Alternate Method for the Synthesis of Six-Membered Carbocycles with Five Stereocenters: 1,2,3,4,6-Pentasubstituted-4-hydroxy-cyclohexanes

A series of novel 1,2,3,4,6-pentasubstituted-4-hydroxy-cyclohexanes (3a–u) were synthesized from the reaction of aromatic ketones with aromatic aldehydes under mild reaction conditions in good yields. The stereochemistry of the synthesized compounds was established using 1D and 2D-NMR spectra.     

Surface characterization and radical decay studies of oxygen plasma‐treated PMMA films

Polymethylmethacrylate (PMMA) films were modified by RF oxygen plasma with various powers applied for different periods, and the effects of these parameters on the surface properties such as hydrophilicity, surface free energy (SFE), chemistry, and topography were investigated by water contact angle, goniometer, X‐ray photoelectron spectroscopy (XPS), and atomic force microscopy, and the types of the created free radicals and their decay were detected by electron spin resonance spectroscopy (ESR). SFE and contact angle results varied depending on the plasma parameters. Oxygen plasma treatment (100 W–30 min) enhanced the hydrophilicity of PMMA surface as shown by decreasing the water contact angle from 70° to 26°. XPS analysis showed the change in the amounts of the present functionalities as well as formation of new groups as free carbonyl and carbonate groups. The roughness of the surface increased considerably from ~2 nm to ~75 nm after 100 W–30 min oxygen plasma treatment. ESR analysis indicated the introduction of peroxy radicals by oxygen plasma treatment, and the intensity of the radicals increased with increasing the applied power. Significant decrease in radical concentration was observed especially for the samples treated with higher powers when the samples were kept under the atmospheric conditions. As a conclusion, RF plasma, causes changes in the chemical and physical properties of the materials depending on the applied parameters, and can be used for the creation of specific groups or radicals to link or immobilize active molecules onto the surface of a material. Copyright © 2012 John Wiley & Sons, Ltd.     

Silver nanoparticle containing silk fibroin bionanotextiles

Development of new generation bionanotextiles is an important growing field, and they have found applications as wound dressings, bandages, tissue scaffolds, etc. In this study, silver nanoparticle (AgNP) containing silk-based bionanotextiles were fabricated by electrospinning, and processing parameters were optimized and discussed in detail. AgNPs were in situ synthesized within fibroin nanofibers by UV reduction of silver ions to metallic silver. The influence of post-treatments via methanol treatment and glutaraldehyde (GA) vapor exhibited changes in the secondary structure of silk. Methanol treatment increased the tensile properties of fibers due to supported crystalline silk structure, while GA vapor promoted amorphous secondary structure. AgNP containing silk fibroin bionanotextiles had strong antibacterial activity against gram-positive Staphylococcus aureus and gram-negative Pseudomonas aeruginosa.     

Alginate/Polyoxyethylene and Alginate/Gelatin Hydrogels: Preparation,Characterization, and Application in Tissue Engineering

Hydrogels are attractive biomaterials for three-dimensional cell culture and tissue engineering applications. The preparation of hydrogels using alginate and gelatin provides cross-linked hydrophilic polymers that can swell but do not dissolve in water. In this work, we first reinforced pure alginate by using polyoxyethylene as a supporting material. In an alginate/PEO sample that contains 20 % polyoxyethylene, we obtained a stable hydrogel for cell culture experiments. We also prepared a stable alginate/gelatin hydrogel by cross-linking a periodate-oxidized alginate with another functional component such as gelatin. The hydrogels were found to have a high fluid uptake. In this work, preparation, characterization, swelling, and surface properties of these scaffold materials were described. Lyophilized scaffolds obtained from hydrogels were used for cell viability experiments, and the results were presented in detail.     

Synthesis of new cyclotriphosphazene derivatives bearing Schiff bases and their thermal and absorbance properties

In this study, a series of cyclotriphosphazene derivatives containing a Schiff base (3a–3d) were synthesized by the reactions of hexachlorocyclotriphosphazene (1) with bis-aryl Schiff bases ( 2a – 2d ) having different terminal groups (H, F, Cl, and Br). The products ( 3a – 3d ) were characterized by elemental and mass analyses, FT-IR, and ¹ H, ¹³ C, and ³¹ P NMR spectroscopies. Furthermore, the structure of compound 3a was also determined by X-ray crystallography. The thermal behaviors and the spectral properties of the new cyclotriphosphazene compounds ( 3a – 3d ) were investigated and the results were compared in the series.     

