Considerations of Accuracy and Uncertainty with Kriging Surrogate Models in Single-Objective Electromagnetic Design Optimization

The high computational cost of evaluating objective functions in electromagnetic optimal design problems necessitates the use of cost-effective techniques. This paper discusses the use of one popular technique, surrogate modelling, with emphasis placed on the importance of considering both the accuracy of, and uncertainty in, the surrogate model. After briefly reviewing how such considerations have been made in the single-objective optimization of electromagnetic devices, their use with kriging surrogate models is investigated. Traditionally, space-filling experimental designs are used to construct the initial kriging model, with the aim to maximize the accuracy of the initial surrogate model, from which the optimization search will start. Utility functions, which balance the predictions made by this model with its uncertainty, are often used to select the next point to be evaluated. In this paper, the performances of several different utility functions are examined using experimental designs which yield initial kriging models of varying degrees of accuracy. It is found that no advantage is necessarily achieved through searching for optima using utility functions on initial kriging models of higher accuracy, and that a reduction in the total number of objective function evaluations may be achieved by starting the iterative optimization search earlier with utility functions on kriging models of lower accuracy. The implications for electromagnetic optimal design are discussed

Probability of improvement methods for constrained multi-objective optimization

This paper shows how the simultaneous consideration of multiple Kriging models can lead to useful metrics for the selection of design vectors in constrained multiobjective optimization. The savings in computational cost with such methods make them particularly useful for optimal electromagnetic design

Modeling uncertain and dynamic casualty health in optimization-based decision support for mass casualty incident response

When designing a decision support program for use in coordinating the response to Mass Casualty Incidents, the modelling of the health of casualties presents a significant challenge. In this paper we propose one such health model, capable of acknowledging both the uncertain and dynamic nature of casualty health. Incorporating this into a larger optimisation model capable of use in real-time and in an online manner, computational experiments examining the effect of errors in health assessment, regular updates of health and delays in communication are reported. Results demonstrate the often significant impact of these factors

Online optimization of casualty processing in major incident response: An experimental analysis

When designing an optimization model for use in mass casualty incident (MCI) response, the dynamic and uncertain nature of the problem environment poses a significant challenge. Many key problem parameters, such as the number of casualties to be processed, will typically change as the response operation progresses. Other parameters, such as the time required to complete key response tasks, must be estimated and are therefore prone to errors. In this work we extend a multi-objective combinatorial optimization model for MCI response to improve performance in dynamic and uncertain environments. The model is developed to allow for use in real time, with continuous communication between the optimization model and problem environment. A simulation of this problem environment is described, allowing for a series of computational experiments evaluating how model utility is influenced by a range of key dynamic or uncertain problem and model characteristics. It is demonstrated that the move to an online system mitigates against poor communication speed, while errors in the estimation of task duration parameters are shown to significantly reduce model utility

The eVALuate study: two parallel randomised trials, one comparing laparoscopic with abdominal hysterectomy, the other comparing laparoscopic with vaginal hysterectomy

OBJECTIVE: To compare the effects of laparoscopic hysterectomy and abdominal hysterectomy in the abdominal trial, and laparoscopic hysterectomy and vaginal hysterectomy in the vaginal trial. DESIGN: Two parallel, multicentre, randomised trials. Setting 28 UK centres and two South African centres. Participants 1380 women were recruited; 1346 had surgery; 937 were followed up at one year. PRIMARY OUTCOME: outcome Rate of major complications. RESULTS: In the abdominal trial laparoscopic hysterectomy was associated with a higher rate of major complications than abdominal hysterectomy (11.1% v 6.2%, P = 0.02; difference 4.9%, 95% confidence interval 0.9% to 9.1%) and the number needed to treat to harm was 20. Laparoscopic hysterectomy also took longer to perform (84 minutes v 50 minutes) but was less painful (visual analogue scale 3.51 v 3.88, P = 0.01) and resulted in a shorter stay in hospital after the operation (3 days v 4 days). Six weeks after the operation, laparoscopic hysterectomy was associated with less pain and better quality of life than abdominal hysterectomy (SF-12, body image scale, and sexual activity questionnaires). In the vaginal trial we found no evidence of a difference in major complication rates between laparoscopic hysterectomy and vaginal hysterectomy (9.8% v 9.5%, P = 0.92; difference 0.3%, − 5.2% to 5.8%), and the number needed to treat to harm was 333.We found no evidence of other differences between laparoscopic hysterectomy and vaginal hysterectomy except that laparoscopic hysterectomy took longer to perform (72 minutes v 39 minutes) and was associated with a higher rate of detecting unexpected pathology (16.4% v 4.8%, P = < 0.01). However, this trial was underpowered. CONCLUSIONS: Laparoscopic hysterectomy was associated with a significantly higher rate of major complications than abdominal hysterectomy. It also took longer to perform but was associated with less pain, quicker recovery, and better short term quality of life. The trial comparing vaginal hysterectomy with laparoscopic hysterectomy was underpowered and is inconclusive on the rate of major complications; however, vaginal hysterectomy took less time

