Rural Renewable Energy Resources Assessment and Electricity Development Scenario Simulation Based on the LEAP Model by Hai Jiang, Haoshuai Jia, Yong Qiao, Wenzhi Liu, Yijun Miao, Wuhao Wen, Ruonan Li, Chang Wen

“…By optimizing the hybrid power generation system through genetic algorithms, wind energy, solar energy, biomass energy, and coal power are combined to balance the annual electricity demand in rural areas. …”
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Validating laboratory predictions of soil rewetting respiration pulses using field data by X. Li, X. Li, M. Pallandt, M. Pallandt, D. Naidu, D. Naidu, J. Rousk, G. Hugelius, G. Hugelius, S. Manzoni, S. Manzoni

“…LR and FR were explained by six predictors using random forest algorithms and partial dependence plots. Results indicated that the most important drivers of LR and FR were SOC and temperature, respectively. …”
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A Multi-Spatial-Scale Ocean Sound Speed Profile Prediction Model Based on a Spatio-Temporal Attention Mechanism by Shuwen Wang, Ziyin Wu, Shuaidong Jia, Dineng Zhao, Jihong Shang, Mingwei Wang, Jieqiong Zhou, Xiaoming Qin

“…Nowadays, spatio-temporal series prediction algorithms are emerging, but their prediction accuracy requires improvement. …”
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Enhanced 3-D Reconstruction Method for Polarimetric Coherent Optimal-Based Tomographic SAR by Shuhang Dong, Zekun Jiao, Liangjiang Zhou, Xiaolan Qiu, Qiancheng Yan

“…However, in the practical application, there are relatively few models and algorithms for full-polarized SAR joint 3-D imaging. …”
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Diagnostic Utility of ¹⁸F-FDG PET/CT in Infective Endocarditis by Corina-Ioana Anton, Alice-Elena Munteanu, Mihaela Raluca Mititelu, Militaru Alexandru Ștefan, Cosmin-Alexandru Buzilă, Adrian Streinu-Cercel

“…Its integration into diagnostic algorithms may improve clinical management and outcomes in complex IE cases.…”
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A national survey on how to improve the integration of traditional Chinese medicine and artificial intelligence: Attitudes and perceptions from medical staff by Yinger Gu, Xinyin Hu, Hye Won Lee, Zheng Yao, Tianyi Zhou, Nv Xia, Pingchun Yang, Jinglu Guo, Haifeng Huang, Lisi Wang, Wei Wang, Cheng Wang, Qiaoping Zhao, Lingling Lou, Wenjie Wu, Ke Ren, Guomei You, Longlong Fan, Jue Zhou, Fangfang Wang, Xiaoteng Chen, Fan Qu

“…The top three concerns about the potential risks associated with the integration of TCM and AI were the misinterpretation of cultural contexts, flexibility in dialectical treatment, and simplification of traditional TCM experience by algorithms. The top three most promising applications were the intelligent syndrome differentiation system (54.6 %), the TCM four diagnostic instruments (49.1 %), and the acupuncture and Tui Na robot (47.8 %). …”
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Biodegradation of CAHs and BTEX in groundwater at a multi-polluted pesticide site undergoing natural attenuation: Insights from identifying key bioindicators using machine learning... by Feiyang Xia, Tingting Fan, Mengjie Wang, Lu Yang, Da Ding, Jing Wei, Yan Zhou, Dengdeng Jiang, Shaopo Deng

“…Advanced machine learning (ML) algorithms help identify key microbial indicators for different pollution types (CAHs, BTEX plumes, and mixed plumes). …”
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A Systematic Review of the Applications of Electronic Nose and Electronic Tongue in Food Quality Assessment and Safety by Ramkumar Vanaraj, Bincy I.P, Gopiraman Mayakrishnan, Ick Soo Kim, Seong-Cheol Kim

