Measurement of ocular component contributions to residual astigmatism in adult human eyes

The aim of this study was to determine whether an ophthalmophakometric technique could offer a feasible means of investigating ocular component contributions to residual astigmatism in human eyes. Current opinion was gathered on the prevalence, magnitude and source of residual astigmatism. It emerged that a comprehensive evaluation of the astigmatic contributions of the eye's internal ocular surfaces and their respective axial separations (effectivity) had not been carried out to date. An ophthalmophakometric technique was developed to measure astigmatism arising from the internal ocular components. Procedures included the measurement of refractive error (infra-red autorefractometry), anterior corneal surface power (computerised video keratography), axial distances (A-scan ultrasonography) and the powers of the posterior corneal surface in addition to both surfaces of the crystalline lens (multi-meridional still flash ophthalmophakometry). Computing schemes were developed to yield the required biometric data. These included (1) calculation of crystalline lens surface powers in the absence of Purkinje images arising from its anterior surface, (2) application of meridional analysis to derive spherocylindrical surface powers from notional powers calculated along four pre-selected meridians, (3) application of astigmatic decomposition and vergence analysis to calculate contributions to residual astigmatism of ocular components with obliquely related cylinder axes, (4) calculation of the effect of random experimental errors on the calculated ocular component data. A complete set of biometric measurements were taken from both eyes of 66 undergraduate students. Effectivity due to corneal thickness made the smallest cylinder power contribution (up to 0.25DC) to residual astigmatism followed by contributions of the anterior chamber depth (up to 0.50DC) and crystalline lens thickness (up to 1.00DC). In each case astigmatic contributions were predominantly direct. More astigmatism arose from the posterior corneal surface (up to 1.00DC) and both crystalline lens surfaces (up to 2.50DC). The astigmatic contributions of the posterior corneal and lens surfaces were found to be predominantly inverse whilst direct astigmatism arose from the anterior lens surface. Very similar results were found for right versus left eyes and males versus females. Repeatability was assessed on 20 individuals. The ophthalmophakometric method was found to be prone to considerable accumulated experimental errors. However, these errors are random in nature so that group averaged data were found to be reasonably repeatable. A further confirmatory study was carried out on 10 individuals which demonstrated that biometric measurements made with and without cycloplegia did not differ significantly.

From postgraduate student to published writer:discourse variation and development in TESOL

This thesis is part of a project whose overall aim is to assist participants on an MSc TESOL course who wish to begin to publish articles in the field to do so. The project, which is undertaken within a naturalistic paradigm, has two intimately related and mutually constitutive strands: one descriptive, one interventionist. The descriptive strand consists of an analytical model of the TESOL article genre, and it is instantiated in this thesis. The interventionist strand consists of a series of pedagogic interactions and materials intended to assist project participants formulate a text suitable for publication within the target genre, and it is reported on in this thesis. I begin the thesis by looking in detail at the research approach which characterises the project. I then attempt to explain the situational context of the work and to position it within the context of other research in the areas of discourse community membership, academic genres, genre learning and academic enculturation. Having thus contextualised the work, I next attempt a detailed exploration of the problems of postgraduate students in TESOL when first attempting to write in the TESOL article genre: this exploration is undertaken from both a linguistic and a pedagogic perspective. Then in subsequent chapters, both a linguistic and a pedagogic response to these problems are proposed: the first consisting of an analytical model of the target genre, the second consisting of a series of pedagogic interactions and materials. The relationships between the two lines of response are also examined in some detail. Then in the final part of the thesis, I report feedback from the interventionist strand and attempt to conduct an evaluation of the whole project to date. Criteria for evaluation are proposed and examined in some detail in the context of the research approach of the project. The concluding chapter is a brief discussion of future directions for this work.

Waste to power

ABSTRACT: There has been a growing trend towards the use of biomass as a primary energy source, which now contributes over 54% of the European pulp and paper industry energy needs [1]. The remaining part comes from natural gas, which to a large extent serves as the major source of energy for numerous recovered fiber paper mills located in regions with limited available forest resources. The cost of producing electricity to drive paper machinery and generate heat for steam is increasing as world demand for fossil fuels increases. Additionally, recovered fiber paper mills are also significant producers of fibrous sludge and reject waste material that can contain high amounts of useful energy. Currently, a majority of these waste fractions is disposed of by landspreading, incineration, or landfill. Paper mills must also pay a gate fee to process their waste streams in this way and the result of this is a further increase in operating costs. This work has developed methods to utilize the waste fractions produced at recovered fiber paper mills for the onsite production of combined heat and power (CHP) using advanced thermal conversion methods (pyrolysis and gasification) that are well suited to relatively small scales of throughput. The electrical power created would either be used onsite to power the paper making process or alternatively exported to the national grid, and the surplus heat created could also be used onsite or exported to a local customer. The focus of this paper is to give a general overview of the project progress so far and will present the experimental results of the most successful thermal conversion trials carried out by this work to date. Application: The research provides both paper mills and energy providers with methodologies to condition their waste materials for conversion into useful energy. The research also opens up new markets for gasifier and pyrolysis equipment manufacturers and suppliers.

