Dynamic association between energy transition technologies, renewable energy production, trade openness, green investment, carbon tax, and carbon neutrality: empirical evidences from China

The existing millennium documents the most adverse consequences of global warming which in contrast to pre-industrial era are more devastating. Thus, these prevailing consequences raise numerous concerns regarding the well-being of future and current generation. Scholars, in this regard, are putting efforts punctiliously towards methods that could halt the surging emissions. This paper also attempts to contributes to existing literature by reporting the empirical evidences regarding the role of energy transition technologies, renewable energy production (REP), trade openness, green investment, and carbon taxes in carbon neutrality in Chinse economy covering the time span of 1980–2020. By employing Dynamic Auto-regressive Distributed Lags (DARDL) model to check the association, findings exposed that electricity production from water sources, electricity production from solar sources, REP, trade openness, green investment, and carbon taxes are negatively correlated with CO2 emissions. Study offers policymakers a help in formulating policies related to achieve carbon neutrality using renewable sources of energy production, carbon taxes, and green investmen

Signals 1, 2 and B cell fate or: Where, when and for how long?

Diverse B cell responses are important for generating antibody‐mediated protection against highly variable pathogens. While some antigens can trigger T‐independent B cell proliferation and short‐term antibody production, development of long‐term humoral immunity requires T‐dependent B cell responses. The “two‐signal” model of B cell activation has long been invoked to explain alternate B cell recruitment into immune response to foreign antigens vs. induction of tolerance to self‐antigens. However, a number of other factors appear to influence the fate of mature B cells responding to antigen in vivo. In this review, we will discuss how various spatiotemporal scenarios of antigen access into secondary lymphoid organs, antigen valency and cellular environment of antigen acquisition by B cells, duration of B cell access to antigen and the timing of T cell help may affect follicular B cell fate, including death, survival, anergy, and recruitment into T‐dependent responses. We will also highlight unresolved questions related to B cell activation and tolerance in vivo that may have important implications for vaccine development and autoimmunity.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156186/2/imr12865.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156186/1/imr12865_am.pd

Language-driven Object Fusion into Neural Radiance Fields with Pose-Conditioned Dataset Updates

Neural radiance field is an emerging rendering method that generates high-quality multi-view consistent images from a neural scene representation and volume rendering. Although neural radiance field-based techniques are robust for scene reconstruction, their ability to add or remove objects remains limited. This paper proposes a new language-driven approach for object manipulation with neural radiance fields through dataset updates. Specifically, to insert a new foreground object represented by a set of multi-view images into a background radiance field, we use a text-to-image diffusion model to learn and generate combined images that fuse the object of interest into the given background across views. These combined images are then used for refining the background radiance field so that we can render view-consistent images containing both the object and the background. To ensure view consistency, we propose a dataset updates strategy that prioritizes radiance field training with camera views close to the already-trained views prior to propagating the training to remaining views. We show that under the same dataset updates strategy, we can easily adapt our method for object insertion using data from text-to-3D models as well as object removal. Experimental results show that our method generates photorealistic images of the edited scenes, and outperforms state-of-the-art methods in 3D reconstruction and neural radiance field blending

Structural and Functional Analysis of a β2-Adrenergic Receptor Complex with GRK5.

The phosphorylation of agonist-occupied G-protein-coupled receptors (GPCRs) by GPCR kinases (GRKs) functions to turn off G-protein signaling and turn on arrestin-mediated signaling. While a structural understanding of GPCR/G-protein and GPCR/arrestin complexes has emerged in recent years, the molecular architecture of a GPCR/GRK complex remains poorly defined. We used a comprehensive integrated approach of cross-linking, hydrogen-deuterium exchange mass spectrometry (MS), electron microscopy, mutagenesis, molecular dynamics simulations, and computational docking to analyze GRK5 interaction with the β2-adrenergic receptor (β2AR). These studies revealed a dynamic mechanism of complex formation that involves large conformational changes in the GRK5 RH/catalytic domain interface upon receptor binding. These changes facilitate contacts between intracellular loops 2 and 3 and the C terminus of the β2AR with the GRK5 RH bundle subdomain, membrane-binding surface, and kinase catalytic cleft, respectively. These studies significantly contribute to our understanding of the mechanism by which GRKs regulate the function of activated GPCRs. PAPERCLIP

Using Cognitive Work Analysis for Information System Design - a Dashboard for Visualising Liquidity

