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Creeping bentgrass (Agrostis stolonifera L.) is commonly used on golf course greens and fairways in cool-humid regions but is plagued by numerous fungal diseases, one of which is dollar spot disease (Sclerotinia homoeocarpa F. T. Bennett). Dollar spot occurs frequently throughout the growing season requiring biweekly fungicide applications for complete control. The objective of this study was to investigate methods of reducing the number of fungicide applications needed to maintain dollar spot at acceptable levels through dew removal and potential mechanisms of resistance in bentgrass. In the first study, a combination of mowing three times a week and dragging by hose the remaining four days to remove dew was used in an attempt to reduce disease severity. The main effect of this combination treatment was not significant (p>0.05) and did not reduce the number of fungicide applications compared to normal mowing three times a week. However, dollar spot was managed curatively with 20-80% fewer applications compared to a normal preventative fungicide program. In the second experiment, two experimental germplasms with varying disease resistance were tested for the possible production of antifungal compounds known as phytoanticipins. Preliminary results indicate the resistant line may contain compounds not present in the susceptible line.

Pleasure is part of hedonic well-being, with roots back to Epicurus 2000 years ago. With the new evolving neuroscientific methods of the late 20th and beginning of the 21st century, we are now able to study the biological components of pleasure. This thesis aims to review empirical studies on the neural correlates of pleasure, which can have important implications for well-being, and treatment of addiction and affective disorders. Recent studies have suggested that pleasure can be separated into coding and causing. Discoveries show that causing of pleasure is created in so called hedonic hot spots, areas of the brain that intensely creates pleasure in the shell of nucleus accumbens and in the ventral pallidum. Areas that codes pleasure on the other hand is represented into more cortical areas of the brain, including orbitofrontal cortex, anterior cingulate cortex and anterior insular cortex. There has been a growing understanding about how pleasure is represented in the brain, and a discussion on interpretations and limitations are provided followed by future research suggestions in the final section.

Turbulence is ubiquitous in naturally-occurring and man-made flows. Despite its importance in scientific and engineering applications, the transition from smooth laminar flow to disorganized turbulent flow is poorly understood. In some cases, the transition can be understood in the context of linear stability theory, which predicts when the underlying laminar solution will become unstable as a parameter is varied. For a large class of flows, however, this approach fails spectacularly, with theory predicting that the laminar flow is stable but experiments and simulations showing the emergence of spatiotemporal complexity. In this dissertation, the direct or subcritical transition to turbulence in Taylor-Couette flow (i.e., the flow between independently rotating co-axial cylinders) is studied experimentally. Chapter 1 discusses different scenarios for the transition to turbulence and recent advances in understanding the subcritical transition within the framework of dynamical systems theory. Chapter 2 presents a comprehensive review of earlier investigations of linearly stable Taylor-Couette flow. Chapter 3 presents the first systematic study of long-lived super-transients in Taylor-Couette flow with the aim of determining the correct dynamical model for turbulent dynamics in the transitional regime. Chapter 4 presents the results of experiments regarding the stability of Taylor-Couette flow to finite-amplitude perturbations in the form of injection/suction of fluid from the test section. Chapter 5 presents numerical investigations of axisymmetric laminar states with realistic boundary conditions. Chapter 6 discusses in detail the implementation of time-resolved tomographic particle image velocimetry (PIV) in the Taylor-Couette geometry and presents preliminary tomographic PIV measurements of the growth of turbulent spots from finite-amplitude perturbations. The main results are summarized in Chapter 7.

