70 research outputs found
Ăvaluation de la capacitĂ© du canal UWB minier
La capacitĂ© du canal permet de caractĂ©riser les performances maximales dâun canal de transmission, le nombre maximal de bits susceptible dâĂȘtre transmis par seconde. Pour un canal donnĂ©, lâUWB peut garantir un grand dĂ©bit pour la transmission de donnĂ©es. Le canal de transmission UWB est gĂ©nĂ©ralement un canal Ă trajets multiples, surtout pour les applications Ă lâintĂ©rieur. Aussi, la rĂ©ponse de ce canal est sĂ©lective dans le
domaine frĂ©quentiel. Pour Ă©tudier la capacitĂ© de nâimporte quel canal il faut dâabord le caractĂ©riser et le modĂ©liser. Dans notre recherche, on va se baser sur les mesures faites
par Chehri et Fortier dans la mine CANMET Ă Val-dâOr qui est situĂ©e Ă 500 km au nord de MontrĂ©al, Canada. Ces mesures montrent que la distribution Nakagami donne
un bon ajustement pour lâamplitude du signal reçue Ă petit Ă©chelle.
La formule classique de la capacitĂ© de Shannon est obtenue pour les canaux ayant des rĂ©ponses frĂ©quentielles plates. Cette formule ne sâapplique pas directement dans
notre modĂšle de canal. Pour utiliser la formule classique de la capacitĂ© de Shannon, nous devons dâabord diviser la bande de frĂ©quences en un nombre trĂšs grand (thĂ©oriquement
infini) de petites bandes, considérées comme des sous-canaux à réponse plates dans le domaine fréquentiel. Ensuite, on peut appliquer une distribution optimale de
puissance maximisant la capacitĂ© pour une puissance dâĂ©mission totale limitĂ©e. Cette mĂ©thode est connue sous le nom de "waterfilling".
Les travaux antĂ©rieurs sur lâĂ©valuation de la capacitĂ© du canal UWB en externe (outdoor) nâont pas tenu compte des Ă©vanouissements du canal, et en interne (indoor), le
cas dâun milieu UWB minier nâa pas encore Ă©tĂ© abordĂ©. Dans ce mĂ©moire de maĂźtrise on sâest particuliĂšrement intĂ©ressĂ© au problĂšme dâĂ©valuation de la capacitĂ© du canal UWB
minier. En utilisant la mĂ©thode "waterfilling" on a calculĂ© la capacitĂ© dâun canal UWB minier dâune maniĂšre optimale en tenant compte des caractĂ©ristiques dâĂ©vanouissement
du canal. Les résultats obtenus prouvent la pertinence de la méthode "waterfilling" dans ces type des canaux ; cette méthode donne une amélioration importante de la capacité,
dâun facteur entre 1.1 Ă 1.22 fois plus grand que la capacitĂ© uniforme lorsque le SNR 40 dB, la capacitĂ© optimale et la capacitĂ© uniforme convergent, et on remarque que les deux mĂ©thodes donnent les mĂȘmes rĂ©sultats lorsque le rapport signal sur bruit est grand (> 80 dB).
Capacity plays an important role in characterizing the maximum performance for channel transmission by providing the maximum number of bits that can be transmitted per second. Furthermore, for a given channel, a large rate for data transmission can be guaranteed using UWB modulation.
In fact, the UWB transmission channel is generally a multipath channel especially for indoor applications. Thus, the channel response is selective in the frequency domain.
To be able to study the capacity of any channel, it should be characterized and modeled. In this research, we depend on the measures taken by Chehri and Fortier in the CANMET mine in Val-dâOr, located 500 km north of Montreal, Canada. These measurements show that the Nakagami distribution gives a good adjustment for the amplitude of the signal received at a small scale.
Indeed, the classical formula for the Shannon capacity is used for flat channels. Thus, we can first divide the whole frequency band into many small bands, in which
the sub-channel can be considered frequency-flat. After that, we can apply an optimal distribution of power to maximize the capacity of total transmission over limited power; this method is known as "waterfilling".
