Time stability of soil water storage measured by neutron probe and the effects of calibration procedures in a small watershed

The knowledge of soil water storage (SWS) of soil profiles is crucial for the adoption of vegetation restoration practices. With the aim of identifying representative sites to obtain the mean SWS of a watershed, a time stability analysis of neutron probe evaluations of SWS was performed by the means of relative differences and Spearman rank correlation coefficients. At the same time, the effects of different neutron probe calibration procedures were explored on time stability analysis. mean SWS estimation. and preservation of the spatial variability of SWS. The selected watershed, with deep gullies and undulating slopes which cover an area of 20 ha, is characterized by an Ust-Sandiic Entisol and an Aeolian sandy soil. The dominant vegetation species are bunge needlegrass (Stipa bungeana Trim) and korshinsk peashrub (Carugano Korshinskii kom.). From June 11, 2007 to July 23,2008, SWS of the top1 m soil layer was evaluated for 20 dates, based on neutron probe data of 12 sampling sites. Three calibration procedures were employed: type 1, most complete, with each site having its own linear calibration equation (TrE); type II. with TrE equations extended over the whole field: and type III, with one single linear calibration curve for the whole field (UnE) and also correcting its intercept based on site specific relative difference analysis (RdE) and on linear fitting of data (RcE), both maintaining the same slope. A strong time stability of SWS estimated by TrE equations was identified. Soil particle size and soil organic matter content were recognized as the influencing factors for spatial variability of SWS. Land use influenced neither the spatial variability nor the time stability of SWS. Time stability analysis identified one site to represent the mean SWS of the whole watershed with mean absolute percentage errors of less than 10%, therefore. this site can be used as a predictor for the mean SWS of the watershed. Some equations of type II were found to be unsatisfactory to yield reliable mean SWS values or in preserving the associated soil spatial variability. Hence, it is recommended to be cautious in extending calibration equations to other sites since they might not consider the field variability. For the equations with corrected intercept (type III), which consider the spatial variability of calibration in a different way in relation to TrE, it was found that they can yield satisfactory means and standard deviation of SWS, except for the RdE equations, which largely leveled off the SWS values in the watershed. Correlation analysis showed that the neutron probe calibration was linked to soil bulk density and to organic matter content. Therefore, spatial variability of soil properties should be taken into account during the process of neutron probe calibration. This study provides useful information on the mean SWS observation with a time stable site and on distinct neutron probe calibration procedures, and it should be extended to soil water management studies with neutron probes, e.g., the process of vegetation restoration in wider area and soil types of the Loess Plateau in China. (C) 2009 Elsevier B.V. All rights reserved.

Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

MODIS NDVI time-series allow the monitoring of Eucalyptus plantation biomass

The use of remote sensing is necessary for monitoring forest carbon stocks at large scales. Optical remote sensing, although not the most suitable technique for the direct estimation of stand biomass, offers the advantage of providing large temporal and spatial datasets. In particular, information on canopy structure is encompassed in stand reflectance time series. This study focused on the example of Eucalyptus forest plantations, which have recently attracted much attention as a result of their high expansion rate in many tropical countries. Stand scale time-series of Normalized Difference Vegetation Index (NDVI) were obtained from MODIS satellite data after a procedure involving un-mixing and interpolation, on about 15,000 ha of plantations in southern Brazil. The comparison of the planting date of the current rotation (and therefore the age of the stands) estimated from these time series with real values provided by the company showed that the root mean square error was 35.5 days. Age alone explained more than 82% of stand wood volume variability and 87% of stand dominant height variability. Age variables were combined with other variables derived from the NDVI time series and simple bioclimatic data by means of linear (Stepwise) or nonlinear (Random Forest) regressions. The nonlinear regressions gave r-square values of 0.90 for volume and 0.92 for dominant height, and an accuracy of about 25 m(3)/ha for volume (15% of the volume average value) and about 1.6 m for dominant height (8% of the height average value). The improvement including NDVI and bioclimatic data comes from the fact that the cumulative NDVI since planting date integrates the interannual variability of leaf area index (LAI), light interception by the foliage and growth due for example to variations of seasonal water stress. The accuracy of biomass and height predictions was strongly improved by using the NDVI integrated over the two first years after planting, which are critical for stand establishment. These results open perspectives for cost-effective monitoring of biomass at large scales in intensively-managed plantation forests. (C) 2011 Elsevier Inc. All rights reserved.

