Effect of atmospheric ageing on volatility and ROS of biodiesel exhaust nano-particles

Generally, the magnitude of pollutant emissions from diesel engines is ultimately coupled to the structure of fuel molecules. The presence of oxygen, level of unsaturation and the carbon chain length of respective molecules influence the combustion chemistry. It is speculated that increased oxygen content in the fuel may lead to the increased oxidative potential (Stevanovic, S. 2013). Also, upon the exposure to UV and ozone in the atmosphere, the chemical composition of the exhaust is changed. The presence of an oxidant and UV is triggering the cascade of photochemical reactions as well as the partitioning of semi-volatile compounds between the gas and particle phase. To gain an insight into the relationship between the molecular structures of the esters, their volatile organic content and the potential toxicity of diesel exhaust particulate matter, measurements were conducted on a modern common rail diesel engine. This research also investigates the contribution of atmospheric conditions on the transfer of semi-volatile fraction of diesel exhaust from the gas phase to the particle phase and the extent to which semi-volatile compounds (SVOCs) are related to the oxidative potential, expressed through the concentration of reactive oxygen species (ROS) (Stevanovic, S. 2013)...

Simultaneous determination of aldrin, dieldrin, endrin, heptachlor, and p,p'-DDT in medicinal plant extracts using a novel high performance liquid chromatography method

A high performance liquid chromatographic method for the simultaneous determination of five organochlorine pesticides (aldrin, p,p’-DDT, dieldrin, endrin, and heptachlor) was developed. The method was used to determine the levels of these pesticides in medicinal plant samples. Analysis was carried out using a Merck LiChrospher 100 RP C18 (5 μm) column with a gradient solvent system of acetonitrile-water and PDA UV detection (224 nm). Quantification was carried out by the external standard method. The limit of detection for the utilized method was below the local legal limits (ANZFA) for similar plant materials for all 5 pesticides excepting endrin. Medicinal plant extracts were further analyzed by conventional GC-ECD and GC-NPD means using SPE and GPC cleanup as required.

Volatility timing : how best to forecast portfolio exposures

This paper investigates how best to forecast optimal portfolio weights in the context of a volatility timing strategy. It measures the economic value of a number of methods for forming optimal portfolios on the basis of realized volatility. These include the traditional econometric approach of forming portfolios from forecasts of the covariance matrix, and a novel method, where a time series of optimal portfolio weights are constructed from observed realized volatility and directly forecast. The approach proposed here of directly forecasting portfolio weights shows a great deal of merit. Resulting portfolios are of equivalent economic benefit to a number of competing approaches and are more stable across time. These findings have obvious implications for the manner in which volatility timing is undertaken in a portfolio allocation context.

Improved sub-cellular resolution via simultaneous analysis of organelle proteomics data across varied experimental conditions

Spatial organisation of proteins according to their function plays an important role in the specificity of their molecular interactions. Emerging proteomics methods seek to assign proteins to sub-cellular locations by partial separation of organelles and computational analysis of protein abundance distributions among partially separated fractions. Such methods permit simultaneous analysis of unpurified organelles and promise proteome-wide localisation in scenarios wherein perturbation may prompt dynamic re-distribution. Resolving organelles that display similar behavior during a protocol designed to provide partial enrichment represents a possible shortcoming. We employ the Localisation of Organelle Proteins by Isotope Tagging (LOPIT) organelle proteomics platform to demonstrate that combining information from distinct separations of the same material can improve organelle resolution and assignment of proteins to sub-cellular locations. Two previously published experiments, whose distinct gradients are alone unable to fully resolve six known protein-organelle groupings, are subjected to a rigorous analysis to assess protein-organelle association via a contemporary pattern recognition algorithm. Upon straightforward combination of single-gradient data, we observe significant improvement in protein-organelle association via both a non-linear support vector machine algorithm and partial least-squares discriminant analysis. The outcome yields suggestions for further improvements to present organelle proteomics platforms, and a robust analytical methodology via which to associate proteins with sub-cellular organelles.

Virus resistance and gene silencing in plants can be induced by simultaneous expression of sense and antisense RNA

Many examples of extreme virus resistance and posttranscriptional gene silencing of endogenous or reporter genes have been described in transgenic plants containing sense or antisense transgenes. In these cases of either cosuppression or antisense suppression, there appears to be induction of a surveillance system within the plant that specifically degrades both the transgene and target RNAs. We show that transforming plants with virus or reporter gene constructs that produce RNAs capable of duplex formation confer virus immunity or gene silencing on the plants. This was accomplished by using transcripts from one sense gene and one antisense gene colocated in the plant genome, a single transcript that has self-complementarity, or sense and antisense transcripts from genes brought together by crossing. A model is presented that is consistent with our data and those of other workers, describing the processes of induction and execution of posttranscriptional gene silencing.

