233 resultados para Mathematical resilience


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Over the last 30 years, numerous research groups have attempted to provide mathematical descriptions of the skin wound healing process. The development of theoretical models of the interlinked processes that underlie the healing mechanism has yielded considerable insight into aspects of this critical phenomenon that remain difficult to investigate empirically. In particular, the mathematical modeling of angiogenesis, i.e., capillary sprout growth, has offered new paradigms for the understanding of this highly complex and crucial step in the healing pathway. With the recent advances in imaging and cell tracking, the time is now ripe for an appraisal of the utility and importance of mathematical modeling in wound healing angiogenesis research. The purpose of this review is to pedagogically elucidate the conceptual principles that have underpinned the development of mathematical descriptions of wound healing angiogenesis, specifically those that have utilized a continuum reaction-transport framework, and highlight the contribution that such models have made toward the advancement of research in this field. We aim to draw attention to the common assumptions made when developing models of this nature, thereby bringing into focus the advantages and limitations of this approach. A deeper integration of mathematical modeling techniques into the practice of wound healing angiogenesis research promises new perspectives for advancing our knowledge in this area. To this end we detail several open problems related to the understanding of wound healing angiogenesis, and outline how these issues could be addressed through closer cross-disciplinary collaboration.

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If the land sector is to make significant contributions to mitigating anthropogenic greenhouse gas (GHG) emissions in coming decades, it must do so while concurrently expanding production of food and fiber. In our view, mathematical modeling will be required to provide scientific guidance to meet this challenge. In order to be useful in GHG mitigation policy measures, models must simultaneously meet scientific, software engineering, and human capacity requirements. They can be used to understand GHG fluxes, to evaluate proposed GHG mitigation actions, and to predict and monitor the effects of specific actions; the latter applications require a change in mindset that has parallels with the shift from research modeling to decision support. We compare and contrast 6 agro-ecosystem models (FullCAM, DayCent, DNDC, APSIM, WNMM, and AgMod), chosen because they are used in Australian agriculture and forestry. Underlying structural similarities in the representations of carbon flows though plants and soils in these models are complemented by a diverse range of emphases and approaches to the subprocesses within the agro-ecosystem. None of these agro-ecosystem models handles all land sector GHG fluxes, and considerable model-based uncertainty exists for soil C fluxes and enteric methane emissions. The models also show diverse approaches to the initialisation of model simulations, software implementation, distribution, licensing, and software quality assurance; each of these will differentially affect their usefulness for policy-driven GHG mitigation prediction and monitoring. Specific requirements imposed on the use of models by Australian mitigation policy settings are discussed, and areas for further scientific development of agro-ecosystem models for use in GHG mitigation policy are proposed.

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BACKGROUND Many koala populations around Australia are in serious decline, with a substantial component of this decline in some Southeast Queensland populations attributed to the impact of Chlamydia. A Chlamydia vaccine for koalas is in development and has shown promise in early trials. This study contributes to implementation preparedness by simulating vaccination strategies designed to reverse population decline and by identifying which age and sex category it would be most effective to target. METHODS We used field data to inform the development and parameterisation of an individual-based stochastic simulation model of a koala population endemic with Chlamydia. The model took into account transmission, morbidity and mortality caused by Chlamydia infections. We calibrated the model to characteristics of typical Southeast Queensland koala populations. As there is uncertainty about the effectiveness of the vaccine in real-world settings, a variety of potential vaccine efficacies, half-lives and dosing schedules were simulated. RESULTS Assuming other threats remain constant, it is expected that current population declines could be reversed in around 5-6 years if female koalas aged 1-2 years are targeted, average vaccine protective efficacy is 75%, and vaccine coverage is around 10% per year. At lower vaccine efficacies the immunological effects of boosting become important: at 45% vaccine efficacy population decline is predicted to reverse in 6 years under optimistic boosting assumptions but in 9 years under pessimistic boosting assumptions. Terminating a successful vaccination programme at 5 years would lead to a rise in Chlamydia prevalence towards pre-vaccination levels. CONCLUSION For a range of vaccine efficacy levels it is projected that population decline due to endemic Chlamydia can be reversed under realistic dosing schedules, potentially in just 5 years. However, a vaccination programme might need to continue indefinitely in order to maintain Chlamydia prevalence at a sufficiently low level for population growth to continue.

