Sensitivity of deexcitation energies of superdeformed secondary minima to the density dependence of symmetry energy with the relativistic mean-field theory

The relationship between deexcitation energies of superdeformed secondary minima relative to ground states and the density dependence of the symmetry energy is investigated for heavy nuclei using the relativistic mean field (RMF) model. It is shown that the deexcitation energies of superdeformed secondary minima are sensitive to differences in the symmetry energy that are mimicked by the isoscalar-isovector coupling included in the model. With deliberate investigations on a few Hg isotopes that have data of deexcitation energies, we find that the description for the deexcitation energies can be improved due to the softening of the symmetry energy. Further, we have investigated deexcitation energies of odd-odd heavy nuclei that are nearly independent of pairing correlations, and have discussed the possible extraction of the constraint on the density dependence of the symmetry energy with the measurement of deexcitation energies of these nuclei.Comment: 14 pages, 3 figure

Influence of Dynamic Ozone Dry Deposition on Ozone Pollution

Identifying the contributions of chemistry and transport to observed ozone pollution using regional-to-global models relies on accurate representation of ozone dry deposition. We use a recently developed configuration of the NOAA GFDL chemistry-climate model - in which the atmosphere and land are coupled through dry deposition-to investigate the influence of ozone dry deposition on ozone pollution over northern midlatitudes. In our model, deposition pathways are tied to dynamic terrestrial processes, such as photosynthesis and water cycling through the canopy and soil. Small increases in winter deposition due to more process-based representation of snow and deposition to surfaces reduce hemispheric-scale ozone throughout the lower troposphere by 5-12 ppb, improving agreement with observations relative to a simulation with the standard configuration for ozone dry deposition. Declining snow cover by the end of the 21st-century tempers the previously identified influence of rising methane on winter ozone. Dynamic dry deposition changes summer surface ozone by -4 to +7 ppb. While previous studies emphasize the importance of uptake by plant stomata, new diagnostic tracking of depositional pathways reveals a widespread impact of nonstomatal deposition on ozone pollution. Daily variability in both stomatal and nonstomatal deposition contribute to daily variability in ozone pollution. Twenty-first century changes in summer deposition result from a balance among changes in individual pathways, reflecting differing responses to both high carbon dioxide (through plant physiology versus biomass accumulation) and water availability. Our findings highlight a need for constraints on the processes driving ozone dry deposition to test representation in regional-to-global models.Peer reviewe

Comparison of Emissions Inventories of Anthropogenic Air Pollutants in China

Anthropogenic air pollutant emissions have been increasing rapidly in China. Modelers use emissions inventories to assess temporal and spatial distribution of these emissions to estimate their impacts on regional and global air quality. However, large uncertainties exist in emissions estimates and assessing discrepancies in these inventories is essential for better understanding of the trends in air pollution over China. We compare five different emissions inventories estimating emissions of carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), particulate matter with an aerodynamic diameter of 10 um or less (PM10) from China. The emissions inventories analyzed in this paper include Regional Emissions inventory in ASia v2.1 (REAS); Multi-resolution Emission Inventory for China (MEIC); Emission Database for Global Atmospheric Research v4.2 (EDGAR); the inventory by Yu Zhao (ZHAO); and the Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS). We focus on the period between 2000 and 2008 during which the Chinese economic activities have more than doubled. In addition to the national total, we also analyzed emissions from four source sectors (industry, transportation, power, and residential) and within seven regions in China (East, North, Northeast, Central, Southwest, Northwest, and South) and found that large disagreements (~ seven fold) exist among the five inventories at disaggregated levels. These discrepancies lead to differences of 67 ug/m3, 15 ppbv, and 470 ppbv for monthly mean PM10, O3, and CO, respectively, in modelled regional concentrations in China. We also find that MEIC inventory emissions estimates create a VOC-limited environment that produces much lower O3 mixing ratio in the East and Central China compared to the simulations using REAS and EDGAR estimates. Our results illustrate that a better understanding of Chinese emissions at more disaggregated levels is essential for finding an effective mitigation measure for reducing national and regional air pollution in China

