Direct activity measurements in liquid Ag−Cu alloys using a valved knudsen cell-mass spectrometer system

The primary objective of this investigation was to demonstrate a new method of measuring activities. The mass spectrometric analysis of effusates from a unique valved Knudsen cell was used to determine the activity of Ag in the liquid Ag−Cu system at 1400 K. The alloy compositions were varied from one composition extreme to the otherin situ. The system exhibits positive deviation from ideal behavior, and the results are in agreement with previous investigations and are summarized by the equation

Standing up to the big squeeze

Consumer confidence is at its lowest ebb since 1980. Economic growth is at a standstill & unemployment & inflation are both rising. Here's a front-line report from more than three dozen operators who are fending off the recession's dual pressures of slow sales & rising costs. They are using discount pricing, partnering with vendors, setting pay for performance standards & a variety of other recession-beating practices.     

Mechanical properties of certain oriented crystalline polymers

The yield stress is a simple function of the deformation ratio in the direction of testing for specimens oriented by uniaxial or biaxial stretching or rolling. Unless the yield stress increases more rapidly than in proportion to the deformation ratio, there will be instability during tensile creep under high loads. The relative merit of various polymers differs for creep and stress relaxation. Fatigue and bend recovery are also related to the molecular structure.     

Cuticular hydrocarbons ofReticulitermes virginicus (Banks) and their role as potential species- and caste-recognition cues

The cuticular hydrocarbon components of four castes ofReticulitermes virginicus (Banks) have been identified and quantitated. Components identified includen-alkanes; 2-, 3-, 11-, 13-, and 15-methyl-alkanes; 11,15-dimethylalkanes, (Z)-9-alkenes; (Z,Z)-7,9-dienes; and (E/Z)-6,9-dienes ranging in carbon number from C₂₁ to C₄₀. All caste forms ofR.virginicus contained the same components, but showed caste-specific proportions. Comparison of these hydrocarbons with those of the sympatric termiteR. flavipes (Kollar) suggest that cuticular hydrocarbons might serve as species- and caste-recognition cues. A bioassay was developed to test this species-recognition hypothesis, with the experimental results supporting the hypothesis.Isoptera: Rhinotermitidae.     

Cuticular lipids of the booklouse,Liposcelis bostrychophila: hydrocarbons,aldehydes, fatty acids,and fatty acid amides

The booklouse, Liposcelis bostrychophila, is an increasingly common pest of stored food products worldwide. We report here the cuticular lipid composition of this pest (the first report of the hydrocarbons of any member of the Order Psocoptera and the first report of fatty acid amides as cuticular components for any insect). No unsaturated hydrocarbons were present. A homologous series of n-alkanes (C₂₁–C₃₄), monomethyl alkanes (3-, 4-, 5-, 7-, 9-, 11-, 12-, 13- and 15-methyl-) with a carbon chain range of C₂₈–C₄₂, and dimethyl alkanes (3, 7-; 9, 13-; 11, 15-; 13, 17-; 9, 21-; 11, 19-; and 13, 21-); with a carbon number range of C₃₁–C₄₃ were identified. The relative abundances of these hydrocarbons were low, comprising approximately 0.0125% of total biomass. The amides were a homologous series (C₁₆–C₂₂ in chain length), with the major amide being stearoyl amide. In addition to the amides, free fatty acids (C_16:1, C_16:0, C_18:2, C_18:1, and C_18:0 in chain length) and three straight chain aldehydes (C₁₅, C₁₆, and C_17:1 in chain length) also occurred as cuticular components. These findings are discussed in terms of the chemical and physiological ecology of this species.     

Analysing neurobiological models using communicating automata

Two important issues in computational modelling in cognitive neuroscience are: first, how to formally describe neuronal networks (i.e. biologically plausible models of the central nervous system), and second, how to analyse complex models, in particular, their dynamics and capacity to learn. We make progress towards these goals by presenting a communicating automata perspective on neuronal networks. Specifically, we describe neuronal networks and their biological mechanisms using Data-rich Communicating Automata, which extend classic automata theory with rich data types and communication. We use two case studies to illustrate our approach. In the first case study, we model a number of learning frameworks, which vary in respect of their biological detail, for instance the Backpropagation (BP) and the Generalized Recirculation (GeneRec) learning algorithms. We then used the SPIN model checker to investigate a number of behavioral properties of the neural learning algorithms. SPIN is a well-known model checker for reactive distributed systems, which has been successfully applied to many non-trivial problems. The verification results show that the biologically plausible GeneRec learning is less stable than BP learning. In the second case study, we presented a large scale (cognitive-level) neuronal network, which models an attentional spotlight mechanism in the visual system. A set of properties of this model was verified using Uppaal, a popular real-time model checker. The results show that the asynchronous processing supported by concurrency theory is not only a more biologically plausible way to model neural systems, but also provides a better performance in cognitive modelling of the brain than conventional artificial neural networks that use synchronous updates. Finally, we compared our approach with several other related theories that apply formal methods to cognitive modelling. In addition, the practical implications of the approach are discussed in the context of neuronal network based controllers.     

Generating hydrogen-rich fuel-cell feeds from dimethyl ether (DME) using physical mixtures of a commercial Cu/Zn/Al2O3 catalyst and several solid–acid catalysts

Homogeneous physical mixtures containing a commercial Cu/ZnO/Al₂O₃ catalyst and a solid–acid catalyst were used to examine the acidity effects on dimethyl ether hydrolysis and their subsequent effects on dimethyl ether steam reforming (DME-SR). The acid catalysts used were zeolites Y [Si/Al = 2.5 and 15: denoted Y(Si/Al)], ZSM-5 [Si/Al = 15, 25, 40, and 140: denoted Z(Si/Al)] and other conventional catalyst supports (ZrO₂, and γ-Al₂O₃). The homogeneous physical mixtures contained equal amounts, by volume, of the solid–acid catalyst and the commercial Cu/ZnO/Al₂O₃ catalyst (BASF K3-110, denoted as K3). The steam reforming of dimethyl ether was carried out in an isothermal packed-bed reactor at ambient pressure.

The most promising physical mixtures for the low-temperature production of hydrogen from DME contained ZSM-5 as the solid–acid catalyst, with hydrogen yields exceeding 90% (T = 275 °C, S/C = 1.5, τ = 1.0 s and P = 0.78 atm) and hydrogen selectivities exceeding 94%, comparable to those observed for methanol steam reforming (MeOH-SR) over BASF K3-110, with values equaling 95% and 99%, respectively (T = 225 °C, S/C = 1.0, τ = 1.0 s and P = 0.78 atm). Large production rates of hydrogen were directly related to the type of acid catalyst used. The hydrogen production activity trend as a function of physical mixture was