The synthetic aperture radar (SAR) onboard Earth observing satellites has been acknowledged as an integral tool for many applications in monitoring the marine environment. Some of these applications include regional sea-ice monitoring and detection of illegal or accidental oil discharges from ships. Nonetheless, a practicality of the usage of SAR images is greatly hindered by the presence of speckle noises. Such noise must be eliminated or reduced to be utilized in real-world applications to ensure the safety of the marine environment. Thus this thesis presents a novel two-phase total variation optimization segmentation approach to tackle such a challenging task. In the total variation optimization phase, the Rudin-Osher-Fatemi total variation model was modified and implemented iteratively to estimate the piecewise smooth state by minimizing the total variation constraints. In the finite mixture model classification phase, an expectation-maximization method was performed to estimate the final class likelihoods using a Gaussian mixture model. Then a maximum likelihood classification technique was utilized to obtain the final segmented result. For its evaluation, a synthetic image was used to test its effectiveness. Then it was further applied to two distinct real SAR images, X-band COSMO-SkyMed imagery containing verified oil-spills and C-band RADARSAT-2 imagery mainly containing two different sea-ice types to confirm its robustness. Furthermore, other well-established methods were compared with the proposed method to ensure its performance. With the advantage of a short processing time, the visual inspection and quantitative analysis including kappa coefficients and F1 scores of segmentation results confirm the superiority of the proposed method over other existing methods.

我國都市發展中，土地利用型態的迅速改變，然而，任何不當或過量的開發均會加速自然生態地區的喪失和經濟資源的浪費。因此，為促進土地資源合理配置，決策規劃者將更需要即時性空間資料的輔助，以有效掌握環境資源變化的情形，拉近都市規劃與實際發展間之差距。 本研究應用四時期SPOT衛星影像遙測技術於大面積土地的探測，並進行監督式影像分類獲取研究區四個時期的土地覆蓋分類成果圖，再配合當地人口之統計資料以及都市計畫之相關圖資，將此空間與屬性資料建構至地理資訊系統中，藉以瞭解都市發展的過程與規律，進而提出都市未來可能的發展方向和趨勢，以提供都市計畫擬訂者科學且客觀的輔助資料，作為其制訂都市整體規劃、動態監測都市發展和及時修正規劃之參考依據。

L'estemfiliosi de la perera és una malaltia fúngica ocasionada pel fong Deuteromicet Stemphylium vesicarium. Els símptomes característics d'aquesta malaltia són lesions necròtiques en fulles i fruits, provocant el depreciament econòmic d'aquests últims. Si les condicions climàtiques són favorables aquesta malaltia pot arribar a provocar la pèrdua total de la producció. La malaltia es localitza bàsicament en la conca mediterrània, sent les zones fructícoles de Girona a Catalunya i Emilia-Romagna a Itàlia els llocs on les pèrdues de producció són més grans. Actualment l'únic mètode de control és la cobertura permanent dels òrgans de la planta amb fungicides. Per obtenir aquesta protecció és necessari realitzar aplicacions preventives amb una cadència fixa, setmanal o quinzenal, de diferents fungicides en els arbres. Aquesta cadència d'aplicació comporta que al llarg del període vegetatiu de la perera es realitzin entre 20 i 25 aplicacions de fungicida, per cadències setmanals, o entre 10 i 13 aplicacions si la cadència és quinzenal. Aquest elevat nombre de tractaments comporta uns efectes toxicològics a nivell mediambiental i per a la salut humana, un augment del cost econòmic de la producció i en alguns casos afavorir l'aparició de resistències del patogen a determinats fungicides. Molts d' aquests tractaments es realitzen sense que les condicions ambientals siguin favorables a l'inici d'infeccions del fong, i són per tant innecessàries. Amb l'objectiu d'obtenir una eina per determinar el risc d'infeccions en funció de les condicions climàtiques i realitzar d'aquesta manera els tractaments amb fungicides només quan són necessaris, es va elaborar el Sistema pel Tractament Racionalitzat de l'Estemfiliosi de la Perera (STREP). El model consisteix en relacionar quantitativament amb la severitat de la malaltia els paràmetres climàtics de durada del període d'humectació i temperatura mitjana durant aquests períodes. En aquest treball s'ha determinat l'eficàcia en el control de la malaltia per diferents fungicides aplicats de manera preventiva amb una cadència fixa en diferents finques comercials i durant varis anys. S'ha constatat que no hi ha cap producte totalment eficaç en el control de la malaltia, sent l'eficàcia obtinguda