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In this study, a South African indigenous microalga Acutodesmus bajacalifornicus was evaluated in different cultivation media. Eleven potential cultivation media were identified and tested on A. bajacalifornicus, a potential source for biodiesel production. A. bajacalifornicus had the highest growth rate in the JG medium (in-house formulation), with a competitive average specific growth rate of 0.47 d−1. The highest biomass productivity was in the Hase medium, but with relatively low productivity of 53.1 mg.L−1.d−1. Analysis of the biomass lipid content and profile of each cell culture, using fatty acid methyl ester (FAME) gas chromatography (GC) showed that the lipid content varied between cultivation media, with minimum lipid content of 20% (w/w) and an average close to 47% (w/w). Utilising biodiesel property predictive formulas, and the lipid profiles obtained in this study, it was possible to predict the properties of biodiesel that could be generated from A. bajacalifornicus. It was found that biomass from eight of the media adhered to South African summer grade biodiesel standards. As such, A. bajacalifornicus is a potential candidate for microalgal biodiesel production in South Africa. However, the bioenergy yield rate would need to be improved to have a similar attractiveness to other studies.

We compare DNA mixture analysis via DNAˑVIEW® Mixture Solution™ and the current combined probability of inclusion (CPI) method of the South African Police Service (SAPS). South Africa has a high incidence of property-related crimes and sexual offences and consequently a great deal of low-template (LT-DNA) forensic DNA mixture casework and a perpetual backlog. A range of casework and laboratory-prepared sexual assault mixtures with initial male DNA amounts varying from about 2 to 200 cells were analysed to evaluate the benefits of a continuous model program. Unfortunately CPI methods are nearly useless for LT-DNA cases because of dropout-common from a mixture contribution of fewer than 20 or 30 cells. We further argue that proposed CPI elaborations to circumvent dropout lack supporting research or even explanation. Mixture Solution models mixture data as continuous rather than binary, with a mathematically coherent ("probabilistic") model which incorporates dropout and other phenomena realistically. Much more information is thereby utilised resulting in applicability to more cases (7 or fewer contributor cells suffice), stronger evidence against a suspect who is a mixture contributor and stronger evidence to absolve a non-contributor. Mixture Solution incidentally provides information which, along with rfu data, allows estimating contributions in terms of number of cells, which is a useful perspective. The method of calculation is explained.

Coenraad Christoffel Andries (Coen) Labuschagne was born on May 16, 1958. He was married to Laetitia Lourens, an anaesthesiologist. They were a high school couple who met at the Roodepoort High School. After their wedding they settled in Florida on the West Rand in South Africa. Coen and Laetitia had a daughter Minette, and they experienced the trauma of losing her unexpectedly while she was still a student. On July 10, 2018 Laetitia had to cope with a similar tragedy when Coen, after a short illness, passed away.

We show that the paper in which P.J. Daniell introduced his well-known integral, used modern Riesz space techniques to derive the properties of the integral and to prove a fundamental decomposition result for the integral. The latter result was proved a decade later by F. Riesz and was considered to be the origin of Riesz space theory. After a survey of Daniell’s paper, we generalize P.E. Protter’s version of the Lp-valued (0 ≤ p ≤∞) Daniell integral to a vector lattice-valued Daniell integral, following closely Daniell’s original method. A.C.M van Rooij and W.B. van Zuijlen also introduced integrals for functions with values in a partially ordered vector space a more general setting than the one we use.

