Large-scale diversity estimation through surname origin inference

The study of surnames as both linguistic and geographical markers of the past has proven valuable in several research fields spanning from biology and genetics to demography and social mobility. This article builds upon the existing literature to conceive and develop a surname origin classifier based on a data-driven typology. This enables us to explore a methodology to describe large-scale estimates of the relative diversity of social groups, especially when such data is scarcely available. We subsequently analyze the representativeness of surname origins for 15 socio-professional groups in France

Genetic and Environmental Structure of DSM-IV Criteria for Antisocial Personality Disorder: A Twin Study

Results from previous studies on DSM-IV and DSM-5 Antisocial Personality Disorder (ASPD) have suggested that the construct is etiologically multidimensional. To our knowledge, however, the structure of genetic and environmental influences in ASPD has not been examined using an appropriate range of biometric models and diagnostic interviews. The 7 ASPD criteria (section A) were assessed in a population-based sample of 2794 Norwegian twins by a structured interview for DSM-IV personality disorders. Exploratory analyses were conducted at the phenotypic level. Multivariate biometric models, including both independent and common pathways, were compared. A single phenotypic factor was found, and the best-fitting biometric model was a single-factor common pathway model, with common-factor heritability of 51% (95% CI 40–67%). In other words, both genetic and environmental correlations between the ASPD criteria could be accounted for by a single common latent variable. The findings support the validity of ASPD as a unidimensional diagnostic construct

The Dutch disease revisited : absorption constraint and learning by doing

This paper revisits the Dutch disease by analyzing the general equilibrium effects of a resource shock on a dependent economy, both in a static and dynamic set- ting. The novel aspect of this study is to incorporate in one coherent framework two distinct features of the Dutch disease literature that have previously been analyzed in isolation: capital accumulation with absorption constraint, and productivity growth induced by learning-by-doing. The result of long run exchange rate appreciation is maintained in line with part of the Dutch Disease literature. In addition, a permanent change in the employment shares occurs after the resource windfall, in favor of the non-traded sector and away from the traded sector growth engine of the economy. In other words, in the long run both of the classic symptoms of the Dutch Disease remain in place.info:eu-repo/semantics/publishedVersio

Specific Antisocial and Borderline Personality Disorder Criteria and General Substance Use : A Twin Study

Antisocial (ASPD) and borderline (BPD) personality disorders (PDs) are associated with increased risk for substance use. They are "specific" risk factors among PDs in that they withstand adjusting for the other PDs, whereas the reverse does not hold. Specificity is a classic sign of causation. This empirical work addresses 3 further problems that can undermine causal inferences in personality and substance-use research: hierarchical nature of etiologic factors in psychiatry, imperfectly operationalized PD criteria, and possible genetic or environmental confounding, as seen in lack of "etiologic continuity." We used exploratory structural equation bifactor modeling and biometric models to mitigate these problems. The participants were Norwegian adult twins of ages 19-36 years (N = 2,801). Criteria for Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), PDs were assessed using a structured interview. General substance-use risk was indicated by World Health Organization Composite International Diagnostic Interviewed alcohol use disorder and illicit drug use, and by self-reported regular smoking. A general risk factor for all criteria of both ASPD and BPD was the strongest individual correlate of general substance use and showed etiologic continuity, though just 3 specific PD criteria could predict substance use to the same extent. The findings indicate that a broad latent factor for both ASPD and BPD may be a specific and a genetically and environmentally unconfounded risk factor for substance use. Substance-use treatment research might benefit from attending to transdiagnostic models of ASPD, BPD, and related behavioral disinhibition.Peer reviewe

Joint factorial structure of psychopathology and personality

Background Normative and pathological personality traits have rarely been integrated into a joint large-scale structural analysis with psychiatric disorders, although a recent study suggested they entail a common individual differences continuum. Methods We explored the joint factor structure of 11 psychiatric disorders, five personality-disorder trait domains (DSM-5 Section III), and five normative personality trait domains (the 'Big Five') in a population-based sample of 2796 Norwegian twins, aged 19-46. Results Three factors could be interpreted: (i) a general risk factor for all psychopathology, (ii) a risk factor specific to internalizing disorders and traits, and (iii) a risk factor specific to externalizing disorders and traits. Heritability estimates for the three risk factor scores were 48% (95% CI 41-54%), 35% (CI 28-42%), and 37% (CI 31-44%), respectively. All 11 disorders had uniform loadings on the general factor (congruence coefficient of 0.991 with uniformity). Ignoring sign and excluding the openness trait, this uniformity of factor loadings held for all the personality trait domains and all disorders (congruence 0.983). Conclusions Based on our findings, future research should investigate joint etiologic and transdiagnostic models for normative and pathological personality and other psychopathology.Peer reviewe

