Academic literature on the topic 'Variability of flats size'

In all biological systems, phenotypes are quantitative measures of an organism's traits. To understand the relation between a genotype and phenotypes, the influence of genetic perturbations, such as gene deletions, on phenotypes is studied. Although it is common practice to look at the mean value of phenotypes to detect changes, it is less common to model such modifications by considering phenotypic variability. However, phenotypic variability could also contain important information about the phenotype-genotype map. Also, phenotypic variability is a determinant of an organism's robustness and fitness. This thesis is a collection of five studies devised to identify and analyse phenotypic variability in S. pombe, S. cerevisiae and E. coli. The first chapter determines the probabilistic nature of the dynamic transition from quiescence to proliferation in S. pombe. Based on the viability and the random nature of the quiescence of knockout genes, we demonstrate that two competing stochastic models explain the data equally well. The second and third chapters provide novel approaches to identifying mutant genes that increase/decrease phenotypic variability throughout the cell cycle of S. cerevisiae. Using machine learning algorithms, we observe that mutants divide in four categories acting positively and/or negatively on phenotypic variability. Additionally, we show that phenotypic robustness is inversely related to cell fitness. The fourth chapter builds morphological interaction networks in S. cerevisiae. By employing a Bayesian network framework, we show that cell size dictates nuclear size throughout most of the cell cycle. The fifth chapter investigates the growth rate of bacterial populations subject to fluctuations in the variance of their cell size distributions. By employing a population balance equation combined with an agent-based model, our results indicate that the cell size distribution affects the growth rate. Moreover, we show that cells possess a cell size regulator within their cycle.

The majority of studies on plant biomass partitioning have focused on the effects of environment. Optimal Partitioning Theory (OPT) suggests that plants should allocate biomass to the organ that acquires the most limiting resource. Though, it has recently been disputed as to how much of this variation is due to variation in size and not environment. Additionally, while a few studies have examined differences between growth forms, the effects of evolutionary history have been largely ignored. Leaf morphology and physiology may also contribute to patterns of biomass partitioning.The role of plant size has been shown to be considerable to plant biomass allocation. Allometric biomass Partitioning Theory (APT) has recently been proposed to predict how plants should partition metabolic production based on the constraints of body size. Here, I assess the relative contribution of environment, growth form, leaf traits and phylogeny on variation in biomass allocation, after accounting for changes in size, using both an empirical and experimental approach. I use a global dataset of seed plants in addition to growing plants with differing evolutionary histories and growth forms hydroponically in two nutrient levels to examine patterns of organ partitioning while accounting for allometrically driven biomass allocation. Both the empirical and experimental interspecific analyses indicate that phylogeny accounts for the majority of the variation in biomass partitioning. Leaf biomass partitioning is partially related to growth form, however this appears to be due to differences in leaf morphology and physiology. While a strong phylogenetic signal exists, about half of the variation was not explained by any of the factors interspecifically, suggesting room for plasticity in partitioning. Intraspecifically, biomass allocation and partitioning was related to environmental factors in the directions predicted by OPT. However, the species-specific allocation response to environmental differences was not uniform, therefore obscuring interspecific patterns. These results have important implications for ecological studies; such that partitioning studies must first assess the role of plant size and evolutionary history in order to fully understand variability in biomass partitioning. Additionally, differences from environment can be incorporated with allometric changes to help understand how plants should allocate biomass.

