Modelado matemático del efecto de las medidas de cuidado por COVID-19 sobre otras enfermedades respiratorias / Mathematical modelling of the impact of COVID-19 care measures on other respiratory diseases

RESUMEN INTRODUCCIÓN Los modelos matemáticos de la transmisión de enfermedades infecciosas permiten estudiar distintos mecanismos que afectan su comportamiento temporal. Este trabajo analizó el efecto sobre la dinámica de la influenza y el virus sincitial respiratorio (VSR) de la disminución de la transmisibilidad debida a las medidas de cuidado adoptadas para reducir la circulación de COVID-19. MÉTODOS Se empleó un modelo determinista tipo SIRS (susceptible-infectado-recuperado-susceptible) con modulación estacional para representar la influenza y el VSR, en ambos casos con inmunidad de corta duración y ciclo anual. Los cambios en la transmisibilidad de la enfermedad se modelaron reduciéndola durante dos años y planteando distintos escenarios. RESULTADOS En el modelo planteado, la reducción en la transmisibilidad genera cambios que se sostienen en los años siguientes: eventos epidémicos muy pronunciados con alargamiento del intervalo interbrote. Este efecto resulta dominante respecto del comportamiento estacional. El escenario de una reducción inicial de la transmisibilidad del 40% resulta compatible con el comportamiento de influenza y VSR reportados actualmente para Argentina. DISCUSIÓN El modelo general propuesto, en condiciones de disminución transitoria en la transmisibilidad, exhibe una epidemiología compatible con la observada recientemente en Argentina para ambas enfermedades e ilustra el modelado como herramienta útil en la comprensión de efectos no intuitivos.

ABSTRACT INTRODUCTION Mathematical models of infectious diseases transmission allow to study different mechanisms which affect their temporal behavior. This work analyzed the impact of the decrease in transmissibility, as a result of measures of personal care adopted to reduce circulation of COVID-19, on the dynamics of influenza and respiratory syncytial virus (RSV). METHODS A deterministic SIRS (susceptible-infected-recovered-susceptible) model with seasonal modulation was used to represent two diseases with short-term immunity and annual cycle: influenza and RSV. Changes in disease transmissibility were modeled by reducing it for two years and analyzing different scenarios. RESULTS In the proposed model, transmissibility reduction brings changes which sustain in the following years: very pronounced epidemic events with lengthening of the inter-outbreak interval. This effect prevails over the seasonal behavior. The scenario of 40% initial reduction in transmissibility is compatible with the behavior of influenza and RSV currently reported in Argentina. DISCUSSION The general model proposed here, under conditions of temporary reduced transmissibility, shows an epidemiology compatible with recently reported data of influenza and RSV in Argentina. This result illustrates modeling as a useful tool to understand non-intuitive effects.

Optimization and Quest of HPMC loaded Stavudine Controlled Release Dosage Development by Central Composite Design utilizing Reduced Factorial Screening Technique

Abstract The current research focused on screening and finding the significant independent variables in stavudine loaded tablet, followed by optimizing the best formulation using central composite design. The objective of the study to develop stavudine loaded controlled release tablet utilizing reduced factorial design, followed by optimization technique as well as characterization of prepared tablets. Preliminary trial batches were prepared using different grades of hydroxypropyl methylcellulose. The resolution-IV reduced factorial design was selected to screen the significant independent variables in the dosage form design. A total number of eight runs were prepared and responses were recorded. The signified factors identified by half-normal and Pareto chart. The prepared tablets are evaluated for various physiochemical characterizations. Three dependent responses such as hardness, dissolution at 6 hour and 12 hours are considered in optimization process. Later on, drug-polymer interaction study was carried out. The principal of the study design based on finding the best formulation with prefixed set parameter values utilizing the concept of screening technique. It observed that HPMC K15M (57.18 %), HPMC K100 (66.32 %) and PVP K30 (7.97 %) as best composition in a formulation batch would fulfill the predetermined parameter with specific values.

Simulación de escenarios para predecir el comportamiento de la COVID-19 en Perú / Scenario simulation to predict the behavior of COVID-19 in Peru

Introducción: La COVID-19 ha constituido un reto de múltiples dimensiones para la humanidad, aún más para los decisores responsables de accionar de manera certera y oportuna para su enfrentamiento. En Perú, con una tendencia actual favorable de la Pandemia, es inminente la propagación de la variante Delta, de allí que requieran de informaciones predictivas que posibiliten adoptar decisiones anticipadas para mitigar sus efectos. Objetivo: Simular escenarios aplicando la modelación físico-matemática, para la predicción del comportamiento de la COVID-19 en Perú que facilite la adopción de decisiones. Material y Métodos: Modelación físico-matemática mediante herramientas y funciones del software MATLAB. Resultados: Determinación del comportamiento de las principales variables de la COVID-19 en Perú; modelo físico-matemático basado en el clásico SIR con nuevos compartimientos relacionados con la vacunación y los expuestos, así como su ajuste a los datos de Perú; simulación de escenarios, incluyendo la variante Delta, para fallecidos, infectados acumulados, infectados no vacunados e infectados vacunados. Conclusiones: El modelo concebido para la simulación de escenarios de evolución de la COVID-19, demostró su capacidad de predicción del comportamiento de las variables más importantes que determinan dicha evolución en Perú; debe ocurrir otra ola de contagios y llegarse a cifras acumulativas entre 2,9 y 3,36 millones de infectados y entre 215 y 255 mil fallecidos; las principales estrategias de mitigación deben dirigirse a garantizar el distanciamiento y aislamiento social, así como a incrementar el régimen de vacunación(AU)

