scholarly journals Counts-in-cells of subhaloes in the IllustrisTNG simulations: the role of baryonic physics

2021 ◽  
Author(s):  
Christine C Dantas
Keyword(s):  
Probability Distribution Function ◽  
Equilibrium Distribution ◽  
Negative Binomial ◽  
Matter Density ◽  
Quasi Equilibrium ◽  
Density Range ◽  
Time Dependencies ◽  
Best Fit ◽  
In Cells

Abstract We present an analysis of the Counts-in-Cells (CiC) statistics of subhaloes in the publicly available IllustrisTNG cosmological simulations (TNG100-1, TNG100-3 and TNG300-3), considering their full and dark-only versions, in redshifts ranging from z = 0 to z = 5, and different cell sizes. We evaluated two CiC models: the gravitational quasi-equilibrium distribution (GQED) and the negative binomial distribution (NBD), both presenting good fits, with small detectable differences in the presence of baryons. Scaling and time dependencies of the best-fit parameters showed similar trends compared with the literature. We derived a matter density-in-cells probability distribution function (PDF), associated with the GQED, which was compared to the PDF proposed by Uhlemann et al., for the IllustrisTNG 100-3-Dark run at z = 0. Our results indicate that the simplest gravithermodynamical assumptions of the GQED model hold in the presence of baryonic dissipation. Interestingly, the smoothed (density-in-cells) version of the GQED is also adequate for describing the dark matter one-point statistics of subhaloes and converges, to subpercentage levels (for an interval of parameters), to the Uhlemann et al. PDF in the high density range.

scholarly journals Clustering of hotspots in the cosmic microwave background

2019 ◽  
Vol 206 ◽  
pp. 09017
Author(s):  
En Zuo Joel Low ◽  
Abel Yang
Keyword(s):  
Cosmic Microwave Background ◽  
Galaxy Formation ◽  
Equilibrium Distribution ◽  
Negative Binomial ◽  
Clustering Algorithms ◽  
Quasi Equilibrium ◽  
Microwave Background ◽  
Temperature Maps ◽  
Recombination Epoch ◽  
Frequency Temperature

The physics behind the origin and composition of the Cosmic Microwave Background (CMB) is a well-established topic in the field of Cosmology. Literature on CMB anisotropies reveal consistency with Gaussianity [1], but these were conducted on full multi-frequency temperature maps. In this thesis, we utilise clustering algorithms to specifically conduct statistical analyses on the distribution of hotspots in the CMB. We describe a series of data processing and clustering methodologies conducted, with results that conclusively show that the counts-in-cells distribution of hotspots in the CMB does not follow a Poisson distribution. Rather, the distribution exhibits a much closer fit to both the Negative Binomial Distribution (NBD) and the Gravitational Quasi-Equilibrium Distribution (GQED). From this result, we conclude that structure likely existed in the early universe, from the period of the recombination Epoch, possibly opening new insights in the field of galaxy formation.

scholarly journals Is area deprivation associated with greater impacts of COVID-19 in care homes across England? A preliminary analysis of COVID-19 outbreaks and deaths

2021 ◽  
pp. jech-2020-215039 ◽  
Author(s):  
Anders Malthe Bach-Mortensen ◽  
Michelle Degli Esposti
Keyword(s):  
Negative Binomial ◽  
Care Home ◽  
Negative Binomial Regression ◽  
Population Characteristics ◽  
Care Homes ◽  
Future Research ◽  
Area Deprivation ◽  
Binomial Regression ◽  
Index Of Multiple Deprivation

IntroductionThe COVID-19 pandemic has disproportionately impacted care homes and vulnerable populations, exacerbating existing health inequalities. However, the role of area deprivation in shaping the impacts of COVID-19 in care homes is poorly understood. We examine whether area deprivation is linked to higher rates of COVID-19 outbreaks and deaths among care home residents across upper tier local authorities in England (n=149).MethodsWe constructed a novel dataset from publicly available data. Using negative binomial regression models, we analysed the associations between area deprivation (Income Deprivation Affecting Older People Index (IDAOPI) and Index of Multiple Deprivation (IMD) extent) as the exposure and COVID-19 outbreaks, COVID-19-related deaths and all-cause deaths among care home residents as three separate outcomes—adjusting for population characteristics (size, age composition, ethnicity).ResultsCOVID-19 outbreaks in care homes did not vary by area deprivation. However, COVID-19-related deaths were more common in the most deprived quartiles of IDAOPI (incidence rate ratio (IRR): 1.23, 95% CI 1.04 to 1.47) and IMD extent (IRR: 1.16, 95% CI 1.00 to 1.34), compared with the least deprived quartiles.DiscussionThese findings suggest that area deprivation is a key risk factor in COVID-19 deaths among care home residents. Future research should look to replicate these results when more complete data become available.

scholarly journals Dark matter candidates in a type-II radiative neutrino mass model

2021 ◽  
Vol 2021 (6) ◽  
Author(s):  
Roberto A. Lineros ◽  
Mathias Pierre
Keyword(s):  
Dark Matter ◽  
Neutral Particle ◽  
Matter Density ◽  
Indirect Detection ◽  
Dark Matter Candidate ◽  
Neutrino Masses ◽  
Type Ii ◽  
Mass Model ◽  
Direct And Indirect Detection

Abstract We explore the connection between Dark Matter and neutrinos in a model inspired by radiative Type-II seessaw and scotogenic scenarios. In our model, we introduce new electroweakly charged states (scalars and a vector-like fermion) and impose a discrete ℤ2 symmetry. Neutrino masses are generated at the loop level and the lightest ℤ2-odd neutral particle is stable and it can play the role of a Dark Matter candidate. We perform a numerical analysis of the model showing that neutrino masses and flavour structure can be reproduced in addition to the correct dark matter density, with viable DM masses from 700 GeV to 30 TeV. We explore direct and indirect detection signatures and show interesting detection prospects by CTA, Darwin and KM3Net and highlight the complementarity between these observables.

