Conventional or “primed” human embryonic stem cells (hESCs) rely on FGF and TGFβ signalling for self-renewal, and occupy a developmentally advanced state of pluripotency comparable to mouse EpiSCs. Recent reports demonstrate that a naïve state of human pluripotency can be consistently derived either through transient histone deacetylase inhibition mediated resetting of conventional hESCs or via isolation of the inner cell mass. Long-term propagation of this state can be achieved using a cocktail of MEK, GSK3 and PKC inhibition in conjunction with leukaemia inhibitory factor (LIF) supplementation (t2iLGö) and a feeder layer of inactivated mouse embryonic fibroblasts. However, the way in which this signalling environment is interpreted in order to maintain naïve pluripotency remains unclear. I demonstrate a substrate consisting of a high concentration of tissue-derived laminin in combination with t2iLGö is sufficient to replace the feeder layer. Cultures maintained under these conditions are karyotypically normal, maintain a naive pluripotent transcriptional profile and exhibit reduced aberrant expression of mesodermal and endodermal lineage markers. I utilise the increased stringency of this culture system in combination with small molecule inhibitors to examine the roles of FGF, Activin/Nodal and JAK/STAT signalling in human naïve pluripotency. Naïve hESCs proliferate and maintain pluripotency marker expression in the presence of FGF receptor inhibition. In contrast, TGFβ signalling inhibition leads to rapid downregulation of human specific naïve pluripotency marker, KLF17, followed by the eventual collapse of the naïve transcription factor circuitry. Naïve hESCs self-renew in both the absence of LIF and presence of JAK/STAT inhibitors. However, further investigation of JAK/STAT signalling identified the increased potency of Interleukin 6 (IL-6) over LIF to activate the JAK/STAT pathway. Supplemental IL-6 improves colony-forming capacity under self-renewing conditions and attenuates differentiation following inhibitor withdrawal. Furthermore, prolonged activation of IL-6 signalling suppresses expression of GATA2 and GATA3 and upregulates KLF4 transcripts. Finally, I investigate whether ablation of PKCι is sufficient to replace the activity of the PKC inhibitor, Gö6983. Established naïve cultures that are PKCι null continue to express naïve markers and suppress upregulation of lineage makers following withdrawal of Gö6983. Furthermore, ablation of PKCι in conventional ESCs enables the maintenance of NANOG expression and the emergence of KLF17 expression in the absence of Gö6983 during histone deactylase mediated resetting.

In the current study, children’s understanding of false belief, intention, and their ability to distinguish the appearance of a character from its reality was investigated. Seventy-two three to five years olds were recruited from several preschools in the Silicon Valley in California. During the experiment, children were shown an animated movie in a computer and asked the false belief, intention, and appearance-reality distinction questions. Following the animated movie, children were also asked if they understand 10 mental words that depicted the human mind, such as think, want, believe, etc. The relationship between the children’s knowledge of the human mind and the mental words they understood was explored. Results of the current study revealed that children who were four and half to five performed better than children three and half to four on false belief tasks. Children’s performance on intention and appearance-reality distinction questions did not differ significantly across age. However, girls’ performance was superior to boys’ performance on intention questions. Similarly, girls’ knowledge of overall naïve psychology was also superior to that of boys. Moreover, the order of the naïve psychology concepts that children passed in current study was from intention to appearance-reality distinction and then false belief. Finally, the regression analysis of the data revealed that the mental word vocabulary children processed was closely related to naïve psychology development. More specifically, the number of total mental words that were reported by children or assessed by contextual questions was a significant predictor of naïve psychology knowledge.

Statistical analysis is used quite heavily in production operations. To use certain advanced statistical approaches such as Bayesian analysis, statistical models must be built. This thesis demonstrates the process of building the Bayesian models and addresses some of the classical limitations by presenting mathematical examples and proofs, by demonstrating the process with experimental and simulated implementations, and by completing basic analysis of the performance of the implemented models. From the analysis, it is shown that the performance of the Bayesian models is directly related to the amount of separation between the likelihood distributions that describe the behavior of the data features used to generate the multivariate Bayesian models. More specifically, the more features that had clear separation between the likelihood distributions for each possible condition, the more accurate the results were. This is shown to be true regardless of the quantity of data used to generate the model distributions during model building. In cases where distribution overlap is present, it is found that models performance become more consistent as the amount of data used to generate the models increases. In cases where distribution overlap is minimal, it is found that models performance become consistent within 4-6 data sets.

No description available.