Introduction: COVID-19 has been a multi-dimensional challenge for humanity, even more so for decision-makers responsible for acting in an accurate and timely manner to confront it. In Peru, with is a current favorable trend of the Pandemic, the spread of the Delta variant is imminent, hence the need for predictive information that makes it possible to make early decisions to mitigate its effects. Objective: To simulate scenarios applying the physical-mathematical modeling to predict the behavior of COVID-19 in Peru and facilitate decision-making. Material and Methods: Physical-mathematical modeling using MATLAB software tools and functions. Results: Determination of the behavior of the main variables associated with COVID-19 in Peru; physical-mathematical modeling based on the classic SIR with new compartments related to vaccination and those exposed, as well as its adjustment to the data from Peru; simulation of scenarios including the Delta variant for deceased persons, cumulative number of infected individuals, and infection in vaccinated and unvaccinated individuals. Conclusions: The model conceived for the simulation of COVID-19 evolution scenarios demonstrated its ability to predict the behavior of the most important variables that determine such evolution in Peru; another wave of infections may occur and cumulative figures between 2.9 and 3.36 million infected individuals and between 215 and 255 thousand deaths may be reached. The main mitigation strategies should be aimed at guaranteeing social distancing and isolation, as well as increasing the vaccination regimen(AU)

Numerical Simulation of a Physiological Mathematical Model of Energy Consumption in a Sarcomere / Simulación Numérica de un Modelo Matemático Fisiológico de Consumo de Energía en un Sarcómero

ABSTRACT The paradigm of biological systems provides a framework to quantify the behavior of biological processes. Mathematical modeling is one of the analytical tools of biological systems used to reproduce the variables of a system for prediction. This article presents the analysis of muscular contraction, the physiological process responsible of generating force in skeletal muscle, from the point of view of mathematical modeling. The aim is to provide numerical evidences about the force generated by the sarcomere, and the energy required to produce such a force. The proposed scheme includes a model to activate the contractile cycle, based on the action potential that reaches the neuromuscular junction, the calcium release into the sarcoplasm, the contraction response, and the quantification of the energy that the sarcomere requires to perform mechanical work. The results shows that the proposed scheme is acceptable because it reproduces experimental data of force, velocity, and energy reported in the literature. The results of the proposed scheme are encouraging to scale the model at the muscle or muscle group level, in such a way that the quantification of energy can be an alternative to the indirect estimation methods of energy consumption that currently exist.

Advances in the development of constraint-based genome-scale metabolic network models / 生物工程学报

Genome-scale metabolic network model (GSMM) is becoming an important tool for studying cellular metabolic characteristics, and remarkable advances in relevant theories and methods have been made. Recently, various constraint-based GSMMs that integrated genomic, transcriptomic, proteomic, and thermodynamic data have been developed. These developments, together with the theoretical breakthroughs, have greatly contributed to identification of target genes, systems metabolic engineering, drug discovery, understanding disease mechanism, and many others. This review summarizes how to incorporate transcriptomic, proteomic, and thermodynamic-constraints into GSMM, and illustrates the shortcomings and challenges of applying each of these methods. Finally, we illustrate how to develop and refine a fully integrated GSMM by incorporating transcriptomic, proteomic, and thermodynamic constraints, and discuss future perspectives of constraint-based GSMM.

Examining the Impact of Aging and Interventions towards Burden of Diabetes Mellitus in Lao Population: A Model-Based Study / Lao Medical Journal

Background@#Diabetes Mellitus (DM) is a major public health concern, but with minimal data on how this affects the Lao population. @*Objective@#We aimed at predicting the impact of the burden of DM, and determine the effectiveness of DM screening techniques to reduce related mortality in Lao PDR.@*Methods@#A compartmentally deterministic model was created to reflect the demography in 2005 and 2015, and DM prevalence in 2015 of the Vientiane capital population. The parameters were retrieved from calibration and literature reviews. The model predicted demographic structure and DM in 2035. The effectiveness of DM screening tests, either Fasting Plasma Glucose (FPG) or glycated hemoglobin (HbA1c), was examined in term of mortality reduction.@*Results@#By 2035, the Vientiane population is expected to have annual grow of 0.89% with higher proportion of more elderly people; those aged 45 years old and older are expected to account for 39.3% in 2035. Overall prevalence of DM was expected to rise from 9.65% in 2015 to 13.4% in 2035 as a result of the aging population. The model predicts that the prevalence of DM would double (28.42%) in those aged >60 years old by 2035. The mortality rate is expected to increase more than double from 890 in 2015 to 1,808 deaths per 100,000 people in 2035, with the highest rate in those with undiagnosed diabetes and those older than 60 years. Screening by FPG test at an initial age of 35 years old is estimated to reduce mortality by 17.93%, and 16.80% for initial age screening at 45 years. Screening by HbA1c test would slightly increase the mortality reduction by approximately 1.20% at both initial screening ages.@*Conclusion@#This mathematical modeling projected the steadily increase of prevalence and death related to DM over 30 years of simulation. Early screening by glycemia would reduce the mortality.

