996 resultados para domain reverse
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This chapter examines the role of the advanced nurse practitioner (ANP) within the domains of practice identified by the Royal College of Nursing (2002) as the teaching and coaching function. (Note that this is referred to by the NMC as the education function. It approaches the analysis against the backdrop of three policy documents: The Expert Patient: a new approach to chronic disease management for the 21st century(DoH 2001), Choosing Health: making healthy choices easier (DoH 2004), Our health, our care, our say (DoH 2006). It draws into the frame the experiences of ANP students as they work with patients, clients and carers, with the intention of enabling health and managing illness. It uses examples from a range of everyday practice setting to illustrate the inherent challenges of the teaching and coaching function of the ANP, at the same time as recognising its significance if patients, clients and carers are to be enabled to make choices that might optimize their well-being. Before this, however, some statistics are presented to focus thinking on why education is an invaluable component of advanced nursing practice.
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Ferr?, S. and King, R. D. (2004) A dichotomic search algorithm for mining and learning in domain-specific logics. Fundamenta Informaticae. IOS Press. To appear
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The atom pencil we describe here is a versatile tool that writes arbitrary structures by atomic deposition in a serial lithographic process. This device consists of a transversely laser-cooled and collimated cesium atomic beam that passes through a 4-pole atom-flux concentrator and impinges on to micron- and sub-micron-sized apertures. The aperture translates above a fixed substrate and enables the writing of sharp features with sizes down to 280 nm. We have investigated the writing and clogging properties of an atom pencil tip fabricated from silicon oxide pyramids perforated at the tip apex with a sub-micron aperture.
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An aim of proactive risk management strategies is the timely identification of safety related risks. One way to achieve this is by deploying early warning systems. Early warning systems aim to provide useful information on the presence of potential threats to the system, the level of vulnerability of a system, or both of these, in a timely manner. This information can then be used to take proactive safety measures. The United Nation’s has recommended that any early warning system need to have four essential elements, which are the risk knowledge element, a monitoring and warning service, dissemination and communication and a response capability. This research deals with the risk knowledge element of an early warning system. The risk knowledge element of an early warning system contains models of possible accident scenarios. These accident scenarios are created by using hazard analysis techniques, which are categorised as traditional and contemporary. The assumption in traditional hazard analysis techniques is that accidents are occurred due to a sequence of events, whereas, the assumption of contemporary hazard analysis techniques is that safety is an emergent property of complex systems. The problem is that there is no availability of a software editor which can be used by analysts to create models of accident scenarios based on contemporary hazard analysis techniques and generate computer code that represent the models at the same time. This research aims to enhance the process of generating computer code based on graphical models that associate early warning signs and causal factors to a hazard, based on contemporary hazard analyses techniques. For this purpose, the thesis investigates the use of Domain Specific Modeling (DSM) technologies. The contributions of this thesis is the design and development of a set of three graphical Domain Specific Modeling languages (DSML)s, that when combined together, provide all of the necessary constructs that will enable safety experts and practitioners to conduct hazard and early warning analysis based on a contemporary hazard analysis approach. The languages represent those elements and relations necessary to define accident scenarios and their associated early warning signs. The three DSMLs were incorporated in to a prototype software editor that enables safety scientists and practitioners to create and edit hazard and early warning analysis models in a usable manner and as a result to generate executable code automatically. This research proves that the DSM technologies can be used to develop a set of three DSMLs which can allow user to conduct hazard and early warning analysis in more usable manner. Furthermore, the three DSMLs and their dedicated editor, which are presented in this thesis, may provide a significant enhancement to the process of creating the risk knowledge element of computer based early warning systems.