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There is strong evidence to suggest that the combination of alcohol and chronic repetitive stress leads to long-lasting effects on brain function, specifically areas associated with stress, motivation and decision-making such as the amygdala, nucleus accumbens and prefrontal cortex. Alcohol and stress together facilitate the imprinting of long-lasting memories. The molecular mechanisms and circuits involved are being studied but are not fully understood. Current evidence suggests that corticosterone (animals) or cortisol (humans), in addition to direct transcriptional effects on the genome, can directly regulate pre- and postsynaptic synaptic transmission through membrane bound glucocorticoid receptors (GR). Indeed, corticosterone-sensitive synaptic receptors may be critical sites for stress regulation of synaptic responses. Direct modulation of synaptic transmission by corticosterone may contribute to the regulation of synaptic plasticity and memory during stress (Johnson et al., 2005; Prager et al., 2010). Specifically, previous data has shown that long term alcohol (1) increases the expression of NR2Bcontaining NMDA receptors at glutamate synapses, (2) changes receptor density, and (3) changes morphology of dendritic spines (Prendergast and Mulholland; 2012). During alcohol withdrawal these changes are associated with increased glucocorticoid signalling and increased neuronal excitability. It has therefore been proposed that these synapse changes lead to the anxiety and alcohol craving associated with withdrawal (Prendergast and Mulholland; 2012). My lab is targeting this receptor system and the amygdala in order to understand the effect of combining alcohol and stress on these pathways. Lastly, we are testing GR specific compounds as potential new medications to promote the development of resilience to developing addiction.

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The rise and popularity of dystopian fiction in recent years is quite marked and critics often attribute such high sales of books and box office as being linked to the impact September 11 has had on the world, especially in the United States. While the events of September 11, 2001 saw a heightened anxiety by nations and their citizens about the fear and threat of terrorism – an anxiety which is paradoxically lowered and raised by increased surveillance practices, security checks and warnings – other changes since the last stages of the twentieth century have also raised concerns and anxieties. In this paper I use examples of Young Adult (YA) dystopian fiction to illustrate the potential these texts have for providing their readers with alternative ways of thinking about the challenges that others face and their capacity for resilience.

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Analytical techniques for measuring and planning railway capacity expansion activities have been considered in this article. A preliminary mathematical framework involving track duplication and section sub divisions is proposed for this task. In railways these features have a great effect on network performance and for this reason they have been considered. Additional motivations have also arisen from the limitations of prior models that have not included them.

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This article focusses upon multi-modal transportation systems (MMTS) and the issues surrounding the determination of system capacity. For that purpose a multi-objective framework is advocated that integrates all the different modes and many different competing capacity objectives. This framework is analytical in nature and facilitates a variety of capacity querying and capacity expansion planning.

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- Objective Ambulance personnel provide emergency medical services to the community, often attending to highly challenging and traumatic scenes in complex and chaotic circumstances. Currently the assessment of predictors of psychological well-being remains limited. The current study investigated whether workplace belongingness was significant in predicting psychological distress as well as the presence of resilience in ambulance personnel whilst controlling for more routinely examined factors. - Method Australian ambulance officers (N = 740) completed a survey battery including the Kessler 10 (Kessler & Mroczek, 1994), Brief Resilience Scale (Smith et al., 2008) and Psychological Sense of Organisational Membership (Cockshaw & Shochet, 2010) scale. - Results Controlling for more commonly examined factors such as severity of trauma exposure and length of service, hierarchical multiple regression analyses demonstrated that workplace belongingness was significantly associated with reduced distress levels and enhanced resilience levels. - Conclusions Results suggest that strategies to enhance a sense of workplace belongingness in emergency service organisations could promote the well-being of emergency workers despite routine exposure to potentially traumatic events.

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Secure communication channels are typically constructed from an authenticated key exchange (AKE) protocol, which authenticates the communicating parties and establishes shared secret keys, and a secure data transmission layer, which uses the secret keys to encrypt data. We address the partial leakage of communicating parties' long-term secret keys due to various side-channel attacks, and the partial leakage of plaintext due to data compression. Both issues can negatively affect the security of channel establishment and data transmission. In this work, we advance the modelling of security for AKE protocols by considering more granular partial leakage of parties' long-term secrets. We present generic and concrete constructions of two-pass leakage-resilient key exchange protocols that are secure in the proposed security models. We also examine two techniques--heuristic separation of secrets and fixed-dictionary compression--for enabling compression while protecting high-value secrets.

