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A bioassay containing Kluyveromyces marxianus in microtiter plates was used to determine the inhibitory action of 28 antibiotics (aminoglycosides, beta-lactams, macrolides, quinolones, tetracyclines and sulfonamides) against this yeast in whey. For this purpose, the dose-response curve for each antibiotic was constructed using 16 replicates of 12 different concentrations of the antibiotic. The plates were incubated at 40°C until the negative samples exhibited their indicator (5-7h). Subsequently, the absorbances of the yeast cells in each plate were measured by the turbidimetric method (λ=600nm) and the logistic regression model was applied. The concentrations causing 10% (IC10) and 50% (IC50) of growth inhibition of the yeast were calculated. The results allowed to conclude that whey contaminated with cephalosporins, quinolones and tetracyclines at levels close to the Maximum Residue Limits inhibits the growth of K. marxianus. Therefore, previous inactivation treatments should be implemented in order to re-use this contaminated whey by fermentation with K. marxianus.

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The COVID-19 pandemic has caused widespread infections, deaths, and substantial economic losses. Vaccine development efforts have led to authorized candidates reducing hospitalizations and mortality, although variant emergence remains a concern. Peru faced a significant impact due to healthcare deficiencies. This study employed logistic regression to mathematically model COVID-19's dynamics in Peru over three years and assessed the correlations between cases, deaths, and people vaccinated. We estimated the critical time (tc) for cases (627 days), deaths (389 days), and people vaccinated (268 days), which led to the maximum speed values on those days. Negative correlations were identified between people vaccinated and cases (-0.40) and between people vaccinated and deaths (-0.75), suggesting reciprocal relationships between those pairs of variables. In addition, Granger causality tests determined that the vaccinated population dynamics can be used to forecast the behavior of deaths (p-value < 0.05), evidencing the impact of vaccinations against COVID-19. Also, the coefficient of determination (R2) indicated a robust representation of the real data. Using the Peruvian context as an example case, the logistic model's projections of cases, deaths, and vaccinations provide crucial insights into the pandemic, guiding public health tactics and reaffirming the essential role of vaccinations and resource distribution for an effective fight against COVID-19.

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Extracting practical information from the large amounts of data gathered during the live imaging analysis of plant organs is a challenging issue. The present work investigates the use of the logistic growth model to analyze experimental data from root elongation assays performed in milli-fluidic devices with in situ imaging. Lactuca sativa was used as a bioindicator and was subjected to wide concentration ranges of four different herbicides: 2,4-D, atrazine, glyphosate, and paraquat. The model parameters were directly connected to standard indicators of toxicity and plant development, such as the LD50 and the absolute growth rate, respectively. In addition, it was found that realistic predictions of the maximum root length can be achieved about 60 h before the bioassay end point, which could significantly shorten the turnaround time. The combination of milli-fluidic devices, real-time imaging, and model-based data analysis becomes a powerful tool for environmental studies and ecotoxicity testing.

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Resumen Introducción: la teoría del caos se usa para explicación de fenómenos complejos, cuya naturaleza no responde a comportamientos lineales y que a su vez no permite determinar con exactitud medidas y cálculos, pero que a pesar de ello se han logrado avances significativos en la ciencia, pudiéndose expandir además hasta las explicaciones de fenómenos sociales, siendo en este caso la violencia. Materiales y Métodos: se emplearon expresiones matemáticas para validar un modelo de realidad que describa aproximadamente índices de violencia a partir de datos reales. Resultados: se obtuvieron relaciones matemáticas que describen el comportamiento caótico, las cuales dependiendo de la tasa de violencia define si el valor tiende a cero, a un valor constante o un comportamiento caótico. Conclusiones: se obtuvo una relación matemática que describe el comportamiento entrópico de la violencia en sociedad, cuya tendencia caótica describe aproximadamente índices de violencia reales.

Abstract Introduction: chaos theory is used to explain complex phenomena, whose nature does not respond to linear behavior and which in turn does not allow exact measurements and calculations to be determined, but despite this, significant advances have been made in science, being able to also expand to the explanations of social phenomena, in this case being violence. Materials and Methods: mathematical expressions are used to validate the reality, which describes rates of violence from real data in Colombia. Results: mathematical relationships describing chaotic behavior were obtained, which, depending on the rate of violence, define whether the value tends to zero, a constant value or chaotic behavior. Conclusions: a mathematical relationship was obtained that describes the entropic behavior of violence in society, whose chaotic trend approximately describes real violence values.

