ABSTRACT
This paper presents a novel optofluidic Michelson interferometer based on droplet microfluidics used to create a droplet grating. The droplet grating is formed by a stream of plugs in the microchannel with constant refractive index variation. It has a real-time tunability in the grating period through varying the flow rates of the liquids and index variation via different combinations of liquids. The optofluidic Michelson interferometer is highly sensitive and is suitable for the measurement of biomedical and biochemical buffer solutions. The experimental results show that it has a sensitivity of 66.7 nm per refractive index unit (RIU) and a detection range of 0.086 RIU.
Subject(s)
Biosensing Techniques/instrumentation , Interferometry/instrumentation , Microfluidic Analytical Techniques/instrumentation , Optical Devices , Refractometry/instrumentation , Equipment Design , Equipment Failure AnalysisABSTRACT
This paper presents a two coupled oscillators model to describe the dynamics of a tuning fork with a probe attached. The two coupled oscillators are unbalanced only in their effective masses and the damping ratios. By applying a frequency domain system identification approach in experimental investigation of various probe attachment cases, a good accuracy of the model is demonstrated. The effectiveness of the model is further demonstrated in quantitative analysis of the noise performance and the sensitivity of force sensing with a tuning fork probe. Compared with existing models, the proposed model can more accurately characterize the dynamics of a tuning fork probe.
ABSTRACT
We present a multiple compartment, mammillary distributed-parameter model for capillary-tissue exchange, which can be implemented with dynamic contrast-enhanced imaging to study kinetic heterogeneity in tumors. The proposed n-compartment model consists of a vascular distributed-parameter compartment in direct exchange with a number (n - 1) of interstitial compartments. It is applied to a prostate tumor case study to illustrate the possible co-existence of two kinetically distinct compartments in the tumor, and the estimation of useful physiological parameters (such as perfusion, mean transit time, fractional volumes, and transfer and rate constants) associated with tissue microcirculation. The present model exhibits the convenient property of a separable impulse residue response function in time domain, which can be used to provide further insights and understanding on the physiological basis of tissue enhancement parameters commonly used for correlation studies with tumor histological diagnosis.
Subject(s)
Capillaries/physiopathology , Contrast Media/pharmacokinetics , Models, Cardiovascular , Neoplasms/blood supply , Neoplasms/physiopathology , Breast Neoplasms/blood supply , Breast Neoplasms/diagnosis , Breast Neoplasms/physiopathology , Humans , Image Enhancement/methods , Kinetics , Magnetic Resonance Imaging/methods , Male , Neoplasms/diagnosis , Prostatic Neoplasms/blood supply , Prostatic Neoplasms/diagnosis , Prostatic Neoplasms/physiopathology , Reproducibility of Results , Sensitivity and Specificity , Tissue Distribution , Tomography, X-Ray Computed/methodsABSTRACT
A robust backpropagation training algorithm with a dead zone scheme is used for the online tuning of the neuralnetwork (NN) tracking control system. This assures the convergence of the multilayered NN in the presence of disturbance. It is proved in this paper that the selection of a smaller range of the dead zone leads to a smaller estimate error of the NN, and hence a smaller tracking error of the NN tracking controller. The proposed algorithm is applied to a three-layered network with adjustable weights and a complete convergence proof is provided. The results can also be extended to the network with more hidden layers.