Prediction in the one-way error component model with serial correlation

This paper derives the best linear unbiased predictor for a one-way error component model with serial correlation. A transformation derived by Baltagi and Li (1991) is used to show how the forecast can be easily computed from the GLS estimates and residuals. This result is useful for panel data applications which utilize the error component specification and exhibit serial correlation in the remainder disturbance term. Analytical expressions for this predictor are given when the remainder disturbances follow (1) an AR(1) process, (2) an AR(2) process, (3) a special AR(4) process for quarterly data, and (4) an MA(1) process.     

The role of kinesin, dynein and microtubules in pancreatic secretion

The regulated secretion of pancreatic zymogens depends on a functional cytoskeleton and intracellular vesicle transport. To study the dynamics of tubulin and its motor proteins dynein and kinesin during secretion in pancreatic acinar cells, we infused rats with 0.1 μg/kg/h caerulein. Electron and fluorescence microscopy detected neither dynein nor kinesin at the apical secretory pole, nor on the surface of mature zymogen granules. After 30 min of secretagogue stimulation, kinesin and the Golgi marker protein 58 K were reallocated towards the apical plasma membrane and association of kinesin with tubulin was enhanced. Disruption of acinar cell microtubules had no effect on initial caerulein-induced amylase release but completely blocked secretion during a second stimulus. Our results suggest that mature zymogen granule exocytosis is independent of intact microtubules, kinesin and dynein. However, microtubule-dependent mechanisms seem to be important for the replenishment of secretory vesicles by redistribution of Golgi elements towards the apical cell pole. J. Schnekenburger and I.-A. Weber have contributed equally to this work.     

The impact of parameter uncertainty in insurance pricing and reserve with the temperature‐related mortality model

Changes in mortality rates have an impact on the life insurance industry, the financial sector (as a significant proportion of the financial markets is driven by pension funds), governmental agencies, and decision makers and policymakers. Thus the pricing of financial, pension and insurance products that are contingent upon survival or death and which is related to the accuracy of central mortality rates is of key importance. Recently, a temperature‐related mortality (TRM) model was proposed by Seklecka et al. (Journal of Forecasting, 2017, 36(7), 824–841), and it has shown evidence of outperformance compared with the Lee and Carter (Journal of the American Statistical Association, 1992, 87, 659–671) model and several others of its extensions, when mortality‐experience data from the UK are used. There is a need for awareness, when fitting the TRM model, of model risk when assessing longevity‐related liabilities, especially when pricing long‐term annuities and pensions. In this paper, the impact of uncertainty on the various parameters involved in the model is examined. We demonstrate a number of ways to quantify model risk in the estimation of the temperature‐related parameters, the choice of the forecasting methodology, the structures of actuarial products chosen (e.g., annuity, endowment and life insurance), and the actuarial reserve. Finally, several tables and figures illustrate the main findings of this paper.     

Method and situational factors in sales forecast accuracy

In this study the interaction of forecasting method (econometric versus exponential smoothing) and two situational factors are evaluated for their effects upon accuracy. Data from two independent sets of ex ante quarterly forecasts for 19 classes of mail were used to test hypotheses. Counter to expectations, the findings revealed that forecasting method did not interact with the forecast time horizon (short versus long term). However, as hypothesized, forecasting method interacted significantly with product/market definition (First Class versus other mail), an indicator of buyer sensitivity to marketing/environmental changes. Results are discussed in the context of future research on forecast accuracy.     

超临界流体技术制备纳米材料进展

目前,已经有多种与超临界流体有关的技术用于纳米材料的制备。在这些技术方法中,超临界流体可以作为介质,也可以直接作为反应物来参与制备过程。超临界流体技术广泛应用于制备无机材料、有机材料、高分子聚合物、医药、电子等方面纳米级材料。本文概述了超临界流体制备纳米材料的研究和应用情况。     

湿地甲烷排放研究进展

甲烷是一种仅次于二氧化碳的重要温室气体,对全球变暖的贡献率为25%。近年来大气中甲烷浓度显著增加,湿地甲烷释放量约占全球甲烷通量的20%,是大气甲烷的主要自然来源之一。甲烷主要通过产甲烷菌在厌氧条件下产生,在氧化条件下,甲烷通过土壤中的甲烷氧化菌氧化,并通过气泡、扩散和植物传输三种途径释放到大气。湿地甲烷通量在时间和空间两个方面有较大的变化,这与甲烷产生、氧化和传输过程有关,同时受到不同环境因素的影响,如:土壤质地、氧化还原电位、有机物、土壤酸碱度、植被条件、气候因素、农业管理措施等。文章还对湿地甲烷排放的观测方法和排放模型进行了简单介绍,并对今后的研究提出了几点建议。     

