非线性接触率和种群动力学对SI传染病模型的影响

本文研究了具有一般非线性接触率和易感类中具有Logistic增长的SI传染病模型的正不变集、平衡位置以及平衡位置的稳定性．     

A dynamic model of thoracic differentiation for the control of turning in the stick insect

Leg movements of stick insects (Carausius morosus) making turns towards visual targets are examined in detail, and a dynamic model of this behaviour is proposed. Initial results suggest that front legs shape most of the body trajectory, while the middle and hind legs just follow external forces (Rosano H, Webb B, in The control of turning in real and simulated stick insects, vol. 4095, pp 145–156, 2006). However, some limitations of this explanation and dissimilarities in the turning behaviour of the insect and the model were found. A second set of behavioural experiments was made by blocking front tarsi to further investigate the active role of the other legs for the control of turning. The results indicate that it is necessary to have different roles for each pair of legs to replicate insect behaviour. We demonstrate that the rear legs actively rotate the body while the middle legs move sideways tangentially to the hind inner leg. Furthermore, we show that on average the middle inner and hind outer leg contribute to turning while the middle outer leg and hind inner leg oppose body rotation. These behavioural results are incorporated into a 3D dynamic robot simulation. We show that the simulation can now replicate more precisely the turns made by the stick insect. This work was supported by CONACYT México and the European Commission under project FP6-2003-IST2-004690 SPARK.     

Logistic regression when covariates are random effects from a non‐linear mixed model

In many studies, the association of longitudinal measurements of a continuous response and a binary outcome are often of interest. A convenient framework for this type of problems is the joint model, which is formulated to investigate the association between a binary outcome and features of longitudinal measurements through a common set of latent random effects. The joint model, which is the focus of this article, is a logistic regression model with covariates defined as the individual‐specific random effects in a non‐linear mixed‐effects model (NLMEM) for the longitudinal measurements. We discuss different estimation procedures, which include two‐stage, best linear unbiased predictors, and various numerical integration techniques. The proposed methods are illustrated using a real data set where the objective is to study the association between longitudinal hormone levels and the pregnancy outcome in a group of young women. The numerical performance of the estimating methods is also evaluated by means of simulation.     

Multiscale landscape genomic models to detect signatures of selection in the alpine plant Biscutella laevigata

Plant species are known to adapt locally to their environment, particularly in mountainous areas where conditions can vary drastically over short distances. The climate of such landscapes being largely influenced by topography, using fine‐scale models to evaluate environmental heterogeneity may help detecting adaptation to micro‐habitats. Here, we applied a multiscale landscape genomic approach to detect evidence of local adaptation in the alpine plant Biscutella laevigata. The two gene pools identified, experiencing limited gene flow along a 1‐km ridge, were different in regard to several habitat features derived from a very high resolution (VHR) digital elevation model (DEM). A correlative approach detected signatures of selection along environmental gradients such as altitude, wind exposure, and solar radiation, indicating adaptive pressures likely driven by fine‐scale topography. Using a large panel of DEM‐derived variables as ecologically relevant proxies, our results highlighted the critical role of spatial resolution. These high‐resolution multiscale variables indeed indicate that the robustness of associations between genetic loci and environmental features depends on spatial parameters that are poorly documented. We argue that the scale issue is critical in landscape genomics and that multiscale ecological variables are key to improve our understanding of local adaptation in highly heterogeneous landscapes.     

Host plant quality,selection history and trade-offs shape the immune responses of Manduca sexta

Immune defences are an important component of fitness. Yet susceptibility to pathogens is common, suggesting the presence of ecological and evolutionary limitations on immune defences. Here, we use structural equation modelling to quantify the direct effects of resource quality and selection history, and their indirect effects mediated via body condition prior to an immune challenge on encapsulation and melanization immune defences in the tobacco hornworm, Manduca sexta. We also investigate allocation trade-offs among immune defences and growth rate following an immune challenge. We found considerable variation in the magnitude and direction of the direct effects of resource quality and selection history on immune defences and their indirect effects mediated via body condition and allocation trade-offs. Greater resource quality and evolutionary exposure to pathogens had positive direct effects on encapsulation and melanization. The indirect effect of resource quality on encapsulation mediated via body condition was substantial, whereas indirect effects on melanization were negligible. Individuals in better condition prior to the immune challenge had greater encapsulation; however, following the immune challenge, greater encapsulation traded off with slower growth rate. Our study demonstrates the importance of experimentally and analytically disentangling the relative contributions of direct and indirect effects to understand variation in immune defences.     

Impacts of imperfect reference data on the apparent accuracy of species presence–absence models and their predictions

Aim To explore the impacts of imperfect reference data on the accuracy of species distribution model predictions. The main focus is on impacts of the quality of reference data (labelling accuracy) and, to a lesser degree, data quantity (sample size) on species presence–absence modelling. Innovation The paper challenges the common assumption that some popular measures of model accuracy and model predictions are prevalence independent. It highlights how imperfect reference data may impact on a study and the actions that may be taken to address problems. Main conclusions The theoretical independence of prevalence of popular accuracy measures, such as sensitivity, specificity, true skills statistics (TSS) and area under the receiver operating characteristic curve (AUC), is unlikely to occur in practice due to reference data error; all of these measures of accuracy, together with estimates of species occurrence, showed prevalence dependency arising through the use of a non‐gold‐standard reference. The number of cases used also had implications for the ability of a study to meet its objectives. Means to reduce the negative effects of imperfect reference data in study design and interpretation are suggested.     

Respiratory system dynamical mechanical properties: modeling in time and frequency domain

The mechanical properties of the respiratory system are important determinants of its function and can be severely compromised in disease. The assessment of respiratory system mechanical properties is thus essential in the management of some disorders as well as in the evaluation of respiratory system adaptations in response to an acute or chronic process. Most often, lungs and chest wall are treated as a linear dynamic system that can be expressed with differential equations, allowing determination of the system’s parameters, which will reflect the mechanical properties. However, different models that encompass nonlinear characteristics and also multicompartments have been used in several approaches and most specifically in mechanically ventilated patients with acute lung injury. Additionally, the input impedance over a range of frequencies can be assessed with a convenient excitation method allowing the identification of the mechanical characteristics of the central and peripheral airways as well as lung periphery impedance. With the evolution of computational power, the airway pressure and flow can be recorded and stored for hours, and hence continuous monitoring of the respiratory system mechanical properties is already available in some mechanical ventilators. This review aims to describe some of the most frequently used models for the assessment of the respiratory system mechanical properties in both time and frequency domain.