Vortex Duality in Higher Dimensions

A dynamic vortex line traces out a world sheet in spacetime. This thesis shows that the information of all its dynamic behaviour is completely contained in the world sheet. Furthermore a mathematical framework for order–disorder phase transitions in terms of the proliferation of such vortex world sheets is presented, leading to the prediction of quantized vortex lines of electric current in phase-disordered superconductors.LEI Universiteit LeidenTheoretical Physic

A Musical instrument in MEMS

In this work we describe a MEMS instrument that resonates at audible frequencies, and with which music can be made. The sounds are generated by mechanical resonators and capacitive displacement sensors. Damping by air scales unfavourably for generating audible frequencies with small devices. Therefore a vacuum of 1.5 mbar is used to increase the quality factor and consequently the duration of the sounds to around 0.25 s. The instrument will be demonstrated during the MME 2010 conference opening, in a musical composition especially made for the occasion

Prevention of late-life Depression in Primary Care: Do we know where to begin?

OBJECTIVE: This study attempted to compare two models for selective (people at elevated risk) and indicated (those with subsyndromal depressive symptoms) prevention and to determine the optimal strategy for prevention of late-life depression. METHOD: Onset was assessed at 3 years with the Geriatric Mental State AGECAT in a randomly selected cohort of 1,940 nondepressed and nondemented older people in Amsterdam. Risk factors that can easily be identified in primary care were used. RESULTS: The association of risk factors with depression incidence was expressed in absolute and relative risk estimates, number needed to treat, and population-attributable fractions. Prevention models were identified with classification and regression tree analyses. In the indicated prevention model, subsyndromal symptoms of depression were associated with a risk of almost 40% of developing depression and a number needed to treat of 5.8, accounting for 24.6% of new cases. Adding more risk factors raised the absolute risk to 49.3%, with a lower number needed to treat but also lower attributable fraction values. In the selective prevention model, spousal death showed the highest risk, becoming even higher if the subjects also had a chronic illness. Overall, the attributable fraction values in the indicated model were higher, identifying more people at risk. CONCLUSIONS: Consideration of the costs and benefits of both models in the context of the availability of evidence-based preventative interventions indicated that prevention aimed at elderly people with depressive symptoms is preferred. The focus on treatment should be readdressed; a new approach is needed, with a stronger emphasis on prevention

Heritabilities of Apolipoprotein and Lipid Levels in Three Countries

This study investigated the influence of genes and environment on the variation of apolipoprotein and lipid levels, which are important intermediate phenotypes in the pathways toward cardiovascular disease. Heritability estimates are presented, including those for apolipoprotein E and All levels which have rarely been reported before. We studied twin samples from the Netherlands (two cohorts; n = 160 pairs, aged 13-22 and n = 204 pairs, aged 34-62), Australia (n = 1362 pairs, aged 28-92) and Sweden (n = 302 pairs, aged 42-88). The variation of apolipoprotein and lipid levels depended largely on the influences of additive genetic factors in each twin sample. There was no significant evidence for the influence of common environment. No sex differences in heritability estimates for any phenotype in any of the samples were observed. Heritabilities ranged from 0.48-0.87, with most heritabilities exceeding 0.60. The heritability estimates in the Dutch samples were significantly higher than in the Australian sample. The heritabilities for the Swedish were intermediate to the Dutch and the Australian samples and not significantly different from the heritabilities in these other two samples. Although sample specific effects are present, we have shown that genes play a major role in determining the variance of apolipoprotein and lipid levels in four independent twin samples from three different countries

A recurrent neural network architecture to model physical activity energy expenditure in older people

