Regulations and policy measures related to the reduction of ambient particulate matter

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Tuning the reduction power of supported gold nanoparticle photocatalysts for selective reductions by manipulating wavelength of visible light irradiation

Gold nanoparticles supported on CeO2 were found to be efficient photocatalysts for three selective reductions of organic compounds at ambient temperatures, under irradiation of visible light; their reduction ability can be tuned by manipulating the irradiation wavelength.

Can partial coherence interferometry be used to determine retinal shape?

Purpose: To determine likely errors in estimating retinal shape using partial coherence interferometric instruments when no allowance is made for optical distortion. Method: Errors were estimated using Gullstrand’s No. 1 schematic eye and variants which included a 10 D axial myopic eye, an emmetropic eye with a gradient-index lens, and a 10.9 D accommodating eye with a gradient-index lens. Performance was simulated for two commercial instruments, the IOLMaster (Carl Zeiss Meditec) and the Lenstar LS 900 (Haag-Streit AG). The incident beam was directed towards either the centre of curvature of the anterior cornea (corneal-direction method) or the centre of the entrance pupil (pupil-direction method). Simple trigonometry was used with the corneal intercept and the incident beam angle to estimate retinal contour. Conics were fitted to the estimated contours. Results: The pupil-direction method gave estimates of retinal contour that were much too flat. The cornea-direction method gave similar results for IOLMaster and Lenstar approaches. The steepness of the retinal contour was slightly overestimated, the exact effects varying with the refractive error, gradient index and accommodation. Conclusion: These theoretical results suggest that, for field angles ≤30º, partial coherence interferometric instruments are of use in estimating retinal shape by the corneal-direction method with the assumptions of a regular retinal shape and no optical distortion. It may be possible to improve on these estimates out to larger field angles by using optical modeling to correct for distortion.

Hierarchical robust design optimisation of shock control bump devices for airfoil drag reduction

The paper investigates a detailed Active Shock Control Bump Design Optimisation on a Natural Laminar Flow (NLF) aerofoil; RAE 5243 to reduce cruise drag at transonic flow conditions using Evolutionary Algorithms (EAs) coupled to a robust design approach. For the uncertainty design parameters, the positions of boundary layer transition (xtr) and the coefficient of lift (Cl) are considered (250 stochastic samples in total). In this paper, two robust design methods are considered; the first approach uses a standard robust design method, which evaluates one design model at 250 stochastic conditions for uncertainty. The second approach is the combination of a standard robust design method and the concept of hierarchical (multi-population) sampling (250, 50, 15) for uncertainty. Numerical results show that the evolutionary optimization method coupled to uncertainty design techniques produces useful and reliable Pareto optimal SCB shapes which have low sensitivity and high aerodynamic performance while having significant total drag reduction. In addition,it also shows the benefit of using hierarchical robust method for detailed uncertainty design optimization.

Innate Immunity in Lobsters: Partial Purification and Characterization of a Panulirus cygnus Anti-A Lectin

A lectin detected in haemolymph from the Australian spiny lobster Panulirus cygnus agglutinated human ABO Group A cells to a higher titre than Group O or B. The lectin also agglutinated rat and sheep erythrocytes, with reactivity with rat erythrocytes strongly enhanced by treatment with the proteolytic enzyme papain, an observation consistent with reactivity via a glycolipid. The lectin, purified by affinity chromatography on fixed rat-erythrocyte stroma, was inhibited equally by N-acetylglucosamine and N-acetylgalactosamine. Comparison of data from gel filtration of haemolymph (behaving as a 1,800,000 Da macromolecule), and polyacrylamide gel electrophoresis of purified lectin (a single 67,000 Da band), suggested that in haemolymph the lecin was a multimer. The purified anti-A lectin autoprecipitated unless the storage solution contained chaotropic inhibitors (125 mmol/L sucrose: 500 mmol/L urea). The properties of this anti-A lectin and other similar lectins are consistent with a role in innate immunity in these invertebrates.

Mixed convection flow of micropolar fluid in an open ended arc-shape cavity

Numerical simulations for mixed convection of micropolar fluid in an open ended arc-shape cavity have been carried out in this study. Computation is performed using the Alternate Direct Implicit (ADI) method together with the Successive Over Relaxation (SOR) technique for the solution of governing partial differential equations. The flow phenomenon is examined for a range of values of Rayleigh number, 102 ≤ Ra ≤ 106, Prandtl number, 7 ≤ Pr ≤ 50, and Reynolds number, 10 ≤ Re ≤ 100. The study is mainly focused on how the micropolar fluid parameters affect the fluid properties in the flow domain. It was found that despite the reduction of flow in the core region, the heat transfer rate increases, whereas the skin friction and microrotation decrease with the increase in the vortex viscosity parameter, Δ.

