COVID-19 em Londrina-PR: Modelo SEIR com Otimização de Parâmetros

The first cases of COVID-19 in Londrina-PR were manifested in March 2020 and the disease lasts until the present moment. We aim to inform citizens in a scientific way about how the disease spreads. The present work seeks to describe the behavior of the disease over time. We started from a compartmental model of ordinary differential equations like SEIR to find relevant information such as: transmission rates and prediction of the peak of infected people. We used the data released by city hall of Londrina to carry out simulations in periods of 14 days, applying a parameter optimization technique to obtain results with the greatest possible credibility.

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Modeling quarantine during epidemics and mass-testing using drones

10.1101/2020.04.15.20067025 ◽

2020 ◽

Cited By ~ 2

Author(s):

Leonid Sedov ◽

Alexander Krasnochub ◽

Valentin Polishchuk

Keyword(s):

Differential Equations ◽

Metropolitan Area ◽

Extended Model ◽

Epidemic Spread ◽

Infected People ◽

Peak Number ◽

Infected Population ◽

Sir Epidemic ◽

Spread Model ◽

Over Time

We extend the classical SIR epidemic spread model by introducing the “quarantined” compartment. We solve (numerically) the differential equations that govern the extended model and quantify how quarantining “flattens the curve” for the proportion of infected population over time. Furthermore, we explore the potential of using drones to deliver tests, enabling mass-testing for the infection; we give a method to estimate the drone fleet needed to deliver the tests in a metropolitan area. Application of our models to COVID-19 spread in Sweden shows how the proposed methods could substantially decrease the peak number of infected people, almost without increasing the duration of the epidemic.

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Estimation and prediction of COVID-19 cases in Brazilian metropolises

Revista Latino-Americana de Enfermagem ◽

10.1590/1518-8345.4501.3345 ◽

2020 ◽

Vol 28 ◽

Author(s):

George Jó Bezerra Sousa ◽

Thiago Santos Garces ◽

Virna Ribeiro Feitosa Cestari ◽

Thereza Maria Magalhães Moreira ◽

Raquel Sampaio Florêncio ◽

...

Keyword(s):

Differential Equations ◽

Preventive Measures ◽

Transmission Rate ◽

Model Fit ◽

Health Needs ◽

Infected People ◽

Transmission Rates ◽

Estimation And Prediction ◽

First Case ◽

Rapid Spread

Objective to estimate the transmission rate, the epidemiological peak, and the number of deaths by the new coronavirus. Method a mathematical and epidemiological model of susceptible, infected, and recovered cases was applied to the nine Brazilian capitals with the highest number of cases of the infection. The number of cases for the 80 days following the first case was estimated by solving the differential equations. The results were logarithmized and compared with the actual values to observe the model fit. In all scenarios, it was considered that no preventive measures had been taken. Results the nine metropolises studied showed an upward curve of confirmed cases of COVID-19. The prediction data point to the peak of the infection between late April and early May. Fortaleza and Manaus had the highest transmission rates (≥2·0 and ≥1·8, respectively). Rio de Janeiro may have the largest number of infected people (692,957) and Florianópolis the smallest (24,750). Conclusion the estimates of the transmission rate, epidemiological peak, and number of deaths from coronavirus in Brazilian metropolises presented expressive and important numbers the Brazilian Ministry of Health needs to consider. The results confirm the rapid spread of the virus and its high mortality in the country.

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Optimal Force Distribution for Payload Positioning Using a Planar Dual-Arm Robot

Journal of Dynamic Systems Measurement and Control ◽

10.1115/1.3153038 ◽

1989 ◽

Vol 111 (2) ◽

pp. 205-210 ◽

Cited By ~ 18

Author(s):

C. R. Carignan ◽

D. L. Akin

Keyword(s):

Differential Equations ◽

Parameter Optimization ◽

Optimization Technique ◽

Force Distribution ◽

Torque Distribution ◽

Optimal Force ◽

Dual Arm Robot ◽

Arm Transport ◽

Dual Arm ◽

Optimal Force Distribution

This paper presents a parameter optimization technique for deciding the force distribution on a payload being transported along a predetermined trajectory using two planar manipulator arms. The methodology begins by transforming the singular dynamics of two-arm transport to an ordinary set of differential equations and then proceeds to obtain a relation between the torques exerted by each arm. This relation is then used in a quadratic torque cost which is subsequently minimized to yield an optimal torque distribution. Significant savings in energy were found to occur when the arms were allowed to interact by transmission of forces through the payload. Even more significant are the savings found over one-arm transport of payloads where the arm torques are fixed by the prescribed trajectory.

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On attracting sets in artificial networks: cross activation

ITM Web of Conferences ◽

10.1051/itmconf/20181601005 ◽

2018 ◽

Vol 16 ◽

pp. 01005

Author(s):

Felix Sadyrbaev

Keyword(s):

Dynamical Systems ◽

Differential Equations ◽

Mathematical Models ◽

Ordinary Differential Equations ◽

Critical Points ◽

Regulatory Networks ◽

Main Diagonal ◽

Sigmoidal Function ◽

Genomic Regulatory Networks ◽

Over Time

Mathematical models of artificial networks can be formulated in terms of dynamical systems describing the behaviour of a network over time. The interrelation between nodes (elements) of a network is encoded in the regulatory matrix. We consider a system of ordinary differential equations that describes in particular also genomic regulatory networks (GRN) and contains a sigmoidal function. The results are presented on attractors of such systems for a particular case of cross activation. The regulatory matrix is then of particular form consisting of unit entries everywhere except the main diagonal. We show that such a system can have not more than three critical points. At least n–1 eigenvalues corresponding to any of the critical points are negative. An example for a particular choice of sigmoidal function is considered.

