A multi-server perishable inventory system with negative customer

In this paper, we consider a continuous review perishable inventory system with multi-server service facility. In such systems the demanded item is delivered to the customer only after performing some service, such as assembly of parts or installation, etc. Compared to many inventory models in which the inventory is depleted at the demand rate, however in this model, it is depleted, at the rate at which the service is completed. We assume that the arrivals of customers are according to a Markovian arrival process (MAP) and that the service time has exponential distribution. The ordering policy is based on (s, S) policy. The lead time is assumed to have exponential distribution. The customer who finds either all servers are busy or no item (excluding those in service) is in the stock, enters into an orbit of infinite size. These orbiting customers send requests at random time points for possible selection of their demands for service. The interval time between two successive request-time points is assumed to have exponential distribution. In addition to the regular customers, a second flow of negative customers following an independent MAP is also considered so that a negative customer will remove one of the customers from the orbit. The joint probability distribution of the number of busy servers, the inventory level and the number of customers in the orbit is obtained in the steady state. Various measures of stationary system performance are computed and the total expected cost per unit time is calculated. The results are illustrated numerically.     

Silk proteins for biomedical applications: Bioengineering perspectives

Biomaterials of either natural or synthetic origin are used to fabricate implantable devices, as carriers for bioactive molecules or as substrates to facilitate tissue regeneration. For the design of medical devices it is fundamental to use materials characterized by non-immunogenicity, biocompatibility, slow and/or controllable biodegradability, non-toxicity, and structural integrity. The success of biomaterial-derived biodevices tends to be based on the biomimetic architecture of the materials. Recently, proteins from natural precursors that are essentially structural and functional polymers, have gained popularity as biomaterials. The silks produced by silkworms or spiders are of particular interest as versatile protein polymers. These form the basis for diverse biomedical applications that exploit their unique biochemical nature, biocompatibility and high mechanical strength. This review discusses and summarizes the latest advances in the engineering of silk-based biomaterials, focusing specifically on the fabrication of diverse bio-mimetic structures such as films, hydrogels, scaffolds, nanofibers and nanoparticles; their functionalization and potential for biomedical applications.     

Design of vessels subjected to external pressure

An analytical procedure, developed to simulate the graphic method for the design of vessels subjected to external pressure or vacuum, suggested by the ASME Code, Section VIII, Division 1, is presented in this contribution. A comprehensive computer program based on this method is also presented. The program also covers the design of stiffener rings. The procedure can be easily extended to include other international standards such as the British and German codes, since the method is based on the concept of the number of lobes at collapse. The method produced reproducible results over the entire range of L/D₀ and D₀/t ratios of the code. The deviation observed at any point in this range is less than 0.5% for factor A. The variation in allowable pressure is less than 2%.     

Considering the fault dependency concept with debugging time lag in software reliability growth modeling using a power function of testing time

Since the early 1970s tremendous growth has been seen in the research of software reliability growth modeling.In general, software reliability growth models (SRGMs) are applicable to the late stages of testing in software development and they can provide useful information about how to improve the reliability of software products.A number of SRGMs have been proposed in the literature to represent time-dependent fault identification/removal phenomenon;still new models are being proposed that could fit a greater number of reliability growth curves.Often,it is assumed that detected faults axe immediately corrected when mathematical models are developed.This assumption may not be realistic in practice because the time to remove a detected fault depends on the complexity of the fault,the skill and experience of the personnel,the size of the debugging team,the technique,and so on.Thus,the detected fault need not be immediately removed,and it may lag the fault detection process by a delay effect factor.In this paper,we first review how different software reliability growth models have been developed,where fault detection process is dependent not only on the number of residual fault content but also on the testing time,and see how these models can be reinterpreted as the delayed fault detection model by using a delay effect factor.Based on the power function of the testing time concept,we propose four new SRGMs that assume the presence of two types of faults in the software:leading and dependent faults.Leading faults are those that can be removed upon a failure being observed.However,dependent faults are masked by leading faults and can only be removed after the corresponding leading fault has been removed with a debugging time lag.These models have been tested on real software error data to show its goodness of fit,predictive validity and applicability.     

