Fuzzy minimum weight edge covering problem

Minimum weight edge covering problem, known as a classic problem in graph theory, is employed in many scientific and engineering applications. In the applications, the weight may denote cost, time, or opponent’s payoff, which can be vague in practice. This paper considers the edge covering problem under fuzzy environment, and formulates three models which are expected minimum weight edge cover model, α-minimum weight edge cover model, and the most minimum weight edge cover model. As an extension for the models, we respectively introduce the crisp equivalent of each model in the case that the weights are independent trapezoidal fuzzy variables. Due to the complexity of the problem, a hybrid intelligent algorithm is employed to solve the models, which can deal with the problem with any type of fuzzy weights. At last, some numerical experiments are given to show the application of the models and the robustness of the algorithm.     

Automated chemiluminescent dual-analyte immunoassay based on resolved immunosensing channels

A novel system of series-wound immunosensing channels (SWIC) was proposed for automated chemiluminescent (CL) dual-analyte immunoassay by immobilizing respectively different capture antibodies on the inner walls of series-wound glass channels. This system could use a single enzyme as label to perform multiplex immunoassay in one fluid way. Using α-fetoprotein (AFP) and carcinoembryonic antigen (CEA) as model analytes, the mixture including AFP, horseradish peroxidase (HRP)-labeled anti-AFP antibody, CEA and HRP-labeled anti-CEA antibody was introduced into the SWIC for carrying out the on-line incubation. Upon injection of CL substrate the CL signals from the two immunosensing channels were conveniently resolved and near-simultaneously collected with the aid of optical shutter. AFP and CEA could be rapidly assayed in the ranges of 1.0-100 and 1.0-80 ng/ml with detection limits of 0.41 and 0.39 ng/ml, respectively. The assay results of clinical serum samples were in an acceptable agreement with the reference values. This designed flow-through immunosensing system based on SWIC provided an automated, reusable, simple, sensitive and low-cost approach for multianalyte immunoassay.     

Shape‐Selective Alkylation of Naphthalene over Zeolites: Steric Interaction of Reagents with Zeolites

Steric interaction of reagents with zeolites was studied in isopropylation, sec‐butylation, and tert‐butylation of naphthalene (NP) over several large‐pore zeolites to elucidate the mechanism of selective catalysis. Selectivities for dialkylnaphthalene (DAN) isomers were influenced by the type of zeolite and bulkiness of alkylating agent. Selective formation of β,β‐ and 2,6‐diisopropylnaphthalene (DIPN) occurred only over H‐mordenite (MOR) in the isopropylation of NP using propene; bulky transition states of α,α‐ and α,β‐DIPN are excluded because of steric restriction by the channels, resulting in selective formation of β,β‐ and 2,6‐DIPN. However, low selectivities for β,β‐ and 2,6‐DIPN were observed over the zeolites, SSZ‐24 (AFI), SSZ‐55 (ATS), and SSZ‐42 (IFR) with 12‐membered‐ring (12‐MR) pore entrances of one‐dimensional channels, CIT‐5 (CFI), UTD‐1 (DON), and SSZ‐53 (SFH) with 14‐membered‐ring (14‐MR) pore entrances of one‐dimensional channels, and Y‐zeolite (FAU), zeolite β (BEA), and CIT‐1 (CON) with 12‐MR pore entrances of three‐dimensional channels, because their channels are too large for the exclusion of bulky isomers. Catalysis over these zeolites occurs under kinetic and/or thermodynamic control, resulting in predominant formation of α,α‐ and α,β‐DIPN at lower temperatures and an increase of the stable isomer β,β‐DIPN at higher temperatures. The selectivities for β,β‐ and 2,6‐DAN were enhanced with the increase in bulkiness of alkylating agents: 1‐butene for sec‐butylation and 2‐methylpropene for tert‐butylation. In particular, β,β‐di‐tert‐butylnaphthalene (DTBN) was selectively formed in the tert‐butylation. The selectivities for β,β‐ and 2,6‐DAN were enhanced even in large channels: the transition states of the least bulky isomers only fit the channels because other bulky isomers are excluded by steric restriction of the channels. However, tert‐butylation over FAU, BEA, and CON had selectivities for 2,6‐DTBN of around 50–60%, although selectivities for β,β‐DTBN were almost 100% selectivity; these zeolites can hardly recognize the differences between 2,6‐ and 2,7‐DTBN. The results indicate that the fitting of the least bulky isomers to zeolite channels, leading to the exclusion of other bulky isomers, is essential for highly shape‐selective catalysis.     