Road pavements are constructed of bulk raw materials such as aggregate, cement, bitumen and water. The environmental, social, and economic impacts of the materials and processes should be quantified and monitored towards the optimisation of pavement design. At present, no such protocol is in place in South Africa. This paper proposes a framework for the development of a pavement life cycle assessment model, starting by documenting the life cycle inventory for bitumen, one of the leading environmental and social burdensome materials used for pavement development. This inventory acts as the first building block in the development of a life cycle assessment model by evaluating and delineating primary flows (inputs of materials and energy and outputs of pollution) related to the supply chain of bitumen in South Africa. The primary flows are represented by indicators which measure their quantitative impacts. The inventory provides impact category indicators for environmental and social related emissions, energy- and water-use and currently excludes other indicators such as emissions to water, waste generation, jobs creation and economic transformation, amongst others. These indicators are omitted due to lack of quality data at present and difficulty in the quantification of impacts, but recognition is given to their relevancy and importance. The approach is envisioned to function as the first version of a living protocol that will be improved on through further research. Although the primary target audience is South African road authorities, the approach can be adapted for use in any country.

In this paper we formulate and proof Girsanov’s theorem in vector lattices. To reach this goal, we develop the theory of cross-variation processes, derive the cross-variation formula and the Kunita–Watanabe inequality. Also needed and derived are properties of exponential processes, Ito’s rule for multi-dimensional processes and the integration by parts formula for martingales. After proving Girsanov’s theorem for the one-dimensional case, we also discuss the multi-dimensional case.

In most countries the agricultural sector, especially crop irrigation, is a considerable energy consumer. Farm irrigation studies in South Africa showed that energy and water is wasted on a large scale and there is a large potential for improving efficiency. The present study focusses on the measurement and verification (M&V) of irrigation pumping energy conservation measures (ECMs) under the Eskom Standard Product Programme funding mechanism in South Africa. A novel M&V methodology was developed to quantify ECM impacts under the Programme, which has special conditions and unique M&V requirements, which makes normal approaches inapplicable. Methods were designed to effectively determine conservative but representative impacts without continuous power demand profile measurement. The design involved unique methods to quantify operational demand reduction, annual energy consumption and annual average demand reduction impacts. The design was broadened to include pumps irrigating multiple crop areas and different kind of crops. The methodologies and techniques developed were validated and verified through establishing independent cross-check measures. The paper discusses a regional top-down M&V approach to verify the actual total energy efficiency and load reduction on the electricity grid for a specific region.

This paper investigates the use of the Taguchi method for the design of line-start permanent magnet synchronous motors (LS-PMSMs). To address the inherent limitation of the Taguchi method in solving multiresponse optimization problems, an improved regression rate methodology and a weighted factor multiobjective technique are incorporated to form a Taguchi method based multiobjective design framework. To validate the proposed method, a prototype machine has been designed, constructed, and experimentally evaluated. It shows that the proposed method can effectively take into account both steady-state and transient synchronization performances in the design of LS-PMSMs.

There has been a considerable amount of research work on using the Taguchi method for electrical machine design in recent years. However, for the large community of electrical machine designers, this method is still less known. The purpose of this paper is to summarise the past and current research work of applying the Taguchi method in electrical machine designs. We attempt to give readers some insight into the advantages and disadvantages, challenges, current status and future perspective of the method.

The change of variable formula, or Ito's rule, is studied in a Dedekind complete vector lattice E with weak order unit E. Using the functional calculus we prove that for a Holder continuous semimartingale X t = X a + M t + B t , t ∈ J , and a twice continuously differentiable function f, the formula (0.1) f ( X t ) = f ( X a ) + ∫ 0 t f ′ ( X s ) d M s + ∫ 0 t f ′ ( X s ) d B s + 1 2 ∫ 0 t f ″ ( X s ) d 〈 M 〉 s , 0 ≤ s ≤ t ∈ J holds. The first integral in the formula is an Ito integral with reference to the local martingale M and the second and third integrals are Dobrakov-type integrals of a vector valued function with reference to a vector valued measure. Using the formula, we prove Levy's characterization of Brownian motion as being a continuous martingale with compensator tE. The proof of this result yields a concrete description of abstract Brownian motion defined in vector lattices.

