Hamiltonian monte carlo with energy conserving subsampling

© 2019 Khue-Dung Dang, Matias Quiroz, Robert Kohn, Minh-Ngoc Tran, Mattias Villani. Hamiltonian Monte Carlo (HMC) samples efficiently from high-dimensional posterior distributions with proposed parameter draws obtained by iterating on a discretized version of the Hamiltonian dynamics. The iterations make HMC computationally costly, especially in problems with large data sets, since it is necessary to compute posterior densities and their derivatives with respect to the parameters. Naively computing the Hamiltonian dynamics on a subset of the data causes HMC to lose its key ability to generate distant parameter proposals with high acceptance probability. The key insight in our article is that efficient subsampling HMC for the parameters is possible if both the dynamics and the acceptance probability are computed from the same data subsample in each complete HMC iteration. We show that this is possible to do in a principled way in a HMC-within-Gibbs framework where the subsample is updated using a pseudo marginal MH step and the parameters are then updated using an HMC step, based on the current subsample. We show that our subsampling methods are fast and compare favorably to two popular sampling algorithms that use gradient estimates from data subsampling. We also explore the current limitations of subsampling HMC algorithms by varying the quality of the variance reducing control variates used in the estimators of the posterior density and its gradients

Potential reuse of coal mine wastewater: a case study in Quang Ninh, Vietnam

In Vietnam, the local regulation and environmental impact are driving coal mining industry to reuse the large volume of wastewater it produces. The co-research project between National University of Civil Engineering (NUCE) and Mitsubishi Rayon Corporation (MRC) has started early 2013 to evaluate if the MRC membranes could be a great tool for treatment of coal mine wastewater for reuse. The experiment were conducted at one of coal mine plants in Quang Ninh province, Vietnam. It was found that pre-treatment of coal mine wastewater was an important part in the treatment process. The MRC membrane was a significant barrier to maintain stable and high quality effluent to meet the requirement of Vietnam national technical standard for domestic use

From the factory to the field: considerations of product characteristics for insecticide-treated net (ITN) bioefficacy testing

BACKGROUND: Insecticide-treated nets (ITNs) undergo a series of tests to obtain listing by World Health Organization (WHO) Prequalification. These tests characterize the bioefficacy, physical and chemical properties of the ITN. ITN procurers assume that product specifications relate to product performance. Here, ITN test methods and their underlying assumptions are discussed from the perspective of the ITN manufacturing process and product characteristics. METHODS: Data were extracted from WHO Pesticide Evaluation Scheme (WHOPES) meeting reports from 2003 to 2017, supplemented with additional chemical analysis to critically evaluate ITNs bioassays with a focus on sampling, washing and wash resistance, and bioefficacy testing. Production methods for ITNs and their impact on testing outcomes are described. RESULTS AND RECOMMENDATIONS: ITNs are not homogenous products. They vary within panels and between the sides and the roof. Running tests of wash resistance using a before/after tests on the same sample or band within a net reduces test variability. As mosquitoes frequently interact with ITN roofs, additional sampling of the roof when evaluating ITNs is advisable because in nets where roof and sides are of the same material, the contribution of roof sample (20-25%) to the average is less than the tolerance for the specification (25%). Mosquito mortality data cannot be reliably used to evaluate net surface concentration to determine regeneration time (RT) and resistance to washing as nets may regenerate beyond the insecticide concentrations needed to kill 100% of susceptible mosquitoes. Chemical assays to quantify surface concentration are needed. The Wash Resistance Index (WRI) averaged over the first four washes is only informative if the product has a log linear loss rate of insecticide. Using a WRI that excludes the first wash off gives more reliable results. Storage conditions used for product specifications are lower than those encountered under product shipping and storage that may exceed 50 degrees C, and should be reconsidered. Operational monitoring of new ITNs and linking observed product performance, such as bioefficacy after 2 or 3 years of use, with product characteristics, such as WRI, will aid the development of more robust test methods and product specifications for new products coming to market

Eco-friendly facile synthesis of Co3O4-Pt nanorods for ethylene detection towards fruit quality monitoring

Ethylene, a biomarker widely employed for evaluating fruit ripening during storage, exists at extremely low concentrations. Therefore a gas sensor with high sensitivity and a sub-ppm detection limit is needed. In this work, porous Co3O4 nanorods were synthesized through a hydrothermal method involving Co(NO3)2, Na2C2O4, H2O and ethylene glycol (EG), followed by annealing at 400 degrees C in air. The surface of the porous Co3O4 nanorods was functionalized with Pt nanoparticles to enhance the ethylene sensing performance. The effect of Co3O4 surface functionalisation with Pt nanoparticles was investigated by adding different amounts of nanoparticles. The sensor's outstanding performance at the optimum working temperature of 250 degrees C is attributed to the synergy between the high catalytic activity of Pt nanoparticles and the extensive surface area of the porous Co3O4 nanorods. Compared to pure Co3O4, the 0.031 wt% Pt sensor showed better ethylene sensing performance with a response 3.4 times that of pristine Co3O4. The device also demonstrated high selectivity, repeatability, long-term stability and a detection limit of 0.13 ppm for ethylene, which is adequate for fruit quality monitoring. The gas sensing mechanism of porous Co3O4 nanorods and the influence of Pt decoration on sensor performance are discussed

Subsampling sequential Monte Carlo for static Bayesian models

© 2020, Springer Science+Business Media, LLC, part of Springer Nature. We show how to speed up sequential Monte Carlo (SMC) for Bayesian inference in large data problems by data subsampling. SMC sequentially updates a cloud of particles through a sequence of distributions, beginning with a distribution that is easy to sample from such as the prior and ending with the posterior distribution. Each update of the particle cloud consists of three steps: reweighting, resampling, and moving. In the move step, each particle is moved using a Markov kernel; this is typically the most computationally expensive part, particularly when the dataset is large. It is crucial to have an efficient move step to ensure particle diversity. Our article makes two important contributions. First, in order to speed up the SMC computation, we use an approximately unbiased and efficient annealed likelihood estimator based on data subsampling. The subsampling approach is more memory efficient than the corresponding full data SMC, which is an advantage for parallel computation. Second, we use a Metropolis within Gibbs kernel with two conditional updates. A Hamiltonian Monte Carlo update makes distant moves for the model parameters, and a block pseudo-marginal proposal is used for the particles corresponding to the auxiliary variables for the data subsampling. We demonstrate both the usefulness and limitations of the methodology for estimating four generalized linear models and a generalized additive model with large datasets

Analysis of Probability of Non-zero Secrecy Capacity for Multi-hop Networks in Presence of Hardware Impairments over Nakagami-m Fading Channels

In this paper, we evaluate probability of non-zero secrecy capacity of multi-hop relay networks over Nakagami-m fading channels in presence of hardware impairments. In the considered protocol, a source attempts to transmit its data to a destination by using multi-hop randomize-and-forward (RF) strategy. The data transmitted by the source and relays are overheard by an eavesdropper. For performance evaluation, we derive exact expressions of probability of non-zero secrecy capacity (PoNSC), which are expressed by sums of infinite series of exponential functions and exponential integral functions. We then perform Monte Carlo simulations to verify the theoretical analysis