Statistical analysis and meta-analysis of microarray data

The microarray technology provides a high-throughput technique to study gene expression. Microarrays can help us diagnose different types of cancers, understand biological processes, assess host responses to drugs and pathogens, find markers for specific diseases, and much more. Microarray experiments generate large amounts of data. Thus, effective data processing and analysis are critical for making reliable inferences from the data. ^ The first part of dissertation addresses the problem of finding an optimal set of genes (biomarkers) to classify a set of samples as diseased or normal. Three statistical gene selection methods (GS, GS-NR, and GS-PCA) were developed to identify a set of genes that best differentiate between samples. A comparative study on different classification tools was performed and the best combinations of gene selection and classifiers for multi-class cancer classification were identified. For most of the benchmarking cancer data sets, the gene selection method proposed in this dissertation, GS, outperformed other gene selection methods. The classifiers based on Random Forests, neural network ensembles, and K-nearest neighbor (KNN) showed consistently god performance. A striking commonality among these classifiers is that they all use a committee-based approach, suggesting that ensemble classification methods are superior. ^ The same biological problem may be studied at different research labs and/or performed using different lab protocols or samples. In such situations, it is important to combine results from these efforts. The second part of the dissertation addresses the problem of pooling the results from different independent experiments to obtain improved results. Four statistical pooling techniques (Fisher inverse chi-square method, Logit method. Stouffer's Z transform method, and Liptak-Stouffer weighted Z-method) were investigated in this dissertation. These pooling techniques were applied to the problem of identifying cell cycle-regulated genes in two different yeast species. As a result, improved sets of cell cycle-regulated genes were identified. The last part of dissertation explores the effectiveness of wavelet data transforms for the task of clustering. Discrete wavelet transforms, with an appropriate choice of wavelet bases, were shown to be effective in producing clusters that were biologically more meaningful. ^

A methodology to estimate time varying user responses to travel time and travel time reliability in a road pricing environment

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

Design of experiments to study the impact of process parameters on droplet size and development of non-invasive imaging techniques in tablet coating

Atomisation of an aqueous solution for tablet film coating is a complex process with multiple factors determining droplet formation and properties. The importance of droplet size for an efficient process and a high quality final product has been noted in the literature, with smaller droplets reported to produce smoother, more homogenous coatings whilst simultaneously avoiding the risk of damage through over-wetting of the tablet core. In this work the effect of droplet size on tablet film coat characteristics was investigated using X-ray microcomputed tomography (XμCT) and confocal laser scanning microscopy (CLSM). A quality by design approach utilising design of experiments (DOE) was used to optimise the conditions necessary for production of droplets at a small (20 μm) and large (70 μm) droplet size. Droplet size distribution was measured using real-time laser diffraction and the volume median diameter taken as a response. DOE yielded information on the relationship three critical process parameters: pump rate, atomisation pressure and coating-polymer concentration, had upon droplet size. The model generated was robust, scoring highly for model fit (R2 = 0.977), predictability (Q2 = 0.837), validity and reproducibility. Modelling confirmed that all parameters had either a linear or quadratic effect on droplet size and revealed an interaction between pump rate and atomisation pressure. Fluidised bed coating of tablet cores was performed with either small or large droplets followed by CLSM and XμCT imaging. Addition of commonly used contrast materials to the coating solution improved visualisation of the coating by XμCT, showing the coat as a discrete section of the overall tablet. Imaging provided qualitative and quantitative evidence revealing that smaller droplets formed thinner, more uniform and less porous film coats.

Food preferences and weight change during low-fat and low-carbohydrate diets.

UNLABELLED: Understanding associations between food preferences and weight loss during various effective diets could inform efforts to personalize dietary recommendations and provide insight into weight loss mechanisms. We conducted a secondary analysis of data from a clinical trial in which participants were randomized to either a 'choice' arm, in which they were allowed to select between a low-fat diet (n = 44) or low-carbohydrate diet (n = 61), or to a 'no choice' arm, in which they were randomly assigned to a low-fat diet (n = 49) or low-carbohydrate diet (n = 53). All participants were provided 48 weeks of lifestyle counseling. Food preferences were measured at baseline and every 12 weeks thereafter with the Geiselman Food Preference Questionnaire. Participants were 73% male and 51% African American, with a mean age of 55. Baseline food preferences, including congruency of food preferences with diet, were not associated with weight outcomes. In the low-fat diet group, no associations were found between changes in food preferences and weight over time. In the low-carbohydrate diet group, increased preference for low-carbohydrate diet congruent foods from baseline to 12 weeks was associated with weight loss from 12 to 24 weeks. Additionally, weight loss from baseline to 12 weeks was associated with increased preference for low-carbohydrate diet congruent foods from 12 to 24 weeks. Results suggest that basing selection of low-carbohydrate diet or low-fat diet on food preferences is unlikely to influence weight loss. Congruency of food preferences and weight loss may influence each other early during a low-carbohydrate diet but not low-fat diet, possibly due to different features of these diets. CLINICAL TRIAL REGISTRY: NCT01152359.

