Nano-ZnO particle addition to monolithic magnesium for enhanced tensile and compressive response

In this study, the effects of nanoscale ZnO reinforcement on the room temperature tensile and compressive response of monolithic Mg were studied. Experimental observations indicated strength properties improvement due to nanoscale ZnO addition. A maximum increment in tensile yield strength by similar to 55% and compressive yield strength by 90% (with reduced tension-compression asymmetry) was achieved when 0.8 vol.% ZnO nanoparticles were added to Mg. While the fracture strain values under tensile loads were found to increase significantly (by similar to 95%, in case of Mg-0.48ZnO), it remained largely unaffected under compressive loads. The microstructural characteristics studied in order to comprehend the mechanical response showed significant grain refinement due to grain boundary pinning effect of nano-ZnO particles which resulted in strengthening of Mg. Texture analysis using X-ray and EBSD methods indicated weakening of basal fibre texture in Mg/ZnO nanocomposites which contributed towards the reduction in tension-compression yield asymmetry and enhancement in tensile ductility when compared to pure Mg. (C) 2014 Elsevier B.V. All rights reserved.

Estimation of Aboveground Phytomass of Plantations Using Digital Photogrammetry and High Resolution Remote Sensing Data

The study follows an approach to estimate phytomass using recent techniques of remote sensing and digital photogrammetry. It involved tree inventory of forest plantations in Bhakra forest range of Nainital district. Panchromatic stereo dataset of Cartosat-1 was evaluated for mean stand height retrieval. Texture analysis and tree-tops detection analyses were done on Quick-Bird PAN data. The composite texture image of mean, variance and contrast with a 5x5 pixel window was found best to separate tree crowns for assessment of crown areas. Tree tops count obtained by local maxima filtering was found to be 83.4 % efficient with an RMSE+/-13 for 35 sample plots. The predicted phytomass ranged from 27.01 to 35.08 t/ha in the case of Eucalyptus sp. while in the case of Tectona grandis from 26.52 to 156 t/ha. The correlation between observed and predicted phytomass in Eucalyptus sp. was 0.468 with an RMSE of 5.12. However, the phytomass predicted in Tectona grandis was fairly strong with R-2=0.65 and RMSE of 9.89 as there was no undergrowth and the crowns were clearly visible. Results of the study show the potential of Cartosat-1 derived DSM and Quick-Bird texture image for the estimation of stand height, stem diameter, tree count and phytomass of important timber species.

Mg/BN nanocomposites: Nano-BN addition for enhanced room temperature tensile and compressive response

The present study elucidates the effects of nanoscale boron nitride particles addition on the microstructural and mechanical characteristics of monolithic magnesium. Novel light-weight Mg nanocomposites containing 0.3, 0.6 and 1.2vol% nano-size boron nitride particulates were synthesized using the disintegrated melt deposition method followed by hot extrusion. Microstructural characterization of developed Mg/x-boron nitride composites revealed significant grain refinement due to the uniform distribution of nano-boron nitride particulates. Texture analysis of selected Mg-1.2 boron nitride nanocomposite showed an increase in the intensity of fiber texture alongside enhanced localized recrystallization when compared to monolithic Mg. Mechanical properties evaluation under indentation, tension and compression loading indicated superior response of Mg/x-boron nitride composites in comparison to pure Mg. The uniform distribution of nanoscale boron nitride particles and the modified crystallographic texture achieved due to the nano-boron nitride addition attributes to the superior mechanical characteristics of Mg/boron nitride nanocomposites.