mitjana. Aquesta eficàcia de control esta en funció del nivell de pressió de la malaltia, obtenint eficàcies inferiors quan el nivell en els testimonis no tractats és elevat. En assajos en condicions controlades s'ha determinat que els fungicides analitzats aplicats de manera curativa o postinfecciosa, quan ja s'han iniciat les infeccions, presenten una eficàcia més baixa que quan s'apliquen preventivament. El tiram és el producte amb una eficàcia més elevada en la major part de les condicions experimentals. S' ha analitzat durant 5 anys, 1992-1996, en diferents plantacions de perera de Girona, la dinàmica dels paràmetres ambientals de durada deis períodes amb humectació, la temperatura mitjana de l'aire, la temperatura mitjana durant els períodes d'humectació, la durada dels períodes amb humitat relativa superior al 90% i la pluviometria. S 'ha constatat que la humectació deguda a la rosada és la principal causa d'humectació i que és un procés lent i continu. Les durades més freqüents d'humectació han estat períodes inferiors a 12 hores i les temperatures més freqüents durant aquests períodes han estat entre 11 i 21°C. S'ha determinat també que existeixen períodes amb humitat relativa elevada però sense formació de pel·lícula d'aigua i s'ha observat que ocasionalment existeixen períodes breus d'interrupció de la humectació en que poden existir humanitats relatives elevades o baixes.La capacitat predictiva del model STREP ha estat avaluada mitjançant 42 assajos en condicions naturals i controlades, determinant que en més del 95 % dels casos avaluats les prediccions de malaltia s'han correspost amb les observades, i que només en dos casos el model ha infraestimat el nivell de risc d'infecció. Demostrant així que el model STREP és fiable en les seves prediccions. S'ha estudiat l'efecte de la humitat relativa durant els períodes interromputs d'humectació i les durades d'aquests períodes, en les infeccions produïdes pel fong. S'ha constatat que el model STREP hauria d'incorporar com a períodes separats els períodes d'humectació interromputs amb relatives elevades (>98%) s'haurien de considerar com a períodes continus. Per una altra banda s'ha comprovat que els períodes amb humitats relatives elevades sense formació d'humectació en condicions naturals no són suficients per provocar l'inici d'infeccions de S. Vesicarium.S'ha utilitzat el model STREP com a eina per guiar els tractaments fungicides en diferents parcel·les de finques comercials durant dos anys. D'aquests assajos es pot concloure que utilitzant valors de risc acumulat SA:0.4 com a llindar per a realitzar els tractaments es controla la malaltia amb una eficàcia semblant als tractaments setmanals, però amb una reducció del nombre d'aplicacions necessàries entre un 25 i un 50%. Utilitzar un llindar SA:0.6 en finques amb varietats sensibles i una pressió d'inòcul del patogen elevada presenta bons resultats però inferiors als obtinguts amb tractaments setmanals, no obstant l'estalvi de tractaments ha estat molt important (50-70%).De tots aquests resultats es conclou que el model STREP és adequat per ésser utilitzat en programes pilot a escala comercial en el control racional de l'estemfiliosi de la perera. En funció d'aquests resultats es considerarà la seva implementació en Estacions d'Avisos Fitosanitaris. / Brown spot of pear, caused by Stemphylium vesicarium, is an important disease in fruit-growing areas of Europe, mainly in Girona (Catalonia) and Emilia-Romagna (Italy). Infections and necrosis occur on leaves and fruits. If the environmental conditions are favourable for the disease, the loss of production will be very high. The control of brown spot of pear is based on protecting sprays of fungicide applied, al 7-to 15-day intervals depending on the type of fungicide. The high number of fungicide applications needed to maintain acceptable levels of disease can produce toxicological effects on ecosystems, humans and increased costs of pear production. We have determined the efficacy of disease control by different fungicides, sprayed with a preventive strategy in 3 trials during 2 years. None of the fungicides showed high efficacy of disease control, and the efficacy was related to the disease level. Experiments under controlled-conditions showed that treatments done with post-¬infection strategies have a low efficacy. Thiram was the fungicide with better