Sample-Based High-Dimensional Convexity Testing

In the problem of high-dimensional convexity testing, there is an unknown set S in the n-dimensional Euclidean space which is promised to be either convex or c-far from every convex body with respect to the standard multivariate normal distribution. The job of a testing algorithm is then to distinguish between these two cases while making as few inspections of the set S as possible. In this work we consider sample-based testing algorithms, in which the testing algorithm only has access to labeled samples (x,S(x)) where each x is independently drawn from the normal distribution. We give nearly matching sample complexity upper and lower bounds for both one-sided and two-sided convexity testing algorithms in this framework. For constant c, our results show that the sample complexity of one-sided convexity testing is exponential in n, while for two-sided convexity testing it is exponential in the square root of n

Economic Development and Public Transit: Making the Most of the Washington Growth Management Act

Rapid and unplanned urban growth in the urbanizing and rural fringe areas of the United States has led to numerous problems for state, local, and regional governments. In particular, six crises are readily identifiable, each of which threatens to undermine quality of life and local competitive economic advantage. These crises include the following: (1) deterioration of central cities, first-ring suburbs, and closer-in neighborhoods, resulting in depopulation and abandonment of housing and the employment base; (2) spiraling suburban sprawl, creating massive infrastructure as well as energy costs; (3) loss of prime agricultural lands; (4) environmental crises and threats to open space, air and water quality, environmentally sensitive lands, and natural resources; (5) transportation congestion and resultant loss of quality of life; and (6) inflating cost of housing and its effect on affordable housing. These problems do not lend themselves to facile solutions or quick fixes; they must be addressed through the development and application of comprehensive state and regional growth management plans. This Article explores the history and development of growth management and delineates how growth management planning for the Washington Puget Sound region can be effectively implemented to provide a comprehensive system for attaining environmental and transit objectives

Economic Development and Public Transit: Making the Most of the Washington Growth Management Act

Rapid and unplanned urban growth in the urbanizing and rural fringe areas of the United States has led to numerous problems for state, local, and regional governments. In particular, six crises are readily identifiable, each of which threatens to undermine quality of life and local competitive economic advantage. These crises include the following: (1) deterioration of central cities, first-ring suburbs, and closer-in neighborhoods, resulting in depopulation and abandonment of housing and the employment base; (2) spiraling suburban sprawl, creating massive infrastructure as well as energy costs; (3) loss of prime agricultural lands; (4) environmental crises and threats to open space, air and water quality, environmentally sensitive lands, and natural resources; (5) transportation congestion and resultant loss of quality of life; and (6) inflating cost of housing and its effect on affordable housing. These problems do not lend themselves to facile solutions or quick fixes; they must be addressed through the development and application of comprehensive state and regional growth management plans. This Article explores the history and development of growth management and delineates how growth management planning for the Washington Puget Sound region can be effectively implemented to provide a comprehensive system for attaining environmental and transit objectives

Competing protein-protein interactions regulate binding of Hsp27 to its client protein tau.

Small heat shock proteins (sHSPs) are a class of oligomeric molecular chaperones that limit protein aggregation. However, it is often not clear where sHSPs bind on their client proteins or how these protein-protein interactions (PPIs) are regulated. Here, we map the PPIs between human Hsp27 and the microtubule-associated protein tau (MAPT/tau). We find that Hsp27 selectively recognizes two aggregation-prone regions of tau, using the conserved β4-β8 cleft of its alpha-crystallin domain. The β4-β8 region is also the site of Hsp27-Hsp27 interactions, suggesting that competitive PPIs may be an important regulatory paradigm. Indeed, we find that each of the individual PPIs are relatively weak and that competition for shared sites seems to control both client binding and Hsp27 oligomerization. These findings highlight the importance of multiple, competitive PPIs in the function of Hsp27 and suggest that the β4-β8 groove acts as a tunable sensor for clients

Effects of MCNP Model Resolution on Predicting Water Equivalent Thickness of Nanocomposite Materials in High-Energy Proton Fields

Manned missions beyond low-Earth orbit present tremendous, multifaceted radiological challenges. The deep space radiation environment contains high-energy protons and heavy ions, which are not sufficiently shielded by the aluminum alloys that have historically been used in spacecraft. To address these shielding concerns, polymer-based nanocomposites have been proposed. Radiation transport simulations of these nanocomposite materials could reduce the lead time for materials development, however, the level of detail necessary in a model to accurately predict the water equivalent thickness (WET) of a nanoscale material is unknown. In this work, MCNP6.2 is used to simulate the transport of high-energy protons through several models, varying three parameters (experimental setup geometry, particle tracking physics, and nanocomposite geometry), and the results are compared to available experimental measurements. The MCNP results indicate that the inclusion of δ-ray production in the particle tracking physics alters both the magnitude of the Bragg peak and the simulated proton range. Altering the other two parameters showed less than a 1% change in proton range, which is within the statistical error. The simulated WET of the nanocomposite, modeled as a bulk homogeneous material, was comparable to the published experimental results, with a WET of 44.70 mm in a 105 MeV proton beam and 22.61 mm in a 63MeV proton beam, and computed/experimental ratios of 0.9572 and 1.025, respectively

