3D protein structure matching by patch signatures

For determining functionality dependencies between two proteins, both represented as 3D structures, it is an essential condition that they have one or more matching structural regions called patches. As 3D structures for proteins are large, complex and constantly evolving, it is computationally expensive and very time-consuming to identify possible locations and sizes of patches for a given protein against a large protein database. In this paper, we address a vector space based representation for protein structures, where a patch is formed by the vectors within the region. Based on our previews work, a compact representation of the patch named patch signature is applied here. A similarity measure of two patches is then derived based on their signatures. To achieve fast patch matching in large protein databases, a match-and-expand strategy is proposed. Given a query patch, a set of small k-sized matching patches, called candidate patches, is generated in match stage. The candidate patches are further filtered by enlarging k in expand stage. Our extensive experimental results demonstrate encouraging performances with respect to this biologically critical but previously computationally prohibitive problem.

Binocular interaction:Contrast matching and contrast discrimination are predicted by the same model

How do signals from the 2 eyes combine and interact? Our recent work has challenged earlier schemes in which monocular contrast signals are subject to square-law transduction followed by summation across eyes and binocular gain control. Much more successful was a new 'two-stage' model in which the initial transducer was almost linear and contrast gain control occurred both pre- and post-binocular summation. Here we extend that work by: (i) exploring the two-dimensional stimulus space (defined by left- and right-eye contrasts) more thoroughly, and (ii) performing contrast discrimination and contrast matching tasks for the same stimuli. Twenty-five base-stimuli made from 1 c/deg patches of horizontal grating, were defined by the factorial combination of 5 contrasts for the left eye (0.3-32%) with five contrasts for the right eye (0.3-32%). Other than in contrast, the gratings in the two eyes were identical. In a 2IFC discrimination task, the base-stimuli were masks (pedestals), where the contrast increment was presented to one eye only. In a matching task, the base-stimuli were standards to which observers matched the contrast of either a monocular or binocular test grating. In the model, discrimination depends on the local gradient of the observer's internal contrast-response function, while matching equates the magnitude (rather than gradient) of response to the test and standard. With all model parameters fixed by previous work, the two-stage model successfully predicted both the discrimination and the matching data and was much more successful than linear or quadratic binocular summation models. These results show that performance measures and perception (contrast discrimination and contrast matching) can be understood in the same theoretical framework for binocular contrast vision. © 2007 VSP.

Measurement of key compositional parameters in two species of energy grass by Fourier transform infrared spectroscopy

Two energy grass species, switch grass, a North American tuft grass, and reed canary grass, a European native, are likely to be important sources of biomass in Western Europe for the production of biorenewable energy. Matching chemical composition to conversion efficiency is a primary goal for improvement programmes and for determining the quality of biomass feed-stocks prior to use and there is a need for methods which allow cost effective characterisation of chemical composition at high rates of sample through-put. In this paper we demonstrate that nitrogen content and alkali index, parameters greatly influencing thermal conversion efficiency, can be accurately predicted in dried samples of these species grown under a range of agronomic conditions by partial least square regression of Fourier transform infrared spectra (R2 values for plots of predicted vs. measured values of 0.938 and 0.937, respectively). We also discuss the prediction of carbon and ash content in these samples and the application of infrared based predictive methods for the breeding improvement of energy grasses.

Contrast matching and discrimation in human vision

The aim of this work was to investigate human contrast perception at various contrast levels ranging from detection threshold to suprathreshold levels by using psychophysical techniques. The work consists of two major parts. The first part deals with contrast matching, and the second part deals with contrast discrimination. Contrast matching technique was used to determine when the perceived contrasts of different stimuli were equal. The effects of spatial frequency, stimulus area, image complexity and chromatic contrast on contrast detection thresholds and matches were studied. These factors influenced detection thresholds and perceived contrast at low contrast levels. However, at suprathreshold contrast levels perceived contrast became directly proportional to the physical contrast of the stimulus and almost independent of factors affecting detection thresholds. Contrast discrimination was studied by measuring contrast increment thresholds which indicate the smallest detectable contrast difference. The effects of stimulus area, external spatial image noise and retinal illuminance were studied. The above factors affected contrast detection thresholds and increment thresholds measured at low contrast levels. At high contrast levels, contrast increment thresholds became very similar so that the effect of these factors decreased. Human contrast perception was modelled by regarding the visual system as a simple image processing system. A visual signal is first low-pass filtered by the ocular optics. This is followed by spatial high-pass filtering by the neural visual pathways, and addition of internal neural noise. Detection is mediated by a local matched filter which is a weighted replica of the stimulus whose sampling efficiency decreases with increasing stimulus area and complexity. According to the model, the signals to be compared in a contrast matching task are first transferred through the early image processing stages mentioned above. Then they are filtered by a restoring transfer function which compensates for the low-level filtering and limited spatial integration at high contrast levels. Perceived contrasts of the stimuli are equal when the restored responses to the stimuli are equal. According to the model, the signals to be discriminated in a contrast discrimination task first go through the early image processing stages, after which signal dependent noise is added to the matched filter responses. The decision made by the human brain is based on the comparison between the responses of the matched filters to the stimuli, and the accuracy of the decision is limited by pre- and post-filter noises. The model for human contrast perception could accurately describe the results of contrast matching and discrimination in various conditions.

