Entrainment, Instability, Quasi-periodicity, and Chaos in a Compound Neural Oscillator

We studied the dynamical behavior of a class of compound central pattern generator (CPG) models consisting of a simple neural network oscillator driven by both constant and periodic inputs of varying amplitudes, frequencies, and phases. We focused on a specific oscillator composed of two mutually inhibiting types of neuron (inspiratory and expiratory neurons) that may be considered as a minimal model of the mammalian respiratory rhythm generator. The simulation results demonstrated how a simple CPG model— with a minimum number of neurons and mild nonlinearities— may reproduce a host of complex dynamical behaviors under various periodic inputs. In particular, the network oscillated spontaneously only when both neurons received adequate and proportionate constant excitations. In the presence of a periodic source, the spontaneous rhythm was overriden by an entrained oscillation of varying forms depending on the nature of the source. Stable entrained oscillations were inducible by two types of inputs: (1) anti-phase periodic inputs with alternating agonist-antagonist drives to both neurons and (2) a single periodic drive to only one of the neurons. In-phase inputs, which exert periodic drives of similar magnitude and phase relationships to both neurons, resulted in varying disruptions of the entrained oscillations including magnitude attenuation, harmonic and phase distortions, and quasi-periodic interference. In the absence of significant phasic feedback, chaotic motion developed only when the CPG was driven by multiple periodic inputs. Apneic episodes with repetitive alternation of active (intrinsic oscillation) and inactive (cessation of oscillation) states developed when the network was driven by a moderate periodic input of low frequency. %and amplitudes of intermediate strength, Similar results were demonstrated in other, more complex oscillator models (that is, half-center oscillator and three-phase respiratory network model). These theoretical results may have important implications in elucidating the mechanisms of rhythmogenesis in the mature and developing respiratory CPG as well as other compound CPGs in mammalian and invertebrate nervous systems.     

Comparison of Linear,Nonlinear and Semiparametric Mixed‐effects Models for Estimating HIV Dynamic Parameters

The potency of antiretroviral agents in AIDS clinical trials can be assessed on the basis of an early viral response such as viral decay rate or change in viral load (number of copies of HIV RNA) of the plasma. Linear, parametric nonlinear, and semiparametric nonlinear mixed‐effects models have been proposed to estimate viral decay rates in viral dynamic models. However, before applying these models to clinical data, a critical question that remains to be addressed is whether these models produce coherent estimates of viral decay rates, and if not, which model is appropriate and should be used in practice. In this paper, we applied these models to data from an AIDS clinical trial of potent antiviral treatments and found significant incongruity in the estimated rates of reduction in viral load. Simulation studies indicated that reliable estimates of viral decay rate were obtained by using the parametric and semiparametric nonlinear mixed‐effects models. Our analysis also indicated that the decay rates estimated by using linear mixed‐effects models should be interpreted differently from those estimated by using nonlinear mixed‐effects models. The semiparametric nonlinear mixed‐effects model is preferred to other models because arbitrary data truncation is not needed. Based on real data analysis and simulation studies, we provide guidelines for estimating viral decay rates from clinical data. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Bayesian analysis for nonlinear regression model under skewed errors,with application in growth curves

We have considered a Bayesian approach for the nonlinear regression model by replacing the normal distribution on the error term by some skewed distributions, which account for both skewness and heavy tails or skewness alone. The type of data considered in this paper concerns repeated measurements taken in time on a set of individuals. Such multiple observations on the same individual generally produce serially correlated outcomes. Thus, additionally, our model does allow for a correlation between observations made from the same individual. We have illustrated the procedure using a data set to study the growth curves of a clinic measurement of a group of pregnant women from an obstetrics clinic in Santiago, Chile. Parameter estimation and prediction were carried out using appropriate posterior simulation schemes based in Markov Chain Monte Carlo methods. Besides the deviance information criterion (DIC) and the conditional predictive ordinate (CPO), we suggest the use of proper scoring rules based on the posterior predictive distribution for comparing models. For our data set, all these criteria chose the skew‐t model as the best model for the errors. These DIC and CPO criteria are also validated, for the model proposed here, through a simulation study. As a conclusion of this study, the DIC criterion is not trustful for this kind of complex model.     

