134,248 research outputs found
Eugenio Montale (1994-1998). Repertorio bibliografico ragionato
No full textRepertorio bibliografico su Montale (1994-1998). Sono di R. Castellana le seguenti parti:
C. Montale critico e saggista
D. Traduzioni
E. Carteggi
F. Testimonianze, biografie, interviste, catalogh
Fiction e non fiction: storia, teorie e forme
No full textChe cos’è la finzione narrativa e che cosa la distingue da altri tipi di discorso? Ma soprattutto: in quali modi può convivere con le istanze di verità e di referenzialità presenti in un testo letterario? Il libro, rivolto in primo luogo agli studenti dei corsi di laurea in Lettere moderne e in Lingue e letterature straniere, fornisce alcune risposte a queste e altre domande, affrontandole da una prospettiva teorica oltre che storica. A un primo capitolo sullo statuto della fiction, dove sono prese in esame e discusse soprattutto le proposte della narratologia, ne seguono altri tre dedicati ai generi della modernità nei quali, storicamente, il problema della compresenza di fiction e non fiction si è posto con maggior forza: le factual fictions inglesi del Sei e del Settecento (e dunque le origini stesse del novel), il romanzo storico dell’Ottocento e il romanzo saggio. I quattro capitoli successivi si concentrano invece sulla commistione tra finzionalità e fattualità nei generi ibridi del secondo Novecento e degli anni Duemila: il nonfiction novel, la non fiction, la biofiction e infine l’autofiction, forse il genere più emblematico delle ambiguità e dei paradossi dell’estremo contemporaneo. Chiude il volume una riflessione interdisciplinare su analogie e differenze tra la finzione giuridica e la finzione letteraria.
Indice
Introduzione di Riccardo Castellana
1. Che cos’è la fiction? di Riccardo Castellana
La fiction e il gioco/Che cos’è la fiction? Una risposta facile/Menti trasparenti/La fiction in terza persona/La fiction in prima persona/Segnali contraddittori e casi limite/Finto, finzionale, fittizio, finzionalizzato/Politiche della fiction
2. Le narrazioni pseudofattuali e le origini del novel di Riccardo Capoferro
Introduzione/Retoriche empiriche/Narrazioni empiriche/Realtà, finzione e realismo
3. L’ora della verità. Storia e romanzo nell’Ottocento di Francesco de Cristofaro e Marco Viscardi
Il brevetto di Walter Scott/Il passato come presente/La Storia finta/Il passato come presente/Rappresentare l’evento/Personaggi reali e personaggi d’invenzione/L’individuo e il mondo
4. Fiction e non fiction nel romanzo-saggio di Valeria Cavalloro
Fermarsi a pensare/Una forma di medio periodo/Il soggetto pensante: tre forme di “presenza”/Universale e particolare
5. Nonfiction novel e New journalism di Marco Mongelli
Nonfiction novel e New journalism/Alle origini della non fiction: due paradigmi/Il nonfiction novel oggi: ripresa e innovazione dei modelli/Conclusioni
6. La non fiction di Raffaello Palumbo Mosca
Di che cosa parliamo quando parliamo di non fiction/Questioni di etica: nonfiction novel e non fiction contemporanea/Sciascia (e Manzoni): un modello ancora attivo?/«Era vuota la casella della realtà raccontata dagli scrittori»: Sandro Veronesi e la letteratura di cose viste/Etica e saggismo: Campo del sangue di Eraldo Affinati/Fait divers, cronaca: L’abusivo di Antonio Franchini e Gomorra di Roberto Saviano/ Brevi conclusioni
7. La biofiction di Riccardo Castellana
Questioni terminologiche/Una definizione/Finzioni eterodiegetiche/Finzioni omodiegetiche/L’autobiofiction/Dal romanzo storico alla biofiction/La New biography e il modernismo/Il postmoderno e dopo/Biofiction italiane/Conclusioni
8. L’autofiction di Lorenzo Marchese
Nascita dell’autofiction/Generi e stili: alcuni esempi/Autenticità e immagine pubblic/L’arte di fingers/Oltre l’io possibile
9. La finzione giuridica e la finzione letteraria di Angela Condello e Tiziano Toracca
Premessa/Finzioni che non mentono/Finzioni diverse/Tra diritto e letteratura: un’omologia feconda Bibliografia
RECENSIONI: L. Mirone, Laletteraturaenoi, 31 marzo 2021 (https://laletteraturaenoi.it/2021/03/31/fiction-e-non-fiction/); M. Martinengo, Italianistica, LI, 1:(2022), pp. 220-222; D. Matteini, Rivista di letterature moderne e comparate, 76,2 2023, pp. 217-221
Bayesian Tensor Factorisation for Bottom-up Hidden Tree Markov Models
No full textBottom-Up Hidden Tree Markov Model is a highly expressive model for tree-structured data. Unfortunately, it cannot be used in practice due to the intractable size of its state-transition matrix. We propose a new approximation which lies on the Tucker factorisation of tensors. The probabilistic interpretation of such approximation allows us to define a new probabilistic model for tree-structured data. Hence, we define the new approximated model and we derive its learning algorithm. Then, we empirically assess the effective power of the new model evaluating it on two different tasks. In both cases, our model outperforms the other approximated model known in the literature
A tensor framework for learning in structured domains