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Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder that has a major impact on the ability to function effectively in daily life. PTSD may develop as a response to exposure to an event or events perceived as potentially harmful or life-threatening. It has high prevalence rates in the community, especially among vulnerable groups such as military personnel or those in emergency services. Despite extensive research in this field, the underlying mechanisms of the disorder remain largely unknown. The identification of risk factors for PTSD has posed a particular challenge as there can be delays in onset of the disorder, and most people who are exposed to traumatic events will not meet diagnostic criteria for PTSD. With the advent of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM V), the classification for PTSD has changed from an anxiety disorder into the category of stress- and trauma-related disorders. This has the potential to refocus PTSD research on the nature of stress and the stress response relationship. This review focuses on some of the important findings from psychological and biological research based on early models of stress and resilience. Improving our understanding of PTSD by investigating both genetic and psychological risk and coping factors that influence stress response, as well as their interaction, may provide a basis for more effective and earlier intervention.

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This thesis concerns the development of mathematical models to describe the interactions that occur between spray droplets and leaves. Models are presented that not only provide a contribution to mathematical knowledge in the field of fluid dynamics, but are also of utility within the agrichemical industry. The thesis is presented in two parts. First, thin film models are implemented with efficient numerical schemes in order to simulate droplets on virtual leaf surfaces. Then the interception event is considered, whereby energy balance techniques are employed to instantaneously predict whether an impacting droplet will bounce, splash, or adhere to a leaf.

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Objective This study explored the dimensionality and measurement invariance of the 25-item Connor-Davidson Resilience Scale (CD-RISC; Connor & Davidson, 2003) across samples of adult (n = 321; aged 20–36) and adolescent (n = 199; aged 12–18) Australian cricketers. Design Cross-sectional, self-report survey Methods An online, multi-section questionnaire. Results Confirmatory factor and item level analyses supported the psychometric superiority of a revised 10-item, unidimensional model of resilience over the original 25-item, five-factor measurement model. Positive and moderate correlations with hardiness as well as negative and moderate correlations with burnout components were evidenced thereby providing support for the convergent validity of the unidimensional model. Measurement invariance analyses of the unidimensional model across the two age-group samples supported configural (i.e., same factor structure across groups), metric (i.e., same pattern of factor loadings across the groups), and partial scalar invariance (i.e., mostly the same intercepts across the groups). Conclusion Evidence for a psychometrically sound measure of resilient qualities of the individual provides an important foundation upon which researchers can identify the antecedents to and outcomes of resilience in sport contexts.

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This project investigated the calcium distributions of the skin, and the growth patterns of skin substitutes grown in the laboratory, using mathematical models. The research found that the calcium distribution in the upper layer of the skin is controlled by three different mechanisms, not one as previously thought. The research also suggests that tight junctions, which are adhesions between neighbouring skin cells, cannot be solely responsible for the differences in the growth patterns of skin substitutes and normal skin.

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Healthy transparent cornea depends upon the regulation of fluid, nutrient and oxygen transport through the tissue to sustain cell metabolism and other critical processes for normal functioning. This research considers the corneal geometry and investigates oxygen distribution using a two-dimensional Monod kinetic model, showing that previous studies make assumptions that lead to predictions of near-anoxic levels of oxygen tension in the limbal regions of the cornea. It also considers the comparison of experimental spatial and temporal data with the predictions of novel mathematical models with respect to distributed mitotic rates during corneal epithelial wound healing.

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This study presents a comprehensive mathematical formulation model for a short-term open-pit mine block sequencing problem, which considers nearly all relevant technical aspects in open-pit mining. The proposed model aims to obtain the optimum extraction sequences of the original-size (smallest) blocks over short time intervals and in the presence of real-life constraints, including precedence relationship, machine capacity, grade requirements, processing demands and stockpile management. A hybrid branch-and-bound and simulated annealing algorithm is developed to solve the problem. Computational experiments show that the proposed methodology is a promising way to provide quantitative recommendations for mine planning and scheduling engineers.