Influence of electric discharges on bearings of electric machina

Bearing currents are one of cause’s bearings faults. The character of a lubricator belongs to main factor influencing an inception of bearing currents. We have analyzed the electric character variety kind of lubricators; the influence of lubricators on a bearing current was analyzed too. Some results from the mentioned research are introduced within this paper

Affine registration of native and contrast-enhanced CT brain images

Tato práce se zabývá řešením problému registrace obrazů mozku pořízených rentgenovou výpočetní tomografií. Úvodem práce je seznámení s metodami geometrických transformací obrazů, zejména pak afinní transformací. Dále se text zabývá problematikou interpolačních metod, výpočtů podobnostních kriterií a následné optimalizace. Veškerá problematika je řešena speciálně pro trojrozměrná data. Druhá část práce je praktickou ukázkou programu v prostředí MatLab® pro registraci pořízených snímků pomocí afinní transformace, jehož součástí je také algoritmus pro odstranění schodového artefaktu, podložky pod hlavu a pacientského stolu. Jako optimalizační algoritmus je použita metoda kontrolovaného náhodného prohledávání (CRS). Vzhledem k typu medicínských obrazů poskytovaných ve formátu DICOM je součástí práce také proces jejich načtení a uložení.This thesis is dealing with problem of brain images registration aquired by computed tomography. At the beginning is explanation of image geometrical transformation methods, notably affine transformation. Following part of text the is dealing with interpolation methods issues, calculation of similarity criterion and subsequent optimalization. All issues are handled especially for three-dimensional data. Second part of this work is practical sample of MatLab® program enviroment for registration of acquired frames by affine tranformation. In this program is algorithm for removement of stair-step artefact, under head pillow and patient’s desk, too. As an optimalization algorithm is used control random search (CRS) methode. Due to medical images type, which are distributed in DICOM format, is included process for their load and save at this work.

The Effect of Rhodamine-Derived Superparamagnetic Maghemite Nanoparticles on the Motility of Human Mesenchymal Stem Cells and Mouse Embryonic Fibroblast Cells

Nanoparticles have become popular in life sciences in the last few years. They have been produced in many variants and have recently been used in both biological experiments and in clinical applications. Due to concerns over nanomaterial risks, there has been a dramatic increase in investigations focused on safety research. The aim of this paper is to present the advanced testing of rhodamine-derived superparamagnetic maghemite nanoparticles (SAMN-R), which are used for their nontoxicity, biocompatibility, biodegradability, and magnetic properties. Recent results were expanded upon from the basic cytotoxic tests to evaluate cell proliferation and migration potential. Two cell types were used for the cell proliferation and tracking study: mouse embryonic fibroblast cells (3T3) and human mesenchymal stem cells (hMSCs). Advanced microscopic methods allowed for the precise quantification of the function of both cell types. This study has demonstrated that a dose of nanoparticles lower than 20 microg-cm -2 per area of the dish does not negatively affect the cells’ morphology, migration, cytoskeletal function, proliferation, potential for wound healing, and single-cell migration in comparison to standard CellTracker Green CMFDA (5-chloromethylfluorescein diacetate). A higher dose of nanoparticles could be a potential risk for cytoskeletal folding and detachment of the cells from the solid extracellular matrix

High-Resolution Quantitative Phase Imaging of Plasmonic Metasurfaces with Sensitivity down to a Single Nanoantenna

Optical metasurfaces have emerged as a new generation of building blocks for multifunctional optics. Design and realization of metasurface elements place everincreasing demands on accurate assessment of phase alterations introduced by complex nanoantenna arrays, a process referred to as quantitative phase imaging. Despite considerable effort, the widefield (nonscanning) phase imaging that would approach resolution limits of optical microscopy and indicate the response of a single nanoantenna still remains a challenge. Here, we report on a new strategy in incoherent holographic imaging of metasurfaces, in which unprecedented spatial resolution and light sensitivity are achieved by taking full advantage of the polarization selective control of light through the geometric (PancharatnamBerry) phase. The measurement is carried out in an inherently stable common-path setup composed of a standard optical microscope and an add-on imaging module. Phase information is acquired from the mutual coherence function attainable in records created in broadband spatially incoherent light by the self-interference of scattered and leakage light coming from the metasurface. In calibration measurements, the phase was mapped with the precision and spatial background noise better than 0.01 and 0.05 rad, respectively. The imaging excels at the high spatial resolution that was demonstrated experimentally by the precise amplitude and phase restoration of vortex metalenses and a metasurface grating with 833 lines/mm. Thanks to superior light sensitivity of the method, we demonstrated for the first time to our knowledge the widefield measurement of the phase altered by a single nanoantenna while maintaining the precision well below 0.15 rad

Methods of Detection, Segmentation and Classification of Difficult to Define Bone Tumor Lesions in 3D CT Data

Cílem této práce byl vývoj algoritmů pro detekci, segmentaci a klasifikaci obtížně definovatelných kostních metastatických nádorových lézí v oblasti páteře z obrazových CT dat. Pro tyto účely byla vytvořena pacientská databáze anotovaná lékařskými experty. Postupně byly navrženy tři metody, z nichž první je založena na přepracování a kombinaci metod dostupných z předchozího řešení projektu, druhá je velmi rychlá varianta založená na fuzzy k-means shlukové analýze, třetí metoda využívá moderních metod strojového učení, konkrétně hluboké učení konvolučních neuronových sítí. Dále byla navržena modifikace upřesňující výsledky následnou meta-analýzou nalezených kandidátů lézí pomocí náhodného lesa. Dosažené výsledky byly objektivně vyhodnoceny a porovnány s výsledky algoritmů publikovaných jinými autory. Pro hodnocení byly použity dva přístupy: technický, voxelově založený a klinický, objektově založený. Dosažené výsledky byly následně zhodnoceny a diskutovány.The aim of this work was the development of algorithms for detection segmentation and classification of difficult to define bone metastatic cancerous lesions from spinal CT image data. For this purpose, the patient database was created and annotated by medical experts. Successively, three methods were proposed and developed; the first of them is based on the reworking and combination of methods developed during the preceding project phase, the second method is a fast variant based on the fuzzy k-means cluster analysis, the third method uses modern machine learning algorithms, specifically deep learning of convolutional neural networks. Further, an approach that elaborates the results by a subsequent random forest based meta-analysis of detected lesion candidates was proposed. The achieved results were objectively evaluated and compared with results achieved by algorithms published by other authors. The evaluation was done by two objective methodologies, technical voxel-based and clinical object-based ones. The achieved results were subsequently evaluated and discussed.