No full textLearning machines for structured data (e.g., trees) are intrinsically based on their capacity to learn representations by aggregating information from the multi-way relationships emerging from the structure topology. While complex aggregation functions are desirable in this context to increase the expressiveness of the learned representations, the modelling of higher-order interactions among structure constituents is unfeasible, in practice, due to the exponential number of parameters required. Therefore, the common approach is to define models which rely only on first-order interactions among structure constituents. In this work, we leverage tensors theory to define a framework for learning in structured domains. Such a framework is built on the observation that more expressive models require a tensor parameterisation. This observation is the stepping stone for the application of tensor decompositions in the context of recursive models. From this point of view, the advantage of using tensor decompositions is twofold since it allows limiting the number of model parameters while injecting inductive biases that do not ignore higher-order interactions. We apply the proposed framework on probabilistic and neural models for structured data, defining different models which leverage tensor decompositions. The experimental validation clearly shows the advantage of these models compared to first-order and full-tensorial models
Tensor decompositions in recursive neural networks for tree-structured data
No full textThe paper introduces two new aggregation functions to encode structural knowledge from tree-structured data. They leverage the Canonical and Tensor-Train decompositions to yield expressive context aggregation while limiting the number of model parameters. Finally, we define two novel neural recursive models for trees leveraging such aggregation functions, and we test them on two tree classification tasks, showing the advantage of proposed models when tree outdegree increases
Generalising Recursive Neural Models by Tensor Decomposition
No full textMost machine learning models for structured data encode the structural knowledge of a node by leveraging simple aggregation functions (in neural models, typically a weighted sum) of the information in the node's neighbourhood. Nevertheless, the choice of simple context aggregation functions, such as the sum, can be widely sub-optimal. In this work we introduce a general approach to model aggregation of structural context leveraging a tensor-based formulation. We show how the exponential growth in the size of the parameter space can be controlled through an approximation based on the Tucker tensor decomposition. This approximation allows limiting the parameters space size, decoupling it from its strict relation with the size of the hidden encoding space. By this means, we can effectively regulate the trade-off between expressivity of the encoding, controlled by the hidden size, computational complexity and model generalisation, influenced by parameterisation. Finally, we introduce a new Tensorial Tree-LSTM derived as an instance of our framework and we use it to experimentally assess our working hypotheses on tree classification scenarios
Latent tuberculosis infection in healthcare workers. Strategies and proposal of specific algorithms
No full textThe diagnosis and treatment of Latent Tuberculosis Infection (LTBI) are priority elements of control programs of Tuberculosis (TB). It is believed that it will not be possible to eradicate TB within 2050 unless the overall population with LTBI is found. Healthcare Workers (HCWs) are an important group of people which has a high risk of becoming infected by LTBI or that is already infected. Despite that, the health surveillance for this issue is not homogeneously articulated on national territory within the three steps of (i) preventive screening, (ii) periodical screening and (iii) investigation of cases of unprotected exposures. The diagnosis of LTBI is made possible by two immunologic tests, a cutaneous test (Tuberculin Skin Test by Mantoux, TST) and a hematic test (Interferon Gamma Release Assay, IGRA), while at the same time excluding the active TB by means of a chest radiography. While TST has been successfully used since one century, the current increasing usage of IGRAs raises the issue of its proper indication as an integrative, alternative or substitutional exam compared to TST. The aim of this work is to design easily accessible specific algorithms which are not included within up to date scientific literature and which could facilitate Italian doctors in handling TB cases in their clinical practice, without substituting available official guidelines. With that aim we have made an analysis of the advantages and limits of TST and IGRAs (with a special focus on issues related to the usage of IGRAs among HCWs) and of the two main diagnostic procedures recommended within the different national and international guidelines. Algorithms have been structured according to a sequential strategy in order to take advantage of the most favourable cost-benefit ratio and to avoid diagnostic and therapeutic errors, thus compensating better than the other strategies to the lack of a gold standard diagnostic test for LTBI. The proposed algorithms could be used within the health surveillance of HCWs. A structured, synergic and timely action among the healthcare manager, the occupational physician and the pulmonologist could lead to a more effective Health Surveillance and to a more accurate diagnosis of LTBI in HCWs, that ultimately would help in the prevention of active TB, thus making more doctors aware of an issue which would otherwise keep being latent... just as the infection!
Che cos’è la paraletteratura?
No full textRecensione a D. Couégnas, Paraletteratura, La Nuova Italia, Firenze, 1997
Matematiche ed ermeneutica: alcuni recenti contributi dell'epistemologia francese.
No full textA cura di F. Minazzi e D. Ri
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