System testing of a production Ada (trademark) project: The GRODY study

The use of the Ada language and design methodologies that utilize its features has a strong impact on all phases of the software development project lifecycle. At the National Aeronautics and Space Administration/Goddard Space Flight Center (NASA/GSFC), the Software Engineering Laboratory (SEL) conducted an experiment in parallel development of two flight dynamics systems in FORTRAN and Ada. The teams found some qualitative differences between the system test phases of the two projects. Although planning for system testing and conducting of tests were not generally affected by the use of Ada, the solving of problems found in system testing was generally facilitated by Ada constructs and design methodology. Most problems found in system testing were not due to difficulty with the language or methodology but to lack of experience with the application

Optimized thermoelectric properties of Mo_3Sb_(7-x)Te_x with significant phonon scattering by electrons

Heavily doped compounds Mo_3Sb_(7−x)Te_x (x = 0, 1.0, 1.4, 1.8) were synthesized by solid state reaction and sintered by spark plasma sintering. Both X-ray diffraction and electron probe microanalysis indicated the maximum solubility of Te was around x = 1.8. The trends in the electrical transport properties can generally be understood using a single parabolic band model, which predicts that the extremely high carrier concentration of Mo_3Sb_7 (~10^(22) cm^(−3)) can be reduced to a nearly optimized level (~2 × 10^(21) cm^(−3)) for thermoelectric figure of merit (zT) by Te-substitution with x = 1.8. The increased lattice thermal conductivity by Te-doping was found to be due to the decreased Umklapp and electron–phonon scattering, according to a Debye model fitting. The thermoelectric figure of merit (zT) monotonously increased with increasing temperature and reached its highest value of about 0.51 at 850 K for the sample with x = 1.8, making these materials competitive with the state-of-the-art thermoelectric SiGe alloys. Evidence of significant electron–phonon scattering is found in the thermal conductivity

The well-coordinated linkage between acidogenicity and aciduricity via insoluble glucans on the surface of Streptococcus mutans.

Streptococcus mutans is considered the principal cariogenic bacterium for dental caries. Despite the recognition of their importance for cariogenesis, the possible coordination among S. mutans' main virulence factors, including glucan production, acidogenicity and aciduricity, has been less well studied. In the present study, using S. mutans strains with surface-displayed pH-sensitive pHluorin, we revealed sucrose availability- and Gtf functionality-dependent proton accumulation on S. mutans surface. Consistent with this, using a pH-sensitive dye, we demonstrated that both in vivo cell-produced and in vitro enzymatically synthesized insoluble glucans displayed proton-concentrating ability. Global transcriptomics revealed proton accumulation triggers the up-regulation of genes encoding functions involved in acid tolerance response in a glucan-dependent manner. Our data suggested that this proton enrichment around S. mutans could pre-condition the bacterium for acid-stress. Consistent with this hypothesis, we found S. mutans strains defective in glucan production were more acid sensitive. Our study revealed for the first time that insoluble glucans is likely an essential factor linking acidogenicity with aciduricity. The coordination of these key virulence factors could provide new insights on how S. mutans may have become a major cariogenic pathogen

Optimizing Urban Distribution Routes for Perishable Foods Considering Carbon Emission Reduction

The increasing demand for urban distribution increases the number of transportation vehicles which intensifies the congestion of urban traffic and leads to a lot of carbon emissions. This paper focuses on carbon emission reduction in urban distribution, taking perishable foods as the object. It carries out optimization analysis of urban distribution routes to explore the impact of low carbon policy on urban distribution routes planning. On the base of analysis of the cost components and corresponding constraints of urban distribution, two optimization models of urban distribution route with and without carbon emissions cost are constructed, and fuel quantity related to cost and carbon emissions in the model is calculated based on traffic speed, vehicle fuel quantity and passable time period of distribution. Then an improved algorithm which combines genetic algorithm and tabu search algorithm is designed to solve models. Moreover, an analysis of the influence of carbon tax price is also carried out. It is concluded that in the process of urban distribution based on the actual network information, the path optimization considering the low carbon factor can effectively reduce the distribution process of CO2, and reduce the total cost of the enterprise and society, thus achieving greater social benefits at a lower cost. In addition, the government can encourage low-carbon distribution by rationally adjusting the price of carbon tax to achieve a higher social benefit

Promoting hydrogen production and minimizing catalyst deactivation from the pyrolysis-catalytic steam reforming of biomass on nanosized NiZnAlOx catalysts

