This study examines the impact of Economic Sustainability Plan (ESP) on the performance of the Nigerian economy as a national economic resilient policy in the post COVID-19 era within the framework of a macro, model. The study is hinged on the Keynesian general theory of employment, income and interest. Annual time series data spanning from 1970 to 2019 for within sample forecast, and a six-year out-of-sample forecast spanning from 2020 to 2025 were used. The policy scenario of 21.3 percent increase in government expenditure under the ESP as a stimulus package was simulated and the findings showed that increase in government expenditure under the ESP in critical areas would bring about significant impact on the macroeconomic performance of the Nigerian economy, especially on employment, inflation, economic growth and balance of payment in the post COVID-19 era. Emergent from these findings, the study recommended among others that the government should mobilize resources to finance the ESP in order to stimulate the economy in the post COVID-19 era by ensuring prudential fiscal management of resources; and the Central Bank of Nigeria (CBN) should ensure that financial institutions saddled with the responsibility of disbursement of intervention funds reduce interest rate from 9 percent to 5 percent as reflected in the ESP.
We propose a probabilistic approach to modelling the propagation of the coronavirus disease 2019 (COVID-19) in Madagascar, with all its specificities. With the strategy of the Malagasy state, which consists of isolating all suspected cases and hospitalized confirmed case, we get an epidemic model with seven compartments: susceptible (S), Exposed (E), Infected (I), Asymptomatic (A), Hospitalized (H), Cured (C) and Death (D). In addition to the classical deterministic models used in epidemiology, the stochastic model offers a natural representation of the evolution of the COVID-19 epidemic. We inferred the models with the official data provided by the COVID-19 Command Center (CCO) of Madagascar, between March and August 2020. The basic reproduction number R0 and the other parameters were estimated with a Bayesian approach. We developed an algorithm that allows having a temporal estimate of this number with confidence intervals. The estimated values are slightly lower than the international references. Generally, we were able to obtain a simple but effective model to describe the spread of the disease.
For Madagascar, with the uncertainty over vaccines against the novel coronavirus 2019 and its variants, non-pharmaceutical approach are widely used. Our objective is to propose a mathematical control model which will serve as a tool to help decision-makers in the strategy to be implemented to better face the pandemic. By separating asymptomatic cases which are often not reported and symptomatic who are hospitalized after tests; we develop a mathematical model of the propagation of covid-19 in Madagascar, by integrating control strategies. We study the stability of the model by expressing the basic reproduction number using the next-generation matrix. Simulation with different parameters, shows the effects of non-pharmaceutical measures on the speed of the disease spread. By integrating a control parameter linked to compliance with barrier measures in the virus propagation equation, we were able to show the impacts of the implementation of social distancing measures on the basic reproduction number. The strict application of social distancing measures and total confinement are unfavorable for economic situation even if they allow the contamination to be reduced quickly. Without any restrictions, the disease spreads at high speed and the peak is reached fairly quickly. In this condition, hospitals are overwhelmed and the death rate increases rapidly. With 50% respect for non-pharmaceutical strategies such as rapid detection and isolation of positive cases and barrier gestures; the basic reproduction number R_0 can go down from 3 to 1.7. The pressures on the economic and social situation are rather viable. It is the most suitable for the Malagasy health system. The results proposed are a way to control the spread of the disease and limit its devastation in a country like Madagascar.
Thomas-Fermi theory is an approximate method, which is widely used to describe the properties of matter at various hierarchical levels (atomic nucleus, atom, molecule, solid, etc.). Special development is achieved using Thomas-Fermi theory to the theory of extreme states of matter appearing under high pressures, high temperatures or strong external fields. Relevant sections of physics and related sciences (astrophysics, quantum chemistry, a number of applied sciences) determine the scope of Thomas-Fermi theory. Popularity Thomas-Fermi theory is related to its relative simplicity, clarity and versatility. The latter means that the result of the calculation by Tho-mas-Fermi theory applies immediately to all chemical elements: the transition from element to element is as simple scale transformation. These features make it to be a highly convenient tool for qualitative and, in many cases, and quantitative analysis.