Through the quantification of physical activity energy expenditure (PAEE), health care monitoring has the potential to stimulate vital and healthy ageing, inducing behavioural changes in older people and linking these to personal health gains. To be able to measure PAEE in a health care perspective, methods from wearable accelerometers have been developed, however, mainly targeted towards younger people. Since elderly subjects differ in energy requirements and range of physical activities, the current models may not be suitable for estimating PAEE among the elderly. Furthermore, currently available methods seem to be either simple but non-generalizable or require elaborate (manual) feature construction steps. Because past activities influence present PAEE, we propose a modeling approach known for its ability to model sequential data, the recurrent neural network (RNN). To train the RNN for an elderly population, we used the growing old together validation (GOTOV) dataset with 34 healthy participants of 60 years and older (mean 65 years old), performing 16 different activities. We used accelerometers placed on wrist and ankle, and measurements of energy counts by means of indirect calorimetry. After optimization, we propose an architecture consisting of an RNN with 3 GRU layers and a feedforward network combining both accelerometer and participant-level data. Our efforts included switching mean to standard deviation for down-sampling the input data and combining temporal and static data (person-specific details such as age, weight, BMI). The resulting architecture produces accurate PAEE estimations while decreasing training input and time by a factor of 10. Subsequently, compared to the state-of-the-art, it is capable to integrate longer activity data which lead to more accurate estimations of low intensity activities EE. It can thus be employed to investigate associations of PAEE with vitality parameters of older people related to metabolic and cognitive health and mental well-being.Algorithms and the Foundations of Software technolog

The emergence of gauge invariance: the stay-at-home gauge versus local-global duality

In condensed matter physics gauge symmetries other than the U(1) of electromagnetism are of an emergent nature. Two emergence mechanisms for gauge symmetry are well established: the way these arise in Kramers-Wannier type local-global dualities, and as a way to encode local constraints encountered in (doped) Mott insulators. We demonstrate that these gauge structures are closely related, and appear as counterparts in either the canonical or field-theoretical language. The restoration of symmetry in a disorder phase transition is due to having the original local variables subjected to a coherent superposition of all possible topological defect configurations, with the effect that correlation functions are no longer well-defined. This is completely equivalent to assigning gauge freedom to those variables. Two cases are considered explicitly: the well-known vortex duality in bosonic Mott insulators serves to illustrate the principle. The acquired wisdoms are then applied to the less familiar context of dualities in quantum elasticity, where we elucidate the relation between the quantum nematic and linearized gravity. We reflect on some deeper implications for the emergence of gauge symmetry in general.Comment: RevTeX, 12 pages, 4 figure

Common and specific determinants of 9-year depression and anxiety course-trajectories: a machine-learning investigation in the Netherlands Study of Depression and Anxiety (NESDA)

Background: Given the strong relationship between depression and anxiety, there is an urge to investigate their shared and specific long-term course determinants. The current study aimed to identify and compare the main determinants of the 9-year trajectories of combined and pure depression and anxiety symptom severity. Methods: Respondents with a 6-month depression and/or anxiety diagnosis (n=1,701) provided baseline data on 152 sociodemographic, clinical and biological variables. Depression and anxiety symptom severity assessed at baseline, 2-, 4-, 6- and 9-year follow-up, were used to identify data-driven course-trajectory subgroups for general psychological distress, pure depression, and pure anxiety severity scores. For each outcome (classprobability), a Superlearner (SL) algorithm identified an optimally weighted (minimum mean squared error) combination of machine-learning prediction algorithms. For each outcome, the top determinants in the SL were identified by determining variable-importance and correlations between each SL-predicted and observed outcome (rho pred) were calculated. Results: Low to high prediction correlations (rho pred: 0.41-0.91, median=0.73) were found. In the SL, important determinants of psychological distress were age, young age of onset, respiratory rate, participation disability, somatic disease, low income, minor depressive disorder and mastery score. For course of pure depression and anxiety symptom severity, similar determinants were found. Specific determinants of pure depression included several types of healthcare-use, and of pure-anxiety course included somatic arousal and psychological distress. Limitations: Limited sample size for machine learning. Conclusions: The determinants of depression- and anxiety-severity course are mostly shared. Domain-specific exceptions are healthcare use for depression and somatic arousal and distress for anxiety-severity course.Stress-related psychiatric disorders across the life spa

Discovery and fine-mapping of glycaemic and obesity-related trait loci using high-density imputation

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated