Size distribution of polycyclic aromatic hydrocarbons in a roadway tunnel in Lisbon, Portugal

Atmospheric aerosols of four aerodynamic size ranges were collected using high volume cascade impactors in an extremely busy roadway tunnel in Lisbon (Portugal). Dust deposited on the tunnel walls and guardrails was also collected. Average particle mass concentrations in the tunnel atmosphere were more than 30 times higher than in the outside urban background air, revealing its origins almost exclusively from fresh vehicle emissions. Most of the aerosol mass was concentrated in submicrometer fractions (65%), and polycyclic aromatic hydrocarbons (PAH) were even more concentrated in the finer particles with an average of 84% of total PAH present in sizes smaller than 0.49 mu m. The most abundant PAH were methylated phenanthrenes, fluoranthene and pyrene. About 46% of the total PAH mass was attributed to lower molecular weight compounds (two and three rings), suggesting a strong influence of diesel vehicle emissions on the production of local particulate PAH. The application of diagnostic ratios confirmed the relevance of this source of PAH in the tunnel ambient air. Deposited dust presented PAH profiles similar to the coarser aerosol size range, in agreement with the predominant origin of coarser aerosol particles from soil dust resuspension and vehicle wear products. (c) 201 1 Elsevier Ltd. All rights reserved.

Arrow Plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on samples subgroups

Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

Size-segregated chemical composition of aerosol emissions in an urban road tunnel in Portugal

An atmospheric aerosol study was performed in 2008 inside an urban road tunnel, in Lisbon, Portugal. Using a high volume impactor, the aerosol was collected into four size fractions (PM0.5, PM0.5-1, PM1-2.5 and PM2.5-10) and analysed for particle mass (PM), organic and elemental carbon (OC and EC), polycyclic aromatic hydrocarbons (PAH), soluble inorganic ions and elemental composition. Three main groups of compounds were discriminated in the tunnel aerosol: carbonaceous, soil component and vehicle mechanical wear. Measurements indicate that Cu can be a good tracer for wear emissions of road traffic. Cu levels correlate strongly with Fe, Mn, Sn and Cr, showing a highly linear constant ratio in all size ranges, suggesting a unique origin through sizes. Ratios of Cu with other elements can be used to source apportion the trace elements present in urban atmospheres, mainly on what concerns coarse aerosol particles. (C) 2013 Elsevier Ltd. All rights reserved.

Longitudinal versus polar wrinkling of core-shell fibers with anisotropic size mismatches

We consider a fiber made of a soft elastic material, encased in a stiff elastic shell (core-shell geometry). If the core and shell dimensions are mismatched, e.g., because the core shrinks while the shell does not, but the two remain attached, then an elastic instability is triggered whereby wrinkles may appear on the shell. The wrinkle orientation may be longitudinal (along the fiber axis), polar (along the fiber perimeter), or a mixture of both, depending on the fiber's geometrical and material parameters. Here we investigate under what conditions longitudinal or polar wrinkling will occur.

Arrow plot and CA maps on microarray preprocessing methods

Microarray allow to monitoring simultaneously thousands of genes, where the abundance of the transcripts under a same experimental condition at the same time can be quantified. Among various available array technologies, double channel cDNA microarray experiments have arisen in numerous technical protocols associated to genomic studies, which is the focus of this work. Microarray experiments involve many steps and each one can affect the quality of raw data. Background correction and normalization are preprocessing techniques to clean and correct the raw data when undesirable fluctuations arise from technical factors. Several recent studies showed that there is no preprocessing strategy that outperforms others in all circumstances and thus it seems difficult to provide general recommendations. In this work, it is proposed to use exploratory techniques to visualize the effects of preprocessing methods on statistical analysis of cancer two-channel microarray data sets, where the cancer types (classes) are known. For selecting differential expressed genes the arrow plot was used and the graph of profiles resultant from the correspondence analysis for visualizing the results. It was used 6 background methods and 6 normalization methods, performing 36 pre-processing methods and it was analyzed in a published cDNA microarray database (Liver) available at http://genome-www5.stanford.edu/ which microarrays were already classified by cancer type. All statistical analyses were performed using the R statistical software.

On the choice of posittioning and cluster size for fixed relay stations in a LTE network

The long term evolution (LTE) is one of the latest standards in the mobile communications market. To achieve its performance, LTE networks use several techniques, such as multi-carrier technique, multiple-input-multiple-output and cooperative communications. Inside cooperative communications, this paper focuses on the fixed relaying technique, presenting a way for determining the best position to deploy the relay station (RS), from a set of empirical good solutions, and also to quantify the associated performance gain using different cluster size configurations. The best RS position was obtained through realistic simulations, which set it as the middle of the cell's circumference arc. Additionally, it also confirmed that network's performance is improved when the number of RSs is increased. It was possible to conclude that, for each deployed RS, the percentage of area served by an RS increases about 10 %. Furthermore, the mean data rate in the cell has been increased by approximately 60 % through the use of RSs. Finally, a given scenario with a larger number of RSs, can experience the same performance as an equivalent scenario without RSs, but with higher reuse distance. This conduces to a compromise solution between RS installation and cluster size, in order to maximize capacity, as well as performance.