Titanium-oxide magneli phases in four chondritic porous interplanetary dust particles

Detailed analytical electron microscope analyses of four fine-grained chondritic porous interplanetary dust particles (IDPs)reveal the presence of titanium oxide Magneli phases, TinO2n-1 (n=4,5,6), and rare Ti-metal. The titanium minerals are indigenous to these chondritic IDPs. The association of Magneli phases, Ti-metal, and carbonaceous material in chondritic IDPs, along with the grain size distributions support in situ solid carbon gasification in these extraterrestrial particles. The active catalyst in this process is titanium metal that we infer may be of interstellar origin. This favorable catalysis uniquely leads to the formation of Magneli phases. As chondritic IDPs may be solid debris of short-period comets, our data indicate that nuclei of short-period comets may show distinctive chemical reactions that lead to Ti-mineral assemblages that typically include Magneli phases. The proposed model provides a plausible mechnism to explain the higher solid carbon content of chondritic IDPs relative to bulk carbon abundances typical for carbonaceous chondrite matrices that represent another type of more evolved, that is, metamorphosed, undifferentiated solar system bodies.

Contemporaneous correlations within individuals in an automated web-based walking program (Walk@Work) over a six week period (three phases) of time

Introduction: Participants may respond to phases of a workplace walking program at different rates. This study evaluated the factors that contribute to the number of steps through phases of the program. The intervention was automated through a web-based program designed to increase workday walking. Methods: The study reviewed independent variable influences throughout phases I–III. A convenience sample of university workers (n=56; 43.6±1.7 years; BMI 27.44±.2.15 kg/m2; 48 female) were recruited at worksites in Australia. These workers were given a pedometer (Yamax SW 200) and access to the website program. For analyses, step counts entered by workers into the website were downloaded and mean workday steps were compared using a seemingly unrelated regression. This model was employed to capture the contemporaneous correlation within individuals in the study across observed time periods. Results: The model predicts that the 36 subjects with complete information took an average 7460 steps in the baseline two week period. After phase I, statistically significance increases in steps (from baseline) were explained by age, working status (full or part time), occupation (academic or professional), and self reported public transport (PT) use (marginally significant). Full time workers walked more than part time workers by about 440 steps, professionals walked about 300 steps more than academics, and PT users walked about 400 steps more than non-PT users. The ability to differentiate steps after two weeks among participants suggests a differential affect of the program after only two weeks. On average participants increased steps from week two to four by about 525 steps, but regular auto users had nearly 750 steps less than non-auto users at week four. The effect of age was diminished in the 4th week of observation and accounted for 34 steps per year of age. In phase III, discriminating between participants became more difficult, with only age effects differentiating their increase over baseline. The marginal effect of age by phase III compared to phase I, increased from 36 to 50, suggesting a 14 step per year increase from the 2nd to 6th week. Discussion: The findings suggest that participants responded to the program at different rates, with uniformity of effect achieved by the 6th week. Participants increased steps, however a tapering off occurred over time. Age played the most consistent role in predicting steps over the program. PT use was associated with increased step counts, while Auto use was associated with decreased step counts.

Advantages of tandem LC-MS for the rapid assessment of tissue-specific metabolic complexity using a pentafluorophenylpropyl stationary phase

In this study, a tandem LC-MS (Waters Xevo TQ) MRM-based MS method was developed for rapid, broad profiling of hydrophilic metabolites from biological samples, in either positive or negative ion modes without the need for an ion pairing reagent, using a reversed-phase pentafluorophenylpropyl (PFPP) column. The developed method was successfully applied to analyze various biological samples from C57BL/6 mice, including urine, duodenum, liver, plasma, kidney, heart, and skeletal muscle. As result, a total 112 of hydrophilic metabolites were detected within 8 min of running time to obtain a metabolite profile of the biological samples. The analysis of this number of hydrophilic metabolites is significantly faster than previous studies. Classification separation for metabolites from different tissues was globally analyzed by PCA, PLS-DA and HCA biostatistical methods. Overall, most of the hydrophilic metabolites were found to have a "fingerprint" characteristic of tissue dependency. In general, a higher level of most metabolites was found in urine, duodenum, and kidney. Altogether, these results suggest that this method has potential application for targeted metabolomic analyzes of hydrophilic metabolites in a wide ranges of biological samples.

