The intersectional hybrid between Weigela hortensis and W. maximowiczii (Caprifoliaceae)

Morphologically intermediate plants between Weigela hortensis (Siebold & Zucc.) K.Koch and W. maximowiczii (S.Moore) Rehder have been found in Miyagi and Yamagata Pref., northern Japan. Quantitative character analyses of flowers, pollen stainability and molecular analyses indicated that the intermediate plants were hybrids of those two species. This is the first record of an intersectional hybrid with W. maximowiczii (sect. Weigelastrum ) as one of the parent species. The morphological differences among hybrid individuals imply the possibility of backcrosses or formation of second or later generations of hybrids, although those may be quite rare because of a low frequency of viable pollen grains. Causes of hybridization between two distantly-related species in Weigela are discussed. © 2002 The Linnean Society of London, Botanical Journal of the Linnean Society , 2002, 138 , 369–380.     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.

     

Parameter estimation for the distribution of single cell lag times

In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level.We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.     

Can transposable element copy number distribution parameters be estimated from natural populations of Drosophila melanogaster?

The copy frequency distribution of a transposable element family in a Drosophila melanogaster natural population is generally characterised by the values of the Charlesworths' model parameters α and β (Charlesworth & Charlesworth, 1983). The estimation of these parameters is made using the observed distribution of the occupied sites in a population sample. Several results have been interpreted as due either to the influence of stochastic factors or to deterministic factors (transposition, excision, selection…). The accuracy of this method was tested by estimations performed on samples from simulated populations. The results show that with the sample size usually used for natural population studies, the confidence intervals are too large to reasonably deduce either the element copy number distribution or the values of transposition and excision rate and selective coefficients.     

Confidence Intervals for the Risk Ratio in Cohort Studies under Inverse Sampling

Three simple interval estimates for the risk ratio in inverse sampling are considered. The first two interval estimates are derived on the basis of Fieller's Theorem and the delta method with the logarithmic transformation, respectively. The third interval estimate is derived on the basis of an F-test statistic proposed by BENNETT (1981) for testing equal probabilities of a disease between two comparison groups when the disease is rare. To evaluate the performance of these three methods, a Monte Carlo simulation is used to compare the actual coverage probability with the nominal confidence level for each method and to estimate the expected length of the corresponding confidence interval in a variety of situations. On the basis of the results found in the simulation, we have concluded that the method with the logarithmic transformation is either equivalent to or better than the other two methods for all situations considered here.     

On blocking rules for the bootstrap with dependent data

We address the issue of optimal block choice in applicationsof the block bootstrap to dependent data. It is shown that optimalblock size depends significantly on context, being equal ton^1/3, n^1/4 and n^1/5 in the cases of variance or bias estimation,estimation of a onesided distribution function, and estimationof a two-sided distribution function, respectively. A clearintuitive explanation of this phenomenon is given, togetherwith outlines of theoretical arguments in specific cases. Itis shown that these orders of magnitude of block sizes can beused to produce a simple, practical rule for selecting blocksize empirically. That technique is explored numerically.     

Comparing Stochastically Restricted Linear Estimators in a Regression Model

Conditions for superiority of the minimum dispersion estimator over another with respect to the covariance matrix are derived when the vector parameter of a regression model is subject to competing stochastic restrictions. The restrictions may also consist both of a deterministic part and a stochastic part.     

Structural variability of C3larvin toxin. Intrinsic dynamics of the α/β fold of the C3-like group of mono-ADP-ribosyltransferase toxins

C3larvin toxin is a new member of the C3 class of the mono-ADP-ribosyltransferase toxin family. The C3 toxins are known to covalently modify small G-proteins, e.g. RhoA, impairing their function, and serving as virulence factors for an offending pathogen. A full-length X-ray structure of C3larvin (2.3 Å) revealed that the characteristic mixed α/β fold consists of a central β-core flanked by two helical regions. Topologically, the protein can be separated into N and C lobes, each formed by a β-sheet and an α-motif, and connected by exposed loops involved in the recognition, binding, and catalysis of the toxin/enzyme, i.e. the ADP-ribosylation turn–turn and phosphate–nicotinamide PN loops. Herein, we provide two new C3larvin X-ray structures and present a systematic study of the toxin dynamics by first analyzing the experimental variability of the X-ray data-set followed by contrasting those results with theoretical predictions based on Elastic Network Models (GNM and ANM). We identify residues that participate in the stability of the N-lobe, putative hinges at loop residues, and energy-favored deformation vectors compatible with conformational changes of the key loops and 3D-subdomains (N/C-lobes), among the X-ray structures. We analyze a larger ensemble of known C3bot1 conformations and conclude that the characteristic ‘crab-claw’ movement may be driven by the main intrinsic modes of motion. Finally, via computational simulations, we identify harmonic and anharmonic fluctuations that might define the C3larvin ‘native state.’ Implications for docking protocols are derived.