Dusty Donuts: Modeling the Reverberation Response of the Circumnuclear Dusty Torus Emission in AGN

The obscuring circumnuclear torus of dusty molecular gas is one of the major components of AGN (active galactic nuclei), yet its size, composition, and structure are not well understood. These properties can be studied by analyzing the temporal variations of the infrared (IR) dust emission from the torus in response to variations in the AGN continuum luminosity; a technique known as reverberation mapping. In a recent international campaign 12 AGN were monitored using the Spitzer Space Telescope and several ground-based telescopes, providing a unique set of well-sampled mid-IR and optical light curves which are required in order to determine the approximate sizes of the tori in these AGN. To help extract structural information contained in the data a computer model, TORMAC, has been developed that simulates the reverberation response of the clumpy torus emission. Given an input optical light curve, the code computes the emission of a 3D ensemble of dust clouds as a function of time at selected IR wavelengths, taking into account light travel delays. A large library of torus reverberation response simulations has been constructed, to investigate the effects of various geometrical and structural properties such as inclination, cloud distribution, disk half-opening angle, and radial depth. The effects of dust cloud orientation, cloud optical depth, anisotropy of the illuminating AGN radiation field, dust cloud shadowing, and cloud occultation are also explored in detail. TORMAC was also used to generate synthetic IR light curves for the Seyfert 1 galaxy, NGC 6418, using the observed optical light curve as the input, to investigate how the torus and dust cloud properties incorporated in the code affect the results obtained from reverberation mapping. This dissertation presents the most comprehensive investigation to date showing that radiative transfer effects within the torus and anisotropic illumination of the torus can strongly influence the torus IR response at different wavelengths, and should be accounted for when interpreting reverberation mapping data. TORMAC provides a powerful modeling tool that can generate simulated IR light curves for direct comparison to observations. As many types of astronomical sources are both variable and embedded in, or surrounded, by dust, TORMAC also has applications for dust reverberation studies well beyond the AGN observed in the Spitzer monitoring campaign

Genotypes of kappa-casein gen in creole cattle of Bambamarca district (Cajamarca, Peru)

El presente estudio tuvo como objetivo determinar la frecuencia alélica y genotípica del gen kappa-caseína (κ-CN) en ganado bovino criollo. Se recolectaron 48 muestras de sangre de bovinos de nueve centros poblados del distrito de Bambamarca (Cajamarca, Perú). Se extrajo el ADN y la genotipificación se realizó mediante análisis de RFLP-PCR del gen κ-CN. Las frecuencias genotípicas encontradas fueron de 0.56, 0.27 y 0.17 para los genotipos AB, AA y BB, respectivamente, en tanto que las frecuencias alélicas resultaron ser de 0.552 y 0.448 para los alelos A y B, respectivamente. Se concluye que los animales evaluados presentan una baja proporción de individuos con el genotipo deseado BB, genotipo que favorece la producción de queso.The aim of this study was to determine the allelic and genotypic frequency of kappacasein gene (κ-CN) in creole cattle. For this purpose, 48 blood samples were collected from animals in nine villages of the Bambamarca district, Cajamarca, Peru. DNA was extracted and genotyping was performed by PCR-RFLP analysis of κ-CN gene. Genotype frequencies of 0.56, 0.27 and 0.17 for the AB, AA and BB genotypes were found, while the allele frequencies were 0.552 and 0.448 for alleles A and B respectively. It was concluded that the tested group had a low proportion of individuals with the desired BB genotype that favors the production of cheese

