-Yao Gao, Hua-Wei Yi, Yi Zhang, Tong Wang, Zhi-Ling Lou, Tao-Feng Wei, Yun-Bi Lu, Tingting Li, Chun Tang, Wei-Ping Zhang

“…Conversely, Pink1 knockout mitigated protein aggregation in both mouse brains and HEK293 cells. …”
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A hybrid deep learning model for sentiment analysis of COVID-19 tweets with class balancing by Md. Alamin Talukder, Md. Ashraf Uddin, Suman Roy, Partho Ghose, Smita Sarker, Ansam Khraisat, Mohsin Kazi, Md Momtazur Rahman, Musawer Hakimi

“…This study proposes a hybrid deep learning (DL) model that integrates Bidirectional Encoder Representations from Transformers (BERT) for contextual feature extraction with Long Short-Term Memory (LSTM) networks for sequential learning to classify COVID-19-related sentiments. …”
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Damage Behavior of Multilayer Axisymmetric Shells Obtained by the FDM Method by Salenko O., Drahobetskyi V., Symonova A., Onishchenko E., Kostenko A., Tsurkan D., Vasiukov D.

“…The research demonstrates that this design feature helps localize damage and mitigates the formation of significant trunk cracks, particularly along generative cracks.…”
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Dynamic climate graph network and adaptive climate action strategy for climate risk assessment and low-carbon policy responses by Fang Zhou, Yan Shi, Pengfei Zhao, Zhengzhao Gu, Ye Li

“…BackgroundThe increasing urgency to mitigate and adapt to climate change demands innovative methodologies capable of analyzing complex climate systems and informing policy decisions. …”
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CUNet-CLSTM: A Novel Fusion of CUNet and CLSTM for Superior Liver Cancer Detection in CT Scans by K. Vijayaprabakaran, Padmanaban Ramalingam, Rajakumar Ramalingam, A. Ilavendhan, R. Vedhapriyavadhana

“…Compared to state-of-the-art models, the proposed CUNet-CLSTM not only improves segmentation accuracy, but also mitigates overfitting through sequential feature learning and optimizes computational efficiency by providing an end-to-end framework, reducing the complexity of multi-stage pipelines. …”
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Intelligent Perception and Seam Tracking System for Thick Plate Weldments Based on Constant-Focus Optical Path by Lei Zhai, Wenze Ren, Fei Li, Rong Wu, Jinsong Lin, Jiahui Feng, Jun Zheng, Yang Liu

“…This methodology specifically targets and mitigates several critical shortcomings inherent in conventional vision-guided welding techniques, including limited detection ranges, diminished precision in both detection and tracking, and suboptimal real-time performance. …”
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Methodological Integration of Machine Learning and Geospatial Analysis for PM10 Pollution Mapping by Kalid Hassen Yasin, Muaz Ismael Yasin, Anteneh Derribew Iguala, Tadele Bedo Gelete, Erana Kebede

“…Air pollution mitigation necessitates accurate spatial modelling to inform public health interventions. …”
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The evolutionary game equilibrium theory on power market bidding involving renewable energy companies by Lefeng Cheng, Pan Peng, Wentian Lu, Jian Sun, Fan Wu, Mingming Shi, Xiaodong Yuan, Yang Chen

“…To address these challenges, this study proposes a novel evolutionary game-theoretic framework featuring a “mixed-strategy distortion” mechanism, which introduces adaptive periodic adjustments in bidding ranges. …”
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Predicting the potential distribution areas of Leptotrombidium rubellum under current and future climate change by Qunzheng Mu, Qunzheng Mu, Fengfeng Li, Wenyu Li, Wenyu Li, Xiaoxia Wang, Mingyuan Tang, Kehan Chen, Yihao Jiang, Jingqi Liu, Shirong Zhang, Qiyong Liu, Chuan Wang

“…Enhanced surveillance in currently suitable and future at-risk regions is critical to mitigate invasion risks.…”
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Investigating Catching Hotspots of Fishing Boats: A Framework Using BeiDou Big Data and Deep Learning Algorithms by Fen Wang, Xingyu Liu, Tanxue Chen, Hongxiang Feng, Qin Lin

“…The findings underscore the need for strengthened surveillance during moratoriums and post-ban catch regulation to mitigate overfishing risks.…”
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A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelity by Ryan L'Abbate, Anthony D'Onofrio, Samuel Stein, Samuel Yen-Chi Chen, Ang Li, Pin-Yu Chen, Juntao Chen, Ying Mao

“…Consequently, there is an urgent need to use qubits efficiently and mitigate both present limitations and future complexities. …”
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Enhancing perpendicular magnetic anisotropy and magneto-optical signal of electron beam evaporated [Co/Pt]1 and [Co/Pt]2 thin films by D. Doménech, A. Villar, C. Redondo, N. A. Río-López, J. M. Porro, R. Morales

“…Adding a second Co/Pt repetition mitigates this limitation, yielding samples with both strong magneto-optical signals and high coercivities, featuring the largest effective anisotropy.…”
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Navigating Uncertainty: Advanced Techniques in Pedestrian Intention Prediction for Autonomous Vehicles—A Comprehensive Review by Alireza Mirzabagheri, Majid Ahmadi, Ning Zhang, Reza Alirezaee, Saeed Mozaffari, Shahpour Alirezaee

“…Autonomous vehicles present a promising solution to mitigate these fatalities by improving road safety through advanced prediction of pedestrian behavior. …”
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Limits of Solar Flare Forecasting Models and New Deep Learning Approach by G. Francisco, M. Berretti, S. Chierichini, R. Mugatwala, J. Fernandes, T. Barata, D. Del Moro

“…Reliable forecasting models are necessary to mitigate the risks posed by solar flares to human technology. …”
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Enhancing knee osteoarthritis diagnosis with DMS: a novel dense multi-scale convolutional neural network approach by Di Zhang, Yuting Dong, Yao Xu, Junhui Qian, Miaoyu Ye, Qiang Yuan, Jian Luo

“…This module utilizes dense connections in convolutions of varying sizes (1 × 1, 3 × 3, 5 × 5) and across layers, enhancing feature reuse and complexity recognition, thereby improving recognition capabilities. …”
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