A numerical flow simulation based on the rate form of the equation of state

A finite-difference numerical method of solution for the unsteady, incompressible Navier-Stokes equations using primitive variables is presented. The rate form of the equation of state is used for the calculation of pressure. This form of the equation of state is well-suited for use with the unsteady form of the conservation equations (mass, momentum and energy). An implicit algorithm is used for the time integration for greater numerical stability. This method is used to solve a known benchmark problem in steady-state natural convection as a test of steady-state accuracy. The results of the simulation are compared to the benchmark.     

Non‐geostationary satellite orbit communications satellite constellations history

This special issue of the journal on ‘constellations’ comes at a critical time in their development as a second wave of such non‐geostationary satellite orbit (NGSO) systems is being planned and deployed. These mega‐constellations as they have become known are, with a few exceptions, very much larger than those in the first wave and are focused on broadband and 5G applications rather than speech and narrow band data as those deployed in the first wave during the 1990s. However, as we explain in this editorial, there are many similarities in the design and business plans to the first wave and, perhaps, many similar lessons to be learned.     

Arsenic incorporation in MBE grown Hg1−xCdxTe

The p-type doping of Hg_1−xCd_xTe (MCT) has proven to be a significant challenge in present day MCT-based detector technology. One of the most promising acceptor candidates, arsenic, behaves as an amphoteric dopant which can be activated as an acceptor during Hg-rich, low temperature annealing of as-grown molecular beam epitaxy (MBE) samples. This study focuses on developing an understanding of the microscopic behavior of arsenic incorporation during MBE growth. In particular, the question of whether arsenic incorporates as individual As atoms, as As₂ dimers, or as As₄ tetramers is addressed for MBE growth with an As₄ source. A quasithermodynamical model is employed to describe the MCT growth and As incorporation, with parameters fitted to an extensive database of samples grown at the Microphysics Laboratory. The best fits for growth temperatures between 175 and 185°C are obtained for arsenic incorporation as As₄ or possibly as As₄ clusters, with lower probabilities for As₂ and individual As atoms. Based on these results, we investigate the relaxed atomic configurations of As₄ and As₂ in bulk HgTe by ab initio total energy calculations. The calculations are performed in the pseudopotential density-functional framework within the local density approximation, employing supercells with periodic boundary conditions. The lattice distortions due to As₄ and As₂ in bulk HgTe are predicted to be modest due to the small size of these arsenic clusters.     

Bayesian Inference for ARFIMA Models

This article develops practical methods for Bayesian inference in the autoregressive fractionally integrated moving average (ARFIMA) model using the exact likelihood function, any proper prior distribution, and time series that may have thousands of observations. These methods utilize sequentially adaptive Bayesian learning, a sequential Monte Carlo algorithm that can exploit massively parallel desktop computing with graphics processing units (GPUs). The article identifies and solves several problems in the computation of the likelihood function that apparently have not been addressed in the literature. Four applications illustrate the utility of the approach. The most ambitious is an ARFIMA(2,d,2) model for the Campito tree ring time series (length 5405), for which the methods developed in the article provide an essentially uncorrelated sample of size 16,384 from the exact posterior distribution in under four hours. Less ambitious applications take as little as 4 minutes without exploiting GPUs.     

Targeting S100A9 Reduces Neutrophil Recruitment,Inflammation and Lung Damage in Abdominal Sepsis

S100A9, a pro-inflammatory alarmin, is up-regulated in inflamed tissues. However, the role of S100A9 in regulating neutrophil activation, inflammation and lung damage in sepsis is not known. Herein, we hypothesized that blocking S100A9 function may attenuate neutrophil recruitment in septic lung injury. Male C57BL/6 mice were pretreated with the S100A9 inhibitor ABR-238901 (10 mg/kg), prior to cercal ligation and puncture (CLP). Bronchoalveolar lavage fluid (BALF) and lung tissue were harvested for analysis of neutrophil infiltration as well as edema and CXC chemokine production. Blood was collected for analysis of membrane-activated complex-1 (Mac-1) expression on neutrophils as well as CXC chemokines and IL-6 in plasma. Induction of CLP markedly increased plasma levels of S100A9. ABR-238901 decreased CLP-induced neutrophil infiltration and edema formation in the lung. In addition, inhibition of S100A9 decreased the CLP-induced up-regulation of Mac-1 on neutrophils. Administration of ABR-238901 also inhibited the CLP-induced increase of CXCL-1, CXCL-2 and IL-6 in plasma and lungs. Our results suggest that S100A9 promotes neutrophil activation and pulmonary accumulation in sepsis. Targeting S100A9 function decreased formation of CXC chemokines in circulation and lungs and attenuated sepsis-induced lung damage. These novel findings suggest that S100A9 plays an important pro-inflammatory role in sepsis and could be a useful target to protect against the excessive inflammation and lung damage associated with the disease.     

Hydraulic study of turbulent flow in MTR-type nuclear fuel assembly

For a more accurate safety analysis for the McMaster nuclear reactor (MNR), local velocity measurements in a mock-up of the 18-plate fuel assembly were conducted in the low Reynolds number region with emphasis on edge effects. With modification of the curved plates in the assembly to flat ones, velocity in the narrow channels was measured by laser Doppler velocimetry (LDV). The velocity profile in individual channels and the channel-to-channel flow distribution were obtained. The effect of the sudden transition from the larger rectangular channel to the circular pipe on the velocity profile and the effect of the handle presence in the top end fitting on the flow distribution were investigated. The pressure drop along the assembly was measured and compared to a simple 1D correlation prediction.     

Control of concentration during academic tasks.

Evaluated 3 strategies for controlling concentration during academic tasks. 82 undergraduates served as Ss. One strategy, self-initiated relaxation (SIR), required Ss to employ a combination of relaxation techniques to set and maintain constructive study and test-taking states. The 2nd strategy, self-coaching (SC), was an extension of the positive self-talk techniques developed by D. Meichenbaum (1972). Ss were taught to coach (talk) themselves into constructive states and to maintain these states during studying and test taking. Finally, a 3rd strategy that combined SIR and SC was created. Results indicate that the 3rd strategy, SIR plus SC, significantly facilitated some aspects of academic performance in comparison to a no-treatment control group. (18 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Computationally efficient curve-fitting procedure for large two-dimensional experimental infrared spectroscopic arrays using the Pearson VII model

Extraction of quantitative information from large sets of sequential time-series spectra (two-dimensional, 2D, data) using a curve-fitting procedure is investigated. The difference between any experimental spectrum and any curve-fitted spectrum is constructed in a least-squares manner and the Pearson VII model is selected as the general band-shape function for the infrared absorbance spectra. The starting point for the curve-fitting procedure is a 2D peak map. Next, an interior spectrum from the 2D array is chosen, initial guesses of the band parameters are provided by an initialization scheme, and curve fitting is performed. Once optimal values of the Pearson VII model band parameters are obtained from the starting spectrum in the 2D array, these are then used as reasonable and judicious initial guesses for subsequent curve fitting of the neighboring spectra in the time series. This increases computational efficiency enormously. By adjusting the band center positions for moving bands, and re-optimizing each subsequent curve-fitting calculation to account for changing band shapes, the entire 2D array is rapidly and efficiently modeled. A 2D experimental spectroscopic time-series array from a homogeneous rhodium-catalyzed hydroformylation reaction was successfully curve fitted in this manner. The procedure holds considerable promise for the curve fitting of massive time-series spectroscopic data, such as that arising from on-line process monitoring of expensive value-added specialty chemical and pharmaceutical syntheses.