State convergence and keyspace reduction of the mixer stream cipher

This paper presents an analysis of the stream cipher Mixer, a bit-based cipher with structural components similar to the well-known Grain cipher and the LILI family of keystream generators. Mixer uses a 128-bit key and 64-bit IV to initialise a 217-bit internal state. The analysis is focused on the initialisation function of Mixer and shows that there exist multiple key-IV pairs which, after initialisation, produce the same initial state, and consequently will generate the same keystream. Furthermore, if the number of iterations of the state update function performed during initialisation is increased, then the number of distinct initial states that can be obtained decreases. It is also shown that there exist some distinct initial states which produce the same keystream, resulting in a further reduction of the effective key space

Gold coating of silica and zinc oxide nanoparticles by the surface reduction of gold(I) chloride

The possibility of a surface inner sphere electron transfer mechanism leading to the coating of gold via the surface reduction of gold(I) chloride on metal and semi-metal oxide nanoparticles was investigated. Silica and zinc oxide nanoparticles are known to have very different surface chemistry, potentially leading to a new class of gold coated nanoparticles. Monodisperse silica nanoparticles were synthesised by the well known Stöber protocol in conjunction with sonication. The nanoparticle size was regulated solely by varying the amount of ammonia solution added. The presence of surface hydroxyl groups was investigated by liquid proton NMR. The resultant nanoparticle size was directly measured by the use of TEM. The synthesised silica nanoparticles were dispersed in acetonitrile (MeCN) and added to a bis acetonitrile gold(I) co-ordination complex [Au(MeCN)2]+ in MeCN. The silica hydroxyl groups were deprotonated in the presence of MeCN generating a formal negative charge on the siloxy groups. This allowed the [Au(MeCN)2]+ complex to undergo ligand exchange with the silica nanoparticles, which formed a surface co-ordination complex with reduction to gold(0), that proceeded by a surface inner sphere electron transfer mechanism. The residual [Au(MeCN)2]+ complex was allowed to react with water, disproportionating into gold(0) and gold(III) respectively, with gold(0) being added to the reduced gold already bound on the silica surface. The so-formed metallic gold seed surface was found to be suitable for the conventional reduction of gold(III) to gold(0) by ascorbic acid. This process generated a thin and uniform gold coating on the silica nanoparticles. This process was modified to include uniformly gold coated composite zinc oxide nanoparticles (Au@ZnO NPs) using surface co-ordination chemistry. AuCl dissolved in acetonitrile (MeCN) supplied chloride ions which were adsorbed onto ZnO NPs. The co-ordinated gold(I) was reduced on the ZnO surface to gold(0) by the inner sphere electron transfer mechanism. Addition of water disproportionated the remaining gold(I) to gold(0) and gold(III). Gold(0) bonded to gold(0) on the NP surface with gold(III) was reduced to gold(0) by ascorbic acid (ASC), which completed the gold coating process. This gold coating process of Au@ZnO NPs was modified to incorporate iodide instead of chloride. ZnO NPs were synthesised by the use of sodium oxide, zinc iodide and potassium iodide in refluxing basic ethanol with iodide controlling the presence of chemisorbed oxygen. These ZnO NPs were treated by the addition of gold(I) chloride dissolved in acetonitrile leaving chloride anions co-ordinated on the ZnO NP surface. This allowed acetonitrile ligands in the added [Au(MeCN)2]+ complex to surface exchange with adsorbed chloride from the dissolved AuCl on the ZnO NP surface. Gold(I) was then reduced by the surface inner sphere electron transfer mechanism. The presence of the reduced gold on the ZnO NPs allowed adsorption of iodide to generate a uniform deposition of gold onto the ZnO NP surface without the use of additional reducing agents or heat.

Nitrate reduction over nanoscale zero-valent iron prepared by hydrogen reduction of goethite

