WorldWideScience

Sample records for three-year time-series study

  1. Statistical partitioning of a three-year time series of direct urban net CO2 flux measurements into biogenic and anthropogenic components

    Science.gov (United States)

    Menzer, Olaf; McFadden, Joseph P.

    2017-12-01

    Eddy covariance flux measurements are increasingly used to quantify the net carbon dioxide exchange (FC) in urban areas. FC represents the sum of anthropogenic emissions, biogenic carbon release from plant and soil respiration, and carbon uptake by plant photosynthesis. When FC is measured in natural ecosystems, partitioning into respiration and photosynthesis is a well-established procedure. In contrast, few studies have partitioned FC at urban flux tower sites due to the difficulty of accounting for the temporal and spatial variability of the multiple sources and sinks. Here, we partitioned a three-year time series of flux measurements from a suburban neighborhood of Minneapolis-Saint Paul, Minnesota, USA. We segregated FC into one subset that captured fluxes from a residential neighborhood and into another subset that covered a golf course. For both land use types we modeled anthropogenic flux components based on winter data and extrapolated them to the growing season, to estimate gross primary production (GPP) and ecosystem respiration (Reco) at half-hourly, daily, monthly and annual scales. During the growing season, GPP had the largest magnitude (up to - 9.83 g C m-2 d-1) of any component CO2 flux, biogenic or anthropogenic, and both GPP and Reco were more dynamic seasonally than anthropogenic fluxes. Owing to the balancing of Reco against GPP, and the limitations of the growing season in a cold temperate climate zone, the net biogenic flux was only 1.5%-4.5% of the anthropogenic flux in the dominant residential land use type, and between 25%-31% of the anthropogenic flux in highly managed greenspace. Still, the vegetation sink at our site was stronger than net anthropogenic emissions on 16-20 days over the residential area and on 66-91 days over the recreational area. The reported carbon flux sums and dynamics are a critical step toward developing models of urban CO2 fluxes within and across cities that differ in vegetation cover.

  2. Studies on time series applications in environmental sciences

    CERN Document Server

    Bărbulescu, Alina

    2016-01-01

    Time series analysis and modelling represent a large study field, implying the approach from the perspective of the time and frequency, with applications in different domains. Modelling hydro-meteorological time series is difficult due to the characteristics of these series, as long range dependence, spatial dependence, the correlation with other series. Continuous spatial data plays an important role in planning, risk assessment and decision making in environmental management. In this context, in this book we present various statistical tests and modelling techniques used for time series analysis, as well as applications to hydro-meteorological series from Dobrogea, a region situated in the south-eastern part of Romania, less studied till now. Part of the results are accompanied by their R code. .

  3. Earthquake forecasting studies using radon time series data in Taiwan

    Science.gov (United States)

    Walia, Vivek; Kumar, Arvind; Fu, Ching-Chou; Lin, Shih-Jung; Chou, Kuang-Wu; Wen, Kuo-Liang; Chen, Cheng-Hong

    2017-04-01

    For few decades, growing number of studies have shown usefulness of data in the field of seismogeochemistry interpreted as geochemical precursory signals for impending earthquakes and radon is idendified to be as one of the most reliable geochemical precursor. Radon is recognized as short-term precursor and is being monitored in many countries. This study is aimed at developing an effective earthquake forecasting system by inspecting long term radon time series data. The data is obtained from a network of radon monitoring stations eastblished along different faults of Taiwan. The continuous time series radon data for earthquake studies have been recorded and some significant variations associated with strong earthquakes have been observed. The data is also examined to evaluate earthquake precursory signals against environmental factors. An automated real-time database operating system has been developed recently to improve the data processing for earthquake precursory studies. In addition, the study is aimed at the appraisal and filtrations of these environmental parameters, in order to create a real-time database that helps our earthquake precursory study. In recent years, automatic operating real-time database has been developed using R, an open source programming language, to carry out statistical computation on the data. To integrate our data with our working procedure, we use the popular and famous open source web application solution, AMP (Apache, MySQL, and PHP), creating a website that could effectively show and help us manage the real-time database.

  4. Ocean time-series near Bermuda: Hydrostation S and the US JGOFS Bermuda Atlantic time-series study

    Science.gov (United States)

    Michaels, Anthony F.; Knap, Anthony H.

    1992-01-01

    Bermuda is the site of two ocean time-series programs. At Hydrostation S, the ongoing biweekly profiles of temperature, salinity and oxygen now span 37 years. This is one of the longest open-ocean time-series data sets and provides a view of decadal scale variability in ocean processes. In 1988, the U.S. JGOFS Bermuda Atlantic Time-series Study began a wide range of measurements at a frequency of 14-18 cruises each year to understand temporal variability in ocean biogeochemistry. On each cruise, the data range from chemical analyses of discrete water samples to data from electronic packages of hydrographic and optics sensors. In addition, a range of biological and geochemical rate measurements are conducted that integrate over time-periods of minutes to days. This sampling strategy yields a reasonable resolution of the major seasonal patterns and of decadal scale variability. The Sargasso Sea also has a variety of episodic production events on scales of days to weeks and these are only poorly resolved. In addition, there is a substantial amount of mesoscale variability in this region and some of the perceived temporal patterns are caused by the intersection of the biweekly sampling with the natural spatial variability. In the Bermuda time-series programs, we have added a series of additional cruises to begin to assess these other sources of variation and their impacts on the interpretation of the main time-series record. However, the adequate resolution of higher frequency temporal patterns will probably require the introduction of new sampling strategies and some emerging technologies such as biogeochemical moorings and autonomous underwater vehicles.

  5. Interrupted time-series analysis: studying trends in neurosurgery.

    Science.gov (United States)

    Wong, Ricky H; Smieliauskas, Fabrice; Pan, I-Wen; Lam, Sandi K

    2015-12-01

    OBJECT Neurosurgery studies traditionally have evaluated the effects of interventions on health care outcomes by studying overall changes in measured outcomes over time. Yet, this type of linear analysis is limited due to lack of consideration of the trend's effects both pre- and postintervention and the potential for confounding influences. The aim of this study was to illustrate interrupted time-series analysis (ITSA) as applied to an example in the neurosurgical literature and highlight ITSA's potential for future applications. METHODS The methods used in previous neurosurgical studies were analyzed and then compared with the methodology of ITSA. RESULTS The ITSA method was identified in the neurosurgical literature as an important technique for isolating the effect of an intervention (such as a policy change or a quality and safety initiative) on a health outcome independent of other factors driving trends in the outcome. The authors determined that ITSA allows for analysis of the intervention's immediate impact on outcome level and on subsequent trends and enables a more careful measure of the causal effects of interventions on health care outcomes. CONCLUSIONS ITSA represents a significant improvement over traditional observational study designs in quantifying the impact of an intervention. ITSA is a useful statistical procedure to understand, consider, and implement as the field of neurosurgery evolves in sophistication in big-data analytics, economics, and health services research.

  6. Seasonal time series forecasting: a comparative study of arima and ...

    African Journals Online (AJOL)

    This paper addresses the concerns of Faraway and Chatfield (1998) who questioned the forecasting ability of Artificial Neural Networks (ANN). In particular the paper compares the performance of Artificial Neural Networks (ANN) and ARIMA models in forecasting of seasonal (monthly) Time series. Using the Airline data ...

  7. STUDIES IN ASTRONOMICAL TIME SERIES ANALYSIS. VI. BAYESIAN BLOCK REPRESENTATIONS

    Energy Technology Data Exchange (ETDEWEB)

    Scargle, Jeffrey D. [Space Science and Astrobiology Division, MS 245-3, NASA Ames Research Center, Moffett Field, CA 94035-1000 (United States); Norris, Jay P. [Physics Department, Boise State University, 2110 University Drive, Boise, ID 83725-1570 (United States); Jackson, Brad [The Center for Applied Mathematics and Computer Science, Department of Mathematics, San Jose State University, One Washington Square, MH 308, San Jose, CA 95192-0103 (United States); Chiang, James, E-mail: jeffrey.d.scargle@nasa.gov [W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305 (United States)

    2013-02-20

    This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it-an improved and generalized version of Bayesian Blocks-that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piecewise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by Arias-Castro et al. In the spirit of Reproducible Research all of the code and data necessary to reproduce all of the figures in this paper are included as supplementary material.

  8. Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations

    Science.gov (United States)

    Scargle, Jeffrey D.; Norris, Jay P.; Jackson, Brad; Chiang, James

    2013-01-01

    This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it-an improved and generalized version of Bayesian Blocks [Scargle 1998]-that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piece- wise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by [Arias-Castro, Donoho and Huo 2003]. In the spirit of Reproducible Research [Donoho et al. (2008)] all of the code and data necessary to reproduce all of the figures in this paper are included as auxiliary material.

  9. STUDIES IN ASTRONOMICAL TIME SERIES ANALYSIS. VI. BAYESIAN BLOCK REPRESENTATIONS

    International Nuclear Information System (INIS)

    Scargle, Jeffrey D.; Norris, Jay P.; Jackson, Brad; Chiang, James

    2013-01-01

    This paper addresses the problem of detecting and characterizing local variability in time series and other forms of sequential data. The goal is to identify and characterize statistically significant variations, at the same time suppressing the inevitable corrupting observational errors. We present a simple nonparametric modeling technique and an algorithm implementing it—an improved and generalized version of Bayesian Blocks—that finds the optimal segmentation of the data in the observation interval. The structure of the algorithm allows it to be used in either a real-time trigger mode, or a retrospective mode. Maximum likelihood or marginal posterior functions to measure model fitness are presented for events, binned counts, and measurements at arbitrary times with known error distributions. Problems addressed include those connected with data gaps, variable exposure, extension to piecewise linear and piecewise exponential representations, multivariate time series data, analysis of variance, data on the circle, other data modes, and dispersed data. Simulations provide evidence that the detection efficiency for weak signals is close to a theoretical asymptotic limit derived by Arias-Castro et al. In the spirit of Reproducible Research all of the code and data necessary to reproduce all of the figures in this paper are included as supplementary material.

  10. Thyroid cancers: a three year retrospective histopathological study

    International Nuclear Information System (INIS)

    Than-Than-Htwe; Maung-Ko

    2001-01-01

    A laboratory based retrospective study was done on thyroid tissue specimen that were received from the surgically removed thyroid swellings of various reasons. It was a three year study from 1996-1998 with a total number of cases as (n=1690). Cases were between the age range of 8-88 years including both sexes. A routine histopathological examination was done according to the standard WHO classification, using conventional methods and techniques of specimen sectioning and processing. Occurrence of thyroid cancer among total cases of thyroid dysfunction is highly significant (P 0.860). The results obtained were discussed. (author)

  11. Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section

    Directory of Open Access Journals (Sweden)

    Chaolong Jia

    2014-01-01

    Full Text Available Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach. Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described.

  12. Multiscale entropy based study of the pathological time series

    International Nuclear Information System (INIS)

    Wang Jun; Ma Qianli

    2008-01-01

    This paper studies the multiscale entropy (MSE) of electrocardiogram's ST segment and compares the MSE results of ST segment with that of electrocardiogram in the first time. Electrocardiogram complexity changing characteristics has important clinical significance for early diagnosis. Study shows that the average MSE values and the varying scope fluctuation could be more effective to reveal the heart health status. Particularly the multiscale values varying scope fluctuation is a more sensitive parameter for early heart disease detection and has a clinical diagnostic significance. (general)

  13. Determinants of Private Investment in Ethiopia: A Time Series Study ...

    African Journals Online (AJOL)

    In spite of little improvement in the post‐socialist era, the share of private investment in GDP has never been above 6 percent even until 2003. Yet, the reasons behind the weak performance have not been well studied. Hence, investigating the performance trend and maim constraints of private investment in Ethiopia ...

  14. Becoming a mental health nurse; A three year longitudinal study

    Directory of Open Access Journals (Sweden)

    Harvey Wells

    2015-03-01

    Full Text Available This longitudinal case series study explores how students’ conceptions of ‘mental health nursing’ changed whilst on a three-year pre-registration Mental Health Nursing programme. The study was carried out in two university nursing schools in the South East of England and this paper reports a detailed analysis of 6 individual case studies. The researchers utilised Novak’s approach to concept mapping to elicit students’ personal knowledge structures, which were explored further using semi-structured individual qualitative interviews. The maps were analysed by looking at their gross morphology to interpret changes over time into types of learning achieved and the associated interview data were analysed using thematic content analysis. Results from analysis of the map structures suggest that whilst four of the selected students learned deeply, one participant learned superficially and one appeared not to learn at all. The associated interview data provides an interesting insight into the students’ reflective narratives on the process of learning. The findings also demonstrate further evidence of the practicability of using Novakian concept maps to self-prompt qualitative research interviews. Implications for the professional education of Mental Health Nurses are discussed.

  15. The inner state differences of preterm birth rates in Brazil: a time series study.

    Science.gov (United States)

    de Oliveira, Rosana Rosseto; Melo, Emiliana Cristina; Fujimori, Elizabeth; Mathias, Thais Aidar de Freitas

    2016-05-17

    Preterm birth is a serious public health problem, as it is linked to high rates of neonatal and child morbidity and mortality. The prevalence of premature births has increased worldwide, with regional differences. The objective of this study was to analyze the trend of preterm births in the state of Paraná, Brazil, according to Macro-regional and Regional Health Offices (RHOs). This is an ecological time series study using preterm births records from the national live birth registry system of Brazil's National Health Service - Live Birth Information System (Sinasc), for residents of the state of Paraná, Brazil, between 2000 and 2013. The preterm birth rates was calculated on a yearly basis and grouped into three-year periods (2000-2002, 2003-2005, 2006-2008, 2009-2011) and one two-year period (2012-2013), according to gestational age and mother's Regional Health Office of residence. The polynomial regression model was used for trend analysis. The predominance of preterm birth rate increased from 6.8 % in 2000 to 10.5 % in 2013, with an average increase of 0.20 % per year (r(2) = 0.89), and a greater share of moderate preterm births (32 to rate of prematurity and average annual growth during that period (7.55 % and 0.35 %, respectively). The trend analysis of preterm birth rates according to RHO showed a growing trend for almost all RHOs - except for the 7(th) RHO where a declining trend was observed (-0.95 a year); and in the 20(th), 21(st) and 22(nd) RHOs which remained unchanged. In the last three-year of the study period (2011-2013), no RHO showed preterm birth rates below 7.3 % or prevalence of moderate preterm birth below 9.4 %. The results show an increase in preterm births with differences among Macro-regional and RHOs, which indicate the need to improve actions during the prenatal period according to the specificities of each region.

  16. The inner state differences of preterm birth rates in Brazil: a time series study

    Directory of Open Access Journals (Sweden)

    Rosana Rosseto de Oliveira

    2016-05-01

    Full Text Available Abstract Background Preterm birth is a serious public health problem, as it is linked to high rates of neonatal and child morbidity and mortality. The prevalence of premature births has increased worldwide, with regional differences. The objective of this study was to analyze the trend of preterm births in the state of Paraná, Brazil, according to Macro-regional and Regional Health Offices (RHOs. Methods This is an ecological time series study using preterm births records from the national live birth registry system of Brazil’s National Health Service - Live Birth Information System (Sinasc, for residents of the state of Paraná, Brazil, between 2000 and 2013. The preterm birth rates was calculated on a yearly basis and grouped into three-year periods (2000–2002, 2003–2005, 2006–2008, 2009–2011 and one two-year period (2012–2013, according to gestational age and mother’s Regional Health Office of residence. The polynomial regression model was used for trend analysis. Results The predominance of preterm birth rate increased from 6.8 % in 2000 to 10.5 % in 2013, with an average increase of 0.20 % per year (r2 = 0.89, and a greater share of moderate preterm births (32 to <37 weeks, which increased from 5.8 % to 9 %. The same pattern was observed for all Macro-regional Health Offices, with highlight to the Northern Macro-Regional Office, which showed the highest average rate of prematurity and average annual growth during that period (7.55 % and 0.35 %, respectively. The trend analysis of preterm birth rates according to RHO showed a growing trend for almost all RHOs – except for the 7th RHO where a declining trend was observed (−0.95 a year; and in the 20th, 21st and 22nd RHOs which remained unchanged. In the last three-year of the study period (2011–2013, no RHO showed preterm birth rates below 7.3 % or prevalence of moderate preterm birth below 9.4 %. Conclusions The results show an increase in preterm births

  17. A normalized difference vegetation index (NDVI) time-series of idle agriculture lands: A preliminary study

    NARCIS (Netherlands)

    Vaiphasa, C.; Piamduaytham, S.; Vaiphasa, T.; Skidmore, A.K.

    2011-01-01

    In this paper, the NDVI time-series collected from the study area between year 2003 and 2005 of all land cover types are plotted and compared. The study area is the agricultural zones in Banphai District, Khonkean, Thailand. The LANDSAT satellite images of different dates were first transformed into

  18. Profile of pediatric malignancy: a three year study

    OpenAIRE

    Bhalodia Jignasa N, Patel Mandakini M

    2011-01-01

    The objective of this study was to find out the profile of childhood cancers in South Gujarat region, during November 2002 to October 2005. Between November 2002 to October 2005 data was analyzed for the malignancies occurring in the age group 0-14 years. Data was categorized according to incidence of pediatric malignancies in different age groups, sex and types of tumors. All the children below 15 years with confirmed diagnosis of cancer by means of histological or cytological examinations w...

  19. Intratemporal Facial Nerve Paralysis- A Three Year Study

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    Anirban Ghosh

    2016-08-01

    Full Text Available Introduction This study on intratemporal facial paralysis is an attempt to understand the aetiology of facial nerve paralysis, effect of different management protocols and the outcome after long-term follow-up. Materials and Methods A prospective longitudinal study was conducted from September 2005 to August 2008 at the Department of Otorhinolaryngology of a medical college in Kolkata comprising 50 patients of intratemporal facial palsy. All cases were periodically followed up for at least 6 months and their prognostic outcome along with different treatment options were analyzed. Result Among different causes of facial palsy, Bell’s palsy is the commonest cause; whereas cholesteatoma and granulation were common findings in otogenic facial palsy. Traumatic facial palsies were exclusively due to longitudinal fracture of temporal bone running through geniculate ganglion. Herpes zoster oticus and neoplasia related facial palsies had significantly poorer outcome. Discussion Otogenic facial palsy showed excellent outcome after mastoid exploration and facial decompression. Transcanal decompression was performed in traumatic facial palsies showing inadequate recovery. Complete removal of cholesteatoma over dehiscent facial nerve gave better postoperative recovery. Conclusion The stapedial reflex test is the most objective and reproducible of all topodiagnostic tests. Return of the stapedial reflex within 3 weeks of injury indicates good prognosis. Bell’s palsy responded well to conservative measures. All traumatic facial palsies were due to longitudinal fracture and 2/3rd of these patients showed favourable outcome with medical therapy.

  20. THREE YEARS STUDY OF SCHWANNOMAS OF PERIPHERAL NERVES

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    Subha Dhua

    2017-02-01

    Full Text Available BACKGROUND In this paper authors present three cases of schwannomas including a case of multiple schwannomas without the features of neurofibromatosis (NF. There was no family history of neurofibromatosis. All the patients underwent surgical excision and improved from the symptomatic lesions. Histopathology confirmed these lesions as schwannomas. The authors recommend surgery for symptomatic lesions. Asymptomatic tumours can be monitored. Regular follow up is essential as they may develop fresh lesions at any time. The relevant literature is discussed. • Malignant transformation of the schwannomas is rare and has poor prognosis. It should be considered in the differential diagnosis of schwannomas. • We should distinguish between “ancient schwannoma” and malignant transformation of schwannoma since treatment and prognosis vary. • Imaging is not entirely reliable in differentiating benign from malignant peripheral nerve tumours. MATERIALS AND METHODS All the patients underwent surgical excision and improved from the symptomatic lesions. Histopathology confirmed these lesions as schwannomas. The authors recommend surgery for symptomatic lesions. RESULTS The histopathological studies confirmed the lesion as Flexi Schwannoma and surgery was considered to be the best option. CONCLUSION Schwannomas and meningiomas are usually benign tumours curable by complete removal. They occur either as single sporadic tumors in otherwise healthy individuals in the fourth to sixth decades of life or as multiple tumours at an early age as part of the autosomal dominant genetic disorder neurofibromatosis 2 (NF2. The hallmark feature of NF2 is bilateral vestibular schwannomas. Multiplicity, a lobular growth pattern, and invasiveness are typical features of NF2 schwannomas. The diagnosis of NF2 is difficult in a group of heterogeneous and poorly defined patients who do not have BVSs but present with other features suggestive of NF2, namely (1 multiple

  1. The Ahmed versus Baerveldt study: three-year treatment outcomes.

    Science.gov (United States)

    Christakis, Panos G; Tsai, James C; Kalenak, Jeffrey W; Zurakowski, David; Cantor, Louis B; Kammer, Jeffrey A; Ahmed, Iqbal I K

    2013-11-01

    To compare 2 commonly used aqueous drainage devices for the treatment of refractory glaucoma. International, multicenter, randomized trial. Patients aged 18 years or older with uncontrolled or high-risk glaucoma refractory to maximum medical therapy, many of whom had failed trabeculoplasty and trabeculectomy. Eligible patients were randomized to an Ahmed-FP7 valve implant (New World Medical, Inc., Rancho Cucamonga, CA) or a Baerveldt-350 implant (Abbott Medical Optics, Inc., Santa Ana, CA) using a standardized surgical technique. The primary outcome was failure, defined as intraocular pressure (IOP) outside of the target range (5-18 mmHg, with ≥20% reduction from baseline) for 2 consecutive visits after 3 months, vision-threatening complications, de novo glaucoma procedures, or loss of light perception. Secondary outcome measures include IOP, medication use, visual acuity, complications, and interventions. A total of 238 patients were enrolled and randomized; 124 received the Ahmed implant and 114 received the Baerveldt implant. Baseline characteristics were similar in both groups. Half the study group had secondary glaucoma, and 37% had previously failed trabeculectomy. The mean preoperative IOP was 31.4±10.8 mmHg on 3.1±1.0 glaucoma medications. Median baseline Snellen visual acuity was 20/100. At 3 years, the cumulative probability of failure was 51% in the Ahmed group and 34% in the Baerveldt group (P = 0.03). Mean IOP was 15.7±4.8 mmHg in the Ahmed group (49% reduction) and 14.4±5.1 mmHg in the Baerveldt group (55% reduction; P = 0.09). Mean number of glaucoma medications was 1.8±1.4 in the Ahmed group (42% reduction) and 1.1±1.3 in the Baerveldt group (65% reduction; P = 0.002). There was a moderate but similar decrease in visual acuity in both groups (PAhmed, 62% Baerveldt; P = 0.12); however, the Baerveldt group had a higher rate of hypotony-related vision-threatening complications (0% Ahmed, 6% Baerveldt; P = 0.005). More interventions were

  2. Assessments of higher-order ionospheric effects on GPS coordinate time series: A case study of CMONOC with longer time series

    Science.gov (United States)

    Jiang, Weiping; Deng, Liansheng; Zhou, Xiaohui; Ma, Yifang

    2014-05-01

    Higher-order ionospheric (HIO) corrections are proposed to become a standard part for precise GPS data analysis. For this study, we deeply investigate the impacts of the HIO corrections on the coordinate time series by implementing re-processing of the GPS data from Crustal Movement Observation Network of China (CMONOC). Nearly 13 year data are used in our three processing runs: (a) run NO, without HOI corrections, (b) run IG, both second- and third-order corrections are modeled using the International Geomagnetic Reference Field 11 (IGRF11) to model the magnetic field, (c) run ID, the same with IG but dipole magnetic model are applied. Both spectral analysis and noise analysis are adopted to investigate these effects. Results show that for CMONOC stations, HIO corrections are found to have brought an overall improvement. After the corrections are applied, the noise amplitudes decrease, with the white noise amplitudes showing a more remarkable variation. Low-latitude sites are more affected. For different coordinate components, the impacts vary. The results of an analysis of stacked periodograms show that there is a good match between the seasonal amplitudes and the HOI corrections, and the observed variations in the coordinate time series are related to HOI effects. HOI delays partially explain the seasonal amplitudes in the coordinate time series, especially for the U component. The annual amplitudes for all components are decreased for over one-half of the selected CMONOC sites. Additionally, the semi-annual amplitudes for the sites are much more strongly affected by the corrections. However, when diplole model is used, the results are not as optimistic as IGRF model. Analysis of dipole model indicate that HIO delay lead to the increase of noise amplitudes, and that HIO delays with dipole model can generate false periodic signals. When dipole model are used in modeling HIO terms, larger residual and noise are brought in rather than the effective improvements.

  3. The inner state differences of preterm birth rates in Brazil: a time series study

    OpenAIRE

    de Oliveira, Rosana Rosseto; Melo, Emiliana Cristina; Fujimori, Elizabeth; Mathias, Thais Aidar de Freitas

    2016-01-01

    Abstract Background Preterm birth is a serious public health problem, as it is linked to high rates of neonatal and child morbidity and mortality. The prevalence of premature births has increased worldwide, with regional differences. The objective of this study was to analyze the trend of preterm births in the state of Paraná, Brazil, according to Macro-regional and Regional Health Offices (RHOs). Methods This is an ecological time series study using preterm births records from the national l...

  4. The study of coastal groundwater depth and salinity variation using time-series analysis

    International Nuclear Information System (INIS)

    Tularam, G.A.; Keeler, H.P.

    2006-01-01

    A time-series approach is applied to study and model tidal intrusion into coastal aquifers. The authors examine the effect of tidal behaviour on groundwater level and salinity intrusion for the coastal Brisbane region using auto-correlation and spectral analyses. The results show a close relationship between tidal behaviour, groundwater depth and salinity levels for the Brisbane coast. The known effect can be quantified and incorporated into new models in order to more accurately map salinity intrusion into coastal groundwater table

  5. Statistical models and time series forecasting of sulfur dioxide: a case study Tehran.

    Science.gov (United States)

    Hassanzadeh, S; Hosseinibalam, F; Alizadeh, R

    2009-08-01

    This study performed a time-series analysis, frequency distribution and prediction of SO(2) levels for five stations (Pardisan, Vila, Azadi, Gholhak and Bahman) in Tehran for the period of 2000-2005. Most sites show a quite similar characteristic with highest pollution in autumn-winter time and least pollution in spring-summer. The frequency distributions show higher peaks at two residential sites. The potential for SO(2) problems is high because of high emissions and the close geographical proximity of the major industrial and urban centers. The ACF and PACF are nonzero for several lags, indicating a mixed (ARMA) model, then at Bahman station an ARMA model was used for forecasting SO(2). The partial autocorrelations become close to 0 after about 5 lags while the autocorrelations remain strong through all the lags shown. The results proved that ARMA (2,2) model can provides reliable, satisfactory predictions for time series.

  6. Predictive time-series modeling using artificial neural networks for Linac beam symmetry: an empirical study.

    Science.gov (United States)

    Li, Qiongge; Chan, Maria F

    2017-01-01

    Over half of cancer patients receive radiotherapy (RT) as partial or full cancer treatment. Daily quality assurance (QA) of RT in cancer treatment closely monitors the performance of the medical linear accelerator (Linac) and is critical for continuous improvement of patient safety and quality of care. Cumulative longitudinal QA measurements are valuable for understanding the behavior of the Linac and allow physicists to identify trends in the output and take preventive actions. In this study, artificial neural networks (ANNs) and autoregressive moving average (ARMA) time-series prediction modeling techniques were both applied to 5-year daily Linac QA data. Verification tests and other evaluations were then performed for all models. Preliminary results showed that ANN time-series predictive modeling has more advantages over ARMA techniques for accurate and effective applicability in the dosimetry and QA field. © 2016 New York Academy of Sciences.

  7. Argon concentration time-series as a tool to study gas dynamics in the hyporheic zone.

    Science.gov (United States)

    Mächler, Lars; Brennwald, Matthias S; Kipfer, Rolf

    2013-07-02

    The oxygen dynamics in the hyporheic zone of a peri-alpine river (Thur, Switzerland), were studied through recording and analyzing the concentration time-series of dissolved argon, oxygen, carbon dioxide, and temperature during low flow conditions, for a period of one week. The argon concentration time-series was used to investigate the physical gas dynamics in the hyporheic zone. Differences in the transport behavior of heat and gas were determined by comparing the diel temperature evolution of groundwater to the measured concentration of dissolved argon. These differences were most likely caused by vertical heat transport which influenced the local groundwater temperature. The argon concentration time-series were also used to estimate travel times by cross correlating argon concentrations in the groundwater with argon concentrations in the river. The information gained from quantifying the physical gas transport was used to estimate the oxygen turnover in groundwater after water recharge. The resulting oxygen turnover showed strong diel variations, which correlated with the water temperature during groundwater recharge. Hence, the variation in the consumption rate was most likely caused by the temperature dependence of microbial activity.

  8. Apparent oxygen utilization rates calculated from tritium and helium-3 profiles at the Bermuda Atlantic Time-series Study site

    Directory of Open Access Journals (Sweden)

    R. H. R. Stanley

    2012-06-01

    Full Text Available We present three years of Apparent Oxygen Utilization Rates (AOUR estimated from oxygen and tracer data collected over the ocean thermocline at monthly resolution between 2003 and 2006 at the Bermuda Atlantic Time-series Study (BATS site. We estimate water ages by calculating a transit time distribution from tritium and helium-3 data. The vertically integrated AOUR over the upper 500 m, which is a regional estimate of export, during the three years is 3.1 ± 0.5 mol O2 m−2 yr−1. This is comparable to previous AOUR-based estimates of export production at the BATS site but is several times larger than export estimates derived from sediment traps or 234Th fluxes. We compare AOUR determined in this study to AOUR measured in the 1980s and show AOUR is significantly greater today than decades earlier because of changes in AOU, rather than changes in ventilation rates. The changes in AOU are likely a methodological artefact associated with problems with early oxygen measurements.

  9. Studies in astronomical time series analysis. I - Modeling random processes in the time domain

    Science.gov (United States)

    Scargle, J. D.

    1981-01-01

    Several random process models in the time domain are defined and discussed. Attention is given to the moving average model, the autoregressive model, and relationships between and combinations of these models. Consideration is then given to methods for investigating pulse structure, procedures of model construction, computational methods, and numerical experiments. A FORTRAN algorithm of time series analysis has been developed which is relatively stable numerically. Results of test cases are given to study the effect of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the light curve of the quasar 3C 272 is considered as an example.

  10. Study of Railway Track Irregularity Standard Deviation Time Series Based on Data Mining and Linear Model

    Directory of Open Access Journals (Sweden)

    Jia Chaolong

    2013-01-01

    Full Text Available Good track geometry state ensures the safe operation of the railway passenger service and freight service. Railway transportation plays an important role in the Chinese economic and social development. This paper studies track irregularity standard deviation time series data and focuses on the characteristics and trend changes of track state by applying clustering analysis. Linear recursive model and linear-ARMA model based on wavelet decomposition reconstruction are proposed, and all they offer supports for the safe management of railway transportation.

  11. Long time series

    DEFF Research Database (Denmark)

    Hisdal, H.; Holmqvist, E.; Hyvärinen, V.

    Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the......Awareness that emission of greenhouse gases will raise the global temperature and change the climate has led to studies trying to identify such changes in long-term climate and hydrologic time series. This report, written by the...

  12. Interactions between particulate air pollution and temperature in air pollution mortality time series studies

    International Nuclear Information System (INIS)

    Roberts, Steven

    2004-01-01

    In many community time series studies on the effect of particulate air pollution on mortality, particulate air pollution is modeled additively. In this study, we investigated the interaction between daily particulate air pollution and daily mean temperature in Cook County, Illinois and Allegheny County, Pennsylvania, using data for the period 1987-1994. This was done through the use of joint particulate air pollution-temperature response surfaces and by stratifying the effect of particulate air pollution on mortality by temperature. Evidence that the effect of particulate air pollution on mortality may depend on temperature is found. However, the results were sensitive to the number of degrees of freedom used in the confounder adjustments, the particulate air pollution exposure measure, and how the effects of temperature on mortality are modeled. The results were less sensitive to the estimation method used--generalized linear models and natural cubic splines or generalized additive models and smoothing splines. The results of this study suggest that in community particulate air pollution mortality time series studies the possibility of an interaction between daily particulate air pollution and daily mean temperature should be considered

  13. [Time series studies of air pollution by fires and the effects on human health].

    Science.gov (United States)

    do Carmo, Cleber Nascimento; Hacon, Sandra de Souza

    2013-11-01

    Burnoffs (intentional fires for agricultural purposes) and forest fires of large proportions have been observed in various regions of the planet. Exposure to high levels of air pollutants emitted by fires can be responsible for various harmful effects on human health. In this article, the literature on estimating acute effects of air pollution on human health by fires in the regions with the highest number of fires on the planet, using a time series approach is summarized. An attempt was made to identify gaps in knowledge. The study consisted of a narrative review, in which the characteristics of the selected studies were grouped by regions of the planet with a higher incidence of burnoffs: Amazon, America, Australia and Asia. The results revealed a large number of studies in Australia, few studies in the Amazon and great heterogeneity in the results on the significant effects on human health.

  14. Monitoring Quarry Area with Landsat Long Time-Series for Socioeconomic Study

    Directory of Open Access Journals (Sweden)

    Haoteng Zhao

    2018-03-01

    Full Text Available Quarry sites result from human activity, which includes the removal of original vegetation and the overlying soil to dig out stones for building use. Therefore, the dynamics of the quarry area provide a unique view of human mining activities. Actually, the topographic changes caused by mining activities are also a result of the development of the local economy. Thus, monitoring the quarry area can provide information about the policies of the economy and environmental protection. In this paper, we developed a combined method of machine learning classification and quarry region analysis to estimate the quarry area in a quarry region near Beijing. A temporal smoothing based on the classification results of all years was applied in post-processing to remove outliers and obtain gently changing sequences along the monitoring term. The method was applied to Landsat images to derive a quarry distribution map and quarry area time series from 1984 to 2017, revealing significant inter-annual variability. The time series revealed a five-stage development of the quarry area with different growth patterns. As the study region lies on two jurisdictions—Tianjin and Hebei—a comparison of the quarry area changes in the two jurisdictions was applied, which revealed that the different policies in the two regions could impose different impacts on the development of a quarry area. An analysis concerning the relationship between quarry area and gross regional product (GRP was performed to explore the potential application on socioeconomic studies, and we found a strong positive correlation between quarry area and GRP in Langfang City, Hebei Province. These results demonstrate the potential benefit of annual monitoring over the long-term for socioeconomic studies, which can be used for mining decision making.

