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Soil microbial biomass and microbial stoichiometric ratios are important for understanding carbon and nutrient cycling in terrestrial ecosystems. Here, we compiled data from 12245 observations of soil microbial biomass from 1626 published studies to map global patterns of microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), microbial biomass phosphorus (MBP), and their stoichiometry using a random forest model. Concentrations of MBC, MBN, and MBP were most closely linked to soil organic carbon, while climatic factors were most important for stoichiometry in microbial biomass ratios. Modeled seasonal MBC concentrations peaked in summer in tundra and in boreal forests, but in autumn in subtropical and in tropical biomes. The global mean MBC/MBN, MBC/MBP, and MBN/MBP ratios were estimated to be 10, 48, and 6.7, respectively, at 0-30 cm soil depth. The highest concentrations, stocks, and microbial C/N/P ratios were found at high latitudes in tundra and boreal forests, probably due to the higher soil organic matter content, greater fungal abundance, and lower nutrient availability in colder than in warmer biomes. At 30-100 cm soil depth, concentrations of MBC, MBN, and MBP were highest in temperate forests. The MBC/MBP ratio showed greater flexibility at the global scale than did the MBC/MBN ratio, possibly reflecting physiological adaptations and microbial community shifts with latitude. The results of this study are important for understanding C, N, and P cycling at the global scale, as well as for developing soil C-cycling models including soil microbial C, N, and P as important parameters.

The discharge of acid mine drainage from abandoned high sulfur (S) coal mines has caused serious pollution in the Shandi River, Yangquan, Shanxi Province. To determine the impact of long-term acid mine drainage on the microorganisms in the river, we collected river sediments from a polluted tributary (Group P) and the mainstream of Shandi River (Group R) to study the bacterial diversity and community composition. The results showed that the tributary was seriously polluted by acid drainage from abandoned coal mines, with the pH value of the sediment being Metallibacterium, Acidiphilium, and Acidithiobacillus, were the dominant genera in Group P samples, while the Group R was dominated by the neutral anaerobic iron-reducing bacteria Geothrix and Geobacter. Results of principal co-ordinates analysis (PCoA) revealed that the bacterial communities are significantly different between groups P and R, and the significant different species were mainly attributed to phylum Proteobacteria, Actinobacteria, and Acidobacteria. The distribution of the microbial community is mainly influenced by pH, and the Fe and Cd concentrations. Metallicactrium, the dominant genus, is negatively correlated with pH (R2 = − 0.95) and positively correlated with Fe (R2 = 0.99), while Geothrix and Geobacter, are mainly affected by the heavy metals. This study determined the impact of river pollution caused by abandoned coal mine drainage, especially on the microbial diversity and community composition within the river sediment.

Above and belowground compartments in ecosystems are closely coupled on daily to annual timescales. In mature forests, this interlinkage and how it is impacted by drought is still poorly understood. Here, we pulse‐labelled 100‐year‐old trees with 13CO2 within a 15‐year‐long irrigation experiment in a naturally dry pine forest to quantify how drought regime affects the transfer and use of assimilates from trees to the rhizosphere and associated microbial communities. It took 4 days until new 13C‐labelled assimilates were allocated to the rhizosphere. One year later, the 13C signal of the 3‐h long pulse labelling was still detectable in stem and soil respiration, which provides evidence that parts of the assimilates are stored in trees before they are used for metabolic processes in the rhizosphere. Irrigation removing the natural water stress reduced the mean C residence time from canopy uptake until soil respiration from 89 to 40 days. Moreover, irrigation increased the amount of assimilates transferred to and respired in the soil within the first 10 days by 370%. A small precipitation event rewetting surface soils altered this pattern rapidly and reduced the effect size to +35%. Microbial biomass incorporated 46 ± 5% and 31 ± 7% of the C used in the rhizosphere in the dry control and irrigation treatment respectively. Mapping the spatial distribution of soil‐respired 13CO2 around the 10 pulse‐labelled trees showed that tree rhizospheres extended laterally 2.8 times beyond tree canopies, implying that there is a strong overlap of the rhizosphere among adjacent trees. Irrigation increased the rhizosphere area by 60%, which gives evidence of a long‐term acclimation of trees and their rhizosphere to the drought regime. The moisture‐sensitive transfer and use of C in the rhizosphere has consequences for C allocation within trees, soil microbial communities and soil carbon storage., To quantify the transfer of carbon from tree canopies into the belowground, we conducted a pulse‐labelling with 100‐year old trees in a 15‐year‐long irrigation experiment within a naturally dry pine forest. It took four days until new assimilates were allocated from tree canopies to the rhizosphere. One year later, the 13C signal of the three‐hour long pulse labelling was still detectable in stem and soil respiration. Mapping the spatial distribution of soil‐respired 13CO2 around pulse‐labelled trees showed that rhizospheres extended laterally 2.8 times beyond tree canopies. Drought reduced the transfer rates and spatial distribution of assimilates allocated to the soil.

