COSMO-SkyMed potential to detect and monitor Mediterranean maquis fires and regrowth: a pilot study in Capo Figari, Sardinia, Italy

Mediterranean maquis is a complex and widespread ecosystem in the region, intrinsically prone to fire. Many species have developed specific adaptation traits to cope with fire, ensuring resistance and resilience. Due to the recent changes in socio-economy and land uses, fires are more and more frequent in the urban-rural fringe and in the coastlines, both now densely populated. The detection of fires and the monitoring of vegetation regrowth is thus of primary interest for local management and for understanding the ecosystem dynamics and processes, also in the light of the recurrent droughts induced by climate change. Among the main objectives of the COSMO-SkyMed radar constellation mission there is the monitoring of environmental hazards; the very high revisiting time of this mission is optimal for post-hazard response activities. However, very few studies exploited such data for fire and vegetation monitoring. In this research, Cosmo-SkyMed is used in a Mediterranean protected area covered by maquis to detect the burnt area extension and to conduct a mid-term assessment of vegetation regrowth. The positive results obtained in this research highlight the importance of the very high-resolution continuous acquisitions and the multi-polarization information provided by COSMO-SkyMed for monitoring fire impacts on vegetation

Aboveground forest biomass estimation with Landsat and LiDAR data and uncertainty analysis of the estimates.

Landsat Thematic mapper (TM) image has long been the dominate data source, and recently LiDAR has offered an important new structural data stream for forest biomass estimations. On the other hand, forest biomass uncertainty analysis research has only recently obtained sufficient attention due to the difficulty in collecting reference data. This paper provides a brief overview of current forest biomass estimation methods using both TM and LiDAR data. A case study is then presented that demonstrates the forest biomass estimation methods and uncertainty analysis. Results indicate that Landsat TM data can provide adequate biomass estimates for secondary succession but are not suitable for mature forest biomass estimates due to data saturation problems. LiDAR can overcome TM?s shortcoming providing better biomass estimation performance but has not been extensively applied in practice due to data availability constraints. The uncertainty analysis indicates that various sources affect the performance of forest biomass/carbon estimation. With that said, the clear dominate sources of uncertainty are the variation of input sample plot data and data saturation problem related to optical sensors. A possible solution to increasing the confidence in forest biomass estimates is to integrate the strengths of multisensor data

Status of the X17 search in Montreal

At the Montreal Tandem accelerator, an experiment is being set up to measure internal pair creation from the decay of nuclear excited states using a multiwire proportional chamber and scintillator bars surrounding it from the DAPHNE experiment. The acceptance covers a solid angle of nearly 4$\pi$. Preamplifiers and the data acquisition hardware have been designed and tested. The water-cooled $^7$LiF target, mounted on an Al foil is in a thin carbon fiber section of the beamline. The experiment will focus at first on a measurement of the internal pair creation from the 18.15 MeV state of $^8$Be. Assuming the ATOMKI evaluation of the electron-pair production rate from X17, a Geant4 simulation predicts observation of a clear signal after about two weeks of data taking with a 2 $\mu$A proton beam. The IPC measurement could eventually be extended to the giant dipole resonance of $^8$Be, as well as to other nuclei, in particular to $^{10}$B.Comment: 5 pages, 4 figures, Proceedings contribution, TRIUMF Ariel Workshop, May 25-27 202

LD Hub:a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis

Motivation: LD score regression is a reliable and efficient method of using genome-wide association study (GWAS) summary-level results data to estimate the SNP heritability of complex traits and diseases, partition this heritability into functional categories, and estimate the genetic correlation between different phenotypes. Because the method relies on summary level results data, LD score regression is computationally tractable even for very large sample sizes. However, publicly available GWAS summary-level data are typically stored in different databases and have different formats, making it difficult to apply LD score regression to estimate genetic correlations across many different traits simultaneously. Results: In this manuscript, we describe LD Hub - a centralized database of summary-level GWAS results for 173 diseases/traits from different publicly available resources/consortia and a web interface that automates the LD score regression analysis pipeline. To demonstrate functionality and validate our software, we replicated previously reported LD score regression analyses of 49 traits/diseases using LD Hub; and estimated SNP heritability and the genetic correlation across the different phenotypes. We also present new results obtained by uploading a recent atopic dermatitis GWAS meta-analysis to examine the genetic correlation between the condition and other potentially related traits. In response to the growing availability of publicly accessible GWAS summary-level results data, our database and the accompanying web interface will ensure maximal uptake of the LD score regression methodology, provide a useful database for the public dissemination of GWAS results, and provide a method for easily screening hundreds of traits for overlapping genetic aetiologies

Constraints on Low-Mass WIMP Interactions on 19F from PICASSO

Recent results from the PICASSO dark matter search experiment at SNOLAB are reported. These results were obtained using a subset of 10 detectors with a total target mass of 0.72 kg of 19F and an exposure of 114 kgd. The low backgrounds in PICASSO allow recoil energy thresholds as low as 1.7 keV to be obtained which results in an increased sensitivity to interactions from Weakly Interacting Massive Particles (WIMPs) with masses below 10 GeV/c^2. No dark matter signal was found. Best exclusion limits in the spin dependent sector were obtained for WIMP masses of 20 GeV/c^2 with a cross section on protons of sigma_p^SD = 0.032 pb (90% C.L.). In the spin independent sector close to the low mass region of 7 GeV/c2 favoured by CoGeNT and DAMA/LIBRA, cross sections larger than sigma_p^SI = 1.41x10^-4 pb (90% C.L.) are excluded.Comment: 23 pages, 7 figures, to be published in Phys. Lett.

