Sonochemical Synthesis of a Nanocrystalline Tin(IV) Complex based on a Bulky Anthracene Carboxylate Ligand: Spectroscopic and Photophysical Properties

In order systematically investigate the effect of ligand with a large conjugated π-system on the structure and optical properties of tin complex, anthracene-9-carboxylic acid (L¹) is selected as a primary ligand, and quinoline-2-carboxylic acid (L²) used as second ligand to incorporate with anthracene-9-carboxylic acid to construct a new tin(IV)-carboxylate coordination complex under thermal gradient condition. Prepared complex was fully characterized based on its ¹H and ¹³C NMR, IR and UV spectra and elemental analysis. The molecular structure of complex was determined by single-crystal X-ray analysis. The nanocrystalline complexes of the prepared complex were successfully obtained at 30, 50 and 60 °C by a facile sonochemical route. The new nanocrystalline complexes were characterized by scanning electron microscopy, X-ray powder diffraction, IR spectroscopy and elemental analysis. The photoluminescence properties of the nanocrystalline complexes and crystalline bulk complex in the solid-state indicated that the size of the complex particles has a remarkable effect on the optical properties of it. Absorption and emission peaks of the nanocrystalline complexes blue shifted significantly in comparison with those of in the single-crystal form. Application of the prepared complex in fabrication of an organic light-emitting diode has been demonstrated. The current–voltage (I–V) characteristics and the electroluminescence (EL) properties of the complex have been investigated. The EL of the compound exhibits green emission at 552 nm.     

Highly efficient supported AlCl3-based cationic catalysts to produce polyα-olefin oil base stocks

The main aim of this research is to decrease the amount of AlCl₃ content that is very corrosive and hazardous in the catalytic system, required for the α-olefin oligomerization without substantial change of final oil features. This was successfully achieved by supporting AlCl₃ on different carriers. More precisely, a series of supported bimetallic catalysts was synthesized by immobilization of AlCl₃ and TiCl₄ onto Al₂O₃, SiO₂, and mixed supports, that is, Al₂O₃/FeCl₃ and SiO₂/FeCl₃. It was found that silica and alumina-based catalysts had higher catalytic activities compared to support free AlCl₃; however, this enhancement for silica-based supports was more significant. According to gel permeation chromatography (GPC) results, the use of single supports, that is, Al₂O₃ and SiO₂, increased oligomer's molecular weight, while the application of mixed supports resulted in the decrease of molecular weight of the oligomers. Viscosity characteristics of the synthesized oligomers have also been studied at two different temperatures of 40 and 100°C (KV⁴⁰ and KV¹⁰⁰). The viscosity index (VI) values, derived from KV⁴⁰ and KV¹⁰⁰, of the prepared oligomers were in the range of 126–145. The molecular weight and termination mechanisms of the oligomers were studied by ¹H-NMR spectroscopy. The obtained results disclosed that the employed reaction conditions led to the production of oligomer chains with various structures including vinylidene (Vd), and di and three-substituted vinylene (2Vn, 3Vn) structures.     

Enabling Interoperability among Grid Meta-Schedulers

The goal of Grid computing is to integrate the usage of computer resources from cooperating partners in the form of Virtual Organizations (VO). One of its key functions is to match jobs to execution resources efficiently. For interoperability between VOs, this matching operation occurs in resource brokering middleware, commonly referred to as the meta-scheduler or meta-broker. In this paper, we present an approach to a meta-scheduler architecture, combining hierarchical and peer-to-peer models for flexibility and extensibility. Interoperability is further promoted through the introduction of a set of protocols, allowing meta-schedulers to maintain sessions and exchange job and resource state using Web Services. Our architecture also incorporates a resource model that enables an efficient resource matching across multiple Virtual Organizations, especially where the compute resources and state are dynamic. Experiments demonstrate these new functional features across three distributed organizations (BSC, FIU, and IBM), that internally use different job scheduling technologies, computing infrastructure and security mechanisms. Performance evaluations through actual system measurements and simulations provide the insights on the architecture’s effectiveness and scalability.     

Experimental Study of RC Rectangular Liquid Containing Structures Retrofitted with GFRP Composites

The continual functioning of Liquid Containing Structures “LCS” is necessary for the well being of a society. These structures are designed based on serviceability criteria such as cracking that leads to leakage. Cracks form in liquid containing structures (LCS) for different reasons such as restrained thermal and shrinkage deformations, applied external loads such as earthquake loads, etc. These cracks can create exposure condition to initiate the corrosion process in reinforcement. The effectiveness of glass fiber reinforced polymer (GFRP) composites in recovering the structural strength of damaged members is widely recognized by engineers. However, the effectiveness on the use of GFRP composites as a protecting layer to prevent the passage of liquid through the cracks has not yet been reported in the literature. This concept inspires the main purpose of the investigation in this experimental study. Cracked reinforced concrete specimens subjected to different conditions of loading such as direct tension and cyclic flexure are repaired externally using GFRP sheets. The specimens are then subjected to hydrostatic pressure using a water pressure chamber at the crack location. This study shows that the application of GFRP composites for crack remediation in liquid containing structures could be very effective under monotonic loading. However, the effectiveness under cyclic flexure especially under higher load levels is questionable.     

