'I just want a job' : what do we really know about young people in jobs without training?

Over recent years, a central concern of policy has been to drive up post-16 participation rates in full-time education and address the needs of young people not in education, employment or training (NEET). As a result, young people who enter work which is classified as 'without training' at 16/17 have largely been ignored. However, the decision to Raise the Participation Age (RPA) for continuing in learning for all 17-year olds from 2013 and for all 18-year olds from 2015 in England, together with a growing unease about the impact of the current recession on youth unemployment rates, have revived interest in the 'jobs without training' (JWT) group. This paper draws on the findings from two studies: first, a qualitative study in two contrasting local labour markets, of young people in JWT, together with their employers and parents; and second, an evaluation of the Learning Agreement Pilots (LAP), which was the first policy initiative in England targeted at the JWT group. Both studies reveal a dearth of understanding about early labour market entrants and a lack of policy intervention and infrastructure to support the needs of the JWT group throughout the UK. From this, it is concluded that questionable assumptions have been made about the composition and the aspirations of young people in JWT, and their employers, on the basis of little or no evidence. As a consequence, a policy 'quick fix' to satisfy the RPA agenda will not easily be achieved. If the decision to raise the participation age is adopted also by the Welsh and Scottish parliaments, similar challenges may have to be faced

Activity of different desoximetasone preparations compared to other topical corticosteroids in the vasoconstriction assay

Introduction: We report on a double-blind, vehicle-controlled, single-center confirmatory study with random assignment. The purpose of the study was to investigate the topical bioavailability of different topical corticosteroid formulations in healthy human beings focussing on desoximetasone (DM). Materials and Methods: Two DM 0.25% formulations {[}ointment (DM-o) and fatty ointment (DM-fo, water-free); class III corticosteroids], the corresponding active ingredient-free vehicles and three comparators of different strength {[}clobetasol propionate 0.05% (CP 0.05%), fatty ointment, class IV; hydrocortisone (HC) 1%, fatty ointment, class I, and betamethasone (BM) 0.05%, fatty ointment, class III] were tested using the vasoconstriction assay. The degree of vasoconstriction (blanching) in the treatment field was compared to the one found in untreated control fields using chromametric measurements and clinical assessment. Results/Conclusion: DM-o 0.25%, DM-fo 0.25% and BM 0.05% showed similar vasoconstrictive potential, i.e., clear blanching. In fact, both DM preparations were proven to be non-inferior to BM 0.05%, while CP 0.05% was found a little less active. HC 1.0% and the DM vehicles showed no clear-cut vasoconstrictive effect. No adverse events related to the study medications were observed. Good topical bioavailability of both DM formulations was detected by chromametric measurement and clinical assessment. Copyright (C) 2008 S. Karger AG, Basel

Heat shock proteins and regulatory T cells

Heat shock proteins (HSPs) are important molecules required for ideal protein function. Extensive research on the functional properties of HSPs indicates that HSPs may be implicated in a wide range of physiological functions including immune function. In the immune system, HSPs are involved in cell proliferation, differentiation, cytokine release, and apoptosis. Therefore, the ability of the immune system, in particular immune cells, to function optimally and in unison with other physiological systems is in part dependent on signaling transduction processes, including bidirectional communication with HSPs. Regulatory T cells (Tregs) are important T cells with suppressive functions and impairments in their function have been associated with a number of autoimmune disorders. The purpose of this paper is to examine the relationship between HSPs and Tregs. The interrelationship between cells and proteins may be important in cellular functions necessary for cell survival and expansion during diseased state

Optimisation of air cooled, open-cathode fuel cells: Current of lowest resistance and electro-thermal performance mapping

Selecting the ideal operating point for a fuel cell depends on the application and consequent trade-off between efficiency, power density and various operating considerations. A systematic methodology for determining the optimal operating point for fuel cells is lacking; there is also the need for a single-value metric to describe and compare fuel cell performance. This work shows how the ‘current of lowest resistance’ can be accurately measured using electrochemical impedance spectroscopy and used as a useful metric of fuel cell performance. This, along with other measures, is then used to generate an ‘electro-thermal performance map’ of fuel cell operation. A commercial air-cooled open-cathode fuel cell is used to demonstrate how the approach can be used; in this case leading to the identification of the optimum operating temperature of ∼45 °C

