151 resultados para Oberwolfach Problems


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The research on integrated energy system technology meets the major national strategic needs of China. Focusing on the vital theory of planning and optimal operation of integrated energy system, six fundamental problems in the study of integrated energy system are proposed systematically, including the common modeling technology for integrated energy system, the integrated simulation of integrated energy system, the planning theory and method of integrated energy system, the security theory and method of integrated energy system, the optimal operation and control of integrated energy system, the benefit assessment and operational mechanisms of integrated energy system. The status of domestic and foreign research directions related to each scientific problems are surveyed and anticipated.

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Much interest now focuses on the use of the contingent valuation method (CVM) to assess non-use value of environmental goods. The paper reviews recent literature and highlights particular problems of information provision and respondent knowledge, comprehension and cognition. These must be dealt with by economists in designing CVM surveys for eliciting non-use values. Cognitive questionnaire design methods are presented which invoke concepts from psychology and tools from cognitive survey design (focus groups and verbal reports) to reduce a complex environmnetal good into a meaningful commodity that can be valued by respondents in a contingent market. This process is illustrated with examples from the authors' own research valuing alternative afforestation programmes. -Authors

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Recent research has supported the view that the distributions of many pests and diseases have extended towards higher latitudes over the last 50 years. Probably driven by a combination of climate change and trade, this extension to the ranges of hundreds of plant pathogens may have serious implications not only for agriculture, horticulture and forestry, but also for turf production &maintenance. Here we review our data relating to the current status of three emerging pest and disease problems across North West Europe (rapid blight, Labyrinthula sp. , the root knot nematode, Meloidogyne minor and the pacific stem gall nematode, Anguina pacificae ) and discuss the factors which may be involved in their spread and increasing impact on the turf industry. With turf production and maintenance becoming an increasingly international business, we ask if biosecurity and the promotion of plant health in turf production fields and associated sport facilities should be a greater priority for the industry. We also examine if a lack of effective biosecurity measures in the materials supply chain has led to increased plant health problems.

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Symposium Chair: Dr Jennifer McGaughey

Title: Early Warning Systems: problems, pragmatics and potential

Early Warning Systems (EWS) provide a mechanism for staff to recognise, refer and manage deteriorating patients on general hospital wards. Implementation of EWS in practice has required considerable change in the delivery of critical care across hospitals. Drawing their experience of these changes the authors will demonstrate the problems and potential of using EWS to improve patient outcomes.

The first paper (Dr Jennifer McGaughey: Early Warning Systems: what works?) reviews the research evidence regarding the factors that support or constrain the implementation of Early Warning System (EWS) in practice. These findings explain those processes which impact on the successful achievement of patient outcomes. In order to improve detection and standardise practice National EWS have been implemented in the United Kingdom. The second paper (Catherine Plowright: The implementation of the National EWS in a District General Hospital) focuses on the process of implementing and auditing a National EWS. This process improvement is essential to contribute to future collaborative research and collection of robust datasets to improve patient safety as recommended by the Royal College of Physicians (RCP 2012). To successfully implement NEWS in practice requires strategic planning and staff education. The practical issues of training staff is discussed in the third paper. This paper (Collette Laws-Chapman: Simulation as a modality to embed the use of Early Warning Systems) focuses on using simulation and structured debrief to enhance learning in the early recognition and management of deteriorating patients. This session emphasises the importance of cognitive and social skills developed alongside practical skills in the simulated setting.

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Background: A growing body of epidemiological research suggests high rates of traumatic brain injury (TBI) in prisoners. The aim of this review is to systematically explore the literature surrounding the rates of TBI and their co-occurrences in a prison population.
Methods: Six electronic databases were systematically searched for articles published between 1980 and 2014. Studies were screened for inclusion based on predetermined criteria by two researchers who independently performed data extraction. Study quality was appraised based on a modified quality assessment tool.
Results: Twenty six studies were included in this review. Quality assessment ranged from 20% (poor) to 80% (good) with an overall average of 60%. Twenty four papers included TBI prevalence rates, which ranged from 5.69%-88%. Seventeen studies explored co-occurring factors including rates of aggression (n=7), substance abuse (n=9), anxiety and depression (n=5), neurocognitive deficits (n=4), and psychiatric conditions (n=3).
Conclusions: The high degree of variation in TBI rates may be attributed to the inconsistent way in which TBI was measured with only seven studies using valid and reliable screening tools. Additionally, gaps in the literature surrounding personality outcomes in prisoners with TBI, female prisoners with TBI, and qualitative outcomes were found.

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The Arc-Length Method is a solution procedure that enables a generic non-linear problem to pass limit points. Some examples are provided of mode-jumping problems solutions using a commercial nite element package, and other investigations are carried out on a simple structure of which the numerical solution can be compared with an analytical one. It is shown that Arc-Length Method is not reliable when bifurcations are present in the primary equilibrium path; also the presence of very sharp snap-backs or special boundary conditions may cause convergence diÆculty at limit points. An improvement to the predictor used in the incremental procedure is suggested, together with a reliable criteria for selecting either solution of the quadratic arc-length constraint. The gap that is sometimes observed between the experimantal load level of mode-jumping and its arc-length prediction is explained through an example.

