1000 resultados para transitional relation graph


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Gaining an improved understanding of people diagnosed with schizophrenia has the potential to influence priorities for therapy. Psychosis is commonly understood through the perspective of the medical model. However, the experience of social context surrounding psychosis is not well understood. In this research project we used a phenomenological methodology with a longitudinal design to interview 7 participants across a 12-month period to understand the social experiences surrounding psychosis. Eleven themes were explicated and divided into two phases of the illness experience: (a) transition into emotional shutdown included the experiences of not being acknowledged, relational confusion, not being expressive, detachment, reliving the past, and having no sense of direction; and (b) recovery from emotional shutdown included the experiences of being acknowledged, expression, resolution, independence, and a sense of direction. The experiential themes provide clinicians with new insights to better assess vulnerability, and have the potential to inform goals for therapy.

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In this chapter I look at some issues around the transfer of cultural industry policy between two very different national contexts, the UK and Russia. Specifically it draws on a partnership project between Manchester and St. Petersburg financed by the European Union as part of a program to promote economic development through knowledge transfer between Europe and the countries of the former Soviet Union. This specific project attempted to place the cultural industries squarely within the dimension of economic development, and drew on the expertise of Manchester’s Creative Industries Development Service and other partners to effect this policy transfer

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In response to concerns about the quality of English Language Learning (ELL) education at tertiary level, the Chinese Ministry of Education (CMoE) launched the College English Reform Program (CERP) in 2004. By means of a press release (CMoE, 2005) and a guideline document titled College English Curriculum Requirements (CECR) (CMoE, 2007), the CERP proposed two major changes to the College English assessment policy, which were: (1) the shift to optional status for the compulsory external test, the College English Test Band 4 (CET4); and (2) the incorporation of formative assessment into the existing summative assessment framework. This study investigated the interactions between the College English assessment policy change, the theoretical underpinnings, and the assessment practices within two Chinese universities (one Key University and one Non-Key University). It adopted a sociocultural theoretical perspective to examine the implementation process as experienced by local actors of institutional and classroom levels. Systematic data analysis using a constant comparative method (Merriam, 1998) revealed that contextual factors and implementation issues did not lead to significant differences in the two cases. Lack of training in assessment and the sociocultural factors such as the traditional emphasis on the product of learning and hierarchical teacher/students relationship are decisive and responsible for the limited effect of the reform.

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In this paper a new graph-theory and improved genetic algorithm based practical method is employed to solve the optimal sectionalizer switch placement problem. The proposed method determines the best locations of sectionalizer switching devices in distribution networks considering the effects of presence of distributed generation (DG) in fitness functions and other optimization constraints, providing the maximum number of costumers to be supplied by distributed generation sources in islanded distribution systems after possible faults. The proposed method is simulated and tested on several distribution test systems in both cases of with DG and non DG situations. The results of the simulations validate the proposed method for switch placement of the distribution network in the presence of distributed generation.

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The objective of this thesis is to investigate whether the corporate governance practices adopted by Chinese listed firms are associated with the quality of earnings information. Based on a review of agency and institutional theory, this study develops hypotheses that predict the monitoring effectiveness of the board and the audit committee. Using a combination of univariate and multivariate analyses, the association between corporate governance mechanisms and earnings management are tested from 2004 to 2008. Through analysing the empirical results, a number of findings are summarised as below. First, board independence is weakened by the introduction of government officials as independent directors on the boards. Government officials acting as independent directors, claim that they meet the definition of independent director set by the regulation. However, they have some connection with the State, which is the controlling shareholder in listed SOEs affiliated companies. Consequently, the effect of the independent director’s expertise in constraining earnings management is mitigated as demonstrated by an insignificant association between board expertise and earnings management. An alternative explanation for the inefficiency of board independence may point to the pre-selection of independent directors by the powerful CEO. It is argued that a CEO can manipulate the board composition and choose the "desirable" independent directors to monitor themselves. Second, a number of internal mechanisms, such as board size, board activities, and the separation of the roles of the CEO and chair are found to be significantly associated with discretionary accruals. This result suggests that there are advantages in having a large and active board in the Chinese setting. This can offset the disadvantages associated with large boards, such as increased bureaucracy, and hence, increase the constraining effects of a large and resourceful board. Third, factor analysis identifies two factors: CEO power and board power. CEO power is the factor which consists of CEO duality and turnover, and board power is composed of board size and board activity. The results of CEO power show that if a Chinese listed company has CEO duality and turnover at the same time, it is more likely to have a high level of earnings management. The significant and negative relationship between board power and accruals indicate that large boards with frequent meetings can be associated with low level of earnings management. Overall, the factor analysis suggests that certain governance mechanisms complement each other to become more efficient monitors of opportunistic earnings management. A combination of board characteristics can increase the negative association with earnings management. Fourth, the insignificant results between audit committees and earnings management in Chinese listed firms suggests that the Chinese regulator should strengthen the audit committee functions. This thesis calls for listed firms to disclose more information on audit committee composition and activities, which can facilitate future research on the Chinese audit committee’s monitoring role. Fifth, the interactive results between State ownership and board characteristics show that dominant State ownership has a moderating effect on board monitoring power as the State totally controls 42% of the issued shares. The high percentage of State ownership makes it difficult for the non-controlling institutional shareholders to challenge the State’s dominant status. As a result, the association between non-controlling institutional ownership and earnings management is insignificant in most situations. Lastly, firms audited by the international Big4 have lower abnormal accruals than firms audited by domestic Chinese audit firms. In addition, the inverse U-shape relationship between audit tenure and earnings quality demonstrates the changing effects of audit quality after a certain period of appointment. Furthermore, this thesis finds that listing in Hong Kong Stock Exchanges can be an alternative governance mechanism to discipline Chinese firms to follow strict Hong Kong listing requirements. Management of Hong Kong listed companies are exposed to the scrutiny of international investors and Hong Kong regulators. This in turn reduces their chances of conducting self-interested earnings manipulation. This study is designed to fill the gap in governance literature in China that is related to earnings management. Previous research on corporate governance mechanisms and earnings management in China is not conclusive. The current research builds on previous literature and provides some meaningful implications for practitioners, regulators, academic, and international investors who have investment interests in a transitional country. The findings of this study contribute to corporate governance and earnings management literature in the context of the transitional economy of China. The use of alternative measures for earnings management yields similar results compared with the accruals models and produces additional findings.