Resumo Introdução: a teoria do caos é utilizada para explicar fenômenos complexos, cuja natureza não responde ao comportamento linear e que por sua vez não permite determinar medidas e cálculos exatos, mas apesar disso, avanços significativos foram feitos na ciência, expandindo para as explicações de fenômenos sociais, neste caso a violência. Materiais e Métodos: foram utilizadas expressões matemáticas para validar um modelo de realidade que descreve aproximadamente as taxas de violência a partir de dados reais. Resultados: foram obtidas relações matemáticas que descrevem o comportamento caótico, que, dependendo da taxa de violência, definem-se o valor que tende a zero, um valor constante ou um comportamento caótico. Conclusões: obteve-se uma relação matemática que descreve o comportamento entrópico da violência na sociedade, cuja tendência caótica descreve de forma aproximada os índices reais de violência.

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Symptoms-based models for predicting SARS-CoV-2 infection may improve clinical decision-making and be an alternative to resource allocation in under-resourced settings. In this study we aimed to test a model based on symptoms to predict a positive test result for SARS-CoV-2 infection during the COVID-19 pandemic using logistic regression and a machine-learning approach, in Bogotá, Colombia. Participants from the CoVIDA project were included. A logistic regression using the model was chosen based on biological plausibility and the Akaike Information criterion. Also, we performed an analysis using machine learning with random forest, support vector machine, and extreme gradient boosting. The study included 58,577 participants with a positivity rate of 5.7%. The logistic regression showed that anosmia (aOR = 7.76, 95% CI [6.19, 9.73]), fever (aOR = 4.29, 95% CI [3.07, 6.02]), headache (aOR = 3.29, 95% CI [1.78, 6.07]), dry cough (aOR = 2.96, 95% CI [2.44, 3.58]), and fatigue (aOR = 1.93, 95% CI [1.57, 2.93]) were independently associated with SARS-CoV-2 infection. Our final model had an area under the curve of 0.73. The symptoms-based model correctly identified over 85% of participants. This model can be used to prioritize resource allocation related to COVID-19 diagnosis, to decide on early isolation, and contact-tracing strategies in individuals with a high probability of infection before receiving a confirmatory test result. This strategy has public health and clinical decision-making significance in low- and middle-income settings like Latin America.

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Resumen El objetivo de este trabajo es aportar nuevas evidencias de calidad psicométrica para la adaptación argentina de la versión reducida del Cuestionario de Personalidad de Eysenck (EPQ-RS). Participaron 1136 personas de población general (52.5% femenino, edad media = 29.6 años, DE = 11.9) residentes en Buenos Aires, Argentina. La adaptación argentina se compone de 42 ítems con formato de respuesta dicotómica. Se realizó un análisis factorial confirmatorio a partir de la matriz de correlaciones tetracóricas. Esto permitió replicar la estructura propuesta por Eysenck para el modelo PEN (Psicoticismo-Extraversión-Neuroticismo) y la escala Sinceridad. Posteriormente, se ajustó el modelo logístico de dos parámetros por separado para los ítems de cada escala. Los ítems no mostraron funcionamiento diferencial según género. La discriminación de los ítems resultó moderada-alta. Los parámetros b se localizaron en rangos acotados de cada uno de los rasgos medidos, lo que originó que la precisión de las escalas varíe en el recorrido de los continuos. La escala Neuroticismo aporta más información en niveles medios del rasgo, Psicoticismo en los medio-bajos y Extraversión en los medio-altos. La escala Sinceridad mostró una función de información relativamente plana en todo el recorrido del rasgo. Se brindan evidencias de validez basadas en la relación con otras pruebas que miden facetas del neuroticismo y sintomatología. Las evidencias de validez y confiabilidad obtenidas ofrecen garantías de calidad suficientes para la aplicación de este instrumento en el contexto local y confirman la vigencia del modelo teórico que operacionaliza el EPQ-RS.