A comprehensive review of integrative pharmacology-based investigation: A paradigm shift in traditional Chinese medicine

Over the past decade, traditional Chinese medicine (TCM) has widely embraced systems biology and its various data integration approaches to promote its modernization. Thus, integrative pharmacology-based traditional Chinese medicine (TCMIP) was proposed as a paradigm shift in TCM. This review focuses on the presentation of this novel concept and the main research contents, methodologies and applications of TCMIP. First, TCMIP is an interdisciplinary science that can establish qualitative and quantitative pharmacokinetics-pharmacodynamics (PK-PD) correlations through the integration of knowledge from multiple disciplines and techniques and from different PK-PD processes

Modelagem da qualidade da água em sistemas de macrodrenagem de bacias urbanas / Water quality modeling in urban basins macrodrainage systems

RESUMO A remoção da cobertura vegetal e a impermeabilização de grandes áreas somadas à ineficiência dos serviços básicos de saneamento, contribuem para o aumento das cargas poluidoras pontuais e difusas que são transportadas superficialmente pelas águas pluviais, causando impactos negativos ao sistema de drenagem. Como o despejo ilegal de efluentes domésticos em redes de drenagem é uma realidade observada em todo o país, principalmente no meio urbano, hoje, a maior preocupação dos gestores e estudiosos é voltada às fontes pontuais de poluição e, apesar da importância, as fontes difusas têm recebido pouca atenção. Este trabalho objetivou modelar, utilizando o programa Storm Water Management Model (SWMM), a qualidade das águas pluviais a partir da avaliação do acúmulo de poluentes na superfície do solo em períodos secos e da lavagem durante eventos de precipitação na Bacia Hidrográfica Riacho do Prado, inserida no perímetro urbano da cidade de Campina Grande, Paraíba. Oito pontos no canal de drenagem foram monitorados, analisando-se as variáveis demanda bioquímica de oxigênio (DBO), demanda química de oxigênio (DQO) e fósforo total (FT), além da determinação da vazão. Os resultados obtidos nas simulações do comportamento dos poluentes em escala temporal para o evento medido do dia 08 de junho de 2018 foram condizentes com os valores observados nas análises laboratoriais, confirmando a eficiência dos resultados para as outras simulações realizadas. Os dias antecedentes sem chuva e a intensidade da precipitação se mostraram importantes na análise da carga poluente.

ABSTRACT Removal of vegetation cover and the expansion of impermeable land, together with the inefficiency of basic sanitation services, contribute to the increase of point and diffuse pollutant loads drained by rainwater, causing negative impacts at drainage system. As the illegal discharging of domestic sewage in drainage canals is a reality observed throughout the country, especially in urban areas, today the main concern of managers and researchers is directed to the point sources of pollution and, despite the importance, diffuse sources have received little attention. This work aims to model the rainwater quality using the Storm Water Management Model (SWMM) from the evaluation of buildup pollutants on the soil surface in dry periods and the washoff during precipitation events in the Riacho do Prado watershed located in the urban area of Campina Grande, Paraíba. Eight points were monitored at the drainage canal, in which the variables BOD5, COD, and total phosphorus were analyzed, in addition to flow determination. The results obtained on the simulations of behavior of pollutants in time scale for the actual event of 06/08/2018 were in agreement with the values observed at laboratory analyses, confirming the efficiency of results for the other simulations. The previous days without rain and the intensity of precipitation were important in the analysis of the pollutant load.

Modelagem multinomial aplicada à pesquisa em psicologia / Modelo multinomial aplicado a la investigación psicológica / Multinomial modeling applied to psychological research

Teorias sobre fenômenos psicológicos frequentemente fazem referência a processos que não são diretamente observáveis (processos latentes). Tradicionalmente, no entanto, a investigação desses fenômenos é feita de forma indireta aos processos latentes. O objetivo deste artigo é introduzir os conceitos fundamentais de modelagem multinomial. Aqui mostramos como modelos de processos latentes são derivados de modelos puramente descritivos através da redução do espaço de parâmetros motivada por uma ou mais teorias psicológicas. Os resultados são os modelos multinomiais que fornecem medidas simples de processos psicológicos (probabilidades) e que podem ser quantitativamente testados com dados reais. O uso de modelagem multinomial permite a análise direta dos efeitos de variáveis independentes nos próprios processos latentes que controlam o desempenho em uma ou mais tarefas experimentais, assim, facilitando o teste de predições e explicações teóricas sobre fenômenos psicológicos.

Theories about psychological phenomena often refer to unobservable processes (latent processes). Traditionally, however, the psychological investigation of these phenomena is done indirectly to the latent processes themselves. The objective of this article is to introduce fundamental concepts about multinomial modeling. Here we show that latent processes models are derived from purely descriptive models by reducing the parameter space according to one or more psychological theories. The result is multinomial models that deliver simple measures of psychological processes (probabilities) and that can be tested quantitatively with real data. The use of multinomial modeling allows direct analysis of the effects of independent variables on the latent processes that control performance on one or more experimental tasks, thus making it easier to test theoretical predictions and explanations about psychological phenomena.

