Academic literature on the topic 'Multicale molecular simulations'
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Journal articles on the topic "Multicale molecular simulations"
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Javan Nikkhah, Sousa, Elsi Turunen, Anneli Lepo, Tapio Ala-Nissila, and Maria Sammalkorpi. "Multicore Assemblies from Three-Component Linear Homo-Copolymer Systems: A Coarse-Grained Modeling Study." Polymers 13, no. 13 (June 30, 2021): 2193. http://dx.doi.org/10.3390/polym13132193.
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Multicore polymer micelles and aggregates are assemblies that contain several cores. The dual-length-scale compartmentalized solvophobic–solvophilic molecular environment makes them useful for, e.g., advanced drug delivery, high-precision synthesis platforms, confined catalysis, and sensor device applications. However, designing and regulating polymer systems that self-assemble to such morphologies remains a challenge. Using dissipative particle dynamics (DPD) simulations, we demonstrate how simple, three-component linear polymer systems consisting of free solvophilic and solvophobic homopolymers, and di-block copolymers, can self-assemble in solution to form well-defined multicore assemblies. We examine the polymer property range over which multicore assemblies can be expected and how the assemblies can be tuned both in terms of their morphology and structure. For a fixed degree of polymerization, a certain level of hydrophobicity is required for the solvophobic component to lead to formation of multicore assemblies. Additionally, the transition from single-core to multicore requires a relatively high solvophobicity difference between the solvophilic and solvophobic polymer components. Furthermore, if the solvophilic polymer is replaced by a solvophobic species, well-defined multicore–multicompartment aggregates can be obtained. The findings provide guidelines for multicore assemblies’ formation from simple three-component systems and how to control polymer particle morphology and structure.
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Ng, Kam, Vladimir Nazarov, Sergey Kuchinsky, Aramais Zakharian, and Ming-Jun Li. "Analysis of Crosstalk in Multicore Fibers: Statistical Distributions and Analytical Expressions." Photonics 10, no. 2 (February 7, 2023): 174. http://dx.doi.org/10.3390/photonics10020174.
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We present a study of multicore fiber (MCF) crosstalk using the coupled mode theory. We derived a general closed-form simulation formula for the crosstalk of MCF under random perturbations, which includes both the average crosstalk and the crosstalk statistical distribution. From this general formula, we further derived simple analytical expressions for the average crosstalk under the assumption of exponential distribution of fiber segment lengths. We show that the analytical expressions approximate very well the results for other distributions, such as Dirac and Gaussian, and thus they can be used as a general analytical approach for estimating the average crosstalk. Results from numerical simulations of average crosstalk are shown to be in full correspondence with analytic results. We also performed numerical simulations of crosstalk statistical distributions generated from our general closed-form simulation formula and find that these agree well with the χ2-distribution function with four degrees of freedom. Finally, we conducted crosstalk measurements under different bending deployment conditions, and the measured crosstalk distributions and average crosstalk are found to be in agreement with the modeling results.
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Peng, Liu, Manaschai Kunaseth, Hikmet Dursun, Ken-ichi Nomura, Weiqiang Wang, Rajiv K. Kalia, Aiichiro Nakano, and Priya Vashishta. "Exploiting hierarchical parallelisms for molecular dynamics simulation on multicore clusters." Journal of Supercomputing 57, no. 1 (February 3, 2011): 20–33. http://dx.doi.org/10.1007/s11227-011-0560-1.
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Qiu, Yang. "Partial-Failure Segregated Spectrum Assignment for Multicast Traffic in Flex-Grid Optical Networks." Photonics 9, no. 7 (July 12, 2022): 488. http://dx.doi.org/10.3390/photonics9070488.
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In this paper, we propose a new algorithm called the partial-failure segregated multicasting routing and spectrum assignment (PFS MRSA) algorithm to improve the service blocking performance of the multicast transmission in flex-grid optical networks (FGONs). By segregating one failure destination leaf-node from a blocked multicast request and accommodating the failure destination leaf-node and the remaining multicast request independently, the success probability of accommodating the originally blocked multicast request can be greatly increased. In this way, the proposed PFS MRSA algorithm can effectively reduce the service blocking probability for the multicast services in FGONs. Simulation results show that the proposed PFS MRSA algorithm achieves significant reduction in service blocking probability when compared with the conventional MRSA algorithms, and such reduction can even reach 100% in some scenarios with low traffic load.
