A Potent Mimetic of the Siglec-8 Ligand 6’-Sulfo-Sialyl Lewisx

Siglecs are members of the immunoglobulin gene family containing sialic acid binding N-terminal domains. Among them, Siglec-8 is expressed on various cell types of the immune system such as eosinophils, mast cells and weakly on basophils. Cross-linking of Siglec-8 with monoclonal antibodies triggers apoptosis in eosinophils and inhibits degranulation of mast cells, making Siglec-8 a promising target for the treatment of eosinophil- and mast cell-associated diseases such as asthma. The tetrasaccharide 6’-sulfo-sialyl Lewis^x has been identified as a specific Siglec-8 ligand in glycan array screening. Here, we describe an extended study enlightening the pharmacophores of 6’-sulfo-sialyl Lewis^x and the successful development of a high-affinity mimetic. Retaining the neuraminic acid core, the introduction of a carbocyclic mimetic of the Gal moiety and a sulfonamide substituent in the 9-position gave a 20-fold improved binding affinity. Finally, the residence time, which usually is the Achilles tendon of carbohydrate/lectin interactions, could be improved.     

Design,Facile Synthesis and Characterization of Porphyrin-Zirconium-Ferrite@SiO2 Core-Shell and Catalytic Application in Cyclohexane Oxidation

Silicon - In this study, a new magnetic ZrFe2O4@SiO2-TCPP nanocatalyst with high efficiency was used for the oxidation of cyclohexane to cyclohexanone (Ke) and cyclohexanol (Al). The mesoporous...     

TVD-MRDL: traffic violation detection system using MapReduce-based deep learning for large-scale data

Maintaining a fluid and safe traffic is a major challenge for human societies because of its social and economic impacts. Various technologies have considerably paved the way for the elimination of traffic problems and have been able to effectively detect drivers’ violations. However, the high volume of the real-time data collected from surveillance cameras and traffic sensors along with the data obtained from individuals have made the use of traditional methods ineffective. Therefore, using Hadoop for processing large-scale structured and unstructured data as well as multimedia data can be of great help. In this paper, the TVD-MRDL system based on the MapReduce techniques and deep learning was employed to discover effective solutions. The Distributed Deep Learning System was implemented to analyze traffic big data and to detect driver violations in Hadoop. The results indicated that more accurate monitoring automatically creates the power of deterrence and behavior change in drivers and it prevents drivers from committing unusual behaviors in society. So, if the offending driver is identified quickly after committing the violation and is punished with the appropriate punishment and dealt with decisively and without negligence, we will surely see a decrease in violations at the community level. Also, the efficiency of the TVD-MRDL performance increased by more than 75% as the number of data nodes increased.

     

A comprehensive decision making structure for partitioning of make-to-order, make-to-stock and hybrid products

Manufacturing systems produce their products by making use of three main strategies: make-to-order, make-to-stock and hybrid (combination of MTO and MTS strategies) systems. Hence, several products must be considered and partitioned in terms of many different conflicting criteria, leading to a large set of subjective or ambiguous data. Thus, an effective evaluation approach is essential to improve decision quality. In this paper a comprehensive decision, making structure is proposed to choose the proper strategy for producing the products. It consists of a novel hybrid methodology, which combines analytical hierarchy process (AHP) and technique for order performance by similarity to ideal solution (TOPSIS) for partitioning of products. In this study, the rating of each alternative regarding different criteria (throughout the TOPSIS technique) is described by means of linguistic variables. Furthermore, fuzzy AHP methodology is applied to determine the weights of evaluation criteria. At the end, the effectiveness of the proposed model is demonstrated through a case study.     

A Model for Identifying the Behavior of Alzheimer’s Disease Patients in Smart Homes

Wireless Personal Communications - In recent years, Smart Cities and Smart Homes have been studied as an important field of research. The design and construction of smart homes have flourished so...     

