A scanning reflector using an off-axis space-fed phased-array feed

An architecture for a scanning reflector antenna that supports wide-angle scanning, multioctave tunable bandwidths, transmit and receive operation, and monopulse processing is presented. It consists of a parabolic dish with an offset phased array. The array is actually a feed-through lens fed from a small feed array in the back of the lens. Beam steering is accomplished by using the feed array to illuminate clusters of elements within the lens that correspond to far-field beam positions. The evolution of the architecture and a computer model is described. Simulated and measured performance results are reported. Off-axis scanning of 10° to 15° appears to be possible while still supporting gain magnifications of four to five     

A multi-objective supply chain model integrated with location of distribution centers and supplier selection decisions

Today, in the competitive markets, supply chain works as an interrelating network of suppliers, manufacturers, distributors, and customers, to satisfy customer demands. Coordinating all parts of the supply chain is a multi-level process and needs important decisions that affect on the performance of each part and whole supply chain and some conflicting objectives should be considered. In this paper, the supplier selection problem is integrated with production decision and distributor location problems and a new mathematical model is proposed. Delivery time, total cost, and quality are the objective functions considered and weighting method is used to solve the multi-objective problem. A modified genetic algorithm is proposed to obtain Pareto optimal solution sets. Computational experiments are included for validation of proposed algorithm. The results show that the proposed algorithm gives high-quality solutions as well as better computational times.     

Manganese chloride tetrahydrate (CMC-001) enhanced liver MRI: evaluation of efficacy and safety in healthy volunteers

Object

To evaluate the efficacy of three dose levels of the oral hepatobiliary manganese-based magnetic resonance imaging (MRI) contrast agent CMC-001, and assess its safety profile and patient acceptability.

Materials and methods

After ethics committee approval, 32 healthy volunteers (males/females: 18/14) were included. Liver MRI was performed before and 3?h after ingestion of 0.8, 0.4, and 0.2?g of CMC-001 on separate occasions. Liver-to-muscle signal intensity (SI) ratio from baseline to post-contrast and image quality was assessed. Adverse drug reactions/adverse events (ADRs/AEs) and clinico-laboratory tests were monitored.

Results

The increase in liver-to-muscle SI ratio was significantly higher after 0.8?g (0.696) compared to 0.4?g (0.458) and 0.2?g (0.223) (in all pair-wise comparisons, P?Conclusion Liver MRI using 0.8?g CMC-001 has the highest efficacy and still acceptable ADRs and should therefore be preferred.     

Dispersant-assisted low frequency electrophoretically deposited TiO2 nanoparticles in non-aqueous suspensions for gas sensing applications

The effect of dispersant on deposition mechanism of TiO₂ nanoparticles at 1 Hz under non-uniform AC fields was investigated. It was found that by adding Dolapix to suspension, deposition pattern is drastically changed enabling particles to enter the gap leaving the electrodes intact. Using low frequency AC electrophoretic deposition technique in the presence of dispersant, we succeeded in fabricating gas sensor in less than 2 min. Gas sensing measurements were performed in the temperature range of 450–550 °C. The results explained that the sensor has good stability in time and repeatability performance toward high response. The maximum sensitivity of about 180 for the TiO₂ nanoparticles sensor is observed with 47 ppm NO₂ gas and the response and recovery times is about 60–150 s. The optimum temperature of the gas sensor was obtained in 450 °C where sensor showed a linear trend up to 50 ppm of NO₂ gas. This sensing behavior in un-doped TiO₂ as NO₂ sensor can be mainly ascribed to the porous structure of the sensing film and its good contacts to the substrate and electrode assembly.     

YSZ electrolyte coating on NiO–YSZ composite by electrophoretic deposition for solid oxide fuel cells (SOFCs)

A thick dense film of YSZ has been fabricated on a porous NiO–YSZ substrate from the YSZ powders in the mixtures of absolute acetyl acetone–ethanol suspensions by electrophoretic deposition (EPD) method. Parameters affected on substrate porosity like pre-sintering temperature and percentage of starch and parameters affected on EPD process like applied voltage and time of deposition have been investigated. Linear dependence between weights of deposition, deposition time and applied voltage were observed. A crack-free dense thick film of YSZ was obtained on porous NiO–YSZ substrate. Adhesion between the two layers was observed by SEM. The ability of ionic transfer and permeability of the YSZ electrolyte were investigated by EIS, as well.     

Application of local improvements to reduced-order models to sampling methods for nonlinear PDEs with noise

In this work, we extend upon the results of Raissi and Seshaiyer [A multi-fidelity stochastic collocation method for parabolic partial differential equations with random input data, Int. J. Uncertain. Quantif. 4(3) (2014), pp. 225–242]. In Raissi and Seshaiyer (2014), the authors propose to use deterministic model reduction techniques to enhance the performance of sampling methods like Monte-Carlo or stochastic collocation. However, in order to be able to apply the method proposed in Raissi and Seshaiyer (2014) to non-linear problems a crucial step needs to be taken. This step involves local improvements to reduced-order models. This paper is an illustration of the importance of this step. Local improvements to reduced-order models are achieved using sensitivity analysis of the proper orthogonal decomposition.     

Safe Autonomy Under Perception Uncertainty Using Chance-Constrained Temporal Logic

Autonomous vehicles have found wide-ranging adoption in aerospace, terrestrial as well as marine use. These systems often operate in uncertain environments and in the presence of noisy sensors, and use machine learning and statistical sensor fusion algorithms to form an internal model of the world that is inherently probabilistic. Autonomous vehicles need to operate using this uncertain world-model, and hence, their correctness cannot be deterministically specified. Even once probabilistic correctness is specified, proving that an autonomous vehicle will operate correctly is a challenging problem. In this paper, we address these challenges by proposing a correct-by-synthesis approach to autonomous vehicle control. We propose a probabilistic extension of temporal logic, named Chance Constrained Temporal Logic (C2TL), that can be used to specify correctness requirements in presence of uncertainty. C2TL extends temporal logic by including chance constraints as predicates in the formula which allows modeling of perception uncertainty while retaining its ease of reasoning. We present a novel automated synthesis technique that compiles C2TL specification into mixed integer constraints, and uses second-order (quadratic) cone programming to synthesize optimal control of autonomous vehicles subject to the C2TL specification. We also present a risk distribution approach that enables synthesis of plans with lower cost without increasing the overall risk. We demonstrate the effectiveness of the proposed approach on a diverse set of illustrative examples.     

Creep simulation of adhesively bonded joints using modified generalized time hardening model

Creep behavior of double lap adhesively bonded joints was investigated using experimental tests and numerical analysis. Firstly, uniaxial creep tests were carried out to obtain the creep characteristics and constitutive parameters of the adhesive at different stress and temperature levels. Generalized time hardening model was used to predict the creep behavior of the adhesive. This model was modified to simulate the creep behavior at different stress and temperature levels. Secondly, the developed model was used to simulate the creep behavior of bonded joints using finite element based numerical analysis. Creep deformations of the joints were measured experimentally and good agreement was observed in comparison with the results obtained using numerical simulation. Afterward, stress redistribution due to the creep along the adhesively bonded joint was obtained numerically. It was observed that temperature level had a significant effect on the stress redistribution along the adhesive thickness.     

Dynamic multi-robot task allocation under uncertainty and temporal constraints

Autonomous Robots - We consider the problem of dynamically allocating tasks to multiple agents under time window constraints and task completion uncertainty. Our objective is to minimize the number...