Methods of Moments for Resolving Aerosol Dynamics

The study on aerosol dynamics processes, such as formation of nano/microscale aerosol particle and its subsequent growth in quiescent or evolving flows, has received much attention from both chemical engineering and atmospheric environment communities. The suitable theoretical method for resolving aerosol dynamical processes is widely known as population balance modeling (PBM), which is based on solving the population balance equation (PBE) in terms of particle number concentration. The study on the solution of the PBE has undergone rapid development in last several decades. In this chapter, the development of the method of moments for solving the PBE is presented. Three main methods of moments, including the Taylor series expansion method of moments, log-normal method of moments, and quadrature method of moments, are discussed

Understanding the Role of Commitments in Explaining P2P Lending Investing Willingness: Antecedents and Consequences

As a relatively new e-commerce phenomenon, peer-to-peer (P2P) lending has the potential to thoroughly change the structure of the loan segment in the financial industry. And the success of P2P lending heavily depend on users’ continuous use. However, this topic has not been fully studied in IS research. The high practical significance and lack of research indicate the importance of the present study. This study aims to apply Meyer and Allen’s three-component model of commitment to construct a research model, which incorporates context-specific antecedents. To test the model, we use a survey of 216 actual lenders of the P2P lending platform in China. Results derived from data indicated that lenders’ continuous investments were jointly determined by continuous commitment and affective commitment. Further, platform assurance, trust on third-party, economic feasibility and quality of alternatives performed well as antecedents of continuous commitment. And perceived critical mass and platform assurance were significantly associated with affective commitment. The results of this research provided theoretical implications for future research and practical implications for the success of P2P lending platforms

Prevalence and in-hospital outcomes of diabetes among patients with acute coronary syndrome in China: findings from the Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome Project

Abstract Background Guidelines have classified patients with acute coronary syndrome (ACS) and diabetes as a special population, with specific sections presented for the management of these patients considering their extremely high risk. However, in China up-to-date information is lacking regarding the burden of diabetes in patients with ACS and the potential impact of diabetes status on the in-hospital outcomes of these patients. This study aims to provide updated estimation for the burden of diabetes in patients with ACS in China and to evaluate whether diabetes is still associated with excess risks of early mortality and major adverse cardiovascular and cerebrovascular events (MACCE) for ACS patients. Methods The Improving Care for Cardiovascular Disease in China-ACS Project was a collaborative study of the American Heart Association and the Chinese Society of Cardiology. A total of 63,450 inpatients with a definitive diagnosis of ACS were included. Prevalence of diabetes was evaluated in the overall study population and subgroups. Multivariate logistic regression was performed to examine the association between diabetes and in-hospital outcomes, and a propensity-score-matched analysis was further conducted. Results Among these ACS patients, 23,880 (37.6%) had diabetes/possible diabetes. Both STEMI and NSTE-ACS patients had a high prevalence of diabetes/possible diabetes (36.8% versus 39.0%). The prevalence of diabetes/possible diabetes was higher in women (45.0% versus 35.2%, p < 0.001). Even in patients younger than 45 years, 26.9% had diabetes/possible diabetes. While receiving comparable treatments for ACS, diabetes/possible diabetes was associated with a twofold higher risk of all-cause death (adjusted odds ratio 2.04 [95% confidence interval 1.78–2.33]) and a 1.5-fold higher risk of MACCE (adjusted odds ratio 1.54 [95% confidence interval 1.39–1.72]). Conclusions Diabetes was highly prevalent in patients with ACS in China. Considerable excess risks for early mortality and major adverse cardiovascular events were found in these patients. Trial registration NCT02306616. Registered December 3, 201

Simulation of Aerosol Evolution within Background Pollution for Nucleated Vehicle Exhaust via TEMOM

This work is intended to study the effect of background particles on vehicle emissions in representative realistic atmospheric environments. The coupling of Reynolds-Averaged Navier–Stokes equation (RANS) and Taylor-series Expansion Method Of Moments (TEMOM) is performed to track the emissions of the vehicle and simulating the evolution of the matters. The transport equation of mass, momentum, heat, and the first three orders of moments are taken into account with the effect of binary homogeneous nucleation, Brownian coagulation, condensation, and thermophoresis. The parameterization model is utilized for nucleation. The measured data for Beijing’s particle size distribution under both polluted and nonpolluted conditions are utilized as background particles. The relationship between the macroscopic measurement results and the microscopic dynamic process is analyzed by comparing the variation trend of several physical quantities in the process of aerosol evolution. It is found with an increase of background particle concentration, the nucleation is inhibited, which is consistent with the existing studies

