Stability studies of HIV-1 Pr55gag virus-like particles made in insect cells after storage in various formulation media

Background: HIV-1 Pr55gag virus-like particles (VLPs) expressed by baculovirus in insect cells are considered to be a very promising HIV-1 vaccine candidate, as they have been shown to elicit broad cellular immune responses when tested in animals, particularly when used as a boost to DNA or BCG vaccines. However, it is important for the VLPs to retain their structure for them to be fully functional and effective. The medium in which the VLPs are formulated and the temperature at which they are stored are two important factors affecting their stability. FINDINGS We describe the screening of 3 different readily available formulation media (sorbitol, sucrose and trehalose) for their ability to stabilise HIV-1 Pr55gag VLPs during prolonged storage. Transmission electron microscopy (TEM) was done on VLPs stored at two different concentrations of the media at three different temperatures (4[degree sign]C, --20[degree sign]C and -70[degree sign]C) over different time periods, and the appearance of the VLPs was compared. VLPs stored in 15% trehalose at -70[degree sign]C retained their original appearance the most effectively over a period of 12 months. VLPs stored in 5% trehalose, sorbitol or sucrose were not all intact even after 1 month storage at the temperatures tested. In addition, we showed that VLPs stored under these conditions were able to be frozen and re-thawed twice before showing changes in their appearance. Conclusions Although the inclusion of other analytical tools are essential to validate these preliminary findings, storage in 15% trehalose at -70[degree sign]C for 12 months is most effective in retaining VLP stability.

Sources of hydrochemical variability and implications associated with CSG water extraction

Coal Seam Gas (CSG) production is achieved by extracting groundwater to depressurize coal seam aquifers in order to promote methane gas desorption from coal micropores. CSG waters are characteristically alkaline, have a neutral pH (~7), are of the Na-HCO3-Cl type, and exhibit brackish salinity. In 2004, a CSG exploration company carried out a gas flow test in an exploration well located in Maramarua (Waikato Region, New Zealand). This resulted in 33 water samples exhibiting noteworthy chemical variations induced by pumping. This research identifies the main causes of hydrochemical variations in CSG water, makes recommendations to manage this effect, and discusses potential environmental implications. Hydrochemical variations were studied using Factor Analysis and this was supported with hydrochemical modelling and a laboratory experiment. This reveals carbon dioxide (CO2) degassing as the principal source of hydrochemical variability (about 33%). Factor Analysis also shows that major ion variations could also reflect changes in hydrochemical composition induced by different pumping regimes. Subsequent chloride, calcium, and TDS variations could be a consequence of analytical errors potentially committed during laboratory determinations. CSG water chemical variations due to degassing during pumping can be minimized with good completion and production techniques; variations due to sample degassing can be controlled by taking precautions during sampling, transit, storage and analysis. In addition, the degassing effect observed in CSG waters can lead to an underestimation of their potential environmental effect. Calcium precipitation due to exposure to normal atmospheric pressure results in a 23% increase in SAR values from Maramarua CSG water samples.

A multivariate approach to the identification of surrogate parameters for heavy metals in stormwater

Stormwater is a potential and readily available alternative source for potable water in urban areas. However, its direct use is severely constrained by the presence of toxic pollutants, such as heavy metals (HMs). The presence of HMs in stormwater is of concern because of their chronic toxicity and persistent nature. In addition to human health impacts, metals can contribute to adverse ecosystem health impact on receiving waters. Therefore, the ability to predict the levels of HMs in stormwater is crucial for monitoring stormwater quality and for the design of effective treatment systems. Unfortunately, the current laboratory methods for determining HM concentrations are resource intensive and time consuming. In this paper, applications of multivariate data analysis techniques are presented to identify potential surrogate parameters which can be used to determine HM concentrations in stormwater. Accordingly, partial least squares was applied to identify a suite of physicochemical parameters which can serve as indicators of HMs. Datasets having varied characteristics, such as land use and particle size distribution of solids, were analyzed to validate the efficacy of the influencing parameters. Iron, manganese, total organic carbon, and inorganic carbon were identified as the predominant parameters that correlate with the HM concentrations. The practical extension of the study outcomes to urban stormwater management is also discussed.

