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Complement modulates glutamate release and synaptic function in an EAE mouse model of multiple sclerosis: a neuroimmunological study
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CRISI E RINASCITA: UN DUALISMO INGANNEVOLE. RESPONSABILITÀ E RIFORME IN TEMPO DI CRISI TOTALE: IL CASO DEL NEW DEAL E DELL’EUROPA DEI DIRITTI
No full textPremessa una breve riflessione circa l’influenza esercitata dal binomio crisi/rinascita sull’immaginario collettivo occidentale, il contributo si concentrerà su alcune vicende tratte dalla storia giuridica del recente passato, al fine di evidenziare le azioni di riforma che hanno permesso di superare situazioni di profonda depressione economica e sociale. Ci si soffermerà in particolare sull’epopea giuridica del New Deal, che consentì alla presidenza Roosevelt di condurre gli Stati Uniti d’America oltre la Grande Depressione, e sulla ricostruzione dell’Europa seguita al secondo conflitto mondiale.After a brief reflection on the influence exerted by the crisis/rebirth binomial on the Western Western collective imaginary, the contribution will focus on some events from the legal history of the recent past, to highlight the reform actions that have made it possible to overcome situations of deep economic and social depression. It will focus in particular on the legal epic of the legal epic of the New Deal, which enabled the Roosevelt presidency to lead the United States of America beyond the Great Depression, and on the reconstruction of Europe following the Second World War
Preliminary Validation of a COLREGs-Compliant Navigation Framework Using LiDAR and RGB Data Fusion
No full textThis paper presents a preliminary validation of a novel navigation framework for Autonomous Surface Vehicles that integrates obstacle detection and path planning while complying with the International Regulations for Preventing Collisions at Sea. While this planning framework was previously tested for rules compliance using assumed obstacle data, this work focuses on testing it with real detection-derived inputs. Obstacle detection combines 3D LiDAR point clouds with YOLOv8-based image interpretation, with an Adaptive Kalman Filter tracking and localizing detected objects for path planning. The planner employs a COLREGs-aware A∗ algorithm, using obstacle positions, velocities, and classes to compute collision-free paths. Validation was conducted in the Stonefish simulator, enabling software-in-the-loop testing with the vehicle's dynamic model
Fault Classification in Distribution Networks Using Graph Neural Networks and Discrete Stockwell Transform
No full textDeep learning models have shown great potential for fault location and classification tasks in distribution systems. Emerging multi-scale data sources such as waveform measurement units, synchro-phasors, smart meters, weather data, and other information from electricity markets provide a rich source of information that can be leveraged for various applications in power system operations. However, the lack of sufficient training datasets poses a significant challenge in effectively training these models to achieve high accuracy and generalization. This paper proposes a novel architecture for the generation of fault datasets from the distribution system and the fault location tasks. It then develops a fault classification solution using graph convolutional neural network that can capture topology information, combined with discrete orthogonal Stockwell's transform for extracting frequency-domain features from time-series data. Pre-processing of the bus voltage angle and magnitude from strategic locations was used. The method was tested to predict faulted buses in the Cigre distribution test system. Comparisons were made with various standard classifiers. The results show the usefulness of the data generation solution for developing fault location models and the benefit of integrating topology data into the classifier with a graph convolutional neural network technique, as it outperforms other techniques in most scenarios
Fenton-like disinfection properties of polyethyleneimine/polyaniline-modified SiO2-loaded copper composites and exploration of lab-scale continuous-flow reactor applications
No full textBacterial contamination in aquatic environments remains a persistent threat to public health. In this study, we synthesized copper nanoparticle-loaded polyethyleneimine/polyaniline-functionalized SiO2 composites (Cu/PEI/SiO2 and Cu/PANI/SiO2) as novel Fenton-like catalysts for water disinfection. The composites were systematically characterized by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and transmission electron microscopy (TEM), confirming the successful integration of copper nanoparticles into the matrix. Fenton-like disinfection experiments demonstrated that both composites achieved complete inactivation (7-log reduction) of Escherichia coli (E. coli), Ralstonia solanacearum (R. solanacearum), and Staphylococcus aureus (S. aureus) within 15, 20, and 25 min, respectively. Electron paramagnetic resonance (EPR) spectroscopy confirmed the presence of hydroxyl radicals (•OH) and superoxide radicals (•O2−) in both composites, verifying a radical-mediated disinfection mechanism. To assess practical applicability, we constructed a lab-scale continuous-flow reactor. Long-term tests revealed that both composites maintained consistent and effective bactericidal performance over a 4-hour continuous operation, exhibiting excellent stability and durability. These findings highlight the potential of Cu/PEI/SiO2 and Cu/PANI/SiO2 as efficient, sustainable materials for advanced water disinfection technologies
Stereoselective Polycondensation of Levoglucosenone linked with 1,3-benzenedithiol and their properties
No full textEsc peptides and derivatives potentiate the activity of CFTR with gating defects and display antipseudomonal activity in cystic fibrosis-like lung disease
No full textCystic fibrosis (CF) is a rare disease caused by mutations in the gene encoding the CF transmembrane conductance regulator (CFTR), a chloride channel with an important role in the airways. Despite the clinical efficacy of present modulators in restoring the activity of defective CFTR, there are patients who show persistent pulmonary infections, mainly due to Pseudomonas aeruginosa. Recently, we reported an unprecedented property of antimicrobial peptides i.e. Esc peptides, which consists in their ability to act as potentiators of CFTR carrying the most common mutation (the loss of phenylalanine 508) affecting protein folding, trafficking and gating. In this work, by electrophysiology experiments and computational studies, the capability of these peptides and de-novo designed analogs was demonstrated to recover the function of other mutated forms of CFTR which severely affect the channel gating (G551D and G1349D). This is presumably due to direct interaction of the peptides with the nucleotide binding domains (NBDs) of CFTR, followed by a novel local phenomenon consisting in distancing residues located at the cytosolic side of the NBDs interface, thus stabilizing the open conformation of the pore at its cytosolic end. The most promising peptides for the dual antimicrobial and CFTR potentiator activities were also shown to display antipseudomonal activity in conditions mimicking the CF pulmonary ion transport and mucus obstruction, with a higher efficacy than the clinically used colistin. These studies should assist in development of novel drugs for lung pathology in CF, with dual CFTR potentiator and large spectrum antibiotic activities
