1,172 research outputs found

    Material and Design Considerations for a Portable Ultra-Violet (UV) Light Emitting Diode (LED) Water Purification Device

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    Department of Defense personnel often deploy to austere environments where clean water is not readily available. Ultraviolet (UV) radiation through the use of light emitting diodes (LEDs) in a portable device offers a potential method for expedient water treatment. This research studied the application of one diode, low power, UV LEDs and nine diode, high power, UV LEDs within a portable steel reactor and Teflon reactors of three different wall thicknesses. Reactor efficiency was determined through measuring and comparing the rate constants for Advanced Oxidation of hydrogen peroxide with yellow tartrazine as a witness dye. Experiments conducted with low power UV LEDs indicate that the medium thickness reactor has a statistically significant higher rate constant than the steel and thin cylinder reactors. All high power UV LED tests had rate constants ten times higher than the low UV LEDs, but exhibited no significant difference between materials or thicknesses. Additionally, this research examined the microorganism inactivation in the optimum reactor by exposing E. coli to UV radiation. The experiments demonstrated complete reduction of E. coli at a flow rate up to 15 mL/min, and a 2-Log reduction at 20 mL/min, thus demonstrating proof of concept for future portable UV LED disinfection units

    Quantitative study of quasi-one-dimensional Bose gas experiments via the stochastic Gross-Pitaevskii equation

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    The stochastic Gross-Pitaevskii equation is shown to be an excellent model for quasi-one-dimensional Bose gas experiments, accurately reproducing the in situ density profiles recently obtained in the experiments of Trebbia et al. [Phys. Rev. Lett. 97, 250403 (2006)] and van Amerongen et al. [Phys. Rev. Lett. 100, 090402 (2008)], and the density fluctuation data reported by Armijo et al. [Phys. Rev. Lett. 105, 230402 (2010)]. To facilitate such agreement, we propose and implement a quasi-one-dimensional stochastic equation for the low-energy, axial modes, while atoms in excited transverse modes are treated as independent ideal Bose gases.Comment: 10 pages, 5 figures; updated figures with experimental dat

    Phase coherence in quasicondensate experiments: an ab initio analysis via the stochastic Gross-Pitaevskii equation

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    We perform an ab initio analysis of the temperature dependence of the phase coherence length of finite temperature, quasi-one-dimensional Bose gases measured in the experiments of Richard et al. (Phys. Rev. Lett. 91, 010405 (2003)) and Hugbart et al. (Eur. Phys. J. D 35, 155-163 (2005)), finding very good agreement across the entire observed temperature range (0.8<T/Tϕ<280.8<T/T_{\phi}<28). Our analysis is based on the one-dimensional stochastic Gross-Pitaevskii equation, modified to self-consistently account for transverse, quasi-one-dimensional effects, thus making it a valid model in the regime μ fewω\mu ~ few \hbar \omega_\perp. We also numerically implement an alternative identification of TϕT_{\phi}, based on direct analysis of the distribution of phases in a stochastic treatment.Comment: Amended manuscript with improved agreement to experiment, following some additional clarifications by Mathilde Hugbart and Fabrice Gerbier and useful comments by the reviewer; accepted for publication in Physical Review

    Steam - oxygen gasification of refuse derived fuel in fluidized beds: Modelling and pilot plant testing

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    A one-dimensional kinetic model for steam‑oxygen gasification of refuse derived fuel in a bubbling fluidized bed reactor has been developed. The model incorporates the reaction network of steam‑oxygen gasification within the fluid dynamics of a fluidized bed to predict waste and tars conversion, gas composition and overall gasification performance. The model was validated by comparing outlet products composition and temperature profile with experimental data from a pilot-scale fluidized bed gasifier, operated at different conditions. The model showed accurate predictive capability and ease of computation. The effects of the operating conditions on gas yield and process efficiency were evaluated and the most appropriate fuel feeding height, equivalent ratio and the relative amount of steam to inject were identified

    7-Bromo-4b-methyl-7,8-dihydro-4bH-9-thia-8a-aza­fluorene 9,9-dioxide

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    The title compound, C12H12BrNO2S, was isolated after direct irradiation (hν 350 nm, hexa­ne) of a mixture of stereoisomeric sulfonamides containing a vicinal dibromide and a conjugated diene. This product is one of a group of substrates that has contributed to our understanding of the photoreactivity patterns of non-bridged sulfonamides. The crystal structure was determined from a non-merohedrally twinned data set, where the twin law corresponded to a 180° rotation about the a* axis. The minor twin component refined to a value of 0.176 (3). The conformation of the mol­ecule is planar at one end, as the benzene ring and the adjacent fused five-membered ring are coplanar, and U-shaped at the other end, where the five-membered ring is fused to the heterocyclic six-membered ring containing an allyl bromide group

    Respondents of health survey powered by the innovative NURO app exhibit correlations between exercise frequencies and diet habits, and between stress levels and sleep wellness

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    Nurosene's NURO app (nurosene.com) is an innovative smartphone application that gathers and analyzes active self-report metrics from users, empowering them with data-driven health machine intelligence. We present the data collected and analyzed from the initial round of participants who responded to a 12-question survey on their life-style and health status. Exploratory results using a variational autoencoder (VAE) suggested that much of the variability of the 12 dimensional data could be accounted for by two approximately uncorrelated latent variables: one pertaining to stress and sleep, and the other pertaining to exercise and diet. Subsequent modeling of the data using exploratory and confirmatory factor analyses (EFAs and CFAs) found that optimal data fits consisted of four factors, namely exercise, diet, stress, and sleep. Covariance values were high between exercise and diet, and between stress and sleep, but much lower between other pairings of non-identical factors. Both EFAs and CFAs provided extra contexts to and quantified the more preliminary VAE observations. Overall, our results significantly reduce the apparent complexity of the response data. This reduction allows for more efficient future stratification and analyses of participants based on simpler latent variables. Our discovery of novel relationships between stress and sleep, and between exercise and diet suggests the possibility of applying predictive analytics in future efforts
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