Relating MODIS vegetation index time-series with structure, light absorption and stem production of fast-growing Eucalyptus plantations

By allowing the estimation of forest structural and biophysical characteristics at different temporal and spatial scales, remote sensing may contribute to our understanding and monitoring of planted forests. Here, we studied 9-year time-series of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on a network of 16 stands in fast-growing Eucalyptus plantations in Sao Paulo State, Brazil. We aimed to examine the relationships between NDVI time-series spanning entire rotations and stand structural characteristics (volume, dominant height, mean annual increment) in these simple forest ecosystems. Our second objective was to examine spatial and temporal variations of light use efficiency for wood production, by comparing time-series of Absorbed Photosynthetically Active Radiation (APAR) with inventory data. Relationships were calibrated between the NDVI and the fractions of intercepted diffuse and direct radiation, using hemispherical photographs taken on the studied stands at two seasons. APAR was calculated from the NDVI time-series using these relationships. Stem volume and dominant height were strongly correlated with summed NDVI values between planting date and inventory date. Stand productivity was correlated with mean NDVI values. APAR during the first 2 years of growth was variable between stands and was well correlated with stem wood production (r(2) = 0.78). In contrast, APAR during the following years was less variable and not significantly correlated with stem biomass increments. Production of wood per unit of absorbed light varied with stand age and with site index. In our study, a better site index was accompanied both by increased APAR during the first 2 years of growth and by higher light use efficiency for stem wood production during the whole rotation. Implications for simple process-based modelling are discussed. (C) 2009 Elsevier B.V. All rights reserved.

Effects of coping strategies, social support and work-nonwork conflict on shift worker's health

Objectives This study examines the direct and mediated effects of shift workers' coping strategies and social support on structural work-nonwork conflict and subjective health. Methods The participants were 172 registered female nurses, aged 21 to 40 years. They all worked full-time, on rapidly rotating, 8-hour shifts in metropolitan general hospitals. All the respondents completed a self-administered questionnaire requesting demographic information and data on sources of social support, work-nonwork conflict, and coping strategies. Results A path model with good fit (chi(2)=28.88, df=23, P>.23, CFI=0.97) demonstrated complex effects of social support and coping on structural work-nonwork conflict and health. Conclusions Structural work-nonwork conflict mediated the effects of social support from supervisors and emotionally expressive coping on psychological symptoms. Control of shifts mediated the effect of social support from supervisors on structural work-nonwork conflict. Disengagement coping had direct and mediated effects on psychological and physical health. However, it also had mediated effects, with the effect on psychological health being mediated by support from co-workers and the effect on physical symptoms being mediated by family support. Go-worker support mediated the effect of social support from supervisors on psychological symptoms. Overall, these findings support previous research and clarify the process by which coping strategies and social support affect structural work-nonwork conflict and health in shift work.

Estimation of contribution of changes in classic risk factors to trends in coronary-event rates across the WHO MONICA Project populations

Background From the mid-1980s to mid-1990s, the WHO MONICA Project monitored coronary events and classic risk factors for coronary heart disease (CHD) in 38 populations from 21 countries. We assessed the extent to which changes in these risk factors explain the variation in the trends in coronary-event rates across the populations. Methods In men and women aged 35-64 years, non-fatal myocardial infarction and coronary deaths were registered continuously to assess trends in rates of coronary events. We carried out population surveys to estimate trends in risk factors. Trends in event rates were regressed on trends in risk score and in individual risk factors. Findings Smoking rates decreased in most male populations but trends were mixed in women; mean blood pressures and cholesterol concentrations decreased, body-mass index increased, and overall risk scores and coronary-event rates decreased. The model of trends in 10-year coronary-event rates against risk scores and single risk factors showed a poor fit, but this was improved with a 4-year time lag for coronary events. The explanatory power of the analyses was limited by imprecision of the estimates and homogeneity of trends in the study populations. Interpretation Changes in the classic risk factors seem to partly explain the variation in population trends in CHD. Residual variance is attributable to difficulties in measurement and analysis, including time lag, and to factors that were not included, such as medical interventions. The results support prevention policies based on the classic risk factors but suggest potential for prevention beyond these.

