930 resultados para seral stages
Resumo:
Suicide has drawn much attention from both the scientific community and the public. Examining the impact of socio-environmental factors on suicide is essential in developing suicide prevention strategies and interventions, because it will provide health authorities with important information for their decision-making. However, previous studies did not examine the impact of socio-environmental factors on suicide using a spatial analysis approach. The purpose of this study was to identify the patterns of suicide and to examine how socio-environmental factors impact on suicide over time and space at the Local Governmental Area (LGA) level in Queensland. The suicide data between 1999 and 2003 were collected from the Australian Bureau of Statistics (ABS). Socio-environmental variables at the LGA level included climate (rainfall, maximum and minimum temperature), Socioeconomic Indexes for Areas (SEIFA) and demographic variables (proportion of Indigenous population, unemployment rate, proportion of population with low income and low education level). Climate data were obtained from Australian Bureau of Meteorology. SEIFA and demographic variables were acquired from ABS. A series of statistical and geographical information system (GIS) approaches were applied in the analysis. This study included two stages. The first stage used average annual data to view the spatial pattern of suicide and to examine the association between socio-environmental factors and suicide over space. The second stage examined the spatiotemporal pattern of suicide and assessed the socio-environmental determinants of suicide, using more detailed seasonal data. In this research, 2,445 suicide cases were included, with 1,957 males (80.0%) and 488 females (20.0%). In the first stage, we examined the spatial pattern and the determinants of suicide using 5-year aggregated data. Spearman correlations were used to assess associations between variables. Then a Poisson regression model was applied in the multivariable analysis, as the occurrence of suicide is a small probability event and this model fitted the data quite well. Suicide mortality varied across LGAs and was associated with a range of socio-environmental factors. The multivariable analysis showed that maximum temperature was significantly and positively associated with male suicide (relative risk [RR] = 1.03, 95% CI: 1.00 to 1.07). Higher proportion of Indigenous population was accompanied with more suicide in male population (male: RR = 1.02, 95% CI: 1.01 to 1.03). There was a positive association between unemployment rate and suicide in both genders (male: RR = 1.04, 95% CI: 1.02 to 1.06; female: RR = 1.07, 95% CI: 1.00 to 1.16). No significant association was observed for rainfall, minimum temperature, SEIFA, proportion of population with low individual income and low educational attainment. In the second stage of this study, we undertook a preliminary spatiotemporal analysis of suicide using seasonal data. Firstly, we assessed the interrelations between variables. Secondly, a generalised estimating equations (GEE) model was used to examine the socio-environmental impact on suicide over time and space, as this model is well suited to analyze repeated longitudinal data (e.g., seasonal suicide mortality in a certain LGA) and it fitted the data better than other models (e.g., Poisson model). The suicide pattern varied with season and LGA. The north of Queensland had the highest suicide mortality rate in all the seasons, while there was no suicide case occurred in the southwest. Northwest had consistently higher suicide mortality in spring, autumn and winter. In other areas, suicide mortality varied between seasons. This analysis showed that maximum temperature was positively associated with suicide among male population (RR = 1.24, 95% CI: 1.04 to 1.47) and total population (RR = 1.15, 95% CI: 1.00 to 1.32). Higher proportion of Indigenous population was accompanied with more suicide among total population (RR = 1.16, 95% CI: 1.13 to 1.19) and by gender (male: RR = 1.07, 95% CI: 1.01 to 1.13; female: RR = 1.23, 95% CI: 1.03 to 1.48). Unemployment rate was positively associated with total (RR = 1.40, 95% CI: 1.24 to 1.59) and female (RR=1.09, 95% CI: 1.01 to 1.18) suicide. There was also a positive association between proportion of population with low individual income and suicide in total (RR = 1.28, 95% CI: 1.10 to 1.48) and male (RR = 1.45, 95% CI: 1.23 to 1.72) population. Rainfall was only positively associated with suicide in total population (RR = 1.11, 95% CI: 1.04 to 1.19). There was no significant association for rainfall, minimum temperature, SEIFA, proportion of population with low educational attainment. The second stage is the extension of the first stage. Different spatial scales of dataset were used between the two stages (i.e., mean yearly data in the first stage, and seasonal data in the second stage), but the results are generally consistent with each other. Compared with other studies, this research explored the variety of the impact of a wide range of socio-environmental factors on suicide in different geographical units. Maximum temperature, proportion of Indigenous population, unemployment rate and proportion of population with low individual income were among the major determinants of suicide in Queensland. However, the influence from other factors (e.g. socio-culture background, alcohol and drug use) influencing suicide cannot be ignored. An in-depth understanding of these factors is vital in planning and implementing suicide prevention strategies. Five recommendations for future research are derived from this study: (1) It is vital to acquire detailed personal information on each suicide case and relevant information among the population in assessing the key socio-environmental determinants of suicide; (2) Bayesian model could be applied to compare mortality rates and their socio-environmental determinants across LGAs in future research; (3) In the LGAs with warm weather, high proportion of Indigenous population and/or unemployment rate, concerted efforts need to be made to control and prevent suicide and other mental health problems; (4) The current surveillance, forecasting and early warning system needs to be strengthened, to trace the climate and socioeconomic change over time and space and its impact on population health; (5) It is necessary to evaluate and improve the facilities of mental health care, psychological consultation, suicide prevention and control programs; especially in the areas with low socio-economic status, high unemployment rate, extreme weather events and natural disasters.
