Showing papers by "Dalian University of Technology published in 2005"

Green supply chain management in China: pressures, practices and performance

Abstract: Purpose – Green supply chain management (GSCM) has emerged as a key approach for enterprises seeking to become environmentally sustainable. This paper aims to evaluate and describe GSCM drivers, practices and performance among various Chinese manufacturing organizations.Design/methodology/approach – Based on a literature review, four propositions are put forward. An empirical study using survey research was completed. The survey questionnaire was designed with 54 items using literature and industry expert input. An exploratory factor analysis was conducted to derive groupings of GSCM pressures, practice and performance from the survey data which included 314 responses. A categorical and descriptive nature of the results is then presented with an evaluation and comparative analysis with previous research findings.Findings – Chinese enterprises have increased their environmental awareness due to regulatory, competitive, and marketing pressures and drivers. However, this awareness has not been translated int...

Fabrication of superhydrophobic surfaces by dislocation-selective chemical etching on aluminum, copper, and zinc substrates.

Abstract: A surface roughening method by simple chemical etching was developed for the fabrication of superhydrophobic surfaces on three polycrystalline metals, namely aluminum, copper, and zinc. The key to the etching technique was the use of a dislocation etchant that preferentially dissolves the dislocation sites in the grains. The etched metallic surfaces, when hydrophobized with fluoroalkylsilane, exhibited superhydrophobic properties with water contact angles of larger than 150°, as well as roll-off angles of less than 10° for 8-μL drops. Also, the dislocation etching concept introduced here may be helpful in the fabrication of superhydrophobic surfaces on other polycrystalline substrates.

Heptamethine cyanine dyes with a large stokes shift and strong fluorescence: a paradigm for excited-state intramolecular charge transfer.

Abstract: New heptamethine cyanine dyes with an alkylamino group at the central position were found to exhibit a large Stokes shift (>140 nm) and strong fluorescence. They were suggested to be a new paradigm for excited-state intramolecular charge transfer (ICT). The configuration change of the bridgehead amine accompanying ICT was investigated in different viscosity and pH media.

Colorimetric and ratiometric fluorescence sensing of fluoride: tuning selectivity in proton transfer.

Abstract: Phenyl-1H-anthra[1,2-d]imidazole-6,11-dione (1) and its derivatives (2 and 3) have been investigated as new colorimetric and ratiometric fluorescent chemosensors for fluoride. Acute spectral responses of 1 and 3 to fluoride in acetonitrile have been observed: an approximately 100 nm red shift in absorption and fluorescence emission and a very large ratiometric fluorescent response (Rmax/Rmin is 88 for sensor 1 and 548 for sensor 3). From the changes in the absorption, fluorescence, and 1H NMR titration spectra, proton-transfer mechanisms have been deduced. In ground states, a two-step process has been observed: first, the formation of the sensor-fluoride hydrogen-bond complex [LH···F]- and then the fluoride-induced deprotonation of the complex to form L- and FHF-. In excited states, the excited-state intermolecular proton-transfer made a contribution to the deprotonation. The selectivity for F- can be tuned by electron push−pull properties of the substituents on the phenyl para position of the sensors. ...

Preparation of titania nanotubes and their environmental applications as electrode.

Abstract: Titanium oxide nanotubes were successfully grown from a titanium plate by direct anodic oxidation with 0.2 wt % hydrofluoric acid being the supporting electrolyte. These nanotubes are of uniform size and are well-aligned into high-density arrays. They look like honeywell with the structure similar to that of porous alumina obtained by the same technique. TiO2 anatase phase was identified by X-ray diffraction. Significant blue-shift in the spectrum of UV−vis absorption was observed. The mechanism of the novel, simple, and direct growth of the nanotubes was postulated. To investigate their potentials in environmental applications, degradation of pentachlorophenol (PCP) in aqueous solution was carried out using photoelectrocatalytic (PEC) processes, comparing with electrochemical process (EP) and photocatalytic (PC). A significant photoelectrochemical synergetic effect was observed. The kinetic constant of PEC degradation of PCP using TiO2 nanotubes electrode was 86.5% higher than that using TiO2 film electr...

