1,721,054 research outputs found

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The 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

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    “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

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    We 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

    Preliminary results of continuous monitoring of a slope with clayey soils prone to shallow landslides

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    Rainfall-induced shallow landslides are one of the most common type of landslides of the entire world. Besides the limited volume of soil mobilized by these phenomena, they can provoke serious damages to cultivations, infrastructures and buildings due to their high speed of development and their high density in small areas. Shallow landslides triggering is strictly linked with the hydrological and mechanical responses of a usually unsaturated soil to rainfalls. When these phenomena occur in clayey soils, hydro-mechanical behaviors are more complex because of other different physico-chemical processes affecting soil shear strength, such as softening caused by repeated cycles of shrinking-swelling. Thus, to identify the physical and hydrological conditions leading to landslide triggering, a continuous monitoring of unsaturated soil is needed, in particular related to the change in soil hydrological properties related to different rainy or dry periods. This becomes fundamental also for correctly modeling slope safety factor. In this work, the preliminary results of the continuous monitoring of a slope prone to shallow landslides with clayey soils are presented. The test-site is located in Ardivestra catchment (central Oltrepò Pavese, northern Apennines, northwestern Italy). It was affected by several shallow failures in the years 2009-2014. The main aims of this work were: i) to characterize the slope soils by a multidisciplinary point of view; ii) to identify the main soil hydrological behaviors; iii) to recognize the processes and the mechanisms which could promote the triggering of shallow landslide. The test-site soils were characterized by a multidisciplinary point of view, for identifying the features that can influence the soil hydro-mechanical behavior. Soil geotechnical characterization allowed to measure the physical parameters (grain size distribution, Atterberg Limits, volumetric index properties), the shear strength (direct shear tests, oedometric tests), the shrinking-swelling potential. Hydrological characterization determined the water retention and hydraulic conductivity properties. Pedological and mineralogical characterizations were also carried out. Field monitoring allowed to identify the soil hydrological behaviors, linked to different meteorological conditions. The station integrated field devices for measuring soil hydrological parameters (water content, pore water pressure, water electrical conductivity) at different depths, with data of rainfall, air temperature, wind speed and direction. The monitoring period has started in November 2015. These results allowed also for recognizing the predisposing factors and the hydro-mechanical conditions that can lead to trigger shallow landslides. Moreover, these analyses provided important indications for the correct application of slope stability models in slopes with clayey soils

    Soil water content estimated by Support Vector Machine for the assessment of shallow landslides triggering conditions: the role of antecedent meteorological conditions

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    Soil water content is a key parameter for representing water dynamics in soils. Its prediction is fundamental for different practical applications, such as identifying shallow landslides triggering. Support vector machine (SVM) is a machine learning technique, which can be used to predict the temporal trend of a quantity since training from past data. SVM was applied to a test slope of Oltrepò Pavese (northern Italy), where meteorological parameters coupled with soil water content at different depths (0.2, 0.4, 0.6, 1.0, 1.2, 1.4 m) were measured. Two SVM models were developed for water content assessment: (i) model 1, considering rainfall amount, air temperature, air humidity, net solar radiation, and wind speed; (ii) model 2, considering the same predictors of model 1 together with antecedent condition parameters (cumulated rainfall of 7, 30, and 60 days; mean air temperature of 7, 30, and 60 days). SVM model 2 showed significantly higher satisfactory results than model 1, for both training and test phases and for all the considered soil levels. SVM models trends were implemented in a methodology of slope safety factor assessment. For a real event occurred in the tested slope, the triggering time was correctly predicted using data estimated by SVM model based on antecedent meteorological conditions. This confirms the necessity of including these predictors for building a SVM technique able to estimate correctly soil moisture dynamics in time. The results of this paper show a promising potential application of the SVM methodologies for modeling soil moisture required in slope stability analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We 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

    Interaction between education and income on the risk of all-cause mortality: prospective results from the MOLI-SANI study

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    To investigate the separate and inter-related associations of education and household income in relation to all-cause mortality. Prospective study on 16,247 men and women (aeyen35 years), a sub-sample of the MOLI-SANI cohort that had been randomly recruited within an Italian general population. Both education and income were used as categorical variables. Hazard ratios (HR) were calculated by Cox-proportional hazard models. Over a median follow-up of 7.7 years (125,016 person-years), 694 deaths were ascertained. Either education (HR = 0.68; 95 % CI 0.51-0.91) or income (HR = 0.57; 0.42-0.77) was inversely associated with mortality. After simultaneous adjustment, the association of education appeared to be largely explained by income. A significant interaction between both variables was found (p = 0.0078). The inverse association with mortality was stronger when a higher income was combined with a higher educational level (HR = 0.59; 0.38-0.92 for the highest combination of the two indicators). Either education or income was the predictor of mortality in a large sample of the Italian population. The two variables significantly interacted and the inverse association of income with mortality tended to be stronger within higher education groups
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