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A validation of the factorial, Taguchi and response surface methodology (RSM) statistical models is developed for the analysis of mechanical tests of hybrid materials, with an epoxy matrix reinforced with natural Chambira fiber and synthetic fibers of glass, carbon and Kevlar. These materials present variability in their properties, so for the validation of the models a research methodology with a quantitative approach based on the statistical process of the design of experiments (DOE) was adopted; for which the sampling is in relation to the design matrix using 90 treatments with three replicates for each of the study variables. The analysis of the models reveals that the greatest pressure is obtained by considering only the source elements that are significant; this is reflected in the increase in the coefficient of determination and in the predictive capacity. The modified factorial model is best suited for the research, since it has an R2 higher than 90% in almost all the evaluated mechanical properties of the material; with respect to the combined optimization of the variables, the model showed an overall contribution of 99.73% and global desirability of 0.7537. These results highlight the effectiveness of the modified factorial model in the analysis of hybrid materials.

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The solvent-free esterification of the free fatty acids (FFAs) obtained by the hydrolysis of castor oil (a non-edible vegetable oil) with 2-ethyl-1-hexanol (a branched fatty alcohol) was catalyzed by different free lipases. Eversa Transform 2.0 (ETL) features surpassed most commercial lipases. Some process parameters were optimized by the Taguchi method (L16'). As a result, a conversion over 95% of the FFAs of castor oil into esters with lubricants properties was achieved under optimized reaction conditions (15 wt% of biocatalyst content, 1:4 molar ratio (FFAs/alcohol), 30 °C, 180 rpm, 96 h). The substrates molar ratio had the highest influence on the dependent variable (conversion at 24 h). FFAs/2-ethyl-1-hexanol esters were characterized regarding the physicochemical and tribological properties. Interestingly, the modification of the FFAs with 2-ethyl-1-hexanol by ETL increased the oxidative stability of the FFAs feedstock from 0.18 h to 16.83 h. The biolubricants presented a lower friction coefficient than the reference commercial mineral lubricant (0.052 ± 0.07 against 0.078 ± 0.04). Under these conditions, ETL catalyzed the oligomerization of ricinoleic acid (a hydroxyl fatty acid) into estolides, reaching a conversion of 25.15% of the initial FFAs (for the first time).

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Salicylic acid is an intermediate product in the synthesis of dyes, medications and aspirin. An electrodialysis module has been constructed with commercial cationic, anionic and bipolar membranes for the conversion of sodium salicylate into salicylic acid. The effect of operating conditions such as applied electric potential, salt concentration, initial acid concentration and volumetric flow on bipolar membrane electrodialysis (BMED) yields were investigated using Taguchi analysis. The results obtained in 210 min of work show an average concentration of salicylic acid of 0.0185 M, an average electric current efficiency of 85.3%, and a specific energy consumption of 2.24 kWh/kg of salicylic acid. It was concluded that the proposed bipolar membrane electrodialysis process is an efficient alternative to produce salicylic acid (SAH) from sodium salicylate (SANa) in an environmentally friendly manner. Furthermore, the production of sodium hydroxide was obtained as a by-product of the process carried out.

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Agave lechuguilla agro-waste is a promising renewable material for biorefining purposes. The procurement of added-value co-products, such as bioactive phytochemicals, is required to improve bioprocesses and promote the bio-based economy of the productive areas of Mexico. In this study, we aimed to evaluate the effect of post-harvest management and enzymatic pretreatment as the first stages of the A. lechuguilla valorization process. Four drying methods were compared, and enzymatic hydrolysis was optimized to obtain a flavonoid-enriched extract applying ultrasound-assisted extraction. In both experiments, the total phenolic (TPC) and flavonoid (TFC) contents, HPLC-UV flavonoid profiles, and radical scavenging capacity (DPPH) were considered as response variables. The results demonstrated that light exposure during the drying process particularly affected the flavonoid content, whereas oven-dehydration at 40 °C in the dark preserved the flavonoid diversity and antioxidant functionality of the extracts. Flavonoid glycoside recovery, particularly anthocyanidins, was 1.5-1.4-fold enhanced by enzymatic hydrolysis using the commercial mix Ultraflo© under optimized conditions (pH 4, 40 °C, 180 rpm, and 2.5 h) compared to the unpretreated biomass. The extraction of flavonoids from A. lechuguilla bagasse can be carried out using a scalable drying method and enzymatic pretreatment. This study confirmed the potential of this agro-waste as a source of marketable natural products.

