Feasibility and performances of compressed-sensing and sparse map-making with Herschel/PACS data

The Herschel Space Observatory of ESA was launched in May 2009 and is in operation since. From its distant orbit around L2 it needs to transmit a huge quantity of information through a very limited bandwidth. This is especially true for the PACS imaging camera which needs to compress its data far more than what can be achieved with lossless compression. This is currently solved by including lossy averaging and rounding steps on board. Recently, a new theory called compressed-sensing emerged from the statistics community. This theory makes use of the sparsity of natural (or astrophysical) images to optimize the acquisition scheme of the data needed to estimate those images. Thus, it can lead to high compression factors. A previous article by Bobin et al. (2008) showed how the new theory could be applied to simulated Herschel/PACS data to solve the compression requirement of the instrument. In this article, we show that compressed-sensing theory can indeed be successfully applied to actual Herschel/PACS data and give significant improvements over the standard pipeline. In order to fully use the redundancy present in the data, we perform full sky map estimation and decompression at the same time, which cannot be done in most other compression methods. We also demonstrate that the various artifacts affecting the data (pink noise, glitches, whose behavior is a priori not well compatible with compressed-sensing) can be handled as well in this new framework. Finally, we make a comparison between the methods from the compressed-sensing scheme and data acquired with the standard compression scheme. We discuss improvements that can be made on ground for the creation of sky maps from the data.Comment: 11 pages, 6 figures, 5 tables, peer-reviewed articl

Janus kinase 2 activation mechanisms revealed by analysis of suppressing mutations

Background: Janus kinases (JAKs; JAK1 to JAK3 and tyrosine kinase 2) mediate cytokine signals in the regulation of hematopoiesis and immunity. JAK2 clinical mutations cause myeloproliferative neoplasms and leukemia, and the mutations strongly concentrate in the regulatory pseudokinase domain Janus kinase homology (JH) 2. Current clinical JAK inhibitors target the tyrosine kinase domain and lack mutation and pathway selectivity. Objective: We sought to characterize mechanisms and differences for pathogenic and cytokine-induced JAK2 activation to enable design of novel selective JAK inhibitors. Methods: We performed a systematic analysis of JAK2 activation requirements using structure-guided mutagenesis, cell-signaling assays, microscopy, and biochemical analysis. Results: Distinct structural requirements were identified for activation of different pathogenic mutations. Specifically, the predominant JAK2 mutation, V617F, is the most sensitive to structural perturbations in multiple JH2 elements (C helix [aC], Src homology 2-JH2 linker, and ATP binding site). In contrast, activation of K539L is resistant to most perturbations. Normal cytokine signaling shows distinct differences in activation requirements: JH2 ATP binding site mutations have only a minor effect on signaling, whereasJH2aCmutations reduce homomeric (JAK2-JAK2) erythropoietin signaling and almost completely abrogate heteromeric (JAK2-JAK1) IFN-gamma signaling, potentially by disrupting a dimerization interface on JH2. Conclusions: These results suggest that therapeutic approaches targeting the JH2 ATP binding site and aC could be effective in inhibiting most pathogenic mutations. JH2 ATP site targeting has the potential for reduced side effects by retaining erythropoietin and IFN-gamma functions. Simultaneously, however, we identified the JH2 aC interface as a potential target for pathway-selective JAK inhibitors in patients with diseases with unmutated JAK2, thus providing new insights into the development of novel pharmacologic interventions.Peer reviewe

Spatiotemporal trends of cutaneous leishmaniasis in Costa Rica.

BACKGROUND: Cutaneous leishmaniasis (CL) remains an important neglected tropical disease in Costa Rica, which has one of the largest burdens of this disease in Latin America. METHODS: We identified district-level hotspots of CL from 2006 to 2017 and conducted temporal analysis to identify where hotspots were increasing across the country. RESULTS: Clear patterns of CL risk were detected, with persistent hotspots located in the Caribbean region, where risk was also found to be increasing over time in some areas. CONCLUSIONS: We identify spatiotemporal hotspots, which may be used in support of the leishmaniasis plan of action for the Americas

