Efficient distribution of carbon emissions reduction targets at the city level: A case of Yangtze River Delta region

The Chinese central government has released detailed carbon emissions abatement targets at the provincial level, but provides no specific emissions reduction targets at the city level. Most provincial governments simply allocate carbon emissions reduction tasks to their cities based on the GDP of their cities. Allocation approaches, however, should emphasize the most effective distribution to reach overall targets that reflect actual reduction capacities of cities. This paper proposes an allocation method at the city level by combining a data envelop analysis method, an entropy weight method and a clustering analysis method using the Yangtze River Delta region as a case study. Results of our analysis indicate that cities with higher carbon emissions abatement potentials, financial abilities, a larger number of above-scaled industrial enterprises and higher GDP are better positioned to reduce carbon emissions and should be assigned proportionately higher reduction targets. The merits and policy implications of the proposed approach are discussed in comparison to simply using GDP to allocate emission reduction targets

Na V 1.6a is required for normal activation of motor circuits normally excited by tactile stimulation

A screen for zebrafish motor mutants identified two noncomplementing alleles of a recessive mutation that were named non-active ( nav mi89 and nav mi130 ). nav embryos displayed diminished spontaneous and touch-evoked escape behaviors during the first 3 days of development. Genetic mapping identified the gene encoding Na V 1.6a ( scn8aa ) as a potential candidate for nav . Subsequent cloning of scn8aa from the two alleles of nav uncovered two missense mutations in Na V 1.6a that eliminated channel activity when assayed heterologously. Furthermore, the injection of RNA encoding wild-type scn8aa rescued the nav mutant phenotype indicating that scn8aa was the causative gene of nav . In-vivo electrophysiological analysis of the touch-evoked escape circuit indicated that voltage-dependent inward current was decreased in mechanosensory neurons in mutants, but they were able to fire action potentials. Furthermore, tactile stimulation of mutants activated some neurons downstream of mechanosensory neurons but failed to activate the swim locomotor circuit in accord with the behavioral response of initial escape contractions but no swimming. Thus, mutant mechanosensory neurons appeared to respond to tactile stimulation but failed to initiate swimming. Interestingly fictive swimming could be initiated pharmacologically suggesting that a swim circuit was present in mutants. These results suggested that Na V 1.6a was required for touch-induced activation of the swim locomotor network. © 2010 Wiley Periodicals, Inc. Develop Neurobiol 70:508–522, 2010Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75774/1/20791_ftp.pd

Initial low/hard state, multiple jet ejections and X-ray/radio correlations during the outburst of XTE J1859+226

We have studied the 1999 soft X-ray transient outburst of XTE J1859+226 at radio and X-ray wavelengths. The event was characterised by strong variability in the disc, corona and jet - in particular, a number of radio flares (ejections) took place and seemed well-correlated with hard X-ray events. Apparently unusual for the `canonical soft' X-ray transient, there was an initial period of low/hard state behaviour during the rise from quiescence but prior to the peak of the main outburst - we show that not only could this initial low/hard state be an ubiquitous feature of soft X-ray transient outbursts but that it could also be extremely important in our study of outburst mechanisms.Comment: 12 pages, Accepted for publication in MNRA

PMRD: a curated database for genes and mutants involved in plant male reproduction

BACKGROUND: Male reproduction is an essential biological event in the plant life cycle separating the diploid sporophyte and haploid gametophyte generations, which involves expression of approximately 20,000 genes. The control of male reproduction is also of economic importance for plant breeding and hybrid seed production. With the advent of forward and reverse genetics and genomic technologies, a large number of male reproduction-related genes have been identified. Thus it is extremely challenging for individual researchers to systematically collect, and continually update, all the available information on genes and mutants related to plant male reproduction. The aim of this study is to manually curate such gene and mutant information and provide a web-accessible resource to facilitate the effective study of plant male reproduction. DESCRIPTION: Plant Male Reproduction Database (PMRD) is a comprehensive resource for browsing and retrieving knowledge on genes and mutants related to plant male reproduction. It is based upon literature and biological databases and includes 506 male sterile genes and 484 mutants with defects of male reproduction from a variety of plant species. Based on Gene Ontology (GO) annotations and literature, information relating to a further 3697 male reproduction related genes were systematically collected and included, and using in text curation, gene expression and phenotypic information were captured from the literature. PMRD provides a web interface which allows users to easily access the curated annotations and genomic information, including full names, symbols, locations, sequences, expression patterns, functions of genes, mutant phenotypes, male sterile categories, and corresponding publications. PMRD also provides mini tools to search and browse expression patterns of genes in microarray datasets, run BLAST searches, convert gene ID and generate gene networks. In addition, a Mediawiki engine and a forum have been integrated within the database, allowing users to share their knowledge, make comments and discuss topics. CONCLUSION: PMRD provides an integrated link between genetic studies and the rapidly growing genomic information. As such this database provides a global view of plant male reproduction and thus aids advances in this important area.Xiao Cui, Qiudao Wang, Wenzhe Yin, Huayong Xu, Zoe A Wilson, Chaochun Wei, Shenyuan Pan, and Dabing Zhan

