989 resultados para reduction chemistry


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Electrocatalytic reduction of water to molecular hydrogen via the hydrogen evolution reaction may provide a sustainable energy supply for the future, but its commercial application is hampered by the use of precious platinum catalysts. All alternatives to platinum thus far are based on nonprecious metals, and, to our knowledge, there is no report about a catalyst for electrocatalytic hydrogen evolution beyond metals. Here we couple graphitic-carbon nitride with nitrogen-doped graphene to produce a metal-free hybrid catalyst, which shows an unexpected hydrogen evolution reaction activity with comparable overpotential and Tafel slope to some of well-developed metallic catalysts. Experimental observations in combination with density functional theory calculations reveal that its unusual electrocatalytic properties originate from an intrinsic chemical and electronic coupling that synergistically promotes the proton adsorption and reduction kinetics.

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Effective machine fault prognostic technologies can lead to elimination of unscheduled downtime and increase machine useful life and consequently lead to reduction of maintenance costs as well as prevention of human casualties in real engineering asset management. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique and historical failure knowledge embedded in the closed loop diagnostic and prognostic system. To estimate a discrete machine degradation state which can represent the complex nature of machine degradation effectively, the proposed prognostic model employed a classification algorithm which can use a number of damage sensitive features compared to conventional time series analysis techniques for accurate long-term prediction. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for the comparison of intelligent diagnostic test using five different classification algorithms. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state probability using the Support Vector Machine (SVM) classifier. The results obtained were very encouraging and showed that the proposed prognostics system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

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The fact that nature provides specific enzymes to selectively remove superoxide (O2.−) from aerobic organisms, namely, the superoxide dismutase enzymes,1 has led to the suggestion that this radical ion may cause the oxidative damage associated with degradative disease and aging.2 Intriguingly, however, superoxide itself is relatively unreactive toward most cellular components, which suggests that dismutase enzymes may ultimately protect the cell against more pernicious oxidants formed from superoxide. As such, there is increasing interest in the endogenous chemistry of superoxide and the pathways by which it might beget more reactive oxygen species. Protonation of superoxide to form the hydroperoxyl radical (HOO.) and dismutation of the same species to hydrogen peroxide (HOOH), with subsequent metal-catalyzed reduction to the hydroxyl radical (HO.), are well-characterized processes in which both the HOO. and HO. radicals are significantly more reactive than their common progenitor.2 Recent examples, however, have also linked superoxide to the putative production of singlet oxygen3 and ozone,4, 5 although the definitive characterization of these chemistries in the cellular milieu has proved challenging

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The electrodeposition of copper onto copper, gold, palladium and glassy carbon (GC) electrodes via a hydrogen bubble templating method is reported. It is found that the composition of the underlying electrode material significantly influences the morphology of the copper electrodeposit. Highly ordered porous structures are achieved with Cu and Au electrodes, however on Pd this order is disrupted and a rough randomly oriented surface is formed whereas on GC a bubble templating effect is not observed. Chronopotentiograms recorded during the electrodeposition process allows bubble formation and detachment from the surface to be monitored where distinctly different potential versus time profiles are observed at the different electrodes. The porous Cu surfaces are characterised with scanning electron microscopy, X-ray diffraction and cyclic voltammetric measurements recorded under alkaline conditions. The latter demonstrates that there are active sites present on electrodeposited copper whose coverage and reactivity depend on the underlying electrode material. The most active Cu surface is achieved at a Pd substrate for both the hydrogen evolution reaction and the catalytic reduction of ferricyanide ions with thiosulphate ions. This demonstrates that the highly ordered porous structure on the micron scale which typifies the morphology that can be achieved with the hydrogen bubbling template method is not required in producing the most effective material.

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Anatase TiO2 nanocrystals were painted on H-titanate nanofibers by using an aqueous solution of titanyl sulfate. The anatase nanocrystals were bonded solidly onto the titanate fibers through formation of coherent interfaces at which the oxygen atoms were shared by the nanocrystals and the fiber. This approach allowed us to create large anatase surfaces on the nanofibers, which are active in photocatalytic reactions. This method was also applied successfully to coat anatase nanocrystals on surfaces of fly ash and layered clay. The painted nanofibers exhibited a much higher catalytic activity for the photocatalytic degradation of sulforhodamine B and the selective oxidation of benzylamine to the corresponding imine (with a product selectivity >99%) under UV irradiation than both the parent H-titanate nanofibers and a commercial TiO2 powder, P25. We found that gold nanoparticles supported on H-titanate nanofibers showed no catalytic activity for the reduction of nitrobenzene to azoxybenzene, whereas the gold nanoparticles supported on the painted nanofibers and P25 could efficiently reduce nitrobenzene to azoxybenzene as the sole product under visible light irradiation. These results were different from those from the reduction on the gold nanoparticles photocatalyst on ZrO2, in which the azoxybenzene was the intermediate and converted to azobenzene quickly. Evidently, the support materials significantly affect the product selectivity of the nitrobenzene reduction. Finally, the new photocatalysts could be easily dispersed into and separated from a liquid because of their fibril morphology, which is an important advantage for practical applications.

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Traffic accidents often cause lane closure, and diminish stability of travel time as well as the level of road services. On the other hand, research on the implementation of ITS services aiming at the reduction of traffic accidents has made considerable progress lately. However there has been little discussion on the benefits obtained by traffic accident reduction from the view point of travel time reliability. Therefore, in this research, relationships between traffic accidents and travel time reliability are examined, and the benefit of traffic accident reduction is calculated based on the scheduling model under travel time uncertainties. The results show the significance of traffic accident reduction for the improvement of travel time reliability.

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Capacity reduction programmes, in the form of buybacks or decommissioning, have had relatively widespread application in fisheries in the US, Europe and Australia. A common criticism of such programmes is that they remove the least efficient vessels first, resulting in an increase in average efficiency of the remaining fleet, which tends to increase the effective fishing power of the remaining fleet. In this paper, the effects of a buyback programme on average technical efficiency in Australia’s Northern Prawn Fishery are examined using a multi-output production function approach with an explicit inefficiency model. As expected, the results indicate that average efficiency of the remaining vessels was generally greater than that of the removed vessels. Further, there was some evidence of an increase in average scale efficiency in the fleet as the remaining vessels were closer, on average, to the optimal scale. Key factors affecting technical efficiency included company structure and the number of vessels fishing. In regard to fleet size, our model suggests positive externalities associated with more boats fishing at any point in time (due to information sharing and reduced search costs), but also negative externalities due to crowding, with the latter effect dominating the former. Hence, the buyback resulted in a net increase in the individual efficiency of the remaining vessels due to reduced crowding, as well as raising average efficiency through removal of less efficient vessels.

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This work investigated the impact of the HVAC filtration system and indoor particle sources on the relationship between indoor and outdoor airborne particle size and concentrations in an operating room. Filters with efficiency between 65% and 99.97% were used in the investigation and indoor and outdoor particle size and concentrations were measured. A balance mass model was used for the simulation of the impact of the surgical team, deposition rate, HVAC exhaust and air change rates on indoor particle concentration. The experimental results showed that high efficiency filters would not be expected to decrease the risk associated with indoor particles larger than approximately 1 µm in size because normal filters are relatively efficient for these large particles. A good fraction of outdoor particles were removed by deposition on the HVAC system surfaces and this deposition increased with particle size. For particles of 0.3-0.5 µm in diameter, particle reduction was about 23%, while for particles >10 µm the loss was about 78%. The modelling results showed that depending on the type of filter used, the surgical team generated between 93-99% of total particles, while the outdoor air contributed only 1-6%.

