Selecting EEG components using time series analysis in brain death diagnosis

In diagnosis of brain death for human organ transplant, EEG (electroencephalogram) must be flat to conclude the patient’s brain death but it has been reported that the flat EEG test is sometimes difficult due to artifacts such as the contamination from the power supply and ECG (electrocardiogram, the signal from the heartbeat). ICA (independent component analysis) is an effective signal processing method that can separate such artifacts from the EEG signals. Applying ICA to EEG channels, we obtain several separated components among which some correspond to the brain activities while others contain artifacts. This paper aims at automatic selection of the separated components based on time series analysis. In the flat EEG test in brain death diagnosis, such automatic component selection is helpful.     

环境温度对爪鲵体温及能量代谢的影响

应用封闭式小动物能量代谢仪测定了爪鲵在6℃、10℃、15℃、20℃和25℃环境条件下的体温和能量代谢以及在极端环境中的耐受性,探讨环境温度对爪鲵体温及能量代谢的影响.结果表明:爪鲵体温与环境温度呈正相关,其直线回归方程为:Tb=0.6966 0.9518Ta,相关非常显著.爪鲵对极端环境温度的耐受力较弱,在32℃-35℃高温和-2℃到-6℃低温 环境中的致死体温(TbL50)分别为27.7℃±0.9165℃和2.85℃±0.1539℃.在环 境温度为6℃-25℃的范围内,爪鲵的能量代谢与环境温度呈指数回归相关,指数方程为MR=0 .7495e0.0408x,相关显著.其代谢水平随环境温度的升高而升高,不同于内热源动物的代谢特征,爪鲵的体温调节和能量代谢显示出外热源动物的特点     

Effect of ambient temperature on the circadian activity rhythm in common marmosets, Callithrix j. jacchus (primates)

Whereas the (zeitgeber) effect of ambient temperature T_a and temperature cycles TaC's on circadian rhythmicity has been well documented for heterofhermic mammals, inconsistent results have been obtained for strictly homeothermic species. Hence, it might be inferred that the susceptibility of the mammalian circadian timing system (CTS) to Ta and TaC's depends on the range of the animals' core and/or brain temperature rhythm. This hypothesis was tested in the common marmoset (Callithrix j. jacchus, n=12), a small diurnal primate with an amplitude in body temperature rhythm that is larger than for other homeothermic primates studied so far. Within the range 20-30°C, no systematic effects of constant Ta on most parameters of the marmosets' light-dark (LD)-entrained and free-running circadian activity rhythm (CAR) were found. Significant differences could be established in the average amount of activity per circadian cycle. It was highest at Ta 25°C (LD) and 20°C (light-light, LL) and most probably reflected a temperature-induced masking effect. A 24h trapezoidal TaC of 20:30°C entrained the free-running CAR in two of six marmosets and produced relative coordination in all others. Accordingly, in all animals tested, it had an effect on the CTS. In marmosets free running in LL at a Ta of 20°C or 30°C, 3h warm and cold pulses of 30°C and 20°C, respectively, produced neither systematic phase responses nor period responses of the CAR. So, there is no evidence of a phase-response mechanism underlying circadian entrainment. The results show that large-amplitude TaC's function as a weak zeitgeber for the marmosets' CTS. Since this zeitgeber effect is significantly larger than that found in owl monkeys, the results are consistent with the starting hypothesis that the zeitgeber effect of a given T,C on the mammalian CTS may be related to the amplitude of the species' core and/or brain temperature cycle.     

Further demonstration of the ambient temperature dependence of the annual biological cycles in the edible dormouse,Glis glis

Summary In the male edible dormouse, it has been proposed that the annual temperature cycle is the major external factor triggering annual biological rhythms in this hibernating species. The present study was designed to explore (i) the effects of suppression of the annual thermoperiodic cycle under natural photoperiodic conditions, and (ii) the effects of acute exposure to a warm environment on basal plasma T4 levels observed during hibernation. The results of the first experiment demonstrate an absence of circannual cycles of hibernation, body weight, and endocrine thyroid and gonadal functions in the absence of annual fluctuations of temperature (constant warm environment at 24°C) despite the maintenance of a normal photoperiodic cycle. On the other hand, acute exposure to 24°C during the late stage of hibernation stimulated thyroid function as expressed by a consistent transitory rise in plasma T4 concentrations, which was maximal within 7 days and restored to basal levels after 14 days. These findings are in close agreement with the concept that in the edible dormouse, the annual thyroid cycle is synchronized with the annual temperature cycle. Moreover, the present study, combined with prior data indicating that the thyroid cycle induces the testis cycle, suggests that the ambient temperature cycle may be intricately involved in the control of neuroendocrine cycles in dormice, although the mechanism is still unknown.     

