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)...

An effort towards understanding the sources of impurities in generating nanoparticles via liquid-phase methods

Generating nano-sized materials of a controlled size and chemical composition is essential for the manufacturing of materials with enhanced properties on an industrial scale, as well as for research purposes, such as toxicological studies. Among the generation methods for airborne nanoparticles (also known as aerosolisation methods), liquid-phase techniques have been widely applied due to the simplicity of their use and their high particle production rate. The use of a collison nebulizer is one such technique, in which the atomisation takes place as a result of the liquid being sucked into the air stream and injected toward the inner walls of the nebulizer reservoir via nozzles, before the solution is dispersed. Despite the above-mentioned benefits, this method also falls victim to various sources of impurities (Knight and Petrucci 2003; W. LaFranchi, Knight et al. 2003). Since these impurities can affect the characterization of the generated nanoparticles, it is crucial to understand and minimize their effect.

Validating SMPS-measured size distribution of double-mode spherical Silica nanoparticles by Transmission Electron Microscope (TEM)

A nanoparticles size is one of their key physical characteristics that can affect their fate in a human’s respiratory tract (in case of inhalation) and also in the environment. Hence, measuring the size distribution of nanoparticles is absolutely essential and contributes greatly to their characterization. For years, Scanning Mobility Particle Sizers (SMPS), which rely on measuring the electrical mobility diameter of particles, have been used as one of the most reliable real-time instruments for the size distribution measurement of nanoparticles. Despite its benefits, this instrument has some drawbacks, including equivalency problems for non-spherical particles (i.e. assuming a non-spherical particle is equal to a spherical particle of diameter d due to the same electrical mobility), as well as limitations in terms of its use in workplaces, because of its large size and the complexity of its operation...

Alveolar dose of ultrafine particles for children in urban environments

The aim of this study was to quantify school children’s exposure to ultrafine particles (UFP) in urban environments. The study was conducted as part of a larger epidemiological project aiming to determine the association between exposures to UFPs and children’s health, titled “Ultrafine Particles from Traffic Emissions and Children’s Health”1 (UPTECH). School children aged 8-11 years old at 24 state schools within the Brisbane Metropolitan Area participated in the present study. This paper presents the methodology and results for calculating deposited UFP surface area in the alveolar region (dose), where UFP deposition is more efficient for particles larger than 6 nm...

Biodiesel with controlled physicochemical properties, a means to further reduce diesel engine particle emissions

The issue of particle emissions from diesel engines is still a matter of concern due its deleterious effects both on human health and environment(Ristovski et al., 2012). Recently, International Agency for Research on Cancer (IARC) inclusion of diesel engine exhaust particles as carcinogenic to human health added a new margin on it. Apart from the use of after treatment technology, biodiesel is also considered as potential way to reduce particle emission alongside with other emissions(Xue, Grift, & Hansen, 2011). Global biodiesel production is still reasonably small compared to its counterpart fossil diesel, but even this small amount comes from a wide variety of feed stocks. Contrary to fossil diesel, the important physicochemical properties of biodiesel vary among different feed stocks(Hoekman, Broch, Robbins, Ceniceros, & Natarajan, 2012).

Metrological performances of a diffusion charger particle counter for personal monitoring

Airborne particles have been shown to be associated with a wide range of adverse health effects, which has led to a recent increase in medical research to gain better insight into their health effects. However, accurate evaluation of the exposure-dose-response relationship is highly dependent on the ability to track actual exposure levels of people to airborne particles. This is quite a complex task, particularly in relation to submicrometer and ultrafine particles, which can vary quite significantly in terms of particle surface area and number concentrations. Therefore, suitable monitors that can be worn for measuring personal exposure to these particles are needed. This paper presents an evaluation of the metrological performance of six diffusion charger sensors, NanoTracer (Philips Aerasense) monitors, when measuring particle number and surface area concentrations, as well as particle number distribution mean when compared to reference instruments. Tests in the laboratory (by generating monodisperse and polydisperse aerosols) and in the field (using natural ambient particles) were designed to evaluate the response of these devices under both steady-state and dynamics conditions. Results showed that the NanoTracers performed well when measuring steady state aerosols, however they strongly underestimated actual concentrations during dynamic response testing. The field experiments also showed that, when the majority of the particles were smaller than 20 nm, which occurs during particle formation events in the atmosphere, the NanoTracer underestimated number concentration quite significantly. Even though the NanoTracer can be used for personal monitoring of exposure to ultrafine particles, it also has limitations which need to be considered in order to provide meaningful results.

