Glucocorticoid therapy for trauma--ready for prime time?

Methods\ud Objective\ud To test the efficacy of hydrocortisone therapy in trauma patients.\ud \ud Design\ud Multicenter randomized, double blind, placebocontrolled study.\ud \ud Setting\ud Seven intensive care units (ICUs) in France during November 2006 to August 2009.\ud \ud Subjects\ud 150 patients with severe trauma who required ICU stay for at least 48 hours were included in the study.\ud \ud Intervention\ud Patients were randomly assigned to a continuous intravenous infusion of either hydrocortisone (200 mg/day for 5 days, followed by 100 mg on day 6 and 50 mg on day 7) or placebo. The treatment was stopped if patients had an appropriate adrenal response.\ud \ud Outcomes\ud Hospital-acquired pneumonia within 28 days. Secondary outcomes included the duration of mechanical ventilation, ICU length of stay, hyponatremia, and death.\ud \ud Results\ud An intention-to-treat (ITT) analysis included 149 patients and the modified ITT analysis included 113 patients with corticosteroid insufficiency. In the ITT analysis, 26 of 73 patients (35.6%) treated with hydrocortisone and 39 of 76 patients (51.3%) receiving placebo developed hospital -acquired pneumonia by day 28 (hazard ratio (HR), 0.51; 95% confidence interval (CI), 0.30-0.83; P = 0.007). In the modified ITT analysis, 20 of 56 patients (35.7%) in the hydrocortisone group and 31 of 57 patients (54.4%) in the placebo group developed hospital-acquired pneumonia by day 28 (HR, 0.47; 95% CI, 0.25-0.86; P = 0.01). Mechanical ventilation-free days increased with hydrocortisone use by 4 days (95% CI, 2-7; P = 0.001) in the ITT analysis and 6 days (95% CI, 2-11; P < 0.001) in the modified ITT analysis. Hyponatremia was observed in 7 of 76 (9.2%) in the placebo group vs. none in the hydrocortisone group (absolute difference, −9%; 95% CI, −16% to −3%; P = 0.01). Four of 76 patients (5.3%) in the placebo group and 6 of 73 (8.2%) in the hydrocortisone group died (absolute difference, 3%; 95% CI, −5% to 11%; P = 0.44).\ud \ud Conclusions\ud In intubated trauma patients, the use of an intravenous stress-dose of hydrocortisone, compared with placebo, resulted in a decreased risk of hospital-acquired pneumonia

D-SPACE4Cloud: A Design Tool for Big Data Applications

The last years have seen a steep rise in data generation worldwide, with the development and widespread adoption of several software projects targeting the Big Data paradigm. Many companies currently engage in Big Data analytics as part of their core business activities, nonetheless there are no tools and techniques to support the design of the underlying hardware configuration backing such systems. In particular, the focus in this report is set on Cloud deployed clusters, which represent a cost-effective alternative to on premises installations. We propose a novel tool implementing a battery of optimization and prediction techniques integrated so as to efficiently assess several alternative resource configurations, in order to determine the minimum cost cluster deployment satisfying QoS constraints. Further, the experimental campaign conducted on real systems shows the validity and relevance of the proposed method

Performance Degradation and Cost Impact Evaluation of Privacy Preserving Mechanisms in Big Data Systems

Big Data is an emerging area and concerns managing datasets whose size is beyond commonly used software tools ability to capture, process, and perform analyses in a timely way. The Big Data software market is growing at 32% compound annual rate, almost four times more than the whole ICT market, and the quantity of data to be analyzed is expected to double every two years. Security and privacy are becoming very urgent Big Data aspects that need to be tackled. Indeed, users share more and more personal data and user-generated content through their mobile devices and computers to social networks and cloud services, losing data and content control with a serious impact on their own privacy. Privacy is one area that had a serious debate recently, and many governments require data providers and companies to protect users’ sensitive data. To mitigate these problems, many solutions have been developed to provide data privacy but, unfortunately, they introduce some computational overhead when data is processed. The goal of this paper is to quantitatively evaluate the performance and cost impact of multiple privacy protection mechanisms. A real industry case study concerning tax fraud detection has been considered. Many experiments have been performed to analyze the performance degradation and additional cost (required to provide a given service level) for running applications in a cloud system

Constructing Search Spaces for Search-Based Software Testing Using Neural Networks

A central requirement for any Search-Based Software Testing (SBST) technique is a convenient and meaningful fitness landscape. Whether one follows a targeted or a diversification driven strategy, a search landscape needs to be large, continuous, easy to construct and representative of the underlying property of interest. Constructing such a landscape is not a trivial task often requiring a significant manual effort by an expert. We present an approach for constructing meaningful and convenient fitness landscapes using neural networks (NN) – for targeted and diversification strategies alike. We suggest that output of an NN predictor can be interpreted as a fitness for a targeted strategy. The NN is trained on a corpus of execution traces and various properties of interest, prior to searching. During search, the trained NN is queried to predict an estimate of a property given an execution trace. The outputs of the NN form a convenient search space which is strongly representative of a number of properties. We believe that such a search space can be readily used for driving a search towards specific properties of interest. For a diversification strategy, we propose the use of an autoencoder; a mechanism for compacting data into an n-dimensional “latent” space. In it, datapoints are arranged according to the similarity of their salient features. We show that a latent space of execution traces possesses characteristics of a convenient search landscape: it is continuous, large and crucially, it defines a notion of similarity to arbitrary observations

