Loneliness and the risk of type 2 diabetes by Sara Fokdal Lehn, Lau Caspar Thygesen, Trine Allerslev Horsbøl, Allan Kofoed-Enevoldsen, Siri Rosenkilde, Sofie Have Hoffmann, Anne Bonde Thorsted, Katrine Rich Madsen, Peter Bindslev Iversen, Marie Stjerne Grønkjær

“…Loneliness was based on self-report, while type 2 diabetes was measured using an algorithm combining several health registers including type 2 diabetes patients treated both within the hospital sector and general practice. …”
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CCD Standard Curve Fitting for Microarray Detection Base on Multi-Layer Perceptron by Zhenhua Gan, Dongyu He, Peishu Wu, Baoping Xiong, Nianyin Zeng, Fumin Zou, Feng Guo, Qin Bao, Fengyan Zhao

“…The experimental results show that the MLP neural network constrained by minimizing the relative error has good fitting performance for the standard curve of CCD scanner, with the maximum relative error of only 0.89% while the standard deviation of relative error of only 0.25%. …”
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Integrated single cell and bulk RNA sequencing analyses reveal the impact of tryptophan metabolism on prognosis and immunotherapy in colon cancer by Yanyan Hu, Ximo Xu, Hao Zhong, Chengshen Ding, Sen zhang, Wei Qin, Enkui Zhang, Duohuo Shu, Mengqin Yu, Naijipu Abuduaini, Xiao Yang, Bo Feng, Jianwen Li

“…The Oncopredict algorithm facilitated the identification of sensitive chemotherapeutic agents, while the immune escape score was employed to evaluate the immunotherapy response across risk groups. …”
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A global daily mesoscale front dataset from satellite observations: in situ validation and cross-dataset comparison by Q. Xing, H. Yu, W. Yu, W. Yu, W. Yu, W. Yu, X. Chen, X. Chen, X. Chen, X. Chen, H. Wang, H. Wang, H. Wang

“…The development of front detection algorithms has enabled the automatic extraction of frontal information from satellite observations, providing valuable tools for understanding the biophysical interactions within marine ecosystems. …”
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Machine learning, clinical-radiomics approach with HIM for hemorrhagic transformation prediction after thrombectomy and treatment by Sheng Hu, Junyu Liu, Jiayi Hong, Yuting Chen, Ziwen Wang, Jibo Hu, Shiying Gai, Xiaochao Yu, Jingjing Fu

“…An optimal machine learning (ML) algorithm was used for model development. Subsequently, models for clinical, radiomics, and clinical-radiomics were developed. …”
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Transformer Oil Acid Value Prediction Method Based on Infrared Spectroscopy and Deep Neural Network by Linjie Fang, Chuanshuai Zong, Zhenguo Pang, Ye Tian, Xuezeng Huang, Yining Zhang, Xiaolong Wang, Shiji Zhang

“…The traditional detection method of transformer oil acid value has limitations, such as long detection period and toxicity of reagents; while, with the traditional spectral analysis, it is difficult to realize the efficient extraction of key features related to the acid value content. …”
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Simulations suggest offshore wind farms modify low-level jets by D. Quint, D. Quint, J. K. Lundquist, J. K. Lundquist, J. K. Lundquist, D. Rosencrans

“…We develop and present an algorithm to detect LLJs at each hour of the year at each of these locations. …”
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Identifying propionate metabolism-related genes as biomarkers of sepsis development and therapeutic targets by Lechen Yang, Weifeng Shang, Dongjie Chen, Hang Qian, Sheng Zhang, Xiaojun Pan, Sisi Huang, Jiao Liu, Dechang Chen

“…High propionate metabolism was associated with metabolism such as short-chain fatty acids, while low metabolism was related to negative regulation of wound healing. …”
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Lantern-Explorer: A Collision-Avoidance Autonomous Exploration Drone System Based on Laser SLAM with Optimized Hardware and Software by L. Zhu, L. Zhu, R. Zhong, R. Zhong, D. Xie, D. Xie, X. Yuan, X. Yuan

“…On the software side, we designed an adaptive LiDAR odometry accuracy controller to achieve precise flight attitude control, ensuring high-speed flight while maintaining stability. Additionally, we proposed the improved omnidirectional LiDAR perception algorithm, FUEL-360, for autonomous exploration. …”
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SpecPCM: A Low-Power PCM-Based In-Memory Computing Accelerator for Full-Stack Mass Spectrometry Analysis by Keming Fan, Ashkan Moradifirouzabadi, Xiangjin Wu, Zheyu Li, Flavio Ponzina, Anton Persson, Eric Pop, Tajana Rosing, Mingu Kang