Abstract The aim of this work is to provide new evidence of psychometric quality for the Argentinean adaptation of the brief version of the Eysenck Personality Questionnaire (EPQ-RS). 1136 people from the general population (52.5% female, mean age = 29.6 years, SD = 11.9) residing in Buenos Aires, Argentina participated. The Argentinean adaptation consists of 42 items with dichotomous response format. A confirmatory factor analysis was performed from the tetrachoric correlation matrix. This allowed replicating the structure proposed by Eysenck for the PEN model (Psychoticism - Extroversion - Neuroticism) and the Lie scale. Subsequently, the two-parameter logistic model was adjusted separately for the items of each scale. The items did not show differential functioning by gender. Items discrimination was moderate-high. Parameters b were located in narrow ranges of each one of the measured traits, which caused the precision of the scales to vary along the trait continuums. The Neuroticism scale provides more information at medium levels of the trait, Psychoticism in the medium-low and Extraversion in the medium-high. The Lie scale showed a relatively flat information function throughout the trait. Evidence of validity based on the relationship with other tests that measure facets of neuroticism and symptomatology is provided. The evidence of validity and reliability obtained offers sufficient quality guarantees for the application of this instrument in the local context and confirms topicality of the theoretical model that operationalizes the EPQ-RS.

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Between June 2018 and April 2019, a sampling campaign was carried out to collect PM2.5, monitoring meteorological parameters and anthropogenic events in the Sartenejas Valley, Venezuela. We develop a logistic model for PM2.5 exceedances (≥ 12.5 µg m-3). Source appointment was done using elemental composition and morphology of PM by scanning electron microscopy coupled with energy dispersive spectroscopy (SEM-EDS). A proposal of an early warning system (EWS) for PM pollution episodes is presented. The logistic model has a holistic success rate of 94%, with forest fires and motor vehicle flows as significant variables. Source appointment analysis by occurrence of events showed that samples with higher concentrations of PM had carbon-rich particles and traces of K associated with biomass burning, as well as aluminosilicates and metallic elements associated with resuspension of soil dust by motor-vehicles. Quantitative source appointment analysis showed that soil dust, garbage burning/marine aerosols and wildfires are three majority sources of PM. An EWS for PM pollution episodes around the Sartenejas Valley is proposed considering the variables and elements mentioned.

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Abstract Introduction: Coronary artery bypass grafting (CABG) performed with and without cardiopulmonary bypass (CPB) support has been widely discussed in the literature. However, little is known about the outcomes of those techniques in Brazil. This study aims at exploring 30-day mortality and morbidity outcomes of on- and off-pump isolated CABG in a large sample from Southern Brazil. Methods: A single-center cohort with 1,767 patients undergoing isolated CABG (January 2013 - December 2018) was initially evaluated. Patients undergoing off-pump (N=397) and on-pump (N=1,370) CABG were identified. To obtain two completely homogeneous study groups, propensity score matching was used. The paired groups were compared by descriptive and univariate analyses. Then, logistic regression was used to verify the effects of on- and off-pump CABG on 30-day mortality. Results: None of the baseline characteristics showed significant difference between the groups (P>0.05). None of the analyzed morbidity outcomes showed any difference between the groups, including acute myocardial infarction (3.0% vs. 1.5%; P=0.192), stroke (2.4% vs. 4.2%; P=0.193), and major reoperation (0.6% vs. 0.3%; P=1.000), as well as the major adverse cardiovascular and cerebrovascular events composite outcome (6.3% vs. 7.5%; P=0.541). Mortality also did not differ (1.5% vs. 2.4%; P=0.401), and CPB support was not an independent predictor of risk for 30-day mortality (odds ratio: 2.052; 95% confidence interval: 0,609-6.913; P=0.246). Conclusion: After matching by propensity analyses, similar rates of on- and off-pump 30-day mortality and other major outcomes were observed. In addition, the use of CPB support was not an independent predictor of risk for the occurrence of 30-day mortality.

