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Objectives: To determine the trend of bacterial resistance of Escherichia coli to Imipenem (IPM) and Meropenem (MEM), by means of a linear regression model, taking the information collected in the bulletins of bacterial resistance generated by the GREBO group of Bogota between 2010 and 2014. Methods/Statistical Analysis: From the information published in newsletters GREBO group between 2010 and 2014, the behavior of E. coli bacterial resistance to antibiotics was analyzed. From this information simple linear regression models using the statistical software Statgraphics XVI were generated. Findings: The generated mathematical models to predict the evolution of antibiotic resistance as a function of time and that were significant are: Resistance IPM * Year = 0.00000208772 (p value 0.0020; adjusted R2 = 92.86%); Resistance MEM = 0.00000149115 * Year (p value 0.0026; adjusted R2 = 91.84%). Application/Improvements: There is a relationship between the values of resistance and over the years, with variable time sufficient to explain the behavior of the resistance of E. coli variable. In 2015 IPM resistance is estimated that this in 0.42% (CI 0.02% - 0.8%) and MEM 0.3% (CI 0.17% - 0.42%).

Abstract Decision-making for sustainable design requires the evaluation of different options considering all sustainability dimensions simultaneously: economic, environmental and social. Each dimension has a specific relative importance, which depends on the process that is being assessed. The determination of the relative importance is not a simple task, principally, during early design stages when detailed information about the process is scarce, and when core decisions affecting the entire design are made. An example of this kind of decisions during early design stages is the selection of the chemical process route, which, once defined, provides the guidelines for the process design. The present study proposes a multi-criteria analysis based methodology to evaluate different chemical process route options under sustainability criteria and to guide the selection among them. The methodology uses normalized indicators to assess each sustainability dimension, and a multi-criteria analysis method (MCDA) to calculate the weights and influences between dimensions. Indicators, dimension weights and influences are integrated into the Sustainable Cumulative Index ( SCI ) that can be used to compare chemical process route options in sustainability terms and to support their selection. The proposed methodology is illustrated through the assessment and selection of a chemical process route to produce ethyl acetate.

Abstract This work describes the nonlinear Thomson effect produced by a transient current source powering a thermoelectric cooler. The electric effect of the capacitive impedance in the semiconductors was considered in the equations as a novelty term that naturally appears by solving the Boltzmann equation to find the mathematical form of the current density. Thus, considering the new term and heath energy balances, a one-dimensional mathematical model for a thermoelectric cooler (TEC) powered by a time-dependent current was developed, finding a new nonlinear Thomson effect in the heath transfer equations. To evaluate the impact of the nonlinear effect on the thermodynamic behavior of the thermoelectric cooler, a continuous, sinusoidal and square-pulse current conditions were simulated. The temperature profile, temporal evolution, and the effective coefficient of performance (COP) were calculated. The results revealed a new thermoelectric heat transfer in addition to the Thomson flow created by virtual junctions throughout the semiconductors caused by the instantaneous change of current. This fact was evidenced by three results: the shifting of the temperature mean value due to the peak current change 0.45 A is 1.68 K 1.68\hspace{0.1667em}\mathrm{K} and 2.56 K 2.56\hspace{0.1667em}\mathrm{K} to sinusoidal and square current supplies, respectively; it was determined that a TEC powered by a square-pulse current signal had greater effective efficacy, having more pronounced cold side supercooling temperature peaks compared to those powered by a constant sinusoidal current signal.

