Adjusting to Really Big Changes: The Labor Market in China, 1989-2009

China’s emerging labor market was buffeted by changes in demand and supply and institutional changes in the last two decades. Using the Chinese Urban Household Survey data from 1989 to 2009, our study shows that the market responded with substantial changes in the structure of wages and in employment and types of jobs that workers obtained that mirrors the adjustments found in labor markets in advanced economies. However, the one place where the Chinese labor market appears to diverge from the labor markets in advanced countries is the rapid convergence in earnings and occupational positions of cohorts who entered the job market under more or less favorable conditions. On this dimension, China’s labor market seems more flexible than those in other countries. Three related factors may explain this pattern: (1) the rapid growth of China’s economy; (2) the high rate of employee turnover; (3) the relative weakness of internal labor markets in China. Bottom line, the Chinese labor market has responded about as well as one could expect to the changes in the demand and supply factors and institutional shocks in this critical period in Chinese economic history.

Adoption and Termination of Employee Involvement Programs

This study uses a 10-year longitudinal database on U.S. manufacturing establishments to analyze the dynamics of the adoption and termination of employee involvement programs (EI). We show that firms' use of EI has not grown continuously, but rather introduce and terminate EI policies in ways that imply that the policies are complementary with each other and with other advanced human resource practices, seemingly moving toward an equilibrium distribution of EI policies. Using a Markov model, we estimate the long-run distribution of the number of EI programs in firms and find that adjustment to the steady-state distribution takes about 20 years.

Introduction of DSP technology into the bioelectronics laboratory class

Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.Includes bibliographical references (leaf 46).by Richard Perng.S.B.and M.Eng

Asian American Nonprofit Organizations in U.S. Metropolitan Areas

This article analyzes the characteristics of Asian American nonprofit organizations in major U.S. metropolitan areas. The data are based on internet archives of nonprofit organization Form 990 and related information. Asian American nonprofits are less than 20 years old on average. They remain a relatively small part of the nonprofit sector. Religious organizations are generally the largest group among Asian American nonprofits, followed by cultural organizations, service agencies, and public interest associations of similar proportions. Asian American secular organizations as a group tend to be younger, are more likely to by in central cities, in wealthy and poor communities, as well as in metropolitan areas with a more homogenous Asian ethnic population and a relatively more active general population in community organizing. The opposite is true for religious Asian American organizations. The pattern is less consistent among Asian American cultural, service, and public interest organizations. Regarding organization size, more established Asian American nonprofits, pan-Asian American organizations, and those agencies located in communities with a larger Asian American population have more total assets and annual revenue

Innate recognition of non-self nucleic acids

A variety of innate immune system receptors recognize and respond to the nucleic acids of invading pathogens

Accurate Force Field for Molybdenum by Machine Learning Large Materials Data

In this work, we present a highly accurate spectral neighbor analysis potential (SNAP) model for molybdenum (Mo) developed through the rigorous application of machine learning techniques on large materials data sets. Despite Mo's importance as a structural metal, existing force fields for Mo based on the embedded atom and modified embedded atom methods still do not provide satisfactory accuracy on many properties. We will show that by fitting to the energies, forces and stress tensors of a large density functional theory (DFT)-computed dataset on a diverse set of Mo structures, a Mo SNAP model can be developed that achieves close to DFT accuracy in the prediction of a broad range of properties, including energies, forces, stresses, elastic constants, melting point, phonon spectra, surface energies, grain boundary energies, etc. We will outline a systematic model development process, which includes a rigorous approach to structural selection based on principal component analysis, as well as a differential evolution algorithm for optimizing the hyperparameters in the model fitting so that both the model error and the property prediction error can be simultaneously lowered. We expect that this newly developed Mo SNAP model will find broad applications in large-scale, long-time scale simulations.Comment: 25 pages, 9 figure