168 resultados para content analysis and indexing – thesauruses general terms


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Critical analysis and problem-solving skills are two graduate attributes that are important in ensuring that graduates are well equipped in working across research and practice settings within the discipline of psychology. Despite the importance of these skills, few psychology undergraduate programmes have undertaken any systematic development, implementation, and evaluation of curriculum activities to foster these graduate skills. The current study reports on the development and implementation of a tutorial programme designed to enhance the critical analysis and problem-solving skills of undergraduate psychology students. Underpinned by collaborative learning and problem-based learning, the tutorial programme was administered to 273 third year undergraduate students in psychology. Latent Growth Curve Modelling revealed that students demonstrated a significant linear increase in self-reported critical analysis and problem-solving skills across the tutorial programme. The findings suggest that the development of inquiry-based curriculum offers important opportunities for psychology undergraduates to develop critical analysis and problem-solving skills.

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The objective of this work is to determine the thermal stability and vibrational spectra of datolite CaBSiO4(OH) and relate these properties to the structure of the mineral. The thermal analysis of datolite shows a mass loss of 5.83% over a 700775 °C temperature range. This mass loss corresponds to 1 water (H2O) molecules pfu. A quantitative chemical analysis using electron probe was undertaken. The Raman spectrum of datolite is characterized by bands at 917 and 1077 cm−1 assigned to the symmetric stretching modes of BO and SiO tetrahedra. A very intense Raman band is observed at 3498 cm−1 assigned to the stretching vibration of the OH units in the structure of datolite. BOH out-of-plane vibrations are characterized by the infrared band at 782 cm−1. The vibrational spectra are based upon the structure of datolite based on sheets of four- and eight-membered rings of alternating SiO4 and BO3(OH) tetrahedra with the sheets bonded together by calcium atoms.

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Hitherto, the Malaconothridae contained Malaconothrus Berlese, 1904 and Trimalaconothrus Berlese, 1916, defined by the possession of one pre-tarsal claw (monodactyly) or by three claws (tridactyly) respectively. However, monodactyly is a convergent apomorphy within the Oribatida and an unreliable character for a classification. Therefore we undertook a phylogenetic analysis of 102 species as the basis for a taxonomic review of the Malaconothridae. We identified two major clades, equivalent to the genera Tyrphonothrus Knülle, 1957 and Malaconothrus. These genera are redefined. Trimala-conothrus becomes the junior subjective synonym of Malaconothrus. Some 42 species of Trimalaconothrus are recom-bined to Malaconothrus and 15 species to Tyrphonothrus. Homonyms created by the recombinations are rectified. The replacement name M. hammerae nom. nov. is proposed for M. angulatus Hammer, 1958, the junior homonym of M. an-gulatus (Willmann, 1931) and the replacement name M. luxtoni nom. nov. is proposed for M. scutatus Luxton, 1987, the junior homonym of M. scutatus Mihelč ič, 1959. Trimalaconothrus iteratus Subías, 2004 is an unnecessary replacement name and is a junior objective synonym of Malaconothrus longirostrum (Hammer 1966). Malaconothrus praeoccupatus Subías, 2004 is a junior objective synonym of M. machadoi Balogh & Mahunka, 1969. Malaconothrus obsessus (Subías, 2004), an unnecessary replacement name for Trimalaconothrus albulus Hammer 1966 sensu Tseng 1982, becomes an available name for what is in fact a previously-undescribed species of Malaconothrus. We describe four new species of Tyrphonothrus: T. gnammaensis sp. nov. from Western Australia, T. gringai sp. nov. and T. maritimus sp. nov. from New South Wales, and T. taylori sp. nov. from Queensland. We describe six new species of Malaconothrus: M. beecroftensis sp. nov., M. darwini sp. nov. M. gundungurra sp. nov. and M. knuellei sp. nov. from New South Wales, M. jowettae sp. nov. from Norfolk Island, and M. talaitae sp. nov. from Victoria.

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With an increased emphasis on genotyping of single nucleotide polymorphisms (SNPs) in disease association studies, the genotyping platform of choice is constantly evolving. In addition, the development of more specific SNP assays and appropriate genotype validation applications is becoming increasingly critical to elucidate ambiguous genotypes. In this study, we have used SNP specific Locked Nucleic Acid (LNA) hybridization probes on a real-time PCR platform to genotype an association cohort and propose three criteria to address ambiguous genotypes. Based on the kinetic properties of PCR amplification, the three criteria address PCR amplification efficiency, the net fluorescent difference between maximal and minimal fluorescent signals and the beginning of the exponential growth phase of the reaction. Initially observed SNP allelic discrimination curves were confirmed by DNA sequencing (n = 50) and application of our three genotype criteria corroborated both sequencing and observed real-time PCR results. In addition, the tested Caucasian association cohort was in Hardy-Weinberg equilibrium and observed allele frequencies were very similar to two independently tested Caucasian association cohorts for the same tested SNP. We present here a novel approach to effectively determine ambiguous genotypes generated from a real-time PCR platform. Application of our three novel criteria provides an easy to use semi-automated genotype confirmation protocol.

