An algebraic approach for determination of DG parameters to support voltage profiles in radial distribution networks

Rapidly increasing electricity demands and capacity shortage of transmission and distribution facilities are the main driving forces for the growth of Distributed Generation (DG) integration in power grids. One of the reasons for choosing a DG is its ability to support voltage in a distribution system. Selection of effective DG characteristics and DG parameters is a significant concern of distribution system planners to obtain maximum potential benefits from the DG unit. This paper addresses the issue of improving the network voltage profile in distribution systems by installing a DG of the most suitable size, at a suitable location. An analytical approach is developed based on algebraic equations for uniformly distributed loads to determine the optimal operation, size and location of the DG in order to achieve required levels of network voltage. The developed method is simple to use for conceptual design and analysis of distribution system expansion with a DG and suitable for a quick estimation of DG parameters (such as optimal operating angle, size and location of a DG system) in a radial network. A practical network is used to verify the proposed technique and test results are presented.

Hybrid genetic algorithm for elimination of severe stress concentration in railhead ends

This paper presents a computational method for eliminating severe stress concentration at the unsupported railhead ends in rail joints through innovative shape optimization of the contact zone, which is complex due to near field nonlinear contact. With a view to minimizing the computational efforts, hybrid genetic algorithm method coupled with parametric finite element has been developed and compared with the traditional genetic algorithm (GA). The shape of railhead top surface where the wheel contacts nonlinearly was optimized using the hybridized GA method. Comparative study of the optimal result and the search efficiency between the traditional and hybrid GA methods has shown that the hybridized GA provides the optimal shape in fewer computational cycles without losing accuracy. The method will be beneficial to solving complex engineering problems involving contact nonlinearity.

Small angle X-ray scattering mapping and kinetics study of sub-critical CO2 sorption by two Australian coals

Time- and position-resolved synchrotron small angle X-ray scattering data were acquired from samples of two Australian coal seams: Bulli seam (Bulli 4, Ro=1.42%, Sydney Basin), which naturally contains CO2 and Baralaba seam (Ro=0.67%, Bowen Basin), a potential candidate for sequestering CO2. This experimental approach has provided unique, pore-size-specific insights into the kinetics of CO2 sorption in the micro- and small mesopores (diameter 5 to 175 Å) and the density of the sorbed CO2 at reservoir-like conditions of temperature and hydrostatic pressure. For both samples, at pressures above 5 bar, the density of CO2 confined in pores was found to be uniform, with no densification in near-wall regions. In the Bulli 4 sample, CO2 first flooded the slit pores between polyaromatic sheets. In the pore-size range analysed, the confined CO2 density was close to that of the free CO2. The kinetics data are too noisy for reliable quantitative analysis, but qualitatively indicate faster kinetics in mineral-matter-rich regions. In the Baralaba sample, CO2 preferentially invaded the smallest micropores and the confined CO2 density was up to five times that of the free CO2. Faster CO2 sorption kinetics was found to be correlated with higher mineral matter content but, the mineral-matter-rich regions had lower-density CO2 confined in their pores. Remarkably, the kinetics was pore-size dependent, being faster for smaller pores. These results suggest that injection into the permeable section of an interbedded coal-clastic sequence could provide a viable combination of reasonable injectivity and high sorption capacity.

Process compliance measurement based on behavioural profiles

Process compliance measurement is getting increasing attention in companies due to stricter legal requirements and market pressure for operational excellence. On the other hand, the metrics to quantify process compliance have only been defined recently. A major criticism points to the fact that existing measures appear to be unintuitive. In this paper, we trace back this problem to a more foundational question: which notion of behavioural equivalence is appropriate for discussing compliance? We present a quantification approach based on behavioural profiles, which is a process abstraction mechanism. Behavioural profiles can be regarded as weaker than existing equivalence notions like trace equivalence, and they can be calculated efficiently. As a validation, we present a respective implementation that measures compliance of logs against a normative process model. This implementation is being evaluated in a case study with an international service provider.

Process compliance analysis based on behavioural profiles

Process compliance measurement is getting increasing attention in companies due to stricter legal requirements and market pressure for operational excellence. In order to judge on compliance of the business processing, the degree of behavioural deviation of a case, i.e., an observed execution sequence, is quantified with respect to a process model (referred to as fitness, or recall). Recently, different compliance measures have been proposed. Still, nearly all of them are grounded on state-based techniques and the trace equivalence criterion, in particular. As a consequence, these approaches have to deal with the state explosion problem. In this paper, we argue that a behavioural abstraction may be leveraged to measure the compliance of a process log – a collection of cases. To this end, we utilise causal behavioural profiles that capture the behavioural characteristics of process models and cases, and can be computed efficiently. We propose different compliance measures based on these profiles, discuss the impact of noise in process logs on our measures, and show how diagnostic information on non-compliance is derived. As a validation, we report on findings of applying our approach in a case study with an international service provider.

