Wake angle for surface gravity waves on a finite depth fluid

Linear water wave theory suggests that wave patterns caused by a steadily moving disturbance are contained within a wedge whose half-angle depends on the depth-based Froude number $F_H$. For the problem of flow past an axisymmetric pressure distribution in a finite-depth channel, we report on the apparent angle of the wake, which is the angle of maximum peaks. For moderately deep channels, the dependence of the apparent wake angle on the Froude number is very different to the wedge angle, and varies smoothly as $F_H$ passes through the critical value $F_H=1$. For shallow water, the two angles tend to follow each other more closely, which leads to very large apparent wake angles for certain regimes.

Lipid-modified azurin of Neisseria meningitidis is a copper protein localized on the outer membrane surface and not regulated by FNR

The laz gene of Neisseria meningitidis is predicted to encode a lipid-modified azurin (Laz). Laz is very similar to azurin, a periplasmic protein, which belongs to the copper-containing proteins in the cupredoxin superfamily. In other bacteria, azurin is an electron donor to nitrite reductase, an important enzyme in the denitrifying process. It is not known whether Laz could function as an electron transfer protein in this important pathogen. Laz protein was heterologously expressed in Escherichia coli and purified. Electrospray mass spectrometry indicated that the Laz protein contains one copper ion. Laz was shown to be redox-active in the presence of its redox center copper ion. When oxidized, Laz exhibits an intense blue colour and absorbs visible light around 626 nm. The absorption is lost when exposed to diethyldithiocarbamate, a copper chelating agent. Polyclonal antibodies were raised against purified Laz for detecting expression of Laz under different growth conditions and to determine the orientation of Laz on the outer membrane. The expression of Laz under microaerobic and microaerobic denitrifying conditions was slightly higher than that under aerobic conditions. However, the expression of Laz was similar between the wild type strain and an fnr mutant, suggesting that Fumarate/Nitrate reduction regulator (FNR) does not regulate the expression of Laz despite the presence of a partial FNR box upstream of the laz gene. We propose that some Laz protein is exposed on the outer membrane surface of N. meningitidis as the αLaz antibodies can increase killing by complement in a capsule deficient N. meningitidis strain, in a dose-dependent fashion.

The development of virtual leaf surface models for interactive agrichemical spray applications

This project constructed virtual plant leaf surfaces from digitised data sets for use in droplet spray models. Digitisation techniques for obtaining data sets for cotton, chenopodium and wheat leaves are discussed and novel algorithms for the reconstruction of the leaves from these three plant species are developed. The reconstructed leaf surfaces are included into agricultural droplet spray models to investigate the effect of the nozzle and spray formulation combination on the proportion of spray retained by the plant. A numerical study of the post-impaction motion of large droplets that have formed on the leaf surface is also considered.

Lactose surface modification by decantation: Are drug-fine lactose ratios the key to better dispersion of salmeterol xinafoate from lactose-interactive mixtures?

Purpose The role of fine lactose in the dispersion of salmeterol xinafoate (SX) from lactose mixtures was studied by modifying the fine lactose concentration on the surface of the lactose carriers using wet decantation. Methods Fine lactose was removed from lactose carriers by wet decantation using ethanol saturated with lactose. Particle sizing was achieved by laser diffraction. Fine particle fractions (FPFs) were determined by Twin Stage Impinger using a 2.5% SX mixture, and SX was analyzed by a validated high-performance liquid chromatography method. Adhesion forces between probes of SX and silica and the lactose surfaces were determined by atomic force microscopy. Results FPFs of SX were related to fine lactose concentration in the mixture for inhalation grade lactose samples. Reductions in FPF (2-4-fold) of Aeroflo 95 and 65 were observed after removing fine lactose by wet decantation; FPFs reverted to original values after addition of micronized lactose to decanted mixtures. FPFs of SX of sieved and decanted fractions of Aeroflo carriers were significantly different (p < 0.001). The relationship between FPF and fine lactose concentration was linear. Decanted lactose demonstrated surface modification through increased SX-lactose adhesion forces; however, any surface modification other than removal of fine lactose only slightly influenced FPF. Conclusions Fine lactose played a key and dominating role in controlling FPF. SX to fine lactose ratios influenced dispersion of SX with maximum dispersion occurring as the ratio approached unity.

