1,354,510 research outputs found
Short Films: Imposter
No full textA film by Catherine Gerbasi, Lexi Kakis and Dana Hillard. Edited by Catherine Gerbasi
El mundo lírico de Vicente Gerbasi
No full textTesis de la Universidad Complutense de Madrid, Facultad de Filología, 1997Análisis de las tres obras fundamentales del poeta venezolano Vicente Gerbasi, atendiendo a los principales motivos que en ella se desarrollan. Análisis de su teoría poética aplicada a su proceso de creaciónFac. de FilologíaTRUEpu
AI-based medical image analysis and interpretation: from feature extraction to decision support
No full textNegli ultimi anni, abbiamo assistito a un'enorme diffusione di modelli di Intelligenza Artificiale (IA) ad elevate prestazioni che affrontano diverse sfide nel campo della visione artificiale in ambito biomedico. Tuttavia, l'integrazione clinica di queste tecnologie è ancora limitata a causa di sfide come la scarsità di dati e la necessità di risultati interpretabili. La tesi propone la creazione di pipeline automatizzate per l'analisi di immagini cliniche utilizzando l'IA, con tre casi studio in ambito oncologico, cardiologico e neurologico. Le pipeline mirano a performance elevate, garantendo allo stesso tempo riproducibilità, interpretabilità e facilità di generalizzazione. I primi due casi riguardano sistemi per migliorare l'efficienza diagnostica nello screening di microcalcificazioni mammarie maligne e malattie coronariche, rispettivamente. Nel terzo caso, viene presentato un workflow per la predizione della prognosi e l’identificazione di nuovi biomarcatori utilizzando sequenze di risonanza magnetica di pazienti con ictus ischemico acuto. Infine, viene approfondito il tema dell'impiego di modelli generalisti o “fondativi" che sta gradualmente cambiando il panorama dell'IA. Nel dominio medico, questo approccio promette di superare limitazioni comuni, in particolare quelle legate alla quantità e qualità dei dati. Viene presentato uno studio di validazione disegnato per testare l'adattamento di un algoritmo di segmentazione progettato per un uso generale su un set di dati reale di pazienti con ictus emorragico. Le alte prestazioni ottenute da tale sistema mostrano come questo nuovo approccio sia facile da implementare e possa quindi accelerare il processo di segmentazione manuale dell'ematoma dalla TAC di pronto soccorso. Se, da un lato, questo dimostra il grande potenziale dell'approccio generalista, è anche innegabile che diverse sfide, in particolare legate alla sfera medico-legale ed etica, devono essere affrontate tempestivamente per garantire la sicurezza di tali software al fine di arrivare a migliorare l'accessibilità, l'equità e l'inclusività nell'assistenza sanitaria.Over the past few years, we have witnessed an explosion of highly performing Artificial Intelligence (AI) models addressing diverse tasks in computer vision within the healthcare domain. However, their integration into everyday clinical practice remains limited. The field of AI-based medical image analysis faces multiple challenges, including a scarcity of data, variable image quality, and the imperative for interpretable and generalizable results. Conversely, the potential benefits of employing such technology in routine clinical practice are extensive. These include the possibility of seamlessly incorporating fully automated decision support systems at different stages of the clinical routine, ranging from early diagnosis to prognosis prediction. This thesis aims to delineate a comprehensive workflow for building fully automated and easy to customize AI-based medical image analysis pipelines. Three distinct case studies, designed and analyzed in collaboration with highly specialized European centers, are presented. Each case pertains to a specific medical domain - oncological, cardiological, or neurological - presenting unique challenges from both clinical and technical perspectives. The proposed pipelines are crafted to meet specific criteria: high performance, reproducibility, ease of generalization, and interpretability by the final clinical user, who must view the system as trustworthy, even without expertise in the technical implementation. Additionally, the applications have been meticulously designed to demand limited computational resources while maintaining optimal performance. The first two case studies present fully automated systems designed to enhance the efficiency and diagnostic accuracy during screening programs. The first system accurately identifies malignant microcalcifications from mammograms during breast screening programs to mitigate the high false positive rate. In the second case, a quick and accurate automated system is introduced to rule out patients requiring further clinical investigations during coronary artery disease screenings, based on the degree of occlusion of the three main coronary arteries visible from cardiac CT angiography. These pipelines are specifically crafted to alleviate time-consuming and operator-dependent tasks. In the last case study, an easily generalizable workflow for prognosis prediction and biomarkers discovery is discussed. The presented pipeline is capable of identifying novel imaging biomarkers from follow-up MRI sequences with the objective of predicting poor long-term functional outcomes in acute ischemic stroke patients. This kind of system has the potential to fully exploit the information content in routinely acquired clinical images, providing insights into the pathophysiological mechanisms of the disease and predicting its possible evolution. This goes beyond qualitative