China’s Informal Institutions: the Case of Private Enterprise in Wenzhou

The private enterprises have been growing at a rapid pace during the last 20 years in China. The private sector now accounts for 62 percent of the total economic activity, contributing 71 percent of gross industrial output (China’s Bureau of Statistics, 2008). Despite this impressive growth, the private sector is still facing formal institutional restrictions, such as limited state bank loans, heavy tax burdens, higher requirement for registration and licensing, competitions from state-owned counterparts, and so on (Bramall, 2008). The survival and prosperity of private enterprises, to some extent, have to resort to the adaptive informal strategies by bending governmental rules. One of the Chinese cultural byproducts, guanxi, that is, an interpersonal network, plays a significant part in this process. Previous research has shown that guanxi, especially the patron-client ties, can help entrepreneurs reduce potential risks, facilitate business transactions, create alternative financing channels, and promote business success (Leung and Wong, 1995)

A Comparative Look at Attitudes toward Gender and Division of Household Labor in Russia, Japan, Germany and the United States

This article uses a comparative approach and a macro-institutional framework to examine the influence of historical, social, political and cultural contexts on attitudes toward gender and division of household labor (including childcare). Data used to answer the research questions come from the 2002 International Social Survey Program (ISSP) module on Family and Changing Gender Roles. Four countries that represent distinctive social, political, and economic systems are examined--US, West Germany, Russia and Japan. Findings show that attitudes toward gender and household labor differ across the four countries. Generally, respondents from Japan and West Germany show relatively more conservative attitudes, whereas those from the U.S. show more progressive attitudes. Russian respondents exhibit some kind of mixed attitudes toward gendered division of household labor. On some measures, e.g. attitudes regarding gender and childcare, respondents from Russia tend to be more progressive than those from the US, West Germany and Japan; but on other measures, e.g. attitudes toward gender roles (men’s job as breadwinners and women’s as homemakers), Russian respondents tend to be more conservative than respondents from the other three countries. The inconsistency of their responses to different measures reflects the complexity of the historical and cultural influence on gender attitudes in Russia. Findings also show a gap between men and women, with women being more progressive than men in attitudes toward gender and division of household labor. Male-female differences vary across countries. In the measure regarding men and childcare, the gender gap is greatest in the U.S, followed by West Germany, Japan, and least in Russia. In the measure regarding men and household work, Russia shows the greatest gender gap, followed by West Germany and the U.S, Japan shows the least. This variation in the size of the gender gap, again, reflects the complex influence of institutional and cultural on men’s and women’s attitudes toward gendered division of labor

Attitudes toward Female Labor Force Participation in Eastern and Western Europe

Fair employment opportunities for women are considered as a strong indicator for achieving gender equity. Despite a steady growth in the rates of female labor force participation, chances for men and women to get employed and promoted in the workforce remain uneven. Moreover, the gender pay gap still exists and widens as educational attainment and job tenure increase (Bonvillain, 2006). The unfairness for women’s employment provokes researchers to examine the belief system on women’s role in work and family. Previous research has documented a strong association between gender attitudes and the actual social opportunities for women.  For example, studies on attitudes about gender, work and family among scientists contend that stereotypical attitudes about women’s occupations in science might create interactions and structures that help legitimatize the gender hierarchy and maintain science as a male domain (Hanson et al. 2004). Other research argues that as the rate of women’s labor force participation increases, attitudes change toward a greater acceptance of women’s non-familial roles (Cherlin and Walters, 1981; Mason and Lu, 1988).This paper examines attitudes toward women’s labor force participation which can influence and be influenced by the actual work environment for women, in order to gain a thorough understanding of gender inequality that  exist in the workforce

Impact of Simulated 1/f Noise for HI Intensity Mapping Experiments

Cosmology has entered an era where the experimental limitations are not due to instrumental sensitivity but instead due to inherent systematic uncertainties in the instrumentation and data analysis methods. The field of HI intensity mapping (IM) is still maturing, however early attempts are already systematics limited. One such systematic limitation is 1/f noise, which largely originates within the instrumentation and manifests as multiplicative gain fluctuations. To date there has been little discussion about the possible impact of 1/f noise on upcoming single-dish HI IM experiments such as BINGO, FAST or SKA. Presented in this work are Monte-Carlo end-to-end simulations of a 30 day HI IM survey using the SKA-MID array covering a bandwidth of 950 and 1410 MHz. These simulations extend 1/f noise models to include not just temporal fluctuations but also correlated gain fluctuations across the receiver bandpass. The power spectral density of the spectral gain fluctuations are modelled as a power-law, and characterised by a parameter $\beta$. It is found that the degree of 1/f noise frequency correlation will be critical to the success of HI IM experiments. Small values of $\beta$ ($\beta$ < 0.25) or high correlation is preferred as this is more easily removed using current component separation techniques. The spectral index of temporal fluctuations ($\alpha$) is also found to have a large impact on signal-to-noise. Telescope slew speed has a smaller impact, and a scan speed of 1 deg s$^{-1}$ should be sufficient for a HI IM survey with the SKA.Comment: 22 pages, 15 figures, 2 table

Rapid land cover classification using a 36-year time series of multi-source remote sensing data

