Search

Age has long been recognized as a critical factor in predicting outcomes after head injury, with individuals older than 60 years predicted to have a worse outcome than those younger than 60. The object of this study was to determine the effect of age by decade of life beginning at birth in patients with head injuries of all levels of severity.The New York State Trauma Registry was searched for head injuries from January 1, 1994 to December 31, 1995; the 13,908 cases found were placed into age groups by decade. Data were sought for each patient on demographics, Glasgow Coma Score, ICD-9 injury code, New Injury Severity Score (NISS), and mechanism of injury. These data were analyzed with chi-square and one-way ANOVA tests, with significance set at p0.05.The risk of dying was significantly increased in patients beginning at 30 years of age compared with those in the younger age groups, with the greatest increases occurring after age 60 (p0.001). For the population with available Glasgow Coma Score data (n = 12,844), the mortality rate for patients ages 0 to 30 was 10.9%, and for patients ages 31 to 50 was 12.4%. The mean Glasgow Coma Score for nonsurvivors ages 0 to 20 (3.9) and for nonsurvivors ages 31 to 50 (5.1) were significantly different, with a risk ratio of 1.3 (p0.001).The risk of dying for patients suffering head injuries increases as early as 30 years of age, making it necessary for health-care providers to consider increased monitoring and treatment for patients in this younger age group.

The viewpoint of the universities that were formed in the early 1990s from the UK polytechnics is taken as the background to comments on the final report of the study, sponsored by the Research Support Libraries Group (RSLG), into the requirements for a UK wide strategic framework and for research information provision and in the UK and the recommendation that a new national body be formed, a Research Libraries Network (RLN), to offer strategic direction.

Residential Demand Response has shown promising results in smart grid applications. It can be achieved manually or autonomously. The variety of algorithms applied to achieve autonomous Demand Response have lacked a common baseline. The selection of testing environment is typically skewed by the desire to find one in which a particular algorithm performs well. This work evaluates several algorithms in a common evaluation environment. Which has been designed to encompass the range of conditions in a typical Residential Demand Response application. The environments described exhibit the following characteristics: non-stationary, dynamic, multi-actor, multi-objective. These characteristics will then be used to provide heuristics for algorithm selection. The algorithms used were selected to cover the spectrum of possible approaches to Demand Response. Some are centralised, others distributed. There are collaborative approaches and non-collaborative ones. Some are learning based, others require no training. This work provides criteria for which particular algorithms should be applied to a given application.

Smart Grid (SG) technologies are becoming increasingly dynamic, motivating the use of computational intelligence to support the SG by predicting and intelligently responding to certain requests (e.g, reducing electricity costs given fluctuating prices). The presented work intends to do precisely this, to make intelligent decisions to switch on electric devices at times when the electricity price (prices that change over time) is the lowest while at the same time attempting to balance energy usage by avoiding turning on multiple devices at the same time, whenever possible. To this end, we use Monte Carlo Tree Search (MCTS), a real-time decision algorithm. MCTS takes into consideration what might happen in the future by approximating what other entities/agents (electric devices) might do via Monte Carlo simulations. We propose two variants of this method: (a) max n MCTS approach where the competition for resources (e.g, lowest electricity price) happens in one single decision tree and where all the devices are considered, and (b) two-agent MCTS approach, where the competition for resources is distributed among various decision trees. To validate our results, we used two scenarios, a rather simple one where there are no constraints associated to the problem, and another more complex, and realistic scenario with equality and inequality constraints associated to the problem. The results achieved by this real-time decision tree algorithm are very promising, specially those achieved by the max n MCTS approach.

The Research Support Libraries Programme (RSLP) is a three year programme (1999-2002) funded by the UK higher education funding bodies with the aim of improving support for research in UK higher education and libraries. Presents a report commissioned by the RSLP on the operation of the programme, particularly on the experience of collaborative working. The report includes a discussion based on the experiences of those involved in the programme's projects, covering various aspects of the projects from setup to completion, and including both the benefits and drawbacks of collaborative working. Concludes with a set of recommendations for future collaborative projects in this area.

