Dynamic Versus Static Oxidation of Nb/Al-AlOx_x/Nb Trilayer

High quality Nb-based superconductor-insulator-superconductor (SIS) junctions with Al oxide (AlO$_x$) tunnel barriers grown from Al overlayers are widely reported in the literature. However, the thin barriers required for high critical current density (J$_c$) junctions exhibit defects that result in significant subgap leakage current that is detrimental for many applications. High quality, high-J$_c$ junctions can be realized with AlN$_x$ barriers, but control of J$_c$ is more difficult than with AlO$_x$. It is therefore of interest to study the growth of thin AlO$_x$ barriers with the ultimate goal of achieving high quality, high-J$_c$ AlO$_x$ junctions. In this work, 100\%\ O$_2$ and 2\%\ O$_2$ in Ar gas mixtures are used both statically and dynamically to grow AlO$_x$ tunnel barriers over a large range of oxygen exposures. In situ ellipsometry is used for the first time to extensively measure AlO$_x$ tunnel barrier growth in real time, revealing a number of unexpected patterns. Finally, a set of test junction wafers was fabricated that exhibited the well-known dependence of J$_c$ on oxygen exposure (E) in order to further validate the experimental setup

An automated digital fluorescence imaging system of tumor margins using clustering-based image thresholding

Summarization: An optical system for efficient fluorescence imaging of cancer margins aiming at enhanced discrimination of the tumor area from the surrounding normal tissue, is presented. Fluorescence imaging was used to acquire grayscale images of brain tumor samples of 10 μm slice thickness. The tumor cells are characterized as Gli36Δ5 cells expressing Green Fluorescent Protein (GFP). An image processing technique involving the clustering-based concept of Otsu segmentation was applied to enhance the contrast and difference between the tumor and the rest of the tissue for improved visualization of tumor margins. Edge detection was performed on these processed images to mark the boundaries of the tumor area. The fluorescence imaging results depict clear demarcation of tumor boundary and a substantial improvement of the contrast, post processing.Παρουσιάστηκε στο: IEEE International Conference on Imaging Systems and Techniques (IST

Bioinformatics of lung cancer

Summarization: The objective of this study is to explore novel bioinformatics techniques, namely, the Polarimetric Exploratory Data Analysis (pEDA), for early identification and discrimination of precancerous and cancerous lung tissues. The outcome of this study indicates that the full-width-at half maximum (FWHM) and Dynamic Range (DR) extracted from histograms of inherent (label-free) near infrared (NIR) diffused-polarimetric reflectance signals provide an important metrics for the characterization of cancerous tissue. Application of pEDA on the acquired data has been proved an effective diagnostic tool aimed at discriminating optical information among normal, precancerous, and cancerous lung tissue samples. Therefore, it can eventually be proved a useful diagnostic tool in the early detection of Non-Small Cell Lung Cancer (NSCLC) as well as in classical cytopathology and histopathology.Παρουσιάστηκε στο: IEEE International Conference on Imaging Systems and Techniques (IST

Label-free discrimination of lung cancer cells through mueller matrix decomposition of diffuse reflectance imaging

Summarization: In this article, we explore the potential of an original label-free Near-Infrared (NIR) imaging technique, based on Mueller Matrix decomposition reflectance, for efficient detection and classification of histopathological samples of lung cancer cells. Experimental results were acquired, processed, and analyzed by means of an accurate, fully-automated, auto-calibrated liquid-crystal NIR polarimetric imaging system, developed for real-time Mueller matrix analysis and optical characterization of target media. The polarimetric Figure-of-Merits (FOMs), estimated using Mueller matrix decomposition, as well as the statistics associated with the sixteen Mueller matrix elements of each lung cell sample indicate that enhanced discrimination among the samples can be achieved. Similarly, polarimetric Exploratory Data Analysis (pEDA), based on histograms obtained from diffuse reflectance polarimetric signals, has been used to determine if aberrations and/or changes in the spread of the histogram between different stages of lung cancer can be proved effective biomarkers for its progression and also discrimination among different lung pathologies. The outcome of this study indicates that Mueller matrix formalism may be proved extremely useful in discriminating among healthy and malignant lung cells as well as differentiating among the different types of malignancies with high accuracy. As a result, it may contribute positively to the enhancement and implementation of the operational principles of the Whole Slide Imaging (WSI) field.Presented on

Integration of bioinspired vision principles towards the design of autonomous guidance, navigation, and control systems

Summarization: In this study, key-characteristics of different bioinspired vision systems are presented, and their importance in the design of autonomous navigation systems is highlighted. Two paradigms reflecting authors' research efforts in the design of vision systems, mimicking the human and animal retina, are presented. The first paradigm relates to the development of novel polymer nanostructures and nanoantennas aimed at integrating polarization principles with CMOS designs, mimicking bioinspired retina systems. The second paradigm relates to the development and testing of a novel neuromorphic spike event-based polarimetric Dynamic Vision Sensor (DVS), for dynamic imaging of a scene, with enhanced temporal contrast and high object discrimination. The outcome of this study indicates that integration of several bioinspired vision principles, such as polarization of light and neuromorphic detection, play an important role in the design of innovative bioinspired nanomaterials and neuromorphic vision architectures.Παρουσιάστηκε στο: 9th International Conference on Information, Intelligence, Systems and Application