A Comparison of Algorithms for the Construction of SZ Cluster Catalogues

We evaluate the construction methodology of an all-sky catalogue of galaxy clusters detected through the Sunyaev-Zel'dovich (SZ) effect. We perform an extensive comparison of twelve algorithms applied to the same detailed simulations of the millimeter and submillimeter sky based on a Planck-like case. We present the results of this "SZ Challenge" in terms of catalogue completeness, purity, astrometric and photometric reconstruction. Our results provide a comparison of a representative sample of SZ detection algorithms and highlight important issues in their application. In our study case, we show that the exact expected number of clusters remains uncertain (about a thousand cluster candidates at |b|> 20 deg with 90% purity) and that it depends on the SZ model and on the detailed sky simulations, and on algorithmic implementation of the detection methods. We also estimate the astrometric precision of the cluster candidates which is found of the order of ~2 arcmins on average, and the photometric uncertainty of order ~30%, depending on flux.Comment: Accepted for publication in A&A: 14 pages, 7 figures. Detailed figures added in Appendi

Direct subthalamic nucleus stimulation influences speech and voice quality in Parkinson's disease patients

BACKGROUND DBS of the subthalamic nucleus (STN) considerably ameliorates cardinal motor symptoms in PD. Reported STN-DBS effects on secondary dysarthric (speech) and dysphonic symptoms (voice), as originating from vocal tract motor dysfunctions, are however inconsistent with rather deleterious outcomes based on post-surgical assessments. OBJECTIVE To parametrically and intra-operatively investigate the effects of deep brain stimulation (DBS) on perceptual and acoustic speech and voice quality in Parkinson's disease (PD) patients. METHODS We performed an assessment of instantaneous intra-operative speech and voice quality changes in PD patients (n = 38) elicited by direct STN stimulations with variations of central stimulation features (depth, laterality, and intensity), separately for each hemisphere. RESULTS First, perceptual assessments across several raters revealed that certain speech and voice symptoms could be improved with STN-DBS, but this seems largely restricted to right STN-DBS. Second, computer-based acoustic analyses of speech and voice features revealed that both left and right STN-DBS could improve dysarthric speech symptoms, but only right STN-DBS can considerably improve dysphonic symptoms, with left STN-DBS being restricted to only affect voice intensity features. Third, several subareas according to stimulation depth and laterality could be identified in the motoric STN proper and close to the associative STN with optimal (and partly suboptimal) stimulation outcomes. Fourth, low-to-medium stimulation intensities showed the most optimal and balanced effects compared to high intensities. CONCLUSIONS STN-DBS can considerably improve both speech and voice quality based on a carefully arranged stimulation regimen along central stimulation features

Component separation methods for the Planck mission

The Planck satellite will map the full sky at nine frequencies from 30 to 857 GHz. The CMB intensity and polarization that are its prime targets are contaminated by foreground emission. The goal of this paper is to compare proposed methods for separating CMB from foregrounds based on their different spectral and spatial characteristics, and to separate the foregrounds into components of different physical origin. A component separation challenge has been organized, based on a set of realistically complex simulations of sky emission. Several methods including those based on internal template subtraction, maximum entropy method, parametric method, spatial and harmonic cross correlation methods, and independent component analysis have been tested. Different methods proved to be effective in cleaning the CMB maps from foreground contamination, in reconstructing maps of diffuse Galactic emissions, and in detecting point sources and thermal Sunyaev-Zeldovich signals. The power spectrum of the residuals is, on the largest scales, four orders of magnitude lower than that of the input Galaxy power spectrum at the foreground minimum. The CMB power spectrum was accurately recovered up to the sixth acoustic peak. The point source detection limit reaches 100 mJy, and about 2300 clusters are detected via the thermal SZ effect on two thirds of the sky. We have found that no single method performs best for all scientific objectives. We foresee that the final component separation pipeline for Planck will involve a combination of methods and iterations between processing steps targeted at different objectives such as diffuse component separation, spectral estimation and compact source extraction.Comment: Matches version accepted by A&A. A version with high resolution figures is available at http://people.sissa.it/~leach/compsepcomp.pd

Spatiotemporal dynamics of vector-borne disease risk across human land-use gradients: examining the role of agriculture, indigenous territories, and protected areas in Costa Rica

