Focusing on an ‘atypical’ group of creative workers, viz., rural-to-urban migrant painters in China, this article takes hope as a lens to investigate an extreme case of creative work precarity. ...Drawing on the findings of a 42-month longitudinal ethnographic study, I demonstrate how wall painters cope with the precarious present by channelling their initial hopes for a future of freedom, original work and stability into three different, everyday practices: playing, creating and waiting. Approaching precarity from an intersectional perspective, this study explicates how the multiple dimensions of precarity interact with each other in forming wall painters’ shifting modes of hope. Manifesting the fluidity and contingency of wall painters’ hopes in the vicissitudes of Dafen during China’s post-industrial turn, this study reconciles the debate in creative labour studies that sees hope as either a utopian fantasy or an everyday practice and further contributes to the political economy of hope in creative labour studies.
Dielectric materials with good thermal transport performance and desirable dielectric properties have significant potential to address the critical challenges of heat dissipation for microelectronic ...devices and power equipment under high electric field. This work reported the role of synergistic effect and interface on through-plane thermal conductivity and dielectric properties by intercalating the hybrid fillers of the alumina and boron nitride nanosheets (BNNs) into epoxy resin. For instance, epoxy composite with hybrid fillers at a relatively low loading shows an increase of around 3 times in through-plane thermal conductivity and maintains a close dielectric breakdown strength compared to pure epoxy. Meanwhile, the epoxy composite shows extremely low dielectric loss of 0.0024 at room temperature and 0.022 at 100 ℃ and 10
Hz. And covalent bonding and hydrogen-bond interaction models were presented for analyzing the thermal conductivity and dielectric properties.
Objective
To assess perceptions of risk and related factors concerning COVID-19 epidemic among residents in Chongqing city, China.
Methods
With convenience sampling, a web questionnaire survey was ...conducted among 476 residents living in Chongqing on February 13rd to 14th in 2020, when citizens just started to get back to work.
Results
Residents’ estimated perceived risks were (4.63 ± 0.57), (4.19 ± 0.76), (3.23 ± 0.91) and (2.29 ± 0.96) for the infectivity, pathogenicity, lethality and self-rated infection possibility of COVID-19, respectively. Females (OR = 4.234), people with income ≥ 2000 yuan (2000–4999 yuan: OR = 5.052, 5000–9999 yuan: OR = 4.301, ≥ 10,000 yuan: OR = 23.459), the married status (OR = 1.811), the divorced status, widows or widowers (OR = 3.038), people living with families including children (OR = 5.085) or chronic patients (OR = 2.423) had a higher perceived risk level, as well as people who used free media websites (OR = 1.756), community workers (OR = 4.064) or community information platforms (OR = 2.235) as main media information sources. The perceived risk increased by 4.9% for every one-year increase of age. People who used WeChat contacts (OR = 0.196) as the main media information source, reported a lower perceived risk.
Conclusion
Residents reported a high level of risk perception towards COVID-19 in Chongqing and it was impacted by the population demographic characteristics. Media information sources, including community information platforms and community workers may cause the increase of public risk perceptions.
To satisfy the increasing demand of mobile data traffic and meet the stringent requirements of the emerging Internet-of-Things (IoT) applications such as smart city, healthcare, and augmented/virtual ...reality (AR/VR), the fifth-generation (5G) enabling technologies are proposed and utilized in networks. As an emerging key technology of 5G and a key enabler of IoT, multiaccess edge computing (MEC), which integrates telecommunication and IT services, offers cloud computing capabilities at the edge of the radio access network (RAN). By providing computational and storage resources at the edge, MEC can reduce latency for end users. Hence, this article investigates MEC for 5G and IoT comprehensively. It analyzes the main features of MEC in the context of 5G and IoT and presents several fundamental key technologies which enable MEC to be applied in 5G and IoT, such as cloud computing, software-defined networking/network function virtualization, information-centric networks, virtual machine (VM) and containers, smart devices, network slicing, and computation offloading. In addition, this article provides an overview of the role of MEC in 5G and IoT, bringing light into the different MEC-enabled 5G and IoT applications as well as the promising future directions of integrating MEC with 5G and IoT. Moreover, this article further elaborates research challenges and open issues of MEC for 5G and IoT. Last but not least, we propose a use case that utilizes MEC to achieve edge intelligence in IoT scenarios.
A
bstract
We study unbinned multivariate analysis techniques, based on Statistical Learning, for indirect new physics searches at the LHC in the Effective Field Theory framework. We focus in ...particular on high-energy ZW production with fully leptonic decays, modeled at different degrees of refinement up to NLO in QCD. We show that a considerable gain in sensitivity is possible compared with current projections based on binned analyses. As expected, the gain is particularly significant for those operators that display a complex pattern of interference with the Standard Model amplitude. The most effective method is found to be the “Quadratic Classifier” approach, an improvement of the standard Statistical Learning classifier where the quadratic dependence of the differential cross section on the EFT Wilson coefficients is built-in and incorporated in the loss function. We argue that the Quadratic Classifier performances are nearly statistically optimal, based on a rigorous notion of optimality that we can establish for an approximate analytic description of the ZW process.
•We examine whether China's coal consumption has actually reached its peak.•A novel regional division method is proposed based on coal dependence and economic level.•Coal Kuznets curve hypothesis ...holds for the whole panel and subpanels in China.•Only coal-dependent developing region has not reached a peak in the use of coal.•Province-specific results vary provinces.
