scholarly journals MATHEMATICAL MODELS FOR VACCINATION, WANING IMMUNITY AND IMMUNE SYSTEM BOOSTING: A GENERAL FRAMEWORK

BIOMAT 2014 ◽  
2015 ◽  
Author(s):  
M. V. BARBAROSSA ◽  
G. RÖST
Keyword(s):  
Immune System ◽  
Mathematical Models ◽  
General Framework ◽  
Waning Immunity

scholarly journals Impact of booster vaccination on the control of COVID-19 Delta wave in the context of waning immunity: application to France in the winter 2021/22

2022 ◽  
Vol 27 (1) ◽  
Author(s):  
Paolo Bosetti ◽  
Cécile Tran Kiem ◽  
Alessio Andronico ◽  
Juliette Paireau ◽  
Daniel Levy-Bruhl ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Booster Vaccination ◽  
Delta Wave ◽  
Transmission Rates ◽  
Waning Immunity ◽  
Protective Behaviours

Europe has experienced a large COVID-19 wave caused by the Delta variant in winter 2021/22. Using mathematical models applied to Metropolitan France, we find that boosters administered to ≥ 65, ≥ 50 or ≥ 18 year-olds may reduce the hospitalisation peak by 25%, 36% and 43% respectively, with a delay of 5 months between second and third dose. A 10% reduction in transmission rates might further reduce it by 41%, indicating that even small increases in protective behaviours may be critical to mitigate the wave.

Online Machine Learning

2013 ◽  
pp. 27-54 ◽  
Author(s):  
Óscar Fontenla-Romero ◽  
Bertha Guijarro-Berdiñas ◽  
David Martinez-Rego ◽  
Beatriz Pérez-Sánchez ◽  
Diego Peteiro-Barral
Keyword(s):  
Machine Learning ◽  
Online Learning ◽  
Mathematical Models ◽  
General Framework ◽  
Current Application ◽  
Data Set

Machine Learning (ML) addresses the problem of adjusting those mathematical models which can accurately predict a characteristic of interest from a given phenomenon. They achieve this by extracting information from regularities contained in a data set. From its beginnings two visions have always coexisted in ML: batch and online learning. The former assumes full access to all data samples in order to adjust the model whilst the latter overcomes this limiting assumption thus expanding the applicability of ML. In this chapter, we review the general framework and methods of online learning since its inception are reviewed and its applicability in current application areas is explored.

scholarly journals A Dual-Aggressive Model of Tumor-Immune System Interactions

2019 ◽  
Vol 15 (10) ◽  
pp. 155
Author(s):  
Abdulkareem Ibrahim Afolabi ◽  
Normah Maan
Keyword(s):  
Steady State ◽  
Immune System ◽  
Numerical Analysis ◽  
Mathematical Models ◽  
Malignant Tumor ◽  
Physical Phenomenon ◽  
Biomedical Literature ◽  
The Stability ◽  
Total Elimination ◽  
Insight Into

<p class="0abstract">Biomedical literature suggested that the tumor-immune system physical phenomenon usually climaxes into either tumor elimination or escape. In retort to the phenomenological mechanics of tumor-immune system interaction, researchers had used Mathematical models mostly prey-predator and competitive extensively, to model the dynamics of tumor immune system interaction. However, these models had not accounted for total elimination and, or escape of tumor as hypothesizes by immunoediting hypotheses. In this work, we propose a dual aggressive model based on the biological narration of tumor-immune system interactions. The stability analyses of tumor-negative steady state are stable if the rate at which body cells dies is less than their proliferation rate a confirmation of biological listed causes of the tumor. The tumor-positive steady state is always unstable and saddle with the likelihood of either elimination or escape of tumor. Numerical analysis validates our analytical results and provides insight into the dynamics of the benignant and malignant tumor. The immunosuppression by tumor is not only visible but also validated by both analytical and numerical analysis.</p>

Mathematical models of self-propelled particles

2017 ◽  
Vol 27 (06) ◽  
pp. 997-1004 ◽  
Author(s):  
N. Bellomo ◽  
F. Brezzi
Keyword(s):  
Mathematical Models ◽  
General Framework ◽  
Future Research ◽  
Large Systems

This paper presents the papers published in two special issues devoted to the modeling of large systems of self-propelled particles. The contents of these papers are presented in the general framework of the conceptual analytic difficulties and of the computational problems that are met when dealing with this class of systems. In addition, some perspective ideas on possible objectives of future research are extracted from the contents of this issue and brought to the reader’s attention.

scholarly journals Modeling Biology Spanning Different Scales: An Open Challenge

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Filippo Castiglione ◽  
Francesco Pappalardo ◽  
Carlo Bianca ◽  
Giulia Russo ◽  
Santo Motta
Keyword(s):  
Immune System ◽  
Mathematical Models ◽  
Multiscale Modeling ◽  
Time Scales ◽  
High Throughput ◽  
Biological Systems ◽  
Living System ◽  
Huge Amount ◽  
Modern Biology ◽  
Unified Description

It is coming nowadays more clear that in order to obtain a unified description of the different mechanisms governing the behavior and causality relations among the various parts of a living system, the development of comprehensive computational and mathematical models at different space and time scales is required. This is one of the most formidable challenges of modern biology characterized by the availability of huge amount of high throughput measurements. In this paper we draw attention to the importance of multiscale modeling in the framework of studies of biological systems in general and of the immune system in particular.

scholarly journals SOFT ALMOST β-CONTINUITY IN SOFT TOPOLOGICAL SPACES

2020 ◽  
Vol 8 (2) ◽  
pp. 06-14
Author(s):  
Alpa Singh Rajput ◽  
S. S. Thakur ◽  
Om Prakash Dubey
Keyword(s):  
Image Segmentation ◽  
Information Systems ◽  
Mathematical Models ◽  
General Framework ◽  
Continuous Mapping ◽  
Topological Spaces ◽  
Major Area ◽  
Soft Topology ◽  
Continuous Mappings

Purpose: In the present paper the concept of soft almost β-continuous mappings and soft almost β-open mappings in soft topological spaces have been introduced and studied. Methodology: This notion is weaker than both soft almost pre-continuous mappings, soft almost semi-continuous mapping. The diagrams of implication among these soft classes of soft mappings have been established. Main Findings: We extend the concept of almost β-continuous mappings and almost β-open mappings in soft topology. Implications: Mapping is an important and major area of topology and it can give many relationships between other scientific areas and mathematical models. This notion captures the idea of hanging-togetherness of image elements in an object by assigning strength of connectedness to every possible path between every possible pair of image elements. It is an important tool for the designing of algorithms for image segmentation. The novelty of Study: Hope that the concepts and results established in this paper will help the researcher to enhance and promote the further study on soft topology to carry out a general framework for the development of information systems.

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