Survey and applications of standardized energy metrics to mobile networks

The energy consumption and the energy efficiency have become very important issue in optimizing the current as well as in designing the future telecommunications networks. The energy and power metrics are being introduced in order to enable assessment and comparison of the energy consumption and power efficiency of the telecommunications networks and other transmission equipment. The standardization of the energy and power metrics is a significant ongoing activity aiming to define the baseline energy and power metrics for the telecommunications systems. This article provides an up-to-date overview of the energy and power metrics being proposed by the various standardization bodies and subsequently adopted worldwide by the equipment manufacturers and the network operators. © Institut Télécom and Springer-Verlag 2012.and Springer-Verlag 2012.

From biomedical literature to knowledge:mining protein-protein interactions

To date, more than 16 million citations of published articles in biomedical domain are available in the MEDLINE database. These articles describe the new discoveries which accompany a tremendous development in biomedicine during the last decade. It is crucial for biomedical researchers to retrieve and mine some specific knowledge from the huge quantity of published articles with high efficiency. Researchers have been engaged in the development of text mining tools to find knowledge such as protein-protein interactions, which are most relevant and useful for specific analysis tasks. This chapter provides a road map to the various information extraction methods in biomedical domain, such as protein name recognition and discovery of protein-protein interactions. Disciplines involved in analyzing and processing unstructured-text are summarized. Current work in biomedical information extracting is categorized. Challenges in the field are also presented and possible solutions are discussed.

Linking performance outcomes to salesperson organizational citizenship behavior in an industrial sales setting

More than ever before, firms in the industrial marketplace are focusing on the contribution of the salesperson and selling role to organizational success. Considerable recent research shows that not only in-role but also extra-role behaviors-organizational citizenship behaviors (OCBs)-are important in modeling salesperson performance. Yet, to date little effort has focused on examining the impact of OCB on relevant performance outcomes. Employing a sample of 207 industrial field salespeople from two companies and industries across the United States, this study reveals differences in impact of OCB on four diverse performance outcome types. The findings are discussed in terms of managerial applicability to industrial sales organizations, and a resulting set of next research steps is presented.

A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty

Dynamically adaptive systems (DASs) are intended to monitor the execution environment and then dynamically adapt their behavior in response to changing environmental conditions. The uncertainty of the execution environment is a major motivation for dynamic adaptation; it is impossible to know at development time all of the possible combinations of environmental conditions that will be encountered. To date, the work performed in requirements engineering for a DAS includes requirements monitoring and reasoning about the correctness of adaptations, where the DAS requirements are assumed to exist. This paper introduces a goal-based modeling approach to develop the requirements for a DAS, while explicitly factoring uncertainty into the process and resulting requirements. We introduce a variation of threat modeling to identify sources of uncertainty and demonstrate how the RELAX specification language can be used to specify more flexible requirements within a goal model to handle the uncertainty. © 2009 Springer Berlin Heidelberg.

A simple Bayesian modelling approach to event extraction from Twitter

With the proliferation of social media sites, social streams have proven to contain the most up-to-date information on current events. Therefore, it is crucial to extract events from the social streams such as tweets. However, it is not straightforward to adapt the existing event extraction systems since texts in social media are fragmented and noisy. In this paper we propose a simple and yet effective Bayesian model, called Latent Event Model (LEM), to extract structured representation of events from social media. LEM is fully unsupervised and does not require annotated data for training. We evaluate LEM on a Twitter corpus. Experimental results show that the proposed model achieves 83% in F-measure, and outperforms the state-of-the-art baseline by over 7%.© 2014 Association for Computational Linguistics.

Learning to collaborate:a study of individual and organizational learning, and interorganizational relationships

This paper examines learning to collaborate in the context of industrial supply relationships. Evidence of collaboration, and individual and organizational learning, from an in-depth case study of a large organization and its relations with two key suppliers is discussed. Analytic methods developed to elicit such evidence and provide insights into learning processes and outcomes are presented. It is argued that it is possible for an organization and individuals to learn to develop resilient collaborative relationships, but this requires a more thorough consideration and understanding of issues such as trust, commitment and teamwork than has been typical to date. Suggestions for future practice and research are presented.

