Quantitative analysis of microscopy

Particle tracking is an essential tool for the study of dynamics of biological processes. The dynamics of these processes happens in three-dimensional (3D) space as the biological structures themselves are 3D. The focus of this thesis is on the development of single particle tracking methods for analysis of the dynamics of biological processes through the use of image processing techniques. Firstly, introduced is a novel particle tracking method that works with two-dimensional (2D) image data. This method uses the theory of Haar-like features for particle detection and trajectory linking is achieved using a combination of three Kalman filters within an interacting multiple models framework. The trajectory linking process utilises an extended state space variable which better describe the morphology and intensity profiles of the particles under investigation at their current position. This tracking method is validated using both 2D synthetically generated images as well as 2D experimentally collected images. It is shown that this method outperforms 14 other stateof-the-art methods. Next this method is used to analyse the dynamics of fluorescently labelled particles using a live-cell fluorescence microscopy technique, specifically a variant of the super-resolution (SR) method PALM, spt-PALM. From this application, conclusions about the organisation of the proteins under investigation at the cell membrane are drawn. Introduced next is a second particle tracking method which is highly efficient and capable of working with both 2D and 3D image data. This method uses a novel Haar-inspired feature for particle detection, drawing inspiration from the type of particles to be detected which are typically circular in 2D space and spherical in 3D image space. Trajectory linking in this method utilises a global nearest neighbour methodology incorporating both motion models to describe the motion of the particles under investigation and a further extended state space variable describing many more aspects of the particles to be linked. This method is validated using a variety of both 2D and 3D synthetic image data. The methods performance is compared with 14 other state-of-the-art methods showing it to be one of the best overall performing methods. Finally, analysis tools to study a SR image restoration method developed by our research group, referred to as Translation Microscopy (TRAM) are investigated [1]. TRAM can be implemented on any standardised microscope and deliver an improvement in resolution of up to 7-fold. However, the results from TRAM and other SR imaging methods require specialised tools to validate and analyse them. Tools have been developed to validate that TRAM performs correctly using a specially designed ground truth. Furthermore, through analysis of results on a biological sample corroborate other published results based on the size of biological structures, showing again that TRAM performs as expected.EPSC

Adaptive Indoor Pedestrian Tracking Using Foot-Mounted Miniature Inertial Sensor

This dissertation introduces a positioning system for measuring and tracking the momentary location of a pedestrian, regardless of the environmental variations. This report proposed a 6-DOF (degrees of freedom) foot-mounted miniature inertial sensor for indoor localization which has been tested with simulated and real-world data. To estimate the orientation, velocity and position of a pedestrian we describe and implement a Kalman filter (KF) based framework, a zero-velocity updates (ZUPTs) methodology, as well as, a zero-velocity (ZV) detection algorithm. The novel approach presented in this dissertation uses the interactive multiple model (IMM) filter in order to determine the exact state of pedestrian with changing dynamics. This work evaluates the performance of the proposed method in two different ways: At first a vehicle traveling in a straight line is simulated using commonly used kinematic motion models in the area of tracking (constant velocity (CV), constant acceleration (CA) and coordinated turn (CT) models) which demonstrates accurate state estimation of targets with changing dynamics is achieved through the use of multiple model filter models. We conclude by proposing an interactive multiple model estimator based adaptive indoor pedestrian tracking system for handling dynamic motion which can incorporate different motion types (walking, running, sprinting and ladder climbing) whose threshold is determined individually and IMM adjusts itself adaptively to correct the change in motion models. Results indicate that the overall IMM performance will at all times be similar to the best individual filter model within the IMM

Uncertainty Modelling of High-precision Trajectories for Industrial Real-time Measurement Applications

Within the field of large volume metrology, kinematic tasks such as the movement of an industrial robot have been measured using laser trackers. In spite of the kinematic applications, to date most research has focused on static measurements. It is crucial to have a reliable uncertainty of kinematic measurements in order to assess spatiotemporal path deviations of a robot. With this in mind an approach capable of real-time was developed, to determine the uncertainties of kinematic measurements

Millimeter-wave Mobile Sensing and Environment Mapping: Models, Algorithms and Validation

Integrating efficient connectivity, positioning and sensing functionalities into 5G New Radio (NR) and beyond mobile cellular systems is one timely research paradigm, especially at mm-wave and sub-THz bands. In this article, we address the radio-based sensing and environment mapping prospect with specific emphasis on the user equipment (UE) side. We first describe an efficient l1-regularized least-squares (LS) approach to obtain sparse range--angle charts at individual measurement or sensing locations. For the subsequent environment mapping, we then introduce a novel state model for mapping diffuse and specular scattering, which allows efficient tracking of individual scatterers over time using interacting multiple model (IMM) extended Kalman filter and smoother. We provide extensive numerical indoor mapping results at the 28~GHz band deploying OFDM-based 5G NR uplink waveform with 400~MHz channel bandwidth, covering both accurate ray-tracing based as well as actual RF measurement results. The results illustrate the superiority of the dynamic tracking-based solutions, compared to static reference methods, while overall demonstrate the excellent prospects of radio-based mobile environment sensing and mapping in future mm-wave networks

ATC Trajectory Reconstruction for Automated Evaluation of Sensor and Tracker Performance

