Pirate Story

What is children’s cinema? This thesis explores this question by identifying three codes of children’s film and illuminating them through a short film entitled “Pirate Story.” The film is about a boy and his grandfather, and the pirates that inhabit a bedtime story. The pirates compete with the grandfather to have narrative authority over their own existence. This film examines the role of the narrator, use of animation, and absence of the parental figures as elements that are signifiers of children’s cinema. It was shot on HD video, with animation created in After Effects. Production also involved creation of a life-size pirate ship set, costumes, and musical score. This film serves to show that children’s cinema contains unique codes that inform the audience’s viewing experience and are important in the development of spectatorship into adulthood

Statistical modelling of Ca2+ oscillations in the presence of single cell heterogeneity

Intracellular calcium oscillations are a versatile signalling mechanism responsible for many biological phenomena including immune responses and insulin secretion. There is now compelling evidence that whole-cell calcium oscillations are stochastic, arising from random molecular interactions at the subcellular level. This poses a significant challenge for modelling. In this thesis, we develop a probabilistic approach that treats calcium oscillations as a stochastic point process. By employing an intensity function — a one dimension function over time which corresponds to the mean calcium spiking rate — we capture intrinsic cellular heterogeneity as well as inhomogeneous extracellular conditions, such as time-dependent stimulation. We adopt a Bayesian approach to infer the model parameters from calcium oscillations. Under this approach we need to be able to infer the intensity function. One method is to use a parametric model for the intensity function. For example we could assume the intensity function has the linear form x(t) = at + b. Then the intensity function is reduced to only needing to infer the two parameters a and b. However, parametric models suffer from strict assumptions, in this case, for the shape of the intensity function. Therefore, to lessen such assumptions, we utilise a non-parametric approach. This requires a prior distribution over the space of functions. We use two such priors, namely Gaussian processes and piecewise constant functions. We use Markov chain Monte Carlo (MCMC) techniques to sample from the posterior distribution to obtain estimates for our model parameters. Although advan- tageous — due to sampling from the true posterior distribution — MCMC algorithms can experience issues relating to their computational cost and imprecise samplers. We discuss the issues arising for our particular model and data and develop methods to improve the functionality of the MCMC algorithms in this case. For example we discuss the difficulty of inferring the length scale of the Gaussian process when fitted from calcium oscillations. An important mechanism of calcium oscillations is the refractory period, the min- imum amount of time before the next calcium oscillation. Thus, it may be beneficial to explicitly include the refractory period as part of the model. We investigate the advantages and disadvantages of including the refractory period. We fit the model to HEK293 cells and astrocytes challenged under a variety of stimulation protocols. We find that our model can accurately generate surrogate spike sequences with similar properties to those the model is fitted from. Therefore, the model can be used to cheaply create spike sequences that are synonymous to those found experimentally. Moreover, our model captures the similarity between calcium spike sequences obtained from step-change stimulus protocols and constant stimulus protocols. Combining intensity functions inferred from constant stimulus experiments closely follow the intensity function from a step change experiment. This implies it may be possible to build surrogate spike sequences for complex time-dependent stimulation protocols by combining results from simpler experiments. Of particular interest are patterns found in the intensity function which describes the heterogeneity in the calcium oscillations over time. Common patterns could help to understand the different time scales of the calcium response. Standard approaches often fail in grouping intensity functions with similar shape. Therefore, we develop an approach to cluster intensity functions based on their shape alone by utilising the Haar basis. In summary, we have developed novel statistical approaches based on the concept of stochastic point processes and non-standard MCMC techniques. We have successfully applied these new methodologies to gain a deeper understanding into the stochastic nature of intracellular calcium oscillations, in particular how different cell types respond to a variety of stimulation protocols. In turn, this brings us one step closer to unravel the complex dynamics of this pivotal intracellular messenger which controls life from its very beginning to its end

Statistical modelling of Ca2+ oscillations in the presence of single cell heterogeneity

