ScarGAN: Chained Generative Adversarial Networks to Simulate Pathological Tissue on Cardiovascular MR Scans

Medical images with specific pathologies are scarce, but a large amount of data is usually required for a deep convolutional neural network (DCNN) to achieve good accuracy. We consider the problem of segmenting the left ventricular (LV) myocardium on late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) scans of which only some of the scans have scar tissue. We propose ScarGAN to simulate scar tissue on healthy myocardium using chained generative adversarial networks (GAN). Our novel approach factorizes the simulation process into 3 steps: 1) a mask generator to simulate the shape of the scar tissue; 2) a domain-specific heuristic to produce the initial simulated scar tissue from the simulated shape; 3) a refining generator to add details to the simulated scar tissue. Unlike other approaches that generate samples from scratch, we simulate scar tissue on normal scans resulting in highly realistic samples. We show that experienced radiologists are unable to distinguish between real and simulated scar tissue. Training a U-Net with additional scans with scar tissue simulated by ScarGAN increases the percentage of scar pixels correctly included in LV myocardium prediction from 75.9% to 80.5%.Comment: 12 pages, 5 figures. To appear in MICCAI DLMIA 201

A comparison of general and ambulance specific stressors: predictors of job satisfaction and health problems in a nationwide one-year follow-up study of Norwegian ambulance personnel

Objectives To address the relative importance of general job-related stressors, ambulance specific stressors and individual characteristics in relation to job satisfaction and health complaints (emotional exhaustion, psychological distress and musculoskeletal pain) among ambulance personnel. Materials and methods A nationwide prospective questionnaire survey of ambulance personnel in operational duty at two time points (n = 1180 at baseline, T1 and n = 298 at one-year follow up, T2). The questionnaires included the Maslach Burnout Inventory, The Job Satisfaction Scale, Hopkins Symptom Checklist (SCL-10), Job Stress Survey, the Norwegian Ambulance Stress Survey and the Basic Character Inventory. Results Overall, 42 out of the possible 56 correlations between job stressors at T1 and job satisfaction and health complaints at T2 were statistically significant. Lower job satisfaction at T2 was predicted by frequency of lack of leader support and severity of challenging job tasks. Emotional exhaustion at T2 was predicted by neuroticism, frequency of lack of support from leader, time pressure, and physical demands. Adjusted for T1 levels, emotional exhaustion was predicted by neuroticism (beta = 0.15, p < .05) and time pressure (beta = 0.14, p < 0.01). Psychological distress at T2 was predicted by neuroticism and lack of co-worker support. Adjusted for T1 levels, psychological distress was predicted by neuroticism (beta = 0.12, p < .05). Musculoskeletal pain at T2 was predicted by, higher age, neuroticism, lack of co-worker support and severity of physical demands. Adjusted for T1 levels, musculoskeletal pain was predicted neuroticism, and severity of physical demands (beta = 0.12, p < .05). Conclusions Low job satisfaction at T2 was predicted by general work-related stressors, whereas health complaints at T2 were predicted by both general work-related stressors and ambulance specific stressors. The personality variable neuroticism predicted increased complaints across all health outcomes

Reducing Subway Crowding: Analysis of an Off-Peak Discount Experiment in Hong Kong

Increases in ridership are outpacing capacity expansions in several transit systems. By shifting their focus to demand management, agencies can instead influence how customers use the system and get more out of their present capacity. This paper uses Hong Kong's Mass Transit Railway (MTR) system as a case study to explore the effects of crowding reduction strategies and how to use fare data to support these measures. The MTR system introduced a discount in September 2014 to encourage users to travel before the peak and reduce onboard crowding. To understand the impacts of this intervention, first, existing congestion patterns were reviewed and a clustering analysis was used to reveal typical travel patterns among users. Then, changes to users' departure times were studied at three levels to evaluate the promotion's effects. Patterns of all users were measured across both the whole system and for specific rail segments. The travel patterns of the user groups, who have more homogeneous usage characteristics, were also evaluated and revealed groups who had differing responses to the promotion. The incentive was found to have affected morning travel, particularly at the beginning of the peak hour period and among users with commuter-like behavior. Aggregate and group-specific elasticities were developed to inform future promotions and the results were also used to suggest other potential incentive designs

Validity and reliability of questionnaires measuring physical activity self-efficacy, enjoyment, social support among Hong Kong Chinese children

AbstractBackgroundPhysical activity (PA) correlates have not been extensively studied in Hong Kong children.ObjectiveThe aim of this study is to assess the validity and reliability of translated scales to measure PA related self-efficacy, enjoyment and social support in Hong Kong Chinese children.MethodsSample 1 (n=273, aged 8–12years) was recruited (May–June, 2013) from two primary schools. Confirmatory factor analyses (CFA) were conducted to assess factorial validity. Criterion validity was assessed by correlating measured constructs with self-reported PA. Cronbach's alpha was computed to assess scale internal consistency. The intraclass correlation coefficient (ICC) was performed to assess scale test–retest reliability. Criterion validity was further examined in Sample 2 (n=84, aged 8–12years) from a third school by correlating measured constructs with objectively measured PA collected in September 2013 and February 2014.ResultsThe CFA results supported the one-factor structure of the scales. All PA correlates were significantly (p<0.01) associated with self-reported PA in Sample 1. Self-efficacy and enjoyment were significantly (p<0.05) correlated with objectively measured PA in Sample 2. All the scales demonstrated acceptable internal consistency. All ICC values of the scales suggested acceptable test–retest reliability.ConclusionThe results provide psychometric support for using the scales to measure PA correlates among Hong Kong Chinese children

