Gerência de nuvens computacionais considerando diferentes classes de serviço.

O modelo de nuvens computacionais de infraestrutura como serviço (IaaS, na sigla em inglês) vem crescendo significativamente nos últimos anos. Este aumento em sua adoção trouxe uma grande diversidade de perfis de usuários, com diferentes tipos de aplicação, requisitos e orçamentos. Para satisfazer essas necessidades diversas,provedores deIas podem oferecer múltiplas classes de serviço, com diferentes preços e objetivos de nível de serviço (SLOs,na sigla em inglês)definidos para elas. Porém, gerenciar nuvens considerando múltiplas classes não é trivial, pois decisões de gerência de recursos podem gerar impactos diferentes dependendo de como cada classe é afetada. Além disso, a elasticidade da demanda e as incertezas da oferta de recursos típicas deste ambiente tornam ainda mais difícil o cumprimento dos diferentes SLOs mantendo uma alta utilização e um baixo custo. Nesta tese, investigou-se a hipótese de que quando provedores de nuvem deIaaS realizam uma gerência de recursos adequada, oferecendo múltiplas classes de serviço e cumprindo suas metas de qualidade de serviço(QoS,na sigla em inglês),eles obtêm uma alta utilização de seus recursos e aumentam a sua receita. Verificou-se que esta hipótese é verdadeira para os diversos cenários de nuvem avaliados neste trabalho,para os quais foram demonstradas grandes vantagens de se oferecer múltiplas classes de serviço na nuvem. Porém, observou-se que para ter esses benefícios é necessário realizar uma gerência de recursos eficiente,de tal forma que as garantias de QoS para as diferentes classes sejam definidas adequadamente e cumpridas pelo provedor. Desta forma, nesta tese também mostrou-se como provedores de IaaS podem realizar uma gerência de recursos adequada para múltiplas classes de serviço. Para isto, foram propostos e avaliados nesta tese: (1) um método baseado em predição para planejar a capacidade e as garantias de QoS de uma nova classe introduzida em uma nuvem de IaaS existente, com base na capacidade excedente da nuvem; (2) um modelo de controle de admissão baseado em predição,que permite ao provedor oferecer diferentes classes de serviço e cumprir SLOs de disponibilidade de VM para elas; e (3) um modelo analítico de planejamento de capacidade da nuvem que estima métricas de QoS para cada classe oferecida em diferentes cenários, e que busca encontrar a capacidade mínima necessária para cumprir as metas de taxa de admissão e disponibilidade de VM definidas para cada classe.Infrastructure as a Service (IaaS) is a cloud computing model that has been growing significantly in recent years. This increasingly adoption attracted users with different types of applications, requirements and budget to the cloud. To satisfy different users’s needs, IaaS providers can offer multiple service classes with different pricing and Service Level Objectives (SLOs) defined for them. However, managing such clouds considering multiple service classes is nottrivial, becauseres our cemanagement decisions may have different consequences depending on howeach classisaffected. Moreover, the demand elasticity and uncertain resource availability typically seen in cloudenvironments turns evenmore difficult for providers to fulfill different SLOs while having a high utilization and low infrastructure costs. In this thesis, we investigate the hypothesis that when IaaS cloud providers make an adequate resource management, offering multiple service classes and fulfilling their Quality of Service (QoS) guarantees, they achieve a high resource utilization and increase their revenue. We demonstrate that this hypothesis is true for the many different scenarios evaluated in this work,which shows great advantages on offering multiple service classes in the cloud. However, we also observe that cloud providers need an efficient resource management in order to have these benefits, in a way they can define and fulfill adequate SLOs for different classes. Thus, we also show in this thesis how IaaS providers can make adequate resource management decisions for multiple service classes, by proposing and evaluating: (1) a predictive method to planthe capacityand QoS guarantees of anew service class introducedin an existing IaaS cloud, based on unused resources; (2) a prediction-based admission control model that allows the provider to offer multiple classes and fulfill VM availability SLOs for them; and (3) a capacity planning analytical model that estimates QoS metrics for eachclass indifferents cenarios, and aimstofindthem in imumres ource capacity required to fulfill VM availability and admission rate SLOs for eachclass

Convergence calls: multimedia storytelling at British news websites

This article uses qualitative interviews with senior editors and managers from a selection of the UK's national online news providers to describe and analyse their current experimentation with multimedia and video storytelling. The results show that, in a period of declining newspaper readership and TV news viewing, editors are keen to embrace new technologies, which are seen as being part of the future of news. At the same time, text is still reported to be the cornerstone for news websites, leading to changes in the grammar and function of news video when used online. The economic rationale for convergence is examined and the article investigates the partnerships sites have entered into in order to be able to serve their audience with video content. In-house video is complementing syndicated content, and the authors examine the resulting developments in newsroom training and recruitment practices. The article provides journalism and interactive media scholars with case studies on the changes taking place in newsrooms as a result of the shift towards multimedia, multiplatform news consumption

Variations of training load, monotony, and strain and dose-response relationships with maximal aerobic speed, maximal oxygen uptake, and isokinetic strength in professional soccer players

