Archivio della ricerca della Scuola Superiore Sant'Anna
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Patent opposition, IP firm capabilities, and technology entry: empirical evidence from European patent data
No full textENOTRIA Dataset
No full textENOTRIA is a dataset of around 2.8 M images extracted from the game "Enotria: The Last Song" for designing and developing machine learning algorithms for research purposes. The dataset can be downloaded on Zenodo at the following link: https://zenodo.org/records/14288178
Photocatalytic dye removal with ZnO/Laser-Induced graphene nanocomposite
Full text linkZnO has been deposited on Laser Induced Graphene (LIG) by Atomic Layer Deposition (ALD) running up to 100, 200 and 400 number of cycles. Two different LIG substrates have been used, which differed by their porosity degree. The ALD technique allows to grow ZnO stoichiometrically on the chosen substrates down to the bottom of the pores of the material, guaranteeing an increasing coverage with increasing number of deposition cycles. The crystallinity of the deposited ZnO is also proven via XRD analysis. The photocatalytic activity of the ZnO@LIG nanocomposites has been evaluated through monitoring the discoloration of a 10-5 M methylene blue (MB) solution upon UV irradiation (λ = 365 nm) over a time span of 120 min. Results indicate that the photocatalytic performance of the nanocomposites increases with the ZnO deposition time. For nanocomposites showing the higher ZnO coverage degree, after 120 min of irradiation a net MB photodegradation percentage of 71 ± 4 % and 69 ± 4 % is reached respectively for the less porous and more porous substrate. Conversely, the MB adsorption percentage of the samples decreases upon ZnO deposition, due to the reduced accessible porosity and the hydrophobicity of the nanocomposites. The method used to produce such solid supported nanocomposites is straightforward and represents a valuable option to obtain efficient environmental-friendly photoactive materials
Design and Validation of a Tripping-Eliciting Platform Based on Compliant Random Obstacles
Full text linkGoal: The experimental study of the stumble phenomena is essential to develop novel technological solutions to limit harmful effects in at-risk populations. A versatile platform to deliver realistic and unanticipated tripping perturbations, controllable in their strength and timing, would be beneficial for this field of study. Methods: We built a modular tripping-eliciting system based on multiple compliant trip blocks that deliver unanticipated tripping perturbations. The system was validated with a study with 9 healthy subjects. Results: The system delivered 33 out of 34 perturbations (a minimum of 3 per subject) during the desired gait phase, and 31 effectively induced a tripping event. The recovery strategies adopted after the perturbations were qualitatively consistent with the literature. The analysis of the inertial motion unit signals and the questionnaires suggests a limited adaptation to the perturbation throughout experiments. Conclusions: The platform succeeded in providing realistic trip perturbations, concurrently limiting subjects' adaptation. The presence of multiple compliant obstacles, tunable regarding position and perturbation strength, represents a novelty in the field, allowing the study of stumbling phenomena caused by obstacles with different levels of sturdiness. The overall system is modular and can be easily adapted for different application
Dallo sviluppo sostenibile ai sistemi alimentari sostenibili negli accordi di libero scambio dell'Unione europea
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Impaired HDL Cholesterol Function and High Interleukin-1ß Levels Hold Prognostic Value after ST-elevation Myocardial Infarction
Full text linkGlobal, Regional, and National Burden of Nontraumatic Subarachnoid Hemorrhage
Full text linkImportance: Nontraumatic subarachnoid hemorrhage (SAH) represents the third most common stroke type with unique etiologies, risk factors, diagnostics, and treatments. Nevertheless, epidemiological studies often cluster SAH with other stroke types leaving its distinct burden estimates obscure. Objective: To estimate the worldwide burden of SAH. Design, setting, and participants: Based on the repeated cross-sectional Global Burden of Disease (GBD) 2021 study, the global burden of SAH in 1990 to 2021 was estimated. Moreover, the SAH burden was compared with other diseases, and its associations with 14 individual risk factors were investigated with available data in the GBD 2021 study. The GBD study included the burden estimates of nontraumatic SAH among all ages in 204 countries and territories between 1990 and 2021. Exposures: SAH and 14 modifiable risk factors. Main outcomes and measures: Absolute numbers and age-standardized rates with 95% uncertainty intervals (UIs) of SAH incidence, prevalence, mortality, and disability-adjusted life-years (DALYs) as well as risk factor-specific population attributable fractions (PAFs). Results: In 2021, the global age-standardized SAH incidence was 8.3 (95% UI, 7.3-9.5), prevalence was 92.2 (95% UI, 84.1-100.6), mortality was 4.2 (95% UI, 3.7-4.8), and DALY rate was 125.2 (95% UI, 110.5-142.6) per 100 000 people. The highest burden estimates were found in Latin America, the Caribbean, Oceania, and high-income Asia Pacific. Although the absolute number of SAH cases increased, especially in regions with a low sociodemographic index, all age-standardized burden rates decreased between 1990 and 2021: the incidence by 28.8% (95% UI, 25.7%-31.6%), prevalence by 16.1% (95% UI, 14.8%-17.7%), mortality by 56.1% (95% UI, 40.7%-64.3%), and DALY rate by 54.6% (95% UI, 42.8%-61.9%). Of 300 diseases, SAH ranked as the 36th most common cause of death and 59th most common cause of DALY in the world. Of all worldwide SAH-related DALYs, 71.6% (95% UI, 63.8%-78.6%) were associated with the 14 modeled risk factors of which high systolic blood pressure (population attributable fraction [PAF] = 51.6%; 95% UI, 38.0%-62.6%) and smoking (PAF = 14.4%; 95% UI, 12.4%-16.5%) had the highest attribution. Conclusions and relevance: Although the global age-standardized burden rates of SAH more than halved over the last 3 decades, SAH remained one of the most common cardiovascular and neurological causes of death and disabilities in the world, with increasing absolute case numbers. These findings suggest evidence for the potential health benefits of proactive public health planning and resource allocation toward the prevention of SAH
Fast, Robust, and Learned Distribution-Based Sorting
Full text linkDespite a long history of research and achievements in designing sorting routines, new hardware features and application requirements pose advanced challenges that computer scientists are recently tackling through novel data-aware (learned) algorithms. This paper aims to better understand the strengths and limitations of learned sorters for numerical data, by addressing two main research and engineering questions: (Q1) Which is the best trade-off, in sorting items, between the efficacy of a ‘‘learned’’ model in approximating the distribution of the input data and its time-space complexity? and (Q2) Which algorithmic structure for distribution-based sorting is suited to leverage a learned model in order to achieve state-of-the-art performance?
To answer Q1, we implement a variant of the best-known learned model (i.e.,
the two-layers RMI) and, also, design a fully new learned model that turns out to be space-time efficient and efficacious in approximating adversarial input distributions. We experimentally test them over 11 datasets of 200M and 800M 64-bit floating-point items, thus offering a comprehensive answer to Q1. We then address Q2 by plugging the best-learned models from above into a distribution-based sorting scheme that leads to three new sorters whose performance is tested over 33 datasets (real and synthetic) of sizes up to 800M items.
Our experimental results will show that our sorters perform better than 6 (classic and learned) best-known sorters on 29 out of those 33 datasets, thus achieving new state-of-the-art tradeoffs