Archivio della ricerca - Fondazione Bruno Kessler
Not a member yet
21227 research outputs found
Sort by
Learning of Lifted Macro-Events for Heuristic-Search Temporal Planning
No full textLearning domain knowledge from small training problems to improve planning performance on arbitrarily sized problems is a highly active research area. Many works explored the use of macro-actions to create "shortcuts" in the search space, at the cost of increasing the branching factor of the problem. In temporal planning, a recent technique proposes to equip a heuristic-search temporal planner with selected "macro-events": a "shortcut" mechanism similar to macro-actions but with state-dependent semantics.
In this paper, we generalize macro-events to a lifted representation, making them independent of specific problem objects. We devise a fully automated framework that, given a domain and a collection of small training problems, constructs and selects a suitable set of lifted macro-events. We define a learning pipeline that mixes the optimization of the statistical expectation on an abstraction of the problem with an empirical refinement of the selection on a validation set. We experimentally show that the proposed approach scales to complex problems, yielding substantial improvements over the baseline
Measurement of the Lund jet plane in hadronic decays of top quarks and W bosons with the ATLAS detector
No full textThe development of IBIC microscopy at the 100 kV ion implanter of the University of Torino (LIUTo) and the application for the assessment of the radiation hardness of a silicon photodiode
No full textThe ion beam induced charge (IBIC) technique is widely used to characterize the electronic properties of semiconductor materials and devices. Its main advantage over other charge collection microscopies stems in the use of MeV ion probes, which provide both measurable induced charge signals from single ions, and high spatial resolution, which is maintained along the ion range. It is a fact, however, that the use of low-energy ions in the keV range can provide the IBIC technique with complementary analytical capabilities that are not available with MeV ions, for example, the higher sensitivity to the status, contamination and morphology of the surface and the fact that the induced signal depends on the transport of only one type of charge carrier. This paper outlines the upgrade that was made at the 100 kV ion implanter of the University of Torino, originally installed for material and surface modification, to explore the rather unexplored keV-IBIC field and to assess its potential to characterize semiconductor devices. Finally, we report the first IBIC application of our apparatus, which regards the assessment of the radiation damage of a commercially available silicon photodiode, adopting the IAEA experimental protocol and the relevant interpretative model
A Survey on Automatic Credibility Assessment Using Textual Credibility Signals in the Era of Large Language Models
No full textIn the age of social media and generative AI, the ability to automatically assess the credibility of online content has become increasingly critical, complementing traditional approaches to false information detection. Credibility assessment relies on aggregating diverse credibility signals – small units of information, such as content subjectivity, bias, or a presence of persuasion techniques – into a final credibility label/score. However, current research in automatic credibility assessment and credibility signals detection remains highly fragmented, with many signals studied in isolation and lacking integration. Notably, there is a scarcity of approaches that detect and aggregate multiple credibility signals simultaneously. These challenges are further exacerbated by the absence of a comprehensive and up-to-date overview of research works that connects these research efforts under a common framework and identifies shared trends, challenges, and open problems. In this survey, we address this gap by presenting a systematic and comprehensive literature review of 175 research papers, focusing on textual credibility signals within the field of Natural Language Processing (NLP), which undergoes a rapid transformation due to advancements in Large Language Models (LLMs). While positioning the NLP research into the the broader multidisciplinary landscape, we examine both automatic credibility assessment methods as well as the detection of nine categories of credibility signals. We provide an in-depth analysis of three key categories: 1) factuality, subjectivity and bias, 2) persuasion techniques and logical fallacies, and 3) check-worthy and fact-checked claims. In addition to summarising existing methods, datasets, and tools, we outline future research direction and emerging opportunities, with particular attention to evolving challenges posed by generative AI
Development of a Comprehensive Evaluation Scale for LLM-Powered Counseling Chatbots (CES-LCC) Using the eDelphi Method
Get PDFBackground/Objectives: With advancements in Large Language Models (LLMs), counseling chatbots are becoming essential tools for delivering scalable and accessible mental health support. Traditional evaluation scales, however, fail to adequately capture the sophisticated capabilities of these systems, such as personalized interactions, empathetic responses, and memory retention. This study aims to design a robust and comprehensive evaluation scale, the Comprehensive Evaluation Scale for LLM-Powered Counseling Chatbots (CES-LCC), using the eDelphi method to address this gap. Methods: A panel of 16 experts in psychology, artificial intelligence, human-computer interaction, and digital therapeutics participated in two iterative eDelphi rounds. The process focused on refining dimensions and items based on qualitative and quantitative feedback. Initial validation, conducted after assembling the final version of the scale, involved 49 participants using the CES-LCC to evaluate an LLM-powered chatbot delivering Self-Help Plus (SH+), an Acceptance and Commitment Therapy-based intervention for stress management. Results: The final version of the CES-LCC features 27 items grouped into nine dimensions: Understanding Requests, Providing Helpful Information, Clarity and Relevance of Responses, Language Quality, Trust, Emotional Support, Guidance and Direction, Memory, and Overall Satisfaction. Initial real-world validation revealed high internal consistency (Cronbach’s alpha = 0.94), although minor adjustments are required for specific dimensions, such as Clarity and Relevance of Responses. Conclusions: The CES-LCC fills a critical gap in the evaluation of LLM-powered counseling chatbots, offering a standardized tool for assessing their multifaceted capabilities. While preliminary results are promising, further research is needed to validate the scale across diverse populations and settings
