广州市北京路步行街旅游形象策划

商业步行街是当今城市旅游购物和休闲的一个重要场所。广州市北京路是广州历史和现代有名的商业街之一,也是广州的一个著名景点。为了更好地包装广州市北京路的旅游形象,在详细分析其旅游文脉和旅游发展现状的基础上,采用企业识别系统的相关理论,对该区旅游形象MI、BI、VI三个方面进行了较为科学的策划。认为广州市北京路应突出“岭南第一街”的特点,对步行街的企业行为系统、市民行为系统等进行有效管理和规范,并改善现有的视觉景观和视觉标志,着力塑造一个集旅游观光、购物消费和休闲娱乐于一体的旅游形象。     

印象榔梨

榔梨,地处省会长沙东郊浏阳河畔,镇域总面积34平方公里,辖5村3社区,总人口6万人,其中集镇建成区面积5平方公里。2010年,全镇168家工业企业完成企业总产值40亿元,其中50家规模企业完成企业总产值35亿元。实现镇域财政收入8.2亿元,其中镇级财政收入4亿元,同比增长63%。是全市2009年度＂十强乡镇＂、＂城乡一体化试点镇＂。     

政策

26宗住宅闲置土地名单公布 2010年12月30日，国土资源部发布《关于房地产闲置土地情况的公告》，公布了北京等地由房地产开发企业自身原因造成且尚未处置的26宗住宅闲置土地相关情况。公告显示，位于北京、上海、江苏、福建、河南、湖北、湖南、云南的26宗住宅闲置土地，总面积达201．7公顷。（中国国土资源报）     

枣庄：逃离“矿竭城衰”陷阱

打开百度,搜索＂枣庄＂,别称一栏赫然显示＂煤城＂。枣庄人说,这是一个因枣得名,因煤而兴的城市。然而,很少有人知道,中国历史上最大的民族资本企业＂中兴公司＂就诞生于枣庄,与河北的开滦煤矿、辽宁的抚顺煤矿并称为中国的＂三大煤矿＂;中国工业史上的第一支股票也是从此处走进人们的视野。     

模式内部变率引起的1.5℃和2℃升温阈值出现时间模拟的不确定性研究

模式内部变率是模拟结果不确定性的重要来源,然而它对于1.5℃和2℃升温阈值出现时间不确定性的影响尚不清楚。因此,基于耦合模式比较计划第五阶段(CMIP5)的多模式数据研究了模式内部变率对1.5℃和2℃升温阈值出现时间不确定性的影响以及对未来排放情景的敏感性。结果表明,模式内部变率对升温阈值出现时间模拟的影响与外强迫的影响相当,单个模式内部不同成员达到全球平均1.5℃或2℃增温的年份相差2~12年;其影响具有明显的空间差异,影响极大值出现在欧亚大陆以北洋面、白令海峡周围区域、北美东北部及其与格陵兰岛之间的海域、南半球高纬地区等;低排放情景下模式内部变率的影响大于高排放情景。     

区域产业升级理论评价和升级目标层次论建构

产业升级相关文献综述表明,区域产业升级具有丰富的理论含义.产业结构升级研究寻求对产业宏观结构比例的统计学意义上的优化;产业地域分工思路则考察产业分布演进的空间格局及其升级含义;企业升级思路则细化到产业内部,指出企业创新以获得更高附加值是产业升级的根本;集群研究则注意到区域产业发展的整体特征,并指出了推动产业集聚、产业联系与创新等升级含义.中国集群实践更进一步验证了集群层面集体效率的提升以及企业发展环境的和谐共进(区域发展目标)也是影响产业升级的重要方面.在讨论产业升级的经济维度与空间维度、个体层面与系统层面的基础上重新构建区域产业发展的理论框架,认为企业升级、集群升级和区域和谐3个层次构成了区域产业升级的3个目标层次,其相互衔接与互动对于区域产业发展具有重要意义.     

违法用地中的政府行为

面对人多地少,发展经济需要占用土地的矛盾,土地违法事件愈演愈烈,几呈泛滥之势,而且查处的难度越来越大。这些问题表面看来是个人与企业等违法乱占土地,但其本质在于地方政府违法。     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models: An Empirical Validation of ISWRidge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p 〈0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to cheek the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height （X1 ） and potential energy （X2 ） significantly impact （p 〈 0. 0001 ） the amplitude-based refleeted rate; the P-values for the deviance and Pearson are all 〉 0.05 （0.2839, 0.3438, respectively）. That is, the goodness-of-fit between ridge height （ X1 ） and potential energy （X2） can further predict parameters under the scenario of the best parsimonious model. Investigation of 6 predictive powers （ R2, Max-rescaled R^2, Sorners＇ D, Gamma, Tau-a, and c, respectively） indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.     

Evaluation of Inference Adequacy in Cumulative Logistic Regression Models： An Empirical Validation of ISW-Ridge Relationships

Internal solitary wave propagation over a submarine ridge results in energy dissipation, in which the hydrodynamic interaction between a wave and ridge affects marine environment. This study analyzes the effects of ridge height and potential energy during wave-ridge interaction with a binary and cumulative logistic regression model. In testing the Global Null Hypothesis, all values are p<0.001, with three statistical methods, such as Likelihood Ratio, Score, and Wald. While comparing with two kinds of models, tests values obtained by cumulative logistic regression models are better than those by binary logistic regression models. Although this study employed cumulative logistic regression model, three probability functions p^1, p^2 and p^3, are utilized for investigating the weighted influence of factors on wave reflection. Deviance and Pearson tests are applied to check the goodness-of-fit of the proposed model. The analytical results demonstrated that both ridge height (X1) and potential energy (X2) significantly impact (p<0.0001) the amplitude-based reflected rate; the P-values for the deviance and Pearson are all >0.05 (0.2839, 0.3438, respectively). That is, the goodness-of-fit between ridge height (X1) and potential energy (X2) can further predict parameters under the scenario of the best parsimonious model.Investigation of 6 predictive powers (R2, Max-rescaled R2, Somers'D, Gamma, Tau-a, and c, respectively) indicate that these predictive estimates of the proposed model have better predictive ability than ridge height alone, and are very similar to the interaction of ridge height and potential energy. It can be concluded that the goodness-of-fit and prediction ability of the cumulative logistic regression model are better than that of the binary logistic regression model.