Pulsed dc- and sine-wave-excited cold atmospheric plasma plumes: A comparative analysis

Cold atmospheric-pressure plasma plumes are generated in the ambient air by a single-electrode plasma jet device powered by pulsed dc and ac sine-wave excitation sources. Comprehensive comparisons of the plasma characteristics, including electrical properties, optical emission spectra, gas temperatures, plasma dynamics, and bacterial inactivation ability of the two plasmas are carried out. It is shown that the dc pulse excited plasma features a much larger discharge current and stronger optical emission than the sine-wave excited plasma. The gas temperature in the former discharge remains very close to the room temperature across the entire plume length; the sine-wave driven discharge also shows a uniform temperature profile, which is 20-30 degrees higher than the room temperature. The dc pulse excited plasma also shows a better performance in the inactivation of gram-positive staphylococcus aureus bacteria. These results suggest that the pulsed dc electric field is more effective for the generation of nonequilibrium atmospheric pressure plasma plumes for advanced plasma health care applications.

What is the apparent angle of a Kelvin ship wave pattern?

While the half-angle which encloses a Kelvin ship wave pattern is commonly accepted to be 19.47 degrees, recent observations and calculations for sufficiently fast-moving ships suggest that the apparent wake angle decreases with ship speed. One explanation for this decrease in angle relies on the assumption that a ship cannot generate wavelengths much greater than its hull length. An alternative interpretation is that the wave pattern that is observed in practice is defined by the location of the highest peaks; for wakes created by sufficiently fast-moving objects, these highest peaks no longer lie on the outermost divergent waves, resulting in a smaller apparent angle. In this paper, we focus on the problems of free surface flow past a single submerged point source and past a submerged source doublet. In the linear version of these problems, we measure the apparent wake angle formed by the highest peaks, and observe the following three regimes: a small Froude number pattern, in which the divergent waves are not visible; standard wave patterns for which the maximum peaks occur on the outermost divergent waves; and a third regime in which the highest peaks form a V-shape with an angle much less than the Kelvin angle. For nonlinear flows, we demonstrate that nonlinearity has the effect of increasing the apparent wake angle so that some highly nonlinear solutions have apparent wake angles that are greater than Kelvin's angle. For large Froude numbers, the effect on apparent wake angle can be more dramatic, with the possibility of strong nonlinearity shifting the wave pattern from the third regime to the second. We expect our nonlinear results will translate to other more complicated flow configurations, such as flow due to a steadily moving closed body such as a submarine.

Acoustic identification of 12 species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

Single voxel Magnetic Resonance Spectroscopic (1H-MRS) analysis of deep brain structures after traumatic prefrontal brain injury (TBI) in rat

Chronic difficulties arising from mild brain injury (TBI) are difficult to predict because the processes underlying changes after TBI are poorly understood. In mild brain injury the extent of neuropsychiatric and cognitive symptoms correspond poorly to overt tissue loss (Barth 1983; Liu 2010). Cellular, immune and hormonal cascades occurring after injury and continuing during the healing process may impact uninjured brain regions sensitive to the effects of physiological and emotional stress, which receive projections from the injury site. Changes in these most basic properties due to injury or disease have profound implications for virtually every aspect of brain function through disruption of neurotransmitter, neuroendocrine and metabolic systems. In order to screen for changes in transmitter and metabolic activity, in this study we developed Single voxel proton Magnetic Resonance Spectroscopy (1H-MRS) for use in both injured and control animals. We first evaluated if 1H-MRS could be used to evaluate in vivo, alterations in brain metabolism and catabolism of the prefrontal cortex, amygdala and ventral hippocampus in both control and injured animals after controlled cortical impact injury to the rat prefrontal cortex. We found that metabolite measurements for Myo-Inositol, Choline, creatine, Glutamate+Glutamine, and N-acetyl-acetate are attainable in deep brain structures in vivo in injured and controls rats. We next seek to evaluate longitudinally, in vivo, alterations in brain metabolism and catabolism of the prefrontal cortex, amygdala and ventral hippocampus during the first month after controlled cortical impact injury to the rat prefrontal cortex. These ongoing studies will provide data on the changes in transmitters and metabolites over time in injured and non-injured subjects. These studies address some of the fundamental questions about how mild brain injury has such diverse effects on overall brain health and function.

Osseointegrated prosthetic limb for amputees: Single stage surgery

The Osseointegrated Prosthetic Limb (OPL) was introduced in 2011. The socket prostheses failed to address a few major requirements of normal gait. Our hypothesis was that using an Osseointegrated Prosthetic limb will result in superior function of daily activities, without compromising patients’ safety. Traditionally this surgery was done as a two-stage procedure. The aims of this study were (A)to describe the single - surgical procedure of the OPL; and (B)To present data on potential risks and benefits with sssessment of clinical and functional outcomes at follow up.

