Consistently Simulating a Wide Range of Atmospheric Scenarios for K2-18b with a Flexible Radiative Transfer Module

The atmospheres of small, potentially rocky exoplanets are expected to cover a diverse range in composition and mass. Studying such objects therefore requires flexible and wide-ranging modeling capabilities. We present in this work the essential development steps that lead to our flexible radiative transfer module, REDFOX, and validate REDFOX for the Solar system planets Earth, Venus and Mars, as well as for steam atmospheres. REDFOX is a k-distribution model using the correlated-k approach with random overlap method for the calculation of opacities used in the $\delta$-two-stream approximation for radiative transfer. Opacity contributions from Rayleigh scattering, UV / visible cross sections and continua can be added selectively. With the improved capabilities of our new model, we calculate various atmospheric scenarios for K2-18b, a super-Earth / sub-Neptune with $\sim$8 M$_\oplus$ orbiting in the temperate zone around an M-star, with recently observed H$_2$O spectral features in the infrared. We model Earth-like, Venus-like, as well as H$_2$-He primary atmospheres of different Solar metallicity and show resulting climates and spectral characteristics, compared to observed data. Our results suggest that K2-18b has an H$_2$-He atmosphere with limited amounts of H$_2$O and CH$_4$. Results do not support the possibility of K2-18b having a water reservoir directly exposed to the atmosphere, which would reduce atmospheric scale heights, hence too the amplitudes of spectral features inconsistent with the observations. We also performed tests for H$_2$-He atmospheres up to 50 times Solar metallicity, all compatible with the observations.Comment: 28 pages, 13 figures, accepted for publication in Ap

Exploring sources of resistance to brown rot in an interspecific almond × peach population

BACKGROUND: Monilinia spp. are responsible for brown rot, one of the most significant stone fruit diseases. Planting resistant cultivars seems a promising alternative, although most commercial cultivars are susceptible to brown rot. The aim of this study was to explore resistance to Monilinia fructicola over two seasons in a backcross one interspecific population between almond ‘Texas’ and peach ‘Earlygold’ (named T1E). RESULTS: ‘Texas’ almond was resistant to brown rot inoculation, whereas peach was highly susceptible. Phenotypic data from the T1E population indicated wide differences in response to M. fructicola. Additionally, several non-wounded individuals exhibited resistance to brown rot. Quantitative trait loci (QTLs) were identified in several linkage groups, but only two proximal QTLs in G4 were detected over both seasons and accounted for 11.3–16.2% of the phenotypic variation. CONCLUSION: Analysis of the progeny allowed the identification of resistant genotypes that could serve as a source of resistance in peach breeding programs. The finding of loci associated with brown rot resistance would shed light on implementing a strategy based on marker-assisted selection (MAS) for introgression of this trait into elite peach materials. New peach cultivars resistant to brown rot may contribute to the implementation of more sustainable crop protection strategies.info:eu-repo/semantics/acceptedVersio

Counting a black hole in Lorentzian product triangulations

We take a step toward a nonperturbative gravitational path integral for black-hole geometries by deriving an expression for the expansion rate of null geodesic congruences in the approach of causal dynamical triangulations. We propose to use the integrated expansion rate in building a quantum horizon finder in the sum over spacetime geometries. It takes the form of a counting formula for various types of discrete building blocks which differ in how they focus and defocus light rays. In the course of the derivation, we introduce the concept of a Lorentzian dynamical triangulation of product type, whose applicability goes beyond that of describing black-hole configurations.Comment: 42 pages, 11 figure

Quest for barley canopy architecture genes in the hortillus population and whealbi germplasm collection

Barley grains are predominantly used for animal feed and malting, and breeding traditionally focused on increase of grain yield by partitioning biomass from straw to grains. The increasing demand for renewable energy sources makes straw, and specially barley straw characterized by the largest content of carbohydrates among the cereals, a valuable product for its potential conversion into biofuels and other products. The BarPLUS project aims at finding genes, alleles and candidate lines related to barley canopy architecture and photosynthesis, to maximize barley biomass and yield (https://barplus.wordpress.com/). In this framework, our research group focuses on identifying genes and alleles controlling tillering, leaf size and leaf angle traits in barley by exploiting both induced and natural allelic variation. Using a forward genetics approach, we screened the HorTILLUS population (Szurman-Zubrzycka et al., 2018) under both field and controlled conditions, identifying 5 mutants with increased tillering and/or erect leaves. After crossing with four reference cultivars, pools of F2 wild-type and mutant plants were selected to map and identify the underlying genes by exome sequencing (Mascher et al., 2014). In parallel, TILLING of the HorTILLUS population identified four lines carrying mutations in the LBO (Lateral branching oxidoreductase) gene involved in tiller number. In order to explore also natural genetic variation, we are taking advantage of the \u2018WHEALBI\u2019 germplasm collection, which includes 403 exome sequenced diverse accessions (BustosKorts et al., 2019): a field trial on a subset of 240 lines (Fiorenzuola d\u2019Arda, Italy) allowed us to conduct a preliminary genome wide association study based on high-throughput phenotyping for leaf angle (PocketPlant3D smartphone app) and quantitative image-analysis for leaf size. Results will be compared with those from a greenhouse experiment on the same 240 accessions to analyze a wide range of morphological traits and identify associated markers and genomic regions

