Crude oil aggregation by microscopy and dynamic light scattering

This research is focused on establishing a methodology to evaluate the aggregation state of Mexican crude oil solutions from two different sources and SARA compositions, by using Dynamic Light Scattering (DLS). Different crude oil concentrations were established and monitored through time in order to determine their effects on the aggregation state. DLS results indicate that the aggregation state of the studied solutions is influenced by crude oil composition, specifically by the amount of resins. Particle size and elemental analysis of the aggregates were performed by Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDX), respectively. Results from these techniques reveal particulated low-porosity smooth surfaces due to the presence of resin, as well as the determination of the characteristic elements found in asphaltenes. High-Resolution Transmission Electron Microscopy (HTEM) indicated the presence of asphaltene aggregates constituted by nanometric particles and asphaltene stacking as well as ultrafine nanocrystalline-oriented structures.     

Impact of N on the atomic-scale Sb distribution in quaternary GaAsSbN-capped InAs quantum dots

The use of GaAsSbN capping layers on InAs/GaAs quantum dots (QDs) has recently been proposed for micro- and optoelectronic applications for their ability to independently tailor electron and hole confinement potentials. However, there is a lack of knowledge about the structural and compositional changes associated with the process of simultaneous Sb and N incorporation. In the present work, we have characterized using transmission electron microscopy techniques the effects of adding N in the GaAsSb/InAs/GaAs QD system. Firstly, strain maps of the regions away from the InAs QDs had revealed a huge reduction of the strain fields with the N incorporation but a higher inhomogeneity, which points to a composition modulation enhancement with the presence of Sb-rich and Sb-poor regions in the range of a few nanometers. On the other hand, the average strain in the QDs and surroundings is also similar in both cases. It could be explained by the accumulation of Sb above the QDs, compensating the tensile strain induced by the N incorporation together with an In-Ga intermixing inhibition. Indeed, compositional maps of column resolution from aberration-corrected Z-contrast images confirmed that the addition of N enhances the preferential deposition of Sb above the InAs QD, giving rise to an undulation of the growth front. As an outcome, the strong redshift in the photoluminescence spectrum of the GaAsSbN sample cannot be attributed only to the N-related reduction of the conduction band offset but also to an enhancement of the effect of Sb on the QD band structure.     

Hydroxyapatite growth on cotton fibers modified chemically

We have prepared carboxymethyl cellulose fibers (CMC) by chemically modifying cotton cellulose with monochloroacetic acid and calcium chloride solution. This modification favored the growth of hydroxyapatite (HAP) on the surface of the CMC fibers in contact with simulated body fluid solutions (SBF). After soaking in SBF for periods of 7, 14 and 21 days, formation of HAP was observed. Analysis by scanning electron microscopy and X-ray diffraction showed that crystallinity, crystallite size, and growth of HAP increased with the soaking time. The amount of HAP deposited on CMC fibers increased greatly after 21 days of immersion in the SBF, while the substrate surface was totally covered with hemispherical aggregates with the size of the order of 2 microns. Elemental analysis showed the presence of calcium and phosphate, with calcium/phosphate atomic ratio of 1.54. Fourier transform infrared spectroscopy bands confirmed the presence of HAP. The results suggest that cotton modified by calcium treatment has a nucleating ability and can accelerate the nucleation of HAP crystals.     

Modification of appetite by bread consumption: A systematic review of randomized controlled trials

The inclusion of different ingredients or the use of different baking technologies may modify the satiety response to bread, and aid in the control of food intake. The aim of this study was to perform a systematic search of randomized clinical trials on the effect of bread consumption on appetite ratings in humans. The search equation was (“Bread”[MeSH]) AND (“Satiation”[MeSH] OR “Satiety response”[MeSH]), and the filter “clinical trials.” As a result of this procedure, 37 publications were selected. The satiety response was considered as the primary outcome. The studies were classified as follows: breads differing in their flour composition, breads differing in ingredients other than flours, breads with added organic acids, or breads made using different baking technologies. In addition, we have revised the data related to the influence of bread on glycemic index, insulinemic index and postprandial gastrointestinal hormones responses. The inclusion of appropriate ingredients such as fiber, proteins, legumes, seaweeds and acids into breads and the use of specific technologies may result in the development of healthier breads that increase satiety and satiation, which may aid in the control of weight gain and benefit postprandial glycemia. However, more well-designed randomized control trials are required to reach final conclusions.     

Viscosity virtual sensor to control combustion in fossil fuel power plants

Thermo-electrical power plants utilize fossil fuel oil to transform the calorific power of fuel into electric power. An optimal combustion in the boiler requires the fuel oil to be in its best conditions. One of fuel's most important properties to consider is viscosity. Viscosity has influence on the optimal combustion between fuel and air. Hardware viscosity meters for fuel oils are expensive and unreliable to operate in power plant conditions. Chemical laboratory measures viscosity accurately with special apparatus, but they cannot be used in a real time process. This paper describes the development of a virtual sensor that estimates fuel oil viscosity in the combustion process of a power plant. A virtual sensor or soft sensor is a computer program that estimates the value of a certain variable based on related measurements and a model of the process where the variable participates. In this project, a probabilistic model is constructed using automatic learning algorithms with historical data and experts' advice. The learning and validation experiments are described and discussed. The virtual sensor is installed in the Tuxpan Power Plant in Veracruz, Mexico.     

Environmental and individual exposure to secondhand aerosol of electronic cigarettes in confined spaces: Results from the TackSHS Project†

Secondhand electronic cigarette (e-cigarette) aerosol (SHA) might impair indoor air quality and expose bystanders. This study aims to investigate exposure to SHA in controlled conditions of enclosed settings simulating real-world scenario. An experiment was performed in a car and in a room, in which SHA was generated during a 30-minute ad libitum use of an e-cigarette. The experiment was replicated on five consecutive days in each setting. We measured PM_2.5, airborne nicotine concentrations, and biomarkers of exposure to SHA, such as nicotine metabolites, tobacco-specific nitrosamines, propylene glycol, and glycerol in bystanders’ saliva samples before, during, and after the exposure period. Self-reported health symptoms related to exposure to SHA were also recorded. The results showed that the highest median PM_2.5 concentration was recorded during the exposure period, being 21 µg/m³ in the room setting and 16 µg/m³ in the car setting—about twofold increase compared to the baseline. Most concentrations of the airborne nicotine and all biomarkers were below the limit of quantification in both settings. Bystanders in both settings experienced some short-term irritation symptoms, expressed as dry throat, nose, eyes, and phlegm. In conclusion, short-term use of an e-cigarette in confined spaces increased indoor PM_2.5 level and caused some irritation symptoms in bystanders.     

STATISTICAL LINGUISTIC LAWS IN ECOLOGICAL MODELS

This paper gives the theoretical setup so that an ecological model, as a particular mathematical model, can be considered a text written in a formal language (mathematics), and therefore, statistical linguistic laws can be applied to obtain information parameters in different semantic levels of the same model. The statistical laws will be useful to: a) compare semantic levels, submodels, and different models mutually; b) prove that information temperature parameter is an indirect measure of meaning: the significance or semantic component of information, opposed to significant, or comprehension, on the part of the observer (modeller) of the model text. We will apply these ideas in two practical examples.