The analysis of the error statistics in a 5 × 40 Gbit/s fibre link with hybrid amplification

We quantify the error statistics and patterning effects in a 5 × 40 Gbit/s WDM RZ-OOK SMF/DCF fibre link using hybrid Raman/EDFA amplification. By extensive use of a numerical model, we determine how the error statistics change with the transmission distance. This knowledge is used as a basis for a constrained coding technique in order to improve the transmission error rate. We propose an adaptive constrained code for mitigation of the patterning effects and demonstrate that this approach can substantially reduce the bit error rate (BER) even for very large values of the channel BER (BER > 10^− 1). The proposed technique can be used in combination with forward error correction schemes (FEC) to extend the range of channel BERs that an FEC scheme is effective over.     

Partially coherent optical processor for enhancement of partial second order derivatives of an image: Analysis and implementation

We present an optical processor capable to perform partial second derivatives of an image working with partially coherent illumination. The proposed system utilizes a liquid crystal display, onto which images to be derived are displayed. The method is based on the capacity of these devices to generate simultaneously a contrast reverted replica of the image displayed on it. A positive replica of original image is obtained when the LCD is between crossed polarizers, while the negative one is obtained with the LCD is between parallel polarizers. Since the LCD is a diffraction element, both polarizer arrangements may be simultaneously implemented, for example, in a 4f optical processor using polarization filtering of the different diffraction orders. When three images (two replicas of original image displaced in opposite direction and the other one with contrast reverted and centered at the origin.) are imagined across a slightly defocused plane, one obtains an image with enhanced second derivatives in a given direction. No other incoherent (or partially coherent) optical system is presently known which can perform partial second-order derivatives of an image. Experimental results obtained are presented.     

Wavelet-based edge correlation incorporated iterative reconstruction for undersampled MRI

Undersampling k-space is an effective way to decrease acquisition time for MRI. However, aliasing artifacts introduced by undersampling may blur the edges of magnetic resonance images, which often contain important information for clinical diagnosis. Moreover, k-space data is often contaminated by the noise signals of unknown intensity. To better preserve the edge features while suppressing the aliasing artifacts and noises, we present a new wavelet-based algorithm for undersampled MRI reconstruction. The algorithm solves the image reconstruction as a standard optimization problem including a ?₂ data fidelity term and ?₁ sparsity regularization term. Rather than manually setting the regularization parameter for the ?₁ term, which is directly related to the threshold, an automatic estimated threshold adaptive to noise intensity is introduced in our proposed algorithm. In addition, a prior matrix based on edge correlation in wavelet domain is incorporated into the regularization term. Compared with nonlinear conjugate gradient descent algorithm, iterative shrinkage/thresholding algorithm, fast iterative soft-thresholding algorithm and the iterative thresholding algorithm using exponentially decreasing threshold, the proposed algorithm yields reconstructions with better edge recovery and noise suppression.     

An effusion-evaporation model for image edge detection

A novel quasi-physical edge detection model is presented. The model, referred to as the effusion-evaporation model (EEM), is inspired by the natural phenomenon that the water effusing from the ground evaporates in the sunshine and leaves a wire like water stain on the ground surface, which reflects the physiognomy of the terrain. Based on the simulation of water effusing and evaporating, an EEM regards the complement of gradient magnitude image as a three-dimensional terrain, and the concave regions, which contain the residual water in the evolution final state, are used to determine the edges. Subjective and objective comparisons are performed on the proposed algorithm and two conventional edge detectors, namely Canny and LoG. The comparison results show that the proposed method outperforms Canny and LoG detectors for the real images and the standard test images with Gaussian noise.