An integrated aurora image retrieval system: AuroraEye

With the digital all-sky imager (ASI) emergence in aurora research, millions of images are captured annually. However, only a fraction of which can be actually used. To address the problem incurred by low efficient manual processing, an integrated image analysis and retrieval system is developed. For precisely representing aurora image, macroscopic and microscopic features are combined to describe aurora texture. To reduce the feature dimensionality of the huge dataset, a modified local binary pattern (LBP) called ALBP is proposed to depict the microscopic texture, and scale-invariant Gabor and orientation-invariant Gabor are employed to extract the macroscopic texture. A physical property of aurora is inducted as region features to bridge the gap between the low-level visual features and high-level semantic description. The experiments results demonstrate that the ALBP method achieves high classification rate and low computational complexity. The retrieval simulation results show that the developed retrieval system is efficient for huge dataset. (c) 2010 Elsevier Inc. All rights reserved.

Automated Quality Assurance Applied to Mammographic Imaging

L. Blot, A. Davis, M. Holubinka, R. Marti and R. Zwiggelaar, 'Automated quality assurance applied to mammographic imaging', EURASIP Journal of Applied Signal Processing 2002 (7), 736-745 (2002)

Novel structured emulsions for delivering of food flavours

Flavour release from food is determined by the binding of flavours to other food ingredients and the partition of flavour molecules among different phases. Food emulsions are used as delivery systems for food flavours, and tailored structuring in emulsions provides novel means to better control flavour release. The current study investigated four structured oil-in-water emulsions with structuring in the oil phase, oil-water interface, and water phase. Oil phase structuring was achieved by the formation of monoglyceride (MG) liquid crystals in the oil droplets (MG structured emulsions). Structured interface was created by the adsorption of a whey protein isolate (WPI)-pectin double layer at the interface (multilayer emulsion). Water phase structured emulsions referred to emulsion filled protein gels (EFP gels), where emulsion droplets were embedded in WPI gel network, and emulsions with maltodextrins (MDs) of different dextrose-equivalent (DE) values. Flavour compounds with different physicochemical properties were added into the emulsions, and flavour release (release rate, headspace concentration and air-emulsion partition coefficient) was described by GC headspace analysis. Emulsion structures, including crystalline structure, particle size, emulsion stability, rheology, texture, and microstructures, were characterized using differential scanning calorimetry and X-ray diffraction, light scattering, multisample analytical centrifuge, rheometry, texture analysis, and confocal laser scanning microscopy, respectively. In MG structured emulsions, MG self-assembled into liquid crystalline structures and stable β-form crystals were formed after 3 days of storage at 25 °C. The inclusion of MG crystals allowed tween 20 stabilized emulsions to present viscoelastic properties, and it made WPI stabilized emulsions more sensitive to the change of pH and NaCl concentrations. Flavour compounds in MG structured emulsions had lower initial headspace concentration and air-emulsion partition coefficients than those in unstructured emulsions. Flavour release can be modulated by changing MG content, oil content and oil type. WPI-pectin multilayer emulsions were stable at pH 5.0, 4.0, and 3.0, but they presented extensive creaming when subjected to salt solutions with NaCl ≥ 150 mM and mixed with artificial salivas. Increase of pH from 5.0 to 7.0 resulted in higher headspace concentration but unchanged release rate, and increase of NaCl concentration led to increased headspace concentration and release rate. The study also showed that salivas could trigger higher release of hydrophobic flavours and lower release of hydrophilic flavours. In EFP gels, increases in protein content and oil content contributed to gels with higher storage modulus and force at breaking. Flavour compounds had significantly reduced release rates and air-emulsion partition coefficients in the gels than the corresponding ungelled emulsions, and the reduction was in line with the increase of protein content. Gels with stronger gel network but lower oil content were prepared, and lower or unaffected release rates of the flavours were observed. In emulsions containing maltodextrins, water was frozen at a much lower temperature, and emulsion stability was greatly improved when subjected to freeze-thawing. Among different MDs, MD DE 6 offered the emulsion the highest stability. Flavours had lower air-emulsion partition coefficients in the emulsions with MDs than those in the emulsion without MD. Moreover, the involvement of MDs in the emulsions allowed most flavours had similar release profiles before and after freeze-thaw treatment. The present study provided information about different structured emulsions as delivery systems for flavour compounds, and on how food structure can be designed to modulate flavour release, which could be helpful in the development of functional foods with improved flavour profile.

