984 resultados para ACTIVE-MATRIX DISPLAYS


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Objectives The purpose for this study was to determine the relative benefit of nap and active rest breaks for reducing driver sleepiness. Methods Participants were 20 healthy young adults (20-25 years), including 8 males and 12 females. A counterbalanced within-subjects design was used such that each participant completed both conditions on separate occasions, a week apart. The effects of the countermeasures were evaluated by established physiological (EEG theta and alpha absolute power), subjective (Karolinska Sleepiness Scale), and driving performance measures (Hazard Perception Task). Participants woke at 5am, and undertook a simulated driving task for two hours; each participant then had either a 15-minute nap opportunity or a 15-minute active rest break that included 10 minutes of brisk walking, followed by another hour of simulated driving. Results The nap break reduced EEG theta and alpha absolute power and eventually reduced subjective sleepiness levels. In contrast, the active rest break did not reduce EEG theta and alpha absolute power levels with the power levels eventually increasing. An immediate reduction of subjective sleepiness was observed, with subjective sleepiness increasing during the final hour of simulated driving. No difference was found between the two breaks for hazard perception performance. Conclusions Only the nap break produced a significant reduction in physiological sleepiness. The immediate reductions of subjective sleepiness following the active rest break could leave drivers with erroneous perceptions of their sleepiness, particularly as physiological sleepiness continued to increase after the break.

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This thesis addressed issues that have prevented qualitative researchers from using thematic discovery algorithms. The central hypothesis evaluated whether allowing qualitative researchers to interact with thematic discovery algorithms and incorporate domain knowledge improved their ability to address research questions and trust the derived themes. Non-negative Matrix Factorisation and Latent Dirichlet Allocation find latent themes within document collections but these algorithms are rarely used, because qualitative researchers do not trust and cannot interact with the themes that are automatically generated. The research determined the types of interactivity that qualitative researchers require and then evaluated interactive algorithms that matched these requirements. Theoretical contributions included the articulation of design guidelines for interactive thematic discovery algorithms, the development of an Evaluation Model and a Conceptual Framework for Interactive Content Analysis.

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One of the hallmarks of cancer is the ability to activate invasion and metastasis (Hanahan et al., 2011). Cancer morbidity and mortality are largely related to the spread of the primary, localised tumour to adjacent and distant sites (Pantel et al., 2004). Appropriate management and treatment decisions of predicting metastatic disease at the time of diagnosis is thus crucial, which supports better understanding of the metastatic process. There are common events that occur during metastasis: dissociation from the primary tumour mass, reorganisation/remodelling of extracellular matrix, cell migration, recognition and transversal of endothelial cells and the vascular circulation and lodgement and proliferation within ectopic stroma (Wells, 2006). One of the key and initial events is the increased capability of cancer cells to move, escaping the regulation of normal physiological control. The cellular cytoskeleton plays an important role in cancer cell motility and active cytoskeletal rearrangement can result in metastatic disease. This active change in cytoskeletal dynamics results in manipulation of plasma membrane and cellular balance between cellular adhesion and motility which in turn determines cancer cell movement. Members of the tetraspanins play important roles in regulation of cancer migration and cancer-endothelial cell interactions, which are critical for cancer invasion and metastasis. Their involvements in active cytoskeletal dynamics, cancer metastasis and potential clinical application will be discussed in this review. In particular, tetraspanin member, CD151, is highlighted for its major role in cancer invasion and metastasis