Hydrogen production from the thermochemical conversion of biomass was carried out with nano-sized NiZnAlOx catalysts using a two-stage fixed bed reactor system. The gases derived from the pyrolysis of wood sawdust in the first stage were catalytically steam reformed in the second stage. The NiZnAlOx catalysts were synthesized by a co-precipitation method with different Ni molar fractions (5, 10, 15, 25 and 35%) and a constant Zn:Al molar ratio of 1:4. The catalysts were characterized by a wide range of techniques, including N2 adsorption, SEM, XRD, TEM and temperature-programmed oxidation (TPO) and reduction (TPR). Fine metal particles of size around 10–11 nm were obtained and the catalysts had high stability characteristics, which improved the dispersion of active centers during the reaction and promoted the performance of the catalysts. The yield of gas was increased from 49.3 to 74.8 wt.%, and the volumetric concentration of hydrogen was increased from 34.7 to 48.1 vol.%, when the amount of Ni loading was increased from 5 to 35%. Meanwhile, the CH4 fraction decreased from 10.2 to 0.2 vol.% and the C2–C4 fraction was reduced from 2.4 vol.% to 0.0 vol.%. During the reaction, the crystal size of all catalysts was successfully maintained at around 10–11 nm with lowered catalyst coke formation, (particularly for the 35NiZn4Al catalyst where negligible coke was found) and additionally no obvious catalyst sintering was detected. The efficient production of hydrogen from the thermochemical conversion of renewable biomass indicates that it is a promising sustainable route to generate hydrogen from biomass using the NiZnAl metal oxide catalyst prepared in this work via a two-stage reaction system

Quadratic Regularization Design for 3d Cylindrical PET

Statistical methods for tomographic image reconstruction lead to improved spatial resolution and noise properties in PET. Penalized-likelihood (PL) image reconstruction methods involve maximizing an objective function that is based on the log-likelihood of the sinogram measurements and on a roughness penalty function to control noise. In emission tomography, PL methods (and MAP methods) based on conventional quadratic regularization functions lead to nonuniform and anisotropic spatial resolution, even for idealized shift-invariant imaging systems. We have previously addressed this problem for parallel-beam 2D emission tomography, and for fan-beam 2D transmission tomography by designing data-dependent, shift-variant regularizers that improve resolution uniformity and isotropy, even for idealized shift-invariant imaging systems. This paper extends those methods to 3D cylindrical PET, using an analytical design approach that is numerically efficient.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85859/1/Fessler212.pd

Quadratic Regularization Design for 2-D CT

Statistical methods for tomographic image reconstruction have improved noise and spatial resolution properties that may improve image quality in X-ray computed tomography (CT). Penalized weighted least squares (PWLS) methods using conventional quadratic regularization lead to nonuniform and anisotropic spatial resolution due to interactions between the weighting, which is necessary for good noise properties, and the regularizer. Previously, we addressed this problem for parallel-beam emission tomography using matrix algebra methods to design data-dependent, shift-variant regularizers that improve resolution uniformity. This paper develops a fast angular integral mostly analytical (AIMA) regularization design method for 2-D fan-beam X-ray CT imaging, for which parallel-beam tomography is a special case. Simulation results demonstrate that the new method for regularization design requires very modest computation and leads to nearly uniform and isotropic spatial resolution in transmission tomography when using quadratic regularization.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85858/1/Fessler18.pd

Quadratic regularization design for fan beam transmission tomography

Statistical methods for tomographic image reconstruction have shown considerable potential for improving image quality in X-ray CT. Penalized-likelihood (PL) image reconstruction methods require maximizing an objective function that is based on the log-likelihood of the sinogram measurements and on a roughness penalty function to control noise. In transmission tomography, PL methods (and MAP methods) based on conventional quadratic regularization functions lead to nonuniform and anisotropic spatial resolution, even for idealized shift-invariant imaging systems. We have previously addressed this problem for parallel-beam emission tomography by designing data-dependent, shift-variant regularizers that improve resolution uniformity. This paper extends those methods to the fan-beam geometry used in X-ray CT imaging. Simulation results demonstrate that the new method for regularization design requires very modest computation and leads to nearly uniform and isotropic spatial resolution in the fan-beam geometry when using quadratic regularization.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85936/1/Fessler208.pd

Quadratic Regularization Design for Iterative Reconstruction in 3D multi-slice Axial CT

In X-ray CT, statistical methods for tomographic image reconstruction create images with better noise properties than conventional filtered back projection (FBP) techniques. Penalized-likelihood (PL) image reconstruction methods maximize an objective function based on the log-likelihood of sinogram measurements and on a user defined roughness penalty which controls noise. Penalized-likelihood methods (as well as penalized weighted least squares methods) based on conventional quadratic regularizers result in nonuniform and anisotropic spatial resolution. We have previously addressed this problem for 2D emission tomography, 2D fan-beam transmission tomography, and 3D cylindrical emission tomography. This paper extends those methods to 3D multi-slice axial CT with small cone angles.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85860/1/Fessler222.pd