343 research outputs found
Mesoscopic simulation of diffusive contaminant spreading in gas flows at low pressure
Many modern production and measurement facilities incorporate multiphase
systems at low pressures. In this region of flows at small, non-zero Knudsen-
and low Mach numbers the classical mesoscopic Monte Carlo methods become
increasingly numerically costly. To increase the numerical efficiency of
simulations hybrid models are promising. In this contribution, we propose a
novel efficient simulation approach for the simulation of two phase flows with
a large concentration imbalance in a low pressure environment in the low
intermediate Knudsen regime. Our hybrid model comprises a lattice-Boltzmann
method corrected for the lower intermediate Kn regime proposed by Zhang et al.
for the simulation of an ambient flow field. A coupled event-driven
Monte-Carlo-style Boltzmann solver is employed to describe particles of a
second species of low concentration. In order to evaluate the model, standard
diffusivity and diffusion advection systems are considered.Comment: 9 pages, 8 figure
Recommended from our members
Hydro schemes and reactive flow in 1-d and 2-d
The behavior of the implementation of Craig Tarver's reactive flow model for high explosives in a hydro code is investigated. The model produces the correct shock propagation rates. The effects of geometry, zoning and artificial viscosity are compared in one (1D) and two (2D) dimensions. Sensitivities to the solution scheme of the hydro equations are also investigated. A comparison with an experimentally verified, analytic theory is presented for the speed of spherically diverging reactive flow fronts. We show that for LX-14 the reactive flow results obey that theory and a lag of about 1.5 to 2.0 mm is produced in a spherical system in about 5 cm of travel from the origin compared to programmed burn. Reactive flow is shown to produce a more strongly developed Mach stem than does conventional, programmed lighting assisted by beta burn. The reactive flow results appear to be close to convergence for zone sizes of 1/16 mm. Several numerical anomalies in code/model behavior are shown and their limited effects are discussed. Some one-dimensional results for LX-17 are also briefly discussed
Verification of Item Usage Rules in Product Configuration
In the development of complex products product configuration systems are often used to support the development process. Item Usage Rules (IURs) are conditions for including specific items in products bills of materials based on a high-level product description. Large number of items and significant complexity of IURs make it difficult to maintain and analyze IURs manually. In this paper we present an automated approach for verifying IURs, which guarantees the presence of exactly one item from a predefined set in each product, as well as that an IUR can be reformulated without changing the set of products for which the item was included
On Optimization Modulo Theories, MaxSMT and Sorting Networks
Optimization Modulo Theories (OMT) is an extension of SMT which allows for
finding models that optimize given objectives. (Partial weighted) MaxSMT --or
equivalently OMT with Pseudo-Boolean objective functions, OMT+PB-- is a
very-relevant strict subcase of OMT. We classify existing approaches for MaxSMT
or OMT+PB in two groups: MaxSAT-based approaches exploit the efficiency of
state-of-the-art MAXSAT solvers, but they are specific-purpose and not always
applicable; OMT-based approaches are general-purpose, but they suffer from
intrinsic inefficiencies on MaxSMT/OMT+PB problems.
We identify a major source of such inefficiencies, and we address it by
enhancing OMT by means of bidirectional sorting networks. We implemented this
idea on top of the OptiMathSAT OMT solver. We run an extensive empirical
evaluation on a variety of problems, comparing MaxSAT-based and OMT-based
techniques, with and without sorting networks, implemented on top of
OptiMathSAT and {\nu}Z. The results support the effectiveness of this idea, and
provide interesting insights about the different approaches.Comment: 17 pages, submitted at Tacas 1
Generalized Totalizer Encoding for Pseudo-Boolean Constraints
Pseudo-Boolean constraints, also known as 0-1 Integer Linear Constraints, are
used to model many real-world problems. A common approach to solve these
constraints is to encode them into a SAT formula. The runtime of the SAT solver
on such formula is sensitive to the manner in which the given pseudo-Boolean
constraints are encoded. In this paper, we propose generalized Totalizer
encoding (GTE), which is an arc-consistency preserving extension of the
Totalizer encoding to pseudo-Boolean constraints. Unlike some other encodings,
the number of auxiliary variables required for GTE does not depend on the
magnitudes of the coefficients. Instead, it depends on the number of distinct
combinations of these coefficients. We show the superiority of GTE with respect
to other encodings when large pseudo-Boolean constraints have low number of
distinct coefficients. Our experimental results also show that GTE remains
competitive even when the pseudo-Boolean constraints do not have this
characteristic.Comment: 10 pages, 2 figures, 2 tables. To be published in 21st International
Conference on Principles and Practice of Constraint Programming 201
On Tackling the Limits of Resolution in SAT Solving
The practical success of Boolean Satisfiability (SAT) solvers stems from the
