Hybrid stochastic simulations of intracellular reaction-diffusion systems.

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.

Why Monte Carlo Simulations are Inferences and not Experiments

Monte Carlo simulations arrive at their results by introducing randomness, sometimes derived from a physical randomizing device. Nonetheless, we argue, they open no new epistemic channels beyond that already employed by traditional simulations: the inference by ordinary argumentation of conclusions from assumptions built into the simulations. We show that Monte Carlo simulations cannot produce knowledge other than by inference, and that they resemble other computer simulations in the manner in which they derive their conclusions. Simple examples of Monte Carlo simulations are analysed to identify the underlying inferences.

More than just Good Luck. How to Explain the Success of Monte Carlo Simulations

Monte Carlo simulation is a powerful method in many natural and social sciences. But what sort of method is it? And where does its power come from? Are Monte Carlo simulations experiments, theories or something else? The aim of this talk is to answer these questions and to explain the power of Monte Carlo simulations. I provide a classification of Monte Carlo techniques and defend the claim that Monte Carlo simulation is a sort of inference.

Polar MM5 Simulations of the Winter Climate of the Laurentide Ice Sheet at the LGM

Optimized regional climate simulations are conducted using the Polar MM5, a version of the fifth-generation Pennsylvania State University-NCAR Mesoscale Model (MM5), with a 60-km horizontal resolution domain over North America during the Last Glacial Maximum (LGM, 21 000 calendar years ago), when much of the continent was covered by the Laurentide Ice Sheet (LIS). The objective is to describe the LGM annual cycle at high spatial resolution with an emphasis on the winter atmospheric circulation. Output from a tailored NCAR Community Climate Model version 3 (CCM3) simulation of the LGM climate is used to provide the initial and lateral boundary conditions for Polar MM5. LGM boundary conditions include continental ice sheets, appropriate orbital forcing, reduced CO2 concentration, paleovegetation, modified sea surface temperatures, and lowered sea level. Polar MM5 produces a substantially different atmospheric response to the LGM boundary conditions than CCM3 and other recent GCM simulations. In particular, from November to April the upper-level flow is split around a blocking anticyclone over the LIS, with a northern branch over the Canadian Arctic and a southern branch impacting southern North America. The split flow pattern is most pronounced in January and transitions into a single, consolidated jet stream that migrates northward over the LIS during summer. Sensitivity experiments indicate that the winter split flow in Polar MM5 is primarily due to mechanical forcing by LIS, although model physics and resolution also contribute to the simulated flow configuration. Polar MM5 LGM results are generally consistent with proxy climate estimates in the western United States, Alaska, and the Canadian Arctic and may help resolve some long-standing discrepancies between proxy data and previous simulations of the LGM climate.

A Model Study of the Circulation in the Pearl River Estuary (PRE) and Its Adjacent Coastal Waters: 1. Simulations and Comparison with Observations

The Princeton Ocean Model is used to study the circulation features in the Pearl River Estuary and their responses to tide, river discharge, wind, and heat flux in the winter dry and summer wet seasons. The model has an orthogonal curvilinear grid in the horizontal plane with variable spacing from 0.5 km in the estuary to 1 km on the shelf and 15 sigma levels in the vertical direction. The initial conditions and the subtidal open boundary forcing are obtained from an associated larger-scale model of the northern South China Sea. Buoyancy forcing uses the climatological monthly heat fluxes and river discharges, and both the climatological monthly wind and the realistic wind are used in the sensitivity experiments. The tidal forcing is represented by sinusoidal functions with the observed amplitudes and phases. In this paper, the simulated tide is first examined. The simulated seasonal distributions of the salinity, as well as the temporal variations of the salinity and velocity over a tidal cycle are described and then compared with the in situ survey data from July 1999 and January 2000. The model successfully reproduces the main hydrodynamic processes, such as the stratification, mixing, frontal dynamics, summer upwelling, two-layer gravitational circulation, etc., and the distributions of hydrodynamic parameters in the Pearl River Estuary and coastal waters for both the winter and the summer season.

Antenna Simulations and Measurements of Focal Plane Array Facet Reflectors

We present a conceptual prototype model of a focal plane array unit for the STEAMR instrument, highlighting the challenges presented by the required high relative beam proximity of the instrument and focus on how edge-diffraction effects contribute to the array's performance. The analysis was carried out as a comparative process using both PO & PTD and MoM techniques. We first highlight general differences between these computational techniques, with the discussion focusing on diffractive edge effects for near-field imaging reflectors with high truncation. We then present the results of in-depth modeling analyses of the STEAMR focal plane array followed by near-field antenna measurements of a breadboard model of the array. The results of these near-field measurements agree well with both simulation techniques although MoM shows slightly higher complex beam coupling to the measurements than PO & PTD.

Unraveling the Conformational Determinants of Peptide Dendrimers Using Molecular Dynamics Simulations

Peptide dendrimers are synthetic tree-like molecules composed of amino acids. There are at least two kinds of preferential structural behaviors exhibited by these molecules, which acquire either compact or noncompact shapes. However, the key structural determinants of such behaviors remained, until now, unstudied. Herein, we conduct a comprehensive investigation of the structural determinants of peptide dendrimers by employing long molecular dynamics simulations to characterize an extended set of third generation dendrimers. Our results clearly show that a trade-off between electrostatic effects and hydrogen bond formation controls structure acquisition in these systems. Moreover, by selectively changing the dendrimers charge we are able to manipulate the exhibited compactness. In contrast, the length of branching residues does not seem to be a major structural determinant. Our results are in accordance with the most recent experimental evidence and shed some light on the key molecular level interactions controlling structure acquisition in these systems. Thus, the results presented constitute valuable insights that can contribute to the development of truly tailor-made dendritic systems.