Urban heat islands (UHIs) are a key topic in urban climate studies. However, systematic criteria for UHI comparisons were lacking prior to 2012, when the concept of Local Climate Zones (LCZs) was i...

To overcome the spread of the severe COVID-19 outbreak, various lockdown measures have been taken worldwide. China imposed the strictest home-quarantine measures during the COVID-19 outbreak in the year 2020. This provides a valuable opportunity to study the impact of anthropogenic emission reductions on air quality. Based on the GEE platform and satellite imagery, this study analyzed the changes in the concentrations of NO2, O3, CO, and SO2 in the same season (1 February–1 May) before and after the epidemic control (2019–2021) for 16 typical representative cities of China. The results showed that NO2 concentrations significantly decreased by around 20–24% for different types of metropolises, whereas O3 increased for most of the studied metropolises, including approximately 7% in megacities and other major cities. Additionally, the concentrations of CO and SO2 showed no statistically significant changes during the study intervals. The study also indicated strong variations in air pollutants among different geographic regions. In addition to the methods in this study, it is essential to include the differences in meteorological impact factors in the study to identify future references for air pollution reduction measures.

Urban and vegetation morphology profiles are important factors in local climate-related studies, but they are not as easily measured as land cover information to study urban landscape at metropolitan area. This study aims to develop a GIS-based Local Climate Zones (LCZs) mapping scheme to map and compare the LCZs for three major metropolitans in Texas: Dallas-Fort Worth (DFW), Austin, and San Antonio. Based on an analysis of the land cover and urban morphology, variables including land cover, height of roughness elements, building surface fraction, pervious surface fraction (PSF), and land use planning codes were generated and selected as LCZs classification properties. Then we designed the LCZs mapping scheme with decision-making algorithm was built for LCZs mapping. The key findings of LCZs of our study areas are that: 1) Most of the urbanized area are categorized into LCZ “open” types (characterized by building surface fraction of 15–40% and pervious surface fraction of 30–60%) for all three metropolitan areas with different proportions and spatial diversity; 2) LCZ D Low plants is dominant in areas surrounding DFW, while LCZ A Dense trees and LCZ D Low plants are dominant in Austin and San Antonio with clear regional contrast; 3) LCZs maps are in accordance with the underlying regional environment of the areas. Our study indicated that LiDAR-derived products can support LCZs mapping to identify urban morphological information and standardize the mapping scheme for further comparative studies of metropolitan areas.

The properties of some types of noncovalent interactions formed by triplet diphenylcarbene (DPC3) have been investigated by means of density functional theory (DFT) calculations and quantum theory of atoms in molecules (QTAIM) studies. The DPC3···LA (LA = AlF3, SiF4, PF5, SF2, ClF) complexes have been analyzed from their equilibrium geometries, binding energies, charge transfer and properties of electron density. The triel bond in the DPC3···AlF3 complex exhibits a partially covalent nature, with the binding energy − 65.7kJ/mol. The tetrel bond, pnicogen bond, chalcogen bond and halogen bond in the DPC3···LA (LA = SiF4, PF5, SF2, ClF) complexes show the character of a weak closed-shell noncovalent interaction. Polarization plays an important role in the formation of the studied complexes. The strength of intermolecular interaction decreases in the order LA = AlF3 > ClF > SF2 > SiF4 > PF5. In the process of complexation, the charge transferrs from DPC3 to the antibonding orbital of AlF3/SF2/ClF, the quantity of charge transfer is very small between DPC3 and SiF4/PF5. The electron spin density transferrs from the radical DPC3 to ClF and SF2 in the formation of halogen bond and chalcogen bond, but for the DPC3···AlF3/SiF4/PF5 complexes, the transfer of electron spin density is minimal.

