scholarly journals An Evolutionary Justification of the Emergence of Leadership Using Mathematical Models

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2271
Author(s):  
Daniel Solow ◽  
Joseph Szmerekovsky ◽  
Sukumarakurup Krishnakumar
Keyword(s):  
Mathematical Models ◽  
Group Size ◽  
Computer Simulations ◽  
Mathematical Analysis ◽  
Survival Probability ◽  
Group Cohesion ◽  
Well Being ◽  
Mathematical Justification

The value and importance of leadership is evident by its prevalence throughout human societies and organizations. Based on an evolutionary argument, models are presented here that provide a mathematical justification as to how and why leadership arose in the first place and then persisted. In this setting, by a leader is meant a person whose overall actions are ultimately responsible for the well-being and survival of the group. The proposed models contain parameters whose values reflect group size, harshness of the environment, diversity of actions taken by individuals, and the amount of group cohesion. Mathematical analysis and computer simulations are used to identify conditions on these parameters under which leadership results in an increased survival probability for the community.

scholarly journals COVID-19 International Border Surveillance Cohort Study at Toronto’s Pearson Airport

2021 ◽  
Author(s):  
Vivek Goel ◽  
David Bulir ◽  
Eric De Propetis ◽  
Munaza Jamil ◽  
Laura Rosella ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Well Being ◽  
Primary Objective ◽  
Control Measures ◽  
List Type ◽  
Subjective Well Being ◽  
Loss To Follow Up ◽  
Final Destination ◽  
Airport Terminal ◽  
International Border

AbstractObjectivesThe primary objective was to estimate the positivity rate of air travelers coming to Toronto, Canada in September and October, 2020, at arrival, day 7 and day 14. Secondary objectives were to estimate degree of risk based on country of origin; to assess knowledge and attitudes towards COVID-19 control measures; and subjective well-being during the quarantine period.DesignProspective cohort of arriving international travelers.SettingToronto Pearson Airport Terminal 1, Toronto, Canada.ParticipantsPassengers arriving on international flights. Inclusion criteria were those aged 18 or older who had a final destination within 100 km of the airport; spoke English or French; and provided consent. Excluded were those taking a connecting flight; who had no internet access; who exhibited symptoms of COVID-19 on arrival; or who were exempted from quarantine.Main outcome measuresPositive for SARS-CoV-2 virus on RT-PCR with self-administered nasal-oral swab, and general well-being using the WHO-5 index.ResultsOf 16,361 passengers enrolled, 248 (1·5%, 95% CI 1.3%,1.5%) tested positive. Of these, 167 (67%) were identified on arrival, 67 (27%) on day 7, and 14 (6%) on day 14. The positivity rate increased from 1% in September to 2% in October. Average well-being score declined from 19.8 (out of a maximum of 25) to 15.5 between arrival and day 7 (p<0.001).ConclusionsA single arrival test will pick up two-thirds of individuals who will become positive, with most of the rest detected on the second test at day 7. These results support strategies identified through mathematical models that a reduced quarantine combined with testing can be as effective as a 14 day quarantine.Article SummaryStrengths and limitations of this studyDecisions regarding border restrictions have been based on trial and error and mathematical models with limited empirical data to support such decision-making.This study assessed the prevalence of SARS-CoV-2 in a cohort of international travellers at arrival, day 7 and 14 of quarantine.It is limited to one airport and there is the potential from bias due to non-participation and loss to follow-up.Self-collected nasal-oral swabs were used which facilitated participation but may have reduced sensitivity.

Design and Analysis of Computer Experiments

2017 ◽  
pp. 264-279
Author(s):  
Xinwei Deng ◽  
Ying Hung ◽  
C. Devon Lin
Keyword(s):  
Complex Systems ◽  
Mathematical Models ◽  
Gaussian Process ◽  
Computer Simulations ◽  
Process Modeling ◽  
Computer Experiments ◽  
Space Filling ◽  
Science And Engineering ◽  
The Past ◽  
Statistical Approaches

Computer experiments refer to the study of complex systems using mathematical models and computer simulations. The use of computer experiments becomes popular for studying complex systems in science and engineering. The design and analysis of computer experiments have received broad attention in the past decades. In this chapter, we present several widely used statistical approaches for design and analysis of computer experiments, including space-filling designs and Gaussian process modeling. A special emphasis is given to recently developed design and modeling techniques for computer experiments with quantitative and qualitative factors.

