Efficient Alternating Minimization Solvers for Wyner Multi-View Unsupervised Learning

In this work, we adopt Wyner common information framework for unsupervised multi-view representation learning. Within this framework, we propose two novel formulations that enable the development of computational efficient solvers based on the alternating minimization principle. The first formulation, referred to as the {\em variational form}, enjoys a linearly growing complexity with the number of views and is based on a variational-inference tight surrogate bound coupled with a Lagrangian optimization objective function. The second formulation, i.e., the {\em representational form}, is shown to include known results as special cases. Here, we develop a tailored version from the alternating direction method of multipliers (ADMM) algorithm for solving the resulting non-convex optimization problem. In the two cases, the convergence of the proposed solvers is established in certain relevant regimes. Furthermore, our empirical results demonstrate the effectiveness of the proposed methods as compared with the state-of-the-art solvers. In a nutshell, the proposed solvers offer computational efficiency, theoretical convergence guarantees (local minima), scalable complexity with the number of views, and exceptional accuracy as compared with the state-of-the-art techniques. Our focus here is devoted to the discrete case and our results for continuous distributions are reported elsewhere

Optimal control analysis of a malaria transmission model with applications to Democratic Republic of Congo

In this paper, a dynamical model of malaria transmission with vector-bias and timedependent controls is investigated. The controls include the RTS,S malaria vaccine, using insecticide-treated mosquito net, treatment of infectious human, and indoor spraying. For constant controls, the existence and stability of equilibrium, as well as the existence of backward bifurcation, are obtained. The sensitivity analysis quantifies the impact of parameters and controls on the basic reproduction number. For time-dependent controls, by using the Pontryagin’s maximum principle the existence and expression of optimal controls are established. As an application of the model and control strategies, the malaria transmission and controls in Democratic Republic of Congo are discussed. To be specific, we simulate the reported cases of Democratic Republic of Congo by World Health Organization and predict the trends. Cost-effectiveness analysis and numerical simulations show that combining all controls can minimize the number of infected humans to the full extent, using insecticide-treated mosquito net is the most cost-effectiveness strategy, combining RTS,S malaria vaccine with using insecticide-treated mosquito net and treatment of infectious human is also cost-effective among all the strategies with good effect

The Wyner Variational Autoencoder for Unsupervised Multi-Layer Wireless Fingerprinting

Wireless fingerprinting refers to a device identification method leveraging hardware imperfections and wireless channel variations as signatures. Beyond physical layer characteristics, recent studies demonstrated that user behaviours could be identified through network traffic, e.g., packet length, without decryption of the payload. Inspired by these results, we propose a multi-layer fingerprinting framework that jointly considers the multi-layer signatures for improved identification performance. In contrast to previous works, by leveraging the recent multi-view machine learning paradigm, i.e., data with multiple forms, our method can cluster the device information shared among the multi-layer features without supervision. Our information-theoretic approach can be extended to supervised and semi-supervised settings with straightforward derivations. In solving the formulated problem, we obtain a tight surrogate bound using variational inference for efficient optimization. In extracting the shared device information, we develop an algorithm based on the Wyner common information method, enjoying reduced computation complexity as compared to existing approaches. The algorithm can be applied to data distributions belonging to the exponential family class. Empirically, we evaluate the algorithm in a synthetic dataset with real-world video traffic and simulated physical layer characteristics. Our empirical results show that the proposed method outperforms the state-of-the-art baselines in both supervised and unsupervised settings

