Parylene Based Flexible Multifunctional Biomedical Probes And Their Applications

MEMS (Micro Electro Mechanical System) based flexible devices have been studied for decades, and they are rapidly being incorporated into modern society in various forms such as flexible electronics and wearable devices. Especially in neuroscience, flexible interfaces provide tremendous possibilities and opportunities to produce reliable, scalable and biocompatible instruments for better exploring neurotransmission and neurological disorders. Of all the types of biomedical instruments such as electroencephalography (EEG) and electrocorticography (ECoG), MEMS-based needle-shape probes have been actively studied in recent years due to their better spatial resolution, selectivity, and sensitivity in chronical invasive physiology monitoring. In order to address the inherent issue of invasiveness that causes tissue damage, research has been made on biocompatible materials, implanting methods and probe structural design. In this dissertation, different types of microfabricated probes for various applications are reviewed. General methods for some key fabrication steps include photolithography patterning, chemical vapor deposition, metal deposition and dry etching are covered in detail. Likewise, three major achievements, which aim to the tagets of flexibility, functionality and mechanical property are introduced and described in detail from chapter 3 to 5. The essential fabrication processes based on XeF2 isotropic silicon etching and parylene conformal deposition are covered in detail, and a set of characterization is summarized

LRF-Net: Learning Local Reference Frames for 3D Local Shape Description and Matching

The local reference frame (LRF) acts as a critical role in 3D local shape description and matching. However, most of existing LRFs are hand-crafted and suffer from limited repeatability and robustness. This paper presents the first attempt to learn an LRF via a Siamese network that needs weak supervision only. In particular, we argue that each neighboring point in the local surface gives a unique contribution to LRF construction and measure such contributions via learned weights. Extensive analysis and comparative experiments on three public datasets addressing different application scenarios have demonstrated that LRF-Net is more repeatable and robust than several state-of-the-art LRF methods (LRF-Net is only trained on one dataset). In addition, LRF-Net can significantly boost the local shape description and 6-DoF pose estimation performance when matching 3D point clouds.Comment: 28 pages, 14 figure

Sub-Ohmic spin-boson model with off-diagonal coupling: Ground state properties

We have carried out analytical and numerical studies of the spin-boson model in the sub-ohmic regime with the influence of both the diagonal and off-diagonal coupling accounted for via the Davydov D1 variational ansatz. While a second-order phase transition is known to be exhibited by this model in the presence of diagonal coupling only, we demonstrate the emergence of a discontinuous first order phase transition upon incorporation of the off-diagonal coupling. A plot of the ground state energy versus magnetization highlights the discontinuous nature of the transition between the isotropic (zero magnetization) state and nematic (finite magnetization) phases. We have also calculated the entanglement entropy and a discontinuity found at a critical coupling strength further supports the discontinuous crossover in the spin-boson model in the presence of off-diagonal coupling. It is further revealed via a canonical transformation approach that for the special case of identical exponents for the spectral densities of the diagonal and the off-diagonal coupling, there exists a continuous crossover from a single localized phase to doubly degenerate localized phase with differing magnetizations.Comment: 11 pages, 7 figure

Fuzzy Determination of Target Shifting Time and Torque Control of Shifting Phase for Dry Dual Clutch Transmission

Based on the independently developed five-speed dry dual clutch transmission (DDCT), the paper proposes the torque coordinating control strategy between engine and two clutches, which obtains engine speed and clutch transferred torque in the shifting process, adequately reflecting the driver intention and improving the shifting quality. Five-degree-of-freedom (DOF) shifting dynamics model of DDCT with single intermediate shaft is firstly established according to its physical characteristics. Then the quantitative control objectives of the shifting process are presented. The fuzzy decision of shifting time and the model-based torque coordinating control strategy are proposed and also verified by simulating under different driving intentions in up-/downshifting processes with the DCT model established on the MATLAB/Simulink. Simulation results validate that the shifting control algorithm proposed in this paper can not only meet the shifting quality requirements, but also adapt to the various shifting intentions, having a strong robustness