Experimental Conditions for Determination of the Neutrino Mass Hierarchy with Reactor Antineutrinos

This article reports the optimized experimental requirements to determine neutrino mass hierarchy using electron antineutrinos ($\bar{\nu}_e$) generated in a nuclear reactor. The features of the neutrino mass hierarchy can be extracted from the $|\Delta m^{2}_{31}|$ and $|\Delta m^{2}_{32}|$ oscillations by applying the Fourier sine and cosine transform to the $L/E$ spectrum. To determine the neutrino mass hierarchy above 90\% probability, the requirements on the energy resolution as a function of the baseline are studied at $\sin 2\theta_{13}=0.1$. If the energy resolution of the neutrino detector is less than $0.04/ \sqrt{E_{\nu}}$ and the determination probability obtained from Bayes' theorem is above 90\%, the detector needs to be located around 48--53 km from the reactor(s) to measure the energy spectrum of $\bar{\nu}_e$. These results will be helpful for setting up an experiment to determine the neutrino mass hierarchy, which is an important problem in neutrino physics

Mean semi-deviation from a target and robust portfolio choice under distribution and mean return ambiguity

Cataloged from PDF version of article.We consider the problem of optimal portfolio choice using the lower partial moments risk measure for a market consisting of n risky assets and a riskless asset. For when the mean return vector and variance/covariance matrix of the risky assets are specified without specifying a return distribution, we derive distributionally robust portfolio rules. We then address potential uncertainty (ambiguity) in the mean return vector as well, in addition to distribution ambiguity, and derive a closed-form portfolio rule for when the uncertainty in the return vector is modelled via an ellipsoidal uncertainty set. Our result also indicates a choice criterion for the radius of ambiguity of the ellipsoid. Using the adjustable robustness paradigm we extend the single-period results to multiple periods, and derive closed-form dynamic portfolio policies which mimic closely the single-period policy. © 2013 Elsevier B.V. All rights reserved

Robust portfolio choice with CVaR and VaR under distribution and mean return ambiguity

Cataloged from PDF version of article.We consider the problem of optimal portfolio choice using the Conditional Value-at-Risk (CVaR) and Value-at-Risk (VaR) measures for a market consisting of n risky assets and a riskless asset and where short positions are allowed. When the distribution of returns of risky assets is unknown but the mean return vector and variance/covariance matrix of the risky assets are fixed, we derive the distributionally robust portfolio rules. Then, we address uncertainty (ambiguity) in the mean return vector in addition to distribution ambiguity, and derive the optimal portfolio rules when the uncertainty in the return vector is modeled via an ellipsoidal uncertainty set. In the presence of a riskless asset, the robust CVaR and VaR measures, coupled with a minimum mean return constraint, yield simple, mean-variance efficient optimal portfolio rules. In a market without the riskless asset, we obtain a closed-form portfolio rule that generalizes earlier results, without a minimum mean return restriction

The Creative Class and the Creative Economy in Spain

This article describes an application in Spain of Florida's model (2002/Citation2010, Citation2005) about creativity, economy and growth. Creativity is an indicator that measures and combines technology, talent, and tolerance. Each of these is composed of three subindices. The most important conclusion from the data reported here is that creativity in particular, and growth in general, was less related to tolerance than the other two indices. However, the subindex of tolerance reflecting bohemia was important; the other two (foreigners and gays) were not

Flow-based detection and proxy-based evasion of encrypted malware C2 traffic

State of the art deep learning techniques are known to be vulnerable to evasion attacks where an adversarial sample is generated from a malign sample and misclassified as benign. Detection of encrypted malware command and control traffic based on TCP/IP flow features can be framed as a learning task and is thus vulnerable to evasion attacks. However, unlike e.g. in image processing where generated adversarial samples can be directly mapped to images, going from flow features to actual TCP/IP packets requires crafting the sequence of packets, with no established approach for such crafting and a limitation on the set of modifiable features that such crafting allows. In this paper we discuss learning and evasion consequences of the gap between generated and crafted adversarial samples. We exemplify with a deep neural network detector trained on a public C2 traffic dataset, white-box adversarial learning, and a proxy-based approach for crafting longer flows. Our results show 1) the high evasion rate obtained by using generated adversarial samples on the detector can be significantly reduced when using crafted adversarial samples; 2) robustness against adversarial samples by model hardening varies according to the crafting approach and corresponding set of modifiable features that the attack allows for; 3) incrementally training hardened models with adversarial samples can produce a level playing field where no detector is best against all attacks and no attack is best against all detectors, in a given set of attacks and detectors. To the best of our knowledge this is the first time that level playing field feature set- and iteration-hardening are analyzed in encrypted C2 malware traffic detection.Comment: 9 pages, 6 figure

Production and optical properties of liquid scintillator for the JSNS2^{2} experiment

The JSNS$^{2}$ (J-PARC Sterile Neutrino Search at J-PARC Spallation Neutron Source) experiment will search for neutrino oscillations over a 24 m short baseline at J-PARC. The JSNS$^{2}$ inner detector will be filled with 17 tons of gadolinium-loaded liquid scintillator (LS) with an additional 31 tons of unloaded LS in the intermediate $\gamma$-catcher and outer veto volumes. JSNS$^{2}$ has chosen Linear Alkyl Benzene (LAB) as an organic solvent because of its chemical properties. The unloaded LS was produced at a refurbished facility, originally used for scintillator production by the RENO experiment. JSNS$^{2}$ plans to use ISO tanks for the storage and transportation of the LS. In this paper, we describe the LS production, and present measurements of its optical properties and long term stability. Our measurements show that storing the LS in ISO tanks does not result in degradation of its optical properties.Comment: 7 pages, 4 figures

A pitfall of whole exome sequencing:: variants in the 5 ' UTR Splice Site of BTK causing XLA

Transplantation and immunomodulatio