Acquired Immune Deficiency Syndrome (AIDS) has become one of the most severe public health issues and nowadays around 38 million people are living with the human immunodeficiency virus (HIV). Ensuring healthy lives and promoting well-being is one of 17 United Nations Sustainable Development Goals. Here, we used the Markov chain matrix and geospatial clustering to comprehensively quantify the trends of the AIDS epidemic at the provincial administrate level in the mainland of China from 2005 to 2017. The Geographically Weighted Regression (GWR) model was further adopted to explore four groups of potential influencing factors (i.e., economy, traffic and transportation, medical care, and education) of the AIDS incidence rate in 2017 and their spatially distributed patterns. Results showed that the AIDS prevalence in southeastern China had been dominant and become prevalent in the past decade. The AIDS intensity level had been increasing between 2008 and 2011 but been gradually decreasing afterward. The analysis of the Markov chain matrix indicated that the AIDS epidemic has been generally in control on the Chinese mainland. The economic development was closely related to the rate of AIDS incidence on the Chinese mainland. The GWR result further suggested that medical care and the education effects on AIDS incidence rate can vary with different regions, but significant conclusions cannot be directly demonstrated. Our findings contribute an analytical framework of understanding AIDS epidemic trends and spatial variability of potential underlying factors throughout a complex extent to customize scientific prevention.

As a new and popular technology, intelligent technology is widely used in all walks of life, especially for the realization of electrical engineering automation control. The establishment of the structure of intelligent technology mainly relies on two elements, namely artificial intelligence and computer network technology. The two are integrated and coordinated to produce a new technical field. Looking to the future, intelligent technology will continue to introduce new and better services to all walks of life, and the future development path will inevitably be bright. Based on this, this article briefly introduces the application of intelligent technology to electrical engineering automation control, so as to help intelligent technology to be better used in electrical automation.

In recent years, mainframes or peripherals have been integrated on mainstream embedded CPU, making these systems easy to use USB for data transmission. With the development of SOPC technology, FPGA has gradually transitioned from a single timing control and signal processing to an embedded CPU at the core of the system. The embedded FPGA platform also has an increasing demand for data transmission using USB. This paper designs an implementation scheme for extending USB host and USB peripherals on the embedded platform, and gives detailed design of hardware and embedded software. It implements and verifies the data transmission function of the host and peripherals.

In Northern China, karst systems in widely distributed carbonate rocks are one of the most important water supplies for local inhabitants. Constrained by the specific geological and geomorphological conditions, most karst water in this region is discharged as individual or groups of springs. This paper summarizes the characteristics, chemistry, and environmental quality of these karst systems in Northern China. Five structural models of karst water systems were identified based on the relationships between the karst geological strata and karst groundwater flow fields. These specific structural models may closely relate to the attendant environmental geological issues and consistent risks from pollution. Over the past 40 years, the karst water systems in Northern China have suffered from various environmental problems, including deteriorating water quality, the drying up of springs, a continuous decline in the level of karst water, and so on. Based on the field investigation and previous data, a preliminary summary is provided of the environmental problems related to the development and evolutionary trends of karst water in this region. The results highlight the significant challenges associated with karst water, and it is essential that all segments of society be made aware of the situation in order to demand change. In addition, the study provides a scientific basis for the management, protection, and sustainable utilization of karst water resources.

The Local Climate Zones (LCZs) concept was initiated in 2012 to improve the documentation of Urban Heat Island (UHI) observations. Despite the indispensable role and initial aim of LCZs concept in metadata reporting for atmospheric UHI research, its role in surface UHI investigation also needs to be emphasized. This study incorporated LCZs concept to study surface UHI effect for San Antonio, Texas. LCZ map was developed by a GIS-based LCZs classification scheme with the aid of airborne Lidar dataset and other freely available GIS data. Then, the summer LST was calculated based Landsat imagery, which was used to analyse the relations between LST and LCZs and the statistical significance of the differences of LST among the typical LCZs, in order to test if LCZs are able to efficiently facilitate SUHI investigation. The linkage of LCZs and land surface temperature (LST) indicated that the LCZs mapping can be used to compare and investigate the SUHI. Most of the pairs of LCZs illustrated significant differences in average LSTs with considerable significance. The intra-urban temperature comparison among different urban classes contributes to investigate the influence of heterogeneous urban morphology on local climate formation.

