Optimization of the multiwavelength erbium-doped fiber laser in a unidirectional cavity without an isolator

A highly uniform multiwavelength erbium-doped fiber ring laser with an intracavity sine phase modulator is demonstrated. The flat output spectrum is achieved by optimizing the cavity structure, modulation amplitude, and frequency of the sine phase modulator. Fifteen lasing lines with wavelength spacing of 0.9 nm appear simultaneously and stably with power differences less than 2 dB and side-mode suppression ratio higher than 32 dB. In addition, the proposed cavity can support unidirectional operation without optical isolators. An output power difference of about 20 dB is realized between the counterclockwise and clockwise directions, which is almost independent of the pump power and lasing wavelengths. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

Response of linear, viscous damped systems to excitations having time-varying frequency

The response of linear, viscous damped systems to excitations having time-varying frequency is the subject of exact and approximate analyses, which are supplemented by an analog computer study of single degree of freedom system response to excitations having frequencies depending linearly and exponentially on time.

The technique of small perturbations and the methods of stationary phase and saddle-point integration, as well as a novel bounding procedure, are utilized to derive approximate expressions characterizing the system response envelope—particularly near resonances—for the general time-varying excitation frequency.

Descriptive measurements of system resonant behavior recorded during the course of the analog study—maximum response, excitation frequency at which maximum response occurs, and the width of the response peak at the half-power level—are investigated to determine dependence upon natural frequency, damping, and the functional form of the excitation frequency.

The laboratory problem of determining the properties of a physical system from records of its response to excitations of this class is considered, and the transient phenomenon known as “ringing” is treated briefly.

It is shown that system resonant behavior, as portrayed by the above measurements and expressions, is relatively insensitive to the specifics of the excitation frequency-time relation and may be described to good order in terms of parameters combining system properties with the time derivative of excitation frequency evaluated at resonance.

One of these parameters is shown useful for predicting whether or not a given excitation having a time-varying frequency will produce strong or subtle changes in the response envelope of a given system relative to the steady-state response envelope. The parameter is shown, additionally, to be useful for predicting whether or not a particular response record will exhibit the “ringing” phenomenon.

Technology for Single Cell Protein Analysis in Immunology and Cancer Prognostics

The first chapter of this thesis deals with automating data gathering for single cell microfluidic tests. The programs developed saved significant amounts of time with no loss in accuracy. The technology from this chapter was applied to experiments in both Chapters 4 and 5.

The second chapter describes the use of statistical learning to prognose if an anti-angiogenic drug (Bevacizumab) would successfully treat a glioblastoma multiforme tumor. This was conducted by first measuring protein levels from 92 blood samples using the DNA-encoded antibody library platform. This allowed the measure of 35 different proteins per sample, with comparable sensitivity to ELISA. Two statistical learning models were developed in order to predict whether the treatment would succeed. The first, logistic regression, predicted with 85% accuracy and an AUC of 0.901 using a five protein panel. These five proteins were statistically significant predictors and gave insight into the mechanism behind anti-angiogenic success/failure. The second model, an ensemble model of logistic regression, kNN, and random forest, predicted with a slightly higher accuracy of 87%.

The third chapter details the development of a photocleavable conjugate that multiplexed cell surface detection in microfluidic devices. The method successfully detected streptavidin on coated beads with 92% positive predictive rate. Furthermore, chambers with 0, 1, 2, and 3+ beads were statistically distinguishable. The method was then used to detect CD3 on Jurkat T cells, yielding a positive predictive rate of 49% and false positive rate of 0%.

The fourth chapter talks about the use of measuring T cell polyfunctionality in order to predict whether a patient will succeed an adoptive T cells transfer therapy. In 15 patients, we measured 10 proteins from individual T cells (~300 cells per patient). The polyfunctional strength index was calculated, which was then correlated with the patient's progress free survival (PFS) time. 52 other parameters measured in the single cell test were correlated with the PFS. No statistical correlator has been determined, however, and more data is necessary to reach a conclusion.

Finally, the fifth chapter talks about the interactions between T cells and how that affects their protein secretion. It was observed that T cells in direct contact selectively enhance their protein secretion, in some cases by over 5 fold. This occurred for Granzyme B, Perforin, CCL4, TNFa, and IFNg. IL- 10 was shown to decrease slightly upon contact. This phenomenon held true for T cells from all patients tested (n=8). Using single cell data, the theoretical protein secretion frequency was calculated for two cells and then compared to the observed rate of secretion for both two cells not in contact, and two cells in contact. In over 90% of cases, the theoretical protein secretion rate matched that of two cells not in contact.

