970 resultados para functionality


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BACKGROUND: The purpose of this study was to evaluate whether compliance and rehabilitative efforts were predictors of early clinical outcome of total hip resurfacing arthroplasty. METHODS: A cross-sectional survey was utilized to collect information from 147 resurfacing patients, who were operated on by a single surgeon, regarding their level of commitment to rehabilitation following surgery. Patients were followed for a mean of 52 months (range, 24 to 90 months). Clinical outcomes and functional capabilities were assessed utilizing the Harris hip objective rating system, the SF-12 Health Survey, and an eleven-point satisfaction score. A linear regression analysis was used to determine whether there was any correlation between the rehabilitation commitment scores and any of the outcome measures, and a multivariate regression model was used to control for potentially confounding factors. RESULTS: Overall, an increased level of commitment to rehabilitation was positively correlated with each of the following outcome measures: SF-12 Mental Component Score, SF-12 Physical Component Score, Harris Hip score, and satisfaction scores. These correlations remained statistically significant in the multivariate regression model. CONCLUSIONS: Patients who were more committed to their therapy after hip resurfacing returned to higher levels of functionality and were more satisfied following their surgery.

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Inflammation and the formation of an avascular fibrous capsule have been identified as the key factors controlling the wound healing associated failure of implantable glucose sensors. Our aim is to guide advantageous tissue remodeling around implanted sensor leads by the temporal release of dexamethasone (Dex), a potent anti-inflammatory agent, in combination with the presentation of a stable textured surface.

First, Dex-releasing polyurethane porous coatings of controlled pore size and thickness were fabricated using salt-leaching/gas-foaming technique. Porosity, pore size, thickness, drug release kinetics, drug loading amount, and drug bioactivity were evaluated. In vitro sensor functionality test were performed to determine if Dex-releasing porous coatings interfered with sensor performance (increased signal attenuation and/or response times) compared to bare sensors. Drug release from coatings monitored over two weeks presented an initial fast release followed by a slower release. Total release from coatings was highly dependent on initial drug loading amount. Functional in vitro testing of glucose sensors deployed with porous coatings against glucose standards demonstrated that highly porous coatings minimally affected signal strength and response rate. Bioactivity of the released drug was determined by monitoring Dex-mediated, dose-dependent apoptosis of human peripheral blood derived monocytes in culture.

The tissue modifying effects of Dex-releasing porous coatings were accessed by fully implanting Tygon® tubing in the subcutaneous space of healthy and diabetic rats. Based on encouraging results from these studies, we deployed Dex-releasing porous coatings from the tips of functional sensors in both diabetic and healthy rats. We evaluated if the tissue modifying effects translated into accurate, maintainable and reliable sensor signals in the long-term. Sensor functionality was accessed by continuously monitoring glucose levels and performing acute glucose challenges at specified time points.

Sensors treated with porous Dex-releasing coatings showed diminished inflammation and enhanced vascularization of the tissue surrounding the implants in healthy rats. Functional sensors with Dex-releasing porous coatings showed enhanced sensor sensitivity over a 21-day period when compared to controls. Enhanced sensor sensitivity was accompanied with an increase in sensor signal lag and MARD score. These results indicated that Dex-loaded porous coatings were able to elicit a favorable tissue response, and that such tissue microenvironment could be conducive towards extending the performance window of glucose sensors in vivo.

The diabetic pilot animal study showed differences in wound healing patters between healthy and diabetic subjects. Diabetic rats showed lower levels of inflammation and vascularization of the tissue surrounding implants when compared to their healthy counterparts. Also, functional sensors treated with Dex-releasing porous coatings did not show enhanced sensor sensitivity over a 21-day period. Moreover, increased in sensor signal lag and MARD scores were present in porous coated sensors regardless of Dex-loading when compared to bare implants. These results suggest that the altered wound healing patterns presented in diabetic tissues may lead to premature sensor failure when compared to sensors implanted in healthy rats.

