In this paper, two different technical criteria, i.e., the oil recovery factor (ORF) and break-over pressure (BOP), are studied and compared to determine the minimum miscibility pressures (MMPs) of two light crude oil–CO2 systems. More specifically, five slim-tube tests with the live light crude oil–CO2 system and five coreflood tests with the dead light crude oil–CO2 system are conducted to measure the ORFs at different injection pressures and the actual reservoir temperature of Tres=53.0°C. The linear and quadratic extrapolation methods as well as the linear intersection method are applied by using the ORF criterion. Three different high threshold ORFs of 88% for the slim-tube tests or 87% for the coreflood tests, 90% and 95% are chosen to determine the MMPs by means of the linear and quadratic extrapolation methods. On the other hand, the linear intersection method is used to determine the MMP by finding a sudden slope change point in the measured ORF versus injection pressure curve for the slim-tube or coreflood tests. Moreover, the BOP criterion is based on the cubic regression of the measured ORF versus injection pressure data and used to determine the MMPs, which correspond to four different low threshold slopes or incremental ORFs per incremental injection pressure increase of 5, 3, 2, and 1%/MPa. It is found that different MMP ranges can be obtained from the same measured ORF versus injection pressure data if different MMP criteria, regression methods, and threshold values or numerical options are adopted. The determined MMP is better given in a small pressure range than specified as a definitive pressure value. Two MMP ranges of the live and dead light crude oil–CO2 systems are determined to be 15.2–15.4MPa and 12.4–12.9MPa at Tres=53.0°C, respectively.
In this investigation, we reported the two-dimensional (2D) self-assembly of a pair of triangular macrocycles (TMC1 and TMC2) at a highly oriented pyrolytic graphite (HOPG)/1-phenyloctane interface. Although with the similar triangle-shaped phenyl backbones, TMC1 and TMC2 displayed different 2D nanopatterns. Control experiments with varying concentrations and temperatures have been carried out. Phase separations were recorded in the coassembly of TMC1 and TMC2. Scanning tunneling microscopy (STM) measurements, as well as density function theory (DFT) calculations, revealed the formation mechanism of the TMC1 and TMC2 nanoarrays. Moreover, minor ring-opening phenomena of TMC2 were detected by STM, which demonstrates the advantages of STM in trace content analysis.
Using a double-slit structure fabricated on a gold film or a subwavelength (300 nm) plasmonic waveguide, high-contrast and broadband plasmonic sensors based on the interference of surface plasmon polaritons (SPPs) are experimentally demonstrated on chips. By adjusting the focused spot position of the p-polarized incident light on the double-slit structure to compensate for the propagation loss of the SPPs, the interfering SPPs from the two slits have nearly equal intensities. As a result, nearly completely destructive interference can be experimentally achieved in a broad bandwidth (>200 nm), revealing the robust design and fabrication of the double-slit structure. More importantly, a high sensing figure of merit (FOM*) of >1 x 10(4) RIU-1 (refractive index unit), which is much greater than the previous experimental results, is obtained at the destructive wavelength because of a high contrast ratio (C = 0.96). The high-contrast and broadband on-chip sensor fabricated on the subwavelength plasmonic waveguide may find important applications in the real-time sensing of particles and molecules.
Miniaturizing optical devices beyond the diffraction limit is of great importance for high-integration photonic circuits. By directly fabricating a double-slit aperture structure of different sizes in a subwavelength plasmonic waveguide, an ultra-small plasmonic wavelength splitter is realized experimentally. Due to the different slit widths, the surface plasmon polaritons (SPPs) in the opposite directions exhibit anti-phase interferences. As a result, the SPPs excited at different wavelengths can be split to propagate in the opposite directions along the subwavelength plasmonic waveguide. The plasmonic wavelength splitter only occupies a footprint of about 1.4 mu m(2) on the metal surface, and the splitting wavelengths and their separation can be easily varied by adjusting the structural parameters. This provides it with important applications in the areas of the optical modulating, sensing, and computing networks in highly integrated plasmonic circuits. (C) 2015 Optical Society of America
The existence and importance of peroxyformic acid (PFA) in the atmosphere has been under controversy. We present here, for the first time, the observation data for PFA from four field measurements carried out in China. These data provided powerful evidence that PFA can stay in the atmosphere, typically in dozens of pptv level. The relationship between PFA and other detected peroxides was examined. The results showed that PFA had a strong positive correlation with its homolog, peroxyacetic acid, due to their similar sources and sinks. Through an evaluation of PFA production and removal rates, we proposed that the reactions between peroxyformyl radical (HC(O)O2) and formaldehyde or the hydroperoxyl radical (HO2) were likely to be the major source and degradation into formic acid (FA) was likely to be the major sink for PFA. Based on a box model evaluation, we proposed that the HC(O)O2 and PFA chemistry was a major source for FA under low NOx conditions. Furthermore, it is found that the impact of the HC(O)O2 and PFA chemistry on radical cycling was dependent on the yield of HC(O)O2 radical from HC(O) + O2 reaction. When this yield exceeded 50%, the HC(O)O2 and PFA chemistry should not be neglected for calculating the radical budget. To make clear the exact importance of HC(O)O2 and PFA chemistry in the atmosphere, further kinetic, field and modeling studies are required.
