Examining the Extent to which Talent Housing Policy Acts as a Catalyst for Innovation Development in China

Since the beginning of economic reform in 1978, China has entered a rapidly growing period where technology innovation has become the new boosting engine of promoting economic development. With the burgeoning of emerging industries in China, the demand for innovation talents is rising greatly. Due to the great gap between Chinese mega cities and other cities in the field of innovation activities, people who possess these tech and innovative skills tend to concentrate in several mega cities, which intensifies housing affordable issue in these areas. And in return, housing affordability become an obstacle for innovation development. In order to improve the living conditions of talents and optimize the environment for innovation activities, local governments have formulated a variety of talent housing policies. As an important part of mitigating the housing burden for certain group of people, the purpose of this study is to explore if talent housing policy can affect regional innovation development and what are the impacts. This study incorporated a mixed-methodology research design to first, analyze the development and current situation of talent housing policies, and secondly explore how talent housing policy impact regional innovation activities by running several regression models using quantitative statistics. Finally, policy suggestions have been proposed based on above analysis. The research result illustrates that talent housing policy affects regional innovation development positively and this relationship can inform policy makers, urban planners, and public officials on better implementing housing policy to attract talented people

Data security and risk assessment in cloud computing

Cloud computing has attracted more and more attention as it reduces the cost of IT infrastructure of organizations. In our country, business Cloud services, such as Alibaba Cloud, Huawei Cloud, QingCloud, UCloud and so on are gaining more and more uses, especially small or median organizations. In the cloud service scenario, the program and data are migrating into cloud, resulting the lack of trust between customers and cloud service providers. However, the recent study on Cloud computing is mainly focused on the service side, while the data security and trust have not been sufficiently studied yet. This paper investigates into the data security issues from data life cycle which includes five steps when an organization uses Cloud computing. A data management framework is given out, including not only the data classification but also the risk management framework. Concretely, the data is divided into two varieties, business and personal information. And then, four classification levels (high, medium, low, normal) according to the different extent of the potential adverse effect is introduced. With the help of classification, the administrators can identify the application or data to implement corresponding security controls. At last, the administrators conduct the risk assessment to alleviate the risk of data security. The trust between customers and cloud service providers will be strengthen through this way

Isolation and Cultivation Methods of Actinobacteria

Actinobacteria (actinomycetes) have been received much attention, as these bacteria produce a variety of natural drugs and other bioactive metabolites. The distribution of actinomycetes in various natural habitats, including soil, ocean, extreme environments, plant, lichens and animals, is described. The collection and pretreatment of test samples from different sources, design principle of selective isolation media, selection of inhibitors, selective isolation procedures of special actinomycetes, and cultivation methods are introduced and discussed

Morphological Identification of Actinobacteria

Actinobacteria is a phylum of gram-positive bacteria with high G+C content. Among gram-positive bacteria, actinobacteria exhibit the richest morphological differentiation, which is based on a filamentous degree of organization like filamentous fungi. The actinobacteria morphological characteristics are basic foundation and information of phylogenetic systematics. Classic actinomycetes have well-developed radial mycelium, which can be divided into substrate mycelium and aerial mycelium according to morphology and function. Some actinobacteria can form complicated structures, such as spore, spore chain, sporangia, and sporangiospore. The structure of hyphae and ultrastructure of spore or sporangia can be observed with microscopy. Actinobacteria have different cultural characteristics in various kinds of culture media, which are important in the classification identification, general with spores, aerial hyphae, with or without color and the soluble pigment, different growth condition on various media as the main characteristics. The morphological differentiation of actinobacteria, especially streptomycetes, is controlled by relevant genes. Both morphogenesis and antibiotic production in the streptomycetes are initiated in response to starvation, and these events are coupled

Molecular Phylogenetic Identification of Actinobacteria

Molecular phylogenetics plays an important role in prokaryote taxonomy and identification. The content of this chapter is to introduce the common application of genetic criteria including 16S rRNA gene sequence nucleotide similarity and phylogeny, DNA G+C content, and DNA–DNA hybridization. However, the genomics era might put forward some new criteria. This chapter emphasizes the methods and basic principles of molecular identification and taxonomy of actinobacteria

Cultural, Physiological, and Biochemical Identification of Actinobacteria

The traditional phenotypic tests are commonly used in actinobacterial identification. They constitute the basis for the formal description of taxa, from species and subspecies up to genus and family. The classical phenotypic characteristics of actinobacteria comprise morphological, physiological, and biochemical features. The morphology of actinobacteria includes both cellular and colonial characters. The physiological and biochemical features include data on growth at different temperatures, pH values, salt concentrations, or atmospheric conditions, and data on growth in the presence of various substances such as antimicrobial agents, the presence or activity of various enzymes, and with respect to metabolization of compounds. The phenotype is the observable expression of the genotype. Gene expression is directly related to the environmental conditions. Actinobacterial phenotype cannot be based on the simple observation of the organism. Strains of the most closely related taxa should be compared in their phenotypic analysis using identical methods. The comparisons must include the type strain of the type species of the appropriate genera. Furthermore, with the development of technology, microbial physiological and biochemical identification technology is becoming fast, simple, and automated

