<div> <div> <div> <p>The exploratory profiling and quantitative bioassays of lipids, small metabolites, and peptides have always been challenging tasks. The most popular instrument platform deployed to solve these problems is chromatography coupled with mass spectrometry. However, it requires large amounts of instrument time, intensive labor, and frequent maintenance, and usually produces results with bias. Thus, the pace of exploratory research is one of poor efficacy and low throughput. The work in this dissertation provides two practical tactics to address these problems. The first solution is multiple reaction monitoring profiling (MRM-profiling), a new concept intended to shift the exploratory research from current identification-centered metabolomics and lipidomics to functional group screening by taking advantage of precursor ion scan and product ion scan. It is also demonstrated that MRM-profiling is capable of quantifying the relative amount of lipids within the same subclass. Besides, an application of the whole workflow to investigate the strain-level differences of bacteria is described. The results have zeroed in on several potential lipid biomarkers and corresponding MRM transitions. The second strategy is aimed to increase the throughput of targeted bioassays by conducting induced nanoelectrospray ionization (nESI) in batch mode. A novel prototype instrument named "Dip-and-Go" system is presented. Characterization of its ability to carry out reaction screening and bioassays exhibits the versatility of the system. The distinct electrophoretic cleaning mechanism contributes to the removal of salt during ionization, which assures the accuracy of measurement.</p></div></div></div>

<p dir="ltr">Plant secondary metabolites (PSMs) are specialized compounds produced in response to a range of insect herbivores and microbes, making them important in shaping tri-trophic interactions. However, despite being well-studied in the context of plant-insect coevolution, it is unclear how PSMs impact microbial communities associated with plants and the insect herbivores that feed on them. The overarching goal of this dissertation was to better understand how variation in plant defensive responses, particularly expression of PSMs, influences the composition and functional potential of microbial communities associated with plant tissues (roots and leaves) and insect herbivores. Monarchs (<i>Danaus plexippus</i>) and their milkweed hosts (<i>Asclepias spp.)</i> are well-studied for mechanisms of plant defense and insect counter defense, but little is known about the role of associated microbial communities in this iconic system. To address this knowledge gap, a combination of metabarcoding and metagenomics was used to characterize the taxonomic composition and functional gene profiles of bacterial communities associated with plant tissues (i.e., phyllosphere and rhizosphere) and monarch caterpillars fed on multiple milkweed species (<i>A. curassavica</i>, <i>A. syriaca</i>, and <i>A. tuberosa</i>). Findings show the composition of phyllosphere, rhizosphere, and monarch microbiomes vary across milkweed species in terms of diversity and relative abundance of bacterial taxa. Furthermore, phyllosphere and rhizosphere microbiomes were shown to have distinct functional gene profiles and presence of potential PSM metabolism genes that also varied across milkweed species. Rhizosphere microbiomes had a greater overall capacity for PSM metabolism compared to the phyllosphere, having more genes, and associated metabolic pathways involved in degradation or detoxification of known classes of PSMs. However, plant associated microbiomes were not generally affected by monarch feeding, evidenced by few changes in taxonomic composition or abundance of genes predicted to be involved in PSM metabolism. Interestingly, monarch microbiomes shared >90% of their taxa with their host plants, but there was little evidence of PSM metabolism genes present in functional gene profiles. Overall, this dissertation lays the foundation for understanding how PSMs shape all the microbial communities associated with monarchs and their milkweed hosts. Findings suggest plant defensive responses affect the assembly, functional potential and ultimately the evolution of plant and insect microbiomes.</p>