Intracellular calcium oscillations are a versatile signalling mechanism responsible for many biological phenomena including immune responses and insulin secretion. There is now compelling evidence that whole-cell calcium oscillations are stochastic, arising from random molecular interactions at the subcellular level. This poses a significant challenge for modelling. In this thesis, we develop a probabilistic approach that treats calcium oscillations as a stochastic point process. By employing an intensity function — a one dimension function over time which corresponds to the mean calcium spiking rate — we capture intrinsic cellular heterogeneity as well as inhomogeneous extracellular conditions, such as time-dependent stimulation. We adopt a Bayesian approach to infer the model parameters from calcium oscillations. Under this approach we need to be able to infer the intensity function. One method is to use a parametric model for the intensity function. For example we could assume the intensity function has the linear form x(t) = at + b. Then the intensity function is reduced to only needing to infer the two parameters a and b. However, parametric models suffer from strict assumptions, in this case, for the shape of the intensity function. Therefore, to lessen such assumptions, we utilise a non-parametric approach. This requires a prior distribution over the space of functions. We use two such priors, namely Gaussian processes and piecewise constant functions. We use Markov chain Monte Carlo (MCMC) techniques to sample from the posterior distribution to obtain estimates for our model parameters. Although advan- tageous — due to sampling from the true posterior distribution — MCMC algorithms can experience issues relating to their computational cost and imprecise samplers. We discuss the issues arising for our particular model and data and develop methods to improve the functionality of the MCMC algorithms in this case. For example we discuss the difficulty of inferring the length scale of the Gaussian process when fitted from calcium oscillations. An important mechanism of calcium oscillations is the refractory period, the min- imum amount of time before the next calcium oscillation. Thus, it may be beneficial to explicitly include the refractory period as part of the model. We investigate the advantages and disadvantages of including the refractory period. We fit the model to HEK293 cells and astrocytes challenged under a variety of stimulation protocols. We find that our model can accurately generate surrogate spike sequences with similar properties to those the model is fitted from. Therefore, the model can be used to cheaply create spike sequences that are synonymous to those found experimentally. Moreover, our model captures the similarity between calcium spike sequences obtained from step-change stimulus protocols and constant stimulus protocols. Combining intensity functions inferred from constant stimulus experiments closely follow the intensity function from a step change experiment. This implies it may be possible to build surrogate spike sequences for complex time-dependent stimulation protocols by combining results from simpler experiments. Of particular interest are patterns found in the intensity function which describes the heterogeneity in the calcium oscillations over time. Common patterns could help to understand the different time scales of the calcium response. Standard approaches often fail in grouping intensity functions with similar shape. Therefore, we develop an approach to cluster intensity functions based on their shape alone by utilising the Haar basis. In summary, we have developed novel statistical approaches based on the concept of stochastic point processes and non-standard MCMC techniques. We have successfully applied these new methodologies to gain a deeper understanding into the stochastic nature of intracellular calcium oscillations, in particular how different cell types respond to a variety of stimulation protocols. In turn, this brings us one step closer to unravel the complex dynamics of this pivotal intracellular messenger which controls life from its very beginning to its end

Development of novel methods for obtaining robust dynamic susceptibility contrast magnetic resonance imaging biomarkers from diseased brain in children

Dynamic susceptibility contrast (DSC-) MRI is an important imaging technique from which estimates of perfusion measures including cerebral blood volume (CBV), cerebral blood flow (CBF) and mean transit time (MTT) can be calculated. These perfusion measures can be used to indicate health in a range of diseases. However, acquisition protocol varies from centre-to-centre, which leads to variability in data quality between centres and limits the clinical applicability of DSC-MRI. Currently, the recommended process for assessing data quality is by eye, which is very time consuming and subjective between reviewers. In this work an automated processing pipeline for DSC-MRI was produced. Work to develop the pipeline demonstrated that data quality of DSC-MRI data can be assessed using machine learning classifiers, which were trained using metrics calculated from the data and the results of qualitative review. It also showed that it was possible to denoise the data using singular value decomposition (SVD) based methods, which were validated on a simulator and confirmed in patient data. The pipeline created was applied to a multicentre patient dataset where it demonstrated the importance of denoising DSC-MRI data in improving data quality and how data quality can vary with acquisition protocol. It was also applied to a single centre study of patients receiving differing treatments for brain tumours and suggested there are no significant changes in relative CBV (rCBV) in non-tumour brain between differing treatment groups. The pipeline developed during this work has wider applications in other imaging modalities and could be adapted to be applied to other perfusion imaging methods, such as dynamic contrast enhanced (DCE-) MRI, or any other imaging modality that involves analysis of a signal variation with time, such as computed tomography (CT) perfusion imaging or positron emission tomography (PET)

