Modelling of rheological behaviour of macaíba pulp at different temperatures

ABSTRACT Fruit pulps undergo temperature variations during processing, leading to viscosity changes. This study aimed to analyse the rheological behaviour of macaíba pulp at different temperatures (10 to 50 ºC, with 5 ºC increments) and speeds (2.5 to 200 rpm, totalling 17 speeds). Experimental measurements were performed in a Brookfield viscometer, fitting the Ostwald-de-Waele, Mizrahi-Berk, Herschel-Bulkley, and Casson models to the experimental data of shear stress as a function of shear rate. Among the models used, the Mizrahi-Berk model (R² > 0.9656 and average percentage deviation - P ≤ 4.1%) was found to best fit the rheogram data. Macaíba pulp exhibited a non-newtonian behaviour and was characterised as pseudoplastic. It showed fluid behaviour indexes below unity under the studied conditions, with decreases in apparent viscosity as temperature and shear rate increased. Such behaviour could be described by the Arrhenius equation. The Mizrahi-Berk and Falguera-Ibarz models (R² > 0.99 and P ≤ 10%) best fitted the data and were used to represent the viscosity behaviour of macaíba pulp. The activation energy values of macaíba pulp ranged between 17.53 and 25.37 kJ mol-1, showing a rheological behaviour like other fruit pulps.

Parameter estimate for three-parameter kappa distribution using LHmoments approach

The method of higher-order L-moments (LH-moment) was proposed as a more robust alternative compared to classical L-moments to characterize extreme events. The new derivation will be done for Mielke-Johnson’s Kappa and Three-Parameters Kappa Type-II (K3D-II) distributions based on the LH-moments approach. The data of maximum monthly rainfall for Embong station in Terengganu were used as a case study. The analyses were conducted using the classical L-moments method with η=0 and LH-moments methods with η=1, η=2, η=3 and η=4 for a complete data series and upper parts of the distributions. The most suitable distributions were determined based on the Mean Absolute Deviation Index (MADI), Mean Square Deviation Index (MSDI), and Correlation (r). Also, L-moment and LH-moment ratio diagrams were used to represent visual proofs of the results. The analysis showed that LH-moments methods at a higher order of K3D-II distribution best fit the data of maximum monthly rainfalls for the Embong station for the upper parts of the distribution compared to L-moments. The results also proved that whenever η increases, LH-moments reflect more and more characteristics of the upper part of the distribution. This seems to suggest that LH-moments estimates for the upper part of the distribution events are superior to L-moments in fitting the data of maximum monthly rainfalls.

Best fit probability distribution analysis of precipitation and potential evapotranspiration of India’s highly dense population state - Bihar

Planning of water resources and its management with the ambiguity and non-uniformity accompanying with precipitation and other meteorological physical characteristics may perhaps effect on agricultural production in Bihar where the farmers mostly depend on precipitation. The precipitation and potential evapotranspiration temporal distribution of the state is irregular due to geomorphology, climatic and other anthropogenic factors of the state. In the present study, attempt is taken to expose the best-fit probability distribution among the various available probability distribution of annual average precipitation and potential evapotranspiration based on 102 year of past records of all 37 districts of the state. On the basis of ranks of goodness of fit tests such as Kolmogorov Smirnov, Anderson Darling and Chi-Squared, the normal distribution was observed the best-fit probability distribution for 11 districts followed by Weibull (3P) for 9 districts, the Beta distribution for 5 districts and other distribution for rest districts for precipitation. Whereas Cauchy distribution was come out with the best-fit probability distribution for potential evapotranspiration for all districts and the second best was Gamma (3P) covering almost 60% of the total districts followed by General Extreme Value distribution (32%). The results can be used in future hydraulic design, hydrological study for estimation of return period and water resource planners for policy development.

Spatiotemporal variations in exposure: Chagas disease in Colombia as a case study

Age-stratified serosurvey data are often used to understand spatiotemporal trends in disease incidence and exposure through estimating the Force-of-Infection (FoI). Typically, median or mean FoI estimates are used as the response variable in predictive models, often overlooking the uncertainty in estimated FoI values when fitting models and evaluating their predictive ability. To assess how this uncertainty impact predictions, we compared three approaches with three levels of uncertainty integration. We propose a performance indicator to assess how predictions reflect initial uncertainty.In Colombia, 76 serosurveys (1980–2014) conducted at municipality level provided age-stratified Chagas disease prevalence data. The yearly FoI was estimated at the serosurvey level using a time-varying catalytic model. Environmental, demographic and entomological predictors were used to fit and predict the FoI at municipality level from 1980 to 2010 across Colombia.A stratified bootstrap method was used to fit the models without temporal autocorrelation at the serosurvey level. The predictive ability of each model was evaluated to select the best-fit models within urban, rural and (Amerindian) indigenous settings. Model averaging, with the 10 best-fit models identified, was used to generate predictions.Our analysis shows a risk of overconfidence in model predictions when median estimates of FoI alone are used to fit and evaluate models, failing to account for uncertainty in FoI estimates. Our proposed methodology fully propagates uncertainty in the estimated FoI onto the generated predictions, providing realistic assessments of both central tendency and current uncertainty surrounding exposure to Chagas disease.