Spatial planning has been globally developed as a policy tool to govern built-up land expansion. However, causal evidence of the effect of spatial planning on built-up land expansion is limited, which raises doubts on the credibility of spatial planning and hinders theoretical developments in land-system science. We evaluated the effect of the Major Function Oriented Zone (MFOZ), the first strategic spatial plan in China, on built-up land expansion in Fujian Province over three time intervals (2013–2015, 2013–2018 and 2013–2020). Propensity score matching (PSM) was applied to overcome selection bias and obtain causal evidence. We implemented a conventional conformance evaluation as a reference for the PSM-based conformance evaluation, to demonstrate the problem of selection bias. The conventional conformance evaluation showed that the MFOZ effectively governed built-up land expansion in the three time intervals. The PSM-based conformance evaluation showed the smaller effect of the MFOZ and the effect was significant only in the time period 2013–2018 and 2013–2020. That is, the conventional conformance evaluation results in an initially ineffective effect of the MFOZ being estimated as effective in 2013–2015 and exaggerates the effect of the MFOZ on built-up land expansion in 2013–2018 and 2013–2020. In aggregate, Fujian’s MFOZ prevented a total of 79.31 km2 of built-up land within the development-restricted zone between 2013 and 2020. To conclude, we recommend a wider application of the PSM-based conformance evaluation in evaluating the effect of spatial planning on land-use change, since this method accounts for selection bias and provides more accurate results regarding causality than conventional conformance evaluations.

Beijing is an international metropolis, with rapid urbanization during the last 30 years. However, it faces the challenge of sustainability with limited natural resources. This paper attempts to incorporate emergy analysis on urban metabolism to investigate the sustainability of the entire Beijing at the county level. Based on the time-series climate data and socioeconomic data, we calculated the structure, intensities, environment pressures and output efficiency of the urban metabolic emergy system by counties between 2005 and 2014. The result shows that the metabolic emergy stores of Beijing, especially in Capital Function Core (CFC) area, had been increasing significantly during the study period, especially for the increasing imported and exported emergy accounting. The 16 districts of Beijing can be grouped into four types of functional areas in terms of the function in urban metabolism. The five parts of urban metabolic emergy system had obviously spatial difference by counties, and the renewable emergy in CFC area and Urban Function Development (UFD) zone was obviously lower than in City Development (CD) zone and Ecological Conservation Development (ECD) area. The non-renewable emergy and waste emergy in CFC area, UFD zone and CD zone were obviously higher than that in ECD area. The imported emergy and exported emergy were significantly higher in Dongcheng, Xicheng and Chaoyang district. Emergy use intensities of CFC area had been increasing with the rapid rise in imported emergy and exported emergy, resulting in the increasing environmental pressure. However, the district governments of CFC area are trying to enhance output efficiency and sustainability to reduce waste emergy. The indices of emergy yield rate (EYR) and emergy sustainable index (ESI) had been gradually decreasing and the region with the highest value of EYR and ESI, in decreasing order, are: ECD area, CD zone, UFD zone, and CFC area. The result indicates that CFC area is more fragile and dependent on external resources. Therefore, the Beijing government, especially the district governments of CFC area should encourage the exploitation and utilization of renewable resources and energy, increase the consumption efficiency of non-renewable resources and energy, and establish the mechanism to re-use wastes of resources and energy in order to promote the urban metabolism.

The adjacent cities of Laredo in the US and Nuevo Laredo in Mexico have been growing at an unprecedented pace over the past decades. The trans-boundary flows of commodities and capital between these two cities, as well as significant population growth have created an interdependent system in this area. This characteristic provides an opportunity to thoroughly examine drivers behind landscape changes in the two cities. The aim of this study is to examine urban growth and the influencing factors of Laredo-Nuevo Laredo. Results of initial remote sensing-GIS analysis indicated that there was considerable urban expansion in both cities from 1985 to 2014. Spatially, Laredo demonstrated a more dispersed and rapid growth pattern compared to Nuevo Laredo. Additional results from a logistic regression using data at the pixel level on both sides of the border revealed a number of factors that influenced urban growth for both cites. These factors included: (1) elevation, (2) distance to nearest urban clusters, (3) distance to local roads, and (4) density of urban pixels. In addition, this study found that some dominant variables (population density and density of highways) affected urban growth differently for the two cities. Furthermore, globalization factors related to industrial activities/maquiladoras also played a significant role in affecting urban growth although the trajectories were not completely clear.

