Organisatsioonide valmisolek ja vajadused edukaks ühinemiseks Pärnu Täiskasvanute Gümnaasiumi ja Pärnumaa Kutsehariduskeskuse näitel

https://www.ester.ee/record=b5458486*es

Constraints on the Ultra-High Energy Neutrino Flux from Gamma-Ray Bursts from a Prototype Station of the Askaryan Radio Array

We report on a search for ultra-high-energy (UHE) neutrinos from gamma-ray bursts (GRBs) in the data set collected by the Testbed station of the Askaryan Radio Array (ARA) in 2011 and 2012. From 57 selected GRBs, we observed no events that survive our cuts, which is consistent with 0.12 expected background events. Using NeuCosmA as a numerical GRB reference emission model, we estimate upper limits on the prompt UHE GRB neutrino fluence and quasi-diffuse flux from $10^{7}$ to $10^{10}$ GeV. This is the first limit on the prompt UHE GRB neutrino quasi-diffuse flux above $10^{7}$ GeV.Comment: 14 pages, 8 figures, Published in Astroparticle Physics Journa

First Constraints on the Ultra-High Energy Neutrino Flux from a Prototype Station of the Askaryan Radio Array

The Askaryan Radio Array (ARA) is an ultra-high energy ($>10^{17}$ eV) cosmic neutrino detector in phased construction near the South Pole. ARA searches for radio Cherenkov emission from particle cascades induced by neutrino interactions in the ice using radio frequency antennas ($\sim150-800$ MHz) deployed at a design depth of 200 m in the Antarctic ice. A prototype ARA Testbed station was deployed at $\sim30$ m depth in the 2010-2011 season and the first three full ARA stations were deployed in the 2011-2012 and 2012-2013 seasons. We present the first neutrino search with ARA using data taken in 2011 and 2012 with the ARA Testbed and the resulting constraints on the neutrino flux from $10^{17}-10^{21}$ eV.Comment: 26 pages, 15 figures. Since first revision, added section on systematic uncertainties, updated limits and uncertainty band with improvements to simulation, added appendix describing ray tracing algorithm. Final revision includes a section on cosmic ray backgrounds. Published in Astropart. Phys.

Performance of two Askaryan Radio Array stations and first results in the search for ultra-high energy neutrinos

Ultra-high energy neutrinos are interesting messenger particles since, if detected, they can transmit exclusive information about ultra-high energy processes in the Universe. These particles, with energies above $10^{16}\mathrm{eV}$, interact very rarely. Therefore, detectors that instrument several gigatons of matter are needed to discover them. The ARA detector is currently being constructed at South Pole. It is designed to use the Askaryan effect, the emission of radio waves from neutrino-induced cascades in the South Pole ice, to detect neutrino interactions at very high energies. With antennas distributed among 37 widely-separated stations in the ice, such interactions can be observed in a volume of several hundred cubic kilometers. Currently 3 deep ARA stations are deployed in the ice of which two have been taking data since the beginning of the year 2013. In this publication, the ARA detector "as-built" and calibrations are described. Furthermore, the data reduction methods used to distinguish the rare radio signals from overwhelming backgrounds of thermal and anthropogenic origin are presented. Using data from only two stations over a short exposure time of 10 months, a neutrino flux limit of $3 \cdot 10^{-6} \mathrm{GeV} / (\mathrm{cm^2 \ s \ sr})$ is calculated for a particle energy of 10^{18}eV, which offers promise for the full ARA detector.Comment: 21 pages, 34 figures, 1 table, includes supplementary materia

Deriving criteria to select arthropod species for laboratory tests to assess the ecological risks from cultivating arthropod-resistant genetically engineered crops

Arthropods form a major part of the biodiversity in agricultural landscapes. Many species are valued because they provide ecosystem services, including biological control, pollination and decomposition, or because they are of conservation interest. Some arthropods reduce crop yield and quality, and conventional chemical pesticides, biological control agents and genetically engineered (GE) crops are used to control them. A common concern addressed in the ecological risk assessment (ERA) that precedes regulatory approval of these pest control methods is their potential to adversely affect valued non-target arthropods (NTAs). A key concept of ERA is early-tier testing using worst-case exposure conditions in the laboratory and surrogate test species that are most likely to reveal an adverse effect. If no adverse effects are observed in those species at high exposures, confidence of negligible ecological risk from the use of the pest control method is increased. From experience with chemical pesticides and biological control agents, an approach is proposed for selecting test species for early-tier ERA of GE arthropod-resistant crops. Surrogate species should be selected that most closely meet three criteria: (i) Potential sensitivity: species should be the most likely to be sensitive to the arthropod-active compound based on the known spectrum of activity of the active ingredient, its mode of action, and the phylogenetic relatedness of the test and target species; (ii) Relevance: species should be representative of valued taxa or functional groups that are most likely to be exposed to the arthropod-active compound in the field; and (iii) Availability and reliability: suitable life-stages of the test species must be obtainable in sufficient quantity and quality, and validated test protocols must be available that allow consistent detection of adverse effects on ecologically relevant parameters. Our proposed approach ensures that the most suitable species are selected for testing and that the resulting data provide the most rigorous test of the risk hypothesis of no adverse effect in order to increase the quality and efficiency of ERAs for cultivation of GE crops

The Minimum Detectable Difference (MDD) Concept for Establishing Trust in Nonsignificant Results: A Critical Review

Current regulatory guidelines for pesticide risk assessment recommend that nonsignificant results should be complemented by the minimum detectable difference (MDD), a statistical indicator that is used to decide whether the experiment could have detected biologically relevant effects. We review the statistical theory of the MDD and perform simulations to understand its properties and error rates. Most importantly, we compare the skill of the MDD in distinguishing between true and false negatives (i.e., type II errors) with 2 alternatives: the minimum detectable effect (MDE), an indicator based on a post hoc power analysis common in medical studies; and confidence intervals (CIs). Our results demonstrate that MDD and MDE only differ in that the power of the MDD depends on the sample size. Moreover, although both MDD and MDE have some skill in distinguishing between false negatives and true absence of an effect, they do not perform as well as using CI upper bounds to establish trust in a nonsignificant result. The reason is that, unlike the CI, neither MDD nor MDE consider the estimated effect size in their calculation. We also show that MDD and MDE are no better than CIs in identifying larger effects among the false negatives. We conclude that, although MDDs are useful, CIs are preferable for deciding whether to treat a nonsignificant test result as a true negative, or for determining an upper bound for an unknown true effect.Environ Toxicol Chem2020;00:1-15. (c) 2020 The Authors.Environmental Toxicology and Chemistrypublished by Wiley Periodicals LLC on behalf of SETAC