Subcutaneous Tissue Thickness is an Independent Predictor of Image Noise in Cardiac CT

Background: Few data on the definition of simple robust parameters to predict image noise in cardiac computed tomography (CT) exist. Objectives: To evaluate the value of a simple measure of subcutaneous tissue as a predictor of image noise in cardiac CT. Methods: 86 patients underwent prospective ECG-gated coronary computed tomographic angiography (CTA) and coronary calcium scoring (CAC) with 120 kV and 150 mA. The image quality was objectively measured by the image noise in the aorta in the cardiac CTA, and low noise was defined as noise < 30HU. The chest anteroposterior diameter and lateral width, the image noise in the aorta and the skin-sternum (SS) thickness were measured as predictors of cardiac CTA noise. The association of the predictors and image noise was performed by using Pearson correlation. Results: The mean radiation dose was 3.5 ± 1.5 mSv. The mean image noise in CT was 36.3 ± 8.5 HU, and the mean image noise in non-contrast scan was 17.7 ± 4.4 HU. All predictors were independently associated with cardiac CTA noise. The best predictors were SS thickness, with a correlation of 0.70 (p < 0.001), and noise in the non-contrast images, with a correlation of 0.73 (p < 0.001). When evaluating the ability to predict low image noise, the areas under the ROC curve for the non-contrast noise and for the SS thickness were 0.837 and 0.864, respectively. Conclusion: Both SS thickness and CAC noise are simple accurate predictors of cardiac CTA image noise. Those parameters can be incorporated in standard CT protocols to adequately adjust radiation exposure.

Application of evolutionary algorithms and the boundary element method in the optimization of noise barrier profiles

[EN]This Ph.D. thesis presents a general, robust methodology that may cover any type of 2D acoustic optimization problem. A procedure involving the coupling of Boundary Elements (BE) and Evolutionary Algorithms is proposed for systematic geometric modifications of road barriers that lead to designs with ever-increasing screening performance. Numerical simulations involving single- and multi-objective optimizations of noise barriers of varied nature are included in this document. results disclosed justify the implementation of this methodology by leading to optimal solutions of previously defined topologies that, in general, greatly outperform the acoustic efficiency of classical, widely used barrier designs normally erected near roads.

Characterization and modeling of low-frequency noise in MOSFETs

For many years, RF and analog integrated circuits have been mainly developed using bipolar and compound semiconductor technologies due to their better performance. In the last years, the advance made in CMOS technology allowed analog and RF circuits to be built with such a technology, but the use of CMOS technology in RF application instead of bipolar technology has brought more issues in terms of noise. The noise cannot be completely eliminated and will therefore ultimately limit the accuracy of measurements and set a lower limit on how small signals can be detected and processed in an electronic circuit. One kind of noise which affects MOS transistors much more than bipolar ones is the low-frequency noise. In MOSFETs, low-frequency noise is mainly of two kinds: flicker or 1/f noise and random telegraph signal noise (RTS). The objective of this thesis is to characterize and to model the low-frequency noise by studying RTS and flicker noise under both constant and switched bias conditions. The effect of different biasing schemes on both RTS and flicker noise in time and frequency domain has been investigated.

Noisy Oncology: applications of bounded noise transitions in modelling tumor growth

I tumori macroscopici e microscopici, dopo la loro prima fase di crescita, sono composti da un numero medio elevato di cellule. Così, in assenza di perturbazioni esterne, la loro crescita e i punti di equilibrio possono essere descritti da equazioni differenziali. Tuttavia, il tumore interagisce fortemente col macroambiente che lo circonda e di conseguenza una descrizione del tutto deterministica risulta a volte inappropriata. In questo caso si può considerare l'interazione con fluttuazioni statistiche, causate da disturbi esterni, utilizzando le equazioni differenziali stocastiche (SDE). Questo è vero in modo particolare quando si cerca di modellizzare tumori altamente immunogenici che interagiscono con il sistema immunitario, in quanto la complessità di questa interazione risulta in fenomeni di multistabilità. Così, il rumore può provocare disturbi e indurre transizioni di stato (Noise-Induced-Transitions). E' importante notare che una NIT può avere implicazioni profonde sulla vita di un paziente, dal momento che una transizione da uno stato di equilibrio piccolo, nelle dimensioni del tumore, ad uno stato di equilibrio macroscopico, nella maggior parte dei casi significa il passaggio dalla vita alla morte. Generalmente l'approccio standard è quello di modellizzare le fluttuazioni stocastiche dei parametri per mezzo di rumore gaussiano bianco o colorato. In alcuni casi però questa procedura è altamente inadeguata, a causa della illimitatezza intrinseca dei rumori gaussiani che può portare a gravi incongruenze biologiche: pertanto devono essere utilizzati dei rumori "limitati", che, tuttavia, sono molto meno studiati di quelli gaussiani. Inoltre, l'insorgenza di NIT dipende dal tipo di rumore scelto, che rivela un nuovo livello di complessità in biologia. Lo scopo di questa tesi è quello di studiare le applicazioni di due tipi diversi di "rumori limitati" nelle transizioni indotte in due casi: interazione tra tumore e sistema immunitario e chemioterapia dei tumori. Nel primo caso, abbiamo anche introdotto un nuovo modello matematico di terapia, che estende, in modo nuovo, il noto modello di Norton-Simon.