A Bayesian model averaging approach for estimating the relative risk of mortality associated with heat waves in 105 U.S. cities

Estimating the risks heat waves pose to human health is a critical part of assessing the future impact of climate change. In this article, we propose a flexible class of time series models to estimate the relative risk of mortality associated with heat waves and conduct Bayesian model averaging (BMA) to account for the multiplicity of potential models. Applying these methods to data from 105 U.S. cities for the period 1987-2005, we identify those cities having a high posterior probability of increased mortality risk during heat waves, examine the heterogeneity of the posterior distributions of mortality risk across cities, assess sensitivity of the results to the selection of prior distributions, and compare our BMA results to a model selection approach. Our results show that no single model best predicts risk across the majority of cities, and that for some cities heat-wave risk estimation is sensitive to model choice. Although model averaging leads to posterior distributions with increased variance as compared to statistical inference conditional on a model obtained through model selection, we find that the posterior mean of heat wave mortality risk is robust to accounting for model uncertainty over a broad class of models.     

Dendroclimatic analysis of Pinus peuce Griseb. at subalpine and treeline locations in Pirin Mountains,Bulgaria

Tree rings are a natural archive containing valuable information about environmental changes. Among the most sensitive ecosystems to such changes are high-mountain forests. Tree-ring series from such locations are exceptionally valuable both for climate reconstructions and for studying the effects of climate changes on forest ecosystems.The objective of our study is to present new long tree-ring width chronologies of Pinus peuce Griseb. from several locations at Pirin Mountains in southwestern Bulgaria, to explore their correlation with monthly temperatures and precipitation in the research area and to assess their potential for climate reconstruction.We built three long-term index chronologies for the radial increment of P. peuce from treeline locations in the study region. The longest chronology spans 675 years. We studied the impact of monthly air temperature and precipitation on its growth for the past 86 years using multiple regression analysis. Our analysis shows that P. peuce growth is positively influenced by high temperatures at the end of the previous growing season, especially at the two sites in Banderitsa valley until the middle of the 1970s, and negatively affected by cold winters. In some of the sample plots its growth was also positively correlated with high summer temperatures. However, even at these high altitudes in some of the locations on steep slopes P. peuce showed signs of negative impact of drought during the hottest summer months (especially in August).Our chronologies contribute to the paleoclimatic record for southwestern Bulgaria, which could provide baseline information about past climate variability and improve our understanding of current and future environmental changes.     

A multi-scale dendroclimatological analysis of four common species in the southern Canadian boreal forest

A comprehensive assessment of the tree growth/climate relationship was undertaken to better understand the potential impacts of climate change on the growth dynamics of four widespread and common boreal tree species, namely jack pine (Pinus banksiana), black spruce (Picea mariana), eastern larch (Larix laricina), and trembling aspen (Populus tremuloides), located at the southern limits of the Canadian boreal forest. Over intra-annual time scales, results show that precipitation is likely the main driver of stem radius change (∆R), with jack pine radius exhibiting the most consistent positive relationship. Precipitation had a stronger relationship with stem radius variation in black spruce and eastern larch during periods when volumetric water content (VWC) in the root zone was below average, pointing to the likelihood that certain species rely more heavily on available moisture in the uppermost layers of the soil column to replenish stem water, especially during extended dry periods. Warm air temperatures had an immediate negative impact on stem water content due to transpiration. This was most marked during periods of reduced moisture availability in the root zone, when trees are more susceptible to net water volume loss. During periods when moisture was not limiting, a positive relationship between lagged air temperature and ∆R was detected. Warm air temperatures may therefore play an important role in stimulating radial growth when moisture requirements are met. At annual temporal resolution, the growth/climate relationship changed over the lifetime of our study species. Over the last several decades, the relationship between precipitation and annual radial tree growth has weakened, while positive relationships between spring and summer air temperature and annual radial tree growth have emerged, likely signaling a decrease in moisture limitations, and a positive response to spring warming. Our findings reveal that boreal forest tree species may benefit from spring and summer warming over the near term, providing there is sufficient moisture to support growth. Over the long term, rates of evapotranspiration are expected to overshadow gains in moisture related to an increase in precipitation. Under these circumstances, we are likely to see reduced growth rates and an increasingly negative response of boreal tree species growth to warm air temperatures.     