An Approach to Integrating Environmental Considerations Within Managerial Decision‐Making

Recent environmental trends, including (1) an expansion of existing command and control directives, (2) the introduction of market‐based policy instruments, and (3) the adoption of extended producer responsibility, have created a need for new tools to help managerial decision‐making. To address this need, we develop a nonlinear mathematical programming model from a profit‐maximizing firm's perspective, which can be tailored as a decision‐support tool for firms facing environmental goals and constraints. We typify our approach using the specific context of diesel engine manufacturing and remanufacturing. Our model constructs are based on detailed interviews with top managers from two leading competitors in the medium and heavy‐duty diesel engine industry. The approach allows the incorporation of traditional operations‐planning considerations—in particular, capacity, production, and inventory—together with environmental considerations that range from product design through production to product end of life. A current hurdle to implementing such a model is the availability of input data. We therefore highlight the need not only to involve all departments within businesses but also for industrial ecologists and business managers to work together to implement meaningful decision models that are based on accurate and timely data and can have positive economic and environmental impact.     

Interaction between CFTR and prestin (SLC26A5)

Cystic fibrosis transmembrane conductance regulator (CFTR) is a cAMP-activated chloride channel that is present in a variety of epithelial cell types, and usually expressed in the luminal membrane. In contrast, prestin (SLC26A5) is a voltage-dependent motor protein, which is present in the basolateral membrane of cochlear outer hair cells (OHCs), and plays an important role in the frequency selectivity and sensitivity of mammalian hearing. By using in situ hybridization and immunofluorescence, we found that both mRNA and protein of CFTR are present in OHCs, and that CFTR localizes in both the apical and the lateral membranes. CFTR was not detected in the lateral membrane of inner hair cells (IHCs) or in that of OHCs derived from prestin-knockout mice, i.e., in instances where prestin is not expressed. These results suggest that prestin may interact physically with CFTR in the lateral membrane of OHCs. Immunoprecipitation experiments confirmed a prestin-CFTR interaction. Because chloride is important for prestin function and for the efferent-mediated inhibition of cochlear output, the prestin-directed localization of CFTR to the lateral membrane of OHCs has a potential physiological significance. Aside from its role as a chloride channel, CFTR is known as a regulator of multiple protein functions, including those of the solute carrier family 26 (SLC26). Because prestin is in the SLC26 family, several members of which interact with CFTR, we explored the potential modulatory relationship associated with a direct, physical interaction between prestin and CFTR. Electrophysiological experiments demonstrated that cAMP-activated CFTR is capable of enhancing voltage-dependent charge displacement, a signature of OHC motility, whereas prestin does not affect the chloride conductance of CFTR.     

中国人均生态足迹与生物承载力变化的EMD分析及情景预测

利用经验模态分解(EMD)方法分解并提取1961～2001年中国人均生态足迹与生物承载力变化的波动周期,建立具有周期性波动的非线性动力学预测模型,提出未来50a中国人均生态足迹和生物承载力变化的3种预测情景。结果表明:(1)40a来,中国人均生态足迹在波动中不断增加,具有明显的3.5a和8a两个波动周期;中国人均生物承载力在波动中不断减少,具有明显的2.7a和28a两个周期。(2)若一切照旧,即未来50a中国人均生态足迹与生物承载力保持过去40a的年均变化率不变,则人均生态足迹会持续上升,2050年达到3.391g.hm2;人均生物承载力持续下降,2050年降为0.490g.hm2;而人均生态赤字急剧拉大,2050年为3.024g.hm2,可持续发展形势非常严峻。(3)若缓慢变化,即未来20a中国人均生态足迹保持年均增长率1.195%、人均生物承载力年均减少率0.614%不变,则2025年人均生态足迹为1.849g.hm2、人均生物承载力为0.860g.hm2、人均赤字0.989g.hm2。(4)若人均生态足迹快速减少,即2025～2050年中国人均生态足迹年均减少率为0.996%、人均生物承载力年均减少率为0.614%不变,则2050年人均生态足迹为1.381g.hm2、人均生物承载力0.739g.hm2、人均生态赤字0.641g.hm2,但这需要中国经济发展和技术水平的极大提高、能源消费结构的多元化、居民消费意识和消费模式的快速转变、人民生活质量的极大改善。这样,中国的生态发展才有助于实现全球水平的生态可持续发展,在促进世界可持续发展的道路上起到积极的推动作用。     