efficacy for both preventive and after-infection strategies. During five years,1992-1996, we studied the dynamics of environmental conditions of wetness period, temperature, high relative humidity period (>90%) and rainfall. The most frequent wetness periods were shorter than 12h. The temperature during these periods was between 11-21°C. There were periods with high relative humidity but without wetness formation, and there were also wetness periods interrupted by dry periods. The relative humidity during these dry periods was high or low. The research has been focused to eliminate unnecessary sprays, and an infection model for S. vesicarium (STREP) was previously developed, which quantifies the effect of wetness duration and temperature on the severity of infection by S. vesicarium. The model was evaluated in 42 field trials and was validated in relation lo its capacity to predict the intensity of disease. Most part of disease level predictions (95%) were coincident with disease levels observed, showing that STREP model was a reasonable good predictor. We studied the effect of relative humidity during interrupted wetness periods, and the effect on disease progression of periods with high relative humidity but without wetness on disease levels. Interrupted periods with low relative humidity can be considered as two separated periods, but if the relative humidity is high (>98 %) it can be considered as a continuous period. Periods shorter than 12-18 h with high relative humidity but without wetness were insufficient to start infections. The STREP model was evaluated during two years and was used for scheduling treatments with fungicides, and showed that the efficacy with SA:0.4 threshold was similar to weekly sprays, but saving 25-50 % of fungicide sprays. The utilisation of a threshold SA:0.6 showed a smaller efficacy than weekly sprays but it saved applications about 50-70 %. From these results it can be accepted say that the STREP model can be used in pilot trials as a forecaster for scheduling sprays in commercial orchards for rational control of brown spot of pear. If the results are acceptable, the model will be integrated on Grower's Warning Stations.

Sustainable development is now being recognised as a vital component of our society in the environmental, ethical, social, technological, economic, and institutional aspects, or dimensions, so, this thesis develops a framework to quantitatively measure sustainability. This thesis is distinctive in that it focuses on quantitative methods encapsulated in a formal assessment procedure and includes sustainability concepts that have rarely been put into practical use in sustainability reports. The framework is designed along the strategy that the methodology needs to be scale invariant and recursive, meaning the procedure is the same irrespective of the scale the user is interested in, and that different people can focus at different levels of sustainability by following a similar procedure. While the quantification process is aimed to be as unbiased as possible, a configuration of the tools from Total Quality Management (TQM) is adapted to identify sustainability indicators which are then mapped onto a scalar with mathematical functions. The sustainability indices are presented according to the amount of details needed by different users ─ some may need just one overall figure while others may need sustainability indices broken down by the six sustainability dimensions and presented on a spider diagram, while others may need all the details for analysis. This methodology also caters for sustainability analysis by different stakeholders. To fully demonstrate the potential of the methodology, the author has chosen to test it on a large-size industry sector so that it can have the capacity to be scaled up to a country or down to a small business, and on an industry sector that is important on its own right. Furthermore, this sector needs to be illustrative and has nontrivial complex problems. Under these criteria, the electricity sector of New Zealand was selected. The robustness of the methodology was investigated with inputs from three evaluators with different views: a standard view from the author that was made after much research in the sector and in the concepts of sustainability, a view with an environmental bias and one that focuses on commercial interests.

