Connections of activated hopping processes with the breakdown of the Stokes-Einstein relation and with aspects of dynamical heterogeneities

We develop a new extended version of the mode-coupling theory (MCT) for glass transition, which incorporates activated hopping processes via the dynamical theory originally formulated to describe diffusion-jump processes in crystals. The dynamical-theory approach adapted here to glass-forming liquids treats hopping as arising from vibrational fluctuations in quasi-arrested state where particles are trapped inside their cages, and the hopping rate is formulated in terms of the Debye-Waller factors characterizing the structure of the quasi-arrested state. The resulting expression for the hopping rate takes an activated form, and the barrier height for the hopping is ``self-generated'' in the sense that it is present only in those states where the dynamics exhibits a well defined plateau. It is discussed how such a hopping rate can be incorporated into MCT so that the sharp nonergodic transition predicted by the idealized version of the theory is replaced by a rapid but smooth crossover. We then show that the developed theory accounts for the breakdown of the Stokes-Einstein relation observed in a variety of fragile glass formers. It is also demonstrated that characteristic features of dynamical heterogeneities revealed by recent computer simulations are reproduced by the theory. More specifically, a substantial increase of the non-Gaussian parameter, double-peak structure in the probability distribution of particle displacements, and the presence of a growing dynamic length scale are predicted by the extended MCT developed here, which the idealized version of the theory failed to reproduce. These results of the theory are demonstrated for a model of the Lennard-Jones system, and are compared with related computer-simulation results and experimental data.Comment: 13 pages, 5 figure

Characterization of carbon nanotubes synthesized from hydrocarbon-rich flame

The present study focuses on the characterization of carbon nanotubes (CNTs) synthesized from flame under an atmospheric condition. A laminar flame burner was utilized to establish a rich premixed propane/air flame at the equivalence ratio Φ = 1.8-2.2. The flame was impinged on a stainless steel wire mesh coated with nickel (Ni) catalyst to grow CNTs. Distribution and yield of the CNTs on the substrate were quantified. Carbon nanotubes formed on the substrate were harvested and characterized using scanning electron microscopy (SEM), field emission scanning electron microscopy (FESEM), energy dispersive X-ray spectroscopy (EDX), and thermogravimetric analysis (TGA). The FESEM micrograph showed that the CNTs produced were in disarray. The synthesized CNTs were an average of 50-60 nm in diameter while the length of the tubes was in the order of microns. TGA analysis showed that 75% of CNTs were present in the sample and the oxidation temperature was 510°C

Optical properties of amorphous selenium films

Recently there has been a substantial renewed interest in the electrical and optical properties of amorphous selenium (a-Se) films due to its use as an ultra-sensitive photoconductor in the newly developed flat panel x-ray image detector and high definition digital and video camera. This project has examined the optical properties of a range of a-Se films fabricated by conventional vacuum deposition technique. The films were deposited at two substrate temperatures called hot and cold deposition: (i) at 51C, which is above the glass transition temperature (Tg ≈ 40C), and (ii) at 3C, well below the glass transition temperature. The transmission spectrum T() of all the a-Se films were measured over a wide range of wavelengths from 500 nm to 2500 nm, and analyzed using the Swanepoel technique. The thickness, absorption coefficient (), refractive index n(), and optical bandgap, EgT and EgU, in different absorption regions of a-Se were all extracted using the Swanepoel technique. A systematic way to improve the accuracy of the calculations was also developed and the n vs.  data was fitted to the Sellmeier dispersion equation. The optical bandgap EgT was obtained from the h vs h plot of the absorption spectrum and the Urbach tail was obtained from a semi-logarithmic plot of  vs h. With all essential optical properties collected, the influence of thermal annealing, the deposition temperature, doping, thickness and aging time on the optical properties of a-Se films was studied. Amorphous selenium is essentially a glass, and all glasses exhibit some degree of structural relaxation effects during which the physical properties such as the refractive index and the bandgap change with time, called "aging". First of all, thermal annealing an a-Se film at T = 51C for an hour reduces the thickness by ~15% and increases the refractive index by ~0.5%. The optical bandgap does not change by more than 0.2%. While the decrease in the thickness is thought to be due to the rearrangement of the molecular clusters and the amorphous network, the increase in the refractive index is believed to be linked to the densification and the polarizability of the material. Although the influence of the thickness of the film, the temperature of the glass substrate, and the doping of 67ppm of chlorine on the optical properties of the a-Se film was found to be negligible, there are noticeable changes during aging. It was found that an aged a-Se film that was cold deposited has an increased refractive index that is believed to be caused by densification alone. In a period of 2 months, the thickness of a cold deposited a-Se:67ppm-Cl film shrinks by 3.5% and the refractive index increases by 3.7%. The optical bandgap of the film decreases by 0.6%. Similar aging trends in the thickness, the refractive index, and the optical bandgap were also observed in a cold deposited a-Se film but no significant changes, at least not more than 0.5% deviation, were noted in a period of about 1-3 weeks in any aging a-Se films that were hot deposited or annealed

Parallel computations and control of adaptive structures

The equations of motion for structures with adaptive elements for vibration control are presented for parallel computations to be used as a software package for real-time control of flexible space structures. A brief introduction of the state-of-the-art parallel computational capability is also presented. Time marching strategies are developed for an effective use of massive parallel mapping, partitioning, and the necessary arithmetic operations. An example is offered for the simulation of control-structure interaction on a parallel computer and the impact of the approach presented for applications in other disciplines than aerospace industry is assessed

Investigating neovascularization in rat decellularized intestine - an in vitro platform for studying angiogenesis

One of the main challenges currently faced by tissue engineers is the loss of tissues post implantation due to delayed neovascularization. Several strategies are under investigation to create vascularized tissue but none have yet overcome this problem. In this study we produced a decellularized natural vascular scaffold from rat intestine to use as an in vitro platform for neovascularization studies for tissue engineered constructs. Decellularization resulted in almost complete (97%) removal of nuclei and DNA, while collagen, glycosaminoglycans and laminin content was preserved. Decellularization did, however, result in the loss of elastin and fibronectin. Some proangiogenic factors were retained, as fragments of decellularized intestine were able to stimulate angiogenesis in the chick chorioallantoic membrane assay. We demonstrated that decellularization left perfusable vascular channels intact, and these could be repopulated with human dermal microvascular endothelial cells. Optimization of reendothelialisation of the vascular channels showed this was improved by continuous perfusion of the vasculature and further improved by infusion of human dermal fibroblasts into the intestinal lumen, from where they invaded into the decellularized tissue. Finally we explored the ability of the perfused cells to form new vessels. In the absence of exogenous angiogenic stimuli, Dll4, a marker of endothelial capillary-tip cell activation during sprouting angiogenesis was absent, indicating the reformed vasculature was largely quiescent. However, after addition of VEGFA, Dll4 positive endothelial cells could be detected, demonstrating this engineered vascular construct maintained its capacity for neovascularization. In summary we have demonstrated how a natural xenobiotic vasculature can be used as an in vitro model platform to study 3 neovascularization and provide information on factors that are critical for efficient reendothelialisation of decellularized tissue

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

Is the Convergence of Accounting Standards Good for Stock Markets?

This paper examines the impact of the convergence of Hong Kong Accounting Standard 40 (HKAS 40) with the International Financial Reporting Standard (IFRS) on the stock prices of firms in the property industry. Using a sample of 22111 firm-day observations, we show that the new standard has a negative impact on the stock performance of these firms.Hong Kong Accounting Standard 40, Event Window, Stock Return.