Inhaled particle surface area dose: Stationary vs personal monitoring

The aim of this paper is to determine the suitability of solely stationary measurements for exposure assessment and management applications. For this purpose, quantified inhaled particle surface area (IPSA) doses using both stationary and personal particle exposure monitors were evaluated and compared.

Numerical treatment of a two-dimensional variable-order fractional nonlinear reaction-diffusion model

A two-dimensional variable-order fractional nonlinear reaction-diffusion model is considered. A second-order spatial accurate semi-implicit alternating direction method for a two-dimensional variable-order fractional nonlinear reaction-diffusion model is proposed. Stability and convergence of the semi-implicit alternating direct method are established. Finally, some numerical examples are given to support our theoretical analysis. These numerical techniques can be used to simulate a two-dimensional variable order fractional FitzHugh-Nagumo model in a rectangular domain. This type of model can be used to describe how electrical currents flow through the heart, controlling its contractions, and are used to ascertain the effects of certain drugs designed to treat arrhythmia.

GPU accelerated algorithms for computing matrix function vector products with applications to exponential integrators and fractional diffusion

The efficient computation of matrix function vector products has become an important area of research in recent times, driven in particular by two important applications: the numerical solution of fractional partial differential equations and the integration of large systems of ordinary differential equations. In this work we consider a problem that combines these two applications, in the form of a numerical solution algorithm for fractional reaction diffusion equations that after spatial discretisation, is advanced in time using the exponential Euler method. We focus on the efficient implementation of the algorithm on Graphics Processing Units (GPU), as we wish to make use of the increased computational power available with this hardware. We compute the matrix function vector products using the contour integration method in [N. Hale, N. Higham, and L. Trefethen. Computing Aα, log(A), and related matrix functions by contour integrals. SIAM J. Numer. Anal., 46(5):2505–2523, 2008]. Multiple levels of preconditioning are applied to reduce the GPU memory footprint and to further accelerate convergence. We also derive an error bound for the convergence of the contour integral method that allows us to pre-determine the appropriate number of quadrature points. Results are presented that demonstrate the effectiveness of the method for large two-dimensional problems, showing a speedup of more than an order of magnitude compared to a CPU-only implementation.

Molecular recognition of 2,4,6-trinitrotoluene by 6-aminohexanethiol and surface-enhanced Raman scattering sensor

2,4,6-trinitrotoluene (TNT) is one of the most commonly used nitro aromatic explosives in landmine, military and mining industry. This article demonstrates rapid and selective identification of TNT by surface-enhanced Raman spectroscopy (SERS) using 6-aminohexanethiol (AHT) as a new recognition molecule. First, Meisenheimer complex formation between AHT and TNT is confirmed by the development of pink colour and appearance of new band around 500 nm in UV-visible spectrum. Solution Raman spectroscopy study also supported the AHT:TNT complex formation by demonstrating changes in the vibrational stretching of AHT molecule between 2800-3000 cm−1. For surface enhanced Raman spectroscopy analysis, a self-assembled monolayer (SAM) of AHT is formed over the gold nanostructure (AuNS) SERS substrate in order to selectively capture TNT onto the surface. Electrochemical desorption and X-ray photoelectron studies are performed over AHT SAM modified surface to examine the presence of free amine groups with appropriate orientation for complex formation. Further, AHT and butanethiol (BT) mixed monolayer system is explored to improve the AHT:TNT complex formation efficiency. Using a 9:1 AHT:BT mixed monolayer, a very low detection limit (LOD) of 100 fM TNT was realized. The new method delivers high selectivity towards TNT over 2,4 DNT and picric acid. Finally, real sample analysis is demonstrated by the extraction and SERS detection of 302 pM of TNT from spiked.