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INTRODUCTION: Coronary artery bypass grafting (CABG) performed with and without cardiopulmonary bypass (CPB) support has been widely discussed in the literature. However, little is known about the outcomes of those techniques in Brazil. This study aims at exploring 30-day mortality and morbidity outcomes of on- and off-pump isolated CABG in a large sample from Southern Brazil. METHODS: A single-center cohort with 1,767 patients undergoing isolated CABG (January 2013 - December 2018) was initially evaluated. Patients undergoing off-pump (N=397) and on-pump (N=1,370) CABG were identified. To obtain two completely homogeneous study groups, propensity score matching was used. The paired groups were compared by descriptive and univariate analyses. Then, logistic regression was used to verify the effects of on- and off-pump CABG on 30-day mortality. RESULTS: None of the baseline characteristics showed significant difference between the groups (P>0.05). None of the analyzed morbidity outcomes showed any difference between the groups, including acute myocardial infarction (3.0% vs. 1.5%; P=0.192), stroke (2.4% vs. 4.2%; P=0.193), and major reoperation (0.6% vs. 0.3%; P=1.000), as well as the major adverse cardiovascular and cerebrovascular events composite outcome (6.3% vs. 7.5%; P=0.541). Mortality also did not differ (1.5% vs. 2.4%; P=0.401), and CPB support was not an independent predictor of risk for 30-day mortality (odds ratio: 2.052; 95% confidence interval: 0,609-6.913; P=0.246). CONCLUSION: After matching by propensity analyses, similar rates of on- and off-pump 30-day mortality and other major outcomes were observed. In addition, the use of CPB support was not an independent predictor of risk for the occurrence of 30-day mortality.

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With advancements in medical treatments for cancer, an increase in the life expectancy of patients undergoing new treatments is expected. Consequently, the field of statistics has evolved to present increasingly flexible models to explain such results better. In this paper, we present a lung cancer dataset with some covariates that exhibit nonproportional hazards (NPHs). Besides, the presence of long-term survivors is observed in subgroups. The proposed modeling is based on the generalized time-dependent logistic model with each subgroup's effect time and a random term effect (frailty). In practice, essential covariates are not observed for several reasons. In this context, frailty models are useful in modeling to quantify the amount of unobservable heterogeneity. The frailty distribution adopted was the weighted Lindley distribution, which has several interesting properties, such as the Laplace transform function on closed form, flexibility in the probability density function, among others. The proposed model allows for NPHs and long-term survivors in subgroups. Parameter estimation was performed using the maximum likelihood method, and Monte Carlo simulation studies were conducted to evaluate the estimators' performance. We exemplify this model's use by applying data of patients diagnosed with lung cancer in the state of São Paulo, Brazil.

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When modeling growth curves, it should be considered that longitudinal data may show residual autocorrelation, and, if this characteristic is not considered, the results and inferences may be compromised. The Bayesian approach, which considers priori information about studied phenomenon has been shown to be efficient in estimating parameters. However, as it is generally not possible to obtain marginal distributions analytically, it is necessary to use some method, such as the weighted resampling method, to generate samples of these distributions and thus obtain an approximation. Among the advantages of this method, stand out the generation of independent samples and the fact that it is not necessary to evaluate convergence. In this context, the objective of this work research was: to present the Bayesian nonlinear modeling of the coffee tree height growth, irrigated and non-irrigated (NI), considering the residual autocorrelation and the nonlinear Logistic, Brody, von Bertalanffy and Richard models. Among the results, it was found that, for NI plants, the Deviance Information Criterion (DIC) and the Criterion of density Predictive Ordered (CPO), indicated that, among the evaluated models, the Logistic model is the one that best describes the height growth of the coffee tree over time. For irrigated plants, these same criteria indicated the Brody model. Thus, the growth of the non-irrigated and irrigated coffee tree followed different growth patterns, the height of the non-irrigated coffee tree showed sigmoidal growth with maximum growth rate at 726 days after planting and the irrigated coffee tree starts its development with high growth rates that gradually decrease over time.

