Dipole-interacting Fermionic Dark Matter in positron, antiproton, and gamma-ray channels

Cosmic ray signals from dipole-interacting dark matter annihilation are considered in the positron, antiproton and photon channels. The predicted signals in the positron channel could nicely account for the excess of positron fraction from Fermi LAT, PAMELA, HEAT and AMS-01 experiments for the dark matter mass larger than 100 GeV with a boost (enhancement) factor of 30-80. No excess of antiproton over proton ratio at the experiments also gives a severe restriction for this scenario. With the boost factors, the predicted signals from Galactic halo and signals as mono-energetic gamma-ray lines (monochromatic photons) for the region close to the Galactic center are investigated. The gamma-ray excess of recent tentative analyses based on Fermi LAT data and the potential probe of the monochromatic lines at a planned experiment, AMS-02, are also considered.Comment: Version to be published in PRD(2013), Title changed, text modifie

Learning a Static Analyzer from Data

To be practically useful, modern static analyzers must precisely model the effect of both, statements in the programming language as well as frameworks used by the program under analysis. While important, manually addressing these challenges is difficult for at least two reasons: (i) the effects on the overall analysis can be non-trivial, and (ii) as the size and complexity of modern libraries increase, so is the number of cases the analysis must handle. In this paper we present a new, automated approach for creating static analyzers: instead of manually providing the various inference rules of the analyzer, the key idea is to learn these rules from a dataset of programs. Our method consists of two ingredients: (i) a synthesis algorithm capable of learning a candidate analyzer from a given dataset, and (ii) a counter-example guided learning procedure which generates new programs beyond those in the initial dataset, critical for discovering corner cases and ensuring the learned analysis generalizes to unseen programs. We implemented and instantiated our approach to the task of learning JavaScript static analysis rules for a subset of points-to analysis and for allocation sites analysis. These are challenging yet important problems that have received significant research attention. We show that our approach is effective: our system automatically discovered practical and useful inference rules for many cases that are tricky to manually identify and are missed by state-of-the-art, manually tuned analyzers

Influence of error terms in Bayesian calibration of energy system models

Calibration represents a crucial step in the modelling process to obtain accurate simulation results and quantify uncertainties. We scrutinise the statistical Kennedy & O’Hagan framework, which quantifies different sources of uncertainty in the calibration process, including both model inputs and errors in the model. In specific, we evaluate the influence of error terms on the posterior predictions of calibrated model inputs. We do so by using a simulation model of a heat pump in cooling mode. While posterior values of many parameters concur with the expectations, some parameters appear not to be inferable. This is particularly true for parameters associated with model discrepancy, for which prior knowledge is typically scarce. We reveal the importance of assessing the identifiability of parameters by exploring the dependency of posteriors on the assigned prior knowledge. Analyses with random datasets show that results are overall consistent, which confirms the applicability and reliability of the framework

Overweight, obesity, and colorectal cancer screening: Disparity between men and women

BACKGROUND: To estimate the association between body-mass index (BMI: kg/m(2)) and colorectal cancer (CRC) screening among US adults aged ≥ 50 years. METHODS: Population-based data from the 2001 Behavioral Risk Factor Surveillance Survey. Adults (N = 84,284) aged ≥ 50 years were classified by BMI as normal weight (18.5–<25), overweight (25–<30), obesity class I (30–<35), obesity class II (35–<40), and obesity class III (≥ 40). Interval since most recent screening fecal occult blood test (FOBT): (0 = >1 year since last screening vs. 1 = screened within the past year), and screening sigmoidoscopy (SIG): (0 = > 5 years since last screening vs. 1 = within the past 5 years) were the outcomes. RESULTS: Results differed between men and women. After adjusting for age, health insurance, race, and smoking, we found that, compared to normal weight men, men in the overweight (odds ratio [OR] 1.25, 95% CI = 1.05–1.51) and obesity class I (OR = 1.21, 95% CI = 1.03–1.75) categories were more likely to have obtained a screening SIG within the previous 5 years, while women in the obesity class I (OR = 0.86, 95%CI = 0.78–0.94) and II (OR = 0.88, 95%CI = 0.79–0.99) categories were less likely to have obtained a screening SIG compared to normal weight women. BMI was not associated with FOBT. CONCLUSION: Weight may be a correlate of CRC screening behavior but in a different way between men and women

Sommerfeld enhancement from Goldstone pseudo-scalar exchange

We point out that the exchange of a Goldstone pseudo-scalar can provide an enhancement in the dark matter annihilation rate capable of explaining the excess flux seen in high energy cosmic ray data. The mechanism of enhancement involves the coupling of s and d waves through the tensor force that is very strong and, in fact, singular at short distances. The results indicate that large enhancements require some amount of fine tuning. We also discuss the enhancement due to other singular attractive potentials, such as WIMP models with a permanent electric dipole.Comment: 14 pages, 4 figures, v2 includes contact informatio

Satisfaction with food policies for consumer

노트 : Selected paper prepared for presentation at the Agricultural & Applied Economics Association’s 2016 AAEA Annual Meeting, Boston, Massachusetts, July 31-August 2, 201

Raman-scattered O VI Features in the Symbiotic Nova RR Telescopii

RR Tel is an interacting binary system in which a hot white dwarf (WD) accretes matter from a Mira-type variable star via gravitational capture of its stellar wind. This symbiotic nova shows intense Raman-scattered O VI 1032 and 1038 features at 6825 ˚A and 7082 ˚A. We present high-resolution optical spectra of RR Tel taken in 2016 and 2017 with the Magellan Inamori Kyocera Echelle (MIKE) spectrograph at Magellan-Clay telescope, Chile. We aim to study the stellar wind accretion in RR Tel from the profile analysis of Raman O VI features. With an asymmetric O VI disk model, we derive a representative Keplerian speed of > 35 km s−1 , and the corresponding scale < 0.8 au. The best-fit for the Raman profiles is obtained with a mass loss rate of the Mira M˙ ∼ 2 × 10−6 M yr−1 and a wind terminal velocity v∞ ∼ 20 km s−1 . We compare the MIKE data with an archival spectrum taken in 2003 with the Fibre-fed Extended Range Optical Spectrograph (FEROS) at the MPG/ESO 2.2 m telescope. It allows us to highlight the profile variation of the Raman O VI features, indicative of a change in the density distribution of the O VI disk in the last two decades. We also report the detection of O VI recombination lines at 3811 ˚A and 3834 ˚A, which are blended with other emission lines. Our profile decomposition suggests that the recombination of O VII takes place nearer to the WD than the O VI 1032 and 1038 emission region.Fil: Heo, J. E.. Observatorio Gemini; Chile. Universidad de La Serena; Chile. Sejong University; Corea del SurFil: Lee, H. W.. Universidad de Sejong; Corea del SurFil: Angeloni, R.. Universidad de La Serena; ChileFil: Palma, Tali. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Departamento de Astrofísica Estelar; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Di Mille, F.. Observatorio Las Campanas; Chil