Advanced Monte Carlo Simulation and Machine Learning for Frequency Domain Optical Coherence Tomography

Optical Coherence Tomography(OCT) is a popular, rapidly growing imaging technique with an increasing number of bio-medical applications due to its noninvasive nature. However, there are three major challenges in understanding and improving an OCT system: (1) Obtaining an OCT image is not easy. It either takes a real medical experiment or requires days of computer simulation. Without much data, it is difficult to study the physical processes underlying OCT imaging of different objects simply because there aren't many imaged objects. (2) Interpretation of an OCT image is also hard. This challenge is more profound than it appears. For instance, it would require a trained expert to tell from an OCT image of human skin whether there is a lesion or not. This is expensive in its own right, but even the expert cannot be sure about the exact size of the lesion or the width of the various skin layers. The take-away message is that analyzing an OCT image even from a high level would usually require a trained expert, and pixel-level interpretation is simply unrealistic. The reason is simple: we have OCT images but not their underlying ground-truth structure, so there is nothing to learn from. (3) The imaging depth of OCT is very limited (millimeter or sub-millimeter on human tissues). While OCT utilizes infrared light for illumination to stay noninvasive, the downside of this is that photons at such long wavelengths can only penetrate a limited depth into the tissue before getting back-scattered. To image a particular region of a tissue, photons first need to reach that region. As a result, OCT signals from deeper regions of the tissue are both weak (since few photons reached there) and distorted (due to multiple scatterings of the contributing photons). This fact alone makes OCT images very hard to interpret.

This thesis addresses the above challenges by successfully developing an advanced Monte Carlo simulation platform which is 10000 times faster than the state-of-the-art simulator in the literature, bringing down the simulation time from 360 hours to a single minute. This powerful simulation tool not only enables us to efficiently generate as many OCT images of objects with arbitrary structure and shape as we want on a common desktop computer, but it also provides us the underlying ground-truth of the simulated images at the same time because we dictate them at the beginning of the simulation. This is one of the key contributions of this thesis. What allows us to build such a powerful simulation tool includes a thorough understanding of the signal formation process, clever implementation of the importance sampling/photon splitting procedure, efficient use of a voxel-based mesh system in determining photon-mesh interception, and a parallel computation of different A-scans that consist a full OCT image, among other programming and mathematical tricks, which will be explained in detail later in the thesis.

Next we aim at the inverse problem: given an OCT image, predict/reconstruct its ground-truth structure on a pixel level. By solving this problem we would be able to interpret an OCT image completely and precisely without the help from a trained expert. It turns out that we can do much better. For simple structures we are able to reconstruct the ground-truth of an OCT image more than 98% correctly, and for more complicated structures (e.g., a multi-layered brain structure) we are looking at 93%. We achieved this through extensive uses of Machine Learning. The success of the Monte Carlo simulation already puts us in a great position by providing us with a great deal of data (effectively unlimited), in the form of (image, truth) pairs. Through a transformation of the high-dimensional response variable, we convert the learning task into a multi-output multi-class classification problem and a multi-output regression problem. We then build a hierarchy architecture of machine learning models (committee of experts) and train different parts of the architecture with specifically designed data sets. In prediction, an unseen OCT image first goes through a classification model to determine its structure (e.g., the number and the types of layers present in the image); then the image is handed to a regression model that is trained specifically for that particular structure to predict the length of the different layers and by doing so reconstruct the ground-truth of the image. We also demonstrate that ideas from Deep Learning can be useful to further improve the performance.

It is worth pointing out that solving the inverse problem automatically improves the imaging depth, since previously the lower half of an OCT image (i.e., greater depth) can be hardly seen but now becomes fully resolved. Interestingly, although OCT signals consisting the lower half of the image are weak, messy, and uninterpretable to human eyes, they still carry enough information which when fed into a well-trained machine learning model spits out precisely the true structure of the object being imaged. This is just another case where Artificial Intelligence (AI) outperforms human. To the best knowledge of the author, this thesis is not only a success but also the first attempt to reconstruct an OCT image at a pixel level. To even give a try on this kind of task, it would require fully annotated OCT images and a lot of them (hundreds or even thousands). This is clearly impossible without a powerful simulation tool like the one developed in this thesis.

