968 resultados para GROWTH FUNCTIONS


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Pore architecture of scaffolds is known to play a critical role in tissue engineering as it provides the vital framework for the seeded cells to organize into a functioning tissue. In this report, we investigated the effects of different concentration on silk fibroin protein 3D scaffold pore microstructure. Four pore size ranges of silk fibroin scaffolds were made by freeze-dry technique, with the pore sizes ranging from 50 to 300 µm. The pore size of the scaffold decreases as the concentration increases. Human mesenchymal stem cells were in vitro cultured in these scaffolds. After BMP7 gene transferred, DNA assay, ALP assay, hematoxylin–eosin staining, alizarin red staining and reverse transcription-polymerase chain reaction were performed to analyze the effect of the pore size on cell growth, differentiation and the secretion of extracellular matrix (ECM). Cell morphology in these 3D scaffolds was investigated by confocal microscopy. This study indicates mesenchymal stem cells prefer the group of scaffolds with pore size between 100 and 300 µm for better proliferation and ECM production

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This article applies social network analysis techniques to a case study of police corruption in order to produce findings which will assist in corruption prevention and investigation. Police corruption is commonly studied but rarely are sophisticated tools of analyse engaged to add rigour to the field of study. This article analyses the ‘First Joke’ a systemic and long lasting corruption network in the Queensland Police Force, a state police agency in Australia. It uses the data obtained from a commission of inquiry which exposed the network and develops hypotheses as to the nature of the networks structure based on existing literature into dark networks and criminal networks. These hypotheses are tested by entering the data into UCINET and analysing the outcomes through social network analysis measures of average path distance, centrality and density. The conclusions reached show that the network has characteristics not predicted by the literature.

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Adult articular cartilage has depth-dependent mechanical and biochemical properties which contribute to zone-specific functions. The compressive moduli of immature cartilage and tissue-engineered cartilage are known to be lower than those of adult cartilage. The objective of this study was to determine if such tissues exhibit depth-dependent compressive properties, and how these depth-varying properties were correlated with cell and matrix composition of the tissue. The compressive moduli of fetal and newborn bovine articular cartilage increased with depth (p < 0.05) by a factor of 4-5 from the top 0.1 mm (28 +/- 13 kPa, 141 +/- 10 kPa, respectively) to 1 mm deep into the tissue. Likewise, the glycosaminoglycan and collagen content increased with depth (both p < 0.001), and correlated with the modulus (both p < 0.01). In contrast, tissue-engineered cartilage formed by either layering or mixing cells from the superficial and middle zone of articular cartilage exhibited similarly soft regions at both construct surfaces, as exemplified by large equilibrium strains. The properties of immature cartilage may provide a template for developing tissue-engineered cartilage which aims to repair cartilage defects by recapitulating the natural development and growth processes. These results suggest that while depth-dependent properties may be important to engineer into cartilage constructs, issues other than cell heterogeneity must be addressed to generate such tissues. (c) 2005 Elsevier Ltd. All rights reserved.

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Growth and profitability are often essential parts of the overall managerial goals of firms. High growth can be seen as an indicator of success and as a mean for achieving competitive advantage and higher profitability. But high growth can also lead to a number of managerial and organisational challenges, that may affect the profitability negatively. The aim of this article is to analyse the relationship between growth and profitability for Danish gazelle firms, and furthermore to investigate how the strategic orientation of the firm affects this relationship. Our study finds a clear positive relationship between growth and profitability among gazelle firms pursuing a broad market strategy. A managerial implication of this is that the growth strategy should be clearly integrated with the general strategic orientation of the firm.

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Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

