Electroencephalogram cepstral distances in alzheimer’s disease diagnosis

Alzheimer's disease (AD) represents one ofthe greatest public health challenges worldwide nowadays, because it affects millions of people ali o ver the world and it is expected that the disease will increase considerably in the near future. This study is the first application attempt of cepstral analysis on Electroencephalogram (EEG) signals to find new parameters in arder to achieve a better differentiation belween EEGs of AD patients and Control subjects. The results show that the methodology that uses a combined Wavelet (WT) Biorthogonal (Bior) 3.5 and cepstrum analysis was able to describe the EEG dynamics with a higher discriminative power than the other WTs/spectmm methodologies m previous studies. The most important significance figures were found in cepstral distances between cepstrums oftheta and alpha bands (p=0. 00006<0. 05).

Alteration of the bone tissue material properties in type 1 diabetes mellitus: A Fourier transform infrared microspectroscopy study

International audience

Nonuniform Depth Distribution Selection with Discrete Fourier Transform

info:eu-repo/semantics/inPress

Designing Hydrogels that Transform their Shape in Response to Molecular Cues

There has been considerable interest in developing shape-changing soft materials for potential applications in drug delivery, microfluidics and biosensing. These shape- changing materials are inspired by the morphological changes exhibited by plants in nature, such as the Venus flytrap. One specific class of shape-change is that from a flat sheet to a folded structure (e.g., a tube). Such “self-folding” materials are usually composed of polymer hydrogels, and these typically fold in response to external stimuli such as pH and temperature. In order to develop these hydrogels for the previously described applications, it is necessary to expand the range of triggers. The focus of this dissertation is the advancement of shape-changing polymer hydrogels that are sensitive to uncommon cues such as specific biomolecules (enzymes), the substrates for such enzymes, or specific multivalent cations. First, we describe a hybrid gel that responds to the presence of low concentrations of a class of enzymes known as matrix metalloproteinases (MMPs). The hybrid gel was created by utilizing photolithographic techniques to combine two or more gels with distinct chemical composition into the same material. Certain portions of the hybrid gel are composed of a biopolymer derivative with crosslinkable groups. The hybrid gel is flat in water; however, in the presence of MMPs, the regions containing the biopolymer are degraded and the flat sheet folds to form a 3D structure. We demonstrate that hydrogels with different patterns can transform into different 3D structures such as tubes, helices and pancakes. Furthermore, this shape change can be made to occur at physiological concentrations of enzymes. Next, we report a gel with two layers that undergoes a shape change in the presence of glucose. The enzyme glucose oxidase (GOx) is immobilized in one of the layers. GOx catalyzes the conversion of glucose to gluconic acid. The production of gluconic acid decreases the local pH. The decrease in local pH causes one of the layers to swell. As a result, the flat sheet folds to form a tube. The tube unfolds to form a flat sheet when it is transferred to a solution with no glucose present. Therefore, this biomolecule- triggered shape transformation is reversible, meaning the glucose sensing gel is reusable. Furthermore, this shape change only occurs in the presence of glucose and it does not occur in the presence of other small sugars such as fructose. In our final study, we report the shape change of a gel with two layers in the presence of multivalent ions such as Ca2+ and Sr2+. The gel consists of a passive layer and an active layer. The passive layer is composed of dimethylyacrylamide (DMAA), which does not interact with multivalent ions. The active layer consists of DMAA and the biopolymer alginate. In the presence of Ca2+ ions, the alginate chains crosslink and the active layer shrinks. As a result, the gel converts from a flat sheet to a folded tube. What is particularly unusual is the direction of folding. In most cases, when flat rectangular gels fold, they do so about their short-side. However, our gels typically fold about their long-side. We hypothesize that non-homogeneous swelling determines the folding axis.