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Li, Jiamin, Lingling Chen, Pengcheng Zhu, Dongming Wang, and Xiaohu You. "Satellite-Assisted Cell-Free Massive MIMO Systems with Multi-Group Multicast." Sensors 21, no. 18 (September 16, 2021): 6222. http://dx.doi.org/10.3390/s21186222.
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In this paper, we use satellite-assisted and multi-group multicast mechanisms to relieve ground traffic pressure and improve data transmission efficiency of cell-free massive MIMO systems. We propose to estimate channel state information (CSI) by common pilot scheme. Given the estimated CSI, we derive the closed-form expressions of achievable rate with maximum ratio transmission (MRT) and zero-forcing (ZF) precoding. The correctness of the closed-form expressions is verified through simulations. The results show that with the help of satellite and multicast, the average system spectrum efficiency (SE) can be significantly improved.
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Al-hussaniy, Hany Akeel. "The development of molecular docking and molecular dynamics and their application in the field of chemistry and computer simulation." Journal of medical pharmaceutical and allied sciences 12, no. 1 (January 31, 2023): 5552–62. http://dx.doi.org/10.55522/jmpas.v12i1.4137.
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With the rapid development of modern life science, computational Molecular docking has gradually become one of the core disciplines and methods of modern life science research. Computational docking studies the relationship between the structure and pharmacodynamics of biological macromolecules and the interaction between biological macromolecules and ligands. It promotes the development of protein engineering, protein design, and computer-aided drug design with powerful and various docking software in predicting the three-dimensional structure and dynamic characteristics of proteins from protein sequences. Nowadays, this computing power can be provided by the GPU through the use of a general-purpose computing model on GPUs. This article presents two approaches to parallelizing the descriptive algorithms on the GPU to solve the molecular docking problem and then evaluating them in terms of the computation time achieved. The proposed approaches are effective in accelerating molecular docking on GPUs compared to a single-core or multicore CPU. Besides introducing parallelization approaches, we propose a new descriptive algorithm based on the bee swarm algorithm to solve the molecular docking problem as an alternative to traditional descriptive algorithms such as the genetic algorithm.
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Guo, Xiaojin, Liying Sang, and Huanlin Liu. "Minimization Number of Network-Coded Links Based on Improved Adaptive Genetic Algorithm for Multi-source Optical Networks." Journal of Optical Communications 40, no. 3 (July 26, 2019): 205–12. http://dx.doi.org/10.1515/joc-2017-0030.
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Abstract With the rapid development of multi-source optical multicast application, the wavelength division multiplexing (WDM) with limited number of wavelength channels is facing with the new challenge of bandwidth shortage. Optical multicast adopting network coding can improve the bandwidth utilization, but optical network coding needs to increase optical storage and computation overhead in WDM optical network. For reducing the number of optical network-coded links, an improved adaptive genetic algorithm (IAGA) is proposed to minimize the number of network-coded links for multicast. By designing the maximization difference crossover operation, IAGA can guarantee the diversity of population and avoid individuals from falling into a local optimal. By adaptively adjusting the crossover probability, IAGA makes the population diverse at the beginning stages and makes the excellent individuals remain in a stable condition. Compared with other algorithms, the simulation result shows that the proposed algorithm has fastest convergence speed, which means that it takes the shortest time to find the minimum numbers of coded link solutions.
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Martin, Richard L., Prabhat, David D. Donofrio, James A. Sethian, and Maciej Haranczyk. "Accelerating analysis of void space in porous materials on multicore and GPU platforms." International Journal of High Performance Computing Applications 26, no. 4 (February 5, 2012): 347–57. http://dx.doi.org/10.1177/1094342011431591.
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Developing computational tools that enable discovery of new materials for energy-related applications is a challenge. Crystalline porous materials are a promising class of materials that can be used for oil refinement, hydrogen or methane storage as well as carbon dioxide capture. Selecting optimal materials for these important applications requires analysis and screening of millions of potential candidates. Recently, we proposed an automatic approach based on the Fast Marching Method (FMM) for performing analysis of void space inside materials, a critical step preceding expensive molecular dynamics simulations. This breakthrough enables unsupervised, high-throughput characterization of large material databases. The algorithm has three steps: (1) calculation of the cost-grid which represents the structure and encodes the occupiable positions within the void space; (2) using FMM to segment out patches of the void space in the grid of (1), and find how they are connected to form either periodic channels or inaccessible pockets; and (3) generating blocking spheres that encapsulate the discovered inaccessible pockets and are used in proceeding molecular simulations. In this work, we expand upon our original approach through (A) replacement of the FMM-based approach with a more computationally efficient flood fill algorithm; and (B) parallelization of all steps in the algorithm, including a GPU implementation of the most computationally expensive step, the cost-grid generation. We report the acceleration achievable in each step and in the complete application, and discuss the implications for high-throughput material screening.
