Precision luminosity measurement at ILC

In these proceedings a novel approach to deal with the beam-induced effects in luminosity measurement is presented. Based on the relativistic kinematics of the collision frame of the Bhabha process, the beam-beam related uncertainties can be reduced to the permille level independently of a precision with which the beam parameters are known. Specific event selection combined with the corrective methods we introduce, leads to the systematic uncertainty from the beam-induced effects to be at a few permille level in the peak region above the 80% of the nominal centre-of-mass energies at ILC.Comment: Talk presented on behalf of the FCAL Collaboration at the International Workshop on Future Linear Colliders (LCWS13) Tokyo, Japan, 11-15 November 201

MicroRNA-551b expression profile in low and high-grade cervical intraepithelial neoplasia

OBJECTIVE: To evaluate the expression of microRNA (miR)-551b in patients with low and high grade cervical intraepithelial neoplasia (CIN) and to find an association with high-risk Human Papillomavirus (HR-HPV) infection-related prognostic biomarkers. PATIENTS AND METHODS: The expression level of miR-551b was determined in 50 paraffin-embedded cervical specimens (10 normal squamous epithelium, 18 condylomas, 8 CIN1, and 14 CIN2-3) using quantitative Real-time polymerase chain reaction (qRT-PCR). χ2-test compared miR-551b expression in different diagnosis groups. An Ordered Logistic Regression and a Probit correlation were made to correlate miR-551b expression levels with the cervical tissue histological findings. The immunohistochemical distribution of p16 and Ki-67 according to histopathological findings was also assessed. RESULTS: The distribution of the miR-551b expression profile was significantly lower in CIN1-3 samples compared to other histological diagnosis groups (condyloma and negative). The expression levels were inversely correlated to the cervical pathological grade, from negative to CIN2-3. A 1% increase in miR-551b expression level produced an increase of 19% to the probability of a minor histological grade diagnosis in a range from negative to CIN2-3 and an increase of 13% to the probability of a negative histological grade diagnosis. Among the cases with miR-551b expression < 0.02 (considered as cut-off value) a significant statistical correlation was found between p16 and Ki-67 expression and the diagnosis of CIN2-3. CONCLUSIONS: O ur d ata s howed a s ignificant inverse correlation between miR-551b expression and the histological grading of the lesions, suggesting a tumor suppressive function in the different stages of cervical dysplasia

Domain wall entropy of the bimodal two-dimensional Ising spin glass

We report calculations of the domain wall entropy for the bimodal two-dimensional Ising spin glass in the critical ground state. The L * L system sizes are large with L up to 256. We find that it is possible to fit the variance of the domain wall entropy to a power function of L. However, the quality of the data distributions are unsatisfactory with large L > 96. Consequently, it is not possible to reliably determine the fractal dimension of the domain walls.Comment: 4 pages, 2 figures, submitted to PR

Genome-wide association study of behavioural and psychiatric features in human prion disease.

Prion diseases are rare neurodegenerative conditions causing highly variable clinical syndromes, which often include prominent neuropsychiatric symptoms. We have recently carried out a clinical study of behavioural and psychiatric symptoms in a large prospective cohort of patients with prion disease in the United Kingdom, allowing us to operationalise specific behavioural/psychiatric phenotypes as traits in human prion disease. Here, we report exploratory genome-wide association analysis on 170 of these patients and 5200 UK controls, looking for single-nucleotide polymorphisms (SNPs) associated with three behavioural/psychiatric phenotypes in the context of prion disease. We also specifically examined a selection of candidate SNPs that have shown genome-wide association with psychiatric conditions in previously published studies, and the codon 129 polymorphism of the prion protein gene, which is known to modify various aspects of the phenotype of prion disease. No SNPs reached genome-wide significance, and there was no evidence of altered burden of known psychiatric risk alleles in relevant prion cases. SNPs showing suggestive evidence of association (P<10(-5)) included several lying near genes previously implicated in association studies of other psychiatric and neurodegenerative diseases. These include ANK3, SORL1 and a region of chromosome 6p containing several genes implicated in schizophrenia and bipolar disorder. We would encourage others to acquire phenotype data in independent cohorts of patients with prion disease as well as other neurodegenerative and neuropsychiatric conditions, to allow meta-analysis that may shed clearer light on the biological basis of these complex disease manifestations, and the diseases themselves

Energy gap of the bimodal two-dimensional Ising spin glass

An exact algorithm is used to compute the degeneracies of the excited states of the bimodal Ising spin glass in two dimensions. It is found that the specific heat at arbitrary low temperature is not a self-averaging quantity and has a distribution that is neither normal or lognormal. Nevertheless, it is possible to estimate the most likely value and this is found to scale as L^3 T^(-2) exp(-4J/kT), for a L*L lattice. Our analysis also explains, for the first time, why a correlation length \xi ~ exp(2J/kT) is consistent with an energy gap of 2J. Our method allows us to obtain results for up to 10^5 disorder realizations with L <= 64. Distributions of second and third excitations are also shown.Comment: 4 pages, 4 figure

An ica algorithm for analyzing multiple data sets

In this paper we derive an independent-component analysis (ICA) method for analyzing two or more data sets simultaneously. Our model permits there to be components individual to the various data sets, and others that are common to all the sets. We explore the assumed time autocorrelation of independent signal components and base our algorithm on prediction analysis. We illustrate the algorithm using a simple image separation example. Our aim is to apply this method to functional brain mapping using functional magnetic resonance imaging (fMRI). 1