Small scale fisheries serve as a “safety net” to the landless poor and significantly contribute to nutrition, food security, sustainable livelihood and poverty alleviation especially in developing countries such as Zambia. In spite of this substantial contribution, fisheries are highly susceptible to climate change and variability. The main aim of this study is to investigate the implications of climate variability on small scale fishing activities and the fishers’ adaptive capacity in the Kafue Flats of Zambia. Climatic data from Mumbwa, Kafue Polder, Mt Makulu, Magoye and Lusaka City meteorological stations is examined for the monthly, seasonal and annual variabilities with a central focus on the mean rainfall, temperature and wind speed over the 1982-2011 period. Additionally, the periodic size variation of the Kafue flats catchment area and its effects on the fishing activities are explored using satellite imagery in change detection analysis, employing ARC GIS 10.1 and ENVI 4.8. Further, the study explores the livelihood strategies of the fishing communities in determining their adaptive capacity to climate variability effects. Accordingly, the data sets are analysed using MS EXCEL, SPSS, ANCLIM, TREND TOOL, to establish climatic trends and deduce evidence of change and variability in the Kafue flats. Using snowball sampling technique and household survey, 110 fisher-folk were selected for the study. Besides, dissemination of face-to-face- questionnaires and key informant interviews are employed in this study. Climate variability analysis revealed that strong winds, storms, high rainfall and floods have adverse effects on the fisher-folk and their fishing activities. Thus, 90.9% of the fisher-folk indicated that heavy stormy rains have a larger potential to wreak havoc and cause death due to boat submergence. In addition, 95.5% of the fisher-folk stated that fishing activities do not take place during strong winds and heavy storms until calm weather conditions prevail. It is also established that the fisher-folk who are inclined to remain in a declining fishery are those restricted by a lack of alternative livelihoods and poverty. For instance, nearly half (44.5 %) of the fisher-folk interviewed lack alternative sources of livelihood. The conclusion from the study is that, climate variability has a wide range of impacts on fisheries and fishery dependent households. The explicit and localized impacts of climate variability on fisheries include reduced primary productivity, decrease in lake water levels and fish catches resulting from reduced precipitation and high run off. Therefore, there is need to enhance resilience and adoption of sustainable mitigation and adaptation strategies. The fisher-folk should be educated on alternative livelihoods to enable them cope in an event where climate change and variability severely impact on fisheries.<br>Dissertation (MSc)--University of Pretoria, 2015.<br>Geography Geoinformatics and Mateology<br>MSc<br>Unrestricted

This study investigated the relationship between working memory and language in typically developing young children. The aim was to gain a better understanding of language development, in particular, the involvement of visual and verbal short-term memory in language acquisition and its influence on vocabulary size. It explored possible underlying causes of why some children have problems in the process of learning to talk, whereas other children acquire language easily. A total of 51 New Zealand English speaking children aged two to five completed a battery of assessments measuring receptive and expressive vocabulary and visual and verbal short-term memory. The standardized tests administered included the Receptive One Word Picture Vocabulary Test (Brownell, 2000b), the Expressive One Word Picture Vocabulary Test (Brownell, 2000a), the Visual Patterns Test (Stokes, Klee, Cruickshank, & Pleass, 2009), and the Test of Early Nonword Repetition (Stokes & Klee, 2009a). Receptive vocabulary knowledge was strongly associated with visual (r = .75) and verbal (r = .60) short-term memory performance and age (r = .72). The relationship of expressive vocabulary to visual short-term memory (r = .80) was stronger than to verbal short-term memory (r = .62) but significant for both and also for age (r= .83). Significant unique predictors for expressive vocabulary were age (R2 change = .60) as well as visual (R2 change = .04) and verbal (R2 change = .04) short-term memory. However, age appeared to be the only unique predictor for receptive vocabulary (R2 change = .54). In addition, the findings suggested that visual and verbal short-term memory increases as children get older. Hence, the Visual Patterns Test and Test of Early Nonword Repetition seem to be good predictors, over and above age, of expressive vocabulary knowledge.

