Probability distribution of financial returns in a model of multiplicative Brownian motion with stochastic diffusion coefficient

NASA Astrophysics Data System (ADS)

Silva, Antonio

2005-03-01

It is well-known that the mathematical theory of Brownian motion was first developed in the Ph. D. thesis of Louis Bachelier for the French stock market before Einstein [1]. In Ref. [2] we studied the so-called Heston model, where the stock-price dynamics is governed by multiplicative Brownian motion with stochastic diffusion coefficient. We solved the corresponding Fokker-Planck equation exactly and found an analytic formula for the time-dependent probability distribution of stock price changes (returns). The formula interpolates between the exponential (tent-shaped) distribution for short time lags and the Gaussian (parabolic) distribution for long time lags. The theoretical formula agrees very well with the actual stock-market data ranging from the Dow-Jones index [2] to individual companies [3], such as Microsoft, Intel, etc. [] [1] Louis Bachelier, ``Th'eorie de la sp'eculation,'' Annales Scientifiques de l''Ecole Normale Sup'erieure, III-17:21-86 (1900).[] [2] A. A. Dragulescu and V. M. Yakovenko, ``Probability distribution of returns in the Heston model with stochastic volatility,'' Quantitative Finance 2, 443--453 (2002); Erratum 3, C15 (2003). [cond-mat/0203046] [] [3] A. C. Silva, R. E. Prange, and V. M. Yakovenko, ``Exponential distribution of financial returns at mesoscopic time lags: a new stylized fact,'' Physica A 344, 227--235 (2004). [cond-mat/0401225

Gamma-Ray Burst Intensity Distributions

NASA Technical Reports Server (NTRS)

Band, David L.; Norris, Jay P.; Bonnell, Jerry T.

2004-01-01

We use the lag-luminosity relation to calculate self-consistently the redshifts, apparent peak bolometric luminosities L(sub B1), and isotropic energies E(sub iso) for a large sample of BATSE bursts. We consider two different forms of the lag-luminosity relation; for both forms the median redshift, for our burst database is 1.6. We model the resulting sample of burst energies with power law and Gaussian dis- tributions, both of which are reasonable models. The power law model has an index of a = 1.76 plus or minus 0.05 (95% confidence) as opposed to the index of a = 2 predicted by the simple universal jet profile model; however, reasonable refinements to this model permit much greater flexibility in reconciling predicted and observed energy distributions.

Predictability in community dynamics.

PubMed

Blonder, Benjamin; Moulton, Derek E; Blois, Jessica; Enquist, Brian J; Graae, Bente J; Macias-Fauria, Marc; McGill, Brian; Nogué, Sandra; Ordonez, Alejandro; Sandel, Brody; Svenning, Jens-Christian

2017-03-01

The coupling between community composition and climate change spans a gradient from no lags to strong lags. The no-lag hypothesis is the foundation of many ecophysiological models, correlative species distribution modelling and climate reconstruction approaches. Simple lag hypotheses have become prominent in disequilibrium ecology, proposing that communities track climate change following a fixed function or with a time delay. However, more complex dynamics are possible and may lead to memory effects and alternate unstable states. We develop graphical and analytic methods for assessing these scenarios and show that these dynamics can appear in even simple models. The overall implications are that (1) complex community dynamics may be common and (2) detailed knowledge of past climate change and community states will often be necessary yet sometimes insufficient to make predictions of a community's future state. © 2017 John Wiley & Sons Ltd/CNRS.

Implications of Lag-Luminosity Relationship for Unified GRB Paradigms

NASA Technical Reports Server (NTRS)

Norris, J. P.; White, Nicholas E. (Technical Monitor)

2002-01-01

Spectral lags (tau(sub lag)) are deduced for 1437 long (T(sub 90) greater than 2 s) BATSE gamma-ray bursts (GRBs) with peak flux F(sub p) greater than 0.25 photons cm(sup -2)/s, near to the BATSE trigger threshold. The lags are modeled to approximate the observed distribution in the F(sub p)-T(sub lag) plane, realizing a noise-free representation. Assuming a two-branch lag-luminosity relationship, the lags are self-consistently corrected for cosmological effects to yield distributions in luminosity, distance, and redshift. The results have several consequences for GRB populations and for unified gamma-ray/afterglow scenarios which would account for afterglow break times and gamma-ray spectral evolution in terms of jet opening angle, viewing angle, or a profiled jet with variable Lorentz factor: A component of the burst sample is identified - those with few, wide pulses, lags of a few tenths to several seconds, and soft spectra - whose Log[N]-Log[F(sub p)] distribution approximates a -3/2 power-law, suggesting homogeneity and thus relatively nearby sources. The proportion of these long-lag bursts increases from negligible among bright BATSE bursts to approx. 50% at trigger threshold. Bursts with very long lags, approx. 1-2 less than tau(sub lag) (S) less than 10, show a tendency to concentrate near the Supergalactic Plane with a quadrupole moment of approx. -0.10 +/- 0.04. GRB 980425 (SN 1998bw) is a member of this subsample of approx. 90 bursts with estimated distances less than 100 Mpc. The frequency of the observed ultra-low luminosity bursts is approx. 1/4 that of SNe Ib/c within the same volume. If truly nearby, the core-collapse events associated with these GRBs might produce gravitational radiation detectable by LIGO-II. Such nearby bursts might also help explain flattening of the cosmic ray spectrum at ultra-high energies, as observed by AGASA.

Time-dependent Electron Acceleration in Blazar Transients: X-Ray Time Lags and Spectral Formation

NASA Astrophysics Data System (ADS)

Lewis, Tiffany R.; Becker, Peter A.; Finke, Justin D.

2016-06-01

Electromagnetic radiation from blazar jets often displays strong variability, extending from radio to γ-ray frequencies. In a few cases, this variability has been characterized using Fourier time lags, such as those detected in the X-rays from Mrk 421 using BeppoSAX. The lack of a theoretical framework to interpret the data has motivated us to develop a new model for the formation of the X-ray spectrum and the time lags in blazar jets based on a transport equation including terms describing stochastic Fermi acceleration, synchrotron losses, shock acceleration, adiabatic expansion, and spatial diffusion. We derive the exact solution for the Fourier transform of the electron distribution and use it to compute the Fourier transform of the synchrotron radiation spectrum and the associated X-ray time lags. The same theoretical framework is also used to compute the peak flare X-ray spectrum, assuming that a steady-state electron distribution is achieved during the peak of the flare. The model parameters are constrained by comparing the theoretical predictions with the observational data for Mrk 421. The resulting integrated model yields, for the first time, a complete first-principles physical explanation for both the formation of the observed time lags and the shape of the peak flare X-ray spectrum. It also yields direct estimates of the strength of the shock and the stochastic magnetohydrodynamical wave acceleration components in the Mrk 421 jet.

Radio pulsar glitches as a state-dependent Poisson process

NASA Astrophysics Data System (ADS)

Fulgenzi, W.; Melatos, A.; Hughes, B. D.

2017-10-01

Gross-Pitaevskii simulations of vortex avalanches in a neutron star superfluid are limited computationally to ≲102 vortices and ≲102 avalanches, making it hard to study the long-term statistics of radio pulsar glitches in realistically sized systems. Here, an idealized, mean-field model of the observed Gross-Pitaevskii dynamics is presented, in which vortex unpinning is approximated as a state-dependent, compound Poisson process in a single random variable, the spatially averaged crust-superfluid lag. Both the lag-dependent Poisson rate and the conditional distribution of avalanche-driven lag decrements are inputs into the model, which is solved numerically (via Monte Carlo simulations) and analytically (via a master equation). The output statistics are controlled by two dimensionless free parameters: α, the glitch rate at a reference lag, multiplied by the critical lag for unpinning, divided by the spin-down rate; and β, the minimum fraction of the lag that can be restored by a glitch. The system evolves naturally to a self-regulated stationary state, whose properties are determined by α/αc(β), where αc(β) ≈ β-1/2 is a transition value. In the regime α ≳ αc(β), one recovers qualitatively the power-law size and exponential waiting-time distributions observed in many radio pulsars and Gross-Pitaevskii simulations. For α ≪ αc(β), the size and waiting-time distributions are both power-law-like, and a correlation emerges between size and waiting time until the next glitch, contrary to what is observed in most pulsars. Comparisons with astrophysical data are restricted by the small sample sizes available at present, with ≤35 events observed per pulsar.

Modeling exposure–lag–response associations with distributed lag non-linear models

PubMed Central

Gasparrini, Antonio

2014-01-01

In biomedical research, a health effect is frequently associated with protracted exposures of varying intensity sustained in the past. The main complexity of modeling and interpreting such phenomena lies in the additional temporal dimension needed to express the association, as the risk depends on both intensity and timing of past exposures. This type of dependency is defined here as exposure–lag–response association. In this contribution, I illustrate a general statistical framework for such associations, established through the extension of distributed lag non-linear models, originally developed in time series analysis. This modeling class is based on the definition of a cross-basis, obtained by the combination of two functions to flexibly model linear or nonlinear exposure-responses and the lag structure of the relationship, respectively. The methodology is illustrated with an example application to cohort data and validated through a simulation study. This modeling framework generalizes to various study designs and regression models, and can be applied to study the health effects of protracted exposures to environmental factors, drugs or carcinogenic agents, among others. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24027094

Quantifying the effect of water activity and storage temperature on single spore lag times of three moulds isolated from spoiled bakery products.

PubMed

Dagnas, Stéphane; Gougouli, Maria; Onno, Bernard; Koutsoumanis, Konstantinos P; Membré, Jeanne-Marie

2017-01-02

The inhibitory effect of water activity (a w ) and storage temperature on single spore lag times of Aspergillus niger, Eurotium repens (Aspergillus pseudoglaucus) and Penicillium corylophilum strains isolated from spoiled bakery products, was quantified. A full factorial design was set up for each strain. Data were collected at levels of a w varying from 0.80 to 0.98 and temperature from 15 to 35°C. Experiments were performed on malt agar, at pH5.5. When growth was observed, ca 20 individual growth kinetics per condition were recorded up to 35days. Radius of the colony vs time was then fitted with the Buchanan primary model. For each experimental condition, a lag time variability was observed, it was characterized by its mean, standard deviation (sd) and 5 th percentile, after a Normal distribution fit. As the environmental conditions became stressful (e.g. storage temperature and a w lower), mean and sd of single spore lag time distribution increased, indicating longer lag times and higher variability. The relationship between mean and sd followed a monotonous but not linear pattern, identical whatever the species. Next, secondary models were deployed to estimate the cardinal values (minimal, optimal and maximal temperatures, minimal water activity where no growth is observed anymore) for the three species. That enabled to confirm the observation made based on raw data analysis: concerning the temperature effect, A. niger behaviour was significantly different from E. repens and P. corylophilum: T opt of 37.4°C (standard deviation 1.4°C) instead of 27.1°C (1.4°C) and 25.2°C (1.2°C), respectively. Concerning the a w effect, from the three mould species, E. repens was the species able to grow at the lowest a w (aw min estimated to 0.74 (0.02)). Finally, results obtained with single spores were compared to findings from a previous study carried out at the population level (Dagnas et al., 2014). For short lag times (≤5days), there was no difference between lag time of the population (ca 2000 spores inoculated in one spot) and mean (nor 5 th percentile) of single spore lag time distribution. In contrast, when lag time was longer, i.e. under more stressful conditions, there was a discrepancy between individual and population lag times (population lag times shorter than 5 th percentiles of single spore lag time distribution), confirming a stochastic process. Finally, the temperature cardinal values estimated with single spores were found to be similar to those obtained at the population level, whatever the species. All these findings will be used to describe better mould spore lag time variability and then to predict more accurately bakery product shelf-life. Copyright © 2016 Elsevier B.V. All rights reserved.

Asymmetric impact of rainfall on India's food grain production: evidence from quantile autoregressive distributed lag model

NASA Astrophysics Data System (ADS)

Pal, Debdatta; Mitra, Subrata Kumar

2018-01-01

This study used a quantile autoregressive distributed lag (QARDL) model to capture asymmetric impact of rainfall on food production in India. It was found that the coefficient corresponding to the rainfall in the QARDL increased till the 75th quantile and started decreasing thereafter, though it remained in the positive territory. Another interesting finding is that at the 90th quantile and above the coefficients of rainfall though remained positive was not statistically significant and therefore, the benefit of high rainfall on crop production was not conclusive. However, the impact of other determinants, such as fertilizer and pesticide consumption, is quite uniform over the whole range of the distribution of food grain production.

Lags in the response of mountain plant communities to climate change

PubMed Central

Alexander, Jake M.; Chalmandrier, Loïc; Lenoir, Jonathan; Burgess, Treena I.; Essl, Franz; Haider, Sylvia; Kueffer, Christoph; McDougall, Keith; Milbau, Ann; Nuñez, Martin A.; Pauchard, Aníbal; Rabitsch, Wolfgang; Rew, Lisa J.; Sanders, Nathan J.; Pellissier, Loïc

2018-01-01

Rapid climatic changes and increasing human influence at high elevations around the world will have profound impacts on mountain biodiversity. However, forecasts from statistical models (e.g. species distribution models) rarely consider that plant community changes could substantially lag behind climatic changes, hindering our ability to make temporally realistic projections for the coming century. Indeed, the magnitudes of lags, and the relative importance of the different factors giving rise to them, remain poorly understood. We review evidence for three types of lag: “dispersal lags” affecting plant species’ spread along elevational gradients, “establishment lags” following their arrival in recipient communities, and “extinction lags” of resident species. Variation in lags is explained by variation among species in physiological and demographic responses, by effects of altered biotic interactions, and by aspects of the physical environment. Of these, altered biotic interactions could contribute substantially to establishment and extinction lags, yet impacts of biotic interactions on range dynamics are poorly understood. We develop a mechanistic community model to illustrate how species turnover in future communities might lag behind simple expectations based on species’ range shifts with unlimited dispersal. The model shows a combined contribution of altered biotic interactions and dispersal lags to plant community turnover along an elevational gradient following climate warming. Our review and simulation support the view that accounting for disequilibrium range dynamics will be essential for realistic forecasts of patterns of biodiversity under climate change, with implications for the conservation of mountain species and the ecosystem functions they provide. PMID:29112781

Response of spectral vegetation indices to soil moisture in grasslands and shrublands

USGS Publications Warehouse

Zhang, Li; Ji, Lei; Wylie, Bruce K.

2011-01-01

The relationships between satellite-derived vegetation indices (VIs) and soil moisture are complicated because of the time lag of the vegetation response to soil moisture. In this study, we used a distributed lag regression model to evaluate the lag responses of VIs to soil moisture for grasslands and shrublands at Soil Climate Analysis Network sites in the central and western United States. We examined the relationships between Moderate Resolution Imaging Spectroradiometer (MODIS)-derived VIs and soil moisture measurements. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) showed significant lag responses to soil moisture. The lag length varies from 8 to 56 days for NDVI and from 16 to 56 days for NDWI. However, the lag response of NDVI and NDWI to soil moisture varied among the sites. Our study suggests that the lag effect needs to be taken into consideration when the VIs are used to estimate soil moisture.

Effect of lag time distribution on the lag phase of bacterial growth - a Monte Carlo analysis

USDA-ARS?s Scientific Manuscript database

The objective of this study is to use Monte Carlo simulation to evaluate the effect of lag time distribution of individual bacterial cells incubated under isothermal conditions on the development of lag phase. The growth of bacterial cells of the same initial concentration and mean lag phase durati...

TIME-DEPENDENT ELECTRON ACCELERATION IN BLAZAR TRANSIENTS: X-RAY TIME LAGS AND SPECTRAL FORMATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, Tiffany R.; Becker, Peter A.; Finke, Justin D., E-mail: pbecker@gmu.edu, E-mail: tlewis13@gmu.edu, E-mail: justin.finke@nrl.navy.mil

2016-06-20

Electromagnetic radiation from blazar jets often displays strong variability, extending from radio to γ -ray frequencies. In a few cases, this variability has been characterized using Fourier time lags, such as those detected in the X-rays from Mrk 421 using Beppo SAX. The lack of a theoretical framework to interpret the data has motivated us to develop a new model for the formation of the X-ray spectrum and the time lags in blazar jets based on a transport equation including terms describing stochastic Fermi acceleration, synchrotron losses, shock acceleration, adiabatic expansion, and spatial diffusion. We derive the exact solution formore » the Fourier transform of the electron distribution and use it to compute the Fourier transform of the synchrotron radiation spectrum and the associated X-ray time lags. The same theoretical framework is also used to compute the peak flare X-ray spectrum, assuming that a steady-state electron distribution is achieved during the peak of the flare. The model parameters are constrained by comparing the theoretical predictions with the observational data for Mrk 421. The resulting integrated model yields, for the first time, a complete first-principles physical explanation for both the formation of the observed time lags and the shape of the peak flare X-ray spectrum. It also yields direct estimates of the strength of the shock and the stochastic magnetohydrodynamical wave acceleration components in the Mrk 421 jet.« less

An energy-balance model with multiply-periodic and quasi-chaotic free oscillations. [for climate forecasting

NASA Technical Reports Server (NTRS)

Bhattacharya, K.; Ghil, M.

1979-01-01

A slightly modified version of the one-dimensional time-dependent energy-balance climate model of Ghil and Bhattacharya (1978) is presented. The albedo-temperature parameterization has been reformulated and the smoothing of the temperature distribution in the tropics has been eliminated. The model albedo depends on time-lagged temperature in order to account for finite growth and decay time of continental ice sheets. Two distinct regimes of oscillatory behavior which depend on the value of the albedo-temperature time lag are considered.

SDSS IV MaNGA—Rotation Velocity Lags in the Extraplanar Ionized Gas from MaNGA Observations of Edge-on Galaxies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bizyaev, D.; Pan, K.; Brinkmann, J.

2017-04-20

We present a study of the kinematics of the extraplanar ionized gas around several dozen galaxies observed by the Mapping of Nearby Galaxies at the Apache Point Observatory (MaNGA) survey. We considered a sample of 67 edge-on galaxies out of more than 1400 extragalactic targets observed by MaNGA, in which we found 25 galaxies (or 37%) with regular lagging of the rotation curve at large distances from the galactic midplane. We model the observed H α emission velocity fields in the galaxies, taking projection effects and a simple model for the dust extinction into account. We show that the verticalmore » lag of the rotation curve is necessary in the modeling, and estimate the lag amplitude in the galaxies. We find no correlation between the lag and the star formation rate in the galaxies. At the same time, we report a correlation between the lag and the galactic stellar mass, central stellar velocity dispersion, and axial ratio of the light distribution. These correlations suggest a possible higher ratio of infalling-to-local gas in early-type disk galaxies or a connection between lags and the possible presence of hot gaseous halos, which may be more prevalent in more massive galaxies. These results again demonstrate that observations of extraplanar gas can serve as a potential probe for accretion of gas.« less

SDSS IV MaNGA—Rotation Velocity Lags in the Extraplanar Ionized Gas from MaNGA Observations of Edge-on Galaxies

NASA Astrophysics Data System (ADS)

Bizyaev, D.; Walterbos, R. A. M.; Yoachim, P.; Riffel, R. A.; Fernández-Trincado, J. G.; Pan, K.; Diamond-Stanic, A. M.; Jones, A.; Thomas, D.; Cleary, J.; Brinkmann, J.

2017-04-01

We present a study of the kinematics of the extraplanar ionized gas around several dozen galaxies observed by the Mapping of Nearby Galaxies at the Apache Point Observatory (MaNGA) survey. We considered a sample of 67 edge-on galaxies out of more than 1400 extragalactic targets observed by MaNGA, in which we found 25 galaxies (or 37%) with regular lagging of the rotation curve at large distances from the galactic midplane. We model the observed Hα emission velocity fields in the galaxies, taking projection effects and a simple model for the dust extinction into account. We show that the vertical lag of the rotation curve is necessary in the modeling, and estimate the lag amplitude in the galaxies. We find no correlation between the lag and the star formation rate in the galaxies. At the same time, we report a correlation between the lag and the galactic stellar mass, central stellar velocity dispersion, and axial ratio of the light distribution. These correlations suggest a possible higher ratio of infalling-to-local gas in early-type disk galaxies or a connection between lags and the possible presence of hot gaseous halos, which may be more prevalent in more massive galaxies. These results again demonstrate that observations of extraplanar gas can serve as a potential probe for accretion of gas.

Time series regression model for infectious disease and weather.

PubMed

Imai, Chisato; Armstrong, Ben; Chalabi, Zaid; Mangtani, Punam; Hashizume, Masahiro

2015-10-01

Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Association between Daily Hydrogen Sulfide Exposure and Incidence of Emergency Hospital Visits: A Population-Based Study

PubMed Central

Finnbjornsdottir, Ragnhildur Gudrun; Carlsen, Hanne Krage; Thorsteinsson, Throstur; Oudin, Anna; Lund, Sigrun Helga; Gislason, Thorarinn; Rafnsson, Vilhjalmur

2016-01-01

Background The adverse health effects of high concentrations of hydrogen sulfide (H2S) exposure are well known, though the possible effects of low concentrations have not been thoroughly studied. The aim was to study short-term associations between modelled ambient low-level concentrations of intermittent hydrogen sulfide (H2S) and emergency hospital visits with heart diseases (HD), respiratory diseases, and stroke as primary diagnosis. Methods The study is population-based, using data from patient-, and population-registers from the only acute care institution in the Reykjavik capital area, between 1 January, 2007 and 30 June, 2014. The study population was individuals (≥18yr) living in the Reykjavik capital area. The H2S emission originates from a geothermal power plant in the vicinity. A model was used to estimate H2S exposure in different sections of the area. A generalized linear model assuming Poisson distribution was used to investigate the association between emergency hospital visits and H2S exposure. Distributed lag models were adjusted for seasonality, gender, age, traffic zones, and other relevant factors. Lag days from 0 to 4 were considered. Results The total number of emergency hospital visits was 32961 with a mean age of 70 years. In fully adjusted un-stratified models, H2S concentrations exceeding 7.00μg/m3 were associated with increases in emergency hospital visits with HD as primary diagnosis at lag 0 risk ratio (RR): 1.067; 95% confidence interval (CI): 1.024–1.111, lag 2 RR: 1.049; 95%CI: 1.005–1.095, and lag 4 RR: 1.046; 95%CI: 1.004–1.089. Among males an association was found between H2S concentrations exceeding 7.00μg/m3, and HD at lag 0 RR: 1.087; 95%CI: 1.032–1.146 and lag 4 RR: 1080; 95%CI: 1.025–1.138; and among those 73 years and older at lag 0 RR: 1.075; 95%CI: 1.014–1.140 and lag 3 RR: 1.072; 95%CI: 1.009–1.139. No associations were found with other diseases. Conclusions The study showed an association between emergency hospital visits with HD as primary diagnosis and same day H2S concentrations exceeding 7.00μg/m3, more pronounced among males and those 73 years and older than among females and younger individuals. PMID:27218467

Accounting for inherent variability of growth in microbial risk assessment.

PubMed

Marks, H M; Coleman, M E

2005-04-15

Risk assessments of pathogens need to account for the growth of small number of cells under varying conditions. In order to determine the possible risks that occur when there are small numbers of cells, stochastic models of growth are needed that would capture the distribution of the number of cells over replicate trials of the same scenario or environmental conditions. This paper provides a simple stochastic growth model, accounting only for inherent cell-growth variability, assuming constant growth kinetic parameters, for an initial, small, numbers of cells assumed to be transforming from a stationary to an exponential phase. Two, basic, microbial sets of assumptions are considered: serial, where it is assume that cells transform through a lag phase before entering the exponential phase of growth; and parallel, where it is assumed that lag and exponential phases develop in parallel. The model is based on, first determining the distribution of the time when growth commences, and then modelling the conditional distribution of the number of cells. For the latter distribution, it is found that a Weibull distribution provides a simple approximation to the conditional distribution of the relative growth, so that the model developed in this paper can be easily implemented in risk assessments using commercial software packages.

New scaling model for variables and increments with heavy-tailed distributions

NASA Astrophysics Data System (ADS)

Riva, Monica; Neuman, Shlomo P.; Guadagnini, Alberto

2015-06-01

Many hydrological (as well as diverse earth, environmental, ecological, biological, physical, social, financial and other) variables, Y, exhibit frequency distributions that are difficult to reconcile with those of their spatial or temporal increments, ΔY. Whereas distributions of Y (or its logarithm) are at times slightly asymmetric with relatively mild peaks and tails, those of ΔY tend to be symmetric with peaks that grow sharper, and tails that become heavier, as the separation distance (lag) between pairs of Y values decreases. No statistical model known to us captures these behaviors of Y and ΔY in a unified and consistent manner. We propose a new, generalized sub-Gaussian model that does so. We derive analytical expressions for probability distribution functions (pdfs) of Y and ΔY as well as corresponding lead statistical moments. In our model the peak and tails of the ΔY pdf scale with lag in line with observed behavior. The model allows one to estimate, accurately and efficiently, all relevant parameters by analyzing jointly sample moments of Y and ΔY. We illustrate key features of our new model and method of inference on synthetically generated samples and neutron porosity data from a deep borehole.

Improvement of Reynolds-Stress and Triple-Product Lag Models

NASA Technical Reports Server (NTRS)

Olsen, Michael E.; Lillard, Randolph P.

2017-01-01

The Reynolds-stress and triple product Lag models were created with a normal stress distribution which was denied by a 4:3:2 distribution of streamwise, spanwise and wall normal stresses, and a ratio of r(sub w) = 0.3k in the log layer region of high Reynolds number flat plate flow, which implies R11(+)= [4/(9/2)*.3] approximately 2.96. More recent measurements show a more complex picture of the log layer region at high Reynolds numbers. The first cut at improving these models along with the direction for future refinements is described. Comparison with recent high Reynolds number data shows areas where further work is needed, but also shows inclusion of the modeled turbulent transport terms improve the prediction where they influence the solution. Additional work is needed to make the model better match experiment, but there is significant improvement in many of the details of the log layer behavior.

A FOURIER-TRANSFORMED BREMSSTRAHLUNG FLASH MODEL FOR THE PRODUCTION OF X-RAY TIME LAGS IN ACCRETING BLACK HOLE SOURCES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kroon, John J.; Becker, Peter A., E-mail: jkroon@gmu.edu, E-mail: pbecker@gmu.edu

Accreting black hole sources show a wide variety of rapid time variability, including the manifestation of time lags during X-ray transients, in which a delay (phase shift) is observed between the Fourier components of the hard and soft spectra. Despite a large body of observational evidence for time lags, no fundamental physical explanation for the origin of this phenomenon has been presented. We develop a new theoretical model for the production of X-ray time lags based on an exact analytical solution for the Fourier transform describing the diffusion and Comptonization of seed photons propagating through a spherical corona. The resultingmore » Green's function can be convolved with any source distribution to compute the associated Fourier transform and time lags, hence allowing us to explore a wide variety of injection scenarios. We show that thermal Comptonization is able to self-consistently explain both the X-ray time lags and the steady-state (quiescent) X-ray spectrum observed in the low-hard state of Cyg X-1. The reprocessing of bremsstrahlung seed photons produces X-ray time lags that diminish with increasing Fourier frequency, in agreement with the observations for a wide range of sources.« less

Ambient ozone concentration and emergency department visits for panic attacks.

PubMed

Cho, Jaelim; Choi, Yoon Jung; Sohn, Jungwoo; Suh, Mina; Cho, Seong-Kyung; Ha, Kyoung Hwa; Kim, Changsoo; Shin, Dong Chun

2015-03-01

The effect of ambient air pollution on panic disorder in the general population has not yet been thoroughly elucidated, although the occurrence of panic disorder in workers exposed to organic solvents has been reported previously. We investigated the association of ambient air pollution with the risk of panic attack-related emergency department visits. Using health insurance claims, we collected data from emergency department visits for panic attacks in Seoul, Republic of Korea (2005-2009). Daily air pollutant concentrations were obtained using automatic monitoring system data. We conducted a time-series study using a generalized additive model with Poisson distribution, which included spline variables (date of visit, daily mean temperature, and relative humidity) and parametric variables (daily mean air pollutant concentration, national holiday, and day of the week). In addition to single lag models (lag1 to lag3), cumulative lag models (lag0-1 to lag0-3) were constructed using moving-average concentrations on the days leading up to the visit. The risk was expressed as relative risk (RR) per one standard deviation of each air pollutant and its 95% confidence interval (95% CI). A total of 2320 emergency department visits for panic attacks were observed during the study period. The adjusted RR of panic attack-related emergency department visits was 1.051 (95% CI, 1.014-1.090) for same-day exposure to ozone. In cumulative models, adjusted RRs were 1.068 (1.029-1.107) in lag0-2 and 1.074 (1.035-1.114) in lag0-3. The ambient ozone concentration was significantly associated with emergency department visits for panic attacks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Modelling the association of dengue fever cases with temperature and relative humidity in Jeddah, Saudi Arabia-A generalised linear model with break-point analysis.

PubMed

Alkhaldy, Ibrahim

2017-04-01

The aim of this study was to examine the role of environmental factors in the temporal distribution of dengue fever in Jeddah, Saudi Arabia. The relationship between dengue fever cases and climatic factors such as relative humidity and temperature was investigated during 2006-2009 to determine whether there is any relationship between dengue fever cases and climatic parameters in Jeddah City, Saudi Arabia. A generalised linear model (GLM) with a break-point was used to determine how different levels of temperature and relative humidity affected the distribution of the number of cases of dengue fever. Break-point analysis was performed to modelled the effect before and after a break-point (change point) in the explanatory parameters under various scenarios. Akaike information criterion (AIC) and cross validation (CV) were used to assess the performance of the models. The results showed that maximum temperature and mean relative humidity are most probably the better predictors of the number of dengue fever cases in Jeddah. In this study three scenarios were modelled: no time lag, 1-week lag and 2-weeks lag. Among these scenarios, the 1-week lag model using mean relative humidity as an explanatory variable showed better performance. This study showed a clear relationship between the meteorological variables and the number of dengue fever cases in Jeddah. The results also demonstrated that meteorological variables can be successfully used to estimate the number of dengue fever cases for a given period of time. Break-point analysis provides further insight into the association between meteorological parameters and dengue fever cases by dividing the meteorological parameters into certain break-points. Copyright © 2016 Elsevier B.V. All rights reserved.

AN INTEGRATED MODEL FOR THE PRODUCTION OF X-RAY TIME LAGS AND QUIESCENT SPECTRA FROM HOMOGENEOUS AND INHOMOGENEOUS BLACK HOLE ACCRETION CORONAE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kroon, John J.; Becker, Peter A., E-mail: jkroon@gmu.edu, E-mail: pbecker@gmu.edu

2016-04-20

Many accreting black holes manifest time lags during outbursts, in which the hard Fourier component typically lags behind the soft component. Despite decades of observations of this phenomenon, the underlying physical explanation for the time lags has remained elusive, although there are suggestions that Compton reverberation plays an important role. However, the lack of analytical solutions has hindered the interpretation of the available data. In this paper, we investigate the generation of X-ray time lags in Compton scattering coronae using a new mathematical approach based on analysis of the Fourier-transformed transport equation. By solving this equation, we obtain the Fouriermore » transform of the radiation Green’s function, which allows us to calculate the exact dependence of the time lags on the Fourier frequency, for both homogeneous and inhomogeneous coronal clouds. We use the new formalism to explore a variety of injection scenarios, including both monochromatic and broadband (bremsstrahlung) seed photon injection. We show that our model can successfully reproduce both the observed time lags and the time-averaged (quiescent) X-ray spectra for Cyg X-1 and GX 339-04, using a single set of coronal parameters for each source. The time lags are the result of impulsive bremsstrahlung injection occurring near the outer edge of the corona, while the time-averaged spectra are the result of continual distributed injection of soft photons throughout the cloud.« less

Flap-Lag-Torsion Stability in Forward Flight

NASA Technical Reports Server (NTRS)

Panda, B.; Chopra, I.

1985-01-01

An aeroelastic stability of three-degree flap-lag-torsion blade in forward flight is examined. Quasisteady aerodynamics with a dynamic inflow model is used. The nonlinear time dependent periodic blade response is calculated using an iterative procedure based on Floquet theory. The periodic perturbation equations are solved for stability using Floquet transition matrix theory as well as constant coefficient approximation in the fixed reference frame. Results are presented for both stiff-inplane and soft-inplane blade configurations. The effects of several parameters on blade stability are examined, including structural coupling, pitch-flap and pitch-lag coupling, torsion stiffness, steady inflow distribution, dynamic inflow, blade response solution and constant coefficient approximation.

Per capita alcohol consumption and suicide mortality in a panel of US states from 1950 to 2002

PubMed Central

Kerr, William C.; Subbaraman, Meenakshi; Ye, Yu

2011-01-01

Introduction and Aims The relationship between per capita alcohol consumption and suicide rates has been found to vary in significance and magnitude across countries. This study utilizes a panel of time-series measures from the US states to estimate the effects of changes in current and lagged alcohol sales on suicide mortality risk. Design and Methods Generalized least squares estimation utilized 53 years of data from 48 US states or state groups to estimate relationships between total and beverage-specific alcohol consumption measures and age-standardized suicide mortality rates in first-differenced semi-logged models. Results An additional liter of ethanol from total alcohol sales was estimated to increase suicide rates by 2.3% in models utilizing a distributed lag specification while no effect was found in models including only current alcohol consumption. A similar result is found for men, while for women both current and distributed lag measures were found to be significantly related to suicide rates with an effect of about 3.2% per liter from current and 5.8% per liter from the lagged measure. Beverage-specific models indicate that spirits is most closely linked with suicide risk for women while beer and wine are for men. Unemployment rates are consistently positively related to suicide rates. Discussion and Conclusions Results suggest that chronic effects, potentially related to alcohol abuse and dependence, are the main source of alcohol’s impact on suicide rates in the US for men and are responsible for about half of the effect for women. PMID:21896069

INVASIVE SPECIES: PREDICTING GEOGRAPHIC DISTRIBUTIONS USING ECOLOGICAL NICHE MODELING

EPA Science Inventory

Present approaches to species invasions are reactive in nature. This scenario results in management that perpetually lags behind the most recent invasion and makes control much more difficult. In contrast, spatially explicit ecological niche modeling provides an effective solut...

Emergence of the interplay between hierarchy and contact splitting in biological adhesion highlighted through a hierarchical shear lag model.

PubMed

Brely, Lucas; Bosia, Federico; Pugno, Nicola M

2018-06-20

Contact unit size reduction is a widely studied mechanism as a means to improve adhesion in natural fibrillar systems, such as those observed in beetles or geckos. However, these animals also display complex structural features in the way the contact is subdivided in a hierarchical manner. Here, we study the influence of hierarchical fibrillar architectures on the load distribution over the contact elements of the adhesive system, and the corresponding delamination behaviour. We present an analytical model to derive the load distribution in a fibrillar system loaded in shear, including hierarchical splitting of contacts, i.e. a "hierarchical shear-lag" model that generalizes the well-known shear-lag model used in mechanics. The influence on the detachment process is investigated introducing a numerical procedure that allows the derivation of the maximum delamination force as a function of the considered geometry, including statistical variability of local adhesive energy. Our study suggests that contact splitting generates improved adhesion only in the ideal case of extremely compliant contacts. In real cases, to produce efficient adhesive performance, contact splitting needs to be coupled with hierarchical architectures to counterbalance high load concentrations resulting from contact unit size reduction, generating multiple delamination fronts and helping to avoid detrimental non-uniform load distributions. We show that these results can be summarized in a generalized adhesion scaling scheme for hierarchical structures, proving the beneficial effect of multiple hierarchical levels. The model can thus be used to predict the adhesive performance of hierarchical adhesive structures, as well as the mechanical behaviour of composite materials with hierarchical reinforcements.

Characterizing the relationship between temperature and mortality in tropical and subtropical cities: a distributed lag non-linear model analysis in Hue, Viet Nam, 2009-2013.

PubMed

Dang, Tran Ngoc; Seposo, Xerxes T; Duc, Nguyen Huu Chau; Thang, Tran Binh; An, Do Dang; Hang, Lai Thi Minh; Long, Tran Thanh; Loan, Bui Thi Hong; Honda, Yasushi

2016-01-01

The relationship between temperature and mortality has been found to be U-, V-, or J-shaped in developed temperate countries; however, in developing tropical/subtropical cities, it remains unclear. Our goal was to investigate the relationship between temperature and mortality in Hue, a subtropical city in Viet Nam. We collected daily mortality data from the Vietnamese A6 mortality reporting system for 6,214 deceased persons between 2009 and 2013. A distributed lag non-linear model was used to examine the temperature effects on all-cause and cause-specific mortality by assuming negative binomial distribution for count data. We developed an objective-oriented model selection with four steps following the Akaike information criterion (AIC) rule (i.e. a smaller AIC value indicates a better model). High temperature-related mortality was more strongly associated with short lags, whereas low temperature-related mortality was more strongly associated with long lags. The low temperatures increased risk in all-category mortality compared to high temperatures. We observed elevated temperature-mortality risk in vulnerable groups: elderly people (high temperature effect, relative risk [RR]=1.42, 95% confidence interval [CI]=1.11-1.83; low temperature effect, RR=2.0, 95% CI=1.13-3.52), females (low temperature effect, RR=2.19, 95% CI=1.14-4.21), people with respiratory disease (high temperature effect, RR=2.45, 95% CI=0.91-6.63), and those with cardiovascular disease (high temperature effect, RR=1.6, 95% CI=1.15-2.22; low temperature effect, RR=1.99, 95% CI=0.92-4.28). In Hue, the temperature significantly increased the risk of mortality, especially in vulnerable groups (i.e. elderly, female, people with respiratory and cardiovascular diseases). These findings may provide a foundation for developing adequate policies to address the effects of temperature on health in Hue City.

Characterizing the relationship between temperature and mortality in tropical and subtropical cities: a distributed lag non-linear model analysis in Hue, Viet Nam, 2009–2013

PubMed Central

Dang, Tran Ngoc; Seposo, Xerxes T.; Duc, Nguyen Huu Chau; Thang, Tran Binh; An, Do Dang; Hang, Lai Thi Minh; Long, Tran Thanh; Loan, Bui Thi Hong; Honda, Yasushi

2016-01-01

Background The relationship between temperature and mortality has been found to be U-, V-, or J-shaped in developed temperate countries; however, in developing tropical/subtropical cities, it remains unclear. Objectives Our goal was to investigate the relationship between temperature and mortality in Hue, a subtropical city in Viet Nam. Design We collected daily mortality data from the Vietnamese A6 mortality reporting system for 6,214 deceased persons between 2009 and 2013. A distributed lag non-linear model was used to examine the temperature effects on all-cause and cause-specific mortality by assuming negative binomial distribution for count data. We developed an objective-oriented model selection with four steps following the Akaike information criterion (AIC) rule (i.e. a smaller AIC value indicates a better model). Results High temperature-related mortality was more strongly associated with short lags, whereas low temperature-related mortality was more strongly associated with long lags. The low temperatures increased risk in all-category mortality compared to high temperatures. We observed elevated temperature-mortality risk in vulnerable groups: elderly people (high temperature effect, relative risk [RR]=1.42, 95% confidence interval [CI]=1.11–1.83; low temperature effect, RR=2.0, 95% CI=1.13–3.52), females (low temperature effect, RR=2.19, 95% CI=1.14–4.21), people with respiratory disease (high temperature effect, RR=2.45, 95% CI=0.91–6.63), and those with cardiovascular disease (high temperature effect, RR=1.6, 95% CI=1.15–2.22; low temperature effect, RR=1.99, 95% CI=0.92–4.28). Conclusions In Hue, the temperature significantly increased the risk of mortality, especially in vulnerable groups (i.e. elderly, female, people with respiratory and cardiovascular diseases). These findings may provide a foundation for developing adequate policies to address the effects of temperature on health in Hue City. PMID:26781954

Temporal and micro-spatial heterogeneity in the distribution of Anopheles vectors of malaria along the Kenyan coast

PubMed Central

2013-01-01

Background The distribution of anopheline mosquitoes is determined by temporally dynamic environmental and human-associated variables, operating over a range of spatial scales. Macro-spatial short-term trends are driven predominantly by prior (lagged) seasonal changes in climate, which regulate the abundance of suitable aquatic larval habitats. Micro-spatial distribution is determined by the location of these habitats, proximity and abundance of available human bloodmeals and prevailing micro-climatic conditions. The challenge of analysing—in a single coherent statistical framework—the lagged and distributed effect of seasonal climate changes simultaneously with the effects of an underlying hierarchy of spatial factors has hitherto not been addressed. Methods Data on Anopheles gambiae sensu stricto and A. funestus collected from households in Kilifi district, Kenya, were analysed using polynomial distributed lag generalized linear mixed models (PDL GLMMs). Results Anopheline density was positively and significantly associated with amount of rainfall between 4 to 47 days, negatively and significantly associated with maximum daily temperature between 5 and 35 days, and positively and significantly associated with maximum daily temperature between 29 and 48 days in the past (depending on Anopheles species). Multiple-occupancy households harboured greater mosquito numbers than single-occupancy households. A significant degree of mosquito clustering within households was identified. Conclusions The PDL GLMMs developed here represent a generalizable framework for analysing hierarchically-structured data in combination with explanatory variables which elicit lagged effects. The framework is a valuable tool for facilitating detailed understanding of determinants of the spatio-temporal distribution of Anopheles. Such understanding facilitates delivery of targeted, cost-effective and, in certain circumstances, preventative antivectorial interventions against malaria. PMID:24330615

Extending the Distributed Lag Model framework to handle chemical mixtures.

PubMed

Bello, Ghalib A; Arora, Manish; Austin, Christine; Horton, Megan K; Wright, Robert O; Gennings, Chris

2017-07-01

Distributed Lag Models (DLMs) are used in environmental health studies to analyze the time-delayed effect of an exposure on an outcome of interest. Given the increasing need for analytical tools for evaluation of the effects of exposure to multi-pollutant mixtures, this study attempts to extend the classical DLM framework to accommodate and evaluate multiple longitudinally observed exposures. We introduce 2 techniques for quantifying the time-varying mixture effect of multiple exposures on an outcome of interest. Lagged WQS, the first technique, is based on Weighted Quantile Sum (WQS) regression, a penalized regression method that estimates mixture effects using a weighted index. We also introduce Tree-based DLMs, a nonparametric alternative for assessment of lagged mixture effects. This technique is based on the Random Forest (RF) algorithm, a nonparametric, tree-based estimation technique that has shown excellent performance in a wide variety of domains. In a simulation study, we tested the feasibility of these techniques and evaluated their performance in comparison to standard methodology. Both methods exhibited relatively robust performance, accurately capturing pre-defined non-linear functional relationships in different simulation settings. Further, we applied these techniques to data on perinatal exposure to environmental metal toxicants, with the goal of evaluating the effects of exposure on neurodevelopment. Our methods identified critical neurodevelopmental windows showing significant sensitivity to metal mixtures. Copyright © 2017 Elsevier Inc. All rights reserved.

Performance of fuzzy approach in Malaysia short-term electricity load forecasting

NASA Astrophysics Data System (ADS)

Mansor, Rosnalini; Zulkifli, Malina; Yusof, Muhammad Mat; Ismail, Mohd Isfahani; Ismail, Suzilah; Yin, Yip Chee

2014-12-01

Many activities such as economic, education and manafucturing would paralyse with limited supply of electricity but surplus contribute to high operating cost. Therefore electricity load forecasting is important in order to avoid shortage or excess. Previous finding showed festive celebration has effect on short-term electricity load forecasting. Being a multi culture country Malaysia has many major festive celebrations such as Eidul Fitri, Chinese New Year and Deepavali but they are moving holidays due to non-fixed dates on the Gregorian calendar. This study emphasis on the performance of fuzzy approach in forecasting electricity load when considering the presence of moving holidays. Autoregressive Distributed Lag model was estimated using simulated data by including model simplification concept (manual or automatic), day types (weekdays or weekend), public holidays and lags of electricity load. The result indicated that day types, public holidays and several lags of electricity load were significant in the model. Overall, model simplification improves fuzzy performance due to less variables and rules.

Wavelet-based functional linear mixed models: an application to measurement error-corrected distributed lag models.

PubMed

Malloy, Elizabeth J; Morris, Jeffrey S; Adar, Sara D; Suh, Helen; Gold, Diane R; Coull, Brent A

2010-07-01

Frequently, exposure data are measured over time on a grid of discrete values that collectively define a functional observation. In many applications, researchers are interested in using these measurements as covariates to predict a scalar response in a regression setting, with interest focusing on the most biologically relevant time window of exposure. One example is in panel studies of the health effects of particulate matter (PM), where particle levels are measured over time. In such studies, there are many more values of the functional data than observations in the data set so that regularization of the corresponding functional regression coefficient is necessary for estimation. Additional issues in this setting are the possibility of exposure measurement error and the need to incorporate additional potential confounders, such as meteorological or co-pollutant measures, that themselves may have effects that vary over time. To accommodate all these features, we develop wavelet-based linear mixed distributed lag models that incorporate repeated measures of functional data as covariates into a linear mixed model. A Bayesian approach to model fitting uses wavelet shrinkage to regularize functional coefficients. We show that, as long as the exposure error induces fine-scale variability in the functional exposure profile and the distributed lag function representing the exposure effect varies smoothly in time, the model corrects for the exposure measurement error without further adjustment. Both these conditions are likely to hold in the environmental applications we consider. We examine properties of the method using simulations and apply the method to data from a study examining the association between PM, measured as hourly averages for 1-7 days, and markers of acute systemic inflammation. We use the method to fully control for the effects of confounding by other time-varying predictors, such as temperature and co-pollutants.

Forecasting vegetation greenness with satellite and climate data

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2004-01-01

A new and unique vegetation greenness forecast (VGF) model was designed to predict future vegetation conditions to three months through the use of current and historical climate data and satellite imagery. The VGF model is implemented through a seasonality-adjusted autoregressive distributed-lag function, based on our finding that the normalized difference vegetation index is highly correlated with lagged precipitation and temperature. Accurate forecasts were obtained from the VGF model in Nebraska grassland and cropland. The regression R2 values range from 0.97-0.80 for 2-12 week forecasts, with higher R2 associated with a shorter prediction. An important application would be to produce real-time forecasts of greenness images.

Comparison of the Lag Screw Placements for the Treatment of Stable and Unstable Intertrochanteric Femoral Fractures regarding Trabecular Bone Failure.

PubMed

Celik, Talip; Mutlu, Ibrahim; Ozkan, Arif; Kisioglu, Yasin

2016-01-01

Background. In this study, the cut-out risk of Dynamic Hip Screw (DHS) was investigated in nine different positions of the lag screw for two fracture types by using Finite Element Analysis (FEA). Methods. Two types of fractures (31-A1.1 and A2.1 in AO classification) were generated in the femur model obtained from Computerized Tomography images. The DHS model was placed into the fractured femur model in nine different positions. Tip-Apex Distances were measured using SolidWorks. In FEA, the force applied to the femoral head was determined according to the maximum value being observed during walking. Results. The highest volume percentage exceeding the yield strength of trabecular bone was obtained in posterior-inferior region in both fracture types. The best placement region for the lag screw was found in the middle of both fracture types. There are compatible results between Tip-Apex Distances and the cut-out risk except for posterior-superior and superior region of 31-A2.1 fracture type. Conclusion. The position of the lag screw affects the risk of cut-out significantly. Also, Tip-Apex Distance is a good predictor of the cut-out risk. All in all, we can supposedly say that the density distribution of the trabecular bone is a more efficient factor compared to the positions of lag screw in the cut-out risk.

The relationship between carbon dioxide and agriculture in Ghana: a comparison of VECM and ARDL model.

PubMed

Asumadu-Sarkodie, Samuel; Owusu, Phebe Asantewaa

2016-06-01

In this paper, the relationship between carbon dioxide and agriculture in Ghana was investigated by comparing a Vector Error Correction Model (VECM) and Autoregressive Distributed Lag (ARDL) Model. Ten study variables spanning from 1961 to 2012 were employed from the Food Agricultural Organization. Results from the study show that carbon dioxide emissions affect the percentage annual change of agricultural area, coarse grain production, cocoa bean production, fruit production, vegetable production, and the total livestock per hectare of the agricultural area. The vector error correction model and the autoregressive distributed lag model show evidence of a causal relationship between carbon dioxide emissions and agriculture; however, the relationship decreases periodically which may die over-time. All the endogenous variables except total primary vegetable production lead to carbon dioxide emissions, which may be due to poor agricultural practices to meet the growing food demand in Ghana. The autoregressive distributed lag bounds test shows evidence of a long-run equilibrium relationship between the percentage annual change of agricultural area, cocoa bean production, total livestock per hectare of agricultural area, total pulses production, total primary vegetable production, and carbon dioxide emissions. It is important to end hunger and ensure people have access to safe and nutritious food, especially the poor, orphans, pregnant women, and children under-5 years in order to reduce maternal and infant mortalities. Nevertheless, it is also important that the Government of Ghana institutes agricultural policies that focus on promoting a sustainable agriculture using environmental friendly agricultural practices. The study recommends an integration of climate change measures into Ghana's national strategies, policies and planning in order to strengthen the country's effort to achieving a sustainable environment.

Effect of heat shock and recovery temperature on variability of single cell lag time of Cronobacter turicensis.

PubMed

Xu, Y Zh; Métris, A; Stasinopoulos, D M; Forsythe, S J; Sutherland, J P

2015-02-01

The effect of heat stress and subsequent recovery temperature on the individual cellular lag of Cronobacter turicensis was analysed using optical density measurements. Low numbers of cells were obtained through serial dilution and the time to reach an optical density of 0.035 was determined. Assuming the lag of a single cell follows a shifted Gamma distribution with a fixed shape parameter, the effect of recovery temperature on the individual lag of untreated and sublethally heat treated cells of Cr. turicensis were modelled. It was found that the shift parameter (Tshift) increased asymptotically as the temperature decreased while the logarithm of the scale parameter (θ) decreased linearly with recovery temperature. To test the validity of the model in food, growth of low numbers of untreated and heat treated Cr. turicensis in artificially contaminated infant first milk was measured experimentally and compared with predictions obtained by Monte Carlo simulations. Although the model for untreated cells slightly underestimated the actual growth in first milk at low temperatures, the model for heat treated cells was in agreement with the data derived from the challenge tests and provides a basis for reliable quantitative microbiological risk assessments for Cronobacter spp. in infant milk. Copyright © 2014 Elsevier Ltd. All rights reserved.

Catchment Legacies and Time Lags: A Parsimonious Watershed Model to Predict the Effects of Legacy Storage on Nitrogen Export

PubMed Central

Van Meter, Kimberly J.; Basu, Nandita B.

2015-01-01

Nutrient legacies in anthropogenic landscapes, accumulated over decades of fertilizer application, lead to time lags between implementation of conservation measures and improvements in water quality. Quantification of such time lags has remained difficult, however, due to an incomplete understanding of controls on nutrient depletion trajectories after changes in land-use or management practices. In this study, we have developed a parsimonious watershed model for quantifying catchment-scale time lags based on both soil nutrient accumulations (biogeochemical legacy) and groundwater travel time distributions (hydrologic legacy). The model accurately predicted the time lags observed in an Iowa watershed that had undergone a 41% conversion of area from row crop to native prairie. We explored the time scales of change for stream nutrient concentrations as a function of both natural and anthropogenic controls, from topography to spatial patterns of land-use change. Our results demonstrate that the existence of biogeochemical nutrient legacies increases time lags beyond those due to hydrologic legacy alone. In addition, we show that the maximum concentration reduction benefits vary according to the spatial pattern of intervention, with preferential conversion of land parcels having the shortest catchment-scale travel times providing proportionally greater concentration reductions as well as faster response times. In contrast, a random pattern of conversion results in a 1:1 relationship between percent land conversion and percent concentration reduction, irrespective of denitrification rates within the landscape. Our modeling framework allows for the quantification of tradeoffs between costs associated with implementation of conservation measures and the time needed to see the desired concentration reductions, making it of great value to decision makers regarding optimal implementation of watershed conservation measures. PMID:25985290

Catchment legacies and time lags: a parsimonious watershed model to predict the effects of legacy storage on nitrogen export.

PubMed

Van Meter, Kimberly J; Basu, Nandita B

2015-01-01

Nutrient legacies in anthropogenic landscapes, accumulated over decades of fertilizer application, lead to time lags between implementation of conservation measures and improvements in water quality. Quantification of such time lags has remained difficult, however, due to an incomplete understanding of controls on nutrient depletion trajectories after changes in land-use or management practices. In this study, we have developed a parsimonious watershed model for quantifying catchment-scale time lags based on both soil nutrient accumulations (biogeochemical legacy) and groundwater travel time distributions (hydrologic legacy). The model accurately predicted the time lags observed in an Iowa watershed that had undergone a 41% conversion of area from row crop to native prairie. We explored the time scales of change for stream nutrient concentrations as a function of both natural and anthropogenic controls, from topography to spatial patterns of land-use change. Our results demonstrate that the existence of biogeochemical nutrient legacies increases time lags beyond those due to hydrologic legacy alone. In addition, we show that the maximum concentration reduction benefits vary according to the spatial pattern of intervention, with preferential conversion of land parcels having the shortest catchment-scale travel times providing proportionally greater concentration reductions as well as faster response times. In contrast, a random pattern of conversion results in a 1:1 relationship between percent land conversion and percent concentration reduction, irrespective of denitrification rates within the landscape. Our modeling framework allows for the quantification of tradeoffs between costs associated with implementation of conservation measures and the time needed to see the desired concentration reductions, making it of great value to decision makers regarding optimal implementation of watershed conservation measures.

Theory for Transitions Between Exponential and Stationary Phases: Universal Laws for Lag Time

NASA Astrophysics Data System (ADS)

Himeoka, Yusuke; Kaneko, Kunihiko

2017-04-01

The quantitative characterization of bacterial growth has attracted substantial attention since Monod's pioneering study. Theoretical and experimental works have uncovered several laws for describing the exponential growth phase, in which the number of cells grows exponentially. However, microorganism growth also exhibits lag, stationary, and death phases under starvation conditions, in which cell growth is highly suppressed, for which quantitative laws or theories are markedly underdeveloped. In fact, the models commonly adopted for the exponential phase that consist of autocatalytic chemical components, including ribosomes, can only show exponential growth or decay in a population; thus, phases that halt growth are not realized. Here, we propose a simple, coarse-grained cell model that includes an extra class of macromolecular components in addition to the autocatalytic active components that facilitate cellular growth. These extra components form a complex with the active components to inhibit the catalytic process. Depending on the nutrient condition, the model exhibits typical transitions among the lag, exponential, stationary, and death phases. Furthermore, the lag time needed for growth recovery after starvation follows the square root of the starvation time and is inversely related to the maximal growth rate. This is in agreement with experimental observations, in which the length of time of cell starvation is memorized in the slow accumulation of molecules. Moreover, the lag time distributed among cells is skewed with a long time tail. If the starvation time is longer, an exponential tail appears, which is also consistent with experimental data. Our theory further predicts a strong dependence of lag time on the speed of substrate depletion, which can be tested experimentally. The present model and theoretical analysis provide universal growth laws beyond the exponential phase, offering insight into how cells halt growth without entering the death phase.

Supersonic Pitch Damping Predictions of Blunt Entry Vehicles from Static CFD Solutions

NASA Technical Reports Server (NTRS)

Schoenenberger, Mark

2013-01-01

A technique for predicting supersonic pitch damping of blunt axisymmetric bodies from static CFD data is presented. The contributions to static pitching moment due to forebody and aftbody pressure distributions are broken out and considered separately. The one-dimension moment equation is cast to model the separate contributions from forebody and aftbody pressures with no traditional damping term included. The aftbody contribution to pitching moment is lagged by a phase angle of the natural oscillation period. This lag represents the time for aftbody wake structures to equilibrate while the body is oscillation. The characteristic equation of this formulation indicates that the lagged backshell moment adds a damping moment equivalent in form to a constant pitch damping term. CFD calculations of the backshell's contribution to the static pitching moment for a range of angles-of-attack is used to predict pitch damping coefficients. These predictions are compared with ballistic range data taken of the Mars Exploration Rover (MER) capsule and forced oscillation data of the Mars Viking capsule. The lag model appears to capture dynamic stability variation due to backshell geometry as well as Mach number.

Improving models of democracy: the example of lagged effects of economic development, education, and gender equality.

PubMed

Balaev, Mikhail

2014-07-01

The author examines how time delayed effects of economic development, education, and gender equality influence political democracy. Literature review shows inadequate understanding of lagged effects, which raises methodological and theoretical issues with the current quantitative studies of democracy. Using country-years as a unit of analysis, the author estimates a series of OLS PCSE models for each predictor with a systematic analysis of the distributions of the lagged effects. The second set of multiple OLS PCSE regressions are estimated including all three independent variables. The results show that economic development, education, and gender have three unique trajectories of the time-delayed effects: Economic development has long-term effects, education produces continuous effects regardless of the timing, and gender equality has the most prominent immediate and short term effects. The results call for the reassessment of model specifications and theoretical setups in the quantitative studies of democracy. Copyright © 2014 Elsevier Inc. All rights reserved.

Association with meteo-climatological factors and daily emergency visits for renal colic and urinary calculi in Cuneo, Italy. A retrospective observational study, 2007-2010

NASA Astrophysics Data System (ADS)

Condemi, Vincenzo; Gestro, Massimo; Dozio, Elena; Tartaglino, Bruno; Corsi Romanelli, Massimiliano Marco; Solimene, Umberto; Meco, Roberto

2015-03-01

The incidence of nephrolithiasis is rising worldwide, especially in women and with increasing age. Incidence and prevalence of kidney stones are affected by genetic, nutritional, and environmental factors. The aim of this study is to investigate the link between various meteorological factors (independent variables) and the daily number of visits to the Emergency Department (ED of the S. Croce and Carle Hospital of Cuneo for renal colic (RC) and urinary stones (UC) as the dependent variable over the years 2007-2010. The Poisson generalized regression models (PGAMs) have been used in different progressive ways. The results of PGAMs (stage 1) adjusted for seasonal and calendar factors confirmed a significant correlation ( p < 0.03) with the thermal parameter. Evaluation of the dose-response effect [PGAMs combined with distributed lags nonlinear models (DLNMs)—stage 2], expressed in terms of relative risk (RR) and cumulative relative risk (RRC), indicated a relative significant effect up to 15 lag days of lag (RR > 1), with a first peak after 5 days (lag ranges 0-1, 0-3, and 0-5) and a second weak peak observed along the 5-15 lag range days. The estimated RR for females was significant, mainly in the second and fourth age group considered (19-44 and >65 years): RR for total ED visits 1.27, confidence interval (CI) 1.11-1.46 (lag 0-5 days); RR 1.42, CI 1.01-2.01 (lag 0-10 days); and RR 1.35, CI 1.09-1.68 (lag 0-15 days). The research also indicated a moderate involvement of the thermal factor in the onset of RC caused by UC, exclusively in the female sex. Further studies will be necessary to confirm these results.

Remotely Sensed Environmental Conditions and Malaria Mortality in Three Malaria Endemic Regions in Western Kenya.

PubMed

Sewe, Maquins Odhiambo; Ahlm, Clas; Rocklöv, Joacim

2016-01-01

Malaria is an important cause of morbidity and mortality in malaria endemic countries. The malaria mosquito vectors depend on environmental conditions, such as temperature and rainfall, for reproduction and survival. To investigate the potential for weather driven early warning systems to prevent disease occurrence, the disease relationship to weather conditions need to be carefully investigated. Where meteorological observations are scarce, satellite derived products provide new opportunities to study the disease patterns depending on remotely sensed variables. In this study, we explored the lagged association of Normalized Difference Vegetation Index (NVDI), day Land Surface Temperature (LST) and precipitation on malaria mortality in three areas in Western Kenya. The lagged effect of each environmental variable on weekly malaria mortality was modeled using a Distributed Lag Non Linear Modeling approach. For each variable we constructed a natural spline basis with 3 degrees of freedom for both the lag dimension and the variable. Lag periods up to 12 weeks were considered. The effect of day LST varied between the areas with longer lags. In all the three areas, malaria mortality was associated with precipitation. The risk increased with increasing weekly total precipitation above 20 mm and peaking at 80 mm. The NDVI threshold for increased mortality risk was between 0.3 and 0.4 at shorter lags. This study identified lag patterns and association of remote- sensing environmental factors and malaria mortality in three malaria endemic regions in Western Kenya. Our results show that rainfall has the most consistent predictive pattern to malaria transmission in the endemic study area. Results highlight a potential for development of locally based early warning forecasts that could potentially reduce the disease burden by enabling timely control actions.

Nanoflare vs Footpoint Heating : Observational Signatures

NASA Technical Reports Server (NTRS)

Winebarger, Amy; Alexander, Caroline; Lionello, Roberto; Linker, Jon; Mikic, Zoran; Downs, Cooper

2015-01-01

Time lag analysis shows very long time lags between all channel pairs. Impulsive heating cannot address these long time lags. 3D Simulations of footpoint heating shows a similar pattern of time lags (magnitude and distribution) to observations. Time lags and relative peak intensities may be able to differentiate between TNE and impulsive heating solutions. Adding a high temperature channel (like XRT Be-­thin) may improve diagnostics.

[Influence of humidex on incidence of bacillary dysentery in Hefei: a time-series study].

PubMed

Zhang, H; Zhao, K F; He, R X; Zhao, D S; Xie, M Y; Wang, S S; Bai, L J; Cheng, Q; Zhang, Y W; Su, H

2017-11-10

Objective: To investigate the effect of humidex combined with mean temperature and relative humidity on the incidence of bacillary dysentery in Hefei. Methods: Daily counts of bacillary dysentery cases and weather data in Hefei were collected from January 1, 2006 to December 31, 2013. Then, the humidex was calculated from temperature and relative humidity. A Poisson generalized linear regression combined with distributed lag non-linear model was applied to analyze the relationship between humidex and the incidence of bacillary dysentery, after adjusting for long-term and seasonal trends, day of week and other weather confounders. Stratified analyses by gender, age and address were also conducted. Results: The risk of bacillary dysentery increased with the rise of humidex. The adverse effect of high humidex (90 percentile of humidex) appeared in 2-days lag and it was the largest at 4-days lag ( RR =1.063, 95 %CI : 1.037-1.090). Subgroup analyses indicated that all groups were affected by high humidex at lag 2-5 days. Conclusion: High humidex could significantly increase the risk of bacillary dysentery, and the lagged effects were observed.

Comparison of the Lag Screw Placements for the Treatment of Stable and Unstable Intertrochanteric Femoral Fractures regarding Trabecular Bone Failure

PubMed Central

Mutlu, Ibrahim; Ozkan, Arif; Kisioglu, Yasin

2016-01-01

Background. In this study, the cut-out risk of Dynamic Hip Screw (DHS) was investigated in nine different positions of the lag screw for two fracture types by using Finite Element Analysis (FEA). Methods. Two types of fractures (31-A1.1 and A2.1 in AO classification) were generated in the femur model obtained from Computerized Tomography images. The DHS model was placed into the fractured femur model in nine different positions. Tip-Apex Distances were measured using SolidWorks. In FEA, the force applied to the femoral head was determined according to the maximum value being observed during walking. Results. The highest volume percentage exceeding the yield strength of trabecular bone was obtained in posterior-inferior region in both fracture types. The best placement region for the lag screw was found in the middle of both fracture types. There are compatible results between Tip-Apex Distances and the cut-out risk except for posterior-superior and superior region of 31-A2.1 fracture type. Conclusion. The position of the lag screw affects the risk of cut-out significantly. Also, Tip-Apex Distance is a good predictor of the cut-out risk. All in all, we can supposedly say that the density distribution of the trabecular bone is a more efficient factor compared to the positions of lag screw in the cut-out risk. PMID:27995133

Use DNA to learn from the past: how modern and ancient DNA studies may help reveal the past and predict the future distribution of species

NASA Astrophysics Data System (ADS)

Edwards, M. E.; Alsos, I. G.; Sjögren, P.; Coissac, E.; Gielly, L.; Yoccoz, N.; Føreid, M. K.; Taberlet, P.

2015-12-01

Knowledge of how climate change affected species distribution in the past may help us predict the effect of ongoing environmental changes. We explore how the use of modern (AFLP fingerprinting techniques) and ancient DNA (metabarcoding P6 loop of chloroplast DNA) help to reveal past distribution of vascular plant species, dispersal processes, and effect of species traits. Based on studies of modern DNA combined with species distribution models, we show the dispersal routes and barriers to dispersal throughout the circumarctic/circumboreal region, likely dispersal vectors, the cost of dispersal in term of loss of genetic diversity, and how these relates to species traits, dispersal distance, and size of colonized region. We also estimate the expected future distribution and loss of genetic diversity and show how this relates to life form and adaptations to dispersal. To gain more knowledge on time lags in past range change events, we rely on palaeorecords. Current data on past distribution are limited by the taxonomic and time resolution of macrofossil and pollen records. We show how this may be improved by studying ancient DNA of lake sediments. DNA of lake sediments recorded about half of the flora surrounding the lake. Compared to macrofossil, the taxonomic resolution is similar but the detection rate is considerable improved. By taking into account main determinants of founder effect, dispersal vectors, and dispersal lags, we may improve our ability to forecast effects of climate change, whereas more studies on ancient DNA may provide us with knowledge on distribution time lags.

Prestressing force monitoring method for a box girder through distributed long-gauge FBG sensors

NASA Astrophysics Data System (ADS)

Chen, Shi-Zhi; Wu, Gang; Xing, Tuo; Feng, De-Cheng

2018-01-01

Monitoring prestressing forces is essential for prestressed concrete box girder bridges. However, the current monitoring methods used for prestressing force were not applicable for a box girder neither because of the sensor’s setup being constrained or shear lag effect not being properly considered. Through combining with the previous analysis model of shear lag effect in the box girder, this paper proposed an indirect monitoring method for on-site determination of prestressing force in a concrete box girder utilizing the distributed long-gauge fiber Bragg grating sensor. The performance of this method was initially verified using numerical simulation for three different distribution forms of prestressing tendons. Then, an experiment involving two concrete box girders was conducted to study the feasibility of this method under different prestressing levels preliminarily. The results of both numerical simulation and lab experiment validated this method’s practicability in a box girder.

Analysis of classical Fourier, SPL and DPL heat transfer model in biological tissues in presence of metabolic and external heat source

NASA Astrophysics Data System (ADS)

Kumar, Dinesh; Singh, Surjan; Rai, K. N.

2016-06-01

In this paper, the temperature distribution in a finite biological tissue in presence of metabolic and external heat source when the surface subjected to different type of boundary conditions is studied. Classical Fourier, single-phase-lag (SPL) and dual-phase-lag (DPL) models were developed for bio-heat transfer in biological tissues. The analytical solution obtained for all the three models using Laplace transform technique and results are compared. The effect of the variability of different parameters such as relaxation time, metabolic heat source, spatial heat source, different type boundary conditions on temperature distribution in different type of the tissues like muscle, tumor, fat, dermis and subcutaneous based on three models are analyzed and discussed in detail. The result obtained in three models is compared with experimental observation of Stolwijk and Hardy (Pflug Arch 291:129-162, 1966). It has been observe that the DPL bio-heat transfer model provides better result in comparison of other two models. The value of metabolic and spatial heat source in boundary condition of first, second and third kind for different type of thermal therapies are evaluated.

Statistical properties of Fourier-based time-lag estimates

NASA Astrophysics Data System (ADS)

Epitropakis, A.; Papadakis, I. E.

2016-06-01

Context. The study of X-ray time-lag spectra in active galactic nuclei (AGN) is currently an active research area, since it has the potential to illuminate the physics and geometry of the innermost region (I.e. close to the putative super-massive black hole) in these objects. To obtain reliable information from these studies, the statistical properties of time-lags estimated from data must be known as accurately as possible. Aims: We investigated the statistical properties of Fourier-based time-lag estimates (I.e. based on the cross-periodogram), using evenly sampled time series with no missing points. Our aim is to provide practical "guidelines" on estimating time-lags that are minimally biased (I.e. whose mean is close to their intrinsic value) and have known errors. Methods: Our investigation is based on both analytical work and extensive numerical simulations. The latter consisted of generating artificial time series with various signal-to-noise ratios and sampling patterns/durations similar to those offered by AGN observations with present and past X-ray satellites. We also considered a range of different model time-lag spectra commonly assumed in X-ray analyses of compact accreting systems. Results: Discrete sampling, binning and finite light curve duration cause the mean of the time-lag estimates to have a smaller magnitude than their intrinsic values. Smoothing (I.e. binning over consecutive frequencies) of the cross-periodogram can add extra bias at low frequencies. The use of light curves with low signal-to-noise ratio reduces the intrinsic coherence, and can introduce a bias to the sample coherence, time-lag estimates, and their predicted error. Conclusions: Our results have direct implications for X-ray time-lag studies in AGN, but can also be applied to similar studies in other research fields. We find that: a) time-lags should be estimated at frequencies lower than ≈ 1/2 the Nyquist frequency to minimise the effects of discrete binning of the observed time series; b) smoothing of the cross-periodogram should be avoided, as this may introduce significant bias to the time-lag estimates, which can be taken into account by assuming a model cross-spectrum (and not just a model time-lag spectrum); c) time-lags should be estimated by dividing observed time series into a number, say m, of shorter data segments and averaging the resulting cross-periodograms; d) if the data segments have a duration ≳ 20 ks, the time-lag bias is ≲15% of its intrinsic value for the model cross-spectra and power-spectra considered in this work. This bias should be estimated in practise (by considering possible intrinsic cross-spectra that may be applicable to the time-lag spectra at hand) to assess the reliability of any time-lag analysis; e) the effects of experimental noise can be minimised by only estimating time-lags in the frequency range where the sample coherence is larger than 1.2/(1 + 0.2m). In this range, the amplitude of noise variations caused by measurement errors is smaller than the amplitude of the signal's intrinsic variations. As long as m ≳ 20, time-lags estimated by averaging over individual data segments have analytical error estimates that are within 95% of the true scatter around their mean, and their distribution is similar, albeit not identical, to a Gaussian.

A climate-based prediction model in the high-risk clusters of the Mekong Delta region, Vietnam: towards improving dengue prevention and control.

PubMed

Phung, Dung; Talukder, Mohammad Radwanur Rahman; Rutherford, Shannon; Chu, Cordia

2016-10-01

To develop a prediction score scheme useful for prevention practitioners and authorities to implement dengue preparedness and controls in the Mekong Delta region (MDR). We applied a spatial scan statistic to identify high-risk dengue clusters in the MDR and used generalised linear-distributed lag models to examine climate-dengue associations using dengue case records and meteorological data from 2003 to 2013. The significant predictors were collapsed into categorical scales, and the β-coefficients of predictors were converted to prediction scores. The score scheme was validated for predicting dengue outbreaks using ROC analysis. The north-eastern MDR was identified as the high-risk cluster. A 1 °C increase in temperature at lag 1-4 and 5-8 weeks increased the dengue risk 11% (95% CI, 9-13) and 7% (95% CI, 6-8), respectively. A 1% rise in humidity increased dengue risk 0.9% (95% CI, 0.2-1.4) at lag 1-4 and 0.8% (95% CI, 0.2-1.4) at lag 5-8 weeks. Similarly, a 1-mm increase in rainfall increased dengue risk 0.1% (95% CI, 0.05-0.16) at lag 1-4 and 0.11% (95% CI, 0.07-0.16) at lag 5-8 weeks. The predicted scores performed with high accuracy in diagnosing the dengue outbreaks (96.3%). This study demonstrates the potential usefulness of a dengue prediction score scheme derived from complex statistical models for high-risk dengue clusters. We recommend a further study to examine the possibility of incorporating such a score scheme into the dengue early warning system in similar climate settings. © 2016 John Wiley & Sons Ltd.

A new approach to modeling temperature-related mortality: Non-linear autoregressive models with exogenous input.

PubMed

Lee, Cameron C; Sheridan, Scott C

2018-07-01

Temperature-mortality relationships are nonlinear, time-lagged, and can vary depending on the time of year and geographic location, all of which limits the applicability of simple regression models in describing these associations. This research demonstrates the utility of an alternative method for modeling such complex relationships that has gained recent traction in other environmental fields: nonlinear autoregressive models with exogenous input (NARX models). All-cause mortality data and multiple temperature-based data sets were gathered from 41 different US cities, for the period 1975-2010, and subjected to ensemble NARX modeling. Models generally performed better in larger cities and during the winter season. Across the US, median absolute percentage errors were 10% (ranging from 4% to 15% in various cities), the average improvement in the r-squared over that of a simple persistence model was 17% (6-24%), and the hit rate for modeling spike days in mortality (>80th percentile) was 54% (34-71%). Mortality responded acutely to hot summer days, peaking at 0-2 days of lag before dropping precipitously, and there was an extended mortality response to cold winter days, peaking at 2-4 days of lag and dropping slowly and continuing for multiple weeks. Spring and autumn showed both of the aforementioned temperature-mortality relationships, but generally to a lesser magnitude than what was seen in summer or winter. When compared to distributed lag nonlinear models, NARX model output was nearly identical. These results highlight the applicability of NARX models for use in modeling complex and time-dependent relationships for various applications in epidemiology and environmental sciences. Copyright © 2018 Elsevier Inc. All rights reserved.

How much does the time lag between wildlife field-data collection and LiDAR-data acquisition matter for studies of animal distributions? A case study using bird communities

Treesearch

Kerri T. Vierling; Charles E. Swift; Andrew T. Hudak; Jody C. Vogeler; Lee A. Vierling

2014-01-01

Vegetation structure quantified by light detection and ranging (LiDAR) can improve understanding of wildlife occupancy and species-richness patterns. However, there is often a time lag between the collection of LiDAR data and wildlife data. We investigated whether a time lag between the LiDAR acquisition and field-data acquisition affected mapped wildlife distributions...

Investigation of Spectral Lag and Epeak as Joint Luminosity Indicators in GRBs

NASA Technical Reports Server (NTRS)

White, Nicholas E. (Technical Monitor); Norris, Jay P.

2003-01-01

Models for gamma-ray bursts which invoke jetted, colliding shells would appear to have at least two determinants for luminosity, e.g., observer viewing angle and Lorentz factor, or possibly shell mass. The latter two internal physical parameters may vary from pulse to pulse within a burst, and such variation might be reflected in evolution of observables such as spectral lag and peak in the spectral energy distribution. We analyze bright BATSE bursts using the 16-channel medium energy resolution (MER) data, with time resolutions of 16 and 64 ms, measuring spectral lags and peak energies for significant pulse structures within a burst, identified using a Bayesian block algorithm. We then explore correlations between the measured parameters and total flux for the individual pulse structures.

Using lagged dependence to identify (de)coupled surface and subsurface soil moisture values

NASA Astrophysics Data System (ADS)

Carranza, Coleen D. U.; van der Ploeg, Martine J.; Torfs, Paul J. J. F.

2018-04-01

Recent advances in radar remote sensing popularized the mapping of surface soil moisture at different spatial scales. Surface soil moisture measurements are used in combination with hydrological models to determine subsurface soil moisture values. However, variability of soil moisture across the soil column is important for estimating depth-integrated values, as decoupling between surface and subsurface can occur. In this study, we employ new methods to investigate the occurrence of (de)coupling between surface and subsurface soil moisture. Using time series datasets, lagged dependence was incorporated in assessing (de)coupling with the idea that surface soil moisture conditions will be reflected at the subsurface after a certain delay. The main approach involves the application of a distributed-lag nonlinear model (DLNM) to simultaneously represent both the functional relation and the lag structure in the time series. The results of an exploratory analysis using residuals from a fitted loess function serve as a posteriori information to determine (de)coupled values. Both methods allow for a range of (de)coupled soil moisture values to be quantified. Results provide new insights into the decoupled range as its occurrence among the sites investigated is not limited to dry conditions.

Oscillatory shear rheology measurements and Newtonian modeling of insoluble monolayers

NASA Astrophysics Data System (ADS)

Rasheed, Fayaz; Raghunandan, Aditya; Hirsa, Amir H.; Lopez, Juan M.

2017-04-01

Circular systems are advantageous for interfacial studies since they do not suffer from end effects, but their hydrodynamics is more complicated because their flows are not unidirectional. Here, we analyze the shear rheology of a harmonically driven knife-edge viscometer through experiments and computations based on the Navier-Stokes equations with a Newtonian interface. The measured distribution of phase lag in the surface velocity relative to the knife-edge speed is found to have a good signal-to-noise ratio and provides robust comparisons to the computations. For monomolecular films of stearic acid, the surface shear viscosity deduced from the model was found to be the same whether the film is driven steady or oscillatory, for an order of magnitude range in driving frequencies and amplitudes. Results show that increasing either the amplitude or forcing frequency steepens the phase lag next to the knife edge. In all cases, the phase lag is linearly proportional to the radial distance from the knife edge and scales with surface shear viscosity to the power -1 /2 .

The influence of temperature on mortality and its Lag effect: a study in four Chinese cities with different latitudes.

PubMed

Bao, Junzhe; Wang, Zhenkun; Yu, Chuanhua; Li, Xudong

2016-05-04

Global climate change is one of the most serious environmental issues faced by humanity, and the resultant change in frequency and intensity of heat waves and cold spells could increase mortality. The influence of temperature on human health could be immediate or delayed. Latitude, relative humidity, and air pollution may influence the temperature-mortality relationship. We studied the influence of temperature on mortality and its lag effect in four Chinese cities with a range of latitudes over 2008-2011, adjusting for relative humidity and air pollution. We recorded the city-specific distributions of temperature and mortality by month and adopted a Poisson regression model combined with a distributed lag nonlinear model to investigate the lag effect of temperature on mortality. We found that the coldest months in the study area are December through March and the hottest months are June through September. The ratios of deaths during cold months to hot months were 1.43, 1.54, 1.37 and 1.12 for the cities of Wuhan, Changsha, Guilin and Haikou, respectively. The effects of extremely high temperatures generally persisted for 3 days, whereas the risk of extremely low temperatures could persist for 21 days. Compared with the optimum temperature of each city, at a lag of 21 days, the relative risks (95 % confidence interval) of extreme cold temperatures were 4.78 (3.63, 6.29), 2.38 (1.35, 4.19), 2.62 (1.15, 5.95) and 2.62 (1.44, 4.79) for Wuhan, Changsha, Guilin and Haikou, respectively. The respective risks were 1.35 (1.18, 1.55), 1.19 (0.96, 1.48), 1.22 (0.82, 1.82) and 2.47 (1.61, 3.78) for extreme hot temperatures, at a lag of 3 days. Temperature-mortality relationships vary among cities at different latitudes. Local governments should establish regional prevention and protection measures to more effectively confront and adapt to local climate change. The effects of hot temperatures predominantly occur over the short term, whereas those of cold temperatures can persist for an extended number of days.

Association with meteo-climatological factors and daily emergency visits for renal colic and urinary calculi in Cuneo, Italy. A retrospective observational study, 2007-2010.

PubMed

Condemi, Vincenzo; Gestro, Massimo; Dozio, Elena; Tartaglino, Bruno; Corsi Romanelli, Massimiliano Marco; Solimene, Umberto; Meco, Roberto

2015-03-01

The incidence of nephrolithiasis is rising worldwide, especially in women and with increasing age. Incidence and prevalence of kidney stones are affected by genetic, nutritional, and environmental factors. The aim of this study is to investigate the link between various meteorological factors (independent variables) and the daily number of visits to the Emergency Department (ED of the S. Croce and Carle Hospital of Cuneo for renal colic (RC) and urinary stones (UC) as the dependent variable over the years 2007-2010.The Poisson generalized regression models (PGAMs) have been used in different progressive ways. The results of PGAMs (stage 1) adjusted for seasonal and calendar factors confirmed a significant correlation (p < 0.03) with the thermal parameter. Evaluation of the dose-response effect [PGAMs combined with distributed lags nonlinear models (DLNMs)-stage 2], expressed in terms of relative risk (RR) and cumulative relative risk (RRC), indicated a relative significant effect up to 15 lag days of lag (RR > 1), with a first peak after 5 days (lag ranges 0-1, 0-3, and 0-5) and a second weak peak observed along the 5-15 lag range days. The estimated RR for females was significant, mainly in the second and fourth age group considered (19-44 and >65 years): RR for total ED visits 1.27, confidence interval (CI) 1.11-1.46 (lag 0-5 days); RR 1.42, CI 1.01-2.01 (lag 0-10 days); and RR 1.35, CI 1.09-1.68 (lag 0-15 days). The research also indicated a moderate involvement of the thermal factor in the onset of RC caused by UC, exclusively in the female sex. Further studies will be necessary to confirm these results.

Using Remote Sensing, Weather, and Demographic Data to Create Risk Maps for Zika, Dengue, and Chikungunya in Brazil

NASA Astrophysics Data System (ADS)

Manore, C.; Conrad, J.; Del Valle, S.; Ziemann, A.; Fairchild, G.; Generous, E. N.

2017-12-01

Mosquito-borne diseases such as Zika, dengue, and chikungunya viruses have dynamics coupled to weather, ecology, human infrastructure, socio-economic demographics, and behavior. We use time-varying remote sensing and weather data, along with demographics and ecozones to predict risk through time for Zika, dengue, and chikungunya outbreaks in Brazil. We use distributed lag methods to quantify the lag between outbreaks and weather. Our statistical model indicates that the relationships between the variables are complex, but that quantifying risk is possible with the right data at appropriate spatio-temporal scales.

Sequential data assimilation for a distributed hydrologic model considering different time scale of internal processes

NASA Astrophysics Data System (ADS)

Noh, S.; Tachikawa, Y.; Shiiba, M.; Kim, S.