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The healthcare industry is beginning to appreciate the benefits which can be obtained from using Mobile Health Systems (MHS) at the point-of-care. As a result, healthcare organisations are investing heavily in mobile health initiatives with the expectation that users will employ the system to enhance performance. Despite widespread endorsement and support for the implementation of MHS, empirical evidence surrounding the benefits of MHS remains to be fully established. For MHS to be truly valuable, it is argued that the technological tool be infused within healthcare practitioners work practices and used to its full potential in post-adoptive scenarios. Yet, there is a paucity of research focusing on the infusion of MHS by healthcare practitioners. In order to address this gap in the literature, the objective of this study is to explore the determinants and outcomes of MHS infusion by healthcare practitioners. This research study adopts a post-positivist theory building approach to MHS infusion. Existing literature is utilised to develop a conceptual model by which the research objective is explored. Employing a mixed-method approach, this conceptual model is first advanced through a case study in the UK whereby propositions established from the literature are refined into testable hypotheses. The final phase of this research study involves the collection of empirical data from a Canadian hospital which supports the refined model and its associated hypotheses. The results from both phases of data collection are employed to develop a model of MHS infusion. The study contributes to IS theory and practice by: (1) developing a model with six determinants (Availability, MHS Self-Efficacy, Time-Criticality, Habit, Technology Trust, and Task Behaviour) and individual performance-related outcomes of MHS infusion (Effectiveness, Efficiency, and Learning), (2) examining undocumented determinants and relationships, (3) identifying prerequisite conditions that both healthcare practitioners and organisations can employ to assist with MHS infusion, (4) developing a taxonomy that provides conceptual refinement of IT infusion, and (5) informing healthcare organisations and vendors as to the performance of MHS in post-adoptive scenarios.
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We have previously shown that treatment of prostate cancer and melanoma cells expressing GRP78 on their cell surface with antibody directed against the COOH-terminal domain of GRP78 upregulates and activates p53 causing decreased cell proliferation and upregulated apoptosis. In this report, we demonstrate that treatment of 1-LN prostate cancer cells with this antibody decreases cell surface expression of GRP78, Akt(Thr308) and Akt(Ser473) kinase activities and reduces phosphorylation of FOXO, and GSK3beta. This treatment also suppresses activation of ERK1/2, p38 MAPK and MKK3/6; however, it upregulates MKK4 activity. JNK, as determined by its phosphorylation state, is subsequently activated, triggering apoptosis. Incubation of cells with antibody reduced levels of anti-apoptotic Bcl-2, while elevating pro-apoptotic BAD, BAX and BAK expression as well as cleaved caspases-3, -7, -8 and -9. Silencing GRP78 or p53 gene expression by RNAi prior to antibody treatment abrogated these effects. We conclude that antibody directed against the COOH-terminal domain of GRP78 may prove useful as a pan suppressor of proliferative/survival signaling in cancer cells expressing GRP78 on their cell surface.
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We present measurements of morphological features in a thick turbid sample using light-scattering spectroscopy (LSS) and Fourier-domain low-coherence interferometry (fLCI) by processing with the dual-window (DW) method. A parallel frequency domain optical coherence tomography (OCT) system with a white-light source is used to image a two-layer phantom containing polystyrene beads of diameters 4.00 and 6.98 mum on the top and bottom layers, respectively. The DW method decomposes each OCT A-scan into a time-frequency distribution with simultaneously high spectral and spatial resolution. The spectral information from localized regions in the sample is used to determine scatterer structure. The results show that the two scatterer populations can be differentiated using LSS and fLCI.
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We demonstrate in vivo human retinal imaging using an intraoperative microscope-mounted optical coherence tomography system (MMOCT). Our optomechanical design adapts an Oculus Binocular Indirect Ophthalmo Microscope (BIOM3), suspended from a Leica ophthalmic surgical microscope, with spectral domain optical coherence tomography (SD-OCT) scanning and relay optics. The MMOCT enables wide-field noncontact real-time cross-sectional imaging of retinal structure, allowing for SD-OCT augmented intrasurgical microscopy for intraocular visualization. We experimentally quantify the axial and lateral resolution of the MMOCT and demonstrate fundus imaging at a 20Hz frame rate.
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We have developed an alternative approach to optical design which operates in the analytical domain so that an optical designer works directly with rays as analytical functions of system parameters rather than as discretely sampled polylines. This is made possible by a generalization of the proximate ray tracing technique which obtains the analytical dependence of the rays at the image surface (and ray path lengths at the exit pupil) on each system parameter. The resulting method provides an alternative direction from which to approach system optimization and supplies information which is not typically available to the system designer. In addition, we have further expanded the procedure to allow asymmetric systems and arbitrary order of approximation, and have illustrated the performance of the method through three lens design examples.
