在荧光漂白恢复测量中荧光恢复起始时间的研究

在荧光漂白恢复测量中,漂白过程结束的准确时间相对于漂白控制信号后沿会有一定的延迟时间,不易确定.光电倍增管快门开启又要推迟一段时间.因此,荧光恢复起始时间,即漂白结束的瞬间不能准确给出,开始阶段数据收集不全.本文分析了荧光恢复起始时间不准确所造成的误差,测量了起始时间.并尽量减少此误差,使恢复初期收集到的数据更完全,荧光恢复过程的时间座标更准确.     

Detection of chaos: New approach to atmospheric pollen time-series analysis

Pollen and spores are biological particles that are ubiquitous to the atmosphere and are pathologically significant, causing plant diseases and inhalant allergies. One of the main objectives of aerobiological surveys is forecasting. Prediction models are required in order to apply aerobiological knowledge to medical or agricultural practice; a necessary condition of these models is not to be chaotic. The existence of chaos is detected through the analysis of a time series. The time series comprises hourly counts of atmospheric pollen grains obtained using a Burkard spore trap from 1987 to 1989 at Mar del Plata. Abraham's method to obtain the correlation dimension was applied. A low and fractal dimension shows chaotic dynamics. The predictability of models for atomspheric pollen forecasting is discussed.     

一类灰色项时间序列模型及其应用

利用灰色系统理论与时间序列分析,提出了带灰色项的时间序列模型,对这类模型进行了分析,给出了建模与预报方法,并将其应用于我国农业产值问题的预报与研究之中,模型的正确性得到了检验．     

A complementary note on the supercritical birth,death and catastrophe process

A central limit theorem for the population size of the super-critical linear birth and death process with a linear catastrophe component has previously been obtained under a fourth order moment condition on the increment distribution. In this note we show that this result is valid under a second order moment condition, and that no lesser condition will suffice. This is accomplished by giving a new, self-contained and simple proof of the asymptotic normality of a certain tail sum of independent variates.     

Semiparametric models and inference for biomedical time series with extra-variation

Biomedical trials often give rise to data having the form of time series of a common process on separate individuals. One model which has been proposed to explain variations in such series across individuals is a random effects model based on sample periodograms. The use of spectral coefficients enables models for individual series to be constructed on the basis of standard asymptotic theory, whilst variations between individuals are handled by permitting a random effect perturbation of model coefficients. This paper extends such methodology in two ways: first, by enabling a nonparametric specification of underlying spectral behaviour; second, by addressing some of the tricky computational issues which are encountered when working with this class of random effect models. This leads to a model in which a population spectrum is specified nonparametrically through a dynamic system, and the processes measured on individuals within the population are assumed to have a spectrum which has a random effect perturbation from the population norm. Simulation studies show that standard MCMC algorithms give effective inferences for this model, and applications to biomedical data suggest that the model itself is capable of revealing scientifically important structure in temporal characteristics both within and between individual processes.     

Does the level of infant mortality affect the rate of decline?: Time series data from 21 countries

Some scholars have suggested that an inverse care law holds for infant mortality--that infant mortality reductions are more rapid in regions with lower infant mortality. This theory has not been subjected to proper quantitative analysis. This paper examines time series data on infant mortality from 21 countries to test whether percentage reductions in infant mortality are larger when infant mortality is lower. We apply the Dickey-Fuller generalized least squares (DFGLS) unit root test to infant mortality rate (IMR) time series data from 21 mostly European nations for 1870-1988 to test the statistical significance of beta in a regression analysis of Deltaln IMR(t)=alpha+beta ln IMR(t-1)+epsilon(t). Evidence that beta is significant and negative would support the claim that infant mortality declines more rapidly when substantial mortality reductions have already been achieved. With the preferred specification, the DFGLS unit root test rejected the inverse benefit hypothesis in all countries except the Netherlands at the 5% and 10% cutoffs and Australia at the 10% cutoff. The rejection of the inverse benefit hypothesis was robust to alternative specifications of the lag structure of IMR and to transformations of IMR other than logarithmic. Based on late 19th and 20th century data from countries in Europe and Latin America, there is scarce evidence that percentage reductions in infant mortality are generally smaller in higher mortality countries. These findings suggest that large percentage reductions in infant mortality are possible for countries at any stage in economic development and are reflective of durable advances in human knowledge, social institutions and physical capital.     

