Oceanographic and trophodynamic underpinnings of anchovy success in the northern California Current by Kelsey Swieca, Kelsey Swieca, Su Sponaugle, Su Sponaugle, Moritz S. Schmid, Jami Ivory, Robert K. Cowen

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Regional insights into the relationship between metabolic associated steatotic liver disease and chronic kidney disease: a socioeconomic perspective on disease correlation by Jiang Bai, Lijuan Zhang, Mingyan Zhang, Yifan Hao, Zhen Yi, Yun Zhou

“…Methods This analysis integrates MASLD and country-level CKD data from the Global Burden of Disease study 2021. …”
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NeuroFuzzXAI: A Hybrid Artificial Intelligence Framework for Epileptic Seizure Detection by Flavia COSTI, Emanuel COVACI, Ovidiu ROMAN, Darian ONCHIS

“…The deep learning component alone achieved a high classification accuracy, but integrating fuzzy logic refined decision boundaries and enhanced interpretability. …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…To further refine the predictive model, three feature selection methods—successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS), and principal component analysis (PCA)—were assessed. …”
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A Scoping Review Mapping Trans* and Gender Diverse People's Representation in Cancer Research by Morgan Stirling, Michaela A. Bourque, Mikayla Hunter, John Queenan, Claire Ludwig, Janice Ristock, Lyndsay Harrison, Amanda Ross‐White, Nathan C. Nickel, Annette Schultz, Versha Banerji, Jacqueline Gahagan, Alyson Mahar

“…We followed JBI's meta‐aggregation approach for mixed methods reviews by qualitizing quantitative data through narrative interpretation and pooling to integrate the extracted data. …”
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Orthodontic Ceramic Bracket Removal Using Lasers: A Systematic Review by Mateusz Michalak, Sylwia Kiryk, Agnieszka Kotela, Kamila Wiśniewska, Jan Kiryk, Jacek Zbigniew Zborowski, Jacek Matys, Maciej Dobrzyński

“…CO₂ and Er:YAG lasers were the most effective in reducing SBS while preserving enamel integrity. However, variations in laser settings, study methodologies, and the predominance of in vitro studies limit the ability to establish standardized clinical guidelines. …”
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Research on Underwater Target Detection Technology Based on SMV-YOLOv11n by Dongcheng Liao, Yijun Shen, Jinyu Ou, Yanlian Du

“…Traditional detection methods face challenges due to underwater environmental factors such as low brightness and high blurriness. …”
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The Role of ESG in Driving Firm Profitability by Mubanga Lackson Chipimo, John Bwalya, Joseph Katongo Kanyanga

“…Design/Methodology- Using a mixed-methods approach, the study analysed panel data from 2014 to 2024 for listed food companies in Zambia. …”
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BSE-YOLO: An Enhanced Lightweight Multi-Scale Underwater Object Detection Model by Yuhang Wang, Hua Ye, Xin Shu

“…Underwater images often exhibit characteristics such as low contrast, blurred and small targets, object clustering, and considerable variations in object morphology. Traditional detection methods tend to be susceptible to omission and false positives under these circumstances. …”
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Complete Coverage Path Planning for Wind Turbine Blade Wall-Climbing Robots Based on Bio-Inspired Neural Networks and Energy Consumption Model by Da Chen, Gang Yu, Shuchen Huang

“…To overcome the limitations of the existing inspection methods, which suffer from low detection precision and inefficiency, this paper proposes a novel complete coverage path planning (CCPP) algorithm for wall-climbing robots operating on wind turbine blades. …”
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Otomycosis risk after non-suppurative middle ear surgery by Fatih Gul, Ozgenur Kocak, Ali Ozturk, Mehmet Ali Babademez

“…Objectives: The aim of this study was to investigate the risk factors that may cause postoperative otomycosis in patients undergoing Chronic Nonsuppurative Otitis Media (CNSOM) surgery. Methods: In this retrospective study, 409 out of 523 patients met the inclusion criteria. 44 patients diagnosed with otomycosis CNSOM were analyzed. …”
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Dynamic Agricultural Pest Classification Using Enhanced SAO-CNN and Swarm Intelligence Optimization for UAVs by Shiwei Chu, Wenxia Bao

