Attenzione e disinteresse nell'esperienza estetica e artistica

La tesi intende indagare l’attenzione come nozione strutturale dell’esperienza estetica, come costellazione di pratiche molto più ampia della semplice direzione, focalizzazione, distribuzione dello sguardo del singolo soggetto - spettatore. Obiettivo della ricerca è analizzare l’attenzione nei suoi legami con i concetti di contemplazione e azione, distanza e partecipazione, in vista di una teorizzazione articolata in riferimento all’esperienza artistica contemporanea, nei suoi richiami ad un’arte sempre più interattiva e comunitaria. La formulazione di una nozione di attenzione legata all’esperienza estetica è rilevante in particolare nella sua connessione con il disinteresse: è necessario evidenziare come le pratiche attenzionali siano un insieme assolutamente eterogeneo e non classificabile come semplicemente corrispondente alle nozioni di controllo, azione/reazione e selezione, ma anzi possano essere ricomprese all’interno della non-strumentalità, della non-produttività, della contemplazione intesa come una sorta di inattività performativa

Activation of Stress Kinases in the Brain of Mucopolysaccharidosis IIIB mice

The accumulation of heparan sulfate (HS) in lysosomes is the primary consequence of the enzyme defect (α-N-acetylglucosaminidase) in mucopolysaccharidosis type IIIB. This accumulation triggers a cascade of pathological events that progressively leads to CNS pathology. Here we examined the activation of the three major stress kinases in the neuronal tissue of a murine model of the disease. ERK1/2 was significantly higher in the cortex of 1–2-month-old affected animals compared with wild-type (Wt) littermates. Similarly, ERK1/2 was stimulated in neurons cultured from MPS IIIB mice. SAPK/JNK was also found to be activated in the cortex of 1–2-month-old affected animals compared with Wt subjects, and the same was found for cultured neurons. In contrast, the active form of p38MAPK was lower in the cortex of 1-month-old MPS IIIB mice compared with Wt animals, but no significant difference was found between the two p38MAPK analyzed in normal and affected neurons cultured in vitro. These data indicate the possible involvement of MAPK dysregulation in the early stage of MPS IIIB brain disease. © 2011 Wiley-Liss, Inc

Predicting social media addiction fromInstagram profiles: A data mining approach

In this short paper, we describe an application of data mining techniques to predict Instagram users’ addiction from a set of features related to (i) Instagram captions extracted from photos, videos, comments, and stories, and Instagram indicators such as number of followers and following, blocked and closed friends, and frequency of use. We first applied text mining to explore and describe the main contents of Instagram captions. Next, we used a set of non parametric models and ensemble methods to predict Instagram addiction as measured by the Instagram addiction scale [1]. Models were compared via cross-validation using test and training (random) sets from the original dataset. Results showed that Instagram addiction is mainly predicted by the overall time spent on Instagram, writing stories and comments, and number of followers. Moreover, the results suggest that Instagram users made use of photos/videos and stories/comments differently, with the latter being mostly related to emoticons, experiences, and relationships with other users

Teaching iCub to recognize objects using deep convolutional neural networks

Providing robots with accurate and robust visual recognition capabilities in the real-world today is a challenge which prevents the use of autonomous agents for concrete applications. Indeed, the majority of tasks, as manipulation and interaction with other agents, critically depends on the ability to visually recognize the entities involved in a scene. At the same time, computer vision systems based on deep Convolutional Neural Networks (CNNs) are marking a breakthrough in fields as largescale image classification and retrieval. In this work we investigate how latest results on deep learning can advance the visual recognition capabilities of a robotic platform (the iCub humanoid robot) in a real-world scenario. We benchmark the performance of the resulting system on a new dataset of images depicting 28 objects, named iCubWorld28, that we plan on releasing. As in the spirit of the iCubWorld dataset series, this has been collected in a framework reflecting the typical iCub\u2019s daily visual experience. Moreover, in this release we provide four different acquisition sessions, to test incremental learning capabilities over multiple days. Our study addresses the question: how many objects can the iCub recognize today

Detection of Soluble Organic and Inorganic Compounds with an Array of Pure and Blended Optical Reporters

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An Investigation on the Role of Spike Latency in an Artificial Olfactory System

Experimental studies have shown that the reactions to external stimuli may appear only few hundreds of milliseconds after the physical interaction of the stimulus with the proper receptor. This behavior suggests that neurons transmit the largest meaningful part of their signal in the first spikes, and than that the spike latency is a good descriptor of the information content in biological neural networks. In this paper this property has been investigated in an artificial sensorial system where a single layer of spiking neurons is trained with the data generated by an artificial olfactory platform based on a large array of chemical sensors. The capability to discriminate between distinct chemicals and mixtures of them was studied with spiking neural networks endowed with and without lateral inhibitions and considering as output feature of the network both the spikes latency and the average firing rate. Results show that the average firing rate of the output spikes sequences shows the best separation among the experienced vapors, however the latency code is able in a shorter time to correctly discriminate all the tested volatile compounds. This behavior is qualitatively similar to those recently found in natural olfaction, and noteworthy it provides practical suggestions to tail the measurement conditions of artificial olfactory systems defining for each specific case a proper measurement time

Cytotoxic Activity of Origanum Vulgare L. on Hepatocellular Carcinoma cell Line HepG2 and Evaluation of its Biological Activity

The potential of plant essential oils (EOs) in anticancer treatment has recently received many research efforts to overcome the development of multidrug resistance and their negative side effects. The aims of the current research are to study (i) the cytotoxic effect of the crude EO extracted from Origanum vulgare subsp hirtum and its main constituents (carvacrol, thymol, citral and limonene) on hepatocarcinoma HepG2 and healthy human renal cells HEK293; (ii) the antibacterial and phytotoxic activities of the above EO and its main constituents. Results showed that cell viability percentage of treated HepG2 by EO and its main constituents was significantly decreased when compared to untreated cells. The calculated inhibition concentration (IC50) values for HepG2 were lower than healthy renal cells, indicating the sort of selectivity of the studied substances. Citral is not potentially recommended as an anticancer therapeutic agent, since there are no significant differences between IC50 values against both tested cell lines. Results showed also that oregano EO and its main constituents have a significant antibacterial activity and a moderate phytotoxic effect. The current research verified that oregano EO and its main constituents could be potentially utilized as anticancer therapeutic agents