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“Poetry Makes Claim to a Truth Which Holds Independently of Us”. An Interview with Charles Taylor
No full textThis interview with Charles Taylor revolves around some key theoretical issues that emerge from his latest book. Among the topics discussed are: the existence of a universal “truth” brought to light by Romanticism; the notion of “interspace”; the importance of poetry in modern life experience; reconnecting with nature as a form of empowerment; the contribution of Cosmic Connections to Taylor’s account of the ethical and spiritual sources of modern identity
A Wider Space of Meaning: Poetry As a Resonant Response to Disenchantment
Get PDFThis critical notice discusses Charles Taylor’s last book, Cosmic Connections (2024). The work is first contextualized against Taylor’s intellectual path by asking what philosophical question is answered by the image of poetry as an extra or para-epistemic response to modern disenchantment. The second part of the essay reconstructs Taylor’s argument as follows. After describing how Romanticism revolutionized the way moderns enter a resonant relationship with the cosmos by resorting to the notions of “interspace” and “epistemic retreat”, he outlines the trajectory of this insight within post-Romantic poetry. While Rilke and Hopkins continue the search for a resonant whole with the converging images of “inscape” and “Weltinnenraum”, Baudelaire and Mallarmé take modern disenchantment to its extreme consequences without, however, quenching the evocative power of the lyrical force field. With the “modernist” Eliot and Miłosz, the sense of intellectual powerlessness scales back from the heights reached by the Symbolists, but the search for a believable cosmic order does not go beyond a stubborn faith in the “ethogenic” potentials of human history. Accordingly, Taylor’s book ends with an examination of the prospects for an ethical growth of humanity and its dependency on the spiritual goal of uncovering mimetic, narrative, and theoretical ways to strengthen resonant bonds with others and the world
GREEN NANOMATERIAL SYNTHESIS VIA RF SPUTTERING IN LIQUIDS AND ONTO POWDERS FOR SCALABLE, CRM-FREE CATALYSTS FOR WATER ELECTROLYSIS
No full textWe presented a dry and green synthesis approach using RF magnetron sputtering, a physical vapor deposition (PVD) technique, to fabricate nanofluids (nanoparticles suspended in liquids) and nanohybrids (catalyst-coated powders) as catalysts for water electrolysis applications. This solvent-free method eliminates hazardous chemicals and complex multi-step procedures, enabling sustainable and scalable production of ultrapure catalysts. For nanohybrids, copper-coated multi-walled carbon nanotubes (Cu/CNTs) and nickel-coated titania nanopowders (Ni/TiO2) were synthesized via RF magnetron sputtering combined with a vibrating deposition stage, which ensured uniform nanoparticle coating.1 For nanofluids, ultrapure nanoparticles (gold, copper, nickel, platinum) were obtained by RF sputtering directly into a liquid medium, preserving their native nanoscale morphology.2 These nanoparticles were then seamlessly transferred onto functional substrates such as Nafion membranes and graphene, forming uniform catalyst-coated membranes (CCM) and nanohybrids with ultra-low precious metal loading at the nanogram scale. Comprehensive characterization using SEM-EDX, XPS, XRD, AFM, and TEM confirmed nanoparticle integrity and dispersion. Electrochemical tests demonstrated an excellent hydrogen evolution reaction (HER) performance, comparable to commercial Pt-based materials. Therefore, this process addresses key challenges in PEM electrolyzer technology by lowering material costs, and offering a green, scalable, and industrially viable fabrication route
Development of a Passive Skin for Glass Building Surfaces in a Smart Electromagnetic Environment
No full textElectromagnetic metasurfaces (MTS), also referred to as Reconfigurable Intelligent Surfaces (RIS) in their dynamic form, have the potential to actively shape the wireless communication environment, particularly in 5G and 6G systems. They help overcome significant path loss issues, especially at millimeter-wave (mmWave) frequencies within the FR2 band. Our study focuses on MTS from a fabrication standpoint, highlighting the microfabrication methods employed to create a static and passive MTS prototype on a 6′′-optically transparent wafer substrate. This MTS design is intended for integration onto large glass surfaces commonly found in urban settings
Drone‐Based High‐Resolution LiDAR for Undercanopy Archaeology in Mediterranean Environment: Rusellae Case Study (Italy)
Get PDFThis paper presents a novel methodology and workflow successful in identifying and mapping undercanopy archaeology in woodland Mediterranean areas. The study area is characterized by dense vegetation typical of the Mediterranean area, located in southern Tuscany (Italy), within the territory of the ancient city of Rusellae next to the Tyrrhenian seaside. In February 2021, a drone-based LiDAR acquisition was led over an area of 550 ha, with an average of ~700 points/m2. Specifically, the combination of aerial drone and LiDAR sensor enabled us to obtain high-resolution and high-quantity data, requiring significant processing efforts facilitated by the collaboration among various expertise in different fields, such as archaeology, computer science and geomatics. Among the most significant, this experience demonstrates the implementation of a methodology that, under certain circumstances, can be effective for the archaeological study of Mediterranean landscapes covered by dense canopy and undergrowth vegetation. The results provide new insights into these areas by shedding light on previously unknown archaeological features and enhancing our understanding of past landscapes
Predicting human cooperation: Sensitizing drift-diffusion model to interaction and external stimuli
No full textHuman cooperation arises naturally and is essential for the development of successful societies. This study aims to identify which aspects of the interaction influence societal cooperation and defection. Specifically, we investigate human cooperation within the framework of the Multiplayer Iterated Prisoner’s Dilemma game, modelling the decision-making process by using the drift-diffusion model (DDM). We propose a novel Bayesian model for the evolution of the DDM parameters, based on the nature of interactions experienced with other players. This approach enables us to predict the evolution of the expected rate of cooperation within the population. We successfully validate our model using an unseen test dataset—separated from the training one—and apply it to explore three strategic scenarios known from previous research to affect cooperation: (i) manipulation of co-players, (ii) the use of rewards and punishments, and (iii) time pressure. Our model successfully explains the test dataset and behaves consistently with established findings in the literature on human behaviour in these simulated scenarios. These results support the potential of our model as a foundational tool for developing and testing strategies that foster cooperation, improving our ability to study, understand and intervene in scenarios where individual and collective interests conflict
