Impact of Lockdown on Air Pollution: Evidence from the “2+26” Cities in the Beijing-Tianjin-Hebei Region

To prevent the spread of COVID-19 in China, many cities were locked down after January 23, 2020. Based on the panel data of the “2+26” cities from 10 January to 15 March 2020, this paper took the lockdown as a quasi-natural experiment and established a multi-phase DID model to investigate whether the lockdown measures significantly reduced air pollution in locked-down cities in the Beijing-Tianjin-Hebei (BTH) region. The core innovation of this paper is that we considered the urban immigration scale index as a mediating variable , which is rarely adopted in the existing literature, and we identified the relationships between the lockdown, the intracity migration index, the urban immigration scale index and air pollution. The results showed that compared with the non-locked-down cities, the lockdown significantly reduced air pollution. Furthermore, it was found that the lockdown reduced air pollution by reducing intracity migration and the urban scale of immigration. Moreover, compared with the corresponding period in 2019, air pollution was significantly reduced in the locked-down cities of the “2+26” cities. Air pollution is closely related to human activity, and green production and technological innovations are critical for reducing air pollution in the BTH region

Research on the Marketing Strategy of Online Education -- Taking New Oriental as an Example

In recent years, with the development of society and the progress of science and technology, online learning has penetrated into people's daily life, and people's demand for high-quality curriculum products is more and more strong. From a macro perspective, the continuous growth of national financial investment in education, the continuous upgrading of China's consumption structure, the development of 5G technology and the popularization of AI intelligence make online teaching less limited. The online education industry is showing an explosive growth trend. More and more online education institutions are listed for financing, and the market value is soaring. However, in 2019, except for GSX, the latest online learning platforms such as New Oriental, Speak English Fluently and Sunlands, have been in a state of loss. Most of these agencies seize the market by increasing advertising investment, but at the same time, they also bring huge marketing costs, which affect the financial performance of the company. With the enhancement of Matthew effect, large-scale educational institutions occupy a large market through free classes and low-price classes, while small and medium-sized institutions with weak capital strength are often unable to afford high sales costs, facing the risk of capital chain rupture. Taking new Oriental online as an example, this paper analyzes the problems existing in the marketing strategies of online education institutions. It also puts forward suggestions on four aspects, which are target market, differentiated value, marketing mix and marketing mode, so as to make sure that online education institutions can control marketing expenses and achieve profits by improving course quality, expanding marketing channels and implementing precise positioning

Intrinsic Capacitance, Charge Storage Mechanisms, and Defect Engineering of Molybdenum Disulfide Nanosheets

Single layer 2D materials such as the metallic, 1T polymorph of molybdenum disulfide (MoS2) hold significant promise for next-generation supercapacitors due to their high theoretical surface area and ability to be assembled into electrodes with high bulk density boosting volumetric capacitance. While significant research has emerged in the last few years devoted to MoS2 and graphene-MoS2 hybrid electrode systems, little is known regarding fundamental double-layer charging mechanisms in this system. In this work, we determine the potential and frequency dependent area-specific double-layer capacitance of the electrode/electrolyte interface using the 1T and 2H polymorphs of MoS2. Furthermore, we aim to understand restacking effects and possible intercalation mechanisms in multilayer MoS2 films, as well as how the intrinsic capacitance can be enhanced by defect engineering. To by-pass the challenges and uncertainties associated with porous electrodes, we carry out measurements on non-porous monolayer electrodes supported by atomically flat graphite single crystals. Monolayer films were prepared by using a variation of the Langmuir Blodgett deposition method to create films of chemically exfoliated molybdenum disulfide (MoS2) and chemically reduced graphene oxide (rGO) using a recently developed barrier-free densification method. The films were characterized to determine surface coverage, surface roughness, layer number and electrode material chemistry. The frequency and voltage-dependent capacitance of monolayer, bilayer, and trilayer films were measured by cyclic voltammetry and impedance spectroscopy. The results demonstrate that the metallic 1T polymorph of MoS2 (Ca,1T = 14.9 µF/cm2) has over tenfold the capacitance of the semiconducting 2H polymorph (Ca,2H = 1.35 µF/cm2) near the open circuit potential and under negative polarization in aqueous electrolyte. However, under positive polarization the capacitance is significantly reduced and behaves similarly to the 2H polymorph. While the capacitance of rGO films does not increase with increasing layer number, the capacitance of 1T-MoS2 films scaled with layer number, even at high frequency, suggesting easy and rapid ion intercalation between the restacked sheets. The results of these studies allow us to determine the limiting factors and upper limits of capacitance expected from MoS2 composites and provides engineering design criteria for building higher performance MoS2 composite electrodes. Furthermore, in order to extend the potential upper capacitance limits of MoS2 supercapacitors, defect engineering is explored in MoS2 nanosheet films. Two types of defects are introduced into MoS2: sulfur vacancies and edge sites. Sulfur vacancies are created by increasing the amount of lithium intercalant used while edge sites are produced simply by decreasing the lateral size of MoS2 nanosheets through sonication. When transitioning from 0% to 6.6% sulfur vacancies, the intrinsic capacitance increases consistently. Conversely, while decreasing flake size by 40 nm increases the measured capacitance, further size reduction by 80 nm results in decreased capacitance. These results demonstrate that defect engineering through careful tuning of MoS2 nanosheet synthesis allows for considerable improvements to the intrinsic capacitance