A multi-objective algorithm for virtual machine placement in cloud environments using a hybrid of particle swarm optimization and flower pollination optimization

The demand for virtual machine requests has increased recently due to the growing number of users and applications. Therefore, virtual machine placement (VMP) is now critical for the provision of efficient resource management in cloud data centers. The VMP process considers the placement of a set of virtual machines onto a set of physical machines, in accordance with a set of criteria. The optimal solution for multi-objective VMP can be determined by using a fitness function that combines the objectives. This paper proposes a novel model to enhance the performance of the VMP decision-making process. Placement decisions are made based on a fitness function that combines three criteria: placement time, power consumption, and resource wastage. The proposed model aims to satisfy minimum values for the three objectives for placement onto all available physical machines. To optimize the VMP solution, the proposed fitness function was implemented using three optimization algorithms: particle swarm optimization with Lévy flight (PSOLF), flower pollination optimization (FPO), and a proposed hybrid algorithm (HPSOLF-FPO). Each algorithm was tested experimentally. The results of the comparative study between the three algorithms show that the hybrid algorithm has the strongest performance. Moreover, the proposed algorithm was tested against the bin packing best fit strategy. The results show that the proposed algorithm outperforms the best fit strategy in total server utilization.

Morphological and microsatellite DNA diversity of Djallonké sheep in Guinea-Bissau

Background The present study aimed at characterizing the Djallonké Sheep (DS), the only local sheep breed raised in Guinea-Bissau. A total of 200 animals were sampled from four regions (Bafatá, Gabú, Oio and Cacheu) and described using 7 visual criteria and 8 measurements. These parameters have been studied by principal components analysis. The genetic diversity and population structure of 92 unrelated animals were studied using 12 microsatellite markers. Results The values of quantitative characters in the Bafatá region were significantly higher than those obtained in the other three regions. A phenotypic diversity of the DS population was observed and three genetic types distinguished: animals with “large traits” in the region of Bafatá, animals with “intermediate traits” in the regions of Gabú and Oio and animals with “small traits” in the Cacheu region. The hair coat colors are dominated by the white color, the shape of the facial head profile is mainly convex and the ears “erected horizontally”. Most of the morphobiometric characteristics were significantly influenced by the “region” and “sex of animals”. The average Polymorphism Information Content (PIC) of 0.65 ± 0.11 supports the use of markers in genetic characterization. Gabú subpopulation had the highest genetic diversity measures (He = 0.716 ± 0.089) while Cacheu DS subpopulation presented the smallest (He = 0.651 ± 0.157). Only Gabú and Bafatá subpopulations presented significant heterozygote deficiency across all loci indicating possible significant inbreeding. Mean values for FIT,FST, FIS and GST statistics across all loci were 0.09, 0.029, 0.063 and 0.043 respectively. The overall genetic differentiation observed between the four DS subpopulations studied was low. Bafatá and Gabú are the most closely related subpopulations (DS = 0.04, genetic identity = 0.96) while Bafatá and Cacheu were the most genetically distant subpopulations (DS = 0.14, genetic identity = 0.87). Using Bayesian approach, the number of K groups that best fit the data is detected between 2 and 3, which is consistent with the morphological analysis and the factorial analysis of correspondence. Conclusions The molecular results on DS population of Guinea-Bissau confirmed the ones obtained with morphological analysis. The three genetic types observed phenotypically might be due to a combination of the agro-ecological differences and the management of breeding rather than genetic factors.

GA Optimization for Regression Modeling of Electromagnetic Performances Predicted by a Subdomain Model for SMPMSM in an Electric Vehicle

This paper investigates a nonlinear modeling optimization of 12s/8p surface-mounted permanent magnet synchronous machines (SMPMSM) with a radial magnetization pattern. The modeling is based on subdomain model (SDM) computation, where the analytical models are developed to predict the electromagnetic (EM) performances, such as, average EM torque and EM torque ripple in PM machines. A genetic algorithm is applied to the proposed model in order to search for the optimal solutions. The objective function of the optimizations is obtaining a higher average EM torque and achieving the minimum EM torque ripple. The data, viz, and the average EM torque and its ripples predicted by SDM are employed in regression analysis in order to find the model of best fit. After that, the most suitable fit of the computing equation is selected. The preliminary and optimal designs of 12s/8p PM motors are also compared in terms of parameters and motor performance. As a result, the regression model and GA framework has reduced the use of magnet materials and the EM torque ripple of the SMPMSM, making it ideal for use in an electric car. Lastly, the proposed model can determine the appropriate configuration design parameters for SMPMSM in order to achieve the best motor performance.