2011-12-01

Applications of the sequential data assimilation methods have been increasing in hydrology to reduce uncertainty in the model prediction. In a distributed hydrologic model, there are many types of state variables and each variable interacts with each other based on different time scales. However, the framework to deal with the delayed response, which originates from different time scale of hydrologic processes, has not been thoroughly addressed in the hydrologic data assimilation. In this study, we propose the lagged filtering scheme to consider the lagged response of internal states in a distributed hydrologic model using two filtering schemes; particle filtering (PF) and ensemble Kalman filtering (EnKF). The EnKF is one of the widely used sub-optimal filters implementing an efficient computation with limited number of ensemble members, however, still based on Gaussian approximation. PF can be an alternative in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions involved. In case of PF, advanced particle regularization scheme is implemented together to preserve the diversity of the particle system. In case of EnKF, the ensemble square root filter (EnSRF) are implemented. Each filtering method is parallelized and implemented in the high performance computing system. A distributed hydrologic model, the water and energy transfer processes (WEP) model, is applied for the Katsura River catchment, Japan to demonstrate the applicability of proposed approaches. Forecasted results via PF and EnKF are compared and analyzed in terms of the prediction accuracy and the probabilistic adequacy. Discussions are focused on the prospects and limitations of each data assimilation method.

The WS transform for the Kuramoto model with distributed amplitudes, phase lag and time delay

NASA Astrophysics Data System (ADS)

Lohe, M. A.

2017-12-01

We apply the Watanabe-Strogatz (WS) transform to a generalized Kuramoto model with distributed parameters describing the amplitude of oscillation, phase lag, and time delay at each node of the system. The model has global coupling and identical frequencies, but allows for repulsive interactions at arbitrary nodes leading to conformist-contrarian phenomena together with variable amplitude and time-delay effects. We show how to determine the initial values of the WS system for any initial conditions for the Kuramoto system, and investigate the asymptotic behaviour of the WS variables. For the case of zero time delay the possible asymptotic configurations are determined by the sign of a single parameter μ which measures whether or not the attractive nodes dominate the repulsive nodes. If μ>0 the system completely synchronizes from general initial conditions, whereas if μ<0 one of two types of phase-locked synchronization occurs, depending on the initial values, while for μ=0 periodic solutions can occur. For the case of arbitrary non-uniform time delays we derive a stability condition for completely synchronized solutions.

Distributed lags time series analysis versus linear correlation analysis (Pearson's r) in identifying the relationship between antipseudomonal antibiotic consumption and the susceptibility of Pseudomonas aeruginosa isolates in a single Intensive Care Unit of a tertiary hospital.

PubMed

Erdeljić, Viktorija; Francetić, Igor; Bošnjak, Zrinka; Budimir, Ana; Kalenić, Smilja; Bielen, Luka; Makar-Aušperger, Ksenija; Likić, Robert

2011-05-01

The relationship between antibiotic consumption and selection of resistant strains has been studied mainly by employing conventional statistical methods. A time delay in effect must be anticipated and this has rarely been taken into account in previous studies. Therefore, distributed lags time series analysis and simple linear correlation were compared in their ability to evaluate this relationship. Data on monthly antibiotic consumption for ciprofloxacin, piperacillin/tazobactam, carbapenems and cefepime as well as Pseudomonas aeruginosa susceptibility were retrospectively collected for the period April 2006 to July 2007. Using distributed lags analysis, a significant temporal relationship was identified between ciprofloxacin, meropenem and cefepime consumption and the resistance rates of P. aeruginosa isolates to these antibiotics. This effect was lagged for ciprofloxacin and cefepime [1 month (R=0.827, P=0.039) and 2 months (R=0.962, P=0.001), respectively] and was simultaneous for meropenem (lag 0, R=0.876, P=0.002). Furthermore, a significant concomitant effect of meropenem consumption on the appearance of multidrug-resistant P. aeruginosa strains (resistant to three or more representatives of classes of antibiotics) was identified (lag 0, R=0.992, P<0.001). This effect was not delayed and it was therefore identified both by distributed lags analysis and the Pearson's correlation coefficient. Correlation coefficient analysis was not able to identify relationships between antibiotic consumption and bacterial resistance when the effect was delayed. These results indicate that the use of diverse statistical methods can yield significantly different results, thus leading to the introduction of possibly inappropriate infection control measures. Copyright © 2010 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.

Association between flood and the morbidity of bacillary dysentery in Zibo City, China: a symmetric bidirectional case-crossover study

NASA Astrophysics Data System (ADS)

Zhang, Feifei; Ding, Guoyong; Liu, Zhidong; Zhang, Caixia; Jiang, Baofa

2016-12-01

This study examined the relationship between daily morbidity of bacillary dysentery and flood in 2007 in Zibo City, China, using a symmetric bidirectional case-crossover study. Odds ratios (ORs) and 95 % confidence intervals (CIs) on the basis of multivariate model and stratified analysis at different lagged days were calculated to estimate the risk of flood on bacillary dysentery. A total of 902 notified bacillary dysentery cases were identified during the study period. The median of case distribution was 7-year-old and biased to children. Multivariable analysis showed that flood was associated with an increased risk of bacillary dysentery, with the largest OR of 1.849 (95 % CI 1.229-2.780) at 2-day lag. Gender-specific analysis showed that there was a significant association between flood and bacillary dysentery among males only (ORs >1 from lag 1 to lag 5), with the strongest lagged effect at 2-day lag (OR = 2.820, 95 % CI 1.629-4.881), and the result of age-specific indicated that youngsters had a slightly larger risk to develop flood-related bacillary dysentery than older people at one shorter lagged day (OR = 2.000, 95 % CI 1.128-3.546 in youngsters at lag 2; OR = 1.879, 95 % CI 1.069-3.305 in older people at lag 3). Our study has confirmed that there is a positive association between flood and the risk of bacillary dysentery in selected study area. Males and youngsters may be the vulnerable and high-risk populations to develop the flood-related bacillary dysentery. Results from this study will provide recommendations to make available strategies for government to deal with negative health outcomes due to floods.

Association between flood and the morbidity of bacillary dysentery in Zibo City, China: a symmetric bidirectional case-crossover study.

PubMed

Zhang, Feifei; Ding, Guoyong; Liu, Zhidong; Zhang, Caixia; Jiang, Baofa

2016-12-01

This study examined the relationship between daily morbidity of bacillary dysentery and flood in 2007 in Zibo City, China, using a symmetric bidirectional case-crossover study. Odds ratios (ORs) and 95 % confidence intervals (CIs) on the basis of multivariate model and stratified analysis at different lagged days were calculated to estimate the risk of flood on bacillary dysentery. A total of 902 notified bacillary dysentery cases were identified during the study period. The median of case distribution was 7-year-old and biased to children. Multivariable analysis showed that flood was associated with an increased risk of bacillary dysentery, with the largest OR of 1.849 (95 % CI 1.229-2.780) at 2-day lag. Gender-specific analysis showed that there was a significant association between flood and bacillary dysentery among males only (ORs >1 from lag 1 to lag 5), with the strongest lagged effect at 2-day lag (OR = 2.820, 95 % CI 1.629-4.881), and the result of age-specific indicated that youngsters had a slightly larger risk to develop flood-related bacillary dysentery than older people at one shorter lagged day (OR = 2.000, 95 % CI 1.128-3.546 in youngsters at lag 2; OR = 1.879, 95 % CI 1.069-3.305 in older people at lag 3). Our study has confirmed that there is a positive association between flood and the risk of bacillary dysentery in selected study area. Males and youngsters may be the vulnerable and high-risk populations to develop the flood-related bacillary dysentery. Results from this study will provide recommendations to make available strategies for government to deal with negative health outcomes due to floods.

GENERALIZED ADDITIVE DISTRIBUTED LAG MODELS: QUANTIFYING MORTALITY DISPLACEMENT. (R827353C004,R827353C005)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Association between Gastrointestinal Illness and Precipitation in Areas Impacted by Combined Sewer Systems: Utilizing a Distributed Lag Model

EPA Science Inventory

Combined sewer systems collect rainwater runoff, sewage, and industrial wastewater for transit to treatment facilities. With heavy precipitation, volumes can exceed capacity of treatment facilities, and wastewater discharges directly to receiving waters. These combined sewer over...

Fine Particulate air Pollution is Associated with Higher Vulnerability to Atrial Fibrillation—The APACR Study

PubMed Central

Liao, Duanping; Shaffer, Michele L.; He, Fan; Rodriguez-Colon, Sol; Wu, Rongling; Whitsel, Eric A.; Bixler, Edward O.; Cascio, Wayne E.

2011-01-01

The acute effects and the time course of fine particulate pollution (PM2.5) on atrial fibrillation/flutter (AF) predictors, including P-wave duration, PR interval duration, and P-wave complexity, were investigated in a community-dwelling sample of 106 nonsmokers. Individual-level 24-h beat-to-beat electrocardiogram (ECG) data were visually examined. After identifying and removing artifacts and arrhythmic beats, the 30-min averages of the AF predictors were calculated. A personal PM2.5 monitor was used to measure individual-level, real-time PM2.5 exposures during the same 24-h period, and corresponding 30-min average PM2.5 concentration were calculated. Under a linear mixed-effects modeling framework, distributed lag models were used to estimate regression coefficients (βs) associating PM2.5 with AF predictors. Most of the adverse effects on AF predictors occurred within 1.5–2 h after PM2.5 exposure. The multivariable adjusted βs per 10-µg/m3 rise in PM2.5 at lag 1 and lag 2 were significantly associated with P-wave complexity. PM2.5 exposure was also significantly associated with prolonged PR duration at lag 3 and lag 4. Higher PM2.5 was found to be associated with increases in P-wave complexity and PR duration. Maximal effects were observed within 2 h. These findings suggest that PM2.5 adversely affects AF predictors; thus, PM2.5 may be indicative of greater susceptibility to AF. PMID:21480044

A Geostatistical Scaling Approach for the Generation of Non Gaussian Random Variables and Increments

NASA Astrophysics Data System (ADS)

Guadagnini, Alberto; Neuman, Shlomo P.; Riva, Monica; Panzeri, Marco

2016-04-01

We address manifestations of non-Gaussian statistical scaling displayed by many variables, Y, and their (spatial or temporal) increments. Evidence of such behavior includes symmetry of increment distributions at all separation distances (or lags) with sharp peaks and heavy tails which tend to decay asymptotically as lag increases. Variables reported to exhibit such distributions include quantities of direct relevance to hydrogeological sciences, e.g. porosity, log permeability, electrical resistivity, soil and sediment texture, sediment transport rate, rainfall, measured and simulated turbulent fluid velocity, and other. No model known to us captures all of the documented statistical scaling behaviors in a unique and consistent manner. We recently proposed a generalized sub-Gaussian model (GSG) which reconciles within a unique theoretical framework the probability distributions of a target variable and its increments. We presented an algorithm to generate unconditional random realizations of statistically isotropic or anisotropic GSG functions and illustrated it in two dimensions. In this context, we demonstrated the feasibility of estimating all key parameters of a GSG model underlying a single realization of Y by analyzing jointly spatial moments of Y data and corresponding increments. Here, we extend our GSG model to account for noisy measurements of Y at a discrete set of points in space (or time), present an algorithm to generate conditional realizations of corresponding isotropic or anisotropic random field, and explore them on one- and two-dimensional synthetic test cases.

The Measurement of Pressure Through Tubes in Pressure Distribution Tests

NASA Technical Reports Server (NTRS)

Hemke, Paul E

1928-01-01

The tests described in this report were made to determine the error caused by using small tubes to connect orifices on the surface of aircraft to central pressure capsules in making pressure distribution tests. Aluminum tubes of 3/16-inch inside diameter were used to determine this error. Lengths from 20 feet to 226 feet and pressures whose maxima varied from 2 inches to 140 inches of water were used. Single-pressure impulses for which the time of rise of pressure from zero to a maximum varied from 0.25 second to 3 seconds were investigated. The results show that the pressure recorded at the capsule on the far end of the tube lags behind the pressure at the orifice end and experiences also a change in magnitude. For the values used in these tests the time lag and pressure change vary principally with the time of rise of pressure from zero to a maximum and the tube length. Curves are constructed showing the time lag and pressure change. Empirical formulas are also given for computing the time lag. Analysis of pressure distribution tests made on airplanes in flight shows that the recorded pressures are slightly higher than the pressures at the orifice and that the time lag is negligible. The apparent increase in pressure is usually within the experimental error, but in the case of the modern pursuit type of airplane the pressure increase may be 5 per cent. For pressure-distribution tests on airships the analysis shows that the time lag and pressure change may be neglected.

The Disparate Labor Market Impacts of Monetary Policy

ERIC Educational Resources Information Center

Carpenter, Seth B.; Rodgers, William M., III

2004-01-01

Employing two widely used approaches to identify the effects of monetary policy, this paper explores the differential impact of policy on the labor market outcomes of teenagers, minorities, out-of-school youth, and less-skilled individuals. Evidence from recursive vector autoregressions and autoregressive distributed lag models that use…

Getting the tail to wag the dog: Incorporating groundwater transport into catchment solute transport models using rank StorAge Selection (rSAS) functions

NASA Astrophysics Data System (ADS)

Harman, C. J.

2015-12-01

Surface water hydrologic models are increasingly used to analyze the transport of solutes through the landscape, such as nitrate. However, many of these models cannot adequately capture the effect of groundwater flow paths, which can have long travel times and accumulate legacy contaminants, releasing them to streams over decades. If these long lag times are not accounted for, the short-term efficacy of management activities to reduce nitrogen loads may be overestimated. Models that adopt a simple 'well-mixed' assumption, leading to an exponential transit time distribution at steady state, cannot adequately capture the broadly skewed nature of groundwater transit times in typical watersheds. Here I will demonstrate how StorAge Selection functions can be used to capture the long lag times of groundwater in a typical subwatershed-based hydrologic model framework typical of models like SWAT, HSPF, HBV, PRMS and others. These functions can be selected and calibrated to reproduce historical data where available, but can also be fitted to the results of a steady-state groundwater transport model like MODFLOW/MODPATH, allowing those results to directly inform the parameterization of an unsteady surface water model. The long tails of the transit time distribution predicted by the groundwater model can then be completely captured by the surface water model. Examples of this application in the Chesapeake Bay watersheds and elsewhere will be given.

Modeling the growth kinetics of Bacillus cereus as a function of temperature, pH, sodium lactate and sodium chloride concentrations.

PubMed

Olmez, Hülya Kaptan; Aran, Necla

2005-02-01

Mathematical models describing the growth kinetic parameters (lag phase duration and growth rate) of Bacillus cereus as a function of temperature, pH, sodium lactate and sodium chloride concentrations were obtained in this study. In order to get a residual distribution closer to a normal distribution, the natural logarithm of the growth kinetic parameters were used in modeling. For reasons of parsimony, the polynomial models were reduced to contain only the coefficients significant at a level of p

Malaria incidence trends and their association with climatic variables in rural Gwanda, Zimbabwe, 2005-2015.

PubMed

Gunda, Resign; Chimbari, Moses John; Shamu, Shepherd; Sartorius, Benn; Mukaratirwa, Samson

2017-09-30

Malaria is a public health problem in Zimbabwe. Although many studies have indicated that climate change may influence the distribution of malaria, there is paucity of information on its trends and association with climatic variables in Zimbabwe. To address this shortfall, the trends of malaria incidence and its interaction with climatic variables in rural Gwanda, Zimbabwe for the period January 2005 to April 2015 was assessed. Retrospective data analysis of reported cases of malaria in three selected Gwanda district rural wards (Buvuma, Ntalale and Selonga) was carried out. Data on malaria cases was collected from the district health information system and ward clinics while data on precipitation and temperature were obtained from the climate hazards group infrared precipitation with station data (CHIRPS) database and the moderate resolution imaging spectro-radiometer (MODIS) satellite data, respectively. Distributed lag non-linear models (DLNLM) were used to determine the temporal lagged association between monthly malaria incidence and monthly climatic variables. There were 246 confirmed malaria cases in the three wards with a mean incidence of 0.16/1000 population/month. The majority of malaria cases (95%) occurred in the > 5 years age category. The results showed no correlation between trends of clinical malaria (unconfirmed) and confirmed malaria cases in all the three study wards. There was a significant association between malaria incidence and the climatic variables in Buvuma and Selonga wards at specific lag periods. In Ntalale ward, only precipitation (1- and 3-month lag) and mean temperature (1- and 2-month lag) were significantly associated with incidence at specific lag periods (p < 0.05). DLNM results suggest a key risk period in current month, based on key climatic conditions in the 1-4 month period prior. As the period of high malaria risk is associated with precipitation and temperature at 1-4 month prior in a seasonal cycle, intensifying malaria control activities over this period will likely contribute to lowering the seasonal malaria incidence.

Lag threads organize the brain’s intrinsic activity

PubMed Central

Mitra, Anish; Snyder, Abraham Z.; Blazey, Tyler; Raichle, Marcus E.

2015-01-01

It has been widely reported that intrinsic brain activity, in a variety of animals including humans, is spatiotemporally structured. Specifically, propagated slow activity has been repeatedly demonstrated in animals. In human resting-state fMRI, spontaneous activity has been understood predominantly in terms of zero-lag temporal synchrony within widely distributed functional systems (resting-state networks). Here, we use resting-state fMRI from 1,376 normal, young adults to demonstrate that multiple, highly reproducible, temporal sequences of propagated activity, which we term “lag threads,” are present in the brain. Moreover, this propagated activity is largely unidirectional within conventionally understood resting-state networks. Modeling experiments show that resting-state networks naturally emerge as a consequence of shared patterns of propagation. An implication of these results is that common physiologic mechanisms may underlie spontaneous activity as imaged with fMRI in humans and slowly propagated activity as studied in animals. PMID:25825720

Mechanism of asymmetric polymerase assembly at the eukaryotic replication fork

PubMed Central

Georgescu, Roxana E; Langston, Lance; Yao, Nina Y; Yurieva, Olga; Zhang, Dan; Finkelstein, Jeff; Agarwal, Tani; O’Donnell, Mike E

2015-01-01

Eukaryotes use distinct polymerases for leading- and lagging-strand replication, but how they target their respective strands is uncertain. We reconstituted Saccharomyces cerevisiae replication forks and found that CMG helicase selects polymerase (Pol) ε to the exclusion of Pol δ on the leading strand. Even if Pol δ assembles on the leading strand, Pol ε rapidly replaces it. Pol δ–PCNA is distributive with CMG, in contrast to its high stability on primed ssDNA. Hence CMG will not stabilize Pol δ, instead leaving the leading strand accessible for Pol ε and stabilizing Pol ε. Comparison of Pol ε and Pol δ on a lagging-strand model DNA reveals the opposite. Pol δ dominates over excess Pol ε on PCNA-primed ssDNA. Thus, PCNA strongly favors Pol δ over Pol ε on the lagging strand, but CMG over-rides and flips this balance in favor of Pol ε on the leading strand. PMID:24997598

Ambient air pollution, temperature and out-of-hospital coronary deaths in Shanghai, China.

PubMed

Dai, Jinping; Chen, Renjie; Meng, Xia; Yang, Changyuan; Zhao, Zhuohui; Kan, Haidong

2015-08-01

Few studies have evaluated the effects of ambient air pollution and temperature in triggering out-of-hospital coronary deaths (OHCDs) in China. We evaluated the associations of air pollution and temperature with daily OHCDs in Shanghai, China from 2006 to 2011. We applied an over-dispersed generalized additive model and a distributed lag nonlinear model to analyze the effects of air pollution and temperature, respectively. A 10 μg/m(3) increase in the present-day PM10, PM2.5, SO2, NO2 and CO were associated with increases in OHCD mortality of 0.49%, 0.68%, 0.88%, 1.60% and 0.08%, respectively. A 1 °C decrease below the minimum-mortality temperature corresponded to a 3.81% increase in OHCD mortality on lags days 0-21, and a 1 °C increase above minimum-mortality temperature corresponded to a 4.61% increase over lag days 0-3. No effects were found for in-hospital coronary deaths. This analysis suggests that air pollution, low temperature and high temperature may increase the risk of OHCDs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Forecasting carbon dioxide emissions based on a hybrid of mixed data sampling regression model and back propagation neural network in the USA.

PubMed

Zhao, Xin; Han, Meng; Ding, Lili; Calin, Adrian Cantemir

2018-01-01

The accurate forecast of carbon dioxide emissions is critical for policy makers to take proper measures to establish a low carbon society. This paper discusses a hybrid of the mixed data sampling (MIDAS) regression model and BP (back propagation) neural network (MIDAS-BP model) to forecast carbon dioxide emissions. Such analysis uses mixed frequency data to study the effects of quarterly economic growth on annual carbon dioxide emissions. The forecasting ability of MIDAS-BP is remarkably better than MIDAS, ordinary least square (OLS), polynomial distributed lags (PDL), autoregressive distributed lags (ADL), and auto-regressive moving average (ARMA) models. The MIDAS-BP model is suitable for forecasting carbon dioxide emissions for both the short and longer term. This research is expected to influence the methodology for forecasting carbon dioxide emissions by improving the forecast accuracy. Empirical results show that economic growth has both negative and positive effects on carbon dioxide emissions that last 15 quarters. Carbon dioxide emissions are also affected by their own change within 3 years. Therefore, there is a need for policy makers to explore an alternative way to develop the economy, especially applying new energy policies to establish a low carbon society.

Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008–2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion

PubMed Central

Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

2016-01-01

Background Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. Methods The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008–2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. Results The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse “V” shape and “V” shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. Conclusion We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across provinces. Future research should explore the risk factors that cause spatial correlated structure or high variation of HFMD incidence which can be explained by temperature. When analyzing association between HFMD incidence and climatic variables, spatial heterogeneity among provinces should be evaluated. Moreover, the extra-Poisson multilevel model was capable of modeling the association between overdispersion of HFMD incidence and climatic variables. PMID:26808311

Short-Term Effects of Climatic Variables on Hand, Foot, and Mouth Disease in Mainland China, 2008-2013: A Multilevel Spatial Poisson Regression Model Accounting for Overdispersion.

PubMed

Liao, Jiaqiang; Yu, Shicheng; Yang, Fang; Yang, Min; Hu, Yuehua; Zhang, Juying

2016-01-01

Hand, Foot, and Mouth Disease (HFMD) is a worldwide infectious disease. In China, many provinces have reported HFMD cases, especially the south and southwest provinces. Many studies have found a strong association between the incidence of HFMD and climatic factors such as temperature, rainfall, and relative humidity. However, few studies have analyzed cluster effects between various geographical units. The nonlinear relationships and lag effects between weekly HFMD cases and climatic variables were estimated for the period of 2008-2013 using a polynomial distributed lag model. The extra-Poisson multilevel spatial polynomial model was used to model the exact relationship between weekly HFMD incidence and climatic variables after considering cluster effects, provincial correlated structure of HFMD incidence and overdispersion. The smoothing spline methods were used to detect threshold effects between climatic factors and HFMD incidence. The HFMD incidence spatial heterogeneity distributed among provinces, and the scale measurement of overdispersion was 548.077. After controlling for long-term trends, spatial heterogeneity and overdispersion, temperature was highly associated with HFMD incidence. Weekly average temperature and weekly temperature difference approximate inverse "V" shape and "V" shape relationships associated with HFMD incidence. The lag effects for weekly average temperature and weekly temperature difference were 3 weeks and 2 weeks. High spatial correlated HFMD incidence were detected in northern, central and southern province. Temperature can be used to explain most of variation of HFMD incidence in southern and northeastern provinces. After adjustment for temperature, eastern and Northern provinces still had high variation HFMD incidence. We found a relatively strong association between weekly HFMD incidence and weekly average temperature. The association between the HFMD incidence and climatic variables spatial heterogeneity distributed across provinces. Future research should explore the risk factors that cause spatial correlated structure or high variation of HFMD incidence which can be explained by temperature. When analyzing association between HFMD incidence and climatic variables, spatial heterogeneity among provinces should be evaluated. Moreover, the extra-Poisson multilevel model was capable of modeling the association between overdispersion of HFMD incidence and climatic variables.

Numerical simulation of time fractional dual-phase-lag model of heat transfer within skin tissue during thermal therapy.

PubMed

Kumar, Dinesh; Rai, K N

2017-07-01

In this paper, we investigated the thermal behavior in living biological tissues using time fractional dual-phase-lag bioheat transfer (DPLBHT) model subjected to Dirichelt boundary condition in presence of metabolic and electromagnetic heat sources during thermal therapy. We solved this bioheat transfer model using finite element Legendre wavelet Galerkin method (FELWGM) with help of block pulse function in sense of Caputo fractional order derivative. We compared the obtained results from FELWGM and exact method in a specific case, and found a high accuracy. Results are interpreted in the form of standard and anomalous cases for taking different order of time fractional DPLBHT model. The time to achieve hyperthermia position is discussed in both cases as standard and time fractional order derivative. The success of thermal therapy in the treatment of metastatic cancerous cell depends on time fractional order derivative to precise prediction and control of temperature. The effect of variability of parameters such as time fractional derivative, lagging times, blood perfusion coefficient, metabolic heat source and transmitted power on dimensionless temperature distribution in skin tissue is discussed in detail. The physiological parameters has been estimated, corresponding to the value of fractional order derivative for hyperthermia treatment therapy. Copyright © 2017 Elsevier Ltd. All rights reserved.

Repetition and lag effects in movement recognition.

PubMed

Hall, C R; Buckolz, E

1982-03-01

Whether repetition and lag improve the recognition of movement patterns was investigated. Recognition memory was tested for one repetition, two-repetitions massed, and two-repetitions distributed with movement patterns at lags of 3, 5, 7, and 13. Recognition performance was examined both immediately afterwards and following a 48 hour delay. Both repetition and lag effects failed to be demonstrated, providing some support for the claim that memory is unaffected by repetition at a constant level of processing (Craik & Lockhart, 1972). There was, as expected, a significant decrease in recognition memory following the retention interval, but this appeared unrelated to repetition or lag.

Distributed Lag Models: Examining Associations between the Built Environment and Health

PubMed Central

Baek, Jonggyu; Sánchez, Brisa N.; Berrocal, Veronica J.; Sanchez-Vaznaugh, Emma V.

2016-01-01

Built environment factors constrain individual level behaviors and choices, and thus are receiving increasing attention to assess their influence on health. Traditional regression methods have been widely used to examine associations between built environment measures and health outcomes, where a fixed, pre-specified spatial scale (e.g., 1 mile buffer) is used to construct environment measures. However, the spatial scale for these associations remains largely unknown and misspecifying it introduces bias. We propose the use of distributed lag models (DLMs) to describe the association between built environment features and health as a function of distance from the locations of interest and circumvent a-priori selection of a spatial scale. Based on simulation studies, we demonstrate that traditional regression models produce associations biased away from the null when there is spatial correlation among the built environment features. Inference based on DLMs is robust under a range of scenarios of the built environment. We use this innovative application of DLMs to examine the association between the availability of convenience stores near California public schools, which may affect children’s dietary choices both through direct access to junk food and exposure to advertisement, and children’s body mass index z-scores (BMIz). PMID:26414942

Education and Economic Growth in Pakistan: A Cointegration and Causality Analysis

ERIC Educational Resources Information Center

Afzal, Muhammad; Rehman, Hafeez Ur; Farooq, Muhammad Shahid; Sarwar, Kafeel

2011-01-01

This study explored the cointegration and causality between education and economic growth in Pakistan by using time series data on real gross domestic product (RGDP), labour force, physical capital and education from 1970-1971 to 2008-2009 were used. Autoregressive Distributed Lag (ARDL) Model of Cointegration and the Augmented Granger Causality…

Stress transfer around a broken fiber in unidirectional fiber-reinforced composites considering matrix damage evolution and interface slipping

NASA Astrophysics Data System (ADS)

Yang, Zhong; Zhang, BoMing; Zhao, Lin; Sun, XinYang

2011-02-01

A shear-lag model is applied to study the stress transfer around a broken fiber within unidirectional fiber-reinforced composites (FRC) subjected to uniaxial tensile loading along the fiber direction. The matrix damage and interfacial debonding, which are the main failure modes, are considered in the model. The maximum stress criterion with the linear damage evolution theory is used for the matrix. The slipping friction stress is considered in the interfacial debonding region using Coulomb friction theory, in which interfacial clamping stress comes from radial residual stress and mismatch of Poisson's ratios of constituents (fiber and matrix). The stress distributions in the fiber and matrix are obtained by the shear-lag theory added with boundary conditions, which includes force continuity and displacement compatibility constraints in the broken and neighboring intact fibers. The result gives axial stress distribution in fibers and shear stress in the interface and compares the theory reasonably well with the measurement by a polarized light microscope. The relation curves between damage, debonding and ineffective region lengths with external strain loading are obtained.

Numerical solution of non-linear dual-phase-lag bioheat transfer equation within skin tissues.

PubMed

Kumar, Dinesh; Kumar, P; Rai, K N

2017-11-01

This paper deals with numerical modeling and simulation of heat transfer in skin tissues using non-linear dual-phase-lag (DPL) bioheat transfer model under periodic heat flux boundary condition. The blood perfusion is assumed temperature-dependent which results in non-linear DPL bioheat transfer model in order to predict more accurate results. A numerical method of line which is based on finite difference and Runge-Kutta (4,5) schemes, is used to solve the present non-linear problem. Under specific case, the exact solution has been obtained and compared with the present numerical scheme, and we found that those are in good agreement. A comparison based on model selection criterion (AIC) has been made among non-linear DPL models when the variation of blood perfusion rate with temperature is of constant, linear and exponential type with the experimental data and it has been found that non-linear DPL model with exponential variation of blood perfusion rate is closest to the experimental data. In addition, it is found that due to absence of phase-lag phenomena in Pennes bioheat transfer model, it achieves steady state more quickly and always predict higher temperature than thermal and DPL non-linear models. The effect of coefficient of blood perfusion rate, dimensionless heating frequency and Kirchoff number on dimensionless temperature distribution has also been analyzed. The whole analysis is presented in dimensionless form. Copyright © 2017 Elsevier Inc. All rights reserved.

Daily ambient temperature and renal colic incidence in Guangzhou, China: a time-series analysis

NASA Astrophysics Data System (ADS)

Yang, Changyuan; Chen, Xinyu; Chen, Renjie; Cai, Jing; Meng, Xia; Wan, Yue; Kan, Haidong

2016-08-01

Few previous studies have examined the association between temperature and renal colic in developing regions, especially in China, the largest developing country in the world. We collected daily emergency ambulance dispatches (EADs) for renal colic from Guangzhou Emergency Center from 1 January 2008 to 31 December 2012. We used a distributed-lag nonlinear model in addition to the over-dispersed generalized additive model to investigate the association between daily ambient temperature and renal colic incidence after controlling for seasonality, humidity, public holidays, and day of the week. We identified 3158 EADs for renal colic during the study period. This exposure-response curve was almost flat when the temperature was low and moderate and elevated when the temperature increased over 21 °C. For heat-related effects, the significant risk occurred on the concurrent day and diminished until lag day 7. The cumulative relative risk of hot temperatures (90th percentile) and extremely hot temperatures (99th percentile) over lag days 0-7 was 1.92 (95 % confidence interval, 1.21, 3.05) and 2.45 (95 % confidence interval, 1.50, 3.99) compared with the reference temperature of 21 °C. This time-series analysis in Guangzhou, China, suggested a nonlinear and lagged association between high outdoor temperatures and daily EADs for renal colic. Our findings might have important public health significance to prevent renal colic.

Modeling steam pressure under martian lava flows

USGS Publications Warehouse

Dundas, Colin M.; Keszthelyi, Laszlo P.

2013-01-01

Rootless cones on Mars are a valuable indicator of past interactions between lava and water. However, the details of the lava–water interactions are not fully understood, limiting the ability to use these features to infer new information about past water on Mars. We have developed a model for the pressurization of a dry layer of porous regolith by melting and boiling ground ice in the shallow subsurface. This model builds on previous models of lava cooling and melting of subsurface ice. We find that for reasonable regolith properties and ice depths of decimeters, explosive pressures can be reached. However, the energy stored within such lags is insufficient to excavate thick flows unless they draw steam from a broader region than the local eruption site. These results indicate that lag pressurization can drive rootless cone formation under favorable circumstances, but in other instances molten fuel–coolant interactions are probably required. We use the model results to consider a range of scenarios for rootless cone formation in Athabasca Valles. Pressure buildup by melting and boiling ice under a desiccated lag is possible in some locations, consistent with the expected distribution of ice implanted from atmospheric water vapor. However, it is uncertain whether such ice has existed in the vicinity of Athabasca Valles in recent history. Plausible alternative sources include surface snow or an aqueous flood shortly before the emplacement of the lava flow.

Durability of classification and action learning: differences revealed using ex-Gaussian distribution analysis.

PubMed

Moutsopoulou, Karolina; Waszak, Florian

2013-05-01

It has been shown that in associative learning it is possible to disentangle the effects caused on behaviour by the associations between a stimulus and a classification (S-C) and the associations between a stimulus and the action performed towards it (S-A). Such evidence has been provided using ex-Gaussian distribution analysis to show that different parameters of the reaction time distribution reflect the different processes. Here, using this method, we investigate another difference between these two types of associations: What is the relative durability of these associations across time? Using a task-switching paradigm and by manipulating the lag between the point of the creation of the associations and the test phase, we show that S-A associations have stronger effects on behaviour when the lag between the two repetitions of a stimulus is short. However, classification learning affects behaviour not only in short-term lags but also (and equally so) when the lag between prime and probe is long and the same stimuli are repeatedly presented within a different classification task, demonstrating a remarkable durability of S-C associations.

Effective record length for the T-year event

USGS Publications Warehouse

Tasker, Gary D.

1983-01-01

The effect of serial dependence on the reliability of an estimate of the T-yr. event is of importance in hydrology because design decisions are based upon the estimate. In this paper the reliability of estimates of the T-yr. event from two common distributions is given as a function of number of observations and lag-one serial correlation coefficient for T = 2, 10, 20, 50, and 100 yr. A lag-one autoregressive model is assumed with either a normal or Pearson Type-III disturbance term. Results indicate that, if observations are serially correlated, the effective record length should be used to estimate the discharge associated with the expected exceedance probability. ?? 1983.

Forecasting the number of zoonotic cutaneous leishmaniasis cases in south of Fars province, Iran using seasonal ARIMA time series method.

PubMed

Sharafi, Mehdi; Ghaem, Haleh; Tabatabaee, Hamid Reza; Faramarzi, Hossein

2017-01-01

To predict the trend of cutaneous leishmaniasis and assess the relationship between the disease trend and weather variables in south of Fars province using Seasonal Autoregressive Integrated Moving Average (SARIMA) model. The trend of cutaneous leishmaniasis was predicted using Mini tab software and SARIMA model. Besides, information about the disease and weather conditions was collected monthly based on time series design during January 2010 to March 2016. Moreover, various SARIMA models were assessed and the best one was selected. Then, the model's fitness was evaluated based on normality of the residuals' distribution, correspondence between the fitted and real amounts, and calculation of Akaike Information Criteria (AIC) and Bayesian Information Criteria (BIC). The study results indicated that SARIMA model (4,1,4)(0,1,0) (12) in general and SARIMA model (4,1,4)(0,1,1) (12) in below and above 15 years age groups could appropriately predict the disease trend in the study area. Moreover, temperature with a three-month delay (lag3) increased the disease trend, rainfall with a four-month delay (lag4) decreased the disease trend, and rainfall with a nine-month delay (lag9) increased the disease trend. Based on the results, leishmaniasis follows a descending trend in the study area in case drought condition continues, SARIMA models can suitably measure the disease trend, and the disease follows a seasonal trend. Copyright © 2017 Hainan Medical University. Production and hosting by Elsevier B.V. All rights reserved.

Modelling malaria incidence by an autoregressive distributed lag model with spatial component.

PubMed

Laguna, Francisco; Grillet, María Eugenia; León, José R; Ludeña, Carenne

2017-08-01

The influence of climatic variables on the dynamics of human malaria has been widely highlighted. Also, it is known that this mosquito-borne infection varies in space and time. However, when the data is spatially incomplete most popular spatio-temporal methods of analysis cannot be applied directly. In this paper, we develop a two step methodology to model the spatio-temporal dependence of malaria incidence on local rainfall, temperature, and humidity as well as the regional sea surface temperatures (SST) in the northern coast of Venezuela. First, we fit an autoregressive distributed lag model (ARDL) to the weekly data, and then, we adjust a linear separable spacial vectorial autoregressive model (VAR) to the residuals of the ARDL. Finally, the model parameters are tuned using a Markov Chain Monte Carlo (MCMC) procedure derived from the Metropolis-Hastings algorithm. Our results show that the best model to account for the variations of malaria incidence from 2001 to 2008 in 10 endemic Municipalities in North-Eastern Venezuela is a logit model that included the accumulated local precipitation in combination with the local maximum temperature of the preceding month as positive regressors. Additionally, we show that although malaria dynamics is highly heterogeneous in space, a detailed analysis of the estimated spatial parameters in our model yield important insights regarding the joint behavior of the disease incidence across the different counties in our study. Copyright © 2017 Elsevier Ltd. All rights reserved.

Considering spatial heterogeneity in the distributed lag non-linear model when analyzing spatiotemporal data.

PubMed

Chien, Lung-Chang; Guo, Yuming; Li, Xiao; Yu, Hwa-Lung

2018-01-01

The distributed lag non-linear (DLNM) model has been frequently used in time series environmental health research. However, its functionality for assessing spatial heterogeneity is still restricted, especially in analyzing spatiotemporal data. This study proposed a solution to take a spatial function into account in the DLNM, and compared the influence with and without considering spatial heterogeneity in a case study. This research applied the DLNM to investigate non-linear lag effect up to 7 days in a case study about the spatiotemporal impact of fine particulate matter (PM 2.5 ) on preschool children's acute respiratory infection in 41 districts of northern Taiwan during 2005 to 2007. We applied two spatiotemporal methods to impute missing air pollutant data, and included the Markov random fields to analyze district boundary data in the DLNM. When analyzing the original data without a spatial function, the overall PM 2.5 effect accumulated from all lag-specific effects had a slight variation at smaller PM 2.5 measurements, but eventually decreased to relative risk significantly <1 when PM 2.5 increased. While analyzing spatiotemporal imputed data without a spatial function, the overall PM 2.5 effect did not decrease but increased in monotone as PM 2.5 increased over 20 μg/m 3 . After adding a spatial function in the DLNM, spatiotemporal imputed data conducted similar results compared with the overall effect from the original data. Moreover, the spatial function showed a clear and uneven pattern in Taipei, revealing that preschool children living in 31 districts of Taipei were vulnerable to acute respiratory infection. Our findings suggest the necessity of including a spatial function in the DLNM to make a spatiotemporal analysis available and to conduct more reliable and explainable research. This study also revealed the analytical impact if spatial heterogeneity is ignored.

A near-infrared, optical, and ultraviolet polarimetric and timing investigation of complex equatorial dusty structures

NASA Astrophysics Data System (ADS)

Marin, F.; Rojas Lobos, P. A.; Hameury, J. M.; Goosmann, R. W.

2018-05-01

Context. From stars to active galactic nuclei, many astrophysical systems are surrounded by an equatorial distribution of dusty material that is, in a number of cases, spatially unresolved even with cutting edge facilities. Aims: In this paper, we investigate if and how one can determine the unresolved and heterogeneous morphology of dust distribution around a central bright source using time-resolved polarimetric observations. Methods: We used polarized radiative transfer simulations to study a sample of circumnuclear dusty morphologies. We explored a grid of geometrically variable models that are uniform, fragmented, and density stratified in the near-infrared, optical, and ultraviolet bands, and we present their distinctive time-dependent polarimetric signatures. Results: As expected, varying the structure of the obscuring equatorial disk has a deep impact on the inclination-dependent flux, polarization degree and angle, and time lags we observe. We find that stratified media are distinguishable by time-resolved polarimetric observations, and that the expected polarization is much higher in the infrared band than in the ultraviolet. However, because of the physical scales imposed by dust sublimation, the average time lags of months to years between the total and polarized fluxes are important; these time lags lengthens the observational campaigns necessary to break more sophisticated, and therefore also more degenerated, models. In the ultraviolet band, time lags are slightly shorter than in the infrared or optical bands, and, coupled to lower diluting starlight fluxes, time-resolved polarimetry in the UV appears more promising for future campaigns. Conclusions: Equatorial dusty disks differ in terms of inclination-dependent photometric, polarimetric, and timing observables, but only the coupling of these different markers can lead to inclination-independent constraints on the unresolved structures. Even though it is complex and time consuming, polarized reverberation mapping in the ultraviolet-blue band is probably the best technique to rely on in this field.

Can the Air Pollution Index be used to communicate the health risks of air pollution?

PubMed

Li, Li; Lin, Guo-Zhen; Liu, Hua-Zhang; Guo, Yuming; Ou, Chun-Quan; Chen, Ping-Yan

2015-10-01

The validity of using the Air Pollution Index (API) to assess health impacts of air pollution and potential modification by individual characteristics on air pollution effects remain uncertain. We applied distributed lag non-linear models (DLNMs) to assess associations of daily API, specific pollution indices for PM10, SO2, NO2 and the weighted combined API (APIw) with mortality during 2003-2011 in Guangzhou, China. An increase of 10 in API was associated with a 0.88% (95% confidence interval (CI): 0.50, 1.27%) increase of non-accidental mortality at lag 0-2 days. Harvesting effects appeared after 2 days' exposure. The effect estimate of API over lag 0-15 days was statistically significant and similar with those of pollutant-specific indices and APIw. Stronger associations between API and mortality were observed in the elderly, females and residents with low educational attainment. In conclusion, the API can be used to communicate health risks of air pollution. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of the progressive failure of brittle matrix composites

NASA Technical Reports Server (NTRS)

Thomas, David J.

1995-01-01

This report investigates two of the most common modes of localized failures, namely, periodic fiber-bridged matrix cracks and transverse matrix cracks. A modification of Daniels' bundle theory is combined with Weibull's weakest link theory to model the statistical distribution of the periodic matrix cracking strength for an individual layer. Results of the model predictions are compared with experimental data from the open literature. Extensions to the model are made to account for possible imperfections within the layer (i.e., nonuniform fiber lengths, irregular crack spacing, and degraded in-situ fiber properties), and the results of these studies are presented. A generalized shear-lag analysis is derived which is capable of modeling the development of transverse matrix cracks in material systems having a general multilayer configuration and under states of full in-plane load. A method for computing the effective elastic properties for the damaged layer at the global level is detailed based upon the solution for the effects of the damage at the local level. This methodology is general in nature and is therefore also applicable to (0(sub m)/90(sub n))(sub s) systems. The characteristic stress-strain response for more general cases is shown to be qualitatively correct (experimental data is not available for a quantitative evaluation), and the damage evolution is recorded in terms of the matrix crack density as a function of the applied strain. Probabilistic effects are introduced to account for the statistical nature of the material strengths, thus allowing cumulative distribution curves for the probability of failure to be generated for each of the example laminates. Additionally, Oh and Finney's classic work on fracture location in brittle materials is extended and combined with the shear-lag analysis. The result is an analytical form for predicting the probability density function for the location of the next transverse crack occurrence within a crack bounded region. The results of this study verified qualitatively the validity of assuming a uniform crack spacing (as was done in the shear-lag model).

The cold effect of ambient temperature on ischemic and hemorrhagic stroke hospital admissions: A large database study in Beijing, China between years 2013 and 2014-Utilizing a distributed lag non-linear analysis.

PubMed

Luo, Yanxia; Li, Haibin; Huang, Fangfang; Van Halm-Lutterodt, Nicholas; Qin Xu; Wang, Anxin; Guo, Jin; Tao, Lixin; Li, Xia; Liu, Mengyang; Zheng, Deqiang; Chen, Sipeng; Zhang, Feng; Yang, Xinghua; Tan, Peng; Wang, Wei; Xie, Xueqin; Guo, Xiuhua

2018-01-01

The effects of ambient temperature on stroke death in China have been well addressed. However, few studies are focused on the attributable burden for the incident of different types of stroke due to ambient temperature, especially in Beijing, China. We purpose to assess the influence of ambient temperature on hospital stroke admissions in Beijing, China. Data on daily temperature, air pollution, and relative humidity measurements and stroke admissions in Beijing were obtained between 2013 and 2014. Distributed lag non-linear model was employed to determine the association between daily ambient temperature and stroke admissions. Relative risk (RR) with 95% confidence interval (CI) and Attribution fraction (AF) with 95% CI were calculated based on stroke subtype, gender and age group. A total number of 147, 624 stroke admitted cases (including hemorrhagic and ischemic types of stroke) were documented. A non-linear acute effect of cold temperature on ischemic and hemorrhagic stroke hospital admissions was evaluated. Compared with the 25th percentile of temperature (1.2 °C), the cumulative RR of extreme cold temperature (first percentile of temperature, -9.6 °C) was 1.51 (95% CI: 1.08-2.10) over lag 0-14 days for ischemic type and 1.28 (95% CI: 1.03-1.59) for hemorrhagic stroke over lag 0-3 days. Overall, 1.57% (95% CI: 0.06%-2.88%) of ischemic stroke and 1.90% (95% CI: 0.40%-3.41%) of hemorrhagic stroke was attributed to the extreme cold temperature over lag 0-7 days and lag 0-3 days, respectively. The cold temperature's impact on stroke admissions was found to be more obvious in male gender and the youth compared to female gender and the elderly. Exposure to extreme cold temperature is associated with increasing both ischemic and hemorrhagic stroke admissions in Beijing, China. Copyright © 2017 Elsevier Ltd. All rights reserved.

Study on the association between ambient air pollution and daily cardiovascular and respiratory mortality in an urban district of Beijing.

PubMed

Zhang, Fengying; Li, Liping; Krafft, Thomas; Lv, Jinmei; Wang, Wuyi; Pei, Desheng

2011-06-01

The association between daily cardiovascular/respiratory mortality and air pollution in an urban district of Beijing was investigated over a 6-year period (January 2003 to December 2008). The purpose of this study was to evaluate the relative importance of the major air pollutants [particulate matter (PM), SO2, NO2] as predictors of daily cardiovascular/respiratory mortality. The time-series studied comprises years with lower level interventions to control air pollution (2003-2006) and years with high level interventions in preparation for and during the Olympics/Paralympics (2007-2008). Concentrations of PM10, SO2, and NO2, were measured daily during the study period. A generalized additive model was used to evaluate daily numbers of cardiovascular/respiratory deaths in relation to each air pollutant, controlling for time trends and meteorological influences such as temperature and relative humidity. The results show that the daily cardiovascular/respiratory death rates were significantly associated with the concentration air pollutants, especially deaths related to cardiovascular disease. The current day effects of PM10 and NO2 were higher than that of single lags (distributed lags) and moving average lags for respiratory disease mortality. The largest RR of SO2 for respiratory disease mortality was in Lag02. For cardiovascular disease mortality, the largest RR was in Lag01 for PM10, and in current day (Lag0) for SO2 and NO2. NO2 was associated with the largest RRs for deaths from both cardiovascular disease and respiratory disease.

The weekly associations between climatic factors and Plasmodium vivax and Plasmodium falciparum malaria in China, 2005-2014.

PubMed

Hundessa, Samuel; Williams, Gail; Li, Shanshan; Guo, Jinpeng; Zhang, Wenyi; Guo, Yuming

2017-05-01

Meteorological factors play a crucial role in malaria transmission, but limited evidence is available from China. This study aimed to estimate the weekly associations between meteorological factors and Plasmodium vivax and Plasmodium falciparum malaria in China. The Distributed Lag Non-Linear Model was used to examine non-linearity and delayed effects of average temperature, rainfall, relative humidity, sunshine hours, wind speed and atmospheric pressure on malaria. Average temperature was associated with P. vivax and P. falciparum cases over long ranges of lags. The effect was more immediate on P. vivax (0-6 weeks) than on P. falciparum (1-9 weeks). Relative humidity was associated with P. vivax and P. falciparum over 8-10 weeks and 5-8 weeks lag, respectively. A significant effect of wind speed on P. vivax was observed at 0-2 weeks lag, but no association was found with P. falciparum. Rainfall had a decreasing effect on P. vivax, but no association was found with P. falciparum. Sunshine hours were negatively associated with P. falciparum, but the association was unclear for P. vixax. However, the effects of atmospheric pressure on both malaria types were not significant at any lag. Our study highlights a substantial effect of weekly climatic factors on P. vivax and P. falciparum malaria transmission in China, with different lags. This provides an evidence base for health authorities in developing a malaria early-warning system. © The Author 2017. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Association between dengue fever incidence and meteorological factors in Guangzhou, China, 2005-2014.

PubMed

Xiang, Jianjun; Hansen, Alana; Liu, Qiyong; Liu, Xiaobo; Tong, Michael Xiaoliang; Sun, Yehuan; Cameron, Scott; Hanson-Easey, Scott; Han, Gil-Soo; Williams, Craig; Weinstein, Philip; Bi, Peng

2017-02-01

This study aims to (1) investigate the associations between climatic factors and dengue; and (2) identify the susceptible subgroups. De-identified daily dengue cases in Guangzhou for 2005-2014 were obtained from the Chinese Center for Disease Control and Prevention. Weather data were downloaded from the China Meteorological Data Sharing Service System. Distributed lag non-linear models (DLNM) were used to graphically demonstrate the three-dimensional temperature-dengue association. Generalised estimating equation models (GEE) with piecewise linear spline functions were used to quantify the temperature-dengue associations. Threshold values were estimated using a broken-stick model. Middle-aged and older people, people undertaking household duties, retirees, and those unemployed were at high risk of dengue. Reversed U-shaped non-linear associations were found between ambient temperature, relative humidity, extreme wind velocity, and dengue. The optimal maximum temperature (T max ) range for dengue transmission in Guangzhou was 21.6-32.9°C, and 11.2-23.7°C for minimum temperature (T min ). A 1°C increase of T max and T min within these ranges was associated with 11.9% and 9.9% increase in dengue at lag0, respectively. Although lag effects of temperature were observed for up to 141 days for T max and 150 days for T min , the maximum lag effects were observed at 32 days and 39 days respectively. Average relative humidity was negatively associated with dengue when it exceeded 78.9%. Maximum wind velocity (>10.7m/s) inhibited dengue transmission. Climatic factors had significant impacts on dengue in Guangzhou. Lag effects of temperature on dengue lasted the local whole epidemic season. To reduce the likely increasing dengue burden, more efforts are needed to strengthen the capacity building of public health systems. Copyright © 2016 Elsevier Inc. All rights reserved.

Scaling of Ln(Permeability) in Sediments and Velocity Distributions in Turbulence: The Possibility of an Analogy.

NASA Astrophysics Data System (ADS)

Molz, F. J.; Kozubowski, T. J.; Miller, R. S.; Podgorski, K.

2005-12-01

The theory of non-stationary stochastic processes with stationary increments gives rise to stochastic fractals. When such fractals are used to represent measurements of (assumed stationary) physical properties, such as ln(k) increments in sediments or velocity increments "delta(v)" in turbulent flows, the resulting measurements exhibit scaling, either spatial, temporal or both. (In the present context, such scaling refers to systematic changes in the statistical properties of the increment distributions, such as variance, with the lag size over which the increments are determined.) Depending on the class of probability density functions (PDFs) that describe the increment distributions, the resulting stochastic fractals will display different properties. Until recently, the stationary increment process was represented using mainly Gaussian, Gamma or Levy PDFs. However, measurements in both sediments and fluid turbulence indicate that these PDFs are not commonly observed. Based on recent data and previous studies referenced and discussed in Meerschaert et al. (2004) and Molz et al. (2005), the measured increment PDFs display an approximate double exponential (Laplace) shape at smaller lags, and this shape evolves towards Gaussian at larger lags. A model for this behavior based on the Generalized Laplace PDF family called fractional Laplace motion, in analogy with its Gaussian counterpart - fractional Brownian motion, has been suggested (Meerschaert et al., 2004) and the necessary mathematics elaborated (Kozubowski et al., 2005). The resulting stochastic fractal is not a typical self-affine monofractal, but it does exhibit monofractal-like scaling in certain lag size ranges. To date, it has been shown that the Generalized Laplace family fits ln(k) increment distributions and reproduces the original 1941 theory of Kolmogorov when applied to Eulerian turbulent velocity increments. However, to make a physically self-consistent application to turbulence, one must adopt a Lagrangian viewpoint, and the details of this approach are still being developed. The potential analogy between turbulent delta(v) and sediment delta[ln(k)] is intriguing, and perhaps offers insight into the underlying chaotic processes that constitute turbulence and may result also in the pervasive heterogeneity observed in most natural sediments. Properties of the new Laplace fractal are presented, and potential applications to both sediments and fluid turbulence are discussed.

Transport and time lag of chlorofluorocarbon gases in the unsaturated zone, Rabis Creek, Denmark

USGS Publications Warehouse

Engesgaard, Peter; Højberg, Anker L.; Hinsby, Klaus; Jensen, Karsten H.; Laier, Troels; Larsen, Flemming; Busenberg, Eurybiades; Plummer, Niel

2004-01-01

Transport of chlorofluorocarbon (CFC) gases through the unsaturated zone to the water table is affected by gas diffusion, air–water exchange (solubility), sorption to the soil matrix, advective–dispersive transport in the water phase, and, in some cases, anaerobic degradation. In deep unsaturated zones, this may lead to a time lag between entry of gases at the land surface and recharge to groundwater. Data from a Danish field site were used to investigate how time lag is affected by variations in water content and to explore the use of simple analytical solutions to calculate time lag. Numerical simulations demonstrate that either degradation or sorption of CFC-11 takes place, whereas CFC-12 and CFC-113 are nonreactive. Water flow did not appreciably affect transport. An analytical solution for the period with a linear increase in atmospheric CFC concentrations (approximately early 1970s to early 1990s) was used to calculate CFC profiles and time lags. We compared the analytical results with numerical simulations. The time lags in the 15-m-deep unsaturated zone increase from 4.2 to between 5.2 and 6.1 yr and from 3.4 to 3.9 yr for CFC-11 and CFC-12, respectively, when simulations change from use of an exponential to a linear increase in atmospheric concentrations. The CFC concentrations at the water table before the early 1990s can be estimated by displacing the atmospheric input function by these fixed time lags. A sensitivity study demonstrates conditions under which a time lag in the unsaturated zone becomes important. The most critical parameter is the tortuosity coefficient. The analytical approach is valid for the low range of tortuosity coefficients (τ = 0.1–0.4) and unsaturated zones greater than approximately 20 m in thickness. In these cases the CFC distribution may still be from either the exponential or linear phase. In other cases, the use of numerical models, as described in our work and elsewhere, is an option.

Effect of Saturation Pressure Difference on Metal–Silicide Nanopowder Formation in Thermal Plasma Fabrication

PubMed Central

Shigeta, Masaya; Watanabe, Takayuki

2016-01-01

A computational investigation using a unique model and a solution algorithm was conducted, changing only the saturation pressure of one material artificially during nanopowder formation in thermal plasma fabrication, to highlight the effects of the saturation pressure difference between a metal and silicon. The model can not only express any profile of particle size–composition distribution for a metal–silicide nanopowder even with widely ranging sizes from sub-nanometers to a few hundred nanometers, but it can also simulate the entire growth process involving binary homogeneous nucleation, binary heterogeneous co-condensation, and coagulation among nanoparticles with different compositions. Greater differences in saturation pressures cause a greater time lag for co-condensation of two material vapors during the collective growth of the metal–silicide nanopowder. The greater time lag for co-condensation results in a wider range of composition of the mature nanopowder. PMID:28344300

Effect of Saturation Pressure Difference on Metal-Silicide Nanopowder Formation in Thermal Plasma Fabrication.

PubMed

Shigeta, Masaya; Watanabe, Takayuki

2016-03-07

A computational investigation using a unique model and a solution algorithm was conducted, changing only the saturation pressure of one material artificially during nanopowder formation in thermal plasma fabrication, to highlight the effects of the saturation pressure difference between a metal and silicon. The model can not only express any profile of particle size-composition distribution for a metal-silicide nanopowder even with widely ranging sizes from sub-nanometers to a few hundred nanometers, but it can also simulate the entire growth process involving binary homogeneous nucleation, binary heterogeneous co-condensation, and coagulation among nanoparticles with different compositions. Greater differences in saturation pressures cause a greater time lag for co-condensation of two material vapors during the collective growth of the metal-silicide nanopowder. The greater time lag for co-condensation results in a wider range of composition of the mature nanopowder.

Air pollution is associated with primary health care visits for asthma in Sweden: A case-crossover design with a distributed lag non-linear model.

PubMed

Taj, Tahir; Jakobsson, Kristina; Stroh, Emilie; Oudin, Anna

2016-05-01

Air pollution can increase the symptoms of asthma and has an acute effect on the number of emergency room visits and hospital admissions because of asthma, but little is known about the effect of air pollution on the number of primary health care (PHC) visits for asthma. To investigate the association between air pollution and the number of PHC visits for asthma in Scania, southern Sweden. Data on daily PHC visits for asthma were obtained from a regional healthcare database in Scania, which covers approximately half a million people. Air pollution data from 2005 to 2010 were obtained from six urban background stations. We used a case-crossover study design and a distributed lag non-linear model in the analysis. The air pollution levels were generally within the EU air quality guidelines. The mean number of daily PHC visits for asthma was 34. The number of PHC visits increased by 5% (95% confidence interval (CI): 3.91-6.25%) with every 10µg m(-3) increase in daily mean NO2 lag (0-15), suggesting that daily air pollution levels are associated with PHC visits for asthma. Even though the air quality in Scania between 2005 and 2010 was within EU's guidelines, the number of PHC visits for asthma increased with increasing levels of air pollution. This suggests that as well as increasing hospital and emergency room visits, air pollution increases the burden on PHC due to milder symptoms of asthma. Copyright © 2016 Elsevier Ltd. All rights reserved.

Physiological Equivalent Temperature Index and mortality in Tabriz (The northwest of Iran).

PubMed

Sharafkhani, Rahim; Khanjani, Narges; Bakhtiari, Bahram; Jahani, Yunes; Sadegh Tabrizi, Jafar

2018-01-01

There are few epidemiological studies about climate change and the effect of temperature variation on health using human thermal indices such as the Physiological Equivalent Temperature (PET) Index in Iran. This study was conducted in Tabriz, the northwest of Iran and Distributed Lag Non-linear Models (DLNM) combined with quasi-Poisson regression models were used to assess the impacts of PET on mortality by using the DLNM Package in R Software. The effect of air pollutants, time trend, day of the week and holidays were controlled as confounders. There was a significant relation between high (30°C, 27°C) and low (-0.8°C, -9.2°C and -14.2°C) PET and total (non-accidental) mortality; and a significant increase in respiratory and cardiovascular deaths in high PET values. Heat stress increased Cumulative Relative Risk (CRR) for total (non-accidental), respiratory and cardiovascular mortality significantly (CRR Non Accidental Death, PET=30°C, lag 0-30 =1.67, 95%CI: 1.31-2.13; CRR Respiratory Death, PET=30°C, lag 0-13 =1.88, 95%CI: 1.30-2.72; CRR Cardiovascular Death, PET=30°C, lag0-30 =1.67 95%CI: 1.16-2.40). Heat stress increases the risk of total (non-accidental), respiratory mortality, but cold stress decreases the risk of total (non-accidental) mortality in Tabriz which is one of the cold cities of Iran. Copyright © 2017 Elsevier Ltd. All rights reserved.

A study on thermal damage during hyperthermia treatment based on DPL model for multilayer tissues using finite element Legendre wavelet Galerkin approach.

PubMed

Kumar, Dinesh; Rai, K N

2016-12-01

Hyperthermia is a process that uses heat from the spatial heat source to kill cancerous cells without damaging the surrounding healthy tissues. Efficacy of hyperthermia technique is related to achieve temperature at the infected cells during the treatment process. A mathematical model on heat transfer in multilayer tissues in finite domain is proposed to predict the control temperature profile at hyperthermia position. The treatment technique uses dual-phase-lag model of heat transfer in multilayer tissues with modified Gaussian distribution heat source subjected to the most generalized boundary condition and interface at the adjacent layers. The complete dual-phase-lag model of bioheat transfer is solved using finite element Legendre wavelet Galerkin approach. The present solution has been verified with exact solution in a specific case and provides a good accuracy. The effect of the variability of different parameters such as lagging times, external heat source, metabolic heat source and the most generalized boundary condition on temperature profile in multilayer tissues is analyzed and also discussed the effective approach of hyperthermia treatment. Furthermore, we studied the modified thermal damage model with regeneration of healthy tissues as well. For viewpoint of thermal damage, the least thermal damage has been observed in boundary condition of second kind. The article concludes with a discussion of better opportunities for future clinical application of hyperthermia treatment. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of the prediction model for dengue incidence in Can Tho city, a Mekong Delta area in Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Manh, Cuong Do

2015-01-01

The Mekong Delta is highly vulnerable to climate change and a dengue endemic area in Vietnam. This study aims to examine the association between climate factors and dengue incidence and to identify the best climate prediction model for dengue incidence in Can Tho city, the Mekong Delta area in Vietnam. We used three different regression models comprising: standard multiple regression model (SMR), seasonal autoregressive integrated moving average model (SARIMA), and Poisson distributed lag model (PDLM) to examine the association between climate factors and dengue incidence over the period 2003-2010. We validated the models by forecasting dengue cases for the period of January-December, 2011 using the mean absolute percentage error (MAPE). Receiver operating characteristics curves were used to analyze the sensitivity of the forecast of a dengue outbreak. The results indicate that temperature and relative humidity are significantly associated with changes in dengue incidence consistently across the model methods used, but not cumulative rainfall. The Poisson distributed lag model (PDLM) performs the best prediction of dengue incidence for a 6, 9, and 12-month period and diagnosis of an outbreak however the SARIMA model performs a better prediction of dengue incidence for a 3-month period. The simple or standard multiple regression performed highly imprecise prediction of dengue incidence. We recommend a follow-up study to validate the model on a larger scale in the Mekong Delta region and to analyze the possibility of incorporating a climate-based dengue early warning method into the national dengue surveillance system. Copyright © 2014 Elsevier B.V. All rights reserved.

Exponential lag function projective synchronization of memristor-based multidirectional associative memory neural networks via hybrid control

NASA Astrophysics Data System (ADS)

Yuan, Manman; Wang, Weiping; Luo, Xiong; Li, Lixiang; Kurths, Jürgen; Wang, Xiao

2018-03-01

This paper is concerned with the exponential lag function projective synchronization of memristive multidirectional associative memory neural networks (MMAMNNs). First, we propose a new model of MMAMNNs with mixed time-varying delays. In the proposed approach, the mixed delays include time-varying discrete delays and distributed time delays. Second, we design two kinds of hybrid controllers. Traditional control methods lack the capability of reflecting variable synaptic weights. In this paper, the controllers are carefully designed to confirm the process of different types of synchronization in the MMAMNNs. Third, sufficient criteria guaranteeing the synchronization of system are derived based on the derive-response concept. Finally, the effectiveness of the proposed mechanism is validated with numerical experiments.

Turbulence Modeling for Shock Wave/Turbulent Boundary Layer Interactions

NASA Technical Reports Server (NTRS)

Lillard, Randolph P.

2011-01-01

Accurate aerodynamic computational predictions are essential for the safety of space vehicles, but these computations are of limited accuracy when large pressure gradients are present in the flow. The goal of the current project is to improve the state of compressible turbulence modeling for high speed flows with shock wave / turbulent boundary layer interactions (SWTBLI). Emphasis will be placed on models that can accurately predict the separated region caused by the SWTBLI. These flows are classified as nonequilibrium boundary layers because of the very large and variable adverse pressure gradients caused by the shock waves. The lag model was designed to model these nonequilibrium flows by incorporating history effects. Standard one- and two-equation models (Spalart Allmaras and SST) and the lag model will be run and compared to a new lag model. This new model, the Reynolds stress tensor lag model (lagRST), will be assessed against multiple wind tunnel tests and correlations. The basis of the lag and lagRST models are to preserve the accuracy of the standard turbulence models in equilibrium turbulence, when the Reynolds stresses are linearly related to the mean strain rates, but create a lag between mean strain rate effects and turbulence when nonequilibrium effects become important, such as in large pressure gradients. The affect this lag has on the results for SWBLI and massively separated flows will be determined. These computations will be done with a modified version of the OVERFLOW code. This code solves the RANS equations on overset grids. It was used for this study for its ability to input very complex geometries into the flow solver, such as the Space Shuttle in the full stack configuration. The model was successfully implemented within two versions of the OVERFLOW code. Results show a substantial improvement over the baseline models for transonic separated flows. The results are mixed for the SWBLI assessed. Separation predictions are not as good as the baseline models, but the over prediction of the peak heat flux downstream of the reattachment shock that plagues many models is reduced.

A new mechanistic growth model for simultaneous determination of lag phase duration and exponential growth rate and a new Belehdradek-type model for evaluating the effect of temperature on growth rate

USDA-ARS?s Scientific Manuscript database

A new mechanistic growth model was developed to describe microbial growth under isothermal conditions. The new mathematical model was derived from the basic observation of bacterial growth that may include lag, exponential, and stationary phases. With this model, the lag phase duration and exponen...

Applications of physics to economics and finance: Money, income, wealth, and the stock market

NASA Astrophysics Data System (ADS)

Dragulescu, Adrian Antoniu

Several problems arising in Economics and Finance are analyzed using concepts and quantitative methods from Physics. The dissertation is organized as follows: In the first chapter it is argued that in a closed economic system, money is conserved. Thus, by analogy with energy, the equilibrium probability distribution of money must follow the exponential Boltzmann-Gibbs law characterized by an effective temperature equal to the average amount of money per economic agent. The emergence of Boltzmann-Gibbs distribution is demonstrated through computer simulations of economic models. A thermal machine which extracts a monetary profit can be constructed between two economic systems with different temperatures. The role of debt and models with broken time-reversal symmetry for which the Boltzmann-Gibbs law does not hold, are discussed. In the second chapter, using data from several sources, it is found that the distribution of income is described for the great majority of population by an exponential distribution, whereas the high-end tail follows a power law. From the individual income distribution, the probability distribution of income for families with two earners is derived and it is shown that it also agrees well with the data. Data on wealth is presented and it is found that the distribution of wealth has a structure similar to the distribution of income. The Lorenz curve and Gini coefficient were calculated and are shown to be in good agreement with both income and wealth data sets. In the third chapter, the stock-market fluctuations at different time scales are investigated. A model where stock-price dynamics is governed by a geometrical (multiplicative) Brownian motion with stochastic variance is proposed. The corresponding Fokker-Planck equation can be solved exactly. Integrating out the variance, an analytic formula for the time-dependent probability distribution of stock price changes (returns) is found. The formula is in excellent agreement with the Dow-Jones index for the time lags from 1 to 250 trading days. For time lags longer than the relaxation time of variance, the probability distribution can be expressed in a scaling form using a Bessel function. The Dow-Jones data follow the scaling function for seven orders of magnitude.

Analysis and IbM simulation of the stages in bacterial lag phase: basis for an updated definition.

PubMed

Prats, Clara; Giró, Antoni; Ferrer, Jordi; López, Daniel; Vives-Rego, Josep

2008-05-07

The lag phase is the initial phase of a culture that precedes exponential growth and occurs when the conditions of the culture medium differ from the pre-inoculation conditions. It is usually defined by means of cell density because the number of individuals remains approximately constant or slowly increases, and it is quantified with the lag parameter lambda. The lag phase has been studied through mathematical modelling and by means of specific experiments. In recent years, Individual-based Modelling (IbM) has provided helpful insights into lag phase studies. In this paper, the definition of lag phase is thoroughly examined. Evolution of the total biomass and the total number of bacteria during lag phase is tackled separately. The lag phase lasts until the culture reaches a maximum growth rate both in biomass and cell density. Once in the exponential phase, both rates are constant over time and equal to each other. Both evolutions are split into an initial phase and a transition phase, according to their growth rates. A population-level mathematical model is presented to describe the transitional phase in cell density. INDividual DIScrete SIMulation (INDISIM) is used to check the outcomes of this analysis. Simulations allow the separate study of the evolution of cell density and total biomass in a batch culture, they provide a depiction of different observed cases in lag evolution at the individual-cell level, and are used to test the population-level model. The results show that the geometrical lag parameter lambda is not appropriate as a universal definition for the lag phase. Moreover, the lag phase cannot be characterized by a single parameter. For the studied cases, the lag phases of both the total biomass and the population are required to fully characterize the evolution of bacterial cultures. The results presented prove once more that the lag phase is a complex process that requires a more complete definition. This will be possible only after the phenomena governing the population dynamics at an individual level of description, and occurring during the lag and exponential growth phases, are well understood.

Modeling the lag period and exponential growth of Listeria monocytogenes under conditions of fluctuating temperature and water activity values.

PubMed

Muñoz-Cuevas, Marina; Fernández, Pablo S; George, Susan; Pin, Carmen

2010-05-01

The dynamic model for the growth of a bacterial population described by Baranyi and Roberts (J. Baranyi and T. A. Roberts, Int. J. Food Microbiol. 23:277-294, 1994) was applied to model the lag period and exponential growth of Listeria monocytogenes under conditions of fluctuating temperature and water activity (a(w)) values. To model the duration of the lag phase, the dependence of the parameter h(0), which quantifies the amount of work done during the lag period, on the previous and current environmental conditions was determined experimentally. This parameter depended not only on the magnitude of the change between the previous and current environmental conditions but also on the current growth conditions. In an exponentially growing population, any change in the environment requiring a certain amount of work to adapt to the new conditions initiated a lag period that lasted until that work was finished. Observations for several scenarios in which exponential growth was halted by a sudden change in the temperature and/or a(w) were in good agreement with predictions. When a population already in a lag period was subjected to environmental fluctuations, the system was reset with a new lag phase. The work to be done during the new lag phase was estimated to be the workload due to the environmental change plus the unfinished workload from the uncompleted previous lag phase.

Estimating the Delay between Host Infection and Disease (Incubation Period) and Assessing Its Significance to the Epidemiology of Plant Diseases

PubMed Central

Leclerc, Melen; Doré, Thierry; Gilligan, Christopher A.; Lucas, Philippe; Filipe, João A. N.

2014-01-01

Knowledge of the incubation period of infectious diseases (time between host infection and expression of disease symptoms) is crucial to our epidemiological understanding and the design of appropriate prevention and control policies. Plant diseases cause substantial damage to agricultural and arboricultural systems, but there is still very little information about how the incubation period varies within host populations. In this paper, we focus on the incubation period of soilborne plant pathogens, which are difficult to detect as they spread and infect the hosts underground and above-ground symptoms occur considerably later. We conducted experiments on Rhizoctonia solani in sugar beet, as an example patho-system, and used modelling approaches to estimate the incubation period distribution and demonstrate the impact of differing estimations on our epidemiological understanding of plant diseases. We present measurements of the incubation period obtained in field conditions, fit alternative probability models to the data, and show that the incubation period distribution changes with host age. By simulating spatially-explicit epidemiological models with different incubation-period distributions, we study the conditions for a significant time lag between epidemics of cryptic infection and the associated epidemics of symptomatic disease. We examine the sensitivity of this lag to differing distributional assumptions about the incubation period (i.e. exponential versus Gamma). We demonstrate that accurate information about the incubation period distribution of a pathosystem can be critical in assessing the true scale of pathogen invasion behind early disease symptoms in the field; likewise, it can be central to model-based prediction of epidemic risk and evaluation of disease management strategies. Our results highlight that reliance on observation of disease symptoms can cause significant delay in detection of soil-borne pathogen epidemics and mislead practitioners and epidemiologists about the timing, extent, and viability of disease control measures for limiting economic loss. PMID:24466153

Estimating the delay between host infection and disease (incubation period) and assessing its significance to the epidemiology of plant diseases.

PubMed

Leclerc, Melen; Doré, Thierry; Gilligan, Christopher A; Lucas, Philippe; Filipe, João A N

2014-01-01

Knowledge of the incubation period of infectious diseases (time between host infection and expression of disease symptoms) is crucial to our epidemiological understanding and the design of appropriate prevention and control policies. Plant diseases cause substantial damage to agricultural and arboricultural systems, but there is still very little information about how the incubation period varies within host populations. In this paper, we focus on the incubation period of soilborne plant pathogens, which are difficult to detect as they spread and infect the hosts underground and above-ground symptoms occur considerably later. We conducted experiments on Rhizoctonia solani in sugar beet, as an example patho-system, and used modelling approaches to estimate the incubation period distribution and demonstrate the impact of differing estimations on our epidemiological understanding of plant diseases. We present measurements of the incubation period obtained in field conditions, fit alternative probability models to the data, and show that the incubation period distribution changes with host age. By simulating spatially-explicit epidemiological models with different incubation-period distributions, we study the conditions for a significant time lag between epidemics of cryptic infection and the associated epidemics of symptomatic disease. We examine the sensitivity of this lag to differing distributional assumptions about the incubation period (i.e. exponential versus Gamma). We demonstrate that accurate information about the incubation period distribution of a pathosystem can be critical in assessing the true scale of pathogen invasion behind early disease symptoms in the field; likewise, it can be central to model-based prediction of epidemic risk and evaluation of disease management strategies. Our results highlight that reliance on observation of disease symptoms can cause significant delay in detection of soil-borne pathogen epidemics and mislead practitioners and epidemiologists about the timing, extent, and viability of disease control measures for limiting economic loss.

Manual choice reaction times in the rate-domain

PubMed Central

Harris, Christopher M.; Waddington, Jonathan; Biscione, Valerio; Manzi, Sean

2014-01-01

Over the last 150 years, human manual reaction times (RTs) have been recorded countless times. Yet, our understanding of them remains remarkably poor. RTs are highly variable with positively skewed frequency distributions, often modeled as an inverse Gaussian distribution reflecting a stochastic rise to threshold (diffusion process). However, latency distributions of saccades are very close to the reciprocal Normal, suggesting that “rate” (reciprocal RT) may be the more fundamental variable. We explored whether this phenomenon extends to choice manual RTs. We recorded two-alternative choice RTs from 24 subjects, each with 4 blocks of 200 trials with two task difficulties (easy vs. difficult discrimination) and two instruction sets (urgent vs. accurate). We found that rate distributions were, indeed, very close to Normal, shifting to lower rates with increasing difficulty and accuracy, and for some blocks they appeared to become left-truncated, but still close to Normal. Using autoregressive techniques, we found temporal sequential dependencies for lags of at least 3. We identified a transient and steady-state component in each block. Because rates were Normal, we were able to estimate autoregressive weights using the Box-Jenkins technique, and convert to a moving average model using z-transforms to show explicit dependence on stimulus input. We also found a spatial sequential dependence for the previous 3 lags depending on whether the laterality of previous trials was repeated or alternated. This was partially dissociated from temporal dependency as it only occurred in the easy tasks. We conclude that 2-alternative choice manual RT distributions are close to reciprocal Normal and not the inverse Gaussian. This is not consistent with stochastic rise to threshold models, and we propose a simple optimality model in which reward is maximized to yield to an optimal rate, and hence an optimal time to respond. We discuss how it might be implemented. PMID:24959134

Local Colonization-Extinction Dynamics Generate Lags in the Response to Climate Change in Eastern North American Forests

NASA Astrophysics Data System (ADS)

Talluto, M. V.; Boulangeat, I.; Vissault, S.; Gravel, D.

2015-12-01

Climate change is likely to push many species to the limits of their ecological niches and lead to mismatches between species ranges and local environmental conditions. Forested ecosystems in particular may have difficulty tracking climate change due to slow growth and dispersal rates. Correlative species distribution models (SDMs), commonly used to predict the response of species distributions to climate change, relate species occurrences to climate to describe the present niche; however they often project into the future without accounting for slow processes that might produce lags in the response to climate change. An alternative type of model that analyzes patch-scale colonization and extinction (C-E) rates along an environmental gradient has been successful in describing species range limits in theoretical studies. Because the model is stochastic and dynamic, it is more robust to changes in the environmental gradient than static SDMs. We applied such a model to 40 of the most abundant trees in eastern North American forests, using repeated observations across multiple decades to parameterize the C-E rates. We show that C-E rates for many species respond to climate in a manner that generates predicted range limits when the species is at equilibrium with the environment. Moreover, current distributions of many species are significantly out of equilibrium with the present climate, with predicted range limits shifted 10s to 100s of km northward from the present distribution. These results suggest that present warming has already exceeded the thermal tolerance at the southern range limits for the dominant trees of eastern North American forests, producing millions of ha of newly suitable areas north of the present distribution of these species that have not yet been colonized, as well as large southern regions where species are present but expected to be lost in the long-term as dead trees are not replaced, even if no further climate warming occurs.

Association of Interleukin-17 polymorphism (-197G/A) in chronic and localized aggressive periodontitis.

PubMed

Chaudhari, Harshal Liladhar; Warad, Shivaraj; Ashok, Nipun; Baroudi, Kusai; Tarakji, Bassel

2016-01-01

Interleukin 17(IL-17) is a pro-inflammatory cytokine produced mainly by Th17 cells. The present study was undertaken to investigate a possible association between IL-17 A genetic polymorphism at (-197A/G) and susceptibility to chronic and localized aggressive periodontitis (LAgP) in an Indian population. The study was carried out on 105 subjects, which included 35 LAgP patients, 35 chronic periodontitis patients and 35 healthy controls. Blood samples were drawn from the subjects and analyzed for IL-17 genetic polymorphism at (-197A/G), by using the polymerase chain reaction-restriction fragment length polymorphism method. A statistically significant difference was seen in the genotype distribution among chronic periodontitis patients, LAgP patients and healthy subjects. There was a significant difference in the distribution of alleles among chronic periodontitis patients, LAgP patients and healthy subjects. The odds ratio for A allele versus G allele was 5.1 between chronic periodontitis patients and healthy controls, and 5.1 between LAgp patients and healthy controls. Our study concluded that IL-17 A gene polymorphism at (-197A/G) is linked to chronic periodontitis and LAgP in Indian population. The presence of allele A in the IL-17 gene polymorphism (-197A/G) can be considered a risk factor for chronic periodontitis and LAgP.

The Association between Dust Storms and Daily Non-Accidental Mortality in the United States, 1993-2005.

PubMed

Crooks, James Lewis; Cascio, Wayne E; Percy, Madelyn S; Reyes, Jeanette; Neas, Lucas M; Hilborn, Elizabeth D

2016-11-01

The impact of dust storms on human health has been studied in the context of Asian, Saharan, Arabian, and Australian storms, but there has been no recent population-level epidemiological research on the dust storms in North America. The relevance of dust storms to public health is likely to increase as extreme weather events are predicted to become more frequent with anticipated changes in climate through the 21st century. We examined the association between dust storms and county-level non-accidental mortality in the United States from 1993 through 2005. Dust storm incidence data, including date and approximate location, are taken from the U.S. National Weather Service storm database. County-level mortality data for the years 1993-2005 were acquired from the National Center for Health Statistics. Distributed lag conditional logistic regression models under a time-stratified case-crossover design were used to study the relationship between dust storms and daily mortality counts over the whole United States and in Arizona and California specifically. End points included total non-accidental mortality and three mortality subgroups (cardiovascular, respiratory, and other non-accidental). We estimated that for the United States as a whole, total non-accidental mortality increased by 7.4% (95% CI: 1.6, 13.5; p = 0.011) and 6.7% (95% CI: 1.1, 12.6; p = 0.018) at 2- and 3-day lags, respectively, and by an average of 2.7% (95% CI: 0.4, 5.1; p = 0.023) over lags 0-5 compared with referent days. Significant associations with non-accidental mortality were estimated for California (lag 2 and 0-5 day) and Arizona (lag 3), for cardiovascular mortality in the United States (lag 2) and Arizona (lag 3), and for other non-accidental mortality in California (lags 1-3 and 0-5). Dust storms are associated with increases in lagged non-accidental and cardiovascular mortality. Citation: Crooks JL, Cascio WE, Percy MS, Reyes J, Neas LM, Hilborn ED. 2016. The association between dust storms and daily non-accidental mortality in the United States, 1993-2005. Environ Health Perspect 124:1735-1743; http://dx.doi.org/10.1289/EHP216.

Spatio-temporal distribution of dengue fever under scenarios of climate change in the southern Taiwan

NASA Astrophysics Data System (ADS)

Lee, Chieh-Han; Yu, Hwa-Lung

2014-05-01

Dengue fever has been recognized as the most important widespread vector-borne infectious disease in recent decades. Over 40% of the world's population is risk from dengue and about 50-100 million people are infected world wide annually. Previous studies have found that dengue fever is highly correlated with climate covariates. Thus, the potential effects of global climate change on dengue fever are crucial to epidemic concern, in particular, the transmission of the disease. This present study investigated the nonlinearity of time-delayed impact of climate on spatio-temporal variations of dengue fever in the southern Taiwan during 1998 to 2011. A distributed lag nonlinear model (DLNM) is used to assess the nonlinear lagged effects of meteorology. The statistically significant meteorological factors are considered, including weekly minimum temperature and maximum 24-hour rainfall. The relative risk and the distribution of dengue fever then predict under various climate change scenarios. The result shows that the relative risk is similar for different scenarios. In addition, the impact of rainfall on the incidence risk is higher than temperature. Moreover, the incidence risk is associated to spatially population distribution. The results can be served as practical reference for environmental regulators for the epidemic prevention under climate change scenarios.

Added effect of heat wave on mortality in Seoul, Korea.

PubMed

Lee, Won Kyung; Lee, Hye Ah; Lim, Youn Hee; Park, Hyesook

2016-05-01

A heat wave could increase mortality owing to high temperature. However, little is known about the added (duration) effect of heat wave from the prolonged period of high temperature on mortality and different effect sizes depending on the definition of heat waves and models. A distributed lag non-linear model with a quasi-Poisson distribution was used to evaluate the added effect of heat wave on mortality after adjusting for long-term and intra-seasonal trends and apparent temperature. We evaluated the cumulative relative risk of the added wave effect on mortality on lag days 0-30. The models were constructed using nine definitions of heat wave and two relationships (cubic spline and linear threshold model) between temperature and mortality to leave out the high temperature effect. Further, we performed sensitivity analysis to evaluate the changes in the effect of heat wave on mortality according to the different degrees of freedom for time trend and cubic spline of temperature. We found that heat wave had the added effect from the prolonged period of high temperature on mortality and it was considerable in the aspect of cumulative risk because of the lagged influence. When heat wave was defined with a threshold of 98th percentile temperature and ≥2, 3, and 4 consecutive days, mortality increased by 14.8 % (7.5-22.6, 95 % confidence interval (CI)), 18.1 % (10.8-26.0, 95 % CI), 18.1 % (10.7-25.9, 95 % CI), respectively, in cubic spline model. When it came to the definitions of 90th and 95th percentile, the risk increase in mortality declined to 3.7-5.8 % and 8.6-11.3 %, respectively. This effect was robust to the flexibility of the model for temperature and time trend, while the definitions of a heat wave were critical in estimating its relationship with mortality. This finding could help deepen our understanding and quantifying of the relationship between heat wave and mortality and select an appropriate definition of heat wave and temperature model in the future studies.

