Rationale and study design of a cross sectional study documenting the prevalence of Heart Failure amongst the minority ethnic communities in the UK: the E-ECHOES Study (Ethnic - Echocardiographic Heart of England Screening Study)

Background: Heart failure is an important cause of cardiovascular morbidity and mortality. Studies to date have not established the prevalence heart failure amongst the minority ethnic community in the UK. The aim of the E-ECHOES (Ethnic - Echocardiographic Heart of England Screening Study) is to establish, for the first time, the community prevalence and severity of left ventricular systolic dysfunction (LVSD) and heart failure amongst the South Asian and Black African-Caribbean ethnic groups in the UK.Methods/Design: This is a community based cross-sectional population survey of a sample of South Asian (i.e. those originating from India, Pakistan, Bangladesh) and Black African-Caribbean male and female subjects aged 45 years and over. Data collection undertaken using a standardised protocol comprising a questionnaire incorporating targeted clinical history taking, physical examination, and investigations with resting electrocardiography and echocardiography; and blood sampling with consent. This is the largest study on heart failure amongst these ethnic groups. Full data collection started in September 2006 and will be completed by August 2009.Discussion: The E-ECHOES study will enable the planning and delivery of clinically and cost-effective treatment of this common and debilitating condition within these communities. In addition it will increase knowledge of the aetiology and management of heart failure within minority ethnic communities

Comprehensive Survey for Cloud Computing Based Nature-Inspired Algorithms Optimization Scheduling

Many applications in the real world include optimizing specific targets, such as cost minimization, energy conservation, climate, and maximizing production, efficiency, and sustainability. The optimization problem is strongly non-linear with multifunctional landscapes under several dynamic, non-linear constraints in some instances. It is challenging to address those issues. Also, with the increasing strength of modern computers, simplistic brute force methods are still inefficient and unwanted. Practical algorithms are also vital for these implementations whenever possible. Cloud computing has become an essential and popular emerging computing environment that supports on-demand services and provides internet-based services. Cloud computing allows a range of services and tools to be easily accessed from anywhere in the world. Since cloud computing has global access to its services, there will always be threats and challenges facing its servers and services, such as; task scheduling, security, energy efficiency, network load, and other challenges. In the research area, many algorithms have been addressed to solve these problems. This paper investigates relevant analysis and surveys on the above topics, threats, and outlooks. This paper offers an overview of nature-inspired algorithms, their applications, and valuation, emphasizing cloud computing problems. Many problems in science and engineering can be viewed as optimization problems with complex non-linear constraints. Highly nonlinear solutions typically need advanced optimization algorithms, and conventional algorithms can have difficulty addressing these issues. Because of its simplicity and usefulness, nature-inspired algorithms are currently being used. There are nevertheless some significant concerns with computing and swarming intelligence influenced by evolution