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The increasing diversity of the Internet has created a vast number of multilingual resources on the Web. A huge number of these documents are written in various languages other than English. Consequently, the demand for searching in non-English languages is growing exponentially. It is desirable that a search engine can search for information over collections of documents in other languages. This research investigates the techniques for developing high-quality Chinese information retrieval systems. A distinctive feature of Chinese text is that a Chinese document is a sequence of Chinese characters with no space or boundary between Chinese words. This feature makes Chinese information retrieval more difficult since a retrieved document which contains the query term as a sequence of Chinese characters may not be really relevant to the query since the query term (as a sequence Chinese characters) may not be a valid Chinese word in that documents. On the other hand, a document that is actually relevant may not be retrieved because it does not contain the query sequence but contains other relevant words. In this research, we propose two approaches to deal with the problems. In the first approach, we propose a hybrid Chinese information retrieval model by incorporating word-based techniques with the traditional character-based techniques. The aim of this approach is to investigate the influence of Chinese segmentation on the performance of Chinese information retrieval. Two ranking methods are proposed to rank retrieved documents based on the relevancy to the query calculated by combining character-based ranking and word-based ranking. Our experimental results show that Chinese segmentation can improve the performance of Chinese information retrieval, but the improvement is not significant if it incorporates only Chinese segmentation with the traditional character-based approach. In the second approach, we propose a novel query expansion method which applies text mining techniques in order to find the most relevant words to extend the query. Unlike most existing query expansion methods, which generally select the highly frequent indexing terms from the retrieved documents to expand the query. In our approach, we utilize text mining techniques to find patterns from the retrieved documents that highly correlate with the query term and then use the relevant words in the patterns to expand the original query. This research project develops and implements a Chinese information retrieval system for evaluating the proposed approaches. There are two stages in the experiments. The first stage is to investigate if high accuracy segmentation can make an improvement to Chinese information retrieval. In the second stage, a text mining based query expansion approach is implemented and a further experiment has been done to compare its performance with the standard Rocchio approach with the proposed text mining based query expansion method. The NTCIR5 Chinese collections are used in the experiments. The experiment results show that by incorporating the text mining based query expansion with the hybrid model, significant improvement has been achieved in both precision and recall assessments.
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This paper argues that management education needs to consider a trend in learning design which advances creative learning through an alliance with art-based pedagogical processes. A shift is required from skills training to facilitating transformational learning through experiences that expand human potential, facilitated by artistic processes. This creative learning focus stems from a qualitative and quantitative analysis of an arts-based intervention for management development, called Management Jazz, conducted over three years at a large Australian University. The paper reviews some of the salient literature in the field, including an ‘Artful Learning Wave Trajectory’ Model. The Model considers four stages of the learning process: capacity, artful event, increased capability, and application/action to produce product. Methodology for the field-based research analysis of the intervention outcomes is presented. Three illustrative examples of arts-based learning are provided from the Management Jazz program. Finally, research findings indicate that artful learning opportunities enhance capacity for awareness of creativity in one’s self and in others, leading, through a transformative process, to enhanced leaders and managers. The authors conclude that arts-based management education can enhance creative capacity and develop managers and leaders for the 21st century business environment.
