Controlled Release Study on Bifidocin A from a Polyvinyl Alcohol/Chitosan Blend Particle-Based Biodegradable and Active Packaging Coupled with Mechanistic Assessment and Experimental Modeling

On the basis of PVA-CS, which is incorporated with Bifidocin A, anti-microbial biodegradable films were prepared, characterized by their abilities to control the Bifidocin A’s total release rate into foods as needed for packaging of active foods. This study aimed to explore the anti-microbial effects and release kinetics of active substances in polyvinyl alcoholchitosan (PVA-CS) particle composite films added with Bifidocin A. Pseudomonas fluorescens was used as indicator bacteria to evaluate the anti-microbial activity of the films. Fick’s law, power law and negative exponential growth model were applied to further study the release kinetics of Bifidocin A. The results revealed that the composite films of PVA and CS had better mechanical properties and anti-microbial activity when the content of Bifidocin A was 50% with 1:1 PVA/CS, but it impairs the structure of the film, which can be resolved by including a suitable amount of grycerol. The anti-microbial was released faster at higher temperature and concentration of Bifidocin A, and the diffusion coeffcients increased significantlywith the increase of temperature and concentration. According to the thermodynamic parameters, the release of Bifidocin A was endothermic and spontaneous. High correlation factors (R2 > 0.99) were acquired by fitting the release data of the Bifidocin A with the negative exponential growth model. The potential of Bifidocin A to deliver from the films into the food analog appropriately at low temperatures favored the obtained active films to be applied on food packaging, especially suitable for refrigerated foods.

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The Effect of Roxarsone on Soil Enzyme Activities

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.155-156.917 ◽

2012 ◽

Vol 155-156 ◽

pp. 917-921

Author(s):

J.X. Sun ◽

L.Z. Guan ◽

Y. Zhang ◽

Guang Cai Zhang

Keyword(s):

Incubation Period ◽

Growth Model ◽

Exponential Growth ◽

Enzyme Activities ◽

Urease Activity ◽

Simulation Experiment ◽

Soil Enzyme ◽

Soil Enzyme Activities ◽

Exponential Growth Model ◽

Negative Exponential

An indoor simulation experiment has been carried out to study the effects of Roxarsone on the soil neutral phosphatase, catalase and urease activity. The result showed that the enzyme activities were reduced by the Roxarsone, and the effect degree was aggravated with the increasing consistency. It also showed that inhibition of various enzymes on the rise - decrease trend during the whole incubation period reached its peak on the tenth day as 54.71%,33.92% and 13.81% sorting the phosphatase, the catalase and the urease in a descending order consulting the enzyme sensitivity to Roxarsone. Taking the ED10 as an example, which is 18.83, 48.31 and 185.2 mg.kg-1 on the tenth day: Negative exponential growth model were used to fit the regression rate of enzyme activities with time indicating that the time of Roxarsone toxic effects on soil enzyme extended with the consistency being increased.

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Estimating COVID-19 cases infected with the variant alpha (VOC 202012/01): an analysis of screening data in Tokyo, January-March 2021

Theoretical Biology and Medical Modelling ◽

10.1186/s12976-021-00146-x ◽

2021 ◽

Vol 18 (1) ◽

Author(s):

Hiroaki Murayama ◽

Taishi Kayano ◽

Hiroshi Nishiura

Keyword(s):

Confidence Interval ◽

Growth Model ◽

Exponential Growth ◽

Reproduction Number ◽

Hypergeometric Distribution ◽

Actual Number ◽

Growth Data ◽

Exponential Growth Model

Abstract Background In Japan, a part of confirmed patients’ samples have been screened for the variant of concern (VOC), including the variant alpha with N501Y mutation. The present study aimed to estimate the actual number of cases with variant alpha and reconstruct the epidemiological dynamics. Methods The number of cases with variant alpha out of all PCR confirmed cases was estimated, employing a hypergeometric distribution. An exponential growth model was fitted to the growth data of variant alpha cases over fourteen weeks in Tokyo. Results The weekly incidence with variant alpha from 18–24 January 2021 was estimated at 4.2 (95% confidence interval (CI): 0.7, 44.0) cases. The expected incidence in early May ranged from 420–1120 cases per week, and the reproduction number of variant alpha was on the order of 1.5 even under the restriction of contact from January-March, 2021, Tokyo. Conclusions The variant alpha was predicted to swiftly dominate COVID-19 cases in Tokyo, and this has actually occurred by May 2021. Devising the proposed method, any country or location can interpret the virological sampling data.

