403 research outputs found

    Mesoscopic simulation of diffusive contaminant spreading in gas flows at low pressure

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    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

    Verification of Item Usage Rules in Product Configuration

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    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

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    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

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    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

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    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

    Carbene footprinting accurately maps binding sites in protein–ligand and protein–protein interactions

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    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

    Evaluating Imide-Based Mass Spectrometry-Cleavable Cross-Linkers for Structural Proteomics Studies

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    Disuccinimidyl dibutyric urea (DSBU) is a mass spectrometry (MS)-cleavable cross-linker that has multiple applications in structural biology, ranging from isolated protein complexes to comprehensive system-wide interactomics. DSBU facilitates a rapid and reliable identification of cross-links through the dissociation of its urea group in the gas phase. In this study, we further advance the structural capabilities of DSBU by remodeling the urea group into an imide, thus introducing a novel class of cross-linkers. This modification preserves the MS cleavability of the amide bond, granted by the two acyl groups of the imide function. The central nitrogen atom enables the introduction of affinity purification tags. Here, we introduce disuccinimidyl disuccinic imide (DSSI) as a prototype of this class of cross-linkers. It features a phosphonate handle for immobilized metal ion affinity chromatography enrichment. We detail DSSI synthesis and describe its behavior in solution and in the gas phase while cross-linking isolated proteins and human cell lysates. DSSI and DSBU cross-links are compared at the same enrichment depth to bridge these two cross-linker classes. We validate DSSI cross-links by mapping them in high-resolution structures of large protein assemblies. The cross-links observed yield insights into the morphology of intrinsically disordered proteins and their complexes. The DSSI linker might spearhead a novel class of MS-cleavable and enrichable cross-linkers

    Recent Progress in the Use of Glucagon and Glucagon Receptor Antagonists in the Treatment of Diabetes Mellitus

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    Glucagon is an important pancreatic hormone, released into blood circulation by alpha cells of the islet of Langerhans. Glucagon induces gluconeogenesis and glycogenolysis in hepatocytes, leading to an increase in hepatic glucose production and subsequently hyperglycemia in susceptible individuals. Hyperglucagonemia is a constant feature in patients with T2DM. A number of bioactive agents that can block glucagon receptor have been identified. These glucagon receptor antagonists can reduce the hyperglycemia associated with exogenous glucagon administration in normal as well as diabetic subjects. Glucagon receptor antagonists include isoserine and beta-alanine derivatives, bicyclic 19-residue peptide BI-32169, Des-His1-[Glu9] glucagon amide and related compounds, 5-hydroxyalkyl-4-phenylpyridines, N-[3-cano-6- (1,1 dimethylpropyl)-4,5,6,7-tetrahydro-1-benzothien-2-yl]-2-ethylbutamide, Skyrin and NNC 250926. The absorption, dosage, catabolism, excretion and medicinal chemistry of these agents are the subject of this review. It emphasizes the role of glucagon in glucose homeostasis and how it could be applied as a novel tool for the management of diabetes mellitus by blocking its receptors with either monoclonal antibodies, peptide and non-peptide antagonists or gene knockout techniques

    The megakaryocytic transcription factor ARID3A suppresses leukemia pathogenesis

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    Given the plasticity of hematopoietic stem and progenitor cells, multiple routes of differentiation must be blocked in the the pathogenesis of acute myeloid leukemia, the molecular basis of which is incompletely understood. We report that posttranscriptional repression of the transcription factor ARID3A by miR-125b is a key event in the pathogenesis of acute megakaryoblastic leukemia (AMKL). AMKL is frequently associated with trisomy 21 and GATA1 mutations (GATA1s), and children with Down syndrome are at a high risk of developing the disease. The results of our study showed that chromosome 21-encoded miR-125b synergizes with Gata1s to drive leukemogenesis in this context. Leveraging forward and reverse genetics, we uncovered Arid3a as the main miR-125b target behind this synergy. We demonstrated that, during normal hematopoiesis, this transcription factor promotes megakaryocytic differentiation in concert with GATA1 and mediates TGFβ-induced apoptosis and cell cycle arrest in complex with SMAD2/3. Although Gata1s mutations perturb erythroid differentiation and induce hyperproliferation of megakaryocytic progenitors, intact ARID3A expression assures their megakaryocytic differentiation and growth restriction. Upon knockdown, these tumor suppressive functions are revoked, causing a blockade of dual megakaryocytic/erythroid differentiation and subsequently of AMKL. Inversely, restoring ARID3A expression relieves the arrest of megakaryocytic differentiation in AMKL patient-derived xenografts. This work illustrates how mutations in lineage-determining transcription factors and perturbation of posttranscriptional gene regulation can interact to block multiple routes of hematopoietic differentiation and cause leukemia. In AMKL, surmounting this differentiation blockade through restoration of the tumor suppressor ARID3A represents a promising strategy for treating this lethal pediatric disease
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