Combination of MCDM and covering techniques in a hierarchical model for facility location: A case study

In this paper, locating some warehouses as distribution centers (DCs) in a real-world military logistics system will be investigated. There are two objectives: finding the least number of DCs and locating them in the best possible locations. The first objective implies the minimum cost of locating the facilities and the latter expresses the quality of the DCs locations, which is evaluated by studying the value of appropriate attributes affecting the quality of a location. Quality of a location depends on a number of attributes; so the value of each location is determined by using Multi Attribute Decision Making models, by considering the feasible alternatives, the related attributes and their weights according to decision maker’s (DM) point of view. Then, regarding the obtained values and the minimum number of DCs, the two objective functions are formed. Constraints imposed on these two objectives cover all centers, which must be supported by the DCs. Using Multiple Objective Decision Making techniques, the locations of DCs are determined. In the final phase, we use a simple set partitioning model to assign each supported center to only one of the located DCs.     

Computing topological indices of Sudoku graphs

In QSAR/QSPR study, physico-chemical properties and topological indices such as Randi?, atom-bond connectivity (ABC) and geometric-arithmetic (GA) index are used to predict the bioactivity of chemical compounds. A topological index is actually designed by transforming a chemical structure into a numeric number. These topological indices correlate certain physico-chemical properties like boiling point, stability, strain energy etc. of chemical compounds. Graph theory has found a considerable use in this area of research. The topological indices of certain interconnection networks were studied recently by Imran et al. (Appl Math Comput 244:936–951, 2014). In this paper, we extend this study to \(n\times n\) Sudoku graphs and derive analytical closed results of general Randi? index \(R_{\alpha }(G)\) for different values of “\(\alpha \)” for Sudoku (SK). We also compute the general Randi?, first Zagreb, ABC, GA, \(ABC_{4}\) and \(GA_{5}\) indices and give closed formulae of these indices for Sudoku graphs.     

Dispersive solid phase extraction of lead(II) using a silica nanoparticle-based ionic liquid ferrofluid

We demonstrate the application of an ionic liquid-based ferrofluid to the dispersive solid phase extraction of lead(II) using PAN as the chelator. The ionic liquid contains silica nanoparticles with a magnetic core as the dispersion medium, and its use results in improved stability of the colloidal dispersion and a complete extraction of lead(II) within a few seconds. In addition, there is no need for centrifugation. Specifically, the effect of different variables on the extraction of lead(II) was studied using an experimental design. Lead(II) was quantified by AAS. Under optimized conditions, the calibration graph for lead(II) is linear in the range from 5 to 372 μg L⁻¹, the relative standard deviation is 1.34 % (for n = 7), the limit of detection is 1.66 μg L⁻¹, and the enrichment factor is 200. The maximum adsorption capacity of sorbent was calculated to be 10.7 mg g⁻¹, and adsorption follows a Langmuir isotherm.

A schematic view of D-SPE experimental set up. We demonstrate the application of an ionic liquid-based ferrofluid to the dispersive solid phase extraction of lead(II) using PAN as the chelator. The ionic liquid contains silica nanoparticles with a magnetic core as the dispersion medium

     

RFID-generated traceability for contaminated product recall in perishable food supply networks

As perishable food supply networks become more complex, incidents of contamination in these supply networks have become fairly common. Added to this complexity is the fact that there have been long delays in identifying the contamination source in several such incidents. Even when the contamination source was identified, there have been cases where the ultimate destination of all contaminated products were not known with complete certainty due, in part, to dispersion in these supply networks. We study the recall dynamics in a three-stage perishable food supply network through three different visibility levels in the presence of contamination. Specifically, we consider allocation of liability among the different players in the perishable supply network based on the accuracy with which the contamination source is identified. We illustrate the significance of finer levels of granularity both upstream and downstream as well as determine appropriate visibility levels and recall policies.     

Extraction of antidepressant drugs in biological samples using alkanol‐based nano structured supramolecular solvent microextraction followed by gas chromatography with mass spectrometric analysis

In the present study, a supramolecular solvent was formed from reverse micelle aggregates of octanol. The proposed supramolecular solvent was used for rapid extraction of some antidepressants drugs including amitriptyline, imipramine, desipramine, maprotiline, sertraline, and doxepin from biological samples. Alkanol‐based supramolecular solvents have a unique array of physicochemical properties, making them a very attractive alternative to replace organic solvents in analytical extractions. The parameters affecting the extraction of target analytes (i.e., the volume of tetrahydrofuran and octanol as the major components comprising the supramolecular solvent, chain length of alkanols, sample solution pH, salt addition, and ultrasonic time) were investigated and optimized by factor by factor optimization method. Under the optimum conditions, preconcentration factors of 470, 490, 460, 385, 370, and 430 were obtained for amitriptyline, doxepin, imipramine, desipramine, maprotiline, and sertraline, respectively. The linear ranges and coefficients of determination (R²) were obtained in the range of 0.01–100 μg/L and 0.9974–0.9991, respectively. Also the limits of detection (S/N = 3) of 0.003–0.03 μg/L, and precisions (n = 5) of 4.9–8.9% were calculated. Finally, the method was successfully applied for the extraction of antidepressant drugs in biological samples, and relative recoveries in the range of 91–102% were obtained.     