  15. Therapeutic Assessment of Complex Trauma: A Single-Case Time-Series Study.

    Science.gov (United States)

    Tarocchi, Anna; Aschieri, Filippo; Fantini, Francesca; Smith, Justin D

    2013-06-01

    The cumulative effect of repeated traumatic experiences in early childhood incrementally increases the risk of adjustment problems later in life. Surviving traumatic environments can lead to the development of an interrelated constellation of emotional and interpersonal symptoms termed complex posttraumatic stress disorder (CPTSD). Effective treatment of trauma begins with a multimethod psychological assessment and requires the use of several evidence-based therapeutic processes, including establishing a safe therapeutic environment, reprocessing the trauma, constructing a new narrative, and managing emotional dysregulation. Therapeutic Assessment (TA) is a semistructured, brief intervention that uses psychological testing to promote positive change. The case study of Kelly, a middle-aged woman with a history of repeated interpersonal trauma, illustrates delivery of the TA model for CPTSD. Results of this single-case time-series experiment indicate statistically significant symptom improvement as a result of participating in TA. We discuss the implications of these findings for assessing and treating trauma-related concerns, such as CPTSD.

  16. Studies in astronomical time series analysis: Modeling random processes in the time domain

    Science.gov (United States)

    Scargle, J. D.

    1979-01-01

    Random process models phased in the time domain are used to analyze astrophysical time series data produced by random processes. A moving average (MA) model represents the data as a sequence of pulses occurring randomly in time, with random amplitudes. An autoregressive (AR) model represents the correlations in the process in terms of a linear function of past values. The best AR model is determined from sampled data and transformed to an MA for interpretation. The randomness of the pulse amplitudes is maximized by a FORTRAN algorithm which is relatively stable numerically. Results of test cases are given to study the effects of adding noise and of different distributions for the pulse amplitudes. A preliminary analysis of the optical light curve of the quasar 3C 273 is given.

  17. GPS Position Time Series @ JPL

    Science.gov (United States)

    Owen, Susan; Moore, Angelyn; Kedar, Sharon; Liu, Zhen; Webb, Frank; Heflin, Mike; Desai, Shailen

    2013-01-01

    Different flavors of GPS time series analysis at JPL - Use same GPS Precise Point Positioning Analysis raw time series - Variations in time series analysis/post-processing driven by different users. center dot JPL Global Time Series/Velocities - researchers studying reference frame, combining with VLBI/SLR/DORIS center dot JPL/SOPAC Combined Time Series/Velocities - crustal deformation for tectonic, volcanic, ground water studies center dot ARIA Time Series/Coseismic Data Products - Hazard monitoring and response focused center dot ARIA data system designed to integrate GPS and InSAR - GPS tropospheric delay used for correcting InSAR - Caltech's GIANT time series analysis uses GPS to correct orbital errors in InSAR - Zhen Liu's talking tomorrow on InSAR Time Series analysis

  18. Ecological Momentary Assessments and Automated Time Series Analysis to Promote Tailored Health Care : A Proof-of-Principle Study

    NARCIS (Netherlands)

    van der Krieke, Lian; Emerencia, Ando C; Bos, Elisabeth H; Rosmalen, Judith Gm; Riese, Harriëtte; Aiello, Marco; Sytema, Sjoerd; de Jonge, Peter

    2015-01-01

    BACKGROUND: Health promotion can be tailored by combining ecological momentary assessments (EMA) with time series analysis. This combined method allows for studying the temporal order of dynamic relationships among variables, which may provide concrete indications for intervention. However,

  19. The ego under observation : childpsychiatric study of 40 three year old low birthweight children and 40 three year old full term and normal birthweight children

    NARCIS (Netherlands)

    D.M.J. De Raeymaecker (Dirk)

    1981-01-01

    textabstractThis comparative child-psychiatric study of a group of three-year-old children of low birth weight and a control group of full-term children had its origins in the co-operation which exists between the department of paediatrics and the department of child psychiatry in Sophia Children's

  20. Estimation of Dusty Days Using the Model of Time Series: A Case Study of Hormozgan Province

    Directory of Open Access Journals (Sweden)

    Mohsen Farahi

    2016-04-01

    Full Text Available Dust storm is one of the climatic hazards in the arid and semi-arid regions. Southern Iran with its hot and dry climate is more likely affected by the adverse consequences of dust storms due to the proximity to the dusty deserts of Saudi Arabia and Iraq, on one hand, and the synoptic situation for the occurrence of the dust storms in the Persian Gulf, on the other hand. In this study, the frequency of dusty days in Hormozgan Province was investigated and predicted. To this end, data were collected from the three synoptic stations in Bandar Abbas, Bandar Lengeh and Bandar-e Jask from the Iran Meteorological Organization during the statistical period of 1968-2008. Then, using the non-seasonal ARIMA (p, d, q, were analyzed in 16Minitab and the frequency of the dusty days in the region were predicted. Results of the study show that the ARIMA (1, 1, 1noc was the most appropriate pattern for predicting the frequency of dusty days in Hormozgan Province. The results showed that the predictions for Bandar-e Jask, compared to those of Bandar Abbas and Bandar Lengeh are more accurate in terms of continuous increasing trend and the interval stability of the time series prediction and the smaller difference between the observed values with the predicted values.

  1. Modeling time-series count data: the unique challenges facing political communication studies.

    Science.gov (United States)

    Fogarty, Brian J; Monogan, James E

    2014-05-01

    This paper demonstrates the importance of proper model specification when analyzing time-series count data in political communication studies. It is common for scholars of media and politics to investigate counts of coverage of an issue as it evolves over time. Many scholars rightly consider the issues of time dependence and dynamic causality to be the most important when crafting a model. However, to ignore the count features of the outcome variable overlooks an important feature of the data. This is particularly the case when modeling data with a low number of counts. In this paper, we argue that the Poisson autoregressive model (Brandt and Williams, 2001) accurately meets the needs of many media studies. We replicate the analyses of Flemming et al. (1997), Peake and Eshbaugh-Soha (2008), and Ura (2009) and demonstrate that models missing some of the assumptions of the Poisson autoregressive model often yield invalid inferences. We also demonstrate that the effect of any of these models can be illustrated dynamically with estimates of uncertainty through a simulation procedure. The paper concludes with implications of these findings for the practical researcher. Copyright © 2013 Elsevier Inc. All rights reserved.

  2. Gut microbiota trajectory in patients with severe burn: A time series study.

    Science.gov (United States)

    Wang, Xinying; Yang, Jianbo; Tian, Feng; Zhang, Li; Lei, Qiucheng; Jiang, Tingting; Zhou, Jihong; Yuan, Siming; Wang, Jun; Feng, Zhijian; Li, Jieshou

    2017-12-01

    This time series experiments aimed to investigate the dynamic change of gut microbiomes after severe burn and its association with enteral nutrition (EN). Seven severely burned patients who suffered from a severe metal dust explosion injury were recruited in this study. The dynamic changes of gut microbiome of fecal samples at six time points (1-3days, 2, 3, 4, 5 and 6weeks after severe burn) were detected using 16S ribosomal RNA pyrosequencing technology. Following the post-burn temporal order, gut microbiota dysbiosis was detected in the gut microbiome after severe burn, then it was gradually resolved. The bio-diversity of gut bacteria was initially decreased, and then returned to normal level. In addition, at the early stage (from 2 to 4weeks), the majority of those patients' gut microbiome were opportunistic pathogen genus, Enterococcus and Escherichia; while at the end of this study, the majority was a beneficial genus, Bacteroides. EN can promote the recovery of gut microbiota, especially in EN well-tolerated patients. Severe burn injury can cause a dramatic dysbiosis of gut microbiota. A trend of enriched beneficial bacteria and diminished opportunistic pathogen bacteria may serve as prognosis microbiome biomarkers of severe burn patients. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. A combined teamwork training and work standardisation intervention in operating theatres: controlled interrupted time series study.

    Science.gov (United States)

    Morgan, Lauren; Pickering, Sharon P; Hadi, Mohammed; Robertson, Eleanor; New, Steve; Griffin, Damian; Collins, Gary; Rivero-Arias, Oliver; Catchpole, Ken; McCulloch, Peter

    2015-02-01

    Teamwork training and system standardisation have both been proposed to reduce error and harm in surgery. Since the approaches differ markedly, there is potential for synergy between them. Controlled interrupted time series with a 3 month intervention and observation phases before and after. Operating theatres conducting elective orthopaedic surgery in a single hospital system (UK Hospital Trust). Teamwork training based on crew resource management plus training and follow-up support in developing standardised operating procedures. Focus of subsequent standardisation efforts decided by theatre staff. Paired observers watched whole procedures together. We assessed non-technical skills using NOTECHS II, technical performance using glitch rate and compliance with WHO checklist using a simple quality tool. We measured complication and readmission rates and hospital stay using hospital administrative records. Before/after change was compared in the active and control groups using two-way ANOVA and regression models. 1121 patients were operated on before and 1100 after intervention. 44 operations were observed before and 50 afterwards. Non-technical skills (p=0.002) and WHO compliance (pteamwork and system improvement causes marked improvements in team behaviour and WHO performance, but not technical performance or outcome. These findings are consistent with the synergistic hypothesis, but larger controlled studies with a strong implementation strategy are required to test potential outcome effects. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  4. A COMPARATIVE STUDY OF SIMULATION AND TIME SERIES MODEL IN QUANTIFYING BULLWHIP EFFECT IN SUPPLY CHAIN

    Directory of Open Access Journals (Sweden)

    T. V. O. Fabson

    2011-11-01

    Full Text Available Bullwhip (or whiplash effect is an observed phenomenon in forecast driven distribution channeland careful management of these effects is of great importance to managers of supply chain.Bullwhip effect refers to situations where orders to the suppliers tend to have larger variance thansales to the buyer (demand distortion and the distortion increases as we move up the supply chain.Due to the fact that demand of customer for product is unstable, business managers must forecast inorder to properly position inventory and other resources. Forecasts are statistically based and in mostcases, are not very accurate. The existence of forecast errors made it necessary for organizations tooften carry an inventory buffer called “safety stock”. Moving up the supply chain from the end userscustomers to raw materials supplier there is a lot of variation in demand that can be observed, whichcall for greater need for safety stock.This study compares the efficacy of simulation and Time Series model in quantifying the bullwhipeffects in supply chain management.

  5. Time series study of EUV spicules observed by SUMER/SoHO

    Science.gov (United States)

    Xia, L. D.; Popescu, M. D.; Doyle, J. G.; Giannikakis, J.

    2005-08-01

    Here we study the dynamic properties of EUV spicules seen at the solar limb. The selected data were obtained as time series in polar coronal holes by SUMER/SoHO. The short exposure time and the almost fixed position of the spectrometer's slit allow the analysis of spicule properties such as occurrence, lifetime and Doppler velocity. Our data reveal that spicules occur repeatedly at the same location with a birth rate of around 0.16/min as estimated at 10´´ above the limb and a lifetime ranging from 15 down to ≈3 min. We are able to see some spicules showing a process of “falling after rising” indicated by the sudden change of the Doppler velocity sign. A periodicity of ≈5 min is sometimes discernible in their occurrence. Most spicules have a height between 10´´ and 20´´ above the limb. Some can stretch up to 40´´; these “long macro-spicules” seem to be comprised of a group of high spicules. Some of them have an obvious periodicity in the radiance of ≈5 min.

  6. How to determine life expectancy change of air pollution mortality: a time series study

    Directory of Open Access Journals (Sweden)

    Chau PYK

    2011-03-01

    Full Text Available Abstract Background Information on life expectancy (LE change is of great concern for policy makers, as evidenced by discussions of the "harvesting" (or "mortality displacement" issue, i.e. how large an LE loss corresponds to the mortality results of time series (TS studies. Whereas loss of LE attributable to chronic air pollution exposure can be determined from cohort studies, using life table methods, conventional TS studies have identified only deaths due to acute exposure, during the immediate past (typically the preceding one to five days, and they provide no information about the LE loss per death. Methods We show how to obtain information on population-average LE loss by extending the observation window (largest "lag" of TS to include a sufficient number of "impact coefficients" for past exposures ("lags". We test several methods for determining these coefficients. Once all of the coefficients have been determined, the LE change is calculated as time integral of the relative risk change after a permanent step change in exposure. Results The method is illustrated with results for daily data of non-accidental mortality from Hong Kong for 1985 - 2005, regressed against PM10 and SO2 with observation windows up to 5 years. The majority of the coefficients is statistically significant. The magnitude of the SO2 coefficients is comparable to those for PM10. But a window of 5 years is not sufficient and the results for LE change are only a lower bound; it is consistent with what is implied by other studies of long term impacts. Conclusions A TS analysis can determine the LE loss, but if the observation window is shorter than the relevant exposures one obtains only a lower bound.

  7. Effect of an evidence-based website on healthcare usage: an interrupted time-series study

    Science.gov (United States)

    Spoelman, Wouter A; Bonten, Tobias N; de Waal, Margot W M; Drenthen, Ton; Smeele, Ivo J M; Nielen, Markus M J; Chavannes, Niels H

    2016-01-01

    Objectives Healthcare costs and usage are rising. Evidence-based online health information may reduce healthcare usage, but the evidence is scarce. The objective of this study was to determine whether the release of a nationwide evidence-based health website was associated with a reduction in healthcare usage. Design Interrupted time series analysis of observational primary care data of healthcare use in the Netherlands from 2009 to 2014. Setting General community primary care. Population 912 000 patients who visited their general practitioners 18.1 million times during the study period. Intervention In March 2012, an evidence-based health information website was launched by the Dutch College of General Practitioners. It was easily accessible and understandable using plain language. At the end of the study period, the website had 2.9 million unique page views per month. Main outcomes measures Primary outcome was the change in consultation rate (consultations/1000 patients/month) before and after the release of the website. Additionally, a reference group was created by including consultations about topics not being viewed at the website. Subgroup analyses were performed for type of consultations, sex, age and socioeconomic status. Results After launch of the website, the trend in consultation rate decreased with 1.620 consultations/1000 patients/month (p<0.001). This corresponds to a 12% decline in consultations 2 years after launch of the website. The trend in consultation rate of the reference group showed no change. The subgroup analyses showed a specific decline for consultations by phone and were significant for all other subgroups, except for the youngest age group. Conclusions Healthcare usage decreased by 12% after providing high-quality evidence-based online health information. These findings show that e-Health can be effective to improve self-management and reduce healthcare usage in times of increasing healthcare costs. PMID:28186945

  8. Effect of an evidence-based website on healthcare usage: an interrupted time-series study.

    Science.gov (United States)

    Spoelman, Wouter A; Bonten, Tobias N; de Waal, Margot W M; Drenthen, Ton; Smeele, Ivo J M; Nielen, Markus M J; Chavannes, Niels H

    2016-11-09

    Healthcare costs and usage are rising. Evidence-based online health information may reduce healthcare usage, but the evidence is scarce. The objective of this study was to determine whether the release of a nationwide evidence-based health website was associated with a reduction in healthcare usage. Interrupted time series analysis of observational primary care data of healthcare use in the Netherlands from 2009 to 2014. General community primary care. 912 000 patients who visited their general practitioners 18.1 million times during the study period. In March 2012, an evidence-based health information website was launched by the Dutch College of General Practitioners. It was easily accessible and understandable using plain language. At the end of the study period, the website had 2.9 million unique page views per month. Primary outcome was the change in consultation rate (consultations/1000 patients/month) before and after the release of the website. Additionally, a reference group was created by including consultations about topics not being viewed at the website. Subgroup analyses were performed for type of consultations, sex, age and socioeconomic status. After launch of the website, the trend in consultation rate decreased with 1.620 consultations/1000 patients/month (pHealthcare usage decreased by 12% after providing high-quality evidence-based online health information. These findings show that e-Health can be effective to improve self-management and reduce healthcare usage in times of increasing healthcare costs. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  9. A scalable database model for multiparametric time series: a volcano observatory case study

    Science.gov (United States)

    Montalto, Placido; Aliotta, Marco; Cassisi, Carmelo; Prestifilippo, Michele; Cannata, Andrea

    2014-05-01

    The variables collected by a sensor network constitute a heterogeneous data source that needs to be properly organized in order to be used in research and geophysical monitoring. With the time series term we refer to a set of observations of a given phenomenon acquired sequentially in time. When the time intervals are equally spaced one speaks of period or sampling frequency. Our work describes in detail a possible methodology for storage and management of time series using a specific data structure. We designed a framework, hereinafter called TSDSystem (Time Series Database System), in order to acquire time series from different data sources and standardize them within a relational database. The operation of standardization provides the ability to perform operations, such as query and visualization, of many measures synchronizing them using a common time scale. The proposed architecture follows a multiple layer paradigm (Loaders layer, Database layer and Business Logic layer). Each layer is specialized in performing particular operations for the reorganization and archiving of data from different sources such as ASCII, Excel, ODBC (Open DataBase Connectivity), file accessible from the Internet (web pages, XML). In particular, the loader layer performs a security check of the working status of each running software through an heartbeat system, in order to automate the discovery of acquisition issues and other warning conditions. Although our system has to manage huge amounts of data, performance is guaranteed by using a smart partitioning table strategy, that keeps balanced the percentage of data stored in each database table. TSDSystem also contains modules for the visualization of acquired data, that provide the possibility to query different time series on a specified time range, or follow the realtime signal acquisition, according to a data access policy from the users.

  10. Stochastic approaches for time series forecasting of boron: a case study of Western Turkey.

    Science.gov (United States)

    Durdu, Omer Faruk

    2010-10-01

    In the present study, a seasonal and non-seasonal prediction of boron concentrations time series data for the period of 1996-2004 from Büyük Menderes river in western Turkey are addressed by means of linear stochastic models. The methodology presented here is to develop adequate linear stochastic models known as autoregressive integrated moving average (ARIMA) and multiplicative seasonal autoregressive integrated moving average (SARIMA) to predict boron content in the Büyük Menderes catchment. Initially, the Box-Whisker plots and Kendall's tau test are used to identify the trends during the study period. The measurements locations do not show significant overall trend in boron concentrations, though marginal increasing and decreasing trends are observed for certain periods at some locations. ARIMA modeling approach involves the following three steps: model identification, parameter estimation, and diagnostic checking. In the model identification step, considering the autocorrelation function (ACF) and partial autocorrelation function (PACF) results of boron data series, different ARIMA models are identified. The model gives the minimum Akaike information criterion (AIC) is selected as the best-fit model. The parameter estimation step indicates that the estimated model parameters are significantly different from zero. The diagnostic check step is applied to the residuals of the selected ARIMA models and the results indicate that the residuals are independent, normally distributed, and homoscadastic. For the model validation purposes, the predicted results using the best ARIMA models are compared to the observed data. The predicted data show reasonably good agreement with the actual data. The comparison of the mean and variance of 3-year (2002-2004) observed data vs predicted data from the selected best models show that the boron model from ARIMA modeling approaches could be used in a safe manner since the predicted values from these models preserve the basic

  11. Future mission studies: Forecasting solar flux directly from its chaotic time series

    Science.gov (United States)

    Ashrafi, S.

    1991-01-01

    The mathematical structure of the programs written to construct a nonlinear predictive model to forecast solar flux directly from its time series without reference to any underlying solar physics is presented. This method and the programs are written so that one could apply the same technique to forecast other chaotic time series, such as geomagnetic data, attitude and orbit data, and even financial indexes and stock market data. Perhaps the most important application of this technique to flight dynamics is to model Goddard Trajectory Determination System (GTDS) output of residues between observed position of spacecraft and calculated position with no drag (drag flag = off). This would result in a new model of drag working directly from observed data.

  12. Characteristics of Articles About Human Papillomavirus Vaccination in Japanese Newspapers: Time-Series Analysis Study.

    Science.gov (United States)

    Ueda, Nao; Yokouchi, Ryoki; Onoda, Taro; Ogihara, Atsushi

    2017-12-19

    Media coverage and reports have a major influence on individual vaccination and other health-related activities. People use the media to seek information and knowledge on health-related behaviors. They obtain health-related information from media such as television and newspapers, and they trust such information. While several studies have examined the relation between media coverage and individual health, there is a lack of studies that have analyzed media reports of health information. In particular, we have found no analyses related to cervical cancer (human papillomavirus [HPV]) vaccine. This study aimed to identify mentions of cervical cancer vaccine in Japan's printed news media and to determine their characteristics. We used the archival databases of 2 Japanese newspapers, Yomiuri Shimbun (Yomidasu Rekishikan) and Asahi Shimbun (Kikuzo II Visual), for text mining. First, we created a database by extracting articles published between January 1, 2007, and December 31, 2014, that matched the terms "cervical cancer" AND "vaccination" in a keyword search. Then, we tallied the extracted articles based on the month of publication and number of characters in order to conduct a time-series analysis. We extracted a total of 219 articles. Of these, 154 (70.3%) were positive and 51 (23.3%) were negative toward HPV vaccination. Of the 51 negative articles, 4 (7.8%) were published before June 2013, when routine vaccination was temporarily discontinued due to concerns regarding side effects, and 47 (92.2%) were published since then. The negative reports commonly cited side effects, although prior to June 2013, these issues were hardly mentioned. Although foreign media reports mentioned side effects before routine vaccination was temporarily discontinued, fewer articles mentioned side effects than recommendations for vaccination. Furthermore, on June 13, 2013, the World Health Organization's advisory body Global Advisory Committee on Vaccine Safety issued a statement

  13. Classroom Connectivity and Algebra 1 Achievement: A Three-Year Longitudinal Study

    Science.gov (United States)

    Irving, Karen E.; Pape, Stephen J.; Owens, Douglas T.; Abrahamson, Louis; Silver, David; Sanalan, Vehbi A.

    2016-01-01

    Findings from three years of a longitudinal randomized control trial involving a national U.S. sample of Algebra 1 teachers and students are reported. The study examines the effects of a connected classroom technology (CCT) professional development and classroom intervention on student achievement when compared to classroom instruction with…

  14. Particulate organic carbon mass distribution at the Bermuda Atlantic Time-series Study (BATS) site

    Science.gov (United States)

    Gundersen, Kjell; Orcutt, Karen M.; Purdie, Duncan A.; Michaels, Anthony F.; Knap, Anthony H.

    Errors in total particulate organic carbon (total POC) measurements caused by particles settling in Niskin water samplers, loss of bacterial cells during filtration and undersampling of rare particles such as the diazotrophic cyanobacterium Trichodesmium spp. were investigated at the Bermuda Atlantic Time-series Study (BATS) site. Regular core samples of temperature, primary production, bacterial abundance, chlorophyll- a (Chl- a) and POC were collected at monthly intervals from 1991 to 1996. During this period of time, shorter investigations of particles settling in water samples (1991-1992), bacterial cells lost during filtration (1992-1993), and Trichodesmium abundance (1995-1996) were performed at the BATS site. The BATS site shows striking seasonal patterns in hydrography and phytoplankton primary productivity, with a strong maximum immediately following the deep winter mixing of the water column. Following the peak in primary production, bacterial abundance showed only slightly elevated levels in spring. Maxima of Chl- a and POC also were associated with the primary production peaks, but these particle concentrations became less pronounced through summer and fall. An average of 26% of total POC collected in Niskin water bottles settled below the spigot before it could be sampled. An average of 47% of all bacterial cells passed the nominal pore size of a Whatman GF/F filter, and total POC measurements generated from GF/F filtered seawater samples had to be corrected for this loss. The average integrated stocks of total POC in the upper 65 m of the water column was 32% pigmented phytoplankton, 15% microheterotrophs, 54% other detrital matter (32 : 15 : 54). Phytoplankton C equaled bacterial C in the 65-135 m depth range (16 : 19 : 65), but phytoplankton C was virtually non-existent deeper than 135 m (2 : 14 : 74). Bacterial C biomass was higher than phytoplankton in surface waters outside the spring bloom period, but carbon not accounted for by phytoplankton

  15. Investigation of Noises in GPS Time Series: Case Study on Epn Weekly Solutions

    Science.gov (United States)

    Klos, Anna; Bogusz, Janusz; Figurski, Mariusz; Kosek, Wieslaw; Gruszczynski, Maciej

    2014-05-01

    The noises in GPS time series are stated to be described the best by the combination of white (Gaussian) and power-law processes. They are mainly the effect of mismodelled satellite orbits, Earth orientation parameters, atmospheric effects, antennae phase centre effects, or of monument instability. Due to the fact, that velocities of permanent stations define the kinematic reference frame, they have to fulfil the requirement of being stable at 0.1 mm/yr. The previously performed researches showed, that the wrong assumption of noise model leads to the underestimation of velocities and their uncertainties from 2 up to even 11, especially in the Up direction. This presentation focuses on more than 200 EPN (EUREF Permanent Network) stations from the area of Europe with various monument types (concrete pillars, buildings, metal masts, with or without domes, placed on the ground or on the rock) and coordinates of weekly changes (GPS weeks 0834-1459). The topocentric components (North, East, Up) in ITRF2005 which come from the EPN Re-Processing made by the Military University of Technology Local Analysis Centre (MUT LAC) were processed with Maximum Likelihood Estimation (MLE) using CATS software. We have assumed the existence of few combinations of noise models (these are: white, flicker and random walk noise with integer spectral indices and power-law noise models with fractional spectral indices) and investigated which of them EPN weekly time series are likely to follow. The results show, that noises in GPS time series are described the best by the combination of white and flicker noise model. It is strictly related to the so-called common mode error (CME) that is spatially correlated error being one of the dominant error source in GPS solutions. We have assumed CME as spatially uniform, what was a good approximation for stations located hundreds of kilometres one to another. Its removal with spatial filtering reduces the amplitudes of white and flicker noise by a

  16. The Validity and Precision of the Comparative Interrupted Time-Series Design: Three Within-Study Comparisons

    Science.gov (United States)

    St. Clair, Travis; Hallberg, Kelly; Cook, Thomas D.

    2016-01-01

    We explore the conditions under which short, comparative interrupted time-series (CITS) designs represent valid alternatives to randomized experiments in educational evaluations. To do so, we conduct three within-study comparisons, each of which uses a unique data set to test the validity of the CITS design by comparing its causal estimates to…

  17. An ecological time-series study of heat-related mortality in three European cities

    Directory of Open Access Journals (Sweden)

    Russo Antonio

    2008-01-01

    Full Text Available Abstract Background Europe has experienced warmer summers in the past two decades and there is a need to describe the determinants of heat-related mortality to better inform public health activities during hot weather. We investigated the effect of high temperatures on daily mortality in three cities in Europe (Budapest, London, and Milan, using a standard approach. Methods An ecological time-series study of daily mortality was conducted in three cities using Poisson generalized linear models allowing for over-dispersion. Secular trends in mortality and seasonal confounding factors were controlled for using cubic smoothing splines of time. Heat exposure was modelled using average values of the temperature measure on the same day as death (lag 0 and the day before (lag 1. The heat effect was quantified assuming a linear increase in risk above a cut-point for each city. Socio-economic status indicators and census data were linked with mortality data for stratified analyses. Results The risk of heat-related death increased with age, and females had a greater risk than males in age groups ≥65 years in London and Milan. The relative risks of mortality (per °C above the heat cut-point by gender and age were: (i Male 1.10 (95%CI: 1.07–1.12 and Female 1.07 (1.05–1.10 for 75–84 years, (ii M 1.10 (1.06–1.14 and F 1.08 (1.06–1.11 for ≥85 years in Budapest (≥24°C; (i M 1.03 (1.01–1.04 and F 1.07 (1.05–1.09, (ii M 1.05 (1.03–1.07 and F 1.08 (1.07–1.10 in London (≥20°C; and (i M 1.08 (1.03–1.14 and F 1.20 (1.15–1.26, (ii M 1.18 (1.11–1.26 and F 1.19 (1.15–1.24 in Milan (≥26°C. Mortality from external causes increases at higher temperatures as well as that from respiratory and cardiovascular disease. There was no clear evidence of effect modification by socio-economic status in either Budapest or London, but there was a seemingly higher risk for affluent non-elderly adults in Milan. Conclusion We found broadly consistent

  18. Software for the nuclear reactor dynamics study using time series processing

    International Nuclear Information System (INIS)

    Valero, Esbel T.; Montesino, Maria E.

    1997-01-01

    The parametric monitoring in Nuclear Power Plant (NPP) permits the operational surveillance of nuclear reactor. The methods employed in order to process this information such as FFT, autoregressive models and other, have some limitations when those regimens in which appear strongly non-linear behaviors are analyzed. In last years the chaos theory has offered new ways in order to explain complex dynamic behaviors. This paper describes a software (ECASET) that allow, by time series processing from NPP's acquisition system, to characterize the nuclear reactor dynamic as a complex dynamical system. Here we show using ECASET's results the possibility of classifying the different regimens appearing in nuclear reactors. The results of several temporal series processing from real systems are introduced. This type of analysis complements the results obtained with traditional methods and can constitute a new tool for monitoring nuclear reactors. (author). 13 refs., 3 figs

  19. Studies in astronomical time series analysis. IV - Modeling chaotic and random processes with linear filters

    Science.gov (United States)

    Scargle, Jeffrey D.

    1990-01-01

    While chaos arises only in nonlinear systems, standard linear time series models are nevertheless useful for analyzing data from chaotic processes. This paper introduces such a model, the chaotic moving average. This time-domain model is based on the theorem that any chaotic process can be represented as the convolution of a linear filter with an uncorrelated process called the chaotic innovation. A technique, minimum phase-volume deconvolution, is introduced to estimate the filter and innovation. The algorithm measures the quality of a model using the volume covered by the phase-portrait of the innovation process. Experiments on synthetic data demonstrate that the algorithm accurately recovers the parameters of simple chaotic processes. Though tailored for chaos, the algorithm can detect both chaos and randomness, distinguish them from each other, and separate them if both are present. It can also recover nonminimum-delay pulse shapes in non-Gaussian processes, both random and chaotic.

  20. A Spatial Data Infrastructure Integrating Multisource Heterogeneous Geospatial Data and Time Series: A Study Case in Agriculture

    Directory of Open Access Journals (Sweden)

    Gloria Bordogna

    2016-05-01

    Full Text Available Currently, the best practice to support land planning calls for the development of Spatial Data Infrastructures (SDI capable of integrating both geospatial datasets and time series information from multiple sources, e.g., multitemporal satellite data and Volunteered Geographic Information (VGI. This paper describes an original OGC standard interoperable SDI architecture and a geospatial data and metadata workflow for creating and managing multisource heterogeneous geospatial datasets and time series, and discusses it in the framework of the Space4Agri project study case developed to support the agricultural sector in Lombardy region, Northern Italy. The main novel contributions go beyond the application domain for which the SDI has been developed and are the following: the ingestion within an a-centric SDI, potentially distributed in several nodes on the Internet to support scalability, of products derived by processing remote sensing images, authoritative data, georeferenced in-situ measurements and voluntary information (VGI created by farmers and agronomists using an original Smart App; the workflow automation for publishing sets and time series of heterogeneous multisource geospatial data and relative web services; and, finally, the project geoportal, that can ease the analysis of the geospatial datasets and time series by providing complex intelligent spatio-temporal query and answering facilities.

  1. Time Series Analysis OF SAR Image Fractal Maps: The Somma-Vesuvio Volcanic Complex Case Study

    Science.gov (United States)

    Pepe, Antonio; De Luca, Claudio; Di Martino, Gerardo; Iodice, Antonio; Manzo, Mariarosaria; Pepe, Susi; Riccio, Daniele; Ruello, Giuseppe; Sansosti, Eugenio; Zinno, Ivana

    2016-04-01

    The fractal dimension is a significant geophysical parameter describing natural surfaces representing the distribution of the roughness over different spatial scale; in case of volcanic structures, it has been related to the specific nature of materials and to the effects of active geodynamic processes. In this work, we present the analysis of the temporal behavior of the fractal dimension estimates generated from multi-pass SAR images relevant to the Somma-Vesuvio volcanic complex (South Italy). To this aim, we consider a Cosmo-SkyMed data-set of 42 stripmap images acquired from ascending orbits between October 2009 and December 2012. Starting from these images, we generate a three-dimensional stack composed by the corresponding fractal maps (ordered according to the acquisition dates), after a proper co-registration. The time-series of the pixel-by-pixel estimated fractal dimension values show that, over invariant natural areas, the fractal dimension values do not reveal significant changes; on the contrary, over urban areas, it correctly assumes values outside the natural surfaces fractality range and show strong fluctuations. As a final result of our analysis, we generate a fractal map that includes only the areas where the fractal dimension is considered reliable and stable (i.e., whose standard deviation computed over the time series is reasonably small). The so-obtained fractal dimension map is then used to identify areas that are homogeneous from a fractal viewpoint. Indeed, the analysis of this map reveals the presence of two distinctive landscape units corresponding to the Mt. Vesuvio and Gran Cono. The comparison with the (simplified) geological map clearly shows the presence in these two areas of volcanic products of different age. The presented fractal dimension map analysis demonstrates the ability to get a figure about the evolution degree of the monitored volcanic edifice and can be profitably extended in the future to other volcanic systems with

  2. Study on Apparent Kinetic Prediction Model of the Smelting Reduction Based on the Time-Series

    Directory of Open Access Journals (Sweden)

    Guo-feng Fan

    2012-01-01

    Full Text Available A series of direct smelting reduction experiment has been carried out with high phosphorous iron ore of the different bases by thermogravimetric analyzer. The derivative thermogravimetric (DTG data have been obtained from the experiments. One-step forward local weighted linear (LWL method , one of the most suitable ways of predicting chaotic time-series methods which focus on the errors, is used to predict DTG. In the meanwhile, empirical mode decomposition-autoregressive (EMD-AR, a data mining technique in signal processing, is also used to predict DTG. The results show that (1 EMD-AR(4 is the most appropriate and its error is smaller than the former; (2 root mean square error (RMSE has decreased about two-thirds; (3 standardized root mean square error (NMSE has decreased in an order of magnitude. Finally in this paper, EMD-AR method has been improved by golden section weighting; its error would be smaller than before. Therefore, the improved EMD-AR model is a promising alternative for apparent reaction rate (DTG. The analytical results have been an important reference in the field of industrial control.

  3. A Time Series Analysis of Global Soil Moisture Data Products for Water Cycle Studies

    Science.gov (United States)

    Zhan, X.; Yin, J.; Liu, J.; Fang, L.; Hain, C.; Ferraro, R. R.; Weng, F.

