Falls after discharge from hospital : is there a gap between older peoples' knowledge about falls prevention strategies and the research evidence?

Purpose: The aim of this study was to examine whether older people are prepared to engage in appropriate falls prevention strategies after discharge from hospital. Design and Methods We used a semi-structured interview to survey older patients about to be discharged from hospital and examined their knowledge regarding falls prevention strategies to utilize in the post-discharge period. The study was part of a prospective cohort study, nested within a larger, randomized controlled trial. Participants (n = 333) were asked to suggest strategies to reduce their falls risk at home after discharge, and their responses were compared with current reported research evidence for falls prevention interventions.  Results Participants’ strategies (n = 629) were classified into 7 categories: behavioral, support while mobilizing, approach to movement, physical environment, visual, medical, and activities or exercise. Although exercise has been identified as an effective falls risk reduction strategy, only 2.9% of participants suggested engaging in exercises. Falls prevention was most often conceptualized by participants as requiring 1 (35.4%) or 2 (40.8%) strategies for avoiding an accidental event, rather than engaging in sustained multiple risk reduction behaviors.  Implications Results demonstrate that older patients have low levels of knowledge about appropriate falls prevention strategies that could be used after discharge in spite of their increased falls risk during this period. Findings suggest that health care workers should design and deliver falls prevention education programs specifically targeted to older people who are to be discharged from hospital.

A security architecture for cloud storage combining proofs of retrievability and fairness

We investigate existing cloud storage schemes and identify limitations in each one based on the security services that they provide. We then propose a new cloud storage architecture that extends CloudProof of Popa et al. to provide availability assurance. This is accomplished by incorporating a proof of storage protocol. As a result, we obtain the first secure storage cloud computing scheme that furnishes all three properties of availability, fairness and freshness.

Geoproof : proofs of geographic location for cloud computing environment

Cloud computing has emerged as a major ICT trend and has been acknowledged as a key theme of industry by prominent ICT organisations. However, one of the major challenges that face the cloud computing concept and its global acceptance is how to secure and protect the data that is the property of the user. The geographic location of cloud data storage centres is an important issue for many organisations and individuals due to the regulations and laws that require data and operations to reside in specific geographic locations. Thus, data owners may need to ensure that their cloud providers do not compromise the SLA contract and move their data into another geographic location. This paper introduces an architecture for a new approach for geographic location assurance, which combines the proof of storage protocol (POS) and the distance-bounding protocol. This allows the client to check where their stored data is located, without relying on the word of the cloud provider. This architecture aims to achieve better security and more flexible geographic assurance within the environment of cloud computing.

Patients undergoing subacute rehabilitation have accurate expectations of their health-related quality of life at discharge

Background Expectations held by patients and health professionals may affect treatment choices and participation (by both patients and health professionals) in therapeutic interventions in contemporary patient-centered healthcare environments. If patients in rehabilitation settings overestimate their discharge health-related quality of life, they may become despondent as their progress falls short of their expectations. On the other hand, underestimating their discharge health-related quality of life may lead to a lack of motivation to participate in therapies if they do not perceive likely benefit. There is a scarcity of empirical evidence evaluating whether patients' expectations of future health states are accurate. The purpose of this study is to evaluate the accuracy with which older patients admitted for subacute in-hospital rehabilitation can anticipate their discharge health-related quality of life. Methods A prospective longitudinal cohort investigation of agreement between patients' anticipated discharge health-related quality of life (as reported on the EQ-5D instrument at admission to a rehabilitation unit) and their actual self-reported health-related quality of life at the time of discharge from this unit was undertaken. The mini-mental state examination was used as an indicator of patients' cognitive ability. Results Overall, 232(85%) patients had all assessment data completed and were included in analysis. Kappa scores ranged from 0.42-0.68 across the five EQ-5D domains and two patient cognition groups. The percentage of exact correct matches within each domain ranged from 69% to 85% across domains and cognition groups. Overall 40% of participants in each cognition group correctly anticipated all of their self-reported discharge EQ-5D domain responses. Conclusions Patients admitted for subacute in-hospital rehabilitation were able to anticipate the discharge health-related quality of life on the EQ-5D instrument with a moderate level of accuracy. This finding adds to the foundational empirical work supporting joint treatment decision making and patient-centered models of care during rehabilitation following acute illness or injury. Accurate patient expectations of the impact of treatment (or disease progression) on future health-related related quality of life is likely to allow patients and health professionals to successfully target interventions to priority areas where meaningful gains can be achieved.

A penalty-based grouping genetic algorithm for multiple composite SaaS components clustering in Cloud

Software as a Service (SaaS) in Cloud is getting more and more significant among software users and providers recently. A SaaS that is delivered as composite application has many benefits including reduced delivery costs, flexible offers of the SaaS functions and decreased subscription cost for users. However, this approach has introduced a new problem in managing the resources allocated to the composite SaaS. The resource allocation that has been done at the initial stage may be overloaded or wasted due to the dynamic environment of a Cloud. A typical data center resource management usually triggers a placement reconfiguration for the SaaS in order to maintain its performance as well as to minimize the resource used. Existing approaches for this problem often ignore the underlying dependencies between SaaS components. In addition, the reconfiguration also has to comply with SaaS constraints in terms of its resource requirements, placement requirement as well as its SLA. To tackle the problem, this paper proposes a penalty-based Grouping Genetic Algorithm for multiple composite SaaS components clustering in Cloud. The main objective is to minimize the resource used by the SaaS by clustering its component without violating any constraint. Experimental results demonstrate the feasibility and the scalability of the proposed algorithm.