New product launch decisions with robust optimization

We consider a problem where a company must decide the order in which to launch new products within a given time horizon and budget constraints, and where the parameters of the adoption rate of these new products are subject to uncertainty. This uncertainty can bring significant change to the optimal launch sequence. We present a robust optimization approach that incorporates such uncertainty on the Bass diffusion model for new products as well as on the price response function of partners that collaborate with the company in order to bring its products to market. The decision-maker optimizes his worst-case profit over an uncertainty set where nature chooses the time periods in which (integer) units of the budgets of uncertainty are used for worst impact. This leads to uncertainty sets with binary variables. We show that a conservative approximation of the robust problem can nonetheless be reformulated as a mixed integer linear programming problem, is therefore of the same structure as the deterministic problem and can be solved in a tractable manner. Finally, we illustrate our approach on numerical experiments. Our model also incorporates contracts with potential commercialization partners. The key output of our work is a sequence of product launch times that protects the decision-maker against parameter uncertainty for the adoption rates of the new products and the response of potential partners to partnership offers.     

Production systems with interruptions, arbitrary topology and finite buffers

We consider a production system with finite buffers and arbitrary topology where service time is subject to interruptions in one of three ways, viz. machine breakdown, machine vacations or Npolicy. We develop a unified approximation (analytical) methodology to calculate the throughput of the system using queueing networks together with decomposition, isolation and expansion techniques. The methodology is rigorously tested covering a large experimental region. Orthogonal arrays are used to design the experiments in order to keep the number of experiments manageable. The results obtained using the approximation methodology are compared to the simulation results. The ttests carried out to investigate the differences between the two results show that they are statistically insignificant. Finally, we test the methodology by applying it to several arbitrary topology networks. The results show that the performance of the approximation methodology is consistent, robust and produces excellent results in a variety of experimental conditions.     

The variational iteration method for solitary patterns solutions of gBBM equation

We consider solitary patterns solutions of generalized Benjamin–Bona–Mahony equations (shortly gBBM). The variational iteration method (shortly VIM) is applied for the numerical solution subject to appropriate initial condition. The numerical solutions of our model equation are calculated in the form of convergence power series with easily computable components. The VIM performs extremely well in terms of accuracy, efficiently, simplicity, stability and reliability.     

A New Benzothiazin-functionalized Calix[4]arene-based Fluorescent Chemosensor for the Selective Detection of Co2+ Ion

Calixarenes, which have a great place in supramolecular chemistry, have become the most prominent macrocyclic compounds in synthetic organic chemistry due to their easy synthesis and functionalization. In this study, p-tert-butyl calix[4]arene dihydrazide derivative was synthesized and then reacted with 3-oxo-3,4-dihydro-2 H-benzo[b][1,4] thiazin-2-ylideneacetyl chloride to prepare new calixarene based chromophore compound 4. The structure of the synthesized compound was elucidated by spectroscopic methods such as ¹H NMR ¹³C NMR and FT-IR spectroscopy. Chromogenic and fluorescence properties of compound 4 were evaluated. It was observed from both studies that compound 4 was Co²⁺ selective and shows fluorescence Switched-off behavior. Stoichiometry, binding constant and the detection limit were calculated. The stoichiometry between compound 4 and Co²⁺ was found to be 1:1. The binding constant value (K) was calculated as 666.67 M^??1 using Benesi–Hildebrand equation, while the detection limit for Co²⁺ ion was calculated as 0.0465 µM.

     

Efficient adaptive regression spline algorithms based on mapping approach with a case study on finance

Multivariate adaptive regression splines (MARS) has become a popular data mining (DM) tool due to its flexible model building strategy for high dimensional data. Compared to well-known others, it performs better in many areas such as finance, informatics, technology and science. Many studies have been conducted on improving its performance. For this purpose, an alternative backward stepwise algorithm is proposed through Conic-MARS (CMARS) method which uses a penalized residual sum of squares for MARS as a Tikhonov regularization problem. Additionally, by modifying the forward step of MARS via mapping approach, a time efficient procedure has been introduced by S-FMARS. Inspiring from the advantages of MARS, CMARS and S-FMARS, two hybrid methods are proposed in this study, aiming to produce time efficient DM tools without degrading their performances especially for large datasets. The resulting methods, called SMARS and SCMARS, are tested in terms of several performance criteria such as accuracy, complexity, stability and robustness via simulated and real life datasets. As a DM application, the hybrid methods are also applied to an important field of finance for predicting interest rates offered by a Turkish bank to its customers. The results show that the proposed hybrid methods, being the most time efficient with competing performances, can be considered as powerful choices particularly for large datasets.