Teorías sobre fenómenos psicológicos a menudo se refieren a procesos que no son directamente observables (procesos latentes). Sin embargo, la investigación de estos fenómenos se realiza tradicionalmente de manera indirecta con respecto a los procesos latentes. El propósito de este artículo es presentar los conceptos fundamentales del modelado multinomial. Aquí mostramos cómo los modelos de procesos latentes se derivan de modelos puramente descriptivos al reducir el espacio de parámetros motivado por una o más teorías psicológicas. El resultado son modelos multinomiales que proporcionan medidas simples de procesos psicológicos (probabilidades) y que pueden probarse cuantitativamente con datos reales. El uso de modelos multinomiales permite el análisis directo de los efectos de variables independientes en los procesos latentes que controlan el rendimiento en una o más tareas experimentales, lo que facilita la prueba de predicciones y explicaciones teóricas sobre fenómenos psicológicos.

Prediction of cumulative rate of COVID-19 deaths in Brazil: a modeling study / Projeção da taxa cumulativa de óbitos por COVID-19 no Brasil: um estudo de modelagem

ABSTRACT: Objective: Estimating the potential number of COVID-19 deaths in Brazil for the coming months. Methods: The study included all confirmed cases of COVID-19 deaths, from the first confirmed death on March 17th to May 15th, 2020. These data were collected from an official Brazilian website of the Ministry of Health. The Boltzmann function was applied to a data simulation for each set of data regarding all states of the country. Results: The model data were well-fitted, with R2 values close to 0.999. Up to May 15th, 14,817 COVID-19 deaths have been confirmed in the country. Amazonas has the highest rate of accumulated cases per 1,000,000 inhabitants (321.14), followed by Ceará (161.63). Rio de Janeiro, Roraima, Amazonas, Pará, and Pernambuco are estimated to experience a substantial increase in the rate of cumulative cases until July 15th. Mato Grosso do Sul, Paraná, Minas Gerais, Rio Grande do Sul, and Santa Catarina will show lower rates per 1,000,000 inhabitants. Conclusion: We estimate a substantial increase in the rate of cumulative cases in Brazil over the next months. The Boltzmann function proved to be a simple tool for epidemiological forecasting that can assist in the planning of measures to contain COVID-19.

RESUMO: Objetivo: Estimar o número potencial de mortes por COVID-19 no Brasil nos próximos meses. Métodos: O estudo incluiu todos os casos confirmados de óbitos do COVID-19, desde o primeiro óbito confirmado em 17 de março até 15 de maio de 2020. Esses dados foram coletados no site oficial do Ministério da Saúde. A função Boltzmann foi aplicada a uma simulação de dados para cada conjunto de dados referente a todos os estados do país. Resultados: Os dados do modelo foram bem ajustados, com valores de R2 próximos a 0,999. Até 15 de maio, 14.817 mortes de COVID-19 foram confirmadas no país. O Amazonas possui a maior taxa de casos acumulados por 1.000.000 habitantes (321,14), seguido pelo Ceará (161,63). Estimou-se que os estados do Rio de Janeiro, Roraima, Amazonas, Pará e Pernambuco sofrerão um aumento substancial na taxa de casos acumulados até 15 de julho. Mato Grosso do Sul, Paraná, Minas Gerais, Rio Grande do Sul e Santa Catarina apresentarão taxas potenciais mais baixas por 1.000.000 habitantes. Conclusão: Foi estimado um aumento substancial na taxa de casos cumulativos no Brasil nos próximos meses. A função Boltzmann provou ser uma ferramenta simples para previsão epidemiológica que pode auxiliar no planejamento de medidas para conter o COVID-19.

Comparison of Different Extraction Techniques of Zingiber officinale Essential Oil

Abstract This study aims to find the best conditions for the extraction of Zingiber officinale essential oil using the supercritical fluid extraction (SFE), steam distillation (SD) and hydrodistillation (HD) techniques, regarding the maximum oil yield. For the HD technique is evaluated the best ratio between plant mass and water volume and for SFE and SD the pressure condition was investigated. Principal Component Analysis (PCA) was used to evaluate the similarity between the composition of the essential oil in different pressures and extraction methods. The experimental extraction curve was plotted and three different mathematical models were used to fit the data for SD and SFE methods, obtaining the relevant mass transfer parameters. The essential oil compounds were identified by gas chromatography coupled with mass spectrometry (GC-MS), being α-zingiberene the main component with different contents (from 11.9 to 28.9%). The best condition for the SFE was 100 bar, 40 °C (0.0508 goil/gplant) with 19.34% of α-zingiberene; for the SD, 3 bar (133 °C) (0.00616 goil/gplant) with 28.9% of α-zingiberene; and HD, the volume of 750 mL (0.006988 goil/gplant) with 15.70% of α-zingiberene, all measured on a dry basis.

