Probabilistic Analysis of Optimization Problems on Generalized Random Shortest Path Metrics

Simple heuristics often show a remarkable performance in practice for optimization problems. Worst-case analysis often falls short of explaining this performance. Because of this, "beyond worst-case analysis" of algorithms has recently gained a lot of attention, including probabilistic analysis of algorithms. The instances of many optimization problems are essentially a discrete metric space. Probabilistic analysis for such metric optimization problems has nevertheless mostly been conducted on instances drawn from Euclidean space, which provides a structure that is usually heavily exploited in the analysis. However, most instances from practice are not Euclidean. Little work has been done on metric instances drawn from other, more realistic, distributions. Some initial results have been obtained by Bringmann et al. (Algorithmica, 2013), who have used random shortest path metrics on complete graphs to analyze heuristics. The goal of this paper is to generalize these findings to non-complete graphs, especially Erd\H{o}s-R\'enyi random graphs. A random shortest path metric is constructed by drawing independent random edge weights for each edge in the graph and setting the distance between every pair of vertices to the length of a shortest path between them with respect to the drawn weights. For such instances, we prove that the greedy heuristic for the minimum distance maximum matching problem, the nearest neighbor and insertion heuristics for the traveling salesman problem, and a trivial heuristic for the $k$-median problem all achieve a constant expected approximation ratio. Additionally, we show a polynomial upper bound for the expected number of iterations of the 2-opt heuristic for the traveling salesman problem.Comment: An extended abstract appeared in the proceedings of WALCOM 201

Reasons for and consequences of missed appointments in general practice in the UK: questionnaire survey and prospective review of medical records

Background Missed appointments are a common occurrence in primary care in the UK, yet little is known about the reasons for them, or the consequences of missing an appointment. This paper aims to determine the reasons for missed appointments and whether patients who miss an appointment subsequently consult their general practitioner (GP). Secondary aims are to compare psychological morbidity, and the previous appointments with GPs between subjects and a comparison group. Methods Postal questionnaire survey and prospective medical notes review of adult patients missing an appointment and the comparison group who attended appointments over a three week period in seven general practices in West Yorkshire. Results Of the 386 who missed appointments 122 (32%) responded. Of the 386 in the comparison group 223 (58%) responded, resulting in 23 case-control matched pairs with complete data collection. Over 40% of individuals who missed an appointment and participated said that they forgot the appointment and a quarter said that they tried very hard to cancel the appointment or that it was at an inconvenient time. A fifth reported family commitments or being too ill to attend. Over 90% of the patients who missed an appointment subsequently consulted within three months and of these nearly 60% consulted for the stated problem that was going to be presented in the missed consultation. The odds of missing an appointment decreased with increasing age and were greater among those who had missed at least one appointment in the previous 12 months. However, estimates for comparisons between those who missed appointments and the comparison group were imprecise due to the low response rate. Conclusion Patients who miss appointments tend to cite practice factors and their own forgetfulness as the main reasons for doing so, and most attend within three months of a missed appointment. This study highlights a number of implications for future research. More work needs to be done to engage people who miss appointments into research in a meaningful way

Interprofessional communication with hospitalist and consultant physicians in general internal medicine : a qualitative study

This study helps to improve our understanding of the collaborative environment in GIM, comparing the communication styles and strategies of hospitalist and consultant physicians, as well as the experiences of providers working with them. The implications of this research are globally important for understanding how to create opportunities for physicians and their colleagues to meaningfully and consistently participate in interprofessional communication which has been shown to improve patient, provider, and organizational outcomes

Machine learning analysis of complex late gadolinium enhancement patterns to improve risk prediction of major arrhythmic events

Background: Machine learning analysis of complex myocardial scar patterns affords the potential to enhance risk prediction of life-threatening arrhythmia in stable coronary artery disease (CAD). Objective: To assess the utility of computational image analysis, alongside a machine learning (ML) approach, to identify scar microstructure features on late gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) that predict major arrhythmic events in patients with CAD. Methods: Patients with stable CAD were prospectively recruited into a CMR registry. Shape-based scar microstructure features characterizing heterogeneous (‘peri-infarct’) and homogeneous (‘core’) fibrosis were extracted. An ensemble of machine learning approaches were used for risk stratification, in addition to conventional analysis using Cox modeling. Results: Of 397 patients (mean LVEF 45.4 ± 16.0) followed for a median of 6 years, 55 patients (14%) experienced a major arrhythmic event. When applied within an ML model for binary classification, peri-infarct zone (PIZ) entropy, peri-infarct components and core interface area outperformed a model representative of the current standard of care (LVEFClass I): AUROC (95%CI) 0.81 (0.81–0.82) vs. 0.64 (0.63–0.65), p = 0.002. In multivariate cox regression analysis, these features again remained significant after adjusting for LVEFClass I: PIZ entropy hazard ratio (HR) 1.88, 95% confidence interval (CI) 1.38–2.56, p < 0.001; number of PIZ components HR 1.34, 95% CI 1.08–1.67, p = 0.009; core interface area HR 1.6, 95% CI 1.29–1.99, p = <0.001. Conclusion: Machine learning models using LGE-CMR scar microstructure improved arrhythmic risk stratification as compared to guideline-based clinical parameters; highlighting a potential novel approach to identifying candidates for implantable cardioverter defibrillators in stable CAD

