929 resultados para approaches to moral issues


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The common view that research informs teaching assumes a linear approach whereby teaching is considered an output of research. This paper reports the findings of an action research project that identified the issues and challenges faced by those working across health and social care when working with people with dementia from minority ethnic communities. It explored the research-teaching nexus by using an approach to teaching that was research-based as opposed to research-led. A storyboarding technique was used which involved identifying and dissecting real life experiences for discussion. The realisation that each story was unique to the individual demonstrated the benefits and importance of education and training for applying a person-centred approach to dementia care. This project also revealed the benefits of actively engaging course participants with research moving them from being recipients of research, to research- active. Such a process not only encouraged their intrinsic motivations but, also, critical thinking and reflective practice to support deep learning. Such findings demonstrate the benefits of linking teaching with research.

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In this extended abstract, we discuss recent research at Worcester into the inclusion of AI into ‘Serious Games’. Serious Games research intends to harness the power of computer game technology to produce educational and training materials. We prefer the name ‘Immersive Environments’ (IEs) since this emphasises the human psychological dimension. Creation of compelling and convincing learning software requires a rich engagement of the learner, and a convincing learning experience. We believe that various aspects of the AI tradition can inform the production of such learning.

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The work of cataloging and digitizing the Historical Ar-chive of the Prelature of Humahuaca, presents us with documen-tary mass, almost unused for historical research. Due to organiza-tional reasons, this documentary heritage was limited to consulta-tion of researchers. The development of “Documenta” project will allow us to know the contents of that file, get closer to these do-cuments for consultation and scientific production.

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This article examines European Union (EU) approaches to the question of human rights violations in Kosovo before and after its proclamation of independence, in February 2008. While the 1999 NATO-led humanitarian intervention in the region was often justified as necessary due to the continuous abuses of human rights, perpetrated by the Serbian forces against the ethic Kosovo Albanians, the post-interventionist period has witnessed a dramatic reversal of roles, with the rights of the remaining Serbian minority being regularly abused by the dominant Albanian population. However, in contrast to the former scenario, the Brussels administration has remained quite salient about the post-independence context – a grey zone of unviable political and social components, capable of generating new confrontations and human rights abuses within the borders of Kosovo. Aware of this dynamic and the existing EU official rhetoric, it is possible to conclude that the embedded human rights concerns in Kosovo are not likely to disappear, but even more importantly, their relevance has been significantly eroded.

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Purpose – The purpose of this paper is to survey various meanings attached to a public-private partnership (PPP) and related aspects in Western literature, and identify commonalities and differences between them. Additionally, the article intends to critically assess conflicting and overlapping views on contractual and institutional PPPs, their forms and models, and draw insights for transitional economies. Design/methodology/approach – The article contrasts and compares views on PPP meanings, forms and models within Western PPP literature, and also draws comparisons with understanding of partnership aspects in the Russian language sources. The paper examines theories underpinning PPPs, builds connections to PPP advantages and drawbacks, and provides critical assessment of net benefits that PPPs may bring along to the society. Findings – The article concludes that future PPP research in transitional countries such as Kazakhstan and Russia, particularly in the area of organisational and power arrangements in partnerships, may delineate new concepts such as government as a guarantor of a PPP project, social significance of a PPP project, and risk management in a country’s contextual environment. Practical implications – In transitional countries, in which PPPs are in their infancy, clarification of theoretical positions, and identification of commonalities and differences between meanings attached to the PPP terminology may enable better decisions by researchers and practitioners in their selection and further development of partnerships and related concepts. Originality/value – Research in the field of PPPs in transitional countries such as Russia and Kazakhstan is in its infancy. The paper intends to contribute to the body of knowledge about PPPs by providing detailed account and categorisation of their principal meanings, forms, models, underpinning theories, and drawing insights for future research in transitional countries.

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Abstract. The use of artificial immune systems in intrusion detection is an appealing concept for two reasons. Firstly, the human immune system provides the human body with a high level of protection from invading pathogens, in a robust, self-organised and distributed manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. It is hoped that biologically inspired approaches in this area, including the use of immune-based systems will be able to meet this challenge. Here we collate the algorithms used, the development of the systems and the outcome of their implementation. It provides an introduction and review of the key developments within this field, in addition to making suggestions for future research.

