Controlled Release of Salicylic Acid from Biodegradable Cross-Linked Polyesters

The purpose of this work was to develop a family of crosslinked poly(xylitol adipate salicylate)s with a wide range of tunable release properties for delivering pharmacologically active salicylic acid. The synthesis parameters and release conditions were varied to modulate polyester properties and to understand the mechanism of release. Varying release rates were obtained upon longer curing (35% in the noncured polymer to 10% in the cured polymer in 7 days). Differential salicylic acid loading led to the synthesis of polymers with variable cross-linking and the release could be tuned (100% release for the lowest loading to 30% in the highest loading). Controlled release was monitored by changing various factors, and the release profiles were dependent on the stoichiometric composition, pH, curing time, and presence of enzyme. The polymer released a combination of salicylic acid and disalicylic acid, and the released products were found to be nontoxic. Minimal hemolysis and platelet activation indicated good blood compatibility. These polymers qualify as ``bioactive'' and ``resorbable'' and can, therefore, find applications as immunomodulatory resorbable biomaterials with tunable release properties.

Coupling geomorphology parameters with lithology for micro-level groundwater resource assessment: a case study from semi-arid hard rock terrain in Tamil Nadu, India

The standard procedure of groundwater resource estimation in India till date is based on the specific yield parameters of each rock type (lithology) derived through pumping test analysis. Using the change in groundwater level, specific yield, and area of influence, groundwater storage change could be estimated. However, terrain conditions in the form of geomorphological variations have an important bearing on the net groundwater recharge. In this study, an attempt was made to use both lithology and geomorphology as input variables to estimate the recharge from different sources in each lithology unit influenced by the geomorphic conditions (lith-geom), season wise separately. The study provided a methodological approach for an evaluation of groundwater in a semi-arid hard rock terrain in Tirunelveli, Tamil Nadu, India. While characterizing the gneissic rock, it was found that the geomorphologic variations in the gneissic rock due to weathering and deposition behaved differently with respect to aquifer recharge. The three different geomorphic units identified in gneissic rock (pediplain shallow weathered (PPS), pediplain moderate weathered (PPM), and buried pediplain moderate (BPM)) showed a significant variation in recharge conditions among themselves. It was found from the study that Peninsular gneiss gives a net recharge value of 0.13 m/year/unit area when considered as a single unit w.r.t. lithology, whereas the same area considered with lith-geom classes gives recharge values between 0.1 and 0.41 m/year presenting a different assessment. It is also found from this study that the stage of development (SOD) for each lith-geom unit in Peninsular gneiss varies from 168 to 230 %, whereas the SOD is 223 % for the lithology as a single unit.

Fast and slow climate responses to CO2 and solar forcing: A linear multivariate regression model characterizing transient climate change

Climate change in response to a change in external forcing can be understood in terms of fast response to the imposed forcing and slow feedback associated with surface temperature change. Previous studies have investigated the characteristics of fast response and slow feedback for different forcing agents. Here we examine to what extent that fast response and slow feedback derived from time-mean results of climate model simulations can be used to infer total climate change. To achieve this goal, we develop a multivariate regression model of climate change, in which the change in a climate variable is represented by a linear combination of its sensitivity to CO2 forcing, solar forcing, and change in global mean surface temperature. We derive the parameters of the regression model using time-mean results from a set of HadCM3L climate model step-forcing simulations, and then use the regression model to emulate HadCM3L-simulated transient climate change. Our results show that the regression model emulates well HadCM3L-simulated temporal evolution and spatial distribution of climate change, including surface temperature, precipitation, runoff, soil moisture, cloudiness, and radiative fluxes under transient CO2 and/or solar forcing scenarios. Our findings suggest that temporal and spatial patterns of total change for the climate variables considered here can be represented well by the sum of fast response and slow feedback. Furthermore, by using a simple 1-D heat-diffusion climate model, we show that the temporal and spatial characteristics of climate change under transient forcing scenarios can be emulated well using information from step-forcing simulations alone.

Parameters Inversion of Fluid-Saturated Porous Media Based on Neural Networks

The multi-layers feedforward neural network is used for inversion of material constants of fluid-saturated porous media. The direct analysis of fluid-saturated porous media is carried out with the boundary element method. The dynamic displacement responses obtained from direct analysis for prescribed material parameters constitute the sample sets training neural network. By virtue of the effective L-M training algorithm and the Tikhonov regularization method as well as the GCV method for an appropriate selection of regularization parameter, the inverse mapping from dynamic displacement responses to material constants is performed. Numerical examples demonstrate the validity of the neural network method.

Influence of cluster-assembly parameters on the field emission properties of nanostructured carbon films

Supersonic cluster beam deposition has been used to produce films with different nanostructures by controlling the deposition parameters such as the film thickness, substrate temperature and cluster mass distribution. The field emission properties of cluster-assembled carbon films have been characterized and correlated to the evolution of the film nanostructure. Threshold fields ranging between 4 and 10 V/mum and saturation current densities as high as 0.7 mA have been measured for samples heated during deposition. A series of voltage ramps, i.e., a conditioning process, was found to initiate more stable and reproducible emission. It was found that the presence of graphitic particles (onions, nanotube embryos) in the films substantially enhances the field emission performance. Films patterned on a micrometer scale have been conditioned spot by spot by a ball-tip anode, showing that a relatively high emission site density can be achieved from the cluster-assembled material. (C) 2002 American Institute of Physics.

