A versatile content addressable memory architecture

In this paper, a novel configurable content addressable memory (CCAM) cell is proposed, to increase the flexibility of embedded CAMs for SoC employment. It can be easily configured as a Binary CAM (BiCAM) or Ternary CAM (TCAM) without significant penalty of power consumption or searching speed. A 64x128 CCAM array has been built and verified through simulation. ©2007 IEEE.

Crystal structure and magnetic properties of the new phase Mn3IrSi

A new phase in the ternary Ir-Mn-Si system has been synthesised. From powder neutron diffraction data the crystal structure was determined to be of the AlAu4 type and to be described in the cubic space group P2(1)3 with the unit cell a = 6.4973(3) Angstrom. Susceptibility measurements using a SQUID-magnetometer showed a transition typical of anti ferromagnetism, with T-N = 210 K. Low temperature antiferromagnetic order is confirmed by extra peaks in neutron diffractograms recorded at 10 and 80 K. (C) 2004 Elsevier B.V. All rights reserved.

Crystal and magnetic structure of Mn3IrSi

A new ternary Ir-Mn-Si phase with stoichiometry Mn₃IrSi has been synthesized and found to crystallize in the cubic AlAu₄-type structure, space group P2₁3 with Z=4, which is an ordered form of the beta-Mn structure. The unit cell dimension was determined by x-ray powder diffraction to a=6.4973(3) Angstrom. In addition to the crystal structure, we have determined the magnetic structure and properties using superconducting quantum interference device magnetometry and Rietveld refinements of neutron powder diffraction data. A complex noncollinear magnetic structure is found, with magnetic moments of 2.97(4)u(B) at 10 K only on the Mn atoms. The crystal structure consists of a triangular network built up by Mn atoms, on which the moments are rotated 120degrees around the triangle axes. The magnetic unit cell is the same as the crystallographic and carries no net magnetic moment. The Neel temperature was determined to be 210 K. A first-principles study, based on density functional theory in a general noncollinear formulation, reproduces the experimental results with good agreement. The observed magnetic structure is argued to be the result of frustration of antiferromagnetic couplings by the triangular geometry.

Polarisabilities of alkylimidazolium ionic liquids

The molar polarisability and molar volume for 71 ionic liquids were extracted from 157 measurements of their refractive index and density, which were then further deconstructed into atomic contributions by means of a Designed Regression analysis. Using this approach, the density and refractive index for any chosen ionic liquid with alkyl-substituted imidazolium cations can be predicted in good agreement with experimental data.

Ferromagnetism in DyRh and DyRhX (X = Fe, Ni, Co, Gd) thin films

In an effort to achieve large high-field magnetization and increased Curie temperature, polycrystalline DyRh, (DyRh)95X5 and (DyRh)85X15 (X = Fe, Co, Ni, Gd) thin films have been prepared via ultra-high vacuum DC co-sputtering on SiO2 and Si wafers, using Ta as seed and cap material. A body-centred cubic CsCl-like crystal formation (B2 phase) was achieved for DyRh around the equiatomic equilibrium, known from single crystals. The maximum in-plane spontaneous magnetization at T = 4K in fields of μ0H = 5T of was found to be μ0MS,4K = (1.50 ± 0.09)T with a ferromagnetic transition at TC = (5 ± 1)K and a coercivity of μ0HC,4K[D] = (0.010 ± 0.001)T (at T = 4K) for layers deposited on substrates heated to 350°C. Samples prepared at room temperature exhibited poorer texture, smaller grains and less B2-phase content; this did impact on the Curie temperature which was higher compared to those layers with best crystallisation; however the maximal magnetization stayed unaffected. Ferromagnetic coupling was observed in ternary alloys of DyRhGd and DyRhNi with an increased Curie temperature, larger initial permeability, and
high-field magnetization which was best for (DyRh)85Gd15 with μ0MS,4K[Gd15] = (2.10 ± 0.13)T. DyRhFe and DyRhCo showed antiparallel coupling of the spontaneous magnetic moments.