Characterisation of freeze-dried wafers and solvent evaporated films as potential drug delivery systems to mucosal surfaces

Freeze-dried (lyophilised) wafers and solvent cast films from sodium alginate (ALG) and sodium carboxymethylcellulose (CMC) have been developed as potential drug delivery systems for mucosal surfaces including wounds. The wafers (ALG, CMC) and films (CMC) were prepared by freeze-drying and drying in air (solvent evaporation) respectively, aqueous gels of the polymers containing paracetamol as a model drug. Microscopic architecture was examined using scanning electron microscopy, hydration characteristics with confocal laser scanning microscopy and dynamic vapour sorption. Texture analysis was employed to investigate mechanical characteristics of the wafers during compression. Differential scanning calorimetry was used to investigate polymorphic changes of paracetamol occurring during formulation of the wafers and films. The porous freeze-dried wafers exhibited higher drug loading and water absorption capacity than the corresponding solvent evaporated films. Moisture absorption, ease of hydration and mechanical behaviour were affected by the polymer and drug concentration. Two polymorphs of paracetamol were observed in the wafers and films, due to partial conversion of the original monoclinic to the orthorhombic polymorph during the formulation process. The results showed the potential of employing the freeze-dried wafers and solvent evaporated films in diverse mucosal applications due to their ease of hydration and based on different physical mechanical properties exhibited by both type of formulations.

Hyperacetylation in prostate cancer induces cell cycle aberrations, chromatin reorganization and altered gene expression profiles.

Histone acetylation is a fundamental mechanism in the regulation of local chromatin conformation and gene expression. Research has focused on the impact of altered epigenetic environments on the expression of specific genes and their pathways. However, changes in histone acetylation also have a global impact on the cell. In this study we used digital texture analysis to assess global chromatin patterns following treatment with trichostatin A (TSA) and have observed significant alterations in the condensation and distribution of higher-order chromatin, which were associated with altered gene expression profiles in both immortalised normal PNT1A prostate cell line and androgen-dependent prostate cancer cell line LNCaP. Furthermore, the extent of TSA-induced disruption was both cell cycle and cell line dependent. This was illustrated by the identification of sub-populations of prostate cancer cells expressing high levels of H3K9 acetylation in the G2/M phase of the cell cycle that were absent in normal cell populations. In addition, the analysis of enriched populations of G1 cells showed a global decondensation of chromatin exclusively in normal cells.

The mechanical and rheological characterisation of implantable medical devices formulated from binary mixtures of cellulose derivatives

This study highlights the potential associated with utilising multi-component polymeric gels to formulate materials that possess unique rheological and mechanical properties. The synergistic effect* and interaction between hydroxyethylcellulose (HEC) and sodium carboxymethylcellulose (NaCMC), polymers which are commonly employed as drug delivery platforms for implantable medical devices (1), have been determined using dynamic, continuous shear and texture profile analysis. * The difference between the actual response of a binary mixture and the sum of the two components comprising the mixture Increases in polymer concentration resulted in an increase in G', G? and ?' whereas tan d decreased. Similarly, significant increases were also apparent in continuous shear and texture analysis. All binary mixtures showed positive synergy values which may suggest associative interaction between the two components.

Contribuições para a localização e mapeamento em robótica através da identificação visual de lugares

Tese de doutoramento, Informática (Engenharia Informática), Universidade de Lisboa, Faculdade de Ciências, 2015

classification and content based retrieval of digital mammograms and placental sonograms

Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.

Grey Level Co-Occurrence Matrices: Generalisation And Some New Features

Grey Level Co-occurrence Matrices (GLCM) are one of the earliest techniques used for image texture analysis. In this paper we defined a new feature called trace extracted from the GLCM and its implications in texture analysis are discussed in the context of Content Based Image Retrieval (CBIR). The theoretical extension of GLCM to n-dimensional gray scale images are also discussed. The results indicate that trace features outperform Haralick features when applied to CBIR.