Beach grain size plays a major role in controlling beach slope and sediment transport rates and is a crucial criterion in selecting the appropriate fill material for beach nourishment. Yet, little is known about how and why beach grain size (and sorting) varies both spatially and temporally on high-energy sandy beaches. Therefore, in this PhD research project, the presence, magnitude and predictability of any spatio-temporal sediment variability was investigated on a number of contrasting high-energy (average significant wave height = 0.8 to 3.5 m), predominantly macrotidal (MSR = 3.1 – 6.2 m), sandy (0.26 – 0.64 mm) beach sites around the southwest peninsula of the United Kingdom (UK). The spatial extent of the data collected ranges from regional (one off snapshot of the sediment conditions on 53 beaches over 485 km of coastline) to local scales (repeated high-resolution samples from across the inter- and subtidal zone of a single high-energy sandy beach; Perranporth, UK). The temporal scales of the sampling ranges from tidal scale (~12 hours) up to monthly (long-term monitoring since 2008). A combination of traditional and modern field data collection methods has provided new insights into the sediment dynamics of sandy beaches. Surface and 0.25 m core sediment samples from the 53 beaches around the southwest UK and high-resolution digital measurements with longer 1 m sand cores from the intertidal zone, plus grab samples from the subtidal zone, at Perranporth, indicated the presence of three quasi-permanent spatial trends. On all sandy beaches, surface sediments became coarser (and better sorted) in the seaward direction across the intertidal zone. Peak sediment sizes were observed on the lower beach around mean low water springs, which were an average 19% coarser (and 8% better sorted) than sediments sampled on the upper intertidal beach. Sediment size (and sorting) also increased (improved) with distance down the sediment column over the top 0.25 m to 1 m. Peak sediment sizes at depth were an average 16% coarser (and 16% better sorted) than surface sediments. In the subtidal zone, surface sediments became finer and poorer sorted with increasing offshore distance. Minimum sediment size occurred on the subtidal bar crest and were an average 21% finer (and 51% poorer sorted) than the lower beach sediments and 5% finer (and 38% poorer sorted) than upper beach sediments. The coarsest sediments were usually the best sorted at all locations. The intertidal coarsening was deterministically linked to the location and amount of breaking wave-induced turbulence. The peak sediment sizes (and sorting) on the lower beach correlated with the location of peak wave dissipation (sediment size to amount of wave dissipation, r2 = 0.86) and the finer sediment sizes on the upper beach and bar were coincident with reduced amounts of wave dissipation in these regions. Long-term seasonal monitoring of the surface sediments at Perranporth indicated a background seasonality, where the winter months were an average 35% coarser and 22% better sorted than samples collected in summer. This seasonal pattern was punctuated by episodic storm events that promoted a significant coarsening (up to 112% in the extreme winter storms of 2014) of the surface sediments and significant beach erosion up to 175 m3/m. An empirical model forced by the degree of disequilibrium between an instantaneous and antecedent (weighted average) wave steepness time series was able to capture up to 86% of the sediment grain size and sorting variability, incorporating both the seasonal and storm driven change. The same model, applied to daily observations of sediment size and sorting changes was able to explain 72% of the variability. A conceptual model is proposed that extends the cross-shore sediment transport shape functions to include the various sediment (size and sorting) responses alongside the morphodynamic evolution during persistently high and low wave steepness conditions. Under high steepness waves, the finer material is preferentially removed from the lower intertidal beach, leaving behind coasrer sediments. This fine material is transported to the subtidal bar, which becomes finer (and more poorly sorted) inversely with the coarsening (and improved sorting) of the intertidal zone sediments. Under low steepness waves, this fine material is returned from the bar to the intertidal beach. This work provides a detailed, quantitative insight into the magnitude of sediment grain size and sorting changes exhibited by sandy beaches on a number of spatial and temporal scales. Several consistent trends were observed on a range of sandy beaches despite their different environmental conditions and geological histories. This improved understanding of sediment grain size and sorting changes on beaches will hopefully aid future research efforts and ensure that this fundamental aspect of coastal science is not overlooked or oversimplified.

In this work, the various sources of errors in radar rain estimation are quantified and procedures are developed to reduce them. The few topics explored here are: the variability of drop size distributions (DSDs), radar calibration, and errors in polarimetric rain estimation. The findings resulting from this study include 1) a new filtering technique that reduces the spurious DSD sampling variability while maintaining the physical variability, 2) a generalization of previously suggested DSD models in terms of scaling concepts, 3) the experimental evidence of the physical interpretation of DSD evolution and of R-Z relationships, 4) the time scale dependence of the DSD variability and its implication for radar rain estimation, 5) the quantification of error sources in polarimetric rain estimation and its feasibility in operational environment, and 6) a complete set of stable radar calibration methods and their theoretical limits. All error statistics from this work will be used as a guideline in radar rain estimation.

This research seeks to advance our understanding of how to make better informed species conservation decisions on a global scale and advance our understanding of how species' spatial distributions (their geographic ranges) may be respond to climate change, so we can know which areas should be set aside to ensure their present and future conservation. To understand how species' geographic ranges may change, it's important to first assess how geographic ranges are defined and measured. The quantifiable measurement of a species' geographic range, (its geographic range size), is a key criterion the International Union for the Conservation of Nature uses to determine the conservation status and prioritization of species worldwide. Thus, part one of this thesis evaluates different measures for how geographic range size is commonly quantified in the conservation community, to determine whether some range size measures are more reliable than others.Further, to evaluate how species' geographic ranges may respond to climate change, I examine the climatic factors influencing observable longitudinal range size gradients in the North American tree species range maps from E.L. Little's Atlas of North American Trees.