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Bail-in is quickly becoming a predominant approach to banking resolution. The EU Bank Recovery Resolution Directive and the US Federal Deposit Insurance Corporation’s single point of entry strategy envisage creditors’ recapitalisations
to resolve a failing financial institution. However, this legislation focuses on the domestic aspects of bail-in, leaving the question of how it is applied
to a cross-border banking group open. Cross-border banking resolution has been historically subject to coordination failures, which have resulted in disorderly resolutions with dangerous systemic effects. The goal of this article is to assess whether bail-in is subject to the same coordination problems that affect other resolution tools, and to discuss the logic of international legal cooperation in bail-in policies. We demonstrate that, in spite of the evident benefit in terms of fiscal sustainability, bail-in suffers from complex coordination problems which, if not addressed, might lead to regulatory arbitrage and lengthy court battles, and, ultimately, may disrupt resolutions. We argue that only a binding legal regime can address those problems. In doing so, we discuss the recent Financial Stability
Board’s proposal on cross-border recognition of resolution action, and the role of international law in promoting cooperation in banking resolution.

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This paper is concerned with the application of an automated hybrid approach in addressing the university timetabling problem. The approach described is based on the nature-inspired artificial bee colony (ABC) algorithm. An ABC algorithm is a biologically-inspired optimization approach, which has been widely implemented in solving a range of optimization problems in recent years such as job shop scheduling and machine timetabling problems. Although the approach has proven to be robust across a range of problems, it is acknowledged within the literature that there currently exist a number of inefficiencies regarding the exploration and exploitation abilities. These inefficiencies can often lead to a slow convergence speed within the search process. Hence, this paper introduces a variant of the algorithm which utilizes a global best model inspired from particle swarm optimization to enhance the global exploration ability while hybridizing with the great deluge (GD) algorithm in order to improve the local exploitation ability. Using this approach, an effective balance between exploration and exploitation is attained. In addition, a traditional local search approach is incorporated within the GD algorithm with the aim of further enhancing the performance of the overall hybrid method. To evaluate the performance of the proposed approach, two diverse university timetabling datasets are investigated, i.e., Carter's examination timetabling and Socha course timetabling datasets. It should be noted that both problems have differing complexity and different solution landscapes. Experimental results demonstrate that the proposed method is capable of producing high quality solutions across both these benchmark problems, showing a good degree of generality in the approach. Moreover, the proposed method produces best results on some instances as compared with other approaches presented in the literature.

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This paper examines the prevalence of vision problems and the accessibility to and quality of vision care in rural China. We obtained data from 4 sources: 1) the National Rural Vision Care Survey; 2) the Private Optometrists Survey; 3) the County Hospital Eye Care Survey; and 4) the Rural School Vision Care Survey. The data from each of the surveys were collected by the authors during 2012. Thirty-three percent of the rural population surveyed self-reported vision problems. Twenty-two percent of subjects surveyed had ever had a vision exam. Among those who self-reported having vision problems, 34% did not wear eyeglasses. Fifty-four percent of those with vision problems who had eyeglasses did not have a vision exam prior to receiving glasses. However, having a vision exam did not always guarantee access to quality vision care. Four channels of vision care service were assessed. The school vision examination program did not increase the usage rate of eyeglasses. Each county-hospital was staffed with three eye-doctors having one year of education beyond high school, serving more than 400,000 residents. Private optometrists often had low levels of education and professional certification. In conclusion, our findings shows that the vision care system in rural China is inadequate and ineffective in meeting the needs of the rural population sampled.

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Generating timetables for an institution is a challenging and time consuming task due to different demands on the overall structure of the timetable. In this paper, a new hybrid method which is a combination of a great deluge and artificial bee colony algorithm (INMGD-ABC) is proposed to address the university timetabling problem. Artificial bee colony algorithm (ABC) is a population based method that has been introduced in recent years and has proven successful in solving various optimization problems effectively. However, as with many search based approaches, there exist weaknesses in the exploration and exploitation abilities which tend to induce slow convergence of the overall search process. Therefore, hybridization is proposed to compensate for the identified weaknesses of the ABC. Also, inspired from imperialist competitive algorithms, an assimilation policy is implemented in order to improve the global exploration ability of the ABC algorithm. In addition, Nelder–Mead simplex search method is incorporated within the great deluge algorithm (NMGD) with the aim of enhancing the exploitation ability of the hybrid method in fine-tuning the problem search region. The proposed method is tested on two differing benchmark datasets i.e. examination and course timetabling datasets. A statistical analysis t-test has been conducted and shows the performance of the proposed approach as significantly better than basic ABC algorithm. Finally, the experimental results are compared against state-of-the art methods in the literature, with results obtained that are competitive and in certain cases achieving some of the current best results to those in the literature.