Determination of a Drop Damage Index to Estimate Bruising Susceptibility of Apple Royal Gala by Logistic Model

2002 ◽  
pp. 359-374
Author(s):  
Paolo Menesatti ◽  
Graziella Paglia ◽  
Silvia Solaini ◽  
Angelo Zanella
Keyword(s):  
Logistic Model ◽  
Damage Index

scholarly journals Determination of reasonable damage index for suspension bridge tower

2018 ◽  
Vol 439 ◽  
pp. 042067
Author(s):  
Lei Liu ◽  
Tieyi Zhong ◽  
Guangzhi Fu ◽  
Junhua Xiao
Keyword(s):  
Damage Index ◽  
Suspension Bridge ◽  
Bridge Tower

A Maximum Sustainable Area Model for Harvesting Eichhornia Crassipe in Environmental Phytoremediation

2014 ◽  
Vol 513-517 ◽  
pp. 2975-2978
Author(s):  
Ling Sun ◽  
Ze Sheng Zhu
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Logistic Model ◽  
Eichhornia Crassipes ◽  
Goodness Of Fit ◽  
Remote Sensing Images ◽  
Area Model ◽  
Fit Index

The aim of this study was to investigate the use of a model to determine harvest area of Eichhornia crassipes in environmental phytoremediation. A logistic model was constructed to eatimate the area of Eichhornia crassipes and tested in Eichhornia crassipes samples. The area of Eichhornia crassipes was measured nine times in experiment period using GPS and satellite remote sensing images. The measurements were shown to lead to a determination of the parameters of accurate logistic model with an overall Goodness of Fit Index of 0.9753. This indicates that there is a possibility of obtaining maximum harvest area of Eichhornia crassipes from the logistic model and suggests that it is possible to implement environmental phytoremediation with the continuous harvest at the maximum sustainable area of Eichhornia crassipes.

scholarly journals Modelagem otimizada de indicadores biológicos de qualidade da água

Revista DAE ◽  
2019 ◽  
Vol 221 (68) ◽  
pp. 131-141
Author(s):  
Gabriel da Costa Cantos Jerônimo ◽  
Luiz Felipe Ramos Turci ◽  
Paulo Augusto Zaitune Pamplin ◽  
Patrícia Neves Mendes
Keyword(s):  
Population Growth ◽  
Logistic Model ◽  
Growth Models ◽  
Lemna Minor ◽  
Growth Data ◽  
Model Quality ◽  
Nonlinear Growth ◽  
Statistical Indicators ◽  
Selection Of

Resumo 27/06/2018 DOI: https://doi.org/10.36659 /dae.2020.011 Turci, L. F. R Pamplin, P. A. Z https://orcid.org/0000-0001-7516-0963 https://orcid.org/0000-0001-7318-9121 O estudo de plantas aquáticas (macrófitas) é importante, uma vez que essas plantas apresentam potencial de utilização em estudos de ecotoxicologia, como bioindicadores no tratamento de águas residuárias. A mode- lagem criteriosa do crescimento dessas plantas, especificamente a Lemna minor, é útil na determinação das condições de otimização dessas aplicações; assim, deseja-se sempre obter o modelo que melhor represente a dinâmica de crescimento populacional da planta em estudo. Neste trabalho, apresenta-se uma metodologia de ajuste e seleção de modelos de crescimento não lineares com base em indicadores estatísticos que servem como avaliadores de qualidade dos modelos. Para ilustrar o uso da metodologia, foi feito o cultivo de Lemna minor em meio Steinberg e foram ajustados três modelos aos dados médios de crescimento de suas frondes, selecionando o modelo Logístico como o melhor. Palavras-chave: Modelo de crescimento populacional. Avaliadores de qualidade. Lemna minor. Abstract The study of aquatic plants (macrophytes) is important since such plants present a potential utilization in ecotoxi- cology as bioindicators, as well in wastewater treatment. The criterious growth modelling of such plants, specifically Lemna minor, is useful for the determination of the optimal conditions of mentionedin applications - so one always looks for the best model that represents the dynamic of population growth of the plant in study. This work presents a methodology of adjustment and selection of nonlinear growth models based on statistical indicators, which work as quality evaluators for the models. To illustrate this methodology, Lemna minor was grown in Steinberg environ- ment, and three models were fitted to the fronds growth data, the Logistic model was selected as the best model. Keywords: Population growth model. Quality evaluators. Lemna minor.

