1,721,090 research outputs found
Per Giani e Carlo Stuparich
No full textLa postfazione disegna un ritratto storico-letterario dei fratelli Stuparich e ricostruisce le circostanze del loro passaggio sui monti Lessini. Giani e Carlo Stuparich, volontari triestini, colaboratori della «Voce», vennero nominati ufficiali della Milizia Territoriale (Giani a Vicenza, Carlo a Verona) dopo essere sopravvissuti ai primi due mesi di guerra di trincea sul Carso. E da Verona, nel settembre 1915, Carlo partì con il suo battaglione per costruire una strada militare nel cuore dei monti Lessini: la strada di Podestaria. Ventidue anni dopo Giani tornò in pellegrinaggio nei luoghi dove il fratello, morto in combattimento nel 1916, aveva soggiornato. Il racconto di quell’esperienza (in origine un elzeviro uscito nella terza pagina de «La Stampa» nel 1937) è qui riunito alle diciotto lettere che Carlo spedì a Giani da Verona e da Bosco Chiesanuova; lettere che vengono per la prima volta pubblicate nel loro testo integrale
Il carteggio di Giani e Carlo Stuparich (1913-1914): la formazione letteraria di due fratelli
No full textLo studio prende in esame lo scambio epistolare intercorso tra Giani e Carlo Stuparich negli anni 1913-1914. Il materiale epistolare, in parte inedito, è custodito nell’Archivio diplomatico della Biblioteca Civica A. Hortis di Trieste, nell’Archivio degli scrittori e della cultura regionale dell’Università degli Studi di Trieste e nell’Archivio familiare di Roma. L’analisi fa luce sulla formazione umana e letteraria dei due fratelli e permette di ricostruire i loro legami con il milieu intellettuale di primo Novecento
Prediction of Soil Sorption Partition Coefficient of Heterogeneous Organic Non-Ionic Compounds from Molecular Structure
No full textStatistical external validation and consensus modeling: A QSPR case study for Koc prediction
No full textThe soil sorption partition coefficient (log Koc) of a heterogeneous set of 643 organic non-ionic compounds, with a range of more than 6 log units, is predicted by a statistically validated QSAR modeling approach. The applied multiple linear regression (ordinary least squares, OLS) is based on a variety of theoretical molecular descriptors selected by the genetic algorithms-variable subset selection (GA-VSS) procedure. The models were validated for predictivity by different internal and external validation approaches. For external validation we applied self organizing maps (SOM) to split the original data set: the best four-dimensional model, developed on a reduced training set of 93 chemicals, has a predictivity of 78% when applied on 550 validation chemicals (prediction set). The selected molecular descriptors, which could be interpreted through their mechanistic meaning, were compared with the more common physico-chemical descriptors log Kow and log Sw. The chemical applicability domain of each model was verified by the leverage approach in order to propose only reliable data. The best predicted data were obtained by consensus modeling from 10 different models in the genetic algorithm model population
The optimal type of boluses following a pizza meal in children and adolescents with type 1 diabetes
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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
Development and statistical validation of QSAR models for regulatory acceptance in managing the chemical risk: BCF and Koc.
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