Analysis of Contributions to NO2 Ambient Air Quality Levels in Madrid City (Spain) through Modeling. Implications for the Development of Policies and Air Quality Monitoring

As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large cities across Europe, particularly for NO2. Modeling air quality in urban areas is rather complex since observed concentration values are a consequence of the interaction of multiple sources and processes that involve a wide range of spatial and temporal scales. Besides a consistent and robust multi-scale modeling system, comprehensive and flexible emission inventories are needed. This paper discusses the application of the WRF-SMOKE-CMAQ system to the Madrid city (Spain) to assess the contribution of the main emitting sectors in the region. A detailed emission inventory was compiled for this purpose. This inventory relies on bottom-up methods for the most important sources. It is coupled with the regional traffic model and it makes use of an extensive database of industrial, commercial and residential combustion plants. Less relevant sources are downscaled from national or regional inventories. This paper reports the methodology and main results of the source apportionment study performed to understand the origin of pollution (main sectors and geographical areas) and define clear targets for the abatement strategy. Finally the structure of the air quality monitoring is analyzed and discussed to identify options to improve the monitoring strategy not only in the Madrid city but the whole metropolitan area.

Analysis of fire behaviour simulations over Spain with WRF-FIRE

Wildland fire spread and behaviour are complex phenomena owing to both the number of involved physico-chemical factors, and the non-linear relationship between variables. Spain is plagued by forest and brush fires every summer, when the extremely dry weather sets in along with high temperatures. The use of fire behaviour models requires the availability of high resolution environmental and fuel data; in the absence of real data, errors on the simulated fire spread can be compounded to affect the spatial and temporal accuracy of predicted data. The effect of input values on the accuracy of WRF-FIRE simulations was evaluated to assess the capabilities of the new system for wildland fire in accurately forecasting fire behaviour. The results confirm that the use of accurate meteorological data and a custom fuel moisture content model is crucial to obtain precise simulations of fire behaviour.

Who has a repeat abortion? Identifying women at risk of repeated terminations of pregnancy : analysis of routinely collected health care data

Peer reviewed

Knowledge-based analysis of microarray gene expression data by using support vector machines

We introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. We test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, we use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

Minisatellite marker analysis of Trypanosoma brucei: Reconciliation of clonal, panmictic, and epidemic population genetic structures

The African trypanosome, Trypanosoma brucei, has been shown to undergo genetic exchange in the laboratory, but controversy exists as to the role of genetic exchange in natural populations. Much of the analysis to date has been derived from isoenzyme or randomly amplified polymorphic DNA data with parasite material from a range of hosts and geographical locations. These markers fail to distinguish between the human infective (T. b. rhodesiense) and nonhuman infective (T. b. brucei) “subspecies” so that parasites derived from hosts other than humans potentially contain both subspecies. To overcome some of the inherent problems with the use of such markers and diverse populations, we have analyzed a well-defined population from a discrete geographical location (Busoga, Uganda) using three recently described minisatellite markers. The parasites were primarily isolated from humans and cattle with the latter isolates further characterized by their ability to resist lysis by human serum (equivalent to human infectivity). The minisatellite markers show high levels of polymorphism, and from the data obtained we conclude that T. b. rhodesiense is genetically isolated from T. b. brucei and can be unambiguously identified by its multilocus genotype. Analysis of the genotype frequencies in the separated T. b. brucei and T. b. rhodesiense populations shows the former has an epidemic population structure whereas the latter is clonal. This finding suggests that the strong linkage disequilibrium observed in previous analyses, where human and nonhuman infective trypanosomes were not distinguished, results from the treatment of two genetically isolated populations as a single population.

Analysis and interpretation of cost data in randomised controlled trials: review of published studies

Objective To review critically the statistical methods used for health economic evaluations in randomised controlled trials where an estimate of cost is available for each patient in the study.

Analysis of Cell Division and Elongation Underlying the Developmental Acceleration of Root Growth in Arabidopsis thaliana1

To investigate the relation between cell division and expansion in the regulation of organ growth rate, we used Arabidopsis thaliana primary roots grown vertically at 20°C with an elongation rate that increased steadily during the first 14 d after germination. We measured spatial profiles of longitudinal velocity and cell length and calculated parameters of cell expansion and division, including rates of local cell production (cells mm−1 h−1) and cell division (cells cell−1 h−1). Data were obtained for the root cortex and also for the two types of epidermal cell, trichoblasts and atrichoblasts. Accelerating root elongation was caused by an increasingly longer growth zone, while maximal strain rates remained unchanged. The enlargement of the growth zone and, hence, the accelerating root elongation rate, were accompanied by a nearly proportionally increased cell production. This increased production was caused by increasingly numerous dividing cells, whereas their rates of division remained approximately constant. Additionally, the spatial profile of cell division rate was essentially constant. The meristem was longer than generally assumed, extending well into the region where cells elongated rapidly. In the two epidermal cell types, meristem length and cell division rate were both very similar to that of cortical cells, and differences in cell length between the two epidermal cell types originated at the apex of the meristem. These results highlight the importance of controlling the number of dividing cells, both to generate tissues with different cell lengths and to regulate the rate of organ enlargement.

