550 resultados para ARBITRARY MAGNITUDE


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The Queensland Department of Main Roads uses Weigh-in-Motion (WiM) devices to covertly monitor (at highway speed) axle mass, axle configurations and speed of heavy vehicles on the road network. Such data is critical for the planning and design of the road network. Some of the data appears excessively variable. The current work considers the nature, magnitude and possible causes of WiM data variability. Over fifty possible causes of variation in WiM data have been identified in the literature. Data exploration has highlighted five basic types of variability specifically: ----- • cycling, both diurnal and annual;----- • consistent but unreasonable data;----- • data jumps;----- • variations between data from opposite sides of the one road; and ----- • non-systematic variations.----- This work is part of wider research into procedures to eliminate or mitigate the influence of WiM data variability.

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A review of the literature related to issues involved in irrigation induced agricultural development (IIAD) reveals that: (1) the magnitude, sensitivity and distribution of social welfare of IIAD is not fully analysed; (2) the impacts of excessive pesticide use on farmers’ health are not adequately explained; (3) no analysis estimates the relationship between farm level efficiency and overuse of agro-chemical inputs under imperfect markets; and (4) the method of incorporating groundwater extraction costs is misleading. This PhD thesis investigates these issues by using primary data, along with secondary data from Sri Lanka. The overall findings of the thesis can be summarised as follows. First, the thesis demonstrates that Sri Lanka has gained a positive welfare change as a result of introducing new irrigation technology. The change in the consumer surplus is Rs.48,236 million, while the change in the producer surplus is Rs. 14,274 millions between 1970 and 2006. The results also show that the long run benefits and costs of IIAD depend critically on the magnitude of the expansion of the irrigated area, as well as the competition faced by traditional farmers (agricultural crowding out effects). The traditional sector’s ability to compete with the modern sector depends on productivity improvements, reducing production costs and future structural changes (spillover effects). Second, the thesis findings on pesticides used for agriculture show that, on average, a farmer incurs a cost of approximately Rs. 590 to 800 per month during a typical cultivation period due to exposure to pesticides. It is shown that the value of average loss in earnings per farmer for the ‘hospitalised’ sample is Rs. 475 per month, while it is approximately Rs. 345 per month for the ‘general’ farmers group during a typical cultivation season. However, the average willingness to pay (WTP) to avoid exposure to pesticides is approximately Rs. 950 and Rs. 620 for ‘hospitalised’ and ‘general’ farmers’ samples respectively. The estimated percentage contribution for WTP due to health costs, lost earnings, mitigating expenditure, and disutility are 29, 50, 5 and 16 per cent respectively for hospitalised farmers, while they are 32, 55, 8 and 5 per cent respectively for ‘general’ farmers. It is also shown that given market imperfections for most agricultural inputs, farmers are overusing pesticides with the expectation of higher future returns. This has led to an increase in inefficiency in farming practices which is not understood by the farmers. Third, it is found that various groundwater depletion studies in the economics literature have provided misleading optimal water extraction quantity levels. This is due to a failure to incorporate all production costs in the relevant models. It is only by incorporating quality changes to quantity deterioration, that it is possible to derive socially optimal levels. Empirical results clearly show that the benefits per hectare per month considering both the avoidance costs of deepening agro-wells by five feet from the existing average, as well as the avoidance costs of maintaining the water salinity level at 1.8 (mmhos/Cm), is approximately Rs. 4,350 for farmers in the Anuradhapura district and Rs. 5,600 for farmers in the Matale district.

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Adequate blood supply and sufficient mechanical stability are necessary for timely fracture healing. Damage to vessels impairs blood supply; hindering the transport of oxygen which is an essential metabolite for cells involved in repair. The degree of mechanical stability determines the mechanical conditions in the healing tissues. The mechanical conditions can influence tissue differentiation and may also inhibit revascularization. Knowledge of the actual conditions in a healing fracture in vivo is extremely limited. This study aimed to quantify the pressure, oxygen tension and temperature in the external callus during the early phase of bone healing. Six Merino-mix sheep underwent a tibial osteotomy. The tibia was stabilized with a standard mono-lateral external fixator. A multi-parameter catheter was placed adjacent to the osteotomy gap on the medial aspect of the tibia. Measurements of oxygen tension and temperature were performed for ten days post-op. Measurements of pressure were performed during gait on days three and seven. The ground reaction force and the interfragmentary movements were measured simultaneously. The maximum pressure during gait increased (p=0.028) from three (41.3 [29.2-44.1] mm Hg) to seven days (71.8 [61.8-84.8] mm Hg). During the same interval, there was no change (p=0.92) in the peak ground reaction force or in the interfragmentary movement (compression: p=0.59 and axial rotation: p=0.11). Oxygen tension in the haematoma (74.1 mm Hg [68.6-78.5]) was initially high post-op and decreased steadily over the first five days. The temperature increased over the first four days before reaching a plateau at approximately 38.5 degrees C on day four. This study is the first to report pressure, oxygen tension and temperature in the early callus tissues. The magnitude of pressure increased even though weight bearing and IFM remained unchanged. Oxygen tensions were initially high in the haematoma and fell gradually with a low oxygen environment first established after four to five days. This study illustrates that in bone healing the local environment for cells may not be considered constant with regard to oxygen tension, pressure and temperature.