Commercially Available Products in Increase Soil Water-Holding Capacity

Although adding organic matter is traditionally the most effective way to enhance soil water-holding capacity, several commercial products in the market also have the potential to increase soil water-holding capacity. In this fact sheet, we discuss the properties and characteristics of those commercially available products and recommended application rates. We also explore some limitations of using these products

Landscaping in the Utah Wildland-Urban Interface

The wildland-urban interface (WUI) is simply where human development mingles with wildland, or in other words, developed land next to undeveloped land. This area is at the highest risk for damage from wildfire. As our communities grow outward, the WUI is only expanding, putting more people at risk from wildfire. Therefore, it is important for homes built there to have fire-protective landscaping. Also, because Utah is a desert state currently in a drought, low-water landscaping is important for all Utah landscapes, including the WUI. This fact sheet addresses these issues and provides guidance on fire-protective and low-water landscaping

The mathematics pipeline in England: Patterns, interventions and excellence

This report from the Mathematics Pipeline Project (2021-23) presents a system-level overview of the mathematics pipeline in England for all young people in schools from age 4 to 16 and, thereafter, a diminishing number of students who proceed to study mathematics at A level, undergraduate and postgraduate level. The project was particularly interested in those students who have the potential to remain in the mathematics pipeline into advanced and higher education, what is termed the excellence stream in the report. The goal of the project was to better understand and visualise the whole pipeline and to identify areas where well-designed interventions might help to improve flow and diversity within the excellence stream. Whilst systemic change offers the potential for greatest impact, that was beyond the remit of the project. Rather, the report offers insights and ideas to individuals and organisations that might be interested in developing, or investing in, targeted interventions to improve the mathematics excellence stream in England

Developing and Piloting a Design Guide for Outdoor Classrooms in Utah

The outdoor classroom design guide can help applicants successfully apply for the Utah Outdoor Classroom Grant introduced by the Office of Outdoor Recreation (OOR) in 2021. The design guide includes case studies, design resources, and critical information for community involvement from statewide locations and will serve as a free public resource

Extension-Based Community Engagement Project Contributions to Landscape Architecture Core Competencies and Professional Values

This study evaluates the contribution of Extension-based community engagement design projects to the development of core technical competencies and professional values in the landscape architecture program at Utah State University. Many university design programs--including landscape architecture--employ community engagement to address local and regional design dilemmas. Programs within traditional agriculture schools often frame these activities as contributory to their institutions\u27 land-grant missions. Engaged scholarship is well enumerated within the literature of landscape architecture. However, little has been published on how Extension facilitates these engagements or its contribution to the development of core competencies and professional values. Utah State University\u27s (USU) landscape architecture program alumni and students were surveyed to determine their perceptions of Extension-based design projects\u27 contribution to the development of core competencies and professional values. Results revealed projects contribute to the development of core technical competencies including software skills, problem-solving, as well as acculturation of professional values and interpersonal skills such as collaboration, empathy, and leadership. As land-grant design programs assess the value of Extension-based community engagement projects, this study illuminates benefits for developing core competencies and professional values in the next generation of design practitioners

Collaborative Development of Utah\u27s Outdoor Recreation Strategic Plan: Process and Findings From 14 Regional Workshops

Outdoor recreation within Utah is managed and provided through a patchwork of federal and state agencies as well as county and municipal governments. Each of these entities manages outdoor recreation following different mandates and internal objectives. Rarely has there been an opportunity for representatives from federal, state, county, and local governments to sit down, discuss the long-standing and emerging challenges they face, and collectively develop ideas about how to work towards less-disparate and more aligned outdoor recreation management systems. In late 2022 and early 2023, we convened hundreds of land managers, outdoor recreation and tourism professionals, and elected officials across 14 workshops to do just that. The goals of the workshops were to: 1) facilitate a discussion about the threats to, and opportunities for, outdoor recreation within different regions of the state; and 2) use the identified threats and opportunities to solicit input on region-specific outdoor recreation policy, program, and project needs. Information gather through the workshop process was also used to identify outdoor recreation policy, program, and project needs common throughout the state. The common needs identified in the regional workshops directly informed the development of the objectives of Utah\u27s Outdoor Recreation Strategic Plan - a guiding document intended to improve outdoor recreation opportunities and support the alignment of policy and management actions across the many outdoor recreation providers within the state. The purpose of this report is to document the collaborative process for engaging stakeholders in the development of the objectives of Utah\u27s Outdoor Recreation Strategic Plan and to detail the findings generated from the process