49 research outputs found

    CO<sub>2</sub> Adsorption Behavior and Kinetics on Amine-Functionalized Composites Silica with Trimodal Nanoporous Structure

    No full text
    A trimodal porous support with special trimodal pore structure has been prepared by physically mixing the silica gel (HPS) and SBA-15 and then devoted to fabricate TEPA<b>-</b>functionalized adsorbent for CO<sub>2</sub> capture. The trimodal multistage mesopores structure can promote the TEPA dispersion and mitigate the mass-transfer resistance in the adsorbent and, hence, improve capture performance, compared to the single mesoporous support. The influence of the mass ratios of HPS to SBA-15, amine loaded amount, CO<sub>2</sub> concentration, adsorption temperatures, and water vapor were studied. The CO<sub>2</sub>-saturated adsorption amount of 5.05 mmol/g was obtained at 75 °C in dry N<sub>2</sub> flow containing 15 vol % CO<sub>2</sub> when the mass ratio of SBA-15 to HPS was 1:2 with 50 wt % TEPA loadings. Moreover, the CO<sub>2</sub>-saturated adsorption amount presented a 16% improvement in humid N<sub>2</sub> flow containing 15 vol % CO<sub>2</sub> flow at 75 °C. In addition, the S2HPS-TEPA50% also demonstrated good stability after 10 adsorption/desorption cycles. Based on in situ DRIFTS results of CO<sub>2</sub> adsorption/desorption process, the reaction mechanism of CO<sub>2</sub> with active sites was proposed by analyzing the relationships among variations of intensities of functional groups during the reaction. The intraparticle diffusion model was adapted to study CO<sub>2</sub> kinetics and the intraparticle diffusion prediction indicated that boundary layer diffusion was the rate-controlling step in the process of CO<sub>2</sub> capture. Overall, these results indicate that S2HPS-TEPA50% is promising for CO<sub>2</sub> capture

    Characteristics of Competitors in Natural Survivals

    No full text
    Title: Characteristics ofcompetitors in natural survivals Aim: This graduation paper brings a comprehensive overview about the sport branch "natural survival", its organization, structure and race character. The main aim is to :find the characteristics of a group of competitors, their preparation, equipment, way of living and specializations. Method: Research material for our graduation paper has been collected through: Results: Quantitative data collection - a questionnaire. Document analysis, analysis of written materials and websites - qualitative content analysis. Preparation ofcompetitors for these races is not speci:fic. Race attractiveness decides the most about the competitors' participation in individua! races, and race duration decides the least. It is possible to include these races for testing skills, abilities and team cooperation for common sports people with the doser relation to outdoor sports. Comparison of number of competitors in the last years has confinned that the number ofcompetitors has settled down. A new sport branch "natural survival" has been formed. Keywords: Natural survival, sociological research, competitors' preparation and equipment, communication. Strana

    Additional file 14: Figure S4. of Bone-associated gene evolution and the origin of flight in birds

    No full text
    Body mass association with ω (dN/dS). Avian cladogram showing from CoEvol, the labels are the estimated ω (minimum maximum) for each branch on top and the estimated weight (minimum maximum). (DOC 423 kb

    Additional file 15: Table S11. of Bone-associated gene evolution and the origin of flight in birds

    No full text
    Covariance between dS, ω (dN/dS), gc content, and the three body mass measures (minimum, maximum and average) in 45 bird genomes using gene-based tree. The upper triangle shows the values obtained for all birds and the lower triangle excluding flightless birds. Each cell represent the covariance values and posterior probability are the bracketed values, posterior probability (** - < = 0.025 or > =0.975; * - < =0.05 or > =0.95) are highlighted in bold for the statistically significant correlations. (DOC 35 kb

    Additional file 16: Table S12. of Bone-associated gene evolution and the origin of flight in birds

    No full text
    Covariance between dS, ω (dN/dS), gc content, and the three body mass measures (minimum, maximum and average) in 39 mammalian genomes using gene-based tree. The upper triangle shows the values obtained for all mammals and the lower triangle excluding bats. Each cell represent the covariance values and posterior probability are the bracketed values, posterior probability (** - < = 0.025 or > =0.975; * - < =0.05 or > =0.95) are highlighted in bold for the statistically significant correlations. (DOC 35 kb

    Additional file 19: Table S13. of Bone-associated gene evolution and the origin of flight in birds

    No full text
    Estimation of dN and dS for each branch under Model 0. For each branch, average of dN and dS and the corresponding standard deviation. (DOC 165 kb

    Additional file 4: Table S2. of Bone-associated gene evolution and the origin of flight in birds

    No full text
    Positively selected sites of bone-associated genes in Mammalian dataset after multiple testing correction. The alignment length is on Amino acids (aa). Gene in bold are positively selected under the comparison M2a vs M1a. Q-value estimations for multiple testing are represented as positive selected (1) and negative selected (0). (DOC 88 kb

    Additional file 11: Table S8. of Bone-associated gene evolution and the origin of flight in birds

    No full text
    Results from the nested models (M0, M1a, M2a) likelihood ratio test results PAML from Mammalian dataset excluding bats. The alignment length is on Amino acids (aa). Bold represents statistical significance (p < 0.05). Q-value estimations for multiple testing are represented as positive selected (1) and negative selected (0). (DOC 162 kb

    Additional file 12: Table S9. of Bone-associated gene evolution and the origin of flight in birds

    No full text
    Branch model for birds. Bold represents statistical significance (p < 0.05). Q-value estimations for multiple testing are represented as positive selected (1) and negative selected (0). (DOC 114 kb
    corecore