736 resultados para Research issues
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[À l'origine dans / Was originally part of : ESPUM - Dép. médecine sociale et préventive - Travaux et publications]
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[À l'origine dans / Was originally part of : ESPUM - Dép. médecine sociale et préventive - Travaux et publications]
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[À l'origine dans / Was originally part of : ESPUM - Dép. médecine sociale et préventive - Travaux et publications]
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Using sexual assault on college campuses as a context for interrogating issues management, this study offers a normative model for inclusive issues management through an engagement approach that can better account for the gendered and emotional dimensions of issues. Because public relations literature and research have offered little theoretical or practical guidance for how issues managers can most effectively deal with issues such as sexual assault, this study represents a promising step forward. Results for this study were obtained through 32 in-depth interviews with university issues managers, six focus groups with student populations, and approximately 92 hours of participant observation. By focusing on inclusion, this revised model works to have utility for an array of issues that have previously fallen outside of the dominant masculine and rationale spheres that have worked to silence marginalized publics’ experiences. Through adapting previous issues management models to focus on inclusion at the heart of a strategic process, and engagement as the strategy for achieving this, this study offers a framework for ensuring more voices are heard—which enables organizations to more effectively communicate with their publics. Additionally, findings from this research may also help practitioners at different types of organizations develop better, and proactive, communication strategies for handling emotional and gendered issues as to avoid negative media attention and work to change organizational culture.
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A variety of conservation policies now frame the management of fishing activity and so do also the spatial planning of different sectorial activities. These framework policies are additional to classical fishery management. There is a risk that the policies applying on the marine system are not coherent from a fisheries point of view. The spatial management of fishing activity at regional scale has the potential to meet multiple management objectives, on a habitat basis. Here we consider how to integrate multiple objectives of different policies into integrated ocean management scenarios. In the EU, European Directives and the CFP are now implementing the ecosystem approach to the management of human activity at sea. In this context, we further identify three research needs: • Develop Management Strategy Evaluation (MSE) for multiple-objective and multiple-sector spatial management schemes • Improve knowledge on and evaluation of functional habitats • Develop spatially-explicit end-to-end models with appropriate complexity for spatial MSE The contribution is based on the results of a workshop of the EraNet COFASP.
Managing Succession and Knowledge Transfer in Family Businesses: Lessons from a Comparative Research
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The most natural mode of family firm succession is the intergenerational ownership transfer. Statistical evidence, however, suggests that in most cases the succession process fails. There can be several reasons as a lot of personal, emotional and structural factors can act as an inhibitor to succession. The effectiveness of the implementation of any succession strategy is strongly dependent on the efficiency of intergenerational knowledge transfer, which is related to the parties’ absorptive capacity and willingness to learn. The paper is based on the experiences learned from the INSIST project. In the framework of the project different aspects of family business succession have been investigated in three participating countries (Hungary, Poland and the United Kingdom). The aim of the paper is to identify the patterns of management, succession, knowledge transfer and learning in family businesses. Issues will be examined in detail such as the succession strategies of companies investigated and the efforts family businesses and their managers make in order to harmonize family goals (such as emotional stability, harmony, and reputation) with business- related objectives (e.g. survival, growth or profitability).
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Based on a case study conducted by the researcher on a sample of 618 UG students, this paper focuses on identifying certain flaws in the present educational communication. The researcher after presenting the data analysis of the survey, attempts to highlight the present ELT scenario and its relevance to the present day needs of the society. It also emphasizes on the need to focus on practical dimensions of learning. It substantiates that inadequate language proficiency, lack of presentation skills knowledge and unawareness about life skills are the main reasons for the educated unemployment. Finally, the researcher concludes this paper with some suggestions and recommendations which will help the learners to enhance their communication skills.
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Xenakis’s first electroacoustic pieces (Diamorphoses, 1957; Concret PH, 1958; Analogique B, 1959; Orient-Occident, 1960; and Bohor, 1962) can be called musique concrète. Indeed, these works use the concrète musique tape techniques. But their spirit and aesthetic is very different from those set forth in Pierre Schaeffer’s theories. In fact, these works are quite particular in their whole conception. The two authors of this article are researching this period of Xenakis’s electroacoustic music. In this article, they offer a brief survey of the issues these works raised. To illustrate some of these issues, they use Diamorphoses and Bohor as examples.
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The current research project focuses on the analysis of the critical issues of industrial heritage management in Italy and the preservation of organizational history within the reuse projects of former industrial sites. The organizational and managerial perspective is crucial on two levels. Firstly, it is important in the analysis of the original significance of the site, and in particular its organizational history, and its conservation within the new regeneration strategy. Secondly, it is crucial at the phase of management of reuse projects and its feasibility and sustainability analysis. Based on the analysis of the literature, a unique classification of the reuse strategies that can be implemented in order to regenerate former industrial sites has been formulated. The exploratory research thus adapts a multiple case study design. Eight Italian case studies have been chosen, one for each type of regeneration strategy. Each case study is explored as a stand-alone entity through the analysis of the local differences and idiosyncrasies of the specific context, the factors that stood behind the choice of the reuse strategy and the way the reuse project evolved through the years. Then, the current management of each reuse project is analysed. The narration and musealization of the organizational history is investigated through the spatial dimension, the level of content and the level of expression. Secondly, the case studies are compared through a cross-case analysis from three different perspectives: issues on the phase of preparation and implementation of the reuse projects, critical issues behind the current management of new projects and issues on the ways of preservation and narration of organizational history within the new project. The research shows that all regeneration strategies are affected by the conflict between preservation and change, by the issue of materiality and selectivity.