“…These bio-inspired sensing systems mimic human olfactory and gustatory functions through sensor arrays and advanced data processing techniques, including artificial intelligence and pattern recognition algorithms. The e-nose is primarily used for detecting volatile organic compounds (VOCs) in food, making it effective for freshness evaluation, spoilage detection, aroma profiling, and adulteration identification. …”
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Multiple automated machine-learning prediction models for postoperative reintubation in patients with acute aortic dissection: a multicenter cohort study by Shuyu Wen, Chao Zhang, Junwei Zhang, Ying Zhou, Yin Xu, Minghui Xie, Jinchi Zhang, Zhu Zeng, Long Wu, Weihua Qiao, Xingjian Hu, Xingjian Hu, Nianguo Dong, Nianguo Dong

“…This study aims to employ machine learning algorithms to establish a practical platform for the prediction of reintubation.MethodsA total of 861 patients diagnosed with AAD and undergoing surgical procedures, 688 patients as training and testing cohort from a single center, and 173 patients as validation cohort from four centers were enrolled. …”
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Transforming urinary stone disease management by artificial intelligence-based methods: A comprehensive review by Anastasios Anastasiadis, Antonios Koudonas, Georgios Langas, Stavros Tsiakaras, Dimitrios Memmos, Ioannis Mykoniatis, Evangelos N. Symeonidis, Dimitrios Tsiptsios, Eliophotos Savvides, Ioannis Vakalopoulos, Georgios Dimitriadis, Jean de la Rosette

“…Electronic patient records, containing big data, offer AI the opportunity to develop and analyze more precise and efficient diagnostic and treatment algorithms. Nevertheless, the existing applications are not generalizable in real-life practice, and high-quality studies are needed to establish the integration of AI in the management of urinary stone disease.…”
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Integrating machine learning and single-cell sequencing to identify shared biomarkers in type 1 diabetes mellitus and clear cell renal cell carcinoma by Yi Li, Rui Zeng, Rui Zeng, Yuhua Huang, Yumin Zhuo, Jun Huang

“…Subsequently, the LASSO and SVM algorithms were employed to identify shared hub genes between the two diseases. …”
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Geospatial impact evaluation of a low-cost agricultural intervention for enhancing environmental resilience by Pratap Khattri, Rachel Sayers, Kunwar K. Singh, Ryan Slapikas, Chet Bahadur Tamang, Dinee Tamang, Brad Sagara, Ariel BenYishay

“…We assessed the causal impact of a program promoting sugarcane farming on its adoption and environmental outcomes, measured using multi-temporal satellite imagery, crop phenology, and clustering algorithms, along with machine learning and visual interpretation methods. …”
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Population Structure of the Invasive Asian Tiger Mosquito, Aedes albopictus, in Europe by Margaret K. Corley, Luciano Veiga Cosme, Peter A. Armbruster, Nigel Beebe, Anna Bega, Sebastien Boyer, Beniamino Caputo, Chun‐Hong Chen, Jacob E. Crawford, Alessandra dellaTorre, Roger Eritja, Michael C. Fontaine, Richard J. Gill, Trang Huynh, Perparim Kadriaj, Kevin Maringer, Ademir Jesus Martins, Andrew Maynard, Shomen Mukherjee, Leonard E. Munstermann, Verena Pichler, Maria Sharakhova, Sinnathamby Noble Surendran, Sandra Urbanelli, Enkelejda Velo, Isra Wahid, Muhammet Mustafa Akiner, Georgios Balatsos, Gilles Besnard, Maria Louise Borg, Daniel Bravo‐Barriga, Rubén Bueno Marí, Francisco Collantes, Cintia Horvath, Mihaela Kavran, Raquel Medialdea‐Carrera, Tanya Melillo, Antonios Michaelakis, Ognyan Mikov, Arianna Puggioli, Elton Rogozi, Francis Schaffner, Kayleigh Hackett, Thomas Johnson, Tina Wu, João Pinto, Vera Valadas, Adalgisa Caccone