Delay-dependent exponential stability of cellular neural networks with time-varying delays

Abstract: The global exponential stability of cellular neural networks (CNNs) with time-varying delays is analyzed. Two new sufficient conditions ensuring global exponential stability for delayed CNNs are obtained. The conditions presented here are related to the size of delay. The stability results improve the earlier publications. Two examples are given to demonstrate the effectiveness of the obtained results.

Design of multimaterial compliant mechanisms using level-set methods

Abstract: A monolithic compliant mechanism transmits applied forces from specified input ports to output ports by elastic deformation of its comprising materials, fulfilling required functions analogous to a rigid-body mechanism. In this paper, we propose a level-set method for designing monolithic compliant mechanisms made of multiple materials as an optimization of continuum heterogeneous structures. Central to the method is a multiphase level-set model that precisely specifies the distinct material regions and their sharp interfaces as well as the geometric boundary of the structure. Combined with the classical shape derivatives, the level-set method yields an Eulerian computational system of geometric partial differential equations, capable of performing topological changes and capturing geometric evolutions at the interface and the boundary. The proposed method is demonstrated for single-input and single-output mechanisms and illustrated with several two-dimensional examples of synthetics of multimaterial mechanisms of force inverters and gripping and clamping devices. An analysis on the formation of de facto hinges is presented based on the shape gradient information. A scheme to ensure a well-connected topology of the mechanism during the process of optimization is also presented.

Crossings and Nestings of Matchings and Partitions

Abstract: We present results on the enumeration of crossings and nestings for matchings and set partitions. Using a bijection between partitions and vacillating tableaux, we show that if we fix the sets of minimal block elements and maximal block elements, the crossing number and the nesting number of partitions have a symmetric joint distribution. It follows that the crossing numbers and the nesting numbers are distributed symmetrically over all partitions of $[n]$, as well as over all matchings on $[2n]$. As a corollary, the number of $k$-noncrossing partitions is equal to the number of $k$-nonnesting partitions. The same is also true for matchings. An application is given to the enumeration of matchings with no $k$-crossing (or with no $k$-nesting).

Boron dipyrromethene fluorophore based fluorescence sensor for the selective imaging of Zn(II) in living cells

Abstract: A simple PET fluorescence sensor (BDA) for Zn2+ that utilizes 1,3,5,7-tetramethyl-boron dipyrromethene as a reporting group and di(2-picolyl)amine as a chelator for Zn2+ has been synthesized and characterized. BDA has an excitation (491 nm) and emission wavelength (509 nm) in the visible range. The fluorescence quantum yields of the zinc-free and zinc-bound states of BDA are 0.077 and 0.857, respectively. With a low pKa of 2.1 ± 0.1, BDA has the advantage of less sensitivity to pH than fluorescein-based Zn2+ sensors, and the fluorescence emission of zinc-binding is pH-independent in the range of pH 3–10. Under physiological conditions, metal ions such as Na+, K+, Ca2+, Mg2+, Mn2+ and Fe2+ have little interference. The apparent dissociation constant (Kd) is 1.0 ± 0.1 nM. Using fluorescence microscopy, the sensor is shown to be capable of imaging intracellular Zn2+ changes.

Cooperative co-evolutionary differential evolution for function optimization

Abstract: The differential evolution (DE) is a stochastic, population-based, and relatively unknown evolutionary algorithm for global optimization that has recently been successfully applied to many optimization problems. This paper presents a new variation on the DE algorithm, called the cooperative co-evolutionary differential evolution (CCDE). CCDE adopts the cooperative co-evolutionary architecture, which was proposed by Potter and had been successfully applied to genetic algorithm, to improve significantly the performance of the DE. Such improvement is achieved by partitioning a high-dimensional search space by splitting the solution vectors of DE into smaller vectors, then using multiple cooperating subpopulations (or smaller vectors) to co-evolve subcomponents of a solution. Applying the new DE algorithm to on 11 benchmark functions, we show that CCDE has a marked improvement in performance over the traditional DE and cooperative co-evolutionary genetic algorithm (CCGA).

