1,721,406 research outputs found
LGBTQI+ icons between resistance and normalization: looking for mediatization of emotions in hashtags
No full textThe mediatization of emotions emerges as an affordance of social media, the study of which involves paying attention to digital practices and to the construction and expression of public affection. This happens both for the great events and for the daily demonstrations of support or its denial. In this article we work on the phenomenon of the mediatization of emotions linked to two LGBTQI+ icons and expressed in hashtags on Twitter. Placing it in a specific context – the one of well-known television characters who have declared their homosexual orientation or transgender identity. The objective is to understand if the cloud of feelings they have created on Twitter is to be attributed to a true globally mediatized emotional exchange, or just an expression of emotions on the social media, and discover which emotional dynamics, linked to the LGBTQI+ world, they express
Icone gay: tra processi di normalizzazione e di resistenza. Ricostruire la semantica degli hashtag
No full textThe mediatization of emotions emerges as an affordance of social media, the
study of which involves paying attention to digital practices and the
formation of the sense of public affection, of connected audiences expressing
their participation through expressions of sentiment. This happens both for
the great events and for the daily demonstrations of support or of its
negation. Here we choose to analyze the tweets in which the fans express
their opinions on the participation in the reality shows of their “icons”:
Vladimir Luxuria and Cristiano Malgioglio. To reconstruct the hashtag
semantics we use: the NodeXL software for network analysis and Iramuteq
for the extraction of lexical worlds
Roles of the Core Components of the Mammalian miRISC in Chromatin Biology
Full text linkThe Argonaute (AGO) and the Trinucleotide Repeat Containing 6 (TNRC6) family proteins are the core components of the mammalian microRNA-induced silencing complex (miRISC), the machinery that mediates microRNA function in the cytoplasm. The cytoplasmic miRISC-mediated post-transcriptional gene repression has been established as the canonical mechanism through which AGO and TNRC6 proteins operate. However, growing evidence points towards an additional mechanism through which AGO and TNRC6 regulate gene expression in the nucleus. While several mechanisms through which miRISC components function in the nucleus have been described, in this review we aim to summarize the major findings that have shed light on the role of AGO and TNRC6 in mammalian chromatin biology and on the implications these novel mechanisms may have in our understanding of regulating gene expression
Dynamic Preisach hystersis model for magnetostrictive materials for energy application
Full text linkRecently Magnetostrictive materials have been proposed as active materials to be used in several energy harvesting technology [1]. In this kind of application, the working condition of the material is highly dynamic and non linear.
As a result static models of magnetostrictive materials are usually not very accurate and can be not reliable to develop a sufficiently accurate designof the energy harvesting devices. The presence of hysteresis requires accurate
mathematical modeling in order to correctly foresee the behavior of real materials (ferromagnetic or magnetostrictive) used in control systems or in
electrical machines and thus simplifying the design of such controllers or predicting with acceptable accuracy electromagnetic fields in such
devices[2]. In order to overcome this problem, this paper addresses the development of Dynamic Preisach hysteresis model (DPM) for magnetostrictive materials for energy application operating in hysteretic and time varying nonlinear
regimes. DPM is a development of classical Preisach Model which is able to include dynamical features in the mathematical model of hysteresis.
In this paper the magnetostrictive material considered is Terfenol-D. Its hysteresis is modeled by applying the DPM whose identification procedure is performed by using a neural network procedure previously publised [3]. The
neural network used is a multiplayer perceptron trained with the Levenberg-Marquadt training algorithm. This allows to obtain both Everett integrals and the Preisach distribution function, without any special conditioning of the measured data, owing to the filtering capabilities of the neural network interpolators.
The model is able to reconstruct both the magnetization relation and the Field-strain relation. The model is validated through comparison and prediction of data collected from a typical Terfenol-D transducer
Methods of qualitative analysis and virtual communication places. Study on the evolution of telework in Italy along with a dedicated mailing list
No full textIn attesa di informazioni sulla eventuale pubblicazione
Development of a hibrid material for aerospace application, made of C/E sandwich panels with Glare protection; an experimental evaluation of a impact behaviour
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