G\"odel Type Metrics in Three Dimensions

We show that the G{\" o}del type Metrics in three dimensions with arbitrary two dimensional background space satisfy the Einstein-perfect fluid field equations. There exists only one first order partial differential equation satisfied by the components of fluid's velocity vector field. We then show that the same metrics solve the field equations of the topologically massive gravity where the two dimensional background geometry is a space of constant negative Gaussian curvature. We discuss the possibility that the G{\" o}del Type Metrics to solve the Ricci and Cotton flow equations. When the vector field $u^{\mu}$ is a Killing vector field we finally show that the stationary G{\" o}del Type Metrics solve the field equations of the most possible gravitational field equations where the interaction lagrangian is an arbitrary function of the electromagnetic field and the curvature tensors.Comment: 17 page

Fear information and social phobic beliefs in children: a prospective paradigm and preliminary results

This paper presents a first attempt to develop a prospective paradigm to test Rachman’s (Behav. Res. Ther. 15 (1977) 375) theory of fear acquisition for social fears. Following the prospective paradigm for animal fears developed by Field et al. (Behav. Res. Ther. 39 (2001) 1259) an attempt is made to adapt this paradigm to look at the effect of fear information in the development of social fears. A large group of normal children (N=135)who were at an age (10–13 years) at which social concerns are most pertinent were tested using this paradigm. They were given positive, negative or neutral information about three social situations: public speaking, eating in public, and meeting a new group of children. Children’s fear beliefs were measured before and after the information was given and the information was given by a teacher, a same age peer or no information was given (a control). The results indicate that although information can change social fear beliefs it is dependent upon the type of social activity and who provides the information. The implications of these initial results for our understanding of both the role of fear information in the development of social fear beliefs, and the limitations of this current paradigm are discussed

Race and Ancestry in Immune Response to Breast Cancer

Martini and colleagues performed genetic ancestry estimation on a unique international triple-negative breast cancer (TNBC) study enriched for participants with African ancestry. They identified gene signatures indicative of ancestry in race-associated TNBC and found ancestry-associated immunologic differences that may contribute to racial disparities in breast cancer

Formal Quantum Efficiencies for the Photocatalytic Reduction of CO2 in a Gas Phase Batch Reactor

The photocatalytic reduction of CO2 to fuels, or useful products, is an area of active research. In this work, nanoengineering and surface modification of titania were investigated as approaches for improving the CO2 reduction efficiency in a fixed-bed gas phase batch photoreactor under UV–vis irradiation. Titania nanotubes were prepared by a hydrothermal method, and TiO2 (P25) was surface modified with copper clusters. Unmodified TiO2 (P25) was used as the bench-mark comparison. The titania nanotubes and Cu-TiO2 materials showed higher efficiency for the photocatalytic reduction of CO2 to yield CH4 as compared to P25. Carbon monoxide yields were similar for all photocatalysts tested. The photocatalytic reduction of CO2 was observed on all photocatalyst tested, with the nanotubes proving to be the most efficient for the production of CH4. The product yields per mass of catalyst observed in this work are similar to those reported in the literature (with similar reactor parameters) but the calculated formal quantum efficiencies for CO2 reduction are very low (4.41 × 10−5 to 5.95 × 10-4)

Multifunctional photo/thermal catalysts for the reduction of carbon dioxide

The photochemical fixation of CO2 to energy rich products for solar energy storage or feedstock chemicals is an attractive, albeit daunting, challenge. The overall feasibility of CO2 conversion is limited by the availability of efficient photo-active materials that meet the energetic requirements for CO2 reduction and are optically matched to the solar spectrum. Surface modification of TiO2 with earth abundant metal oxides presents one approach to develop visible active photocatalysts through band gap narrowing, while providing catalytic sites to lower the activation energy for CO2 reduction. In this work density functional theory was used to model the effect of surface modification of rutile and anatase using MnOx nanoclusters. The results indicate the formation of inter-band gap states following surface modification with MnOx, but surface water can change this. Oxygen vacancies are predicted to form in supported MnOx and the interaction with CO2 was investigated. MnOx-TiO2 was synthesized and characterised using surface analytical methods and photoelectrochemistry. The interaction of CO2 with the materials under irradiation was probed using in-situ FTIR to interrogate the role of oxygen vacancies in CO2 binding and reaction. These results provide insights into the requirements of a multifunctional catalyst for CO2 conversion

Specific heat study of single crystalline Pr0.63_{0.63} Ca0.37_{0.37} MnO3_{3} in presence of a magnetic field

We present the results of a study of specific heat on a single crystal of Pr$_{0.63}$Ca$_{0.37}$MnO$_3$ performed over a temperature range 3K-300K in presence of 0 and 8T magnetic fields. An estimate of the entropy and latent heat in a magnetic field at the first order charge ordering (CO) transition is presented. The total entropy change at the CO transition which is $\approx$ 1.8 J/mol K at 0T, decreases to $\sim$ 1.5 J/mol K in presence of 8T magnetic field. Our measurements enable us to estimate the latent heat $L_{CO}$ $\approx$ 235 J/mol involved in the CO transition. Since the entropy of the ferromagnetic metallic (FMM) state is comparable to that of the charge-ordered insulating (COI) state, a subtle change in entropy stabilises either of these two states. Our low temperature specific heat measurements reveal that the linear term is absent in 0T and surprisingly not seen even in the metallic FMM state.Comment: 8 pages (in RevTEX format), 12 figures (in postscript format) Submitted to Phys. Rev.

Optimising approximate entropy for assessing cardiac dyssynchrony with radionuclide ventriculography

Left ventricular dyssynchrony can be assessed with phase parameters from radionuclide ventriculography (RNVG), including approximate entropy (ApEn). The input values used to calculate ApEn will affect the results significantly, so it is essential to optimise ApEn for the application. However to date, no optimisation for ApEn applied to images has been published. In this paper, generated data were used to simulate patient phase images, allowing the input parameters for ApEn to be tested and optimised in a controlled environment. Clinical images were then used to confirm that the selected parameters were appropriate. The results demonstrate the effect of input parameters for ApEn and the most appropriate use with RNVG phase images. This work demonstrates the importance of optimisation and standardisation when using ApEn as a measure of dyssynchrony

An approach for normalization and quality control for NanoString RNA expression data

The NanoString RNA counting assay for formalin-fixed paraffin embedded samples is unique in its sensitivity, technical reproducibility and robustness for analysis of clinical and archival samples. While commercial normalization methods are provided by NanoString, they are not optimal for all settings, particularly when samples exhibit strong technical or biological variation or where housekeeping genes have variable performance across the cohort. Here, we develop and evaluate a more comprehensive normalization procedure for NanoString data with steps for quality control, selection of housekeeping targets, normalization and iterative data visualization and biological validation. The approach was evaluated using a large cohort (N= 1649$) from the Carolina Breast Cancer Study, two cohorts of moderate sample size (N=359 and 130) and a small published dataset (N=12). The iterative process developed here eliminates technical variation (e.g. from different study phases or sites) more reliably than the three other methods, including NanoString's commercial package, without diminishing biological variation, especially in long-term longitudinal multiphase or multisite cohorts. We also find that probe sets validated for nCounter, such as the PAM50 gene signature, are impervious to batch issues. This work emphasizes that systematic quality control, normalization and visualization of NanoString nCounter data are an imperative component of study design that influences results in downstream analyses