Associations between apolipoprotein E genotype and circulating F<Subscript>2</Subscript>-isoprostane levels in humans

Apolipoprotein E (apoE), an important determinant of plasma lipoprotein metabolism, has three common alleles (ε2, ε3, and ε4). Population studies have shown that the risk of diseases characterized by oxidative damage, such as coronary heart disease and Alzheimer’s disease, is significantly higher in ɛ4 carriers. We evaluated the association between apoE genotypes and plasma F₂-isoprostane levels, an index of lipid peroxidation, in humans. Two hundred seventy-four healthy subjects (104 males, 170 females; 46.9±13.0 yr; 200 whites, 74 blacks; 81 nonsmokers, 64 passive smokers, and 129 active smokers) recruited for a randomized clinical antioxidant intervention trial were included in this analysis. ApoE genotype was determined by PCR and restriction enzyme digestion. Free plasma F₂-isoprostane was measured by GC-MS. Genotype groups were compared using multiple regression analysis with adjustment for sex, age, race, smoking status, body mass index, plasma ascorbic acid, and β-carotene. Subjects with ε3/ε4 and ε4/ε4 genotype (ε4-carriers) and with ε2/ε3 and ε3/ε3 (non-ε4-carriers) were pooled for analysis. In subjects with high cholesterol levels (total cholesterol above 200 mg/dl), plasma F₂-isoprostane levels were 29% higher in ε4 carriers than in non-ε4-carriers (P=0.0056). High-cholesterol subjects that are ε4 carriers have significantly higher levels of lipid peroxidation as assessed by circulating F₂-isoprostane levels.     

Privacy Preserving Geo-Linkage in the Big Urban Data Era

Big data technologies and a range of Government open data initiatives provide the basis for discovering new insights into cities; how they are planned, how they managed and the day-to-day challenges they face in health, transport and changing population profiles. The Australian Urban Research Infrastructure Network (AURIN – www.aurin.org.au) project is one example of such a big data initiative that is currently running across Australia. AURIN provides a single gateway providing online (live) programmatic access to over 2000 data sets from over 70 major and typically definitive data-driven organizations across federal and State government, across industry and across academia. However whilst open (public) data is useful to bring data-driven intelligence to cities, more often than not, it is the data that is not-publicly accessible that is essential to understand city challenges and needs. Such sensitive (unit-level) data has unique requirements on access and usage to meet the privacy and confidentiality demands of the associated organizations. In this paper we highlight a novel geo-privacy supporting solution implemented as part of the AURIN project that provides seamless and secure access to individual (unit-level) data from the Department of Health in Victoria. We illustrate this solution across a range of typical city challenges in localized contexts around Melbourne. We show how unit level data can be combined with other data in a privacy-protecting manner. Unlike other secure data access and usage solutions that have been developed/deployed, the AURIN solution allows any researcher to access and use the data in a manner that meets all of the associated privacy and confidentiality concerns, without obliging them to obtain ethical approval or any other hurdles that are normally put in place on access to and use of sensitive data. This provides a paradigm shift in secure access to sensitive data with geospatial content.     

Model-based and Fuzzy Logic Approaches to Condition Monitoring of Operational Wind Turbines

 It is common for wind turbines to be installed in remote locations on land or offshore, leading to difficulties in routine inspection and maintenance. Further, wind turbines in these locations are often subject to harsh operating conditions. These challenges mean there is a requirement for a high degree of maintenance. The data generated by monitoring systems can be used to obtain models of wind turbines operating under different conditions, and hence predict output signals based on known inputs. A model-based condition monitoring system can be implemented by comparing output data obtained from operational turbines with those predicted by the models, so as to detect changes that could be due to the presence of faults. This paper discusses several techniques for model-based condition monitoring systems: linear models, artificial neural networks, and state dependent parameter "pseudo" transfer functions. The models are identified using supervisory control and data acquisition (SCADA) data acquired from an operational wind firm. It is found that the multiple-input single-output state dependent parameter method outperforms both multivariate linear and artificial neural network-based approaches. Subsequently, state dependent parameter models are used to develop adaptive thresholds for critical output signals. In order to provide an early warning of a developing fault, it is necessary to interpret the amount by which the threshold is exceeded, together with the period of time over which this occurs. In this regard, a fuzzy logic-based inference system is proposed and demonstrated to be practically feasible.     

A simple approach to neutral atom microscopy

Scanning surfaces using a beam of noncharged atoms or molecules allows for especially nondestructive and low-energy surface imaging, with the potential to obtain new information about surfaces that cannot be easily obtained otherwise. We have developed a new approach, operating with the sample at a close working distance from an aperture, the need for optics to focus the beam is obviated. Compared to more complex approaches, the theoretical performance has no other disadvantage than the short working distance. Resolution of 1.5 μm has been achieved, and submicron resolution appears to be practical. Construction of the microscope and results are presented, including first images done in reflection mode, theory for optimization of the design and avenues for future improvement.     

THOMAS FLEISHMAN On The Role of IS in Health Care

Abstract

MORE THAN 50 PERCENT OF firms are expected to use IT outsourcing in 2006. the sourcing issue is among the top five agenda items for IT executives, as the amount of such outsourcing grows, its impact on the economies of companies and nations increases and political controversy over the consequent jobs lost to off-shore outsourcing heightens. Thus, outsourcing is, and will likely continue to be, a hot professional and political topic and a major determinant of the future of IT.     

The Fine Art of Communicating

Communication problems are more widespread than we think. It's time to realize why MIS management, users, and vendors use the same words but fail to reach common ground.     

Accelerating Ray Tracing using Constrained Tetrahedralizations

In this paper we introduce the constrained tetrahedralization as a new acceleration structure for ray tracing. A constrained tetrahedralization of a scene is a tetrahedralization that respects the faces of the scene geometry. The closest intersection of a ray with a scene is found by traversing this tetrahedralization along the ray, one tetrahedron at a time. We show that constrained tetrahedralizations are a viable alternative to current acceleration structures, and that they have a number of unique properties that set them apart from other acceleration structures: constrained tetrahedralizations are not hierarchical yet adaptive; the complexity of traversing them is a function of local geometric complexity rather than global geometric complexity; constrained tetrahedralizations support deforming geometry without any effort; and they have the potential to unify several data structures currently used in global illumination.