92 research outputs found

    Vaccines in children with inflammatory bowel disease: Brief review

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    Incidence of inflammatory bowel diseases (IBDs), including Crohn’s disease (CD) and ulcerative colitis (UC), is increasing worldwide. Children with IBDs have a dysfunctional immune system and they are frequently treated with immunomodulating drugs and biological therapy, which significantly impair immune system functions and lead to an increased risk of infections. Vaccines are essential to prevent at least part of these infections and this explains why strict compliance to the immunization guidelines specifically prepared for IBD patients is strongly recommended. However, several factors might lead to insufficient immunization. In this paper, present knowledge on the use of vaccines in children with IBDs is discussed. Literature review showed that despite a lack of detailed quantification of the risk of infections in children with IBDs, these children might have infections more frequently than age-matched healthy subjects, and at least in some cases, these infections might be even more severe. Fortunately, most of these infections could be prevented when recommended schedules of immunization are carefully followed. Vaccines given to children with IBDs generally have adequate immunogenicity and safety. Attention must be paid to live attenuated vaccines that can be administered only to children without or with mild immune system function impairment. Vaccination of their caregivers is also recommended. Unfortunately, compliance to these recommendations is generally low and multidisciplinary educational programs to improve vaccination coverage must be planned, in order to protect children with IBD from vaccine-preventable diseases

    Automated migration of build scripts using dynamic analysis and search-based refactoring

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    The efficiency of a build system is an important factor for developer productivity. As a result, developer teams have been increasingly adopting new build systems that allow higher build parallelization. However, migrating the existing legacy build scripts to new build systems is a tedious and error-prone process. Unfortunately, there is insufficient support for automated migration of build scripts, making the migration more problematic. We propose the first dynamic approach for automated migration of build scripts to new build systems. Our approach works in two phases. First, from a set of execution traces, we synthesize build scripts that accurately capture the intent of the original build. The synthesized build scripts are typically long and hard to maintain. Second, we apply refactorings that raise the abstraction level of the synthesized scripts (e.g., introduce functions for similar fragments). As different refactoring sequences may lead to different build scripts, we use a search-based approach that explores various sequences to identify the best (e.g., shortest) build script. We optimize search-based refactoring with partial-order reduction to faster explore refactoring sequences. We implemented the proposed two phase migration approach in a tool called METAMORPHOSIS that has been recently used at Microsoft

    Search based software engineering: Trends, techniques and applications

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    © ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

    A Hybrid Model for Dynamic Simulation of Custom Software Projects in a Multiproject Environment

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    This paper describes SimHiProS, a hybrid simulation model of software production. The goal is to gain insight on the dynamics induced by resource sharing in multiproject management. In order to achieve it the hierarchy of decisions in a multiproject organization is modeled and some resource allocation methods based on algorithms from the OR/AI domain are used. Other critical issues such as the hybrid nature of software production and the effects of measurement and control are also incorporated in the model. Some first results are presented.Ministerio de Ciencia e Innovación TIN2004-06689-C03-03Ministerio de Ciencia e Innovación TIN2007-67843-C06-0

    M3G: Maximum Margin Microarray Gridding

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    <p>Abstract</p> <p>Background</p> <p>Complementary DNA (cDNA) microarrays are a well established technology for studying gene expression. A microarray image is obtained by laser scanning a hybridized cDNA microarray, which consists of thousands of spots representing chains of cDNA sequences, arranged in a two-dimensional array. The separation of the spots into distinct cells is widely known as microarray image gridding.</p> <p>Methods</p> <p>In this paper we propose M<sup>3</sup>G, a novel method for automatic gridding of cDNA microarray images based on the maximization of the margin between the rows and the columns of the spots. Initially the microarray image rotation is estimated and then a pre-processing algorithm is applied for a rough spot detection. In order to diminish the effect of artefacts, only a subset of the detected spots is selected by matching the distribution of the spot sizes to the normal distribution. Then, a set of grid lines is placed on the image in order to separate each pair of consecutive rows and columns of the selected spots. The optimal positioning of the lines is determined by maximizing the margin between these rows and columns by using a maximum margin linear classifier, effectively facilitating the localization of the spots.</p> <p>Results</p> <p>The experimental evaluation was based on a reference set of microarray images containing more than two million spots in total. The results show that M<sup>3</sup>G outperforms state of the art methods, demonstrating robustness in the presence of noise and artefacts. More than 98% of the spots reside completely inside their respective grid cells, whereas the mean distance between the spot center and the grid cell center is 1.2 pixels.</p> <p>Conclusions</p> <p>The proposed method performs highly accurate gridding in the presence of noise and artefacts, while taking into account the input image rotation. Thus, it provides the potential of achieving perfect gridding for the vast majority of the spots.</p

    A queueing model for managing small projects under uncertainties

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    We consider a situation in which a home improvement project contractor has a team of regular crew members who receive compensation even when they are idle. Because both projects arrivals and the completion time of each project are uncertain, the contractor needs to manage the utilization of his crews carefully. One common approach adopted by many home improvement contractors is to accept multiple projects to keep his crew members busy working on projects to generate positive cash flows. However, this approach has a major drawback because it causes "intentional" (or foreseeable) project delays. Intentional project delays can inflict explicit and implicit costs on the contractor when frustrating customers abandon their projects and/or file complaints or lawsuits. In this paper, we present a queueing model to capture uncertain customer (or project) arrivals and departures, along with the possibility of customer abandonment. Also, associated with each admission policy (i.e., the maximum number of projects that the contractor will accept), we model the underlying tradeoff between accepting too many projects (that can increase customer dissatisfaction) and accepting too few projects (that can reduce crew utilization). We examine this tradeoff analytically so as to determine the optimal admission policy and the optimal number of crew members. We further apply our model to analyze other issues including worker productivity and project pricing. Finally, our model can be extended to allow for multiple classes of projects with different types of crew members

    Properties that influence business process management maturity and its effect on organizational performance

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    Abstract BPM maturity is a measure to evaluate how professionally an organization manages its business processes. Previous research provides evidence that higher BPM maturity leads to better performance of processes and of the organization as a whole. It also claims that different organizations should strive for different levels of maturity, depending on their properties. This paper presents an empirical investigation of these claims, based on a sample of 120 organizations and looking at a selection of organizational properties. Our results reveal that higher BPM maturity contributes to better performance, but only up to a point. Interestingly, it contradicts the popular belief that higher innovativeness is associated with lower BPM maturity, rather showing that higher innovativeness is associated with higher BPM maturity. In addition, the paper shows that companies in different regions have a different level of BPM maturity. These findings can be used as a benchmark and a motivation for organizations to increase their BPM maturity
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