Penta-graphene has recently been proposed as a new allotrope of carbon composed of pure pentagons, and displays many novel properties going beyond graphene [Zhang et al., Proc. Natl. Acad. Sci. U. S. A., 2015, 112, 2372]. To further explore the property modulations, we have carried out a theoretical investigation of the hydrogenated and fluorinated penta-graphene sheets. Our first-principles calculations reveal that hydrogenation and fluorination can effectively tune the electronic and mechanical properties of penta-graphene: turning the sheet from semiconducting to insulating; changing the Poisson's ratio from negative to positive, and reducing the Young's modulus. Moreover, the band gaps of the hydrogenated and fluorinated penta-graphene sheets are larger than those of fully hydrogenated and fluorinated graphene by 0.37 and 0.04 eV, respectively. The phonon dispersions and ab initio molecular dynamics simulations confirm that the surface modified penta-graphene sheets are dynamically and thermally stable, and show that the hydrogenated penta-graphene has more Raman-active modes with higher frequencies as compared to the fluorinated penta-graphene.
In this paper, two new quantitative technical criteria are developed to determine the minimum miscibility pressures (MMPs) from the vanishing interfacial tension (VIT) technique: the linear correlation coefficient (LCC) criterion and the critical interfacial thickness (CIT) criterion. Six series of dynamic interfacial tension (IFT) tests for the dead and live light crude oil–CO2 systems are conducted under different test conditions. The MMP is determined when the LCC is smaller than 0.990 or the interfacial thickness is smaller than 1.0nm for the first time. The determined respective MMPs of 12.9MPa and 13.2MPa for the dead and live light crude oil–CO2 systems from the VIT technique agree well with the MMPs of 12.4–12.9MPa for the former system from the coreflood tests and fairly well with 15.2–15.4MPa for the latter system from the slim-tube tests. In addition, the specific effects of three experimental factors on the determined MMPs are studied by applying the two new quantitative technical criteria: (a) the initial vs. equilibrium IFTs; (b) the oil composition; and (c) the initial gas–oil ratio (GOR). The measured initial other than equilibrium IFTs are found to be sufficiently accurate to determine the MMP from the VIT technique. This is because the pendant oil drops used in the dynamic IFT tests are so small that they can be saturated with CO2 almost instantaneously. The live light crude oil pre-saturated with CH4-dominated hydrocarbons has a slightly higher MMP in comparison with the dead light crude oil. Moreover, the initial GOR effect on the MMP is found to be negligible in a lower GOR range (1:1–10:1 in volume) or in a large CO2 concentration range (31.76–94.69mol%). It becomes pronounced in a higher GOR range (200:1–4000:1 in volume) or in an extremely small range of high CO2 concentrations (98.79–99.99mol%).
We generate a large number of monodisperse disk packings in two dimensions via geometric-based packing algorithms including the relaxation algorithm and the Torquato–Jiao algorithm. Using the geometric-structure approach, a clear boundary of the geometrical feasible region in the order map is found which quite differs from that of the jammed region. For a certain packing density higher than 0.83, the crystalline degree varies in different packing samples. We find that the local hexatic order may increase in two fairly different ways as the system densifies. Therefore, two typical non-equilibrium jammed patterns, termed polycrystal and distorted crystal, are defined at high packing densities. Furthermore, their responses to isotropic compression are investigated using a compression–relaxation molecular dynamic protocol. The distorted crystal pattern is more stable than the polycrystal one with smaller displacements despite its low occurrence frequency. The results are helpful in understanding the structure and phase transition of disk packings.
Background Type D personality and medication nonadherence have been shown to be associated with poor health outcomes. Type D personality is associated with poor medication adherence in patients with coronary artery disease, myocardial infarction, and heart failure. However, the relationship between type D personality and medication adherence in patients with Type 2 Diabetes Mellitus (T2DM) remains unknown. This study aims to examine whether type D personality was associated with medication adherence in patients with T2DM. Design and Settings A follow-up study was conducted in general hospital of the People's Liberation Army in Beijing. Methods 412 T2DM patients (205 females), who were recruited by circular systematic random sampling, provided demographic and baseline data about medical information and completed measures of Type D personality. Then, 330 patients went on to complete a self-report measure of medication adherence at the sixth month after baseline data collection. Chi-square test, t tests, and hierarchical multiple regression analyses were conducted, as needed. Results Patients with type D personality were significantly more likely to have poor medication adherence (p$<$0.001). Type D personality predicts poor medication adherence before and after controlling for covariates when it was analyzed as a categorical variable. However, the dimensional construct of type D personality was not associated with medication adherence when analyzed as a continuous variable. Conclusion Although, as a dimensional construct, type D personality may not reflect the components of the personality associated with poor medication adherence in patients with T2DM, screening for type D personality may help to identify those who are at higher risk of poor medication adherence. Interventions, aiming to improve medication adherence, should be launched for these high-risk patients.
An ultra-small and broadband polarization splitter is numerically and experimentally demonstrated based on the double-slit interference in a polymer-film-coated double-slit structure. The hybrid slab waveguide(air-polymer-Au) supports both the transverse-magnetic and transverse-electric modes. The incident beam from the back side can excite these two guided modes of orthogonally polarized states in the hybrid structure. By exploiting the difference slit widths and the large mode birefringence, these two guided modes propagate to the opposite directions along the front metal surface. Moreover, the short interference length broadens the operation bandwidth. Experimentally, a polarization splitter with a lateral dimension of only about 1.6 μm and an operation bandwidth of 50 nm is realized. By designing the double-slit structure in a hybrid strip waveguide, the device dimension can be significant downscaled to about 0.3 × 1.3 μm2. Such an ultra-small and broadband polarization splitter may find important applications in the integrated photonic circuits.
Rapid urbanization and population growth have resulted in worldwide serious water shortage and environmental deterioration. It is then essential for efficient and feasible allocation of scarce water and environment resources to the competing users. Due to inherent uncertainties, decision making for resources allocation is vulnerable to failure. The scheme feasibility can be evaluated by reliability, representing the failure probability. A progressive reliability oriented multi-objective (PROMO) optimal decision-making procedure is proposed in this study to deal with problems with numerous reliability objectives. Dimensionality of the objectives is reduced by a top-down hierarchical reliability analysis (HRA) process combining optimization with evaluation. Pareto solutions of the reformulated model, representing alternative schemes non-dominated with each other, are generated by a metalmodel-based optimization algorithm. Evaluation and identification of Pareto solutions are conducted by multi-criteria decision analysis (MCDA). The PROMO procedure is demonstrated for a case study on industrial structure transformation under strict constraints of water resources and total environmental emissions amounts in Guangzhou City, South China. The Pareto front reveals tradeoffs between economic returns of the industries and system reliability. For different reliability preference scenarios, the Pareto solutions are ranked and the top-rated one was recommended for implementation. The model results indicate that the PROMO procedure is effective for model solving and scheme selection of uncertainty-based multi-objective decision making.
Rapid urbanization and population growth have resulted in worldwide serious water shortage and environmental deterioration. It is then essential for efficient and feasible allocation of scarce water and environment resources to the competing users. Due to inherent uncertainties, decision making for resources allocation is vulnerable to failure. The scheme feasibility can be evaluated by reliability, representing the failure probability. A progressive reliability-oriented multi-objective (PROMO) optimal decision-making procedure is proposed in this study to deal with problems with numerous reliability objectives. Dimensionality of the objectives is reduced by a top-down hierarchical reliability analysis (HRA) process combining optimization with evaluation. Pareto solutions of the reformulated model, representing alternative schemes non-dominated with each other, are generated by a metalmodel-based optimization algorithm. Evaluation and identification of Pareto solutions are conducted by multi-criteria decision analysis (MCDA). The PROMO procedure is demonstrated for a case study on industrial structure transformation under strict constraints of water resources and total environmental emissions amounts in Guangzhou City, South China. The Pareto front reveals tradeoffs between economic returns of the industries and system reliability. For different reliability preference scenarios, the Pareto solutions are ranked and the top-rated one was recommended for implementation. The model results indicate that the PROMO procedure is effective for model solving and scheme selection of uncertainty-based multi-objective decision making.
