Flux closure vortexlike domain structures in ferroelectric thin films

Enhanced piezoresponse force microscopy was used to study flux closure vortexlike structures of 90° ferroelastic domains at the nanoscale in thin ferroelectric lead zirconium titanate (PZT) films. Using an external electric field, a vortexlike structure was induced far away from a grain boundary, indicating that physical edges are not necessary for nucleation contrary to previous suggestions. We demonstrate two different configurations of vortexlike structures, one of which has not been observed before. The stability of these structures is found to be size dependent, supporting previous predictions. © 2010 The American Physical Society.

Engineered discoidin domain from factor VIII binds αvβ3 integrin with antibody-like affinity

Alternative scaffolds are non-antibody proteins that can be engineered to bind new targets. They have found useful niches in the therapeutic space due to their smaller size and the ease with which they can be engineered to be bispecific. We sought a new scaffold that could be used for therapeutic ends and chose the C2 discoidin domain of factor VIII, which is well studied and of human origin. Using yeast surface display, we engineered the C2 domain to bind to αvβ3 integrin with a 16 nM affinity while retaining its thermal stability and monomeric nature. We obtained a crystal structure of the engineered domain at 2.1 Å resolution. We have christened this discoidin domain alternative scaffold the “discobody.”

Digital holographic interferometry and the angular spectrum method applied to measuring the domain inversion in ferroelectric crystal

The application of digital holographic interferometry on the quantitative measurement of the domain inversion in a RuO2: LiNbO3 crystal wafer is presented. The recorded holograms are reconstructed by the angular spectrum method. From the reconstructed phase distribution we can clearly observe the boundary between the inverted and un-inverted domain regions. Comparisons with the results reconstructed by use of the Fresnel transform method are given. Factors that influence the measurement include the spectrum filter size and the spectrum movement are discussed. The spectrum filter size has an effect on the measurement of the details. Although the spectrum movement affects every single reconstructed image, it has no influence on the final measurement.

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.

Single domain YBCO/Ag bulk superconductors fabricated by seeded infiltration and growth

We have applied the seeded infiltration and growth (IG) technique to the processing of samples containing Ag in an attempt to fabricate Ag-doped Y-Ba-Cu-O (YBCO) bulk superconductors with enhanced mechanical properties. The IG technique has been used successfully to grow bulk Ag-doped YBCO superconductors of up to 25 mm in diameter in the form of single grains. The distribution of Ag in the parent Y-123 matrix fabricated by the IG technique is observed to be at least as uniform as that in samples grown by conventional top seeded melt growth (TSMG). Fine Y-211 particles were observed to be embedded within the Y-123 matrix for the IG processed samples, leading to a high critical current density, Jc, of over 70 kA/cm2 at 77.3 K in self-field. The distribution of Y-211 in the IG sample microstructure, however, is inhomogeneous, which leads to a variation in the spatial distribution of Jc throughout the bulk matrix. A maximum-trapped field of around 0.43 T at 1.2 mm above the sample surface (i.e. including 0.7 mm for the sensor mould thickness) is observed at liquid nitrogen temperature, despite the relatively small grain size of the sample (20 mm diameter × 7 mm thickness). © 2008 IOP Publishing Ltd.

Evolution of phenylalanyl-tRNA synthetase by domain losing

The gene duplication, fusion and horizontal transfer are the frequent events during evolution of many proteins, including the aminoacyl-tRNA synthetases (AARSs). However, in this work, it was shown that the main event during evolution of phenylalanyl-tRNA synthetase (PheRS) is a domain loss, and the function/activity of PheRS is not affected by domain losing. Generally, the size of genome and number of genes are increased during evolution from bacteria to eukaryote, but the interesting thing is that the type and number of PheRS domains in eukaryotae are obviously less than those in bacteria. The evolution of PheRS by domain losing seems to be related to the functional evolution of some AARSs from the multiple specificities to the single specificity.

On the generality of crowding: visual crowding in size, saturation, and hue compared to orientation.