There are numerous text documents available in electronic form. More and more are becoming available every day. Such documents represent a massive amount of information that is easily accessible. Seeking value in this huge collection requires organization; much of the work of organizing documents can be automated through text classification. The accuracy and our understanding of such systems greatly influences their usefulness. In this paper, we seek 1) to advance the understanding of commonly used text classification techniques, and 2) through that understanding, improve the tools that are available for text classification. We begin by clarifying the assumptions made in the derivation of Naive Bayes, noting basic properties and proposing ways for its extension and improvement. Next, we investigate the quality of Naive Bayes parameter estimates and their impact on classification. Our analysis leads to a theorem which gives an explanation for the improvements that can be found in multiclass classification with Naive Bayes using Error-Correcting Output Codes. We use experimental evidence on two commonly-used data sets to exhibit an application of the theorem. Finally, we show fundamental flaws in a commonly-used feature selection algorithm and develop a statistics-based framework for text feature selection. Greater understanding of Naive Bayes and the properties of text allows us to make better use of it in text classification.

The overarching goal of this project was to improve breast cancer screening protocols first by collecting small angle x-ray scattering (SAXS) images from breast biopsy tissue, and second, by applying pattern recognition techniques as a semi-automatic screen. Wavelet based features were generated from the SAXS image data. The features were supplied to a classifier, which sorted the images into distinct groups, such as normal and tumor. <p>The main problem in the project was to find a set of features that provided sufficient separation for classification into groups of normal and tumor. In the original SAXS patterns, information useful for classification was obscured. The wavelet maps allowed new scale-based information to be uncovered from each SAXS pattern. The new information was subsequently used to define features that allowed for classification. Several calculations were tested to extract useful features from the wavelet decomposition maps. The wavelet map average intensity feature was selected as the most promising feature. The wavelet map intensity feature was improved by using pre-processing to remove the high central intensities from the SAXS patterns, and by using different wavelet bases for the wavelet decomposition. <p>The investigation undertaken for this project showed very promising results. A classification rate of 100% was achieved for distinguishing between normal samples and tumor samples. The system also showed promising results when tested on unrelated MRI data. In the future, the semi-automatic pattern recognition tool developed for this project could be automated. With a larger set of data for training and testing, the tool could be improved upon and used to assist radiologists in the detection and classification of breast lesions.

The overarching goal of this project was to improve breast cancer screening protocols first by collecting small angle x-ray scattering (SAXS) images from breast biopsy tissue, and second, by applying pattern recognition techniques as a semi-automatic screen. Wavelet based features were generated from the SAXS image data. The features were supplied to a classifier, which sorted the images into distinct groups, such as normal and tumor. <p>The main problem in the project was to find a set of features that provided sufficient separation for classification into groups of normal and tumor. In the original SAXS patterns, information useful for classification was obscured. The wavelet maps allowed new scale-based information to be uncovered from each SAXS pattern. The new information was subsequently used to define features that allowed for classification. Several calculations were tested to extract useful features from the wavelet decomposition maps. The wavelet map average intensity feature was selected as the most promising feature. The wavelet map intensity feature was improved by using pre-processing to remove the high central intensities from the SAXS patterns, and by using different wavelet bases for the wavelet decomposition. <p>The investigation undertaken for this project showed very promising results. A classification rate of 100% was achieved for distinguishing between normal samples and tumor samples. The system also showed promising results when tested on unrelated MRI data. In the future, the semi-automatic pattern recognition tool developed for this project could be automated. With a larger set of data for training and testing, the tool could be improved upon and used to assist radiologists in the detection and classification of breast lesions.

This thesis gives a functorial interpretation of the Naive Space of Maps Nd as a parametrizing space for a family of maps from certain rational curves to P¹. / text

One of the most immediately compelling arguments against the disjunctivist position within the philosophy of perception points to the well-accepted fact that hallucinations can have the same neural cause as veridical perceptions; this is known as the causal argument. Since the main motivation for disjunctivism is to preserve naive realism, critics claim that naive realism is then incompatible with certain, well-accepted claims of neuropsychology, and, thus, disjunctivism is false. After surveying the general arguments for disjunctivism offered by Hinton, Snowden, and Martin, the causal argument is split into a stronger version and a weaker version. The strong argument relies on a narrow conception of the ‘same cause, same effect’ principle and this narrow conception is extremely controversial, ultimately entailing that mental events supervene only on the total brain state of an individual. The weak argument, which embraces a wider conception of the ‘same cause, same effect’ principle finds the disjunctivist position explanatorily redundant. The two major camps within disjunctivism, positive disjunctivism and negative disjunctivism, offer different approaches to the weak argument, and what emerges from the discussion of these two theories is that negative disjunctivism has a major dialectical advantage against positive disjunctivism, and that negative disjunctivism offers a satisfying response to the weak causal argument. M. G. F. Martin offers an insightful analysis of ‘indistinguishability’ and in doing so clarifies the disjunctivist thesis, sets limits to our understanding of our own mental states, and places the burden with the common-kind theorist.

The general purpose of this study was to consider the relationship between an individual's perception of his parent-child experiences and the adequacy of a naive cognitive model to describe his judgements of others.