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There has been minimal research focused on short-term study abroad language immersion programs, in particular, with home-stay families. The importance of authentic intercultural experience is increasingly clear and was acknowledged as central to the process of language learning (Liddicoat, 2004). In Hong Kong, education programs for pre-service language teachers have significantly emphasised language and intercultural training through short-term study abroad, and these short overseas language immersion courses have become a compulsory component for teacher training (Bodycott & Crew, 2001) in the last decade. This study aims to investigate eight Hong Kong pre-service teachers’ and their home-stay families’ experiences of a short-term (two months) language immersion program in Australia. The focus is on listening to commentaries concerning the development of communicative competence, intercultural competence and professional growth during the out-of-class study abroad experience. The conceptual framework adopted in this study views language and intercultural learning from social constructivist perspectives. Central to this framing is the notion that the internalisation of higher mental functions involves the transfer from the inter-psychological to the intra-psychological plane, that is, a progression process from the socially supported to individually controlled performance. From this perspective, language serves as a way to communicate about, and in relation to, actions and experience. Three research questions were addressed and studied through qualitative methodology. 1. How do the pre-service teachers and their home-stay families perceive the out-of-class component of the program in terms of opportunities for the development of language proficiency and communicative competence? 2. How do the pre-service teachers and their home-stay families perceive the out-of-class component of the program in terms of the development of intercultural competence? 3. How do the pre-service teachers and home-stay families perceive the outof- class component of the program in terms of teachers’ professional growth? Data were generated from multiple data collection methods and analysed through thematic analysis from both a “bottom up” and “top down” approach. The study showed that the pre-service teachers perceived that the immersion program influenced, to varying degrees, their language proficiency, communication and intercultural awareness, as well as their self-awareness and professional growth. These pre-service teachers believed that effective language learning centres on active engagement in the target language community. A mismatch between the views and evaluations of the two groups – the pre-service teachers and the home-stay family members – provides some evidence of misalignments in terms of expectations and perceptions of each other’s roles and responsibilities. The study has highlighted challenges encountered, and provided suggestions for ways of meeting these challenges. The inclusion in the study of the home-stay families’ perceptions and commentaries provided insights, which can inform program development. There is clearly further work to be done in terms of predeparture orientation and preparation, not only for the main participants themselves, the students, but also for the host families.

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Ghrelin was first identified in 1999 by Kojima and colleagues (Kojima et al. 1999) as the natural ligand of an orphan G-protein coupled receptor, the Growth Hormone (GH) secretagogue receptor (GHS-R), which had been identified several years earlier through the actions of a growing number of synthetic growth hormone releasing peptides (GHRPs) and non-peptidyl GH secretagogues (Howard et al. 1996). Early studies, therefore, focussed on the actions of ghrelin as an important regulator of GH secretion. As a result Kojima et al (1999) designated this GH-releasing peptide, ghrelin (ghre is the Proto-Indo-European root of the word 'grow'). We now recognise that the functions of ghrelin extend well beyond its GH releasing actions and that it is a multi-functional peptide with both endocrine and autocrine/paracrine modes of action.

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Ghrelin is a peptide hormone that was originally isolated from the stomach as the endogenous ligand for the growth hormone secretagogue receptor (GHSR). Ghrelin has many functions, including the regulation of appetite and gut motility, growth hormone release from the anterior pituitary and roles in the cardiovascular and immune systems. Ghrelin and its receptor are expressed in a number of cancers and cancer cell lines and may play a role in processes associated with cancer progression, including cell proliferation, apoptosis, and cell invasion and migration.

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Numerous econometric models have been proposed for forecasting property market performance, but limited success has been achieved in finding a reliable and consistent model to predict property market movements over a five to ten year timeframe. This research focuses on office rental growth forecasts and overviews many of the office rent models that have evolved over the past 20 years. A model by DiPasquale and Wheaton is selected for testing in the Brisbane, Australia office market. The adaptation of this study did not provide explanatory variables that could assist in developing a reliable, predictive model of office rental growth. In light of this result, the paper suggests a system dynamics framework that includes an econometric model based on historical data as well as user input guidance for the primary variables. The rent forecast outputs would be assessed having regard to market expectations and probability profiling undertaken for use in simulation exercises. The paper concludes with ideas for ongoing research.

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Crystal growth of bulk CdTe in short-duration microgravity is performed by the unidirectional cooling method. The largest growth grains in microgravity samples are 4X2mm. The cooling profiles indicate undercooling melts in microgravity. Cooling melt samples in microgravity generate strong gradient of temperature due to stop thermal convections. Temperature distribution in the melt is calculated by the one-dimensional equation of heat conduction, and about 100 K-undercooling is considered to occur at the cooling surface.

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Optimal design for generalized linear models has primarily focused on univariate data. Often experiments are performed that have multiple dependent responses described by regression type models, and it is of interest and of value to design the experiment for all these responses. This requires a multivariate distribution underlying a pre-chosen model for the data. Here, we consider the design of experiments for bivariate binary data which are dependent. We explore Copula functions which provide a rich and flexible class of structures to derive joint distributions for bivariate binary data. We present methods for deriving optimal experimental designs for dependent bivariate binary data using Copulas, and demonstrate that, by including the dependence between responses in the design process, more efficient parameter estimates are obtained than by the usual practice of simply designing for a single variable only. Further, we investigate the robustness of designs with respect to initial parameter estimates and Copula function, and also show the performance of compound criteria within this bivariate binary setting.