Detecting Anomalies in Graphs with Numeric Labels

This paper presents Yagada, an algorithm to search labelled graphs for anomalies using both structural data and numeric attributes. Yagada is explained using several security-related examples and validated with experiments on a physical Access Control database. Quantitative analysis shows that in the upper range of anomaly thresholds, Yagada detects twice as many anomalies as the best-performing numeric discretization algorithm. Qualitative evaluation shows that the detected anomalies are meaningful, representing a com- bination of structural irregularities and numerical outliers.

Why multiples matter: Reconceptualising the population referred to child and family social workers

Building on a body of previous research by the author and colleagues in relation to multiple adverse childhood experiences (MACE), this paper addresses the question of ‘why multiples matter’ in relation to issues of cumulative adversity. Illustrative evidence is drawn from three research domains, epidemiology, multiple services use and child maltreatment to demonstrate the collective weight of evidence to suggest a targeting of those children and families experiencing multiple adversities to diminish the effects of such adversities realised across the life-course. Whilst the history of previous largely unsuccessful attempts to widen the range of children prioritised for intervention by child and family social workers might lead to pessimism in relation to their ability to respond to a MACE informed public health agenda, there are clear possibilities for developing agency structures, assessment tools and social work practices directed toward meeting the needs of those sub populations already prioritised by social workers: namely Children in Need, Children in need of Protection and Looked after Children.

Using Graphs to Visualise and Detect Anomalies in Access Control System Transactions

Physical Access Control Systems are commonly used to secure doors in buildings such as airports, hospitals, government buildings and offices. These systems are designed primarily to provide an authentication mechanism, but they also log each door access as a transaction in a database. Unsupervised learning techniques can be used to detect inconsistencies or anomalies in the mobility data, such as a cloned or forged Access Badge, or unusual behaviour by staff members. In this paper, we present an overview of our method of inferring directed graphs to represent a physical building network and the flows of mobility within it. We demonstrate how the graphs can be used for Visual Data Exploration, and outline how to apply algorithms based on Information Theory to the graph data in order to detect inconsistent or abnormal behaviour.

European Recommendations for Primary Prevention of Congenital Anomalies: A Joined Effort of EUROCAT and EUROPLAN Projects to Facilitate Inclusion of This Topic in the National Rare Disease Plans

Congenital anomalies (CA) are the paradigm example of rare diseases liable to primary prevention actions due to the multifactorial etiology of many of them, involving a number of environmental factors together with genetic predispositions. Yet despite the preventive potential, lack of attention to an integrated preventive strategy has led to the prevalence of CA remaining relatively stable in recent decades. The 2 European projects, EUROCAT and EUROPLAN, have joined efforts to provide the first science-based and comprehensive set of recommendations for the primary prevention of CA in the European Union. The resulting EUROCAT-EUROPLAN 'Recommendations on Policies to Be Considered for the Primary Prevention of Congenital Anomalies in National Plans and Strategies on Rare Diseases' were issued in 2012 and endorsed by EUCERD (European Union Committee of Experts on Rare Diseases) in 2013. The recommendations exploit interdisciplinary expertise encompassing drugs, diet, lifestyles, maternal health status, and the environment. The recommendations include evidence-based actions aimed at reducing risk factors and at increasing protective factors and behaviors at both individual and population level. Moreover, consideration is given to topics specifically related to CA (e.g. folate status, teratogens) as well as of broad public health impact (e.g. obesity, smoking) which call for specific attention to their relevance in the pre- and periconceptional period. The recommendations, reported entirely in this paper, are a comprehensive tool to implement primary prevention into national policies on rare diseases in Europe.

Detecting localized homogeneous anomalies over spatio-temporal data

The last decade has witnessed an unprecedented growth in availability of data having spatio-temporal characteristics. Given the scale and richness of such data, finding spatio-temporal patterns that demonstrate significantly different behavior from their neighbors could be of interest for various application scenarios such as – weather modeling, analyzing spread of disease outbreaks, monitoring traffic congestions, and so on. In this paper, we propose an automated approach of exploring and discovering such anomalous patterns irrespective of the underlying domain from which the data is recovered. Our approach differs significantly from traditional methods of spatial outlier detection, and employs two phases – i) discovering homogeneous regions, and ii) evaluating these regions as anomalies based on their statistical difference from a generalized neighborhood. We evaluate the quality of our approach and distinguish it from existing techniques via an extensive experimental evaluation.

Scaling Up Market Anomalies

This paper implements momentum among a host of market anomalies. Our investment universe consists of the 15 top (long-leg) and 15 bottom (short-leg) anomaly portfolios. The proposed active strategy buys (sells short) a subset of the top (bottom) anomaly portfolios based on past one-month return. The evidence shows statistically strong and economically meaningful persistence in anomaly payoffs. Our strategy consistently outperforms a naive benchmark that equal weights anomalies and yields an abnormal monthly return ranging between 1.27% and 1.47%. The persistence is robust to the post-2000 period, and various other considerations, and is stronger following episodes of high investor sentiment.

Multiples in the Newborn Intensive Care Unit: parents' and nurses' perspectives

This paper discusses the issues of parents and nurses when mulitples are admitted to busy NICU's

Selective serotonin reuptake inhibitor antidepressant use in first trimester pregnancy and risk of specific congenital anomalies: a European register-based study

Evidence of an association between early pregnancy exposure to selective serotonin reuptake inhibitors (SSRI) and congenital heart defects (CHD) has contributed to recommendations to weigh benefits and risks carefully. The objective of this study was to determine the specificity of association between first trimester exposure to SSRIs and specific CHD and other congenital anomalies (CA) associated with SSRI exposure in the literature (signals). A population-based case-malformed control study was conducted in 12 EUROCAT CA registries covering 2.1 million births 1995-2009 including livebirths, fetal deaths from 20 weeks gestation and terminations of pregnancy for fetal anomaly. Babies/fetuses with specific CHD (n = 12,876) and non-CHD signal CA (n = 13,024), were compared with malformed controls whose diagnosed CA have not been associated with SSRI in the literature (n = 17,083). SSRI exposure in first trimester pregnancy was associated with CHD overall (OR adjusted for registry 1.41, 95% CI 1.07-1.86, fluoxetine adjOR 1.43 95% CI 0.85-2.40, paroxetine adjOR 1.53, 95% CI 0.91-2.58) and with severe CHD (adjOR 1.56, 95% CI 1.02-2.39), particularly Tetralogy of Fallot (adjOR 3.16, 95% CI 1.52-6.58) and Ebstein's anomaly (adjOR 8.23, 95% CI 2.92-23.16). Significant associations with SSRI exposure were also found for ano-rectal atresia/stenosis (adjOR 2.46, 95% CI 1.06-5.68), gastroschisis (adjOR 2.42, 95% CI 1.10-5.29), renal dysplasia (adjOR 3.01, 95% CI 1.61-5.61), and clubfoot (adjOR 2.41, 95% CI 1.59-3.65). These data support a teratogenic effect of SSRIs specific to certain anomalies, but cannot exclude confounding by indication or associated factors.