Polyaniline immobilized on polycaprolactam nanofibers as a sorbent in electrochemically controlled solid-phase microextraction coupled with HPLC for the determination of angiotensin II receptor antagonists in human blood plasma

In this research, electrospun polycaprolactam nanofibers were collected on a fine stainless steel mesh sheet without a binder, and a layer of conductive polyaniline was chemically deposited on the nanofibers. The polyaniline immobilized on the polycaprolactam nanofibers provided high electrical conductivity, acceptable mechanical stability, and a large surface area. This assembly was then used as a working electrode in electrochemically controlled solid-phase microextraction (EC-SPME), a fast and environmentally friendly method. The polymer layers were characterized by SEM and FTIR techniques. Significant factors affecting the EC-SPME efficiency were investigated, including the desorption conditions, the sorbent used, the pH of the sample solution, the extraction voltage, the extraction time, and the ionic strength. Under the optimum conditions, the limits of detection and quantification for the target analytes were 0.9–1.8 μg L⁻¹ and 3.0–6.1 μg L⁻¹, respectively. The linear dynamic range was 5–2000 μg L⁻¹, with R² > 0.993. The method was coupled with HPLC analysis and applied to the determination of angiotensin ΙΙ receptor antagonists (ARA-ΙΙs) in human plasma, and relative recoveries of 91.1–104.3% with RSDs of ≤8.3% were obtained.

     

Molecular parameterization and determination of the electrode potentials of anticoagulant derivatives: Electrochemical and quantum chemical study

This research presents calculations and computation of two anticoagulant derivatives electrode potentials in methanol. For this purpose, the ab initio molecular orbital calculations (HF) and density functional theory (DFT) together with the 6-31G(d) basis set were utilized. The calculated values were compared with the experimental values obtained by linear sweep voltammetry. The observed and the calculated changes in the reduction potential of the anticoagulant derivatives differed from those of the reference compound (catechol), being less than 20 mV. In this way, a method was provided, by which the reduction potentials of the related molecules could be predicted very accurately. Actually, the resulting data illustrated that the method was likely to be useful for the prediction of biomolecules electrode potentials in different aprotic solvents. The bond lengths, bond angles and dipole moment of the studied compounds were calculated in two different solvents and the solvent effects were discussed.     

Single facility location and relocation problem with time dependent weights and discrete planning horizon

In this paper a single facility location problem with multiple relocation opportunities is investigated. The weight associated with each demand point is a known function of time. We consider either rectilinear, or squared Euclidean, or Euclidean distances. Relocations can take place at pre-determined times. The objective function is to minimize the total location and relocation costs. An algorithm which finds the optimal locations, relocation times and the total cost, for all three types of distance measurements and various weight functions, is developed. Locations are found using constant weights, and relocations times are the solution to a Dynamic Programming or Binary Integer Programming (BIP) model. The time horizon can be finite or infinite.     

Preparation of HMWCNT/PLLA nanocomposite scaffolds for application in nerve tissue engineering and evaluation of their physical,mechanical and cellular activity properties

This study was aimed to prepare biodegradable and porous nanocomposite scaffolds with microtubular orientation structure as a model for nerve tissue engineering by thermally induced phase separation (TIPS) method using dioxane as the solvent, crystalline poly (L‐lactic acid) (PLLA) and multi‐walled carbon nanotubes (MWCNTs). In order to overcome dispersion of MWCNTs in the PLLA matrix, heparinization of MWCNTs was performed. Solvent crystallization, oriented structure, the mean pore diameter and porosity percentage of the scaffolds were controlled by fundamental system parameters including temperature‐gradient of the system, polymer solution concentration and carbon nanotube content. Scanning Electron Microscopy (SEM), ImageJ, software and dynamic mechanical thermal analysis (DMTA) were used to investigate the structural and mechanical properties. TEM observation was carried out for characterization of nanotube dispersion in PLLA. It was found that the scaffolds containing heparinized multi‐walled carbon nanotubes (HMWCNTs) exhibited higher storage modulus, better carbon nanotube (CNT) dispersion and tubular orientation structure than those with non heparinized MWCNTs. In‐vitro studies were also conducted by using murine P₁₉ cell line as a suitable model system to analyze neuronal differentiation over a 2‐week period. Immunofluorescence and DAPI staining were used to confirm the cells' attachment and differentiation on the PLLA/HMWCNT nanocomposite scaffolds. Based on the results, we can conclude that the PLLA/HMWCNT scaffolds enhanced the nerve cell differentiation and proliferation, and therefore, acted as a positive cue to support neurite outgrowth. Copyright © 2015 John Wiley & Sons, Ltd.