Non-linear position control for hover and automatic landing of unmanned aerial vehicles

This study presents a disturbance attenuation controller for horizontal position stabilisation for hover and automatic landings of a rotary-wing unmanned aerial vehicle (RUAV) operating close to the landing deck in rough seas. Based on a helicopter model representing aerodynamics during the landing phase, a non-linear state feedback H∞ controller is designed to achieve rapid horizontal position tracking in a gusty environment. Practical constraints including flapping dynamics, servo dynamics and time lag effect are considered. A high-fidelity closed-loop simulation using parameters of the Vario XLC gas-turbine helicopter verifies performance of the proposed horizontal position controller. The proposed controller not only increases the disturbance attenuation capability of the RUAV, but also enables rapid position response when gusts occur. Comparative studies show that the H∞ controller exhibits performance improvement and can be applied to ship/RUAV landing systems.

Integrating collaborative filtering and matching-based search for product recommendations

Currently, recommender systems (RS) have been widely applied in many commercial e-commerce sites to help users deal with the information overload problem. Recommender systems provide personalized recommendations to users and, thus, help in making good decisions about which product to buy from the vast amount of product choices. Many of the current recommender systems are developed for simple and frequently purchased products like books and videos, by using collaborative-filtering and content-based approaches. These approaches are not directly applicable for recommending infrequently purchased products such as cars and houses as it is difficult to collect a large number of ratings data from users for such products. Many of the ecommerce sites for infrequently purchased products are still using basic search-based techniques whereby the products that match with the attributes given in the target user’s query are retrieved and recommended. However, search-based recommenders cannot provide personalized recommendations. For different users, the recommendations will be the same if they provide the same query regardless of any difference in their interest. In this article, a simple user profiling approach is proposed to generate user’s preferences to product attributes (i.e., user profiles) based on user product click stream data. The user profiles can be used to find similarminded users (i.e., neighbours) accurately. Two recommendation approaches are proposed, namely Round- Robin fusion algorithm (CFRRobin) and Collaborative Filtering-based Aggregated Query algorithm (CFAgQuery), to generate personalized recommendations based on the user profiles. Instead of using the target user’s query to search for products as normal search based systems do, the CFRRobin technique uses the attributes of the products in which the target user’s neighbours have shown interest as queries to retrieve relevant products, and then recommends to the target user a list of products by merging and ranking the returned products using the Round Robin method. The CFAgQuery technique uses the attributes of the products that the user’s neighbours have shown interest in to derive an aggregated query, which is then used to retrieve products to recommend to the target user. Experiments conducted on a real e-commerce dataset show that both the proposed techniques CFRRobin and CFAgQuery perform better than the standard Collaborative Filtering and the Basic Search approaches, which are widely applied by the current e-commerce applications.

Robots for environmental monitoring : significant advancements and applications

Robotic systems are increasingly being utilised as fundamental data-gathering tools by scientists, allowing new perspectives and a greater understanding of the planet and its environmental processes. Today's robots are already exploring our deep oceans, tracking harmful algal blooms and pollution spread, monitoring climate variables, and even studying remote volcanoes. This article collates and discusses the significant advancements and applications of marine, terrestrial, and airborne robotic systems developed for environmental monitoring during the last two decades. Emerging research trends for achieving large-scale environmental monitoring are also reviewed, including cooperative robotic teams, robot and wireless sensor network (WSN) interaction, adaptive sampling and model-aided path planning. These trends offer efficient and precise measurement of environmental processes at unprecedented scales that will push the frontiers of robotic and natural sciences.

Fabrication and in vitro characterisation of bioactive glass composite scaffolds for bone regeneration

Here we fabricate and characterise bioactive composite scaffolds for bone tissue engineering applications. 45S5 Bioglass® (45S5) or strontium-substituted bioactive glass (SrBG) were incorporated into polycaprolactone (PCL) and fabricated into 3D bioactive composite scaffolds utilising additive manufacturing technology. We show that composite scaffolds (PCL/45S5 and PCL/SrBG) can be reproducibly manufactured with a scaffold morphology highly resembling that of PCL scaffolds. Additionally, micro-CT analysis reveals BG particles were homogeneously distributed throughout the scaffolds. Mechanical data suggested that PCL/45S5 and PCL/SrBG composite scaffolds have higher compressive Young’s modulus compared to PCL scaffolds at similar porosity (~75%). After 1 day in accelerated degradation conditions using 5M NaOH, PCL/SrBG, PCL/45S5 and PCL lost 48.6 ±3.8%, 12.1 ±1% and 1.6 ±1% of its original mass, respectively. In vitro studies were conducted using MC3T3 cells under normal and osteogenic conditions. All scaffolds were shown to be non-cytotoxic, and supported cell attachment and proliferation. Our results also indicate that the inclusion of bioactive glass (BG) promotes precipitation of calcium phosphate on the scaffold surfaces which leads to earlier cell differentiation and matrix mineralisation when compared to PCL scaffolds. However, as indicated by ALP activity, no significant difference in osteoblast differentiation was found between PCL/45S5 and PCL/SrBG scaffolds. These results suggest that PCL/45S5 and PCL/SrBG composite scaffold shows potential as a next generation bone scaffold.