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Introduction The consistency of measuring small field output factors is greatly increased by reporting the measured dosimetric field size of each factor, as opposed to simply stating the nominal field size [1] and therefore requires the measurement of cross-axis profiles in a water tank. However, this makes output factor measurements time consuming. This project establishes at which field size the accuracy of output factors are not affected by the use of potentially inaccurate nominal field sizes, which we believe establishes a practical working definition of a ‘small’ field. The physical components of the radiation beam that contribute to the rapid change in output factor at small field sizes are examined in detail. The physical interaction that dominates the cause of the rapid dose reduction is quantified, and leads to the establishment of a theoretical definition of a ‘small’ field. Methods Current recommendations suggest that radiation collimation systems and isocentre defining lasers should both be calibrated to permit a maximum positioning uncertainty of 1 mm [2]. The proposed practical definition for small field sizes is as follows: if the output factor changes by ±1.0 % given a change in either field size or detector position of up to ±1 mm then the field should be considered small. Monte Carlo modelling was used to simulate output factors of a 6 MV photon beam for square fields with side lengths from 4.0 to 20.0 mm in 1.0 mm increments. The dose was scored to a 0.5 mm wide and 2.0 mm deep cylindrical volume of water within a cubic water phantom, at a depth of 5 cm and SSD of 95 cm. The maximum difference due to a collimator error of ±1 mm was found by comparing the output factors of adjacent field sizes. The output factor simulations were repeated 1 mm off-axis to quantify the effect of detector misalignment. Further simulations separated the total output factor into collimator scatter factor and phantom scatter factor. The collimator scatter factor was further separated into primary source occlusion effects and ‘traditional’ effects (a combination of flattening filter and jaw scatter etc.). The phantom scatter was separated in photon scatter and electronic disequilibrium. Each of these factors was plotted as a function of field size in order to quantify how each affected the change in small field size. Results The use of our practical definition resulted in field sizes of 15 mm or less being characterised as ‘small’. The change in field size had a greater effect than that of detector misalignment. For field sizes of 12 mm or less, electronic disequilibrium was found to cause the largest change in dose to the central axis (d = 5 cm). Source occlusion also caused a large change in output factor for field sizes less than 8 mm. Discussion and conclusions The measurement of cross-axis profiles are only required for output factor measurements for field sizes of 15 mm or less (for a 6 MV beam on Varian iX linear accelerator). This is expected to be dependent on linear accelerator spot size and photon energy. While some electronic disequilibrium was shown to occur at field sizes as large as 30 mm (the ‘traditional’ definition of small field [3]), it has been shown that it does not cause a greater change than photon scatter until a field size of 12 mm, at which point it becomes by far the most dominant effect.

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The purpose of this study was to investigate the effect of very small air gaps (less than 1 mm) on the dosimetry of small photon fields used for stereotactic treatments. Measurements were performed with optically stimulated luminescent dosimeters (OSLDs) for 6 MV photons on a Varian 21iX linear accelerator with a Brainlab lMLC attachment for square field sizes down to 6 mm 9 6 mm. Monte Carlo simulations were performed using EGSnrc C++ user code cavity. It was found that the Monte Carlo model used in this study accurately simulated the OSLD measurements on the linear accelerator. For the 6 mm field size, the 0.5 mm air gap upstream to the active area of the OSLD caused a 5.3 % dose reduction relative to a Monte Carlo simulation with no air gap...

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Purpose Accelerometers are recognized as a valid and objective tool to assess free-living physical activity. Despite the widespread use of accelerometers, there is no standardized way to process and summarize data from them, which limits our ability to compare results across studies. This paper a) reviews decision rules researchers have used in the past, b) compares the impact of using different decision rules on a common data set, and c) identifies issues to consider for accelerometer data reduction. Methods The methods sections of studies published in 2003 and 2004 were reviewed to determine what decision rules previous researchers have used to identify wearing period, minimal wear requirement for a valid day, spurious data, number of days used to calculate the outcome variables, and extract bouts of moderate to vigorous physical activity (MVPA). For this study, four data reduction algorithms that employ different decision rules were used to analyze the same data set. Results The review showed that among studies that reported their decision rules, much variability was observed. Overall, the analyses suggested that using different algorithms impacted several important outcome variables. The most stringent algorithm yielded significantly lower wearing time, the lowest activity counts per minute and counts per day, and fewer minutes of MVPA per day. An exploratory sensitivity analysis revealed that the most stringent inclusion criterion had an impact on sample size and wearing time, which in turn affected many outcome variables. Conclusions These findings suggest that the decision rules employed to process accelerometer data have a significant impact on important outcome variables. Until guidelines are developed, it will remain difficult to compare findings across studies

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The aim of this study was to examine the effect of endurance training on skeletal muscle phospholipid molecular species from high-fat fed rats. Twelve female Sprague-Dawley rats were fed a high-fat diet (78.1% energy). The rats were randomly divided into two groups, a sedentary control group and a trained group (125 min of treadmill running at 8 m/min, 4 days/wk for 4 weeks). Forty-eight hours after their last training bout phospholipids were extracted from the red and white vastus lateralis and analyzed by electrospray-ionization mass spectrometry. Exercise training was associated with significant alterations in the relative abundance of a number of phospholipid molecular species. These changes were more prominent in red vastus lateralis than white vastus lateralis. The largest observed change was an increase of similar to 30% in the abundance of 1-palmitoyl-2-linoleoyl phosphatidylcholine ions in oxidative fibers. Reductions in the relative abundance of a number of phospholipids containing long-chain n-3 polyunsaturated fatty acids were also observed. These data suggest a possible reduction in phospholipid remodeling in the trained animals. This results in a decrease in the phospholipid n-3 to n-6 ratio that may in turn influence endurance capacity.