Competing biosecurity and risk rationalities in the Chittagong poultry commodity chain, Bangladesh

This paper anthropologically explores how key actors in the Chittagong live bird trading network perceive biosecurity and risk in relation to avian influenza between production sites, market maker scenes and outlets. They pay attention to the past and the present, rather than the future, downplaying the need for strict risk management, as outbreaks have not been reported frequently for a number of years. This is analysed as ‘temporalities of risk perception regarding biosecurity’, through Black Swan theory, the idea that unexpected events with major effects are often inappropriately rationalized (Taleb in The Black Swan. The impact of the highly improbable, Random House, New York, 2007). This incorporates a sociocultural perspective on risk, emphasizing the contexts in which risk is understood, lived, embodied and experienced. Their risk calculation is explained in terms of social consent, practical intelligibility and convergence of constraints and motivation. The pragmatic and practical orientation towards risk stands in contrast to how risk is calculated in the avian influenza preparedness paradigm. It is argued that disease risk on the ground has become a normalized part of everyday business, as implied in Black Swan theory. Risk which is calculated retrospectively is unlikely to encourage investment in biosecurity and, thereby, points to the danger of unpredictable outlier events

Prioritising public health: a qualitative study of decision making to reduce health inequalities

<p>Abstract</p> <p>Background</p> <p>The public health system in England is currently facing dramatic change. Renewed attention has recently been paid to the best approaches for tackling the health inequalities which remain entrenched within British society and across the globe. In order to consider the opportunities and challenges facing the new public health system in England, we explored the current experiences of those involved in decision making to reduce health inequalities, taking cardiovascular disease (CVD) as a case study.</p> <p>Methods</p> <p>We conducted an in-depth qualitative study employing 40 semi-structured interviews and three focus group discussions. Participants were public health policy makers and planners in CVD in the UK, including: Primary Care Trust and Local Authority staff (in various roles); General Practice commissioners; public health academics; consultant cardiologists; national guideline managers; members of guideline development groups, civil servants; and CVD third sector staff.</p> <p>Results</p> <p>The short term target- and outcome-led culture of the NHS and the drive to achieve "more for less", combined with the need to address public demand for acute services often lead to investment in "downstream" public health intervention, rather than the "upstream" approaches that are most effective at reducing inequalities. Despite most public health decision makers wishing to redress this imbalance, they felt constrained due to difficulties in partnership working and the over-riding influence of other stakeholders in decision making processes. The proposed public health reforms in England present an opportunity for public health to move away from the medical paradigm of the NHS. However, they also reveal a reluctance of central government to contribute to shifting social norms.</p> <p>Conclusions</p> <p>It is vital that the effectiveness and cost effectiveness of all new and existing policies and services affecting public health are measured in terms of their impact on the social determinants of health and health inequalities. Researchers have a vital role to play in providing the complex evidence required to compare different models of prevention and service delivery. Those working in public health must develop leadership to raise the profile of health inequalities as an issue that merits attention, resources and workforce capacity; and advocate for central government to play a key role in shifting social norms.</p

Comprehensive phenotypic characterization of late gadolinium enhancement predicts sudden cardiac death in coronary artery disease

