Coarse-Graining

Today the most commonly used system architectures in data processing can be divided into three categories, general purpose processors, application specific architectures and reconfigurable architectures. Application specific architectures are efficient and give good performance, but are inflexible. Recently reconfigurable systems have drawn increasing attention due to their combination of flexibility and efficiency. Re-configurable architectures limit their flexibility to a particular algorithm. This paper introduces approaches to mapping point arithmetic. After presenting an optimal formulation using applications onto CGRAs supporting both integer and floating point unit.High-level design entry tools are essential for reconfigurable systems, especially coarse-grained reconfigurable architectures.Coarse-grained reconfigurable architectures have drawn increasing attention due to their performance and flexibility. However, their applications have been restricted to domains based on integer arithmetic since typical CGRAs support only integer arithmetic or logical operations. In this project we introduce an approach to map applications onto CGRAs supporting floating point addition. The increase in requirements for more flexibility and higher performance in embedded systems design, reconfigurable computing is becoming more and more popular. Keywords— High-level synthesis, CGRA, FPGA, Floating point unit , Reconfigurable architecture. I. INTRODUCTION Various coarse-grained reconfigurable architectures (CGRAs) have been proposed in recent years [1]–[3], with different target domains of applications and different tradeoffs between flexibility and performance. Typically, they consist is not easy to map an application onto the reconfigurable array host mostly reduced instruction set computing (RISC)] processor. The computation intensive kernels of the applications—typically loop—are mapped to the reconfigurable array while the remaining code is executed by the processor. However, it of a reconfigurable array of processing elements (PEs) and abecause of the high complexity of the problem that requires compiling the application on a dynamically reconfigurable parallel architecture, with additional complexity of dealing with complex routing resources. The problem of mapping an application onto a CGRA to minimize the number of resources giving best performance has been shown to be NP-complete [16].Few automatic mapping/compiling/synthesis tools have been developed to exploit the parallelism found in the applications and extensive computation resources of CGRAs. Some researchers [1], [4] have used structure-based or graphical user interface based design tools to manually generate a mapping, which would have a difficulty in handling big designs. Some researchers [5], [6] have only focused on instruction-level parallelism, failing to fully utilize the resources in CGRAs, which is possible by exploiting loop-level parallelism. Some researchers [7], [8], [17] have introduced a compiler to exploit the parallelism in the CGRA provided by the abundant resources. However, their approaches use shared registers to solve the mapping problem. While these shared registers explicitly during the mapping process. registers can be eliminated if routing resources are considered simplify the mapping process, theycan increase the critical path delay or latency. We show in this paper that the shared More recently, routing-aware mapping algorithms have been introduced [9]–[11]. However, they rely on step-by-step approaches, where scheduling, binding, and routing algorithms are performed sequentially. Thus, it tends to fall into a local integer type application domains, whereas ours extends the routing at the same time, thereby generating better optimized solutions. It also explicitly considers incorporating Steiner points for more efficient routing (some previous incorporate Steiner points although it is not clear whether they approaches use a kind of maze routing algorithm that can are actually incorporated). In [7], they have also presented a unified approach based on the simulated annealing algorithm. However, it takes too much time to get a solution. few minutes. Furthermore, all previous mapping/compiling/synthesis tools have been restricted to coverage to floating pointtype application domains.the approach in [7] takes hundreds of minutes whereas our optimum. Our unified approach considers scheduling and binding.

Theoretical studies of the molecular mechanisms responsible for the formation and stability of protein complexes have gained importance due to their practical applications in the understanding of the molecular basis of several diseases, in protein engineering and biotechnology. The objective of this project is to critically analyze and refine a coarse-grained force field for protein-protein interactions based on experimental thermodynamic properties and to apply it to cancer-related S100A4 protein system. Our ultimate goal is to generate knowledge for a better understanding of the physical mechanisms responsible for the association of particular proteins in different environments. We studied the role of short and long-range interactions on the complexation of homo-associations. Furthermore, we analyzed the influence of the pH and its correlation with the charge regulation mechanism. We analyzed and refined the adjustable Lennard-Jones parameter for a mesoscopic model based on experimental second virial data for lysozyme, chymotrypsinogen, and ribonuclease A via Monte Carlo simulations. From of that, the S100A3 protein was used to test the new calibrated parameters. Finally, we evaluated the dimerization process of S100A4 proteins, observing the role of physical-chemistry variables involved in the thermodynamical stability of different oligomers.