Mathematical model construction and analysis of the effect of estradiol on the electrical activity of gastric antrum in female rabbits / 解剖学报

Objective To investigate the expression of estrogen receptor in gastric antrum and the effect of estrogen on electrical activity of gastric antrum smooth muscle in female rabbits in virtue of the constructed mathematical model in order to explore the regulation of estrogen on gastric motility. Methods Using immunofluorescence to observe the expression of estrogen receptor in gastric antrum. Using BL-420F bio monitor to monitor: Comparing the difference of antral electromyography index between rabbits in ovariectomized group and rabbits in sham operating group; Observing the dose-response relationship between doses of estradiol (0,0. 1,0. 15,0. 2,0. 25 and 0. 3 mg/ kg). To construct the mathematical model, and to analyze the dose-response relationship and mechanism of action. Rresult The expression of estrogen receptor in the antral wall of the stomach was negative. The activity index of gastric antrum myoelectric activity was significantly decreased after ovarian ablation (P<0. 01). With the increase of estradiol dose, the activity index of gastric antrum muscle increased and then decreased. Analysis of variance showed that the difference of antral electromyographic activity index between adjacent groups was significant (P<0. 05) or extremely significant (P<0. 01). Taking the estradiol dose as the independent variable x, the antral electromyography activity index was the dependent variable y, and the fitting wass obtained: y= 2. 80 + 5. 65 × exp{ -0. 5 × [(x-0. 159) / 0. 038 ]

Aplicação de solução semianalítica para modelagem de ensaios de sorção e difusão pura com lixiviado / Application of semi-analytical solution for modeling sorption and pure diffusion assays with leachate

RESUMO A implementação da Política Nacional de Resíduos Sólidos (Lei nº 12.305, de 2 de agosto de 2010) foi um marco para a disposição final e o tratamento de resíduos sólidos no país. A contaminação decorrente da negligência na disposição dos resíduos sólidos urbanos atinge sistemas naturais vitais para a existência humana. Torna-se, portanto, fundamental compreender os mecanismos que estão envolvidos no transporte de contaminantes e os dispositivos geotécnicos para mitigar e/ou remediar os impactos. Neste trabalho, é apresentada a utilização de modelagens matemáticas aplicadas aos resultados dos experimentos realizado por Ritter, em 1998, para determinar o transporte dos principais íons inorgânicos, encontrados no lixiviado do aterro Jardim Gramacho (K+, Cl-, Na+ e NH4 +), por difusão química e sorção. O Aterro de Resíduos Urbanos de Jardim Gramacho está localizado em Duque de Caxias, no estado do Rio de Janeiro, e operou por mais de 30 anos, de 1978 a 2012. Para a compreensão dos mecanismos de transporte, foi utilizada uma solução semi-analítica denominada de camada contaminada equivalente (CCE), proposta por Paz, em 2015, com o objetivo de traçar, no tempo e no espaço, o comportamento desses contaminantes ao longo da amostra de solo utilizada. A vantagem da utilização dessa solução analítica é que ela atende com maior rigor as condições de contorno dos experimentos analisados, quando comparadas com as soluções disponíveis na literatura. Os resultados mostram que os coeficientes de difusão efetivo determinados pela solução CCE apresentam-se dentro dos intervalos indicados na literatura.

ABSTRACT The implementation of the National Solid Waste Policy (Law No. 12.305, of August 2, 2010) was a milestone for the final disposal and treatment of solid waste in the country. The contamination due to negligence in the disposal of urban solid waste reaches natural resources and systems vital to human existence. It is, therefore, essential to understand the mechanisms involved in the transport of contaminants and the best geotechnical devices to mitigate and/or remediate impacts. This paper presents the use of mathematical models applied to the results of the experiments carried out by Ritter, in 1998, to determine the transport of the main inorganic ions found in the leachate of Jardim Gramacho landfill (K+, Cl-, Na+, and NH4 +), by chemical diffusion and sorption mechanisms. The Jardim Gramacho Urban Waste Landfill was located in Duque de Caxias, state of Rio de Janeiro, and operated for more than 30 years, from 1978 to 2012. In order to understand these transport mechanisms, a semi-analytical solution, denominated Equivalent Contaminated Layer (ECL) proposed by Paz, in 2015, was used to trace, in time and space, the behavior of these contaminants along the soil sample used. The advantage of using this analytical solution is that it meets more accurately the boundary conditions of the analyzed experiments, when compared with the solutions available in the literature. The results show that the effective diffusion coefficients determined by the ECL solution are within the ranges indicated in the literature.

Estimativa do potencial de recuperação energética de resíduos sólidos urbanos usando modelos matemáticos de biodigestão anaeróbia e incineração / Estimation of municipal solid waste energy recovery potential using mathematical models of anaerobic biodigestion and incineration

RESUMO Atualmente, um dos grandes problemas enfrentados pelos gestores de resíduos sólidos urbanos (RSU) é a disposição final dos resíduos gerados por sua população. As disposições de resíduos devem ser feitas em espaços e sob condições adequados de modo a minimizar os impactos socioeconômicos e ambientais. Nesse contexto, este artigo teve por objetivo estimar o potencial de recuperação energética de RSU usando modelos de simulação matemática para a biodigestão anaeróbia e a incineração. Como objeto de estudo, foram considerados os resíduos dispostos no aterro sanitário de Caieiras, localizado no município de Caieiras (SP). Para avaliação da biodigestão anaeróbia, foram analisados modelos matemáticos que permitem estimar a produção de metano em função dos diversos fatores que interferem no processo (concentração de acetato e de micro-organismos, variação do pH, entre outros). No caso da incineração, foram considerados modelos matemáticos empíricos (baseados nas análises imediata, gravimétrica e elementar) para estimar o poder calorífico inferior dos RSU. De acordo com os resultados obtidos, para a biodigestão anaeróbia seria possível obter potência média de 38,8 MW. Caso a incineração fosse adotada como método de tratamento dos RSU, seria possível obter potência elétrica média de 214 MW (considerando a incineração de 100% dos resíduos). Com base nas simulações realizadas para a biodigestão anaeróbia e a incineração como possíveis métodos de destinação dos RSU, conclui-se que o processo de incineração apresenta potencial de geração de eletricidade aproximadamente cinco vezes maior do que a conversão energética da biodigestão anaeróbia.

