Antihydrogen Beam Formation by Transporting an Antiproton Beam Through an Electron-Positron Plasma That Produces Magnetobound Positronium

This paper from the 2016 Conference on Application of Accelerators in Research and Industry conference proceedings describes the use of a classical trajectory simulation to study the formation of an antihydrogen beam by transporting an antiproton beam through an electron-positron plasma that produces magnetobound positronium

Noninvasive Determination of 2-[18F]-Fluoroisonicotinic Acid Hydrazide Pharmacokinetics by Positron Emission Tomography in Mycobacterium tuberculosis-Infected Mice

Tuberculosis (TB) is a global pandemic requiring sustained therapy to facilitate curing and to prevent the emergence of drug resistance. There are few adequate tools to evaluate drug dynamics within infected tissues in vivo. In this report, we evaluated a fluorinated analog of isoniazid (INH), 2-[18F]fluoroisonicotinic acid hydrazide (2-[18F]-INH), as a probe for imaging Mycobacterium tuberculosis-infected mice by dynamic positron emission tomography (PET). We developed a tail vein catheter system to safely deliver drugs to M. tuberculosis aerosol-infected mice inside sealed biocontainment devices. Imaging was rapid and noninvasive, and it could simultaneously visualize multiple tissues. Dynamic PET imaging demonstrated that 2-[18F]-INH was extensively distributed and rapidly accumulated at the sites of infection, including necrotic pulmonary TB lesions. Compared to uninfected animals, M. tuberculosis-infected mice had a significantly higher PET signal within the lungs (P 0.85), suggesting that 2-[18F]-INH accumulated at the site of the pulmonary infection. Furthermore, our data indicated that similar to INH, 2-[18F]-INH required specific activation and accumulated within the bacterium. Pathogen-specific metabolism makes positron-emitting INH analogs attractive candidates for development into imaging probes with the potential to both detect bacteria and yield pharmacokinetic data in situ. Since PET imaging is currently used clinically, this approach could be translated from preclinical studies to use in humans.Chemistry and Chemical Biolog

The NN scattering 3S1-3D1 mixing angle at NNLO

The 3S1-3D1 mixing angle for nucleon-nucleon scattering, epsilon_1, is calculated to next-to-next-to-leading order in an effective field theory with perturbative pions. Without pions, the low energy theory fits the observed epsilon_1 well for momenta less than $\sim 50$ MeV. Including pions perturbatively significantly improves the agreement with data for momenta up to $\sim 150$ MeV with one less parameter. Furthermore, for these momenta the accuracy of our calculation is similar to an effective field theory calculation in which the pion is treated non-perturbatively. This gives phenomenological support for a perturbative treatment of pions in low energy two-nucleon processes. We explain why it is necessary to perform spin and isospin traces in d dimensions when regulating divergences with dimensional regularization in higher partial wave amplitudes.Comment: 17 pages, journal versio

Towing tank and flume testing of passively adaptive composite tidal turbine blades

Composite tidal turbine blades with bend-twist (BT) coupled layups allow the blade to self-adapt to local site conditions by passively twisting. Passive feathering has the potential to increase annual energy production and shed thrust loads and power under extreme tidal flows. Decreased hydrodynamic thrust and power during extreme conditions means that the turbine support structure, generator, and other components can be sized more appropriately, resulting in a higher utilization factor and increased cost effectiveness

BIODIESEL FROM MICROALGAE: THE EFFECT OF FUEL PROPERTIES ON POLLUTANT EMISSIONS

Recently, biofuels have been presented as a viable alternative for the main challenges of the energy industry: the depleting supplies of petroleum and the global warming due to greenhouse effect. Biofuels may be produced from several different feedstocks, such as sugarcane, animal fat, oil crops or even microalgae. Replacing conventional petroleum sourced fuels with biofuels may significantly reduce global greenhouse effect gases emission when considering the life cycle of such fuels. Even with this advantage, biofuels present new challenges concerning the engine adaptation and the pollutant emissions. In this context, this paper aims to clarify the relation between fuel properties of microalgae biodiesel and pollutant emissions, studying which properties are desirable in these new fuels to guarantee engine operation without degradation of performance in comparison to conventional diesel

Numerical models to predict the performance of tidal stream turbines working under off-design conditions

As previously experienced by the wind industry, it is envisaged that tidal stream turbine blades will presentmisalignments or blade deformations over time as they are constantly working under harsh and highlyunsteady environments. Blade misalignment will affect the power capture of a tidal stream turbine andif not detected in time could affect other components of the drive train. Therefore, the aim of this paperis to compare the use of two numerical modelling techniques to predict the performance of a tidal streamturbine working under off-design conditions, in this case, the misalignment of one or more blades. Thetechniques used in this study are Blade Element Momentum Theory and Computational Fluid Dynamics.The numerical models simulate the performance of a three-bladed horizontal axis tidal stream turbine withone or two blades offset from the optimum pitch setting. The simulations were undertaken at 1.0 m/s flowspeeds. The results demonstrated that both unsteady BEMT and steady or transient CFD are able topredict power coefficients when there is a certain level of misalignment in one or even two blades. However,both techniques failed to accurately predict a loss of power performance at high rotational speeds

Exhaustive and Efficient Constraint Propagation: A Semi-Supervised Learning Perspective and Its Applications

This paper presents a novel pairwise constraint propagation approach by decomposing the challenging constraint propagation problem into a set of independent semi-supervised learning subproblems which can be solved in quadratic time using label propagation based on k-nearest neighbor graphs. Considering that this time cost is proportional to the number of all possible pairwise constraints, our approach actually provides an efficient solution for exhaustively propagating pairwise constraints throughout the entire dataset. The resulting exhaustive set of propagated pairwise constraints are further used to adjust the similarity matrix for constrained spectral clustering. Other than the traditional constraint propagation on single-source data, our approach is also extended to more challenging constraint propagation on multi-source data where each pairwise constraint is defined over a pair of data points from different sources. This multi-source constraint propagation has an important application to cross-modal multimedia retrieval. Extensive results have shown the superior performance of our approach.Comment: The short version of this paper appears as oral paper in ECCV 201