In order to improve the adaptability of the tracked vehicle in the road and strengthen the grip of the tracked vehicle, a track surface adaptive mechanism was provided. In theory, it has been proved practically. Meanwhile, RecurDyn, which is a multi-body kinematics software, was used to build a multi-body soft hybrid model, based on structure, elasticity, linear damping adaptive tracked vehicle; meanwhile the model was used to carry on the kinematics simulation. Through the comparison between simulated motion trail and that of traditional motion trail, this paper analyzed the deviation of the motion trail and also simulated the motion trail of the warped surface so as to test the adaptive ability of the mechanism. According to the results, the adaptive mechanism was equipped with great surface adaptability. It can also adapt to the complex warped surface, and enjoy a damping effect.
An agent-based simulation model hierarchy emulating disease states and behaviors critical to progression of diabetes type 2 was designed and implemented in the DEVS framework. This model was built to approximately reproduce some essential findings that were previously reported for a rather complex model of diabetes progression. Our models are translations of basicelements of this previously reported system dynamics model of diabetes. The system dynamics model, which mimics diabetes progression over an aggregated US population, was disaggregated and reconstructed bottom-up at the individual (agent) level. Four levels of model complexity were defined in order to systematically evaluate which parameters are needed to mimic outputs of the system dynamics model. The four estimated models attempted to replicate stock counts representing disease states in the system dynamics model while estimating impacts of an elderliness factor, obesity factor and health-related behavioral parameters. Health-related behavior was modeled as a simple realization of the Theory of Planned Behavior, a joint function of individual attitude and diffusion of social norms that spread over each agent’s social network. Although the most complex agent-based simulation model contained 31 adjustable parameters, all models were considerably less complex than the system dynamics model which required numerous time series inputs to make its predictions. All three elaborations of the baseline model provided significantly improved fits to the output of the system dynamics model, although behavioral factors appeared to contribute more than the elderliness factor. The results illustrate a promising approach to translate complex system dynamics models into agent-based model alternatives that are both conceptually simpler and capable of capturing main effects of complex local agent-agent interactions.
The selection and comparison of different growth models for describing weight gain of piglets raised in organic farming is investigated by using the Akaike's Information Criterion (AIC). In total, 49,699 data points of 5188 piglets recorded between 2007 and 2013 were considered. From the day of birth, up to 40 days (i.e. until weaning) the model of von Bertalanffy was favored by the AIC. This model is with 60.32% more likely to truly reflect reality than any other of the analyzed models. Up to 105 days, the two-linear model was favored by the AIC (probability 99.75%). The intersection point of the two-linear model was calculated by 53.8 days, which fitted well to the actual change in the food situations.
In this paper, a new two-parameter distribution called generalized power Akshaya distribution extended from Akshaya distribution is introduced. This distribution is proposed to model lifetime data. Statistical properties like density, hazard, survival and moments are derived. Two parameters estimation is introduced using maximum likelihood and Bayesian techniques. Finally, an application of real data and a simulation study are introduced to illustrate the usefulness of the proposed distribution.
In order to know the current collaborative development situation and relationship of E-commerce and logistics, the paper evaluates the whole collaborative development level of Chinese E-commerce and logistics from 2008 to 2014 using the DEA model. Fund, infrastructure, labor and collaborative development are evaluated and analyzed in this model. The research indicates that E-commerce facilitates the logistics development but logistics can’t support E-commerce development well due to the lag effect which leads to lower collaborative development level. So optimizing the ratio of logistics investment and output, promoting logistics service quality and accelerating logistics development have been the key factors for promoting the collaborative development of E-commerce and logistics.
In this paper, we consider r -generalization of the central factorial numbers with odd arguments of the first and second kind. Mainly, we obtain various identities and properties related to these numbers. Matrix representation and the relation between these numbers and Pascal matrix are given. Furthermore, the distributions of the signless r-central factorial numbers are derived. In addition, connections between these numbers and the Legendre-Stirling numbers are given.