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Galbraith, Madeline, Federico Bocci, and José N. Onuchic. "Stochastic fluctuations promote ordered pattern formation of cells in the Notch-Delta signaling pathway." PLOS Computational Biology 18, no. 7 (July 21, 2022): e1010306. http://dx.doi.org/10.1371/journal.pcbi.1010306.
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The Notch-Delta signaling pathway mediates cell differentiation implicated in many regulatory processes including spatiotemporal patterning in tissues by promoting alternate cell fates between neighboring cells. At the multicellular level, this "lateral inhibition” principle leads to checkerboard patterns with alternation of Sender and Receiver cells. While it is well known that stochasticity modulates cell fate specification, little is known about how stochastic fluctuations at the cellular level propagate during multicell pattern formation. Here, we model stochastic fluctuations in the Notch-Delta pathway in the presence of two different noise types–shot and white–for a multicell system. Our results show that intermediate fluctuations reduce disorder and guide the multicell lattice toward checkerboard-like patterns. By further analyzing cell fate transition events, we demonstrate that intermediate noise amplitudes provide enough perturbation to facilitate “proofreading” of disordered patterns and cause cells to switch to the correct ordered state (Sender surrounded by Receivers, and vice versa). Conversely, high noise can override environmental signals coming from neighboring cells and lead to switching between ordered and disordered patterns. Therefore, in analogy with spin glass systems, intermediate noise levels allow the multicell Notch system to escape frustrated patterns and relax towards the lower energy checkerboard pattern while at large noise levels the system is unable to find this ordered base of attraction.
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Aldinucci, Marco, Cristina Calcagno, Mario Coppo, Ferruccio Damiani, Maurizio Drocco, Eva Sciacca, Salvatore Spinella, Massimo Torquati, and Angelo Troina. "On Designing Multicore-Aware Simulators for Systems Biology Endowed with OnLine Statistics." BioMed Research International 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/207041.
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The paper arguments are on enabling methodologies for the design of a fully parallel, online, interactive tool aiming to support the bioinformatics scientists .In particular, the features of these methodologies, supported by the FastFlow parallel programming framework, are shown on a simulation tool to perform the modeling, the tuning, and the sensitivity analysis of stochastic biological models. A stochastic simulation needs thousands of independent simulation trajectories turning into big data that should be analysed by statistic and data mining tools. In the considered approach the two stages are pipelined in such a way that the simulation stage streams out the partial results of all simulation trajectories to the analysis stage that immediately produces a partial result. The simulation-analysis workflow is validated for performance and effectiveness of the online analysis in capturing biological systems behavior on a multicore platform and representative proof-of-concept biological systems. The exploited methodologies include pattern-based parallel programming and data streaming that provide key features to the software designers such as performance portability and efficient in-memory (big) data management and movement. Two paradigmatic classes of biological systems exhibiting multistable and oscillatory behavior are used as a testbed.
Dissertations / Theses on the topic "Multicale molecular simulations"
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Bidoggia, Silvia. "Mixed-monolayer protected gold nanoparticles for applications in medicine." Doctoral thesis, Università degli studi di Trieste, 2013. http://hdl.handle.net/10077/8573.
