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With the increasing penetration of renewable energy resources, their variable, intermittent and unpredictable characteristics bring new challenges to the power system. These challenges require micro-meteorological data and techniques to provide more support for the power systems, including planning, dispatching, operation, and so on. This paper aims to provide readers with insights into the effects of micro-meteorology on power systems, as well as the actual improvement brought by micro-meteorology in some power system scenarios. This paper provides a review including the relevant micro-meteorological techniques such as observation, assimilation and numerical techniques, as well as artificial intelligence, presenting a relatively complete overview of the most recent and relevant micro-meteorology-related literature associated with power systems. The impact of micro-meteorology on power systems is analyzed in six different forms of power generation and three typical scenarios of different stages in the power system, as well as integrated energy systems and disaster prevention and reduction. Finally, a case study in China is provided. This case takes wind power prediction as an example in a power system to compare the performance when applying micro-meteorological data or not. The experimental results demonstrated that using the micro-meteorological reanalysis dataset with high spatial--temporal resolution for wind power prediction performed better, verifying the improvement of micro-meteorology to the power system to some extent. [ABSTRACT FROM AUTHOR]

In recent years, global warming has become increasingly severe, and the ecological and environmental problems facing mankind have become increasingly serious. As the main areas of transportation activities, cities are also the main places of carbon emissions. As a necessary condition for human's daily-life travel, it is particularly important to calculate the carbon emissions from urban transportation. Due to the different characteristics of economy and population in different regions of a city, the carbon emissions of urban buses show different characteristics in terms of temporal and spatial distribution. The developments of science and technology promote the application of big data analysis to specific practical life, enabling people to research and solve problems from a new perspective. This paper uses the GPS data of urban buses in Sanya City, China, to identify operation conditions from urban buses, and calculates the distance and time under different conditions. Based on the measured data of carbon emissions, this paper visualizes the distribution characteristics of carbon emissions by density analysis; explains the time distribution characteristics by the visual analysis of carbon emissions in different time periods, working days and rest days, and different energy types; and illustrates the spatial distribution characteristics by the spatial distributions of carbon emissions from Sanya's buses on working days and rest days, as well as in different routes, providing reference for a low-carbon development of urban green transport. [ABSTRACT FROM AUTHOR]

With the massive use of lithium-ion batteries in electric vehicles and energy storage, the environmental and resource problems faced by used lithium-ion batteries are becoming more and more prominent. In order to better resource utilization and environmental protection, this paper employs bibliometric and data analysis methods to explore publications related to waste lithium-ion battery recycling from 1984 to 2021. The Web of Science core set from the SCIE online database was used for this article. These findings demonstrate a considerable increase trend in the number of publications published in the subject of recycling used lithium-ion batteries, with a natural-sciences-centric focus. Argonne National Lab, Chinese Academy of Sciences, and China Academic and Scientific Research Center are the top three institutions in terms of quantity of papers published. The affiliated journals corresponding to these three institutions also have high impact factors, which are 106.47, 44.85, and 58.69, respectively. In comparison to comparable institutes in other nations, the American Argonne National Laboratory supports 223 research articles in this area. China and the US make up the majority of the research's funding. The two key aspects of current lithium-ion battery recycling research are material structure research and environmentally friendly recycling. Nevertheless, high-capacity lithium-ion batteries, waste lithium-ion integrated structures, and gentle recycling of spent lithium-ion batteries will be the major aspects of study in the future. It is hoped that the above analysis can bring new ideas and methods to the field of waste lithium-ion battery recycling and provide a basis for the subsequent research and application of waste lithium-ion battery recycling. [ABSTRACT FROM AUTHOR]

Identifying the relationships between the yield of rainfed maize and planting densities as well as the hybrids used is crucial for ensuring the sustainable development of the grain industry in high latitude China. In this study, we collected 108 grain yield date points from our multiyear (2017–2020) field experiments and combined 213 data points collected from 21 published papers to appraise the impact of planting density and hybrids on maize yield. It was found that grain yield forms a curvilinear relationship with plant density as it increased from 22,500 to 112,500 plants ha−1. The optimum plant density (OPD) was determined to be 72500 plants ha−1, with a maximum maize grain yield of 10.56 Mg ha−1. The interannual variability in grain yields among hybrids with different planting densities was mainly due to the differences in dry matter (DM), especially post-silking. Grain yields increased significantly with a rise in the proportion of post-silking DM to DM at maturity. In addition, both the collected literature and our field experiments showed that the OPD was positively correlated with solar radiation accumulated during the maize growth period and with each hybrid's year of release. This study suggests that increasing plant density and selecting new hybrids with suitable growth periods are effective approaches for increasing grain yield in high latitude China. [ABSTRACT FROM AUTHOR]

