New approaches to disease causation research based on the sufficient-component cause model

Up to date, the sufficient-component cause model seems to be a theoretical framework for disease causation in epidemiology, and its implications in epidemiological research methods is currently still limited. Recently, pitfalls in current epidemiological research methods were addressed based on the sufficient-component cause model; hence, new research approaches are needed as alternatives. Therefore, this paper aims to review and suggest new epidemiological methods used to assess disease causation. A new approach was discussed to identify potential mechanisms of disease occurrence which may be useful for risk prediction and disease prevention. In addition, a novel “exposed case-control” design was introduced to identify potential component causes. Furthermore, this paper suggested a new approach of conducting a systematic review/meta-analysis related to causation studies

Classical causation research practices and sufficient-component cause model – Appraisal and pitfalls

The sufficient-component cause model is one of the most discussed recent theories in disease causation. Despite some limitations, it seems one of the best theories to explain real world phenomena. It seems that this model has many implications on the current classical research methods related to disease causation. However, these implications have not been sufficiently explored. Therefore, based on the sufficient-component cause model, this paper aims to review, identify and rectify pitfalls in the classical causation research practices, especially those related to cohort study design

AMACoT: a marketplace architecture for trading Cloud of Things resources

Cloud of Things (CoT) is increasingly viewed as a paradigm that can satisfy the diverse requirements of emerging IoT applications. The potential of CoT is not yet realised due to challenges in sharing and reusing IoT physical resources across multiple applications. Existing approaches provide small-scale and hardware-dependent shared access to IoT resources. This paper considers using market mechanisms to commoditise CoT resources as the approach to enable shared access to CoT resources and to improve their reusability. In order to achieve this, the requirements for trading CoT resources are discussed to conceptualise the proposed approach. A generic description model for CoT resource is introduced to quantify the value of CoT resources. In this paper, a marketplace architecture for trading CoT resources referred to as AMACoT is proposed. By formulating the trading of CoT resources as an optimisation problem, the proposed approach is experimentally validated. The evaluation measures the system performance and verifies the optimisation problem using three evolutionary algorithms. The evaluation of the optimisation algorithms demonstrates the optimality of trading CoT resources solutions in terms of resource cost, resource utilisation, provider lock-in and provider profit

Adaptive trading of Cloud of Things resources

Cloud of Things (CoT) consists of heterogeneous Cloud and Internet of Things (IoT) resources. CoT increasingly requires adaptive run-time management due to the CoT dynamism, environmental uncertainties and unpredictable changes in IoT resources. Adapting to these changes benefits particularly trading of CoT resources where the adaptability of traded resources and applications remains a challenge. Runtime changes in CoT trading environments can impact vital aspects including resource allocation, resource utilisation and application performance. This paper adopts monitoring, analysis, planning and execution (MAPE) model from autonomic computing to support adaptations when trading CoT resources. This is achieved by applying the MAPE model to systematically capture and identify changes in CoT environment. Based on the identified adaptations, an adaptive model is proposed to react to these changes

A multiobjective QoS model for trading Cloud of Things resources

The emerging Cloud of Things (CoT) paradigm promises to meet the diverse requirements of many real-world applications, which previously could not be fulfilled by either Cloud Computing or Internet of Things (IoT). Trading CoT resources is a challenging aspect particularly when managing Quality of Service (QoS) as resource providers and application developers have different priorities. This paper focuses on the challenge of supporting QoS when trading CoT resources and performing resource allocation. The contributions of this paper are 1) the problem of managing QoS while trading CoT resources is investigated as an optimisation problem 2) a QoS model is proposed to solve the problem by optimising five different QoS objectives 3) evaluation which confirms the feasibility of the proposed model in optimising diverse QoS requirements

A heuristic approach for the allocation of resources in large-scale computing infrastructures