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2011/2012In the last years, gold nanoparticles (AuNPs) protected by an organic shell of ligands have received a large interest for applications in the biomedical field in particular for diagnosis, imaging and therapy. This class of nanomaterials is largely used because of the easy of synthesis with different core sizes and shapes and controlled dispersion. Moreover, NPs can be protected by a large variety of organic compounds, with different functionalities and to allow the linkage of drugs and biomolecules. The nature of the ligand is responsible of the solubility of the NPs and could be also tuned in order to have NPs soluble in water and in the biological environment. Additionally, at least gold is no toxic, biocompatible and could be easily released from the body. The present thesis is focused on three projects. The first one deals with the study of the morphology of gold nanoparticles coated by a mixture of hydrogenated and fluorinated ligands which solubility in water is favored by the presence of PEG chains. Few years ago, our research group has shown that mixtures of these hydrogenated and fluorinated ligands, forming the monolayer of gold nanoparticles, phase-segregate in separated domains because of the reciprocal immiscibility of the two chains. During this thesis, we wanted to investigate more deeply the organization of such monolayers and in particular, to understand the shape and the size of these domains. In collaboration with the group of Prof. S. Pricl and Prof. M. Fermeglia of the University of Trieste, in silico experiments have been performed in order to predict the size and the shape of these domains. Moreover, we have studied how the shape and the size of these domains is influenced by the ratio between the two thiols, the size of the core and the difference in length between the two ligands. The obtained results were supported by further ESR experiments performed by Prof. Lucarini of the University of Bologna. ESR experiments have allowed us to estimate the value of the affinity constants of the probe for the fluorinated and hydrogenated domains of the monolayer and to establish that mixed monolayers have chemical and physical properties that cannot be predicted by simply knowing the properties of homoligand monolayers. The results that have been reported in a recent publication on ACS Nano are presented in Chapter 3. The second project of this PhD thesis is based on the synthesis and characterization of water soluble gold nanoparticles coated by different ratios of charged hydrogenated ligands and commercially available fluorinated ligands. Some of these nanoparticles, with an average core diameter between 3 and 4 nm, have been used for preliminary investigations in vitro. In particular, cell membrane permeation and the cellular toxicity have been evaluated. These experiments have been performed in collaboration with the group of Prof. Stellacci in IFOM-IEO, Milan. Preliminary results are described in Chapter 4. The last part of this PhD project is focused on the synthesis and characterization of NPs coated by mixtures of commercially available fluorinated and hydrogenated thiols. These NPs present the advantages over those described in Chapter 3 and Chapter 4 because they are suited for a direct “visualization” by STM experiments and may help us in understanding the rules governing the organization of mixtures of fluorinated and hydrogenated ligands on a curved surface. The choice to synthesize NPs without charged groups is dictated by the limitations of STM technique. In Chapter 5 synthetic aspects and preliminary STM results would be presented.
XXV Ciclo
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Khan, MD Ashfaquzzaman. "Scalable molecular dynamics simulation using FPGAs and multicore processors." Thesis, Boston University, 2013. https://hdl.handle.net/2144/12792.
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Thesis (Ph.D.)--Boston University
PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you.While Molecular Dynamics Simulation (MD) uses a large fraction of the world's High Performance Compute cycles, the modeling of many physical phenomena remains far out of reach. Improving the cost-effectiveness of MD has therefore received much attention, especially in using accelerators or modifying the computation itself. While both approaches have demonstrated great potential, scalability has emerged as a critical common challenge. The goal of this research is to study this issue and develop MD solutions that not only achieve substantial acceleration but also remain scalable. In the first part of this research, we focus on Discrete Molecular Dynamics Simulation (DMD)., which achieves high performance by simplifying the underlying computation by converting it into a Discrete Event Simulation (DES). In addition to the inherent serial nature of DES, causality issues make DMD a notorious target for parallelization. We propose a parallel version of DMD that, unlike any previous work, uses task decomposition and efficient synchronization and achieves more than 8.5x speed-up for 3D physical systems on a 12 core processor, with potential for further strong scaling. The second part of this research focuses on FPGA acceleration of timestep-driven MD. We first enhance an existing FPGA kernel to take advantage of the Block RAM architecture of FPGAs. This results in a 50% improvement in speed-up, without sacrificing simulation quality. We then parallelize the design targeting multiple on-board FPGA cores. We combine this with software pipelining and careful load distribution at the application level to achieve a 3.37x speedup over its CPU counterpart. In the third part we create a framework that integrates the FPGA accelerator into a prominent MD package called NAMD. This framework allows users to switch between the actual accelerator and a simulated version, and provides a means to study different characteristics, such as the communication pattern, of such an accelerated system. Using this framework, we identify the drawbacks of the current FPGA kernel and provide guidelines for future designs. In addition, the integrated design achieves 2.22x speed-up over a quad-core CPU, making it the first ever FPCA-accelerated full-parallel MD package to achieve a positive end-to-end speed-up.
Book chapters on the topic "Multicale molecular simulations"
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Swat, Maciej H., Susan D. Hester, Ariel I. Balter, Randy W. Heiland, Benjamin L. Zaitlen, and James A. Glazier. "Multicell Simulations of Development and Disease Using the CompuCell3D Simulation Environment." In Methods in Molecular Biology, 361–428. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-59745-525-1_13.
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Chau, Nguyen Hai. "Parallelization of the Fast Multipole Method for Molecular Dynamics Simulations on Multicore Computers." In Advanced Computational Methods for Knowledge Engineering, 209–24. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00293-4_16.
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