Adaptive Finite Element Approximations for Kohn-Sham Models

The Kohn-Sham equation is a powerful, widely used approach for computation of ground state electronic energies and densities in chemistry, materials science, biology, and nanosciences. In this paper, we study the adaptive finite element approximations for the Kohn-Sham model. Based on the residual type a posteriori error estimators proposed in this paper, we introduce an adaptive finite element algorithm with a quite general marking strategy and prove the convergence of the adaptive finite element approximations. Using D{\" o}rfler's marking strategy, we then get the convergence rate and quasi-optimal complexity. We also carry out several typical numerical experiments that not only support our theory,but also show the robustness and efficiency of the adaptive finite element computations in electronic structure calculations.Comment: 38pages, 7figure

Comparison of daily and sub-daily SWAT models for daily streamflow simulation in the Upper Huai River Basin of China

Despite the significant role of precipitation in the hydrological cycle, few studies have been conducted to evaluate the impacts of the temporal resolution of rainfall inputs on the performance of SWAT (soil and water assessment tool) models in large-sized river basins. In this study, both daily and hourly rainfall observations at 28 rainfall stations were used as inputs to SWAT for daily streamflow simulation in the Upper Huai River Basin. Study results have demonstrated that the SWAT model with hourly rainfall inputs performed better than the model with daily rainfall inputs in daily streamflow simulation, primarily due to its better capability of simulating peak flows during the flood season. The sub-daily SWAT model estimated that 58% of streamflow was contributed by baseflow compared to 34 % estimated by the daily model. Using the future daily and three-hour precipitation projections under the RCP (Representative Concentration Pathways) 4.5 scenario as inputs, the sub-daily SWAT model predicted a larger amount of monthly maximum daily flow during the wet years than the daily model. The differences between the daily and sub-daily SWAT model simulation results indicated that temporal rainfall resolution could have much impact on the simulation of hydrological process, streamflow, and consequently pollutant transport by SWAT models. There is an imperative need for more studies to examine the effects of temporal rainfall resolution on the simulation of hydrological and water pollutant transport processes by SWAT in river basins of different environmental conditions

Efficient Revocable ID-Based Signature With Cloud Revocation Server

Over the last few years, identity-based cryptosystem (IBC) has attracted widespread attention because it avoids the high overheads associated with public key certificate management. However, an unsolved but critical issue about IBC is how to revoke a misbehaving user. There are some revocable identity-based encryption schemes that have been proposed recently, but little work on the revocation problem of identity-based signature has been undertaken so far. One approach for revocation in identity-based settings is to update users\u27 private keys periodically, which is usually done by the key generation center (KGC). But with this approach, the load on the KGC will increase quickly when the number of users increases. In this paper, we propose an efficient revocable identity-based signature (RIBS) scheme in which the revocation functionality is outsourced to a cloud revocation server (CRS). In our proposed approach, most of the computations needed during key-updates are offloaded to the CRS. We describe the new framework and the security model for the RIBS scheme with CRS and we prove that the proposed scheme is existentially unforgeable against adaptively chosen messages and identity attacks in the random oracle model. Furthermore, we monstrate that our scheme outperforms previous IBS schemes in terms of lower computation and communication costs

Impacts of climate change on TN load and its control in a River Basin with complex pollution sources

It is increasingly recognized that climate change could affect the quality of water through complex natural and anthropogenic mechanisms. Previous studies on climate change and water quality have mostly focused on assessing its impact on pollutant loads from agricultural runoff. A sub-daily SWAT model was developed to simulate the discharge, transport, and transformation of nitrogen from all known anthropogenic sources including industries, municipal sewage treatment plants, concentrated and scattered feedlot operations, rural households, and crop production in the Upper Huai River Basin. This is a highly polluted basin with total nitrogen (TN) concentrations frequently exceeding Class V of the Chinese Surface Water Quality Standard (GB3838-2002). Climate change projections produced by 16 Global Circulation Models (GCMs) under the RCP 4.5 and RCP 8.5 scenarios in the mid (2040–2060) and late (2070–2090) century were used to drive the SWAT model to evaluate the impacts of climate change on both the TN loads and the effectiveness of three water pollution control measures (reducing fertilizer use, constructing vegetative filter strips, and improving septic tank performance) in the basin. SWAT simulation results have indicated that climate change is likely to cause an increase in both monthly average and extreme TN loads in February, May, and November. The projected impact of climate change on TN loads in August is more varied between GCMs. In addition, climate change is projected to have a negative impact on the effectiveness of septic tanks in reducing TN loads, while its impacts on the other two measures are more uncertain. Despite the uncertainty, reducing fertilizer use remains the most effective measure for reducing TN loads under different climate change scenarios. Meanwhile, improving septic tank performance is relatively more effective in reducing annual TN loads, while constructing vegetative filter strips is more effective in reducing annual maximum monthly TN loads

Inverse design of topological metaplates for flexural waves with machine learning