This paper proposes a new stochastic model of traffic dynamics in La-grangian coordinates. The source of uncertainty is heterogeneity in driving behavior , captured using driver-specific speed-spacing relations, i.e., parametric uncertainty. It also results in smooth vehicle trajectories in a stochastic context, which is in agreement with real-world traffic dynamics and, thereby, overcoming issues with aggressive oscillation typically observed in sample paths of stochastic traffic flow models. We utilize ensemble filtering techniques for data assimilation (traffic state estimation), but derive the mean and covariance dynamics as the ensemble sizes go to infinity, thereby bypassing the need to sample from the parameter distributions while estimating the traffic states. As a result, the estimation algorithm is just a standard Kalman-Bucy algorithm, which renders the proposed approach amenable to real-time applications using recursive data. Data assimilation examples are performed and our results indicate good agreement with out-of-sample data.

Scientists and philosophers frequently speak about levels of description, levels of explanation, and ontological levels. In this paper, I propose a unified framework for modelling levels. I give a general definition of a system of levels and show that it can accommodate descriptive, explanatory, and ontological notions of levels. I further illustrate the usefulness of this framework by applying it to some salient philosophical questions: (1) Is there a linear hierarchy of levels, with a fundamental level at the bottom? And what does the answer to this question imply for physicalism, the thesis that everything supervenes on the physical? (2) Are there emergent properties? (3) Are higher-level descriptions reducible to lower-level ones? (4) Can the relationship between normative and non-normative domains be viewed as one involving levels? Although I use the terminology of “levels”, the proposed framework can also represent “scales”, “domains”, or “subject matters”, where these are not linearly but only partially ordered by relations of supervenience or inclusion.

Ceramides are lipids that are involved in numerous biologically important structures (e.g. the stratum corneum and
ceramide-rich platforms) and processes (e.g. signal transduction and membrane fusion), but their behavior is not fully
understood. We report coarse-grain force field parameters for N-lignoceryl-sphingosine (ceramide NS, also known as
ceramide 2) that are consistent with the Martini force field. These parameters were optimized for simulations in the gel
phase and validated against atomistic simulations. Coarse-grained simulations with our parameters provide areas per
lipid, membrane thicknesses and electron density profiles that are in good agreement with atomistic simulations.
Properties of the simulated membranes are compared with available experimental data. The obtained parameters were
used to model the phase behavior of ceramide NS as a function of temperature and hydration. At low water content and
above the main phase transition temperature, the bilayer melts into an irregular phase, which may correspond to the
unstructured melted chain phase observed in X-ray diffraction experiments. The developed parameters also reproduce
the extended conformation of ceramide, which may occur in the stratum corneum. The parameters presented herein will
facilitate studies on important complex functional structures such as the uppermost layer of the skin and ceramide-rich
platforms in phospholipid membranes.

A 5 year old male child reported to the department of Pediatrics with large head ,facial puffiness,enlarged abdomen and corneal opacity. Examination revealed that the child had stunted growth and a short neck. Shape of the head was dolichocephalic with marked macrocephaly. Coarse facial features like depressed and broad nasal bridge, flaring of both nostrils, prominent supra orbital rim bilaterally, Facial asymmetry was more marked on the right side due to diffuse swelling at angle and body of mandible. Child had an enlarged abdomen, herniated umbilicus and massive hepatosplenomegaly. Both the hands were short and stubby. There was history of delayed milestones and appeared to be disabled intellectually.