Na modelagem de curvas de crescimento deve-se considerar que dados longitudinais podem apresentar autocorrelação residual, sendo que, se tal característica não é considerada, os resultados e inferências podem ser comprometidos. A abordagem bayesiana, que considera informações à priori sobre o fenômeno em estudo tem se mostrado eficiente na estimação de parâmetros. No entanto, como geralmente não é possível obter as distribuições marginais de forma analítica, faz-se necessário a utilização de algum método, como o método de reamostragem ponderada, para gerar amostras dessas distribuições e assim obter uma aproximação para as mesmas. Dentre as vantagens desse método, destaca-se a geração de amostras independentes e o fato de não ser necessário avaliar convergência. Diante desse contexto, o objetivo deste trabalho foi apresentar a modelagem não linear bayesiana do crescimento em altura de plantas do cafeeiro, irrigadas e não irrigadas (NI), considerando a autocorrelação residual e os modelos não lineares Logístico, Brody, von Bertalanffy e Richards. Em vista dos resultados, verificou-se que, para as plantas NI, o DIC e CPOc, indicaram que, dentre os modelos avaliados, o modelo Logístico é o que melhor descreve o crescimento em altura do cafeeiro ao longo do tempo. E, para as plantas irrigadas, esses mesmos critérios indicaram o modelo Brody. Assim, o crescimento da planta do cafeeiro não irrigado e irrigado seguiram padrões de crescimento distintos, a altura do cafeeiro não irrigado apresentou crescimento sigmoidal com taxa máxima de crescimento aos 726 dias após o plantio, já o cafeeiro irrigado inicia seu desenvolvimento com altas taxas de crescimento que vão diminuindo aos poucos com o tempo.

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Based on detailed household survey of apple farmers in Shandong and Shaanxi, this article used a binary logistic regression model to examine the impact of asset specificity on farmers' intergenerational succession arrangements of apple orchard. The results showed that the farmers' intergenerational willingness of younger generation to succeed them is generally weak. The specificity of human capital, physical assets, land assets and geographic location significantly impacted on farmers' intergenerational succession of family-operated apple orchard. Especially, the production technology level of apple planting decision-makers, the value of orchard facilities and machinery owned by apple growers, orchard topography, orchard fertility, government support, and the length of village hardened roads have significantly positive impacts on farmers' willingness. The education achievement of apple planting decision-makers, orchard irrigation area, and the number of village apple disasters negatively impacted farmers' willingness. Therefore, technical training should be intensified to effectively increase the human capital of farmers, infrastructure construction should be strengthened to improve apple production conditions, and professional farmers' operations should be supported to develop moderate-scale operations.

Com base em uma pesquisa domiciliar detalhada de produtores de maçã em Shandong e Shaanxi, este artigo usou um modelo de regressão logística binária para examinar o impacto da especificidade dos ativos nos arranjos de sucessão intergeracional dos produtores de pomar de maçã. Os resultados mostram que a disposição intergeracional dos agricultores da geração mais jovem para sucedê-los é geralmente fraca. A especificidade do capital humano, ativos físicos, ativos de terra e localização geográfica impactaram significativamente na sucessão intergeracional dos agricultores de pomar de maçã administrado por famílias. Especialmente, o nível de tecnologia de produção dos tomadores de decisão de plantio de maçã, o valor das instalações de pomar e maquinários de propriedade dos produtores, topografia do pomar, fertilidade do pomar, apoio do governo e a extensão das estradas da aldeia têm impactos significativamente positivos na vontade dos agricultores. As conquistas educacionais dos tomadores de decisão de plantio de maçã, a área de irrigação do pomar e o número de desastres de maçã nas aldeias impactam negativamente a vontade dos agricultores. Portanto, o treinamento técnico deve ser intensificado para aumentar efetivamente o capital humano dos agricultores, a construção da infraestrutura deve ser reforçada para melhorar as condições de produção de maçã e as operações dos agricultores profissionais devem ser apoiadas para desenvolver operações em escala moderada.

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A presente nota de pesquisa estima o impacto das mortes por Covid-19 sobre a esperança de vida no Brasil e regiões para os primeiros seis meses de 2020. Com base nos dados do Datasus e nas tábuas de vida com decremento simples, estimou-se que as mortes por Covid-19 ocorridas até 18 de agosto de 2020 tiveram impacto estatisticamente negativo na esperança de vida ao nascer, tanto masculina (-1,05 ano) quanto feminina (-0,85 ano). Em termos regionais, a maior perda em anos de vida é estimada no Norte (-1,65 ano para homens e -1,48 ano para mulheres), enquanto o Sul foi a região com menor impacto (-0,5 ano para homens e -0,36 para mulheres). Os resultados do modelo logístico para o país apontam que a mortalidade por Covid-19 tende a ser maior entre a população com mais de 65 anos, homens, pretos e de baixa instrução. As comorbidades aumentam a chance de desfecho morte, especialmente doença hepática e renal crônica. Tais análises foram ainda desagregadas por grandes regiões brasileiras.