A major electronics upgrade for the H.E.S.S. Cherenkov telescopes 1-4

The High Energy Stereoscopic System (H.E.S.S.) is an array of imaging atmospheric Cherenkov telescopes (IACTs) located in the Khomas Highland in Namibia. It consists of four 12-m telescopes (CT1-4), which started operations in 2003, and a 28-m diameter one (CT5), which was brought online in 2012. It is the only IACT system featuring telescopes of different sizes, which provides sensitivity for gamma rays across a very wide energy range, from ~30 GeV up to ~100 TeV. Since the camera electronics of CT1-4 are much older than the one of CT5, an upgrade is being carried out; first deployment was in 2015, full operation is planned for 2016. The goals of this upgrade are threefold: reducing the dead time of the cameras, improving the overall performance of the array and reducing the system failure rate related to aging. Upon completion, the upgrade will assure the continuous operation of H.E.S.S. at its full sensitivity until and possibly beyond the advent of CTA. In the design of the new components, several CTA concepts and technologies were used and are thus being evaluated in the field: The upgraded read-out electronics is based on the NECTAR readout chips; the new camera front- and back-end control subsystems are based on an FPGA and an embedded ARM computer; the communication between subsystems is based on standard Ethernet technologies. These hardware solutions offer good performance, robustness and flexibility. The design of the new cameras is reported here.Comment: Proceedings of the 34th International Cosmic Ray Conference, 30 July- 6 August, 2015, The Hague, The Netherland

The first GCT camera for the Cherenkov Telescope Array

The Gamma Cherenkov Telescope (GCT) is proposed to be part of the Small Size Telescope (SST) array of the Cherenkov Telescope Array (CTA). The GCT dual-mirror optical design allows the use of a compact camera of diameter roughly 0.4 m. The curved focal plane is equipped with 2048 pixels of ~0.2{\deg} angular size, resulting in a field of view of ~9{\deg}. The GCT camera is designed to record the flashes of Cherenkov light from electromagnetic cascades, which last only a few tens of nanoseconds. Modules based on custom ASICs provide the required fast electronics, facilitating sampling and digitisation as well as first level of triggering. The first GCT camera prototype is currently being commissioned in the UK. On-telescope tests are planned later this year. Here we give a detailed description of the camera prototype and present recent progress with testing and commissioning.Comment: In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.0589

A Vehicular Traffic Flow Model Based on a Stochastic Acceleration Process

A new vehicular traffic flow model based on a stochastic jump process in vehicle acceleration and braking is introduced. It is based on a master equation for the single car probability density in space, velocity and acceleration with an additional vehicular chaos assumption and is derived via a Markovian ansatz for car pairs. This equation is analyzed using simple driver interaction models in the spatial homogeneous case. Velocity distributions in stochastic equilibrium, together with the car density dependence of their moments, i.e. mean velocity and scattering and the fundamental diagram are presented.Comment: 27 pages, 6 figure

Combining random forest and 2D correlation analysis to identify serum spectral signatures for neuro-oncology

Fourier transform infrared (FTIR) spectroscopy has long been established as an analytical tech- nique for the measurement of vibrational modes of molecular systems. More recently, FTIR has been used for the analysis of biofluids with the aim of becoming a tool to aid diagnosis. For the clinician, this represents a convenient, fast, non-subjective option for the study of biofluids and the diagnosis of disease states. The patient also benefits from this method, as the procedure for the collection of serum is much less invasive and stressful than traditional biopsy. This is especially true of patients in whom brain cancer is suspected. A brain biopsy carries a degree of morbidity and mortality and on occasion may even be inconclusive. We therefore present a method for the diagnosis of brain cancer from serum samples using FTIR and machine learning techniques. The scope of the study involved 433 patients from whom were collected 9 spectra each in the range 600-4000 cm−1. To begin development of the novel method, various pre-processing steps were investigated and ranked in terms of final accuracy of the diagnosis. Random Forest machine learning was utilised as a classifier to separate patients into cancer or non-cancer categories based upon the intensities of wavenumbers present in their spectra. Generalised 2D correlational analysis was then employed to further augment the machine learning, and also to establish spec- tral features important for the distinction between cancer and non-cancer serum samples. Using these methods, sensitivities of up to 92.8% and specificities of up to 91.5% were possible. Fur- thermore, ratiometrics were also investigated in order to establish any correlations present in the dataset. We show a rapid, computationally light, accurate, statistically robust methodology for the identification of spectral features present in differing disease states. With current advances in IR technology, such as the development of rapid discrete frequency collection, this approach is import to allow future clinical translation and enables IR to achieve its potential