The activation energy for GaAs/AlGaAs interdiffusion

Copyright 1997 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. This article appeared in Journal of Applied Physics 82, 4842 (1997) and may be found at

An optical study of interdiffusion in ZnSe/ZnCdSe

Copyright 1996 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics. This article appeared in Applied Physics Letters 69, 1579 (1996) and may be found at

Some aspects of presumed filtered density functions formulation in the context of large eddy simulation of turbulent reacting flows

In Large Eddy Simulations (LES) of turbulent flows, spatially-averaged versions of the Navier-Stokes equations are solved on a grid, which is coarse relative to the smallest turbulent length scales. In order to couple the detailed chemistry and the computed flow field in LES of reacting flows, the so-called filtered density function-based approach for subfilter-scale modelling was suggested. This approach was named as the laminar flamelet and allowed to link the complex chemistry to a single variable, i.e. mixture fraction. The mixture fraction is obtained by the solution of corresponding filtered transport equation and subgrid-scale (SGS) variance (the residual field) is usually modelled. The objective of this article is to present in-depth analysis of filtered density functions (FDFs) by analysing experimental data obtained from two-dimensional planar, laser induced fluorescence measurements in isothermal swirling coaxial turbulent jets at a constant Reynolds number of 29000. The FDFs were analysed as a function of flow swirl number, spatial locations in the flow and were linked to the measured subgrid scale variance. In addition, presumed FDFs were also analysed and associated laminar flamelet solution integration errors were evaluated. It was experimentally found that the FDFs can become unimodal when SGS variance reaches a certain value. However, bimodal FDFs were observed in flow regions with high SGS variance. It was demonstrated that bimodality does not automatically result in large errors in resolved variables when top-hat FDF or -FDF formulations are used. It was suggested that possible source of errors in resolved variables could be linked to the SGS variance models rather than to the presumed FDF-based models

Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

Inferring gene regulatory networks from gene expression data by a dynamic Bayesian network-based model

Enabled by recent advances in bioinformatics, the inference of gene regulatory networks (GRNs) from gene expression data has garnered much interest from researchers. This is due to the need of researchers to understand the dynamic behavior and uncover the vast information lay hidden within the networks. In this regard, dynamic Bayesian network (DBN) is extensively used to infer GRNs due to its ability to handle time-series microarray data and modeling feedback loops. However, the efficiency of DBN in inferring GRNs is often hampered by missing values in expression data, and excessive computation time due to the large search space whereby DBN treats all genes as potential regulators for a target gene. In this paper, we proposed a DBN-based model with missing values imputation to improve inference efficiency, and potential regulators detection which aims to lessen computation time by limiting potential regulators based on expression changes. The performance of the proposed model is assessed by using time-series expression data of yeast cell cycle. The experimental results showed reduced computation time and improved efficiency in detecting gene-gene relationships

Kinetic Monte Carlo Simulations of Crystal Growth in Ferroelectric Alloys

The growth rates and chemical ordering of ferroelectric alloys are studied with kinetic Monte Carlo (KMC) simulations using an electrostatic model with long-range Coulomb interactions, as a function of temperature, chemical composition, and substrate orientation. Crystal growth is characterized by thermodynamic processes involving adsorption and evaporation, with solid-on-solid restrictions and excluding diffusion. A KMC algorithm is formulated to simulate this model efficiently in the presence of long-range interactions. Simulations were carried out on Ba(Mg_{1/3}Nb_{2/3})O_3 (BMN) type materials. Compared to the simple rocksalt ordered structures, ordered BMN grows only at very low temperatures and only under finely tuned conditions. For materials with tetravalent compositions, such as (1-x)Ba(Mg_{1/3}Nb_{2/3})O_3 + xBaZrO_3 (BMN-BZ), the model does not incorporate tetravalent ions at low-temperature, exhibiting a phase-separated ground state instead. At higher temperatures, tetravalent ions can be incorporated, but the resulting crystals show no chemical ordering in the absence of diffusive mechanisms.Comment: 13 pages, 16 postscript figures, submitted to Physics Review B Journa

Detention Properties of Subsurface Stormwater Modules Under Tropical Climate

Subsurface stormwater module is one of the components of a sustainable drainage system. However, the performance of subsurface stormwater module as on-site detention under tropical climate like Malaysia has not been extensively studied in the literature. The current study involves on-site installation of pilot scale subsurface stormwater modules exposed to tropical climate to simulate real conditions to evaluate the detention performance. Rainfall together with the changes in water level and volume of water detained in the installation were observed for six months between April 2021 to October 2021. The subsurface stormwater module used in the current study has a porosity of 94%. It was found that the subsurface stormwater module setup was able to detain between 35.2% to 95.6% of the rainfall volume generated from total rainfall between 11.1 mm to 56.8 mm. The findings can be used as design consideration for using subsurface stormwater module under tropical climate

Detention Properties of Subsurface Stormwater Modules Under Tropical Climate

Subsurface stormwater module is one of the components of a sustainable drainage system. However, the performance of subsurface stormwater module as on-site detention under tropical climate like Malaysia has not been extensively studied in the literature. The current study involves on-site installation of pilot scale subsurface stormwater modules exposed to tropical climate to simulate real conditions to evaluate the detention performance. Rainfall together with the changes in water level and volume of water detained in the installation were observed for six months between April 2021 to October 2021. The subsurface stormwater module used in the current study has a porosity of 94%. It was found that the subsurface stormwater module setup was able to detain between 35.2% to 95.6% of the rainfall volume generated from total rainfall between 11.1 mm to 56.8 mm. The findings can be used as design consideration for using subsurface stormwater module under tropical climate

Students\u27 Views on General Education: Insights Gained from the Narratives of Chinese Students in Hong Kong

The General University Requirements (GUR) is a component of the new 4-year undergraduate program at The Hong Kong Polytechnic University (PolyU). This study examined students’ views and experiences of the GUR using a qualitative methodology. Written comments of 240 freshmen, sophomores, and senior-year students with reference to open-ended questions on their memorable experiences in the GUR study were collected. The qualitative findings suggested that students generally had positive views on the GUR in terms of its widely adopted active and experiential learning pedagogy, useful and attractive contents, caring teaching staff, and rich learning outcomes. Challenges were also identified for further improvement of the GUR

Some integral inequalities on time scales

In this paper, some new integral inequalities on time scales are presented by using elementarily analytic methods in calculus of time scales.Comment: 8 page