The present study deals with the unsteady dynamics of cavitation around the NACA 0015 hydrofoil in a channel. A finite element model is proposed to solve the governing equations of momentum and mass conservation. Turbulent flows around the hydrofoil are described by the Prandtl-Kolmogorov model. The cavitation phenomenon is modeled through a mixture model involving liquid and vapor flows and the Zwart-Gerber-Belamri (ZGB) model is considered to evaluate the transport of the water vapor fraction. The variational finite element model formulation includes the mixing of the characteristic method and the finite element. Also, at the open sides of the channel flow, an open boundary condition is imposed. Numerical experiments are performed for cavitation numbers 0.8 and 0.4. The presented model predicts the essential features of unsteady cavitating flows, the generation of vapor cavities, the time-dependent oscillations of the variables and the presence of vortical flow structures associated to vapor volume concentrations during the shedding process.
Under the possible hydrological conditions, with a design hyetograph of 3-month average rainfall intensities of Singapore, multiple regression equations on hydrological processes, specifically on overflow volume, average vertical ex-filtration rate and horizontal flow coefficient, of a soak-away rain garden are established based on simulated results of a mathematical model. The model that is based on Richard's equation is developed using COMSOL Multiphysics. The regression equation on overflow volume and the regression equation on log of horizontal flow coefficient show a very strong relationship with the independent variables (saturated hydraulic conductivity of the filter media, saturated hydraulic conductivity of the in-situ soil, depth to groundwater table, and surface area of the soak-away rain garden). The coefficients of determination of the fitted equations on overflow volume and log of horizontal flow coefficient were 0.992 and 0.986, respectively. However , the regression equation on average vertical ex-filtration rate has high p-values (p-values > significance level, α = 0.01) for saturated hydraulic conductivity of the in-situ soil and surface area of the soak-away rain garden. Thus, forward stepwise regression was used to develop the best regression equation on average vertical ex-filtration rate with saturated hydraulic conductivity of the filter media and depth to groundwater table. The coefficient of determination of the fitted equation was found to be 0.911. These easy to use regression equations will be of great utility for local mangers in the design of soak-away rain gardens.
Nowadays death of a newborn baby due to hypothermia is one of the vital factors. To overcome the problem infant radiant warmer has been used in hospitals which helps to prevent excessive heat loss of the baby by maintaining a proper temperature. However, in practice, it is critical to regulating proper thermal stability that is exactly required for a premature baby to conquer the heat loss problem. In this study, we have established a computational model for heat transfer analysis using the Finite Element Method. The heat transfer to the surrounding area skin of newborn with the help of Infant Radiant Warmer (IRW) is simulated to study the best range of light source to overcome the hypothermia. We simulate the efficiency and effect of the infant radiant of the thermal radiation using COMSOL Multiphysics program. For this simulation, we considered the distance between the infant’s mattress and the bottom surface of the heater unit as 70 cm and the heater power 500 watts, and 600 watts. We have investigated mattress temperature, baby temperature and surface radiosity which are important to understand to increase newborn baby body temperature. It is found that the temperature of mattress raises up to 36 - 36.5 degrees Celsius and skin temperature raises up to 37 - 37.5 degrees Celsius.
In this article, we derive a boundary element formulation for the pricing of barrier option. The price of a barrier option is modeled as the solution of Black-Scholes’ equation. Then the problem is transformed to a boundary value problem of heat equation with a moving boundary. The boundary integral representation and integral equation are derived. A boundary element method is designed to solve the integral equation. Special quadrature rules for the singular integral are used. A numerical example is also demonstrated. This boundary element formulation is correct.
The previous studies on detection of communities on complex networks were focused on nondirected graphs, such as Neural Networks, social networks, social interrelations, the contagion of diseases, and bibliographies. However, there are also other problems whose modeling entails obtaining a weakly connected directed graph such as the student access to the university, the public transport networks, or trophic chains. Those cases deserve particularized study with an analysis and the resolution adjusted to them. Additionally, this is a challenge, since the existing algorithms in most of the cases were origi-nally designed for non-directed graphs or symmetrical and regular graphs. Our proposal is a Benchmark Generator of Weakly Connected Directed Graphs whose properties can be defined by the end-users according to their necessities. The source code of the generators described in this article is available in GitHub under the GNU license.
(2) (PDF) A Proposal for a Benchmark Generator of Weakly Connected Directed Graphs. Available from: https://www.researchgate.net/publication/338325513_A_Proposal_for_a_Benchmark_Generator_of_Weakly_Connected_Directed_Graphs [accessed Dec 04 2020].