A Mechanistic Study of Carbonic Anhydrase Enhanced Calcite Dissolution

Carbonic anhydrase (CA) has been shown to promote calcite dissolution (Liu, 2001, https://doi.org/10.1111/j.1755-6724.2001.tb00531.x; Subhas et al., 2017, https://doi.org/10.1073/pnas.1703604114), and understanding the catalytic mechanism will facilitate our understanding of the oceanic alkalinity cycle. We use atomic force microscopy (AFM) to directly observe calcite dissolution in CA‐bearing solution. CA is found to etch the calcite surface only when in extreme proximity (~1 nm) to the mineral. Subsequently, the CA‐induced etch pits create step edges that serve as active dissolution sites. The possible catalytic mechanism is through the adsorption of CA on the calcite surface, followed by proton transfer from the CA catalytic center to the calcite surface during CO2 hydration. This study shows that the accessibility of CA to particulate inorganic carbon (PIC) in the ocean is critical in properly estimating oceanic CaCO3 and alkalinity cycles

A Mechanistic Study of Carbonic Anhydrase Enhanced Calcite Dissolution

Carbonic anhydrase (CA) has been shown to promote calcite dissolution (Liu, 2001, https://doi.org/10.1111/j.1755-6724.2001.tb00531.x; Subhas et al., 2017, https://doi.org/10.1073/pnas.1703604114), and understanding the catalytic mechanism will facilitate our understanding of the oceanic alkalinity cycle. We use atomic force microscopy (AFM) to directly observe calcite dissolution in CA‐bearing solution. CA is found to etch the calcite surface only when in extreme proximity (~1 nm) to the mineral. Subsequently, the CA‐induced etch pits create step edges that serve as active dissolution sites. The possible catalytic mechanism is through the adsorption of CA on the calcite surface, followed by proton transfer from the CA catalytic center to the calcite surface during CO2 hydration. This study shows that the accessibility of CA to particulate inorganic carbon (PIC) in the ocean is critical in properly estimating oceanic CaCO3 and alkalinity cycles

Weight management for patients in general practice tailored to health literacy

Our aim was to develop and evaluate the feasibility and impact of a PHC approach to weight management tailored to the level of health literacy of obese patients. There were three key activities undertaken in this regard: 1) a literature review; 2) a pilot study; and 3) a weight management trial called “Better Management of Weight in General Practice” (BMWGP). In this report we describe the three activities and use the BMWGP baseline data to explore three issues. First, we look at the effectiveness of a screening tool to identify patients with low health literacy in general practice. Second, we describe the association between health literacy and a range of factors, behavioural intentions, lifestyle behaviours and quality of life to better understand the link between health literacy and health in a population of patients with obesity attending general practices. Third, we identify the groups most likely to experience weight stigma and how stigma relates to health literacy.The research reported in this paper is a project of the Australian Primary Health Care Research Institute which is supported by a grant from the Australian Government Department of Health and Ageing under the Primary Health Care Research Evaluation and Development Strategy

An Atomic Force Microscopy Study of Calcite Dissolution in Seawater

We present the first examination of calcite dissolution in seawater using Atomic Force Microscopy (AFM). We quantify step retreat velocity and etch pit density to compare dissolution in seawater to low ionic strength water, and also to compare calcite dissolution under AFM conditions to those conducted in bulk solution experiments (e.g. Subhas et al., 2015, Dong et al., 2018). Bulk dissolution rates and step retreat velocities are slower at high and mid-saturation state (Ω) values and become comparable to low ionic strength water rates at low Ω. The onset of defect-assisted etch pit formation in seawater is at Ω ∼ 0.85 (defined as Ω_(critical)), higher than in low ionic strength water (Ω ∼ 0.54). There is an abrupt increase in etch pit density (from ∼10⁶ cm⁻² to ∼10⁸ cm⁻²) occurring when Ω falls below 0.7 in seawater, compared to Ω ∼ 0.1 in low ionic strength water, suggesting a transition from defect-assisted dissolution to homogeneous dissolution much closer to equilibrium in seawater. The step retreat velocity (v) does not scale linearly with undersaturation (1-Ω) across an Ω range of 0.4 to 0.9 in seawater, potentially indicating a high order correlation between kink rate and Ω for non-Kossel crystals such as calcite, or surface complexation processes during calcite dissolution in seawater