Interferometric tomography of continuous fields with incomplete projections

Interferometric tomography in the presence of an opaque object is investigated. The developed iterative algorithm does not need to augment the missing information. It is based on the successive reconstruction of the difference field, the difference between the object field to be reconstructed and its estimate, only in the difined region. The application of the algorithm results in stable convergence

Reconstruction of Strongly Refracting Asymmetric Fields from Interferometric Measurements.

A reconstruction method for strongly refracting, asymmetric refractive index fields from optical pathlength measurements has been developed, tested by numerical simulations, and successfully applied to experimental data. Fundamentally, the procedure is a computational inversion of a nonlinearPh.D.Mechanical engineeringUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/157706/1/8017228.pd

Systematic non-dimensional parametric investigation for the thermo-fluid dynamics of two-layered fluid systems

Fluid dynamics and heat transfer of immiscible two-layered fluid systems have been of great importance in a variety of industrial as well as extraterrestrial exploration applications. Control and optimization of such a liquid-liquid arrangement need complete understanding of complex synergistic phenomena, especially those induced by surface tension at the fluid interface. Previously-reported investigations for the natural and Marangoni convection of two-layered immiscible systems have been incoherent, having no systematic presentation based on the key dimensionless parameters that govern the flow. The paper here presents a rigorous scheme and the results of a non-dimensional analysis, which allows a systematic and coherent interpretation of the system flow. The approach leads to ten non-dimensional parameters to completely characterize the thermo-fluid dynamics under the hypothesis of flat non-deformable interface. The system for a set of dimensionless parameters can have five degrees of freedom in physical variables, with fifteen dimensional physical variables appearing in the governing equations. The effect and importance of each non-dimensional parameter have also been numerically analyzed in search of a further reduction of the parameters describing the phenomena. © 2012 Elsevier Ltd. All rights reserved

Interferometric Tomographic Measurement of an Instataneous Flow Field Under Adverse Environments

Measurement of an instantaneous flow field by interferometric tomography, that is, reconstruction of a three-dimensional refractive-index field from multi-directional projection data, has been conducted. In order to simulate the expected experimental arrangement at a wind tunnel, reconstructions are made from a restricted view angle less than 40 degrees and incomplete projections. In addition, appreciable ambient air and experimental setup disturbances are present. A new phase-stepping technique, based on a generalized phase-stepping approach of a four-bucket model, is applied for expeditious and accurate phase information extraction from projection interferograms under the harsh environments. Phase errors caused by the various disturbances, which can include ambient refractive-index change, optical component disturbance, hologram repositioning error, etc., are partially compensated with a linear corrective model. A new computational tomographic technique based on a series expansion approach was also utilized to efficiently deal with arbitrary boundary shapes and the continuous flow fields in reconstruction. The results of the preliminary investigation are encouraging; however, the technique needs to be further developed in the future through refinement of the approaches reported here and through hybridization with previously developed techniques. Keywords: interferometry, tomography, phase steppin

Automated Precision Localization of Peripherally Inserted Central Catheter Tip through Model-Agnostic Multi-Stage Networks

Peripherally inserted central catheters (PICCs) have been widely used as one of the representative central venous lines (CVCs) due to their long-term intravascular access with low infectivity. However, PICCs have a fatal drawback of a high frequency of tip mispositions, increasing the risk of puncture, embolism, and complications such as cardiac arrhythmias. To automatically and precisely detect it, various attempts have been made by using the latest deep learning (DL) technologies. However, even with these approaches, it is still practically difficult to determine the tip location because the multiple fragments phenomenon (MFP) occurs in the process of predicting and extracting the PICC line required before predicting the tip. This study aimed to develop a system generally applied to existing models and to restore the PICC line more exactly by removing the MFs of the model output, thereby precisely localizing the actual tip position for detecting its disposition. To achieve this, we proposed a multi-stage DL-based framework post-processing the PICC line extraction result of the existing technology. The performance was compared by each root mean squared error (RMSE) and MFP incidence rate according to whether or not MFCN is applied to five conventional models. In internal validation, when MFCN was applied to the existing single model, MFP was improved by an average of 45%. The RMSE was improved by over 63% from an average of 26.85mm (17.16 to 35.80mm) to 9.72mm (9.37 to 10.98mm). In external validation, when MFCN was applied, the MFP incidence rate decreased by an average of 32% and the RMSE decreased by an average of 65\%. Therefore, by applying the proposed MFCN, we observed the significant/consistent detection performance improvement of PICC tip location compared to the existing model.Comment: Subin Park and Yoon Ki Cha have contributed equally to this work as the co-first author. Kyung-Su Kim ([email protected]) and Myung Jin Chung ([email protected]) have contributed equally to this work as the co-corresponding autho

Blocking Microglial Proliferation by CSF-1R Inhibitor Does Not Alter the Neuroprotective Effects of Adoptive Regulatory T Cells in 3xTg Alzheimer’s Disease Mice

Alzheimer’s disease (AD) is a chronic neurodegenerative disease that causes cognitive impairment. Neuroinflammation induced by activated microglia exacerbates AD. Regulatory T cells (Tregs) play roles in limiting neuroinflammation by converting microglial polarization. Therefore, adoptive Treg therapy is considered an attractive option for neurodegenerative disorders. However, the mechanism underlying Treg therapy via microglial modulation is not fully understood. In this study, we sought to determine whether adoptively transferred Tregs were effective when microglia proliferation was inhibited by using GW2580, which is an inhibitor of CSF1R. We found that inhibition of microglial proliferation during Treg transfer did not alter the therapeutic effects of Tregs on cognitive deficits and the accumulation of Aβ and pTAU in 3xTg-AD mice. The expression of pro- and anti-inflammatory markers in the hippocampus of 3xTg mice showed that GW2580 did not affect the inhibition of neuroinflammation by Treg transfer. Additionally, adoptively transferred Tregs were commonly detected in the brain on day 7 after transfer and their levels decreased slowly over 100 days. Our findings suggest that adoptively transferred Tregs can survive longer than 100 days in the brain, suppressing microglial activation and thus alleviating AD pathology. The present study provides valuable evidence to support the prolonged efficacy of adoptive Treg therapy in AD