scholarly journals Existence and uniqueness of monotone wavefronts in a nonlocal resource-limited model

2019 ◽  
Vol 150 (5) ◽  
pp. 2462-2483 ◽  
Author(s):  
Elena Trofimchuk ◽  
Manuel Pinto ◽  
Sergei Trofimchuk

AbstractWe are revisiting the topic of travelling fronts for the food-limited (FL) model with spatio-temporal nonlocal reaction. These solutions are crucial for understanding the whole model dynamics. Firstly, we prove the existence of monotone wavefronts. In difference with all previous results formulated in terms of ‘sufficiently small parameters’, our existence theorem indicates a reasonably broad and explicit range of the model key parameters allowing the existence of monotone waves. Secondly, numerical simulations realized on the base of our analysis show appearance of non-oscillating and non-monotone travelling fronts in the FL model. These waves were never observed before. Finally, invoking a new approach developed recently by Solar et al., we prove the uniqueness (for a fixed propagation speed, up to translation) of each monotone front.

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Aziz Khan ◽  
Hashim M. Alshehri ◽  
J. F. Gómez-Aguilar ◽  
Zareen A. Khan ◽  
G. Fernández-Anaya

AbstractThis paper is about to formulate a design of predator–prey model with constant and time fractional variable order. The predator and prey act as agents in an ecosystem in this simulation. We focus on a time fractional order Atangana–Baleanu operator in the sense of Liouville–Caputo. Due to the nonlocality of the method, the predator–prey model is generated by using another FO derivative developed as a kernel based on the generalized Mittag-Leffler function. Two fractional-order systems are assumed, with and without delay. For the numerical solution of the models, we not only employ the Adams–Bashforth–Moulton method but also explore the existence and uniqueness of these schemes. We use the fixed point theorem which is useful in describing the existence of a new approach with a particular set of solutions. For the illustration, several numerical examples are added to the paper to show the effectiveness of the numerical method.


Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 458
Author(s):  
Leobardo Hernandez-Gonzalez ◽  
Jazmin Ramirez-Hernandez ◽  
Oswaldo Ulises Juarez-Sandoval ◽  
Miguel Angel Olivares-Robles ◽  
Ramon Blanco Sanchez ◽  
...  

The electric behavior in semiconductor devices is the result of the electric carriers’ injection and evacuation in the low doping region, N-. The carrier’s dynamic is determined by the ambipolar diffusion equation (ADE), which involves the main physical phenomena in the low doping region. The ADE does not have a direct analytic solution since it is a spatio-temporal second-order differential equation. The numerical solution is the most used, but is inadequate to be integrated into commercial electric circuit simulators. In this paper, an empiric approximation is proposed as the solution of the ADE. The proposed solution was validated using the final equations that were implemented in a simulator; the results were compared with the experimental results in each phase, obtaining a similarity in the current waveforms. Finally, an advantage of the proposed methodology is that the final expressions obtained can be easily implemented in commercial simulators.


2021 ◽  
Vol 13 (13) ◽  
pp. 2604
Author(s):  
Patrick Osei Darko ◽  
Margaret Kalacska ◽  
J. Pablo Arroyo-Mora ◽  
Matthew E. Fagan

Hyperspectral remote sensing across multiple spatio-temporal scales allows for mapping and monitoring mangrove habitats to support urgent conservation efforts. The use of hyperspectral imagery for assessing mangroves is less common than for terrestrial forest ecosystems. In this study, two well-known measures in statistical physics, Mean Information Gain (MIG) and Marginal Entropy (ME), have been adapted to high spatial resolution (2.5 m) full range (Visible-Shortwave-Infrared) airborne hyperspectral imagery. These two spectral complexity metrics describe the spatial heterogeneity and the aspatial heterogeneity of the reflectance. In this study, we compare MIG and ME with surface reflectance for mapping mangrove extent and species composition in the Sierpe mangroves in Costa Rica. The highest accuracy for separating mangroves from forest was achieved with visible-near infrared (VNIR) reflectance (98.8% overall accuracy), following by shortwave infrared (SWIR) MIG and ME (98%). Our results also show that MIG and ME can discriminate dominant mangrove species with higher accuracy than surface reflectance alone (e.g., MIG–VNIR = 93.6% vs. VNIR Reflectance = 89.7%).


2018 ◽  
Vol 11 (8) ◽  
pp. 3391-3407 ◽  
Author(s):  
Zacharias Marinou Nikolaou ◽  
Jyh-Yuan Chen ◽  
Yiannis Proestos ◽  
Jos Lelieveld ◽  
Rolf Sander

Abstract. Chemical mechanism reduction is common practice in combustion research for accelerating numerical simulations; however, there have been limited applications of this practice in atmospheric chemistry. In this study, we employ a powerful reduction method in order to produce a skeletal mechanism of an atmospheric chemistry code that is commonly used in air quality and climate modelling. The skeletal mechanism is developed using input data from a model scenario. Its performance is then evaluated both a priori against the model scenario results and a posteriori by implementing the skeletal mechanism in a chemistry transport model, namely the Weather Research and Forecasting code with Chemistry. Preliminary results, indicate a substantial increase in computational speed-up for both cases, with a minimal loss of accuracy with regards to the simulated spatio-temporal mixing ratio of the target species, which was selected to be ozone.


