967 resultados para Polyphosphates quantification


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Carbon nanotubes (CNT) could serve as potential reinforcement for metal matrix composites for improved mechanical properties. However dispersion of carbon nanotubes (CNT) in the matrix has been a longstanding problem, since they tend to form clusters to minimize their surface area. The aim of this study was to use plasma and cold spraying techniques to synthesize CNT reinforced aluminum composite with improved dispersion and to quantify the degree of CNT dispersion as it influences the mechanical properties. Novel method of spray drying was used to disperse CNTs in Al-12 wt.% Si prealloyed powder, which was used as feedstock for plasma and cold spraying. A new method for quantification of CNT distribution was developed. Two parameters for CNT dispersion quantification, namely Dispersion parameter (DP) and Clustering Parameter (CP) have been proposed based on the image analysis and distance between the centers of CNTs. Nanomechanical properties were correlated with the dispersion of CNTs in the microstructure. Coating microstructure evolution has been discussed in terms of splat formation, deformation and damage of CNTs and CNT/matrix interface. Effect of Si and CNT content on the reaction at CNT/matrix interface was thermodynamically and kinetically studied. A pseudo phase diagram was computed which predicts the interfacial carbide for reaction between CNT and Al-Si alloy at processing temperature. Kinetic aspects showed that Al4C3 forms with Al-12 wt.% Si alloy while SiC forms with Al-23wt.% Si alloy. Mechanical properties at nano, micro and macro-scale were evaluated using nanoindentation and nanoscratch, microindentation and bulk tensile testing respectively. Nano and micro-scale mechanical properties (elastic modulus, hardness and yield strength) displayed improvement whereas macro-scale mechanical properties were poor. The inversion of the mechanical properties at different scale length was attributed to the porosity, CNT clustering, CNT-splat adhesion and Al 4C3 formation at the CNT/matrix interface. The Dispersion parameter (DP) was more sensitive than Clustering parameter (CP) in measuring degree of CNT distribution in the matrix.

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Tumor functional volume (FV) and its mean activity concentration (mAC) are the quantities derived from positron emission tomography (PET). These quantities are used for estimating radiation dose for a therapy, evaluating the progression of a disease and also use it as a prognostic indicator for predicting outcome. PET images have low resolution, high noise and affected by partial volume effect (PVE). Manually segmenting each tumor is very cumbersome and very hard to reproduce. To solve the above problem I developed an algorithm, called iterative deconvolution thresholding segmentation (IDTS) algorithm; the algorithm segment the tumor, measures the FV, correct for the PVE and calculates mAC. The algorithm corrects for the PVE without the need to estimate camera's point spread function (PSF); also does not require optimizing for a specific camera. My algorithm was tested in physical phantom studies, where hollow spheres (0.5-16 ml) were used to represent tumors with a homogeneous activity distribution. It was also tested on irregular shaped tumors with a heterogeneous activity profile which were acquired using physical and simulated phantom. The physical phantom studies were performed with different signal to background ratios (SBR) and with different acquisition times (1-5 min). The algorithm was applied on ten clinical data where the results were compared with manual segmentation and fixed percentage thresholding method called T50 and T60 in which 50% and 60% of the maximum intensity respectively is used as threshold. The average error in FV and mAC calculation was 30% and -35% for 0.5 ml tumor. The average error FV and mAC calculation were ~5% for 16 ml tumor. The overall FV error was ∼10% for heterogeneous tumors in physical and simulated phantom data. The FV and mAC error for clinical image compared to manual segmentation was around -17% and 15% respectively. In summary my algorithm has potential to be applied on data acquired from different cameras as its not dependent on knowing the camera's PSF. The algorithm can also improve dose estimation and treatment planning.^