Feasibility of Universal Anomaly Detection without Knowing the Abnormality in Medical Images

Many anomaly detection approaches, especially deep learning methods, have been recently developed to identify abnormal image morphology by only employing normal images during training. Unfortunately, many prior anomaly detection methods were optimized for a specific "known" abnormality (e.g., brain tumor, bone fraction, cell types). Moreover, even though only the normal images were used in the training process, the abnormal images were often employed during the validation process (e.g., epoch selection, hyper-parameter tuning), which might leak the supposed ``unknown" abnormality unintentionally. In this study, we investigated these two essential aspects regarding universal anomaly detection in medical images by (1) comparing various anomaly detection methods across four medical datasets, (2) investigating the inevitable but often neglected issues on how to unbiasedly select the optimal anomaly detection model during the validation phase using only normal images, and (3) proposing a simple decision-level ensemble method to leverage the advantage of different kinds of anomaly detection without knowing the abnormality. The results of our experiments indicate that none of the evaluated methods consistently achieved the best performance across all datasets. Our proposed method enhanced the robustness of performance in general (average AUC 0.956)

Segment Anything Model (SAM) for Digital Pathology: Assess Zero-shot Segmentation on Whole Slide Imaging

The segment anything model (SAM) was released as a foundation model for image segmentation. The promptable segmentation model was trained by over 1 billion masks on 11M licensed and privacy-respecting images. The model supports zero-shot image segmentation with various segmentation prompts (e.g., points, boxes, masks). It makes the SAM attractive for medical image analysis, especially for digital pathology where the training data are rare. In this study, we evaluate the zero-shot segmentation performance of SAM model on representative segmentation tasks on whole slide imaging (WSI), including (1) tumor segmentation, (2) non-tumor tissue segmentation, (3) cell nuclei segmentation. Core Results: The results suggest that the zero-shot SAM model achieves remarkable segmentation performance for large connected objects. However, it does not consistently achieve satisfying performance for dense instance object segmentation, even with 20 prompts (clicks/boxes) on each image. We also summarized the identified limitations for digital pathology: (1) image resolution, (2) multiple scales, (3) prompt selection, and (4) model fine-tuning. In the future, the few-shot fine-tuning with images from downstream pathological segmentation tasks might help the model to achieve better performance in dense object segmentation

Morphology of supported polymer electrolyte ultra-thin films: a numerical study

Morphology of polymer electrolytes membranes (PEM), e.g., Nafion, inside PEM fuel cell catalyst layers has significant impact on the electrochemical activity and transport phenomena that determine cell performance. In those regions, Nafion can be found as an ultra-thin film, coating the catalyst and the catalyst support surfaces. The impact of the hydrophilic/hydrophobic character of these surfaces on the structural formation of the films has not been sufficiently explored yet. Here, we report about Molecular Dynamics simulation investigation of the substrate effects on the ionomer ultra-thin film morphology at different hydration levels. We use a mean-field-like model we introduced in previous publications for the interaction of the hydrated Nafion ionomer with a substrate, characterized by a tunable degree of hydrophilicity. We show that the affinity of the substrate with water plays a crucial role in the molecular rearrangement of the ionomer film, resulting in completely different morphologies. Detailed structural description in different regions of the film shows evidences of strongly heterogeneous behavior. A qualitative discussion of the implications of our observations on the PEMFC catalyst layer performance is finally proposed

Precipitation sensitivity to autoconversion rate in a numerical weather-prediction model

