Effect of a general school-based physical activity intervention on bone mineral content and density: A cluster-randomized controlled trial.

Background: Specific physical loading leads to enhanced bone development during childhood. A general physical activity program mimicking a real-life situation was successful at increasing general physical health in children. Yet, it is not clear whether it can equally increase bone mineral mass. We performed a cluster-randomized controlled trial in children of both gender and different pubertal stages to determine whether a school-based physical activity (PA) program during one school-year influences bone mineral content (BMC) and density (BMD), irrespective of gender.Methods: Twenty-eight 1st and 5th grade (6-7 and 11-12 year-old) classes were cluster randomized to an intervention (INT, 16 classes, n = 297) and control (CON; 12 classes, n = 205) group. The intervention consisted of a multi-component PA intervention including daily physical education with at least 10 min of jumping or strength training exercises of various intensities. Measurements included anthropometry, and BMC and BMD of total body, femoral neck, total hip and lumbar spine using dual-energy X-ray absorptiometry (DXA). PA was assessed by accelerometers and Tanner stages by questionnaires. Analyses were performed by a regression model adjusted for gender, baseline height and weight, baseline PA, post-intervention pubertal stage, baseline BMC, and cluster.Results: 275 (72%) of 380 children who initially agreed to have DXA measurements had also post-intervention DXA and PA data. Mean age of prepubertal and pubertal children at baseline was 8.7 +/- 2.1 and 11.1 +/- 0.6 years, respectively. Compared to CON, children in INT showed statistically significant increases in BMC of total body, femoral neck, and lumbar spine by 5.5%, 5.4% and 4.7% (all p < 0.05), respectively, and BMD of total body and lumbar spine by 8.4% and 7.3% (both p < 0.01), respectively. There was no gender*group, but a pubertal stage*group interaction consistently favoring prepubertal children.Conclusion: A general school-based PA intervention can increase bone health in elementary school children of both genders, particularly before puberty. (C) 2010 Elsevier Inc. All rights reserved.

Cluster recognition in spatial-temporal sequences: The case of forest fires

Forest fire sequences can be modelled as a stochastic point process where events are characterized by their spatial locations and occurrence in time. Cluster analysis permits the detection of the space/time pattern distribution of forest fires. These analyses are useful to assist fire-managers in identifying risk areas, implementing preventive measures and conducting strategies for an efficient distribution of the firefighting resources. This paper aims to identify hot spots in forest fire sequences by means of the space-time scan statistics permutation model (STSSP) and a geographical information system (GIS) for data and results visualization. The scan statistical methodology uses a scanning window, which moves across space and time, detecting local excesses of events in specific areas over a certain period of time. Finally, the statistical significance of each cluster is evaluated through Monte Carlo hypothesis testing. The case study is the forest fires registered by the Forest Service in Canton Ticino (Switzerland) from 1969 to 2008. This dataset consists of geo-referenced single events including the location of the ignition points and additional information. The data were aggregated into three sub-periods (considering important preventive legal dispositions) and two main ignition-causes (lightning and anthropogenic causes). Results revealed that forest fire events in Ticino are mainly clustered in the southern region where most of the population is settled. Our analysis uncovered local hot spots arising from extemporaneous arson activities. Results regarding the naturally-caused fires (lightning fires) disclosed two clusters detected in the northern mountainous area.

Community cluster of meningococcal disease by Neisseria meningitidis serogroup C in Andalusia, Spain, March to May 2011.

Between March and May of 2011, a cluster of three fatal cases of meningococcal sepsis occurred in Andalusia, Spain, in a municipality with a population of around 20,000 inhabitants. The cases were in their mid-teens to early thirties and were notified to the epidemiological surveillance system of Andalusia (Sistema de Vigilancia Epidemiológica de Andalucía, SVEA) during a 68-day period from March through May 2011. All three were infected with the same strain of Neisseria meningitidis serogroup C genosubtype VR1:5-1;VR2:10-8. None of the cases had been previously vaccinated against N. meningitidis serogroup C. Antibiotic post-exposure chemoprophylaxis was administered to close contacts of every diagnosed case. Once the cluster was confirmed, the local population was informed through the media about the control measures taken by the health authorities. The vaccination history against N. meningitidis serogroup C of the population under 25 years-old in the municipality was checked. Vaccination was offered to unimmunised individuals younger than 25 years of age and an additional dose of vaccine was offered to those who had been vaccinated between 2000 and 2006 with a vaccination schedule of three doses before the first year of age. No further cases occurred since the beginning of these actions.

