Application of the parametrical surface-wave prediction model to rapidly varying wind fields during JONSWAP 1973

The capability of a parametrical surface wave model to predict the sea state on a small array for highly variable wind fields is shown for three examples. The model treats the wind sea, for which the nonlinear interaction is most effective, in a parametrical sense. The swell is propagated along characteristics, and the source function for the swell is assumed to be zero. The model output is compared with wave measure- ments from the JONSWAP 73 experimen

State Strategies to Improve Quality and Efficiency: Making the Most of Opportunities in National Health Reform

Examines ten states' initiatives to address key components of quality and efficiency improvement, including data collection, aggregation, and standardization; public reporting; payment reform; consumer engagement; and provider engagement

Identification of three stage-specific proteinases of Plasmodium falciparum.

We have identified and characterized three stage-specific proteinases of Plasmodium falciparum that are active at neutral pH. We analyzed ring-, trophozoite-, schizont-, and merozoite-stage parasites by gelatin substrate PAGE and characterized the identified proteinases with class-specific proteinase inhibitors. No proteinase activity was detected with rings. Trophozoites had a 28 kD proteinase that was inhibited by inhibitors of cysteine proteinases. Mature schizonts had a 35-40 kD proteinase that also was inhibited by cysteine proteinase inhibitors. Merozoite fractions had a 75 kD proteinase that was inhibited by serine proteinase inhibitors. The stage-specific activity of these proteinases and the correlation between the effects of proteinase inhibitors on the isolated enzymes with the effects of the inhibitors on whole parasites suggest potential critical functions for these proteinases in the life cycle of malaria parasites

Gentrification and Neighborhood Housing Cycles: Will America’s Future Downtowns Be Rich?

This paper identifies a new factor, the age of the housing stock, that affects where high- and low-income neighborhoods are located in U.S. cities. High-income households, driven by a high demand for housing services, will tend to locate in areas of the city where the housing stock is relatively young. Because cities develop and redevelop from the center outward over time, the location of these neighborhoods varies over the city’s history. The model predicts a suburban location for the rich in an initial period, when young dwellings are found only in the suburbs, while predicting eventual gentrification once central redevelopment creates a young downtown housing stock. Empirical work indicates that if the influence of spatial variation in dwelling ages were eliminated, longstanding central city/suburban disparities in neighborhood economic status would be reduced by up to 50 percent. Model estimates further predict that between 2000 and 2020, central-city/suburban differences in economic status will widen somewhat in smaller cities but narrow sharply in the largest American cities as they become more gentrified.

Recommended Core Measures for Evaluating the Patient-Centered Medical Home: Cost, Utilization, and Clinical Quality

Outlines the process of the Patient-Centered Medical Home Evaluators' Collaborative for identifying core standardized measures and their recommended principles and measures for evaluating cost and utilization and clinical quality

Gentrification and Neighborhood Housing Cycles: Will America's Future Downtowns be Rich?

This paper identifies a new factor, the age of the housing stock, that affects where high- and low-income neighborhoods are located in U.S. cities. High-income households, driven by a high demand for housing services, will tend to locate in areas of the city where the housing stock is relatively young. Because cities develop and redevelop from the center outward over time, the location of these neighborhoods varies over the city’s history. The model predicts a suburban location for the rich in an initial period, when young dwellings are found only in the suburbs, while predicting eventual gentrification once central redevelopment creates a young downtown housing stock. Empirical work indicates that if the influence of spatial variation in dwelling ages were eliminated, longstanding central city/suburban disparities in neighborhood economic status would be reduced by up to 50 percent. Model estimates further predict that between 2000 and 2020, central-city/suburban differences in economic status will widen somewhat in smaller cities but narrow sharply in the largest American cities as they become more gentrified.spatial expansion of cities, housing cycles, urban expansion

A Network of SLC and ABC Transporter and DME Genes Involved in Remote Sensing and Signaling in the Gut-Liver-Kidney Axis.

Genes central to drug absorption, distribution, metabolism and elimination (ADME) also regulate numerous endogenous molecules. The Remote Sensing and Signaling Hypothesis argues that an ADME gene-centered network-including SLC and ABC "drug" transporters, "drug" metabolizing enzymes (DMEs), and regulatory genes-is essential for inter-organ communication via metabolites, signaling molecules, antioxidants, gut microbiome products, uremic solutes, and uremic toxins. By cross-tissue co-expression network analysis, the gut, liver, and kidney (GLK) formed highly connected tissue-specific clusters of SLC transporters, ABC transporters, and DMEs. SLC22, SLC25 and SLC35 families were network hubs, having more inter-organ and intra-organ connections than other families. Analysis of the GLK network revealed key physiological pathways (e.g., involving bile acids and uric acid). A search for additional genes interacting with the network identified HNF4α, HNF1α, and PXR. Knockout gene expression data confirmed ~60-70% of predictions of ADME gene regulation by these transcription factors. Using the GLK network and known ADME genes, we built a tentative gut-liver-kidney "remote sensing and signaling network" consisting of SLC and ABC transporters, as well as DMEs and regulatory proteins. Together with protein-protein interactions to prioritize likely functional connections, this network suggests how multi-specificity combines with oligo-specificity and mono-specificity to regulate homeostasis of numerous endogenous small molecules