Solving the Task Variant Allocation Problem in Distributed Robotics

We consider the problem of assigning software processes (or tasks) to hardware processors in distributed robotics environments. We introduce the notion of a task variant, which supports the adaptation of software to specific hardware configurations. Task variants facilitate the trade-off of functional quality versus the requisite capacity and type of target execution processors. We formalise the problem of assigning task variants to processors as a mathematical model that incorporates typical constraints found in robotics applications; the model is a constrained form of a multi-objective, multi-dimensional, multiple-choice knapsack problem. We propose and evaluate three different solution methods to the problem: constraint programming, a constructive greedy heuristic and a local search metaheuristic. Furthermore, we demonstrate the use of task variants in a real instance of a distributed interactive multi-agent navigation system, showing that our best solution method (constraint programming) improves the system’s quality of service, as compared to the local search metaheuristic, the greedy heuristic and a randomised solution, by an average of 16, 31 and 56% respectively

Explaining cross-cultural service interactions in tourism with Shenkar’s Cultural Friction

In this paper, we commence a new dialogue on cross-cultural research in tourism. Using Shenkar’s (2001) metaphor of cultural friction as the analytical framework, we examine crosscultural service interactions between guests and service-providers in a luxury hotel. Cultural friction departs from, and extends, the notion of ‘cultural distance’, as it recognises asymmetry in social-economic conditions and considers the goals and the influence of control and power between the interacting parties. We use the Critical Incident Technique and Narrative Inquiry as the data collection technique and analytical approach respectively. The findings reveal that guests and service-providers use a number of strategies to exert power and gain control during their interactions, including subjective essentialism and stereotyping, to achieve their goals. The implications for tourism and hospitality management include providing cross-cultural sensitivity training to service-providers, ensuring a cultural-diverse employee composition, and to foster cross-cultural understanding amongst employees. We further suggest to develop strategies to facilitate effective cross-cultural service interactions based on evidence about cultural norms, expectations and behaviours from specific cultural groups. Further research is recommended to connect specific interactions between the interacting parties to examine whether the various strategies used leads to effective cross-cultural communication

MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters

Microbial Biotechnolog

Effect of remote ischaemic conditioning on clinical outcomes in patients with acute myocardial infarction (CONDI-2/ERIC-PPCI): a single-blind randomised controlled trial.

BACKGROUND: Remote ischaemic conditioning with transient ischaemia and reperfusion applied to the arm has been shown to reduce myocardial infarct size in patients with ST-elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI). We investigated whether remote ischaemic conditioning could reduce the incidence of cardiac death and hospitalisation for heart failure at 12 months. METHODS: We did an international investigator-initiated, prospective, single-blind, randomised controlled trial (CONDI-2/ERIC-PPCI) at 33 centres across the UK, Denmark, Spain, and Serbia. Patients (age >18 years) with suspected STEMI and who were eligible for PPCI were randomly allocated (1:1, stratified by centre with a permuted block method) to receive standard treatment (including a sham simulated remote ischaemic conditioning intervention at UK sites only) or remote ischaemic conditioning treatment (intermittent ischaemia and reperfusion applied to the arm through four cycles of 5-min inflation and 5-min deflation of an automated cuff device) before PPCI. Investigators responsible for data collection and outcome assessment were masked to treatment allocation. The primary combined endpoint was cardiac death or hospitalisation for heart failure at 12 months in the intention-to-treat population. This trial is registered with ClinicalTrials.gov (NCT02342522) and is completed. FINDINGS: Between Nov 6, 2013, and March 31, 2018, 5401 patients were randomly allocated to either the control group (n=2701) or the remote ischaemic conditioning group (n=2700). After exclusion of patients upon hospital arrival or loss to follow-up, 2569 patients in the control group and 2546 in the intervention group were included in the intention-to-treat analysis. At 12 months post-PPCI, the Kaplan-Meier-estimated frequencies of cardiac death or hospitalisation for heart failure (the primary endpoint) were 220 (8·6%) patients in the control group and 239 (9·4%) in the remote ischaemic conditioning group (hazard ratio 1·10 [95% CI 0·91-1·32], p=0·32 for intervention versus control). No important unexpected adverse events or side effects of remote ischaemic conditioning were observed. INTERPRETATION: Remote ischaemic conditioning does not improve clinical outcomes (cardiac death or hospitalisation for heart failure) at 12 months in patients with STEMI undergoing PPCI. FUNDING: British Heart Foundation, University College London Hospitals/University College London Biomedical Research Centre, Danish Innovation Foundation, Novo Nordisk Foundation, TrygFonden