Comparison of topography- and aperture-dependent motion compensation algorithms for airborne SAR

This letter presents a comparison between threeFourier-based motion compensation (MoCo) algorithms forairborne synthetic aperture radar (SAR) systems. These algorithmscircumvent the limitations of conventional MoCo, namelythe assumption of a reference height and the beam-center approximation.All these approaches rely on the inherent time–frequencyrelation in SAR systems but exploit it differently, with the consequentdifferences in accuracy and computational burden. Aftera brief overview of the three approaches, the performance ofeach algorithm is analyzed with respect to azimuthal topographyaccommodation, angle accommodation, and maximum frequencyof track deviations with which the algorithm can cope. Also, ananalysis on the computational complexity is presented. Quantitativeresults are shown using real data acquired by the ExperimentalSAR system of the German Aerospace Center (DLR).

Using free data mining software and clustering algorithms to find predictors from student qualifications

In this project a research both in finding predictors via clustering techniques and in reviewing the Data Mining free software is achieved. The research is based in a case of study, from where additionally to the KDD free software used by the scientific community; a new free tool for pre-processing the data is presented. The predictors are intended for the e-learning domain as the data from where these predictors have to be inferred are student qualifications from different e-learning environments. Through our case of study not only clustering algorithms are tested but also additional goals are proposed.

Forest fires cluster detection with space-time scan statistics

Forest fires are defined as uncontrolled fires often occurring in wildland areas, but that can also affect houses or agricultural resources. Causes are both natural (e.g.,lightning phenomena) and anthropogenic (human negligence or arsons).Major environmental factors influencing the fire ignition and propagation are climate and vegetation. Wildfires are most common and severe during drought period and on windy days. Moreover, under water-stress conditions, which occur after a long hot and dry period, the vegetation is more vulnerable to fire. These conditions are common in the United State and Canada, where forest fires represent a big problem. We focused our analysis on the state of Florida, for which a big dataset on forest fires detection is readily available. USDA Forest Service Remote Sensing Application Center, in collaboration with NASA-Goddard Space Flight Center and the University of Maryland, has compiled daily MODIS Thermal Anomalies (fires and biomass burning images) produced by NASA using a contextual algorithm that exploits the strong emission of mid-infrared radiation from fires. Fire classes were converted in GIS format: daily MODIS fire detections are provided as the centroids of the 1 kilometer pixels and compiled into daily Arc/INFO point coverage.

Identificació de paisatges funcionals mitjançant anàlisi cluster

El terme paisatge i les seves aplicacions són cada dia més utilitzats per les administracions i altres entitats com a eina de gestió del territori. Aprofitant la gran quantitat de dades en bases compatibles amb SIG (Sistemes d’Informació Geogràfica) existents a Catalunya s’ha desenvolupat una síntesi cartogràfica on s’identifiquen els Paisatges Funcionals (PF) de Catalunya, concepte que fa referència al comportament fisico-ecològic del terreny a partir de variables topogràfiques i climàtiques convenientment transformades i agregades. S’ha utilitzat un mètode semiautomàtic i iteratiu de classificació no supervisada (clustering) que permet la creació d’una llegenda jeràrquica o nivells de generalització. S’ha obtingut com a resultat el Mapa de Paisatges Funcionals de Catalunya (MPFC) amb una llegenda de 26 categories de paisatges i 5 nivells de generalització amb una resolució espacial de 180 m. Paral·lelament, s’han realitzat validacions indirectes sobre el mapa obtingut a partir dels coneixements naturalistes i la cartografia existent, així com també d’un mapa d’incertesa (aplicant lògica difusa) que aporten informació de la fiabilitat de la classificació realitzada. Els Paisatges Funcionals obtinguts permeten relacionar zones de condicions topo-climàtiques homogènies i dividir el territori en zones caracteritzades ambientalment i no políticament amb la intenció que sigui d’utilitat a l’hora de millorar la gestió dels recursos naturals i la planificació d’actuacions humanes.

Oxidative stress enhances the expression of sulfur assimilation genes: preliminary insights on the Enterococcus faecalis iron-sulfur cluster machinery regulation

The Firmicutes bacteria participate extensively in virulence and pathological processes. Enterococcus faecalis is a commensal microorganism; however, it is also a pathogenic bacterium mainly associated with nosocomial infections in immunocompromised patients. Iron-sulfur [Fe-S] clusters are inorganic prosthetic groups involved in diverse biological processes, whose in vivo formation requires several specific protein machineries. Escherichia coli is one of the most frequently studied microorganisms regarding [Fe-S] cluster biogenesis and encodes the iron-sulfur cluster and sulfur assimilation systems. In Firmicutes species, a unique operon composed of the sufCDSUB genes is responsible for [Fe-S] cluster biogenesis. The aim of this study was to investigate the potential of the E. faecalis sufCDSUB system in the [Fe-S] cluster assembly using oxidative stress and iron depletion as adverse growth conditions. Quantitative real-time polymerase chain reaction demonstrated, for the first time, that Gram-positive bacteria possess an OxyR component responsive to oxidative stress conditions, as fully described for E. coli models. Likewise, strong expression of the sufCDSUB genes was observed in low concentrations of hydrogen peroxide, indicating that the lowest concentration of oxygen free radicals inside cells, known to be highly damaging to [Fe-S] clusters, is sufficient to trigger the transcriptional machinery for prompt replacement of [Fe-S] clusters.