Melt-electrospun polycaprolactone-strontium substituted bioactive glass scaffolds for bone regeneration

Polycaprolactone (PCL) is a resorbable polymer used extensively in bone tissue engineering owing to good structural properties and processability. Strontium substituted bioactive glass (SrBG) has the ability to promote osteogenesis and may be incorporated into scaffolds intended for bone repair. Here we describe for the first time, the development of a PCL-SrBG composite scaffold incorporating 10% (weight) of SrBG particles into PCL bulk, produced by the technique of melt-electrospinning. We show that we are able to reproducibly manufacture composite scaffolds with an interconnected porous structure and, furthermore, these scaffolds were demonstrated to be non-cytotoxic in vitro. Ions present in the SrBG component were shown to dissolve into cell culture media and promoted precipitation of a calcium phosphate layer on the scaffold surface which in turn led to noticeably enhanced alkaline phosphatase activity in MC3T3-E1 cells compared to PLC-only scaffolds. These results suggest that melt-electrospun PCL-SrBG composite scaffolds show potential to become effective bone graft substitutes.

A concept-based retrieval method for entity-oriented search

Entity-oriented retrieval aims to return a list of relevant entities rather than documents to provide exact answers for user queries. The nature of entity-oriented retrieval requires identifying the semantic intent of user queries, i.e., understanding the semantic role of query terms and determining the semantic categories which indicate the class of target entities. Existing methods are not able to exploit the semantic intent by capturing the semantic relationship between terms in a query and in a document that contains entity related information. To improve the understanding of the semantic intent of user queries, we propose concept-based retrieval method that not only automatically identifies the semantic intent of user queries, i.e., Intent Type and Intent Modifier but introduces concepts represented by Wikipedia articles to user queries. We evaluate our proposed method on entity profile documents annotated by concepts from Wikipedia category and list structure. Empirical analysis reveals that the proposed method outperforms several state-of-the-art approaches.

Scene invariant multi camera crowd counting

Automated crowd counting has become an active field of computer vision research in recent years. Existing approaches are scene-specific, as they are designed to operate in the single camera viewpoint that was used to train the system. Real world camera networks often span multiple viewpoints within a facility, including many regions of overlap. This paper proposes a novel scene invariant crowd counting algorithm that is designed to operate across multiple cameras. The approach uses camera calibration to normalise features between viewpoints and to compensate for regions of overlap. This compensation is performed by constructing an 'overlap map' which provides a measure of how much an object at one location is visible within other viewpoints. An investigation into the suitability of various feature types and regression models for scene invariant crowd counting is also conducted. The features investigated include object size, shape, edges and keypoints. The regression models evaluated include neural networks, K-nearest neighbours, linear and Gaussian process regresion. Our experiments demonstrate that accurate crowd counting was achieved across seven benchmark datasets, with optimal performance observed when all features were used and when Gaussian process regression was used. The combination of scene invariance and multi camera crowd counting is evaluated by training the system on footage obtained from the QUT camera network and testing it on three cameras from the PETS 2009 database. Highly accurate crowd counting was observed with a mean relative error of less than 10%. Our approach enables a pre-trained system to be deployed on a new environment without any additional training, bringing the field one step closer toward a 'plug and play' system.

Rank minimization across appearance and shape for AAM ensemble fitting

Active Appearance Models (AAMs) employ a paradigm of inverting a synthesis model of how an object can vary in terms of shape and appearance. As a result, the ability of AAMs to register an unseen object image is intrinsically linked to two factors. First, how well the synthesis model can reconstruct the object image. Second, the degrees of freedom in the model. Fewer degrees of freedom yield a higher likelihood of good fitting performance. In this paper we look at how these seemingly contrasting factors can complement one another for the problem of AAM fitting of an ensemble of images stemming from a constrained set (e.g. an ensemble of face images of the same person).

Perspectives in multiphasic osteochondral tissue engineering

Critical-sized osteochondral defects are clinically challenging, with limited treatment options available. By engineering osteochondral grafts using a patient's own cells and osteochondral scaffolds designed to facilitate cartilage and bone regeneration, osteochondral defects may be treated with less complications and better long-term clinical outcomes. Scaffolds can influence the development and structure of the engineered tissue, and there is an increased awareness that osteochondral tissue engineering concepts need to take the in vivo complexities into account in order to increase the likelihood of successful osteochondral tissue repair. The developing trend in osteochondral tissue engineering is the utilization of multiphasic scaffolds to recapitulate the multiphasic nature of the native tissue. Cartilage and bone have different structural, mechanical, and biochemical microenvironments. By designing osteochondral scaffolds with tissue-specific architecture, it may be possible to enhance osteochondral repair within shorter timeframe. While there are promising in vivo outcomes using multiphasic approaches, functional regeneration of osteochondral constructs still remains a challenge. In this review, we provide an overview of in vivo osteochondral repair studies that have taken place in the past three years, and define areas which needs improvement in future studies