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Cancer and cardio-vascular diseases are the leading causes of death world-wide. Caused by systemic genetic and molecular disruptions in cells, these disorders are the manifestation of profound disturbance of normal cellular homeostasis. People suffering or at high risk for these disorders need early diagnosis and personalized therapeutic intervention. Successful implementation of such clinical measures can significantly improve global health. However, development of effective therapies is hindered by the challenges in identifying genetic and molecular determinants of the onset of diseases; and in cases where therapies already exist, the main challenge is to identify molecular determinants that drive resistance to the therapies. Due to the progress in sequencing technologies, the access to a large genome-wide biological data is now extended far beyond few experimental labs to the global research community. The unprecedented availability of the data has revolutionized the capabilities of computational researchers, enabling them to collaboratively address the long standing problems from many different perspectives. Likewise, this thesis tackles the two main public health related challenges using data driven approaches. Numerous association studies have been proposed to identify genomic variants that determine disease. However, their clinical utility remains limited due to their inability to distinguish causal variants from associated variants. In the presented thesis, we first propose a simple scheme that improves association studies in supervised fashion and has shown its applicability in identifying genomic regulatory variants associated with hypertension. Next, we propose a coupled Bayesian regression approach -- eQTeL, which leverages epigenetic data to estimate regulatory and gene interaction potential, and identifies combinations of regulatory genomic variants that explain the gene expression variance. On human heart data, eQTeL not only explains a significantly greater proportion of expression variance in samples, but also predicts gene expression more accurately than other methods. We demonstrate that eQTeL accurately detects causal regulatory SNPs by simulation, particularly those with small effect sizes. Using various functional data, we show that SNPs detected by eQTeL are enriched for allele-specific protein binding and histone modifications, which potentially disrupt binding of core cardiac transcription factors and are spatially proximal to their target. eQTeL SNPs capture a substantial proportion of genetic determinants of expression variance and we estimate that 58% of these SNPs are putatively causal. The challenge of identifying molecular determinants of cancer resistance so far could only be dealt with labor intensive and costly experimental studies, and in case of experimental drugs such studies are infeasible. Here we take a fundamentally different data driven approach to understand the evolving landscape of emerging resistance. We introduce a novel class of genetic interactions termed synthetic rescues (SR) in cancer, which denotes a functional interaction between two genes where a change in the activity of one vulnerable gene (which may be a target of a cancer drug) is lethal, but subsequently altered activity of its partner rescuer gene restores cell viability. Next we describe a comprehensive computational framework --termed INCISOR-- for identifying SR underlying cancer resistance. Applying INCISOR to mine The Cancer Genome Atlas (TCGA), a large collection of cancer patient data, we identified the first pan-cancer SR networks, composed of interactions common to many cancer types. We experimentally test and validate a subset of these interactions involving the master regulator gene mTOR. We find that rescuer genes become increasingly activated as breast cancer progresses, testifying to pervasive ongoing rescue processes. We show that SRs can be utilized to successfully predict patients' survival and response to the majority of current cancer drugs, and importantly, for predicting the emergence of drug resistance from the initial tumor biopsy. Our analysis suggests a potential new strategy for enhancing the effectiveness of existing cancer therapies by targeting their rescuer genes to counteract resistance. The thesis provides statistical frameworks that can harness ever increasing high throughput genomic data to address challenges in determining the molecular underpinnings of hypertension, cardiovascular disease and cancer resistance. We discover novel molecular mechanistic insights that will advance the progress in early disease prevention and personalized therapeutics. Our analyses sheds light on the fundamental biological understanding of gene regulation and interaction, and opens up exciting avenues of translational applications in risk prediction and therapeutics.

