30 resultados para domain-specific expertise


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Due to dynamic variability, identifying the specific conditions under which non-functional requirements (NFRs) are satisfied may be only possible at runtime. Therefore, it is necessary to consider the dynamic treatment of relevant information during the requirements specifications. The associated data can be gathered by monitoring the execution of the application and its underlying environment to support reasoning about how the current application configuration is fulfilling the established requirements. This paper presents a dynamic decision-making infrastructure to support both NFRs representation and monitoring, and to reason about the degree of satisfaction of NFRs during runtime. The infrastructure is composed of: (i) an extended feature model aligned with a domain-specific language for representing NFRs to be monitored at runtime; (ii) a monitoring infrastructure to continuously assess NFRs at runtime; and (iii) a exible decision-making process to select the best available configuration based on the satisfaction degree of the NRFs. The evaluation of the approach has shown that it is able to choose application configurations that well fit user NFRs based on runtime information. The evaluation also revealed that the proposed infrastructure provided consistent indicators regarding the best application configurations that fit user NFRs. Finally, a benefit of our approach is that it allows us to quantify the level of satisfaction with respect to NFRs specification.

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The sharing of product and process information plays a central role in coordinating supply chains operations and is a key driver for their success. "Linked pedigrees" - linked datasets, that encapsulate event based traceability information of artifacts as they move along the supply chain, provide a scalable mechanism to record and facilitate the sharing of track and trace knowledge among supply chain partners. In this paper we present "OntoPedigree" a content ontology design pattern for the representation of linked pedigrees, that can be specialised and extended to define domain specific traceability ontologies. Events captured within the pedigrees are specified using EPCIS - a GS1 standard for the specification of traceability information within and across enterprises, while certification information is described using PROV - a vocabulary for modelling provenance of resources. We exemplify the utility of OntoPedigree in linked pedigrees generated for supply chains within the perishable goods and pharmaceuticals sectors.

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Some organizations end up reimplementing the same class of business process over and over: an "administrative process", which consists of managing a form through several states and involving various roles in the organization. This results in wasted time that could be dedicated to better understanding the process or dealing with the fine details that are specific to the process. Existing virtual office solutions require specific training and infrastructure andmay result in vendor lock-in. In this paper, we propose using a high-level domain-specific language (AdminDSL) to describe the administrative process and a separate code generator targeting a standard web framework. We have implemented the approach using Xtext, EGL and the Django web framework, and we illustrate it through two case studies: a synthetic examination process which illustrates the architecture of the generated code, and a real-world workplace survey process that identified several future avenues for improvement.

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During inflammation, many cell types release reactive oxygen species (ROS) via the respiratory burst. These ROS are potent oxidants of LDL and its major protein, apolipoprotein B. Whilst native LDL is taken up by endothelial cells via a feedback controlled receptor-regulated process, oxidative modification of LDL renders it a ligand for many scavenger receptors. Scavenger receptors include CD-36, LOX-1 and the prototypic macrophage SR A I/II, all of which are variably expressed. Uncontrolled uptake of oxidised LDL is implicated in the pathogenesis of atherosclerosis. In addition, oxidised LDL increases CCR2 protein and mRNA expression on monocytes, and thus may contribute to monocyte retention and perpetuation in inflammatory, unstable atherosclerotic lesions. However, little data are available on the effects of specific minor modifications to apolipoprotein B. In order to identify the sequence specificity and nature of oxidative modifications which confer altered properties on LDL, we have investigated the effects of modified peptides (which correspond to the putative LDLR binding domain) on LDL uptake by HUVECs and U937 monocytes.

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Eukaryotic translation elongation factor 3 (eEF3) is a fungal-specific ATPase proposed to catalyze the release of deacylated-tRNA from the ribosomal E-site. In addition, it has been shown to interact with the aminoacyl-tRNA binding GTPase elongation factor 1A (eEF1A), perhaps linking the E and A sites. Domain mapping demonstrates that amino acids 775-980 contain the eEF1A binding sites. Domain III of eEF1A, which is also involved in actin-related functions, is the site of eEF3 binding. The binding of eEF3 to eEF1A is enhanced by ADP, indicating the interaction is favored post-ATP hydrolysis but is not dependent on the eEF1A-bound nucleotide. A temperature-sensitive P915L mutant in the eEF1A binding site of eEF3 has reduced ATPase activity and affinity for eEF1A. These results support the model that upon ATP hydrolysis, eEF3 interacts with eEF1A to help catalyze the delivery of aminoacyl-tRNA at the A-site of the ribosome. The dynamics of when eEF3 interacts with eEF1A may be part of the signal for transition of the post to pre-translocational ribosomal state in yeast.

