965 resultados para unified growth models


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The goal of mangrove restoration projects should be to improve community structure and ecosystem function of degraded coastal landscapes. This requires the ability to forecast how mangrove structure and function will respond to prescribed changes in site conditions including hydrology, topography, and geophysical energies. There are global, regional, and local factors that can explain gradients of regulators (e.g., salinity, sulfides), resources (nutrients, light, water), and hydroperiod (frequency, duration of flooding) that collectively account for stressors that result in diverse patterns of mangrove properties across a variety of environmental settings. Simulation models of hydrology, nutrient biogeochemistry, and vegetation dynamics have been developed to forecast patterns in mangroves in the Florida Coastal Everglades. These models provide insight to mangrove response to specific restoration alternatives, testing causal mechanisms of system degradation. We propose that these models can also assist in selecting performance measures for monitoring programs that evaluate project effectiveness. This selection process in turn improves model development and calibration for forecasting mangrove response to restoration alternatives. Hydrologic performance measures include soil regulators, particularly soil salinity, surface topography of mangrove landscape, and hydroperiod, including both the frequency and duration of flooding. Estuarine performance measures should include salinity of the bay, tidal amplitude, and conditions of fresh water discharge (included in the salinity value). The most important performance measures from the mangrove biogeochemistry model should include soil resources (bulk density, total nitrogen, and phosphorus) and soil accretion. Mangrove ecology performance measures should include forest dimension analysis (transects and/or plots), sapling recruitment, leaf area index, and faunal relationships. Estuarine ecology performance measures should include the habitat function of mangroves, which can be evaluated with growth rate of key species, habitat suitability analysis, isotope abundance of indicator species, and bird census. The list of performance measures can be modified according to the model output that is used to define the scientific goals during the restoration planning process that reflect specific goals of the project.

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The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^

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Porous layers can be formed electrochemically on (100) oriented n-InP substrates in aqueous KOH. A nanoporous layer is obtained underneath a dense near-surface layer and the pores appear to propagate from holes through the near-surface layer. In the early stages of the anodization transmission electron microscopy (TEM) clearly shows individual porous domains that appear to have a square-based pyramidal shape. Each domain appears to develop from an individual surface pit which forms a channel through this near-surface layer. We suggest that the pyramidal structure arises as a result of preferential pore propagation along the <100> directions. AFM measurements show that the density of surface pits increases with time. Each of these pits acts as a source for a pyramidal porous domain. When the domains grow, the current density increases correspondingly. Eventually the domains meet, forming a continuous porous layer, the interface between the porous and bulk InP becomes relatively flat and its total effective surface area decreases resulting in a decrease in the current density. Current-time curves at constant potential exhibit a peak and porous layers are observed to form beneath the electrode surface. The density of pits formed on the surface increases with time and approaches a plateau value. Porous layers are also observed in highly doped InP but are not observed in wafers with doping densities below ~5 × 1017 cm-3. Numerical models of this process have been developed invoking a mechanism of directional selectivity of pore growth preferentially along the <100> lattice directions. Manipulation of the parameters controlling these curves shows that the fall-off in current is controlled by the rate of diffusion of electrolyte through the pore structure with the final decline in current being caused by the termination of growth at the pore tips through the formation of passivating films or some other irreversible modification of the pore tips.

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Parkinson’s disease (PD) is a progressive neurodegenerative disease characterised by motor and non-motor symptoms, resulting from the degeneration of nigrostriatal dopaminergic neurons and peripheral autonomic neurons. Given the limited success of neurotrophic factors in clinical trials, there is a need to identify new small molecule drugs and drug targets to develop novel therapeutic strategies to protect all neurons that degenerate in PD. Epigenetic dysregulation has been implicated in neurodegenerative disorders, while targeting histone acetylation is a promising therapeutic avenue for PD. We and others have demonstrated that histone deacetylase inhibitors have neurotrophic effects in experimental models of PD. Activators of histone acetyltransferases (HAT) provide an alternative approach for the selective activation of gene expression, however little is known about the potential of HAT activators as drug therapies for PD. To explore this potential, the present study investigated the neurotrophic effects of CTPB (N-(4-chloro-3-trifluoromethyl-phenyl)-2-ethoxy-6-pentadecyl-benzamide), which is a potent small molecule activator of the histone acetyltransferase p300/CBP, in the SH-SY5Y neuronal cell line. We report that CTPB promoted the survival and neurite growth of the SH-SY5Y cells, and also protected these cells from cell death induced by the neurotoxin 6-hydroxydopamine. This study is the first to investigate the phenotypic effects of the HAT activator CTPB, and to demonstrate that p300/CBP HAT activation has neurotrophic effects in a cellular model of PD.