Previous works on the evaluation of UWB channel capacity considered the external (outdoor) case, however, they did not consider the fading channel. Also, the internal
(indoor) studies did not discuss the case of the mining channel. In this thesis, we paid particular attention to the problem of evaluating the UWB channel in the mine. By
using the "waterfilling" method, we calculated the capacity of a UWB channel mining optimally, taking into account the characteristics of the fading channel. The results
demonstrate the relevance of the "waterfilling" method in these types of channels. We show that, when the transmitted signal-to-noise ratio (SNR) is lower than 40 dB, using
optimal power spectrum allocation at the transmitter side can increase transmission rate compared to the uniform power spectrum allocation scheme. Whereas, when the
transmitted SNR is higher than 80 dB, the benefit of optimal power spectrum allocation is very limited
Oncometabolites:linking altered metabolism with cancer
The discovery of cancer-associated mutations in genes encoding key metabolic enzymes has provided a direct link between altered metabolism and cancer. Advances in mass spectrometry and nuclear magnetic resonance technologies have facilitated high-resolution metabolite profiling of cells and tumors and identified the accumulation of metabolites associated with specific gene defects. Here we review the potential roles of such "oncometabolites" in tumor evolution and as clinical biomarkers for the detection of cancers characterized by metabolic dysregulation
Characterization of metabolites in infiltrating gliomas using ex vivo &supl;H high-resolution magic angle spinning spectroscopy.
Gliomas are routinely graded according to histopathological criteria established by the World Health Organization. Although this classification can be used to understand some of the variance in the clinical outcome of patients, there is still substantial heterogeneity within and between lesions of the same grade. This study evaluated image-guided tissue samples acquired from a large cohort of patients presenting with either new or recurrent gliomas of grades II-IV using ex vivo proton high-resolution magic angle spinning spectroscopy. The quantification of metabolite levels revealed several discrete profiles associated with primary glioma subtypes, as well as secondary subtypes that had undergone transformation to a higher grade at the time of recurrence. Statistical modeling further demonstrated that these metabolomic profiles could be differentially classified with respect to pathological grading and inter-grade conversions. Importantly, the myo-inositol to total choline index allowed for a separation of recurrent low-grade gliomas on different pathological trajectories, the heightened ratio of phosphocholine to glycerophosphocholine uniformly characterized several forms of glioblastoma multiforme, and the onco-metabolite D-2-hydroxyglutarate was shown to help distinguish secondary from primary grade IV glioma, as well as grade II and III from grade IV glioma. These data provide evidence that metabolite levels are of interest in the assessment of both intra-grade and intra-lesional malignancy. Such information could be used to enhance the diagnostic specificity of in vivo spectroscopy and to aid in the selection of the most appropriate therapy for individual patients
Metabolic Profiling of IDH Mutation and Malignant Progression in Infiltrating Glioma.
Infiltrating low grade gliomas (LGGs) are heterogeneous in their behavior and the strategies used for clinical management are highly variable. A key factor in clinical decision-making is that patients with mutations in the isocitrate dehydrogenase 1 and 2 (IDH1/2) oncogenes are more likely to have a favorable outcome and be sensitive to treatment. Because of their relatively long overall median survival, more aggressive treatments are typically reserved for patients that have undergone malignant progression (MP) to an anaplastic glioma or secondary glioblastoma (GBM). In the current study, ex vivo metabolic profiles of image-guided tissue samples obtained from patients with newly diagnosed and recurrent LGG were investigated using proton high-resolution magic angle spinning spectroscopy (1H HR-MAS). Distinct spectral profiles were observed for lesions with IDH-mutated genotypes, between astrocytoma and oligodendroglioma histologies, as well as for tumors that had undergone MP. Levels of 2-hydroxyglutarate (2HG) were correlated with increased mitotic activity, axonal disruption, vascular neoplasia, and with several brain metabolites including the choline species, glutamate, glutathione, and GABA. The information obtained in this study may be used to develop strategies for in vivo characterization of infiltrative glioma, in order to improve disease stratification and to assist in monitoring response to therapy
Super Resolution Convolutional Neural Networks for Increasing Spatial Resolution of 1H Magnetic Resonance Spectroscopic Imaging
Texture analysis-and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction:a preliminary study
