It is increasingly recognized that a key component of successful infection control efforts is understanding the complex, two-way interaction between disease dynamics and human behavioral and social ...dynamics. Human behavior such as contact precautions and social distancing clearly influence disease prevalence, but disease prevalence can in turn alter human behavior, forming a coupled, nonlinear system. Moreover, in many cases, the spatial structure of the population cannot be ignored, such that social and behavioral processes and/or transmission of infection must be represented with complex networks. Research on studying coupled disease–behavior dynamics in complex networks in particular is growing rapidly, and frequently makes use of analysis methods and concepts from statistical physics. Here, we review some of the growing literature in this area. We contrast network-based approaches to homogeneous-mixing approaches, point out how their predictions differ, and describe the rich and often surprising behavior of disease–behavior dynamics on complex networks, and compare them to processes in statistical physics. We discuss how these models can capture the dynamics that characterize many real-world scenarios, thereby suggesting ways that policy makers can better design effective prevention strategies. We also describe the growing sources of digital data that are facilitating research in this area. Finally, we suggest pitfalls which might be faced by researchers in the field, and we suggest several ways in which the field could move forward in the coming years.
•We systematically survey how the behavior affects disease spreading and prevention in well-mixed and networked populations.•The coupled disease–behavior dynamics is closely related with evolution or economic rules, and further influences the pattern formation.•Theoretical prediction gets the empirical validation via digital data or experiments.•Many novel findings or phenomena need the support of methods in statistical physics.
The reactions between SO.sub.3 and atmospheric acids are indispensable in improving the formation of aerosol particles. However, relative to those of SO.sub.3 with organic acids, the reaction of ...SO.sub.3 with inorganic acids has not received much attention. Here, we explore the atmospheric reaction between SO.sub.3 and H.sub.2 SO.sub.4, a typical inorganic acid, in the gas phase and at the air-water interface using quantum chemical (QC) calculations and Born-Oppenheimer molecular dynamics simulations. We also report the effect of H.sub.2 S.sub.2 O.sub.7, the product of the reaction between SO.sub.3 and H.sub.2 SO.sub.4, on new particle formation (NPF) in various environments using the Atmospheric Cluster Dynamics Code (ACDC) kinetic model and QC calculations. The present findings show that the gas-phase reactions of SO.sub.3 + H.sub.2 SO.sub.4 without and with water molecules are both low-energy-barrier processes. With the involvement of interfacial water molecules, H.sub.2 O induced the formation of the S2O72-â¯H3O+ ion pair, HSO4- mediated the formation of the HSO4-â¯H3O+ ion pair, and the deprotonation of H.sub.2 S.sub.2 O.sub.7 was observed and proceeded on the picosecond timescale. The present findings suggest the potential contribution of the SO.sub.3 -H.sub.2 SO.sub.4 reaction to NPF and aerosol particle growth, showing that (i) although H.sub.2 S.sub.2 O.sub.7 is easily hydrolyzed with water to form H.sub.2 SO.sub.4, it can directly participate in H.sub.2 SO.sub.4 -NH.sub.3 -based cluster formation and can present a more obvious enhancement effect on SA-A-based cluster formation, and (ii) the formed interfacial S2O72- can attract candidate species from the gas phase to the water surface and, thus, accelerate particle growth.
Ligand binding affinity calculations based on molecular dynamics (MD) simulations and non-physical (alchemical) thermodynamic cycles have shown great promise for structure-based drug design. However, ...their broad uptake and impact is held back by the notoriously complex setup of the calculations. Only a few tools other than the free energy perturbation approach by Schrödinger Inc. (referred to as FEP+) currently enable end-to-end application. Here, we present for the first time an approach based on the open-source software pmx that allows to easily set up and run alchemical calculations for diverse sets of small molecules using the GROMACS MD engine. The method relies on theoretically rigorous non-equilibrium thermodynamic integration (TI) foundations, and its flexibility allows calculations with multiple force fields. In this study, results from the Amber and Charmm force fields were combined to yield a consensus outcome performing on par with the commercial FEP+ approach. A large dataset of 482 perturbations from 13 different protein–ligand datasets led to an average unsigned error (AUE) of 3.64 ± 0.14 kJ mol −1 , equivalent to Schrödinger's FEP+ AUE of 3.66 ± 0.14 kJ mol −1 . For the first time, a setup is presented for overall high precision and high accuracy relative protein–ligand alchemical free energy calculations based on open-source software.