Stability and continuity of women's core beliefs and psychopathological symptoms from pregnancy to one year postpartum

Unhealthy core beliefs are theorized to be stable constructs throughout the life-span, but no research to date, outside of the context of clinical intervention, has addressed this claim over a period of greater than 6 weeks. This study explores the stability and continuity of core beliefs and psychopathological symptoms in a group of women over a major life event and for 1 year subsequently. Eighty-seven women completed measures assessing their core beliefs and psychopathological symptoms during pregnancy and at 6 and 12 months after giving birth. General maternal psychopathological symptoms significantly decreased across the group between pregnancy and 6 months postpartum, and between pregnancy and 1 year, but showed evidence of stability in the ranks of individuals across time. The majority of core beliefs remained both stable and continuous throughout this period of major transition. These findings generally support the theoretical contention that core beliefs are relatively stable and continuous self-constructs. Science+Business Media, LLC.

Evolution, recurrency and kernels in learning to model inflation

This paper provides the most fully comprehensive evidence to date on whether or not monetary aggregates are valuable for forecasting US inflation in the early to mid 2000s. We explore a wide range of different definitions of money, including different methods of aggregation and different collections of included monetary assets. We use non-linear, artificial intelligence techniques, namely, recurrent neural networks, evolution strategies and kernel methods in our forecasting experiment. In the experiment, these three methodologies compete to find the best fitting US inflation forecasting models and are then compared to forecasts from a naive random walk model. The best models were non-linear autoregressive models based on kernel methods. Our findings do not provide much support for the usefulness of monetary aggregates in forecasting inflation. There is evidence in the literature that evolutionary methods can be used to evolve kernels hence our future work should combine the evolutionary and kernel methods to get the benefits of both.

Challenges in teaching English to young learners:global perspectives and local realities

Drawing on data from a recent research international research project, this article focuses on the challenges faced by teachers of English to young learners against the backdrop of the global rise of English. A mixed-methods approach was used to obtain the data, including a survey, which was completed by 4,459 teachers worldwide, and case studies, including observations and interviews with teachers, in five different primary schools in five different countries. A number of challenges emerged as affecting large numbers of teachers in different educational contexts, namely, teaching speaking, motivation, differentiating learning, teaching large classes, discipline, teaching writing, and teaching grammar. Importantly, some of these challenges have not been highlighted in the literature on young learner teaching to date. Other challenges are more localised, such as developing teachers' English competence. The article argues that teacher education should focus less on introducing teachers to general approaches to English language teaching and more on supporting teachers to meet the challenges that they have identified.

Improving T cell-induced response to subunit vaccines:opportunities for a proteomic systems approach

Prophylactic vaccines are an effective strategy to prevent development of many infectious diseases. With new and re-emerging infections posing increasing risks to food stocks and the health of the population in general, there is a need to improve the rationale of vaccine development. One key challenge lies in development of an effective T cell-induced response to subunit vaccines at specific sites and in different populations. Objectives: In this review, we consider how a proteomic systems-based approach can be used to identify putative novel vaccine targets, may be adopted to characterise subunit vaccines and adjuvants fully. Key findings: Despite the extensive potential for proteomics to aid our understanding of subunit vaccine nature, little work has been reported on identifying MHC 1-binding peptides for subunit vaccines generating T cell responses in the literature to date. Summary: In combination with predictive and structural biology approaches to mapping antigen presentation, proteomics offers a powerful and as yet un-tapped addition to the armoury of vaccine discovery to predict T-cell subset responses and improve vaccine design strategies.

The Complex Unified Evolutionary Approach to the Creation of the Multilevel Distributed Control System of a Gas-transport Company

The objects of a large-scale gas-transport company (GTC) suggest a complex unified evolutionary approach, which covers basic building concepts, up-to-date technologies, models, methods and means that are used in the phases of design, adoption, maintenance and development of the multilevel automated distributed control systems (ADCS).. As a single methodological basis of the suggested approach three basic Concepts, which contain the basic methodological principles and conceptual provisions on the creation of distributed control systems, were worked out: systems of the lower level (ACS of the technological processes based on up-to-date SCADA), of the middle level (ACS of the operative-dispatch production control based on MES-systems) and of the high level (business process control on the basis of complex automated systems ERP).

Introduction to performance improvement management software (PIM-DEA)

This chapter provides information on the use of Performance Improvement Management Software (PIMDEA). This advanced DEA software enables users to make the best possible analysis of the data, using the latest theoretical developments in Data Envelopment Analysis (DEA). PIM-DEA software gives full capacity to assess efficiency and productivity, set targets, identify benchmarks, and much more, allowing users to truly manage the performance of organizational units. PIM-DEA is easy to use and powerful, and it has an extensive range of the most up-to-date DEA models and which can handle large sets of data.