Ischaemic stroke is a leading cause of death and disability in the developed world. Despite that considerable advances in experimental research enabled understanding of the pathophysiology of the disease and identified hundreds of potential neuroprotective drugs for treatment, no such drug has shown efficacy in humans. The failure in the translation from bench to bedside has been partially attributed to the poor quality and rigour of animal studies. Recently, it has been suggested that multicentre animal studies imitating the design of randomised clinical trials could improve the translation of experimental research. Magnetic resonance imaging (MRI) could be pivotal in such studies due to its non-invasive nature and its high sensitivity to ischaemic lesions, but its accuracy and concordance across centres has not yet been evaluated. This thesis focussed on the use of MRI for the assessment of late infarct size, the primary outcome used in stroke models. Initially, a systematic review revealed that a plethora of imaging protocols and data analysis methods are used for this purpose. Using meta-analysis techniques, it was determined that T2-weighted imaging (T2WI) was best correlated with gold standard histology for the measurement of infarctbased treatment effects. Then, geometric accuracy in six different preclinical MRI scanners was assessed using structural phantoms and automated data analysis tools developed in-house. It was found that geometric accuracy varies between scanners, particularly when centre-specific T2WI protocols are used instead of a standardised protocol, though longitudinal stability over six months is high. Finally, a simulation study suggested that the measured geometric errors and the different protocols are sufficient to render infarct volumes and related group comparisons across centres incomparable. The variability increases when both factors are taken into account and when infarct volume is expressed as a relative estimate. Data in this study were analysed using a custom-made semi-automated tool that was faster and more reliable in repeated analyses than manual analysis. Findings of this thesis support the implementation of standardised methods for the assessment and optimisation of geometric accuracy in MRI scanners, as well as image acquisition and analysis of in vivo data for the measurement of infarct size in multicentre animal studies. Tools and techniques developed as part of the thesis show great promise in the analysis of phantom and in vivo data and could be a step towards this endeavour.

Although hybrid electric vehicles (HEVs) generally improve fuel economy (FE) compared to conventional vehicles, evidence of higher FE variability in HEVs compared to conventional vehicles indicates that apart from the improvement in FE, the reduction of FE variability is also of significant importance for HEVs. Over the years research on how to optimise powertrain component sizes of HEVs has generally focused on improving FE over a given driving pattern; FE variability over a realistic range of driving patterns has generally been overlooked, and this can lead to FE benefits of HEVs not being fully realised in real-world usage. How to reduce the FE variability in HEVs due to variation in driving patterns through the optimisation of powertrain component sizes is considered as the research question. This research proposes a new methodology in which powertrain components are optimised over a range of driving patterns representing different traffic conditions and driving styles simultaneously. This improves upon the traditional methodology followed in the reviewed literature, where an optimisation is performed for each individual driving pattern. An analysis shows that the traditional methodology could produce around 20% FE variability due to variation in driving patterns. This study considers a computer simulation model of a series-parallel Toyota Prius HEV for the investigation. Four powertrain components, namely, internal combustion engine, generator, motor, and battery of the Toyota Prius are optimised for FE using a genetic algorithm. For both the proposed and traditional methodologies, the powertrain components are optimised based on 5 standard driving patterns representing different traffic conditions and driving styles. During the optimisation, the proposed methodology considers all the 5 driving patterns simultaneously, whereas the traditional methodology considers each driving pattern separately. The optimum designs of both the methodologies and the simulation model of the Toyota Prius which is the benchmark vehicle for this study are evaluated for FE over the aforementioned 5 standard driving patterns and also 10 real-world driving patterns of a predefined route consisting of urban and highway driving patterns. The proposed methodology provides a single optimum design over the 5 standard driving patterns, whereas the traditional methodology provides 5 different optimum designs, one for each driving pattern. The single optimum design produced by the proposed methodology is independent of the sequence of driving patterns. The proposed methodology reduces FE variability by 5.3% and up to 48.9% with comparable average FE compared to the Toyota Prius and traditional methodology, respectively over the 10 real-world driving patterns, whereas none of the optimum designs of the traditional methodology is able to reduce FE variability compared to the Toyota Prius. This research provides a promising direction to address customer concerns related to FE in the real-world and improves understanding of the effect of driving patterns on the design of powertrain components.