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In a series of experiments, we tested category-specific activation in normal parti¬cipants using magnetoencephalography (MEG). Our experiments explored the temporal processing of objects, as MEG characterises neural activity on the order of milliseconds. Our experiments explored object-processing, including assessing the time-course of ob¬ject naming, early differences in processing living compared with nonliving objects and processing objects at the basic compared with the domain level, and late differences in processing living compared with nonliving objects and processing objects at the basic compared with the domain level. In addition to studies using normal participants, we also utilised MEG to explore category-specific processing in a patient with a deficit for living objects. Our findings support the cascade model of object naming (Humphreys et al., 1988). In addition, our findings using normal participants demonstrate early, category-specific perceptual differences. These findings are corroborated by our patient study. In our assessment of the time-course of category-specific effects as well as a separate analysis designed to measure semantic differences between living and nonliving objects, we found support for the sensory/motor model of object naming (Martin, 1998), in addition to support for the cascade model of object naming. Thus, object processing in normal participants appears to be served by a distributed network in the brain, and there are both perceptual and semantic differences between living and nonliving objects. A separate study assessing the influence of the level at which you are asked to identify an object on processing in the brain found evidence supporting the convergence zone hypothesis (Damasio, 1989). Taken together, these findings indicate the utility of MEG in exploring the time-course of object processing, isolating early perceptual and later semantic effects within the brain.

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Cognitive linguistics scholars argue that metaphor is fundamentally a conceptual process of mapping one domain of experience onto another domain. The study of metaphor in the context of Translation Studies has not, unfortunately, kept pace with the discoveries about the nature and role of metaphor in the cognitive sciences. This study aims primarily to fill part of this gap of knowledge. Specifically, the thesis is an attempt to explore some implications of the conceptual theory of metaphor for translation. Because the study of metaphor in translation is also based on views about the nature of translation, the thesis first presents a general overview of the discipline of Translation Studies, describing the major models of translation. The study (in Chapter Two) then discusses the major traditional theories of metaphor (comparison, substitution and interaction theories) and shows how the ideas of those theories were adopted in specific translation studies of metaphor. After that, the study presents a detailed account of the conceptual theory of metaphor and some hypothetical implications for the study of metaphor in translation from the perspective of cognitive linguistics. The data and methodology are presented in Chapter Four. A novel classification of conceptual metaphor is presented which distinguishes between different source domains of conceptual metaphors: physical, human-life and intertextual. It is suggested that each source domain places different demands on translators. The major sources of the data for this study are (1) the translations done by the Foreign Broadcasting Information Service (FBIS), which is a translation service of the Central Intelligence Agency (CIA) in the United Sates of America, of a number of speeches by the Iraqi president Saddam Hussein during the Gulf Crisis (1990-1991) and (2) official (governmental) Omani translations of National Day speeches of Sultan Qaboos bin Said of Oman.

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This research investigated expertise in hazardous substance risk assessment (HSRA). Competent pro-active risk assessment is needed to prevent occupational ill-health caused by hazardous substance exposure occurring in the future. In recent years there has been a strong demand for HSRA expertise and a shortage of expert practitioners. The discipline of Occupational Hygiene was identified as the key repository of knowledge and skills for HSRA and one objective of this research was to develop a method to elicit this expertise from experienced occupational hygienists. In the study of generic expertise, many methods of knowledge elicitation (KE) have been investigated, since this has been relevant to the development of 'expert systems' (thinking computers). Here, knowledge needed to be elicited from human experts, and this stage was often a bottleneck in system development, since experts could not explain the basis of their expertise. At an intermediate stage, information collected was used to structure a basic model of hazardous substance risk assessment activity (HSRA Model B) and this formed the basis of tape transcript analysis in the main study with derivation of a 'classification' and a 'performance matrix'. The study aimed to elicit the expertise of occupational hygienists and compare their performance with other health and safety professionals (occupational health physicians, occupational health nurses, health and safety practitioners and trainee health and safety inspectors), as evaluated using the matrix. As a group, the hygienists performed best in the exercise, and this group were particularly good at process elicitation and at recommending specific control measures, although the other groups also performed well in selected aspects of the matrix and the work provided useful findings and insights. From the research, two models of HSRA have been derived, an HSRA aid, together with a novel videotape KE technique and interesting research findings. The implications of this are discussed with respect to future training of HS professionals and wider application of the videotape KE method.