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Paropsis atomaria is a recently emerged pest of eucalypt plantations in subtropical Australia. Its broad host range of at least 20 eucalypt species and wide geographical distribution provides it the potential to become a serious forestry pest both within Australia and, if accidentally introduced, overseas. Although populations of P. atomaria are genetically similar throughout its range, population dynamics differ between regions. Here, we determine temperature-dependent developmental requirements using beetles sourced from temperate and subtropical zones by calculating lower temperature thresholds, temperature-induced mortality, and day-degree requirements. We combine these data with field mortality estimates of immature life stages to produce a cohort-based model, ParopSys, using DYMEX™ that accurately predicts the timing, duration, and relative abundance of life stages in the field and number of generations in a spring–autumn (September–May) field season. Voltinism was identified as a seasonally plastic trait dependent upon environmental conditions, with two generations observed and predicted in the Australian Capital Territory, and up to four in Queensland. Lower temperature thresholds for development ranged between 4 and 9 °C, and overall development rates did not differ according to beetle origin. Total immature development time (egg–adult) was approximately 769.2 ± S.E. 127.8 DD above a lower temperature threshold of 6.4 ± S.E. 2.6 °C. ParopSys provides a basic tool enabling forest managers to use the number of generations and seasonal fluctuations in abundance of damaging life stages to estimate the pest risk of P. atomaria prior to plantation establishment, and predict the occurrence and duration of damaging life stages in the field. Additionally, by using local climatic data the pest potential of P. atomaria can be estimated to predict the risk of it establishing if accidentally introduced overseas. Improvements to ParopSys’ capability and complexity can be made as more biological data become available.
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Denaturation of extracellular matrix proteins exposes cryptic binding sites. It is hypothesized that binding of cell adhesion receptors to these cryptic binding sites regulates cellular behaviour during tissue repair and regeneration. To test this hypothesis, we quantify the adhesion of pre-osteoblastic cells to native (Col) and partially-denatured (pdCol) collagen I using single-cell force spectroscopy. During early stages of cell attachment (≤180 s) pre-osteoblasts (MC3T3-E1) adhered significantly stronger to pdCol compared to Col. RGD (Arg-Gly-Asp)-containing peptides suppressed this elevated cell adhesion. We show that the RGD-binding α5β1- and αv-integrins mediated pre-osteoblast adhesion to pdCol, but not to Col. On pdCol pre-osteoblasts had a higher focal adhesion kinase tyrosine-phosphorylation level that correlated with enhanced spreading and motility. Moreover, pre-osteoblasts cultured on pdCol showed a pronounced matrix mineralization activity. Our data suggest that partially-denatured collagen exposes RGD-motifs that trigger binding of α5β1- and αv-integrins. These integrins initiate cellular processes that stimulate osteoblast adhesion, spreading, motility and differentiation. Taken together, these quantitative insights reveal an approach for the development of alternative collagen I- based surfaces for tissue engineering applications.
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Introduction The purpose of this study was to develop, implement and evaluate the impact of an educational intervention, comprising an innovative model of clinical decisionmaking and educational delivery strategy for facilitating nursing students‘ learning and development of competence in paediatric physical assessment practices. Background of the study Nursing students have an undergraduate education that aims to produce graduates of a generalist nature who demonstrate entry level competence for providing nursing care in a variety of health settings. Consistent with population morbidity and health care roles, paediatric nursing concepts typically form a comparatively small part of undergraduate curricula and students‘ exposure to paediatric physical assessment concepts and principles are brief. However, the nursing shortage has changed traditional nursing employment patterns and new graduates form the majority of the recruitment pool for paediatric nursing speciality staff. Paediatric nursing is a popular career choice for graduates and anecdotal evidence suggests that nursing students who select a clinical placement in their final year intend to seek employment in paediatrics upon graduation. Although concepts of paediatric nursing are included within undergraduate curriculum, students‘ ability to develop the required habits of mind to practice in what is still regarded as a speciality area of practice is somewhat limited. One of the areas of practice where this particularly impacts is in paediatric nursing physical assessment. Physical assessment is a fundamental component of nursing practice and competence in this area of practice is central to nursing students‘ development of clinical capability for practice as a registered nurse. Timely recognition of physiologic deterioration of patients is a key outcome of nurses‘ competent use of physical assessment strategies, regardless of the practice context. In paediatric nursing contexts children‘s physical assessment practices must specifically accommodate the child‘s different physiological composition, function and pattern of clinical deterioration (Hockenberry & Barrera, 2007). Thus, to effectively manage physical assessment of patients within the paediatric practice setting nursing students need to integrate paediatric nursing theory into their practice. This requires significant information processing and it is in this process where students are frequently challenged. The provision of rules or models can guide practice and assist novice-level nurses to develop