Hot wire manufacturing and resolution effects in high Reynolds number flows

Lo studio della turbolenza è di fondamentale importanza non solo per la fluidodinamica teorica ma anche perchè viene riscontrata in una moltitudine di problemi di interesse ingegneristico. All'aumentare del numero di Reynolds, le scale caratteristiche tendono a ridurre le loro dimensioni assolute. Nella fluidodinamica sperimentale già da lungo tempo si è affermata l'anemometria a filo caldo, grazie ad ottime caratteristiche di risoluzione spaziale e temporale. Questa tecnica, caratterizzata da un basso costo e da una relativa semplicità, rende possibile la realizzazione di sensori di tipo artigianale, che hanno il vantaggio di poter essere relizzati in dimensioni inferiori. Nonostante l'ottima risoluzione spaziale degli hot-wire, infatti, si può verificare, ad alto numero di Reynolds, che le dimensioni dell'elemento sensibile siano superiori a quelle delle piccole scale. Questo impedisce al sensore di risolvere correttamente le strutture più piccole. Per questa tesi di laurea è stato allestito un laboratorio per la costruzione di sensori a filo caldo con filo di platino. Sono in questo modo stati realizzati diversi sensori dalle dimensioni caratteristiche inferiori a quelle dei sensori disponibili commercialmente. I sensori ottenuti sono quindi stati testati in un getto turbolento, dapprima confrontandone la risposta con un sensore di tipo commerciale, per verificarne il corretto funzionamento. In seguito si sono eseguite misure più specifiche e limitate ad alcune particolari zone all'interno del campo di moto, dove è probabile riscontrare effetti di risoluzione spaziale. Sono stati analizzati gli effetti della dimensione fisica del sensore sui momenti statistici centrali, sugli spettri di velocità e sulle funzioni di densità di probabilità.

A numerical study of temperature effects on hot wire measurements inside turbulent channel flows

A way to investigate turbulence is through experiments where hot wire measurements are performed. Analysis of the in turbulence of a temperature gradient on hot wire measurements is the aim of this thesis work. Actually - to author's knowledge - this investigation is the first attempt to document, understand and ultimately correct the effect of temperature gradients on turbulence statistics. However a numerical approach is used since instantaneous temperature and streamwise velocity fields are required to evaluate this effect. A channel flow simulation at Re_tau = 180 is analyzed to make a first evaluation of the amount of error introduced by temperature gradient inside the domain. Hot wire data field is obtained processing the numerical flow field through the application of a proper version of the King's law, which connect voltage, velocity and temperature. A drift in mean streamwise velocity profile and rms is observed when temperature correction is performed by means of centerline temperature. A correct mean velocity pro�le is achieved correcting temperature through its mean value at each wall normal position, but a not negligible error is still present into rms. The key point to correct properly the sensed velocity from the hot wire is the knowledge of the instantaneous temperature field. For this purpose three correction methods are proposed. At the end a numerical simulation at Re_tau =590 is also evaluated in order to confirm the results discussed earlier.

Automated Segmentation and Non-Rigid Registration for the Quantitative Evaluation of Myocardial Perfusion from Magnetic Resonance Images

Myocardial perfusion quantification by means of Contrast-Enhanced Cardiac Magnetic Resonance images relies on time consuming frame-by-frame manual tracing of regions of interest. In this Thesis, a novel automated technique for myocardial segmentation and non-rigid registration as a basis for perfusion quantification is presented. The proposed technique is based on three steps: reference frame selection, myocardial segmentation and non-rigid registration. In the first step, the reference frame in which both endo- and epicardial segmentation will be performed is chosen. Endocardial segmentation is achieved by means of a statistical region-based level-set technique followed by a curvature-based regularization motion. Epicardial segmentation is achieved by means of an edge-based level-set technique followed again by a regularization motion. To take into account the changes in position, size and shape of myocardium throughout the sequence due to out of plane respiratory motion, a non-rigid registration algorithm is required. The proposed non-rigid registration scheme consists in a novel multiscale extension of the normalized cross-correlation algorithm in combination with level-set methods. The myocardium is then divided into standard segments. Contrast enhancement curves are computed measuring the mean pixel intensity of each segment over time, and perfusion indices are extracted from each curve. The overall approach has been tested on synthetic and real datasets. For validation purposes, the sequences have been manually traced by an experienced interpreter, and contrast enhancement curves as well as perfusion indices have been computed. Comparisons between automatically extracted and manually obtained contours and enhancement curves showed high inter-technique agreement. Comparisons of perfusion indices computed using both approaches against quantitative coronary angiography and visual interpretation demonstrated that the two technique have similar diagnostic accuracy. In conclusion, the proposed technique allows fast, automated and accurate measurement of intra-myocardial contrast dynamics, and may thus address the strong clinical need for quantitative evaluation of myocardial perfusion.

