Optimised accelerated solvent extraction of PCBs and PAHs from compost

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In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

Surrogate-based optimization is widely used for aerodynamic shape optimization, and its effectiveness depends on representative sampling of the design space. However, traditional sampling methods are hard-pressed to effectively sample high-dimensional desi ...

The analysis of proteins in the gas phase benefits from detectors that exhibit high efficiency and precise spatial resolution. Although modern secondary electron multipliers already address numerous analytical requirements, additional methods are desired f ...

Domain generalization (DG) aims to learn a model from multiple training (i.e., source) domains that can generalize well to the unseen test (i.e., target) data coming from a different distribution. Single domain generalization (SingleDG) has recently emerge ...

Background Universal access to basic sanitation remains a global challenge, particularly in low- and middle-income countries. Efforts are underway to improve access to sanitation in informal settlements, often through shared facilities. However, access to ...

Bioaerosols are emitted from various sources into the indoor environment and can positively and negatively impact human health. Humans are the major source of bioaerosol emissions indoors, specifically for bacteria. However, efficient sampling to guarantee ...

Hybrid halide perovskites are currently one of the most studied semiconductors. However, due to poor intrinsic and extrinsic stability, further developments to commercialize devices based on hybrid halide perovskites are limited. Many different strategies ...

This work aims to study the effects of wind uncertainties in civil engineering structural design. Optimising the design of a structure for safety or operability without factoring in these uncertainties can result in a design that is not robust to these per ...

We generalize the hidden-fermion family of neural network quantum states to encompass both continuous and discrete degrees of freedom and solve the nuclear many-body Schrodinger equation in a systematically improvable fashion. We demonstrate that adding hi ...

Production quality and process efficiency are the two main drivers that lead any industrial strategy. To ensure product quality, a duality historically existed between two approaches, namely batch sampling and systematic sampling. In batch sampling, the ba ...

Measuring the thermoelectric transport properties of a material is a prerequisite to determining its usefulness for application in waste heat recovery or cooling and the basis for devising improvement strategies. While well-established characterization met ...

The present invention describes an imaging system that allows visualization of a wide range of samples both in terms of morphology and in terms of material (e.g. density distribution, varying chemical composition, or anything that induces a change of optic ...

We consider the numerical approximation of an optimal control problem for an elliptic Partial Differential Equation (PDE) with random coefficients. Specifically, the control function is a deterministic, distributed forcing term that minimizes the expected ...

Enhanced sampling techniques have become an essential tool in computational chemistry and physics, where they are applied to sample activated processes that occur on a time scale that is inaccessible to conventional simulations. Despite their popularity, i ...

Physically based rendering is a process for photorealistic digital image synthesis and one of the core problems in computer graphics. It involves simulating the light transport, i.e. the emission, propagation, and scattering of light through a virtual scen ...

We analyze about 200 naturally occurring networks with distinct dynamical origins to formally test whether the commonly assumed hypothesis of an underlying scale-free structure is generally viable. This has recently been questioned on the basis of statisti ...

Environmental pollutants including emerging contaminants are a growing concern worldwide. Organic wastes, such as food waste, compost, animal manure, crop residues, and sludge are generally used as feedstock. The conventional treatment methodologies (prima ...

While the extant innovation literature has provided extensive evidence of the so-called "demand-pull" effect, the possible diverse impact of demand evolution on product vs process innovation activities has not been yet investigated. This paper develops a f ...

Weighted least squares polynomial approximation uses random samples to determine projections of functions onto spaces of polynomials. It has been shown that, using an optimal distribution of sample locations, the number of samples required to achieve quasi ...

The maximal achievable advantage of a (computationally unbounded) distinguisher to determine whether a source

Z

is distributed according to distribution

P_0

P_1

, when given access to one sample of

Z

, is characterized by the statistical distance ...

Optimised accelerated solvent extraction of PCBs and PAHs from compost

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Gibbs sampling the posterior of neural networks

DiffAirfoil: An Efficient Novel Airfoil Sampler Based on Latent Space Diffusion Model for Aerodynamic Shape Optimization

Highly sensitive single-molecule detection of macromolecule ion beams

Center-aware Adversarial Augmentation for Single Domain Generalization

Environmental determinants of access to shared sanitation in informal settlements: a cross-sectional study in Abidjan and Nairobi

Comparison of two methods for bioaerosol sampling and characterization in a low-biomass chamber environment

Structure-property relationships and mixed conductivity in layered hybrid perovskites based on phenyl-derived spacers

Multi-Level Monte Carlo Methods for Uncertainty Quantification and Risk-Averse Optimisation

Hidden-nucleons neural-network quantum states for the nuclear many-body problem

Virtual metrology applied to milling process

Development of microdevices for the in-plane thermoelectric characterization of deposited films

System and methods for differential imaging using a lock-in camera

Complexity analysis of stochastic gradient methods for PDE-constrained optimal control problems with uncertain parameters

Global Free-Energy Landscapes as a Smoothly Joined Collection of Local Maps

Light Path Gradients for Forward and Inverse Rendering

True scale-free networks hidden by finite size effects

Biochar and environmental sustainability: Emerging trends and techno-economic perspectives

The role of demand in fostering product vs process innovation: a model and an empirical test

Multilevel weighted least squares polynomial approximation

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples