Novel approaches in nonlinear optical fibre-based signal processing

All-optical data processing is expected to play a major role in future optical communications. Nonlinear effects in optical fibres have many attractive features and a great, not yet fully explored potential in optical signal processing. Here, we overview our recent advances in developing novel techniques and approaches to all-optical processing based on optical fibre nonlinearities.

Recent developments in all-optical nonlinear signal processing for fiber-optic communications

All-optical data processing is expected to play a major role in future optical communications. Nonlinear effects in optical fibers have attractive applications in optical signal processing. In this paper, we review our recent advances in developing all-optical processing techniques at high speed based on optical fiber nonlinearities.

All-optical nonlinear fibre signal processing

All-optical technologies for data processing and signal manipulation are expected to play a major role in future optical communications. Nonlinear phenomena occurring in optical fibre have many attractive features and great, but not yet fully exploited potential in optical signal processing. Here, we overview our recent results and advances in developing novel photonic techniques and approaches to all-optical processing based on fibre nonlinearities. Amongst other topics, we will discuss phase-preserving optical 2R regeneration, the possibility of using parabolic/flat-top pulses for optical signal processing and regeneration, and nonlinear optical pulse shaping. A method for passive nonlinear pulse shaping based on pulse pre-chirping and propagation in a normally dispersive fibre will be presented. The approach provides a simple way of generating various temporal waveforms of fundamental and practical interest. Particular emphasis will be given to the formation and characterization of pulses with a triangular intensity profile. A new technique of doubling/copying optical pulses in both the frequency and time domains using triangular-shaped pulses will be also introduced.

Multimodal field data entry:performance and usability issues

Mobile technologies have yet to be widely adopted by the Architectural, Engineering, and Construction (AEC) industry despite being one of the major growth areas in computing in recent years. This lack of uptake in the AEC industry is likely due, in large part, to the combination of small screen size and inappropriate interaction demands of current mobile technologies. This paper discusses the scope for multimodal interaction design with a specific focus on speech-based interaction to enhance the suitability of mobile technology use within the AEC industry by broadening the field data input capabilities of such technologies. To investigate the appropriateness of using multimodal technology for field data collection in the AEC industry, we have developed a prototype Multimodal Field Data Entry (MFDE) application. This application, which allows concrete testing technicians to record quality control data in the field, has been designed to support two different modalities of data input speech-based data entry and stylus-based data entry. To compare the effectiveness or usability of, and user preference for, the different input options, we have designed a comprehensive lab-based evaluation of the application. To appropriately reflect the anticipated context of use within the study design, careful consideration had to be given to the key elements of a construction site that would potentially influence a test technician's ability to use the input techniques. These considerations and the resultant evaluation design are discussed in detail in this paper.

Approximation of Experimental Data by Bezier Curves

Very often the experimental data are the realization of the process, fully determined by some unknown function, being distorted by hindrances. Treatment and experimental data analysis are substantially facilitated, if these data to represent as analytical expression. The experimental data processing algorithm and the example of using this algorithm for spectrographic analysis of oncologic preparations of blood is represented in this article.

Technological innovation in electronic inventory solutions:an analysis of patent data

The purpose of this paper is to investigate the technological development of electronic inventory solutions from perspective of patent analysis. We first applied the international patent classification to classify the top categories of data processing technologies and their corresponding top patenting countries. Then we identified the core technologies by the calculation of patent citation strength and standard deviation criterion for each patent. To eliminate those core innovations having no reference relationships with the other core patents, relevance strengths between core technologies were evaluated also. Our findings provide market intelligence not only for the research and development community, but for the decision making of advanced inventory solutions.

Nonlinear pulse shaping in fibres for pulse generation and optical processing

The development of new all-optical technologies for data processing and signal manipulation is a field of growing importance with a strong potential for numerous applications in diverse areas of modern science. Nonlinear phenomena occurring in optical fibres have many attractive features and great, but not yet fully explored, potential in signal processing. Here, we review recent progress on the use of fibre nonlinearities for the generation and shaping of optical pulses and on the applications of advanced pulse shapes in all-optical signal processing. Amongst other topics, we will discuss ultrahigh repetition rate pulse sources, the generation of parabolic shaped pulses in active and passive fibres, the generation of pulses with triangular temporal profiles, and coherent supercontinuum sources. The signal processing applications will span optical regeneration, linear distortion compensation, optical decision at the receiver in optical communication systems, spectral and temporal signal doubling, and frequency conversion. © Copyright 2012 Sonia Boscolo and Christophe Finot.