Beliefs underlying blood donors’ intentions to donate during two phases of an avian influenza outbreak

Using a Theory of Planned Behavior (TPB) framework the current study explored the beliefs of current blood donors (N=172) about donating during a low and high-risk phase of a potential avian influenza outbreak. While the majority of behavioral, normative, and control beliefs identified in preliminary research differed as a function of donors’ intentions to donate during both phases of an avian influenza outbreak, regression analyses suggested that the targeting of different specific beliefs during each phase of an outbreak would yield most benefit in bolstering donors’ intentions to remain donating. The findings provide insight in how to best motivate donors in different phases of an avian influenza outbreak.

TiO2 nanofibers of different crystal phases for transesterification of alcohols with dimethyl carbonate

TiO2 nanofibers with different crystal phases have been discovered to be efficient catalysts for the transesterification of alcohols with dimethyl carbonate to produce corresponding methyl carbonates. Advantages of this catalytic system include excellent selectivity (>99%), general suitability to alcohols, reusability and ease of preparation and separation of fibrous catalysts. Activities of TiO2 catalysts were found to correlate with their crystal phases which results in different absorption abilities and activation energies on the catalyst surfaces. The kinetic isotope effect (KIE) investigation identified the rate-determining step, and the isotope labeling of oxygen-18 of benzyl alcohol clearly demonstrated the reaction pathway. Finally, the transesterification mechanism of alcohols with dimethyl carbonate catalyzed by TiO2 nanofibers was proposed, in which the alcohol released the proton to form benzyl alcoholic anion, and subsequently the anion attacks the carbonyl carbon of dimethyl carbonate to produce the target product of benzyl methyl carbonate.

Eight weeks of episodic visual navigation inside a non-stationary environment using adaptive spherical views

This paper presents a long-term experiment where a mobile robot uses adaptive spherical views to localize itself and navigate inside a non-stationary office environment. The office contains seven members of staff and experiences a continuous change in its appearance over time due to their daily activities. The experiment runs as an episodic navigation task in the office over a period of eight weeks. The spherical views are stored in the nodes of a pose graph and they are updated in response to the changes in the environment. The updating mechanism is inspired by the concepts of long- and short-term memories. The experimental evaluation is done using three performance metrics which evaluate the quality of both the adaptive spherical views and the navigation over time.

The combination of empirical mode decomposition and minimum entropy deconvolution for roller bearing diagnostics in non-stationary operation

Diagnostics is based on the characterization of mechanical system condition and allows early detection of a possible fault. Signal processing is an approach widely used in diagnostics, since it allows directly characterizing the state of the system. Several types of advanced signal processing techniques have been proposed in the last decades and added to more conventional ones. Seldom, these techniques are able to consider non-stationary operations. Diagnostics of roller bearings is not an exception of this framework. In this paper, a new vibration signal processing tool, able to perform roller bearing diagnostics in whatever working condition and noise level, is developed on the basis of two data-adaptive techniques as Empirical Mode Decomposition (EMD), Minimum Entropy Deconvolution (MED), coupled by means of the mathematics related to the Hilbert transform. The effectiveness of the new signal processing tool is proven by means of experimental data measured in a test-rig that employs high power industrial size components.

Voltage unbalance reduction in low voltage feeders by dynamic switching of residential customers among three phases

Low voltage distribution feeders with large numbers of single phase residential loads experience severe current unbalance that often causes voltage unbalance problems. The addition of intermittent generation and new loads in the form of roof top photovoltaic generation and electric vehicles makes these problems even more acute. In this paper, an intelligent dynamic residential load transfer scheme is proposed. Residential loads can be transferred from one phase to another phase to minimize the voltage unbalance along the feeder. Each house is supplied through a static transfer switch with three-phase input and single-phase output connection. The main controller, installed at the transformer will observe the power consumption in each load and determine which house(s) should be transferred from one phase to another in order to keep the voltage unbalance in the feeder at a minimum. The efficacy of the proposed load transfer scheme is verified through MATLAB and PSCAD/EMTDC simulations.

Learning detectors quickly with stationary statistics

Computer vision is increasingly becoming interested in the rapid estimation of object detectors. The canonical strategy of using Hard Negative Mining to train a Support Vector Machine is slow, since the large negative set must be traversed at least once per detector. Recent work has demonstrated that, with an assumption of signal stationarity, Linear Discriminant Analysis is able to learn comparable detectors without ever revisiting the negative set. Even with this insight, the time to learn a detector can still be on the order of minutes. Correlation filters, on the other hand, can produce a detector in under a second. However, this involves the unnatural assumption that the statistics are periodic, and requires the negative set to be re-sampled per detector size. These two methods differ chie y in the structure which they impose on the co- variance matrix of all examples. This paper is a comparative study which develops techniques (i) to assume periodic statistics without needing to revisit the negative set and (ii) to accelerate the estimation of detectors with aperiodic statistics. It is experimentally verified that periodicity is detrimental.