Multistatic micro‐Doppler radar feature extraction for classification of unloaded/loaded micro‐drones

This paper presents the use of micro-Doppler signatures collected by a multistatic radar to detect and discriminate between micro-drones hovering and flying while carrying different payloads, which may be an indication of unusual or potentially hostile activities. Different features have been extracted and tested, namely features related to the Radar Cross Section of the micro-drones, as well as the Singular Value Decomposition (SVD) and centroid of the micro-Doppler signatures. In particular, the added benefit of using multistatic information in comparison with conventional radar is quantified. Classification performance when identifying the weight of the payload that the drone was carrying while hovering was found to be consistently above 96% using the centroid-based features and multistatic information. For the non-hovering scenarios classification results with accuracy above 95% were also demonstrated in preliminary tests in discriminating between three different payload weights

Validation of Doloplus-2 among nonverbal nursing home patients - an evaluation of Doloplus-2 in a clinical setting

In the present study, more patients were categorized as having pain while using Doloplus-2 compared with nurses' estimation of pain without using any tools. The fact that nurses could not report if the patients were in pain in one third of the patients supports the claim that Doloplus-2 is a useful supplement for estimating pain in this population. However, nurses must use their clinical experience in addition to the use of Doloplus-2, as behaviour can have different meaning for different patients. Further research is still needed about the use of Doloplus-2 in patients not able to self-report their pain.THE WORK (AS DEFINED BELOW) IS PROVIDED UNDER THE TERMS OF THIS BIOMED CENTRAL OPEN ACCESS LICENSE ("LICENSE"). THE WORK IS PROTECTED BY COPYRIGHT AND/OR OTHER APPLICABLE LAW. ANY USE OF THE WORK OTHER THAN AS AUTHORIZED UNDER THIS LICENSE IS PROHIBITED.BY EXERCISING ANY RIGHTS TO THE WORK PROVIDED HERE, YOU ACCEPT AND AGREE TO BE BOUND BY THE TERMS OF THIS LICENSE. THE LICENSOR GRANTS YOU THE RIGHTS CONTAINED HERE IN CONSIDERATION OF YOUR ACCEPTANCE OF SUCH TERMS AND CONDITIONS

Extracting causal relations on HIV drug resistance from literature

<p>Abstract</p> <p>Background</p> <p>In HIV treatment it is critical to have up-to-date resistance data of applicable drugs since HIV has a very high rate of mutation. These data are made available through scientific publications and must be extracted manually by experts in order to be used by virologists and medical doctors. Therefore there is an urgent need for a tool that partially automates this process and is able to retrieve relations between drugs and virus mutations from literature.</p> <p>Results</p> <p>In this work we present a novel method to extract and combine relationships between HIV drugs and mutations in viral genomes. Our extraction method is based on natural language processing (NLP) which produces grammatical relations and applies a set of rules to these relations. We applied our method to a relevant set of PubMed abstracts and obtained 2,434 extracted relations with an estimated performance of 84% for F-score. We then combined the extracted relations using logistic regression to generate resistance values for each <drug, mutation> pair. The results of this relation combination show more than 85% agreement with the Stanford HIVDB for the ten most frequently occurring mutations. The system is used in 5 hospitals from the Virolab project <url>http://www.virolab.org</url> to preselect the most relevant novel resistance data from literature and present those to virologists and medical doctors for further evaluation.</p> <p>Conclusions</p> <p>The proposed relation extraction and combination method has a good performance on extracting HIV drug resistance data. It can be used in large-scale relation extraction experiments. The developed methods can also be applied to extract other type of relations such as gene-protein, gene-disease, and disease-mutation.</p