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Although the debate of what data science is has a long history and has not reached a complete consensus yet, Data Science can be summarized as the process of learning from data. Guided by the above vision, this thesis presents two independent data science projects developed in the scope of multidisciplinary applied research. The first part analyzes fluorescence microscopy images typically produced in life science experiments, where the objective is to count how many marked neuronal cells are present in each image. Aiming to automate the task for supporting research in the area, we propose a neural network architecture tuned specifically for this use case, cell ResUnet (c-ResUnet), and discuss the impact of alternative training strategies in overcoming particular challenges of our data. The approach provides good results in terms of both detection and counting, showing performance comparable to the interpretation of human operators. As a meaningful addition, we release the pre-trained model and the Fluorescent Neuronal Cells dataset collecting pixel-level annotations of where neuronal cells are located. In this way, we hope to help future research in the area and foster innovative methodologies for tackling similar problems. The second part deals with the problem of distributed data management in the context of LHC experiments, with a focus on supporting ATLAS operations concerning data transfer failures. In particular, we analyze error messages produced by failed transfers and propose a Machine Learning pipeline that leverages the word2vec language model and K-means clustering. This provides groups of similar errors that are presented to human operators as suggestions of potential issues to investigate. The approach is demonstrated on one full day of data, showing promising ability in understanding the message content and providing meaningful groupings, in line with previously reported incidents by human operators.
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Recent research trends in computer-aided drug design have shown an increasing interest towards the implementation of advanced approaches able to deal with large amount of data. This demand arose from the awareness of the complexity of biological systems and from the availability of data provided by high-throughput technologies. As a consequence, drug research has embraced this paradigm shift exploiting approaches such as that based on networks. Indeed, the process of drug discovery can benefit from the implementation of network-based methods at different steps from target identification to drug repurposing. From this broad range of opportunities, this thesis is focused on three main topics: (i) chemical space networks (CSNs), which are designed to represent and characterize bioactive compound data sets; (ii) drug-target interactions (DTIs) prediction through a network-based algorithm that predicts missing links; (iii) COVID-19 drug research which was explored implementing COVIDrugNet, a network-based tool for COVID-19 related drugs. The main highlight emerged from this thesis is that network-based approaches can be considered useful methodologies to tackle different issues in drug research. In detail, CSNs are valuable coordinate-free, graphically accessible representations of structure-activity relationships of bioactive compounds data sets especially for medium-large libraries of molecules. DTIs prediction through the random walk with restart algorithm on heterogeneous networks can be a helpful method for target identification. COVIDrugNet is an example of the usefulness of network-based approaches for studying drugs related to a specific condition, i.e., COVID-19, and the same ‘systems-based’ approaches can be used for other diseases. To conclude, network-based tools are proving to be suitable in many applications in drug research and provide the opportunity to model and analyze diverse drug-related data sets, even large ones, also integrating different multi-domain information.
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Depth estimation from images has long been regarded as a preferable alternative compared to expensive and intrusive active sensors, such as LiDAR and ToF. The topic has attracted the attention of an increasingly wide audience thanks to the great amount of application domains, such as autonomous driving, robotic navigation and 3D reconstruction. Among the various techniques employed for depth estimation, stereo matching is one of the most widespread, owing to its robustness, speed and simplicity in setup. Recent developments has been aided by the abundance of annotated stereo images, which granted to deep learning the opportunity to thrive in a research area where deep networks can reach state-of-the-art sub-pixel precision in most cases. Despite the recent findings, stereo matching still begets many open challenges, two among them being finding pixel correspondences in presence of objects that exhibits a non-Lambertian behaviour and processing high-resolution images. Recently, a novel dataset named Booster, which contains high-resolution stereo pairs featuring a large collection of labeled non-Lambertian objects, has been released. The work shown that training state-of-the-art deep neural network on such data improves the generalization capabilities of these networks also in presence of non-Lambertian surfaces. Regardless being a further step to tackle the aforementioned challenge, Booster includes a rather small number of annotated images, and thus cannot satisfy the intensive training requirements of deep learning. This thesis work aims to investigate novel view synthesis techniques to augment the Booster dataset, with ultimate goal of improving stereo matching reliability in presence of high-resolution images that displays non-Lambertian surfaces.
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This article analyzed whether the practices of hearing health care were consistent with the principles of universality, comprehensiveness and equity from the standpoint of professionals. It involved qualitative research conducted at a Medium Complexity Hearing Health Care Center. A social worker, three speech therapists, a physician and a psychologist constituted the study subjects. Interviews were conducted as well as observation registered in a field diary. The thematic analysis technique was used in the analysis of the material. The analysis of interviews resulted in the construction of the following themes: Universality and access to hearing health, Comprehensive Hearing Health Care and Hearing Health and Equity. The study identified issues that interfere with the quality of service and run counter to the principles of Brazilian Unified Health System. The conclusion reached was that a relatively simple investment in training and professional qualification can bring about significant changes in order to promote a more universal, comprehensive and equitable health service.
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Wild animals have been kept as pets for centuries, in Brazil companionship is one of the main reasons why wild species are legally bred and traded. This paper is an attempt to call the attention for problems concerning the welfare of wild pets involved in the trading system in Brazil. Some issues presented are: a) the significant increase in the number of wildlife breeders and traders and the difficulties faced by of the Brazilian government in controlling this activity; b) the main welfare issues faced by breeders and owners of wild pets; and c) the destination of wild pets no longer wanted. Finally, some recommendations are made having the welfare of the animals as a priority.