Autonomic activity during human sleep as a function of time and sleep stage

While there is a developing understanding of the influence of sleep on cardiovascular autonomic activity in humans, there remain unresolved issues. In particular, the effect of time within the sleep period, independent of sleep stage, has not been investigated. Further, the influence of sleep on central sympathetic nervous system (SNS) activity is uncertain because results using the major method applicable to humans, the low frequency (LF) component of heart rate Variability (HRV), have been contradictory, and because the method itself is open to criticism. Sleep and cardiac activity were measured in 14 young healthy subjects on three nights. Data was analysed in 2-min epochs. All epochs meeting specified criteria were identified, beginning 2 h before, until 7 h after, sleep onset. Epoch values were allocated to 30-min bins and during sleep were also classified into stage 2, slow wave sleep (SWS) and rapid eye movement (REM) sleep. The measures of cardiac activity were heart irate (HR), blood pressure (BP), high frequency (HF) and LF components of HRV and pre-ejection period (PEP). During non-rapid eye movement (NREM) sleep autonomic balance shifted from sympathetic to parasympathetic dominance, although this appeared to be more because of a shift in parasympathetic nervous system (PNS) activity. Autonomic balance during REM was in general similar to wakefulness. For BP and the HF and LF components the change occurred abruptly at sleep onset and was then constant over time within each stage of sleep, indicating that any change in autonomic balance over the sleep period is a consequence of the changing distribution of sleep stages. Two variables, HR and PEP, did show time effects reflecting a circadian influence over HR and perhaps time asleep affecting PEP. While both the LF component and PEP showed changes consistent with reduced sympathetic tone during sleep, their pattern of change over time differed.

Modelling the Distribution of Ischaemic Stroke-Specific Survival Time Using an EM-based Mixture Approach with Random Effects Adjustment

A two-component survival mixture model is proposed to analyse a set of ischaemic stroke-specific mortality data. The survival experience of stroke patients after index stroke may be described by a subpopulation of patients in the acute condition and another subpopulation of patients in the chronic phase. To adjust for the inherent correlation of observations due to random hospital effects, a mixture model of two survival functions with random effects is formulated. Assuming a Weibull hazard in both components, an EM algorithm is developed for the estimation of fixed effect parameters and variance components. A simulation study is conducted to assess the performance of the two-component survival mixture model estimators. Simulation results confirm the applicability of the proposed model in a small sample setting. Copyright (C) 2004 John Wiley Sons, Ltd.

Time flies with music whatever its emotional valence

The present study used a temporal bisection task to investigate whether music affects time estimation differently from a matched auditory neutral stimulus, and whether the emotional valence of the musical stimuli (i.e., sad vs. happy music) modulates this effect. The results showed that, compared to sine wave control music, music presented in a major (happy) or a minor (sad) key shifted the bisection function toward the right, thus increasing the bisection point value (point of subjective equality). This indicates that the duration of a melody is judged shorter than that of a non-melodic control stimulus, thus confirming that ""time flies"" when we listen to music. Nevertheless, sensitivity to time was similar for all the auditory stimuli. Furthermore, the temporal bisection functions did not differ as a function of musical mode. (C) 2010 Elsevier B.V. All rights reserved.

STATIC IMAGES WITH DIFFERENT INDUCED INTENSITIES OF HUMAN BODY MOVEMENTS AFFECT SUBJECTIVE TIME

Modulation of subjective time was examined using static images eliciting perceptions of different intensities of body movement. Undergraduate students were exposed to photographs of dancer sculptures in different dance positions for 36 sec. and asked to estimate the exposure duration. Lower movement intensities were related to shorter estimated durations. Mean durations for images of unmoving dancers were underestimated and for dancers taking a ballet step were overestimated. Temporal estimations were also related to the order of presentation of the stimuli, which suggested that subjective time estimations were influenced by the experimental context. Subjective time is related not only to the visual perception of moving images, but also of elicited perceptions of movement in static images, suggesting an embodiment effect on subjective time estimation.