“…Our approach integrates contributions across multiple levels: application, algorithm, circuit, device, and instruction sets. We leverage a robust hyperdimensional computing (HD) algorithm with a novel dimension-packing method and develop specialized hardware for the end-to-end MS pipeline to overcome the nonideal behavior of PCM devices. …”
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Research on the integrated "cloud-edge-end" intelligent and precise management and control technology system for coal mine disasters by LIU Yubing, LI Yiteng, LI Zhonghui, YIN Shan, JING Chao, LI Kai, LI Zhenxing, ZHAO Shenglei, LIU Chengfei

“…On the cloud side, digital twin technology was applied for visual simulation, while coal mine major disaster safety situation analysis was conducted using Delphi theory and deep learning models. …”
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Joint Distribution pada Weighted Majority Vote (WMV) untuk Peningkatan Kinerja Sentiment Analysis Tersupervisi pada Dataset Twitter by Bagus Setya Rintyarna

“…Most of the sentiment analysis on the Indonesian language Twitter dataset relies on a single machine learning algorithm. This study combines the performance of various algorithms/experts while reducing the level of misclassification by updating the weights dynamically using a joint distribution-based weighted majority vote (WMV) from the Bayesian Network. …”
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Peningkatan Performa Ensemble Learning pada Segmentasi Semantik Gambar dengan Teknik Oversampling untuk Class Imbalance by Arie Nugroho, M. Arief Soeleman, Ricardus Anggi Pramunendar, Affandy Affandy, Aris Nurhindarto

“…The use of synthetic oversampling techniques can improve the level of accuracy in minority classes. The random forest algorithm experienced an increase in accuracy by 37% while the LGBM algorithm increased by 41%. …”
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Network-based machine learning reveals cardiometabolic multimorbidity patterns and modifiable lifestyle factors: a community-focused analysis of NHANES 2015–2018 by Danhui Mao, Junfang Mu, Yajing Li, Lu He, Qianhui Chai, Xin Zhao, Xiaojun Ren, Hui Cheng

“…Among the machine learning algorithms, Logistic Regression exhibited the best performance, with an Accuracy of 0.954 and an AUC-ROC area of 0.998. …”
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Smart agriculture: utilizing machine learning and deep learning for drought stress identification in crops by Tariq Ali, Saif Ur Rehman, Shamshair Ali, Khalid Mahmood, Silvia Aparicio Obregon, Rubén Calderón Iglesias, Tahir Khurshaid, Imran Ashraf

“…Notably, the accuracy of SVM was 82%, while gradient boosting and RNN showed 96%, and 94%, respectively and LSTM obtained an astounding 97% accuracy. …”
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Generalized Logistic Function: A Retracker to Improve the Accuracy of Water Level Time Series in Coastal Areas and Lakes by Arash Amini, Behzad Voosoghi, Mohammad Amin Khalili, Diego Di Martire, Shirzad Roohi, Mahmoud Pirooznia

“…The results demonstrate the superiority of the GLFA over the GLFN in coastal areas, while over lakes, the results are nearly equivalent. …”
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An Automated and Efficient Slope Unit Division Method Coupled with Computer Graphics and Hydrological Principles by Ting Xiao, Li Zhu, Lichang Wang, Beibei Yang, Can Wang, Haipeng Yao

“…This framework achieves automated slope unit delineation without thresholds while enabling multi-attribute fusion optimization, effectively addressing the shortcomings of HPAM. …”
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Personalized metronomic radiopharmaceutical therapy through injection profile optimization via physiologically based pharmacokinetic (PBPK) modeling by Aryan Golzaryan, M. Soltani, Farshad Moradi Kashkooli, Babak Saboury, Arman Rahmim

“…We designed a treatment algorithm to select optimal regimens with high AD, while investigating what we term radiopharmaceutical delivery payload (RDP). …”
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Simulation-Based Analysis of DRL Exploitation Rate for Voltage and Frequency Stability in a Single-Inverter Microgrid Control System by Noer Fadzri Perdana Dinata, Makbul Anwari Muhammad Ramli, Muhammad Irfan Jambak, Prisma Megantoro, Muhammad Abu Bakar Sidik

“…A comparison with a traditional Proportional-Integral-Derivative (PID) controller reveals that while the DRL agent with 2%-FER demonstrates strong performance in managing transient events, the PID controller provides superior stability in steady-state operation. …”
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Comparative Analysis of Resampling Techniques for Class Imbalance in Financial Distress Prediction Using XGBoost by Guodong Hou, Dong Ling Tong, Soung Yue Liew, Peng Yin Choo

“…Results show that standard Synthetic Minority Oversampling Technique (SMOTE) enhanced F1-score (up to 0.73) and Matthews Correlation Coefficient (MCC, up to 0.70), while SMOTE-Tomek and Borderline-SMOTE further boosted recall, slightly sacrificing precision. …”
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