University of Southampton

About: University of Southampton is a education organization based out in Southampton, United Kingdom. It is known for research contribution in the topics: Population & Laser. The organization has 37184 authors who have published 99400 publications receiving 3462915 citations. The organization is also known as: Southampton University & Soton Uni.

Examining the Challenges of Scientific Workflows

Abstract: Workflows have emerged as a paradigm for representing and managing complex distributed computations and are used to accelerate the pace of scientific progress. A recent National Science Foundation workshop brought together domain, computer, and social scientists to discuss requirements of future scientific applications and the challenges they present to current workflow technologies.

Searching for dark matter annihilation in recently discovered Milky Way Satellites with Fermi-LAT

Abstract: We search for excess gamma-ray emission coincident with the positions of confirmed and candidate Milky Way satellite galaxies using six years of data from the Fermi Large Area Telescope (LAT). Our sample of 45 stellar systems includes 28 kinematically confirmed dark-matter-dominated dwarf spheroidal galaxies (dSphs) and 17 recently discovered systems that have photometric characteristics consistent with the population of known dSphs. For each of these targets, the relative predicted gamma-ray flux due to dark matter annihilation is taken from kinematic analysis if available, and estimated from a distance-based scaling relation otherwise, assuming that the stellar systems are DM-dominated dSphs. LAT data coincident with four of the newly discovered targets show a slight preference (each ~ 2sigma local) for gamma-ray emission in excess of the background. However, the ensemble of derived gamma-ray flux upper limits for individual targets is consistent with the expectation from analyzing random blank-sky regions, and a combined analysis of the population of stellar systems yields no globally significant excess (global significance < 1sigma ). Our analysis has increased sensitivity compared to the analysis of 15 confirmed dSphs by Ackermann et al. The observed constraints on the DM annihilation cross section are statistically consistent with the background expectation, improving by a factor of ~2 for large DM masses ({m}{DM,b\bar{b}}≳ 1 {TeV} and {m}{DM,{tau }+{tau }-}≳ 70 {GeV}) and weakening by a factor of ~1.5 at lower masses relative to previously observed limits.

Evidence-based guidelines for the pharmacological treatment of anxiety disorders: recommendations from the British Association for Psychopharmacology

Abstract: These British Association for Psychopharmacology guidelines cover the range and aims of treatment for anxiety disorders. They are based explicitly on the available evidence and are presented as recommendations to aid clinical decision making in primary and secondary medical care. They may also serve as a source of information for patients and their carers. The recommendations are presented together with a more detailed review of the available evidence. A consensus meeting involving experts in anxiety disorders reviewed the main subject areas and considered the strength of evidence and its clinical implications. The guidelines were constructed after extensive feedback from participants and interested parties. The strength of supporting evidence for recommendations was rated. The guidelines cover the diagnosis of anxiety disorders and key steps in clinical management, including acute treatment, relapse prevention and approaches for patients who do not respond to first-line treatments.

Discrimination between strain and temperature effects using dual-wavelength fibre grating sensors

Abstract: The spectral behaviour of two superimposed fibre gratings having different Bragg wavelengths (850 and 1300 nm) with respect to strain and temperature has been studied. The results show that the ratio of sensitivity at two Bragg wavelengths is dependent on strain and temperature, which can be used for simultaneous measurement of these parameters using a single sensing element.

Evolutionary Optimization of Computationally Expensive Problems via Surrogate Modeling

Abstract: We present a parallel evolutionary optimization algorithm that leverages surrogate models for solving computationally expensive design problems with general constraints, on a limited computational budget. The essential backbone of our framework is an evolutionary algorithm coupled with a feasible sequential quadratic programming solver in the spirit of Lamarckian learning. We employ a trust-region approach for interleaving use of exact modelsfortheobjectiveandconstraintfunctionswithcomputationallycheapsurrogatemodelsduringlocalsearch. In contrastto earlier work, we construct local surrogatemodels using radial basis functionsmotivated by theprinciple of transductive inference. Further, the present approach retains the intrinsic parallelism of evolutionary algorithms and can hence be readily implemented on grid computing infrastructures. Experimental results are presented for some benchmark test functions and an aerodynamic wing design problem to demonstrate that our algorithm converges to good designs on a limited computational budget.