L'article contient une version legerement modifiee du rapport soumis au RSLP (Research Support Libraries Programme), rapport d'etude sur les obstacles au partage des ressources entre bibliotheques, en particulier dans l'enseignement superieur. Il examine notamment les entraves a la cooperation au niveau des attitudes, au niveau organisationnel et au niveau juridique. La premiere partie traite du contexte, des concepts et de questions actuelles lies a la collaboration dans les bibliotheques universitaires. Le chapitre suivant presente les activites collaboratives developpees actuellement dans sept zones urbaines et metropolitaines specifiques du Royaume Uni. Les resultats d'une enquete du SCONUL permettent d'apprecier les perceptions des utilisateurs et l'influence des disciplines sur la collaboration et le partage des ressources. Des paralleles sont etablis avec l'experience americaine du Boston Library Consortium ainsi qu'avec d'autres initiatives en Australie, en Afrique du Sud et en Europe. L'analyse des obstacles a la cooperation porte notamment sur des facteurs specifiques lies aux principales fonctions des bibliotheques (acces, developpement et gestion des collections, services techniques, stockage, personnel, gestion de la bibliotheque, questions financieres et juridiques), ainsi sur que des facteurs non specifiques lies a la gestion du changement. Les recommandations relatives a la facon de surmonter ces obstacles sont recapitulees dans la derniere partie.

peer-reviewed Many countries envisage a future where renewable electricity will be the predominant energy source. For example, Ireland’s smart grid roadmap has targets of 40% of electricity from renewables by 2020 and 80% by 2050. To achieve these targets will require new ways of operating the grid. We propose that there will be two types of demand, a load which can be influenced by dynamic pricing and a more tightly controlled flexible load that can be used to shape the aggregate demand. Key examples of this flexible load are electric vehicles (EVs), electric storage heating and hot water heating. This paper explores two algorithms that implement tight set point control for a set of EVs on a distribution feeder line. The first algorithm uses a variable power charger for charging the EVs and the second algorithm shows that it is possible to achieve similar results with a much simpler on-off charger.

Improving the efficiency of the smart grid, and in particular efficient integration of energy from renewable sources, is the key to sustainability of electricity provision. In order to optimize energy usage, efficient demand response mechanisms are needed to shift energy usage to periods of low demand, or to periods of high availability of renewable energy. In this paper we propose a multi-agent approach that uses load forecasting for residential demand response. Electrical devices in a household are controlled by reinforcement learning agents which, using the information on current electricity load and load prediction for the next 24 hours, learn how to meet their electricity needs while ensuring that the overall demand stays within the available transformer limits. Simulations are performed in a small neighbourhood consisting of 9 homes each with an agent-controlled electric vehicle. Performance of agents with 24-hour load prediction is compared to the performance of those with current load information only and those which do not have any load information.

peer-reviewed Applications such as generator scheduling, household smart device scheduling, transmission line overload management and microgrid islanding autonomy all play key roles in the smart grid ecosystem. Management of these applications could benefit from short-term load prediction, which has been successfully achieved on large-scale systems such as national grids. However, the scale of the data for analysis is much smaller, similar to the load of a single transformer, making prediction difficult. This paper examines several prediction approaches for day and week ahead electrical load of a community of houses that are supplied by a common residential transformer, in particular: artificial neural networks; fuzzy logic; auto-regression; autoregressive moving average; auto-regressive integrated moving average; and wavelet neural networks. In our evaluation, the methods use pre-recorded electrical load data with added weather information. Data is recorded from a smart-meter trial that took place during 2009-2010 in Ireland, which registered individual household consumption for 17 months. Two different scenarios are investigated, one with 90 houses, and another with 230 houses. Results for the two scenarios are compared and the performances of the evaluated prediction methods are discussed.

