Policy, Space and Governance: Lessons from Beijing

Beijing is China’s capital city with a population of over 22 million. It is known to be well on its way to be a “World City,” – one that has something to do with or concerns people from all over the world. At the same time, Beijing is known as a city that tops the world in traffic congestion and bad PM 2.5. Many plans and efforts have been over the years by the city of Beijing to improve its urban life. Nonetheless, the problems do not seem to disappear. This paper, by tracing the planning efforts made in Beijing and changing policy orientations at the national level, reveals the intricate relationship between policy, planning, and urban governance. The authors argue, in our modern time, planning needs to be more integrated with public policy, public policy needs to be more relevant to that  with Number I Many authors tried to describe Beijing. Few, however, tempted to explain how it has become the way it is from a planner’s perspective. This paper is an effort filling this gap. It traces the trajectory of urban planning and urban evolution in Beijing since 1949, the founding year of the new China. This period of time, although relatively short, has greatly affected the way the city is and offers a great deal for city planners and city governors to ponder.  Through a discussion of the background, planning process, and characteristics of different versions of the city’s Master plans and the relationships between the Plans and their implementation, the authors reveal an incompatibility between urban planning and China’s policy implementation protocol, which is movement based. In order China’s urban planning can have more meaningful significance, new ideas, new strategies, new implementation protocols, and even new institutional arrangements are necessary

Factors That Influence The Regional Agricultural Production Structure In China

An analysis of the regional specialization trend in China since the beginning of its economic reform in 1979, and the determinants of this trend. The indices of regional specialization are calculated for years 1985 to 2006. Important policy changes during this period, mainly agricultural policy changes, are discussed. After applying the fixed effect regression on a modified Heckscher-Ohlin model, it is found that: (a) among scale, natural resource and human investment variables, only human investment are significant; (b) WTO membership has had a positive total effect on regional specialization of China's agricultural production; (c) Regions that produce a larger portion of exportable products have become more specialized since entering WTO; (d) Center region of China is the one with the least specialization

\u3cem\u3eJMASM30\u3c/em\u3e PI-LCA: A SAS Program Computing the Two-point Mixture Index of Fit for Two-class LCA Models with Dichotomous Variables (SAS)

The two-point mixture index of fit enjoys some desirable features in model fit assessment and model selection, however, a need exists for efficient computational strategies. Applying an NLP algorithm, a program using the SAS matrix language is presented to estimate the two-point index of fit for two-class LCA models with dichotomous response variables. The program offers a tool to compute π ∗ for twoclass models and it also provides an alternative program for conducting latent class analysis with SAS. This study builds a foundation for further research on computational approaches for M-class models

Effects of Model Selection on the Coverage Probability of Confidence Intervals in Binary-Response Logistic Regression

While model selection is viewed as a fundamental task in data analysis, it imposes considerable effects on the subsequent inference. In applied statistics, it is common to carry out a data-driven approach in model selection and draw inference conditional on the selected model, as if it is given a priori. Parameter estimates following this procedure, however, generally do not reflect uncertainty about the model structure. As far as confidence intervals are concerned, it is often misleading to report estimates based upon conventional 1−α without considering possible post-model-selection impact. This paper addresses the coverage probability of confidence intervals of logit coefficients in binary-response logistic regression. We conduct simulation studies to examine the performance of automatic model selectors AIC and BIC, and their subsequent effects on actual coverage probability of interval estimates. Important considerations (e.g. model structure, covariate correlation, etc.) that may have key influence are investigated. This study contributes in terms of understanding quantitatively how the post-model-selection confidence intervals perform in terms of coverage in binary-response logistic regression models. A major conclusion was that while it is usually below the nominal level, there is no simple predictable pattern with regard to how and how far the actual coverage probability of confidence intervals may fall. The coverage probability varies given the effects of multiple factors: (1) While the model structure always plays a role of paramount importance, the covariate correlation significantly affects the interval's coverage, with the tendency that a higher correlation indicates a lower coverage probability. (2) No evidence shows that AIC inevitably outperforms BIC in terms of achieving higher coverage probability, or vice versa. The model selector's performance is dependent upon the uncertain model structure and/or the unknown parameter vector θ . (3) While the effect of sample size is intriguing, a larger sample size does not necessarily achieve asymptotically more accurate inference on interval estimates. (4) Although the binary threshold of the logistic model may affect the coverage probability, such effect is less important. It is more likely to become substantial with an unrestricted model when extreme values along the dimensions of other factors (e.g. small sample size, high covariate correlation) are observed