Multicast algorithms evaluation using an adaptative routing in ATM networks

This paper proposes a multicast implementation based on adaptive routing with anticipated calculation. Three different cost measures for a point-to-multipoint connection: bandwidth cost, connection establishment cost and switching cost can be considered. The application of the method based on pre-evaluated routing tables makes possible the reduction of bandwidth cost and connection establishment cost individually

New perspectives in the use of ink evidence in forensic science: Part II. Development and testing of mathematical algorithms for the automatic comparison of ink samples analysed by HPTLC

In the first part of this research, three stages were stated for a program to increase the information extracted from ink evidence and maximise its usefulness to the criminal and civil justice system. These stages are (a) develop a standard methodology for analysing ink samples by high-performance thin layer chromatography (HPTLC) in reproducible way, when ink samples are analysed at different time, locations and by different examiners; (b) compare automatically and objectively ink samples; and (c) define and evaluate theoretical framework for the use of ink evidence in forensic context. This report focuses on the second of the three stages. Using the calibration and acquisition process described in the previous report, mathematical algorithms are proposed to automatically and objectively compare ink samples. The performances of these algorithms are systematically studied for various chemical and forensic conditions using standard performance tests commonly used in biometrics studies. The results show that different algorithms are best suited for different tasks. Finally, this report demonstrates how modern analytical and computer technology can be used in the field of ink examination and how tools developed and successfully applied in other fields of forensic science can help maximising its impact within the field of questioned documents.

Decision Support Methods for Global Optomization

Immobile location-allocation (LA) problems is a type of LA problem that consists in determining the service each facility should offer in order to optimize some criterion (like the global demand), given the positions of the facilities and the customers. Due to the complexity of the problem, i.e. it is a combinatorial problem (where is the number of possible services and the number of facilities) with a non-convex search space with several sub-optimums, traditional methods cannot be applied directly to optimize this problem. Thus we proposed the use of clustering analysis to convert the initial problem into several smaller sub-problems. By this way, we presented and analyzed the suitability of some clustering methods to partition the commented LA problem. Then we explored the use of some metaheuristic techniques such as genetic algorithms, simulated annealing or cuckoo search in order to solve the sub-problems after the clustering analysis

Implementation of zonal control algorithms in adaptive optical systems with sparse control matrices

Miralls deformables més i més grans, amb cada cop més actuadors estan sent utilitzats actualment en aplicacions d'òptica adaptativa. El control dels miralls amb centenars d'actuadors és un tema de gran interès, ja que les tècniques de control clàssiques basades en la seudoinversa de la matriu de control del sistema es tornen massa lentes quan es tracta de matrius de dimensions tan grans. En aquesta tesi doctoral es proposa un mètode per l'acceleració i la paral.lelitzacó dels algoritmes de control d'aquests miralls, a través de l'aplicació d'una tècnica de control basada en la reducció a zero del components més petits de la matriu de control (sparsification), seguida de l'optimització de l'ordenació dels accionadors de comandament atenent d'acord a la forma de la matriu, i finalment de la seva posterior divisió en petits blocs tridiagonals. Aquests blocs són molt més petits i més fàcils de fer servir en els càlculs, el que permet velocitats de càlcul molt superiors per l'eliminació dels components nuls en la matriu de control. A més, aquest enfocament permet la paral.lelització del càlcul, donant una com0onent de velocitat addicional al sistema. Fins i tot sense paral. lelització, s'ha obtingut un augment de gairebé un 40% de la velocitat de convergència dels miralls amb només 37 actuadors, mitjançant la tècnica proposada. Per validar això, s'ha implementat un muntatge experimental nou complet , que inclou un modulador de fase programable per a la generació de turbulència mitjançant pantalles de fase, i s'ha desenvolupat un model complert del bucle de control per investigar el rendiment de l'algorisme proposat. Els resultats, tant en la simulació com experimentalment, mostren l'equivalència total en els valors de desviació després de la compensació dels diferents tipus d'aberracions per als diferents algoritmes utilitzats, encara que el mètode proposat aquí permet una càrrega computacional molt menor. El procediment s'espera que sigui molt exitós quan s'aplica a miralls molt grans.

Solving Large Location-Allocation problems by Clustering and Simulated Annealing

Globalization involves several facility location problems that need to be handled at large scale. Location Allocation (LA) is a combinatorial problem in which the distance among points in the data space matter. Precisely, taking advantage of the distance property of the domain we exploit the capability of clustering techniques to partition the data space in order to convert an initial large LA problem into several simpler LA problems. Particularly, our motivation problem involves a huge geographical area that can be partitioned under overall conditions. We present different types of clustering techniques and then we perform a cluster analysis over our dataset in order to partition it. After that, we solve the LA problem applying simulated annealing algorithm to the clustered and non-clustered data in order to work out how profitable is the clustering and which of the presented methods is the most suitable