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Raman spectroscopy complimented with infrared spectroscopy has been used to study the rare earth based mineral decrespignyite (Y,REE)4Cu(CO3)4Cl(OH)5•2(H2O) and compared with the Raman spectra of a series of selected natural halogenated carbonates from different origins including bastnasite, parisite and northupite. The Raman spectrum of decrespignyite displays three bands are at 1056, 1070 and 1088 cm-1 attributed to the CO32- symmetric stretching vibration. The observation of three symmetric stretching vibrations is very unusual. The position of CO32- symmetric stretching vibration varies with mineral composition. Raman bands of decrespignyite show bands at 1391, 1414, 1489 and 1547 cm-1. Raman spectra of bastnasite, parisite and northupite show a single band at 1433, 1420 and 1554 cm-1 assigned to the ν3 (CO3)2- antisymmetric stretching mode. The observation of additional Raman bands for the ν3 modes for some halogenated carbonates is significant in that it shows distortion of the carbonate anion in the mineral structure. Four Raman bands are observed at 791, 815, 837 and 849 cm-1and assigned to the (CO3)2- ν2 bending modes. Raman bands are observed for decrespignyite at 694, 718 and 746 cm-1 and are assigned to the (CO3)2- ν4 bending modes. Raman bands are observed for the carbonate ν4 in phase bending modes at 722 cm-1 for bastnasite, 736 and 684 cm-1 for parisite, 714 cm-1 for northupite. Multiple bands are observed in the OH stretching region for decrespignyite, bastnasite and parisite indicating the presence of water and OH units in the mineral structure.