    2017-12-01

    Water is essential for sustaining life on our planet Earth and water cycle is one of the most important processes of out weather and climate system. As one of the major components of the water cycle, soil moisture impacts significantly the other water cycle components (e.g. evapotranspiration, runoff, etc) and the carbon cycle (e.g. plant/crop photosynthesis and respiration). Understanding of soil moisture status and dynamics is crucial for monitoring and predicting the weather, climate, hydrology and ecological processes. Satellite remote sensing has been used for soil moisture observation since the launch of the Scanning Multi-channel Microwave Radiometer (SMMR) on NASA's Nimbus-7 satellite in 1978. Many satellite soil moisture data products have been made available to the science communities and general public. The soil moisture operational product system (SMOPS) of NOAA NESDIS has been operationally providing global soil moisture data products from each of the currently available microwave satellite sensors and their blends. This presentation will provide an update of SMOPS products. The time series of each of these soil moisture data products are analyzed against other data products, such as precipitation and evapotranspiration from other independent data sources such as the North America Land Data Assimilation System (NLDAS). Temporal characteristics of these water cycle components are explored against some historical events, such as the 2010 Russian, 2010 China and 2012 United States droughts, 2015 South Carolina floods, etc. Finally whether a merged global soil moisture data product can be used as a climate data record is evaluated based on the above analyses.

  4. Musculoskeletal symptoms and job strain among nursing personnel: a study over a three year period.

    Science.gov (United States)

    Josephson, M; Lagerström, M; Hagberg, M; Wigaeus Hjelm, E

    1997-01-01

    OBJECTIVES: To examine the variation of symptoms from the neck, shoulders, and back over a three year period among female nursing personnel and the relation between job strain and musculoskeletal symptoms. METHODS: At a county hospital the female nursing personnel answered a questionnaire at baseline and then once a year over a period of three years. There were 565, 553, 562, and 419 subjects who answered the questionnaire at the first, second, third, and fourth survey, respectively. Of the study group, 285 nursing personnel answered the questionnaire on four occasions. Ongoing symptoms of the neck, shoulders, and back were assessed by means of a 10 point (0-9) scale with the verbal end points "no symptoms" and "very intense symptoms." Cases were defined as nursing personnel reporting ongoing symptoms, score > 6, from at least one of the body regions. For assessments of job strain, a Swedish version of Karasek and Theorell's model was used. RESULTS: Of the 285 subjects, 13% were defined as cases at all four assessments, and 46% varied between cases and not cases during the study period. In the repeated cross sectional surveys the estimated rate ratio (RR) for being a case was between 1.1 and 1.5 when comparing the group with job strain and the group without job strain. For the combination of job strain and perceived high physical exertion the estimated RR was between 1.5 and 2.1. When the potential risk factors were assessed one, two, or three years before the assessment of symptoms the estimated RR for becoming a case was between 1.4 and 2.2 when comparing the group with job strain and the group without job strain. CONCLUSION: Almost half of the healthcare workers varied between being a case and not, over a three year period. The analysis indicated that job strain is a risk factor for musculoskeletal symptoms and that the risk is higher when it is combined with perceived high physical exertion. PMID:9423583

  5. Studies on English Vocabulary Learning Strategies of Three-year Business English Majors

    Institute of Scientific and Technical Information of China (English)

    Liu Fang-rong

    2008-01-01

    Vocabulary learning strategies have been studied by a lot of scholars and teachers to a different extent on language learner of different levels. Little research has been done on three-year .Business English majors. This study is intended to examine the vocabulary learning strategies applied by those students to their vocabulary learning during the course of English learning. This study is carried out in the form of doing a questionnaire among 117 three-year Business English majors. The collected data is analyzed in the computer by using the SPSS software. The result is that most of the students give up the concept and strategy of repetition and accept the concept of context and practicing. In addition, most of the students know how to make use of cognitive strategies to learn vocabulary. However, those students seldom employ metacognitive strategies and social/affective strategies to facilitate their vocabulary learning. In fight of these, some recommendations have given to those students to help them learn more vocabulary by appropriately using the vocabulary learning strategies.

  6. Time-series analysis to study the impact of an intersection on dispersion along a street canyon.

    Science.gov (United States)

    Richmond-Bryant, Jennifer; Eisner, Alfred D; Hahn, Intaek; Fortune, Christopher R; Drake-Richman, Zora E; Brixey, Laurie A; Talih, M; Wiener, Russell W; Ellenson, William D

    2009-12-01

    This paper presents data analysis from the Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study to assess the transport of ultrafine particulate matter (PM) across urban intersections. Experiments were performed in a street canyon perpendicular to a highway in Brooklyn, NY, USA. Real-time ultrafine PM samplers were positioned on either side of an intersection at multiple locations along a street to collect time-series number concentration data. Meteorology equipment was positioned within the street canyon and at an upstream background site to measure wind speed and direction. Time-series analysis was performed on the PM data to compute a transport velocity along the direction of the street for the cases where background winds were parallel and perpendicular to the street. The data were analyzed for sampler pairs located (1) on opposite sides of the intersection and (2) on the same block. The time-series analysis demonstrated along-street transport, including across the intersection when background winds were parallel to the street canyon and there was minimal transport and no communication across the intersection when background winds were perpendicular to the street canyon. Low but significant values of the cross-correlation function (CCF) underscore the turbulent nature of plume transport along the street canyon. The low correlations suggest that flow switching around corners or traffic-induced turbulence at the intersection may have aided dilution of the PM plume from the highway. This observation supports similar findings in the literature. Furthermore, the time-series analysis methodology applied in this study is introduced as a technique for studying spatiotemporal variation in the urban microscale environment.

  7. Predicting Charging Time of Battery Electric Vehicles Based on Regression and Time-Series Methods: A Case Study of Beijing

    Directory of Open Access Journals (Sweden)

    Jun Bi

    2018-04-01

    Full Text Available Battery electric vehicles (BEVs reduce energy consumption and air pollution as compared with conventional vehicles. However, the limited driving range and potential long charging time of BEVs create new problems. Accurate charging time prediction of BEVs helps drivers determine travel plans and alleviate their range anxiety during trips. This study proposed a combined model for charging time prediction based on regression and time-series methods according to the actual data from BEVs operating in Beijing, China. After data analysis, a regression model was established by considering the charged amount for charging time prediction. Furthermore, a time-series method was adopted to calibrate the regression model, which significantly improved the fitting accuracy of the model. The parameters of the model were determined by using the actual data. Verification results confirmed the accuracy of the model and showed that the model errors were small. The proposed model can accurately depict the charging time characteristics of BEVs in Beijing.

  8. Time-series-based hybrid mathematical modelling method adapted to forecast automotive and medical waste generation: Case study of Lithuania.

    Science.gov (United States)

    Karpušenkaitė, Aistė; Ruzgas, Tomas; Denafas, Gintaras

    2018-05-01

    The aim of the study was to create a hybrid forecasting method that could produce higher accuracy forecasts than previously used 'pure' time series methods. Mentioned methods were already tested with total automotive waste, hazardous automotive waste, and total medical waste generation, but demonstrated at least a 6% error rate in different cases and efforts were made to decrease it even more. Newly developed hybrid models used a random start generation method to incorporate different time-series advantages and it helped to increase the accuracy of forecasts by 3%-4% in hazardous automotive waste and total medical waste generation cases; the new model did not increase the accuracy of total automotive waste generation forecasts. Developed models' abilities to forecast short- and mid-term forecasts were tested using prediction horizon.

  9. Evolution of stratospheric ozone and water vapour time series studied with satellite measurements

    Directory of Open Access Journals (Sweden)

    A. Jones

    2009-08-01

    Full Text Available The long term evolution of stratospheric ozone and water vapour has been investigated by extending satellite time series to April 2008. For ozone, we examine monthly average ozone values from various satellite data sets for nine latitude and altitude bins covering 60° S to 60° N and 20–45 km and covering the time period of 1979–2008. Data are from the Stratospheric Aerosol and Gas Experiment (SAGE I+II, the HALogen Occultation Experiment (HALOE, the Solar BackscatterUltraViolet-2 (SBUV/2 instrument, the Sub-Millimetre Radiometer (SMR, the Optical Spectrograph InfraRed Imager System (OSIRIS, and the SCanning Imaging Absorption spectroMeter for Atmospheric CHartograpY (SCIAMACHY. Monthly ozone anomalies are calculated by utilising a linear regression model, which also models the solar, quasi-biennial oscillation (QBO, and seasonal cycle contributions. Individual instrument ozone anomalies are combined producing an all instrument average. Assuming a turning point of 1997 and that the all instrument average is represented by good instrumental long term stability, the largest statistically significant ozone declines (at two sigma from 1979–1997 are seen at the mid-latitudes between 35 and 45 km, namely −7.2%±0.9%/decade in the Northern Hemisphere and −7.1%±0.9%/in the Southern Hemisphere. Furthermore, for the period 1997 to 2008 we find that the same locations show the largest ozone recovery (+1.4% and +0.8%/decade respectively compared to other global regions, although the estimated trend model errors indicate that the trend estimates are not significantly different from a zero trend at the 2 sigma level. An all instrument average is also constructed from water vapour anomalies during 1991–2008, using the SAGE II, HALOE, SMR, and the Microwave Limb Sounder (Aura/MLS measurements. We report that the decrease in water vapour values after 2001 slows down around 2004–2005 in the lower tropical stratosphere (20–25 km and has even

  10. Three year results of the Prospective Evaluation of Radial Keratotomy (PERK study

    Directory of Open Access Journals (Sweden)

    Waring III George

    1990-01-01

    Full Text Available The Prospective Evaluation of Radial Keratotomy (PERK study is a nine-center clinical trial of a standardized technique of radial keratotomy in 435 patients who had simple myopia with a preoperative refractive error between -2.00 and -8.00 diopters (D. We report results for one eye of each patient. The surgical technique consisted of eight incisions using a diamond micrometer knife with the blade length determined by intraoperative ultrasonic pachymetry and the diameter of the central clear zone determined by the preoperative refractive error. At three years after surgery, 58% of eyes had refractive error within one diopter of emmetropia; 26% were undercorrected, and 16% were overcorrected by more than one diopter. Uncorrected visual acuity was 20/40 or better in 76% of eyes. The operation was more effective in eyes with a preoperative refractive error between -2.00 and -4.37 diopters. Between one and three years after surgery, the refractive error changed by 1.00 diopter or more in 12% of eyes, indicating a lack of stability in some eyes.

  11. US independent to spend over $1bn in next three years. Case study: Anadarko

    International Nuclear Information System (INIS)

    Anon.

    1996-01-01

    This special report draws together four articles connected with the current state of the Liquefied Natural Gas (LNG) industry. The first looks at rapidly expanding demand for LNG in the Asia-Pacific region. Growth prospects for the industry are good with a tripling of output anticipated by the year 2015. The Tiga project, in Malaysia, part of an ambitious expansion programme, is set to enable Malaysia to challenge Indonesia as the world's leading LNG producer, and is described in the second report. Thirdly, the increasing size of bulk gas carriers, the most sophisticated merchant ships afloat, offer improved economic returns. Plans are underway for a vessel capable of carrying 160,000 cm of gas. The report concludes with a case study of the A3 company Anadarko's financial prospects. The US independent company is planning an ambitious capital expenditure programme of over $1bn in the next three years. (UK)

  12. A three-year longitudinal study of affective temperaments and risk for psychopathology.

    Science.gov (United States)

    DeGeorge, Daniella P; Walsh, Molly A; Barrantes-Vidal, Neus; Kwapil, Thomas R

    2014-08-01

    Affective temperaments are presumed to underlie bipolar psychopathology. The TEMPS-A has been widely used to assess affective temperaments in clinical and non-clinical samples. Cross-sectional research supports the association of affective temperaments and mood psychopathology; however, longitudinal research examining risk for the development of bipolar disorders is lacking. The present study examined the predictive validity of affective temperaments, using the TEMPS-A, at a three-year follow-up assessment. The study interviewed 112 participants (77% of the original sample) at a three-year follow-up of 145 non-clinically ascertained young adults psychometrically at-risk for bipolar disorders, who previously took part in a cross-sectional examination of affective temperaments and mood psychopathology. At the reassessment, 29 participants (26%) met criteria for bipolar spectrum disorders, including 13 participants who transitioned into disorders during the follow-up period (14% of the originally undiagnosed sample). Cyclothymic/irritable and hyperthymic temperaments predicted both total cases and new cases of bipolar spectrum disorders at the follow-up. Cyclothymic/irritable temperament was associated with more severe outcomes, including DSM-IV-TR bipolar disorders, bipolar spectrum psychopathology, major depressive episodes, and substance use disorders. Hyperthymic temperament was associated with bipolar spectrum psychopathology and hypomania, whereas dysthymic temperament was generally unassociated with psychopathology and impairment. The present sample of young adults is still young relative to the age of onset of mood psychopathology. These results provide the first evidence of the predictive validity of affective temperaments regarding risk for the development of bipolar psychopathology. Affective temperaments provide a useful construct for understanding bipolar psychopathology. Copyright © 2014 Elsevier B.V. All rights reserved.

  13. Analysing Stable Time Series

    National Research Council Canada - National Science Library

    Adler, Robert

    1997-01-01

    We describe how to take a stable, ARMA, time series through the various stages of model identification, parameter estimation, and diagnostic checking, and accompany the discussion with a goodly number...

  14. Multivariate Time Series Search

    Data.gov (United States)

    National Aeronautics and Space Administration — Multivariate Time-Series (MTS) are ubiquitous, and are generated in areas as disparate as sensor recordings in aerospace systems, music and video streams, medical...

  15. Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality: a time-series study.

    Science.gov (United States)

    Fang, Xin; Li, Runkui; Kan, Haidong; Bottai, Matteo; Fang, Fang; Cao, Yang

    2016-08-16

    To demonstrate an application of Bayesian model averaging (BMA) with generalised additive mixed models (GAMM) and provide a novel modelling technique to assess the association between inhalable coarse particles (PM10) and respiratory mortality in time-series studies. A time-series study using regional death registry between 2009 and 2010. 8 districts in a large metropolitan area in Northern China. 9559 permanent residents of the 8 districts who died of respiratory diseases between 2009 and 2010. Per cent increase in daily respiratory mortality rate (MR) per interquartile range (IQR) increase of PM10 concentration and corresponding 95% confidence interval (CI) in single-pollutant and multipollutant (including NOx, CO) models. The Bayesian model averaged GAMM (GAMM+BMA) and the optimal GAMM of PM10, multipollutants and principal components (PCs) of multipollutants showed comparable results for the effect of PM10 on daily respiratory MR, that is, one IQR increase in PM10 concentration corresponded to 1.38% vs 1.39%, 1.81% vs 1.83% and 0.87% vs 0.88% increase, respectively, in daily respiratory MR. However, GAMM+BMA gave slightly but noticeable wider CIs for the single-pollutant model (-1.09 to 4.28 vs -1.08 to 3.93) and the PCs-based model (-2.23 to 4.07 vs -2.03 vs 3.88). The CIs of the multiple-pollutant model from two methods are similar, that is, -1.12 to 4.85 versus -1.11 versus 4.83. The BMA method may represent a useful tool for modelling uncertainty in time-series studies when evaluating the effect of air pollution on fatal health outcomes. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

  16. Occupation and three-year incidence of respiratory symptoms and lung function decline: the ARIC Study

    Directory of Open Access Journals (Sweden)

    Mirabelli Maria C

    2012-03-01

    Full Text Available Abstract Background Specific occupations are associated with adverse respiratory health. Inhalation exposures encountered in these jobs may place workers at risk of new-onset respiratory disease. Methods We analyzed data from 8,967 participants from the Atherosclerosis Risk in Communities (ARIC study, a longitudinal cohort study. Participants included in this analysis were free of chronic cough and phlegm, wheezing, asthma, chronic bronchitis, emphysema, and other chronic lung conditions at the baseline examination, when they were aged 45-64 years. Using data collected in the baseline and first follow-up examination, we evaluated associations between occupation and the three-year incidence of cough, phlegm, wheezing, and airway obstruction and changes in forced expiratory volume in one second (FEV1 and forced vital capacity (FVC measured by spirometry. All associations were adjusted for age, cigarettes per day, race, smoking status, and study center. Results During the approximately three-year follow-up, the percentage of participants developing chronic cough was 3%; chronic phlegm, 3%; wheezing, 3%; and airway obstruction, defined as FEV1 1/FVC 1 and FVC were 56 mL and 66 mL, respectively, among men and 40 mL and 52 mL, respectively, among women. Relative to a referent category of managerial and administrative support occupations, elevated risks of new-onset chronic cough and chronic phlegm were observed for mechanics and repairers (chronic cough: RR: 1.81, 95% CI: 1.02, 3.21; chronic phlegm: RR: 2.10, 95% CI: 1.23, 3.57 and cleaning and building service workers (chronic cough: RR: 1.85, 95% CI: 1.01, 3.37; chronic phlegm: RR: 2.28, 95% CI: 1.27, 4.08. Despite the elevated risk of new-onset symptoms, employment in cleaning and building services was associated with attenuated lung function decline, particularly among men, who averaged annual declines in FEV1 and FVC of 14 mL and 23 mL, respectively, less than the declines observed in the

  17. Effect of an evidence-based website on healthcare usage: an interrupted time-series study.

    NARCIS (Netherlands)

    Spoelman, W.A.; Bonten, T.N.; Waal, M.W.M. de; Drenthen, T.; Smeele, I.J.M.; Nielen, M.M.; Chavannes, N.

    2016-01-01

    Objectives: Healthcare costs and usage are rising. Evidence-based online health information may reduce healthcare usage, but the evidence is scarce. The objective of this study was to determine whether the release of a nationwide evidence-based health website was associated with a reduction in

  18. Statistics for Time-Series Spatial Data: Applying Survival Analysis to Study Land-Use Change

    Science.gov (United States)

    Wang, Ninghua Nathan

    2013-01-01

    Traditional spatial analysis and data mining methods fall short of extracting temporal information from data. This inability makes their use difficult to study changes and the associated mechanisms of many geographic phenomena of interest, for example, land-use. On the other hand, the growing availability of land-change data over multiple time…

  19. Time-series photometric spot modeling. I - Parameter study and application to HD 17433 = VY Arietis

    Science.gov (United States)

    Strassmeier, K. G.; Bopp, B. W.

    1992-01-01

    New UBVRI photometry of the active chromosphere binary HD 17433 (VY) Ari from 1987 through 1991 is presented, and the long-term and short-term spot behavior is studied. A 0.2 mag variation of the mean brightness and a maximum wave amplitude of up to 0.4 mag in 1988 are found. The newly measured photometric period of 16.42 d suggests asynchronous rotation of the primary component by about 30 percent.

  20. Meteorological factors, air pollutants, and emergency department visits for otitis media: a time series study

    Science.gov (United States)

    Gestro, Massimo; Condemi, Vincenzo; Bardi, Luisella; Fantino, Claudio; Solimene, Umberto

    2017-10-01

    Abstract Otitis media (OM) is a very common disease in children, which results in a significant economic burden to the healthcare system for hospital-based outpatient departments, emergency departments (EDs), unscheduled medical examinations, and antibiotic prescriptions. The aim of this retrospective observational study is to investigate the association between climate variables, air pollutants, and OM visits observed in the 2007-2010 period at the ED of Cuneo, Italy. Measures of meteorological parameters (temperature, humidity, atmospheric pressure, wind) and outdoor air pollutants (particulate matter, ozone, nitrous dioxide) were analyzed at two statistical stages and in several specific steps (crude and adjusted models) according to Poisson's regression. Response variables included daily examinations for age groups 0-3, 0-6, and 0-18. Control variables included upper respiratory infections (URI), flu (FLU), and several calendar factors. A statistical procedure was implemented to capture any delayed effects. Results show a moderate association for temperature ( T), age 0-3, and 0-6 with P < 0.05, as well as nitrous dioxide (NO2) with P < 0.005 at age 0-18. Results of subsequent models point out to URI as an important control variable. No statistical association was observed for other pollutants and meteorological variables. The dose-response models (DLNM—final stage) implemented separately on a daily and hourly basis point out to an association between temperature (daily model) and RR 1.44 at age 0-3, CI 1.11-1.88 (lag time 0-1 days) and RR 1.43, CI 1.05-1.94 (lag time 0-3 days). The hourly model confirms a specific dose-response effect for T with RR 1.20, CI 1.04-1.38 (lag time range from 0 to 11 to 0-15 h) and for NO2 with RR 1.03, CI 1.01-1.05 (lag time range from 0 to 8 to 0-15 h). These results support the hypothesis that the clinical context of URI may be an important risk factor in the onset of OM diagnosed at ED level. The study highlights the

  1. Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

    Science.gov (United States)

    Diao, Chunyuan

    In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of

  2. Impact of banking institutions on national economy an empirical study of time series analysis in Pakistan

    Directory of Open Access Journals (Sweden)

    Nouman Badar

    2015-09-01

    Full Text Available This paper examines the long and short term relationship of financial sector development on economic growth of Pakistan where development of financial sector is detected by the variables truly depicts the efficiency of financial sector i.e. Money Supply, size of Advances, Private sector Credit growth and Bank’s equity with economic growth which is pronounced by Gross Domestic Product in this study. Data of almost 22 years ranges from 1992 to 2013 of overall banking industry is taken to obtain results by employing Johnson and Jusellious co integration technique to detect long run association while Granger Casualty test is used to determine cause and effect relationship and to measure short term dynamics Vector Error correction model is used. The result shows that both long and short run relationship exists between growth of financial sector and economy of Pakistan

  3. A study of finite mixture model: Bayesian approach on financial time series data

    Science.gov (United States)

    Phoong, Seuk-Yen; Ismail, Mohd Tahir

    2014-07-01

    Recently, statistician have emphasized on the fitting finite mixture model by using Bayesian method. Finite mixture model is a mixture of distributions in modeling a statistical distribution meanwhile Bayesian method is a statistical method that use to fit the mixture model. Bayesian method is being used widely because it has asymptotic properties which provide remarkable result. In addition, Bayesian method also shows consistency characteristic which means the parameter estimates are close to the predictive distributions. In the present paper, the number of components for mixture model is studied by using Bayesian Information Criterion. Identify the number of component is important because it may lead to an invalid result. Later, the Bayesian method is utilized to fit the k-component mixture model in order to explore the relationship between rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia. Lastly, the results showed that there is a negative effect among rubber price and stock market price for all selected countries.

  4. A comparative study of time series modeling methods for reactor noise analysis

    International Nuclear Information System (INIS)

    Kitamura, Masaharu; Shigeno, Kei; Sugiyama, Kazusuke

    1978-01-01

    Two modeling algorithms were developed to study at-power reactor noise as a multi-input, multi-output process. A class of linear, discrete time description named autoregressive-moving average model was used as a compact mathematical expression of the objective process. One of the model estimation (modeling) algorithms is based on the theory of Kalman filtering, and the other on a conjugate gradient method. By introducing some modifications in the formulation of the problem, realization of the practically usable algorithms was made feasible. Through the testing with several simulation models, reliability and effectiveness of these algorithms were confirmed. By applying these algorithms to experimental data obtained from a nuclear power plant, interesting knowledge about the at-power reactor noise was found out. (author)

  5. Effect of ambient temperature on emergency department visits in Shanghai, China: a time series study.

    Science.gov (United States)

    Zhang, Yue; Yan, Chenyang; Kan, Haidong; Cao, Junshan; Peng, Li; Xu, Jianming; Wang, Weibing

    2014-11-25

    Many studies have examined the association between ambient temperature and mortality. However, less evidence is available on the temperature effects on gender- and age-specific emergency department visits, especially in developing countries. In this study, we examined the short-term effects of daily ambient temperature on emergency department visits (ED visits) in Shanghai. Daily ED visits and daily ambient temperatures between January 2006 and December 2011 were analyzed. After controlling for secular and seasonal trends, weather, air pollution and other confounding factors, a Poisson generalized additive model (GAM) was used to examine the associations between ambient temperature and gender- and age-specific ED visits. A moving average lag model was used to evaluate the lag effects of temperature on ED visits. Low temperature was associated with an overall 2.76% (95% confidence interval (CI): 1.73 to 3.80) increase in ED visits per 1°C decrease in temperature at Lag1 day, 2.03% (95% CI: 1.04 to 3.03) and 2.45% (95% CI: 1.40 to 3.52) for males and females. High temperature resulted in an overall 1.78% (95% CI: 1.05 to 2.51) increase in ED visits per 1°C increase in temperature on the same day, 1.81% (95% CI: 1.08 to 2.54) among males and 1.75% (95% CI: 1.03 to 2.49) among females. The cold effect appeared to be more acute among younger people aged effects were consistent on individuals aged ≥65 years. In contrast, the effects of high temperature were relatively consistent over all age groups. These findings suggest a significant association between ambient temperature and ED visits in Shanghai. Both cold and hot temperatures increased the relative risk of ED visits. This knowledge has the potential to advance prevention efforts targeting weather-sensitive conditions.

  6. Comparative study of four time series methods in forecasting typhoid fever incidence in China.

    Directory of Open Access Journals (Sweden)

    Xingyu Zhang

    Full Text Available Accurate incidence forecasting of infectious disease is critical for early prevention and for better government strategic planning. In this paper, we present a comprehensive study of different forecasting methods based on the monthly incidence of typhoid fever. The seasonal autoregressive integrated moving average (SARIMA model and three different models inspired by neural networks, namely, back propagation neural networks (BPNN, radial basis function neural networks (RBFNN, and Elman recurrent neural networks (ERNN were compared. The differences as well as the advantages and disadvantages, among the SARIMA model and the neural networks were summarized and discussed. The data obtained for 2005 to 2009 and for 2010 from the Chinese Center for Disease Control and Prevention were used as modeling and forecasting samples, respectively. The performances were evaluated based on three metrics: mean absolute error (MAE, mean absolute percentage error (MAPE, and mean square error (MSE. The results showed that RBFNN obtained the smallest MAE, MAPE and MSE in both the modeling and forecasting processes. The performances of the four models ranked in descending order were: RBFNN, ERNN, BPNN and the SARIMA model.

  7. A time series study of drug sales and turbidity of tap water in Le Havre, France.

    Science.gov (United States)

    Beaudeau, Pascal; Le Tertre, Alain; Zeghnoun, Abdelkrim; Zanobetti, Antonella; Schwartz, Joel

    2012-06-01

    The 80,000 inhabitants of the lower part of Le Havre obtain their water supply from two karstic springs, Radicatel and Saint-Laurent. Until 2000, the Radicatel water was settled when turbidity exceeded 3 NTU, then filtered and chlorinated, whereas the Saint-Laurent water was simply chlorinated. Our study aimed to characterize the link between water turbidity and the incidence of acute gastroenteritis (AGE). Records on drug sales used for the treatment of AGE were collected from January 1994 to June 1996 (period 1) and from March 1997 to July 2000 (period 2). Daily counts of drug sales were modeled using a Poisson Regression. We used data set 2 as a discovery set, identifying relevant (i.e. both significant and plausible) exposure covariates and lags. We then tested this model on period 1 as a replication dataset. In period 2, the daily drug sales correlated with finished water turbidity at both resources. Settling substantially modified the risk related to turbidity of both raw and finished waters at Radicatel. Correlations were reproducible in period 1 for water from the Radicatel spring. Timeliness of treatment adaptation to turbidity conditions appears to be crucial for reducing the infectious risk due to karstic waters.

  8. Comparative study of four time series methods in forecasting typhoid fever incidence in China.

    Science.gov (United States)

    Zhang, Xingyu; Liu, Yuanyuan; Yang, Min; Zhang, Tao; Young, Alistair A; Li, Xiaosong

    2013-01-01

    Accurate incidence forecasting of infectious disease is critical for early prevention and for better government strategic planning. In this paper, we present a comprehensive study of different forecasting methods based on the monthly incidence of typhoid fever. The seasonal autoregressive integrated moving average (SARIMA) model and three different models inspired by neural networks, namely, back propagation neural networks (BPNN), radial basis function neural networks (RBFNN), and Elman recurrent neural networks (ERNN) were compared. The differences as well as the advantages and disadvantages, among the SARIMA model and the neural networks were summarized and discussed. The data obtained for 2005 to 2009 and for 2010 from the Chinese Center for Disease Control and Prevention were used as modeling and forecasting samples, respectively. The performances were evaluated based on three metrics: mean absolute error (MAE), mean absolute percentage error (MAPE), and mean square error (MSE). The results showed that RBFNN obtained the smallest MAE, MAPE and MSE in both the modeling and forecasting processes. The performances of the four models ranked in descending order were: RBFNN, ERNN, BPNN and the SARIMA model.

  9. The impact of heatwaves on emergency department visits in Brisbane, Australia: a time series study.

    Science.gov (United States)

    Toloo, Ghasem Sam; Yu, Weiwei; Aitken, Peter; FitzGerald, Gerry; Tong, Shilu

    2014-04-09

    The acute health effects of heatwaves in a subtropical climate and their impact on emergency departments (ED) are not well known. The purpose of this study is to examine overt heat-related presentations to EDs associated with heatwaves in Brisbane. Data were obtained for the summer seasons (December to February) from 2000-2012. Heatwave events were defined as two or more successive days with daily maximum temperature ≥34°C (HWD1) or ≥37°C (HWD2). Poisson generalised additive model was used to assess the effect of heatwaves on heat-related visits (International Classification of Diseases (ICD) 10 codes T67 and X30; ICD 9 codes 992 and E900.0). Overall, 628 cases presented for heat-related illnesses. The presentations significantly increased on heatwave days based on HWD1 (relative risk (RR) = 4.9, 95% confidence interval (CI): 3.8, 6.3) and HWD2 (RR = 18.5, 95% CI: 12.0, 28.4). The RRs in different age groups ranged between 3-9.2 (HWD1) and 7.5-37.5 (HWD2). High acuity visits significantly increased based on HWD1 (RR = 4.7, 95% CI: 2.3, 9.6) and HWD2 (RR = 81.7, 95% CI: 21.5, 310.0). Average length of stay in ED significantly increased by >1 hour (HWD1) and >2 hours (HWD2). Heatwaves significantly increase ED visits and workload even in a subtropical climate. The degree of impact is directly related to the extent of temperature increases and varies by socio-demographic characteristics of the patients. Heatwave action plans should be tailored according to the population needs and level of vulnerability. EDs should have plans to increase their surge capacity during heatwaves.

  10. Developing a dengue early warning system using time series model: Case study in Tainan, Taiwan

    Science.gov (United States)

    Chen, Xiao-Wei; Jan, Chyan-Deng; Wang, Ji-Shang

    2017-04-01

    Dengue fever (DF) is a climate-sensitive disease that has been emerging in southern regions of Taiwan over the past few decades, causing a significant health burden to affected areas. This study aims to propose a predictive model to implement an early warning system so as to enhance dengue surveillance and control in Tainan, Taiwan. The Seasonal Autoregressive Integrated Moving Average (SARIMA) model was used herein to forecast dengue cases. Temporal correlation between dengue incidences and climate variables were examined by Pearson correlation analysis and Cross-correlation tests in order to identify key determinants to be included as predictors. The dengue surveillance data between 2000 and 2009, as well as their respective climate variables were then used as inputs for the model. We validated the model by forecasting the number of dengue cases expected to occur each week between January 1, 2010 and December 31, 2015. In addition, we analyzed historical dengue trends and found that 25 cases occurring in one week was a trigger point that often led to a dengue outbreak. This threshold point was combined with the season-based framework put forth by the World Health Organization to create a more accurate epidemic threshold for a Tainan-specific warning system. A Seasonal ARIMA model with the general form: (1,0,5)(1,1,1)52 is identified as the most appropriate model based on lowest AIC, and was proven significant in the prediction of observed dengue cases. Based on the correlation coefficient, Lag-11 maximum 1-hr rainfall (r=0.319, Pclimate variables. Comparing the four multivariate models(i.e.1, 4, 9 and 13 weeks ahead), we found that including the climate variables improves the prediction RMSE as high as 3.24%, 10.39%, 17.96%, 21.81% respectively, in contrast to univariate models. Furthermore, the ability of the four multivariate models to determine whether the epidemic threshold would be exceeded in any given week during the forecasting period of 2010-2015 was

  11. Application of radon time series data for seismo - geochemical studies along different fault zones of Taiwan

    International Nuclear Information System (INIS)

    Walia, Vivek; Arvind Kumar; Lin, Shih-Jung; Liao, Yu-Tzu; Wen, Kuo-Liang; Yang, Tsanyao Frank; Fu, Ching-Chou; Chen, Cheng-Hong

    2015-01-01

    The Island of Taiwan is a product of the collision between Philippine Sea plate and Eurasian plate which makes it a region of high seismicity. In the southern part of the island the Eurasian plate is subducting under the Philippine Sea plate while in the northern area of the island the Philippine Sea plate bounded by the Ryukyu trench is subducting beneath the Eurasian plate. Behind the Ryukyu trench, the spreading Okinawa trough has developed. The northern part of Taiwan Island is located at the western extrapolation of the Okinawa trough. Over the last few years, we focused on the temporal variations of soil-gas composition at established geochemical observatories along the Hsincheng fault in the Hsinchu area, Hsinhua fault in the Tainan areas, and at Jaosi in the Ilan areas of Taiwan. As per the present practice, the data from various stations are examined synoptically to evaluate earthquake precursory signals against the backdrop of rainfall and other environmental factors. For the earthquake prediction the efficiency of an operation system depends not only upon its logical correctness, but also upon the response time. The database has been developed by the established network of continuous soil-gas monitoring stations along different faults covering NW, SW and eastern Taiwan. The data processing includes a low-pass filter to reduce the noise level. It filters out the high frequency noise and daily variation caused by different parameters like measurement uncertainty, background noise, environmental parameters and earth tides. The rolling average and normalization were used to quantify the probability distribution of variation in the data. In recent years manually operating real-time database had been developed and efforts were made to improve data processing system for earthquake precursory studies by changing the operating system from manual to automatic. We tried to replace the business package software 'Visual Signal' to an open source programming

  12. Acute and Subacute Effects of Urban Air Pollution on Cardiopulmonary Emergencies and Mortality: Time Series Studies in Austrian Cities

    Directory of Open Access Journals (Sweden)

    Daniel Rabczenko

    2013-10-01

    Full Text Available Daily pollution data (collected in Graz over 16 years and in the Linz over 18 years were used for time series studies (GAM and case-crossover on the relationship with daily mortality (overall and specific causes of death. Diagnoses of patients who had been transported to hospitals in Linz were also available on a daily basis from eight years for time series analyses of cardiopulmonary emergencies. Increases in air pollutant levels over several days were followed by increases in mortality and the observed effects increased with the length of the exposure window considered, up to a maximum of 15 days. These mortality changes in Graz and Linz showed similar patterns like the ones found before in Vienna. A significant association of mortality could be demonstrated with NO2, PM2.5 and PM10 even in summer, when concentrations are lower and mainly related to motor traffic. Cardiorespiratory ambulance transports increased with NO2/PM2.5/PM10 by 2.0/6.1/1.7% per 10 µg/m³ on the same day. Monitoring of NO2 (related to motor traffic and fine particulates at urban background stations predicts acute effects on cardiopulmonary emergencies and extended effects on cardiopulmonary mortality. Both components of urban air pollution are indicators of acute cardiopulmonary health risks, which need to be monitored and reduced, even below current standards.

