What do people value when they provide unpaid care for an older person? A meta-ethnography with interview follow-up

Government policies to shift care into the community and demographic changes mean that unpaid (informal) carers will increasingly be relied on to deliver care, particularly to older people. As a result, careful consideration needs to be given to informal care in economic evaluations. Current methods for economic evaluations may neglect important aspects of informal care. This paper reports the development of a simple measure of the caring experience for use in economic evaluations. A meta-ethnography was used to reduce qualitative research to six conceptual attributes of caring. Sixteen semi-structured interviews were then conducted with carers of older people, to check the attributes and develop them into the measure. Six attributes of the caring experience comprise the final measure: getting on, organisational assistance, social support, activities, control, and fulfilment. The final measure (the Carer Experience Scale) focuses on the process of providing care, rather than health outcomes from caring. Arguably this provides a more direct assessment of carers' welfare. Following work to test and scale the measure, it may offer a promising way of incorporating the impact on carers in economic evaluations. © 2008 Elsevier Ltd. All rights reserved

The need to “carer proof” healthcare decisions

yesPopulation ageing and fiscal austerity are set to increase the reliance on family carers, who already provide much of the support for people with long term health conditions. Although most carers are willing, providing care can be hugely stressful, affecting mental and physical health1 and resulting in social isolation and financial hardship.2 When under strain, carers are less likely to be effective, increasing the risk that the care recipient is admitted to hospital or a care home.3 Health systems could reduce strain on family carers by routinely considering carers’ needs alongside patients’ needs in everyday healthcare decisions—a concept we term “carer proofing”.non

The service required quality ensure model of LTE technology downlink

У статті запропонована математична модель розподілу ресурсних блоків у низхідному каналі зв’яз- ку технології LTE. Запропонована модель спрямована на забезпечення гарантованої якості обслуговування користувачів безпроводової мережі шляхом виділення для користувацьких станцій необхідних швидкостей передачі. Проведено порівняльний аналіз отриманих рішень при використанні різних цільових функційВ статье представлена математическая модель распределения ресурсных блоков в нисходящем кана- ле связи технологии LTE. Предложенная модель направлена на обеспечение гарантированного каче- ства обслуживания пользователей беспроводной сети путем выделения пользовательским станциям требуемых скоростей передачи. Проведен сравни- тельный анализ получаемых решений при использова- нии различных целевых функци

Childhood accidental poisoning in western Iraq: Pattern and risk factors

No Abstrac

EXPERIMENTAL INVESTIGATION OF CRYSTALLIZATION FOULING ON GROOVED STAINLESS STEEL SURFACES DURING CONVECTIVE HEAT TRANSFER

The beneficial aspects of enhanced or extended heat transfer surfaces may be off-set if operated under fouling conditions. In the present paper, preliminary experimental results for crystallization fouling of CaSO4 solutions onto surfaces with different structures are reported. Flat stainless steel plates (50 mm x 59 mm) with \u27V\u27 shaped grooves on the side of fluid flow were used as heat transfer surfaces. Experiments were carried out both under clean and fouling conditions to discern how the same surface structures perform under such circumstances. In addition, the impact of both, the direction of grooves with respect to fluid flow (crossed, longitudinal and mixed flow grooves) and the groove dimensions has also been investigated. Fouling trends are discussed in terms of delay time and fouling rate. Significant differences have been found for the various flow conditions

A Centralised Routing Protocol with a Scheduled Mobile Sink-Based AI for Large Scale I-IoT

Extensive efforts have been undertaken to enhance thecentralisedmonitoring-basedsoftwaredefinednetwork(SDN) concept of the large-scale Intelligent-Internet of Things (I-IoT). Furthermore, the number of IoT devices in vast environments is increasing and a scalable routing protocol has therefore become essential. However, due to associated resource restrictions, only very small functions can be configured using IoT nodes, principally those related to the power supply. One solution for increasing network scalability and prolonging the life of the network is to use the mobile sink (MS). However, determining the optimal set of data gathering points (SDG), optimal path, scheduling the entire network with the MS in an energy efficient manner and prolonging the life of the network present huge challenges, particularly in large-scale networks. This paper therefore proposes an energy efficient routing protocol based on artificial intelligence (AI), i.e., particle swarm optimisation (PSO) and genetic algorithm (GA), for large scale I-IoT networks under the SDN and cloud architecture. The basic premise is to exploit cloud resources such as storage and data-centre units by using a centralised SDN controller-based AI to calculate: a load-balanced table of clusters (CT), an optimal SDG, and an optimal path for the MS (MSOpath). Moreover, the proposed new routing technique will prevent significant energy dissipation by the cluster head (CH) and by all nodes in general by scheduling the whole network. Consequently, the SDN controller essentially balances energy consumption by the network during the routing construction process as it considers both the SDG and the movement of the MS. Simulation results demonstrate the effectiveness of the suggested model by improving the network lifespan up to 54%, volume of data aggregated by the MS up to 93% and reducing the delay of the MSOpath by 61% in comparison to other approaches

Construction bid model for residential building projects in Dubai

Many construction firms face hardships during the economic crisis due to inaccurate bidding and difficulty in obtaining new projects because of cost fluctuation. The best option for construction firms during an economic crisis is to control their construction bid costs that fit the situation. The bidding cost during the economic crisis has led to losses in the execution of projects. The study investigated how the construction sector of Dubai, United Arab Emirate, experienced poor bidding performance during the economic crisis. This is evident when material cost was fluctuating and the construction companies had a tough time getting new projects due to inaccurate bidding. This research looked into the details of construction bidding management during the bidding stage by developing a construction bid mathematical model to assist construction firms avoid bidding problems during the economic crisis. Using the data gathered from the year 2009 and 2010 economic crash, a construction bid mathematical model and bidding plan methodology were developed to better prepare construction companies during economic crisis. The chronology of this study was divided into two phases. Phase one involved conducting an extensive literature review and collecting secondary data. Phase two focused on primary data gathering and analysis of the data collected. Documentary analysis and questionnaire surveys were engaged as a source and tool to gather the data. Data were analyzed using coefficient of variation and severity index. From the available data, the bid mathematical model for bidding was successfully developed. Then, ten experts validated this model and the data were analyzed whereby the results showed that the model has successfully reduced the estimation inaccuracy as well as predicted the problem faced especially bidding during the economic crisis. The findings have shown that it is very important to have a crisis-response plan in place to eradicate risks, secure the market and provide solutions to problems faced during the crisis. In conclusion, the model can be used to minimize the adverse effects on the construction companies, including the projects and stakeholders in the construction industry