Study Design Retrospective, multicenter review of the spinopelvic parameters in young children with scoliosis. Objectives To describe sagittal alignment of the spine and pelvis in young children with scoliosis. Summary of Background Data The natural history of spinopelvic parameters has been defined for the first 10 years of life in normal children; however, they have not been described for children with scoliosis. Such information is important because these values can be used as a baseline for the assessment of radiographic outcomes after surgical intervention. Methods Seven measures of sagittal alignment were taken from standing lateral radiographs of 80 children with scoliosis (coronal Cobb angle greater than 50°) and compared with age-matched normal children described in the literature. Statistical analysis was performed using 2-tailed Student t tests (level of significance = .05) and Pearson correlation coefficient. Results Patients had a mean age of 4.8 years (range, 1–10 years) and a mean Cobb angle of 72.0° ± 16°. Mean sagittal spine parameters were sagittal balance (2.2 ± 4 cm), thoracic kyphosis (38.0° ± 20.8°), and lumbar lordosis (49.0° ± 16.6°). These values were similar to those of children without scoliosis. Mean sagittal pelvic parameters were: pelvic incidence (46.5° ± 15.8°), pelvic tilt (10.7° ± 13.6°), sacral slope (35.5° ± 12.1°), and pelvic radius (55.7° ± 21.3°). Pelvic incidence was not significantly different from that of age-matched normal children; however, pelvic tilt was significantly higher and sacral slope was significantly lower in children with scoliosis. Conclusions Sagittal plane spine parameters and some pelvic parameters were similar for young children with scoliosis versus age-matched normal children; however, children with scoliosis showed signs of increased pelvic tilt and decreased sacral slope. These values can be used as a baseline for both the natural history and the assessment of radiographic outcomes after surgical intervention.

peer-reviewed Smart Grid technologies are becoming increasingly dynamic, so the use of computational intelligence is becoming more and more common to support the grid to automatically and intelligently respond to certain requests (e.g., reducing electricity costs giving a pricing history). In this work, we propose the use of a particular computational intelligence approach, denominated Distributed W-Learning, that aims to reduce electricity costs in a dynamic environment (e.g., changing prices over a period of time) by turning electric devices on (i.e., clothes dryer, electric vehicle) at residential level, at times when the electricity price is the lowest, while also, balancing the use of energy by avoiding turning on the devices at the same time. We make this problem as realistic as possible, by considering the use of real-world constraints (e.g., time to complete a task, boundary times within which a device can be used). Our results clearly indicate that the use of computational intelligence can be beneficial in this type of dynamic and complex problems.

While there are several best practice standards available for minimizing the energy requirement for compressed air use in an industrial context, moving to best practice often requires investment and operational change. In production facilities, there is often a reluctance to commit to this type of change without a clear view of the benefit. Furthermore, there is very little detailed information available in the open literature that allows even a qualitative assessment of priorities. In order to address this shortcoming, analyses of two industrial compressed air systems which are already installed in manufacturing plants have been conducted in the context of energy usage. The installations are quite different in compressed air needs: one is focused on actuation and drying; while the other uses compressed air primarily for material handling. In both sites, the energy of the compressed air is evaluated at each key element of the system and the typical end use application profile is assessed. Simple models of the consumption rates are used to relate duty cycle and device count with actual total consumption. A new way of assessing the leak rate from the entire system has been developed, based on the pressure decay time, and has been implemented at one site. In this way, the energy balance of the system entire has been analyzed quantitatively, with the effect of distribution leaks accounted for directly. It is found that in both sites, open blowing operations (e.g. drying) are the largest, consumers which are amenable to optimization. It is also found that the measured leak rate at one site represented 23% of the compressed air generated, with an energy input of 455kWh per day. It is concluded that this approach can help to identify priorities for optimizing CA use at an industrial site.Copyright © 2010 by ASME

`Privatization' has taken many different forms over recent years, and different kinds of privatization have very different sociological implications for consumers of state services. The paper develops a typology of privatization and considers how each type might change the relationship between producers and consumers. It is argued that consumer powerlessness is endemic in many areas of state provision, but that privatization does not necessarily affect this. Indeed, the story of privatization in Britain over the last ten years suggests that those forms of privatization which most empower consumers relative to producers have been precisely those forms which are least developed.

Proponents of privatisation have claimed that it would bring advantages for those employed in the newly privatised industries. It would result in “better pay, conditions and employment opportunities for the employees” (Moore, 1983). Furthermore, each major privatisation has encouraged workers to buy shares in their company and, most have set aside a small number of free shares for employees with the result that over ninety percent of employees in the majority of these companies own shares in them. The government has argued tht as employees accumulate shares in their company the industrial relations' climate will improve because workers will increasingly identify with the interests of the company.

This review explores the relationship between oral and dental health and disease in substance misusers. Although it focuses on oral cancer, we also examine the relationship of misuse with dental caries and periodontal diseases. It is difficult to separate out the inter-related aetiological factors such as the use of alcohol and tobacco (smoked and chewed). They probably act in a synergistic manner.