A Lagging Model for Describing Drawdown Induced by a Constant-Rate Pumping in a Leaky Confined Aquifer

NASA Astrophysics Data System (ADS)

Lin, Ye-Chen; Yeh, Hund-Der

2017-10-01

This study proposes a generalized Darcy's law with considering phase lags in both the water flux and drawdown gradient to develop a lagging flow model for describing drawdown induced by constant-rate pumping (CRP) in a leaky confined aquifer. The present model has a mathematical formulation similar to the dual-porosity model. The Laplace-domain solution of the model with the effect of wellbore storage is derived by the Laplace transform method. The time-domain solution for the case of neglecting the wellbore storage and well radius is developed by the use of Laplace transform and Weber transform. The results of sensitivity analysis based on the solution indicate that the drawdown is very sensitive to the change in each of the transmissivity and storativity. Also, a study for the lagging effect on the drawdown indicates that its influence is significant associated with the lag times. The present solution is also employed to analyze a data set taken from a CRP test conducted in a fractured aquifer in South Dakota, USA. The results show the prediction of this new solution with considering the phase lags has very good fit to the field data, especially at early pumping time. In addition, the phase lags seem to have a scale effect as indicated in the results. In other words, the lagging behavior is positively correlated with the observed distance in the Madison aquifer.

Effects of local and regional climatic fluctuations on dengue outbreaks in southern Taiwan

PubMed Central

Chaves, Luis Fernando; Chen, Po-Jiang

2017-01-01

Background Southern Taiwan has been a hotspot for dengue fever transmission since 1998. During 2014 and 2015, Taiwan experienced unprecedented dengue outbreaks and the causes are poorly understood. This study aims to investigate the influence of regional and local climate conditions on the incidence of dengue fever in Taiwan, as well as to develop a climate-based model for future forecasting. Methodology/Principle findings Historical time-series data on dengue outbreaks in southern Taiwan from 1998 to 2015 were investigated. Local climate variables were analyzed using a distributed lag non-linear model (DLNM), and the model of best fit was used to predict dengue incidence between 2013 and 2015. The cross-wavelet coherence approach was used to evaluate the regional El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) effects on dengue incidence and local climate variables. The DLNM results highlighted the important non-linear and lag effects of minimum temperature and precipitation. Minimum temperature above 23°C or below 17°C can increase dengue incidence rate with lag effects of 10 to 15 weeks. Moderate to high precipitation can increase dengue incidence rates with a lag of 10 or 20 weeks. The model of best fit successfully predicted dengue transmission between 2013 and 2015. The prediction accuracy ranged from 0.7 to 0.9, depending on the number of weeks ahead of the prediction. ENSO and IOD were associated with nonstationary inter-annual patterns of dengue transmission. IOD had a greater impact on the seasonality of local climate conditions. Conclusions/Significance Our findings suggest that dengue transmission can be affected by regional and local climatic fluctuations in southern Taiwan. The climate-based model developed in this study can provide important information for dengue early warning systems in Taiwan. Local climate conditions might be influenced by ENSO and IOD, to result in unusual dengue outbreaks. PMID:28575035

Effects of local and regional climatic fluctuations on dengue outbreaks in southern Taiwan.

PubMed

Chuang, Ting-Wu; Chaves, Luis Fernando; Chen, Po-Jiang

2017-01-01

Southern Taiwan has been a hotspot for dengue fever transmission since 1998. During 2014 and 2015, Taiwan experienced unprecedented dengue outbreaks and the causes are poorly understood. This study aims to investigate the influence of regional and local climate conditions on the incidence of dengue fever in Taiwan, as well as to develop a climate-based model for future forecasting. Historical time-series data on dengue outbreaks in southern Taiwan from 1998 to 2015 were investigated. Local climate variables were analyzed using a distributed lag non-linear model (DLNM), and the model of best fit was used to predict dengue incidence between 2013 and 2015. The cross-wavelet coherence approach was used to evaluate the regional El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) effects on dengue incidence and local climate variables. The DLNM results highlighted the important non-linear and lag effects of minimum temperature and precipitation. Minimum temperature above 23°C or below 17°C can increase dengue incidence rate with lag effects of 10 to 15 weeks. Moderate to high precipitation can increase dengue incidence rates with a lag of 10 or 20 weeks. The model of best fit successfully predicted dengue transmission between 2013 and 2015. The prediction accuracy ranged from 0.7 to 0.9, depending on the number of weeks ahead of the prediction. ENSO and IOD were associated with nonstationary inter-annual patterns of dengue transmission. IOD had a greater impact on the seasonality of local climate conditions. Our findings suggest that dengue transmission can be affected by regional and local climatic fluctuations in southern Taiwan. The climate-based model developed in this study can provide important information for dengue early warning systems in Taiwan. Local climate conditions might be influenced by ENSO and IOD, to result in unusual dengue outbreaks.

Kinetic analysis of elastomeric lag damper for helicopter rotors

NASA Astrophysics Data System (ADS)

Liu, Yafang; Wang, Jidong; Tong, Yan

2018-02-01

The elastomeric lag dampers suppress the ground resonance and air resonance that play a significant role in the stability of the helicopter. In this paper, elastomeric lag damper which is made from silicone rubber is built. And a series of experiments are conducted on this elastomeric lag damper. The stress-strain curves of elastomeric lag dampers employed shear forces at different frequency are obtained. And a finite element model is established based on Burgers model. The result of simulation and tests shows that the simple, linear model will yield good predictions of damper energy dissipation and it is adequate for predicting the stress-strain hysteresis loop within the operating frequency and a small-amplitude oscillation.

Mean air temperature as a risk factor for stroke mortality in São Paulo, Brazil

NASA Astrophysics Data System (ADS)

Ikefuti, Priscilla V.; Barrozo, Ligia V.; Braga, Alfésio L. F.

2018-05-01

In Brazil, chronic diseases account for the largest percentage of all deaths among men and women. Among the cardiovascular diseases, stroke is the leading cause of death, accounting for 10% of all deaths. We evaluated associations between stroke and mean air temperature using recorded mortality data and meteorological station data from 2002 to 2011. A time series analysis was applied to 55,633 mortality cases. Ischemic and hemorrhagic strokes (IS and HS, respectively) were divided to test different impact on which subgroup. Poisson regression with distributed lag non-linear model was used and adjusted for seasonality, pollutants, humidity, and days of the week. HS mortality was associated with low mean temperatures for men relative risk (RR) = 2.43 (95% CI, 1.12-5.28) and women RR = 1.39 (95% CI, 1.03-1.86). RR of IS mortality was not significant using a 21-day lag window. Analyzing the lag response separately, we observed that the effect of temperature is acute in stroke mortality (higher risk among lags 0-5). However, for IS, higher mean temperatures were significant for this subtype with more than 15-day lag. Our findings showed that mean air temperature is associated with stroke mortality in the city of São Paulo for men and women and IS and HS may have different triggers. Further studies are needed to evaluate physiologic differences between these two subtypes of stroke.

Quantifying the influence of temperature on hand, foot and mouth disease incidence in Wuhan, Central China.

PubMed

Huang, Jiao; Chen, Shi; Wu, Yang; Tong, Yeqing; Wang, Lei; Zhu, Min; Hu, Shuhua; Guan, Xuhua; Wei, Sheng

2018-01-31

Hand, foot and mouth disease (HFMD) is a substantial burden throughout Asia, but the effects of temperature pattern on HFMD risk are inconsistent. To quantify the effect of temperature on HFMD incidence, Wuhan was chosen as the study site because of its high temperature variability and high HFMD incidence. Daily series of HFMD counts and meteorological variables during 2010-2015 were obtained. Distributed lag non-linear models were applied to characterize the temperature-HFMD relationship and to assess its variability across different ages, genders, and types of child care. Totally, 80,219 patients of 0-5 years experienced HFMD in 2010-2015 in Wuhan. The cumulative relative risk of HFMD increased linearly with temperature over 7 days (lag0-7), while it presented as an approximately inverted V-shape over 14 days (lag0-14). The cumulative relative risk at lag0-14 peaked at 26.4 °C with value of 2.78 (95%CI: 2.08-3.72) compared with the 5 th percentile temperature (1.7 °C). Subgroup analyses revealed that children attended daycare were more vulnerable to temperature variation than those cared for at home. This study suggests that public health actions should take into consideration local weather conditions and demographic characteristics.

A critique of the cross-lagged panel model.

PubMed

Hamaker, Ellen L; Kuiper, Rebecca M; Grasman, Raoul P P P

2015-03-01

The cross-lagged panel model (CLPM) is believed by many to overcome the problems associated with the use of cross-lagged correlations as a way to study causal influences in longitudinal panel data. The current article, however, shows that if stability of constructs is to some extent of a trait-like, time-invariant nature, the autoregressive relationships of the CLPM fail to adequately account for this. As a result, the lagged parameters that are obtained with the CLPM do not represent the actual within-person relationships over time, and this may lead to erroneous conclusions regarding the presence, predominance, and sign of causal influences. In this article we present an alternative model that separates the within-person process from stable between-person differences through the inclusion of random intercepts, and we discuss how this model is related to existing structural equation models that include cross-lagged relationships. We derive the analytical relationship between the cross-lagged parameters from the CLPM and the alternative model, and use simulations to demonstrate the spurious results that may arise when using the CLPM to analyze data that include stable, trait-like individual differences. We also present a modeling strategy to avoid this pitfall and illustrate this using an empirical data set. The implications for both existing and future cross-lagged panel research are discussed. (c) 2015 APA, all rights reserved).

Long-Lag, Wide-pulse Gamma-Ray Bursts

NASA Technical Reports Server (NTRS)

Norris, J. P.; Bonnell, J. T.; Kazanas, D.; Scargle, . D.; Hakkila, J.; Giblin, T. W.

2004-01-01

Currently, the best available probe of the early phase of gamma-ray burst (GRB) jet attributes is the prompt gamma-ray emission, in which several intrinsic and extrinsic variables determine GRB pulse evolution. Bright, usually complex bursts have many narrow pulses that are difficult to model due to overlap. However, the relatively simple, long spectral lag, wide-pulse bursts may have simpler physics and are easier to model. In this work we analyze the temporal and spectral behavior of wide pulses in 24 long-lag bursts, using a pulse model with two shape parameters - width and asymmetry - and the Band spectral model with three shape parameters. We find that pulses in long-lag bursts are distinguished both temporally and spectrally from those in bright bursts: the pulses in long spectral lag bursts are few in number, and approximately 100 times wider (10s of seconds), have systematically lower peaks in vF(v), harder low-energy spectra and softer high-energy spectra. We find that these five pulse descriptors are essentially uncorrelated for our long-lag sample, suggesting that at least approximately 5 parameters are needed to model burst temporal and spectral behavior. However, pulse width is strongly correlated with spectral lag; hence these two parameters may be viewed as mutual surrogates. We infer that accurate formulations for estimating GRB luminosity and total energy will depend on several gamma-ray attributes, at least for long-lag bursts. The prevalence of long-lag bursts near the BATSE trigger threshold, their predominantly low vF(v) spectral peaks, and relatively steep upper power-law spectral indices indicate that Swift will detect many such bursts.

The reciprocal relationship between work characteristics and employee burnout and engagement: a longitudinal study of firefighters.

PubMed

Ângelo, R P; Chambel, M J

2015-04-01

The paradigm of this study is positive occupational psychology, with the job demands-resources model as the research model and the Conservation of Resources theory as the general stress theory. The research design analyses the job demands-resources model's dynamic nature with normal and reversed causation effects between work characteristics and psychological well-being among Portuguese firefighters. In addition, we analyse a positive (engagement) dimension and a negative (burnout) dimension in the firefighters' well-being, because previously, studies have merely focused on the strain or stress of these professionals. The research questionnaire was distributed to a sample of 651 firefighters, and a two-wave full panel design was used. Cross-lagged panel analyses indicated that the causal direction of the relationship between organizational demands and burnout is reciprocal. Also, we found that the reciprocal model, including cross-lagged reciprocal relationships between organizational demands/supervisory support and burnout/engagement, respectively, is what fits the data best. Practical implications to develop organizational change programmes and suggestions for future research regarding the promotion of occupational health are discussed. Copyright © 2013 John Wiley & Sons, Ltd.

Comb model for the anomalous diffusion with dual-phase-lag constitutive relation

NASA Astrophysics Data System (ADS)

Liu, Lin; Zheng, Liancun; Fan, Yu; Chen, Yanping; Liu, Fawang

2018-10-01

As a development of the Fick's model, the dual-phase-lag constitutive relationship with macroscopic and microscopic relaxation characteristics is introduced to describe the anomalous diffusion in comb model. The Dirac delta function in the formulated governing equation represents the special spatial structure of comb model that the horizontal current only exists on the x axis. Solutions are obtained by analytical method with Laplace transform and Fourier transform. The dependence of concentration field and mean square displacement on different parameters are presented and discussed. Results show that the macroscopic and microscopic relaxation parameters have opposite effects on the particle distribution and mean square displacement. Furthermore, four significant results with constant 1/2 are concluded, namely the product of the particle number and the mean square displacement on the x axis equals to 1/2, the exponent of mean square displacement is 1/2 at the special case τq= τP, an asymptotic form of mean square displacement (MSD∼t1/2 as t→0, ∞) is obtained as well at the short time behavior and the long time behavior.

Groundwater Pollution Source Identification using Linked ANN-Optimization Model

NASA Astrophysics Data System (ADS)

Ayaz, Md; Srivastava, Rajesh; Jain, Ashu

2014-05-01

Groundwater is the principal source of drinking water in several parts of the world. Contamination of groundwater has become a serious health and environmental problem today. Human activities including industrial and agricultural activities are generally responsible for this contamination. Identification of groundwater pollution source is a major step in groundwater pollution remediation. Complete knowledge of pollution source in terms of its source characteristics is essential to adopt an effective remediation strategy. Groundwater pollution source is said to be identified completely when the source characteristics - location, strength and release period - are known. Identification of unknown groundwater pollution source is an ill-posed inverse problem. It becomes more difficult for real field conditions, when the lag time between the first reading at observation well and the time at which the source becomes active is not known. We developed a linked ANN-Optimization model for complete identification of an unknown groundwater pollution source. The model comprises two parts- an optimization model and an ANN model. Decision variables of linked ANN-Optimization model contain source location and release period of pollution source. An objective function is formulated using the spatial and temporal data of observed and simulated concentrations, and then minimized to identify the pollution source parameters. In the formulation of the objective function, we require the lag time which is not known. An ANN model with one hidden layer is trained using Levenberg-Marquardt algorithm to find the lag time. Different combinations of source locations and release periods are used as inputs and lag time is obtained as the output. Performance of the proposed model is evaluated for two and three dimensional case with error-free and erroneous data. Erroneous data was generated by adding uniformly distributed random error (error level 0-10%) to the analytically computed concentration values. The main advantage of the proposed model is that it requires only upper half of the breakthrough curve and is capable of predicting source parameters when the lag time is not known. Linking of ANN model with proposed optimization model reduces the dimensionality of the decision variables of the optimization model by one and hence complexity of optimization model is reduced. The results show that our proposed linked ANN-Optimization model is able to predict the source parameters for the error-free data accurately. The proposed model was run several times to obtain the mean, standard deviation and interval estimate of the predicted parameters for observations with random measurement errors. It was observed that mean values as predicted by the model were quite close to the exact values. An increasing trend was observed in the standard deviation of the predicted values with increasing level of measurement error. The model appears to be robust and may be efficiently utilized to solve the inverse pollution source identification problem.

Transaction-neutral implanted data collection interface as EMR driver: a model for emerging distributed medical technologies.

PubMed

Lorence, Daniel; Sivaramakrishnan, Anusha; Richards, Michael

2010-08-01

Electronic Medical Record (EMR) and Electronic Health Record (EHR) adoption continues to lag across the US. Cost, inconsistent formats, and concerns about control of patient information are among the most common reasons for non-adoption in physician practice settings. The emergence of wearable and implanted mobile technologies, employed in distributed environments, promises a fundamentally different information infrastructure, which could serve to minimize existing adoption resistance. Proposed here is one technology model for overcoming adoption inconsistency and high organization-specific implementation costs, using seamless, patient controlled data collection. While the conceptual applications employed in this technology set are provided by way of illustration, they may also serve as a transformative model for emerging EMR/EHR requirements.

A model for field toxicity tests

USGS Publications Warehouse

Kaiser, Mark S.; Finger, Susan E.

1996-01-01

Toxicity tests conducted under field conditions present an interesting challenge for statistical modelling. In contrast to laboratory tests, the concentrations of potential toxicants are not held constant over the test. In addition, the number and identity of toxicants that belong in a model as explanatory factors are not known and must be determined through a model selection process. We present one model to deal with these needs. This model takes the record of mortalities to form a multinomial distribution in which parameters are modelled as products of conditional daily survival probabilities. These conditional probabilities are in turn modelled as logistic functions of the explanatory factors. The model incorporates lagged values of the explanatory factors to deal with changes in the pattern of mortalities over time. The issue of model selection and assessment is approached through the use of generalized information criteria and power divergence goodness-of-fit tests. These model selection criteria are applied in a cross-validation scheme designed to assess the ability of a model to both fit data used in estimation and predict data deleted from the estimation data set. The example presented demonstrates the need for inclusion of lagged values of the explanatory factors and suggests that penalized likelihood criteria may not provide adequate protection against overparameterized models in model selection.

Comparing lagged linear correlation, lagged regression, Granger causality, and vector autoregression for uncovering associations in EHR data.

PubMed

Levine, Matthew E; Albers, David J; Hripcsak, George

2016-01-01

Time series analysis methods have been shown to reveal clinical and biological associations in data collected in the electronic health record. We wish to develop reliable high-throughput methods for identifying adverse drug effects that are easy to implement and produce readily interpretable results. To move toward this goal, we used univariate and multivariate lagged regression models to investigate associations between twenty pairs of drug orders and laboratory measurements. Multivariate lagged regression models exhibited higher sensitivity and specificity than univariate lagged regression in the 20 examples, and incorporating autoregressive terms for labs and drugs produced more robust signals in cases of known associations among the 20 example pairings. Moreover, including inpatient admission terms in the model attenuated the signals for some cases of unlikely associations, demonstrating how multivariate lagged regression models' explicit handling of context-based variables can provide a simple way to probe for health-care processes that confound analyses of EHR data.

A spatiotemporal dengue fever early warning model accounting for nonlinear associations with meteorological factors: a Bayesian maximum entropy approach

NASA Astrophysics Data System (ADS)

Lee, Chieh-Han; Yu, Hwa-Lung; Chien, Lung-Chang

2014-05-01

Dengue fever has been identified as one of the most widespread vector-borne diseases in tropical and sub-tropical. In the last decade, dengue is an emerging infectious disease epidemic in Taiwan especially in the southern area where have annually high incidences. For the purpose of disease prevention and control, an early warning system is urgently needed. Previous studies have showed significant relationships between climate variables, in particular, rainfall and temperature, and the temporal epidemic patterns of dengue cases. However, the transmission of the dengue fever is a complex interactive process that mostly understated the composite space-time effects of dengue fever. This study proposes developing a one-week ahead warning system of dengue fever epidemics in the southern Taiwan that considered nonlinear associations between weekly dengue cases and meteorological factors across space and time. The early warning system based on an integration of distributed lag nonlinear model (DLNM) and stochastic Bayesian Maximum Entropy (BME) analysis. The study identified the most significant meteorological measures including weekly minimum temperature and maximum 24-hour rainfall with continuous 15-week lagged time to dengue cases variation under condition of uncertainty. Subsequently, the combination of nonlinear lagged effects of climate variables and space-time dependence function is implemented via a Bayesian framework to predict dengue fever occurrences in the southern Taiwan during 2012. The result shows the early warning system is useful for providing potential outbreak spatio-temporal prediction of dengue fever distribution. In conclusion, the proposed approach can provide a practical disease control tool for environmental regulators seeking more effective strategies for dengue fever prevention.

[Relationship between sulfur dioxide pollution and upper respiratory outpatients in Jiangbei, Ningbo].

PubMed

Wu, Yifeng; Zhao, Fengmin; Qian, Xujun; Xu, Guozhang; He, Tianfeng; Shen, Yueping; Cai, Yibiao

2015-07-01

To describe the daily average concentration of sulfur dioxide (SO2) in Ningbo, and to analysis the health impacts it caused in upper respiratory disease. With outpatients log and air pollutants monitoring data matched in 2011-2013, the distributed lag non-linear models were used to analysis the relative risk of the number of upper respiratory patients associated with SO2, and also excessive risk, and the inferred number of patients due to SO2 pollution. The daily average concentration of SO2 didn't exceed the limit value of second class area. The coefficient of upper respiratory outpatient number and daily average concentration of SO2 matched was 0.44,with the excessive risk was 10% to 18%, the lag of most SO2 concentrations was 4 to 6 days. It could be estimated that about 30% of total upper respiratory outpatients were caused by SO2 pollution. Although the daily average concentration of SO2 didn't exceed the standard in 3 years, the health impacts still be caused with lag effect.

Collective Dynamics of Oscillator Networks: Why do we suffer from heavy jet lag?

NASA Astrophysics Data System (ADS)

Kori, Hiroshi

The circadian rhythm of the entire body in mammals is orchestrated by a small tissue in the brain called the suprachiamatic nucleus (SCN). The SCN consists of a population of neurons, each of which exhibit circadian (i.e., approximately 24 h) gene expression. Neurons form a complex network and interact with each other using various types of neurotransmitters. The rhythmic gene expressions of individual cells in the SCN synchronize through such interaction. Jet-lag symptoms arise from temporal mismatch between the internal circadian clock orchestrated by the SCN and external solar time. It may take about one week or even longer to recover from jet lag after a long-distance trip. We recently found that recovery from jet lag is considerably accelerated in the knocked-out (KO) mice lacking the receptors of a certain neurotransmitter in the SCN. Importantly, all other properties of mice including sleep-awake rhythms and breeding seem to be intact. Only the response to the jet lag changes. It was also found that after a few days of jet lag, cells in the SCN desynchronize in the wild type (WT) mice, whereas they do not in KO mice. This desynchrony might be a main reason for heavy jet lag symptoms. To understand the mechanism underlying jet lag, we propose a simple model of the SCN, which is a network of phase oscillators. Despite its simplicity, this model can reproduce important dynamical properties of the SCN. For example, this model reproduces the desynchrony of oscillators after jet lag. Moreover, when intercellular interaction is weaker, this desynchrony is suppressed and the recover from jet lag is considerably accelerated. Our mathematical study provides a deeper understanding of jet lag and an idea how to circumvent heavy jet lag symptoms

Association of short-term exposure to ground-level ozone and respiratory outpatient clinic visits in a rural location – Sublette County, Wyoming, 2008–2011

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pride, Kerry R., E-mail: hgp3@cdc.gov; Wyoming Department of Health, 6101 Yellowstone Road, Suite 510, Cheyenne, WY 82002; Peel, Jennifer L.

Objective: Short-term exposure to ground-level ozone has been linked to adverse respiratory and other health effects; previous studies typically have focused on summer ground-level ozone in urban areas. During 2008–2011, Sublette County, Wyoming (population: ~10,000 persons), experienced periods of elevated ground-level ozone concentrations during the winter. This study sought to evaluate the association of daily ground-level ozone concentrations and health clinic visits for respiratory disease in this rural county. Methods: Clinic visits for respiratory disease were ascertained from electronic billing records of the two clinics in Sublette County for January 1, 2008–December 31, 2011. A time-stratified case-crossover design, adjusted formore » temperature and humidity, was used to investigate associations between ground-level ozone concentrations measured at one station and clinic visits for a respiratory health concern by using an unconstrained distributed lag of 0–3 days and single-day lags of 0 day, 1 day, 2 days, and 3 days. Results: The data set included 12,742 case-days and 43,285 selected control-days. The mean ground-level ozone observed was 47±8 ppb. The unconstrained distributed lag of 0–3 days was consistent with a null association (adjusted odds ratio [aOR]: 1.001; 95% confidence interval [CI]: 0.990–1.012); results for lags 0, 2, and 3 days were consistent with the null. However, the results for lag 1 were indicative of a positive association; for every 10-ppb increase in the 8-h maximum average ground-level ozone, a 3.0% increase in respiratory clinic visits the following day was observed (aOR: 1.031; 95% CI: 0.994–1.069). Season modified the adverse respiratory effects: ground-level ozone was significantly associated with respiratory clinic visits during the winter months. The patterns of results from all sensitivity analyzes were consistent with the a priori model. Conclusions: The results demonstrate an association of increasing ground-level ozone with an increase in clinic visits for adverse respiratory-related effects in the following day (lag day 1) in Sublette County; the magnitude was strongest during the winter months; this association during the winter months in a rural location warrants further investigation. - Highlights: • We assessed elevated ground-level ozone in frontier Sublette County, Wyoming. • Ground-level ozone concentrations were moderately to highly correlated between stations. • Adverse respiratory-related clinic visits occurred year round at lag 1. • Strongest association of clinic visits was in the coldest months at lag 1.« less

Modeling emission lag after photoexcitation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jensen, Kevin L.; Petillo, John J.; Ovtchinnikov, Serguei

A theoretical model of delayed emission following photoexcitation from metals and semiconductors is given. Its numerical implementation is designed for beam optics codes used to model photocathodes in rf photoinjectors. The model extends the Moments approach for predicting photocurrent and mean transverse energy as moments of an emitted electron distribution by incorporating time of flight and scattering events that result in emission delay on a sub-picosecond level. The model accounts for a dynamic surface extraction field and changes in the energy distribution and time of emission as a consequence of the laser penetration depth and multiple scattering events during transport.more » Usage in the Particle-in-Cell code MICHELLE to predict the bunch shape and duration with or without laser jitter is given. The consequences of delayed emission effects for ultra-short pulses are discussed.« less

Modeling emission lag after photoexcitation

DOE PAGES

Jensen, Kevin L.; Petillo, John J.; Ovtchinnikov, Serguei; ...

2017-10-28

A theoretical model of delayed emission following photoexcitation from metals and semiconductors is given. Its numerical implementation is designed for beam optics codes used to model photocathodes in rf photoinjectors. The model extends the Moments approach for predicting photocurrent and mean transverse energy as moments of an emitted electron distribution by incorporating time of flight and scattering events that result in emission delay on a sub-picosecond level. The model accounts for a dynamic surface extraction field and changes in the energy distribution and time of emission as a consequence of the laser penetration depth and multiple scattering events during transport.more » Usage in the Particle-in-Cell code MICHELLE to predict the bunch shape and duration with or without laser jitter is given. The consequences of delayed emission effects for ultra-short pulses are discussed.« less

A lagged variable model for characterizing temporally dynamic export of legacy anthropogenic nitrogen from watersheds to rivers.

PubMed

Chen, Dingjiang; Guo, Yi; Hu, Minpeng; Dahlgren, Randy A

2015-08-01

Legacy nitrogen (N) sources originating from anthropogenic N inputs (NANI) may be a major cause of increasing riverine N exports in many regions, despite a significant decline in NANI. However, little quantitative knowledge exists concerning the lag effect of NANI on riverine N export. As a result, the N leaching lag effect is not well represented in most current watershed models. This study developed a lagged variable model (LVM) to address temporally dynamic export of watershed NANI to rivers. Employing a Koyck transformation approach used in economic analyses, the LVM expresses the indefinite number of lag terms from previous years' NANI with a lag term that incorporates the previous year's riverine N flux, enabling us to inversely calibrate model parameters from measurable variables using Bayesian statistics. Applying the LVM to the upper Jiaojiang watershed in eastern China for 1980-2010 indicated that ~97% of riverine export of annual NANI occurred in the current year and succeeding 10 years (~11 years lag time) and ~72% of annual riverine N flux was derived from previous years' NANI. Existing NANI over the 1993-2010 period would have required a 22% reduction to attain the target TN level (1.0 mg N L(-1)), guiding watershed N source controls considering the lag effect. The LVM was developed with parsimony of model structure and parameters (only four parameters in this study); thus, it is easy to develop and apply in other watersheds. The LVM provides a simple and effective tool for quantifying the lag effect of anthropogenic N input on riverine export in support of efficient development and evaluation of watershed N control strategies.

Analysis on flood generation processes by means of a continuous simulation model

NASA Astrophysics Data System (ADS)

Fiorentino, M.; Gioia, A.; Iacobellis, V.; Manfreda, S.

2006-03-01

In the present research, we exploited a continuous hydrological simulation to investigate on key variables responsible of flood peak formation. With this purpose, a distributed hydrological model (DREAM) is used in cascade with a rainfall generator (IRP-Iterated Random Pulse) to simulate a large number of extreme events providing insight into the main controls of flood generation mechanisms. Investigated variables are those used in theoretically derived probability distribution of floods based on the concept of partial contributing area (e.g. Iacobellis and Fiorentino, 2000). The continuous simulation model is used to investigate on the hydrological losses occurring during extreme events, the variability of the source area contributing to the flood peak and its lag-time. Results suggest interesting simplification for the theoretical probability distribution of floods according to the different climatic and geomorfologic environments. The study is applied to two basins located in Southern Italy with different climatic characteristics.

Hierarchical Distributed-Lag Models: Exploring Varying Geographic Scale and Magnitude in Associations Between the Built Environment and Health

PubMed Central

Baek, Jonggyu; Sanchez-Vaznaugh, Emma V.; Sánchez, Brisa N.

2016-01-01

It is well known that associations between features of the built environment and health depend on the geographic scale used to construct environmental attributes. In the built environment literature, it has long been argued that geographic scales may vary across study locations. However, this hypothesized variation has not been systematically examined due to a lack of available statistical methods. We propose a hierarchical distributed-lag model (HDLM) for estimating the underlying overall shape of food environment–health associations as a function of distance from locations of interest. This method enables indirect assessment of relevant geographic scales and captures area-level heterogeneity in the magnitudes of associations, along with relevant distances within areas. The proposed model was used to systematically examine area-level variation in the association between availability of convenience stores around schools and children's weights. For this case study, body mass index (weight kg)/height (m)2) z scores (BMIz) for 7th grade children collected via California's 2001–2009 FitnessGram testing program were linked to a commercial database that contained locations of food outlets statewide. Findings suggested that convenience store availability may influence BMIz only in some places and at varying distances from schools. Future research should examine localized environmental or policy differences that may explain the heterogeneity in convenience store–BMIz associations. PMID:26888753

Modeling zoonotic cutaneous leishmaniasis incidence in central Tunisia from 2009-2015: Forecasting models using climate variables as predictors

PubMed Central

Bellali, Hedia; Ben-Alaya, Nissaf; Saez, Marc; Malouche, Dhafer; Chahed, Mohamed Kouni

2017-01-01

Transmission of zoonotic cutaneous leishmaniasis (ZCL) depends on the presence, density and distribution of Leishmania major rodent reservoir and the development of these rodents is known to have a significant dependence on environmental and climate factors. ZCL in Tunisia is one of the most common forms of leishmaniasis. The aim of this paper was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Monthly reported ZCL cases, environmental and bioclimatic data were collected over 6 years (2009–2015). Three rural areas in the governorate of Sidi Bouzid were selected as the study area. Cross-correlation analysis was used to identify the relevant lagged effects of possible risk factors, associated with ZCL cases. Non-parametric modeling techniques known as generalized additive model (GAM) and generalized additive mixed models (GAMM) were applied in this work. These techniques have the ability to approximate the relationship between the predictors (inputs) and the response variable (output), and express the relationship mathematically. The goodness-of-fit of the constructed model was determined by Generalized cross-validation (GCV) score and residual test. There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The results showed seasonal distribution of reported ZCL cases from August to January. The model highlighted that rodent density, average temperature, cumulative rainfall and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence. The GAMM model could be applied to predict the occurrence of ZCL in central Tunisia and could help for the establishment of an early warning system to control and prevent ZCL in central Tunisia. PMID:28841642

Modeling zoonotic cutaneous leishmaniasis incidence in central Tunisia from 2009-2015: Forecasting models using climate variables as predictors.

PubMed

Talmoudi, Khouloud; Bellali, Hedia; Ben-Alaya, Nissaf; Saez, Marc; Malouche, Dhafer; Chahed, Mohamed Kouni

2017-08-01

Transmission of zoonotic cutaneous leishmaniasis (ZCL) depends on the presence, density and distribution of Leishmania major rodent reservoir and the development of these rodents is known to have a significant dependence on environmental and climate factors. ZCL in Tunisia is one of the most common forms of leishmaniasis. The aim of this paper was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Monthly reported ZCL cases, environmental and bioclimatic data were collected over 6 years (2009-2015). Three rural areas in the governorate of Sidi Bouzid were selected as the study area. Cross-correlation analysis was used to identify the relevant lagged effects of possible risk factors, associated with ZCL cases. Non-parametric modeling techniques known as generalized additive model (GAM) and generalized additive mixed models (GAMM) were applied in this work. These techniques have the ability to approximate the relationship between the predictors (inputs) and the response variable (output), and express the relationship mathematically. The goodness-of-fit of the constructed model was determined by Generalized cross-validation (GCV) score and residual test. There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The results showed seasonal distribution of reported ZCL cases from August to January. The model highlighted that rodent density, average temperature, cumulative rainfall and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence. The GAMM model could be applied to predict the occurrence of ZCL in central Tunisia and could help for the establishment of an early warning system to control and prevent ZCL in central Tunisia.

Impacts of temperature change on ambulance dispatches and seasonal effect modification.

PubMed

Cheng, Jian; Xu, Zhiwei; Zhao, Desheng; Xie, Mingyu; Yang, Huihui; Wen, Liying; Li, Kesheng; Su, Hong

2016-12-01

Ambulance dispatch is a proxy of acute health outcomes, and growing epidemiological evidence documented its relation to extreme temperature events. Research, however, on short-term temperature change and ambulance dispatches is scarce. We aimed to investigate the effect of short-term temperature change on ambulance dispatches and potential modification by season. Daily data on ambulance dispatch and weather factors were collected in Huainan, a Chinese inland city from December 2011 through December 2013. A Poison generalized linear regression model combined with distributed lag nonlinear model was constructed to examine the association of temperature change between neighboring days (TCN) with ambulance dispatches. The effect modification by season was also examined. There were 48,700 ambulance attendances during the study period. A statistically significant association of TCN with ambulance dispatches was observed. Temperature rise between neighboring days (TCN > 0) was associated with elevated adverse risk of ambulance dispatches, and the effects appeared to be acute (lag0, on the current day) and could last for at least a week, while temperature drop between neighboring days (TCN < 0) had a protective effect. For a 1 °C increase of TCN at lag0 and lag06 (on the 7-day moving average), the risk of ambulance dispatches increased by 2 % (95 % CI 1-3 %) and 7 (95 % CI 1-13 %), respectively. Extreme TCN increase (95th percentile, 3.3 °C vs. 0 °C) at lag0 and lag05 was accompanied by 6 (95 % CI 3-8 %) and 27 % (95 % CI 12-44 %) increase in ambulance dispatches. Ambulance dispatches were more vulnerable to extremely great temperature rise in summer and autumn. TCN was adopted for the first time to quantify the impact of short-term temperature change on ambulance dispatches. Temperature drop between neighboring days (TCN < 0) had a protective effect on ambulance dispatches, while temperature rise between neighboring days (TCN > 0) could acutely trigger the increase in ambulance dispatches, and TCN effect differs by season.

Lag Times and Peak Coefficients for Rural Watersheds in Kansas

DOT National Transportation Integrated Search

1999-10-01

Lag time is an essential input to the most common synthetic unit-hydrograph models. The lag time for an ungaged stream must be estimated from the physical characteristics of the stream and its watershed. In this study, a lag-time formula for small ru...

Seasonal modeling of hand, foot, and mouth disease as a function of meteorological variations in Chongqing, China

NASA Astrophysics Data System (ADS)

Wang, Pin; Zhao, Han; You, Fangxin; Zhou, Hailong; Goggins, William B.

2017-08-01

Hand, foot, and mouth disease (HFMD) is an enterovirus-induced infectious disease, mainly affecting children under 5 years old. Outbreaks of HFMD in recent years indicate the disease interacts with both the weather and season. This study aimed to investigate the seasonal association between HFMD and weather variation in Chongqing, China. Generalized additive models and distributed lag non-linear models based on a maximum lag of 14 days, with negative binomial distribution assumed to account for overdispersion, were constructed to model the association between reporting HFMD cases from 2009 to 2014 and daily mean temperature, relative humidity, total rainfall and sun duration, adjusting for trend, season, and day of the week. The year-round temperature and relative humidity, rainfall in summer, and sun duration in winter were all significantly associated with HFMD. An inverted-U relationship was found between mean temperature and HFMD above 19 °C in summer, with a maximum morbidity at 27 °C, while the risk increased linearly with the temperature in winter. A hockey-stick association was found for relative humidity in summer with increasing risks over 60%. Heavy rainfall, relative to no rain, was found to be associated with reduced HFMD risk in summer and 2 h of sunshine could decrease the risk by 21% in winter. The present study showed meteorological variables were differentially associated with HFMD incidence in two seasons. Short-term weather variation surveillance and forecasting could be employed as an early indicator for potential HFMD outbreaks.

Woody plants and the prediction of climate-change impacts on bird diversity.

PubMed

Kissling, W D; Field, R; Korntheuer, H; Heyder, U; Böhning-Gaese, K

2010-07-12

Current methods of assessing climate-induced shifts of species distributions rarely account for species interactions and usually ignore potential differences in response times of interacting taxa to climate change. Here, we used species-richness data from 1005 breeding bird and 1417 woody plant species in Kenya and employed model-averaged coefficients from regression models and median climatic forecasts assembled across 15 climate-change scenarios to predict bird species richness under climate change. Forecasts assuming an instantaneous response of woody plants and birds to climate change suggested increases in future bird species richness across most of Kenya whereas forecasts assuming strongly lagged woody plant responses to climate change indicated a reversed trend, i.e. reduced bird species richness. Uncertainties in predictions of future bird species richness were geographically structured, mainly owing to uncertainties in projected precipitation changes. We conclude that assessments of future species responses to climate change are very sensitive to current uncertainties in regional climate-change projections, and to the inclusion or not of time-lagged interacting taxa. We expect even stronger effects for more specialized plant-animal associations. Given the slow response time of woody plant distributions to climate change, current estimates of future biodiversity of many animal taxa may be both biased and too optimistic.

Epidemiological features and risk factors associated with the spatial and temporal distribution of human brucellosis in China

PubMed Central

2013-01-01

Background Human brucellosis incidence in China has been increasing dramatically since 1999. However, epidemiological features and potential factors underlying the re-emergence of the disease remain less understood. Methods Data on human and animal brucellosis cases at the county scale were collected for the year 2004 to 2010. Also collected were environmental and socioeconomic variables. Epidemiological features including spatial and temporal patterns of the disease were characterized, and the potential factors related to the spatial heterogeneity and the temporal trend of were analysed using Poisson regression analysis, Granger causality analysis, and autoregressive distributed lag (ADL) models, respectively. Results The epidemic showed a significantly higher spatial correlation with the number of sheep and goats than swine and cattle. The disease was most prevalent in grassland areas with elevation between 800–1,600 meters. The ADL models revealed that local epidemics were correlated with comparatively lower temperatures and less sunshine in winter and spring, with a 1–7 month lag before the epidemic peak in May. Conclusions Our findings indicate that human brucellosis tended to occur most commonly in grasslands at moderate elevation where sheep and goats were the predominant livestock, and in years with cooler winter and spring or less sunshine. PMID:24238301

The Short-Term Effect of Ambient Temperature on Mortality in Wuhan, China: A Time-Series Study Using a Distributed Lag Non-Linear Model

PubMed Central

Zhang, Yunquan; Li, Cunlu; Feng, Renjie; Zhu, Yaohui; Wu, Kai; Tan, Xiaodong; Ma, Lu

2016-01-01

Less evidence concerning the association between ambient temperature and mortality is available in developing countries/regions, especially inland areas of China, and few previous studies have compared the predictive ability of different temperature indictors (minimum, mean, and maximum temperature) on mortality. We assessed the effects of temperature on daily mortality from 2003 to 2010 in Jiang’an District of Wuhan, the largest city in central China. Quasi-Poisson generalized linear models combined with both non-threshold and double-threshold distributed lag non-linear models (DLNM) were used to examine the associations between different temperature indictors and cause-specific mortality. We found a U-shaped relationship between temperature and mortality in Wuhan. Double-threshold DLNM with mean temperature performed best in predicting temperature-mortality relationship. Cold effect was delayed, whereas hot effect was acute, both of which lasted for several days. For cold effects over lag 0–21 days, a 1 °C decrease in mean temperature below the cold thresholds was associated with a 2.39% (95% CI: 1.71, 3.08) increase in non-accidental mortality, 3.65% (95% CI: 2.62, 4.69) increase in cardiovascular mortality, 3.87% (95% CI: 1.57, 6.22) increase in respiratory mortality, 3.13% (95% CI: 1.88, 4.38) increase in stroke mortality, and 21.57% (95% CI: 12.59, 31.26) increase in ischemic heart disease (IHD) mortality. For hot effects over lag 0–7 days, a 1 °C increase in mean temperature above the hot thresholds was associated with a 25.18% (95% CI: 18.74, 31.96) increase in non-accidental mortality, 34.10% (95% CI: 25.63, 43.16) increase in cardiovascular mortality, 24.27% (95% CI: 7.55, 43.59) increase in respiratory mortality, 59.1% (95% CI: 41.81, 78.5) increase in stroke mortality, and 17.00% (95% CI: 7.91, 26.87) increase in IHD mortality. This study suggested that both low and high temperature were associated with increased mortality in Wuhan, and that mean temperature had better predictive ability than minimum and maximum temperature in the association between temperature and mortality. PMID:27438847

Gamma-Ray Bursts and Cosmology

NASA Technical Reports Server (NTRS)

Norris, Jay P.

2003-01-01

The unrivalled, extreme luminosities of gamma-ray bursts (GRBs) make them the favored beacons for sampling the high redshift Universe. To employ GRBs to study the cosmic terrain -- e.g., star and galaxy formation history -- GRB luminosities must be calibrated, and the luminosity function versus redshift must be measured or inferred. Several nascent relationships between gamma-ray temporal or spectral indicators and luminosity or total energy have been reported. These measures promise to further our understanding of GRBs once the connections between the luminosity indicators and GRB jets and emission mechanisms are better elucidated. The current distribution of 33 redshifts determined from host galaxies and afterglows peaks near z $\\sim$ 1, whereas for the full BATSE sample of long bursts, the lag-luminosity relation predicts a broad peak z $\\sim$ 1--4 with a tail to z $\\sim$ 20, in rough agreement with theoretical models based on star formation considerations. For some GRB subclasses and apparently related phenomena -- short bursts, long-lag bursts, and X-ray flashes -- the present information on their redshift distributions is sparse or entirely lacking, and progress is expected in Swift era when prompt alerts become numerous.

Global climate change: impact of diurnal temperature range on mortality in Guangzhou, China.

PubMed

Yang, Jun; Liu, Hua-Zhang; Ou, Chun-Quan; Lin, Guo-Zhen; Zhou, Qin; Shen, Gi-Chuan; Chen, Ping-Yan; Guo, Yuming

2013-04-01

Diurnal temperature range (DTR) is an important meteorological indicator associated with global climate change, but little is known about the effects of DTR on mortality. We examined the effects of DTR on cause-/age-/education-specific mortality in Guangzhou, a subtropical city in China during 2003-2010. A quasi-Poisson regression model combined with distributed lag non-linear model was used to examine the effects of DTR, after controlling for daily mean temperature, air pollutants, season and day of the week. A 1 °C increase in DTR at lag 0-4 days was associated with a 0.47% (95% confidence interval: 0.01%-0.93%) increase in non-accidental mortality. Stroke mortality was most sensitive to DTR. Female, the elderly and those with low education were more susceptible to DTR than male, the youth and those with high education, respectively. Our findings suggest that vulnerable subpopulations should pay more attention to protect themselves from unstable daily weather. Copyright © 2012 Elsevier Ltd. All rights reserved.

Haze is an important medium for the spread of rotavirus.

PubMed

Ye, Qing; Fu, Jun-Feng; Mao, Jian-Hua; Shen, Hong-Qiang; Chen, Xue-Jun; Shao, Wen-Xia; Shang, Shi-Qiang; Wu, Yi-Feng

2016-09-01

This study investigated whether the rotavirus infection rate in children is associated with temperature and air pollutants in Hangzhou, China. This study applied a distributed lag non-linear model (DLNM) to assess the effects of daily meteorological data and air pollutants on the rotavirus positive rate among outpatient children. There was a negative correlation between temperature and the rotavirus infection rate. The impact of temperature on the detection rate of rotavirus presented an evident lag effect, the temperature change shows the greatest impact on the detection rate of rotavirus approximate at lag one day, and the maximum relative risk (RR) was approximately 1.3. In 2015, the maximum cumulative RR due to the cumulative effect caused by the temperature drop was 2.5. Particulate matter (PM) 2.5 and PM10 were the primary air pollutants in Hangzhou. The highest RR of rotavirus infection occurred at lag 1-1.5 days after the increase in the concentration of these pollutants, and the RR increased gradually with the increase in concentration. Based on the average concentrations of PM2.5 of 53.9 μg/m(3) and PM10 of 80.6 μg/m(3) in Hangzhou in 2015, the cumulative RR caused by the cumulative effect was 2.5 and 2.2, respectively. The current study suggests that temperature is an important factor impacting the rotavirus infection rate of children in Hangzhou. Air pollutants significantly increased the risk of rotavirus infection, and dosage, lag and cumulative effects were observed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Competency criteria and the class inclusion task: modeling judgments and justifications.

PubMed

Thomas, H; Horton, J J

1997-11-01

Preschool age children's class inclusion task responses were modeled as mixtures of different probability distributions. The main idea: Different response strategies are equivalent to different probability distributions. A child displays cognitive strategy s if P (child uses strategy s, given the child's observed score X = x) = p(s) is the most probable strategy. The general approach is widely applicable to many settings. Both judgment and justification questions were asked. Judgment response strategies identified were subclass comparison, guessing, and inclusion logic. Children's justifications lagged their judgments in development. Although justification responses may be useful, C. J. Brainerd was largely correct: If a single response variable is to be selected, a judgments variable is likely the preferable one. But the process must be modeled to identify cognitive strategies, as B. Hodkin has demonstrated.

Chromosome behaviour in Rhoeo spathacea var. variegata.

PubMed

Lin, Y J

1980-01-01

Rhoeo spathacea var. variegata is unusual in that its twelve chromosomes are arranged in a ring at meiosis. The order of the chromosomes has been established, and each chromosome arm has been designated a letter in accordance with the segmental interchange theory. Chromosomes are often irregularly orientated at metaphase I. Chromosomes at anaphase I are generally distributed equally (6-6, 58.75%) although not necessarily balanced. Due to adjacent distribution, 7-5 distribution at anaphase I was frequently observed (24.17%), and due to lagging, 6-1-5 and 5-2-5 distributions were also observed (10.83% and 3.33% respectively). Three types of abnormal distribution, 8-4, 7-1-4 and 6-2-4 were observed very infrequently (2.92% total), and their possible origins are discussed. Irregularities, such as adjacent distribution and lagging, undoubtedly reduce the fertility of the plant because of the resulting unbalanced gametes.

Testing ground for fluctuation theorems: The one-dimensional Ising model

NASA Astrophysics Data System (ADS)

Lemos, C. G. O.; Santos, M.; Ferreira, A. L.; Figueiredo, W.

2018-04-01

In this paper we determine the nonequilibrium magnetic work performed on a Ising model and relate it to the fluctuation theorem derived some years ago by Jarzynski. The basic idea behind this theorem is the relationship connecting the free energy difference between two thermodynamic states of a system and the average work performed by an external agent, in a finite time, through nonequilibrium paths between the same thermodynamic states. We test the validity of this theorem by considering the one-dimensional Ising model where the free energy is exactly determined as a function of temperature and magnetic field. We have found that the Jarzynski theorem remains valid for all the values of the rate of variation of the magnetic field applied to the system. We have also determined the probability distribution function for the work performed on the system for the forward and reverse processes and verified that predictions based on the Crooks relation are equally correct. We also propose a method to calculate the lag between the current state of the system and that of the equilibrium based on macroscopic variables. We have shown that the lag increases with the sweeping rate of the field at its final value for the reverse process, while it decreases in the case of the forward process. The lag increases linearly with the size of the chain and with a slope decreasing with the inverse of the rate of variation of the field.

The attentional blink reveals serial working memory encoding: evidence from virtual and human event-related potentials.

PubMed

Craston, Patrick; Wyble, Brad; Chennu, Srivas; Bowman, Howard

2009-03-01

Observers often miss a second target (T2) if it follows an identified first target item (T1) within half a second in rapid serial visual presentation (RSVP), a finding termed the attentional blink. If two targets are presented in immediate succession, however, accuracy is excellent (Lag 1 sparing). The resource sharing hypothesis proposes a dynamic distribution of resources over a time span of up to 600 msec during the attentional blink. In contrast, the ST(2) model argues that working memory encoding is serial during the attentional blink and that, due to joint consolidation, Lag 1 is the only case where resources are shared. Experiment 1 investigates the P3 ERP component evoked by targets in RSVP. The results suggest that, in this context, P3 amplitude is an indication of bottom-up strength rather than a measure of cognitive resource allocation. Experiment 2, employing a two-target paradigm, suggests that T1 consolidation is not affected by the presentation of T2 during the attentional blink. However, if targets are presented in immediate succession (Lag 1 sparing), they are jointly encoded into working memory. We use the ST(2) model's neural network implementation, which replicates a range of behavioral results related to the attentional blink, to generate "virtual ERPs" by summing across activation traces. We compare virtual to human ERPs and show how the results suggest a serial nature of working memory encoding as implied by the ST(2) model.

Surveillance on the endemic of Zika virus infection by meteorological factors in Colombia: a population-based spatial and temporal study.

PubMed

Chien, Lung-Chang; Lin, Ro-Ting; Liao, Yunqi; Sy, Francisco S; Pérez, Adriana

2018-04-17

Zika virus (ZIKV) infection is a pandemic and a public health emergency. It is transmitted by mosquitoes, primarily the Aedes genus. In light of no treatment currently, it is crucial to develop effective vector control programs to prevent the spread of ZIKV infection earlier when observing possible risk factors, such as weather conditions enhancing mosquito breeding and surviving. This study collected daily meteorological measurements and weekly ZIKV infectious cases among 32 departments of Colombia from January 2015-December 2016. This study applied the distributed lag nonlinear model to estimate the association between the number of ZIKA virus infection and meteorological measurements, controlling for spatial and temporal variations. We examined at most three meteorological factors with 20 lags in weeks in the model. Average humidity, total rainfall, and maximum temperature were more predictable of ZIKV infection outbreaks than other meteorological factors. Our models can detect significantly lagged effects of average humidity, total rainfall, and maximum temperature on outbreaks up to 15, 14, and 20 weeks, respectively. The spatial analysis identified 12 departments with a significant threat of ZIKV, and eight of those high-risk departments were located between the Equator and 6°N. The outbreak prediction also performed well in identified high-risk departments. Our results demonstrate that meteorological factors could be used for predicting ZIKV epidemics. Building an early warning surveillance system is important for preventing ZIKV infection, particularly in endemic areas.

Finite element model predictions of static deformation from dislocation sources in a subduction zone: Sensitivities to homogeneous, isotropic, Poisson-solid, and half-space assumptions

USGS Publications Warehouse

Masterlark, Timothy

2003-01-01

Dislocation models can simulate static deformation caused by slip along a fault. These models usually take the form of a dislocation embedded in a homogeneous, isotropic, Poisson-solid half-space (HIPSHS). However, the widely accepted HIPSHS assumptions poorly approximate subduction zone systems of converging oceanic and continental crust. This study uses three-dimensional finite element models (FEMs) that allow for any combination (including none) of the HIPSHS assumptions to compute synthetic Green's functions for displacement. Using the 1995 Mw = 8.0 Jalisco-Colima, Mexico, subduction zone earthquake and associated measurements from a nearby GPS array as an example, FEM-generated synthetic Green's functions are combined with standard linear inverse methods to estimate dislocation distributions along the subduction interface. Loading a forward HIPSHS model with dislocation distributions, estimated from FEMs that sequentially relax the HIPSHS assumptions, yields the sensitivity of predicted displacements to each of the HIPSHS assumptions. For the subduction zone models tested and the specific field situation considered, sensitivities to the individual Poisson-solid, isotropy, and homogeneity assumptions can be substantially greater than GPS. measurement uncertainties. Forward modeling quantifies stress coupling between the Mw = 8.0 earthquake and a nearby Mw = 6.3 earthquake that occurred 63 days later. Coulomb stress changes predicted from static HIPSHS models cannot account for the 63-day lag time between events. Alternatively, an FEM that includes a poroelastic oceanic crust, which allows for postseismic pore fluid pressure recovery, can account for the lag time. The pore fluid pressure recovery rate puts an upper limit of 10-17 m2 on the bulk permeability of the oceanic crust. Copyright 2003 by the American Geophysical Union.

Four-Year Cross-Lagged Associations between Physical and Mental Health in the Medical Outcomes Study.

ERIC Educational Resources Information Center

Hays, Ron D.; And Others

1994-01-01

Applied structural equation modeling to evaluation of cross-lagged panel models. Self-reports of physical and mental health at three time points spanning four-year interval were analyzed to illustrate cross-lagged analysis methodology. Data were analyzed from 856 patients with hypertension, diabetes, heart disease, or depression. Cross-lagged…

The Association between Dust Storms and Daily Non-Accidental Mortality in the United States, 1993–2005

PubMed Central

Crooks, James Lewis; Cascio, Wayne E.; Percy, Madelyn S.; Reyes, Jeanette; Neas, Lucas M.; Hilborn, Elizabeth D.

2016-01-01

Background: The impact of dust storms on human health has been studied in the context of Asian, Saharan, Arabian, and Australian storms, but there has been no recent population-level epidemiological research on the dust storms in North America. The relevance of dust storms to public health is likely to increase as extreme weather events are predicted to become more frequent with anticipated changes in climate through the 21st century. Objectives: We examined the association between dust storms and county-level non-accidental mortality in the United States from 1993 through 2005. Methods: Dust storm incidence data, including date and approximate location, are taken from the U.S. National Weather Service storm database. County-level mortality data for the years 1993–2005 were acquired from the National Center for Health Statistics. Distributed lag conditional logistic regression models under a time-stratified case-crossover design were used to study the relationship between dust storms and daily mortality counts over the whole United States and in Arizona and California specifically. End points included total non-accidental mortality and three mortality subgroups (cardiovascular, respiratory, and other non-accidental). Results: We estimated that for the United States as a whole, total non-accidental mortality increased by 7.4% (95% CI: 1.6, 13.5; p = 0.011) and 6.7% (95% CI: 1.1, 12.6; p = 0.018) at 2- and 3-day lags, respectively, and by an average of 2.7% (95% CI: 0.4, 5.1; p = 0.023) over lags 0–5 compared with referent days. Significant associations with non-accidental mortality were estimated for California (lag 2 and 0–5 day) and Arizona (lag 3), for cardiovascular mortality in the United States (lag 2) and Arizona (lag 3), and for other non-accidental mortality in California (lags 1–3 and 0–5). Conclusions: Dust storms are associated with increases in lagged non-accidental and cardiovascular mortality. Citation: Crooks JL, Cascio WE, Percy MS, Reyes J, Neas LM, Hilborn ED. 2016. The association between dust storms and daily non-accidental mortality in the United States, 1993–2005. Environ Health Perspect 124:1735–1743; http://dx.doi.org/10.1289/EHP216 PMID:27128449

Adding In-Plane Flexibility to the Equations of Motion of a Single Rotor Helicopter

NASA Technical Reports Server (NTRS)

Curtiss, H. C., Jr.

2000-01-01

This report describes a way to add the effects of main rotor blade flexibility in the in- plane or lead-lag direction to a large set of non-linear equations of motion for a single rotor helicopter with rigid blades(l). Differences between the frequency of the regressing lag mode predicted by the equations of (1) and that measured in flight (2) for a UH-60 helicopter indicate that some element is missing from the analytical model of (1) which assumes rigid blades. A previous study (3) noted a similar discrepancy for the CH-53 helicopter. Using a relatively simple analytical model in (3), compared to (1), it was shown that a mechanical lag damper increases significantly the coupling between the rigid lag mode and the first flexible mode. This increased coupling due to a powerful lag damper produces an increase in the lowest lag frequency when viewed in a frame rotating with the blade. Flight test measurements normally indicate the frequency of this mode in a non-rotating or fixed frame. This report presents the additions necessary to the full equations of motion, to include main rotor blade lag flexibility. Since these additions are made to a very complex nonlinear dynamic model, in order to provide physical insight, a discussion of the results obtained from a simplified set of equations of motion is included. The reduced model illustrates the physics involved in the coupling and should indicate trends in the full model.

Long-Lag, Wide-pulse Gamma-Ray Bursts

NASA Technical Reports Server (NTRS)

Norris, J. P.; Bonnell, J. T.; Kazanas, D.; Scargie, J. D.; Hakkila, J.; Giblin, T. W.

2005-01-01

The best available probe of the early phase of gamma-ray burst (GRB) jet attributes is the prompt gamma-ray emission, in which several intrinsic and extrinsic variables determine observed GRB pulse evolution, including at least: jet opening angle, profiles of Lorentz factor and matter/field density, distance of emission region from central source, and viewing angle. Bright, usually complex bursts have many narrow pulses that are difficult to model due to overlap. However, the relatively simple, long spectral lag, wide-pulse bursts may have simpler physics and are easier to model. We have analyzed the temporal and spectral behavior of wide pulses in 24 long-lag bursts from the BATSE sample, using a pulse model with two shape parameters - width and asymmetry - and the Band spectral model with three shape parameters. We find that pulses in long-lag bursts are distinguished both temporally and spectrally from those in bright bursts: the pulses in long spectral lag bursts are few in number, and approximately 100 times wider (10s of seconds), have systemtically lower peaks in nu*F(nu), harder low-energy spectra and softer high-energy spectra. These five pulse descriptors are essentially uncorrelated for our long-lag sample, suggesting that at least approximately 5 parameters are needed to model burst temporal and spectral behavior, roughly commensurate with the theoretical phase space. However, we do find that pulse width is strongly correlated with spectral lag; hence these two parameters may be viewed as mutual surrogates. The prevalence of long-lag bursts near the BATSE trigger threshold, their predominantly low nu*F(nu) spectral peaks, and relatively steep upper power-law spectral indices indicate that Swiift will detect many such bursts.

Time-averaged fluxes of lead and fallout radionuclides to sediments in Florida Bay

USGS Publications Warehouse

Robbins, J.A.; Holmes, C.; Halley, R.; Bothner, Michael H.; Shinn, E.; Graney, J.; Keeler, G.; TenBrink, M.; Orlandini, K.A.; Rudnick, D.

2000-01-01

Recent, unmixed sediments from mud banks of central Florida Bay were dated using 210Pb/226Ra, and chronologies were verified by comparing sediment lead temporal records with Pb/Ca ratios in annual layers of coral (Montastrea annularis) located on the ocean side of the Florida Keys. Dates of sediment lead peaks (1978±2) accord with prior observations of a 6 year lag between the occurrence of maximum atmospheric lead in 1972 and peak coral lead in 1978. Smaller lags of 1–2 years occur between the maximum atmospheric radionuclide fallout and peaks in sediment temporal records of 137Cs and Pu. Such lags are consequences of system time averaging (STA) in which atmospherically delivered particle-associated constituents accumulate and mix in a (sedimentary?) reservoir before transferring to permanent sediments and coral. STA model calculations, using time-dependent atmospheric inputs, produced optimized profiles in excellent accord with measured sediment 137Cs, Pu, lead, and coral lead distributions. Derived residence times of these particle tracers (16±1, 15.7±0.7, 19±3, and 16±2 years, respectively) are comparable despite differences in sampling locations, in accumulating media, and in element loading histories and geochemical properties. For a 16 year weighted mean residence time, STA generates the observed 6 year lead peak lag. Evidently, significant levels of nondegradable, particle-associated contaminants can persist in Florida Bay for many decades following elimination of external inputs. Present results, in combination with STA model analysis of previously reported radionuclide profiles, suggest that decade-scale time averaging may occur widely in recent coastal marine sedimentary environments.

Physiological and Psychophysical Modeling of the Precedence Effect

PubMed Central

Xia, Jing; Brughera, Andrew; Colburn, H. Steven

2010-01-01

Many past studies of sound localization explored the precedence effect (PE), in which a pair of brief, temporally close sounds from different directions is perceived as coming from a location near that of the first-arriving sound. Here, a computational model of low-frequency inferior colliculus (IC) neurons accounts for both physiological and psychophysical responses to PE click stimuli. In the model, IC neurons have physiologically plausible inputs, receiving excitation from the ipsilateral medial superior olive (MSO) and long-lasting inhibition from both ipsilateral and contralateral MSOs, relayed through the dorsal nucleus of the lateral lemniscus. In this model, physiological suppression of the lagging response depends on the inter-stimulus delay (ISD) between the lead and lag as well as their relative locations. Psychophysical predictions are generated from a population of model neurons. At all ISDs, predicted lead localization is good. At short ISDs, the estimated location of the lag is near that of the lead, consistent with subjects perceiving both lead and lag from the lead location. As ISD increases, the estimated lag location moves closer to the true lag location, consistent with listeners’ perception of two sounds from separate locations. Together, these simulations suggest that location-dependent suppression in IC neurons can explain the behavioral phenomenon known as the precedence effect. PMID:20358242

On modeling the paleohydrologic response of closed-basin lakes to fluctuations in climate: Methods, applications, and implications

NASA Astrophysics Data System (ADS)

Liu, Ganming; Schwartz, Franklin W.

2014-04-01

Climate reconstructions using tree rings and lake sediments have contributed significantly to the understanding of Holocene climates. Approaches focused specifically on reconstructing the temporal water-level response of lakes, however, are much less developed. This paper describes a statistical correlation approach based on time series with Palmer Drought Severity Index (PDSI) values derived from instrumental records or tree rings as a basis for reconstructing stage hydrographs for closed-basin lakes. We use a distributed lag correlation model to calculate a variable, ωt that represents the water level of a lake at any time t as a result of integrated climatic forcing from preceding years. The method was validated using both synthetic and measured lake-stage data and the study found that a lake's "memory" of climate fades as time passes, following an exponential-decay function at rates determined by the correlation time lag. Calculated trends in ωt for Moon Lake, Rice Lake, and Lake Mina from A.D. 1401 to 1860 compared well with the established chronologies (salinity, moisture, and Mg/Ca ratios) reconstructed from sediments. This method provides an independent approach for developing high-resolution information on lake behaviors in preinstrumental times and has been able to identify problems of climate signal deterioration in sediment-based climate reconstructions in lakes with a long time lag.

Effective Capital Provision Within Government. Methodologies for Right-Sizing Base Infrastructure

DTIC Science & Technology

2005-01-01

unknown distributions, since they more accurately represent the complexity of real -world problems. Forecasting uncertain future demand flows is critical to...ordering system with no time lags and no additional costs for instantaneous delivery, shortage and holding costs would be eliminated, because the...order a fixed quantity, Q. 4.1.4 Analyzed Time Step Time is an important dimension in inventory models, since the way the system changes over time affects

A Time Series Analysis: Weather Factors, Human Migration and Malaria Cases in Endemic Area of Purworejo, Indonesia, 2005–2014

PubMed Central

REJEKI, Dwi Sarwani Sri; NURHAYATI, Nunung; AJI, Budi; MURHANDARWATI, E. Elsa Herdiana; KUSNANTO, Hari

2018-01-01

Background: Climatic and weather factors become important determinants of vector-borne diseases transmission like malaria. This study aimed to prove relationships between weather factors with considering human migration and previous case findings and malaria cases in endemic areas in Purworejo during 2005–2014. Methods: This study employed ecological time series analysis by using monthly data. The independent variables were the maximum temperature, minimum temperature, maximum humidity, minimum humidity, precipitation, human migration, and previous malaria cases, while the dependent variable was positive malaria cases. Three models of count data regression analysis i.e. Poisson model, quasi-Poisson model, and negative binomial model were applied to measure the relationship. The least Akaike Information Criteria (AIC) value was also performed to find the best model. Negative binomial regression analysis was considered as the best model. Results: The model showed that humidity (lag 2), precipitation (lag 3), precipitation (lag 12), migration (lag1) and previous malaria cases (lag 12) had a significant relationship with malaria cases. Conclusion: Weather, migration and previous malaria cases factors need to be considered as prominent indicators for the increase of malaria case projection. PMID:29900134

Correlation between the change in the kinetics of the ribosomal RNA rrnB P2 promoter and the transition from lag to exponential phase with Pseudomonas fluorescens.

PubMed

McKellar, Robin C

2008-01-15

Developing accurate mathematical models to describe the pre-exponential lag phase in food-borne pathogens presents a considerable challenge to food microbiologists. While the growth rate is influenced by current environmental conditions, the lag phase is affected in addition by the history of the inoculum. A deeper understanding of physiological changes taking place during the lag phase would improve accuracy of models, and in earlier studies a strain of Pseudomonas fluorescens containing the Tn7-luxCDABE gene cassette regulated by the rRNA promoter rrnB P2 was used to measure the influence of starvation, growth temperature and sub-lethal heating on promoter expression and subsequent growth. The present study expands the models developed earlier to include a model which describes the change from exponential to linear increase in promoter expression with time when the exponential phase of growth commences. A two-phase linear model with Poisson weighting was used to estimate the lag (LPDLin) and the rate (RLin) for this linear increase in bioluminescence. The Spearman rank correlation coefficient (r=0.830) between the LPDLin and the growth lag phase (LPDOD) was extremely significant (P

Accretion Disk Reverberation with Hubble Space Telescope Observations of NGC 4593: Evidence for Diffuse Continuum Lags

NASA Astrophysics Data System (ADS)

Cackett, Edward M.; Chiang, Chia-Ying; McHardy, Ian; Edelson, Rick; Goad, Michael R.; Horne, Keith; Korista, Kirk T.

2018-04-01

The Seyfert 1 galaxy NGC 4593 was monitored spectroscopically with the Hubble Space Telescope as part of a reverberation mapping campaign that also included Swift, Kepler, and ground-based photometric monitoring. During 2016 July 12–August 6, we obtained 26 spectra across a nearly continuous wavelength range of ∼1150–10000 Å. These were combined with Swift data to produce a UV/optical “lag spectrum,” which shows the interband lag relative to the Swift UVW2 band as a function of wavelength. The broad shape of the lag spectrum appears to follow the τ ∝ λ 4/3 relation seen previously in photometric interband lag measurements of other active galactic nuclei (AGNs). This shape is consistent with the standard thin disk model, but the magnitude of the lags implies a disk that is a factor of ∼3 larger than predicted, again consistent with what has been previously seen in other AGNs. In all cases these large disk sizes, which are also implied by independent gravitational microlensing of higher-mass AGNs, cannot be simply reconciled with the standard model. However, the most striking feature in this higher-resolution lag spectrum is a clear excess around the 3646 Å Balmer jump. This strongly suggests that diffuse emission from gas in the much larger broad-line region (BLR) must also contribute significantly to the interband lags. While the relative contributions of the disk and BLR cannot be uniquely determined in these initial measurements, it is clear that both will need to be considered to comprehensively model and understand AGN lag spectra.

Large daily stock variation is associated with cardiovascular mortality in two cities of Guangdong, China.

PubMed

Lin, Hualiang; Zhang, Yonghui; Xu, Yanjun; Liu, Tao; Xiao, Jianpeng; Luo, Yuan; Xu, Xiaojun; He, Yanhui; Ma, Wenjun

2013-01-01

The current study aimed to examine the effects of daily change of the Shenzhen Stock Exchange Index on cardiovascular mortality in Guangzhou and Taishan, China. Daily mortality and stock performance data during 2006-2010 were collected to construct the time series for the two cities. A distributed lag non-linear model was utilized to examine the effect of daily stock index changes on cardiovascular mortality after controlling for potential confounding factors. We observed a delayed non-linear effect of the stock index change on cardiovascular mortality: both rising and declining of the stock index were associated with increased cardiovascular deaths. In Guangzhou, the 15-25 lag days cumulative relative risk of an 800 index drop was 2.08 (95% CI: 1.38-3.14), and 2.38 (95% CI: 1.31-4.31) for an 800 stock index increase on the cardiovascular mortality, respectively. In Taishan, the cumulative relative risk over 15-25 days lag was 1.65 (95% CI: 1.13-2.42) for an 800 index drop and 2.08 (95% CI: 1.26-3.42) for an 800 index rising, respectively. Large ups and downs in daily stock index might be important predictor of cardiovascular mortality.

Impact of meteorological factors on the spatiotemporal patterns of dengue fever incidence.

PubMed

Chien, Lung-Chang; Yu, Hwa-Lung

2014-12-01

Dengue fever is one of the most widespread vector-borne diseases and has caused more than 50 million infections annually over the world. For the purposes of disease prevention and climate change health impact assessment, it is crucial to understand the weather-disease associations for dengue fever. This study investigated the nonlinear delayed impact of meteorological conditions on the spatiotemporal variations of dengue fever in southern Taiwan during 1998-2011. We present a novel integration of a distributed lag nonlinear model and Markov random fields to assess the nonlinear lagged effects of weather variables on temporal dynamics of dengue fever and to account for the geographical heterogeneity. This study identified the most significant meteorological measures to dengue fever variations, i.e., weekly minimum temperature, and the weekly maximum 24-hour rainfall, by obtaining the relative risk (RR) with respect to disease counts and a continuous 20-week lagged time. Results show that RR increased as minimum temperature increased, especially for the lagged period 5-18 weeks, and also suggest that the time to high disease risks can be decreased. Once the occurrence of maximum 24-hour rainfall is >50 mm, an associated increased RR lasted for up to 15 weeks. A temporary one-month decrease in the RR of dengue fever is noted following the extreme rain. In addition, the elevated incidence risk is identified in highly populated areas. Our results highlight the high nonlinearity of temporal lagged effects and magnitudes of temperature and rainfall on dengue fever epidemics. The results can be a practical reference for the early warning of dengue fever. Copyright © 2014 Elsevier Ltd. All rights reserved.

Is short-term exposure to ambient fine particles associated with measles incidence in China? A multi-city study.

PubMed

Chen, Gongbo; Zhang, Wenyi; Li, Shanshan; Williams, Gail; Liu, Chao; Morgan, Geoffrey G; Jaakkola, Jouni J K; Guo, Yuming

2017-07-01

China's rapid economic development has resulted in severe particulate matter (PM) air pollution and the control and prevention of infectious disease is an ongoing priority. This study examined the relationships between short-term exposure to ambient particles with aerodynamic diameter ≤2.5µm (PM 2.5 ) and measles incidence in China. Data on daily numbers of new measles cases and concentrations of ambient PM 2.5 were collected from 21 cities in China during Oct 2013 and Dec 2014. Poisson regression was used to examine city-specific associations of PM 2.5 and measles, with a constrained distributed lag model, after adjusting for seasonality, day of the week, and weather conditions. Then, the effects at the national scale were pooled with a random-effect meta-analysis. A 10µg/m 3 increase in PM 2.5 at lag 1day, lag 2day and lag 3day was significantly associated with increased measles incidence [relative risk (RR) and 95% confidence interval (CI) were 1.010 (1.003, 1.018), 1.010 (1.003, 1.016) and 1.006 (1.000, 1.012), respectively]. The cumulative relative risk of measles associated with PM 2.5 at lag 1-3 days was 1.029 (95% CI: 1.010, 1.048). Stratified analyses by meteorological factors showed that the PM 2.5 and measles associations were stronger on days with high temperature, low humidity, and high wind speed. We provide new evidence that measles incidence is associated with exposure to ambient PM 2.5 in China. Effective policies to reduce air pollution may also reduce measles incidence. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison of short-term associations with meteorological variables between COPD and pneumonia hospitalization among the elderly in Hong Kong—a time-series study

NASA Astrophysics Data System (ADS)

Lam, Holly Ching-yu; Chan, Emily Ying-yang; Goggins, William Bernard

2018-05-01

Pneumonia and chronic obstructive pulmonary diseases (COPD) are the commonest causes of respiratory hospitalization among older adults. Both diseases have been reported to be associated with ambient temperature, but the associations have not been compared between the diseases. Their associations with other meteorological variables have also not been well studied. This study aimed to evaluate the associations between meteorological variables, pneumonia, and COPD hospitalization among adults over 60 and to compare these associations between the diseases. Daily cause-specific hospitalization counts in Hong Kong during 2004-2011 were regressed on daily meteorological variables using distributed lag nonlinear models. Associations were compared between diseases by ratio of relative risks. Analyses were stratified by season and age group (60-74 vs. ≥ 75). In hot season, high temperature (> 28 °C) and high relative humidity (> 82%) were statistically significantly associated with more pneumonia in lagged 0-2 and lagged 0-10 days, respectively. Pneumonia hospitalizations among the elderly (≥ 75) also increased with high solar radiation and high wind speed. During the cold season, consistent hockey-stick associations with temperature and relative humidity were found for both admissions and both age groups. The minimum morbidity temperature and relative humidity were at about 21-22 °C and 82%. The lagged effects of low temperature were comparable for both diseases (lagged 0-20 days). The low-temperature-admissions associations with COPD were stronger and were strongest among the elderly. This study found elevated pneumonia and COPD admissions risks among adults ≥ 60 during periods of extreme weather conditions, and the associations varied by season and age group. Vulnerable groups should be advised to avoid exposures, such as staying indoor and maintaining satisfactory indoor conditions, to minimize risks.

Prediction of dexamethasone release from PLGA microspheres prepared with polymer blends using a design of experiment approach.

PubMed

Gu, Bing; Burgess, Diane J

2015-11-10

Hydrophobic drug release from poly (lactic-co-glycolic acid) (PLGA) microspheres typically exhibits a tri-phasic profile with a burst release phase followed by a lag phase and a secondary release phase. High burst release can be associated with adverse effects and the efficacy of the formulation cannot be ensured during a long lag phase. Accordingly, the development of a long-acting microsphere product requires optimization of all drug release phases. The purpose of the current study was to investigate whether a blend of low and high molecular weight polymers can be used to reduce the burst release and eliminate/minimize the lag phase. A single emulsion solvent evaporation method was used to prepare microspheres using blends of two PLGA polymers (PLGA5050 (25 kDa) and PLGA9010 (113 kDa)). A central composite design approach was applied to investigate the effect of formulation composition on dexamethasone release from these microspheres. Mathematical models obtained from this design of experiments study were utilized to generate a design space with maximized microsphere drug loading and reduced burst release. Specifically, a drug loading close to 15% can be achieved and a burst release less than 10% when a composition of 80% PLGA9010 and 90 mg of dexamethasone is used. In order to better describe the lag phase, a heat map was generated based on dexamethasone release from the PLGA microsphere/PVA hydrogel composite coatings. Using the heat map an optimized formulation with minimum lag phase was selected. The microspheres were also characterized for particle size/size distribution, thermal properties and morphology. The particle size was demonstrated to be related to the polymer concentration and the ratio of the two polymers but not to the dexamethasone concentration. Copyright © 2015 Elsevier B.V. All rights reserved.

Practical limitations on the use of diurnal temperature signals to quantify groundwater upwelling

USGS Publications Warehouse

Briggs, Martin A.; Lautz, Laura K.; Buckley, Sean F.; Lane, John W.

2014-01-01

Groundwater upwelling to streams creates unique habitat by influencing stream water quality and temperature; upwelling zones also serve as vectors for contamination when groundwater is degraded. Temperature time series data acquired along vertical profiles in the streambed have been applied to simple analytical models to determine rates of vertical fluid flux. These models are based on the downward propagation characteristics (amplitude attenuation and phase-lag) of the surface diurnal signal. Despite the popularity of these models, there are few published characterizations of moderate-to-strong upwelling. We attribute this limitation to the thermodynamics of upwelling, under which the downward conductive signal transport from the streambed interface occurs opposite the upward advective fluid flux. Governing equations describing the advection–diffusion of heat within the streambed predict that under upwelling conditions, signal amplitude attenuation will increase, but, counterintuitively, phase-lag will decrease. Therefore the extinction (measurable) depth of the diurnal signal is very shallow, but phase lag is also short, yielding low signal to noise ratio and poor model sensitivity. Conversely, amplitude attenuation over similar sensor spacing is strong, yielding greater potential model sensitivity. Here we present streambed thermal time series over a range of moderate to strong upwelling sites in the Quashnet River, Cape Cod, Massachusetts. The predicted inverse relationship between phase-lag and rate of upwelling was observed in the field data over a range of conditions, but the observed phase-lags were consistently shorter than predicted. Analytical solutions for fluid flux based on signal amplitude attenuation return results consistent with numerical models and physical seepage meters, but the phase-lag analytical model results are generally unreasonable. Through numerical modeling we explore reasons why phase-lag may have been over-predicted by the analytical models, and develop guiding relations of diurnal temperature signal extinction depth based on stream diurnal signal amplitude, upwelling magnitude, and streambed thermal properties that will be useful in designing future experiments.

A distributed lag approach to fitting non-linear dose-response models in particulate matter air pollution time series investigations.

PubMed

Roberts, Steven; Martin, Michael A

2007-06-01

The majority of studies that have investigated the relationship between particulate matter (PM) air pollution and mortality have assumed a linear dose-response relationship and have used either a single-day's PM or a 2- or 3-day moving average of PM as the measure of PM exposure. Both of these modeling choices have come under scrutiny in the literature, the linear assumption because it does not allow for non-linearities in the dose-response relationship, and the use of the single- or multi-day moving average PM measure because it does not allow for differential PM-mortality effects spread over time. These two problems have been dealt with on a piecemeal basis with non-linear dose-response models used in some studies and distributed lag models (DLMs) used in others. In this paper, we propose a method for investigating the shape of the PM-mortality dose-response relationship that combines a non-linear dose-response model with a DLM. This combined model will be shown to produce satisfactory estimates of the PM-mortality dose-response relationship in situations where non-linear dose response models and DLMs alone do not; that is, the combined model did not systemically underestimate or overestimate the effect of PM on mortality. The combined model is applied to ten cities in the US and a pooled dose-response model formed. When fitted with a change-point value of 60 microg/m(3), the pooled model provides evidence for a positive association between PM and mortality. The combined model produced larger estimates for the effect of PM on mortality than when using a non-linear dose-response model or a DLM in isolation. For the combined model, the estimated percentage increase in mortality for PM concentrations of 25 and 75 microg/m(3) were 3.3% and 5.4%, respectively. In contrast, the corresponding values from a DLM used in isolation were 1.2% and 3.5%, respectively.

Spectral evolution of GRBs with negative spectral lag using Fermi GBM observations

NASA Astrophysics Data System (ADS)

Chakrabarti, Arundhati; Chaudhury, Kishor; Sarkar, Samir K.; Bhadra, Arunava

2018-06-01

The positive spectral lag of Gamma Ray Bursts (GRBs) is often explained in terms of hard-to-soft spectral evolution of GRB pulses. While positive lags of GRBs is very common, there are few GRB pulses that exhibits negative spectral lags. In the present work we examine whether negative lags of GRBs also can be interpreted in terms of spectral evolution of GRB pulses or not. Using Fermi-GBM data, we identify two GRBs, GRB 090426C and GRB 150213A, with clean pulses that exhibit negative spectral lag. An indication of soft to hard transition has been noticed for the negative spectral lag events from the spectral evolution study. The implication of the present findings on the models of GRB spectral lags are discussed.

Modeling Inflation Using a Non-Equilibrium Equation of Exchange

NASA Technical Reports Server (NTRS)

Chamberlain, Robert G.

2013-01-01

Inflation is a change in the prices of goods that takes place without changes in the actual values of those goods. The Equation of Exchange, formulated clearly in a seminal paper by Irving Fisher in 1911, establishes an equilibrium relationship between the price index P (also known as "inflation"), the economy's aggregate output Q (also known as "the real gross domestic product"), the amount of money available for spending M (also known as "the money supply"), and the rate at which money is reused V (also known as "the velocity of circulation of money"). This paper offers first a qualitative discussion of what can cause these factors to change and how those causes might be controlled, then develops a quantitative model of inflation based on a non-equilibrium version of the Equation of Exchange. Causal relationships are different from equations in that the effects of changes in the causal variables take time to play out-often significant amounts of time. In the model described here, wages track prices, but only after a distributed lag. Prices change whenever the money supply, aggregate output, or the velocity of circulation of money change, but only after a distributed lag. Similarly, the money supply depends on the supplies of domestic and foreign money, which depend on the monetary base and a variety of foreign transactions, respectively. The spreading of delays mitigates the shocks of sudden changes to important inputs, but the most important aspect of this model is that delays, which often have dramatic consequences in dynamic systems, are explicitly incorporated.macroeconomics, inflation, equation of exchange, non-equilibrium, Athena Project

Ensemble flood simulation for a small dam catchment in Japan using 10 and 2 km resolution nonhydrostatic model rainfalls

NASA Astrophysics Data System (ADS)

Kobayashi, Kenichiro; Otsuka, Shigenori; Apip; Saito, Kazuo

2016-08-01

This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency nonhydrostatic model (JMA-NHM) are used as the input data to a rainfall-runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a high-resolution 2 km spatial resolutions. A distributed rainfall-runoff model is constructed for the Kasahori dam catchment (approx. 70 km2) and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km resolution JMA-NHM ensemble simulation are more appropriate than the 10 km resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140 m3 s-1, a threshold value for flood control. The inflows with the 10 km resolution ensemble rainfall are all considerably smaller than the observations, while at least one simulated discharge out of 11 ensemble members with the 2 km resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the position-shifted rainfalls shows much better results than the original ensemble discharge simulations.

