An analysis of the analysis of herbivore population dynamics

Time series analysis of herbivore data with weather included as covariate is commonly used as a mean to shed light on the state and ecology of the studied population. Conclusions about the herbivore population are drawn from statistical parameter values and presence/absence in the most parsimonious model. However, this procedure is only reliable if the statistical parameters have general interpretations regardless of system characteristics. Here we investigated the extent to which this is true by deriving six different vegetation–herbivore-systems and analyzing their respective statistical parameters. The analysis was done in both continuous and discrete time. It turned out that both density parameters (a₁ and a₂) and rainfall coefficients change with biological interactions and amount of average rainfall, and they do so in different ways in different systems. This means that there is no valid general interpretation of them and, most important, the probability of detecting density dependence and effects of rainfall vary between systems. Hence, you can not make inference about the biological processes from statistical analysis without knowing the system that you study and what model best describes the interactions within it.     

基于时间聚类分析和独立成分分析的癫痫fMRI盲分析方法

提出了一种基于时间聚类分析和独立成分分析的癫痫fMRI数据盲分析方法,并将两种方法有效联合,提取发作间期的癫痫fMRI激活时空信息.该方法首先由时间聚类分析得到与激活相关的时间峰度特征曲线,以此特征作为时间参考信息;再由空间独立成分分析分解fMRI信号得到空间独立成分;最后将每个独立成分所对应的时间曲线与参考曲线做相关分析提取相应脑激活图.提出的方法无需任何关于癫痫fMRI的先验假设信息,有效解决了独立成分的排序问题,实现了对数据的盲分析.仿真试验结果阐明了这一方法的有效性及可靠性,对癫痫数据的试验结果显示空间定位准确性优于统计参数图方法.     

多元统计方法在节肢动物群落分析中的应用

近年来有关节肢动物群落的研究报道较多,而传统的、简单的多样性指数分析远远不能满足对高通量群落数据的挖掘。采用多元统计方法可以较好地分析群落数据。其中,在研究某一处理的长期效应时,主响应曲线是一种经典的多元分析方法;而非度量多维尺度分析具有能处理较大量的数据且常能以低维排序图反映结果的优点,是一种具有广泛应用前景的排序技术。本文以Bt棉与非Bt棉不同比例混作棉田的节肢动物群落为例,详尽地介绍了主响应曲线和非度量多维尺度在节肢动物群落分析中的应用。     

Nonlinear analysis of EEG signals: Surrogate data analysis

ObjectivesThe electroencephalogram (EEG) signal contains information about the state and condition of the brain. The aim of the study is to conduct a nonlinear analysis of the EEG signals and to compare the differences in the nonlinear characteristics of the EEG during normal state and the epileptic state.DataThe EEG data used for this study – which consisted of epileptic EEG and normal EEG – were obtained from the EEG database available with the Bonn University, Germany.ResultsThe attractors seen in normal and epileptic human brain dynamics were studied and compared. Surrogate data analyses were conducted on two nonlinear measures, namely the largest Lyapunov exponent and the correlation dimension, to test the hypothesis whether EEG signals were in accordance with linear stochastic models.DiscussionsThe existence of deterministic chaos in brain activity is confirmed by the existence of a chaotic attractor; also, saturation of the correlation dimension towards a definite value is the manifestation of a deterministic dynamics. Also a reduction is observed between the dimensionalities of the brain attractors from normal state to the epileptic state. The evaluation of the largest Lyapunov exponent also confirms the lowering of complexity during an episode of seizure.ConclusionIn case of Lyapunov exponent of EEG data, the change due to surrogating is small suggesting that it is not representing the system complexity properly but there is a marked change in the case of correlation dimension value due to surrogating.     

Fractal analysis of knee-joint vibroarthrographic signals via power spectral analysis

Parameters useful for the diagnosis of pathological processes leading to the deterioration of the articular cartilage surfaces of knee joints, such as osteoarthritis, may be derived from vibroarthrographic (VAG) signals. In the present work, we explore fractal analysis to parameterize the temporal and spectral variability of normal and abnormal VAG signals. The power spectrum analysis method was used with the 1/f model to derive estimates of the fractal dimension (FD). Classification accuracy of up to 0.74 was obtained with a single FD parameter, in terms of the area under the receiver operating characteristic curve (A_z), with a database of 89 VAG signals. Combinations of the features derived in the present work with other features we have reported upon recently, when used with several neural networks with radial basis functions, resulted in A_z values in the range [0.92, 0.96], with an exceptional case of perfect classification with A_z = 1.0. The proposed methods could help in the detection and monitoring of knee-joint pathology.     

Physical analysis of virus particles using electrospray differential mobility analysis

This review critically examines an emerging tool to measure viral clearance from biomanufacturing streams, monitor assembly of viruses and virus-like particles, rapidly identify viruses from biological milieu, assay virus neutralization, and prepare bionanoconjugates for bacterial detection. Electrospray differential mobility analysis (ES-DMA) is a tool of choice to simultaneously determine viral size and concentration because it provides full multimodal size distributions with subnanometer precision from individual capsid proteins to intact viral particles. The review contrasts ES-DMA to similar tools and highlights expected growth areas including at-line process sensing as a process analytical technology (PAT), bioseparating as a distinct unit operation, monitoring viral reactions, and interrogating virus-host protein interactions.     