  13. Visual time series analysis

    DEFF Research Database (Denmark)

    Fischer, Paul; Hilbert, Astrid

    2012-01-01

    We introduce a platform which supplies an easy-to-handle, interactive, extendable, and fast analysis tool for time series analysis. In contrast to other software suits like Maple, Matlab, or R, which use a command-line-like interface and where the user has to memorize/look-up the appropriate...... commands, our application is select-and-click-driven. It allows to derive many different sequences of deviations for a given time series and to visualize them in different ways in order to judge their expressive power and to reuse the procedure found. For many transformations or model-ts, the user may...... choose between manual and automated parameter selection. The user can dene new transformations and add them to the system. The application contains efficient implementations of advanced and recent techniques for time series analysis including techniques related to extreme value analysis and filtering...

  14. Modelling bursty time series

    International Nuclear Information System (INIS)

    Vajna, Szabolcs; Kertész, János; Tóth, Bálint

    2013-01-01

    Many human-related activities show power-law decaying interevent time distribution with exponents usually varying between 1 and 2. We study a simple task-queuing model, which produces bursty time series due to the non-trivial dynamics of the task list. The model is characterized by a priority distribution as an input parameter, which describes the choice procedure from the list. We give exact results on the asymptotic behaviour of the model and we show that the interevent time distribution is power-law decaying for any kind of input distributions that remain normalizable in the infinite list limit, with exponents tunable between 1 and 2. The model satisfies a scaling law between the exponents of interevent time distribution (β) and autocorrelation function (α): α + β = 2. This law is general for renewal processes with power-law decaying interevent time distribution. We conclude that slowly decaying autocorrelation function indicates long-range dependence only if the scaling law is violated. (paper)

  15. Time Series Momentum

    DEFF Research Database (Denmark)

    Moskowitz, Tobias J.; Ooi, Yao Hua; Heje Pedersen, Lasse

    2012-01-01

    We document significant “time series momentum” in equity index, currency, commodity, and bond futures for each of the 58 liquid instruments we consider. We find persistence in returns for one to 12 months that partially reverses over longer horizons, consistent with sentiment theories of initial...... under-reaction and delayed over-reaction. A diversified portfolio of time series momentum strategies across all asset classes delivers substantial abnormal returns with little exposure to standard asset pricing factors and performs best during extreme markets. Examining the trading activities...

  16. Applied time series analysis

    CERN Document Server

    Woodward, Wayne A; Elliott, Alan C

    2011-01-01

    ""There is scarcely a standard technique that the reader will find left out … this book is highly recommended for those requiring a ready introduction to applicable methods in time series and serves as a useful resource for pedagogical purposes.""-International Statistical Review (2014), 82""Current time series theory for practice is well summarized in this book.""-Emmanuel Parzen, Texas A&M University""What an extraordinary range of topics covered, all very insightfully. I like [the authors'] innovations very much, such as the AR factor table.""-David Findley, U.S. Census Bureau (retired)""…

  17. Predicting chaotic time series

    International Nuclear Information System (INIS)

    Farmer, J.D.; Sidorowich, J.J.

    1987-01-01

    We present a forecasting technique for chaotic data. After embedding a time series in a state space using delay coordinates, we ''learn'' the induced nonlinear mapping using local approximation. This allows us to make short-term predictions of the future behavior of a time series, using information based only on past values. We present an error estimate for this technique, and demonstrate its effectiveness by applying it to several examples, including data from the Mackey-Glass delay differential equation, Rayleigh-Benard convection, and Taylor-Couette flow

  18. A Three-Year Field Validation Study to Improve the Integrated Pest Management of Hot Pepper

    Directory of Open Access Journals (Sweden)

    Ji-Hoon Kim

    2013-09-01

    Full Text Available To improve the integrated pest management (IPM of hot pepper, field study was conducted in Hwasung from 2010 to 2012 and an IPM system was developed to help growers decide when to apply pesticides to control anthracnose, tobacco budworm, Phytophthora blight, bacterial wilt, and bacterial leaf spot. The three field treatments consisted of IPM sprays following the forecast model advisory, a periodic spray at 7-to-10-day intervals, and no spray (control. The number of annual pesticide applications for the IPM treatment ranged from six to eight, whereas the plots subjected to the periodic treatment received pesticide 11 or 12 times annually for three years. Compared to the former strategy, our improved IPM strategy features more intense pest management, with frequent spraying for anthracnose and mixed spraying for tobacco budworm or Phytophthora blight. The incidences for no pesticide control in 2010, 2011, and 2012 were 91, 97.6, and 41.4%, respectively. Conversely, the incidences for the IPM treatment for those years were 7.6, 62.6, and 2%, and the yields from IPM-treated plots were 48.6 kg, 12.1 kg, and 48.8 kg. The incidence and yield in the IPM-treated plots were almost the same as those of the periodic treatment except in 2011, in which no unnecessary sprays were given, meaning that the IPM control was quite successful. From reviewing eight years of field work, sophisticated forecasts that optimize pesticide spray timing reveal that reliance on pesticides can be reduced without compromising yield. Eco-friendly strategies can be implemented in the pest management of hot pepper.

  19. Atmospheric Pressure and Abdominal Aortic Aneurysm Rupture: Results From a Time Series Analysis and Case-Crossover Study.

    Science.gov (United States)

    Penning de Vries, Bas B L; Kolkert, Joé L P; Meerwaldt, Robbert; Groenwold, Rolf H H

    2017-10-01

    Associations between atmospheric pressure and abdominal aortic aneurysm (AAA) rupture risk have been reported, but empirical evidence is inconclusive and largely derived from studies that did not account for possible nonlinearity, seasonality, and confounding by temperature. Associations between atmospheric pressure and AAA rupture risk were investigated using local meteorological data and a case series of 358 patients admitted to hospital for ruptured AAA during the study period, January 2002 to December 2012. Two analyses were performed-a time series analysis and a case-crossover study. Results from the 2 analyses were similar; neither the time series analysis nor the case-crossover study showed a significant association between atmospheric pressure ( P = .627 and P = .625, respectively, for mean daily atmospheric pressure) or atmospheric pressure variation ( P = .464 and P = .816, respectively, for 24-hour change in mean daily atmospheric pressure) and AAA rupture risk. This study failed to support claims that atmospheric pressure causally affects AAA rupture risk. In interpreting our results, one should be aware that the range of atmospheric pressure observed in this study is not representative of the atmospheric pressure to which patients with AAA may be exposed, for example, during air travel or travel to high altitudes in the mountains. Making firm claims regarding these conditions in relation to AAA rupture risk is difficult at best. Furthermore, despite the fact that we used one of the largest case series to date to investigate the effect of atmospheric pressure on AAA rupture risk, it is possible that this study is simply too small to demonstrate a causal link.

  20. Analysis of forecasting malaria case with climatic factors as predictor in Mandailing Natal Regency: a time series study

    Science.gov (United States)

    Aulia, D.; Ayu, S. F.; Matondang, A.

    2018-01-01

    Malaria is the most contagious global concern. As a public health problem with outbreaks, affect the quality of life and economy, also could lead to death. Therefore, this research is to forecast malaria cases with climatic factors as predictors in Mandailing Natal Regency. The total number of positive malaria cases on January 2008 to December 2016 were taken from health department of Mandailing Natal Regency. Climates data such as rainfall, humidity, and temperature were taken from Center of Statistic Department of Mandailing Natal Regency. E-views ver. 9 is used to analyze this study. Autoregressive integrated average, ARIMA (0,1,1) (1,0,0)12 is the best model to explain the 67,2% variability data in time series study. Rainfall (P value = 0.0005), temperature (P value = 0,0029) and humidity (P value = 0.0001) are significant predictors for malaria transmission. Seasonal adjusted factor (SAF) in November and March shows peak for malaria cases.

  1. Impact of exposure measurement error in air pollution epidemiology: effect of error type in time-series studies.

    Science.gov (United States)

    Goldman, Gretchen T; Mulholland, James A; Russell, Armistead G; Strickland, Matthew J; Klein, Mitchel; Waller, Lance A; Tolbert, Paige E

    2011-06-22

    Two distinctly different types of measurement error are Berkson and classical. Impacts of measurement error in epidemiologic studies of ambient air pollution are expected to depend on error type. We characterize measurement error due to instrument imprecision and spatial variability as multiplicative (i.e. additive on the log scale) and model it over a range of error types to assess impacts on risk ratio estimates both on a per measurement unit basis and on a per interquartile range (IQR) basis in a time-series study in Atlanta. Daily measures of twelve ambient air pollutants were analyzed: NO2, NOx, O3, SO2, CO, PM10 mass, PM2.5 mass, and PM2.5 components sulfate, nitrate, ammonium, elemental carbon and organic carbon. Semivariogram analysis was applied to assess spatial variability. Error due to this spatial variability was added to a reference pollutant time-series on the log scale using Monte Carlo simulations. Each of these time-series was exponentiated and introduced to a Poisson generalized linear model of cardiovascular disease emergency department visits. Measurement error resulted in reduced statistical significance for the risk ratio estimates for all amounts (corresponding to different pollutants) and types of error. When modelled as classical-type error, risk ratios were attenuated, particularly for primary air pollutants, with average attenuation in risk ratios on a per unit of measurement basis ranging from 18% to 92% and on an IQR basis ranging from 18% to 86%. When modelled as Berkson-type error, risk ratios per unit of measurement were biased away from the null hypothesis by 2% to 31%, whereas risk ratios per IQR were attenuated (i.e. biased toward the null) by 5% to 34%. For CO modelled error amount, a range of error types were simulated and effects on risk ratio bias and significance were observed. For multiplicative error, both the amount and type of measurement error impact health effect estimates in air pollution epidemiology. By modelling

  2. Early diagenesis of recently deposited organic matter: A 9-yr time-series study of a flood deposit

    Science.gov (United States)

    Tesi, T.; Langone, L.; Goñi, M. A.; Wheatcroft, R. A.; Miserocchi, S.; Bertotti, L.

    2012-04-01

    In Fall 2000, the Po River (Italy) experienced a 100-yr return period flood that resulted in a 1-25 cm-thick deposit in the adjacent prodelta (10-25 m water depth). In the following years, numerous post-depositional perturbations occurred including bioturbation, reworking by waves with heights exceeding 5 m, as well as periods of extremely high and low sediment supply. Cores collected in the central prodelta after the Fall 2000 flood and over the following 9 yr, allowed characterization of the event-strata in their initial state and documentation of their subsequent evolution. Sedimentological characteristics were investigated using X-radiographs and sediment texture analyses, whereas the composition of sedimentary organic matter (OM) was studied via bulk and biomarker analyses, including organic carbon (OC), total nitrogen (TN), carbon stable isotope composition (δ13C), lignin phenols, cutin-products, p-hydroxy benzenes, benzoic acids, dicarboxylic acids, and fatty acids. The 9-yr time-series analysis indicated that roughly the lower half of the original event bed was preserved in the sediment record. Conversely, the upper half of the deposit experienced significant alterations including bioturbation, addition of new material, as well as coarsening. Comparison of the recently deposited material with 9-yr old preserved strata represented a unique natural laboratory to investigate the diagenesis of sedimentary OM in a non-steady system. Bulk data indicated that OC and TN were degraded at similar rates (loss ∼17%) whereas biomarkers exhibited a broad spectrum of reactivities (loss from ∼6% to ∼60%) indicating selective preservation during early diagenesis. Given the relevance of episodic sedimentation in several margins, this study has demonstrated the utility of event-response and time-series sampling of the seabed for understanding the early diagenesis in non-steady conditions.

  3. Road Traffic Injury Trends in the City of Valledupar, Colombia. A Time Series Study from 2008 to 2012.

    Directory of Open Access Journals (Sweden)

    Jorge Martín Rodríguez

    Full Text Available To analyze the behavior temporal of road-traffic injuries (RTI in Valledupar, Colombia from January 2008 to December 2012.An observational study was conducted based on records from the Colombian National Legal Medicine and Forensic Sciences Institute regional office in Valledupar. Different variables were analyzed, such as the injured person's sex, age, education level, and type of road user; the timeframe, place and circumstances of crashes and the vehicles associated with the occurrence. Furthermore, a time series analysis was conducted using an auto-regressive integrated moving average.There were 105 events per month on an average, 64.9% of RTI involved men; 82.3% of the persons injured were from 18 to 59 years of age; the average age was 35.4 years of age; the road users most involved in RTI were motorcyclists (69%, followed by pedestrians (12%. 70% had up to upper-secondary education. Sunday was the day with the most RTI occurrences; 93% of the RTI occurred in the urban area. The time series showed a seasonal pattern and a significant trend effect. The modeling process verified the existence of both memory and extrinsic variables related.An RTI occurrence pattern was identified, which showed an upward trend during the period analyzed. Motorcyclists were the main road users involved in RTI, which suggests the need to design and implement specific measures for that type of road user, from regulations for graduated licensing for young drivers to monitoring road user behavior for the promotion of road safety.

  4. Evaluating the Impact of Criminalizing Drunk Driving on Road-Traffic Injuries in Guangzhou, China: A Time-Series Study

    Directory of Open Access Journals (Sweden)

    Ang Zhao

    2016-08-01

    Full Text Available Background: Road-traffic injury (RTI is a major public-health concern worldwide. However, the effectiveness of laws criminalizing drunk driving on the improvement of road safety in China is not known. Methods: We collected daily aggregate data on RTIs from the Guangzhou First-Aid Service Command Center from 2009 to 2012. We performed an interrupted time-series analysis to evaluate the change in daily RTIs before (January 1, 2009, to April 30, 2011 and after (May 1, 2011, to December 31, 2012 the criminalization of drunk driving. We evaluated the impact of the intervention on RTIs using the overdispersed generalized additive model after adjusting for temporal trends, seasonality, day of the week, and holidays. Daytime/Nighttime RTIs, alcoholism, and non-traffic injuries were analyzed as comparison groups using the same model. Results: From January 1, 2009, to December 31, 2012, we identified a total of 54 887 RTIs. The standardized daily number of RTIs was almost stable in the pre-intervention period but decreased gradually in the post-intervention period. After the intervention, the standardized daily RTIs decreased 9.6% (95% confidence interval [CI], 6.5%–12.8%. There were similar decreases for the daily daytime and nighttime RTIs. In contrast, the standardized daily cases of alcoholism increased 38.8% (95% CI, 35.1%–42.4%, and daily non-traffic injuries increased 3.6% (95% CI, 1.4%–5.8%. Conclusions: This time-series study provides scientific evidence suggesting that the criminalization of drunk driving from May 1, 2011, may have led to moderate reductions in RTIs in Guangzhou, China.

  5. Evaluating the Impact of Criminalizing Drunk Driving on Road-Traffic Injuries in Guangzhou, China: A Time-Series Study.

    Science.gov (United States)

    Zhao, Ang; Chen, Renjie; Qi, Yongqing; Chen, Ailan; Chen, Xinyu; Liang, Zijing; Ye, Jianjun; Liang, Qing; Guo, Duanqiang; Li, Wanglin; Li, Shuangming; Kan, Haidong

    2016-08-05

    Road-traffic injury (RTI) is a major public-health concern worldwide. However, the effectiveness of laws criminalizing drunk driving on the improvement of road safety in China is not known. We collected daily aggregate data on RTIs from the Guangzhou First-Aid Service Command Center from 2009 to 2012. We performed an interrupted time-series analysis to evaluate the change in daily RTIs before (January 1, 2009, to April 30, 2011) and after (May 1, 2011, to December 31, 2012) the criminalization of drunk driving. We evaluated the impact of the intervention on RTIs using the overdispersed generalized additive model after adjusting for temporal trends, seasonality, day of the week, and holidays. Daytime/Nighttime RTIs, alcoholism, and non-traffic injuries were analyzed as comparison groups using the same model. From January 1, 2009, to December 31, 2012, we identified a total of 54 887 RTIs. The standardized daily number of RTIs was almost stable in the pre-intervention period but decreased gradually in the post-intervention period. After the intervention, the standardized daily RTIs decreased 9.6% (95% confidence interval [CI], 6.5%-12.8%). There were similar decreases for the daily daytime and nighttime RTIs. In contrast, the standardized daily cases of alcoholism increased 38.8% (95% CI, 35.1%-42.4%), and daily non-traffic injuries increased 3.6% (95% CI, 1.4%-5.8%). This time-series study provides scientific evidence suggesting that the criminalization of drunk driving from May 1, 2011, may have led to moderate reductions in RTIs in Guangzhou, China.

  6. Real life study of three years omalizumab in patients with difficult-to-control asthma.

    Science.gov (United States)

    López Tiro, J Jesús; Contreras, E Angélica Contreras; del Pozo, M Elena Ramírez; Gómez Vera, J; Larenas Linnemann, D

    2015-01-01

    Even though there are multiple options for the treatment of asthma, there still exists a fair group of patients with difficult-to-control asthma. We describe for the first time the real-world effects of three-year omalizumab treatment on patients with difficult-to-control asthma, seen in a social security hospital in a Latin American country. Difficult-to-control asthmatic patients from the out-patient clinic of a regional hospital were recruited to receive a three-year omalizumab course. Efficacy parameters were asthma control test (ACT) score; FEV1; daily beclomethasone maintenance dose; and unplanned visits for asthma exacerbations (emergency room (ER), hospitalisations, intensive care). 52 patients were recruited, 47 completed the three-year treatment (42 female, 15-67 years, mean age 43.5). Comparing efficacy parameters of the year before omalizumab with the 3rd year of omalizumab: mean ACT improved from 12.4 to 20.5, mean FEV1 from 66.3% (standard deviation (SD) 19.1%) to 88.4% (SD 16.2%) of predicted, while mean beclomethasone dose reduced from 1750 to 766 mcg/day and there was a significant reduction in patients experiencing ER visits (from 95% to 19%, pomalizumab, two because of an adverse event (anaphylaxis, severe headache, both resolved without sequelae). Omalizumab improved most clinical parameters of Mexican patients with difficult-to-control asthma. Especially the rates of ER visits and hospitalisation were significantly reduced, thus reducing costs. Omalizumab was generally well tolerated. Copyright © 2013 SEICAP. Published by Elsevier Espana. All rights reserved.

  7. A Case Study in Exploring Time Series: Inflation and the Growth of the Money Supply in Zaire, 1965-1982

    NARCIS (Netherlands)

    N. Mamingi (Nlandu); M.E. Wuyts (Marc)

    1986-01-01

    textabstractTo the economist, time series constitute key data sources for empirical analysis. This is especially true for macroeconomic analysis, which relies virtually exclusively on observations of macroeconomic aggregates as they evolve over time.

  8. Parameter estimation methods for gene circuit modeling from time-series mRNA data: a comparative study

    KAUST Repository

    Fan, M.; Kuwahara, Hiroyuki; Wang, X.; Wang, S.; Gao, Xin

    2015-01-01

    Parameter estimation is a challenging computational problemin the reverse engineering of biological systems. Because advances in biotechnology have facilitated wide availability of time-series gene expression data, systematic parameter esti- mation

  9. A Three-Year Feedback Study of a Remote Laboratory Used in Control Engineering Studies

    Science.gov (United States)

    Chevalier, Amélie; Copot, Cosmin; Ionescu, Clara; De Keyser, Robin

    2017-01-01

    This paper discusses the results of a feedback study for a remote laboratory used in the education of control engineering students. The goal is to show the effectiveness of the remote laboratory on examination results. To provide an overview, the two applications of the remote laboratory are addressed: 1) the Stewart platform, and 2) the quadruple…

  10. Impact of STROBE statement publication on quality of observational study reporting: interrupted time series versus before-after analysis.

    Directory of Open Access Journals (Sweden)

    Sylvie Bastuji-Garin

    Full Text Available In uncontrolled before-after studies, CONSORT was shown to improve the reporting of randomised trials. Before-after studies ignore underlying secular trends and may overestimate the impact of interventions. Our aim was to assess the impact of the 2007 STROBE statement publication on the quality of observational study reporting, using both uncontrolled before-after analyses and interrupted time series.For this quasi-experimental study, original articles reporting cohort, case-control, and cross-sectional studies published between 2004 and 2010 in the four dermatological journals having the highest 5-year impact factors (≥ 4 were selected. We compared the proportions of STROBE items (STROBE score adequately reported in each article during three periods, two pre STROBE period (2004-2005 and 2006-2007 and one post STROBE period (2008-2010. Segmented regression analysis of interrupted time series was also performed.Of the 456 included articles, 187 (41% reported cohort studies, 166 (36.4% cross-sectional studies, and 103 (22.6% case-control studies. The median STROBE score was 57% (range, 18%-98%. Before-after analysis evidenced significant STROBE score increases between the two pre-STROBE periods and between the earliest pre-STROBE period and the post-STROBE period (median score2004-05 48% versus median score2008-10 58%, p<0.001 but not between the immediate pre-STROBE period and the post-STROBE period (median score2006-07 58% versus median score2008-10 58%, p = 0.42. In the pre STROBE period, the six-monthly mean STROBE score increased significantly, by 1.19% per six-month period (absolute increase 95%CI, 0.26% to 2.11%, p = 0.016. By segmented analysis, no significant changes in STROBE score trends occurred (-0.40%; 95%CI, -2.20 to 1.41; p = 0.64 in the post STROBE statement publication.The quality of reports increased over time but was not affected by STROBE. Our findings raise concerns about the relevance of uncontrolled before

  11. Study of the dependence of resolution temporal activity for a Philips gemini TF PET/CT scanner by applying a statistical analysis of time series

    International Nuclear Information System (INIS)

    Sanchez Merino, G.; Cortes Rpdicio, J.; Lope Lope, R.; Martin Gonzalez, T.; Garcia Fidalgo, M. A.

    2013-01-01

    The aim of the present work is to study the dependence of temporal resolution with the activity using statistical techniques applied to the series of values time series measurements of temporal resolution during daily equipment checks. (Author)

  12. Forecasting Cryptocurrencies Financial Time Series

    DEFF Research Database (Denmark)

    Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco

    2018-01-01

    This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely...

  13. The effects of pay for performance on disparities in stroke, hypertension, and coronary heart disease management: interrupted time series study.

    Science.gov (United States)

    Lee, John Tayu; Netuveli, Gopalakrishnan; Majeed, Azeem; Millett, Christopher

    2011-01-01

    The Quality and Outcomes Framework (QOF), a major pay-for-performance programme, was introduced into United Kingdom primary care in April 2004. The impact of this programme on disparities in health care remains unclear. This study examines the following questions: has this pay for performance programme improved the quality of care for coronary heart disease, stroke and hypertension in white, black and south Asian patients? Has this programme reduced disparities in the quality of care between these ethnic groups? Did general practices with different baseline performance respond differently to this programme? Retrospective cohort study of patients registered with family practices in Wandsworth, London during 2007. Segmented regression analysis of interrupted time series was used to take into account the previous time trend. Primary outcome measures were mean systolic and diastolic blood pressure, and cholesterol levels. Our findings suggest that the implementation of QOF resulted in significant short term improvements in blood pressure control. The magnitude of benefit varied between ethnic groups with a statistically significant short term reduction in systolic BP in white and black but not in south Asian patients with hypertension. Disparities in risk factor control were attenuated only on few measures and largely remained intact at the end of the study period. Pay for performance programmes such as the QOF in the UK should set challenging but achievable targets. Specific targets aimed at reducing ethnic disparities in health care may also be needed.

  14. A Review of Subsequence Time Series Clustering

    Directory of Open Access Journals (Sweden)

    Seyedjamal Zolhavarieh

    2014-01-01

    Full Text Available Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

  15. A review of subsequence time series clustering.

    Science.gov (United States)

    Zolhavarieh, Seyedjamal; Aghabozorgi, Saeed; Teh, Ying Wah

    2014-01-01

    Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

  16. A Review of Subsequence Time Series Clustering

    Science.gov (United States)

    Teh, Ying Wah

    2014-01-01

    Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies. PMID:25140332

  17. Three-year Treatment Outcomes in the Ahmed Baerveldt Comparison Study

    Science.gov (United States)

    Barton, Keith; Feuer, William J; Budenz, Donald L; Schiffman, Joyce; Costa, Vital P.; Godfrey, David G.; Buys, Yvonne M.

    2014-01-01

    Purpose To compare three year outcomes and complications of the Ahmed FP7 Glaucoma Valve (AGV) and Baerveldt 101–350 Glaucoma Implant (BGI) for the treatment of refractory glaucoma. Design Multicenter randomized controlled clinical trial. Participants 276 patients; 143 in the AGV group and 133 in the BGI group. Methods Patients aged 18–85 years with refractory glaucoma and intraocular pressures (IOPs) ≥18 mmHg in whom an aqueous shunt was planned were randomized to either an AGV or a BGI. Main Outcome Measures IOP, visual acuity, supplemental medical therapy, complications, and failure (IOP > 21 mmHg or not reduced by 20% from baseline, IOP ≤ 5 mmHg, reoperation for glaucoma or removal of implant, or loss of light perception vision). Results At 3 years, IOP (mean ± standard deviation) (SD) was 14.3 ± 4.7 mmHg (AGV group) and 13.1 ± 4.5 mmHg (BGI group) (p = 0.086) on 2.0 ± 1.4 and 1.5 ± 1.4 glaucoma medications respectively (p = 0.020). The cumulative probabilities of failure were 31.3% (standard error = 4.0%) (SE) (AGV) and 32.3% (4.2%) (BGI) (p = 0.99). Postoperative complications associated with reoperation or vision loss of ≥ 2 Snellen lines occurred in 24 patients (22%) (AGV) and 38 patients (36%) (BGI) (p = 0.035). The mean change in the Logarithm of the Minimum Angle of Resolution visual acuity (logMAR VA) at 3 years was similar (AGV: 0.21 ± 0.88, BGI: 0.26 ± 0.74) in the two treatment groups at 3 years (p=0.66). The cumulative proportion of patients (SE) undergoing reoperation for glaucoma prior to the three year postoperative time point was 14.5% (3.0%) in the AGV group compared to 7.6% (2.4%) in the BGI group (p=0.053, log-rank). The relative risk of reoperation for glaucoma in the AGV group was 2.1 times that of the BGI group (95% Confidence Interval:1.0–4.8, p=0.045; Cox proportional hazards regression). Conclusions AGV implantation was associated with the need for significantly greater adjunctive medication to achieve equal success

  18. Duality between Time Series and Networks

    Science.gov (United States)

    Campanharo, Andriana S. L. O.; Sirer, M. Irmak; Malmgren, R. Dean; Ramos, Fernando M.; Amaral, Luís A. Nunes.

    2011-01-01

    Studying the interaction between a system's components and the temporal evolution of the system are two common ways to uncover and characterize its internal workings. Recently, several maps from a time series to a network have been proposed with the intent of using network metrics to characterize time series. Although these maps demonstrate that different time series result in networks with distinct topological properties, it remains unclear how these topological properties relate to the original time series. Here, we propose a map from a time series to a network with an approximate inverse operation, making it possible to use network statistics to characterize time series and time series statistics to characterize networks. As a proof of concept, we generate an ensemble of time series ranging from periodic to random and confirm that application of the proposed map retains much of the information encoded in the original time series (or networks) after application of the map (or its inverse). Our results suggest that network analysis can be used to distinguish different dynamic regimes in time series and, perhaps more importantly, time series analysis can provide a powerful set of tools that augment the traditional network analysis toolkit to quantify networks in new and useful ways. PMID:21858093

  19. Application of Time-series Model to Predict Groundwater Quality Parameters for Agriculture: (Plain Mehran Case Study)

    Science.gov (United States)

    Mehrdad Mirsanjari, Mir; Mohammadyari, Fatemeh

    2018-03-01

    Underground water is regarded as considerable water source which is mainly available in arid and semi arid with deficient surface water source. Forecasting of hydrological variables are suitable tools in water resources management. On the other hand, time series concepts is considered efficient means in forecasting process of water management. In this study the data including qualitative parameters (electrical conductivity and sodium adsorption ratio) of 17 underground water wells in Mehran Plain has been used to model the trend of parameters change over time. Using determined model, the qualitative parameters of groundwater is predicted for the next seven years. Data from 2003 to 2016 has been collected and were fitted by AR, MA, ARMA, ARIMA and SARIMA models. Afterward, the best model is determined using information criterion or Akaike (AIC) and correlation coefficient. After modeling parameters, the map of agricultural land use in 2016 and 2023 were generated and the changes between these years were studied. Based on the results, the average of predicted SAR (Sodium Adsorption Rate) in all wells in the year 2023 will increase compared to 2016. EC (Electrical Conductivity) average in the ninth and fifteenth holes and decreases in other wells will be increased. The results indicate that the quality of groundwater for Agriculture Plain Mehran will decline in seven years.

  20. Prevention of brachial plexus injury-12 years of shoulder dystocia training: an interrupted time-series study.

    Science.gov (United States)

    Crofts, J F; Lenguerrand, E; Bentham, G L; Tawfik, S; Claireaux, H A; Odd, D; Fox, R; Draycott, T J

    2016-01-01

    To investigate management and outcomes of incidences of shoulder dystocia in the 12 years following the introduction of an obstetric emergencies training programme. Interrupted time-series study comparing management and neonatal outcome of births complicated by shoulder dystocia over three 4-year periods: (i) Pre-training (1996-99), (ii) Early training (2001-04), and (iii) Late training (2009-12). Southmead Hospital, Bristol, UK, with approximately 6000 births per annum. Infants and their mothers who experienced shoulder dystocia. A bi-monthly multi-professional 1-day intrapartum emergencies training course, that included a 30-minute practical session on shoulder dystocia management, commenced in 2000. Neonatal morbidity (brachial plexus injury, humeral fracture, clavicular fracture, 5-minute Apgar score dystocia (resolution manoeuvres performed, traction applied, head-to-body delivery interval). Compliance with national guidance improved with continued training. At least one recognised resolution manoeuvre was used in 99.8% (561/562) of cases of shoulder dystocia in the late training period, demonstrating a continued improvement from 46.3% (150/324, P dystocia. © 2015 Royal College of Obstetricians and Gynaecologists.

  1. Solar magnetic field studies using the 12 micron emission lines. I - Quiet sun time series and sunspot slices

    Science.gov (United States)

    Deming, Drake; Boyle, Robert J.; Jennings, Donald E.; Wiedemann, Gunter

    1988-01-01

    The use of the extremely Zeeman-sensitive IR emission line Mg I, at 12.32 microns, to study solar magnetic fields. Time series observations of the line in the quiet sun were obtained in order to determine the response time of the line to the five-minute oscillations. Based upon the velocity amplitude and average period measured in the line, it is concluded that it is formed in the temperature minimum region. The magnetic structure of sunspots is investigated by stepping a small field of view in linear 'slices' through the spots. The region of penumbral line formation does not show the Evershed outflow common in photospheric lines. The line intensity is a factor of two greater in sunspot penumbrae than in the photosphere, and at the limb the penumbral emission begins to depart from optical thinness, the line source function increasing with height. For a spot near disk center, the radial decrease in absolute magnetic field strength is steeper than the generally accepted dependence.

  2. Modeling Biogeochemical-Physical Interactions and Carbon Flux in the Sargasso Sea (Bermuda Atlantic Time-series Study site)

    Science.gov (United States)

    Signorini, Sergio R.; McClain, Charles R.; Christian, James R.

    2001-01-01

    An ecosystem-carbon cycle model is used to analyze the biogeochemical-physical interactions and carbon fluxes in the Bermuda Atlantic Time-series Study (BATS) site for the period of 1992-1998. The model results compare well with observations (most variables are within 8% of observed values). The sea-air flux ranges from -0.32 to -0.50 mol C/sq m/yr, depending upon the gas transfer algorithm used. This estimate is within the range (-0.22 to -0.83 mol C/sq m/yr) of previously reported values which indicates that the BATS region is a weak sink of atmospheric CO2. The overall carbon balance consists of atmospheric CO2 uptake of 0.3 Mol C/sq m/yr, upward dissolved inorganic carbon (DIC) bottom flux of 1.1 Mol C/sq m/yr, and carbon export of 1.4 mol C/sq m/yr via sedimentation. Upper ocean DIC levels increased between 1992 and 1996 at a rate of approximately 1.2 (micro)mol/kg/yr, consistent with observations. However, this trend was reversed during 1997-1998 to -2.7 (micro)mol/kg/yr in response to hydrographic changes imposed by the El Nino-La Nina transition, which were manifested in the Sargasso Sea by the warmest SST and lowest surface salinity of the period (1992-1998).

  3. Cluster survey of the high-altitude cusp properties: a three-year statistical study

    Directory of Open Access Journals (Sweden)

    B. Lavraud

    2004-09-01

    Full Text Available The global characteristics of the high-altitude cusp and its surrounding regions are investigated using a three-year statistical survey based on data obtained by the Cluster spacecraft. The analysis involves an elaborate orbit-sampling methodology that uses a model field and takes into account the actual solar wind conditions and level of geomagnetic activity. The spatial distribution of the magnetic field and various plasma parameters in the vicinity of the low magnetic field exterior cusp are determined and it is found that: 1 The magnetic field distribution shows the presence of an intermediate region between the magnetosheath and the magnetosphere: the exterior cusp, 2 This region is characterized by the presence of dense plasma of magnetosheath origin; a comparison with the Tsyganenko (1996 magnetic field model shows that it is diamagnetic in nature, 3 The spatial distributions show that three distinct boundaries with the lobes, the dayside plasma sheet and the magnetosheath surround the exterior cusp, 4 The external boundary with the magnetosheath has a sharp bulk velocity gradient, as well as a density decrease and temperature increase as one goes from the magnetosheath to the exterior cusp, 5 While the two inner boundaries form a funnel, the external boundary shows no clear indentation, 6 The plasma and magnetic pressure distributions suggest that the exterior cusp is in equilibrium with its surroundings in a statistical sense, and 7 A preliminary analysis of the bulk flow distributions suggests that the exterior cusp is stagnant under northward IMF conditions but convective under southward IMF conditions.

