Validating adult and paediatric nutrition screening and assessment tools in Vietnamese language in two acute hospital in Ho Chi Minh City, Vietnam

Despite being commonly prevalent in acute care hospitals worldwide, malnutrition often goes unidentified and untreated due to a lack in the implementation of a nutrition care pathway. The aim of this study was to validate nutrition screening and assessment tools in Vietnamese language. After converting into Vietnamese, Malnutrition Screening Tool (MST) and Subjective Global Assessment (SGA) were used to identify malnutrition in the adult setting; and the Paediatric Nutrition Screening Tool (PNST) and paediatric Subjective Global Nutritional Assessment (SGNA) were used in the paediatric setting in two acute care hospitals in Vietnam. This cross-sectional observational study sampled 123 adults (median age 78 years [39–96 years], 63% males) and 105 children (median age 20 months [2–100 months], 66% males). In adults, nutrition risk and malnutrition were identified in 29% and 45% of the cohort respectively. Nutrition risk and malnutrition were identified in 71% and 43% of the paediatric cohort respectively. The sensitivity and specificity of the screening tools were: 62% and 99% for the MST compared to the SGA; 89% and 42% for the PNST compared to the SGNA. This study provides a stepping stone to the potential use of evidence-based nutrition screening and assessment tools in Vietnamese language within the adult and paediatric Vietnamese acute care setting. Further work is required into integrating a complete nutrition care pathway within the acute care setting in Vietnamese hospitals.

Web 2.0 technology: Social learning tools in higher education in Saudi Arabia

Information and communication technology (ICT) has created opportunities for students' online interaction in higher education throughout the world. Limited research has been done in this area in Saudi Arabia. This study investigated university students' engagement and perceptions of online collaborative learning using Social Learning Tools (SLTs). In addition, it explored the quality of knowledge construction that occurred in this environment. A mixed methods case study approach was adopted, and the data was gathered from undergraduate students (n=43) who were enrolled in a 15-week course at a Saudi university. The results showed that while the students had positive perceptions towards SLTs and their engagement, data gathered from their work also showed little evidence of high levels of knowledge construction.

Tools for compositional data with a total

Compositional data analysis usually deals with relative information between parts where the total (abundances, mass, amount, etc.) is unknown or uninformative. This article addresses the question of what to do when the total is known and is of interest. Tools used in this case are reviewed and analysed, in particular the relationship between the positive orthant of D-dimensional real space, the product space of the real line times the D-part simplex, and their Euclidean space structures. The first alternative corresponds to data analysis taking logarithms on each component, and the second one to treat a log-transformed total jointly with a composition describing the distribution of component amounts. Real data about total abundances of phytoplankton in an Australian river motivated the present study and are used for illustration.

Functional genes and gene array analysis as tools for monitoring hydrocarbon biodegradation

Bioremediation, which is the exploitation of the intrinsic ability of environmental microbes to degrade and remove harmful compounds from nature, is considered to be an environmentally sustainable and cost-effective means for environmental clean-up. However, a comprehensive understanding of the biodegradation potential of microbial communities and their response to decontamination measures is required for the effective management of bioremediation processes. In this thesis, the potential to use hydrocarbon-degradative genes as indicators of aerobic hydrocarbon biodegradation was investigated. Small-scale functional gene macro- and microarrays targeting aliphatic, monoaromatic and low molecular weight polyaromatic hydrocarbon biodegradation were developed in order to simultaneously monitor the biodegradation of mixtures of hydrocarbons. The validity of the array analysis in monitoring hydrocarbon biodegradation was evaluated in microcosm studies and field-scale bioremediation processes by comparing the hybridization signal intensities to hydrocarbon mineralization, real-time polymerase chain reaction (PCR), dot blot hybridization and both chemical and microbiological monitoring data. The results obtained by real-time PCR, dot blot hybridization and gene array analysis were in good agreement with hydrocarbon biodegradation in laboratory-scale microcosms. Mineralization of several hydrocarbons could be monitored simultaneously using gene array analysis. In the field-scale bioremediation processes, the detection and enumeration of hydrocarbon-degradative genes provided important additional information for process optimization and design. In creosote-contaminated groundwater, gene array analysis demonstrated that the aerobic biodegradation potential that was present at the site, but restrained under the oxygen-limited conditions, could be successfully stimulated with aeration and nutrient infiltration. During ex situ bioremediation of diesel oil- and lubrication oil-contaminated soil, the functional gene array analysis revealed inefficient hydrocarbon biodegradation, caused by poor aeration during composting. The functional gene array specifically detected upper and lower biodegradation pathways required for complete mineralization of hydrocarbons. Bacteria representing 1 % of the microbial community could be detected without prior PCR amplification. Molecular biological monitoring methods based on functional genes provide powerful tools for the development of more efficient remediation processes. The parallel detection of several functional genes using functional gene array analysis is an especially promising tool for monitoring the biodegradation of mixtures of hydrocarbons.