Statistical analysis of shape of objects based on landmark data.

Two objects with homologous landmarks are said to be of the same shape if the configurations of landmarks of one object can be exactly matched with that of the other by translation, rotation/reflection, and scaling. The observations on an object are coordinates of its landmarks with reference to a set of orthogonal coordinate axes in an appropriate dimensional space. The origin, choice of units, and orientation of the coordinate axes with respect to an object may be different from object to object. In such a case, how do we quantify the shape of an object, find the mean and variation of shape in a population of objects, compare the mean shapes in two or more different populations, and discriminate between objects belonging to two or more different shape distributions. We develop some methods that are invariant to translation, rotation, and scaling of the observations on each object and thereby provide generalizations of multivariate methods for shape analysis.

Forensic analysis of buildings affected by mining subsidence based on Differential Interferometry (Part III)

This work presents a forensic analysis of buildings affected by mining subsidence, which is based on deformation data obtained by Differential Interferometry (DInSAR). The proposed test site is La Union village (Murcia, SE Spain) where subsidence was triggered in an industrial area due to the collapse of abandoned underground mining labours occurred in 1998. In the first part of this work the study area was introduced, describing the spatial and temporal evolution of ground subsidence, through the elaboration of a cracks map on the buildings located within the affected area. In the second part, the evolution of the most significant cracks found in the most damaged buildings was monitored using biaxial extensometric units and inclinometers. This article describes the work performed in the third part, where DInSAR processing of satellite radar data, available between 1998 and 2008, has permitted to determine the spatial and temporal evolution of the deformation of all the buildings of the study area in a period when no continuous in situ instrumental data is available. Additionally, the comparison of these results with the forensic data gathered in the 2005–2008 period, reveal that there is a coincidence between damaged buildings, buildings where extensometers register significant movements of cracks, and buildings deformation estimated from radar data. As a result, it has been demonstrated that the integration of DInSAR data into forensic analysis methodologies contributes to improve significantly the assessment of the damages of buildings affected by mining subsidence.

Participation and performance trends in 6-hour ultra-marathoners – a retrospective data analysis of worldwide participation from 1991-2010

Participation trends in 6-hour ultra-marathons held word-wide were investigated to gain basic demographic data on 6-hour ultra-marathoners and where these races took place. Participation trends and the association between nationality and race performance were investigated in all 6-hour races held worldwide between 1991 and 2010. Participation increased linearly in both women and men across years. The annual number of finishes was significantly higher in men than in women (P=0.013). The male-to-female ratio remained stable at ~4 since 1991. Runners in age group 45-49 years showed the largest increase in participation for both men (800 participants in 18 years) and women (208 participants in 16 years). Europe attracted most of the runners from other continents (166 runners), more than all other continents combined (55 runners). European runners also showed the best top ten performances (73±3 km for women and 77±11 km for men), while African (with 65±9 km for men) and South American (54±4 km for women and 65±2 km for men) runners showed the weakest. To summarize, participation in 6-hour ultra-marathons increased across years. Most of the development took place in Europe and in athletes in the age group 45-49 years. Europe also attracted the most diverse field of athletes with runners from all other continents. European runners accounted for the most runners and achieved the best top ten performances.

Subsidence damage assessment of a Gothic church using differential interferometry and field data

The Santas Justa and Rufina Gothic church (fourteenth century) has suffered several physical, mechanical, chemical, and biochemical types of pathologies along its history: rock alveolization, efflorescence, biological activity, and capillary ascent of groundwater. However, during the last two decades, a new phenomenon has seriously affected the church: ground subsidence caused by aquifer overexploitation. Subsidence is a process that affects the whole Vega Baja of the Segura River basin and consists of gradual sinking in the ground surface caused by soil consolidation due to a pore pressure decrease. This phenomenon has been studied by differential synthetic aperture radar interferometry techniques, which illustrate settlements up to 100 mm for the 1993–2009 period for the whole Orihuela city. Although no differential synthetic aperture radar interferometry information is available for the church due to the loss of interferometric coherence, the spatial analysis of nearby deformation combined with fieldwork has advanced the current understanding on the mechanisms that affect the Santas Justa and Rufina church. These results show the potential interest and the limitations of using this remote sensing technique as a complementary tool for the forensic analysis of building structures.