Introducing assistive technology into the existing homes of older people: Feasibility, acceptability, costs and outcomes

We examined how far, and at what cost, the housing stock could be modified to accommodate the assistive technology (AT) necessary to enable older people to remain in their own homes. A multidisciplinary team devised seven hypothetical user profiles for 10 case study areas, with five local authorities and five housing associations in England and Wales. Each profile was considered at two times, five years apart, with the users' functional abilities deteriorating in between. In addition, in-depth interviews were carried out with a sample of 67 older people in the case study areas about their use and experience of a wide range of AT. The interviews showed the need to listen to older people and that they welcomed AT when it addressed a perceived need. The results showed that the extent of adaptation required of buildings to accommodate a user's needs varied greatly. It was also found that there was confusion about the terminology of AT, including the idea of the 'smart house'. The study shows that the adaptability of the housing depends on a range of factors and costs.

Optimal maintenance policies under different operational schedules

In the reliability literature, maintenance time is usually ignored during the optimization of maintenance policies. In some scenarios, costs due to system failures may vary with time, and the ignorance of maintenance time will lead to unrealistic results. This paper develops maintenance policies for such situations where the system under study operates iteratively at two successive states: up or down. The costs due to system failure at the up state consist of both business losses & maintenance costs, whereas those at the down state only include maintenance costs. We consider three models: Model A, B, and C: Model A makes only corrective maintenance (CM). Model B performs imperfect preventive maintenance (PM) sequentially, and CM. Model C executes PM periodically, and CM; this PM can restore the system as good as the state just after the latest CM. The CM in this paper is imperfect repair. Finally, the impact of these maintenance policies is illustrated through numerical examples.

Investigating the feasibility of a swarm-array computing approach

The work reported in this paper proposes a novel synergy between parallel computing and swarm robotics to offer a new computing paradigm, 'swarm-array computing' that can harness and apply autonomic computing for parallel computing systems. One approach among three proposed approaches in swarm-array computing based on landscapes of intelligent cores, in which the cores of a parallel computing system are abstracted to swarm agents, is investigated. A task is executed and transferred seamlessly between cores in the proposed approach thereby achieving self-ware properties that characterize autonomic computing. FPGAs are considered as an experimental platform taking into account its application in space robotics. The feasibility of the proposed approach is validated on the SeSAm multi-agent simulator.

Achieving intelligent agents and its feasibility in swarm-array computing

The work reported in this paper proposes ‘Intelligent Agents’, a Swarm-Array computing approach focused to apply autonomic computing concepts to parallel computing systems and build reliable systems for space applications. Swarm-array computing is a robotics a swarm robotics inspired novel computing approach considered as a path to achieve autonomy in parallel computing systems. In the intelligent agent approach, a task to be executed on parallel computing cores is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and can be seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-* objectives of autonomic computing. The approach is validated on a multi-agent simulator.

Using continuous ground-based radar and lidar measurements for evaluating the representation of clouds in four operational models

The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw. Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud

Feasibility of guided CBT self-help for childhood anxiety disorders in primary care

Anxiety disorders in childhood are common, disabling and run a chronic course. Cognitive Behaviour Therapy (CBT) effective but is expensive and trained therapists are scarce. Guided self-help treatments may be a means of widening access to treatment. This study aimed to examine the feasibility of guided CBT self-help for childhood anxiety disorders in Primary Care, specifically in terms of therapist adherence, patient and therapist satisfaction and clinical gain. Participants were children aged 5-12 years referred to two Primary Child and Adolescent Mental Health Services (PCAMHSs) in Oxfordshire, UK, who met diagnostic criteria for a primary anxiety disorder. Of the 52 eligible children, 41 anxious children were assessed for anxiety severity and interference before and after receiving CBT self-help, delivered via the parent (total therapy time= 5 hours) by Primary Mental Health Workers (PMHWs). Therapy sessions were rated for treatment adherence and patients and PMHWs completed satisfaction questionnaires after treatment completion. Over 80% of therapy sessions were rated at a high level of treatment adherence. Parents and PMHWs reported high satisfaction with the treatment. 61% of the children assessed no longer met criteria for their primary anxiety disorder diagnosis following treatment, and 76% were rated as ‘much’/’very much’ improved on the Clinician’s Global Impression-Improvement scale. There were significant reductions on parent and child report measures of anxiety symptoms, interference, and depression. Preliminary exploration indicated that parental anxiety was associated with child treatment outcome. The findings suggest that guided CBT self-help represents a promising treatment for childhood anxiety in primary care.