Processamento Inteligente de Sinais de Pressão e Temperatura Adquiridos Através de Sensores Permanentes em Poços de Petróleo

Originally aimed at operational objectives, the continuous measurement of well bottomhole pressure and temperature, recorded by permanent downhole gauges (PDG), finds vast applicability in reservoir management. It contributes for the monitoring of well performance and makes it possible to estimate reservoir parameters on the long term. However, notwithstanding its unquestionable value, data from PDG is characterized by a large noise content. Moreover, the presence of outliers within valid signal measurements seems to be a major problem as well. In this work, the initial treatment of PDG signals is addressed, based on curve smoothing, self-organizing maps and the discrete wavelet transform. Additionally, a system based on the coupling of fuzzy clustering with feed-forward neural networks is proposed for transient detection. The obtained results were considered quite satisfactory for offshore wells and matched real requisites for utilization

A mobile image enhancement technology for visually impaired

In this thesis, an image enhancement application is developed for low-vision patients when they use iPhones to see images/watch videos. The thesis has two contributions. The first contribution is the new image enhancement algorithm which combines human vision features. The new image enhancement algorithm is modified from a wavelet transform based image enhancement algorithm developed by Dr. Jinshan Tang. Different from the original algorithm, the new image enhancement algorithm combines human visual feature into the algorithm and thus can make the new algorithm more effective. Experimental simulation results show that the proposed algorithm has better visual results than the algorithm without combining visual features. The second contribution of this thesis is the development of a mobile image enhancement application. In this application, users with low-vision can see clearer images on an iPhone which is installed with the application I have developed.

The Nature of Microvariability in Blazar 0716+714

We organized an international campaign to observe the blazar 0716+714 in the optical band. The observations took place from February 24, 2009 to February 26, 2009. The global campaign was carried out by observers from more that sixteen countries and resulted in an extended light curve nearly seventy-eight hours long. The analysis and the modeling of this light curve form the main work of this dissertation project. In the first part of this work, we present the time series and noise analyses of the data. The time series analysis utilizes discrete Fourier transform and wavelet analysis routines to search for periods in the light curve. We then present results of the noise analysis which is based on the idea that each microvariability curve is the realization of the same underlying stochastic noise processes in the blazar jet. Neither reoccuring periods nor random noise can successfully explain the observed optical fluctuations. Hence in the second part, we propose and develop a new model to account for the microvariability we see in blazar 0716+714. We propose that the microvariability is due to the emission from turbulent regions in the jet that are energized by the passage of relativistic shocks. Emission from each turbulent cell forms a pulse of emission, and when convolved with other pulses, yields the observed light curve. We use the model to obtain estimates of the physical parameters of the emission regions in the jet.

Singularity and multifractal characterization of signals with wavelets. Application to clay soil images

In the field of multiscale analysis of signals, including images, the wavelet transform is one of the most attractive and powerful tool due to its ability to focus on signals structures at different scales. Wavelet Transform at different scales is successfully applied to image characterization (which can be applied to a watermarking scheme) and multiscale singularity detection and processing. In this work we show further research of computation of multifractals properties such as the multifractal spectrum (D(alpha)) applied to dye stained images of natural terrain. This can be useful for statically describing preferential flow path geometry.

Analysis of Pancreas Histological Images for Glucose Intolerance Identification using Wavelet Decomposition

Subtle structural differencescan be observed in the islets of Langer-hans region of microscopic image of pancreas cell of the rats having normal glucose tolerance and the rats having pre-diabetic(glucose intolerant)situa-tions. This paper proposes a way to automatically segment the islets of Langer-hans region fromthe histological image of rat's pancreas cell and on the basis of some morphological feature extracted from the segmented region the images are classified as normal and pre-diabetic.The experiment is done on a set of 134 images of which 56 are of normal type and the rests 78 are of pre-diabetictype. The work has two stages: primarily,segmentationof theregion of interest (roi)i.e. islets of Langerhansfrom the pancreatic cell and secondly, the extrac-tion of the morphological featuresfrom the region of interest for classification. Wavelet analysis and connected component analysis method have been used for automatic segmentationof the images. A few classifiers like OneRule, Naïve Bayes, MLP, J48 Tree, SVM etc.are used for evaluation among which MLP performed the best.

Wavelet analysis and hierarchical clustering of ofm phenotypic population's variations originated from southern america and europe and attempts of a first relation to molecular divergence.