scholarly journals 5-LO-derived LTB4 plays a key role in MCP-1 expression in HMGB1-exposed VSMCs via a BLTR1 signaling axis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jong Min Choi ◽  
Seung Eun Baek ◽  
Ji On Kim ◽  
Eun Yeong Jeon ◽  
Eun Jeong Jang ◽  
...  
Keyword(s):  
Tissue Injury ◽  
Vascular Inflammation ◽  
High Mobility ◽  
Leukotriene B4 ◽  
Monocyte Chemoattractant Protein 1 ◽  
Signaling Axis ◽  
Cellular Source ◽  
Leukotriene Receptor ◽  
In Cells

AbstractMonocyte chemoattractant protein-1 (MCP-1) plays an important role in initiating vascular inflammation; however, its cellular source in the injured vasculatures is unclear. Given the importance of high mobility group box 1 (HMGB1) in tissue injury, we investigated the role of vascular smooth muscle cells (VSMCs) in MCP-1 production in response to HMGB1. In primary cultured rat aortic VSMCs stimulated with HMGB1, the expression of MCP-1 and 5-lipoxygenase (LO) was increased. The increased MCP-1 expression in HMGB1 (30 ng/ml)-stimulated cells was significantly attenuated in 5-LO-deficient cells as well as in cells treated with zileuton, a 5-LO inhibitor. Likewise, MCP-1 expression and production were also increased in cells stimulated with exogenous leukotriene B4 (LTB4), but not exogenous LTC4. LTB4-induced MCP-1 expression was attenuated in cells treated with U75302, a LTB4 receptor 1 (BLTR1) inhibitor as well as in BLTR1-deficient cells, but not in 5-LO-deficient cells. Moreover, HMGB1-induced MCP-1 expression was attenuated in BLTR1-deficient cells or by treatment with a BLTR1 inhibitor, but not other leukotriene receptor inhibitors. In contrast to MCP-1 expression in response to LTB4, the increased MCP-1 production in HMGB1-stimulated VSMC was markedly attenuated in 5-LO-deficient cells, indicating a pivotal role of LTB4-BLTR1 signaling in MCP-1 expression in VSMCs. Taken together, 5-LO-derived LTB4 plays a key role in MCP-1 expression in HMGB1-exposed VSMCs via BLTR1 signaling, suggesting the LTB4-BLTR1 signaling axis as a potential therapeutic target for vascular inflammation in the injured vasculatures.

scholarly journals Glycans in autophagy, endocytosis and lysosomal functions

2021 ◽  
Author(s):  
Fulvio Reggiori ◽  
Hans-Joachim Gabius ◽  
Massimo Aureli ◽  
Winfried Römer ◽  
Sandro Sonnino ◽  
...  
Keyword(s):  
Sugar Code ◽  
Endogenous Lectins ◽  
Biological Aspects ◽  
Molecular Signals ◽  
Lysosomal Proteins ◽  
In Cells

AbstractGlycans have been shown to function as versatile molecular signals in cells. This prompted us to look at their roles in endocytosis, endolysosomal system and autophagy. We start by introducing the cell biological aspects of these pathways, the concept of the sugar code, and provide an overview on the role of glycans in the targeting of lysosomal proteins and in lysosomal functions. Moreover, we review evidence on the regulation of endocytosis and autophagy by glycans. Finally, we discuss the emerging concept that cytosolic exposure of luminal glycans, and their detection by endogenous lectins, provides a mechanism for the surveillance of the integrity of the endolysosomal compartments, and serves their eventual repair or disposal.

scholarly journals GLM-Based Flexible Monitoring Methods: An Application to Real-Time Highway Safety Surveillance

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 362
Author(s):  
Arshad Jamal ◽  
Tahir Mahmood ◽  
Muhamad Riaz ◽  
Hassan M. Al-Ahmadi
Keyword(s):  
Real Time ◽  
Control Charts ◽  
Negative Binomial ◽  
Highway Safety ◽  
Monitoring Methods ◽  
Count Data Models ◽  
Crash Data ◽  
Safety Surveillance ◽  
Study Results ◽  
Best Fit

Statistical modeling of historical crash data can provide essential insights to safety managers for proactive highway safety management. While numerous studies have contributed to the advancement from the statistical methodological front, minimal research efforts have been dedicated to real-time monitoring of highway safety situations. This study advocates the use of statistical monitoring methods for real-time highway safety surveillance using three years of crash data for rural highways in Saudi Arabia. First, three well-known count data models (Poisson, negative binomial, and Conway–Maxwell–Poisson) are applied to identify the best fit model for the number of crashes. Conway–Maxwell–Poisson was identified as the best fit model, which was used to find the significant explanatory variables for the number of crashes. The results revealed that the road type and road surface conditions significantly contribute to the number of crashes. From the perspective of real-time highway safety monitoring, generalized linear model (GLM)-based exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) control charts are proposed using the randomized quantile residuals and deviance residuals of Conway–Maxwell (COM)–Poisson regression. A detailed simulation-based study is designed for predictive performance evaluation of the proposed control charts with existing counterparts (i.e., Shewhart charts) in terms of the run-length properties. The study results showed that the EWMA type control charts have better detection ability compared with the CUSUM type and Shewhart control charts under small and/or moderate shift sizes. Finally, the proposed monitoring methods are successfully implemented on actual traffic crash data to highlight the efficacy of the proposed methods. The outcome of this study could provide the analysts with insights to plan sound policy recommendations for achieving desired safety goals.

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