An Integrated Mechanical Fault Diagnosis Framework Using Improved GOOSE-VMD, RobustICA, and CYCBD by Jingzong Yang, Xuefeng Li

“…By employing an energy-feature-driven fitness function, this approach achieves synergistic optimization of the mode number and penalty factor. …”
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Biomass Demineralization and Pretreatment Strategies to Reduce Inhibitor Concentrations in Itaconic Acid Fermentation by <i>Aspergillus terreus</i> by Gregory J. Kennedy, Michael J. Bowman, Kim L. Ascherl, Nancy N. Nichols, Badal C. Saha

“…., lignocellulose) has been shown to be problematic, requiring post-hydrolysis mitigation to allow growth and IA production by the fungus. …”
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Rapid flips between warm and cold extremes in a warming world by Sijia Wu, Ming Luo, Gabriel Ngar-Cheung Lau, Wei Zhang, Lin Wang, Zhen Liu, Lijie Lin, Yijing Wang, Erjia Ge, Jianfeng Li, Yuanchao Fan, Yimin Chen, Weilin Liao, Xiaoyu Wang, Xiaocong Xu, Zhixin Qi, Ziwei Huang, Faith Ka Shun Chan, David Yongqin Chen, Xiaoping Liu, Tao Pei

“…Abstract Rapid temperature flips are sudden shifts from extreme warm to cold or vice versa–both challenge humans and ecosystems by leaving a very short time to mitigate two contrasting extremes, but are yet to be understood. …”
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Tracking objects using Grassmann manifold appearance modeling based on wireless multimedia sensor networks by Yinghong Xie, Xiaosheng Yu, Chengdong Wu

“…Visual object tracking methods based on wireless multimedia sensor network is one of the research hotspots while the present linear method for processing feature vectors often lead to the tracking drift when tracking object with significant nonplanar pose variations through wireless sensor networks. …”
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LWSARDet: A Lightweight SAR Small Ship Target Detection Network Based on a Position–Morphology Matching Mechanism by Yuliang Zhao, Yang Du, Qiutong Wang, Changhe Li, Yan Miao, Tengfei Wang, Xiangyu Song

“…To address these challenges, we propose a lightweight SAR small ship detection network, LWSARDet, which mitigates feature redundancy and reduces computational complexity in existing models. …”
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DMA-Net: Dynamic Morphology-Aware Segmentation Network for Remote Sensing Images by Chao Deng, Haojian Liang, Xiao Qin, Shaohua Wang

“…The proposed framework incorporates three primary parts: a Multi-Axis Vision Transformer (MaxViT) encoder achieves a balance between local feature extraction and global context modeling through multi-axis self-attention mechanisms; a Hierarchy Attention Decoder (HA-Decoder) enhanced with Hierarchy Convolutional Groups (HCG) for precise recovery of fine-grained spatial details; and a Channel and Spatial Attention Bridge (CSA-Bridge) to mitigate the encoder–decoder semantic gap while amplifying discriminative feature representations. …”
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A Novel Approach to Retinal Blood Vessel Segmentation Using Bi-LSTM-Based Networks by Pere Marti-Puig, Kevin Mamaqi Kapllani, Bartomeu Ayala-Márquez

“…The proposed architecture integrates Bidirectional Long Short-Term Memory (Bi-LSTM) layers with dropout to mitigate overfitting. A distinguishing feature of this approach is the column-wise processing, which improves feature extraction and segmentation accuracy. …”
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Identification of Elephant Rumbles in Seismic Infrasonic Signals Using Spectrogram-Based Machine Learning by Janitha Vidunath, Chamath Shamal, Ravindu Hiroshan, Udani Gamlath, Chamira U. S. Edussooriya, Sudath R. Munasinghe

“…The process converts seismic rumbles to a spectrogram and the existing methods of spectrogram feature extraction and appropriate machine learning algorithms are compared on their merit for automatic seismic rumble identification. …”
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A Relative Attitude Detection Method for Unmanned Aerial Vehicles Based on You Only Look Once Framework by Jingting Qiu, Feifan Yu, Fengrui Xu, Xinmin Chen, Jiqiang Wang

“…Within URA-YOLO, we propose an enhanced multiscale feature fusion (EMF) module that increases the network’s perceptual range and extracts feature information corresponding to various image sizes. …”
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Vision Foundation Model Guided Multimodal Fusion Network for Remote Sensing Semantic Segmentation by Chen Pan, Xijian Fan, Tardi Tjahjadi, Haiyan Guan, Liyong Fu, Qiaolin Ye, Ruili Wang

