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Utilizing δ15N of biomonitors to assess N emission sources and deposition chemistry?
Published 2024-12-01Get full text
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Urban Functional Zone Mapping by Integrating Multi-Source Data and Spatial Relationship Characteristics
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Key technologies for preparation and multi scene utilization of multi-source solid waste based carbon fixation mining materials
Published 2025-02-01“…In order to achieve the goal of "coal mine loss reduction mining-functional utilization of solid waste-CO2 low-carbon disposal", this study innovatively proposed the key technologies of CO2 mineralization multi-source solid waste preparation of carbon fixation mining materials and multi scenario utilization.Taking the modified magnesium coal based solid waste (including modified magnesium slag, fly ash and coal gangue) as an example, the direct mineralization method was used to mineralize it on the ground to prepare carbon fixation mining materials, so as to meet the application requirements of multiple scenarios in the mine. …”
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Banana inflorescence as a new source of bioactive and pharmacological ingredients for food industry
Published 2024-12-01“…Despite these promising attributes, the utilization of banana inflorescence as a functional food and nutraceutical resource remains underexplored and currently, there is no comprehensive review paper to investigate this potential. …”
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Limited Microbial Contribution in Salt Lake Sediment and Water to Each Other’s Microbial Communities
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Overview of solutions to improve efficiency of ground source heat pump system
Published 2023-12-01“…Shallow geothermal energy, with applications ranging from road snow melting and deicing to building heating/cooling, primarily utilizes closed-loop vertical buried pipes for resource exploitation. …”
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INTERVAL ESTIMATION OF THE VOLUMES OF RESOURCE CONSUMPTION AT THE STOCHASTIC BASIC DATA
Published 2018-12-01Get full text
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Rice bran as a sustainable source for value added materials: an overview
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Electrophysiological characterization of sourced human iPSC-derived motor neurons
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Advances in preparation and application of coal-based functional nanomaterials
Published 2025-07-01“…However, traditional coal utilization as a primary carbon emission source fundamentally conflicts with the “dual-carbon” strategic goals. …”
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Synthesis and Fluorescence Mechanism of Nitrogen-Doped Carbon Dots Utilizing Biopolymer and Urea
Published 2025-05-01Get full text
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AN INVESTMENT SUPPORT STRATEGY FOR HEAT SUPPLY, WATER-SUPPLY AND OVERFLOW-PIPE ENTERPRISES IN UKRAINE
Published 2013-05-01Get full text
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Enhancing water use efficiency: Insights from hydrological variability encounter of multiple water sources and implications for terminal Lake management in arid regions
Published 2025-06-01“…The escalating conflict between agricultural and ecological water demands, intensified by global climate change, poses significant challenges for water resource allocation in arid inland river basins. This study investigates the potential for integrated management of multiple water sources within the context of the Tarim River, Cherchen River, and Taitema Lake area. …”
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Multi-Source Rainfall Data Assimilation based on Broad Learning System over Yunnan Province
Published 2025-04-01“…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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