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Due to their large surface area, complex chemical composition and high alveolar deposition rate, ultrafine particles (UFPs) (< 0.1 ìm) pose a significant risk to human health and their toxicological effects have been acknowledged by the World Health Organisation. Since people spend most of their time indoors, there is a growing concern about the UFPs present in some indoor environments. Recent studies have shown that office machines, in particular laser printers, are a significant indoor source of UFPs. The majority of printer-generated UFPs are organic carbon and it is unlikely that these particles are emitted directly from the printer or its supplies (such as paper and toner powder). Thus, it was hypothesised that these UFPs are secondary organic aerosols (SOA). Considering the widespread use of printers and human exposure to these particles, understanding the processes involved in particle formation is of critical importance. However, few studies have investigated the nature (e.g. volatility, hygroscopicity, composition, size distribution and mixing state) and formation mechanisms of these particles. In order to address this gap in scientific knowledge, a comprehensive study including state-of-art instrumental methods was conducted to characterise the real-time emissions from modern commercial laser printers, including particles, volatile organic compounds (VOCs) and ozone (O3). The morphology, elemental composition, volatility and hygroscopicity of generated particles were also examined. The large set of experimental results was analysed and interpreted to provide insight into: (1) Emissions profiles of laser printers: The results showed that UFPs dominated the number concentrations of generated particles, with a quasi unimodal size distribution observed for all tests. These particles were volatile, non-hygroscopic and mixed both externally and internally. Particle microanalysis indicated that semi-volatile organic compounds occupied the dominant fraction of these particles, with only trace quantities of particles containing Ca and Fe. Furthermore, almost all laser printers tested in this study emitted measurable concentrations of VOCs and O3. A positive correlation between submicron particles and O3 concentrations, as well as a contrasting negative correlation between submicron particles and total VOC concentrations were observed during printing for all tests. These results proved that UFPs generated from laser printers are mainly SOAs. (2) Sources and precursors of generated particles: In order to identify the possible particle sources, particle formation potentials of both the printer components (e.g. fuser roller and lubricant oil) and supplies (e.g. paper and toner powder) were investigated using furnace tests. The VOCs emitted during the experiments were sampled and identified to provide information about particle precursors. The results suggested that all of the tested materials had the potential to generate particles upon heating. Nine unsaturated VOCs were identified from the emissions produced by paper and toner, which may contribute to the formation of UFPs through oxidation reactions with ozone. (3) Factors influencing the particle emission: The factors influencing particle emissions were also investigated by comparing two popular laser printers, one showing particle emissions three orders of magnitude higher than the other. The effects of toner coverage, printing history, type of paper and toner, and working temperature of the fuser roller on particle number emissions were examined. The results showed that the temperature of the fuser roller was a key factor driving the emission of particles. Based on the results for 30 different types of laser printers, a systematic positive correlation was observed between temperature and particle number emissions for printers that used the same heating technology and had a similar structure and fuser material. It was also found that temperature fluctuations were associated with intense bursts of particles and therefore, they may have impact on the particle emissions. Furthermore, the results indicated that the type of paper and toner powder contributed to particle emissions, while no apparent relationship was observed between toner coverage and levels of submicron particles. (4) Mechanisms of SOA formation, growth and ageing: The overall hypothesis that UFPs are formed by reactions with the VOCs and O3 emitted from laser printers was examined. The results proved this hypothesis and suggested that O3 may also play a role in particle ageing. In addition, knowledge about the mixing state of generated particles was utilised to explore the detailed processes of particle formation for different printing scenarios, including warm-up, normal printing, and printing without toner. The results indicated that polymerisation may have occurred on the surface of the generated particles to produce thermoplastic polymers, which may account for the expandable characteristics of some particles. Furthermore, toner and other particle residues on the idling belt from previous print jobs were a very clear contributing factor in the formation of laser printer-emitted particles. In summary, this study not only improves scientific understanding of the nature of printer-generated particles, but also provides significant insight into the formation and ageing mechanisms of SOAs in the indoor environment. The outcomes will also be beneficial to governments, industry and individuals.

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Recent algorithms for monocular motion capture (MoCap) estimate weak-perspective camera matrices between images using a small subset of approximately-rigid points on the human body (i.e. the torso and hip). A problem with this approach, however, is that these points are often close to coplanar, causing canonical linear factorisation algorithms for rigid structure from motion (SFM) to become extremely sensitive to noise. In this paper, we propose an alternative solution to weak-perspective SFM based on a convex relaxation of graph rigidity. We demonstrate the success of our algorithm on both synthetic and real world data, allowing for much improved solutions to marker less MoCap problems on human bodies. Finally, we propose an approach to solve the two-fold ambiguity over bone direction using a k-nearest neighbour kernel density estimator.

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Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.

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Recommender systems are one of the recent inventions to deal with ever growing information overload in relation to the selection of goods and services in a global economy. Collaborative Filtering (CF) is one of the most popular techniques in recommender systems. The CF recommends items to a target user based on the preferences of a set of similar users known as the neighbours, generated from a database made up of the preferences of past users. With sufficient background information of item ratings, its performance is promising enough but research shows that it performs very poorly in a cold start situation where there is not enough previous rating data. As an alternative to ratings, trust between the users could be used to choose the neighbour for recommendation making. Better recommendations can be achieved using an inferred trust network which mimics the real world "friend of a friend" recommendations. To extend the boundaries of the neighbour, an effective trust inference technique is required. This thesis proposes a trust interference technique called Directed Series Parallel Graph (DSPG) which performs better than other popular trust inference algorithms such as TidalTrust and MoleTrust. Another problem is that reliable explicit trust data is not always available. In real life, people trust "word of mouth" recommendations made by people with similar interests. This is often assumed in the recommender system. By conducting a survey, we can confirm that interest similarity has a positive relationship with trust and this can be used to generate a trust network for recommendation. In this research, we also propose a new method called SimTrust for developing trust networks based on user's interest similarity in the absence of explicit trust data. To identify the interest similarity, we use user's personalised tagging information. However, we are interested in what resources the user chooses to tag, rather than the text of the tag applied. The commonalities of the resources being tagged by the users can be used to form the neighbours used in the automated recommender system. Our experimental results show that our proposed tag-similarity based method outperforms the traditional collaborative filtering approach which usually uses rating data.