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Mixed-mode chromatography (MMC) is a fast growing area in recent years, thanks to the new generation of mixed-mode stationary phases and better understanding of multimode ...interactions. MMC has superior applications in the separation of compounds that are not retained or not well resolved by typical reversed-phase LC methods, especially for polar and charged molecules. Due to the multiple retention modes that a single MMC column can offer, often MMC provides additional dimension to a separation method by adjusting the mobile phase conditions. Mixed-mode media is also an effective way to clean up complex sample matrices for purification purposes or for sensitive detection of trace amounts of analytes. In this article, we discuss mixed-mode stationary phases and separation mechanisms and review recent advances in pharmaceutical and biopharmaceutical applications including the analysis and/or purification of counterions, small molecule drugs, impurities, formulation excipients, peptides and proteins.
In this paper, a Pearson’s correlation coefficient based decision tree (PCC-Tree) is established and its parallel implementation is developed in the framework of Map-Reduce (MR-PCC-Tree). The ...proposed methods employ Pearson’s correlation coefficient as a new measure of feature quality to confirm the optimal splitting attributes and splitting points in the growth of decision trees. Besides, the proposed MR-PCC-Tree adopts Map-Reduce technology to every component during the decision trees learning process for parallel computing, which mainly consists of a parallel Pearson’s correlation coefficient based splitting rule and a parallel splitting data method. The experimental analysis is conducted on a series of UCI benchmark data sets with different scales. In contrast to several traditional decision tree classifiers including BFT, C4.5, LAD, SC and NBT on 17 data sets, the proposed PCC-Tree is no worse than the traditional models as a whole. Furthermore, the experimental results on other 8 data sets show the feasibility of the proposed MR-PCC-Tree and its good parallel performance on reducing computational time for large-scale data classification problems.
Based on dust storm frequency (DSF) data from the China Meteorological Administration, Arctic sea-ice concentration (SIC) data from the Hadley Centre, and atmospheric reanalysis data from the ...National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric Research (NCAR), temporal variations and regime shifts of East Asian DSF and Arctic SIC during 1961-2015 are revealed, and the possible relationship between them is explored. The results show that East Asian DSF in spring is closely associated with the preceding winter SIC from the northern Greenland Sea to the Barents Sea (20° W-60° E, 74.5° N-78.5° N). In the past half-century, both East Asian DSF and Arctic SIC have shown significant declining trends, with consistent regime shifts in the early 1980s. Further statistical analyses indicate that the abrupt decrease of East Asian DSF in spring may be attributed to the concurrent sharp loss of Arctic SIC in the preceding winter. It is the loss of Arctic SIC that causes the atmospheric circulation anomalies downstream by stimulating a Rossby wave train, resulting in decelerated wind speed, dampened vertical wind shear and restrained synoptic-scale disturbances over the dust source region, eventually leading to the decline in East Asian DSF over decadal timescales.
•Metal catalyst is uniformly constructed on the fiber surface under mild condition.•Controllable and stable assembly of CNTs on the fiber surface is realized.•PDA slows down the diffusion of metal ...catalyst into fiber.•PDA gives full play to the advantage of CNTs in strengthening and toughening CFRP.
Based on the Platform effect of polydopamine (PDA), the distribution of metal catalyst on the surface of carbon fiber was investigated in this study. Through PDA-based carbon coating, directional Carbon nanotubes (CNTs) are grown on the high strength carbon fiber body without damaging the interface structure and properties of Carbon fiber reinforced plastic (CFRP) by Chemical vapor deposition (CVD) approach. The results indicated that the PDA coating endows CNTs with a uniform distribution on the fiber surface, which effectively mitigate the corrosion of the fiber body by the high temperature and metal catalyst during the CVD process, thus augmenting the mechanical properties of the carbon fibers and their composites. The failure mechanism of the composite under stress was clarified by the transverse and longitudinal fracture morphology, which further developed the interface theory of CFRP.
PM2.5 chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely ...updated information on China’s PM2.5 chemical composition is the basis for research and environmental management. Here, we developed a full-coverage near-real-time PM2.5 chemical composition data set at 10 km spatial resolution since 2000, combining the Weather Research and Forecasting–Community Multiscale Air Quality modeling system, ground observations, a machine learning algorithm, and multisource-fusion PM2.5 data. PM2.5 chemical components in our data set are in good agreement with the available observations (correlation coefficients range from 0.64 to 0.75 at a monthly scale from 2000 to 2020 and from 0.67 to 0.80 at a daily scale from 2013 to 2020; most normalized mean biases within ±20%). Our data set reveals the long-term trends in PM2.5 chemical composition in China, especially the rapid decreases after 2013 for sulfate, nitrate, ammonium, organic matter, and black carbon, at the rate of −9.0, −7.2, −8.1, −8.4, and −9.2% per year, respectively. The day-to-day variability is also well captured, including evolutions in spatial distribution and shares of PM2.5 components. As part of Tracking Air Pollution in China (http://tapdata.org.cn), this daily-updated data set provides large opportunities for health and climate research as well as policy-making in China.