Motor potential profile and a robust method for extracting it from time series of motor positions

Molecular motors are small, and, as a result, motor operation is dominated by high-viscous friction and large thermal fluctuations from the surrounding fluid environment. The small size has hindered, in many ways, the studies of physical mechanisms of molecular motors. For a macroscopic motor, it is possible to observe/record experimentally the internal operation details of the motor. This is not yet possible for molecular motors. The chemical reaction in a molecular motor has many occupancy states, each having a different effect on the motor motion. The overall effect of the chemical reaction on the motor motion can be characterized by the motor potential profile. The potential profile reveals how the motor force changes with position in a motor step, which may lead to insights into how the chemical reaction is coupled to force generation. In this article, we propose a mathematical formulation and a robust method for constructing motor potential profiles from time series of motor positions measured in single molecule experiments. Numerical examples based on simulated data are shown to demonstrate the method. Interestingly, it is the small size of molecular motors (negligible inertia) that makes it possible to recover the potential profile from time series of motor positions. For a macroscopic motor, the variation of driving force within a cycle is smoothed out by the large inertia.     

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。     

A benchmark test of accuracy and precision in estimating dynamical systems characteristics from a time series

Characteristics of dynamical systems are often estimated to describe physiological processes. For instance, Lyapunov exponents have been determined to assess the stability of the cardio-vascular system, respiration, and, more recently, human gait and posture. However, the systematic evaluation of the accuracy and precision of these estimates is problematic because the proper values of the characteristics are typically unknown. We fill this void with a set of standardized time series with well-defined dynamical characteristics that serve as a benchmark. Estimates ought to match these characteristics, at least to good approximation. We outline a procedure to employ this generic benchmark test and illustrate its capacity by examining methods for estimating the maximum Lyapunov exponent. In particular, we discuss algorithms by Wolf and co-workers and by Rosenstein and co-workers and evaluate their performances as a function of signal length and signal-to-noise ratio. In all scenarios, the precision of Rosenstein's algorithm was found to be equal to or greater than Wolf's algorithm. The latter, however, appeared more accurate if reasonably large signal lengths are available and noise levels are sufficiently low. Due to its modularity, the presented benchmark test can be used to evaluate and tune any estimation method to perform optimally for arbitrary experimental data.     

Identifying cardinal dates in phytoplankton time series to enable the analysis of long-term trends

Phenology and seasonal succession in aquatic ecosystems are strongly dependent on physical factors. In order to promote investigations into this coupling, methods of characterising annual time series of phytoplankton were derived and applied to a 31-year data set from Saidenbach Reservoir (Saxony, Germany). Field data are often scarce and irregularly sampled, particularly in the transition period from winter to spring, so reliable methods of determining cardinal dates in the time series are necessary. The proposed methods were used to determine the beginning, maximum and end of the spring mass development of phytoplankton by estimating the inflexion points (A), fitting a Weibull-type function (B) and fitting linear segments to the logarithmic values (C). For the data set from Saidenbach Reservoir, all three methods proved to be relevant to the analysis of long-term trends. Differences between the maxima determined by the different methods seemed small, but there were deviations when the maximum was related to physical factors such as ice-out. The Weibull-type fit gave the most reliable and comprehensible results and is recommended for trend analyses. For all methods, long-term analysis of the duration of the spring mass development and the duration of the spring full circulation revealed a period of consistently low values (1975-1990) followed by a period of higher values (1990-2005). These periods were also identified for the date of ice-out, although in this case there was a period of high values followed by a period of low values. A sensitivity analysis that compared results from subsampled time series with increasing time intervals indicated that a minimum of one sample every three weeks is needed to obtain reliable results.     

On the equivalence of case-crossover and time series methods in environmental epidemiology

The case-crossover design was introduced in epidemiology 15 years ago as a method for studying the effects of a risk factor on a health event using only cases. The idea is to compare a case's exposure immediately prior to or during the case-defining event with that same person's exposure at otherwise similar "reference" times. An alternative approach to the analysis of daily exposure and case-only data is time series analysis. Here, log-linear regression models express the expected total number of events on each day as a function of the exposure level and potential confounding variables. In time series analyses of air pollution, smooth functions of time and weather are the main confounders. Time series and case-crossover methods are often viewed as competing methods. In this paper, we show that case-crossover using conditional logistic regression is a special case of time series analysis when there is a common exposure such as in air pollution studies. This equivalence provides computational convenience for case-crossover analyses and a better understanding of time series models. Time series log-linear regression accounts for overdispersion of the Poisson variance, while case-crossover analyses typically do not. This equivalence also permits model checking for case-crossover data using standard log-linear model diagnostics.     