Mutations as molecular tools : The metabolic-rate dependent molecular clock and DNA barcoding of allied species

Mutation and recombination are the fundamental processes leading to genetic variation in natural populations. This variation forms the raw material for evolution through natural selection and drift. Therefore, studying mutation rates may reveal information about evolutionary histories as well as phylogenetic interrelationships of organisms. In this thesis two molecular tools, DNA barcoding and the molecular clock were examined. In the first part, the efficiency of mutations to delineate closely related species was tested and the implications for conservation practices were assessed. The second part investigated the proposition that a constant mutation rate exists within invertebrates, in form of a metabolic-rate dependent molecular clock, which can be applied to accurately date speciation events. DNA barcoding aspires to be an efficient technique to not only distinguish between species but also reveal population-level variation solely relying on mutations found on a short stretch of a single gene. In this thesis barcoding was applied to discriminate between Hylochares populations from Russian Karelia and new Hylochares findings from the greater Helsinki region in Finland. Although barcoding failed to delineate the two reproductively isolated groups, their distinct morphological features and differing life-history traits led to their classification as two closely related, although separate species. The lack of genetic differentiation appears to be due to a recent divergence event not yet reflected in the beetles molecular make-up. Thus, the Russian Hylochares was described as a new species. The Finnish species, previously considered as locally extinct, was recognized as endangered. Even if, due to their identical genetic make-up, the populations had been regarded as conspecific, conservation strategies based on prior knowledge from Russia would not have guaranteed the survival of the Finnish beetle. Therefore, new conservation actions based on detailed studies of the biology and life-history of the Finnish Hylochares were conducted to protect this endemic rarity in Finland. The idea behind the strict molecular clock is that mutation rates are constant over evolutionary time and may thus be used to infer species divergence dates. However, one of the most recent theories argues that a strict clock does not tick per unit of time but that it has a constant substitution rate per unit of mass-specific metabolic energy. Therefore, according to this hypothesis, molecular clocks have to be recalibrated taking body size and temperature into account. This thesis tested the temperature effect on mutation rates in equally sized invertebrates. For the first dataset (family Eucnemidae, Coleoptera) the phylogenetic interrelationships and evolutionary history of the genus Arrhipis had to be inferred before the influence of temperature on substitution rates could be studied. Further, a second, larger invertebrate dataset (family Syrphidae, Diptera) was employed. Several methodological approaches, a number of genes and multiple molecular clock models revealed that there was no consistent relationship between temperature and mutation rate for the taxa under study. Thus, the body size effect, observed in vertebrates but controversial for invertebrates, rather than temperature may be the underlying driving force behind the metabolic-rate dependent molecular clock. Therefore, the metabolic-rate dependent molecular clock does not hold for the here studied invertebrate groups. This thesis emphasizes that molecular techniques relying on mutation rates have to be applied with caution. Whereas they may work satisfactorily under certain conditions for specific taxa, they may fail for others. The molecular clock as well as DNA barcoding should incorporate all the information and data available to obtain comprehensive estimations of the existing biodiversity and its evolutionary history.

Simulation and modelling tools for quantitative safety assessments of unmanned aircraft systems and operations

This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.

Statistical tools for analyzing water quality data

Water quality data are often collected at different sites over time to improve water quality management. Water quality data usually exhibit the following characteristics: non-normal distribution, presence of outliers, missing values, values below detection limits (censored), and serial dependence. It is essential to apply appropriate statistical methodology when analyzing water quality data to draw valid conclusions and hence provide useful advice in water management. In this chapter, we will provide and demonstrate various statistical tools for analyzing such water quality data, and will also introduce how to use a statistical software R to analyze water quality data by various statistical methods. A dataset collected from the Susquehanna River Basin will be used to demonstrate various statistical methods provided in this chapter. The dataset can be downloaded from website http://www.srbc.net/programs/CBP/nutrientprogram.htm.