  4. Acute effects of air pollution on spontaneous abortion, premature delivery, and stillbirth in Ahvaz, Iran: a time-series study.

    Science.gov (United States)

    Dastoorpoor, Maryam; Idani, Esmaeil; Goudarzi, Gholamreza; Khanjani, Narges

    2018-02-01

    Living in areas with high air pollution may have adverse effects on human health. There are few studies about the association between breathing polluted air and adverse pregnancy outcomes in the Middle East. The aim of this study was to determine the relationship between air pollution and spontaneous abortion, premature birth, and stillbirth in Ahvaz. A time-series study was conducted. Data about spontaneous abortion, premature deliveries, and stillbirth was collected from Ahvaz Imam Khomeini Hospital. Air pollution data including NO, CO, NO 2 , PM 10 , SO 2 , O 3 , and climate data were, respectively, collected from the Environmental Protection Agency and the Khuzestan Province Meteorology Office from March 2008 until March 2015. The relationship between air pollutants with the number of abortions, premature births, and stillbirths was found using a quasi-Poisson distributed lag model, adjusted by trend, seasonality, temperature, relative humidity, weekdays, and holidays. The average daily dust in Ahvaz on 7.2% days of the year was higher than 500 μg/m 3 (very dangerous). Findings from this study indicate a significant association between each 10-unit increase in SO 2 and spontaneous abortion in lag 0 and 9 days. There was a significant relation between each 10-unit increase in NO 2 and CO, and premature birth in lag 0. Also, we found a significant association between each 10-unit increase in CO and premature delivery in lag 1; PM 10 and premature delivery in lags 10, 11, and 12; and NO and premature delivery in lags 3, 4, 10, 11, 12, and 13 (p value polluted air during pregnancy may increase adverse pregnancy outcomes and stillbirth. Pregnant women should avoid polluted air.

  5. Detecting discontinuities in GNSS coordinate time series with STARS: case study, the Bologna and Medicina GPS sites

    Science.gov (United States)

    Bruni, S.; Zerbini, Susanna; Raicich, F.; Errico, M.; Santi, E.

    2014-12-01

    Global navigation satellite systems (GNSS) data are a fundamental source of information for achieving a better understanding of geophysical and climate-related phenomena. However, discontinuities in the coordinate time series might be a severe limiting factor for the reliable estimate of long-term trends. A methodological approach has been adapted from Rodionov (Geophys Res Lett 31:L09204, 2004; Geophys Res Lett 31:L12707, 2006) and from Rodionov and Overland (J Marine Sci 62:328-332, 2005) to identify both the epoch of occurrence and the magnitude of jumps corrupting GNSS data sets without any a priori information on these quantities. The procedure is based on the Sequential t test Analysis of Regime Shifts (STARS) (Rodionov in Geophys Res Lett 31:L09204, 2004). The method has been tested against a synthetic data set characterized by typical features exhibited by real GNSS time series, such as linear trend, seasonal cycle, jumps, missing epochs and a combination of white and flicker noise. The results show that the offsets identified by the algorithm are split into 48 % of true-positive, 28 % of false-positive and 24 % of false-negative events. The procedure has then been applied to GPS coordinate time series of stations located in the southeastern Po Plain, in Italy. The series span more than 15 years and are affected by offsets of different nature. The methodology proves to be effective, as confirmed by the comparison between the corrected GPS time series and those obtained by other observation techniques.

  6. Sick building syndrome (SBS) and exposure to water-damaged buildings: time series study, clinical trial and mechanisms.

    Science.gov (United States)

    Shoemaker, Ritchie C; House, Dennis E

    2006-01-01

    Occupants of water-damaged buildings (WDBs) with evidence of microbial amplification often describe a syndrome involving multiple organ systems, commonly referred to as "sick building syndrome" (SBS), following chronic exposure to the indoor air. Studies have demonstrated that the indoor air of WDBs often contains a complex mixture of fungi, mycotoxins, bacteria, endotoxins, antigens, lipopolysaccharides, and biologically produced volatile compounds. A case-series study with medical assessments at five time points was conducted to characterize the syndrome after a double-blinded, placebo-controlled clinical trial conducted among a group of study participants investigated the efficacy of cholestyramine (CSM) therapy. The general hypothesis of the time series study was that chronic exposure to the indoor air of WDBs is associated with SBS. Consecutive clinical patients were screened for diagnosis of SBS using criteria of exposure potential, symptoms involving at least five organ systems, and the absence of confounding factors. Twenty-eight cases signed voluntary consent forms for participation in the time-series study and provided samples of microbial contaminants from water-damaged areas in the buildings they occupied. Twenty-six participants with a group-mean duration of illness of 11 months completed examinations at all five study time points. Thirteen of those participants also agreed to complete a double-blinded, placebo-controlled clinical trial. Data from Time Point 1 indicated a group-mean of 23 out of 37 symptoms evaluated; and visual contrast sensitivity (VCS), an indicator of neurological function, was abnormally low in all participants. Measurements of matrix metalloproteinase 9 (MMP9), leptin, alpha melanocyte stimulating hormone (MSH), vascular endothelial growth factor (VEGF), immunoglobulin E (IgE), and pulmonary function were abnormal in 22, 13, 25, 14, 1, and 7 participants, respectively. Following 2 weeks of CSM therapy to enhance toxin elimination

  7. Acute effects of ambient air pollution on lower respiratory infections in Hanoi children: An eight-year time series study.

    Science.gov (United States)

    Nhung, Nguyen Thi Trang; Schindler, Christian; Dien, Tran Minh; Probst-Hensch, Nicole; Perez, Laura; Künzli, Nino

    2018-01-01

    Lower respiratory diseases are the most frequent causes of hospital admission in children worldwide, particularly in developing countries. Daily levels of air pollution are associated with lower respiratory diseases, as documented in many time-series studies. However, investigations in low-and-middle-income countries, such as Vietnam, remain sparse. This study investigated the short-term association of ambient air pollution with daily counts of hospital admissions due to pneumonia, bronchitis and asthma among children aged 0-17 in Hanoi, Vietnam. We explored the impact of age, gender and season on these associations. Daily ambient air pollution concentrations and hospital admission counts were extracted from electronic databases received from authorities in Hanoi for the years 2007-2014. The associations between outdoor air pollution levels and hospital admissions were estimated for time lags of zero up to seven days using Quasi-Poisson regression models, adjusted for seasonal variations, meteorological variables, holidays, influenza epidemics and day of week. All ambient air pollutants were positively associated with pneumonia hospitalizations. Significant associations were found for most pollutants except for ozone and sulfur dioxide in children aged 0-17. Increments of an interquartile range (21.9μg/m 3 ) in the 7-day-average level of NO 2 were associated with a 6.1% (95%CI 2.5% to 9.8%) increase in pneumonia hospitalizations. These associations remained stable in two-pollutant models. All pollutants other than CO were positively associated with hospitalizations for bronchitis and asthma. Associations were stronger in infants than in children aged 1-5. Strong associations between hospital admissions for lower respiratory infections and daily levels of air pollution confirm the need to adopt sustainable clean air policies in Vietnam to protect children's health. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

  8. A prospective study on the neurological complications of breast cancer and its treatment: Updated analysis three years after cancer diagnosis.

    Science.gov (United States)

    Fontes, Filipa; Pereira, Susana; Castro-Lopes, José Manuel; Lunet, Nuno

    2016-10-01

    To quantify the prevalence of neurological complications among breast cancer patients at one and three years after diagnosis, and to identify factors associated with neuropathic pain (NP) and chemotherapy-induced peripheral neuropathy (CIPN). Prospective cohort study including 475 patients with newly diagnosed breast cancer, recruited among those proposed for surgical treatment (Portuguese Institute of Oncology, Porto). Patients underwent a neurological evaluation and had their cognitive function assesses with the Montreal Cognitive Assessment, before treatment and at one and three years after enrollment. We estimated the prevalence of each neurological complication, and odds ratios (OR), adjusted for socio-demographic and clinical characteristics, to identify factors associated with NP and CIPN. More than half of the patients [54.7%, 95% confidence interval (95%CI): 50.2-59.2] presented at least one neurological complication, at one or at three years after cancer diagnosis. Between the first and the third year of follow-up, there was an increase in the prevalence of NP (from 21.1% to 23.6%), cognitive impairment (from 7.2% to 8.2%), cerebrovascular disease (from 0.6% to 1.5%) and brain metastasis (from 0.0% to 0.6%). The prevalence of CIPN decreased from 14.1% to 12.6%. Axillary lymph node dissection was associated with NP at one year (OR = 2.75, 95%CI: 1.34-5.63) and chemotherapy with NP at three years (OR = 2.10, 95%CI: 1.20-3.67). Taxane-based chemotherapy was strongly associated with prevalence of CIPN at one and three years. Neurological complications are frequent even three years after cancer diagnosis and NP remained the major contributor to the burden of these conditions among survivors. Copyright © 2016. Published by Elsevier Ltd.

  9. The Continuity of College Students' Autonomous Learning Motivation and Its Predictors: A Three-Year Longitudinal Study

    Science.gov (United States)

    Pan, Yingqiu; Gauvain, Mary

    2012-01-01

    This study examined change in Chinese students' autonomous learning motivation in the first three years of college and how this change is accounted for by intra- and inter-individual variables. The sample included 633 (328 female) college freshmen. Results showed that students' autonomous learning motivation decreased over years in college.…

  10. Forecasting Cryptocurrencies Financial Time Series

    OpenAIRE

    Catania, Leopoldo; Grassi, Stefano; Ravazzolo, Francesco

    2018-01-01

    This paper studies the predictability of cryptocurrencies time series. We compare several alternative univariate and multivariate models in point and density forecasting of four of the most capitalized series: Bitcoin, Litecoin, Ripple and Ethereum. We apply a set of crypto–predictors and rely on Dynamic Model Averaging to combine a large set of univariate Dynamic Linear Models and several multivariate Vector Autoregressive models with different forms of time variation. We find statistical si...

  11. Effects of decompressive cervical surgery on blood pressure in cervical spondylosis patients with hypertension: a time series cohort study.

    Science.gov (United States)

    Liu, Hong; Wang, Hai-Bo; Wu, Lin; Wang, Shi-Jun; Yang, Ze-Chuan; Ma, Run-Yi; Reilly, Kathleen H; Yan, Xiao-Yan; Ji, Ping; Wu, Yang-feng

    2016-01-06

    Patients with cervical spondylosis myelopathy (CSM) and complicated with hypertension are often experiencing a blood pressure decrease after taking cervical decompressive surgery in clinical observations, but how this blood pressure reduction is associated with the surgery, which cut cervical sympathetic nervous, has never been rigorously assessed. Thus, the purpose of this study is to investigate the effect of cervical decompressive surgery on blood pressure among CSM patients with hypertension. The study will be a time series cohort study. Fifty eligible patients will be selected consecutively from the Peking University First Hospital. Two 24-h ambulatory blood pressure measurement (ABPM) will be taken before the surgery, apart by at least 3 days. The patients will be followed up for another two ABPMs at 1 and 3 months after the surgery. We will recruit subjects with cervical spondylosis myelopathy meeting operation indications and scheduled for receiving cervical decompressive surgery, aged 18-84 years, have a history of hypertension or office systolic blood pressure ≥140 mmHg on initial screening, and willing to participate in the study and provide informed consent. Exclusion criteria includes a history of known secondary hypertension, visual analogue scale (VAS) score ≥4, and unable to comply with study due to severe psychosis. The change in systolic ABPs over the four times will be analyzed to observe the overall pattern of the blood pressure change in relation to the surgery, but the primary analysis will be the comparison of systolic ABP between the 2(nd) and 3(rd), 4(th) measurements (before and after the surgery). We will also calculate the regression-to-the-mean adjusted changes in systolic ABP as sensitivity analysis. Secondary endpoints are the changes in 24 h ABPM diastolic blood pressure, blood pressure control status, the use and dose adjustment of antihypertensive medication, and the incidence of operative complications. Primary outcome

  12. Introduction to Time Series Modeling

    CERN Document Server

    Kitagawa, Genshiro

    2010-01-01

    In time series modeling, the behavior of a certain phenomenon is expressed in relation to the past values of itself and other covariates. Since many important phenomena in statistical analysis are actually time series and the identification of conditional distribution of the phenomenon is an essential part of the statistical modeling, it is very important and useful to learn fundamental methods of time series modeling. Illustrating how to build models for time series using basic methods, "Introduction to Time Series Modeling" covers numerous time series models and the various tools f

  13. Historical Fire Detection of Tropical Forest from NDVI Time-series Data: Case Study on Jambi, Indonesia

    Directory of Open Access Journals (Sweden)

    Dyah R. Panuju

    2010-03-01

    Full Text Available In addition to forest encroachment, forest fire is a serious problem in Indonesia. Attempts at managing its widespread and frequent occurrence has led to intensive use of remote sensing data. Coarse resolution images have been employed to derive hot spots as an indicator of forest fire. However, most efforts to verify the hot spot data and to verify fire accidents have been restricted to the use of medium or high resolution data. At present, it is difficult to verify solely upon those data due to severe cloud cover and low revisit time. In this paper, we present a method to validate forest fire using NDVI time series data. With the freely available NDVI data from SPOT VEGETATION, we successfully detected changes in time series data which were associated with fire accidents.

  14. Modelling fourier regression for time series data- a case study: modelling inflation in foods sector in Indonesia

    Science.gov (United States)

    Prahutama, Alan; Suparti; Wahyu Utami, Tiani

    2018-03-01

    Regression analysis is an analysis to model the relationship between response variables and predictor variables. The parametric approach to the regression model is very strict with the assumption, but nonparametric regression model isn’t need assumption of model. Time series data is the data of a variable that is observed based on a certain time, so if the time series data wanted to be modeled by regression, then we should determined the response and predictor variables first. Determination of the response variable in time series is variable in t-th (yt), while the predictor variable is a significant lag. In nonparametric regression modeling, one developing approach is to use the Fourier series approach. One of the advantages of nonparametric regression approach using Fourier series is able to overcome data having trigonometric distribution. In modeling using Fourier series needs parameter of K. To determine the number of K can be used Generalized Cross Validation method. In inflation modeling for the transportation sector, communication and financial services using Fourier series yields an optimal K of 120 parameters with R-square 99%. Whereas if it was modeled by multiple linear regression yield R-square 90%.

  15. Reducing waiting time and raising outpatient satisfaction in a Chinese public tertiary general hospital-an interrupted time series study

    Directory of Open Access Journals (Sweden)

    Jing Sun

    2017-08-01

    Full Text Available Abstract Background It is globally agreed that a well-designed health system deliver timely and convenient access to health services for all patients. Many interventions aiming to reduce waiting times have been implemented in Chinese public tertiary hospitals to improve patients’ satisfaction. However, few were well-documented, and the effects were rarely measured with robust methods. Methods We conducted a longitudinal study of the length of waiting times in a public tertiary hospital in Southern China which developed comprehensive data collection systems. Around an average of 60,000 outpatients and 70,000 prescribed outpatients per month were targeted for the study during Oct 2014-February 2017. We analyzed longitudinal time series data using a segmented linear regression model to assess changes in levels and trends of waiting times before and after the introduction of waiting time reduction interventions. Pearson correlation analysis was conducted to indicate the strength of association between waiting times and patient satisfactions. The statistical significance level was set at 0.05. Results The monthly average length of waiting time decreased 3.49 min (P = 0.003 for consultations and 8.70 min (P = 0.02 for filling prescriptions in the corresponding month when respective interventions were introduced. The trend shifted from baseline slight increasing to afterwards significant decreasing for filling prescriptions (P =0.003. There was a significant negative correlation between waiting time of filling prescriptions and outpatient satisfaction towards pharmacy services (r = −0.71, P = 0.004. Conclusions The interventions aimed at reducing waiting time and raising patient satisfaction in Fujian Provincial Hospital are effective. A long-lasting reduction effect on waiting time for filling prescriptions was observed because of carefully designed continuous efforts, rather than a one-time campaign, and with appropriate incentives

  16. Reducing waiting time and raising outpatient satisfaction in a Chinese public tertiary general hospital-an interrupted time series study.

    Science.gov (United States)

    Sun, Jing; Lin, Qian; Zhao, Pengyu; Zhang, Qiongyao; Xu, Kai; Chen, Huiying; Hu, Cecile Jia; Stuntz, Mark; Li, Hong; Liu, Yuanli

    2017-08-22

    It is globally agreed that a well-designed health system deliver timely and convenient access to health services for all patients. Many interventions aiming to reduce waiting times have been implemented in Chinese public tertiary hospitals to improve patients' satisfaction. However, few were well-documented, and the effects were rarely measured with robust methods. We conducted a longitudinal study of the length of waiting times in a public tertiary hospital in Southern China which developed comprehensive data collection systems. Around an average of 60,000 outpatients and 70,000 prescribed outpatients per month were targeted for the study during Oct 2014-February 2017. We analyzed longitudinal time series data using a segmented linear regression model to assess changes in levels and trends of waiting times before and after the introduction of waiting time reduction interventions. Pearson correlation analysis was conducted to indicate the strength of association between waiting times and patient satisfactions. The statistical significance level was set at 0.05. The monthly average length of waiting time decreased 3.49 min (P = 0.003) for consultations and 8.70 min (P = 0.02) for filling prescriptions in the corresponding month when respective interventions were introduced. The trend shifted from baseline slight increasing to afterwards significant decreasing for filling prescriptions (P =0.003). There was a significant negative correlation between waiting time of filling prescriptions and outpatient satisfaction towards pharmacy services (r = -0.71, P = 0.004). The interventions aimed at reducing waiting time and raising patient satisfaction in Fujian Provincial Hospital are effective. A long-lasting reduction effect on waiting time for filling prescriptions was observed because of carefully designed continuous efforts, rather than a one-time campaign, and with appropriate incentives implemented by a taskforce authorized by the hospital managers. This

  17. Data mining in time series databases

    CERN Document Server

    Kandel, Abraham; Bunke, Horst

    2004-01-01

    Adding the time dimension to real-world databases produces Time SeriesDatabases (TSDB) and introduces new aspects and difficulties to datamining and knowledge discovery. This book covers the state-of-the-artmethodology for mining time series databases. The novel data miningmethods presented in the book include techniques for efficientsegmentation, indexing, and classification of noisy and dynamic timeseries. A graph-based method for anomaly detection in time series isdescribed and the book also studies the implications of a novel andpotentially useful representation of time series as strings. Theproblem of detecting changes in data mining models that are inducedfrom temporal databases is additionally discussed.

  18. Remotely-sensed, nocturnal, dew point correlates with malaria transmission in Southern Province, Zambia: a time-series study.

    Science.gov (United States)

    Nygren, David; Stoyanov, Cristina; Lewold, Clemens; Månsson, Fredrik; Miller, John; Kamanga, Aniset; Shiff, Clive J

    2014-06-13

    Plasmodium falciparum transmission has decreased significantly in Zambia in the last decade. The malaria transmission is influenced by environmental variables. Incorporation of environmental variables in models of malaria transmission likely improves model fit and predicts probable trends in malaria disease. This work is based on the hypothesis that remotely-sensed environmental factors, including nocturnal dew point, are associated with malaria transmission and sustain foci of transmission during the low transmission season in the Southern Province of Zambia. Thirty-eight rural health centres in Southern Province, Zambia were divided into three zones based on transmission patterns. Correlations between weekly malaria cases and remotely-sensed nocturnal dew point, nocturnal land surface temperature as well as vegetation indices and rainfall were evaluated in time-series analyses from 2012 week 19 to 2013 week 36. Zonal as well as clinic-based, multivariate, autoregressive, integrated, moving average (ARIMAX) models implementing environmental variables were developed to model transmission in 2011 week 19 to 2012 week 18 and forecast transmission in 2013 week 37 to week 41. During the dry, low transmission season significantly higher vegetation indices, nocturnal land surface temperature and nocturnal dew point were associated with the areas of higher transmission. Environmental variables improved ARIMAX models. Dew point and normalized differentiated vegetation index were significant predictors and improved all zonal transmission models. In the high-transmission zone, this was also seen for land surface temperature. Clinic models were improved by adding dew point and land surface temperature as well as normalized differentiated vegetation index. The mean average error of prediction for ARIMAX models ranged from 0.7 to 33.5%. Forecasts of malaria incidence were valid for three out of five rural health centres; however, with poor results at the zonal level. In this

  19. Predicting the transition from frequent cannabis use to cannabis dependence: a three-year prospective study.

    NARCIS (Netherlands)

    van der Pol, P.; Liebregts, N.; de Graaf, R.; Korf, D.J.; van den Brink, W.; van Laar, M.

    2013-01-01

    Background Frequent cannabis users are at high risk of dependence, still most (near) daily users are not dependent. It is unknown why some frequent users develop dependence, whereas others do not. This study aims to identify predictors of first-incidence DSM-IV cannabis dependence in frequent

  20. Predicting the transition from frequent cannabis use to cannabis dependence: a three-year prospective study

    NARCIS (Netherlands)

    van der Pol, Peggy; Liebregts, Nienke; de Graaf, Ron; Korf, Dirk J.; van den Brink, Wim; van Laar, Margriet

    2013-01-01

    Frequent cannabis users are at high risk of dependence, still most (near) daily users are not dependent. It is unknown why some frequent users develop dependence, whereas others do not. This study aims to identify predictors of first-incidence DSM-IV cannabis dependence in frequent cannabis users. A

  1. Positive Mental Health Three Years After East Azerbaijan Earthquake: A Comparative Study

    Directory of Open Access Journals (Sweden)

    Hassan Rafiey

    2016-10-01

    Conclusion: Attention to long-term mental and social outcomes is the missing link of health studies in incidents and disasters, which must be considered to recover and enhance mental and social health of survivors of natural disasters at the earliest time after the incidents.

  2. Burnout and Physical Health among Social Workers: A Three-Year Longitudinal Study

    Science.gov (United States)

    Kim, Hansung; Ji, Juye; Kao, Dennis

    2011-01-01

    The high risk of burnout in the social work profession is well established, but little is known about burnout's impact on the physical health of social workers. This article examines the relationship between burnout and physical health, using data from a longitudinal study of social workers. California-registered social workers (N = 406) were…

  3. A Three-Year Journey: Lessons Learned from Integrating Teacher Preparation and Urban Studies

    Science.gov (United States)

    Yontz, Brian D.

    2012-01-01

    This narrative outlines the process of how an independent liberal arts college integrated coursework and learning experiences focused on urban school teacher preparation with an existing university program in Urban Studies. Programmatic changes and additions to teacher education programs at independent liberal arts colleges are often very…

  4. Biomedical Engineering and Cognitive Science Secondary Science Curriculum Development: A Three Year Study

    Science.gov (United States)

    Klein, Stacy S.; Sherwood, Robert D.

    2005-01-01

    This study reports on a multi-year effort to create and evaluate cognitive-based curricular materials for secondary school science classrooms. A team of secondary teachers, educational researchers, and academic biomedical engineers developed a series of curriculum units that are based in biomedical engineering for secondary level students in…

  5. Mentoring Support and Power: A Three Year Predictive Field Study on Protege Networking and Career Success

    Science.gov (United States)

    Blickle, Gerhard; Witzki, Alexander H.; Schneider, Paula B.

    2009-01-01

    Career success of early employees was analyzed from a power perspective and a developmental network perspective. In a predictive field study with 112 employees mentoring support and mentors' power were assessed in the first wave, employees' networking was assessed after two years, and career success (i.e. income and hierarchical position) and…

  6. A THREE YEAR RETROSPECTIVE STUDY OF OVARIAN NEOPLASMS WITH SPECIAL EMPHASIS ON SURFACE EPITHELIAL TUMOURS

    Directory of Open Access Journals (Sweden)

    Krishna Bharathi Yarlagadda

    2016-07-01

    Full Text Available BACKGROUND Ovarian tumours being second most common gynaecological cancer in India account for 30% of all cancers of female genital tract. Study conducted to determine relative frequencies of various histological types based on WHO classification and their age distribution with particular emphasis on surface epithelial tumours. This study is undertaken to find out the frequency of incidence of different histopathological subtypes with particular emphasis on surface epithelial tumours and age distribution of ovarian tumours in our institute located in coastal Andhra Pradesh. METHODS This is a retrospective study of 100 cases of ovarian neoplasms collected during a period of 3 years from June 2013 to May 2016 from the Department of Pathology, Katuri Medical College and Hospital, Chinakondrupadu, Guntur, A. P, India. The patients attending our hospital are mostly from rural areas around. Paraffin blocks of all 100 ovarian neoplasms retrieved. Complete clinical and radiological findings analysed from our records. RESULTS The tumours are grouped according to the nature of tumour whether benign or borderline or malignant according to cell of origin, histological subtyping, and age group. Surface epithelial tumours are the most common. Benign tumours outnumber the malignant tumours. Benign ovarian tumours showed a peak in 21-40 Yrs. age group and malignant in the age group of 41- 60 Yrs. Results of our study compared with other studies. CONCLUSION Because of the geographic location, poverty, and illiteracy, patients seek medical advice late. So, awareness among public by health education, passive surveillance, and community screening facility will be helpful in early detection of ovarian neoplasms.

  7. [Development and applications of photosensitive device systems to biological studies]. Three year progress report

    International Nuclear Information System (INIS)

    1978-01-01

    The research has been directed to the two areas of x-ray diffraction and bioluminescence, with emphasis in the area of x-ray detection. Interest in x-ray image intensification techniques for biological and medical applications is long standing, and more and more utilized each year. During the past year, as the result of publications and participation in several workshops, the demonstrated advantages of our system over fast scan TV systems and multiwire chambers have become recognized, and several groups have requested us to supply them with a similar system. This is particularly true for use at the synchrotron x-ray sources. Although in recent years less effort has been spent in bioluminescence studies, results have been numerous, both in instrumentation development and experimental results. Bioluminescence is not only of interest in itself, but is a powerful tool for nondestructive study of other biological processes

  8. Non-nutritive sucking habits after three years of age: A case-control study

    Directory of Open Access Journals (Sweden)

    Izabella Barbosa Fernandes

    2015-01-01

    Full Text Available Background: Non-nutritive sucking habits can result in negative consequences on the development of orofacial structures and occlusion. Aim: Assess factors associated with non-nutritive sucking habits in children after 3 years old. Materials and Methods: A case-control study was carried out in two stages. In the first stage, a cross-sectional study was conducted with 638 children aged 3-6 years. In the second stage, a case-control study (1:2 was conducted. The case group included all children who presented some non-nutritive sucking habits in the first stage of the study (n = 110. The control group (n = 220 was made up of children who had never presented non-nutritive sucking habits, matched to the case group for gender and age. The data were collected during the national poliomyelitis vaccination campaign, through a questionnaire applied to parents/guardians with questions related to the presence of sucking habits, sociodemographic aspects, birth aspects, and early life of the child. Statistical analysis involved descriptive analysis, chi-square test, Mann-Whitney test, and conditional logistic regression. Results: Reduction in maternal education was a protective factor for the development of non-nutritive sucking habits (education ≤8 years OR = 0.38, CI 95%: 0.16, 0.89, P = 0.025. Prematurity (OR = 3.30, CI 95%: 1.13, 9.69, P = 0.030 and a longer period using a baby bottle (OR = 1.03, CI 95%: 1.01, 1.05, P = 0.006 remained associated with a greater possibility of the occurrence of sucking habits, regardless of monthly family income. Conclusion: Non-nutritive sucking habits were associated with maternal education, premature birth, and greater time of bottle feeding in children after 3 years old.

  9. [Main Causes of Occupational Allergic Contact Dermatitis: A Three Year Study in the Center of Portugal].

    Science.gov (United States)

    Pestana, Catarina; Gomes, Raquel; Pinheiro, Vítor; Gouveia, Miguel; Antunes, Isabel; Gonçalo, Margarida

    2016-08-01

    Allergic contact dermatitis, along with irritant contact dermatitis and immediate contact reactions, contact urticarial, are the most frequent dermatological occupational disease, but seldom reported to the National authorities. We performed a 3-year retrospective study at the allergology section in the Dermatology Clinic of the University Hospital of Coimbra to evaluate the main occupations diagnosed as occupational allergic contact dermatitis, most common allergens and the effect of the modification of the work station in the evolution of the disease. During 2012 - 2014 among the 941 patch tested patients, 77 (8.2%) were diagnosed with occupational allergic contact dermatitis, with 169 positive patch tests related to occupational exposure, 55 detected within the baseline and 114 in complementary test series. In most cases allergic contact dermatitis involved the hands (88.3%), main professional activities were nail estheticians and hairdressers due to the manipulation of (meth)acrylates, the most common allergen in the study. After the diagnosis, 27.3% abandoned the work, 23.4% changed the work station, 49% avoided exposure to the responsible allergen. Contact dermatitis resolved in 39% of the patients, improved in 39% but had no change in the remaining 22%. This study, although including only patients from the center of Portugal, evaluates a large sample of patients with different occupations studied with a larger variety of allergens. Apart from classical allergens and professions responsible for occupational allergic contact dermatitis that we found in lower numbers (thiuram mix, paraphenylenodiamine, chromium and cobalt in health care workers, hairdressers and in the building industry), (meth)acrylates tested outside the European and Portuguese Baseline Series were the main cause of occupational allergic contact dermatitis, namely in nail estheticians. Methylisothiazolinone, the second more frequent occupational contact allergen in the present study was

  10. A Three-Year Epidemiological Study of Animal Bites and Rabies in Hamedan Province of Iran

    Directory of Open Access Journals (Sweden)

    Abdolmajid Mohammadzadeh

    2017-05-01

    Full Text Available Background Rabies is an almost invariably fatal disease that is associated with animal bites. Hence, gathering data about cases of animal bites can help in clarifying the relative status of the disease. Objectives This study was conducted to provide an epidemiological overview on animal bites and rabies occurred in Hamedan province, Iran, during 2011 - 2013. Methods This cross sectional descriptive study was conducted in Hamedan province, Iran. The information was retrieved from the vice-chancellery for health (Hamedan University of Medical Sciences and veterinary directorate general of Hamedan province. The data were analyzed using the SPSS software. The Chi-square test was used to determine statistically significant differences with P values less than 0.05. Results There was just one report of rabies death during the mentioned period. The total number of reported animal bites was 14327 with the incidence of 2.69 cases/1000 individuals, which included 3287 (22.9% women and 11040 (77.1% men. Of these cases, 9868 (68.9% resided in rural areas, while 4459 (31.3% were urban residents. Most animal bites, 3516 (24.54% cases, occurred in the 20 - 29 year-old age group. The lower limbs injuries were significantly higher than other sites with 7462 (52.08% records. In addition, the majority of people were bitten by dogs (11040 cases, 77%. Conclusions This study indicated that the incidence of animal bites was increased during 2011 - 2013 in Hamedan province. Therefore, it seems necessary to take appropriate educational programs along with both pre-exposure immunization and postexposure prophylaxis to control this infection in the region.

  11. A SPECT study of language and brain reorganization three years after pediatric brain injury.

    Science.gov (United States)

    Chiu Wong, Stephanie B; Chapman, Sandra B; Cook, Lois G; Anand, Raksha; Gamino, Jacquelyn F; Devous, Michael D

    2006-01-01

    Using single photon emission computed tomography (SPECT), we investigated brain plasticity in children 3 years after sustaining a severe traumatic brain injury (TBI). First, we assessed brain perfusion patterns (i.e., the extent of brain blood flow to regions of the brain) at rest in eight children who suffered severe TBI as compared to perfusion patterns in eight normally developing children. Second, we examined differences in perfusion between children with severe TBI who showed good versus poor recovery in complex discourse skills. Specifically, the children were asked to produce and abstract core meaning for two stories in the form of a lesson. Inconsistent with our predictions, children with severe TBI showed areas of increased perfusion as compared to normally developing controls. Adult studies have shown the reverse pattern with TBI associated with reduced perfusion. With regard to the second aim and consistent with previously identified brain-discourse relations, we found a strong positive association between perfusion in right frontal regions and discourse abstraction abilities, with higher perfusion linked to better discourse outcomes and lower perfusion linked to poorer discourse outcomes. Furthermore, brain-discourse patterns of increased perfusion in left frontal regions were associated with lower discourse abstraction ability. The results are discussed in terms of how brain changes may represent adaptive and maladaptive plasticity. The findings offer direction for future studies of brain plasticity in response to neurocognitive treatments.

  12. Navigated versus conventional total knee arthroplasty: A prospective study at three years follow-up.

    Science.gov (United States)

    Martín-Hernández, C; Sanz-Sainz, M; Revenga-Giertych, C; Hernández-Vaquero, D; Fernández-Carreira, J M; Albareda-Albareda, J; Castillo-Palacios, A; Ranera-Garcia, M

    2018-03-28

    Computer-assisted surgery application in total knee arthroplasty (TKA) has shown more accurate implant alignment compared with conventional instrumentation and is associated with more homogeneous alignment results. Although longer implant survival and superior clinical outcomes should be expected from navigated TKA, currently available evidence does not support this hypothesis. The aim of this study was to compare navigated TKA with conventional TKA regarding clinical and radiological outcomes after a 3-year follow-up under the hypothesis that navigated TKA would provide better outcomes than conventional TKA. In a prospective multicentre study, 119 patients underwent navigated TKA and 80 patients received conventional instrumentation. Patients were evaluated at the baseline and at postoperative months 3, 12, 24, and 36. Analysis included the American Knee Society Score (KSS), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Short Form-12 (SF12) Health Survey, and radiographic assessment. All clinical scores improved significantly for all patients during the follow-up but were significantly better in the navigation group. The percentage of patients showing a mechanical axis between 3° of varus and 3° of valgus was significantly higher in the ATR group (93%) than in the conventional TKA group (71%) (P<.01). The use of computer-assisted surgery in TKA provides more accurate mechanical alignment and superior short-term functional outcomes compared to conventional TKA. Copyright © 2018 SECOT. Publicado por Elsevier España, S.L.U. All rights reserved.

  13. Effects of an exercise program during three years in obese boys: an intervention study

    Directory of Open Access Journals (Sweden)

    Yolanda Escalante

    2013-01-01

    Full Text Available The aim of this study was to determine the effect of a long-term exercise program (3 years on kinanthopometric and metabolic in obese children. The sample consisted of eight boys between 8 and 11 years, who conducted a aerobic multi-sport exercise program (three sessions, 90 minutes per week. Carried out an assessment kinanthropometric assessing the following parameters: height, weight, body mass index (BMI, zBMI, fat mass and fat free mass, and a metabolic assessing: total cholesterol (TC, HDL cholesterol, LDL cholesterol, triglycerides (TG, insuline, glucose, Homeostasis Model Assessment (HOMA-IR, ratio LDL/HDL and TC/HDL. Following the intervention, changes were observed on zBMI (ceasing to be obese after the intervention, total cholesterol, LDL, and ratio total cholesterol/HDL and glucose levels at the long term, showing that longitudinal interventions generate positive benefits on obese children mainly in the lipid profile.