Using data from 56 tight gas wells from the study field (Y field) in the Ordos basin of China, this paper presents performance-based reservoir characterization of the study field from production data and geophysical data. Post-fracturing evaluation is realized by applying our new modified production decline type curves for fractured wells. Compared to traditional type curves, our newly proposed modified dimensionless type curves help identify field data diagnostics for various flow regimes of fractured wells and also facilitate the curve matching process with real data to obtain fruitful and crucial reservoir and fractured well information, including key parameters such as reservoir flowing capacity (kh), well productivity, fracture length, drainage area and original gas in place. This paper intends to promote the extensive application of this new technique. With the support of the reservoir information provided by production decline analysis using our modified type curves, the commercial flow units are delineated in terms of interrelated porosity-permeability of sandstone based on pore throat aperture crossplotting and corresponding flow unit productivity. Furthermore, two crossplots of well logging interpreted porosity versus resistivity are constructed, suggesting their good correlated relationships with relative flow unit productivity and initial gas abundance in place, respectively. The two crossplots enable qualitative evaluation of formation penetrated by well, which makes them very useful and practical as wireline logging is basically available for every well. The well production routine is also analyzed systematically by considering a well's inflow performance, tubing performance and minimal liquid-carrying gas flow rate to investigate if a gas well is producing at optimal conditions or if a measure should be taken to improve the well's production. Through analysis of the Y field, this study introduces an integrated workflow with the support of the new modified type curves to effectively help understand the reservoir characteristics and the flow behaviors of the tight gas field. The key takeaway from this study is that the new modified dimensionless production decline curves in terms of q D M   v s.   t D M can be applied in field practice to achieve a systematically comparable understanding of the performance of MHFHWs globally. [ABSTRACT FROM AUTHOR]

The mechanical performance analysis of the members is the primary basis for evaluating the hoisting quality and safety of the valve hall grid structure. Ordinarily, manual analysis of monitoring data and on-site experience inspection are employed to structural judgment, but it is challenging to evaluate the correlation of the various members and the overall safety of a valve hall. In this paper, an intelligent correlation real-time analysis method based on a BPNN (Back Propagation Neural Network) for the mechanical properties of members is proposed to intelligently control the safety of valve hall grid structure hoisting. The correlation between the mechanical properties of multi-points in the grid structure is used to model the target measuring points. In addition, an intelligent real-time analysis system is used to manage and apply the mechanical property correlation and abnormality of members in real-time. Then, the model is applied to a super-span valve hall in South China, and the application effect is good. The mechanical property correlation model can accurately reflect the mechanical state of the valve hall grid structure hoisting process. Simultaneously, it can effectively pinpoint hidden dangers and locate risk members. It provides a new reference for the normal operation and maintenance of a super-span valve hall grid. [ABSTRACT FROM AUTHOR]

miRNAs biomarkers are emerging as an essential part of clinical oncology. Their oncogenic and tumour suppressor properties playing a role in malignancy has generated interest in their potential for use in disease prognosis. While several studies on miRNA have been carried out across the globe, evaluating the clinical implications of miRNAs in cancer diagnosis and prognosis research has currently not been attempted. A study delineating the area of miRNA research, including the topics presently being focused on, the seminal papers in this field, and the direction of research interest, does not exist. This study aims to conduct a large-scale, global data analysis and bibliometric profiling analysis of studies to evaluate the research output of clinical implications of miRNAs in cancer diagnosis and prognosis listed in the SCOPUS database. A systematic search strategy was followed to identify and extract all relevant studies, subsequently analysed to generate a bibliometric map. SPSS software (version 27) was used to calculate bibliometric indicators or parameters for analysis, such as year and country of affiliation with leading authors, journals, and institutions. It is also used to analyse annual research outputs, including total citations and the number of times it has been cited with productive nations and H-index. The number of global research articles retrieved for miRNA-Cancer research over the study period 2003 to 2019 was 18,636. Between 2012 and 2019, the growth rate of global publications is six times (n = 15,959; 90.71 percent articles) that of 2003 to 2011. (2704; 9.29 per cent articles). China published the most publications in the field of miRNA in cancer (n = 7782; 41%), while the United States had the most citations (n = 327,538; 48%) during the time span. Of these journals, Oncotarget has the highest percentage of article publications. The journal Cancer Research had the most citations (n = 41,876), with 6.20 per cent (n = 41,876). This study revealed a wide variety of journals in which miRNA-Cancer research are published; these bibliometric parameters exhibit crucial clinical information on performance assessment of research productivity and quality of research output. Therefore, this study provides a helpful reference for clinical oncologists, cancer scientists, policy decision-makers and clinical data researchers. [ABSTRACT FROM AUTHOR]

