Archivio della ricerca - Fondazione Bruno Kessler
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A compact QRNG for IoT applications
No full textThe present paper describes a new QRNG based on the arrival time of photons. The device needs an external light source to fully control the generation of random bit. This allows to ensure an almost constant data rate, regardless possible environmental parameter variations, and a minimization of the contribution of other unwanted sources of noise (DCR). To increase the output rate, the QRNG is split up into several e lementary generators organized in an array working simultaneously. Moreover, an embedded post-processing block allows to improve the output entropy for a high quality random sequence. The device, now under test, has been designed in a standard 150nm CMOS technology. Preliminary results showed an average activity of about 30 Mbps (raw data)
Physicochemical and Antimicrobial Evaluation of Bacterial Cellulose Derived from Spent Tea Waste
No full textBacterial cellulose (BC) is a high-purity biopolymer with excellent physicochemical and mechanical properties, including high crystallinity, water absorption, biocompatibility, and structural tunability. However, its large-scale production is hindered by high substrate costs and limited sustainability. In this study, spent black tea waste was utilized as a low-cost and eco-friendly carbon source for BC synthesis by Komagataeibacter xylinus ATCC 53524 under varying initial pH conditions (4–9). Six different BC membranes were produced and systematically characterized in terms of mechanical strength, water absorption capacity, electrical conductivity, antimicrobial performance, and polyvinyl alcohol (PVA) attachment efficiency. Morphological and chemical analyses were conducted using SEM and FTIR techniques to investigate pH-induced structural variations. The results revealed that the BC6 sample (pH 6) exhibited the highest tensile strength (2.4 MPa), elongation (13%), PVA incorporation (12%), and electrical conductivity, confirming the positive impact of near-neutral conditions on nanofiber assembly and functional integration. In contrast, the BC4 sample (pH 4) demonstrated strong antimicrobial activity (log reduction = 3.5) against E. coli, suggesting that acidic pH conditions enhance bioactivity. SEM images confirmed the most cohesive and uniform fiber morphology at pH 6, while FTIR spectra indicated the preservation of characteristic cellulose functional groups across all samples. Overall, this study presents a sustainable and efficient strategy for BC production using food waste and demonstrates that synthesis pH is a key parameter in tuning its functional performance. The optimized BC membranes show potential for biomedical, flexible electronic, and antibacterial material applications, particularly in wearable electrode technologies
NUTSHELL: A Dataset for Abstract Generation from Scientific Talks
No full textScientific communication is receiving increasing attention in natural language processing, especially to help researches access, summarize, and generate content. One emerging application in this area is Speech-to-Abstract Generation (SAG), which aims to automatically generate abstracts from recorded scientific presentations. SAG enables researchers to efficiently engage with conference talks, but progress has been limited by a lack of large-scale datasets. To address this gap, we introduce NUTSHELL, a novel multimodal dataset of *ACL conference talks paired with their corresponding abstracts. We establish strong baselines for SAG and evaluate the quality of generated abstracts using both automatic metrics and human judgments. Our results highlight the challenges of SAG and demonstrate the benefits of training on NUTSHELL. By releasing NUTSHELL under an open license (CC-BY 4.0), we aim to advance research in SAG and foster the development of improved models and evaluation methods
A Preliminary Study on the Detection of Glacial Lake Outburst Flood in Norway Using Sentinel 2 Imagery
No full textOver recent decades, glacier retreat has altered dynamics and increased hazards, such as glacial lake outburst floods (GLOFs), leading to severe downstream flooding. While GLOFs are typically detected through on-site monitoring, existing remote sensing methods primarily map glacial lakes, without identifying GLOF events. This paper proposes an unsupervised approach to detect GLOFs using Sentinel-2 image time series. We train a deep network to model non-draining lake time series, preventing them from appearing as anomalies when drained. The model, based on convolutional Long-Short-Term Memory and a 3D convolutional neural network, reconstructs non-draining lake time series. Inference errors reveal draining lakes. Preliminary experiments on Norwegian glacial lakes show promising results for automated GLOF detection
Energy scale and resolution for anti-kt jets with radius parameters R=0.2 and 0.6 measured in proton-proton collisions at √s = 13 TeV with the ATLAS detector
No full textWorthIt: Check-worthiness Estimation of Italian Social Media Posts