Determination of number of kanbans in a supply chain system via Memetic algorithm

In this research multi-stage supply chain system which is controlled by kanban system, is evaluated. In kanban system, decision making is based on determination of the number of kanbans as well as batch sizes. This paper attempts to model supply chain system with regard to costs under just-in-time (JIT) production philosophy. Since adopted model is of mixed integer non-linear programming (MINLP) type and solving it by exact algorithm such as branch and bound (B&B) takes a lot of time, a heuristic method via Memetic algorithm (MA) is presented. Some problems are solved by our proposed MA to illustrate its performance.     

Restoration of bilinearly distorted images. 3: Constrained least-squares method

A constrained least-squares solution based on a second difference smoothing measure is obtained for images which are distorted by a bilinear (quadratic and with nonzero memory) system in the presence of additive signal-independent noise. Results are applied to a partially coherent diffraction-limited imaging system. It is found that the optimum weight given to the smoothness factor is larger for a coherent (nonlinear) system than for an incoherent (linear) system. However, the restoration quality improves as the imaging system approaches incoherence.     

Solving a bi-objective cell formation problem with stochastic production quantities by a two-phase fuzzy linear programming approach

We propose a bi-objective cell formation problem with demand of products expressed in a number of probabilistic scenarios. To deal with the uncertain demand of products, a framework of two-stage stochastic programming model is presented. The proposed model considers minimizing the sum of the miscellaneous costs (machine constant cost, expected machine variable cost, cell fixed-charge cost, and expected intercell movement cost) and expected total cell loading variation. Because of conflicting objectives, we develop a two-phase fuzzy linear programming approach for solving bi-objective cell formation problem. To show the effectiveness of the proposed approach, numerical examples are solved and the results are compared with the two existing approaches in the literature. The computational results show that the proposed fuzzy method achieves lower objective functions as well as higher satisfaction degrees.     

Microstructural and microwave dielectric properties of LZT (Li2ZnTi3O8) ceramics sintered in presence of bismuth borate glass for LTCC applications

In the present research, the Li₂ZnTi₃O₈(LZT) ceramics were synthesized throughout solid-state ceramic processing, then mixed with bismuth borate (BiBO) glass prepared based on conventional melt quenching method. Wetting behavior of BiBO glass on the LZT ceramic substrate was monitored by hot stage microscopy. Afterward, dielectric LZT ceramics containing different amounts of BiBO glass (0.25–6 wt%) were sintered at various temperatures. X-ray diffraction and electron back scatter diffraction examinations revealed the presence of two crystalline phases of Li₂ZnTi₃O₈ and Bi₂Ti₂O₇. The maximum value of relative density (above 95%) was obtained in the case of specimens contained more than 5 wt% glass. The microwave dielectric properties of the finally sintered BiBO glass containing LZT ceramics were as follows: dielectric constant (ε_r) = 21.44–25.09, quality factor (Q × f) = 10839–54708 GHz and temperature coefficient of resonant frequency (τ_f) = (? 15.58) ? (? 12.86)ppm/°C.     

Preparation, Characterization and Photocatalytic Properties of Ba-Cd-Sr-Ti Doped Fe3O4 Nanohollow Spheres on Removal of Congo Red Under Visible-Light Irradiation

In this study, Ba-Cd-Sr-Ti doped Fe₃O₄ nanohollow spheres were successfully prepared via a simple solvothermal method. The crystal size, structure, morphology and elemental analysis of the as-prepared sample were investigated in detail by X-ray diffraction (XRD), FT-IR, scanning electron microscopy (SEM) and energy dispersive X-ray (EDX) spectroscopy, respectively. Magnetic hysteresis measurement was carried out on a vibrant sample magnetometer (VSM) showing the soft ferromagnetic property at room temperature. The synthesized nanohollow spheres were employed as a photocatalyst to study the photocatalytic degradation of dye contaminations. The UV-Vis results showed that the specimen could well catalyze the decolorizing of congo red (CR) solution and a removal efficiency of 99.5 % was obtained at pH 6. The optical characteristic of the products was studied by estimating the band-gap energy based on diffuse-reflectance spectroscopy (DRS) which represented the doped magnetite with semiconductor metals to be more prone in the visible region as compared to UV region. Some factors such as initial dye concentration, pH, and contact time influencing the decomposition of CR were evaluated.