145 resultados para 187-1155A


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This paper uses dynamic computer simulation techniques to develop and apply a multi-criteria procedure using non-destructive vibration-based parameters for damage assessment in truss bridges. In addition to changes in natural frequencies, this procedure incorporates two parameters, namely the modal flexibility and the modal strain energy. Using the numerically simulated modal data obtained through finite element analysis of the healthy and damaged bridge models, algorithms based on modal flexibility and modal strain energy changes before and after damage are obtained and used as the indices for the assessment of structural health state. The application of the two proposed parameters to truss-type structures is limited in the literature. The proposed multi-criteria based damage assessment procedure is therefore developed and applied to truss bridges. The application of the approach is demonstrated through numerical simulation studies of a single-span simply supported truss bridge with eight damage scenarios corresponding to different types of deck and truss damage. Results show that the proposed multi-criteria method is effective in damage assessment in this type of bridge superstructure.

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Aim: The primary purpose of this meta-analysis was to explore, clarify and report the strength of the relationship between alexithymia, as measured by the Toronto Alexithymia Scale (TAS-20), and parenting style as measured by the Parental Bonding Instrument (PBI). Methods: Web of Science, PsycInfo, PubMed and ProQuest: Dissertations and Theses searches were undertaken, yielding nine samples with sufficient data to be included in the meta-analysis. Results: Evidence indicated moderate to strong relationships between maternal care and alexithymia, and between maternal care and two of the three TAS-20 alexithymia facets (Difficulties Describing Feelings and Difficulties Identifying Feelings, but not Externally Oriented Thinking). Moderate relationships were observed for both maternal- and paternal-overprotection and alexithymia respectively, and for overprotection (both maternal and paternal) and Difficulties Describing Feelings. Conclusion: This study is the first meta-analysis of the relationship between parenting styles and alexithymia, and findings confirm an especially strong association between maternal care and key elements of alexithymia. This review highlights the issues that still remain to be addressed in exploring the link between parenting style and alexithymia.

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Endometrial carcinoma is the most common gynecological malignancy in the United States. Although most women present with early disease confined to the uterus, the majority of persistent or recurrent tumors are refractory to current chemotherapies. We have identified a total of 11 different FGFR2 mutations in 3/10 (30%) of endometrial cell lines and 19/187 (10%) of primary uterine tumors. Mutations were seen primarily in tumors of the endometrioid histologic subtype (18/115 cases investigated, 16%). The majority of the somatic mutations identified were identical to germline activating mutations in FGFR2 and FGFR3 that cause Apert Syndrome, Beare-Stevenson Syndrome, hypochondroplasia, achondroplasia and SADDAN syndrome. The two most common somatic mutations identified were S252W (in eight tumors) and N550K (in five samples). Four novel mutations were identified, three of which are also likely to result in receptor gain-of-function. Extensive functional analyses have already been performed on many of these mutations, demonstrating they result in receptor activation through a variety of mechanisms. The discovery of activating FGFR2 mutations in endometrial carcinoma raises the possibility of employing anti-FGFR molecularly targeted therapies in patients with advanced or recurrent endometrial carcinoma.

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According to the diagnosis of schizophrenia in the DSM-IV-TR (American Psychiatric Association, 2000), negative symptoms are those personal characteristics that are thought to be reduced from normal functioning, while positive symptoms are aspects of functioning that exist as an excess or distortion of normal functioning. Negative symptoms are generally considered to be a core feature of people diagnosed with schizophrenia. However, negative symptoms are not always present in those diagnosed, and a diagnosis can be made with only negative or only positive symptoms, or with a combination of both. Negative symptoms include an observed loss of emotional expression (affective flattening), loss of motivation or self directedness (avolition), loss of speech (alogia), and also a loss of interests and pleasures (anhedonia). Positive symptoms include the perception of things that others do not perceive (hallucinations), and extraordinary explanations for ordinary events (delusions) (American Psychiatric Association, 2000). Both negative and positive symptoms are derived from watching the patient and thus do not consider the patient’s subjective experience. However, aspects of negative symptoms, such as observed affective flattening are highly contended. Within conventional psychiatry, the absence of emotional expression is assumed to coincide with an absence of emotional experience. Contrasting research findings suggests that patients who were observed to score low on displayed emotional expression, scored high on self ratings of emotional experience. Patients were also observed to be significantly lower on emotional expression when compared with others (Aghevli, Blanchard, & Horan, 2003; Selton, van der Bosch, & Sijben, 1998). It appears that there is little correlation between emotional experience and emotional expression in patients, and that observer ratings cannot help us to understand the subjective experience of the negative symptoms. This chapter will focus on research into the subjective experiences of negative symptoms. A framework for these experiences will be used from the qualitative research findings of the primary author (Le Lievre, 2010). In this study, the primary author found that subjective experiences of the negative symptoms belonged to one of the two phases of the illness experience; “transitioning into emotional shutdown” or “recovering from emotional shutdown”. This chapter will use the six themes from the phase of “transitioning into emotional shutdown”. This phase described the experience of turning the focus of attention away from the world and onto the self and the past, thus losing contact with the world and others (emotional shutdown). Transitioning into emotional shutdown involved; “not being acknowledged”, “relational confusion”, “not being expressive”, “reliving the past”, “detachment”, and “no sense of direction” (Le Lievre, 2010). Detail will be added to this framework of experience from other qualitative research in this area. We will now review the six themes that constitute a “transition into emotional shutdown” and corresponding previous research findings.

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Existing recommendation systems often recommend products to users by capturing the item-to-item and user-to-user similarity measures. These types of recommendation systems become inefficient in people-to-people networks for people to people recommendation that require two way relationship. Also, existing recommendation methods use traditional two dimensional models to find inter relationships between alike users and items. It is not efficient enough to model the people-to-people network with two-dimensional models as the latent correlations between the people and their attributes are not utilized. In this paper, we propose a novel tensor decomposition-based recommendation method for recommending people-to-people based on users profiles and their interactions. The people-to-people network data is multi-dimensional data which when modeled using vector based methods tend to result in information loss as they capture either the interactions or the attributes of the users but not both the information. This paper utilizes tensor models that have the ability to correlate and find latent relationships between similar users based on both information, user interactions and user attributes, in order to generate recommendations. Empirical analysis is conducted on a real-life online dating dataset. As demonstrated in results, the use of tensor modeling and decomposition has enabled the identification of latent correlations between people based on their attributes and interactions in the network and quality recommendations have been derived using the 'alike' users concept.

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Nursing training for an Intensive Care Unit (ICU) is a resource intensive process. High demands are made on staff, students and physical resources. Interactive, 3D computer simulations, known as virtual worlds, are increasingly being used to supplement training regimes in the health sciences; especially in areas such as complex hospital ward processes. Such worlds have been found to be very useful in maximising the utilisation of training resources. Our aim is to design and develop a novel virtual world application for teaching and training Intensive Care nurses in the approach and method for shift handover, to provide an independent, but rigorous approach to teaching these important skills. In this paper we present a virtual world simulator for students to practice key steps in handing over the 24/7 care requirements of intensive care patients during the commencing first hour of a shift. We describe the modelling process to provide a convincing interactive simulation of the handover steps involved. The virtual world provides a practice tool for students to test their analytical skills with scenarios previously provided by simple physical simulations, and live on the job training. Additional educational benefits include facilitation of remote learning, high flexibility in study hours and the automatic recording of a reviewable log from the session. To the best of our knowledge, we believe this is a novel and original application of virtual worlds to an ICU handover process. The major outcome of the work was a virtual world environment for training nurses in the shift handover process, designed and developed for use by postgraduate nurses in training.