Scheduling tools to reduce the cost of cane railway transport

Cane railway systems provide empty bins for harvesters to fill and full bins of cane for the factory to process. These operations need to be conducted in a timely fashion to minimise delays to harvesters and the factory and to minimise the cut-to-crush delay, while also minimising the cost of providing this service. A range of tools has been provided over the years to assist in this process. This paper reviews the objectives of the cane transport system and the tools available to achieve those objectives. The facilities within these tools to assist in the control of costs are highlighted.

CFD tools in engineering design studies and medical sciences

In the recent time CFD tools have become increasingly useful in the engineering design studies especially in the area of aerospace vehicles. This is largely due to the advent of high speed computing platforms in addition to the development of new efficient algorithms. The algorithms based on kinetic schemes have been shown to be very robust and further meshless methods offer certain advantages over the other methods. Preliminary investigations of blood flow visualization through artery using CFD tool have shown encouraging results which further needs to be verified and validated.

Methods and tools for mass spectrometric lipidome analysis

The analysis of lipid compositions from biological samples has become increasingly important. Lipids have a role in cardiovascular disease, metabolic syndrome and diabetes. They also participate in cellular processes such as signalling, inflammatory response, aging and apoptosis. Also, the mechanisms of regulation of cell membrane lipid compositions are poorly understood, partially because a lack of good analytical methods. Mass spectrometry has opened up new possibilities for lipid analysis due to its high resolving power, sensitivity and the possibility to do structural identification by fragment analysis. The introduction of Electrospray ionization (ESI) and the advances in instrumentation revolutionized the analysis of lipid compositions. ESI is a soft ionization method, i.e. it avoids unwanted fragmentation the lipids. Mass spectrometric analysis of lipid compositions is complicated by incomplete separation of the signals, the differences in the instrument response of different lipids and the large amount of data generated by the measurements. These factors necessitate the use of computer software for the analysis of the data. The topic of the thesis is the development of methods for mass spectrometric analysis of lipids. The work includes both computational and experimental aspects of lipid analysis. The first article explores the practical aspects of quantitative mass spectrometric analysis of complex lipid samples and describes how the properties of phospholipids and their concentration affect the response of the mass spectrometer. The second article describes a new algorithm for computing the theoretical mass spectrometric peak distribution, given the elemental isotope composition and the molecular formula of a compound. The third article introduces programs aimed specifically for the analysis of complex lipid samples and discusses different computational methods for separating the overlapping mass spectrometric peaks of closely related lipids. The fourth article applies the methods developed by simultaneously measuring the progress curve of enzymatic hydrolysis for a large number of phospholipids, which are used to determine the substrate specificity of various A-type phospholipases. The data provides evidence that the substrate efflux from bilayer is the key determining factor for the rate of hydrolysis.

Simulation and graph mining tools for improving gene mapping efficiency

Gene mapping is a systematic search for genes that affect observable characteristics of an organism. In this thesis we offer computational tools to improve the efficiency of (disease) gene-mapping efforts. In the first part of the thesis we propose an efficient simulation procedure for generating realistic genetical data from isolated populations. Simulated data is useful for evaluating hypothesised gene-mapping study designs and computational analysis tools. As an example of such evaluation, we demonstrate how a population-based study design can be a powerful alternative to traditional family-based designs in association-based gene-mapping projects. In the second part of the thesis we consider a prioritisation of a (typically large) set of putative disease-associated genes acquired from an initial gene-mapping analysis. Prioritisation is necessary to be able to focus on the most promising candidates. We show how to harness the current biomedical knowledge for the prioritisation task by integrating various publicly available biological databases into a weighted biological graph. We then demonstrate how to find and evaluate connections between entities, such as genes and diseases, from this unified schema by graph mining techniques. Finally, in the last part of the thesis, we define the concept of reliable subgraph and the corresponding subgraph extraction problem. Reliable subgraphs concisely describe strong and independent connections between two given vertices in a random graph, and hence they are especially useful for visualising such connections. We propose novel algorithms for extracting reliable subgraphs from large random graphs. The efficiency and scalability of the proposed graph mining methods are backed by extensive experiments on real data. While our application focus is in genetics, the concepts and algorithms can be applied to other domains as well. We demonstrate this generality by considering coauthor graphs in addition to biological graphs in the experiments.