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BACKGROUND: The role of the microbiome has become synonymous with human health and disease. Bile acids, as essential components of the microbiome, have gained sustained credibility as potential modulators of cancer progression in several disease models. At physiological concentrations, bile acids appear to influence cancer phenotypes, although conflicting data surrounds their precise physiological mechanism of action. Previously, we demonstrated bile acids destabilised the HIF-1α subunit of the Hypoxic-Inducible Factor-1 (HIF-1) transcription factor. HIF-1 overexpression is an early biomarker of tumour metastasis and is associated with tumour resistance to conventional therapies, and poor prognosis in a range of different cancers. METHODS: Here we investigated the effects of bile acids on the cancer growth and migratory potential of cell lines where HIF-1α is known to be active under hypoxic conditions. HIF-1α status was investigated in A-549 lung, DU-145 prostate and MCF-7 breast cancer cell lines exposed to bile acids (CDCA and DCA). Cell adhesion, invasion, migration was assessed in DU-145 cells while clonogenic growth was assessed in all cell lines. RESULTS: Intracellular HIF-1α was destabilised in the presence of bile acids in all cell lines tested. Bile acids were not cytotoxic but exhibited greatly reduced clonogenic potential in two out of three cell lines. In the migratory prostate cancer cell line DU-145, bile acids impaired cell adhesion, migration and invasion. CDCA and DCA destabilised HIF-1α in all cells and significantly suppressed key cancer progression associated phenotypes; clonogenic growth, invasion and migration in DU-145 cells. CONCLUSIONS: These findings suggest previously unobserved roles for bile acids as physiologically relevant molecules targeting hypoxic tumour progression.

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Background: Mechanisms underlying the effect of estrogen exposure on breast cancer risk remain unclear. Insulin-like growth factor-1 (IGF-1) levels have been positively associated with breast cancer and are a potential mechanism. Objectives: The objectives of this thesis are: 1) to explore whether the reproductive risk factors and the lifetime cumulative number of menstrual cycles (LCMC), as measures for long-term estrogen exposure, are associated with IGF-1 levels, and 2) to examine the effect of an aromatase inhibitor (AI) on IGF-1 levels, and the potential interaction with BMI. Methods: A cross sectional study and a randomized controlled trial nested with the MAP.3 chemoprevention trial were used to address objective 1 and 2, respectively. 567 postmenopausal women were selected. Anthropometric measurements, lifestyle factors, reproductive characteristics and serum IGF-1 concentrations were collected at baseline and one year. Objective 1. The LCMC was computed as a composite measure of the reproductive characteristics. Multivariable linear regression models were used to assess the association between IGF-1 levels and LCMC and the hormonal risk factors, while adjusting for potential covariates. Objective 2. Changes in IGF-1 were compared between the exemestane and placebo, and effect modification by BMI was tested with an interaction term. Results: Objective 1. Women aged 55 years or older at menopause had 16.26 ng/mL (95% CI: 1.76, 30.75) higher IGF-1 compared to women aged less than 50 years at menopause. Women in the highest category of menstrual cycles (≥500 cycles) had an average 19.00 ng/mL (95%CI: 5.86, 32.14) higher concentration of IGF-1 compared to women in the lowest category (<350). Exogenous hormones had no effect on postmenopausal IGF-1 levels. Objective 2. Exemestane significantly increased IGF-1 levels by 18% (95% CI: 14%-22%); while, placebo had no effect on IGF-1. The changes in IGF-1 were significantly different between the treatment arms (P<0.0001) and no significant interaction was observed between treatment and BMI on IGF-1 changes (P=0.1327). Conclusion: Objective 1. Larger number of menstrual cycles and a later age at menopause are positively associated with IGF-1. IGF-1 may be one mechanism by which prolonged estrogen exposure increases cancer risk. Objective 2. We conclude that the reduced cancer risk observed with AI therapy likely occurs in an IGF-1 independent mechanism. Further studies exploring the clinical consequences of increased IGF-1 on AI therapy are needed.