稻纵卷叶螟迁入数量时间序列的混沌诊断

稻纵卷叶螟是一种重要的迁飞性水稻害虫,为更好地进行预测控制,研究清楚其迁入行为的动力学结构则对预报建模意义重大,本文利用从时间序列提取吸引关联维来确定系统性质的方法,对全国十个测报站的稻纵卷叶螟迁入数量的时间序列进行了关联维的计算,结果表明,这一迁飞行为是随机的。     

武汉东湖鱼产量时间序列模型及回归分析

随着城市人口的增长和经济的快速发展,武汉东湖的水体富营养化日益严重。80年代以来,东湖通过实施滤食性鱼类治理水华取得了一定成效。利用统计学软件SPSS,应用时间序列模型和回归分析对东湖44年鱼产量数据进行运算,对东湖鱼产量变化进行了分析和预测:东湖最高鱼产量在1700～1850t之间,比较合理的鱼产量应维持在1150t左右。     

Establishing the stochastic nature of intracellular calcium oscillations from experimental data

Calcium has been established as a key messenger in both intra- and intercellular signaling. Experimentally observed intracellular calcium responses to different agonists show a variety of behaviors from simple spiking to complex oscillatory regimes. Here we study typical experimental traces of calcium oscillations in hepatocytes obtained in response to phenylephrine and ATP. The traces were analyzed with methods of nonlinear time series analysis in order to determine the stochastic/deterministic nature of the intracellular calcium oscillations. Despite the fact that the oscillations appear, visually, to be deterministic yet perturbed by noise, our analyses provide strong evidence that the measured calcium traces in hepatocytes are prevalently of stochastic nature. In particular, bursting calcium oscillations are temporally correlated Gaussian series distorted by a monotonic, instantaneous, time-independent function, whilst the spiking behavior appears to have a dynamical nonlinear component whereby the overall determinism level is still low. The biological importance of this finding is discussed in relation to the mechanisms incorporated in mathematical models as well as the role of stochasticity and determinism at cellular and tissue levels which resemble typical statistical and thermodynamic effects in physics.     

林分生长量估测模型的研究

本文用ARIMA（2,2,0）序列模拟了林分的平均生长过程,给出了落叶松（LarixolgensisHenry）人工林林分在树高、胸径、材积三个指标上平均总生长量的2阶求和自回归滑动平均模型,经模型残量的自相关检验及预测效果检验,估测效果良好．     

DNA序列的多重分形Hurst分析

为了深入研究基因组序列的多重分形性质,首先选取12条较长的DNA序列,并根据此12条DNA序列的编码／非编码片段将DNA序列转换成相应的12条时间序列,其次对这12个时间序列进行多重分形Hurst分析,计算它们的Hurst指数,并且利用Hurst指数分析序列的自相似性,进一步将得到的Hurst指数与DNA一维游走模型相比较,发现12条序列均具有长程相关性,这说明DNA序列中确实存在着长程相关现象。     

Analysis of bioclimatic time series and their neural network-based classification to characterise drought risk patterns in South Italy

A new approach to characterise geographical areas with a drought risk index (DRI) is suggested, by applying an artificial neural network (ANN) classifier to bioclimatic time series for which operational temporal units (OtUs) are defined. A climatic database, corresponding to a grid of 8 km x 8 km cells covering the Italian peninsula, was considered. Each cell is described by the time series of seven variables recorded from 1989 to 2000. Sixteen cells were selected according to land cover homogeneity and completeness of the time series data. The periodic components of the time series were calculated by means of the fast Fourier transform (FFT) method. Temporal units corresponding to the period of the sinusoidal functions most related to the data were used as OtUs. The ANN for each OtU calculates a DRI value ranging between -1 and 1. The value is interpretable as the proximity of the OtUs to one of two situations corresponding to minimum and maximum drought risk, respectively. The former set (DRI = -1) is represented by an ideal OtU with minimum values of temperatures and evapo-transpiration, and maximum values of rainfall, normalised difference vegetation index (NDVI) and soil water content. The second set (DRI = 1) is represented by the reciprocal OtU to the former one. The classification of the cells based on DRI time profiles showed that, at the scale used in this work, DRI has no dependence on land cover class, but is related to the location of the cells. The methodology was integrated with GIS (geographic information system) software, and used to show the geographic pattern of DRI in a given area at different periods.     

Influence of land-use types and climatic variables on seasonal patterns of NDVI in Mediterranean Iberian ecosystems

Question: What is the influence of management on the functioning of vegetation over time in Mediterranean ecosystems under different climate conditions? Location: Mediterranean shrublands and forests in SE Iberia (Andalusia). Methods: We evaluated the Normalized Difference Vegetation Index (NDVI) for the 1997-2002 time series to determine phenological vegetation patterns under different historical management regimes. Three altitudinal ranges were considered within each area to explore climate × management interactions. Each phenological pattern was analysed using time series statistics, together with precipitation (monthly and cumulative) and temperature. Results: NDVI time series were significantly different under different management regimes, particularly in highly transformed areas, which showed the lowest NDVI, weakest annual seasonality and a more immediate phenological response to precipitation. The NDVI relationship with precipitation was strongest in the summer-autumn period, when precipitation is the main plant growth-limiting factor. Conclusions: NDVI time series analyses elucidated complex influences of land use and climate on ecosystem functioning in these Mediterranean ecosystems. We demonstrated that NDVI time series analyses are a useful tool for monitoring programmes because of their sensitivity to changes, ease of use and applicability to large-scale studies.     