Versioning of Granulated Data in Hierarchically Composed Workspaces

ACM Computing Classification System (1998): F.4.1.

VGI quality control

This paper presents a framework for considering quality control of volunteered geographic information (VGI). Different issues need to be considered during the conception, acquisition and post-acquisition phases of VGI creation. This includes items such as collecting metadata on the volunteer, providing suitable training, giving corrective feedback during the mapping process and use of control data, among others. Two examples of VGI data collection are then considered with respect to this quality control framework, i.e. VGI data collection by National Mapping Agencies and by the most recent Geo-Wiki tool, a game called Cropland Capture. Although good practices are beginning to emerge, there is still the need for the development and sharing of best practice, especially if VGI is to be integrated with authoritative map products or used for calibration and/or validation of land cover in the future.

Using overlay test to evaluate fracture properties of field-aged asphalt concrete

Field material testing provides firsthand information on pavement conditions which are most helpful in evaluating performance and identifying preventive maintenance or overlay strategies. High variability of field asphalt concrete due to construction raises the demand for accuracy of the test. Accordingly, the objective of this study is to propose a reliable and repeatable methodology to evaluate the fracture properties of field-aged asphalt concrete using the overlay test (OT). The OT is selected because of its efficiency and feasibility for asphalt field cores with diverse dimensions. The fracture properties refer to the Paris’ law parameters based on the pseudo J-integral (A and n) because of the sound physical significance of the pseudo J-integral with respect to characterizing the cracking process. In order to determine A and n, a two-step OT protocol is designed to characterize the undamaged and damaged behaviors of asphalt field cores. To ensure the accuracy of determined undamaged and fracture properties, a new analysis method is then developed for data processing, which combines the finite element simulations and mechanical analysis of viscoelastic force equilibrium and evolution of pseudo displacement work in the OT specimen. Finally, theoretical equations are derived to calculate A and n directly from the OT test data. The accuracy of the determined fracture properties is verified. The proposed methodology is applied to a total of 27 asphalt field cores obtained from a field project in Texas, including the control Hot Mix Asphalt (HMA) and two types of warm mix asphalt (WMA). The results demonstrate a high linear correlation between n and −log A for all the tested field cores. Investigations of the effect of field aging on the fracture properties confirm that n is a good indicator to quantify the cracking resistance of asphalt concrete. It is also indicated that summer climatic condition clearly accelerates the rate of aging. The impact of the WMA technologies on fracture properties of asphalt concrete is visualized by comparing the n-values. It shows that the Evotherm WMA technology slightly improves the cracking resistance, while the foaming WMA technology provides the comparable fracture properties with the HMA. After 15 months aging in the field, the cracking resistance does not exhibit significant difference between HMA and WMAs, which is confirmed by the observations of field distresses.

Integration of Satellite and Financial Data to Model Future Economic Impact of Citrus Crops (Final Project Report)

This study analyzed the health and overall landcover of citrus crops in Florida. The analysis was completed using Landsat satellite imagery available free of charge from the University of Maryland Global Landcover Change Facility. The project hypothesized that combining citrus production (economic) data with citrus area per county derived from spectral signatures would yield correlations between observable spectral reflectance throughout the year, and the fiscal impact of citrus on local economies. A positive correlation between these two data types would allow us to predict the economic impact of citrus using spectral data analysis to determine final crop harvests.

Data partitioning and replication management in distributed geographic information system (GIS) database

This research presents several components encompassing the scope of the objective of Data Partitioning and Replication Management in Distributed GIS Database. Modern Geographic Information Systems (GIS) databases are often large and complicated. Therefore data partitioning and replication management problems need to be addresses in development of an efficient and scalable solution. ^ Part of the research is to study the patterns of geographical raster data processing and to propose the algorithms to improve availability of such data. These algorithms and approaches are targeting granularity of geographic data objects as well as data partitioning in geographic databases to achieve high data availability and Quality of Service(QoS) considering distributed data delivery and processing. To achieve this goal a dynamic, real-time approach for mosaicking digital images of different temporal and spatial characteristics into tiles is proposed. This dynamic approach reuses digital images upon demand and generates mosaicked tiles only for the required region according to user's requirements such as resolution, temporal range, and target bands to reduce redundancy in storage and to utilize available computing and storage resources more efficiently. ^ Another part of the research pursued methods for efficient acquiring of GIS data from external heterogeneous databases and Web services as well as end-user GIS data delivery enhancements, automation and 3D virtual reality presentation. ^ There are vast numbers of computing, network, and storage resources idling or not fully utilized available on the Internet. Proposed "Crawling Distributed Operating System "(CDOS) approach employs such resources and creates benefits for the hosts that lend their CPU, network, and storage resources to be used in GIS database context. ^ The results of this dissertation demonstrate effective ways to develop a highly scalable GIS database. The approach developed in this dissertation has resulted in creation of TerraFly GIS database that is used by US government, researchers, and general public to facilitate Web access to remotely-sensed imagery and GIS vector information. ^

