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Deep Learning for RNA–RNA Interaction Prediction
No full textRNA–RNA interactions (RRIs) play a central role in post-transcriptional gene regulation, influencing processes such as translation, splicing, RNA stability, and ribonucleoprotein complex assembly. While accurate computational prediction of RRIs could pave the way for RNA-targeted therapies, it remains a major challenge due to the intricate and dynamic behavior of long RNA molecules in vivo. To address these challenges, we introduce RIME, a deep learning framework that predicts
RRIs using only sequence information. RIME leverages embeddings from the Nucleotide Transformer language model, which capture complex biological patterns beyond conventional thermodynamics-based features. Across multiple datasets, RIME consistently outperforms existing tools and successfully highlights key sequence determinants of RNA interactions, such as low-complexity repeats, as
confirmed by enrichment analyses. Notably, the model excels in predicting high-confidence and functionally validated interactions, demonstrating its ability to extract meaningful signals from the complex sequence landscape of long RNAs.
The code implementing RIME is freely available at: https://github.com/giorgiobini/
RIME. A web server is also accessible at: https://tools.tartaglialab.com/rna_rna
Effects of PEG surface modification of magnetic nanoparticles on sonocatalysis and photocatalysis in PVDF composites
No full textThis study reveals an innovative combination of polyvinylidene fluoride (PVDF) polymer membrane with nanostructured Zn0.3Co0.7Fe2O4 magnetic fillers that enables photo- and sonocatalytic degradation of organic dyes. Our findings demonstrate that additional coating of Zn0.3Co0.7Fe2O4 nanoparticles functionalized with polyethylene glycol (PEG) increases the crystallinity of the PVDF matrix and reduces phase separation, thereby enhancing sonocatalytic degradation of methylene blue (50.4% degradation compared to 25.8% for composite with bare nanoparticles). However, the insulating nature of PEG limits photocatalytic activity. These findings highlight the complex interplay between microstructure and catalytic performance, emphasizing the importance of comprehensive material characterization for composite performance tuning
The Importance of Predictive Models in Forest Fire Risk Management: the example of Liguria Region
No full textThis PhD thesis is the result of the four-year work and research in the theme of wildfire modeling and its operational use. As described in the Introduction, all the researches were strongly conditioned by the hiring in the Corpo Nazionale dei Vigili del Fuoco (the National Fire Brigade) during the second year of the PhD. Starting from the experience in the wildfire management that has been developed during the entry course to the National Fire Brigade and, in particular, during real events, the wildfire risk management in the Liguria Region is described in this thesis, as the common thread of the implementations ad analysis performed during the PhD research.
In Liguria region the operational preparedness to the wildfire risk is based on the SPIRL model, which forecasts the wildfire danger at municipal level. Basing on the outputs of the model, tactical and operative actions are performed, as the improvement of the ready-to-go firefighting units, and monitoring actions on the field. The real case of the Albenga wildfire, occurred in 2022, gives the chance to analyze the real benefits derived from
the application of this type of preparedness, comparing the improvement of the units of National Fire Brigade, the forecasted wildfire danger and the number of wildfires occurred.
In the operative management of a wildfire event, decision-makers in Liguria region have the possibility to simulate the possible wildfire spread by the use of the PROPAGATOR model, an empirical stochastic model developed by CIMA Foundation.
The model has been implemented during the PhD research, introducing new firefighting activities that can be simulated, and evaluating and producing the maps of the Rate of Spread and the Fireline Intensity.
The spatial resolution of the model can now vary, enlarging the possible applications of the model in the simulation of large wildfires, which last for entire days or weeks, or very detailed wildfires of small dimension (as the prescribed fires)
A CFD Model for the Direct Coupling of the Combustion Process and Glass Melting Flow Simulation in Glass Furnaces
No full textThe objectives of reducing and increasing pollutant emissions during the glass production process also apply to the glass industry, meaning that the accurate modeling of a glass furnace is of critical strategic value. In the available literature, several CFD studies have proposed various models with different levels of complexity. Two basic aspects are shared by the existing models, limiting their accuracy and their impact on furnace design: the combustion space is usually solved with reliance on simplified models (e.g., Flamelet and global kinetic mechanisms); and the glass tank is solved separately, using an iterative approach to couple two (or more) simulated domains. This work presents the development of an innovative CFD model to overcome these limitations and to perform accurate simulations of industrial glass furnaces. The reactive flow is solved using a reduced chemical kinetic mechanism and the EDC (eddy dissipation concept) turbulence–chemistry interaction model to properly reproduce the complex combustion development. The glass bath is solved as a laminar flow with the appropriate temperature-dependent glass properties. The two domains are simulated simultaneously and thermally coupled through an interface. This procedure allows for the more accurate calculation of the heat flow and the temperature distributions on the glass bath, accounting for their subsequent influence on the glass convective motions. The simulation of an existing glass furnace, along with selected comparisons with experimental data, are presented to demonstrate the validity of the proposed model. The developed model provides a contribution that allows us to advance the wider understanding of glass furnace dynamics
I frati del popolo. I cappuccini alle elezioni del 18 aprile 1948
No full textPoveri e umili, i cappuccini sono ritenuti i frati del popolo. Un prestigio, quello diffuso tra le classi subalterne, che agli albori della Guerra fredda può diventare un’efficace arma di contenimento dell’avanzata comunista. Attraverso il ritrovamento e lo studio di una corposa documentazione inedita, il volume intende ricostruire il ruolo dell’Ordine nelle elezioni del 18 aprile 1948. Dai campi alle fabbriche, dalle città alle più piccole frazioni, i frati cercano un contatto con le masse popolari diseredate per arginarne la scristianizzazione. Durante l’azione di apostolato sociale si scontrano con poteri locali, agguerrite cellule socialcomuniste, preti diffidenti, massoni e mafiosi. Con il loro racconto in presa diretta descrivono una vivida geografia della miseria, restituendoci una fotografia nitida e intensa degli italiani sopravvissuti al regime e al conflitto mondiale. Un viaggio dell’Italia profonda dell’immediato dopoguerra alle prese con fame, ostilità verso il clero e miraggio rivoluzionario. Uno sguardo inedito sulle elezioni che hanno segnato le sorti del Paese
Optimized Washwater Treatment for Sulphur-Oxides Emission Control: A Data-Driven Case Study on Cruise Ship Scrubber Technology
No full textThe maritime sector faces increasing regulatory pressure to mitigate sulphur oxides (SOx) emissions, necessitating innovative solutions to minimize environmental impacts. Over recent years, exhaust gas cleaning system (EGCS or “scrubber”) technologies have been extensively studied to mitigate SOx emission, however, yet gaps remain in optimizing scrubber washwater treatment processes to minimize marine pollution.
This study examines advanced scrubber washwater treatment technologies deployed on a cruise ship, emphasizing their role in aligning with international standards while preserving marine ecosystems. Using operational and laboratory data, the research evaluates key parameters, including pH, heavy metals, and hydrocarbons, under varying voyage scenarios. Results highlight the efficacy of multi-stage filtration systems, achieving significant pollution reduction and compliance with the MARPOL Convention guidelines. The findings provide actionable insights for sustainable maritime practices and policy formulation
