A lateral dynamics of a wheelchair: identification and analysis of tire parameters

In vehicle dynamics studies, the tire behaviour plays an important role in planar motion of the vehicle. Therefore, a correct representation of tire is a necessity. This paper describes a mathematical model for wheelchair tire based on the Magic Formula model. This model is widely used to represent forces and moments between the tire and the ground; however some experimental parameters must be determined. The purpose of this work is to identify the tire parameters for the wheelchair tire model, implementing them in a dynamic model of the wheelchair. For this, we developed an experimental test rig to measure the tires parameters for the lateral dynamics of a wheelchair. This dynamic model was made using a multi-body software and the wheelchair behaviour was analysed and discussed according to the tire parameters. The result of this work is one step further towards the understanding of wheelchair dynamics.     

A comparison of static and dynamic optimization muscle force predictions during wheelchair propulsion

The primary purpose of this study was to compare static and dynamic optimization muscle force and work predictions during the push phase of wheelchair propulsion. A secondary purpose was to compare the differences in predicted shoulder and elbow kinetics and kinematics and handrim forces. The forward dynamics simulation minimized differences between simulated and experimental data (obtained from 10 manual wheelchair users) and muscle co-contraction. For direct comparison between models, the shoulder and elbow muscle moment arms and net joint moments from the dynamic optimization were used as inputs into the static optimization routine. RMS errors between model predictions were calculated to quantify model agreement. There was a wide range of individual muscle force agreement that spanned from poor (26.4% F_max error in the middle deltoid) to good (6.4% F_max error in the anterior deltoid) in the prime movers of the shoulder. The predicted muscle forces from the static optimization were sufficient to create the appropriate motion and joint moments at the shoulder for the push phase of wheelchair propulsion, but showed deviations in the elbow moment, pronation–supination motion and hand rim forces. These results suggest the static approach does not produce results similar enough to be a replacement for forward dynamics simulations, and care should be taken in choosing the appropriate method for a specific task and set of constraints. Dynamic optimization modeling approaches may be required for motions that are greatly influenced by muscle activation dynamics or that require significant co-contraction.     

Forward dynamic optimization of handle path and muscle activity for handle based isokinetic wheelchair propulsion: A simulation study

Push-rim wheelchair propulsion is biomechanically inefficient and physiologically stressful to the musculoskeletal structure of human body. This study focuses to obtain a new, optimized propulsion shape for wheelchair users, which is within the ergonomic ranges of joint motion, thus reducing the probability of injuries. To identify the propulsion movement, forward dynamic optimization was performed on a 3D human musculoskeletal model linked to a handle based propulsion mechanism, having shape and muscle excitations as optimization variables. The optimization resulted in a handle path shape with a circularity ratio of 0.95, and produced a net propulsion power of 34.7 watts for an isokinetic propulsion cycle at 50?rpm. Compared to push-rim propulsion, the compact design of the new propulsion mechanism along with the ergonomically optimized propulsion shape may help to reduce the risk of injuries and thus improve the quality of life for wheelchair users.     

Computational centrosomics: An approach to understand the dynamic behaviour of centrosome

Centrosomes are the key regulating element of cell cycle progression. Aberrations in their functional mechanism leads to several cancer related disorders. Although genomic studies in the field of centrosome have been extensively carried out, with the lack of structural conformation, the proteomic analysis of pathological genetic mutation is still a challenging task. Several computational algorithms and high range force fields are used to design the 3D structure conformation of proteins, which has now become the leading platform for in-silico drug discovery approaches. Application of these highly efficient platforms in centrosomics studies will be a novel approach to develop an efficient drug therapy for the treatment of their dysfunction disorders.     

A dynamic model of water gain and loss in larval Mexican bean beetle

Abstract. Quantitative effects of temperature, vapour pressure deficit, host, and larval body size were experimentally determined. A simulation model for dynamic water balance in the Mexican bean beetle, Epilachna varivestis Mulsant, is presented and parameters are estimated from laboratory data for water gain/loss equations. The model is based on water loss through the cuticle, spiracles and frass, and water gain through ingestion.     

Evolution of new gene functions: simulation and analysis of the amplification model

Creation of new genes and functions is a central feature of evolution. Duplication of existing genes has long been assumed to be the source of new genes, but the precise mechanism has remained unclear. One suggestion is that new genes are created via temporary amplifications, which simultaneously increase both the selective advantage of weak, pre-existing secondary functions and the target for optimizing mutations. This paper examines the amplification model by formalizing it into a mathematical framework. This framework is used to perform stochastic (Monte Carlo) simulations. In addition, experimental data from Salmonella typhimurium LT2 are used to support the modelling, by providing estimates for parameter values. The results show that amplification of tandem repeats is likely to contribute to creation of new genes in nature.     