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Evidence-based medicine relies on repositories of empirical research evidence that can be used to support clinical decision making for improved patient care. However, retrieving evidence from such repositories at local sites presents many challenges. This paper describes a methodological framework for automatically indexing and retrieving empirical research evidence in the form of the systematic reviews and associated studies from The Cochrane Library, where retrieved documents are specific to a patient-physician encounter and thus can be used to support evidence-based decision making at the point of care. Such an encounter is defined by three pertinent groups of concepts - diagnosis, treatment, and patient, and the framework relies on these three groups to steer indexing and retrieval of reviews and associated studies. An evaluation of the indexing and retrieval components of the proposed framework was performed using documents relevant for the pediatric asthma domain. Precision and recall values for automatic indexing of systematic reviews and associated studies were 0.93 and 0.87, and 0.81 and 0.56, respectively. Moreover, precision and recall for the retrieval of relevant systematic reviews and associated studies were 0.89 and 0.81, and 0.92 and 0.89, respectively. With minor modifications, the proposed methodological framework can be customized for other evidence repositories. © 2010 Elsevier Inc.

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This thesis explores the process of developing a principled approach for translating a model of mental-health risk expertise into a probabilistic graphical structure. Probabilistic graphical structures can be a combination of graph and probability theory that provide numerous advantages when it comes to the representation of domains involving uncertainty, domains such as the mental health domain. In this thesis the advantages that probabilistic graphical structures offer in representing such domains is built on. The Galatean Risk Screening Tool (GRiST) is a psychological model for mental health risk assessment based on fuzzy sets. In this thesis the knowledge encapsulated in the psychological model was used to develop the structure of the probability graph by exploiting the semantics of the clinical expertise. This thesis describes how a chain graph can be developed from the psychological model to provide a probabilistic evaluation of risk that complements the one generated by GRiST’s clinical expertise by the decomposing of the GRiST knowledge structure in component parts, which were in turned mapped into equivalent probabilistic graphical structures such as Bayesian Belief Nets and Markov Random Fields to produce a composite chain graph that provides a probabilistic classification of risk expertise to complement the expert clinical judgements

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Clinical Decision Support Systems (CDSSs) need to disseminate expertise in formats that suit different end users and with functionality tuned to the context of assessment. This paper reports research into a method for designing and implementing knowledge structures that facilitate the required flexibility. A psychological model of expertise is represented using a series of formally specified and linked XML trees that capture increasing elements of the model, starting with hierarchical structuring, incorporating reasoning with uncertainty, and ending with delivering the final CDSS. The method was applied to the Galatean Risk and Safety Tool, GRiST, which is a web-based clinical decision support system (www.egrist.org) for assessing mental-health risks. Results of its clinical implementation demonstrate that the method can produce a system that is able to deliver expertise targetted and formatted for specific patient groups, different clinical disciplines, and alternative assessment settings. The approach may be useful for developing other real-world systems using human expertise and is currently being applied to a logistics domain. © 2013 Polish Information Processing Society.

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This thesis examines the ways Indonesian politicians exploit the rhetorical power of metaphors in the Indonesian political discourse. The research applies the Conceptual Metaphor Theory, Metaphorical Frame Analysis and Critical Discourse Analysis to textual and oral data. The corpus comprises: 150 political news articles from two newspapers (Harian Kompas and Harian Waspada, 2010-2011 edition), 30 recordings of two television news and talk-show programmes (TV-One and Metro-TV), and 20 interviews with four legislators, two educated persons and two laymen. For this study, a corpus of written bahasa Indonesia was also compiled, which comprises 150 texts of approximately 439,472 tokens. The data analysis shows the potential power of metaphors in relation to how politicians communicate the results of their thinking, reasoning and meaning-making through language and discourse and its social consequences. The data analysis firstly revealed 1155 metaphors. These metaphors were then classified into the categories of conventional metaphor, cognitive function of metaphor, metaphorical mapping and metaphor variation. The degree of conventionality of metaphors is established based on the sum of expressions in each group of metaphors. Secondly, the analysis revealed that metaphor variation is influenced by the broader Indonesian cultural context and the natural and physical environment, such as the social dimension, the regional, style and the individual. The mapping system of metaphor is unidirectionality. Thirdly, the data show that metaphoric thought pervades political discourse in relation to its uses as: (1) a felicitous tool for the rhetoric of political leaders, (2) part of meaning-making that keeps the discourse contexts alive and active, and (3) the degree to which metaphor and discourse shape the conceptual structures of politicians‟ rhetoric. Fourthly, the analysis of data revealed that the Indonesian political discourse attempts to create both distance and solidarity towards general and specific social categories accomplished via metaphorical and frame references to the conceptualisations of us/them. The result of the analysis shows that metaphor and frame are excellent indicators of the us/them categories which work dialectically in the discourse. The acts of categorisation via metaphors and frames at both textual and conceptual level activate asymmetrical concepts and contribute to social and political hierarchical constructs, i.e. WEAKNESS vs.POWER, STUDENT vs. TEACHER, GHOST vs. CHOSEN WARRIOR, and so on. This analysis underscores the dynamic nature of categories by documenting metaphorical transfers between, i.e. ENEMY, DISEASE, BUSINESS, MYSTERIOUS OBJECT and CORRUPTION, LAW, POLITICS and CASE. The metaphorical transfers showed that politicians try to dictate how they categorise each other in order to mobilise audiences to act on behalf of their ideologies and to create distance and solidarity.

