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Control charts for autocorrelated processes under parameter estimationStatistical Processes Monitoring is a collection of statistical-based methodologies and methods for monitoring the quality of manufactured products or services. Within these tools, control charts are powerful ones to assist practitioners on the detection of departures from in-control situations as long as the assumptions made on their design are fulfilled; otherwise, their power might decrease. For instance, control charts performance has been shown to be negatively affected when using estimated parameters (in which case the Average Run Length, ARL, becomes a random variable) or when dealing with autocorrelated data. Given that, this research is focused on the effect of parameter estimation on the performance of the X-bar and the modified S^2 control charts for monitoring the mean and the variance, respectively, of autocorrelated processes under parameter estimation. The average of the ARL and its standard deviation are considered as performance measures as they take into account the sampling variability of the ARL. Furthermore, a bootstrapping methodology is applied to adjust control limits in order to have a guaranteed conditional in-control performance with a certain probability and the effect on the out-of-control ARL is also studied.
Effects of sound on growth, viability, protein production yield and gene expression in Escherichia coli.The effect of sound on biological systems is a subject that has been previously explored, mainly in relation to its use to increase agricultural production. However, the potential of this phenomenon has not been exploited properly because present studies have focused only on one or two sound elements for the characterization of their biological effects. In this sense, the effects of other sound wave elements have been overlooked. In the present work, the effects of frequency, amplitude, duration, intermittence and pulse - individually and in combination - were characterized in Escherichia coli through the measurement of its biomass, viability and yield production of recombinant protein. The treatments of frequency and duration increased the concentration of biomass in 19% and 44% respectively at time 24 h; however, high variability was observed in both treatments. The amplitude treatment had a significant effect on the viability, which the duration of the exponential phase was doubled. The intermittency treatment increased the yield of recombinant protein 1.5 times without significant contribution of the other sound elements. Based on this observation, the effect that intermittency could have on the upregulation of the expression of genes involved in the production of recombinant proteins was investigated. The RNA of three candidate genes (BarA, CheA and CpxR) was quantified in the presence of an intermittent sound. All genes were upregulated (1.38, 2.66 and 1.33 times respectively); however, only upregulation related to chemotaxis (CheA) was statistically significant. Finally, an omnidirectional sound source was adapted to small-volume commercial bioreactors to characterize the distribution of sound within the container. It was determined that the implementation of sound induction in a commercial bioreactor is feasible, although limited to certain specific frequencies close to 500 and 1000 Hz. The integral nature of this characterization presents a deeper understanding of bacterial systems and also offers a way through which it is possible to explore its application for industrial purposes.
Characterization of the skin secretions of Dryophytes arenicolor and identification of Arenin, a novel Kunitz-like polypeptideZootherapy is the treatment of human ailments with remedies made from animals and their products. Despite its prevalence in the traditional medical practices worldwide, research on this phenomenon has often been neglected in comparison to medicinal plant research. Amphibian skin secretions are enriched with complex cocktails of bioactive molecules such as proteins, peptides, biogenic amines, alkaloids, guanidine derivatives, steroids and other minor components spanning a wide spectrum of pharmacological actions exploited for centuries in folk medicine. This study presents evidence on the protein profile of the skin secretions of the canyon tree frog, Dryophytes arenicolor, an anuran from the Hylidae family, previously described as an ingredient used in Mexican Traditional Medicine practices. At the same time, it presents the reverse-phase liquid chromatography isolation, mass spectrometry characterization, identification at mRNA level and 3D modelling of a novel 58 amino acids Kunitz-like polypeptide from the skin secretions of D. arenicolor, arenin. To evaluate the bioactivity potential of arenin, cell viability assays were performed on HDFa, Caco-2 and MCF7 cells cultured with different concentrations of arenin. At 2 µg/mL of arenin, HDFa and Caco-2 cells showed a viability of 52.1%±2.86 and 108.8%±4.86, respectively. A viability shift was observed at 4 µg/mL of arenin, since HDFa and Caco-2 cells showed a viability of 100.74%±2.60 and 62.77%±1.69. This viability alternance continued being observed at 8 and 16 µg/mL of arenin, suggesting a multi-target interaction in an hormetic-like fashion. This work demonstrates the lack of typical 12-50 amino acid long peptides in the skin secretions of D. arenicolor and proposes that arenin, one of its major constituents, plays a key role in its defense against predators. The hormetic response produced by arenin in cell proliferation assays requires further transcriptomic, metabolomic and proteomic research to unveil the mechanisms underlying the variable effect on cell viability observed at different concentrations of arenin.
Optimization of distribution networks using evolutionary algorithmsOne of the biggest problems that a distribution network (DN) must face is the constant increase in load demand, which eventually will cause the degradation of its optimal operation. To overcome these challenges the distribution network usually is oversized or reinforced, however, although this is a quick and practical solution, it is not necessarily the most economical and efficient one. For this reason, it is desirable to implement an optimization algorithm to improve the network without increasing investment costs. The optimization of a power distribution network is not an easy task, because this is the most extensive part of the entire electrical system. Due to this extension, along with the high complexity of the topology, and some quality parameters that must be respected, the entire design or improvement of a distribution network can be considered as an extremely hard combinatorial, non-convex, and non-linear optimization problem, difficult to solve by conventional methods. For these reasons, we propose a Two-Stage Multiobjective Evolutionary Approach (TS-MOEAP) capable to design and optimize distribution networks, at primary and secondary levels. Due to the complexity of the optimization problem, the approach is implemented in two stages, that can be summarized as follows: Stage-1. Optimal placement and sizing of generation units, as well as optimal branch routing and conductor sizing. For this purpose, an Improved Particle Swarm Optimization technique (IPSO) combined with a greedy algorithm is introduced. Stage-2. Optimal network reconfiguration. For this, an Improved Nondominated Sorting Genetic Algorithm with a Heuristic Mutation Operator (INSGA-HO) is presented, aiming at minimizing the total power loss and investment cost of the system. Finally, to complement the optimization process, the software DER-CAM will be used to find optimal investment solutions for Distributed Energy Resources (DER). Both algorithms are successfully applied to design and optimize real distribution networks that presented several problems, concluding that the combination of these approaches -network reconfiguration with optimal installation of DERs- can converge toward better configurations than other algorithms.
Emotional Domotics: acquisition of an equation for the correlation of emotional states and environmental variables through the facial expressions analysis of the userThe emotional domotics that is a concept developed by our research team seeks to integrate the subject or user of an inhabitable space as central element for the modulation and control of the environmental variables in a house automation implementation. This research proposed working with an influence on the subject emotional and physiological state, presenting an approach to state the subjects analysis when the light hue, temperature, and humidity are varied. The first experimental results led to the finding of the emotional response time dynamics. Such dynamics were important for further design and implementation of the control loops in-house automation systems for emotion modulation. Throughout this document, the details and progress of the research in emotional domotics, with the aim of developing a controlled algorithm for living space based on the user’s emotional state, will be illustrated and detailed. This project is centered on domotics (home automation) systems, which is, a set of elements installed, interconnected and controlled by a computer system. After introducing the investigation’s core, general preview, and the experiment´s description conducted with light hue variation. After the first experiments that led to the emotional response time dynamics. further research was developed in order to acquire and communicate the control system and to process and recover the physiological variables. The final sections of the work present a final experiment in which together the variables of temperature, humidity, and light intensity were applied to a more complete testing methodology. Which led to the final correlation equations for each of five basic emotions selected. These equations may allow us to propose an initial plant model for a control system to be developed by future researchers.