Retrieving the distribution of comet 67P/Churyumov-Gerasimenko surface temperatures for individual Rosetta/VIRTIS-M spectra (pixel) by linear spectral unmixing - Method and first results -

Knowledge of surface temperature and its variations as function of illumination conditions is key for understanding the thermodynamical properties, the chemical properties and the physical structure of the regolith (porosity, roughness) of planets and small bodies in the solar system. The surface temperature can be retrieved from near-infrared spectra at wavelengths where thermal emission becomes non-negligible with respect to the reflected components. At 5 micron, the longest wavelength measured by VIRTIS-M on the Rosetta mission which observed comet 67P/Churyumov-Gerasimenko (67P/C-G), the minimum brightness temperature that can be measured is ~150K (instrumental noise equivalent temperature). The usual technique is to fit a Planck function to each spectrum, providing one temperature per pixel. However, the calculation of a distribution of temperatures per pixel is justified by the fact that the local topography changes at all scales resulting in variable illumination conditions (variable incidence angle and shadow casting) within the area covered by each pixel. This causes a distribution of temperatures which turns out in a distribution of thermal emission contributions. Furthermore, the combination of different thermal emission contributions (the linear combination of several Planck curves) is not a Planck function. Consequently, fitting one Planck function to a spectrum results in retrieving a value for the brightness temperature that is not representative of thermophysical properties of the regolith, because it is not the average of all temperatures in the area covered by that pixel

Business constraints and growth potential of micro and small manufacturing enterprises in Uganda

Ugandan micro and small enterprises (MSEs) still perform poorly. Studies associating poor performance of manufacturers with lack of finance and low investment ignore micro enterprises. Those focusing on MSEs are either exploratory in nature or employ a descriptive analysis, which cannot show the extent to which business constraints explain the performance of MSEs. Thus, this paper tries to examine the extent to which the growth of MSEs is associated with business constraints while controlling for owners’ attributes and firms’ characteristics. The results reveal that MSEs’ growth potential is negatively associated with limited access to productive resources (finance and business development services), high taxes and lack of market access

Type inference in flexible model-driven engineering using classification algorithms

Flexible or bottom-up model-driven engineering (MDE) is an emerging approach to domain and systems modelling. Domain experts, who have detailed domain knowledge, typically lack the technical expertise to transfer this knowledge using traditional MDE tools. Flexible MDE approaches tackle this challenge by promoting the use of simple drawing tools to increase the involvement of domain experts in the language definition process. In such approaches, no metamodel is created upfront, but instead the process starts with the definition of example models that will be used to infer the metamodel. Pre-defined metamodels created by MDE experts may miss important concepts of the domain and thus restrict their expressiveness. However, the lack of a metamodel, that encodes the semantics of conforming models has some drawbacks, among others that of having models with elements that are unintentionally left untyped. In this paper, we propose the use of classification algorithms to help with the inference of such untyped elements. We evaluate the proposed approach in a number of random generated example models from various domains. The correct type prediction varies from 23 to 100% depending on the domain, the proportion of elements that were left untyped and the prediction algorithm used

Non-Linearity in Ecosystem Services: Temporal and Spatial Variability in Coastal Protection

Natural processes tend to vary over time and space, as well as between species. The ecosystem services these natural processes provide are therefore also highly variable. It is often assumed that ecosystem services are provided linearly (unvaryingly, at a steady rate), but natural processes are characterized by thresholds and limiting functions. In this paper, we describe the variability observed in wave attenuation provided by marshes, mangroves, seagrasses, and coral reefs and therefore also in coastal protection. We calculate the economic consequences of assuming coastal protection to be linear. We suggest that, in order to refine ecosystem-based management practices, it is essential that natural variability and cumulative effects be considered in the valuation of ecosystem services