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Since 2005, harmonized catch assessment surveys (CASs) have been implemented on Lake Victoria in the three riparian countries Uganda, Kenya, and Tanzania to monitor the commercial fish stocks and provide their management advice. The regionally harmonized standard operating procedures for CASs have not been wholly followed due to logistical difficulties. Yet the new approaches adopted have not been documented. This study investigated the alternative approaches used to estimate fish catches on the lake with the aim of determining the most reliable one for providing management advice and also the effect of current sampling routine on the precision of catch estimates provided. The study found the currently used lake-wide approach less reliable and more biased in providing catch estimates compared to the district based approach. Noticeable differences were detected in catch estimates between different months of the year. The study recommends future analyses of CAS data collected on the lake to follow the district based approach. Future CASs should also consider seasonal variations in the sampling design by providing for replication of sampling. The SOPs need updating to document the procedures that deviate from the original sampling design.

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The use of artificial immune systems in intrusion detection is an appealing concept for two reasons. Firstly, the human immune system provides the human body with a high level of protection from invading pathogens, in a robust, self-organised and distributed manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. It is hoped that biologically inspired approaches in this area, including the use of immune-based systems will be able to meet this challenge. Here we review the algorithms used, the development of the systems and the outcome of their implementation. We provide an introduction and analysis of the key developments within this field, in addition to making suggestions for future research.

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Abstract. The use of artificial immune systems in intrusion detection is an appealing concept for two reasons. Firstly, the human immune system provides the human body with a high level of protection from invading pathogens, in a robust, self-organised and distributed manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. It is hoped that biologically inspired approaches in this area, including the use of immune-based systems will be able to meet this challenge. Here we collate the algorithms used, the development of the systems and the outcome of their implementation. It provides an introduction and review of the key developments within this field, in addition to making suggestions for future research.

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The use of artificial immune systems in intrusion detection is an appealing concept for two reasons. Firstly, the human immune system provides the human body with a high level of protection from invading pathogens, in a robust, self-organised and distributed manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. It is hoped that biologically inspired approaches in this area, including the use of immune-based systems will be able to meet this challenge. Here we review the algorithms used, the development of the systems and the outcome of their implementation. We provide an introduction and analysis of the key developments within this field, in addition to making suggestions for future research.

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Serosurveillance is a powerful tool fundamental to understanding infectious disease dynamics. The presence of virus neutralising antibody (VNAb) in sera is considered the best evidence of infection, or indeed vaccination, and the gold standard serological assay for their detection is the virus neutralisation test (VNT). However, VNTs are labour intensive, costly and time consuming. In addition, VNTs for the detection of antibodies to highly pathogenic viruses require the use of high containment facilities, restricting the application of these assays to the few laboratories with adequate facilities. As a result, robust serological data on such viruses are limited. In this thesis I develop novel VNTs for the detection of VNAb to two important, highly pathogenic, zoonotic viruses; rabies and Rift Valley fever virus (RVFV). The pseudotype-based neutralisation test developed in this study allows for the detection of rabies VNAb without the requirement for high containment facilities. This assay was utilised to investigate the presence of rabies VNAb in animals from a variety of ecological settings. In this thesis I present evidence of natural rabies infection in both domestic dogs and lions from rabies endemic settings. The assay was further used to investigate the kinetics of VNAb response to rabies vaccination in a cohort of free-roaming dogs. The RVFV neutralisation assay developed herein utilises a recombinant luciferase expressing RVFV, which allows for rapid, high-throughput serosurveillance of this important neglected pathogen. In this thesis I present evidence of RVFV infection in a variety of domestic and wildlife species from Northern Tanzania, in addition to the detection of low-level transmission of RVFV during interepidemic periods. Additionally, the investigation of a longitudinal cohort of domestic livestock also provided evidence of rapid waning of RVF VNAb following natural infection. Collectively, the serological data presented in this thesis are consistent with existing data in the literature generated using the gold standard VNTs. Increasing the availability of serological assays will allow the generation of robust serological data, which are imperative to enhancing our understanding of the complex, multi-host ecology of these two viruses.