Use of water in aiding olefin/paraffin (liquid + liquid) extraction via complexation with a silver bis(trifluoromethylsulfonyl)imide salt

This paper describes the extraction of C₅–C₈ linear α-olefins from olefin/paraffin mixtures of the same carbon number via a reversible complexation with a silver salt (silver bis(trifluoromethylsulfonyl)imide, Ag[Tf₂N]) to form room temperature ionic liquids [Ag(olefin)_x][Tf₂N]. From the experimental (liquid + liquid) equilibrium data for the olefin/paraffin mixtures and Ag[Tf₂N], 1-pentene showed the best separation performance while C₇ and C₈ olefins could only be separated from the corresponding mixtures on addition of water which also improves the selectivity at lower carbon numbers like the C₅ and C₆, for example. Using infrared and Raman spectroscopy of the complex and Ag[Tf₂N] saturated by olefin, the mechanism of the extraction was found to be based on both chemical complexation and the physical solubility of the olefin in the ionic liquid ([Ag(olefin)_x][Tf₂N]). These experiments further support the use of such extraction techniques for the separation of olefins from paraffins.

Probabilistic Inference in Credal Networks: New Complexity Results

Credal networks are graph-based statistical models whose parameters take values in a set, instead of being sharply specified as in traditional statistical models (e.g., Bayesian networks). The computational complexity of inferences on such models depends on the irrelevance/independence concept adopted. In this paper, we study inferential complexity under the concepts of epistemic irrelevance and strong independence. We show that inferences under strong independence are NP-hard even in trees with binary variables except for a single ternary one. We prove that under epistemic irrelevance the polynomial-time complexity of inferences in credal trees is not likely to extend to more general models (e.g., singly connected topologies). These results clearly distinguish networks that admit efficient inferences and those where inferences are most likely hard, and settle several open questions regarding their computational complexity. We show that these results remain valid even if we disallow the use of zero probabilities. We also show that the computation of bounds on the probability of the future state in a hidden Markov model is the same whether we assume epistemic irrelevance or strong independence, and we prove an analogous result for inference in Naive Bayes structures. These inferential equivalences are important for practitioners, as hidden Markov models and Naive Bayes networks are used in real applications of imprecise probability.

On the complexity of solving polytree-shaped limited memory influence diagrams with binary variables

Influence diagrams are intuitive and concise representations of structured decision problems. When the problem is non-Markovian, an optimal strategy can be exponentially large in the size of the diagram. We can avoid the inherent intractability by constraining the size of admissible strategies, giving rise to limited memory influence diagrams. A valuable question is then how small do strategies need to be to enable efficient optimal planning. Arguably, the smallest strategies one can conceive simply prescribe an action for each time step, without considering past decisions or observations. Previous work has shown that finding such optimal strategies even for polytree-shaped diagrams with ternary variables and a single value node is NP-hard, but the case of binary variables was left open. In this paper we address such a case, by first noting that optimal strategies can be obtained in polynomial time for polytree-shaped diagrams with binary variables and a single value node. We then show that the same problem is NP-hard if the diagram has multiple value nodes. These two results close the fixed-parameter complexity analysis of optimal strategy selection in influence diagrams parametrized by the shape of the diagram, the number of value nodes and the maximum variable cardinality.

On the Complexity of Strong and Epistemic Credal Networks

Credal networks are graph-based statistical models whose parameters take values on a set, instead of being sharply specified as in traditional statistical models (e.g., Bayesian networks). The result of inferences with such models depends on the irrelevance/independence concept adopted. In this paper, we study the computational complexity of inferences under the concepts of epistemic irrelevance and strong independence. We strengthen complexity results by showing that inferences with strong independence are NP-hard even in credal trees with ternary variables, which indicates that tractable algorithms, including the existing one for epistemic trees, cannot be used for strong independence. We prove that the polynomial time of inferences in credal trees under epistemic irrelevance is not likely to extend to more general models, because the problem becomes NP-hard even in simple polytrees. These results draw a definite line between networks with efficient inferences and those where inferences are hard, and close several open questions regarding the computational complexity of such models.

Measuring beta diversity for presence-absence data

1. Little consensus has been reached as to general features of spatial variation in beta diversity, a fundamental component of species diversity. This could reflect a genuine lack of simple gradients in beta diversity, or a lack of agreement as to just what constitutes beta diversity. Unfortunately, a large number of approaches have been applied to the investigation of variation in beta diversity, which potentially makes comparisons of the findings difficult.

2. We review 24 measures of beta diversity for presence/absence data (the most frequent form of data to which such measures are applied) that have been employed in the literature, express many of them for the first time in common terms, and compare some of their basic properties.

3. Four groups of measures are distinguished, with a fundamental distinction arising between 'broad sense' measures incorporating differences in composition attributable to species richness gradients, and 'narrow sense' measures that focus on compositional differences independent of such gradients. On a number of occasions on which the former have been employed in the literature the latter may have been more appropriate, and there are many situations in which consideration of both kinds of measures would be valuable.