Context-sensitive design in transportation infrastructure: relating tire/pavement noise with wearing course characteristics

A design can be defined as context-sensitive when it achieves effective technical and functional transportation solutions, while preserving and enhancing natural environments and minimizing impacts on local communities. Traffic noise is one of the most critical environmental impacts of transportation infrastructure and it affects both humans and ecosystems. Tire/pavement noise is caused by a set of interactions at the contact patch and it is the predominant source of road noise at the regular traffic speeds. Wearing course characteristics affect tire/pavement noise through various mechanisms. Furthermore, acoustic performance of road pavements varies over time and it is influenced by both aging and temperature. Three experimentations have been carried out to evaluate wearing course characteristics effects on tire/pavement noise. The first study involves the evaluation of skid resistance, surface texture and tire/pavement noise of an innovative application of multipurpose cold-laid microsurfacing. The second one involves the evaluation of the surface and acoustic characteristics of the different pavement sections of the test track of the Centre for Pavement and Transportation Technology (CPATT) at the University of Waterloo. In the third study, a set of highway sections have been selected in Southern Ontario with various types of pavements. Noise measurements were carried out by means of the Statistical Pass-by (SPB) method in the first case study, whereas in the second and in the third one, Close-proximity (CPX) and the On-Board Sound Intensity (OBSI) methods have been performed in parallel. Test results have contributed to understand the effects of pavement materials, temperature and aging on tire/pavement noise. Negligible correlation was found between surface texture and roughness with noise. As a general trend, aged and stiffer materials have shown to provide higher noise levels than newer and less stiff ones. Noise levels were also observed to be higher with temperature increase.

Nonlinear three-dimensional noise filter with low-dose CT angiography: effect on the detection of small high-contrast objects in a phantom model

To study the effect of a nonlinear noise filter on the detection of simulated endoleaks in a phantom with 80- and 100-kVp multidetector computed tomographic (CT) angiography.

The near babylonian speech confusion in early detection of psychosis

It is barely 15 years since, in 1996, the issue theme of Schizophrenia Bulletin (Vol 22, 2) “Early Detection, and Intervention in Schizophrenia” signified the commencement of this field of research. Since that time the field of early detection research has developed rapidly and it may be translated into clinical practice by the introduction of an Attenuated Psychosis Syndrome in Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, (DSM-5) (www.dsm5.org/ProposedRevisions/Pages/proposedrevision.aspx?rid=412#). Attenuated psychotic symptoms (APS) had first been suggested as a clinical predictor of first-episode psychosis by the Personal Assessment and Crisis Evaluation (PACE) Clinic group as part of the ultrahigh risk (UHR) criteria.1 The term ultrahigh risk became broadly accepted for this set of criteria for imminent risk of developing psychosis in the late 1990s. The use of the term “prodrome” for a state characterized by at-risk (AR) criteria was criticized as a retrospective concept inevitably followed by the full-blown disorder.1 Although alternative terms have been suggested, prodrome is still used in prospective studies (eg, prodromally symptomatic, potentially or putatively prodromal, prodrome-like state/symptoms). Some alternative suggestions such as prepsychotic state/symptoms, subthreshold psychotic symptoms, early psychosis, subsyndromal psychosis, hypopsychosis, or subpsychosis were short-lived. Other terms still in use include UHR, at-risk mental state (ARMS), AR, high risk, clinical high risk (CHR), or early and late AR state. Further, the term psychotic-like experiences (PLEs) has recently (re-)entered early detection research. …