Perception of peripherally viewed shapes is impaired when surrounded by similar shapes. This phenomenon is commonly referred to as "crowding". Although studied extensively for perception of characters (mainly letters) and, to a lesser extent, for orientation, little is known about whether and how crowding affects perception of other features. Nevertheless, current crowding models suggest that the effect should be rather general and thus not restricted to letters and orientation. Here, we report on a series of experiments investigating crowding in the following elementary feature dimensions: size, hue, and saturation. Crowding effects in these dimensions were benchmarked against those in the orientation domain. Our primary finding is that all features studied show clear signs of crowding. First, identification thresholds increase with decreasing mask spacing. Second, for all tested features, critical spacing appears to be roughly half the viewing eccentricity and independent of stimulus size, a property previously proposed as the hallmark of crowding. Interestingly, although critical spacings are highly comparable, crowding magnitude differs across features: Size crowding is almost as strong as orientation crowding, whereas the effect is much weaker for saturation and hue. We suggest that future theories and models of crowding should be able to accommodate these differences in crowding effects.

Vowel normalisation: Time-domain processing of the internal dynamics of speech

Human listeners can identify vowels regardless of speaker size, although the sound waves for an adult and a child speaking the ’same’ vowel would differ enormously. The differences are mainly due to the differences in vocal tract length (VTL) and glottal pulse rate (GPR) which are both related to body size. Automatic speech recognition machines are notoriously bad at understanding children if they have been trained on the speech of an adult. In this paper, we propose that the auditory system adapts its analysis of speech sounds, dynamically and automatically to the GPR and VTL of the speaker on a syllable-to-syllable basis. We illustrate how this rapid adaptation might be performed with the aid of a computational version of the auditory image model, and we propose that an auditory preprocessor of this form would improve the robustness of speech recognisers.

Investigation of DyBa2Cu3O7-d superconducting domains grown by the infiltration technique starting with small size Dy-211 particles

An infiltration and growth process is here used as an alternative to the classical top-seeded melt-textured growth process for the production of Dy-123 single-domains with finely dispersed small size Dy-211 particles. The starting materials are the 211-particles and a barium and copper rich liquid phase precursor. The infiltration and growth process allows for controlling both the spatial and size distribution of the 211-particles in the final superconducting 123-single-domain. The main parameters (set-ups, maximum processing temperature with respect to the peritectic temperature, nature of reactant, porosity of the 211-preform) of the infiltration and growth process are discussed. Moreover, different processes of chimie douce are shown in order to produce Dy-211 particles with controlled shape and size, particles that can be used as precursors for the infiltration and growth process. © 2005 IOP Publishing Ltd.

The effect of wind tunnel size on incident shock boundary layer in-teraction experiments

We examine the effects of varying the tunnel width to height ratio on the shock boundary layer interac-tion of an incident oblique shock with a turbulent boundary layer. The computational domain is a simpli-fied representation of typical wind tunnel experiments; the top wall of the tunnel is not modeled; only the flow conditions imposed by the shock are modeled on the top of the computational domain. A hy-pothesis of the expected effect of width to height ratio is presented and tested computationally. All flows are found to be three dimensional for the single shock strength range of width to height ratios considered. The effect of tunnel width is a function of the boundary layer thickness which decreases the effective width.

Investigation of mode characteristics for a square cavity with a pedestal by a three-dimensional finite-difference time-domain technique

Mode characteristics of a strongly confined square cavity suspended in air via a pedestal on the substrate are investigated by a three-dimensional finite-difference time-domain technique. The mode wavelengths and mode quality factors (Q factors) are calculated as the functions of the size of the pedestal and the slope angle 0 of the sidewalls of the square slab, respectively For the square slab with side length of 2 mu m, thickness of 0.2 mu m, and refractive index of 3.4, on a square pedestal with refractive index of 3.17, the Q factor of the whispering-gallery (WG)-like mode transverse-electric TE(3.5)o first increases with the side length b of the square pedestal and then quickly decreases as b > 0.4 mu m, but the Q factor of the WG-like mode TE(4.6)o drops down quickly as b > 0.2 mu m, owing to their different symmetries. The results indicate that the pedestal can also result in mode selection in the WG-like modes. In addition, the numerical results show that the Q factors decrease 50% as the slope angle of the sidewalls varies from 90 degrees to 80 degrees. The mode characteristics of WG-like modes in the square cavity with a rectangular pedestal are also discussed. The results show that the nonsquare pedestal largely degrades the WG-like modes. (c) 2006 Optical Society of America