“…The rapid advancement of agricultural modernization demands urgent solutions for accurate and real-time pest monitoring to enhance crop productivity. Traditional manual methods lack efficiency and fail to capture dynamic pest behaviors, while existing deep learning models struggle with robustness in complex environments. …”
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Determination of Substructure and Sub-ballast Layer Thickness of High-Speed Railway by Tran Anh DUNG, Pham Van KY, Le Hai HA

“…This study focuses on determining the appropriate thickness for the sub-ballast and substructure layers to accommodate these axle loads. Using analytical methods, calculations were performed to determine optimal trackbed thickness. …”
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DCASAM: advancing aspect-based sentiment analysis through a deep context-aware sentiment analysis model by Xiangkui Jiang, Binglong Ren, Qing Wu, Wuwei Wang, Hong Li

“…To address these challenges, we propose the Deep Context-Aware Sentiment Analysis Model (DCASAM). This model integrates the capabilities of Deep Bidirectional Long Short-Term Memory Network (DBiLSTM) and Densely Connected Graph Convolutional Network (DGCN), enhancing the ability to capture long-distance dependencies and subtle contextual variations.The DBiLSTM component effectively captures sequential dependencies, while the DGCN component leverages densely connected structures to model intricate relationships within the data. …”
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A Daily Reference Crop Evapotranspiration Forecasting Model Based on Improved Informer by Junrui Pan, Long Yu, Bo Zhou, Junhong Zhao

“…Daily reference crop evapotranspiration (ET₀) is crucial for precision irrigation management, yet traditional prediction methods struggle to capture its dynamic variations due to the complexity and nonlinearity of meteorological conditions. …”
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STFDSGCN: Spatio-Temporal Fusion Graph Neural Network Based on Dynamic Sparse Graph Convolution GRU for Traffic Flow Forecast by Jiahao Chang, Jiali Yin, Yanrong Hao, Chengxin Gao

“…The characteristics of multivariate heterogeneity in traffic flow forecasting exhibit significant variation, heavily influenced by spatio-temporal dynamics and unforeseen events. …”
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Effect of exercise intervention on anxiety among college students: a meta-analysis by Peng Chen, Peng Chen, Nur Shakila Mazalan, Denise Koh, Yusha Gu

“…However, substantial heterogeneity was observed in single intervention time (I2 = 75%), intervention frequency (I2 = 75%), and intervention period (I2 = 72%), indicating significant variations across studies. These differences suggest that varying durations, frequencies, and periods of intervention yielded different effects on college students’ anxiety levels.ConclusionThis meta-analysis has found that structured physical exercise programs, especially mind–body integrative exercises, can alleviate anxiety to the greatest extent, offering evidence-based guidance for implementing targeted exercise interventions in college mental health programs.Systematic review registrationhttps://doi.org/10.37766/inplasy2024.11.0006.…”
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Spatiotemporal Analysis of Eco-Geological Environment Using the RAGA-PP Model in Zigui County, China by Xueling Wu, Jiaxin Lu, Chaojie Lv, Liuting Qin, Rongrui Liu, Yanjuan Zheng

“…Focusing on Zigui County, this study developed a 16-indicator evaluation system integrating geological, ecological, and socioeconomic factors. …”
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Tips and tricks for gut microbiota investigation using scanning electron microscopy (SEM): going from sample preparation to imaging and landscape analysis by Meriem Boukili, Omar Zmerli, Florence Fenollar, Sara Bellali, Jacques Bou Khalil

“…This concept emerges as a complementary technique capable of providing deeper insight to describe GM components previously elusive with other methods.…”
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Unraveling the Genetic and Environmental Risk Factors of Autism Spectrum Disorder Through a Case‐Control Study in Armenia by Meri Mkhitaryan, Tamara Avetisyan, Hermine Yeritsyan, Hayk Harutyunyan, Konstantin Yenkoyan

“…This study investigates genetic mutations and prenatal factors associated with ASD, including their interplay, in a multicenter case‐control study. Methods The study included 297 participants (149 ASD cases, 148 controls). …”
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