Tracer concentration profiles measured in central London as part of the REPARTEE campaign

There have been relatively few tracer experiments carried out that have looked at vertical plume spread in urban areas. In this paper we present results from two tracer (cyclic perfluorocarbon) experiments carried out in 2006 and 2007 in central London centred on the BT Tower as part of the REPARTEE (Regent’s Park and Tower Environmental Experiment) campaign. The height of the tower gives a unique opportunity to study vertical dispersion profiles and transport times in central London. Vertical gradients are contrasted with the relevant Pasquill stability classes. Estimation of lateral advection and vertical mixing times are made and compared with previous measurements. Data are then compared with a simple operational dispersion model and contrasted with data taken in central London as part of the DAPPLE campaign. This correlates dosage with non-dimensionalised distance from source. Such analyses illustrate the feasibility of the use of these empirical correlations over these prescribed distances in central London.

Substitution of dietary monounsaturated fatty acids for saturated fatty acids in a free-living population: a feasibility study

The fatty acid composition of the diet of seven free-living subjects (five men and two women) aged 41–56 years was altered for 1 month. The aim was to increase the intake of monounsaturated fatty acids (MUFAs) from subjects current habitual levels of 12% dietary energy to a target intake of 18% dietary energy, and to decrease saturated fatty acid (SFA) from habitual levels of 16% dietary energy to target levels of 10% dietary energy. The change in fatty acid intake was achieved by supplying volunteers with foods prepared using MUFA-containing spreads or olive oil (ready meals, sweet biscuits and cakes) and also by supplying spreads, cooking oil and MUFA-enriched milk for domestic use. Body weight and plasma total cholesterol measurements were made at baseline and at 2 and 4 weeks on the diet as an aid to maintaining subject compliance. MUFA consumption was significantly increased from 12% dietary energy to 16% dietary energy (P<0.01), and SFA intake was reduced from 16% dietary energy to 6% dietary energy (P<0.01) during the 4-week intervention. The diet failed to achieve the target increase in MUFA but exceeded the target reduction in SFA. This was due to the fact that subjects reduced their total fat intake from a mean habitual level of 38% dietary energy to a mean level of 30% dietary energy. During the dietary period, mean plasma cholesterol levels were lower at 2 weeks (P<0.01) and at 4 weeks (P<0.01) than the baseline, with a mean reduction of 20% over the dietary period. This study demonstrates the difficulty of achieving increased MUFA intakes (by SFA substitution) in free-living populations when only a limited range of fatty-acid modified food products are provided to volunteers.

Uncertainty and feasibility studies: an Italian case study

Uncertainty affects all aspects of the property market but one area where the impact of uncertainty is particularly significant is within feasibility analyses. Any development is impacted by differences between market conditions at the conception of the project and the market realities at the time of completion. The feasibility study needs to address the possible outcomes based on an understanding of the current market. This requires the appraiser to forecast the most likely outcome relating to the sale price of the completed development, the construction costs and the timing of both. It also requires the appraiser to understand the impact of finance on the project. All these issues are time sensitive and analysis needs to be undertaken to show the impact of time to the viability of the project. The future is uncertain and a full feasibility analysis should be able to model the upside and downside risk pertaining to a range of possible outcomes. Feasibility studies are extensively used in Italy to determine land value but they tend to be single point analysis based upon a single set of “likely” inputs. In this paper we look at the practical impact of uncertainty in variables using a simulation model (Crystal Ball ©) with an actual case study of an urban redevelopment plan for an Italian Municipality. This allows the appraiser to address the issues of uncertainty involved and thus provide the decision maker with a better understanding of the risk of development. This technique is then refined using a “two-dimensional technique” to distinguish between “uncertainty” and “variability” and thus create a more robust model.