90,704 research outputs found
A note on the author citation and typification of Cineraria aurantiaca Hoppe (Tephroseris integrifolia subsp. aurantiaca; Asteraceae)
No full textBartolucci, Fabrizio, Villani, Mariacristina, Galasso, Gabriele (2021): A note on the author citation and typification of Cineraria aurantiaca Hoppe (Tephroseris integrifolia subsp. aurantiaca; Asteraceae). Phytotaxa 512 (4): 297-299, DOI: 10.11646/phytotaxa.512.4.6, URL: http://dx.doi.org/10.11646/phytotaxa.512.4.
Equity and Inclusivity in European National Standardised Assessment: A context Analysis
No full textAbstract Large-scale standardised assessments can exclude certain groups of
students at various stages, from the test’s design to the analysis of its results.
Students with disabilities, for example, may find it challenging to access the test
due to the design or technological barriers, leading to their exclusion (Hickey,
2015). Additionally, biased or stereotyped analyses, such as the belief that girls
are inherently worse at math, can exclude certain students (Villani & Carbone,
2020). The impact of these exclusion mechanisms can have significant implications for students’ learning paths and the entire school system. Over the past
twenty years, there have been efforts to make large-scale standardised assessments more inclusive (Cawthon & Shyyan, 2022; Hickey, 2015). According to
Cawthon and Shyyan (2022), strategies for addressing assessment accessibility
aim to balance equity in testing experiences while maintaining standardised test
designs. However, this balance raises questions about what is measured and the
various methods available to demonstrate an understanding of that construct
L???adeguamento del patrimonio infrastrutturale esistente
No full textIl nostro Paese ha un'orografia complessa ed è caratterizzato da un sistema insediativo
composto per lo più da città di medie dimensioni, da
paesi e da borghi, formatosi in un territorio prealpino,
appenninico, e comunque collinare come nelle Isole
maggiori, tutti accomunati dalla presenza di emergenze
storico-ambientali, testimonianza di una storia
plurisecolare. A questo dato territoriale, corrisponde un
patrimonio stradale costituito, solo nella misura del 4%
(circa 7.000 km), da strade a carreggiate separate,
assimilabili al tipo autostradale, e quindi
prevalentemente composto da strade a carreggiata
unica, appartenenti a differenti Enti ed Amministrazioni,
spesso inadeguate in termini di sicurezza della
circolazione
All-inkjet-printed thin-film transistors: Manufacturing process reliability by root cause analysis
No full textWe report on the detailed electrical investigation of all-inkjet-printed thin-film transistor (TFT) arrays focusing on TFT failures and their origins. The TFT arrays were manufactured on flexible polymer substrates in ambient condition without the need for cleanroom environment or inert atmosphere and at a maximum temperature of 150 °C. Alternative manufacturing processes for electronic devices such as inkjet printing suffer from lower accuracy compared to traditional microelectronic manufacturing methods. Furthermore, usually printing methods do not allow the manufacturing of electronic devices with high yield (high number of functional devices). In general, the manufacturing yield is much lower compared to the established conventional manufacturing methods based on lithography. Thus, the focus of this contribution is set on a comprehensive analysis of defective TFTs printed by inkjet technology. Based on root cause analysis, we present the defects by developing failure categories and discuss the reasons for the defects. This procedure identifies failure origins and allows the optimization of the manufacturing resulting finally to a yield improvement. © The Author(s) 2016
Fault diagnosis for industrial robots
No full textIn the last decade considerable research efforts have been spent to seek for systematic approaches to Fault Diagnosis (FD) in dynamical systems. Special attention has been put in robotic systems, especially for those operating in remote or hazardous environments, where a high degree of safety as well as self-diagnostics capabilities are required. On the other hand, the development of effective strategies of fault diagnosis for robot manipulators operating in an industrial context is a critical research task. Several FD techniques for robot manipulators have been proposed in the literature, although the problem of their application to industrial robots has not been extensively investigated. In this chapter different discretetime observer-based approaches to FD for mechanical manipulators are presented and critically compared. First, a rough FD technique is considered, which is based solely on the prediction capabilities of the manipulator dynamic model. Next, an observer-based technique is presented, where a robust time-delayed compensation is introduced to cope with disturbances and modeling uncertainties. Finally, two different observer-based schemes are developed, where the uncertain terms in the model are dynamically estimated: the first scheme is based on the recursive estimation of the uncertain terms, while the second one adaptively estimates the parameters of a suitable parametric model of the uncertainties. All the considered schemes are experimentally tested on a six-degree-of-freedom industrial robot and the performance are critically compared each other
«La luce volatile» di Napoli e i «paesi dell’anima»
No full textStilemi ed emblemi del paesaggio nella narrativa di Pomili
Characterization and applications in seconds time scale of new totally porous sub-2micron CSPs: brush-type and macrocyclic selectors.
