Classification of jinjiang oysters Crassostrea rivularis (Gould, 1861) from China, based on morphology and phylogenetic analysis

The jinjiang oyster Crassostrea rivularis [Gould, 1861. Descriptions of Shells collected in the North Pacific Exploring Expedition under Captains Ringgold and Rodgers. Proc. Boston Soc. Nat. Hist. 8 (April) 33-40] is one of the most important and best-known oysters in China. Based on the color of its flesh, two forms of C rivularis are recognized and referred to as the "white meat" and 11 red meat" oysters. The classification of white and red forms of this species has been a subject of confusion and debate in China. To clarify the taxonomic status of the two forms of C. rivularis, we collected and analyzed oysters from five locations along China's coast using both morphological characters and DNA sequences from mitochondrial 16S rRNA and cytochrome oxidase 1, and the nuclear 28S rRNA genes. Oysters were classified as white or red forms according to their morphological characteristics and then subjected to DNA sequencing. Both morphological and DNA sequence data suggest that the red and white oysters are two separate species. Phylogenetic analysis of DNA sequences obtained in this study and existing sequences of reference species show that the red oyster is the same species as C. ariakensis Wakiya [1929. Japanese food oysters. Jpn. J. Zool. 2, 359-367.], albeit the red oysters from north and south China are genetically distinctive. The white oyster is the same species as a newly described species from Hong Kong, C. hongkongensis Lam and Morton [2003. Mitochondrial DNA and identification of a new species of Crassostrea (Bivalvia: Ostreidae) cultured for centuries in the Pearl River Delta, Hong Kong, China. Aqua. 228, 1-13]. Although the name C. rivularis has seniority over C. ariakensis and C. hongkongensis, the original description of Ostrea rivularis by Gould [1861] does not fit shell characteristics of either the red or the white oysters. We propose that the name of C. rivularis Gould [1861] should be suspended, the red oyster should take the name C. ariakensis, and the white oyster should take the name C. hongkongensis. (C) 2004 Elsevier B.V. All rights reserved.

Classification of common oysters from North China

Oysters are commonly found on rocky shores along China's northern coast, although there is considerable confusion as to what species they are. To determine the taxonomic status of these oysters, we collected specimens from nine locations north of the Yangtze River and conducted genetic identification using DNA sequences. Fragments from three genes, mitochondrial 165 rRNA, mitochondria! cytochrome oxidase I (COI), and nuclear 285 rRNA, were sequenced in six oysters from each of the nine sites. Phylogenetic analysis of all three gene fragments clearly demonstrated that the small oysters commonly found on intertidal rocks in north China are Crassostrea gigas (Thunberg, 1793), not C. plicatula (the zhe oyster) as widely assumed. Their small size and irregular shell characteristics are reflections of the stressful intertidal environment they live in and not reliable characters for classification. Our study confirms that the oysters from Weifang, referred to as Jinjiang oysters or C. rivularis (Gould, 1861), are C. ariakensis (Wakiya, 1929). We found no evidence for the existence of C. talienwhanensis (Crosse, 1862) and other Crassostrea species in north China. Our study highlights the need for reclassifying oysters of China with molecular data.

共情、共情唤醒机制及共情结果的关系

Empathy was defined as affective experience isomorphic to another person’s affective experience elicited by the person’s affective state in this research. By constructing questionnaires and situational measurement approaches, the relationship among empathy, perspective-taking, imagination, empathic concern, distress, and interconnectedness and helping was analyzed. Perspective-taking and imagination were regarded as arousal mechanisms of empathy. Empathic concern and distress were reactive outcomes of empathy. Interpersonal outcomes of empathy were discussed in this research were empathic interconnectedness and helping. The results showed that perspective-taking had significant positive influence on empathic concern. Empathy partly mediated the effects of perspective-taking on empathic concern. Influence of imagination on empathic distress was partly mediated by empathy also. Perspective-taking had significant negative influence on empathic distress. Empathy had direct effects on its reactive outcomes, and indirect effects on its interpersonal outcomes mediated totally by empathic concern. Classification analysis according to the relationship among empathy, its arousal mechanisms, and reactive outcomes of empathy showed that disposition of empathic reactivity could be divided into 4 styles: general high empathy (22.5%), general low empathy (25.7%), empathic concern (24.4%) and empathic distress (27.3%). 4 styles were different in interpersonal acuity and mental health. It was suggested that adaptive function of 4 styles was different. And the styles of disposition of empathic reactivity significantly predicted situational empathy and its intrapersonal and interpersonal outcomes.