ABSTRACT Currently, one of the major problems faced by managers of solid urban waste is the final disposal of the waste generated by their population. Waste disposals should be done in spaces and/or under appropriate conditions, in order to minimize socioeconomic and environmental impacts. In this context, this article aims at estimating the energy recovery potential of urban solid waste using mathematical simulation models for anaerobic biodigestion and incineration. As object of study, the waste disposed in Caieiras landfill, located in the city of Caieiras/SP, was considered. To evaluate the anaerobic digestion, mathematical models were used to estimate methane production as function of the various factors that influence the process (acetate and microorganisms concentration, pH variation among others). In the case of incineration, empirical mathematical models (based on immediate, gravimetric and elementary analysis) were used to estimate the lower heating value of urban solid waste. According to the results obtained, it would be possible to obtain an average power of 38.8 MW for anaerobic digestion. If the incineration method was adopted, it would be possible to obtain an average electrical power of 214 MW (considering the total incineration of the waste). Based on the simulations carried out for anaerobic biodigestion and incineration as possible methods of municipal solid waste disposal, it is concluded that the incineration process of municipal solid waste presents a greater potential of electricity generation, approximately five times higher than the energy conversion potential of anaerobic digestion.

Mathematical Modeling of the Quorum Sensing in Vibrio harveyi / Modelado Matemático de la Detección de Quórum en Vibrio harveyi

Abstract One of the most used bacteria in the Quorum Sensing (QS) experimental works is the Vibrio harveyi, which is used as reporter bacteria to detect the Autoinducers-2 (AI-2) activity of other bacteria. Nevertheless, the description of its QS mechanism by the mathematical modeling is an approach still unexploited. For biological systems, it is necessary to consider the high variability of the experimental data, thus identifiability and parametric reliability analyses must be performed before a model could be used. The following work describes a methodology for parameter fitting and parametric identifiability analysis in a model that describes the dynamics of AI-2 in V. harveyi bacteria. Identifiability analyses showed that all parameters are identifiable, but parametric dependency analyses showed two linearly dependent parameters. According to our results, the model is adequate to describe the AI-2 dynamics in V. harveyi.

Resumen Una de las bacterias más utilizadas en los trabajos experimentales de detección de quorum (QS) es la Vibrio harveyi, que se utiliza como bacteria reportera para detectar la actividad de Autoinductores-2 (AI-2) de otras bacterias. Sin embargo, la descripción de su mecanismo de QS por medio del modelado matemático es un enfoque aún no explotado. En el caso de los sistemas biológicos, es necesario considerar la alta variabilidad de los datos experimentales, por lo que deben realizarse análisis de identificabilidad y fiabilidad paramétrica antes de que un modelo pueda ser usado. El siguiente trabajo describe una metodología para el ajuste de parámetros y el análisis de la identificabilidad paramétrica en un modelo que describe la dinámica de la AI-2 en las bacterias V. harveyi. Los análisis de identificabilidad mostraron que todos los parámetros son identificables, pero los análisis de dependencia paramétrica mostraron dos parámetros linealmente dependientes. De acuerdo con los resultados, el modelo es adecuado para describir la dinámica AI-2 en V. harveyi.

Fuzzy logic and hospital admission due to respiratory diseases using estimated values by mathematical model / Lógica fuzzy e internações por doenças respiratórias usando dados estimados por modelo matemático

Abstract Hospitalizations due to respiratory diseases generate financial costs for the Health System in addition to social costs. Objective of this study was to develop and validate a fuzzy linguistic model for prediction of hospitalization due to respiratory diseases. We constructed a fuzzy model for prediction of hospitalizations due to pneumonia, bronchitis, bronchiolitis and asthma second exposure to fine particulate matter (PM2.5) in residents of Volta Redonda, RJ, in 2012. The model contains two inputs, PM2.5 and temperature, with three membership functions for each input, and an output with three membership functions for admissions, which were obtained from DATASUS. There were 752 hospitalizations in the period, the average concentration of PM2.5 was 17.1 µg/m3 (SD = 4.4). The model showed a good accuracy with PM2.5, the result was between 90% and 76.5% for lags 1, 2 and 3, a sensitivity of up to 95%. This study provides support for creating executable software with a low investment, along with the use of a portable instrument could allow number of hospital admission due to respiratory diseases and provide support to local health managers. Furthermore, the fuzzy model is very simple and involves low computational costs, an implementation making possible.

Resumo Internações por doenças respiratórias geram custos financeiros para o Sistema de Saúde além de custos sociais. O objetivo deste estudo foi elaborar e validar um modelo linguístico "fuzzy" para previsão do número de internações por doenças respiratórias. Foi construído um modelo "fuzzy" para predição de internações por pneumonias, bronquite, bronquiolite e asma segundo exposição ao material particulado fino (PM2,5) em residentes de Volta Redonda, RJ, em 2012. O modelo contém duas entradas PM2,5 e temperatura, com três funções de pertinência para cada entrada, e uma saída com três funções de pertinência para internações, que foram obtidas do DATASUS. Foram 752 internações no período, a concentração média do PM2,5 foi 17,1 µg/m3 (dp = 4,4). O modelo mostrou uma boa acurácia com PM2,5, o resultado foi entre 90% e 76,5% para os lags 1, 2 e 3, com sensibilidade de até 95%. Este estudo fornece subsídios para a criação de programa executável, que não exige um grande investimento, juntamente com o uso de um instrumento portátil pode permitir uma estimativa do número de internações e prestar apoio aos gestores municipais de saúde. Além disso, o modelo "fuzzy" é muito simples e implica em baixas despesas computacionais, tornando possível uma implementação.

