Molecular structure and granule morphology of native and heat‐moisture‐treated pinhão starch

Pinhão seed is an unconventional source of starch and the pines grow up in native forests of southern Latin America. In this study, pinhão starch was adjusted at 15, 20 and 25% moisture content and heated to 100, 110 and 120 °C for 1 h. A decrease in λ max (starch/iodine complex) was observed as a result of increase in temperature and moisture content of HMT. The ratio of crystalline to amorphous phase in pinhão starch was determined via Fourier transform infra red by taking 1045/1022 band ratio. A decrease in crystallinity occurred as a result of HMT. Polarised light microscopy indicated a loss of birefringence of starch granules under 120 °C at 25% moisture content. Granule size distribution was further confirmed via scanning electron microscopy which showed the HMT effects. These results increased the understanding on molecular and structural properties of HMT pinhão starch and broadened its food and nonfood industrial applications.     

基于粒子群优化和支持向量机的花粉浓度预测模型

为了提高花粉浓度预报的准确率，解决现有花粉浓度预报准确率不高的问题，提出了一种基于粒子群优化（PSO）算法和支持向量机（SVM）的花粉浓度预报模型。首先，综合考虑气温、气温日较差、相对湿度、降水量、风力、日照时数等多种气象要素，选择与花粉浓度相关性较强的气象要素构成特征向量；其次，利用特征向量与花粉浓度数据建立SVM预测模型，并使用PSO算法找出最优参数；然后利用最优参数优化花粉浓度预测模型；最后，使用优化后的模型对花粉未来24 h浓度进行预测，并与未优化的SVM、多元线性回归法（MLR）、反向神经网络（BPNN）作对比。此外使用优化后的模型对某市南郊观象台和密云两个站点进行逐日花粉浓度预测。实验结果表明，相比其他预报方法，所提方法能有效提高花粉浓度未来24 h预测精度，并具有较高的泛化能力。     

Backtesting portfolio value-at-risk with estimated portfolio weights

This article theoretically and empirically analyzes backtesting portfolio value-at-risk (VaR) with estimation risk in an intrinsically multi-variate framework. It particularly takes into account the estimation of portfolio weights in forecasting portfolio VaR and its impact on backtesting. It shows that the estimation risk from estimating portfolio weights and that from estimating the multi-variate dynamic model make the existing methods in a univariate framework inapplicable. It proposes a general theory to quantify estimation risk applicable to the present problem and suggests practitioners a simple but effective way to implement valid inference to overcome the effect of estimation risk in backtesting portfolio VaR. In particular, we apply our theory to the efficient mean-variance-skewness portfolio for a multi-variate generalized autoregressive conditional heteroscedasticity model with multi-variate general hyperbolic distributed innovations. Some Monte Carlo simulations and an empirical application demonstrate the merits of our method.     

灰色预测模型在油气操作成本预测中的应用

油气操作成本是油气田生产消耗的主要项目，为了有效地控制油气操作成本，必须制定准确的油气操作成本计划。而油气操作成本在我国是最近几年才提出来的，数据项比较少，给油气操作成本预测带来一定的难度。为此，文章根据灰色预测的基本原理，采用灰色系统理论进行油气操作成本预测，就可以弥补对预测所需的数据少，而且也无须剔除不可比因素，只要所建模型能满足精度要求，预测结果就可以信赖。     

油气操作成本预测方法研究

油气操作成本在油气生产中占有较大的比重，油气操作成本的高低直接影响油田开发的经济效益。为了有效地控制油田油气操作成本，根据影响油气操作的因素，将油气操作成本按其影响因素进行分类，对基本运行费和油气处理费采用回归预测的方法，通过对相关数据的收集，建立对应的数学模型进行预测，对其他各项操作成本，采用单位费用和计划工作量进行预测，最后进行汇总，得到油气操作成本，其预测结果可作为油气操作成本计划制订的依据。该方法简单、操作性强，预测效果较好，在油田可以推广使用。     

服装湿冷机理分析

本文在明确冷暖感、湿冷感、接触湿冷感等概念的基础上,分析了在冬季着装状态下,人体热量、水汽 散失的途径和人体产生冷感的原因。     

重复压裂气井产能模拟研究

由于重复压裂气井原有裂缝的失效程度难以评价。导致重复压裂气井的产能预测常常有很大的误差。为此，根据重复压裂气井的压前产量和舍水率，拟合了原有裂缝的有效率，在考虑新裂缝和原有裂缝共同作用的情况下，建立了气、水两相平面二维的裂缝-油藏数学模型，通过对模型的数值求解，对重复压裂气井进行了产能评价。研究表明，在考虑新、老裂缝共同作用下的产能评价方法，能更为准确地预测重复压裂后的生产动态情况，对压裂时机的确定、压后经济效益的预测都具有重要的指导意义。     

Potential of in-field and low temperature drying for reducing chlorophyll contents in canola (Brassica napus L)

The presence of green seeds in canola arises primarily from the common practice of swathing the crop prematurely in order to hasten the harvesting process and reduce the shattering losses. The purpose of this study was to determine the effects of plant maturity, swathing and duration of swathing on moisture and chlorophyll contents of canola seeds (Brassica napus L cv Westar), and to determine the effect of canola conditioning with air at 25·C and 90% RH on chlorophyll content. A standing crop of canola with 50% to 10% (w/w) seed moisture content was sampled at regular intervals in two consecutive harvest years (1989 and 1990). Canola was also swathed at three different stages of maturity, and seeds were checked for chlorophyll at 2-3 day intervals and compared with chlorophyll contents of seed from standing crop. Samples were conditioned in a thin layer with air at 25·C and 90% RH for 24 h, and chlorophyll was determined before and after conditioning. The chlorophyll of seeds decreased exponentially with a decrease in moisture content. Conditioning canola seeds decreased chlorophyll content by an average of 16% (SD = ± 12%).     

我国“十五“电力供需预测分析

分析“十五”期间我国电力需求预测和电力预测中的不确定因素,提出建议采取的措施。     

Modeling and assimilation of root zone soil moisture using remote sensing observations in Walnut Gulch Watershed during SMEX04

Soil moisture status in the root zone is an important component of the water cycle at all spatial scales (e.g., point, field, catchment, watershed, and region). In this study, the spatio-temporal evolution of root zone soil moisture of the Walnut Gulch Experimental Watershed (WGEW) in Arizona was investigated during the Soil Moisture Experiment 2004 (SMEX04). Root zone soil moisture was estimated via assimilation of aircraft-based remotely sensed surface soil moisture into a distributed Soil-Water-Atmosphere-Plant (SWAP) model. An ensemble square root filter (EnSRF) based on a Kalman filtering scheme was used for assimilating the aircraft-based soil moisture observations at a spatial resolution of 800 m × 800 m. The SWAP model inputs were derived from the SSURGO soil database, LAI (Leaf Area Index) data from SMEX04 database, and data from meteorological stations/rain gauges at the WGEW. Model predictions are presented in terms of temporal evolution of soil moisture probability density function at various depths across the WGEW. The assimilation of the remotely sensed surface soil moisture observations had limited influence on the profile soil moisture. More specifically, root zone soil moisture depended mostly on the soil type. Modeled soil moisture profile estimates were compared to field measurements made periodically during the experiment at the ground based soil moisture stations in the watershed. Comparisons showed that the ground-based soil moisture observations at various depths were within ± 1 standard deviation of the modeled profile soil moisture. Density plots of root zone soil moisture at various depths in the WGEW exhibited multi-modal variations due to the uneven distribution of precipitation and the heterogeneity of soil types and soil layers across the watershed.