2,567 research outputs found
Ulrich Beck: modernità e cosmopolitismo fra Occidente e non-Occidente
No full textQuesto contributo offre alcune considerazioni su due dei temi centrali della riflessione di Ulrich Beck: la (ri)formulazione dell'idea di modernità nei termini di "seconda modernità"; e la conseguente esigenza di formulazione di un adeguato corredo metodologico e concettuale di impronta cosmopolita per l'analisi di questa nuova condizione della storia dell'umanità.
L'idea di una "seconda modernità", proiettata al di là dei caratteri industriali e delle categorie interpretative della modernità classica, nell'offrire un'alternativa alla tesi dell'avvento di una condizione postmoderna, ne coopta e neutralizza la critica, facendo uso dell'incertezza epistemologica prodotta dalla crisi dei fondamenti scientifici moderni per sancire teoricamente e legittimare un'incertezza sociale a sua volta deterministicamente ricondotta all'avvento di una società – anche globale – del rischio.
La proposta di un cosmopolitismo metodologico come necessario per l'analisi della seconda modernità elude la questione relativa all'inadeguatezza di categorie analitiche metodologicamente nazionaliste per lo studio della prima modernità; e, al tempo stesso, marginalizza o silenzia, eurocentricamente, tanto il ruolo costitutivo del mondo non occidentale nella genealogia intellettuale e istituzionale della modernità, quanto il "lato oscuro" di quest'ultima così come definita dall'Occidente
Recensione al libro Le invasioni barbariche nel meridione dell’Impero: Visigoti, Vandali, Ostrogoti. Atti del Convegno (Cosenza, 24-26 luglio 1998), a cura di P. Delogu, Soveria Mannelli 2001
No full text
Amelioration of acute inflammation by systemic administration of a cell-permeable peptide inhibitor of NF-κB activation.
No full textAbstract
OBJECTIVE:
We used an experimental model of inflammation in mice, carrageenan-induced paw edema, to study the antiinflammatory effects of the NEMO-binding domain (NBD) peptide, which blocks activation of the inducible transcription factor NF-kappaB.
METHODS:
Paw edema was induced by subplantar injection of 1% lambda-carrageenan into the mouse left hind paw. Test agents were given intraperitoneally immediately after carrageenan injection. The increase in footpad thickness was considered to be edema. In some experiments, the mice were killed and the paws were removed for histologic and molecular biology analysis. NF-kappaB DNA binding activity was evaluated in nuclear extracts by electrophoretic mobility shift assays. The expression levels of NF-kappaB-regulated cyclooxygenase 2 (COX-2) protein and tumor necrosis factor alpha (TNFalpha) messenger RNA (mRNA) were evaluated by immunoblot analysis and polymerase chain reaction amplification of reverse-transcribed mRNA, respectively.
RESULTS:
We found that systemically administered NBD peptide significantly inhibited edema formation and cellular infiltration in inflamed mouse paws. This antiinflammatory activity was most likely due to inhibition of expression of proinflammatory mediators, such as TNFalpha and COX-2, in inflamed tissues.
CONCLUSION:
These studies further establish NF-kappaB as a target for antiinflammatory therapy and provide support for the use of the NBD peptide as a possible therapeutic agent for inflammatory diseases
A physics-driven and machine learning-based digital twinning approach to transient thermal systems
No full textPurpose – In this study, the authors propose a novel digital twinning approach specifically designed
for controlling transient thermal systems. The purpose of this study is to harness the combined power of
deep learning (DL) and physics-based methods (PBM) to create an active virtual replica of the physical
system.
Design/methodology/approach – To achieve this goal, we introduce a deep neural network (DNN)
as the digital twin and a Finite Element (FE) model as the physical system. This integrated approach is
used to address the challenges of controlling an unsteady heat transfer problem with an integrated
feedback loop.
Findings – The results of our study demonstrate the effectiveness of the proposed digital twinning
approach in regulating the maximum temperature within the system under varying and unsteady heat flux
conditions. The DNN, trained on stationary data, plays a crucial role in determining the heat transfer
coefficients necessary to maintain temperatures below a defined threshold value, such as the material’s
melting point. The system is successfully controlled in 1D, 2D and 3D case studies. However, careful
evaluations should be conducted if such a training approach, based on steady-state data, is applied to
completely different transient heat transfer problems.
Originality/value – The present work represents one of the first examples of a comprehensive digital
twinning approach to transient thermal systems, driven by data. One of the noteworthy features of this
approach is its robustness. Adopting a training based on dimensionless data, the approach can
seamlessly accommodate changes in thermal capacity and thermal conductivity without the need for
retraining
Anti-inflammatory activity of 15-deoxy-delta12,14-PGJ2 and 2-cyclopenten-1-one: role of the heat shock response.
No full textIl cavallino della Giara: variazioni dell'attività tiroidea e di alcune costanti ematiche tra l'inverno e l'estate
No full textDecentralized gain adaptation for optimal pinning controllability of complex networks
No full textCoordinating ensembles of dynamical systems in a decentralized manner is of central importance when controlling complex networks. Pinning control is a much used technique where only a small fraction of the network nodes is directly controlled, with control gains being typically selected uniformly across the control layer. In this letter, we tackle the problem of optimally selecting the control gains of a pinning control strategy. Indeed, in networks of nonlinear dynamical systems fulfilling the socalled QUAD assumption, pinning controllability improves as the smallest eigenvalue λ_1 of an extended Laplacian matrix increases. Based on this observation, we pose a constrained optimization problem on the network. Rather than solving it in a centralized fashion, we propose a fully decentralized multilayer approach. Specifically, one layer is used to evaluate the sensitivity of λ_1 to the variation of the gains, while the second layer uses such an estimate to dynamically tune the control gains. The effectiveness of the approach is demonstrated via a representative example
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