An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Optimization of complex QoS-aware service compositions

In Service-oriented Architectures, business processes can be realized by composing loosely coupled services. The problem of QoS-aware service composition is widely recognized in the literature. Existing approaches on computing an optimal solution to this problem tackle structured business processes, i.e., business processes which are composed of XOR-block, AND-block, and repeat loop orchestration components. As of yet, OR-block and unstructured orchestration components have not been sufficiently considered in the context of QoS-aware service composition. The work at hand addresses this shortcoming. An approach for computing an optimal solution to the service composition problem is proposed considering the structured orchestration components, such as AND/XOR/OR-block and repeat loop, as well as unstructured orchestration components.

Characterisation of the micro-architecture of direct writing melt electrospun tissue engineering scaffolds using diffusion tensor and computed tomography microimaging

This article describes the first steps toward comprehensive characterization of molecular transport within scaffolds for tissue engineering. The scaffolds were fabricated using a novel melt electrospinning technique capable of constructing 3D lattices of layered polymer fibers with well - defined internal microarchitectures. The general morphology and structure order was then determined using T 2 - weighted magnetic resonance imaging and X - ray microcomputed tomography. Diffusion tensor microimaging was used to measure the time - dependent diffusivity and diffusion anisotropy within the scaffolds. The measured diffusion tensors were anisotropic and consistent with the cross - hatched geometry of the scaffolds: diffusion was least restricted in the direction perpendicular to the fiber layers. The results demonstrate that the cross - hatched scaffold structure preferentially promotes molecular transport vertically through the layers ( z - axis), with more restricted diffusion in the directions of the fiber layers ( x – y plane). Diffusivity in the x – y plane was observed to be invariant to the fiber thickness. The characteristic pore size of the fiber scaffolds can be probed by sampling the diffusion tensor at multiple diffusion times. Prospective application of diffusion tensor imaging for the real - time monitoring of tissue maturation and nutrient transport pathways within tissue engineering scaffolds is discussed.

Fred’s Flow (Canada) and Murphy Well (Australia) : thick komatiitic lava flows with contrasting compositions, emplacement mechanisms and water contents

Two Archaean komatiitic flows, Fred’s Flow in Canada and the Murphy Well Flow in Australia, have similar thicknesses (120 and 160 m) but very different compositions and internal structures. Their contrasting differentiation profiles are keys to determine the cooling and crystallization mechanisms that operated during the eruption of Archaean ultramafic lavas. Fred’s Flow is the type example of a thick komatiitic basalt flow. It is strongly differentiated and consists of a succession of layers with contrasting textures and compositions. The layering is readily explained by the accumulation of olivine and pyroxene in a lower cumulate layer and by evolution of the liquid composition during downward growth of spinifex-textured rocks within the upper crust. The magmas that erupted to form Fred’s Flow had variable compositions, ranging from 12 to 20 wt% MgO, and phenocryst contents from 0 to 20 vol%. The flow was emplaced by two pulses. A first ~20-m-thick pulse was followed by another more voluminous but less magnesian pulse that inflated the flow to its present 120 m thickness. Following the second pulse, the flow crystallized in a closed system and differentiated into cumulates containing 30–38 wt% MgO and a residual gabbroic layer with only 6 wt% MgO. The Murphy Well Flow, in contrast, has a remarkably uniform composition throughout. It comprises a 20-m-thick upper layer of fine-grained dendritic olivine and 2–5 vol% amygdales, a 110–120 m intermediate layer of olivine porphyry and a 20–30 m basal layer of olivine orthocumulate. Throughout the flow, MgO contents vary little, from only 30 to 33 wt%, except for the slightly more magnesian basal layer (38–40 wt%). The uniform composition of the flow and dendritic olivine habits in the upper 20 m point to rapid cooling of a highly magnesian liquid with a composition like that of the bulk of the flow. Under equilibrium conditions, this liquid should have crystallized olivine with the composition Fo94.9, but the most magnesian composition measured by electron microprobe in samples from the flow is Fo92.9. To explain these features, we propose that the parental liquid contained around 32 wt% MgO and 3 wt% H2O. This liquid degassed during the eruption, creating a supercooled liquid that solidified quickly and crystallized olivine with non-equilibrium textures and compositions.

