The ability of a lubricating oil to reduce friction in mechanical surfaces which are in relative sliding motion depends on the base oil behaviour. Previous studies have demonstrated that temperature has a significant influence on the friction behaviour of mineral and synthetic base oils by using a laboratory based friction testing machine. However, the effect of a constantly changing load under different temperature conditions has not been explored fully. In this study, the effect of an increasing load on the friction behaviour of four six different mineral base oils and a polyalphaolefin (PAO) base oil were studied using the SRV4® tribometer. The sliding surfaces were AISI 52100 steel ball and disc. The average loads (range: 50 – 250 N), temperatures (range: 40 – 120 oC), relative humidity of 20 % and a sliding speed of 0.2 m.s-1 were selected as the test conditions. The seven base oils were selected from four API base oil groups. Stribeck curves were used as a tool to characterize the friction behaviour of the base oils. The results show that for all the base oils, the coefficient of friction and the Stribeck parameter decrease gradually with the increase in applied normal load under constant temperature conditions. The increase in temperature increased the coefficient of friction and decreased the Stribeck parameter at each load stage. The external friction mechanisms dominated the friction behaviour under all test conditions. Viscosity showed a strong influence on the film forming characteristics of the seven base oils only at 40 and 60 oC. Between 80 and 120 oC, the oil-surface interactions were predominant. The results further demonstrated that effect of an increasing temperature on the coefficient of friction was bigger between 80 and 100 oC for all Group III base oils and was consistent between 40 and 120 oC for the Group III+ and PAO base oil. The highly saturated (PAO and Group III+) base oils have demonstrated good thermal stability and less reactivity compared to the less saturated base oils (GI and GIII) under all test conditions. The friction behaviour of the PAO base oil was the most affected by the presence of dissolved water. The presence of water proved to increase the friction at the sliding steel interfaces. / Dissertation (MEng)--University of Pretoria, 2018. / Chemical Engineering / MEng / Unrestricted

The literature on compressive parameter estimation has been mostly focused on the use of sparsity dictionaries that encode a discretized sampling of the parameter space; these dictionaries, however, suffer from coherence issues that must be controlled for successful estimation. To bypass such issues with discretization, we propose the use of statistical parameter estimation methods within the Approximate Message Passing (AMP) algorithm for signal recovery. Our method leverages the recently proposed use of custom denoisers in place of the usual thresholding steps (which act as denoisers for sparse signals) in AMP. We introduce the design of analog denoisers that are based on statistical parameter estimation algorithms, and we focus on two commonly used examples: frequency estimation and bearing estimation, coupled with the Root MUSIC estimation algorithm. We first analyze the performance of the proposed analog denoiser for signal recovery, and then link the performance in signal estimation to that of parameter estimation. Numerical experiments show significant improvements in estimation performance versus previously proposed approaches for compressive parameter estimation.

Synthetic biology endeavors to forward engineer genetic circuits with novel function. A major inspiration for the field has been the enormous success in the engineering of digital electronic circuits over the past half century. This dissertation approaches synthetic biology from the perspective of the engineering design cycle, a concept ubiquitous across many engineering disciplines. First, an analysis of the state of the engineering design cycle in synthetic biology is presented, pointing out the most limiting challenges currently facing the field. Second, a principle commonly used in electronics to weigh the tradeoffs between hardware and software implementations of a function, called co-design, is applied to synthetic biology. Designs to implement a specific logical function in three distinct domains are proposed and their pros and cons weighed. Third, automatic transitioning between an abstract design, its physical implementation, and accurate models of the corresponding system are critical for success in synthetic biology. We present a framework for accomplishing this task and demonstrate how it can be used to explore a design space. A major limitation of the aforementioned approach is that adequate parameter values for the performance of genetic components do not yet exist. Thus far, it has not been possible to uniquely attribute the function of a device to the function of the individual components in a way that enables accurate prediction of the function of new devices assembled from the same components. This lack presents a major challenge to rapid progression through the design cycle. We address this challenge by first collecting high time-resolution fluorescence trajectories of individual cells expressing a fluorescent protein, as well as snapshots of the number of corresponding mRNA molecules per cell. We then leverage the information embedded in the cell-cell variability of the population to extract parameter values for a stochastic model of gene expression more complex than typically used. Such analysis opens the door for models of genetic components that can more reliably predict the function of new combinations of these basic components. / Ph. D.

