Design of a closed-loop supply chain (CLSC) model using an interactive fuzzy goal programming

A closed-loop supply chain (CLSC) network is composed of both forward and reverse flows. An essential issue to be considered in designing any supply chain network is determination of number and locations of facilities in each layer of the network. Such a problem is a challenging job, since it contains sub-problems which are proven to be nondeterministic polynomial time complete. This paper proposes a CLSC distribution network design problem in which reverse flows are imported into forward model proposed by Selim and Ozkarahan (Int J Adv Manuf Technol 36:401–418, 1). Such a model is considered assuming forward covering (model I) and backward covering (model II) objectives, and then results are compared against the model incorporating covering of both forward and backward networks (model III). Our aim is to accentuate on the role of considering backward parameters in design of a CLSC network and to show how results differ from considering sub-problems separately. To model and solve the problem, a fuzzy goal programming approach is developed for network design in an interactive manner between decision maker and the model. To validate the presented model and the proposed solution approach, a test problem is presented and comparison of results is made using this problem. The results show that the proposed model can solve the CLSC problems in a manageable time. Moreover, outputs of the three models differ significantly. Therefore, the role of incorporating backward flows into the network design problem has been shown using our experiments.     

Effect of clay dispersion on the cell structure of LDPE/clay nanocomposite foams

In this study, the effect of clay and its dispersion state on the cell morphology and foaming behavior of chemically crosslinked polyethylene (PE) foams were examined. In addition, the effect of foaming process on the clay morphology was also considered. It was shown that the morphology of the clay before the foaming process and its compatibility with PE matrix play a major role in determining the final foam properties. A PE‐g‐MA compatibilizer was used to increase the melt intercalation of PE onto the clay galleries and to improve clay dispersion in the PE matrix. The uniform dispersion of clay provided greater and well‐ dispersed nucleation sites. This led to smaller cell size, narrower cell size distribution, and higher cell density, and lower foam density. During the foaming process, intercalated clays were delaminated due to the rapid polymer melt expansion that inhibited gas release and increased foam expansion ratio. POLYM. COMPOS., 2011. © 2011 Society of Plastics Engineers     

Recursive evaluation of time convolution integrals in the spectral boundary integral method for mode III dynamic fracture problems

The shear crack, propagating spontaneously on a frictional interface, is a useful idealization of a natural earthquake. However, the corresponding boundary value problems are quite challenging in terms of required memory and processor power. While the huge computation amount is reduced by the spectral boundary integral method, the computation effort is still huge. In this paper, a recursive method for the evaluation of convolution integrals was tested in the spectral formulation of the boundary integral method applied to 2D anti-plane crack propagation problems. It is shown that analysis of a 2D anti-plane crack propagation problem involving N_t time steps, based on the recursive evaluation of convolution integrals, requires O(αN_t) computational resources for each Fourier mode (as opposed to O(N_t²) for a classical algorithm), where α is a constant depending on the implementation of the method with typical values much less than N_t. Therefore, this recursive scheme renders feasible investigation of long deformational processes involving large surfaces and long periods of time, while preserving accuracy. The computation methodology implemented here can be extended easily to 3D cases where it can be employed for the simulation of complex spontaneously fault rupture problems which carry a high computational cost.     

A predictive algorithm for multimedia data compression

In lossless image compression, many prediction methods are proposed so far to achieve better compression performance/complexity trade off. In this paper, we concentrate on some well-known and widely used low-complexity algorithms exploited in many modern compression systems, including MED, GAP, Graham, Ljpeg, DARC, and GBSW. This paper proposes a new gradient-based tracking and adapting technique that outperforms some existing methods. This paper aims to design an efficient highly adaptive predictor that can be incorporated in modeling step of image compression systems. This claim is proved by testing the proposed method upon a wide variety of images with different characteristics. Six special sets of images including face, sport, texture, sea, text, and medical constitute our dataset.     

Combining emerging patterns with random forest for complex activity recognition in smart homes

New healthcare technologies are emerging with the increasing age of the society, where the development of smart homes for monitoring the elders’ activities is in the center of them. Identifying the resident’s activities in an apartment is an important module in such systems. Dense sensing approach aims to embed sensors in the environment to report the detected events continuously. The events are segmented and analyzed via classifiers to identify the corresponding activity. Although several methods were introduced in recent years for detecting simple activities, the recognition of complex ones requires more effort. Due to the different time duration and event density of each activity, finding the best size of the segments is one of the challenges in detecting the activity. Also, using appropriate classifiers that are capable of detecting simple and interleaved activities is the other issue. In this paper, we devised a two-phase approach called CARER (Complex Activity Recognition using Emerging patterns and Random forest). In the first phase, the emerging patterns are mined, and various features of the activities are extracted to build a model using the Random Forest technique. In the second phase, the sequences of events are segmented dynamically by considering their recency and sensor correlation. Then, the segments are analyzed by the generated model from the previous phase to recognize both simple and complex activities. We examined the performance of the devised approach using the CASAS dataset. To do this, first we investigated several classifiers. The outcome showed that the combination of emerging patterns and the random forest provide a higher degree of accuracy. Then, we compared CARER with the static window approach, which used Hidden Markov Model. To have a fair comparison, we replaced the dynamic segmentation module of CARER with the static one. The results showed more than 12% improvement in f-measure. Finally, we compared our work with Dynamic sensor segmentation for real-time activity recognition, which used dynamic segmentation. The f-measure metric demonstrated up to 12.73% improvement.     