Molecular profiling of the developing mouse axial skeleton: a role for Tgfbr2 in the development of the intervertebral disc

Background Very little is known about how intervertebral disc (IVD) is formed or maintained. Members of the TGF-β superfamily are secreted signaling proteins that regulate many aspects of development including cellular differentiation. We recently showed that deletion of Tgfbr2 in Col2a expressing mouse tissue results in alterations in development of IVD annulus fibrosus. The results suggested TGF-β has an important role in regulating development of the axial skeleton, however, the mechanistic basis of TGF-β action in these specialized joints is not known. One of the hurdles to understanding development of IVD is a lack of known markers. To identify genes that are enriched in the developing mouse IVD and to begin to understand the mechanism of TGF-β action in IVD development, we undertook a global analysis of gene expression comparing gene expression profiles in developing mouse vertebrae and IVD. We also compared expression profiles in tissues from wild type and Tgfbr2 mutant mice as well as in sclerotome cultures treated with TGF-β or BMP4. Results Lists of IVD and vertebrae enriched genes were generated. Expression patterns for several genes were verified either through in situ hybridization or literature/database searches resulting in a list of genes that can be used as markers of IVD. Cluster analysis using genes listed under the Gene Ontology terms multicellular organism development and pattern specification indicated that mutant IVD more closely resembled vertebrae than wild type IVD. We also generated lists of genes regulated by TGF-β or BMP4 in cultured sclerotome. As expected, treatment with BMP4 resulted in up-regulation of cartilage marker genes including Acan, Sox 5, Sox6, and Sox9. In contrast, treatment with TGF-β1 did not regulate expression of cartilage markers but instead resulted in up-regulation of many IVD markers including Fmod and Adamtsl2. Conclusions We propose TGF-β has two functions in IVD development: 1) to prevent chondrocyte differentiation in the presumptive IVD and 2) to promote differentiation of annulus fibrosus from sclerotome. We have identified genes that are enriched in the IVD and regulated by TGF-β that warrant further investigation as regulators of IVD development

Identification of Aluminum Responsive Genes in Al-Tolerant Soybean Line PI 416937

Soybean is one of the most aluminum (Al) sensitive plants. The complex inheritance of Al tolerance trait has so far undermined breeding efforts to develop Al-tolerant soybeans. Discovering the genetic factors underlying the Al tolerance mechanisms would undoubtedly accelerate the pace of such endeavor. As a first step toward this goal, we analyzed the transcriptome profile in roots of Al-tolerant soybean line PI 416937 comparing Al-treated and untreated control plants using DNA microarrays. Many genes involved in transcription activation, stress response, cell metabolism and signaling were differentially expressed. Patterns of gene expression and mechanisms of Al toxicity and tolerance suggest that Cys2His2 and ADR6 transcription activators, cell wall modifying enzymes, and phytosulfokines growth factor play role in soybean Al tolerance. Our data provide insights into the molecular mechanisms of soybean Al tolerance and will have practical value in genetic improvement of Al tolerance trait

GenDrux: A biomedical literature search system to identify gene expression-based drug sensitivity in breast cancer

Background This paper describes the development of a web-based tool, GenDrux, which extracts and presents (over the Internet) information related to the disease-gene-drug nexus. This information is archived from the relevant biomedical literature using automated methods. GenDrux is designed to alleviate the difficulties of manually processing the vast biomedical literature to identify disease-gene-drug relationships. GenDrux will evolve with the literature without additional algorithmic modifications. Results GenDrux, a pilot system, is developed in the domain of breast cancer and can be accessed at http://www.microarray.uab.edu/drug_gene.pl. GenDrux can be queried based on drug, gene and/or disease name. From over 8,000 relevant abstracts from the biomedical literature related to breast cancer, we have archived a corpus of more than 4,000 articles that depict gene expression-drug activity relationships for breast cancer and related cancers. The archiving process has been automated. Conclusions The successful development, implementation, and evaluation of this and similar systems when created may provide clinicians with a tool for literature management, clinical decision making, thus setting the platform for personalized therapy in the future