abstract: Cancer is a disease involving abnormal growth of cells. Its growth dynamics is perplexing. Mathematical modeling is a way to shed light on this progress and its medical treatments. This dissertation is to study cancer invasion in time and space using a mathematical approach. Chapter 1 presents a detailed review of literature on cancer modeling. Chapter 2 focuses sorely on time where the escape of a generic cancer out of immune control is described by stochastic delayed differential equations (SDDEs). Without time delay and noise, this system demonstrates bistability. The effects of response time of the immune system and stochasticity in the tumor proliferation rate are studied by including delay and noise in the model. Stability, persistence and extinction of the tumor are analyzed. The result shows that both time delay and noise can induce the transition from low tumor burden equilibrium to high tumor equilibrium. The aforementioned work has been published (Han et al., 2019b). In Chapter 3, Glioblastoma multiforme (GBM) is studied using a partial differential equation (PDE) model. GBM is an aggressive brain cancer with a grim prognosis. A mathematical model of GBM growth with explicit motility, birth, and death processes is proposed. A novel method is developed to approximate key characteristics of the wave profile, which can be compared with MRI data. Several test cases of MRI data of GBM patients are used to yield personalized parameterizations of the model. The aforementioned work has been published (Han et al., 2019a). Chapter 4 presents an innovative way of forecasting spatial cancer invasion. Most mathematical models, including the ones described in previous chapters, are formulated based on strong assumptions, which are hard, if not impossible, to verify due to complexity of biological processes and lack of quality data. Instead, a nonparametric forecasting method using Gaussian processes is proposed. By exploiting the local nature of the spatio-temporal process, sparse (in terms of time) data is sufficient for forecasting. Desirable properties of Gaussian processes facilitate selection of the size of the local neighborhood and computationally efficient propagation of uncertainty. The method is tested on synthetic data and demonstrates promising results. / Dissertation/Thesis / Doctoral Dissertation Applied Mathematics 2020

A vertex cover of a given graph is a vertex set including at least one endpoint from every edge. A vertex cover number τ is the size of a minimum vertex cover. If the vertices from a vertex cover are required to induce a connected subgraph, the resulting set is called a connected vertex cover. The corresponding parameter τc is called a connected vertex cover number. The decision versions of both problems are NP-complete. To better understand a relation between these two vertex cover numbers, Cardinal and Levy define the price of connectivity as a ratio between τc and τ. It is not surprising that determining whether the price of connectivity of a given graph is at most t is NP- hard. The notion of price of connectivity can be extended for more graph properties, such as for the dominating set. The price of connectivity has already been investigated in several papers, with some focusing on critical graphs whose price of connectivity is strictly greater than the price of connectivity of every induced subgraph. This thesis provides an overview of the current state of research into the price of connectivity. Moreover, we focus on the structural properties of critical graphs for the price of connectivity for vertex cover and discuss a possible characterization of graphs in which the price of connectivity for a...

The main goal in seismic exploration is to identify locations of hydrocarbons reservoirs and give insights on where to drill new wells. Therefore, estimating an Earth model that represents the right physics of the Earth's subsurface is crucial in identifying these targets. Recent seismic data, with long offsets and wide azimuth features, are more sensitive to anisotropy. Accordingly, multiple anisotropic parameters need to be extracted from the recorded data on the surface to properly describe the model. I study the prospect of applying a scattering integral approach for multi-parameter inversion for a transversely isotropic model with a vertical axis of symmetry. I mainly analyze the sensitivity kernels to understand the sensitivity of seismic data to anisotropy parameters. Then, I use a frequency domain scattering integral approach to invert for the optimal parameterization. The scattering integral approach is based on the explicit computation of the sensitivity kernels. I present a new method to compute the traveltime sensitivity kernels for wave equation tomography using the unwrapped phase. I show that the new kernels are a better alternative to conventional cross-correlation/Rytov kernels. I also derive and analyze the sensitivity kernels for a transversely isotropic model with a vertical axis of symmetry. The kernels structure, for various opening/scattering angles, highlights the trade-off regions between the parameters. For a surface recorded data, I show that the normal move-out velocity vn, ƞ and δ parameterization is suitable for a simultaneous inversion of diving waves and reflections. Moreover, when seismic data is inverted hierarchically, the horizontal velocity vh, ƞ and ϵ is the parameterization with the least trade-off. In the frequency domain, the hierarchical inversion approach is naturally implemented using frequency continuation, which makes vh, ƞ and ϵ parameterization attractive. I formulate the multi-parameter inversion using the scattering integral method. Application to various synthetic and real data examples show accurate inversion results. I show that a good background ƞ model is required to accurately recover vh. For 3-D problems, I promote a hybrid approach, where efficient ray tracing is used to compute the sensitivity kernels. The proposed method highly reduces the computational cost.

