A Development of a Sound Recognition-Based Cardiopulmonary Resuscitation Training System by Dong Hyun Choi, Yoon Ha Joo, Ki Hong Kim, Jeong Ho Park, Hyunjin Joo, Hyoun-Joong Kong, Hyunju Lee, Kyoung Jun Song, Sungwan Kim

“…Each spectrogram was matched with the depth, rate, and release velocity of the compression measured at the same time interval by the ZOLL X Series monitor/defibrillator. Deep learning models utilizing spectrograms as input were trained using transfer learning based on EfficientNet to predict the depth (Depth model), rate (Rate model), and release velocity (Recoil model) of compressions. …”
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Two-decade spatiotemporal variations in ground-level ozone over Ontario, Canada by Zhou Zang, Jane Liu, Erjia Ge, Yi Zhang

“…Understanding long-term trends and spatially explicit details of O3 is important for supporting air quality management in Ontario.MethodWe construct a high-resolution (daily, 10 km) dataset of maximum daily 8-hour average O3 (MDA8 O3) over Ontario from 2004 to 2023, through a two-step machine learning model. …”
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Ecosystem services thresholds and interconnected feedback loops in the vulnerable Tarim River Basin: Confronting climate and vegetation transformations by Chun Luo, Xiaofei Ma, Yonghui Wang, Wei Yan, Yonglong Han, Wei Yu, Binbin Fan

“…Ecological thresholds play a key role in understanding ecosystem stability and vulnerability, and in predicting the impacts of future environmental changes. …”
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Analysis of antibiotic use and access to drugs among poultry farmers in Kenya by Dishon M. Muloi, Mitchelle R. Kasudi, Maurice K. Murungi, Eugine Lusanji Ibayi, Samuel Kahariri, Charity Karimi, Max Korir, Bridgit Muasa, Damaris Mwololo, Romona Ndanyi, Robert Ndungi, Jane Njiru, Ruth Omani, Rose Owada, Sylvia Omulo, Allan Azegele, Eric M. Fèvre

“…Using a machine learning framework, we predicted farm-level antibiotic use based on collected demographic and production traits. …”
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Quantitative 3D reconstruction of viral vector distribution in rodent and ovine brain following local delivery by Roberta Poceviciute, Kenneth Mitchell, Angeliki Maria Nikolakopoulou, Suehyun K. Cho, Xiaobo Ma, Phillip Chen, Samantha Figueroa, Ethan J. Sarmiento, Aryan Singh, Oren Hartstein, William G. Loudon, Florent Cros, Alexander S. Kiselyov

“…This pipeline, which combined existing and newly developed machine-learning and other computational tools, effectively removed false positive artifacts abundant in large-scale images of uncleared tissue sections, and subsampling adequately predicted the dispersion of model viral vectors from the point of local drug delivery. …”
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Calculation of capacity and optimization design-composite slab wall soil solidification foundation based on neural network by Linggang ZHOU, Yiting HU, Xinwei CHEN, Feng TU, Zhaofeng WU, Yang YU, Yanbing WANG, Yin MAN, Weichao LI

“…Objective The soil solidification technique is widely used in soft foundation treatment. To exploit spatial plasticity of this technique, composite slab wall soil solidification foundations have gradually been applied in engineering projects. …”
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Spatiotemporal Changes of China's Carbon Emissions by Bofeng Cai, Xiuquan Wang, Guohe Huang, Jinnan Wang, Dong Cao, Brian W. Baetz, Lei Liu, Hua Zhang, Adam Fenech, Zhu Liu

“…This suggests a clear transition to a more intensive economic growth model in South China as a result of the energy conservation and emission reduction policies, while the expanded carbon hot spots in North China are mainly dominated by the Grand Western Development Program. …”
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Impact of a national primary care pay-for-performance scheme on ambulatory care sensitive hospital admissions: a small-area analysis in England by Tim Doran, Christos Grigoroglou, Luke Munford, Evangelos Kontopantelis, Navneet Kapur, Darren Ashcroft, Roger Webb