This study aimed to identify variations in weekly training load, training monotony, and training strain across a 10-week period (during both, pre- and in-season phases); and to analyze the dose-response relationships between training markers and maximal aerobic speed (MAS), maximal oxygen uptake, and isokinetic strength. Twenty-seven professional soccer players (24.9±3.5 years old) were monitored across the 10-week period using global positioning system units. Players were also tested for maximal aerobic speed, maximal oxygen uptake, and isokinetic strength before and after 10 weeks of training. Large positive correlations were found between sum of training load and extension peak torque in the right lower limb (r = 0.57, 90%CI[0.15;0.82]) and the ratio agonist/antagonist in the right lower limb (r = 0.51, [0.06;0.78]). It was observed that loading measures fluctuated across the period of the study and that the load was meaningfully associated with changes in the fitness status of players. However, those magnitudes of correlations were small-to-large, suggesting that variations in fitness level cannot be exclusively explained by the accumulated load and loading profile

Implementation of Diabetes Prevention in Health Care Organizations: Best Practice Recommendations

Approximately 1 in 3 American adults has prediabetes, a condition characterized by blood glucose levels that are above normal, not in the type 2 diabetes ranges, and that increases the risk of developing type 2 diabetes. Evidence-based treatments can be used to prevent or delay type 2 diabetes in adults with prediabetes. The American Medical Association (AMA) has collaborated with health care organizations across the country to build sustainable diabetes prevention strategies. In 2017, the AMA formed the Diabetes Prevention Best Practices Workgroup (DPBP) with representatives from 6 health care organizations actively implementing diabetes prevention. Each organization had a unique strategy, but all included the National Diabetes Prevention Program lifestyle change program as a core evidence-based intervention. DPBP established the goal of disseminating best practices to guide other health care organizations in implementing diabetes prevention and identifying and managing patients with prediabetes. Workgroup members recognized similarities in some of their basic steps and considerations and synthesized their practices to develop best practice recommendations for 3 strategy maturity phases. Recommendations for each maturity phase are classified into 6 categories: (1) organizational support; (2) workforce and funding; (3) promotion and dissemination; (4) clinical integration and support; (5) evaluation and outcomes; (6) and program. As the burden of chronic disease grows, prevention must be prioritized and integrated into health care. These maturity phases and best practice recommendations can be used by any health care organization committed to diabetes prevention. Further research is suggested to assess the impact and adoption of diabetes prevention best practices

Virtual morality in the helping professions: simulated action and resilience

Recent advances in virtual technologies have allowed the investigation of simulated moral actions in aversive moral dilemmas. Previous studies have employed diverse populations in order to explore these actions, with little research considering the significance of occupation on moral decision-making. For the first time, in this study we have investigated simulated moral actions in Virtual Reality made by professionally trained paramedics and fire service incident commanders who are frequently faced with and must respond to moral dilemmas. We found that specially trained individuals showed distinct empathic and related personality trait scores and that these declined with years of experience working in the profession. Supporting the theory that these professionals develop resilience in moral conflict, reduced emotional arousal was observed during virtual simulations of a distressing dilemma. Furthermore, trained professionals demonstrated less regret following the execution of a moral action in virtual reality when compared to untrained control populations. We showed that, contrary to previous research, trained individuals made the same moral judgments and moral actions as untrained individuals, though showing less arousal and regret. In the face of increasing concerns regarding empathy decline in healthcare professionals, we suggest that the nature of this decline is complex and likely reflects the development of a necessary emotional resilience to distressing events

On ethically solvent leaders : the roles of pride and moral identity in predicting leader ethical behavior.

The popular media has repeatedly pointed to pride as one of the key factors motivating leaders to behave unethically. However, given the devastating consequences that leader unethical behavior may have, a more scientific account of the role of pride is warranted. The present study differentiates between authentic and hubristic pride and assesses its impact on leader ethical behavior, while taking into consideration the extent to which leaders find it important to their self-concept to be a moral person. In two experiments we found that with higher levels of moral identity, authentically proud leaders are more likely to engage in ethical behavior than hubristically proud leaders, and that this effect is mediated by leaders’ motivation to act selflessly. A field survey among organizational leaders corroborated that moral identity may bring the positive effect of authentic pride and the negative effect of hubristic pride on leader ethical behavior to the forefront

Iron deposition and inflammation in multiple sclerosis. Which one comes first?

Whether iron deposition is an epiphenomenon of the multiple sclerosis (MS) disease process or may play a primary role in triggering inflammation and disease development remains unclear at this time, and should be studied at the early stages of disease pathogenesis. However, it is difficult to study the relationship between iron deposition and inflammation in early MS due to the delay between the onset of symptoms and diagnosis, and the poor availability of tissue specimens. In a recent article published in BMC Neuroscience, Williams et al. investigated the relationship between inflammation and iron deposition using an original animal model labeled as "cerebral experimental autoimmune encephalomyelitis", which develops CNS perivascular iron deposits. However, the relative contribution of iron deposition vs. inflammation in the pathogenesis and progression of MS remains unknown. Further studies should establish the association between inflammation, reduced blood flow, iron deposition, microglia activation and neurodegeneration. Creating a representative animal model that can study independently such relationship will be the key factor in this endeavor

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected