增速正常回归,总体运行良好——2011年6月港口运输生产简评

2011年上半年,国家坚持实施积极的财政政策和稳健的货币政策,治理通胀,控制经济增速,第二季度GDP同比增长9.5%,较第一季度放缓0.2个百分点。受宏观经济影响，6月份港口运输生产继续高位运行（见表1），但发展速度有所放缓，其主要特点如下：

宏大叙事的日常回归——徐汇衡复风貌区保护更新样本

作家陈丹燕在《永不拓宽的街道》一书后序中说，对于上海历史文化风貌区的保护更像是让我们记得来时的路。当她在书里细数一条条历史街道以及与之相关的人、事、物时，这些故事仿佛比作家著名的“上海三部曲”来得更有滋有味。

增速正常回归 总体运行良好——6月份港口运输生产简评

2011年上半年．国家坚持实施积极的财政政策和稳健的货币政策，治理通胀．控制经济增速．二季度国内生产总值（GDP）同比增长9．5％，较一季度放缓了0．2个百分点。受宏观经济影响．6月份港口运输生产继续高位运行．但发展速度有所放缓。至6月30日，上半年港口运输生产总体呈平稳增长态势。

苗木价格下跌是苗木市场的理性回归么?

今年的苗木市场有所回暖，让很多苗木人看到了希望，但是这种小幅度增涨依旧无法与前几年高潮时相比。据业内人士分析．现在的苗木行情确实是大不如前，但这却是苗木行惰在经历了10多年疯狂后的正常回归。这样的回归，既有其理性，也是苗木市场走向正常的表现。

Poisson分布的特征

证明了满足EX =DX <∞的具有非退化分布的母体X服从Poisson分布的充要条件是T2 -T1关于T1有常回归 ,其中T1= X =1n∑ni =1Xi,T2 =1n- 1∑ni =1(Xi- X) 2

一类Poisson型分布的特征

证明了满足EX2 <∞的具有非退化分布的母体X服从Poisson型分布P(λ ,α ,1)的充要条件是T2 -T1关于T1有常回归 ,其中T1= X =1n ∑ni =1Xi,T2 =1n - 1∑ni=1(Xi- X) 2

风电场输出功率的多时段联合概率密度预测

风电场输出功率波动性较强,难以精确预测,掌握其输出功率的分布规律对含有风电场的电力系统的运行决策具有重要意义。文中在分析风电场有功功率输出特性的基础上,提出了风电场输出功率多时段联合概率密度预测,利用风电场输出功率在时段间较强的相关性,估计其波动的幅度与速度特征,为系统运行提供更全面的决策信息。结合多元回归估计常条件相关—多元广义自回归条件异方差(CCC-MGARCH)模型与稀疏贝叶斯学习方法,给出了一种基于数值天气预报信息的风电场输出功率短期多时段联合概率密度预测方法。该方法依据CCC-MGARCH模型思想,将未来多个时段内风电场输出功率的联合概率密度预测问题分解为:风电场在各个时段内独立的输出功率概率密度预测子问题和时段间关联的输出功率预测误差相关系数矩阵估计子问题,利用稀疏贝叶斯学习方法在概率密度预测问题上的优势,形成预测效果好、计算效率高的风电场输出功率多时段联合概率密度预测方法。应用实例与分析说明了该方法的有效性。

华丽·素朴·丑陋——《立春》难解之“孔雀”情结

继《孔雀》后顾长卫第二部独立执导的影片《立春》问世,影片彰显的是一个个孤独又纠结的中小城市的另类,因了对音乐、美术、舞蹈等艺术的钟情爱好,总想出类拔萃,于是屡战屡败、屡败屡战,结局是绝大多数回归庸常。与其说这是一部关于'理想与现实'主题的影片,不如说是一部人与人之间难以理解、沟通、宽容却又仍要理解、沟通、宽容的影片。从情感的角度来看,还是哈代说的那句话:呼唤人的和被呼唤的,很少能够相互应答。

2005年1-3季度印机行业57家主要企业指标完成情况分析

2005年1～3季度,印机行业经济走势继续正常回归,虽有波动,但增长平稳.

2005年上半年印机行业57家主要企业指标完成情况分析

2005年上半年,印机行业汇总了57家主要成员单位的统计报表,从上半年经济运行的各项经济指标看,印机行业经济发展走势正常回归,略有波动.简要分析如下:

IPO重启利空有限 绩优蓝筹股值得关注

中国证监会于2009年5月22日就《关于进一步改革和完善新股发行体制的指导意见(征求意见稿)》公开征求社会意见,证监会征求意见稿的发布意味着A股IPO将于近期重启。虽然IPO重启是股市的融资功能正常回归,本来在市场预期之中,但市场仍出现了短期的调整。如何理解IPO重启对股市的影响?投资者应该如何操作?我们认为,IPO重启利空有限,A股市场表现关键还是要看宏观经济、上市公司盈利预期和股票估值三个因素。在市场机会把握方面,在IPO的前期,投资者应该重点关注绩优蓝筹股的投资机会和那些参股即将进行IPO的上市公司,在IPO的中后期,应重点关注打新股。

An Experiment of a Statistical Downscaling Forecast Model for Summer Precipitation over China

A combination of the optimal subset regression (OSR) approach,the coupled general circulation model of the National Climate Center (NCC-CGCM) and precipitation observations from 160 stations over China is used to construct a statistical downscaling forecast model for precipitation in summer.Retroactive forecasts are performed to assess the skill of statistical downscaling during the period from 2003 to 2009.The results show a poor simulation for summer precipitation by the NCCCGCM for China,and the average spatial anomaly correlation coefficient (ACC) is 0.01 in the forecast period.The forecast skill can be improved by OSR statistical downscaling,and the OSR forecast performs better than the NCC-CGCM in most years except 2003.The spatial ACC is more than 0.2 in the years 2008 and 2009,which proves to be relatively skillful.Moreover,the statistical downscaling forecast performs relatively well for the main rain belt of the summer precipitation in some years,including 2005,2006,2008,and 2009.However,the forecast skill of statistical downscaling is restricted to some extent by the relatively low skill of the NCCCGCM.

Catheter ablation of atrial fibrillation in the elderly

Background Atrial fibrillation （AF） catheter ablation has emerged as a promising treatment strategy for AF, but has not been widely adopted in the elderly population. The present study aimed to determine the safety and efficacy of AF catheter ablation in the elderly popula-tion. Methods and Results The study population consisted of 316 patients with paroxysmal AF who underwent left atrial ablation. Ninety-five patients were≥65 years （48 males, mean age 68.9 ± 3.0 years old） and 221 patients were〈65 years old （130 males, mean age 52.5 ± 10.4 years old）. After a mean follow-up period of 34.0 ± 15.1 months, 55 （57.9%） patients in the elderly group were free from ar-rhythmia recurrence compared with 149 （67.4%） patients in the younger group （P=0.169）. Procedural complications were uncommon in both study groups. In logistic regression analysis, left atrial diameter （P=0.003）, hypertension （P=0.001）, dyslipidemia （P=0.039）, and coronary artery disease （P=0.018） were independent predictors of AF recurrence in the elderly population. Conclusions Catheter ablation of AF is safe and effective in older patients. Invasive strategies should be considered as an alternative choice in symptomatic elderly patients with AF.

Relation between Mesophilic and Psychrotrophic Aerobic Sporulating Microorganisms in Milk

The occurrence and the detection system of mesophilic and psychrotrophic aerobic sporulating microorganisms （MPAS） in raw cow＇s milk were studied. Samples of raw cow＇s bulk tank milk were taken 21 times in 14 farms during one year. Basis of the method for MPAS assessment is the milk sample inactivation at the temperature 80-82 ℃ for 30 minutes followed by incubation in cultivation dishes at 30 -4- 1 ℃ for 3 days-mesophilic aerobic sporulates （MAS）, and at 6.5 .4- 1 ℃ for 10 days-psychrotrophic aerobic sporulates （PAS）. The total count of MPAS was within the span 2.5-340 CFU/mL （colony forming units）. Average plate count of MPAS was 59.4 CFU/mL with variation coefficient 93.1%. MPAS count found in the same dishes at incubation for mesophilic and subsequently strictly psychrophilic microorganisms （MAS ＋ SPAS） which enables to exclude overestimation of results by sporulates able to grow at both incubation temperatures was on average 56.9 CFU/mL what represents 95.8% out of the number of sums of individual dishes at two temperatures （MAS ＋ PAS）. Correlation coefficient of these two types of results r = 0.99 gives evidence of close dependence that is expressed by linear regression equation y = 0.9773x. We can consider the method using at first 30 .4- 1 ℃ and subsequently 6.5 -4-1℃ （MAS ＋ SPAS） as more correct than the method with the opposite order of cultivation temperatures because of better regression coefficient of linear dependence and higher correlation coefficient in relation to the sum of independent incubations （MAS ＋ PAS）.

Application of Fast and Robust Equalization in Communication Technology

In this paper, the authors explore the potential of several popular equalization techniques while overcoming their disadvantages. First, extensive literature survey on equalization is conducted. The focus is on popular linear equalization algorithms such as the conventional least mean square (LMS ) algorithm, the recursive least squares ( RLS ) algorithm, the filtered X LMS algorithm and their development. To overcome the slow convergence problem while keeping the simplicity of the LMS based algorithms, an H 2 optimal initialization is proposed.

Retrieval and analysis of sea surface air temperature and relative humidity

Air temperature and relative humidity have been the main parameters of meteorology study. In the past data could be obtained from in-situ observations, but the observations are local and sparse, especially over ocean. Now we can get them from satellites, yet it is hard to estimate them from sat- ellites directly so far. This paper presents a new method to retrieve monthly averaged sea air temper- ature （SAT） and relative humidity （RH） near sea surface from satellite data with artificial neural networks （ANN）. Compared with the observations in Pacific and Atlantic, the root mean square （RMS） and the correlation between the estimated SAT and the observations are about 0.91 ~C and 0.99, respectively. The RMS and the correlation of RH are about 3.73% and 0.65, respectively. Compared with the multiple regression method, the ANN methodology is more powerful in building nonlinear relations in this research. Thus the global monthly average SAT and RH are retrieved from the fixed ANN network from July 1987 to May 2004. In general the annual average SAT shows the increasing trend in recent 18 years. The abnormality of SAT is decomposed with the empirical or- thogonal function （EOF）. The leading three EOFs could explain 84% of the total variation. EOF1 （76.1%） presents the seasonal change of the SAT abnormality. EOF2 （4.6%） is mainly related with ENSO. EOF3 （3.3%） shows some new interesting phenomena appearing in the three main currents in Pacific, Atlantic and Indian Ocean.

油价反弹未可知

在金融危机的打击下,国际石油市场和国内市场都发生了巨大变化。然而,油份暴涨后的正常回归与市场环境变化带来的需求变化,需要正确地加以区别,眼下市场的低迷并不肯定为明年的总体走势。

明天的中国

未来世界不是一个由于全球化而变得平坦和统一的世界,不是一个因多极化而变得平衡的世界,而是一个被全球一体化和国家地区分裂相互对立的力量所左右的、以地缘政治和原教旨主义的反常回归和技术与通信革命为特征的、

Removing barometric pressure effects from groundwater level and identifying main influential constituents

Changes in barometric pressure can affect the micro-dynamic state of groundwater level.The groundwater level data carry a lot of important information of tectonic activity and earthquakes.It is very significant to eliminate the barometric pressure effects from the groundwater level data in order to recognize seismic anomalies effectively.With the analysis of the main influential constituents of barometric pressure and their changes,we can have a better understanding of the changes of the aquifer medium,which can provide useful information for earthquake prediction.Taking the May 12,2008 Wenchuan earthquake as an example,this paper deals with the influence of barometric pressure on groundwater level based on observational data from Nanxi,Qionglai and Chaohu wells.The methods of the linear regression and the deconvolution regression were employed to remove the barometric pressure from the groundwater level data.The harmonic analysis and the spectral analysis were used to recognize the main influential waves of barometric pressure effect.A comparison was conducted on the main influential waves before and after the earthquake.The results showed that the main influential waves of barometric pressure effect changed and the amplitudes of all constituents also changed.This phenomenon may result from the characteristics of the influential constituents of pressure,or from the changes of the aquifer medium,which were caused by the earthquake.

Forecasting Container Throughput of Qingdao Port with a Hybrid Model

This paper proposes a hybrid forecasting method to forecast container throughput of Qingdao Port.To eliminate the influence of outliers,local outlier factor(lof) is extended to detect outliers in time series,and then different dummy variables are constructed to capture the effect of outliers based on domain knowledge.Next,a hybrid forecasting model combining projection pursuit regression(PPR) and genetic programming(GP) algorithm is proposed.Finally,the hybrid model is applied to forecasting container throughput of Qingdao Port and the results show that the proposed method significantly outperforms ANN,SARIMA,and PPR models.