Multifractal portrayal of the Swiss population

Fractal geometry is a fundamental approach for describing the complex irregularities of the spatial structure of point patterns. The present research characterizes the spatial structure of the Swiss population distribution in the three Swiss geographical regions (Alps, Plateau and Jura) and at the entire country level. These analyses were carried out using fractal and multifractal measures for point patterns, which enabled the estimation of the spatial degree of clustering of a distribution at different scales. The Swiss population dataset is presented on a grid of points and thus it can be modelled as a "point process" where each point is characterized by its spatial location (geometrical support) and a number of inhabitants (measured variable). The fractal characterization was performed by means of the box-counting dimension and the multifractal analysis was conducted through the Renyi's generalized dimensions and the multifractal spectrum. Results showed that the four population patterns are all multifractals and present different clustering behaviours. Applying multifractal and fractal methods at different geographical regions and at different scales allowed us to quantify and describe the dissimilarities between the four structures and their underlying processes. This paper is the first Swiss geodemographic study applying multifractal methods using high resolution data.

First use of multiple substances: Identification of meaningful patterns

Context: Understanding the process through which adolescents and young adults are trying legal and illegal substances is a crucial point for the development of tailored prevention and treatment programs. However, patterns of substance first use can be very complex when multiple substances are considered, requiring reduction into a few meaningful number of categories. Data: We used data from a survey on adolescent and young adult health conducted in 2002 in Switzerland. Answers from 2212 subjects aged 19 and 20 were included. The first consumption ever of 10 substances (tobacco, cannabis, medicine to get high, sniff (volatile substances, and inhalants), ecstasy, GHB, LSD, cocaine, methadone, and heroin) was considered for a grand total of 516 different patterns. Methods: In a first step, automatic clustering was used to decrease the number of patterns to 50. Then, two groups of substance use experts, three social field workers, and three toxicologists and health professionals, were asked to reduce them into a maximum of 10 meaningful categories. Results: Classifications obtained through our methodology are of practical interest by revealing associations invisible to purely automatic algorithms. The article includes a detailed analysis of both final classifications, and a discussion on the advantages and limitations of our approach.

Effects of the naturally occurring food mycotoxin ochratoxin A on brain cells in culture.

The potential of ochratoxin A (OTA) to damage brain cells was studied by using a three-dimensional cell culture system as model for the developing brain. Aggregating cell cultures of foetal rat telencephalon were tested either during an early developmental period, or during a phase of advanced maturation, over a wide range of OTA concentrations (0.4 nM to 50 microM). By monitoring changes in activities of cell type-specific enzymes (ChAt and GAD, for cholinergic and GABAergic neurones, respectively, GS for astrocytes and CNP for oligodendrocytes), the concentration-dependent toxicity and neurodevelopmental effects of OTA were determined. OTA proved to be highly toxic, since a 10-day treatment at 50 nM caused a general cytotoxicity in both mature and immature cultures. At 10 nM of OTA, cell type-specific effects were observed: in immature cultures, a loss in neuronal and oligodendroglial enzyme activities, and an increase in the activity of the astroglial marker glutamine synthetase were found, Furthermore, at 2 and 10 nM of OTA, a clustering of microglial cells was observed. In mature cultures, OTA was somewhat less potent, but caused a similar pattern of toxic effects. A 24 h-treatment with OTA resulted in a concentration-dependent decrease in protein synthesis, with IC50 values of 25 nM and 33 nM for immature and mature cultures respectively. Acute (24 h) treatment at high OTA concentrations (10 to 50 microM) caused a significant increase in reactive oxygen species formation, as measured by the intracellular oxidation of 2',7'-dichlorofluorescin. These results suggest that OTA has the potential to be a potent toxicant to brain cells, and that its effects at nanomolar concentrations are primarily due to the inhibition of protein synthesis, whereas ROS seem not to be involved in the toxicity mediated by a chronic exposure to OTA at such low concentrations.