To investigate whether China's coal consumption has actually peaked, this study tests the national and regional coal Kuznets curve (CKC) hypothesis by using a panel dataset of 30 provinces covering 2000 to 2016. To fully capture the trends of coal consumption at the national, regional, and provincial levels, this study proposes a novel regional division method based on coal dependence and economic level. Considering the potential cross-sectional dependence and slope homogeneity, the newly developed methods allowing for heterogeneous slope coefficients are employed. The whole panel and subpanel results validate the CKC hypothesis for China, and province-specific results are mixed. The subpanel results reveal that only in the coal-dependent developing region has the peak of coal consumption not been reached, and for other regions, coal consumption displays a downward trend along with gross domestic product (GDP) increases. Furthermore, the province-specific results suggest that coal consumption will continue to increase slightly in certain provinces. This study implies that to reduce coal consumption, the coal-dependent developing region and provinces with a future turning point should act with great urgency to achieve a balance of economic growth and environmental responsibility. In addition, policymakers formulating coal consumption reduction policy in China must consider the remarkable differences across regions and provinces.
Cytidine base editors (CBEs) and adenine base editors (ABEs), composed of a cytidine deaminase or an evolved adenine deaminase fused to Cas9 nickase, enable the conversion of C·G to T·A or A·T to G·C ...base pair in organisms, respectively. Here, we show that BE3 and ABE7.10 systems can achieve a targeted mutation efficiency of 53-88% and 44-100%, respectively, in both blastocysts and Founder (F0) rabbits. Meanwhile, this strategy can be used to precisely mimic human pathologies by efficiently inducing nonsense or missense mutations as well as RNA mis-splicing in rabbit. In addition, the reduced frequencies of indels with higher product purity are also determined in rabbit blastocysts by BE4-Gam, which is an updated version of the BE3 system. Collectively, this work provides a simple and efficient method for targeted point mutations and generation of disease models in rabbit.
The observation data of dam displacement can reflect the dam’s actual service behavior intuitively. Therefore, the establishment of a precise data-driven model to realize accurate and reliable safety ...monitoring of dam deformation is necessary. This study proposes a novel probabilistic prediction approach for concrete dam displacement based on optimized relevance vector machine (ORVM). A practical optimization framework for parameters estimation using the parallel Jaya algorithm (PJA) is developed, and various simple kernel/multi-kernel functions of relevance vector machine (RVM) are tested to obtain the optimal selection. The proposed model is tested on radial displacement measurements of a concrete arch dam to mine the effect of hydrostatic, seasonal and irreversible time components on dam deformation. Four algorithms, including support vector regression (SVR), radial basis function neural network (RBF-NN), extreme learning machine (ELM) and the HST-based multiple linear regression (HST-MLR), are used for comparison with the ORVM model. The simulation results demonstrate that the proposed multi-kernel ORVM model has the best performance for predicting the displacement out of range of the used measurements dataset. Meanwhile, the ORVM model has the advantages of probabilistic output and can provide reasonable confidence interval (CI) for dam safety monitoring. This study lays the foundation for the application of RVM in the field of dam health monitoring.
Stem cell therapy may replace lost photoreceptors and preserve residual photoreceptors during retinal degeneration (RD). Unfortunately, the degenerative microenvironment compromises the fate of ...grafted cells, demanding supplementary strategies for microenvironment regulation. Donor cells with both proper regeneration capability and intrinsic ability to improve microenvironment are highly desired. Here, we use cell surface markers (C-Kit
/SSEA4
) to effectively eliminate tumorigenic embryonic cells and enrich retinal progenitor cells (RPCs) from human embryonic stem cell (hESC)-derived retinal organoids, which, following subretinal transplantation into RD models of rats and mice, significantly improve vision and preserve the retinal structure. We characterize the pattern of integration and materials transfer following transplantation, which likely contribute to the rescued photoreceptors. Moreover, C-Kit
/SSEA4
cells suppress microglial activation, gliosis and the production of inflammatory mediators, thereby providing a healthier host microenvironment for the grafted cells and delaying RD. Therefore, C-Kit
/SSEA4
cells from hESC-derived retinal organoids are a promising therapeutic cell source.
Epidermal cell fate determination-including trichome initiation, root hair formation, and flavonoid and mucilage biosynthesis in
(
)-are controlled by a similar transcriptional regulatory network. In ...the network, it has been proposed that the MYB-bHLH-WD40 (MBW) activator complexes formed by an R2R3 MYB transcription factor, a bHLH transcription factor and the WD40-repeat protein TRANSPARENT TESTA GLABRA1 (TTG1) regulate the expression of downstream genes required for cell fate determination, flavonoid or mucilage biosynthesis, respectively. In epidermal cell fate determination and mucilage biosynthesis, the MBW activator complexes activate the expression of
(
). GL2 is a homeodomain transcription factor that promotes trichome initiation in shoots, mucilage biosynthesis in seeds, and inhibits root hair formation in roots. The MBW activator complexes also activate several R3 MYB genes. The R3 MYB proteins, in turn, competing with the R2R3 MYBs for binding bHLH transcription factors, therefore inhibiting the formation of the MBW activator complexes, lead to the inhibition of trichome initiation in shoots, and promotion of root hair formation in roots. In flavonoid biosynthesis, the MBW activator complexes activate the expression of the late biosynthesis genes in the flavonoid pathway, resulting in the production of anthocyanins or proanthocyanidins. Research progress in recent years suggests that the transcriptional regulatory network that controls epidermal cell fate determination and anthocyanin biosynthesis in
is far more complicated than previously thought. In particular, more regulators of GL2 have been identified, and GL2 has been shown to be involved in the regulation of anthocyanin biosynthesis. This review focuses on the research progress on the regulation of GL2 expression, and the roles of GL2 in the regulation of epidermal cell fate determination and anthocyanin biosynthesis in Arabidopsis.
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