In recent years, global warming and climate change have become international issues for both industrialized and developing countries. Increasingly we will need to understand and manage our Greenhouse Gas (GHG) risks in order to comply with national and regional policies aimed at reducing GHG emissions. It is for these reasons that it is fast becoming critical to know which processes cause GHG emissions and how much they are causing. This article will describe the link that exists between processes and GHG emissions. As a demonstration, the article will describe how these GHG emissions was generated during the 2003 World Summit on Sustainable Development (WSSD) and how a model was developed to determine what the GHG emissions were during the WSSD. The GHG study, and subsequent model development, was done in order to keep the WSSD in line with its principles for the ecologically sound management of the environment and the issue of climate change. It was proposed that the WSSD be made carbon neutral. This meant that all the GHG (and thus carbon or carbon equivalent) emission generated by actions of the WSSD be offset over a period of time. In order to offset the GHG emissions of the WSSD it was essential to have a good assessment of the amount of emissions that was generated during the Summit. An emission Footprint model was developed, based on information obtained throughout the Summit. The method used a number of resources to determine the emissions resulting from delegate air travel to and from the host city, road travel to and from Summit venues, energy consumption at hotels and venues and waste generation amongst others. This paper will provide the critical factors that influenced and contributed towards the model. The results of the model will also be provided and discussed.

The processes that were followed to develop the baseline to Measure and Verify (M&V) a Municipal Demand Side Management (DSM) water pumping project that is being implemented is described in this paper. This paper is a follow-up on a previous paper presented at the ICUE 2004 (Measurement and Verification of a Municipal Water Pumping Project). The previous paper described the M&V process and the methodology that would be used to develop the baseline for the project. The project is currently in the implementation phase. To develop the baseline, energy data was recorded for all the pumps as well as the total flow from the pump station. The baseline was developed by determining an average 30 minute weekday, Saturday and Sunday profile. The baseline also includes a relation between daily water pumped and electricity consumption. Therefore, the baseline can be adjusted if the total amount of water pumped daily is lower or higher than the average values used. This will ensure that the baseline takes possible load growth or possible load reduction into consideration. The baseline will be used to determine the impact of the project after implementation.

In the setting of a Dedekind complete Riesz space on which a conditional expectation is defined, we study the Ito integral. This integral obtains the integration of a stochastic process of a continuous parameter relative to a martingale. A considerable part of the paper is devoted to aspects of integration of a vector-valued function with respect to a vector measure. Here we use the Dobrakov integral that is, in our case, a generalization of the well known Bartle integral. We discuss natural and predictable processes to prove a general version of the Doob–Meyer decomposition of a submartingale. This decomposition provides an essential tool used in the definition of the stochastic integral. We derive the properties of the stochastic integral that are useful in developing the theory of stochastic processes in Riesz spaces.

We define and study order continuity, topological continuity, γ-Holder-continuity and Kolmogorov–Centsov-continuity of continuous-time stochastic processes in vector lattices and show that every such kind of continuous submartingale has a continuous compensator of the same kind. The notion of variation is introduced for continuous time stochastic processes and for a γ-Holder-continuous martingale with finite variation, we prove that it is a constant martingale. The localization technique for not necessarily bounded martingales is introduced and used to prove our main result which states that the quadratic variation of a continuous-time γ-Holder continuous martingale X is equal to its compensator 〈 X 〉 .

Social consideration, assessed using a social life cycle assessment (S-LCA), is a relatively new concept that has yet to be standardised. Attempts at measuring social sustainability in pavement management have been made in South Africa, using social impact assessments (SIAs) and empowerment impact assessment models (EmpIAs). However, these models only focus on certain social considerations and do not incorporate holistic social sustainability in evaluations. The first response to these challenges is to identify and secure universal acceptance for indicators which measure social impacts of pavements and the broader impacts of technical and managerial choices in pavement infrastructure provision. These indicators may then be used to develop a situational- and location-specific social life cycle inventory (S-LCI).This study starts by identifying key social indicators in pavement infrastructure provision and proposes a framework for an S-LCA. Potential indicators were sourced from a large database, focusing on indicators most aligned with social sustainability. Indicators were assessed and scored using an adapted methodology and refinement was conducted through sensitivity analyses employing Bayesian-based Monte Carlo simulations. By allowing weightings and scores of sub-goals and criteria to be changed, the results reflect the importance of inputs from local stakeholders on the impacts of sustainability. A worked example is provided to demonstrate its implementation.The framework is envisioned to function as the first version of a living protocol that will be improved on through further research. Although the primary target audience is South African road authorities, the approach can be adapted for use in any country.