  14. Phytoremediation of arsenic contaminated soil by arsenic accumulators: a three year study.

    Science.gov (United States)

    Raj, Anshita; Singh, Nandita

    2015-03-01

    To investigate whether phytoremediation can remove arsenic from the contaminated area, a study was conducted for three consecutive years to determine the efficiency of Pteris vittata, Adiantum capillus veneris, Christella dentata and Phragmites karka, on arsenic removal from the arsenic contaminated soil. Arsenic concentrations in the soil samples were analysed after harvesting in 2009, 2010 and 2011 at an interval of 6 months. Frond arsenic concentrations were also estimated in all the successive harvests. Fronds resulted in the greatest amount of arsenic removal. Root arsenic concentrations were analysed in the last harvest. Approximately 70 % of arsenic was removed by P. vittata which was recorded as the highest among the four plant species. However, 60 % of arsenic was removed by A. capillus veneris, 55.1 % by C. dentata and 56.1 % by P. karka of arsenic was removed from the contaminated soil in 3 years.

  15. Three year naturalistic outcome study of panic disorder patients treated with paroxetine.

    Science.gov (United States)

    Dannon, Pinhas N; Iancu, Iulian; Cohen, Ami; Lowengrub, Katherine; Grunhaus, Leon; Kotler, Moshe

    2004-06-11

    This naturalistic open label follow-up study had three objectives: 1) To observe the course of illness in Panic Disorder patients receiving long-term versus intermediate-term paroxetine treatment, 2) To compare the relapse rates and side-effect profile after long-term paroxetine treatment between patients with Panic Disorder and Panic Disorder with Agoraphobia, 3) To observe paroxetine's tolerability over a 24 month period. 143 patients with panic disorder (PD), with or without agoraphobia, successfully finished a short-term (ie 12 week) trial of paroxetine treatment. All patients then continued to receive paroxetine maintenance therapy for a total of 12 months. At the end of this period, 72 of the patients chose to discontinue paroxetine pharmacotherapy and agreed to be monitored throughout a one year discontinuation follow-up phase. The remaining 71 patients continued on paroxetine for an additional 12 months and then were monitored, as in the first group, for another year while medication-free. The primary limitation of our study is that the subgroups of patients receiving 12 versus 24 months of maintenance paroxetine therapy were selected according to individual patient preference and therefore were not assigned in a randomized manner. Only 21 of 143 patients (14%) relapsed during the one year medication discontinuation follow-up phase. There were no significant differences in relapse rates between the patients who received intermediate-term (up to 12 months) paroxetine and those who chose the long-term course (24 month paroxetine treatment). 43 patients (30.1%) reported sexual dysfunction. The patients exhibited an average weight gain of 5.06 kg. All patients who eventually relapsed demonstrated significantly greater weight increase (7.3 kg) during the treatment phase. The extension of paroxetine maintenance treatment from 12 to 24 months did not seem to further decrease the risk of relapse after medication discontinuation. Twenty-four month paroxetine

  16. Three year naturalistic outcome study of panic disorder patients treated with paroxetine

    Directory of Open Access Journals (Sweden)

    Lowengrub Katherine

    2004-06-01

    Full Text Available Abstract Background This naturalistic open label follow-up study had three objectives: 1 To observe the course of illness in Panic Disorder patients receiving long-term versus intermediate-term paroxetine treatment 2 To compare the relapse rates and side-effect profile after long-term paroxetine treatment between patients with Panic Disorder and Panic Disorder with Agoraphobia. 3 To observe paroxetine's tolerability over a 24 month period. Methods 143 patients with panic disorder (PD, with or without agoraphobia, successfully finished a short-term (ie 12 week trial of paroxetine treatment. All patients then continued to receive paroxetine maintenance therapy for a total of 12 months. At the end of this period, 72 of the patients chose to discontinue paroxetine pharmacotherapy and agreed to be monitored throughout a one year discontinuation follow-up phase. The remaining 71 patients continued on paroxetine for an additional 12 months and then were monitored, as in the first group, for another year while medication-free. The primary limitation of our study is that the subgroups of patients receiving 12 versus 24 months of maintenance paroxetine therapy were selected according to individual patient preference and therefore were not assigned in a randomized manner. Results Only 21 of 143 patients (14% relapsed during the one year medication discontinuation follow-up phase. There were no significant differences in relapse rates between the patients who received intermediate-term (up to 12 months paroxetine and those who chose the long-term course (24 month paroxetine treatment. 43 patients (30.1% reported sexual dysfunction. The patients exhibited an average weight gain of 5.06 kg. All patients who eventually relapsed demonstrated significantly greater weight increase (7.3 kg during the treatment phase. Conclusions The extension of paroxetine maintenance treatment from 12 to 24 months did not seem to further decrease the risk of relapse after

  17. Three-Year Retention Rates of Levetiracetam, Topiramate, and Oxcarbazepine: A Retrospective Hospital-Based Study.

    Science.gov (United States)

    Sunwoo, Jun-Sang; Park, Byeong-Su; Ahn, Seon Jae; Hwang, Sungeun; Park, Chan-Young; Jun, Jin-Sun; Kim, Dong Wook; Lee, Soon-Tae; Jung, Keun-Hwa; Park, Kyung-Il; Chu, Kon; Jung, Ki-Young; Lee, Sang Kun

    We evaluated and compared the 3-year retention rates of levetiracetam (LEV), topiramate (TPM), and oxcarbazepine (OXC) in patients with epilepsy in routine clinical practice. We retrospectively reviewed medical records of patients with epilepsy who were newly prescribed LEV, TPM, or OXC from 2006 to 2010. The retention rates were estimated by the Kaplan-Meier analysis, and independent risk factors for drug discontinuation were analyzed by the Cox regression method. A total of 588 patients were included: LEV (n = 345), TPM (n = 190), and OXC (n = 53). Among them, 82% had focal epilepsy, whereas 14.8% had generalized epilepsy. The 3-year retention rates for LEV, TPM, and OXC, were 81.2%, 78.3%, and 54.7%, respectively. Levetiracetam and TPM had equivalent retention rates, whereas patients remained on OXC for a significantly shorter amount of time (P effects leading to drug withdrawal of OXC (87.5%) was higher than that of LEV (34.4%, P < 0.001) and TPM (52.5%, P = 0.012). The current study suggested that LEV and TPM had comparable retention profiles in the long-term treatment for both focal and generalized epilepsy. Meanwhile, OXC therapy seemed to be relatively less useful because of its poor tolerability.

  18. Psychopathological factors that can influence academic achievement in early adolescence: a three-year prospective study.

    Science.gov (United States)

    Voltas, Núria; Hernández-Martínez, Carmen; Aparicio, Estefania; Arija, Victoria; Canals, Josefa

    2014-12-30

    This three-phase prospective study investigated psychosocial factors predicting or associated with academic achievement. An initial sample of 1,514 school-age children was assessed with screening tools for emotional problems (Screen for Childhood Anxiety and Related Emotional Disorders; Leyton Obsessional Inventory-Child Version; Children's Depression Inventory). The following year, 562 subjects (risk group/without risk group) were re-assessed and attention deficit/hyperactivity disorder (ADHD) was assessed. Two years later, 242 subjects were followed, and their parents informed about their academic achievement. Results showed that early depression (phase 1 B = -.130, p = .001; phase 1 + phase 2 B = -.187, p anxiety symptoms (phase 1 + phase 2 B = -1.721, p = .018), and ADHD were predictors of lower academic achievement (phase 1 + phase 2 B = -3.415, p = .005). However, some anxiety symptoms can improve academic achievement (Social phobia B = .216, p = .018; Generalized anxiety B = .313, p academic achievement. We can conclude that in the transition period to adolescence, school-health professionals and teachers need to consider the emotional issues of students to avoid unwanted academic outcomes.

  19. Three years of distribution of intestinal parasites in an Education and Research Hospital: A retrospective study

    Directory of Open Access Journals (Sweden)

    Bayram Pektaş

    2015-09-01

    Full Text Available Objective: In this study, we aimed to evaluate the patients who applied to various clinics in our hospital with gastrointestinal complaints in terms of intestinal parasites, retrospectively. Methods: Totally 41967 stool samples of patients applied to Parasitology laboratory in Konya Education and Research Hospital in January 2010-December 2012 were investigated under microscope after multiplexing by native lugol and formol ethyl acetate method. Trichrome dying was performed to the suspected samples. The stool samples, in which Entamoeba histolytica /E.dispar cannot be differentiated, were investigated by ELISA method in order to identify adhesin antigens. Results: Intestinal parasite was determined in 2145 (5.11% of 41.967 patients who applied to our laboratory in 3 years. 39.4%, 44.3% and 16.2% of positive patients were 0-15, 16-50 and >50 years old, respectively. Blastocyctis hominis, Entamoeba spp and Giardia intestinalis were found in 59.9%, 25% and 13.7% of the positive samples, respectively. Entamoeba spp and Giardia intestinalis were found most frequently in 0-15 years old patients, while Blastocyctis hominis was found most frequently in 15-49 years old patients. There was a statistically significant difference between these parasites and age groups (p<0.01. The distribution of the positive cases among the years was found as 6.8% in 2010, 5.4% in 2011, 3.3% in 2012 and there was a statistically significant difference between the years (p<0.01. Conclusion: According to our results, the frequency of parasite infection still maintains its importance, although the frequency was decreased compared to previous years. J Clin Exp Invest 2015; 6 (3: 269-273

  20. Adopting a healthy lifestyle when pregnant and obese - an interview study three years after childbirth.

    Science.gov (United States)

    Dencker, Anna; Premberg, Åsa; Olander, Ellinor K; McCourt, Christine; Haby, Karin; Dencker, Sofie; Glantz, Anna; Berg, Marie

    2016-07-30

    Obesity during pregnancy is increasing and is related to life-threatening and ill-health conditions in both mother and child. Initiating and maintaining a healthy lifestyle when pregnant with body mass index (BMI) ≥ 30 kg/m(2) can improve health and decrease risks during pregnancy and of long-term illness for the mother and the child. To minimise gestational weight gain women with BMI ≥ 30 kg/m(2) in early pregnancy were invited to a lifestyle intervention including advice and support on diet and physical activity in Gothenburg, Sweden. The aim of this study was to explore the experiences of women with BMI ≥ 30 kg/m(2) regarding minimising their gestational weight gain, and to assess how health professionals' care approaches are reflected in the women's narratives. Semi-structured interviews were conducted with 17 women who had participated in a lifestyle intervention for women with BMI ≥ 30 kg/m(2) during pregnancy 3 years earlier. The interviews were digitally recorded and transcribed in full. Thematic analysis was used. The meaning of changing lifestyle for minimising weight gain and of the professional's care approaches is described in four themes: the child as the main motivation for making healthy changes; a need to be seen and supported on own terms to establish healthy routines; being able to manage healthy activities and own weight; and need for additional support to maintain a healthy lifestyle. To support women with BMI ≥ 30 kg/m(2) to make healthy lifestyle changes and limit weight gain during pregnancy antenatal health care providers should 1) address women's weight in a non-judgmental way using BMI, and provide accurate and appropriate information about the benefits of limited gestational weight gain; 2) support the woman on her own terms in a collaborative relationship with the midwife; 3) work in partnership to give the woman the tools to self-manage healthy activities and 4) give continued personal support and

  1. From Networks to Time Series

    Science.gov (United States)

    Shimada, Yutaka; Ikeguchi, Tohru; Shigehara, Takaomi

    2012-10-01

    In this Letter, we propose a framework to transform a complex network to a time series. The transformation from complex networks to time series is realized by the classical multidimensional scaling. Applying the transformation method to a model proposed by Watts and Strogatz [Nature (London) 393, 440 (1998)], we show that ring lattices are transformed to periodic time series, small-world networks to noisy periodic time series, and random networks to random time series. We also show that these relationships are analytically held by using the circulant-matrix theory and the perturbation theory of linear operators. The results are generalized to several high-dimensional lattices.

  2. A Study of Wavelet Analysis and Data Extraction from Second-Order Self-Similar Time Series

    Directory of Open Access Journals (Sweden)

    Leopoldo Estrada Vargas

    2013-01-01

    Full Text Available Statistical analysis and synthesis of self-similar discrete time signals are presented. The analysis equation is formally defined through a special family of basis functions of which the simplest case matches the Haar wavelet. The original discrete time series is synthesized without loss by a linear combination of the basis functions after some scaling, displacement, and phase shift. The decomposition is then used to synthesize a new second-order self-similar signal with a different Hurst index than the original. The components are also used to describe the behavior of the estimated mean and variance of self-similar discrete time series. It is shown that the sample mean, although it is unbiased, provides less information about the process mean as its Hurst index is higher. It is also demonstrated that the classical variance estimator is biased and that the widely accepted aggregated variance-based estimator of the Hurst index results biased not due to its nature (which is being unbiased and has minimal variance but to flaws in its implementation. Using the proposed decomposition, the correct estimation of the Variance Plot is described, as well as its close association with the popular Logscale Diagram.

  3. A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models.

    Science.gov (United States)

    BackgroundExposure measurement error in copollutant epidemiologic models has the potential to introduce bias in relative risk (RR) estimates. A simulation study was conducted using empirical data to quantify the impact of correlated measurement errors in time-series analyses of a...

  4. Investigation of Relationship Between Hydrologic Processes of Precipitation, Evaporation and Stream Flow Using Linear Time Series Models (Case study: Western Basins of Lake Urmia

    Directory of Open Access Journals (Sweden)

    M. Moravej

    2016-02-01

    Full Text Available Introduction: Studying the hydrological cycle, especially in large scales such as water catchments, is difficult and complicated despite the fact that the numbers of hydrological components are limited. This complexity rises from complex interactions between hydrological components and environment. Recognition, determination and modeling of all interactive processes are needed to address this issue, but it's not feasible for dealing with practical engineering problems. So, it is more convenient to consider hydrological components as stochastic phenomenon, and use stochastic models for modeling them. Stochastic simulation of time series models related to water resources, particularly hydrologic time series, have been widely used in recent decades in order to solve issues pertaining planning and management of water resource systems. In this study time series models fitted to the precipitation, evaporation and stream flow series separately and the relationships between stream flow and precipitation processes are investigated. In fact, the three mentioned processes should be modeled in parallel to each other in order to acquire a comprehensive vision of hydrological conditions in the region. Moreover, the relationship between the hydrologic processes has been mostly studied with respect to their trends. It is desirable to investigate the relationship between trends of hydrological processes and climate change, while the relationship of the models has not been taken into consideration. The main objective of this study is to investigate the relationship between hydrological processes and their effects on each other and the selected models. Material and Method: In the current study, the four sub-basins of Lake Urmia Basin namely Zolachay (A, Nazloochay (B, Shahrchay (C and Barandoozchay (D were considered. Precipitation, evaporation and stream flow time series were modeled by linear time series. Fundamental assumptions of time series analysis namely

  5. The DYFAMED time-series station: A reference site for environmental studies in the North Western Mediterranean Sea

    International Nuclear Information System (INIS)

    Marty, J.C.; Vescovali, I.; Oubelkheir, K.; Stock, A.; Chiaverini, J.; Pizay, M.D.

    1999-01-01

    The observation site is located in the central part of the Ligurian sea, at about 50 km off Nice, on the Nice Corsica transect. The Ligurian sea is characterised by three different areas. The coastal area is submitted to inputs from coast and from the liguro-provencal current. The frontal zone is delimited by the ligurian current and the central area. This frontal zone isolates the central part of the basin where is located the DYFAMED site. In this central area, the primary production is dependent on inputs of nutrients from deeper waters but also, for a badly evaluated part, on atmospheric inputs of nitrogen and some trace metals particularly during summer. Since 1987, data have been collected on the time series station, in the frame of the Jgofs-France program. Then, the scientific observation service has been officially created by INSU/CNRS in 1995

  6. Parameter estimation methods for gene circuit modeling from time-series mRNA data: a comparative study

    KAUST Repository

    Fan, M.

    2015-03-29

    Parameter estimation is a challenging computational problemin the reverse engineering of biological systems. Because advances in biotechnology have facilitated wide availability of time-series gene expression data, systematic parameter esti- mation of gene circuitmodels fromsuch time-series mRNA data has become an importantmethod for quantitatively dissecting the regulation of gene expression. By focusing on themodeling of gene circuits, we examine here the perform- ance of three types of state-of-the-art parameter estimation methods: population-basedmethods, onlinemethods and model-decomposition-basedmethods. Our results show that certain population-basedmethods are able to generate high- quality parameter solutions. The performance of thesemethods, however, is heavily dependent on the size of the param- eter search space, and their computational requirements substantially increase as the size of the search space increases. In comparison, onlinemethods andmodel decomposition-basedmethods are computationally faster alternatives and are less dependent on the size of the search space. Among other things, our results show that a hybrid approach that augments computationally fastmethods with local search as a subsequent refinement procedure can substantially increase the qual- ity of their parameter estimates to the level on par with the best solution obtained fromthe population-basedmethods whilemaintaining high computational speed. These suggest that such hybridmethods can be a promising alternative to themore commonly used population-basedmethods for parameter estimation of gene circuit models when limited prior knowledge about the underlying regulatorymechanismsmakes the size of the parameter search space vastly large. © The Author 2015. Published by Oxford University Press.

  7. Parameter estimation methods for gene circuit modeling from time-series mRNA data: a comparative study.

    Science.gov (United States)

    Fan, Ming; Kuwahara, Hiroyuki; Wang, Xiaolei; Wang, Suojin; Gao, Xin

    2015-11-01

    Parameter estimation is a challenging computational problem in the reverse engineering of biological systems. Because advances in biotechnology have facilitated wide availability of time-series gene expression data, systematic parameter estimation of gene circuit models from such time-series mRNA data has become an important method for quantitatively dissecting the regulation of gene expression. By focusing on the modeling of gene circuits, we examine here the performance of three types of state-of-the-art parameter estimation methods: population-based methods, online methods and model-decomposition-based methods. Our results show that certain population-based methods are able to generate high-quality parameter solutions. The performance of these methods, however, is heavily dependent on the size of the parameter search space, and their computational requirements substantially increase as the size of the search space increases. In comparison, online methods and model decomposition-based methods are computationally faster alternatives and are less dependent on the size of the search space. Among other things, our results show that a hybrid approach that augments computationally fast methods with local search as a subsequent refinement procedure can substantially increase the quality of their parameter estimates to the level on par with the best solution obtained from the population-based methods while maintaining high computational speed. These suggest that such hybrid methods can be a promising alternative to the more commonly used population-based methods for parameter estimation of gene circuit models when limited prior knowledge about the underlying regulatory mechanisms makes the size of the parameter search space vastly large. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  8. A COMPARATIVE STUDY OF FORECASTING MODELS FOR TREND AND SEASONAL TIME SERIES DOES COMPLEX MODEL ALWAYS YIELD BETTER FORECAST THAN SIMPLE MODELS

    Directory of Open Access Journals (Sweden)

    Suhartono Suhartono

    2005-01-01

    Full Text Available Many business and economic time series are non-stationary time series that contain trend and seasonal variations. Seasonality is a periodic and recurrent pattern caused by factors such as weather, holidays, or repeating promotions. A stochastic trend is often accompanied with the seasonal variations and can have a significant impact on various forecasting methods. In this paper, we will investigate and compare some forecasting methods for modeling time series with both trend and seasonal patterns. These methods are Winter's, Decomposition, Time Series Regression, ARIMA and Neural Networks models. In this empirical research, we study on the effectiveness of the forecasting performance, particularly to answer whether a complex method always give a better forecast than a simpler method. We use a real data, that is airline passenger data. The result shows that the more complex model does not always yield a better result than a simpler one. Additionally, we also find the possibility to do further research especially the use of hybrid model by combining some forecasting method to get better forecast, for example combination between decomposition (as data preprocessing and neural network model.

  9. Time Series with Long Memory

    OpenAIRE

    西埜, 晴久

    2004-01-01

    The paper investigates an application of long-memory processes to economic time series. We show properties of long-memory processes, which are motivated to model a long-memory phenomenon in economic time series. An FARIMA model is described as an example of long-memory model in statistical terms. The paper explains basic limit theorems and estimation methods for long-memory processes in order to apply long-memory models to economic time series.

  10. A Study of Mexican Free-Tailed Bat Chirp Syllables: Bayesian Functional Mixed Models for Nonstationary Acoustic Time Series

    KAUST Repository

    Martinez, Josue G.; Bohn, Kirsten M.; Carroll, Raymond J.; Morris, Jeffrey S.

    2013-01-01

    We describe a new approach to analyze chirp syllables of free-tailed bats from two regions of Texas in which they are predominant: Austin and College Station. Our goal is to characterize any systematic regional differences in the mating chirps and assess whether individual bats have signature chirps. The data are analyzed by modeling spectrograms of the chirps as responses in a Bayesian functional mixed model. Given the variable chirp lengths, we compute the spectrograms on a relative time scale interpretable as the relative chirp position, using a variable window overlap based on chirp length. We use 2D wavelet transforms to capture correlation within the spectrogram in our modeling and obtain adaptive regularization of the estimates and inference for the regions-specific spectrograms. Our model includes random effect spectrograms at the bat level to account for correlation among chirps from the same bat, and to assess relative variability in chirp spectrograms within and between bats. The modeling of spectrograms using functional mixed models is a general approach for the analysis of replicated nonstationary time series, such as our acoustical signals, to relate aspects of the signals to various predictors, while accounting for between-signal structure. This can be done on raw spectrograms when all signals are of the same length, and can be done using spectrograms defined on a relative time scale for signals of variable length in settings where the idea of defining correspondence across signals based on relative position is sensible.

  11. A Study of Mexican Free-Tailed Bat Chirp Syllables: Bayesian Functional Mixed Models for Nonstationary Acoustic Time Series

    KAUST Repository

    Martinez, Josue G.

    2013-06-01

    We describe a new approach to analyze chirp syllables of free-tailed bats from two regions of Texas in which they are predominant: Austin and College Station. Our goal is to characterize any systematic regional differences in the mating chirps and assess whether individual bats have signature chirps. The data are analyzed by modeling spectrograms of the chirps as responses in a Bayesian functional mixed model. Given the variable chirp lengths, we compute the spectrograms on a relative time scale interpretable as the relative chirp position, using a variable window overlap based on chirp length. We use 2D wavelet transforms to capture correlation within the spectrogram in our modeling and obtain adaptive regularization of the estimates and inference for the regions-specific spectrograms. Our model includes random effect spectrograms at the bat level to account for correlation among chirps from the same bat, and to assess relative variability in chirp spectrograms within and between bats. The modeling of spectrograms using functional mixed models is a general approach for the analysis of replicated nonstationary time series, such as our acoustical signals, to relate aspects of the signals to various predictors, while accounting for between-signal structure. This can be done on raw spectrograms when all signals are of the same length, and can be done using spectrograms defined on a relative time scale for signals of variable length in settings where the idea of defining correspondence across signals based on relative position is sensible.

  12. Testing for Stationarity and Nonlinearity of Daily Streamflow Time Series Based on Different Statistical Tests (Case Study: Upstream Basin Rivers of Zarrineh Roud Dam

    Directory of Open Access Journals (Sweden)

    Farshad Fathian

    2017-02-01

    Full Text Available Introduction: Time series models are one of the most important tools for investigating and modeling hydrological processes in order to solve problems related to water resources management. Many hydrological time series shows nonstationary and nonlinear behaviors. One of the important hydrological modeling tasks is determining the existence of nonstationarity and the way through which we can access the stationarity accordingly. On the other hand, streamflow processes are usually considered as nonlinear mechanisms while in many studies linear time series models are used to model streamflow time series. However, it is not clear what kind of nonlinearity is acting underlying the streamflowprocesses and how intensive it is. Materials and Methods: Streamflow time series of 6 hydro-gauge stations located in the upstream basin rivers of ZarrinehRoud dam (located in the southern part of Urmia Lake basin have been considered to investigate stationarity and nonlinearity. All data series used here to startfrom January 1, 1997, and end on December 31, 2011. In this study, stationarity is tested by ADF and KPSS tests and nonlinearity is tested by BDS, Keenan and TLRT tests. The stationarity test is carried out with two methods. Thefirst one method is the augmented Dickey-Fuller (ADF unit root test first proposed by Dickey and Fuller (1979 and modified by Said and Dickey (1984, which examinsthe presence of unit roots in time series.The second onemethod is KPSS test, proposed by Kwiatkowski et al. (1992, which examinesthestationarity around a deterministic trend (trend stationarity and the stationarity around a fixed level (level stationarity. The BDS test (Brock et al., 1996 is a nonparametric method for testing the serial independence and nonlinear structure in time series based on the correlation integral of the series. The null hypothesis is the time series sample comes from an independent identically distributed (i.i.d. process. The alternative hypothesis

  13. An electronic trigger tool to optimise intravenous to oral antibiotic switch: a controlled, interrupted time series study

    Directory of Open Access Journals (Sweden)

    Marvin A. H. Berrevoets

    2017-08-01

    Full Text Available Abstract Background Timely switch from intravenous (iv antibiotics to oral therapy is a key component of antimicrobial stewardship programs in order to improve patient safety, promote early discharge and reduce costs. We have introduced a time-efficient and easily implementable intervention that relies on a computerized trigger tool, which identifies patients who are candidates for an iv to oral antibiotic switch. Methods The intervention was introduced on all internal medicine wards in a teaching hospital. Patients were automatically identified by an electronic trigger tool when parenteral antibiotics were used for >48 h and clinical or pharmacological data did not preclude switch therapy. A weekly educational session was introduced to alert the physicians on the intervention wards. The intervention wards were compared with control wards, which included all other hospital wards. An interrupted time-series analysis was performed to compare the pre-intervention period with the post-intervention period using ‘% of i.v. prescriptions >72 h’ and ‘median duration of iv therapy per prescription’ as outcomes. We performed a detailed prospective evaluation on a subset of 244 prescriptions to evaluate the efficacy and appropriateness of the intervention. Results The number of intravenous prescriptions longer than 72 h was reduced by 19% in the intervention group (n = 1519 (p < 0.01 and the median duration of iv antibiotics was reduced with 0.8 days (p = <0.05. Compared to the control group (n = 4366 the intervention was responsible for an additional decrease of 13% (p < 0.05 in prolonged prescriptions. The detailed prospective evaluation of a subgroup of patients showed that adherence to the electronic reminder was 72%. Conclusions An electronic trigger tool combined with a weekly educational session was effective in reducing the duration of intravenous antimicrobial therapy.

  14. Homogenising time series: beliefs, dogmas and facts

    Science.gov (United States)

    Domonkos, P.

    2011-06-01

    In the recent decades various homogenisation methods have been developed, but the real effects of their application on time series are still not known sufficiently. The ongoing COST action HOME (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As a part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever before to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. Empirical results show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities often have similar statistical characteristics than natural changes caused by climatic variability, thus the pure application of the classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality than in raw time series. Some problems around detecting multiple structures of inhomogeneities, as well as that of time series comparisons within homogenisation procedures are discussed briefly in the study.

  15. Network structure of multivariate time series.

    Science.gov (United States)

    Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

    2015-10-21

    Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

  16. Comparison of the Gen Expression Programming, Nonlinear Time Series and Artificial Neural Network in Estimating the River Daily Flow (Case Study: The Karun River

    Directory of Open Access Journals (Sweden)

    R. Zamani

    2015-06-01

    Full Text Available Today, the daily flow forecasting of rivers is an important issue in hydrology and water resources and thus can be used the results of daily river flow modeling in water resources management, droughts and floods monitoring. In this study, due to the importance of this issue, using nonlinear time series models and artificial intelligence (Artificial Neural Network and Gen Expression Programming, the daily flow modeling has been at the time interval (1981-2012 in the Armand hydrometric station on the Karun River. Armand station upstream basin is one of the most basins in the North Karun basin and includes four sub basins (Vanak, Middle Karun, Beheshtabad and Kohrang.The results of this study shown that artificial intelligence models have superior than nonlinear time series in flow daily simulation in the Karun River. As well as, modeling and comparison of artificial intelligence models showed that the Gen Expression Programming have evaluation criteria better than artificial neural network.

  17. Applied time series analysis and innovative computing

    CERN Document Server

    Ao, Sio-Iong

    2010-01-01

    This text is a systematic, state-of-the-art introduction to the use of innovative computing paradigms as an investigative tool for applications in time series analysis. It includes frontier case studies based on recent research.

  18. Study of Glycemic Variability Through Time Series Analyses (Detrended Fluctuation Analysis and Poincaré Plot) in Children and Adolescents with Type 1 Diabetes.

    Science.gov (United States)

    García Maset, Leonor; González, Lidia Blasco; Furquet, Gonzalo Llop; Suay, Francisco Montes; Marco, Roberto Hernández

    2016-11-01

    Time series analysis provides information on blood glucose dynamics that is unattainable with conventional glycemic variability (GV) indices. To date, no studies have been published on these parameters in pediatric patients with type 1 diabetes. Our aim is to evaluate the relationship between time series analysis and conventional GV indices, and glycosylated hemoglobin (HbA1c) levels. This is a transversal study of 41 children and adolescents with type 1 diabetes. Glucose monitoring was carried out continuously for 72 h to study the following GV indices: standard deviation (SD) of glucose levels (mg/dL), coefficient of variation (%), interquartile range (IQR; mg/dL), mean amplitude of the largest glycemic excursions (MAGE), and continuous overlapping net glycemic action (CONGA). The time series analysis was conducted by means of detrended fluctuation analysis (DFA) and Poincaré plot. Time series parameters (DFA alpha coefficient and elements of the ellipse of the Poincaré plot) correlated well with the more conventional GV indices. Patients were grouped according to the terciles of these indices, to the terciles of eccentricity (1: 12.56-16.98, 2: 16.99-21.91, 3: 21.92-41.03), and to the value of the DFA alpha coefficient (> or ≤1.5). No differences were observed in the HbA1c of patients grouped by GV index criteria; however, significant differences were found in patients grouped by alpha coefficient and eccentricity, not only in terms of HbA1c, but also in SD glucose, IQR, and CONGA index. The loss of complexity in glycemic homeostasis is accompanied by an increase in variability.

  19. Effect of a population-level performance dashboard intervention on maternal-newborn outcomes: an interrupted time series study.

    Science.gov (United States)

    Weiss, Deborah; Dunn, Sandra I; Sprague, Ann E; Fell, Deshayne B; Grimshaw, Jeremy M; Darling, Elizabeth; Graham, Ian D; Harrold, JoAnn; Smith, Graeme N; Peterson, Wendy E; Reszel, Jessica; Lanes, Andrea; Walker, Mark C; Taljaard, Monica

    2018-06-01

    To assess the effect of the Maternal Newborn Dashboard on six key clinical performance indicators in the province of Ontario, Canada. Interrupted time series using population-based data from the provincial birth registry covering a 3-year period before implementation of the Dashboard and 2.5 years after implementation (November 2009 through March 2015). All hospitals in the province of Ontario providing maternal-newborn care (n=94). A hospital-based online audit and feedback programme. Rates of the six performance indicators included in the Dashboard. 2.5 years after implementation, the audit and feedback programme was associated with statistically significant absolute decreases in the rates of episiotomy (decrease of 1.5 per 100 women, 95% CI 0.64 to 2.39), induction for postdates in women who were less than 41 weeks at delivery (decrease of 11.7 per 100 women, 95% CI 7.4 to 16.0), repeat caesarean delivery in low-risk women performed before 39 weeks (decrease of 10.4 per 100 women, 95% CI 9.3 to 11.5) and an absolute increase in the rate of appropriately timed group B streptococcus screening (increase of 2.8 per 100, 95% CI 2.2 to 3.5). The audit and feedback programme did not significantly affect the rates of unsatisfactory newborn screening blood samples or formula supplementation at discharge. No statistically significant effects were observed for the two internal control outcomes or the four external control indicators-in fact, two external control indicators (episiotomy and postdates induction) worsened relative to before implementation. An electronic audit and feedback programme implemented in maternal-newborn hospitals was associated with clinically relevant practice improvements at the provincial level in the majority of targeted indicators. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  20. DNA-based molecular fingerprinting of eukaryotic protists and cyanobacteria contributing to sinking particle flux at the Bermuda Atlantic time-series study

    Science.gov (United States)

    Amacher, Jessica; Neuer, Susanne; Lomas, Michael

    2013-09-01

    We used denaturing gradient gel electrophoresis (DGGE) to examine the protist and cyanobacterial communities in the euphotic zone (0-120 m) and in corresponding 150 m particle interceptor traps at the Bermuda Atlantic Time-series Study (BATS) in a two-year monthly time-series from May 2008 to April 2010. Dinoflagellates were the most commonly detected taxa in both water column and trap samples throughout the time series. Diatom sequences were found only eight times in the water column, and only four times in trap material. Small-sized eukaryotic taxa, including the prasinophyte genera Ostreococcus, Micromonas, and Bathycoccus, were present in trap samples, as were the cyanobacteria Prochlorococcus and Synechococcus. Synechococcus was usually overrepresented in trap material, whereas Prochlorococcus was underrepresented compared to the water column. Both seasonal and temporal variability affected patterns of ribosomal DNA found in sediment traps. The two years of this study were quite different hydrographically, with higher storm activity and the passing of a cyclonic eddy causing unusually deep mixing in winter 2010. This was reflected in the DGGE fingerprints of the water column, which showed greater phylotype richness of eukaryotes and a lesser richness of cyanobacteria in winter of 2010 compared with the winter of 2009. Increases in eukaryotic richness could be traced to increased diversity of prasinophytes and prymnesiophytes. The decrease in cyanobacterial richness was in turn reflected in the trap composition, but the increase in eukaryotes was not, indicating a disproportionate contribution of certain taxa to sinking particle flux.

  1. Time series with tailored nonlinearities

    Science.gov (United States)

    Räth, C.; Laut, I.

    2015-10-01

    It is demonstrated how to generate time series with tailored nonlinearities by inducing well-defined constraints on the Fourier phases. Correlations between the phase information of adjacent phases and (static and dynamic) measures of nonlinearities are established and their origin is explained. By applying a set of simple constraints on the phases of an originally linear and uncorrelated Gaussian time series, the observed scaling behavior of the intensity distribution of empirical time series can be reproduced. The power law character of the intensity distributions being typical for, e.g., turbulence and financial data can thus be explained in terms of phase correlations.

