999 resultados para FCC 110 SURFACES


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An investigation has been made of the interactions between silicone oil and various solid substrates immersed in aqueous solutions. Measurements were made using an atomic force microscope (AFM) using the colloid-probe method. The silicone oil drop is simulated by coating a small silica sphere with the oil, and measuring the force as this coated sphere is brought close to contact with a flat solid surface. It is found that the silicone oil surface is negatively charged, which causes a double-layer repulsion between the oil drop and another negatively charged surface such as mica. With hydrophilic solids, this repulsion is strong enough to prevent attachment of the drop to the solid. However, with hydrophobic surfaces there is an additional attractive force which overcomes the double-layer repulsion, and the silicone oil drop attaches to the solid. A "ramp" force appears in some, but not all, of the data sets. There is circumstantial evidence that this force results from compression of the silicone oil film coated on the glass sphere.

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This paper discusses the outcomes of a research project on nutrients build-up on urban road surfaces. Nutrient build-up was investigated on road sites belonging to residential, industrial and commercial land use. Collected build-up samples were separated into five particle size ranges and were tested for total nitrogen (TN), total phosphorus (TP) and sub species of nutrients, namely, NO2-, NO3-, TKN and PO43-. Multivariate analytical techniques were used to analyse the data and to develop detailed understanding on build-up. Data analysis revealed that the solids loads on urban road surfaces are highly influenced by factors such as land use, antecedent dry period and traffic volume. However, the nutrient build-up process was found to be independent of the type of land use. It was solely dependent on the particle size of solids build-up. Most of the nutrients were associated with the particle size range <150 μm. Therefore, the removal of particles below 150 µm from road surfaces is of importance for the removal of nitrogen and phosphorus from road surface solids build-up. It is also important to consider the differences in the composition of nitrogen and phosphorus build-up in the context of designing effective stormwater quality mitigation strategies.

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This paper presents the outcomes of a study which focused on evaluating roof surfaces as stormwater harvesting catchments. Build-up and wash-off samples were collected from model roof surfaces. The collected build-up samples were separated into five different particle size ranges prior to the analysis of physico-chemical parameters. Study outcomes showed that roof surfaces are efficient catchment surfaces for the deposition of fine particles which travel over long distances. Roof surfaces contribute relatively high pollutant loads to the runoff and hence significantly influence the quality of the harvested rainwater. Pollutants associated with solids build-up on roof surfaces can vary with time, even with minimal changes to total solids load and particle size distribution. It is postulated that this variability is due to changes in distant atmospheric pollutant sources and wind patterns. The study highlighted the requirement for first flush devices to divert the highly polluted initial portion of roof runoff. Furthermore, it is highly recommended to not to harvest runoff from small intensity rainfall events since there is a high possibility that the runoff would contain a significant amount of pollutants even after the initial runoff fraction.

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Corneal-height data are typically measured with videokeratoscopes and modeled using a set of orthogonal Zernike polynomials. We address the estimation of the number of Zernike polynomials, which is formalized as a model-order selection problem in linear regression. Classical information-theoretic criteria tend to overestimate the corneal surface due to the weakness of their penalty functions, while bootstrap-based techniques tend to underestimate the surface or require extensive processing. In this paper, we propose to use the efficient detection criterion (EDC), which has the same general form of information-theoretic-based criteria, as an alternative to estimating the optimal number of Zernike polynomials. We first show, via simulations, that the EDC outperforms a large number of information-theoretic criteria and resampling-based techniques. We then illustrate that using the EDC for real corneas results in models that are in closer agreement with clinical expectations and provides means for distinguishing normal corneal surfaces from astigmatic and keratoconic surfaces.

