False discovery rate analysis of brain diffusion direction maps

Diffusion tensor imaging (DTI) is a novel modality of magnetic resonance imaging that allows noninvasive mapping of the brain's white matter. A particular map derived from DTI measurements is a map of water principal diffusion directions, which are proxies for neural fiber directions. We consider a study in which diffusion direction maps were acquired for two groups of subjects. The objective of the analysis is to find regions of the brain in which the corresponding diffusion directions differ between the groups. This is attained by first computing a test statistic for the difference in direction at every brain location using a Watson model for directional data. Interesting locations are subsequently selected with control of the false discovery rate. More accurate modeling of the null distribution is obtained using an empirical null density based on the empirical distribution of the test statistics across the brain. Further, substantial improvements in power are achieved by local spatial averaging of the test statistic map. Although the focus is on one particular study and imaging technology, the proposed inference methods can be applied to other large scale simultaneous hypothesis testing problems with a continuous underlying spatial structure.Comment: Published in at http://dx.doi.org/10.1214/07-AOAS133 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

A Computational Study of Nicotine Conformations in the Gas Phase and in Water

The conformational preferences of nicotine in three protonation states and in the gas phase as well as aqueous solution are investigated using several computational procedures. Conformational aspects emphasized are N-methyl stereochemistry, relative rotation of the pyridine and pyrrolidine rings, and pyrrolidine ring conformation. All methods consistently predicted that the N-methyl trans species are most stable for all protonation states in both gas phase and in water. However, the cis/trans energy gap is significantly reduced in water. Additionally, the two pyridine ring rotamers, which are energetically equivalent in the gas phase, experience different solvation energies in water

Optimal Clustering under Uncertainty

Classical clustering algorithms typically either lack an underlying probability framework to make them predictive or focus on parameter estimation rather than defining and minimizing a notion of error. Recent work addresses these issues by developing a probabilistic framework based on the theory of random labeled point processes and characterizing a Bayes clusterer that minimizes the number of misclustered points. The Bayes clusterer is analogous to the Bayes classifier. Whereas determining a Bayes classifier requires full knowledge of the feature-label distribution, deriving a Bayes clusterer requires full knowledge of the point process. When uncertain of the point process, one would like to find a robust clusterer that is optimal over the uncertainty, just as one may find optimal robust classifiers with uncertain feature-label distributions. Herein, we derive an optimal robust clusterer by first finding an effective random point process that incorporates all randomness within its own probabilistic structure and from which a Bayes clusterer can be derived that provides an optimal robust clusterer relative to the uncertainty. This is analogous to the use of effective class-conditional distributions in robust classification. After evaluating the performance of robust clusterers in synthetic mixtures of Gaussians models, we apply the framework to granular imaging, where we make use of the asymptotic granulometric moment theory for granular images to relate robust clustering theory to the application.Comment: 19 pages, 5 eps figures, 1 tabl

Software Risk Identification for Interplanetary Probes

The need for a systematic and effective software risk identification methodology is critical for interplanetary probes that are using increasingly complex and critical software. Several probe failures are examined that suggest more attention and resources need to be dedicated to identifying software risks. The direct causes of these failures can often be traced to systemic problems in all phases of the software engineering process. These failures have lead to the development of a practical methodology to identify risks for interplanetary probes. The proposed methodology is based upon the tailoring of the Software Engineering Institute's (SEI) method of taxonomy-based risk identification. The use of this methodology will ensure a more consistent and complete identification of software risks in these probes

Maternal fluoxetine exposure alters cortical hemodynamic and calcium response of offspring to somatosensory stimuli

Epidemiological studies have found an increased incidence of neurodevelopmental disorders in populations prenatally exposed to selective serotonin reuptake inhibitors (SSRIs). Optical imaging provides a minimally invasive way to determine if perinatal SSRI exposure has long-term effects on cortical function. Herein we probed the functional neuroimaging effects of perinatal SSRI exposure in a fluoxetine (FLX)-exposed mouse model. While resting-state homotopic contralateral functional connectivity was unperturbed, the evoked cortical response to forepaw stimulation was altered in FLX mice. The stimulated cortex showed decreased activity for FLX versus controls, by both hemodynamic responses [oxyhemoglobin (Hb

