Evolution of locomotion in Anthropoidea: the semicircular canal evidence

Our understanding of locomotor evolution in anthropoid primates has been limited to those taxa for which good postcranial fossil material and appropriate modern analogues are available. We report the results of an analysis of semicircular canal size variation in 16 fossil anthropoid species dating from the Late Eocene to the Late Miocene, and use these data to reconstruct evolutionary changes in locomotor adaptations in anthropoid primates over the last 35 Ma. Phylogenetically informed regression analyses of semicircular canal size reveal three important aspects of anthropoid locomotor evolution: (i) the earliest anthropoid primates engaged in relatively slow locomotor behaviours, suggesting that this was the basal anthropoid pattern; (ii) platyrrhines from the Miocene of South America were relatively agile compared with earlier anthropoids; and (iii) while the last common ancestor of cercopithecoids and hominoids likely was relatively slow like earlier stem catarrhines, the results suggest that the basal crown catarrhine may have been a relatively agile animal. The latter scenario would indicate that hominoids of the later Miocene secondarily derived their relatively slow locomotor repertoires.     

Estimation of Several Missing Values in F-Square Designs

The present study deals with the estimation of several missing values in F-square designs. The estimating equations for the non-iterative least squares estimation of Missing Values and explicit expressions for the estimators of the particular patterns of Missing Values are presented. This procedure is illustrated with the help of a numerical example.     

A comment on phylogenetic correction

Statistical methods are now commonly used to take into account the expected lack of independence of observations across different species (due to their phylogenetic relatedness) when computing correlations or regressions among traits. The methods are often interpreted as removing that part of the regression or correlation that is an artifact due to phylogeny and there is an expectation that the corrected regression or correlation coefficients will usually be closer to zero. It is shown here that this is not an accurate way to interpret these methods. The effect of taking phylogeny into account is to reduce the variance of the estimated regression or correlation coefficients. Their means are not because since estimates of regression coefficients are unbiased whether or not the correct phylogeny is taken into account. Estimates of correlations are only slightly biased (and in the opposite direction that many expect).     

Determination of total protein in hyperimmune serum samples by near-infrared spectrometry and multivariate calibration

In the present work, the determination of the total protein concentration in hyperimmune serum samples was performed through a partial least-squares near-infrared (NIR-PLS) method. The method was based on the chemometric treatment of the NIR spectra of samples. The influences of spectra preprocessing and spectral window utilized in the construction of PLS model were studied. Models were built using reference data of 19 samples selected through the use of hierarchical cluster analysis (HCA) of NIR spectra of samples and another 24 samples were employed for external validation of the method. A model with better prediction capacity was obtained after whole spectra preprocessing by multiplicative scattering correction (MSC) algorithm and using data in the spectral range of 2158-2209 nm. Under optimized conditions a RMSEP of 0.21 g dl⁻¹ and a quality coefficient value (QC) of only 5.8% were obtained for the prediction of total protein content in the samples used for external validation. Also, a determination coefficient, r², of 0.97 was obtained in the correlation of predicted and reference data of samples situated in the validation set.     

Comparison of the Vibration Mode of Metals in HNO3 by a Partial Least-Squares Regression Analysis of Near-Infrared Spectra

The near-infrared (NIR) spectra of such metals as Cu(II), Mn(II), Zn(II) and Fe(III) in HNO₃ in the 700–1860 nm region were subjected to a partial least-squares regression analysis and leave-out cross-validation to develop chemometric models. The models yielded a coefficient of determination in cross validation of 0.9744 [Cu(II)], 0.9631 [Mn(II)], 0.9154 [Zn(II)] and 0.741 [Fe(III)]. The regression coefficients for Cu(II), Mn(II) and Zn(II), but not for Fe(III), showed strong negative peaks at around 1050–1200 nm, a zone where spectral bands have been reported to decrease with increasing pH value. A positive peak at around 710–750 nm, which may have been due to water absorption, was observed in regression coefficients of Cu(II), Mn(II) and Zn(II) but not in Fe(III), while a negative peak was observed in that for Fe(III) at around 710–750 nm. These results indicate that the divalent cations [Cu(II), Mn(II) and Zn(II)] showed different absorption in the NIR region from the trivalent cation [Fe(III)], suggesting that the vibration mode of water, which mirrors the interaction between cations and water, may be influenced by valency.     

利用机载激光雷达技术估测东北林区典型针叶林的蓄积量

为了推广激光雷达技术在森林蓄积量估测计量方面的应用,本研究以东北林区云冷杉林、落叶松林、红松林和樟子松林4种典型针叶林为对象,基于机载激光雷达获取的点云数据提取特征变量,结合800块地面样地数据,采用逐步回归方法和偏最小二乘方法,建立4种针叶林的蓄积量模型。结果表明: 偏最小二乘法建立的模型精度优于逐步回归方法(ΔR²=0.05～0.15,ΔRRMSE=2.6%～4.2%);在参与建模的3类点云特征变量中,贡献最大的是点云高度变量(被选择26次),其他变量有一定的辅助作用(分别被选择12次和11次);使用偏最小二乘方法建立的林分蓄积量模型中,红松林(R²=0.79,RMSE=60.92,RRMSE=22.9%)和落叶松林(R²=0.76,RMSE=28.39,RRMSE=25.8%)的精度最高,云冷杉林(R²=0.81,RMSE=46.96,RRMSE=27.7%)次之,樟子松林(R²=0.50,RMSE=55.49,RRMSE=30.4%)的精度稍低。研究结果为东北林区4种典型针叶林蓄积量估测提供了一种有效的方法。     

Rapid Evaluation of Least-Squares and Minimum-Evolution Criteria on Phylogenetic Trees