Design and Fabrication of Bond Wire Micro-Magnetics

This thesis presents a new approach for the design and fabrication of bond wire magnetics for power converter applications by using standard IC gold bonding wires and micro-machined magnetic cores. It shows a systematic design and characterization study for bond wire transformers with toroidal and race-track cores for both PCB and silicon substrates. Measurement results show that the use of ferrite cores increases the secondary self-inductance up to 315 µH with a Q-factor up to 24.5 at 100 kHz. Measurement results on LTCC core report an enhancement of the secondary self-inductance up to 23 µH with a Q-factor up to 10.5 at 1.4 MHz. A resonant DC-DC converter is designed in 0.32 µm BCD6s technology at STMicroelectronics with a depletion nmosfet and a bond wire micro-transformer for EH applications. Measures report that the circuit begins to oscillate from a TEG voltage of 280 mV while starts to convert from an input down to 330 mV to a rectified output of 0.8 V at an input of 400 mV. Bond wire magnetics is a cost-effective approach that enables a flexible design of inductors and transformers with high inductance and high turns ratio. Additionally, it supports the development of magnetics on top of the IC active circuitry for package and wafer level integrations, thus enabling the design of high density power components. This makes possible the evolution of PwrSiP and PwrSoC with reliable highly efficient magnetics.

Tecniche per la separazione live di piani di profondita in un flusso video mediante Kinect e una applicazione nell'intrattenimento digitale

Keying e composizione sono da sempre tecniche ampiamente utilizzate in contesti multimediali, quali produzione cinematografica e televisiva; il chroma keying è in particolare la tecnica più popolare, ma presenta una serie di limiti e problematiche. In questo elaborato viene proposta una tecnica alternativa di estrazione, basata sull'uso della profondità, operante in tempo reale e che sfrutta il device Kinect di Microsoft. Sono proposti una serie di algoritmi, basati su tecniche di edge detection, utilizzati per il miglioramento della depth map lungo i bordi di estrazione; viene infine testato il risultato ottenuto dall'implementazione del sistema e proposta una possibile applicazione nell'ambito del teatro multimediale.

Functional dna nanostructures for in vitro biosensing in live cells

DNA is a fascinating biomolecule that is well known for its genetic role in living systems. The emerging area of DNA nanotechnology provides an alternative view that exploits unparallel self-assembly ability of DNA molecules for material use of DNA. Although many reports exist on the results of DNA self-assembling systems, still few of them focus on the in vitro study about the function of such DNA nanostructures in live cells. Due to this, there are still a limited research about the in vitro functionality of such designs. To address an aspect of this issue, we have designed, synthesized and characterized two multifunctional fluorescencent nanobiosensors by DNA self-assembling. Each structure was designed and implemented to be introduced in live cells in order to give information on their functioning in real-time. Computational tools were used in order to design a graphic model of two new DNA motifs and also to obtain the specific sequences to all the ssDNA molecules. By thermal self-assembly techniques we have successfully synthesized the structure and corroborate their formation by the PAGE technique. In addition, we have established the conditions to characterize their structural conformation change when they perform their sensor response. The sensing behavior was also accomplished by fluorescence spectroscopy techniques; FRET evaluation and fluorescence microscopy imaging. Providing the evidence about their adequate sensing performance outside and inside the cells detected in real-time. In a preliminary evaluation we have tried to show the in vitro functionality of our structures in different cancer cell lines with the ability to perform local sensing responses. Our findings suggest that DNA sensor nanostructures could serve as a platform to exploit further therapeutic achievements in live cells.

Effetti della risoluzione spaziale nella stima della dissipazione con sensore hot-wire

L'obiettivo primario di questo elaborato di tesi è quello di stimare l'effetto della risoluzione spaziale e quindi della lunghezza finita del sensore di un anemometro a filo caldo, sul calcolo delle derivate che contribuiscono a valutare la dissipazione.

L'interpretazione a distanza: presentazione della piattaforma veasyt live!, case study italiano e proposta di seminario.

Il presente elaborato offre una panoramica generale del Remote Interpreting (RI) con l'obiettivo di strutturare un ipotetico seminario da tenere alla SLLTI (Scuola di Lingue e Letterature, Traduzione e Interpretazione, ex SSLMIT) di Forlì, in collaborazione con l'azienda VEASYT, spin-off dell’università Ca' Foscari di Venezia, per introdurre l'argomento agli studenti del corso di laurea in Interpretazione di Conferenza. A tal scopo la tesi è stata suddivisa in dieci capitoli, ognuno dei quali analizza una sfaccettatura dell'interpretazione da remoto; la prima parte verte sull'evoluzione storica delle nuove tecnologie nel mondo dell'interpretariato, con particolare attenzione all'introduzione degli impianti per l'interpretazione simultanea e delle Tecnologie dell'Informazione e della Comunicazione (TIC); si presentano inoltre i principali tipi di interpretazione a distanza, seguendo la loro comparsa in ordine cronologico, e i dispositivi necessari per effettuare una sessione di video-interpretazione. Nella seconda parte si descrivono alcuni ambiti di applicazione del RI (RI per non udenti, in ambito giuridico, in ambito medico-sanitario) e si illustra la situazione a livello mondiale passando in rassegna, a titolo di esempio, alcune aziende presenti in Australia, Stati Uniti, Germania, Austria e Gran Bretagna. Nella terza parte si presentano alcuni regolamenti e disposizioni raccomandati da associazioni di categoria e dalle istituzioni europee e si analizzano i principali vantaggi e svantaggi del RI. Nella quarta parte si mettono a confronto le caratteristiche e il tipo di formazione di un interprete che lavora in situ con quelle di un interprete che lavora a distanza, illustrando alcune strategie sviluppate dagli interpreti durante le sessioni di RI. L'ultima parte riguarda l'azienda VEASYT, la quale viene presentata come case study italiano, descrivendo la sua piattaforma per il servizio di interpretariato da remoto e la modalità di reclutamento degli interpreti. In conclusione si trova la proposta di seminario da tenere ipoteticamente alla SLLTI di Forlì, che viene articolata seguendo la successione dei capitoli precedenti.