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While researchers have devoted considerable attention to exploring the ways that intentional environmental reregulation creates new avenues for capital accumulation (e.g. Smith, 2007; Castree, 2008), it remains somewhat unclear how the less grandiose day-to-day work of environmental regulators may also help create new sources of ecological value. Through an ethnographic study of environmental regulators tasked with enforcing key environmental laws, I shed light on the subtle ways that rule interpretation and scientific practice structure the frames, models, and methodologies regulators use to enact “best professional judgments” about ecological systems, and ultimately to assign particular values to nature. I also show the ways that non-human nature pushes back against such assessments, which in combination with the interpretive work of environmental regulation, opens spaces of conflict in at least two arenas: one focused on modes of quantification, where actors contend between economistic, ecological, statutory, and moral frames for making value assessments; and one focused on presentations of value, where actors contend between value assessments that best represent their self-defined interests. The ‘value settlements’ environmental regulators reach in these contested spaces allow processes of commensuration to proceed, and ultimately make nature legible for capitalization and exchange. Accounting for the ways that these basic regulatory practice help create ecological value is essential for creating a fuller picture of the ways capital and natural capital relate.

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This dissertation combines three separate studies that measure coastal change using airborne laser data. The initial study develops a method for measuring subaerial and subaqueous volume change incrementally alongshore, and compares those measurements to shoreline change in order to quantify their relationship in Palm Beach County, Florida. A poor correlation (R2 = 0.39) was found between shoreline and volume change before the hurricane season in the northern section of Palm Beach County because of beach nourishment and inlet dynamics. However, a relatively high R2 value of 0.78 in the southern section of Palm Beach County was found due to little disturbance from tidal inlets and coastal engineering projects. The shoreline and volume change caused by the 2004 hurricane season was poorly correlated with R2 values of 0.02 and 0.42 for the north and south sections, respectively. The second study uses airborne laser data to investigate if there is a significant relationship between shoreline migration before and after Hurricane Ivan near Panama City, Florida. In addition, the relationship between shoreline change and subaerial volume was quantified and a new method for quantifying subaqueous sediment change was developed. No significant spatial relationship was found between shoreline migration before and after the hurricane. Utilization of a single coefficient to represent all relationships between shoreline and subaerial volume change was found to be problematic due to the spatial variability in the linear relationship. Differences in bathymetric data show only a small portion of sediment was transported beyond the active zone and most sediment remained within the active zone despite the occurrence of a hurricane. The third study uses airborne laser bathymetry to measure the offshore limit of change, and compares that location with calculated depth of closures and subaqueous geomorphology. There appears to be strong geologic control of the depth of closure in Broward and Miami-Dade Counties. North of Hillsboro Inlet, hydrodynamics control the geomorphology which in turn indicates the location of the depth of closure.

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Carbon nanotubes (CNT) could serve as potential reinforcement for metal matrix composites for improved mechanical properties. However dispersion of carbon nanotubes (CNT) in the matrix has been a longstanding problem, since they tend to form clusters to minimize their surface area. The aim of this study was to use plasma and cold spraying techniques to synthesize CNT reinforced aluminum composite with improved dispersion and to quantify the degree of CNT dispersion as it influences the mechanical properties. Novel method of spray drying was used to disperse CNTs in Al-12 wt.% Si pre-alloyed powder, which was used as feedstock for plasma and cold spraying. A new method for quantification of CNT distribution was developed. Two parameters for CNT dispersion quantification, namely Dispersion parameter (DP) and Clustering Parameter (CP) have been proposed based on the image analysis and distance between the centers of CNTs. Nanomechanical properties were correlated with the dispersion of CNTs in the microstructure. Coating microstructure evolution has been discussed in terms of splat formation, deformation and damage of CNTs and CNT/matrix interface. Effect of Si and CNT content on the reaction at CNT/matrix interface was thermodynamically and kinetically studied. A pseudo phase diagram was computed which predicts the interfacial carbide for reaction between CNT and Al-Si alloy at processing temperature. Kinetic aspects showed that Al4C3 forms with Al-12 wt.% Si alloy while SiC forms with Al-23wt.% Si alloy. Mechanical properties at nano, micro and macro-scale were evaluated using nanoindentation and nanoscratch, microindentation and bulk tensile testing respectively. Nano and micro-scale mechanical properties (elastic modulus, hardness and yield strength) displayed improvement whereas macro-scale mechanical properties were poor. The inversion of the mechanical properties at different scale length was attributed to the porosity, CNT clustering, CNT-splat adhesion and Al4C3 formation at the CNT/matrix interface. The Dispersion parameter (DP) was more sensitive than Clustering parameter (CP) in measuring degree of CNT distribution in the matrix.