“…Objective We aimed to spatially describe hospital admissions for ambulatory care sensitive conditions (ACSC) in England at small-area geographical level and assess whether recorded practice performance under one of the world’s largest primary care pay-for-performance schemes led to reductions in these potentially avoidable hospitalisations for chronic conditions incentivised in the scheme.Setting We obtained numbers of ACSC hospital admissions from the Hospital Episode Statistics database and information on recorded practice performance from the Quality and Outcomes Framework (QOF) administrative dataset for 2015/2016. …”
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Urban morphology impacts on urban microclimate using artificial intelligence – a review by Ahmed Marey, Jiwei Zou, Sherif Goubran, Liangzhu Leon Wang, Abhishek Gaur

“…By synthesizing 111 studies over the last decade utilizing urban morphology and AI models to predict urban microclimate, this review aims to bridge these gaps and highlight AI’s unique potential to contribute to the field. …”
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Fast real-time detection and counting of thrips in greenhouses with multi-level feature attention and fusion by Zhangzhang He, Xinyue Chen, Ying Gao, Yu Zhang, Yuheng Guo, Tong Zhai, Xiaochen Wei, Huan Li, Haipeng Zhu, Yongkun Fu, Zhiliang Zhang, Zhiliang Zhang

“…Next, we design a lightweight channel-spatial hybrid attention mechanism to further refine multi-scale features, enhancing the model’s ability to extract global and local features with minimal computational cost. …”
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Anthropogenic and natural influence on vegetation ecosystems from 1982 to 2023 by Teligeer Bao, Huaqiang Li, Yonghong Hao, Matthew Tom Harrison, Ke Liu, Gulnazar Ali

“…Here, we used 12 machine learning algorithms to perform pixel correction on 42 years of moderate resolution imaging spectroradiometer normalized difference vegetation index (NDVI) and GIMMS NDVI data. The models exhibited high accuracy (93%–97%), yielding a robust ensemble R ^2 of 0.88 at the spatial scale. …”
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Multi-Source Rainfall Data Assimilation based on Broad Learning System over Yunnan Province by Yuanyuan ZHOU, Xiaohui YANG, Tiangui XIAO

“…The accurate estimation of rainfall is always a topic of concern， given its pivotal role in accurately predicting rainfall-related disasters.This study proposed a multi-source rainfall assimilation technology based on a broad learning system （BLS） to improve the accuracy of rainfall estimation.Yunnan Province， located in China's low-latitude plateau， was chosen as the geographical area of interest to establish a multi-source rainfall assimilation model within this region.In particular， the model utilizes five satellite-derived rainfall datasets （3B42V7， IMERG， GSMaP， CMORPH， PERSIANN） and the latitude and longitude information as the source data， and the ground-based rainfall gauge data serves as the reference data.The time span of all the datasets is from April 2014 to December 2017.A leave-one-year-out cross-validation （LOYOCV） method was applied to verify the performance of the established assimilation model， where statistical indicators including Pearson’s correlation coefficient （CC）， root-mean square error （RMSE）， mean absolute error （MAE）， Nash efficiency coefficient （NSE） and Kling-Gupta efficiency （KGE） were used to quantify the accuracy of assimilation rainfall at different spatiotemporal scales.Concurrently， assimilation models based on support vector machine （SVM） and deep neural network （DNN） were established to highlight the accuracy and efficiency of the BLS， respectively.Additionally， the effectiveness of the latitude and longitude information within the proposed assimilation model was examined.The results show that the daily average statistical index of assimilation rainfall based on BLS is better than that of the other five satellite-based products in LOYOCV.At the temporal scale， the proposed assimilation technique effectively reflects the temporal variations observed in gauge-recorded rainfall.Moreover， it can accurately estimate the rainfall amounts during rainstorms in Yunnan Province throughout 2017.It is worth noting that the rainfall data generated through the BLS method outperforms the CMORPH product （the most accurate one among the five satellite-derived rainfall products） in both rainy and dry seasons （May to October and November to April of next year， respectively）.At the spatial scale， BLS-based rainfall results in most areas of Yunnan Province showed higher CC and NSE as well as smaller RMSE and MAE than the satellite-based products.The evaluation of the assimilation models based on BLS， SVM， and DNN highlights that the BLS exhibits superior functional mapping capabilities compared to SVM and demands fewer computational resources than DNN.It is reasonable to conclude that the multi-source rainfall assimilation approach utilizing the BLS while incorporating latitude and longitude information can enhance the precision of rainfall estimates in Yunnan Province.The proposed method presents practical significance in multi-source rainfall data assimilation.…”
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Immune landscape and TAM density in endometrial cancer: implications for immune checkpoint inhibitors efficacy by Olivia Le Saux, Renaud Sabatier, Isabelle Treilleux, Léa-Isabelle Renaud, Pierre-Emmanuel Brachet, Alejandra Martinez, Jean-Sébastien Frenel, Cyril Abdeddaim, Justine Berthet, Sarah Barrin, Amélie Colombe-Vermorel, Laetitia Odeyer, Alexandra Lainé, Christophe Caux, Bertrand Dubois, Isabelle Ray-Coquard