The Development of Midlatitude Cirrus Models for MODIS Using FIRE-I, FIRE-II, and ARM In Situ Data

NASA Technical Reports Server (NTRS)

Nasiri, Shaima L.; Baum, Bryan A.; Heymsfield, Andrew J.; Yang, Ping; Poellot, Michael R.; Kratz, David P.; Hu, Yong-Xiang

2002-01-01

Detailed in situ data from cirrus clouds have been collected during dedicated field Campaigns, but the use of the size and habit distribution data has been lagging in the development of more realistic cirrus scattering models. In this study, the authors examine the use of in situ cirrus data collected during three field campaigns to develop more realistic midlatitude cirrus microphysical models. Data are used from the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)-I (1986) and FIRE-II (1991) campaigns and from a recent Atmospheric Radiation Measurement (ARM) Program campaign held in March-April of 2000. The microphysical models are based on measured vertical distributions of both particle size and particle habit and are used to develop new scattering models for a suite of moderate-resolution imaging spectroradiometer (MODIS) bands spanning visible. near-infrared, and infrared wavelengths. The sensitivity of the resulting scattering properties to the underlying assumptions of the assumed particle size and habit distributions are examined. It is found that the near-infrared bands are sensitive not only to the discretization of the size distribution but also to the assumed habit distribution. In addition. the results indicate that the effective diameter calculated from a given size distribution tends to be sensitive to the number of size bins that are used to discretize the data and also to the ice-crystal habit distribution.

Tracking lags in historical plant species' shifts in relation to regional climate change.

PubMed

Ash, Jeremy D; Givnish, Thomas J; Waller, Donald M

2017-03-01

Can species shift their distributions fast enough to track changes in climate? We used abundance data from the 1950s and the 2000s in Wisconsin to measure shifts in the distribution and abundance of 78 forest-understory plant species over the last half-century and compare these shifts to changes in climate. We estimated temporal shifts in the geographic distribution of each species using vectors to connect abundance-weighted centroids from the 1950s and 2000s. These shifts in distribution reflect colonization, extirpation, and changes in abundance within sites, separately quantified here. We then applied climate analog analyses to compute vectors representing the climate change that each species experienced. Species shifted mostly to the northwest (mean: 49 ± 29 km) primarily reflecting processes of colonization and changes in local abundance. Analog climates for these species shifted even further to the northwest, however, exceeding species' shifts by an average of 90 ± 40 km. Most species thus failed to match recent rates of climate change. These lags decline in species that have colonized more sites and those with broader site occupancy, larger seed mass, and higher habitat fidelity. Thus, species' traits appear to affect their responses to climate change, but relationships are weak. As climate change accelerates, these lags will likely increase, potentially threatening the persistence of species lacking the capacity to disperse to new sites or locally adapt. However, species with greater lags have not yet declined more in abundance. The extent of these threats will likely depend on how other drivers of ecological change and interactions among species affect their responses to climate change. © 2016 John Wiley & Sons Ltd.

Helicopter vibration suppression using simple pendulum absorbers on the rotor blade

NASA Technical Reports Server (NTRS)

Hamouda, M.-N. H.; Pierce, G. A.

1981-01-01

A design procedure is presented for the installation of simple pendulums on the blades of a helicopter rotor to suppress the root reactions. The procedure consists of a frequency response analysis for a hingeless rotor blade excited by a harmonic variation of spanwise airload distributions during forward flight, as well as a concentrated load at the tip. The structural modeling of the blade provides for elastic degrees of freedom in flap and lead-lag bending plus torsion. Simple flap and lead-lag pendulums are considered individually. Using a rational order scheme, the general nonlinear equations of motion are linearized. A quasi-steady aerodynamic representation is used in the formation of the airloads. The solution of the system equations derives from their representation as a transfer matrix. The results include the effect of pendulum tuning on the minimization of the hub reactions.

Investor structure and the price-volume relationship in a continuous double auction market: An agent-based modeling perspective

NASA Astrophysics Data System (ADS)

Zhang, Wei; Bi, Zhengzheng; Shen, Dehua

2017-02-01

This paper investigates the impact of investor structure on the price-volume relationship by simulating a continuous double auction market. Connected with the underlying mechanisms of the price-volume relationship, i.e., the Mixture of Distribution Hypothesis (MDH) and the Sequential Information Arrival Hypothesis (SIAH), the simulation results show that: (1) there exists a strong lead-lag relationship between the return volatility and trading volume when the number of informed investors is close to the number of uninformed investors in the market; (2) as more and more informed investors entering the market, the lead-lag relationship becomes weaker and weaker, while the contemporaneous relationship between the return volatility and trading volume becomes more prominent; (3) when the informed investors are in absolute majority, the market can achieve the new equilibrium immediately. Therefore, we can conclude that the investor structure is a key factor in affecting the price-volume relationship.

Impact of climate variability on Plasmodium vivax and Plasmodium falciparum malaria in Yunnan Province, China.

PubMed

Bi, Yan; Yu, Weiwei; Hu, Wenbiao; Lin, Hualiang; Guo, Yuming; Zhou, Xiao-Nong; Tong, Shilu

2013-12-17

Malaria remains a public health problem in the remote and poor area of Yunnan Province, China. Yunnan faces an increasing risk of imported malaria infections from Mekong river neighboring countries. This study aimed to identify the high risk area of malaria transmission in Yunnan Province, and to estimate the effects of climatic variability on the transmission of Plasmodium vivax and Plasmodium falciparum in the identified area. We identified spatial clusters of malaria cases using spatial cluster analysis at a county level in Yunnan Province, 2005-2010, and estimated the weekly effects of climatic factors on P. vivax and P. falciparum based on a dataset of daily malaria cases and climatic variables. A distributed lag nonlinear model was used to estimate the impact of temperature, relative humidity and rainfall up to 10-week lags on both types of malaria parasite after adjusting for seasonal and long-term effects. The primary cluster area was identified along the China-Myanmar border in western Yunnan. A 1°C increase in minimum temperature was associated with a lag 4 to 9 weeks relative risk (RR), with the highest effect at lag 7 weeks for P. vivax (RR = 1.03; 95% CI, 1.01, 1.05) and 6 weeks for P. falciparum (RR = 1.07; 95% CI, 1.04, 1.11); a 10-mm increment in rainfall was associated with RRs of lags 2-4 weeks and 9-10 weeks, with the highest effect at 3 weeks for both P. vivax (RR = 1.03; 95% CI, 1.01, 1.04) and P. falciparum (RR = 1.04; 95% CI, 1.01, 1.06); and the RRs with a 10% rise in relative humidity were significant from lag 3 to 8 weeks with the highest RR of 1.24 (95% CI, 1.10, 1.41) for P. vivax at 5-week lag. Our findings suggest that the China-Myanmar border is a high risk area for malaria transmission. Climatic factors appeared to be among major determinants of malaria transmission in this area. The estimated lag effects for the association between temperature and malaria are consistent with the life cycles of both mosquito vector and malaria parasite. These findings will be useful for malaria surveillance-response systems in the Mekong river region.

Both low and high temperature may increase the risk of stroke mortality

PubMed Central

Chen, Renjie; Wang, Cuicui; Meng, Xia; Chen, Honglei; Thach, Thuan Quoc; Wong, Chit-Ming

2013-01-01

Objective: To examine temperature in relation to stroke mortality in a multicity time series study in China. Methods: We obtained data on daily temperature and mortality from 8 large cities in China. We used quasi-Poisson generalized additive models and distributed lag nonlinear models to estimate the accumulative effects of temperature on stroke mortality across multiple days, adjusting for long-term and seasonal trends, day of the week, air pollution, and relative humidity. We applied the Bayesian hierarchical model to pool city-specific effect estimates. Results: Both cold and hot temperatures were associated with increased risk of stroke mortality. The potential effect of cold temperature might last more than 2 weeks. The pooled relative risks of extreme cold (first percentile of temperature) and cold (10th percentile of temperature) temperatures over lags 0–14 days were 1.39 (95% posterior intervals [PI] 1.18–1.64) and 1.11 (95% PI 1.06–1.17), compared with the 25th percentile of temperature. In contrast, the effect of hot temperature was more immediate. The relative risks of stroke mortality over lags 0–3 days were 1.06 (95% PI 1.02–1.10) for extreme hot temperature (99th percentile of temperature) and 1.14 (95% PI 1.05–1.24) for hot temperature (90th percentile of temperature), compared with the 75th percentile of temperature. Conclusions: This study showed that both cold and hot temperatures were associated with increased risk of stroke mortality in China. Our findings may have important implications for stroke prevention in China. PMID:23946311

Both low and high temperature may increase the risk of stroke mortality.

PubMed

Chen, Renjie; Wang, Cuicui; Meng, Xia; Chen, Honglei; Thach, Thuan Quoc; Wong, Chit-Ming; Kan, Haidong

2013-09-17

To examine temperature in relation to stroke mortality in a multicity time series study in China. We obtained data on daily temperature and mortality from 8 large cities in China. We used quasi-Poisson generalized additive models and distributed lag nonlinear models to estimate the accumulative effects of temperature on stroke mortality across multiple days, adjusting for long-term and seasonal trends, day of the week, air pollution, and relative humidity. We applied the Bayesian hierarchical model to pool city-specific effect estimates. Both cold and hot temperatures were associated with increased risk of stroke mortality. The potential effect of cold temperature might last more than 2 weeks. The pooled relative risks of extreme cold (first percentile of temperature) and cold (10th percentile of temperature) temperatures over lags 0-14 days were 1.39 (95% posterior intervals [PI] 1.18-1.64) and 1.11 (95% PI 1.06-1.17), compared with the 25th percentile of temperature. In contrast, the effect of hot temperature was more immediate. The relative risks of stroke mortality over lags 0-3 days were 1.06 (95% PI 1.02-1.10) for extreme hot temperature (99th percentile of temperature) and 1.14 (95% PI 1.05-1.24) for hot temperature (90th percentile of temperature), compared with the 75th percentile of temperature. This study showed that both cold and hot temperatures were associated with increased risk of stroke mortality in China. Our findings may have important implications for stroke prevention in China.

Time-lag effects of global vegetation responses to climate change.

PubMed

Wu, Donghai; Zhao, Xiang; Liang, Shunlin; Zhou, Tao; Huang, Kaicheng; Tang, Bijian; Zhao, Wenqian

2015-09-01

Climate conditions significantly affect vegetation growth in terrestrial ecosystems. Due to the spatial heterogeneity of ecosystems, the vegetation responses to climate vary considerably with the diverse spatial patterns and the time-lag effects, which are the most important mechanism of climate-vegetation interactive effects. Extensive studies focused on large-scale vegetation-climate interactions use the simultaneous meteorological and vegetation indicators to develop models; however, the time-lag effects are less considered, which tends to increase uncertainty. In this study, we aim to quantitatively determine the time-lag effects of global vegetation responses to different climatic factors using the GIMMS3g NDVI time series and the CRU temperature, precipitation, and solar radiation datasets. First, this study analyzed the time-lag effects of global vegetation responses to different climatic factors. Then, a multiple linear regression model and partial correlation model were established to statistically analyze the roles of different climatic factors on vegetation responses, from which the primary climate-driving factors for different vegetation types were determined. The results showed that (i) both the time-lag effects of the vegetation responses and the major climate-driving factors that significantly affect vegetation growth varied significantly at the global scale, which was related to the diverse vegetation and climate characteristics; (ii) regarding the time-lag effects, the climatic factors explained 64% variation of the global vegetation growth, which was 11% relatively higher than the model ignoring the time-lag effects; (iii) for the area with a significant change trend (for the period 1982-2008) in the global GIMMS3g NDVI (P < 0.05), the primary driving factor was temperature; and (iv) at the regional scale, the variation in vegetation growth was also related to human activities and natural disturbances. Considering the time-lag effects is quite important for better predicting and evaluating the vegetation dynamics under the background of global climate change. © 2015 John Wiley & Sons Ltd.

Seasonal variability of stratospheric methane: implications for constraining tropospheric methane budgets using total column observations

NASA Astrophysics Data System (ADS)

Saad, Katherine M.; Wunch, Debra; Deutscher, Nicholas M.; Griffith, David W. T.; Hase, Frank; De Mazière, Martine; Notholt, Justus; Pollard, David F.; Roehl, Coleen M.; Schneider, Matthias; Sussmann, Ralf; Warneke, Thorsten; Wennberg, Paul O.

2016-11-01

Global and regional methane budgets are markedly uncertain. Conventionally, estimates of methane sources are derived by bridging emissions inventories with atmospheric observations employing chemical transport models. The accuracy of this approach requires correctly simulating advection and chemical loss such that modeled methane concentrations scale with surface fluxes. When total column measurements are assimilated into this framework, modeled stratospheric methane introduces additional potential for error. To evaluate the impact of such errors, we compare Total Carbon Column Observing Network (TCCON) and GEOS-Chem total and tropospheric column-averaged dry-air mole fractions of methane. We find that the model's stratospheric contribution to the total column is insensitive to perturbations to the seasonality or distribution of tropospheric emissions or loss. In the Northern Hemisphere, we identify disagreement between the measured and modeled stratospheric contribution, which increases as the tropopause altitude decreases, and a temporal phase lag in the model's tropospheric seasonality driven by transport errors. Within the context of GEOS-Chem, we find that the errors in tropospheric advection partially compensate for the stratospheric methane errors, masking inconsistencies between the modeled and measured tropospheric methane. These seasonally varying errors alias into source attributions resulting from model inversions. In particular, we suggest that the tropospheric phase lag error leads to large misdiagnoses of wetland emissions in the high latitudes of the Northern Hemisphere.

Disentangling endogenous versus exogenous pattern formation in spatial ecology: a case study of the ant Azteca sericeasur in southern Mexico.

PubMed

Li, Kevin; Vandermeer, John H; Perfecto, Ivette

2016-05-01

Spatial patterns in ecology can be described as reflective of environmental heterogeneity (exogenous), or emergent from dynamic relationships between interacting species (endogenous), but few empirical studies focus on the combination. The spatial distribution of the nests of Azteca sericeasur, a keystone tropical arboreal ant, is thought to form endogenous spatial patterns among the shade trees of a coffee plantation through self-regulating interactions with controlling agents (i.e. natural enemies). Using inhomogeneous point process models, we found evidence for both types of processes in the spatial distribution of A. sericeasur. Each year's nest distribution was determined mainly by a density-dependent relationship with the previous year's lagged nest density; but using a novel application of a Thomas cluster process to account for the effects of nest clustering, we found that nest distribution also correlated significantly with tree density in the later years of the study. This coincided with the initiation of agricultural intensification and tree felling on the coffee farm. The emergence of this significant exogenous effect, along with the changing character of the density-dependent effect of lagged nest density, provides clues to the mechanism behind a unique phenomenon observed in the plot, that of an increase in nest population despite resource limitation in nest sites. Our results have implications in coffee agroecological management, as this system provides important biocontrol ecosystem services. Further research is needed, however, to understand the effective scales at which these relationships occur.

The changing trend in nitrate concentrations in major aquifers due to historical nitrate loading from agricultural land across England and Wales from 1925 to 2150.

PubMed

Wang, L; Stuart, M E; Lewis, M A; Ward, R S; Skirvin, D; Naden, P S; Collins, A L; Ascott, M J

2016-01-15

Nitrate is necessary for agricultural productivity, but can cause considerable problems if released into aquatic systems. Agricultural land is the major source of nitrates in UK groundwater. Due to the long time-lag in the groundwater system, it could take decades for leached nitrate from the soil to discharge into freshwaters. However, this nitrate time-lag has rarely been considered in environmental water management. Against this background, this paper presents an approach to modelling groundwater nitrate at the national scale, to simulate the impacts of historical nitrate loading from agricultural land on the evolution of groundwater nitrate concentrations. An additional process-based component was constructed for the saturated zone of significant aquifers in England and Wales. This uses a simple flow model which requires modelled recharge values, together with published aquifer properties and thickness data. A spatially distributed and temporally variable nitrate input function was also introduced. The sensitivity of parameters was analysed using Monte Carlo simulations. The model was calibrated using national nitrate monitoring data. Time series of annual average nitrate concentrations along with annual spatially distributed nitrate concentration maps from 1925 to 2150 were generated for 28 selected aquifer zones. The results show that 16 aquifer zones have an increasing trend in nitrate concentration, while average nitrate concentrations in the remaining 12 are declining. The results are also indicative of the trend in the flux of groundwater nitrate entering rivers through baseflow. The model thus enables the magnitude and timescale of groundwater nitrate response to be factored into source apportionment tools and to be taken into account alongside current planning of land-management options for reducing nitrate losses. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

The influence of interactions between accommodation and convergence on the lag of accommodation.

PubMed

Schor, C

1999-03-01

Several models of myopia predict that growth of axial length is stimulated by blur. Accommodative lag has been suggested as an important source of blur in the development of myopia and this study has modeled how cross-link interactions between accommodation and convergence might interact with uncorrected distance heterophoria and refractive error to influence accommodative lag. Accommodative lag was simulated with two models of interactions between accommodation and convergence (one with and one without adaptable tonic elements). Simulations of both models indicate that both uncorrected hyperopia and esophoria increase the lag of accommodative and uncorrected myopia and exophoria decrease the lag or introduce a lead of accommodation in response to the near (40 cm) stimulus. These effects were increased when gain of either cross-link, accommodative convergence (AC/A) or convergence accommodation (CA/C), was increased within a moderate range of values while the other was fixed at a normal value (clamped condition). These effects were exaggerated when both the AC/A and CA/C ratios were increased (covaried condition) and affects of cross-link gain were negated when an increase of one cross-link (e.g. AC/A) was accompanied by a reduction of the other cross-link (e.g. CA/C) (reciprocal condition). The inclusion of tonic adaptation in the model reduced steady state errors of accommodation for all conditions except when the AC/A ratio was very high (2 MA/D). Combinations of cross-link interactions between accommodation and convergence that resemble either clamped or reciprocal patterns occur naturally in clinical populations. Simulations suggest that these two patterns of abnormal cross-link interactions could affect the progression of myopia differently. Adaptable tonic accommodation and tonic vergence could potentially reduce the progression of myopia by reducing the lag of accommodation.

El Niño revisited: the influence of El Niño Southern Oscillation on the world's largest tuna fisheries.

NASA Astrophysics Data System (ADS)

Receveur, A.; Simon, N.; Menkes, C.; Tremblay-Boyer, L.; Senina, I.; Lehodey, P.

2016-12-01

El Niño Southern Oscillation (ENSO) drives global climate on inter-annual scales and impacts the ecosystem structure in the warm-pool and cold-tongue of the Pacific Ocean. During the El Niño phase of ENSO, the warm-pool can stretch from the western equatorial Pacific to the eastern Pacific allowing species associated with the warm-pool to correspondingly spread eastwards. Conversely, during the la Niña phase the warm-pool is pushed to the far western equatorial Pacific by the cold-tongue allowing species associated with this ecosystem to spread westwards. Consequently, ENSO dynamics are likely to be critical for understanding the ecological processes supporting fisheries in the equatorial Pacific Ocean. Surface inhabiting tuna, such as skipjack, are thought to track the convergence of the warm-pool and cold-tongue with fishing vessels tracking this tuna behavior. Given the reliance of Pacific Island economies on tuna fisheries, knowing when tunas are more likely to be present in high density in their territorial waters is beneficial for harvest control policies such as effort trading between nations. We use the SEAPODYM model to investigate the response of bigeye and skipjack tuna species to the phases of ENSO. SEAPODYM is an age structured model that integrates fisheries dependent and independent data with environmental data. We analyze the outputs of SEAPODYM using wavelets to assess the impact of environmental and biotic variables on the abundance and distribution of adult and juvenile age classes and to study time series cycle and temporal lags to ENSO. The main result for skipjack is the eastward or westward movement of the biomass pattern which is significantly lagged with the warm pool ENSO displacement. That lag ranges from 8 months for juvenile up to 18 months for adults. Such delayed response, can be traced in the model. Higher temperature in the central Pacific during El Niño leads to better recruitment which leads to lagged increase of juvenile biomass and lagged increase of adults. This suggest that previous analysis showing a phase displacement between El Niño and skipjack CPUE are biased by the effort movements of the fleet and may not accurately represent the tuna biomass movements.

How to compare cross-lagged associations in a multilevel autoregressive model.

PubMed

Schuurman, Noémi K; Ferrer, Emilio; de Boer-Sonnenschein, Mieke; Hamaker, Ellen L

2016-06-01

By modeling variables over time it is possible to investigate the Granger-causal cross-lagged associations between variables. By comparing the standardized cross-lagged coefficients, the relative strength of these associations can be evaluated in order to determine important driving forces in the dynamic system. The aim of this study was twofold: first, to illustrate the added value of a multilevel multivariate autoregressive modeling approach for investigating these associations over more traditional techniques; and second, to discuss how the coefficients of the multilevel autoregressive model should be standardized for comparing the strength of the cross-lagged associations. The hierarchical structure of multilevel multivariate autoregressive models complicates standardization, because subject-based statistics or group-based statistics can be used to standardize the coefficients, and each method may result in different conclusions. We argue that in order to make a meaningful comparison of the strength of the cross-lagged associations, the coefficients should be standardized within persons. We further illustrate the bivariate multilevel autoregressive model and the standardization of the coefficients, and we show that disregarding individual differences in dynamics can prove misleading, by means of an empirical example on experienced competence and exhaustion in persons diagnosed with burnout. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

An Illustration of a Longitudinal Cross-Lagged Design for Larger Structural Equation Models. Teacher's Corner.

ERIC Educational Resources Information Center

Burkholder, Gary J.; Harlow, Lisa L.

2003-01-01

Tested a model of HIV behavior risk, using a fully cross-lagged, longitudinal design to illustrate the analysis of larger structural equation models. Data from 527 women who completed a survey at three time points show excellent fit of the model to the data. (SLD)

Niche syndromes, species extinction risks, and management under climate change.

PubMed

Sax, Dov F; Early, Regan; Bellemare, Jesse

2013-09-01

The current distributions of species are often assumed to correspond with the total set of environmental conditions under which species can persist. When this assumption is incorrect, extinction risk estimated from species distribution models can be misleading. The degree to which species can tolerate or even thrive under conditions found beyond their current distributions alters extinction risks, time lags in realizing those risks, and the usefulness of alternative management strategies. To inform these issues, we propose a conceptual framework within which empirical data could be used to generate hypotheses regarding the realized, fundamental, and 'tolerance' niche of species. Although these niche components have rarely been characterized over geographic scales, we suggest that this could be done for many plant species by comparing native, naturalized, and horticultural distributions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Spatial and temporal dynamics of deep percolation, lag time and recharge in an irrigated semi-arid region

NASA Astrophysics Data System (ADS)

Nazarieh, F.; Ansari, H.; Ziaei, A. N.; Izady, A.; Davari, K.; Brunner, P.

2018-05-01

The time required for deep percolating water to reach the water table can be considerable in areas with a thick vadose zone. Sustainable groundwater management, therefore, has to consider the spatial and temporal dynamics of groundwater recharge. The key parameters that control the lag time have been widely examined in soil physics using small-scale lysimeters and modeling studies. However, only a small number of studies have analyzed how deep-percolation rates affect groundwater recharge dynamics over large spatial scales. This study examined how the parameters influencing lag time affect groundwater recharge in a semi-arid catchment under irrigation (in northeastern Iran) using a numerical modeling approach. Flow simulations were performed by the MODFLOW-NWT code with the Vadose-Zone Flow (UZF) Package. Calibration of the groundwater model was based on data from 48 observation wells. Flow simulations showed that lag times vary from 1 to more than 100 months. A sensitivity analysis demonstrated that during drought conditions, the lag time was highly sensitive to the rate of deep percolation. The study illustrated two critical points: (1) the importance of providing estimates of the lag time as a basis for sustainable groundwater management, and (2) lag time not only depends on factors such as soil hydraulic conductivity or vadose zone depth but also depends on the deep-percolation rates and the antecedent soil-moisture condition. Therefore, estimates of the lag time have to be associated with specific percolation rates, in addition to depth to groundwater and soil properties.

Effects of temperature on mortality in Hong Kong: a time series analysis

NASA Astrophysics Data System (ADS)

Yi, Wen; Chan, Albert P. C.

2015-07-01

Although interest in assessing the impacts of hot temperature and mortality in Hong Kong has increased, less evidence on the effect of cold temperature on mortality is available. We examined both the effects of heat and cold temperatures on daily mortality in Hong Kong for the last decade (2002-2011). A quasi-Poisson model combined with a distributed lag non-linear model was used to assess the non-linear and delayed effects of temperatures on cause-specific and age-specific mortality. Non-linear effects of temperature on mortality were identified. The relative risk of non-accidental mortality associated with cold temperature (11.1 °C, 1st percentile of temperature) relative to 19.4 °C (25th percentile of temperature) was 1.17 (95 % confidence interval (CI): 1.04, 1.29) for lags 0-13. The relative risk of non-accidental mortality associated with high temperature (31.5 °C, 99th percentile of temperature) relative to 27.8 °C (75th percentile of temperature) was 1.09 (95 % CI: 1.03, 1.17) for lags 0-3. In Hong Kong, extreme cold and hot temperatures increased the risk of mortality. The effect of cold lasted longer and greater than that of heat. People older than 75 years were the most vulnerable group to cold temperature, while people aged 65-74 were the most vulnerable group to hot temperature. Our findings may have implications for developing intervention strategies for extreme cold and hot temperatures.

Effects of temperature on mortality in Hong Kong: a time series analysis.

PubMed

Yi, Wen; Chan, Albert P C

2015-07-01

Although interest in assessing the impacts of hot temperature and mortality in Hong Kong has increased, less evidence on the effect of cold temperature on mortality is available. We examined both the effects of heat and cold temperatures on daily mortality in Hong Kong for the last decade (2002-2011). A quasi-Poisson model combined with a distributed lag non-linear model was used to assess the non-linear and delayed effects of temperatures on cause-specific and age-specific mortality. Non-linear effects of temperature on mortality were identified. The relative risk of non-accidental mortality associated with cold temperature (11.1 °C, 1st percentile of temperature) relative to 19.4 °C (25th percentile of temperature) was 1.17 (95% confidence interval (CI): 1.04, 1.29) for lags 0-13. The relative risk of non-accidental mortality associated with high temperature (31.5 °C, 99th percentile of temperature) relative to 27.8 °C (75th percentile of temperature) was 1.09 (95% CI: 1.03, 1.17) for lags 0-3. In Hong Kong, extreme cold and hot temperatures increased the risk of mortality. The effect of cold lasted longer and greater than that of heat. People older than 75 years were the most vulnerable group to cold temperature, while people aged 65-74 were the most vulnerable group to hot temperature. Our findings may have implications for developing intervention strategies for extreme cold and hot temperatures.

Modelling the growth of Leuconostoc mesenteroides by Artificial Neural Networks.

PubMed

García-Gimeno, R M; Hervás-Martínez, C; Rodríguez-Pérez, R; Zurera-Cosano, G

2005-12-15

The combined effect of temperature (10.5 to 24.5 degrees C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the predicted specific growth rate (Gr), lag-time (Lag) and maximum population density (yEnd) of Leuconostoc mesenteroides under aerobic and anaerobic conditions, was studied using an Artificial Neural Network-based model (ANN) in comparison with Response Surface Methodology (RS). For both aerobic and anaerobic conditions, two types of ANN model were elaborated, unidimensional for each of the growth parameters, and multidimensional in which the three parameters Gr, Lag, and yEnd are combined. Although in general no significant statistical differences were observed between both types of model, we opted for the unidimensional model, because it obtained the lowest mean value for the standard error of prediction for generalisation. The ANN models developed provided reliable estimates for the three kinetic parameters studied; the SEP values in aerobic conditions ranged from between 2.82% for Gr, 6.05% for Lag and 10% for yEnd, a higher degree accuracy than those of the RS model (Gr: 9.54%; Lag: 8.89%; yEnd: 10.27%). Similar results were observed for anaerobic conditions. During external validation, a higher degree of accuracy (Af) and bias (Bf) were observed for the ANN model compared with the RS model. ANN predictive growth models are a valuable tool, enabling swift determination of L. mesenteroides growth parameters.

Exploring lag times between monthly atmospheric deposition and stream chemistry in Appalachian forests using cross-correlation

NASA Astrophysics Data System (ADS)

DeWalle, David R.; Boyer, Elizabeth W.; Buda, Anthony R.

2016-12-01

Forecasts of ecosystem changes due to variations in atmospheric emissions policies require a fundamental understanding of lag times between changes in chemical inputs and watershed response. Impacts of changes in atmospheric deposition in the United States have been documented using national and regional long-term environmental monitoring programs beginning several decades ago. Consequently, time series of weekly NADP atmospheric wet deposition and monthly EPA-Long Term Monitoring stream chemistry now exist for much of the Northeast which may provide insights into lag times. In this study of Appalachian forest basins, we estimated lag times for S, N and Cl by cross-correlating monthly data from four pairs of stream and deposition monitoring sites during the period from 1978 to 2012. A systems or impulse response function approach to cross-correlation was used to estimate lag times where the input deposition time series was pre-whitened using regression modeling and the stream response time series was filtered using the deposition regression model prior to cross-correlation. Cross-correlations for S were greatest at annual intervals over a relatively well-defined range of lags with the maximum correlations occurring at mean lags of 48 months. Chloride results were similar but more erratic with a mean lag of 57 months. Few high-correlation lags for N were indicated. Given the growing availability of atmospheric deposition and surface water chemistry monitoring data and our results for four Appalachian basins, further testing of cross-correlation as a method of estimating lag times on other basins appears justified.

Modelling growth of Penicillium expansum and Aspergillus niger at constant and fluctuating temperature conditions.

PubMed

Gougouli, Maria; Koutsoumanis, Konstantinos P

2010-06-15

The growth of Penicillium expansum and Aspergillus niger, isolated from yogurt production environment, was investigated on malt extract agar with pH=4.2 and a(w)=0.997, simulating yogurt, at isothermal conditions ranging from -1.3 to 35 degrees C and from 5 to 42.3 degrees C, respectively. The growth rate (mu) and (apparent) lag time (lambda) of the mycelium growth were modelled as a function of temperature using a Cardinal Model with Inflection (CMI). The results showed that the CMI can describe successfully the effect of temperature on fungal growth within the entire biokinetic range for both isolates. The estimated values of the CMI for mu were T(min)=-5.74 degrees C, T(max)=30.97 degrees C, T(opt)=22.08 degrees C and mu(opt)=0.221 mm/h for P. expansum and T(min)=10.13 degrees C, T(max)=43.13 degrees C, T(opt)=31.44 degrees C, and mu(opt)=0.840 mm/h for A. niger. The cardinal values for lambda were very close to the respective values for mu indicating similar temperature dependence of the growth rate and the lag time of the mycelium growth. The developed models were further validated under fluctuating temperature conditions using various dynamic temperature scenarios. The time-temperature conditions studied included single temperature shifts before or after the end of the lag time and continuous periodic temperature fluctuations. The prediction of growth at changing temperature was based on the assumption that after a temperature shift the growth rate is adopted instantaneously to the new temperature, while the lag time was predicted using a cumulative lag approach. The results showed that when the temperature shifts occurred before the end of the lag, they did not cause any significant additional lag and the observed total lag was very close to the cumulative lag predicted by the model. In experiments with temperature shifts after the end of the lag time, accurate predictions were obtained when the temperature profile included temperatures which were inside the region of growth, showing that the assumption that mu is adopted instantaneously to the current temperature is concrete. In contrast, for scenarios with temperatures close or outside the growth region the models overestimated growth, indicating that fungi were stressed by this type of temperature shifts. The present study provides useful data for understanding the behavior of P. expansum and A. niger at dynamic temperature conditions while the developed models can be used as effective tools in assessing the risk of fungal spoilage and predicting shelf life of foods. Copyright 2010. Published by Elsevier B.V.

An objective method to determine the probability distribution of the minimum apparent age of a sample of radio-isotopic dates

NASA Astrophysics Data System (ADS)

Ickert, R. B.; Mundil, R.

2012-12-01

Dateable minerals (especially zircon U-Pb) that crystallized at high temperatures but have been redeposited, pose both unique opportunities and challenges for geochronology. Although they have the potential to provide useful information on the depositional age of their host rocks, their relationship to the host is not always well constrained. For example, primary volcanic deposits will often have a lag time (time between eruption and deposition) that is smaller than can be resolved using radiometric techniques, and the age of eruption and of deposition will be coincident within uncertainty. Alternatively, ordinary clastic sedimentary rocks will usually have a long and variable lag time, even for the youngest minerals. Intermediate cases, for example moderately reworked volcanogenic material, will have a short, but unknown lag time. A compounding problem with U-Pb zircon is that the residence time of crystals in their host magma chamber (time between crystallization and eruption) can be high and is variable, even within the products of a single eruption. In cases where the lag and/or residence time suspected to be large relative to the precision of the date, a common objective is to determine the minimum age of a sample of dates, in order to constrain the maximum age of the deposition of the host rock. However, both the extraction of that age as well as assignment of a meaningful uncertainty is not straightforward. A number of ad hoc techniques have been employed in the literature, which may be appropriate for particular data sets or specific problems, but may yield biased or misleading results. Ludwig (2012) has developed an objective, statistically justified method for the determination of the distribution of the minimum age, but it has not been widely adopted. Here we extend this algorithm with a bootstrap (which can show the effect - if any - of the sampling distribution itself). This method has a number of desirable characteristics: It can incorporate all data points while being resistant to outliers, it utilizes the measurement uncertainties, and it does not require the assumption that any given cluster of data represents a single geological event. In brief, the technique generates a synthetic distribution from the input data by resampling with replacement (a bootstrap). Each resample is a random selection from a Gaussian distribution defined by the mean and uncertainty of the data point. For this distribution, the minimum value is calculated. This procedure is repeated many times (>1000) and a distribution of minimum values is generated, from which a confidence interval can be constructed. We demonstrate the application of this technique using natural and synthetic datasets, show the advantages and limitations, and relate it to other methods. We emphasize that this estimate remains strictly a minimum age - as with any other estimate that does not explicitly incorporate lag or residence time, it will not reflect a depositional age if the lag/residence time is larger than the uncertainty of the estimate. We recommend that this or similar techniques be considered by geochronologists. Ludwig, K.R., 2012. Isoplot 3.75, A geochronological toolkit for Microsoft Excel; Berkeley Geochronology Center Special Publication no. 5

Analysis on ultrashort-pulse laser ablation for nanoscale film of ceramics

NASA Astrophysics Data System (ADS)

Ho, C. Y.; Tsai, Y. H.; Chiou, Y. J.

2017-06-01

This paper uses the dual-phase-lag model to study the ablation characteristics of femtosecond laser processing for nanometer-sized ceramic films. In ultrafast process and ultrasmall size where the two lags occur, a dual-phase-lag can be applied to analyse the ablation characteristics of femtosecond laser processing for materials. In this work, the ablation rates of nanometer-sized lead zirconate titanate (PZT) ceramics are investigated using a dual-phase-lag and the model is solved by Laplace transform method. The results obtained from this work are validated by the available experimental data. The effects of material thermal properties on the ablation characteristics of femtosecond laser processing for ceramics are also discussed.

Size-segregated particle number concentrations and respiratory emergency room visits in Beijing, China.

PubMed

Leitte, Arne Marian; Schlink, Uwe; Herbarth, Olf; Wiedensohler, Alfred; Pan, Xiao-Chuan; Hu, Min; Richter, Matthia; Wehner, Birgit; Tuch, Thomas; Wu, Zhijun; Yang, Minjuan; Liu, Liqun; Breitner, Susanne; Cyrys, Josef; Peters, Annette; Wichmann, H-Erich; Franck, Ulrich

2011-04-01

The link between concentrations of particulate matter (PM) and respiratory morbidity has been investigated in numerous studies. The aim of this study was to analyze the role of different particle size fractions with respect to respiratory health in Beijing, China. Data on particle size distributions from 3 nm to 1 µm; PM10 (PM ≤ 10 µm), nitrogen dioxide (NO(2)), and sulfur dioxide concentrations; and meteorologic variables were collected daily from March 2004 to December 2006. Concurrently, daily counts of emergency room visits (ERV) for respiratory diseases were obtained from the Peking University Third Hospital. We estimated pollutant effects in single- and two-pollutant generalized additive models, controlling for meteorologic and other time-varying covariates. Time-delayed associations were estimated using polynomial distributed lag, cumulative effects, and single lag models. Associations of respiratory ERV with NO(2) concentrations and 100-1,000 nm particle number or surface area concentrations were of similar magnitude-that is, approximately 5% increase in respiratory ERV with an interquartile range increase in air pollution concentration. In general, particles < 50 nm were not positively associated with ERV, whereas particles 50-100 nm were adversely associated with respiratory ERV, both being fractions of ultrafine particles. Effect estimates from two-pollutant models were most consistent for NO(2). Present levels of air pollution in Beijing were adversely associated with respiratory ERV. NO(2) concentrations seemed to be a better surrogate for evaluating overall respiratory health effects of ambient air pollution than PM(10) or particle number concentrations in Beijing.

Prenatal Particulate Air Pollution and Asthma Onset in Urban Children. Identifying Sensitive Windows and Sex Differences.

PubMed

Hsu, Hsiao-Hsien Leon; Chiu, Yueh-Hsiu Mathilda; Coull, Brent A; Kloog, Itai; Schwartz, Joel; Lee, Alison; Wright, Robert O; Wright, Rosalind J

2015-11-01

The influence of particulate air pollution on respiratory health starts in utero. Fetal lung growth and structural development occurs in stages; thus, effects on postnatal respiratory disorders may differ based on timing of exposure. We implemented an innovative method to identify sensitive windows for effects of prenatal exposure to particulate matter with a diameter less than or equal to 2.5 μm (PM2.5) on children's asthma development in an urban pregnancy cohort. Analyses included 736 full-term (≥37 wk) children. Each mother's daily PM2.5 exposure was estimated over gestation using a validated satellite-based spatiotemporal resolved model. Using distributed lag models, we examined associations between weekly averaged PM2.5 levels over pregnancy and physician-diagnosed asthma in children by age 6 years. Effect modification by sex was also examined. Most mothers were ethnic minorities (54% Hispanic, 30% black), had 12 or fewer years of education (66%), and did not smoke in pregnancy (80%). In the sample as a whole, distributed lag models adjusting for child age, sex, and maternal factors (education, race and ethnicity, smoking, stress, atopy, prepregnancy obesity) showed that increased PM2.5 exposure levels at 16-25 weeks gestation were significantly associated with early childhood asthma development. An interaction between PM2.5 and sex was significant (P = 0.01) with sex-stratified analyses showing that the association exists only for boys. Higher prenatal PM2.5 exposure at midgestation was associated with asthma development by age 6 years in boys. Methods to better characterize vulnerable windows may provide insight into underlying mechanisms.

Hierarchical Distributed-Lag Models: Exploring Varying Geographic Scale and Magnitude in Associations Between the Built Environment and Health.

PubMed

Baek, Jonggyu; Sanchez-Vaznaugh, Emma V; Sánchez, Brisa N

2016-03-15

It is well known that associations between features of the built environment and health depend on the geographic scale used to construct environmental attributes. In the built environment literature, it has long been argued that geographic scales may vary across study locations. However, this hypothesized variation has not been systematically examined due to a lack of available statistical methods. We propose a hierarchical distributed-lag model (HDLM) for estimating the underlying overall shape of food environment-health associations as a function of distance from locations of interest. This method enables indirect assessment of relevant geographic scales and captures area-level heterogeneity in the magnitudes of associations, along with relevant distances within areas. The proposed model was used to systematically examine area-level variation in the association between availability of convenience stores around schools and children's weights. For this case study, body mass index (weight kg)/height (m)2) z scores (BMIz) for 7th grade children collected via California's 2001-2009 FitnessGram testing program were linked to a commercial database that contained locations of food outlets statewide. Findings suggested that convenience store availability may influence BMIz only in some places and at varying distances from schools. Future research should examine localized environmental or policy differences that may explain the heterogeneity in convenience store-BMIz associations. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Non steady-state descriptions of drug permeation through stratum corneum. I. The biphasic brick-and-mortar model.

PubMed

Heisig, M; Lieckfeldt, R; Wittum, G; Mazurkevich, G; Lee, G

1996-03-01

The diffusion equation should be solved for the non-steady-state problem of drug diffusion within a two-dimensional, biphasic stratum corneum membrane having homogeneous lipid and corneocyte phases. A numerical method was developed for a brick-and-mortar SC-geometry, enabling an explicit solution for time-dependent drug concentration within both phases. The lag time and permeability were calculated. It is shown how the barrier property of this model membrane depends on relative phase permeability, corneocyte alignment, and corneocyte-lipid partition coefficient. Additionally, the time-dependent drug concentration profiles within the membrane can be observed during the lag and steady-state phases. The model SC-membrane predicts, from purely morphological principles, lag times and permeabilities that are in good agreement with experimental values. The long lag times and very small permeabilities reported for human SC can only be predicted for a highly-staggered corneocyte geometry and corneocytes that are 1000 times less permeable than the lipid phase. Although the former conclusion is reasonable, the latter is questionable. The elongated, flattened corneocyte shape renders lag time and permeability insensitive to large changes in their alignment within the SC. Corneocyte/lipid partitioning is found to be fundamentally different to SC/donor partitioning, since increasing drug lipophilicity always reduces both lag time and permeability.

A Large-scale Finite Element Model on Micromechanical Damage and Failure of Carbon Fiber/Epoxy Composites Including Thermal Residual Stress

NASA Astrophysics Data System (ADS)

Liu, P. F.; Li, X. K.

2018-06-01

The purpose of this paper is to study micromechanical progressive failure properties of carbon fiber/epoxy composites with thermal residual stress by finite element analysis (FEA). Composite microstructures with hexagonal fiber distribution are used for the representative volume element (RVE), where an initial fiber breakage is assumed. Fiber breakage with random fiber strength is predicted using Monte Carlo simulation, progressive matrix damage is predicted by proposing a continuum damage mechanics model and interface failure is simulated using Xu and Needleman's cohesive model. Temperature dependent thermal expansion coefficients for epoxy matrix are used. FEA by developing numerical codes using ANSYS finite element software is divided into two steps: 1. Thermal residual stresses due to mismatch between fiber and matrix are calculated; 2. Longitudinal tensile load is further exerted on the RVE to perform progressive failure analysis of carbon fiber/epoxy composites. Numerical convergence is solved by introducing the viscous damping effect properly. The extended Mori-Tanaka method that considers interface debonding is used to get homogenized mechanical responses of composites. Three main results by FEA are obtained: 1. the real-time matrix cracking, fiber breakage and interface debonding with increasing tensile strain is simulated. 2. the stress concentration coefficients on neighbouring fibers near the initial broken fiber and the axial fiber stress distribution along the broken fiber are predicted, compared with the results using the global and local load-sharing models based on the shear-lag theory. 3. the tensile strength of composite by FEA is compared with those by the shear-lag theory and experiments. Finally, the tensile stress-strain curve of composites by FEA is applied to the progressive failure analysis of composite pressure vessel.

A Large-scale Finite Element Model on Micromechanical Damage and Failure of Carbon Fiber/Epoxy Composites Including Thermal Residual Stress

NASA Astrophysics Data System (ADS)

Liu, P. F.; Li, X. K.

2017-09-01

The purpose of this paper is to study micromechanical progressive failure properties of carbon fiber/epoxy composites with thermal residual stress by finite element analysis (FEA). Composite microstructures with hexagonal fiber distribution are used for the representative volume element (RVE), where an initial fiber breakage is assumed. Fiber breakage with random fiber strength is predicted using Monte Carlo simulation, progressive matrix damage is predicted by proposing a continuum damage mechanics model and interface failure is simulated using Xu and Needleman's cohesive model. Temperature dependent thermal expansion coefficients for epoxy matrix are used. FEA by developing numerical codes using ANSYS finite element software is divided into two steps: 1. Thermal residual stresses due to mismatch between fiber and matrix are calculated; 2. Longitudinal tensile load is further exerted on the RVE to perform progressive failure analysis of carbon fiber/epoxy composites. Numerical convergence is solved by introducing the viscous damping effect properly. The extended Mori-Tanaka method that considers interface debonding is used to get homogenized mechanical responses of composites. Three main results by FEA are obtained: 1. the real-time matrix cracking, fiber breakage and interface debonding with increasing tensile strain is simulated. 2. the stress concentration coefficients on neighbouring fibers near the initial broken fiber and the axial fiber stress distribution along the broken fiber are predicted, compared with the results using the global and local load-sharing models based on the shear-lag theory. 3. the tensile strength of composite by FEA is compared with those by the shear-lag theory and experiments. Finally, the tensile stress-strain curve of composites by FEA is applied to the progressive failure analysis of composite pressure vessel.

Ozone and hypertensive disorders of pregnancy in Florida: Identifying critical windows of exposure.

PubMed

Hu, Hui; Ha, Sandie; Xu, Xiaohui

2017-02-01

Ozone (O 3 ) has been linked to hypertensive disorders of pregnancy (HDP). However, inconsistent results have been reported, and no study has examined the critical exposure windows during pregnancy. We used Florida birth vital statistics records to investigate the association between HDP and O 3 exposure among 655,529 pregnancies with conception dates between 2005 and 2007. Individual O 3 exposure was assessed at mothers' home address at the time of delivery using the Hierarchical Bayesian space-time statistical model. We examined the association during three predefined exposure windows including trimester 1, trimester 2, and trimesters 1&2, as well as in each week of the first two trimesters using distributed lag models. Pregnancies with HDP had a higher mean exposure to O 3 (39.07 in trimester 1, 39.02 in trimester 2, and 39.06 in trimesters 1&2, unit: ppb) than those without HDP (38.65 in trimester 1, 38.57 in trimester 2, and 38.61 in trimesters 1&2, unit: ppb). In the adjusted logistic regression model, increased odds of HDP were observed for each 5 ppb increase in O 3 (OR Trimester1 =1.04, 95% CI: 1.03, 1.06; OR Trimester2 =1.03, 95% CI: 1.02, 1.04; OR Trimester1&2 =1.07, 95% CI: 1.05, 1.08). In the distributed lag models, elevated odds of HDP were observed with increased O 3 exposure during the 1st to 24th weeks of gestation, with higher odds during early pregnancy. O 3 exposure during pregnancy is related to increased odds of HDP, and early pregnancy appears to be a potentially critical window of exposure. Copyright © 2016 Elsevier Inc. All rights reserved.

ARE THE kHz QPO LAGS IN NEUTRON STAR 4U 1608–52 DUE TO REVERBERATION?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cackett, Edward M., E-mail: ecackett@wayne.edu

2016-08-01

X-ray reverberation lags have recently been discovered in both active galactic nuclei (AGNs) and black hole X-ray binaries. A recent study of the neutron star low-mass X-ray binary (LMXB) 4U 1608 52 has also shown significant lags, whose properties hint at a reverberation origin. Here, we adapt general relativistic ray tracing impulse response functions used to model X-ray reverberation in AGNs for neutron star LMXBs. Assuming that relativistic reflection forms the broad iron line and associated reflection continuum, we use reflection fits to the energy spectrum along with the impulse response functions to calculate the expected lags as a functionmore » of energy over the range of observed kHz quasi-periodic oscillation (QPO) frequencies in 4U 1608 52. We find that the lag energy spectrum is expected to increase with increasing energy above 8 keV, while the observed lags in 4U 1608 52 show the opposite behavior. This demonstrates that the lags in the lower kHz QPO of 4U 1608 52 are not solely due to reverberation. We do note, however, that the models appear to be more consistent with the much flatter lag energy spectrum observed in the upper kHz QPO of several neutron star LMXBs, suggesting that lower and upper kHz QPOs may have different origins.« less

Effects of Extreme Temperatures on Cause-Specific Cardiovascular Mortality in China

PubMed Central

Wang, Xuying; Li, Guoxing; Liu, Liqun; Westerdahl, Dane; Jin, Xiaobin; Pan, Xiaochuan

2015-01-01

Objective: Limited evidence is available for the effects of extreme temperatures on cause-specific cardiovascular mortality in China. Methods: We collected data from Beijing and Shanghai, China, during 2007–2009, including the daily mortality of cardiovascular disease, cerebrovascular disease, ischemic heart disease and hypertensive disease, as well as air pollution concentrations and weather conditions. We used Poisson regression with a distributed lag non-linear model to examine the effects of extremely high and low ambient temperatures on cause-specific cardiovascular mortality. Results: For all cause-specific cardiovascular mortality, Beijing had stronger cold and hot effects than those in Shanghai. The cold effects on cause-specific cardiovascular mortality reached the strongest at lag 0–27, while the hot effects reached the strongest at lag 0–14. The effects of extremely low and high temperatures differed by mortality types in the two cities. Hypertensive disease in Beijing was particularly susceptible to both extremely high and low temperatures; while for Shanghai, people with ischemic heart disease showed the greatest relative risk (RRs = 1.16, 95% CI: 1.03, 1.34) to extremely low temperature. Conclusion: People with hypertensive disease were particularly susceptible to extremely low and high temperatures in Beijing. People with ischemic heart disease in Shanghai showed greater susceptibility to extremely cold days. PMID:26703637

Effects of Extreme Temperatures on Cause-Specific Cardiovascular Mortality in China.

PubMed

Wang, Xuying; Li, Guoxing; Liu, Liqun; Westerdahl, Dane; Jin, Xiaobin; Pan, Xiaochuan

2015-12-21

Limited evidence is available for the effects of extreme temperatures on cause-specific cardiovascular mortality in China. We collected data from Beijing and Shanghai, China, during 2007-2009, including the daily mortality of cardiovascular disease, cerebrovascular disease, ischemic heart disease and hypertensive disease, as well as air pollution concentrations and weather conditions. We used Poisson regression with a distributed lag non-linear model to examine the effects of extremely high and low ambient temperatures on cause-specific cardiovascular mortality. For all cause-specific cardiovascular mortality, Beijing had stronger cold and hot effects than those in Shanghai. The cold effects on cause-specific cardiovascular mortality reached the strongest at lag 0-27, while the hot effects reached the strongest at lag 0-14. The effects of extremely low and high temperatures differed by mortality types in the two cities. Hypertensive disease in Beijing was particularly susceptible to both extremely high and low temperatures; while for Shanghai, people with ischemic heart disease showed the greatest relative risk (RRs = 1.16, 95% CI: 1.03, 1.34) to extremely low temperature. People with hypertensive disease were particularly susceptible to extremely low and high temperatures in Beijing. People with ischemic heart disease in Shanghai showed greater susceptibility to extremely cold days.

Large Daily Stock Variation Is Associated with Cardiovascular Mortality in Two Cities of Guangdong, China

PubMed Central

Lin, Hualiang; Zhang, Yonghui; Xu, Yanjun; Liu, Tao; Xiao, Jianpeng; Luo, Yuan; Xu, Xiaojun; He, Yanhui; Ma, Wenjun

2013-01-01

Objective The current study aimed to examine the effects of daily change of the Shenzhen Stock Exchange Index on cardiovascular mortality in Guangzhou and Taishan, China. Methods Daily mortality and stock performance data during 2006–2010 were collected to construct the time series for the two cities. A distributed lag non-linear model was utilized to examine the effect of daily stock index changes on cardiovascular mortality after controlling for potential confounding factors. Results We observed a delayed non-linear effect of the stock index change on cardiovascular mortality: both rising and declining of the stock index were associated with increased cardiovascular deaths. In Guangzhou, the 15–25 lag days cumulative relative risk of an 800 index drop was 2.08 (95% CI: 1.38–3.14), and 2.38 (95% CI: 1.31–4.31) for an 800 stock index increase on the cardiovascular mortality, respectively. In Taishan, the cumulative relative risk over 15–25 days lag was 1.65 (95% CI: 1.13–2.42) for an 800 index drop and 2.08 (95% CI: 1.26–3.42) for an 800 index rising, respectively. Conclusions Large ups and downs in daily stock index might be important predictor of cardiovascular mortality. PMID:23874619

Summer outdoor temperature and occupational heat-related illnesses in Quebec (Canada)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adam-Poupart, Ariane; Smargiassi, Audrey; Institut national de santé publique du Québec

2014-10-15

Background: Predicted rise in global mean temperature and intensification of heat waves associated with climate change present an increasing challenge for occupational health and safety. Although important scientific knowledge has been gathered on the health effects of heat, very few studies have focused on quantifying the association between outdoor heat and mortality or morbidity among workers. Objective: To quantify the association between occupational heat-related illnesses and exposure to summer outdoor temperatures. Methods: We modeled 259 heat-related illnesses compensated by the Workers' Compensation Board of Quebec between May and September, from 1998 to 2010, with maximum daily summer outdoor temperatures inmore » 16 health regions of Quebec (Canada) using generalized linear models with negative binomial distributions, and estimated the pooled effect sizes for all regions combined, by sex and age groups, and for different time lags with random-effect models for meta-analyses. Results: The mean daily compensation count was 0.13 for all regions of Quebec combined. The relationship between daily counts of compensations and maximum daily temperatures was log-linear; the pooled incidence rate ratio (IRR) of daily heat-related compensations per 1 °C increase in daily maximum temperatures was 1.419 (95% CI 1.326 to 1.520). Associations were similar for men and women and by age groups. Increases in daily maximum temperatures at lags 1 and 2 and for two and three-day lag averages were also associated with increases in daily counts of compensations (IRRs of 1.206 to 1.471 for every 1 °C increase in temperature). Conclusion: This study is the first to quantify the association between occupational heat-related illnesses and exposure to summer temperatures in Canada. The model (risk function) developed in this study could be useful to improve the assessment of future impacts of predicted summer outdoor temperatures on workers and vulnerable groups, particularly in colder temperate zones. - Highlights: • 259 heat-related compensated illnesses were modeled with ambient temperature • An overall risk ratio of 1.419 (95% CI 1.326–1.520) for every 1 °C increase was found • Risk estimates were similar for men and women and by large age groups. • There were little lag effects (IRRs of 1.206 to 1.471 for every 1 °C increase)« less

Association of cold temperature and mortality and effect modification in the subtropical plateau monsoon climate of Yuxi, China.

PubMed

Ding, Zan; Li, Liujiu; Wei, Ruqin; Dong, Wenya; Guo, Pi; Yang, Shaoyi; Liu, Ju; Zhang, Qingying

2016-10-01

Consistent evidence has shown excess mortality associated with cold temperature, but some important details of the cold-mortality association (e.g. slope and threshold) have not been adequately investigated and few studies focused on the cold effect in high-altitude areas of developing countries. We attempted to quantify the cold effect on mortality, identify the details, and evaluate effect modification in the distinct subtropical plateau monsoon climate of Yuxi, a high plateau region in southwest China. From daily mortality and meteorological data during 2009-2014, we used a quasi-Poisson model combined with a "natural cubic spline-natural cubic spline" distributed lag non-linear model to estimate the temperature-mortality relationship and then a simpler "hockey-stick" model to investigate the cold effect and details. Cold temperature was associated with increased mortality, and the relative risk of cold effect (1st relative to 10th temperature percentile) on non-accidental, cardiovascular, and respiratory mortality for lag 0-21 days was 1.40 (95% confidence interval: 1.19-1.66), 1.61 (1.28-2.02), and 1.13 (0.78-1.64), respectively. A 1°C decrease below a cold threshold of 9.1°C (8th percentile) for lags 0-21 was associated with a 7.35% (3.75-11.09%) increase in non-accidental mortality. The cold-mortality association was not significantly affected by cause-specific mortality, gender, age, marital status, ethnicity, occupation, or previous history of hypertension. There is an adverse impact of cold on mortality in Yuxi, China, and a temperature of 9.1°C is an important cut-off for cold-related mortality for residents. Copyright © 2016 Elsevier Inc. All rights reserved.

Response of Vegetation Dynamics to Projected Climate Change based on NDVI Simulations using Stepwise Cluster Analysis in the Three-River Headwaters Region of China

NASA Astrophysics Data System (ADS)

Zheng, Y.; Lv, E.; Huang, Y.

2016-12-01

Located in the hinterland of the Qinghai-Tibetan Plateau, the Three-River Headwaters region (THR) features unique eco-environmental conditions and fragile ecosystems, and is very vulnerable to climate change. To investigate the effects of climate change on the ecosystem, the Normalized Difference Vegetation Index (NDVI) was employed as an indicator to reflect the vegetation dynamics in response to climate change. This study proposed a model based on Stepwise-cluster analysis to predict the temporal and spatial distributions of NDVI values for five future years according to Global Circulation Models (GCMs) climate projections under the RCP4.5 scenario. The obtained spatial results showed very good agreements between simulations and remote sensing observations of the NDVI value for both training and validation, and the developed model demonstrated its capability of predicting the monthly changes of NDVI through representing the relationships between it and various climatic factors, including remote sensed precipitation and temperature with no, 1 and 2-month lag period. The monthly average precipitation with one-month lag period was further found to be the most important climatic factor that drives the changes of NDVI in the THR. Compared with the values of NDVI in 2000 - 2013, the predicting results indicate the values of NDVI for the THR in growing season (May to October) will decrease by 15.74% in the next 100 years, suggesting that the THR is going to experience an environmental degradation. The results also show that precipitation is the primary driving factor relative to temperature, especially the one-month-lag precipitation. Findings from this study would help policy makers draw up effective water resource and eco-environmental management strategies for adapting to climate change in the THR.

Measuring Asymmetric Interactions in Resting State Brain Networks*

PubMed Central

Joshi, Anand A.; Salloum, Ronald; Bhushan, Chitresh; Leahy, Richard M.

2015-01-01

Directed graph representations of brain networks are increasingly being used in brain image analysis to indicate the direction and level of influence among brain regions. Most of the existing techniques for directed graph representations are based on time series analysis and the concept of causality, and use time lag information in the brain signals. These time lag-based techniques can be inadequate for functional magnetic resonance imaging (fMRI) signal analysis due to the limited time resolution of fMRI as well as the low frequency hemodynamic response. The aim of this paper is to present a novel measure of necessity that uses asymmetry in the joint distribution of brain activations to infer the direction and level of interaction among brain regions. We present a mathematical formula for computing necessity and extend this measure to partial necessity, which can potentially distinguish between direct and indirect interactions. These measures do not depend on time lag for directed modeling of brain interactions and therefore are more suitable for fMRI signal analysis. The necessity measures were used to analyze resting state fMRI data to determine the presence of hierarchy and asymmetry of brain interactions during resting state. We performed ROI-wise analysis using the proposed necessity measures to study the default mode network. The empirical joint distribution of the fMRI signals was determined using kernel density estimation, and was used for computation of the necessity and partial necessity measures. The significance of these measures was determined using a one-sided Wilcoxon rank-sum test. Our results are consistent with the hypothesis that the posterior cingulate cortex plays a central role in the default mode network. PMID:26221690

Environmental effects and individual body condition drive seasonal fecundity of rabbits: identifying acute and lagged processes.

PubMed

Wells, Konstans; O'Hara, Robert B; Cooke, Brian D; Mutze, Greg J; Prowse, Thomas A A; Fordham, Damien A

2016-07-01

The reproduction of many species is determined by seasonally-driven resource supply. But it is difficult to quantify whether the fecundity is sensitive to short- or long-term exposure to environmental conditions such as rainfall that drive resource supply. Using 25 years of data on individual fecundity of European female rabbits, Oryctolagus cuniculus, from semiarid Australia, we investigate the role of individual body condition, rainfall and temperature as drivers of seasonal and long-term and population-level changes in fecundity (breeding probability, ovulation rate, embryo survival). We built distributed lag models in a hierarchical Bayesian framework to account for both immediate and time-lagged effects of climate and other environmental drivers, and possible shifts in reproduction over consecutive seasons. We show that rainfall during summer, when rabbits typically breed only rarely, increased breeding probability immediately and with time lags of up to 10 weeks. However, an earlier onset of the yearly breeding period did not result in more overall reproductive output. Better body condition was associated with an earlier onset of breeding and higher embryo survival. Breeding probability in the main breeding season declined with increased breeding activity in the preceding season and only individuals in good body condition were able to breed late in the season. Higher temperatures reduce breeding success across seasons. We conclude that a better understanding of seasonal dynamics and plasticity (and their interplay) in reproduction will provide crucial insights into how lagomorphs are likely to respond and potentially adapt to the influence of future climate and other environmental change.

Air pollution and mortality in Latin America: the role of education.

PubMed

O'Neill, Marie S; Bell, Michelle L; Ranjit, Nalini; Cifuentes, Luis A; Loomis, Dana; Gouveia, Nelson; Borja-Aburto, Victor H

2008-11-01

People with less education in Europe, Asia, and the United States are at higher risk of mortality associated with daily and longer-term air pollution exposure. We examined whether educational level modified associations between mortality and ambient particulate pollution (PM10) in Latin America, using several timescales. The study population included people who died during 1998-2002 in Mexico City, Mexico; Santiago, Chile; and São Paulo, Brazil. We fit city-specific robust Poisson regressions to daily deaths for nonexternal-cause mortality, and then stratified by age, sex, and educational attainment among adults older than age 21 years (none, some primary, some secondary, and high school degree or more). Predictor variables included a natural spline for temporal trend, linear PM10 and apparent temperature at matching lags, and day-of-week indicators. We evaluated PM10 for lags 0 and 1 day, and fit an unconstrained distributed lag model for cumulative 6-day effects. The effects of a 10-microg/m increment in lag 1 PM10 on all nonexternal-cause adult mortality were for Mexico City 0.39% (95% confidence interval = 0.13%-0.65%); São Paulo 1.04% (0.71%-1.38%); and for Santiago 0.61% (0.40%-0.83%). We found cumulative 6-day effects for adult mortality in Santiago (0.86% [0.48%-1.23%]) and São Paulo (1.38% [0.85%-1.91%]), but no consistent gradients by educational status. PM10 had important short- and intermediate-term effects on mortality in these Latin American cities, but associations did not differ consistently by educational level.

Modeling of wave-coherent pressures in the turbulent boundary layer above water waves

NASA Technical Reports Server (NTRS)

Papadimitrakis, Yiannis ALEX.

1988-01-01

The behavior of air pressure fluctuations induced by progressive water waves generated mechanically in a laboratory tank was simulated by solving a modified Orr-Sommerfeld equation in a transformed Eulerian wave-following frame of reference. Solution is obtained by modeling the mean and wave-coherent turbulent Reynolds stresses, the behavior of which in the turbulent boundary layer above the waves was simulated using a turbulent kinetic energy-dissipation model, properly modified to account for free-surface proximity and favorable pressure gradient effects. The distribution of both the wave-coherent turbulent Reynolds stress and pressure amplitudes and their corresponding phase lags was found to agree reasonably well with available laboratory data.

Animal reservoir, natural and socioeconomic variations and the transmission of hemorrhagic fever with renal syndrome in Chenzhou, China, 2006-2010.

PubMed

Xiao, Hong; Tian, Huai-Yu; Gao, Li-Dong; Liu, Hai-Ning; Duan, Liang-Song; Basta, Nicole; Cazelles, Bernard; Li, Xiu-Jun; Lin, Xiao-Ling; Wu, Hong-Wei; Chen, Bi-Yun; Yang, Hui-Suo; Xu, Bing; Grenfell, Bryan

2014-01-01

China has the highest incidence of hemorrhagic fever with renal syndrome (HFRS) worldwide. Reported cases account for 90% of the total number of global cases. By 2010, approximately 1.4 million HFRS cases had been reported in China. This study aimed to explore the effect of the rodent reservoir, and natural and socioeconomic variables, on the transmission pattern of HFRS. Data on monthly HFRS cases were collected from 2006 to 2010. Dynamic rodent monitoring data, normalized difference vegetation index (NDVI) data, climate data, and socioeconomic data were also obtained. Principal component analysis was performed, and the time-lag relationships between the extracted principal components and HFRS cases were analyzed. Polynomial distributed lag (PDL) models were used to fit and forecast HFRS transmission. Four principal components were extracted. Component 1 (F1) represented rodent density, the NDVI, and monthly average temperature. Component 2 (F2) represented monthly average rainfall and monthly average relative humidity. Component 3 (F3) represented rodent density and monthly average relative humidity. The last component (F4) represented gross domestic product and the urbanization rate. F2, F3, and F4 were significantly correlated, with the monthly HFRS incidence with lags of 4 months (r = -0.289, P<0.05), 5 months (r = -0.523, P<0.001), and 0 months (r = -0.376, P<0.01), respectively. F1 was correlated with the monthly HFRS incidence, with a lag of 4 months (r = 0.179, P = 0.192). Multivariate PDL modeling revealed that the four principal components were significantly associated with the transmission of HFRS. The monthly trend in HFRS cases was significantly associated with the local rodent reservoir, climatic factors, the NDVI, and socioeconomic conditions present during the previous months. The findings of this study may facilitate the development of early warning systems for the control and prevention of HFRS and similar diseases.

Gravel sediment routing from widespread, low-intensity landscape disturbance, Current River basin, Missouri

USGS Publications Warehouse

Jacobson, Robert B.; Gran, K.B.

1999-01-01

During the last 160 years, land-use changes in the Ozarks have had the potential to cause widespread, low-intensity delivery of excess amounts of gravel-sized sediment to stream channels. Previous studies have indicated that this excess gravel bedload is moving in wave-like forms through Ozarks drainage basins. The longitudinal, areal distribution of gravel bars along 160 km of the Current River, Missouri, was evaluated to determine the relative effects of valley-scale controls, tributary basin characteristics, and lagged sediment transport in creating areas of gravel accumulations. The longitudinal distribution of gravel-bar area shows a broad scale wave-like form with increases in gravel-bar area weakly associated with tributary junctions. Secondary peaks of gravel area with 1·8–4·1 km spacing (disturbance reaches) are superimposed on the broad form. Variations in valley width explain some, but not all, of the short-spacing variation in gravel-bar area. Among variables describing tributary drainage basin morphometry, present-day land use and geologic characteristics, only drainage area and road density relate even weakly to gravel-bar areal inventories. A simple, channel network-based sediment routing model shows that many of the features of the observed longitudinal gravel distribution can be replicated by uniform transport of sediment from widespread disturbances through a channel network. These results indicate that lagged sediment transport may have a dominant effect on the synoptic spatial distribution of gravel in Ozarks streams; present-day land uses are only weakly associated with present-day gravel inventories; and valley-scale characteristics have secondary controls on gravel accumulations in disturbance reaches.

Mortality risks during extreme temperature events (ETEs) using a distributed lag non-linear model

NASA Astrophysics Data System (ADS)

Allen, Michael J.; Sheridan, Scott C.

2018-01-01

This study investigates the relationship between all-cause mortality and extreme temperature events (ETEs) from 1975 to 2004. For 50 U.S. locations, these heat and cold events were defined based on location-specific thresholds of daily mean apparent temperature. Heat days were defined by a 3-day mean apparent temperature greater than the 95th percentile while extreme heat days were greater than the 97.5th percentile. Similarly, calculations for cold and extreme cold days relied upon the 5th and 2.5th percentiles. A distributed lag non-linear model assessed the relationship between mortality and ETEs for a cumulative 14-day period following exposure. Subsets for season and duration effect denote the differences between early- and late-season as well as short and long ETEs. While longer-lasting heat days resulted in elevated mortality, early season events also impacted mortality outcomes. Over the course of the summer season, heat-related risk decreased, though prolonged heat days still had a greater influence on mortality. Unlike heat, cold-related risk was greatest in more southerly locations. Risk was highest for early season cold events and decreased over the course of the winter season. Statistically, short episodes of cold showed the highest relative risk, suggesting unsettled weather conditions may have some relationship to cold-related mortality. For both heat and cold, results indicate higher risk to the more extreme thresholds. Risk values provide further insight into the role of adaptation, geographical variability, and acclimatization with respect to ETEs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Yan-Fei; Green, Paul J.; Pancoast, Anna

We study the time lags between the continuum emission of quasars at different wavelengths, based on more than four years of multi-band ( g , r , i , z ) light curves in the Pan-STARRS Medium Deep Fields. As photons from different bands emerge from different radial ranges in the accretion disk, the lags constrain the sizes of the accretion disks. We select 240 quasars with redshifts of z ≈ 1 or z ≈ 0.3 that are relatively emission-line free. The light curves are sampled from day to month timescales, which makes it possible to detect lags on themore » scale of the light crossing time of the accretion disks. With the code JAVELIN , we detect typical lags of several days in the rest frame between the g band and the riz bands. The detected lags are ∼2–3 times larger than the light crossing time estimated from the standard thin disk model, consistent with the recently measured lag in NGC 5548 and microlensing measurements of quasars. The lags in our sample are found to increase with increasing luminosity. Furthermore, the increase in lags going from g − r to g − i and then to g − z is slower than predicted in the thin disk model, particularly for high-luminosity quasars. The radial temperature profile in the disk must be different from what is assumed. We also find evidence that the lags decrease with increasing line ratios between ultraviolet Fe ii lines and Mg ii, which may point to changes in the accretion disk structure at higher metallicity.« less

Associations between ambient air pollution and daily mortality in a cohort of congestive heart failure: Case-crossover and nested case-control analyses using a distributed lag nonlinear model.

PubMed

Buteau, Stephane; Goldberg, Mark S; Burnett, Richard T; Gasparrini, Antonio; Valois, Marie-France; Brophy, James M; Crouse, Dan L; Hatzopoulou, Marianne

2018-04-01

Persons with congestive heart failure may be at higher risk of the acute effects related to daily fluctuations in ambient air pollution. To meet some of the limitations of previous studies using grouped-analysis, we developed a cohort study of persons with congestive heart failure to estimate whether daily non-accidental mortality were associated with spatially-resolved, daily exposures to ambient nitrogen dioxide (NO 2 ) and ozone (O 3 ), and whether these associations were modified according to a series of indicators potentially reflecting complications or worsening of health. We constructed the cohort from the linkage of administrative health databases. Daily exposure was assigned from different methods we developed previously to predict spatially-resolved, time-dependent concentrations of ambient NO 2 (all year) and O 3 (warm season) at participants' residences. We performed two distinct types of analyses: a case-crossover that contrasts the same person at different times, and a nested case-control that contrasts different persons at similar times. We modelled the effects of air pollution and weather (case-crossover only) on mortality using distributed lag nonlinear models over lags 0 to 3 days. We developed from administrative health data a series of indicators that may reflect the underlying construct of "declining health", and used interactions between these indicators and the cross-basis function for air pollutant to assess potential effect modification. The magnitude of the cumulative as well as the lag-specific estimates of association differed in many instances according to the metric of exposure. Using the back-extrapolation method, which is our preferred exposure model, we found for the case-crossover design a cumulative mean percentage changes (MPC) in daily mortality per interquartile increment in NO 2 (8.8 ppb) of 3.0% (95% CI: -0.9, 6.9%) and for O 3 (16.5 ppb) 3.5% (95% CI: -4.5, 12.1). For O 3 there was strong confounding by weather (unadjusted MPC = 7.1%; 95% CI: 1.7, 12.7%). For the nested case-control approach the cumulative MPC for NO 2 in daily mortality was 2.9% (95% CI: -0.9, 6.9%) and for O 3 7.3% (95% CI: 3.0, 11.9%). We found evidence of effect modification between daily mortality and cumulative NO 2 and O 3 according to the prescribed dose of furosemide in the nested case-control analysis, but not in the case-crossover analysis. Mortality in congestive heart failure was associated with exposure to daily ambient NO 2 and O 3 predicted from a back-extrapolation method using a land use regression model from dense sampling surveys. The methods used to assess exposure can have considerable influence on the estimated acute health effects of the two air pollutants. Copyright © 2018 Elsevier Ltd. All rights reserved.

Shear-lag analysis about an internally-dropped ply

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vizzini, A.J.

1995-12-31

The region around a terminated ply is modeled as several elastic layers separated by shear regions. A shear-lag analysis is then performed allowing for the thickness of the elastic and shear layers to vary. Boundary conditions, away for the ply drop, are based on the deflections determined by a finite element model. The interlaminar stresses are compared against those generated by the finite element model for tapered laminates under pure extension, pure bending, and extension-bending coupling. The shear-lag analysis predicts the interlaminar shear at and near the ply drop for pure extension and in cases involving bending if the deflectionsmore » due to bending are removed. The interlaminar shear stress and force equilibrium are used to determine the interlaminar normal stress. The trends in the interlaminar normal stress shown by the finite element model are partially captured by the shear-lag analysis. This simple analysis indicates that the mechanism for load transfer about a ply drop is primarily due to shear transfer through the resin rich areas.« less

Improving the effectiveness of an interruption lag by inducing a memory-based strategy.

PubMed

Morgan, Phillip L; Patrick, John; Tiley, Leyanne

2013-01-01

The memory for goals model (Altmann & Trafton, 2002) posits the importance of a short delay (the 'interruption lag') before an interrupting task to encode suspended goals for retrieval post-interruption. Two experiments used the theory of soft constraints (Gray, Simms, Fu & Schoelles, 2006) to investigate whether the efficacy of an interruption lag could be improved by increasing goal-state access cost to induce a more memory-based encoding strategy. Both experiments used a copying task with three access cost conditions (Low, Medium, and High) and a 5-s interruption lag with a no lag control condition. Experiment 1 found that the participants in the High access cost condition resumed more interrupted trials and executed more actions correctly from memory when coupled with an interruption lag. Experiment 2 used a prospective memory test post-interruption and an eyetracker recorded gaze activity during the interruption lag. The participants in the High access cost condition with an interruption lag were best at encoding target information during the interruption lag, evidenced by higher scores on the prospective memory measure and more gaze activity on the goal-state during the interruption lag. Theoretical and practical issues regarding the use of goal-state access cost and an interruption lag are discussed. Copyright © 2012. Published by Elsevier B.V.

[Impact of daily mean temperature, cold spells, and heat waves on stroke mortality a multivariable Meta-analysis from 12 counties of Hubei province, China].

PubMed

Zhang, Y Q; Yu, C H; Bao, J Z

2017-04-10

Objective: To assess the acute effects of daily mean temperature, cold spells, and heat waves on stroke mortality in 12 counties across Hubei province, China. Methods: Data related to daily mortality from stroke and meteorology in 12 counties across Hubei province during 2009-2012, were gathered. Distributed lag nonlinear model (DLNM) was first used, to estimate the county-specific associations between daily mean temperature, cold spells, heat waves and stroke mortality. Multivariate Meta-analysis was then applied to pool the community-specific relationships between temperature and stroke mortality (exposure-response relationship) as well as both cold- and- heat-associated risks on mortality at different lag days (lag-response relationship). Results: During 2009-2012, a total population of 6.7 million was included in this study with 42 739 persons died of stroke. An average of 2.7 (from 0.5 to 6.0) stroke deaths occurred daily in each county, with annual average mean temperature as 16.6 ℃ (from 14.7 ℃ to 17.4 ℃) during the study period. An inverse J-shaped association between temperature and stroke mortality was observed at the provincial level. Pooled mortality effect of cold spells showed a 2-3-day delay and lasted about 10 days, while effect of heat waves appeared acute but attenuated within a few days. The mortality risks on cold-spell days ranged from 0.968 to 1.523 in 12 counties at lag 3-14, with pooled effect as 1.180 (95 %CI: 1.043-1.336). The pooled mortality risk (ranged from 0.675 to 2.066) on heat-wave days at lag 0-2 was 1.114 (95 %CI: 1.012-1.227). Conclusions: An inverse J-shaped association between temperature and stroke mortality was observed in Hubei province, China. Both cold spells and heat waves were associated with increased stroke mortality, while different lag patterns were observed in the mortality effects of heat waves and cold spells.

A three-level model for binary time-series data: the effects of air pollution on school absences in the Southern California Children's Health Study.

PubMed

Rondeau, Virginie; Berhane, Kiros; Thomas, Duncan C

2005-04-15

A three-level model is proposed to simultaneously examine the effects of daily exposure to air pollution and individual risk factors on health outcomes without aggregating over subjects or time. We used a logistic transition model with random effects to take into account heterogeneity and overdispersion of the observations. A distributed lag structure for pollution has been included, assuming that the event on day t for a subject depends on the levels of air pollution for several preceding days. We illustrate this proposed model via detailed analysis of the effect of air pollution on school absenteeism based on data from the Southern California Children's Health Study.

Evaluation of Airborne Remote Sensing Techniques for Predicting the Distribution of Energetic Compounds on Impact Areas

DTIC Science & Technology

2007-08-01

GPS) antennas. A fluxgate magnetometer is mounted in the forward assembly to compensate for the magnetic signature of the aircraft. A laser...recorded digitally on the ORAGS™ console (Figure 5) inside the helicopter in a binary format. The magnetometers are sampled at a 1200-Hz sample rate and...GPS. Accurate positioning requires a correction for this lag. Time lags among the magnetometers , fluxgate , and GPS signals were measured by a

Hamiltonian model and dynamic analyses for a hydro-turbine governing system with fractional item and time-lag

NASA Astrophysics Data System (ADS)

Xu, Beibei; Chen, Diyi; Zhang, Hao; Wang, Feifei; Zhang, Xinguang; Wu, Yonghong

2017-06-01

This paper focus on a Hamiltonian mathematical modeling for a hydro-turbine governing system including fractional item and time-lag. With regards to hydraulic pressure servo system, a universal dynamical model is proposed, taking into account the viscoelastic properties and low-temperature impact toughness of constitutive materials as well as the occurrence of time-lag in the signal transmissions. The Hamiltonian model of the hydro-turbine governing system is presented using the method of orthogonal decomposition. Furthermore, a novel Hamiltonian function that provides more detailed energy information is presented, since the choice of the Hamiltonian function is the key issue by putting the whole dynamical system to the theory framework of the generalized Hamiltonian system. From the numerical experiments based on a real large hydropower station, we prove that the Hamiltonian function can describe the energy variation of the hydro-turbine suitably during operation. Moreover, the effect of the fractional α and the time-lag τ on the dynamic variables of the hydro-turbine governing system are explored and their change laws identified, respectively. The physical meaning between fractional calculus and time-lag are also discussed in nature. All of the above theories and numerical results are expected to provide a robust background for the safe operation and control of large hydropower stations.

Improving precipitation forecast with hybrid 3DVar and time-lagged ensembles in a heavy rainfall event

NASA Astrophysics Data System (ADS)

Wang, Yuanbing; Min, Jinzhong; Chen, Yaodeng; Huang, Xiang-Yu; Zeng, Mingjian; Li, Xin

2017-01-01

This study evaluates the performance of three-dimensional variational (3DVar) and a hybrid data assimilation system using time-lagged ensembles in a heavy rainfall event. The time-lagged ensembles are constructed by sampling from a moving time window of 3 h along a model trajectory, which is economical and easy to implement. The proposed hybrid data assimilation system introduces flow-dependent error covariance derived from time-lagged ensemble into variational cost function without significantly increasing computational cost. Single observation tests are performed to document characteristic of the hybrid system. The sensitivity of precipitation forecasts to ensemble covariance weight and localization scale is investigated. Additionally, the TLEn-Var is evaluated and compared to the ETKF(ensemble transformed Kalman filter)-based hybrid assimilation within a continuously cycling framework, through which new hybrid analyses are produced every 3 h over 10 days. The 24 h accumulated precipitation, moisture, wind are analyzed between 3DVar and the hybrid assimilation using time-lagged ensembles. Results show that model states and precipitation forecast skill are improved by the hybrid assimilation using time-lagged ensembles compared with 3DVar. Simulation of the precipitable water and structure of the wind are also improved. Cyclonic wind increments are generated near the rainfall center, leading to an improved precipitation forecast. This study indicates that the hybrid data assimilation using time-lagged ensembles seems like a viable alternative or supplement in the complex models for some weather service agencies that have limited computing resources to conduct large size of ensembles.

Population pharmacokinetics of rifampin in the treatment of Mycobacterium tuberculosis in Asian elephants.

PubMed

Egelund, E F; Isaza, R; Brock, A P; Alsultan, A; An, G; Peloquin, C A

2015-04-01

The objective of this study was to develop a population pharmacokinetic model for rifampin in elephants. Rifampin concentration data from three sources were pooled to provide a total of 233 oral concentrations from 37 Asian elephants. The population pharmacokinetic models were created using Monolix (version 4.2). Simulations were conducted using ModelRisk. We examined the influence of age, food, sex, and weight as model covariates. We further optimized the dosing of rifampin based upon simulations using the population pharmacokinetic model. Rifampin pharmacokinetics were best described by a one-compartment open model including first-order absorption with a lag time and first-order elimination. Body weight was a significant covariate for volume of distribution, and food intake was a significant covariate for lag time. The median Cmax of 6.07 μg/mL was below the target range of 8-24 μg/mL. Monte Carlo simulations predicted the highest treatable MIC of 0.25 μg/mL with the current initial dosing recommendation of 10 mg/kg, based upon a previously published target AUC0-24/MIC > 271 (fAUC > 41). Simulations from the population model indicate that the current dose of 10 mg/kg may be adequate for MICs up to 0.25 μg/mL. While the targeted AUC/MIC may be adequate for most MICs, the median Cmax for all elephants is below the human and elephant targeted ranges. © 2014 John Wiley & Sons Ltd.

Assessing the impact of humidex on HFMD in Guangdong Province and its variability across social-economic status and age groups

NASA Astrophysics Data System (ADS)

Zhang, Wangjian; Du, Zhicheng; Zhang, Dingmei; Yu, Shicheng; Huang, Yong; Hao, Yuantao

2016-01-01

Humidex is a meteorological index that combines the impacts of temperature and humidity, and is directly comparable with dry temperature in degrees Celsius. However, to date, no research has focused on the effect of humidex on hand, foot and mouth disease (HFMD). The current study was designed to address this research need. Case-based HFMD surveillance data and daily meteorological data collected between 2010 and 2012 was obtained from the China CDC and the National Meteorological Information Center, respectively. Distributed lag nonlinear models were applied to assess the impact of humidex on HFMD among children under 15 years oldin Guangdong, and its variability across social-economic status and age groups. We found that relative risk (RR) largely increased with humidex. Lag-specific and cumulative humidex-RR curves for children from the Pearl-River Delta Region as well as older children were more likely to show two-peak distribution patterns. One RR peak occurred at a humidex of between 15 and 20, and the other occurred between 30 and 35. This study provides a comprehensive picture of the impact of humidex on HFMD incidence in Guangdong Province. Results from the present study should be important in the development of area-and-age-targeted control programs.