We present fast new algorithms for evaluating trees with respectto least squares and minimum evolution (ME), the most commonlyused criteria for inferring phylogenetic trees from distancedata. The new algorithms include an optimal O(N2) time algorithmfor calculating the edge (branch or internode) lengths on atree according to ordinary or unweighted least squares (OLS);an O(N3) time algorithm for edge lengths under weighted leastsquares (WLS) including the Fitch-Margoliash method; and anoptimal O(N4) time algorithm for generalized least-squares (GLS)edge lengths (where N is the number of taxa in the tree). TheME criterion is based on the sum of edge lengths. Consequently,the edge lengths algorithms presented here lead directly toO(N2), O(N3), and O(N4) time algorithms for ME under OLS, WLS,and GLS, respectively. All of these algorithms are as fast asor faster than any of those previously published, and the algorithmsfor OLS and GLS are the fastest possible (with respect to orderof computational complexity). A major advantage of our new methodsis that they are as well adapted to multifurcating trees asthey are to binary trees. An optimal algorithm for determiningpath lengths from a tree with given edge lengths is also developed.This leads to an optimal O(N2) algorithm for OLS sums of squaresevaluation and corresponding O(N3) and O(N4) time algorithmsfor WLS and GLS sums of squares, respectively. The GLS algorithmis time-optimal if the covariance matrix is already inverted.The speed of each algorithm is assessed analytically—thespeed increases we calculate are confirmed by the dramatic speedincreases resulting from their implementation in PAUP* 4.0.The new algorithms enable far more extensive tree searches andstatistical evaluations (e.g., bootstrap, parametric bootstrap,or jackknife) in the same amount of time. Hopefully, the fastalgorithms for WLS and GLS will encourage the use of these criteriafor evaluating trees and their edge lengths (e.g., for approximatedivergence time estimates), since they should be more statisticallyefficient than OLS.     

On the mean square error associated with adaptive generalized ridge regression

Some numerical results are presented for generalized ridge regression where the additive constants are based on the data. The adaptive estimator so obtained is compared with the least-squares estimator on the basis of mean square error (MSE). It is shown that the MSE of each component of the vector of ridge estimators may be as low as 47.1% of the variance of the corresponding component of the least squares vector or as high as 125.2%.     

Theoretical foundation of the balanced minimum evolution method of phylogenetic inference and its relationship to weighted least-squares tree fitting

Due to its speed, the distance approach remains the best hope for building phylogenies on very large sets of taxa. Recently (R. Desper and O. Gascuel, J. Comp. Biol. 9:687-705, 2002), we introduced a new "balanced" minimum evolution (BME) principle, based on a branch length estimation scheme of Y. Pauplin (J. Mol. Evol. 51:41-47, 2000). Initial simulations suggested that FASTME, our program implementing the BME principle, was more accurate than or equivalent to all other distance methods we tested, with running time significantly faster than Neighbor-Joining (NJ). This article further explores the properties of the BME principle, and it explains and illustrates its impressive topological accuracy. We prove that the BME principle is a special case of the weighted least-squares approach, with biologically meaningful variances of the distance estimates. We show that the BME principle is statistically consistent. We demonstrate that FASTME only produces trees with positive branch lengths, a feature that separates this approach from NJ (and related methods) that may produce trees with branches with biologically meaningless negative lengths. Finally, we consider a large simulated data set, with 5,000 100-taxon trees generated by the Aldous beta-splitting distribution encompassing a range of distributions from Yule-Harding to uniform, and using a covarion-like model of sequence evolution. FASTME produces trees faster than NJ, and much faster than WEIGHBOR and the weighted least-squares implementation of PAUP*. Moreover, FASTME trees are consistently more accurate at all settings, ranging from Yule-Harding to uniform distributions, and all ranges of maximum pairwise divergence and departure from molecular clock. Interestingly, the covarion parameter has little effect on the tree quality for any of the algorithms. FASTME is freely available on the web.     

On the alignment of multiple time series fragments

We consider a local least-squares criterion for aligning multipletime series fragments differing by locations and show the consistencyof the time-lag estimator and the asymptotic normality of thelocation estimator. We apply the criterion to the problem ofaligning 50 glacial varve fragments and construct a 3000-yearsurrogate for global temperature.     

人参药材中人参皂苷与生态因子的相关性及人参生态区划

为了扩大人参(Panax ginseng)栽培面积, 解决人参资源日益短缺的问题, 研究了人参皂苷与生态因子之间的相关性。利用超高效液相(UPLC)色谱法, 测定了辽宁、吉林和黑龙江三省不同产区人参样品中3种人参皂苷(Rg1、Re和Rb1)的含量, 并基于“中药材产地适宜性分析地理信息系统”(TCMGIS)平台, 获得采样区域10个生态因子(包括活动积温、年平均气温、海拔、相对湿度、年日照时数、年降水量、7月最高气温、7月平均气温、1月最低气温和1月平均气温等)数据; 利用因子分析法对16个人参基地进行因子得分评价, 得分最高的是吉林和辽宁的人参基地, 故将吉林和辽宁的人参基地作为人参生态适宜性分析的最佳区域; 通过偏最小二乘回归法建立3种人参皂苷成分与上述10个生态因子间的回归方程并获取其相应的权重, 结果发现多个温度因子与人参皂苷含量呈强负相关关系, 说明热量因子对人参皂苷活性成分的累积起主要作用, 而水分因子、地理因子和光照因子与人参皂苷含量呈弱相关关系; 以因子得分最高的吉林和辽宁人参基地为基点区域, 分别对3种人参皂苷进行单成分生态适宜性区划以及综合区划, 得知3种人参皂苷成分积累的最佳区域主要集中在长白山脉, 而燕山山脉和太行山脉只有少量分布区域。