Air Traffic Control: A Local Approach to the Trajectory Segmentation Issue

Proceedings of: 23rd International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA-AIE 2010) Córdoba-Spain, June 04-06, 2010This paper presents a new approach for trajectory segmentation in the area of Air Traffic Control, as a basic tool for offline validation with recorded opportunity traffic data. Our approach uses local information to classify each measurement individually, constructing the final segments over these classified samples as the final solution of the process. This local classification is based on a domain transformation using motion models to identify the deviations at a local scale, as an alternative to other global approaches based on combinatorial analysis over the trajectory segmentation domain.This work was supported in part by Projects CICYT TIN2008-06742-C02-02/TSI, CICYT TEC2008-06732-C02-02/TEC, CAM CONTEXTS (S2009/TIC-1485) and DPS2008-07029-C02-02.Publicad

Evolution of motif variants and positional bias of the cyclic-AMP response element

BACKGROUND: Transcription factors regulate gene expression by interacting with their specific DNA binding sites. Some transcription factors, particularly those involved in transcription initiation, always bind close to transcription start sites (TSS). Others have no such preference and are functional on sites even tens of thousands of base pairs (bp) away from the TSS. The Cyclic-AMP response element (CRE) binding protein (CREB) binds preferentially to a palindromic sequence (TGACGTCA), known as the canonical CRE, and also to other CRE variants. CREB can activate transcription at CREs thousands of bp away from the TSS, but in mammals CREs are found far more frequently within 1 to 150 bp upstream of the TSS than in any other region. This property is termed positional bias. The strength of CREB binding to DNA is dependent on the sequence of the CRE motif. The central CpG dinucleotide in the canonical CRE (TGACGTCA) is critical for strong binding of CREB dimers. Methylation of the cytosine in the CpG can inhibit binding of CREB. Deamination of the methylated cytosines causes a C to T transition, resulting in a functional, but lower affinity CRE variant, TGATGTCA. RESULTS: We performed genome-wide surveys of CREs in a number of species (from worm to human) and showed that only vertebrates exhibited a CRE positional bias. We performed pair-wise comparisons of human CREs with orthologous sequences in mouse, rat and dog genomes and found that canonical and TGATGTCA variant CREs are highly conserved in mammals. However, when orthologous sequences differ, canonical CREs in human are most frequently TGATGTCA in the other species and vice-versa. We have identified 207 human CREs showing such differences. CONCLUSION: Our data suggest that the positional bias of CREs likely evolved after the separation of urochordata and vertebrata. Although many canonical CREs are conserved among mammals, there are a number of orthologous genes that have canonical CREs in one species but the TGATGTCA variant in another. These differences are likely due to deamination of the methylated cytosines in the CpG and may contribute to differential transcriptional regulation among orthologous genes

Self-Assembled Molecular-Electronic Films Controlled by Room Temperature Quantum Interference

If single-molecule, room-temperature, quantum interference (QI) effects could be translated into massively parallel arrays of molecules located between planar electrodes, QI-controlled molecular transistors would become available as building blocks for future electronic devices. Here, we demonstrate unequivocal signatures of room-temperature QI in vertical tunneling transistors, formed from self-assembled monolayers (SAMs), with stable room-temperature switching operations. As a result of constructive QI effects, the conductances of the junctions formed from anthanthrene-based molecules with two different connectivities differ by a factor of 34, which can further increase to 173 by controlling the molecule-electrode interface with different terminal groups. Field-effect control is achieved using an ionic liquid gate, whose strong vertical electric field penetrates through the graphene layer and tunes the energy levels of the SAMs. The resulting room-temperature on-off current ratio of the lowest-conductance SAMs can reach up to 306, about one order of magnitude higher than that of the highest-conductance SAMs

Impact of stoichiometry representation on simulation of genotype-phenotype relationships in metabolic networks.

<div><p>Genome-scale metabolic networks provide a comprehensive structural framework for modeling genotype-phenotype relationships through flux simulations. The solution space for the metabolic flux state of the cell is typically very large and optimization-based approaches are often necessary for predicting the active metabolic state under specific environmental conditions. The objective function to be used in such optimization algorithms is directly linked with the biological hypothesis underlying the model and therefore it is one of the most relevant parameters for successful modeling. Although linear combination of selected fluxes is widely used for formulating metabolic objective functions, we show that the resulting optimization problem is sensitive towards stoichiometry representation of the metabolic network. This undesirable sensitivity leads to different simulation results when using numerically different but biochemically equivalent stoichiometry representations and thereby makes biological interpretation intrinsically subjective and ambiguous. We hereby propose a new method, Minimization of Metabolites Balance (MiMBl), which decouples the artifacts of stoichiometry representation from the formulation of the desired objective functions, by casting objective functions using metabolite turnovers rather than fluxes. By simulating perturbed metabolic networks, we demonstrate that the use of stoichiometry representation independent algorithms is fundamental for unambiguously linking modeling results with biological interpretation. For example, MiMBl allowed us to expand the scope of metabolic modeling in elucidating the mechanistic basis of several genetic interactions in <em>Saccharomyces cerevisiae</em>.</p> </div

All-inkjet-printed thin-film transistors: manufacturing process reliability by root cause analysis