[Acute effect of daily mean temperature on ischemic heart disease mortality: a multivariable meta-analysis from 12 counties across Hubei Province, China].

PubMed

Zhang, Y Q; Yu, C H; Bao, J Z

2016-11-06

Objective: To evaluate the acute effects of daily mean temperature on ischemic heart disease (IHD) mortality in 12 counties across Hubei Province, China. Methods: We obtained the daily IHD mortality data and meteorological data of the 12 counties for 2009-2012. The distributed lag nonlinear model (DLNM) was used to estimate the community-specific association between mean temperature and IHD mortality. A multivariate meta-analysis was then applied to pool the community-specific relationship between temperature and IHD mortality, and the effects of cold and heat on mortality risk. Results: In 2009-2012, of the 6 702 012 people included in this study, 19 688 died of IHD. A daily average of 1.2 IHD deaths occurred in each community. The annual average mean temperature was 16.6 ℃ during the study period. A nonlinear temperature-IHD mortality relationship was observed for different cumulative lag days at the provincial level. The pooled heat effect was acute but attenuated within 2 days. In contrast, the cold effect was delayed and persisted for more than 2 weeks. Compared with a reference temperature (25 th percentile of mean temperature during the study period, P 25 ), the cold effect for P 10 of mean temperature was associated with IHD mortality, the RR (95% CI ) was 1.084 (1.008-1.167) at lag 0-14, and 1.149 (1.053-1.253) at lag 0-21. For the P 1 cold temperature, the mortality RR (95% CI ) values were 1.116 (0.975-1.276) and 1.220 (1.04-1.428), respectively. We found no significant association between high temperatures and IHD mortality in the present study at different lag days. Conclusion: In Hubei Province, low temperature was associated with increased IHD mortality risk, and cold effects lasted for several days; no significant effect of high temperature was observed.

Comparison of short-term associations with meteorological variables between COPD and pneumonia hospitalization among the elderly in Hong Kong-a time-series study.

PubMed

Lam, Holly Ching-Yu; Chan, Emily Ying-Yang; Goggins, William Bernard

2018-05-05

Pneumonia and chronic obstructive pulmonary diseases (COPD) are the commonest causes of respiratory hospitalization among older adults. Both diseases have been reported to be associated with ambient temperature, but the associations have not been compared between the diseases. Their associations with other meteorological variables have also not been well studied. This study aimed to evaluate the associations between meteorological variables, pneumonia, and COPD hospitalization among adults over 60 and to compare these associations between the diseases. Daily cause-specific hospitalization counts in Hong Kong during 2004-2011 were regressed on daily meteorological variables using distributed lag nonlinear models. Associations were compared between diseases by ratio of relative risks. Analyses were stratified by season and age group (60-74 vs. ≥ 75). In hot season, high temperature (> 28 °C) and high relative humidity (> 82%) were statistically significantly associated with more pneumonia in lagged 0-2 and lagged 0-10 days, respectively. Pneumonia hospitalizations among the elderly (≥ 75) also increased with high solar radiation and high wind speed. During the cold season, consistent hockey-stick associations with temperature and relative humidity were found for both admissions and both age groups. The minimum morbidity temperature and relative humidity were at about 21-22 °C and 82%. The lagged effects of low temperature were comparable for both diseases (lagged 0-20 days). The low-temperature-admissions associations with COPD were stronger and were strongest among the elderly. This study found elevated pneumonia and COPD admissions risks among adults ≥ 60 during periods of extreme weather conditions, and the associations varied by season and age group. Vulnerable groups should be advised to avoid exposures, such as staying indoor and maintaining satisfactory indoor conditions, to minimize risks.

Association between temperature and emergency room visits for cardiorespiratory diseases, metabolic syndrome-related diseases, and accidents in metropolitan Taipei.

PubMed

Wang, Yu-Chun; Lin, Yu-Kai

2014-01-01

This study evaluated risks of the emergency room visits (ERV) for cerebrovascular diseases, heart diseases, ischemic heart disease, hypertensive diseases, chronic renal failure (CRF), diabetes mellitus (DM), asthma, chronic airway obstruction not elsewhere classified (CAO), and accidents associated with the ambient temperature from 2000 to 2009 in metropolitan Taipei. The distributed lag non-linear model was used to estimate the cumulative relative risk (RR) and confidence interval (CI) of cause-specific ERV associated with daily temperature from lag 0 to lag 3 after controlling for potential confounders. This study identified that temperatures related to the lowest risk of ERV was 26 °C for cerebrovascular diseases, 18 °C for CRF, DM, and accidents, and 30 °C for hypertensive diseases, asthma, and CAO. These temperatures were used as the reference temperatures to measure RR for the corresponding diseases. A low temperature (14°C) increased the ERV risk for cerebrovascular diseases, hypertensive diseases, and asthma, with respective cumulative 4-day RRs of 1.56 (95% CI: 1.23, 1.97), 1.78 (95% CI: 1.37, 2.34), and 2.93 (95% CI: 1.26, 6.79). The effects were greater on, or after, lag one. At 32°C, the cumulative 4-day RR for ERV was significant for CRF (RR = 2.36; 95% CI: 1.33, 4.19) and accidents (RR = 1.23; 95% CI: 1.14, 1.33) and the highest RR was seen on lag 0 for CRF (RR = 1.69; 95% CI: 1.01, 3.58), DM (RR = 1.69; 95% CI: 1.09, 2.61), and accidents (RR = 1.19; 95% CI: 1.11, 1.27). Higher temperatures are associated with the increased ERV risks for CRF, DM, and accidents and lower temperatures with the increased ERV risks for cerebrovascular diseases, hypertensive diseases, and asthma in the subtropical metropolitan.

Association between Temperature and Emergency Room Visits for Cardiorespiratory Diseases, Metabolic Syndrome-Related Diseases, and Accidents in Metropolitan Taipei

PubMed Central

Wang, Yu-Chun; Lin, Yu-Kai

2014-01-01

Objective This study evaluated risks of the emergency room visits (ERV) for cerebrovascular diseases, heart diseases, ischemic heart disease, hypertensive diseases, chronic renal failure (CRF), diabetes mellitus (DM), asthma, chronic airway obstruction not elsewhere classified (CAO), and accidents associated with the ambient temperature from 2000 to 2009 in metropolitan Taipei. Methods The distributed lag non-linear model was used to estimate the cumulative relative risk (RR) and confidence interval (CI) of cause-specific ERV associated with daily temperature from lag 0 to lag 3 after controlling for potential confounders. Results This study identified that temperatures related to the lowest risk of ERV was 26 °C for cerebrovascular diseases, 18 °C for CRF, DM, and accidents, and 30 °C for hypertensive diseases, asthma, and CAO. These temperatures were used as the reference temperatures to measure RR for the corresponding diseases. A low temperature (14°C) increased the ERV risk for cerebrovascular diseases, hypertensive diseases, and asthma, with respective cumulative 4-day RRs of 1.56 (95% CI: 1.23, 1.97), 1.78 (95% CI: 1.37, 2.34), and 2.93 (95% CI: 1.26, 6.79). The effects were greater on, or after, lag one. At 32°C, the cumulative 4-day RR for ERV was significant for CRF (RR = 2.36; 95% CI: 1.33, 4.19) and accidents (RR = 1.23; 95% CI: 1.14, 1.33) and the highest RR was seen on lag 0 for CRF (RR = 1.69; 95% CI: 1.01, 3.58), DM (RR = 1.69; 95% CI: 1.09, 2.61), and accidents (RR = 1.19; 95% CI: 1.11, 1.27). Conclusions Higher temperatures are associated with the increased ERV risks for CRF, DM, and accidents and lower temperatures with the increased ERV risks for cerebrovascular diseases, hypertensive diseases, and asthma in the subtropical metropolitan. PMID:24932702

Accelerating recovery from jet lag: prediction from a multi-oscillator model and its experimental confirmation in model animals

NASA Astrophysics Data System (ADS)

Kori, Hiroshi; Yamaguchi, Yoshiaki; Okamura, Hitoshi

2017-04-01

The endogenous circadian clock drives oscillations that are completely synchronized with the environmental day-night rhythms with a period of approximately 24 hours. Temporal misalignment between one’s internal circadian clock and the external solar time often occurs in shift workers and long-distance travelers; such misalignments are accompanied by sleep disturbances and gastrointestinal distress. Repeated exposure to jet lag and rotating shift work increases the risk of lifestyle-related diseases, such as cardiovascular complaints and metabolic insufficiencies. However, the mechanism behind the disruption of one’s internal clock is not well understood. In this paper, we therefore present a new theoretical concept called “jet lag separatrix” to understand circadian clock disruption and slow recovery from jet lag based on the mathematical model describing the hierarchical structure of the circadian clock. To demonstrate the utility of our theoretical study, we applied it to predict that re-entrainment via a two-step jet lag in which a four-hour shift of the light-dark cycle is given in the span of two successive days requires fewer days than when given as a single eight-hour shift. We experimentally verified the feasibility of our theory in C57BL/6 strain mice, with results indicating that this pre-exposure of jet lag is indeed beneficial.

Multiscale statistics of trajectories with applications to fluid particles in turbulence and football players

NASA Astrophysics Data System (ADS)

Schneider, Kai; Kadoch, Benjamin; Bos, Wouter

2017-11-01

The angle between two subsequent particle displacement increments is evaluated as a function of the time lag. The directional change of particles can thus be quantified at different scales and multiscale statistics can be performed. Flow dependent and geometry dependent features can be distinguished. The mean angle satisfies scaling behaviors for short time lags based on the smoothness of the trajectories. For intermediate time lags a power law behavior can be observed for some turbulent flows, which can be related to Kolmogorov scaling. The long time behavior depends on the confinement geometry of the flow. We show that the shape of the probability distribution function of the directional change can be well described by a Fischer distribution. Results for two-dimensional (direct and inverse cascade) and three-dimensional turbulence with and without confinement, illustrate the properties of the proposed multiscale statistics. The presented Monte-Carlo simulations allow disentangling geometry dependent and flow independent features. Finally, we also analyze trajectories of football players, which are, in general, not randomly spaced on a field.

Suicide and meteorological factors in São Paulo, Brazil, 1996-2011: a time series analysis.

PubMed

Bando, Daniel H; Teng, Chei T; Volpe, Fernando M; Masi, Eduardo de; Pereira, Luiz A; Braga, Alfésio L

2017-01-01

Considering the scarcity of reports from intertropical latitudes and the Southern Hemisphere, we aimed to examine the association between meteorological factors and suicide in São Paulo. Weekly suicide records stratified by sex were gathered. Weekly averages for minimum, mean, and maximum temperature (°C), insolation (hours), irradiation (MJ/m2), relative humidity (%), atmospheric pressure (mmHg), and rainfall (mm) were computed. The time structures of explanatory variables were modeled by polynomial distributed lag applied to the generalized additive model. The model controlled for long-term trends and selected meteorological factors. The total number of suicides was 6,600 (5,073 for men), an average of 6.7 suicides per week (8.7 for men and 2.0 for women). For overall suicides and among men, effects were predominantly acute and statistically significant only at lag 0. Weekly average minimum temperature had the greatest effect on suicide; there was a 2.28% increase (95%CI 0.90-3.69) in total suicides and a 2.37% increase (95%CI 0.82-3.96) among male suicides with each 1 °C increase. This study suggests that an increase in weekly average minimum temperature has a short-term effect on suicide in São Paulo.

Memory of the Lake Rotorua catchment - time lag of the water in the catchment and delayed arrival of contaminants from past land use activities

NASA Astrophysics Data System (ADS)

Morgenstern, Uwe; Daughney, Christopher J.; Stewart, Michael K.; McDonnell, Jeffrey J.

2013-04-01

The transit time distribution of streamflow is a fundamental descriptor of the flowpaths of water through a catchment and the storage of water within it, controlling its response to landuse change, pollution, ecological degradation, and climate change. Significant time lags (catchment memory) in the responses of streams to these stressors and their amelioration or restoration have been observed. Lag time can be quantified via water transit time of the catchment discharge. Mean transit times can be in the order of years and decades (Stewart et al 2012, Morgenstern et al., 2010). If the water passes through large groundwater reservoirs, it is difficult to quantify and predict the lag time. A pulse shaped tracer that moves with the water can allow quantification of the mean transit time. Environmental tritium is the ideal tracer of the water cycle. Tritium is part of the water molecule, is not affected by chemical reactions in the aquifer, and the bomb tritium from the atmospheric nuclear weapons testing represents a pulse shaped tracer input that allows for very accurate measurement of the age distribution parameters of the water in the catchment discharge. Tritium time series data from all catchment discharges (streams and springs) into Lake Rotorua, New Zealand, allow for accurate determination of the age distribution parameters. The Lake Rotorua catchment tritium data from streams and springs are unique, with high-quality tritium data available over more than four decades, encompassing the time when the bomb-tritium moved through the groundwater system, and from a very high number of streams and springs. Together with the well-defined tritium input into the Rotorua catchment, this data set allows for the best understanding of the water dynamics through a large scale catchment, including validation of complicated water mixing models. Mean transit times of the main streams into the lake range between 27 and 170 years. With such old water discharging into the lake, most of the water inflows into the lake are not yet fully representing the nitrate loading in their sub-catchments from current land use practises. These water inflows are still 'diluted' by pristine old water, but over time, the full amount of nitrate load will arrive at the lake. With the age distribution parameters, it is possible to predict the increase in nitrate load to the lake via the groundwater discharges. All sub-catchments have different mean transit times. The mean transit times are not necessarily correlated with observable hydrogeologic properties like hydraulic conductivity and catchment size. Without such age tracer data, it is therefore difficult to predict mean transit times (lag times, memory) of water transfer through catchments. References: Stewart, M.K., Morgenstern, U., McDonnell, J.J., Pfister, L. (2012). The 'hidden streamflow' challenge in catchment hydrology: A call to action for streamwater transit time analysis. Hydrol. Process. 26,2061-2066, Invited commentary. DOI: 10.1002/hyp.9262 Morgenstern, U., Stewart, M.K., and Stenger, R. (2010) Dating of streamwater using tritium in a post nuclear bomb pulse world: continuous variation of mean transit time with streamflow, Hydrol. Earth Syst. Sci, 14, 2289-2301

Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions.

PubMed

Teklehaimanot, Hailay D; Schwartz, Joel; Teklehaimanot, Awash; Lipsitch, Marc

2004-11-19

Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt transmission earlier in the epidemic, perhaps at the expense of some level of accuracy. Expected case numbers were modeled using a Poisson regression with lagged weather factors in a 4th-degree polynomial distributed lag model. For each week, the numbers of malaria cases were predicted using coefficients obtained using all years except that for which the prediction was being made. The effectiveness of alerts generated by the prediction system was compared against that of alerts based on observed cases. The usefulness of the prediction system was evaluated in cold and hot districts. The system predicts the overall pattern of cases well, yet underestimates the height of the largest peaks. Relative to alerts triggered by observed cases, the alerts triggered by the predicted number of cases performed slightly worse, within 5% of the detection system. The prediction-based alerts were able to prevent 10-25% more cases at a given sensitivity in cold districts than in hot ones. The prediction of malaria cases using lagged weather performed well in identifying periods of increased malaria cases. Weather-derived predictions identified epidemics with reasonable accuracy and better timeliness than early detection systems; therefore, the prediction of malarial epidemics using weather is a plausible alternative to early detection systems.

Effects of temperature variation between neighbouring days on daily hospital visits for childhood asthma: a time-series analysis.

PubMed

Li, K; Ni, H; Yang, Z; Wang, Y; Ding, S; Wen, L; Yang, H; Cheng, J; Su, H

2016-07-01

To identify the relationship between temperature variation between neighbouring days (TVN) and hospital visits for childhood asthma in age- and sex-specific groups. An ecological design was used to explore the effect of TVN on hospital visits for childhood asthma. A Poisson generalised linear regression model combined with a distributed lag non-linear model was used to analyse the association between TVN and hospital visits for childhood asthma. All hospital visits for childhood asthma from June 2010 to July 2013 were included (n = 17,022). Daily climate data were obtained from Hefei Meteorological Bureau. A significant correlation was found between TVN and hospital visits for childhood asthma in age- and sex-specific groups. For different gender groups, the effect of TVN on childhood asthma was the greatest at 3 and 5 days lag for males and females. For different age groups, the effect of TVN on childhood asthma was the greatest at 1 and 5 days lag for 0-4 years and 5-14 years children, respectively. A 1 °C increase in TVN was associated with a 4.2% (95% confidence interval 0.9-7.6%) increase in hospital visits for childhood asthma. TVN is associated with hospital visits for childhood asthma. Once the temperature change rapidly, guardians will be urged to pay more attention to their children's health, which may reduce the morbidity of childhood asthma. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Global exponential stability and lag synchronization for delayed memristive fuzzy Cohen-Grossberg BAM neural networks with impulses.

PubMed

Yang, Wengui; Yu, Wenwu; Cao, Jinde; Alsaadi, Fuad E; Hayat, Tasawar

2018-02-01

This paper investigates the stability and lag synchronization for memristor-based fuzzy Cohen-Grossberg bidirectional associative memory (BAM) neural networks with mixed delays (asynchronous time delays and continuously distributed delays) and impulses. By applying the inequality analysis technique, homeomorphism theory and some suitable Lyapunov-Krasovskii functionals, some new sufficient conditions for the uniqueness and global exponential stability of equilibrium point are established. Furthermore, we obtain several sufficient criteria concerning globally exponential lag synchronization for the proposed system based on the framework of Filippov solution, differential inclusion theory and control theory. In addition, some examples with numerical simulations are given to illustrate the feasibility and validity of obtained results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Lagged PM2.5 effects in mortality time series: Critical impact of covariate model

EPA Science Inventory

The two most common approaches to modeling the effects of air pollution on mortality are the Harvard and the Johns Hopkins (NMMAPS) approaches. These two approaches, which use different sets of covariates, result in dissimilar estimates of the effect of lagged fine particulate ma...

An Evaluation of a Phase-Lag Boundary Condition for Francis Hydroturbine Simulations Using a Pressure-Based Solver

NASA Astrophysics Data System (ADS)

Wouden, Alex; Cimbala, John; Lewis, Bryan

2014-11-01

While the periodic boundary condition is useful for handling rotational symmetry in many axisymmetric geometries, its application fails for analysis of rotor-stator interaction (RSI) in multi-stage turbomachinery flow. The inadequacy arises from the underlying geometry where the blade counts per row differ, since the blade counts are crafted to deter the destructive harmonic forces of synchronous blade passing. Therefore, to achieve the computational advantage of modeling a single blade passage per row while preserving the integrity of the RSI, a phase-lag boundary condition is adapted to OpenFOAM® software's incompressible pressure-based solver. The phase-lag construct is accomplished through restating the implicit periodic boundary condition as a constant boundary condition that is updated at each time step with phase-shifted data from the coupled cells adjacent to the boundary. Its effectiveness is demonstrated using a typical Francis hydroturbine modeled as single- and double-passages with phase-lag boundary conditions. The evaluation of the phase-lag condition is based on the correspondence of the overall computational performance and the calculated flow parameters of the phase-lag simulations with those of a baseline full-wheel simulation. Funded in part by DOE Award Number: DE-EE0002667.

Reverberation Mapping of the Continuum Source in Active Galactic Nuclei

NASA Astrophysics Data System (ADS)

Fausnaugh, Michael Martin

I present results from a monitoring campaign of 11 active galactic nuclei (AGN) conducted in Spring of 2014. I use the reverberation mapping method to probe the interior structures of the AGN, specifically the broad line regions (BLRs) and accretion disks. One of these AGN, NGC 5548, was also subject to multi-wavelength (X-ray, UV, optical, and near-IR) monitoring using 25 ground-based telescopes and four space-based facilities. For NGC 5548, I detect lags between the continuum emission at different wavelengths that follow a trend consistent with the prediction for continuum reprocessing by an accretion disk with temperature profile T ∝ R -3/4. However, the lags imply a disk radius that is 3 times larger than the prediction from standard thin-disk models. The lags at wavelengths longer than the Vband are also equal to or greater than the lags of high-ionization-state emission lines (such as HeII lambda1640 and lambda4686), suggesting that the continuum-emitting source is of a physical size comparable to the inner broad-line region. Using optical spectra from the Large Binocular Telescope, I estimate the bias of the interband continuum lags due to BLR emission observed in the filters, and I find that the bias for filters with high levels of BLR contamination (˜20%) can be important for the shortest continuum lags. This likely has a significant impact on the u and U bands owing to Balmer continuum emission. I then develop a new procedure for the internal (night-to-night) calibration of time series spectra that can reach precisions of ˜1 millimagnitude and improves traditional techniques by up to a factor of 5. At this level, other systematic issues (e.g., the nightly sensitivity functions and Fe II contamination) limit the final precision of the observed light curves. Using the new calibration method, I next present the data and first results from the optical spectroscopic monitoring component of the reverberation mapping campaign. Five AGN were sufficiently variable to measure continuum-Hbeta lags and super-massive black hole masses: MCG+08-11-011, NGC 2617, NGC 4051, 3C 382, and Mrk 374. I also obtain Hgamma and HeII lags for all objects except 3C 382. The HeII lags indicate radial stratification of the BLR, and the masses derived from different emission lines are in general agreement. The relative responsivities of these lines to continuum variations are also in qualitative agreement with photoionization models. Finally, I measure optical continuum lags for the two most variable targets, MCG+08-11-011 and NGC 2617. I again find lags consistent with geometrically thin accretion-disk models that have temperature profiles T ∝ R-3/4. The observed lags are larger than predictions based on standard thin-disk theory by factors of 3.3 for MCG+08-11-011 and 2.3 for NGC 2617. Using a physical model, these differences can be explained if the mass accretion rates are larger than inferred from the optical continuum luminosity by a factor of 4.3 in MCG+08-11-011 and a factor of 1.3 in NGC 2617. While the X-ray variability in NGC 2617 precedes the UV/optical variability, the long 2.6 day lag is problematic for coronal reprocessing models.

When Long-Range Zero-Lag Synchronization is Feasible in Cortical Networks

PubMed Central

Viriyopase, Atthaphon; Bojak, Ingo; Zeitler, Magteld; Gielen, Stan

2012-01-01

Many studies have reported long-range synchronization of neuronal activity between brain areas, in particular in the beta and gamma bands with frequencies in the range of 14–30 and 40–80 Hz, respectively. Several studies have reported synchrony with zero phase lag, which is remarkable considering the synaptic and conduction delays inherent in the connections between distant brain areas. This result has led to many speculations about the possible functional role of zero-lag synchrony, such as for neuronal communication, attention, memory, and feature binding. However, recent studies using recordings of single-unit activity and local field potentials report that neuronal synchronization may occur with non-zero phase lags. This raises the questions whether zero-lag synchrony can occur in the brain and, if so, under which conditions. We used analytical methods and computer simulations to investigate which connectivity between neuronal populations allows or prohibits zero-lag synchrony. We did so for a model where two oscillators interact via a relay oscillator. Analytical results and computer simulations were obtained for both type I Mirollo–Strogatz neurons and type II Hodgkin–Huxley neurons. We have investigated the dynamics of the model for various types of synaptic coupling and importantly considered the potential impact of Spike-Timing Dependent Plasticity (STDP) and its learning window. We confirm previous results that zero-lag synchrony can be achieved in this configuration. This is much easier to achieve with Hodgkin–Huxley neurons, which have a biphasic phase response curve, than for type I neurons. STDP facilitates zero-lag synchrony as it adjusts the synaptic strengths such that zero-lag synchrony is feasible for a much larger range of parameters than without STDP. PMID:22866034

How to induce multiple delays in coupled chaotic oscillators?

NASA Astrophysics Data System (ADS)

Bhowmick, Sourav K.; Ghosh, Dibakar; Roy, Prodyot K.; Kurths, Jürgen; Dana, Syamal K.

2013-12-01

Lag synchronization is a basic phenomenon in mismatched coupled systems, delay coupled systems, and time-delayed systems. It is characterized by a lag configuration that identifies a unique time shift between all pairs of similar state variables of the coupled systems. In this report, an attempt is made how to induce multiple lag configurations in coupled systems when different pairs of state variables attain different time shift. A design of coupling is presented to realize this multiple lag synchronization. Numerical illustration is given using examples of the Rössler system and the slow-fast Hindmarsh-Rose neuron model. The multiple lag scenario is physically realized in an electronic circuit of two Sprott systems.

Homozygous diploid deletion strains of Saccharomyces cerevisiae that determine lag phase and dehydration tolerance.

PubMed

D'Elia, Riccardo; Allen, Patricia L; Johanson, Kelly; Nickerson, Cheryl A; Hammond, Timothy G

2005-06-01

This study identifies genes that determine length of lag phase, using the model eukaryotic organism, Saccharomyces cerevisiae. We report growth of a yeast deletion series following variations in the lag phase induced by variable storage times after drying-down yeast on filters. Using a homozygous diploid deletion pool, lag times ranging from 0 h to 90 h were associated with increased drop-out of mitochondrial genes and increased survival of nuclear genes. Simple linear regression (R2 analysis) shows that there are over 500 genes for which > 70% of the variation can be explained by lag alone. In the genes with a positive correlation, such that the gene abundance increases with lag and hence the deletion strain is suitable for survival during prolonged storage, there is a strong predominance of nucleonic genes. In the genes with a negative correlation, such that the gene abundance decreases with lag and hence the strain may be critical for getting yeast out of the lag phase, there is a strong predominance of glycoproteins and transmembrane proteins. This study identifies yeast deletion strains with survival advantage on prolonged storage and amplifies our understanding of the genes critical for getting out of the lag phase.

Homozygous diploid deletion strains of Saccharomyces cerevisiae that determine lag phase and dehydration tolerance

NASA Technical Reports Server (NTRS)

D'Elia, Riccardo; Allen, Patricia L.; Johanson, Kelly; Nickerson, Cheryl A.; Hammond, Timothy G.

2005-01-01

This study identifies genes that determine length of lag phase, using the model eukaryotic organism, Saccharomyces cerevisiae. We report growth of a yeast deletion series following variations in the lag phase induced by variable storage times after drying-down yeast on filters. Using a homozygous diploid deletion pool, lag times ranging from 0 h to 90 h were associated with increased drop-out of mitochondrial genes and increased survival of nuclear genes. Simple linear regression (R2 analysis) shows that there are over 500 genes for which > 70% of the variation can be explained by lag alone. In the genes with a positive correlation, such that the gene abundance increases with lag and hence the deletion strain is suitable for survival during prolonged storage, there is a strong predominance of nucleonic genes. In the genes with a negative correlation, such that the gene abundance decreases with lag and hence the strain may be critical for getting yeast out of the lag phase, there is a strong predominance of glycoproteins and transmembrane proteins. This study identifies yeast deletion strains with survival advantage on prolonged storage and amplifies our understanding of the genes critical for getting out of the lag phase.

Analysis of Quasi-periodic Oscillations and Time Lag in Ultraluminous X-Ray Sources with XMM-Newton

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Zi-Jian; Xiao, Guang-Cheng; Zhang, Shu

We investigated the power density spectrum (PDS) and time lag of ultraluminous X-ray sources (ULXs) observed by XMM-Newton . We determined the PDSs for each ULX and found that five of them show intrinsic variability due to obvious quasi-periodic oscillations (QPOs) of mHz–1 Hz, consistent with previous reports. We further investigated these five ULXs to determine their possible time lag. The ULX QPOs exhibit a soft time lag that is linearly related to the QPO frequency. We discuss the likelihood of the ULX QPOs being type-C QPO analogs, and the time lag models. The ULXs might harbor intermediate-mass black holesmore » if their QPOs are type-C QPO analogs. We suggest that the soft lag and the linearity may be due to reverberation.« less

Modeling eye gaze patterns in clinician-patient interaction with lag sequential analysis.

PubMed

Montague, Enid; Xu, Jie; Chen, Ping-Yu; Asan, Onur; Barrett, Bruce P; Chewning, Betty

2011-10-01

The aim of this study was to examine whether lag sequential analysis could be used to describe eye gaze orientation between clinicians and patients in the medical encounter. This topic is particularly important as new technologies are implemented into multiuser health care settings in which trust is critical and nonverbal cues are integral to achieving trust. This analysis method could lead to design guidelines for technologies and more effective assessments of interventions. Nonverbal communication patterns are important aspects of clinician-patient interactions and may affect patient outcomes. The eye gaze behaviors of clinicians and patients in 110 videotaped medical encounters were analyzed using the lag sequential method to identify significant behavior sequences. Lag sequential analysis included both event-based lag and time-based lag. Results from event-based lag analysis showed that the patient's gaze followed that of the clinician, whereas the clinician's gaze did not follow the patient's. Time-based sequential analysis showed that responses from the patient usually occurred within 2 s after the initial behavior of the clinician. Our data suggest that the clinician's gaze significantly affects the medical encounter but that the converse is not true. Findings from this research have implications for the design of clinical work systems and modeling interactions. Similar research methods could be used to identify different behavior patterns in clinical settings (physical layout, technology, etc.) to facilitate and evaluate clinical work system designs.

Modeling Eye Gaze Patterns in Clinician-Patient Interaction with Lag Sequential Analysis

PubMed Central

Montague, E; Xu, J; Asan, O; Chen, P; Chewning, B; Barrett, B

2011-01-01

Objective The aim of this study was to examine whether lag-sequential analysis could be used to describe eye gaze orientation between clinicians and patients in the medical encounter. This topic is particularly important as new technologies are implemented into multi-user health care settings where trust is critical and nonverbal cues are integral to achieving trust. This analysis method could lead to design guidelines for technologies and more effective assessments of interventions. Background Nonverbal communication patterns are important aspects of clinician-patient interactions and may impact patient outcomes. Method Eye gaze behaviors of clinicians and patients in 110-videotaped medical encounters were analyzed using the lag-sequential method to identify significant behavior sequences. Lag-sequential analysis included both event-based lag and time-based lag. Results Results from event-based lag analysis showed that the patients’ gaze followed that of clinicians, while clinicians did not follow patients. Time-based sequential analysis showed that responses from the patient usually occurred within two seconds after the initial behavior of the clinician. Conclusion Our data suggest that the clinician’s gaze significantly affects the medical encounter but not the converse. Application Findings from this research have implications for the design of clinical work systems and modeling interactions. Similar research methods could be used to identify different behavior patterns in clinical settings (physical layout, technology, etc.) to facilitate and evaluate clinical work system designs. PMID:22046723

Extended causal modeling to assess Partial Directed Coherence in multiple time series with significant instantaneous interactions.

PubMed

Faes, Luca; Nollo, Giandomenico

2010-11-01

The Partial Directed Coherence (PDC) and its generalized formulation (gPDC) are popular tools for investigating, in the frequency domain, the concept of Granger causality among multivariate (MV) time series. PDC and gPDC are formalized in terms of the coefficients of an MV autoregressive (MVAR) model which describes only the lagged effects among the time series and forsakes instantaneous effects. However, instantaneous effects are known to affect linear parametric modeling, and are likely to occur in experimental time series. In this study, we investigate the impact on the assessment of frequency domain causality of excluding instantaneous effects from the model underlying PDC evaluation. Moreover, we propose the utilization of an extended MVAR model including both instantaneous and lagged effects. This model is used to assess PDC either in accordance with the definition of Granger causality when considering only lagged effects (iPDC), or with an extended form of causality, when we consider both instantaneous and lagged effects (ePDC). The approach is first evaluated on three theoretical examples of MVAR processes, which show that the presence of instantaneous correlations may produce misleading profiles of PDC and gPDC, while ePDC and iPDC derived from the extended model provide here a correct interpretation of extended and lagged causality. It is then applied to representative examples of cardiorespiratory and EEG MV time series. They suggest that ePDC and iPDC are better interpretable than PDC and gPDC in terms of the known cardiovascular and neural physiologies.

Population pharmacokinetics of oxycodone in patients with cancer-related pain.

PubMed

Komatsu, Toshiaki; Kokubun, Hideya; Suzuki, Ai; Takayanagi, Risa; Yamada, Yasuhiko; Matoba, Motohiro; Yago, Kazuo

2012-09-01

Oxycodone is an opioid widely prescribed to cancer patients for pain relief. However, the pharmacokinetics of oxycodone has not been sufficiently examined. Therefore the aim of this work was to study population pharmacokinetics of oxycodone in patients with cancer pain. The authors analyzed 108 serum oxycodone samples of 33 individuals with nonlinear mixed-effects model (NONMEM). Population pharmacokinetics was calculated using the one-compartment model of clearance, volume of distribution, bioavailability, absorption constant rate, and lag time. An exponential error model was used to determine interindividual variability and a relative error model was applied to assess residual variability. Population pharmacokinetics of oxycodone at the end point were as follows: CL(L/h) = 10.7 × [1 + (2 - Child-Pugh Classification)] (Class: A = 0, B = 1, C = 2); V(d) (L) = 193; k(a) (h(-1)) = 0.336; T(lag) (h) = 0.859; F (%) = 63.9. Interindividual variability was CL: 30.5%, V(d): 44.6%, and F: 37.0%, and residual variability was 16.2%. As the total clearance in patients with liver dysfunction (Child-Pugh class B) was reduced to 33.3%, serum concentration of oxycodone increased by 1.5. Therefore, it became clear that dose adjustments are essential when treating patients with liver dysfunction. These findings suggest that population parameters are useful for evaluating pharmacokinetics of oxycodone in patients with cancer pain.

A way around the Nyquist lag

NASA Astrophysics Data System (ADS)

Penland, C.

2017-12-01

One way to test for the linearity of a multivariate system is to perform Linear Inverse Modeling (LIM) to a multivariate time series. LIM yields an estimated operator by combining a lagged covariance matrix with the contemporaneous covariance matrix. If the underlying dynamics is linear, the resulting dynamical description should not depend on the particular lag at which the lagged covariance matrix is estimated. This test is known as the "tau test." The tau test will be severely compromised if the lag at which the analysis is performed is approximately half the period of an internal oscillation frequency. In this case, the tau test will fail even though the dynamics are actually linear. Thus, until now, the tau test has only been possible for lags smaller than this "Nyquist lag." In this poster, we investigate the use of Hilbert transforms as a way to avoid the problems associated with Nyquist lags. By augmenting the data with dimensions orthogonal to those spanning the original system, information that would be inaccessible to LIM in its original form may be sampled.

Prediction of Malaysian monthly GDP

NASA Astrophysics Data System (ADS)

Hin, Pooi Ah; Ching, Soo Huei; Yeing, Pan Wei

2015-12-01

The paper attempts to use a method based on multivariate power-normal distribution to predict the Malaysian Gross Domestic Product next month. Letting r(t) be the vector consisting of the month-t values on m selected macroeconomic variables, and GDP, we model the month-(t+1) GDP to be dependent on the present and l-1 past values r(t), r(t-1),…,r(t-l+1) via a conditional distribution which is derived from a [(m+1)l+1]-dimensional power-normal distribution. The 100(α/2)% and 100(1-α/2)% points of the conditional distribution may be used to form an out-of sample prediction interval. This interval together with the mean of the conditional distribution may be used to predict the month-(t+1) GDP. The mean absolute percentage error (MAPE), estimated coverage probability and average length of the prediction interval are used as the criterions for selecting the suitable lag value l-1 and the subset from a pool of 17 macroeconomic variables. It is found that the relatively better models would be those of which 2 ≤ l ≤ 3, and involving one or two of the macroeconomic variables given by Market Indicative Yield, Oil Prices, Exchange Rate and Import Trade.

Evaluating the Effects of Temperature on Mortality in Manila City (Philippines) from 2006–2010 Using a Distributed Lag Nonlinear Model

PubMed Central

Seposo, Xerxes T.; Dang, Tran Ngoc; Honda, Yasushi

2015-01-01

The effect of temperature on the risk of mortality has been described in numerous studies of category-specific (e.g., cause-, sex-, age-, and season-specific) mortality in temperate and subtropical countries, with consistent findings of U-, V-, and J-shaped exposure-response functions. In this study, we analyzed the relationship between temperature and mortality in Manila City (Philippines), during 2006–2010 to identify the potential susceptible populations. We collected daily all-cause and cause-specific death counts from the Philippine Statistics Authority-National Statistics Office and the meteorological variables were collected from the Philippine Atmospheric Geophysical and Astronomical Services Administration. Temperature-mortality relationships were modeled using Poisson regression combined with distributed lag nonlinear models, and were used to perform cause-, sex-, age-, and season-specific analyses. The minimum mortality temperature was 30 °C, and increased risks of mortality were observed per 1 °C increase among elderly persons (RR: 1.53, 95% CI: 1.31–1.80), women (RR: 1.47, 95% CI: 1.27–1.69), and for respiratory causes of death (RR: 1.52, 95% CI: 1.23–1.88). Seasonal effect modification was found to greatly affect the risks in the lower temperature range. Thus, the temperature-mortality relationship in Manila City exhibited an increased risk of mortality among elderly persons, women, and for respiratory-causes, with inherent effect modification in the season-specific analysis. The findings of this study may facilitate the development of public health policies to reduce the effects of air temperature on mortality, especially for these high-risk groups. PMID:26086706

A Distributed Lag Autoregressive Model of Geostationary Relativistic Electron Fluxes: Comparing the Influences of Waves, Seed and Source Electrons, and Solar Wind Inputs

NASA Astrophysics Data System (ADS)

Simms, Laura; Engebretson, Mark; Clilverd, Mark; Rodger, Craig; Lessard, Marc; Gjerloev, Jesper; Reeves, Geoffrey

2018-05-01

Relativistic electron flux at geosynchronous orbit depends on enhancement and loss processes driven by ultralow frequency (ULF) Pc5, chorus, and electromagnetic ion cyclotron (EMIC) waves, seed electron flux, magnetosphere compression, the "Dst effect," and substorms, while solar wind inputs such as velocity, number density, and interplanetary magnetic field Bz drive these factors and thus correlate with flux. Distributed lag regression models show the time delay of highest influence of these factors on log10 high-energy electron flux (0.7-7.8 MeV, Los Alamos National Laboratory satellites). Multiple regression with an autoregressive term (flux persistence) allows direct comparison of the magnitude of each effect while controlling other correlated parameters. Flux enhancements due to ULF Pc5 and chorus waves are of equal importance. The direct effect of substorms on high-energy electron flux is strong, possibly due to injection of high-energy electrons by the substorms themselves. Loss due to electromagnetic ion cyclotron waves is less influential. Southward Bz shows only moderate influence when correlated processes are accounted for. Adding covariate compression effects (pressure and interplanetary magnetic field magnitude) allows wave-driven enhancements to be more clearly seen. Seed electrons (270 keV) are most influential at lower relativistic energies, showing that such a population must be available for acceleration. However, they are not accelerated directly to the highest energies. Source electrons (31.7 keV) show no direct influence when other factors are controlled. Their action appears to be indirect via the chorus waves they generate. Determination of specific effects of each parameter when studied in combination will be more helpful in furthering modeling work than studying them individually.

Analysis of Flow and Transport in non-Gaussian Heterogeneous Formations Using a Generalized Sub-Gaussian Model

NASA Astrophysics Data System (ADS)

Guadagnini, A.; Riva, M.; Neuman, S. P.

2016-12-01

Environmental quantities such as log hydraulic conductivity (or transmissivity), Y(x) = ln K(x), and their spatial (or temporal) increments, ΔY, are known to be generally non-Gaussian. Documented evidence of such behavior includes symmetry of increment distributions at all separation scales (or lags) between incremental values of Y with sharp peaks and heavy tails that decay asymptotically as lag increases. This statistical scaling occurs in porous as well as fractured media characterized by either one or a hierarchy of spatial correlation scales. In hierarchical media one observes a range of additional statistical ΔY scaling phenomena, all of which are captured comprehensibly by a novel generalized sub-Gaussian (GSG) model. In this model Y forms a mixture Y(x) = U(x) G(x) of single- or multi-scale Gaussian processes G having random variances, U being a non-negative subordinator independent of G. Elsewhere we developed ways to generate unconditional and conditional random realizations of isotropic or anisotropic GSG fields which can be embedded in numerical Monte Carlo flow and transport simulations. Here we present and discuss expressions for probability distribution functions of Y and ΔY as well as their lead statistical moments. We then focus on a simple flow setting of mean uniform steady state flow in an unbounded, two-dimensional domain, exploring ways in which non-Gaussian heterogeneity affects stochastic flow and transport descriptions. Our expressions represent (a) lead order autocovariance and cross-covariance functions of hydraulic head, velocity and advective particle displacement as well as (b) analogues of preasymptotic and asymptotic Fickian dispersion coefficients. We compare them with corresponding expressions developed in the literature for Gaussian Y.

Prenatal fine particulate exposure and early childhood asthma: Effect of maternal stress and fetal sex.

PubMed

Lee, Alison; Leon Hsu, Hsiao-Hsien; Mathilda Chiu, Yueh-Hsiu; Bose, Sonali; Rosa, Maria José; Kloog, Itai; Wilson, Ander; Schwartz, Joel; Cohen, Sheldon; Coull, Brent A; Wright, Robert O; Wright, Rosalind J

2018-05-01

The impact of prenatal ambient air pollution on child asthma may be modified by maternal stress, child sex, and exposure dose and timing. We prospectively examined associations between coexposure to prenatal particulate matter with an aerodynamic diameter of less than 2.5 microns (PM 2.5 ) and maternal stress and childhood asthma (n = 736). Daily PM 2.5 exposure during pregnancy was estimated using a validated satellite-based spatiotemporally resolved prediction model. Prenatal maternal negative life events (NLEs) were dichotomized around the median (high: NLE ≥ 3; low: NLE < 3). We used Bayesian distributed lag interaction models to identify sensitive windows for prenatal PM 2.5 exposure on children's asthma by age 6 years, and determine effect modification by maternal stress and child sex. Bayesian distributed lag interaction models identified a critical window of exposure (19-23 weeks' gestation, cumulative odds ratio, 1.15; 95% CI, 1.03-1.26; per interquartile range [1.7 μg/m 3 ] increase in prenatal PM 2.5 level) during which children concomitantly exposed to prenatal PM 2.5 and maternal stress had increased risk of asthma. No significant association was seen in children born to women reporting low prenatal stress. When examining modifying effects of prenatal stress and fetal sex, we found that boys born to mothers with higher prenatal stress were most vulnerable (19-21 weeks' gestation; cumulative odds ratio, 1.28; 95% CI, 1.15-1.41; per interquartile range increase in PM 2.5 ). Prenatal PM 2.5 exposure during sensitive windows is associated with increased risk of child asthma, especially in boys concurrently exposed to elevated maternal stress. Copyright © 2017 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Bayesian distributed lag interaction models to identify perinatal windows of vulnerability in children's health.

PubMed

Wilson, Ander; Chiu, Yueh-Hsiu Mathilda; Hsu, Hsiao-Hsien Leon; Wright, Robert O; Wright, Rosalind J; Coull, Brent A

2017-07-01

Epidemiological research supports an association between maternal exposure to air pollution during pregnancy and adverse children's health outcomes. Advances in exposure assessment and statistics allow for estimation of both critical windows of vulnerability and exposure effect heterogeneity. Simultaneous estimation of windows of vulnerability and effect heterogeneity can be accomplished by fitting a distributed lag model (DLM) stratified by subgroup. However, this can provide an incomplete picture of how effects vary across subgroups because it does not allow for subgroups to have the same window but different within-window effects or to have different windows but the same within-window effect. Because the timing of some developmental processes are common across subpopulations of infants while for others the timing differs across subgroups, both scenarios are important to consider when evaluating health risks of prenatal exposures. We propose a new approach that partitions the DLM into a constrained functional predictor that estimates windows of vulnerability and a scalar effect representing the within-window effect directly. The proposed method allows for heterogeneity in only the window, only the within-window effect, or both. In a simulation study we show that a model assuming a shared component across groups results in lower bias and mean squared error for the estimated windows and effects when that component is in fact constant across groups. We apply the proposed method to estimate windows of vulnerability in the association between prenatal exposures to fine particulate matter and each of birth weight and asthma incidence, and estimate how these associations vary by sex and maternal obesity status in a Boston-area prospective pre-birth cohort study. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The Impacts of Air Temperature on Accidental Casualties in Beijing, China.

PubMed

Ma, Pan; Wang, Shigong; Fan, Xingang; Li, Tanshi

2016-11-02

Emergency room (ER) visits for accidental casualties, according to the International Classification of Deceases 10th Revision Chapters 19 and 20, include injury, poisoning, and external causes (IPEC). Annual distribution of 187,008 ER visits that took place between 2009 and 2011 in Beijing, China displayed regularity rather than random characteristics. The annual cycle from the Fourier series fitting of the number of ER visits was found to explain 63.2% of its total variance. In this study, the possible effect and regulation of meteorological conditions on these ER visits are investigated through the use of correlation analysis, as well as statistical modeling by using the Distributed Lag Non-linear Model and Generalized Additive Model. Correlation analysis indicated that meteorological variables that positively correlated with temperature have a positive relationship with the number of ER visits, and vice versa. The temperature metrics of maximum, minimum, and mean temperatures were found to have similar overall impacts, including both the direct impact on human mental/physical conditions and indirect impact on human behavior. The lag analysis indicated that the overall impacts of temperatures higher than the 50th percentile on ER visits occur immediately, whereas low temperatures show protective effects in the first few days. Accidental casualties happen more frequently on warm days when the mean temperature is higher than 14 °C than on cold days. Mean temperatures of around 26 °C result in the greatest possibility of ER visits for accidental casualties. In addition, males were found to face a higher risk of accidental casualties than females at high temperatures. Therefore, the IPEC-classified ER visits are not pure accidents; instead, they are associated closely with meteorological conditions, especially temperature.

Predictions of Control Inputs, Periodic Responses and Damping Levels of an Isolated Experimental Rotor in Trimmed Flight

NASA Technical Reports Server (NTRS)

Gaonkar, G. H.; Subramanian, S.

1996-01-01

Since the early 1990s the Aeroflightdynamics Directorate at the Ames Research Center has been conducting tests on isolated hingeless rotors in hover and forward flight. The primary objective is to generate a database on aeroelastic stability in trimmed flight for torsionally soft rotors at realistic tip speeds. The rotor test model has four soft inplane blades of NACA 0012 airfoil section with low torsional stiffness. The collective pitch and shaft tilt are set prior to each test run, and then the rotor is trimmed in the following sense: the longitudinal and lateral cyclic pitch controls are adjusted through a swashplate to minimize the 1/rev flapping moment at the 12 percent radial station. In hover, the database comprises lag regressive-mode damping with pitch variations. In forward flight the database comprises cyclic pitch controls, root flap moment and lag regressive-mode damping with advance ratio, shaft angle and pitch variations. This report presents the predictions and their correlation with the database. A modal analysis is used, in which nonrotating modes in flap bending, lag bending and torsion are computed from the measured blade mass and stiffness distributions. The airfoil aerodynamics is represented by the ONERA dynamic stall models of lift, drag and pitching moment, and the wake dynamics is represented by a state-space wake model. The trim analysis of finding, the cyclic controls and the corresponding, periodic responses is based on periodic shooting with damped Newton iteration; the Floquet transition matrix (FTM) comes out as a byproduct. The stabillty analysis of finding the frequencies and damping levels is based on the eigenvalue-eigenvector analysis of the FTM. All the structural and aerodynamic states are included from modeling to trim analysis. A major finding is that dynamic wake dramatically improves the correlation for the lateral cyclic pitch control. Overall, the correlation is fairly good.

Performance of a coupled lagged ensemble weather and river runoff prediction model system for the Alpine Ammer River catchment

NASA Astrophysics Data System (ADS)

Smiatek, G.; Kunstmann, H.; Werhahn, J.

2012-04-01

The Ammer River catchment located in the Bavarian Ammergau Alps and alpine forelands, Germany, represents with elevations reaching 2185 m and annual mean precipitation between1100 and 2000 mm a very demanding test ground for a river runoff prediction system. Large flooding events in 1999 and 2005 motivated the development of a physically based prediction tool in this area. Such a tool is the coupled high resolution numerical weather and river runoff forecasting system AM-POE that is being studied in several configurations in various experiments starting from the year 2005. Corner stones of the coupled system are the hydrological water balance model WaSiM-ETH run at 100 m grid resolution, the numerical weather prediction model (NWP) MM5 driven at 3.5 km grid cell resolution and the Perl Object Environment (POE) framework. POE implements the input data download from various sources, the input data provision via SOAP based WEB services as well as the runs of the hydrology model both with observed and with NWP predicted meteorology input. The one way coupled system utilizes a lagged ensemble prediction system (EPS) taking into account combination of recent and previous NWP forecasts. Results obtained in the years 2005-2011 reveal that river runoff simulations depict high correlation with observed runoff when driven with monitored observations in hindcast experiments. The ability to runoff forecasts is depending on lead times in the lagged ensemble prediction and shows still limitations resulting from errors in timing and total amount of the predicted precipitation in the complex mountainous area. The presentation describes the system implementation, and demonstrates the application of the POE framework in networking, distributed computing and in the setup of various experiments as well as long term results of the system application in the years 2005 - 2011.

Predicting the hand, foot, and mouth disease incidence using search engine query data and climate variables: an ecological study in Guangdong, China.

PubMed

Du, Zhicheng; Xu, Lin; Zhang, Wangjian; Zhang, Dingmei; Yu, Shicheng; Hao, Yuantao

2017-10-06

Hand, foot, and mouth disease (HFMD) has caused a substantial burden in China, especially in Guangdong Province. Based on the enhanced surveillance system, we aimed to explore whether the addition of temperate and search engine query data improves the risk prediction of HFMD. Ecological study. Information on the confirmed cases of HFMD, climate parameters and search engine query logs was collected. A total of 1.36 million HFMD cases were identified from the surveillance system during 2011-2014. Analyses were conducted at aggregate level and no confidential information was involved. A seasonal autoregressive integrated moving average (ARIMA) model with external variables (ARIMAX) was used to predict the HFMD incidence from 2011 to 2014, taking into account temperature and search engine query data (Baidu Index, BDI). Statistics of goodness-of-fit and precision of prediction were used to compare models (1) based on surveillance data only, and with the addition of (2) temperature, (3) BDI, and (4) both temperature and BDI. A high correlation between HFMD incidence and BDI ( r =0.794, p<0.001) or temperature ( r =0.657, p<0.001) was observed using both time series plot and correlation matrix. A linear effect of BDI (without lag) and non-linear effect of temperature (1 week lag) on HFMD incidence were found in a distributed lag non-linear model. Compared with the model based on surveillance data only, the ARIMAX model including BDI reached the best goodness-of-fit with an Akaike information criterion (AIC) value of -345.332, whereas the model including both BDI and temperature had the most accurate prediction in terms of the mean absolute percentage error (MAPE) of 101.745%. An ARIMAX model incorporating search engine query data significantly improved the prediction of HFMD. Further studies are warranted to examine whether including search engine query data also improves the prediction of other infectious diseases in other settings. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Predicting the hand, foot, and mouth disease incidence using search engine query data and climate variables: an ecological study in Guangdong, China

PubMed Central

Du, Zhicheng; Xu, Lin; Zhang, Wangjian; Zhang, Dingmei; Yu, Shicheng; Hao, Yuantao

2017-01-01

Objectives Hand, foot, and mouth disease (HFMD) has caused a substantial burden in China, especially in Guangdong Province. Based on the enhanced surveillance system, we aimed to explore whether the addition of temperate and search engine query data improves the risk prediction of HFMD. Design Ecological study. Setting and participants Information on the confirmed cases of HFMD, climate parameters and search engine query logs was collected. A total of 1.36 million HFMD cases were identified from the surveillance system during 2011–2014. Analyses were conducted at aggregate level and no confidential information was involved. Outcome measures A seasonal autoregressive integrated moving average (ARIMA) model with external variables (ARIMAX) was used to predict the HFMD incidence from 2011 to 2014, taking into account temperature and search engine query data (Baidu Index, BDI). Statistics of goodness-of-fit and precision of prediction were used to compare models (1) based on surveillance data only, and with the addition of (2) temperature, (3) BDI, and (4) both temperature and BDI. Results A high correlation between HFMD incidence and BDI (r=0.794, p<0.001) or temperature (r=0.657, p<0.001) was observed using both time series plot and correlation matrix. A linear effect of BDI (without lag) and non-linear effect of temperature (1 week lag) on HFMD incidence were found in a distributed lag non-linear model. Compared with the model based on surveillance data only, the ARIMAX model including BDI reached the best goodness-of-fit with an Akaike information criterion (AIC) value of −345.332, whereas the model including both BDI and temperature had the most accurate prediction in terms of the mean absolute percentage error (MAPE) of 101.745%. Conclusions An ARIMAX model incorporating search engine query data significantly improved the prediction of HFMD. Further studies are warranted to examine whether including search engine query data also improves the prediction of other infectious diseases in other settings. PMID:28988169

Using nonlinear forecasting to learn the magnitude and phasing of time-varying sediment suspension in the surf zone

USGS Publications Warehouse

Jaffe, B.E.; Rubin, D.M.

1996-01-01

The time-dependent response of sediment suspension to flow velocity was explored by modeling field measurements collected in the surf zone during a large storm. Linear and nonlinear models were created and tested using flow velocity as input and suspended-sediment concentration as output. A sequence of past velocities (velocity history), as well as velocity from the same instant as the suspended-sediment concentration, was used as input; this velocity history length was allowed to vary. The models also allowed for a lag between input (instantaneous velocity or end of velocity sequence) and output (suspended-sediment concentration). Predictions of concentration from instantaneous velocity or instantaneous velocity raised to a power (up to 8) using linear models were poor (correlation coefficients between predicted and observed concentrations were less than 0.10). Allowing a lag between velocity and concentration improved linear models (correlation coefficient of 0.30), with optimum lag time increasing with elevation above the seabed (from 1.5 s at 13 cm to 8.5 s at 60 cm). These lags are largely due to the time for an observed flow event to effect the bed and mix sediment upward. Using a velocity history further improved linear models (correlation coefficient of 0.43). The best linear model used 12.5 s of velocity history (approximately one wave period) to predict concentration. Nonlinear models gave better predictions than linear models, and, as with linear models, nonlinear models using a velocity history performed better than models using only instantaneous velocity as input. Including a lag time between the velocity and concentration also improved the predictions. The best model (correlation coefficient of 0.58) used 3 s (approximately a quarter wave period) of the cross-shore velocity squared, starting at 4.5 s before the observed concentration, to predict concentration. Using a velocity history increases the performance of the models by specifying a more complete description of the dynamical forcing of the flow (including accelerations and wave phase and shape) responsible for sediment suspension. Incorporating such a velocity history and a lag time into the formulation of the forcing for time-dependent models for sediment suspension in the surf zone will greatly increase our ability to predict suspended-sediment transport.

A new model of strabismic amblyopia: Loss of spatial acuity due to increased temporal dispersion of geniculate X-cell afferents on to cortical neurons.

PubMed

Crewther, D P; Crewther, S G

2015-09-01

Although the neural locus of strabismic amblyopia has been shown to lie at the first site of binocular integration, first in cat and then in primate, an adequate mechanism is still lacking. Here we hypothesise that increased temporal dispersion of LGN X-cell afferents driven by the deviating eye onto single cortical neurons may provide a neural mechanism for strabismic amblyopia. This idea was investigated via single cell extracellular recordings of 93 X and 50 Y type LGN neurons from strabismic and normal cats. Both X and Y neurons driven by the non-deviating eye showed shorter latencies than those driven by either the strabismic or normal eyes. Also the mean latency difference between X and Y neurons was much greater for the strabismic cells compared with the other two groups. The incidence of lagged X-cells driven by the deviating eye of the strabismic cats was higher than that of LGN X-cells from normal animals. Remarkably, none of the cells recorded from the laminae driven by the non-deviating eye were of the lagged class. A simple computational model was constructed in which a mixture of lagged and non-lagged afferents converge on to single cortical neurons. Model cut-off spatial frequencies to a moving grating stimulus were sensitive to the temporal dispersion of the geniculate afferents. Thus strabismic amblyopia could be viewed as a lack of developmental tuning of geniculate lags for neurons driven by the amblyopic eye. Monocular control of fixation by the non-deviating eye is associated with reduced incidence of lagged neurons, suggesting that in normal vision, lagged neurons might play a role in maintaining binocular connections for cortical neurons. Copyright © 2014 Elsevier Ltd. All rights reserved.

Modeling Time-Dependent Association in Longitudinal Data: A Lag as Moderator Approach

ERIC Educational Resources Information Center

Selig, James P.; Preacher, Kristopher J.; Little, Todd D.

2012-01-01

We describe a straightforward, yet novel, approach to examine time-dependent association between variables. The approach relies on a measurement-lag research design in conjunction with statistical interaction models. We base arguments in favor of this approach on the potential for better understanding the associations between variables by…

The nitrate time bomb: a numerical way to investigate nitrate storage and lag time in the unsaturated zone.

PubMed

Wang, L; Butcher, A S; Stuart, M E; Gooddy, D C; Bloomfield, J P

2013-10-01

Nitrate pollution in groundwater, which is mainly from agricultural activities, remains an international problem. It threatens the environment, economics and human health. There is a rising trend in nitrate concentrations in many UK groundwater bodies. Research has shown it can take decades for leached nitrate from the soil to discharge into groundwater and surface water due to the 'store' of nitrate and its potentially long travel time in the unsaturated and saturated zones. However, this time lag is rarely considered in current water nitrate management and policy development. The aim of this study was to develop a catchment-scale integrated numerical method to investigate the nitrate lag time in the groundwater system, and the Eden Valley, UK, was selected as a case study area. The method involves three models, namely the nitrate time bomb-a process-based model to simulate the nitrate transport in the unsaturated zone (USZ), GISGroundwater--a GISGroundwater flow model, and N-FM--a model to simulate the nitrate transport in the saturated zone. This study answers the scientific questions of when the nitrate currently in the groundwater was loaded into the unsaturated zones and eventually reached the water table; is the rising groundwater nitrate concentration in the study area caused by historic nitrate load; what caused the uneven distribution of groundwater nitrate concentration in the study area; and whether the historic peak nitrate loading has reached the water table in the area. The groundwater nitrate in the area was mainly from the 1980s to 2000s, whilst the groundwater nitrate in most of the source protection zones leached into the system during 1940s-1970s; the large and spatially variable thickness of the USZ is one of the major reasons for unevenly distributed groundwater nitrate concentrations in the study area; the peak nitrate loading around 1983 has affected most of the study area. For areas around the Bowscar, Beacon Edge, Low Plains, Nord Vue, Dale Springs, Gamblesby, Bankwood Springs, and Cliburn, the peak nitrate loading will arrive at the water table in the next 34 years; statistical analysis shows that 8.7 % of the Penrith Sandstone and 7.3 % of the St Bees Sandstone have not been affected by peak nitrate. This research can improve the scientific understanding of nitrate processes in the groundwater system and support the effective management of groundwater nitrate pollution for the study area. With a limited number of parameters, the method and models developed in this study are readily transferable to other areas.

Calibration of Watershed Lag Time Equation for Philippine Hydrology using RADARSAT Digital Elevation Models

NASA Astrophysics Data System (ADS)

Cipriano, F. R.; Lagmay, A. M. A.; Horritt, M.; Mendoza, J.; Sabio, G.; Punay, K. N.; Taniza, H. J.; Uichanco, C.

2015-12-01

Widespread flooding is a major problem in the Philippines. The country experiences heavy amount of rainfall throughout the year and several areas are prone to flood hazards because of its unique topography. Human casualties and destruction of infrastructure are just some of the damages caused by flooding and the Philippine government has undertaken various efforts to mitigate these hazards. One of the solutions was to create flood hazard maps of different floodplains and use them to predict the possible catastrophic results of different rain scenarios. To produce these maps with accurate output, different input parameters were needed and one of those is calculating hydrological components from topographical data. This paper presents how a calibrated lag time (TL) equation was obtained using measurable catchment parameters. Lag time is an essential input in flood mapping and is defined as the duration between the peak rainfall and peak discharge of the watershed. The lag time equation involves three measurable parameters, namely, watershed length (L), maximum potential retention (S) derived from the curve number, and watershed slope (Y), all of which were available from RADARSAT Digital Elevation Models (DEM). This approach was based on a similar method developed by CH2M Hill and Horritt for Taiwan, which has a similar set of meteorological and hydrological parameters with the Philippines. Rainfall data from fourteen water level sensors covering 67 storms from all the regions in the country were used to estimate the actual lag time. These sensors were chosen by using a screening process that considers the distance of the sensors from the sea, the availability of recorded data, and the catchment size. The actual lag time values were plotted against the values obtained from the Natural Resource Conservation Management handbook lag time equation. Regression analysis was used to obtain the final calibrated equation that would be used to calculate the lag time specifically for rivers in the Philippine setting. The calculated lag time values could then be used as a parameter for modeling different flood scenarios in the country.

A nonlinear lag correction algorithm for a-Si flat-panel x-ray detectors

PubMed Central

Starman, Jared; Star-Lack, Josh; Virshup, Gary; Shapiro, Edward; Fahrig, Rebecca

2012-01-01

Purpose: Detector lag, or residual signal, in a-Si flat-panel (FP) detectors can cause significant shading artifacts in cone-beam computed tomography reconstructions. To date, most correction models have assumed a linear, time-invariant (LTI) model and correct lag by deconvolution with an impulse response function (IRF). However, the lag correction is sensitive to both the exposure intensity and the technique used for determining the IRF. Even when the LTI correction that produces the minimum error is found, residual artifact remains. A new non-LTI method was developed to take into account the IRF measurement technique and exposure dependencies. Methods: First, a multiexponential (N = 4) LTI model was implemented for lag correction. Next, a non-LTI lag correction, known as the nonlinear consistent stored charge (NLCSC) method, was developed based on the LTI multiexponential method. It differs from other nonlinear lag correction algorithms in that it maintains a consistent estimate of the amount of charge stored in the FP and it does not require intimate knowledge of the semiconductor parameters specific to the FP. For the NLCSC method, all coefficients of the IRF are functions of exposure intensity. Another nonlinear lag correction method that only used an intensity weighting of the IRF was also compared. The correction algorithms were applied to step-response projection data and CT acquisitions of a large pelvic phantom and an acrylic head phantom. The authors collected rising and falling edge step-response data on a Varian 4030CB a-Si FP detector operating in dynamic gain mode at 15 fps at nine incident exposures (2.0%–92% of the detector saturation exposure). For projection data, 1st and 50th frame lag were measured before and after correction. For the CT reconstructions, five pairs of ROIs were defined and the maximum and mean signal differences within a pair were calculated for the different exposures and step-response edge techniques. Results: The LTI corrections left residual 1st and 50th frame lag up to 1.4% and 0.48%, while the NLCSC lag correction reduced 1st and 50th frame residual lags to less than 0.29% and 0.0052%. For CT reconstructions, the NLCSC lag correction gave an average error of 11 HU for the pelvic phantom and 3 HU for the head phantom, compared to 14–19 HU and 2–11 HU for the LTI corrections and 15 HU and 9 HU for the intensity weighted non-LTI algorithm. The maximum ROI error was always smallest for the NLCSC correction. The NLCSC correction was also superior to the intensity weighting algorithm. Conclusions: The NLCSC lag algorithm corrected for the exposure dependence of lag, provided superior image improvement for the pelvic phantom reconstruction, and gave similar results to the best case LTI results for the head phantom. The blurred ring artifact that is left over in the LTI corrections was better removed by the NLCSC correction in all cases. PMID:23039642

Time-series Analysis of Heat Waves and Emergency Department Visits in Atlanta, 1993 to 2012

PubMed Central

Chen, Tianqi; Sarnat, Stefanie E.; Grundstein, Andrew J.; Winquist, Andrea

2017-01-01

Background: Heat waves are extreme weather events that have been associated with adverse health outcomes. However, there is limited knowledge of heat waves’ impact on population morbidity, such as emergency department (ED) visits. Objectives: We investigated associations between heat waves and ED visits for 17 outcomes in Atlanta over a 20-year period, 1993–2012. Methods: Associations were estimated using Poisson log-linear models controlling for continuous air temperature, dew-point temperature, day of week, holidays, and time trends. We defined heat waves as periods of ≥2 consecutive days with temperatures beyond the 98th percentile of the temperature distribution over the period from 1945–2012. We considered six heat wave definitions using maximum, minimum, and average air temperatures and apparent temperatures. Associations by heat wave characteristics were examined. Results: Among all outcome-heat wave combinations, associations were strongest between ED visits for acute renal failure and heat waves defined by maximum apparent temperature at lag 0 [relative risk (RR) = 1.15; 95% confidence interval (CI): 1.03–1.29], ED visits for ischemic stroke and heat waves defined by minimum temperature at lag 0 (RR = 1.09; 95% CI: 1.02–1.17), and ED visits for intestinal infection and heat waves defined by average temperature at lag 1 (RR = 1.10; 95% CI: 1.00–1.21). ED visits for all internal causes were associated with heat waves defined by maximum temperature at lag 1 (RR = 1.02; 95% CI: 1.00, 1.04). Conclusions: Heat waves can confer additional risks of ED visits beyond those of daily air temperature, even in a region with high air-conditioning prevalence. https://doi.org/10.1289/EHP44 PMID:28599264

A new paradigm for Aedes spp. surveillance using gravid ovipositing sticky trap and NS1 antigen test kit.

PubMed

Lau, Sai Ming; Chua, Tock H; Sulaiman, Wan-Yussof; Joanne, Sylvia; Lim, Yvonne Ai-Lian; Sekaran, Shamala Devi; Chinna, Karuthan; Venugopalan, Balan; Vythilingam, Indra

2017-03-21

Dengue remains a serious public health problem in Southeast Asia and has increased 37-fold in Malaysia compared to decades ago. New strategies are urgently needed for early detection and control of dengue epidemics. We conducted a two year study in a high human density dengue-endemic urban area in Selangor, where Gravid Ovipositing Sticky (GOS) traps were set up to capture adult Aedes spp. mosquitoes. All Aedes mosquitoes were tested using the NS1 dengue antigen test kit. All dengue cases from the study site notified to the State Health Department were recorded. Weekly microclimatic temperature, relative humidity (RH) and rainfall were monitored. Aedes aegypti was the predominant mosquito (95.6%) caught in GOS traps and 23% (43/187 pools of 5 mosquitoes each) were found to be positive for dengue using the NS1 antigen kit. Confirmed cases of dengue were observed with a lag of one week after positive Ae. aegypti were detected. Aedes aegypti density as analysed by distributed lag non-linear models, will increase lag of 2-3 weeks for temperature increase from 28 to 30 °C; and lag of three weeks for increased rainfall. Proactive strategy is needed for dengue vector surveillance programme. One method would be to use the GOS trap which is simple to setup, cost effective (below USD 1 per trap) and environmental friendly (i.e. use recyclable plastic materials) to capture Ae. aegypti followed by a rapid method of detecting of dengue virus using the NS1 dengue antigen kit. Control measures should be initiated when positive mosquitoes are detected.

Time-series Analysis of Heat Waves and Emergency Department Visits in Atlanta, 1993 to 2012.

PubMed

Chen, Tianqi; Sarnat, Stefanie E; Grundstein, Andrew J; Winquist, Andrea; Chang, Howard H

2017-05-31

Heat waves are extreme weather events that have been associated with adverse health outcomes. However, there is limited knowledge of heat waves' impact on population morbidity, such as emergency department (ED) visits. We investigated associations between heat waves and ED visits for 17 outcomes in Atlanta over a 20-year period, 1993-2012. Associations were estimated using Poisson log-linear models controlling for continuous air temperature, dew-point temperature, day of week, holidays, and time trends. We defined heat waves as periods of consecutive days with temperatures beyond the 98th percentile of the temperature distribution over the period from 1945-2012. We considered six heat wave definitions using maximum, minimum, and average air temperatures and apparent temperatures. Associations by heat wave characteristics were examined. Among all outcome-heat wave combinations, associations were strongest between ED visits for acute renal failure and heat waves defined by maximum apparent temperature at lag 0 [relative risk (RR) = 1.15; 95% confidence interval (CI): 1.03-1.29], ED visits for ischemic stroke and heat waves defined by minimum temperature at lag 0 (RR = 1.09; 95% CI: 1.02-1.17), and ED visits for intestinal infection and heat waves defined by average temperature at lag 1 (RR = 1.10; 95% CI: 1.00-1.21). ED visits for all internal causes were associated with heat waves defined by maximum temperature at lag 1 (RR = 1.02; 95% CI: 1.00, 1.04). Heat waves can confer additional risks of ED visits beyond those of daily air temperature, even in a region with high air-conditioning prevalence. https://doi.org/10.1289/EHP44.

Understanding User Behavioral Patterns in Open Knowledge Communities

ERIC Educational Resources Information Center

Yang, Xianmin; Song, Shuqiang; Zhao, Xinshuo; Yu, Shengquan

2018-01-01

Open knowledge communities (OKCs) have become popular in the era of knowledge economy. This study aimed to explore how users collaboratively create and share knowledge in OKCs. In particular, this research identified the behavior distribution and behavioral patterns of users by conducting frequency distribution and lag sequential analyses. Some…

Population trends influence species ability to track climate change

Treesearch

Joel Ralston; William V. DeLuca; Richard E. Feldman; David I. King

2016-01-01

Shifts of distributions have been attributed to species tracking their fundamental climate niches through space. However, several studies have now demonstrated that niche tracking is imperfect, that species' climate niches may vary with population trends, and that geographic distributions may lag behind rapid climate change. These reports of imperfect niche...

Cosmological velocity correlations - Observations and model predictions

NASA Technical Reports Server (NTRS)

Gorski, Krzysztof M.; Davis, Marc; Strauss, Michael A.; White, Simon D. M.; Yahil, Amos

1989-01-01

By applying the present simple statistics for two-point cosmological peculiar velocity-correlation measurements to the actual data sets of the Local Supercluster spiral galaxy of Aaronson et al. (1982) and the elliptical galaxy sample of Burstein et al. (1987), as well as to the velocity field predicted by the distribution of IRAS galaxies, a coherence length of 1100-1600 km/sec is obtained. Coherence length is defined as that separation at which the correlations drop to half their zero-lag value. These results are compared with predictions from two models of large-scale structure formation: that of cold dark matter and that of baryon isocurvature proposed by Peebles (1980). N-body simulations of these models are performed to check the linear theory predictions and measure sampling fluctuations.

Analysis of brain patterns using temporal measures

DOEpatents

Georgopoulos, Apostolos

2015-08-11

A set of brain data representing a time series of neurophysiologic activity acquired by spatially distributed sensors arranged to detect neural signaling of a brain (such as by the use of magnetoencephalography) is obtained. The set of brain data is processed to obtain a dynamic brain model based on a set of statistically-independent temporal measures, such as partial cross correlations, among groupings of different time series within the set of brain data. The dynamic brain model represents interactions between neural populations of the brain occurring close in time, such as with zero lag, for example. The dynamic brain model can be analyzed to obtain the neurophysiologic assessment of the brain. Data processing techniques may be used to assess structural or neurochemical brain pathologies.

Assessing the cold temperature effect on hospital visit by allergic rhinitis in Seoul, Korea.

PubMed

Kim, Hyomi; Kim, Honghyok; Lee, Jong-Tae

2018-08-15

The association between temperature and health outcome has been studied in worldwide. However, studies for mild diseases such as AR, with high prevalence and considerable economic burden, are lacking compared to other relatively severe respiratory diseases. We aimed to assess the trend of hospital visit by AR and estimate the cold temperature effect on hospital visit by allergic rhinitis in Seoul, Korea, 2003-2011. We fitted generalized additive model with quasi-poisson distribution, controlling for humidity, long-term trend, day of week, national holiday, and influenza epidemic. We estimated the cumulative cold temperature effect (10%, -1.7°C) referent to 7.9°C for the considered lag periods using distributed lag non-linear model: vary from the day of hospital visit to 10days before. Stratified analysis by season was also conducted. To adjust for possible confounding effect of air pollutants, we additionally adjusted for PM 10 , O 3 and NO 2 respectively. Hospital visit counts and rates per 1,000,000 show increasing trend especially in elderly population (over 65years). Hospital visit rate is higher in children population (age<13years). Statistically significant cold temperature effects were found in the total (1.094(95%CI: 1.037, 1.153)), male (1.100 (95%CI: 1.010, 1.163)), female (1.088 (95%CI: 1.059, 1.170)) and adult (1.113 (95%CI: 1.059, 1.170)) population with consideration of 3-day lag period. In the stratified analysis by the season, the strongest effect was shown in the autumn (Sep-Nov) season. Confounding effects by air pollutants were not found. In this study, we found significant increasing trend of hospital visit by AR. This study provides suggestive evidence of cold temperature effect on hospital visit by AR. To reduce the growing burden of AR, it is important to find possible related environmental risk factors. More studies should be conducted for better understanding of temperature effect on AR. Copyright © 2018 Elsevier B.V. All rights reserved.

X-ray time lags in PG 1211+143

NASA Astrophysics Data System (ADS)

Lobban, A. P.; Vaughan, S.; Pounds, K.; Reeves, J. N.

2018-05-01

We investigate the X-ray time lags of a recent ˜630 ks XMM-Newton observation of PG 1211+143. We find well-correlated variations across the XMM-Newton EPIC bandpass, with the first detection of a hard lag in this source with a mean time delay of up to ˜3 ks at the lowest frequencies. We find that the energy-dependence of the low-frequency hard lag scales approximately linearly with log(E) when averaged over all orbits, consistent with the propagating fluctuations model. However, we find that the low-frequency lag behaviour becomes more complex on time-scales longer than a single orbit, suggestive of additional modes of variability. We also detect a high-frequency soft lag at ˜10-4 Hz with the magnitude of the delay peaking at ≲ 0.8 ks, consistent with previous observations, which we discuss in terms of small-scale reverberation.

Population trends influence species ability to track climate change.

PubMed

Ralston, Joel; DeLuca, William V; Feldman, Richard E; King, David I

2017-04-01

Shifts of distributions have been attributed to species tracking their fundamental climate niches through space. However, several studies have now demonstrated that niche tracking is imperfect, that species' climate niches may vary with population trends, and that geographic distributions may lag behind rapid climate change. These reports of imperfect niche tracking imply shifts in species' realized climate niches. We argue that quantifying climate niche shifts and analyzing them for a suite of species reveal general patterns of niche shifts and the factors affecting species' ability to track climate change. We analyzed changes in realized climate niche between 1984 and 2012 for 46 species of North American birds in relation to population trends in an effort to determine whether species differ in the ability to track climate change and whether differences in niche tracking are related to population trends. We found that increasingly abundant species tended to show greater levels of niche expansion (climate space occupied in 2012 but not in 1980) compared to declining species. Declining species had significantly greater niche unfilling (climate space occupied in 1980 but not in 2012) compared to increasing species due to an inability to colonize new sites beyond their range peripheries after climate had changed at sites of occurrence. Increasing species, conversely, were better able to colonize new sites and therefore showed very little niche unfilling. Our results indicate that species with increasing trends are better able to geographically track climate change compared to declining species, which exhibited lags relative to changes in climate. These findings have important implications for understanding past changes in distribution, as well as modeling dynamic species distributions in the face of climate change. © 2016 John Wiley & Sons Ltd.

Integrating Environmental and Mosquito Data to Model Disease: Evaluating Alternative Modeling Approaches for Forecasting West Nile Virus in South Dakota, USA

NASA Astrophysics Data System (ADS)

Davis, J. K.; Vincent, G. P.; Hildreth, M.; Kightlinger, L.; Carlson, C.; Wimberly, M. C.

2017-12-01

South Dakota has the highest annual incidence of human cases of West Nile virus (WNV) in all US states, and human cases can vary wildly among years; predicting WNV risk in advance is a necessary exercise if public health officials are to respond efficiently and effectively to risk. Case counts are associated with environmental factors that affect mosquitoes, avian hosts, and the virus itself. They are also correlated with entomological risk indices obtained by trapping and testing mosquitoes. However, neither weather nor insect data alone provide a sufficient basis to make timely and accurate predictions, and combining them into models of human disease is not necessarily straightforward. Here we present lessons learned in three years of making real-time forecasts of this threat to public health. Various methods of integrating data from NASA's North American Land Data Assimilation System (NLDAS) with mosquito surveillance data were explored in a model comparison framework. We found that a model of human disease summarizing weather data (by polynomial distributed lags with seasonally-varying coefficients) and mosquito data (by a mixed-effects model that smooths out these sparse and highly-variable data) made accurate predictions of risk, and was generalizable enough to be recommended in similar applications. A model based on lagged effects of temperature and humidity provided the most accurate predictions. We also found that model accuracy was improved by allowing coefficients to vary smoothly throughout the season, giving different weights to different predictor variables during different parts of the season.

Single-cell analysis of S. cerevisiae growth recovery after a sublethal heat-stress applied during an alcoholic fermentation.

PubMed

Tibayrenc, Pierre; Preziosi-Belloy, Laurence; Ghommidh, Charles

2011-06-01

Interest in bioethanol production has experienced a resurgence in the last few years. Poor temperature control in industrial fermentation tanks exposes the yeast cells used for this production to intermittent heat stress which impairs fermentation efficiency. Therefore, there is a need for yeast strains with improved tolerance, able to recover from such temperature variations. Accordingly, this paper reports the development of methods for the characterization of Saccharomyces cerevisiae growth recovery after a sublethal heat stress. Single-cell measurements were carried out in order to detect cell-to-cell variability. Alcoholic batch fermentations were performed on a defined medium in a 2 l instrumented bioreactor. A rapid temperature shift from 33 to 43 °C was applied when ethanol concentration reached 50 g l⁻¹. Samples were collected at different times after the temperature shift. Single cell growth capability, lag-time and initial growth rate were determined by monitoring the growth of a statistically significant number of cells after agar medium plating. The rapid temperature shift resulted in an immediate arrest of growth and triggered a progressive loss of cultivability from 100 to 0.0001% within 8 h. Heat-injured cells were able to recover their growth capability on agar medium after a lag phase. Lag-time was longer and more widely distributed as the time of heat exposure increased. Thus, lag-time distribution gives an insight into strain sensitivity to heat-stress, and could be helpful for the selection of yeast strains of technological interest.

Bioavailability of a Lipidic Formulation of Curcumin in Healthy Human Volunteers

PubMed Central

Pawar, Yogesh B.; Munjal, Bhushan; Arora, Saurabh; Karwa, Manoj; Kohli, Gunjan; Paliwal, Jyoti K.; Bansal, Arvind K.

2012-01-01

Numerous publications have reported the significant pharmacodynamic activity of Curcumin (CRM) despite low or undetectable levels in plasma. The objective of the present study was to perform a detailed pharmacokinetic evaluation of CRM after the oral administration of a highly bioavailable lipidic formulation of CRM (CRM-LF) in human subjects. Cmax, Tmax and AUC0–∞ were found to be 183.35 ± 37.54 ng/mL, 0.60 ± 0.05 h and 321.12 ± 25.55 ng/mL respectively, at a dose of 750 mg. The plasma profile clearly showed three distinct phases, viz., absorption, distribution and elimination. A close evaluation of the primary pharmacokinetic parameters provided valuable insight into the behavior of the CRM after absorption by CRM-LF. CRM-LF showed a lag time (Tlag) of 0.18 h (around 12 min). Pharmacokinetic modeling revealed that CRM-LF followed a two-compartment model with first order absorption, lag time and first order elimination. A high absorption rate constant (K01, 4.51/h) signifies that CRM-LF ensured rapid absorption of the CRM into the central compartment. This was followed by the distribution of CRM from the central to peripheral compartment (K12, 2.69/h). The rate of CRM transfer from the peripheral to central compartment (K21, 0.15/h) was slow. This encourages higher tissue levels of CRM as compared with plasma levels. The study provides an explanation of the therapeutic efficacy of CRM, despite very low/undetectable levels in the plasma. PMID:24300368

Lag and seasonality considerations in evaluating AVHRR NDVI response to precipitation

USGS Publications Warehouse

Ji, Lei; Peters, Albert J.

2005-01-01

Assessment of the relationship between the normalized difference vegetation index (NDVI) and precipitation is important in understanding vegetation and climate interaction at a large scale. NDVI response to precipitation, however, is difficult to quantify due to the lag and seasonality effects, which will vary due to vegetation cover type, soils and climate. A time series analysis was performed on biweekly NDVI and precipitation around weather stations in the northern and central U.S. Great Plains. Regression models that incorporate lag and seasonality effects were used to quantify the relationship between NDVI and lagged precipitation in grasslands and croplands. It was found that the time lag was shorter in the early growing season, but longer in the mid- to late-growing season for most locations. The regression models with seasonal adjustment indicate that the relationship between NDVI and precipitation over the entire growing season was strong, with R2 values of 0.69 and 0.72 for grasslands and croplands, respectively. We conclude that vegetation greenness can be predicted using current and antecedent precipitation, if seasonal effects are taken into account.

[Are simple time lags responsible for cyclic variation of population density? : A comparison of laboratory population dynamics of Brachionus calyciflorus pallas (rotatoria) with computer simulations].

PubMed

Halbach, Udo; Burkhardt, Heinz Jürgen

1972-09-01

Laboratory populations of the rotifer Brachionus calyciflorus were cultured at different temperatures (25, 20, 15°C) but otherwise at constant conditions. The population densities showed relatively constant oscillations (Figs. 1 to 3A-C). Amplitudes and frequencies of the oscillations were positively correlated with temperature (Table 1). A test was made, whether the logistic growth function with simple time lag is able to describe the population curves. There are strong similarities between the simulations (Figs. 1-3E) and the real population dynamics if minor adjustments of the empirically determined parameters are made. There-fore it is suggested that time lags are responsible for the observed oscillations. However, the actual time lags probably do not act in the simple manner of the model, because birth and death rates react with different time lags, and both parameters are dependent on individual age and population density. A more complex model, which incorporates these modifications, should lead to a more realistic description of the observed oscillations.

Generalized viscothermoelasticity theory of dual-phase-lagging model for damping analysis in circular micro-plate resonators

NASA Astrophysics Data System (ADS)

Grover, D.; Seth, R. K.