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ABSTRACT: The ability of Antarctic krill Euphausia superba Dana to withstand the overwintering period is critical to their success. Laboratory evidence suggests that krill may shrink in body length during this time in response to the low availability of food. Nevertheless, verification that krill can shrink in the natural environment is lacking because winter data are difficult to obtain. One of the few sources of winter krill population data is from commercial vessels. We examined length-frequency data of adult krill (>35 mm total body length) obtained from commercial vessels in the Scotia-Weddell region and compared our results with those obtained from a combination of science and commercial sampling operations carried out in this region at other times of the year. Our analyses revealed body-length shrinkage in adult females but not males during overwinter, based on both the tracking of modal size classes over seasons and sex-ratio patterns. Other explanatory factors, such as differential mortality, immigration and emigration, could not explain the observed differences. The same pattern was also observed at South Georgia and in the Western Antarctic Peninsula. Fitted seasonally modulated von Bertalanffy growth functions predicted a pattern of overwintering shrinkage in all body-length classes of females, but only stagnation in growth in males. This shrinkage most likely reflects morphometric changes resulting from the contraction of the ovaries and is not necessarily an outcome of winter hardship. The sex-dependent changes that we observed need to be incorporated into life cycle and population dynamic models of this species, particularly those used in managing the fishery. KEY WORDS: Southern Ocean · Population dynamics · Production · Life cycle · Fishery

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ABSTRACT: The ability of Antarctic krill Euphausia superba Dana to withstand the overwintering period is critical to their success. Laboratory evidence suggests that krill may shrink in body length during this time in response to the low availability of food. Nevertheless, verification that krill can shrink in the natural environment is lacking because winter data are difficult to obtain. One of the few sources of winter krill population data is from commercial vessels. We examined length-frequency data of adult krill (>35 mm total body length) obtained from commercial vessels in the Scotia-Weddell region and compared our results with those obtained from a combination of science and commercial sampling operations carried out in this region at other times of the year. Our analyses revealed body-length shrinkage in adult females but not males during overwinter, based on both the tracking of modal size classes over seasons and sex-ratio patterns. Other explanatory factors, such as differential mortality, immigration and emigration, could not explain the observed differences. The same pattern was also observed at South Georgia and in the Western Antarctic Peninsula. Fitted seasonally modulated von Bertalanffy growth functions predicted a pattern of overwintering shrinkage in all body-length classes of females, but only stagnation in growth in males. This shrinkage most likely reflects morphometric changes resulting from the contraction of the ovaries and is not necessarily an outcome of winter hardship. The sex-dependent changes that we observed need to be incorporated into life cycle and population dynamic models of this species, particularly those used in managing the fishery. KEY WORDS: Southern Ocean · Population dynamics · Production · Life cycle · Fishery