Low Pressure Die Casting (LPDC) process is one the most common casting process to produce structural automotive components, such as alloy wheels and suspension components. It has been identified that cavity filling and solidification process are two most critical aspects to produce premium quality casting components.During the solidification process of casting alloy, it is a well known phenomenon that metal experiences volumetric shrinkage due to its density difference between liquid and solid phase. When this volumetric shrinkage is not properly compensated, then a casting defect commonly known as solidification shrinkage occurs. The solidification shrinkage has very detrimental effects on structural integrity required for premium quality casting such as aluminium alloy wheels.Literature and practical experiences of foundry men show that it is critical to achieve unidirectional solidification pattern by avoiding an isolated hot spot in order to minimise the solidification shrinkage. However, it is found that the geometry of industrial casting applications is often constrained by other design factors that would not naturally avoid these isolated hot spots. The subject of this research, aluminium alloy wheels, is not excluded from this constraint.In aluminium alloy wheels, an isolated hot spot is commonly observed in an area known as rim and spoke junction due to its geometry constraints. Consequently, the solidification shrinkage is commonly experienced, which is undesirable due to its detrimental effects for the structural integrity of alloy wheels. In order to minimise the solidification shrinkage, forced cooling method is applied to avoid an isolated hot spot. The control of this forced cooling is achieved by cooling media, flow rate of cooling media and duration cooling circuit. Foundry experiments in industrial environment were conducted producing aluminium alloy wheels using commercially treated A356 (Al-Si) alloy, where different durations of cooling circuit were used to understand the sensitivity of solidification shrinkage formation to the duration of cooling circuit. This was followed by metallurgical structure analysis and numerical modelling to suggest the sensitivity of cooling circuit duration in controlling solidification shrinkage.The major finding conclusion of this research is that control of the shrinkage formation is not very sensitive to the duration cooling circuit. It is suggested that as casting solidifies initially from the mould wall, it retracts away from the cast-mould interface due to thermal contraction. Consequently, air gap is formed between casting and mould interface, creating an effective thermal resistance layer. Thereafter, heat transfer across the cast-mould interface is not sensitive to the change in the cooling channel which is a distance to the cast-mould interface.Some limitations of numerical modelling and metallurgical analysis were also identified during this research and recommendations were made to improve the accuracy of local hot spot prediction in production of aluminium alloy wheels. More specifically, numerical modelling of the effect of grain refinement and use of non homogeneous material property (particularly fraction of solid) for rapidly chilled area. Fraction of eutectic rather than secondary dendrites arm spacing is a proper microstructure parameter that can be used to locate the hot spot.

Thesis (MA)--Stellenbosch University, 2015. / ENGLISH ABSTRACT: Image classification has long been used in earth observation and is driven by the need for accurate maps to develop conceptual and predictive models of Earth system processes. Synthetic aperture radar (SAR) imagery is used ever more frequently in land cover classification due to its complementary nature with optical data. There is therefore a growing need for reliable, accurate methods for using SAR and optical data together in land use and land cover classifications. However, combining data sets inevitably increases data dimensionality and these large, complex data sets are difficult to handle. It is therefore important to assess the benefits and limitations of using multi-temporal, dual-sensor data for applications such as land cover classification. This thesis undertakes this assessment through four main experiments based on combined RADARSAT-2 and SPOT-5 imagery of the southern part of Reunion Island. In Experiment 1, the use of feature selection for dimensionality reduction was considered. The rankings of important features for both single-sensor and dual-sensor data were assessed for four dates spanning a 6-month period, which coincided with both the wet and dry season. The mean textural features produced from the optical bands were consistently ranked highly across all dates. In the two later dates (29 May and 9 August 2014), the SAR features were more prevalent, showing that SAR and optical data have complementary natures. SAR data can be used to separate classes when optical imagery is insufficient. Experiment 2 compared the accuracy of six supervised and machine learning classification algorithms