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Controlled Release of Antimicrobial Compounds from Highly Swellable Polymers

Journal of Food Protection ◽

10.4315/0362-028x-67.6.1190 ◽

2004 ◽

Vol 67 (6) ◽

pp. 1190-1194 ◽

Cited By ~ 45

Author(s):

G. G. BUONOCORE ◽

M. SINIGAGLIA ◽

M. R. CORBO ◽

A. BEVILACQUA ◽

E. LA NOTTE ◽

...

Keyword(s):

Polymer Matrix ◽

Sodium Benzoate ◽

Food Packaging ◽

Microbial Growth ◽

Release Kinetics ◽

Multilayer Structures ◽

Cross Link ◽

Active Compounds ◽

Antimicrobial Efficiency ◽

Kinetics Of

The suitability of antimicrobial release films made from highly swellable polymers for use in food packaging was evaluated. The possibility of modulating the release kinetics of active compounds either by regulating the degree of cross-link of the polymer matrix or by using multilayer structures was addressed. The release kinetics of lysozyme, nisin, and sodium benzoate (active compounds with different molecular weights) were determined at ambient temperature (25°C). The effectiveness of the proposed active films in inhibiting microbial growth was addressed by determining the antimicrobial efficiency of the released active compounds. Micrococcus lysodeikticus, Alicyclobacillus acidoterrestris, and Saccharomycescerevisiaewere used to test the antimicrobial efficiency of released lysozyme, nisin, and sodium benzoate, respectively. Results indicate that the release kinetics of both lysozyme and nisin can be modulated through the degree of cross-link of the polymer matrix, whereas multilayer structures need to be used to control the release kinetics of sodium benzoate. All the active compounds released from the investigated active films were effective in inhibiting microbial growth.

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Estimated Effect of COVID-19 Lockdown on Skin Tumor Size and Survival: An Exponential Growth Model

Actas Dermo-Sifiliográficas (English Edition) ◽

10.1016/j.adengl.2020.09.008 ◽

2020 ◽

Vol 111 (8) ◽

pp. 629-638

Author(s):

A. Tejera-Vaquerizo ◽

J. Cañueto ◽

A. Toll ◽

J. Santos-Juanes ◽

A. Jaka ◽

...

Keyword(s):

Growth Model ◽

Exponential Growth ◽

Tumor Size ◽

Skin Tumor ◽

Exponential Growth Model

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Bayesian D-optimal designs for the exponential growth model

Journal of Statistical Planning and Inference ◽

10.1016/0378-3758(94)00056-2 ◽

1995 ◽

Vol 44 (3) ◽

pp. 385-397 ◽

Cited By ~ 24

Author(s):

Saurabh Mukhopadhyay ◽

Linda M. Haines

Keyword(s):

Growth Model ◽

Exponential Growth ◽

Optimal Designs ◽

Exponential Growth Model

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Models for Predicting Global Plastic Waste

Aresty Rutgers Undergraduate Research Journal ◽

10.14713/arestyrurj.v1i2.154 ◽

2021 ◽

Vol 1 (2) ◽

Author(s):

Yuexing Hao ◽

Glenn Shafer

Keyword(s):

Growth Model ◽

Real World ◽

Exponential Growth ◽

Plastic Waste ◽

The Self ◽

Scientific Models ◽

Adaptive Model ◽

The Real ◽

Exponential Growth Model ◽

Self Adaptive

For more than half a century, plastic prod-ucts have been a part of people’s lives. When plastic waste is thrown into nature, it can cause a sequence of dangerous effects. Previous researchers esti-mated that global plastic waste in 2020 will be more than 400 million tons. To reduce plastic waste, they built scientific models to analyze the sources of plas-tic and provided solutions for regenerating these plastic wastes. However, their models are static and inaccurate, which may cause some false predictions.In this paper, we first observe the distribution of the real-world plastic waste data. Then, we build simple exponential growth model and logistics model to match these data. By testing different models on our plots, we discover that the SELF-ADAPTIVE MODEL is the best to describe and correctly predict our future plastic waste production, as this model combines the benefits of SIMPLE EXPONENTIAL GROWTH MODEL and the LOGISTIC MODEL. The self-Adaptive model has the potential to minimize the error rate and make the predictions more accurate. Based on this model, we can develop more accurate and informative solu-tions for the real-world plastic problems.