Hedonism and the experience machine

Money isn’t everything, so what is? Many government leaders, social policy theorists, and members of the general public have a ready answer: happiness. This paper examines an opposing view due to Robert Nozick, which centres on his experience-machine thought experiment. Despite the example's influence among philosophers, the argument behind it is riddled with difficulties. Dropping the example allows us to re-version Nozick's argument in a way that makes it far more forceful - and less dependent on people's often divergent intutions about the experience machine

Modernization and Its Discontents

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/67022/2/10.1177_000276427702100208.pd

Regionally aggregated, stitched and de‐drifted CMIP‐climate data, processed with netCDF‐SCM v2.0.0

The world's most complex climate models are currently running a range of experiments as part of the Sixth Coupled Model Intercomparison Project (CMIP6). Added to the output from the Fifth Coupled Model Intercomparison Project (CMIP5), the total data volume will be in the order of 20PB. Here, we present a dataset of annual, monthly, global, hemispheric and land/ocean means derived from a selection of experiments of key interest to climate data analysts and reduced complexity climate modellers. The derived dataset is a key part of validating, calibrating and developing reduced complexity climate models against the behaviour of more physically complete models. In addition to its use for reduced complexity climate modellers, we aim to make our data accessible to other research communities. We facilitate this in a number of ways. Firstly, given the focus on annual, monthly, global, hemispheric and land/ocean mean quantities, our dataset is orders of magnitude smaller than the source data and hence does not require specialized ‘big data’ expertise. Secondly, again because of its smaller size, we are able to offer our dataset in a text-based format, greatly reducing the computational expertise required to work with CMIP output. Thirdly, we enable data provenance and integrity control by tracking all source metadata and providing tools which check whether a dataset has been retracted, that is identified as erroneous. The resulting dataset is updated as new CMIP6 results become available and we provide a stable access point to allow automated downloads. Along with our accompanying website (cmip6.science.unimelb.edu.au), we believe this dataset provides a unique community resource, as well as allowing non-specialists to access CMIP data in a new, user-friendly way

Methods for high-dimensonal analysis of cells dissociated from cyropreserved synovial tissue

Background: Detailed molecular analyses of cells from rheumatoid arthritis (RA) synovium hold promise in identifying cellular phenotypes that drive tissue pathology and joint damage. The Accelerating Medicines Partnership RA/SLE Network aims to deconstruct autoimmune pathology by examining cells within target tissues through multiple high-dimensional assays. Robust standardized protocols need to be developed before cellular phenotypes at a single cell level can be effectively compared across patient samples. Methods: Multiple clinical sites collected cryopreserved synovial tissue fragments from arthroplasty and synovial biopsy in a 10% DMSO solution. Mechanical and enzymatic dissociation parameters were optimized for viable cell extraction and surface protein preservation for cell sorting and mass cytometry, as well as for reproducibility in RNA sequencing (RNA-seq). Cryopreserved synovial samples were collectively analyzed at a central processing site by a custom-designed and validated 35-marker mass cytometry panel. In parallel, each sample was flow sorted into fibroblast, T-cell, B-cell, and macrophage suspensions for bulk population RNA-seq and plate-based single-cell CEL-Seq2 RNA-seq. Results: Upon dissociation, cryopreserved synovial tissue fragments yielded a high frequency of viable cells, comparable to samples undergoing immediate processing. Optimization of synovial tissue dissociation across six clinical collection sites with ~ 30 arthroplasty and ~ 20 biopsy samples yielded a consensus digestion protocol using 100 μg/ml of Liberase™ TL enzyme preparation. This protocol yielded immune and stromal cell lineages with preserved surface markers and minimized variability across replicate RNA-seq transcriptomes. Mass cytometry analysis of cells from cryopreserved synovium distinguished diverse fibroblast phenotypes, distinct populations of memory B cells and antibody-secreting cells, and multiple CD4+ and CD8+ T-cell activation states. Bulk RNA-seq of sorted cell populations demonstrated robust separation of synovial lymphocytes, fibroblasts, and macrophages. Single-cell RNA-seq produced transcriptomes of over 1000 genes/cell, including transcripts encoding characteristic lineage markers identified. Conclusions: We have established a robust protocol to acquire viable cells from cryopreserved synovial tissue with intact transcriptomes and cell surface phenotypes. A centralized pipeline to generate multiple high-dimensional analyses of synovial tissue samples collected across a collaborative network was developed. Integrated analysis of such datasets from large patient cohorts may help define molecular heterogeneity within RA pathology and identify new therapeutic targets and biomarkers

