岷江上游花椒地/林地边界土壤水分分布及影响域

在岷江上游干旱河谷区选取典型的花椒地,林地边界,利用TDR仪测定干旱条件下和雨后0-15cm表土层水分体积分数,刻画沿样带梯度土壤水分分布以及不同时段土壤水分变化,同时用移动窗口法判定土壤水分的边界影响域。结果表明,在干旱河谷区土壤水分体积分数较低并沿样带存在明显的变化,从林地到边界到花椒地土壤水分体积分数基本呈“V”字型变化;而在林地和花椒地内部,水分体积分数呈“W”型波动。干旱时土壤水分体积分数日间变化不大,而雨后水分体积分数逐日递减。土壤水分的影响域在雨后可达14m,干旱时为8m。     

Membrane protein sequestering by ionic protein-lipid interactions

Neuronal exocytosis is catalysed by the SNAP receptor protein syntaxin-1A, which is clustered in the plasma membrane at sites where synaptic vesicles undergo exocytosis. However, how syntaxin-1A is sequestered is unknown. Here we show that syntaxin clustering is mediated by electrostatic interactions with the strongly anionic lipid phosphatidylinositol-4,5-bisphosphate (PIP2). Using super-resolution stimulated-emission depletion microscopy on the plasma membranes of PC12 cells, we found that PIP2 is the dominant inner-leaflet lipid in microdomains about 73 nanometres in size. This high accumulation of PIP2 was required for syntaxin-1A sequestering, as destruction of PIP2 by the phosphatase synaptojanin-1 reduced syntaxin-1A clustering. Furthermore, co-reconstitution of PIP2 and the carboxy-terminal part of syntaxin-1A in artificial giant unilamellar vesicles resulted in segregation of PIP2 and syntaxin-1A into distinct domains even when cholesterol was absent. Our results demonstrate that electrostatic protein-lipid interactions can result in the formation of microdomains independently of cholesterol or lipid phases.     

Forecast Combination for Euro Area Inflation: A Cure in Times of Crisis?

The period of extraordinary volatility in euro area headline inflation starting in 2007 raised the question whether forecast combination methods can be used to hedge against bad forecast performance of single models during such periods and provide more robust forecasts. We investigate this issue for forecasts from a range of short‐term forecasting models. Our analysis shows that there is considerable variation of the relative performance of the different models over time. To take that into account we suggest employing performance‐based forecast combination methods—in particular, one with more weight on the recent forecast performance. We compare such an approach with equal forecast combination that has been found to outperform more sophisticated forecast combination methods in the past, and investigate whether it can improve forecast accuracy over the single best model. The time‐varying weights assign weights to the economic interpretations of the forecast stemming from different models. We also include a number of benchmark models in our analysis. The combination methods are evaluated for HICP headline inflation and HICP excluding food and energy. We investigate how forecast accuracy of the combination methods differs between pre‐crisis times, the period after the global financial crisis and the full evaluation period, including the global financial crisis with its extraordinary volatility in inflation. Overall, we find that forecast combination helps hedge against bad forecast performance and that performance‐based weighting outperforms simple averaging. Copyright © 2017 John Wiley & Sons, Ltd.     

基于3D-CDF(2,2)和3D SPIHT的序列图像压缩编码研究

研究了3D DWT和3D SPIHT算法,用CDF（2,2）双正交小波为帧内小波变换的小波基,考虑到边界延拓效应,时间维小波变换也选用CDF（2,2）双正交小波为时间维小波变换的小波基,实验结果表明算法对于视频序列图像压缩是非常有效的,其压缩效果明显优于基于3D-DCT的压缩编码算法.