We report on the detailed electrical investigation of all-inkjet-printed thin-film transistor (TFT) arrays focusing on TFT failures and their origins. The TFT arrays were manufactured on flexible polymer substrates in ambient condition without the need for cleanroom environment or inert atmosphere and at a maximum temperature of 150 degrees C. Alternative manufacturing processes for electronic devices such as inkjet printing suffer from lower accuracy compared to traditional microelectronic manufacturing methods. Furthermore, usually printing methods do not allow the manufacturing of electronic devices with high yield (high number of functional devices). In general, the manufacturing yield is much lower compared to the established conventional manufacturing methods based on lithography. Thus, the focus of this contribution is set on a comprehensive analysis of defective TFTs printed by inkjet technology. Based on root cause analysis, we present the defects by developing failure categories and discuss the reasons for the defects. This procedure identifies failure origins and allows the optimization of the manufacturing resulting finally to a yield improvement

P-hydroxyphenylpyruvate, an intermediate of the Phe/Tyr catabolism, improves mitochondrial oxidative metabolism under stressing conditions and prolongs survival in rats subjected to profound hemorrhagic shock

The aim of this study was to test the effect of a small volume administration of p-hydroxyphenylpyruvate (pHPP) in a rat model of profound hemorrhagic shock and to assess a possible metabolic mechanism of action of the compound. The results obtained show that hemorrhaged rats treated with 2-4% of the estimated blood volume of pHPP survived significantly longer (p<0.001) than rats treated with vehicle. In vitro analysis on cultured EA.hy 926 cells demonstrated that pHPP improved cell growth rate and promoted cell survival under stressing conditions. Moreover, pHPP stimulated mitochondria-related respiration under ATP-synthesizing conditions and exhibited antioxidant activity toward mitochondria-generated reactive oxygen species. The compound effects reported in the in vitro and in vivo analyses were obtained in the same millimolar concentration range. These data disclose pHPP as an efficient energetic substrates-supplier to the mitochondrial respiratory chain as well as an antioxidant supporting the view that the compound warrants further evaluation as a therapeutic agent. © 2014 Cotoia et al

Growth landscape formed by perception and import of glucose in yeast

An important challenge in systems biology is to quantitatively describe microbial growth using a few measurable parameters that capture the essence of this complex phenomenon. Two key events at the cell membrane—extracellular glucose sensing and uptake—initiate the budding yeast’s growth on glucose. However, conventional growth models focus almost exclusively on glucose uptake. Here we present results from growth-rate experiments that cannot be explained by focusing on glucose uptake alone. By imposing a glucose uptake rate independent of the sensed extracellular glucose level, we show that despite increasing both the sensed glucose concentration and uptake rate, the cell’s growth rate can decrease or even approach zero. We resolve this puzzle by showing that the interaction between glucose perception and import, not their individual actions, determines the central features of growth, and characterize this interaction using a quantitative model. Disrupting this interaction by knocking out two key glucose sensors significantly changes the cell’s growth rate, yet uptake rates are unchanged. This is due to a decrease in burden that glucose perception places on the cells. Our work shows that glucose perception and import are separate and pivotal modules of yeast growth, the interaction of which can be precisely tuned and measured.National Institutes of Health (U.S.). Pioneer AwardNatural Sciences and Engineering Research Council of Canada (NSERC). Graduate Fellowshi

Mining biological information from 3D short time-series gene expression data: the OPTricluster algorithm

<p>Abstract</p> <p>Background</p> <p>Nowadays, it is possible to collect expression levels of a set of genes from a set of biological samples during a series of time points. Such data have three dimensions: gene-sample-time (GST). Thus they are called 3D microarray gene expression data. To take advantage of the 3D data collected, and to fully understand the biological knowledge hidden in the GST data, novel subspace clustering algorithms have to be developed to effectively address the biological problem in the corresponding space.</p> <p>Results</p> <p>We developed a subspace clustering algorithm called Order Preserving Triclustering (OPTricluster), for 3D short time-series data mining. OPTricluster is able to identify 3D clusters with coherent evolution from a given 3D dataset using a combinatorial approach on the sample dimension, and the order preserving (OP) concept on the time dimension. The fusion of the two methodologies allows one to study similarities and differences between samples in terms of their temporal expression profile. OPTricluster has been successfully applied to four case studies: immune response in mice infected by malaria (<it>Plasmodium chabaudi</it>), systemic acquired resistance in <it>Arabidopsis thaliana</it>, similarities and differences between inner and outer cotyledon in <it>Brassica napus </it>during seed development, and to <it>Brassica napus </it>whole seed development. These studies showed that OPTricluster is robust to noise and is able to detect the similarities and differences between biological samples.</p> <p>Conclusions</p> <p>Our analysis showed that OPTricluster generally outperforms other well known clustering algorithms such as the TRICLUSTER, gTRICLUSTER and K-means; it is robust to noise and can effectively mine the biological knowledge hidden in the 3D short time-series gene expression data.</p

On plexus representation of dissimilarities

Correspondence analysis has found widespread application in analysing vegetation gradients. However, it is not clear how it is robust to situations where structures other than a simple gradient exist. The introduction of instrumental variables in canonical correspondence analysis does not avoid these difficulties. In this paper I propose to examine some simple methods based on the notion of the plexus (sensu McIntosh) where graphs or networks are used to display some of the structure of the data so that an informed choice of models is possible. I showthat two different classes of plexus model are available. These classes are distinguished by the use in one case of a global Euclidean model to obtain well-separated pair decomposition (WSPD) of a set of points which implicitly involves all dissimilarities, while in the other a Riemannian view is taken and emphasis is placed locally, i.e., on small dissimilarities. I showan example of each of these classes applied to vegetation data