A dynamic model of larval Mexican bean beetle survival as a function of body water balance

Abstract. This paper presents evidence of the relationship between survival and body water content in the Mexican bean beetle, Epilachna varivestis Mulsant (Coleoptera: Coccinellidae). Results of a simulation model for dynamically describing water balance and survival are compared with experimental data for the Mexican bean beetle feeding on both lima bean and soybean under different variable temperature and moisture regimes.     

A new dynamic model for highly efficient mass transfer in aerated bioreactors and consequences for kLa identification

Gas–liquid mass transfer is often rate‐limiting in laboratory and industrial cultures of aerobic or autotrophic organisms. The volumetric mass transfer coefficient k_La is a crucial characteristic for comparing, optimizing, and upscaling mass transfer efficiency of bioreactors. Reliable dynamic models and resulting methods for parameter identification are needed for quantitative modeling of microbial growth dynamics. We describe a laboratory‐scale stirred tank reactor (STR) with a highly efficient aeration system (k_La ≈ 570 h^?1). The reactor can sustain yeast culture with high cell density and high oxygen uptake rate, leading to a significant drop in gas concentration from inflow to outflow (by 21%). Standard models fail to predict the observed mass transfer dynamics and to identify k_La correctly. In order to capture the concentration gradient in the gas phase, we refine a standard ordinary differential equation (ODE) model and obtain a system of partial integro‐differential equations (PIDE), for which we derive an approximate analytical solution. Specific reactor configurations, in particular a relatively short bubble residence time, allow a quasi steady‐state approximation of the PIDE system by a simpler ODE model which still accounts for the concentration gradient. Moreover, we perform an appropriate scaling of all variables and parameters. In particular, we introduce the dimensionless overall efficiency κ, which is more informative than k_La since it combines the effects of gas inflow, exchange, and solution. Current standard models of mass transfer in laboratory‐scale aerated STRs neglect the gradient in the gas concentration, which arises from highly efficient bubbling systems and high cellular exchange rates. The resulting error in the identification of κ (and hence k_La) increases dramatically with increasing mass transfer efficiency. Notably, the error differs between cell‐free and culture‐based methods of parameter identification, potentially confounding the determination of the “biological enhancement” of mass transfer. Our new model provides an improved theoretical framework that can be readily applied to aerated bioreactors in research and biotechnology. Biotechnol. Bioeng. 2012; 109: 2997–3006. © 2012 Wiley Periodicals, Inc.     

A dynamic model of facilitation on environmental stress gradients

Theories based on competition for resources in animals and other non‐sessile organisms rarely consider the role of facilitative interactions. Yet these interactions are important for community assembly, especially under stressful environments (e.g. the stress‐gradient hypothesis, SGH). To make an explicit link between species interaction theory and SGH patterns, I used a classic resource competition model promoting coexistence between a beneficiary and its facilitator sharing a common resource along a stress gradient. I compared model outcomes for two fundamentally different mechanisms of facilitation (alleviation of resource versus non‐resource stress), and also tested the effect of a reciprocal cost of facilitation from the beneficiary. I then tested model's biological relevance using experimental data from two tuber moth species (Lepidoptera, Gelechiidae) for which facilitation in resource access was previously established. Simulation outcomes revealed that both the mode of facilitation and the incorporation of facilitation costs affected the shape of the facilitation–stress relationship. These predictions are in line with current SGH observations and experiments on both plants and animals and reconcile the frequently reported variability of this relationship in nature. Moreover, a sensitivity analysis of model's parameters confirmed the robustness of the modelling framework to uncover the mechanisms responsible for observed species interaction–stress patterns. Finally, when parameterized with tuber moth demographic data, model's results corresponded to observed interaction outcomes along resource stress gradients. Overall, having a common model for plants and animals may simplify assumptions in SGH studies, allow contrasting the shapes of different consumer–resource relationships and specifying the conditions that favour one type of interaction outcome over another.     

Identification of the PcrA DNA helicase reaction pathway by applying advanced targeted molecular dynamic simulations

PcrA DNA helicase uses the free energy of hydrolysis and binding of ATP to unwind double-stranded DNA (ds-DNA). There are two states of PcrA, termed the substrate and product complexes and, through the conformational changes between these two states, PcrA moves along ds-DNA and separates the two strands. In this study, two different methods, namely chain minimisation (CM, less reliable method) and auto targeted molecular dynamic (TMD) simulation (more reliable), were performed to generate two different initial reaction pathways between these two states, and then fixed root mean square distance (RMSD) TMD simulation was performed to optimise these two initial pathways. In general, the two optimised pathways share very similar major conformational changes, but are different in the minor motions. The potential energy profiles of the two improved pathways are generally similar, but the one generated by the improved TMD path is slightly lower. Considering the poor reliability of the initial path generated by CM and insignificant improvements of the auto-TMD path, our study suggests that fixed RMSD TMD simulation can generate reliable reaction pathways, but the different initial paths still have some influence on the detailed conformational analysis.     