The  first simulation study of the crystallisation of a binary mixture of triglycerides using molecular dynamics simulations is reported. Coarse-grained models of tristearin (SSS) and tripalmitin (PPP) molecules have been considered. The models have been preliminarily tested in the crystallisation of pure SSS and PPP systems. Two different quenching procedures have been tested and their performances have been analysed. The structures obtained from the crystallisation procedures show a high orientation order and a high content of molecules in the tuning fork conformation, comparable with the crystalline α phase. The behaviour of melting temperatures for the α phase of the mixture SSS/PPP obtained from the simulations is in qualitative agreement with the behaviour that was experimentally determined.

Exposure of polymethylmethacrylate (PMMA) during electron beam lithography (EBL) produces small polymer fragments that dissolve rapidly during the development process. The resist dissolution behavior varies greatly depending on the nature of the developer (solvent) and therefore influences the selection of the EBL parameters, such as dose (sensitivity). A molecular scale examination of the development process is necessary to elucidate the resist–developer interaction mechanisms. In this work, the authors investigate the interaction of short PMMA chains (containing up to 10 MMA units) with common developer components methyl isobutyl ketone (MIBK) and isopropyl alcohol (IPA). For this purpose, the authors conduct molecular dynamics simulations using the Accelrys Materials Studio package. The simulation results were used to characterize the mixtures in the spirit of the Flory–Huggins theory of polymers and also to extract the diffusivities. The authors found that the behavior of PMMA fragments differed considerably in MIBK as compared with IPA. PMMA fragments containing more than three monomers exhibit stronger attractive interaction with MIBK. For all fragment sizes simulated, the diffusivity of PMMA fragments is 60–160% higher in MIBK as well. Similarly, the authors observed differences in the gyration radii. The authors conclude that the kinetic factor seems to be more significant as compared to affinity factor when accounting for differences in exposure sensitivities due to developer selection.

Sedimentary successions exposed at basin margins as a result of late-stage inversion, uplift and erosion usually represent only a limited portion of the entire basin fill; thus, they are highly incomplete records of basin evolution. Small satellite basins, however, might have the potential of recording more complete histories. The late Miocene sedimentary history of the Șimleu Basin, a northeastern satellite of the vast Pannonian Basin, was investigated through the study of large outcrops and correlative well-logs. A full transgressive-regressive cycle is reconstructed, which formed within a ca. 1 million-year time frame (10.6-9.6 Ma). The transgressive phase is represented by coarse-grained deltas overlain by deep-water lacustrine marls. Onset of the regressive phase is indicated by sandy turbidite lobes and channels, followed by slope shales, and topped by stacked deltaic lobes and fluvial deposits. The deep-to shallow-water sedimentary facies are similar to those deposited in the central, deep part of the Pannonian Basin. The Șimleu Basin is thus a close and almost complete outcrop analogue of the Pannonian Basin's lacustrine sedimentary record known mainly from subsurface data, such as well-logs, cores and seismic sections from the basin interior. This study demonstrates that deposits of small satellite basins may reflect the whole sequence of processes that shaped the major basin, although at a smaller spatial and temporal scale.

Spider silk is a fascinating material combining mechanical properties such as maximum strength and high toughness comparable or better than man-made materials, with biocompatible degradability characteristics. Experimental measurements have shown that pH triggers the dimer formation of the N-terminal domain (NTD) of the major ampullate spidroin 1 (MaSp 1). A coarse-grained model accounting for electrostatics, van der Waals and pH-dependent charge-fluctuation interactions, by means of Monte Carlo simulations, gave us a more comprehensive view of the NTD dimerization process. A detailed analysis of the electrostatic properties and free energy derivatives for the NTD homoassociation was carried out at different pH values and salt concentrations for the protein wild type and for several mutants. We observed an enhancement of dipole–dipole interactions at pH 6 due to the ionization of key amino acids, a process identified as the main driving force for dimerization. Analytical estimates based on the DVLO theory framework corroborate our findings. Molecular dynamics simulations using the OPEP coarse-grained force field for proteins show that the mutant E17Q is subject to larger structural fluctuations when compared to the wild type. Estimates of the association rate constants for this mutant were evaluated by the Debye–Smoluchowski theory and are in agreement with the experimental data when thermally relaxed structures are used instead of the crystallographic data. Our results can contribute to the design of new mutants with specific association properties.