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The objective of this study is to design and development of an enzyme-linked biosensor for detection and quantification of phosphate species. Various concentrations of phosphate species were tested and completed for this study. Phosphate is one of the vital nutrients for all living organisms. Phosphate compounds can be found in nature (e.g., water sediments), and they often exist in aninorganic form. The amount of phosphates in the environment strongly influences the operations of living organisms. Excess amount of phosphate in the environment causes eutrophication which in turn causes oxygen deficit for the other living organisms. Fish die and degradation of habitat in the water occurs as a result of eutrophication. In contrast, low phosphate concentration causes death of vegetation since plants utilize the inorganic phosphate for photosynthesis, respiration, and regulation of enzymes. Therefore, the phosphate quantity in lakes and rivers must be monitored. Result demonstrated that phosphate species could be detected in various organisms via enzyme-linked biosensor in this research.

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Date of Acceptance: 31/08/2015 The authors would like to thank Total E&P and BG Group for project funding and support and the Industry Technology Facilitator for enabling the collaborative development (grant number 3322PSD). The authors would also like to thank Aberdeen Formation Evaluation Society and the College of Physical Sciences at the University of Aberdeen for partial financial support. Dougal Jerram, Raymi Castilla, Claude Gout, Frances Abbots and an anonymous reviewer are thanked for their constructive comments and suggestions to improve the standard of this manuscript. The authors would also like to express their gratitude toJohn Still and Colin Taylor for technical assistance in the laboratory and Nick Timms (Curtin University) and Angela Halfpenny (CSIRO) for their assistance with the full thin section scanning equipment.

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Date of Acceptance: 31/08/2015 The authors would like to thank Total E&P and BG Group for project funding and support and the Industry Technology Facilitator for enabling the collaborative development (grant number 3322PSD). The authors would also like to thank Aberdeen Formation Evaluation Society and the College of Physical Sciences at the University of Aberdeen for partial financial support. Dougal Jerram, Raymi Castilla, Claude Gout, Frances Abbots and an anonymous reviewer are thanked for their constructive comments and suggestions to improve the standard of this manuscript. The authors would also like to express their gratitude toJohn Still and Colin Taylor for technical assistance in the laboratory and Nick Timms (Curtin University) and Angela Halfpenny (CSIRO) for their assistance with the full thin section scanning equipment.

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Purpose To quantify diadenosine polyphosphate levels in tears of congenital aniridia patients to estimate the ocular surface changes associated with congenital aniridia compared to normal individuals. Methods Fifteen patients diagnosed with congenital aniridia and a control group of forty volunteers were studied. Tears were collected to quantify the levels of diadenosine polyphosphates Ap4A and Ap5A by high-performance liquid chromatography (H.P.L.C). Break-up time (BUT), corneal staining, McMonnies questionnaire and the Schirmer I test were applied to both groups. Results Dinucleotides in congenital aniridia patients were higher than in control subjects. For the congenital aniridia group, under 15 years old, the values were 0.77 ± 0.01 μm and 0.17 ± 0.02 μm for Ap4A and Ap5A, respectively. The group aged from 15 to 40 years old provided concentrations of 4.37 ± 0.97 μm and 0.46 ± 0.05 μm for Ap4A and Ap5A, the group over 40 gave concentrations of 11.17 ± 5.53 μm and 0.68 ± 0.17 μm for Ap4A and Ap5A. Dinucleotide concentrations increased with age, being statistically significant different among the three age groups (p < 0.05). Congenital aniridia patients showed a normal tear secretion and no dry eye McMonnies scores, except for the group over 40 years old. BUT values decreased and corneal staining increased with age and correlated with the levels of diadenosine polyphosphates (p < 0.05). Conclusions The levels of dinucleotides in tears increase in aniridia patients compared with healthy subjects, and they seem to be related with the progression of corneal disorders in aniridia patients, both of which increase with ageing.