The increasing energy consumption, mostly supplied by fossil fuels, has motivated the research and development of alternative fuel technologies to decrease the humanity’s dependence on fossil fuels, which leads to pollution of natural sources. Small-scale biomass gasification, using air-steam blends for partial oxidation, is a good alternative since biomass is a neutral carbon feedstock for sustainable energy generation. This research presents results obtained from an experimental study on coffee husk (CH) gasification, using air-steam blends for partial oxidation in a 10 kW fixed-bed gasifier. Parametric studies on equivalence ratio (ER) (1.53 < ER < 6.11) and steam-fuel (SF) ratio (0.23 < SF < 0.89) were carried out. The results show that increasing both SF and ER results in a syngas rich in CH4 and H2 but poor in CO. Also, decreased SF and ER decrease the peak temperature (Tpeak) at the gasifier combustion zone. The syngas high heating value (HHV) ranged from 3112 kJ/SATPm3 to 5085 kJ/SATPm3 and its maximum value was obtained at SF = 0.87 and ER = 4.09. The dry basis molar concentrations of the species, produced under those operating conditions (1.53 < ER < 6.11 and 0.23 < SF < 0.89), were between 1.12 and 4.1% for CH4, between 7.77 and 13.49% for CO, and between 7.54 and 19.07% for H2. Other species were in trace amount.

El aumento de la demanda energética, así como de las emisiones contaminantes ha generado un incremento de la investigación de tecnologías que permitan mitigar ambas problemáticas a nivel mundial. Dentro de las alternativas para mejorar la eficiencia de los procesos térmicos, el régimen de combustión sin llama se presenta como una de las alternativas más promisorias, puesto que permite obtener altos valores del rendimiento térmico mediante el mejoramiento de la transferencia de calor y del proceso de combustión, con la consiguiente reducción de las emisiones contaminantes. Debido a esto, en el presente estudio se realiza una revisión del estado del arte de dicha tecnología, haciendo énfasis en los aspectos fenomenológicos asociados, las principales características del régimen y su estabilidad, pasando por los mecanismos de obtención y la presentación de una serie de estudios, tanto a nivel nacional como internacional, en los que se utilizaron combustibles fósiles y alternativos. La revisión finaliza con la discusión de algunos casos en los cuales se ha implementado el régimen a nivel industrial.

Power quality information is useful not only to determine electricity fitness but also for another important application: load identification. One approach to identify loads is through non-intrusive load monitoring systems that estimate the nature and operation of individual appliances with measurements in a single point. In this work, load identification is addressed as a classification task by taking advantage of power quality information. Therefore, discriminant analysis of power quality characteristics are proposed, thus requiring simpler design and fitting processes than traditional techniques. In this regard, classifiers based on linear and quadratic discriminant analysis are implemented for laboratory measurements with noticeable performance.

This paper presents an experimental study carried out in an industrial furnace for frits production using different configurations of burners based on different combustion techniques such as enriched air combustion, flat-flame oxy-combustion and preheater air combustion. The residence time of combustion gases inside the furnace also was modified. Several combustion configurations were tested and its effects on productivity and thermal energy specific consumption and efficiency were determined. The results show that higher residence time of the combustion gases can decrease significantly the specific consumption of fuel, while the change of the burners and combustion techniques did not show significant effects on decreasing the energy consumption. However, it is highlighted that the oxy-combustion flat-flame burners produced the lowest specific consumption of fuel. Even though the experiments were conducted in a furnace for frit production, the corresponding results can also be applied to guide or improve other industrial high temperature processes.

The use of fossil resources for electricity production is one of the primary reasons for increasing greenhouse emissions and is a non-renewable resource. Therefore, the electricity generation by wind and solar resources have had greater applicability in recent years. Hybrid Renewable Energy Systems (HRES) integrates renewable sources and storage systems, increasing the reliability of generators. For the sizing of HRES, Artificial Intelligence (AI) methods such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) stand out. This article presents the sizing of an HRES for the Colombian context, taking into account the energy consumption by three typical demands, four types of wind turbines, three types of solar panels, and a storage system for the system configuration. Two optimization approaches were set-up with both optimization strategies (i.e., GA and PSO). The first one implies the minimization of the Loss Power Supply Probability (LPSP). In contrast, the second one concerns adding the Total Annual Cost (TAC) or the Levelized Cost of Energy (LCOE) to the objective function. Results obtained show that HRES can supply the energy demand, where the PSO method gives configurations that are more adjusted to the considered electricity demands.