Application of graphite screen printed electrode modified with dysprosium tungstate nanoparticles in voltammetric determination of epinephrine in the presence of acetylcholine

The current work focuses on the development of a sensitive and selective electrochemical device based on a graphite screen printed electrode modified with Dy_2(WO_4)_3 nanoparticles(DWO/SPE) for the analysis of epinephrine in samples also containing acetylcholine. The study proves that the sensor has excellent electron-mediating behavior in the oxidation of epinephrine in a 0.1 mol/L phosphate buffer solution(PBS)(pH 7.0). The application of the DWO/SPE in differential pulse voltammetry(DPV) is found to lead to distinct response for the oxidation of epinephrine and acetylcholine, with the potentials of the epinephrine and acetylcholine peaks(△E_p) to be 550 mV apart. The detection limits of the method for epinephrine and acetylcholine are 0.5 and 0.7 μmol/L(S/N = 3) and the responses are found to be linear in the concentration ranges of 1.0-900.0 μmol/L and 1.0-1200.0 μmol/L in a PBS buffer(pH = 7.0)respectively. The modified electrode was used for the detection of epinephrine and acetylcholine in real samples and found to produce satisfactory results. These results can be a proof that Dy_2(WO_4)_3 nanoparticles can find promising applications in electrochemical sensors to be used for the analysis of(bio)chemical species.     

Hybrid credit ranking intelligent system using expert system and artificial neural networks

The main goal of all commercial banks is to collect the savings of legal and real persons and allocate them as credit to industrial, services and production companies. Non repayment of such credits cause many problems to the banks such as incapability to repay the central bank’s loans, increasing the amount of credit allocations comparing to credit repayment and incapability to allocate more credits to customers. The importance of credit allocation in banking industry and it’s important role in economic growth and employment creation leads the development of many models to evaluate the credit risk of applicants. But many of these models are classic and are incapable to do credit evaluation completely and efficiently. Therefore the demand to use artificial intelligence in this field has grown up. In this paper after providing appropriate credit ranking model and collecting expert’s knowledge, we design a hybrid intelligent system for credit ranking using reasoning-transformational models. Expert system as symbolic module and artificial neural network as non-symbolic module are components of this hybrid system. Such models provide the unique features of each components, the reasoning and explanation of expert system and the generalization and adaptability of artificial neural networks. The results of this system demonstrate hybrid intelligence system is more accurate and powerful in credit ranking comparing to expert systems and traditional banking models.     

Perchlorate-selective membrane sensors based on two nickel-hexaazamacrocycle complexes

The perchlorate salts of nickel(II) complexes of 1,3,5,8,10,13-hexaazacyclotetradecane (1) and 1,8-tert-butyl-1,3,5,8,10,13-hexaazacyclotetradecane (2) were used in construction of PVC based membrane electrodes. These sensors show very good selectivity for ClO₄⁻ ions over a wide variety of anions. These electrodes exhibit Nernstian behavior with the slopes of 59.5 and 59.3 mV per decade for (1) and (2), respectively. The working concentration ranges of the sensors are 1.0 × 10⁻¹–9.0 × 10⁻⁷ M (1) and 1.0 × 10⁻¹–5.0 × 10⁻⁷ M (2) with the detection limits of 6.0 × 10⁻⁷ and 2.0 × 10⁻⁷ M, respectively. The response time of the both sensors is very fast, and can be used for 2 (I) and 12 (II) weeks in a pH range of 3.0–11.0. These electrodes were applied to the determination of perchlorate ions in wastewater and cattle urine samples.     

Metamodel-based collaborative optimization framework

This paper focuses on the metamodel-based collaborative optimization (CO). The objective is to improve the computational efficiency of CO in order to handle multidisciplinary design optimization problems utilising high fidelity models. To address these issues, two levels of metamodel building techniques are proposed: metamodels in the disciplinary optimization are based on multi-fidelity modelling (the interaction of low and high fidelity models) and for the system level optimization a combination of a global metamodel based on the moving least squares method and trust region strategy is introduced. The proposed method is demonstrated on a continuous fiber-reinforced composite beam test problem. Results show that methods introduced in this paper provide an effective way of improving computational efficiency of CO based on high fidelity simulation models.     

Packaging for microelectromechanical and nanoelectromechanical systems

Packaging is a core technology for the advancement of microelectromechanical systems (MEMS) and nanoelectromechanical systems (NEMS). We discuss MEMS packaging challenges in the context of functional interfaces, reliability, modeling and integration. These challenges are application-dependent; therefore, two case studies on accelerometers and BioMEMS are presented for an in-depth illustration. Presently, most NEMS are in the exploratory stage and hence a unique path to identify the relevant packaging issues for these devices has not been determined. We do, however, expect the self-assembly of nano-devices to play a key role in NEMS packaging. We demonstrate this point in two case studies, one on a silicon nanowire biosensor, and the other on self-assembly in molecular biology. MEMS/NEMS have the potential to have a tremendous impact on various sectors such as automotive, aerospace, heavy duty applications, and health care. Packaging engineers have an opportunity to make this impact a reality by developing low-cost, high-performance and high-reliability packaging solutions.     