An Assessment of an electronic feeding system and “dynamic” grouping in loose-housed sows

1986 ◽  
Vol 1986 ◽  
pp. 120-120
Author(s):  
R.J. Lambert ◽  
M. Ellis ◽  
P. Rowlinson
Keyword(s):  
Group Size ◽  
Well Being ◽  
Feeding System ◽  
Group Management ◽  
Large Group

Recently, sow-activated electronic concentrate dispensers allowing dry sows to be group-housed and individually fed have been seriously considered as an alternative to the close confinement of pregnant sows. For the system to be economic, each feeding unit needs to be used to its maximum potential, while at the same time considering the well-being of the animals.Previous work has established that levels of aggression may be minimised within a set group size and the maximum number of sows per feeder may be increased to over 30 by feeding only once per day on this system (Lambert et al., 1985). With groups of this size, the practical aspects of large group management need to be considered.

Dynamics and Simulation of General Human and Humanoid Motion in Sports

2011 ◽  
pp. 36-62 ◽  
Author(s):  
Veljko Potkonjak ◽  
Miomir Vukobratovic ◽  
Kalman Babkovic ◽  
Branislav Borovac
Keyword(s):  
Mathematical Models ◽  
Motion Planning ◽  
Mathematical Analysis ◽  
Humanoid Robot ◽  
Dynamic Control ◽  
Humanoid Robots ◽  
Assistive Devices ◽  
Kinematics And Dynamics ◽  
Biologically Inspired ◽  
Biologically Inspired Robot

This chapter relates biomechanics to robotics. The mathematical models are derived to cover the kinematics and dynamics of virtually any motion of a human or a humanoid robot. Benefits for humanoid robots are seen in fully dynamic control and a general simulator for the purpose of system designing and motion planning. Biomechanics in sports and medicine can use these as a tool for mathematical analysis of motion and disorders. Better results in sports and improved diagnostics are foreseen. This work is a step towards the biologically-inspired robot control needed for a diversity of tasks expected in humanoids, and robotic assistive devices helping people to overcome disabilities or augment their physical potentials. This text deals mainly with examples coming from sports in order to justify this aspect of research.

scholarly journals Challenges of biofilm control and utilization: lessons from mathematical modelling

2019 ◽  
Vol 16 (155) ◽  
pp. 20190042 ◽  
Author(s):  
Paulina A. Dzianach ◽  
Gary A. Dykes ◽  
Norval J. C. Strachan ◽  
Ken J. Forbes ◽  
Francisco J. Pérez-Reche
Keyword(s):  
Wastewater Treatment ◽  
Mathematical Modelling ◽  
Mathematical Models ◽  
Computer Simulations ◽  
Biofilm Formation ◽  
Food Industry ◽  
Interspecies Interactions ◽  
Collective Knowledge ◽  
Medical Sector ◽  
Pattern Formations

This article reviews modern applications of mathematical descriptions of biofilm formation. The focus is on theoretically obtained results which have implications for areas including the medical sector, food industry and wastewater treatment. Examples are given as to how models have contributed to the overall knowledge on biofilms and how they are used to predict biofilm behaviour. We conclude that the use of mathematical models of biofilms has demonstrated over the years the ability to significantly contribute to the vast field of biofilm research. Among other things, they have been used to test various hypotheses on the nature of interspecies interactions, viability of biofilm treatment methods or forces behind observed biofilm pattern formations. Mathematical models can also play a key role in future biofilm research. Many models nowadays are analysed through computer simulations and continue to improve along with computational capabilities. We predict that models will keep on providing answers to important challenges involving biofilm formation. However, further strengthening of the ties between various disciplines is necessary to fully use the tools of collective knowledge in tackling the biofilm phenomenon.

