41 research outputs found

    Changing Games and Evolving Contexts: Political Bargaining In European Energy Disputes

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    Energy has recently become a very important item on the political agenda of most Western countries; it is bound to be even more so in the future, due to the increasing scarcity of natural gas and oil. With Russia using the energy weapons to advance its economic and political goals, energy security has become a central topic in European politics. Important political bargaining models like game theory can offer valuable insights and contribute to the explanation of the outcome of important political confrontations like the ones between Russia and its former satellites. Game theory, however, fails to adequately account for an evolving context which can affect the preferences of the disputing actors, an issue which is likely to systematically produce inaccurate explanations and predictions. The relevance of the preferences of external actors will be demonstrated in this work by finding empirical evidence that the start of the dispute has damaged GDP and stock market performances of external players; in fact, this would give them a reason to become a relevant part of the game by exerting pressure on the two players so as to reach an agreement in the shortest time possible. The growing importance of external actors, I argue, needs to be modeled by game theory because, as it was especially the case for the Russia-Ukraine dispute in 2006, their role can be pivotal to in determining the duration and the outcome of the political bargaining. I select a Pooled Panel Nonlinear Auto Regressive Conditional Heteroskedasticity (PP-NARCH) model and Box-Tiao intervention models to support the validity of what I define a Fully-Fuzzy game. I rely more on the general message conveyed by the statistical models considered, thus freeing my analysis from the specificity of the model chosen for its better fit. My work, however, would be incomplete if simply finding empirical evidence of a negative effect of the gas disputes on the real growth of GDP and main stock markets of European countries. I summarize the most relevant statements, agreements, and partnerships which are likely to have exerted pressure on Russia and the other negotiating country

    The RISCOSS platform for risk management in open source software adoption

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    Managing risks related to OSS adoption is a must for organizations that need to smoothly integrate OSS-related practices in their development processes. Adequate tool support may pave the road to effective risk management and ensure the sustainability of such activity. In this paper, we present the RISCOSS platform for managing risks in OSS adoption. RISCOSS builds upon a highly configurable data model that allows customization to several types of scopes. It implements two different working modes: exploration, where the impact of decisions may be assessed before making them; and continuous assessment, where risk variables (and their possible consequences on business goals) are continuously monitored and reported to decision-makers. The blackboard-oriented architecture of the platform defines several interfaces for the identified techniques, allowing new techniques to be plugged in.Peer ReviewedPostprint (author’s final draft

    Managing risk in open source software adoption

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    By 2016 an estimated 95% of all commercial software packages will include Open Source Software (OSS). This extended adoption is yet not avoiding failure rates in OSS projects to be as high as 50%. Inadequate risk management has been identified among the top mistakes to avoid when implementing OSS-based solutions. Understanding, managing and mitigating OSS adoption risks is therefore crucial to avoid potentially significant adverse impact on the business. In this position paper we portray a short report of work in progress on risk management in OSS adoption processes. We present a risk-aware technical decision-making management platform integrated in a business-oriented decision-making framework, which together support placing technical OSS adoption decisions into organizational, business strategy as well as the broader OSS community context. The platform will be validated against a collection of use cases coming from different types of organizations: big companies, SMEs, public administration, consolidated OSS communities and emergent small OSS products.Postprint (published version

    Predictive Analysis on Twitter: Techniques and Applications

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    Predictive analysis of social media data has attracted considerable attention from the research community as well as the business world because of the essential and actionable information it can provide. Over the years, extensive experimentation and analysis for insights have been carried out using Twitter data in various domains such as healthcare, public health, politics, social sciences, and demographics. In this chapter, we discuss techniques, approaches and state-of-the-art applications of predictive analysis of Twitter data. Specifically, we present fine-grained analysis involving aspects such as sentiment, emotion, and the use of domain knowledge in the coarse-grained analysis of Twitter data for making decisions and taking actions, and relate a few success stories

    Massively distributed authorship of academic papers

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    Wiki-like or crowdsourcing models of collaboration can provide a number of benefits to academic work. These techniques may engage expertise from different disciplines, and potentially increase productivity. This paper presents a model of massively distributed collaborative authorship of academic papers. This model, developed by a collective of thirty authors, identifies key tools and techniques that would be necessary or useful to the writing process. The process of collaboratively writing this paper was used to discover, negotiate, and document issues in massively authored scholarship. Our work provides the first extensive discussion of the experiential aspects of large-scale collaborative research.Peer ReviewedPostprint (author's final draft

    Cultivation-Independent Methods Reveal Differences among Bacterial Gut Microbiota in Triatomine Vectors of Chagas Disease

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    Chagas disease is one of the most important endemic diseases of South and Central America. Its causative agent is the protozoan Trypanosoma cruzi, which is transmitted to humans by blood-feeding insects known as triatomine bugs. These vectors mainly belong to Rhodnius, Triatoma and Panstrongylus genera of Reduviidae. The bacterial communities in the guts of these vectors may have important effects on the biology of T. cruzi. For this reason, we analyzed the bacterial diversity hosted in the gut of different species of triatomines using cultivation-independent methods. Among Rhodnius sp., we observed similar bacterial communities from specimens obtained from insectaries or sylvatic conditions. Endosymbionts of the Arsenophonus genus were preferentially associated with insects of the Panstrongylus and Triatoma genera, whereas the bacterial genus Serratia and Candidatus Rohrkolberia were typical of Rhodnius and Dipetalogaster, respectively. The diversity of the microbiota tended to be the largest in the Triatoma genus, with species of both Arsenophonus and Serratia being detected in T. infestans