Surface electromyography during physical exercise in water: A systematic review

Background Aquatic exercise has been widely used for rehabilitation and functional recovery due to its physical and physiological benefits. However, there is a high variability in reporting on the muscle activity from surface electromyographic (sEMG) signals. The aim of this study is to present an updated review of the literature on the state of the art of muscle activity recorded using sEMG during activities and exercise performed by humans in water. Methods A literature search was performed to identify studies of aquatic exercise movement. Results Twenty-one studies were selected for critical appraisal. Sample size, functional tasks analyzed, and muscles recorded were studied for each paper. The clinical contribution of the paper was evaluated. Conclusions Muscle activity tends to be lower in water-based compared to land-based activity; however more research is needed to understand why. Approaches from basic and applied sciences could support the understanding of relevant aspects for clinical practice.

Prediction of maximal surface electromyographically based voluntary contractions of erector spinae muscles from sonographic measurements during isometric contractions

Objectives Currently, there are no studies combining electromyography (EMG) and sonography to estimate the absolute and relative strength values of erector spinae (ES) muscles in healthy individuals. The purpose of this study was to establish whether the maximum voluntary contraction (MVC) of the ES during isometric contractions could be predicted from the changes in surface EMG as well as in fiber pennation and thickness as measured by sonography. Methods Thirty healthy adults performed 3 isometric extensions at 45° from the vertical to calculate the MVC force. Contractions at 33% and 100% of the MVC force were then used during sonographic and EMG recordings. These measurements were used to observe the architecture and function of the muscles during contraction. Statistical analysis was performed using bivariate regression and regression equations. Results The slope for each regression equation was statistically significant (P < .001) with R2 values of 0.837 and 0.986 for the right and left ES, respectively. The standard error estimate between the sonographic measurements and the regression-estimated pennation angles for the right and left ES were 0.10 and 0.02, respectively. Conclusions Erector spinae muscle activation can be predicted from the changes in fiber pennation during isometric contractions at 33% and 100% of the MVC force. These findings could be essential for developing a regression equation that could estimate the level of muscle activation from changes in the muscle architecture.

A comparison land-water environment of maximal voluntary isometric contraction during manual muscle testing through surface electromyography

Background The aim of this study was to compare through surface electromyographic (sEMG) recordings of the maximum voluntary contraction (MVC) on dry land and in water by manual muscle test (MMT). Method Sixteen healthy right-handed subjects (8 males and 8 females) participated in measurement of muscle activation of the right shoulder. The selected muscles were the cervical erector spinae, trapezius, pectoralis, anterior deltoid, middle deltoid, infraspinatus and latissimus dorsi. The MVC test conditions were random with respect to the order on the land/in water. Results For each muscle, the MVC test was performed and measured through sEMG to determine differences in muscle activation in both conditions. For all muscles except the latissimus dorsi, no significant differences were observed between land and water MVC scores (p = 0.063–0.679) and precision (%Diff = 7–10%) were observed between MVC conditions in the muscles trapezius, anterior deltoid and middle deltoid. Conclusions If the procedure for data collection is optimal, under MMT conditions it appears that comparable MVC sEMG values were achieved on land and in water and the integrity of the EMG recordings were maintained during wáter immersion.