Further improved F-expansion method and new exact solutions of Konopelchenko–Dubrovsky equation

Abstract: In this paper, with the aid of the symbolic computation we improve the extended F-expansion method in [Chaos, Solitons & Fractals 2004; 22:111] and propose the further improved F-expansion method Using this method, we have gotten many new exact solutions which we have never seen before within our knowledge of the (2 + 1)-dimensional Konopelchenko–Dubrovsky equation In addition,the solutions we get are more general than the solutions that the extended F-expansion method getsThe solutions we get include Jacobi elliptic function solutions, soliton-like solutions, trigonometric function solutions and so on Our method can also apply to other partial differential equations and can also get many new exact solutions

Extended Jacobi elliptic function rational expansion method and abundant families of Jacobi elliptic function solutions to (1 + 1)-dimensional dispersive long wave equation

Abstract: Our Jacobi elliptic function rational expansion method is extended to be a more powerful method, called the extended Jacobi elliptic function rational expansion method, by using more general ansatz. The (1 + 1)-dimensional dispersive long wave equation is chosen to illustrate the approach. As a consequence, we can successfully obtain the solutions found by most existing Jacobi elliptic function methods and find other new and more general solutions at the same time. When the modulus m → 1, these doubly periodic solutions degenerate as soliton solutions. The method can be also applied to other nonlinear differential equations.

Influence of Tertiary Phosphanes on the Coordination Configurations and Electrochemical Properties of Iron Hydrogenase Model Complexes: Crystal Structures of [(μ‐S2C3H6)Fe2(CO)6–nLn] (L = PMe2Ph, n = 1, 2; PPh3, P(OEt)3, n = 1)

Abstract: A series of mono- and disubstituted diiron complexes [(μ-pdt)Fe2(CO)5L] [pdt = 1,3-propanedithiolato; L = PMe3 (2), PMe2Ph (3PPh3 (4), P(OEt)3 (5)] and [(μ-pdt)Fe2(CO)4L2] [L = PMe2Ph (6), PPh3 (7), P(OEt)3 (8)] were prepared as Fe-only hydrogenase-active-site models by controllable CO displacement of [(μ-pdt)Fe2(CO)6] by tertiary phosphanes. The coordination configurations of 3–6 were characterized by X-ray crystallography. Disubstituted diiron complex 6 features an apical/apical coordination mode, instead of the typical transoid basal/basal configuration. The electrochemistry of 2–6 and 8 was studied by cyclic voltammetry to evaluate the effects of different tertiary phosphane ligands on the redox properties of the iron atoms of model complexes. (© Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2005)

Application of the empirical mode decomposition to the analysis of esophageal manometric data in gastroesophageal reflux disease

Abstract: The Empirical Mode Decomposition (EMD) is a general signal processing method for analyzing nonlinear and nonstationary time series. The central idea of EMD is to decompose a time series into a finite and often small number of intrinsic mode functions (IMFs). An IMF is defined as any function having the number of extrema and the number of zero-crossings equal (or differing at most by one), and also having symmetric envelopes defined by the local minima, and maxima respectively. The decomposition procedure is adaptive, data-driven, therefore, highly efficient. In this contribution, we applied the idea of EMD to develop strategies to automatically identify the relevant IMFs that contribute to the slow-varying trend in the data, and presented its application on the analysis of esophageal manometric time series in gastroesophageal reflux disease. The results from both extensive simulations and real data show that the EMD may prove to be a vital technique for the analysis of esophageal manometric data.

Long-Term prediction of discharges in manwan reservoir using artificial neural network models

Abstract: Several artificial neural network (ANN) models with a feed-forward, back-propagation network structure and various training algorithms, are developed to forecast daily and monthly river flow discharges in Manwan Reservoir. In order to test the applicability of these models, they are compared with a conventional time series flow prediction model. Results indicate that the ANN models provide better accuracy in forecasting river flow than does the auto-regression time series model. In particular, the scaled conjugate gradient algorithm furnishes the highest correlation coefficient and the smallest root mean square error. This ANN model is finally employed in the advanced water resource project of Yunnan Power Group.

Deterministic convergence of an online gradient method for BP neural networks

Abstract: Online gradient methods are widely used for training feedforward neural networks. We prove in this paper a convergence theorem for an online gradient method with variable step size for backward propagation (BP) neural networks with a hidden layer. Unlike most of the convergence results that are of probabilistic and nonmonotone nature, the convergence result that we establish here has a deterministic and monotone nature.

