Virial mass in DGP brane cosmology

We study the virial mass discrepancy in the context of a DPG brane-world scenario and show that such a framework can offer viable explanations to account for the mass discrepancy problem. This is done by defining a geometrical mass $\mathcal{N}$ that we prove to be proportional to the virial mass. Estimating $\mathcal{N}$ using observational data, we show that it behaves linearly with $r$ and has a value of the order of $M_{200}$, pointing to a possible resolution of the virial mass discrepancy. We also obtain the radial velocity dispersion of galaxy clusters and show that it is compatible with the radial velocity dispersion profile of such clusters. This velocity dispersion profile can be used to differentiate various models predicting the virial mass.Comment: 12 pages, 1 figure, to appear in CQ

Direct observation of molecular cooperativity near the glass transition

We describe direct observations of molecular cooperativity near the glass transition in poly-vinyl-acetate (PVAc), through nanometer-scale probing of dielectric fluctuations. Molecular clusters switched spontaneously between two to four distinct configurations, producing complex random-telegraph-signals (RTS). Analysis of the RTS and their power spectra shows that individual clusters exhibit both transient dynamical heterogeneity and non-exponential kinetics.Comment: 14 pages pdf, need Acrobat Reade

Anomalous relaxation and self-organization in non-equilibrium processes

We study thermal relaxation in ordered arrays of coupled nonlinear elements with external driving. We find, that our model exhibits dynamic self-organization manifested in a universal stretched-exponential form of relaxation. We identify two types of self-organization, cooperative and anti-cooperative, which lead to fast and slow relaxation, respectively. We give a qualitative explanation for the behavior of the stretched exponent in different parameter ranges. We emphasize that this is a system exhibiting stretched-exponential relaxation without explicit disorder or frustration.Comment: submitted to PR

Solar system constraints on f(T) gravity

We use recent observations from solar system orbital motions in order to constrain f(T) gravity. In particular, imposing a quadratic f(T) correction to the linear-in-T form, which is a good approximation for every realistic case, we extract the spherical solutions of the theory. Using these spherical solutions to describe the Sun's gravitational field, we use recently determined supplementary advances of planetary perihelia, to infer upper bounds on the allowed f(T) corrections. We find that the maximal allowed divergence of the gravitational potential in f(T) gravity from that in the teleparallel equivalent of General Relativity is of the order of 6.2 \times 10^{-10}, in the applicability region of our analysis. This is much smaller than the corresponding (significantly small too) divergence that is predicted from cosmological observations, as expected. Such a tiny allowed divergence from the linear form should be taken into account in f(T) model building.Comment: 7 pages, no figures, version published in Mon.Not.Roy.Astron.So

Factor Structure of the National Alzheimerʼs Coordinating Centers Uniform Dataset Neuropsychological Battery: An Evaluation of Invariance Between and Within Groups Over Time

The neuropsychological battery from the National Alzheimer’s Disease Coordinating Center (NACC) is designed to provide a sensitive assessment of mild cognitive disorders for multicenter investigations. Comprised of eight common neuropsychological tests (12 measures), the battery assesses cognitive domains affected early in the course of Alzheimer’s disease (AD). We examined the factor structure of the battery across levels of cognition (normal, mild cognitive impairment (MCI), dementia) based on Clinical Dementia Rating (CDR) scores to determine cognitive domains tapped by the battery. Using data pooled from 29 NIA funded Alzheimer’s Disease Centers, exploratory factor analysis was used to derive a general model using half of the sample; four factors representing memory, attention, executive function, and language were identified. Confirmatory factor analysis (CFA) was used on the second half of the sample to evaluate invariance between groups and within groups over one year. Factorial invariance testing included systematic addition of constraints and comparisons of nested models. The general CFA model had a good fit. As constraints were added, model fit deteriorated slightly. Comparisons within groups demonstrated stability over one year. In a range of cognition from normal to dementia, factor structures and factor loadings will vary little. Further work is needed to determine if domains become more or less distinct in severely cognitively compromised individuals

Phenotypic regional fMRI activation patterns during memory encoding in MCI and AD

Reliable blood-oxygen-level-dependent (BOLD) fMRI phenotypic biomarkers of Alzheimer's disease (AD) or mild cognitive impairment (MCI) are likely to emerge only from a systematic, quantitative, and aggregate examination of the functional neuroimaging research literature

Theranostic body fluid cleansing: rationally designed magnetic particles enable capturing and detection of bacterial pathogens

We report on theoretical and experimental considerations on bacteria capturing and enrichment via magnetic separation enabling integrated diagnosis and treatment of blood stream infections. We show optimization of carrier-pathogen interactions based on a mathematical model followed by an experimental proof-of-concept study along with investigations on the process safety

Identification of MCI individuals using structural and functional connectivity networks

Different imaging modalities provide essential complementary information that can be used to enhance our understanding of brain disorders. This study focuses on integrating multiple imaging modalities to identify individuals at risk for mild cognitive impairment (MCI). MCI, often an early stage of Alzheimer’s disease (AD), is difficult to diagnose due to its very mild or insignificant symptoms of cognitive impairment. Recent emergence of brain network analysis has made characterization of neurological disorders at a whole-brain connectivity level possible, thus providing new avenues for brain diseases classification. Employing multiple-kernel Support Vector Machines (SVMs), we attempt to integrate information from diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI) for improving classification performance. Our results indicate that the multimodality classification approach yields statistically significant improvement in accuracy over using each modality independently. The classification accuracy obtained by the proposed method is 96.3%, which is an increase of at least 7.4% from the single modality-based methods and the direct data fusion method. A cross-validation estimation of the generalization performance gives an area of 0.953 under the receiver operating characteristic (ROC) curve, indicating excellent diagnostic power. The multimodality classification approach hence allows more accurate early detection of brain abnormalities with greater sensitivity

Tissue-Specific Genetic Control of Splicing: Implications for the Study of Complex Traits

Numerous genome-wide screens for polymorphisms that influence gene expression have provided key insights into the genetic control of transcription. Despite this work, the relevance of specific polymorphisms to in vivo expression and splicing remains unclear. We carried out the first genome-wide screen, to our knowledge, for SNPs that associate with alternative splicing and gene expression in human primary cells, evaluating 93 autopsy-collected cortical brain tissue samples with no defined neuropsychiatric condition and 80 peripheral blood mononucleated cell samples collected from living healthy donors. We identified 23 high confidence associations with total expression and 80 with alternative splicing as reflected by expression levels of specific exons. Fewer than 50% of the implicated SNPs however show effects in both tissue types, reflecting strong evidence for distinct genetic control of splicing and expression in the two tissue types. The data generated here also suggest the possibility that splicing effects may be responsible for up to 13 out of 84 reported genome-wide significant associations with human traits. These results emphasize the importance of establishing a database of polymorphisms affecting splicing and expression in primary tissue types and suggest that splicing effects may be of more phenotypic significance than overall gene expression changes