Dataset Information

`Friend or foe' and decision making initiative in complex conflict environments.

ABSTRACT: We present a novel mathematical model of two adversarial forces in the vicinity of a non-combatant population in order to explore the impact of each force pursuing specific decision-making strategies. Each force has the opportunity to draw support by enabling the decision-making initiative of the population, in tension with maintaining tactical and organisational effectiveness over their adversary. Each dynamic model component of force, population and decision-making, is defined by the archetypal Lanchester, Lotka-Volterra and Kuramoto-Sakaguchi models, with feedback between each component adding heterogeneity. Developing a scheme where cultural factors determine decision-making strategies for each force, this work highlights the parametric and topological factors that influence favourable results in a non-linear system where physical outcomes are highly dependent on the non-physical and cognitive nature of each force's intended strategy.

SUBMITTER: Zuparic M

PROVIDER: S-EPMC9901805 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

`Friend or foe' and decision making initiative in complex conflict environments.

Zuparic Mathew M Shelyag Sergiy S Angelova Maia M Zhu Ye Y Kalloniatis Alexander A

PloS one 20230206 2

We present a novel mathematical model of two adversarial forces in the vicinity of a non-combatant population in order to explore the impact of each force pursuing specific decision-making strategies. Each force has the opportunity to draw support by enabling the decision-making initiative of the population, in tension with maintaining tactical and organisational effectiveness over their adversary. Each dynamic model component of force, population and decision-making, is defined by the archetypa ...[more]

PMID: 36745613

Similar Datasets

Project description:BackgroundA higher chemotherapy completion rate is associated with better outcomes including treatment efficacy and overall survival. Exercise may have the potential to improve relative dose intensity (RDI) by reducing the frequency and severity of chemotherapy-related toxicities. We examined the association between exercise adherence and RDI and possible clinical- and health-related fitness predictors of RDI.MethodsChemotherapy records were extracted from the electronic medical record for patients enrolled in the ENACT trial (n = 105). Chemotherapy completion was assessed using average RDI. A threshold of 85% was established for "high" versus "low" RDI. Logistic regression analyses were used to estimate the associations between the clinical- and health-related fitness predictors of RDI.ResultsPatients with breast cancer (BC) had a significantly higher average RDI (89.8% ± 17.6%) compared with gastrointestinal cancer (GI) (76.8% ± 20.9%, p = 0.004) and pancreatic cancer (PC) (65.2% ± 20.1%, p < 0.001). Only 25% of BC patents required a dose reduction compared to 56.3% of GI and 86.4% of PC patients. Cancer site was significantly associated with RDI. Compared with BC, patients with GI (β = -0.12, p = 0.03) and PC (β = -0.22, p = 0.006) achieved significantly lower RDI. Every 2.72 unit increase in overall exercise adherence led to a significant 7% decrease in RDI (p = 0.001) in GI patients. Metastatic GI patients had a 15% RDI increase for every 2.72 unit increase in exercise adherence (p = 0.04).ConclusionExercise is a supportive therapy that has potential to enhance chemotherapy tolerance and completion. The relationship between exercise adherence and RDI is influenced by factor such as cancer site and treatment type. Special attention must be paid to how exercise is prescribed to ensure that exercise adherence does not negatively affect RDI. Cancer site, exercise dosage, and multimodal interventions to address toxicities are key areas identified for future research.

Dataset Information

`Friend or foe' and decision making initiative in complex conflict environments.

Publications

`Friend or foe' and decision making initiative in complex conflict environments.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets