IRIS Università degli Studi dell'Aquila
Not a member yet
68355 research outputs found
Sort by
Patient-Reported Outcomes After First Pulmonary Vein Isolation for ParoxYsmal Atrial Fibrillation: Cryoballoon vs. Radiofrequency (SPY-AF)
Full text linkBackground/Objectives: Patient-reported outcome after treatment is an important factor that positively correlates with the quality of care and can influence the patient’s future health choices. Both radiofrequency ablation (RFA) and cryoballoon ablation (CBA) are effective techniques for pulmonary vein isolation in patients with atrial fibrillation (AF) and have shown similar results in efficacy and safety, but they have not been thoroughly compared in terms of patient satisfaction. The aim of this study is to assess the satisfaction of paroxysmal AF patients who underwent RFA and CBA after their first procedure. Methods: Consecutive patients who underwent their first procedure of pulmonary vein isolation with RFA or CBA in eight international centres were included. A ten-point Likert scale was used for measuring patient-reported outcomes, evaluating anxiety before procedure, pain during and after ablation, motivation to repeat the procedure in future if necessary, and real and perceived procedural time. Results: A total of 483 patients were enrolled. Median age was 63 [56–69] years, and 281 (58.1%) patients were men. In total, 385 (79.7%) patients underwent RFA and 98 (20.3%) underwent CBA. RFA and CBA were equivalent in terms of the satisfaction of the patient, with the only exception being groin pain, which was lower in the CBA group (2 [0–3] vs. 3 [1–4], p = 0.002). Conscious sedation was used in 414 (86.7%) patients and general anaesthesia in 69 (14.3%) patients. The use of general anaesthesia reduced the perceived pain during and after the procedure in both techniques (p < 0.05), but it resulted in lower pre-procedural anxiety only in RFA patients compared to those under conscious sedation (4 [2–6] vs. 5 [3–7], p = 0.007). Anaesthetic management alone did not affect the willingness to repeat the procedure in RFA patients, while CBA patients under general anaesthesia were more motivated to repeat the procedure than those under conscious sedation (10 [8–10] vs. 7 [6–8], p < 0.001). The perceived procedure time was shorter than the actual time in all settings. Conclusions: Anaesthetic management seems to have a greater impact on patient-reported outcome than the technique used during ablation. Despite this, patients most motivated to repeat the procedure were those who underwent CBA under general anaesthesia
STRATEGIE DI MODELLAZIONE HBIM: IL CASO STUDIO DELLA CHIESA DI SAN SEBASTIANO A CANISTRO (AQ)
No full textIn the field of architectural heritage, data and information management plays a key role, as their structured organization is essential for knowledge and documentation of the asset. In this, Historic Building Information Modelling (HBIM), thanks to offering itself as a single, shared and easily updatable information system, represents a great opportunity both to form a reliable knowledge base and to make the processes concerning an architectural asset (management and maintenance, restoration, etc.) more efficient. This is despite the well-known critical issues related to extending a methodology developed for new buildings to historic buildings. These issues concern the geometric modelling of complex architectural shapes and the enrichment of HBIM models with information that does not result from design choices but from surveys and analyses of artifacts.