Permanent matching of coupled optical bottle resonators with better than 0.16 GHz precision

The fabrication precision is one of the most critical challenges to the creation of practical photonic circuits composed of coupled high Q-factor microresonators. While very accurate transient tuning of microresonators based on local heating has been reported, the record precision of permanent resonance positioning achieved by post-processing is still within 1 and 5 GHz. Here we demonstrate two coupled bottle microresonators fabricated at the fiber surface with resonances that are matched with a better than 0.16 GHz precision. This corresponds to a better than 0.17 Å precision in the effective fiber radius variation. The achieved fabrication precision is only limited by the resolution of our optical spectrum analyzer and can be potentially improved by an order of magnitude.

Sediment accretion and organic carbon burial relative to sea-level rise and storm events in two mangrove forests in Everglades National Park

The goal of this investigation was to examine how sediment accretion and organic carbon (OC) burial rates in mangrove forests respond to climate change. Specifically, will the accretion rates keep pace with sea-level rise, and what is the source and fate of OC in the system? Mass accumulation, accretion and OC burial rates were determined via 210Pb dating (i.e. 100 year time scale) on sediment cores collected from two mangrove forest sites within Everglades National Park, Florida (USA). Enhanced mass accumulation, accretion and OC burial rates were found in an upper layer that corresponded to a well-documented storm surge deposit. Accretion rates were 5.9 and 6.5 mm yr− 1 within the storm deposit compared to overall rates of 2.5 and 3.6 mm yr− 1. These rates were found to be matching or exceeding average sea-level rise reported for Key West, Florida. Organic carbon burial rates were 260 and 393 g m− 2 yr− 1 within the storm deposit compared to 151 and 168 g m− 2 yr− 1 overall burial rates. The overall rates are similar to global estimates for OC burial in marine wetlands. With tropical storms being a frequent occurrence in this region the resulting storm surge deposits are an important mechanism for maintaining both overall accretion and OC burial rates. Enhanced OC burial rates within the storm deposit could be due to an increase in productivity created from higher concentrations of phosphorus within storm-delivered sediments and/or from the deposition of allochthonous OC. Climate change-amplified storms and sea-level rise could damage mangrove forests, exposing previously buried OC to oxidation and contribute to increasing atmospheric CO2 concentrations. However, the processes described here provide a mechanism whereby oxidation of OC would be limited and the overall OC reservoir maintained within the mangrove forest sediments.

Sediment Accretion and Organic Carbon Burial Relative to Sea-Level Rise and Storm Events in Two Mangrove Forests in Everglades National Park

The goal of this investigation was to examine how sediment accretion and organic carbon (OC) burial rates in mangrove forests respond to climate change. Specifically, will the accretion rates keep pace with sea-level rise, and what is the source and fate of OC in the system? Mass accumulation, accretion and OC burial rates were determined via 210Pb dating (i.e. 100 year time scale) on sediment cores collected from two mangrove forest sites within Everglades National Park, Florida (USA). Enhanced mass accumulation, accretion and OC burial rates were found in an upper layer that corresponded to a well-documented storm surge deposit. Accretion rates were 5.9 and 6.5 mm yr− 1 within the storm deposit compared to overall rates of 2.5 and 3.6 mm yr− 1. These rates were found to be matching or exceeding average sea-level rise reported for Key West, Florida. Organic carbon burial rates were 260 and 393 g m− 2 yr− 1 within the storm deposit compared to 151 and 168 g m− 2 yr− 1 overall burial rates. The overall rates are similar to global estimates for OC burial in marine wetlands. With tropical storms being a frequent occurrence in this region the resulting storm surge deposits are an important mechanism for maintaining both overall accretion and OC burial rates. Enhanced OC burial rates within the storm deposit could be due to an increase in productivity created from higher concentrations of phosphorus within storm-delivered sediments and/or from the deposition of allochthonous OC. Climate change-amplified storms and sea-level rise could damage mangrove forests, exposing previously buried OC to oxidation and contribute to increasing atmospheric CO2 concentrations. However, the processes described here provide a mechanism whereby oxidation of OC would be limited and the overall OC reservoir maintained within the mangrove forest sediments.

