Graph neural networks and transfer entropy enhance forecasting of mesozooplankton community dynamics by Minhyuk Jeung, Min-Chul Jang, Kyoungsoon Shin, Seung Won Jung, Sang-Soo Baek

“…Therefore, we demonstrate that incorporating the graph structure of ecosystem dynamics can improve the accuracy of mesozooplankton modeling by providing influential information about species of interest. …”
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Precision in practice: exploring the impact of ai and machine learning on ultrasound guided regional anaesthesia by Noor Ul Huda Bhatti, Syed Ghazi Ali Kirmani, Maryam Butt

“…Considering this, anaesthesiologists nationwide must integrate effective AI models to improve their clinical practice. This would minimize adverse outcomes in regional anaesthesia and ultimately enhance patient care and satisfaction. …”
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Enhancing river and lake wastewater reuse recommendation in industrial and agricultural using AquaMeld techniques by J. Priskilla Angel Rani, C. Yesubai Rubavathi

“…The main motivation is combining the two models into the MLP-RNN to improve prediction accuracy. …”
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Artificial intelligence assisted wearable flexible sensors for sports: research progress in technology integration and application by Jie Wu, Zhiqi Mo, Xing Gao, Wanru Xin, Weiquan Shi, Jaeyoung Park

“…This article provides a comprehensive review of the latest advancements in artificial intelligence-assisted wearable flexible sensors for motion detection, focusing on the operational mechanisms, performance enhancements, and algorithm optimization of convolutional neural networks (CNN), temporal data modeling, multimodal fusion technology, and natural language generation. …”
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Enhanced Fishing Monitoring in the Central-Eastern North Pacific Using Deep Learning with Nightly Remote Sensing by Jiajun Li, Jinyou Li, Kui Zhang, Xi Li, Zuozhi Chen

“…The results showed that YOLO-based computer vision models effectively detected dense small fishing targets, with original YOLOv8 achieving a precision (P) of 89% and a recall (R) of 79%, while refined versions improved these metrics to 93% and 99%, respectively. …”
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Knowledge graph based entity selection framework for ad-hoc retrieval by Pankaj Singh, Plaban Kumar Bhowmick

“…Recent entity-based retrieval models utilizing knowledge bases have shown significant improvement in ad-hoc retrieval. …”
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AGW-YOLO-Based UAV Remote Sensing Approach for Monitoring Levee Cracks by HU Weibo, ZHOU Shaoliang, ZHAO Erfeng, ZHAO Xueqiang

“…The advanced WIoUv3 loss function further boosted the model's performance, achieving a mAP@0.5 of 84.5% and an F1 score of 83%, marking an approximate 3.4% improvement over the baseline, and showcasing a favorable balance between detection accuracy and model efficiency. …”
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Predicting adolescent psychopathology from early life factors: A machine learning tutorial by Faizaan Siddique, Brian K. Lee

“…Future early risk predictions models may improve with the inclusion of additional relevant covariates.…”
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Timeseries Fault Classification in Power Transmission Lines by Non-Intrusive Feature Extraction and Selection Using Supervised Machine Learning by Rab Nawaz, Hani A. Albalawi, Syed Basit Ali Bukhari, Khawaja Khalid Mehmood, Muhammad Sajid

“…Feature selection through dimensionality reduction techniques is used to improve model performance and more efficient use of computational resources. …”
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Review of Research on Artificial Intelligence-driven Joint Radar Communication by Xianmei WANG, Xiangbo LIU, Yuzheng REN, Yang LU, Haijun ZHANG

“…Traditional joint radar communication algorithms often rely on precise mathematical modeling and channel estimation and cannot adapt to dynamic and complex environments that are difficult to describe. …”
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Predicting Olive Tree Chlorophyll Fluorescence Using Explainable AI with Sentinel-2 Imagery in Mediterranean Environment by Leonardo Costanza, Beatriz Lorente, Francisco Pedrero Salcedo, Francesco Pasanisi, Vincenzo Giannico, Francesca Ardito, Carlota María Martí Martínez, Simone Pietro Garofalo