biomarkers or simple lesion measurements, which are often the only indicators used to guide the best clinical intervention. Finally, the recent emergence of generalist foundation models that are gradually shifting the landscape of AI is deeply discussed. In the medical domain, this approach holds significant promise in overcoming common limitations, particularly those related to data quantity and quality. An evaluation study designed to test the adaptation of a general-purpose segmentation algorithm on a real dataset of patients with hemorrhagic ictus is presented. The high performance of the implemented system showcases a novel and easy-to-implement approach for expediting the manual hematoma delineation process from CT scans acquired in emergency rooms. If, on the one hand, this demonstrates the great potential of the generalist approach, it is also undeniable that various concerns, particularly from legal and ethical perspectives, must be promptly addressed to ensure the safety of the final supporting tools improving healthcare accessibility, fairness, and inclusivity
T.A.R.A.N.T.O. project: supported TiO2 MOCVD thin films and doped TiO2 powders for photocatalytic water remediation
No full textT.A.R.A.N.TO research project (PON, ARS01_00637) aims to develop technologies suitable to generate
renewable energy and the remediation of the polluted environmental compartments, thus favouring circular
economy and decarbonisation practices. The proposed technologies intend to promote the transformation
of wastes in renewable energy sources. ICMATE role is focused on the fabrication of supported
photocatalysts based on TiO2, both as thin films (anatase, MOCVD coatings [2]) on stainless steel micrometric
nets and over-grafted modified TiO2 nano-micro-powder (in anatase-rutile form [2]), Fig.1. This approach
makes the whole support photo-active, thanks to the net MOCVD functionalisation and takes advantage from
to the synergic action of the grafted powder, joined to a simplified catalyst management (easiness in
placement-recovering)
Exploitation of Atomic Layer Deposition (ALD) technique for the synthesis of inorganic nanostructured thin films
No full textAtomic Layer Deposition (ALD), belonging to Chemical Vapor Deposition (CVD) techniques, is an attractive
process for the manufacturing of nanostructured thin films, with thickness down to a fraction of a monolayer.
It is a powerful and unique technique that has achieved a lot of interest: it allows the deposition of high
quality thin films with atomic level control and high conformal coverage even on complex shaped surfaces
[1]. The advantages of ALD method include low impurity content, pinhole-free deposition, and low processing
temperature (LT-ALD), so permitting the employment of temperature-sensitive substrates [2]. The basics of
the technique and an overview of its potentiality are here presented
Influence of substrate on structural properties of TiO2 thin films obtained via MOCVD
No full textAmong the techniques developed for depositing thin films, metal-organic chemical vapor deposition is one of the most promising. In the present work, the deposition of TiO2 thin films on stainless steel, titanium, barium borosilicate glass and alumina substrates, using titanium tetraisopropoxide as a precursor, was investigated. The films were deposited at 420 °C. The resulting film phase, checked by X-ray powder diffraction, was found to be polycrystalline anatase and was oriented with the a axis perpendicular to the substrate surface, except for alumina substrates where titania films were randomly oriented. Some considerations on texture and crystallite size as a function of film thickness are reported. Annealing up to 1100 °C induced the complete anatase-rutile transformation on alumina substrates
The crystal structure of α-TiCl3 and the reticular disorder introduced by ball-milling
No full textBy X-ray powder diffraction methods the crystal structures of α-TiCl3 and of the products obtained by dry ball-milling activation of this form were studied. TiCl3 microcrystals show initially a structural disorder in the positions of titanium atoms and the successive mechanical activation introduces into the structure some stacking faults, mainly associated to ±60° rotations of the triple layers Cl[BOND]Ti[BOND]Cl. The structural investigation has been carried out by an accurate fit of observed X-ray patterns to those calculated in correspondence of structures containing well-defined disordered sequences and of likewise well-defined crystallite sizes. Like γ-TiCl3 and MgCl2, α-TiCl3 is very sensitive to mechanical activation, which improves the performances of these three compounds when they are employed as catalysts, or supports for catalysts, in Ziegler-Natta polymerization processes
Trust in online customer-firm interaction: a literature review and directions for research
No full textTrust is a key element in developing customer-firm relationships in virtual marketplace. The peculiarities of the online settings, however, threaten firms' capability to exploit opportunities derived from such environments. This can lead to customers mostly using the online setting as an information source rather than as a place to conduct transactions. Trust is a key antecedent of online transactions. In this chapter, the authors focus on trust's role in the virtual marketplace by reviewing a series of relevant studies and proposing directions for future research
Un dispositivo per l'indagine strutturale mediante diffrazione dei raggi x di campioni policristallini che si deteriorano all'aria
No full text- …