Sensor Planning for Bayesian Nonparametric Target Modeling

Bayesian nonparametric models, such as the Gaussian process and the Dirichlet process, have been extensively applied for target kinematics modeling in various applications including environmental monitoring, traffic planning, endangered species tracking, dynamic scene analysis, autonomous robot navigation, and human motion modeling. As shown by these successful applications, Bayesian nonparametric models are able to adjust their complexities adaptively from data as necessary, and are resistant to overfitting or underfitting. However, most existing works assume that the sensor measurements used to learn the Bayesian nonparametric target kinematics models are obtained a priori or that the target kinematics can be measured by the sensor at any given time throughout the task. Little work has been done for controlling the sensor with bounded field of view to obtain measurements of mobile targets that are most informative for reducing the uncertainty of the Bayesian nonparametric models. To present the systematic sensor planning approach to leaning Bayesian nonparametric models, the Gaussian process target kinematics model is introduced at first, which is capable of describing time-invariant spatial phenomena, such as ocean currents, temperature distributions and wind velocity fields. The Dirichlet process-Gaussian process target kinematics model is subsequently discussed for modeling mixture of mobile targets, such as pedestrian motion patterns.

Novel information theoretic functions are developed for these introduced Bayesian nonparametric target kinematics models to represent the expected utility of measurements as a function of sensor control inputs and random environmental variables. A Gaussian process expected Kullback Leibler divergence is developed as the expectation of the KL divergence between the current (prior) and posterior Gaussian process target kinematics models with respect to the future measurements. Then, this approach is extended to develop a new information value function that can be used to estimate target kinematics described by a Dirichlet process-Gaussian process mixture model. A theorem is proposed that shows the novel information theoretic functions are bounded. Based on this theorem, efficient estimators of the new information theoretic functions are designed, which are proved to be unbiased with the variance of the resultant approximation error decreasing linearly as the number of samples increases. Computational complexities for optimizing the novel information theoretic functions under sensor dynamics constraints are studied, and are proved to be NP-hard. A cumulative lower bound is then proposed to reduce the computational complexity to polynomial time.

Three sensor planning algorithms are developed according to the assumptions on the target kinematics and the sensor dynamics. For problems where the control space of the sensor is discrete, a greedy algorithm is proposed. The efficiency of the greedy algorithm is demonstrated by a numerical experiment with data of ocean currents obtained by moored buoys. A sweep line algorithm is developed for applications where the sensor control space is continuous and unconstrained. Synthetic simulations as well as physical experiments with ground robots and a surveillance camera are conducted to evaluate the performance of the sweep line algorithm. Moreover, a lexicographic algorithm is designed based on the cumulative lower bound of the novel information theoretic functions, for the scenario where the sensor dynamics are constrained. Numerical experiments with real data collected from indoor pedestrians by a commercial pan-tilt camera are performed to examine the lexicographic algorithm. Results from both the numerical simulations and the physical experiments show that the three sensor planning algorithms proposed in this dissertation based on the novel information theoretic functions are superior at learning the target kinematics with

little or no prior knowledge

Seawater carbonate chemistry and brown dottyback (Pseudochromis fuscus) movement and feeding behaviour during experiments, 2011

