Self-consistent continuum solvation (SCCS): The case of charged systems

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Deep heteroscedastic regression involves jointly optimizing the mean and covariance of the predicted distribution using the negative log-likelihood. However, recent works show that this may result in sub-optimal convergence due to the challenges associated ...

Polyelectrolyte brushes are responsive to salt in the environment, and this has found broad applications in antifouling, biolubrication, and drug delivery. Salt primarily influences the conformation of the polyelectrolytes through ion adsorption. While ion ...

The combination of palladium salts and bipyridyl ligands can lead to the formation of a large variety of coordination complexes, with different shapes and sizes, displaying a very versatile host-guest chemistry. Increasing their structural complexity remai ...

Deep learning models (DLM) are efficient replacements for computationally intensive optimization techniques. Musculoskeletal models (MSM) typically involve resource-intensive optimization processes for determining joint and muscle forces. Consequently, DLM ...

In this work, we systematically evaluate the accuracy in band gap prediction of range-separated hybrid functionals on a large set of semiconducting and insulating materials and carry out comparisons with the performance of their global counterparts. We obs ...

Purpose: To develop a self-navigated motion compensation strategy for 3D radial MRI that can compensate for continuous head motion by measuring rigid body motion parameters with high temporal resolution from the central k-space acquisition point (self-enco ...

Second-order Moller-Plesset perturbation theory (MP2) is the most expedient wave function-based method for considering electron correlation in quantum chemical calculations and, as such, provides a cost-effective framework to assess the effects of basis se ...

Due to the subtle balance of intermolecular interactions that govern structure-property relations, predicting the stability of crystal structures formed from molecular building blocks is a highly non-trivial scientific problem. A particularly active and fr ...

The high zinc and iron contents of electric arc furnace (EAF) dust in the forms of zinc ferrite (ZnFe2O4) and magnetite (Fe3O4) make it a valuable secondary source of these metals. ZnFe2O4 and Fe3O4 are known to form a solid solution at all compositions, a ...

The analysis of motor evoked potentials (MEPs) generated by transcranial magnetic stimulation (TMS) is crucial in research and clinical medical practice. MEPs are characterized by their latency and the treatment of a single patient may require the characte ...

Demand forecasting is becoming increasingly important as firms launch new products with short life cycles more frequently. This paper provides a framework based on state-of-the-art techniques that enables firms to use quantitative methods to forecast sales ...

We develop a computationally efficient scheme to accurately determine finite-temperature band gaps for metal halide perovskites belonging to the class ABX(3) (A = Rb, Cs; B = Ge, Sn, Pb; and X = F, Cl, Br, I). First, an initial estimate of the band gap is ...

Predicting wind flow in highly complex terrain like the Alps is a challenge for all models. When physical processes need to be resolved in a spatially explicit manner, grids with high horizontal resolution of a few hundred meters are often required and dra ...

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 ...

The modeling of non-covalent interactions, solvation effects, and chemical reactions in complex molecular environment is a challenging task. Current state-of-the-art approaches often rely on static computations using implicit solvent models and harmonic ap ...

Background: Signal processing tools are required to efficiently analyze data collected in body-surface-potential map (BSPM) recordings. A limited number of such tools exist for studying persistent atrial fibrillation (persAF). We propose two novel, spatiot ...

To improve the accuracy of bifacial gain estimation, recent radiative models of solar energy systems have abandoned the traditional assumption of isotropic ground-reflected radiance. However, surface reflectance itself is still commonly considered as a con ...

Poor decisions and selfish behaviors give rise to seemingly intractable global problems, such as the lack of transparency in democratic processes, the spread of conspiracy theories, and the rise in greenhouse gas emissions. However, people are more predict ...

In the past two decades, wind energy has been under fast development worldwide. The dramatic increase of wind power penetration in electricity production has posed a big challenge to grid integration due to the high uncertainty of wind power. Accurate real ...

Non-covalent interactions are ubiquitous in nature. The diversity and functionality of these interactions are employed by nature as a universal tool for building the molecular mechanism of life. Although weak, these interactions play a key role in both for ...

Self-consistent continuum solvation (SCCS): The case of charged systems

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TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

Ion Adsorption Enhances Apparent Nonelectrostatic Attraction between Monomers in Polyelectrolyte Brushes

Palladium-based supramolecular assemblies: from complex structures to water-soluble anion-receptors

Glenohumeral joint force prediction with deep learning

Range-separated hybrid functionals for accurate prediction of band gaps of extended systems

Rapid motion estimation and correction using self-encoded FID navigators in 3D radial MRI

Plane Waves Versus Correlation-Consistent Basis Sets: A Comparison of MP2 Non-Covalent Interaction Energies in the Complete Basis Set Limit

A data-driven interpretation of the stability of organic molecular crystals

Enhanced Leaching of Zinc Ferrite by the Formation of a Solid Solution With Magnetite in Hydrochloric Acid Solution

DELMEP: a deep learning algorithm for automated annotation of motor evoked potential latencies

A Machine Learning-based Framework for Forecasting Sales of New Products With Short Life Cycles Using Deep Neural Networks

Accurate and efficient band-gap predictions for metal halide perovskites at finite temperature

Wind-Topo: Downscaling near-surface wind fields to high-resolution topography in highly complex terrain with deep learning

Virtual metrology applied to milling process

Modeling non-covalent interactions in condensed phase

Novel spatiotemporal processing tools for body-surface potential map signals for the prediction of catheter ablation outcome in persistent atrial fibrillation

Worldwide performance evaluation of ground surface reflectance models

Discrete-Choice Mining of Social Processes

Numerical Weather Prediction and Artificial Neural Network Coupling for Wind Energy Forecast

Structural and analytical identifications of biomolecules by cold ion spectroscopy of non-covalent complexes