Relation between potential and catalytic activity of rhodium in propylene combustion

The relation between the catalyst potential and the catalytic performance has been investigated in the gas-phase combustion of propylene with oxygen over rhodium catalysts at 375 °C. The rhodium catalyst, deposited on yttria-stabilized zirconia (YSZ) solid electrolyte, also served as working electrode in the electrochemical cell. Under open-circuit conditions, the measured catalyst potential was found to be a sensitive indicator of the oxidation state of the rhodium catalyst, which influences the catalytic reaction rate dramatically and depends strongly both on the method of catalyst film preparation and on the composition of the reacting gas mixture. In turn, under closed-circuit conditions, the applied catalyst potential is a convenient tool to maintain the catalyst in its more active, reduced form and to control its catalytic performance. The activity of atomic oxygen at the three-phase boundary (tpb) during open-circuit catalytic reaction was estimated from solid electrolyte potentiometric (SEP) measurements, in good agreement with the average surface oxidation state obtained from XRD and XPS analyses. O/Rh atomic ratios higher than stoichiometric were found by XPS at the outer surface of the catalysts suggesting a strong open circuit O^2– spillover due to strong metal support interactions (SMSI) and a concomitant extension of the electric double layer to the gas-exposed catalyst surface, similarly to emersed electrodes in aqueous electrochemistry. Applying potentials up to several hundreds of mV, highly nonfaradaic promotion of propylene combustion was achieved. Electrochemical promotion of catalysis (EPOC) was most efficient at stoichiometric gas composition, that is, close to the limit of surface reduction, and with the catalyst exhibiting the smallest O^2– spillover population at open-circuit conditions.     

Nonfragile observer‐based H ∞ sliding mode control for Itô stochastic systems with Markovian switching

The paper is devoted to investigating sliding mode control for a class of nonlinear uncertain stochastic systems with input nonlinearity and Markovian switching. A nonfragile observer subjected to the transition rates of the modes is designed. By some specified matrices, the connections among the designed sliding surfaces corresponding to every mode are established. The state estimation‐based sliding mode control law is derived to guarantee the reachability of the sliding surface in finite time interval. The sufficient conditions on asymptotically stochastic stability of the error system and sliding mode dynamics with a given disturbance attenuation level are derived in terms of linear matrix inequalities. Finally, an example is provided to illustrate the efficiency of the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.     

Explicit control of adaptive automation under different levels of environmental stress

This article examines the effectiveness of three different forms of explicit control of adaptive automation under low- and high-stress conditions, operationalised by different levels of noise. In total, 60 participants were assigned to one of three types of automation design (free, prompted and forced choice). They were trained for 4?h on a highly automated simulation of a process control environment, called AutoCAMS. This was followed by a 4-h testing session under noise exposure and quiet conditions. Measures of performance, psychophysiology and subjective reactions were taken. The results showed that all three modes of explicit control of adaptive automation modes were able to attenuate the negative effects of noise. This was partly due to the fact that operators opted for higher levels of automation under noise. It also emerged that forced choice showed marginal advantages over the two other automation modes. Statement of Relevance: This work is relevant to the design of adaptive automation since it emphasises the need to consider the impact of work-related stressors during task completion. During the presence of stressors, different forms of operator support through automation may be required than under more favourable working conditions.     

Development of a Remote Collaborative Forging Engineering System

The ever-growing demand for high-quality products with lower cost and shorter time-to-market is a challenge in today’s global market. This paper presents a methodology for merging the new technologies of networking and multimedia, with a conventional forging system to form a remote collaborative forging engineering system. The activities of conventional forging engineering design and manufacturing processes planning were analysed and a structural model is proposed for forging enterprises to investigate and improve their engineering activities. The synergy of networking and multimedia technologies is adopted in communicating and coordinating the activities of the engineers of a multinational enterprise dispersed in different locations, using computer supported cooperative work. For the next generation forging engineering environments, the concept of a remote collaborative forging engineering system provides a new approach and strategy to enhance their competitive advantages; and it also provides a fast, economical and experience-sharing method for the enterprises. An industrial example is used to illustrate the proposed system.     

