Relative stereociliary motion in a hair bundle opposes amplification at distortion frequencies

Direct gating of mechanoelectrical-transduction channels by mechanical force is a basic feature of hair cells that assures fast transduction and underpins the mechanical amplification of acoustic inputs. But the associated nonlinearity - the gating compliance - inevitably distorts signals. Because reducing distortion would make the ear a better detector, we sought mechanisms with that effect. Mimicking in vivo stimulation, we used stiff probes to displace individual hair bundles at physiological amplitudes and measured the coherence and phase of the relative stereociliary motions with a dual-beam differential interferometer. Although stereocilia moved coherently and in phase at the stimulus frequencies, large phase lags at the frequencies of the internally generated distortion products indicated dissipative relative motions. Tip links engaged these relative modes and decreased the coherence in both stimulated and free hair bundles. These results show that a hair bundle breaks into a highly dissipative serial arrangement of stereocilia at distortion frequencies, precluding their amplification.Comment: 33 pages in total, including the main article with one table and three figures, as well as the supplemental information that itself contains two figure

Radar Signal Processing for Interference Mitigation

It is necessary for radars to suppress interferences to near the noise level to achieve the best performance in target detection and measurements. In this dissertation work, innovative signal processing approaches are proposed to effectively mitigate two of the most common types of interferences: jammers and clutter. Two types of radar systems are considered for developing new signal processing algorithms: phased-array radar and multiple-input multiple-output (MIMO) radar. For phased-array radar, an innovative target-clutter feature-based recognition approach termed as Beam-Doppler Image Feature Recognition (BDIFR) is proposed to detect moving targets in inhomogeneous clutter. Moreover, a new ground moving target detection algorithm is proposed for airborne radar. The essence of this algorithm is to compensate for the ground clutter Doppler shift caused by the moving platform and then to cancel the Doppler-compensated clutter using MTI filters that are commonly used in ground-based radar systems. Without the need of clutter estimation, the new algorithms outperform the conventional Space-Time Adaptive Processing (STAP) algorithm in ground moving target detection in inhomogeneous clutter. For MIMO radar, a time-efficient reduced-dimensional clutter suppression algorithm termed as Reduced-dimension Space-time Adaptive Processing (RSTAP) is proposed to minimize the number of the training samples required for clutter estimation. To deal with highly heterogeneous clutter more effectively, we also proposed a robust deterministic STAP algorithm operating on snapshot-to-snapshot basis. For cancelling jammers in the radar mainlobe direction, an innovative jamming elimination approach is proposed based on coherent MIMO radar adaptive beamforming. When combined with mutual information (MI) based cognitive radar transmit waveform design, this new approach can be used to enable spectrum sharing effectively between radar and wireless communication systems. The proposed interference mitigation approaches are validated by carrying out simulations for typical radar operation scenarios. The advantages of the proposed interference mitigation methods over the existing signal processing techniques are demonstrated both analytically and empirically

Doctor of Philosophy

dissertationEach year in the United States, a quarter million cases of stroke are caused directly by atherosclerotic disease of the cervical carotid artery. This represents a significant portion of health care costs that could be avoided if high-risk carotid artery lesions could be detected early on in disease progression. There is mounting evidence that Magnetic Resonance Imaging of the carotid artery can better classify subjects who would benefit from interventions. Turbo Spin Echo sequences are a class of Magnetic Resonance Imaging sequences that provide a variety of tissue contrasts. While high resolution Turbo Spin Echo images have demonstrated important details of carotid artery morphology, it is evident that pulsatile blood and wall motion related to the cardiac cycle are still significant sources of image degradation. In addition, patient motion artifacts due to the relatively long scan times of Turbo Spin Echo sequences result in an unacceptable fraction of noninterpretable studies. This dissertation presents work done to detect and correct for types of voluntary and physiological patient motion

Three Dimensional Positron Annihilation Momentum Measurement Technique (3DPAMM) Applied to Measure Oxygen-Atom Defects in 6H Silicon Carbide

A three-dimensional Positron Annihilation Spectroscopy System (3DPASS) capable to simultaneously measure three-dimensional electron-positron (e--e+) momentum densities measuring photons derived from e--e+ annihilation events was designed and characterized. 3DPASS simultaneously collects a single data set of correlated energies and positions for two coincident annihilation photons using solid-state double-sided strip detectors (DSSD). Positions of photons were determined using an interpolation method which measures a figure-of-merit proportional to the areas of transient charges induced on both charge collection strips directly adjacent to the charge collection strips interacting with the annihilation photons. The subpixel resolution was measured for both double-sided strip detectors (DSSD) and quantified using a new method modeled after a Gaussian point-spread function with a circular aperture. Error associated with location interpolation within an intrinsic pixel in each of the DSSDs, the subpixel resolution, was on the order of ± 0.20 mm (this represents one-standard deviation). The subpixel resolution achieved was less than one twenty-fifth of the 25-mm2 square area of an intrinsic pixel created by the intersection of the DSSDs’ orthogonal charge collection strips. The 2D ACAR and CDBAR response for single-crystal copper and 6H silicon carbide (6H SiC) was compared with results in the literature. Two additional samples of 6H SiC were irradiated with 24 MeV O+ ions, one annealed and one un-annealed, and measured using 3DPASS. Three-dimensional momentum distributions with correlated energies and coincident annihilation photons’ positions were presented for all three 6H SiC samples. 3DPASS was used for the first experimental PAS measurement of the structure of oxygen defects in bulk 6H SiC

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest

Multimodal Image Fusion and Its Applications.

Image fusion integrates different modality images to provide comprehensive information of the image content, increasing interpretation capabilities and producing more reliable results. There are several advantages of combining multi-modal images, including improving geometric corrections, complementing data for improved classification, and enhancing features for analysis...etc. This thesis develops the image fusion idea in the context of two domains: material microscopy and biomedical imaging. The proposed methods include image modeling, image indexing, image segmentation, and image registration. The common theme behind all proposed methods is the use of complementary information from multi-modal images to achieve better registration, feature extraction, and detection performances. In material microscopy, we propose an anomaly-driven image fusion framework to perform the task of material microscopy image analysis and anomaly detection. This framework is based on a probabilistic model that enables us to index, process and characterize the data with systematic and well-developed statistical tools. In biomedical imaging, we focus on the multi-modal registration problem for functional MRI (fMRI) brain images which improves the performance of brain activation detection.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120701/1/yuhuic_1.pd