Changes in olfactory-mediated behaviour caused by elevated CO2 levels in the ocean could affect recruitment to reef fish populations because larval fish become more vulnerable to predation. However, it is currently unclear how elevated CO2 will impact the other key part of the predator-prey interaction - the predators. We investigated the effects of elevated CO2 and reduced pH on olfactory preferences, activity levels and feeding behaviour of a common coral reef meso-predator, the brown dottyback (Pseudochromis fuscus). Predators were exposed to either current-day CO2 levels or one of two elevated CO2 levels (~600 µatm or ~950 µatm) that may occur by 2100 according to climate change predictions. Exposure to elevated CO2 and reduced pH caused a shift from preference to avoidance of the smell of injured prey, with CO2treated predators spending approximately 20% less time in a water stream containing prey odour compared with controls. Furthermore, activity levels of fish was higher in the high CO2 treatment and feeding activity was lower for fish in the mid CO2treatment; indicating that future conditions may potentially reduce the ability of the fish to respond rapidly to fluctuations in food availability. Elevated activity levels of predators in the high CO2 treatment, however, may compensate for reduced olfactory ability, as greater movement facilitated visual detection of food. Our findings show that, at least for the species tested to date, both parties in the predator-prey relationship may be affected by ocean acidification. Although impairment of olfactory-mediated behaviour of predators might reduce the risk of predation for larval fishes, the magnitude of the observed effects of elevated CO2 acidification appear to be more dramatic for prey compared to predators. Thus, it is unlikely that the altered behaviour of predators is sufficient to fully compensate for the effects of ocean acidification on prey mortality.

Seawater carbonate chemistry and fish Amphiprion percula behaviour during experiments, 2012

Predicted future CO2 levels have been found to alter sensory responses and behaviour of marine fishes. Changes include increased boldness and activity, loss of behavioural lateralization, altered auditory preferences and impaired olfactory function. Impaired olfactory function makes larval fish attracted to odours they normally avoid, including ones from predators and unfavourable habitats. These behavioural alterations have significant effects on mortality that may have far-reaching implications for population replenishment, community structure and ecosystem function. However, the underlying mechanism linking high CO2 to these diverse responses has been unknown. Here we show that abnormal olfactory preferences and loss of behavioural lateralization exhibited by two species of larval coral reef fish exposed to high CO2 can be rapidly and effectively reversed by treatment with an antagonist of the GABA-A receptor. GABA-A is a major neurotransmitter receptor in the vertebrate brain. Thus, our results indicate that high CO2 interferes with neurotransmitter function, a hitherto unrecognized threat to marine populations and ecosystems. Given the ubiquity and conserved function of GABA-A receptors, we predict that rising CO2 levels could cause sensory and behavioural impairment in a wide range of marine species, especially those that tightly control their acid-base balance through regulatory changes in HCO3 and Cl levels.

Seawater carbonate chemistry and growth rate during experiments with phylotypes of Symbiodinium (Dinophyceae), 2011

We investigated the effect of elevated partial pressure of CO2 (pCO2) on the photosynthesis and growth of four phylotypes (ITS2 types A1, A13, A2, and B1) from the genus Symbiodinium, a diverse dinoflagellate group that is important, both free-living and in symbiosis, for the viability of cnidarians and is thus a potentially important model dinoflagellate group. The response of Symbiodinium to an elevated pCO2 was phylotype-specific. Phylotypes A1 and B1 were largely unaffected by a doubling in pCO2 in contrast, the growth rate of A13 and the photosynthetic capacity of A2 both increased by ~ 60%. In no case was there an effect of ocean acidification (OA) upon respiration (dark- or light-dependent) for any of the phylotypes examined. Our observations suggest that OA might preferentially select among free-living populations of Symbiodinium, with implications for future symbioses that rely on algal acquisition from the environment (i.e., horizontal transmission). Furthermore, the carbon environment within the host could differentially affect the physiology of different Symbiodinium phylotypes. The range of responses we observed also highlights that the choice of species is an important consideration in OA research and that further investigation across phylogenetic diversity, for both the direction of effect and the underlying mechanism(s) involved, is warranted.

Risk Preferences and the Role of Emotions

There is a large volume of research showing that emotions have relevant effects on decision-making. We contribute to this literature by experimentally investigating the impact of four specific emotional states - joviality, sadness, fear, and anger - on risk attitudes. In order to do so, we fit two models of behavior under risk: the Expected Utility model (EU) and the Rank Dependent Expected Utility model (RDEU), assuming several functional forms of the weighting function. Our results indicate that all emotional states mitigate risk aversion. Furthermore, we show that there are some differences across gender and participants' experience in laboratory experiments.

Pure higher-order effects in the portfolio choice model

This paper examines the effects of higher-order risk attitudes and statistical moments on the optimal allocation of risky assets within the standard portfolio choice model. We derive the expressions for the optimal proportion of wealth invested in the risky asset to show they are functions of portfolio returns third- and fourth-order moments as well as on the investor’s risk preferences of prudence and temperance. We illustrate the relative importance that the introduction of those higher-order effects have in the decision of expected utility maximizers using data for the US.