4. We particularly recommend (i) considering beta diversity measures in terms of matching/mismatching components (usually denoted a , b and c) and thereby identifying the contribution of different sources of variation in species composition, and (ii) the use of ternary plots to express the relationship between the values of these measures and of the components, and as a way of understanding patterns in beta diversity.

Schur idempotents and hyperreflexivity

We show that the set of Schur idempotents with hyperreflexive range is a Boolean lattice which contains all contractions. We establish a preservation result for sums which implies that the weak* closed span of a hyperreflexive and a ternary masa-bimodule is hyperreflexive, and prove that the weak* closed span of finitely many tensor products of a hyperreflexive space and a hyperreflexive range of a Schur idempotent (respectively, a ternary masa-bimodule) is hyperreflexive.

Evaluation of the ionic liquids 1-alkyl-3-methylimidazolium hexafluorophosphate as a solvent for the extraction of benzene from cyclohexane : ( Liquid + liquid ) equilibria

In the catalytic hydrogenation of benzene to cyclohexane, the separation of unreacted benzene from the product stream is inevitable and essential for an economically viable process. In order to evaluate the separation efficiency of ionic liquids (ILs) as a solvent in this extraction processes, the ternary (liquid + liquid) equilibrium of 1-alkyl-3-methylimidazolium hexafluorophosphate, [Cnmim][PF6] (n = 4, 5, 6), with benzene and cyclohexane was studied at T = 298.15 K and atmospheric pressure. The reliability of the experimentally determined tie-line data was confirmed by applying the Othmer–Tobias equation. The solute distribution coefficient and solvent selectivity for the systems studied were calculated and compared with literature data for other ILs and sulfolane. It turns out that the benzene distribution coefficient increases and solvent selectivity decreases as the length of the cation alkyl chain grows, and the ionic liquids [Cnmim][PF6] proved to be promising solvents for benzene–cyclohexane extractive separation. Finally, an NRTL model was applied to correlate and fit the experimental LLE data for the ternary systems studied.

Deep separation of benzene from cyclohexane by liquid extraction using ionic liquids as the solvent

Separation of benzene and cyclohexane is one of the most important and difficult processes in the petrochemical industry, especially for low benzene concentration. In this work, three ionic liquids (ILs), [Bmim][BF ₄], [Bpy][BF ₄], and [Bmim][SCN], were investigated as the solvent in the extraction of benzene from cyclohexane. The corresponding ternary liquid-liquid equilibria (LLE) were experimentally determined at T = 298.15 K and atmospheric pressure. The LLE data were correlated with the nonrandom two-liquid model, and the parameters were fitted. The separation capabilities of the ILs were evaluated in terms of the benzene distribution coefficient and solvent selectivity. The effect of the IL structure on the separation was explained based on a well-founded physical model, COSMO-RS. Finally, the extraction processes were defined, and the operation parameters were analyzed. It shows that the ILs studied are suitable solvents for the extractive separation of benzene and cyclohexane, and their separation efficiency can be generally ranked as [Bmim][BF ₄] > [Bpy][BF ₄] > [Bmim][SCN]. The extraction process for a feed with 15 mol % benzene was optimized. High product purity (cyclohexane 0.997) and high recovery efficiency (cyclohexane 96.9% and benzene 98.1%) can be reached. © 2012 American Chemical Society.

Gene regulatory mechanisms underpinning prostate cancer susceptibility

Molecular characterization of genome-wide association study (GWAS) loci can uncover key genes and biological mechanisms underpinning complex traits and diseases. Here we present deep, high-throughput characterization of gene regulatory mechanisms underlying prostate cancer risk loci. Our methodology integrates data from 295 prostate cancer chromatin immunoprecipitation and sequencing experiments with genotype and gene expression data from 602 prostate tumor samples. The analysis identifies new gene regulatory mechanisms affected by risk locus SNPs, including widespread disruption of ternary androgen receptor (AR)-FOXA1 and AR-HOXB13 complexes and competitive binding mechanisms. We identify 57 expression quantitative trait loci at 35 risk loci, which we validate through analysis of allele-specific expression. We further validate predicted regulatory SNPs and target genes in prostate cancer cell line models. Finally, our integrated analysis can be accessed through an interactive visualization tool. This analysis elucidates how genome sequence variation affects disease predisposition via gene regulatory mechanisms and identifies relevant genes for downstream biomarker and drug development.