An implementation of neural simulation-based inference for parameter estimation in ATLAS
No full textNeural simulation-based inference (NSBI) is a powerful class of machine-learning-based methods for statistical inference that naturally handles high-dimensional parameter estimation without the need to bin data into low-dimensional summary histograms. Such methods are promising for a range of measurements, including at the Large Hadron Collider, where no single observable may be optimal to scan over the entire theoretical phase space under consideration, or where binning data into histograms could result in a loss of sensitivity. This work develops a NSBI framework for statistical inference, using neural networks to estimate probability density ratios, which enables the application to a full-scale analysis. It incorporates a large number of systematic uncertainties, quantifies the uncertainty due to the finite number of events in training samples, develops a method to construct confidence intervals, and demonstrates a series of intermediate diagnostic checks that can be performed to validate the robustness of the method. As an example, the power and feasibility of the method are assessed on simulated data for a simplified version of an off-shell Higgs boson couplings measurement in the four-lepton final states. This approach represents an extension to the standard statistical methodology used by the experiments at the Large Hadron Collider, and can benefit many physics analyses
Le fluitazioni del legname nelle Alpi orientali. Fra continuità e discontinuità (XV-XIX secolo)
Get PDFThis essay focuses on the Eastern Alps, one of the most important wood-producing areas in northern Italy due to its rich forests (spruce, fir, larch, and beech) and to the growing demand of the densely populated Venetian mainland. Until the introduction of the railway in the mid-nineteenth century, an enviro-technical system was progressively developed along this area’s rivers and streams to link the forests to the markets for the transport of timber, an asset that has interconnected mountains and plains for centuries. The descent of the logs corresponded to a parallel ascent of goods that were not available in the mountains, such as wheat and wine. These goods were traded along the river route used by the rafts, intersecting and using the land road system. In the early modern period, a system of ports was established from which it was possible to float on rafts. Beyond this threshold, only rafting was practicable thanks to the infrastructure system (locks and canals) whose main resource was always water
Translation in the Hands of Many: Centering Lay Users in Machine Translation Interactions
No full textConverging societal and technical factors have transformed language technologies into user-facing applications used by the general public across languages. Machine Translation (MT) has become a global tool, with cross-lingual services now also supported by dialogue systems powered by multilingual Large Language Models (LLMs). Widespread accessibility has extended MT’s reach to a vast base of *lay users*, many with little to no expertise in the languages or the technology itself. And yet, the understanding of MT consumed by such a diverse group of users—their needs, experiences, and interactions with multilingual systems—remains limited. In our position paper, we first trace the evolution of MT user profiles, focusing on non-experts and how their engagement with technology may shift with the rise of LLMs. Building on an interdisciplinary body of work, we identify three factors—usability, trust, and literacy—that are central to shaping user interactions and must be addressed to align MT with user needs. By examining these dimensions, we provide insights to guide the progress of more user-centered MT
Artificial Intelligence Methods and Digital Intervention Strategies for Predicting and Managing Chronic Obstructive Pulmonary Disease Exacerbations: An Umbrella Review
Get PDFBackground: Chronic Obstructive Pulmonary Disease (COPD) is a major global health burden in which acute exacerbations accelerate progression and increase hospitalizations. Emerging technologies, such as wearable biosensors, artificial intelligence (AI), and digital health tools, enable more proactive disease management. Objectives: This umbrella review synthesized evidence from systematic reviews and meta-analyses on (1) AI-driven prediction of COPD exacerbations using low-cost wearable biosignals, and (2) the effectiveness of digital health interventions on disease management, quality of life, and medication adherence. Methods: A systematic search of PubMed, Scopus, and Web of Science (2015–2025) identified eligible reviews. Methodological quality was assessed using AMSTAR-2, and study overlap was quantified with the Corrected Covered Area (CCA). A narrative synthesis was conducted across two research questions. Protocol registered in PROSPERO (CRD420251164450). Results: Twenty-seven reviews met the inclusion criteria. AI models demonstrated promising internal predictive accuracy but lacked external validation and clinical integration. Digital health interventions, such as mHealth applications and telerehabilitation, showed small to moderate improvements in quality of life and physical function. Reported effects varied considerably (OR = 0.20–2.37; I2 = 0–94%), indicating substantial heterogeneity across studies. Evidence for improvements in medication adherence and exacerbation reduction was inconsistent, and most included reviews were rated “Low” or “Critically Low” in methodological quality, limiting the generalizability of findings. Conclusions: AI and digital tools show strong promise for proactive COPD management, particularly through wearable-derived biosignals, outperforming traditional static assessments. However, their clinical readiness remains limited due to small-scale studies, interpretability challenges, inconsistent outcome measures, and a lack of external validation. To support real-world translation and regulatory adoption, future research must prioritize large-scale, rigorous, and equitable studies with standardized methodologies and robust generalizability testing