Measuring sparticle masses in non-universal string inspired models at the LHC

We demonstrate that some of the suggested five supergravity points for study at the LHC could be approximately derived from perturbative string theories or M-theory, but that charge and colour breaking minima would result. As a pilot study, we then analyse a perturbative string model with non-universal soft masses that are optimised in order to avoid global charge and colour breaking minima. By combining measurements of up to six kinematic edges from squark decay chains with data from a new kinematic variable, designed to improve slepton mass measurements, we demonstrate that a typical LHC experiment will be able to determine squark, slepton and neutralino masses with an accuracy sufficient to permit an optimised model to be distinguished from a similar standard SUGRA point. The technique thus generalizes SUSY searches at the LHC

Fluorescent emission in different silicon carbide polytypes

Silicon carbide (SiC) is a widely used material in several industrial applications such as high power electronics, light emitting diodes, and in research application such as photo-voltaic and quantum technologies. As nanoparticles it can be synthetised in many sizes and different polytypes from 200 nm down to 1 nm. In the form of quantum dots they are used as optical biomarkers, and their emission, occurring from the blue to the orange spectral region, is based on quantum confinement effect. In this work we report on emission in the red and near infrared in different SiC polytypes, specifically in 4H, 6H and 3C. In 4H SiC the red visible emission yielded non classical light attributed to an intrinsic defect, identified as a carbon-antisite vacancy pair. Similar spectral emission was observed in 3C SiC bulk and nanoparticles, also yielding very bright single photon emission. Emission in the far red has been observed in homogeneous hetero-structure in SiC tetrapods. © 2013 Copyright SPIE

Detecting exotic heavy leptons at the Large Hadron Collider

New almost-degenerate charged and neutral heavy leptons are a feature of a number of theories of physics beyond the Standard Model. The prospects for detecting these at the Large Hadron Collider using a time-of-flight technique are considered, along with any cosmological or experimental constraints on their masses. Based on a discovery criterion of 10 detected exotic leptons we conclude that, with an integrated luminosity of 100 fb-1, it should be possible to detect such leptons provided their masses are less than 950 GeV. It should also be possible to use the angular distribution of the produced particles to distinguish these exotic leptons from supersymmetric scalar leptons, at a better than 90% confidence level, for masses up to 580 GeV

Exploring small extra dimensions at the Large Hadron Collider

Many models that include small extra space dimensions predict graviton states which are well separated in mass, and which can be detected as resonances in collider experiments. It has been shown that the ATLAS detector at the Large Hadron Collider can identify such narrow states up to a mass of 2080 GeV in the decay mode G->ee, using a conservative model. This work extends the study of the ee channel over the full accessible parameter space, and shows that the reach could extend as high as 3.5 TeV. It then discusses ways in which the expected universal coupling of the resonance can be confirmed using other decay modes. In particular, the mode G-> di-photons is shown to be measurable with good precision, which would provide powerful confirmation of the graviton hypothesis. The decays G-> mu mu, WW, ZZ and jet--jet are measurable over a more limited range of couplings and masses. Using information from mass and cross-section measurements, the underlying parameters can be extracted. In one test model, the size of the extra dimension can be determined to a precision in length of 7x10^-33 m

On Convergence and Threshold Properties of Discrete Lotka-Volterra Population Protocols

In this work we focus on a natural class of population protocols whose dynamics are modelled by the discrete version of Lotka-Volterra equations. In such protocols, when an agent $a$ of type (species) $i$ interacts with an agent $b$ of type (species) $j$ with $a$ as the initiator, then $b$'s type becomes $i$ with probability $P\_{ij}$. In such an interaction, we think of $a$ as the predator, $b$ as the prey, and the type of the prey is either converted to that of the predator or stays as is. Such protocols capture the dynamics of some opinion spreading models and generalize the well-known Rock-Paper-Scissors discrete dynamics. We consider the pairwise interactions among agents that are scheduled uniformly at random. We start by considering the convergence time and show that any Lotka-Volterra-type protocol on an $n$-agent population converges to some absorbing state in time polynomial in $n$, w.h.p., when any pair of agents is allowed to interact. By contrast, when the interaction graph is a star, even the Rock-Paper-Scissors protocol requires exponential time to converge. We then study threshold effects exhibited by Lotka-Volterra-type protocols with 3 and more species under interactions between any pair of agents. We start by presenting a simple 4-type protocol in which the probability difference of reaching the two possible absorbing states is strongly amplified by the ratio of the initial populations of the two other types, which are transient, but "control" convergence. We then prove that the Rock-Paper-Scissors protocol reaches each of its three possible absorbing states with almost equal probability, starting from any configuration satisfying some sub-linear lower bound on the initial size of each species. That is, Rock-Paper-Scissors is a realization of a "coin-flip consensus" in a distributed system. Some of our techniques may be of independent value

Determining the Effects of Past Negative Experiences Involving Patient Care

As the cost of healthcare continues to raise, the need to address nurse attrition, which is a contributing factor, also rises. While there are various factors that influence nurses’ decision to leave or stay, job satisfaction and ethical climate are significant variables. This study examined the effects of negative previous work experiences on job satisfaction and ethical climate. The results showed previous work experiences moderated both job satisfaction and ethical climate. In addition, ethical climate mediated the effects of previous experiences on job satisfaction. The implications include identifying nurses who may have had negative experiences prior to their current employment and providing them with ongoing support

Postcopulatory sexual selection

The female reproductive tract is where competition between the sperm of different males takes place, aided and abetted by the female herself. Intense postcopulatory sexual selection fosters inter-sexual conflict and drives rapid evolutionary change to generate a startling diversity of morphological, behavioural and physiological adaptations. We identify three main issues that should be resolved to advance our understanding of postcopulatory sexual selection. We need to determine the genetic basis of different male fertility traits and female traits that mediate sperm selection; identify the genes or genomic regions that control these traits; and establish the coevolutionary trajectory of sexes

Chandrasekhar-Kendall functions in astrophysical dynamos

Some of the contributions of Chandrasekhar to the field of magnetohydrodynamics are highlighted. Particular emphasis is placed on the Chandrasekhar-Kendall functions that allow a decomposition of a vector field into right- and left-handed contributions. Magnetic energy spectra of both contributions are shown for a new set of helically forced simulations at resolutions higher than what has been available so far. For a forcing function with positive helicity, these simulations show a forward cascade of the right-handed contributions to the magnetic field and nonlocal inverse transfer for the left-handed contributions. The speed of inverse transfer is shown to decrease with increasing value of the magnetic Reynolds number.Comment: 10 pages, 5 figures, proceedings of the Chandrasekhar Centenary Conference, to be published in PRAMANA - Journal of Physic

Hip fracture risk assessment: Artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study

Copyright @ 2013 Tseng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background - Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared. Methods - The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests. Results - In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively). Conclusions - The risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.National Health Research Institutes in Taiwa