Using the spectral measure μ S of the stopping time S , we define the stopping element X S as a Daniell integral ∫ X t d μ S for an adapted stochastic process ( X t ) t ∈ J that is a Daniell summable vector-valued function. This is an extension of the definition previously given for right-order-continuous sub martingales with the Doob-Meyer decomposition property. The more general definition of X S necessitates a new proof of Doob's optional sampling theorem, because the definition given earlier for sub martingales implicitly used Doob's theorem applied to martingales. We provide such a proof, thus removing the heretofore necessary assumption of the Doob-Meyer decomposition property in the result. Another advancement presented in this paper is our use of unbounded order continuity of a stochastic process, which properly characterizes the notion of continuity of sample paths almost everywhere, found in the classical theory.

Social consideration, assessed using a social life cycle assessment (S-LCA), is a relatively new concept that has yet to be standardised. Attempts at measuring social sustainability in pavement management have been made in South Africa, using social impact assessments (SIAs) and empowerment impact assessment models (EmpIAs). However, these models only focus on certain social considerations and do not incorporate holistic social sustainability in evaluations. The first response to these challenges is to identify and secure universal acceptance for indicators which measure social impacts of pavements and the broader impacts of technical and managerial choices in pavement infrastructure provision. These indicators may then be used to develop a situational- and location-specific social life cycle inventory (S-LCI). This study starts by identifying key social indicators in pavement infrastructure provision and proposes a framework for an S-LCA. Potential indicators were sourced from a large database, focusing on indicators most aligned with social sustainability. Indicators were assessed and scored using an adapted methodology and refinement was conducted through sensitivity analyses employing Bayesian-based Monte Carlo simulations. By allowing weightings and scores of sub-goals and criteria to be changed, the results reflect the importance of inputs from local stakeholders on the impacts of sustainability. A worked example is provided to demonstrate its implementation. The framework is envisioned to function as the first version of a living protocol that will be improved on through further research. Although the primary target audience is South African road authorities, the approach can be adapted for use in any country.

Understanding the influence of feed material mineral assemblage on spiral separation is paramount for the successful and consistent operation of a spiral plant. Plant stability is required to maintain high recovery of valuable heavy minerals (VHM). Standard material analysis methods used in the heavy mineral industry to evaluate spiral separation behaviour are unable to quantify performance differences in the case of large variations in feed assemblage. This study illustrates a systematic approach to evaluate spiral separation performance. This technique was applied on a four-stage spiral plant. The performance information was used in a circuit simulation to clearly illustrate the importance of correct setting of the spiral splitter position and resulting spiral mass loading to ensure optimal circuit stability and maximum VHM recovery.

The different definitions for Markov processes used in the classical case are studied in the abstract setting of vector lattices where they are not all equivalent. Strong Markov processes are defined and it is shown that a Brownian motion is a strong Markov process. This fact is used in a proof that a Brownian filtration is right-continuous. This holds in the classical case only for the augmentation of the Brownian filtration, but in the abstract case the augmented filtration is not larger than the original one.

In this paper, a robust design framework is proposed to mitigate torque ripple for line-start permanent magnet synchronous machines (LS-PMSM) by using the Taguchi method. The framework is intended for fine-tuning initial optimum designs to further improve the steady-state torque quality of LS-PMSMs. The proposed framework was successfully implemented on an LS-PMSM design. A notable decrease in steady-state torque ripple was achieved without a significant reduction in steady-state performance and transient load synchronization capability. It has been shown that the proposed robust torque ripple mitigation framework is both functional and time efficient and can be applied to a wide range of electrical machines.