Corneal confocal microscopy detects early nerve regeneration in diabetic neuropathy after simultaneous pancreas and kidney transplantation

Diabetic neuropathy is associated with increased morbidity and mortality. To date, limited data in subjects with impaired glucose tolerance and diabetes demonstrate nerve fiber repair after intervention. This may reflect a lack of efficacy of the interventions but may also reflect difficulty of the tests currently deployed to adequately assess nerve fiber repair, particularly in short-term studies. Corneal confocal microscopy (CCM) represents a novel noninvasive means to quantify nerve fiber damage and repair. Fifteen type 1 diabetic patients undergoing simultaneous pancreas-kidney transplantation (SPK) underwent detailed assessment of neurologic deficits, quantitative sensory testing (QST), electrophysiology, skin biopsy, corneal sensitivity, and CCM at baseline and at 6 and 12 months after successful SPK. At baseline, diabetic patients had a significant neuropathy compared with control subjects. After successful SPK there was no significant change in neurologic impairment, neurophysiology, QST, corneal sensitivity, and intraepidermal nerve fiber density (IENFD). However, CCM demonstrated significant improvements in corneal nerve fiber density, branch density, and length at 12 months. Normalization of glycemia after SPK shows no significant improvement in neuropathy assessed by the neurologic deficits, QST, electrophysiology, and IENFD. However, CCM shows a significant improvement in nerve morphology, providing a novel noninvasive means to establish early nerve repair that is missed by currently advocated assessment techniques.

Simultaneous estimation of hunting pressure, harvest and hunter success rates using WinBUGS

The use of hierarchical Bayesian spatial models in the analysis of ecological data is increasingly prevalent. The implementation of these models has been heretofore limited to specifically written software that required extensive programming knowledge to create. The advent of WinBUGS provides access to Bayesian hierarchical models for those without the programming expertise to create their own models and allows for the more rapid implementation of new models and data analysis. This facility is demonstrated here using data collected by the Missouri Department of Conservation for the Missouri Turkey Hunting Survey of 1996. Three models are considered, the first uses the collected data to estimate the success rate for individual hunters at the county level and incorporates a conditional autoregressive (CAR) spatial effect. The second model builds upon the first by simultaneously estimating the success rate and harvest at the county level, while the third estimates the success rate and hunting pressure at the county level. These models are discussed in detail as well as their implementation in WinBUGS and the issues arising therein. Future areas of application for WinBUGS and the latest developments in WinBUGS are discussed as well.

Terrorism risk, resilience and volatility : a comparison of terrorism patterns in three Southeast Asian countries

Objective This article explores patterns of terrorist activity over the period from 2000 through 2010 across three target countries: Indonesia, the Philippines and Thailand. Methods We use self-exciting point process models to create interpretable and replicable metrics for three key terrorism concepts: risk, resilience and volatility, as defined in the context of terrorist activity. Results Analysis of the data shows significant and important differences in the risk, volatility and resilience metrics over time across the three countries. For the three countries analysed, we show that risk varied on a scale from 0.005 to 1.61 “expected terrorist attacks per day”, volatility ranged from 0.820 to 0.994 “additional attacks caused by each attack”, and resilience, as measured by the number of days until risk subsides to a pre-attack level, ranged from 19 to 39 days. We find that of the three countries, Indonesia had the lowest average risk and volatility, and the highest level of resilience, indicative of the relatively sporadic nature of terrorist activity in Indonesia. The high terrorism risk and low resilience in the Philippines was a function of the more intense, less clustered pattern of terrorism than what was evident in Indonesia. Conclusions Mathematical models hold great promise for creating replicable, reliable and interpretable “metrics” to key terrorism concepts such as risk, resilience and volatility.

Marine aerosol hygroscopicity and volatility, measured on the Chatham Rise (New Zealand)

The Surface Ocean Aerosol Production (SOAP) study was undertaken in February/March 2012 in the biologically active waters of the Chatham Rise, NZ. Aerosol hygroscopicity and volatility were examined with a volatility hygroscopicity tandem differential mobility analyser. These observations confirm results from other hygroscopicity-based studies that the dominant fraction of the observed remote marine particles were non-sea salt sulfates. Further observations are required to clarify the influences of seawater composition, meteorology and analysis techniques seasonally across different ocean basins.