2018-05-01

Analysis and numerical results are presented for the thermoelastic dissipation of a homogeneous isotropic, thermally conducting, Kelvin-Voigt type circular micro-plate based on Kirchhoff's Love plate theory utilizing generalized viscothermoelasticity theory of dual-phase-lagging model. The analytical expressions for thermoelastic damping of vibration and frequency shift are obtained for generalized dual-phase-lagging model and coupled viscothermoelastic plates. The scaled thermoelastic damping has been illustrated in case of circular plate and axisymmetric circular plate for fixed aspect ratio for clamped and simply supported boundary conditions. It is observed that the damping of vibrations significantly depend on time delay and mechanical relaxation times in addition to thermo-mechanical coupling in circular plate under resonance conditions and plate dimensions.

Accuracy of Reaction Cross Section for Exotic Nuclei in Glauber Model Based on MCMC Diagnostics

NASA Astrophysics Data System (ADS)

Rueter, Keiti; Novikov, Ivan

2017-01-01

Parameters of a nuclear density distribution for an exotic nuclei with halo or skin structures can be determined from the experimentally measured reaction cross-section. In the presented work, to extract parameters such as nuclear size information for a halo and core, we compare experimental data on reaction cross-sections with values obtained using expressions of the Glauber Model. These calculations are performed using a Markov Chain Monte Carlo algorithm. We discuss the accuracy of the Monte Carlo approach and its dependence on k*, the power law turnover point in the discreet power spectrum of the random number sequence and on the lag-1 autocorrelation time of the random number sequence.

Tapered US carbon emissions during good times: what's old, what's new?

PubMed

Eng, Yoke-Kee; Wong, Chin-Yoong

2017-11-01

In light of a slow buildup in CO 2 emissions since the recovery, this paper revisits the relationship between CO 2 emissions and the US economy using a nonlinear autoregressive distributed lag model, in which the determinants are identified through an expanded real business cycle model. We find convincing evidence that CO 2 emissions decline more rapidly during recessions than increase during expansions over the long run. Of all determinants considered, long-run asymmetry is fostered once vehicle miles traveled is controlled. This calls for a greater attention to public transportation development and vehicle miles traveled tax for slowing down stock buildup of CO 2 emissions during good times.

Catchment Legacies and Trajectories: Understanding Time Lags in Catchment Response as a Function of Hydrologic and Biogeochemical Controls

NASA Astrophysics Data System (ADS)

Basu, N. B.; Van Meter, K. J.

2012-12-01

Increased nutrient loads delivered from watersheds due to agricultural intensification, industrialization, and urbanization have contributed globally to the persistence of large hypoxic zones in inland and coastal waters. Watershed management practices targeting these non-point source pollutants often lead to little or no improvement in water quality, even after extensive implementation of conservation measures or Best Management Practices (BMPs). The lag time between implementation of a conservation measure and resultant water quality benefits has recently been recognized as an important factor in the "apparent" failure of these BMPs. When conservation measures are implemented without explicit consideration of the lag time and with expectations that they will lead to immediate benefits, the resulting failure to meet such expectations can discourage vital restoration efforts. It is therefore important to quantify the lag times associated with watershed management efforts a priori and to implement restoration strategies targeted specifically at minimizing lag times and maximizing restoration benefits. The focus of this research is to develop a framework for understanding the time lags between land-use changes and stream water quality benefits. We hypothesize that such time lags arise from nutrient legacies building over decades of fertilizer application. For nitrogen (N), one can conceptualize this as either hydrologic legacy, in the form of dissolved nitrate that is delayed due to slow groundwater transport, or as biogeochemical legacy, in the form of organic N, possibly in dissolved or readily mineralizable forms. Indeed, mass-balance studies across the Mississippi and Thames river basins indicate the possibility of missing N mass in these landscapes, with inputs being consistently greater than the outputs even when accounting for all possible pathways of nitrogen transformation. Historical soil data within the upper Mississippi River Basin (MRB) indicate that agriculture depletes organic N in surface soil, but leads to N accumulations deeper in the profile. Nitrogen accumulation estimates (approximately 2 million Mt/yr) based on the historical data are startlingly close to the deficit suggested by mass-balance studies of the MRB (3 million Mt/yr). Understanding the lag times associated with such biogeochemical legacies requires quantification of this accumulation as a function of landscape attributes, climate, and management controls, as well as the rate of mineralization of accumulated N after implementation of management practices. Understanding hydrologic legacy requires a partitioning of flow along various pathways (e.g., overland flow, tile flow, or groundwater pathways), and the distribution of travel times along the pathways. Based on this framework, we developed a coupled hydrologic and biogeochemical model to quantify these legacies and predict landscape recovery times as a function of natural and anthropogenic controls.

Modelling the work to be done by Escherichia coli to adapt to sudden temperature upshifts.

PubMed

Swinnen, I A M; Bernaerts, K; Van Impe, J F

2006-05-01

This paper studies and models the effect of the amplitude of a sudden temperature upshift DeltaT on the adaptation period of Escherichia coli, in terms of the work to be done by the cells during the subsequent lag phase (i.e., the product of growth rate mumax and lag phase duration lambda). Experimental data are obtained from bioreactor experiments with E. coli K12 MG1655. At a predetermined time instant during the exponential growth phase, a sudden temperature upshift is applied (no other environmental changes take place). The length of the (possibly) induced lag phase and the specific growth rate after the shift are quantified with the growth model of Baranyi and Roberts (Int J Food Microbiol 23, 1994, 277). Different models to describe the evolution of the product lambda x mumax as a function of the amplitude of the temperature shift are statistically compared. The evolution of lambda x mumax is influenced by the amplitude of the temperature shift DeltaT and by the normal physiological temperature range. As some cut-off is observed, the linear model with translation is preferred to describe this evolution. This work contributes to the characterization of microbial lag phenomena, in this case for E. coli K12 MG1655, in view of accurate predictive model building.

A Flight-Dynamic Helicopter Mathematical Model with a Single Flap-Lag- Torsion Main Rotor

DTIC Science & Technology

1990-02-01

allows several hinge sequences and two offsets in the hinges. Quasi-steady Greenberg theory is used to calculate the blade-section aerodynamic forces...steady Greenberg model is used (ref. 3), Unsteady inflow effects are included using the three-state nonlinear Pitt/Peters dynamic inflow model (ref. 4...sectional aerodynamic model is based on quasi-steady Greenberg theory, which is a Theodorsen theory modified to account for lead-lag motions (refs. 3,14). The

Calibration of a rainfall-runoff hydrological model and flood simulation using data assimilation

NASA Astrophysics Data System (ADS)

Piacentini, A.; Ricci, S. M.; Thual, O.; Coustau, M.; Marchandise, A.

2010-12-01

Rainfall-runoff models are crucial tools for long-term assessment of flash floods or real-time forecasting. This work focuses on the calibration of a distributed parsimonious event-based rainfall-runoff model using data assimilation. The model combines a SCS-derived runoff model and a Lag and Route routing model for each cell of a regular grid mesh. The SCS-derived runoff model is parametrized by the initial water deficit, the discharge coefficient for the soil reservoir and a lagged discharge coefficient. The Lag and Route routing model is parametrized by the velocity of travel and the lag parameter. These parameters are assumed to be constant for a given catchment except for the initial water deficit and the velocity travel that are event-dependent (landuse, soil type and moisture initial conditions). In the present work, a BLUE filtering technique was used to calibrate the initial water deficit and the velocity travel for each flood event assimilating the first available discharge measurements at the catchment outlet. The advantages of the BLUE algorithm are its low computational cost and its convenient implementation, especially in the context of the calibration of a reduced number of parameters. The assimilation algorithm was applied on two Mediterranean catchment areas of different size and dynamics: Gardon d'Anduze and Lez. The Lez catchment, of 114 km2 drainage area, is located upstream Montpellier. It is a karstic catchment mainly affected by floods in autumn during intense rainstorms with short Lag-times and high discharge peaks (up to 480 m3.s-1 in September 2005). The Gardon d'Anduze catchment, mostly granite and schistose, of 545 km2 drainage area, lies over the departements of Lozère and Gard. It is often affected by flash and devasting floods (up to 3000 m3.s-1 in September 2002). The discharge observations at the beginning of the flood event are assimilated so that the BLUE algorithm provides optimal values for the initial water deficit and the velocity travel before the flood peak. These optimal values are used for a new simulation of the event in forecast mode (under the assumption of perfect rain-fall). On both catchments, it was shown over a significant number of flood events, that the data assimilation procedure improves the flood peak forecast. The improvement is globally more important for the Gardon d'Anduze catchment where the flood events are stronger. The peak can be forecasted up to 36 hours head of time assimilating very few observations (up to 4) during the rise of the water level. For multiple peaks events, the assimilation of the observations from the first peak leads to a significant improvement of the second peak simulation. It was also shown that the flood rise is often faster in reality than it is represented by the model. In this case and when the flood peak is under estimated in the simulation, the use of the first observations can be misleading for the data assimilation algorithm. The careful estimation of the observation and background error variances enabled the satisfying use of the data assimilation in these complex cases even though it does not allow the model error correction.

Empirical evidence for multi-scaled controls on wildfire size distributions in California

NASA Astrophysics Data System (ADS)

Povak, N.; Hessburg, P. F., Sr.; Salter, R. B.

2014-12-01

Ecological theory asserts that regional wildfire size distributions are examples of self-organized critical (SOC) systems. Controls on SOC event-size distributions by virtue are purely endogenous to the system and include the (1) frequency and pattern of ignitions, (2) distribution and size of prior fires, and (3) lagged successional patterns after fires. However, recent work has shown that the largest wildfires often result from extreme climatic events, and that patterns of vegetation and topography may help constrain local fire spread, calling into question the SOC model's simplicity. Using an atlas of >12,000 California wildfires (1950-2012) and maximum likelihood estimation (MLE), we fit four different power-law models and broken-stick regressions to fire-size distributions across 16 Bailey's ecoregions. Comparisons among empirical fire size distributions across ecoregions indicated that most ecoregion's fire-size distributions were significantly different, suggesting that broad-scale top-down controls differed among ecoregions. One-parameter power-law models consistently fit a middle range of fire sizes (~100 to 10000 ha) across most ecoregions, but did not fit to larger and smaller fire sizes. We fit the same four power-law models to patch size distributions of aspect, slope, and curvature topographies and found that the power-law models fit to a similar middle range of topography patch sizes. These results suggested that empirical evidence may exist for topographic controls on fire sizes. To test this, we used neutral landscape modeling techniques to determine if observed fire edges corresponded with aspect breaks more often than expected by random. We found significant differences between the empirical and neutral models for some ecoregions, particularly within the middle range of fire sizes. Our results, combined with other recent work, suggest that controls on ecoregional fire size distributions are multi-scaled and likely are not purely SOC. California wildfire ecosystems appear to be adaptive, governed by stationary and non-stationary controls, which may be either exogenous or endogenous to the system.

Exposure and health impact evaluation based on simultaneous measurement of indoor and ambient PM2.5 in Haidian, Beijing.

PubMed

Qi, Meng; Zhu, Xi; Du, Wei; Chen, Yilin; Chen, Yuanchen; Huang, Tianbo; Pan, Xuelian; Zhong, Qirui; Sun, Xu; Zeng, Eddy Y; Xing, Baoshan; Tao, Shu

2017-01-01

Because people spend most of their time indoors, the characterization of indoor air quality is important for exposure assessment. Unfortunately, indoor air data are scarce, leading to a major data gap in risk assessment. In this study, PM 2.5 concentrations in both indoor and outdoor air were simultaneously measured using on-line particulate counters in 13 households in Haidian, Beijing for both heating and non-heating seasons. A bimodal distribution of PM 2.5 concentrations suggests rapid transitions between polluted and non-polluted situations. The PM 2.5 concentrations in indoor and outdoor air varied synchronously, with the indoor variation lagging. The lag time in the heating season was longer than that in the non-heating season. The particle sizes in indoor air were smaller than those in ambient air in the heating season and vice versa in the non-heating season. PM 2.5 concentrations in indoor air were generally lower than those in ambient air except when ambient concentrations dropped sharply to very low levels or there were internal emissions from cooking or other activities. The effectiveness of an air cleaner to reduce indoor PM 2.5 concentrations was demonstrated. Non-linear regression models were developed to predict indoor air PM 2.5 concentrations based on ambient data with lag time incorporated. The models were applied to estimate the overall population exposure to PM 2.5 and the health consequences in Haidian. The health impacts would be significantly overestimated without the indoor exposure being taken into consideration, and this bias would increase as the ambient air quality improved in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chimera and modulated drift states in a ring of nonlocally coupled oscillators with heterogeneous phase lags

NASA Astrophysics Data System (ADS)

Choe, Chol-Ung; Kim, Ryong-Son; Ri, Ji-Song

2017-09-01

We consider a ring of phase oscillators with nonlocal coupling strength and heterogeneous phase lags. We analyze the effects of heterogeneity in the phase lags on the existence and stability of a variety of steady states. A nonlocal coupling with heterogeneous phase lags that allows the system to be solved analytically is suggested and the stability of solutions along the Ott-Antonsen invariant manifold is explored. We present a complete bifurcation diagram for stationary patterns including the uniform drift and modulated drift states as well as chimera state, which reveals that the stable modulated drift state and a continuum of metastable drift states could occur due to the heterogeneity of the phase lags. We verify our theoretical results using the direct numerical simulations of the model system.

Granular resistive force theory explains the neuromechanical phase lag during sand-swimming

NASA Astrophysics Data System (ADS)

Ding, Yang; Sharpe, Sarah; Goldman, Daniel

2012-11-01

Undulatory locomotion is a common gait used by a diversity of animals in a range of environments. This mode of locomotion is characterized by the propagation of a traveling wave of body bending, which propels the animal in the opposite direction of the wave. Previous studies of undulatory locomotion in fluids, on land, and even within sand revealed that the wave of muscle activation progresses faster than the traveling wave of curvature. This leads to an increasing phase lag between activation and curvature at more posterior segments, known as the neuromechanical phase lag. In this study, we compare biological measurements of phase lag during the sand-swimming of the sandfish lizard to predictions of a simple model of undulatory swimming that consists of prescribed kinematics and granular resistive forces. The neuromechanical phase lag measured using electromyography (EMG) quantitatively matches the predicted phase lag between the local body curvature and torque exerted by granular resistive forces. Two effects are responsible for the phase lag in this system: the yaw motion of the body and different integration length over a traveling force pattern for different positions along the body.

Leading and lagging indicators of occupational health and safety: The moderating role of safety leadership.

PubMed

Sheehan, Cathy; Donohue, Ross; Shea, Tracey; Cooper, Brian; Cieri, Helen De

2016-07-01

In response to the call for empirical evidence of a connection between leading and lagging indicators of occupational health and safety (OHS), the first aim of the current research is to consider the association between leading and lagging indicators of OHS. Our second aim is to investigate the moderating effect of safety leadership on the association between leading and lagging indicators. Data were collected from 3578 employees nested within 66 workplaces. Multi-level modelling was used to test the two hypotheses. The results confirm an association between leading and lagging indicators of OHS as well as the moderating impact of middle management safety leadership on the direct association. The association between leading and lagging indicators provides OHS practitioners with useful information to substantiate efforts within organisations to move away from a traditional focus on lagging indicators towards a preventative focus on leading indicators. The research also highlights the important role played by middle managers and the value of OHS leadership development and investment at the middle management level. Copyright © 2016 Elsevier Ltd. All rights reserved.

Untangling the drivers of nonlinear systems with information theory

NASA Astrophysics Data System (ADS)

Wing, S.; Johnson, J.

2017-12-01

Many systems found in nature are nonlinear. The drivers of the system are often nonlinearly correlated with one another, which makes it a challenge to understand the effects of an individual driver. For example, solar wind velocity (Vsw) and density (nsw) are both found to correlate well with radiation belt fluxes and are thought to be drivers of the magnetospheric dynamics; however, the Vsw is anti-correlated with nsw, which can potentially confuse interpretation of these relationships as causal or coincidental. Information theory can untangle the drivers of these systems, describe the underlying dynamics, and offer constraints to modelers and theorists, leading to better understanding of the systems. Two examples are presented. In the first example, the solar wind drivers of geosynchronous electrons with energy range of 1.8-3.5 MeV are investigated using mutual information (MI), conditional mutual information (CMI), and transfer entropy (TE). The information transfer from Vsw to geosynchronous MeV electron flux (Je) peaks with a lag time (t) of 2 days. As previously reported, Je is anticorrelated with nsw with a lag of 1 day. However, this lag time and anticorrelation can be attributed mainly to the Je(t + 2 days) correlation with Vsw(t) and nsw(t + 1 day) anticorrelation with Vsw(t). Analyses of solar wind driving of the magnetosphere need to consider the large lag times, up to 3 days, in the (Vsw, nsw) anticorrelation. Using CMI to remove the effects of Vsw, the response of Je to nsw is 30% smaller and has a lag time < 24 hr, suggesting that the loss mechanism due to nsw or solar wind dynamic pressure has to start operating in < 24 hr. nsw transfers about 36% as much information as Vsw (the primary driver) to Je. Nonstationarity in the system dynamics are investigated using windowed TE. When the data is ordered according to high or low transfer entropy it is possible to understand details of the triangle distribution that has been identified between Je(t + 2 days) vs. Vsw(t). In the second example, the previously identified causal parameters of the solar cycle such as the solar polar field, meridional flow, polar faculae (proxy for polar field), dipole axis strength, are investigated. We discuss the response lag times of the sunspot numbers and information transferred to the sunspot numbers from the dynamic time series of these parameters.

Stochastic Car-Following Model for Explaining Nonlinear Traffic Phenomena

NASA Astrophysics Data System (ADS)

Meng, Jianping; Song, Tao; Dong, Liyun; Dai, Shiqiang

There is a common time parameter for representing the sensitivity or the lag (response) time of drivers in many car-following models. In the viewpoint of traffic psychology, this parameter could be considered as the perception-response time (PRT). Generally, this parameter is set to be a constant in previous models. However, PRT is actually not a constant but a random variable described by the lognormal distribution. Thus the probability can be naturally introduced into car-following models by recovering the probability of PRT. For demonstrating this idea, a specific stochastic model is constructed based on the optimal velocity model. By conducting simulations under periodic boundary conditions, it is found that some important traffic phenomena, such as the hysteresis and phantom traffic jams phenomena, can be reproduced more realistically. Especially, an interesting experimental feature of traffic jams, i.e., two moving jams propagating in parallel with constant speed stably and sustainably, is successfully captured by the present model.

A Falling Corona Model for the Anomalous Behavior of the Broad Emission Lines in NGC 5548

NASA Astrophysics Data System (ADS)

Sun, Mouyuan; Xue, Yongquan; Cai, Zhenyi; Guo, Hengxiao

2018-04-01

NGC 5548 has been intensively monitored by the AGN Space Telescope and Optical Reverberation Mapping collaboration. Approximately after half of the light curves, the correlation between the broad emission lines and the lag-corrected ultraviolet (UV) continua becomes weak. This anomalous behavior is accompanied by an increase of soft X-ray emission. We propose a simple model to understand this anomalous behavior, i.e., the corona might fall down, thereby increasing the covering fraction of the inner disk. Therefore, X-ray and extreme-UV emission suffer from spectral variations. The UV continua variations are driven by both X-ray and extreme-UV variations. Consequently, the spectral variability induced by the falling corona would dilute the correlation between the broad emission lines and the UV continua. Our model can explain many additional observational facts, including the dependence of the anomalous behavior on velocity and ionization energy. We also show that the time lag and correlation between the X-ray and the UV variations change as NGC 5548 displays the anomalous behavior. The time lag is dramatically longer than the expectation from disk reprocessing if the anomalous behavior is properly excluded. During the anomalous state, the time lag approaches the light-travel timescale of disk reprocessing albeit with a much weaker correlation. We speculate that the time lag in the normal state is caused by reprocessing of the broad line region gas. As NGC 5548 enters the abnormal state, the contribution of the broad line region gas is smaller; the time lag reflects disk reprocessing. We also discuss alternative scenarios.

The effect of viscoelasticity on the stress distribution of adhesively single-lap joint with an internal break in the composite adherends

NASA Astrophysics Data System (ADS)

Reza, Arash; Shishesaz, Mohammad

2017-09-01

The aim of this research is to study the effect of a break in the laminated composite adherends on stress distribution in the adhesively single-lap joint with viscoelastic adhesive and matrix. The proposed model involves two adherends with E-glass fibers and poly-methyl-methacrylate matrix that have been adhered to each other by phenolic-epoxy resin. The equilibrium equations that are based on shear-lag theory have been derived in the Laplace domain, and the governing differential equations of the model have been derived analytically in the Laplace domain. A numerical inverse Laplace transform, which is called Gaver-Stehfest method, has been used to extract desired results in the time domain. The results obtained at the initial time completely matched with the results of elastic solution. Also, a comparison between results obtained from the analytical and finite element models show a relatively good match. The results show that viscoelastic behavior decreases the peak of stress near the break. Finally, the effect of size and location of the break, as well as volume fraction of fibers, on the stress distribution in the adhesive layer is fully investigated.

Investigating Disk-halo Flows and Accretion: A Kinematic and Morphological Analysis of Extraplanar H I in NGC 3044 and NGC 4302

NASA Astrophysics Data System (ADS)

Zschaechner, Laura K.; Rand, Richard J.; Walterbos, Rene

2015-01-01

To further understand the origins of and physical processes operating in extra-planar gas, we present observations and kinematic models of H I in the two nearby, edge-on spiral galaxies NGC 3044 and NGC 4302. We model NGC 3044 as a single, thick disk. Substantial amounts of extra-planar H I are also detected. We detect a decrease in rotation speed with height (a lag) that shallows radially, reaching zero at approximately R 25. The large-scale kinematic asymmetry of the approaching and receding halves suggests a recent disturbance. The kinematics and morphology of NGC 4302, a Virgo Cluster member, are greatly disturbed. We model NGC 4302 as a combination of a thin disk and a second, thicker disk, the latter having a hole near the center. We detect lagging extra-planar gas, with indications of shallowing in the receding half, although its characteristics are difficult to constrain. A bridge is detected between NGC 4302 and its companion, NGC 4298. We explore trends involving the extra-planar H I kinematics of these galaxies, as well as galaxies throughout the literature, as well as possible connections between lag properties with star formation and environment. Measured lags are found to be significantly steeper than those modeled by purely ballistic effects, indicating additional factors. Radial shallowing of extra-planar lags is typical and occurs between 0.5R 25 and R 25, suggesting internal processes are important in dictating extra-planar kinematics.

A cross-lagged model of the reciprocal associations of loneliness and memory functioning.

PubMed

Ayalon, Liat; Shiovitz-Ezra, Sharon; Roziner, Ilan

2016-05-01

The study was designed to evaluate the reciprocal associations of loneliness and memory functioning using a cross-lagged model. The study was based on the psychosocial questionnaire of the Health and Retirement Study, which is a U.S. nationally representative survey of individuals over the age of 50 and their spouses of any age. A total of 1,225 respondents had complete data on the loneliness measure in 2004 and at least in 1 of the subsequent waves (e.g., 2008, 2012) and were maintained for analysis. A cross-lagged model was estimated to examine the reciprocal associations of loneliness and memory functioning, controlling for age, gender, education, depressive symptoms, number of medical conditions, and the number of close social relationships. The model had adequate fit indices: χ2(860, N = 1,225) = 1,401.54, p < .001, Tucker-Lewis index = .957, comparative fit index = .963, and root mean square error of approximation = .023 (90% confidence interval [.021, .025]). The lagged effect of loneliness on memory functioning was nonsignificant, B(SE) = -.11(.08), p = .15, whereas the lagged effect of memory functioning on loneliness was significant, B(SE) = -.06(.02), p = .01, indicating that lower levels of memory functioning precede higher levels of loneliness 4 years afterward. Further research is required to better understand the mechanisms responsible for the temporal association between reduced memory functioning and increased loneliness. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Ambient temperature and coronary heart disease mortality in Beijing, China: a time series study

PubMed Central

2012-01-01

Background Many studies have examined the association between ambient temperature and mortality. However, less evidence is available on the temperature effects on coronary heart disease (CHD) mortality, especially in China. In this study, we examined the relationship between ambient temperature and CHD mortality in Beijing, China during 2000 to 2011. In addition, we compared time series and time-stratified case-crossover models for the non-linear effects of temperature. Methods We examined the effects of temperature on CHD mortality using both time series and time-stratified case-crossover models. We also assessed the effects of temperature on CHD mortality by subgroups: gender (female and male) and age (age > =65 and age < 65). We used a distributed lag non-linear model to examine the non-linear effects of temperature on CHD mortality up to 15 lag days. We used Akaike information criterion to assess the model fit for the two designs. Results The time series models had a better model fit than time-stratified case-crossover models. Both designs showed that the relationships between temperature and group-specific CHD mortality were non-linear. Extreme cold and hot temperatures significantly increased the risk of CHD mortality. Hot effects were acute and short-term, while cold effects were delayed by two days and lasted for five days. The old people and women were more sensitive to extreme cold and hot temperatures than young and men. Conclusions This study suggests that time series models performed better than time-stratified case-crossover models according to the model fit, even though they produced similar non-linear effects of temperature on CHD mortality. In addition, our findings indicate that extreme cold and hot temperatures increase the risk of CHD mortality in Beijing, China, particularly for women and old people. PMID:22909034

The Impact of Ambient Air Pollution on Daily Hospital Visits for Various Respiratory Diseases and the Relevant Medical Expenditures in Shanghai, China.

PubMed

Zhang, Hao; Niu, Yue; Yao, Yili; Chen, Renjie; Zhou, Xianghong; Kan, Haidong

2018-02-28

The evidence concerning the acute effects of ambient air pollution on various respiratory diseases was limited in China, and the attributable medical expenditures were largely unknown. From 2013 to 2015, we collected data on the daily visits to the emergency- and outpatient-department for five main respiratory diseases and their medical expenditures in Shanghai, China. We used the overdispersed generalized additive model together with distributed lag models to fit the associations of criteria air pollutants with hospital visits, and used the linear models to fit the associations with medical expenditures. Generally, we observed significant increments in emergency visits (8.81-17.26%) and corresponding expenditures (0.33-25.81%) for pediatric respiratory diseases, upper respiratory infection (URI), and chronic obstructive pulmonary disease (COPD) for an interquartile range increase of air pollutant concentrations over four lag days. As a comparison, there were significant but smaller increments in outpatient visits (1.36-4.52%) and expenditures (1.38-3.18%) for pediatric respiratory diseases and upper respiratory infection (URI). No meaningful changes were observed for asthma and lower respiratory infection. Our study suggested that short-term exposure to outdoor air pollution may induce the occurrences or exacerbation of pediatric respiratory diseases, URI, and COPD, leading to considerable medical expenditures upon the patients.

Testing the Causal Links between School Climate, School Violence, and School Academic Performance: A Cross-Lagged Panel Autoregressive Model

ERIC Educational Resources Information Center

Benbenishty, Rami; Astor, Ron Avi; Roziner, Ilan; Wrabel, Stephani L.

2016-01-01

The present study explores the causal link between school climate, school violence, and a school's general academic performance over time using a school-level, cross-lagged panel autoregressive modeling design. We hypothesized that reductions in school violence and climate improvement would lead to schools' overall improved academic performance.…

Reciprocal Effects between Intrinsic Reading Motivation and Reading Competence? A Cross-Lagged Panel Model for Academic Track and Nonacademic Track Students

ERIC Educational Resources Information Center

Schaffner, Ellen; Philipp, Maik; Schiefele, Ulrich

2016-01-01

Previous research has demonstrated positive relations between intrinsic reading motivation and reading competence. However, the causal direction of these relations and the moderating role of relevant background variables (e.g., students' achievement level) are not well understood. In the present study, a cross-lagged panel model was applied to…

Dynamic Relationship between Gross Domestic Product and Domestic Investment in Rwanda

ERIC Educational Resources Information Center

Ocaya, Bruno; Ruranga, Charles; Kaberuka, William

2012-01-01

This study uses a VAR model to analyse the dynamic relationship between gross domestic product (GDP) and domestic investment (DI) in Rwanda for the period 1970 to 2011. Several selection lag criteria chose a maximum lag of one, and a bivariate VAR(1) model specification in levels was adopted. Unit root tests show that both GDP and DI series are…

Using Baidu Search Index to Predict Dengue Outbreak in China

NASA Astrophysics Data System (ADS)

Liu, Kangkang; Wang, Tao; Yang, Zhicong; Huang, Xiaodong; Milinovich, Gabriel J.; Lu, Yi; Jing, Qinlong; Xia, Yao; Zhao, Zhengyang; Yang, Yang; Tong, Shilu; Hu, Wenbiao; Lu, Jiahai

2016-12-01

This study identified the possible threshold to predict dengue fever (DF) outbreaks using Baidu Search Index (BSI). Time-series classification and regression tree models based on BSI were used to develop a predictive model for DF outbreak in Guangzhou and Zhongshan, China. In the regression tree models, the mean autochthonous DF incidence rate increased approximately 30-fold in Guangzhou when the weekly BSI for DF at the lagged moving average of 1-3 weeks was more than 382. When the weekly BSI for DF at the lagged moving average of 1-5 weeks was more than 91.8, there was approximately 9-fold increase of the mean autochthonous DF incidence rate in Zhongshan. In the classification tree models, the results showed that when the weekly BSI for DF at the lagged moving average of 1-3 weeks was more than 99.3, there was 89.28% chance of DF outbreak in Guangzhou, while, in Zhongshan, when the weekly BSI for DF at the lagged moving average of 1-5 weeks was more than 68.1, the chance of DF outbreak rose up to 100%. The study indicated that less cost internet-based surveillance systems can be the valuable complement to traditional DF surveillance in China.

Time-lag of the earthquake energy release between three seismic regions

NASA Astrophysics Data System (ADS)

Tsapanos, Theodoros M.; Liritzis, Ioannis

1992-06-01

Three complete data sets of strong earthquakes ( M≥5.5), which occurred in the seismic regions of Chile, Mexico and Kamchatka during the time period 1899 1985, have been used to test the existence of a time-lag in the seismic energy release between these regions. These data sets were cross-correlated in order to determine whether any pair of the sets are correlated. For this purpose statistical tests, such as the T-test, the Fisher's transformation and probability distribution have been applied to determine the significance of the obtained correlation coefficients. The results show that the time-lag between Chile and Kamchatka is -2, which means that Kamchatka precedes Chile by 2 years, with a correlation coefficient significant at 99.80% level, a weak correlation between Kamchatka-Mexico and noncorrelation for Mexico-Chile.

Short-term effects of fine particulate air pollution on cardiovascular hospital emergency room visits: a time-series study in Beijing, China.

PubMed

Su, Chang; Breitner, Susanne; Schneider, Alexandra; Liu, Liqun; Franck, Ulrich; Peters, Annette; Pan, Xiaochuan

2016-05-01

The link between particulate matter (PM) and cardiovascular morbidity has been investigated in numerous studies. Less evidence exists, however, about how age, gender and season may modify this relationship. The aim of this study was to evaluate the association between ambient PM2.5 (PM ≤ 2.5 µm) and daily hospital emergency room visits (ERV) for cardiovascular diseases in Beijing, China. Moreover, potential effect modification by age, gender, season, air mass origin and the specific period with 2008 Beijing Olympic were investigated. Finally, the temporal lag structure of PM2.5 has also been explored. Daily counts of cardiovascular ERV were obtained from the Peking University Third Hospital from January 2007 to December 2008. Concurrently, data on PM2.5, PM10 (PM ≤ 10 µm), nitrogen dioxide and sulfur dioxide concentrations were obtained from monitoring networks and a fixed monitoring station. Poisson regression models adjusting for confounders were used to estimate immediate, delayed and cumulative air pollution effects. The temporal lag structure was also estimated using polynomial distributed lag (PDL) models. We calculated the relative risk (RR) for overall cardiovascular disease ERV as well as for specific causes of disease; and also investigated the potential modifying effect of age, gender, season, air mass origin and the period with 2008 Beijing Olympics. We observed adverse effects of PM2.5 on cardiovascular ERV--an IQR increase (68 μg/m(3)) in PM2.5 was associated with an overall RR of 1.022 (95% CI 0.990-1.057) obtained from PDL model. Strongest effects of PM2.5 on cardiovascular ERV were found for a lag of 7 days; the respective estimate was 1.012 (95% CI 1.002-1.022). The effects were more pronounced in females and in spring. Arrhythmia and cerebrovascular diseases showed a stronger association with PM2.5. We also found stronger PM-effects for stagnant and southern air masses and the period of Olympics modified the air pollution effects. We observed a rather delayed effect of PM2.5 on cardiovascular ERV, which was modified by gender and season. Our findings provide new evidence about effect modifications and may have implications to improve policy making for particulate air pollution standards in Beijing, China.

The economic impact of NASA R and D spending Appendices

NASA Technical Reports Server (NTRS)

Evans, M. K.

1976-01-01

Seven appendices related to a previous report on the economic impact of NASA R and D spending were presented. They dealt with: (1) theoretical and empirical development of aggregate production functions, (2) the calculation of the time series for the rate of technological progress, (3) the calculation of the industry mix variable, (4) the estimation of distributed lags, (5) the estimation of the equations for gamma, (6) a ten-year forecast of the U.S. economy, (7) simulations of the macroeconomic model for increases in NASA R and D spending of $1.0, $.0.5, and 0.1 billions.

Time-varying mixed logit model for vehicle merging behavior in work zone merging areas.

PubMed

Weng, Jinxian; Du, Gang; Li, Dan; Yu, Yao

2018-08-01

This study aims to develop a time-varying mixed logit model for the vehicle merging behavior in work zone merging areas during the merging implementation period from the time of starting a merging maneuver to that of completing the maneuver. From the safety perspective, vehicle crash probability and severity between the merging vehicle and its surrounding vehicles are regarded as major factors influencing vehicle merging decisions. Model results show that the model with the use of vehicle crash risk probability and severity could provide higher prediction accuracy than previous models with the use of vehicle speeds and gap sizes. It is found that lead vehicle type, through lead vehicle type, through lag vehicle type, crash probability of the merging vehicle with respect to the through lag vehicle, crash severities of the merging vehicle with respect to the through lead and lag vehicles could exhibit time-varying effects on the merging behavior. One important finding is that the merging vehicle could become more and more aggressive in order to complete the merging maneuver as quickly as possible over the elapsed time, even if it has high vehicle crash risk with respect to the through lead and lag vehicles. Copyright © 2018 Elsevier Ltd. All rights reserved.

Single molecular biology: coming of age in DNA replication.

PubMed

Liu, Xiao-Jing; Lou, Hui-Qiang

2017-09-20

DNA replication is an essential process of the living organisms. To achieve precise and reliable replication, DNA polymerases play a central role in DNA synthesis. Previous investigations have shown that the average rates of DNA synthesis on the leading and lagging strands in a replisome must be similar to avoid the formation of significant gaps in the nascent strands. The underlying mechanism has been assumed to be coordination between leading- and lagging-strand polymerases. However, Kowalczykowski's lab members recently performed single molecule techniques in E. coli and showed the real-time behavior of a replisome. The leading- and lagging-strand polymerases function stochastically and independently. Furthermore, when a DNA polymerase is paused, the helicase slows down in a self-regulating fail-safe mechanism, akin to a ''dead-man's switch''. Based on the real-time single-molecular observation, the authors propose that leading- and lagging-strand polymerases synthesize DNA stochastically within a Gaussian distribution. Along with the development and application of single-molecule techniques, we will witness a new age of DNA replication and other biological researches.

Numerical investigation of thermal response of laser-irradiated biological tissue phantoms embedded with gold nanoshells.

PubMed

Phadnis, Akshay; Kumar, Sumit; Srivastava, Atul

2016-10-01

The work presented in this paper focuses on numerically investigating the thermal response of gold nanoshells-embedded biological tissue phantoms with potential applications into photo-thermal therapy wherein the interest is in destroying the cancerous cells with minimum damage to the surrounding healthy cells. The tissue phantom has been irradiated with a pico-second laser. Radiative transfer equation (RTE) has been employed to model the light-tissue interaction using discrete ordinate method (DOM). For determining the temperature distribution inside the tissue phantom, the RTE has been solved in combination with a generalized non-Fourier heat conduction model namely the dual phase lag bio-heat transfer model. The numerical code comprising the coupled RTE-bio-heat transfer equation, developed as a part of the current work, has been benchmarked against the experimental as well as the numerical results available in the literature. It has been demonstrated that the temperature of the optical inhomogeneity inside the biological tissue phantom embedded with gold nanoshells is relatively higher than that of the baseline case (no nanoshells) for the same laser power and operation time. The study clearly underlines the impact of nanoshell concentration and its size on the thermal response of the biological tissue sample. The comparative study concerned with the size and concentration of nanoshells showed that 60nm nanoshells with concentration of 5×10 15 mm -3 result into the temperature levels that are optimum for the irreversible destruction of cancer infected cells in the context of photo-thermal therapy. To the best of the knowledge of the authors, the present study is one of the first attempts to quantify the influence of gold nanoshells on the temperature distributions inside the biological tissue phantoms upon laser irradiation using the dual phase lag heat conduction model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Inferring hydraulic properties of alpine aquifers from the propagation of diurnal snowmelt signals

NASA Astrophysics Data System (ADS)

Kurylyk, Barret L.; Hayashi, Masaki

2017-05-01

Alpine watersheds source major rivers throughout the world and supply essential water for irrigation, human consumption, and hydroelectricity. Coarse depositional units in alpine watersheds can store and transmit significant volumes of groundwater and thus augment stream discharge during the dry season. These environments are typically data scarce, which has limited the application of physically based models to investigate hydrologic sensitivity to environmental change. This study focuses on a coarse alpine talus unit within the Lake O'Hara watershed in the Canadian Rockies. We investigate processes controlling the hydrologic functioning of the talus unit using field observations and a numerical groundwater flow model driven with a distributed snowmelt model. The model hydraulic parameters are adjusted to investigate how these properties influence the propagation of snowmelt-induced diurnal signals. The model results expectedly demonstrate that diurnal signals at the talus outlet are progressively damped and lagged with lower hydraulic conductivity and higher specific yield. The simulations further indicate that the lag can be primarily controlled by a higher hydraulic conductivity upper layer, whereas the damping can be strongly influenced by a lower hydraulic conductivity layer along the base of the talus. The simulations specifically suggest that the talus slope can be represented as a two layer system with a high conductivity zone (0.02 m s-1) overlying a 10 cm thick lower conductivity zone (0.002 m s-1). This study demonstrates that diurnal signals can be used to elucidate the hydrologic functioning and hydraulic properties of shallow aquifers and thus aid in the parameterization of hydrological models.

Diverse Responses of Global Vegetation to Climate Changes: Spatial Patterns and Time-lag Effects

NASA Astrophysics Data System (ADS)

Wu, D.; Zhao, X.; Zhou, T.; Huang, K.; Xu, W.

2014-12-01

Global climate changes have enormous influences on vegetation growth, meanwhile, response of vegetation to climate express space diversity and time-lag effects, which account for spatial-temporal disparities of climate change and spatial heterogeneity of ecosystem. Revelation of this phenomenon will help us further understanding the impact of climate change on vegetation. Assessment and forecast of global environmental change can be also improved under further climate change. Here we present space diversity and time-lag effects patterns of global vegetation respond to three climate factors (temperature, precipitation and solar radiation) based on quantitative analysis of satellite data (NDVI) and Climate data (Climate Research Unit). We assessed the time-lag effects of global vegetation to main climate factors based on the great correlation fitness between NDVI and the three climate factors respectively among 0-12 months' temporal lags. On this basis, integrated response model of NDVI and the three climate factors was built to analyze contribution of different climate factors to vegetation growth with multiple regression model and partial correlation model. In the result, different vegetation types have distinct temporal lags to the three climate factors. For the precipitation, temporal lags of grasslands are the shortest while the evergreen broad-leaf forests are the longest, which means that grasslands are more sensitive to precipitation than evergreen broad-leaf forests. Analysis of different climate factors' contribution to vegetation reveal that vegetation are dominated by temperature in the high northern latitudes; they are mainly restricted by precipitation in arid and semi-arid areas (Australia, Western America); in humid areas of low and intermediate latitudes (Amazon, Eastern America), vegetation are mainly influenced by solar radiation. Our results reveal the time-lag effects and major driving factors of global vegetation growth and explain the spatiotemporal variations of global vegetation in last 30 years. Significantly, it is as well as in forecasting and assessing the influences of future climate change on the vegetation dynamics. This work was supported by the High Technology Research and Development Program of China (Grant NO.2013AA122801).

Fungal mycelia show lag time before re-growth on endogenous carbon.

PubMed

Pollack, Judith K; Li, Zheng Jian; Marten, Mark R

2008-06-15

Nutrient starvation is a common occurrence for filamentous fungi. To better understand the effects of starvation, we used a parallel plate flow chamber to study individual fungal mycelia when subjected to a step change in glucose concentration. We report the presence of a finite "lag time" in starved mycelia during which they ceased to grow/extend while switching from growth on exogenous carbon to re-growth on endogenous carbon. This lag time precedes other morphological or physiological changes such as change in growth rate (50-70% reduction), vacuolation (up to 16%), and decreased hyphal diameter (almost 50% reduction). Data suggests that during lag time, vacuolar degradation produces sufficient endogenous carbon to support survival and restart hyphal extension. Lag time is inversely related to the size of the mycelium at the time of starvation, which suggests a critical flow of endogenous carbon to the apical tip. We present a mathematical model consistent with our experimental observations that relate lag time, area, and flow of endogenous carbon. (c) 2008 Wiley Periodicals, Inc.

Is a matrix exponential specification suitable for the modeling of spatial correlation structures?

PubMed Central

Strauß, Magdalena E.; Mezzetti, Maura; Leorato, Samantha

2018-01-01

This paper investigates the adequacy of the matrix exponential spatial specifications (MESS) as an alternative to the widely used spatial autoregressive models (SAR). To provide as complete a picture as possible, we extend the analysis to all the main spatial models governed by matrix exponentials comparing them with their spatial autoregressive counterparts. We propose a new implementation of Bayesian parameter estimation for the MESS model with vague prior distributions, which is shown to be precise and computationally efficient. Our implementations also account for spatially lagged regressors. We further allow for location-specific heterogeneity, which we model by including spatial splines. We conclude by comparing the performances of the different model specifications in applications to a real data set and by running simulations. Both the applications and the simulations suggest that the spatial splines are a flexible and efficient way to account for spatial heterogeneities governed by unknown mechanisms. PMID:29492375

Torque coordinating robust control of shifting process for dry dual clutch transmission equipped in a hybrid car

NASA Astrophysics Data System (ADS)

Zhao, Z.-G.; Chen, H.-J.; Yang, Y.-Y.; He, L.

2015-09-01

For a hybrid car equipped with dual clutch transmission (DCT), the coordination control problems of clutches and power sources are investigated while taking full advantage of the integrated starter generator motor's fast response speed and high accuracy (speed and torque). First, a dynamic model of the shifting process is established, the vehicle acceleration is quantified according to the intentions of the driver, and the torque transmitted by clutches is calculated based on the designed disengaging principle during the torque phase. Next, a robust H∞ controller is designed to ensure speed synchronisation despite the existence of model uncertainties, measurement noise, and engine torque lag. The engine torque lag and measurement noise are used as external disturbances to initially modify the output torque of the power source. Additionally, during the torque switch phase, the torque of the power sources is smoothly transitioned to the driver's demanded torque. Finally, the torque of the power sources is further distributed based on the optimisation of system efficiency, and the throttle opening of the engine is constrained to avoid sharp torque variations. The simulation results verify that the proposed control strategies effectively address the problem of coordinating control of clutches and power sources, establishing a foundation for the application of DCT in hybrid cars.

Effects of removal of different chemical components on moisture sorption property of Populus euramericana Cv. under dynamic hygrothermal conditions

NASA Astrophysics Data System (ADS)

Yang, Tiantian; Zhou, Haizhen; Ma, Erni; Wang, Jiamin

2018-09-01

Effects of chemical components on wood sorption property under dynamic condition were investigated for the first time. Hemicellulose, lignin and extractive (denoted as DHC, DL and DE, respectively) were removed from Populus euramericana Cv., 20 mm in radial (R) and tangential (T) directions with thickness of 4 mm along the grain, then the wood was subjected to cyclic tests where relative humidity (RH) varied from 45% to 75% sinusoidally at 25 °C. Based on measured data automatically, the results showed that, various chemical components had different effects on dynamic sorption behaviors of wood. The DL exhibited the largest moisture content and diffusion coefficient, followed by the DE, Control and DHC. This indicated lignin or extractive removal accelerated the dynamic sorption process and improved hygroscopicity of wood, while hemicellulose removal caused opposite effects. Theoretical sorption model was further applied and the modeled curves fitted satisfactorily with experimental data. Dynamic moisture gradient distribution inside the different treated wood was investigated and amplitude of moisture showed negative relation with wood element depth, while phase lag presented an opposite trend. Amplitude of DL was the largest while its phase lag was the least. Conditioning thickness for RH was greatest for DHC, about twice as much as the minimum of DL.

Work gets unfair for the depressed: cross-lagged relations between organizational justice perceptions and depressive symptoms.

PubMed

Lang, Jessica; Bliese, Paul D; Lang, Jonas W B; Adler, Amy B

2011-05-01

The organizational justice literature has consistently documented substantial correlations between organizational justice and employee depression. Existing theoretical literature suggests this relationship occurs because perceptions of organizational (in)justice lead to subsequent psychological health problems. Building on recent research on the affective nature of justice perceptions, in the present research we broaden this perspective by arguing there are also theoretical arguments for a reverse effect whereby psychological health problems influence perceptions of organizational justice. To contrast both theoretical perspectives, we test longitudinal lagged effects between organizational justice perceptions (i.e., distributive justice, interactional justice, interpersonal justice, informational justice, and procedural justice) and employee depressive symptoms using structural equation modeling. Analyses of 3 samples from different military contexts (N₁ = 625, N₂ = 134, N₃ = 550) revealed evidence of depressive symptoms leading to subsequent organizational justice perceptions. In contrast, the opposite effects of organizational justice perceptions on depressive symptoms were not significant for any of the justice dimensions. The findings have broad implications for theoretical perspectives on psychological health and organizational justice perceptions.

TESTING THE PROPAGATING FLUCTUATIONS MODEL WITH A LONG, GLOBAL ACCRETION DISK SIMULATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogg, J Drew; Reynolds, Christopher S.

2016-07-20

The broadband variability of many accreting systems displays characteristic structures; log-normal flux distributions, root-mean square (rms)-flux relations, and long inter-band lags. These characteristics are usually interpreted as inward propagating fluctuations of the mass accretion rate in an accretion disk driven by stochasticity of the angular momentum transport mechanism. We present the first analysis of propagating fluctuations in a long-duration, high-resolution, global three-dimensional magnetohydrodynamic (MHD) simulation of a geometrically thin ( h / r ≈ 0.1) accretion disk around a black hole. While the dynamical-timescale turbulent fluctuations in the Maxwell stresses are too rapid to drive radially coherent fluctuations in themore » accretion rate, we find that the low-frequency quasi-periodic dynamo action introduces low-frequency fluctuations in the Maxwell stresses, which then drive the propagating fluctuations. Examining both the mass accretion rate and emission proxies, we recover log-normality, linear rms-flux relations, and radial coherence that would produce inter-band lags. Hence, we successfully relate and connect the phenomenology of propagating fluctuations to modern MHD accretion disk theory.« less

Investigating critical effects of variegated lubricants, glidants and hydrophilic additives on lag time of press coated ethylcellulose tablets.

PubMed

Patadia, Riddhish; Vora, Chintan; Mittal, Karan; Mashru, Rajashree

2016-01-01

The research envisaged focuses on vital impacts of variegated lubricants, glidants and hydrophilic additives on lag time of press coated ethylcellulose (EC) tablets using prednisone as a model drug. Several lubricants and glidants such as magnesium stearate, colloidal SiO2, sodium stearyl fumarate, talc, stearic acid, polyethylene glycol (6000) and glyceryl behenate were investigated to understand their effects on lag time by changing their concentrations in outer coat. Further, the effects of hydrophilic additives on lag time were examined for hydroxypropylmethylcellulose (E5), hydroxypropylcellulose (EF and SSL), povidone (K30), copovidone, polyethylene glycol (4000), lactose and mannitol. In vitro drug release testing revealed that each selected lubricant/glidant, if present even at concentration of 0.25% w/w, significantly reduced the lag time of press coated tablets. Specifically, colloidal SiO2 and/or magnesium stearate were detrimental while other lubricants/glidants were relatively less injurious. Among hydrophilic additives, freely water soluble fillers had utmost influence in lag time, whereas, comparatively less impact was observed with polymeric binders. Concisely, glidant and lubricant should be chosen to have minimal impact on lag time and further judicious selection of hydrophilic additives should be exercised for modulating lag time of pulsatile release formulations.

Time-dependent oral absorption models

NASA Technical Reports Server (NTRS)

Higaki, K.; Yamashita, S.; Amidon, G. L.

2001-01-01

The plasma concentration-time profiles following oral administration of drugs are often irregular and cannot be interpreted easily with conventional models based on first- or zero-order absorption kinetics and lag time. Six new models were developed using a time-dependent absorption rate coefficient, ka(t), wherein the time dependency was varied to account for the dynamic processes such as changes in fluid absorption or secretion, in absorption surface area, and in motility with time, in the gastrointestinal tract. In the present study, the plasma concentration profiles of propranolol obtained in human subjects following oral dosing were analyzed using the newly derived models based on mass balance and compared with the conventional models. Nonlinear regression analysis indicated that the conventional compartment model including lag time (CLAG model) could not predict the rapid initial increase in plasma concentration after dosing and the predicted Cmax values were much lower than that observed. On the other hand, all models with the time-dependent absorption rate coefficient, ka(t), were superior to the CLAG model in predicting plasma concentration profiles. Based on Akaike's Information Criterion (AIC), the fluid absorption model without lag time (FA model) exhibited the best overall fit to the data. The two-phase model including lag time, TPLAG model was also found to be a good model judging from the values of sum of squares. This model also described the irregular profiles of plasma concentration with time and frequently predicted Cmax values satisfactorily. A comparison of the absorption rate profiles also suggested that the TPLAG model is better at prediction of irregular absorption kinetics than the FA model. In conclusion, the incorporation of a time-dependent absorption rate coefficient ka(t) allows the prediction of nonlinear absorption characteristics in a more reliable manner.

An out of phase coupling between the atmosphere and the ocean over the North Atlantic Ocean

NASA Astrophysics Data System (ADS)

Ribera, Pedro; Ordoñez, Paulina; Gallego, David; Peña-Ortiz, Cristina

2017-04-01

An oscillation band, with a period ranging between 40 and 60 years, has been identified as the most intense signal over the North Atlantic Ocean using several oceanic and atmospheric reanalyses between 1856 and the present. This signal represents the Atlantic Multidecadal Oscillation, an oscillation between warmer and colder than normal conditions in SST. Simultaneously, those changes in SST are accompanied by changes in atmospheric conditions represented by surface pressure, temperature and circulation. In fact, the evolution of the surface pressure pattern along this oscillation shows a North Atlantic Oscillation-like pattern, suggesting the existence of an out of phase coupling between atmospheric and oceanic conditions. Further analysis shows that the evolution of the oceanic SST distribution modifies atmospheric baroclinic conditions in the mid to high latitudes of the North Atlantic and leads the atmospheric variability by 6-7 years. If AMO represents the oceanic conditons and NAO represents the atmospheric variability then it could be said that AMO of one sign leads NAO of the opposite sign with a lag of 6-7 years. On the other hand, the evolution of atmospheric conditions, represented by pressure distribution patterns, favors atmospheric circulation anomalies and induces a heat advection which tends to change the sign of the existing SST distribution and oceanic conditions with a lag of 16-17 years. In this case, NAO of one sign leads AMO of the same sign with a lag of 16-17 years.

An FEM-based AI approach to model parameter identification for low vibration modes of wind turbine composite rotor blades

NASA Astrophysics Data System (ADS)

Navadeh, N.; Goroshko, I. O.; Zhuk, Y. A.; Fallah, A. S.

2017-11-01

An approach to construction of a beam-type simplified model of a horizontal axis wind turbine composite blade based on the finite element method is proposed. The model allows effective and accurate description of low vibration bending modes taking into account the effects of coupling between flapwise and lead-lag modes of vibration transpiring due to the non-uniform distribution of twist angle in the blade geometry along its length. The identification of model parameters is carried out on the basis of modal data obtained by more detailed finite element simulations and subsequent adoption of the 'DIRECT' optimisation algorithm. Stable identification results were obtained using absolute deviations in frequencies and in modal displacements in the objective function and additional a priori information (boundedness and monotony) on the solution properties.

Temperature, hospital admissions and emergency room visits in Lhasa, Tibet: a time-series analysis.

PubMed

Bai, Li; Cirendunzhu; Woodward, Alistair; Dawa; Zhaxisangmu; Chen, Bin; Liu, Qiyong

2014-08-15

Tibet of China, with an average altitude of over 4000 m, has experienced noticeable changes in its climate over the last 50 years. The association between temperature and morbidity (most commonly represented by hospital admissions) has been documented mainly in developed countries. Little is known about patterns in China; nor have the health effects of temperature variations been closely studied in highland areas, worldwide. We investigated the temperature-morbidity association in Lhasa, the capital city of Tibet, using sex- and age-specific hospitalizations, excluding those due to external causes. A distributed lag non-linear model (DLNM) was applied to assess the nonlinear and delayed effects of temperature on morbidity (including total emergency room visits, total and cause-specific hospital admissions, sex- and age-specific non-external admissions). High temperatures are associated with increases in morbidity, to a greater extent than low temperatures. Lag effects of high and low temperatures were cause-specific. The relative risks (RR) of high temperature for total emergency room visits and non-external hospitalizations were 1.162 (95% CI: 1.002-1.349) and 1.161 (95% CI: 1.007-1.339) respectively, for lag 0-14 days. The strongest cumulative effect of heat for lag 0-27 days was on admissions for infectious diseases (RR: 2.067, 95% CI: 1.026-4.027). Acute heat effects at lag 0 were related with increases of renal (RR: 1.478, 95% CI: 1.005-2.174) and respiratory diseases (RR: 1.119, 95% CI: 1.010-1.240), whereas immediate cold effects increased admission for digestive diseases (RR: 1.132, 95% CI: 1.002-1.282). Those ≥65 years of age and males were more vulnerable to high temperatures. We provide a first look at the temperature-morbidity relationship in Tibet. Exposure to both hot and cold temperatures resulted in increased admissions to hospital, but the immediate causes varied. We suggest that initiatives should be taken to reduce the adverse effects of temperature extremes in Tibet. Copyright © 2014. Published by Elsevier B.V.

Toward comparing experiment and theory for corroborative research on hingeless rotor stability in forward flight (an experimental and analytical investigation of isolated rotor-flap-lag stability in forward flight)

NASA Technical Reports Server (NTRS)

Gaonkar, G.

1986-01-01

For flap-lag stability of isolated rotors, experimental and analytical investigations are conducted in hover and forward flight on the adequacy of a linear quasisteady aerodynamics theory with dynamic inflow. Forward flight effects on lag regressing mode are emphasized. Accordingly, a soft inplane hingeless rotor with three blades is tested at advance ratios as high as 0.55 and at shaft angles as high as 20 degrees. The 1.62 m model rotor is untrimmed with an essentially unrestricted tilt of the tip path plane. In combination with lag natural frequencies, collective pitch settings and flap-lag coupling parameters, the data base comprises nearly 1200 test points (damping and frequency) in forward flight and 200 test points in hover. By computerized symbolic manipulation, a linear analytical model is developed in substall to predict stability margins with mode identificaton. To help explain the correlation between theory and data it also predicts substall and stall regions of the rotor disk from equilibrium values. The correlation shows both the strengthts and weaknesses of the theory in substall.

Continuum Reverberation Mapping of the Accretion Disks in Two Seyfert 1 Galaxies

NASA Astrophysics Data System (ADS)

Fausnaugh, M. M.; Starkey, D. A.; Horne, Keith; Kochanek, C. S.; Peterson, B. M.; Bentz, M. C.; Denney, K. D.; Grier, C. J.; Grupe, D.; Pogge, R. W.; De Rosa, G.; Adams, S. M.; Barth, A. J.; Beatty, Thomas G.; Bhattacharjee, A.; Borman, G. A.; Boroson, T. A.; Bottorff, M. C.; Brown, Jacob E.; Brown, Jonathan S.; Brotherton, M. S.; Coker, C. T.; Crawford, S. M.; Croxall, K. V.; Eftekharzadeh, Sarah; Eracleous, Michael; Joner, M. D.; Henderson, C. B.; Holoien, T. W.-S.; Hutchison, T.; Kaspi, Shai; Kim, S.; King, Anthea L.; Li, Miao; Lochhaas, Cassandra; Ma, Zhiyuan; MacInnis, F.; Manne-Nicholas, E. R.; Mason, M.; Montuori, Carmen; Mosquera, Ana; Mudd, Dale; Musso, R.; Nazarov, S. V.; Nguyen, M. L.; Okhmat, D. N.; Onken, Christopher A.; Ou-Yang, B.; Pancoast, A.; Pei, L.; Penny, Matthew T.; Poleski, Radosław; Rafter, Stephen; Romero-Colmenero, E.; Runnoe, Jessie; Sand, David J.; Schimoia, Jaderson S.; Sergeev, S. G.; Shappee, B. J.; Simonian, Gregory V.; Somers, Garrett; Spencer, M.; Stevens, Daniel J.; Tayar, Jamie; Treu, T.; Valenti, Stefano; Van Saders, J.; Villanueva, S., Jr.; Villforth, C.; Weiss, Yaniv; Winkler, H.; Zhu, W.

2018-02-01

We present optical continuum lags for two Seyfert 1 galaxies, MCG+08-11-011 and NGC 2617, using monitoring data from a reverberation mapping campaign carried out in 2014. Our light curves span the ugriz filters over four months, with median cadences of 1.0 and 0.6 days for MCG+08-11-011 and NGC 2617, respectively, combined with roughly daily X-ray and near-UV data from Swift for NGC 2617. We find lags consistent with geometrically thin accretion-disk models that predict a lag-wavelength relation of τ ∝ λ 4/3. However, the observed lags are larger than predictions based on standard thin-disk theory by factors of 3.3 for MCG+08-11-011 and 2.3 for NGC 2617. These differences can be explained if the mass accretion rates are larger than inferred from the optical luminosity by a factor of 4.3 in MCG+08-11-011 and a factor of 1.3 in NGC 2617, although uncertainty in the SMBH masses determines the significance of this result. While the X-ray variability in NGC 2617 precedes the UV/optical variability, the long (2.6 day) lag is problematic for coronal reprocessing models.

Climate variables as predictors for seasonal forecast of dengue occurrence in Chennai, Tamil Nadu

NASA Astrophysics Data System (ADS)

Subash Kumar, D. D.; Andimuthu, R.

2013-12-01

Background Dengue is a recently emerging vector borne diseases in Chennai. As per the WHO report in 2011 dengue is one of eight climate sensitive disease of this century. Objective Therefore an attempt has been made to explore the influence of climate parameters on dengue occurrence and use for forecasting. Methodology Time series analysis has been applied to predict the number of dengue cases in Chennai, a metropolitan city which is the capital of Tamil Nadu, India. Cross correlation of the climate variables with dengue cases revealed that the most influential parameters were monthly relative humidity, minimum temperature at 4 months lag and rainfall at one month lag (Table 1). However due to intercorrelation of relative humidity and rainfall was high and therefore for predictive purpose the rainfall at one month lag was used for the model development. Autoregressive Integrated Moving Average (ARIMA) models have been applied to forecast the occurrence of dengue. Results and Discussion The best fit model was ARIMA (1,0,1). It was seen that the monthly minimum temperature at four months lag (β= 3.612, p = 0.02) and rainfall at one month lag (β= 0.032, p = 0.017) were associated with dengue occurrence and they had a very significant effect. Mean Relative Humidity had a directly significant positive correlation at 99% confidence level, but the lagged effect was not prominent. The model predicted dengue cases showed significantly high correlation of 0.814(Figure 1) with the observed cases. The RMSE of the model was 18.564 and MAE was 12.114. The model is limited by the scarcity of the dataset. Inclusion of socioeconomic conditions and population offset are further needed to be incorporated for effective results. Conclusion Thus it could be claimed that the change in climatic parameters is definitely influential in increasing the number of dengue occurrence in Chennai. The climate variables therefore can be used for seasonal forecasting of dengue with rise in minimum temperature and rainfall at a city level. Table 1. Cross correlation of climate variables with dengue cases in Chennai ** p<0.01,*p<0.05

Multivariate dynamic Tobit models with lagged observed dependent variables: An effectiveness analysis of highway safety laws.

PubMed

Dong, Chunjiao; Xie, Kun; Zeng, Jin; Li, Xia

2018-04-01

Highway safety laws aim to influence driver behaviors so as to reduce the frequency and severity of crashes, and their outcomes. For one specific highway safety law, it would have different effects on the crashes across severities. Understanding such effects can help policy makers upgrade current laws and hence improve traffic safety. To investigate the effects of highway safety laws on crashes across severities, multivariate models are needed to account for the interdependency issues in crash counts across severities. Based on the characteristics of the dependent variables, multivariate dynamic Tobit (MVDT) models are proposed to analyze crash counts that are aggregated at the state level. Lagged observed dependent variables are incorporated into the MVDT models to account for potential temporal correlation issues in crash data. The state highway safety law related factors are used as the explanatory variables and socio-demographic and traffic factors are used as the control variables. Three models, a MVDT model with lagged observed dependent variables, a MVDT model with unobserved random variables, and a multivariate static Tobit (MVST) model are developed and compared. The results show that among the investigated models, the MVDT models with lagged observed dependent variables have the best goodness-of-fit. The findings indicate that, compared to the MVST, the MVDT models have better explanatory power and prediction accuracy. The MVDT model with lagged observed variables can better handle the stochasticity and dependency in the temporal evolution of the crash counts and the estimated values from the model are closer to the observed values. The results show that more lives could be saved if law enforcement agencies can make a sustained effort to educate the public about the importance of motorcyclists wearing helmets. Motor vehicle crash-related deaths, injuries, and property damages could be reduced if states enact laws for stricter text messaging rules, higher speeding fines, older licensing age, and stronger graduated licensing provisions. Injury and PDO crashes would be significantly reduced with stricter laws prohibiting the use of hand-held communication devices and higher fines for drunk driving. Copyright © 2018 Elsevier Ltd. All rights reserved.

A study of optimal model lag and spatial inputs to artificial neural network for rainfall forecasting

NASA Astrophysics Data System (ADS)

Luk, K. C.; Ball, J. E.; Sharma, A.

2000-01-01

Artificial neural networks (ANNs), which emulate the parallel distributed processing of the human nervous system, have proven to be very successful in dealing with complicated problems, such as function approximation and pattern recognition. Due to their powerful capability and functionality, ANNs provide an alternative approach for many engineering problems that are difficult to solve by conventional approaches. Rainfall forecasting has been a difficult subject in hydrology due to the complexity of the physical processes involved and the variability of rainfall in space and time. In this study, ANNs were adopted to forecast short-term rainfall for an urban catchment. The ANNs were trained to recognise historical rainfall patterns as recorded from a number of gauges in the study catchment for reproduction of relevant patterns for new rainstorm events. The primary objective of this paper is to investigate the effect of temporal and spatial information on short-term rainfall forecasting. To achieve this aim, a comparison test on the forecast accuracy was made among the ANNs configured with different orders of lag and different numbers of spatial inputs. In developing the ANNs with alternative configurations, the ANNs were trained to an optimal level to achieve good generalisation of data. It was found in this study that the ANNs provided the most accurate predictions when an optimum number of spatial inputs was included into the network, and that the network with lower lag consistently produced better performance.

Modelization of the Current and Future Habitat Suitability of Rhododendron ferrugineum Using Potential Snow Accumulation

PubMed Central

Komac, Benjamin; Esteban, Pere; Trapero, Laura; Caritg, Roger

2016-01-01

Mountain areas are particularly sensitive to climate change. Species distribution models predict important extinctions in these areas whose magnitude will depend on a number of different factors. Here we examine the possible impact of climate change on the Rhododendron ferrugineum (alpenrose) niche in Andorra (Pyrenees). This species currently occupies 14.6 km2 of this country and relies on the protection afforded by snow cover in winter. We used high-resolution climatic data, potential snow accumulation and a combined forecasting method to obtain the realized niche model of this species. Subsequently, we used data from the high-resolution Scampei project climate change projection for the A2, A1B and B1 scenarios to model its future realized niche model. The modelization performed well when predicting the species’s distribution, which improved when we considered the potential snow accumulation, the most important variable influencing its distribution. We thus obtained a potential extent of about 70.7 km2 or 15.1% of the country. We observed an elevation lag distribution between the current and potential distribution of the species, probably due to its slow colonization rate and the small-scale survey of seedlings. Under the three climatic scenarios, the realized niche model of the species will be reduced by 37.9–70.1 km2 by the end of the century and it will become confined to what are today screes and rocky hillside habitats. The particular effects of climate change on seedling establishment, as well as on the species’ plasticity and sensitivity in the event of a reduction of the snow cover, could worsen these predictions. PMID:26824847

Fine particulate matter estimated by mathematical model and hospitalizations for pneumonia and asthma in children

PubMed Central

César, Ana Cristina Gobbo; Nascimento, Luiz Fernando Costa; Mantovani, Katia Cristina Cota; Vieira, Luciana Cristina Pompeo

2016-01-01

Abstract Objective: To estimate the association between exposure to fine particulate matter with an aerodynamic diameter <2.5 microns (PM2.5) and hospitalizations for pneumonia and asthma in children. Methods: An ecological study of time series was performed, with daily indicators of hospitalization for pneumonia and asthma in children up to 10 years of age, living in Taubaté (SP) and estimated concentrations of PM2.5, between August 2011 and July 2012. A generalized additive model of Poisson regression was used to estimate the relative risk, with lag zero up to five days after exposure; the single pollutant model was adjusted by the apparent temperature, as defined from the temperature and relative air humidity, seasonality and weekday. Results: The values of the relative risks for hospitalization for pneumonia and asthma were significant for lag 0 (RR=1.051, 95%CI; 1.016 to 1.088); lag 2 (RR=1.066, 95%CI: 1.023 to 1.113); lag 3 (RR=1.053, 95%CI: 1.015 to 1.092); lag 4 (RR=1.043, 95%CI: 1.004 to 1.088) and lag 5 (RR=1.061, 95%CI: 1.018 to 1.106). The increase of 5mcg/m3 in PM2.5 contributes to increase the relative risk for hospitalization from 20.3 to 38.4 percentage points; however, the reduction of 5µg/m3 in PM2.5 concentration results in 38 fewer hospital admissions. Conclusions: Exposure to PM2.5 was associated with hospitalizations for pneumonia and asthma in children younger than 10 years of age, showing the role of fine particulate matter in child health and providing subsidies for the implementation of preventive measures to decrease these outcomes. PMID:26522821

The Cardiopulmonary Effects of Ambient Air Pollution and Mechanistic Pathways: A Comparative Hierarchical Pathway Analysis

PubMed Central

Thomas, Duncan C.; Zhang, Junfeng; Kipen, Howard M.; Rich, David Q.; Zhu, Tong; Huang, Wei; Hu, Min; Wang, Guangfa; Wang, Yuedan; Zhu, Ping; Lu, Shou-En; Ohman-Strickland, Pamela; Diehl, Scott R.; Eckel, Sandrah P.

2014-01-01

Previous studies have investigated the associations between exposure to ambient air pollution and biomarkers of physiological pathways, yet little has been done on the comparison across biomarkers of different pathways to establish the temporal pattern of biological response. In the current study, we aim to compare the relative temporal patterns in responses of candidate pathways to different pollutants. Four biomarkers of pulmonary inflammation and oxidative stress, five biomarkers of systemic inflammation and oxidative stress, ten parameters of autonomic function, and three biomarkers of hemostasis were repeatedly measured in 125 young adults, along with daily concentrations of ambient CO, PM2.5, NO2, SO2, EC, OC, and sulfate, before, during, and after the Beijing Olympics. We used a two-stage modeling approach, including Stage I models to estimate the association between each biomarker and pollutant over each of 7 lags, and Stage II mixed-effect models to describe temporal patterns in the associations when grouping the biomarkers into the four physiological pathways. Our results show that candidate pathway groupings of biomarkers explained a significant amount of variation in the associations for each pollutant, and the temporal patterns of the biomarker-pollutant-lag associations varied across candidate pathways (p<0.0001) and were not linear (from lag 0 to lag 3: p = 0.0629, from lag 3 to lag 6: p = 0.0005). These findings suggest that, among this healthy young adult population, the pulmonary inflammation and oxidative stress pathway is the first to respond to ambient air pollution exposure (within 24 hours) and the hemostasis pathway responds gradually over a 2–3 day period. The initial pulmonary response may contribute to the more gradual systemic changes that likely ultimately involve the cardiovascular system. PMID:25502951

Simultaneous pharmacodynamic analysis of the lag and bactericidal phases exhibited by beta-lactams against Escherichia coli.

PubMed Central

Li, R C

1996-01-01

Antibiotic-bacterium interactions are complex in nature. In many cases, bacterial killing does not commence immediately after the addition of an antibiotic, and a lag period is observed. Antibiotic permeation and/or the intermediate steps that exist between antibiotic-receptor binding and expression of cell death are two major possible causes for such lag period. This study was primarily designed to determine the relationship, if any, between antibiotic concentrations and the lag periods by a modeling approach. Short-term time-kill studies were conducted for amoxicillin, ampicillin, penicillin-G, oxacillin, and dicloxacillin against Escherichia coli. In conjunction with the use of a saturable rate model to describe the concentration-dependent killing process, a first-order induction (initiation) rate constant was used to characterize the delay in bacterial killing during the lag period. For all of the beta-lactams tested, parameters describing the bactericidal effect suggest that amoxicillin and ampicillin were much more potent than oxacillin and dicloxacillin. The induction rate constant estimates for both ampicillin and amoxicillin were found to relate linearly to concentrations. Nevertheless, these induction rate constant estimates were lower for penicillin-G, oxacillin, and dicloxacillin and increased nonlinearly with concentrations until an apparent plateau was observed. These findings support the hypothesis that the permeation process is potentially a rate-limiting step for the rapid bactericidal beta-lactams such as ampicillin and amoxicillin. However, as suggested by previous observations of the various morphological changes induced by beta-lactams, the contribution of the steps following antibiotic-receptor complex formation to the lag period might be significant for the less bactericidal antibiotics such as oxacillin and dicloxacillin. Findings from the present modeling approach can potentially be used to guide future bench experimentation. PMID:8891135

Estimation of daily reference evapotranspiration (ETo) using artificial intelligence methods: Offering a new approach for lagged ETo data-based modeling

NASA Astrophysics Data System (ADS)

Mehdizadeh, Saeid

2018-04-01

Evapotranspiration (ET) is considered as a key factor in hydrological and climatological studies, agricultural water management, irrigation scheduling, etc. It can be directly measured using lysimeters. Moreover, other methods such as empirical equations and artificial intelligence methods can be used to model ET. In the recent years, artificial intelligence methods have been widely utilized to estimate reference evapotranspiration (ETo). In the present study, local and external performances of multivariate adaptive regression splines (MARS) and gene expression programming (GEP) were assessed for estimating daily ETo. For this aim, daily weather data of six stations with different climates in Iran, namely Urmia and Tabriz (semi-arid), Isfahan and Shiraz (arid), Yazd and Zahedan (hyper-arid) were employed during 2000-2014. Two types of input patterns consisting of weather data-based and lagged ETo data-based scenarios were considered to develop the models. Four statistical indicators including root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R2), and mean absolute percentage error (MAPE) were used to check the accuracy of models. The local performance of models revealed that the MARS and GEP approaches have the capability to estimate daily ETo using the meteorological parameters and the lagged ETo data as inputs. Nevertheless, the MARS had the best performance in the weather data-based scenarios. On the other hand, considerable differences were not observed in the models' accuracy for the lagged ETo data-based scenarios. In the innovation of this study, novel hybrid models were proposed in the lagged ETo data-based scenarios through combination of MARS and GEP models with autoregressive conditional heteroscedasticity (ARCH) time series model. It was concluded that the proposed novel models named MARS-ARCH and GEP-ARCH improved the performance of ETo modeling compared to the single MARS and GEP. In addition, the external analysis of the performance of models at stations with similar climatic conditions denoted the applicability of nearby station' data for estimation of the daily ETo at target station.

Developing GIS-based eastern equine encephalitis vector-host models in Tuskegee, Alabama.

PubMed

Jacob, Benjamin G; Burkett-Cadena, Nathan D; Luvall, Jeffrey C; Parcak, Sarah H; McClure, Christopher J W; Estep, Laura K; Hill, Geoffrey E; Cupp, Eddie W; Novak, Robert J; Unnasch, Thomas R

2010-02-24

A site near Tuskegee, Alabama was examined for vector-host activities of eastern equine encephalomyelitis virus (EEEV). Land cover maps of the study site were created in ArcInfo 9.2 from QuickBird data encompassing visible and near-infrared (NIR) band information (0.45 to 0.72 microm) acquired July 15, 2008. Georeferenced mosquito and bird sampling sites, and their associated land cover attributes from the study site, were overlaid onto the satellite data. SAS 9.1.4 was used to explore univariate statistics and to generate regression models using the field and remote-sampled mosquito and bird data. Regression models indicated that Culex erracticus and Northern Cardinals were the most abundant mosquito and bird species, respectively. Spatial linear prediction models were then generated in Geostatistical Analyst Extension of ArcGIS 9.2. Additionally, a model of the study site was generated, based on a Digital Elevation Model (DEM), using ArcScene extension of ArcGIS 9.2. For total mosquito count data, a first-order trend ordinary kriging process was fitted to the semivariogram at a partial sill of 5.041 km, nugget of 6.325 km, lag size of 7.076 km, and range of 31.43 km, using 12 lags. For total adult Cx. erracticus count, a first-order trend ordinary kriging process was fitted to the semivariogram at a partial sill of 5.764 km, nugget of 6.114 km, lag size of 7.472 km, and range of 32.62 km, using 12 lags. For the total bird count data, a first-order trend ordinary kriging process was fitted to the semivariogram at a partial sill of 4.998 km, nugget of 5.413 km, lag size of 7.549 km and range of 35.27 km, using 12 lags. For the Northern Cardinal count data, a first-order trend ordinary kriging process was fitted to the semivariogram at a partial sill of 6.387 km, nugget of 5.935 km, lag size of 8.549 km and a range of 41.38 km, using 12 lags. Results of the DEM analyses indicated a statistically significant inverse linear relationship between total sampled mosquito data and elevation (R2 = -.4262; p < .0001), with a standard deviation (SD) of 10.46, and total sampled bird data and elevation (R2 = -.5111; p < .0001), with a SD of 22.97. DEM statistics also indicated a significant inverse linear relationship between total sampled Cx. erracticus data and elevation (R2 = -.4711; p < .0001), with a SD of 11.16, and the total sampled Northern Cardinal data and elevation (R2 = -.5831; p < .0001), SD of 11.42. These data demonstrate that GIS/remote sensing models and spatial statistics can capture space-varying functional relationships between field-sampled mosquito and bird parameters for determining risk for EEEV transmission.

Correspondence between the distribution of hydrodynamic time parameters and the distribution of biological and chemical variables in a semi-enclosed coral reef lagoon

NASA Astrophysics Data System (ADS)

Torréton, Jean-Pascal; Rochelle-Newall, Emma; Jouon, Aymeric; Faure, Vincent; Jacquet, Séverine; Douillet, Pascal

2007-09-01

Hydrodynamic modeling can be used to spatially characterize water renewal rates in coastal ecosystems. Using a hydrodynamic model implemented over the semi-enclosed Southwest coral lagoon of New Caledonia, a recent study computed the flushing lag as the minimum time required for a particle coming from outside the lagoon (open ocean) to reach a specific station [Jouon, A., Douillet, P., Ouillon, S., Fraunié, P., 2006. Calculations of hydrodynamic time parameters in a semi-opened coastal zone using a 3D hydrodynamic model. Continental Shelf Research 26, 1395-1415]. Local e -flushing time was calculated as the time requested to reach a local grid mesh concentration of 1/e from the precedent step. Here we present an attempt to connect physical forcing to biogeochemical functioning of this coastal ecosystem. An array of stations, located in the lagoonal channel as well as in several bays under anthropogenic influence, was sampled during three cruises. We then tested the statistical relationships between the distribution of flushing indices and those of biological and chemical variables. Among the variables tested, silicate, chlorophyll a and bacterial biomass production present the highest correlations with flushing indices. Correlations are higher with local e-flushing times than with flushing lags or the sum of these two indices. In the bays, these variables often deviate from the relationships determined in the main lagoon channel. In the three bays receiving significant riverine inputs, silicate is well above the regression line, whereas data from the bay receiving almost insignificant freshwater inputs generally fit the lagoon channel regressions. Moreover, in the three bays receiving important urban and industrial effluents, chlorophyll a and bacterial production of biomass generally display values exceeding the lagoon channel regression trends whereas in the bay under moderate anthropogenic influence values follow the regressions obtained in the lagoon channel. The South West lagoon of New Caledonia can hence be viewed as a coastal mesotrophic ecosystem that is flushed by oligotrophic oceanic waters which subsequently replace the lagoonal waters with water considerably impoverished in resources for microbial growth. This flushing was high enough during the periods of study to influence the distribution of phytoplankton biomass, bacterial production of biomass and silicate concentrations in the lagoon channel as well as in some of the bay areas.

Monochloramine Disinfection Kinetics of Nitrosomonas europaea by Propidium Monoazide Quantitative PCR and Live/Dead BacLight Methods▿

PubMed Central

Wahman, David G.; Wulfeck-Kleier, Karen A.; Pressman, Jonathan G.

2009-01-01

Monochloramine disinfection kinetics were determined for the pure-culture ammonia-oxidizing bacterium Nitrosomonas europaea (ATCC 19718) by two culture-independent methods, namely, Live/Dead BacLight (LD) and propidium monoazide quantitative PCR (PMA-qPCR). Both methods were first verified with mixtures of heat-killed (nonviable) and non-heat-killed (viable) cells before a series of batch disinfection experiments with stationary-phase cultures (batch grown for 7 days) at pH 8.0, 25°C, and 5, 10, and 20 mg Cl2/liter monochloramine. Two data sets were generated based on the viability method used, either (i) LD or (ii) PMA-qPCR. These two data sets were used to estimate kinetic parameters for the delayed Chick-Watson disinfection model through a Bayesian analysis implemented in WinBUGS. This analysis provided parameter estimates of 490 mg Cl2-min/liter for the lag coefficient (b) and 1.6 × 10−3 to 4.0 × 10−3 liter/mg Cl2-min for the Chick-Watson disinfection rate constant (k). While estimates of b were similar for both data sets, the LD data set resulted in a greater k estimate than that obtained with the PMA-qPCR data set, implying that the PMA-qPCR viability measure was more conservative than LD. For N. europaea, the lag phase was not previously reported for culture-independent methods and may have implications for nitrification in drinking water distribution systems. This is the first published application of a PMA-qPCR method for disinfection kinetic model parameter estimation as well as its application to N. europaea or monochloramine. Ultimately, this PMA-qPCR method will allow evaluation of monochloramine disinfection kinetics for mixed-culture bacteria in drinking water distribution systems. PMID:19561179

Ambient air pollution and birth weight in full-term infants in Atlanta, 1994-2004.

PubMed

Darrow, Lyndsey A; Klein, Mitchel; Strickland, Matthew J; Mulholland, James A; Tolbert, Paige E

2011-05-01

An emerging body of evidence suggests that ambient levels of air pollution during pregnancy are associated with fetal growth. We examined relationships between birth weight and temporal variation in ambient levels of carbon monoxide, nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone, particulate matter ≤ 10 μm in diameter (PM₁₀), ≤ 2.5 μm (PM(2.5)), 2.5 to 10 µm (PM(2.5-10)), and PM(2.5) chemical component measurements for 406,627 full-term births occurring between 1994 and 2004 in five central counties of metropolitan Atlanta. We assessed relationships between birth weight and pollutant concentrations during each infant's first month of gestation and third trimester, as well as in each month of pregnancy using distributed lag models. We also conducted capture-area analyses limited to mothers residing within 4 miles (6.4 km) of each air quality monitoring station. In the five-county analysis, ambient levels of NO₂, SO₂, PM(2.5) elemental carbon, and PM(2.5) water-soluble metals during the third trimester were significantly associated with small reductions in birth weight (-4 to -16 g per interquartile range increase in pollutant concentrations). Third-trimester estimates were generally higher in Hispanic and non-Hispanic black infants relative to non-Hispanic white infants. Distributed lag models were also suggestive of associations between air pollutant concentrations in late pregnancy and reduced birth weight. The capture-area analyses provided little support for the associations observed in the five-county analysis. Results provide some support for an effect of ambient air pollution in late pregnancy on birth weight in full-term infants.

Spatio-temporal modelling of dengue fever incidence in Malaysia

NASA Astrophysics Data System (ADS)

Che-Him, Norziha; Ghazali Kamardan, M.; Saifullah Rusiman, Mohd; Sufahani, Suliadi; Mohamad, Mahathir; @ Kamariah Kamaruddin, Nafisah

2018-04-01

Previous studies reported significant relationship between dengue incidence rate (DIR) and both climatic and non-climatic factors. Therefore, this study proposes a generalised additive model (GAM) framework for dengue risk in Malaysia by using both climatic and non-climatic factors. The data used is monthly DIR for 12 states of Malaysia from 2001 to 2009. In this study, we considered an annual trend, seasonal effects, population, population density and lagged DIR, rainfall, temperature, number of rainy days and El Niño-Southern Oscillation (ENSO). The population density is found to be positively related to monthly DIR. There are generally weak relationships between monthly DIR and climate variables. A negative binomial GAM shows that there are statistically significant relationships between DIR with climatic and non-climatic factors. These include mean rainfall and temperature, the number of rainy days, sea surface temperature and the interaction between mean temperature (lag 1 month) and sea surface temperature (lag 6 months). These also apply to DIR (lag 3 months) and population density.

An experimental and analytical investigation of stall effects on flap-lag stability in forward flight

NASA Technical Reports Server (NTRS)

Nagabhushanam, J.; Gaonkar, Gopal H.; Mcnulty, Michael J.

