Electrical characteristics and memory behavior of Ge3N4GaAs MIS devices

MIS devices have been fabricated by the low temperature chemical vapor deposition of Ge₃N₄ on n-GaAs. From the current-voltage data an estimate of the Ge₃N₄ dielectric constant is made as 6.3 ± 0.2 and devices exhibit a breakdown field strength of ～ 5 × 10⁶ V/cm. Capacitance and conductance measurements have been performed to investigate the electrical characteristics of the Ge₃N₄GaAs interface. The interface properties of the devices are found to depend on the Ge₃N₄ deposition parameters. No major hysteresis is observed in the C-V plot and under large negative gate bias, the capacitance increases as the measurement frequency is lowered. Interface state distribution, evaluated from the conductance data, is found to have a minimum density of states of 2 × 10¹¹ cm^?2 eV^?1 with a distinct shoulder between 0.4 and 0.55 eV from the conduction band. This shoulder is assigned to an electron trap level and from thermally stimulated current measurements we obtained the density of traps as 3 × 10¹⁷ cm^?3.GaAs-MNOS devices have also been fabricated and their charge storage properties have been studied. Pulse voltages as large as 30–35 V are needed to write/erase the memory in the devices.     

Analysis of tapered-land hybrid aerostatic journal bearings

Results of the analysis of hybrid (aerostatic and aerodynamic) taperedland ournal bearings are presented. For a known bearing geometry, the Reynolds equation is reduced to a set of partial differential equations by using a first-order perturbation method. These differential equations are solved by a finite-difference numerical technique. The effects of various design and operational parameters on the load-carrying capacity and the attitude angle of the bearing were studied. The results are expressed in terms of non-dimensional parameters to enable their direct use for design purposes.     

Preparation and Evaluation of Methotrexate-Loaded Biodegradable Polyanhydride Microspheres

Methotrexate-loaded biodegradable polyanhydride microspheres were prepared by modified hot-melt technique and aqueous solvent evaporation technique. The effect of particle size, drug loading and microencapsulation technique on the in vitro drug release was studied. The in vitro release of methotrexate was evaluated using an automated flow-through cell system. The release profile consisted of burst release and sustained release phases. The burst release from the microspheres prepared by the modified technique was lower than that from the aqueous solvent evaporation technique. In addition, the microspheres with lower loadings released smaller amounts during the burst release phase. For a given loading and processing technique, the amount released by burst decreased with an increase in particle size. The microspheres prepared by the modified hot-melt technique with 10% loading and 177-250 μm size fraction gave desirable prolonged release. This formulation was tested in vivo in rats by subcutaneous implantation. The peak serum level of methotrexate was reached between 15-18 hours compared to that between 0-3 hours observed following the administration of an equivalent dose of methotrexate solution. No microspheres were found at the site of implantation at 48 hours post-implantation.     

Catalytic dehydrogenation of cyclohexane over Ag-M/ACC catalysts for hydrogen supply

Dehydrogenation of cyclohexane to benzene has been carried out over Ag supported on activated carbon cloth (Ag/ACC) catalysts using a spray- pulse reactor. Hydrogen evolution was studied for hydrogen storage and supply system applications. The maximum rate of hydrogen evolution rate using monometallic Ag/ACC catalysts was 6.9 mmol/g_met/min for Ag loading of 10 wt%. An enhanced hydrogen evolution was observed by adding a small amount of noble metal (1 wt% Pt, Pd, Rh) to the Ag based catalysts. A synergistic effect was observed in the case of the Pt promoted catalysts on the hydrogen production were twice as compared to 10 wt% Ag catalyst only.     

Boosted multivariate trees for longitudinal data

Machine learning methods provide a powerful approach for analyzing longitudinal data in which repeated measurements are observed for a subject over time. We boost multivariate trees to fit a novel flexible semi-nonparametric marginal model for longitudinal data. In this model, features are assumed to be nonparametric, while feature-time interactions are modeled semi-nonparametrically utilizing P-splines with estimated smoothing parameter. In order to avoid overfitting, we describe a relatively simple in sample cross-validation method which can be used to estimate the optimal boosting iteration and which has the surprising added benefit of stabilizing certain parameter estimates. Our new multivariate tree boosting method is shown to be highly flexible, robust to covariance misspecification and unbalanced designs, and resistant to overfitting in high dimensions. Feature selection can be used to identify important features and feature-time interactions. An application to longitudinal data of forced 1-second lung expiratory volume (FEV1) for lung transplant patients identifies an important feature-time interaction and illustrates the ease with which our method can find complex relationships in longitudinal data.     

Genotypic characterization of Listeria spp. isolated from fresh water fish

A total of 200 samples (muscles and viscera, 100 of each) of fresh water fish, walking catfish (Clarias batrachus) were screened for Listeria spp. All the samples were subjected to a two-step enrichment followed by plating on selective media. Confirmation of the isolates was on the basis of biochemical characters, haemolysis on blood agar and Christie, Atkins, Munch Petersen test. A total of 39 isolates of Listeria spp. were recovered. Of these 26 (67%), 8 (21%), 3 (8%) and 2 (5%) were Listeria monocytogenes, Listeria seeligeri, Listeria grayi and Listeria welshimeri, respectively. The isolates were subjected to a PCR assay for detection of the virulence-associated genes individually or together. The plcA, actA, hlyA and iap genes were detected in six strains, three genes (actA, hlyA and iap) in nine strains, the plcA, hlyA and iap in our strain, the hlyA and iap were in three strains, actA and hlyA in four strains, plcA and hlyA in our strain and hlyA in two strains. The hlyA and iap were also detected in L. seeligeri.     

Structural,morphological, and dynamic mechanical properties of Zn‐filled Nylon 11

Nylon 11 samples were filled with metal (Zn) fillers of two different concentrations (1 and 5% w/w) each. The samples in the form of disc were obtained by using hot press molder. The structural properties have been investigated using density measurement and wide angle X‐ray diffraction (WAXD) technique. The morphology of pure and Zn‐filled samples has been studied using scanning electron microscopy. Glass transition (T_g) temperature was determined using dynamic mechanical thermal analyzer (DMTA). The result shows that there is slight crystal modification due to the addition of metal fillers (Zn), and the crystallinity has improved. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 3094–3098, 2007     

Efficient mapping and acceleration of AES on custom multi‐core architectures

Multi‐core processors can deliver significant performance benefits for multi‐threaded software by adding processing power with minimal latency, given the proximity of the processors. Cryptographic applications are inherently complex and involve large computations. Most cryptographic operations can be translated into logical operations, shift operations, and table look‐ups. In this paper we design a novel processor (called mu‐core) with a reconfigurable Arithmetic Logic Unit, and design custom two‐dimensional multi‐core architectures on top of it to accelerate cryptographic kernels. We propose an efficient mapping of instructions from the multi‐core grid to the individual processor cores and illustrate the performance of AES‐128E algorithm over custom‐sized grids. The model was developed using Simulink and the performance analysis suggests a positive trend towards development of large multi‐core (or multi‐ µ‐core) architectures to achieve high throughputs in cryptographic operations. Copyright © 2010 John Wiley & Sons, Ltd.