1,720,968 research outputs found
Implementing screening of undiagnosed obstructive sleep apnea syndrome and comorbidities
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Sampling strategies for estimating forest cover from remote sensing-based two-stage inventories
Full text linkBackground: Remote sensing-based inventories are essential in estimating forest cover in tropical and subtropical countries, where ground inventories cannot be performed periodically at a large scale owing to high costs and forest inaccessibility (e.g. REDD projects) and are mandatory for constructing historical records that can be used as forest
cover baselines. Given the conditions of such inventories, the survey area is partitioned into a grid of imagery segments of pre-fixed size where the proportion of forest cover can be measured within segments using a combination of unsupervised (automated or semi-automated) classification of satellite imagery and manual (i.e. visual on-screen)
enhancements. Because visual on-screen operations are time expensive procedures, manual classification can be performed only for a sample of imagery segments selected at a first stage, while forest cover within each selected segment is estimated at a second stage from a sample of pixels selected within the segment. Because forest cover data arising from unsupervised satellite imagery classification may be freely available (e.g. Landsat imagery) over the entire survey area (wall-to-wall data) and are likely to be good proxies of manually classified cover data (sample data), they can be adopted as suitable auxiliary information.
Methods: The question is how to choose the sample areas where manual classification is carried out. We have investigated the efficiency of one-per-stratum stratified sampling for selecting segments and pixels, where to carry out manual classification and to determine the efficiency of the difference estimator for exploiting auxiliary information at the estimation level. The performance of this strategy is compared with simple random sampling without replacement.
Results: Our results were obtained theoretically from three artificial populations constructed from the Landsat classification (forest/non forest) available at pixel level for a study area located in central Italy, assuming three levels of error rates of the unsupervised classification of satellite imagery. The exploitation of map data as auxiliary information in the difference estimator proves to be highly effective with respect to the Horvitz-Thompson estimator, in which no auxiliary information is exploited. The use of one-per-stratum stratified sampling provides relevant improvement with respect to the use of simple random sampling without replacement.
Conclusions: The use of one-per-stratum stratified sampling with many imagery segments selected at the first stage and few pixels within at the second stage - jointly with a difference estimator - proves to be a suitable strategy to estimate forest cover by remote sensing-based inventories
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
Appropriate 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
Cardiovascular and metabolic comorbidities in patients with obstructive sleep apnoea syndrome
No full text""The purpose of this study was to evaluate the correlation between severity of obstructive sleep apnoea syndrome (OSAS), cardiovascular disease and metabolic syndrome. We recruited 1185 patients with OSAS who underwent a complete ENT examination, including nasolaryngeal fibre optic endoscopy with Müller's manoeuvre, overnight cardio-respiratory monitoring, Epworth Sleepiness Scale (ESS) to measure daytime sleepiness, body mass index (BMI), measurement of blood pressure and blood tests.SUBSEQUENTLY, SUBJECTS WERE DIVIDED INTO THREE SUBGROUPS ACCORDING TO THE APNOEA HYPOPNOEA INDEX (AHI): mild OSAS (AHI 5-15), moderate OSAS (AHI 15-30) and severe OSAS (AHI > 30). In the sample collected, 347 (262 males and 85 females) of 1185 patients suffered from mild OSAS, 363 (269 males and 94 females) from moderate OSAS and 475 (330 males and 145 females) from severe OSAS. In the group suffering from mild OSAS, we found: 127 patients affected by hypertension, 48 with diabetes, 11 with dyslipidaemia and 32 with metabolic syndrome. In the group with moderate OSAS there were 157 patients with hypertension, 63 with diabetes, 72 with dyslipidaemia and 47 with metabolic syndrome. In the group suffering from severe OSAS there were 244 patients with hypertension, 138 with diabetes, 47 with dyslipidaemia and 90 with metabolic syndrome. For data analysis, we used the Spearman correlation test adjusted according to Sidak between the dependent variable AHI and the independent variables BMI, ESS, average SO2 (SO(2med)), hypertension, diabetes mellitus, dyslipidaemia and metabolic syndrome. The results show different patterns of correlation in terms of statistical significance: BMI ρ(s) = 0.26, SO(2med) ρ(s) = -0:51, hypertension ρ(s) = -0.05, dyslipidaemia ρ(s) = 0.22 for women, and BMI ρ(s) = 0.53, ESS ρ(s) = 0.28, SO(2med) ρ(s) = -0.50, hypertension ρ(s) = 0.17, diabetes mellitus ρ(s) = 0.28 and metabolic syndrome ρ(s) = 0.26 for men. The results of the study confirm the existence of a statistically significant correlation between the severity of OSAS and BMI, ESS, average SO2, hypertension, diabetes mellitus, dyslipidaemia and metabolic syndrome."
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