BODE index versus GOLD classification for explaining anxious and depressive symptoms in patients with COPD – a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Anxiety and depression are common and treatable risk factors for re-hospitalisation and death in patients with COPD. The degree of lung function impairment does not sufficiently explain anxiety and depression. The BODE index allows a functional classification of COPD beyond FEV₁. The aim of this cross-sectional study was (1) to test whether the BODE index is superior to the GOLD classification for explaining anxious and depressive symptoms; and (2) to assess which components of the BODE index are associated with these psychological aspects of COPD.</p> <p>Methods</p> <p>COPD was classified according to the GOLD stages based on FEV_1%predictedin 122 stable patients with COPD. An additional four stage classification was constructed based on the quartiles of the BODE index. The hospital anxiety and depression scale was used to assess anxious and depressive symptoms.</p> <p>Results</p> <p>The overall prevalence of anxious and depressive symptoms was 49% and 52%, respectively. The prevalence of anxious symptoms increased with increasing BODE stages but not with increasing GOLD stages. The prevalence of depressive symptoms increased with both increasing GOLD and BODE stages. The BODE index was superior to FEV_1%predictedfor explaining anxious and depressive symptoms. Anxious symptoms were explained by dyspnoea. Depressive symptoms were explained by both dyspnoea and reduced exercise capacity.</p> <p>Conclusion</p> <p>The BODE index is superior to the GOLD classification for explaining anxious and depressive symptoms in COPD patients. These psychological consequences of the disease may play a role in future classification systems of COPD.</p

Determining the bubble nucleation efficiency of low-energy nuclear recoils in superheated C3_3F8_8 dark matter detectors

The bubble nucleation efficiency of low-energy nuclear recoils in superheated liquids plays a crucial role in interpreting results from direct searches for weakly interacting massive particle (WIMP) dark matter. The PICO Collaboration presents the results of the efficiencies for bubble nucleation from carbon and fluorine recoils in superheated C$_3$F$_8$ from calibration data taken with 5 distinct neutron spectra at various thermodynamic thresholds ranging from 2.1 keV to 3.9 keV. Instead of assuming any particular functional forms for the nuclear recoil efficiency, a generalized piecewise linear model is proposed with systematic errors included as nuisance parameters to minimize model-introduced uncertainties. A Markov-Chain Monte-Carlo (MCMC) routine is applied to sample the nuclear recoil efficiency for fluorine and carbon at 2.45 keV and 3.29 keV thermodynamic thresholds simultaneously. The nucleation efficiency for fluorine was found to be $\geq 50\, \%$ for nuclear recoils of 3.3 keV (3.7 keV) at a thermodynamic Seitz threshold of 2.45 keV (3.29 keV), and for carbon the efficiency was found to be $\geq 50\, \%$ for recoils of 10.6 keV (11.1 keV) at a threshold of 2.45 keV (3.29 keV). Simulated data sets are used to calculate a p-value for the fit, confirming that the model used is compatible with the data. The fit paradigm is also assessed for potential systematic biases, which although small, are corrected for. Additional steps are performed to calculate the expected interaction rates of WIMPs in the PICO-60 detector, a requirement for calculating WIMP exclusion limits.Comment: 17 pages, 22 figures, 5 table

Search for inelastic dark matter-nucleus scattering with the PICO-60 CF3_{3}I and C3_{3}F8_{8} bubble chambers

PICO bubble chambers have exceptional sensitivity to inelastic dark matter-nucleus interactions due to a combination of their extended nuclear recoil energy detection window from a few keV to $O$(100 keV) or more and the use of iodine as a heavy target. Inelastic dark matter-nucleus scattering is interesting for studying the properties of dark matter, where many theoretical scenarios have been developed. This study reports the results of a search for dark matter inelastic scattering with the PICO-60 bubble chambers. The analysis reported here comprises physics runs from PICO-60 bubble chambers using CF$_{3}$I and C$_{3}$F$_{8}$. The CF$_{3}$I run consisted of 36.8 kg of CF$_{3}$I reaching an exposure of 3415 kg-day operating at thermodynamic thresholds between 7 and 20 keV. The C$_{3}$F$_{8}$ runs consisted of 52 kg of C$_{3}$F$_{8}$ reaching exposures of 1404 kg-day and 1167 kg-day running at thermodynamic thresholds of 2.45 keV and 3.29 keV, respectively. The analysis disfavors various scenarios, in a wide region of parameter space, that provide a feasible explanation of the signal observed by DAMA, assuming an inelastic interaction, considering that the PICO CF$_{3}$I bubble chamber used iodine as the target material.Comment: 7 pages, 3 figure