The objective of this study was to remove systematic bias among fine particulate matter (PM2.5) mass concentration measurements made by different types of samplers used in the Pittsburgh Aerosol Research and Inhalation Epidemiology Study (PARIES). PARIES is a retrospective epidemiology study that aims to provide a comprehensive analysis of the associations between air quality and human health effects in the Pittsburgh, Pennsylvania, region from 1999 to 2008. Calibration was needed in order to minimize the amount of systematic error in PM2.5 exposure estimation as a result of including data from 97 different PM2.5 samplers at 47 monitoring sites. Ordinary regression often has been used for calibrating air quality measurements from pairs of measurement devices; however, this is only appropriate when one of the two devices (the "independent" variable) is free from random error, which is rarely the case. A group of methods known as "errors-in-variables" (e.g., Deming regression, reduced major axis regression) has been developed to handle calibration between two devices when both are subject to random error, but these methods require information on the relative sizes of the random errors for each device, which typically cannot be obtained from the observed data. When data from more than two devices (or repeats of the same device) are available, the additional information is not used to inform the calibration. A more general approach that often has been overlooked is the use of a measurement error structural equation model (SEM) that allows the simultaneous comparison of three or more devices (or repeats). The theoretical underpinnings of all of these approaches to calibration are described, and the pros and cons of each are discussed. In particular, it is shown that both ordinary regression (when used for calibration) and Deming regression are particular examples of SEMs but with substantial deficiencies. To illustrate the use of SEMs, the 7865 daily average PM2.5 mass concentration measurements made by seven collocated samplers at an urban monitoring site in Pittsburgh, Pennsylvania, were used. These samplers, which included three federal reference method (FRM) samplers, three speciation samplers, and a tapered element oscillating microbalance (TEOM), operated at various times during the 10-year PARIES study period. Because TEOM measurements are known to depend on temperature, the constructed SEM provided calibration equations relating the TEOM to the FRM and speciation samplers as a function of ambient temperature. It was shown that TEOM imprecision and TEOM bias (relative to the FRM) both decreased as temperature increased. It also was shown that the temperature dependency for bias was non-linear and followed a sigmoidal (logistic) pattern. The speciation samplers exhibited only small bias relative to the FRM samplers, although the FRM samplers were shown to be substantially more precise than both the TEOM and the speciation samplers. Comparison of the SEM results to pairwise simple linear regression results showed that the regression results can differ substantially from the correctly-derived calibration equations, especially if the less-precise device is used as the independent variable in the regression. (C) 2014 Elsevier Ltd. All rights reserved.
Airborne particles in urban Beijing during haze days and normal days were collected and analyzed in the autumn and winter seasons to reveal the chemical characteristics variations of air pollution. The air quality in haze days was substantially worse than that in normal days. Both the relatively low wind speed and high relative humidity were in favor of the accumulation of pollution species and new formation of secondary PM2.5 in the atmosphere. Elevated concentrations of elements and water-soluble inorganic ions were found on haze days for both PM10 and PM2.5. Particularly, the crustal element, such as Fe, in both PM10 and PM2.5 were substantially higher in autumn normal days and winter haze days than those in autumn haze days and winter normal days, indicating that the abundance of Fe in autumn haze days mainly be originated from crustal dust while in winter haze days it might be primarily emitted from anthropogenic sources (iron and steel smelting) instead of road dust. Secondary ion species (SO42−, NO3−, NH4+) in particles were generated much more during haze episodes, and contributed a higher proportion in PM2.5 than in PM10 during the two sampling periods. Moreover, HYSPLIT model was used to explain the possible transport of airborne particles from distant sources. By comparing with south-type trajectory, west-type trajectory entrained larger amounts of primary crustal pollutants, while, south-type trajectory was comprised of a higher mass of anthropogenic pollution species. The results of back trajectory analysis indicated that the elevated concentration of aerosol and its chemical components during haze days might be caused by the integrated effects of accumulation under stagnant meteorological condition and the transport emissions of pollutants from anthropogenic sources surrounding Beijing city.
Towards low bit rate mobile visual search, recent works have proposed to aggregate the local features and compress the aggregated descriptor (such as Fisher vector, the vector of locally aggregated descriptors) for low latency query delivery as well as moderate search complexity. Even though Hamming distance can be computed very fast, the computational cost of exhaustive linear search over the binary descriptors grows linearly with either the length of a binary descriptor or the number of database images. In this paper, we propose a novel weighted component hashing (WeCoHash) algorithm for long binary aggregated descriptors to significantly improve search efficiency over a large scale image database. Accordingly, the proposed WeCoHash has attempted to address two essential issues in Hashing algorithms: "what to hash" and "how to search." "What to hash" is tackled by a hybrid approach, which utilizes both image-specific component (i.e., visual word) redundancy and bit dependency within each component of a binary aggregated descriptor to produce discriminative hash values for bucketing. "How to search" is tackled by an adaptive relevance weighting based on the statistics of hash values. Extensive comparison results have shown that WeCoHash is at least 20 times faster than linear search and 10 times faster than local sensitive hash (LSH) when maintaining comparable search accuracy. In particular, the WeCoHash solution has been adopted by the emerging MPEG compact descriptor for visual search (CDVS) standard to significantly speed up the exhaustive search of the binary aggregated descriptors.