BP神经网络样本数据预处理应用研究

提出一种新的线性预处理输入数据的方法,即通过线性运算将样本数据的各个字段值统一到同一个数量级,然后结合数值归一化的方法将数据运用到神经网络。在基于信令的漫游用户实时信用度测评及欠费风险超前控制系统中,使用统一字段值的数量级的方法预处理样本数据取得了很好的预测效果。由此,在模式识别和预测领域,统一样本数据的各个字段值的数量级后再进行网络训练可以取得更好的训练效果。     

Back propagation in time-series forecasting

One of the major constraints on the use of back propagation neural networks as a practical forecasting tool is the number of training patterns needed. We propose a methodology that reduces the data requirements. The general idea is to use the Box-Jenkins model in an exploratory phase to identify the 'lag components' of the series, to determine a compact network structure with one input unit for each lag, and then apply the validation procedure. This process minimizes the size of the network and consequently the data required to train the network. The results obtained in eight studies show the potential of the new methodology as an alternative to the traditional time-series models.     

土壤抗冲性及其影响因素研究进展

通过回顾土壤抗冲性研究历程,归纳了不同的土壤抗冲性表征方式,总结了土壤抗冲性不同测定方法的优缺点,综合探讨了土地利用类型、植被作用和地形坡度等外在影响因素,以及通过不同程度影响或改变土壤的理化性质导致其抗冲性差异的情况,认为土壤抗冲性表征方式和实验方法需规范统一,研究机理和研究尺度有待深入扩展,使得研究成果更好地服务于水土保持实践。     

植物修复重金属与多环芳烃污染土壤强化措施研究进展

重金属和多环芳烃是土壤环境中的重要污染物,其复合污染土壤的修复已成为环境科学研究的热点问题。植物修复技术是目前修复土壤复合污染重要方法之一,但植物本身修复能力有限,需借助化学、微生物、基因工程等手段对其修复效果进行强化。本文对国内外近几年来植物修复重金属-多环芳烃复合污染强化措施研究成果进行综述,并重点讨论了植物根际生长促进菌及菌根在强化修复中的应用,在此基础上对未来该领域需要深入研究的科学问题进行了阐述。     

Beating the random walk in Central and Eastern Europe

We compare the accuracy of vector autoregressive (VAR), restricted vector autoregressive (RVAR), Bayesian vector autoregressive (BVAR), vector error correction (VEC) and Bayesian error correction (BVEC) models in forecasting the exchange rates of five Central and Eastern European currencies (Czech Koruna, Hungarian Forint, Slovak Koruna, Slovenian Tolar and Polish Zloty) against the US Dollar and the Euro. Although these models tend to outperform the random walk model for long‐term predictions (6 months ahead and beyond), even the best models in terms of average prediction error fail to reject the test of equality of forecasting accuracy against the random walk model in short‐term predictions. Copyright © 2005 John Wiley & Sons, Ltd.     

蛋白质组学在药物及疾病标志物研究中的应用进展

蛋白质组学提供了整体水平研究蛋白质的表达、翻译后修饰,以及蛋白质的功能的思路,由此获得蛋白质水平上的关于疾病发生、细胞代谢等过程的全面认识,逐渐被广泛应用于药物及生物标志物研究中.本文介绍了蛋白质组学的经典技术路线和新策略,并综述了其在药物及疾病标志物研究中应用进展.     

Forecasting the Italian industrial production index in real time

Daily electricity consumption data, available almost in real time, can be used in Italy to estimate the level of industrial production in any given month before the month is over. We present a number of procedures that do this using electricity consumption in the first 14 days of the month. (This is an extension of a previous model that used monthly electricity data.) We show that, with a number of adjustments, a model using half-monthly electricity data generates acceptable estimates of the monthly production index. More precisely, these estimates are more accurate than univariate forecasts but less accurate than estimates based on monthly electricity data. A further improvement can be obtained by combining ‘half-monthly’ electricity-based estimates with univariate forecasts. We also present quarterly estimates and discuss confidence intervals for various types of forecasts.     

