1,720,997 research outputs found
Contingent valuation per un piano di riassetto del verde pubblico nel Quartiere di San Benedetto a Cagliari
No full textUn’applicazione di analisi multicriteri per il ranking di due alternative di piano per il Parco naturale di Molentargius
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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
Analisi multicriteri e supporto al piano: una sperimentazione riferita ad un’area protetta della Sardegna
No full textDirect analysis of volumetric absorptive micro sampling (VAMS) devices by ATR-FT-MIR and chemometric analysis: a new challenge
No full textVolumetric Absorptive Micro Sampling (VAMS) strategy, in its simplicity, has made a major contribution to the development of at-home sampling strategies. Mainly used for blood analysis, it absorbs a fixed volume of sample. Folded into its cover, the VAMS device dries, and it can be sent to a lab via mail. In this article, for the first time in our knowledge, we explored the possibility to use this sampling strategy to expand the scope of VAMS to other samples than clinical ones. In this way we used VAMS to sample and analyze milk, which is one of the most important and analyzed samples all over the world. VAMS devices were employed to sample commercial milk samples from Italy, Switzerland and Spain, and for the first time the device was directly analyzed by ATR-FT-IR to predict protein, carbohydrate and fat content in the milk samples. Samples were collected in different sessions from different persons and analyzed by different lab operators to include in the models these sources of variability. Multivariate regression was used to correlate ATR-FT-IR spectra with the investigated properties: models were validated with external validation
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
Navigating the complexity: Managing multivariate error and uncertainties in spectroscopic data modelling
Full text linkSpectroscopy and chemometrics, supported by computer science, have yielded promising outcomes, as evidenced by trends observed in literature searches. However, while researchers meticulously construct chemometric models for exploratory, quantitation and classification purposes, the investigation of data quality, particularly error analysis, remains less frequent. Understanding and quantifying measurement errors is crucial for robust spectroscopic modeling and uncertainty estimation. By unraveling complexities related to multivariate errors and
uncertainties in spectroscopic data, the scientific community is empowered to extract reliable information from spectroscopic analyses, paving the way for enhanced analytical practices. This review underscores the necessity for the scientific community to integrate error analysis and uncertainty estimation into multivariate analysis methods, offering tailored solutions for diverse data types and analysis objectives
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