Atmospheric deposition as a source of heavy metals in urban stormwater

Atmospheric deposition is one of the most important pathways of urban stormwater pollution. Atmospheric deposition which can be in the form of either wet or dry deposition have distinct characteristics in terms of associated particulate sizes, pollutant types and influential parameters. This paper discusses the outcomes of a comprehensive research study undertaken to identify important traffic characteristics and climate factors such as antecedent dry period and rainfall characteristics which influences the characteristics of wet and dry deposition of solids and heavy metals. The outcomes confirmed that Zinc (Zn) is correlated with traffic volume whereas Lead (Pb), Cadmium (Cd), Nickel (Ni), and Copper (Cu) are correlated with traffic congestion. Consequently, reducing traffic congestion will be more effective than reducing traffic volume for improving air quality particularly in relation to Pb, Cd, Ni, and Cu. Zn was found to have the highest atmospheric deposition rate compared to other heavy metals. Zn in dry deposition is associated with relatively larger particle size fractions (>10 µm), whereas Pb, Cd, Ni and Cu are associated with relatively smaller particle size fractions (<10 µm). The analysis further revealed that bulk (wet plus dry) deposition which is correlated with rainfall depth and contains a relatively higher percentage of smaller particles compared to dry deposition which is correlated with the antecedent dry period. As particles subjected to wet deposition are smaller, they disperse over a larger area from the source of origin compared to particles subjected to dry deposition as buoyancy forces become dominant for smaller particles compared to the influence of gravity. Furthermore, exhaust emission particles were found to be primarily associated with bulk deposition compared to dry deposition particles which mainly originate from vehicle component wear.

A non-linear dynamic analysis of heavy haul track line sleepers under wheel flat

Significant wheel-rail dynamic forces occur because of imperfections in the wheels and/or rail. One of the key responses to the transmission of these forces down through the track is impact force on the sleepers. Dynamic analysis of nonlinear systems is very complicated and does not lend itself easily to a classical solution of multiple equations. Trying to deduce the behaviour of track components from experimental data is very difficult because such data is hard to obtain and applies to only the particular conditions of the track being tested. The finite element method can be the best solution to this dilemma. This paper describes a finite element model using the software package ANSYS for various sized flat defects in the tread of a wheel rolling at a typical speed on heavy haul track. The paper explores the dynamic response of a prestressed concrete sleeper to these defects.

Craving as a predictor of treatment outcomes in heavy drinkers with comorbid depressed mood

Alcohol and depression comorbidity is high and is associated with poorer outcomes following treatment. The ability to predict likely treatment response would be advantageous for treatment planning. Craving has been widely studied as a potential predictor, but has performed inconsistently. The effect of comorbid depression on craving's predictive performance however, has been largely neglected, despite demonstrated associations between negative affect and craving. The current study examined the performance of craving, measured pretreatment using the Obsessive subscale of the Obsessive Compulsive Drinking Scale, in predicting 18-week and 12-month post-treatment alcohol use outcomes in a sample of depressed drinkers. Data for the current study were collected during a randomized controlled trial (Baker, Kavanagh, Kay-Lambkin, Hunt, Lewin, Carr, & Connolly, 2010) comparing treatments for comorbid alcohol and depression. A subset of 260 participants from that trial with a Timeline Followback measure of alcohol consumption was analyzed. Pre-treatment craving was a significant predictor of average weekly alcohol consumption at 18 weeks and of frequency of alcohol binges at 18 weeks and 12months, but pre-treatment depressive mood was not predictive, and effects of Baseline craving were independent of depressive mood. Results suggest a greater ongoing risk from craving than from depressive mood at Baseline.

Simulation of phosphine flow in vertical grain storage : a preliminary numerical study

To fumigate grain stored in a silo, phosphine gas is distributed by a combination of diffusion and fan-forced advection. This initial study of the problem mainly focuses on the advection, numerically modelled as fluid flow in a porous medium. We find satisfactory agreement between the flow predictions of two Computational Fluid Dynamics packages, Comsol and Fluent. The flow predictions demonstrate that the highest velocity (>0.1 m/s) occurs less than 0.2m from the inlet and reduces drastically over one metre of silo height, with the flow elsewhere less than 0.002 m/s or 1% of the velocity injection. The flow predictions are examined to identify silo regions where phosphine dosage levels are likely to be too low for effective grain fumigation.