A data mining based method for discovery of web services and their compositions

Due to the availability of huge number of web services, finding an appropriate Web service according to the requirements of a service consumer is still a challenge. Moreover, sometimes a single web service is unable to fully satisfy the requirements of the service consumer. In such cases, combinations of multiple inter-related web services can be utilised. This paper proposes a method that first utilises a semantic kernel model to find related services and then models these related Web services as nodes of a graph. An all-pair shortest-path algorithm is applied to find the best compositions of Web services that are semantically related to the service consumer requirement. The recommendation of individual and composite Web services composition for a service request is finally made. Empirical evaluation confirms that the proposed method significantly improves the accuracy of service discovery in comparison to traditional keyword-based discovery methods.

Improved fabrication of melt electrospun tissue engineering scaffolds using direct writing and advanced electric field control

Direct writing melt electrospinning is an additive manufacturing technique capable of the layer-by-layer fabrication of highly ordered 3d tissue engineering scaffolds from micron-diameter fibres. The utility of these scaffolds, however, is limited by the maximum achievable height of controlled fibre deposition, beyond which the structure becomes increasingly disordered. A source of this disorder is charge build-up on the deposited polymer producing unwanted coulombic forces. In this study we introduce a novel melt electrospinning platform with dual voltage power supplies to reduce undesirable charge effects and improve fibre deposition control. We produced and characterised several 90° cross-hatched fibre scaffolds using a range of needle/collector plate voltages. Fibre thickness was found to be sensitive only to overall potential and invariant to specific tip/collector voltage. We also produced ordered scaffolds up to 200 layers thick (fibre spacing 1 mm, diameter 40 μm) and characterised structure in terms of three distinct zones; ordered, semi-ordered and disordered. Our in vitro analysis indicates successful cell attachment and distribution throughout the scaffolds, with little evidence of cell death after seven days. This study demonstrates the importance of electrostatic control for reducing destabilising polymer charge effects and enabling the fabrication of morphologically suitable scaffolds for tissue engineering.

Melt electrospinning writing

This thesis has developed an innovative additive manufacturing technology platform, which combines melt electrospinning with direct writing, allowing the fabrication of a new class of highly-ordered ultrafine fibrous materials. Bioresorbable polymer fibres were printed using a variety of designs, with filament resolutions not demonstrated by established melt-extrusion based direct writing processes, to form novel medical devices. This platform was applied to tissue engineering scaffold design, where structures were prepared in a variety of shapes and forms, characterised and then seeded with cells to investigate their biocompatibility, cell-seeding and proliferation behaviour as well as the ability to guide cell growth and differentiation.

Influences of biodiesel chemical compositions and physical properties on engine exhaust particle emissions

This thesis presents a comprehensive study on the influences of biodiesel chemical composition and physical properties on diesel engine exhaust particle emissions. It examines biodiesels from several feedstocks having wide variations in their chemical composition (carbon chain length, unsaturation and oxygen content) and physical properties (density, viscosity, surface tension, boiling point etc.), and evaluates their influence on exhaust particle emissions. The outcome of this thesis is significant since it reveals the importance of regulating biodiesels chemical composition in order to ensure lowest possible emissions with better overall performance.

