In this work we provide a systematic scanning tunneling microscopy (STM) study on the self-assembling and mixing behavior of Arylene Ethynylene Macrocycles (AEMs) containing 1,4-phenylene, 1,4-naphthylene or 9,10-anthrylene substituents at the solid/liquid interface. The effect of bulky substituents on the self-assembly structure was investigated and we found that 1,4-phenylene ethynylene macrocycle (AEM-B) and 1,4-naphthylene ethynylene macrocycle (AEM-N) form four and three different patterns at the 1,2,4-trichloride benzene (TCB)/graphite interface, respectively, and a significant concentration effect was observed for both molecules. 9,10-anthrylene ethynylene macrocycle (AEM-A) only forms a filled honeycomb structure at relatively high concentrations. The effect of bulky substituents was attributed to the steric hindrance, which hinders full interdigitation of alkoxy chains. The mixing behavior of binary mixtures of arylene ethynylene macrocycles was also investigated at the TCB/HOPG interface. The results demonstrate that the steric hindrance brought by the bulky groups does not enable sufficient recognition between identical molecules at the interface and random mixing was observed for binary mixtures of AEM-B and AEM-N. The mixing behavior of AEMs could also be predicted by the parameter called the 2D isomorphism coefficient.
This study investigated the influence of carbon nanotubes (CNTs) on the transport and retention behaviors of bacteria (E. coli) in packed porous media at both low and high ionic strength in NaCl and CaCl2 solutions. At low ionic strengths (5 mM NaCl and 0.3 mM CaCl2), both breakthrough curves and retained profiles of bacteria with CNTs (both 5 and 10 mg L-1) were equivalent to those without CNTs, indicating the presence of CNTs did not affect the transport and retention of E. coli at low ionic strengths. The results were supported by those from cell characterization tests (i.e., viability, surface properties, sizes), which showed no significant difference between with and without CNTs. In contrast, breakthrough curves of bacteria with CNTs were lower than those without CNTs at high ionic strengths (25 mM NaCl and 1.2 mM CaCl2), suggesting that the presence of CNTs decreased cell transport at high ionic strengths. The enhanced bacterial deposition in the presence of CNTs was mainly observed at segments near the column inlet, leading to much steeper retained profiles relative to those without CNTs. Additional transport experiments conducted with sand columns predeposited with CNTs revealed that the codeposition of bacteria with CNTs, as well as the deposition of the cell-CNTs cluster formed in cell suspension due to cell bridging effect, largely contributed to the increased deposition of bacteria at high ionic strengths in porous media.
This paper explores whether educational attainment has a cognitive reserve capacity in elder life. Using pilot data from the China Health and Retirement Longitudinal Study (CHARLS), we examined the impact of education on cognitive abilities at old ages. OLS results showed that respondents who completed primary school obtained 18.2 percent higher scores on cognitive tests than those who did not. We then constructed an instrumental variable (IV) by leveraging China's Great Famine of 1959–1961 as a natural experiment to estimate the causal effect of education on cognition. Two-stage least squares (2SLS) results provided sound evidence that completing primary school significantly increases cognition scores, especially in episode memory, by almost 20 percent on average. Moreover, Regression Discontinuity (RD) analysis provides further evidence for the causal interpretation, and shows that the effects are different for the different measures of cognition we explored. Our results also show that the Great Famine can result in long-term health consequences through the pathway of losing educational opportunities other than through the pathway of nutrition deprivation.
Efficient all-optical molecule-plasmon modulation is experimentally demonstrated by employing a compact T-shape single slit on a metal film coated with an azopolymer film, in which the azobenzene molecules can be reoriented by a pump beam. In the T-shape single slit, the transmission spectra exhibit periodic behaviors and are quite sensitive to variations of the refractive index of the azopolymer in the groove. Under a pump beam, the azobenzene molecules are reoriented, so the SPPs in the groove feel a refractive index quite different from that of the originally isotropic azopolymer with randomly orientations. This leads to a high modulation depth of about 53 % (3.3 dB) and a phase variation of >pi experimentally.
Methods for choosing a fixed set of knot locations in additive spline models are fairly well established in the statistical literature. The curse of dimensionality makes it nontrivial to extend these methods to nonadditive surface models, especially when there are more than a couple of covariates. We propose a multivariate Gaussian surface regression model that combines both additive splines and interactive splines, and a highly efficient Markov chain Monte Carlo algorithm that updates all the knot locations jointly. We use shrinkage prior to avoid overfitting with different estimated shrinkage factors for the additive and surface part of the model, and also different shrinkage parameters for the different response variables. Simulated data and an application to firm leverage data show that the approach is computationally efficient, and that allowing for freely estimated knot locations can offer a substantial improvement in out-of-sample predictive performance.
We present for the first time an efficient iterative method to directly solve the four-component Dirac-Kohn-Sham (DKS) density functional theory. Due to the existence of the negative energy continuum in the DKS operator, the existing iterative techniques for solving the Kohn-Sham systems cannot be efficiently applied to solve the DKS systems. The key component of our method is a novel filtering step (F) which acts as a preconditioner in the framework of the locally optimal block preconditioned conjugate gradient (LOBPCG) method. The resulting method, dubbed the LOBPCG-F method, is able to compute the desired eigenvalues and eigenvectors in the positive energy band without computing any state in the negative energy band. The LOBPCG-F method introduces mild extra cost compared to the standard LOBPCG method and can be easily implemented. We demonstrate our method in the pseudopotential framework with a planewave basis set which naturally satisfies the kinetic balance prescription. Numerical results for Pt$_{2}$, Au$_{2}$, TlF, and Bi$_{2}$Se$_{3}$ indicate that the LOBPCG-F method is a robust and efficient method for investigating the relativistic effect in systems containing heavy elements.