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Capable of three-dimensional imaging of the cornea with micrometer-scale resolution, spectral domain-optical coherence tomography (SDOCT) offers potential advantages over Placido ring and Scheimpflug photography based systems for accurate extraction of quantitative keratometric parameters. In this work, an SDOCT scanning protocol and motion correction algorithm were implemented to minimize the effects of patient motion during data acquisition. Procedures are described for correction of image data artifacts resulting from 3D refraction of SDOCT light in the cornea and from non-idealities of the scanning system geometry performed as a pre-requisite for accurate parameter extraction. Zernike polynomial 3D reconstruction and a recursive half searching algorithm (RHSA) were implemented to extract clinical keratometric parameters including anterior and posterior radii of curvature, central cornea optical power, central corneal thickness, and thickness maps of the cornea. Accuracy and repeatability of the extracted parameters obtained using a commercial 859nm SDOCT retinal imaging system with a corneal adapter were assessed using a rigid gas permeable (RGP) contact lens as a phantom target. Extraction of these parameters was performed in vivo in 3 patients and compared to commercial Placido topography and Scheimpflug photography systems. The repeatability of SDOCT central corneal power measured in vivo was 0.18 Diopters, and the difference observed between the systems averaged 0.1 Diopters between SDOCT and Scheimpflug photography, and 0.6 Diopters between SDOCT and Placido topography.
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The beta-adrenergic receptor kinase (beta ARK) phosphorylates its membrane-associated receptor substrates, such as the beta-adrenergic receptor, triggering events leading to receptor desensitization. beta ARK activity is markedly stimulated by the isoprenylated beta gamma subunit complex of heterotrimeric guanine nucleotide-binding proteins (G beta gamma), which translocates the kinase to the plasma membrane and thereby targets it to its receptor substrate. The amino-terminal two-thirds of beta ARK1 composes the receptor recognition and catalytic domains, while the carboxyl third contains the G beta gamma binding sequences, the targeting domain. We prepared this domain as a recombinant His6 fusion protein from Escherichia coli and found that it had both independent secondary structure and functional activity. We demonstrated the inhibitory properties of this domain against G beta gamma activation of type II adenylyl cyclase both in a reconstituted system utilizing Sf9 insect cell membranes and in a permeabilized 293 human embryonic kidney cell system. Gi alpha-mediated inhibition of adenylyl cyclase was not affected. These data suggest that this His6 fusion protein derived from the carboxyl terminus of beta ARK1 provides a specific probe for defining G beta gamma-mediated processes and for studying the structural features of a G beta gamma-binding domain.
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Learning multiple tasks across heterogeneous domains is a challenging problem since the feature space may not be the same for different tasks. We assume the data in multiple tasks are generated from a latent common domain via sparse domain transforms and propose a latent probit model (LPM) to jointly learn the domain transforms, and the shared probit classifier in the common domain. To learn meaningful task relatedness and avoid over-fitting in classification, we introduce sparsity in the domain transforms matrices, as well as in the common classifier. We derive theoretical bounds for the estimation error of the classifier in terms of the sparsity of domain transforms. An expectation-maximization algorithm is derived for learning the LPM. The effectiveness of the approach is demonstrated on several real datasets.
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At the FASEB summer research conference on "Arf Family GTPases", held in Il Ciocco, Italy in June, 2007, it became evident to researchers that our understanding of the family of Arf GTPase activating proteins (ArfGAPs) has grown exponentially in recent years. A common nomenclature for these genes and proteins will facilitate discovery of biological functions and possible connections to pathogenesis. Nearly 100 researchers were contacted to generate a consensus nomenclature for human ArfGAPs. This article describes the resulting consensus nomenclature and provides a brief description of each of the 10 subfamilies of 31 human genes encoding proteins containing the ArfGAP domain.