Generation of high-energy monoenergetic heavy ion beams by radiation pressure acceleration of ultra-intense laser pulses

A novel radiation pressure acceleration (RPA) regime of heavy ion beams from laser-irradiated ultrathin foils is proposed by self-consistently taking into account the ionization dynamics. In this regime, the laser intensity is required to match with the large ionization energy gap when the successive ionization of high-Z atoms passing the noble gas configurations [such as removing an electron from the helium-like charge state $(\text{Z}-2)^+$ to $(\text{Z}-1)^+$]. While the target ions in the laser wing region are ionized to low charge states and undergo rapid dispersions due to instabilities, a self-organized, stable RPA of highly-charged heavy ion beam near the laser axis is achieved. It is also found that a large supplement of electrons produced from ionization helps preserving stable acceleration. Two-dimensional particle-in-cell simulations show that a monoenergetic $\text{Al}^{13+}$ beam with peak energy $1\ \text{GeV}$ and energy spread of $5\%$ is obtained by lasers at intensity $7\times10^{20}\ \text{W}/\text{cm}^2$.Comment: 5 pages, 4 figure

Remarks on the Upper Bounds on the Higgs Boson Mass from Triviality

We study the effects of the one-loop matching conditions on Higgs boson and top quark masses on the triviality bounds on the Higgs boson mass using $\beta_{\lambda}$ with corrected two-loop coefficients. We obtain quite higher results than previous ones and observe that the triviality bounds are not nearly influenced by varying top quark mass over the range measured at CDF and D0. The effects of typo errors in $\beta_{\lambda}^{(2)}$ and the one-loop matching condition on the top quark mass are negligible. We estimate the size of effects on the triviality bounds from the one-loop matching condition on the Higgs boson mass.Comment: 9 pages, tar'ed gzip'ed uuencoded files, LaTex, 5 PostScript figures. To appear in Physical Review

Gastrointestinal helminthiasis presenting with acute diarrhoea and constipation: report of two cases with a second pathology.

Gastrointestinal helminthiasis in developing countries contributes to malnutrition and anemia. Diagnosis and treatment of helminthiasis, especially with low worm load is an unmet public health need in such settings. The infection may sometimes become manifest when a second pathology leads to purgation of the gastrointestinal tract. Two cases of helminthiasis are presented in which the infections only became amenable to diagnosis due to acute diarrhoea caused by giardiasis and lactulose administration. In the first case, acute giardiasis revealed Ascaris lumbricoides infestation, and in the second case primary helminthiasis (strongyloidiasis) was revealed by lactulose, and also led to Vibrio cholera bacteremia. These cases highlight the need to diagnose helminth infestations especially with low worm burdens by means of public health surveillance programmes. These cases highlight the need to diagnose helminth infestations especially with low worm burdens by means of public health surveillance programmes

Functional Assessment of Cardiac Responses of Adult Zebrafish (Danio rerio) to Acute and Chronic Temperature Change Using High-Resolution Echocardiography

The zebrafish (Danio rerio) is an important organism as a model for understanding vertebrate cardiovascular development. However, little is known about adult ZF cardiac function and how contractile function changes to cope with fluctuations in ambient temperature. The goals of this study were to: 1) determine if high resolution echocardiography (HRE) in the presence of reduced cardiodepressant anesthetics could be used to accurately investigate the structural and functional properties of the ZF heart and 2) if the effect of ambient temperature changes both acutely and chronically could be determined non-invasively using HRE in vivo. Heart rate (HR) appears to be the critical factor in modifying cardiac output (CO) with ambient temperature fluctuation as it increases from 78 ± 5.9 bpm at 18°C to 162 ± 9.7 bpm at 28°C regardless of acclimation state (cold acclimated CA– 18°C; warm acclimated WA– 28°C). Stroke volume (SV) is highest when the ambient temperature matches the acclimation temperature, though this difference did not constitute a significant effect (CA 1.17 ± 0.15 μL at 18°C vs 1.06 ± 0.14 μl at 28°C; WA 1.10 ± 0.13 μL at 18°C vs 1.12 ± 0.12 μl at 28°C). The isovolumetric contraction time (IVCT) was significantly shorter in CA fish at 18°C. The CA group showed improved systolic function at 18°C in comparison to the WA group with significant increases in both ejection fraction and fractional shortening and decreases in IVCT. The decreased early peak (E) velocity and early peak velocity / atrial peak velocity (E/A) ratio in the CA group are likely associated with increased reliance on atrial contraction for ventricular filling

Multi-objective optimization of the engine performance and emissions for a hydrogen/gasoline dual-fuel engine equipped with the port water injection system

Hydrogen is one of the most promising options being considered as the fuel of future. However, injection of hydrogen into modern gasoline fueled engines can cause some issues such as power loss. This study, therefore, aims to address this challenge in a simulated hydrogen/gasoline dual-fueled engine by developing a novel and innovative approach without possible side effects such as NOx increment. To achieve this goal, the impacts of water injection and the start of the combustion (SOC) modification in a gasoline/hydrogen duel fueled engine have been rigorously investigated. In current methodology, an engine is simulated using AVL software and the model is validated against the experimental data. The Latin Hypercube design experiment method was employed to determine the design points in 3-dimensional space. Due to the existing trade-off between NOx and BMEP, multi-objective optimization using genetic algorithm (GA) was implemented to determine the optimum values of water injection and SOC in various hydrogen energy shares and the effects of optimum design parameters on the main engine performance and emission parameters were investigated. The results showed that the proposed solution could recover the brake mean effective pressure (BMEP) and in some hydrogen energy shares even increase it above the level of single fueled gasoline engine with the added benefit of there being no increase in NOx compared to the original level. Furthermore, other emissions and engine performance parameters are improved including the engine equivalent Brake specific fuel consumption (BSFC) which was shown to increased up to 4.61

Thermal analysis of airway mucus clearance by ciliary activity in the presence of inertial forces

In this study heat transfer effects on cilia induced mucus flow in human airways is presented. The elliptic wave pattern of cilia tips produces metachronal wave which enables the transportation of highly viscous mucus with nonzero inertial forces. Upper Convective Maxwell model is considered as mucus. The governing partial differential equations are transformed from the fixed frame to the wave frame by using Galilean transformation and viscous dissipation is also incorporated in the energy equation. The non-linear governing equations are evaluated by the perturbation technique by using software “MATHEMATICA” and pressure rise is computed by numerical integration. The impact of interested parameters on temperature profile, velocity, pressure rise and pressure gradient are plotted by the graphs. The comparison of velocities due to symplectic and antiplectic metachronal wave are also achieved graphically

Neuroimaging Feature Extraction using a Neural Network Classifier for Imaging Genetics

A major issue in the association of genes to neuroimaging phenotypes is the high dimension of both genetic data and neuroimaging data. In this article, we tackle the latter problem with an eye toward developing solutions that are relevant for disease prediction. Supported by a vast literature on the predictive power of neural networks, our proposed solution uses neural networks to extract from neuroimaging data features that are relevant for predicting Alzheimer's Disease (AD) for subsequent relation to genetics. Our neuroimaging-genetic pipeline is comprised of image processing, neuroimaging feature extraction and genetic association steps. We propose a neural network classifier for extracting neuroimaging features that are related with disease and a multivariate Bayesian group sparse regression model for genetic association. We compare the predictive power of these features to expert selected features and take a closer look at the SNPs identified with the new neuroimaging features.Comment: Under revie