1987-01-01

Experiments have been performed with a 1.62 m diameter hingeless rotor in a wind tunnel to investigate flap-lag stability of isolated rotors in forward flight. The three-bladed rotor model closely approaches the simple theoretical concept of a hingeless rotor as a set of rigid, articulated flap-lag blades with offset and spring restrained flap and lag hinges. Lag regressing mode stability data was obtained for advance ratios as high as 0.55 for various combinations of collective pitch and shaft angle. The prediction includes quasi-steady stall effects on rotor trim and Floquet stability analyses. Correlation between data and prediction is presented and is compared with that of an earlier study based on a linear theory without stall effects. While the results with stall effects show marked differences from the linear theory results, the stall theory still falls short of adequate agreement with the experimental data.

Climatological variables and the incidence of Dengue fever in Barbados.

PubMed

Depradine, Colin; Lovell, Ernest

2004-12-01

A retrospective study to determine relationships between the incidence of dengue cases and climatological variables and to obtain a predictive equation was carried out for the relatively small Caribbean island of Barbados which is divided into 11 parishes. The study used the weekly dengue cases and precipitation data for the years (1995 - 2000) that occurred in the small area of a single parish. Other climatological data were obtained from the local meteorological offices. The study used primarily cross correlation analysis and found the strongest correlation with the vapour pressure at a lag of 6 weeks. A weaker correlation occurred at a lag of 7 weeks for the precipitation. The minimum temperature had its strongest correlation at a lag of 12 weeks and the maximum temperature a lag of 16 weeks. There was a negative correlation with the wind speed at a lag of 3 weeks. The predictive models showed a maximum explained variance of 35%.

Air pollutants and atmospheric pressure increased risk of ED visit for spontaneous pneumothorax.

PubMed

Park, Joo Hyung; Lee, Sun Hwa; Yun, Seong Jong; Ryu, Seokyong; Choi, Seung Woon; Kim, Hye Jin; Kang, Tae Kyung; Oh, Sung Chan; Cho, Suk Jin

2018-04-14

To investigate the impact of short-term exposure to air pollutants and meteorological variation on ED visits for primary spontaneous pneumothorax (PSP). We retrospectively identified PSP cases that presented at the ED of our tertiary center between January 2015 and September 2016. We classified the days into three types: no PSP day (0 case/day), sporadic days (1-2 cases/day), and cluster days (PSP, ≥3 cases/day). Association between the daily incidence of PSP with air pollutants and meteorological data were determined using Poisson generalized-linear-model to calculate incidence rate ratio (IRRs) and the use of time-series (lag-1 [the cumulative air pollution level on the previous day of PSP], lag-2 [two days ago], and lag-3 [three days ago]). Using multivariate logistic regression analysis, O 3 (p = 0.010), NO 2 (p = 0.047), particulate matters (PM) 10 (p = 0.021), and PM 2.5 (p = 0.008) were significant factors of PSP occurrence. When the concentration of O 3 , NO 2 , PM 10 , and PM 2.5 were increased, PSP IRRs increased approximately 15, 16, 3, and 5-fold, respectively. With the time-series analyses, atmospheric pressure in lag-3 was significantly lower and in lag-2, was significantly higher in PSP days compared with no PSP days. Among air pollutant concentrations, O 3 in lag-1 (p = 0.017) and lag-2 (p = 0.038), NO 2 in lag-1 (p = 0.015) and lag-2 (p = 0.009), PM 10 in lag-1 (p = 0.012), and PM 2.5 in lag-1 (p = 0.021) and lag-2 (p = 0.032) were significantly different between no PSP and PSP days. Increased concentrations of air pollutants and abrupt change in atmospheric pressure were significantly associated with increased IRR of PSP. Copyright © 2018 Elsevier Inc. All rights reserved.

Selenium mobility and distribution in irrigated and nonirrigated alluvial soils

USGS Publications Warehouse

Fio, John L.; Fujii, Roger; Deverel, S.J.

1991-01-01

Dissolution and leaching of soil salts by irrigation water is a primary source of Se to shallow groundwater in the western San Joaquin Valley, California. In this study, the mobility and distribution of selenite and selenate in soils with different irrigation and drainage histories was evaluated using sorption experiments and an advection-dispersion model. The sorption studies showed that selenate (15–12400 µg Se L−1) is not adsorbed to soil, whereas selenite (10–5000 µg Se L−1) is rapidly adsorbed. The time lag between adsorption and desorption of selenite is considerable, indicating a dependence of reaction rate on reaction direction (hysteresis). Selenite adsorption and desorption isotherms were different, and both were described with the Freundlich equation. Model results and chemical analyses of extracts from the soil samples showed that selenite is resistant to leaching and therefore can represent a potential long-term source of Se to groundwater. In contrast, selenate behaves as a conservative constituent under alkaline and oxidized conditions and is easily leached from soil.

Longitudinal development of number line estimation and mathematics performance in primary school children.

PubMed

Friso-van den Bos, Ilona; Kroesbergen, Evelyn H; Van Luit, Johannes E H; Xenidou-Dervou, Iro; Jonkman, Lisa M; Van der Schoot, Menno; Van Lieshout, Ernest C D M

2015-06-01

Children's ability to relate number to a continuous quantity abstraction visualized as a number line is widely accepted to be predictive of mathematics achievement. However, a debate has emerged with respect to how children's placements are distributed on this number line across development. In the current study, different models were applied to children's longitudinal number placement data to get more insight into the development of number line representations in kindergarten and early primary school years. In addition, longitudinal developmental relations between number line placements and mathematical achievement, measured with a national test of mathematics, were investigated using cross-lagged panel modeling. A group of 442 children participated in a 3-year longitudinal study (ages 5-8 years) in which they completed a number-to-position task every 6 months. Individual number line placements were fitted to various models, of which a one-anchor power model provided the best fit for many of the placements at a younger age (5 or 6 years) and a two-anchor power model provided better fit for many of the children at an older age (7 or 8 years). The number of children who made linear placements also grew with age. Cross-lagged panel analyses indicated that the best fit was provided with a model in which number line acuity and mathematics performance were mutually predictive of each other rather than models in which one ability predicted the other in a non-reciprocal way. This indicates that number line acuity should not be seen as a predictor of math but that both skills influence each other during the developmental process. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Mechanisms of Zero-Lag Synchronization in Cortical Motifs

PubMed Central

Gollo, Leonardo L.; Mirasso, Claudio; Sporns, Olaf; Breakspear, Michael

2014-01-01

Zero-lag synchronization between distant cortical areas has been observed in a diversity of experimental data sets and between many different regions of the brain. Several computational mechanisms have been proposed to account for such isochronous synchronization in the presence of long conduction delays: Of these, the phenomenon of “dynamical relaying” – a mechanism that relies on a specific network motif – has proven to be the most robust with respect to parameter mismatch and system noise. Surprisingly, despite a contrary belief in the community, the common driving motif is an unreliable means of establishing zero-lag synchrony. Although dynamical relaying has been validated in empirical and computational studies, the deeper dynamical mechanisms and comparison to dynamics on other motifs is lacking. By systematically comparing synchronization on a variety of small motifs, we establish that the presence of a single reciprocally connected pair – a “resonance pair” – plays a crucial role in disambiguating those motifs that foster zero-lag synchrony in the presence of conduction delays (such as dynamical relaying) from those that do not (such as the common driving triad). Remarkably, minor structural changes to the common driving motif that incorporate a reciprocal pair recover robust zero-lag synchrony. The findings are observed in computational models of spiking neurons, populations of spiking neurons and neural mass models, and arise whether the oscillatory systems are periodic, chaotic, noise-free or driven by stochastic inputs. The influence of the resonance pair is also robust to parameter mismatch and asymmetrical time delays amongst the elements of the motif. We call this manner of facilitating zero-lag synchrony resonance-induced synchronization, outline the conditions for its occurrence, and propose that it may be a general mechanism to promote zero-lag synchrony in the brain. PMID:24763382

How air pollution influences clinical management of respiratory diseases. A case-crossover study in Milan.

PubMed

Santus, Pierachille; Russo, Antonio; Madonini, Enzo; Allegra, Luigi; Blasi, Francesco; Centanni, Stefano; Miadonna, Antonio; Schiraldi, Gianfranco; Amaducci, Sandro

2012-10-18

Environmental pollution is a known risk factor for multiple diseases and furthermore increases rate of hospitalisations. We investigated the correlation between emergency room admissions (ERAs) of the general population for respiratory diseases and the environmental pollutant levels in Milan, a metropolis in northern Italy. We collected data from 45770 ERAs for respiratory diseases. A time-stratified case-crossover design was used to investigate the association between air pollution levels and ERAs for acute respiratory conditions. The effects of air pollutants were investigated at lag 0 to lag 5, lag 0-2 and lag 3-5 in both single and multi-pollutant models, adjusted for daily weather variables. An increase in ozone (O(3)) levels at lag 3-5 was associated with a 78% increase in the number of ERAs for asthma, especially during the warm season. Exposure to carbon monoxide (CO) proved to be a risk factor for pneumonia at lag 0-2 and in the warm season increased the risk of ERA by 66%. A significant association was found between ERAs for COPD exacerbation and levels of sulphur dioxide (SO(2)), CO, nitrate dioxide (NO(2)), and particulate matter (PM(10) and PM(2.5)). The multipollutant model that includes all pollutants showed a significant association between CO (26%) and ERA for upper respiratory tract diseases at lag 0-2. For chronic obstructive pulmonary disease (COPD) exacerbations, only CO (OR 1.19) showed a significant association. Exposure to environmental pollution, even at typical low levels, can increase the risk of ERA for acute respiratory diseases and exacerbation of obstructive lung diseases in the general population.

A longer vernal window: the role of winter coldness and snowpack in driving spring transitions and lags.

PubMed

Contosta, Alexandra R; Adolph, Alden; Burchsted, Denise; Burakowski, Elizabeth; Green, Mark; Guerra, David; Albert, Mary; Dibb, Jack; Martin, Mary; McDowell, William H; Routhier, Michael; Wake, Cameron; Whitaker, Rachel; Wollheim, Wilfred

2017-04-01

Climate change is altering the timing and duration of the vernal window, a period that marks the end of winter and the start of the growing season when rapid transitions in ecosystem energy, water, nutrient, and carbon dynamics take place. Research on this period typically captures only a portion of the ecosystem in transition and focuses largely on the dates by which the system wakes up. Previous work has not addressed lags between transitions that represent delays in energy, water, nutrient, and carbon flows. The objectives of this study were to establish the sequence of physical and biogeochemical transitions and lags during the vernal window period and to understand how climate change may alter them. We synthesized observations from a statewide sensor network in New Hampshire, USA, that concurrently monitored climate, snow, soils, and streams over a three-year period and supplemented these observations with climate reanalysis data, snow data assimilation model output, and satellite spectral data. We found that some of the transitions that occurred within the vernal window were sequential, with air temperatures warming prior to snow melt, which preceded forest canopy closure. Other transitions were simultaneous with one another and had zero-length lags, such as snowpack disappearance, rapid soil warming, and peak stream discharge. We modeled lags as a function of both winter coldness and snow depth, both of which are expected to decline with climate change. Warmer winters with less snow resulted in longer lags and a more protracted vernal window. This lengthening of individual lags and of the entire vernal window carries important consequences for the thermodynamics and biogeochemistry of ecosystems, both during the winter-to-spring transition and throughout the rest of the year. © 2016 The Authors Global Change Biology Published by John Wiley & Sons Ltd.

LAG3 Expression in Active Mycobacterium tuberculosis Infections

PubMed Central

Phillips, Bonnie L.; Mehra, Smriti; Ahsan, Muhammad H.; Selman, Moises; Khader, Shabaana A.; Kaushal, Deepak

2016-01-01

Mycobacterium tuberculosis (MTB) is a highly successful pathogen because of its ability to persist in human lungs for long periods of time. MTB modulates several aspects of the host immune response. Lymphocyte-activation gene 3 (LAG3) is a protein with a high affinity for the CD4 receptor and is expressed mainly by regulatory T cells with immunomodulatory functions. To understand the function of LAG3 during MTB infection, a nonhuman primate model of tuberculosis, which recapitulates key aspects of natural human infection in rhesus macaques (Macaca mulatta), was used. We show that the expression of LAG3 is highly induced in the lungs and particularly in the granulomatous lesions of macaques experimentally infected with MTB. Furthermore, we show that LAG3 expression is not induced in the lungs and lung granulomas of animals exhibiting latent tuberculosis infection. However, simian immunodeficiency virus–induced reactivation of latent tuberculosis infection results in an increased expression of LAG3 in the lungs. This response is not observed in nonhuman primates infected with non-MTB bacterial pathogens, nor with simian immunodeficiency virus alone. Our data show that LAG3 was expressed primarily on CD4+ T cells, presumably by regulatory T cells but also by natural killer cells. The expression of LAG3 coincides with high bacterial burdens and changes in the host type 1 helper T-cell response. PMID:25549835

Recognition memory advantage for negative emotional words has an early expiry date: Evidence from brain oscillations and ERPs.

PubMed

Santaniello, G; Ferré, P; Rodríguez-Gómez, P; Poch, C; Eva, M Moreno; Hinojosa, J A

2018-06-15

Evidence from prior studies has shown an advantage in recognition memory for emotional compared to neutral words. Whether this advantage is short-lived or rather extends over longer periods, as well as whether the effect depends on words' valence (i.e., positive or negative), remains unknown. In the present ERP/EEG study, we investigated this issue by manipulating the lag distance (LAG-2, LAG-8 and LAG-16) between the presentation of old and new words in an online recognition memory task. LAG differences were observed at behavior, ERPs and in the theta frequency band. In line with previous studies, negative words were associated with faster reaction times, higher hit rates and increased amplitude in a positive ERP component between 386 and 564 ms compared to positive and neutral words. Remarkably, the interaction of LAG by EMOTION revealed that negative words were associated with better performance and larger ERPs amplitudes only at LAG-2. Also in the LAG-2 condition, emotional words (i.e., positive and negative words) induced a stronger desynchronization in the beta band between 386 and 542 ms compared to neutral words. These early enhanced memory effects for emotional words are discussed in terms of the Negative Emotional Valence Enhances Recapitulation (NEVER) model and the mobilization-minimization hypothesis. Copyright © 2018 Elsevier Ltd. All rights reserved.

Competition between Primary Nucleation and Autocatalysis in Amyloid Fibril Self-Assembly

PubMed Central

Eden, Kym; Morris, Ryan; Gillam, Jay; MacPhee, Cait E.; Allen, Rosalind J.

2015-01-01

Kinetic measurements of the self-assembly of proteins into amyloid fibrils are often used to make inferences about molecular mechanisms. In particular, the lag time—the quiescent period before aggregates are detected—is often found to scale with the protein concentration as a power law, whose exponent has been used to infer the presence or absence of autocatalytic growth processes such as fibril fragmentation. Here we show that experimental data for lag time versus protein concentration can show signs of kinks: clear changes in scaling exponent, indicating changes in the dominant molecular mechanism determining the lag time. Classical models for the kinetics of fibril assembly suggest that at least two mechanisms are at play during the lag time: primary nucleation and autocatalytic growth. Using computer simulations and theoretical calculations, we investigate whether the competition between these two processes can account for the kinks which we observe in our and others’ experimental data. We derive theoretical conditions for the crossover between nucleation-dominated and growth-dominated regimes, and analyze their dependence on system volume and autocatalysis mechanism. Comparing these predictions to the data, we find that the experimentally observed kinks cannot be explained by a simple crossover between nucleation-dominated and autocatalytic growth regimes. Our results show that existing kinetic models fail to explain detailed features of lag time versus concentration curves, suggesting that new mechanistic understanding is needed. More broadly, our work demonstrates that care is needed in interpreting lag-time scaling exponents from protein assembly data. PMID:25650930

Climate variation and incidence of Ross river virus in Cairns, Australia: a time-series analysis.

PubMed Central

Tong, S; Hu, W

2001-01-01

In this study we assessed the impact of climate variability on the Ross River virus (RRv) transmission and validated an epidemic-forecasting model in Cairns, Australia. Data on the RRv cases recorded between 1985 and 1996 were obtained from the Queensland Department of Health. Climate and population data were supplied by the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. The cross-correlation function (CCF) showed that maximum temperature in the current month and rainfall and relative humidity at a lag of 2 months were positively and significantly associated with the monthly incidence of RRv, whereas relative humidity at a lag of 5 months was inversely associated with the RRv transmission. We developed autoregressive integrated moving average (ARIMA) models on the data collected between 1985 to 1994, and then validated the models using the data collected between 1995 and 1996. The results show that the relative humidity at a lag of 5 months (p < 0.001) and the rainfall at a lag of 2 months (p < 0.05) appeared to play significant roles in the transmission of RRv disease in Cairns. Furthermore, the regressive forecast curves were consistent with the pattern of actual values. PMID:11748035

Nested radiations and the pulse of angiosperm diversification: increased diversification rates often follow whole genome duplications.

PubMed

Tank, David C; Eastman, Jonathan M; Pennell, Matthew W; Soltis, Pamela S; Soltis, Douglas E; Hinchliff, Cody E; Brown, Joseph W; Sessa, Emily B; Harmon, Luke J

2015-07-01

Our growing understanding of the plant tree of life provides a novel opportunity to uncover the major drivers of angiosperm diversity. Using a time-calibrated phylogeny, we characterized hot and cold spots of lineage diversification across the angiosperm tree of life by modeling evolutionary diversification using stepwise AIC (MEDUSA). We also tested the whole-genome duplication (WGD) radiation lag-time model, which postulates that increases in diversification tend to lag behind established WGD events. Diversification rates have been incredibly heterogeneous throughout the evolutionary history of angiosperms and reveal a pattern of 'nested radiations' - increases in net diversification nested within other radiations. This pattern in turn generates a negative relationship between clade age and diversity across both families and orders. We suggest that stochastically changing diversification rates across the phylogeny explain these patterns. Finally, we demonstrate significant statistical support for the WGD radiation lag-time model. Across angiosperms, nested shifts in diversification led to an overall increasing rate of net diversification and declining relative extinction rates through time. These diversification shifts are only rarely perfectly associated with WGD events, but commonly follow them after a lag period. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Predicting safe sex: Assessment of autoregressive and cross-lagged effects within the Theory of Planned Behavior.

PubMed

Eggers, Sander M; Taylor, Myra; Sathiparsad, Reshma; Bos, Arjan Er; de Vries, Hein

2015-11-01

Despite its popularity, few studies have assessed the temporal stability and cross-lagged effects of the Theory of Planned Behavior factors: Attitude, subjective norms and self-efficacy. For this study, 298 adolescent learners from KwaZulu-Natal, South Africa, filled out a Theory of Planned Behavior questionnaire on teenage pregnancy at baseline and after 6 months. Structural equation modeling showed that there were considerable cross-lagged effects between attitude and subjective norms. Temporal stability was moderate with test-retest correlations ranging from 0.37 to 0.51 and the model was able to predict intentions to have safe sex (R2 = 0.69) Implications for practice and future research are discussed. © The Author(s) 2013.

Epidemiology of dengue fever in Hanoi from 2002 to 2010 and its meteorological determinants.

PubMed

Minh An, Dao Thi; Rocklöv, Joacim

2014-01-01

Dengue fever (DF) is a growing public health problem in Vietnam. The disease burden in Vietnam has been increasing for decades. In Hanoi, in contrast to many other regions, extrinsic drivers such as weather have not been proved to be predictive of disease frequency, which limits the usefulness of such factors in an early warning system. The purpose of this research was to review the epidemiology of DF transmission and investigate the role of weather factors contributing to occurrence of DF cases. Monthly data from Hanoi (2002-2010) were used to test the proposed model. Descriptive time-series analysis was conducted. Stepwise multivariate linear regression analysis assuming a negative binomial distribution was established through several models. The predictors used were lags of 1-3 months previous observations of mean rainfall, mean temperature, DF cases, and their interactions. Descriptive analysis showed that DF occurred annually and seasonally with an increasing time trend in Hanoi. The annual low occurred from December to March followed by a gradual increase from April to July with a peak in September, October. The amplitude of the annual peak varied between years. Statistically significant relationships were estimated at lag 1-3 with rainfall, autocorrelation, and their interaction while temperature was estimated as influential at lag 3 only. For these relationships, the final model determined a correlation of 92% between predicted number of dengue cases and the observed dengue disease frequencies. Although the model performance was good, the findings suggest that other forces related to urbanization, density of population, globalization with increasing transport of people and goods, herd immunity, government vector control capacity, and changes in serotypes are also likely influencing the transmission of DF. Additional research taking into account all of these factors besides climatic factors is needed to help developing and developed countries find the right intervention for controlling DF epidemics, and to set up early warning systems with high sensitivity and specificity. Immediate action to control DF outbreak in Hanoi should include an information, communication, and education program that focuses on training Hanoi residents to more efficiently eliminate stagnant puddles and water containers after each rainfall to limit the vector population growth.

Short-term association between air pollution and emergency room admissions for chronic obstructive pulmonary disease in Nis, Serbia.

PubMed

Milutinović, Suzana; Nikić, Dragana; Stosić, Ljiljana; Stanković, Aleksandra; Bogdanović, Dragan

2009-03-01

The present study assesses the short-term association between black smoke (BS) and sulphur dioxide (SO2) levels in urban air and the daily number of emergency room admissions for chronic obstructive pulmonary disease (COPD) in Nis, Serbia. Generalised linear models extending Poisson regression were fitted controlling for time trend, seasonal variations, days of the week, temperature, relative humidity, air pressure, precipitation, rainfall, snowfall, overcast, and wind velocity. The emergency room admissions for all ages for COPD were significantly associated with previous-day level of BS and lag 0-2 (1,60% and 2,26% increase per 10 microg/m3, respectively). After controlling for SO2, single lagged (lag 1 and lag 2) as well as mean lagged values of BS (up to lag 0-3) were significantly associated with COPD emergencies. No effect was found for SO2, even after controlling for black smoke. The present findings support the conclusion that current levels of ambient BS may have an effect on the respiratory health of susceptible persons.

Examining lag effects between industrial land development and regional economic changes: The Netherlands experience.

PubMed

Ustaoglu, Eda; Lavalle, Carlo

2017-01-01

In most empirical applications, forecasting models for the analysis of industrial land focus on the relationship between current values of economic parameters and industrial land use. This paper aims to test this assumption by focusing on the dynamic relationship between current and lagged values of the 'economic fundamentals' and industrial land development. Not much effort has yet been attributed to develop land forecasting models to predict the demand for industrial land except those applying static regressions or other statistical measures. In this research, we estimated a dynamic panel data model across 40 regions from 2000 to 2008 for the Netherlands to uncover the relationship between current and lagged values of economic parameters and industrial land development. Land-use regulations such as land zoning policies, and other land-use restrictions like natural protection areas, geographical limitations in the form of water bodies or sludge areas are expected to affect supply of land, which will in turn be reflected in industrial land market outcomes. Our results suggest that gross domestic product (GDP), industrial employment, gross value added (GVA), property price, and other parameters representing demand and supply conditions in the industrial market explain industrial land developments with high significance levels. It is also shown that contrary to the current values, lagged values of the economic parameters have more sound relationships with the industrial developments in the Netherlands. The findings suggest use of lags between selected economic parameters and industrial land use in land forecasting applications.

Examining lag effects between industrial land development and regional economic changes: The Netherlands experience

PubMed Central

Ustaoglu, Eda; Lavalle, Carlo

2017-01-01

In most empirical applications, forecasting models for the analysis of industrial land focus on the relationship between current values of economic parameters and industrial land use. This paper aims to test this assumption by focusing on the dynamic relationship between current and lagged values of the ‘economic fundamentals’ and industrial land development. Not much effort has yet been attributed to develop land forecasting models to predict the demand for industrial land except those applying static regressions or other statistical measures. In this research, we estimated a dynamic panel data model across 40 regions from 2000 to 2008 for the Netherlands to uncover the relationship between current and lagged values of economic parameters and industrial land development. Land-use regulations such as land zoning policies, and other land-use restrictions like natural protection areas, geographical limitations in the form of water bodies or sludge areas are expected to affect supply of land, which will in turn be reflected in industrial land market outcomes. Our results suggest that gross domestic product (GDP), industrial employment, gross value added (GVA), property price, and other parameters representing demand and supply conditions in the industrial market explain industrial land developments with high significance levels. It is also shown that contrary to the current values, lagged values of the economic parameters have more sound relationships with the industrial developments in the Netherlands. The findings suggest use of lags between selected economic parameters and industrial land use in land forecasting applications. PMID:28877204

A modification of the Regional Nutrient Management model (ReNuMa) to identify long-term changes in riverine nitrogen sources

NASA Astrophysics Data System (ADS)

Hu, Minpeng; Liu, Yanmei; Wang, Jiahui; Dahlgren, Randy A.; Chen, Dingjiang

2018-06-01

Source apportionment is critical for guiding development of efficient watershed nitrogen (N) pollution control measures. The ReNuMa (Regional Nutrient Management) model, a semi-empirical, semi-process-oriented model with modest data requirements, has been widely used for riverine N source apportionment. However, the ReNuMa model contains limitations for addressing long-term N dynamics by ignoring temporal changes in atmospheric N deposition rates and N-leaching lag effects. This work modified the ReNuMa model by revising the source code to allow yearly changes in atmospheric N deposition and incorporation of N-leaching lag effects into N transport processes. The appropriate N-leaching lag time was determined from cross-correlation analysis between annual watershed individual N source inputs and riverine N export. Accuracy of the modified ReNuMa model was demonstrated through analysis of a 31-year water quality record (1980-2010) from the Yongan watershed in eastern China. The revisions considerably improved the accuracy (Nash-Sutcliff coefficient increased by ∼0.2) of the modified ReNuMa model for predicting riverine N loads. The modified model explicitly identified annual and seasonal changes in contributions of various N sources (i.e., point vs. nonpoint source, surface runoff vs. groundwater) to riverine N loads as well as the fate of watershed anthropogenic N inputs. Model results were consistent with previously modeled or observed lag time length as well as changes in riverine chloride and nitrate concentrations during the low-flow regime and available N levels in agricultural soils of this watershed. The modified ReNuMa model is applicable for addressing long-term changes in riverine N sources, providing decision-makers with critical information for guiding watershed N pollution control strategies.

SOFT LAGS IN NEUTRON STAR kHz QUASI-PERIODIC OSCILLATIONS: EVIDENCE FOR REVERBERATION?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barret, Didier, E-mail: didier.barret@irap.omp.eu; CNRS, Institut de Recherche en Astrophysique et Planetologie, 9 Av. colonel Roche, BP 44346, F-31028 Toulouse cedex 4

2013-06-10

High frequency soft reverberation lags have now been detected from stellar mass and supermassive black holes. Their interpretation involves reflection of a hard source of photons onto an accretion disk, producing a delayed reflected emission, with a time lag consistent with the light travel time between the irradiating source and the disk. Independently of the location of the clock, the kHz quasi-periodic oscillation (QPO) emission is thought to arise from the neutron star boundary layer. Here, we search for the signature of reverberation of the kHz QPO emission, by measuring the soft lags and the lag energy spectrum of themore » lower kHz QPOs from 4U1608-522. Soft lags, ranging from {approx}15 to {approx}40 {mu}s, between the 3-8 keV and 8-30 keV modulated emissions are detected between 565 and 890 Hz. The soft lags are not constant with frequency and show a smooth decrease between 680 Hz and 890 Hz. The broad band X-ray spectrum is modeled as the sum of a disk and a thermal Comptonized component, plus a broad iron line, expected from reflection. The spectral parameters follow a smooth relationship with the QPO frequency, in particular the fitted inner disk radius decreases steadily with frequency. Both the bump around the iron line in the lag energy spectrum and the consistency between the lag changes and the inferred changes of the inner disk radius, from either spectral fitting or the QPO frequency, suggest that the soft lags may indeed involve reverberation of the hard pulsating QPO source on the disk.« less

Impact of meteorological factors on the incidence of bacillary dysentery in Beijing, China: A time series analysis (1970-2012).

PubMed

Yan, Long; Wang, Hong; Zhang, Xuan; Li, Ming-Yue; He, Juan

2017-01-01

Influence of meteorological variables on the transmission of bacillary dysentery (BD) is under investigated topic and effective forecasting models as public health tool are lacking. This paper aimed to quantify the relationship between meteorological variables and BD cases in Beijing and to establish an effective forecasting model. A time series analysis was conducted in the Beijing area based upon monthly data on weather variables (i.e. temperature, rainfall, relative humidity, vapor pressure, and wind speed) and on the number of BD cases during the period 1970-2012. Autoregressive integrated moving average models with explanatory variables (ARIMAX) were built based on the data from 1970 to 2004. Prediction of monthly BD cases from 2005 to 2012 was made using the established models. The prediction accuracy was evaluated by the mean square error (MSE). Firstly, temperature with 2-month and 7-month lags and rainfall with 12-month lag were found positively correlated with the number of BD cases in Beijing. Secondly, ARIMAX model with covariates of temperature with 7-month lag (β = 0.021, 95% confidence interval(CI): 0.004-0.038) and rainfall with 12-month lag (β = 0.023, 95% CI: 0.009-0.037) displayed the highest prediction accuracy. The ARIMAX model developed in this study showed an accurate goodness of fit and precise prediction accuracy in the short term, which would be beneficial for government departments to take early public health measures to prevent and control possible BD popularity.

Model selection and assessment for multi­-species occupancy models

USGS Publications Warehouse

Broms, Kristin M.; Hooten, Mevin B.; Fitzpatrick, Ryan M.

2016-01-01

While multi-species occupancy models (MSOMs) are emerging as a popular method for analyzing biodiversity data, formal checking and validation approaches for this class of models have lagged behind. Concurrent with the rise in application of MSOMs among ecologists, a quiet regime shift is occurring in Bayesian statistics where predictive model comparison approaches are experiencing a resurgence. Unlike single-species occupancy models that use integrated likelihoods, MSOMs are usually couched in a Bayesian framework and contain multiple levels. Standard model checking and selection methods are often unreliable in this setting and there is only limited guidance in the ecological literature for this class of models. We examined several different contemporary Bayesian hierarchical approaches for checking and validating MSOMs and applied these methods to a freshwater aquatic study system in Colorado, USA, to better understand the diversity and distributions of plains fishes. Our findings indicated distinct differences among model selection approaches, with cross-validation techniques performing the best in terms of prediction.

The lead-lag relationship between stock index and stock index futures: A thermal optimal path method

NASA Astrophysics Data System (ADS)

Gong, Chen-Chen; Ji, Shen-Dan; Su, Li-Ling; Li, Sai-Ping; Ren, Fei

2016-02-01

The study of lead-lag relationship between stock index and stock index futures is of great importance for its wide application in hedging and portfolio investments. Previous works mainly use conventional methods like Granger causality test, GARCH model and error correction model, and focus on the causality relation between the index and futures in a certain period. By using a non-parametric approach-thermal optimal path (TOP) method, we study the lead-lag relationship between China Securities Index 300 (CSI 300), Hang Seng Index (HSI), Standard and Poor 500 (S&P 500) Index and their associated futures to reveal the variance of their relationship over time. Our finding shows evidence of pronounced futures leadership for well established index futures, namely HSI and S&P 500 index futures, while index of developing market like CSI 300 has pronounced leadership. We offer an explanation based on the measure of an indicator which quantifies the differences between spot and futures prices for the surge of lead-lag function. Our results provide new perspectives for the understanding of the dynamical evolution of lead-lag relationship between stock index and stock index futures, which is valuable for the study of market efficiency and its applications.

Urbanization and Income Inequality in Post-Reform China: A Causal Analysis Based on Time Series Data

PubMed Central

Chen, Guo; Glasmeier, Amy K.; Zhang, Min; Shao, Yang

2016-01-01

This paper investigates the potential causal relationship(s) between China’s urbanization and income inequality since the start of the economic reform. Based on the economic theory of urbanization and income distribution, we analyze the annual time series of China’s urbanization rate and Gini index from 1978 to 2014. The results show that urbanization has an immediate alleviating effect on income inequality, as indicated by the negative relationship between the two time series at the same year (lag = 0). However, urbanization also seems to have a lagged aggravating effect on income inequality, as indicated by positive relationship between urbanization and the Gini index series at lag 1. Although the link between urbanization and income inequality is not surprising, the lagged aggravating effect of urbanization on the Gini index challenges the popular belief that urbanization in post-reform China generally helps reduce income inequality. At deeper levels, our results suggest an urgent need to focus on the social dimension of urbanization as China transitions to the next stage of modernization. Comprehensive social reforms must be prioritized to avoid a long-term economic dichotomy and permanent social segregation. PMID:27433966

Urbanization and Income Inequality in Post-Reform China: A Causal Analysis Based on Time Series Data.

PubMed

Chen, Guo; Glasmeier, Amy K; Zhang, Min; Shao, Yang

2016-01-01

This paper investigates the potential causal relationship(s) between China's urbanization and income inequality since the start of the economic reform. Based on the economic theory of urbanization and income distribution, we analyze the annual time series of China's urbanization rate and Gini index from 1978 to 2014. The results show that urbanization has an immediate alleviating effect on income inequality, as indicated by the negative relationship between the two time series at the same year (lag = 0). However, urbanization also seems to have a lagged aggravating effect on income inequality, as indicated by positive relationship between urbanization and the Gini index series at lag 1. Although the link between urbanization and income inequality is not surprising, the lagged aggravating effect of urbanization on the Gini index challenges the popular belief that urbanization in post-reform China generally helps reduce income inequality. At deeper levels, our results suggest an urgent need to focus on the social dimension of urbanization as China transitions to the next stage of modernization. Comprehensive social reforms must be prioritized to avoid a long-term economic dichotomy and permanent social segregation.

Tracking of climatic niche boundaries under recent climate change.

PubMed

La Sorte, Frank A; Jetz, Walter

2012-07-01

1. Global climate has changed significantly during the past 30 years and especially in northern temperate regions which have experienced poleward shifts in temperature regimes. While there is evidence that some species have responded by moving their distributions to higher latitudes, the efficiency of this response in tracking species' climatic niche boundaries over time has yet to be addressed. 2. Here, we provide a continental assessment of the temporal structure of species responses to recent spatial shifts in climatic conditions. We examined geographic associations with minimum winter temperature for 59 species of winter avifauna at 476 Christmas Bird Count circles in North America from 1975 to 2009 under three sampling schemes that account for spatial and temporal sampling effects. 3. Minimum winter temperature associated with species occurrences showed an overall increase with a weakening trend after 1998. Species displayed highly variable responses that, on average and across sampling schemes, contained a strong lag effect that weakened in strength over time. In general, the conservation of minimum winter temperature was relevant when all species were considered together but only after an initial lag period (c. 35 years) was overcome. The delayed niche tracking observed at the combined species level was likely supported by the post1998 lull in the warming trend. 4. There are limited geographic and ecological explanations for the observed variability, suggesting that the efficiency of species' responses under climate change is likely to be highly idiosyncratic and difficult to predict. This outcome is likely to be even more pronounced and time lags more persistent for less vagile taxa, particularly during the periods of consistent or accelerating warming. Current modelling efforts and conservation strategies need to better appreciate the variation, strength and duration of lag effects and their association with climatic variability. Conservation strategies in particular will benefit through identifying and maintaining dispersal corridors that accommodate diverging dispersal strategies and timetables. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

An integrated error estimation and lag-aware data assimilation scheme for real-time flood forecasting

USDA-ARS?s Scientific Manuscript database

The performance of conventional filtering methods can be degraded by ignoring the time lag between soil moisture and discharge response when discharge observations are assimilated into streamflow modelling. This has led to the ongoing development of more optimal ways to implement sequential data ass...

Interfacial characteristics of hybrid nanocomposite under thermomechanical loading

NASA Astrophysics Data System (ADS)

Choyal, Vijay; Kundalwal, Shailesh I.

2017-12-01

In this work, an improved shear lag model was developed to investigate the interfacial characteristics of three-phase hybrid nanocomposite which is reinforced with microscale fibers augmented with carbon nanotubes on their circumferential surfaces. The shear lag model accounts for (i) radial and axial deformations of different transversely isotropic constituents, (ii) thermomechanical loads on the representative volume element (RVE), and (iii) staggering effect of adjacent RVEs. The results from the current newly developed shear lag model are validated with the finite element simulations and found to be in good agreement. This study reveals that the reduction in the maximum value of the axial stress in the fiber and the interfacial shear stress along its length become more pronounced in the presence of applied thermomechanical loads on the staggered RVEs. The existence of shear tractions along the RVE length plays a significant role in the interfacial characteristics and cannot be ignored.

Reverse Flood Routing with the Lag-and-Route Storage Model

NASA Astrophysics Data System (ADS)

Mazi, K.; Koussis, A. D.

2010-09-01

This work presents a method for reverse routing of flood waves in open channels, which is an inverse problem of the signal identification type. Inflow determination from outflow measurements is useful in hydrologic forensics and in optimal reservoir control, but has been seldom studied. Such problems are ill posed and their solution is sensitive to small perturbations present in the data, or to any related uncertainty. Therefore the major difficulty in solving this inverse problem consists in controlling the amplification of errors that inevitably befall flow measurements, from which the inflow signal is to be determined. The lag-and-route model offers a convenient framework for reverse routing, because not only is formal deconvolution not required, but also reverse routing is through a single linear reservoir. In addition, this inversion degenerates to calculating the intermediate inflow (prior to the lag step) simply as the sum of the outflow and of its time derivative multiplied by the reservoir’s time constant. The remaining time shifting (lag) of the intermediate, reversed flow presents no complications, as pure translation causes no error amplification. Note that reverse routing with the inverted Muskingum scheme (Koussis et al., submitted to the 12th Plinius Conference) fails when that scheme is specialised to the Kalinin-Miljukov model (linear reservoirs in series). The principal functioning of the reverse routing procedure was verified first with perfect field data (outflow hydrograph generated by forward routing of a known inflow hydrograph). The field data were then seeded with random error. To smooth the oscillations caused by the imperfect (measured) outflow data, we applied a multipoint Savitzky-Golay low-pass filter. The combination of reverse routing and filtering achieved an effective recovery of the inflow signal extremely efficiently. Specifically, we compared the reverse routing results of the inverted lag-and-route model and of the inverted Kalinin-Miljukov model. The latter applies the lag-and-route model’s single-reservoir inversion scheme sequentially to its cascade of linear reservoirs, the number of which is related to the stream's hydromorphology. For this purpose, we used the example of Bruen & Dooge (2007), who back-routed flow hydrographs in a 100-km long prismatic channel using a scheme for the reverse solution of the St. Venant equations of flood wave motion. The lag-and-route reverse routing model recovered the inflow hydrograph with comparable accuracy to that of the multi-reservoir, inverted Kalinin-Miljukov model, both performing as well as the box-scheme for reverse routing with the St. Venant equations. In conclusion, the success in the regaining of the inflow signal by the devised single-reservoir reverse routing procedure, with multipoint low-pass filtering, can be attributed to its simple computational structure that endows it with remarkable robustness and exceptional efficiency.

Factors determining dengue outbreak in Malaysia.

PubMed

Ahmad, Rohani; Suzilah, Ismail; Wan Najdah, Wan Mohamad Ali; Topek, Omar; Mustafakamal, Ibrahim; Lee, Han Lim

2018-01-01

A large scale study was conducted to elucidate the true relationship among entomological, epidemiological and environmental factors that contributed to dengue outbreak in Malaysia. Two large areas (Selayang and Bandar Baru Bangi) were selected in this study based on five consecutive years of high dengue cases. Entomological data were collected using ovitraps where the number of larvae was used to reflect Aedes mosquito population size; followed by RT-PCR screening to detect and serotype dengue virus in mosquitoes. Notified cases, date of disease onset, and number and type of the interventions were used as epidemiological endpoint, while rainfall, temperature, relative humidity and air pollution index (API) were indicators for environmental data. The field study was conducted during 81 weeks of data collection. Correlation and Autoregressive Distributed Lag Model were used to determine the relationship. The study showed that, notified cases were indirectly related with the environmental data, but shifted one week, i.e. last 3 weeks positive PCR; last 4 weeks rainfall; last 3 weeks maximum relative humidity; last 3 weeks minimum and maximum temperature; and last 4 weeks air pollution index (API), respectively. Notified cases were also related with next week intervention, while conventional intervention only happened 4 weeks after larvae were found, indicating ample time for dengue transmission. Based on a significant relationship among the three factors (epidemiological, entomological and environmental), estimated Autoregressive Distributed Lag (ADL) model for both locations produced high accuracy 84.9% for Selayang and 84.1% for Bandar Baru Bangi in predicting the actual notified cases. Hence, such model can be used in forestalling dengue outbreak and acts as an early warning system. The existence of relationships among the entomological, epidemiological and environmental factors can be used to build an early warning system for the prediction of dengue outbreak so that preventive interventions can be taken early to avert the outbreaks.

Associations between maternal weekly air pollutant exposures and low birth weight: a distributed lag non-linear model

NASA Astrophysics Data System (ADS)

Wu, Han; Jiang, Baofa; Zhu, Ping; Geng, Xingyi; Liu, Zhong; Cui, Liangliang; Yang, Liping

2018-02-01

When discussing the association between birth weight and air pollution, previous studies mainly focus on the maternal trimester-specific exposures during pregnancy, whereas the possible associations between birth weight and weekly-specific exposures have been largely neglected. We conducted a nested 1:4 matched case-control study in Jinan, China to examine the weekly-specific associations during pregnancy between maternal fine particulate matter (aerodynamic diameter < 2.5 μm, PM2.5), nitrogen dioxide (NO2), and sulfur dioxide (SO2) exposure and birth weight, which is under a representative scenario of very high pollution levels. Ambient air monitoring data from thirteen monitoring stations and daily mean temperature data for Jinan during 2013-2016 were continuously collected. Birth data were obtained from the largest maternity and child care hospital of this city during 2014-2016. Individual exposures to PM2.5, NO2, and SO2 during pregnancy were estimated using an inverse distance weighting method. Birth weight for gender-, gestational age-, and parity-specific standard score (BWGAP z-score) was calculated as the outcome of interest. Distributed lag non-linear models (DLNMs) were applied to estimate weekly-specific relationship between maternal air pollutant exposures and birth weight. For an increase of per inter-quartile range in maternal PM2.5 exposure concentration during pregnancy, the BWGAP z-score decreased significantly during the 27th-33th gestational weeks with the strongest association in the 30th gestational weeks (standard deviation units decrease in BWGAP z-score: -0.049, 95% CI: -0.080 -0.017, in three-pollutant model). No significant association between maternal weekly NO2 or SO2 BWGAP z-score was observed. In conclusion, this study provides evidence that maternal PM2.5 exposure during the 27th-33th gestational weeks may reduce the birth weight in the context of very high pollution level of PM2.5.

On the assumptions underlying milestoning.

PubMed

Vanden-Eijnden, Eric; Venturoli, Maddalena; Ciccotti, Giovanni; Elber, Ron

2008-11-07

Milestoning is a procedure to compute the time evolution of complicated processes such as barrier crossing events or long diffusive transitions between predefined states. Milestoning reduces the dynamics to transition events between intermediates (the milestones) and computes the local kinetic information to describe these transitions via short molecular dynamics (MD) runs between the milestones. The procedure relies on the ability to reinitialize MD trajectories on the milestones to get the right kinetic information about the transitions. It also rests on the assumptions that the transition events between successive milestones and the time lags between these transitions are statistically independent. In this paper, we analyze the validity of these assumptions. We show that sets of optimal milestones exist, i.e., sets such that successive transitions are indeed statistically independent. The proof of this claim relies on the results of transition path theory and uses the isocommittor surfaces of the reaction as milestones. For systems in the overdamped limit, we also obtain the probability distribution to reinitialize the MD trajectories on the milestones, and we discuss why this distribution is not available in closed form for systems with inertia. We explain why the time lags between transitions are not statistically independent even for optimal milestones, but we show that working with such milestones allows one to compute mean first passage times between milestones exactly. Finally, we discuss some practical implications of our results and we compare milestoning with Markov state models in view of our findings.

Modelling the influence of climate on malaria occurrence in Chimoio Municipality, Mozambique.

PubMed

Ferrão, João Luís; Mendes, Jorge M; Painho, Marco

2017-05-25

Mozambique was recently ranked fifth in the African continent for the number of cases of malaria. In Chimoio municipality cases of malaria are increasing annually, contrary to the decreasing trend in Africa. As malaria transmission is influenced to a large extent by climatic conditions, modelling this relationship can provide useful insights for designing precision health measures for malaria control. There is a scarcity of information on the association between climatic variability and malaria transmission risk in Mozambique in general, and in Chimoio in particular. Therefore, the aim of this study is to model the association between climatic variables and malaria cases on a weekly basis, to help policy makers find adequate measures for malaria control and eradication. Time series analysis was conducted using data on weekly climatic variables and weekly malaria cases (counts) in Chimoio municipality, from 2006 to 2014. All data were analysed using SPSS-20, R 3.3.2 and BioEstat 5.0. Cross-correlation analysis, linear processes, namely ARIMA models and regression modelling, were used to develop the final model. Between 2006 and 2014, 490,561 cases of malaria were recorded in Chimoio. Both malaria and climatic data exhibit weekly and yearly systematic fluctuations. Cross-correlation analysis showed that mean temperature and precipitation present significantly lagged correlations with malaria cases. An ARIMA model (2,1,0) (2,1,1) 52 , and a regression model for a Box-Cox transformed number of malaria cases with lags 1, 2 and 3 of weekly malaria cases and lags 6 and 7 of weekly mean temperature and lags 12 of precipitation were fitted. Although, both produced similar widths for prediction intervals, the last was able to anticipate malaria outbreak more accurately. The Chimoio climate seems ideal for malaria occurrence. Malaria occurrence peaks during January to March in Chimoio. As the lag effect between climatic events and malaria occurrence is important for the prediction of malaria cases, this can be used for designing public precision health measures. The model can be used for planning specific measures for Chimoio municipality. Prospective and multidisciplinary research involving researchers from different fields is welcomed to improve the effect of climatic factors and other factors in malaria cases.

Towards a threshold climate for emergency lower respiratory hospital admissions.

PubMed

Islam, Muhammad Saiful; Chaussalet, Thierry J; Koizumi, Naoru

2017-02-01

Identification of 'cut-points' or thresholds of climate factors would play a crucial role in alerting risks of climate change and providing guidance to policymakers. This study investigated a 'Climate Threshold' for emergency hospital admissions of chronic lower respiratory diseases by using a distributed lag non-linear model (DLNM). We analysed a unique longitudinal dataset (10 years, 2000-2009) on emergency hospital admissions, climate, and pollution factors for the Greater London. Our study extends existing work on this topic by considering non-linearity, lag effects between climate factors and disease exposure within the DLNM model considering B-spline as smoothing technique. The final model also considered natural cubic splines of time since exposure and 'day of the week' as confounding factors. The results of DLNM indicated a significant improvement in model fitting compared to a typical GLM model. The final model identified the thresholds of several climate factors including: high temperature (≥27°C), low relative humidity (≤ 40%), high Pm10 level (≥70-µg/m 3 ), low wind speed (≤ 2 knots) and high rainfall (≥30mm). Beyond the threshold values, a significantly higher number of emergency admissions due to lower respiratory problems would be expected within the following 2-3 days after the climate shift in the Greater London. The approach will be useful to initiate 'region and disease specific' climate mitigation plans. It will help identify spatial hot spots and the most sensitive areas and population due to climate change, and will eventually lead towards a diversified health warning system tailored to specific climate zones and populations. Copyright © 2016 Elsevier Inc. All rights reserved.

Ambient Ozone Pollution and Daily Mortality: A Nationwide Study in 272 Chinese Cities.

PubMed

Yin, Peng; Chen, Renjie; Wang, Lijun; Meng, Xia; Liu, Cong; Niu, Yue; Lin, Zhijing; Liu, Yunning; Liu, Jiangmei; Qi, Jinlei; You, Jinling; Zhou, Maigeng; Kan, Haidong

2017-11-21

Few large multicity studies have been conducted in developing countries to address the acute health effects of atmospheric ozone pollution. We explored the associations between ozone and daily cause-specific mortality in China. We performed a nationwide time-series analysis in 272 representative Chinese cities between 2013 and 2015. We used distributed lag models and over-dispersed generalized linear models to estimate the cumulative effects of ozone (lagged over 0-3 d) on mortality in each city, and we used hierarchical Bayesian models to combine the city-specific estimates. Regional, seasonal, and demographic heterogeneity were evaluated by meta-regression. At the national-average level, a 10-μg/m 3 increase in 8-h maximum ozone concentration was associated with 0.24% [95% posterior interval (PI): 0.13%, 0.35%], 0.27% (95% PI: 0.10%, 0.44%), 0.60% (95% PI: 0.08%, 1.11%), 0.24% (95% PI: 0.02%, 0.46%), and 0.29% (95% PI: 0.07%, 0.50%) higher daily mortality from all nonaccidental causes, cardiovascular diseases, hypertension, coronary diseases, and stroke, respectively. Associations between ozone and daily mortality due to respiratory and chronic obstructive pulmonary disease specifically were positive but imprecise and nonsignificant. There were no statistically significant differences in associations between ozone and nonaccidental mortality according to region, season, age, sex, or educational attainment. Our findings provide robust evidence of higher nonaccidental and cardiovascular mortality in association with short-term exposure to ambient ozone in China. https://doi.org/10.1289/EHP1849.

Determinants of Rotavirus Transmission: A Lag Nonlinear Time Series Analysis.

PubMed

van Gaalen, Rolina D; van de Kassteele, Jan; Hahné, Susan J M; Bruijning-Verhagen, Patricia; Wallinga, Jacco

2017-07-01

Rotavirus is a common viral infection among young children. As in many countries, the infection dynamics of rotavirus in the Netherlands are characterized by an annual winter peak, which was notably low in 2014. Previous study suggested an association between weather factors and both rotavirus transmission and incidence. From epidemic theory, we know that the proportion of susceptible individuals can affect disease transmission. We investigated how these factors are associated with rotavirus transmission in the Netherlands, and their impact on rotavirus transmission in 2014. We used available data on birth rates and rotavirus laboratory reports to estimate rotavirus transmission and the proportion of individuals susceptible to primary infection. Weather data were directly available from a central meteorological station. We developed an approach for detecting determinants of seasonal rotavirus transmission by assessing nonlinear, delayed associations between each factor and rotavirus transmission. We explored relationships by applying a distributed lag nonlinear regression model with seasonal terms. We corrected for residual serial correlation using autoregressive moving average errors. We inferred the relationship between different factors and the effective reproduction number from the most parsimonious model with low residual autocorrelation. Higher proportions of susceptible individuals and lower temperatures were associated with increases in rotavirus transmission. For 2014, our findings suggest that relatively mild temperatures combined with the low proportion of susceptible individuals contributed to lower rotavirus transmission in the Netherlands. However, our model, which overestimated the magnitude of the peak, suggested that other factors were likely instrumental in reducing the incidence that year.

The Weighted-Average Lagged Ensemble.

PubMed

DelSole, T; Trenary, L; Tippett, M K

2017-11-01

A lagged ensemble is an ensemble of forecasts from the same model initialized at different times but verifying at the same time. The skill of a lagged ensemble mean can be improved by assigning weights to different forecasts in such a way as to maximize skill. If the forecasts are bias corrected, then an unbiased weighted lagged ensemble requires the weights to sum to one. Such a scheme is called a weighted-average lagged ensemble. In the limit of uncorrelated errors, the optimal weights are positive and decay monotonically with lead time, so that the least skillful forecasts have the least weight. In more realistic applications, the optimal weights do not always behave this way. This paper presents a series of analytic examples designed to illuminate conditions under which the weights of an optimal weighted-average lagged ensemble become negative or depend nonmonotonically on lead time. It is shown that negative weights are most likely to occur when the errors grow rapidly and are highly correlated across lead time. The weights are most likely to behave nonmonotonically when the mean square error is approximately constant over the range forecasts included in the lagged ensemble. An extreme example of the latter behavior is presented in which the optimal weights vanish everywhere except at the shortest and longest lead times.

Does export product quality matter for CO2 emissions? Evidence from China.

PubMed

Gozgor, Giray; Can, Muhlis

2017-01-01

This paper re-estimates the environmental Kuznets curve (EKC) in China. To this end, it uses the unit root tests with structural breaks and the autoregressive-distributed lag (ARDL) estimations over the period 1971-2010. The special role is given to the impact of export product quality on CO 2 emissions in the empirical models. The paper finds that the EKC hypothesis is applicable in China. It also observes the positive effect from energy consumption to CO 2 emissions. In addition, it finds that the export product quality is negatively associated with CO 2 emissions. The paper also argues potential implications.

No evidence for the radiation time lag model after whole genome duplications in Teleostei

PubMed Central

Laurent, Sacha; Salamin, Nicolas

2017-01-01

The short and long term effects of polyploidization on the evolutionary fate of lineages is still unclear despite much interest. First recognized in land plants, it has become clear that polyploidization is widespread in eukaryotes, notably at the origin of vertebrates and teleost fishes. Many hypotheses have been proposed to link the species richness of lineages and whole genome duplications. For instance, the radiation time lag model suggests that paleopolyploidy would favour the apparition of new phenotypic traits, although the radiation of the lineage would not occur before a later dispersion event. Some results indicate that this model may be observed during land plant evolution. In this work, we test predictions of the radiation time lag model using both fossil data and molecular phylogenies in ancient and more recent teleost whole genome duplications. We fail to find any evidence of delayed increase of the species number after any of these events and conclude that paleopolyploidization still remains to be unambiguously linked to taxonomic diversity in teleosts. PMID:28426792

Can the relativistic light-bending model explain X-ray spectral variations of Seyfert galaxies?

NASA Astrophysics Data System (ADS)

Mizumoto, Misaki; Moriyama, Kotaro; Ebisawa, Ken; Mineshige, Shin; Kawanaka, Norita; Tsujimoto, Masahiro

2018-04-01

Many Seyfert galaxies are known to exhibit Fe-K broad emission line features in their X-ray energy spectra. The observed lines have three distinct features: (1) the line profiles are skewed and show significant low-energy tails, (2) the Fe-K band has low variability, which produces a broad and deep dip in the root-mean-square (rms) spectra, and (3) photons in this band have time lags behind those in the adjacent energy bands with amplitudes of several Rg/c, where Rg is the gravitational radius. The "relativistic light-bending model" is proposed to explain these observed features, where a compact X-ray source ("lamp post") above an extreme Kerr black hole illuminates the innermost area of the accretion disc. In this paper, we critically examine the relativistic light-bending model by computing the rms spectra and the lag features using a ray-tracing technique, when a lamp post moves vertically on the black hole spin axis. As a result, we found that the observed deep rms dip requires that the iron is extremely overabundant (≳10 solar), whereas the observed lag amplitude is consistent with the normal iron abundance. Furthermore, disappearance of the lag in the high-flux state requires a source height as high as ˜40 Rg, which contradicts the relativistically broad emission line feature. Our simulations agree with the data that the reverberation feature moves to lower frequencies with larger source height; however, if this scenario is correct, the simulations predict the detection of a clear Fe-K lag at low frequencies, which is not constrained in the data. Therefore, we conclude that the relativistic light-bending model may not explain the characteristic Fe-K spectral variations in Seyfert galaxies.

Can the relativistic light-bending model explain X-ray spectral variations of Seyfert galaxies?

NASA Astrophysics Data System (ADS)

Mizumoto, Misaki; Moriyama, Kotaro; Ebisawa, Ken; Mineshige, Shin; Kawanaka, Norita; Tsujimoto, Masahiro

2018-06-01

Many Seyfert galaxies are known to exhibit Fe-K broad emission line features in their X-ray energy spectra. The observed lines have three distinct features: (1) the line profiles are skewed and show significant low-energy tails, (2) the Fe-K band has low variability, which produces a broad and deep dip in the root-mean-square (rms) spectra, and (3) photons in this band have time lags behind those in the adjacent energy bands with amplitudes of several Rg/c, where Rg is the gravitational radius. The "relativistic light-bending model" is proposed to explain these observed features, where a compact X-ray source ("lamp post") above an extreme Kerr black hole illuminates the innermost area of the accretion disc. In this paper, we critically examine the relativistic light-bending model by computing the rms spectra and the lag features using a ray-tracing technique, when a lamp post moves vertically on the black hole spin axis. As a result, we found that the observed deep rms dip requires that the iron is extremely overabundant (≳10 solar), whereas the observed lag amplitude is consistent with the normal iron abundance. Furthermore, disappearance of the lag in the high-flux state requires a source height as high as ˜40 Rg, which contradicts the relativistically broad emission line feature. Our simulations agree with the data that the reverberation feature moves to lower frequencies with larger source height; however, if this scenario is correct, the simulations predict the detection of a clear Fe-K lag at low frequencies, which is not constrained in the data. Therefore, we conclude that the relativistic light-bending model may not explain the characteristic Fe-K spectral variations in Seyfert galaxies.

Distributed Modelling of Stormflow Generation: Assessing the Effect of Ground Cover

NASA Astrophysics Data System (ADS)

Jarihani, B.; Sidle, R. C.; Roth, C. H.; Bartley, R.; Wilkinson, S. N.

2017-12-01

Understanding the effects of grazing management and land cover changes on surface hydrology is important for water resources and land management. A distributed hydrological modelling platform, wflow, (that was developed as part of Deltares's OpenStreams project) is used to assess the effect of land management practices on runoff generation processes. The model was applied to Weany Creek, a small catchment (13.6 km2) of the Burdekin Basin, North Australia, which is being studied to understand sources of sediment and nutrients to the Great Barrier Reef. Satellite and drone-based ground cover data, high resolution topography from LiDAR, soil properties, and distributed rainfall data were used to parameterise the model. Wflow was used to predict total runoff, peak runoff, time of rise, and lag time for several events of varying magnitudes and antecedent moisture conditions. A nested approach was employed to calibrate the model by using recorded flow hydrographs at three scales: (1) a hillslope sub-catchment: (2) a gullied sub-catchment; and the 13.6 km2 catchment outlet. Model performance was evaluated by comparing observed and predicted stormflow hydrograph attributes using the Nash Sutcliffe efficiency metric. By using a nested approach, spatiotemporal patterns of overland flow occurrence across the catchment can also be evaluated. The results show that a process-based distributed model can be calibrated to simulate spatial and temporal patterns of runoff generation processes, to help identify dominant processes which may be addressed by land management to improve rainfall retention. The model will be used to assess the effects of ground cover changes due to management practices in grazed lands on storm runoff.

Comparison of long-term results between laparoscopy-assisted gastrectomy and open gastrectomy with D2 lymph node dissection for advanced gastric cancer.

PubMed

Hamabe, Atsushi; Omori, Takeshi; Tanaka, Koji; Nishida, Toshirou

2012-06-01

Laparoscopy-assisted gastrectomy (LAG) has been established as a low-invasive surgery for early gastric cancer. However, it remains unknown whether it is applicable also for advanced gastric cancer, mainly because the long-term results of LAG with D2 lymph node dissection for advanced gastric cancer have not been well validated compared with open gastrectomy (OG). A retrospective cohort study was performed to compare LAG and OG with D2 lymph node dissection. For this study, 167 patients (66 LAG and 101 OG patients) who underwent gastrectomy with D2 lymph node dissection for advanced gastric cancer were reviewed. Recurrence-free survival and overall survival time were estimated using Kaplan-Meier curves. Stratified log-rank statistical evaluation was used to compare the difference between the LAG and OG groups stratified by histologic type, pathologic T status, N status, and postoperative adjuvant chemotherapy. The adjusted Cox proportional hazards regression models were used to calculate the hazard ratios (HRs) of LAG. The 5-year recurrence-free survival rate was 89.6% in the LAG group and 75.8% in the OG group (nonsignificant difference; stratified log-rank statistic, 3.11; P = 0.0777). The adjusted HR of recurrence for LAG compared with OG was 0.389 [95% confidence interval (CI) 0.131-1.151]. The 5-year overall survival rate was 94.4% in the LAG group and 78.5% in the OG group (nonsignificant difference; stratified log-rank statistic, 0.4817; P = 0.4877). The adjusted HR of death for LAG compared with OG was 0.633 (95% CI 0.172-2.325). The findings show that LAG with D2 lymph node dissection is acceptable in terms of long-term results for advanced gastric cancer cases and may be applicable for advanced gastric cancer treatment.

Forecasting asthma-related hospital admissions in London using negative binomial models.

PubMed

Soyiri, Ireneous N; Reidpath, Daniel D; Sarran, Christophe

2013-05-01

Health forecasting can improve health service provision and individual patient outcomes. Environmental factors are known to impact chronic respiratory conditions such as asthma, but little is known about the extent to which these factors can be used for forecasting. Using weather, air quality and hospital asthma admissions, in London (2005-2006), two related negative binomial models were developed and compared with a naive seasonal model. In the first approach, predictive forecasting models were fitted with 7-day averages of each potential predictor, and then a subsequent multivariable model is constructed. In the second strategy, an exhaustive search of the best fitting models between possible combinations of lags (0-14 days) of all the environmental effects on asthma admission was conducted. Three models were considered: a base model (seasonal effects), contrasted with a 7-day average model and a selected lags model (weather and air quality effects). Season is the best predictor of asthma admissions. The 7-day average and seasonal models were trivial to implement. The selected lags model was computationally intensive, but of no real value over much more easily implemented models. Seasonal factors can predict daily hospital asthma admissions in London, and there is a little evidence that additional weather and air quality information would add to forecast accuracy.

Parent and Adolescent Distribution of Responsibility for Diabetes Self-care: Links to Health Outcomes

PubMed Central

Reynolds, Kerry A.; Siminerio, Linda; Escobar, Oscar; Becker, Dorothy

2008-01-01

Objective To examine the relation of adolescent and parent responsibility distribution for diabetes self-care to psychological and physical health. Methods We interviewed children (mean age 12 years) annually for 3 years and asked parents to complete a questionnaire. Both reported how diabetes self-care was distributed in the family. Amount of responsibility held by the child only, the parent only, and shared between child and parent was calculated. Psychological distress, competence, and diabetes outcomes were assessed at each wave. Results In both cross-sectional and longitudinal (lagged) analyses, multilevel modeling showed that shared responsibility was consistently associated with better psychological health, good self-care behavior, and good metabolic control, whereas child and parent responsibility were not. In some cases, links of shared responsibility to health outcomes were stronger among older adolescents. Conclusions These findings highlight the importance of shared responsibility for diabetes self-care through early to middle adolescence. PMID:17848390

Fuzzy model to estimate the number of hospitalizations for asthma and pneumonia under the effects of air pollution

PubMed Central

Chaves, Luciano Eustáquio; Nascimento, Luiz Fernando Costa; Rizol, Paloma Maria Silva Rocha

2017-01-01

ABSTRACT OBJECTIVE Predict the number of hospitalizations for asthma and pneumonia associated with exposure to air pollutants in the city of São José dos Campos, São Paulo State. METHODS This is a computational model using fuzzy logic based on Mamdani’s inference method. For the fuzzification of the input variables of particulate matter, ozone, sulfur dioxide and apparent temperature, we considered two relevancy functions for each variable with the linguistic approach: good and bad. For the output variable number of hospitalizations for asthma and pneumonia, we considered five relevancy functions: very low, low, medium, high and very high. DATASUS was our source for the number of hospitalizations in the year 2007 and the result provided by the model was correlated with the actual data of hospitalization with lag from zero to two days. The accuracy of the model was estimated by the ROC curve for each pollutant and in those lags. RESULTS In the year of 2007, 1,710 hospitalizations by pneumonia and asthma were recorded in São José dos Campos, State of São Paulo, with a daily average of 4.9 hospitalizations (SD = 2.9). The model output data showed positive and significant correlation (r = 0.38) with the actual data; the accuracies evaluated for the model were higher for sulfur dioxide in lag 0 and 2 and for particulate matter in lag 1. CONCLUSIONS Fuzzy modeling proved accurate for the pollutant exposure effects and hospitalization for pneumonia and asthma approach. PMID:28658366

Dynamic regimes of local homogeneous population model with time lag

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neverova, Galina; Frisman, Efim

We investigated Moran - Ricker model with time lag 1. It is made analytical and numerical study of the model. It is shown there is co-existence of various dynamic regimes under the same values of parameters. The model simultaneously possesses several different limit regimes: stable state, periodic fluctuations, and chaotic attractor. The research results show if present population size substantially depends on population number of previous year then it is observed quasi-periodic oscillations. Fluctuations with period 2 occur when the growth of population size is regulated by density dependence in the current year.

THE LICK AGN MONITORING PROJECT: BROAD-LINE REGION RADII AND BLACK HOLE MASSES FROM REVERBERATION MAPPING OF Hbeta

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bentz, Misty C.; Walsh, Jonelle L.; Barth, Aaron J.

2009-11-01

We have recently completed a 64-night spectroscopic monitoring campaign at the Lick Observatory 3-m Shane telescope with the aim of measuring the masses of the black holes in 12 nearby (z < 0.05) Seyfert 1 galaxies with expected masses in the range approx10{sup 6}-10{sup 7} M {sub sun} and also the well-studied nearby active galactic nucleus (AGN) NGC 5548. Nine of the objects in the sample (including NGC 5548) showed optical variability of sufficient strength during the monitoring campaign to allow for a time lag to be measured between the continuum fluctuations and the response to these fluctuations in themore » broad Hbeta emission. We present here the light curves for all the objects in this sample and the subsequent Hbeta time lags for the nine objects where these measurements were possible. The Hbeta lag time is directly related to the size of the broad-line region (BLR) in AGNs, and by combining the Hbeta lag time with the measured width of the Hbeta emission line in the variable part of the spectrum, we determine the virial mass of the central supermassive black hole in these nine AGNs. The absolute calibration of the black hole masses is based on the normalization derived by Onken et al., which brings the masses determined by reverberation mapping into agreement with the local M {sub BH}-sigma{sub *}relationship for quiescent galaxies. We also examine the time lag response as a function of velocity across the Hbeta line profile for six of the AGNs. The analysis of four leads to rather ambiguous results with relatively flat time lags as a function of velocity. However, SBS 1116+583A exhibits a symmetric time lag response around the line center reminiscent of simple models for circularly orbiting BLR clouds, and Arp 151 shows an asymmetric profile that is most easily explained by a simple gravitational infall model. Further investigation will be necessary to fully understand the constraints placed on the physical models of the BLR by the velocity-resolved response in these objects.« less

Discovery of a Time Lag between the Soft X-Ray and Radio Emission of the Tidal Disruption Flare ASASSN-14li: Evidence for Linear Disk–Jet Coupling

NASA Astrophysics Data System (ADS)

Pasham, Dheeraj R.; van Velzen, Sjoert

2018-03-01

The tidal disruption of a star by a supermassive black hole can result in transient radio emission. The electrons producing these synchrotron radio flares could either be accelerated inside a relativistic jet or externally by shocks resulting from an outflow interacting with the circumnuclear medium. Until now, evidence for the internal emission mechanism has been lacking; nearly all tidal disruption flare studies have adopted the external shock model to explain the observed properties of radio flares. Here we report a result that presents a challenge to external emission models: we discovered a cross-correlation between the soft X-ray (0.3–1 keV) and 16 GHz radio flux of the tidal disruption flare ASASSN-14li. Variability features in the X-ray light curve appear again in the radio light curve, but after a time lag of {12}-5+6 days. This demonstrates that the soft X-ray-emitting accretion disk regulates the radio emission. This coupling appears to be inconsistent with all previous external emission models for this source but is naturally explained if the radio emission originates from a freely expanding jet. We show that emission internal to an adiabatically expanding jet can also reproduce the observed evolution of the radio spectral energy distribution. Furthermore, both the correlation between X-ray and radio luminosity as well as our radio spectral modeling imply an approximately linear coupling between the accretion rate and jet power.

Association between air pollution and upper respiratory tract infection in hospital outpatients aged 0-14 years in Hefei, China: a time series study.

PubMed

Li, Y R; Xiao, C C; Li, J; Tang, J; Geng, X Y; Cui, L J; Zhai, J X

2018-03-01

To investigate the association between air pollution and upper respiratory tract infection (URTI) in children aged 0-14 years in Hefei, China in 2014-2015. An ecological method (i.e. generalised additive model [GAM]) was used to explore the effects of air pollutants on paediatric hospital outpatients with URTI. GAM was used to evaluate the lag effects (including lag0 to lag6, lag01 and lag06) between daily changes in particulate matter (PM 10 ), fine particulate matter (PM 2.5 ), sulphur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), ozone (O 3 ) and carbon monoxide (CO) and the number of hospital outpatients with URTI in 2014-2015, after controlling for the confounding effects of long-term trends, seasonality, day of the week, public holidays and meteorological factors. PM 10 , PM 2.5 , SO 2 , NO 2 and CO in the single-pollutant models had significant positive effects on the number of paediatric hospital outpatients with URTI. It was found that per 10 μg/m 3 increasing in concentrations of PM 10 at lag3, PM 2.5 , SO 2 , NO 2 and CO at lag06 were associated with an increase of Excess risk (ER) with 0.15% (95% CI: 0.07%∼0.23%), 0.38% (95% CI: 0.17%∼0.60%), 2.92% (95% CI: 1.88%∼3.97%), 4.47% (95% CI: 3.69%∼5.25%) and 0.05% (95% CI: 0.02%∼0.08%), respectively. Only NO 2 remained significantly positively associated with the number of hospital outpatients with URTI in the full-pollutant models, and ERs were 4.72% (95% CI = 3.76%-5.69%) and 4.70% (95% CI = 3.76%-5.65%) per 10 μg/m 3 increase in NO 2 in Model 1 (including PM10, SO 2 , NO 2 , O 3 and CO) and Model 2 (including PM 2.5 , SO 2 , NO 2 , O 3 and CO), respectively. This study showed that short-term exposure to air pollution was associated with increased risk of URTI among paediatric hospital outpatients aged 0-14 years in Hefei. NO 2 was the major air pollutant affecting the daily number of paediatric hospital outpatients with URTI. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Analysis and attenuation of artifacts caused by spatially and temporally correlated noise sources in Green's function estimates

NASA Astrophysics Data System (ADS)

Martin, E. R.; Dou, S.; Lindsey, N.; Chang, J. P.; Biondi, B. C.; Ajo Franklin, J. B.; Wagner, A. M.; Bjella, K.; Daley, T. M.; Freifeld, B. M.; Robertson, M.; Ulrich, C.; Williams, E. F.

2016-12-01

Localized strong sources of noise in an array have been shown to cause artifacts in Green's function estimates obtained via cross-correlation. Their effect is often reduced through the use of cross-coherence. Beyond independent localized sources, temporally or spatially correlated sources of noise frequently occur in practice but violate basic assumptions of much of the theory behind ambient noise Green's function retrieval. These correlated noise sources can occur in urban environments due to transportation infrastructure, or in areas around industrial operations like pumps running at CO2 sequestration sites or oil and gas drilling sites. Better understanding of these artifacts should help us develop and justify methods for their automatic removal from Green's function estimates. We derive expected artifacts in cross-correlations from several distributions of correlated noise sources including point sources that are exact time-lagged repeats of each other and Gaussian-distributed in space and time with covariance that exponentially decays. Assuming the noise distribution stays stationary over time, the artifacts become more coherent as more ambient noise is included in the Green's function estimates. We support our results with simple computational models. We observed these artifacts in Green's function estimates from a 2015 ambient noise study in Fairbanks, AK where a trenched distributed acoustic sensing (DAS) array was deployed to collect ambient noise alongside a road with the goal of developing a permafrost thaw monitoring system. We found that joints in the road repeatedly being hit by cars travelling at roughly the speed limit led to artifacts similar to those expected when several points are time-lagged copies of each other. We also show test results of attenuating the effects of these sources during time-lapse monitoring of an active thaw test in the same location with noise detected by a 2D trenched DAS array.

Evaluation of a Game-Based Simulation During Distributed Exercises

DTIC Science & Technology

2010-09-01

the management team guiding development of the software. The questionnaires have not been used enough to collect data sufficient for factor...capable of internationally distributed exercises without excessive time lags or technical problems, given that commercial games seem to manage while...established by RDECOM-STTC military liaison and managers . Engineering constraints combined to limit the number of participants and the possible roles that

Vector Autoregression, Structural Equation Modeling, and Their Synthesis in Neuroimaging Data Analysis

PubMed Central

Chen, Gang; Glen, Daniel R.; Saad, Ziad S.; Hamilton, J. Paul; Thomason, Moriah E.; Gotlib, Ian H.; Cox, Robert W.

2011-01-01

Vector autoregression (VAR) and structural equation modeling (SEM) are two popular brain-network modeling tools. VAR, which is a data-driven approach, assumes that connected regions exert time-lagged influences on one another. In contrast, the hypothesis-driven SEM is used to validate an existing connectivity model where connected regions have contemporaneous interactions among them. We present the two models in detail and discuss their applicability to FMRI data, and interpretational limits. We also propose a unified approach that models both lagged and contemporaneous effects. The unifying model, structural vector autoregression (SVAR), may improve statistical and explanatory power, and avoids some prevalent pitfalls that can occur when VAR and SEM are utilized separately. PMID:21975109

LAG3 expression in active Mycobacterium tuberculosis infections.

PubMed

Phillips, Bonnie L; Mehra, Smriti; Ahsan, Muhammad H; Selman, Moises; Khader, Shabaana A; Kaushal, Deepak

2015-03-01

Mycobacterium tuberculosis (MTB) is a highly successful pathogen because of its ability to persist in human lungs for long periods of time. MTB modulates several aspects of the host immune response. Lymphocyte-activation gene 3 (LAG3) is a protein with a high affinity for the CD4 receptor and is expressed mainly by regulatory T cells with immunomodulatory functions. To understand the function of LAG3 during MTB infection, a nonhuman primate model of tuberculosis, which recapitulates key aspects of natural human infection in rhesus macaques (Macaca mulatta), was used. We show that the expression of LAG3 is highly induced in the lungs and particularly in the granulomatous lesions of macaques experimentally infected with MTB. Furthermore, we show that LAG3 expression is not induced in the lungs and lung granulomas of animals exhibiting latent tuberculosis infection. However, simian immunodeficiency virus-induced reactivation of latent tuberculosis infection results in an increased expression of LAG3 in the lungs. This response is not observed in nonhuman primates infected with non-MTB bacterial pathogens, nor with simian immunodeficiency virus alone. Our data show that LAG3 was expressed primarily on CD4(+) T cells, presumably by regulatory T cells but also by natural killer cells. The expression of LAG3 coincides with high bacterial burdens and changes in the host type 1 helper T-cell response. Copyright © 2015 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Temporal evolution of photon energy emitted from two-component advective flows: origin of time lag

NASA Astrophysics Data System (ADS)

Chatterjee, Arka; Chakrabarti, Sandip K.; Ghosh, Himadri

2017-12-01

X-ray time lag of black hole candidates contains important information regarding the emission geometry. Recently, study of time lags from observational data revealed very intriguing properties. To investigate the real cause of this lag behavior with energy and spectral states, we study photon paths inside a two-component advective flow (TCAF) which appears to be a satisfactory model to explain the spectral and timing properties. We employ the Monte Carlo simulation technique to carry out the Comptonization process. We use a relativistic thick disk in Schwarzschild geometry as the CENtrifugal pressure supported BOundary Layer (CENBOL) which is the Compton cloud. In TCAF, this is the post-shock region of the advective component. Keplerian disk on the equatorial plane which is truncated at the inner edge i.e. at the outer boundary of the CENBOL, acts as the soft photon source. Ray-tracing code is employed to track the photons to a distantly located observer. We compute the cumulative time taken by a photon during Comptonization, reflection and following the curved geometry on the way to the observer. Time lags between various hard and soft bands have been calculated. We study the variation of time lags with accretion rates, CENBOL size and inclination angle. Time lags for different energy channels are plotted for different inclination angles. The general trend of variation of time lag with QPO frequency and energy as observed in satellite data is reproduced.

In Situ Strength Model for Continuous Fibers and Multi-Scale Modeling the Fracture of C/SiC Composites

NASA Astrophysics Data System (ADS)

Zhang, Sheng; Gao, Xiguang; Song, Yingdong

2018-04-01

A new in situ strength model of carbon fibers was developed based on the distribution of defects to predict the stress-strain response and the strength of C/SiC composites. Different levels of defects in the fibers were considered in this model. The defects in the fibers were classified by their effects on the strength of the fiber. The strength of each defect and the probability that the defect appears were obtained from the tensile test of single fibers. The strength model of carbon fibers was combined with the shear-lag model to predict the stress-strain responses and the strengths of fiber bundles and C/SiC minicomposites. To verify the strength model, tensile tests were performed on fiber bundles and C/SiC minicomposites. The predicted and experimental results were in good agreement. Effects of the fiber length, the fiber number and the heat treatment on the final strengths of fiber bundles and C/SiC minicomposites were also discussed.

Lagged correlations between the NAO and the 11-year solar cycle: forced response or internal variability?

NASA Astrophysics Data System (ADS)

Oehrlein, J.; Chiodo, G.; Polvani, L. M.; Smith, A. K.

2017-12-01

Recently, the North Atlantic Oscillation has been suggested to respond to the 11-year solar cycle with a lag of a few years. The solar/NAO relationship provides a potential pathway for solar activity to modulate surface climate. However, a short observational record paired with the strong internal variability of the NAO raises questions about the robustness of the claimed solar/NAO relationship. For the first time, we investigate the robustness of the solar/NAO signal in four different reanalysis data sets and long integrations from an ocean-coupled chemistry-climate model forced with the 11-year solar cycle. The signal appears to be robust in the different reanalysis datasets. We also show, for the first time, that many features of the observed signal, such as amplitude, spatial pattern, and lag of 2/3 years, can be accurately reproduced in our model simulations. However, in both the reanalysis and model simulations, we find that this signal is non-stationary. A lagged NAO/solar signal can also be reproduced in two sets of model integrations without the 11-year solar cycle. This suggests that the correlation found in observational data could be the result of internal decadal variability in the NAO and not a response to the solar cycle. This has wide implications towards the interpretation of solar signals in observational data.

Associations of PM2.5 and Black Carbon with Hospital Emergency Room Visits during Heavy Haze Events: A Case Study in Beijing, China

PubMed Central

Liang, Fengchao; Tian, Lin; Guo, Qun; Westerdahl, Dane; Jin, Xiaobin; Li, Guoxing; Pan, Xiaochuan

2017-01-01

In January 2013, severe haze events over northeastern China sparked substantial health concerns. This study explores the associations of fine particulate matter less than 2.5 μm (PM2.5) and black carbon (BC) with hospital emergency room visits (ERVs) during a haze season in Beijing. During that period, daily counts of ERVs for respiratory, cardiovascular and ocular diseases were obtained from a Level-3A hospital in Beijing from 1 December 2012 to 28 February 2013, and associations of which with PM2.5 and BC were estimated by time-stratified case-crossover analysis in single- and two-pollutant models. We found a 27.5% (95% confidence interval (CI): 13.0, 43.9%) increase in respiratory ERV (lag02), a 19.4% (95% CI: 2.5, 39.0%) increase in cardiovascular ERV (lag0), and a 12.6% (95% CI: 0.0, 26.7%) increase in ocular ERV (lag0) along with an interquartile range (IQR) increase in the PM2.5. An IQR increase of BC was associated with 27.6% (95% CI: 9.6, 48.6%) (lag02), 18.8% (95% CI: 1.4, 39.2%) (lag0) and 11.8% (95% CI: −1.4, 26.8%) (lag0) increases for changes in these same health outcomes respectively. Estimated associations were consistent after adjusting SO2 or NO2 in two-pollutant models. This study provides evidence that improving air quality and reducing haze days would greatly benefit the population health. PMID:28678202

Associations of PM2.5 and Black Carbon with Hospital Emergency Room Visits during Heavy Haze Events: A Case Study in Beijing, China.

PubMed

Liang, Fengchao; Tian, Lin; Guo, Qun; Westerdahl, Dane; Liu, Yang; Jin, Xiaobin; Li, Guoxing; Pan, Xiaochuan

2017-07-05

In January 2013, severe haze events over northeastern China sparked substantial health concerns. This study explores the associations of fine particulate matter less than 2.5 μm (PM 2.5 ) and black carbon (BC) with hospital emergency room visits (ERVs) during a haze season in Beijing. During that period, daily counts of ERVs for respiratory, cardiovascular and ocular diseases were obtained from a Level-3A hospital in Beijing from 1 December 2012 to 28 February 2013, and associations of which with PM 2.5 and BC were estimated by time-stratified case-crossover analysis in single- and two-pollutant models. We found a 27.5% (95% confidence interval (CI): 13.0, 43.9%) increase in respiratory ERV (lag02), a 19.4% (95% CI: 2.5, 39.0%) increase in cardiovascular ERV (lag0), and a 12.6% (95% CI: 0.0, 26.7%) increase in ocular ERV (lag0) along with an interquartile range (IQR) increase in the PM 2.5 . An IQR increase of BC was associated with 27.6% (95% CI: 9.6, 48.6%) (lag02), 18.8% (95% CI: 1.4, 39.2%) (lag0) and 11.8% (95% CI: -1.4, 26.8%) (lag0) increases for changes in these same health outcomes respectively. Estimated associations were consistent after adjusting SO₂ or NO₂ in two-pollutant models. This study provides evidence that improving air quality and reducing haze days would greatly benefit the population health.

TEMPORAL VARIABILITY FROM THE TWO-COMPONENT ADVECTIVE FLOW SOLUTION AND ITS OBSERVATIONAL EVIDENCE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dutta, Broja G.; Chakrabarti, Sandip K.