In this paper, some theoretical mathematical aspects of the known predator-prey problem are considered by relaxing the assumptions that interaction of a predation leads to little or no effect on growth of the prey population and the prey growth rate parameter is a positive valued function of time. The predator growth model is derived considering that the prey follows a known growth models viz., Logistic and Von Bertalanffy. The result shows that the predator’s population growth models look to be new functions. For either models, the predator population size either converges to a finite positive limit or to 0 or diverges to +∞. It is shown algebraically and illustrated pictorially that there is a condition at which the predator-prey population models both converge to the same finite limit. Derivations and simulation studies are provided in the paper. Analysis of equilibrium points and stability is also included.
In this paper, we present a generalization of the commonly used growth models. We introduce Koya-Goshu biological growth model, as a more general solution of the rate-state ordinary differential equation. It is shown that the commonly used growth models such as Brody, Von Bertalanffy, Richards, Weibull, Monomolecular, Mitscherlich, Gompertz, Logistic , and generalized Logistic functions are its special cases. We have constructed growth and relative growth functions as solutions of the rate-state equation. The generalized growth function is the most flexible so that it can be useful in model selection problems. It is also capable of generating new useful models that have never been used so far. The function incorporates two parameters with one influencing growth pattern and the other influencing asymptotic behaviors. The relationships among these growth models are studies in details and provided in a flow chart.
In this paper, a new method for adding parameters to a well-established distribution to obtain more flexible new families of distributions is applied to the inverse Lomax distribution (ILD). This method is known by the flexible reduced logarithmic-X family of distribution (FRL-X). The proposed distribution can be called a flexible reduced logarithmic-inverse Lomax distribution (FRL-IL). The statistical and reliability properties of the proposed models are
studied including moments, order statistics, moment generating function, and quantile function. The estimation of the model parameters by maximum likelihood and the observed information matrix are also discussed. In order to assess the potential of the newly created distribution. The extended model is applied to real data and the results are given and compared to other models.
There are many blue shifted Galaxies in our universe. Here we will see old simulations to make such predictions from the output graphs using SITA simulations. There are four new simulations also presented here. In these sets of simulations, different point masses are placed in different distances in a 3D Cartesian coordinate grid; and these point masses are allowed to move on universal gravitation force (UGF) acting on each mass at that instant of time at its position. The output pictures depict the three dimensional orbit formations of point masses after some iterations. In an orbit so formed, some Galaxies are coming near (Blue shifted) and some are going away (Red shifted). In this paper, the simulations predicted the existence of a large number of Blue shifted Galaxies, in an expanding universe, in 2004 itself. Over 8300 blue shifted galaxies have been discovered extending beyond the Local Group by Hubble Space Telescope (HST) in the year 2009. Thus Dynamic Universe model predictions came true.
Several authors have used different classical statistical models to fit the Nigerian
Bonny Light crude oil price but the application of machine learning
models and Fuzzy Time Series model on the crude oil price has been grossly
understudied. Therefore, in this study, a classical statistical model—Autoregressive
Integrated Moving Average (ARIMA), two machine learning models—
Artificial Neural Network (ANN) and Random Forest (RF) and Fuzzy
Time Series (FTS) Model were compared in modeling the Nigerian Bonny
Light crude oil price data for the periods from January, 2006 to December,
2020. The monthly secondary data were collected from the Nigerian National
Petroleum Corporation (NNPC) and Reuters website and divided into train
(70%) and test (30%) sets. The train set was used in building the models and
the models were validated using the test set. The performance measures used
for the comparison include: The modified Diebold-Mariano test, the Root
Mean Square Error (RMSE), the Mean Absolute Percentage Error (MAPE)
and Nash-Sutcliffe Efficiency (NSE) values. Based on the performance measures,
ANN (4, 1, 1) and RF performed better than ARIMA (1, 1, 0) model but
FTS model using Chen’s algorithm outperformed every other model. The results
recommend the use of FTS model for forecasting future values of the
Nigerian Bonny Light Crude oil. However, a hybrid model of ARIMA-ANN
or ARIMA-RF should be built and compared with Chen’s algorithm FTS
model for the same data set to further verify the power of FTS model using