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The acyl composition of membrane phospholipids in kidney and brain of mammals of different body mass was examined. It was hypothesized that reduction in unsaturation index (number of double bonds per 100 acyl chains) of membrane phospholipids with increasing body mass in mammals would be made-up of similar changes in acyl composition across all phospholipid classes and that phospholipid class distribution would be regulated and similar in the same tissues of the different-sized mammals. The results of this study supported both hypotheses. Differences in membrane phospholipid acyl composition (i. e. decreased omega-3 fats, increased monounsaturated fats and decreased unsaturation index with increasing body size) were not restricted to any specific phospholipid molecule or to any specific phospholipid class but were observed in all phospholipid classes. With increase in body mass of mammals both monounsaturates and use of less unsaturated polyunsaturates increases at the expense of the long-chain highly unsaturated omega-3 and omega-6 polyunsaturates, producing decreases in membrane unsaturation. The distribution of membrane phospholipid classes was essentially the same in the different-sized mammals with phosphatidylcholine (PC) and phosphatidylethanolamine (PE) together constituting similar to 91% and similar to 88% of all phospholipids in kidney and brain, respectively. The lack of sphingomyelin in the mouse tissues and higher levels in larger mammals suggests an increased presence of membrane lipid rafts in larger mammals. The results of this study support the proposal that the physical properties of membranes are likely to be involved in changing metabolic rate.

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Background Accelerometers have become one of the most common methods of measuring physical activity (PA). Thus, validity of accelerometer data reduction approaches remains an important research area. Yet, few studies directly compare data reduction approaches and other PA measures in free-living samples. Objective To compare PA estimates provided by 3 accelerometer data reduction approaches, steps, and 2 self-reported estimates: Crouter's 2-regression model, Crouter's refined 2-regression model, the weighted cut-point method adopted in the National Health and Nutrition Examination Survey (NHANES; 2003-2004 and 2005-2006 cycles), steps, IPAQ, and 7-day PA recall. Methods A worksite sample (N = 87) completed online-surveys and wore ActiGraph GT1M accelerometers and pedometers (SW-200) during waking hours for 7 consecutive days. Daily time spent in sedentary, light, moderate, and vigorous intensity activity and percentage of participants meeting PA recommendations were calculated and compared. Results Crouter's 2-regression (161.8 +/- 52.3 minutes/day) and refined 2-regression (137.6 +/- 40.3 minutes/day) models provided significantly higher estimates of moderate and vigorous PA and proportions of those meeting PA recommendations (91% and 92%, respectively) as compared with the NHANES weighted cut-point method (39.5 +/- 20.2 minutes/day, 18%). Differences between other measures were also significant. Conclusions When comparing 3 accelerometer cut-point methods, steps, and self-report measures, estimates of PA participation vary substantially.

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Plant tissue has a complex cellular structure which is an aggregate of individual cells bonded by middle lamella. During drying processes, plant tissue undergoes extreme deformations which are mainly driven by moisture removal and turgor loss. Numerical modelling of this problem becomes challenging when conventional grid-based modelling techniques such as Finite Element Methods (FEM) and Finite Difference Methods (FDM) have grid-based limitations. This work presents a meshfree approach to model and simulate the deformations of plant tissues during drying. This method demonstrates the fundamental capabilities of meshfree methods in handling extreme deformations of multiphase systems. A simplified 2D tissue model is developed by aggregating individual cells while accounting for the stiffness of the middle lamella. Each individual cell is simply treated as consisting of two main components: cell fluid and cell wall. The cell fluid is modelled using Smoothed Particle Hydrodynamics (SPH) and the cell wall is modelled using a Discrete Element Method (DEM). During drying, moisture removal is accounted for by reduction of cell fluid and wall mass, which causes local shrinkage of cells eventually leading to tissue scale shrinkage. The cellular deformations are quantified using several cellular geometrical parameters and a favourably good agreement is observed when compared to experiments on apple tissue. The model is also capable of visually replicating dry tissue structures. The proposed model can be used as a step in developing complex tissue models to simulate extreme deformations during drying.