Although the vortex is ubiquitous in nature, its definition is somewhat ambiguous in the field of fluid dynamics. In this absence of a rigorous mathematical definition, considerable confusion appears ...to exist in visualizing and understanding the coherent vortical structures in turbulence. Cited in the previous studies, a vortex cannot be fully described by vorticity, and vorticity should be further decomposed into a rotational and a non-rotational part to represent the rotation and the shear, respectively. In this paper, we introduce several new concepts, including local fluid rotation at a point and the direction of the local fluid rotation axis. The direction and the strength of local fluid rotation are examined by investigating the kinematics of the fluid element in two- and three-dimensional flows. A new vector quantity, which is called the vortex vector in this paper, is defined to describe the local fluid rotation and it is the rotational part of the vorticity. This can be understood as that the direction of the vortex vector is equivalent to the direction of the local fluid rotation axis, and the magnitude of vortex vector is the strength of the location fluid rotation. With these new revelations, a vortex is defined as a connected region where the vortex vector is not zero. In addition, through direct numerical simulation (DNS) and large eddy simulation (LES) examples, it is demonstrated that the newly defined vortex vector can fully describe the complex vertical structures of turbulence.
In many plants, vibration and noise problems occur due to fluid flow, which can greatly disrupt smooth plant operations. These flow-related phenomena are called Flow-Induced Vibration.This book ...explains how and why such vibrations happen and provides hints and tips on how to avoid them in future plant design. The world-leading author team doesn't assume prior knowledge of mathematical methods and provide the reader with information on the basics of modeling. The book includes several practical examples and thorough explanations of the structure, the evaluation method and the mechanisms to aid understanding of flow induced vibration.* Helps ensure smooth plant operations * Explains the structure, evaluation method and mechanisms * Shows how to avoid vibrations in future plant design
This paper presents a Hamiltonian-driven framework of adaptive dynamic programming (ADP) for continuous time nonlinear systems, which consists of evaluation of an admissible control, comparison ...between two different admissible policies with respect to the corresponding the performance function, and the performance improvement of an admissible control. It is showed that the Hamiltonian can serve as the temporal difference for continuous-time systems. In the Hamiltonian-driven ADP, the critic network is trained to output the value gradient. Then, the inner product between the critic and the system dynamics produces the value derivative. Under some conditions, the minimization of the Hamiltonian functional is equivalent to the value function approximation. An iterative algorithm starting from an arbitrary admissible control is presented for the optimal control approximation with its convergence proof. The implementation is accomplished by a neural network approximation. Two simulation studies demonstrate the effectiveness of Hamiltonian-driven ADP.
Brunk and Rothlisberger examine mixed quantum mechanical (QM)/molecular mechanical (MM) molecular dynamics (MD) simulations of biological systems in ground and electronically excited states. They ...present a basic theory of quantum mechanical phenomena in biological systems, detal the QM/MM approach, discuss applications of QM/MM MD, and analyze high-dimensional data sets.
Metal hydrides are suitable for the compact, efficient and safe storage of hydrogen. Considering hydride-based hydrogen storage tanks, the enhancement of the heat and gas transport properties of the ...hydride bed is crucial for increased (un-)loading dynamics of the tank. In this contribution, pelletized composites of different hydrogen storage materials (lithium amide, sodium alanate, magnesium hydride and transition metal hydride Hydralloy C5) with expanded natural graphite (ENG) are discussed. The materials were admixed with up to 25 wt.% ENG and compacted at compaction pressures up to 600 MPa. The resulting hydride-ENG pellets exhibit an increased effective thermal conductivity which can be tuned in a wide range. The pellets have an increased volumetric H2 storage capacity compared to loose hydride powders. High gas permeability in radial direction and sufficient thermal conductivity (>10 W m-1 K-1) in combination with a stable pellet structure indicate a high potential to use suchlike prepared hydride-ENG composites for hydrogen storage applications with high loading dynamics.
Forced oscillations may jeopardize the secure operation of power systems. To mitigate forced oscillations, locating the sources is critical. In this paper, leveraging on Sparse Identification of ...Nonlinear Dynamics (SINDy), an online purely data-driven method to locate the forced oscillation is developed. Validations in all simulated cases (in the WECC 179-bus system) and actual oscillation events (in ISO New England system) in the IEEE Task Force test cases library are carried out, which demonstrate that the proposed algorithm, requiring no model information, can accurately locate sources in most cases, even under resonance condition and when the natural modes are poorly damped. The little tuning requirement and low computational cost make the proposed method viable for online application.
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