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Bone loss may result from remodelling initiated by implant stress protection. Quantifying remodelling requires bone density distributions which can be obtained from computed tomography scans. Pre-operative scans of large animals however are rarely possible. This study aimed to determine if the contra-lateral bone is a suitable control for the purpose of quantifying bone remodelling. CT scans of 8 pairs of ovine tibia were used to determine the likeness of left and right bones. The deviation between the outer surfaces of the bone pairs was used to quantify geometric similarity. The density differences were determined by dividing the bones into discrete volumes along the shaft of the tibia. Density differences were also determined for fractured and contra-lateral bone pairs to determine the magnitude of implant related remodelling. Left and right ovine tibiae were found to have a high degree of similarity with differences of less than 1.0 mm in the outer surface deviation and density difference of less than 5% in over 90% of the shaft region. The density differences (10–40%) as a result of implant related bone remodelling were greater than left-right differences. Therefore, for the purpose of quantifying bone remodelling in sheep, the contra-lateral tibia may be considered an alternative to a pre-operative control.

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The world we live in is well labeled for the benefit of humans but to date robots have made little use of this resource. In this paper we describe a system that allows robots to read and interpret visible text and use it to understand the content of the scene. We use a generative probabilistic model that explains spotted text in terms of arbitrary search terms. This allows the robot to understand the underlying function of the scene it is looking at, such as whether it is a bank or a restaurant. We describe the text spotting engine at the heart of our system that is able to detect and parse wild text in images, and the generative model, and present results from images obtained with a robot in a busy city setting.

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The functional properties of cartilaginous tissues are determined predominantly by the content, distribution, and organization of proteoglycan and collagen in the extracellular matrix. Extracellular matrix accumulates in tissue-engineered cartilage constructs by metabolism and transport of matrix molecules, processes that are modulated by physical and chemical factors. Constructs incubated under free-swelling conditions with freely permeable or highly permeable membranes exhibit symmetric surface regions of soft tissue. The variation in tissue properties with depth from the surfaces suggests the hypothesis that the transport processes mediated by the boundary conditions govern the distribution of proteoglycan in such constructs. A continuum model (DiMicco and Sah in Transport Porus Med 50:57-73, 2003) was extended to test the effects of membrane permeability and perfusion on proteoglycan accumulation in tissue-engineered cartilage. The concentrations of soluble, bound, and degraded proteoglycan were analyzed as functions of time, space, and non-dimensional parameters for several experimental configurations. The results of the model suggest that the boundary condition at the membrane surface and the rate of perfusion, described by non-dimensional parameters, are important determinants of the pattern of proteoglycan accumulation. With perfusion, the proteoglycan profile is skewed, and decreases or increases in magnitude depending on the level of flow-based stimulation. Utilization of a semi-permeable membrane with or without unidirectional flow may lead to tissues with depth-increasing proteoglycan content, resembling native articular cartilage.

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Information overload has become a serious issue for web users. Personalisation can provide effective solutions to overcome this problem. Recommender systems are one popular personalisation tool to help users deal with this issue. As the base of personalisation, the accuracy and efficiency of web user profiling affects the performances of recommender systems and other personalisation systems greatly. In Web 2.0, the emerging user information provides new possible solutions to profile users. Folksonomy or tag information is a kind of typical Web 2.0 information. Folksonomy implies the users‘ topic interests and opinion information. It becomes another source of important user information to profile users and to make recommendations. However, since tags are arbitrary words given by users, folksonomy contains a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise makes it difficult to profile users accurately or to make quality recommendations. This thesis investigates the distinctive features and multiple relationships of folksonomy and explores novel approaches to solve the tag quality problem and profile users accurately. Harvesting the wisdom of crowds and experts, three new user profiling approaches are proposed: folksonomy based user profiling approach, taxonomy based user profiling approach, hybrid user profiling approach based on folksonomy and taxonomy. The proposed user profiling approaches are applied to recommender systems to improve their performances. Based on the generated user profiles, the user and item based collaborative filtering approaches, combined with the content filtering methods, are proposed to make recommendations. The proposed new user profiling and recommendation approaches have been evaluated through extensive experiments. The effectiveness evaluation experiments were conducted on two real world datasets collected from Amazon.com and CiteULike websites. The experimental results demonstrate that the proposed user profiling and recommendation approaches outperform those related state-of-the-art approaches. In addition, this thesis proposes a parallel, scalable user profiling implementation approach based on advanced cloud computing techniques such as Hadoop, MapReduce and Cascading. The scalability evaluation experiments were conducted on a large scaled dataset collected from Del.icio.us website. This thesis contributes to effectively use the wisdom of crowds and expert to help users solve information overload issues through providing more accurate, effective and efficient user profiling and recommendation approaches. It also contributes to better usages of taxonomy information given by experts and folksonomy information contributed by users in Web 2.0.