The role of taxes and their importance in China's budget revenues

The article examines the role of taxes, the composition and structure of taxes in China's budget revenues, trends in tax revenues

Network analyses of upper and lower airway transcriptomes identify shared mechanisms among children with recurrent wheezing and school-age asthma

BackgroundPredicting which preschool children with recurrent wheezing (RW) will develop school-age asthma (SA) is difficult, highlighting the critical need to clarify the pathogenesis of RW and the mechanistic relationship between RW and SA. Despite shared environmental exposures and genetic determinants, RW and SA are usually studied in isolation. Based on network analysis of nasal and tracheal transcriptomes, we aimed to identify convergent transcriptomic mechanisms in RW and SA.MethodsRNA-sequencing data from nasal and tracheal brushing samples were acquired from the Gene Expression Omnibus. Combined with single-cell transcriptome data, cell deconvolution was used to infer the composition of 18 cellular components within the airway. Consensus weighted gene co-expression network analysis was performed to identify consensus modules closely related to both RW and SA. Shared pathways underlying consensus modules between RW and SA were explored by enrichment analysis. Hub genes between RW and SA were identified using machine learning strategies and validated using external datasets and quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Finally, the potential value of hub genes in defining RW subsets was determined using nasal and tracheal transcriptome data.ResultsCo-expression network analysis revealed similarities in the transcriptional networks of RW and SA in the upper and lower airways. Cell deconvolution analysis revealed an increase in mast cell fraction but decrease in club cell fraction in both RW and SA airways compared to controls. Consensus network analysis identified two consensus modules highly associated with both RW and SA. Enrichment analysis of the two consensus modules indicated that fatty acid metabolism-related pathways were shared key signals between RW and SA. Furthermore, machine learning strategies identified five hub genes, i.e., CST1, CST2, CST4, POSTN, and NRTK2, with the up-regulated hub genes in RW and SA validated using three independent external datasets and qRT-PCR. The gene signatures of the five hub genes could potentially be used to determine type 2 (T2)-high and T2-low subsets in preschoolers with RW.ConclusionsThese findings improve our understanding of the molecular pathogenesis of RW and provide a rationale for future exploration of the mechanistic relationship between RW and SA

Iterative learning-based path control for robot-assisted upper-limb rehabilitation

In robot-assisted rehabilitation, the performance of robotic assistance is dependent on the human user’s dynamics, which are subject to uncertainties. In order to enhance the rehabilitation performance and in particular to provide a constant level of assistance, we separate the task space into two subspaces where a combined scheme of adaptive impedance control and trajectory learning is developed. Human movement speed can vary from person to person and it cannot be predefined for the robot. Therefore, in the direction of human movement, an iterative trajectory learning approach is developed to update the robot reference according to human movement and to achieve the desired interaction force between the robot and the human user. In the direction normal to the task trajectory, human’s unintentional force may deteriorate the trajectory tracking performance. Therefore, an impedance adaptation method is utilized to compensate for unknown human force and prevent the human user drifting away from the updated robot reference trajectory. The proposed scheme was tested in experiments that emulated three upper-limb rehabilitation modes: zero interaction force, assistive and resistive. Experimental results showed that the desired assistance level could be achieved, despite uncertain human dynamics

Global analysis of the relationship between reconstructed solar induced chlorophyll fluorescence (SIF) and gross primary production (GPP)

Solar-induced chlorophyll fluorescence (SIF) is increasingly known as an effective proxy for plant photosynthesis, and therefore, has great potential in monitoring gross primary production (GPP). However, the relationship between SIF and GPP remains highly uncertain across space and time. Here, we analyzed the SIF (reconstructed, SIFc)–GPP relationships and their spatiotemporal variability, using GPP estimates from FLUXNET2015 and two spatiotemporally contiguous SIFc datasets (CSIF and GOSIF). The results showed that SIFc had significant positive correlations with GPP at the spatiotemporal scales investigated (p p p > 0.05). Therefore, we propose a two-slope scheme to differentiate ENF from non-ENF biome and synopsize spatiotemporal variability of the GPP/SIFc slope. The relative biases were 7.14% and 11.06% in the estimated cumulative GPP across all EC towers, respectively, for GOSIF and CSIF using a two-slope scheme. The significantly higher GPP/SIFc slopes of the ENF biome in the two-slope scheme are intriguing and deserve further study. In addition, there was still considerable dispersion in the comparisons of CSIF/GOSIF and GPP at both site and biome levels, calling for discriminatory analysis backed by higher spatial resolution to systematically address issues related to landscape heterogeneity and mismatch between SIFc pixel and the footprints of flux towers and their impacts on the SIF–GPP relationship