Electromagnetic Analysis of Transients in the ITER PF Superconducting Joints

Il progetto ITER (International Thermonuclear Experimental Reactor) prevede lo sviluppo e la realizzazione di un prototipo di reattore a fusione nuceare, con lo scopo di ottenere dati sperimentali sulla fisica del plasma e verificare la stabilità e l’affidabilità di componenti ad alto contenuto tecnologico che operano in condizioni estreme di temperatura, corrente e campo magnetico. La reazione di fusione nucleare avviene in una corrente di plasma confinata in una camera toroidale attraverso il campo magnetico prodotto da bobine superconduttive sottoposte ad alto campo magnetico (fino a 12 T) e alte correnti (fino a 100 kA), mantenute a temperature criogeniche (inferiori a 5 K) tramite una corrente di elio supercritico. I componenti del sistema magnetico di ITER devono essere adeguatamente progettati e testati per verificarne l’affidabilità durante tutta la vita utile della macchina, evitando costose operazioni di riparazione in caso di guasto; dato l’elevato costo di ogni test è necessario sviluppare modelli numerici per simulare il comportamento dei componenti in diverse condizioni operative. In questo lavoro si analizzano, tramite due differenti modelli numerici, la resistenza elettrica in corrente continua (DC Resistance) e le perdite di energia in corrente alternata (AC Losses) del giunto superconduttivo che connette due avvolgimenti (Double Pancakes) della bobina inferiore del sistema magnetico per la generazione del campo poloiodale (Poloidal Field Coil), atto al controllo della posizione verticale della corrente di plasma. La validazione dei codici è basata sull’analisi sperimentale del campione PFJEU1 testato presso la SULTAN facility (Villigen, Switzerland) in Ottobre 2016

DNA topoisomerase I inhibition by camptothecin induces escape of RNA polymerase II from promoter-proximal pause site, antisense transcription and histone acetylation at the human HIF-1α gene locus

Top1 inhibition by camptothecin (CPT) perturbs RNA polymerase II (Pol II) density at promoters and along transcribed genes suggesting an involvement of Top1 in Pol II pausing. Here, we demonstrate that Top1 inhibition favors Pol II escape from a promoter-proximal pausing site of the human HIF-1α gene in living cells. Interestingly, alternative splicing at exon 11 was markedly altered in nascent HIF-1α mRNAs, and chromatin structure was also affected with enhanced histone acetylation and reduced nucleosome density in a manner dependent on cdk activity. Moreover, CPT increases transcription of a novel long RNA (5′aHIF1α), antisense to human HIF-1α mRNA, and a known antisense RNA at the 3′-end of the gene, while decreasing mRNA levels under normoxic and hypoxic conditions. The effects require Top1, but are independent from Top1-induced replicative DNA damage. Chromatin RNA immunoprecipitation results showed that CPT can activate antisense transcription mediated by cyclin-dependent kinase (cdk) activity. Thus, Top1 inhibition can trigger a transcriptional stress, involving antisense transcription and increased chromatin accessibility, which is dependent on cdk activity and deregulated Pol II pausing. A changed balance of antisense transcripts and mRNAs may then lead to altered regulation of HIF-1α activity in human cancer cells

Zinc- and Copper-Loaded Nanosponges from Cellulose Nanofibers Hydrogels: New Heterogeneous Catalysts for the Synthesis of Aromatic Acetals

Herein we report the synthesis of cellulose-based metal-loaded nano-sponges and their application as heterogeneous catalysts in organic synthesis. First, the combination in water solution of TEMPO-oxidized cellulose nanofibers (TOCNF) with branched polyethyleneimine (bPEI) and citric acid (CA), and the thermal treatment of the resulting hydrogel, leads to the synthesis of an eco-safe micro- and nano-porous cellulose nano-sponge (CNS). Subsequently, by exploiting the metal chelation characteristics of CNS, already extensively investigated in the field of environmental decontamination, this material is successfully loaded with Cu (II) or Zn (II) metal ions. Efficiency and homogeneity of metal-loading is confirmed by scanning electron microscopy (SEM) analysis with an energy dispersive X-ray spectroscopy (EDS) detector and by inductively coupled plasma-optical emission spectrometry (ICP-OES) analysis. The resulting materials perform superbly as heterogeneous catalysts for promoting the reaction between aromatic aldehydes and alcohols in the synthesis of aromatic acetals, which play a fundamental role as intermediates in organic synthesis. Optimized conditions allow one to obtain conversions higher than 90% and almost complete selectivity toward acetal products, minimizing, and in some cases eliminating, the formation of carboxylic acid by-products. ICP-OES analysis of the reaction medium allows one to exclude any possible metal-ion release, confirming that catalysis undergoes under heterogeneous conditions. The new metal-loaded CNS can be re-used and recycled five times without losing their catalytic activity

Realistic Aspects of Simulation Models for Fake News Epidemics over Social Networks

The pervasiveness of online social networks has reshaped the way people access information. Online social networks make it common for users to inform themselves online and share news among their peers, but also favor the spreading of both reliable and fake news alike. Because fake news may have a profound impact on the society at large, realistically simulating their spreading process helps evaluate the most effective countermeasures to adopt. It is customary to model the spreading of fake news via the same epidemic models used for common diseases; however, these models often miss concepts and dynamics that are peculiar to fake news spreading. In this paper, we fill this gap by enriching typical epidemic models for fake news spreading with network topologies and dynamics that are typical of realistic social networks. Specifically, we introduce agents with the role of influencers and bots in the model and consider the effects of dynamical network access patterns, time-varying engagement, and different degrees of trust in the sources of circulating information. These factors concur with making the simulations more realistic. Among other results, we show that influencers that share fake news help the spreading process reach nodes that would otherwise remain unaffected. Moreover, we emphasize that bots dramatically speed up the spreading process and that time-varying engagement and network access change the effectiveness of fake news spreading