  2. Models for dependent time series

    CERN Document Server

    Tunnicliffe Wilson, Granville; Haywood, John

    2015-01-01

    Models for Dependent Time Series addresses the issues that arise and the methodology that can be applied when the dependence between time series is described and modeled. Whether you work in the economic, physical, or life sciences, the book shows you how to draw meaningful, applicable, and statistically valid conclusions from multivariate (or vector) time series data.The first four chapters discuss the two main pillars of the subject that have been developed over the last 60 years: vector autoregressive modeling and multivariate spectral analysis. These chapters provide the foundational mater

  3. Analysis of Heavy-Tailed Time Series

    DEFF Research Database (Denmark)

    Xie, Xiaolei

    This thesis is about analysis of heavy-tailed time series. We discuss tail properties of real-world equity return series and investigate the possibility that a single tail index is shared by all return series of actively traded equities in a market. Conditions for this hypothesis to be true...... are identified. We study the eigenvalues and eigenvectors of sample covariance and sample auto-covariance matrices of multivariate heavy-tailed time series, and particularly for time series with very high dimensions. Asymptotic approximations of the eigenvalues and eigenvectors of such matrices are found...... and expressed in terms of the parameters of the dependence structure, among others. Furthermore, we study an importance sampling method for estimating rare-event probabilities of multivariate heavy-tailed time series generated by matrix recursion. We show that the proposed algorithm is efficient in the sense...

  4. Application of time series analysis on molecular dynamics simulations of proteins: a study of different conformational spaces by principal component analysis.

    Science.gov (United States)

    Alakent, Burak; Doruker, Pemra; Camurdan, Mehmet C

    2004-09-08

    Time series analysis is applied on the collective coordinates obtained from principal component analysis of independent molecular dynamics simulations of alpha-amylase inhibitor tendamistat and immunity protein of colicin E7 based on the Calpha coordinates history. Even though the principal component directions obtained for each run are considerably different, the dynamics information obtained from these runs are surprisingly similar in terms of time series models and parameters. There are two main differences in the dynamics of the two proteins: the higher density of low frequencies and the larger step sizes for the interminima motions of colicin E7 than those of alpha-amylase inhibitor, which may be attributed to the higher number of residues of colicin E7 and/or the structural differences of the two proteins. The cumulative density function of the low frequencies in each run conforms to the expectations from the normal mode analysis. When different runs of alpha-amylase inhibitor are projected on the same set of eigenvectors, it is found that principal components obtained from a certain conformational region of a protein has a moderate explanation power in other conformational regions and the local minima are similar to a certain extent, while the height of the energy barriers in between the minima significantly change. As a final remark, time series analysis tools are further exploited in this study with the motive of explaining the equilibrium fluctuations of proteins. Copyright 2004 American Institute of Physics

  5. Data Mining Smart Energy Time Series

    Directory of Open Access Journals (Sweden)

    Janina POPEANGA

    2015-07-01

    Full Text Available With the advent of smart metering technology the amount of energy data will increase significantly and utilities industry will have to face another big challenge - to find relationships within time-series data and even more - to analyze such huge numbers of time series to find useful patterns and trends with fast or even real-time response. This study makes a small review of the literature in the field, trying to demonstrate how essential is the application of data mining techniques in the time series to make the best use of this large quantity of data, despite all the difficulties. Also, the most important Time Series Data Mining techniques are presented, highlighting their applicability in the energy domain.

  6. Complex network approach to fractional time series

    Energy Technology Data Exchange (ETDEWEB)

    Manshour, Pouya [Physics Department, Persian Gulf University, Bushehr 75169 (Iran, Islamic Republic of)

    2015-10-15

    In order to extract correlation information inherited in stochastic time series, the visibility graph algorithm has been recently proposed, by which a time series can be mapped onto a complex network. We demonstrate that the visibility algorithm is not an appropriate one to study the correlation aspects of a time series. We then employ the horizontal visibility algorithm, as a much simpler one, to map fractional processes onto complex networks. The degree distributions are shown to have parabolic exponential forms with Hurst dependent fitting parameter. Further, we take into account other topological properties such as maximum eigenvalue of the adjacency matrix and the degree assortativity, and show that such topological quantities can also be used to predict the Hurst exponent, with an exception for anti-persistent fractional Gaussian noises. To solve this problem, we take into account the Spearman correlation coefficient between nodes' degrees and their corresponding data values in the original time series.

  7. Clustering of financial time series

    Science.gov (United States)

    D'Urso, Pierpaolo; Cappelli, Carmela; Di Lallo, Dario; Massari, Riccardo

    2013-05-01

    This paper addresses the topic of classifying financial time series in a fuzzy framework proposing two fuzzy clustering models both based on GARCH models. In general clustering of financial time series, due to their peculiar features, needs the definition of suitable distance measures. At this aim, the first fuzzy clustering model exploits the autoregressive representation of GARCH models and employs, in the framework of a partitioning around medoids algorithm, the classical autoregressive metric. The second fuzzy clustering model, also based on partitioning around medoids algorithm, uses the Caiado distance, a Mahalanobis-like distance, based on estimated GARCH parameters and covariances that takes into account the information about the volatility structure of time series. In order to illustrate the merits of the proposed fuzzy approaches an application to the problem of classifying 29 time series of Euro exchange rates against international currencies is presented and discussed, also comparing the fuzzy models with their crisp version.

  8. Characterizing rainfall of hot arid region by using time-series modeling and sustainability approaches: a case study from Gujarat, India

    Science.gov (United States)

    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

  9. Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

    Science.gov (United States)

    Gao, Feng; DeColstoun, Eric Brown; Ma, Ronghua; Weng, Qihao; Masek, Jeffrey G.; Chen, Jin; Pan, Yaozhong; Song, Conghe

    2012-01-01

    Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived

  10. Multivariate Time Series Decomposition into Oscillation Components.

    Science.gov (United States)

    Matsuda, Takeru; Komaki, Fumiyasu

    2017-08-01

    Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.

  11. Stochastic models for time series

    CERN Document Server

    Doukhan, Paul

    2018-01-01

    This book presents essential tools for modelling non-linear time series. The first part of the book describes the main standard tools of probability and statistics that directly apply to the time series context to obtain a wide range of modelling possibilities. Functional estimation and bootstrap are discussed, and stationarity is reviewed. The second part describes a number of tools from Gaussian chaos and proposes a tour of linear time series models. It goes on to address nonlinearity from polynomial or chaotic models for which explicit expansions are available, then turns to Markov and non-Markov linear models and discusses Bernoulli shifts time series models. Finally, the volume focuses on the limit theory, starting with the ergodic theorem, which is seen as the first step for statistics of time series. It defines the distributional range to obtain generic tools for limit theory under long or short-range dependences (LRD/SRD) and explains examples of LRD behaviours. More general techniques (central limit ...

  12. A three-year prospective longitudinal cohort study of medical students' attitudes toward anatomy teaching and their career aspirations.

    Science.gov (United States)

    Bhangu, Aneel; Boutefnouchet, Tarek; Yong, Xu; Abrahams, Peter; Joplin, Ruth

    2010-01-01

    Today's medical students are faced with numerous learning needs. Continuously developing curricula have reduced time for basic science subjects such as anatomy. This study aimed to determine the students' views on the relevance of anatomy teaching, anatomical knowledge, and the effect these have on their career choices. A Likert scale questionnaire was distributed to second year medical students [response rate 91% (n = 292/320)]. The same questionnaire was subsequently distributed to the cohort three years later when they were final year students [response rate 37% (n = 146/392)]. Students in both the cohorts of study agreed strongly that clinically correlated anatomical teaching was relevant to clinical practice (92% and 86% of second and final year respondents, respectively) and helped them during their clinical placements (73% and 92%, respectively). Only 28% of the second year and 31% of the final year students agreed that their anatomy teaching prepared them to interpret clinical images (P = 0.269). Only 14% of the final year students felt confident in their knowledge of anatomy. Of the final year students, 30% felt that they had enough opportunity to scrub in the operating room. Nearly half of those students who would consider surgery as a career (19%) think that they will eventually become surgeons (11%). This data suggests that modern anatomy curriculum should focus on clinical correlations and clinical image interpretation. Students would value more opportunities to participate in surgeries. Vertical integration of anatomy teaching throughout the full medical course may be useful. Copyright 2010 American Association of Anatomists.

  13. Time Series Analysis of Wheat Futures Reward in China

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Different from the fact that the main researches are focused on single futures contract and lack of the comparison of different periods, this paper described the statistical characteristics of wheat futures reward time series of Zhengzhou Commodity Exchange in recent three years. Besides the basic statistic analysis, the paper used the GARCH and EGARCH model to describe the time series which had the ARCH effect and analyzed the persistence of volatility shocks and the leverage effect. The results showed that compared with that of normal one,wheat futures reward series were abnormality, leptokurtic and thick tail distribution. The study also found that two-part of the reward series had no autocorrelation. Among the six correlative series, three ones presented the ARCH effect. By using of the Auto-regressive Distributed Lag Model, GARCH model and EGARCH model, the paper demonstrates the persistence of volatility shocks and the leverage effect on the wheat futures reward time series. The results reveal that on the one hand, the statistical characteristics of the wheat futures reward are similar to the aboard mature futures market as a whole. But on the other hand, the results reflect some shortages such as the immatureness and the over-control by the government in the Chinese future market.

  14. Three Years Experience of Third Year Undergraduate Medical Students in Different Teaching Learning Methods: A Qualitative Study

    Directory of Open Access Journals (Sweden)

    Ariarathinam Newtonraj

    2017-10-01

    Full Text Available Introduction: India is a second largest populous country producing more than sixty thousand doctors every year. Still in India research on teaching learning methods are subtle. To improve the quality of knowledge and skills of medical students, there is a need to analyse the existing teaching learning methods as well as innovating new methods. Aim: To compare the three years experience of third year MBBS (Bachelor of Medicine and Bachelor of Surgery students in three different teaching learning methods (Tutorials, Integrated Teaching sessions and Routine Lectures. Materials and Methods: Qualitative study was carried out among 60 third year MBBS students in medical college in south India. A semi-structured questionnaire was developed, with the help of literature review and is distributed among 66 students. Six participants excluded due to incomplete information. Questionnaire consisted of totally 16 questions. For the first ten questions answers were captured in Likert scale of one to five (one-poor; five- excellent. Eleventh to sixteenth questions were asked as an open-ended question to mention some positive and negative things about each method. Questions with Likert scale were analysed using Kruskal Wallis H Test and the open ended questions were analysed by thematic analysis. Results: Overall mean rank for Tutorial was 129.03 followed by Integrated Teaching (mean rank 86.33 and Routine Lecture (mean rank 56.14. Students gave better scores for Tutorials in areas such as easily understandable, better attention span and students involvement in the session. Students gave better scoring for Integrated Teaching in areas such as well organized, integration with other departments, ideal usage of audio visual aids and providing detailed information to the students. Drawbacks of Integrated Teaching were failure to attract the students, prolonged sessions (long duration, boring and minimal involvement of students. Lecture classes on the other hand

  15. Experimental Maedi Visna Virus Infection in sheep: a morphological, immunohistochemical and PCR study after three years of infection

    Directory of Open Access Journals (Sweden)

    S Preziuso

    2009-06-01

    Full Text Available A morphological, immunohistochemical and polymerase chain reaction (PCR study was performed on eight ewes experimentally infected with an Italian strain of Maedi-Visna Virus (MVV in order to evaluate the lesions and the viral distribution after three years of infection. At the moment of euthanasia, seven sheep were seropositive for MVV, while one sheep in poor body conditions was seronegative since one year. Lungs, pulmonary lymph nodes, udder, supramammary lymph nodes, carpal joints, the CNS, spleen and bone marrow of the eight infected sheep were collected for histology, for immunohistochemical detection of the MVV core protein p28 and for PCR amplification of a 218 bp viral DNA sequence of the pol region. The most common histological findings consisted of interstitial lymphoproliferative pneumonia and lymphoproliferative mastitis of different severity, while no lesions were observed in the CNS. MVV p28 antigen was immunohistochemically labelled in lungs, udder, pulmonary lymph nodes, spleen and bone marrow but not in the CNS of all the eight infected sheep. A 218 bp sequence of MVV pol region was detected in lung of a seropositive and of the seroconverted negative sheep. The results suggest that (i MVV causes heterogeneous lesions in homogeneously reared ewes, (ii MVV p28 antigen is detectable not only in inflammed target organs, but also in pulmonary lymph nodes, spleen and bone marrow, and (iii immunohistochemistry and PCR are useful methods for Maedi-Visna diagnosis in suspected cases, also when serological tests are negative.

  16. Evaluation of PDQ-8 and its relationship with PDQ-39 in China: a three-year longitudinal study.

    Science.gov (United States)

    Chen, Kui; Yang, Yu-Jie; Liu, Feng-Tao; Li, Da-Ke; Bu, Lu-Lu; Yang, Ke; Wang, Ying; Shen, Bo; Guan, Rong-Yuan; Song, Jie; Wang, Jian; Wu, Jian-Jun

    2017-08-24

    Parkinson's disease is characterized by motor and non-motor symptoms with wide ranging impacts on the health-related quality of life. The 39-item Parkinson's disease Questionnaire (PDQ-39) is the most widely used PD-specific health-related quality-of-life questionnaire. The short-form 8-item Parkinson's disease Questionnaire (PDQ-8) was found to produce results similar to that of the PDQ-39 cross-culturally. However, there is no evaluation of the PDQ-8 in the mainland of China. In this longitudinal study, 283 patients with Parkinson's disease were recruited. The PDQ-39, the PDQ-8 and other scales were administered. Patients attended the clinic once annually for three years to complete the scales. The PDQ-8 was found to have good validity and reliability. There was a strong correlation between the summary indices of the PDQ-8 and the PDQ-39 (r=0.93, P39 well at all follow-up time points (intraclass correlation coefficient: 0.96-0.98). In addition, there was good test-retest reliability of the PDQ-8. The PDQ-8 is a valid and reliable instrument assessing health-related quality of life for PD patients in the mainland of China.

  17. A three year retrospective study on the increasing trend in seroprevalence of dengue infection from southern Odisha, India

    Directory of Open Access Journals (Sweden)

    Sanghamitra Padhi

    2014-01-01

    Full Text Available Background & objectives: In Odisha, several cases of dengue virus infection were detected for the first time in 2010, the importance of dengue as a serious mosquito-borne viral infection was felt only in 2011 with the reporting of many more positive cases. This retrospective three year study was done to find out the seroprevalence of dengue Ig m0 antibody and to know the predominant serotype of dengue virus among the patients suspected to have dengue virus infection in a tertiary care hospital in southern Odisha, India. Methods: Blood samples from clinically suspected dengue cases admitted in the Medicine and Paediatrics departments of a tertiary care hospital were collected. These were processed for detection of dengue specific IgM antibody, carried out by the ELISA method. Dengue IgM antibody positive serum samples were tested for serotypic identification. Results: o0 f the 5102 samples tested, 1074 (21.05 % were positive for dengue IgM. Maximum numbers of cases were found in 2012. Majority (47.86 % of cases were detected in the month of September. The most common affected age group was 11 to 20 yr. DENV1 and DENV2 were the detected serotypes. Interpretation & conclusions: Rapid increase in the dengue cases in 2012 became a public health concern as majority of cases were affecting the young adolescents. Most of the cases were reported in post-monsoon period indicating a need for acceleration of vector control programmes prior to arrival of monsoon.

  18. Performance Evaluation of Linear (ARMA and Threshold Nonlinear (TAR Time Series Models in Daily River Flow Modeling (Case Study: Upstream Basin Rivers of Zarrineh Roud Dam

    Directory of Open Access Journals (Sweden)

    Farshad Fathian

    2017-01-01

    Full Text Available Introduction: Time series models are generally categorized as a data-driven method or mathematically-based method. These models are known as one of the most important tools in modeling and forecasting of hydrological processes, which are used to design and scientific management of water resources projects. On the other hand, a better understanding of the river flow process is vital for appropriate streamflow modeling and forecasting. One of the main concerns of hydrological time series modeling is whether the hydrologic variable is governed by the linear or nonlinear models through time. Although the linear time series models have been widely applied in hydrology research, there has been some recent increasing interest in the application of nonlinear time series approaches. The threshold autoregressive (TAR method is frequently applied in modeling the mean (first order moment of financial and economic time series. Thise type of the model has not received considerable attention yet from the hydrological community. The main purposes of this paper are to analyze and to discuss stochastic modeling of daily river flow time series of the study area using linear (such as ARMA: autoregressive integrated moving average and non-linear (such as two- and three- regime TAR models. Material and Methods: The study area has constituted itself of four sub-basins namely, Saghez Chai, Jighato Chai, Khorkhoreh Chai and Sarogh Chai from west to east, respectively, which discharge water into the Zarrineh Roud dam reservoir. River flow time series of 6 hydro-gauge stations located on upstream basin rivers of Zarrineh Roud dam (located in the southern part of Urmia Lake basin were considered to model purposes. All the data series used here to start from January 1, 1997, and ends until December 31, 2011. In this study, the daily river flow data from January 01 1997 to December 31 2009 (13 years were chosen for calibration and data for January 01 2010 to December 31 2011

  19. Atmospheric Pressure and Abdominal Aortic Aneurysm Rupture : Results from a Time Series Analysis and Case-Crossover Study

    NARCIS (Netherlands)

    Penning De Vries, Bas B.L.; Kolkert, Joé L.P.; Meerwaldt, Robbert; Groenwold, Rolf H.H.

    2017-01-01

    Background: Associations between atmospheric pressure and abdominal aortic aneurysm (AAA) rupture risk have been reported, but empirical evidence is inconclusive and largely derived from studies that did not account for possible nonlinearity, seasonality, and confounding by temperature. Methods:

  20. Effects of Air Pollution on Public and Private Health Expenditures in Iran: A Time Series Study (1972-2014).

    Science.gov (United States)

    Raeissi, Pouran; Harati-Khalilabad, Touraj; Rezapour, Aziz; Hashemi, Seyed Yaser; Mousavi, Abdoreza; Khodabakhshzadeh, Saeed

    2018-05-01

    Environmental pollution is a negative consequence of the development process, and many countries are grappling with this phenomenon. As a developing country, Iran is not exempt from this rule, and Iran pays huge expenditures for the consequences of pollution. The aim of this study was to analyze the long- and short-run impact of air pollution, along with other health indicators, on private and public health expenditures. This study was an applied and developmental study. Autoregressive distributed lag estimating models were used for the period of 1972 to 2014. In order to determine the co-integration between health expenditures and the infant mortality rate, fertility rate, per capita income, and pollution, we used the Wald test in Microfit version 4.1. We then used Eviews version 8 to evaluate the stationarity of the variables and to estimate the long- and short-run relationships. Long-run air pollution had a positive and significant effect on health expenditures, so that a 1.00% increase in the index of carbon dioxide led to an increase of 3.32% and 1.16% in public and private health expenditures, respectively. Air pollution also had a greater impact on health expenditures in the long term than in the short term. The findings of this study indicate that among the factors affecting health expenditures, environmental quality and contaminants played the most important role. Therefore, in order to reduce the financial burden of health expenditures in Iran, it is essential to reduce air pollution by enacting and implementing laws that protect the environment.

  1. Trend Analysis of Soil Salinity in Different Land Cover Types Using Landsat Time Series Data (case Study Bakhtegan Salt Lake)

    Science.gov (United States)

    Taghadosi, M. M.; Hasanlou, M.

    2017-09-01

    Soil salinity is one of the main causes of desertification and land degradation which has negative impacts on soil fertility and crop productivity. Monitoring salt affected areas and assessing land cover changes, which caused by salinization, can be an effective approach to rehabilitate saline soils and prevent further salinization of agricultural fields. Using potential of satellite imagery taken over time along with remote sensing techniques, makes it possible to determine salinity changes at regional scales. This study deals with monitoring salinity changes and trend of the expansion in different land cover types of Bakhtegan Salt Lake district during the last two decades using multi-temporal Landsat images. For this purpose, per-pixel trend analysis of soil salinity during years 2000 to 2016 was performed and slope index maps of the best salinity indicators were generated for each pixel in the scene. The results of this study revealed that vegetation indices (GDVI and EVI) and also salinity indices (SI-1 and SI-3) have great potential to assess soil salinity trends in vegetation and bare soil lands respectively due to more sensitivity to salt features over years of study. In addition, images of May had the best performance to highlight changes in pixels among different months of the year. A comparative analysis of different slope index maps shows that more than 76% of vegetated areas have experienced negative trends during 17 years, of which about 34% are moderately and highly saline. This percent is increased to 92% for bare soil lands and 29% of salt affected soils had severe salinization. It can be concluded that the areas, which are close to the lake, are more affected by salinity and salts from the lake were brought into the soil which will lead to loss of soil productivity ultimately.

  2. Modeling trends of health and health related indicators in Ethiopia (1995-2008: a time-series study

    Directory of Open Access Journals (Sweden)

    Nigatu Tilahun H

    2009-12-01

    Full Text Available Abstract Background The Federal Ministry of Health of Ethiopia has been publishing Health and Health related indicators of the country annually since 1987 E.C. These indicators have been of high importance in indicating the status of health in the country in those years. However, the trends/patterns of these indicators and the factors related to the trends have not yet been investigated in a systematic manner. In addition, there were minimal efforts to develop a model for predicting future values of Health and Health related indicators based on the current trend. Objectives The overall aim of this study was to analyze trends of and develop model for prediction of Health and Health related indicators. More specifically, it described the trends of Health and Health related indicators, identified determinants of mortality and morbidity indicators and developed model for predicting future values of MDG indicators. Methods This study was conducted on Health and Health related indicators of Ethiopia from the year 1987 E.C to 2000 E.C. Key indicators of Mortality and Morbidity, Health service coverage, Health systems resources, Demographic and socio-economic, and Risk factor indicators were extracted and analyzed. The trends in these indicators were established using trend analysis techniques. The determinants of the established trends were identified using ARIMA models in STATA. The trend-line equations were then used to predict future values of the indicators. Results Among the mortality indicators considered in this study, it was only Maternal Mortality Ratio that showed statistically significant decrement within the study period. The trends of Total Fertility Rate, physician per 100,000 population, skilled birth attendance and postnatal care coverage were found to have significant association with Maternal Mortality Ratio trend. There was a reversal of malaria parasite prevalence in 1999 E.C from Plasmodium Falciparum to Plasmodium Vivax. Based on

  3. Integer-valued time series

    NARCIS (Netherlands)

    van den Akker, R.

    2007-01-01

    This thesis adresses statistical problems in econometrics. The first part contributes statistical methodology for nonnegative integer-valued time series. The second part of this thesis discusses semiparametric estimation in copula models and develops semiparametric lower bounds for a large class of

  4. Extreme value modeling for the analysis and prediction of time series of extreme tropospheric ozone levels: a case study.

    Science.gov (United States)

    Escarela, Gabriel

    2012-06-01

    The occurrence of high concentrations of tropospheric ozone is considered as one of the most important issues of air management programs. The prediction of dangerous ozone levels for the public health and the environment, along with the assessment of air quality control programs aimed at reducing their severity, is of considerable interest to the scientific community and to policy makers. The chemical mechanisms of tropospheric ozone formation are complex, and highly variable meteorological conditions contribute additionally to difficulties in accurate study and prediction of high levels of ozone. Statistical methods offer an effective approach to understand the problem and eventually improve the ability to predict maximum levels of ozone. In this paper an extreme value model is developed to study data sets that consist of periodically collected maxima of tropospheric ozone concentrations and meteorological variables. The methods are applied to daily tropospheric ozone maxima in Guadalajara City, Mexico, for the period January 1997 to December 2006. The model adjusts the daily rate of change in ozone for concurrent impacts of seasonality and present and past meteorological conditions, which include surface temperature, wind speed, wind direction, relative humidity, and ozone. The results indicate that trend, annual effects, and key meteorological variables along with some interactions explain the variation in daily ozone maxima. Prediction performance assessments yield reasonably good results.

  5. Association between Ambient Air Pollution and Hospital Emergency Admissions for Respiratory and Cardiovascular Diseases in Beijing: a Time Series Study.

    Science.gov (United States)

    Zhang, Ying; Wang, Shi Gong; Ma, Yu Xia; Shang, Ke Zheng; Cheng, Yi Fan; Li, Xu; Ning, Gui Cai; Zhao, Wen Jing; Li, Nai Rong

    2015-05-01

    To investigate the association between ambient air pollution and hospital emergency admissions in Beijing. In this study, a semi-parametric generalized additive model (GAM) was used to evaluate the specific influences of air pollutants (PM10, SO2, and NO2) on hospital emergency admissions with different lag structures from 2009 to 2011, the sex and age specific influences of air pollution and the modifying effect of seasons on air pollution to analyze the possible interaction. It was found that a 10 μg/m3 increase in concentration of PM10 at lag 03 day, SO2 and NO2 at lag 0 day were associated with an increase of 0.88%, 0.76%, and 1.82% respectively in overall emergency admissions. A 10 μg/m3 increase in concentration of PM10, SO2 and NO2 at lag 5 day were associated with an increase of 1.39%, 1.56%, and 1.18% respectively in cardiovascular disease emergency admissions. For lag 02, a 10 μg/m3 increase in concentration of PM10, SO2 and NO2 were associated with 1.72%, 1.34%, and 2.57% increases respectively in respiratory disease emergency admissions. This study further confirmed that short-term exposure to ambient air pollution was associated with increased risk of hospital emergency admissions in Beijing. Copyright © 2015 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.

  6. A Time Series Study of Lophelia pertusa and Reef Megafauna Responses to Drill Cuttings Exposure on the Norwegian Margin.

    Directory of Open Access Journals (Sweden)

    Autun Purser

    Full Text Available As hotspots of local biodiversity in the deep sea, preservation of cold-water coral reef communities is of great importance. In European waters the most extensive reefs are found at depths of 300 - 500 m on the continental margin. In Norwegian waters many of these reefs are located in areas of interest for oil and gas exploration and production. In this study drilling was carried out in the Morvin drill field in proximity to a number of small Lophelia pertusa coral reefs (closest reefs 100 m upstream and 350 m downstream of point of waste drill material release. In a novel monitoring study, ROV video surveys of 9 reefs were conducted prior, during, immediately after and >1 year after drilling operations. Behavior of coral polyps inhabiting reefs exposed to differing concentrations of drill cuttings and drilling fluids (waste drilling material were compared. Levels of expected exposure to these waste materials were determined for each reef by modelling drill cutting transport following release, using accurate in-situ hydrodynamic data collected during the drilling period and drill cutting discharge data as parameters of a dispersal model. The presence / absence of associate reef species (Acesta excavata, Paragorgia arborea and Primnoa resedaeformis were also determined from each survey video. There were no significant differences in Lophelia pertusa polyp behavior in corals modelled to have been exposed to pulses of >25 ppm drill cutting material and those modelled to be exposed to negligible concentrations of material. From the video data collected, there were no observed degradations of reef structure over time, nor reductions of associate fauna abundance, regardless of modelled exposure concentration at any of the surveyed reefs. This study focused exclusively on adult fauna, and did not assess the potential hazard posed by waste drilling material to coral or other larvae. Video data was collected by various ROV's, using different camera and

  7. Time Series Analysis of Soil Radon Data Using Multiple Linear Regression and Artificial Neural Network in Seismic Precursory Studies

    Science.gov (United States)

    Singh, S.; Jaishi, H. P.; Tiwari, R. P.; Tiwari, R. C.

    2017-07-01

    This paper reports the analysis of soil radon data recorded in the seismic zone-V, located in the northeastern part of India (latitude 23.73N, longitude 92.73E). Continuous measurements of soil-gas emission along Chite fault in Mizoram (India) were carried out with the replacement of solid-state nuclear track detectors at weekly interval. The present study was done for the period from March 2013 to May 2015 using LR-115 Type II detectors, manufactured by Kodak Pathe, France. In order to reduce the influence of meteorological parameters, statistical analysis tools such as multiple linear regression and artificial neural network have been used. Decrease in radon concentration was recorded prior to some earthquakes that occurred during the observation period. Some false anomalies were also recorded which may be attributed to the ongoing crustal deformation which was not major enough to produce an earthquake.

  8. What tools are useful for monitoring endemic diseases? A simulation study based on different time-series components

    DEFF Research Database (Denmark)

    Lopes Antunes, Ana Carolina; Jensen, D; Hisham Beshara Halasa, Tariq

    2017-01-01

    Control and eradication programs play an important role in disease monitoring and surveillance. It is important to follow up on implemented strategies to reduce and/or eliminate a specific disease. The objectives of this study were to investigate the performance of different detection methods......, including methods commonly used in biosurveillance as well as state space models, for monitoring the effect of endemic disease control and eradication programs. We simulated 16 different scenarios of changes in disease sero-prevalence, inspired by real-world data from the Danish PRRS (Porcine Reproductive...... and Respiratory Syndrome) monitoring program. The changes included increases, decreases and/or constant sero-prevalence levels in different combinations. Two state space models were used to model the simulated data and different monitoring methods, such as univariate process control algorithms (UPCA...

  9. Utilizing an Adaptive Grey Model for Short-Term Time Series Forecasting: A Case Study of Wafer-Level Packaging

    Directory of Open Access Journals (Sweden)

    Che-Jung Chang

    2013-01-01

    Full Text Available The wafer-level packaging process is an important technology used in semiconductor manufacturing, and how to effectively control this manufacturing system is thus an important issue for packaging firms. One way to aid in this process is to use a forecasting tool. However, the number of observations collected in the early stages of this process is usually too few to use with traditional forecasting techniques, and thus inaccurate results are obtained. One potential solution to this problem is the use of grey system theory, with its feature of small dataset modeling. This study thus uses the AGM(1,1 grey model to solve the problem of forecasting in the pilot run stage of the packaging process. The experimental results show that the grey approach is an appropriate and effective forecasting tool for use with small datasets and that it can be applied to improve the wafer-level packaging process.

  10. Temporal change in deep-sea benthic ecosystems: a review of the evidence from recent time-series studies.

    Science.gov (United States)

    Glover, A G; Gooday, A J; Bailey, D M; Billett, D S M; Chevaldonné, P; Colaço, A; Copley, J; Cuvelier, D; Desbruyères, D; Kalogeropoulou, V; Klages, M; Lampadariou, N; Lejeusne, C; Mestre, N C; Paterson, G L J; Perez, T; Ruhl, H; Sarrazin, J; Soltwedel, T; Soto, E H; Thatje, S; Tselepides, A; Van Gaever, S; Vanreusel, A

    2010-01-01

    Societal concerns over the potential impacts of recent global change have prompted renewed interest in the long-term ecological monitoring of large ecosystems. The deep sea is the largest ecosystem on the planet, the least accessible, and perhaps the least understood. Nevertheless, deep-sea data collected over the last few decades are now being synthesised with a view to both measuring global change and predicting the future impacts of further rises in atmospheric carbon dioxide concentrations. For many years, it was assumed by many that the deep sea is a stable habitat, buffered from short-term changes in the atmosphere or upper ocean. However, recent studies suggest that deep-seafloor ecosystems may respond relatively quickly to seasonal, inter-annual and decadal-scale shifts in upper-ocean variables. In this review, we assess the evidence for these long-term (i.e. inter-annual to decadal-scale) changes both in biologically driven, sedimented, deep-sea ecosystems (e.g. abyssal plains) and in chemosynthetic ecosystems that are partially geologically driven, such as hydrothermal vents and cold seeps. We have identified 11 deep-sea sedimented ecosystems for which published analyses of long-term biological data exist. At three of these, we have found evidence for a progressive trend that could be potentially linked to recent climate change, although the evidence is not conclusive. At the other sites, we have concluded that the changes were either not significant, or were stochastically variable without being clearly linked to climate change or climate variability indices. For chemosynthetic ecosystems, we have identified 14 sites for which there are some published long-term data. Data for temporal changes at chemosynthetic ecosystems are scarce, with few sites being subjected to repeated visits. However, the limited evidence from hydrothermal vents suggests that at fast-spreading centres such as the East Pacific Rise, vent communities are impacted on decadal scales

  11. Analyzing Seasonal Variations in Suicide With Fourier Poisson Time-Series Regression: A Registry-Based Study From Norway, 1969-2007.

    Science.gov (United States)

    Bramness, Jørgen G; Walby, Fredrik A; Morken, Gunnar; Røislien, Jo

    2015-08-01

    Seasonal variation in the number of suicides has long been acknowledged. It has been suggested that this seasonality has declined in recent years, but studies have generally used statistical methods incapable of confirming this. We examined all suicides occurring in Norway during 1969-2007 (more than 20,000 suicides in total) to establish whether seasonality decreased over time. Fitting of additive Fourier Poisson time-series regression models allowed for formal testing of a possible linear decrease in seasonality, or a reduction at a specific point in time, while adjusting for a possible smooth nonlinear long-term change without having to categorize time into discrete yearly units. The models were compared using Akaike's Information Criterion and analysis of variance. A model with a seasonal pattern was significantly superior to a model without one. There was a reduction in seasonality during the period. Both the model assuming a linear decrease in seasonality and the model assuming a change at a specific point in time were both superior to a model assuming constant seasonality, thus confirming by formal statistical testing that the magnitude of the seasonality in suicides has diminished. The additive Fourier Poisson time-series regression model would also be useful for studying other temporal phenomena with seasonal components. © The Author 2015. 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.

  12. Epidemiological characterization of Acinetobacter baumannii bloodstream isolates from a Chinese Burn Institute: A three-year study.

