Hydroisomerization of long-chain alkane over Pt/SAPO-11 catalysts synthesized from nonaqueous media

SAPO-11 molecular sieves were synthesized from nonaqueous media. The effects of Si and Al sources as well as solvents on the catalytic performance of SAPO-11 were investigated by the hydroisomerization reaction of n-dodecane. The samples were characterized by XRD, XRF, N-2-adsorption, SEM, NH3-TPD, IR-NH3 and Si-29 CP MAS NMR. The SAPO-11 samples synthesized with tetraethoxysilane as the Si source showed higher Si incorporation contents than the SAPO molecular sieves prepared with polymeric Si sources (fumed silica and Si colloidal gel). The reaction results showed that Pt/SAPO-11 catalysts synthesized from ethylene glycol and glycerol media with the monomeric Si and Al sources (tetraethoxysilane, aluminum isopropoxide) exhibited higher catalytic activities than those catalysts with the polymeric Si or Al (pseudo-boehmite) sources, due to the larger external surface area and higher acidity of the former ones. Especially, the catalyst synthesized in an ethylene glycol medium possessed the highest catalytic activity. Over this catalyst, 88% conversion of n-dodecane was achieved at a low temperature of 250 degrees C.

Process control in agile supply chain network.

The work comprises a new theoretical development applied to aid decision making in an increasingly important commercial sector. Agile supply, where small volumes of high margin, short life cycle innovative products are offered, is increasingly carried out through a complex global supply chain network. We outline an equilibrium solution in such a supply chain network, which works through limited cooperation and coordination along edges (links) in the network. The links constitute the stochastic modelling entities rather than the nodes of the network. We utilise newly developed phase plane analysis to identify, model and predict characteristic behaviour in supply chain networks. The phase plane charts profile the flow of inventory and identify out of control conditions. They maintain quality within the network, as well as intelligently track the way the network evolves in conditions of changing variability. The methodology is essentially distribution free, relying as it does on the study of forecasting errors, and can be used to examine contractual details as well as strategic and game theoretical concepts between decision-making components (agents) of a network. We illustrate with typical data drawn from supply chain agile fashion products.

Novelty and Habituation: the Driving Forces in Early Stage Learning for Developmental Robotics

Meng, Q., & Lee, M. (2005). Novelty and Habituation: the Driving Forces in Early Stage Learning for Developmental Robotics. Wermter, S., Palm, G., & Elshaw, M. (Eds.), In: Biomimetic Neural Learning for Intelligent Robots: Intelligent Systems, Cognitive Robotics, and Neuroscience. (pp. 315-332). (Lecture Notes in Computer Science). Springer Berlin Heidelberg.

Novelty and Habituation: the Driving Forces in Early Stage Learning for Developmental Robotics

Q. Meng and M. H. Lee, Novelty and Habituation: the Driving Forces in Early Stage Learning for Developmental Robotics, AI-Workshop on NeuroBotics, University of Ulm, Germany. September 2004.

Instabilities in two-dimensional flower and chain clusters of bubbles

M.A. Fortes et al., Instabilities in two-dimensional flower and chain clusters of bubbles, Colloids and Surfaces A: Physicochemical and Engineering Aspects Volume 309, Issues 1-3, 1 November 2007, Pages 64-70 A Collection of Papers Presented at the 6th Eufoam Conference, Potsdam, Germany, 2-6 July, 2006

Fault identification through the combination of symbolic conflict recognition and Markov Chain-aided belief revision

F. Smith and Q. Shen. Fault identification through the combination of symbolic conflict recognition and Markov Chain-aided belief revision. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 34(5):649-663, 2004.

Systematic Verification of Safety Properties of Arbitrary Network Protocol Compositions Using CHAIN

Formal correctness of complex multi-party network protocols can be difficult to verify. While models of specific fixed compositions of agents can be checked against design constraints, protocols which lend themselves to arbitrarily many compositions of agents-such as the chaining of proxies or the peering of routers-are more difficult to verify because they represent potentially infinite state spaces and may exhibit emergent behaviors which may not materialize under particular fixed compositions. We address this challenge by developing an algebraic approach that enables us to reduce arbitrary compositions of network agents into a behaviorally-equivalent (with respect to some correctness property) compact, canonical representation, which is amenable to mechanical verification. Our approach consists of an algebra and a set of property-preserving rewrite rules for the Canonical Homomorphic Abstraction of Infinite Network protocol compositions (CHAIN). Using CHAIN, an expression over our algebra (i.e., a set of configurations of network protocol agents) can be reduced to another behaviorally-equivalent expression (i.e., a smaller set of configurations). Repeated applications of such rewrite rules produces a canonical expression which can be checked mechanically. We demonstrate our approach by characterizing deadlock-prone configurations of HTTP agents, as well as establishing useful properties of an overlay protocol for scheduling MPEG frames, and of a protocol for Web intra-cache consistency.

A Model of Cerebellar Adaptation of Grip Forces During Lifting

We investigated adaptive neural control of precision grip forces during object lifting. A model is presented that adjusts reactive and anticipatory grip forces to a level just above that needed to stabilize lifted objects in the hand. The model obeys priciples of cerebellar structure and function by using slip sensations as error signals to adapt phasic motor commands to tonic force generators associated with output synergies controlling grip aperture. The learned phasic commands are weight and texture-dependent. Simulations of the new curcuit model reproduce key aspects of experimental observations of force application. Over learning trials, the onset of grip force buildup comes to lead the load force buildup, and the rate-of-rise of grip force, but not load force, scales inversely with the friction of the gripped object.

Conjunctive Chain Modification to the Boundary Contour System Neural Vision Model

The Boundary Contour System neural vision model reproduces perceptual illusory boundary formation by a conjunctive boundary completion process within a large cellular receptive field. The conjunctive chain allows the same kind of conjunction to occur across multiple receptive fields, which allows for sharper, more flexible boundary completion.