A Cartesian‐grid collocation technique with integrated radial basis functions for mixed boundary value problems

In this paper, high‐order systems are reformulated as first‐order systems, which are then numerically solved by a collocation method. The collocation method is based on Cartesian discretization with 1D‐integrated radial basis function networks (1D‐IRBFN) (Numer. Meth. Partial Differential Equations 2007; 23 :1192–1210). The present method is enhanced by a new boundary interpolation technique based on 1D‐IRBFN, which is introduced to obtain variable approximation at irregular points in irregular domains. The proposed method is well suited to problems with mixed boundary conditions on both regular and irregular domains. The main results obtained are (a) the boundary conditions for the reformulated problem are of Dirichlet type only; (b) the integrated RBFN approximation avoids the well‐known reduction of convergence rate associated with differential formulations; (c) the primary variable (e.g. displacement, temperature) and the dual variable (e.g. stress, temperature gradient) have similar convergence order; (d) the volumetric locking effects associated with incompressible materials in solid mechanics are alleviated. Numerical experiments show that the proposed method achieves very good accuracy and high convergence rates. Copyright © 2009 John Wiley & Sons, Ltd.     

Efficient recycling of WC-Co hardmetal sludge by oxidation followed by alkali and sulfuric acid treatments

We present a process to recycle strategic metals, viz. tungsten and cobalt, from a WC-Co hardmetal sludge (WCHS) via oxidation followed by a two-step hydrometallurgical treatment with alkali and acid solutions. The oxidation of WCHS was investigated in the temperature range of 500 to 1000 °C and optimized at 600 °C to transform the maximum WC into an alkali-soluble WO₃. The conditions for the selective dissolution of WO3 in stage-I were optimized as follows: 4.0 M NaOH, pulp density of 175 g/L, and temperature of 100 °C for 1 h, yielding maximum efficacy. Subsequently, in the second step, the optimal conditions for cobalt leaching from the alkali-treated residue were established as follows: 2.0 M H₂SO₄, 25 g/L pulp density, and 75 °C temperature for 30 min. Downstream processing of the obtained metal ions in solutions was also easier, as the only impurity of dicobaltite ions with the Na₂WO₄ solution was precipitated as Co(OH)₃ under atmospheric O₂; meanwhile, the CoSO₄ solution obtained through the second step of processing can be treated via electrolysis to recover the metallic cobalt. The present process is simpler in operation, and the efficient use of eco-friendly lixiviants eliminates the previously reported disadvantage.     

Molybdenum and Phosphorous Dual Doping in Cobalt Monolayer Interfacial Assembled Cobalt Nanowires for Efficient Overall Water Splitting

The necessity for better water splitting requires speedy development of efficient catalysts with high activity, long‐term stability, and cost effectiveness. In this work, a bifunctional catalyst originating from the interfacial assembly of a thin Mo,P‐codoped Co layer (≈50 nm) shelled Co nanowire (Co‐Mo‐P/CoNWs) network is fabricated via a facile approach. The catalyst exhibits low overpotentials of 0.08 and 0.27 V to reach a current response of 20 mA cm^?2 for the hydrogen evolution reaction and oxygen evolution reaction, respectively, together with long‐term stability in 1.0 m KOH medium. The outstanding performance is further demonstrated by a Co‐Mo‐P/CoNWs‐based electrolyzer, which enables a cell voltage of only 1.495 V to reach 10 mA cm^?2, superior to one derived from commercial (Pt/C + RuO₂/C) as well as to various reports recently published elsewhere. It is recognized that the formation of multiactive centers together with the increased active site number caused by Mo and P dual doping synergistically promote both hydrogen and oxygen evolution performance. Such a hybrid material opens a new approach for developing efficient and cost‐effective catalysts for water splitting application.     

On Construction and Evaluation of Analogical Arguments for Persuasive Reasoning

ABSTRACT

Analogical reasoning is a complex process based on a comparison between two pairs of concepts or states of affairs (aka. the source and the target) for characterizing certain features from one to another. Arguments which employ this process to support their claims are called analogical arguments. Our goals are to study the structure and the computation for their defeasibility in light of the argumentation theory. Our proposed assumption-based argumentation with predicate similarity ABA^(p) framework can be seen as an extension of assumption-based argumentation framework (ABA), in which not only assumptions can be used but also similarity of predicates is used to support a claim. ABA ^(p) labels each argument tree with an analogical degree and different ways to aggregate numerical values are studied toward gullible/skeptical characteristics in agent reasoning. The acceptability of analogical arguments is evaluated w.r.t. the semantics of abstract argumentation. Finally, we demonstrate that ABA ^(p) captures the argumentation scheme for argument from analogy and provides an explanation when it is used for persuasion.     