Extending genetic linkage analysis to diffusion tensor images to map single gene effects on brain fiber architecture

We extended genetic linkage analysis - an analysis widely used in quantitative genetics - to 3D images to analyze single gene effects on brain fiber architecture. We collected 4 Tesla diffusion tensor images (DTI) and genotype data from 258 healthy adult twins and their non-twin siblings. After high-dimensional fluid registration, at each voxel we estimated the genetic linkage between the single nucleotide polymorphism (SNP), Val66Met (dbSNP number rs6265), of the BDNF gene (brain-derived neurotrophic factor) with fractional anisotropy (FA) derived from each subject's DTI scan, by fitting structural equation models (SEM) from quantitative genetics. We also examined how image filtering affects the effect sizes for genetic linkage by examining how the overall significance of voxelwise effects varied with respect to full width at half maximum (FWHM) of the Gaussian smoothing applied to the FA images. Raw FA maps with no smoothing yielded the greatest sensitivity to detect gene effects, when corrected for multiple comparisons using the false discovery rate (FDR) procedure. The BDNF polymorphism significantly contributed to the variation in FA in the posterior cingulate gyrus, where it accounted for around 90-95% of the total variance in FA. Our study generated the first maps to visualize the effect of the BDNF gene on brain fiber integrity, suggesting that common genetic variants may strongly determine white matter integrity.

Brain fiber architecture, genetics, and intelligence: a high angular resolution diffusion imaging (HARDI) study

We developed an analysis pipeline enabling population studies of HARDI data, and applied it to map genetic influences on fiber architecture in 90 twin subjects. We applied tensor-driven 3D fluid registration to HARDI, resampling the spherical fiber orientation distribution functions (ODFs) in appropriate Riemannian manifolds, after ODF regularization and sharpening. Fitting structural equation models (SEM) from quantitative genetics, we evaluated genetic influences on the Jensen-Shannon divergence (JSD), a novel measure of fiber spatial coherence, and on the generalized fiber anisotropy (GFA) a measure of fiber integrity. With random-effects regression, we mapped regions where diffusion profiles were highly correlated with subjects' intelligence quotient (IQ). Fiber complexity was predominantly under genetic control, and higher in more highly anisotropic regions; the proportion of genetic versus environmental control varied spatially. Our methods show promise for discovering genes affecting fiber connectivity in the brain.

Mapping genetic influences on brain fiber architecture with high angular resolution diffusion imaging (HARDI)

We report the first 3D maps of genetic effects on brain fiber complexity. We analyzed HARDI brain imaging data from 90 young adult twins using an information-theoretic measure, the Jensen-Shannon divergence (JSD), to gauge the regional complexity of the white matter fiber orientation distribution functions (ODF). HARDI data were fluidly registered using Karcher means and ODF square-roots for interpol ation; each subject's JSD map was computed from the spatial coherence of the ODFs in each voxel's neighborhood. We evaluated the genetic influences on generalized fiber anisotropy (GFA) and complexity (JSD) using structural equation models (SEM). At each voxel, genetic and environmental components of data variation were estimated, and their goodness of fit tested by permutation. Color-coded maps revealed that the optimal models varied for different brain regions. Fiber complexity was predominantly under genetic control, and was higher in more highly anisotropic regions. These methods show promise for discovering factors affecting fiber connectivity in the brain.

Fluid registration of diffusion tensor images using information theory

We apply an information-theoretic cost metric, the symmetrized Kullback-Leibler (sKL) divergence, or $J$-divergence, to fluid registration of diffusion tensor images. The difference between diffusion tensors is quantified based on the sKL-divergence of their associated probability density functions (PDFs). Three-dimensional DTI data from 34 subjects were fluidly registered to an optimized target image. To allow large image deformations but preserve image topology, we regularized the flow with a large-deformation diffeomorphic mapping based on the kinematics of a Navier-Stokes fluid. A driving force was developed to minimize the $J$-divergence between the deforming source and target diffusion functions, while reorienting the flowing tensors to preserve fiber topography. In initial experiments, we showed that the sKL-divergence based on full diffusion PDFs is adaptable to higher-order diffusion models, such as high angular resolution diffusion imaging (HARDI). The sKL-divergence was sensitive to subtle differences between two diffusivity profiles, showing promise for nonlinear registration applications and multisubject statistical analysis of HARDI data.