Structured document storage and refined declarative and navigational access mechanisms in HyperStorM

The combination of SGML and database technology allows to refine both declarative and navigational access mechanisms for structured document collection: with regard to declarative access, the user can formulate complex information needs without knowing a query language, the respective document type definition (DTD) or the underlying modelling. Navigational access is eased by hyperlink-rendition mechanisms going beyond plain link-integrity checking. With our approach, the database-internal representation of documents is configurable. It allows for an efficient implementation of operations, because DTD knowledge is not needed for document structure recognition. We show how the number of method invocations and the cost of parsing can be significantly reduced. Edited by Y.C. Tay. Received April 22, 1996 / Accepted March 16, 1997     

Optic neuropathy resembling normal-pressure glaucoma in a teenager with congenital macrodiscs

We report a unique case of a renal transplant patient with a long-term nonprogressive human immunodeficiency virus type-1 (HIV-1) infection and who is asymptomatic despite sustained immunosuppression. Renal function is normal, and HIV infection was probably acquired through blood transfusion before the transplant. Nonprogression may be due either to an effective immune control of HIV replication or to particular genetic aspects of the virus. Several virological investigations were carried out to verify if she is infected with an attenuated virus strain. Results show an unusual combination of high and stable CD4 count, ongoing viral replication and elevated viral loads. Attempts to isolate the virus from plasma were unsuccessful, but isolation was possible from peripheral blood mononuclear cells, and the virus was shown to be non-syncytium-inducing. Sequence analysis of the nef gene revealed no mutation. This exceptional lack of progression of HIV infection under immunosuppressive therapy requires further investigation.     

Low-Thermal-Conductivity Rare-Earth Zirconates for Potential Thermal-Barrier-Coating Applications

Rare-earth zirconates have been identified as a class of low-thermal-conductivity ceramics for possible use in thermal barrier coatings (TBCs) for gas-turbine engine applications. To document and compare the thermal conductivities of important rare-earth zirconates, we have measured the thermal conductivities of the following hot-pressed ceramics: (i) Gd₂Zr₂O₇ (pyrochlore phase), (ii) Gd₂Zr₂O₇ (fluorite phase), (iii) Gd_2.58Zr_1.57O₇ (fluorite phase), (iv) Nd₂Zr₂O₇ (pyrochlore phase), and (v) Sm₂Zr₂O₇ (pyrochlore phase). We have also measured the thermal conductivity of pressureless-sintered 7 wt% yttria-stabilized zirconia (7YSZ)—the commonly used composition in current TBCs. All rare-earth zirconates investigated here showed nearly identical thermal conductivities, all of which were ∼30% lower than the thermal conductivity of 7YSZ in the temperature range 25°–700°C. This finding is discussed qualitatively with reference to thermal-conductivity theory.     

Improved bibliographic reference parsing based on repeated patterns

Parsing details like author names and titles out of bibliographic references of scientific publications is an important issue that has received considerable attention recently. However, most existing techniques are tailored to the highly standardized reference styles used in the last two to three decades. They do not perform well with the wide variety of reference styles used in older, historic publications. Thus, they are of limited use when creating comprehensive bibliographies covering both historic and contemporary scientific publications. This paper presents a generic approach to bibliographic reference parsing, named RefParse, which is independent of any specific reference style. Its core feature is an inference mechanism that exploits the regularities inherent in any list of references to deduce its format. In addition, our approach learns names of authors, journals, and publishers to increase the accuracy in scenarios where human users double check parsing results to increase data quality. Our evaluation shows that our approach performs comparably to existing ones with contemporary reference lists and also works well with older ones.     

Integration of MODIS-derived metrics to assess interannual variability in snowpack, lake ice, and NDVI in southwest Alaska

Impacts of global climate change are expected to result in greater variation in the seasonality of snowpack, lake ice, and vegetation dynamics in southwest Alaska. All have wide-reaching physical and biological ecosystem effects in the region. We used Moderate Resolution Imaging Spectroradiometer (MODIS) calibrated radiance, snow cover extent, and vegetation index products for interpreting interannual variation in the duration and extent of snowpack, lake ice, and vegetation dynamics for southwest Alaska. The approach integrates multiple seasonal metrics across large ecological regions.Throughout the observation period (2001-2007), snow cover duration was stable within ecoregions, with variable start and end dates. The start of the lake ice season lagged the snow season by 2 to 3 months. Within a given lake, freeze-up dates varied in timing and duration, while break-up dates were more consistent. Vegetation phenology varied less than snow and ice metrics, with start-of-season dates comparatively consistent across years. The start of growing season and snow melt were related to one another as they are both temperature dependent. Higher than average temperatures during the El Niño winter of 2002-2003 were expressed in anomalous ice and snow season patterns. We are developing a consistent, MODIS-based dataset that will be used to monitor temporal trends of each of these seasonal metrics and to map areas of change for the study area.     

Developing decision support for dialysis treatment of chronic kidney failure.

The complexity, variability, quantitative nature, and data density of treatment for chronic kidney failure make dialysis information systems excellent candidates for computerized decision support. We describe the development of an intelligent system building on existing knowledge and susceptible to reconfiguration on the basis of knowledge acquired during the use of the system. Various decision support techniques were used to design and develop the decision support modules. This paper briefly reviews the literature on clinical decision support, discusses some of the problems faced by practitioners in managing chronic kidney failure (end-stage renal disease) patients, and sets forth the decision support techniques used in developing a dialysis decision support system.