This research note estimates the impact of deaths by Covid-19 on life expectancy in Brazil and the Regions for the first six months of 2020. Based on data from Datasus and the decreasing life tables, it was estimated that deaths by Covid-19 that occurred until August 18, 2020 had a statistically negative impact on life expectancy at birth, both male (-1.05 years) and female (-0.85 years). In regional terms, the greatest loss in years of life is estimated in the North (-1.65 years for men and -1.48 years for women), while in the South it was -0.5 year for men and -0.36 for women. The results of the logistic model for the country show that Covid-19 mortality tends to be higher among males, blacks, people with low education level and people over 65 years old. Comorbidities increase the chance of death, especially liver disease and chronic kidney disease. Such analyzes were further disaggregated by large Brazilian regions.

Esta nota de investigación estima el impacto de las muertes por Covid-19 en la esperanza de vida en Brasil y sus regiones durante los primeros seis meses de 2020. Con base en los datos de Datasus y de las tablas de vida decrecientes, se estimó que las muertes por Covid-19 que ocurrieron hasta el 18 de agosto de 2020 tuvieron un impacto estadísticamente negativo en la esperanza de vida al nacer, tanto en hombres (−1,05 años) como en mujeres (−0,85 año). En términos regionales, la mayor pérdida en años de vida se estima en el Norte (−1,65 año para los hombres y −1,48 años para las mujeres), mientras que en el Sur fue de −0,5 años para los hombres y −0,36 para las mujeres. Los resultados del modelo logístico para el país muestran que la mortalidad por Covid-19 tiende a ser mayor entre la población mayor de 65 años, hombres, afrobrasileros y de bajo nivel educativo. Las comorbilidades aumentan la probabilidad de muerte, especialmente la enfermedad hepática y la enfermedad renal crónica. Dichos análisis se desglosaron aun más por grandes regiones brasileñas.

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Abstract: Processes producing sigmoid curves are common in many areas such as biology, agrarian sciences, demography and engineering. Several mathematical functions have been proposed for modeling sigmoid curves. Some models such as the logistic, Gompertz, Richards and Weibull are widely used. This work introduces the Gudermannian function as an option for modeling sigmoid growth curves. The original function was transformed and the resulting equation was called the "Gudermannian growth model." This model was applied to four sets of experimental growth data to illustrate its practical application. The results were compared with those obtained by the logistic and Gompertz models. Since all these models are nonlinear in the parameters, the statistical properties of the least squares estimators were evaluated using measures of nonlinearity. For each experimental data set, the Akaike's corrected information criterion was utilized to discriminate among the models. In general, the Gudermannian model fitted better to the experimental data than the logistic and Gompertz models. The results showed that the Gudermannian model can be a good alternative to the classical sigmoid models.

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This paper presents a brief discussion with regard to the fixed-bed modeling results of a recent paper by Li et al. published in this journal.

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Huanglongbing (HLB) incidence is increasing and threatening citrus production in São Paulo State, Brazil, despite multiple efforts to control the disease and its vector, the Asian citrus psyllid (ACP) (Diaphorina citri). The objective of this research was to study the temporal dynamics of HLB epidemics, under intensive disease management, in 177 individual commercial citrus blocks on a single property in São Paulo State. The effect of internal and external sources of HLB-associated bacteria and its vector were explored based on the disease epidemics and vector dynamics in the studied area. To manage HLB, the property owner used healthy nursery plants, eradicated symptomatic trees, and used insecticides to control ACPs. Logistic and Gompertz models were fitted to the data to describe dynamics of HLB incidence for all blocks. The average number of ACPs per yellow sticky trap was determined for the same blocks for a period of four consecutive years. Both logistic and Gompertz models described the HLB epidemics well, although the Gompertz model provided a slightly better fit. Disease progress rates, HLB incidences, and average ACP count per trap in the 177 blocks were low compared with reports in the literature. HLB incidence and number of ACPs per trap were higher (P ≤ 0.05) in some citrus blocks located on the periphery of the property. A large number of noncommercial trees were found near the property and were a potential primary inoculum source of HLB-associated bacteria, accounting for the higher incidence of HLB and ACPs per trap in blocks located on the periphery of the property. These results support the recommended preventive measures to HLB management and the necessity of external actions, to include trees in commercial orchards, and noncommercial trees located near commercial citrus properties, in an attempt to maximize the effectiveness of these preventive measures.