Author(s):  
Irene Erlyn Wina Rachmawan ◽  
Ali Ridho Barakbah ◽  
Tri Harsono

Deforestation is one of the crucial issues in Indonesia. In 2012, deforestation rate in Indonesia reached 0.84 million hectares, exceeding Brazil. According to the 2009 Guinness World Records, Indonesia's deforestation rate was 1.8 million hectares per year between 2000 and 2005. An interesting view is the fact that Indonesia government denied the deforestation rate in those years and said that the rate was only 1.08 million hectares per year in 2000 and 2005. The different problem is on the technique how to deal with the deforestation rate. In this paper, we proposed a new approach for automatically identifying the deforestation area and measuring the deforestation rate. This approach involves differential image processing for detecting Spatio-temporal nature changes of deforestation. It consists series of important features extracted from multiband satellite images which are considered as the dataset of the research. These data are proceeded through the following stages: (1) Automatic clustering for multiband satellite images, (2) Reinforcement Programming to optimize K-Means clustering, (3) Automatic interpretation for deforestation areas, and (4) Deforestation measurement adjusting with elevation of the satellite. For experimental study, we applied our proposed approach to analyze and measure the deforestation in Mendawai, South Borneo. We utilized Landsat 7 to obtain the multiband images for that area from the year 2001 to 2013. Our proposed approach is able to identify the deforestation area and measure the rate. The experiment with our proposed approach made a temporal measurement for the area and showed the increasing deforestation size of the area 1.80 hectares during those years.


2021 ◽  
Author(s):  
Valentin Buck ◽  
Flemming Stäbler ◽  
Everardo Gonzalez ◽  
Jens Greinert

<p>The study of the earth’s systems depends on a large amount of observations from homogeneous sources, which are usually scattered around time and space and are tightly intercorrelated to each other. The understanding of said systems depends on the ability to access diverse data types and contextualize them in a global setting suitable for their exploration. While the collection of environmental data has seen an enormous increase over the last couple of decades, the development of software solutions necessary to integrate observations across disciplines seems to be lagging behind. To deal with this issue, we developed the Digital Earth Viewer: a new program to access, combine, and display geospatial data from multiple sources over time.</p><p>Choosing a new approach, the software displays space in true 3D and treats time and time ranges as true dimensions. This allows users to navigate observations across spatio-temporal scales and combine data sources with each other as well as with meta-properties such as quality flags. In this way, the Digital Earth Viewer supports the generation of insight from data and the identification of observational gaps across compartments.</p><p>Developed as a hybrid application, it may be used both in-situ as a local installation to explore and contextualize new data, as well as in a hosted context to present curated data to a wider audience.</p><p>In this work, we present this software to the community, show its strengths and weaknesses, give insight into the development process and talk about extending and adapting the software to custom usecases.</p>


2020 ◽  
Vol 81 (3) ◽  
pp. 853-873
Author(s):  
David Thong ◽  
George Streftaris ◽  
Gavin J. Gibson

Abstract One of the most important issues in the critical assessment of spatio-temporal stochastic models for epidemics is the selection of the transmission kernel used to represent the relationship between infectious challenge and spatial separation of infected and susceptible hosts. As the design of control strategies is often based on an assessment of the distance over which transmission can realistically occur and estimation of this distance is very sensitive to the choice of kernel function, it is important that models used to inform control strategies can be scrutinised in the light of observation in order to elicit possible evidence against the selected kernel function. While a range of approaches to model criticism is in existence, the field remains one in which the need for further research is recognised. In this paper, building on earlier contributions by the authors, we introduce a new approach to assessing the validity of spatial kernels—the latent likelihood ratio tests—which use likelihood-based discrepancy variables that can be used to compare the fit of competing models, and compare the capacity of this approach to detect model mis-specification with that of tests based on the use of infection-link residuals. We demonstrate that the new approach can be used to formulate tests with greater power than infection-link residuals to detect kernel mis-specification particularly when the degree of mis-specification is modest. This new tests avoid the use of a fully Bayesian approach which may introduce undesirable complications related to computational complexity and prior sensitivity.


Author(s):  
Viktorija Ponomarenko

The progress in the digital single market (DSM) has been acknowledged as one of the 10 political priorities by the European Commission since 2015. It could contribute € 415 billion per year (GDP) to the economy of the 28 EU Member States and create hundreds of thousands of new jobs. Nowadays, the ICT sector and the European Digital Agenda have declared it as one of the seven pillars of the Europe 2020 strategy. In order to speed up the development of new information technology and its commercialisation, it is necessary to increase software quality aimed at accelerating and improving technology transfer, taking into account process quality management. The aim of this article is to give an overview of a new approach to producing an additional value of the software development projects to improve the technology transfer process.


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