A tuple space implementation for large-scale infrastructures

Coordinating activities in a distributed system is an open research topic. Several models have been proposed to achieve this purpose such as message passing, publish/subscribe, workflows or tuple spaces. We have focused on the latter model, trying to overcome some of its disadvantages. In particular we have applied spatial database techniques to tuple spaces in order to increase their performance when handling a large number of tuples. Moreover, we have studied how structured peer to peer approaches can be applied to better distribute tuples on large networks. Using some of these result, we have developed a tuple space implementation for the Globus Toolkit that can be used by Grid applications as a coordination service. The development of such a service has been quite challenging due to the limitations imposed by XML serialization that have heavily influenced its design. Nevertheless, we were able to complete its implementation and use it to implement two different types of test applications: a completely parallelizable one and a plasma simulation that is not completely parallelizable. Using this last application we have compared the performance of our service against MPI. Finally, we have developed and tested a simple workflow in order to show the versatility of our service.

Adulthood with Turner Syndrome: Quality of life, psychosocial adjustment and clinical management in 70 Italian women

Abstract Background: Turner syndrome (TS) is a chromosomal abnormality (total or partial absence of one of the sexual chromosomes in some or all cells of the body), which affects approximately 1:2000 female. Principal characteristics are short stature and gonadal disgenesis. Clinical management consist of Growth Hormone (GH) treatment and oestrogen replacement therapy (HRT), to induce development of secondary characteristics and to avoid the sequelae of oestrogen deficiency. Aim of the study: To assess clinical management, quality of life (QoL) and general psychosocial adjustment of women with TS. Population: 70 adult Caucasian females with TS (mean age: 27.8, ± 7.6; range 18-48 y.). Setting: Specialist service for Rare Disease care, University Hospital. Methods: Subjects were required to fill in questionnaires collecting ASR, WHOQOL, and 8 open questions. Data were compared with those of the Italian population or to those collected in a comparison group (70 healthy females, mean age: 27.9, ±7.3, range 21-48 y.). Results: Women with TS are educated as well as the Italian Population, but they have a less successful professional life. They show good QoL in general, but they appeared less satisfied in social area. They had statistically higher scores than the comparison group for depression, anxiety and withdrawal. Are less involved in a love relationship. Diagnosis communication was mostly performed by doctors or parents, satisfaction was higher when information was given by parents. Main preoccupation about TS are infertility, feeling of being different and future health problem. Conclusions: Italian people with TS were generally well adapted and have a good QoL, but lived more often with parents and show impaired sentimental and sexual life. They have higher degree of psychological distress compared to a comparison group. Psychological intervention should firstly address parents in order to encourage an open communication on diagnosis issues and on sexual education.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

La città di Bologna e la sua storia: diffusione e condivisione delle conoscenze attraverso Webgis open source e Web Mapping

To understand a city and its urban structure it is necessary to study its history. This is feasible through GIS (Geographical Information Systems) and its by-products on the web. Starting from a cartographic view they allow an initial understanding of, and a comparison between, present and past data together with an easy and intuitive access to database information. The research done led to the creation of a GIS for the city of Bologna. It is based on varied data such as historical map, vector and alphanumeric historical data, etc.. After providing information about GIS we thought of spreading and sharing the collected data on the Web after studying two solutions available on the market: Web Mapping and WebGIS. In this study we discuss the stages, beginning with the development of Historical GIS of Bologna, which led to the making of a WebGIS Open Source (MapServer and Chameleon) and the Web Mapping services (Google Earth, Google Maps and OpenLayers).

Innovation and economic performance of the firms in the service sector: relevant issues and open problems

This thesis is a collection of essays related to the topic of innovation in the service sector. The choice of this structure is functional to the purpose of single out some of the relevant issues and try to tackle them, revising first the state of the literature and then proposing a way forward. Three relevant issues has been therefore selected: (i) the definition of innovation in the service sector and the connected question of measurement of innovation; (ii) the issue of productivity in services; (iii) the classification of innovative firms in the service sector. Facing the first issue, chapter II shows how the initial width of the original Schumpeterian definition of innovation has been narrowed and then passed to the service sector form the manufacturing one in a reduce technological form. Chapter III tackle the issue of productivity in services, discussing the difficulties for measuring productivity in a context where the output is often immaterial. We reconstruct the dispute on the Baumol’s cost disease argument and propose two different ways to go forward in the research on productivity in services: redefining the output along the line of a characteristic approach; and redefining the inputs, particularly analysing which kind of input it’s worth saving. Chapter IV derives an integrated taxonomy of innovative service and manufacturing firms, using data coming from the 2008 CIS survey for Italy. This taxonomy is based on the enlarged definition of “innovative firm” deriving from the Schumpeterian definition of innovation and classify firms using a cluster analysis techniques. The result is the emergence of a four cluster solution, where firms are differentiated by the breadth of the innovation activities in which they are involved. Chapter 5 reports some of the main conclusions of each singular previous chapter and the points worth of further research in the future.