their capabilities (Benner, 1984; Benner, Hooper-Kyriakidis & Stannard, 1999). Nursing practice models are cognitive tools that represent simplified patterns of expert analysis employing concepts that suit the limited reasoning of the inexperienced, and can represent the =rules‘ referred to by Benner (1984). Without a practice model of physical assessment students are likely to be uncertain about how to proceed with data collection, the interpretation of paediatric clinical findings and the appraisal of findings. These circumstances can result in ad hoc and unreliable nursing physical assessment that forms a poor basis for nursing decisions. The educational intervention developed as part of this study sought to resolve this problem and support nursing students‘ development of competence in paediatric physical assessment. Methods This study utilised the Context Input Process Product (CIPP) Model by Stufflebeam (2004) as the theoretical framework that underpinned the research design and evaluation methodology. Each of the four elements in the CIPP model were utilised to guide discrete stages of this study. The Context element informed design of the clinical decision-making process, the Paediatric Nursing Physical Assessment model. The Input element was utilised in appraising relevant literature, identifying an appropriate instructional methodology to facilitate learning and educational intervention delivery to undergraduate nursing students, and development of program content (the CD-ROM kit). Study One employed the Process element and used expert panel approaches to review and refine instructional methods, identifying potential barriers to obtaining an effective evaluation outcome. The Product element guided design and implementation of Study Two, which was conducted in two phases. Phase One employed a quasiexperimental between-subjects methodology to evaluate the impact of the educational intervention on nursing students‘ clinical performance and selfappraisal of practices in paediatric physical assessment. Phase Two employed a thematic analysis and explored the experiences and perspectives of a sample subgroup of nursing students who used the PNPA CD-ROM kit as preparation for paediatric clinical placement. Results Results from the Process review in Study One indicated that the prototype CDROM kit containing the PNPA model met the predetermined benchmarks for face validity and the impact evaluation instrumentation had adequate content validity in comparison with predetermined benchmarks. In the first phase of Study Two the educational intervention did not result in statistically significant differences in measures of student performance or self-appraisal of practice. However, in Phase Two qualitative commentary from students, and from the expert panel who reviewed the prototype CD-ROM kit (Study One, Phase One), strongly endorsed the quality of the intervention and its potential for supporting learning. This raises questions regarding transfer of learning and it is likely that, within this study, several factors have influenced students‘ transfer of learning from the educational intervention to the clinical practice environment, where outcomes were measured. Conclusion In summary, the educational intervention employed in this study provides insights into the potential e-learning approaches offer for delivering authentic learning experiences to undergraduate nursing students. Findings in this study raise important questions regarding possible pedagogical influences on learning outcomes, issues within the transfer of theory to practice and factors that may have influenced findings within the context of this study. This study makes a unique contribution to nursing education, specifically with respect to progressing an understanding of the challenges faced in employing instructive methods to impact upon nursing students‘ development of competence. The important contribution transfer of learning processes make to students‘ transition into the professional practice context and to their development of competence within the context of speciality practice is also highlighted. This study contributes to a greater awareness of the complexity of translating theoretical learning at undergraduate level into clinical practice, particularly within speciality contexts.
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Purpose: Computer vision has been widely used in the inspection of electronic components. This paper proposes a computer vision system for the automatic detection, localisation, and segmentation of solder joints on Printed Circuit Boards (PCBs) under different illumination conditions. Design/methodology/approach: An illumination normalization approach is applied to an image, which can effectively and efficiently eliminate the effect of uneven illumination while keeping the properties of the processed image the same as in the corresponding image under normal lighting conditions. Consequently special lighting and instrumental setup can be reduced in order to detect solder joints. These normalised images are insensitive to illumination variations and are used for the subsequent solder joint detection stages. In the segmentation approach, the PCB image is transformed from an RGB color space to a YIQ color space for the effective detection of solder joints from the background. Findings: The segmentation results show that the proposed approach improves the performance significantly for images under varying illumination conditions. Research limitations/implications: This paper proposes a front-end system for the automatic detection, localisation, and segmentation of solder joint defects. Further research is required to complete the full system including the classification of solder joint defects. Practical implications: The methodology presented in this paper can be an effective method to reduce cost and improve quality in production of PCBs in the manufacturing industry. Originality/value: This research proposes the automatic location, identification and segmentation of solder joints under different illumination conditions.