The subject of this paper is the remote control of multimedia applications, using a personal digital assistant (PDA) as a hand held remote control device. Application specific, context dependent user interfaces are transmitted to the PDA for display on its LCD screen. The user interacts with the touch sensitive screen and the input commands are transmitted back to the application. This approach results in a sophisticated and flexible interface which is at the same time easy to use.

Before 1988, and the passing of the Education Reform Act, the school curriculum in England and Wales was very much a matter of local, even individual, preference. The only compulsory subject required under previous legislation was religious education. In primary schools consensus led to the development of basic skills in numeracy and literacy, extending through creative activities in art, movement and music, with much scientific, historical and geographical endeavour swept into a range of integrated topics and projects. Beyond the age of 11, the curriculum was largely modelled on successful grammar and public schools, with the last two years of compulsory education dictated by the requirements of examination boards. The onset of comprehensive secondary education from the 1960s released time and energy to produce a greater range of curriculum subjects embracing academic, commercial, technical, artistic and craft skills. In 1988, government legislation tightened the choice to a basic curriculum of maths, English, science, technology history, geography, art, music and physical and religious education, with varying degrees of emphasis for pupils from 5 to 14, and with the opportunity for more flexibility from 14 to 16. At the time of writing the issues of the last two years of compulsory education have not yet been resolved. During the experimental and creative phases of curriculum development, starting with the 1960s, several interesting initiatives were pursued. Among these were rural science and rural studies, in which, initially, less able pupils were encouraged to take practical courses in gardening, horticulture and agriculture. Clearly, greater opportunities were found for this in rural schools. In some 'shire' counties of England, schools were equipped with purpose-built rural studies units incorporating glass houses, gardens and stock pens for sheep, pigs, poultry and other livestock. From these practical beginnings sprang the movement for environmental studies. Early proponents such as Sean McB. Carson saw the opportunity to develop more academically respectable school courses offering an integrated approach to learning encompassing science and geography. These environmental studies formed the basis of much integrated work in primary schools, and at secondary level could be offered as external examination subjects at CSE and GCE (latterly GCSE) and Advanced Level GCE (examinations taken at the end of lower and upper secondary education). Other features of the integrated approach included field study, a widening curriculum coverage to embrace history and aesthetic subjects, as well as using the medium of the environment to promote literacy and numeracy skills, and a concern for the conservation of nature. A later, though equally important, dimension was that of the urban or built environment.

This paper describes the adoption of an evaluation strategy—‘illuminative evaluation’—by a major user education research project, the Travelling Workshops Experiment. It is argued that this project is distinctive in its similarity to curriculum innovation and dissemination projects, and it is suggested that innovative programmes cannot be subjected to preordinate evaluation. The components of illuminative evaluation are examined, and a checklist for the systematization of evaluation is offered.

An account of the background against which a non-traditional strategy of evaluation was adopted in the Travelling Workshops Experiment at Newcastle upon Tyne Polytechnic. The author points out that research rarely proceeds along textbook lines and describes how the clear cut distinctions originally envisaged for the internal and external components of the evaluation ot the project soon became blurred in the process of evolving practicable procedures. At the same time, the research team had to resolve the conflict which arose between pressures towards a traditional, tightly controlled approach to evaluation and their own preference for a more exploratory strategy in which behavioural objectives would not be specified at the outset. An alternative model was found in ‘illuminative evaluation’, which eschews pre- and post-testing in favour of a more wide-ranging study ot the contextual determinants of the success of an innovation. Use of this model nonetheless poses many problems, not the least of which is that illuminative evaluation is a broad strategy rather than a set of specific techniques.

The aggressivity of adult males and females was evaluated by measuring (1) the frequency of aggressive displays that individuals made toward a mirror image stimulus following varying periods of social isolation, (2) the display frequency in brief, unisexual and bisexual bouts with live opponents, and (3) the reinforcing effects of mirror image stimulation on performance of an approach response. Isolation up to seven days increased aggressivity in both sexes. Males performed lateral display toward a mirror image or a live conspecific more frequently than females. Mirror image stimulation also was a stronger positive reinforcer in males than in females.