Functionalization of gauzes with liposomes entrapping an anti-inflammatory drug: A strategy to improve wound healing

From ancientness, suitable materials have been developed to cover the wounds in order to prevent infections and promote proper wound healing. In this study, the successful development of functionalized nonwoven gauzes with liposomes entrapping anti-inflammatory piroxicam is reported. Piroxicam is a non-steroidal anti-inflammatory drug (NSAID) that can suppress a persistent inflammatory response, leading to improved wound healing. The results demonstrated that the highest NSAID concentration released is achieved when gauzes were previously cationized with poly(diallyldimethylammonium chloride) (PDDA) and high concentration of phospholipid (≈3000 μM) and multilamellar liposomes (MLVs) were used. MLVs were also the best vehicle considering their biocompatibility with skin human fibroblasts, where no toxicity was observed for neither of the tested conditions.The developed functionalized gauzes can be, therefore, a good strategy to treat chronic wounds.     

Warranty Claims Data Analysis Considering Sales Delay

Sales delay is the time interval from the date of manufacture to the date of sale. In analysing warranty claims data, the existing research relating to the sales delay has mainly focussed on estimating the probability distribution of the sales delay. Longer sales delay may lead to more warranty claims as it can affect the post‐sale reliability of products. However, research into this problem has received little attention. This article estimates the expected number of warranty claims under both renewing and non‐renewing warranty policies taking into account the sales delay. We consider the case with three states, the sales delay state, the operating state and the failed state. We extend the three‐state case into an n state system case, where n ? 3. We then give numerical examples to demonstrate the application of the derived equations. We also present a simulation and a case study where we estimate the reliability of products with three states. Copyright © 2012 John Wiley & Sons, Ltd.     

Geometric quantum computation

Abstract

We describe in detail a general strategy for implementing a conditional geometric phase between two spins. Combined with single-spin operations, this simple operation is a universal gate for quantum computation, in that any unitary transformation can be implemented with arbitrary precision using only single-spin operations and conditional phase shifts. Thus quantum geometrical phases can form the basis of any quantum computation. Moreover, as the induced conditional phase depends only on the geometry of the paths executed by the spins it is resilient to certain types of errors and offers the potential of a naturally fault-tolerant way of performing quantum computation.     

Optimisation of a serine protease coupling to Eudragit S‐100 by experimental design techniques

A full factorial design was used to study the influence of four different variables, namely polymer concentration, carbodiimide concentration, time of reaction and blocking agent concentration, on the coupling of a serine protease into a soluble–insoluble polymer (Eudragit S‐100). All of the four factors studied have played a critical role in the protease coupling. Response surface methodology was used as an optimisation strategy to attain a conjugate with high activity yield and operational stability at 60 °C. Under optimised conditions (Eudragit, 2.5% w/v, carbodiimide, 0.2% w/v, coupling time, 1 h and blocking agent concentration, 0.05%), the conjugate activity yield was about 45% and its operational stability at 60 °C was increased by 1.7 times. After reusing the conjugate for five cycles, the remaining activity was still 72% of the initial value when compared with the native enzyme. Several tests confirmed that the enzyme was covalently crosslinked to Eudragit, which represents an improvement in the carbodiimide coupling of proteases into soluble–insoluble polymers. Copyright © 2005 Society of Chemical Industry     

Representing Hyper-arithmetical Sets by Equations over Sets of Integers

Systems of equations with sets of integers as unknowns are considered. It is shown that the class of sets representable by unique solutions of equations using the operations of union and addition, defined as S+T={m+n?Om??S,n??T}, and with ultimately periodic constants is exactly the class of hyper-arithmetical sets. Equations using addition only can represent every hyper-arithmetical set under a simple encoding. All hyper-arithmetical sets can also be represented by equations over sets of natural numbers equipped with union, addition and subtraction $S \mathop {\mbox {$-^{\hspace {-.5em}\cdot }\,\,$}}T=\{m-n \mid m \in S, n \in T, m \geq n\}$ . Testing whether a given system has a solution is $\varSigma ^{1}_{1}$ -complete for each model. These results, in particular, settle the expressive power of the most general types of language equations, as well as equations over subsets of free groups.     

Scalable plasma simulation with ELMFIRE using efficient data structures for process communication

We describe the parallel full-f gyrokinetic particle-in-cell plasma simulation code ELMFIRE and the issue of solving an electrostatic potential from particle data distributed across several MPI (Message Passing Interface) processes. The potential is solved through a linear system with a strongly sparse matrix and ELMFIRE stores data of the estimated non-zero diagonals of the whole matrix in every MPI process. We present and compare several memory efficient structures for gathering the matrix data while keeping only a local part of the matrix in each process. We also demonstrate that these alternative structures improve scalability, thus enabling ELMFIRE to use more MPI processes and a finer time and space scale than before without sacrificing performance.     

On Metrics to Distinguish Skype Flows from HTTP Traffic

Skype is a Voice over IP (VoIP) Internet application that is gaining huge popularity in recent years. A key point to Skype popularity is its capability to dynamically adapt itself to operate behind firewalls or network proxies. A common way adopted by Skype to delude these network devices is to use port 80, normally expected to comprise HTTP traffic. In this paper, we propose metrics and investigate statistical tests intended to clearly distinguish Skype flows from HTTP traffic. We validate our study using real-world experimental datasets gathered at a commercial Internet Service Provider (ISP). Our experimental results suggest that the proposed methodology may be seen as a promising building block towards a system to detect general protocol anomalies in HTTP traffic.     

An unsupervised approach to feature discretization and selection

Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.