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Dual-shaped offset synthesis using parameter optimization of the solutions to the first-order geometrical optics partial differential equations

10.1109/aps.1990.115144 ◽

1990 ◽

Author(s):

K. Shogen ◽

R. Mittra ◽

V. Galindo-Israel ◽

W. Imbriale

Keyword(s):

Partial Differential Equations ◽

Differential Equations ◽

Parameter Optimization ◽

Geometrical Optics ◽

Partial Differential ◽

First Order

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A Bird’s Eye View of 100 years of research on Hypertension: Machine Learning Classifications of Topics (Preprint)

10.2196/preprints.31292 ◽

2021 ◽

Author(s):

Mustapha Abba ◽

Chidozie Nduka ◽

Seun Anjorin ◽

Shukri Mohamed ◽

Emmanuel Agogo ◽

...

Keyword(s):

Machine Learning ◽

Latent Dirichlet Allocation ◽

Learning Algorithm ◽

Temporal Trends ◽

Relevant Information ◽

Research Articles ◽

Major Cardiovascular Events ◽

And Shifts ◽

Negative Sentiment ◽

Over Time

BACKGROUND Due to scientific and technical advancements in the field, published hypertension research has developed during the last decade. Given the huge amount of scientific material published in this field, identifying the relevant information is difficult. We employed topic modelling, which is a strong approach for extracting useful information from enormous amounts of unstructured text. OBJECTIVE To utilize a machine learning algorithm to uncover hidden topics and subtopics from 100 years of peer-reviewed hypertension publications and identify temporal trends. METHODS The titles and abstracts of hypertension papers indexed in PubMed were examined. We used the Latent Dirichlet Allocation (LDA) model to select 20 primary subjects and then ran a trend analysis to see how popular they were over time. RESULTS We gathered 581,750 hypertension-related research articles from 1900 to 2018 and divided them into 20 categories. Preclinical, risk factors, complications, and therapy studies were the categories used to categorise the publications. We discovered themes that were becoming increasingly ‘hot,' becoming less ‘cold,' and being published seldom. Risk variables and major cardiovascular events subjects displayed very dynamic patterns over time (how? – briefly detail here). The majority of the articles (71.2%) had a negative valency, followed by positive (20.6%) and neutral valencies (8.2 percent). Between 1980 and 2000, negative sentiment articles fell somewhat, while positive and neutral sentiment articles climbed significantly. CONCLUSIONS This unique machine learning methodology provided fascinating insights on current hypertension research trends. This method allows researchers to discover study subjects and shifts in study focus, and in the end, it captures the broader picture of the primary concepts in current hypertension research articles. CLINICALTRIAL Not applicable

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Elaboration of stochastic models to comprehensive evaluation of occupational risks in complex dynamic systems

Journal of Achievements of Materials and Manufacturing Engineering ◽

10.5604/01.3001.0014.8484 ◽

2021 ◽

Vol 1 (104) ◽

pp. 31-41

Author(s):

A.P. Bochkovskyi

Keyword(s):

Differential Equations ◽

Markov Processes ◽

Stochastic Models ◽

Comprehensive Evaluation ◽

System Of Differential Equations ◽

Partial Derivatives ◽

Occupational Risks ◽

The Impact ◽

Negative Factors ◽

Over Time

Purpose: Elaborate stochastic models to comprehensive evaluation of occupational risks in “man - machine - environment” systems taking into account the random and dynamic nature of the impact on the employee of negative factors over time. Design/methodology/approach: Within study, the methods of probability theory and the theory of Markov processes - to find the limit distribution of the random process of dynamic impact on the employee of negative factors over time and obtain main rates against which the level of occupational risks within the "man - machine - environment" systems can be comprehensively evaluated; Erlang phases method, Laplace transform, difference equations theory, method of mathematical induction - to elaborate a method of analytical solution of the appropriate limit task for a system of differential equations in partial derivatives and appropriate limit conditions were used. Findings: A system of differential equations in partial derivatives and relevant limit conditions is derived, which allowed to identify the following main rates for comprehensive evaluation of occupational risks in systems "man - machine - environment": probability of excess the limit of the employee's accumulation of negative impact of the harmful production factor; probability of the employee’s injury of varying severity in a random time. An method to the solution the limit task for a system of differential equations, which allows to provide a lower bounds of the probability of a certain occupational danger occurrence was elaborated. Research limitations/implications: The elaborated approach to injury risk evaluation is designed to predict cases of non-severe injuries. At the same time, this approach allows to consider more severe cases too, but in this case the task will be more difficult. Practical implications: The use of the elaborated models allows to apply a systematic approach to the evaluation of occupational risks in enterprises and to increase the objectivity of the evaluation results by taking into account the real characteristics of the impact of negative factors on the employee over time. Originality/value: For the first time, a special subclass of Markov processes - Markov drift processes was proposed and substantiated for use to comprehensive evaluation of occupational risks in “man - machine - environment” systems.

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