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Purpose:  To study the concentrations of diadenosine polyphosphates in the ocular surface after PRK and LASIK. Methods:  Sixty-one patients (30 males and 31 females) with ages ranging from 20 to 63 (34.04 ± 9.13 years) were recruited in Balear Institute of Ophthalmology, Palma de Mallorca, Spain. LASIK was performed in 92 eyes of 46 patients and PRK in 25 eyes of 15 patients. Variations in the levels of diadenosine polyphosphate (Ap4A and Ap5A), Schirmer I (Jones test), TBUT, corneal staining together with the Dry Eye Questionnaire to evaluate discomfort and dryness were studied. All tests were performed at the preoperative visit and at 1-day, 2-week, 1-month and 3-month postoperative visits. Results:  Ap4A showed a 5 and 3.5 fold increase at the 1-day visit for LASIK and PRK, respectively. LASIK patients continued having higher statistically significant concentrations (p = 0.01) all over the follow-up. Ap5A showed no significant differences at any visit. Tear volume decreased during the 3 months in LASIK. The PRK cases had a normal volume at 1 month. TBUT in LASIK increased at the 1-day visit (p = 0,002) and decreased from the 2 weeks onwards and for the PRK, decreased by a 35% at the 1-day visit and kept reduced for a month. Discomfort only increased at the 1-day visit (p = 0.007). Dryness frequency was similar in all visits. Conclusions:  Ap4A levels only are increased in refractive surgery patients during the first day after the surgery. This increasing suggests that Ap4A may help accelerating the healing process.

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Quantification of the lipid content in liposomal adjuvants for subunit vaccine formulation is of extreme importance, since this concentration impacts both efficacy and stability. In this paper, we outline a high performance liquid chromatography-evaporative light scattering detector (HPLC-ELSD) method that allows for the rapid and simultaneous quantification of lipid concentrations within liposomal systems prepared by three liposomal manufacturing techniques (lipid film hydration, high shear mixing, and microfluidics). The ELSD system was used to quantify four lipids: 1,2-dimyristoyl-sn-glycero-3-phosphocholine (DMPC), cholesterol, dimethyldioctadecylammonium (DDA) bromide, and D-(+)-trehalose 6,6′-dibehenate (TDB). The developed method offers rapidity, high sensitivity, direct linearity, and a good consistency on the responses (R2 > 0.993 for the four lipids tested). The corresponding limit of detection (LOD) and limit of quantification (LOQ) were 0.11 and 0.36 mg/mL (DMPC), 0.02 and 0.80 mg/mL (cholesterol), 0.06 and 0.20 mg/mL (DDA), and 0.05 and 0.16 mg/mL (TDB), respectively. HPLC-ELSD was shown to be a rapid and effective method for the quantification of lipids within liposome formulations without the need for lipid extraction processes.

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Uncertainty quantification (UQ) is both an old and new concept. The current novelty lies in the interactions and synthesis of mathematical models, computer experiments, statistics, field/real experiments, and probability theory, with a particular emphasize on the large-scale simulations by computer models. The challenges not only come from the complication of scientific questions, but also from the size of the information. It is the focus in this thesis to provide statistical models that are scalable to massive data produced in computer experiments and real experiments, through fast and robust statistical inference.

Chapter 2 provides a practical approach for simultaneously emulating/approximating massive number of functions, with the application on hazard quantification of Soufri\`{e}re Hills volcano in Montserrate island. Chapter 3 discusses another problem with massive data, in which the number of observations of a function is large. An exact algorithm that is linear in time is developed for the problem of interpolation of Methylation levels. Chapter 4 and Chapter 5 are both about the robust inference of the models. Chapter 4 provides a new criteria robustness parameter estimation criteria and several ways of inference have been shown to satisfy such criteria. Chapter 5 develops a new prior that satisfies some more criteria and is thus proposed to use in practice.