Flow-shop scheduling with a learning effect

Abstract: The paper is devoted to some flow-shop scheduling problems with a learning effect. The objective is to minimize one of the two regular performance criteria, namely, makespan and total flowtime. A heuristic algorithm with worst-case bound m for each criteria is given, where m is the number of machines. Furthermore, a polynomial algorithm is proposed for both of the special cases: identical processing time on each machine and an increasing series of dominating machines. An example is also constructed to show that the classical Johnson's rule is not the optimal solution for the two-machine flow-shop scheduling to minimize makespan with a learning effect. Some extensions of the problem are also shown.

Improved genetic algorithm for design optimization of truss structures with sizing, shape and topology variables

Abstract: This paper presents an improved genetic algorithm (GA) to minimize weight of truss with sizing, shape and topology variables. Because of the nature of discrete and continuous variables, mixed coding schemes are proposed, including binary and float coding, integer and float coding. Surrogate function is applied to unify the constraints into single one; moreover surrogate reproduction is developed to select good individuals to mating pool on the basis of constraint and fitness values, which completely considers the character of constrained optimization. This paper proposes a new strategy of creating next population by competing between parent and offspring population based on constraint and fitness values; so that lifetime of excellent gene is prolonged. Because the initial population is created randomly and three operators of GA are also indeterminable, it is necessary to check whether the structural topology is desirable. An improved restart operator is proposed to introduce new gene and explore new space, so that the reliability of GA is enhanced. Selected examples are solved; the improved numerical results demonstrate that the enhanced GA scheme is feasible and effective. Copyright © 2005 John Wiley & Sons, Ltd.

Novel self-assembled MgO nanosheet and its precursors.

Abstract: A novel self-assembled microstructure, nestlike Mg(5)(CO(3))(4)(OH)(2).4H(2)O spheres, is formed by a self-assembly of nanosheets in the hydrothermal process. MgO with the similar morphology can be obtained by calcination of nestlike Mg(5)(CO(3))(4)(OH)(2).4H(2)O. MgO precursors with a uniform, ellipsoid-shaped, and smooth surface or flowerlike architecture, built by individual thin sheets, can be well-obtained by carefully controlling pH values of the initial reaction solution. The nestlike MgO exhibits a unique geometrical shape; its surface is composed of uniform MgO nanosheets. The unique MgO microstructure with high surface areas may possess promising applications as the sorbent for chemisorption and destructive adsorption of various pollutants.

A level-set based variational method for design and optimization of heterogeneous objects

Abstract: A heterogeneous object is referred to as a solid object made of different constituent materials. The object is of a finite collection of regions of a set of prescribed material classes of continuously varying material properties. These properties have a discontinuous change across the interface of the material regions. In this paper, we propose a level-set based variational approach for the design of this class of heterogeneous objects. Central to the approach is a variational framework for a well-posed formulation of the design problem. In particular, we adapt the Mumford–Shah model which specifies that any point of the object belongs to either of two types: inside a material region of a well-defined gradient or on the boundary edges and surfaces of discontinuities. Furthermore, the set of discontinuities is represented implicitly, using a multi-phase level set model. This level-set based variational approach yields a computational system of coupled geometric evolution and diffusion partial differential equations. Promising features of the proposed method include strong regularity in the problem formulation and inherent capabilities of geometric and material modeling, yielding a common framework for optimization of the heterogeneous objects that incorporates dimension, shape, topology, and material properties. The proposed method is illustrated with several 2D examples of optimal design of multi-material structures and materials.

Auto cropping for digital photographs

Abstract: In this paper, we propose an effective approach to the nearly untouched problem, still photograph auto cropping, which is one of the important features to automatically enhance photographs. To obtain an optimal result, we first formulate auto cropping as an optimization problem by defining an energy function, which consists of three sub models: composition sub model, conservative sub model, and penalty sub model. Then, particle swarm optimization (PSO) is employed to obtain the optimal solution by maximizing the objective function. Experimental results and user studies over hundreds of photographs show that the proposed approach is effective and accurate in most cases, and can be used in many practical multimedia applications.