Pair production of charged Higgs bosons in the Left-Right Twin Higgs model at the ILC and LHC

Left-Right twin Higgs(LRTH) model predicts the existence of a pair of charged Higgs $\phi^{\pm}$. In this paper, we study the production of the charged Higgs bosons pair $\phi^{\pm}$ via the process $e^{+}e^{-}\to \phi^{+}\phi^{-}$ at the International Linear Collider(ILC). The numerical results show that the production rates are at the level of several tens fb, this process can produce the adequate distinct multi-jet final states and the SM background can be efficiently reduced. We also discuss the charged Higgs boson pair production via the process $q\bar{q}\to \phi^{+}\phi^{-}$ at the $CERN$ Large Hadron Collider(LHC) and estimate there production rates. We find that, as long as the charged Higgs bosons are not too heavy, they can be abundantly produced at the LHC. The possible signatures of these new particles might be detected at the ILC and LHC experiments.Comment: 15 pages, 5 figures, discussion extended, reference added, typos fixed, revised version to be published in Eur.Phys.J.

Secure biometric authentication with improved accuracy

We propose a new hybrid protocol for cryptographically secure biometric authentication. The main advantages of the proposed protocol over previous solutions can be summarised as follows: (1) potential for much better accuracy using different types of biometric signals, including behavioural ones; and (2) improved user privacy, since user identities are not transmitted at any point in the protocol execution. The new protocol takes advantage of state-of-the-art identification classifiers, which provide not only better accuracy, but also the possibility to perform authentication without knowing who the user claims to be. Cryptographic security is based on the Paillier public key encryption scheme

A Brief Review on Dark Matter Annihilation Explanation for e±e^\pm Excesses in Cosmic Ray

Recently data from PAMELA, ATIC, FERMI-LAT and HESS show that there are $e^{\pm}$ excesses in the cosmic ray energy spectrum. PAMELA observed excesses only in $e^+$, but not in anti-proton spectrum. ATIC, FERMI-LAT and HESS observed excesses in $e^++e^-$ spectrum, but the detailed shapes are different which requires future experimental observations to pin down the correct data set. Nevertheless a lot of efforts have been made to explain the observed $e^\pm$ excesses, and also why PAMELA only observed excesses in $e^+$ but not in anti-proton. In this brief review we discuss one of the most popular mechanisms to explain the data, the dark matter annihilation. It has long been known that about 23% of our universe is made of relic dark matter. If the relic dark matter was thermally produced, the annihilation rate is constrained resulting in the need of a large boost factor to explain the data. We will discuss in detail how a large boost factor can be obtained by the Sommerfeld and Briet-Wigner enhancement mechanisms. Some implications for particle physics model buildings will also be discussed.Comment: 22 pages, 6 figures. Several typoes corrected and some references added. Published in Mod. Phys. Lett. A, Vol. 24, No. 27 (2009) pp. 2139-216

Universal features of correlated bursty behaviour

Inhomogeneous temporal processes, like those appearing in human communications, neuron spike trains, and seismic signals, consist of high-activity bursty intervals alternating with long low-activity periods. In recent studies such bursty behavior has been characterized by a fat-tailed inter-event time distribution, while temporal correlations were measured by the autocorrelation function. However, these characteristic functions are not capable to fully characterize temporally correlated heterogenous behavior. Here we show that the distribution of the number of events in a bursty period serves as a good indicator of the dependencies, leading to the universal observation of power-law distribution in a broad class of phenomena. We find that the correlations in these quite different systems can be commonly interpreted by memory effects and described by a simple phenomenological model, which displays temporal behavior qualitatively similar to that in real systems

Distributed flow optimization and cascading effects in weighted complex networks

We investigate the effect of a specific edge weighting scheme $\sim (k_i k_j)^{\beta}$ on distributed flow efficiency and robustness to cascading failures in scale-free networks. In particular, we analyze a simple, yet fundamental distributed flow model: current flow in random resistor networks. By the tuning of control parameter $\beta$ and by considering two general cases of relative node processing capabilities as well as the effect of bandwidth, we show the dependence of transport efficiency upon the correlations between the topology and weights. By studying the severity of cascades for different control parameter $\beta$, we find that network resilience to cascading overloads and network throughput is optimal for the same value of $\beta$ over the range of node capacities and available bandwidth

Predictors of allergen sensitization in Singapore children from birth to 3 years

10.1186/s13223-016-0161-xAllergy, asthma, and clinical immunology : official journal of the Canadian Society of Allergy and Clinical Immunology121Article number 56GUSTO (Growing up towards Healthy Outcomes

An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis

Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.Comment: 54 pages (19 pages main text; 11 Figures; 26 pages of supplementary information). Revised after critical reviews. Accepted for Publication in PLoS ON

Combination Forecasts of Bond and Stock Returns: An Asset Allocation Perspective

We investigate the out-of-sample forecasting ability of the HML, SMB, momentum, short-term and long-term reversal factors along with their size and value decompositions on U.S. bond and stock returns for a variety of horizons ranging from the short run (1 month) to the long run (2 years). Our findings suggest that these factors contain significantly more information for future bond and stock market returns than the typically employed financial variables. Combination of forecasts of the empirical factors turns out to be particularly successful, especially from an an asset allocation perspective. Similar findings pertain to the European and Japanese markets

Chemotherapy-Response Monitoring of Breast Cancer Patients Using Quantitative Ultrasound-Based Intra-Tumour Heterogeneities

© 2017 The Author(s). Anti-cancer therapies including chemotherapy aim to induce tumour cell death. Cell death introduces alterations in cell morphology and tissue micro-structures that cause measurable changes in tissue echogenicity. This study investigated the effectiveness of quantitative ultrasound (QUS) parametric imaging to characterize intra-tumour heterogeneity and monitor the pathological response of breast cancer to chemotherapy in a large cohort of patients (n = 100). Results demonstrated that QUS imaging can non-invasively monitor pathological response and outcome of breast cancer patients to chemotherapy early following treatment initiation. Specifically, QUS biomarkers quantifying spatial heterogeneities in size, concentration and spacing of acoustic scatterers could predict treatment responses of patients with cross-validated accuracies of 82 ± 0.7%, 86 ± 0.7% and 85 ± 0.9% and areas under the receiver operating characteristic (ROC) curve of 0.75 ± 0.1, 0.80 ± 0.1 and 0.89 ± 0.1 at 1, 4 and 8 weeks after the start of treatment, respectively. The patients classified as responders and non-responders using QUS biomarkers demonstrated significantly different survivals, in good agreement with clinical and pathological endpoints. The results form a basis for using early predictive information on survival-linked patient response to facilitate adapting standard anti-cancer treatments on an individual patient basis