The Political Gender Gap: Gender Bias in Facial Inferences that Predict Voting Behavior

Background: Throughout human history, a disproportionate degree of political power around the world has been held by men. Even in democracies where the opportunity to serve in top political positions is available to any individual elected by the majority of their constituents, most of the highest political offices are occupied by male leaders. What psychological factors underlie this political gender gap? Contrary to the notion that people use deliberate, rational strategies when deciding whom to vote for in major political elections, research indicates that people use shallow decision heuristics, such as impressions of competence solely from a candidate’s facial appearance, when deciding whom to vote for. Because gender has previously been shown to affect a number of inferences made from the face, here we investigated the hypothesis that gender of both voter and candidate affects the kinds of facial impressions that predict voting behavior. Methodology/Principal Finding: Male and female voters judged a series of male and female political candidates on how competent, dominant, attractive and approachable they seemed based on their facial appearance. Then they saw a series of pairs of political candidates and decided which politician they would vote for in a hypothetical election for President of the United States. Results indicate that both gender of voter and candidate affect the kinds of facial impressions that predict voting behavior. All voters are likely to vote for candidates who appear more competent. However, male candidates that appear more approachable and female candidates who appear more attractive are more likely to win votes. In particular

Work in Progress: A meta-literature review of Moral Foundations Theory as applied in game studies

This paper outlines an in-progress systematic review of extant research in game studies that has incorporated Moral Foundations Theory (MFT), or relevant extensions of that theory to media entertainment, such as the Moral Intuition and Media Entertainment/Model of Intuitive Morality and Exemplars (MIME). Due to the interdisciplinary nature of these theoretical perspectives as well as game studies broadly, systematic review is critical to helping us collectively understand and collate the research in this area. The systematic review is done in two parts, one as a deep description of the characteristics of included studies, and one as a statistical analysis (as well as a qualitative assessment) of the quality of those included studies. At this stage, an initial set of 24-26 articles focused on gaming and MFT/MIME have been uncovered via systematic database searching, and both study characteristic and study quality coding sheets in progress (shared, within)

Results from EDGES High-Band: II. Constraints on Parameters of Early Galaxies

We use the sky-average spectrum measured by EDGES High-Band ($90-190$ MHz) to constrain parameters of early galaxies independent of the absorption feature at $78$~MHz reported by Bowman et al. (2018). These parameters represent traditional models of cosmic dawn and the epoch of reionization produced with the 21cmFAST simulation code (Mesinger & Furlanetto 2007, Mesinger et al. 2011). The parameters considered are: (1) the UV ionizing efficiency ($\zeta$), (2) minimum halo virial temperature hosting efficient star-forming galaxies ($T^{\rm min}_{\rm vir}$), (3) integrated soft-band X-ray luminosity ($L_{\rm X\,<\,2\,keV}/{\rm SFR}$), and (4) minimum X-ray energy escaping the first galaxies ($E_{0}$), corresponding to a typical H${\rm \scriptstyle I}$ column density for attenuation through the interstellar medium. The High-Band spectrum disfavors high values of $T^{\rm min}_{\rm vir}$ and $\zeta$, which correspond to signals with late absorption troughs and sharp reionization transitions. It also disfavors intermediate values of $L_{\rm X\,<\,2\,keV}/{\rm SFR}$, which produce relatively deep and narrow troughs within the band. Specifically, we rule out $39.4<\log_{10}\left(L_{\rm X\,<\,2\,keV}/{\rm SFR}\right)<39.8$ ($95\%$ C.L.). We then combine the EDGES High-Band data with constraints on the electron scattering optical depth from Planck and the hydrogen neutral fraction from high-$z$ quasars. This produces a lower degeneracy between $\zeta$ and $T^{\rm min}_{\rm vir}$ than that reported in Greig & Mesinger (2017a) using the Planck and quasar constraints alone. Our main result in this combined analysis is the estimate $4.5$~$\leq \log_{10}\left(T^{\rm min}_{\rm vir}/\rm K\right)\leq$~$5.7$ ($95\%$ C.L.). We leave for future work the evaluation of $21$~cm models using simultaneously data from EDGES Low- and High-Band.Comment: Accepted in Ap

Expression profiling identifies genes involved in emphysema severity

Chronic obstructive pulmonary disease (COPD) is a major public health problem. The aim of this study was to identify genes involved in emphysema severity in COPD patients

MS4A1 Dysregulation in Asbestos-Related Lung Squamous Cell Carcinoma Is Due to CD20 Stromal Lymphocyte Expression

Asbestos-related lung cancer accounts for 4–12% of lung cancers worldwide. We have previously identified ADAM28 as a putative oncogene involved in asbestos-related lung adenocarcinoma (ARLC-AC). We hypothesised that similarly gene expression profiling of asbestos-related lung squamous cell carcinomas (ARLC-SCC) may identify candidate oncogenes for ARLC-SCC. We undertook a microarray gene expression study in 56 subjects; 26 ARLC-SCC (defined as lung asbestos body (AB) counts >20AB/gram wet weight (gww) and 30 non-asbestos related lung squamous cell carcinoma (NARLC-SCC; no detectable lung asbestos bodies; 0AB/gww). Microarray and bioinformatics analysis identified six candidate genes differentially expressed between ARLC-SCC and NARLC-SCC based on statistical significance (p<0.001) and fold change (FC) of >2-fold. Two genes MS4A1 and CARD18, were technically replicated by qRT-PCR and showed consistent directional changes. As we also found MS4A1 to be overexpressed in ARLC-ACs, we selected this gene for biological validation in independent test sets (one internal, and one external dataset (2 primary tumor sets)). MS4A1 RNA expression dysregulation was validated in the external dataset but not in our internal dataset, likely due to the small sample size in the test set as immunohistochemical (IHC) staining for MS4A1 (CD20) showed that protein expression localized predominantly to stromal lymphocytes rather than tumor cells in ARLC-SCC. We conclude that differential expression of MS4A1 in this comparative gene expression study of ARLC-SCC versus NARLC-SCC is a stromal signal of uncertain significance, and an example of the rationale for tumor cell enrichment in preparation for gene expression studies where the aim is to identify markers of particular tumor phenotypes. Finally, our study failed to identify any strong gene candidates whose expression serves as a marker of asbestos etiology. Future research is required to determine the role of stromal lymphocyte MS4A1 dysregulation in pulmonary SCCs caused by asbestos