1-GHz fully pipelined 3.7-ns address access time 8 k×1024embedded synchronous DRAM macro

This embedded-DRAM macro is designed as a DRAM cache for a future gigahertz microprocessor system based on a logic-based DRAM technology. The most notable feature of this macro is its ability to run synchronously with a gigahertz CPU clock in a fully pipelined fashion. It is designed to operate with a 1-GHz clock signal at 85°C, nominal process parameters, and a 10% degraded V_DD. The design is fully pipelined and synchronous with 16 independent subarrays. With 1-kb wide I/0 and a 1-GHz clock, the maximum data rate becomes 1 Tb per second. The address access time is 3.7 ns, four cycles with a 1-GHz clock. The subarray cycle time is 12 ns     

Simple consequences of the finite time laplace transform analysis of the periodically reversed switched capacitors

The Finite Time Laplace Transform unifies the basis of periodically reverse switched capacitors and periodically switched capacitors. Several examples utilizing both of these switched capacitors are given. Both capacitors have additive semi-null functions which are removed by either a staircase input signal or a post-sampler. The impedance concept is retained and the simplified analysis is more readily accessible than the ubiquitous charge analysis in the literature. There is questionable substance to allegations of a time-variant nature to any switched capacitor.     

Investigation of copper plates as anode and TiO2/glycine/ZnFe2O4 stabilized on graphite as cathode for textile dyes degradation from aqueous solution under visible light

Journal of Applied Electrochemistry - This study aimed to degrade the two most commonly used dyes in textile industries, Acid Black 172 and Reactive Blue 19, in pollutant water via...     

Investigation of Structural Determinants for the Substrate Specificity in the Zinc‐Dependent Alcohol Dehydrogenase CPCR2 from Candida parapsilosis

Zinc‐dependent alcohol dehydrogenases (ADHs) are a class of enzymes applied in different biocatalytic processes ranging from lab to industrial scale. However, one drawback is the limited substrate range, necessitating a whole array of different ADHs for the relevant substrate classes. In this study, we investigated structural determinants of the substrate spectrum in the zinc‐dependent ADH carbonyl reductase 2 from Candida parapsilosis (CPCR2), combining methods of mutational analysis with in silico substrate docking. Assigned active site residues were genetically randomized, and the resulting mutant libraries were screened with a selection of challenging carbonyl substrates. Three variants (C57A, W116K, and L119M) with improved activities toward different substrates were detected at neighboring positions in the active site. Thus, all possible combinations of the mutations were generated and characterized for their substrate specificity, yielding several improved variants. The most interesting were a C57A variant, with a 27‐fold increase in specific activity for 4′‐acetamidoacetophenone, and the double mutant CPCR2 B16‐(C57A, L119M), with a 45‐fold improvement in the k_cat?K_M^?1 value. The obtained variants were further investigated by in silico docking experiments. The results indicate that the mentioned residues are structural determinants of the substrate specificity of CPCR2, being major players in the definition of the active site. Comparison of these results with closely related enzymes suggests that these might even be transferred to other ADHs.     

Hijacking Chemical Reactions of P450 Enzymes for Altered Chemical Reactions and Asymmetric Synthesis

Cytochrome P450s are heme-containing enzymes capable of the oxidative transformation of a wide range of organic substrates. A protein scaffold that coordinates the heme iron, and the catalytic pocket residues, together, determine the reaction selectivity and regio- and stereo-selectivity of the P450 enzymes. Different substrates also affect the properties of P450s by binding to its catalytic pocket. Modulating the redox potential of the heme by substituting iron-coordinating residues changes the chemical reaction, the type of cofactor requirement, and the stereoselectivity of P450s. Around hundreds of P450s are experimentally characterized, therefore, a mechanistic understanding of the factors affecting their catalysis is increasingly vital in the age of synthetic biology and biotechnology. Engineering P450s can enable them to catalyze a variety of chemical reactions viz. oxygenation, peroxygenation, cyclopropanation, epoxidation, nitration, etc., to synthesize high-value chiral organic molecules with exceptionally high stereo- and regioselectivity and catalytic efficiency. This review will focus on recent studies of the mechanistic understandings of the modulation of heme redox potential in the engineered P450 variants, and the effect of small decoy molecules, dual function small molecules, and substrate mimetics on the type of chemical reaction and the catalytic cycle of the P450 enzymes.