Causal behavioural profiles : efficient computation, applications, and evaluation

Analysis of behavioural consistency is an important aspect of software engineering. In process and service management, consistency verification of behavioural models has manifold applications. For instance, a business process model used as system specification and a corresponding workflow model used as implementation have to be consistent. Another example would be the analysis to what degree a process log of executed business operations is consistent with the corresponding normative process model. Typically, existing notions of behaviour equivalence, such as bisimulation and trace equivalence, are applied as consistency notions. Still, these notions are exponential in computation and yield a Boolean result. In many cases, however, a quantification of behavioural deviation is needed along with concepts to isolate the source of deviation. In this article, we propose causal behavioural profiles as the basis for a consistency notion. These profiles capture essential behavioural information, such as order, exclusiveness, and causality between pairs of activities of a process model. Consistency based on these profiles is weaker than trace equivalence, but can be computed efficiently for a broad class of models. In this article, we introduce techniques for the computation of causal behavioural profiles using structural decomposition techniques for sound free-choice workflow systems if unstructured net fragments are acyclic or can be traced back to S- or T-nets. We also elaborate on the findings of applying our technique to three industry model collections.

Efficient computation of causal behavioural profiles using structural decomposition

Identification of behavioural contradictions is an important aspect of software engineering, in particular for checking the consistency between a business process model used as system specification and a corresponding workflow model used as implementation. In this paper, we propose causal behavioural profiles as the basis for a consistency notion, which capture essential behavioural information, such as order, exclusiveness, and causality between pairs of activities. Existing notions of behavioural equivalence, such as bisimulation and trace equivalence, might also be applied as consistency notions. Still, they are exponential in computation. Our novel concept of causal behavioural profiles provides a weaker behavioural consistency notion that can be computed efficiently using structural decomposition techniques for sound free-choice workflow systems if unstructured net fragments are acyclic or can be traced back to S- or T-nets.

Controlling microencapsulation and release of micronized proteins using poly(ethylene glycol) and electrospraying

The fabrication of tailored microparticles for delivery of therapeutics is a challenge relying upon a complex interplay between processing parameters and materials properties. The emerging use of electrospraying allows better tailoring of particle morphologies and sizes than current techniques, critical to reproducible release profiles. While dry encapsulation of proteins is essential for the release of active therapeutics from microparticles, it is currently uncharacterized in electrospraying. To this end, poly(ethylene glycol) (PEG) was assessed as a micronizing and solubilizing agent for dry protein encapsulation and release from electrosprayed particles made from polycaprolactone (PCL). The physical effect of PEG in protein-loaded poly(lactic-co-glycolic acid) (PLGA) particles was also studied, for comparison. The addition of 5–15 wt% PEG 6 kDa or 35 kDa resulted in reduced PCL particle sizes and broadened distributions, which could be improved by tailoring the electrospraying processing parameters, namely by reducing polymer concentration and increasing flow rate. Upon micronization, protein particle size was reduced to the micrometer domain, resulting in homogenous encapsulation in electrosprayed PCL microparticles. Microparticle size distributions were shown to be the most determinant factor for protein release by diffusion and allowed specific control of release patterns.

Mapping a candidate gene (MdMYB10) for red flesh and foliage colour in apple

BACKGROUND Integrating plant genomics and classical breeding is a challenge for both plant breeders and molecular biologists. Marker-assisted selection (MAS) is a tool that can be used to accelerate the development of novel apple varieties such as cultivars that have fruit with anthocyanin through to the core. In addition, determining the inheritance of novel alleles, such as the one responsible for red flesh, adds to our understanding of allelic variation. Our goal was to map candidate anthocyanin biosynthetic and regulatory genes in a population segregating for the red flesh phenotypes. RESULTS We have identified the Rni locus, a major genetic determinant of the red foliage and red colour in the core of apple fruit. In a population segregating for the red flesh and foliage phenotype we have determined the inheritance of the Rni locus and DNA polymorphisms of candidate anthocyanin biosynthetic and regulatory genes. Simple Sequence Repeats (SSRs) and Single Nucleotide Polymorphisms (SNPs) in the candidate genes were also located on an apple genetic map. We have shown that the MdMYB10 gene co-segregates with the Rni locus and is on Linkage Group (LG) 09 of the apple genome. CONCLUSION We have performed candidate gene mapping in a fruit tree crop and have provided genetic evidence that red colouration in the fruit core as well as red foliage are both controlled by a single locus named Rni. We have shown that the transcription factor MdMYB10 may be the gene underlying Rni as there were no recombinants between the marker for this gene and the red phenotype in a population of 516 individuals. Associating markers derived from candidate genes with a desirable phenotypic trait has demonstrated the application of genomic tools in a breeding programme of a horticultural crop species.