A direct digital frequency synthesizer with fourth-order phase domain Delta Sigma noise shaper and 12-bit current-steering DAC

This paper presents a direct digital frequency synthesizer (DDFS) with a 16-bit accumulator, a fourth-order phase domain single-stage Delta Sigma interpolator, and a 300-MS/s 12-bit current-steering DAC based on the Q(2) Random Walk switching scheme. The Delta Sigma interpolator is used to reduce the phase truncation error and the ROM size. The implemented fourth-order single-stage Delta Sigma noise shaper reduces the effective phase bits by four and reduces the ROM size by 16 times. The DDFS prototype is fabricated in a 0.35-mu m CMOS technology with active area of 1.11 mm(2) including a 12-bit DAC. The measured DDFS spurious-free dynamic range (SFDR) is greater than 78 dB using a reduced ROM with 8-bit phase, 12-bit amplitude resolution and a size of 0.09 mm(2). The total power consumption of the DDFS is 200)mW with a 3.3-V power supply.

A direct digital frequency synthesizer with fourth-order phase domain Delta Sigma noise shaper and 12-bit current-steering DAC

This paper presents a direct digital frequency synthesizer (DDFS) with a 16-bit accumulator, a fourth-order phase domain single-stage Delta Sigma interpolator, and a 300-MS/s 12-bit current-steering DAC based on the Q(2) Random Walk switching scheme. The Delta Sigma interpolator is used to reduce the phase truncation error and the ROM size. The implemented fourth-order single-stage Delta Sigma noise shaper reduces the effective phase bits by four and reduces the ROM size by 16 times. The DDFS prototype is fabricated in a 0.35-mu m CMOS technology with active area of 1.11 mm(2) including a 12-bit DAC. The measured DDFS spurious-free dynamic range (SFDR) is greater than 78 dB using a reduced ROM with 8-bit phase, 12-bit amplitude resolution and a size of 0.09 mm(2). The total power consumption of the DDFS is 200)mW with a 3.3-V power supply.

Surface transformation and inversion domain boundaries in gallium nitride nanorods

Phase transformation and subdomain structure in [0001]-oriented gallium nitride (GaN) nanorods of different sizes are studied using molecular dynamics simulations. The analysis concerns the structure of GaN nanorods at 300 K without external loading. Calculations show that a transformation from wurtzite to a tetragonal structure occurs along {0110} lateral surfaces, leading to the formation of a six-sided columnar inversion domain boundary (IDB) in the [0001] direction of the nanorods. This structural configuration is similar to the IDB structure observed experimentally in GaN epitaxial layers. The transformation is significantly dependent on the size of the nanorods.

Lineage-specific domain fusion in the evolution of purine nucleotide cyclases in cyanobacteria

Cyclic nucleotides (both cAMP and cGMP) play extremely important roles in cyanobacteria, such as regulating heterocyst formation, respiration, or gliding. Catalyzing the formation of cAMP and cGMP from ATP and GTP is a group of functionally important enzymes named adenylate cyclases and guanylate cyclases, respectively. To understand their evolutionary patterns, in this study, we presented a systematic analysis of all the cyclases in cyanobacterial genomes. We found that different cyanobacteria had various numbers of cyclases in view of their remarkable diversities in genome size and physiology. Most of these cyclases exhibited distinct domain architectures, which implies the versatile functions of cyanobacterial cyclases. Mapping the whole set of cyclase domain architectures from diverse prokaryotic organisms to their phylogenetic tree and detailed phylogenetic analysis of cyclase catalytic domains revealed that lineage-specific domain recruitment appeared to be the most prevailing pattern contributing to the great variability of cyanobacterial cyclase domain architectures. However, other scenarios, such as gene duplication, also occurred during the evolution of cyanobacterial cyclases. Sequence divergence seemed to contribute to the origin of putative guanylate cyclases which were found only in cyanobacteria. In conclusion, the comprehensive survey of cyclases in cyanobacteria provides novel insight into their potential evolutionary mechanisms and further functional implications.