The slicing dependence of non-spherically symmetric quasi-local horizons in Vaidya Spacetimes

It is well known that quasi-local black hole horizons depend on the choice of a time coordinate in a spacetime. This has implications for notions such as the surface of the black hole and also on quasi-local physical quantities such as horizon measures of mass and angular momentum. In this paper, we compare different horizons on non-spherically symmetric slicings of Vaidya spacetimes. The spacetimes we investigate include both accreting and evaporating black holes. For some simple choices of the Vaidya mass function function corresponding to collapse of a hollow shell, we compare the area for the numerically found axisymmetric trapping horizons with the area of the spherically symmetric trapping horizon and event horizon. We find that as expected, both the location and area are dependent on the choice of foliation. However, the area variation is not large, of order $0.035\%$ for a slowly evolving horizon with $\dot{m}=0.02$. We also calculate analytically the difference in area between the spherically symmetric quasi-local horizon and event horizon for a slowly accreting black hole. We find that the difference can be many orders of magnitude larger than the Planck area for sufficiently large black holes.Comment: 10 pages, 5 figures, corrected minor typo

Pea-barley intercrop N dynamics in farmers fields

Knowledge about crop performances in farmers’ fields provides a link between on-farm practice and re-search. Thereby scientists may improve their ability to understand and suggest solutions for the problems facing those who have the responsibility of making sound agricultural decisions. Nitrogen (N) availability is known to be highly heterogeneous in terrestrial plant communities (Stevenson and van Kessel, 1997), a heterogeneity that in natural systems is often associated with variation in the distri-bution of plant species. In intercropping systems the relative proportion of component crops is influenced by the distribution of growth factors such as N in both time and space (Jensen, 1996). In pea-barley intercrops, an increase in the N supply promotes the growth of barley thereby decreasing the N accumulation of pea and giving rise to changes in the relative proportions of the intercropped components (Jensen, 1996). The pres-sure of weeds may, however, significantly change the dynamics in intercrops (Hauggaard-Nielsen et al., 2001). Data from farmers’ fields may provide direct, spatially explicit information for evaluating the poten-tials of improving the utilisation of field variability by intercrops

Lung Segmentation from Chest X-rays using Variational Data Imputation

Pulmonary opacification is the inflammation in the lungs caused by many respiratory ailments, including the novel corona virus disease 2019 (COVID-19). Chest X-rays (CXRs) with such opacifications render regions of lungs imperceptible, making it difficult to perform automated image analysis on them. In this work, we focus on segmenting lungs from such abnormal CXRs as part of a pipeline aimed at automated risk scoring of COVID-19 from CXRs. We treat the high opacity regions as missing data and present a modified CNN-based image segmentation network that utilizes a deep generative model for data imputation. We train this model on normal CXRs with extensive data augmentation and demonstrate the usefulness of this model to extend to cases with extreme abnormalities.Comment: Accepted to be presented at the first Workshop on the Art of Learning with Missing Values (Artemiss) hosted by the 37th International Conference on Machine Learning (ICML). Source code, training data and the trained models are available here: https://github.com/raghavian/lungVAE

Generation of spinocerebellar ataxia type 2 patient-derived iPSC line H271

AbstractSpinocerebellar ataxia type 2 (SCA2) is a neurodegenerative disease primarily affecting the cerebellum. Very little is known about the molecular mechanisms underlying the disease and, to date, no cure or treatment is available. Here, we demonstrate the generation of an induced pluripotent stem cell (iPSC) line of a SCA2 patient. The selected clone has been proven to be a bona fide iPSC line, which retains a normal karyotype. Due to its differentiation potential into neurons, this iPSC line will be a valuable tool in studying a disease-specific phenotype of SCA2