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Prostate cancer (PCa) is the most common non-cutaneous malignant disease among males in the developed countries. Radical prostatectomy (RP) is an effective therapy for most PCa patients with localized or locally invaded tumors but in some cases the cancer recurs after RP. PCa is a heterogeneous disease, which is regulated by many factors, such as androgen receptor (AR), estrogen receptors and  (ER and ER), fibroblast growth factors (FGFs) and their receptors (FGFRs). In this study, the role of ERβ, FGF8, FGF13 and FGFRL1 was investigated in PCa. Previous studies have suggested that ER is protective against PCa whereas FGF8 has been shown to induce PCa in transgenic mice. FGF13 and FGFRL1 are poorly understood members of the FGF and FGFR families, respectively. Transgenic mouse models were used to investigate the ability of inactivated ERβ to facilitate FGF8-induced prostate tumorigenesis. Human PCa tissue microarrays (TMAs) were used to study the expression pattern of FGF13 and FGFRL1 in PCa and the results were correlated to corresponding patient data. The targets and biological functions of FGF13 and FGFRL1 were characterized using experimental in vivo and in vitro models. The results show that deficiency of ERβ, which had been expected to have tumor suppressing capacity, seemed to influence epithelial differentiation but did not affect FGF8-induced prostate tumorigenesis. Analysis of the TMAs showed increased expression of FGF13 in PCa. The level of cytoplasmic FGF13 was associated with the PCa biochemical recurrence (BCR), demonstrated by increasing serum PSA value, and was able to act as an independent prognostic biomarker for PCa patients after RP. Expression of FGFRL1, the most recently identified FGFR, was also elevated in PCa. Cytoplasmic and nuclear FGFRL1 was associated with high Gleason score and Ki67 level whereas the opposite was true for the cell membrane FGFRL1. Silencing of FGFRL1 in PC-3M cells led to a strongly decreased growth rate of these cells as xenografts in nude mice and the experiments with PCa cell lines showed that FGFRL1 is able to modulate the FGF2- and FGF8-induced signaling pathways. The next generation sequencing (NGS) experiments with FGFRL1-silenced PC-3M cells revealed candidates for FGFRL1 target genes. In summary, these studies provide new data on the FGF/FGFR signaling pathways in normal and malignant prostate and suggest a potential role for FGF13 and FGFRL1 as novel prognostic markers for PCa patients. Keywords: FGF8, FGF13, FGFRL1, ERβ, prostate cancer, prognostic marker

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Current practices in agricultural management involve the application of rules and techniques to ensure high quality and environmentally friendly production. Based on their experience, agricultural technicians and farmers make critical decisions affecting crop growth while considering several interwoven agricultural, technological, environmental, legal and economic factors. In this context, decision support systems and the knowledge models that support them, enable the incorporation of valuable experience into software systems providing support to agricultural technicians to make rapid and effective decisions for efficient crop growth. Pest control is an important issue in agricultural management due to crop yield reductions caused by pests and it involves expert knowledge. This paper presents a formalisation of the pest control problem and the workflow followed by agricultural technicians and farmers in integrated pest management, the crop production strategy that combines different practices for growing healthy crops whilst minimising pesticide use. A generic decision schema for estimating infestation risk of a given pest on a given crop is defined and it acts as a metamodel for the maintenance and extension of the knowledge embedded in a pest management decision support system which is also presented. This software tool has been implemented by integrating a rule-based tool into web-based architecture. Evaluation from validity and usability perspectives concluded that both agricultural technicians and farmers considered it a useful tool in pest control, particularly for training new technicians and inexperienced farmers.

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There may be advantages to be gained by combining Case-Based Reasoning (CBR) techniques with numerical models. In this paper we consider how CBR can be used as a flexible query engine to improve the usability of numerical models. Particularly they can help to solve inverse and mixed problems, and to solve constraint problems. We discuss this idea with reference to the illustrative example of a pneumatic conveyor. We describe a model of the problem of particle degradation in such a conveyor, and the problems faced by design engineers. The solution of these problems requires a system that allows iterative sharing of control between user, CBR system, and numerical model. This multi-initiative interaction is illustrated for the pneumatic conveyor by means of Unified Modeling Language (UML) collaboration and sequence diagrams. We show approaches to the solution of these problems via a CBR tool.