COVID-19: Estimation of the Actual Onset of Local Epidemic Cycles, Determination of Total Number of Infective, and Duration of the Incubation Period (Preprint)

2020 ◽  
Author(s):  
Rogerio Atem De Carvalho ◽  
Eduardo Atem De Carvalho
Keyword(s):  
Incubation Period ◽  
Statistical Models ◽  
Average Method ◽  
Logistic Model ◽  
Moving Average ◽  
Lag Time ◽  
Inventory Model ◽  
Actual Number ◽  
Initial Value

BACKGROUND Most studies of the epidemic cycles of the pandemic of Sars-CoV-2, or COVID-19 as it became known, define the beginning of specific cycles in countries from the laboratory identification of the first cases of infection, however, there is the awareness that cycles may have started earlier, without proper identification. This influences all the parameters that govern the statistical models used for controlling the infection. OBJECTIVE This work proposes two models based on experimental data. The Logistic Model it is used to obtain three parameters of the epidemic cycle of COVID-19, namely: the final count for the total infected, the daily infection rate and the lag time. Complimentary, a novel inventory model is proposed to calculate the number of infective persons, as well as to determine the incubation period. METHODS The data on epidemic cycles of Germany, Italy, and Sweden are treated previously by the Moving Average Method with Initial value (MAMI), then a variation of the Logistic Model, obtained through curve-fitting, is used to obtain the three parameters. The inventory model is introduced to calculate the actual number of infected persons and the behavior of the incubation period is analyzed. RESULTS After comparing data from the three countries it is possible to determine the actual probable dates of the beginning of the epidemic cycles for each one, determine the size of the incubation period, as well as to determine the total number of infective persons during the cycle. CONCLUSIONS The actual probable dates of the beginning of the epidemic cycles in the countries analyzed are determined, the total number of infected is determined, and it is statistically proven that the incubation cycle for Sars-CoV-2 is five days.

scholarly journals Sorption of fomesafen in Brazilian soils

2013 ◽  
Vol 31 (4) ◽  
pp. 971-977 ◽  
Author(s):  
G.R. Silva ◽  
L. D'Antonino ◽  
L.A. Faustino ◽  
A.A. Silva ◽  
F.A. Ferreira ◽  
...  
Keyword(s):  
Logistic Model ◽  
Dry Matter ◽  
Sorption Process ◽  
Inert Material ◽  
Sorghum Vulgare ◽  
Agronomic Efficiency ◽  
Brazilian Soils ◽  
Plant Poisoning ◽  
Different Soils

The study of the dynamics of a herbicide in the soil focus on the interactions with environmental components to obtain agronomic efficiency, ensuring selectivity to the culture and risk reduction of environmental impact. This study evaluated the sorption process of fomesafen in the Brazilian soils Ultisol, Cambisol, and Organosol. Besides soil, washed sand was used as an inert material for determination of the sorption ratio of fomesafen in the soil. The bioassay method was applied, using Sorghum vulgare plants as bio-indicator of herbicide presence. Plant poisoning evaluation and harvest for dry matter determination were carried out 21 days after sorghum sowing. To calculate C50, the nonlinear log-logistic model was applied and sorption ratios of the herbicide were obtained in different soils. The decreasing sorption ratio of formesafen in the soils was: Organosol > Ultisol > Cambisol. It was concluded that the contents of organic matter and clay in the soils were the attributes that most influenced fomesafen sorption.