The Significance of Identifying Industrial clusters The Case of Scotland

Industrial clustering policy is now an integral part of economic development planning in most advanced economies. However, there have been concerns in some quarters over the ability of an industrial cluster-based development strategy to deliver its promised economic benefits and this has been increasingly been blamed on the failure by governments to identify industrial clusters. In a study published in 2001, the DTI identified clusters across the UK based on the comparative scale and significance of industrial sectors. The study identified thirteen industrial clusters in Scotland. However the clusters identified are not a homogeneous set and they seem to vary in terms of their geographic concentration within Scotland. This paper examines the spatial distribution of industries within Scotland, thereby identifying more localised clusters. The study follows as closely as possible the DTI methodology which was used to identify such concentrations of economic activity with particular attention directed towards the thirteen clusters identified by the DTI. The paper concludes with some remarks of the general problem of identifying the existence of industrial clusters.

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The use of the Internet now has a specific purpose: to find information. Unfortunately, the amount of data available on the Internet is growing exponentially, creating what can be considered a nearly infinite and ever-evolving network with no discernable structure. This rapid growth has raised the question of how to find the most relevant information. Many different techniques have been introduced to address the information overload, including search engines, Semantic Web, and recommender systems, among others. Recommender systems are computer-based techniques that are used to reduce information overload and recommend products likely to interest a user when given some information about the user's profile. This technique is mainly used in e-Commerce to suggest items that fit a customer's purchasing tendencies. The use of recommender systems for e-Government is a research topic that is intended to improve the interaction among public administrations, citizens, and the private sector through reducing information overload on e-Government services. More specifically, e-Democracy aims to increase citizens' participation in democratic processes through the use of information and communication technologies. In this chapter, an architecture of a recommender system that uses fuzzy clustering methods for e-Elections is introduced. In addition, a comparison with the smartvote system, a Web-based Voting Assistance Application (VAA) used to aid voters in finding the party or candidate that is most in line with their preferences, is presented.

Consequences of smoking for body weight, body fat distribution, and insulin resistance

Our aim was to critically evaluate the relations among smoking, body weight, body fat distribution, and insulin resistance as reported in the literature. In the short term, nicotine increases energy expenditure and could reduce appetite, which may explain why smokers tend to have lower body weight than do nonsmokers and why smoking cessation is frequently followed by weight gain. In contrast, heavy smokers tend to have greater body weight than do light smokers or nonsmokers, which likely reflects a clustering of risky behaviors (eg, low degree of physical activity, poor diet, and smoking) that is conducive to weight gain. Other factors, such as weight cycling, could also be involved. In addition, smoking increases insulin resistance and is associated with central fat accumulation. As a result, smoking increases the risk of metabolic syndrome and diabetes, and these factors increase risk of cardiovascular disease. In the context of the worldwide obesity epidemic and a high prevalence of smoking, the greater risk of (central) obesity and insulin resistance among smokers is a matter of major concern

Modelling Breaks and Clusters in the Steady States of Macroeconomic Variables

Macroeconomists working with multivariate models typically face uncertainty over which (if any) of their variables have long run steady states which are subject to breaks. Furthermore, the nature of the break process is often unknown. In this paper, we draw on methods from the Bayesian clustering literature to develop an econometric methodology which: i) finds groups of variables which have the same number of breaks; and ii) determines the nature of the break process within each group. We present an application involving a five-variate steady-state VAR.

