Energy Efficiency Support through Intra-Layer Cloud Stack Adaptation

Energy consumption is a key concern in cloud computing. The paper reports on a cloud architecture to support energy efficiency at service construction, deployment, and operation. This is achieved through SaaS, PaaS and IaaS intra-layer self-adaptation in isolation. The self-adaptation mechanisms are discussed, as well as their implementation and evaluation. The experimental results show that the overall architecture is capable of adapting to meet the energy goals of applications on a per layer basis

Energy-Aware Self-Adaptation for Application Execution on Heterogeneous Parallel Architectures

Hardware in High Performance Computing environments in recent years have increasingly become more heterogeneous in order to improve computational performance. An additional aspect of such systems is the management of power and energy consumption. The increase in heterogeneity requires middleware and programming model abstractions to eliminate additional complexities that it brings, while also offering opportunities such as improved power management. In this paper, we explore application level self-adaptation including aspects such as automated configuration and deployment of applications to different heterogeneous infrastructure and for their redeployment. This therefore not only mitigates complexities associated with heterogeneous devices but aims to take advantage of the heterogeneity. The overall result of this paper is a self-adaptive framework that manages application Quality of Service (QoS) at runtime, which includes the automatic migration of applications between different accelerated infrastructures. Discussion covers when this migration is appropriate and quantifies the likely benefits

Extreme citizen science: lessons learned from initiatives around the globe

The participation of communities living in high conservation value areas is increasingly valued in conservation science and practice, potentially producing multiple positive impacts on both biodiversity and local people. Here, we discuss important steps for implementing a successful extreme citizen science project, based on four case studies from conservation projects with Pantaneiro fishers living in Brazilian Pantanal wetland, Baka hunter-gatherers and Fang farmers in lowland wet forest in Cameroon, Maasai pastoralists in Kenya, and Ju|'hoansi rangers living in the semiarid deserts of Namibia. We highlight the need for a high level of trust between the target communities and project developers, communities' right to choose the data they will be collecting, and researchers' openness to include new tools that were not initially planned. By following these steps, conservation scientists can effectively create bottom-up collaborations with those living on the frontlines of conservation through community-led extreme citizen science

Towards an Energy-Aware Framework for Application Development and Execution in Heterogeneous Parallel Architectures

The Transparent heterogeneous hardware Architecture deployment for eNergy Gain in Operation (TANGO) project’s goal is to characterise factors which affect power consumption in software development and operation for Heterogeneous Parallel Hardware (HPA) environments. Its main contribution is the combination of requirements engineering and design modelling for self-adaptive software systems, with power consumption awareness in relation to these environments. The energy efficiency and application quality factors are integrated into the application lifecycle (design, implementation and operation). To support this, the key novelty of the project is a reference architecture and its implementation. Moreover, a programming model with built-in support for various hardware architectures including heterogeneous clusters, heterogeneous chips and programmable logic devices is provided. This leads to a new cross-layer programming approach for heterogeneous parallel hardware architectures featuring software and hardware modelling. Application power consumption and performance, data location and time-criticality optimization, as well as security and dependability requirements on the target hardware architecture are supported by the architecture

Development of a questionnaire to measure health-related quality of life (HRQoL) in patients with atrial fibrillation (AF-QoL)

<p>Abstract</p> <p>Background</p> <p>The Health-Related Quality of Life (HRQoL) assessment in atrial fibrillation (AF) patients has traditionally been carried out in a poorly standardised fashion, or via the use of non disease-specific HRQoL questionnaires. The development of a HRQoL questionnaire with a good measuring performance will allow for a standardised assessment of the impact of this disease on the patient's daily living.</p> <p>Methods</p> <p>A bibliography review was conducted to identify the most relevant domains of daily living in AF patients. Subsequently, a focus group was created with the aid of cardiologists, and 17 patients were interviewed to identify the most-affected HRQoL domains. A qualitative analysis of the interview answers was performed, which was used to develop a pilot questionnaire administered to a 112-patient sample. Based on patient responses, an analysis was carried out following the statistical procedures defined by the Classical Test Theory (CTT) and the Item Response Theory (IRT). Reliablility was assessed via Cronbach's coefficient alpha and item-total score correlations. A factorial analysis was performed to determine the number of domains. For each domain, a Rasch analysis was carried out, in order to reduce and stand hierarchically the questionnaire items.</p> <p>Results</p> <p>By way of the bibliography review and the expert focus group, 10 domains were identified. The patient interviews allowed for the identification of 286 items that later were downsized to 40 items. The resultant preliminary questionnaire was administered to a 112-patient sample (pilot study). The Rasch analysis led to the definition of two domains, comprising 7 and 11 items respectively, which corresponded to the psychological and physical domains (18 items total), thereby giving rise to the initial AF-QoL-18 questionnaire. Cronbach's coefficient alpha was acceptable (0.91).</p> <p>Conclusion</p> <p>An initial HRQoL questionnaire, AFQoL-18, has been developed to assess HRQoL in AF patients.</p

