1,636 research outputs found
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
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