Coarse-grained (CG) models have proven to be very effective tools in the study of phenomena or systems involving large time- and length-scales. By decreasing the degrees of freedom in the system and using softer interactions than seen in atomistic models, larger time steps can be used and much longer simulation times can be studied. CG simulations are widely used to

Abstract: At the end of 2017, a new version of CG Martini will be released: Martini 3.0. Before it is released, it needs to be tested extensively.
During this bachelor-research, a Martini-model of Hexa-peri-hexabenzocoronene (HPHC) was built, validated, and the self-assembly process of HPHC was simulated. The hypothesis was that HPHC self-assembles into a tubular vesicle. Loose HPHC molecules successfully self-assembled into a nanowire, in which the pi-pi-stacking-distance is consistent with literature. Multiple nanowires successfully self-assembled into nanowire aggregates, e.g. a dimer and a tetramer. A membrane built out of HPHC molecules is stable, and membrane bending has been proven to be possible. Although the double-walled nanotube did not form yet, the results look promising.

Synchronization cluster analysis is an approach to the detection of underlying structures in data sets of multivariate time series, starting from a matrix R of bivariate synchronization indices. A previous method utilized the eigenvectors of R for cluster identification, analogous to several recent attempts at group identification using eigenvectors of the correlation matrix. All of these approaches assumed a one-to-one correspondence of dominant eigenvectors and clusters, which has however been shown to be wrong in important cases. We clarify the usefulness of eigenvalue decomposition for synchronization cluster analysis by translating the problem into the language of stochastic processes, and derive an enhanced clustering method harnessing recent insights from the coarse-graining of finite-state Markov processes. We illustrate the operation of our method using a simulated system of coupled Lorenz oscillators, and we demonstrate its superior performance over the previous approach. Finally we investigate the question of robustness of the algorithm against small sample size, which is important with regard to field applications.

Questions regarding population stability among animals and plants are fundamental to population ecology, yet this has not been a topic studied by archeologists focusing on prehistoric human populations. This is an important knowledge gap. The fluctuation of human populations over decades to centuries – population instability – may constrain the expansion of human economies. A first step toward describing basic patterns of population stability would be to identify sizes of fluctuations through time, since smaller fluctuations are more stable than larger fluctuations. We conduct a biogeographic analysis of the long-term stability of human societies in North America using a continental scale radiocarbon dataset. Our analysis compares the stability of summed calibrated radiocarbon date probability distributions (SPDs) with subsistence strategies and modeled climate stability between 6000 and 300 BP. This coarse-grained analysis reveals general trends regarding the stability of human sys...

The main mechanisms that control the organization of multicellular tissues are still largely open. A commonly used tool to study basic control mechanisms are in vitro experiments in which the growth conditions can be widely varied. However, even in vitro experiments are not free from unknown or uncontrolled influences. One reason why mathematical models become more and more a popular complementary tool to experiments is that they permit the study of hypotheses free from unknown or uncontrolled influences that occur in experiments. Many model types have been considered so far to model multicellular organization ranging from detailed individual-cell based models with explicit representations of the cell shape to cellular automata models with no representation of cell shape, and continuum models, which consider a local density averaged over many individual cells. However, how the different model description may be linked, and, how a description on a coarser level may be constructed bas...

Sedimentary successions exposed at basin margins as a result of late-stage inversion, uplift and erosion usually represent only a limited portion of the entire basin fill; thus, they are highly incomplete records of basin evolution. Small satellite basins, however, might have the potential of recording more complete histories. The late Miocene sedimentary history of the Șimleu Basin, a north-eastern satellite of the vast Pannonian Basin, was investigated through the study of large outcrops and correlative well-logs. A full transgressive–regressive cycle is reconstructed, which formed within a ca. 1 million-year time frame (10.6–9.6 Ma). The transgressive phase is represented by coarse-grained deltas overlain by deep-water lacustrine marls. Onset of the regressive phase is indicated by sandy turbidite lobes and channels, followed by slope shales, and topped by stacked deltaic lobes and fluvial deposits. The deep- to shallow-water sedimentary facies are similar to those deposited in t...