Towards energy aware cloud computing application construction

The energy consumption of cloud computing continues to be an area of significant concern as data center growth continues to increase. This paper reports on an energy efficient interoperable cloud architecture realised as a cloud toolbox that focuses on reducing the energy consumption of cloud applications holistically across all deployment models. The architecture supports energy efficiency at service construction, deployment and operation. We discuss our practical experience during implementation of an architectural component, the Virtual Machine Image Constructor (VMIC), required to facilitate construction of energy aware cloud applications. We carry out a performance evaluation of the component on a cloud testbed. The results show the performance of Virtual Machine construction, primarily limited by available I/O, to be adequate for agile, energy aware software development. We conclude that the implementation of the VMIC is feasible, incurs minimal performance overhead comparatively to the time taken by other aspects of the cloud application construction life-cycle, and make recommendations on enhancing its performance

Trazodone plus pregabalin combination in the treatment of fibromyalgia: a two-phase, 24-week, open-label uncontrolled study

<p>Abstract</p> <p>Background</p> <p>Although trazodone is frequently used by fibromyalgia patients, its efficacy on this disease has not been adequately studied. If effective, pregabalin, whose beneficial effects on pain and sleep quality in fibromyalgia have been demonstrated, could complement the antidepressant and anxiolytic effects of trazodone. The aim of the present study was to assess the effectiveness of trazodone alone and in combination with pregabalin in the treatment of fibromyalgia.</p> <p>Methods</p> <p>This was an open-label uncontrolled study. Trazodone, flexibly dosed (50-300 mg/day), was administered to 66 fibromyalgia patients during 12 weeks; 41 patients who completed the treatment accepted to receive pregabalin, also flexibly dosed (75-450 mg/day), added to trazodone treatment for an additional 12-week period. Outcome measures included the Fibromyalgia Impact Questionnaire (FIQ), the Pittsburgh Sleep Quality Index (PSQI), the Beck Depression Inventory (BDI), the Hospital Anxiety and Depression Scale (HADS), the Brief Pain Inventory (BPI), the Short-Form Health Survey (SF-36), and the Patients' Global Improvement scale (PGI). Emergent adverse reactions were recorded. Data were analyzed with repeated measures one-way ANOVA and paired Student's t test.</p> <p>Results</p> <p>Treatment with trazodone significantly improved global fibromyalgia severity, sleep quality, and depression, as well as pain interference with daily activities although without showing a direct effect on bodily pain. After pregabalin combination additional and significant improvements were seen on fibromyalgia severity, depression and pain interference with daily activities, and a decrease in bodily pain was also apparent. During the second phase of the study, only two patients dropped out due to side effects.</p> <p>Conclusions</p> <p>Trazodone significantly improved fibromyalgia severity and associated symptomatology. Its combination with pregabalin potentiated this improvement and the tolerability of the drugs in association was good.</p> <p>Trial Registration</p> <p>ClinicalTrials.gov: <a href="http://www.clinicaltrials.gov/ct2/show/NCT00791739">NCT00791739</a></p

Valuation of preference-based measures: Can existing preference data be used to select a smaller sample of health states?

Background Different countries have different preferences regarding health, and there are different value sets for popular preference-based measures across different countries. However, the cost of collecting data to generate country-specific value sets can be prohibitive for countries with smaller population size or low- and middle-income countries (LMIC). This paper explores whether existing preference weights could be modelled alongside a small own country valuation study to generate representative estimates. This is explored using a case study modelling UK data alongside smaller US samples to generate US estimates. Methods We analyse EQ-5D valuation data derived from representative samples of the US and UK populations using time trade-off to value 42 health states. A nonparametric Bayesian model was applied to estimate a US value set using the full UK dataset and subsets of the US dataset for 10, 15, 20 and 25 health states. Estimates are compared to a US value set estimated using US values alone using mean predictions and root mean square error. Results The results suggest that using US data elicited for 20 health states alongside the existing UK data produces similar predicted mean valuations and RMSE as the US value set, while 25 health states produce the exact features. Conclusions The promising results suggest that existing preference data could be combined with a small valuation study in a new country to generate preference weights, making own country value sets more achievable for LMIC. Further research is encouraged

Regulation of type 1 diabetes development and B-cell activation in nonobese diabetic mice by early life exposure to a diabetogenic environment

Microbes, including viruses, influence type 1 diabetes (T1D) development, but many such influences remain undefined. Previous work on underlying immune mechanisms has focussed on cytokines and T cells. Here, we compared two nonobese diabetic (NOD) mouse colonies, NODlow and NODhigh, differing markedly in their cumulative T1D incidence (22% vs. 90% by 30 weeks in females). NODhigh mice harbored more complex intestinal microbiota, including several pathobionts; both colonies harbored segmented filamentous bacteria (SFB), thought to suppress T1D. Young NODhigh females had increased B-cell activation in their mesenteric lymph nodes. These phenotypes were transmissible. Co-housing of NODlow with NODhigh mice after weaning did not change T1D development, but T1D incidence was increased in female offspring of co-housed NODlow mice, which were exposed to the NODhigh environment both before and after weaning. These offspring also acquired microbiota and B-cell activation approaching those of NODhigh mice. In NODlow females, the low rate of T1D was unaffected by cyclophosphamide but increased by PD-L1 blockade. Thus, environmental exposures that are innocuous later in life may promote T1D progression if acquired early during immune development, possibly by altering B-cell activation and/or PD-L1 function. Moreover, T1D suppression in NOD mice by SFB may depend on the presence of other microbial influences. The complexity of microbial immune regulation revealed in this murine model may also be relevant to the environmental regulation of human T1D