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Mejia-Teniente L.,CA Ingenieria de Biosistemas | Mejia-Teniente L.,University of Guanajuato | de Jesus Joaquin-Ramos A.,Roque Institute of Technology | Torres-Pacheco I.,CA Ingenieria de Biosistemas | And 4 more authors.
Viruses | Year: 2015

Germin-like proteins (GLPs) are encoded by a family of genes found in all plants, and in terms of function, the GLPs are implicated in the response of plants to biotic and abiotic stresses. CchGLP is a gene encoding a GLP identified in a geminivirus-resistant Capsicum chinense Jacq. accession named BG-3821, and it is important in geminivirus resistance when transferred to susceptible tobacco in transgenic experiments. To characterize the role of this GLP in geminivirus resistance in the original accession from which this gene was identified, this work aimed at demonstrating the possible role of CchGLP in resistance to geminiviruses in Capsicum chinense Jacq. BG-3821. Virus-induced gene silencing studies using a geminiviral vector based in PHYVV component A, displaying that silencing of CchGLP in accession BG-3821, increased susceptibility to geminivirus single and mixed infections. These results suggested that CchGLP is an important factor for geminivirus resistance in C. chinense BG-3821 accession. © 2015 by the authors; licensee MDPI, Basel, Switzerland. Source


Ramirez-Marengo C.,Celaya Institute of Technology | Diaz-Ovalle C.,Roque Institute of Technology | Vazquez-Roman R.,Celaya Institute of Technology | Mannan M.S.,Texas A&M University
Journal of Loss Prevention in the Process Industries | Year: 2015

A stochastic approach for evaluating the risk of vapor cloud explosions is proposed in this work. The proposed methodology aims to incorporate the effect of uncertainty into the risk analysis to produce a better overall view for the risk. Some stochastic variables are used to estimate the probability of vapor cloud explosions: frequency of the release, the probability of not having an immediate ignition, the probability of delayed ignition and the probability of a vapor cloud explosion given a delayed ignition, as well as different possible meteorological conditions. These stochastic variables are represented with probability distribution curves. Different curves for the frequencies of releases from process equipment types (steel process pipes, flanges, manual valves, actuated valves, etc.), different equipment diameters and different leak sizes are also used in this analysis. Monte Carlo simulation is performed to obtain the risk as a probability distribution using the Analytic Solver Platform. Then the risk distribution curve obtained by Monte Carlo simulation is used to estimate the probability of satisfying the risk tolerance criterion. © 2014 Elsevier Ltd. Source


Vazquez-Roman R.,Celaya Institute of Technology | Diaz-Ovalle C.,Roque Institute of Technology | Quiroz-Perez E.,Celaya Institute of Technology | Mannan M.S.,Texas A&M University
Journal of Loss Prevention in the Process Industries | Year: 2016

Accidental gas releases are detected by allocating sensors in optimal places to prevent escalation of the incident. Gas release effects are typically assessed based on calculating the dispersion from releasing points. In this work, a CFD-based approach is proposed to estimate gas dispersion and then to obtain optimal gas sensors allocation. The Ansys-Fluent commercial package is used to estimate concentrations in the open air by solving the governing equations of continuity, momentum, energy and species convection-diffusion combined with the realizable κ-ε model for turbulence viscosity effects. CFD dynamic simulations are carried out for potential gas leaks, assuming worst-case scenarios with F-stability and 2 m/s wind speed during a 4 min releasing period and considering 8 wind directions. The result is a scenario-based methodology to allocate gas sensors supported on fluid dynamics models. The three x-y-z geographical coordinates for the sensor allocation are included in this analysis. To highlight the methodology, a case study considers releases from a large container surrounded by different types of geometric units including sections with high obstacles, low obstacles, and no obstacles. A non-redundant set of perfect sensors are firstly allocated to cover completely the detection for all simulations releases. The benefits of redundant detection via a MooN voting arranging scheme is also discussed. Numerical results demonstrate the capabilities of CFD simulations for this application and highlight the dispersion effects through obstacles with different sizes. © 2016 Elsevier Ltd. Source


Ordonez-Baquera P.L.,Autonomous University of Chihuahua | Gonzalez-Rodriguez E.,Autonomous University of Chihuahua | Aguado-Santacruz G.A.,Roque Institute of Technology | Rascon-Cruz Q.,Autonomous University of Chihuahua | Burrola-Barraza E.,Autonomous University of Chihuahua
Revista Mexicana De Ciencias Pecuarias | Year: 2016

Bouteloua gracilis is a grass native to Mexico, it is used as forage source for livestock because of its high nutritional value. It has high tolerance to osmotic stress and therefore can live in arid zones; however, regulation mechanisms in gene expression that confer these characteristics have not been reported. There is a class of small RNAs (sRNAs) called microRNAs (miRNAs), which regulate gene expression. They are complementary and act by binding to messenger RNAs (mRNAs to inhibit translation or by degrading them. In this work, the isolation of sRNAs from B. gracilis through cloning and sequencing of concatemers is reported. In silico analysis of the sequences obtained allowed to identify conserved sequences in Populus trichocarpa, Brachypodium distachyon, Oryza sativa, Sorghum bicolor, Zea mays, Malus domestica, and Linum usitatissimum. Furthermore, the secondary structure of the miRNA precursor (premiRNA) was predicted from two sequences isolated from In silico analysis using Glycine max, Zea mays, Sorghum bicolor, and Oryza sativa as reference genomes. Finally, six target mRNAs were identified for one of the miRNAs obtained. Identification of miRNAs in Bouteloua gracilis will help to understand how these molecules regulate gene expression and in the future will allow for the study at molecular level, providing insight on how this grass responds to environmental stress. Source


Lopez-Molina A.,Celaya Institute of Technology | Vazquez-Roman R.,Celaya Institute of Technology | Diaz-Ovalle C.,Roque Institute of Technology
Informacion Tecnologica | Year: 2012

The Dow fire and explosion index and the quantitative risk assessment methodology are applied to analyze one of the most unfortunate accidents in Mexican history: the explosion of gas storage tanks at the San Juan Ixhuatepec plant in Mexico. Additional calculations of over-pressure and thermal radiation are carried out to further explain the domino effect produced as a consequence of the accident. The results give evidence that facilities in San Juan Ixhuatepec had a moderate risk level which is in disagreement with people's perception of the Pemex company, proprietary of the plant. This study concludes that the accident was mainly due to human error, as well as the inappropriate location of the plant. Source

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