As a traditional application on various supercomputers, atmospheric modeling has long been suffering from the low performance efficiency. In this paper, we pick the 3D Euler equation solver (the most essential dynamic component for a non-hydrostatic atmospheric model) as the target application, and explore the maximum performance efficiency that can be achieved on CPU-GPU hybrid architectures. Besides presenting the suitable hybrid domain decomposition methodology and taking proper usage of tuning techniques for both the CPU and GPU parts, we further propose a novel GPU tuning technique, namely the customizable data caching mechanism with thread warp rescheduling scheme, which is specifically designed for the Euler solver. Combining all the optimizing approaches together, remarkable performance boost has been achieved on mainstream GPU architectures including Tesla Fermi C2050, K20×, K40 and K80. Especially, on the latest Tesla K80, we demonstrate a 31.64× speedup over the performance of 12-core E5-2697 CPU. In addition, based on a hybrid CPU-GPU node with two 12-core E5-2697 CPUs and two Tesla K80 GPUs, a sustained double-precision performance of 1.04 Tflops (16% of the peak) is achieved, which is remarkably higher than the efficiency of similar optimizing tasks based on heterogeneous platforms (strictly less than 10%, as demonstrated in the related work). In addition, a nearly linear weak scaling efficiency is achieved which demonstrate the effectiveness of our domain decomposition method.
Air pollution is among the top threats to human health in China. As air toxicants, polycyclic aromatic hydrocarbons (PAHs) could bring significant risks to population; however, the exposure to PAHs in China and its health impact are not fully understood. In 2012, a summer exchange program allowed 10 students to travel from Los Angeles to Beijing and stay there for 10 weeks. Based on the program, this study investigated the difference in urinary concentration of 12 hydroxylated-PAHs (Sigma 12OH-PAHs) and malondialdehyde (MDA) between the two cities. The median concentration of Sigma 12OH-PAHs in Beijing (14.1 mu g g(-1) creatinine) was significantly higher than that in Los Angeles (5.78 mu g g(-1) creatinine), indicating a higher exposure in Beijing. The ratios of homogeneous OH-PAHs (e.g., 1-/2-OH-NAP) changed significantly between the two cities (p < 0.01), which might suggest a potential alteration in metabolism subsequent to exposure. A significant association between Sigma 12OH-PAHs and MDA (p < 0.01) was observed, with the association varying between the two cities. This study suggests that exposure to PAHs might be linked to metabolism alteration and calls for future studies to investigate the role this possible alteration played in the health effects of PAHs exposure.
Background: U.S. urban air quality has improved dramatically over the past decades. We evaluated acute effects of fine particulate matter (PM2.5) on cardiovascular (CVD) mortality among residents of Allegheny County in SW Pennsylvania (1999-2011) using spatio-temporal modeling of air pollutants (AP) to reduce misclassification error in exposure assessment.Methods: Spatio-temporal kriging of daily PM2.5 and ozone (03) was used to produce daily exposure estimates at the residence ZIP code. Time-stratified case-crossover analysis was conducted to examine short-term effects of PM2.5 on CVD mortality, adjusting for 03 and apparent mean temperature. We studied both single and distributed lags for days 0-5. All CVD mortality and subcategories of ischemic heart disease (IHD), acute myocardial infarction, cerebrovascular disease, peripheral vascular disease (PVD), heart failure and cardiac arrhythmia were examined.Results: A total of 62,135 deaths were identified. We found significant associations of PM2.5 with IHD and PVD mortality at lag day 5: (2.1% (95% CI, 0.2-4.1%) and (7.6%, 95% CI, 0.05-15.7%) per 10 mu g/m(3) increase of PM2.5 in single lag models and for IHD in distributed lag models. There were no statistically significant associations with PM2.5 for any of the other outcomes.Conclusions: The application of finer scale geographically resolved AP exposures made it possible to study acute effects of PM2.5 on CVD mortality in a large metropolitan area. Our study results demonstrated the continued presence of a dose response relationship of increased risk of CVD mortality within this lower range of PM2.5 exposure. (C) 2016 Elsevier Inc. All rights reserved.