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The promise of ‘big data’ has generated a significant deal of interest in the development of new approaches to research in the humanities and social sciences, as well as a range of important critical interventions which warn of an unquestioned rush to ‘big data’. Drawing on the experiences made in developing innovative ‘big data’ approaches to social media research, this paper examines some of the repercussions for the scholarly research and publication practices of those researchers who do pursue the path of ‘big data’centric investigation in their work. As researchers import the tools and methods of highly quantitative, statistical analysis from the ‘hard’ sciences into computational, digital humanities research, must they also subscribe to the language and assumptions underlying such ‘scientificity’? If so, how does this affect the choices made in gathering, processing, analysing, and disseminating the outcomes of digital humanities research? In particular, is there a need to rethink the forms and formats of publishing scholarly work in order to enable the rigorous scrutiny and replicability of research outcomes?

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A cross-sectional survey was conducted, and the construct validity and reliability of the Brisbane Practice Environment Measure in an Australian sample of registered nurses were examined. Nurses were randomly selected from the database of an Australian nursing organization. The original 33 items of the Brisbane Practice Environment Measure were utilized to inform the psychometric properties using confirmatory factor analysis. The Cronbach's alpha was 0.938 for the total scale and ranged 0.6570.887 for the subscales. A five-factor structure of the measure was confirmed, χ2 = 944.622, (P < 0.01), χ2/d.f. ratio = 2.845, Tucker Lewis Index 0.929, Root Mean Square Error = 0.061 and Comparative Fit Index = 0.906. The selected 28 items of the measure proved reliable and valid in measuring effects of the practice environment upon Australian nurses. The implications are that regular measurement of the practice environment using these 28 items might assist in the development of strategies which might improve job satisfaction and retention of registered nurses in Australia.

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Currently, finite element analyses are usually done by means of commercial software tools. Accuracy of analysis and computational time are two important factors in efficiency of these tools. This paper studies the effective parameters in computational time and accuracy of finite element analyses performed by ANSYS and provides the guidelines for the users of this software whenever they us this software for study on deformation of orthopedic bone plates or study on similar cases. It is not a fundamental scientific study and only shares the findings of the authors about structural analysis by means of ANSYS workbench. It gives an idea to the readers about improving the performance of the software and avoiding the traps. The solutions provided in this paper are not the only possible solutions of the problems and in similar cases there are other solutions which are not given in this paper. The parameters of solution method, material model, geometric model, mesh configuration, number of the analysis steps, program controlled parameters and computer settings are discussed through thoroughly in this paper.

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A qualitative analysis of the expected dilatation strain field in the vicinity of an array of grain-boundary (GB) dislocations is presented. The analysis provides a basis for the prediction of the critical current densities (jc) across low-angle YBa2Cu3O7- (YBCO) GBs as a function of their energy. The introduction of the GB energy allows the extension of the analysis to high-angle GBs using established models which predict the GB energy as a function of misorientation angle. The results are compared to published data for jc across [001]-tilt YBCO GBs for the full range of misorientations, showing a good fit. Since the GB energy is directly related to the GB structure, the analysis may allow a generalization of the scaling behavior of jc with the GB energy. © 1995 The American Physical Society.

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An updated version, this excellent text is a timely addition to the library of any nurse researching in oncology or other settings where individuals’ quality of life must be understood. Health-related quality of life should be a central aspect of studies concerned with health and illness. Indeed, considerable evidence has recently emerged in oncology and other research settings that selfreported quality of life is of great prognostic significance and may be the most reliable predictor of subsequent morbidity and mortality. From a nursing perspective, it is also gratifying to note that novel therapy and other oncology studies increasingly recognize the importance of understanding patients’ subjective experiences of an intervention over time and to ascertain whether patients perceive that a new intervention makes a difference to their quality of life and treatment outcomes. Measurements of quality of life are now routine in clinical trials of chemotherapy drugs and are often considered the prime outcome of interest in the cost/benefit analyses of these treatments. The authors have extensive experience in qualityof- life assessment in cancer clinical trials, where most of the pioneering work into quality of life has been conducted. That said, many of the health-related qualityof- life issues discussed are common to many illnesses, and researchers outside of cancer should find the book equally helpful.