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BACKGROUND/AIMS: The obesity epidemic has spread to young adults, and obesity is a significant risk factor for cardiovascular disease. The prominence and increasing functionality of mobile phones may provide an opportunity to deliver longitudinal and scalable weight management interventions in young adults. The aim of this article is to describe the design and development of the intervention tested in the Cell Phone Intervention for You study and to highlight the importance of adaptive intervention design that made it possible. The Cell Phone Intervention for You study was a National Heart, Lung, and Blood Institute-sponsored, controlled, 24-month randomized clinical trial comparing two active interventions to a usual-care control group. Participants were 365 overweight or obese (body mass index≥25 kg/m2) young adults. METHODS: Both active interventions were designed based on social cognitive theory and incorporated techniques for behavioral self-management and motivational enhancement. Initial intervention development occurred during a 1-year formative phase utilizing focus groups and iterative, participatory design. During the intervention testing, adaptive intervention design, where an intervention is updated or extended throughout a trial while assuring the delivery of exactly the same intervention to each cohort, was employed. The adaptive intervention design strategy distributed technical work and allowed introduction of novel components in phases intended to help promote and sustain participant engagement. Adaptive intervention design was made possible by exploiting the mobile phone's remote data capabilities so that adoption of particular application components could be continuously monitored and components subsequently added or updated remotely. RESULTS: The cell phone intervention was delivered almost entirely via cell phone and was always-present, proactive, and interactive-providing passive and active reminders, frequent opportunities for knowledge dissemination, and multiple tools for self-tracking and receiving tailored feedback. The intervention changed over 2 years to promote and sustain engagement. The personal coaching intervention, alternatively, was primarily personal coaching with trained coaches based on a proven intervention, enhanced with a mobile application, but where all interactions with the technology were participant-initiated. CONCLUSION: The complexity and length of the technology-based randomized clinical trial created challenges in engagement and technology adaptation, which were generally discovered using novel remote monitoring technology and addressed using the adaptive intervention design. Investigators should plan to develop tools and procedures that explicitly support continuous remote monitoring of interventions to support adaptive intervention design in long-term, technology-based studies, as well as developing the interventions themselves.

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Biogas is a mixture of methane and other gases. In its crude state, it contains carbon dioxide (CO2) that reduces its energy efficiency and hydrogen sulfide (H2S) that is toxic and highly corrosive. Because chemical methods of removal are expensive and environmentally hazardous, this project investigated an algal-based system to remove CO2 from biogas. An anaerobic digester was used to mimic landfill biogas. Iron oxide and an alkaline spray were used to remove H2S and CO2 respectively. The CO2-laden alkali solution was added to a helical photobioreactor where the algae metabolized the dissolved CO2 to generate algal biomass. Although technical issues prevented testing of the complete system for functionality, cost analysis was completed and showed that the system, in its current state, is not economically feasible. However, modifications may reduce operation costs.

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Whooping cough remains a problem despite vaccination, and worldwide resurgence of pertussis is evident. Since cellular immunity plays a role in long-term protection against pertussis, we studied pertussis-specific T-cell responses. Around the time of the preschool acellular pertussis (aP) booster dose at 4 years of age, T-cell memory responses were compared in children who were primed during infancy with either a whole-cell pertussis (wP) or an aP vaccine. Peripheral blood mononuclear cells (PBMCs) were isolated and stimulated with pertussis vaccine antigens for 5 days. T cells were characterized by flow-based analysis of carboxyfluorescein succinimidyl ester (CFSE) dilution and CD4, CD3, CD45RA, CCR7, gamma interferon (IFN-γ), and tumor necrosis factor alpha (TNF-α) expression. Before the aP preschool booster vaccination, both the proliferated pertussis toxin (PT)-specific CD4+ and CD8+ T-cell fractions (CFSEdim) were higher in aP-than in wP-primed children. Post-booster vaccination, more pertussis-specific CD4+ effector memory cells (CD45RA- CCR7-) were induced in aP-primed children than in those primed with wP. The booster vaccination did not appear to significantly affect the T-cell memory subsets and functionality in aP-primed or wP-primed children. Although the percentages of Th1 cytokine-producing cells were alike in aP- and wP-primed children pre-booster vaccination, aP-primed children produced more Th1 cytokines due to higher numbers of proliferated pertussis-specific effector memory cells. At present, infant vaccinations with four aP vaccines in the first year of life result in pertussis-specific CD4+ and CD8+ effector memory T-cell responses that persist in children until 4 years of age and are higher than those in wP-primed children. The booster at 4 years of age is therefore questionable; this may be postponed to 6 years of age.