Meltdown : a tool to help in the interpretation of thermal melt curves acquired by differential scanning fluorimetry

The output of a differential scanning fluorimetry (DSF) assay is a series of melt curves, which need to be interpreted to get value from the assay. An application that translates raw thermal melt curve data into more easily assimilated knowledge is described. This program, called “Meltdown,” conducts four main activities—control checks, curve normalization, outlier rejection, and melt temperature (Tm) estimation—and performs optimally in the presence of triplicate (or higher) sample data. The final output is a report that summarizes the results of a DSF experiment. The goal of Meltdown is not to replace human analysis of the raw fluorescence data but to provide a meaningful and comprehensive interpretation of the data to make this useful experimental technique accessible to inexperienced users, as well as providing a starting point for detailed analyses by more experienced users.

High-temperature, low-H₂O silicic magmas of the Yellowstone Hotspot: an experimental study of Rhyolite from the Bruneau-Jarbidge eruptive center, Central Snake River Plain, USA

The phase relations have been investigated experimentally at 200 and 500 MPa as a function of water activity for one of the least evolved (Indian Batt Rhyolite) and of a more evolved rhyolite composition (Cougar Point Tuff XV) from the 12·8-8·1 Ma Bruneau-Jarbidge eruptive center of the Yellowstone hotspot. Particular priority was given to accurate determination of the water content of the quenched glasses using infrared spectroscopic techniques. Comparison of the composition of natural and experimentally synthesized phases confirms that high temperatures (>900°C) and extremely low melt water contents (<1·5 wt % H₂O) are required to reproduce the natural mineral assemblages. In melts containing 0·5-1·5 wt % H₂O, the liquidus phase is clinopyroxene (excluding Fe-Ti oxides, which are strongly dependent on fO₂), and the liquidus temperature of the more evolved Cougar Point Tuff sample (BJR; 940-1000°C) is at least 30°C lower than that of the Indian Batt Rhyolite lava sample (IBR2; 970-1030°C). For the composition BJR, the comparison of the compositions of the natural and experimental glasses indicates a pre-eruptive temperature of at least 900°C. The composition of clinopyroxene and pigeonite pairs can be reproduced only for water contents below 1·5 wt % H₂O at 900°C, or lower water contents if the temperature is higher. For the composition IBR2, a minimum temperature of 920°C is necessary to reproduce the main phases at 200 and 500 MPa. At 200 MPa, the pre-eruptive water content of the melt is constrained in the range 0·7-1·3 wt % at 950°C and 0·3-1·0 wt % at 1000°C. At 500 MPa, the pre-eruptive temperatures are slightly higher (by 30-50°C) for the same ranges of water concentration. The experimental results are used to explore possible proxies to constrain the depth of magma storage. The crystallization sequence of tectosilicates is strongly dependent on pressure between 200 and 500 MPa. In addition, the normative Qtz-Ab-Or contents of glasses quenched from melts coexisting with quartz, sanidine and plagioclase depend on pressure and melt water content, assuming that the normative Qtz and Ab/Or content of such melts is mainly dependent on pressure and water activity, respectively. The combination of results from the phase equilibria and from the composition of glasses indicates that the depth of magma storage for the IBR2 and BJR compositions may be in the range 300-400 MPa (13 km) and 200-300 MPa (10 km), respectively.

Towards adaptive management of QoS-aware service compositions - Functional architecture

Service compositions enable users to realize their complex needs as a single request. Despite intensive research, especially in the area of business processes, web services and grids, an open and valid question is still how to manage service compositions in order to satisfy both functional and non-functional requirements as well as adapt to dynamic changes. In this paper we propose an (functional) architecture for adaptive management of QoS-aware service compositions. Comparing to the other existing architectures this one offers two major advantages. Firstly, this architecture supports various execution strategies based on dynamic selection and negotiation of services included in a service composition, contracting based on service level agreements, service enactment with flexible support for exception handling, monitoring of service level objectives, and profiling of execution data. Secondly, the architecture is built on the basis of well know existing standards to communicate and exchange data, which significantly reduces effort to integrate existing solutions and tools from different vendors. A first prototype of this architecture has been implemented within an EU-funded Adaptive Service Grid project. © 2006 Springer-Verlag.