Applying linear time-varying constraints to econometric models: With an application to demand systems

When linear equality constraints are invariant through time they can be incorporated into estimation by restricted least squares. If, however, the constraints are time-varying, this standard methodology cannot be applied. In this paper we show how to incorporate linear time-varying constraints into the estimation of econometric models. The method involves the augmentation of the observation equation of a state-space model prior to estimation by the Kalman filter. Numerical optimisation routines are used for the estimation. A simple example drawn from demand analysis is used to illustrate the method and its application.

TIME COURSE OF SKELETAL MUSCLE LOSS AND OXIDATIVE STRESS IN RATS WITH WALKER 256 SOLID TUMOR

Reactive oxygen species oxidize proteins and modulate the proteasomal system in muscle-wasting cancer cachexia. On day 5 (D5), day 10 (D10), and day 14 (D14) after tumor implantation, skeletal muscle was evaluated. Carbonylated proteins and thiobarbituric acid reactive substances were measured. Chemiluminescence was employed for lipid hydroperoxide estimation. Glutathione, superoxide dismutase, and total radical antioxidant capacity were evaluated. The proteasomal system was assessed by mRNA atrogin-1 expression. Increased muscle wasting, lipid hydroperoxide, and superoxide dismutase, and decreased glutathione levels and total radical antioxidant capacity, were found on D5 in accordance with increased mRNA atrogin-1 expression. All parameters were significantly modified in animals treated with alpha-tocopherol. The elevation in aldehylde levels and carbonylated proteins observed on D10 were reversed by cc-tocopherol treatment. Oxidative stress may trigger signal transduction of the proteasomal system and cause protein oxidation. These pathways may be associated with the mechanism of muscle wasting that occurs in cancer cachexia. Muscle Nerve 42: 950-958, 2010

Quantitative analysis of the time courses of enzyme-catalyzed reactions

The catalytic properties of enzymes are usually evaluated by measuring and analyzing reaction rates. However, analyzing the complete time course can be advantageous because it contains additional information about the properties of the enzyme. Moreover, for systems that are not at steady state, the analysis of time courses is the preferred method. One of the major barriers to the wide application of time courses is that it may be computationally more difficult to extract information from these experiments. Here the basic approach to analyzing time courses is described, together with some examples of the essential computer code to implement these analyses. A general method that can be applied to both steady state and non-steady-state systems is recommended. (C) 2001 academic Press.

Optimal input states and feedback for interferometric phase estimation

We derive optimal N-photon two-mode input states for interferometric phase measurements. Under canonical measurements the phase variance scales as N-2 for these states, as compared to N-1 or N-1/2 for states considered bq previous authors. We prove, that it is not possible to realize the canonical measurement by counting photons in the outputs of the interferometer, even if an adjustable auxiliary phase shift is allowed in the interferometer. However. we introduce a feedback algorithm based on Bayesian inference to control this auxiliary phase shift. This makes the measurement close to a canonical one, with a phase variance scaling slightly above N-2. With no feedback, the best result (given that the phase to be measured is completely unknown) is a scaling of N-1. For optimal input states having up to four photons, our feedback scheme is the best possible one, but for higher photon numbers more complicated schemes perform marginally better.

Preprocessing and time-frequency analysis of newborn EEG seizures

Neurological disease or dysfunction in newborn infants is often first manifested by seizures. Prolonged seizures can result in impaired neurodevelopment or even death. In adults, the clinical signs of seizures are well defined and easily recognized. In newborns, however, the clinical signs are subtle and may be absent or easily missed without constant close observation. This article describes the use of adaptive signal processing techniques for removing artifacts from newborn electroencephalogram (EEG) signals. Three adaptive algorithms have been designed in the context of EEG signals. This preprocessing is necessary before attempting a fine time-frequency analysis of EEG rhythmical activities, such as electrical seizures, corrupted by high amplitude signals. After an overview of newborn EEG signals, the authors describe the data acquisition set-up. They then introduce the basic physiological concepts related to normal and abnormal newborn EEGs and discuss the three adaptive algorithms for artifact removal. They also present time-frequency representations (TFRs) of seizure signals and discuss the estimation and modeling of the instantaneous frequency related to the main ridge of the TFR.