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The Aircraft Accident Statistics and Knowledge (AASK) database is a repository of survivor accounts from aviation accidents. Its main purpose is to store observational and anecdotal data from the actual interviews of the occupants involved in aircraft accidents. The database has wide application to aviation safety analysis, being a source of factual data regarding the evacuation process. It is also key to the development of aircraft evacuation models such as airEXODUS, where insight into how people actually behave during evacuation from survivable aircraft crashes is required. This paper describes recent developments with the database leading to the development of AASK v3.0. These include significantly increasing the number of passenger accounts in the database, the introduction of cabin crew accounts, the introduction of fatality information, improved functionality through the seat plan viewer utility and improved ease of access to the database via the internet. In addition, the paper demonstrates the use of the database by investigating a number of important issues associated with aircraft evacuation. These include issues associated with social bonding and evacuation, the relationship between the number of crew and evacuation efficiency, frequency of exit/slide failures in accidents and exploring possible relationships between seating location and chances of survival. Finally, the passenger behavioural trends described in analysis undertaken with the earlier database are confirmed with the wider data set.

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Products manufactured by the electronics sector are having a major impact in telecommunications, transportation space applications, biomedical applications, consumer products, intelligent hand held devices, and of course,the computer. Demands from end-users in terms of greater product functionality, adoption of environmentally friendly materials, and further miniaturization continually pose several challenges to electronics companies. In the context of electronic product design and manufacture, virtual prototying software tools are allowing companies to dramatically reduce the number of phsysical prototypes and design iterations required in product development and hence reduce costs and time to market. This paper details of the trends in these technolgies and provides an example of their use for flip-chip assembly technology.

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FEA and CFD analysis is becoming ever more complex with an emerging demand for simulation software technologies that can address ranges of problems that involve combinations of interactions amongst varying physical phenomena over a variety of time and length scales. Computation modelling of such problems requires software technologies that enable the representation of these complex suites of 'physical' interactions. This functionality requires the structuring of simulation modules for specific physical phemonmena so that the coupling can be effectiely represented. These 'multi-physics' and 'multi-scale' computations are very compute intensive and so the simulation software must operate effectively in parallel if it is to be used in this context. Of course the objective of 'multi-physics' and 'multi-scale' simulation is the optimal design of engineered systems so optimistation is an important feature of such classes of simulation. In this presentation, a multi-disciplinary approach to simulation based optimisation is described with some key examples of application to challenging engineering problems.

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This paper describes modeling technology and its use in providing data governing the assembly and subsequent reliability of electronic chip components on printed circuit boards (PCBs). Products, such as mobile phones, camcorders, intelligent displays, etc., are changing at a tremendous rate where newer technologies are being applied to satisfy the demands for smaller products with increased functionality. At ever decreasing dimensions, and increasing number of input/output connections, the design of these components, in terms of dimensions and materials used, is playing a key role in determining the reliability of the final assembly. Multiphysics modeling techniques are being adopted to predict a range of interacting physics-based phenomena associated with the manufacturing process. For example, heat transfer, solidification, marangoni fluid flow, void movement, and thermal-stress. The modeling techniques used are based on finite volume methods that are conservative and take advantage of being able to represent the physical domain using an unstructured mesh. These techniques are also used to provide data on thermal induced fatigue which is then mapped into product lifetime predictions.