Currently most air traffic controller decisions are based on the information provided by the ground support tools provided by automation systems, based on a network of surveillance sensors and the associated tracker. To guarantee surveillance integrity, it is clear that performance assessments of the different elements of the surveillance system are necessary. Due to the evolution suffered by the surveillance processing chain in the recent past, its complexity has been increased by the integration of new sensor types (e.g., automatic dependent surveillance-broadcast [ADS-B], Mode S radars, and wide area multilateration [WAM]), data link applications, and networking technologies. With new sensors, there is a need for system-level performance evaluations as well as methods for establishing assessment at each component of the tracking evaluation.This work was funded by contract EUROCONTROL’s TRES, by the Spanish Ministry of Economy and Competitiveness under grants CICYT TEC2008-06732/TEC and CYCIT TEC2011-28626, and by the Government of Madrid under grant S2009/TIC-1485 (CONTEXTS).Publicad

Fabrication of Organosilane Nanostructures as Selective Sites for Surface Chemical Reactions

Naturally self-assembled mesospheres provide a practical route for controlling the arrangement of materials on surfaces at the nanoscale. Periodic arrays of well-defined nanostructures can be produced with different nanomaterials and interpattern spacings. Results presented in this dissertation demonstrate particle lithography methods developed for fabricating arrays of organosilane nanostructures. Surfaces were designed for the selective deposition of polymers and nanoparticles to produce multicomponent nanopatterns. The approaches for surface patterning provide new directions for studying surface chemistry at the molecular-level, and have practical application for emerging photovoltaic thin film technologies. Atomic force microscopy (AFM) provides unique capabilities for molecular visualization and ultrasensitive measurements of surface properties with nanoscale resolution. Organosilane nanopatterns bearing different functionalities and chain lengths were characterized using AFM to gain insight on molecular organization and surface-assembly processes. Indirect magnetic modulation (IMM) is a new instrument configuration for force modulation AFM that was developed for investigating mechanical properties of materials. The principle of IMM is based on indirect oscillation of soft nonmagnetic cantilevers through the tip holder assembly, which contains magnetic materials. Imaging can be performed in either ambient or liquid environments. The driving frequency for tip vibration can be selected to enhance contrast in amplitude and phase images, which provides information on the elastic response of thin-film materials. Images acquired with IMM furnish nanoscale resolution views of the morphology and elastic response of organosilane nanostructures. The dampening effect of liquid imaging media on cantilever oscillation during IMM was investigated using a liquid sample cell. Organic photovoltaic (OPV) devices are promising alternatives to traditional silicon based solar cells. A major challenge for OPVs is the requirement for higher efficiencies, or better device performance. The nanoscale morphology and molecular organization of the donor/acceptor materials in the organic layer affects the conductivity of OPV devices. To improve efficiency, new fabrication methods must be developed that are capable of controlling the molecular structure of the donor/acceptor materials. Using particle lithography combined with contact printing, billions of periodic and uniform pillar nanostructures of polythiophene can be fabricated on the surface. The dimensions and spacing can be selectively tuned by using different size latex masks

Fabrication of nanostructured surfaces with well-defined chemistry using particle lithography

Natural self-assembly processes provide nanofabrication capabilities for designing surfaces with nanoscale control of surface chemistry and relative orientation of the nanomaterials on the surfaces. Particle lithography was used to produce periodic arrays of protein nanostructures. Monodisperse mesoparticles can be applied to rapidly prepare millions of uniform protein nanostructures on flat surfaces using the conventional benchtop chemistry steps of mixing, centrifuging, evaporation and drying. Nanopatterns of bovine serum albumin and staphylococcal protein A were produced with particle lithography. The immobilized proteins remain attached to the surface and form nanopatterns over micron areas corresponding to the thickness of a single layer of proteins. The morphology and diameter of the protein nanostructures are tunable by selecting the ratios of protein-to-particle and the diameters of spheres. Organosilane nanopatterns were fabricated using particle lithography combined with vapor deposition to regulate surface chemistry. Colloidal masks produced by particle lithography enable to control and direct the placement of nanoscopic residues of water for hydrosilation. Different geometries of silane nanostructures depend on the length of drying for particle masks. Organosilanes form covalent bonds with the surface through hydrolysis, which provide an excellent platform for further steps of chemical modification. The head groups of organosilane nanopatterns can be designed to generate spatial selectivity for electroless deposition of iron oxide and selective adsorption of gold nanoparticles. New imaging strategies using atomic force microscopy (AFM) were developed for mapping magnetic domains and elastic compliance at size regimes below 100 nm. The AFM-based imaging mode is referred to as magnetic sample modulation (MSM). The AFM tip serves as a force and motion sensor for mapping the vibrational response of magnetic nanomaterials. The information acquired from MSM images includes the distribution of individual magnetic domains as well as spectra of the characteristic resonance frequencies of the vibrating nanomaterials. Indirect magnetic modulation (IMM) based on indirect oscillation of soft nonmagnetic cantilevers was used to investigate elastic response of organosilane nanostructures. With the use of IMM, dynamic parameters of the driving frequencies and amplitude of the tip motion can be optimized to sensitively map the elastic response of samples