Astrometric Effects of a Stochastic Gravitational Wave Background

A stochastic gravitational wave background causes the apparent positions of distant sources to fluctuate, with angular deflections of order the characteristic strain amplitude of the gravitational waves. These fluctuations may be detectable with high precision astrometry, as first suggested by Braginsky et al. in 1990. Several researchers have made order of magnitude estimates of the upper limits obtainable on the gravitational wave spectrum \Omega_gw(f), at frequencies of order f ~ 1 yr^-1, both for the future space-based optical interferometry missions GAIA and SIM, and for VLBI interferometry in radio wavelengths with the SKA. For GAIA, tracking N ~ 10^6 quasars over a time of T ~ 1 yr with an angular accuracy of \Delta \theta ~ 10 \mu as would yield a sensitivity level of \Omega_gw ~ (\Delta \theta)^2/(N T^2 H_0^2) ~ 10^-6, which would be comparable with pulsar timing. In this paper we take a first step toward firming up these estimates by computing in detail the statistical properties of the angular deflections caused by a stochastic background. We compute analytically the two point correlation function of the deflections on the sphere, and the spectrum as a function of frequency and angular scale. The fluctuations are concentrated at low frequencies (for a scale invariant stochastic background), and at large angular scales, starting with the quadrupole. The magnetic-type and electric-type pieces of the fluctuations have equal amounts of power.Comment: 23 pages, 2 figures, references added and minor text correction

Redox-Active Nanomaterials For Nanomedicine Applications

Nanomedicine utilizes the remarkable properties of nanomaterials for the diagnosis, treatment, and prevention of disease. Many of these nanomaterials have been shown to have robust antioxidative properties, potentially functioning as strong scavengers of reactive oxygen species. Conversely, several nanomaterials have also been shown to promote the generation of reactive oxygen species, which may precipitate the onset of oxidative stress, a state that is thought to contribute to the development of a variety of adverse conditions. As such, the impacts of nanomaterials on biological entities are often associated with and influenced by their specific redox properties. In this review, we overview several classes of nanomaterials that have been or projected to be used across a wide range of biomedical applications, with discussion focusing on their unique redox properties. Nanomaterials examined include iron, cerium, and titanium metal oxide nanoparticles, gold, silver, and selenium nanoparticles, and various nanoscale carbon allotropes such as graphene, carbon nanotubes, fullerenes, and their derivatives/variations. Principal topics of discussion include the chemical mechanisms by which the nanomaterials directly interact with biological entities and the biological cascades that are thus indirectly impacted. Selected case studies highlighting the redox properties of nanomaterials and how they affect biological responses are used to exemplify the biologically-relevant redox mechanisms for each of the described nanomaterials

LearnBlock: A Robot-Agnostic Educational Programming Tool

Education is evolving to prepare students for the current sociotechnical changes. An increasing effort to introduce programming and other STEM-related subjects into the core curriculum of primary and secondary education is taking place around the world. The use of robots stands out among STEM initiatives, since robots are proving to be an engaging tool for learning programming and other STEM-related contents. Block-based programming is the option chosen for most educational robotic platforms. However, many robotics kits include their own software tools, as well as their own set of programming blocks. LearnBlock, a new educational programming tool, is proposed here. Its major novelty is its loosely coupled software architecture which makes it, to the best of our knowledge, the first robot-agnostic educational tool. Robot-agnosticism is provided not only in block code, but also in generated code, unifying the translation from blocks to the final programming language. The set of blocks can be easily extended implementing additional Python functions, without modifying the core code of the tool. Moreover, LearnBlock provides an integrated educational programming environment that facilitates a progressive transition from a visual to a general-purpose programming language. To evaluate LearnBlock and demonstrate that it is platform-agnostic, several tests were conducted. Each of them consists of a program implementing a robot behaviour. The block code of each test can run on several educational robots without changes

Insulin and TOR signal in parallel through FOXO and S6K to promote epithelial wound healing

The TOR and Insulin/IGF signalling (IIS) network controls growth, metabolism and ageing. Although reducing TOR or insulin signalling can be beneficial for ageing, it can be detrimental for wound healing, but the reasons for this difference are unknown. Here we show that IIS is activated in the cells surrounding an epidermal wound in Drosophila melanogaster larvae, resulting in PI3K activation and redistribution of the transcription factor FOXO. Insulin and TOR signalling are independently necessary for normal wound healing, with FOXO and S6K as their respective effectors. IIS is specifically required in cells surrounding the wound, and the effect is independent of glycogen metabolism. Insulin signalling is needed for the efficient assembly of an actomyosin cable around the wound, and constitutively active myosin II regulatory light chain suppresses the effects of reduced IIS. These findings may have implications for the role of insulin signalling and FOXO activation in diabetic wound healing

Empirical research on youth transitions to and within the labour market

The research project aimed to provide research outcomes on the magnitude of youth transitions, the main drivers and barriers of youth transitions and potential long-term outcomes (‘scarring’) on people’s subsequent employment trajectories. This report summarises the evidence obtained by making use of a range of individual-level data sets and methods, in particular: • An analysis of Labour Force Survey (LFS) data creating pseudo-cohorts to examine long-term education and labour market trends affecting 16-to-24 year olds from 39 different birth cohorts and subsequent employment trajectories. • An analysis of the ‘Ad Hoc module’ of 2009 from the European Labour Force Survey (EU:LFS) on ‘Youth Transitions’ on individual long-term outcomes of particular youth labour market transitions. • An analysis of various cohort studies (National Child Development Study [NCDS], British Cohort Study [BCS], Youth Cohort Study [YCS], Longitudinal Study of Young People in England [LSYPE]) comparing the episodes young people experience when making transitions into the labour market in youth and early adulthood. This study uses sequential analysis for individual monthly panel data to describe biographies of young people until the age of 25 (based on BCS and NCDS) and until the age of 19 (for YCS and LSYPE). • An analysis of the transition from secondary schooling to further destinations using a recent cohort of School Leavers National Pupil Data (NPD) merged to records of National Client Casework Information System (NCCIS) on young people’s activities after the end of compulsory education including econometric models on drivers and barriers of particular transitions