Archivio della ricerca - Fondazione Bruno Kessler
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Rivoluzioni digitali. Il senso immerso nello spazio pubblico e virtuale iraniano
Get PDFJust as religious space is shaped by the bodies that traverse it, delimit it, respect it, and sanctify it, resistance to religion also manifests through the body that rejects its dictates, secularizes itself, and sheds part of its weight. Religious space is not a fixed and peaceful place but encompasses processes of conflict and negotiation. This is evident in the case of the Islamic Republic of Iran, where politics and religion have been intertwined since 1978 with the establishment of the Velayat-e Faqih political system: the governance of the jurist. While it is true that Iran’s recent history has seen the body assert its presence forcefully in public spaces, as happened during the 1978–79 revolution, the progressively disembodied body of contemporary Iran continues to fight for space, even if it is predominantly virtual.
During the 2022–2023 protests, the movement sparked by the death of Mahsa Jina Amini gradually transformed from a wave of anger expressed in streets and squares into a symbolic and disembodied action within the virtual space. The disembodiment of the protests and their increasing immersion in the digital network have yielded varied political effects. On the one hand, the disembodied protests did not culminate in a genuine popular revolution in Iran. On the other hand, nearly two years after the beginning of the Zan, Zendegi, Azadi (Women, Life, Freedom) movement, the reincarnation of some of its initial demands has become tangible and observable even in public spaces
Timing-optimized FBK Silicon Photomultipliers for a modular ToF-PET scanner: the PETVision
No full textPositron Emission Tomography (PET) is one of the leading methodologies in medical imaging for cancer diagnosis, but PET
scanners present some limitations in terms of cost and performance. In recent years, Time-of-Flight PET (ToF-PET) significantly
improved image reconstruction by adding to the energy used in standard PET machines, the time of arrival information of the two
511 keV annihilation photons. The PETVision project aims to use breakthrough findings in the ToF-PET research field to develop
a highly sensitive, fully modular and cost-accessible scanner to achieve 75 ps FWHM Coincidence Time Resolution (CTR). This
challenge requires a revolutionary technology change in terms of photodetectors, readout electronics and integration methodology
to push the limit of the timing performance.
In controlled laboratory conditions, a CTR of 96 ps FWHM has been achieved by using FBK NUV-HD-MT SiPMs 3 × 3mm2,
40μm cell size with metal masking outside the active area (M0) coupled with a 2mm×2mm×20mm co-doped LYSO:Ce:Ca
crystal. A 60 ps FWHM CTR was achieved using the same device on a 2 mm × 2 mm × 3 mm crystal. These measurements
have been performed using high-frequency readout electronics with high power consumption; thus, they are not scalable to multichannel
systems and are impractical for realistically sized imaging systems. Therefore, much effort is being made to develop
a novel, custom front-end System-on-Chip (SoC) ASIC to be coupled with these next-generation timing-optimized SiPMs and
ensure high-timing performance. Preliminary results using the FastIC+ ASIC, developed at ICCUB and CERN, are extremely
promising, showing a CTR of 89 ps FWHM with a 3mm co-doped LYSO:Ce:Ca crystal using a FBK NUV-HD-MT 3×3mm2
50 μm M0.