Aerosols are known to significantly affect cloud and precipitation patterns and intensity, but these interactions are ignored or very simplistically handled in climate and numerical weather-prediction (NWP) models. A suite of one-way nested Met Office Unified Model (UM) runs, with a single-moment bulk microphysics scheme was used to study two convective cases with contrasting characteristics observed in southern England. The autoconversion process that converts cloud water to rain is directly controlled by the assumed droplet number. The impact of changing cloud droplet number concentration (CDNC) on cloud and precipitation evolution can be inferred through changes to the autoconversion rate. This was done for a range of resolutions ranging from regional NWP (1 km) to high resolution (up to 100 m grid spacing) to evaluate the uncertainties due to changing CDNC as a function of horizontal grid resolution. The first case is characterised by moderately intense convective showers forming below an upper-level potential vorticity anomaly, with a low freezing level. The second case, characterised by one persistent stronger storm, is warmer with a deeper boundary layer. The colder case is almost insensitive to even large changes in CDNC, while in the warmer case a change of a factor of 3 in assumed CDNC affects total surface rain rate by ~17%. In both cases the sensitivity to CDNC is similar at all grid spacings <1 km. The contrasting sensitivities of these cases are induced by their contrasting ice-phase proportion. The ice processes in this model damp the precipitation sensitivity to CDNC. For this model the convection is sensitive to CDNC when the accretion process is more significant than the melting process and vice versa

Atomically dispersed nickel as coke-resistant active sites for methane dry reforming

Dry reforming of methane (DRM) is an attractive route to utilize CO2 as a chemical feedstock with which to convert CH4 into valuable syngas and simultaneously mitigate both greenhouse gases. Ni-based DRM catalysts are promising due to their high activity and low cost, but suffer from poor stability due to coke formation which has hindered their commercialization. Herein, we report that atomically dispersed Ni single atoms, stabilized by interaction with Ce-doped hydroxyapatite, are highly active and coke-resistant catalytic sites for DRM. Experimental and computational studies reveal that isolated Ni atoms are intrinsically coke-resistant due to their unique ability to only activate the first C-H bond in CH4, thus avoiding methane deep decomposition into carbon. This discovery offers new opportunities to develop large-scale DRM processes using earth abundant catalysts

Genome-Wide Association Study and Gene Expression Analysis Identifies CD84 as a Predictor of Response to Etanercept Therapy in Rheumatoid Arthritis

Anti-tumor necrosis factor alpha (anti-TNF) biologic therapy is a widely used treatment for rheumatoid arthritis (RA). It is unknown why some RA patients fail to respond adequately to anti-TNF therapy, which limits the development of clinical biomarkers to predict response or new drugs to target refractory cases. To understand the biological basis of response to anti-TNF therapy, we conducted a genome-wide association study (GWAS) meta-analysis of more than 2 million common variants in 2,706 RA patients from 13 different collections. Patients were treated with one of three anti-TNF medications: etanercept (n = 733), infliximab (n = 894), or adalimumab (n = 1,071). We identified a SNP (rs6427528) at the 1q23 locus that was associated with change in disease activity score (ΔDAS) in the etanercept subset of patients (P = 8×10-8), but not in the infliximab or adalimumab subsets (P>0.05). The SNP is predicted to disrupt transcription factor binding site motifs in the 3′ UTR of an immune-related gene, CD84, and the allele associated with better response to etanercept was associated with higher CD84 gene expression in peripheral blood mononuclear cells (P = 1×10-11 in 228 non-RA patients and P = 0.004 in 132 RA patients). Consistent with the genetic findings, higher CD84 gene expression correlated with lower cross-sectional DAS (P = 0.02, n = 210) and showed a non-significant trend for better ΔDAS in a subset of RA patients with gene expression data (n = 31, etanercept-treated). A small, multi-ethnic replication showed a non-significant trend towards an association among etanercept-treated RA patients of Portuguese ancestry (n = 139, P = 0.4), but no association among patients of Japanese ancestry (n = 151, P = 0.8). Our study demonstrates that an allele associated with response to etanercept therapy is also associated with CD84 gene expression, and further that CD84 expression correlates with disease activity. These findings support a model in which CD84 genotypes and/or expression may serve as a useful biomarker for response to etanercept treatment in RA patients of European ancestry. © 2013 Cui et al