Polysubstance use in cannabis users referred for treatment: drug use profiles, psychiatric comorbidity and cannabis-related beliefs

Background: Population-based surveys demonstrate cannabis users are more likely to use both illicit and licit substances, compared with non-cannabis users. Few studies have examined the substance use profiles of cannabis users referred for treatment. Co-existing mental health symptoms and underlying cannabis-related beliefs associated with these profiles remains unexplored. Methods: Comprehensive drug use and dependence severity (Severity of Dependence Scale-Cannabis) data were collected on a sample of 826 cannabis users referred for treatment. Patients completed the General Health Questionnaire, Cannabis Expectancy Questionnaire, Cannabis Refusal Self-Efficacy Questionnaire, and Positive Symptoms and Manic-Excitement subscales of the Brief Psychiatric Rating Scale. Latent class analysis was performed on last month use of drugs to identify patterns of multiple drug use. Mental health comorbidity and cannabis beliefs were examined by identified drug use pattern. Results: A three-class solution provided the best fit to the data: (1) cannabis and tobacco users (n = 176), (2) cannabis, tobacco, and alcohol users (n = 498), and (3) wide-ranging sub- stance users (n = 132). Wide-ranging substance users (3) reported higher levels of cannabis dependence severity, negative cannabis expectancies, lower opportunistic, and emotional relief self-efficacy, higher levels of depression and anxiety and higher manic-excitement and positive psychotic symptoms. Conclusion: In a sample of cannabis users referred for treatment, wide-ranging substance use was associated with elevated risk on measures of cannabis dependence, co-morbid psychopathology, and dysfunctional cannabis cognitions. These findings have implications for cognitive-behavioral assessment and treatment.

Hunting and gathering : new imperatives in mapping and collecting student learning data to assure quality outcomes

Assurance of learning (AOL) is a quality enhancement and quality assurance process used in higher education. It involves a process of determining programme learning outcomes and standards, and systematically gathering evidence to measure students' performance on these. The systematic assessment of whole-of-programme outcomes provides a basis for curriculum development and management, continuous improvement, and accreditation. To better understand how AOL processes operate, a national study of university practices across one discipline area, business and management, was undertaken. To solicit data on AOL practice, interviews were undertaken with a sample of business school representatives (n = 25). Two key processes emerged: (1) mapping of graduate attributes and (2) collection of assurance data. External drivers such as professional accreditation and government legislation were the primary reasons for undertaking AOL outcomes but intrinsic motivators in relation to continuous improvement were also evident. The facilitation of academic commitment was achieved through an embedded approach to AOL by the majority of universities in the study. A sustainable and inclusive process of AOL was seen to support wider stakeholder engagement in the development of higher education learning outcomes.

The use of phospholipid fatty acid analysis to measure impact of acid rock drainage on microbial communities in sediments

The impact of acid rock drainage (ARD) and eutrophication on microbial communities in stream sediments above and below an abandoned mine site in the Adelaide Hills, South Australia, was quantified by PLFA analysis. Multivariate analysis of water quality parameters, including anions, soluble heavy metals, pH, and conductivity, as well as total extractable metal concentrations in sediments, produced clustering of sample sites into three distinct groups. These groups corresponded with levels of nutrient enrichment and/or concentration of pollutants associated with ARD. Total PLFA concentration, which is indicative of microbial biomass, was reduced by >70% at sites along the stream between the mine site and as far as 18 km downstream. Further downstream, however, recovery of the microbial abundance was apparent, possibly reflecting dilution effect by downstream tributaries. Total PLFA was >40% higher at, and immediately below, the mine site (0-0.1 km), compared with sites further downstream (2.5-18 km), even after accounting for differences in specific surface area of different sediment samples. The increased microbial population in the proximity of the mine source may be associated with the presence of a thriving iron-oxidizing bacteria community as a consequence of optimal conditions for these organisms while the lower microbial population further downstream corresponded with greater sediments' metal concentrations. PCA of relative abundance revealed a number of PLFAs which were most influential in discriminating between ARD-polluted sites and the rest of the sites. These PLFA included the hydroxy fatty acids: 2OH12:0, 3OH12:0, 2OH16:0; the fungal marker: 18:2ω6; the sulfate-reducing bacteria marker 10Me16:1ω7; and the saturated fatty acids 12:0, 16:0, 18:0. Partial constrained ordination revealed that the environmental parameters with the greatest bearing on the PLFA profiles included pH, soluble aluminum, total extractable iron, and zinc. The study demonstrated the successful application of PLFA analysis to rapidly assess the toxicity of ARD-affected waters and sediments and to differentiate this response from the effects of other pollutants, such as increased nutrients and salinity.

