1,721,021 research outputs found
Raloxifene treatment increases plasma levels of beta-endorphin in postmenopausal women: a randomized, placebo-controlled study.
No full textAbstract
OBJECTIVE:
To evaluate the effect of the selective estrogen receptor modulator raloxifene hydrochloride (Evista, Eli Lilly and Company, Indianapolis, IN) on plasma levels of beta-endorphin, and to determine whether beta-endorphin levels and menopausal symptoms are related.
DESIGN:
A randomized, double-blind, placebo-controlled pilot study.
SETTING:
Endocrinology outpatient department.
PATIENT(S):
Forty postmenopausal women.
INTERVENTION(S):
The women received raloxifene, 60 mg/d, or placebo for 3 months. A questionnaire on climacteric symptoms was administered before and after treatment.
MAIN OUTCOME MEASURE(S):
Circulating levels of beta-endorphin, climacteric symptom score, and correlation with beta-endorphin levels.
RESULT(S):
Raloxifene treatment significantly increased levels of beta-endorphin and did not significantly affect climacteric symptoms, with the exception of worsening vasomotor symptoms. No significant relation was seen between plasma levels of beta-endorphin and climacteric symptoms.
CONCLUSION(S):
Raloxifene modulates plasma levels of beta-endorphin without concomitantly relieving climacteric symptoms, as seen with hormone replacement therapy
Understanding the complexity of computational models through optimization and sloppy parameter analyses: The case of the Connectionist Dual-Process Model
Full text linkA major strength of computational cognitive models is their capacity to accurately predict empirical data. However, challenges in understanding how complex models work and the risk of overfitting have often been addressed by trading off predictive accuracy with model simplification. Here, we introduce state-of-the-art model analysis techniques to show how a large number of parameters in a cognitive model can be reduced into a smaller set that is simpler to understand and can be used to make more constrained predictions with. As a test case, we created different versions of the Connectionist Dual-Process model (CDP) of reading aloud whose parameters were optimized on seven different databases. The results showed that CDP was not overfit and could predict a large amount of variance across those databases. Indeed, the quantitative performance of CDP was higher than that of previous models in this area. Moreover, sloppy parameter analysis, a mathematical technique used to quantify the effects of different parameters on model performance, revealed that many of the parameters in CDP have very little effect on its performance. This shows that the dynamics of CDP are much simpler than its relatively large number of parameters might suggest. Overall, our study shows that cognitive models with large numbers of parameters do not necessarily overfit the empirical data and that understanding the behavior of complex models is more tractable using appropriate mathematical tools. The same techniques could be applied to many different complex cognitive models whenever appropriate datasets for model optimization exist
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
482 How Much Experience Is Required For Aortic Valve Morphology Assessment And Valve Size Selection In Tavr Patients?
No full textAppropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
P6323Exercise capacity as predictor for anaemia or iron deficiency in patients with chronic heart failure
No full textComparison of different software solutions for AVC quantification using contrast enhanced MDCT
No full textDispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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