Improvements in Internet of Things (IoT) enabling technology lead to increased potential for creating smart and safe cities for the future. While many first world countries already reap the benefits of this technology, developing countries, specifically those in Sub-Saharan Africa, still need to overcome significant barriers before experiencing the same value. Two of these barriers are a) existing network infrastructure and b) limited financial backing to implement a stand-alone IoT network. In most African cities repeated and extensive cable theft lead to the degradation of the fixed line infrastructure to such an extent that operators are reluctant to replace copper or fibre cables. The uptake of wireless technology, however, increased significantly. While cellular communication technology is prevalent in Africa, it should be noted that in most towns and cities this means a third-generation (3G) or earlier implementation. If an IoT deployment were to be considered for this environment, this should be taken into account. In this paper, a capacity estimation is performed for a typical town in South Africa, using the existing cellular technology as an input parameter. As a small initial step towards the creation of a smart city, the case of using IoT technology for traffic light management is considered in a simulation environment. The results of the simulation verify that the current network can accommodate the load of this implementation and the maximum number of devices that can communicate using the current infrastructure is calculated.

Several recent studies define food insecurity as a situation where the availability of nutritionally adequate and safe foods or the ability to acquire acceptable foods in socially acceptable ways is limited or uncertain. To overcome the challenges of food insecurity household’s employ certain Coping Strategies to mitigate food shortages. A quantitative research method was deployed and a stratified random sample of 600 households in two low income neighborhoods was included during a study conducted in 2015, to measure food insecurity, coping strategies and dietary diversity. The study found that households employed coping strategies to mitigate food shortage, but this leads to low dietary diversity. The study found that the Coping Strategy to “Buy only necessities”, “skip meals” and “purchase food on credit” is employed by a significant number of households. The study found that these coping strategies are associated with lower dietary diversity. This study aimed to increase the general understanding of food insecurity in low-income areas, and how coping strategies impact on dietary diversity in the context of food insecure households The study concluded that although households may use coping strategies to mitigate the impact of food shortages it will directly impact on low dietary diversity with health consequences. In this context, there may be desperate need in low income neighborhoods to amend policy to include a more comprehensive approach that includes adequate information to households on health consequences of low dietary diversity. KEYWORDS: Food Insecurity, Coping Strategies, Economic Development

The use of automated network planning systems is crucial for reducing the deployment cost and planning time of passive optical telecommunication networks. Mixed integer linear programming is well suited for the purpose of modelling passive optical networks; however, excessive computing times for solving large-scale problem instances render these approaches impractical. In this paper, an arc-based, a path-based, and a composite integer linear programming formulation of the passive optical network planning problem are considered. A reduction in computing times and peak memory usage is obtained by applying multiple heuristics as warm-starts to these problem formulations. Finally, the computational results presented in this paper are based on real-world Geographic Information System data — more specifically, a neighbourhood in Potchefstroom, South Africa.

Permanent-magnet synchronous machines (PMSMs) are well suited for high-speed (HS) applications due to their high efficiency, power density, and dynamic response capability. The heat extraction area decreases as the speed increases, making thermal effects more dominant at high speed. The temperature-dependent properties of permanent magnets necessitate high-detail thermal models. This paper presents a 2-D analytical model for a HS PMSM magnet. The diffusion equation is solved where three of the PM boundaries experience convection heat flow; as the case is in radial flux machines. The heat generated on the rotor surface due to eddy currents is also taken into account. The model is verified using numerical techniques and shows good correlation (within 1.5%). The model is also validated through experiments performed on a 4 kW, 30 000 r/min PMSM.

The Ito integral for Brownian motion in a vector lattice, as constructed in Part 1 of this paper, is extended to accommodate a larger class of integrands. This extension provides an analogue of the indefinite Ito integral in the classical setting which yields a local martingale. The assumption is that there exists a conditional expectation operator on the vector lattice and the construction does not depend on a probability measure space. The classical case of the extended Ito integral is a special case of the constructed integral in the vector lattice.