Archivio della ricerca - Fondazione Bruno Kessler
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Integrative AI for the Understanding of Ancient Javanese Architectures
Get PDFThe use of digital techniques has seen an increasing amount of use in recent years for heritage documentation. The development of artificial intelligence (AI) also contributed to this rise, with many different applications to help facilitate the heritage recording process. A by-product of these developments is the increasing amount of available data, in tandem with the ever-increasing need for training data for AI purposes. This paper aims to re-use old datasets and repurpose them using modern methods. The objective is therefore to see if older datasets may be used to improve the quality of AI-based methods, while also investigating the use of new technologies such as Visual Language Models (VLM) to perform semantic queries and Gaussian splatting on these datasets. For this purpose, datasets from a previous documentation project involving Javanese “candi” architecture is used in this paper since this particular subject has not seen too many AI-based documentation research in the literature and is thus an interesting example
to evaluate the generalisation of AI methods. Results show that old datasets can very well be used with modern techniques with
promising results. In terms of semantic segmentation, machine learning yielded an overall accuracy of 0.89 while deep learning
yielded 0.79. Several interesting inferences were also observed in the VLM query results, while Gaussian splatting showed
very strong potential for visualisation-based applications to further enhance the reusability of these old datasets
Search for a new pseudoscalar decaying into a pair of bottom and antibottom quarks in top-associated production in √s = 13 TeV proton–proton collisions with the ATLAS detector
No full textGender-Neutral Rewriting in Italian: Models, Approaches, and Trade-offs
Get PDFGender-neutral rewriting (GNR) aims to reformulate text to eliminate unnecessary gender specifications while preserving meaning, a particularly challenging task in grammatical-gender languages like Italian. In this work, we conduct the first systematic evaluation of state-of-the-art large language models (LLMs) for Italian GNR, introducing a two-dimensional framework that measures both neutrality and semantic fidelity to the input. We compare few-shot prompting across multiple LLMs, fine-tune selected models, and apply targeted cleaning to boost task relevance. Our findings show that open-weight LLMs outperform the only existing model dedicated to GNR in Italian, whereas our fine-tuned models match or exceed the best open-weight LLM’s performance at a fraction of its size. Finally, we discuss the trade-off between optimizing the training data for neutrality and meaning preservation
Interaction quench dynamics and stability of quantum vortices in rotating Bose-Einstein condensates
No full textWe theoretically investigate the nonequilibrium dynamics of quantum vortices in a two-dimensional rotating Bose-Einstein condensate following an interaction quench. Using an ab initio and numerically exact quantum many-body approach, we systematically tune the interplay between interaction strength and angular velocity to prepare quantum vortices in various configurations and examine their postquench dynamics. Our study reveals distinct dynamical regimes: first, vortex distortion accompanied by density cloud fragmentation, matching the initial vortex number, and second, vortex revival, where fragmented densities interact and merge. Notably, we observe complete vortex revival dynamics in the single-vortex case, pseudorevival in double- and triple-vortex configurations, and irregular many-body dynamics in systems with multiple vortices. The observed dynamics is analyzed by the measures of many-body information entropy dynamics establishing the key role played by the dynamical fragmentation and delocalization in Fock space. Our results reveal a universal out-of-equilibrium response of quantum vortices to interaction quenches, highlighting the importance of many-body effects with a possible exploration in quantum simulation with ultracold quantum fluids
Measured gain suppression in FBK LGADs with different active thicknesses
No full textIn recent years, the gain suppression mechanism has been studied for large localized charge deposits in Low-Gain Avalanche Detectors (LGADs). LGADs are a thin silicon detector with a highly doped gain layer that provides moderate internal signal amplification. Using the CENPA Tandem accelerator at the University of Washington, the response of LGADs with different thicknesses to MeV-range energy deposits from a proton beam were studied. Three LGAD prototypes of 50 μm, 100 μm, and 150 μm were characterized. The devices' gain was determined as a function of bias voltage, incidence beam angle, and proton energy. This study was conducted in the scope of the PIONEER experiment, an experiment proposed at the Paul Scherrer Institute to perform high-precision measurements of rare pion decays. LGADs are considered for the active target (ATAR), and energy linearity is an important property for particle ID capabilities
From Mistery to Mastery, and Back Again: Reframing Technological Procreation Through Awe
Get PDFThis paper explores how reproductive biotechnologies — from IVF and surrogacy to ultrasound imaging and genome editing — have progressively mediated and transformed the awe once surrounding natural procreation.
