Direct observation of atomic scale graphitic layer growth

The demand for better understanding of the mechanism of soot formation is driven by the negative environmental and health impact brought about by the burning of fossil fuels. While soot particles accumulate most of their mass from surface reactions, the mechanism for surface growth has so far been characterized primarily by measurements of the kinetics. Here we provide atomic-scale scanning tunneling microscope images of carbon growth by chemistry similar to that of importance in soot formation. At a temperature of 625 K, exposure of the surface of highly ordered pyrolytic graphite to 1 Langmuir of acetylene leads to the formation of both graphitic and amorphous carbonaceous material at the edges of nanoscale pits. Given the similarity of the electronic structure at these graphite defect sites to that of soot material growing in flames at higher temperatures, the present studies shed light on the mechanism for soot growth. These experiments also suggest that healing of defect sites in graphene nanostructures, which are of considerable interest as novel electronic devices, should be possible at modest surface temperatures by exposure of defected graphene to unsaturated hydrocarbons.     

Pervaporation of esters with hydrophobic membrane

Surface-modified alumina membrane (A1₂O₃) was used for ester flavor recovery by pervaporation. This study focused on the permeation characteristics of ester compounds (ethyl acetate, EA; ethyl propionate, EP; ethyl butyrate, EB) through tube-type hydrophobic membrane. Experiments were performed to evaluate the effects of the feed concentration (0.15-0.60 wt%) and temperature (30-50 ‡C) on separation of EA, EP, and EB from aqueous solutions. It was found that the permeation flux increased with increasing feed ester concentration and operating temperature. The fluxes of EA, EP, and EB at 0.60wt% feed concentration and 40 ‡C were 254, 343, and 377 g/m² hr, which was much higher than those of polymer membranes. It was reported that the permeate flux of EA with PDMS was 1.1-58 g/m²Phr at feed concentration of 90-4,800 ppm and 45 ‡C. The separation factors for the 0.15-0.60 wt% feed solution of EA, EP, and EB at 40 ‡C were in the range of 66.9-78.9, 106.5-97.3, and 120.5-122.8, respectively. Due to the high separation factor, phase separation occurred in permeate stream because the ester concentration in permeate was much above the saturation limit.     

Optimal real time pricing of real and reactive powers

This paper presents a theory and simulation results of real time pricing of real and reactive powers that maximizes social benefit. Conventional studies represented the responses of consumers as demand functions, and the objective of optimization was minimization of operating cost of power system. In this paper, the responses of consumers are represented as the inverse of the demand functions and power flow equations are incorporated in the constraints. This makes it possible to incorporate constant power factor demand consumer as a participant. That also makes it possible to maximize the objective function of optimization that is social benefit of participating in the electricity market and to determine the price of electricity at each bus. Not only the real time price of real power but also that of reactive power is determined simultaneously by the incorporation of power factor of loads into the constraint of optimization     

Search-Based Cost-Effective Software Remodularization

Software modularization is a technique used to divide a software system into independent modules (packages) that are expected to be cohesive and loosely coupled. However, as software systems evolve over time to meet new requirements, their modularizations become complex and gradually loose their quality. Thus, it is challenging to automatically optimize the classes’ distribution in packages, also known as remodularization. To alleviate this issue, we introduce a new approach to optimize software modularization by moving classes to more suitable packages. In addition to improving design quality and preserving semantic coherence, our approach takes into consideration the refactoring effort as an objective in itself while optimizing software modularization. We adapt the Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) of Deb et al. to find the best sequence of refactorings that 1) maximize structural quality, 2) maximize semantic cohesiveness of packages (evaluated by a semantic measure based on WordNet), and 3) minimize the refactoring effort. We report the results of an evaluation of our approach using open-source projects, and we show that our proposal is able to produce a coherent and useful sequence of recommended refactorings both in terms of quality metrics and from the developer’s points of view.     

Biocompatible and Biodegradable Neuromorphic Device Based on Hyaluronic Acid for Implantable Bioelectronics

Neurodegenerative disorders are challenging issues for initial diagnosis and cure. False signals from neurons that make up the brain must be corrected. To treat neurodegenerative diseases, neuromorphic devices are inserted into the body and connected to nerves. However, there are major concerns regarding implanting these devices into living bodies, that is, toxicity caused by the materials and the need for an additional operation to remove the device after treatment. In this research, a neuromorphic device is fabricated based on hyaluronic acid (HA), which is biocompatible and biodegradable, that meets the requirements for implantable bioelectronics. The fabricated device have a paired-pulse facilitation index of ≈121.00% and short term-to-long term memory transition behavior that resembled human learning-experience behavior. It is confirmed that the synaptic behavior mechanism of the device is due to an Mg oxide layer formed at the Mg/HA interface. Biodegradability and cell cytotoxicity tests confirmed the suitability of HA-based neuromorphic devices as implantable bioelectronics. Based on the results, it is believed that such implantable devices will lead to better healthcare.     

Hybrid Task and Message Scheduling in Hard Real Time Distributed Systems over FlexRay Bus

FlexRay is a vehicular communication protocol designed to meet growing requirements in hard real time automotive systems and to support time triggered as well as event triggered paradigms. Thus, there has been a lot of recent interest in timing analysis techniques in order to provide bounds for the message communication times on FlexRay. In this paper, we present an approach to compute the WCRT （worst case response time） for periodic and sporadic tasks, within a FlexRay node, responsible for sending messages on the FlexRay SS （static segment） and DS （dynamic segment）. On the other hand, we propose a scheduling table for messages transmitted over the FlexRay SS. An interesting innovation would be the use of a scheduling algorithm performed on a FlexRay node to guarantee the arrival of the right data on the right time and to ensure that every task meets its deadline. As application, we will use the extended SAE （society of automotive engineers） benchmark for the FlexRay network to identify the static and dynamic tasks, and calculate the response time, based on a hybrid scheduling model to further prove that the deadline of the SAE benchmark applications is insured.     

Crystallization behavior of polyphenylene sulfide (PPS) and PPS/carbon fiber composites: Effect of cure

Summary The effect of cure on the crystallization rates of polyphenylene sulfide (PPS) and PPS/carbon fiber composites has been studied by differential scanning calorimetry (DSC). The crystallization rate of PPS increased with increasing degree of cure. The carbon fiber acted as a nucleating agent to enhance the crystallization rate of PPS. The fully cured PPS seemed to be saturated with nucleating sites formed through the cure reaction. Therefore, the presence of carbon fibers gave little effect on the crystallization rate of the fully cured PPS.