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The repair of bone defects that result from periodontal diseases remains a clinical challenge for periodontal therapy. β-tricalcium phosphate (β-TCP) ceramics are biodegradable inorganic bone substitutes with inorganic components that are similar to those of bone. Demineralized bone matrix (DBM) is an acid-extracted organic matrix derived from bone sources that consists of the collagen and matrix proteins of bone. A few studies have documented the effects of DBM on the proliferation and osteogenic differentiation of human periodontal ligament cells (hPDLCs). The aim of the present study was to investigate the effects of inorganic and organic elements of bone on the proliferation and osteogenic differentiation of hPDLCs using three-dimensional porous β-TCP ceramics and DBM with or without osteogenic inducers. Primary hPDLCs were isolated from human periodontal ligaments. The proliferation of the hPDLCs on the scaffolds in the growth culture medium was examined using a Cell‑Counting kit‑8 (CCK-8) and scanning electron microscopy (SEM). Alkaline phosphatase (ALP) activity and the osteogenic differentiation of the hPDLCs cultured on the β-TCP ceramics and DBM were examined in both the growth culture medium and osteogenic culture medium. Specific osteogenic differentiation markers were examined using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). SEM images revealed that the cells on the β-TCP were spindle-shaped and much more spread out compared with the cells on the DBM surfaces. There were no significant differences observed in cell proliferation between the β-TCP ceramics and the DBM scaffolds. Compared with the cells that were cultured on β-TCP ceramics, the ALP activity, as well as the Runx2 and osteocalcin (OCN) mRNA levels in the hPDLCs cultured on DBM were significantly enhanced both in the growth culture medium and the osteogenic culture medium. The organic elements of bone may exhibit greater osteogenic differentiation effects on hPDLCs than the inorganic elements.

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Chronic liver injury and inflammation lead to hepatic fibrosis, cirrhosis, and liver failure. Embryonic and mesenchymal stem cells have been shown to reduce experimental liver fibrosis but have potential limitations, including the formation of dysplastic precursors, tumors, and profibrogenic cells. Other stem-like cells may reduce hepatic inflammation and fibrosis without tumor and profibrogenic cell formation. To test this hypothesis we transplanted human amnion epithelial cells (hAEC), isolated from term delivered placenta, into immunocompetent C57/BL6 mice at week 2 of a 4-week regimen of carbon tetrachloride (CCl4) exposure to induce liver fibrosis. Two weeks following hAEC infusion, intact cells expressing the human-specific markers inner mitochondrial membrane protein and human leukocyte antigen-G were found in mouse liver without evidence of host rejection of the transplanted cells. Human albumin, known to be produced by hAEC, was detected in sera of hAEC-treated mice. Human DNA was detected in mouse liver and also spleen, lungs, and heart of some animals. Following hAEC transplantation, CCl4-treated animals showed decreased serum ALT levels and reduced hepatocyte apoptosis, compared to controls. hAEC-treated mouse liver had lower TNF-α and IL-6 protein levels and higher IL-10 compared to animals given CCl4 alone. Compared to CCl4 controls, hAEC-treated mice showed fewer activated collagen-producing hepatic stellate cells and less fibrosis area and collagen content. Reduced hepatic TGF-β levels in conjunction with a twofold increase in the active form of the collagen-degrading enzyme matrix metalloproteinase-2 in hAEC-treated mice compared to CCl4 controls may account for the reduction in fibrosis. hAEC transplantation into immunocompetent mice leads to cell engraftment, reduced hepatocyte apoptosis, and decreased hepatic inflammation and fibrosis.

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Feminist research on girlhood has drawn extensively on Butler's conceptual work in order to theorise the normative forces of heterosexuality in the everyday construction of gender. This chapter explores girlhood by drawing on memories and artwork generated in a collective biography workshop held in Australian on the topic of girlhood and sexuality. We are interested in thinking through Butler's notion of the heterosexual matrix. Following Renold and Ringrose (2008) we do so with the help of Deleuze and Guattari, who invite us to think about difference as differenciation or continuous becoming, where difference is an evolutionary multiplicity.