Background Late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) offers the potential to noninvasively characterize the phenotypic substrate for sudden cardiac death (SCD). Objectives The authors assessed the utility of infarct characterization by CMR, including scar microstructure analysis, to predict SCD in patients with coronary artery disease (CAD). Methods Patients with stable CAD were prospectively recruited into a CMR registry. LGE quantification of core infarction and the peri-infarct zone (PIZ) was performed alongside computational image analysis to extract morphologic and texture scar microstructure features. The primary outcome was SCD or aborted SCD. Results Of 437 patients (mean age: 64 years; mean left ventricular ejection fraction [LVEF]: 47%) followed for a median of 6.3 years, 49 patients (11.2%) experienced the primary outcome. On multivariable analysis, PIZ mass and core infarct mass were independently associated with the primary outcome (per gram: HR: 1.07 [95% CI: 1.02-1.12]; P = 0.002 and HR: 1.03 [95% CI: 1.01-1.05]; P = 0.01, respectively), and the addition of both parameters improved discrimination of the model (Harrell’s C-statistic: 0.64-0.79). PIZ mass, however, did not provide incremental prognostic value over core infarct mass based on Harrell’s C-statistic or risk reclassification analysis. Severely reduced LVEF did not predict the primary endpoint after adjustment for scar mass. On scar microstructure analysis, the number of LGE islands in addition to scar transmurality, radiality, interface area, and entropy were all associated with the primary outcome after adjustment for severely reduced LVEF and New York Heart Association functional class of >1. No scar microstructure feature remained associated with the primary endpoint when PIZ mass and core infarct mass were added to the regression models. Conclusions Comprehensive LGE characterization independently predicted SCD risk beyond conventional predictors used in implantable cardioverter-defibrillator (ICD) insertion guidelines. These results signify the potential for a more personalized approach to determining ICD candidacy in CAD

The performance of stochastic designs in wellbore drilling operations

© 2018, The Author(s). Wellbore drilling operations frequently entail the combination of a wide range of variables. This is underpinned by the numerous factors that must be considered in order to ensure safety and productivity. The heterogeneity and sometimes unpredictable behaviour of underground systems increases the sensitivity of drilling activities. Quite often the operating parameters are set to certify effective and efficient working processes. However, failings in the management of drilling and operating conditions sometimes result in catastrophes such as well collapse or fluid loss. This study investigates the hypothesis that optimising drilling parameters, for instance mud pressure, is crucial if the margin of safe operating conditions is to be properly defined. This was conducted via two main stages: first a deterministic analysis—where the operating conditions are predicted by conventional modelling procedures—and then a probabilistic analysis via stochastic simulations—where a window of optimised operation conditions can be obtained. The outcome of additional stochastic analyses can be used to improve results derived from deterministic models. The incorporation of stochastic techniques in the evaluation of wellbore instability indicates that margins of the safe mud weight window are adjustable and can be extended considerably beyond the limits of deterministic predictions. The safe mud window is influenced and hence can also be amended based on the degree of uncertainty and the permissible level of confidence. The refinement of results from deterministic analyses by additional stochastic simulations is vital if a more accurate and reliable representation of safe in situ and operating conditions is to be obtained during wellbore operations.Published versio

Diamonds, gold and crime displacement: Hatton Garden, and the evolution of organised crime in the UK

The 2015 Hatton Garden Heist was described as the ‘largest burglary in English legal history’. However, the global attention that this spectacular crime attracted to ‘The Garden’ tended to concentrate upon the value of the stolen goods and the vintage of the burglars. What has been ignored is how the burglary shone a spotlight into Hatton Garden itself, as an area with a unique ‘upperworld’ commercial profile and skills cluster that we identify as an incubator and facilitator for organised crime. The Garden is the UK’s foremost jewellery production and retail centre and this paper seeks to explore how Hatton Garden’s businesses integrated with a fluid criminal population to transition, through hosting lucrative (and bureaucratically complex) VAT gold frauds from 1980 to the early 1990s, to become a major base for sophisticated acquisitive criminal activities. Based on extensive interviews over a thirty year period, evidence from a personal research archive and public records, this paper details a cultural community with a unique criminal profile due to the particularities of its geographical location, ethnic composition, trading culture, skills base and international connections. The processes and structures that facilitate criminal markets are largely under-researched (Antonopoulos et al. 2015: 11), and this paper considers how elements of Hatton Garden’s ‘upperworld’ businesses integrated with project criminals, displaced by policing strategies, to effect this transition

Pressure-induced amorphous-to-amorphous configuration change in Ca-Al metallic glasses

Pressure-induced amorphous-to-amorphous configuration changes in Ca-Al metallic glasses (MGs) were studied by performing in-situ room-temperature high-pressure x-ray diffraction up to about 40 GPa. Changes in compressibility at about 18 GPa, 15.5 GPa and 7.5 GPa during compression are detected in Ca80Al20, Ca72.7Al27.3, and Ca66.4Al33.6 MGs, respectively, whereas no clear change has been detected in the Ca50Al50 MG. The transfer of s electrons into d orbitals under pressure, reported for the pressure-induced phase transformations in pure polycrystalline Ca, is suggested to explain the observation of an amorphous-to-amorphous configuration change in this Ca-Al MG system. Results presented here show that the pressure induced amorphous-to-amorphous configuration is not limited to f electron-containing MGs