Una aproximació d'aprenentatge automàtic per a extracció d'informació adaptativa

Les tècniques de clustering poden ajudar a reduir la supervisió en processos d'obtenció de patrons per a Extracció d'Informació. En aquest treball, que abarca un període de 4 anys de recerca, es comença per estudiar la representació de documents més adequada per a la tasca de clustering. Per tal d'evitar els biaixos dels mètodes individuals de clustering, es consideren mètodes de clustering conjunt. S'exploren diversos mètodes de combinació supervisada, i s'hi afegeixen estratègies automàtiques per a determinar el nombre de clusters de la combinació. També es consideren mecanismes per a obtenir clusterings conjunts ponderats, així com estratègies de combinació no supervisada. Finalment, els resultats del clustering s'utilitzen en un sistema d'adquisició de patrons per a substituir els elements de supervisió humana. Totes aquestes estratègies i mètodes s'avaluen en tasques de clustering de documents i adquisició de patrons usant dades reals. Es comprova que els mots com representació de documents superen altres models per a la tasca de clustering, així com que el clustering conjunt supera les limitacions dels clusterings individuals, i que les estratègies no supervisades d'adquisició de patrons obtenen resultats competitius respecte a les estratègies supervisades.

Clúster creatius en entorns urbans: 22@Bcn i Shoreditch East London

La localització de les empreses de nova economia en zones urbanes, a pesar que el factor distància no sigui important, no deixa de ser considerable pels seus avantatges que els suposa estar situades conjuntament en relació amb les infraestructures, consum, beneficis socioculturals, i facilitat en les transaccions cara a cara. És inevitable que el primer quart del segle vint-i-un estigui lligat a l’economia creativa de forma similar amb que el començament del segle vint estava íntimament lligat a l’economia industrial i la invenció del sistema de producció en massa. La ciutat també va jugar un dels papers més importants per al desenvolupament de “la nova economia industrial” a les albors del segle vint, com ho és la ciutat del coneixement que acull “la nova economia creativa” al segle vint-i-un. És evident que els resultats morfològics, socials, econòmics i urbans són ben diferents en ambdós fenòmens, però l’impacte a les ciutats és molt gran. L’objectiu d’aquest estudi és analitzar els mecanismes d’aglomeració (clustering) d’activitats competitives basades en creació de coneixement i de serveis avançats que estan al darrera de desenvolupaments punters a ciutats com Barcelona, el projecte 22@bcn, i East London, el projecte Shoreditch. L’esforç que han posat les autoritats locals en crear l’entorn apropiat per atreure i crear empreses innovadores, com a motor de desenvolupament d’algunes ciutats modernes europees ha resultat en el sorgiment de nuclis o centres urbans molt dinàmics que suposadament estan preparats i acullen punts de creació de coneixement (“Urban Knowledge Hubs”), amb una demanda i llocs de treball altament qualificats. Aquest és el cas dels projectes de Barcelona (22@bcn) i East London (Shoreditch).

EEG-based functional brain networks: does the network size matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.

Long-term effect of a school-based physical activity program (KISS) on fitness and adiposity in children: a cluster-randomized controlled trial.

BACKGROUND: School-based intervention studies promoting a healthy lifestyle have shown favorable immediate health effects. However, there is a striking paucity on long-term follow-ups. The aim of this study was therefore to assess the 3 yr-follow-up of a cluster-randomized controlled school-based physical activity program over nine month with beneficial immediate effects on body fat, aerobic fitness and physical activity. METHODS AND FINDINGS: Initially, 28 classes from 15 elementary schools in Switzerland were grouped into an intervention (16 classes from 9 schools, n = 297 children) and a control arm (12 classes from 6 schools, n = 205 children) after stratification for grade (1st and 5th graders). Three years after the end of the multi-component physical activity program of nine months including daily physical education (i.e. two additional lessons per week on top of three regular lessons), short physical activity breaks during academic lessons, and daily physical activity homework, 289 (58%) participated in the follow-up. Primary outcome measures included body fat (sum of four skinfolds), aerobic fitness (shuttle run test), physical activity (accelerometry), and quality of life (questionnaires). After adjustment for grade, gender, baseline value and clustering within classes, children in the intervention arm compared with controls had a significantly higher average level of aerobic fitness at follow-up (0.373 z-score units [95%-CI: 0.157 to 0.59, p = 0.001] corresponding to a shift from the 50th to the 65th percentile between baseline and follow-up), while the immediate beneficial effects on the other primary outcomes were not sustained. CONCLUSIONS: Apart from aerobic fitness, beneficial effects seen after one year were not maintained when the intervention was stopped. A continuous intervention seems necessary to maintain overall beneficial health effects as reached at the end of the intervention. TRIAL REGISTRATION: ControlledTrials.com ISRCTN15360785.