Background Costa Rica has undergone significant changes to its forest ecosystems due, in part, to the proliferation of palm oil and other industrial agriculture operations. However, the country also boasts conservation programmes that are among the most robust in the neotropics. Consequently, gradients of anthropogenic to intact ecosystems are found throughout the country. Forest ecosystems may decrease vector-borne disease (VBD) risk by maintaining insect populations in a state of relative equilibrium; however, evidence suggests that intact forests foster biodiversity and may also amplify VBD risk in some circumstances. As a result, focal points of human-vector contact are likely idiosyncratic. This may be particularly true in indigenous territories, which have been shown to play a vital role in maintaining the ecological integrity of conservation areas. Here, we investigate the relationships between anthropogenic landscapes, indigenous territories, protected areas, and risk of VBD. Methods We quantified spatial dynamics of risk across three distinct categories of VBD in Costa Rica: emerging flaviviruses (Zika virus disease and dengue); neglected tropical diseases (cutaneous leishmaniasis and Chagas disease); and a disease nearing eradication (malaria). We collected district-level incidence data from between 2006 and 2017 and used spatial statistics to identify hotspots of elevated risk. We then quantified the associations between anthropogenic landscapes, intact forest ecosystems, and indigenous territories with both the presence and persistence of elevated transmission risk over time using multivariate hurdle models. Findings We detected clear patterns of non-random disease risk across each of the three categories of VBD. Compared with protected areas, districts with higher proportions of human-altered landscapes, particularly agricultural intensification, were at higher risk for VBD across all categories. Districts with the highest proportion of crop cover, compared with the lowest proportion, were significantly associated with the presence of hotspots for Zika virus disease (OR 15·19 [95% CI 6·19–37·26]), dengue (13·00 [7·24–23·35]), leishmaniasis (4·46 [1·18–16·84]), Chagas disease (3·09 [1·47–6·49]), and malaria (8·40 [3·56–19·83]). Interpretation A set of spatial epidemiology tools within a planetary health framework allowed for a refined understanding of the risk of VBD of global public health significance in a biodiversity hotspot. Our findings may be used to better guide targeted public health disease surveillance, control, and prevention programmes. Additional research to understand the role that socioeconomic factors play in the variating VBD risk would contribute additional context to these findings, as these factors are often also spatially associated

Super-long Anabiosis of Ancient Microorganisms in Ice and Terrestrial Models for Development of Methods to Search for Life on Mars, Europa and other Planetary Bodies

Successful missions to Mars, Europe and other bodies of the Solar system have created a prerequisite to search for extraterrestrial life. The first attempts of microbial life detection on the Martian surface by the Viking landed missions gave no biological results. Microbiological investigations of the Martian subsurface ground ice layers seem to be more promising. It is well substantiated to consider the Antarctic ice sheet and the Antarctic and Arctic permafrost as terrestrial analogues of Martian habitats. The results of our long-standing microbiological studies of the Antarctic ice would provide the basis for detection of viable microbial cells on Mars. Our microbiological investigations of the deepest and thus most ancient strata of the Antarctic ice sheet for the first time gave evidence for the natural phenomenon of long-term anabiosis (preservation of viability and vitality for millennia years). A combination of classical microbiological methods, epifluorescence microscopy, SEM, TEM, molecular diagnostics, radioisotope labeling and other techniques made it possible for us to obtain convincing proof of the presence of pro- and eukaryotes in the Antarctic ice sheet. In this communication, we will review and discuss some critical issues related to the detection of viable microorganisms in cold terrestrial environments with regard to future searches for microbial life and/or its biological signatures on extraterrestrial objects

CHEX-MATE: A non-parametric deep learning technique to deproject and deconvolve galaxy cluster X-ray temperature profiles

Temperature profiles of the hot galaxy cluster intracluster medium (ICM) have a complex non-linear structure that traditional parametric modelling may fail to fully approximate. For this study, we made use of neural networks, for the first time, to construct a data-driven non-parametric model of ICM temperature profiles. A new deconvolution algorithm was then introduced to uncover the true (3D) temperature profiles from the observed projected (2D) temperature profiles. An auto-encoder-inspired neural network was first trained by learning a non-linear interpolatory scheme to build the underlying model of 3D temperature profiles in the radial range of [0.02-2] R$_{500}$, using a sparse set of hydrodynamical simulations from the THREE HUNDRED PROJECT. A deconvolution algorithm using a learning-based regularisation scheme was then developed. The model was tested using high and low resolution input temperature profiles, such as those expected from simulations and observations, respectively. We find that the proposed deconvolution and deprojection algorithm is robust with respect to the quality of the data, the morphology of the cluster, and the deprojection scheme used. The algorithm can recover unbiased 3D radial temperature profiles with a precision of around 5\% over most of the fitting range. We apply the method to the first sample of temperature profiles obtained with XMM{\it -Newton} for the CHEX-MATE project and compared it to parametric deprojection and deconvolution techniques. Our work sets the stage for future studies that focus on the deconvolution of the thermal profiles (temperature, density, pressure) of the ICM and the dark matter profiles in galaxy clusters, using deep learning techniques in conjunction with X-ray, Sunyaev Zel'Dovich (SZ) and optical datasets.Comment: 32 pages, 30 figures, 6 tables, Accepted in A&