Enhancing e-Infrastructures with Advanced Technical Computing: Parallel MATLAB® on the Grid

MATLAB® is widely used within the engineering and scientific fields as the language and environment for technical computing, while collaborative Grid computing on e-Infrastructures is used by scientific communities to deliver a faster time to solution. MATLAB allows users to express parallelism in their applications, and then execute code on multiprocessor environments such as large-scale e-Infrastructures. This paper demonstrates the integration of MATLAB and Grid technology with a representative implementation that uses gLite middleware to run parallel programs. Experimental results highlight the increases in productivity and performance that users obtain with MATLAB parallel computing on Grids

Denoising inferred functional association networks obtained by gene fusion analysis.

BACKGROUND: Gene fusion detection - also known as the 'Rosetta Stone' method - involves the identification of fused composite genes in a set of reference genomes, which indicates potential interactions between its un-fused counterpart genes in query genomes. The precision of this method typically improves with an ever-increasing number of reference genomes. RESULTS: In order to explore the usefulness and scope of this approach for protein interaction prediction and generate a high-quality, non-redundant set of interacting pairs of proteins across a wide taxonomic range, we have exhaustively performed gene fusion analysis for 184 genomes using an efficient variant of a previously developed protocol. By analyzing interaction graphs and applying a threshold that limits the maximum number of possible interactions within the largest graph components, we show that we can reduce the number of implausible interactions due to the detection of promiscuous domains. With this generally applicable approach, we generate a robust set of over 2 million distinct and testable interactions encompassing 696,894 proteins in 184 species or strains, most of which have never been the subject of high-throughput experimental proteomics. We investigate the cumulative effect of increasing numbers of genomes on the fidelity and quantity of predictions, and show that, for large numbers of genomes, predictions do not become saturated but continue to grow linearly, for the majority of the species. We also examine the percentage of component (and composite) proteins with relation to the number of genes and further validate the functional categories that are highly represented in this robust set of detected genome-wide interactions. CONCLUSION: We illustrate the phylogenetic and functional diversity of gene fusion events across genomes, and their usefulness for accurate prediction of protein interaction and function

Relationship between the tissue-specificity of mouse gene expression and the evolutionary origin and function of the proteins.

BACKGROUND: The combination of complete genome sequence information with expression data enables us to characterize the relationship between a protein's evolutionary origin or functional category and its expression pattern. In this study, mouse proteins were assigned into functional and phyletic groups and the gene expression patterns of the different protein groupings were examined by microarray analysis in various mouse tissues. RESULTS: Our results suggest that the proteins that are universally distributed in all tissues are predominantly enzymes and transporters. In contrast, the tissue-specific set is dominated by regulatory proteins (signal transduction and transcription factors). An increased tendency to tissue-specificity is observed for metazoan-specific proteins. As the composition of the phyletic groups highly correlates with that of the functional groups, the data were tested in order to determine which of the two factors -- function or phyletic age -- is dominant in shaping the expression profile of a protein. The observed differences in expression patterns of genes between functional groups were found mainly to reflect their different phyletic origin. The connection between tissue specificity and phyletic age cannot be explained by the recent rate of evolution. Finally, although metazoan-specific proteins tend to be tissue-specific compared with phyletically conserved proteins present in all domains of life, many such 'universal' proteins are also tissue-specific. CONCLUSION: The minimal cellular transcriptome of the metazoan cell differs from that of the ancestral unicellular eukaryote: new functions were added (metazoan-specific proteins), whilst other functions became specialized and no longer took place in all cells (tissue-specific pre-metazoan proteins).RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Relationship between the tissue-specificity of mouse gene expression and the evolutionary origin and function of the proteins

BACKGROUND: The combination of complete genome sequence information with expression data enables us to characterize the relationship between a protein's evolutionary origin or functional category and its expression pattern. In this study, mouse proteins were assigned into functional and phyletic groups and the gene expression patterns of the different protein groupings were examined by microarray analysis in various mouse tissues. RESULTS: Our results suggest that the proteins that are universally distributed in all tissues are predominantly enzymes and transporters. In contrast, the tissue-specific set is dominated by regulatory proteins (signal transduction and transcription factors). An increased tendency to tissue-specificity is observed for metazoan-specific proteins. As the composition of the phyletic groups highly correlates with that of the functional groups, the data were tested in order to determine which of the two factors - function or phyletic age - is dominant in shaping the expression profile of a protein. The observed differences in expression patterns of genes between functional groups were found mainly to reflect their different phyletic origin. The connection between tissue specificity and phyletic age cannot be explained by the recent rate of evolution. Finally, although metazoan-specific proteins tend to be tissue-specific compared with phyletically conserved proteins present in all domains of life, many such 'universal' proteins are also tissue-specific. CONCLUSION: The minimal cellular transcriptome of the metazoan cell differs from that of the ancestral unicellular eukaryote: new functions were added (metazoan-specific proteins), whilst other functions became specialized and no longer took place in all cells (tissue-specific pre-metazoan proteins)