Entwicklung, in-house Validierung und Anwendung des ganzheitlichen Verfahrens Biokristallisation für die Unterscheidung von Weizen-, Möhren- und Apfelproben aus unterschiedlichem Anbau und Verarbeitungsschritten

Die Qualität ökologischer Produkte wird über den Prozess und nicht am Produkt selbst bestimmt. Die zunehmende Nachfrage nach ökologischen Produkten fordert Methoden, die den Prozess am Produkt zeigen (Authentizitätsprüfung). Eine Literaturstudie für die vorliegende Habilitationsschrift ergab, dass ganzheitliche Verfahren sich dazu besonders eignen. Zu solchen ganzheitlichen Verfahren gehört die Biokristallisation. Bei diesem Verfahren kristallisiert eine Mischung aus Probe und CuCl2 auf einer Glasplatte zu einem Bild, das sowohl visuell, als auch computergestützt ausgewertet werden kann. Es wurden zunächst alle Schritte im Labor dokumentiert und entsprechende Standardarbeitsanweisungen erstellt. Mit einem eigens entwickelten Computerprogramm werden die Bedingungen während der Probenaufbereitung und Kristallisation für jede Probe und jedes Bild erfasst. Mit einer Texturanalyse können auch die für diese Arbeiten erstellte große Menge an Bildern ausgewertet und die Ergebnisse statistisch bearbeitet werden. Damit ist es möglich das Verfahren und Methoden für Weizen- und Möhrenproben zu charakterisieren. Es wurden verschiedene Einflussgrößen untersucht. Das Verfahren ist besonders gegenüber Änderungen in der Probenvorbereitung (z.B. Vermahlung, Mischungsverhältnis) empfindlich. Es wurde sowohl die Methodenstreuung, als auch der Anteil einzelner Schritte an der Gesamtstreuung für Weizen-, Möhren- und Apfelproben ermittelt. Die Verdampfung und Kristallisation hat den größten Anteil an der Gesamtstreuung. Die Durchführung eines Laboreignungstests zeigte, dass die so dokumentierten und charakterisierten Methoden in anderen Laboratorien erfolgreich eingesetzt werden können. Das Verfahren wurde für die nominale Unterscheidung von Weizen-, Möhren- und Apfelproben aus unterschiedlichem Anbau und Verarbeitungsschritten eingesetzt. Weizen-, Möhren- und Apfelproben aus definiertem Anbau können signifikant unterschieden werden. Weizen-, Möhren- und Apfelproben vom Erzeuger (Markt) konnten im Paarvergleich (ökologisch, konventionell) teilweise signifikant getrennt werden. Das Verfahren ist auch für die Charakterisierung von verarbeiteten Proben einsetzbar. Es konnte der Einfluss von Saftherstellung, Erwärmung und Alterung signifikant gezeigt werden. Darüber hinaus lässt sich das Verfahren auf weitere Probenarten anwenden. Das Verfahren arbeitet ganzheitlich, d.h. es werden keine Einzelstoffe analytisch bestimmt, sondern als Ergebnis wird ein Bild erhalten. Die Textur- und Struktureigenschaften dieses Bildes können mit standardisierten Methoden ausgewertet werden.

Estimating the motion of an underwater robot from a monocular image sequence

When underwater vehicles perform navigation close to the ocean floor, computer vision techniques can be applied to obtain quite accurate motion estimates. The most crucial step in the vision-based estimation of the vehicle motion consists on detecting matchings between image pairs. Here we propose the extensive use of texture analysis as a tool to ameliorate the correspondence problem in underwater images. Once a robust set of correspondences has been found, the three-dimensional motion of the vehicle can be computed with respect to the bed of the sea. Finally, motion estimates allow the construction of a map that could aid to the navigation of the robot