Large-scale sequencing identifies multiple genes and rare variants associated with Crohn's disease susceptibility

Genome-wide association studies (GWASs) have identified hundreds of loci associated with Crohn's disease (CD). However, as with all complex diseases, robust identification of the genes dysregulated by noncoding variants typically driving GWAS discoveries has been challenging. Here, to complement GWASs and better define actionable biological targets, we analyzed sequence data from more than 30,000 patients with CD and 80,000 population controls. We directly implicate ten genes in general onset CD for the first time to our knowledge via association to coding variation, four of which lie within established CD GWAS loci. In nine instances, a single coding variant is significantly associated, and in the tenth, ATG4C, we see additionally a significantly increased burden of very rare coding variants in CD cases. In addition to reiterating the central role of innate and adaptive immune cells as well as autophagy in CD pathogenesis, these newly associated genes highlight the emerging role of mesenchymal cells in the development and maintenance of intestinal inflammation.Large-scale sequence-based analyses identify novel risk variants and susceptibility genes for Crohn's disease, and implicate mesenchymal cell-mediated intestinal homeostasis in disease etiology.Cellular mechanisms in basic and clinical gastroenterology and hepatolog

Surface ozone-temperature relationships in the eastern US: A monthly climatology for evaluating chemistry-climate models

We use long-term, coincident O-3 and temperature measurements at the regionally representative US Environmental Protection Agency Clean Air Status and Trends Network (CASTNet) over the eastern US from 1988 through 2009 to characterize the surface O-3 response to year-to-year fluctuations in weather, for the purpose of evaluating global chemistry-climate models. We first produce a monthly climatology for each site over all available years, defined as the slope of the best-fit line (m(O3-T)) between monthly average values of maximum daily 8-hour average (MDA8) O-3 and monthly average values of daily maximum surface temperature (T-max). Applying two distinct statistical approaches to aggregate the site-specific measurements to the regional scale, we find that summer time m(O3-T) is 3-6 ppb K-1 (r = 0.5-0.8) over the Northeast, 3-4 ppb K-1 (r = 0.5-0.9) over the Great Lakes, and 3-6 ppb K-1 (r = 0.2-0.8) over the Mid-Atlantic. The Geophysical Fluid Dynamics Laboratory (GFDL) Atmospheric Model version 3 (AM3) global chemistry-climate model generally captures the seasonal variations in correlation coefficients and m(O3-T) despite biases in both monthly mean summertime MDA8 O-3 (up to +10 to +30 ppb) and daily T-max (up to +5 K) over the eastern US. During summer, GFDL AM3 reproduces m(O3-T) over the Northeast (m(O3-T) = 2-6 ppb K-1; r = 0.6-0.9), but underestimates m(O3-T) by 4 ppb K-1 over the Mid-Atlantic, in part due to excessively warm temperatures above which O-3 production saturates in the model. Combining T-max biases in GFDL AM3 with an observation-based m(O3-T) estimate of 3 ppb K-1 implies that temperature biases could explain up to 5-15 ppb of the MDA8 O-3 bias in August and September though correcting for excessively cool temperatures would worsen the O-3 bias in June. We underscore the need for long-term, coincident measurements of air pollution and meteorological variables to develop process-level constraints for evaluating chemistry-climate models used to project air quality responses to climate change. Published by Elsevier Ltd