Nitrate reduction with nanoscale zero-valent iron (NZVI) was reported as a potential technology to remove nitrate from nitrate-contaminated water. In this paper, nitrate reduction with NZVI prepared by hydrogen reduction of natural goethite (NZVI-N, -N represents natural goethite) and hydrothermal goethite (NZVI-H, -H represents hydrothermal goethite) was conducted. Besides, the effects of reaction time, nitrate concentration, iron-to-nitrate ratio on nitrate removal rate over NZVI-H and NZVI-N were investigated. To prove their excellent nitrate reduction capacities, NZVI-N and NZVI-H were compared with ordinary zero-valent iron (OZVI-N) through the static experiments. Based on all above investigations, the mechanism of nitrate reduction with NZVI-N was proposed. The result showed that reaction time, nitrate concentration, iron-to-nitrate ratio played an important role in nitrate reduction by NZVI-N and NZVI-H. Compared with OZVI, NZVI-N and NZVI-H showed little relationship with pH. And NZVI-N for nitrate composition offers a higher stability than NZVI-H because of the existence of Al-substitution. Furthermore, NZVI-N, prepared by hydrogen reduction of goethite, has higher activity for nitrate reduction and the products contain hydrogen, nitrogen, NH 4 +, a little nitrite, but no NOx, meanwhile NZVI-N was oxidized to Fe 2+. It is a relatively easy and cost-effective method for nitrate removal, so NZVI-N reducing nitrate has a great potential application in nitrate removal of groundwater. © 2012 Elsevier B.V.

A comparison of methods for classifying clinical samples based on proteomics data : a case study for statistical and machine learning approaches

The discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called “omics” disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems.

Jackknife for bias reduction in predictive regressions

One of the fundamental econometric models in finance is predictive regression. The standard least squares method produces biased coefficient estimates when the regressor is persistent and its innovations are correlated with those of the dependent variable. This article proposes a general and convenient method based on the jackknife technique to tackle the estimation problem. The proposed method reduces the bias for both single- and multiple-regressor models and for both short- and long-horizon regressions. The effectiveness of the proposed method is demonstrated by simulations. An empirical application to equity premium prediction using the dividend yield and the short rate highlights the differences between the results by the standard approach and those by the bias-reduced estimator. The significant predictive variables under the ordinary least squares become insignificant after adjusting for the finite-sample bias. These discrepancies suggest that bias reduction in predictive regressions is important in practical applications.

Photocatalytic reduction of carbon dioxide to formic acid, formaldehyde, and methanol using dye-sensitized TiO2 film

A bifunctionalized TiO2 film containing a dye-sensitized zone and a catalysis zone is designed for visible-light photocatalytic reduction of CO2 to chemicals continuously. Charge separation can be accomplished with electron transferring to catalysis zone and positive charge transforming to anode. Highly efficient conversion of CO2 to formic acid, formaldehyde, and methanol is achieved through the transferring electrons on conduction bands (CB) of TiO2. Reduction of CO2 and O2 evolution take place in separated solutions on different catalysts. The separated solution carried out in this photo-reactor system can avoid CO2 reduction products being oxidized by anode. The yields of reduction products were enhanced remarkably by external electrical power. This study provides not only a new photocatalytic system but also a potential of renewable energy source via carbon dioxide.

Reliability of partial ambiguity fixing with multiple GNSS constellations

Reliable ambiguity resolution (AR) is essential to Real-Time Kinematic (RTK) positioning and its applications, since incorrect ambiguity fixing can lead to largely biased positioning solutions. A partial ambiguity fixing technique is developed to improve the reliability of AR, involving partial ambiguity decorrelation (PAD) and partial ambiguity resolution (PAR). Decorrelation transformation could substantially amplify the biases in the phase measurements. The purpose of PAD is to find the optimum trade-off between decorrelation and worst-case bias amplification. The concept of PAR refers to the case where only a subset of the ambiguities can be fixed correctly to their integers in the integer least-squares (ILS) estimation system at high success rates. As a result, RTK solutions can be derived from these integer-fixed phase measurements. This is meaningful provided that the number of reliably resolved phase measurements is sufficiently large for least-square estimation of RTK solutions as well. Considering the GPS constellation alone, partially fixed measurements are often insufficient for positioning. The AR reliability is usually characterised by the AR success rate. In this contribution an AR validation decision matrix is firstly introduced to understand the impact of success rate. Moreover the AR risk probability is included into a more complete evaluation of the AR reliability. We use 16 ambiguity variance-covariance matrices with different levels of success rate to analyse the relation between success rate and AR risk probability. Next, the paper examines during the PAD process, how a bias in one measurement is propagated and amplified onto many others, leading to more than one wrong integer and to affect the success probability. Furthermore, the paper proposes a partial ambiguity fixing procedure with a predefined success rate criterion and ratio-test in the ambiguity validation process. In this paper, the Galileo constellation data is tested with simulated observations. Numerical results from our experiment clearly demonstrate that only when the computed success rate is very high, the AR validation can provide decisions about the correctness of AR which are close to real world, with both low AR risk and false alarm probabilities. The results also indicate that the PAR procedure can automatically chose adequate number of ambiguities to fix at given high-success rate from the multiple constellations instead of fixing all the ambiguities. This is a benefit that multiple GNSS constellations can offer.