Ejector Enhanced Pulsejet Based Pressure Gain Combustors: An Old Idea With a New Twist

An experimental investigation of pressure-gain combustion for gas turbine application is described. The test article consists of an off-the-shelf valved pulsejet, and an optimized ejector, both housed within a shroud. The combination forms an effective can combustor across which there is a modest total pressure rise rather than the usual loss found in conventional combustors. Although the concept of using a pulsejet to affect semi-constant volume (i.e., pressure-gain) combustion is not new, that of combining it with a well designed ejector to efficiently mix the bypass flow is. The result is a device which to date has demonstrated an overall pressure rise of approximately 3.5 percent at an overall temperature ratio commensurate with modern gas turbines. This pressure ratio is substantially higher than what has been previously reported in pulsejet-based combustion experiments. Flow non-uniformities in the downstream portion of the device are also shown to be substantially reduced compared to those within the pulsejet itself. The standard deviation of total pressure fluctuations, measured just downstream of the ejector was only 5.0 percent of the mean. This smoothing aspect of the device is critical to turbomachinery applications since turbine performance is, in general, negatively affected by flow non-uniformities and unsteadiness. The experimental rig will be described and details of the performance measurements will be presented. Analyses showing the thermodynamic benefits from this level of pressure-gain performance in a gas turbine will also be assessed for several engine types. Issues regarding practical development of such a device are discussed, as are potential emissions reductions resulting from the rich burning nature of the pulsejet and the rapid mixing (quenching) associated with unsteady ejectors

Experimental Persistence Probability for Fluctuating Steps

The persistence behavior for fluctuating steps on the $Si(111)$ $(\sqrt3 \times \sqrt3)R30^{0} - Al$ surface was determined by analyzing time-dependent STM images for temperatures between 770 and 970K. The measured persistence probability follows a power law decay with an exponent of $\theta=0.77 \pm 0.03$. This is consistent with the value of $\theta= 3/4$ predicted for attachment/detachment limited step kinetics. If the persistence analysis is carried out in terms of return to a fixed reference position, the measured persistence probability decays exponentially. Numerical studies of the Langevin equation used to model step motion corroborate the experimental observations.Comment: LaTeX, 11 pages, 4 figures, minor changes in References sectio

Structure of a Cyclophane Host Molecule

The cyclophane tetramethyl 3,8,13,18a,2l,26,31,36aoctahydro- 4,6:9,12:22,24:27,30-tetraetheno-l5,18,21:-33,36,39-diethenylylidenedibenzo[k,ɑl][1,8,17,24]tetraoxacyclodotriacontene-1,2,19,20-tetracarboxylate acetonitrile solvate, C_(56)H_(44)O_(12).CH_3C=N, contains a large cavity and forms host-guest complexes in solution with a variety of quaternary nitrogen compounds. Crystallization from an acetonitrile solution that contained damantyltrimethylammonium iodide led, though, to crystals of the uncomplexed cyclophane (but containing one molecule of acetonitrile of crystallization). The cavity, about 7.6 x 4.0 Å and roughly rectangular in cross section, is occupied by ester groupings from two adjacent cyclophanes, entering from opposite sides. Crystal data: orthorhombic, P2_12_12_1, with a= 11.741 (6), b = 16.155 (5), c = 25.895 (7) Å, v = 4912 Å^3, T = 296 K, Z = 4, M_r= 950.01, D_x = 1.28 g cm^(-3), F(000) = 1992, Mo Kɑ, λ = 0.7107 Å, μ = 0.84 cm^(-1), R = 0.0538 for 2410 independent reflections with I> 0, S = 2.29 for 2610 total reflections