不同生理状态时脑电时间序列的三神复杂度计算比较

为了研究不同生理状态下的脑电复杂度变化特点,本文依照１９９４年徐京等人应用的算法,对４种状态（安静睁眼,清醒闭目,浅度睡眠,深度睡眠）下的三种脑电复杂度（Ｋｃ,Ｃ１,Ｃ２）的变化规律进行了比较分析,Ｋｃ与Ｃ１的变化相一致,从安静睁眼剂的清醒闭目到浅睡到深度睡眠,Ｋｃ与Ｃ１值均依次下降,Ｃ２值的变化则与它们相反,尤其在深睡期显著升高,实验结果提示,复杂度可做为脑电时间序列的研究指标。     

不同生理状态时脑电时间序列的三神复杂度计算比较

为了研究不同生理状态下的脑电复杂度变化特点,本文依照１９９４年徐京华等人应用的算法,对４种状态（安静睁眼、清醒闭目、浅度睡眠、深度睡眠）下的三种脑电复杂度（ＫＣ、Ｃ１、２）的变化规律进行了比较分析,ＫＣ与Ｃ１的变化相一致。从安静睁眼到清醒闭目到浅睡到深度睡眠,ＫＣ与Ｃ１值均依次下降。Ｃ２值的变化则与它们相反,尤其在深睡期显著升高。实验结果提示,复杂度可做为脑电时间序列的研究指标。     

On the Dependence of the Quadratic Risk of the Classical Predictor and the Prediction-Horizon

When constructing predictors on the basis of the linear model of time series of various indicators often the question arises on the dependence of forecasting accuracy and the changing prediction horizon. The dependency of the quadratic risk of the classical predictor and the time horizon is considered.     

Circadian breast skin temperature rhythms: overt and occult benign and occult primary malignant breast disease

Circadian variations of breast surface temperature have been measured in patients with overt or occult benign breast disease, or in those with occult breast cancer. Subjects were studied in a hospital ward environment well-controlled with respect to ambient temperature. Using manual techniques temperatures were recorded half-hourly for 96 hr from replicate sensors placed on quadrants of the left and right breasts inclusive of tumour areas and similar sites on the contralateral breast. Application of time series analysis failed to consistently demonstrate differences in values for the rhythm parameters for the tumour area and contralateral site. It was apparent, however, that the tumour area was generally associated with a reduced initial variance of the series in addition to a reduced percentage variance explained by a time series model with two rhythmic components when compared to the control site. These data suggest that efforts to identify early breast disease from signals of breast temperature should, at least, be directed to studies of temperature variance.     

CICLOGRAMA: A TOOL FOR DETECTION OF RHYTHMICITIES IN SLEEP/WAKE CYCLES

The Fourier spectral analysis of binary time series (or rectangular signals) causes methodological problems, due to the fact that it is based on sinusoidal functions. We propose a new tool for the detection of periodicities in binary time series, focusing on sleep/wake cycles. This methodology is based on a weighted histogram of cycle durations. In this paper, we compare our methodology with the Fourier spectral analysis on the basis of simulated and real binary data sets of various lengths. We also provide an approach to statistical validation of the periodicities determined with our methodology. Furthermore, we analyze the discriminating power of both methods in terms of standard deviation. Our results indicate that the Ciclograma is much more powerful than Fourier analysis when applied on this type of time series.     

Ciclograma: a tool for detection of rhythmicities in sleep/wake cycles

The Fourier spectral analysis of binary time series (or rectangular signals) causes methodological problems, due to the fact that it is based on sinusoidal functions. We propose a new tool for the detection of periodicities in binary time series, focusing on sleep/wake cycles. This methodology is based on a weighted histogram of cycle durations. In this paper, we compare our methodology with the Fourier spectral analysis on the basis of simulated and real binary data sets of various lengths. We also provide an approach to statistical validation of the periodicities determined with our methodology. Furthermore, we analyze the discriminating power of both methods in terms of standard deviation. Our results indicate that the Ciclograma is much more powerful than Fourier analysis when applied on this type of time series.     

ARIMA模型在杭州市中小学生咳嗽症状监测中的应用

目的：探讨时间序列ARIMA模型在时间序列资料分析中的应用,建立咳嗽症状监测数据的预测模型.方法：采用条件最小二乘方法估计模型参数.通过对数转换及差分方法使原始序列平稳,按照残差不相关原则、简洁原则确定模型结构,依据AIC和SBC准则确定模型阶数,最终建立起ARIMA预测模型.结果：ARIMA（1,1,1）模型拟合效果较好,方差估计值为0.7361,AIC=95.6092,SBC=98.8310,对模型进行白噪声残差检验,提示残差为白噪声.结论：症状监测这种具有时间序列特点的资料可以用ARIMA模型来进行拟合估计.本文中预测结果可信区间比较宽,可能是因为时间序列比较短,还未能考虑到季节趋势.另外,所用监测数据是在中小学生在校发生症状的人数,故在节假日会出现缺失值,样本量和时间长度均有限,可能影响模型估计的准确性,本研究的结论还有待于将来资料积累后进行修正和深化.