In the context of the global potential energy crisis and aggravating regional environmental pollution, Chinese photovoltaic power generation still faces the key problems of sustainable development, even given its favorable background in large-scale exploitation. Scientific evaluation of the comprehensive efficiency of photovoltaic power generation is of great significance because it will improve investment decision-making and enhance management level, evaluate the development conditions of photovoltaic power generation and then promote sustainable development capability. The concept of “comprehensive efficiency” is proposed in this paper on the basis of the resource development of solar energy and exploitation of photovoltaic power generation. A system dynamics model is used to study the conduction mechanism of the comprehensive efficiency of photovoltaic power generation. This paper collects data from 2005 to 2015 as research models, establishes the evaluation model of the comprehensive efficiency of photovoltaic power generation and conducts empirical analysis based on a super-efficient data envelopment analysis (SE-DEA) model. With the evaluation results, this paper puts forward political suggestions as to the optimization of the comprehensive efficiency of photovoltaic power generation. The research results may provide policy-oriented references on the sustainable development of photovoltaic power generation and give theoretical guidance on the scientific evaluation and diagnosis of photovoltaic power generation efficiency. [ABSTRACT FROM AUTHOR]

Interests in synthetic aperture radar (SAR) data analysis is driven by the constantly increased spatial resolutions of the acquired images, where the geometries of scene objects can be better defined than in lower resolution data. This paper addresses the problem of the built-up areas extraction in high-resolution (HR) SAR images, which can provide a wealth of information to characterize urban environments. Strong backscattering behavior is one of the distinct characteristics of built-up areas in a SAR image. However, in practical applications, only a small portion of pixels characterizing the built-up areas appears bright. Thus, specific texture measures should be considered for identifying these areas. This paper presents a novel texture measure by combining the proposed labeled co-occurrence matrix technique with the specific spatial variability structure of the considered land-cover type in the fuzzy set theory. The spatial variability is analyzed by means of variogram, which reflects the spatial correlation or non-similarity associated with a particular terrain surface. The derived parameters from the variograms are used to establish fuzzy functions to characterize the built-up class and non built-up class, separately. The proposed technique was tested on TerraSAR-X images acquired of Nanjing (China) and Barcelona (Spain), and on a COSMO-SkyMed image acquired of Hangzhou (China). The obtained classification accuracies point out the effectiveness of the proposed technique in identifying and detecting built-up areas. [ABSTRACT FROM AUTHOR]

This paper presents a hierarchical approach to network construction and time series estimation in persistent scatterer interferometry (PSI) for deformation analysis using the time series of high-resolution satellite SAR images. To balance between computational efficiency and solution accuracy, a dividing and conquering algorithm (i.e., two levels of PS networking and solution) is proposed for extracting deformation rates of a study area. The algorithm has been tested using 40 high-resolution TerraSAR-X images collected between 2009 and 2010 over Tianjin in China for subsidence analysis, and validated by using the ground-based leveling measurements. The experimental results indicate that the hierarchical approach can remarkably reduce computing time and memory requirements, and the subsidence measurements derived from the hierarchical solution are in good agreement with the leveling data. [ABSTRACT FROM AUTHOR]

The location and grade setting of a timber logistics center is an important link in the optimization of the timber logistics system, the rationality of which can effectively improve the efficiency of the timber logistics supply chain. There is a long distance between the main forested areas in China, and more than 55% of the timber demand depends on imports. Research and practice of systematically planning timber logistics centers in the whole country have not been well carried out, which reduces the efficiency of timber logistics. In this paper, 47 timber trading markets with a certain scale in China are selected as the basis for logistics center selection. Based on their transportation network relationship and the number of enterprises in the market, combined with the complex network theory and data analysis method, the network characteristics of three different transportation networks are measured. After determining the transportation capacity indicator, the logistics capacity coefficient is measured based on the freight volume of each node. Then, the important nodes are identified, and each node is graded to systematically set up the timber logistics center. [ABSTRACT FROM AUTHOR]