26 resultados para Metadata schema

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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Background This study addressed the temporal properties of personality disorders and their treatment by schema-centered group psychotherapy. It investigated the change mechanisms of psychotherapy using a novel method by which psychotherapy can be modeled explicitly in the temporal domain. Methodology and Findings 69 patients were assigned to a specific schema-centered behavioral group psychotherapy, 26 to social skills training as a control condition. The largest diagnostic subgroups were narcissistic and borderline personality disorder. Both treatments offered 30 group sessions of 100 min duration each, at a frequency of two sessions per week. Therapy process was described by components resulting from principal component analysis of patients' session-reports that were obtained after each session. These patient-assessed components were Clarification, Bond, Rejection, and Emotional Activation. The statistical approach focused on time-lagged associations of components using time-series panel analysis. This method provided a detailed quantitative representation of therapy process. It was found that Clarification played a core role in schema-centered psychotherapy, reducing rejection and regulating the emotion of patients. This was also a change mechanism linked to therapy outcome. Conclusions/Significance The introduced process-oriented methodology allowed to highlight the mechanisms by which psychotherapeutic treatment became effective. Additionally, process models depicted the actual patterns that differentiated specific diagnostic subgroups. Time-series analysis explores Granger causality, a non-experimental approximation of causality based on temporal sequences. This methodology, resting upon naturalistic data, can explicate mechanisms of action in psychotherapy research and illustrate the temporal patterns underlying personality disorders.

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The "Schema-focussed Emotive Behavioral Therapy" (SET) was developed by our research group as a new group therapy approach for patients with personality disorders from all clusters (A to C; DSM-IV). It was evaluated in a randomised controlled study (n = 93). Data were collected before and after treatment as well as one year after study entry. A completer analysis was conducted with matched subgroups (n = 60). After therapy, SET patients improved in the outcome domains interactional behavior, strain, and symptomatic complaints (IIP-D, GAF, VEV-VW, BSI-P). Furthermore, they showed a significant lower dropout rate. At the follow-up assessment, Cluster C patients of the experimental group deteriorated with regard to symptomatic complaints (BSI-P). In contrast, cluster B patients improved more over time compared to control subjects. SET seems to be an adequate and effective group therapy with effects that seem to be stable over time, especially for patients with Cluster B diagnosis.

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Foreknowledge about the demands of an upcoming trial may be exploited to optimize behavioural responses. In the current study we systematically investigated the benefits of partial foreknowledge--that is, when some but not all aspects of a future trial are known in advance. For this we used an ocular motor paradigm with horizontal prosaccades and antisaccades. Predictable sequences were used to create three partial foreknowledge conditions: one with foreknowledge about the stimulus location only, one with foreknowledge about the task set only, and one with foreknowledge about the direction of the required response only. These were contrasted with a condition of no-foreknowledge and a condition of complete foreknowledge about all three parameters. The results showed that the three types of foreknowledge affected saccadic efficiency differently. While foreknowledge about stimulus-location had no effect on efficiency, task foreknowledge had some effect and response-foreknowledge was as effective as complete foreknowledge. Foreknowledge effects on switch costs followed a similar pattern in general, but were not specific for switching of the trial attribute for which foreknowledge was available. We conclude that partial foreknowledge has a differential effect on efficiency, most consistent with preparatory activation of a motor schema in advance of the stimulus, with consequent benefits for both switched and repeated trials.

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Eosinophilia is an important indicator of various neoplastic and nonneoplastic conditions. Depending on the underlying disease and mechanisms, eosinophil infiltration can lead to organ dysfunction, clinical symptoms, or both. During the past 2 decades, several different classifications of eosinophilic disorders and related syndromes have been proposed in various fields of medicine. Although criteria and definitions are, in part, overlapping, no global consensus has been presented to date. The Year 2011 Working Conference on Eosinophil Disorders and Syndromes was organized to update and refine the criteria and definitions for eosinophilic disorders and to merge prior classifications in a contemporary multidisciplinary schema. A panel of experts from the fields of immunology, allergy, hematology, and pathology contributed to this project. The expert group agreed on unifying terminologies and criteria and a classification that delineates various forms of hypereosinophilia, including primary and secondary variants based on specific hematologic and immunologic conditions, and various forms of the hypereosinophilic syndrome. For patients in whom no underlying disease or hypereosinophilic syndrome is found, the term hypereosinophilia of undetermined significance is introduced. The proposed novel criteria, definitions, and terminologies should assist in daily practice, as well as in the preparation and conduct of clinical trials.

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[1] Instrumental temperature series are often affected by artificial breaks (“break points”) due to (e.g.,) changes in station location, land-use, or instrumentation. The Swiss climate observation network offers a high number and density of stations, many long and relatively complete daily to sub-daily temperature series, and well-documented station histories (i.e., metadata). However, for many climate observation networks outside of Switzerland, detailed station histories are missing, incomplete, or inaccessible. To correct these records, the use of reliable statistical break detection methods is necessary. Here, we apply three statistical break detection methods to high-quality Swiss temperature series and use the available metadata to assess the methods. Due to the complex terrain in Switzerland, we are able to assess these methods under specific local conditions such as the Foehn or crest situations. We find that the temperature series of all stations are affected by artificial breaks (average = 1 break point / 48 years) with discrepancies in the abilities of the methods to detect breaks. However, by combining the three statistical methods, almost all of the detected break points are confirmed by metadata. In most cases, these break points are ascribed to a combination of factors in the station history.