Die von der caprotec bioanalytics GmbH entwickelte und vermarktete Capture Compounds Mass SpectrometryTM (CCMS-Technologie) ermöglicht die spezifische Isolierung und Identifizierung von Proteinen, basierend auf ihre gezielte Wechselwirkung mit kleinen trifunktionalen Moleküle (sog. Capture CompoundsTM). Dadurch wird sowohl eine Reduzierung der Komplexität zellulärer Proteingemische als auch eine Anreicherung niedrig abundanter Proteine erreicht. In der vorliegenden Arbeit erfolgte die Synthese von neuartigen Capture Compounds, die dazu dienen sollen, unterschiedliche biochemische Fragestellungen zu beantworten und das Anwendungsspektrum der CCMS-Technologie stark erweitern. / The Capture Compound Mass SpectrometryTM (CCMS-Technology) is a novel technology developed and marketed by caprotec bioanalytics GmbH. CCMS allows the isolation of sub-proteomes based on specific interactions of target proteins with synthetic small molecules, called Capture Compounds (CCs). In this way, CCMS affords the functional reduction of complex protein mixtures that derived from e.g. cell lysates, and the enrichment and identification of low abundant proteins. In the present work, the synthesis of different novel Capture Compounds that helps studying different biological problems and overcoming present technological limitations of CCMS is described.

AIM: Nutrient profiling can be defined as ‘the science of categorising foods according to their nutritional composition’ and can be used as a valuable tool in food labelling legislation. Validation is an absolute essential step in the implementation of a nutrient profiling model (NPM), it is important to verify whether or not the NPM has a good solid scientific basis and if it is at all suitable for South Africa. This mini-dissertation investigated the construct validity of a NPM for South Africa. OBJECTIVES: 1) To test construct validity for the nutrient profiling model by examining the relationship between the way the NPM categorises foods and the healthiness of diets in South Africa. 2) To assess if the quality of a diet will improve if ‘unhealthy’ foods are replaced by ‘healthy’ foods as defined by the NPM. STUDY DESIGN: Nested in the South African leg of the international PURE (Prospective Urban and Rural Epidemiology) study at baseline. METHOD: The PURE (Prospective Urban and Rural Epidemiology) baseline study conducted in the North-West province in 2005, was identified as a suitable dataset of food intake. For the first objective the proportion of respondent’s diets consisting of healthy or unhealthy food, as classified by the NPM, was calculated. The respondents were divided into four groups based on their dietary quality as characterised by the Diet Quality Index (DQI), the lower the DQI-score the better the diet quality. The proportion of healthy or unhealthy foods were compared to the DQI-scores using one-way ANOVA’s, p-values were calculated using the Tukey post-hoc test. For the second objective the diet quality of four different diets consisting of either YES foods (according to NPM), NO foods, a combination of YES and NO were calculated and compared. RESULTS: The model displayed good construct validity by showing a statistically significant positive relationship between the proportion of ‘healthy’ (p<0.0001) and ‘unhealthy’ (p<0.0001) foods, as classified by the NPM, and participants’ DQI-scores. The second objective was also confirmed and a diet consisting of ‘healthy’ foods or a diet where ‘unhealthy’ foods were substituted by ‘healthy’ foods, had a better DQI than diets consisting only of ‘unhealthy’ foods CONCLUSION: Construct validity was confirmed by proving that the better the diet quality of the respondents the bigger their proportion of foods categorised as ‘healthy’ by the NPM and vice versa. / MSc (Dietetics), North-West University, Potchefstroom Campus, 2014

Published Article / Although research has been conducted in the field of Acoustic Doppler Borehole Flowmeters (ADBF), it has been focused on point source of flow and three dimensional borehole flow techniques. However as of yet, no studies have been conducted on the possible use of Acoustic Doppler Borehole Profiling (ADBP). This technique of borehole flow measurement is possibly a revolutionary concept in how vertical flow in a borehole is measured. It makes use of a single inexpensive transducer that can float on the surface of the water in a borehole and use Acoustic Doppler techniques to profile the flow in a borehole. No complicated and expensive flow probe winching systems will be required. Another added benefit of the ADBP will be the non-evasive technologies that comprise its design. Current borehole flow probes are required to be present at the point of flow measurement in the borehole. The presence of the probe inadvertently alters the flow in the borehole by adding resistance to the flow in the borehole. Under stressed or pumped flow tests these flow resistance effects cause sufficient pressure gradients at the flow sensors to divert part of the flow away from the sensor. This causes erroneous readings of flow as a part of the flow in the borehole is not accounted for. In ADBP the sensor is not physically present at the point of flow being read. This makes the ADBP technique of borehole flow measurement far more representative of the natural flow conditions in the borehole under ambient and stressed conditions.