scholarly journals Analysis of spatial thermal field in a magnetic bearing

Open Physics ◽  
2018 ◽  
Vol 16 (1) ◽  
pp. 52-56
Author(s):  
Dawid Wajnert ◽  
Bronisław Tomczuk
Keyword(s):  
Temperature Field ◽  
Mathematical Models ◽  
Computer Simulations ◽  
Thermal Field ◽  
Three Dimensional ◽  
Magnetic Bearing ◽  
Field Analysis ◽  
Two Dimensional ◽  
Temperature Distributions ◽  
Dimensional Simulation

AbstractThis paper presents two mathematical models for temperature field analysis in a new hybrid magnetic bearing. Temperature distributions have been calculated using a three dimensional simulation and a two dimensional one. A physical model for temperature testing in the magnetic bearing has been developed. Some results obtained from computer simulations were compared with measurements.

scholarly journals Social Influence of Competing Groups and Leaders in Opinion Dynamics

2020 ◽  
Author(s):  
Catherine A. Glass ◽  
David H. Glass
Keyword(s):  
Social Influence ◽  
Group Size ◽  
Computer Simulations ◽  
Parameter Space ◽  
Optimal Strategies ◽  
Opinion Dynamics ◽  
The Other ◽  
Opinion Leaders ◽  
The Impact

Abstract This paper explores the influence of two competing stubborn agent groups on the opinion dynamics of normal agents. Computer simulations are used to investigate the parameter space systematically in order to determine the impact of group size and extremeness on the dynamics and identify optimal strategies for maximizing numbers of followers and social influence. Results show that (a) there are many cases where a group that is neither too large nor too small and neither too extreme nor too central achieves the best outcome, (b) stubborn groups can have a moderating, rather than polarizing, effect on the society in a range of circumstances, and (c) small changes in parameters can lead to transitions from a state where one stubborn group attracts all the normal agents to a state where the other group does so. We also explore how these findings can be interpreted in terms of opinion leaders, truth, and campaigns.

scholarly journals Effective disinfection

2020 ◽  
pp. 40-42
Author(s):  
N. V. Yavnikov
Keyword(s):  
Avian Influenza ◽  
Mathematical Analysis ◽  
Well Being ◽  
Biological Safety

Relevance. The compliance with zoohygienic norms and rules is a prerequisite for the biological safety of a livestock enterprise. Biosafety requirements have been tightened especially in connection with pandemics of ASF, avian influenza and other infections. Disinfection is one of the most important measures to maintain epizootological well-being, and the quality of disinfection directly depends on the effectiveness of the disinfectant used.Methods. The methods of mathematical analysis were applied.Results. The effectiveness of the use of disinfectant solutions based on the Chistobel complex disinfectant was confirmed. The disinfectant is effective for all types of disinfecting treatments at all objects of veterinary supervision.

scholarly journals The Global Response to COVID-19 as an Example of a One-Sided Problem Definition in the Absence of General Collective Intelligence

2020 ◽  
Author(s):  
Andy E Williams
Keyword(s):  
Decision Making ◽  
Mathematical Models ◽  
Group Decision Making ◽  
Group Decision ◽  
Collective Intelligence ◽  
Well Being ◽  
Problem Definition ◽  
Negative Outcomes ◽  
Global Response ◽  
Risk Of Mortality

Problem definitions are defined here as one-sided in the case that while they might take into account one class of negative outcomes, such as those associated with the problem, at the same time they might ignore other classes of negative outcomes, such as those that may be encountered while implementing interventions that try to avoid the problem. An example is amputating all limbs with potentially cancerous moles on them to reduce the risk of mortality due to cancer as much as possible, without considering the increase in mortality due to the amputations. The global response to COVID-19 has been characterized by the availability of mathematical models for the potential mortality due to the spread of the pandemic. However in some cases the researchers guiding the responses of their respective nations with their mathematical models have explicitly pointed out that corresponding mathematical models of the impacts of economic shutdowns or other potential interventions on mortality have not been incorporated, and that there is a critical need to include such models. This paper generalizes this problem of one-sided problem definitions past the COVID-19 response to a wide variety of group problems where the pattern of one-sidedness applies, and explores how in current group decision-making systems one-sided problem definitions might consistently tend to be exploited in a way that is detrimental to collective well-being, as well as how a system of group decision-making meeting the requirements of a General Collective Intelligence solves the problem of one-sidedness to reliably maximize collective well-being.

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