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This review deals with an important aspect of organ transplantation, namely the process of psychic organ integration and organ-related fantasies. The body schema and body self are two important concepts in the integration of a transplanted organ. Different models and theories on organ integration are presented and will be discussed. There is evidence that beside the emotional impact and the influence on well-being, organ integration depends closely on psychic processes involving in the incorporation of the transplanted organ and the respective organ-related fantasies. Therefore, these organ fantasies - whether unconscious or conscious - may play an important role in the future development of the instinctive and highly individual relation the patients elaborate with the new organ. Beside the concern with the new organ, a bereavement to the lost old and sick organ may also influence the patients thoughts. Moreover, the good resolving of all these issues evokes the "good practice" patients develop towards the new situation. This will bring up issues as compliance, infections, rejection episodes and - most important - also organ survival.

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Pasteurellaceae are bacteria with an important role as primary or opportunistic, mainly respiratory, pathogens in domestic and wild animals. Some species of Pasteurellaceae cause severe diseases with high economic losses in commercial animal husbandry and are of great diagnostic concern. Because of new data on the phylogeny of Pasteurellaceae, their taxonomy has recently been revised profoundly, thus requiring an improved phenotypic differentiation procedure to identify the individual species of this family. A new and simplified procedure to identify species of Actinobacillus, Avibacterium, Gallibacterium, Haemophilus, Mannheimia, Nicoletella, and Pasteurella, which are most commonly isolated from clinical samples of diseased animals in veterinary diagnostic laboratories, is presented in the current study. The identification procedure was evaluated with 40 type and reference strains and with 267 strains from routine diagnostic analysis of various animal species, including 28 different bacterial species. Type, reference, and field strains were analyzed by 16S ribosomal RNA (rrs) and rpoB gene sequencing for unambiguous species determination as a basis to evaluate the phenotypic differentiation schema. Primary phenotypic differentiation is based on beta-nicotinamide adenine dinucleotide (beta-NAD) dependence and hemolysis, which are readily determined on the isolation medium. The procedure divides the 28 species into 4 groups for which particular biochemical reactions were chosen to identify the bacterial species. The phenotypic identification procedure allowed researchers to determine the species of 240 out of 267 field strains. The procedure is an easy and cost-effective system for the rapid identification of species of the Pasteurellaceae family isolated from clinical specimens of animals.

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Historical, i.e. pre-1957, upper-air data are a valuable source of information on the state of the atmosphere, in some parts of the world dating back to the early 20th century. However, to date, reanalyses have only partially made use of these data, and only of observations made after 1948. Even for the period between 1948 (the starting year of the NCEP/NCAR (National Centers for Environmental Prediction/National Center for Atmospheric Research) reanalysis) and the International Geophysical Year in 1957 (the starting year of the ERA-40 reanalysis), when the global upper-air coverage reached more or less its current status, many observations have not yet been digitised. The Comprehensive Historical Upper-Air Network (CHUAN) already compiled a large collection of pre-1957 upper-air data. In the framework of the European project ERA-CLIM (European Reanalysis of Global Climate Observations), significant amounts of additional upper-air data have been catalogued (> 1.3 million station days), imaged (> 200 000 images) and digitised (> 700 000 station days) in order to prepare a new input data set for upcoming reanalyses. The records cover large parts of the globe, focussing on, so far, less well covered regions such as the tropics, the polar regions and the oceans, and on very early upper-air data from Europe and the US. The total number of digitised/inventoried records is 61/101 for moving upper-air data, i.e. data from ships, etc., and 735/1783 for fixed upper-air stations. Here, we give a detailed description of the resulting data set including the metadata and the quality checking procedures applied. The data will be included in the next version of CHUAN. The data are available at doi:10.1594/PANGAEA.821222

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In a fast changing world with growing concerns about biodiversity loss and an increasing number of animal and human diseases emerging from wildlife, the need for effective wildlife health investigations including both surveillance and research is now widely recognized. However, procedures applicable to and knowledge acquired from studies related to domestic animal and human health can be on partly extrapolated to wildlife. This article identifies requirements and challenges inherent in wildlife health investigations, reviews important definitions and novel health investigation methods, and proposes tools and strategies for effective wildlife health surveillance programs. Impediments to wildlife health investigations are largely related to zoological, behavioral and ecological characteristics of wildlife populations and to limited access to investigation materials. These concerns should not be viewed as insurmountable but it is imperative that they are considered in study design, data analysis and result interpretation. It is particularly crucial to remember that health surveillance does not begin in the laboratory but in the fields. In this context, participatory approaches and mutual respect are essential. Furthermore, interdisciplinarity and open minds are necessary because a wide range of tools and knowledge from different fields need to be integrated in wildlife health surveillance and research. The identification of factors contributing to disease emergence requires the comparison of health and ecological data over time and among geographical regions. Finally, there is a need for the development and validation of diagnostic tests for wildlife species and for data on free-ranging population densities. Training of health professionals in wildlife diseases should also be improved. Overall, the article particularly emphasizes five needs of wildlife health investigations: communication and collaboration; use of synergies and triangulation approaches; investments for the long term; systematic collection of metadata; and harmonization of definitions and methods.

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Traditional methods do not actually measure peoples’ risk attitude naturally and precisely. Therefore, a fuzzy risk attitude classification method is developed. Since the prospect theory is usually considered as an effective model of decision making, the personalized parameters in prospect theory are firstly fuzzified to distinguish people with different risk attitudes, and then a fuzzy classification database schema is applied to calculate the exact value of risk value attitude and risk be- havior attitude. Finally, by applying a two-hierarchical clas- sification model, the precise value of synthetical risk attitude can be acquired.