Comparison of stool microbiota compositions, stool alpha1-antitrypsin and calprotectin concentrations, and diarrhoeal morbidity of Indonesian infants fed breast milk or probiotic/prebiotic-supplemented formula

Aim The composition of faecal microbiota of babies is known to be influenced by diet. Faecal calprotectin and α1-antitrypsin concentrations may be associated with mucosal permeability and inflammation. We aimed to assess whether there was any difference after consumption of a probiotic/prebiotic formula on faecal microbiota composition, calprotectin and α1-antitrypsin levels, and diarrhoea in comparison with breast milk-fed Indonesian infants. Methods One hundred sixty infants, 2 to 6 weeks old, were recruited to the study. They were either breastfed or formula fed (80 per group). Faecal samples were collected at recruitment and 3 months later. Bacterial groups characteristic of the human faecal microbiota were quantified in faeces by quantitative polymerase chain reaction. Calprotectin and α1-antitrypsin concentrations were measured using commercial kits. Details of diarrhoeal morbidity were documented and rated for severity. Results The compositions of the faecal microbiota of formula-fed compared with breast milk-fed children were similar except that the probiotic strain Bifidobacterium animalis subsp. lactisâ€...DR10 was more abundant after 3 months consumption of the formula. Alpha1-antitrypsin levels were higher in breastfed compared with formula-fed infants. The occurrence of diarrhoea did not differ between the groups of babies. Conclusion Feeding Indonesian babies with a probiotic/prebiotic formula did not produce marked differences in the composition of the faecal microbiota in comparison with breast milk. Detrimental effects of formula feeding on biomarkers of mucosal health were not observed.

Melt electrospinning of poly(epsilon-caprolactone) scaffolds: Phenomenological observations associated with collection and direct writing

Melt electrospinning and its additive manufacturing analogue, melt electrospinning writing (MEW), are two processes which can produce porous materials for applications where solvent toxicity and accumulation in solution electrospinning are problematic. This study explores the melt electrospinning of poly(ε-caprolactone) (PCL) scaffolds, specifically for applications in tissue engineering. The research described here aims to inform researchers interested in melt electrospinning about technical aspects of the process. This includes rapid fiber characterization using glass microscope slides, allowing influential processing parameters on fiber morphology to be assessed, as well as observed fiber collection phenomena on different collector substrates. The distribution and alignment of melt electrospun PCL fibers can be controlled to a certain degree using patterned collectors to create large numbers of scaffolds with shaped macroporous architectures. However, the buildup of residual charge in the collected fibers limits the achievable thickness of the porous template through such scaffolds. One challenge identified for MEW is the ability to control charge buildup so that fibers can be placed accurately in close proximity, and in many centimeter heights. The scale and size of scaffolds produced using MEW, however, indicate that this emerging process will fill a technological niche in biofabrication.

A.c. conductivity studies on the silver molybdo-arsenate glassy system

A new quaternary fast-ion conducting silver molybdo-arsenate [Agl-Ag2O-(MoO3 + As2O5)] (SMA) glassy system has been prepared using the melt-quenching technique for various dopant salt (Agl) concentrations by fixing the formers (MoO3 + As2O5) composition and the modifier (Ag2O) to formers (M/F) ratio. The prepared compounds were characterized by X-ray diffraction. The impedance measurements were made on different Agl compositions of the SMA glasses as a function of frequency (6.5 Hz-65 kHz) and temperature (303-343 K), using the Solatron frequency-response analyser(model 1250). The bulk conductivity and the appropriate physical model (equivalent circuit) of the SMA glass were obtained from the impedance analysis. The a.c. conductivity was calculated for different Agl compositions of SMA glasses at various temperatures and the obtained a.c. conductivity results were analysed using Jonscher's Universal Law. The conduction mechanism for the highest conducting SMA glassy compound has been explained using the diffusion path model.