1,720,960 research outputs found
Multilevel mixed-type data analysis for validating partitions of scrapie isolates
Full text linkThe dissertation arises from a joint study with the Department of Food Safety and Veterinary Public Health of the Istituto Superiore di Sanità. The aim is to investigate and validate the existence of distinct strains of the scrapie disease taking into account the availability of a priori benchmark partition formulated by researchers. Scrapie of small ruminants is caused by prions, which are unconventional infectious agents of proteinaceous nature a ecting humans and animals. Due to the absence of nucleic acids, which precludes direct analysis of strain variation by molecular methods, the presence of di erent sheep scrapie strains is usually investigated by bioassay in laboratory rodents. Data are collected by an experimental study on scrapie conducted at the Istituto Superiore di Sanità by experimental transmission of scrapie isolates to bank voles.
We aim to discuss the validation of a given partition in a statistical classification framework using a multi-step procedure. Firstly, we use unsupervised classification to see how alternative clustering results match researchers’ understanding of the heterogeneity of the isolates. We discuss whether and how clustering results can be eventually exploited to extend the preliminary partition elicited by researchers. Then we motivate the subsequent partition validation based on the predictive performance of several supervised classifiers.
Our data-driven approach contains two main methodological original contributions. We advocate the use of partition validation measures to investigate a given benchmark partition: firstly we discuss the issue of how the data can be used to evaluate a preliminary benchmark partition and eventually modify it with statistical results to find a conclusive partition that could be used as a “gold standard” in future studies. Moreover, collected data have a multilevel structure and for each lower-level unit, mixed-type data are available. Each step in the procedure is then adapted to deal with multilevel mixed-type data. We extend distance-based clustering algorithms to deal with multilevel mixed-type data. Whereas in supervised classification we propose a two-step approach to classify the higher-level units starting from the lower-level observations. In this framework, we also need to define an ad-hoc cross validation algorithm
Registrations decreasing and new possible incentives: investigating EMAS Regulation applying a Structural Equation Modelling approach
No full textThe Environmental Management Systems (EMSs) are a voluntary tool through which companies
can demonstrate their proactive approach towards environmental protection. A survey of the
literature shows that EMSs are effective in order to contribute to a circular economy, setting high
environmental performances. The most widespread EMSs are realized in compliance with the ISO
14001 standard and the EMAS (Eco Management and Audit Scheme) European Regulation. In the
last five years, the number of European organizations with an EMAS registration significantly
dropped. This negative trend occurred also in Italy, where in 2012 for the first time drops out from
EMAS exceeded the new registrations, starting a negative trend. In order to investigate this recent
phenomenon, we conducted a survey targeted to all Italian organizations that dropped out of
EMAS between 2010 and 2015. This article deepens the analysis already presented in a previous
work, applying a Structural Equation Modelling (SEM) approach. We conducted the investigation in
collaboration with ISPRA (Italian Superior Institute for Environmental Protection and Research),
the Italian Competent Body for EMAS. Examining the ISPRA dataset, 397 organizations that did
not renew the certification during the period were identified. We realized data collection between
October and December 2015, obtaining 99 responses with a 25% response rate, that we evaluate
as a good result, considering that the interviewed organizations were not anymore certified, and
often they do not have a responsible in charge of the EMS. The survey has been conducted
through a questionnaire mainly composed of two sections. The main goal of the first part was to
identify the reasons why organizations dropped out of EMAS; the second section aims at identify
policies and support tools that would be most effective in order to encourage new registrations in
the future. We performed an explorative data analysis (EDA) on the results of the survey in order
to find trivial relations among the aspects that determine the non-renewal decision and
expectations to renew the registration. Starting from the EDA results, we build a Structural
Equation Modelling (SEM) dealing with latent variables to summarize the information. In section
one, starting from 44 potential motivations to drop out of the registration, we set eight latent
factors. In section two, we set two latent factors from the ten variables representing actions that
could motivate organization to re-implement EMAS. The aim of this model-based approach is to
find the relationships among not directly observed variables represented by the latent variables on
the SEM. Thus, the primary goal of the research is to identify latent relationships between reasons
to drop out of the scheme and most favorable measures to encourage organization to come back
to EMAS. Results aim at figure out how European and Members States authorities may realize
actions to give new impulse to disseminate EMAS among European companies
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
Dispelling 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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