动态空气动力学参数对玉米田陆-气通量模拟的影响——以BATSle模型为例

基于2006-2008年锦州玉米农田生态系统的通量、气象及生物因子连续观测,利用所建立的考虑玉米不同发育期叶面积指数、冠层高度和风速的地表粗糙度(z0)和零平面位移(d)动态参数化方案对BATS1e陆面模型进行改进,研究空气动力学参数变化对玉米田陆-气通量模拟的影响.结果表明:改进后的拖曳系数(CD)随植被覆盖度增大而增大,更符合实际;感热、潜热和土壤热通量的模拟精度均有不同程度改进,效率系数分别提高0.0569、0.0194和0.0384,生长季累计改进量分别占总辐射的0.9％、1.1％和1.2％;当输入真实的表层土壤湿度后,z0和d动态参数化对感热和潜热的改进作用更大.合理的动态空气动力学参数化方案对陆面过程模拟具有明显改善作用.     

A population dynamic model of Batesian mimicry

A population dynamic model of Batesian mimicry, in which populations of both model and mimetic species were considered, was analyzed. The probability of a predator catching prey on each encouter was assumed to depend on the frequency of the mimic. The change in population size of each species was considered to have two components, growth at the intrinsic growth rate and carrying capacity, and reduction by predation. For simplicity in the analyses, three assumptions were made concerning the carrying capacities of each population: (1) with no density effects on the mimic population growth rate; (2) with no density effects on the model species; and (3) with density effects on both species. The first and second cases were solved analytically, whereas the last was, for the most part, investigated numerically. Under assumption (1), two stable equilibria are possible, in which both species either coexist or go to extinction. Under assumption (2), there are also two stable equilibria possible, in which either only the mimic persists or both go to extinction. These results explain the field records of butterflies (Pachliopta aristolochiae and its mimic Papilio polytes) in the Ryukyu Islands, Japan.     

Model-free model elimination: A new step in the model-free dynamic analysis of NMR relaxation data

Model-free analysis is a technique commonly used within the field of NMR spectroscopy to extract atomic resolution, interpretable dynamic information on multiple timescales from the R ₁, R ₂, and steady state NOE. Model-free approaches employ two disparate areas of data analysis, the discipline of mathematical optimisation, specifically the minimisation of a χ² function, and the statistical field of model selection. By searching through a large number of model-free minimisations, which were setup using synthetic relaxation data whereby the true underlying dynamics is known, certain model-free models have been identified to, at times, fail. This has been characterised as either the internal correlation times, τ _e , τ _f , or τ _s , or the global correlation time parameter, local τ _m , heading towards infinity, the result being that the final parameter values are far from the true values. In a number of cases the minimised χ² value of the failed model is significantly lower than that of all other models and, hence, will be the model which is chosen by model selection techniques. If these models are not removed prior to model selection the final model-free results could be far from the truth. By implementing a series of empirical rules involving inequalities these models can be specifically isolated and removed. Model-free analysis should therefore consist of three distinct steps: model-free minimisation, model-free model elimination, and finally model-free model selection. Failure has also been identified to affect the individual Monte Carlo simulations used within error analysis. Each simulation involves an independent randomised relaxation data set and model-free minimisation, thus simulations suffer from exactly the same types of failure as model-free models. Therefore, to prevent these outliers from causing a significant overestimation of the errors the failed Monte Carlo simulations need to be culled prior to calculating the parameter standard deviations.     

Mechanical responses of the periodontal ligament based on an exponential hyperelastic model: a combined experimental and finite element method

The V–W exponential hyperelastic model is adopted to describe the instantaneous elastic response of the periodontal ligament (PDL). The general theoretical framework of constitutive modeling is described based on nonlinear continuum mechanics, and the elasticity tensor used to develop UMAT subroutine is formulated. Nanoindentation experiment is performed to characterize mechanical properties of an adult pig PDL specimen. Then the experiment is simulated by using the finite element (FE) analysis. Meanwhile, the optimized material parameters are identified by the inverse FE method. The good agreement between the simulated results and experimental data demonstrates that the V–W model is capable of describing the mechanical behavior of the PDL. Therefore, the model and its implementation into FE code are validated. By using the model, we simulate the tooth movement under orthodontic loading to predict the mechanical responses of the PDL. The results show that local concentrations of stress and strain in the PDL are found.     