Novel double-sided linear generator for the wave energy conversion

The direct drive point absorber is a robust and efficient system for wave energy harvesting, where the linear generator represents the most complex part of the system. Therefore, its design and optimization are crucial tasks. The tubular shape of a linear generator’s magnetic circuit offers better permanent magnet flux encapsulation and reduction in radial forces on the translator due to its symmetry. A double stator topology can improve the power density of the linear tubular machine. Common designs employ a set of aligned stators on each side of a translator with radially magnetized permanent magnets. Such designs require doubling the amount of permanent magnet material and lead to an increase in the cogging force. The design presented in this thesis utilizes a translator with buried axially magnetized magnets and axially shifted positioning of the two stators such that no additional magnetic material, compared to single side machine, is required. In addition to the conservation of magnetic material, a significant improvement in the cogging force occurs in the two phase topology, while the double sided three phase system produces more power at the cost of a small increase in the cogging force. The analytical and the FEM models of the generator are described and their results compared to the experimental results. In general, the experimental results compare favourably with theoretical predictions. However, the experimentally observed permanent magnet flux leakage in the double sided machine is larger than predicted theoretically, which can be justified by the limitations in the prototype fabrication and resulting deviations from the theoretical analysis.

Reconfigurable Matching Networks for RF Amplifiers

This article presents applications of reconfigurable matching networks for RF amplifier design. Two possible solutions are given, one where the switching element is a PIN diode, and the other is based on graphene. Due to the fact that its conductivity depends on applied bias voltage, the graphene-based circuits can be used in microwave circuits as controllable elements. The structure of the proposed switch is very simple and it is particularly convenient for microstrip-based circuits. Because of that, a design of reconfigurable amplifier with the graphene-based switch is presented together with the one which has the PIN diode switch. Both amplifiers have the same specifications, and the one with the PIN diode switch is fabricated. The amplifier utilizing the PIN switch was used as a reference to make a comparison the two types of switches. Results of both amplifiers are very similar which indicates possible future applications of the graphene-based switch.

Leveraging Multiple Features for Image Retrieval and Matching

The goal of image retrieval and matching is to find and locate object instances in images from a large-scale image database. While visual features are abundant, how to combine them to improve performance by individual features remains a challenging task. In this work, we focus on leveraging multiple features for accurate and efficient image retrieval and matching. We first propose two graph-based approaches to rerank initially retrieved images for generic image retrieval. In the graph, vertices are images while edges are similarities between image pairs. Our first approach employs a mixture Markov model based on a random walk model on multiple graphs to fuse graphs. We introduce a probabilistic model to compute the importance of each feature for graph fusion under a naive Bayesian formulation, which requires statistics of similarities from a manually labeled dataset containing irrelevant images. To reduce human labeling, we further propose a fully unsupervised reranking algorithm based on a submodular objective function that can be efficiently optimized by greedy algorithm. By maximizing an information gain term over the graph, our submodular function favors a subset of database images that are similar to query images and resemble each other. The function also exploits the rank relationships of images from multiple ranked lists obtained by different features. We then study a more well-defined application, person re-identification, where the database contains labeled images of human bodies captured by multiple cameras. Re-identifications from multiple cameras are regarded as related tasks to exploit shared information. We apply a novel multi-task learning algorithm using both low level features and attributes. A low rank attribute embedding is joint learned within the multi-task learning formulation to embed original binary attributes to a continuous attribute space, where incorrect and incomplete attributes are rectified and recovered. To locate objects in images, we design an object detector based on object proposals and deep convolutional neural networks (CNN) in view of the emergence of deep networks. We improve a Fast RCNN framework and investigate two new strategies to detect objects accurately and efficiently: scale-dependent pooling (SDP) and cascaded rejection classifiers (CRC). The SDP improves detection accuracy by exploiting appropriate convolutional features depending on the scale of input object proposals. The CRC effectively utilizes convolutional features and greatly eliminates negative proposals in a cascaded manner, while maintaining a high recall for true objects. The two strategies together improve the detection accuracy and reduce the computational cost.