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AIMS: This work aimed to estimate the growth of Myceliophthora thermophila M.7·7 in solid-state cultivation (SSC) through quantification of N-acetyl-d-glucosamine (NAG) and enzyme activity. METHODS AND RESULTS: The fungus was cultivated in sugarcane bagasse and wheat bran. A consistent statistical analysis was done to assess the reliability of experimental data. Logistic model equation was fitted to experimental data and growth parameters were estimated. The results showed strong influence of the sample size on NAG and a minimum recommended sample size was identified. Scanning electron microscopy (SEM) was used to identify the strategy of substrate colonization. Wheat bran was attacked firstly, while sugarcane bagasse was consumed after wheat bran depletion. The biomass growth was poorly estimated by secretion kinetics of α-amylase, endoglucanase, protease and xylanase, but enzyme kinetics were important for understanding substrate colonization. CONCLUSIONS: In conclusion, the NAG concentration was strongly affected by the sample size and sampling procedure. The strategy of fungal colonization on the substrates was well characterized through SEM analysis. The colonization strategy has direct influence on the kinetic parameters of the logistic model. Myceliophthora thermophila has a well-defined dynamic of enzyme secretion to degrade the substrate, although the kinetics of enzyme secretion has shown not adequate to characterize the kinetics of fungal growth. SIGNIFICANCE AND IMPACT OF THE STUDY: The paper provides reliable growth kinetic parameters in the SSC of the cellulase producer fungus M. thermophila M.7·7, as well as a robust analysis on three indirect methods (NAG, enzymes and SEM) for estimation of fungal development.

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The objective of this study was to compare non-linear models fitted to the growth curves of quail to determine which model best describes their growth and check the similarity between models by analyzing parameter estimates.Weight and age data of meat-type European quail (Coturnix coturnix coturnix) of three lines were used, from an experiment in a 2 × 4 factorial arrangement in a completely randomized design, consisting of two metabolizable energy levels, four crude protein levels and six replicates. The non-linear Brody, Von Bertalanffy, Richards, Logistic and Gompertz models were used. To choose the best model, the Adjusted Coefficient of Determination, Convergence Rate, Residual Mean Square, Durbin-Watson Test, Akaike Information Criterion and Bayesian Information Criterion were applied as goodness-of-fit indicators. Cluster analysis was performed to check the similarity between models based on the mean parameter estimates. Among the studied models, Richards was the most suitable to describe the growth curves. The Logistic and Richards models were considered similar in the analysis with no distinction of lines as well as in the analyses of Lines 1, 2 and 3.(AU)

Objetivou-se, neste estudo, comparar modelos não lineares ajustados às curvas de crescimento de codornas para determinar qual modelo que melhor descreve o crescimento de codornas e verificar a similaridade dos modelos analisando as estimativas dos parâmetros. Para as análises foram utilizados os dados peso e idade de codornas européias de corte (Coturnix coturnix coturnix) proveniente de três linhagens, em um esquema fatorial 2x4, instalado em um delineamento inteiramente casualizado, com dois níveis de energia metabolizável e quatro níveis de proteína bruta, com seis repetições. Os modelos não lineares utilizados foram: Brody, Von Bertalanffy, Richards, Logístico e Gompertz. Para a escolha do melhor modelo utilizou-se o Coeficiente de Determinação Ajustado, o Percentual de Convergência, o Quadrado Médio do Resíduo, o Teste de Durbin-Watson, o Critério de informação Akaike e o Critério de informação Bayesiano como avaliadores da qualidade do ajuste. Utilizou-se a análise de agrupamento para verificar, baseado nas estimativas médias dos parâmetros, a similaridades entre os modelos. Entre os modelos estudados, o Richard foi o mais adequado para descrever as curvas de crescimento. Os modelos Logístico e Richards foram considerados similares nas análises sem distinção de linhagem, bem como nas análises das Linhagem 1, 2 e 3.(AU)