An increasing number of enterprise applications are intensive in their consumption of IT, but are infrequently used. Consequently, organizations either host an oversized IT infrastructure or they are incapable of realizing the benefits of new applications. A solution to the challenge is provided by the large-scale computing infrastructures of Clouds and Grids which allow resources to be shared. A major challenge is the development of mechanisms that allow efficient sharing of IT resources. Market mechanisms are promising, but there is a lack of research in scalable market mechanisms. We extend the Multi-Attribute Combinatorial Exchange mechanism with greedy heuristics to address the scalability challenge. The evaluation shows a trade-off between efficiency and scalability. There is no statistical evidence for an influence on the incentive properties of the market mechanism. This is an encouraging result as theory predicts heuristics to ruin the mechanism’s incentive properties. Copyright © 2015 John Wiley & Sons, Ltd

Sero-Survey of Equine Infectious Anemia in the Sultanate of Oman during 2007-2009

Equine infectious anemia (EIA) is a fatal and relapsing infectious disease of equines caused by the lentivirus of Retroviridae family which occurs world-wide. It tends to become an inapparent infection if death does not result from the acute clinical attack. The virus persists in infected animals for life and can be detected by serological tests like enzyme-linked immunosorbent assay (ELISA) and agar gel immunodiffusion (AGID) tests. Keeping in view the importance of EIA, a sero-survey and passive surveillance was designed to establish the status of EIA in Oman. For the current study, ELISA was carried out on 331 random horse serum samples collected from all over Oman and 262 serum samples submitted from race horses. Four (0.67%) out of total 593 serum samples were found positive on ELISA. These samples were further tested by agar gel immunodiffusion (AGID) test for the confirmation and were found negative. Based on the analysis of the samples, it can be assumed that the horse population in the Sultanate was free of the disease during the study period (2007-2009)

Multi-attribute combinatorial marketplaces for cloud resource trading

Cloud Computing represents a new era where computing is offered as a service rather than as a physical product. The next level of flexibility will be achieved when Cloud Computing services can be automatically traded. This paper focuses on providing the foundation for simple and flexible Cloud resource trading. This is achieved by proposing vocabularies for the trading of Cloud resources and algorithms for a Cloud marketplace. A multi-attribute combinatorial marketplace is proposed as a solution for situations where Cloud resources need to be traded in combination (bundles). Vocabularies are introduced to serve as a foundation to build standards for Cloud resources trading

A cross-sectional seroepidemiological study of camel Camelus dromedarius brucellosis and associated risk factors in the Sultanate of Oman

Brucellosis is a globally distributed and economically devastating zoonotic disease of multiple species, including camels. Human and livestock brucellosis is prevalent in Oman, especially in southern Dhofar governorates of Oman, where camels share habitat and have close contact with other susceptible species. We conducted a randomized crosssectional sero-epidemiological study to investigate the seroprevalence of brucellosis in camels of Oman. The sera from 2,250 camels from 552 geographically marked farms were screened through Rose Bengal plate agglutination test and later confirmed by the competitive ELISA (COMPLIZA, VLA, UK). In total, nine [0.4%, confidence interval (CI) 0.4, 0.8] camels from eight (1.5%, CI 0.6, 2.8) herds were tested positive for brucellosis. The highest prevalence was recorded in Dhofar (3.7%, CI 1.4, 7.9) and the lowest in Sharqiyah (1.3%, CI 0.0, 7.2) governorate (p = 0.052). All seropositive camels were of local breed and females. Seroprevalence was higher (0.5%, CI 0.2, 1.0) in adults (>4 yr of age) as compared with young (≤4 yr of age) camels (0.2%, CI 0.0, 0.8). The results of binary logistic regression indicated that camel herds located in south (Dhofar) [odds ratio (OR) 6.39, CI 1.01, 40.67], practice of open replacement system (OR 14.49, CI 1.83, 114.51) and with history of abortions (OR 8.01, CI 1.34, 47.77) were more likely to test positive for brucellosis. We conclude that brucellosis is endemic at a low level in camels of Oman and a control strategy based upon test-and-slaughter/inclusion of camels in the current vaccination program after carefully planned vaccine evaluation studies could be considered to control it