Climate change and the potential for range expansion of the Lyme disease vector Ixodes scapularis in Canada

We used an Ixodes scapularis population model to investigate potential northward spread of the tick associated with climate change. Annual degree-days >0 degrees C limits for I. scapularis establishment, obtained from tick population model simulations, were mapped using temperatures projected for the 2020s, 2050s and 2080s by two Global Climate Models (the Canadian CGCM2 and the UK HadCM3) for two greenhouse gas emission scenario enforcings 'A2'and 'B2' of the Intergovernmental Panel on Climate Change. Under scenario 'A2' using either climate model, the theoretical range for I. scapularis establishment moved northwards by approximately 200 km by the 2020s and 1000 km by the 2080s. Reductions in emissions (scenario 'B2') had little effect on projected range expansion up to the 2050s, but the range expansion projected to occur between the 2050s and 2080s was less than that under scenario 'A2'. When the tick population model was driven by projected annual temperature cycles (obtained using CGCM2 under scenario 'A2'), tick abundance almost doubled by the 2020s at the current northern limit of I. scapularis, suggesting that the threshold numbers of immigrating ticks needed to establish new populations will fall during the coming decades. The projected degrees of theoretical range expansion and increased tick survival by the 2020s, suggest that actual range expansion of I. scapularis may be detectable within the next two decades. Seasonal tick activity under climate change scenarios was consistent with maintenance of endemic cycles of the Lyme disease agent in newly established tick populations. The geographic range of I. scapularis-borne zoonoses may, therefore, expand significantly northwards as a consequence of climate change this century.     

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.     

Assessing co-regulation of directly linked genes in biological networks using microarray time series analysis

Differential expression of genes detected with the analysis of high throughput genomic experiments is a commonly used intermediate step for the identification of signaling pathways involved in the response to different biological conditions. The impact analysis was the first approach for the analysis of signaling pathways involved in a certain biological process that was able to take into account not only the magnitude of the expression change of the genes but also the topology of signaling pathways including the type of each interactions between the genes. In the impact analysis, signaling pathways are represented as weighted directed graphs with genes as nodes and the interactions between genes as edges. Edges weights are represented by a β factor, the regulatory efficiency, which is assumed to be equal to 1 in inductive interactions between genes and equal to −1 in repressive interactions. This study presents a similarity analysis between gene expression time series aimed to find correspondences with the regulatory efficiency, i.e. the β factor as found in a widely used pathway database. Here, we focused on correlations among genes directly connected in signaling pathways, assuming that the expression variations of upstream genes impact immediately downstream genes in a short time interval and without significant influences by the interactions with other genes. Time series were processed using three different similarity metrics. The first metric is based on the bit string matching; the second one is a specific application of the Dynamic Time Warping to detect similarities even in presence of stretching and delays; the third one is a quantitative comparative analysis resulting by an evaluation of frequency domain representation of time series: the similarity metric is the correlation between dominant spectral components. These three approaches are tested on real data and pathways, and a comparison is performed using Information Retrieval benchmark tools, indicating the frequency approach as the best similarity metric among the three, for its ability to detect the correlation based on the correspondence of the most significant frequency components.     

山东省典型地表覆被NDVI时间序列谐波分析

NDVI时间序列的谐波分析可描述不同地表覆被的季节变化.本文运用谐波分析法对山东省一年的MDOIS NDVI时间序列数据进行分析处理,提取了该地区几种典型地表覆被的谐波特征.结果表明:利用谐波分析生成的前几个谐波分量就可重建原始时间序列,且重建的时间序列剖面为平滑曲线,因此谐波分析不仅可减少数据量,并可去除噪声的影响;...     

Photoperiodic and ambient temperature control of the annual body mass cycle in Svalbard ptarmigan

The present study describes the photoperiodic control of annual body mass changes in captive. Svalbard ptarmigan, in particular the onset of autumnal increase and midwinter decrease in fat content under natural and simulated daylight-conditions in Tromsø (69° 46 N). Autumnal fattening commences when the birds become photorefractory and presumably depends on this condition. At present it is not known if any causal relationship is involved. Under outdoor ambient temperature, body mass begins to decline in November. However, when Svalbard ptarmigan are caged indoors at higher ambient temperatures and exposed to natural or simulated annual changes in daylength, body mass remains high until February. In these birds the depletion of fat stores appears to be triggered by the increasing daylength, since body mass remained high under permanent exposure to short days throughout spring but decreased promptly following photostimulation in May. When ptarmigan caged indoors were starved in midwinter body mass fell but increased briefly upon refeeding and thereafter declined as in the control birds throughout spring. This indicates that the winter body mass profile in Svalbard ptarmigan is not merely the passive outcome of shifts in the energy expenditure associated with thermoregulation, and that a sliding set point for body mass exists and is temporally fixed at the seasonal maximum in mid winter in birds caged under indoor ambient temperatures. The possibility is discussed that the decline in body mass seen outdoors may be associated with the increased hypothalamus-pituitary-gonadal activity which follows the breaking of photorefractoriness, and that this activity is sufficiently suppressed in Svalbard ptarmigan caged indoors under exposure to short days, to delay the reduction until they are photostimulated.Abbreviations BM body mass - GH growth hormone - HPG hypothalamic-pituitary-gonadal system - LL continous light - NL natural light - SD short day (4 hours light per day) - SL simulated annual changes in daylength - T _a ambient temperature