Starting from these considerations, the contribution aims to develop critical reflections useful for the definition of a framework for the application of the BIM methodology to architectural heritage. In particular, through the experimentation on a case study represented by the church of San Sebastiano in Canistro (AQ), we want to test an operational process that, while taking into account the specificities of each case, can be framed within a standardized process for HBIM information modelling
Investigation on the Detection of Crack Defects in Metals Using Chirp Ultrasonic-Induced Infrared Thermography
No full textChirp ultrasonic infrared thermography is widely applied in material nondestructive testing, while its defect recognition effect is constrained by lateral thermal diffusion and image noise. In this article, a time-frequency domain transient features reconstruction (TFFR) technique has been proposed to solve these issues. First, a 3-D thermal-wave propagation model of metal cracks under a chirp excitation thermal source was developed to analyse the temperature field distribution and thermal-wave diffusion. Second, TFFR was proposed to extract defect characteristics and compared with other algorithms [fractional Fourier transform (FrFT), cross correlation (CC), dual orthogonal demodulation (DOD), principal component analysis (PCA), partial least squares regression (PLSR)]. In addition, the experimental setup of chirp ultrasonic-induced infrared thermography was developed, and the effects of image sequence window size and excitation parameters on TFFR signal-to-noise ratio (SNR) were investigated to determine the optimal parameters. Finally, the crack sizes were calculated and compared with actual measurements, showing that TFFR can effectively reduce lateral heat diffusion and noise, improving SNR. The TFFR phase map achieved minimal size measurement errors, with relative errors of 5.4% and 7.9% for defects 1# and 2#, respectively
Developmental trends in headache: an Italian school-based study of age- and gender-related changes in clinical characteristics and burden from childhood to adolescence
Full text linkBackground: Pediatric headache disorders are a significant public health issue, affecting school performance, social participation, and quality of life. Objective: Our aim was to explore the age- and gender-related changes in the characteristics and burden of headaches from childhood to adolescence, with a focus on diagnostic shifts, frequency, intensity, and quality-of-life. Design: We conducted a cross-sectional survey on five primary and secondary schools in the L'Aquila district, Italy. Methods: Using the translated Italian version of the Headache-Attributed Restriction, Disability, Social Handicap and Impaired Participation questionnaire, we collected data on headache frequency, intensity, duration, associated symptoms, and impact. Diagnoses were algorithmically assigned through International Classification of Headache Disorders, 3rd edition criteria. Statistical analyses examined the effects of age, gender, and their interaction on clinical and quality-of-life outcomes. Results: In total, 431 students were included (mean age: 9.82 ± 2.28 years; range: 6-15; 52.9% female). Findings indicated that as children grow older, headaches become increasingly frequent, longer in duration, and more intensely experienced. The progression from primary to secondary school was accompanied by a transition in diagnosis, with undifferentiated headaches giving way to more specific categories, such as probable or definite migraine and, to a lesser extent, tension-type headache. Age-by-gender interactions revealed that older females experienced greater frequency and a more pronounced impact, while headache frequency affected quality of life with increasing age. Conclusion: Findings highlight gender-specific developmental trends in headache, characterized by increased frequency, intensity, and diagnostic clarity from childhood to adolescence. The burden of headache, particularly among older students, underscores the need for early recognition and age-appropriate interventions
Using Yearly-Resolved Time Series to Disentangle Interannual Variability, Directional Change, and Pseudoturnover in Plant Community Composition
Full text linkQuestions: Change in species composition over time is the result of both interannual variability, that is, year-to-year fluctuations due to weather patterns or demographic processes, and directional change, following succession or changing climatic conditions. Quantifying each component is difficult due to the confounding effects of pseudoturnover (i.e., apparent turnover due to observer error). Can yearly-resolved vegetation plot time series be used to quantify the relative contribution of these components of change, while controlling for pseudoturnover?. Location: A European beech (Fagus sylvatica) forest in Central Apennines, Italy. Methods: We developed an approach based on matrix decomposition and PERMANOVA to disentangle the effect of pseudoturnover, directional change, and interannual variability across nine permanent vegetation plots resurveyed for thirteen consecutive years, comparing the herb layer in a newly formed canopy gap, at the gap margins, and in the forest interior. We used helical graphs, generalized linear models, and non-metric multidimensional scaling to compare the timing and pace of vegetation change. Results: Interannual variability and directional change accounted for similar shares of overall variation (26.7% and 28.9%, respectively). While pseudoturnover accounted for a modest 0.4%, ignoring it would result in a substantial overestimation of interannual variability. Overall, the herb layer reacted vigorously to disturbance-triggered changes in light conditions. Species richness increased from 11 to 23.3 in canopy gaps but remained stable at the gap margin and in the forest interior. The rate of change was 3.0 species/year immediately after disturbance and slowed down to 0.3 species/year after 11 years. Conclusions: The composition of the herb layer varied substantially in the study period and showed a marked year-to-year variation even in the forest interior, where light conditions were relatively stable. A proper estimation of the interannual variability of vegetation, while crucial to benchmark the effects of disturbance in forests, should account for the confounding effect of pseudoturnover
Physics informed neural networks for solving inverse thermal wave coupled boundary-value problems
Full text linkAs one of the essential parameters in thermophysical analysis, effective measurement of thermal diffusivity is necessary. This paper utilizes the Physics-Informed Neural Networks (PINN) framework to simulate the diffusion of thermal waves. The governing equations / boundary-value problem (BVP) for the thermal waves are expressed in a coupled partial differential form, derived using the method of separation of variables. The inverse problem associated with the coupled partial differential equations is solved using a dimensionless equation / BVP with a loss function that incorporates physical information. Even in the presence of experimental system errors, the neural network (NN) method introduced in this work (“new NN method”) was shown to be capable of robustly solving the thermal wave inverse problem without nonlinear DC components at different spatial locations, for determining the unknown thermal diffusivity of green (unsintered) metal powder compact materials. The results indicate that the coupled partial differential equations for the amplitude and phase of thermal waves within the PINN framework represent a promising strategy for determining thermophysical parameters
Il dramma del cambiamento, il cambiamento del dramma. Per una storia del teatro greco del IV secolo a. C.