One century of diagnostic imaging in medicine

The historical outline shows the development of radiologic diagnostics from the early Roentgen days up to this centenary. The roots of radiologic diagnostics go back to the European Renaissance. It is a history of medical pattern recognition and functional analysis by several methods including X-rays, ultrasound waves or strong magnetic fields. The difference between conventional radiographs and a picture reconstructed after digitalization, with several possibilities of postprocessing, is explained. Research and further technical revolutions, like the development of semiconductor elements and computers or tailored contrast media, sophisticated pictorial representations and perceptions, are among the cornerstones of imaging diagnostics. During this century many diseases have changed their manifestation and spread. This is illustrated by tuberculosis and cancer and highlights the growing importance of imaging diagnostics and interventional radiology. The thorny path to independence of radiology is also a history of the medical establishment's resistance.     

Differential removal of insulin-like growth factor binding proteins in rat serum by solvent extraction procedures

Solvent extraction of serum and other biological fluids at an acidic pH is a convenient method to remove the insulin-like growth factor binding proteins (IGFBPs); however, an incomplete removal of IGFBPs can occur and this can potentially interfere with the radioimmunoassay of insulin-like growth factors (IGFs). This study compared the removal of IGFBPs from normal adult rat serum and 5-day old neonatal rat serum by acid-gel filtration, and three solvent extraction methods, i.e., acid-ethanol (AE), acid-cryo-ethanol (ACE) and formic acid-acetone (FAA) treatments by western ligand blotting and slot-blotting analysis. In adult rat serum all three extraction methods removed nearly 75% of total IGFBPs present. For the neonatal serum, AE and FAA were very inefficient in eliminating the IGFBPs, while ACE was somewhat better, as it removed nearly 30% of IGFBPs. Ligand blots of extracted samples showed that IGFBPs of lower size range, 24 to 32 kDa (IGFBP-4, IGFBPs-1 and-2), were resistant to solvent extraction. Acid-gel filtration, in contrast, eliminated >95% of IGF-binding components in both sera. Determination of IGF-I concentrations in samples after gel filtration and extraction methods revealed lower IGF-I values in neonatal serum in acid extracted samples. These data caution against using solvent extractions for IGFBP removal in fetal/neonatal serum.     

Retrospective Testing of Mortality Forecasting Methods for the Projection of Very Elderly Populations in Australia

The purpose of this paper is to present the results of retrospective tests of various extrapolative methods to forecast adult mortality and very elderly populations for Australia. Direct extrapolation methods tested include the Geometric method, Ediev variant, Lee‐Carter method, BMS variant and a relational model. Indirect methods include the extrapolation of parameters of models fitted to the age profile of death rates and a new method involving the extrapolation of features of death frequency distributions namely the modal age and concentration. The geometric, Ediev and Lee‐ Carter BMS methods were very successful in projecting death rates and very elderly populations. Differences between these methods were small. The extrapolation of parametric functions proved successful for males but less so for females. Very elderly populations can be viably projected by directly extrapolating death rates by age when rates of decline in death rates show consistent relationships between ages and are stable over time. Copyright © 2016 John Wiley & Sons, Ltd.     

Grape vine physiology: the contribution of culture in vitro

Conclusion In the area of cell and tissue physiology, the grape vine has been a major reference material. As with all woody perennials, in vitro technologies are relatively delicate. Nevertheless, remarkable progress has produced a situation where, during the past ten years, practical application of results from in vitro work has been envisaged. Reciprocal understanding has yet to be established between scientists developing micropropagation (multiplication with conformity to type) and those using in vitro methods for variety improvement (multiplication for novelty of type). I am convinced that the future should not see one of these objectives dominating the other. On the contrary, certain technologies should be developed to ensure a framework for conformity of propagation and others to obtain greater variability with the goal of plant improvement. This will render effective the two applications considered.     

The role of time series analysis in the evaluation of econometric models

This paper compares the properties of a structural model—the London Business School model of the U.K. economy—with a time series model. Information provided by this type of comparison is a useful diagnostic tool for detecting types of model misspecification. This is a more meaningful way of proceeding rather than attempting to establish the superiority of one type of model over another. In lieu of a better structural model, the effects of inappropriate dynamic specification can be reduced by combining the forecasts of both the structural and time series models. For many variables considered here these provide more accurate forecasts than each of the model types alone.