scholarly journals COVID-19: Estimation of the Actual Onset of Local Epidemic Cycles, Determination of Total Number of Infective, and Duration of the Incubation Period

2020 ◽  
Author(s):  
Rogerio Atem De Carvalho ◽  
Eduardo Atem De Carvalho
Keyword(s):  
Incubation Period ◽  
Statistical Models ◽  
Average Method ◽  
Logistic Model ◽  
Moving Average ◽  
Lag Time ◽  
Inventory Model ◽  
Actual Number ◽  
Initial Value

Background: Most studies of the epidemic cycles of the pandemic of Sars-CoV-2, or COVID-19 as it became known, define the beginning of specific cycles in countries from the laboratory identification of the first cases of infection, however, there is the awareness that cycles may have started earlier, without proper identification. This influences all the parameters that govern the statistical models used for controlling the infection. Purpose: This work proposes two models based on experimental data. The Logistic Model it is used to obtain three parameters of the epidemic cycle of COVID-19, namely: the final count for the total infected, the daily infection rate and the lag time. Complimentary, a novel inventory model is proposed to calculate the number of infective persons, as well as to determine the incubation period. Methods: The data on epidemic cycles of Germany, Italy, and Sweden are treated previously by the Moving Average Method with Initial value (MAMI), then a variation of the Logistic Model, obtained through curve-fitting, is used to obtain the three parameters. The inventory model is introduced to calculate the actual number of infected persons and the behavior of the incubation period is analyzed. Results: After comparing data from the three countries it is possible to determine the actual probable dates of the beginning of the epidemic cycles for each one, determine the size of the incubation period, as well as to determine the total number of infective persons during the cycle. Conclusions: The actual probable dates of the beginning of the epidemic cycles in the countries analyzed are determined, the total number of infected is determined, and it is statistically proven that the incubation cycle for Sars-CoV-2 is five days.

scholarly journals Deposition of bodily chemical components in the carcass of tilapia (Oreochromis sp.) strains

2014 ◽  
Vol 38 (5) ◽  
pp. 487-496 ◽  
Author(s):  
Ivan Bezerra Allaman ◽  
Rafael Vilhena Reis Neto ◽  
Rilke Tadeu Fonseca de Freitas ◽  
Priscila Vieira Rosa ◽  
Aline de Assis Lago ◽  
...  
Keyword(s):  
Logistic Model ◽  
Chemical Deposition ◽  
The Other ◽  
Chemical Components ◽  
Ash Deposition ◽  
Von Bertalanffy ◽  
Balanced Diet ◽  
Commercial Strain ◽  
Genetic Strains

The knowledge of how animals deposited chemical components as water, protein, fat and ash in the carcass is importance for the formulation of a balanced diet, allowing maximum performance with a low environmental impact. So, the study was carried out to evaluate the influence of different tilapia strains (Chitralada, Commercial, Red and Universidade Federal de Lavras [UFLA]) on the deposition of bodily chemical components in the carcass. The bodily components analyzed were water, protein, fat and ash. For the determination of the bodily chemical deposition curves by age, the exponential, Brody, logistic, Gompertz and von Bertalanffy models were adjusted. The Commercial and UFLA strains deposited water at a faster speed (P<0.05) compared with the remaining strains. As for protein, the Red strain had a lower estimated maturity weight (49.37 g), and was more precocious (202 days) with regard to maximum deposition in comparison to the other strains (Chitralada, UFLA and Commercial) in which there was an estimated maturity weight of 231.5 g and maximum depositionfor 337 days. There were no differences (P>0.05) for the logistic model parameter between Red, UFLA and Commercial strains for fat, which presented a maximum fat deposition (0.23 g) at 310 days of age. Regarding ash deposition, the Commercial strain presented a higher maximum deposition (0.10 g) at 337 days, occurring later than the other strains that presented maximum deposition (0.033g) at 254 days of age. Thus, it was concluded that the genetic strains evaluated differ in chemical deposition curves of water, protein, fat and ash.

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