No full textOver the last ten years, the technological progress has led to the development of stationary phases on ever smaller silica particles and instruments (UHPLC/UHPSFC) with a reduced extra-column volume able to reach very high pressure. These innovations allow higher efficiencies, resolutions and permit to reduce the analysis time and the eluent consumption. For these reasons also chiral stationary phases (CSPs) are moving to sub-2μm particles diameter. This talk concerns the development of two different sub-2μm CSPs based on the WhelkO-1[1] and on the teicoplanin selectors[2]. The first selector was covalently bonded on fully porous 1.8 μm Kromasil and the second one on totally porous and monodispersed 1.9 μm Titan silica particles. Both CSPs were packed in columns with an I.D. of 4.6 mm and different lengths, from 10 cm down to 1 cm, the latter geometry permitting very short analysis time. The UHPLC columns packed with the WhelkO-1-CSP were evaluated using normal phase and supercritical fluid eluents. Kinetic performances were estimated using trans-stilbene oxide as a probe, and resulted in efficiencies up to 250’000 plates/m under normal phase conditions. To evaluate the thermodynamic performances a large library screening[3] was performed under sub-critical fluid conditions: in one working day, 81 out of 129 randomly collected racemates were resolved under identical eluting conditions. The new UHPC-Titan120-Chirobiotic-TZWIT-1.9 showed a broad field of application in different environments (reversed phase, polar organic mode, HILIC, sub-critical fluid and normal phase). The thermodynamic performances of the new TEICO-Titan 1.9 μm have been evaluated with several N-protected amino acids, aryloxy acids, pharmaceutical compounds, sulfoxides and phosphine oxides. This CSP frequently showed high enantio-selectivity values: downsizing in column length, from 10-cm down to 1-cm was easily possible maintain high efficiency obtaining baseline separations and providing a considerable reduction of the analysis time. Ultra-fast enantiomeric separations in less than 60 seconds could get a routine in the chiral screening methods.
References
[1] D. Kotoni, A. Ciogli, C. Molinaro, I. D’Acquarica, J. Kocergin, T. Szczerb, H. Ritchie, C. Villani, F. Gasparrini, Anal. Chem., 84 (2012), 6805
[2] Berthod A., Chen X., Kullman J.P., Armstrong D.W., Gasparrini F., D’Acquarica I., Villani C., Carotti A., Anal. Chem. 72 (2000) 1767-1780;
[3] L. Sciascera, O. Ismail, A. Ciogli, D. Kotoni, A. Cavazzini, L. Botta, T. Szczerba, J. Kocergin, C. Villani, F. Gasparrini, JCA, 1383 (2015) 160–16
Plasma functionalization procedure for antibody immobilization for SU-8 based sensor
No full textIn this paper, we report the study on a new protocol for the immobilization process of antigen/antibody assay on SU-8 layers by oxygen plasma treatment. Plasma treatments, at different plasma powers and for different duration times, are performed and their effects on immobilization efficiency are studied. The chemical properties and the surface morphology of SU-8 before and after the functionalization and immobilization of (IgG) are then verified by Raman spectroscopy and atomic force microscopy (AFM). An increase of the surface roughness of SU-8 layers is observed after the oxygen plasma treatment and an intensity variation of functional groups is also evidenced. To demonstrate the validity of the process the distribution of IgG immobilized on SU-8 surfaces is detected by fluorescence microscopy measurement after incubation with fluorescein isothiocyanate (FITC)-tagged anti-human IgG. An increase of the amount of the adsorbed protein of about 20% and a good repeatability on antigen/antibody distribution on the surface are detected for IgG on plasma treated substrates. Finally, label free measurements are performed by SU-8 optical ring resonators reaching detection limits of 0.86 ng cm−2. The proposed approach offers a smart protocol for IgG immobilization on SU-8 substrate that can be easily extended to different antigen/antibody assay and polymeric materials for the realization of high performance immunosensors. © 2016 Elsevier B.V
Up-scaling of the manufacturing of all-inkjet-printed organic thin-film transistors: Device performance and manufacturing yield of transistor arrays
No full textAll-inkjet-printed thin-film transistors (TFTs) have been demonstrated in literature using mainly laboratory inkjet equipment, simple one-channel layout and only a low number of manufactured TFT devices. We report on the development and the up-scaling of the manufacturing of all-inkjet-printed TFT arrays using industrial inkjet equipment. The manufacturing of the TFTs was carried out in ambient condition without the need for cleanroom environments or inert atmospheres and at a maximum temperature of 150°C enabling the use of flexible polymer films as substrate. Arrays of 924 TFTs were manufactured on an area of about DIN A4 (297 × 420 mm2). This allows the consideration of statistics, e.g. to determine the process yield as a function of device design and layout. We present process yields for all-inkjet-printed TTFs up to 82% demonstrating the potential of the developed all-inkjet-printing process. © 2015 Elsevier B.V. All rights reserved
Unveiling healthcare data archiving: Exploring the role of artificial intelligence in medical image analysis
No full textGli archivi sanitari digitali possono essere considerati dei moderni database progettati per immagazzinare e gestire ingenti quantità di informazioni mediche, dalle cartelle cliniche dei pazienti, a studi clinici fino alle immagini mediche e a dati genomici. I dati strutturati e non strutturati che compongono gli archivi sanitari sono oggetto di scrupolose e rigorose procedure di validazione per garantire accuratezza, affidabilità e standardizzazione a fini clinici e di ricerca.