Transparent autonomization in CORBA

Increasingly, software systems are constructed by integrating and composing multiple existing applications. The resulting complexity increases the need for self-management of the system. However, adding autonomic behavior to composite systems is difficult, especially when the constituent components are heterogeneous and they were not originally designed to support such interactions. Moreover, entangling the code for self-management with the code for the business logic of the original applications may actually increase the complexity of the systems, counter to the desired goal. In this paper, we address autonomization of composite systems that use CORBA, one of the first widely used middleware platforms introduced more than 17 years ago that is still commonly used in numerous systems. We propose a model, called Adaptive CORBA Template (ACT), that enables autonomic behavior to be added to CORBA applications automatically and transparently, that is, without requiring any modifications to the code implementing the business logic of the original applications. To do so, ACT uses “generic” interceptors, which are added to CORBA applications at startup time and enable autonomic behavior to be introduced later at runtime. We have developed ACT/J, a prototype of ACT in Java. We describe a case study in which ACT/J is used to introduce three types of autonomic behavior (self-healing, self-optimization, and self-configuration) to a distributed surveillance application.     

The Huynen-Fork Polarization Parameters in the Classification of Dielectric Mine-like Objects

We present a polarimetric approach that can be used to characterize subsurface targets by means of ground-penetrating radar. Several quantities related to the Huynen-fork parameters are basic to the study. These quantities are all expressible in terms of the elements of Sinclair matrix S which in turn, can be determined as functions of frequency by an application of the method-of-moment (MoM)—which is briefly reviewed here—to a mine-like object buried at various depths in a soil of specified dielectric and moisture properties. The quantities in question are the Stokes parameters, the elevation, azimuth, and polarizability angles, as well as the polarization ratios and the scattering eigenvalues which optimize the backscattered power. Some of these quantities are studied here and displayed in various graphs. These frequency dependent graphs exhibit useful symmetry properties. The plots of the polarizability angle (β) vs. frequency seem to remain invariant with target depth, and exhibit resonance features that are later shown to agree well with other standard methods to estimate resonances such as Prony method. A simple analysis of the early-time resonances thus estimated is used to obtain acceptable mine dimensions. The agreement found implies that polarimetric techniques, such as present one, can also be used in the arsenal of techniques yielding target-ID clues.     

A new mathematical modeling and a genetic algorithm search for milk run problem (an auto industry supply chain case study)

The idea of Milk Run has been used in the context of logistic and supply chain problems in order to manage the transportation of materials. In this paper, we propose a new Milk Run method, as a mixed integer approach, to manage supply chain problems. Since the resulted problem formulation is NP-Hard, we use some meta-heuristic and compare the results with the optimal solutions of the proposed Milk Run method. The mathematical modeling of this paper is purposely customized for a special case of an auto industry. We implement the mathematical formulation and the meta-heuristic using some actual data and compare the results with the current strategy. The preliminary results indicate that the proposed method could provide a practical tool to significantly reduce the cost of logistic.     

Scheduling flowshops with condition-based maintenance constraint to minimize expected makespan

Flexible job-shop scheduling problem (FJSP) is an extended traditional job-shop scheduling problem, which more approximates to practical scheduling problems. This paper presents a multi-objective genetic algorithm (MOGA) based on immune and entropy principle to solve the multi-objective FJSP. In this improved MOGA, the fitness scheme based on Pareto-optimality is applied, and the immune and entropy principle is used to keep the diversity of individuals and overcome the problem of premature convergence. Efficient crossover and mutation operators are proposed to adapt to the special chromosome structure. The proposed algorithm is evaluated on some representative instances, and the comparison with other approaches in the latest papers validates the effectiveness of the proposed algorithm.     

An interactive robust data envelopment analysis model for determining alternative targets in Iranian electricity distribution companies

One of the primary concerns on target setting the electricity distribution companies is the uncertainty on input/output data. In this paper, an interactive robust data envelopment analysis (IRDEA) model is proposed to determine the input and output target values of electricity distribution companies with considering the existence perturbation in data. Target setting is implemented with the uncertain data and the decision maker (DM) can search the envelop frontier and find the targets based on his preference. In order to search the envelop frontier, the paper combine the DEA and multi-objective linear programming method such as STEM. The proposed method of this paper is capable of handling uncertainty in data and finding the target values according to the DM’s preferences. To illustrate ability the proposed model, a numerical example is solved. Also, the input and output target values for some of the electricity distribution companies in Iran are reported. The results indicate that the IRDEA model is suitable for target setting based on DM’s preferences and with considering uncertain data.     

A hybrid method for flowshops scheduling with condition-based maintenance constraint and machines breakdown

One of the most important assumptions in production scheduling is that the machines are permanently available without any breakdown. In the real world of scheduling, machines can be made unavailable due to various reasons such as preventive maintenance and unpredicted breakdown. In this paper, we explore flowshop configuration under the assumption of condition-based maintenance to minimize expected makespan. Furthermore, we consider a condition-based maintenance (CBM) strategy which could be used in most industrial settings. The proposed algorithm is designed for non-resumable flowshop state where the processing of jobs after preventive maintenance is restarted from the beginning. We propose a hybrid algorithm based on genetic algorithm and simulated annealing. Additionally, we conduct an extensive parameter calibration with the utilization of Taguchi method and select the optimal levels of the algorithm’s performance influential factors. The preliminary results indicate that the proposed method provides significantly better results compared with other high performing algorithms in the literature.