Effects of exposure to fine particulate matter in elderly hospitalizations due to respiratory diseases in the South of the Brazilian Amazon

Exposure to air pollution is an important cause of hospital admissions due to respiratory diseases. Nevertheless, few studies use pollutant concentration data estimated by mathematical models. A time-series ecological study was developed, using data from hospitalizations due to respiratory diseases in people over 60 years of age, residents of Cuiabá, Brazil, during 2012, obtained from the Brazilian Ministry of Health. The independent variables were the concentrations of fine particulate matter (PM2.5) and carbon monoxide (CO) estimated by mathematical modeling, minimum temperature, and relative humidity (obtained from the Brazilian Meteorological Agency), and the number of forest fires. The generalized linear regression model of Poisson was used, with lags of 0 to 7 days. The coefficients obtained were transformed into relative risk of hospitalization, with respective 95% confidence intervals; alpha=5% was adopted. In that year, 591 hospitalizations were evaluated, with a daily average of 1.61 (SD=1.49), the PM2.5 average concentration was 15.7 µg/m3, and the CO average concentration was 144.2 ppb. Significant associations between exposure to these contaminants and hospitalizations in lags 3 and 4 in 2012 were observed. There was a hospitalization risk increase of 31.8%, with an increase of 3.5 µg/m3 of PM2.5 concentrations and an increase of 188 in the total number of hospitalizations, with an expense of more than ≈US$ 96,000 for the Brazilian Public Health System. This study provided information on the cost of air pollution to the health system and the feasibility of using a mathematical model to estimate environmental concentration of air pollutants.

Drying kinetics modeling of apple and zucchini slices vacuum impregnated with anthocyanins / Modelagem da cinética de secagem de discos de maçã e abobrinha impregnadas a vácuo com antocianinas

ABSTRACT: The aim of this research was to study the drying kinetics of apple and zucchini slices enriched with anthocyanins and to evaluate the influence of drying temperature on the anthocyanin content of apple and zucchini snacks. Apple (Granny Smith) and zucchini (Cucurbita pepo) slices were enriched with anthocyanins by vacuum impregnation with blueberry juice. Then, slices were dehydrated at 40, 50 and 60 ºC with 1.0 m/s air flow. Dehydrated samples were referred to as anthocyanin enriched snacks. Diffusion coefficient values improved by increasing the drying temperature, within the 2.81×10-10 to 5.78×10-10 m2/s range for apple slices and 2.02×10-10 to 3.99×10-10 m2/s for zucchini slices. The activation energy was 31.19 kJ/mol and 80.33 kJ/mol for apple and zucchini slices respectively. Page, Weibull, Logarithmic, Henderson-Pabis and Lewis models best fitted the experimental data. Snacks obtained at 60 °C retained a higher concentration of anthocyanins, reaching values of 592.81±52.55 and 464.62±48.44 mg of cyaniding-3-glucoside equivalent/kg dry matter in apple and zucchini snacks respectively. Combination of vacuum impregnation and hot air drying was a technological alternative for producing snacks with functional properties.

RESUMO: O objetivo deste trabalho foi estudar a cinética de secagem de fatias de maçã e abobrinha enriquecidas com antocianinas e avaliar a influência da temperatura de secagem no teor de antocianinas de discos de maçã e abobrinha. Fatias de maçã (Granny Smith) e abobrinha (Cucurbita pepo) foram enriquecidas com antocianinas por impregnação a vácuo com suco de mirtilo. Em seguida, as fatias foram desidratadas a 40, 50 e 60 ºC com fluxo de ar de 1,0 m / s. As amostras desidratadas foram referidas como snacks enriquecidos com antocianinas. Os valores do coeficiente de difusão melhoraram com o aumento da temperatura de secagem, na faixa de 2.81 × 10-10 a 5.78 × 10-10 m2/s para fatias de maçã e 2.02 × 10-10 a 3.99 × 10-10 m2/s para fatias de abobrinha. A energia de ativação foi 31.19 kJ / mol e 80.33 kJ / mol para as fatias de maçã e abobrinha, respectivamente. Os modelos de Page, Weibull, Logarithmic, Henderson-Pabis e Lewis ajustaram os dados experimentais. Os snacks obtidos a 60 °C retiveram uma maior concentração de antocianinas, atingindo valores de 592.81 ± 52.55 e 464.62 ± 48.44 mg de equivalentes de cianidina-3-glicosídeo / kg de matéria seca nos snacks de maçã e abobrinha, respectivamente. A combinação da impregnação a vácuo e secagem por ar quente foi uma alternativa tecnológica para produção de lanches com propriedades funcionais.