Capillary electrophoresis-mass spectrometry using noncovalently coated capillaries for the analysis of biopharmaceuticals

In this work, the usefulness of capillary electrophoresis–electrospray ionization time-of-flight–mass spectrometry for the analysis of biopharmaceuticals was studied. Noncovalently bound capillary coatings consisting of Polybrene-poly(vinyl sulfonic acid) or Polybrene-dextran sulfate-Polybrene were used to minimize protein and peptide adsorption, and achieve good separation efficiencies. The potential of the capillary electrophoresis-mass spectrometry (CE-MS) system to characterize degradation products was investigated by analyzing samples of the drugs, recombinant human growth hormone (rhGH) and oxytocin, which had been subjected to prolonged storage, heat exposure, and/or different pH values. Modifications could be assigned based on accurate masses as obtained with time-of-flight–mass spectrometry (TOF-MS) and migration times with respect to the parent compound. For heat-exposed rhGH, oxidations, sulfonate formation, and deamidations were observed. Oxytocin showed strong deamidation (up to 40%) upon heat exposure at low pH, whereas at medium and high pH, mainly dimer (>10%) and trisulfide formation (6–7%) occurred. Recombinant human interferon-β-1a (rhIFN-β) was used to evaluate the capability of the CE-MS method to assess glycan heterogeneity of pharmaceutical proteins. Analysis of this N-glycosylated protein revealed a cluster of resolved peaks which appeared to be caused by at least ten glycoforms differing merely in sialic acid and hexose N-acetylhexosamine composition. Based on the relative peak area (assuming an equimolar response per glycoform), a quantitative profile could be derived with the disialytated biantennary glycoform as most abundant (52%). Such a profile may be useful for in-process and quality control of rhIFN-β batches. It is concluded that the separation power provided by combined capillary electrophoresis and TOF-MS allows discrimination of highly related protein species

Agent-based modelling and inundation prediction to enable the identification of businesses affected by flooding

Flooding continues to cause significant disruption to individuals, organisations and communities in many parts of the world. In terms of the impact on businesses in the United Kingdom (UK), flooding is responsible for the loss of millions of pounds to the economy. As part of a UK Engineering and Physical Sciences Research Council funded project on flood risk management, SESAME, research is being carried out with the aim of improving business response to and preparedness for flood events. To achieve this aim, one strand of the research is focused on establishing how agent-based modelling and simulation can be used to evaluate and improve business continuity. This paper reports on the development of the virtual geographic environment (VGE) component of an agent-based model and how this has been combined with inundation prediction to enable the identification of businesses affected by flooding in any urban area of the UK. The VGE has been developed to use layers from Ordnance Survey’s MasterMap, namely the Topography Layer, Integrated Transport Network Layer and Address Layer 2. Coupling the VGE with inundation prediction provides credibility in modelling flood events in any area of the UK. An initial case study is presented focusing on the Lower Don Valley region of Sheffield leading to the identification of businesses impacted by flooding based on a predicted inundation. Further work will focus on the development of agents to model and simulate businesses during and in the aftermath of flood events such that changes in their behaviours can be investigated leading to improved operational response and business continuity

Screening families of patients with premature coronary heart disease to identify avoidable cardiovascular risk: a cross-sectional study of family members and a general population comparison group

&lt;b&gt;Background:&lt;/b&gt; Primary prevention should be targeted at individuals with high global cardiovascular risk, but research is lacking on how best to identify such individuals in the general population. Family history is a good proxy measure of global risk and may provide an efficient mechanism for identifying high risk individuals. The aim was to test the feasibility of using patients with premature cardiovascular disease to recruit family members as a means of identifying and screening high-risk individuals. &lt;b&gt;Findings:&lt;/b&gt; We recruited family members of 50 patients attending a cardiology clinic for premature coronary heart disease (CHD). We compared their cardiovascular risk with a general population control group, and determined their perception of their risk and current level of screening. 103 (36%) family members attended screening (27 siblings, 48 adult offspring and 28 partners). Five (5%) had prevalent CHD. A significantly higher percentage had an ASSIGN risk score &#62;20% compared with the general population (13% versus 2%, p &#60; 0.001). Only 37% of family members were aware they were at increased risk and only 50% had had their blood pressure and serum cholesterol level checked in the previous three years. &lt;b&gt;Conclusions:&lt;/b&gt; Patients attending hospital for premature CHD provide a mechanism to contact family members and this can identify individuals with a high global risk who are not currently screened

Group interventions to improve health outcomes : a framework for their design and delivery

Peer reviewedPublisher PD