No full textCheck-worthiness estimation is the first and a paramount task in the automated fact-checking pipeline. It allows professional fact-checkers to cope with the increasing amount of mis/disinformative textual content being published online by prioritizing claims that are factual/verifiable and worthy of verification. Despite the long tradition of check-worthiness estimation in NLP, there is currently a lack of annotated resources and associated methods for Italian. Moreover, current datasets typically cover a single topic and focus on a limited time frame, affecting models’ generalizability on out-of-distribution data. To fill these gaps, in this paper we introduce WorthIt, the first annotated dataset for factuality/verifiability and check-worthiness estimation of Italian social media posts that covers public discourse on migration, climate change, and public health issues across a large time period of six years. We describe the dataset creation in detail and conduct thorough experimentation with the WorthIt dataset using a wide array of encoder- and decoder-based models. Our results show that fine-tuning monolingual encoder-based models in a multi-task setting provides the best overall performance and that decoder-based models in a few-shot setup still struggle in capturing the relation between factuality/verifiability and check-worthiness. We release our dataset, code, and associated materials to the research community
Universal Roughness and the Dynamics of Urban Expansion
No full text: Urban sprawl reshapes cities, yet its quantitative laws remain elusive. Analyzing built-up expansion in 19 cities (1985-2015) with tools from surface growth physics in radial geometry, we reveal anisotropic, branchlike growth and a piecewise linear scaling between area and population. We uncover a robust local roughness exponent α_{loc}≈0.54, coexisting with variable β and z. This unusual coexistence of universal and variable exponents offers a rare empirical test bed for nonequilibrium growth and an empirical basis for modeling urban sprawl
Spotting Tell-Tale Visual Artifacts in Face Swapping Videos: Strengths and Pitfalls of CNN Detectors
No full textFace swapping manipulations in video streams represents an increasing threat in remote video communications, due to advances in automated and real-time tools. Recent literature proposes to characterize and exploit visual artifacts introduced in video frames by swapping algorithms when dealing with challenging physical scenes, such as face occlusions. This paper investigates the effectiveness of this approach by benchmarking CNN-based data-driven models on two data corpora (including a newly collected one) and analyzing generalization capabilities with respect to different acquisition sources and swapping algorithms. The results confirm excellent performance of general-purpose CNN architectures when operating within the same data source, but a significant difficulty in robustly characterizing occlusion-based visual cues across datasets. This highlights the need for specialized detection strategies to deal with such artifacts
Fabrication technologies of back-side illuminated SiPM for VUV/NUV light detection at Fondazione Bruno Kessler
No full textThe development of Front-Side Illuminated (FSI) Silicon Photomultipliers (SiPMs) has significantly advanced over the past years, with improvements in the fill factor (FF) and photon detection efficiency (PDE). However, further improvements are not straightforward without a deep modification in the internal structure of the microcell. A new approach based on the back-side Illuminated (BSI) SiPMs concept has been proposed to overcome these limitations, offering the potential for 100% FF, even with small microcell sizes. This paper focuses on the fabrication challenges associated with BSI SiPMs, particularly optimized for Vacuum Ultraviolet (VUV) and Near Ultraviolet (NUV) light detection, where high efficiency requires the complete removal of the substrate and the creation of a thin active “entrance window” for an efficient collection of the photogenerated carriers
Microwave-Assisted Synthesis of Visible Light-Driven BiVO4 Nanoparticles: Effects of Eu3+ Ions on the Luminescent, Structural, and Photocatalytic Properties
No full textThe optimization of BiVO4-based structures significantly contributes to the development of a global system towards clean, renewable, and sustainable energies. Enhanced photocatalytic performance has been reported for numerous doped BiVO4 materials. Bi3+-based compounds can be easily doped with rare earth (RE3+) ions due to their equal valence and similar ionic radius. This means that RE3+ ions could be regarded as active co-catalysts and dopants to enhance the photocatalytic activity of BiVO4. In this study, a simple microwave-assisted approach was used for preparing nanostructured Bi1−xEuxVO4 (x = 0, 0.03, 0.06, 0.09, and 0.12) samples. Microwave heating at 170 °C yields a bright yellow powder after 10 min of radiation. The materials are characterized through X-ray diffraction (XRD), transmission electron microscopy (TEM), ultraviolet–visible–near-infrared diffuse reflectance spectroscopy (UV-Vis-NIR DRS), photoluminescence spectroscopy (PL), and micro-Raman techniques. The effects of the different Eu3+ ion concentrations incorporated into the BiVO4 matrix on the formation of the monoclinic scheelite (ms-) or tetragonal zircon-type (tz-) BiVO4 structure, on the photoluminescent intensity, on the decay dynamics of europium emission, and on photocatalytic efficiency in the degradation of Rhodamine B (RhB) were studied in detail. Additionally, microwave chemistry proved to be beneficial in the synthesis of the tz-BiVO4 nanostructure and Eu3+ ion doping, leading to an enhanced luminescent and photocatalytic performance