to determine which performed best with this complex data set. The Random Forest classification algorithm produced the highest accuracies and was therefore used in Experiments 3 and 4. Experiment 3 assessed the benefits of using combined SAR-optical imagery over single-sensor imagery for land cover classifications on four separate dates. The fused imagery produced consistently higher overall accuracies. The 29 May 2014 fused data produced the best accuracy of 69.8%. The fused classifications had more consistent results over the four dates than the single-sensor imagery, which suffered lower accuracies, especially for imagery acquired later in the season. In Experiment 4, the use of multi-temporal, dual-sensor data for classification was evaluated. Feature selection was used to reduce the data set from 638 potential training features to 50, which produced the best accuracy of 74.1% in comparison to 71.9% using all of the features. This result validated the use of multi-temporal data over single-date data for land cover classifications. It also validated the use of feature selection to successfully inform data reduction without compromising the accuracy of the final product. Multi-temporal and dual-sensor data shows potential for mapping land cover in a tropical, mountainous region that would otherwise be challenging to map using single-sensor data. However, accuracies Stellenbosch University https://scholar.sun.ac.za iv generally remained lower than would allow for transferability and replication of the current methodology. Classification algorithm optimisation, supervised segmentation and improved training data should be considered to improve these results. / AFRIKAANSE OPSOMMING: Beeld-klassifikasie word al ‘n geruime tyd in aardwaarneming gebruik en word gedryf deur die behoefte aan akkurate kaarte om konseptuele en voorspellende modelle van aard-stelsel prosesse te ontwikkel. Sintetiese apertuur radar (SAR) beelde word ook meer dikwels in landdekking klassifikasie gebruik as gevolg van die aanvullende waarde daarvan met optiese data. Daar is dus 'n groeiende behoefte aan betroubare, akkurate metodes vir die gesamentlike gebruik van SAR en optiese data in landdekking klassifikasies. Die kombinasie van datastelle bring egter ‘n onvermydelike verhoging in data dimensionaliteit mee, en hierdie groot, komplekse datastelle is moeilik om te hanteer. Dus is dit belangrik om die voordele en beperkings van die gebruik van multi-temporale, dubbel-sensor data vir toepassings soos landdekking-klassifikasie te evalueer. Die waarde van gekombineerde (versmelte) RADARSAT-2 en SPOT-5 beelde word in hierdie tesis deur middel van vier eksperimente geevalueer. In Eksperiment 1 is die gebruik van kenmerk seleksie vir dimensionaliteit-vermindering toegepas. Die ranglys van belangrike kenmerke vir beide enkel-sensor en 'n dubbel-sensor data is beoordeel vir vier datums wat oor 'n tydperk van 6 maande strek. Die gemiddelde tekstuur kenmerke uit die optiese lae is konsekwent hoog oor alle datums geplaas. In die twee later datums (29 Mei en 9 Augustus 2014) was die SAR kenmerke meer algemeen, wat dui op die aanvullende aard van SAR en optiese data. SAR data dus gebruik kan word om klasse te onderskei wanneer optiese beelde onvoldoende daarvoor is. Eksperiment 2 het die akkuraatheid van ses gerigte en masjien-leer klassifikasie algoritmes vergelyk om te bepaal watter die beste met hierdie komplekse datastel presteer. Die random gorest klassifikasie algoritme het die hoogste akkuraatheid bereik en is dus in Eksperimente 3 en 4 gebruik. Eksperiment 3 het die voordele van gekombineerde SAR-optiese beelde oor enkel-sensor beelde vir landdekking klassifikasies op vier afsonderlike datums beoordeel. Die versmelte beelde het konsekwent hoër algehele akkuraathede as enkel-sensor beelde gelewer. Die 29 Mei 2014 data het die hoogste akkuraatheid van 69,8% bereik. Die versmelte klassifikasies het ook meer konsekwente resultate oor die vier datums gelewer en die enkel-sensor beelde het tot laer akkuraathede gelei, veral vir die later datums. In Eksperiment 4 is die gebruik van multi-temporale, dubbel-sensor data vir klassifikasie ge-evalueer. Kenmerkseleksie is gebruik om die data stel van 638 potensiële kenmerke na 50 te verminder, wat die beste akkuraatheid van 74,1% gelewer het. Hierdie resultaat bevestig die belangrikheid van multi-temporale data vir grond dekking klassifikasies. Dit bekragtig ook die gebruik van kenmerkseleksie om data vermindering suksesvol te rig sonder om die akkuraatheid van die finale produk te belemmer. Stellenbosch University https://scholar.sun.ac.za vi Multi-temporale en dubbel-sensor data toon potensiaal vir die kartering van landdekking in 'n tropiese, bergagtige streek wat andersins uitdagend sou wees om te karteer met behulp van enkel-sensor data. Oor die algemeen het akkuraathede egter te laag gebly om vir oordraagbaarheid en herhaling van die huidige metode toe te laat. Klassifikasie algoritme optimalisering, gerigte segmentering en verbeterde opleiding data moet oorweeg word om hierdie resultate te verbeter.