Methods in machine learning for probabilistic modelling of environment, with applications in meteorology and geology

Earth scientists increasingly deal with ‘big data’. Where once we may have struggled to obtain a handful of relevant measurements, we now often have data being collected from multiple sources, on the ground, in the air, and from space. These observations are accumulating at a rate that far outpaces our ability to make sense of them using traditional methods with limited scalability (e.g., mental modelling, or trial-and-error improvement of process based models). The revolution in machine learning offers a new paradigm for modelling the environment: rather than focusing on tweaking every aspect of models developed from the top down based largely on prior knowledge, we now have the capability to instead set up more abstract machine learning systems that can ‘do the tweaking for us’ in order to learn models from the bottom up that can be considered optimal in terms of how well they agree with our (rapidly increasing number of) observations of reality, while still being guided by our prior beliefs. In this thesis, with the help of spatial, temporal, and spatio-temporal examples in meteorology and geology, I present methods for probabilistic modelling of environmental variables using machine learning, and explore the considerations involved in developing and adopting these technologies, as well as the potential benefits they stand to bring, which include improved knowledge-acquisition and decision-making. In each application, the common theme is that we would like to learn predictive distributions for the variables of interest that are well-calibrated and as sharp as possible (i.e., to provide answers that are as precise as possible while remaining honest about their uncertainty). Achieving this requires the adoption of statistical approaches, but the volume and complexity of data available mean that scalability is an important factor — we can only realise the value of available data if it can be successfully incorporated into our models.Engineering and Physical Sciences Research Council (EPSRC

Differential Regulation of Growth-Promoting Signalling Pathways by E-Cadherin

Background: Despite the well-documented association between loss of E-cadherin and carcinogenesis, as well as the link between restoration of its expression and suppression of proliferation in carcinoma cells, the ability of E-cadherin to modulate growth-promoting cell signalling in normal epithelial cells is less well understood and frequently contradictory. The potential for E-cadherin to co-ordinate different proliferation-associated signalling pathways has yet to be fully explored. Methodology/Principal Findings: Using a normal human urothelial (NHU) cell culture system and following a calcium-switch approach, we demonstrate that the stability of NHU cell-cell contacts differentially regulates the Epidermal Growth Factor Receptor (EGFR)/Extracellular Signal-Regulated Kinase (ERK) and Phosphatidylinositol 3-Kinase (PI3-K)/AKT pathways. We show that stable cell contacts down-modulate the EGFR/ERK pathway, whilst inducing PI3-K/AKT activity, which transiently enhances cell growth at low density. Functional inactivation of E-cadherin interferes with the capacity of NHU cells to form stable calcium-mediated contacts, attenuates E-cadherin-mediated PI3-K/AKT induction and enhances NHU cell proliferation by allowing de-repression of the EGFR/ERK pathway and constitutive activation of beta-catenin-TCF signalling. Conclusions/Significance: Our findings provide evidence that E-cadherin can differentially and concurrently regulate specific growth-related signalling pathways in a context-specific fashion, with direct, functional consequences for cell proliferation and population growth. Our observations not only reveal a novel, complex role for E-cadherin in normal epithelial cell homeostasis and tissue regeneration, but also provide the basis for a more complete understanding of the consequences of E-cadherin loss on malignant transformation

Inactivation of presenilins causes pre-synaptic impairment prior to post-synaptic dysfunction

Synaptic dysfunction is widely thought to be a pathogenic precursor to neurodegeneration in Alzheimer’s disease (AD), and the extent of synaptic loss provides the best correlate for the severity of dementia in AD patients. Presenilins 1 and 2 are the major causative genes of early‐onset familial AD. Conditional inactivation of presenilins in the adult cerebral cortex results in synaptic dysfunction and memory impairment, followed by age‐dependent neurodegeneration. To characterize further the consequence of presenilin inactivation in the synapse, we evaluated the temporal development of pre‐synaptic and post‐synaptic deficits in the Schaeffer‐collateral pathway of presenilin conditional double knockout (PS cDKO) mice prior to onset of neurodegeneration. Following presenilin inactivation at 4 weeks, synaptic facilitation and probability of neurotransmitter release are impaired in PS cDKO mice at 5 weeks of age, whereas post‐synaptic NMDA receptor (NMDAR)‐mediated responses are normal at 5 weeks but impaired at 6 weeks of age. Long‐term potentiation induced by theta burst stimulation is also reduced in PS cDKO mice at 6 weeks of age. These results show that loss of presenilins results in pre‐synaptic deficits in short‐term plasticity and probability of neurotransmitter release prior to post‐synaptic NMDAR dysfunction, raising the possibility that presenilins may regulate post‐synaptic NMDAR function in part via a trans‐synaptic mechanism.This work was supported by the National Institute of Health NS041783 (to J.S.). We would like to thank Xiaoyan Zou and Huailong Zhao for technical assistance. (NS041783 - National Institute of Health)Published versio

Time evolution of correlation functions and thermalization

We investigate the time evolution of a classical ensemble of isolated periodic chains of O(N)-symmetric anharmonic oscillators. Our method is based on an exact evolution equation for the time dependence of correlation functions. We discuss its solutions in an approximation which retains all contributions in next-to-leading order in a 1/N expansion and preserves time reflection symmetry. We observe effective irreversibility and approximate thermalization. At large time the system approaches stationary solutions in the vicinity of, but not identical to, thermal equilibrium. The ensemble therefore retains some memory of the initial condition beyond the conserved total energy. Such a behavior with incomplete thermalization is referred to as "mesoscopic dynamics". It is expected for systems in a small volume. Surprisingly, we find that the nonthermal asymptotic stationary solutions do not change for large volume. This raises questions on Boltzmann's conjecture that macroscopic isolated systems thermalize.Comment: 40 pages, 9 figure

KINEMATIC GAIT VARIABLES OF ELDERLY WOMEN WITH DIFFERENT LEVEL OF PHYSICAL ACTIVITY

The aging of populations is an international phenomena caused by the decline of birthrate and the progress of medical science. According to WHO individuals older than 65 years in developed countries and older than 60 years in developing countries are considered elderly. The aging process is characterized by the decrease of muscle mass, strength and power, one of the most important reasons for the decrease of functional abilities and the increase of falling risk (Zhong et al., 2007). Nevertheless, physical activity may retard this process. The principal changes in kinematic gait variables are the decrease of gait velocity, stride length and single support time with an increase of double support time (McGibbon,2003). These changes in gait pattern observed in the elderly population may arise from functional declines of aging and may be even more significant in the absence of appropriate regular physical exercises. Considering the higher proportion of women in the elderly population (WHO, 2002), it is important to understand the changes in gait patterns of elderly women related to physical activity. Therefore, the purpose of this study was to identify the effects of different intensities of physical activity on the cinematic gait variables in older women