No full textThe article carries out a panoramic analysis of the evolution of Greek
theater between the 4th century B.C. and the early Hellenistic age, with focus
on the process that led it from the local dimension of the Athenian milieu to a
broader one first as a form of entertainment spread throughout the Greek world
and later, during the conquests of Alexander and the formation of the Hellenistic
kingdoms, as an instrument of Hellenization and cultural integration of other
populations. Particular attention is given to the progressive renewal of traditional
genres and their contaminations, in relation to the new functions assumed
by the theater and the social diversification of the audience for which it was
intended
Effect of CFTR modulators on glucose homeostasis in children and young adults with cystic fibrosis-related diabetes: a systematic review
Full text linkIntroduction: Cystic fibrosis (CF) is an autosomal recessive disorder caused by mutations in the CFTR gene, leading to impaired chloride transport, thickened mucus, and multiorgan dysfunction. Among its complications, cystic fibrosis-related diabetes (CFRD) is a major concern, characterized by progressive b-cell dysfunction and insulin deficiency. The advent of CFTR modulators, including ivacaftor, lumacaftor/ivacaftor, and elexacaftor/tezacaftor/ivacaftor (ETI), has revolutionized CF management by improving pulmonary function, nutritional status, and overall survival. However, their effects on glucose metabolism remain under investigation. Methods: This systematic review (systematic review registration: PROSPERO 2025 CRD420251021499) analyzes recent evidence on the impact of CFTR modulators on CFRD in children and young adults. Results: Ivacaftor demonstrates potential benefits in glucose regulation, enhancing insulin secretion and glucagon control, particularly in patients with gating mutations. Conversely, lumacaftor/ivacaftor exhibits inconsistent effects, with some studies indicating glucose tolerance improvements while others report insulin sensitivity decline. Discussion: ETI therapy shows modest but generally positive effects on glycemic control, with reductions in HbA1c and fasting glucose, though without significant changes in insulin secretion. While CFTR modulators improve systemic health, their role in directly preventing or reversing CFRD remains unclear. Further longitudinal studies are needed to optimize therapeutic strategies and elucidate the long-term metabolic effects of CFTR modulation in CF patients. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD420251021499
Supervised Learning Approach for Intrusion Detection in Unbalanced Network Traffic
Full text linkIntrusion detection systems (IDS) serve as critical sentinels in network security, assuming a paramount role in identifying and mitigating potential threats. With the evolution of our digital landscape, robust and productive intrusion detection mechanisms have become increasingly imperative. The significance of IDS lies in their ability to safeguard network resources’ integrity, confidentiality, and availability. In an era where cyber threats constantly evolve in complexity and scale, IDS serves as the front line of defence, tirelessly monitoring network traffic to pinpoint suspicious activities and mitigate potential security breaches. To address the class imbalance problem, the Synthetic Minority Over-sampling Technique (SMOTE) was applied to pre-process the CIC-IDS 2017 and NSL-KDD 2009 datasets. Advanced machine learning technique is harnessed to enhance IDS capabilities, specifically through utilising Support Vector Machines (SVM) for subsequent classification tasks. The experimental outcomes on both datasets unveil exceptional accuracy of 99% and performance across multiple intrusion types, underscoring the effectiveness of our SVM-based approach in strengthening IDS