A Mindfulness-Based App Intervention for Pregnant Women: Qualitative Evaluation of a Prototype Using Multiple Case Studies
No full textBackground: Pregnancy is a complex period characterized by significant transformations. How a woman adapts to these changes can affect her quality of life and psychological well-being. Recently developed digital solutions have assumed a crucial role in supporting the psychological well-being of pregnant women. However, these tools have mainly been developed for women who already present clinically relevant psychological symptoms or mental disorders. Objective: This study aimed to develop a mindfulness-based well-being intervention for all pregnant women that can be delivered electronically and guided by an online assistant with wide reach and dissemination. This paper aimed to describe a prototype technology-based mindfulness intervention's design and development process for pregnant women, including the exploration phase, intervention content development, and iterative software development (including design, development, and formative evaluation of paper and low-fidelity prototypes). Methods: Design and development processes were iterative and performed in close collaboration with key stakeholders (N=15), domain experts including mindfulness experts (n=2), communication experts (n=2), and psychologists (n=3), and target users including pregnant women (n=2), mothers with young children (n=2), and midwives (n=4). User-centered and service design methods, such as interviews and usability testing, were included to ensure user involvement in each phase. Domain experts evaluated a paper prototype, while target users evaluated a low-fidelity prototype. Intervention content was developed by psychologists and mindfulness experts based on the Mindfulness-Based Childbirth and Parenting program and adjusted to an electronic format through multiple iterations with stakeholders. Results: An 8-session intervention in a prototype electronic format using text, audio, video, and images was designed. In general, the prototypes were evaluated positively by the users involved. The questionnaires showed that domain experts, for instance, positively evaluated chatbot-related aspects such as empathy and comprehensibility of the terms used and rated the mindfulness traces present as supportive and functional. The target users found the content interesting and clear. However, both parties regarded the listening as not fully active. In addition, the interviews made it possible to pick up useful suggestions in order to refine the intervention. Domain experts suggested incorporating auditory components alongside textual content or substituting text entirely with auditory or audiovisual formats. Debate surrounded the inclusion of background music in mindfulness exercises, with opinions divided on its potential to either distract or aid in engagement. The target users proposed to supplement the app with some face-to-face meetings at crucial moments of the course, such as the beginning and the end. Conclusions: This study illustrates how user-centered and service designs can be applied to identify and incorporate essential stakeholder aspects in the design and development process. Combined with evidence-based concepts, this process facilitated the development of a mindfulness intervention designed for the end users, in this case, pregnant women
Silicon drift detector monolithic arrays for X-ray spectroscopy
No full textThe efficient detection of low-energy X-rays at the keV level with the best possible energy resolution requires the application of silicon drift detectors (SDDs) and advanced application specific integrated circuits (ASICs). Their widespread use in material sciences, alongside dedicated basic science projects, has long been restricted to single, selected SDD elements working at low temperatures. This is because of the limits incurring in the quite elaborated planar technology production process and the need to reach very low leakage current levels, together with the need for highly specialized readout electronics.
We describe, in this review work, the concrete outcomes of the efforts of the ReDSoX collaboration to develop high energy resolution detection systems working at near room temperature based on multi-pixel monolithic silicon drift detectors and custom-designed advanced readout electronics capable of dealing with high photon fluxes, developed for specific projects but suitable for a variety of applications
Response to “Comment on ‘Third density and acoustic virial coefficients of helium isotopologues from ab initio calculations’” [J. Chem. Phys. 162, 244305 (2025)]
No full textAN ACCELERATED METHOD OF IMPREGNATION OF AT LEAST ONE WOODEN ELEMENT
No full textAn accelerated method of impregnation of at least one wooden element comprising at least one mechanical treatment (4) carried out so as to increase the chemical penetration and impregnation; the mechanical treatment (4) comprising at least one heating at a predetermined temperature and at least one compression at a predetermined pressure of the wooden element. Furthermore, the method of the invention also comprises at least one impregnation step (5) in which at least one impregnating solution is applied to the compressed wooden element so as to allow the impregnating solution to at least partially penetrate into the wooden element subsequent to the mechanical treatment (4)