Impinging jet simulation of stationary downburst flow over topography

A non-translating, long duration thunderstorm downburst has been simulated experimentally and numerically by modelling a spatially stationary steady flow impinging air jet. Velocity profiles were shown to compare well with an upper-bound of velocity measurements reported for full-scale microbursts. Velocity speed-up over a range of topographic features in simulated downburst flow was also tested with comparisons made to previous work in a similar flow, and also boundary layer wind tunnel experiments. It was found that the amplification measured above the crest of topographic features in simulated downburst flow was up to 35% less than that observed in boundary layer flow for all shapes tested. From the computational standpoint we conclude that the Shear Stress Transport (SST) model performs the best from amongst a range of eddy-viscosity and second moment closures tested for modelling the impinging jet flow.

Pulsed wall jet simulation of a stationary thunderstorm downburst, Part A: Physical structure and flow field characterization

A pulsed wall jet has been used to simulate the gust front of a thunderstorm downburst. Flow visualization, wind speed and surface pressure measurements were obtained. The characteristics of the hypothesized ring vortex of a full-scale downburst were reproduced at a scale estimated to be 1:3000.

Multiple map hypotheses for planning and navigating in non-stationary environments

This paper presents a method to enable a mobile robot working in non-stationary environments to plan its path and localize within multiple map hypotheses simultaneously. The maps are generated using a long-term and short-term memory mechanism that ensures only persistent configurations in the environment are selected to create the maps. In order to evaluate the proposed method, experimentation is conducted in an office environment. Compared to navigation systems that use only one map, our system produces superior path planning and navigation in a non-stationary environment where paths can be blocked periodically, a common scenario which poses significant challenges for typical planners.

The importance of use and end-of-life phases to the life cycle greenhouse gas (GHG) emissions of concrete : a review

Global climate change is one of the most significant environmental impacts at the moment. One central issue for the building and construction industry to address global climate change is the development of credible carbon labelling schemes for building materials. Various carbon labelling schemes have been developed for concrete due to its high contribution to global greenhouse gas (GHG) emissions. However, as most carbon labelling schemes adopt cradle-to-gate as system boundary, the credibility of the eco-label information may not be satisfactory because recent studies show that the use and end-of-life phases can have a significant impact on the life cycle GHG emissions of concrete in terms of carbonation, maintenance and rehabilitation, other indirect emissions, and recycling activities. A comprehensive review on the life cycle assessment of concrete is presented to holistically examine the importance of use and end-of-life phases to the life cycle GHG quantification of concrete. The recent published ISO 14067: Carbon footprint of products – requirements and guidelines for quantification and communication also mandates the use of cradle-to-grave to provide publicly available eco-label information when the use and end-of-life phases of concrete can be appropriately simulated. With the support of Building Information Modelling (BIM) and other simulation technologies, the contribution of use and end-of-life phases to the life cycle GHG emissions of concrete should not be overlooked in future studies.

Effective control of nanostructured phases in rapid, room-temperature synthesis of nanocrystalline Si in high-density plasmas

An innovative and effective approach based on low-pressure, low-frequency, thermally nonequilibrium, high-density inductively coupled plasmas is proposed to synthesize device-quality nanocrystalline silicon (nc-Si) thin films at room temperature and with very competitive growth rates. The crystallinity and microstructure properties (including crystal structure, crystal volume fraction, surface morphology, etc.) of this nanostructured phase of Si can be effectively tailored in broad ranges for different device applications by simply varying the inductive rf power density from 25.0 to 41.7 mW/cm3. In particular, at a moderate rf power density of 41.7 mW/cm3, the nc-Si films feature a very high growth rate of 2.37 nm/s, a high crystalline fraction of 86%, a vertically aligned columnar structure with the preferential (111) growth orientation and embedded Si quantum dots, as well as a clean, smooth and defect-free interface. We also propose the formation mechanism of nc-Si thin films which relates the high electron density and other unique properties of the inductively coupled plasmas and the formation of the nanocrystalline phase on the Si surface.