Sequential Patterns (sequential + pattern)

Distribution by Scientific Domains

Selected Abstracts

Expression of Oestrogen Receptor , During Development of the Skeleton in Mice Fetuses: Immunohistochemical Study

E. Lovsin Barle
Summary Sequential pattern of ossification and expression of oestrogen receptor , (ER,) during development of the skeleton in male and female mice fetuses was investigated. Twenty-seven mice fetuses of gestational age between 14.5 and 18.5 days post coitum (p.c.) were examined by haematoxylin,eosin and toluidine blue staining to determine the ossification. The presence of ER, was detected by immunostaining using ER,-specific antibodies. Ossification centres were determined in fetuses of 14.5 days p.c. of both sexes in the base of skull, ribs and front limbs, while in the mandible ossification was observed only in female fetuses at that age. ER, was found in all investigated tissues in which the occurrence of ossification centres was determined. ER, was first detected in some tissues involved in ossification at 14.5 days p.c. in fetuses of both genders. There were some minor gender differences in the pattern of ER, expression. ER, was localized in the metatarsal chondrogenic condensations at 14.5 days p.c. and in phalangeal chondrocytes at 17.5 and 18.5 days p.c. only in females. ER,-positive osteogenic cells at 14.5 days p.c. in the mandible were seen only in females. At 16.5 days p.c. male but not female fetuses expressed ER, in the vertebrae. Our findings support the view that ER, protein is found in the tissues that undergo bone formation and that ER, expression in these tissues shows only minor gender differences in mice fetuses. [source]

Substantia nigra pars reticulata neurons code initiation of a serial pattern: implications for natural action sequences and sequential disorders

Melanie Meyer-Luehmann
Abstract Sequences of movements are initiated abnormally in neurological disorders involving basal ganglia dysfunction, such as Parkinson's disease or Tourette's syndrome. The substantia nigra pars reticulata (SNpr) is one of the two primary output structures of the basal ganglia. However, little is known about how substantia nigra mediates the initiation of normal movement sequences. We studied its role in coding initiation of a sequentially stereotyped but natural movement sequence by recording neuronal activity in SNpr during behavioural performance of ,syntactic grooming chains'. These are rule-governed sequences of up to 25 grooming movements emitted in four predictable (syntactic) phases, which occur spontaneously during grooming behaviour by rats and other rodents. Our results show that neuronal activation in central SNpr codes the onset of this entire rule-governed sequential pattern of grooming actions, not elemental grooming movements. We conclude that the context of sequential pattern may be more important than the elemental motor parameters in determining SNpr neuronal activation. [source]

Using discourse analysis and psychological sense of community to understand school transitions

Stephen J. Fyson
The research involved examining the nature of the transition that students experienced in progressing to junior high school from primary school. Students' experiences were chosen as the focus of the research because the issue of substance being investigated was that of alienation. The main methodology that was used was the qualitative procedure of discourse analysis, implemented over a 3-year period. This report describes the findings from the first year of the study. The key findings of the research include the establishment of critical concerns of students. These critical concerns were articulated as psychological sense of community categories of interest, with positive and negative discourse descriptors being developed according to an analysis of students' descriptions of social regularities. The categories of interest were arranged into a sequential pattern that described pathways to increasing commitment or alienation. 2008 Wiley Periodicals, Inc. [source]

Mining interval sequential patterns

Ding-An Chiang
The main task of mining sequential patterns is to analyze the transaction database of a company in order to find out the priorities of items that most customers take when consuming. In this article, we propose a new method,the ISP Algorithm. With this method, we can find out not only the order of consumer items of each customer, but also offer the periodic interval of consumer items of each customer. Compared with other previous periodic association rules, the difference is that the period the algorithm provides is not the repeated purchases in a regular time, but the possible repurchases within a certain time frame. The algorithm utilizes the transaction time interval of individual customers and that of all the customers to find out when and who will buy goods, and what items of goods they will buy. 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 359,373, 2005. [source]

Mining interesting sequential patterns for intelligent systems

Show-Jane Yen
Mining sequential patterns means to discover sequential purchasing behaviors of most customers from a large number of customer transactions. Past transaction data can be analyzed to discover customer purchasing behaviors such that the quality of business decisions can be improved. However, the size of the transaction database can be very large. It is very time consuming to find all the sequential patterns from a large database, and users may be only interested in some sequential patterns. Moreover, the criteria of the discovered sequential patterns for user requirements may not be the same. Many uninteresting sequential patterns for user requirements can be generated when traditional mining methods are applied. Hence, a data mining language needs to be provided such that users can query only knowledge of interest to them from a large database of customer transactions. In this article, a data mining language is presented. From the data mining language, users can specify the items of interest and the criteria of the sequential patterns to be discovered. Also, an efficient data mining technique is proposed to extract the sequential patterns according to the users' requests. 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 73,87, 2005. [source]

Pattern recognition as a caring partnership in families with cancer

Emiko Endo RN PhD
Pattern recognition as a caring partnership in families with cancer The purpose of this study was to address the process of a caring partnership by elaborating pattern recognition as nursing intervention with families with cancer. It is based on Newman's theory of health as expanding consciousness within the unitary-transformative paradigm and is an extension of a previous study of Japanese women with ovarian cancer. A hermeneutic, dialectic method was used to engage 10 Japanese families in which the wife-mothers were hospitalized because of cancer diagnosis. The family included at least the woman with cancer and her primary caregiver. Each of four nurse-researchers entered into partnership with a different family and conducted three interviews with each family. The participants were asked to describe the meaningful persons and events in their family history. The family's story was transmuted into a diagram of sequential patterns of interactional configurations and shared with the family at the second meeting. Evidence of pattern recognition and insight into the meaning of the family pattern were identified further in the remaining meetings. The data revealed five dimensions of a transformative process. Most families found meaning in their patterns and made a shift from separated individuals within the family to trustful caring relationships. One-third of them went through this process within two interviews. The families showed increasing openness, connectedness and trustfulness in caring relationships. In partnership with the family, each nurse-researcher grasped the pattern of the family as a whole and experienced the meaning of caring. Pattern recognition as nursing intervention was a meaning-making transforming process in the family,nurse partnership. [source]

Direct Associations or Internal Transformations?

Exploring the Mechanisms Underlying Sequential Learning Behavior
Abstract We evaluate two broad classes of cognitive mechanisms that might support the learning of sequential patterns. According to the first, learning is based on the gradual accumulation of direct associations between events based on simple conditioning principles. The other view describes learning as the process of inducing the transformational structure that defines the material. Each of these learning mechanisms predicts differences in the rate of acquisition for differently organized sequences. Across a set of empirical studies, we compare the predictions of each class of model with the behavior of human subjects. We find that learning mechanisms based on transformations of an internal state, such as recurrent network architectures (e.g., Elman, 1990), have difficulty accounting for the pattern of human results relative to a simpler (but more limited) learning mechanism based on learning direct associations. Our results suggest new constraints on the cognitive mechanisms supporting sequential learning behavior. [source]