Solar Tunnel Drying: Pretreatment on drying kinetic of plum tomatoes / Secagem de Túnel Solar: O efeito do pré-tratamento na secagem cinética de tomates de ameixa

ABSTRACT: Drying of thin layer tomato was studied using a solar tunnel dryer under the ecological conditions of Isparta, Turkey. During drying process, solar irradiation, drying air temperature, relative humidity, and air velocity were measured constantly in different parts of the dryer. Drying runs were performed using plum tomatoes, characterized by an oval shape, intense red color. The change of tomatoes mass was measured daily. The color measurements of dried products were determined at the beginning and end of experiment. In this study, the fresh tomato samples were sorted, graded, washed in water and then sliced into quarters and halves before pretreated. Sun drying behavior of half and quarter sliced tomatoes pretreated with 10% NaCl solution and non-pretreated was investigated. Results showed that the drying time for pretreated and non-pretreated samples was not significantly different. However, drying time and drying rates were affected by number of tomato slices (quarter and half). Drying characteristic curves were evaluated against thirteen mathematical models and the Midilli et al model was the best descriptive model for solar tunnel drying of thin layer tomato. Color analysis emphasized that if tomatoes are pretreated with 10% NaCl solution, they should be sliced in quarter for better quality.

RESUMO: A secagem do tomate de camada fina foi estudada usando um secador de túnel solar sob as condições ecológicas de Isparta, na Turquia. Durante o processo de secagem, a irradiação solar, a temperatura do ar de secagem, a umidade relativa e a velocidade do ar foram medidas constantemente em diferentes partes do secador. As operações de secagem foram realizadas com tomates ameixa, caracterizados por uma forma oval, cor vermelha intensa. A mudança de massa de tomates foi medida diariamente. As medidas de cor dos produtos secos foram determinadas no início e no final da experiência. Neste estudo, as amostras de tomate fresco foram classificadas, lavadas em água e depois cortadas em quartos e metades antes do pré-tratamento. O comportamento de secagem ao sol do tomate em fatias de meio e quarto pré-tratadas com solução de NaCl a 10% e sem pré-tratamento foi investigado. Os resultados mostraram que o tempo de secagem para amostras pré-tratadas e não pré-tratadas não foram significativamente diferentes. No entanto, o tempo de secagem e as taxas de secagem foram afetadas pelo número de fatias de tomate (trimestre e meio). As curvas características de secagem foram avaliadas contra treze modelos matemáticos, sendo que o modelo de Midilli et al foi o melhor modelo descritivo para secagem em túnel solar de tomate de camada fina. A análise de cores enfatizou que se os tomates forem pré-tratados com solução de NaCl a 10%, eles devem ser cortados em fatias para melhor qualidade.

Modelagem da qualidade da água do rio Poti em Teresina (PI) / Water quality modeling at Poti river in Teresina (Piauí, Brazil)

RESUMO O crescimento desordenado da capital piauiense - marcado, sobretudo, pela ocupação habitacional às margens do rio Poti e pela existência de ligações clandestinas de esgoto bruto nas tubulações de drenagem pluvial - tem contribuído significativamente para a poluição das águas da bacia hidrográfica do rio Parnaíba (região semiárida do Brasil). A presente pesquisa tem como objetivo realizar a modelagem matemática da qualidade da água em um trecho de 36,8 km de extensão do rio Poti, com base na plataforma QUAL-UFMG. A pesquisa apresenta-se como o primeiro estudo envolvendo modelagem da qualidade da água no referido rio. Os componentes modelados foram: oxigênio dissolvido (OD), demanda bioquímica de oxigênio (DBO) e coliformes termotolerantes (CT). Os resultados das medições de campo indicaram desconformidades do parâmetro CT com relação à Resolução CONAMA nº 357/2005. A calibração dos coeficientes de decaimento para cada parâmetro resultou em desvios médios entre dados medidos e modelados de até 20% e coeficientes de eficiência de Nash-Sutcliffe superiores a 0,75, o que indica que o QUAL-UFMG pode ser utilizado como base para predição da qualidade da água em rios localizados em regiões semiáridas. O modelo calibrado também foi comparado aos dados de campo obtidos na literatura. Finalmente, foram realizadas simulações do modelo para diferentes cenários de vazão (mínimas e máximas), apresentando resultados coerentes e que podem ser utilizados para a gestão dos recursos hídricos do estado do Piauí.

ABSTRACT The uncontrolled growth of Piauí's capital, in Brazil, characterized mainly by the occupation of the banks of the river Poti and the existence of illegal connections of raw sewage in rainwater drainage pipes, has contributed significantly to water pollution in the basin of Parnaíba river (semiarid region of Brazil). This research aims at performing the mathematical modeling of water quality in an area of 36.8 km of the Poti river, based on the QUAL-UFMG platform. The research is presented as the first study involving modeling of water quality in said river. Modeled components were: dissolved oxygen (DO), biochemical oxygen demand (BOD) and thermotolerant coliforms (TC). The results obtained from field measurements indicated nonconformities of the parameter TC with respect to CONAMA Resolution nº 357/2005. The calibration of the decay coefficients for each parameter resulted in mean deviations between measured and modeled data of up to 20% and Nash-Sutcliffe efficiency coefficients higher than 0.75, which indicate that the QUAL-UFMG can be used as a basis for predicting the water quality in rivers of semiarid areas. The calibrated model was also compared to field data obtained from the literature. Finally, model simulations were performed for different flow scenarios (minimum and maximum), with consistent results that can be used for the management of the Piauí state water resources.