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Predicting the COVID-19 positive cases in India with concern to Lockdown by using Mathematical and Machine Learning based Models

10.1101/2020.05.16.20104133 ◽

2020 ◽

Cited By ~ 1

Author(s):

Ajit Kumar Pasayat ◽

Satya Narayan Pati ◽

Aashirbad Maharana

Keyword(s):

Machine Learning ◽

Linear Regression ◽

Regression Model ◽

Growth Model ◽

Linear Regression Model ◽

Exponential Growth ◽

Time Window ◽

Epidemic Curve ◽

First Case ◽

Exponential Growth Model

In this study, we analyze the number of infected positive cases of COVID-19 outbreak with concern to lockdown in India in the time window of February 11th 2020 to Jun 30th 2020. The first case in India was reported in Kerala on January 30th 2020. To break the chain of spreading, Government announced a nationwide lockdown on March 24th 2020, which is increased two times. The Ongoing lockdown 3.0 is over on May 18th, 2020. We derived how the lockdown relaxation is going to impact on containment of the outbreak. Here the Exponential Growth Model has been used to derive the epidemic curve based on the data collected from February 11th 2020, to May 11th 2020, and the Machine Learning based Linear Regression model that gives the epidemic curve to predict the cases with the continuous flow of the lockdown. We estimate that if the lockdown is continuing with more relaxation, then the estimated infected cases reach up to 1.16 crores by June 30th 2020, and the lockdown would persist with current restriction, then the expected predicted infected cases are 5.69 lacs. The Exponential Growth Model and the Linear Regression Model are advantageous to predict the number of affected cases of COVID-19. These models can be used for forecasting in long term intervals. It shows from our result that lockdown with certain restriction has a vital role in preventing the spreading of this epidemic in this current situation.

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Pectin-gellan films intended for active food packaging: release kinetics of nisin and physico-mechanical characterization

Journal of Food Science and Technology ◽

10.1007/s13197-020-04800-z ◽

2020 ◽

Author(s):

Lorena Rivera-Hernández ◽

Norberto Chavarría-Hernández ◽

Ma del Rocío López Cuellar ◽

Víctor Manuel Martínez-Juárez ◽

Adriana-Inés Rodríguez-Hernández

Keyword(s):

Food Packaging ◽

Mechanical Characterization ◽

Release Kinetics ◽

Active Food Packaging ◽

Kinetics Of

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Production of annual ryegrass with different doses of nitrogen fertilization in topdressing

Semina Ciências Agrárias ◽

10.5433/1679-0359.2019v40n3p1329 ◽

2019 ◽

Vol 40 (3) ◽

pp. 1329

Author(s):

Delvacir Rezende Bolke ◽

Ione Maria Pereira Haygert-Velho ◽

Luiz Carlos Timm ◽

Dileta Regina Moro Alessio ◽

Andréa Mittelmann ◽

...

Keyword(s):

Growth Model ◽

Exponential Growth ◽

Lolium Multiflorum ◽

Block Design ◽

Control Treatment ◽

Time Interval ◽

Annual Ryegrass ◽

Nitrogen Application ◽

Exponential Growth Model ◽

Different Doses

The objective of this study was to assess the growth of annual ryegrass (Lolium multiflorum) cv. BRS Ponteio with different doses of nitrogen applied in the pasture, thereby adjusting their growth to the exponential growth model. A randomized block design was used with five nitrogen application rates (0, 150, 250, 350, and 450 kg N ha-1) and four replicates, applied in installments. Each plot measured 9 m2. On April 15, 2014, 25 kg ha-1 of viable pure seeds of annual ryegrass were sown at a depth of 0.02 m, in 18 rows spaced at 0.17 m in each plot. Growth in the control treatment (zero nitrogen) pasture lasted 167 days with only three cuts, whereas in pastures treated with 350 and 450 kg N ha-1, growth was extended for an additional 45 days with a 333% increase in the number of cuts. The pastures were used for the same duration (188 days) in the treatments with 150 and 250 kg N ha-1, however, increased nitrogen resulted in two additional cuts and a shorter time interval between cuts. The time interval between each cut and the degree-days interacted dynamically causing distinct growth. Growth of the annual ryegrass BRS Ponteio without nitrogen application is poor and cannot be represented even by a first order linear model. The application of nitrogen topdressing, in the form of urea, decreases the time interval between cuts, increases the dry matter production per hectare, stimulates this production, and follows the exponential growth model.

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