188 resultados para Discrete components


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This theoretical paper attempts to define some of the key components and challenges required to create embodied conversational agents that can be genuinely interesting conversational partners. Wittgenstein’s argument concerning talking lions emphasizes the importance of having a shared common ground as a basis for conversational interactions. Virtual bats suggests that–for some people at least–it is important that there be a feeling of authenticity concerning a subjectively experiencing entity that can convey what it is like to be that entity. Electric sheep reminds us of the importance of empathy in human conversational interaction and that we should provide a full communicative repertoire of both verbal and non-verbal components if we are to create genuinely engaging interactions. Also we may be making the task more difficult rather than easy if we leave out non-verbal aspects of communication. Finally, analogical peacocks highlights the importance of between minds alignment and establishes a longer term goal of being interesting, creative, and humorous if an embodied conversational is to be truly an engaging conversational partner. Some potential directions and solutions to addressing these issues are suggested.

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Background
The use of multiple medicines (polypharmacy) is increasingly common in older people. Ensuring that patients receive the most appropriate combinations of medications (appropriate polypharmacy) is a significant challenge. The quality of evidence to support the effectiveness of interventions to improve appropriate polypharmacy is low. Systematic identification of mediators of behaviour change, using the Theoretical Domains Framework (TDF), provides a theoretically robust evidence base to inform intervention design. This study aimed to (1) identify key theoretical domains that were perceived to influence the prescribing and dispensing of appropriate polypharmacy to older patients by general practitioners (GPs) and community pharmacists, and (2) map domains to associated behaviour change techniques (BCTs) to include as components of an intervention to improve appropriate polypharmacy in older people in primary care.

Methods
Semi-structured interviews were conducted with members of each healthcare professional (HCP) group using tailored topic guides based on TDF version 1 (12 domains). Questions covering each domain explored HCPs’ perceptions of barriers and facilitators to ensuring the prescribing and dispensing of appropriate polypharmacy to older people. Interviews were audio-recorded and transcribed verbatim. Data analysis involved the framework method and content analysis. Key domains were identified and mapped to BCTs based on established methods and discussion within the research team.

Results
Thirty HCPs were interviewed (15 GPs, 15 pharmacists). Eight key domains were identified, perceived to influence prescribing and dispensing of appropriate polypharmacy: ‘Skills’, ‘Beliefs about capabilities’, ‘Beliefs about consequences’, ‘Environmental context and resources’, ‘Memory, attention and decision processes’, ‘Social/professional role and identity’, ‘Social influences’ and ‘Behavioural regulation’. Following mapping, four BCTs were selected for inclusion in an intervention for GPs or pharmacists: ‘Action planning’, ‘Prompts/cues’, ‘Modelling or demonstrating of behaviour’ and ‘Salience of consequences’. An additional BCT (‘Social support or encouragement’) was selected for inclusion in a community pharmacy-based intervention in order to address barriers relating to interprofessional working that were encountered by pharmacists.

Conclusions
Selected BCTs will be operationalised in a theory-based intervention to improve appropriate polypharmacy for older people, to be delivered in GP practice and community pharmacy settings. Future research will involve development and feasibility testing of this intervention.

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Numerical sound synthesis is often carried out using the finite difference time domain method. In order to analyse the stability of the derived models, energy methods can be used for both linear and nonlinear settings. For Hamiltonian systems the existence of a conserved numerical energy-like quantity can be used to guarantee the stability of the simulations. In this paper it is shown how to derive similar discrete conservation laws in cases where energy is dissipated due to friction or in the presence of an energy source due to an external force. A damped harmonic oscillator (for which an analytic solution is available) is used to present the proposed methodology. After showing how to arrive at a conserved quantity, the simulation of a nonlinear single reed shows an example of an application in the context of musical acoustics.

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In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF). This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk) and co-occurrence adjustment (degree balance and distribution). We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of) the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.

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In this paper, a novel and effective lip-based biometric identification approach with the Discrete Hidden Markov Model Kernel (DHMMK) is developed. Lips are described by shape features (both geometrical and sequential) on two different grid layouts: rectangular and polar. These features are then specifically modeled by a DHMMK, and learnt by a support vector machine classifier. Our experiments are carried out in a ten-fold cross validation fashion on three different datasets, GPDS-ULPGC Face Dataset, PIE Face Dataset and RaFD Face Dataset. Results show that our approach has achieved an average classification accuracy of 99.8%, 97.13%, and 98.10%, using only two training images per class, on these three datasets, respectively. Our comparative studies further show that the DHMMK achieved a 53% improvement against the baseline HMM approach. The comparative ROC curves also confirm the efficacy of the proposed lip contour based biometrics learned by DHMMK. We also show that the performance of linear and RBF SVM is comparable under the frame work of DHMMK.

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The principle aspects of passive intermodulation (PIM) characterisation in distributed printed circuits with cascaded lumped nonlinearities are presented. Mechanisms of PIM generations have been investigated experimentally and modelled using the formalism of X-parameters. The devised equivalent circuit models are applied to the analysis of microstrip lines with distributed and cascaded lumped sources of nonlinearity. The dynamic measurements have revealed that PIM generation rates in straight and meandered microstrip lines differ and significantly deviate from those expected for the respective discrete sources of nonlinearity. The obtained results indicate that multiple physical sources of nonlinearity contribute to PIM generation in printed circuits. Finally, it is demonstrated that the electrical discontinuities can have significant effect on the overall PIM response of the distributed passive circuits and cause PIM product leakage and parasitic coupling between isolated circuit elements.

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The food industry is moving towards the use of natural sweeteners such as those produced by Stevia rebaudiana due to the number of health and safety concerns surrounding artificial sweeteners. Despite the fact that these sweeteners are natural; they cannot be assumed safe. Steviol glycosides have a steroidal structure and therefore may have the potential to act as an endocrine disruptor in the body. Reporter gene assays (RGAs), H295R steroidogenesis assay and Ca(2+) fluorimetry based assays using human sperm cells have been used to assess the endocrine disrupting potential of two steviol glycosides: stevioside and rebaudioside A, and their metabolite steviol. A decrease in transcriptional activity of the progestagen receptor was seen following treatment with 25,000 ng/ml steviol in the presence of progesterone (157 ng/ml) resulting in a 31% decrease in progestagen response (p=<0.01). At the level of steroidogenesis, the metabolite steviol (500-25,000 ng/ml) increased progesterone production significantly by 2.3 fold when exposed to 10,000 ng/ml (p=<0.05) and 5 fold when exposed to 25,000 ng/ml (p=<0.001). Additionally, steviol was found to induce an agonistic response on CatSper, a progesterone receptor of sperm, causing a rapid influx of Ca(2+). The response was fully inhibited using a specific CatSper inhibitor. These findings highlight the potential for steviol to act as a potential endocrine disruptor.