2016-09-10

In the propagating oscillatory shock model, the oscillation of the post-shock region, i.e., the Compton cloud, causes the observed low-frequency quasi-periodic oscillations (QPOs). The evolution of QPO frequency is explained by the systematic variation of the Compton cloud size, i.e., the steady radial movement of the shock front, which is triggered by the cooling of the post-shock region. Thus, analysis of the energy-dependent temporal properties in different variability timescales can diagnose the dynamics and geometry of accretion flows around black holes. We study these properties for the high-inclination black hole source XTE J1550-564 during its 1998 outburst and the low-inclinationmore » black hole source GX 339-4 during its 2006–07 outburst using RXTE /PCA data, and we find that they can satisfactorily explain the time lags associated with the QPOs from these systems. We find a smooth decrease of the time lag as a function of time in the rising phase of both sources. In the declining phase, the time lag increases with time. We find a systematic evolution of QPO frequency and hard lags in these outbursts. In XTE J1550-564, the lag changes from hard to soft (i.e., from a positive to a negative value) at a crossing frequency (ν {sub c}) of ∼3.4 Hz. We present possible mechanisms to explain the lag behavior of high and low-inclination sources within the framework of a single two-component advective flow model.« less

Revisiting the generalized scaling law for adhesion: role of compliance and extension to progressive failure.

PubMed

Mojdehi, Ahmad R; Holmes, Douglas P; Dillard, David A

2017-10-25

A generalized scaling law, based on the classical fracture mechanics approach, is developed to predict the bond strength of adhesive systems. The proposed scaling relationship depends on the rate of change of debond area with compliance, rather than the ratio of area to compliance. This distinction can have a profound impact on the expected bond strength of systems, particularly when the failure mechanism changes or the compliance of the load train increases. Based on the classical fracture mechanics approach for rate-independent materials, the load train compliance should not affect the force capacity of the adhesive system, whereas when the area to compliance ratio is used as the scaling parameter, it directly influences the bond strength, making it necessary to distinguish compliance contributions. To verify the scaling relationship, single lap shear tests were performed for a given pressure sensitive adhesive (PSA) tape specimens with different bond areas, number of backing layers, and load train compliance. The shear lag model was used to derive closed-form relationships for the system compliance and its derivative with respect to the debond area. Digital image correlation (DIC) is implemented to verify the non-uniform shear stress distribution obtained from the shear lag model in a lap shear geometry. The results obtained from this approach could lead to a better understanding of the relationship between bond strength and the geometry and mechanical properties of adhesive systems.

Impact of temperature variation between adjacent days on childhood hand, foot and mouth disease during April and July in urban and rural Hefei, China

NASA Astrophysics Data System (ADS)

Cheng, Jian; Zhu, Rui; Xu, Zhiwei; Wu, Jinju; Wang, Xu; Li, Kesheng; Wen, Liying; Yang, Huihui; Su, Hong

2016-06-01

Previous studies have found that both high temperature and low temperature increase the risk of childhood hand, foot and mouth disease (HFMD). However, little is known about whether temperature variation between neighboring days has any effects on childhood HFMD. A Poisson generalized linear regression model, combined with a distributed lag non-linear model, was applied to examine the relationship between temperature change and childhood HFMD in Hefei, China, from 1st January 2010 to 31st December 2012. Temperature change was defined as the difference of current day's mean temperature and previous day's mean temperature. Late spring and early summer (April-July) were chosen as the main study period due to it having the highest childhood HFMD incidence. There was a statistical association between temperature change between neighboring days and childhood HFMD. The effects of temperature change on childhood HFMD increased below a temperature change of 0 °C (temperature drop). The temperature change has the greatest adverse effect on childhood HFMD at 7 days lag, with 4 % (95 % confidence interval 2-7 %) increase per 3 °C drop of temperature. Male children and urban children appeared to be more vulnerable to the effects of temperature change. Temperature change between adjacent days might be an alternative temperature indictor for exploring the temperature-HFMD relationship.

Impact of temperature variation between adjacent days on childhood hand, foot and mouth disease during April and July in urban and rural Hefei, China.

PubMed

Cheng, Jian; Zhu, Rui; Xu, Zhiwei; Wu, Jinju; Wang, Xu; Li, Kesheng; Wen, Liying; Yang, Huihui; Su, Hong

2016-06-01

Previous studies have found that both high temperature and low temperature increase the risk of childhood hand, foot and mouth disease (HFMD). However, little is known about whether temperature variation between neighboring days has any effects on childhood HFMD. A Poisson generalized linear regression model, combined with a distributed lag non-linear model, was applied to examine the relationship between temperature change and childhood HFMD in Hefei, China, from 1st January 2010 to 31st December 2012. Temperature change was defined as the difference of current day's mean temperature and previous day's mean temperature. Late spring and early summer (April-July) were chosen as the main study period due to it having the highest childhood HFMD incidence. There was a statistical association between temperature change between neighboring days and childhood HFMD. The effects of temperature change on childhood HFMD increased below a temperature change of 0 °C (temperature drop). The temperature change has the greatest adverse effect on childhood HFMD at 7 days lag, with 4 % (95 % confidence interval 2-7 %) increase per 3 °C drop of temperature. Male children and urban children appeared to be more vulnerable to the effects of temperature change. Temperature change between adjacent days might be an alternative temperature indictor for exploring the temperature-HFMD relationship.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jiali; Swati, F. N. U.; Stein, Michael L.

Regional climate models (RCMs) are a standard tool for downscaling climate forecasts to finer spatial scales. The evaluation of RCMs against observational data is an important step in building confidence in the use of RCMs for future prediction. In addition to model performance in climatological means and marginal distributions, a model’s ability to capture spatio-temporal relationships is important. This study develops two approaches: (1) spatial correlation/variogram for a range of spatial lags, with total monthly precipitation and non-seasonal precipitation components used to assess the spatial variations of precipitation; and (2) spatio-temporal correlation for a wide range of distances, directions, andmore » time lags, with daily precipitation occurrence used to detect the dynamic features of precipitation. These measures of spatial and spatio-temporal dependence are applied to a high-resolution RCM run and to the National Center for Environmental Prediction (NCEP)-U.S. Department of Energy (DOE) AMIP II reanalysis data (NCEP-R2), which provides initial and lateral boundary conditions for the RCM. The RCM performs better than NCEP-R2 in capturing both the spatial variations of total and non-seasonal precipitation components and the spatio-temporal correlations of daily precipitation occurrences, which are related to dynamic behaviors of precipitating systems. The improvements are apparent not just at resolutions finer than that of NCEP-R2, but also when the RCM and observational data are aggregated to the resolution of NCEP-R2.« less

Assessing weather effects on dengue disease in Malaysia.

PubMed

Cheong, Yoon Ling; Burkart, Katrin; Leitão, Pedro J; Lakes, Tobia

2013-11-26

The number of dengue cases has been increasing on a global level in recent years, and particularly so in Malaysia, yet little is known about the effects of weather for identifying the short-term risk of dengue for the population. The aim of this paper is to estimate the weather effects on dengue disease accounting for non-linear temporal effects in Selangor, Kuala Lumpur and Putrajaya, Malaysia, from 2008 to 2010. We selected the weather parameters with a Poisson generalized additive model, and then assessed the effects of minimum temperature, bi-weekly accumulated rainfall and wind speed on dengue cases using a distributed non-linear lag model while adjusting for trend, day-of-week and week of the year. We found that the relative risk of dengue cases is positively associated with increased minimum temperature at a cumulative percentage change of 11.92% (95% CI: 4.41-32.19), from 25.4 °C to 26.5 °C, with the highest effect delayed by 51 days. Increasing bi-weekly accumulated rainfall had a positively strong effect on dengue cases at a cumulative percentage change of 21.45% (95% CI: 8.96, 51.37), from 215 mm to 302 mm, with the highest effect delayed by 26-28 days. The wind speed is negatively associated with dengue cases. The estimated lagged effects can be adapted in the dengue early warning system to assist in vector control and prevention plan.

Spatial analysis of highway incident durations in the context of Hurricane Sandy.

PubMed

Xie, Kun; Ozbay, Kaan; Yang, Hong

2015-01-01

The objectives of this study are (1) to develop an incident duration model which can account for the spatial dependence of duration observations, and (2) to investigate the impacts of a hurricane on incident duration. Highway incident data from New York City and its surrounding regions before and after Hurricane Sandy was used for the study. Moran's I statistics confirmed that durations of the neighboring incidents were spatially correlated. Moreover, Lagrange Multiplier tests suggested that the spatial dependence should be captured in a spatial lag specification. A spatial error model, a spatial lag model and a standard model without consideration of spatial effects were developed. The spatial lag model is found to outperform the others by capturing the spatial dependence of incident durations via a spatially lagged dependent variable. It was further used to assess the effects of hurricane-related variables on incident duration. The results show that the incidents during and post the hurricane are expected to have 116.3% and 79.8% longer durations than those that occurred in the regular time. However, no significant increase in incident duration is observed in the evacuation period before Sandy's landfall. Results of temporal stability tests further confirm the existence of the significant changes in incident duration patterns during and post the hurricane. Those findings can provide insights to aid in the development of hurricane evacuation plans and emergency management strategies. Copyright © 2014 Elsevier Ltd. All rights reserved.

BIODEGRADATION DURING CONTAMINANT TRANSPORT IN POROUS MEDIA. 4. IMPACT OF MICROBIAL LAG AND BACTERIAL CELL GROWTH. (R825415)

EPA Science Inventory

Abstract

Miscible-displacement experiments were conducted to examine the impact of microbial lag and bacterial cell growth on the transport of salicylate, a model hydrocarbon compound. The impacts of these processes were examined separately, as well as jointly, to dete...

Increases in external cause mortality due to high and low temperatures: evidence from northeastern Europe

NASA Astrophysics Data System (ADS)

Orru, Hans; Åström, Daniel Oudin

2017-05-01

The relationship between temperature and mortality is well established but has seldom been investigated in terms of external causes. In some Eastern European countries, external cause mortality is substantial. Deaths owing to external causes are the third largest cause of mortality in Estonia, after cardiovascular disease and cancer. Death rates owing to external causes may reflect behavioural changes among a population. The aim for the current study was to investigate if there is any association between temperature and external cause mortality, in Estonia. We collected daily information on deaths from external causes (ICD-10 diagnosis codes V00-Y99) and maximum temperatures over the period 1997-2013. The relationship between daily maximum temperature and mortality was investigated using Poisson regression, combined with a distributed lag non-linear model considering lag times of up to 10 days. We found significantly higher mortality owing to external causes on hot (the same and previous day) and cold days (with a lag of 1-3 days). The cumulative relative risks for heat (an increase in temperature from the 75th to 99th percentile) were 1.24 (95% confidence interval, 1.14-1.34) and for cold (a decrease from the 25th to 1st percentile) 1.19 (1.03-1.38). Deaths due to external causes might reflect changes in behaviour among a population during periods of extreme hot and cold temperatures and should therefore be investigated further, because such deaths have a severe impact on public health, especially in Eastern Europe where external mortality rates are high.

Effects of diurnal variations in temperature on non-accidental mortality among the elderly population of Montreal, Québec, 1984-2007.

PubMed

Vutcovici, Maria; Goldberg, Mark S; Valois, Marie-France

2014-07-01

The association between ambient temperature and mortality has been studied extensively. Recent data suggest an independent role of diurnal temperature variations in increasing daily mortality. Elderly adults-a growing subgroup of the population in developed countries-may be more susceptible to the effects of temperature variations. The aim of this study was to determine whether variations in diurnal temperature were associated with daily non-accidental mortality among residents of Montreal, Québec, who were 65 years of age and over during the period between 1984 and 2007. We used distributed lag non-linear Poisson models constrained over a 30-day lag period, adjusted for temporal trends, mean daily temperature, and mean daily concentrations of nitrogen dioxide and ozone to estimate changes in daily mortality with diurnal temperature. We found, over the 30 day lag period, a cumulative increase in daily mortality of 5.12% [95% confidence interval (CI): 0.02-10.49%] for a change from 5.9 °C to 11.1 °C (25th to 75th percentiles) in diurnal temperature, and a 11.27% (95%CI: 2.08-21.29%) increase in mortality associated with an increase of diurnal temperature from 11.1 to 17.5 °C (75th to 99th percentiles). The results were relatively robust to adjustment for daily mean temperature. We found that, in Montreal, diurnal variations in temperature are associated with a small increase in non-accidental mortality among the elderly population. More studies are needed in different geographical locations to confirm this effect.

Phase lags of quasi-periodic oscillations across source states in the low-mass X-ray binary 4U 1636-53

NASA Astrophysics Data System (ADS)

de Avellar, Marcio G. B.

2017-06-01

The majority of attempts to explain the origin and phenomenology of the quasi-periodic oscillations (QPOs) detected in low-mass X-ray binaries invoke dynamical models, and it was just in recent years that renewed attention has been given on how radiative processes occurring in these extreme environments gives rise to the variability features observed in the X-ray light curves of these systems. The study of the dependence of the phase lags upon the energy and frequency of the QPOs is a step towards this end. The methodology we developed here allowed us to study for the first time these dependencies for all QPOs detected in the range of 1 to 1300 Hz in the low-mass X-ray binary 4U 1636-53 as the source changes its state during its cycle in the colour-colour diagram. Our results suggest that within the context of models of up-scattering Comptonization, the phase lags dependencies upon frequency and energy can be used to extract size scales and physical conditions of the medium that produces the lags.

Toward comparing experiment and theory for corroborative research on hingeless rotor stability in forward flight

NASA Technical Reports Server (NTRS)

Gaonkar, G.

1987-01-01

For flap lag stability of isolated rotors, experimental and analytical investigations were conducted in hover and forward flight on the adequacy of a linear quasisteady aerodynamics theory with dynamic flow. Forward flight effects on lag regressing mode were emphasized. A soft inplane hingeless rotor with three blades was tested at advance ratios as high as 0.55 and at shaft angles as high as 20 deg. The 1.62 m model rotor was untrimmed with an essentially unrestricted tilt of the tip path plane. In combination with lag natural frequencies, collective pitch settings and flap lag coupling parameters, the data base comprises nearly 1200 test points (damping and frequency) in forward flight and 200 test points in hover. By computerized symbolic manipulation, a linear model was developed in substall to predict stability margins with mode identification. To help explain the correlation between theory and data it also predicted substall and stall regions of the rotor disk from equilibrium values. The correlation showed both the strengths and weaknesses of the theory in substall ((angle of attack) equal to or less than 12 deg).

The self adapting washer for lag screw fixation of mandibular fractures: finite element analysis and preclinical evaluation.

PubMed

Terheyden, H; Mühlendyck, C; Feldmann, H; Ludwig, K; Härle, F

1999-02-01

Besides rigid fixation, lag screws have distinct advantages compared with plates in appropriate indications in mandibular fractures. However, in current lag screw systems, the relatively small area of the screw head has to transfer the tensile force which can exceed 1000 N in the symphysis, to the thin cortical bone plate. Countersinking, which is obligatory in most systems, will weaken the cortical plate. Finite element analysis (FEA) revealed that load in this situation can exceed the normal tensile strength of metal and bone. Consequently, a new washer was constructed which both increased the supporting surface and did not require countersinking. The washer is self adapting (SAW) to the cortical plate in a defined position, forming a ball and socket joint with the screw head. Using the FEA model, a ten-fold reduction in load on bone and metal was observed with the new washer. In a miniature pig mandibular symphysis fracture model, the clinical applicability and a favourable histological reaction were demonstrated, compared with conventional lag screw designs.

Modeling seasonal leptospirosis transmission and its association with rainfall and temperature in Thailand using time-series and ARIMAX analyses.

PubMed

Chadsuthi, Sudarat; Modchang, Charin; Lenbury, Yongwimon; Iamsirithaworn, Sopon; Triampo, Wannapong

2012-07-01

To study the number of leptospirosis cases in relations to the seasonal pattern, and its association with climate factors. Time series analysis was used to study the time variations in the number of leptospirosis cases. The Autoregressive Integrated Moving Average (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest, namely the northern and northeastern region of Thailand, while the temperature played a role in the northeastern region only. The use of multivariate ARIMA (ARIMAX) model showed that factoring in rainfall (with an 8 months lag) yields the best model for the northern region while the model, which factors in rainfall (with a 10 months lag) and temperature (with an 8 months lag) was the best for the northeastern region. The models are able to show the trend in leptospirosis cases and closely fit the recorded data in both regions. The models can also be used to predict the next seasonal peak quite accurately. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

Characterizing rainfall of hot arid region by using time-series modeling and sustainability approaches: a case study from Gujarat, India

NASA Astrophysics Data System (ADS)

Machiwal, Deepesh; Kumar, Sanjay; Dayal, Devi

2016-05-01

This study aimed at characterization of rainfall dynamics in a hot arid region of Gujarat, India by employing time-series modeling techniques and sustainability approach. Five characteristics, i.e., normality, stationarity, homogeneity, presence/absence of trend, and persistence of 34-year (1980-2013) period annual rainfall time series of ten stations were identified/detected by applying multiple parametric and non-parametric statistical tests. Furthermore, the study involves novelty of proposing sustainability concept for evaluating rainfall time series and demonstrated the concept, for the first time, by identifying the most sustainable rainfall series following reliability ( R y), resilience ( R e), and vulnerability ( V y) approach. Box-whisker plots, normal probability plots, and histograms indicated that the annual rainfall of Mandvi and Dayapar stations is relatively more positively skewed and non-normal compared with that of other stations, which is due to the presence of severe outlier and extreme. Results of Shapiro-Wilk test and Lilliefors test revealed that annual rainfall series of all stations significantly deviated from normal distribution. Two parametric t tests and the non-parametric Mann-Whitney test indicated significant non-stationarity in annual rainfall of Rapar station, where the rainfall was also found to be non-homogeneous based on the results of four parametric homogeneity tests. Four trend tests indicated significantly increasing rainfall trends at Rapar and Gandhidham stations. The autocorrelation analysis suggested the presence of persistence of statistically significant nature in rainfall series of Bhachau (3-year time lag), Mundra (1- and 9-year time lag), Nakhatrana (9-year time lag), and Rapar (3- and 4-year time lag). Results of sustainability approach indicated that annual rainfall of Mundra and Naliya stations ( R y = 0.50 and 0.44; R e = 0.47 and 0.47; V y = 0.49 and 0.46, respectively) are the most sustainable and dependable compared with that of other stations. The highest values of sustainability index at Mundra (0.120) and Naliya (0.112) stations confirmed the earlier findings of R y- R e- V y approach. In general, annual rainfall of the study area is less reliable, less resilient, and moderately vulnerable, which emphasizes the need of developing suitable strategies for managing water resources of the area on sustainable basis. Finally, it is recommended that multiple statistical tests (at least two) should be used in time-series modeling for making reliable decisions. Moreover, methodology and findings of the sustainability concept in rainfall time series can easily be adopted in other arid regions of the world.

Effect of Nozzle Nonlinearities upon Nonlinear Stability of Liquid Propellant Rocket Motors

NASA Technical Reports Server (NTRS)

Padmanabhan, M. S.; Powell, E. A.; Zinn, B. T.

1975-01-01

A three dimensional, nonlinear nozzle admittance relation is developed by solving the wave equation describing finite amplitude oscillatory flow inside the subsonic portion of a choked, slowly convergent axisymmetric nozzle. This nonlinear nozzle admittance relation is then used as a boundary condition in the analysis of nonlinear combustion instability in a cylindrical liquid rocket combustor. In both nozzle and chamber analyses solutions are obtained using the Galerkin method with a series expansion consisting of the first tangential, second tangential, and first radial modes. Using Crocco's time lag model to describe the distributed unsteady combustion process, combustion instability calculations are presented for different values of the following parameters: (1) time lag, (2) interaction index, (3) steady-state Mach number at the nozzle entrance, and (4) chamber length-to-diameter ratio. In each case, limit cycle pressure amplitudes and waveforms are shown for both linear and nonlinear nozzle admittance conditions. These results show that when the amplitudes of the second tangential and first radial modes are considerably smaller than the amplitude of the first tangential mode the inclusion of nozzle nonlinearities has no significant effect on the limiting amplitude and pressure waveforms.

Adaptation, migration or extirpation: climate change outcomes for tree populations

PubMed Central

Aitken, Sally N; Yeaman, Sam; Holliday, Jason A; Wang, Tongli; Curtis-McLane, Sierra

2008-01-01

Abstract Species distribution models predict a wholesale redistribution of trees in the next century, yet migratory responses necessary to spatially track climates far exceed maximum post-glacial rates. The extent to which populations will adapt will depend upon phenotypic variation, strength of selection, fecundity, interspecific competition, and biotic interactions. Populations of temperate and boreal trees show moderate to strong clines in phenology and growth along temperature gradients, indicating substantial local adaptation. Traits involved in local adaptation appear to be the product of small effects of many genes, and the resulting genotypic redundancy combined with high fecundity may facilitate rapid local adaptation despite high gene flow. Gene flow with preadapted alleles from warmer climates may promote adaptation and migration at the leading edge, while populations at the rear will likely face extirpation. Widespread species with large populations and high fecundity are likely to persist and adapt, but will likely suffer adaptational lag for a few generations. As all tree species will be suffering lags, interspecific competition may weaken, facilitating persistence under suboptimal conditions. Species with small populations, fragmented ranges, low fecundity, or suffering declines due to introduced insects or diseases should be candidates for facilitated migration. PMID:25567494

Investigating effects of hydroxypropyl methylcellulose (HPMC) molecular weight grades on lag time of press-coated ethylcellulose tablets.

PubMed

Patadia, Riddhish; Vora, Chintan; Mittal, Karan; Mashru, Rajashree

2016-11-01

The research undertaken exemplifies the effects of hydroxypropyl methylcellulose (HPMC) molecular weight (MW) grades of on lag time of press-coated ethylcellulose (EC) tablets. The formulation comprised an immediate release core (containing prednisone as a model drug) surrounded by compression coating with variegated EC-HPMC blends. Five selected HPMC grades (E5, E15, E50, K100LV and K4M) were explored at three different concentrations (10% w/w, 20% w/w and 30% w/w in outer coat) to understand their effects on lag time and drug release. In vitro drug release testing demonstrated that, with increase in concentration of E5 and E15, up to 30% w/w, the mean lag time decreased progressively; whereas with remaining grades, the mean lag time initially decreased up to 20% w/w level and thereafter increased for 30% w/w level. Importantly, with increase in HPMC concentration in the outer coat, the variability in lag time (%RSD; n = 6) was decreased for each of E5, E15 and E50, whereas increased for K100LV and K4M. In general, the variability in lag time was increased with increase in HPMC MW at studied concentration levels. Markedly, tablets with 30% w/w K4M in outer coat exhibited slight premature release (before the rupture of outer coat) along with high variability in lag time. Overall, the study concluded that low MW HPMCs (E5, E15 and E50) were found rather efficient than higher MW HPMCs for developing robust EC-based press-coated pulsatile release formulations where precise lag time followed by sharp burst release is desired.

Effect of environmental factors on the kinetics of insulin fibril formation: elucidation of the molecular mechanism.

PubMed

Nielsen, L; Khurana, R; Coats, A; Frokjaer, S; Brange, J; Vyas, S; Uversky, V N; Fink, A L

2001-05-22

In the search for the molecular mechanism of insulin fibrillation, the kinetics of insulin fibril formation were studied under different conditions using the fluorescent dye thioflavin T (ThT). The effect of insulin concentration, agitation, pH, ionic strength, anions, seeding, and addition of 1-anilinonaphthalene-8-sulfonic acid (ANS), urea, TMAO, sucrose, and ThT on the kinetics of fibrillation was investigated. The kinetics of the fibrillation process could be described by the lag time for formation of stable nuclei (nucleation) and the apparent rate constant for the growth of fibrils (elongation). The addition of seeds eliminated the lag phase. An increase in insulin concentration resulted in shorter lag times and faster growth of fibrils. Shorter lag times and faster growth of fibrils were seen at acidic pH versus neutral pH, whereas an increase in ionic strength resulted in shorter lag times and slower growth of fibrils. There was no clear correlation between the rate of fibril elongation and ionic strength. Agitation during fibril formation attenuated the effects of insulin concentration and ionic strength on both lag times and fibril growth. The addition of ANS increased the lag time and decreased the apparent growth rate for insulin fibril formation. The ANS-induced inhibition appears to reflect the formation of amorphous aggregates. The denaturant, urea, decreased the lag time, whereas the stabilizers, trimethylamine N-oxide dihydrate (TMAO) and sucrose, increased the lag times. The results indicated that both nucleation and fibril growth were controlled by hydrophobic and electrostatic interactions. A kinetic model, involving the association of monomeric partially folded intermediates, whose concentration is stimulated by the air-water interface, leading to formation of the critical nucleus and thence fibrils, is proposed.

[Fine particulate matter estimated by mathematical model and hospitalizations for pneumonia and asthma in children].

PubMed

César, Ana Cristina Gobbo; Nascimento, Luiz Fernando Costa; Mantovani, Katia Cristina Cota; Pompeo Vieira, Luciana Cristina

2016-01-01

To estimate the association between exposure to fine particulate matter with an aerodynamic diameter <2.5 microns (PM2.5) and hospitalizations for pneumonia and asthma in children. An ecological study of time series was performed, with daily indicators of hospitalization for pneumonia and asthma in children up to 10 years of age, living in Taubaté (SP) and estimated concentrations of PM2.5, between August 2011 and July 2012. A generalized additive model of Poisson regression was used to estimate the relative risk, with lag zero up to five days after exposure; the single pollutant model was adjusted by the apparent temperature, as defined from the temperature and relative air humidity, seasonality and weekday. The values of the relative risks for hospitalization for pneumonia and asthma were significant for lag 0 (RR=1.051, 95%CI; 1.016 to 1.088); lag 2 (RR=1.066, 95%CI: 1.023 to 1.113); lag 3 (RR=1.053, 95%CI: 1.015 to 1.092); lag 4 (RR=1.043, 95%CI: 1.004 to 1.088) and lag 5 (RR=1.061, 95%CI: 1.018 to 1.106). The increase of 5mcg/m(3) in PM2.5 contributes to increase the relative risk for hospitalization from 20.3 to 38.4 percentage points; however, the reduction of 5μg/m(3) in PM2.5 concentration results in 38 fewer hospital admissions. Exposure to PM2.5 was associated with hospitalizations for pneumonia and asthma in children younger than 10 years of age, showing the role of fine particulate matter in child health and providing subsidies for the implementation of preventive measures to decrease these outcomes. Copyright © 2015 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

Dynamic response of induced pressures, suckdown, and temperatures for two tandem jet STOVL configurations

NASA Technical Reports Server (NTRS)

Wardwell, Douglas A.; Corsiglia, Victor R.; Kuhn, Richard E.

1992-01-01

NASA Ames Research Center has been conducting a program to improve the methods for predicting the jet-induced lift loss (suckdown) and hot gas ingestion on jet Short Takeoff and Vertical Landing (STOVL) aircraft during hover near the ground. As part of that program, small-scale hover tests were conducted to expand the current data base and to improve upon the current empirical methods for predicting jet-induced lift loss and hot gas ingestion (HGI) effects. This report is one of three data reports covering data obtained from hover tests conducted at Lockheed Aeronautical Systems, Rye Canyon Facility. It will include dynamic (time dependent) test data for both lift loss and HGI parameters (height, nozzle temperature, nozzle pressure ratio, and inlet location). The flat plate models tested were tandem jet configurations with three planform variations and variable position side-by-side sucking inlets mounted above the planform. Temperature time lags from 8-15 seconds were observed before the model temperatures stabilize. This was larger than the expected 1.5-second lag calculated from literature. Several possible explanations for the flow temperatures to stabilize may include some, or all, of the following: thermocouple lag, radiation to the model surface, and heat loss to the ground board. Further investigations are required to understand the reasons for this temperature lag.

TIDAL DISSIPATION COMPARED TO SEISMIC DISSIPATION: IN SMALL BODIES, EARTHS, AND SUPER-EARTHS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Efroimsky, Michael, E-mail: michael.efroimsky@usno.navy.mil

2012-02-20

While the seismic quality factor and phase lag are defined solely by the bulk properties of the mantle, their tidal counterparts are determined by both the bulk properties and the size effect (self-gravitation of a body as a whole). For a qualitative estimate, we model the body with a homogeneous sphere, and express the tidal phase lag through the lag in a sample of material. Although simplistic, our model is sufficient to understand that the lags are not identical. The difference emerges because self-gravitation pulls the tidal bulge down. At low frequencies, this reduces strain and the damping rate, makingmore » tidal damping less efficient in larger objects. At higher frequencies, competition between self-gravitation and rheology becomes more complex, though for sufficiently large super-Earths the same rule applies: the larger the planet, the weaker the tidal dissipation in it. Being negligible for small terrestrial planets and moons, the difference between the seismic and tidal lagging (and likewise between the seismic and tidal damping) becomes very considerable for large exoplanets (super-Earths). In those, it is much lower than what one might expect from using a seismic quality factor. The tidal damping rate deviates from the seismic damping rate, especially in the zero-frequency limit, and this difference takes place for bodies of any size. So the equal in magnitude but opposite in sign tidal torques, exerted on one another by the primary and the secondary, have their orbital averages going smoothly through zero as the secondary crosses the synchronous orbit. We describe the mantle rheology with the Andrade model, allowing it to lean toward the Maxwell model at the lowest frequencies. To implement this additional flexibility, we reformulate the Andrade model by endowing it with a free parameter {zeta} which is the ratio of the anelastic timescale to the viscoelastic Maxwell time of the mantle. Some uncertainty in this parameter's frequency dependence does not influence our principal conclusions.« less

Shear-lag effect and its effect on the design of high-rise buildings

NASA Astrophysics Data System (ADS)

Thanh Dat, Bui; Traykov, Alexander; Traykova, Marina

2018-03-01

For super high-rise buildings, the analysis and selection of suitable structural solutions are very important. The structure has not only to carry the gravity loads (self-weight, live load, etc.), but also to resist lateral loads (wind and earthquake loads). As the buildings become taller, the demand on different structural systems dramatically increases. The article considers the division of the structural systems of tall buildings into two main categories - interior structures for which the major part of the lateral load resisting system is located within the interior of the building, and exterior structures for which the major part of the lateral load resisting system is located at the building perimeter. The basic types of each of the main structural categories are described. In particular, the framed tube structures, which belong to the second main category of exterior structures, seem to be very efficient. That type of structure system allows tall buildings resist the lateral loads. However, those tube systems are affected by shear lag effect - a nonlinear distribution of stresses across the sides of the section, which is commonly found in box girders under lateral loads. Based on a numerical example, some general conclusions for the influence of the shear-lag effect on frequencies, periods, distribution and variation of the magnitude of the internal forces in the structure are presented.

Time-series analysis of weather and mortality patterns in Nairobi's informal settlements

PubMed Central

Egondi, Thaddaeus; Kyobutungi, Catherine; Kovats, Sari; Muindi, Kanyiva; Ettarh, Remare; Rocklöv, Joacim

2012-01-01

Background Many studies have established a link between weather (primarily temperature) and daily mortality in developed countries. However, little is known about this relationship in urban populations in sub-Saharan Africa. Objectives The objective of this study was to describe the relationship between daily weather and mortality in Nairobi, Kenya, and to evaluate this relationship with regard to cause of death, age, and sex. Methods We utilized mortality data from the Nairobi Urban Health and Demographic Surveillance System and applied time-series models to study the relationship between daily weather and mortality for a population of approximately 60,000 during the period 2003–2008. We used a distributed lag approach to model the delayed effect of weather on mortality, stratified by cause of death, age, and sex. Results Increasing temperatures (above 75th percentile) were significantly associated with mortality in children and non-communicable disease (NCD) deaths. We found all-cause mortality of shorter lag of same day and previous day to increase by 3.0% for a 1 degree decrease from the 25th percentile of 18°C (not statistically significant). Mortality among people aged 50+ and children aged below 5 years appeared most susceptible to cold compared to other age groups. Rainfall, in the lag period of 0–29 days, increased all-cause mortality in general, but was found strongest related to mortality among females. Low temperatures were associated with deaths due to acute infections, whereas rainfall was associated with all-cause pneumonia and NCD deaths. Conclusions Increases in mortality were associated with both hot and cold weather as well as rainfall in Nairobi, but the relationship differed with regard to age, sex, and cause of death. Our findings indicate that weather-related mortality is a public health concern for the population in the informal settlements of Nairobi, Kenya, especially if current trends in climate change continue. PMID:23195509

Precipitation Effects on Microbial Pollution in a River: Lag Structures and Seasonal Effect Modification

PubMed Central

Tornevi, Andreas; Bergstedt, Olof; Forsberg, Bertil

2014-01-01

Background The river Göta Älv is a source of freshwater for 0.7 million swedes. The river is subject to contamination from sewer systems discharge and runoff from agricultural lands. Climate models projects an increase in precipitation and heavy rainfall in this region. This study aimed to determine how daily rainfall causes variation in indicators of pathogen loads, to increase knowledge of variations in river water quality and discuss implications for risk management. Methods Data covering 7 years of daily monitoring of river water turbidity and concentrations of E. coli, Clostridium and coliforms were obtained, and their short-term variations in relation with precipitation were analyzed with time series regression and non-linear distributed lag models. We studied how precipitation effects varied with season and compared different weather stations for predictive ability. Results Generally, the lowest raw water quality occurs 2 days after rainfall, with poor raw water quality continuing for several more days. A rainfall event of >15 mm/24-h (local 95 percentile) was associated with a three-fold higher concentration of E. coli and 30% higher turbidity levels (lag 2). Rainfall was associated with exponential increases in concentrations of indicator bacteria while the effect on turbidity attenuated with very heavy rainfall. Clear associations were also observed between consecutive days of wet weather and decreased water quality. The precipitation effect on increased levels of indicator bacteria was significant in all seasons. Conclusions Rainfall elevates microbial risks year-round in this river and freshwater source and acts as the main driver of varying water quality. Heavy rainfall appears to be a better predictor of fecal pollution than water turbidity. An increase of wet weather and extreme events with climate change will lower river water quality even more, indicating greater challenges for drinking water producers, and suggesting better control of sources of pollution. PMID:24874010

Effects of temperature on mortality in Chiang Mai city, Thailand: a time series study

PubMed Central

2012-01-01

Background The association between temperature and mortality has been examined mainly in North America and Europe. However, less evidence is available in developing countries, especially in Thailand. In this study, we examined the relationship between temperature and mortality in Chiang Mai city, Thailand, during 1999–2008. Method A time series model was used to examine the effects of temperature on cause-specific mortality (non-external, cardiopulmonary, cardiovascular, and respiratory) and age-specific non-external mortality (<=64, 65–74, 75–84, and > =85 years), while controlling for relative humidity, air pollution, day of the week, season and long-term trend. We used a distributed lag non-linear model to examine the delayed effects of temperature on mortality up to 21 days. Results We found non-linear effects of temperature on all mortality types and age groups. Both hot and cold temperatures resulted in immediate increase in all mortality types and age groups. Generally, the hot effects on all mortality types and age groups were short-term, while the cold effects lasted longer. The relative risk of non-external mortality associated with cold temperature (19.35°C, 1st percentile of temperature) relative to 24.7°C (25th percentile of temperature) was 1.29 (95% confidence interval (CI): 1.16, 1.44) for lags 0–21. The relative risk of non-external mortality associated with high temperature (31.7°C, 99th percentile of temperature) relative to 28°C (75th percentile of temperature) was 1.11 (95% CI: 1.00, 1.24) for lags 0–21. Conclusion This study indicates that exposure to both hot and cold temperatures were related to increased mortality. Both cold and hot effects occurred immediately but cold effects lasted longer than hot effects. This study provides useful data for policy makers to better prepare local responses to manage the impact of hot and cold temperatures on population health. PMID:22613086

Aggregation of model amyloid insulin protein in crowding environments and under ac-electric fields

NASA Astrophysics Data System (ADS)

Zheng, Zhongli; Jing, Benxin; Murray, Brian; Sorci, Mirco; Belfort, Georges; Zhu, Y.

2013-03-01

In vitro experiments have been widely used to characterize the misfolding/unfolding pathway characteristic of amylodogenic proteins. Conversion from natively folded amyloidogenic proteins to oligomers via nucleation is the accepted path to fibril formation upon heating over a certain lag time period. In this work, we investigate the effect of crowing environment and external electric fields on the pathway and kinetics of insulin, a well-established amyloid model protein by single fluorescence spectroscopy and imaging. With added co-solutes, such as glycerol and polyvinylpyrrolidone (PVP), to mimic the cellular crowding environments, we have observed that the lag time can be significantly prolonged. The lag time increases with increasing co-solute concentration, yet showing little dependence on solution viscosity. Conversely, applied ac-electric fields can considerably shorten the lag timewhen a critical ac-voltage is exceeded. The strong dependence of lag time on ac-frequency over a narrow range of 500 Hz-5 kHz indicates the effect of ac-electroosmosis on the diffusion controlled process of insulin nucleation. Yet, no conformational structure is detected with insulin under applied ac-fields, suggesting the equivalence of ac-polarization to the conventional thermal activation process for insulin aggregation. These finding suggest that at least the aggregation kinetics of insulin can be altered by local solution condition or external stimuli, which gives new insight to the treatment of amyloid related diseases.

Effective contaminant detection networks in uncertain groundwater flow fields.

PubMed

Hudak, P F

2001-01-01

A mass transport simulation model tested seven contaminant detection-monitoring networks under a 40 degrees range of groundwater flow directions. Each monitoring network contained five wells located 40 m from a rectangular landfill. The 40-m distance (lag) was measured in different directions, depending upon the strategy used to design a particular monitoring network. Lagging the wells parallel to the central flow path was more effective than alternative design strategies. Other strategies allowed higher percentages of leaks to migrate between monitoring wells. Results of this study suggest that centrally lagged groundwater monitoring networks perform most effectively in uncertain groundwater-flow fields.

Modeling optical and UV polarization of AGNs. IV. Polarization timing

NASA Astrophysics Data System (ADS)

Rojas Lobos, P. A.; Goosmann, R. W.; Marin, F.; Savić, D.

2018-03-01

Context. Optical observations cannot resolve the structure of active galactic nuclei (AGN), and a unified model for AGN was inferred mostly from indirect methods, such as spectroscopy and variability studies. Optical reverberation mapping allowed us to constrain the spatial dimension of the broad emission line region and thereby to measure the mass of supermassive black holes. Recently, reverberation was also applied to the polarized signal emerging from different AGN components. In principle, this should allow us to measure the spatial dimensions of the sub-parsec reprocessing media. Aim. We conduct numerical modeling of polarization reverberation and provide theoretical predictions for the polarization time lag induced by different AGN components. The model parameters are adjusted to the observational appearance of the Seyfert 1 galaxy NGC 4151. Methods: We modeled scattering-induced polarization and tested different geometries for the circumnuclear dust component. Our tests included the effects of clumpiness and different dust prescriptions. To further extend the model, we also explored the effects of additional ionized winds stretched along the polar direction, and of an equatorial scattering ring that is responsible for the polarization angle observed in pole-on AGN. The simulations were run using a time-dependent version of the STOKES code. Results: Our modeling confirms the previously found polarization characteristics as a function of the observer`s viewing angle. When the dust adopts a flared-disk geometry, the lags reveal a clear difference between type 1 and type 2 AGN. This distinction is less clear for a torus geometry where the time lag is more sensitive to the geometry and optical depth of the inner surface layers of the funnel. The presence of a scattering equatorial ring and ionized outflows increased the recorded polarization time lags, and the polar outflows smooths out dependence on viewing angle, especially for the higher optical depth of the wind (τ = 0.3). Conclusions: Together with other AGN observables, the polarization time lag places new, independent "seismological" constraints on the inner geometry of AGN. If we conduct time-dependent spectropolarimetric observing campaigns of AGN, this method has a high potential for a census of supermassive black holes.

Drought prediction using co-active neuro-fuzzy inference system, validation, and uncertainty analysis (case study: Birjand, Iran)

NASA Astrophysics Data System (ADS)

Memarian, Hadi; Pourreza Bilondi, Mohsen; Rezaei, Majid

2016-08-01

This work aims to assess the capability of co-active neuro-fuzzy inference system (CANFIS) for drought forecasting of Birjand, Iran through the combination of global climatic signals with rainfall and lagged values of Standardized Precipitation Index (SPI) index. Using stepwise regression and correlation analyses, the signals NINO 1 + 2, NINO 3, Multivariate Enso Index, Tropical Southern Atlantic index, Atlantic Multi-decadal Oscillation index, and NINO 3.4 were recognized as the effective signals on the drought event in Birjand. Based on the results from stepwise regression analysis and regarding the processor limitations, eight models were extracted for further processing by CANFIS. The metrics P-factor and D-factor were utilized for uncertainty analysis, based on the sequential uncertainty fitting algorithm. Sensitivity analysis showed that for all models, NINO indices and rainfall variable had the largest impact on network performance. In model 4 (as the model with the lowest error during training and testing processes), NINO 1 + 2(t-5) with an average sensitivity of 0.7 showed the highest impact on network performance. Next, the variables rainfall, NINO 1 + 2(t), and NINO 3(t-6) with the average sensitivity of 0.59, 0.28, and 0.28, respectively, could have the highest effect on network performance. The findings based on network performance metrics indicated that the global indices with a time lag represented a better correlation with El Niño Southern Oscillation (ENSO). Uncertainty analysis of the model 4 demonstrated that 68 % of the observed data were bracketed by the 95PPU and D-Factor value (0.79) was also within a reasonable range. Therefore, the fourth model with a combination of the input variables NINO 1 + 2 (with 5 months of lag and without any lag), monthly rainfall, and NINO 3 (with 6 months of lag) and correlation coefficient of 0.903 (between observed and simulated SPI) was selected as the most accurate model for drought forecasting using CANFIS in the climatic region of Birjand.

Stochastic models for regulatory networks of the genetic toggle switch.

PubMed

Tian, Tianhai; Burrage, Kevin

2006-05-30

Bistability arises within a wide range of biological systems from the lambda phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks.

Stochastic models for regulatory networks of the genetic toggle switch

PubMed Central

Tian, Tianhai; Burrage, Kevin

2006-01-01

Bistability arises within a wide range of biological systems from the λ phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. In this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks. PMID:16714385

Individual Differences in Working-Memory Capacity and Task Resumption Following Interruptions

ERIC Educational Resources Information Center

Foroughi, Cyrus K.; Werner, Nicole E.; McKendrick, Ryan; Cades, David M.; Boehm-Davis, Deborah A.

2016-01-01

Previous research has shown that there is a time cost (i.e., a resumption lag) associated with resuming a task following an interruption and that the longer the duration of the interruption, the greater the time cost (i.e., resumption lag increases as interruption duration increases). The memory-for-goals model (Altmann & Trafton, 2002)…

Academic Self-Concept and Achievement in Polish Primary Schools: Cross-Lagged Modelling and Gender-Specific Effects

ERIC Educational Resources Information Center

Grygiel, Pawel; Modzelewski, Michal; Pisarek, Jolanta

2017-01-01

This study reports relationships between general academic self-concept and achievement in grade 3 and grade 5. Gender-specific effects were investigated using a longitudinal, two-cycle, 3-year autoregressive cross-lagged panel design in a large, representative sample of Polish primary school pupils (N = 4,226). Analysis revealed (a) reciprocal…

Black Hole Variability in MHD: A Numerical Test of the Propagating Fluctuations Model

NASA Astrophysics Data System (ADS)

Hogg, J. Drew; Reynolds, Christopher S.

2017-08-01

The variability properties of accreting black hole systems offer a crucial probe of the accretion physics providing the angular momentum transport and enabling the mass accretion. A few of the most telling signatures are the characteristic log-normal flux distributions, linear RMS-flux relations, and frequency-dependent time lags between energy bands. These commonly observed properties are often interpreted as evidence of inward propagating mass accretion rate fluctuations where fluctuations in the accretion flow combine multiplicatively. We present recent results from a long, semi-global MHD simulation of a thin (h/r=0.1) accretion disk that naturally reproduces this phenomenology. This bolsters the theoretical underpinnings of the “propagating fluctuations” model and demonstrates the viability of this process manifesting in MHD turbulence driven by the magnetorotational instability. We find that a key ingredient to this model is the modulation of the effective α parameter by the magnetic dynamo.

The dynamic relationship between health expenditure and economic growth: is the health-led growth hypothesis valid for Turkey?

PubMed

Atilgan, Emre; Kilic, Dilek; Ertugrul, Hasan Murat

2017-06-01

The well-known health-led growth hypothesis claims a positive correlation between health expenditure and economic growth. The aim of this paper is to empirically investigate the health-led growth hypothesis for the Turkish economy. The bound test approach, autoregressive-distributed lag approach (ARDL) and Kalman filter modeling are employed for the 1975-2013 period to examine the co-integration relationship between economic growth and health expenditure. The ARDL model is employed in order to investigate the long-term and short-term static relationship between health expenditure and economic growth. The results show that a 1 % increase in per-capita health expenditure will lead to a 0.434 % increase in per-capita gross domestic product. These findings are also supported by the Kalman filter model's results. Our findings show that the health-led growth hypothesis is supported for Turkey.

Early biometric lag in the prediction of small for gestational age neonates and preeclampsia.

PubMed

Schwartz, Nadav; Pessel, Cara; Coletta, Jaclyn; Krieger, Abba M; Timor-Tritsch, Ilan E

2011-01-01

An early fetal growth lag may be a marker of future complications. We sought to determine the utility of early biometric variables in predicting adverse pregnancy outcomes. In this retrospective cohort study, the crown-rump length at 11 to 14 weeks and the head circumference, biparietal diameter, abdominal circumference, femur length, humerus length, transverse cerebellar diameter, and estimated fetal weight at 18 to 24 weeks were converted to an estimated gestational age using published regression formulas. Sonographic fetal growth (difference between each biometric gestational age and the crown-rump length gestational age) minus expected fetal growth (number of days elapsed between the two scans) yielded the biometric growth lag. These lags were tested as predictors of small for gestational age (SGA) neonates (≤10th percentile) and preeclampsia. A total of 245 patients were included. Thirty-two (13.1%) delivered an SGA neonate, and 43 (17.6%) had the composite outcome. The head circumference, biparietal diameter, abdominal circumference, and estimated fetal weight lags were identified as significant predictors of SGA neonates after adjusted analyses (P < .05). The addition of either the estimated fetal weight or abdominal circumference lag to maternal characteristics alone significantly improved the performance of the predictive model, achieving areas under the curve of 0.72 and 0.74, respectively. No significant association was found between the biometric lag variables and the development of preeclampsia. Routinely available biometric data can be used to improve the prediction of adverse outcomes such as SGA. These biometric lags should be considered in efforts to develop screening algorithms for adverse outcomes.

Evaluation of the impacts of climate change on disease vectors through ecological niche modelling.

PubMed

Carvalho, B M; Rangel, E F; Vale, M M

2017-08-01

Vector-borne diseases are exceptionally sensitive to climate change. Predicting vector occurrence in specific regions is a challenge that disease control programs must meet in order to plan and execute control interventions and climate change adaptation measures. Recently, an increasing number of scientific articles have applied ecological niche modelling (ENM) to study medically important insects and ticks. With a myriad of available methods, it is challenging to interpret their results. Here we review the future projections of disease vectors produced by ENM, and assess their trends and limitations. Tropical regions are currently occupied by many vector species; but future projections indicate poleward expansions of suitable climates for their occurrence and, therefore, entomological surveillance must be continuously done in areas projected to become suitable. The most commonly applied methods were the maximum entropy algorithm, generalized linear models, the genetic algorithm for rule set prediction, and discriminant analysis. Lack of consideration of the full-known current distribution of the target species on models with future projections has led to questionable predictions. We conclude that there is no ideal 'gold standard' method to model vector distributions; researchers are encouraged to test different methods for the same data. Such practice is becoming common in the field of ENM, but still lags behind in studies of disease vectors.

Anticipated and zero-lag synchronization in motifs of delay-coupled systems

NASA Astrophysics Data System (ADS)

Mirasso, Claudio R.; Carelli, Pedro V.; Pereira, Tiago; Matias, Fernanda S.; Copelli, Mauro

2017-11-01

Anticipated and zero-lag synchronization have been observed in different scientific fields. In the brain, they might play a fundamental role in information processing, temporal coding and spatial attention. Recent numerical work on anticipated and zero-lag synchronization studied the role of delays. However, an analytical understanding of the conditions for these phenomena remains elusive. In this paper, we study both phenomena in systems with small delays. By performing a phase reduction and studying phase locked solutions, we uncover the functional relation between the delay, excitation and inhibition for the onset of anticipated synchronization in a sender-receiver-interneuron motif. In the case of zero-lag synchronization in a chain motif, we determine the stability conditions. These analytical solutions provide an excellent prediction of the phase-locked regimes of Hodgkin-Huxley models and Roessler oscillators.

[The effects of exposure to ozone on sperm quality in Wuhan].

PubMed

Tian, X J; Wang, X C; Ye, B; Li, C L; Zhang, Y; Ma, L

2017-03-06

Objective: To evaluate the effects of exposure to ozone (O(3)) on sperm quality during different stages of spermatogenesis. Methods: All 1 780 subjects attending to the Reproductive Medicine Center in Renmin Hospital of Wuhan University were recruited from April, 4, 2013 to June, 30, 2015. The subjects were living in Wuhan more than 3 months before attending to the program, aged 20 to 40 years. Semen quality (sperm concentration and sperm count) were measured according to standardized protocols. Corresponding daily 8 hours average concentration of O(3), other polluted concentration, average temperature and relative humidity were collected in different time, including lag 0, 10, 70 and 90 d, and lag 0-9 d, lag 10-14 d, lag 70-90 d and lag 0-90 d. After controlling the age, BMI, education level and other confounders, generalized linear Model was used to investigate the association between O(3) and sperm quality during different stages of spermatogenesis. Results: Average daily concentration of O(3) during the study period was (114.20±74.88) μg/m(3) and the mean values of sperm concentration and count were (76.32±50.17) millions/ml and (164.77 ± 133.05) millions/sample, respectively. Exposure to O(3) was associated with decreasing sperm concentration and count. For every 1 μg/m(3) increase of O(3), the decrease of sperm concentration during lag 10, lag 0-9 and lag 10-14 days exposure windows were 0.040 (95% CI: 0.004-0.077) millions/ml, 0.081 (95% CI: 0.003-0.158) millions/ml and 0.059 (95% CI: 0.001-0.116) millions/ml, respectively. And the decrease of sperm count during lag 10, lag 0-9 days exposure windows were 0.105 (95% CI: 0.008-0.202) millions/sample and 0.221 (95% CI: 0.016-0.426) millions/sample. After stratification, in the ozone concentration

Modelling the perennial energy crop market: the role of spatial diffusion

PubMed Central

Alexander, Peter; Moran, Dominic; Rounsevell, Mark D. A.; Smith, Pete

2013-01-01

Biomass produced from energy crops, such as Miscanthus and short rotation coppice is expected to contribute to renewable energy targets, but the slower than anticipated development of the UK market implies the need for greater understanding of the factors that govern adoption. Here, we apply an agent-based model of the UK perennial energy crop market, including the contingent interaction of supply and demand, to understand the spatial and temporal dynamics of energy crop adoption. Results indicate that perennial energy crop supply will be between six and nine times lower than previously published, because of time lags in adoption arising from a spatial diffusion process. The model simulates time lags of at least 20 years, which is supported empirically by the analogue of oilseed rape adoption in the UK from the 1970s. This implies the need to account for time lags arising from spatial diffusion in evaluating land-use change, climate change (mitigation or adaptation) or the adoption of novel technologies. PMID:24026474

Generalized thermoelastic problem of an infinite body with a spherical cavity under dual-phase-lags

NASA Astrophysics Data System (ADS)

Karmakar, R.; Sur, A.; Kanoria, M.

2016-07-01

The aim of the present contribution is the determination of the thermoelastic temperatures, stress, displacement, and strain in an infinite isotropic elastic body with a spherical cavity in the context of the mechanism of the two-temperature generalized thermoelasticity theory (2TT). The two-temperature Lord-Shulman (2TLS) model and two-temperature dual-phase-lag (2TDP) model of thermoelasticity are combined into a unified formulation with unified parameters. The medium is assumed to be initially quiescent. The basic equations are written in the form of a vector matrix differential equation in the Laplace transform domain, which is then solved by the state-space approach. The expressions for the conductive temperature and elongation are obtained at small times. The numerical inversion of the transformed solutions is carried out by using the Fourier-series expansion technique. A comparative study is performed for the thermoelastic stresses, conductive temperature, thermodynamic temperature, displacement, and elongation computed by using the Lord-Shulman and dual-phase-lag models.

Time-lagged ensemble simulations of the dispersion of the Eyjafjallajökull plume over Europe with COSMO-ART

NASA Astrophysics Data System (ADS)

Vogel, H.; Förstner, J.; Vogel, B.; Hanisch, T.; Mühr, B.; Schättler, U.; Schad, T.

2014-08-01

An extended version of the German operational weather forecast model was used to simulate the ash dispersion during the eruption of the Eyjafjallajökull. As an operational forecast was launched every 6 hours, a time-lagged ensemble was obtained. Sensitivity runs show the ability of the model to simulate thin ash layers when an increased vertical resolution is used. Calibration of the model results with measured data allows for a quantitative forecast of the ash concentration. After this calibration an independent comparison of the simulated number concentration of 3 μm particles and observations at Hohenpeißenberg gives a correlation coefficient of 0.79. However, this agreement could only be reached after additional modifications of the emissions. Based on the time lagged ensemble the conditional probability of violation of a certain threshold is calculated. Improving the ensemble technique used in our study such probabilities could become valuable information for the forecasters advising the organizations responsible for the closing of the airspace.

Modelling the perennial energy crop market: the role of spatial diffusion.

PubMed

Alexander, Peter; Moran, Dominic; Rounsevell, Mark D A; Smith, Pete

2013-11-06

Biomass produced from energy crops, such as Miscanthus and short rotation coppice is expected to contribute to renewable energy targets, but the slower than anticipated development of the UK market implies the need for greater understanding of the factors that govern adoption. Here, we apply an agent-based model of the UK perennial energy crop market, including the contingent interaction of supply and demand, to understand the spatial and temporal dynamics of energy crop adoption. Results indicate that perennial energy crop supply will be between six and nine times lower than previously published, because of time lags in adoption arising from a spatial diffusion process. The model simulates time lags of at least 20 years, which is supported empirically by the analogue of oilseed rape adoption in the UK from the 1970s. This implies the need to account for time lags arising from spatial diffusion in evaluating land-use change, climate change (mitigation or adaptation) or the adoption of novel technologies.

Distributed delays in a hybrid model of tumor-immune system interplay.

PubMed

Caravagna, Giulio; Graudenzi, Alex; d'Onofrio, Alberto

2013-02-01

A tumor is kinetically characterized by the presence of multiple spatio-temporal scales in which its cells interplay with, for instance, endothelial cells or Immune system effectors, exchanging various chemical signals. By its nature, tumor growth is an ideal object of hybrid modeling where discrete stochastic processes model low-numbers entities, and mean-field equations model abundant chemical signals. Thus, we follow this approach to model tumor cells, effector cells and Interleukin-2, in order to capture the Immune surveillance effect. We here present a hybrid model with a generic delay kernel accounting that, due to many complex phenomena such as chemical transportation and cellular differentiation, the tumor-induced recruitment of effectors exhibits a lag period. This model is a Stochastic Hybrid Automata and its semantics is a Piecewise Deterministic Markov process where a two-dimensional stochastic process is interlinked to a multi-dimensional mean-field system. We instantiate the model with two well-known weak and strong delay kernels and perform simulations by using an algorithm to generate trajectories of this process. Via simulations and parametric sensitivity analysis techniques we (i) relate tumor mass growth with the two kernels, we (ii) measure the strength of the Immune surveillance in terms of probability distribution of the eradication times, and (iii) we prove, in the oscillatory regime, the existence of a stochastic bifurcation resulting in delay-induced tumor eradication.

Effect of Asian dust storms on mortality in three Asian cities

NASA Astrophysics Data System (ADS)

Lee, Hyewon; Honda, Yasushi; Lim, Youn-Hee; Guo, Yue Leon; Hashizume, Masahiro; Kim, Ho

2014-06-01

Asian dust storms (ADS) have affected several Asian countries and have been a major concern due to adverse effects on public health. The occurrence of ADS differs in each country based on geographical features and distance from the storms' origin. Many studies have reported significant associations between ADS and morbidity. However, regarding the association between ADS and mortality, only a few studies have found statistically significant ADS effects in Korea, Taiwan and Japan. Accordingly, this study aimed to examine the effects of ADS on daily mortality in three Asian cities (Seoul, South Korea; Taipei, Taiwan; and Kitakyushu, Japan) and to explore the differences in the extent of effects in each city. We performed time-series analyses using a generalized additive model (GAM) with Quasi-Poisson regressions. Deaths due to accidents or external causes were excluded. We used a dummy variable as an indicator of ADS and considered lag effects of ADS. Stratified analyses by disease and age and sensitivity analyses controlling for NO2, SO2, and PM10 were also conducted respectively. Additionally, influenza epidemics were adjusted for considering seasonal patterns, and a meta-analysis was performed. We reported results as excess mortality by percentage due to Asian dust storms. We found significant excess mortality in Seoul and Kitakyushu as follows. In Seoul, ADS showed adverse effects on mortality under 65 years old (lag 2: 4.44%, lag 3: 5%, lag 4: 4.39%). In Kitakyushu, ADS had adverse effects on respiratory mortality (lag 2: 18.82%). Contradictory to results in Seoul and Kitakyushu, ADS seemed to have a protective effect in Taipei: total non-accidental mortality (lag 0: -2.77%, lag 1: -3.24%), mortality over 65 years old (lag 0: -3.35%, lag 1: -3.29%) and respiratory mortality (lag 0: -10.62%, lag 1: -9.67%). Sensitivity analyses showed similar findings as the main results. Our findings suggest that ADS may affect mortality in several Asian cities, and that a dust storm warning system could help protect people from dust storms.

Short communication: Genetic lag represents commercial herd genetic merit more accurately than the 4-path selection model.

PubMed

Dechow, C D; Rogers, G W

2018-05-01

Expectation of genetic merit in commercial dairy herds is routinely estimated using a 4-path genetic selection model that was derived for a closed population, but commercial herds using artificial insemination sires are not closed. The 4-path model also predicts a higher rate of genetic progress in elite herds that provide artificial insemination sires than in commercial herds that use such sires, which counters other theoretical assumptions and observations of realized genetic responses. The aim of this work is to clarify whether genetic merit in commercial herds is more accurately reflected under the assumptions of the 4-path genetic response formula or by a genetic lag formula. We demonstrate by tracing the transmission of genetic merit from parents to offspring that the rate of genetic progress in commercial dairy farms is expected to be the same as that in the genetic nucleus. The lag in genetic merit between the nucleus and commercial farms is a function of sire and dam generation interval, the rate of genetic progress in elite artificial insemination herds, and genetic merit of sires and dams. To predict how strategies such as the use of young versus daughter-proven sires, culling heifers following genomic testing, or selective use of sexed semen will alter genetic merit in commercial herds, genetic merit expectations for commercial herds should be modeled using genetic lag expectations. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Consequences of Fluid Lag in Three-Dimensional Hydraulic Fractures

NASA Astrophysics Data System (ADS)

Advani (Deceased), S. H.; Lee, T. S.; Dean, R. H.; Pak, C. K.; Avasthi, J. M.

1997-04-01

Research investigations on three-dimensional (3-D) rectangular hydraulic fracture configurations with varying degrees of fluid lag are reported. This paper demonstrates that a 3-D fracture model coupled with fluid lag (a small region of reduced pressure) at the fracture tip can predict very large excess pressure measurements for hydraulic fracture processes. Predictions of fracture propagation based on critical stress intensity factors are extremely sensitive to the pressure profile at the tip of a propagating fracture. This strong sensitivity to the pressure profile at the tip of a hydraulic fracture is more strongly pronounced in 3-D models versus 2-D models because 3-D fractures are clamped at the top and bottom, and pressures in the 3-D fractures that are far removed from the fracture tip have little effect on the stress intensity factor at the fracture tip. This rationale for the excess pressure mechanism is in marked contrast to the crack tip process damage zone assumptions and attendant high rock fracture toughness value hypotheses advanced in the literature. A comparison with field data is presented to illustrate the proposed fracture fluid pressure sensitivity phenomenon. This paper does not attempt to calculate the length of the fluid lag region in a propagating fracture but instead attempts to show that the pressure profile at the tip of the propagating fracture plays a major role in fracture propagation, and this role is magnified in 3-D models. Int. J. Numer. Anal. Meth. Geomech., vol. 21, 229-240 (1997).

Modeling the response of a standard accretion disc to stochastic viscous fluctuations

NASA Astrophysics Data System (ADS)

Ahmad, Naveel; Misra, Ranjeev; Iqbal, Naseer; Maqbool, Bari; Hamid, Mubashir

2018-01-01

The observed variability of X-ray binaries over a wide range of time-scales can be understood in the framework of a stochastic propagation model, where viscous fluctuations at different radii induce accretion rate variability that propagate inwards to the X-ray producing region. The scenario successfully explains the power spectra, the linear rms-flux relation as well as the time-lag between different energy photons. The predictions of this model have been obtained using approximate analytical solutions or empirically motivated models which take into account the effect of these propagating variability on the radiative process of complex accretion flows. Here, we study the variation of the accretion rate due to such viscous fluctuations using a hydro-dynamical code for the standard geometrically thin, gas pressure dominated α-disc with a zero torque boundary condition. Our results confirm earlier findings that the time-lag between a perturbation and the resultant inner accretion rate variation depends on the frequency (or time-period) of the perturbation. Here we have quantified that the time-lag tlag ∝f-0.54 , for time-periods less than the viscous time-scale of the perturbation radius and is nearly constant otherwise. This, coupled with radiative process would produce the observed frequency dependent time-lag between different energy bands. We also confirm that if there are random Gaussian fluctuations of the α-parameter at different radii, the resultant inner accretion rate has a power spectrum which is a power-law.

Effects of Temperature, Water Activity, and Syrup Film Composition on the Growth of Wallemia sebi: Development and Assessment of a Model Predicting Growth Lags in Syrup Agar and Crystalline Sugar

PubMed Central

Vindeløv, Jannik; Arneborg, Nils

2002-01-01

We investigated the effects of temperature, water activity (aw), and syrup film composition on the CFU growth of Wallemia sebi in crystalline sugar. At a high aw (0.82) at both high (20°C) and low (10°C) temperatures, the CFU growth of W. sebi in both white and extrawhite sugar could be described using a modified Gompertz model. At a low aw (0.76), however, the modified Gompertz model could not be fitted to the CFU data obtained with the two sugars due to long CFU growth lags and low maximum specific CFU growth rates of W. sebi at 20°C and due to the fact that growth did not occur at 10°C. At an aw of 0.82, regardless of the temperature, the carrying capacity (i.e., the cell concentration at t = ∞) of extrawhite sugar was lower than that of white sugar. Together with the fact that the syrup film of extrawhite sugar contained less amino-nitrogen relative to other macronutrients than the syrup film of white sugar, these results suggest that CFU growth of W. sebi in extrawhite sugar may be nitrogen limited. We developed a secondary growth model which is able to predict colony growth lags of W. sebi on syrup agar as a function of temperature and aw. The ability of this model to predict CFU growth lags of W. sebi in crystalline sugar was assessed. PMID:11916681

Examining spatiotemporal distribution and CPUE-environment relationships for the jumbo flying squid Dosidicus gigas offshore Peru based on spatial autoregressive model

NASA Astrophysics Data System (ADS)

Feng, Yongjiu; Chen, Xinjun; Liu, Yang

2017-09-01

The spatiotemporal distribution and relationship between nominal catch-per-unit-effort (CPUE) and environment for the jumbo flying squid (Dosidicus gigas) were examined in offshore Peruvian waters during 2009-2013. Three typical oceanographic factors affecting the squid habitat were investigated in this research, including sea surface temperature (SST), sea surface salinity (SSS) and sea surface height (SSH). We studied the CPUE-environment relationships for D. gigas using a spatially-lagged version of spatial autoregressive (SAR) model and a generalized additive model (GAM), with the latter for auxiliary and comparative purposes. The annual fishery centroids were distributed broadly in an area bounded by 79.5°-82.7°W and 11.9°-17.1°S, while the monthly fishery centroids were spatially close and lay in a smaller area bounded by 81.0°-81.2°W and 14.3°-15.4°S. Our results show that the preferred environmental ranges for D. gigas offshore Peru were 20.9°-21.9°C for SST, 35.16-35.32 for SSS and 27.2-31.5 cm for SSH in the areas bounded by 78°-80°W/82-84°W and 15°-18°S. Monthly spatial distributions during October to December were predicted using the calibrated GAM and SAR models and general similarities were found between the observed and predicted patterns for the nominal CPUE of D. gigas. The overall accuracies for the hotspots generated by the SAR model were much higher than those produced by the GAM model for all three months. Our results contribute to a better understanding of the spatiotemporal distributions of D. gigas offshore Peru, and offer a new SAR modeling method for advancing fishery science.

Bed conduction impact on fiber optic distributed temperature sensing water temperature measurements

NASA Astrophysics Data System (ADS)

O'Donnell Meininger, T.; Selker, J. S.

2015-02-01

Error in distributed temperature sensing (DTS) water temperature measurements may be introduced by contact of the fiber optic cable sensor with bed materials (e.g., seafloor, lakebed, streambed). Heat conduction from the bed materials can affect cable temperature and the resulting DTS measurements. In the Middle Fork John Day River, apparent water temperature measurements were influenced by cable sensor contact with aquatic vegetation and fine sediment bed materials. Affected cable segments measured a diurnal temperature range reduced by 10% and lagged by 20-40 min relative to that of ambient stream temperature. The diurnal temperature range deeper within the vegetation-sediment bed material was reduced 70% and lagged 240 min relative to ambient stream temperature. These site-specific results illustrate the potential magnitude of bed-conduction impacts with buried DTS measurements. Researchers who deploy DTS for water temperature monitoring should understand the importance of the environment into which the cable is placed on the range and phase of temperature measurements.

Investigating the Relative Contributions of Secondary Ice Formation Processes to Ice Crystal Number Concentrations Within Mixed-Phase Clouds

NASA Astrophysics Data System (ADS)

Sullivan, S.; Nenes, A.

2015-12-01

Measurements of the in-cloud ice nuclei concentration can be three or four orders of magnitude less than those of the in-cloud ice crystal number concentration. Different secondary formation processes, active after initial ice nucleation, have been proposed to explain this discrepancy, but their relative importance, and even the exact physics of each mechanism, are still unclear. We construct a simple bin microphysics model (2IM) including depositional growth, the Hallett-Mossop process, ice-ice collisions, and ice-ice aggregation, with temperature- and supersaturation-dependent efficiencies for each process. 2IM extends the time-lag collision model of Yano and Phillips to additional bins and incorporates the aspect ratio evolution of Jensen and Harrington. Model output and measured ice crystal size distributions are compared to answer three questions: (1) how important is ice-ice aggregation relative to ice-ice collision around -15°C, where the Hallett-Mossop process is no longer active; (2) what process efficiencies lead to the best reproduction of observed ice crystal size distributions; and (3) does ice crystal aspect ratio affect the dominant secondary formation process. The resulting parameterization is intended for eventual use in larger-scale mixed-phase cloud schemes.

Distributional Tests for Gravitational Waves from Core-Collapse Supernovae

NASA Astrophysics Data System (ADS)

Szczepanczyk, Marek; LIGO Collaboration

2017-01-01

Core-Collapse Supernovae (CCSN) are spectacular and violent deaths of massive stars. CCSN are some of the most interesting candidates for producing gravitational-waves (GW) transients. Current published results focus on methodologies to detect single GW unmodelled transients. The advantages of these tests are that they do not require a background for which we have an analytical model. Examples of non-parametric tests that will be compared are Kolmogorov-Smirnov, Mann-Whitney, chi squared, and asymmetric chi squared. I will present methodological results using publicly released LIGO-S6 data recolored to the design sensitivity of Advanced LIGO and that will be time lagged between interferometers sites so that the resulting coincident events are not GW.

Analysis of a unidirectional, symmetric buffer strip laminate with damage

NASA Technical Reports Server (NTRS)

Dharani, L. R.; Goree, J. G.

1984-01-01

A method for predicting the fracture behavior of hybrid buffer strip laminates is presented in which the classical shear-lag model is used to represent the shear stress distribution between adjacent fibers. The method is demonstrated by applying it to a notched graphite/epoxy laminate, and the results show clearly the manner in which the most efficient combination of buffer strip properties can be selected in order to arrest the crack. The ultimate failure stress of the laminate is plotted vs the buffer strip width. It is shown that in the case of graphite-epoxy and S-glass epoxy laminates, the optimum buffer strip spacing to width ratio should be about four to one.

The IOD-ENSO precursory teleconnection over the tropical Indo-Pacific Ocean: dynamics and long-term trends under global warming

NASA Astrophysics Data System (ADS)

Yuan, Dongliang; Hu, Xiaoyue; Xu, Peng; Zhao, Xia; Masumoto, Yukio; Han, Weiqing

2018-01-01

The dynamics of the teleconnection between the Indian Ocean Dipole (IOD) in the tropical Indian Ocean and El Niño-Southern Oscillation (ENSO) in the tropical Pacific Ocean at the time lag of one year are investigated using lag correlations between the oceanic anomalies in the southeastern tropical Indian Ocean in fall and those in the tropical Indo-Pacific Ocean in the following winter-fall seasons in the observations and in high-resolution global ocean model simulations. The lag correlations suggest that the IOD-forced interannual transport anomalies of the Indonesian Throughflow generate thermocline anomalies in the western equatorial Pacific Ocean, which propagate to the east to induce ocean-atmosphere coupled evolution leading to ENSO. In comparison, lag correlations between the surface zonal wind anomalies over the western equatorial Pacific in fall and the Indo-Pacific oceanic anomalies at time lags longer than a season are all insignificant, suggesting the short memory of the atmospheric bridge. A linear continuously stratified model is used to investigate the dynamics of the oceanic connection between the tropical Indian and Pacific Oceans. The experiments suggest that interannual equatorial Kelvin waves from the Indian Ocean propagate into the equatorial Pacific Ocean through the Makassar Strait and the eastern Indonesian seas with a penetration rate of about 10%-15% depending on the baroclinic modes. The IOD-ENSO teleconnection is found to get stronger in the past century or so. Diagnoses of the CMIP5 model simulations suggest that the increased teleconnection is associated with decreased Indonesian Throughflow transports in the recent century, which is found sensitive to the global warming forcing.

Atmospheric Teleconnections From Cumulants

NASA Astrophysics Data System (ADS)

Sabou, F.; Kaspi, Y.; Marston, B.; Schneider, T.

2011-12-01

Multi-point cumulants of fields such as vorticity provide a way to visualize atmospheric teleconnections, complementing other approaches such as the method of empirical orthogonal functions (EOFs). We calculate equal-time two-point cumulants of the vorticity from NCEP reanalysis data during the period 1980 -- 2010 and from direct numerical simulation (DNS) using an idealized dry general circulation model (GCM) (Schneider and Walker, 2006). Extratropical correlations seen in the NCEP data are qualitatively reproduced by the model. Three- and four-point cumulants accumulated from DNS quantify departures of the probability distribution function from a normal distribution, shedding light on the efficacy of direct statistical simulation (DSS) of atmosphere dynamics by cumulant expansions (Marston, Conover, and Schneider, 2008; Marston 2011). Lagged-time two-point cumulants between temperature gradients and eddy kinetic energy (EKE), accumulated by DNS of an idealized moist aquaplanet GCM (O'Gorman and Schneider, 2008), reveal dynamics of storm tracks. Regions of enhanced baroclinicity (as found along the eastern boundary of continents) lead to a local enhancement of EKE and a suppression of EKE further downstream as the storm track self-destructs (Kaspi and Schneider, 2011).

A Protocol for Aging Anurans Using Skeletochronology

USGS Publications Warehouse

McCreary, Brome; Pearl, Christopher A.; Adams, Michael J.

2008-01-01

Age distribution information can be an important part of understanding the biology of any population. Age estimates collected from the annual growth rings found in tooth and bone cross sections, often referred to as Lines of Arrested Growth (LAGs), have been used in the study of various animals. In this manual, we describe in detail all necessary steps required to obtain estimates of age from anuran bone cross sections via skeletochronological assessment. We include comprehensive descriptions of how to fix and decalcify toe specimens (phalanges), process a phalange prior to embedding, embed the phalange in paraffin, section the phalange using a microtome, stain and mount the cross sections of the phalange and read the LAGs to obtain age estimates.

The Effect of Clearance Distribution on the Performance of a Compression-ignition Engine with a Precombustion Chamber

NASA Technical Reports Server (NTRS)

Moore, C. S.; Collins, J. H. Jr

1932-01-01

The clearance distribution in a precombustion chamber cylinder head was varied so that for a constant compression ratio of 13.5 the spherical auxiliary chambers contained 20, 35, 50, and 70 per cent of the total clearance volume. Each chamber was connected to the cylinder by a single circular passage, flared at both ends, and of a cross-sectional area proportional to the chamber volume, thereby giving the same calculated air-flow velocity through each passage. Results of engine-performance tests are presented with variations of power, fuel consumption, explosion pressure, rate of pressure rise, ignition lag, heat loss to the cooling water, and motoring characteristics. For good performance the minimum auxiliary chamber volume, with the cylinder head design used, was 35 per cent of the total clearance volume; for larger volumes the performance improves but slightly. With the auxiliary chamber that contained 35 percent of the clearance volume there were obtained the lowest explosion pressures, medium rates of pressure rise, and slightly less than the maximum power. For all clearance distributions an increase in engine speed decreased the ignition lag in seconds and increased the rate of pressure rise.

Temperature-related mortality in 17 large Chinese cities: how heat and cold affect mortality in China.

PubMed

Ma, Wenjuan; Chen, Renjie; Kan, Haidong

2014-10-01

Few multicity studies have been conducted to investigate the acute health effects of cold and hot temperatures in China. We aimed to examine the relationship between temperature and daily mortality in 17 large Chinese cities. We first calculated city-specific effect of temperature using time-series regression models combined with distributed lag nonlinear models; then we pooled the city-specific estimates with the Bayesian hierarchical models. The cold effects lasted longer than the hot effects. For the cold effects, a 1 °C decrease from the 25th to 1st percentiles of temperature over lags 0-14 days was associated with increases of 1.69% [95% posterior intervals (PI): 1.01%, 2.36%], 2.49% (95% PI: 1.53%, 3.46%) and 1.60% (95% PI: 0.32%, 2.87%) in total, cardiovascular and respiratory mortality, respectively. For the hot effects, a 1 °C increase from the 75th to 99th percentiles of temperature was associated with corresponding increases of 2.83% (95% PI: 1.42%, 4.24%), 3.02% (95% PI: 1.33%, 4.71%) and 4.64% (95% PI: 1.96%, 7.31%). The latitudes, number of air conditioning per household and disposable income per capita were significant modifiers for cold effects; the proportion of the elderly was a significant modifier for hot effects. This largest epidemiological study of temperature to date in China suggested that both cold and hot temperatures were associated with increased mortality. Our findings may have important implications for the public health policies in China. Copyright © 2014 Elsevier Inc. All rights reserved.

Predicting key malaria transmission factors, biting and entomological inoculation rates, using modelled soil moisture in Kenya.

PubMed

Patz, J A; Strzepek, K; Lele, S; Hedden, M; Greene, S; Noden, B; Hay, S I; Kalkstein, L; Beier, J C

1998-10-01

While malaria transmission varies seasonally, large inter-annual heterogeneity of malaria incidence occurs. Variability in entomological parameters, biting rates and entomological inoculation rates (EIR) have been strongly associated with attack rates in children. The goal of this study was to assess the weather's impact on weekly biting and EIR in the endemic area of Kisian, Kenya. Entomological data collected by the U.S. Army from March 1986 through June 1988 at Kisian, Kenya was analysed with concurrent weather data from nearby Kisumu airport. A soil moisture model of surface-water availability was used to combine multiple weather parameters with landcover and soil features to improve disease prediction. Modelling soil moisture substantially improved prediction of biting rates compared to rainfall; soil moisture lagged two weeks explained up to 45% of An. gambiae biting variability, compared to 8% for raw precipitation. For An. funestus, soil moisture explained 32% variability, peaking after a 4-week lag. The interspecies difference in response to soil moisture was significant (P < 0.00001). A satellite normalized differential vegetation index (NDVI) of the study site yielded a similar correlation (r = 0.42 An. gambiae). Modelled soil moisture accounted for up to 56% variability of An. gambiae EIR, peaking at a lag of six weeks. The relationship between temperature and An. gambiae biting rates was less robust; maximum temperature r2 = -0.20, and minimum temperature r2 = 0.12 after lagging one week. Benefits of hydrological modelling are compared to raw weather parameters and to satellite NDVI. These findings can improve both current malaria risk assessments and those based on El Niño forecasts or global climate change model projections.

Time lag between immigration and tuberculosis rates in immigrants in the Netherlands: a time-series analysis.

PubMed

van Aart, C; Boshuizen, H; Dekkers, A; Korthals Altes, H

2017-05-01

In low-incidence countries, most tuberculosis (TB) cases are foreign-born. We explored the temporal relationship between immigration and TB in first-generation immigrants between 1995 and 2012 to assess whether immigration can be a predictor for TB in immigrants from high-incidence countries. We obtained monthly data on immigrant TB cases and immigration for the three countries of origin most frequently represented among TB cases in the Netherlands: Morocco, Somalia and Turkey. The best-fit seasonal autoregressive integrated moving average (SARIMA) model to the immigration time-series was used to prewhiten the TB time series. The cross-correlation function (CCF) was then computed on the residual time series to detect time lags between immigration and TB rates. We identified a 17-month lag between Somali immigration and Somali immigrant TB cases, but no time lag for immigrants from Morocco and Turkey. The absence of a lag in the Moroccan and Turkish population may be attributed to the relatively low TB prevalence in the countries of origin and an increased likelihood of reactivation TB in an ageing immigrant population. Understanding the time lag between Somali immigration and TB disease would benefit from a closer epidemiological analysis of cohorts of Somali cases diagnosed within the first years after entry.

Development of a novel drug delivery system, time-controlled explosion system (TES). IV. In vivo drug release behavior.

PubMed

Ueda, S; Ibuki, R; Kawamura, A; Murata, S; Takahashi, T; Kimura, S; Hata, T

1994-01-01

Time-Controlled Explosion System (TES) has the time-controlled drug release property with a pre-designed lag time. The drug release from the system is initiated by destruction of the membrane. In this study, metoprolol tartrate was used as a model drug. After five types of TES with different in vitro lag times were orally administrated to dogs, plasma metoprolol concentration was monitored. There existed a good correlation between in vitro and in vivo lag time, while the extent of absorbed metoprolol decreased with prolongation of lag time. Next, the in vivo drug release behavior was directly investigated using five different colored TES with a lag time of two hours. Each TES was consecutively administrated to the fasted dogs at predetermined intervals. The amount of metoprolol released was monitored by recovering the administered TES from the gastrointestinal trace. The in vivo release profile corresponded with the in vitro one. It is demonstrated that TES can release the drug in in vivo conditions similarly to in vitro. Based on these results, the decrease of the absorption is suggested to be caused by increased hepatic first-pass metabolism of the drug due to the retarded release rate with longer lag time.

Monthly ENSO Forecast Skill and Lagged Ensemble Size

PubMed Central

DelSole, T.; Tippett, M.K.; Pegion, K.

2018-01-01

Abstract The mean square error (MSE) of a lagged ensemble of monthly forecasts of the Niño 3.4 index from the Climate Forecast System (CFSv2) is examined with respect to ensemble size and configuration. Although the real‐time forecast is initialized 4 times per day, it is possible to infer the MSE for arbitrary initialization frequency and for burst ensembles by fitting error covariances to a parametric model and then extrapolating to arbitrary ensemble size and initialization frequency. Applying this method to real‐time forecasts, we find that the MSE consistently reaches a minimum for a lagged ensemble size between one and eight days, when four initializations per day are included. This ensemble size is consistent with the 8–10 day lagged ensemble configuration used operationally. Interestingly, the skill of both ensemble configurations is close to the estimated skill of the infinite ensemble. The skill of the weighted, lagged, and burst ensembles are found to be comparable. Certain unphysical features of the estimated error growth were tracked down to problems with the climatology and data discontinuities. PMID:29937973

Monthly ENSO Forecast Skill and Lagged Ensemble Size

NASA Astrophysics Data System (ADS)

Trenary, L.; DelSole, T.; Tippett, M. K.; Pegion, K.

2018-04-01

The mean square error (MSE) of a lagged ensemble of monthly forecasts of the Niño 3.4 index from the Climate Forecast System (CFSv2) is examined with respect to ensemble size and configuration. Although the real-time forecast is initialized 4 times per day, it is possible to infer the MSE for arbitrary initialization frequency and for burst ensembles by fitting error covariances to a parametric model and then extrapolating to arbitrary ensemble size and initialization frequency. Applying this method to real-time forecasts, we find that the MSE consistently reaches a minimum for a lagged ensemble size between one and eight days, when four initializations per day are included. This ensemble size is consistent with the 8-10 day lagged ensemble configuration used operationally. Interestingly, the skill of both ensemble configurations is close to the estimated skill of the infinite ensemble. The skill of the weighted, lagged, and burst ensembles are found to be comparable. Certain unphysical features of the estimated error growth were tracked down to problems with the climatology and data discontinuities.

Short-term impacts of floods on enteric infectious disease in Qingdao, China, 2005-2011.

PubMed

Zhang, F; Liu, Z; Gao, L; Zhang, C; Jiang, B

2016-11-01

The current study aimed to examine the relationship between floods and the three enteric infectious diseases, namely bacillary dysentery (BD), hand-foot-mouth disease (HFMD) and other infectious diarrhoea (OID) in Qingdao, China. Relative risks (RRs) and 95% confidence intervals (CIs) of floods on BD, HFMD and OID were calculated using a quasi-Poisson generalized linear model, adjusting for daily average temperature, daily average relative humidity, and seasonal and long-term temporal trends. Two separate models within two different periods were designed. Model 1 for the summer period showed that floods were positively associated with BD for 4- to 12-day lags, with the greatest effects for 7-day (RR 1·41, 95% CI 1·22-1·62) and 11-day (RR 1·42, 95% CI 1·22-1·64) lags. Similar findings were found in model 2 for the whole study period for 5- to 12-day lags. However, HFMD and OID were not significantly associated with floods in both models. Results from this study will provide insight into the health risks associated with floods and may help inform public health precautionary measures for such disasters.