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Airport efficiency is important because it has a direct impact on customer safety and satisfaction and therefore the financial performance and sustainability of airports, airlines, and affiliated service providers. This is especially so in a world characterized by an increasing volume of both domestic and international air travel, price and other forms of competition between rival airports, airport hubs and airlines, and rapid and sometimes unexpected changes in airline routes and carriers. It also reflects expansion in the number of airports handling regional, national, and international traffic and the growth of complementary airport facilities including industrial, commercial, and retail premises. This has fostered a steadily increasing volume of research aimed at modeling and providing best-practice measures and estimates of airport efficiency using mathematical and econometric frontiers. The purpose of this chapter is to review these various methods as they apply to airports throughout the world. Apart from discussing the strengths and weaknesses of the different approaches and their key findings, the paper also examines the steps faced by researchers as they move through the modeling process in defining airport inputs and outputs and the purported efficiency drivers. Accordingly, the chapter provides guidance to those conducting empirical research on airport efficiency and serves as an aid for aviation regulators and airport operators among others interpreting airport efficiency research outcomes.

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Big Data presents many challenges related to volume, whether one is interested in studying past datasets or, even more problematically, attempting to work with live streams of data. The most obvious challenge, in a ‘noisy’ environment such as contemporary social media, is to collect the pertinent information; be that information for a specific study, tweets which can inform emergency services or other responders to an ongoing crisis, or give an advantage to those involved in prediction markets. Often, such a process is iterative, with keywords and hashtags changing with the passage of time, and both collection and analytic methodologies need to be continually adapted to respond to this changing information. While many of the data sets collected and analyzed are preformed, that is they are built around a particular keyword, hashtag, or set of authors, they still contain a large volume of information, much of which is unnecessary for the current purpose and/or potentially useful for future projects. Accordingly, this panel considers methods for separating and combining data to optimize big data research and report findings to stakeholders. The first paper considers possible coding mechanisms for incoming tweets during a crisis, taking a large stream of incoming tweets and selecting which of those need to be immediately placed in front of responders, for manual filtering and possible action. The paper suggests two solutions for this, content analysis and user profiling. In the former case, aspects of the tweet are assigned a score to assess its likely relationship to the topic at hand, and the urgency of the information, whilst the latter attempts to identify those users who are either serving as amplifiers of information or are known as an authoritative source. Through these techniques, the information contained in a large dataset could be filtered down to match the expected capacity of emergency responders, and knowledge as to the core keywords or hashtags relating to the current event is constantly refined for future data collection. The second paper is also concerned with identifying significant tweets, but in this case tweets relevant to particular prediction market; tennis betting. As increasing numbers of professional sports men and women create Twitter accounts to communicate with their fans, information is being shared regarding injuries, form and emotions which have the potential to impact on future results. As has already been demonstrated with leading US sports, such information is extremely valuable. Tennis, as with American Football (NFL) and Baseball (MLB) has paid subscription services which manually filter incoming news sources, including tweets, for information valuable to gamblers, gambling operators, and fantasy sports players. However, whilst such services are still niche operations, much of the value of information is lost by the time it reaches one of these services. The paper thus considers how information could be filtered from twitter user lists and hash tag or keyword monitoring, assessing the value of the source, information, and the prediction markets to which it may relate. The third paper examines methods for collecting Twitter data and following changes in an ongoing, dynamic social movement, such as the Occupy Wall Street movement. It involves the development of technical infrastructure to collect and make the tweets available for exploration and analysis. A strategy to respond to changes in the social movement is also required or the resulting tweets will only reflect the discussions and strategies the movement used at the time the keyword list is created — in a way, keyword creation is part strategy and part art. In this paper we describe strategies for the creation of a social media archive, specifically tweets related to the Occupy Wall Street movement, and methods for continuing to adapt data collection strategies as the movement’s presence in Twitter changes over time. We also discuss the opportunities and methods to extract data smaller slices of data from an archive of social media data to support a multitude of research projects in multiple fields of study. The common theme amongst these papers is that of constructing a data set, filtering it for a specific purpose, and then using the resulting information to aid in future data collection. The intention is that through the papers presented, and subsequent discussion, the panel will inform the wider research community not only on the objectives and limitations of data collection, live analytics, and filtering, but also on current and in-development methodologies that could be adopted by those working with such datasets, and how such approaches could be customized depending on the project stakeholders.

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Many health professionals in Vietnam have limited knowledge and experience in coordinating care for victims of Domestic Violence (DV). This qualitative study aimed to elicit the beliefs of nurses and doctors that are influencing the care of victims of DV. Data were collected by semistructured interviews with nineteen nurses and doctors. Data were analyzed by content analysis and organized by three main themes; behavioral beliefs, normative beliefs and control beliefs. The outcomes of this study will inform the development of intervention strategies that will enable health professionals to better respond to and manage care for women who experience domestic violence in Vietnam.

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