3-氨基-1-（4-氯苯基）-1氢-苯并[f]色烯-2-碳酸乙酯的合成和晶体结构研究

以氰乙酸乙酯、2-萘酚和对氯苯甲醛为反应原料,得到了3-氨基-1-（4-氯苯基）-1氢-苯并[f]色烯-2-碳酸乙酯,通过X-射线单晶衍射对其结构进行表征。结果表明：晶体属于三斜晶体,空间群为P-1。晶胞参数为：Z=2,a=9.2916（7）A°,b=9.4505（8）A°,c=10.9761（7）A°;α=95.077（2）°,β=98.200（2）°,γ=102.892（2）°,V=922.65（12）A°3;R1=0.0466,wR2=0.1326。     

"Quicker and sicker" under Medicare's prospective payment system for hospitals: new evidence on an old issue from a national longitudinal survey

Medicare's prospective payment system for hospitals (PPS), introduced in the USA in 1983, replaced cost reimbursement with a system of fixed rates which created incentives for hospitals to control costs. Previous studies found that elderly patients were discharged from hospital "quicker and sicker" under PPS and concluded that families were coping at home. We analyse a national longitudinal survey, the first National Health and Nutrition Examination Survey and its Epidemiologic Followup Study, which includes data on more outcomes over a longer period than earlier studies. We find that the rate of admission to nursing homes from the community in the first weeks after a hospital discharge more than tripled under PPS, suggesting that families were not always able to cope. As another response to sicker patients, discharges directly to nursing homes from hospitals, which jumped initially under PPS, may have risen further when payment rates were tightened in the early 1990s. Hospital readmissions fell after the first few years. Our findings are strengthened by the fact that we control for patients' health using health information collected independently of hospital admission.     

基于深度学习模型的种植结构复杂区农作物精细分类研究

目的 卫星遥感技术具有覆盖范围广、探测周期短、调查成本低等优势而广泛应用于大区域农作物分类。然而在种植结构复杂区（如城乡结合部）,因其地块破碎、同期生长的作物种类多且分布分散,利用传统的统计分类或机器学习方法进行农作物分类时仍存在精度不高的问题。为提高种植结构复杂区农作物分类精度。方法 文章选取河北省廊坊市广阳区为研究区,以GF-1 PMS全色多光谱融合影像为数据源,采用U-Net、PSPNet及DeepLabv3+,3种深度学习模型进行农作物分类研究。分析模型参数对农作物分类精度的影响,评价3种深度学习模型的农作物分类精度,优选农作物精细分类方法。结果 （1）学习率与3种深度学习模型的分类精度呈正相关关系,较大的学习率（0.01,0.001）下,3种模型收敛速度快,分类精度高。批样本量与模型分类稳定性相关,批样本量设为100时,3种模型的分类稳定性最好。（2）相比PSPNet、DeepLabv3+模型,U-Net模型分类效果最好,总体分类精度为89.32%。（3）GF-1 PMS影像结合U-Net模型可有效提升种植结构复杂区农作物分类精度,大宗作物春玉米、夏玉米的分类精度在80%以上,花生、红薯、蔬菜小宗作物分类精度在60%以上。结论 该研究可为准确获取种植结构复杂区的农作物类型、面积及空间分布信息提供参考依据。     

Investigating regional house price convergence in the United States: Evidence from a pair-wise approach

In this paper we examine long-run house price convergence across US states using a novel econometric approach advocated by Pesaran (2007) and Pesaran et al. (2009). Our empirical modelling strategy employs a probabilistic test statistic for convergence based on the percentage of unit root rejections among all state house price differentials. Using a sieve bootstrap procedure, we construct confidence intervals and find evidence in favour of convergence. We also conclude that speed of adjustment towards long-run equilibrium is inversely related to distance.     

RECURRENT BUBBLES*

We study rational bubbles in a standard linear asset price model. We first consider a class of bubble processes driven by multiplicative i.i.d. shocks. We show that a bubble process in this class either diverges to infinity with probability one, converges to zero with probability one, or keeps fluctuating forever with probability one, depending on investors' “confidence” in expected bubble growth. We call a bubble process having the last property “recurrent.” We develop sufficient conditions for a bubble process to be recurrent when it is driven by non‐i.i.d. shocks, when the risk‐free interest rate is not constant, and when the process is driven by non‐i.i.d. shocks and the risk‐free interest rate is not constant. In the last case we demonstrate via simulation that there can be a prolonged period in which both the bubble and the interest rate stay close to zero.     

On some criteria for the formulation and testing of economic growth models

This paper presents a methodology for the formulation and testing of economic growth models. The model selected includes two production sectors with physical and human capital accumulation. These capital stocks are associated with spillover effects in the production of the physical good and in the accumulation of both factors.     

Gender,productive ability and the perceived returns to education: Evidence from rural India

Recent research has established the importance of perceived (as opposed to actual) returns as a determinant of educational investments. We analyze data from India to highlight gender disparities in the perceived returns to education and the salience of productive characteristics.