Nonlinear Optics and Carrier Dynamics in Nanostructured and Two-Dimensional Materials

Understanding and measuring the interaction of light with sub-wavelength structures and atomically thin materials is of critical importance for the development of next generation photonic devices.  One approach to achieve the desired optical properties in a material is to manipulate its mesoscopic structure or its composition in order to affect the properties of the light-matter interaction.  There has been tremendous recent interest in so called two-dimensional materials, consisting of only a single to a few layers of atoms arranged in a planar sheet.  These materials have demonstrated great promise as a platform for studying unique phenomena arising from the low-dimensionality of the material and for developing new types of devices based on these effects.  A thorough investigation of the optical and electronic properties of these new materials is essential to realizing their potential.  In this work we present studies that explore the nonlinear optical properties and carrier dynamics in nanoporous silicon waveguides, two-dimensional graphite (graphene), and atomically thin black phosphorus. We first present an investigation of the nonlinear response of nanoporous silicon optical waveguides using a novel pump-probe method. A two-frequency heterodyne technique is developed in order to measure the pump-induced transient change in phase and intensity in a single measurement. The experimental data reveal a characteristic material response time and temporally resolved intensity and phase behavior matching a physical model dominated by free-carrier effects that are significantly stronger and faster than those observed in traditional silicon-based waveguides.  These results shed light on the large optical nonlinearity observed in nanoporous silicon and demonstrate a new measurement technique for heterodyne pump-probe spectroscopy. Next we explore the optical properties of low-doped graphene in the terahertz spectral regime, where both intraband and interband effects play a significant role. Probing the graphene at intermediate photon energies enables the investigation of the nonlinear optical properties in the graphene as its electron system is heated by the intense pump pulse. By simultaneously measuring the reflected and transmitted terahertz light, a precise determination of the pump-induced change in absorption can be made. We observe that as the intensity of the terahertz radiation is increased, the optical properties of the graphene change from interband, semiconductor-like absorption, to a more metallic behavior with increased intraband processes. This transition reveals itself in our measurements as an increase in the terahertz transmission through the graphene at low fluence, followed by a decrease in transmission and the onset of a large, photo-induced reflection as fluence is increased.  A hybrid optical-thermodynamic model successfully describes our observations and predicts this transition will persist across mid- and far-infrared frequencies.  This study further demonstrates the important role that reflection plays since the absorption saturation intensity (an important figure of merit for graphene-based saturable absorbers) can be underestimated if only the transmitted light is considered. These findings are expected to contribute to the development of new optoelectronic devices designed to operate in the mid- and far-infrared frequency range.  Lastly we discuss recent work with black phosphorus, a two-dimensional material that has recently attracted interest due to its high mobility and direct, configurable band gap (300 meV to 2eV), depending on the number of atomic layers comprising the sample. In this work we examine the pump-induced change in optical transmission of mechanically exfoliated black phosphorus flakes using a two-color optical pump-probe measurement. The time-resolved data reveal a fast pump-induced transparency accompanied by a slower absorption that we attribute to Pauli blocking and free-carrier absorption, respectively. Polarization studies show that these effects are also highly anisotropic - underscoring the importance of crystal orientation in the design of optical devices based on this material. We conclude our discussion of black phosphorus with a study that employs this material as the active element in a photoconductive detector capable of gigahertz class detection at room temperature for mid-infrared frequencies.

Motion compensation with minimal residue dispersion matching criteria

Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnoloigia, 2016.

Optimization of Pattern Matching Algorithms for Multi- and Many-Core Platforms

Image and video compression play a major role in the world today, allowing the storage and transmission of large multimedia content volumes. However, the processing of this information requires high computational resources, hence the improvement of the computational performance of these compression algorithms is very important. The Multidimensional Multiscale Parser (MMP) is a pattern-matching-based compression algorithm for multimedia contents, namely images, achieving high compression ratios, maintaining good image quality, Rodrigues et al. [2008]. However, in comparison with other existing algorithms, this algorithm takes some time to execute. Therefore, two parallel implementations for GPUs were proposed by Ribeiro [2016] and Silva [2015] in CUDA and OpenCL-GPU, respectively. In this dissertation, to complement the referred work, we propose two parallel versions that run the MMP algorithm in CPU: one resorting to OpenMP and another that converts the existing OpenCL-GPU into OpenCL-CPU. The proposed solutions are able to improve the computational performance of MMP by 3 and 2:7 , respectively. The High Efficiency Video Coding (HEVC/H.265) is the most recent standard for compression of image and video. Its impressive compression performance, makes it a target for many adaptations, particularly for holoscopic image/video processing (or light field). Some of the proposed modifications to encode this new multimedia content are based on geometry-based disparity compensations (SS), developed by Conti et al. [2014], and a Geometric Transformations (GT) module, proposed by Monteiro et al. [2015]. These compression algorithms for holoscopic images based on HEVC present an implementation of specific search for similar micro-images that is more efficient than the one performed by HEVC, but its implementation is considerably slower than HEVC. In order to enable better execution times, we choose to use the OpenCL API as the GPU enabling language in order to increase the module performance. With its most costly setting, we are able to reduce the GT module execution time from 6.9 days to less then 4 hours, effectively attaining a speedup of 45 .