Capacity of fatty acid profiles and substrate utilization patterns to describe differences in soil microbial communities associated with increased salinity or alkalinity at three locations in South Australia

Fatty acid methyl ester (FAME) profiles, together with Biolog substrate utilization patterns, were used in conjunction with measurements of other soil chemical and microbiological properties to describe differences in soil microbial communities induced by increased salinity and alkalinity in grass/legume pastures at three sites in SE South Australia. Total ester-linked FAMEs (EL-FAMEs) and phospholipid-linked FAMEs (PL-FAMEs), were also compared for their ability to detect differences between the soil microbial communities. The level of salinity and alkalinity in affected areas of the pastures showed seasonal variation, being greater in summer than in winter. At the time of sampling for the chemical and microbiological measurements (winter) only the affected soil at site 1 was significantly saline. The affected soils at all three sites had lower organic C and total N concentrations than the corresponding non-affected soils. At site 1 microbial biomass, CO 2-C respiration and the rate of cellulose decomposition was also lower in the affected soil compared to the non-affected soil. Biomarker fatty acids present in both the EL- and PL-FAME profiles indicated a lower ratio of fungal to bacterial fatty acids in the saline affected soil at site 1. Analysis of Biolog substrate utilization patterns indicated that the bacterial community in the affected soil at site 1 utilized fewer carbon substrates and had lower functional diversity than the corresponding community in the non-affected soil. In contrast, increased alkalinity, of major importance at sites 2 and 3, had no effect on microbial biomass, the rate of cellulose decomposition or functional diversity but was associated with significant differences in the relative amounts of several fatty acids in the PL-FAME profiles indicative of a shift towards a bacterial dominated community. Despite differences in the number and relative amounts of fatty acids detected, principal component analysis of the EL- and PL-FAME profiles were equally capable of separating the affected and non-affected soils at all three sites. Redundancy analysis of the FAME data showed that organic C, microbial biomass, electrical conductivity and bicarbonate-extractable P were significantly correlated with variation in the EL-FAME profiles, whereas pH, electrical conductivity, NH 4-N, CO 2-C respiration and the microbial quotient were significantly correlated with variation in the PL-FAME profiles. Redundancy analysis of the Biolog data indicated that cation exchange capacity and bicarbonate-extractable K were significantly correlated with the variation in Biolog substrate utilization patterns.

The application of luminance mapping to discomfort glare : a modified glare index for green buildings

Unfortunately, there is no reliable method to adequately quantify discomfort glare. One of the world's largest investigations on discomfort glare was conducted in five Green Star office buildings in Brisbane. Luminance mapping via high dynamic range images and Post Occupancy Evaluation surveys were used in the data collection. A new glare index, termed the Unified Glare Probability, was developed to predict discomfort glare within these types of office buildings.

Fashion meets journalism : mapping and evaluating Australian fashion journalism

Fashion journalism can be understood as a complex, inter-dependent set of professional practices that have arisen in a variety of media at the intersection of fashion and journalism. This thesis, Fashion Meets Journalism: Mapping and Evaluating Australian Fashion Journalism, answers the question, 'What is Australian fashion journalism?' in three stages: First, it maps the extent of fashion journalism across media in Australia to locate the field and focus on the sites of fashion journalism; second, it foregrounds practices of the journalism branch, evaluating how and why the field is pitted against other types of journalism when they share an inter-dependent set of professional practices. The opinions of leading industry producers are also sought regarding the matter. Then, considering the current position of fashion journalism, implications for fashion media and journalism are explored in order to improve the visibility of fashion journalism and solidify it as a professional practice.