Statistical analysis and meta-analysis of microarray data

The microarray technology provides a high-throughput technique to study gene expression. Microarrays can help us diagnose different types of cancers, understand biological processes, assess host responses to drugs and pathogens, find markers for specific diseases, and much more. Microarray experiments generate large amounts of data. Thus, effective data processing and analysis are critical for making reliable inferences from the data. ^ The first part of dissertation addresses the problem of finding an optimal set of genes (biomarkers) to classify a set of samples as diseased or normal. Three statistical gene selection methods (GS, GS-NR, and GS-PCA) were developed to identify a set of genes that best differentiate between samples. A comparative study on different classification tools was performed and the best combinations of gene selection and classifiers for multi-class cancer classification were identified. For most of the benchmarking cancer data sets, the gene selection method proposed in this dissertation, GS, outperformed other gene selection methods. The classifiers based on Random Forests, neural network ensembles, and K-nearest neighbor (KNN) showed consistently god performance. A striking commonality among these classifiers is that they all use a committee-based approach, suggesting that ensemble classification methods are superior. ^ The same biological problem may be studied at different research labs and/or performed using different lab protocols or samples. In such situations, it is important to combine results from these efforts. The second part of the dissertation addresses the problem of pooling the results from different independent experiments to obtain improved results. Four statistical pooling techniques (Fisher inverse chi-square method, Logit method. Stouffer's Z transform method, and Liptak-Stouffer weighted Z-method) were investigated in this dissertation. These pooling techniques were applied to the problem of identifying cell cycle-regulated genes in two different yeast species. As a result, improved sets of cell cycle-regulated genes were identified. The last part of dissertation explores the effectiveness of wavelet data transforms for the task of clustering. Discrete wavelet transforms, with an appropriate choice of wavelet bases, were shown to be effective in producing clusters that were biologically more meaningful. ^

Identifying the Structure and Fate of Wastewater Derived Organic Micropollutants by High-resolution Mass Spectrometry

Human activities represent a significant burden on the global water cycle, with large and increasing demands placed on limited water resources by manufacturing, energy production and domestic water use. In addition to changing the quantity of available water resources, human activities lead to changes in water quality by introducing a large and often poorly-characterized array of chemical pollutants, which may negatively impact biodiversity in aquatic ecosystems, leading to impairment of valuable ecosystem functions and services. Domestic and industrial wastewaters represent a significant source of pollution to the aquatic environment due to inadequate or incomplete removal of chemicals introduced into waters by human activities. Currently, incomplete chemical characterization of treated wastewaters limits comprehensive risk assessment of this ubiquitous impact to water. In particular, a significant fraction of the organic chemical composition of treated industrial and domestic wastewaters remains uncharacterized at the molecular level. Efforts aimed at reducing the impacts of water pollution on aquatic ecosystems critically require knowledge of the composition of wastewaters to develop interventions capable of protecting our precious natural water resources.

The goal of this dissertation was to develop a robust, extensible and high-throughput framework for the comprehensive characterization of organic micropollutants in wastewaters by high-resolution accurate-mass mass spectrometry. High-resolution mass spectrometry provides the most powerful analytical technique available for assessing the occurrence and fate of organic pollutants in the water cycle. However, significant limitations in data processing, analysis and interpretation have limited this technique in achieving comprehensive characterization of organic pollutants occurring in natural and built environments. My work aimed to address these challenges by development of automated workflows for the structural characterization of organic pollutants in wastewater and wastewater impacted environments by high-resolution mass spectrometry, and to apply these methods in combination with novel data handling routines to conduct detailed fate studies of wastewater-derived organic micropollutants in the aquatic environment.

In Chapter 2, chemoinformatic tools were implemented along with novel non-targeted mass spectrometric analytical methods to characterize, map, and explore an environmentally-relevant “chemical space” in municipal wastewater. This was accomplished by characterizing the molecular composition of known wastewater-derived organic pollutants and substances that are prioritized as potential wastewater contaminants, using these databases to evaluate the pollutant-likeness of structures postulated for unknown organic compounds that I detected in wastewater extracts using high-resolution mass spectrometry approaches. Results showed that application of multiple computational mass spectrometric tools to structural elucidation of unknown organic pollutants arising in wastewaters improved the efficiency and veracity of screening approaches based on high-resolution mass spectrometry. Furthermore, structural similarity searching was essential for prioritizing substances sharing structural features with known organic pollutants or industrial and consumer chemicals that could enter the environment through use or disposal.