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Findings on the role that emotion plays in human behavior have transformed Artificial Intelligence computations. Modern research explores how to simulate more intelligent and flexible systems. Several studies focus on the role that emotion has in order to establish values for alternative decision and decision outcomes. For instance, Busemeyer et al. (2007) argued that emotional state affects the subjectivity value of alternative choice. However, emotional concepts in these theories are generally not defined formally and it is difficult to describe in systematic detail how processes work. In this sense, structures and processes cannot be explicitly implemented. Some attempts have been incorporated into larger computational systems that try to model how emotion affects human mental processes and behavior (Becker-Asano & Wachsmuth, 2008; Marinier, Laird & Lewis, 2009; Marsella & Gratch, 2009; Parkinson, 2009; Sander, Grandjean & Scherer, 2005). As we will see, some tutoring systems have explored this potential to inform user models. Likewise, dialogue systems, mixed-initiative planning systems, or systems that learn from observation could also benefit from such an approach (Dickinson, Brew & Meurers, 2013; Jurafsky & Martin, 2009). That is, considering emotion as interaction can be relevant in order to explain the dynamic role it plays in action and cognition (see Boehner et al., 2007).

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Despite all intentions in the course of the Bologna Process and decades of investment into improving the social dimension, results in many national and international studies show that inequity remains stubbornly persistent, and that inequity based on socio-economic status, parental education, gender, country-of-origin, rural background and more continues to prevail in our Higher Education systems and at the labour market. While improvement has been shown, extrapolation of the gains of the last 40 years in the field show that it could take over 100 years for disadvantaged groups to catch up with their more advantaged peers, should the current rate of improvement be maintained. Many of the traditional approaches to improving equity have also necessitated large-scale public investments, in the form of direct support to underrepresented groups. In an age of austerity, many countries in Europe are finding it necessary to revisit and scale down these policies, so as to accommodate other priorities, such as balanced budgets or dealing with an aging population. An analysis of the current situation indicates that the time is ripe for disruptive innovations to mobilise the cause forward by leaps and bounds, instead of through incrementalist approaches. Despite the list of programmes in this analysis there is very little evidence as to the causal link between programmes, methodologies for their use and increases/improvements in equity in institutions. This creates a significant information gap for institutions and public authorities seeking for indicators to allocate limited resources to equity improving initiatives, without adequate evidence of effectiveness. The IDEAS project and this publication aims at addressing and improving this information gap. (DIPF/Orig.)

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The fruit is one of the most complex and important structures produced by flowering plants, and understanding the development and maturation process of fruits in different angiosperm species with diverse fruit structures is of immense interest. In the work presented here, molecular genetics and genomic analysis are used to explore the processes that form the fruit in two species: The model organism Arabidopsis and the diploid strawberry Fragaria vesca. One important basic question concerns the molecular genetic basis of fruit patterning. A long-standing model of Arabidopsis fruit (the gynoecium) patterning holds that auxin produced at the apex diffuses downward, forming a gradient that provides apical-basal positional information to specify different tissue types along the gynoecium’s length. The proposed gradient, however, has never been observed and the model appears inconsistent with a number of observations. I present a new, alternative model, wherein auxin acts to establish the adaxial-abaxial domains of the carpel primordia, which then ensures proper development of the final gynoecium. A second project utilizes genomics to identify genes that regulate fruit color by analyzing the genome sequences of Fragaria vesca, a species of wild strawberry. Shared and distinct SNPs among three F. vesca accessions were identified, providing a foundation for locating candidate mutations underlying phenotypic variations among different F. vesca accessions. Through systematic analysis of relevant SNP variants, a candidate SNP in FveMYB10 was identified that may underlie the fruit color in the yellow-fruited accessions, which was subsequently confirmed by functional assays. Our lab has previously generated extensive RNA-sequencing data that depict genome-scale gene expression profiles in F. vesca fruit and flower tissues at different developmental stages. To enhance the accessibility of this dataset, the web-based eFP software was adapted for this dataset, allowing visualization of gene expression in any tissues by user-initiated queries. Together, this thesis work proposes a well-supported new model of fruit patterning in Arabidopsis and provides further resources for F. vesca, including genome-wide variant lists and the ability to visualize gene expression. This work will facilitate future work linking traits of economic importance to specific genes and gaining novel insights into fruit patterning and development.