Radiotherapy Monte Carlo simulation using cloud computing technology

Cloud computing allows for vast computational resources to be leveraged quickly and easily in bursts as and when required. Here we describe a technique that allows for Monte Carlo radiotherapy dose calculations to be performed using GEANT4 and executed in the cloud, with relative simulation cost and completion time evaluated as a function of machine count. As expected, simulation completion time decreases as 1=n for n parallel machines, and relative simulation cost is found to be optimal where n is a factor of the total simulation time in hours. Using the technique, we demonstrate the potential usefulness of cloud computing as a solution for rapid Monte Carlo simulation for radiotherapy dose calculation without the need for dedicated local computer hardware as a proof of principal. Funding source Cancer Australia (Department of Health and Ageing) Research Grant 614217

The El Chichon stratospheric cloud : solid particulates and settling rates

Sampling of the El Chichón stratospheric cloud in early May and in late July, 1982, showed that a significant proportion of the cloud consisted of solid particles between 2 μm and 40 μm size. In addition, many particles may have been part of larger aggregates or clusters that ranged in size from < 10 μm to > 50 μm. The majority of individual grains were angular aluminosilicate glass shards with various amounts of smaller, adhering particles. Surface features on individual grains include sulfuric acid droplets and larger (0.5 μm to 1 μm) sulfate gel droplets with various amounts of Na, Mg, Ca and Fe. The sulfate gels probably formed by the interaction of sulfur-rich gases and solid particles within the cloud soon after eruption. Ca-sulfate laths may have formed by condensation within the plume during eruption, or alternatively, at a later stage by the reaction of sulfuric acid aerosols with ash fragments within the stratospheric cloud. A Wilson-Huang formulation for the settling rate of individual particles qualitatively agrees with the observed particle-size distribution for a period at least four months after injection of material into the stratosphere. This result emphasizes the importance of particle shape in controlling the settling rate of volcanic ash from the stratosphere.

Post-discharge surveillance : can patients reliably diagnose surgical wound infections?

Post-discharge surgical wound infection surveillance is an important part of many infection control programs. It is frequently undertaken by patient self-assessment, prompted either by a telephone or postal questionnaire. To assess the reliability of this method, 290 patients were followed for six weeks postoperatively. Their wounds were photographed and also covertly assessed for signs of infection by two experienced infection control nurses (ICNs). Patients also responded to a postal questionnaire seeking evidence of infection at both week four and week six post-surgery. Correlation between the patient's assessment of their wound and the ICNs diagnosis was poor (r=0.37) with a low positive predictive value (28.7%), although negative predictive value was high (98.2%). Assessment of photos for signs of infection by two experienced clinicians also correlated poorly with the ICNs diagnosis of infection (r=0.54). The patient's recall of prescription of an antibiotic by their general practitioner (GP) for wound infection during the postoperative period correlated best with the ICNs diagnosis (r=0.76). This latter measure, particularly when confirmed by the GP in those patients reporting an infection, appears to provide the most valid and resource efficient marker of post-discharge surgical wound infection.

Public, private, or hybrid? What the upstream oil and gas industry can learn from other sectors about ‘the cloud’

Despite the compelling case for moving towards cloud computing, the upstream oil & gas industry faces several technical challenges—most notably, a pronounced emphasis on data security, a reliance on extremely large data sets, and significant legacy investments in information technology (IT) infrastructure—that make a full migration to the public cloud difficult at present. Private and hybrid cloud solutions have consequently emerged within the industry to yield as much benefit from cloud-based technologies as possible while working within these constraints. This paper argues, however, that the move to private and hybrid clouds will very likely prove only to be a temporary stepping stone in the industry’s technological evolution. By presenting evidence from other market sectors that have faced similar challenges in their journey to the cloud, we propose that enabling technologies and conditions will probably fall into place in a way that makes the public cloud a far more attractive option for the upstream oil & gas industry in the years ahead. The paper concludes with a discussion about the implications of this projected shift towards the public cloud, and calls for more of the industry’s services to be offered through cloud-based “apps.”

Cloud computing for healthcare research information sharing

With the widespread application of healthcare Information and Communication Technology (ICT), constructing a stable and sustainable data sharing circumstance has attracted rapidly growing attention in both academic research area and healthcare industry. Cloud computing is one of long dreamed visions of Healthcare Cloud (HC), which matches the need of healthcare information sharing directly to various health providers over the Internet, regardless of their location and the amount of data. In this paper, we discuss important research tool related to health information sharing and integration in HC and investigate the arising challenges and issues. We describe many potential solutions to provide more opportunities to implement EHR cloud. As well, we introduce the development of a HC related collaborative healthcare research example, thus illustrating the prospective of applying Cloud Computing in the health information science research.

Residence time investigation in a co-axial dielectric barrier discharge reactor

The residence time distribution (RTD) is a crucial parameter when treating engine exhaust emissions with a Dielectric Barrier Discharge (DBD) reactor. In this paper, the residence time of such a reactor is investigated using a finite element based software: COMSOL Multiphysics 4.3. Non-thermal plasma (NTP) discharge is being introduced as a promising method for pollutant emission reduction. DBD is one of the most advantageous of NTP technologies. In a two cylinder co-axial DBD reactor, tubes are placed between two electrodes and flow passes through the annuals between these barrier tubes. If the mean residence time increases in a DBD reactor, there will be a corresponding increase in reaction time and consequently, the pollutant removal efficiency can increase. However, pollutant formation can occur during increased mean residence time and so the proportion of fluid that may remain for periods significantly longer than the mean residence time is of great importance. In this study, first, the residence time distribution is calculated based on the standard reactor used by the authors for ultrafine particle (10-500 nm) removal. Then, different geometrics and various inlet velocities are considered. Finally, for selected cases, some roughness elements added inside the reactor and the residence time is calculated. These results will form the basis for a COMSOL plasma and CFD module investigation.