Effects of cement size distribution on capillary pore structure of the simulated cement paste

The evolution of tricalcium silicate (C₃S) microstructure during hydration is tri-dimensionally simulated based on an “Integrated Particle Kinetics Model”. The hydration degree, the contact surfaces between the hydrated particles, the hydraulic radius and the capillary pore size distribution of the simulated cement paste at various degrees of hydration are calculated. Three examples of the C₃S microstructure development with different size distributions are presented. The effects of the cement size distribution on pore structure of cement paste are demonstrated and the results are discussed. In these examples, the cement size distribution varies between 3–40, 5–40 and 10–40 μm, respectively.     

Impact of safety belt use on road accident injury and injury type in Kuwait

The enactment of Kuwait's seat belt law in January 1994 provided an opportunity to examine the impact of seat belt use on road accident fatalities and injury types in this affluent Persian Gulf nation. Via a structured data form, the results of injurious/fatal road accidents for more than 1200 accident victims were gathered from the files of the six major government hospitals which treat most traffic accident victims. Statistical analysis of the data showed that seat belt use has had a positive effect in reducing both road traffic fatalities and multiple injuries in Kuwait. The use of seat belts has also affected the nature of the injuries resulting from road traffic accidents. Non-users of belts experienced higher frequencies of head, face, abdominal and limb injuries. Users of belts, on the other hand, suffered higher frequencies of neck and chest injuries. The interrelationship between the victim, his age, and the type of injuries resulting from road traffic accidents is also investigated.     

Two-dimensional array self-assembled quantum dot sub-diffraction waveguides with low loss and low crosstalk

We model and demonstrate the behavior of two-dimensional (2D) self-assembled quantum dot (QD) sub-diffraction waveguides. By pumping the gain-enabled semiconductor nanoparticles and introducing a signal light, energy coupling of stimulated photons from the QDs enables light transmission along the waveguide. Monte Carlo simulation with randomized inter-dot separation reveals that the optical gain necessary for unity transfer is 3.1 × 10(7)?m(-1) for a 2D (2?μm length by 500?nm width) array compared to 11.6 × 10(7)?m(-1) for a 1D (2?μm length) given 8?nm diameter quantum dots. The theoretical results are borne out in experiments on 2D arrays by measurement of negligible crosstalk component with as little as 200?nm waveguide separation and is indicative of near-field optical coupling behavior. The transmission loss for 500?nm wide structures is determined to be close to 3?dB/4?μm, whereas that for 100?nm width is 3?dB/2.3?μm. Accordingly, higher pump power and gain would be necessary on the narrower device to create similar throughput. Considering existing nanoscale propagation methods, which commonly use negative dielectric materials, our waveguide shows an improved loss characteristic with comparable or smaller dimensions. Thus, the application of QDs to nanophotonic waveguiding represents a promising path towards ultra-high density photonic integrated circuits.     

Minimizing total flow time for the non-permutation flow shop scheduling problem with learning effects and availability constraints

The flow shop scheduling problem is an attractive subject in the field of scheduling, which has attracted the attention of many researchers in the past five decades. In this paper, the non-permutation flow shop scheduling problem with the learning effects and machine availability constraints has been studied for minimizing the total flow time as a performance measure. First, a mixed integer linear programming model has been proposed for the modeling of the problem and then, an effective improving heuristic method, which is able to find proper non-permutation solutions, has been presented. Finally, the computational results are used for evaluation the performance and effectiveness of the proposed heuristic.     

Electrostatically driven synthetic microjet arrays as a propulsion method for micro flight

A novel propulsion method suitable for micromachining is presented that takes advantage of Helmholtz resonance, acoustic streaming, and eventually flow entrainment and thrust augmentation. In this method, an intense acoustic field is created inside the cavity of a Helmholtz resonator. Flow velocities at the resonator throat are amplified by the resonator and create a jet stream due to acoustic streaming. These jets are used to form a propulsion system. In this paper a system hierarchy incorporating the new method is described and the relevant governing equations for the Helmholtz resonator operation and acoustic streaming are derived. These equations can predict various device parameters such as cavity pressure amplitude, exit jet velocity and generated thrust. In a sample embodiment, an electrostatic actuator is used for generation of the initial acoustic field. The relevant design parameters for the actuator are discussed and an equivalent circuit model is synthesized for the device operation. The circuit model can predict the lowest order system resonance frequencies and the small signal energy conversion efficiency. A representative resonator performance is simulated and it is shown that velocities above 16 m/s are expected at jet nozzles. The calculated delivered thrust by this resonator with 0.7 m diaphragm displacement amplitude is 3.3 N at the resonance frequency.