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Item folksonomy or tag information is popularly available on the web now. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. In this paper, we propose to combine item taxonomy and folksonomy to reduce the noise of tags and make personalized item recommendations. The experiments conducted on the dataset collected from Amazon.com demonstrated the effectiveness of the proposed approaches. The results suggested that the recommendation accuracy can be further improved if we consider the viewpoints and the vocabularies of both experts and users.

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Social tags are an important information source in Web 2.0. They can be used to describe users’ topic preferences as well as the content of items to make personalized recommendations. However, since tags are arbitrary words given by users, they contain a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise brings difficulties to improve the accuracy of item recommendations. To eliminate the noise of tags, in this paper we propose to use the multiple relationships among users, items and tags to find the semantic meaning of each tag for each user individually. With the proposed approach, the relevant tags of each item and the tag preferences of each user are determined. In addition, the user and item-based collaborative filtering combined with the content filtering approach are explored. The effectiveness of the proposed approaches is demonstrated in the experiments conducted on real world datasets collected from Amazon.com and citeULike website.

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Social tags in web 2.0 are becoming another important information source to describe the content of items as well as to profile users’ topic preferences. However, as arbitrary words given by users, tags contains a lot of noise such as tag synonym and semantic ambiguity a large number personal tags that only used by one user, which brings challenges to effectively use tags to make item recommendations. To solve these problems, this paper proposes to use a set of related tags along with their weights to represent semantic meaning of each tag for each user individually. A hybrid recommendation generation approaches that based on the weighted tags are proposed. We have conducted experiments using the real world dataset obtained from Amazon.com. The experimental results show that the proposed approaches outperform the other state of the art approaches.

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Hyperthermia and local drug delivery have been proposed the potential therapeutic approaches for bone defects resulting from malignant bone tumors. Development of bioactive materials with magnetic and drug-delivery properties may potentially meet this target. The aim of this study is to develop a multifunctional mesoporous bioactive glass (MBG) scaffold system for both hyperthermia and local-drug delivery application potentially. For this aim, Iron (Fe) containing MBG (Fe-MBG) scaffolds with hierarchically large pores (300-500 µm) and fingerprint-like mesopores (4.5 nm) have been successfully prepared. The effect of Fe on the mesopore structure, physiochemical, magnetism, drug delivery and biological properties of MBG scaffolds has been systematically investigated. The results showed that the morphology of the mesopore varied from straight channels to curved fingerprint-like channels after incorporated parts of Fe into MBG scaffolds. The magnetism magnitude of MBG scaffolds can be tailored by controlling Fe contents. Furthermore, the incorporating of Fe into mesoporous MBG glass scaffolds enhanced the mitochondrial activity and bone-relative gene (ALP and OCN) expression of human bone marrow mesenchymal stem cells (BMSCs) on the scaffolds. The obtained Fe-MBG scaffolds also possessed high specific surface areas and sustained drug delivery. Therefore, Fe-MBG scaffolds are magnetic, degradable and bioactive. The multifunction of Fe-MBG scaffolds indicates that there is a great potential for Fe-MBG scaffolds to be used for the therapy and regeneration of large-bone defects caused by malignant bone tumors through the combination of hyperthermia, local drug delivery and their osteoconductivity.