Single layer lead iodide: Computational exploration of structural, electronic and optical properties, strain induced band modulation and the role of spin-orbital-coupling

Graphitic like layered materials exhibit intriguing electronic structures and thus the search for new types of two-dimensional (2D) monolayer materials is of great interest for developing novel nano-devices. By using density functional theory (DFT) method, here we for the first time investigate the structure, stability, electronic and optical properties of monolayer lead iodide (PbI2). The stability of PbI2 monolayer is first confirmed by phonon dispersion calculation. Compared to the calculation using generalized gradient approximation, screened hybrid functional and spin–orbit coupling effects can not only predicts an accurate bandgap (2.63 eV), but also the correct position of valence and conduction band edges. The biaxial strain can tune its bandgap size in a wide range from 1 eV to 3 eV, which can be understood by the strain induced uniformly change of electric field between Pb and I atomic layer. The calculated imaginary part of the dielectric function of 2D graphene/PbI2 van der Waals type hetero-structure shows significant red shift of absorption edge compared to that of a pure monolayer PbI2. Our findings highlight a new interesting 2D material with potential applications in nanoelectronics and optoelectronics.

The MS risk allele of CD40 is associated with reduced cell-membrane bound expression in antigen presenting cells: Implications for gene function

Human genetic and animal studies have implicated the costimulatory molecule CD40 in the development of multiple sclerosis (MS). We investigated the cell specific gene and protein expression variation controlled by the CD40 genetic variant(s) associated with MS, i.e. the T-allele at rs1883832. Previously we had shown that the risk allele is expressed at a lower level in whole blood, especially in people with MS. Here, we have defined the immune cell subsets responsible for genotype and disease effects on CD40 expression at the mRNA and protein level. In cell subsets in which CD40 is most highly expressed, B lymphocytes and dendritic cells, the MS-associated risk variant is associated with reduced CD40 cell-surface protein expression. In monocytes and dendritic cells, the risk allele additionally reduces the ratio of expression of full-length versus truncated CD40 mRNA, the latter encoding secreted CD40. We additionally show that MS patients, regardless of genotype, express significantly lower levels of CD40 cell-surface protein compared to unaffected controls in B lymphocytes. Thus, both genotype-dependent and independent down-regulation of cell-surface CD40 is a feature of MS. Lower expression of a co-stimulator of T cell activation, CD40, is therefore associated with increased MS risk despite the same CD40 variant being associated with reduced risk of other inflammatory autoimmune diseases. Our results highlight the complexity and likely individuality of autoimmune pathogenesis, and could be consistent with antiviral and/or immunoregulatory functions of CD40 playing an important role in protection from MS. © 2015 Field et al.

High-throughput sequencing of IL23R reveals a low-frequency, nonsynonymous single-nucleotide polymorphism that is associated with ankylosing spondylitis in a Han Chinese population

Objective Ankylosing spondylitis (AS) is a highly heritable common inflammatory arthritis that targets the spine and sacroiliac joints of the pelvis, causing pain and stiffness and leading eventually to joint fusion. Although previous studies have shown a strong association of IL23R with AS in white Europeans, similar studies in East Asian populations have shown no association with common variants of IL23R, suggesting either that IL23R variants have no role or that rare genetic variants contribute. The present study was undertaken to screen IL23R to identify rare variants associated with AS in Han Chinese. Methods A 170-kb region containing IL23R and its flanking regions was sequenced in 50 patients with AS and 50 ethnically matched healthy control subjects from a Han Chinese population. In addition, the 30-kb region of peak association in white Europeans was sequenced in 650 patients with AS and 1,300 healthy controls. Validation genotyping was undertaken in 846 patients with AS and 1,308 healthy controls. Results We identified 1,047 variants, of which 729 were not found in the dbSNP genomic build 130. Several potentially functional rare variants in IL23R were identified, including one nonsynonomous single-nucleotide polymorphism (nsSNP), Gly149Arg (position 67421184 GA on chromosome 1). Validation genotyping showed that the Gly149Arg variant was associated with AS (odds ratio 0.61, P = 0.0054). Conclusion This is the first study to implicate rare IL23R variants in the pathogenesis of AS. The results identified a low-frequency nsSNP with predicted loss-of-function effects that was protectively associated with AS in Han Chinese, suggesting that decreased function of the interleukin-23 (IL-23) receptor protects against AS. These findings further support the notion that IL-23 signaling has an important role in the pathogenesis of AS.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

Do motor vehicle crashes arise from single or multiple unique risk processes? An inquiry into crash causes and modelling

Crashes at any particular transport network location consist of a chain of events arising from a multitude of potential causes and/or contributing factors whose nature is likely to reflect geometric characteristics of the road, spatial effects of the surrounding environment, and human behavioural factors. It is postulated that these potential contributing factors do not arise from the same underlying risk process, and thus should be explicitly modelled and understood. The state of the practice in road safety network management applies a safety performance function that represents a single risk process to explain crash variability across network sites. This study aims to elucidate the importance of differentiating among various underlying risk processes contributing to the observed crash count at any particular network location. To demonstrate the principle of this theoretical and corresponding methodological approach, the study explores engineering (e.g. segment length, speed limit) and unobserved spatial factors (e.g. climatic factors, presence of schools) as two explicit sources of crash contributing factors. A Bayesian Latent Class (BLC) analysis is used to explore these two sources and to incorporate prior information about their contribution to crash occurrence. The methodology is applied to the state controlled roads in Queensland, Australia and the results are compared with the traditional Negative Binomial (NB) model. A comparison of goodness of fit measures indicates that the model with a double risk process outperforms the single risk process NB model, and thus indicating the need for further research to capture all the three crash generation processes into the SPFs.