“…Using a multivariate logistic regression model, we found that a low density of CD68 + tumor-associated macrophages (TAMs) in the stroma, was associated with response to ICI in EC (odds ratio = 11.67, 95% CI (1.69–237.45), p  = 0.033) and showed good accuracy in predicting response to ICI in the whole cohort (AUC = 0.75, 95% CI (0.59–0.91)). …”
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New insights into the role of mitophagy related gene affecting the metastasis of osteosarcoma through scRNA-seq and CRISPR-Cas9 genome editing by Sikuan Zheng, Mengliang Luo, Hong Huang, Xuanxuan Huang, Zhidong Peng, Shaowei Zheng, Jianye Tan

“…We observed that it consistently predicts patient prognosis in both internal and external datasets, demonstrating strong robustness and stability. …”
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Advancements in Medical Radiology Through Multimodal Machine Learning: A Comprehensive Overview by Imran Ul Haq, Mustafa Mhamed, Mohammed Al-Harbi, Hamid Osman, Zuhal Y. Hamd, Zhe Liu

“…This review may help clinicians and researchers comprehend the spatial distribution of the field, outline the current level of advancement, and identify areas of research that need to be explored regarding MMML in radiology.…”
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Effects of Land Use and Land Cover Change on Soil Organic Carbon Stock in Jira Watershed, Mid-Lands of Northern Ethiopia. by Guesh Assefa, Gebeyehu Taye, Kassa Teka

“…The highest SOC was gained due to the conversion of grazing land in to forest land (2007-2017) which has offered a total of 635.53 ton of SOC. A model was created to predict SOC of similar environments by using the observed SOC and NDVI values of the 2017 LULC types. …”
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Post-hoc Evaluation of Sample Size in a Regional Digital Soil Mapping Project by Daniel D. Saurette, Richard J. Heck, Adam W. Gillespie, Aaron A. Berg, Asim Biswas

“…Furthermore, the comparison of the optimal maps to the reference maps showed little difference in the global statistics (concordance correlation coefficient and root mean square error) and spatial trends of the data, confirming that the optimal sample size was sufficient for creating predictions of similar accuracy to the full calibration dataset. …”
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Sugar Maple Litter Decay Rates Are Reduced More Strongly by Drought Than by American Beech Proliferation in the Understory by William F. J. Parsons, Claudele Ghotsa Mekontchou, Audrey Maheu, David Rivest

“…Mass loss did not change with mesh size in a consistent manner over 90 days (initial prediction: L > M > S). We estimated k‐values (year−1) by extending the linearized exponential decay model to 12 Proliferation‐Exclusion‐Species combinations. …”
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Statistics and behavior of clinically significant extra-pulmonary vein atrial fibrillation sources: machine-learning-enhanced electrographic flow mapping in persistent atrial fibri... by Peter Ruppersberg, Steven Castellano, Philip Haeusser, Kostiantyn Ahapov, Melissa H. Kong, Stefan G. Spitzer, Stefan G. Spitzer, Georg Nölker, Andreas Rillig, Tamas Szili-Torok

“…Notably, the majority of significant sources were not continuously active; however, when these sources switched “ON,” the spatial variability of AF cycle lengths in the respective atrium decreased by more than 50%, suggesting an entraining effect.ConclusionsBy systematically optimizing the EGF Model's hyperparameters based on clinical outcomes, we reliably detect and target key AF sources that, when ablated, improve procedural success. …”
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Emission inventory development for spatiotemporal release of vanadium from anthropogenic sources in China by H. Zhang, H. Zhang, B. Zhang, B. Jiang, Q. Li, X. Hu, Y. Xing

“…Emissions induced by vanadium mining show remarkable spatial heterogeneity, with 66.1 % of output in southwestern China. …”
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