Appraising Agroecological Urbanism: A Vision for the Future of Sustainable Cities

By the mid-century, urban areas are expected to house two-thirds of the world’s population of approximately 10 billion people. The key challenge will be to provide food for all with fewer farmers in rural areas and limited options for expanding cultivated fields in urban areas, with sustainable soil management being a fundamental criterion for achieving sustainability goals. Understanding how nature works in a fast changing world and fostering nature-based agriculture (such as low-input farming) are crucial for sustaining food systems in the face of worsening urban heat island (UHI) effects and other climatic variables. The best fit for the context is transformative agroecology, which connects ecological networks, sustainable farming approaches, and social movements through change-oriented research and action. Even though agroecology has been practiced for over a century, its potential to address the socioeconomic impact of the food system remained largely unexplored until recently. Agroecological approaches, which involve effective interactions between researchers, policy makers, farmers, and consumers, can improve social cohesion and socioeconomic synergies while reducing the use of various agricultural inputs. This review presents a timeline of agroecology transformation from the past to the present and discusses the possibilities, prospects, and challenges of agroecological urbanism toward a resilient urban future.

Medidas corporales y estimación de peso vivo en bucerros predestete en la provincia de Granma, Cuba

La investigación se realizó en la oriental provincia de Granma, área que destaca por sus resultados científicos relacionados con el comportamiento productivo de la especie bubalina en Cuba. El objetivo fue estimar el peso vivo a través de medidas corporales en bucerros desde el nacimiento hasta los ocho meses de edad. Se registraron datos de 1 302 animales, hembras y machos nacidos de 120 búfalas de la raza Buffalypso en el período 2008 a 2015, las medidas corporales: alto de la cruz (AC), longitud del cuerpo (LC), perímetro torácico (PT), perímetro abdominal (PA), ancho de la pelvis (AP), largo de la pelvis (LP) y ancho del tórax (AT) fueron medidas con cinta métrica en cm. Mientras el peso vivo (PV) fue determinado con plataforma digital, todas las maniobras se hicieron cada 30 días. Los modelos predictivos utilizados fueron: Quetélet, PV = (PT)2 (longitud de cuerpo) (87,5); Crevat, PV= (PT) (Longitud del cuerpo) (PA) (80) y Correa, PV= (PT)2(Longitud del cuerpo)/ 300. Los resultados comparativos por sexo arrojaron diferencias altamente significativas (P<0,001) para el PA y diferencias significativas (P<0,05) para el PT, PV, LP y LC a favor de los machos. EL modelo que mostró mejor ajuste (r2=0,96, P>0,001) combinó tres variables (PT, PA y LC), aunque el perímetro torácico solo mostró parámetros elevados (r2=0,94, P>0,001). Finalmente se concluye que las elevadas correlaciones entre las medidas corporales y el peso vivo, demuestran que las variables estudiadas pueden por si solas o combinadas explicar el comportamiento del peso vivo, pero la ecuación de predicción del PV (kg) a través de PT (cm) propuesta atribuye mayores ventajas para la práctica del pesaje. The research was carried out in the eastern province of Granma, an area that stands out for its scientific results related to the productive behavior of the buffalo species in Cuba. The objective was to estimate live weight through body measurements in calves from birth to eight months of age. Data were recorded on 1 302 animals, females and males born to 120 buffaloes of the Buffalypso breed in the period 2008 to 2015, body measurements: height at the withers (AC), body length (LC), thoracic perimeter (PT) , abdominal perimeter (PA), pelvic width (AP), pelvic length (LP) and chest width (AT) were measured with a tape measure in cm. While the live weight (PV) was determined with a digital platform, all the maneuvers were done every 30 days. The predictive models used were: Quetélet, PV = (PT) 2 (body length) (87.5); Crevat, PV = (PT) (Body length) (PA) (80) and Correa, PV = (PT) 2 (Body length) / 300. The comparative results by sex yielded highly significant differences (P <0.001) for the PA and significant differences (P <0.05) for the PT, PV, LP and LC in favor of males. The model that showed the best fit (r2 = 0.96, P> 0.001) combined three variables (PT, PA and LC), although the thoracic perimeter only showed elevated parameters (r2 = 0.94, P> 0.001). Finally, it is concluded that the high correlations between body measurements and live weight show that the variables studied can, alone or in combination, explain the behavior of live weight, but the prediction equation of LW (kg) through PT (cm ) proposal attributes greater advantages to the practice of weighing.