Lei Yin,1–3 Chunhong Zhao,3 Jixia Han,4 Zengjun Li,2 Yanan Zhen,3 Ruixue Xiao,3 Zhongfa Xu,3 Yanlai Sun2 1School of Medicine and Life Sciences, University of Jinan-Shandong Academy of Medical Sciences, Jinan, 2Department of Gastrointestinal Cancer Surgery, Shandong Cancer Hospital Affiliated to Shandong University, Shandong Academy of Medical Sciences, Jinan, 3Department of Gastrointestinal Surgery, The Affiliated Hospital of Shandong Academy of Medical Sciences, Jinan, 4Department of General Surgery, The Sixth People’s Hospital of Jinan, Jinan, People’s Republic of China Background: The incidence of colorectal cancer (CRC) is on the rise. Furthermore, late-stage diagnoses and limited efficacious treatment options make CRC a complex clinical challenge. Therefore, a new therapeutic regimen with a completely novel therapeutic mechanism is necessary for CRC. In the present study, the therapeutic efficacy of oncolytic herpes simplex virus type 2 (oHSV2) in CRC was assessed in vitro and in vivo. oHSV2 is an oncolytic agent derived from herpes simplex virus type 2 that encodes granulocyte-macrophage colony-stimulating factor.Materials and methods: We investigated the cytopathic effects of oHSV2 in CRC cell lines using the MTT assay. Then, cell cycle progression and apoptosis of oHSV2 were examined by flow cytometry. We generated a model of CRC with mouse CRC cell CT26 in BALB/c mice. The antitumor effects and adaptive immune response of oHSV2 were assessed in tumor-bearing mice. The therapeutic efficacy of oHSV2 was compared with the traditional chemotherapeutic agent, 5-fluorouracil.Results: The in vitro data showed that oHSV2 infected the CRC cell lines successfully and that the tumor cells formed a significant number of syncytiae postinfection. The oHSV2 killed cancer cells independent of the cell cycle and mainly caused tumor cells necrosis. The in vivo results showed that oHSV2 significantly inhibited tumor growth and prolonged survival of tumor-bearing mice without weight loss. With virus replication, oHSV2 not only resulted in a reduction of myeloid-derived suppressor cells and regulatory T cells in the spleen, but also increased the number of mature dendritic cells in tumor-draining lymph nodes and the effective CD4+T and CD8+T-cells in the tumor microenvironment.Conclusion: Our study provides the first evidence that oHSV2 induces cell death in CRC in vitro and in vivo. These findings indicate that oHSV2 is an effective therapeutic cancer candidate that causes an oncolytic effect and recruits adaptive immune responses for an enhanced therapeutic impact, thus providing a potential therapeutic tool for treatment of CRC. Keywords: colorectal cancer, oncolytic virus, herpes simplex virus type 2, granulocyte–macrophage colony-stimulating factor, immunotherapy, gene therapy

Accurate groundwater level (GWL) prediction can contribute to sustaining reliable water supply to domestic, agricultural and industrial uses as well as ecological services, especially in arid and semi-arid areas. In this paper, a regional GWL modeling framework was first presented through coupling both spatial and temporal clustering techniques. Specifically, the self-organizing map (SOM) was applied to identify spatially homogeneous clusters of GWL piezometers, while GWL time series forecasting was performed through developing a stepwise cluster multisite inference model with various predictors including climate conditions, well extractions, surface runoffs, reservoir operations and GWL measurements at previous steps. The proposed modeling approach was then demonstrated by a case of an arid irrigation district in the western Hexi Corridor, northwest China. Spatial clustering analysis identified 6 regionally representative central piezometers out of 30, for which sensitivity and uncertainty analysis were carried out regarding GWL predictions. As the stepwise cluster tree provided uncertain predictions, we added an AR(1) error model to the mean prediction to forecast GWL 1 month ahead. Model performance indicators suggest that the modeling system is a useful tool to aid decision-making for informed groundwater resource management in arid areas, and would have a great potential to extend its applications to more areas or regions in the future.

Economic evolution is considered as being driven by innovation of research and development (RD (2) regions that have higher economic performance with less innovative records highly likely have a relatively large number of indigenous knowledge unpublished throughout cultural evolution; and (3) English world has research preference to the regions that have lower economic performance with a distinctive culture in China.

Light Detection and Ranging (LiDAR) technology is gradually being adopted as the primary technique for surface structure derivation. There is a tendency for users of LiDAR data to want the highest density data possible, but such dense data sets increase overall costs including financial, processing, and storage without significant value added to the derived outputs, particularly in the case of digital elevation models (DEMs). In this study, we employed three sampling methods (systematic sampling, simple random sampling, and stratified random sampling) to select points from the original LiDAR data set that represented six different sparse densities. Using the sampled data sets, DEMs were generated and sensitivity analyses were conducted to explore whether an optimum LiDAR point sampling method and density could be identified. Despite the fact that significant differences in descriptive statistics were not observed for the three sampling strategies or point densities, there are evident differences a...