Optimisation of the electrical discharge machining process using a GA-based neural network

In this paper, the optimisation of the EDM process parameters from the rough cutting stage to the finish cutting stage has been reported. A trained neural network was used to establish the relationship between the process parameters and machining performance. Genetic algorithms with properly defined objective functions were then adapted to the neural network to determine the optimal process parameters. Examples with specifications intentionally assigned the same values as those recorded in the database or selected arbitrarily have been fed into the developed GA-based neural network in order to verify the optimisation ability throughout the machining process. Accordingly, the optimised results indicate that the GA-based neural network can be successfully used to generate optimal process parameters from the rough cutting stage to the finish cutting stage.     

Morphometric determination of the methodological criteria for the diagnosis of intestinal neuronal dysplasia (IND B)

Intestinal neuronal dysplasia of the submucous plexus (IND B) is an indicator of a developmental abnormality of vegetative gut innervation. It is the mildest form of an inborn error of intestinal innervation. The diagnosis of IND B does not result in a functional conclusion or clinical recommendation but is often accompanied by oligoneuronal hypoganglionosis of the myenteric plexus or an aganglionosis of the rectum. The aim of this study was to demonstrate by morphometric means a way in which the diagnosis of IND B could be made much more reliable. In 20 control subjects, 40 IND B cases and 10 hypoganglionoses with IND B, it was shown that a specific nerve cell staining (e.g. Lactic dehydrogenase, Succinic dehydrogenase, Diaphorase reaction or an immunohistochemical nerve cell staining) was necessary for diagnosis. Cross sections of giant ganglions and cross sections with large nerve cell numbers (> 7 nerve cell profiles) were the most reliable diagnostic criteria. The morphometric examinations were performed with an optic electronic image analysis system. Biopsy serial sections of the rectum-mucosa that contained submucosa demonstrated that 30-40% of the sections contained no submucous ganglion. Sixty to 70% of the sections showed ganglia of the submucous plexus. In 100 biopsy sections in subjects with IND B, 20 +/- 5% contained giant ganglions cross sections. In the patients with hypoganglionosis of the submucous plexus, 55 +/- 4% sections had no ganglion and 18 +/- 3% had giant ganglion cross sections. The data demonstrate that for a reliable diagnosis of IND B, at least 30 sections are necessary, stained with a dehydrogenase reaction that contain a minimum of 4 giant ganglion cross sections. These data demonstrate that IND B is not a qualitative diagnosis as Hirschsprung's disease but rather a quantitative diagnosis.     

Early versus delayed angiotensin-converting enzyme inhibition therapy in acute myocardial infarction. The healing and early afterload reducing therapy trial

BACKGROUND: Although ACE inhibitor therapy has been shown to reduce mortality in patients with acute myocardial infarction (MI), the optimal dose and the timing of its initiation have not been determined. METHODS AND RESULTS: In a double-blind trial of 352 patients with anterior MI, we compared the safety and effectiveness of early (day 1) versus delayed (day 14) initiation of the ACE inhibitor ramipril (10 mg) on echocardiographic measures of left ventricular (LV) area and ejection fraction (EF). An early, low-dose ramipril (0.625 mg) arm was also evaluated. Clinical events did not differ. During the first 14 days, the risk of manifesting a systolic arterial pressure of < or = 90 mm Hg was increased in both ramipril groups. LVEF increased in all groups during this period, but the early, full-dose ramipril group had the greatest improvement in EF (increase: full, 4.9 +/- 10.0; low, 3.9 +/- 8.2%; delayed, 2.4 +/- 8.8%; P for trend < .05) and was the only group that did not demonstrate a significant increase in LV diastolic area. CONCLUSIONS: The results of the present study demonstrated that in patients with anterior MI, the early use of ramipril (titrated to 10 mg) attenuated LV remodeling and was associated with a prompter recovery of LVEF. The use of low-dose regimen did not prevent hypotension and had only intermediate benefits on LV size and function. The more favorable effects on LV topography of the early use of full-dose ramipril support the results of the major clinical trials, which have demonstrated an early survival benefit of ACE inhibition.     

