Spatial and Temporal Association of Outbreaks of H5N1 Influenza Virus Infection in Wild Birds with the 0°C Isotherm

Wild bird movements and aggregations following spells of cold weather may have resulted in the spread of highly pathogenic avian influenza virus (HPAIV) H5N1 in Europe during the winter of 2005–2006. Waterbirds are constrained in winter to areas where bodies of water remain unfrozen in order to feed. On the one hand, waterbirds may choose to winter as close as possible to their breeding grounds in order to conserve energy for subsequent reproduction, and may be displaced by cold fronts. On the other hand, waterbirds may choose to winter in regions where adverse weather conditions are rare, and may be slowed by cold fronts upon their journey back to the breeding grounds, which typically starts before the end of winter. Waterbirds will thus tend to aggregate along cold fronts close to the 0°C isotherm during winter, creating conditions that favour HPAIV H5N1 transmission and spread. We determined that the occurrence of outbreaks of HPAIV H5N1 infection in waterbirds in Europe during the winter of 2005–2006 was associated with temperatures close to 0°C. The analysis suggests a significant spatial and temporal association of outbreaks caused by HPAIV H5N1 in wild birds with maximum surface air temperatures of 0°C–2°C on the day of the outbreaks and the two preceding days. At locations where waterbird census data have been collected since 1990, maximum mallard counts occurred when average and maximum surface air temperatures were 0°C and 3°C, respectively. Overall, the abundance of mallards (Anas platyrhynchos) and common pochards (Aythya ferina) was highest when surface air temperatures were lower than the mean temperatures of the region investigated. The analysis implies that waterbird movements associated with cold weather, and congregation of waterbirds along the 0°C isotherm likely contributed to the spread and geographical distribution of outbreaks of HPAIV H5N1 infection in wild birds in Europe during the winter of 2005–2006

Fast and flexible analysis of direct dark matter search data with machine learning

We present the results from combining machine learning with the profile likelihood fit procedure, using data from the Large Underground Xenon (LUX) dark matter experiment. This approach demonstrates reduction in computation time by a factor of 30 when compared with the previous approach, without loss of performance on real data. We establish its flexibility to capture nonlinear correlations between variables (such as smearing in light and charge signals due to position variation) by achieving equal performance using pulse areas with and without position-corrections applied. Its efficiency and scalability furthermore enables searching for dark matter using additional variables without significant computational burden. We demonstrate this by including a light signal pulse shape variable alongside more traditional inputs, such as light and charge signal strengths. This technique can be exploited by future dark matter experiments to make use of additional information, reduce computational resources needed for signal searches and simulations, and make inclusion of physical nuisance parameters in fits tractable

Simulations of Events for the LUX-ZEPLIN (LZ) Dark Matter Experiment

The LUX-ZEPLIN dark matter search aims to achieve a sensitivity to the WIMP-nucleon spin-independent cross-section down to (1-2) $\times$ $10^{-12}$ pb at a WIMP mass of 40 GeV/$c^2$. This paper describes the simulations framework that, along with radioactivity measurements, was used to support this projection, and also to provide mock data for validating reconstruction and analysis software. Of particular note are the event generators, which allow us to model the background radiation, and the detector response physics used in the production of raw signals, which can be converted into digitized waveforms similar to data from the operational detector. Inclusion of the detector response allows us to process simulated data using the same analysis routines as developed to process the experimental data

Projected sensitivities of the LUX-ZEPLIN experiment to new physics via low-energy electron recoils

LUX-ZEPLIN is a dark matter detector expected to obtain world-leading sensitivity to weakly-interacting massive particles interacting via nuclear recoils with a ∼ 7 -tonne xenon target mass. This paper presents sensitivity projections to several low-energy signals of the complementary electron recoil signal type: 1) an effective neutrino magnetic moment, and 2) an effective neutrino millicharge, both for p p -chain solar neutrinos, 3) an axion flux generated by the Sun, 4) axionlike particles forming the Galactic dark matter, 5) hidden photons, 6) mirror dark matter, and 7) leptophilic dark matter. World-leading sensitivities are expected in each case, a result of the large 5.6 t 1000 d exposure and low expected rate of electron-recoil backgrounds in the < 100     keV energy regime. A consistent signal generation, background model and profile-likelihood analysis framework is used throughout

The LUX-ZEPLIN (LZ) Experiment

We describe the design and assembly of the LUX-ZEPLIN experiment, a direct detection search for cosmic WIMP dark matter particles. The centerpiece of the experiment is a large liquid xenon time projection chamber sensitive to low energy nuclear recoils. Rejection of backgrounds is enhanced by a Xe skin veto detector and by a liquid scintillator Outer Detector loaded with gadolinium for efficient neutron capture and tagging. LZ is located in the Davis Cavern at the 4850' level of the Sanford Underground Research Facility in Lead, South Dakota, USA. We describe the major subsystems of the experiment and its key design features and requirements

Projected sensitivity of the LUX-ZEPLIN experiment to the 0νββ decay of 136Xe

The LUX-ZEPLIN (LZ) experiment will enable a neutrinoless double beta decay search in parallel to the main science goal of discovering dark matter particle interactions. We report the expected LZ sensitivity to ^136Xe neutrinoless double beta decay, taking advantage of the significant (>600 kg) ^136Xe mass contained within the active volume of LZ without isotopic enrichment. After 1000 live-days, the median exclusion sensitivity to the half-life of ^136Xe is projected to be 1.06×10^26 years (90% confidence level), similar to existing constraints. We also report the expected sensitivity of a possible subsequent dedicated exposure using 90% enrichment with ^136Xe at 1.06×10^27 years

Search for Dark Matter and Supersymmetry with a Compressed Mass Spectrum in the Vector Boson Fusion Topology in Proton-Proton Collisions at root s=8 TeV

Peer reviewe

Measurement and interpretation of same-sign W boson pair production in association with two jets in pp collisions at s = 13 TeV with the ATLAS detector

This paper presents the measurement of fducial and diferential cross sections for both the inclusive and electroweak production of a same-sign W-boson pair in association with two jets (W±W±jj) using 139 fb−1 of proton-proton collision data recorded at a centre-of-mass energy of √s = 13 TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed by selecting two same-charge leptons, electron or muon, and at least two jets with large invariant mass and a large rapidity diference. The measured fducial cross sections for electroweak and inclusive W±W±jj production are 2.92 ± 0.22 (stat.) ± 0.19 (syst.)fb and 3.38±0.22 (stat.)±0.19 (syst.)fb, respectively, in agreement with Standard Model predictions. The measurements are used to constrain anomalous quartic gauge couplings by extracting 95% confdence level intervals on dimension-8 operators. A search for doubly charged Higgs bosons H±± that are produced in vector-boson fusion processes and decay into a same-sign W boson pair is performed. The largest deviation from the Standard Model occurs for an H±± mass near 450 GeV, with a global signifcance of 2.5 standard deviations

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis