Assessment of Atomic Data: Problems and Solutions

For the reliable analysis and modeling of astrophysical, laser-produced, and fusion plasmas, atomic data are required for a number of parameters, including energy levels, radiative rates, and electron impact excitation rates. Such data are desired for a range of elements (H to W) and their many ions. However, measurements of atomic data, mainly for radiative and excitation rates, are not feasible for many species, and therefore, calculations are needed. For some ions (such as of C, Fe, and Kr), there is a variety of calculations available in the literature, but often, they differ significantly from one another. Therefore, there is a great demand from the user community to have data "assessed" for accuracy so that they can be confidently applied to the modeling of plasmas. In this paper we highlight the difficulties in assessing atomic data and offer some solutions for improving the accuracy of calculated results.

Synchrophasor-Based Islanding Detection for Distributed Generation Systems Using Systematic Principal Component Analysis Approaches

Systematic principal component analysis (PCA) methods are presented in this paper for reliable islanding detection for power systems with significant penetration of distributed generations (DGs), where synchrophasors recorded by Phasor Measurement Units (PMUs) are used for system monitoring. Existing islanding detection methods such as Rate-of-change-of frequency (ROCOF) and Vector Shift are fast for processing local information, however with the growth in installed capacity of DGs, they suffer from several drawbacks. Incumbent genset islanding detection cannot distinguish a system wide disturbance from an islanding event, leading to mal-operation. The problem is even more significant when the grid does not have sufficient inertia to limit frequency divergences in the system fault/stress due to the high penetration of DGs. To tackle such problems, this paper introduces PCA methods for islanding detection. Simple control chart is established for intuitive visualization of the transients. A Recursive PCA (RPCA) scheme is proposed as a reliable extension of the PCA method to reduce the false alarms for time-varying process. To further reduce the computational burden, the approximate linear dependence condition (ALDC) errors are calculated to update the associated PCA model. The proposed PCA and RPCA methods are verified by detecting abnormal transients occurring in the UK utility network.

Study on Some Key Problems Related to Integrated Energy Systems: 区域综合能源系统若干问题研究

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.

Measuring non-use value of environmental goods using the contingent valuation method:problems of information and cognition and the application of cognitive questionnaire design methods

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

Biosecurity and Emerging Plant Health Problems in Turf Production and Maintenance

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.

Early warning systems: problems, pragmatics and potential

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.

Traumatic brain injury and co-occurring problems in prison populations: a systematic review.

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.

The Reliability of the Arc-Length Method in the Analysis of Mode-Jumping Problems

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.

A Fast Algorithm for Sparse Support Vector Machines for Mobile Computing Applications

This research presents a fast algorithm for projected support vector machines (PSVM) by selecting a basis vector set (BVS) for the kernel-induced feature space, the training points are projected onto the subspace spanned by the selected BVS. A standard linear support vector machine (SVM) is then produced in the subspace with the projected training points. As the dimension of the subspace is determined by the size of the selected basis vector set, the size of the produced SVM expansion can be specified. A two-stage algorithm is derived which selects and refines the basis vector set achieving a locally optimal model. The model expansion coefficients and bias are updated recursively for increase and decrease in the basis set and support vector set. The condition for a point to be classed as outside the current basis vector and selected as a new basis vector is derived and embedded in the recursive procedure. This guarantees the linear independence of the produced basis set. The proposed algorithm is tested and compared with an existing sparse primal SVM (SpSVM) and a standard SVM (LibSVM) on seven public benchmark classification problems. Our new algorithm is designed for use in the application area of human activity recognition using smart devices and embedded sensors where their sometimes limited memory and processing resources must be exploited to the full and the more robust and accurate the classification the more satisfied the user. Experimental results demonstrate the effectiveness and efficiency of the proposed algorithm. This work builds upon a previously published algorithm specifically created for activity recognition within mobile applications for the EU Haptimap project [1]. The algorithms detailed in this paper are more memory and resource efficient making them suitable for use with bigger data sets and more easily trained SVMs.

International Coordination in Cross-Border Bank Bail-ins: Problems and Prospects

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.