In this experiment, rats were administered nicotine (0.3 mg/kg) for 11 consecutive days before and after an electrolytic medial frontal cortex lesion. After drug administration ceased, rats were tested on two spatial memory tasks, the radial arm maze (RAM) and the Morris water task (MWT). Behavioral testing was arranged so that rats were tested on the RAM 1 day after drug administration followed by behavioral testing on the MWT 19 days after drug treatment, or tested on the MWT 1 day after drug administration followed by testing on the RAM 4 days after drug treatment. Results of MWT testing showed that regardless of the drug/behavioral testing interval, lesioned rats given nicotine demonstrated enhancement relative to saline-treated lesioned animals, but the effects were more robust 1 day after drug treatment had ceased. Nicotine-induced behavioral compensation after medial frontal cortex lesions appears to be time-dependent in animals behaviorally tested on the MWT. Results of RAM testing showed that there were no significant differences between lesioned groups at the 1-day drug/testing interval, although nicotine improved performance in non-lesioned rats compared to non-lesioned rats given saline. Four days after drug administration, nicotine improved performance in lesioned rats to the levels of non-lesioned rats given saline or nicotine. This result suggests that previous training on the MWT may have primed behavioral compensation produced by nicotine in medial frontal cortex lesioned rats behaviorally tested on the RAM.

This paper investigates the viability of two different mappings of two parameters of the digital musical instrument Force Ghost. The instrument produces sound by having an  ambience (a recording of rain or of waves on the beach) filtered by bandpass filters  whose center-frequencies are controlled by a midi-keyboard. Five bandpass filters are assigned to each note, corresponding to the fundamental frequency its and its multiples (2f,3f,4f,5f). The mapped parameters are the Q-factor of the bandpass filters and the timbre, defined as the relative level between the even and odd multiples harmonics. These two parameters are mapped to the modulation wheel and the pitch bend wheel. The mappings of the parameters are investigated with the help of musical tasks completed by musicians rounded up with semi-structured interviews. The interviews revealed that the modulation wheel was to be prefered due to the lack of a spring mechanism (which is an attribute of the pitch bend wheel), forcing the wheel back to its default position (in the middle) when released. The results from the musical tasks suggested an indication that none of the sensors have better controllability than the other, regardless of parameter it controls. In conclusion, a sensor that gravitates towards a resting state does not seem to be suitable to control a parameter (scaling) that lacks a “resting value” (as perceived by musicians). / Denna artikel utreder två mappningar av två parametrar hos det digitala musikaliska instrumentet Force Ghost. Instrumentet ljuder genom att en ljudkälla filtreras av bandpassfilter. Ljudkällan i detta fall är ljudet av regnfall i en skog. Varje tangent på ett keyboard är kopplat till minst ett bandpassfilter, vars MIDI-not kopplat till motsvarande frekvens. Denna frekvens är bandpassfiltrets centerfrekvens. När en tangent nedtrycks genereras bandpassfiltret, vilket skapar en ton ur ljudkällan. De två parametrarna i fokus är kopplade till bandpassfiltrerna. De är Q-värdet (kopplat till bandpassfiltrernas bandbredd) och klangfärgen (kopplat till övertonerna; vilka de är och deras amplitudrelation för varje not). Dessa två parametrar är mappade till modulations-hjulet och pitchbend-hjulet. Mappningen av dessa parametrar är undersökt genom musikuppgifter och självständig utforskning genomförda av musiker. Detta spelades in och sedan utfördes en semistrukturerad intervju med musikerna. Intervjuerna visade att modulations-hjulet föredrogs på grund av avsaknaden av fjädermekanismen som finns hos pitchbend-hjulet. Denna mekanism tvingar pitchbend-hjulet tillbaka till sin utgångsposition (i mitten) när den släpps. Resultaten från musikuppgifterna indikerar att ingen av sensorerna har bättre kontrollbarhet än den andre, oavsett vilket parameter den kontrollerar. Sammanfattningsvis, en sensor som graviterar mot ett viloläge verkar inte vara lämplig för att kontrollera en parameter (-skalning) som saknar ett “vilovärde” (så som uppfattat av musiker).