品牌属性权重判断的反应时研究

In current days, many companies have carried out their branding strategies, because strong brand usually provides confidence and reduce risks to its consumers. No matter what a brand is based on tangible products or services, it will possess the common attributes of this category, and it also has its unique attributes. Brand attribute is defined as descriptive features, which are intrinsic characteristics, values or benefits endowed by users of the product or service (Keller, 1993; Romaniuk, 2003). The researches on models of brand multi-attributes are one of the most studied areas of consumer psychology (Werbel, 1978), and attribute weight is one of its key pursuits. Marketing practitioners also paid much attention to evaluations of attributes. Because those evaluations are relevant to the competitiveness and the strategies of promotion and new product development of the company (Green & Krieger, 1995). Then, how brand attributes correlate with weight judgments? And what features the attribute judgment reaction? Especially, what will feature the attribute weight judgment process of consumer who is facing the homogeneity of brands? Enlightened by the lexical hypothesis of researches on personality traits of psychology, this study choose search engine brands as the subject and adopt reaction time, which has been introduced into multi-attributes decision making by many researchers. Researches on independence of affect and cognition and on primacy of affect have cued us that we can categorize brand attributes into informative and affective ones. Meanwhile, Park has gone further to differentiate representative and experiential with functional attributes. This classification reflects the trend of emotion-branding and brand-consumer relationship. Three parts compose the research: the survey to collect attribute words, experiment one on affective primacy and experiment two on correlation between weight judgment and reaction. The results are as follow: In experiment one, we found: (1) affect words are not rated significantly from cognitive attributes, but affect words are responded faster than cognitive ones; (2) subjects comprehend and respond in different ways to functional attribute words and to representative and experiential words. In experiment two, we fund: (1) a significant negative correlation between attributes weight judgment and reaction time; (2) affective attributes will cause faster reaction than cognitive ones; (3) the reaction time difference between functional and representative or experiential attribute is significant, but there is no different between representative and experiential. In sum, we conclude that: (1): In word comprehension and weight judgment, we observed the affective primacy, even when the affect stimulus is presented as meaningful words. (2): The negative correlation between weight judgment and reaction time suggest us that the more important of attribute, the quicker of the reaction. (3): The difference on reaction time of functional, representative and experiential reflects the trend of emotional branding.

Distance Metric Between 3D Models and 3D Images for Recognition and Classification

Similarity measurements between 3D objects and 2D images are useful for the tasks of object recognition and classification. We distinguish between two types of similarity metrics: metrics computed in image-space (image metrics) and metrics computed in transformation-space (transformation metrics). Existing methods typically use image and the nearest view of the object. Example for such a measure is the Euclidean distance between feature points in the image and corresponding points in the nearest view. (Computing this measure is equivalent to solving the exterior orientation calibration problem.) In this paper we introduce a different type of metrics: transformation metrics. These metrics penalize for the deformatoins applied to the object to produce the observed image. We present a transformation metric that optimally penalizes for "affine deformations" under weak-perspective. A closed-form solution, together with the nearest view according to this metric, are derived. The metric is shown to be equivalent to the Euclidean image metric, in the sense that they bound each other from both above and below. For Euclidean image metric we offier a sub-optimal closed-form solution and an iterative scheme to compute the exact solution.

Some Extensions of the K-Means Algorithm for Image Segmentation and Pattern Classification

In this paper we present some extensions to the k-means algorithm for vector quantization that permit its efficient use in image segmentation and pattern classification tasks. It is shown that by introducing state variables that correspond to certain statistics of the dynamic behavior of the algorithm, it is possible to find the representative centers fo the lower dimensional maniforlds that define the boundaries between classes, for clouds of multi-dimensional, mult-class data; this permits one, for example, to find class boundaries directly from sparse data (e.g., in image segmentation tasks) or to efficiently place centers for pattern classification (e.g., with local Gaussian classifiers). The same state variables can be used to define algorithms for determining adaptively the optimal number of centers for clouds of data with space-varying density. Some examples of the applicatin of these extensions are also given.

Gait Dynamics for Recognition and Classification

This paper describes a representation of the dynamics of human walking action for the purpose of person identification and classification by gait appearance. Our gait representation is based on simple features such as moments extracted from video silhouettes of human walking motion. We claim that our gait dynamics representation is rich enough for the task of recognition and classification. The use of our feature representation is demonstrated in the task of person recognition from video sequences of orthogonal views of people walking. We demonstrate the accuracy of recognition on gait video sequences collected over different days and times, and under varying lighting environments. In addition, preliminary results are shown on gender classification using our gait dynamics features.

Multiple Resolution Image Classification

Binary image classifiction is a problem that has received much attention in recent years. In this paper we evaluate a selection of popular techniques in an effort to find a feature set/ classifier combination which generalizes well to full resolution image data. We then apply that system to images at one-half through one-sixteenth resolution, and consider the corresponding error rates. In addition, we further observe generalization performance as it depends on the number of training images, and lastly, compare the system's best error rates to that of a human performing an identical classification task given teh same set of test images.

Permutation Tests for Classification

We introduce and explore an approach to estimating statistical significance of classification accuracy, which is particularly useful in scientific applications of machine learning where high dimensionality of the data and the small number of training examples render most standard convergence bounds too loose to yield a meaningful guarantee of the generalization ability of the classifier. Instead, we estimate statistical significance of the observed classification accuracy, or the likelihood of observing such accuracy by chance due to spurious correlations of the high-dimensional data patterns with the class labels in the given training set. We adopt permutation testing, a non-parametric technique previously developed in classical statistics for hypothesis testing in the generative setting (i.e., comparing two probability distributions). We demonstrate the method on real examples from neuroimaging studies and DNA microarray analysis and suggest a theoretical analysis of the procedure that relates the asymptotic behavior of the test to the existing convergence bounds.

Complex System Classification

The use of terms such as “Engineering Systems”, “System of systems” and others have been coming into greater use over the past decade to denote systems of importance but with implied higher complexity than for the term systems alone. This paper searches for a useful taxonomy or classification scheme for complex Systems. There are two aspects to this problem: 1) distinguishing between Engineering Systems (the term we use) and other Systems, and 2) differentiating among Engineering Systems. Engineering Systems are found to be differentiated from other complex systems by being human-designed and having both significant human complexity as well as significant technical complexity. As far as differentiating among various engineering systems, it is suggested that functional type is the most useful attribute for classification differentiation. Information, energy, value and mass acted upon by various processes are the foundation concepts underlying the technical types.