As the womb evolves from a hidden and protective space into a transparent and surveilled one, the sacred dimension of reproduction — understood both as reverence and as Agambenian separateness — appears increasingly eroded.
By re-centering awe in the debate on reproductive and genetic technologies, this work proposes a reframing of the relationship between theology and technology. It suggests that awe can function as an ethical bridge between these domains, fostering an understanding of procreation grounded in openness, relationality, and the responsible formation of the self as a procreative agent
Search for charged Higgs bosons produced in top-quark decays or in association with top quarks and decaying via H± →τ±ντ in 13 TeV pp collisions with the ATLAS detector
No full textCharged Higgs bosons produced either in top-quark decays or in association with a top quark, subsequently decaying via H± →τ±ντ, are searched for in 140 fb−1 of proton-proton collision data at √s =13 TeV recorded with the ATLAS detector. Depending on whether the top quark is produced together with the H± decays hadronically or semileptonically, the search targets τ +jets or τ +lepton final states, in both cases with a τ-lepton decaying into a neutrino and hadrons. No significant excess over the Standard Model background expectation is observed. For the mass range of 80 ≤mH± ≤3000 GeV, upper limits at 95% confidence level are set on the production cross section of the charged Higgs boson times the branching fraction B(H± →τ±ντ) in the range 4.5 pb–0.4 fb. In the mass range 80–160 GeV, assuming the Standard Model cross section for t ̄t production, this corresponds to upper limits between 0.27% and 0.02% on B(t →bH±) ×B(H± →τ±ντ)
Counterfactual Scenarios for Automated Planning
No full textCounterfactual Explanations (CEs) are a powerful technique used to explain Machine Learning models by showing how the input to a model should be minimally changed for the model to produce a different output. Similar proposals have been made in the context of Automated Planning, where CEs have been characterised in terms of minimal modifications to an existing plan that would result in the satisfaction of a different goal. While such explanations may help diagnose faults and reason about the characteristics of a plan, they fail to capture higher-level properties of the problem being solved. To address this limitation, we propose a novel explanation paradigm that is based on counterfactual scenarios. In particular, given a planning problem P and an LTLf formula ψ defining desired properties of a plan, counterfactual scenarios identify minimal modifications to P such that it admits plans that comply with ψ. In this paper, we present two qualitative instantiations of counterfactual scenarios based on an explicit quantification over plans that must satisfy ψ. We then characterise the computational complexity of generating such counterfactual scenarios when different types of changes are allowed on P. We show that producing counterfactual scenarios is often only as expensive as computing a plan for P, thus demonstrating the practical viability of our proposal and ultimately providing a framework to construct practical algorithms in this area
The Unheard Alternative: Contrastive Explanations for Speech-to-Text Models
Get PDFContrastive explanations, which indicate why an AI system produced one output (the target) instead of another (the foil), are widely recognized in explainable AI as more informative and interpretable than standard explanations. However, obtaining such explanations for speech-to-text (S2T) generative models remains an open challenge. Adopting a feature attribution framework, we propose the first method to obtain contrastive explanations in S2T by analyzing how specific regions of the input spectrogram influence the choice between alternative outputs. Through a case study on gender translation in speech translation, we show that our method accurately identifies the audio features that drive the selection of one gender over another
A Multi-Objective Optimization of a District Heating Network: Integrated and Dynamic Decarbonization Solutions for the Case Study of Riva Del Garda (Italy)
No full textThis study explores the decarbonization of the district heating network in Riva del Garda. The existing system (baseline) was modeled in EnergyPLAN, and future configurations were optimized using a Multi-Objective Evolutionary Algorithm (MOEA) to minimize both CO2 emissions and annual costs. Nine decision variables were assessed under defined boundary conditions to generate alternative future scenarios grouped into five types. In Type A, a large deep geothermal cogeneration plant combined with a small biomass boiler achieved the only zero-emission solution, with lower annual costs than the baseline but high capital needs. Excluding deep geothermal cogeneration (Type B) led to dominance of the biomass boiler and waste heat recovery from the Alto Garda Power (AGP) plant; full decarbonization remained possible only with extensive biomass use at a higher cost. Removing biomass (Type C), the solar thermal plant, and the shallow geothermal heat pump enabled deep but costly decarbonization, including grid electricity dependence. Types D and E, dominated, respectively, by shallow geothermal heat pump and electric boiler, provided moderate emission reductions and further increase in costs. Across all types, thermal storage improved operational flexibility. These analyses were also extended to assess potential district heating network expansions within Riva del Garda and into the neighboring municipality of Arco