This paper presents the application of Cognitive Work Analysis (CWA) to create an Abstraction Hierarchy (AH) model that helps users to identify key functional relationships for managing financial systemic risk. Users may include investors, government agencies, policymakers, and financial institutions. The AH model will ultimately lead to an artefact that embeds visual analytics (the science of analytical reasoning facilitated by interactive interfaces) and combines automated analysis with dynamic interaction with the data. Based on the notion that companies with high leverage (total debt/equity) are more likely to become financially distressed than those with low leverage, our approach demonstrates how the CWA approach can be incorporated into a visual analytics system development methodology, and how the resultant prototype can be successfully applied to visualise macroprudential risk

Assessing the public acceptability of proposed policy interventions to reduce the misuse of antibiotics in Australia: A report on two community juries

Objective To elicit the views of well-informed community members on the acceptability of proposed policy interventions designed to improve community use of antibiotics in Australia. Design Two community juries held in 2016. Setting and participants Western Sydney and Dubbo communities in NSW, Australia. Twenty-nine participants of diverse social and cultural backgrounds, mixed genders and ages recruited via public advertising: one jury was drawn from a large metropolitan setting; the other from a regional/rural setting. Main outcome measure Jury verdict and rationale in response to a prioritization task and structured questions. Results Both juries concluded that potential policy interventions to curb antibiotic misuse in the community should be directed towards: (i) ensuring that the public and prescribers were better educated about the dangers of antibiotic resistance; (ii) making community-based human and animal health-care practitioners accountable for their prescribing decisions. Patient-centred approaches such as delayed prescribing were seen as less acceptable than prescriber-centred approaches; both juries completely rejected any proposal to decrease consumer demand by increasing antibiotic prices. Conclusion These informed citizens acknowledged the importance of raising public awareness of the risks, impacts and costs of antibiotic resistance and placed a high priority on increasing social and professional accountability through restrictive measures. Their overarching aim was that policy interventions should be directed towards creating collective actions and broad social support for changing antibiotic use through establishing and explaining the need for mechanisms to control and support better prescribing by practitioners, while not transferring the burdens, costs and risks of interventions to consumers.This work was supported by a seed grant from the Marie Bashir Institute for Infectious Disease and Biosecurity and NHMRC CRE 1102962. CD, JJ and GLG received funding support from a NHMRC Project grant (#1083079). SMC is funded through NHMRC Career Development Fellowship (#1032963)

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues.

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Discordant bioinformatic predictions of antimicrobial resistance from whole-genome sequencing data of bacterial isolates: an inter-laboratory study.

Antimicrobial resistance (AMR) poses a threat to public health. Clinical microbiology laboratories typically rely on culturing bacteria for antimicrobial-susceptibility testing (AST). As the implementation costs and technical barriers fall, whole-genome sequencing (WGS) has emerged as a 'one-stop' test for epidemiological and predictive AST results. Few published comparisons exist for the myriad analytical pipelines used for predicting AMR. To address this, we performed an inter-laboratory study providing sets of participating researchers with identical short-read WGS data from clinical isolates, allowing us to assess the reproducibility of the bioinformatic prediction of AMR between participants, and identify problem cases and factors that lead to discordant results. We produced ten WGS datasets of varying quality from cultured carbapenem-resistant organisms obtained from clinical samples sequenced on either an Illumina NextSeq or HiSeq instrument. Nine participating teams ('participants') were provided these sequence data without any other contextual information. Each participant used their choice of pipeline to determine the species, the presence of resistance-associated genes, and to predict susceptibility or resistance to amikacin, gentamicin, ciprofloxacin and cefotaxime. We found participants predicted different numbers of AMR-associated genes and different gene variants from the same clinical samples. The quality of the sequence data, choice of bioinformatic pipeline and interpretation of the results all contributed to discordance between participants. Although much of the inaccurate gene variant annotation did not affect genotypic resistance predictions, we observed low specificity when compared to phenotypic AST results, but this improved in samples with higher read depths. Had the results been used to predict AST and guide treatment, a different antibiotic would have been recommended for each isolate by at least one participant. These challenges, at the final analytical stage of using WGS to predict AMR, suggest the need for refinements when using this technology in clinical settings. Comprehensive public resistance sequence databases, full recommendations on sequence data quality and standardization in the comparisons between genotype and resistance phenotypes will all play a fundamental role in the successful implementation of AST prediction using WGS in clinical microbiology laboratories

Water resource management for sustainable development

Water resource management is the cornerstone for sustainable development. According to the United Nations world water development report, one-fifth of the world?s population lives in areas characterized by physical water scarcity.info:eu-repo/semantics/publishedVersio