Selecting volatility forecasting models for portfolio allocation purposes

Techniques for evaluating and selecting multivariate volatility forecasts are not yet understood as well as their univariate counterparts. This paper considers the ability of different loss functions to discriminate between a set of competing forecasting models which are subsequently applied in a portfolio allocation context. It is found that a likelihood-based loss function outperforms its competitors, including those based on the given portfolio application. This result indicates that considering the particular application of forecasts is not necessarily the most effective basis on which to select models.

Simultaneous magnetic resonance imaging and consolidation measurement of articular cartilage

Magnetic resonance imaging (MRI) offers the opportunity to study biological tissues and processes in a non-disruptive manner. The technique shows promise for the study of the load-bearing performance (consolidation) of articular cartilage and changes in articular cartilage accompanying osteoarthritis. Consolidation of articular cartilage involves the recording of two transient characteristics: the change over time of strain and the hydrostatic excess pore pressure (HEPP). MRI study of cartilage consolidation under mechanical load is limited by difficulties in measuring the HEPP in the presence of the strong magnetic fields associated with the MRI technique. Here we describe the use of MRI to image and characterize bovine articular cartilage deforming under load in an MRI compatible consolidometer while monitoring pressure with a Fabry-Perot interferometer-based fiber-optic pressure transducer.

Simultaneous expression of the bacterial Dictyoglomus thermophilum xynB gene under three different Trichoderma reesei promoters

Multiple copies of expression cassettes driven by the Trichoderma reesei xylanase 2 (xyn2) and cellobiohydrolase 2 (cbh2) promoters were introduced into the recombinant T. reesei EC-21 generated to express a thermostable Dictyoglomus thermophilum xylanase (XynB) under the egl2 promoter for further improvement of the enzyme yield. The transformants were screened based on increased XynB activity only. Multiple promoter transformant MPP-4 expressing the xynB gene under all the three promoters was found to be the highest producer of XynB, giving a 65% increase in yield compared to the parental single-promoter recombinant EC-21. The multiple-promoter transformant strains harboured six to nine copies of the xynB gene. Amongst the three promoters, egl2 seemed to have the strongest effect on XynB expression. The shotgun approach we used proved to be effective for rapid enhancement of protein expression using three promoters active at the near-neutral pH of the cultivation medium.

Sequential versus simultaneous viewing of an environment : effects of focal attention to individual object locations on visual spatial learning

We investigated memories of room-sized spatial layouts learned by sequentially or simultaneously viewing objects from a stationary position. In three experiments, sequential viewing (one or two objects at a time) yielded subsequent memory performance that was equivalent or superior to simultaneous viewing of all objects, even though sequential viewing lacked direct access to the entire layout. This finding was replicated by replacing sequential viewing with directed viewing in which all objects were presented simultaneously and participants’ attention was externally focused on each object sequentially, indicating that the advantage of sequential viewing over simultaneous viewing may have originated from focal attention to individual object locations. These results suggest that memory representation of object-to-object relations can be constructed efficiently by encoding each object location separately, when those locations are defined within a single spatial reference system. These findings highlight the importance of considering object presentation procedures when studying spatial learning mechanisms.

Rapid, simultaneous activation of thin nanowire growth in low-temperature, low-pressure chemically active plasmas

Multiscale numerical modeling of the species balance and transport in the ionized gas phase and on the nanostructured solid surface complemented by the heat exchange model is used to demonstrate the possibility of minimizing the Gibbs-Thompson effect in low-temperature, low-pressure chemically active plasma-assisted growth of uniform arrays of very thin Si nanowires, impossible otherwise. It is shown that plasma-specific effects drastically shorten and decrease the dispersion of the incubation times for the nucleation of nanowires on non-uniform Au catalyst nanoparticle arrays. The fast nucleation makes it possible to avoid a common problem of small catalyst nanoparticle burying by amorphous silicon. These results explain a multitude of experimental observations on chemically active plasma-assisted Si nanowire growth and can be used for the synthesis of a range of inorganic nanowires for environmental, biomedical, energy conversion, and optoelectronic applications.

Plasma/ion-controlled metal catalyst saturation : enabling simultaneous growth of carbon nanotube/nanocone arrays

It is shown that the simultaneous saturation of Ni nanoparticles used as catalyst for vertically aligned carbon nanotube and nanocone arrays can be improved in low-temperature plasma- or ion-assisted processes compared with neutral gas-based routes. The results of hybrid multiscale numerical simulations of the catalyst nanoarrays (particle sizes of 2 and 10 nm) saturation with carbon show the possibility of reducing the difference in catalyst incubation times for smallest and largest catalyst particles by up to a factor of 2. This approach is generic and provides process conditions for simultaneous nucleation and growth of uniform arrays of vertically aligned nanostructures. © 2008 American Institute of Physics.