“…We used a SNP chip to genotype 748 Ae. albopictus mosquitoes from 41 localities across Europe, 28 localities in the native range in Asia, and 4 in the Americas. Using multiple algorithms, we examined population genetic structure and differentiation within Europe and across our global dataset to gain insight into the origin of the invasive European populations. …”
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3D‐Printed Titanium Trabecular Scaffolds with Sustained Release of Hypoxia‐Induced Exosomes for Dual‐Mimetic Bone Regeneration by Lincong Luo, Weihan Zheng, Jiaying Li, Tingting Chen, Wanting Xue, Tao Lin, Mingrui Liu, Zi Yan, Jiaxin Yang, Jiamin Li, Jiahao Pu, Yaobin Wu, Konghe Hu, Shiyu Li, Wenhua Huang

“…BTPS is designed using Voronoi algorithms and imaging data, and replicates the geometry and mechanical properties of natural bone. …”
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Toward causal artificial intelligence approach for PM2.5 interpretation: A discovery of structural causal models by Mallika Kliangkhlao, Apaporn Tipsavak, Thanathip Limna, Racha Dejchanchaiwong, Perapong Tekasakul, Kirttayoth Yeranee, Thanyabun Phutson, Bukhoree Sahoh

“…The PC-based SCM is particularly outstanding when compared to other algorithms like GES- and Chow-Lui-based SCMs, delivering a remarkable performance in discovering cause-and-effect relationships with an F-measure of approximately 80 % compared to the gold-standard SCM. …”
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Deep reinforcement learning agents for dynamic spectrum access in television whitespace cognitive radio networks by Udeme C. Ukpong, Olabode Idowu-Bismark, Emmanuel Adetiba, Jules R. Kala, Emmanuel Owolabi, Oluwadamilola Oshin, Abdultaofeek Abayomi, Oluwatobi E. Dare

“…This work presents the development of Deep RL (DRL) models for enhanced DSA in TV Whitespace (TVWS) cognitive radio networks using Deep Q-Networks (DQN) and Quantile-Regression (QR-DQN) algorithms. The implementation was done in the Radio Frequency Reinforcement Learning (RFRL) Gym, a training environment of the RF spectrum designed to provide comprehensive functionality. …”
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State of Charge Estimation for Li-Ion Batteries: An Edge-Based Data-Driven Approach by Sesidhar Dvsr, Chandrashekhar Badachi, Chandrashekar Nagawaram, Panduranga Chary Kondoju, C. Dhanamjayulu, Innocent Kamwa

“…Recently, the confluence of Edge computing with IoT has enabled resource constrained embedded devices to implement machine learning algorithms. TinyML, with its emphasis on integrating machine learning into embedded systems, seeks to move the end users away from high-performance machines, towards devices with limited resources and power. …”
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Long-term planning optimisation of sustainable energy systems: A systematic review and meta-analysis of trends, drivers, barriers, and prospects by Soheil Mohseni, Alan C. Brent

“…In this intricate landscape, the interdependence of optimisation variables that underlie sustainable energy system planning and optimisation processes underscores the critical role of advanced computational models, notably optimisation algorithms and forecasting techniques, as well as innovative business models tailored to renewable energy in the context of diverse distributed energy options. …”
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Automated noise modelling using a triangulated terrain model by Nadine Hobeika, Laurens van Rijssel, Maarit Prusti, Constantijn Dinklo, Denis Giannelli, Balázs Dukai, Arnaud Kok, Rob van Loon, René Nota, Jantien Stoter

“…This study uses the 3D noise modeling guidelines of Common Noise Assessment Methods in Europe (CNOSSOS-EU). Algorithms have been developed and implemented in a prototype to generate and validate the paths between receiver and source points using a TIN that includes the buildings as well as the noise absorption properties of the terrain. …”
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Scoring model for exploring factors influencing mortality in dengue patients at a tertiary care hospital: a retrospective study by Abhishek S. Rao, B. H. Karthik Pai, K. Adithi, Lakshmi Belur Keshav, Karan Malhotra, Sneha Nayak, H. K. Sachidananda

“…The model was developed using three state-of-the-art algorithms: Logistic Regression (LR), Linear SVM, and Ridge Classifier (RC). …”
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