Calibration of the SNO+ experiment

The main goal of the SNO+ experiment is to perform a low-background and high-isotope-mass search for neutrinoless double-beta decay, employing 780 tonnes of liquid scintillator loaded with tellurium, in its initial phase at 0.5% by mass for a total mass of 1330 kg of (130)Te. The SNO+ physics program includes also measurements of geo- and reactor neutrinos, supernova and solar neutrinos. Calibrations are an essential component of the SNO+ data-taking and analysis plan. The achievement of the physics goals requires both an extensive and regular calibration. This serves several goals: the measurement of several detector parameters, the validation of the simulation model and the constraint of systematic uncertainties on the reconstruction and particle identification algorithms. SNO+ faces stringent radiopurity requirements which, in turn, largely determine the materials selection, sealing and overall design of both the sources and deployment systems. In fact, to avoid frequent access to the inner volume of the detector, several permanent optical calibration systems have been developed and installed outside that volume. At the same time, the calibration source internal deployment system was re-designed as a fully sealed system, with more stringent material selection, but following the same working principle as the system used in SNO. This poster described the overall SNO+ calibration strategy, discussed the several new and innovative sources, both optical and radioactive, and covered the developments on source deployment systems.Peer Reviewe

Electric Polarizability of Neutral Hadrons from Lattice QCD

By simulating a uniform electric field on a lattice and measuring the change in the rest mass, we calculate the electric polarizability of neutral mesons and baryons using the methods of quenched lattice QCD. Specifically, we measure the electric polarizability coefficient from the quadratic response to the electric field for 10 particles: the vector mesons $\rho^0$ and $K^{*0}$; the octet baryons n, $\Sigma^0$, $\Lambda_{o}^{0}$, $\Lambda_{s}^{0}$, and $\Xi^0$; and the decouplet baryons $\Delta^0$, $\Sigma^{*0}$, and $\Xi^{*0}$. Independent calculations using two fermion actions were done for consistency and comparison purposes. One calculation uses Wilson fermions with a lattice spacing of $a=0.10$fm. The other uses tadpole improved L\"usher-Weiss gauge fields and clover quark action with a lattice spacing $a=0.17$fm. Our results for neutron electric polarizability are compared to experiment.Comment: 25 pages, 20 figure

Posttraumatic Stress Disorder and Community Collective Efficacy following the 2004 Florida Hurricanes

There is a paucity of research investigating the relationship of community-level characteristics such as collective efficacy and posttraumatic stress following disasters. We examine the association of collective efficacy with probable posttraumatic stress disorder and posttraumatic stress disorder symptom severity in Florida public health workers (n = 2249) exposed to the 2004 hurricane season using a multilevel approach. Anonymous questionnaires were distributed electronically to all Florida Department of Health personnel nine months after the 2004 hurricane season. The collected data were used to assess posttraumatic stress disorder and collective efficacy measured at both the individual and zip code levels. The majority of participants were female (80.42%), and ages ranged from 20 to 78 years (median = 49 years); 73.91% were European American, 13.25% were African American, and 8.65% were Hispanic. Using multi-level analysis, our data indicate that higher community-level and individual-level collective efficacy were associated with a lower likelihood of having posttraumatic stress disorder (OR = 0.93, CI = 0.88–0.98; and OR = 0.94, CI = 0.92–0.97, respectively), even after adjusting for individual sociodemographic variables, community socioeconomic characteristic variables, individual injury/damage, and community storm damage. Higher levels of community-level collective efficacy and individual-level collective efficacy were also associated with significantly lower posttraumatic stress disorder symptom severity (b = −0.22, p<0.01; and b = −0.17, p<0.01, respectively), after adjusting for the same covariates. Lower rates of posttraumatic stress disorder are associated with communities with higher collective efficacy. Programs enhancing community collective efficacy may be an important part of prevention practices and possibly lead to a reduction in the rate of posttraumatic stress disorder post-disaster

The Reproducibility of Lists of Differentially Expressed Genes in Microarray Studies

Reproducibility is a fundamental requirement in scientific experiments and clinical contexts. Recent publications raise concerns about the reliability of microarray technology because of the apparent lack of agreement between lists of differentially expressed genes (DEGs). In this study we demonstrate that (1) such discordance may stem from ranking and selecting DEGs solely by statistical significance (P) derived from widely used simple t-tests; (2) when fold change (FC) is used as the ranking criterion, the lists become much more reproducible, especially when fewer genes are selected; and (3) the instability of short DEG lists based on P cutoffs is an expected mathematical consequence of the high variability of the t-values. We recommend the use of FC ranking plus a non-stringent P cutoff as a baseline practice in order to generate more reproducible DEG lists. The FC criterion enhances reproducibility while the P criterion balances sensitivity and specificity

Effects of rapeseed variety and oil extraction method on the content and ileal digestibility of crude protein and amino acids in rapeseed cake and softly processed rapeseed meal fed to broiler chickens

We examined the effects of rapeseed variety and oil extraction method on crude protein (CP) and amino acid (AA) content in rapeseed co-products, and determined their coefficient of apparent (AID) and standardised ileal digestibility (SID) in broiler chickens. Sixteen rapeseed samples were de-oiled; four were cold-pressed producing rapeseed cake (RSC) and twelve were mild processed and hexane-extracted producing soft rapeseed meal (SRSM). One batch of the variety Compass, grown on the same farm, was processed using both methods obtaining Compass RSC and Compass SRSM. DK Cabernet rapeseed variety, grown on three different farms, was used to produce two SRSM batches and one RSC batch. All rapeseed co-products were ground through a 4 mm screen and mixed into semi-synthetic diets at a level of 500 g/kg. Day-old Ross 308 male broilers were fed a commercial diet for 14 days. A total of 96 pairs of birds were then allotted to 1 of 16 dietary treatments (n = 6) and fed a test diet for 8 days. Birds were then culled allowing removal of ileal digesta from Meckel’s diverticulum to the ileal-caecal junction. Digestibility of CP and AA was determined using titanium dioxide as an inert marker. The SRSM samples had an increased content of CP (419–560 g/kg DM) compared to RSC samples (293–340 g/kg DM). Both AID and SID of lysine, and SID of arginine, histidine and threonine were greater in Compass RSC compared to its SRSM counterpart (P 0.05). The SID of lysine was on average 0.03 units greater (P < 0.001) in RSC than in SRSM. The SRSM produced from variety PR46W21 showed similar or greater AID and SID of individual AA than the RSC from four other rapeseed varieties. It is concluded that selection of rapeseed varieties, and extraction method have a potential to deliver high-protein dietary ingredients with a good digestibility value

Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084

Measurement of the 8B solar neutrino flux in SNO+ with very low backgrounds

A measurement of the 8B solar neutrino flux has been made using a 69.2 kt-day dataset acquired with the SNO+ detector during its water commissioning phase. At energies above 6 MeV the dataset is an extremely pure sample of solar neutrino elastic scattering events, owing primarily to the detector’s deep location, allowing an accurate measurement with relatively little exposure. In that energy region the best fit background rate is 0.25+0.09−0.07  events/kt−day, significantly lower than the measured solar neutrino event rate in that energy range, which is 1.03+0.13−0.12  events/kt−day. Also using data below this threshold, down to 5 MeV, fits of the solar neutrino event direction yielded an observed flux of 2.53+0.31−0.28(stat)+0.13−0.10(syst)×106  cm−2 s−1, assuming no neutrino oscillations. This rate is consistent with matter enhanced neutrino oscillations and measurements from other experiments