“…Subsequently, a multiscale cross-modal feature fusion comprising fusion enhancement and feature recalibration modules is proposed to emphasize the adaptive multiscale interaction of diverse complementary cues between each modality while suppressing the impact of noise and uncertainties present in RS data. …”
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TAE Predict: An Ensemble Methodology for Multivariate Time Series Forecasting of Climate Variables in the Context of Climate Change by Juan Frausto Solís, Erick Estrada-Patiño, Mirna Ponce Flores, Juan Paulo Sánchez-Hernández, Guadalupe Castilla-Valdez, Javier González-Barbosa

“…By combining advanced prediction models and feature selection strategies, this study advances the reliability of climate forecasts and contributes to the development of effective adaptation and mitigation measures in response to climate change challenges.…”
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DMN-YOLO: A Robust YOLOv11 Model for Detecting Apple Leaf Diseases in Complex Field Conditions by Lijun Gao, Hongwu Cao, Hua Zou, Huanhuan Wu

“…Specifically, the model integrates a multi-branch auxiliary feature pyramid network (MAFPN), along with Superficial Assisted Fusion (SAF) and Advanced Auxiliary Fusion (AAF) modules, to strengthen feature interaction, retain shallow-layer information, and improve high-level gradient transmission, thereby enhancing multi-scale lesion detection performance. …”
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YOLO-LSM: A Lightweight UAV Target Detection Algorithm Based on Shallow and Multiscale Information Learning by Chenxing Wu, Changlong Cai, Feng Xiao, Jiahao Wang, Yulin Guo, Longhui Ma

“…Second, a Multiscale Lightweight Convolution (MLConv) is designed, and a lightweight feature extraction module, MLCSP, is constructed to enhance the extraction of detailed information. …”
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Algorithmic Shadow Spectroscopy by Hans Hon Sang Chan, Richard Meister, Matthew L. Goh, Bálint Koczor

“…Finally, we measured a high-quality, experimental shadow spectrum of a spin chain on readily available IBM quantum computers, achieving the same precision as in noise-free simulations without using any advanced error mitigation, and verified scalability in tensor-network simulations of up to 100-qubit systems.…”
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A review of machine learning applications in heart health by Ava Perrone, Taghi M. Khoshgoftaar

“…This study conducts a comprehensive examination of feature selection methodologies, model architectures, and fine-tuning techniques related to diverse diagnostic and prognostic scenarios within the domain of heart health. …”
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Sea Surface Temperature Prediction Based on Spatio-Temporal Graph Contrastive Learning Network by Weihan Dai, Xiaoyu He, Xiulin Geng, Shuai Zhang, Ziheng Gao

“…Notably, STGLN employs both feature-level and topology-level data augmentation techniques to alleviate the influence of data noise. …”
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Estimation of minimal data sets sizes for machine learning predictions in digital mental health interventions by Kirsten Zantvoort, Barbara Nacke, Dennis Görlich, Silvan Hornstein, Corinna Jacobi, Burkhardt Funk

“…Prediction performance is analyzed based on dataset size (N = 100–3654), feature groups (F = 2–129), and algorithm choice (from Naive Bayes to Neural Networks). …”
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Immunosenescence and Inflammaging in Dogs and Cats: A Narrative Review by Brennen A. McKenzie

“…ABSTRACT A consistent and important feature of biological aging is the change in the types and functions of cells comprising the immune system. …”
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Stacking Ensemble Learning and SHAP-Based Insights for Urban Air Quality Forecasting: Evidence from Shenyang and Global Implications by Zhaoxin Xu, Huajian Zhang, Andong Zhai, Chunyu Kong, Jinping Zhang

“…Accurate air quality forecasting is essential for effective mitigation strategies, particularly in rapidly urbanizing regions. …”
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Scoping Review of the Impact of Culture on the Effectiveness of Quality Improvement Programs by Carlos Frederico Pinto, Robin Jones, Francisco Gutierrez-Delgado, Julia Tomkins, Martins Fideles Santos Neto

“…Power distance index (PDI; the ability to speak up without embarrassment) emerged in other industries as the most relevant trait affecting quality and team performance.RESULTSFew publications are available addressing such perspective, and the literature to date revealed that cultures with small PDI tend to perform better in health care safety and quality, and leadership behavior is a dominant feature in this condition. New techniques adopting psychological safety practices can mitigate cultural traits like PDI that hinder quality practices in oncology.CONCLUSIONThe authors consider that psychological safety practices are a culturally sensitive strategy to ASCO's Quality Programs that can mitigate local cultural barriers and develop leadership behaviors that enable safety and quality strategies, and foster more effective international collaboration in ASCO Quality Programs in the future.…”
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