CDCL (Conflict-Driven Clause Learning) approach to SAT solving. However, from a
propositional proof complexity perspective, CDCL is no more powerful than the
resolution proof system, for which many hard examples exist. This paper
proposes a new problem transformation, which enables reducing the decision
problem for formulas in conjunctive normal form (CNF) to the problem of solving
maximum satisfiability over Horn formulas. Given the new transformation, the
paper proves a polynomial bound on the number of MaxSAT resolution steps for
pigeonhole formulas. This result is in clear contrast with earlier results on
the length of proofs of MaxSAT resolution for pigeonhole formulas. The paper
also establishes the same polynomial bound in the case of modern core-guided
MaxSAT solvers. Experimental results, obtained on CNF formulas known to be hard
for CDCL SAT solvers, show that these can be efficiently solved with modern
MaxSAT solvers
CLPM: A Cross-Linked Peptide Mapping Algorithm for Mass Spectrometric Analysis
BACKGROUND: Protein-protein, protein-DNA and protein-RNA interactions are of central importance in biological systems. Quadrapole Time-of-flight (Q-TOF) mass spectrometry is a sensitive, promising tool for studying these interactions. Combining this technique with chemical crosslinking, it is possible to identify the sites of interactions within these complexes. Due to the complexities of the mass spectrometric data of crosslinked proteins, new software is required to analyze the resulting products of these studies. RESULT: We designed a Cross-Linked Peptide Mapping (CLPM) algorithm which takes advantage of all of the information available in the experiment including the amino acid sequence from each protein, the identity of the crosslinker, the identity of the digesting enzyme, the level of missed cleavage, and possible chemical modifications. The algorithm does in silico digestion and crosslinking, calculates all possible mass values and matches the theoretical data to the actual experimental data provided by the mass spectrometry analysis to identify the crosslinked peptides. CONCLUSION: Identifying peptides by their masses can be an efficient starting point for direct sequence confirmation. The CLPM algorithm provides a powerful tool in identifying these potential interaction sites in combination with chemical crosslinking and mass spectrometry. Through this cost-effective approach, subsequent efforts can quickly focus attention on investigating these specific interaction sites
Carbene footprinting accurately maps binding sites in protein–ligand and protein–protein interactions
Specific interactions between proteins and their binding partners are fundamental to life processes. The ability to detect protein complexes, and map their sites of binding, is crucial to understanding basic biology at the molecular level. Methods that employ sensitive analytical techniques such as mass spectrometry have the potential to provide valuable insights with very little material and on short time scales. Here we present a differential protein footprinting technique employing an efficient photo-activated probe for use with mass spectrometry. Using this methodology the location of a carbohydrate substrate was accurately mapped to the binding cleft of lysozyme, and in a more complex example, the interactions between a 100 kDa, multi-domain deubiquitinating enzyme, USP5 and a diubiquitin substrate were located to different functional domains. The much improved properties of this probe make carbene footprinting a viable method for rapid and accurate identification of protein binding sites utilizing benign, near-UV photoactivation
Mapping protein interfaces by a trifunctional cross-linker combined with MALDI-TOF and ESI-FTICR mass spectrometry
Music models aberrant rule decoding and reward valuation in dementia.
Aberrant rule- and reward-based processes underpin abnormalities of socio-emotional behaviour in major dementias. However, these processes remain poorly characterized. Here we used music to probe rule decoding and reward valuation in patients with frontotemporal dementia (FTD) syndromes and Alzheimer's disease (AD) relative to healthy age-matched individuals. We created short melodies that were either harmonically resolved ('finished') or unresolved ('unfinished'); the task was to classify each melody as finished or unfinished (rule processing) and rate its subjective pleasantness (reward valuation). Results were adjusted for elementary pitch and executive processing; neuroanatomical correlates were assessed using voxel-based morphometry. Relative to healthy older controls, patients with behavioural variant FTD showed impairments of both musical rule decoding and reward valuation, while patients with semantic dementia showed impaired reward valuation but intact rule decoding, patients with AD showed impaired rule decoding but intact reward valuation and patients with progressive non-fluent aphasia performed comparably to healthy controls. Grey matter associations with task performance were identified in anterior temporal, medial and lateral orbitofrontal cortices, previously implicated in computing diverse biological and non-biological rules and rewards. The processing of musical rules and reward distils cognitive and neuroanatomical mechanisms relevant to complex socio-emotional dysfunction in major dementias
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