Heavy Weather

Heavy Weather was a monumental sculptural work produced for the prestigious McClelland National Sculpture Survey in 2012. The work was a large cold-cast aluminium figure depicting the artist in athletic costume arching backwards across the top of massive boulder. The pose of the figure was derived from the ‘Fosbury flop’, the awkward backwards manoeuvre associated with high-jump event. The boulder was a portrait of a different kind - a remake of the Ian Fairweather memorial on Bribie Island but elongated to tower upwards. The work thus emphasised two contrasting impressions of movement – immense inertia and writhing agility. Heavy Weather sought to bring these two opposing forces together as a way of representing the tensions that shape our relationship with objects. In so doing, the work contributed to the artist’s ongoing exploration of sculpture, self-portraiture and the civic monument. The work was promoted nationally including the Art Guide and the Melbourne Review. It was also the subject of a article in the Australian Art Collector.

Advanced battery storage control for an autonomous microgrid

A new control method for battery storage to maintain acceptable voltage profile in autonomous microgrids is proposed in this article. The proposed battery control ensures that the bus voltages in the microgrid are maintained during disturbances such as load change, loss of micro-sources, or distributed generations hitting power limit. Unlike the conventional storage control based on local measurements, the proposed method is based on an advanced control technique, where the reference power is determined based on the voltage drop profile at the battery bus. An artificial neural network based controller is used to determine the reference power needed for the battery to hold the microgrid voltage within regulation limits. The pattern of drop in the local bus voltage during power imbalance is used to train the controller off-line. During normal operation, the battery floats with the local bus voltage without any power injection. The battery is charged or discharged during the transients with a high gain feedback loop. Depending on the rate of voltage fall, it is switched to power control mode to inject the reference power determined by the proposed controller. After a defined time period, the battery power injection is reduced to zero using slow reverse-droop characteristics, ensuring a slow rate of increase in power demand from the other distributed generations. The proposed control method is simulated for various operating conditions in a microgrid with both inertial and converter interfaced sources. The proposed battery control provides a quick load pick up and smooth load sharing with the other micro-sources in a disturbance. With various disturbances, maximum voltage drop over 8% with conventional energy storage is reduced within 2.5% with the proposed control method.

Transmission system expansion planning considering combined operation of wind farms and energy storage systems

An energy storage system (ESS) can provide ancillary services such as frequency regulation and reserves, as well as smooth the fluctuations of wind power outputs, and hence improve the security and economics of the power system concerned. The combined operation of a wind farm and an ESS has become a widely accepted operating mode. Hence, it appears necessary to consider this operating mode in transmission system expansion planning, and this is an issue to be systematically addressed in this work. Firstly, the relationship between the cost of the NaS based ESS and its discharging cycle life is analyzed. A strategy for the combined operation of a wind farm and an ESS is next presented, so as to have a good compromise between the operating cost of the ESS and the smoothing effect of the fluctuation of wind power outputs. Then, a transmission system expansion planning model is developed with the sum of the transmission investment costs, the investment and operating costs of ESSs and the punishment cost of lost wind energy as the objective function to be minimized. An improved particle swarm optimization algorithm is employed to solve the developed planning model. Finally, the essential features of the developed model and adopted algorithm are demonstrated by 18-bus and 46-bus test systems.

Ion transport in small-molecule electrolytes based on LiI/3-hydroxypropionitrile with high salt contents

Abnormal “polymer-in-salt” conduction behavior is observed in a solid electrolyte composed of lithium iodide (LiI) and 3-hydroxypropionitrile (HPN). Based on comprehensive investigations by X-ray diffraction (XRD) and Raman and infrared spectroscopy, this abnormal conduction behavior is attributed to the formation of new ionic associates [Lim +In−]· · ·N C (m> n) and the reinforced hydrogen bonding of I· · ·HO in the electrolyte at high LiI concentrations.