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The proportion of functional sequence in the human genome is currently a subject of debate. The most widely accepted figure is that approximately 5% is under purifying selection. In Drosophila, estimates are an order of magnitude higher, though this corresponds to a similar quantity of sequence. These estimates depend on the difference between the distribution of genomewide evolutionary rates and that observed in a subset of sequences presumed to be neutrally evolving. Motivated by the widening gap between these estimates and experimental evidence of genome function, especially in mammals, we developed a sensitive technique for evaluating such distributions and found that they are much more complex than previously apparent. We found strong evidence for at least nine well-resolved evolutionary rate classes in an alignment of four Drosophila species and at least seven classes in an alignment of four mammals, including human. We also identified at least three rate classes in human ancestral repeats. By positing that the largest of these ancestral repeat classes is neutrally evolving, we estimate that the proportion of nonneutrally evolving sequence is 30% of human ancestral repeats and 45% of the aligned portion of the genome. However, we also question whether any of the classes represent neutrally evolving sequences and argue that a plausible alternative is that they reflect variable structure-function constraints operating throughout the genomes of complex organisms.

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Background In order to provide insights into the complex biochemical processes inside a cell, modelling approaches must find a balance between achieving an adequate representation of the physical phenomena and keeping the associated computational cost within reasonable limits. This issue is particularly stressed when spatial inhomogeneities have a significant effect on system's behaviour. In such cases, a spatially-resolved stochastic method can better portray the biological reality, but the corresponding computer simulations can in turn be prohibitively expensive. Results We present a method that incorporates spatial information by means of tailored, probability distributed time-delays. These distributions can be directly obtained by single in silico or a suitable set of in vitro experiments and are subsequently fed into a delay stochastic simulation algorithm (DSSA), achieving a good compromise between computational costs and a much more accurate representation of spatial processes such as molecular diffusion and translocation between cell compartments. Additionally, we present a novel alternative approach based on delay differential equations (DDE) that can be used in scenarios of high molecular concentrations and low noise propagation. Conclusions Our proposed methodologies accurately capture and incorporate certain spatial processes into temporal stochastic and deterministic simulations, increasing their accuracy at low computational costs. This is of particular importance given that time spans of cellular processes are generally larger (possibly by several orders of magnitude) than those achievable by current spatially-resolved stochastic simulators. Hence, our methodology allows users to explore cellular scenarios under the effects of diffusion and stochasticity in time spans that were, until now, simply unfeasible. Our methodologies are supported by theoretical considerations on the different modelling regimes, i.e. spatial vs. delay-temporal, as indicated by the corresponding Master Equations and presented elsewhere.

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There is an urgent need to develop safe, effective, dual-purpose contraceptive agents that combine the prevention of pregnancy with protection against sexually transmitted diseases. Here we report the identification of a group of compounds that on contact with human spermatozoa induce a state of “spermostasis,” characterized by the extremely rapid inhibition of sperm movement without compromising cell viability. These spermostatic agents were more active and significantly less toxic than the reagent in current clinical use, nonoxynol 9, giving therapeutic indices (ratio of spermostatic to cytotoxic activity) that were orders of magnitude greater than this traditional spermicide. Although certain compounds could trigger reactive oxygen species generation by spermatozoa, this activity was not correlated with spermostasis. Rather, the latter was associated with alkylation of two major sperm tail proteins that were identified as A Kinase-Anchoring Proteins (AKAP3 and AKAP4) by mass spectrometry. As a consequence of disrupted AKAP function, the abilities of cAMP to drive protein kinase A-dependent activities in the sperm tail, such as the activation of SRC and the consequent stimulation of tyrosine phosphorylation, were suppressed. Furthermore, analysis of microbicidal activity using Chlamydia muridarum revealed powerful inhibitory effects at the same low micromolar doses that suppressed sperm movement. In this case, the microbicidal action was associated with alkylation of Major Outer Membrane Protein (MOMP), a major chlamydial membrane protein. Taken together, these results have identified for the first time a novel set of cellular targets and chemical principles capable of providing simultaneous defense against both fertility and the spread of sexually transmitted disease.

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We present a mass-conservative vertex-centred finite volume method for efficiently solving the mixed form of Richards’ equation in heterogeneous porous media. The spatial discretisation is particularly well-suited to heterogeneous media because it produces consistent flux approximations at quadrature points where material properties are continuous. Combined with the method of lines, the spatial discretisation gives a set of differential algebraic equations amenable to solution using higher-order implicit solvers. We investigate the solution of the mixed form using a Jacobian-free inexact Newton solver, which requires the solution of an extra variable for each node in the mesh compared to the pressure-head form. By exploiting the structure of the Jacobian for the mixed form, the size of the preconditioner is reduced to that for the pressure-head form, and there is minimal computational overhead for solving the mixed form. The proposed formulation is tested on two challenging test problems. The solutions from the new formulation offer conservation of mass at least one order of magnitude more accurate than a pressure head formulation, and the higher-order temporal integration significantly improves both the mass balance and computational efficiency of the solution.