Nel contesto di un settore sanitario in continua e rapida evoluzione, l’intelligenza artificiale (IA) si propone come una forza trasformativa, capace di riformare gli archivi sanitari digitali migliorando la gestione, l’analisi e il recupero di vasti set di dati clinici, al fine di ottenere decisioni cliniche più informate e ripetibili, interventi tempestivi e risultati migliorati per i pazienti.
Tra i diversi dati archiviati, la gestione e l’analisi delle immagini mediche in archivi digitali presentano numerose sfide dovute all’eterogeneità dei dati, alla variabilità della qualità delle immagini, nonché alla mancanza di annotazioni. L’impiego di soluzioni basate sull’IA può aiutare a risolvere efficacemente queste problematiche, migliorando l’accuratezza dell’analisi delle immagini, standardizzando la qualità dei dati e facilitando la generazione di annotazioni dettagliate.
Questa tesi ha lo scopo di utilizzare algoritmi di IA per l’analisi di immagini mediche depositate in archivi sanitari digitali. Il presente lavoro propone di indagare varie tecniche di imaging medico, ognuna delle quali è caratterizzata da uno specifico dominio di applicazione e presenta quindi un insieme unico di sfide, requisiti e potenziali esiti. In particolare, in questo lavoro di tesi sarà oggetto di approfondimento l’assistenza diagnostica degli algoritmi di IA per tre diverse tecniche di imaging, in specifici scenari clinici:
i) Immagini endoscopiche ottenute durante esami di laringoscopia; ciò include un’esplorazione approfondita di tecniche come la detection di keypoints per la stima della motilità delle corde vocali e la segmentazione di tumori del tratto aerodigestivo superiore;
ii) Immagini di risonanza magnetica per la segmentazione dei dischi intervertebrali, per la diagnosi e il trattamento di malattie spinali, così come per lo svolgimento di interventi chirurgici guidati da immagini;
iii) Immagini ecografiche in ambito reumatologico, per la valutazione della sindrome del tunnel carpale attraverso la segmentazione del nervo mediano.
Le metodologie esposte in questo lavoro evidenziano l’efficacia degli algoritmi di IA nell’analizzare immagini mediche archiviate. I progressi metodologici ottenuti sottolineano il notevole potenziale dell’IA nel rivelare informazioni implicitamente presenti negli archivi sanitari digitali.Medical digital archives can be seen as contemporary databases designed to store and manage vast amounts of medical information, from patient records and clinical studies to medical images and genomics data. The structured and unstructured data that compose the archives undergo rigorous curation processes, to ensure their accuracy, reliability, and standardization for clinical and research purposes.
In the rapidly evolving field of healthcare, artificial intelligence (AI) is emerging as a transformative force, able to reform medical digital archives improving the management, analysis, and retrieval of vast clinical datasets, and ultimately leading to more informed decisions, timely interventions, and improved patient outcomes. Specifically, managing medical images in digital archives poses numerous challenges such as data heterogeneity, image quality variability and lack of annotations, that can be addressed with AI solutions.
This thesis aims to exploit AI algorithms for the analysis of medical images stored in digital archives. This work investigates various medical imaging techniques, each of which is characterized by a specific application domain and consequently presents a unique set of challenges, requirements, and potential outcomes. In particular, it delves into AI diagnostic assistance for three critical imaging techniques in specific clinical scenarios:
i) Endoscopic imaging obtained during laryngoscopy examinations; this includes in-depth exploration of techniques such as keypoint detection for vocal fold motility estimation and upper aerodigestive tract cancer segmentation;
ii) Magnetic resonance imaging for intervertebral disc segmentation, for the diagnosis and treatment of spinal conditions and diseases, as well as image-guided interventions;
iii) Ultrasound imaging in rheumatology, for carpal tunnel syndrome evaluation through median nerve segmentation.
The methodologies presented in this work demonstrate the feasibility of using AI algorithms for the analysis of archived medical images, and the achieved methodological advances highlight the potential of AI-based algorithms in extracting useful information implicitly contained in digital archives
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