A novel automatic virtual metrology system architecture for TFT-LCD industry based on main memory database

The semiconductor and thin-film-transistor–liquid-crystal-display (TFT-LCD) industries widely value Automatic Virtual Metrology System (AVMS). AVMS needs to handle a large volume of VM-related data, which may cause poor internal database performance. In general, AVMS adopts efficient but expensive commercial database management systems (DBMSs) to yield good AVMS performance. This usually makes the AVMS construction cost very high. Therefore, the industries require a novel AVMS architecture with lower cost and greater efficiency in database. This paper proposes a novel AVMS architecture based on Main Memory Database (MMDB) technology. Specifically, the MMDB is used to improve the performance bottlenecks of the current Disk Resident Database (DRDB). Also, we design automatic data-backup and automatic data-query sources integration mechanisms to effectively relieve rapidly increased data volume in the original AVMS architecture. In addition, the novel AVMS architecture adopts a free commercial MMDB to significantly reduce total system cost. Integrated testing results show that the proposed AVMS architecture and developed technologies can enable the AVMS to have better data-storage efficiency, superior data-query performance, and lower database cost. The proposed AVMS architecture and research results in this paper can be a useful reference for TFT-LCD manufacturing companies in constructing their own AVM systems. The proposed AVMS architecture can also be applied in the semiconductor and solar-cell industries.     

Evidence that glucose metabolism regulates leptin secretion from cultured rat adipocytes

Circulating leptin secreted from adipocytes is correlated with fat mass and plasma insulin concentrations in humans and rodents. Plasma leptin, insulin, and glucose decrease during fasting and increase after refeeding; however, the underlying mechanisms regulating the changes of leptin secretion are not known. To investigate the role of insulin-stimulated glucose metabolism in the regulation of leptin secretion, we examined the effects of insulin and inhibitors of glucose transport and metabolism on leptin secretion from rat adipocytes in primary culture. Insulin (0.16-16 nM) increased leptin secretion over 96 h; however, the increase in leptin was more closely related to the amount of glucose taken up by the adipocytes (r = 0.64; P < 0.0001) than to the insulin concentration per se (r = 0.20; P < 0.28), suggesting a role for glucose transport and/or metabolism in regulating leptin secretion. 2-Deoxy-D-glucose (2-DG), a competitive inhibitor of glucose transport and phosphorylation, caused a concentration-dependent (2-50 mg/dl) inhibition of leptin release in the presence of 1.6 nM insulin. The inhibitory effect of 2-DG was reversed by high concentrations of glucose. Two other inhibitors of glucose transport, phloretin (0.05-0.25 mM) and cytochalasin-B (0.5-50 microM), also inhibited leptin secretion. Inhibition of leptin secretion by these agents was proportional to the inhibition of glucose uptake (r = 0.60 to 0.86; all P < 0.01). Two inhibitors of glycolysis, iodoacetate (0.005-1.0 mM) and sodium fluoride (0.1-5 mM), produced concentration-dependent inhibition of leptin secretion in the presence of 1.6 nM insulin. In addition, both 2-DG and sodium fluoride markedly decreased the leptin (ob) messenger RNA content of cultured adipocytes, but did not affect 18S ribosomal RNA content. We conclude that glucose transport and metabolism are important factors in the regulation of leptin expression and secretion and that the effect of insulin to increase adipocyte glucose utilization is likely to contribute to insulin-stimulated leptin secretion. Thus, in vivo, decreased adipose glucose metabolism may be one mechanism by which fasting decreases circulating leptin, whereas increased adipose glucose metabolism would increase leptin after refeeding.