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Purpose: We examine the interaction between trait resilience and control in predicting coping and performance. Drawing on a person–environment fit perspective, we hypothesized resilient individuals would cope and perform better in demanding work situations when control was high. In contrast, those low in resilience would cope and perform better when control was low. Recognizing the relationship between trait resilience and performance also could be indirect, adaptive coping was examined as a mediating mechanism through which high control enables resilient individuals to demonstrate better performance. Methodology: In Study 1 (N = 78) and Study 2 (N = 94), participants completed a demanding inbox task in which trait resilience was measured and high and low control was manipulated. Study 3 involved surveying 368 employees on their trait resilience, control, and demand at work (at Time 1), and coping and performance 1 month later at Time 2. Findings: For more resilient individuals, high control facilitated problem-focused coping (Study 1, 2, and 3), which was indirectly associated with higher subjective performance (Study 1), mastery (Study 2), adaptive, and proficient performance (Study 3). For more resilient individuals, high control also facilitated positive reappraisal (Study 2 and 3), which was indirectly associated with higher adaptive and proficient performance (Study 3). Implications: Individuals higher in resilience benefit from high control because it enables adaptive coping. Originality/value: This research makes two contributions: (1) an experimental investigation into the interaction of trait resilience and control, and (2) investigation of coping as the mechanism explaining better performance.

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The development of offshore oil and gas fields require the placement of different equipment on the sea floor. This is done by deploying the equipment from vessels operating in dynamic positioning on the surface. The deployment operation has different phases, and in higher sea states, it may require wave-load synchronization, when the load is going through the splash zone, and heave compensation when the load is close to the sea floor. In this paper, we analyse the performance of a particular type of hardware operating in a heave compensation mode. We derive a comprehensive model, analyse limits of performance and evaluate a control strategy.

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The Haddon Matrix was developed in the 1960s road safety arena, and has since been used in many public health settings. The literature and two specific case studies are reviewed to describe the background to the Haddon Matrix, identify how it has been critiqued and developed over time and practical applications in the work-related road safety context. Haddon’s original focus on the road, vehicle and driver has been extended and applied to include organisational safety culture, journey management and wider issues in society that affect occupational drivers and the communities in which they work. The paper shows that the Haddon Matrix has been applied in many projects and contexts. Practical work-related road safety applications include providing a comprehensive systems-based safety management framework to inform strategy. It has also been used to structure the review or gap analysis of current programs and processes, identify and develop prevention measures and as a tool for effective post-event investigations.

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Gaining invariance to camera and illumination variations has been a well investigated topic in Active Appearance Model (AAM) fitting literature. The major problem lies in the inability of the appearance parameters of the AAM to generalize to unseen conditions. An attractive approach for gaining invariance is to fit an AAM to a multiple filter response (e.g. Gabor) representation of the input image. Naively applying this concept with a traditional AAM is computationally prohibitive, especially as the number of filter responses increase. In this paper, we present a computationally efficient AAM fitting algorithm based on the Lucas-Kanade (LK) algorithm posed in the Fourier domain that affords invariance to both expression and illumination. We refer to this as a Fourier AAM (FAAM), and show that this method gives substantial improvement in person specific AAM fitting performance over traditional AAM fitting methods.

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Active learning approaches reduce the annotation cost required by traditional supervised approaches to reach the same effectiveness by actively selecting informative instances during the learning phase. However, effectiveness and robustness of the learnt models are influenced by a number of factors. In this paper we investigate the factors that affect the effectiveness, more specifically in terms of stability and robustness, of active learning models built using conditional random fields (CRFs) for information extraction applications. Stability, defined as a small variation of performance when small variation of the training data or a small variation of the parameters occur, is a major issue for machine learning models, but even more so in the active learning framework which aims to minimise the amount of training data required. The factors we investigate are a) the choice of incremental vs. standard active learning, b) the feature set used as a representation of the text (i.e., morphological features, syntactic features, or semantic features) and c) Gaussian prior variance as one of the important CRFs parameters. Our empirical findings show that incremental learning and the Gaussian prior variance lead to more stable and robust models across iterations. Our study also demonstrates that orthographical, morphological and contextual features as a group of basic features play an important role in learning effective models across all iterations.