Parallel vector processing of multidimensional orthogonal transforms for digital signal processing applications

The performance of the parallel vector implementation of the one- and two-dimensional orthogonal transforms is evaluated. The orthogonal transforms are computed using actual or modified fast Fourier transform (FFT) kernels. The factors considered in comparing the speed-up of these vectorized digital signal processing algorithms are discussed and it is shown that the traditional way of comparing th execution speed of digital signal processing algorithms by the ratios of the number of multiplications and additions is no longer effective for vector implementation; the structure of the algorithm must also be considered as a factor when comparing the execution speed of vectorized digital signal processing algorithms. Simulation results on the Cray X/MP with the following orthogonal transforms are presented: discrete Fourier transform (DFT), discrete cosine transform (DCT), discrete sine transform (DST), discrete Hartley transform (DHT), discrete Walsh transform (DWHT), and discrete Hadamard transform (DHDT). A comparison between the DHT and the fast Hartley transform is also included.(34 refs)

Orthogonal polarization spectroscopy to detect mesenteric hypoperfusion

OBJECTIVE: Orthogonal polarization spectral (OPS) imaging is used to assess mucosal microcirculation. We tested sensitivity and variability of OPS in the assessment of mesenteric blood flow (Q (sma)) reduction. SETTING: University Animal Laboratory. INTERVENTIONS: In eight pigs, Q (sma) was reduced in steps of 15% from baseline; five animals served as controls. Jejunal mucosal microcirculatory blood flow was recorded with OPS and laser Doppler flowmetry at each step. OPS data from each period were collected and randomly ordered. Samples from each period were individually chosen by two blinded investigators and quantified [capillary density (number of vessels crossing predefined lines), number of perfused villi] after agreement on the methodology. MEASUREMENT AND RESULTS: Interobserver coefficient of variation (CV) for capillary density from samples representing the same flow condition was 0.34 (0.04-1.41) and intraobserver CV was 0.10 (0.02-0.61). Only one investigator observed a decrease in capillary density [to 62% (48-82%) of baseline values at 45% Q (sma) reduction; P = 0.011], but comparisons with controls never revealed significant differences. In contrast, reduction in perfused villi was detected by both investigators at 75% of mesenteric blood flow reduction. Laser Doppler flow revealed heterogeneous microcirculatory perfusion. CONCLUSIONS: Assessment of capillary density did not reveal differences between animals with and without Q (sma) reduction, and evaluation of perfused villi revealed blood flow reduction only when Q (sma) was very low. Potential explanations are blood flow redistribution and heterogeneity, and suboptimal contrast of OPS images. Despite agreement on the method of analysis, interobserver differences in the quantification of vessel density on gut mucosa using OPS are high.

Agrin defines polarized distribution of orthogonal arrays of particles in astrocytes

Accumulating evidence indicates that agrin, a heparan sulphate proteoglycan of the extracellular matrix, plays a role in the organization and maintenance of the blood-brain barrier. This evidence is based on the differential effects of agrin isoforms on the expression and distribution of the water channel protein, aquaporin-4 (AQP4), on the swelling capacity of cultured astrocytes of neonatal mice and on freeze-fracture data revealing an agrin-dependent clustering of orthogonal arrays of particles (OAPs), the structural equivalent of AQP4. Here, we show that the OAP density in agrin-null mice is dramatically decreased in comparison with wild-types, by using quantitative freeze-fracture analysis of astrocytic membranes. In contrast, anti-AQP4 immunohistochemistry has revealed that the immunoreactivity of the superficial astrocytic endfeet of the agrin-null mouse is comparable with that in wild-type mice. Moreover, in vitro, wild-type and agrin-null astrocytes cultured from mouse embryos at embryonic day 19.5 differ neither in AQP4 immunoreactivity, nor in OAP density in freeze-fracture replicas. Analyses of brain tissue samples and cultured astrocytes by reverse transcription with the polymerase chain reaction have not demonstrated any difference in the level of AQP4 mRNA between wild-type astrocytes and astrocytes from agrin-null mice. Furthermore, we have been unable to detect any difference in the swelling capacity between wild-type and agrin-null astrocytes. These results clearly demonstrate, for the first time, that agrin plays a pivotal role for the clustering of OAPs in the endfoot membranes of astrocytes, whereas the mere presence of AQP4 is not sufficient for OAP clustering.

Nucleic acid sensing by an orthogonal reporter system based on homo-DNA

We have developed an assay for single strand DNA or RNA detection which is based on the homo-DNA templated Staudinger reduction of the profluorophore rhodamine-azide. The assay is based on a three component system, consisting of a homo-DNA/DNA hybrid probe, a set of homo-DNA reporter strands and the target DNA or RNA. We present two different formats of the assay (Omega probe and linear probe) in which the linear probe was found to perform best with catalytic turnover of the reporter strands (TON: 8) and a match/mismatch discrimination of up to 19. The advantage of this system is that the reporting (homo-DNA) and sensing (DNA) domain are decoupled from each other since the two pairing systems are bioorthogonal. This allows independent optimization of either domain which may lead to higher selectivity in in vivo imaging.

Cross-Country Evidence on Output Growth Volatility: Nonstationary Variance and GARCH Models

This paper revisits the issue of conditional volatility in real GDP growth rates for Canada, Japan, the United Kingdom, and the United States. Previous studies find high persistence in the volatility. This paper shows that this finding largely reflects a nonstationary variance. Output growth in the four countries became noticeably less volatile over the past few decades. In this paper, we employ the modified ICSS algorithm to detect structural change in the unconditional variance of output growth. One structural break exists in each of the four countries. We then use generalized autoregressive conditional heteroskedasticity (GARCH) specifications modeling output growth and its volatility with and without the break in volatility. The evidence shows that the time-varying variance falls sharply in Canada, Japan, and the U.K. and disappears in the U.S., excess kurtosis vanishes in Canada, Japan, and the U.S. and drops substantially in the U.K., once we incorporate the break in the variance equation of output for the four countries. That is, the integrated GARCH (IGARCH) effect proves spurious and the GARCH model demonstrates misspecification, if researchers neglect a nonstationary unconditional variance.

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Wet and dry resistivities along three orthogonal directions of ODP Holes 185-801C and 185-1149B

The results of shore-based three-axis resistivity and X-ray computed tomography (CT) measurements on cube-shaped samples recovered during Leg 185 are presented along with moisture and density, P-wave velocity, resistivity, and X-ray CT measurements on whole-round samples of representative lithologies from Site 1149. These measurements augment the standard suite of physical properties obtained during Leg 185 from the cube samples and samples obtained adjacent to the cut cubes. Both shipboard and shore-based measurements of physical properties provide information that assists in characterizing lithologic units, correlating cored material with downhole logging data, understanding the nature of consolidation, and interpreting seismic reflection profiles.