Atlas-Based Segmentation of Brain Tumor Images Using a Markov Random Field-Based Tumor Growth Model and Non-Rigid Registration

We propose a new and clinically oriented approach to perform atlas-based segmentation of brain tumor images. A mesh-free method is used to model tumor-induced soft tissue deformations in a healthy brain atlas image with subsequent registration of the modified atlas to a pathologic patient image. The atlas is seeded with a tumor position prior and tumor growth simulating the tumor mass effect is performed with the aim of improving the registration accuracy in case of patients with space-occupying lesions. We perform tests on 2D axial slices of five different patient data sets and show that the approach gives good results for the segmentation of white matter, grey matter, cerebrospinal fluid and the tumor.

Automated cement segmentation in vertebroplasty

Vertebroplasty is a minimally invasive procedure with many benefits; however, the procedure is not without risks and potential complications, of which leakage of the cement out of the vertebral body and into the surrounding tissues is one of the most serious. Cement can leak into the spinal canal, venous system, soft tissues, lungs and intradiscal space, causing serious neurological complications, tissue necrosis or pulmonary embolism. We present a method for automatic segmentation and tracking of bone cement during vertebroplasty procedures, as a first step towards developing a warning system to avoid cement leakage outside the vertebral body. We show that by using active contours based on level sets the shape of the injected cement can be accurately detected. The model has been improved for segmentation as proposed in our previous work by including a term that restricts the level set function to the vertebral body. The method has been applied to a set of real intra-operative X-ray images and the results show that the algorithm can successfully detect different shapes with blurred and not well-defined boundaries, where the classical active contours segmentation is not applicable. The method has been positively evaluated by physicians.

Long-term effectiveness of canine-to-canine bonded flexible spiral wire lingual retainers

The flexible spiral wire (FSW) canine-to-canine lingual retainer bonded to all 6 anterior teeth is a frequently used type of mandibular fixed retainer. This study aimed to assess the long-term effectiveness of FSW canine-to-canine lingual retainers in maintaining the alignment of the mandibular anterior teeth after orthodontic treatment.

Fully Automatic Segmentation of Brain Tumor Images using Support Vector Machine Classiffication in Combination with Hierarchical Conditional Random Field Regularization

Delineating brain tumor boundaries from magnetic resonance images is an essential task for the analysis of brain cancer. We propose a fully automatic method for brain tissue segmentation, which combines Support Vector Machine classification using multispectral intensities and textures with subsequent hierarchical regularization based on Conditional Random Fields. The CRF regularization introduces spatial constraints to the powerful SVM classification, which assumes voxels to be independent from their neighbors. The approach first separates healthy and tumor tissue before both regions are subclassified into cerebrospinal fluid, white matter, gray matter and necrotic, active, edema region respectively in a novel hierarchical way. The hierarchical approach adds robustness and speed by allowing to apply different levels of regularization at different stages. The method is fast and tailored to standard clinical acquisition protocols. It was assessed on 10 multispectral patient datasets with results outperforming previous methods in terms of segmentation detail and computation times.

Segmentation of brain tumor images based on atlas-registration combined with a Markov-Random-Field lesion growth model

We present an automatic method to segment brain tissues from volumetric MRI brain tumor images. The method is based on non-rigid registration of an average atlas in combination with a biomechanically justified tumor growth model to simulate soft-tissue deformations caused by the tumor mass-effect. The tumor growth model, which is formulated as a mesh-free Markov Random Field energy minimization problem, ensures correspondence between the atlas and the patient image, prior to the registration step. The method is non-parametric, simple and fast compared to other approaches while maintaining similar accuracy. It has been evaluated qualitatively and quantitatively with promising results on eight datasets comprising simulated images and real patient data.

Confocal imaging protocols for live/dead staining in three-dimensional carriers

In tissue engineering, a variety of methods are commonly used to evaluate survival of cells inside tissues or three-dimensional (3D) carriers. Among these methods confocal laser scanning microscopy opened accessibility of 3D tissue using live cell imaging into the tissue or 3D scaffolds. However, although this technique is ideally applied to 3D tissue or scaffolds with thickness up to several millimetres, this application is surprisingly rare and scans are often done on slices with thickness <20 μm. Here, we present novel protocols for the staining of 3D tissue (e.g. intervertebral disc tissue) and scaffolds, such as fibrin gels or alginate beads.