In this work we compare Grapholita molesta Busck (Lepidoptera: Tortricidae) populations originated from Brazil, Chile, Spain, Italy and Greece using power spectral density and phylogenetic analysis to detect any similarities between the population macro- and the molecular micro-level. Log-transformed population data were normalized and AR(p) models were developed to generate for each case population time series of equal lengths. The time-frequency/scale properties of the population data were further analyzed using wavelet analysis to detect any population dynamics frequency changes and cluster the populations. Based on the power spectral of each population time series and the hierarchical clustering schemes, populations originated from Southern America (Brazil and Chile) exhibit similar rhythmic properties and are both closer related with populations originated from Greece. Populations from Spain and especially Italy, have higher distance by terms of periodic changes on their population dynamics. Moreover, the members within the same cluster share similar spectral information, therefore they are supposed to participate in the same temporally regulated population process. On the contrary, the phylogenetic approach revealed a less structured pattern that bears indications of panmixia, as the two clusters contain individuals from both Europe and South America. This preliminary outcome will be further assessed by incorporating more individuals and likely employed a second molecular marker.

Graphene And Carbon Nanotube Nanocomposite For Gene Transfection.

Graphene and carbon nanotube nanocomposite (GCN) was synthesised and applied in gene transfection of pIRES plasmid conjugated with green fluorescent protein (GFP) in NIH-3T3 and NG97 cell lines. The tips of the multi-walled carbon nanotubes (MWCNTs) were exfoliated by oxygen plasma etching, which is also known to attach oxygen content groups on the MWCNT surfaces, changing their hydrophobicity. The nanocomposite was characterised by high resolution scanning electron microscopy; energy-dispersive X-ray, Fourier transform infrared and Raman spectroscopies, as well as zeta potential and particle size analyses using dynamic light scattering. BET adsorption isotherms showed the GCN to have an effective surface area of 38.5m(2)/g. The GCN and pIRES plasmid conjugated with the GFP gene, forming π-stacking when dispersed in water by magnetic stirring, resulting in a helical wrap. The measured zeta potential confirmed that the plasmid was connected to the nanocomposite. The NIH-3T3 and NG97 cell lines could phagocytize this wrap. The gene transfection was characterised by fluorescent protein produced in the cells and pictured by fluorescent microscopy. Before application, we studied GCN cell viability in NIH-3T3 and NG97 line cells using both MTT and Neutral Red uptake assays. Our results suggest that GCN has moderate stability behaviour as colloid solution and has great potential as a gene carrier agent in non-viral based therapy, with low cytotoxicity and good transfection efficiency.

Carbon Nanoparticles For Gene Transfection In Eukaryotic Cell Lines.

For the first time, oxygen terminated cellulose carbon nanoparticles (CCN) was synthesised and applied in gene transfection of pIRES plasmid. The CCN was prepared from catalytic of polyaniline by chemical vapour deposition techniques. This plasmid contains one gene that encodes the green fluorescent protein (GFP) in eukaryotic cells, making them fluorescent. This new nanomaterial and pIRES plasmid formed π-stacking when dispersed in water by magnetic stirring. The frequencies shift in zeta potential confirmed the plasmid strongly connects to the nanomaterial. In vitro tests found that this conjugation was phagocytised by NG97, NIH-3T3 and A549 cell lines making them fluorescent, which was visualised by fluorescent microscopy. Before the transfection test, we studied CCN in cell viability. Both MTT and Neutral Red uptake tests were carried out using NG97, NIH-3T3 and A549 cell lines. Further, we use metabolomics to verify if small amounts of nanomaterial would be enough to cause some cellular damage in NG97 cells. We showed two mechanisms of action by CCN-DNA complex, producing an exogenous protein by the transfected cell and metabolomic changes that contributed by better understanding of glioblastoma, being the major finding of this work. Our results suggested that this nanomaterial has great potential as a gene carrier agent in non-viral based therapy, with low cytotoxicity, good transfection efficiency, and low cell damage in small amounts of nanomaterials in metabolomic tests.

Phytochemical Markers Of Different Types Of Red Propolis.

Propolis is a resin that bees collect from different plant sources and use in the defense of the bee community. The intricate composition of propolis varies depending on plant sources from different geographic regions and many types have been reported. Red coloured propolis found in several states in Brazil and in other countries has known antimicrobial and antioxidant activity. Different analytical methods have been applied to studies regarding the chemical composition and plant origins of red propolis. In this study samples of red propolis from different regions have been characterised using direct infusion electrospray ionisation mass spectrometry (ESI(-)-MS) fingerprinting. Data from the fingerprints was extracted and analysed by multivariate analysis to group the samples according to their composition and marker compounds. Despite similar colour, the red coloured propolis samples were divided into three groups due to contrasting chemical composition, confirming the need to properly characterise the chemical composition of propolis.