Games for groundwater governance: field experiments in Andhra Pradesh, India

Groundwater is a common-pool resource that is subject to depletion in many places around the world as a result of increased use of irrigation and water-demanding cash crops. Where state capacity to control groundwater use is limited, collective action is important to increase recharge and restrict highly water-consumptive crops. We present results of field experiments in hard rock areas of Andhra Pradesh, India, to examine factors affecting groundwater use. Two nongovernmental organizations (NGOs) ran the games in communities where they were working to improve watershed and water management. Results indicate that, when the links between crop choice and groundwater depletion is made explicit, farmers can act cooperatively to address this problem. Longer NGO involvement in the villages was associated with more cooperative outcomes in the games. Individuals with more education and higher perceived community social capital played more cooperatively, but neither gender nor method of payment had a significantly effect on individual behavior. When participants could repeat the game with communication, similar crop choice patterns were observed. The games provided an entry point for discussion on the understanding of communities of the interconnectedness of groundwater use and crop choice.

Understanding stakeholder preferences for flood adaptation alternatives with natural capital implications

Inland flood risks are defined by a range of environmental and social factors, including land use and floodplain management. Shifting patterns of storm intensity and precipitation, attributed to climate change, are exacerbating flood risk in regions across North America. Strategies for adapting to growing flood risks and climate change must account for a community’s specific vulnerabilities, and its local economic, environmental, and social conditions. Through a stakeholder-engaged methodology, we designed an interactive decision exercise to enable stakeholders to evaluate alternatives for addressing specific community flood vulnerabilities. We used a multicriteria framework to understand what drives stakeholder preferences for flood mitigation and adaptation alternatives, including ecosystem-based projects. Results indicated strong preferences for some ecosystem-based projects that utilize natural capital, generated a useful discussion on the role of individual values in driving decisions and a critique of local environmental and hazard planning procedure, and uncovered support for a river management alternative that had previously been considered socially infeasible. We conclude that a multicriteria decision framework may help ensure that the multiple benefit qualities of natural capital projects are considered by decision makers. Application of a utility function can demonstrate the role of individual decision-maker values in decision outcomes and help illustrate why one alternative may be a better choice than another. Although designing an efficient and accurate multicriteria exercise is quite challenging and often data intensive, we imagine that this method is applicable elsewhere. It may be especially suitable to group decisions that involve varying levels of expertise and competing values, as is often the case in planning for the ecological and human impacts of climate change.

Experimental demonstration of possible cryptic female choice on male tsetse fly genitalia

artículo -- Universidad de Costa Rica. Escuela de Biología, 2009. Este documento es privado debido a restricciones de derechos de autor del publicador.

The principle of least effort within the hierarchy of linguistic preferences: external evidence from English