Specklegram in a multiple-mode fiber and its dependence on longitudinal modes of the laser source

A specklegram in a multimode fiber (MMF) has successfully been used as a sensor for detecting external disturbance. Our experiments showed that the sensitivity in the sensor with a multiple longitudinal-mode laser as its source was much higher than that with a single longitudinal-mode laser. In addition, the near-field pattern observations indicated that the coupling between different transverse modes in the MMF is quite weak. Based on the experimental results, a theoretical model for the speckle formation is proposed, taking a bend-caused phase factor into consideration. It is shown in the theoretical analysis that the interferences between different longitudinal modes make a larger contribution to the specklegram signals. (C) 2007 Optical Society of America.

Repetition rate stabilization of the SBS Q-switched fiber laser by external injection

Repetition rate fluctuation is one of the main drawbacks of the low-threshold stimulated Brillouin scattering (SBS) Q-switched fiber laser. A method to stabilize the repetition rate is proposed in this paper by injecting a square-wave modulated light. It is measured experimentally that variance of the repetition rate can be improved from similar to 20% to similar to 1% of the period. It is also found that effectiveness of the method depends on modulation frequency and duty cycle of the injection. Its working mechanism is analyzed qualitatively. (C) 2009 Optical Society of America

The ionic basis of frequency selectivity in hair cells of the bullfrog's sacculus

Hair cells from the bull frog's sacculus, a vestibular organ responding to substrate-borne vibration, possess electrically resonant membrane properties which maximize the sensitivity of each cell to a particular frequency of mechanical input. The electrical resonance of these cells and its underlying ionic basis were studied by applying gigohm-seal recording techniques to solitary hair cells enzymatically dissociated from the sacculus. The contribution of electrical resonance to frequency selectivity was assessed from microelectrode recordings from hair cells in an excised preparation of the sacculus.

Electrical resonance in the hair cell is demonstrated by damped membrane-potential oscillations in response to extrinsic current pulses applied through the recording pipette. This response is analyzed as that of a damped harmonic oscillator. Oscillation frequency rises with membrane depolarization, from 80-160 Hz at resting potential to asymptotic values of 200-250 Hz. The sharpness of electrical tuning, denoted by the electrical quality factor, Q_e, is a bell-shaped function of membrane voltage, reaching a maximum value around eight at a membrane potential slightly positive to the resting potential.

In whole cells, three time-variant ionic currents are activated at voltages more positive than -60 to -50 mV; these are identified as a voltage-dependent, non-inactivating Ca current (I_ca), a voltage-dependent, transient K current (I_a), and a Ca-dependent K current (I_c). The C channel is identified in excised, inside-out membrane patches on the basis of its large conductance (130-200 pS), its selective permeability to Kover Na or Cl, and its activation by internal Ca ions and membrane depolarization. Analysis of open- and closed-lifetime distributions suggests that the C channel can assume at least two open and three closed kinetic states.

Exposing hair cells to external solutions that inhibit the Ca or C conductances degrades the electrical resonance properties measured under current-clamp conditions, while blocking the A conductance has no significant effect, providing evidence that only the Ca and C conductances participate in the resonance mechanism. To test the sufficiency of these two conductances to account for electrical resonance, a mathematical model is developed that describes I_ca, I_c, and intracellular Ca concentration during voltage-clamp steps. I_ca activation is approximated by a third-order Hodgkin-Huxley kinetic scheme. Ca entering the cell is assumed to be confined to a small submembrane compartment which contains an excess of Ca buffer; Ca leaves this space with first-order kinetics. The Ca- and voltage-dependent activation of C channels is described by a five-state kinetic scheme suggested by the results of single-channel observations. Parameter values in the model are adjusted to fit the waveforms of I_ca and I_c evoked by a series of voltage-clamp steps in a single cell. Having been thus constrained, the model correctly predicts the character of voltage oscillations produced by current-clamp steps, including the dependencies of oscillation frequency and Q_e on membrane voltage. The model shows quantitatively how the Ca and C conductances interact, via changes in intracellular Ca concentration, to produce electrical resonance in a vertebrate hair cell.

2W Yb-doped double-clad fiber superfluorescent source with 42 nm 3 dB bandwidth

The output spectrum of Yb-doped double-clad fiber superfluorescent source (SFS) is tailored by placing a broadband dichroic mirror in the pump end of conventional single-pass forward configuration, which constitutes double-pass forward configuration. The 3 dB bandwidth is increased from I I to 42 nm. A maximum output SFS power of 2.12 W and a slope efficiency of 43.2% are obtained. The double-clad fiber is 25 in and the pump power is adequate to saturate the fiber as far as the feedback-induced lasing appears. (c) 2004 Elsevier Ltd. All rights reserved.