This article considers identification and estimation of social network models in a system of simultaneous equations. We show that, with or without row-normalization of the social adjacency matrix, ...the network model has different equilibrium implications, needs different identification conditions, and requires different estimation strategies. When the adjacency matrix is not row-normalized, the variation in the Bonacich centrality across nodes in a network can be used as an IV to identify social interaction effects and improve estimation efficiency. The number of such IVs depends on the number of networks. When there are many networks in the data, the proposed estimators may have an asymptotic bias due to the presence of many IVs. We propose a bias-correction procedure for the many-instrument bias. Simulation experiments show that the bias-corrected estimators perform well in finite samples. We also provide an empirical example to illustrate the proposed estimation procedure.
The development of an atom transfer radical polymerization (ATRP) system without any transition metal catalyst for electronic and biomedical applications was considered to be in pressing need. ...Fluorescein (FL) was used as the organic photocatalyst for the polymerization of methyl methacrylate (MMA)
via
the proposed photoinduced electron transfer–atom transfer radical polymerization (PET–ATRP) mechanism. In the presence of electron donors provided by triethylamine (TEA), fluorescein can activate alkyl bromide and control radical polymerizations by a reductive quenching pathway. The polymerizations could be controlled by an efficient activation and deactivation equilibrium while maintaining the attractive features of “living” radical polymerization. The number-average molecular weight
M
n,GPC
increased with monomer conversion, and the controllability of molecular weight distributions for the obtained PMMA could be achieved in the polymerization processes. MALDI-TOF MS,
1
H NMR spectroscopy and chain extension polymerizations show reserved chain-end functionality in the synthesized polymers and further confirm the “living” feature of the metal-free ATRP methodology. All these research results support the feasibility of the visible light mediated metal-free PET–ATRP platform for the synthesis of elegant macromolecular structures.
Blood-retinal barrier (BRB) includes inner BRB (iBRB) and outer BRB (oBRB), which are formed by retinal capillary endothelial (RCEC) cells and by retinal pigment epithelial (RPE) cells in ...collaboration with Bruch's membrane and the choriocapillaris, respectively. Functions of the BRB are to regulate fluids and molecular movement between the ocular vascular beds and retinal tissues and to prevent leakage of macromolecules and other potentially harmful agents into the retina, keeping the microenvironment of the retina and retinal neurons. These functions are mainly attributed to absent fenestrations of RCECs, tight junctions, expression of a great diversity of transporters, and coverage of pericytes and glial cells. BRB existence also becomes a reason that systemic administration for some drugs is not suitable for the treatment of retinal diseases. Some diseases (such as diabetes and ischemia-reperfusion) impair BRB function via altering tight junctions, RCEC death, and transporter expression. This chapter will illustrate function of BRB, expressions and functions of these transporters, and their clinical significances.
Air pollution has altered the Earth’s radiation balance, disturbed the ecosystem, and increased human morbidity and mortality. Accordingly, a full-coverage high-resolution air pollutant data set with ...timely updates and historical long-term records is essential to support both research and environmental management. Here, for the first time, we develop a near real-time air pollutant database known as Tracking Air Pollution in China (TAP, http://tapdata.org.cn/) that combines information from multiple data sources, including ground observations, satellite aerosol optical depth (AOD), operational chemical transport model simulations, and other ancillary data such as meteorological fields, land use data, population, and elevation. Daily full-coverage PM2.5 data at a spatial resolution of 10 km is our first near real-time product. The TAP PM2.5 is estimated based on a two-stage machine learning model coupled with the synthetic minority oversampling technique and a tree-based gap-filling method. Our model has an averaged out-of-bag cross-validation R 2 of 0.83 for different years, which is comparable to those of other studies, but improves its performance at high pollution levels and fills the gaps in missing AOD on daily scale. The full coverage and near real-time updates of the daily PM2.5 data allow us to track the day-to-day variations in PM2.5 concentrations over China in a timely manner. The long-term records of PM2.5 data since 2000 will also support policy assessments and health impact studies. The TAP PM2.5 data are publicly available through our website for sharing with the research and policy communities.
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