A flexible cluster-oriented alternative clustering algorithm for choosing from the Pareto front of solutions

Supervised alternative clustering is the problem of finding a set of clusterings which are of high quality and different from a given negative clustering. The task is therefore a clear multi-objective optimization problem. Optimizing two conflicting objectives at the same time requires dealing with trade-offs. Most approaches in the literature optimize these objectives sequentially (one objective after another one) or indirectly (by some heuristic combination of the objectives). Solving a multi-objective optimization problem in these ways can result in solutions which are dominated, and not Pareto-optimal. We develop a direct algorithm, called COGNAC, which fully acknowledges the multiple objectives, optimizes them directly and simultaneously, and produces solutions approximating the Pareto front. COGNAC performs the recombination operator at the cluster level instead of at the object level, as in the traditional genetic algorithms. It can accept arbitrary clustering quality and dissimilarity objectives and provides solutions dominating those obtained by other state-of-the-art algorithms. Based on COGNAC, we propose another algorithm called SGAC for the sequential generation of alternative clusterings where each newly found alternative clustering is guaranteed to be different from all previous ones. The experimental results on widely used benchmarks demonstrate the advantages of our approach.

     

Component-based design for SCADA architecture

Supervisory control and data acquisition (SCADA) software which is suitable to distributed control systems is a demand for system developers because the characteristics of existing SCADA software packages are hard to satisfy the requirements of distributed systems. For the strengths of component-oriented techniques, this paper proposes a component-oriented architecture of SCADA software to satisfy the demand of distributed control systems. Design pattern and OPC (OLE for Process Control) technology are also used to make the openness for the architecture.     

Détecteurs HgCdTe pour télécommunication par fibres optiques

This paper deal with the studies and manufacture of HgCdTe detectors for fibre optics telecommunications, operating at 1,3 μm and 1,55 μm either with the Pin structure or with the avalanche mode. Electronic properties of the HgCdTe alloy with the appropriate composition range value, crystal growth methods, means of characterization of the materiel and process technology are described. Performances of the different types of diodes are reported, together with reliability tests, applications and prospects.     

Effective Light Directed Assembly of Building Blocks with Microscale Control

Light‐directed forces have been widely used to pattern micro/nanoscale objects with precise control, forming functional assemblies. However, a substantial laser intensity is required to generate sufficient optical gradient forces to move a small object in a certain direction, causing limited throughput for applications. A high‐throughput light‐directed assembly is demonstrated as a printing technology by introducing gold nanorods to induce thermal convection flows that move microparticles (diameter = 40 µm to several hundreds of micrometers) to specific light‐guided locations, forming desired patterns. With the advantage of effective light‐directed assembly, the microfluidic‐fabricated monodispersed biocompatible microparticles are used as building blocks to construct a structured assembly (≈10 cm scale) in ≈2 min. The control with microscale precision is approached by changing the size of the laser light spot. After crosslinking assembly of building blocks, a novel soft material with wanted pattern is approached. To demonstrate its application, the mesenchymal stem‐cell‐seeded hydrogel microparticles are prepared as functional building blocks to construct scaffold‐free tissues with desired structures. This light‐directed fabrication method can be applied to integrate different building units, enabling the bottom‐up formation of materials with precise control over their internal structure for bioprinting, tissue engineering, and advanced manufacturing.     

Interval spectral stochastic finite element analysis of structures with aggregation of random field and bounded parameters

This paper presents the study on non‐deterministic problems of structures with a mixture of random field and interval material properties under uncertain‐but‐bounded forces. Probabilistic framework is extended to handle the mixed uncertainties from structural parameters and loads by incorporating interval algorithms into spectral stochastic finite element method. Random interval formulations are developed based on K–L expansion and polynomial chaos accommodating the random field Young's modulus, interval Poisson's ratios and bounded applied forces. Numerical characteristics including mean value and standard deviation of the interval random structural responses are consequently obtained as intervals rather than deterministic values. The randomised low‐discrepancy sequences initialized particles and high‐order nonlinear inertia weight with multi‐dimensional parameters are employed to determine the change ranges of statistical moments of the random interval structural responses. The bounded probability density and cumulative distribution of the interval random response are then visualised. The feasibility, efficiency and usefulness of the proposed interval spectral stochastic finite element method are illustrated by three numerical examples. Copyright © 2016 John Wiley & Sons, Ltd.