On allocation of resources during testing phase of a modular software

To provide reliable software, it is tested over a wide range of testing environment. In the process, testing resources such as time, testing personnel etc. are used. These resources are not infinitely large and therefore need to be used judiciously. In this article, we discuss the testing resource allocation problem among modules to maximize the total fault removal from software consisting of several independent components (modules). For the resulting optimization problem, we define marginal testing effort function (MTEF), where the testing resource consumption is represented in terms of fault removal. The three MTEFs proposed in this article account for both exponential and S-shaped growth curves, which are commonly used in software reliability analysis. Results are illustrated numerically using different data sets.     

FX!32 a profile-directed binary translator

A new innovation from Digital allows most x86 Windows applications to run on Alpha platforms with good performance     

Encapsulation of enzymes within polymer spheres to create optical nanosensors for oxidative stress

We describe the fabrication and characterization of poly(ethylene glycol) (PEG) hydrogel spheres containing the enzyme horseradish peroxidase (HRP) for application as optical nanosensors for hydrogen peroxide. HRP was encapsulated in PEG hydrogel spheres by reverse emulsion photopolymerization, yielding spheres with a size range from 250 to 350 nm. Encapsulated HRP activity and sensitivity to hydrogen peroxide were investigated by the Amplex Red assay based on the fluorescence response as a function of H2O2. These HRP-loaded spheres were then introduced to murine macrophages with Amplex Red in the culture media. After phagocytosis, the biocompatibility of spheres was determined by live cell staining using calcein AM (5 microM). The HRP-loaded PEG hydrogel spheres were activated (i.e., fluorescent oxidized Amplex Red produced within the spheres) by oxidative stresses such as exogenous H2O2 (100 microM) and lipopolysaccharide (1 microg/mL), which induced the production of endogenous peroxide inside macrophages. The results presented here indicate that after polymerization, the enzyme activity of HRP was still maintained and that using these HRP-containing nanospheres, peroxide production could be sensed locally within cells.     

Exploitability prediction of software vulnerabilities

The number of security failure discovered and disclosed publicly are increasing at a pace like never before. Wherein, a small fraction of vulnerabilities encountered in the operational phase are exploited in the wild. It is difficult to find vulnerabilities during the early stages of software development cycle, as security aspects are often not known adequately. To counter these security implications, firms usually provide patches such that these security flaws are not exploited. It is a daunting task for a security manager to prioritize patches for vulnerabilities that are likely to be exploitable. This paper fills this gap by applying different machine learning techniques to classify the vulnerabilities based on previous exploit-history. Our work indicates that various vulnerability characteristics such as severity, type of vulnerabilities, different software configurations, and vulnerability scoring parameters are important features to be considered in judging an exploit. Using such methods, it is possible to predict exploit-prone vulnerabilities with an accuracy >85%. Finally, with this experiment, we conclude that supervised machine learning approach can be a useful technique in predicting exploit-prone vulnerabilities.     

InAs/GaAs nanostructures grown on patterned Si(001) by molecular beam epitaxy

The potential benefit from the combination of the optoelectronic and electronic functionality of III-V semiconductors with silicon technology is one of the most desired outcomes to date. Here we have systematically investigated the optical properties of InAs quantum structure embedded in GaAs grown on patterned sub-micron and nanosize holes on Si(001). III-V material tends to accumulate in the patterned sub-micron holes and a material depletion region is observed around holes when GaAs/InAs/GaAs is deposited directly on patterned Si(001). By use of a 60?nm SiO(2) layer and patterning sub-micron and nanosize holes through the oxide layer to the substrate, we demonstrate that high optical quality InAs nanostructures, both quantum dots and quantum wells, formed by a two-monolayer InAs layer embedded in GaAs can be epitaxially grown on Si(001). We also report the power-dependent and temperature-dependent photoluminescence spectra of these structures. The results show that hole diameter (sub-micron versus nanosize) has a strong effect on the structural and optical properties of GaAs/InAs/GaAs nanostructures.     

Diffusion approximations to the dependability of a transport system

In this paper the authors have attempted to derive distributions of the state variables which determine the dependability of a transport system in a big city. The two cases (1) univariate and (2) bivariate have been considered. The approach has been made through the use of the techniques of diffusion processes.