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Free-radical processes underpin the thermo-oxidative degradation of polyolefins. Thus, to extend the lifetime of these polymers, stabilizers are generally added during processing to scavenge the free radicals formed as the polymer degrades. Nitroxide radical precursors, such as hindered amine stabilizers (HAS),1,2 are common polypropylene additives as the nitroxide moiety is a potent scavenger of polymer alkyl radicals (R¥). Oxidation of HAS by radicals formed during polypropylene degradation yields nitroxide radicals (RRNO¥), which rapidly trap the polymer degradation species to produce alkoxyamines, thus retarding oxidative polymer degradation. This increase in polymer stability is demonstrated by a lengthening of the “induction period” of the polymer (the time prior to a sharp rise in the oxidation of the polymer). Instrumental techniques such as chemiluminescence or infrared spectroscopy are somewhat limited in detecting changes in the polymer during the initial stages of degradation. Therefore, other methods for observing polymer degradation have been sought as the useful life of a polymer does not extend far beyond its “induction period”
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Performance evaluation of object tracking systems is typically performed after the data has been processed, by comparing tracking results to ground truth. Whilst this approach is fine when performing offline testing, it does not allow for real-time analysis of the systems performance, which may be of use for live systems to either automatically tune the system or report reliability. In this paper, we propose three metrics that can be used to dynamically asses the performance of an object tracking system. Outputs and results from various stages in the tracking system are used to obtain measures that indicate the performance of motion segmentation, object detection and object matching. The proposed dynamic metrics are shown to accurately indicate tracking errors when visually comparing metric results to tracking output, and are shown to display similar trends to the ETISEO metrics when comparing different tracking configurations.
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The following paper presents an evaluation of airborne sensors for use in vegetation management in powerline corridors. Three integral stages in the management process are addressed including, the detection of trees, relative positioning with respect to the nearest powerline and vegetation height estimation. Image data, including multi-spectral and high resolution, are analyzed along with LiDAR data captured from fixed wing aircraft. Ground truth data is then used to establish the accuracy and reliability of each sensor thus providing a quantitative comparison of sensor options. Tree detection was achieved through crown delineation using a Pulse-Coupled Neural Network (PCNN) and morphologic reconstruction applied to multi-spectral imagery. Through testing it was shown to achieve a detection rate of 96%, while the accuracy in segmenting groups of trees and single trees correctly was shown to be 75%. Relative positioning using LiDAR achieved a RMSE of 1.4m and 2.1m for cross track distance and along track position respectively, while Direct Georeferencing achieved RMSE of 3.1m in both instances. The estimation of pole and tree heights measured with LiDAR had a RMSE of 0.4m and 0.9m respectively, while Stereo Matching achieved 1.5m and 2.9m. Overall a small number of poles were missed with detection rates of 98% and 95% for LiDAR and Stereo Matching.
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Purpose – The paper describes a project created to enhance e-research support activities within an Australian university, based on environmental scanning of e-research activities and funding both nationally and internationally. Participation by the university library is also described.----- Design/methodology/approach – The paper uses a case study that describes the stages of a project undertaken to develop an academic library’s capacity to offer e-research support to its institution’s research community.----- Findings – While the outcomes of the project have been successfully achieved, the work needs to be continued and eventually mainstreamed as core business in order to keep pace with developments in e-research. The continual skilling up of the university’s researchers and research support staff in e-research activities is imperative in reaching the goal of becoming a highly competitive research institution.----- Research limitations/implications – Although a single case study, the work has been contextualised within the national research agenda.----- Practical implications – The paper provides a project model that can adapted within an academic library without external or specialist skills. It is also scalable and can be applied at a divisional or broader level.----- Originality/value – The paper highlights the drivers for research investment in Australia and provides a model of how building e-research support activities can leverage this investment and contribute towards successful research activity.