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Eucalyptus pellita demonstrated good growth and wood quality traits in this study, with young plantation grown timber being suitable for both solid and pulp wood products. All traits examined were under moderate levels of genetic control with little genotype by environment interaction when grown on two contrasting sites in Vietnam. Eucalyptus pellita currently has a significant role in reforestation in the tropics. Research to support expanded of use of this species is needed: particularly, research to better understand the genetic control of key traits will facilitate the development of genetically improved planting stock. This study aimed to provide estimates of the heritability of diameter at breast height over bark, wood basic density, Kraft pulp yield, modulus of elasticity and microfibril angle, and the genetic correlations among these traits, and understand the importance of genotype by environment interactions in Vietnam. Data for diameter and wood properties were collected from two 10-year-old, open-pollinated progeny trials of E. pellita in Vietnam that evaluated 104 families from six native range and three orchard sources. Wood properties were estimated from wood samples using near-infrared (NIR) spectroscopy. Data were analysed using mixed linear models to estimate genetic parameters (heritability, proportion of variance between seed sources and genetic correlations). Variation among the nine sources was small compared to additive variance. Narrow-sense heritability and genetic correlation estimates indicated that simultaneous improvements in most traits could be achieved from selection among and within families as the genetic correlations among traits were either favourable or close to zero. Type B genetic correlations approached one for all traits suggesting that genotype by environment interactions were of little importance. These results support a breeding strategy utilizing a single breeding population advanced by selecting the best individuals across all seed sources. Both growth and wood properties have been evaluated. Multi-trait selection for growth and wood property traits will lead to more productive populations of E. pellita both with improved productivity and improved timber and pulp properties.

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Plantings of mixed native species (termed 'environmental plantings') are increasingly being established for carbon sequestration whilst providing additional environmental benefits such as biodiversity and water quality. In Australia, they are currently one of the most common forms of reforestation. Investment in establishing and maintaining such plantings relies on having a cost-effective modelling approach to providing unbiased estimates of biomass production and carbon sequestration rates. In Australia, the Full Carbon Accounting Model (FullCAM) is used for both national greenhouse gas accounting and project-scale sequestration activities. Prior to undertaking the work presented here, the FullCAM tree growth curve was not calibrated specifically for environmental plantings and generally under-estimated their biomass. Here we collected and analysed above-ground biomass data from 605 mixed-species environmental plantings, and tested the effects of several planting characteristics on growth rates. Plantings were then categorised based on significant differences in growth rates. Growth of plantings differed between temperate and tropical regions. Tropical plantings were relatively uniform in terms of planting methods and their growth was largely related to stand age, consistent with the un-calibrated growth curve. However, in temperate regions where plantings were more variable, key factors influencing growth were planting width, stand density and species-mix (proportion of individuals that were trees). These categories provided the basis for FullCAM calibration. Although the overall model efficiency was only 39-46%, there was nonetheless no significant bias when the model was applied to the various planting categories. Thus, modelled estimates of biomass accumulation will be reliable on average, but estimates at any particular location will be uncertain, with either under- or over-prediction possible. When compared with the un-calibrated yield curves, predictions using the new calibrations show that early growth is likely to be more rapid and total above-ground biomass may be higher for many plantings at maturity. This study has considerably improved understanding of the patterns of growth in different types of environmental plantings, and in modelling biomass accumulation in young (<25. years old) plantings. However, significant challenges remain to understand longer-term stand dynamics, particularly with temporal changes in stand density and species composition. © 2014.

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Abstract: The importance of e-government models lies in their offering a basis to measure and guide e-government. There is still no agreement on how to assess a government online. Most of the e-government models are not based on research, nor are they validated. In most countries, e-government has not reached higher stages of growth. Several scholars have shown a confusing picture of e-government. What is lacking is an in-depth analysis of e-government models. Responding to the need for such an analysis, this study identifies the strengths and weaknesses of major national and local e-government evaluation models. The common limitations of most models are focusing on the government and not the citizen, missing qualitative measures, constructing the e-equivalent of a bureaucratic administration, and defining general criteria without sufficient validations. In addition, this study has found that the metrics defined for national e-government are not suitable for municipalities, and most of the existing studies have focused on national e-governments even though local ones are closer to citizens. There is a need for developing a good theoretical model for both national and local municipal e-government.