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Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histo-compatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVY-DGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available Large-scale massively parallel molecular dynamics (MD) simulations of the human class I major histocompatibility complex (MHC) protein HLA-A*0201 bound to a decameric tumor-specific antigenic peptide GVYDGREHTV were performed using a scalable MD code on high-performance computing platforms. Such computational capabilities put us in reach of simulations of various scales and complexities. The supercomputing resources available for this study allow us to compare directly differences in the behavior of very large molecular models; in this case, the entire extracellular portion of the peptide–MHC complex vs. the isolated peptide binding domain. Comparison of the results from the partial and the whole system simulations indicates that the peptide is less tightly bound in the partial system than in the whole system. From a detailed study of conformations, solvent-accessible surface area, the nature of the water network structure, and the binding energies, we conclude that, when considering the conformation of the α1–α2 domain, the α3 and β2m domains cannot be neglected. © 2004 Wiley Periodicals, Inc. J Comput Chem 25: 1803–1813, 2004

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Social media influence analysis, sometimes also called authority detection, aims to rank users based on their influence scores in social media. Existing approaches of social influence analysis usually focus on how to develop effective algorithms to quantize users’ influence scores. They rarely consider a person’s expertise levels which are arguably important to influence measures. In this paper, we propose a computational approach to measuring the correlation between expertise and social media influence, and we take a new perspective to understand social media influence by incorporating expertise into influence analysis. We carefully constructed a large dataset of 13,684 Chinese celebrities from Sina Weibo (literally ”Sina microblogging”). We found that there is a strong correlation between expertise levels and social media influence scores. Our analysis gave a good explanation of the phenomenon of “top across-domain influencers”. In addition, different expertise levels showed influence variation patterns: e.g., (1) high-expertise celebrities have stronger influence on the “audience” in their expertise domains; (2) expertise seems to be more important than relevance and participation for social media influence; (3) the audiences of top expertise celebrities are more likely to forward tweets on topics outside the expertise domains from high-expertise celebrities.

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The mechanisms for regulating PIKfyve complex activity are currently emerging. The PIKfyve complex, consisting of the phosphoinositide kinase PIKfyve (also known as FAB1), VAC14 and FIG4, is required for the production of phosphatidylinositol-3,5-bisphosphate (PI(3,5)P2). PIKfyve function is required for homeostasis of the endo/lysosomal system and is crucially implicated in neuronal function and integrity, as loss of function mutations in the PIKfyve complex lead to neurodegeneration in mouse models and human patients. Our recent work has shown that the intracellular domain of the Amyloid Precursor Protein (APP), a molecule central to the aetiology of Alzheimer's disease binds to VAC14 and enhances PIKfyve function. Here we utilise this recent advance to create an easy-to-use tool for increasing PIKfyve activity in cells. We fused APP's intracellular domain (AICD) to the HIV TAT domain, a cell permeable peptide allowing proteins to penetrate cells. The resultant TAT-AICD fusion protein is cell permeable and triggers an increase of PI(3,5)P2. Using the PI(3,5)P2 specific GFP-ML1Nx2 probe we show that cell-permeable AICD alters PI(3,5)P2 dynamics. TAT-AICD also provides partial protection from pharmacological inhibition of PIKfyve. All three lines of evidence show that the APP intracellular domain activates the PIKfyve complex in cells, a finding that is important for our understanding of the mechanism of neurodegeneration in Alzheimer's disease.