医学图像融合配准技术

图像融合技术在现代医学中扮演着极其重要的角色,是现代医学图像技术研究的重点。图像融合技术中,图像的配准又是其中的重点、难点和热点。本文按照图像变换特性对图像配准进行了分类,对每个类别的不同配准方法(特征点的获取、图像配准的变换等)进行介绍。但是,图像配准是一个尚处在发展阶段的学科,实现配准的精确化、快速化、自动化仍需要进一步的努力。     

1982-2018年中国植被覆盖变化非线性趋势及其格局分析

探究植被覆盖变化是评估陆地生态系统环境变化的重要手段,但现有研究多采用线性趋势来表达植被覆盖的变化情况而忽略了趋势的非线性。本文使用GLASS FVC数据,利用BFAST方法和格局分析,探讨了1982-2018年我国植被覆盖变化的非线性趋势及其分布格局。结果表明：（1）与线性趋势方法的对比发现,BFAST的检测结果揭示了四川盆地、黄土高原等地的植被覆盖显著增加趋势其实存在中断,青海和东北等地植被覆盖经历了由退化到改善的过程而并非简单的线性增加,而青藏高原中东部等地则由原先的改善趋势变为了退化趋势。（2）将非线性趋势结果进行分类,其中单调型增加类型占比最多,达到33.58%,主要分布在内蒙古、陕西及河南等地;单调型减少占比1.82%,主要分布在东南沿海地区;中断型增加占比22.91%,主要分布在四川盆地东部和华北地区;中断型减少占比2.68%,主要分布在青藏高原东南部;由增到减占比4.20%,主要分布在青海等地;由减到增占比14.62%,主要分布在吉林等地。大范围的植被覆盖增加趋势充分反映了我国过去几十年植被的改善,但同时存在的减少趋势表明潜在的植被退化风险仍不可忽视。（3）不同趋势类型发生改变的时间有所差异,总体上1988-1999年间发生的改变较少,而2000-2011年间发生的改变较多,我国21世纪以来实施的大规模生态保护和恢复工程对植被的改善过程有重要影响。（4）分布格局上,植被覆盖改善趋势类型（单调型增加,中断型增加,由减到增）呈现大聚集,小分散的特点,具有复杂的形状;退化趋势类型（单调型减少,中断型减少,由增到减）的面积均较小,分布也相对离散。全国尺度上趋势空间格局呈现一定规律但分布的异质性较大,区域尺度上植被覆盖经受的干扰显著,变化过程实际也是较为复杂的。本研究表明,使用非线性趋势方法和格局分析,可以更准确地评估植被覆盖的时空变化,从而为生态环境相关工作的开展提供科学的参考。     

Monomeric and Dimeric 9‐O Anthraquinone and Phenanthryl Derivatives of Cinchona Alkaloids as Chiral Solvating Agents for the NMR Enantiodiscrimination of Chiral Hemiesters

Mono‐ and bis‐alkaloid chiral auxiliaries with anthraquinone or phenanthryl cores were probed as chiral solvating agents (CSAs) for the enantiodiscrimination of chiral cyclic hemiesters. The dimeric anthraquinone derivative and the monomeric phenanthryl one showed remarkable efficiency in the nuclear magnetic resonance (NMR) differentiation of enantiomeric mixtures of hemiesters. An anthraquinone analogous with a single alkaloid unit was remarkably less effective. The conformational prevalence of the chiral auxiliaries were ascertained by NMR. Chirality 27:693–699, 2015. © 2015 Wiley Periodicals, Inc.