Comparison of Yb-doped fiber laser with one-end and double-end pumping configuration

A high-power Ytterbium-doped fiber laser (YDFL) with homemade double clad fiber (DCF) is introduced in this paper. The output power characteristics of a linear cavity fiber laser have been studied theoretically by solving the rate equations and experimentally tested with single- and double-end-pumping configurations. When both ends of the fiber are pumped by two high-power laser diodes with a launched power of similar to 300 W each, a maximum CW output of 444 W is obtained with a slope efficiency of similar to 75%. (c) 2006 Elsevier Ltd. All rights reserved.

Efficient frequency upconversion emission in Er3+-doped novel strontium lead bismuth glass

Er3+ -doped strontium lead bismuth glass for developing upconversion lasers has been fabricated and characterized. The Judd-Ofelt intensity parameters Omega(1) (t = 2,4,6), calculated based on the experimental absorption spectrum and Judd-Ofelt theory, were found to be Omega(2) = 2.95 x 10(-20), Omega(4) = 0-91 X 10(-20), and Omega(6) = 0.36 x 10(-20) cm(2). Under 975 nm excitation, intense green and red emissions centered at 525, 546, and 657 nm, corresponding to the transitions H-2(11/2) --> I-4(15/2), S-4(3/2) I-4(15/2), and F-4(9/2) --> I-4(15/2) respectively were observed. The upconversion mechanisms are discussed based oil the energy matching and quadratic dependence on excitation power, and the dominant mechanisms are excited state absorption and energy transfer upconversion for the green and red emissions. The long-lived I-4(11/2) level is supposed to serve as the intermediate state responsible for the upconversion processes. (C) 2004 Published by Elsevier B.V.

Raman spectra of undoped and uranium doped CaF2 single crystals

Raman scattering experiments for nominally pure and uranium doped CaF2 single crystals were presented. In all crystals, the Raman active T_(2g) vibration mode of CaF2 was observed, whose frequency shift and full-width at half-maximum (FWHM) broadening correspond well with defects and impurities in CaF2 lattice. Additional Raman peaks develop in nominally pure CaF2 with high etch pits density and U^(6+):CaF2 crystals. Part of additional Raman peaks in the experimental results, which are assumed due to vibration modes from F- interstitials and vacancies, are in well agreement with the theoretical predications by employing the Green-function formulation.

beam-shaping microstructure optical fiber

Microstructure optical fiber with uniform intensity distribution of the fundamental mode is proposed. The design guide line and characteristics of this kind fiber are demonstrated. The relationship between refractive index profile and structure parameters is investigated. The mechanism of forming uniform fundamental mode in these fibers is analyzed.

Growth of excellent-quality Nd : LuVO4 single crystal and laser properties

High-quality Nd:LuVO4 single crystal was successfully grown by Czochralski method. The assessment of the crystalline quality by the chemical etching method and Conoscope image was reported. The absorption spectra from 300 to 1000 nm and emission spectra from 960 to 1450 nm of Nd: LuVO4 were measured. Laser performance was achieved with Nd:LUVO4 crystal for the transition of F-4(3/2) -> I-4(11/2) (corresponding wavelength 1065.8 nm) in an actively Q-switched operation, and the average output power reached 5.42 W at a pulse repetition frequency (PRF) of 40 kHz under pump power of 18 W, giving an optical conversion efficiency of 30.1%. The pulse energy and peak power reached 138 mu J and 16.2 kW at PRF of 25 kHz under pump power of 14.2 W, and the pulse duration was 8.5 ns. (c) 2005 Elsevier B.V. All rights reserved.

Building up a frequency stabilisation based on a wavemeter for a diode laser and characterisation for a digital mirror device for artificial potentials

It has built and characterised a laser and It has learned what each of the components does. It has been able to run the laser in single-mode and stabilised it around a desired setpoint thanks to a PID controller that It has programmed. It has established a communication between the PID controller programmed in LabVIEW and Arduino Due, the DAC that It has chosen after comparing it with another candidate. It has learned some basics of how the LightCrafter 4500 DMD works. The projected light is the composition of the lights of three LED’s, each of which has a certain on-time. The mirrors chose to be in on- or off-stages depending to the amount of intensity that we want for each colour.

Spectral measurement of diode lasers with a single-mode birefringent fibre

A new, and very simple spectrometer based on birefringent fiber is described. A resolution of 0.02 angstrom has been achieved, and the system has been used to measure diode laser chirp. A length of 10km of fiber would be sufficient to resolve single mode line widths.