Published Article / The design, manufacture and use of diaphragm valves in the minerals industry is becoming increasingly important since this sector is restricted from using excessive amounts of water for their operations. This forces a change in the flow properties of these devices from turbulent to laminar in nature and thus necessitates the characterization of these flows for future designs. Furthermore, diaphragm valves have a short service life due to a variety of reasons that includes the abrasive nature of the flow environment. This paper describes the activities of the Adaptronics Advanced Manufacturing Technology Laboratory (AMTL) at the Cape Peninsula University of Technology in the research and development of diaphragm valves using rapid prototyping technologies. As a first step, an experimental diaphragm valve was reverse engineered and retrofitted with ultrasonic transducers used in Ultrasonic Velocity Profiling (UVP) measurements. The use of this device enables measurements of velocity profiles to gain insight into the flow structure within the valve and the increased pressure losses generated within the valve. It also showed that components fabricated using the Z-Corporation machine could withstand the working environment of diaphragm valves. Research is now conducted on ultrasonic transducer placement in the device to further enhance the velocity profiling through the device. As a second step we produced a thin-walled stainless steel diaphragm valve using rapid prototyping technology and investment casting processes. A study of the durability of this device will be conducted and certain geometric and manufacturing aspects of this valve will be discussed.

AIM: Nutrient profiling can be defined as ‘the science of categorising foods according to their nutritional composition’ and can be used as a valuable tool in food labelling legislation. Validation is an absolute essential step in the implementation of a nutrient profiling model (NPM), it is important to verify whether or not the NPM has a good solid scientific basis and if it is at all suitable for South Africa. This mini-dissertation investigated the construct validity of a NPM for South Africa. OBJECTIVES: 1) To test construct validity for the nutrient profiling model by examining the relationship between the way the NPM categorises foods and the healthiness of diets in South Africa. 2) To assess if the quality of a diet will improve if ‘unhealthy’ foods are replaced by ‘healthy’ foods as defined by the NPM. STUDY DESIGN: Nested in the South African leg of the international PURE (Prospective Urban and Rural Epidemiology) study at baseline. METHOD: The PURE (Prospective Urban and Rural Epidemiology) baseline study conducted in the North-West province in 2005, was identified as a suitable dataset of food intake. For the first objective the proportion of respondent’s diets consisting of healthy or unhealthy food, as classified by the NPM, was calculated. The respondents were divided into four groups based on their dietary quality as characterised by the Diet Quality Index (DQI), the lower the DQI-score the better the diet quality. The proportion of healthy or unhealthy foods were compared to the DQI-scores using one-way ANOVA’s, p-values were calculated using the Tukey post-hoc test. For the second objective the diet quality of four different diets consisting of either YES foods (according to NPM), NO foods, a combination of YES and NO were calculated and compared. RESULTS: The model displayed good construct validity by showing a statistically significant positive relationship between the proportion of ‘healthy’ (p<0.0001) and ‘unhealthy’ (p<0.0001) foods, as classified by the NPM, and participants’ DQI-scores. The second objective was also confirmed and a diet consisting of ‘healthy’ foods or a diet where ‘unhealthy’ foods were substituted by ‘healthy’ foods, had a better DQI than diets consisting only of ‘unhealthy’ foods CONCLUSION: Construct validity was confirmed by proving that the better the diet quality of the respondents the bigger their proportion of foods categorised as ‘healthy’ by the NPM and vice versa. / MSc (Dietetics), North-West University, Potchefstroom Campus, 2014