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ABSTRACT: The objective of this study was to compare non-linear models fitted to the growth curves of quail to determine which model best describes their growth and check the similarity between models by analyzing parameter estimates.Weight and age data of meat-type European quail (Coturnix coturnix coturnix) of three lines were used, from an experiment in a 2 × 4 factorial arrangement in a completely randomized design, consisting of two metabolizable energy levels, four crude protein levels and six replicates. The non-linear Brody, Von Bertalanffy, Richards, Logistic and Gompertz models were used. To choose the best model, the Adjusted Coefficient of Determination, Convergence Rate, Residual Mean Square, Durbin-Watson Test, Akaike Information Criterion and Bayesian Information Criterion were applied as goodness-of-fit indicators. Cluster analysis was performed to check the similarity between models based on the mean parameter estimates. Among the studied models, Richards' was the most suitable to describe the growth curves. The Logistic and Richards models were considered similar in the analysis with no distinction of lines as well as in the analyses of Lines 1, 2 and 3.

RESUMO: Objetivou-se, neste estudo, comparar modelos não lineares ajustados às curvas de crescimento de codornas para determinar qual modelo que melhor descreve o crescimento de codornas e verificar a similaridade dos modelos analisando as estimativas dos parâmetros. Para as análises foram utilizados os dados peso e idade de codornas européias de corte (Coturnix coturnix coturnix) proveniente de três linhagens, em um esquema fatorial 2x4, instalado em um delineamento inteiramente casualizado, com dois níveis de energia metabolizável e quatro níveis de proteína bruta, com seis repetições. Os modelos não lineares utilizados foram: Brody, Von Bertalanffy, Richards, Logístico e Gompertz. Para a escolha do melhor modelo utilizou-se o Coeficiente de Determinação Ajustado, o Percentual de Convergência, o Quadrado Médio do Resíduo, o Teste de Durbin-Watson, o Critério de informação Akaike e o Critério de informação Bayesiano como avaliadores da qualidade do ajuste. Utilizou-se a análise de agrupamento para verificar, baseado nas estimativas médias dos parâmetros, a similaridades entre os modelos. Entre os modelos estudados, o Richard foi o mais adequado para descrever as curvas de crescimento. Os modelos Logístico e Richards foram considerados similares nas análises sem distinção de linhagem, bem como nas análises das Linhagem 1, 2 e 3.

RESUMO

BACKGROUND: To achieve malaria elimination, it is important to determine the role of human mobility in parasite transmission maintenance. The Alto Juruá basin (Brazil) exhibits one of the largest vivax and falciparum malaria prevalence in the Amazon. The goal of this study was to estimate the contribution of human commutes to malaria persistence in this region, using data from an origin-destination survey. METHODS: Data from an origin-destination survey were used to describe the intensity and motivation for commutations between rural and urban areas in two Alto Juruá basin (Brazil) municipalities, Mâncio Lima and Rodrigues Alves. The relative time-person spent in each locality per household was estimated. A logistic model was developed to estimate the effect of commuting on the probability of contracting malaria for a certain residence zone inhabitant commuting to another zone. RESULTS: The main results suggest that the assessed population is not very mobile. A total of [Formula: see text] households reported spending over [Formula: see text] of their annual person-hour in areas within the same residence zone. Study and work were the most prevalent commuting motivations, calculated at [Formula: see text] and [Formula: see text] respectively. Spending person-hours in urban Rodrigues Alves conferred relative protection to urban Mâncio Lima residents. The opposite effect was observed for those spending time in rural areas of both municipalities. CONCLUSION: Residence area is a stronger determinant for contracting malaria than commuting zones in the Alto Juruá region. As these municipalities are a hotspot for Plasmodium transmission, understanding the main local human fluxes is essential for planning control strategies, since the probability of contracting malaria is dependent on the transmission intensity of both the origin and the displacement area. The natural conditions for the circulation of certain pathogens, such as Plasmodium spp., combined with the Amazon human mobility pattern indicate the need for disease control perspective changes. Therefore, intersectoral public policies should become the basis for health mitigation actions.

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