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The indoline dyes D102, D131, D149, and D205 have been characterized when adsorved on fluorine-doped tin oxide (FTO) and TiO2 electrode surfaces. Adsorption from 50:50 acetonitrile - tert-butanol onto flourine-doped tin oxide (FTO) allows approximate Langmuirian binding constants of 6.5 x 10(4), 2.01 x 10(3), 2.0 x 10(4), and 1.5 x 10(4) mol-1 dm3, respectively, to be determined. Voltammetric data obtained in acetonitrile/0.1 M NBu4PF6 indicate reversible on-electron oxidation at Emid = 0.94, 0.91, 0.88, and 0.88 V vs Ag/AgCI(3 M KCI), respectively, with dye aggregation (at high coverage) causing additional peak features at more positive potentials. Slow chemical degradation processes and electron transfer catalysis for iodine oxidation were observed for all four oxidezed indolinium cations. When adsorbed onto TiO2 nanoparticle films (ca. 9nm particle diameter and ca.3/um thickness of FTO0, reversible voltammetric responses with Emid = 1.08, 1.156, 0.92 and 0.95 V vs Ag/AgCI(3 M KCI), respectively, suggest exceptionally fast hole hopping diffusion (with Dapp > 5 x 10(-9) m2 s-1) for adsorbed layers of four indoline dyes, presumably due to pie-pie stacking in surface aggregates. Slow dye degradation is shown to affect charge transport via electron hopping. Spectrelectrochemical data for the adsorbed indoline dyes on FTO-TiO2 revealed a red-shift of absorption peaks after oxidation and the presence of a strong charge transfer band in the near-IR region. The implications of the indoline dye reactivity and fast hole mobility for solar cell devices are discussed.

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Background: Implant surface micro-roughness and hydrophilicity are known to improve the osteogenic differentiation potential of osteoprogenitor cells. This study was aimed to determine whether topographically and chemically modified titanium implant surfaces stimulate an initial osteogenic response in osteoprogenitor cells, which leads to their improved osteogenesis. ----- ----- Methods: Statistical analysis of microarray gene expression profiling data available from studies (at 72 hours) on sand-blasted, large grit acid etched (SLA) titanium surfaces was performed. Subsequently, human osteoprogenitor cells were cultured on SLActive (hydrophilic SLA), SLA and polished titanium surfaces for 24 hours, 3 days and 7 days. The expression of BMP2, BMP6, BMP2K, SP1, ACVR1, FZD6, WNT5A, PDLIM7, ITGB1, ITGA2, OCN, OPN, ALP and RUNX2 were studied using qPCR. ----- ----- Results: Several functional clusters related to osteogenesis were highlighted when genes showing statistically significant differences (from microarray data at 72 hours) in expression on SLA surface (compared with control surface) were analysed using DAVID (online tool). This indicates that differentiation begins very early in response to modified titanium surfaces. At 24 hours, ACVR1 (BMP pathway), FZD6 (Wnt pathway) and SP1 (TGF-β pathway) were significantly up-regulated in cultures on the SLActive surface compared to the other surfaces. WNT5A and ITGB1 also showed higher expression on the modified surfaces. Gene expression patterns on Day 3 and Day 7 did not reveal any significant differences.----- ----- Conclusion: These results suggest that the initial molecular response of osteoprogenitor cells to modified titanium surfaces may be responsible for an improved osteogenic response via the BMP and Wnt signalling pathways.

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Road surface macrotexture is identified as one of the factors contributing to the surface's skid resistance. Existing methods of quantifying the surface macrotexture, such as the sand patch test and the laser profilometer test, are either expensive or intrusive, requiring traffic control. High-resolution cameras have made it possible to acquire good quality images from roads for the automated analysis of texture depth. In this paper, a granulometric method based on image processing is proposed to estimate road surface texture coarseness distribution from their edge profiles. More than 1300 images were acquired from two different sites, extending to a total of 2.96 km. The images were acquired using camera orientations of 60 and 90 degrees. The road surface is modeled as a texture of particles, and the size distribution of these particles is obtained from chord lengths across edge boundaries. The mean size from each distribution is compared with the sensor measured texture depth obtained using a laser profilometer. By tuning the edge detector parameters, a coefficient of determination of up to R2 = 0.94 between the proposed method and the laser profilometer method was obtained. The high correlation is also confirmed by robust calibration parameters that enable the method to be used for unseen data after the method has been calibrated over road surface data with similar surface characteristics and under similar imaging conditions.