A stochastic model for extinction and recurrence of epidemics: estimation and inference for measles outbreaks

Epidemic dynamics pose a great challenge to stochastic modelling because chance events are major determinants of the size and the timing of the outbreak. Reintroduction of the disease through contact with infected individuals from other areas is an important latent stochastic variable. In this study we model these stochastic processes to explain extinction and recurrence of epidemics observed in measles. We develop estimating functions for such a model and apply the methodology to temporal case counts of measles in 60 cities in England and Wales. In order to estimate the unobserved spatial contact process we suggest a method based on stochastic simulation and marginal densities. The estimation results show that it is possible to consider a unified model for the UK cities where the parameters depend on the city size. Stochastic realizations from the dynamic model realistically capture the transitions from an endemic cyclic pattern in large populations to irregular epidemic outbreaks in small human host populations.     

Performance of a new dynamic model for predicting diurnal time courses of stomatal conductance at the leaf level

Under natural conditions, plants are subjected to continuous changes of irradiance that drive variations of stomatal conductance to water vapour (g_s). We propose a dynamic model to predict the temporal response of g_s at the leaf level using an asymmetric sigmoid function with a unique parameter describing time constants for increasing and decreasing g_s. The model parameters were adjusted to observed data using Approximate Bayesian Computation. We tested the model performance for (1) instant changes of irradiance; or (2) continuous and controlled variations of irradiance simulating diurnal time courses. Compared with the two mostly used steady‐state models, our dynamic model described daily time courses of g_s with a higher accuracy. In particular, it was able to describe the hysteresis of g_s responses to increasing/decreasing irradiance and the resulting rapid variations of intrinsic water‐use efficiency. Compared to the mechanistic model of temporal responses of g_s by Kirschbaum, Gross & Pearcy, for which time constants were estimated with a large variance, our model estimated time constants with a higher precision. It is expected to improve predictions of water loss and water‐use efficiency in higher scale models by using a small number of parameters.     

A new model for the effect of pH on microbial growth: an extension of the Gamma hypothesis

Aims: To investigate the appropriateness of the extended Lambert–Pearson model (ELPM) to model the effect of pH (as hydrogen and hydroxyl ions) over the whole biokinetic pH range in comparison with other available models. Methods and Results: Data for the effect of pH on microbial growth were obtained from the literature or in‐house. Data were examined using several models for pH. Models were compared using the residual mean of squares. Using the ELPM, pH was modelled as hydrogen ions and hydroxyl ions; hence, the model was monotonic in each. The ELPM was able to model data more successfully than the cardinal pH model (CPM) and other models in the majority of cases. Conclusions: Examining the effect of pH as hydrogen and hydroxyl ions has the advantage that the basic form of the ELPM can be retained as each is treated as a distinct antimicrobial effect. With the ELPM, each inhibitor is described by two parameters; from these parameters, the pH_min, pH_opt and pH_max can be obtained. Furthermore, the idea of a dose response, absent from other models, becomes important. Significance and Impact of the Study: The CPM is an excellent model for certain situations – where there is a high degree of symmetry between the suboptimal pH and superoptimal pH response and where there are few data points available. The ELPM is more amenable to highly asymmetric behaviour, especially where plateaus of effect around the pH optimum are observed and where the number of data points is not restrictive.     

Microcirculation in the murine liver: a computational fluid dynamic model based on 3D reconstruction from in vivo microscopy

The liver is organized in hexagonal functional units – termed lobules – characterized by a rather peculiar blood microcirculation, due to the presence of a tangled network of capillaries – termed sinusoids. A better understanding of the hemodynamics that governs liver microcirculation is relevant to clinical and biological studies aimed at improving our management of liver diseases and transplantation.Herein, we built a CFD model of a 3D sinusoidal network, based on in vivo images of a physiological mouse liver obtained with a 2-photon microscope. The CFD model was developed with Fluent 16.0 (ANSYS Inc., Canonsburg, PA), particular care was taken in imposing the correct boundary conditions representing a physiological state. To account for the remaining branches of the sinusoids, a lumped parameter model was used to prescribe the correct pressure at each outlet. The effect of an adhered cell on local hemodynamics is also investigated for different occlusion degrees.The model here proposed accurately reproduces the fluid dynamics in a portion of the sinusoidal network in mouse liver. Mean velocities and mass flow rates are in agreement with literature values from in vivo measurements. Our approach provides details on local phenomena, hardly described by other computational studies, either focused on the macroscopic hepatic vasculature or based on homogeneous porous medium model.