The mechanical analog to the topological insulators brings anomalous elastic wave properties which diversifies classic wave functions for potential broad applications. To obtain topological mechanical wave states with good quality at desired frequency ranges, it needs repetitive trials of different geometric parameters with traditional forward designs. In this work, we develop an inverse design of topological edge states for flexural wave using machine learning method which is promising for instantaneous design. Nonlinear mapping function from input targets to output desired parameters are adopted in artificial neural networks where the data sets for training are generated by the plane wave expansion method. Topological edge states are then realized and compared for different bandgap width conditions with such inverse designs, proving that wide bandgap can promote the confinement of the topological edge states. Finally, direction selective propagations with sharp turns are further demonstrated as anomalous wave behaviors. The machine learning inverse design of topological states for flexural wave provides an efficient way to design practical devices with targeted needs for potential applications such as signal processing, sensing and energy harvesting

Investigations on the mechanism of microweld changes during ultrasonic wire bonding by molecular dynamics simulation

Despite the wide and long-term applications of ultrasonic (US) wire bonding and other US metal joining technologies, the mechanism of microweld changes during the bonding process, including formation, deformation and breakage, is rarely known as it is very difficult to be investigated by experiments. In this work, this mechanism under different surface topographies and displacement patterns is studied by molecular dynamics simulation. It is found that microwelds can be formed or broken instantly. Due to the relative motion between the local wire part and the local substrate part, microwelds can be largely deformed or even broken. The impacts of material, surface topography, approaching distance and vibration amplitude on the microweld changes are investigated via the quantification of the shear stress and the equivalent bonded area. It is shown that these four factors significantly influence the final connection and the interface structure. The analysis of the scale influence on the microweld changes shows that the simulation results at a small-scale are able to represent those at a large-scale which is close to the range of the commonly used surface roughness. This deeper understanding on the microweld changes leads to a better control strategy and an enhancement of the bonding process

Assessment of the spatial and temporal variations of water quality for agricultural lands with crop rotation in China by using a HYPE model

Many water quality models have been successfully used worldwide to predict nutrient losses from anthropogenically impacted catchments, but hydrological and nutrient simulations with little data are difficult considering the transfer of model parameters and complication of model calibration and validation. This study aims (i) to assess the performance capabilities of a new and relatively more advantageous model-hydrological predictions for the environment (HYPE) to simulate stream flow and nutrient load in ungauged agricultural areas by using a multi-site and multi-objective parameter calibration method and (ii) to investigate the temporal and spatial variations of total nitrogen (TN) and total phosphorous (TP) concentrations and loads with crop rotation using the model for the first time. A parameter estimation tool (PEST) was used to calibrate parameters, which shows that the parameters related to the effective soil porosity were most sensitive to hydrological modeling. N balance was largely controlled by soil denitrification processes, whereas P balance was influenced by the sedimentation rate and production/decay of P in rivers and lakes. The model reproduced the temporal and spatial variations of discharge and TN/TP relatively well in both calibration (2006–2008) and validation (2009–2010) periods. The lowest NSEs (Nash-Suttclife Efficiency) of discharge, daily TN load, and daily TP load were 0.74, 0.51, and 0.54, respectively. The seasonal variations of daily TN concentrations in the entire simulation period were insufficient, indicated that crop rotation changed the timing and amount of N output. Monthly TN and TP simulation yields revealed that nutrient outputs were abundant in summer in terms of the corresponding discharge. The area-weighted TN and TP load annual yields in five years showed that nutrient loads were extremely high along Hong and Ru rivers, especially in agricultural lands

Genetic Association Study with Metabolic Syndrome and Metabolic-Related Traits in a Cross-Sectional Sample and a 10-Year Longitudinal Sample of Chinese Elderly Population

Background: The metabolic syndrome (MetS) has been known as partly heritable, while the number of genetic studies on MetS and metabolic-related traits among Chinese elderly was limited. Methods: A cross-sectional analysis was performed among 2 014 aged participants from September 2009 to June 2010 in Beijing, China. An additional longitudinal study was carried out among the same study population from 2001 to 2010. Biochemical profile and anthropometric parameters of all the participants were measured. The associations of 23 SNPs located within 17 candidate genes (MTHFR, PPARγ, LPL, INSIG, TCF7L2, FTO, KCNJ11, JAZF1, CDKN2A/B, ADIPOQ, WFS1, CDKAL1, IGF2BP2, KCNQ1, MTNR1B, IRS1, ACE) with overweight and obesity, diabetes, metabolic phenotypes, and MetS were examined in both studies. Results: In this Chinese elderly population, prevalence of overweight, central obesity, diabetes, dyslipidemia, hypertension, and MetS were 48.3%, 71.0%, 32.4%, 75.7%, 68.3% and 54.5%, respectively. In the cross-sectional analyses, no SNP was found to be associated with MetS. Genotype TT of SNP rs4402960 within the gene IGF2BP2 was associated with overweight (odds ratio (OR) = 0.479, 95% confidence interval (CI): 0.316-0.724, p = 0.001) and genotype CA of SNP rs1801131 within the gene MTHFR was associated with hypertension (OR = 1.560, 95% CI: 1.194–2.240, p = 0.001). However, these associations were not observed in the longitudinal analyses. Conclusions: The associations of SNP rs4402960 with overweight as well as the association of SNP rs1801131 with hypertension were found to be statistically significant. No SNP was identified to be associated with MetS in our study with statistical significance