A powerful way to deal with a complex system is to build a coarse-grained model capable of catching its main physical features, while being computationally affordable. Inevitably, such coarse-grained models introduce a set of phenomenological parameters, which are often not easily deducible from the underlying atom-istic system. We present a unique approach to the calculation of these parameters, based on the recently introduced variationally enhanced sampling method. It allows us to obtain the parameters from atomistic simulations, providing thus a direct connection between the microscopic and the mesoscopic scale. The coarse-grained model we consider is that of Ginzburg–Landau, valid around a second-order critical point. In particular, we use it to describe a Lennard–Jones fluid in the region close to the liquid– vapor critical point. The procedure is general and can be adapted to other coarse-grained models. coarse graining | enhanced sampling | Ginzburg–Landau free energy | second-order phase transitions | Lennard–Jones C omputer simulations of condensed systems based on an atomistic description of matter are playing an ever-increasing role in many fields of science. However, as the complexity of the systems studied increases, so does the awareness that a less detailed, but nevertheless accurate, description of the system is necessary. This has been long since recognized, and branches of physics like elasticity or hydrodynamics can be classified in modern terms as coarse-grained (CG) models of matter. In more recent times, a field theoretical model suitable to describe second-order phase transitions has been introduced by Landau (1) and later perfected by Ginzburg (2). In recent decades a number of coarse-grained models that aim at describing polymers or biomolecules have also been proposed (3, 4). In all these approaches some degrees of freedom, deemed not essential to study the phenomenon at hand, are integrated out and the resulting reduced description contains a number of parameters that are not easily determined. Here we use the recently developed variationally enhanced sampling (VES) method (5) to suggest a procedure that allows the determination of such parameters, starting from the microscopic Hamiltonian. This illuminates a somewhat unexpected application of VES, which has been introduced as an enhanced sampling method. We show that it also provides a powerful framework for the optimization of CG models, due to the combination of its enhanced sampling capabilities and its variational flexibility. Moreover, VES takes advantage of its deep connection with relative entropy, a quantity that has been shown to play a key role in multiscale problems (6, 7). As a first test case for our procedure we consider the Ginzburg–Landau (GL) model for continuous phase transitions. An advantage of using this model is that its strengths and limits are well known and that other researchers have already attempted to perform such a calculation (8–14). A system that undergoes a second-order phase transition is described in the GL model by the following free energy, valid in a rotationally invariant one-component real-order parameter scenario, F [ψ] = g ||ψ(r)| 2 d 3 r + a ψ 2 (r) d 3 r + b ψ 4 (r) d 3 r , [1] where the field ψ(r) describes the order parameter fluctuations, and g, a, and b are phenomenological quantities that we call Landau's parameters. To be defined, we apply our method close to the liquid–vapor critical point of a Lennard–Jones fluid. Variationally Enhanced Sampling Before discussing our method, we briefly recall some of the ideas at the basis of VES. The VES method shares with metadynamics (15, 16) the idea of enhancing the sampling by adding an external bias potential, which is a function of a few coarse-grained order parameters, so-called collective variables (CVs). Contrary to metadynamics and other similar methods, VES does not generate the bias potential by periodically adding on the fly small contributions, but as the result of the minimization of a convex functional. Various extensions have been proposed, where VES has been used in different ways (17–22). Let us suppose that the physical behavior of interest is well described by a set of CVs s = s(R), which are function of the coordinates R of the N particles that compose the system. Then we can write the associated free-energy function as F (s) = −(1/β) log d R δ[s − s(R)] e −βU (R) , where β = 1/(kBT) is the inverse temperature and U (R) is the inter-particle potential energy. Significance A multiscale description is believed to be the only feasible route toward the simulation of complex systems. Yet moving from one scale to another is not a trivial task, and many different approaches can be taken. We propose here a systematic approach to go from a fine scale to a coarser one, based on the recently introduced variationally enhanced sampling method. Contrary to other coarse-graining methods, it combines in the same algorithm the sampling enhancement and the optimization of the coarse-graining parameters. We illustrate the method in the case of the vapor–liquid critical transition of a Lennard–Jones fluid. This is done in the context of the Ginzburg–Landau field theoretical description of second-order phase transitions.

