A Graph-Based Framework for Multiscale Modeling of Physiological Transport

Trillions of chemical reactions occur in the human body every second, where the generated products are not only consumed locally but also transported to various locations in a systematic manner to sustain homeostasis. Current solutions to model these biological phenomena are restricted in computability and scalability due to the use of continuum approaches in which it is practically impossible to encapsulate the complexity of the physiological processes occurring at diverse scales. Here, we present a discrete modeling framework defined on an interacting graph that offers the flexibility to model multiscale systems by translating the physical space into a metamodel. We discretize the graph-based metamodel into functional units composed of well-mixed volumes with vascular and cellular subdomains; the operators defined over these volumes define the transport dynamics. We predict glucose drift governed by advective–dispersive transport in the vascular subdomains of an islet vasculature and cross-validate the flow and concentration fields with finite-element–based COMSOL simulations. Vascular and cellular subdomains are coupled to model the nutrient exchange occurring in response to the gradient arising out of reaction and perfusion dynamics. The application of our framework for modeling biologically relevant test systems shows how our approach can assimilate both multi-omics data from in vitro–in vivo studies and vascular topology from imaging studies for examining the structure–function relationship of complex vasculatures. The framework can advance simulation of whole-body networks at user-defined levels and is expected to find major use in personalized medicine and drug discovery.

Four Years of Sediment and Phosphorus Monitoring in the Kraichbach River Using Large-Volume Samplers

Various sampling strategies come into operation to monitor water quality in rivers. Most frequently, grab samples are taken, but they are not suitable for recording the highly dynamic transport of solids and solid-bound pollutants. Composite samples reduce the influence of input and transport dynamics and are better suited to determine the annual river loads. Large-volume samplers (LVSs) produce both a composite sample over a long period of time and an amount of solids which allows for further analyses. In the small sub-catchment area of the Kraichbach river in Baden-Wuerttemberg (Germany) two LVSs have been installed to sample the river flow. The concentration of solids and phosphorus in the supernatant water and the settled sediment in the sampler have been determined and mean concentrations have been derived. Annual river loads were calculated in combination with discharge data from the nearby gauging station. Two sampling strategies of the LVS were tested and compared. For the first strategy, the LVS was used to collect quasi-continuous composite samples throughout the year, whereas, with the second strategy, samples were taken specifically for different flow conditions (low, mean and high flow). This study compares the advantages and constraints of both strategies. Results indicate that the first strategy is better suited to determine annual river loads. Quasi-continuous large-volume composite sampling is recommended for further monitoring campaigns.

Modeling Horizontal Salt Cavern Leaching in Bedded Salt Formations

Summary The leaching of a salt cavern will trigger a series of rock-fluid interactions, including salt rock dissolution, cavity expansion, and brine transport caused by convection, turbulence, and diffusion effects. These interactions have influences on one another. The primary objectives of this study include developing a 3D multiphysical coupled model for horizontal salt cavern leaching and quantifying these interactions. The species transport equation and standard κ-ε equation were combined to describe the brine transport dynamics within the cavity. Based on the velocity and concentration distribution characteristics predicted, the interface movement equation implemented with mesh deformation techniques was applied to describe the cavity expansion. Next, the Volgograd cavern monitored data were collected for model validation. The predicted results are consistent with the field data. The average relative errors are 11.0% for brine displacing concentration and 4.5% for cavity volume. The results suggest that the cavity can be divided into three regions, including the main flow region, circulation region, and reflux region. The results also suggest that the brine concentration distribution is relatively uniform. With the dissolution threshold angle and anisotropic dissolution rates considered, the resultant cavity cross section is crown top and cone bottom. The results also show that the cavity can be divided into dissolution and erosion sections according to its position relative to the injection point.

Quantifying the optimal thickness in polymer:fullerene solar cells from the analysis of charge transport dynamics and photoabsorption

We provide a semi-empirical equation that quantifies the optimal layer thickness in bulk heterojunction organic solar cells, which is based on time-of-flight and time-resolved microwave conductivity measurements and photoabsorption of a film.

Monte Carlo study of transport in low-dimensional quantum disorder systems at finite temperature

Using the quantum generalized Langevin equation and the path integral Monte Carlo approach, we study the transport dynamics of low-dimensional quantum disorder systems at finite temperature. Motivated by the nature of the classical-to-quantum transformation in fluctuations in the time domain, we extend the treatment to the spatial domain and propose a quantum random-correlated potential, describing specifically quantum disorder. For understanding the Anderson localization from the particle transport perspective, we present an intuitive treatment using a classical analogy in which the particle moves through a flat periodic crystal lattice corrugated by classical or quantum disorder. We emphasize an effective classical disorder potential in studying the quantum effects on the transport dynamics. Compared with the classical case, we find that the quantum escape rate from a disordered metastable potential is larger. Moreover, the diffusion enhancement of a quantum system moving in a weak, biased, periodic disorder potential is more significant compared with the classical case; for an effective rock-ratcheted disorder potential, quantum effects increase the directed current with decreasing temperature. For the classical case, we explore surface diffusion on a two-dimensional biased disorder potential at finite temperature; surprisingly, the optimal angle of the external bias force is found to enhance diffusion in the biased disorder surface. Furthermore, to explain the quantum transport dynamics in a disorder potential, we adopt the barrier-crossing mechanism and the mean first passage time theory to establish the probability distribution function.

A theoretical modeling framework for motile and colonial harmful algae

1. Harmful algal blooms are increasing in both severity and frequency across the globe. Many bloom-forming species are capable of vertical motility and colony formation. The cyanobacterium Microcystis aeruginosa is a common example of such a species, yet current models poorly predict vertical distributions of M. aeruginosa. 2. To couple the hydrodynamics, buoyancy, and the colony dynamics of Microcystis, we present a system of one-dimensional advection-diffusion-aggregation equations with Smoluchowski aggregation terms. 3. Results indicate Smoluchowski aggregation accurately describes the colony dynamics of M. aeruginosa. Further, transport dynamics are strongly dependent on colony size, and aggregation processes are highly sensitive to algal concentration and wind-induced mixing. Both of these findings have direct consequences to harmful algal bloom formation. 4. While the theoretical framework outlined in this manuscript was derived for M. aeruginosa, both motility and colony formation are common among bloom-forming algae. As such, this coupling of vertical transport and colony dynamics is a useful step for improving forecasts of surface harmful algal blooms.