TDOA-Based Localization System with Narrow-band Signals

This paper gives a general overview of the challenges that arise in using narrow-band signals, such as GSM, for localisation based on the time properties of the signal. Specifically, synchronisation and retrieving of time information are addressed. We pursue two contributions, namely, analysis of achievable synchronisation precision and processing of narrowband signals that can enable localization down to a meter. Keywords-localization, narrow band signals, TOA, TDOA I.

Detecting offsets in GPS time series: first results from the Detection of Offsets in GPS Experiment

The accuracy of Global Positioning System (GPS) time series is degraded by the presence of offsets. To assess the effectiveness of methods that detect and remove these offsets, we designed and managed the Detection of Offsets in GPS Experiment. We simulated time series that mimicked realistic GPS data consisting of a velocity component, offsets, white and flicker noises (1/f spectrum noises) composed in an additive model. The data set was made available to the GPS analysis community without revealing the offsets, and several groups conducted blind tests with a range of detection approaches. The results show that, at present, manual methods (where offsets are hand picked) almost always give better results than automated or semi‒automated methods (two automated methods give quite similar velocity bias as the best manual solutions). For instance, the fifth percentile range (5% to 95%) in velocity bias for automated approaches is equal to 4.2 mm/year (most commonly ±0.4 mm/yr from the truth), whereas it is equal to 1.8 mm/yr for the manual solutions (most commonly 0.2 mm/yr from the truth). The magnitude of offsets detectable by manual solutions is smaller than for automated solutions, with the smallest detectable offset for the best manual and automatic solutions equal to 5 mm and 8 mm, respectively. Assuming the simulated time series noise levels are representative of real GPS time series, robust geophysical interpretation of individual site velocities lower than 0.2–0.4 mm/yr is therefore certainly not robust, although a limit of nearer 1 mm/yr would be a more conservative choice. Further work to improve offset detection in GPS coordinates time series is required before we can routinely interpret sub‒mm/yr velocities for single GPS stations.

Analysis of Band 4.1B in Integrin-Mediated Cell Adhesion and Signaling

Band 4.1B is a cytoskeletal adaptor protein that regulates various cellular behavior; however, the mechanisms by which Band 4.1B contributes to intracellular signaling are unclear. This project addresses in vivo and in vitro functions for Band 4.1B in integrin-mediated cell adhesion and signaling. Band 4.1B has been shown to bind to β8 integrin, although cooperative functions of these two proteins have not been determined. Here, functional links between β8 integrin and Band 4.1B were investigated using gene knockout strategies. Ablation of β8 integrin and Band 4.1B genes resulted in impaired cardiac morphogenesis, leading to embryonic lethality by E11.5. These embryos displayed malformation of the outflow tract that was likely linked to abnormal regulation of cardiac neural crest migration. These data indicate the importance of cooperative signaling between β8 integrin and Band 4.1B in cardiac development. The involvement of Band 4.1B in integrin-mediated cell adhesion and signaling was further demonstrated by studying its functional roles in vitro. Band 4.1B is highly expressed in the brain, but its signaling in astrocytes is not understood. Here, Band 4.1B was shown to promote cell spreading likely by interacting with β1 integrin via its band 4.1, ezrin, radixin, and moesin (FERM) domain in cell adhesions. In astrocytes, both Band 4.1B and β1 integrin were expressed in cell-ECM contact sites during early cell spreading. Exogenous expression of Band 4.1B, especially its FERM domain, enhanced cell spreading on fibronectin, an ECM ligand for β1 integrin. However, the increased cell spreading was prohibited by blocking β1 integrin. These findings suggest that Band 4.1B is crucial for early adhesion assembly and/or signaling that are mediated by β1 integrin. Collectively, this study was the first to establish Band 4.1B as a modulator of integrin-mediated adhesion and signaling.

HUMAN PROPHASE CHROMOSOME UNIQUE BAND SEQUENCES; DEFINITION, CHARACTERIZATION, AND APPLICATION (CYTOGENETICS, IMAGE PROCESSING)

Extensive experience with the analysis of human prophase chromosomes and studies into the complexity of prophase GTG-banding patterns have suggested that at least some prophase chromosomal segments can be accurately identified and characterized independently of the morphology of the chromosome as a whole. In this dissertation the feasibility of identifying and analyzing specified prophase chromosome segments was thus investigated as an alternative approach to prophase chromosome analysis based on whole chromosome recognition. Through the use of prophase idiograms at the 850-band-stage (FRANCKE, 1981) and a comparison system based on the calculation of cross-correlation coefficients between idiogram profiles, we have demonstrated that it is possible to divide the 24 human prophase idiograms into a set of 94 unique band sequences. Each unique band sequence has a banding pattern that is recognizable and distinct from any other non-homologous chromosome portion.^ Using chromosomes 11p and 16 thru 22 to demonstrate unique band sequence integrity at the chromosome level, we found that prophase chromosome banding pattern variation can be compensated for and that a set of unique band sequences very similar to those at the idiogram level can be identified on actual chromosomes.^ The use of a unique band sequence approach in prophase chromosome analysis is expected to increase efficiency and sensitivity through more effective use of available banding information. The use of a unique band sequence approach to prophase chromosome analysis is discussed both at the routine level by cytogeneticists and at an image processing level with a semi-automated approach to prophase chromosome analysis. ^