Orientational relaxation in a random dipolar lattice: Wave-number and frequency dependence

In order to understand the role of translational modes in the orientational relaxation in dense dipolar liquids, we have carried out a computer ''experiment'' where a random dipolar lattice was generated by quenching only the translational motion of the molecules of an equilibrated dipolar liquid. The lattice so generated was orientationally disordered and positionally random. The detailed study of orientational relaxation in this random dipolar lattice revealed interesting differences from those of the corresponding dipolar liquid. In particular, we found that the relaxation of the collective orientational correlation functions at the intermediate wave numbers was markedly slower at the long times for the random lattice than that of the liquid. This verified the important role of the translational modes in this regime, as predicted recently by the molecular theories. The single-particle orientational correlation functions of the random lattice also decayed significantly slowly at long times, compared to those of the dipolar liquid.

Orchestration of Haemophilus influenzae RecJ Exonuclease by Interaction with Single-Stranded DNA-Binding Protein

RecJ exonuclease plays crucial roles in several DNA repair and recombination pathways, and its ubiquity in bacterial species points to its ancient origin and vital cellular function. RecJ exonuclease from Haemophilus influenzae is a 575-amino-acid protein that harbors the characteristic motifs conserved among RecJ homologs. The purified protein exhibits a process 5'-3' single-stranded-DNA-specific exonuclease activity. The exonuclease activity of H. influenzae RecJ (HiRecJ) was supported by Mg2+ or Mn2+ and inhibited by Cd2+ suggesting a different mode of metal binding in HiRecJ as compared to Escherichia coli RecJ (EcoRecJ). Site-directed mutagenesis of highly conserved residues in HiRecJ abolished enzymatic activity. Interestingly, substitution of alanine for aspartate 77 resulted in a catalytically inactive enzyme that bound to DNA with a significantly higher affinity as compared to the wild-type enzyme. Noticeably, steady-state kinetic studies showed that H. influenzae single-stranded DNA-binding protein (HiSSB) increased the affinity of HiRecJ for single-stranded DNA and stimulated its exonuclease activity. HiSSB, whose C-terminal tail had been deleted, failed to enhance RecJ exonuclease activity. More importantly, HiRecJ was found to directly associate with its cognate single-stranded DNA-binding protein (SSB), as demonstrated by various in vitro assays, Interaction studies carried out with the truncated variants of HiRecJ and HiSSB revealed that the two proteins interact via the C-terminus of SSB protein and the core-catalytic domain of RecJ. Taken together, these results emphasize direct interactio between RecJ and SSB, which confers functional cooperativity to these two proteins. In addition, these results implicate SSB as being involved in the recruitment of RecJ to DNA and provide insights into the interplay between these proteins in repair and recombination pathways.

The dynamics of polymerized carbon nanotubes in semiconductor polymer electronics and electro-mechanical sensing

Polymerized carbon nanotubes (CNTs) are promising materials for polymer-based electronics and electro-mechanical sensors. The advantage of having a polymer nanolayer on CNTs widens the scope for functionalizing it in various ways for polymer electronic devices. However, in this paper, we show for the first time experimentally that, due to a resistive polymer layer having carbon nanoparticle inclusions and polymerized carbon nanotubes, an interesting dynamics can be exploited. We first show analytically that the relative change in the resistance of a single isolated semiconductive nanotube is directly proportional to the axial and torsional dynamic strains, when the strains are small, whereas, in polymerized CNTs, the viscoelasticity of the polymer and its effective electrical polarization give rise to nonlinear effects as a function of frequency and bias voltage. A simplified formula is derived to account for these effects and validated in the light of experimental results. CNT–polymer-based channels have been fabricated on a PZT substrate. Strain sensing performance of such a one-dimensional channel structure is reported. For a single frequency modulated sine pulse as input, which is common in elastic and acoustic wave-based diagnostics, imaging, microwave devices, energy harvesting, etc, the performance of the fabricated channel has been found to be promising.

Gamma-ray luminosity function of gamma-ray bright AGNs

Detection of gamma-ray emissions from a class of active galactic nuclei (viz blazars), has been one of the important findings from the Compton Gamma-Ray Observatory (CGRO). However, their gamma-ray luminosity function has not-been well determined. Few attempts have been made in earlier works, where BL Lacs and Flat Spectrum Radio Quasars (FSRQs) have been considered as a single source class. In this paper, we investigated the evolution and gamma-ray luminosity function of FSRQs and BL Lacs separately. Our investigation indicates no evolution for BL Lacs, however FSRQs show significant evolution. Pure luminosity evolution is assumed for FSRQs and exponential and power law evolution models are examined. Due to the small number of sources, the low luminosity end index of the luminosity function for FSRQs is constrained with an upper limit. BL Lac luminosity function shows no signature of break. As a consistency check, the model source distributions derived from these luminosity functions show no significant departure from the observed source distributions.