The parameter setting problem is part of a complex, automated process for customizing Scania's products; primarily trucks and buses. The problem is modelled as a stateless, acyclic graph of pure functions and variables. A subset of a deterministic, concurrent, demand-driven, declarative programming model is implemented under the Microsoft .NET framework. The implementation is evaluated based on suitability for solving the parameter setting problem, computational performance and general applicability within the organization. It is concluded that the model reduces the complexity of the parameter setting problem, mainly due to demand-driven (lazy) execution. The implementation scales as expected on sequential programs in time and memory with respect to input size. Parallel programs benefit partly from parallelism but bottlenecks in the .NET framework seem to limit the speedup. The general applicability of the programming model within the organization is potentially high and there are many extensions that can be added in the future, such as constraint programming. / Parametersättning är en del av en komplex, automatiserad process för att specialanpassa Scanias produkter – primärt lastbilar och bussar. Problemet är modellerat som en tillståndslös acyklisk graf av rena funktioner och variabler. En deterministisk, parallel, behovstyrd deklarativ programmeringsmodell har implementeras under Microsoft .NET-ramverket. Implementationen utvärderas utifrån lämplighet för parametersättning, prestanda och generell nytta inom organisationen. Modellen lyckas med att reducera komplexiteten för parametersättning, primärt tack vare behovstyrd (lat) exekvering. Implementationen skalar i både tid och minne i enlighet med förväntningarna för sekventiella program. Parallella program har delvis nytta av multipla processorkärnor men flaskhalsar i .NET-ramverket verkar begränsa prestandan. Programmeringsmodellens generella nytta inom organisationen är potentiellt hög och det finns många tillbyggnader som kan läggas till i framtiden, såsom villkorsprogrammering.

Generic simulations of tremor propagation through the upper limb have been achieved using a previously developed postural tremor model, but this model had not yet been compared with experimental data or utilized for subject-specific studies. This work addressed these two issues, which are important for optimizing peripheral tremor suppression techniques. For tractability, we focused on a subsystem of the upper limb: the isolated wrist, including the four prime wrist muscles (extensor carpi ulnaris, flexor carpi ulnaris, extensor carpi radialis, and flexor carpi radialis) and the two degrees of freedom of the wrist (flexion-extension and radial-ulnar deviation). Muscle excitation and joint displacement signals were collected while subjects with Essential Tremor resisted gravity. System identification was implemented for three subjects who experienced significant tremor using two approaches: 1. Generic linear time-invariant (LTI) models, including autoregressive-exogenous (ARX) and state-space forms, were identified from the experimental data, and characteristics including model order and modal parameters were compared with the previously developed postural tremor model; 2. Subject-specific parameters for the previously developed postural tremor model were directly estimated from experimental data using nonlinear least-squares optimization combined with regularization. The identified LTI models fit the experimental data well, with coefficients of determination of 0.74 ± 0.18 and 0.83 ± 0.13 for ARX and state-space forms, respectively. The optimal model orders identified from the experimental data (4.8 ± 1.9 and 6.4 ± 1.9) were slightly lower than the orders of the ARX and state-space forms of the previously developed model (6 and 8). For each subject, at least one pair of identified complex poles aligned with the complex poles of the previously developed model, whereas the identified real poles were assumed to represent drift in the data rather than characteristics of the system. Subject-specific parameter estimates reduced the sum of squared-error (SSE) between the measured and predicted joint displacement signals to be between 10% and 50% of the SSE using generic literature parameters. The predicted joint displacements maintained high coherence at the tremor frequency for flexion-extension (0.90 ± 0.10), which experienced the most tremor. We successfully applied multiple system identification techniques to identify tremor propagation models using only tremorogenic muscle activity as the input. These techniques identified model order, poles, and subject-specific model parameters, and indicate that tremor propagation at the wrist is well approximated by an LTI model.