CoinEM: Tuning-Free Particle-Based Variational Inference for Latent Variable Models

We introduce two new particle-based algorithms for learning latent variable models via marginal maximum likelihood estimation, including one which is entirely tuning-free. Our methods are based on the perspective of marginal maximum likelihood estimation as an optimization problem: namely, as the minimization of a free energy functional. One way to solve this problem is to consider the discretization of a gradient flow associated with the free energy. We study one such approach, which resembles an extension of the popular Stein variational gradient descent algorithm. In particular, we establish a descent lemma for this algorithm, which guarantees that the free energy decreases at each iteration. This method, and any other obtained as the discretization of the gradient flow, will necessarily depend on a learning rate which must be carefully tuned by the practitioner in order to ensure convergence at a suitable rate. With this in mind, we also propose another algorithm for optimizing the free energy which is entirely learning rate free, based on coin betting techniques from convex optimization. We validate the performance of our algorithms across a broad range of numerical experiments, including several high-dimensional settings. Our results are competitive with existing particle-based methods, without the need for any hyperparameter tuning

On the physics behind coastal morphodynamic patterns

Peer ReviewedPostprint (published version

On beach cusp formation

A system of shallow water equations and a bed evolution equation are used to examine the evolution of perturbations on an erodible, initially plane beach subject to normal wave incidence. Both a permeable (under Darcy's law) and an impermeable beach are considered. It is found that alongshore-periodic morphological features reminiscent of swash beach cusps form after a number of incident wave periods on both beaches. On the permeable (impermeable) beach these patterns are accretional (erosional). In both cases flow is ‘horn divergent’. Spacings of the cusps are consistent with observations, and are close to those provided by a standing synchronous linear edge wave. An analysis of the processes leading to bed change is presented. Two physical mechanisms are identified: concentration gradient and flow divergence, which are dominant in the lower and upper swash respectively, and their difference over a wave cycle leads to erosion or deposition on an impermeable beach. Infiltration enters this balance in the upper swash. A bed wave of elevation is shown to advance up the beach at the tip of the uprush, with a smaller wave of depression on the backwash. It is found that cusp horns can grow by a positive feedback mechanism stemming from decreased (increased) backwash on positive (negative) bed perturbations.Postprint (published version

Development of tools to explore the fundamentals of axonemal dynein heavy chain biology and improve the efficiency of genome editing

Motile cilia are microtubule based projections that assist in the movement of fluid over the surface of cells, such as in the respiratory epithelium, or of cells through a fluid, such as in sperm. Ciliary movement is driven by axonemal dyneins (ADs), large molecular complexes which contain long heavy chain ATPase motor subunits. The stability of ADs has been shown to be dependent on multiple cytoplasmically localised proteins, which are involved in their assembly and trafficking to the cilia. The heavy chain subunits have been suggested to be particularly reliant on specialised chaperoning pathways in order to fold into the correct tertiary structure. Hereditary defects in genes encoding the proteins of the ADs or proteins involved in their assembly result in an incurable human disease, primary ciliary dyskinesia (PCD). PCD results in neonatal respiratory distress with lifelong respiratory complications and is also highly heterogenous with mutations in 40 genes associated with it so far. Despite the identification of many putative assembly factors, where and how they interact with AD proteins remains unknown. In order to investigate AD complexes, from the translation of their subunits to their degradation, in greater spatial and temporal detail a heavy chain outer dynein arm subunit (ODA), Dnah5, was tagged with the adaptable SNAP tag in mice. Dnah5 is the largest AD heavy chain and the most commonly mutated gene in PCD. When developing novel therapeutics the SNAP-Dnah5 mouse could be used as a reporter for functional rescue in PCD mouse models which exhibit loss of these complexes from the cilia. The effectiveness of the therapy could then be graded on the restoration of SNAP-DNAH5 fluorescence in the motile cilia. As a secondary aim this project also sought to improve the efficiency of CRISPR/Cas9 induced gene correction, via a novel linkage method, to develop a genome editing therapy for PCD, which could be tested using SNAP-Dnah5 mice. Using the SNAP-Dnah5 mouse tracheal epithelial cells I have directly imaged DNAH5’s docking onto the motile axoneme from the distal end and have demonstrated that there is a very low level of ODA turnover in mature cilia. I have also shown that the Dnah5 transcript localises to large apical clusters in ciliated tracheal epithelial cells and via preliminary pulldown experiments that SNAPDNAH5 might interact with RNA regulatory proteins in maturing motile ciliated cells suggestive of translational regulation. This project demonstrates the utility of this mouse model for future studies

Effects of Resistance Training on Smoking Abstinence Self-Efficacy in Sedentary Smokers

ABSTRACT Introduction: Cigarette smoking is prevalent with 40 million Americans smoking and one in five deaths attributed to this behavior. Aims: This study examined effects of a resistance training (RT) program on smoking abstinence self-efficacy. Methods: Forty (40) participants were randomized into intervention or control groups. Smoking abstinence self-efficacy, withdrawal symptoms, and smoking behavior were measured. Results/Findings: RT group presented with statistically significant greater increases in self-efficacy compared to control. RT group participants also presented with non-significantly greater decreases in smoking behavior and withdrawal symptoms compared to control. Conclusions: This study demonstrates effectiveness of RT in improving smoking abstinence self-efficacy