Speech Enhancement With Inventory Style Speech Resynthesis

We present a new method for the enhancement of speech. The method is designed for scenarios in which targeted speaker enrollment as well as system training within the typical noise environment are feasible. The proposed procedure is fundamentally different from most conventional and state-of-the-art denoising approaches. Instead of filtering a distorted signal we are resynthesizing a new “clean” signal based on its likely characteristics. These characteristics are estimated from the distorted signal. A successful implementation of the proposed method is presented. Experiments were performed in a scenario with roughly one hour of clean speech training data. Our results show that the proposed method compares very favorably to other state-of-the-art systems in both objective and subjective speech quality assessments. Potential applications for the proposed method include jet cockpit communication systems and offline methods for the restoration of audio recordings.

Assessment of speech perception and communication skills in adolescents with cochlear implants for pre- and peri-lingual deafness

This study aimed to assess speech perception and communication skills in adolescents between ages 8 and 18 that received cochlear implants for pre- and peri-lingual deafness.

Corpus-Based Speech Enhancement With Uncertainty Modeling and Cepstral Smoothing

We present a new approach for corpus-based speech enhancement that significantly improves over a method published by Xiao and Nickel in 2010. Corpus-based enhancement systems do not merely filter an incoming noisy signal, but resynthesize its speech content via an inventory of pre-recorded clean signals. The goal of the procedure is to perceptually improve the sound of speech signals in background noise. The proposed new method modifies Xiao's method in four significant ways. Firstly, it employs a Gaussian mixture model (GMM) instead of a vector quantizer in the phoneme recognition front-end. Secondly, the state decoding of the recognition stage is supported with an uncertainty modeling technique. With the GMM and the uncertainty modeling it is possible to eliminate the need for noise dependent system training. Thirdly, the post-processing of the original method via sinusoidal modeling is replaced with a powerful cepstral smoothing operation. And lastly, due to the improvements of these modifications, it is possible to extend the operational bandwidth of the procedure from 4 kHz to 8 kHz. The performance of the proposed method was evaluated across different noise types and different signal-to-noise ratios. The new method was able to significantly outperform traditional methods, including the one by Xiao and Nickel, in terms of PESQ scores and other objective quality measures. Results of subjective CMOS tests over a smaller set of test samples support our claims.

Adverse effect of noise in the operating theatre on surgical-site infection

The aim of this pilot study was to evaluate the noise level in an operating theatre as a possible surrogate marker for intraoperative behaviour, and to detect any correlation between sound level and subsequent surgical-site infection (SSI).

Changes in hemodynamics and tissue oxygenation saturation in the brain and skeletal muscle induced by speech therapy - a near-infrared spectroscopy study

Arts speech therapy (AST) is a therapeutic method within complementary medicine and has been practiced for decades for various medical conditions. It comprises listening and the recitation of different forms of speech exercises under the guidance of a licensed speech therapist. The aim of our study was to noninvasively investigate whether different types of recitation influence hemodynamics and oxygenation in the brain and skeletal leg muscle using near-infrared spectroscopy (NIRS). Seventeen healthy volunteers (eight men and nine women, mean age ± standard deviation 35.6 ± 12.7 years) were enrolled in the study. Each subject was measured three times on different days with the different types of recitation: hexameter, alliteration, and prose verse. Before, during, and after recitation, relative concentration changes of oxyhemoglobin (Δ[O2Hb]), deoxyhemoglobin (Δ[HHb]), total hemoglobin (Δ[tHb]), and tissue oxygenation saturation (StO2) were measured in the brain and skeletal leg muscle using a NIRS device. The study was performed with a randomized crossover design. Significant concentration changes were found during recitation of all verses, with mainly a decrease in Δ[O2Hb] and ΔStO2 in the brain, and an increase in Δ[O2Hb] and Δ[tHb] in the leg muscle during recitation. After the recitations, significant changes were mainly increases of Δ[HHb] and Δ[tHb] in the calf muscle. The Mayer wave spectral power (MWP) was also significantly affected, i.e., mainly the MWP of the Δ[O2Hb] and Δ[tHb] increased in the brain during recitation of hexameter and prose verse. The changes in MWP were also significantly different between hexameter and alliteration, and hexameter and prose. Possible physiological explanations for these changes are discussed. A probable reason is a different effect of recitations on the sympathetic nervous system. In conclusion, these changes show that AST has relevant effects on the hemodynamics and oxygenation of the brain and muscle.