Arabidopsis Cys2/His2 Zinc Finger Transcription Factor ZAT18 Modulates the Plant Growth-Defense Tradeoff

Plant defense responses under unfavorable conditions are often associated with reduced growth. However, the mechanisms underlying the growth-defense tradeoff remain to be fully elucidated, especially at the transcriptional level. Here, we revealed a Cys2/His2-type zinc finger transcription factor, namely, ZAT18, which played dual roles in plant immunity and growth by oppositely regulating the signaling of defense- and growth-related hormones. ZAT18 was first identified as a salicylic acid (SA)-inducible gene and was required for plant responses to SA in this study. In addition, we observed that ZAT18 enhanced the plant immunity with growth penalties that may have been achieved by activating SA signaling and repressing auxin signaling. Further transcriptome analysis of the zat18 mutant showed that the biological pathways of defense-related hormones, including SA, ethylene and abscisic acid, were repressed and that the biological pathways of auxin and cytokinin, which are growth-related hormones, were activated by abolishing the function of ZAT18. The ZAT18-mediated regulation of hormone signaling was further confirmed using qRT-PCR. Our results explored a mechanism by which plants handle defense and growth at the transcriptional level under stress conditions

Fully Connected Conditional Random Fields for High-Resolution Remote Sensing Land Use/Land Cover Classification with Convolutional Neural Networks

The interpretation of land use and land cover (LULC) is an important issue in the fields of high-resolution remote sensing (RS) image processing and land resource management. Fully training a new or existing convolutional neural network (CNN) architecture for LULC classification requires a large amount of remote sensing images. Thus, fine-tuning a pre-trained CNN for LULC detection is required. To improve the classification accuracy for high resolution remote sensing images, it is necessary to use another feature descriptor and to adopt a classifier for post-processing. A fully connected conditional random fields (FC-CRF), to use the fine-tuned CNN layers, spectral features, and fully connected pairwise potentials, is proposed for image classification of high-resolution remote sensing images. First, an existing CNN model is adopted, and the parameters of CNN are fine-tuned by training datasets. Then, the probabilities of image pixels belong to each class type are calculated. Second, we consider the spectral features and digital surface model (DSM) and combined with a support vector machine (SVM) classifier, the probabilities belong to each LULC class type are determined. Combined with the probabilities achieved by the fine-tuned CNN, new feature descriptors are built. Finally, FC-CRF are introduced to produce the classification results, whereas the unary potentials are achieved by the new feature descriptors and SVM classifier, and the pairwise potentials are achieved by the three-band RS imagery and DSM. Experimental results show that the proposed classification scheme achieves good performance when the total accuracy is about 85%

Quantifying the impact of strong ties in international scientific research collaboration.

Tie strength has been examined as an antecedent of creativity. Although it has been discovered that international collaboration affects scientific performance, the effect of tie strength in the international collaboration network has been largely neglected. Based on international publications of 72 countries/regions published from 1993 to 2013, we combine descriptive and panel regression methods to examine how the bonding of strong collaboration ties contributes to countries' international scientific performance. Strong ties occur at an average rate of 1 in 4 collaborators, whereas countries/regions share on average 84% of articles with their strong-tie collaborators. Our quantitative results provide an explanation for this phenomenon in international collaboration: the establishment of a strong tie relationship contributes to above-average productivity and citation frequency for countries/regions. To further explore which types of strong ties tend to have stronger citation impact, we analyse the relationship between persistent and stable collaboration and publication citation impact. Experimental results show that international collaborations with greater persistence and moderate stability tend to produce high impact publications. It is noteworthy that when the collaboration period is divided into different time intervals, similar findings can be found after the same analysis procedure is carried out. This indicates that our conclusions are robust. Overall, this study provides quantitative insights into the added value of long-term commitment and social trust associated with strong collaborative partnerships in international collaboration