High-resolution tropical channel model simulations of tropical cyclone climatology and intraseasonal-to-interannual variability

We tailored a tropical channel configuration of the Weather Research and Forecasting (WRF) Model to study tropical cyclone (TC) activity and associated climate variabilities. This tropical channel model (TCM) covers from 308S to 508N at 27-km horizontal resolution, with physics parameterizations carefully selected to achieve more realistic simulations of TCs and large-scale climate mean states. We performed 15-member ensembles of retrospective simulations from 1982 to 2016 hurricane seasons. A thorough comparison with observations demonstrates that the TCM yields significant skills in simulating TC activity climatology and variabilities in each basin, as well as TC physical structures. The correlation of the ensemble averaged accumulated cyclone energy (ACE) with observations in the western North Pacific (WNP), eastern North Pacific (ENP), and North Atlantic (NAT) is 0.80, 0.64, and 0.61, respectively, but is insignificant in the north Indian Ocean (NIO). Moreover, the TCM-simulated modulations of El Niño–Southern Oscillation (ENSO) and the Madden–Julian oscillation (MJO) on the large-scale environment and TC genesis also agree well with observations. To examine the TCM’s potential for seasonal TC prediction, the model is used to forecast the 2017 and 2018 hurricane seasons, using bias-corrected sea surface temperatures (SSTs) from the CFSv2 seasonal prediction results. The TCM accurately predicts the hyperactive 2017 NAT hurricane season and near-normal WNP and ENP hurricane seasons when initialized in May. In addition, the TCM accurately predicts TC activity in the NAT and WNP during the 2018 season, but underpredicts ENP TC activity, in association with a poor ENSO forecast

Selection of tuning parameters in bridge regression models via Bayesian information criterion

We consider the bridge linear regression modeling, which can produce a sparse or non-sparse model. A crucial point in the model building process is the selection of adjusted parameters including a regularization parameter and a tuning parameter in bridge regression models. The choice of the adjusted parameters can be viewed as a model selection and evaluation problem. We propose a model selection criterion for evaluating bridge regression models in terms of Bayesian approach. This selection criterion enables us to select the adjusted parameters objectively. We investigate the effectiveness of our proposed modeling strategy through some numerical examples.Comment: 20 pages, 5 figure

Heterotic Sigma Models with N=2 Space-Time Supersymmetry

We study the non-linear sigma model realization of a heterotic vacuum with N=2 space-time supersymmetry. We examine the requirements of (0,2) + (0,4) world-sheet supersymmetry and show that a geometric vacuum must be described by a principal two-torus bundle over a K3 manifold.Comment: 20 pages, uses xy-pic; v3: typos corrected, reference added, discussion of constraints on Hermitian form modifie

Chinese Social Media Reaction to Information about 42 Notifiable Infectious Diseases

This study aimed to identify what information triggered social media users' responses regarding infectious diseases. Chinese microblogs in 2012 regarding 42 infectious diseases were obtained through a keyword search in the Weiboscope database. Qualitative content analysis was performed for the posts pertinent to each keyword of the day of the year with the highest daily count. Similar posts were grouped and coded. We identified five categories of information that increased microblog traffic pertaining to infectious diseases: news of an outbreak or a case; health education / information; alternative health information / Traditional Chinese Medicine; commercial advertisement / entertainment; and social issues. News unrelated to the specified infectious diseases also led to elevated microblog traffic. Our study showcases the diverse contexts from which increased social media traffic occur. Our results will facilitate better health communication as causes underlying increased social media traffic are revealed.published_or_final_versio

An inhibitory pull-push circuit in frontal cortex.

Push-pull is a canonical computation of excitatory cortical circuits. By contrast, we identify a pull-push inhibitory circuit in frontal cortex that originates in vasoactive intestinal polypeptide (VIP)-expressing interneurons. During arousal, VIP cells rapidly and directly inhibit pyramidal neurons; VIP cells also indirectly excite these pyramidal neurons via parallel disinhibition. Thus, arousal exerts a feedback pull-push influence on excitatory neurons-an inversion of the canonical push-pull of feedforward input

New mutations at the imprinted Gnas cluster show gene dosage effects of Gsα in postnatal growth and implicate XLαs in bone and fat metabolism, but not in suckling

The imprinted Gnas cluster is involved in obesity, energy metabolism, feeding behavior, and viability. Relative contribution of paternally expressed proteins XLαs, XLN1, and ALEX or a double dose of maternally expressed Gsα to phenotype has not been established. In this study, we have generated two new mutants (Ex1A-T-CON and Ex1A-T) at the Gnas cluster. Paternal inheritance of Ex1A-T-CON leads to loss of imprinting of Gsα, resulting in preweaning growth retardation followed by catch-up growth. Paternal inheritance of Ex1A-T leads to loss of imprinting of Gsα and loss of expression of XLαs and XLN1. These mice have severe preweaning growth retardation and incomplete catch-up growth. They are fully viable probably because suckling is unimpaired, unlike mutants in which the expression of all the known paternally expressed Gnasxl proteins (XLαs, XLN1 and ALEX) is compromised. We suggest that loss of ALEX is most likely responsible for the suckling defects previously observed. In adults, paternal inheritance of Ex1A-T results in an increased metabolic rate and reductions in fat mass, leptin, and bone mineral density attributable to loss of XLαs. This is, to our knowledge, the first report describing a role for XLαs in bone metabolism. We propose that XLαs is involved in the regulation of bone and adipocyte metabolism