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RESUMEN En el presente trabajo se realiza la caracterización del comportamiento ante el desgaste por deslizamiento en seco de un acero inoxidable súper dúplex. Los ensayos fueron desarrollados en un tribómetro tipo bola sobre anillo. Como material del anillo se empleó el acero inoxidable dúplex tipo SAF 2507 sin tratamiento térmico y como material para la bola se usó el acero AISI 52100. Los ensayos se realizaron sin lubricante en condiciones de ambiente (aire), temperatura y humedad estándar de laboratorio. Los parámetros seleccionados, a fin de estudiar sus efectos en el coeficiente desgaste por deslizamiento, fueron: velocidad de deslizamiento (0,9 m/s y 2 m/s), carga normal (9 N, 19 N y 29 N) y distancias de deslizamiento (500 m, 1000 m y 2000 m). Se empleó un diseño experimental de Taguchi con nueve tratamientos y dos réplicas. En la caracterización del acero SAF 2507 se obtuvo valores del coeficiente de desgaste en el intervalo desde 0,19588 x 1012 m2/N hasta 0,72381 x 1012 m2/N, para las condiciones evaluadas. El factor que más afecta el coeficiente de desgaste es la velocidad de deslizamiento. El mecanismo de desgaste identificado para el SAF 2507 es de adhesión y delaminación de alta velocidad.

ABSTRACT In this paper the characterization of the behavior during dry sliding wear of a super duplex stainless steel was performed. The tests were developed in a ball on ring tribometer type. As material of the ring is used the duplex stainless steel type SAF 2507 without heat treatment and as material for the ball is used the steel AISI 52100. Tests were conducted without lubrication in ambient conditions (air), temperature and humidity laboratory standard was used. The parameters selected in order to study its effects on sliding wear coefficient were: sliding speed (0.9 m/s and 2 m/s), normal load (9 N, 19 N and 29 N) and distances slip (500 m, 1000 m and 2000 m). Taguchi experimental design with nine treatments and two replicates was used. In the characterization of steel SAF 2507 wear coefficient values was obtained in the range from 0.19588 x 10-12 m2/N to 0.72381 x 10-12 m2/N, for the conditions tested. The factor that most affects the wear coefficient is the sliding velocity. The wear mechanism identified for the SAF 2507 was adhesion and high speed delamination.

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Microalgae crops targeting biotechnological applications are conducted in photobioreactors, which allow the adjustment and control of parameters of luminosity, agitation and mixing in the cultivation medium to promote better cell growth and accumulation of metabolites. In this sense, the present work used the Taguchi method to find the best adjustment of the operational parameters of an unconventional photobioreactor denominated internally illuminated integrated photobioreactor (ILI-PBR) with LED light aiming at elevating the biomass concentration, volumetric biomass productivity, and volumetric lipid productivity of Chlorella minutissima microalgae cultivated under autotrophic regime. The effects of the factors were evaluated: illumination (blue, white and red); photoperiod (12 h light:12 h dark, 1 h light:1 h dark, and 24 h clear:0 h dark); aeration (0, 3 vvm, 0.4 vvm, and 0.5 vvm); and recirculation flow rate of cultivation medium (5 L min-1, 6.5 L min-1, and 9 L min-1) on the variable responses: biomass concentration, biomass volumetric productivity, lipid content, and volumetric lipid productivity. The use of the Taguchi method allowed the increase of biomass concentration, volumetric biomass productivity, and volumetric lipid productivity in the biomass of Chlorella minutissimain 8.6%, 42%, and 143%, respectively, with the adjustment of the operational parameters of the photobioreactor used.