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Occupant interaction with signage systems is being introduced into evacuation simulations through the newly developed concept of the Visibility Catchment Area or VCA. In this article, we describe the concept of VCA and how it has been extended to incorporate the presence of physical obstructions and termination distance. The VCA concept is then linked to a prototype behavior model intended to represent the occupant's interaction with the signage system. The functionality and performance of the newly developed model is then demonstrated through the simulation of various evacuation scenarios within a hypothetical supermarket layout

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This paper presents work towards generic policy toolkit support for autonomic computing systems in which the policies themselves can be adapted dynamically and automatically. The work is motivated by three needs: the need for longer-term policy-based adaptation where the policy itself is dynamically adapted to continually maintain or improve its effectiveness despite changing environmental conditions; the need to enable non autonomics-expert practitioners to embed self-managing behaviours with low cost and risk; and the need for adaptive policy mechanisms that are easy to deploy into legacy code. A policy definition language is presented; designed to permit powerful expression of self-managing behaviours. The language is very flexible through the use of simple yet expressive syntax and semantics, and facilitates a very diverse policy behaviour space through both hierarchical and recursive uses of language elements. A prototype library implementation of the policy support mechanisms is described. The library reads and writes policies in well-formed XML script. The implementation extends the state of the art in policy-based autonomics through innovations which include support for multiple policy versions of a given policy type, multiple configuration templates, and meta-policies to dynamically select between policy instances and templates. Most significantly, the scheme supports hot-swapping between policy instances. To illustrate the feasibility and generalised applicability of these tools, two dissimilar example deployment scenarios are examined. The first is taken from an exploratory implementation of self-managing parallel processing, and is used to demonstrate the simple and efficient use of the tools. The second example demonstrates more-advanced functionality, in the context of an envisioned multi-policy stock trading scheme which is sensitive to environmental volatility

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This paper presents a policy definition language which forms part of a generic policy toolkit for autonomic computing systems in which the policies themselves can be modified dynamically and automatically. Targeted enhancements to the current state of practice include: policy self-adaptation where the policy itself is dynamically modified to match environmental conditions; improved support for non autonomics-expert developers; and facilitating easy deployment of adaptive policies into legacy code. The policy definition language permits powerful expression of self-managing behaviours and facilitates a diverse policy behaviour space. Features include support for multiple versions of a given policy type, multiple configuration templates, and meta policies to dynamically select between policy instances. An example deployment scenario illustrates advanced functionality in the context of a multi policy stock trading system which is sensitive to environmental volatility.

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Distributed applications are being deployed on ever-increasing scale and with ever-increasing functionality. Due to the accompanying increase in behavioural complexity, self-management abilities, such as self-healing, have become core requirements. A key challenge is the smooth embedding of such functionality into our systems. Natural distributed systems such as ant colonies have evolved highly efficient behaviour. These emergent systems achieve high scalability through the use of low complexity communication strategies and are highly robust through large-scale replication of simple, anonymous entities. Ways to engineer this fundamentally non-deterministic behaviour for use in distributed applications are being explored. An emergent, dynamic, cluster management scheme, which forms part of a hierarchical resource management architecture, is presented. Natural biological systems, which embed self-healing behaviour at several levels, have influenced the architecture. The resulting system is a simple, lightweight and highly robust platform on which cluster-based autonomic applications can be deployed.

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This paper provides an overview of the developing needs for simulation software technologies for the computational modelling of problems that involve combinations of interactions amongst varying physical phenomena over a variety of time and space scales. Computational modelling of such problems requires software tech1nologies that enable the mathematical description of the interacting physical phenomena together with the solution of the resulting suites of equations in a numerically consistent and compatible manner. This functionality requires the structuring of simulation modules for specific physical phenomena so that the coupling can be effectively represented. These multi-physics and multi-scale computations are very compute intensive and the simulation software must operate effectively in parallel if it is to be used in this context. An approach to these classes of multi-disciplinary simulation in parallel is described, with some key examples of application to2 challenging engineering problems.