Integration of temporal analysis and control analysis of metabolic systems.

A theory is developed that integrates approaches to the analysis of pathway transient response and metabolic control analysis. A Temporal Control Coefficient is defined that is a measure of the system's transient response to modulation of enzyme activity or concentration. The approach allows for the analysis of the establishment of a steady state from rest, of the system's 'agility' of response to minor perturbations of a pre-existing steady state and of the macroscopic transition between steady states. In the last-mentioned case it is shown that, like the transient time itself, the control of transient response retains the property of independence from the mechanism of the transition. In consequence, the Temporal Control Coefficient can be defined in terms of the control properties of the initial and final states alone without reference to the mechanism of transition. A summation property is shown to apply to the Temporal Control Coefficients in each case. Connectivity relationships between elasticities and Temporal Control Coefficients are also established.     

Arabidopsis genome analysis as exemplified by analysis of chromosome 4

During the last decade the small cruciferous plant Arabidopsis thaliana has become a model organism for flowering plants. Sequencing and analysis of the Arabidopsis genome is nearing completion. Beside an overview on methods and strategies for Arabidopsis genome analysis, a summary of the results from the first analysis is presented.This includes an overview on chromosomal organisation and topological features as well as a first comparison with other genomes.     

Comparison and analysis of objective functions in flux balance analysis

Flux balance analysis (FBA) is currently one of the most important and used techniques for estimation of metabolic reaction rates (fluxes). This mathematical approach utilizes an optimization criterion in order to select a distribution of fluxes from the feasible space delimited by the metabolic reactions and some restrictions imposed over them, assuming that cellular metabolism is in steady state. Therefore, the obtained flux distribution depends on the specific objective function used. Multiple studies have been aimed to compare distinct objective functions at given conditions, in order to determine which of those functions produces values of fluxes closer to real data when used as objective in the FBA; in other words, what is the best objective function for modeling cell metabolism at a determined environmental condition. However, these comparative studies have been designed in very dissimilar ways, and in general, several factors that can change the ideal objective function in a cellular condition have not been adequately considered. Additionally, most of them have used only one dataset for representing one condition of cell growth, and different measuring techniques have been used. For these reasons, a rigorous study on the effect of factors such as the quantity of used data, the number and type of fluxes utilized as input data, and the selected classification of growth conditions, are required in order to obtain useful conclusions for these comparative studies, allowing limiting clearly the application range on any of those results. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:985–991, 2014     

基于物质流分析和数据包络分析的区域生态效率评价——以江苏省为例

区域生态效率(eco-efficiency)评价是考量区域可持发展的重要内容.基于物质流分析(material flow analysis, MFA)构建区域生态效率评价指标体系,并将污染物排放作为一种非期望输入引入到数据包络分析(data envelopment analysis, DEA)模型中,以江苏省(1990～2005年)为例进行生态效率分析评价.结果表明,江苏省的区域生态效率在1990～2005年期间呈现逐步上升的趋势.但是,同期的总物质投入(total material input, TMI)、物质需求总量(total material requirement, TMR)和污染物排放量也呈上升趋势.因此,江苏省社会经济发展和环境影响总体上呈现"弱脱钩(weak de-link)".     

Quantitative analysis of venation patterns of Arabidopsis leaves by supervised image analysis

The study of transgenic Arabidopsis lines with altered vascular patterns has revealed key players in the venation process, but details of the vascularization process are still unclear, partly because most lines have only been assessed qualitatively. Therefore, quantitative analyses are required to identify subtle perturbations in the pattern and to test dynamic modeling hypotheses using biological measurements. We developed an online framework, designated Leaf Image Analysis Interface (LIMANI), in which venation patterns are automatically segmented and measured on dark-field images. Image segmentation may be manually corrected through use of an interactive interface, allowing supervision and rectification steps in the automated image analysis pipeline and ensuring high-fidelity analysis. This online approach is advantageous for the user in terms of installation, software updates, computer load and data storage. The framework was used to study vascular differentiation during leaf development and to analyze the venation pattern in transgenic lines with contrasting cellular and leaf size traits. The results show the evolution of vascular traits during leaf development, suggest a self-organizing mechanism for leaf venation patterning, and reveal a tight balance between the number of end-points and branching points within the leaf vascular network that does not depend on the leaf developmental stage and cellular content, but on the leaf position on the rosette. These findings indicate that development of LIMANI improves understanding of the interaction between vascular patterning and leaf growth.     

Parsimony analysis of endemicity and analysis of endemicity: A fair comparison

Parsimony Analysis of Endemicity (PAE) has been compared with other methods regarding its performance to identify areas of endemism. It is frequently compared with the Analysis of Endemicity (AE), which seems to perform better than PAE to identify these areas. Here I compare PAE and AE considering the sympatric taxa diagnosed as endemic, being as strictly close as possible to sympatry, and using previously published data of Sciobius (Coleoptera: Curculionidae). AE identified more candidate areas of endemism than PAE, but the number of highly restricted endemic taxa to these areas was insufficient to support them as areas of endemism. Considering strictly sympatry (homopatry), PAE performed better than AE; however, both methods may identify areas with some grade of sympatry, but the recognition of which areas constitute real areas of endemism in the strict sense depends on the interpretation of the researcher.