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Recent research on particle size distributions and particle concentrations near a busy road cannot be explained by the conventional mechanisms for particle evolution of combustion aerosols. Specifically they appear to be inadequate to explain the experimental observations of particle transformation and the evolution of the total number concentration. This resulted in the development of a new mechanism based on their thermal fragmentation, for the evolution of combustion aerosol nano-particles. A complex and comprehensive pattern of evolution of combustion aerosols, involving particle fragmentation, was then proposed and justified. In that model it was suggested that thermal fragmentation occurs in aggregates of primary particles each of which contains a solid graphite/carbon core surrounded by volatile molecules bonded to the core by strong covalent bonds. Due to the presence of strong covalent bonds between the core and the volatile (frill) molecules, such primary composite particles can be regarded as solid, despite the presence of significant (possibly, dominant) volatile component. Fragmentation occurs when weak van der Waals forces between such primary particles are overcome by their thermal (Brownian) motion. In this work, the accepted concept of thermal fragmentation is advanced to determine whether fragmentation is likely in liquid composite nano-particles. It has been demonstrated that at least at some stages of evolution, combustion aerosols contain a large number of composite liquid particles containing presumably several components such as water, oil, volatile compounds, and minerals. It is possible that such composite liquid particles may also experience thermal fragmentation and thus contribute to, for example, the evolution of the total number concentration as a function of distance from the source. Therefore, the aim of this project is to examine theoretically the possibility of thermal fragmentation of composite liquid nano-particles consisting of immiscible liquid v components. The specific focus is on ternary systems which include two immiscible liquid droplets surrounded by another medium (e.g., air). The analysis shows that three different structures are possible, the complete encapsulation of one liquid by the other, partial encapsulation of the two liquids in a composite particle, and the two droplets separated from each other. The probability of thermal fragmentation of two coagulated liquid droplets is discussed and examined for different volumes of the immiscible fluids in a composite liquid particle and their surface and interfacial tensions through the determination of the Gibbs free energy difference between the coagulated and fragmented states, and comparison of this energy difference with the typical thermal energy kT. The analysis reveals that fragmentation was found to be much more likely for a partially encapsulated particle than a completely encapsulated particle. In particular, it was found that thermal fragmentation was much more likely when the volume ratio of the two liquid droplets that constitute the composite particle are very different. Conversely, when the two liquid droplets are of similar volumes, the probability of thermal fragmentation is small. It is also demonstrated that the Gibbs free energy difference between the coagulated and fragmented states is not the only important factor determining the probability of thermal fragmentation of composite liquid particles. The second essential factor is the actual structure of the composite particle. It is shown that the probability of thermal fragmentation is also strongly dependent on the distance that each of the liquid droplets should travel to reach the fragmented state. In particular, if this distance is larger than the mean free path for the considered droplets in the air, the probability of thermal fragmentation should be negligible. In particular, it follows form here that fragmentation of the composite particle in the state with complete encapsulation is highly unlikely because of the larger distance that the two droplets must travel in order to separate. The analysis of composite liquid particles with the interfacial parameters that are expected in combustion aerosols demonstrates that thermal fragmentation of these vi particles may occur, and this mechanism may play a role in the evolution of combustion aerosols. Conditions for thermal fragmentation to play a significant role (for aerosol particles other than those from motor vehicle exhaust) are determined and examined theoretically. Conditions for spontaneous transformation between the states of composite particles with complete and partial encapsulation are also examined, demonstrating the possibility of such transformation in combustion aerosols. Indeed it was shown that for some typical components found in aerosols that transformation could take place on time scales less than 20 s. The analysis showed that factors that influenced surface and interfacial tension played an important role in this transformation process. It is suggested that such transformation may, for example, result in a delayed evaporation of composite particles with significant water component, leading to observable effects in evolution of combustion aerosols (including possible local humidity maximums near a source, such as a busy road). The obtained results will be important for further development and understanding of aerosol physics and technologies, including combustion aerosols and their evolution near a source.