Deciphering interplay between Salmonella invasion effectors

Bacterial pathogens have evolved a specialized type III secretion system (T3SS) to translocate virulence effector proteins directly into eukaryotic target cells. Salmonellae deploy effectors that trigger localized actin reorganization to force their own entry into non-phagocytic host cells. Six effectors (SipC, SipA, SopE/2, SopB, SptP) can individually manipulate actin dynamics at the plasma membrane, which acts as a ‘signaling hub’ during Salmonella invasion. The extent of crosstalk between these spatially coincident effectors remains unknown. Here we describe trans and cis binary entry effector interplay (BENEFIT) screens that systematically examine functional associations between effectors following their delivery into the host cell. The results reveal extensive ordered synergistic and antagonistic relationships and their relative potency, and illuminate an unexpectedly sophisticated signaling network evolved through longstanding pathogen–host interaction

On the Gas Content, Star Formation Efficiency, and Environmental Quenching of Massive Galaxies in Protoclusters at z ≈ 2.0–2.5

We present ALMA Band 6 (ν = 233 GHz, λ = 1.3 mm) continuum observations toward 68 "normal" star-forming galaxies within two Coma-like progenitor structures at z = 2.10 and 2.47, from which ISM masses are derived, providing the largest census of molecular gas mass in overdense environments at these redshifts. Our sample comprises galaxies with a stellar mass range of 1 × 10⁹ M_⊙–4 × 10¹¹ M_⊙ with a mean M_★ ≈ 6 × 10¹⁰ M_⊙. Combining these measurements with multiwavelength observations and spectral energy distribution modeling, we characterize the gas mass fraction and the star formation efficiency, and infer the impact of the environment on galaxies' evolution. Most of our detected galaxies (≳70%) have star formation efficiencies and gas fractions similar to those found for coeval field galaxies and in agreement with the field scaling relations. However, we do find that the protoclusters contain an increased fraction of massive, gas-poor galaxies, with low gas fractions (f_(gas) ≾ 6%–10%) and red rest-frame ultraviolet/optical colors typical of post-starburst and passive galaxies. The relatively high abundance of passive galaxies suggests an accelerated evolution of massive galaxies in protocluster environments. The large fraction of quenched galaxies in these overdense structures also implies that environmental quenching takes place during the early phases of cluster assembly, even before virialization. From our data, we derive a quenching efficiency of ϵ_q ≈ 0.45 and an upper limit on the quenching timescale of τ_q < 1 Gyr

Optimal interdependence between networks for the evolution of cooperation

Recent research has identified interactions between networks as crucial for the outcome of evolutionary games taking place on them. While the consensus is that interdependence does promote cooperation by means of organizational complexity and enhanced reciprocity that is out of reach on isolated networks, we here address the question just how much interdependence there should be. Intuitively, one might assume the more the better. However, we show that in fact only an intermediate density of sufficiently strong interactions between networks warrants an optimal resolution of social dilemmas. This is due to an intricate interplay between the heterogeneity that causes an asymmetric strategy flow because of the additional links between the networks, and the independent formation of cooperative patterns on each individual network. Presented results are robust to variations of the strategy updating rule, the topology of interdependent networks, and the governing social dilemma, thus suggesting a high degree of universality

Aurora kinase A drives the evolution of resistance to third-generation EGFR inhibitors in lung cancer.

Although targeted therapies often elicit profound initial patient responses, these effects are transient due to residual disease leading to acquired resistance. How tumors transition between drug responsiveness, tolerance and resistance, especially in the absence of preexisting subclones, remains unclear. In epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma cells, we demonstrate that residual disease and acquired resistance in response to EGFR inhibitors requires Aurora kinase A (AURKA) activity. Nongenetic resistance through the activation of AURKA by its coactivator TPX2 emerges in response to chronic EGFR inhibition where it mitigates drug-induced apoptosis. Aurora kinase inhibitors suppress this adaptive survival program, increasing the magnitude and duration of EGFR inhibitor response in preclinical models. Treatment-induced activation of AURKA is associated with resistance to EGFR inhibitors in vitro, in vivo and in most individuals with EGFR-mutant lung adenocarcinoma. These findings delineate a molecular path whereby drug resistance emerges from drug-tolerant cells and unveils a synthetic lethal strategy for enhancing responses to EGFR inhibitors by suppressing AURKA-driven residual disease and acquired resistance