“…The objective of this study is to improve the monitoring of olive tree fluorescence (Fv′/Fm′) via remote sensing in a Mediterranean environment, where the frequency of stress factors, such as drought, is increasing. …”
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3D Reconstruction of the Human Colon From Capsule Endoscope Video by Pal Anders Floor, Ivar Farup, Marius Pedersen

“…In this paper, we investigate the possibility of constructing 3D models of whole sections of the human colon using image sequences from wireless capsule endoscope video, providing improved visualization as well as position localization of pathologies for gastroenterologists. …”
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Calibration of Integrated Low-Cost Environmental Sensors for Urban Air Temperature Based on Machine Learning by Fang Nan, Chao Zeng, Huanfeng Shen, Liupeng Lin

“…Multiple linear regression (MLR) and light gradient boosting machine (LightGBM) algorithms were employed for calibration, with leave-one-out cross-validation (LOOCV) being used for model evaluation. …”
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Exosomal microRNA signatures in youth at clinical high risk for bipolar disorder by Xinyu Meng, Shengmin Zhang, Yingzhen Xu, Zaohui Ma, Shuzhe Zhou, Yantao Ma, Hong Ma, Xin Yu, Lili Guan

“…Future research should integrate additional biomarkers for improved discriminative performance.…”
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Kalman Filter-Based Fusion of LiDAR and Camera Data in Bird’s Eye View for Multi-Object Tracking in Autonomous Vehicles by Loay Alfeqy, Hossam E. Hassan Abdelmunim, Shady A. Maged, Diaa Emad

“…Recent multi-modal approaches have improved performance but rely heavily on complex, deep-learning-based fusion techniques. …”
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Myoelectric Control in Rehabilitative and Assistive Soft Exoskeletons: A Comprehensive Review of Trends, Challenges, and Integration with Soft Robotic Devices by Alejandro Toro-Ossaba, Juan C. Tejada, Daniel Sanin-Villa

“…Additionally, we identify persistent challenges such as EMG signal variability, computational complexity, and the real-time adaptability of control algorithms, which limit clinical implementation. By interpreting recent trends, this review highlights the need for improved EMG acquisition techniques, robust adaptive control frameworks, and enhanced real-time learning to optimize human-exoskeleton interaction. …”
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Progress in plant genome sequencing: research directions by M. K. Bragina, D. A. Afonnikov, E. A. Salina

“…Since the first plant genome of Arabidopsis thaliana has been sequenced and published, genome sequencing technologies have undergone significant changes. New algorithms, sequencing technologies and bioinformatic approaches were adopted to obtain genome, transcriptome and exome sequences for model and crop species, which have permitted deep inferences into plant biology. …”
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Enhanced Subspace Iteration Technique for Probabilistic Modal Analysis of Statically Indeterminate Structures by Hongfei Cao, Xi Peng, Bin Xu, Fengjiang Qin, Qiuwei Yang

“…Compared to existing stochastic modal analysis algorithms, the proposed method offers improved computational accuracy and efficiency, particularly in scenarios involving high-discreteness random analyses.…”
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Detection and Prediction of Wind and Solar Photovoltaic Power Ramp Events Based on Data-Driven Methods: A Critical Review by Jie Zhang, Xinchun Zhu, Yigong Xie, Guo Chen, Shuangquan Liu

“…Our analysis reveals that while detection algorithms for ramp events have matured and the overall predictive performance of power forecasting models has improved, existing approaches often struggle to capture localized ramp phenomena, resulting in persistent deviations. …”
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Aberrant fragmentomic features of circulating cell-free mitochondrial DNA enable early detection and prognosis prediction of hepatocellular carcinoma by Yang Liu, Fan Peng, Siyuan Wang, Huanmin Jiao, Kaixiang Zhou, Wenjie Guo, Shanshan Guo, Miao Dang, Huanqin Zhang, Weizheng Zhou, Xu Guo, Jinliang Xing

“…Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. …”
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