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Background: Plant tissue cultures have the potential to reprogram the development of microspores from normal gametophytic to sporophytic pathway resulting in the formation of androgenic embryos. The efficiency of this process depends on the genotype, media composition and external conditions. However, this process frequently results in the regeneration of albino instead of green plants. Successful regeneration of green plants is affected by the concentration of copper sulfate (CuSO4) and silver nitrate (AgNO3) and the length of induction step. In this study, we aimed at concurrent optimization of these three factors in barley (Hordeum vulgare L.), wheat (Triticum aestivum L.), and triticale (x Triticosecale spp. Wittmack ex A. Camus 1927) using the Taguchi method. We evaluated uniform donor plants under varying experimental conditions of in vitro anther culture using the Taguchi approach, and verified the optimized conditions. Results: Optimization of the regeneration conditions resulted in an increase in the number of green regenerants compared with the control. Statistic Taguchi method for optimization of the in vitro tissue culture plant regeneration via anther cultures allowed reduction of the number of experimental designs from 27 needed if full factorial analysis is used to 9. With the increase in the number of green regenerants, the number of spontaneous doubled haploids decreased. Moreover, in barley and triticale, the number of albino regenerants was reduced. Conclusion: The statistic Taguchi approach could be successfully used for various factors (here components of induction media, time of incubation on induction media) at a one time, that may impact on cereals anther cultures to improve the regeneration efficiency

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Autism diagnosis requires validated diagnostic tools employed by mental health professionals with expertise in autism spectrum disorders. This conventionally requires lengthy information processing and technical understanding of each of the areas evaluated in the tools. Classifying the impact of these areas and proposing a system that can aid experts in the diagnosis is a complex task. This paper presents the methodology used to find the most significant items from the ADOS-G tool to detect Autism Spectrum Disorders through Feed-forward Artificial Neural Networks with back-propagation training. The number of cases for the network training data was determined by using the Taguchi method with Orthogonal Arrays reducing the sample size from 531,441 to only 27. The trained network provides an accuracy of 100% with 11 different cases used only for validation, which provides a specificity and sensitivity of 1. The network was used to classify the 12 items from the ADOS-G tool algorithm into three levels of impact for Autism diagnosis: High, Medium and Low. It was found that the items "Showing", "Shared enjoyment in Interaction" and "Frequency of vocalization directed to others", are the areas of highest impact for Autism diagnosis. The methodology here presented can be replicated to different Autism diagnosis tests to classify their impact areas as well.

El diagnóstico del autismo requiere del uso de herramientas de diagnóstico validadas internacionalmente que son utilizadas por los profesionales de la salud expertos en trastornos del espectro autista, lo cual requiere de procesamiento de mucha información y un entendimiento técnico de cada una de las áreas evaluadas en ellas. La clasificación del impacto que tienen cada una de estas áreas, así como la propuesta de un sistema que pueda ayudar a los expertos en el diagnóstico, es una tarea compleja, por lo que en este artículo se presenta una metodología utilizada para encontrar los elementos más significativos de la herramienta de diagnóstico de autismo ADOS-G a través de redes neuronales artificiales entrenadas con retropropagación del error. El número de casos para entrenamiento de la red se seleccionó utilizando el método de Taguchi con arreglos ortogonales, reduciendo el tamaño de la muestra de 531,441 a solo 27 casos. La red entrenada tiene una exactitud del 100% validada con 11 casos diferentes de niños evaluados para diagnóstico de trastorno del espectro autista con lo que se obtuvo una especificidad y sensibilidad de 1. La red neuronal artificial se utilizó para clasificar los 12 elementos del algoritmo de la herramienta ADOS-G en tres niveles de impacto: Alto, Medio y Bajo. Se encontró que los elementos "Mostrar", "Placer compartido durante la interacción" y "Frecuencia de vocalizaciones dirigidas a otros" son las áreas de mayor impacto para el diagnóstico de autismo. La metodología presentada puede ser replicada para diferentes herramientas de diagnóstico de autismo para clasificar sus áreas de mayor impacto también.