Thanks to the collaboration of several universities, research centres and industries, PETVision is set to make significant advancements
in detector design, photo-sensor and front-end electronics by developing an affordable, fast and precise ToF-PET scanner,
enabling early cancer detection and therapy monitoring, opening the way for personalized medicine
Learning Loss and Students' Social Origins during the COVID-19 Pandemic in Italy
No full textThe aim of this paper is twofold. First, it intends to establish the intensity of learning loss in reading and mathematics experienced in Italy by fifth, eighth and thirteenth graders because of school closures owing to the COVID-19 pandemic. Second, it aims to check whether school closures have affected the educational disparities associated with students’ families’ socioeconomic status and three other possible inequality factors: geographic area of residence, migrant status and high school track. To estimate these two possible effects of the pandemic, we use INVALSI data collected in academic years 2018-2019 and 2020-2021 and rely on a counterfactual approach based on coarsened exact matching, where students belonging to the 2020-2021 cohort represent the treated group and those of the 2018-2019 cohort make up the control group. Our results indicate that the learning loss is definitely severe among students attending grades thirteen and eight, while it is less pronounced and involves only mathematics among fifth graders. Furthermore, our analyses show that the intensity of the learning loss is substantially the same irrespective of students’ social origins and their remaining ascriptive traits. A tentative explanation of this counter-intuitive result is presented
Total Cost of Ownership and Evaluation of Google Cloud Resources for the ATLAS Experiment at the LHC
No full textThe ATLAS Google Project was established as part of an ongoing evaluation of the use of commercial clouds by the ATLAS Collaboration, in anticipation of the potential future adoption of such resources by WLCG grid sites to fulfil or complement their computing pledges. Seamless integration of Google cloud resources into the worldwide ATLAS distributed computing infrastructure was achieved at large scale and for an extended period of time, and hence cloud resources are shown to be an effective mechanism to provide additional, flexible computing capacity to ATLAS. For the first time a total cost of ownership analysis has been performed, to identify the dominant cost drivers and explore effective mechanisms for cost control. Network usage significantly impacts the costs of certain ATLAS workflows, underscoring the importance of implementing such mechanisms. Resource bursting has been successfully demonstrated, whilst exposing the true cost of this type of activity. A follow-up to the project is underway to investigate methods for improving the integration of cloud resources in data-intensive distributed computing environments and reducing costs related to network connectivity, which represents the primary expense when extensively utilising cloud resources
Robust solutions via optimisation and predictive process monitoring for the scheduling of the interventional radiology procedures
No full textInterventional radiology (IR) is an increasingly used medical specialty relying on the possibilities offered by medical imaging guidance technologies to perform minimally invasive procedures (both diagnostic and therapeutic) through very small incisions or body orifices. Although the operative context is quite similar to that of the classical operating room (OR) literature, to the best of our knowledge management problems arising in the IR operative context never appeared in the healthcare management literature. This is even more true for studies that combine the OR approach with automatic extraction of information from real hospital health record data as in the present study. Two specific features characterise our case study with respect to the traditional OR literature: due to the Italian legislation, the anaesthetist (usually in a very limited number) must be present for the entire duration of the procedure (
), and the IR does not have its own ward but receives inpatients from different wards (
). The aim of this paper is to introduce a novel approach to determine a robust solution for our case study problem addressing both features
and
. Our approach is based on the interplay between optimisation and predictive process monitoring (PPM) models. The obtained results show that the proposed approach produces schedules that achieve higher usage rate, lower overtime and more patients operated on than the original schedule. We also show that the integration of PPM models within the optimisation workflow improves the quality of the output schedule with respect to the standard one-shot optimisation
Engaging youth in gender-based violence education through gamification: A user experience evaluation of different game modalities