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Background: In order to design appropriate environments for performance and learning of movement skills, physical educators need a sound theoretical model of the learner and of processes of learning. In physical education, this type of modelling informs the organization of learning environments and effective and efficient use of practice time. An emerging theoretical framework in motor learning, relevant to physical education, advocates a constraints-led perspective for acquisition of movement skills and game play knowledge. This framework shows how physical educators could use task, performer and environmental constraints to channel acquisition of movement skills and decision making behaviours in learners. From this viewpoint, learners generate specific movement solutions to satisfy the unique combination of constraints imposed on them, a process which can be harnessed during physical education lessons. Purpose: In this paper the aim is to provide an overview of the motor learning approach emanating from the constraints-led perspective, and examine how it can substantiate a platform for a new pedagogical framework in physical education: nonlinear pedagogy. We aim to demonstrate that it is only through theoretically valid and objective empirical work of an applied nature that a conceptually sound nonlinear pedagogy model can continue to evolve and support research in physical education. We present some important implications for designing practices in games lessons, showing how a constraints-led perspective on motor learning could assist physical educators in understanding how to structure learning experiences for learners at different stages, with specific focus on understanding the design of games teaching programmes in physical education, using exemplars from Rugby Union and Cricket. Findings: Research evidence from recent studies examining movement models demonstrates that physical education teachers need a strong understanding of sport performance so that task constraints can be manipulated so that information-movement couplings are maintained in a learning environment that is representative of real performance situations. Physical educators should also understand that movement variability may not necessarily be detrimental to learning and could be an important phenomenon prior to the acquisition of a stable and functional movement pattern. We highlight how the nonlinear pedagogical approach is student-centred and empowers individuals to become active learners via a more hands-off approach to learning. Summary: A constraints-based perspective has the potential to provide physical educators with a framework for understanding how performer, task and environmental constraints shape each individual‟s physical education. Understanding the underlying neurobiological processes present in a constraints-led perspective to skill acquisition and game play can raise awareness of physical educators that teaching is a dynamic 'art' interwoven with the 'science' of motor learning theories.
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Successful product innovation and the ability of companies to continuously improve their innovation processes are rapidly becoming essential requirements for competitive advantage and long-term growth in both manufacturing and service industries. It is now recognized that companies must develop innovation capabilities across all stages of the product development, manufacture, and distribution cycle. These Continuous Product Innovation (CPI) capabilities are closely associated with a company’s knowledge management systems and processes. Companies must develop mechanisms to continuously improve these capabilities over time. Using results of an international survey on CPI practices, sets of companies are identified by similarities in specific contingencies related to their complexity of product, process, technological, and customer interface. Differences between the learning behaviors found present in the company groups and in the levers used to develop and support these behaviors are identified and discussed. This paper also discusses appropriate mechanisms for firms with similar complexities, and some approaches they can use to improve their organizational learning and product innovation.
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In the quest for shorter time-to-market, higher quality and reduced cost, model-driven software development has emerged as a promising approach to software engineering. The central idea is to promote models to first-class citizens in the development process. Starting from a set of very abstract models in the early stage of the development, they are refined into more concrete models and finally, as a last step, into code. As early phases of development focus on different concepts compared to later stages, various modelling languages are employed to most accurately capture the concepts and relations under discussion. In light of this refinement process, translating between modelling languages becomes a time-consuming and error-prone necessity. This is remedied by model transformations providing support for reusing and automating recurring translation efforts. These transformations typically can only be used to translate a source model into a target model, but not vice versa. This poses a problem if the target model is subject to change. In this case the models get out of sync and therefore do not constitute a coherent description of the software system anymore, leading to erroneous results in later stages. This is a serious threat to the promised benefits of quality, cost-saving, and time-to-market. Therefore, providing a means to restore synchronisation after changes to models is crucial if the model-driven vision is to be realised. This process of reflecting changes made to a target model back to the source model is commonly known as Round-Trip Engineering (RTE). While there are a number of approaches to this problem, they impose restrictions on the nature of the model transformation. Typically, in order for a transformation to be reversed, for every change to the target model there must be exactly one change to the source model. While this makes synchronisation relatively “easy”, it is ill-suited for many practically relevant transformations as they do not have this one-to-one character. To overcome these issues and to provide a more general approach to RTE, this thesis puts forward an approach in two stages. First, a formal understanding of model synchronisation on the basis of non-injective transformations (where a number of different source models can correspond to the same target model) is established. Second, detailed techniques are devised that allow the implementation of this understanding of synchronisation. A formal underpinning for these techniques is drawn from abductive logic reasoning, which allows the inference of explanations from an observation in the context of a background theory. As non-injective transformations are the subject of this research, there might be a number of changes to the source model that all equally reflect a certain target model change. To help guide the procedure in finding “good” source changes, model metrics and heuristics are investigated. Combining abductive reasoning with best-first search and a “suitable” heuristic enables efficient computation of a number of “good” source changes. With this procedure Round-Trip Engineering of non-injective transformations can be supported.