Regional climate model simulations for Europe at 6 and 0.2 k BP: sensitivity to changes in anthropogenic deforestation

This study aims to evaluate the direct effects of anthropogenic deforestation on simulated climate at two contrasting periods in the Holocene, ~6 and ~0.2 k BP in Europe. We apply We apply the Rossby Centre regional climate model RCA3, a regional climate model with 50 km spatial resolution, for both time periods, considering three alternative descriptions of the past vegetation: (i) potential natural vegetation (V) simulated by the dynamic vegetation model LPJ-GUESS, (ii) potential vegetation with anthropogenic land use (deforestation) from the HYDE3.1 (History Database of the Global Environment) scenario (V + H3.1), and (iii) potential vegetation with anthropogenic land use from the KK10 scenario (V + KK10). The climate model results show that the simulated effects of deforestation depend on both local/regional climate and vegetation characteristics. At ~6 k BP the extent of simulated deforestation in Europe is generally small, but there are areas where deforestation is large enough to produce significant differences in summer temperatures of 0.5–1 °C. At ~0.2 k BP, extensive deforestation, particularly according to the KK10 model, leads to significant temperature differences in large parts of Europe in both winter and summer. In winter, deforestation leads to lower temperatures because of the differences in albedo between forested and unforested areas, particularly in the snow-covered regions. In summer, deforestation leads to higher temperatures in central and eastern Europe because evapotranspiration from unforested areas is lower than from forests. Summer evaporation is already limited in the southernmost parts of Europe under potential vegetation conditions and, therefore, cannot become much lower. Accordingly, the albedo effect dominates in southern Europe also in summer, which implies that deforestation causes a decrease in temperatures. Differences in summer temperature due to deforestation range from −1 °C in south-western Europe to +1 °C in eastern Europe. The choice of anthropogenic land-cover scenario has a significant influence on the simulated climate, but uncertainties in palaeoclimate proxy data for the two time periods do not allow for a definitive discrimination among climate model results.

The Nature of Scientific Proof in the Age of Simulations. Is numerical mimicry a third way of establishing truth?

Is numerical mimicry a third way of establishing truth? Kevin Heng received his M.S. and Ph.D. in astrophysics from the Joint Institute for Laboratory Astrophysics (JILA) and the University of Colorado at Boulder. He joined the Institute for Advanced Study in Princeton from 2007 to 2010, first as a Member and later as the Frank & Peggy Taplin Member. From 2010 to 2012 he was a Zwicky Prize Fellow at ETH Z¨urich (the Swiss Federal Institute of Technology). In 2013, he joined the Center for Space and Habitability (CSH) at the University of Bern, Switzerland, as a tenure-track assistant professor, where he leads the Exoplanets and Exoclimes Group. He has worked on, and maintains, a broad range of interests in astrophysics: shocks, extrasolar asteroid belts, planet formation, fluid dynamics, brown dwarfs and exoplanets. He coordinates the Exoclimes Simulation Platform (ESP), an open-source set of theoretical tools designed for studying the basic physics and chemistry of exoplanetary atmospheres and climates (www.exoclime.org). He is involved in the CHEOPS (Characterizing Exoplanet Satellite) space telescope, a mission approved by the European Space Agency (ESA) and led by Switzerland. He spends a fair amount of time humbly learning the lessons gleaned from studying the Earth and Solar System planets, as related to him by atmospheric, climate and planetary scientists. He received a Sigma Xi Grant-in-Aid of Research in 2006

Mechanisms of Ligand–Protein Interaction in Sec-14-like Transporters Investigated by Computer Simulations

We review our recent work on protein-ligand interactions in vitamin transporters of the Sec-14-like protein. Our studies focused on the cellular-retinaldehyde binding protein (CRALBP) and the alpha-tocopherol transfer protein (alpha-TTP). CRALBP is responsible for mobilisation and photo-protection of short-chain cis-retinoids in the dim-light visual cycle or rod photoreceptors. alpha-TTP is a key protein responsible for selection and retention of RRR-alpha-tocopherol, the most active isoform of vitamin E in superior animals. Our simulation studies evidence how subtle chemical variations in the substrate can lead to significant distortion in the structure of the complex, and how these changes can either lead to new protein function, or be used to model engineered protein variants with tailored properties. Finally, we show how integration of computational and experimental results can contribute in synergy to the understanding of fundamental processes at the biomolecular scale.

Up, down, strange and charm quark masses with Nf = 2+1+1 twisted mass lattice QCD

We present a lattice QCD calculation of the up, down, strange and charm quark masses performed using the gauge configurations produced by the European Twisted Mass Collaboration with Nf=2+1+1 dynamical quarks, which include in the sea, besides two light mass degenerate quarks, also the strange and charm quarks with masses close to their physical values. The simulations are based on a unitary setup for the two light quarks and on a mixed action approach for the strange and charm quarks. The analysis uses data at three values of the lattice spacing and pion masses in the range 210–450 MeV, allowing for accurate continuum limit and controlled chiral extrapolation. The quark mass renormalization is carried out non-perturbatively using the RI′-MOM method. The results for the quark masses converted to the scheme are: mud(2 GeV)=3.70(17) MeV, ms(2 GeV)=99.6(4.3) MeV and mc(mc)=1.348(46) GeV. We obtain also the quark mass ratios ms/mud=26.66(32) and mc/ms=11.62(16). By studying the mass splitting between the neutral and charged kaons and using available lattice results for the electromagnetic contributions, we evaluate mu/md=0.470(56), leading to mu=2.36(24) MeV and md=5.03(26) MeV.