Search

Accurate radiotherapy plans are a vital tool in combating cancer. The verification of such plans is a computationally intensive task, and providing clinical experts with access to sufficient resources to conduct plan verification simulations in a suitable and timely manner is a genuine challenge. In this paper we present a new approach to the problem, incorporating the Monte Carlo method for treatment verification. A fully integrated radiotherapy treatment verification workflow built on the BEAM simulation package has been developed within the scope of this work. The Monte Carlo approach is recognized as being superior to the standard clinical techniques available. To be useful in clinical practice, accurate results must be generated within a short time frame. Consequently, turnaround times must be predictable, and results must be of a consistently high standard. These requirements are the key challenges that drive this work. The development of this application is being conducted within the context of the Webcom project. Webcom is an interpreter for a graph-oriented model of computing, implemented as a distributed virtual machine. This platform has been used to construct a workflow tool suite and a novel methodology for dynamic resource federation. These components are applied to the execution of Monte Carlo radiotherapy simulation application on heterogeneous dynamically coordinated resources. The Webcom-based model of workflow management facilitates the execution of resource intensive workflows and provides a basis for the development of scalable services in the heterogeneous environments formed through the dynamic aggregation of mixed autonomous resources. We discuss the motivation behind the project and present the methodology, describe the software design of the current implementation, and demonstrates the utility of the system via experiments conducted in a real and deeply heterogeneous testbed environment.

The 1999-2007 Irish National Seabed Survey is one of the largest ocean floor mapping projects ever attempted. Its aim is to map the ocean floor of the Irish territorial waters (approximately 525000km^2). To date, the Geological Survey of Ireland has gathered in excess of 4TB of multibeam sonar data from the Irish National Seabed, and this data set is expected to exceed 10TB upon completion. The main challenge that arises from having so much data is how to extract accurate information given the size of the data set. Geological interpretation is carried out by visual inspection of bathymetric patterns. The size of this, and similar, data sets renders the extraction of knowledge by human observers infeasible. Consequently, the focus has turned to using artificial intelligence and computational methods for assistance. The commercial and environmental sensitivity of the data means that secure data processing and transmission are of paramount importance. This has lead to the creation of the MarineGrid project within the Grid-Ireland organisation. New methods have been developed for statistical analysis of bathymetric information specifically for automated geological interpretation of rock types on the sea floor and feature extraction from the sea floor. We present a discussion on how to provide Marine and Geological researchers convenient yet secure access to resources that make use of grid technologies including pre-written algorithms in order to exploit the Irish National Seabed Survey data archive.

Introduction: Bacterial meningitis is a medical emergency, the outcome of which is improved by prompt antibiotic treatment. For patients with suspected meningitis and no features of severe disease, the British Infection Society recommends immediate lumbar puncture (LP) before antibiotics, to maximise the chance of a positive cerebrospinal (CSF) culture. In such patients, CT scanning before LP is not needed.\ud \ud Methods: The case notes of adults with meningitis admitted to a large district general hospital over 3 years were reviewed. Patients were classified as Likely Bacterial Meningitis or Likely Viral Meningitis based on their CSF and peripheral blood results using the Meningitest Criteria, with microbiological and virological confirmation.\ud \ud Results: Of 92 patients studied, 24 had Likely Bacterial Meningitis, including 16 with microbiologically confirmed disease (none had PCR tests for bacteria). Sixty-eight had Likely Viral Meningitis, four of whom had viral PCR, including one with herpes simplex virus. No patient had an LP before antibiotics. CSF culture was positive for eight (73%) of the 11 patients who had an LP up to 4 h after starting antibiotics, compared with eight (11%) of 71 patients with a later LP (p

Observational High Time Resolution Astrophysics differs from conventional astrophysics in regard to the detectors employed which have a time resolution less than that obtainable through CCD with a normal readout τ < a few minutes. This paper looks at the implications for HTRA from extremely large telescopes and specifically, as an exemplar its possible impact on pulsar astrophysics. We demonstrate, by using the derived point-spread-function from models of the Euro50 telescope, the possible effects active and adaptive mirrors have on observing rapidly varying astronomical objects.

Extremely large telescopes are an opportunity to fully explore a new frontier in astrophysics. Observations of short time‐scale phenomena ranging from flares in normal stars through magnetospheric phenomena in pulsars to turbulence in AGNs will be possible. Observations of quantum phenomena represent an opportunity to directly infer the physical conditions in an astronomical source in an unique way. New detector technology will enable a complete characterisation of the incoming optical radiation with no additional optics. However the current designs for the 42 m European ELT have 5 active or adaptive mirror elements each one of these will introduce their own degree of timing noise with specific temporal characteristics. Here we explore some of the implications of HTRA in the extremely large telescope era.

Spectra are modeled for observations with the ROSAT PSPC, using 3 models namely Thermal Bremsstrahlung, Raymond-Smith and an Absorbed Power law. For each model a range of parameters are modeled. Hardness Ratios are calculated for each simulation and a grid of HR1 versus HR2 is produced for each of the three models. Hardness Ratios, from observations which do not have enough spectral counts to fit spectra directly, may be compared with the grid to set limits on observational parameters e.g temperature.

We present some results on the long term variability of the X-ray emission from optically catalogued galaxies, especially in view of their nuclear properties. For this investigation we use data from the ROSAT PSPC archive. Some future directions are also discussed.

The Geological Survey of Ireland (G.S.I) at present has over 4 terabytes of multi-beam sonar data gathered over the last five years from the seabed within the Irish designated zone as part of the Irish National Seabed Survey (INSS) and this data-set is expected to exceed 10 terabytes upon completion. Geological interpretation is carried out by visual inspection of bathymetric patterns. Due to the size of this data set and the emergence of similar data sets, the extraction of knowledge from such a data sets by human observers has become infeasible. The focus has turned to using artificial intelligence and computational methods for assistance. The commercial and environmental sensitivity of the data means that secure data processing and transmission are of paramount importance. This has lead to the creation of the MarineGrid project within the Grid Ireland organization. New method's have been developed for statistical analysis of bathymetric information specifically for automated geological interpretation of rock types on the sea floor and feature extraction from the sea floor. In this poster we present a brief synopsis of both a classification algorithm and a feature extraction algorithm and the results obtained from within the NUI Galway MarineGrid project.