We sought to investigate, whether texture analysis of diffusional kurtosis imaging (DKI) enhanced by support vector machine (SVM) analysis may provide biomarkers for gliomas staging and detection of the IDH mutation. First-order statistics and texture feature extraction were performed in 37 patients on both conventional (FLAIR) and mean diffusional kurtosis (MDK) images and recursive feature elimination (RFE) methodology based on SVM was employed to select the most discriminative diagnostic biomarkers. The first-order statistics demonstrated significantly lower MDK values in the IDH-mutant tumors. This resulted in 81.1% accuracy (sensitivityâ=â0.96, specificityâ=â0.45, AUC 0.59) for IDH mutation diagnosis. There were non-significant differences in average MDK and skewness among the different tumour grades. When texture analysis and SVM were utilized, the grading accuracy achieved by DKI biomarkers was 78.1% (sensitivity 0.77, specificity 0.79, AUC 0.79); the prediction accuracy for IDH mutation reached 83.8% (sensitivity 0.96, specificity 0.55, AUC 0.87). For the IDH mutation task, DKI outperformed significantly the FLAIR imaging. When using selected biomarkers after RFE, the prediction accuracy achieved 83.8% (sensitivity 0.92, specificity 0.64, AUC 0.88). These findings demonstrate the superiority of DKI enhanced by texture analysis and SVM, compared to conventional imaging, for gliomas staging and prediction of IDH mutational status
Nuclear Magnetic Resonance metabolomics reveals an excretory metabolic signature of renal cell carcinoma
RCC usually develops and progresses asymptomatically and, when detected, it is frequently at advanced stages and metastatic, entailing a dismal prognosis. Therefore, there is an obvious demand for new strategies enabling an earlier diagnosis. The importance of metabolic rearrangements for carcinogenesis unlocked a new approach for cancer research, catalyzing the increased use of metabolomics. The present study aimed the NMR metabolic profiling of RCC in urine samples from a cohort of RCC patients (n = 42) and controls (n = 49). The methodology entailed variable selection of the spectra in tandem with multivariate analysis and validation procedures. The retrieval of a disease signature was preceded by a systematic evaluation of the impacts of subject age, gender, BMI, and smoking habits. The impact of confounders on the urine metabolomics profile of this population is residual compared to that of RCC. A 32-metabolite/resonance signature descriptive of RCC was unveiled, successfully distinguishing RCC patients from controls in principal component analysis. This work demonstrates the value of a systematic metabolomics workflow for the identification of robust urinary metabolic biomarkers of RCC. Future studies should entail the validation of the 32-metabolite/resonance signature found for RCC in independent cohorts, as well as biological validation of the putative hypotheses advanced
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Application of MR Spectroscopic Techniques for the Development and Translation of Metabolite Markers Characterizing Infiltrating Glioma
Despite ever more advanced characterization, the family of malignant central nervous system diseases known as infiltrating glioma remain pernicious and resistant to treatment. Because of their molecular and pathologic heterogeneity, they are among the most complex cancers in adults, with tremendous variability in patient outcomes being observed across oncologic subtypes. Over the course of therapy, magnetic resonance imaging (MRI) is critical to evaluating the level of response as the diagnostic standard for clinical management. Conventional MRI, having superior soft tissue contrast, provides a non-invasive means of detecting abnormalities that are embedded within neural anatomy. However, gauging the full extent of tumor is difficult owing to non-specific changes, which may either reflect benign processes in the aftermath of treatment or tumor infiltration. Given the ambiguity associated with anatomical imaging, magnetic resonance spectroscopy (MRS) has emerged as a technique that can add diagnostic value to clinical practice by probing signature chemical species characterizing disease. The primary focus of this work was the development of translatable biomarkers for infiltrating glioma using analogous ex vivo methodology that has greater sensitivity and spectral resolution. By analyzing image-guided tissue samples acquired from a large cohort of patients with pathologically distinct subtypes, it was possible to characterize metabolite expression across diverse swathes of tumor representing natural heterogeneity. Quantified data revealed distinct metabolomic profiles for each of the clinically relevant subtypes that enabled their differential classification. Importantly, classification models were able to predict malignant progression on the basis of these profiles, highlighting the potential to determine pathologic trajectory. Separate analysis of contrast-based radiographic subtypes of the most aggressive form of glioma demonstrated unique metabolite expression in the portion of tumor that fails to exhibit contrast and is therefore masked on standard imaging.Since some of the metabolite markers discovered exhibited features that diminished the lifetime of their signal, technical development of an in vivo MRS sequence was also undertaken. The creation of radiofrequency (RF) pulses with reduced peak power requirements was critical to the design of the sequence and enabled improved signal fidelity over longer acquisition times when incorporated into existing frameworks. Results from this project and those obtained ex vivo support greater clinical integration of spectroscopy
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