The Impact of Interpretation Biases on Psychological Responses to the COVID-19 Pandemic:a Prospective Study

BACKGROUND: This study investigates the longitudinal role of interpretation biases in the development and maintenance of health anxiety during the pandemic. Individual differences in behavioural responses to the virus outbreak and decision-making were also examined. METHODS: Two hundred seventy-nine individuals from a pre-pandemic study of interpretation bias and health anxiety completed an online survey during the third wave of the COVID-19 pandemic in Hong Kong. Participants’ health anxiety, interpretation biases, and COVID-specific behaviours (i.e. practice of social distancing, adherence to preventive measures, information seeking), and health decision-making were assessed. RESULTS: Pre-pandemic tendencies to interpret ambiguous physical sensations as signals for illness did not predict health anxiety during the pandemic, b = −0.020, SE = 0.024, t = −0.843, p = .400, 99% CI [−0.082, 0.042], but were associated with a preference for risky treatment option for COVID-19, b = 0.026, SE = 0.010, Wald = 2.614, p = .009, OR = 1.026, 99% CI [1.001, 1.054]. Interpretation biases and health anxiety symptoms during the pandemic were associated with each other and were both found to be significant predictors of practice of social distancing, adherence to preventive measures, and information seeking behaviour. CONCLUSIONS: This study adds to the growing evidence of the role of interpretation biases in health anxiety and the way that people respond to the ongoing pandemic. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12529-022-10079-5

The Genesis 12–19 (G1219) Study: A Twin and Sibling Study of Gene–Environment Interplay and Adolescent Development in the UK

The Genesis 12–19 (G1219) Study is an ongoing longitudinal study of a sample of UK twin pairs, non-twin sibling pairs, and their parents. G1219 was initially designed to examine the role of gene–environment interplay in adolescent depression. However, since then data have continued to be collected from both parents and their offspring into young adulthood. This has allowed for longitudinal analyses of depression and has enabled researchers to investigate multiple phenotypes and to ask questions about intermediate mechanisms. The study has primarily focused on emotional development, particularly depression and anxiety, which have been assessed at multiple levels of analysis (symptoms, cognitions, and relevant environmental experiences). G1219 has also included assessment of a broader range of psychological phenotypes ranging from antisocial behaviors and substance use to sleep difficulties, in addition to multiple aspects of the environment. DNA has also been collected. The first wave of data collection began in the year 1999 and the fifth wave of data collection will be complete before the end of 2012. In this article, we describe the sample, data collection, and measures used. We also summarize some of the key findings to date

Climate analogues: Finding tomorrow’s agriculture today

The analogues approach, developed by CCAFS in R programming, is a novel way of supporting climate and crop models with on-the-ground empirical testing. In essence, the analogues tool connects sites with statistically similar (‘analogous’) climates, across space (i.e. between locations) and/or time (i.e. with past or future climates). A CCAFS dissimilarity index or Hallegatte index can be used to systematically identify climate analogues across the world, for certain regions, or among specific locations. Users may use default criteria or choose from a variety of global climate models (GCMs), scenarios, and input data. Once analogue sites are identified, information gathered from local field studies or databases can be used and compared to provide data for further studies, propose high-potential adaptation pathways, facilitate farmer-to-farmer exchange of knowledge, validate computational models, test new technologies and/or techniques, or enable us to learn from history. Users may manipulate the tool in the free, open-source R software, or access a simplified user-friendly version online

The Nordic Corporate Governance Model

The Nordic Region is remarkable in many ways and has been the subject of increasing interest over the past years. The five countries of Denmark, Finland, Iceland, Norway and Sweden are culturally closely aligned and combine a well-functioning business sector and high GDP with an expansive welfare state and high taxes. What has been well less known outside the Nordic Region is the shared corporate governance model used by companies and for the first time a comprehensive study is available in English to explain this model. The main part of the study is the condensed presentation of the Nordic CG model. It is based on four country reports covering the three EU Member States (DK, F, S) and one EEA Member State (N). Each country report has been drawn up by a team consisting of a legal expert and a corporate governance expert with practical experience. To ensure that the report reflects actual practices, each team was assisted by a reference group consisting of business practitioners with extensive experience from large-cap listed companies and connections to the national CG code committees. To provide an international aspect, the renowned American scholar Ronald J Gilson contributed a comment on the report’s findings in a separate chapter. The key observation of the study is that the Nordic CG model allows the shareholder majority to effectively control and take long-term responsibility for the company that they own. The alleged risk of such a system – the potential that a shareholder majority misuses its power for its own benefit at the expense of minority shareholders – is effectively curbed through a well-developed system of minority protection. The result is a governance model that encourages strong shareholders to engage in the governance of the company in their own interest, while creating value for the company and all its shareholders