Long-time series land cover classification information is the basis for scientific research on urban sprawl, vegetation change, and the carbon cycle. The rapid development of cloud computing platforms such as the Google Earth Engine (GEE) and access to multi-source satellite imagery from Landsat and Sentinel-2 enables the application of machine learning algorithms for image classification. Here, we used the Random Forest algorithm to quickly achieve a time series land cover classification at different scales based on the fixed land classification sample points selected from images acquired in 2022, and the year-by-year spectral differences of sample points. The classification accuracy was enhanced by using multi-source remote sensing data, such as synthetic aperture radar (SAR) and digital elevation model (DEM) data. The results showed that: (i) the maximum difference (threshold) of sample points without land class change determined by counting the sample points of each band of landsat time series from 1986 to 2022 was 0.25; (ii) the kappa coefficient and observed accuracy of the same sensor from Landsat 8 are higher than the results of TM and ETM+ sensor data from 2013 to 2022; (iii) the addition of a mining land cover type increase the kappa coefficient and overall accuracy mean values of the Sentinel 2 image classification for a complex mining and -forest area. Among the land classifications by multi-source remote sensing, the combined variables spectral band + index + topography + SAR result in the highest accuracy, but the overall improvement is limited. The method proposed is applicable to remotely sensed images at different scales and using sensors under complex terrain conditions. The use of GEE cloud computing platform enabled rapid analysis of remotely sensed data to produce land cover maps with high-accuracy and a long time series

HI intensity mapping with FAST

We discuss the detectability of large-scale HI intensity fluctuations using the FAST telescope. We present forecasts for the accuracy of measuring the Baryonic Acoustic Oscillations and constraining the properties of dark energy. The FAST $19$-beam L-band receivers ($1.05$--$1.45$ GHz) can provide constraints on the matter power spectrum and dark energy equation of state parameters ($w_{0},w_{a}$) that are comparable to the BINGO and CHIME experiments. For one year of integration time we find that the optimal survey area is $6000\,{\rm deg}^2$. However, observing with larger frequency coverage at higher redshift ($0.95$--$1.35$ GHz) improves the projected errorbars on the HI power spectrum by more than $2~\sigma$ confidence level. The combined constraints from FAST, CHIME, BINGO and Planck CMB observations can provide reliable, stringent constraints on the dark energy equation of state.Comment: 7 pages, 3 figures, submitted to "Frontiers in Radio Astronomy and FAST Early Sciences Symposium 2015" conference proceedin

Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks

Establishing open and general benchmarks has been a critical driving force behind the success of modern machine learning techniques. As machine learning is being applied to broader domains and tasks, there is a need to establish richer and more diverse benchmarks to better reflect the reality of the application scenarios. Graph learning is an emerging field of machine learning that urgently needs more and better benchmarks. To accommodate the need, we introduce Graph Learning Indexer (GLI), a benchmark curation platform for graph learning. In comparison to existing graph learning benchmark libraries, GLI highlights two novel design objectives. First, GLI is designed to incentivize \emph{dataset contributors}. In particular, we incorporate various measures to minimize the effort of contributing and maintaining a dataset, increase the usability of the contributed dataset, as well as encourage attributions to different contributors of the dataset. Second, GLI is designed to curate a knowledge base, instead of a plain collection, of benchmark datasets. We use multiple sources of meta information to augment the benchmark datasets with \emph{rich characteristics}, so that they can be easily selected and used in downstream research or development. The source code of GLI is available at \url{https://github.com/Graph-Learning-Benchmarks/gli}.Comment: Oral Presentation at LOG 202

Based on Network Pharmacology and Molecular Docking to Discuss the Mechanism of Antitussive and Expectorant Action of Ruanerli

The antitussive and expectorant effects of Ruanerli and its mechanism were investigated by methods of network pharmacology. The outcomes predicted were verified by molecular docking and animal experiments. The components and targets of Ruanerli were obtained by literature investigation and TCMSP database screen. Mapping with two groups of genes related to "cough" and "sputum" from GeneCards database, the target genes of antitussive and expectorant effects of Ruanerli were obtained. GO and KEGG enrichment analysis of the target genes was performed by Metascape platform. The PPI network among the target genes was constructed through STRING data platform. Cytoscape plugin CytoHubba was used to screen the Top10 genes related to antitussive and expectorant effects of Ruanerli, and KEGG pathway enrichment was performed on the Top10 genes through Metascape data platform to predict the possible signal pathways involved in antitussive and expectorant effects of Ruanerli. Autodock Vina was used for molecular docking between the predicted Top10 gene proteins and the Top 3 active ingredients of Ruanerli. Finally, the predicted results were verified by ammonia induced cough test and phenol red excretion test. According to the analysis of multiple databases, 51 chemical components and 282 corresponding targets have been reported, eighty of them were related to the antitussive and expectorant effects of Ruanerli. The Top10 genes selected by Degree value were mainly concentrated in infection and immune-related pathways. Molecular docking test showed that the Top10 genes had strong binding activity with the Top3 chemical components (Caffeic acid, Rutin and Valeraldehyde) in PPI network. Animal experiments showed that the cough induced by ammonia was significantly inhibited when treated with Ruanerli in mice. The levels of IL-6 and IL-13 in serum were reduced and the excretion of phenol red in mice trachea was increased. PCR and WB detection showed that the mRNA levels and protein expressions of inflammatory genes IL6, IL1B, VEGFA, PTGS2 and MAPK3 were decreased, suggesting that the antitussive and expectorant effects of Ruanerli might be related to decreasing the expression of inflammatory genes and the release of inflammatory factors