    Worldwide trends in population-based survival for children, adolescents, and young adults diagnosed with leukaemia, by subtype, during 2000–14 (CONCORD-3) : analysis of individual data from 258 cancer registries in 61 countries

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    Background Leukaemias comprise a heterogenous group of haematological malignancies. In CONCORD-3, we analysed data for children (aged 0–14 years) and adults (aged 15–99 years) diagnosed with a haematological malignancy during 2000–14 in 61 countries. Here, we aimed to examine worldwide trends in survival from leukaemia, by age and morphology, in young patients (aged 0–24 years). Methods We analysed data from 258 population-based cancer registries in 61 countries participating in CONCORD-3 that submitted data on patients diagnosed with leukaemia. We grouped patients by age as children (0–14 years), adolescents (15–19 years), and young adults (20–24 years). We categorised leukaemia subtypes according to the International Classification of Childhood Cancer (ICCC-3), updated with International Classification of Diseases for Oncology, third edition (ICD-O-3) codes. We estimated 5-year net survival by age and morphology, with 95% CIs, using the non-parametric Pohar-Perme estimator. To control for background mortality, we used life tables by country or region, single year of age, single calendar year and sex, and, where possible, by race or ethnicity. All-age survival estimates were standardised to the marginal distribution of young people with leukaemia included in the analysis. Findings 164563 young people were included in this analysis: 121328 (73·7%) children, 22963 (14·0%) adolescents, and 20272 (12·3%) young adults. In 2010–14, the most common subtypes were lymphoid leukaemia (28205 [68·2%] patients) and acute myeloid leukaemia (7863 [19·0%] patients). Age-standardised 5-year net survival in children, adolescents, and young adults for all leukaemias combined during 2010–14 varied widely, ranging from 46% in Mexico to more than 85% in Canada, Cyprus, Belgium, Denmark, Finland, and Australia. Individuals with lymphoid leukaemia had better age-standardised survival (from 43% in Ecuador to ≄80% in parts of Europe, North America, Oceania, and Asia) than those with acute myeloid leukaemia (from 32% in Peru to ≄70% in most high-income countries in Europe, North America, and Oceania). Throughout 2000–14, survival from all leukaemias combined remained consistently higher for children than adolescents and young adults, and minimal improvement was seen for adolescents and young adults in most countries. Interpretation This study offers the first worldwide picture of population-based survival from leukaemia in children, adolescents, and young adults. Adolescents and young adults diagnosed with leukaemia continue to have lower survival than children. Trends in survival from leukaemia for adolescents and young adults are important indicators of the quality of cancer management in this age group.peer-reviewe

    Global survival trends for brain tumors, by histology: analysis of individual records for 556,237 adults diagnosed in 59 countries during 2000–2014 (CONCORD-3)

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    Background: Survival is a key metric of the effectiveness of a health system in managing cancer. We set out to provide a comprehensive examination of worldwide variation and trends in survival from brain tumors in adults, by histology. Methods: We analyzed individual data for adults (15–99 years) diagnosed with a brain tumor (ICD-O-3 topography code C71) during 2000–2014, regardless of tumor behavior. Data underwent a 3-phase quality control as part of CONCORD-3. We estimated net survival for 11 histology groups, using the unbiased nonparametric Pohar Perme estimator. Results: The study included 556,237 adults. In 2010–2014, the global range in age-standardized 5-year net survival for the most common sub-types was broad: in the range 20%–38% for diffuse and anaplastic astrocytoma, from 4% to 17% for glioblastoma, and between 32% and 69% for oligodendroglioma. For patients with glioblastoma, the largest gains in survival occurred between 2000–2004 and 2005–2009. These improvements were more noticeable among adults diagnosed aged 40–70 years than among younger adults. Conclusions: To the best of our knowledge, this study provides the largest account to date of global trends in population-based survival for brain tumors by histology in adults. We have highlighted remarkable gains in 5-year survival from glioblastoma since 2005, providing large-scale empirical evidence on the uptake of chemoradiation at population level. Worldwide, survival improvements have been extensive, but some countries still lag behind. Our findings may help clinicians involved in national and international tumor pathway boards to promote initiatives aimed at more extensive implementation of clinical guidelines

    A layered approach to managing risks in OSS projects

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    In this paper, we propose a layered approach to managing risks in OSS projects. We define three layers: the first one for defining risk drivers by collecting and summarising available data from different data sources, including human-provided contextual information; the second layer, for converting these risk drivers into risk indicators; the third layer for assessing how these indicators impact the business of the adopting organisation. The contributions are: 1) the complexity of gathering data is isolated in one layer using appropriate techniques, 2) the context needed to interpret this data is provided by expert involvement evaluating risk scenarios and answering questionnaires in a second layer, 3) a pattern-based approach and risk reasoning techniques to link risks to business goals is proposed in the third layer.Peer Reviewe
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