I then applied this comprehensive methodological and computational non-targeted analysis workflow to micropollutant fate analysis in domestic wastewaters (Chapter 3), surface waters impacted by water reuse activities (Chapter 4) and effluents of wastewater treatment facilities receiving wastewater from oil and gas extraction activities (Chapter 5). In Chapter 3, I showed that application of chemometric tools aided in the prioritization of non-targeted compounds arising at various stages of conventional wastewater treatment by partitioning high dimensional data into rational chemical categories based on knowledge of organic chemical fate processes, resulting in the classification of organic micropollutants based on their occurrence and/or removal during treatment. Similarly, in Chapter 4, high-resolution sampling and broad-spectrum targeted and non-targeted chemical analysis were applied to assess the occurrence and fate of organic micropollutants in a water reuse application, wherein reclaimed wastewater was applied for irrigation of turf grass. Results showed that organic micropollutant composition of surface waters receiving runoff from wastewater irrigated areas appeared to be minimally impacted by wastewater-derived organic micropollutants. Finally, Chapter 5 presents results of the comprehensive organic chemical composition of oil and gas wastewaters treated for surface water discharge. Concurrent analysis of effluent samples by complementary, broad-spectrum analytical techniques, revealed that low-levels of hydrophobic organic contaminants, but elevated concentrations of polymeric surfactants, which may effect the fate and analysis of contaminants of concern in oil and gas wastewaters.

Taken together, my work represents significant progress in the characterization of polar organic chemical pollutants associated with wastewater-impacted environments by high-resolution mass spectrometry. Application of these comprehensive methods to examine micropollutant fate processes in wastewater treatment systems, water reuse environments, and water applications in oil/gas exploration yielded new insights into the factors that influence transport, transformation, and persistence of organic micropollutants in these systems across an unprecedented breadth of chemical space.

Immunostimulatory effects of different aspects of aquaculture on the host response in the edible sea urchin, paracentrotus lividus

Aquaculture is a fast-growing industry contributing to global food security and sustainable aquaculture, which may reduce pressures on capture fisheries. The overall objective of this thesis was to look at the immunostimulatory effects of different aspects of aquaculture on the host response of the edible sea urchin, Paracentrotus lividus, which are a prized delicacy (roe) in many Asian and Mediterranean countries. In Chapter 1, the importance of understanding the biology, ecology, and physiology of P. lividus, as well as the current status in the culture of this organism for mass production and introducing the thesis objectives for following chapters is discussed. As the research commenced, the difficulties of identifying individuals for repeat sampling became clear; therefore, Chapter 2 was a tagging experiment that indicated PIT tagging was a successful way of identifying individual sea urchins over time with a high tag retention rate. However, it was also found that repeat sampling via syringe to measure host response of an individual caused stress which masked results and thus animals would be sampled and sacrificed going forward. Additionally, from personal observations and discussion with peers, it was suggested to look at the effect that diet has on sea urchin immune function and the parameters I measured which led to Chapter 3. In this chapter, both Laminaria digitata and Mytilus edulis were shown to influence measured immune parameters of differential cell counts, nitric oxide production, and lysozyme activity. Therefore, trials commencing after Trial 5 in Chapter 4, were modified to include starvation in order to remove any effect of diet. Another important aspect of culturing any organism is the study of their immune function and its response to several immunostimulatory agents (Chapter 4). Zymosan A was shown to be an effective immunostimulatory agent in P. lividus. Further work on handled/stored animals (Chapter 5) showed Zymosan A reduced the measured levels of some immune parameters measured relative to the control, which may reduce the amount of stress in the animals. In Chapter 6, animals were infected with Vibrio anguillarum and, although V. anguillarum, impacted immune parameters of P. lividus, it did not cause mortality as predicted. Lastly, throughout this thesis work, it was noted that the immune parameters measured produced different values at different times of the year (Chapter 7); therefore, using collated baseline (control) data, results were compiled to observe seasonal effects. It was determined that both seasonality and sourcing sites influenced immune parameter measurements taken at different times throughout the year. In conclusion, this thesis work fits into the framework of development of aquaculture practices that affect immune function of the host and future research focusing on the edible sea urchin, P. lividus.