The thesis is an investigation of the principle of least effort (Zipf 1949 [1972]). The principle is simple (all effort should be least) and universal (it governs the totality of human behavior). Since the principle is also functional, the thesis adopts a functional theory of language as its theoretical framework, i.e. Natural Linguistics. The explanatory system of Natural Linguistics posits that higher principles govern preferences, which, in turn, manifest themselves as concrete, specific processes in a given language. Therefore, the thesis’ aim is to investigate the principle of least effort on the basis of external evidence from English. The investigation falls into the three following strands: the investigation of the principle itself, the investigation of its application in articulatory effort and the investigation of its application in phonological processes. The structure of the thesis reflects the division of its broad aims. The first part of the thesis presents its theoretical background (Chapter One and Chapter Two), the second part of the thesis deals with application of least effort in articulatory effort (Chapter Three and Chapter Four), whereas the third part discusses the principle of least effort in phonological processes (Chapter Five and Chapter Six). Chapter One serves as an introduction, examining various aspects of the principle of least effort such as its history, literature, operation and motivation. It overviews various names which denote least effort, explains the origins of the principle and reviews the literature devoted to the principle of least effort in a chronological order. The chapter also discusses the nature and operation of the principle, providing numerous examples of the principle at work. It emphasizes the universal character of the principle from the linguistic field (low-level phonetic processes and language universals) and the non-linguistic ones (physics, biology, psychology and cognitive sciences), proving that the principle governs human behavior and choices. Chapter Two provides the theoretical background of the thesis in terms of its theoretical framework and discusses the terms used in the thesis’ title, i.e. hierarchy and preference. It justifies the selection of Natural Linguistics as the thesis’ theoretical framework by outlining its major assumptions and demonstrating its explanatory power. As far as the concepts of hierarchy and preference are concerned, the chapter provides their definitions and reviews their various understandings via decision theories and linguistic preference-based theories. Since the thesis investigates the principle of least effort in language and speech, Chapter Three considers the articulatory aspect of effort. It reviews the notion of easy and difficult sounds and discusses the concept of articulatory effort, overviewing its literature as well as various understandings in a chronological fashion. The chapter also presents the concept of articulatory gestures within the framework of Articulatory Phonology. The thesis’ aim is to investigate the principle of least effort on the basis of external evidence, therefore Chapters Four and Six provide evidence in terms of three experiments, text message studies (Chapter Four) and phonological processes in English (Chapter Six). Chapter Four contains evidence for the principle of least effort in articulation on the basis of experiments. It describes the experiments in terms of their predictions and methodology. In particular, it discusses the adopted measure of effort established by means of the effort parameters as well as their status. The statistical methods of the experiments are also clarified. The chapter reports on the results of the experiments, presenting them in a graphical way and discusses their relation to the tested predictions. Chapter Four establishes a hierarchy of speakers’ preferences with reference to articulatory effort (Figures 30, 31). The thesis investigates the principle of least effort in phonological processes, thus Chapter Five is devoted to the discussion of phonological processes in Natural Phonology. The chapter explains the general nature and motivation of processes as well as the development of processes in child language. It also discusses the organization of processes in terms of their typology as well as the order in which processes apply. The chapter characterizes the semantic properties of processes and overviews Luschützky’s (1997) contribution to NP with respect to processes in terms of their typology and incorporation of articulatory gestures in the concept of a process. Chapter Six investigates phonological processes. In particular, it identifies the issues of lenition/fortition definition and process typology by presenting the current approaches to process definitions and their typology. Since the chapter concludes that no coherent definition of lenition/fortition exists, it develops alternative lenition/fortition definitions. The chapter also revises the typology of phonological processes under effort management, which is an extended version of the principle of least effort. Chapter Seven concludes the thesis with a list of the concepts discussed in the thesis, enumerates the proposals made by the thesis in discussing the concepts and presents some questions for future research which have emerged in the course of investigation. The chapter also specifies the extent to which the investigation of the principle of least effort is a meaningful contribution to phonology.

Nurse Rostering with Genetic Algorithms

In recent years genetic algorithms have emerged as a useful tool for the heuristic solution of complex discrete optimisation problems. In particular there has been considerable interest in their use in tackling problems arising in the areas of scheduling and timetabling. However, the classical genetic algorithm paradigm is not well equipped to handle constraints and successful implementations usually require some sort of modification to enable the search to exploit problem specific knowledge in order to overcome this shortcoming. This paper is concerned with the development of a family of genetic algorithms for the solution of a nurse rostering problem at a major UK hospital. The hospital is made up of wards of up to 30 nurses. Each ward has its own group of nurses whose shifts have to be scheduled on a weekly basis. In addition to fulfilling the minimum demand for staff over three daily shifts, nurses’ wishes and qualifications have to be taken into account. The schedules must also be seen to be fair, in that unpopular shifts have to be spread evenly amongst all nurses, and other restrictions, such as team nursing and special conditions for senior staff, have to be satisfied. The basis of the family of genetic algorithms is a classical genetic algorithm consisting of n-point crossover, single-bit mutation and a rank-based selection. The solution space consists of all schedules in which each nurse works the required number of shifts, but the remaining constraints, both hard and soft, are relaxed and penalised in the fitness function. The talk will start with a detailed description of the problem and the initial implementation and will go on to highlight the shortcomings of such an approach, in terms of the key element of balancing feasibility, i.e. covering the demand and work regulations, and quality, as measured by the nurses’ preferences. A series of experiments involving parameter adaptation, niching, intelligent weights, delta coding, local hill climbing, migration and special selection rules will then be outlined and it will be shown how a series of these enhancements were able to eradicate these difficulties. Results based on several months’ real data will be used to measure the impact of each modification, and to show that the final algorithm is able to compete with a tabu search approach currently employed at the hospital. The talk will conclude with some observations as to the overall quality of this approach to this and similar problems.