Sensitivity Analysis of Dimensionless Parameters for Physical Simulation of Water-Flooding Reservoir

A numerical approach to optimize dimensionless parameters of water-flooding porous media flows is proposed based on the analysis of the sensitivity factor defined as the variation ration of a target function with respect to the variation of dimensionless parameters. A complete set of scaling criteria for water-flooding reservoir of five-spot well pattern case is derived from the 3-D governing equations, involving the gravitational force, the capillary force and the compressibility of water, oil and rock. By using this approach, we have estimated the influences of each dimensionless parameter on experimental results and thus sorted out the dominant ones with larger sensitivity factors ranging from10-4to10-0 .

Phase-variable surface structures are required for infection of Campylobacter jejuni by bacteriophages.

This study characterizes the interaction between Campylobacter jejuni and the 16 phages used in the United Kingdom typing scheme by screening spontaneous mutants of the phage-type strains and transposon mutants of the sequenced strain NCTC 11168. We show that the 16 typing phages fall into four groups based on their patterns of activity against spontaneous mutants. Screens of transposon and defined mutants indicate that the phage-bacterium interaction for one of these groups appears to involve the capsular polysaccharide (CPS), while two of the other three groups consist of flagellatropic phages. The expression of CPS and flagella is potentially phase variable in C. jejuni, and the implications of these findings for typing and intervention strategies are discussed.

Simulating dynamic covariance structures for testing the adaptive behavior of variable selection algorithms (Invited Paper)

Variable selection for regression is a classical statistical problem, motivated by concerns that too large a number of covariates may bring about overfitting and unnecessarily high measurement costs. Novel difficulties arise in streaming contexts, where the correlation structure of the process may be drifting, in which case it must be constantly tracked so that selections may be revised accordingly. A particularly interesting phenomenon is that non-selected covariates become missing variables, inducing bias on subsequent decisions. This raises an intricate exploration-exploitation tradeoff, whose dependence on the covariance tracking algorithm and the choice of variable selection scheme is too complex to be dealt with analytically. We hence capitalise on the strength of simulations to explore this problem, taking the opportunity to tackle the difficult task of simulating dynamic correlation structures. © 2008 IEEE.

Models and algorithms for tracking of maneuvering objects using variable rate particle filters

Standard algorithms in tracking and other state-space models assume identical and synchronous sampling rates for the state and measurement processes. However, real trajectories of objects are typically characterized by prolonged smooth sections, with sharp, but infrequent, changes. Thus, a more parsimonious representation of a target trajectory may be obtained by direct modeling of maneuver times in the state process, independently from the observation times. This is achieved by assuming the state arrival times to follow a random process, typically specified as Markovian, so that state points may be allocated along the trajectory according to the degree of variation observed. The resulting variable dimension state inference problem is solved by developing an efficient variable rate particle filtering algorithm to recursively update the posterior distribution of the state sequence as new data becomes available. The methodology is quite general and can be applied across many models where dynamic model uncertainty occurs on-line. Specific models are proposed for the dynamics of a moving object under internal forcing, expressed in terms of the intrinsic dynamics of the object. The performance of the algorithms with these dynamical models is demonstrated on several challenging maneuvering target tracking problems in clutter. © 2006 IEEE.

Partial soi power LDMOS with a variable low-kappa; Dielectric buried layer and a buried P layer

A power LDMOS on partial silicon on insulator (PSOI) with a variable low-κ dielectric (VLKD) buried layer and a buried p (BP) layer is proposed (VLKD BPSOI). At a low κ value, the electric field strength in the buried dielectric (EI) is enhanced, and a Si window makes the substrate share the vertical voltage drop, leading to a high vertical breakdown voltage (BV). Moreover, three interface field peaks are introduced by the BP, the Si window, and the VLKD, which modulate the fields in the SOI layer, the VLKD layer, and the substrate; consequently, a high BV is obtained. Furthermore, the BP reduces the specific on-resistance (Ron), and the Si window alleviates the self-heating effect (SHE). The BV for VLKD BPSOI is enhanced by 34.5%, and Ron is decreased by 26.6%, compared with those for the conventional PSOI, and VLKD BPSOI also maintains a low SHE. © 2006 IEEE.

Refractive index and thickness analysis of natural silicon dioxide film growing on silicon with variable-angle spectroscopic ellipsometry

The refractive index and thickness of SiO2 thin films naturally grown on Si substrates were determined simultaneously within the wavelength range of 220-1100 nm with variable-angle spectroscopic ellipsometry. Different angles of incidence and wavelength ranges were chosen to enhance the analysis sensitivity for more accurate results. Several optical models describing the practical SiO2-Si system were investigated, and best results were obtained with the optical model, including an interface layer between SiO2 and Si, which proved the existence of the interface layer in this work as described in other publications.