Sedimentary successions exposed at basin margins as a result of late-stage inversion, uplift and erosion usually represent only a limited portion of the entire basin fill; thus, they are highly incomplete records of basin evolution. Small satellite basins, however, might have the potential of recording more complete histories. The late Miocene sedimentary history of the Șimleu Basin, a north-eastern satellite of the vast Pannonian Basin, was investigated through the study of large outcrops and correlative well-logs. A full transgressive–regressive cycle is reconstructed, which formed within a ca. 1 million-year time frame (10.6–9.6 Ma). The transgressive phase is represented by coarse-grained deltas overlain by deep-water lacustrine marls. Onset of the regressive phase is indicated by sandy turbidite lobes and channels, followed by slope shales, and topped by stacked deltaic lobes and fluvial deposits. The deep- to shallow-water sedimentary facies are similar to those deposited in t...

The traditional computational modeling of protein structure, dynamics, and interactions remains difficult for many protein systems. It is mostly due to the size of protein conformational spaces and required simulation time scales that are still too large to be studied in atomistic detail. Lowering the level of protein representation from all-atom to coarse-grained opens up new possibilities for studying protein systems. In this review we provide an overview of coarse-grained models focusing on their design, including choices of representation, models of energy functions, sampling of conformational space, and applications in the modeling of protein structure, dynamics, and interactions. A more detailed description is given for applications of coarse-grained models suitable for efficient combinations with all-atom simulations in multiscale modeling strategies.

Molecular modeling of phospholipids on many scales has progressed significantly over the last years. Here we review several membrane models on intermediate to large length scales restricting ourselves to particle based coarse-grained models with implicit and explicit solvent. We explain similarities and differences as well as their connection to experiments and fine-grained models. We neglect any field descriptions on larger scales. We discuss then a few examples where we focus on studies of lipid phase behavior as well as supported lipid bilayers as these examples can only be meaningfully studied using large-scale models to date.

The Random Walk Spring (RWS) [P.T. Underhill, P.S. Doyle, On the coarse-graining of polymers into bead-spring chains, J. Non-Newtonian Fluid Mech. 122 (2004) 3–31; P.T. Underhill, P.S. Doyle, Development of bead-spring models using the constant extension ensemble, J. Rheol. 49 (5) (2005) 963–987] model is used to examine the influence of successive fine graining on the macroscopic stress predictions of

Aggregation phenomena in colloidal systems with and without shear flow studied with mesoscale Langevin Dynamics method is a primary focus of the current study. Applicability of mesoscale methods to the non-equilibrium time evolving systems (considered in the current study) is limited due to need for the potential of mean force. Available coarse-graining (CG) approaches are suitable for equilibrium system only. To resolve this issue a coarse-graining approach is developed to infer mesoscale interaction potentials in aggregating systems, resulting in an improved potential of mean force for Langevin dynamics (LD) and Brownian dynamics (BD) simulations. Starting from the evolution equation for the solute pair correlation function, this semi--analytical CG approach identifies accurate modeling of the relative acceleration between solute particles in a solvent bath as a reliable route to predicting the time--evolving structural properties of non--equilibrium aggregating systems. Noting th...

ABSTRACT When systems of reacting solid or liquid particles are explicitly modeled on a computational mesh, a wide distribution of initial particle sizes can lead to undesirably large numbers of mesh points. A coarse graining method is presented that avoids this problem by essentially grouping the finest particles together into a number of larger clusters. The excess surface area of these clusters is incorporated into a bias factor that can be multiplied by the intrinsic reaction rate constant to approximate the enhanced reaction rate of the clusters relative to actual particles of the same size. The bias factor can be calculated directly from knowledge of mesh point spacing and of the particle size distribution. Examples are given of the value that the bias factor can have for a model distribution of particle sizes, using computational meshes with varying resolution limits.