Cluster M Mycobacteriophages Bongo, PegLeg, and Rey with Unusually Large Repertoires of tRNA Isotopes

Genomic analysis of a large set of phages infecting the common hostMycobacterium smegmatis mc2155 shows that they span considerable genetic diversity. There are more than 20 distinct types that lack nucleotide similarity with each other, and there is considerable diversity within most of the groups. Three newly isolated temperate mycobacteriophages, Bongo, PegLeg, and Rey, constitute a new group (cluster M), with the closely related phages Bongo and PegLeg forming subcluster M1 and the more distantly related Rey forming subcluster M2. The cluster M mycobacteriophages have siphoviral morphologies with unusually long tails, are homoimmune, and have larger than average genomes (80.2 to 83.7 kbp). They exhibit a variety of features not previously described in other mycobacteriophages, including noncanonical genome architectures and several unusual sets of conserved repeated sequences suggesting novel regulatory systems for both transcription and translation. In addition to containing transfer-messenger RNA and RtcB-like RNA ligase genes, their genomes encode 21 to 24 tRNA genes encompassing complete or nearly complete sets of isotypes. We predict that these tRNAs are used in late lytic growth, likely compensating for the degradation or inadequacy of host tRNAs. They may represent a complete set of tRNAs necessary for late lytic growth, especially when taken together with the apparent lack of codons in the same late genes that correspond to tRNAs that the genomes of the phages do not obviously encode

National CO\u3csub\u3e2\u3c/sub\u3e budgets (2015-2020) inferred from atmospheric CO\u3csub\u3e2\u3c/sub\u3e observations in support of the global stocktake

Accurate accounting of emissions and removals of CO2 is critical for the planning and verification of emission reduction targets in support of the Paris Agreement. Here, we present a pilot dataset of country-specific net carbon exchange (NCE; fossil plus terrestrial ecosystem fluxes) and terrestrial carbon stock changes aimed at informing countries\u27 carbon budgets. These estimates are based on top-down NCE outputs from the v10 Orbiting Carbon Observatory (OCO-2) modeling intercomparison project (MIP), wherein an ensemble of inverse modeling groups conducted standardized experiments assimilating OCO-2 column-Averaged dry-Air mole fraction (XCO2) retrievals (ACOS v10), in situ CO2 measurements or combinations of these data. The v10 OCO-2 MIP NCE estimates are combined with bottom-up estimates of fossil fuel emissions and lateral carbon fluxes to estimate changes in terrestrial carbon stocks, which are impacted by anthropogenic and natural drivers. These flux and stock change estimates are reported annually (2015-2020) as both a global 1gg×g1g gridded dataset and a country-level dataset and are available for download from the Committee on Earth Observation Satellites\u27 (CEOS) website: 10.48588/npf6-sw92 . Across the v10 OCO-2 MIP experiments, we obtain increases in the ensemble median terrestrial carbon stocks of 3.29-4.58gPgCO2yr-1 (0.90-1.25gPgCyr-1). This is a result of broad increases in terrestrial carbon stocks across the northern extratropics, while the tropics generally have stock losses but with considerable regional variability and differences between v10 OCO-2 MIP experiments. We discuss the state of the science for tracking emissions and removals using top-down methods, including current limitations and future developments towards top-down monitoring and verification systems

Estimating global and North American methane emissions with high spatial resolution using GOSAT satellite data

We use 2009-2011 space-borne methane observations from the Greenhouse Gases Observing SATellite (GOSAT) to estimate global and North American methane emissions with 4° x 5° and up to 50 km x 50 km spatial resolution, respectively. GEOS-Chem and GOSAT data are first evaluated with atmospheric methane observations from surface and tower networks (NOAA/ESRL, TCCON) and aircraft (NOAA/ESRL, HIPPO), using the GEOS-Chem chemical transport model as a platform to facilitate comparison of GOSAT with in situ data. This identifies a high-latitude bias between the GOSAT data and GEOS-Chem that we correct via quadratic regression. Our global adjoint-based inversion yields a total methane source of 539 Tg a−1 with some important regional corrections to the EDGARv4.2 inventory used as a prior. Results serve as dynamic boundary conditions for an analytical inversion of North American methane emissions using radial basis functions to achieve high resolution of large sources and provide error characterization. We infer a US anthropogenic methane source of 40.2-42.7 Tg a−1, as compared to 24.9-27.0 Tg a−1 in the EDGAR and EPA bottom-up inventories, and 30.0-44.5 Tg a−1 in recent inverse studies. Our estimate is supported by independent surface and aircraft data and by previous inverse studies for California. We find that the emissions are highest in the southern-central US, the Central Valley of California, and Florida wetlands; large isolated point sources such as the US Four Corners also contribute. Using prior information on source locations, we attribute 29-44 % of US anthropogenic methane emissions to livestock, 22-31 % to oil/gas, 20 % to landfills/wastewater, and 11-15 % to coal. Wetlands contribute an additional 9.0-10.1 Tg a−1