Utilizing Win Ratio Approaches and Two-Stage Enrichment Designs for Small-Sized Clinical Trials

Conventional methods for analyzing composite endpoints in clinical trials often only focus on the time to the first occurrence of all events in the composite. Therefore, they have inherent limitations because the individual patients' first event can be the outcome of lesser clinical importance. To overcome this limitation, the concept of the win ratio (WR), which accounts for the relative priorities of the components and gives appropriate priority to the more clinically important event, was examined. For example, because mortality has a higher priority than hospitalization, it is reasonable to give a higher priority when obtaining the WR. In this paper, we evaluate three innovative WR methods (stratified matched, stratified unmatched, and unstratified unmatched) for two and multiple components under binary and survival composite endpoints. We compare these methods to traditional ones, including the Cox regression, O'Brien's rank-sum-type test, and the contingency table for controlling study Type I error rate. We also incorporate these approaches into two-stage enrichment designs with the possibility of sample size adaptations to gain efficiency for rare disease studies

Structure and cleavage of monosodium urate monohydrate crystals

The structural study of monosodium urate monohydrate, as the principal component in gout stones, reveals that a simple and biocompatible way to breakdown the crystals into polymerised molecules at pH of 7.4 (the acidity of normal human blood) is to peel off them along the [001] direction by sonication.PostprintPeer reviewe

Analysis of Communication Strategies and Approaches of Social Smart Elderly Caring Service Platform

With the development of Internet technology and the intensification of population aging, whether to provide effective smart old-age service security for the elderly has become a social public issue of concern. Through convenient Internet information technology, build an Internet communication platform for smart elderly caring services, and provide comprehensive care and convenience for the elderly with the help of elderly care information dissemination and community mutual assistance in the platform, in order to improve the quality of life of the elderly and the level of social elderly care services, and promote the development of community elderly care services and the elderly silver industry chain. Therefore, aiming at the possible problems in the information communication process of the social smart elderly caring service platform, this paper explores the effective communication strategies and approaches of the social smart elderly caring service platform, which has practical social significance and value

A high-frequency mobility big-data reveals how COVID-19 spread across professions, locations and age groups

As infected and vaccinated population increases, some countries decided not to impose non-pharmaceutical intervention measures anymore and to coexist with COVID-19. However, we do not have a comprehensive understanding of its consequence , especially for China where most population has not been infected and most Omicron transmissions are silent. This paper serves as the first study to reveal the complete silent transmission dynamics of COVID-19 overlaying a big data of more than 0.7 million real individual mobility tracks without any intervention measures throughout a week in a Chinese city, with an extent of completeness and realism not attained in existing studies. Together with the empirically inferred transmission rate of COVID-19, we find surprisingly that with only 70 citizens to be infected initially, 0.33 million becomes infected silently at last. We also reveal a characteristic daily periodic pattern of the transmission dynamics, with peaks in mornings and afternoons. In addition, retailing, catering and hotel staff are more likely to get infected than other professions. Unlike all other age groups and professions, elderly and retirees are more likely to get infected at home than outside home.Comment: 39 pages, 5+9 figure

ChatGPT Informed Graph Neural Network for Stock Movement Prediction

ChatGPT has demonstrated remarkable capabilities across various natural language processing (NLP) tasks. However, its potential for inferring dynamic network structures from temporal textual data, specifically financial news, remains an unexplored frontier. In this research, we introduce a novel framework that leverages ChatGPT's graph inference capabilities to enhance Graph Neural Networks (GNN). Our framework adeptly extracts evolving network structures from textual data, and incorporates these networks into graph neural networks for subsequent predictive tasks. The experimental results from stock movement forecasting indicate our model has consistently outperformed the state-of-the-art Deep Learning-based benchmarks. Furthermore, the portfolios constructed based on our model's outputs demonstrate higher annualized cumulative returns, alongside reduced volatility and maximum drawdown. This superior performance highlights the potential of ChatGPT for text-based network inferences and underscores its promising implications for the financial sector.Comment: Under Review. 10 pages, 2 figure

Convolutional Neural Networks and Feature Fusion for Flow Pattern Identification of the Subsea Jumper

The gas–liquid two-phase flow patterns of subsea jumpers are identified in this work using a multi-sensor information fusion technique, simultaneously collecting vibration signals and electrical capacitance tomography of stratified flow, slug flow, annular flow, and bubbly flow. The samples are then processed to obtain the data set. Additionally, the samples are trained and learned using the convolutional neural network (CNN) and feature fusion model, which are built based on experimental data. Finally, the four kinds of flow pattern samples are identified. The overall identification accuracy of the model is 95.3% for four patterns of gas–liquid two-phase flow in the jumper. Through the research of flow profile identification, the disadvantages of single sensor testing angle and incomplete information are dramatically improved, which has a great significance on the subsea jumper’s operation safety.publishedVersio