Prior selection for panel vector autoregressions

There is a vast literature that specifies Bayesian shrinkage priors for vector autoregressions (VARs) of possibly large dimensions. In this paper I argue that many of these priors are not appropriate for multi-country settings, which motivates me to develop priors for panel VARs (PVARs). The parametric and semi-parametric priors I suggest not only perform valuable shrinkage in large dimensions, but also allow for soft clustering of variables or countries which are homogeneous. I discuss the implications of these new priors for modelling interdependencies and heterogeneities among different countries in a panel VAR setting. Monte Carlo evidence and an empirical forecasting exercise show clear and important gains of the new priors compared to existing popular priors for VARs and PVARs.

Alineamiento múltiple de secuencias con T-Coffee: una aproximación paralela

Las aplicaciones de alineamiento múltiple de secuencias son prototipos de aplicaciones que requieren elevada potencia de cómputo y memoria. Se destacan por la relevancia científica que tienen los resultados que brindan a investigaciones científicas en el campo de la biomedicina, genética y farmacología. Las aplicaciones de alineamiento múltiple tienen la limitante de que no son capaces de procesar miles de secuencias, por lo que se hace necesario crear un modelo para resolver la problemática. Analizando el volumen de datos que se manipulan en el área de las ciencias biológica y la complejidad de los algoritmos de alineamiento de secuencias, la única vía de solución del problema es a través de la utilización de entornos de cómputo paralelos y la computación de altas prestaciones. La investigación realizada por nosotros tiene como objetivo la creación de un modelo paralelo que le permita a los algoritmos de alineamiento múltiple aumentar el número de secuencias a procesar, tratando de mantener la calidad en los resultados para garantizar la precisión científica. El modelo que proponemos emplea como base la clusterización de las secuencias de entrada utilizando criterios biológicos que permiten mantener la calidad de los resultados. Además, el modelo se enfoca en la disminución del tiempo de cómputo y consumo de memoria. Para presentar y validar el modelo utilizamos T-Coffee, como plataforma de desarrollo e investigación. El modelo propuesto pudiera ser aplicado a cualquier otro algoritmo de alineamiento múltiple de secuencias.

Household-based malaria control in a highly endemic area of Africa (Tanzania): determinants of transmission and disease and indicators for monitoring - Kilombero Malaria Project

The Kilombero Malaria Project (KMP) attemps to define opperationally useful indicators of levels of transmission and disease and health system relevant monitoring indicators to evaluate the impact of disease control at the community or health facility level. The KMP is longitudinal community based study (N = 1024) in rural Southern Tanzania, investigating risk factors for malarial morbidity and developing household based malaria control strategies. Biweekly morbidity and bimonthly serological, parasitological and drug consumption surveys are carried out in all study households. Mosquito densities are measured biweekly in 50 sentinel houses by timed light traps. Determinants of transmission and indicators of exposure were not strongly aggregated within households. Subjective morbidity (recalled fever), objective morbidity (elevated body temperature and high parasitaemia) and chloroquine consumption were strongly aggregated within a few households. Nested analysis of anti-NANP40 antibody suggest that only approximately 30% of the titer variance can explained by household clustering and that the largest proportion of antibody titer variability must be explained by non-measured behavioral determinants relating to an individual's level of exposure within a household. Indicators for evaluation and monitoring and outcome measures are described within the context of health service management to describe control measure output in terms of community effectiveness.