Dust Reverberation Mapping and Light-Curve Modelling of Zw229-015

Multiwavelength variability studies of active galactic nuclei (AGN) can be used to probe their inner regions which are not directly resolvable. Dust reverberation mapping (DRM) estimates the size of the dust emitting region by measuring the delays between the infrared (IR) response to variability in the optical light curves. We measure DRM lags of Zw229-015 between optical ground-based and Kepler light curves and concurrent IR Spitzer 3.6 and 4.5 $\mu$m light curves from 2010-2015, finding an overall mean rest-frame lag of 18.3 $\pm$ 4.5 days. Each combination of optical and IR light curve returns lags that are consistent with each other within 1$\sigma$, which implies that the different wavelengths are dominated by the same hot dust emission. The lags measured for Zw229-015 are found to be consistently smaller than predictions using the lag-luminosity relationship. Also, the overall IR response to the optical emission actually depends on the geometry and structure of the dust emitting region as well, so we use Markov chain Monte Carlo (MCMC) modelling to simulate the dust distribution to further estimate these structural and geometrical properties. We find that a large increase in flux between the 2011-2012 observation seasons, which is more dramatic in the IR light curve, is not well simulated by a single dust component. When excluding this increase in flux, the modelling consistently suggests that the dust is distributed in an extended flat disk, and finds a mean inclination angle of 49$^{+3}_{-13}$ degrees.Comment: 32 pages, 32 Figures, 7 Tables; Accepted for publication in MNRA

SNOT-22 in a Control Population

AIM: To assess SNOT-22 and its subscales in a non-rhinosinusitis UK-wide population.  METHODOLOGY/PRINCIPLE: This analysis uses data from the 'Chronic Rhinosinusitis Epidemiology Study' (CRES) which recruited from 30 centres across the UK, and the Socioeconomic Cost of ChrOnic Rhinosinusitis study' (SocCoR); 250 volunteers without CRS were recruited as part of these studies. Study-specific questionnaires including demographics, socioeconomic factors and past medical history as well as SNOT-22 and SF-36 were distributed. The control (non-CRS) population had no self-reported nasal problems in the past, no chronic conditions undergoing active treatment and no hospital admissions in the preceding 12 months.  RESULTS: The mean SNOT-22 total score overall was 12.0. The mean was 10.2 for males with a median of 6.5, and a mean of 13.2 for females with a median of 9. Females scored significantly more highly than males on the sleep/fatigue and facial domains.  CONCLUSIONS: Our data demonstrate differences in SNOT-22 amongst males and females. These data can be used in future studies for comparison with different disease populations with rhinosinusitis. This article is protected by copyright. All rights reserved

Local canopy disturbance as an explanation for long‐term increases in liana abundance

Environmental Biolog

Native diversity buffers against severity of non-native tree invasions

Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species$^{1,2}$. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies$^{3,4}$. Here, leveraging global tree databases$^{5–7}$, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions

The global biogeography of tree leaf form and habit

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17–34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling

Multiwavelength optical and NIR variability analysis of the Blazar PKS 0027-426

Funding: EG and SFH acknowledge support from the Horizon 2020 ERC Starting Grant DUST-IN-THE-WIND (ERC-2015-StG-677117). EG acknowledges support from STFC for funding this PhD. Research leading to these results has received funding from the European Research Council under the European Union 7th Framework Programme (FP7/2007-2013) including ERC grant agreements 240672, 291329, and 306478. We acknowledge support from the Brazilian Instituto Nacional de Ciência Tecnologia (INCT) e-Universe (CNPq grant no. 465376/2014-2).We present multiwavelength spectral and temporal variability analysis of PKS 0027-426 using optical griz observations from Dark Energy Survey between 2013 and 2018 and VEILS Optical Light curves of Extragalactic TransienT Events (VOILETTE) between 2018 and 2019 and near-infrared (NIR) JKs observations from Visible and Infrared Survey Telescope for Astronomy Extragalactic Infrared Legacy Survey (VEILS) between 2017 and 2019. Multiple methods of cross-correlation of each combination of light curve provides measurements of possible lags between optical–optical, optical–NIR, and NIR–NIR emission, for each observation season and for the entire observational period. Inter-band time lag measurements consistently suggest either simultaneous emission or delays between emission regions on time-scales smaller than the cadences of observations. The colour–magnitude relation between each combination of filters was also studied to determine the spectral behaviour of PKS 0027-426. Our results demonstrate complex colour behaviour that changes between bluer when brighter, stable when brighter, and redder when brighter trends over different time-scales and using different combinations of optical filters. Additional analysis of the optical spectra is performed to provide further understanding of this complex spectral behaviour.Publisher PDFPeer reviewe