Get PDFGender-based violence (GBV) remains a critical human rights issue, deeply rooted in gender inequality and affecting individuals globally. The current study evaluated the user experience of a gamified platform designed to raise awareness about GBV. Gamification, using game elements in non-game environments. has been proven to promote online and offline learning, but its effectiveness has yet to be tested in the case of sensitive educational material. We explored how the platform motivated and engaged users through two versions: individual and cooperative. Using the MEEGA360 scale for user experience and the Geneva Emotion Wheel for emotions, 40 users were randomly assigned to one of the versions. Results showed the platform was well-received, with users finding it enjoyable, user-friendly, and effective in facilitating discussions on GBV. Positive emotions like involvement, amusement, and interest were common, though negative emotions like irritation and anger also appeared. Despite these positive outcomes, the platform faced usability challenges and requests for more complex activities and detailed feedback. The cooperative version scored higher on social interaction but did not significantly outperform the individual version. Further research is needed to explore these differences and improve the platform’s effectiveness in GBV prevention
Effects of Different Inertial Measurement Unit Sensor-to-Segment Calibrations on Clinical 3-Dimensional Humerothoracic Joint Angles Estimation
Get PDFCalibrating inertial measurement units (IMUs) involves converting orientation data from a local reference frame into a clinically meaningful reference system. Several solutions exist but little work has been done to compare different calibration methods with each other and an optical motion capture system. Thirteen healthy subjects with no signs of upper limb injury were recruited for this study and instrumented with IMU sensors and optical markers. Three IMU calibration methods were compared: N-pose calibration, functional calibration, and manual alignment. Subjects executed simple single-plane single-joint tasks for each upper limb joint as well as more complex multijoint tasks. We performed a 3-way analysis of variance on range of motion error, root mean squared error, and offset to assess differences between calibrations, tasks, and anatomical axes. Differences in the 3 IMU calibrations are minor and not statistically significant for most tasks and anatomical axes, with the exception of the offset interaction calibration × axes (P < .001, ηG2=.056). Specifically, manual alignment gives the best offset estimation on the abduction/adduction and internal/external rotation axes. Therefore, we recommend the use of a static N-pose calibration procedure as the preferred IMU calibration method to model the humerothoracic joint, as this setup is the simplest as it only requires accurate positioning of the trunk sensor
F-OSFA: A Fog Level Generalizable Solution for Zero-Day DDOS Attacks Detection
Get PDFThe globalization and digitization of society have caused a surge in network traffic, making reliable online services essential for user trust and system functionality. However, these services face ever-increasing threats, particularly complex and well-developed Distributed Denial of Service (DDoS) attacks. Zero-day DDoS attacks, a type of DDoS attack, are especially challenging because their new and unseen nature and lack of training data render traditional Intrusion Detection and Prevention Systems (IDPS) ineffective. To tackle this, we propose the Fog-based One Solution For All (F-OSFA) system - a model with three specialized components. The first component uses a hybrid machine learning and deep learning framework that combines convolutional neural networks (CNNs) and decision trees to detect traditional DDoS attacks. The second component employs a few-shot learning module with a contractive autoencoder for zero-day attack detection. The third component is a signature-based resource usage analyzer to counter attacks mimicking normal traffic. We demonstrate the efficacy of F-OSFA on publicly available datasets and prove the scheme is generalizable and effective. F-OSFA achieves an accuracy of 99.72% on CICDDoS2019 and 99.96% on CICIDS2017. In addition, it demonstrates its efficacy in the zero-day scenario as well by achieving a 96.77% on CICDDoS2019 and 95.98% on CICIDS2017. These evaluations testify to F-OSFA as a reliable and versatile solution against ever-evolving DDoS threats
Quantifying West Nile virus circulation in the avian host population in Northern Italy
No full text:West Nile virus (WNV) is one of the most threatening mosquito-borne pathogens in Italy where hundreds of human cases were recorded during the last decade. Here, we estimated the WNV incidence in the avian population in the Emilia-Romagna region through a modelling framework which enabled us to eventually assess the fraction of birds that present anti-WNV antibodies at the end of each epidemiological season. We fitted an SIR model to ornithological data, consisting of 18,989 specimens belonging to Corvidae species collected between 2013 and 2022: every year from May to November birds are captured or shot and tested for WNV genome presence. We found that the incidence peaks between mid-July and late August, infected corvids seem on average 17% more likely to be captured with respect to susceptible ones and seroprevalence was estimated to be larger than other years at the end of 2018, consistent with the anomalous number of recorded human infections. Thanks to our modelling study we quantified WNV infection dynamics in the corvid community, which is still poorly investigated despite its importance for the virus circulation. To the best of our knowledge, this is among the first studies providing quantitative information on infection and immunity in the bird population, yielding new important insights on WNV transmission dynamics