Most software applications rely on the use of user-name and passwords to authenticate end users. This form of authentication, although used ubiquitously, is widely considered unreliable due to the users inability to keep them secret; passwords being prone to dictionary or rainbow-table attacks; as well as the ease with which social engineering techniques can obtain passwords. This can be mitigated by combining a variety of diferent authentication mechanisms, for example biometric authentication such as fingerprint recognition or physical tokens such as smart cards. The resulting multifactor authentication is typically stronger than any of the techniques used individually. However, it may still be expensive or prohibited to implement and more dificult to deploy due to additional accessories cost, e.g, finger print reader. Multi-modal biometric systems are those which utilise or are capable of utilising, more than one physiological or behavioural characteristic for enrolment, verification, or identification. So, in this research we present a multi-factor authentication scheme that is based on the user's own hardware environment, e.g. laptop with fingerprint reader, thus avoiding the need of deploying tokens and readily available biometrics, e.g., user keystrokes. The aim is to improve the reliability of the authentication using a multi-factor approach without incurring additional cost or making the deployment of the solution overly complex. The presented approach in this research uses unique sequential hardware information available from the user's environment to profile user behaviour. This approach improves upon password mechanisms by introducing a novel Hardware Authentication and User Profiling (HAUP) in form of Multi-Factor Authentication MFA that can be easily integrated into the traditional authentication methods. In addition, this approach observes the advantage of the correlation between user behaviour and hardware environment as an implicit veri_cation identity procedure to discriminate username and password usage, in particular hardware environment by specific pattern. So, the proposed approach uses hardware information to profile the user's environment when user-name and password are typed as part of the log-in process. These Hardware Manufacture Serial Part Numbers (HMSPNs) profiles are then correlated with the users behaviour, e.g., key-stroke behaviour that allows the system to profile user's behaviour dependent on their environment. As a result of this approach, the access control system can determine a particular level of trust for each user and base access control decisions on it in order to reduce potential identity fraud.

For over two decades, mathematicians and cryptologists have evaluated and presented the theoretical performance of Elliptic-curve scalar point-multiplication in projective geometry. Because computation in projective domain is composed of a wide array of formulations and computing optimizations, there is not a comprehensive performance comparison of point-multiplication using projective transformation available to verify its realistic efficiency in 64-bit x86 computing platforms. Today, research on explicit mathematical formulations in projective domain continues to excel by seeking higher computational efficiency and ease of realization. An explicit performance evaluation will help implementers choose better implementation methods and improve Elliptic-curve scalar point-multiplication. This paper was founded on the practical solution that obtaining realistic performance figures should be based on more precise computational cost metrics and specific computing platforms. As part of that solution, an empirical performance benchmark comparison between two approaches implementing projective Elliptic-curve scalar point-multiplication will be presented to provide the selection of, and subsequently ways to improve scalar point-multiplication technology executing in a 64-bit x86 runtime environment.

Application profiling is an important step in the design and optimization of embedded systems. Accurately identifying and analyzing the execution of frequently executed computational kernels is needed to effectively optimize the system implementation, both at design time and runtime. In a traditional design process, it suffices to perform the profiling and optimization steps offline, during design time. The offline profiling guides the design space exploration, hardware software codesign, or power and performance optimizations. When the system implementation can be finalized at design time, this approach works well. However, dynamic optimization techniques, which adapt and reconfigure the system at runtime, require dynamic profiling with minimum runtime overheads. Existing profiling methods are usually software based and incur significant overheads that may be prohibitive or impractical for profiling embedded systems at runtime. In addition, these profiling methods typically focus on profiling the execution of specific tasks executing on a single processor core, but do not consider accurate and holistic profiling across multiple processor cores. Directly utilizing existing profiling approaches and naively combining isolated profiles from multiple processor cores can lead to significant profile inaccuracies of up to 35%. To address these challenges, a hardware-based dynamic application profiler for non-intrusively and accurately profiling software applications in multicore embedded systems is presented. The profiler provides a detailed execution profile for computational kernels and maintains profile accuracy across multiple processor cores. The hardware-based profiler achieves an average error of less than 0.5% for the percentage execution time of profiled applications while being area efficient.