Neural quantum states (NQS) are a novel class of variational many-body wave functions that very flexible in approximating diverse states. Optimization an NQS ansatz requires sampling from the corresponding probability distribution defined by squared function amplitude. For this purpose we propose to use kinetic protocols and demonstrate many important cases such methods lead much smaller autoco...

Monte Carlo approaches have recently been proposed to quantify connectivity in neuronal networks. The key problem is to sample from the conditional distribution of a single neuronal spike train, given the activity of the other neurons in the network. Dependencies between neurons are usually relatively weak; however, temporal dependencies within the spike train of a single neuron are typically s...

A series of interstitial faunal samples was taken from a riffle in the Speed River, southern Ontario, Canada, to compare the field performance of four hyporheic samplers: the standpipe, colonization, and freeze corers and a pump sampler. Each of the samplers proved useful for collecting purely qualitative data, but statistical differences in some of the measured quantitative parameters were ide...

Little is known of the distribution of persistent organic pollutants (POPs) in the deep ocean. Polyethylene passive samplers were used to detect the vertical distribution of truly dissolved POPs at two sites in the Atlantic Ocean. Samplers were deployed at five depths covering 26-2535 m in the northern Atlantic and Tropical Atlantic, in approximately one year deployments. Samplers of different ...

The regulation of particulate matter (PM) emitted by agricultural sources (cotton gins, feed mills, concentrated animal feeding operations (CAFOs) is based upon downwind concentrations of particulate matter less than 10 and 2.5 micrometers (μm) (PM10 and PM2.5) aerodynamic equivalent diameter (AED). Both PM10 and PM2.5 samplers operate by pre-separating PM larger than the size of interest (10 a...

The logistic linear mixed model (LLMM) is one of the most widely used statistical models. Generally, Markov chain Monte Carlo algorithms are to explore posterior densities associated with Bayesian LLMMs. Polson, Scott and Windle’s (2013) Pólya-Gamma data augmentation (DA) technique can be construct full Gibbs (FG) samplers for Here, we develop efficient block (BG) LLMMs using DA method. We comp...

introduction: toluene is an organic solvent that it is one of the byproducts in the coke industry. exposure to toluene causes central nervous system dysfunction and others disorders. many workers are exposed to toluene due to leakage from tracks. therefore the aim of this study was to determine the levels of exposure through environmental and biological monitoring of toluene methods: air toluen...