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RISS 인기검색어
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- 저자 : Brian McDonald (검색결과 4 건)
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McDonald, ThomasM.,Lee, Woo Ram,Mason, Jarad A.,Wiers, Brian M.,Hong, Chang Seop,Long, Jeffrey R. American Chemical Society 2012 JOURNAL OF THE AMERICAN CHEMICAL SOCIETY - Vol.134 No.16
<P>Two new metal organic frameworks, M-2(dobpdc) (M = Zn (1), Mg (2); dobpdc(4-) = 4,4'-dioxido-3,3'-biphenyldicarboxylate), adopting an expanded MOF-74 structure type, were synthesized via solvothermal and microwave methods. Coordinatively unsaturated Mg2+ cations lining the 18.4-angstrom-diameter channels of 2 were functionalized with N,N'-dimethylethylenediamine (mmen) to afford Mg-2(dobpdc)-(mmen)(1.6)(H2O)(0.4) (mmen-Mg-2(dobpdc)). This compound displays an exceptional capacity for CO2 adsorption at low pressures, taking up 2.0 mmol/g (8.1 wt %) at 0.39 mbar and 25 degrees C, conditions relevant to removal of CO2 from air, and 3.14 mmol/g (12.1 wt %) at 0.15 bar and 40 degrees C, conditions relevant to CO2 capture from flue gas. Dynamic gas adsorption/desorption cycling experiments demonstrate that mmen-Mg-2(dobpdc) can be regenerated upon repeated exposures to simulated air and flue gas mixtures, with cycling capacities of 1.05 mmol/g (4.4 wt %) after 1 h of exposure to flowing 390 ppm CO2 in simulated air at 25(degrees)C and 2.52 mmol/g (9.9 wt %) after 15 min of exposure to flowing 15% CO2 in N-2 at 40 degrees C. The purity of the CO2 removed from dry air and flue gas in these processes was estimated to be 96% and 98%, respectively. As a flue gas adsorbent, the regeneration energy was estimated through differential scanning calorimetry experiments to be 2.34 MJ/kg CO2 adsorbed. Overall, the performance characteristics of mmen-Mg-2(dobpdc) indicate it to be an exceptional new adsorbent for CO2 capture, comparing favorably with both amine-grafted silicas and aqueous amine solutions.</P>
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Liu Ying,Zhang Xin,Zhang Li,Oliver Brian G,Wang Hong Guang,Liu Zhi Peng,Chen Zhi Hong,Wood Lisa,Hsu Alan Chen-Yu,Xie Min,McDonald Vanessa,Wan Hua Jing,Luo Feng Ming,Liu Dan,Li Wei Min,Wang Gang 대한천식알레르기학회 2022 Allergy, Asthma & Immunology Research Vol.14 No.4
Purpose: The molecular links between metabolism and inflammation that drive different inflammatory phenotypes in asthma are poorly understood. We aimed to identify the metabolic signatures and underlying molecular pathways of different inflammatory asthma phenotypes. Methods: In the discovery set (n = 119), untargeted ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) was applied to characterize the induced sputum metabolic profiles of asthmatic patients with different inflammatory phenotypes using orthogonal partial least-squares discriminant analysis (OPLS-DA), and pathway topology enrichment analysis. In the validation set (n = 114), differential metabolites were selected to perform targeted quantification. Correlations between targeted metabolites and clinical indices in asthmatic patients were analyzed. Logistic and negative binomial regression models were established to assess the association between metabolites and severe asthma exacerbations. Results: Seventy-seven differential metabolites were identified in the discovery set. Pathway topology analysis uncovered that histidine metabolism, glycerophospholipid metabolism, nicotinate and nicotinamide metabolism, linoleic acid metabolism as well as phenylalanine, tyrosine and tryptophan biosynthesis were involved in the pathogenesis of different asthma phenotypes. In the validation set, 24 targeted quantification metabolites were significantly expressed between asthma inflammatory phenotypes. Finally, adenosine 5′-monophosphate (adjusted relative risk [adj RR] = 1.000; 95% confidence interval [CI] = 1.000–1.000; P = 0.050), allantoin (adj RR = 1.000; 95% CI = 1.000–1.000; P = 0.043) and nicotinamide (adj RR = 1.001; 95% CI = 1.000–1.002; P = 0.021) were demonstrated to predict severe asthma exacerbation rates. Conclusions: Different inflammatory asthma phenotypes have specific metabolic profiles in induced sputum. The potential metabolic signatures may identify therapeutic targets in different inflammatory asthma phenotypes.
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VC-dimension and distance chains in $\mathbb{F}_q^d$
Ruben Ascoli,Livia Betti,Justin Cheigh,Alex Iosevich,Ryan Jeong,Xuyan Liu,Brian McDonald,Wyatt Milgrim,Steven J. Miller,Francisco Romero Acosta,Santiago Velazquez Iannuzzelli 강원경기수학회 2024 한국수학논문집 Vol.32 No.1
Given a domain $X$ and a collection $\mathcal{H}$ of functions $h:X\to \{0,1\}$, the Vapnik-Chervonenkis (VC) dimension of $\mathcal{H}$ measures its complexity in an appropriate sense. In particular, the fundamental theorem of statistical learning says that a hypothesis class with finite VC-dimension is PAC learnable. Recent work by Fitzpatrick, Wyman, the fourth and seventh named authors studied the VC-dimension of a natural family of functions $\mathcal{H}_t^{'2}(E): \F_q^2\to \{0,1\}$, corresponding to indicator functions of circles centered at points in a subset $E\subseteq \mathbb{F}_q^2$. They showed that when $|E|$ is large enough, the VC-dimension of $\mathcal{H}_t^{'2}(E)$ is the same as in the case that $E = \mathbb F_q^2$. We study a related hypothesis class, $\Hh_t^d(E)$, corresponding to intersections of spheres in $\mathbb{F}_q^d$, and ask how large $E\subseteq \mathbb{F}_q^d$ needs to be to ensure the maximum possible VC-dimension. We resolve this problem in all dimensions, proving that whenever $|E|\geq C_dq^{d-1/(d-1)}$ for $d\geq 3$, the VC-dimension of $\Hh_t^d(E)$ is as large as possible. We get a slightly stronger result if $d=3$: this result holds as long as $|E|\geq C_3 q^{7/3}$. Furthermore, when $d=2$ the result holds when $|E|\geq C_2 q^{7/4}$.
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