    Science.gov (United States)

    Huang, Guangtao; Yin, Supeng; Xiang, Lijuan; Gong, Yali; Sun, Kedai; Luo, Xiaoqiang; Zhang, Cheng; Yang, Zichen; Deng, Liuyang; Jiang, Bei; Jin, Shouguang; Chen, Jing; Peng, Yizhi

    2016-11-01

    Acinetobacter baumannii infection is a serious threat to burn patients. Bacteremia due to A. baumannii is becoming the most common cause of mortality following burn. However, the epidemiology of A. baumannii causing burn-related bloodstream infections has rarely been reported. We retrospectively collected 81 A. baumannii isolates from the bloodstream of burn patients over a three-year period. Antibiotic susceptibility tests, the prevalence of antibiotic-resistant genes and sequence typing (ST) were conducted to characterize these strains. Most of the isolates showed an extensive drug-resistant phenotype. The resistance frequencies to imipenem and meropenem were 94% and 91%, respectively. The blaOXA-23-like gene, AmpC, IS-AmpC, PER and SIM are the five most prevalent resistant genes, and their prevalence rates are 93% (75/81), 86% (70/81), 73% (59/81), 73% (59/81) and 52% (42/81), respectively. The 81 isolates were grouped into 10 known and 18 unknown ST types, with ST368 (38%) being the most prevalent. Except for ST457 and four new types (STn2, STn6, STn11 and STn14), the remaining 23 ST types belonged to one clonal complex 92, which is most common among clinical isolate in China. The above results indicated that ST368 isolates possessing both the blaOXA-23-like gene and ampC gene were the main culprits of the increasing nosocomial A. baumannii infection in this study. More attention should be paid to monitoring the molecular epidemiology of A. baumannii isolates from burn patients to prevent further distribution. Such information may help clinicians with therapeutic decisions and infection control in the Burns Institute. Copyright © 2016. Published by Elsevier Ltd.

  13. A Time-Series Study of the Effect of Air Pollution on Outpatient Visits for Acne Vulgaris in Beijing.

    Science.gov (United States)

    Liu, Wei; Pan, Xiaochuan; Vierkötter, Andrea; Guo, Qun; Wang, Xuying; Wang, Qiaowei; Seité, Sophie; Moyal, Dominique; Schikowski, Tamara; Krutmann, Jean

    2018-01-01

    There is increasing evidence that exposure to air pollutants, including particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), and sulfur dioxide (SO2), might aggravate preexisting skin diseases such as eczema and urticaria. Here we investigated if a possible link exists between air pollution and acne vulgaris. We assessed the association between ambient air pollutant concentrations and the number of visits of patients for acne vulgaris to a dermatological outpatient clinic in Beijing, China, from April 1, 2012 to April 30, 2014. In this time period, 59,325 outpatient visits were recorded because of acne vulgaris. Daily air pollution parameters for PM10, PM2.5, SO2, and NO2 were obtained from the Beijing Municipal Environmental Monitoring Center. Increased concentrations of ambient PM2.5, PM10, and NO2 were significantly associated with increased numbers of outpatient visits for acne vulgaris over the 2 years. These effects could be observed for NO2 in a single-pollutant model and for PM2.5, PM10, and NO2 in 2-pollutant models, which are closer to real-life exposure. Of note, these effects were specific because they were not observed for increased SO2 concentrations, which even showed negative correlations in all test models. This study provides indirect evidence for a link between acne vulgaris and air pollution. © 2018 S. Karger AG, Basel.

  14. Impact of a health safety warning and prior authorisation on the use of piroxicam: a time-series study.

    Science.gov (United States)

    Carracedo-Martínez, Eduardo; Pia-Morandeira, Agustin; Figueiras, Adolfo

    2012-03-01

    The aim of this study was to assess the quantitative changes in systemic use of piroxicam after the issue of a health safety warning about its risks and the subsequent implementation of prior authorisation. We determined the number of monthly daily defined doses/1000 inhabitants/day (DHDs) of piroxicam in the period 2005-2008 in a health area in Spain. The data were analysed graphically, and the impact of the safety warning and introduction of prior authorisation were estimated by using segmented regression analysis. The graph showed that the number of DHDs of piroxicam was stable both before and after the health safety warning but registered a very marked decrease after implementation of prior authorisation, after which DHDs of piroxicam remained stable at a 98% inferior level compared with previous to prior authorisation. Segmented regression analysis showed no statistically significant immediate jump in piroxicam utilisation after the safety warning nor a change in the slope afterwards, but it did show a significant immediate jump after prior authorisation. Population exposure to systemic piroxicam remained unaffected by a previous health safety warning but declined sharply after the introduction of prior authorisation. Copyright © 2012 John Wiley & Sons, Ltd.

  15. Estimating spatially distributed soil texture using time series of thermal remote sensing - a case study in central Europe

    Science.gov (United States)

    Müller, Benjamin; Bernhardt, Matthias; Jackisch, Conrad; Schulz, Karsten

    2016-09-01

    For understanding water and solute transport processes, knowledge about the respective hydraulic properties is necessary. Commonly, hydraulic parameters are estimated via pedo-transfer functions using soil texture data to avoid cost-intensive measurements of hydraulic parameters in the laboratory. Therefore, current soil texture information is only available at a coarse spatial resolution of 250 to 1000 m. Here, a method is presented to derive high-resolution (15 m) spatial topsoil texture patterns for the meso-scale Attert catchment (Luxembourg, 288 km2) from 28 images of ASTER (advanced spaceborne thermal emission and reflection radiometer) thermal remote sensing. A principle component analysis of the images reveals the most dominant thermal patterns (principle components, PCs) that are related to 212 fractional soil texture samples. Within a multiple linear regression framework, distributed soil texture information is estimated and related uncertainties are assessed. An overall root mean squared error (RMSE) of 12.7 percentage points (pp) lies well within and even below the range of recent studies on soil texture estimation, while requiring sparser sample setups and a less diverse set of basic spatial input. This approach will improve the generation of spatially distributed topsoil maps, particularly for hydrologic modeling purposes, and will expand the usage of thermal remote sensing products.

  16. SNOW DEPTH ESTIMATION USING TIME SERIES PASSIVE MICROWAVE IMAGERY VIA GENETICALLY SUPPORT VECTOR REGRESSION (CASE STUDY URMIA LAKE BASIN

    Directory of Open Access Journals (Sweden)

    N. Zahir

    2015-12-01

    Full Text Available Lake Urmia is one of the most important ecosystems of the country which is on the verge of elimination. Many factors contribute to this crisis among them is the precipitation, paly important roll. Precipitation has many forms one of them is in the form of snow. The snow on Sahand Mountain is one of the main and important sources of the Lake Urmia’s water. Snow Depth (SD is vital parameters for estimating water balance for future year. In this regards, this study is focused on SD parameter using Special Sensor Microwave/Imager (SSM/I instruments on board the Defence Meteorological Satellite Program (DMSP F16. The usual statistical methods for retrieving SD include linear and non-linear ones. These methods used least square procedure to estimate SD model. Recently, kernel base methods widely used for modelling statistical problem. From these methods, the support vector regression (SVR is achieved the high performance for modelling the statistical problem. Examination of the obtained data shows the existence of outlier in them. For omitting these outliers, wavelet denoising method is applied. After the omission of the outliers it is needed to select the optimum bands and parameters for SVR. To overcome these issues, feature selection methods have shown a direct effect on improving the regression performance. We used genetic algorithm (GA for selecting suitable features of the SSMI bands in order to estimate SD model. The results for the training and testing data in Sahand mountain is [R²_TEST=0.9049 and RMSE= 6.9654] that show the high SVR performance.

  17. Low cost monitoring from space using Landsat TM time series and open source technologies: the case study of Iguazu park

    Science.gov (United States)

    Nole, Gabriele; Lasaponara, Rosa

    2015-04-01

    Up to nowadays, satellite data have become increasingly available, thus offering a low cost or even free of charge unique tool, with a great potential for operational monitoring of vegetation cover, quantitative assessment of urban expansion and urban sprawl, as well as for monitoring of land use changes and soil consumption. This growing observational capacity has also highlighted the need for research efforts aimed at exploring the potential offered by data processing methods and algorithms, in order to exploit as much as possible this invaluable space-based data source. The work herein presented concerns an application study on the monitoring of vegetation cover and urban sprawl conducted with the use of satellite Landsat TM data. The selected test site is the Iguazu park highly significant, being it one of the most threatened global conservation priorities (http://whc.unesco.org/en/list/303/). In order to produce synthetic maps of the investigated areas to monitor the status of vegetation and ongoing subtle changes, satellite Landsat TM data images were classified using two automatic classifiers, Maximum Likelihood (MLC) and Support Vector Machines (SVMs) applied by changing setting parameters, with the aim to compare their respective performances in terms of robustness, speed and accuracy. All process steps have been developed integrating Geographical Information System and Remote Sensing, and adopting free and open source software. Results pointed out that the SVM classifier with RBF kernel was generally the best choice (with accuracy higher than 90%) among all the configurations compared, and the use of multiple bands globally improves classification. One of the critical elements found in the case of monitoring of urban area expansion is given by the presence of urban garden mixed with urban fabric. The use of different configurations for the SVMs, i.e. different kernels and values of the setting parameters, allowed us to calibrate the classifier also to

  18. Time series modeling in traffic safety research.

    Science.gov (United States)

    Lavrenz, Steven M; Vlahogianni, Eleni I; Gkritza, Konstantina; Ke, Yue

    2018-08-01

    The use of statistical models for analyzing traffic safety (crash) data has been well-established. However, time series techniques have traditionally been underrepresented in the corresponding literature, due to challenges in data collection, along with a limited knowledge of proper methodology. In recent years, new types of high-resolution traffic safety data, especially in measuring driver behavior, have made time series modeling techniques an increasingly salient topic of study. Yet there remains a dearth of information to guide analysts in their use. This paper provides an overview of the state of the art in using time series models in traffic safety research, and discusses some of the fundamental techniques and considerations in classic time series modeling. It also presents ongoing and future opportunities for expanding the use of time series models, and explores newer modeling techniques, including computational intelligence models, which hold promise in effectively handling ever-larger data sets. The information contained herein is meant to guide safety researchers in understanding this broad area of transportation data analysis, and provide a framework for understanding safety trends that can influence policy-making. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. A Simulation-Based Study on the Comparison of Statistical and Time Series Forecasting Methods for Early Detection of Infectious Disease Outbreaks.

    Science.gov (United States)

    Yang, Eunjoo; Park, Hyun Woo; Choi, Yeon Hwa; Kim, Jusim; Munkhdalai, Lkhagvadorj; Musa, Ibrahim; Ryu, Keun Ho

    2018-05-11

    Early detection of infectious disease outbreaks is one of the important and significant issues in syndromic surveillance systems. It helps to provide a rapid epidemiological response and reduce morbidity and mortality. In order to upgrade the current system at the Korea Centers for Disease Control and Prevention (KCDC), a comparative study of state-of-the-art techniques is required. We compared four different temporal outbreak detection algorithms: the CUmulative SUM (CUSUM), the Early Aberration Reporting System (EARS), the autoregressive integrated moving average (ARIMA), and the Holt-Winters algorithm. The comparison was performed based on not only 42 different time series generated taking into account trends, seasonality, and randomly occurring outbreaks, but also real-world daily and weekly data related to diarrhea infection. The algorithms were evaluated using different metrics. These were namely, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1 score, symmetric mean absolute percent error (sMAPE), root-mean-square error (RMSE), and mean absolute deviation (MAD). Although the comparison results showed better performance for the EARS C3 method with respect to the other algorithms, despite the characteristics of the underlying time series data, Holt⁻Winters showed better performance when the baseline frequency and the dispersion parameter values were both less than 1.5 and 2, respectively.

  20. Statistical process control: A feasibility study of the application of time-series measurement in early neurorehabilitation after acquired brain injury.

    Science.gov (United States)

    Markovic, Gabriela; Schult, Marie-Louise; Bartfai, Aniko; Elg, Mattias

    2017-01-31

    Progress in early cognitive recovery after acquired brain injury is uneven and unpredictable, and thus the evaluation of rehabilitation is complex. The use of time-series measurements is susceptible to statistical change due to process variation. To evaluate the feasibility of using a time-series method, statistical process control, in early cognitive rehabilitation. Participants were 27 patients with acquired brain injury undergoing interdisciplinary rehabilitation of attention within 4 months post-injury. The outcome measure, the Paced Auditory Serial Addition Test, was analysed using statistical process control. Statistical process control identifies if and when change occurs in the process according to 3 patterns: rapid, steady or stationary performers. The statistical process control method was adjusted, in terms of constructing the baseline and the total number of measurement points, in order to measure a process in change. Statistical process control methodology is feasible for use in early cognitive rehabilitation, since it provides information about change in a process, thus enabling adjustment of the individual treatment response. Together with the results indicating discernible subgroups that respond differently to rehabilitation, statistical process control could be a valid tool in clinical decision-making. This study is a starting-point in understanding the rehabilitation process using a real-time-measurements approach.

  1. Clinical and epidemiological rounds. Time series

    Directory of Open Access Journals (Sweden)

    León-Álvarez, Alba Luz

    2016-07-01

    Full Text Available Analysis of time series is a technique that implicates the study of individuals or groups observed in successive moments in time. This type of analysis allows the study of potential causal relationships between different variables that change over time and relate to each other. It is the most important technique to make inferences about the future, predicting, on the basis or what has happened in the past and it is applied in different disciplines of knowledge. Here we discuss different components of time series, the analysis technique and specific examples in health research.

  2. Time Series Observations in the North Indian Ocean

    Digital Repository Service at National Institute of Oceanography (India)

    Shenoy, D.M.; Naik, H.; Kurian, S.; Naqvi, S.W.A.; Khare, N.

    Ocean and the ongoing time series study (Candolim Time Series; CaTS) off Goa. In addition, this article also focuses on the new time series initiative in the Arabian Sea and the Bay of Bengal under Sustained Indian Ocean Biogeochemistry and Ecosystem...

  3. Modeling of Volatility with Non-linear Time Series Model

    OpenAIRE

    Kim Song Yon; Kim Mun Chol

    2013-01-01

    In this paper, non-linear time series models are used to describe volatility in financial time series data. To describe volatility, two of the non-linear time series are combined into form TAR (Threshold Auto-Regressive Model) with AARCH (Asymmetric Auto-Regressive Conditional Heteroskedasticity) error term and its parameter estimation is studied.

  4. Prenatal methylmercury exposure and language delay at three years of age in the Norwegian Mother and Child Cohort Study.

    Science.gov (United States)

    Vejrup, Kristine; Schjølberg, Synnve; Knutsen, Helle Katrine; Kvalem, Helen Engelstad; Brantsæter, Anne Lise; Meltzer, Helle Margrete; Alexander, Jan; Magnus, Per; Haugen, Margaretha

    2016-01-01

    Prenatal methylmercury (MeHg) exposure and its possible neurodevelopmental effects in susceptible children are of concern. Studies of MeHg exposure and negative health outcomes have shown conflicting results and it has been suggested that co-exposure to other contaminants and/or nutrients in fish may confound the effect of MeHg. Our objective was to examine the association between prenatal exposure to MeHg and language and communication development at three years, adjusting for intake of fish, n-3 long chain polyunsaturated fatty acids (n-3 LCPUFAs) and co-exposure to dioxins and dioxin like polychlorinated biphenyls (dl-PCBs). We used data from the Norwegian Mother and Child Cohort Study (MoBa) collected between 2002 and 2008. The study sample consisted of 46,750 mother-child pairs. MeHg exposure was calculated from reported fish intake during pregnancy by a FFQ in mid-pregnancy. Children's language and communication skills were measured by maternal report on the Dale and Bishop grammar rating and the Ages and Stages communication scale (ASQ). We estimated odds ratios (OR) and 95% confidence intervals (CI) using logistic regressions. Median MeHg exposure was 1.3μg/day, corresponding to 0.14μg/kgbw/week. An exposure level above the 90th percentile (>2.6μg/day, >0.29μg/kgbw/week) was defined as the high MeHg exposure. Results indicated an association between high MeHg exposure and unintelligible speech with an adjusted OR 2.22 (1.31, 3.72). High MeHg exposure was also associated with weaker communication skills adjusted OR 1.33 (1.03, 1.70). Additional adjustment for fish intake strengthened the associations, while adjusting for PCBs and n-3 LCPUFA from diet or from supplements had minor impact. In conclusion, significant associations were found between prenatal MeHg exposure above the 90th percentile and delayed language and communication skills in a generally low exposed population. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. Time Series Forecasting with Missing Values

    Directory of Open Access Journals (Sweden)

    Shin-Fu Wu

    2015-11-01

    Full Text Available Time series prediction has become more popular in various kinds of applications such as weather prediction, control engineering, financial analysis, industrial monitoring, etc. To deal with real-world problems, we are often faced with missing values in the data due to sensor malfunctions or human errors. Traditionally, the missing values are simply omitted or replaced by means of imputation methods. However, omitting those missing values may cause temporal discontinuity. Imputation methods, on the other hand, may alter the original time series. In this study, we propose a novel forecasting method based on least squares support vector machine (LSSVM. We employ the input patterns with the temporal information which is defined as local time index (LTI. Time series data as well as local time indexes are fed to LSSVM for doing forecasting without imputation. We compare the forecasting performance of our method with other imputation methods. Experimental results show that the proposed method is promising and is worth further investigations.

  6. Nephrotoxicity during tenofovir treatment: a three-year follow-up study in a Brazilian reference clinic

    Directory of Open Access Journals (Sweden)

    Lauro Ferreira da Silva Pinto Neto

    2016-01-01

    Full Text Available In this study, 275 patients in use of tenofovir were retrospectively followed-up for three years to evaluate risk factors involved in impaired renal function. Analysis of variance (ANOVA and Tukey's test were used to verify any differences in creatinine levels and estimated clearance at 0, 6, 12, 24 and 36 months, adjusting for the co-variables sex, skin color, age >50 years, arterial hypertension, diabetes and the use of the ritonavir-boosted protease inhibitors (PI/r lopinavir/r or atazanavir/r. The software package STATISTICA 10® was used for statistical analysis. The patients’ mean age was 43.2 ± 10.7 years. Systemic arterial hypertension (SAH and diabetes were found in 20.4% and 8.7% of the patients, respectively. Overall, 96.7% were on tenofovir associated with lamivudine (TDF + 3TC, 39.3% on lopinavir/r, 29.8% on efavirenz, and 17.6% on atazanavir/r. There was a statistically significant difference in estimated creatinine clearance at 24 months, when the co-variables male (F = 3.95; p = 0.048, SAH (F = 6.964; p = 0.009, and age over 50 years (F = 45.81; p < 0.001 were taken into consideration. Analysis of the co-variable use of atazanavir/r showed a tendency toward an increased risk over time (F = 2.437; p = 0.063; however, no significant time interaction was seen. At 36-month, a statistically significant difference was found for age over 50 years, (F = 32.02; p < 0.05 and there was a significant time-by-sex interaction (F = 3.117; p = 0.0149. TDF was discontinued in 12 patients, one because of a femoral neck fracture (0.7% and 11 due to nephrotoxicity (4%. Of these latter cases, 9/11 patients were also using protease inhibitors. These data strongly alert that tenofovir use should be individualized with careful attention to renal function especially in male patients, over 50 years, with SAH, and probably those on ATV/r.

  7. Overview of the US JGOFS Bermuda Atlantic Time-series Study (BATS): a decade-scale look at ocean biology and biogeochemistry

    Science.gov (United States)

    Steinberg, Deborah K.; Carlson, Craig A.; Bates, Nicholas R.; Johnson, Rodney J.; Michaels, Anthony F.; Knap, Anthony H.

    The Bermuda Atlantic Time-series Study (BATS) commenced monthly sampling in October 1988 as part of the US Joint Global Ocean Flux Study (JGOFS) program. The goals of the US JGOFS time-series research are to better understand the basic processes that control ocean biogeochemistry on seasonal to decadal time-scales, determine the role of the oceans in the global carbon budget, and ultimately improve our ability to predict the effects of climate change on ecosystems. The BATS program samples the ocean on a biweekly to monthly basis, a strategy that resolves major seasonal patterns and interannual variability. The core cruises last 4-5 d during which hydrography, nutrients, particle flux, pigments and primary production, bacterioplankton abundance and production, and often complementary ancillary measurements are made. This overview focuses on patterns in ocean biology and biogeochemistry over a decade at the BATS site, concentrating on seasonal and interannual changes in community structure, and the physical forcing and other factors controlling the temporal dynamics. Significant seasonal and interannual variability in phytoplankton and bacterioplankton production, biomass, and community structure exists at BATS. No strong relationship exists between primary production and particle flux during the 10 yr record, with the relationship slightly improved by applying an artificial lag of 1 week between production and flux. The prokaryotic picoplankton regularly dominate the phytoplankton community; diatom blooms are rare but occur periodically in the BATS time series. The increase in Chl a concentrations during bloom periods is due to increases by most of the taxa present, rather than by any single group, and there is seasonal succession of phytoplankton. The bacterioplankton often dominate the living biomass, indicating the potential to consume large amounts of carbon and play a major ecological role within the microbial food web. Bacterial biomass, production, and

  8. Measurement of long-term land subsidence by combination of InSAR and time series analysis - Application study to Kanto Plains of Japan -

    Science.gov (United States)

    Deguchi, T.; Rokugawa, S.; Matsushima, J.

    2009-04-01

    InSAR is an application technique of synthetic aperture radars and is now drawing attention as a methodology capable of measuring subtle surface deformation over a wide area with a high spatial resolution. In this study, the authors applied the method of measuring long-term land subsidence by combining InSAR and time series analysis to Kanto Plains of Japan using 28 images of ENVISAT/ASAR data. In this measuring method, the value of land deformation is set as an unknown parameter and the optimal solution to the land deformation amount is derived by applying a smoothness-constrained inversion algorithm. The vicinity of the Kanto Plain started to subside in the 1910s, and became exposed to extreme land subsidence supposedly in accordance with the reconstruction efforts after the Second World War and the economic development activities. The main causes of the land subsidence include the intake of underground water for the use in industries, agriculture, waterworks, and other fields. In the Kujukuri area, the exploitation of soluble natural gas also counts. The Ministry of Environment reported in its documents created in fiscal 2006 that a total of 214 km2 in Tokyo and the six prefectures around the Plain had undergone a subsidence of 1 cm or more per a year. As a result of long-term land subsidence over approximately five and a half years from 13th January, 2003, to 30th June, 2008, unambiguous land deformation was detected in six areas: (i) Haneda Airport, (ii) Urayasu City, (iii) Kasukabe-Koshigaya, (iv) Southern Kanagawa, (v) Toride-Ryugasaki, and (vi) Kujukuri in Chiba Prefecture. In particular, the results for the Kujukuri area were compared with the leveling data taken around the same area to verify the measuring accuracy. The comparative study revealed that the regression formula between the results obtained by time series analysis and those by the leveling can be expressed as a straight line with a gradient of approximately 1, though including a bias of about

  9. Development of Dense Time Series 30-m Image Products from the Chinese HJ-1A/B Constellation: A Case Study in Zoige Plateau, China

    Directory of Open Access Journals (Sweden)

    Jinhu Bian

    2015-12-01

    Full Text Available Time series remote sensing products with both fine spatial and dense temporal resolutions are urgently needed for many earth system studies. The development of small satellite constellations with identical sensors affords novel opportunities to provide such kind of earth observations. In this paper, a new dense time series 30-m image product was proposed respectively based on an 8-day, 16-day and monthly composition. The products were composited by the Charge Coupled Device (CCD images from the 2-day revisit small satellite constellation for environmental monitoring and disaster mitigation of China (HJ-1A/B. Taking the Zoige plateau in China as a case area where it is covered by highly heterogeneous vegetation landscapes, a detailed methodology was introduced on how to use 183 scenes of CCD images in 2010 to create composite products. The quality of the HJ CCD composites was evaluated by inter-comparison with the monthly 30-m global Web-Enabled Landsat Data (WELD, 16-day 500-m MODIS NDVI, and 8-day 500-m MODIS surface reflectance products. Results showed that the radiometric consistency between HJ and WELD composited Top Of Atmosphere (TOA reflectance was in good agreement except for May, June, July and August when more clouds and invalid data gaps appeared in WELD. Visual assessment and temporal profile analysis also revealed that HJ possessed better visual effects and temporal coherence than that of WELD. The comparison between HJ and MODIS products indicated that HJ composites were radiometrically consistent with MODIS products over areas consisting of large patches of homogeneous surface types, but can better reflect the detailed spatial differences in regions with heterogeneous landscapes. This paper highlights the potential of compositing HJ-1A/B CCD images, allowing for providing a cloud free, time-space consistent, 30-m spatial resolution, and dense in time series image product. Meanwhile, the proposed products could also be treated as a

  10. A procedure to derive intra-and inter-annual changes on vegetation from NDVI time series. A case study in Spain

    International Nuclear Information System (INIS)

    Gilabert, M. A; Martinez, B.; Melia, J.

    2009-01-01

    The objective of this work is to study the spatial patterns of vegetation activity over spain and its temporal variability throughout the period 1989-2002. A multi-resolution analysis (MRA) bases on the wavelet transform has been implemented on NDVI time series from the MEDOKADS database. The MRA decomposes the original signal as a sum of series associated with temporal scales. Specifically, the intra-annual series is processed to define several key features in relation with the vegetation penology. In contras, the inter-annual components of the signal is used to detect trends by means of a Mann-Kendall test and map the magnitude of the land-cover change. Finally, a comprehensive identification of the areas presenting a negative value of the magnitude of change is carried out to select those linked to land degradation processes. Results show a major presence of these areas the Southeast of Spain. (Author) 5 refs.

  11. Detecting relationships between the interannual variability in climate records and ecological time series using a multivariate statistical approach - four case studies for the North Sea region

    Energy Technology Data Exchange (ETDEWEB)

    Heyen, H. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Gewaesserphysik

    1998-12-31

    A multivariate statistical approach is presented that allows a systematic search for relationships between the interannual variability in climate records and ecological time series. Statistical models are built between climatological predictor fields and the variables of interest. Relationships are sought on different temporal scales and for different seasons and time lags. The possibilities and limitations of this approach are discussed in four case studies dealing with salinity in the German Bight, abundance of zooplankton at Helgoland Roads, macrofauna communities off Norderney and the arrival of migratory birds on Helgoland. (orig.) [Deutsch] Ein statistisches, multivariates Modell wird vorgestellt, das eine systematische Suche nach potentiellen Zusammenhaengen zwischen Variabilitaet in Klima- und oekologischen Zeitserien erlaubt. Anhand von vier Anwendungsbeispielen wird der Klimaeinfluss auf den Salzgehalt in der Deutschen Bucht, Zooplankton vor Helgoland, Makrofauna vor Norderney, und die Ankunft von Zugvoegeln auf Helgoland untersucht. (orig.)

  12. A procedure to derive intra-and inter-annual changes on vegetation from NDVI time series. A case study in Spain

    Energy Technology Data Exchange (ETDEWEB)

    Gilabert, M. A; Martinez, B.; Melia, J.

    2009-07-01

    The objective of this work is to study the spatial patterns of vegetation activity over spain and its temporal variability throughout the period 1989-2002. A multi-resolution analysis (MRA) bases on the wavelet transform has been implemented on NDVI time series from the MEDOKADS database. The MRA decomposes the original signal as a sum of series associated with temporal scales. Specifically, the intra-annual series is processed to define several key features in relation with the vegetation penology. In contras, the inter-annual components of the signal is used to detect trends by means of a Mann-Kendall test and map the magnitude of the land-cover change. Finally, a comprehensive identification of the areas presenting a negative value of the magnitude of change is carried out to select those linked to land degradation processes. Results show a major presence of these areas the Southeast of Spain. (Author) 5 refs.

  13. Inferring interdependencies from short time series

    Indian Academy of Sciences (India)

    Abstract. Complex networks provide an invaluable framework for the study of interlinked dynamical systems. In many cases, such networks are constructed from observed time series by first estimating the ...... does not quantify causal relations (unlike IOTA, or .... Africa_map_regions.svg, which is under public domain.

  14. A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models.

    Science.gov (United States)

    Dionisio, Kathie L; Chang, Howard H; Baxter, Lisa K

    2016-11-25

    Exposure measurement error in copollutant epidemiologic models has the potential to introduce bias in relative risk (RR) estimates. A simulation study was conducted using empirical data to quantify the impact of correlated measurement errors in time-series analyses of air pollution and health. ZIP-code level estimates of exposure for six pollutants (CO, NO x , EC, PM 2.5 , SO 4 , O 3 ) from 1999 to 2002 in the Atlanta metropolitan area were used to calculate spatial, population (i.e. ambient versus personal), and total exposure measurement error. Empirically determined covariance of pollutant concentration pairs and the associated measurement errors were used to simulate true exposure (exposure without error) from observed exposure. Daily emergency department visits for respiratory diseases were simulated using a Poisson time-series model with a main pollutant RR = 1.05 per interquartile range, and a null association for the copollutant (RR = 1). Monte Carlo experiments were used to evaluate the impacts of correlated exposure errors of different copollutant pairs. Substantial attenuation of RRs due to exposure error was evident in nearly all copollutant pairs studied, ranging from 10 to 40% attenuation for spatial error, 3-85% for population error, and 31-85% for total error. When CO, NO x or EC is the main pollutant, we demonstrated the possibility of false positives, specifically identifying significant, positive associations for copollutants based on the estimated type I error rate. The impact of exposure error must be considered when interpreting results of copollutant epidemiologic models, due to the possibility of attenuation of main pollutant RRs and the increased probability of false positives when measurement error is present.

  15. Development of temporal modelling for forecasting and prediction of malaria infections using time-series and ARIMAX analyses: a case study in endemic districts of Bhutan.

    Science.gov (United States)

    Wangdi, Kinley; Singhasivanon, Pratap; Silawan, Tassanee; Lawpoolsri, Saranath; White, Nicholas J; Kaewkungwal, Jaranit

    2010-09-03

    Malaria still remains a public health problem in some districts of Bhutan despite marked reduction of cases in last few years. To strengthen the country's prevention and control measures, this study was carried out to develop forecasting and prediction models of malaria incidence in the endemic districts of Bhutan using time series and ARIMAX. This study was carried out retrospectively using the monthly reported malaria cases from the health centres to Vector-borne Disease Control Programme (VDCP) and the meteorological data from Meteorological Unit, Department of Energy, Ministry of Economic Affairs. Time series analysis was performed on monthly malaria cases, from 1994 to 2008, in seven malaria endemic districts. The time series models derived from a multiplicative seasonal autoregressive integrated moving average (ARIMA) was deployed to identify the best model using data from 1994 to 2006. The best-fit model was selected for each individual district and for the overall endemic area was developed and the monthly cases from January to December 2009 and 2010 were forecasted. In developing the prediction model, the monthly reported malaria cases and the meteorological factors from 1996 to 2008 of the seven districts were analysed. The method of ARIMAX modelling was employed to determine predictors of malaria of the subsequent month. It was found that the ARIMA (p, d, q) (P, D, Q)s model (p and P representing the auto regressive and seasonal autoregressive; d and D representing the non-seasonal differences and seasonal differencing; and q and Q the moving average parameters and seasonal moving average parameters, respectively and s representing the length of the seasonal period) for the overall endemic districts was (2,1,1)(0,1,1)12; the modelling data from each district revealed two most common ARIMA models including (2,1,1)(0,1,1)12 and (1,1,1)(0,1,1)12. The forecasted monthly malaria cases from January to December 2009 and 2010 varied from 15 to 82 cases in 2009

  16. OLYMPUS: an automated hybrid clustering method in time series gene expression. Case study: host response after Influenza A (H1N1) infection.

    Science.gov (United States)

    Dimitrakopoulou, Konstantina; Vrahatis, Aristidis G; Wilk, Esther; Tsakalidis, Athanasios K; Bezerianos, Anastasios

    2013-09-01

    The increasing flow of short time series microarray experiments for the study of dynamic cellular processes poses the need for efficient clustering tools. These tools must deal with three primary issues: first, to consider the multi-functionality of genes; second, to evaluate the similarity of the relative change of amplitude in the time domain rather than the absolute values; third, to cope with the constraints of conventional clustering algorithms such as the assignment of the appropriate cluster number. To address these, we propose OLYMPUS, a novel unsupervised clustering algorithm that integrates Differential Evolution (DE) method into Fuzzy Short Time Series (FSTS) algorithm with the scope to utilize efficiently the information of population of the first and enhance the performance of the latter. Our hybrid approach provides sets of genes that enable the deciphering of distinct phases in dynamic cellular processes. We proved the efficiency of OLYMPUS on synthetic as well as on experimental data. The discriminative power of OLYMPUS provided clusters, which refined the so far perspective of the dynamics of host response mechanisms to Influenza A (H1N1). Our kinetic model sets a timeline for several pathways and cell populations, implicated to participate in host response; yet no timeline was assigned to them (e.g. cell cycle, homeostasis). Regarding the activity of B cells, our approach revealed that some antibody-related mechanisms remain activated until day 60 post infection. The Matlab codes for implementing OLYMPUS, as well as example datasets, are freely accessible via the Web (http://biosignal.med.upatras.gr/wordpress/biosignal/). Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  17. Time series analysis time series analysis methods and applications

    CERN Document Server

    Rao, Tata Subba; Rao, C R

    2012-01-01

    The field of statistics not only affects all areas of scientific activity, but also many other matters such as public policy. It is branching rapidly into so many different subjects that a series of handbooks is the only way of comprehensively presenting the various aspects of statistical methodology, applications, and recent developments. The Handbook of Statistics is a series of self-contained reference books. Each volume is devoted to a particular topic in statistics, with Volume 30 dealing with time series. The series is addressed to the entire community of statisticians and scientists in various disciplines who use statistical methodology in their work. At the same time, special emphasis is placed on applications-oriented techniques, with the applied statistician in mind as the primary audience. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowened experts in their respect...

  18. The Potential of Time Series Merged from Landsat-5 TM and HJ-1 CCD for Crop Classification: A Case Study for Bole and Manas Counties in Xinjiang, China

    Directory of Open Access Journals (Sweden)

    Pengyu Hao

    2014-08-01

    Full Text Available Time series data capture crop growth dynamics and are some of the most effective data sources for crop mapping. However, a drawback of precise crop classification at medium resolution (30 m using multi-temporal data is that some images at crucial time periods are absent from a single sensor. In this research, a medium-resolution, 15-day time series was obtained by merging Landsat-5 TM and HJ-1 CCD data (with similar radiometric performances in multi-spectral bands. Subsequently, optimal temporal windows for accurate crop mapping were evaluated using an extension of the Jeffries–Matusita (JM distance from the merged time series. A support vector machine (SVM was then used to compare the classification accuracy of the optimal temporal windows and the entire time series. In addition, different training sample sizes (10% to 90% of the entire training sample in 10% increments; five repetitions for each sample size were used to investigate the stability of optimal temporal windows. The results showed that time series in optimal temporal windows can achieve high classification accuracies. The optimal temporal windows were robust when the training sample size was sufficiently large. However, they were not stable when the sample size was too small (i.e., less than 300 and may shift in different agro-ecosystems, because of different classes. In addition, merged time series had higher temporal resolution and were more likely to comprise the optimal temporal periods than time series from single-sensor data. Therefore, the use of merged time series increased the possibility of precise crop classification.

  19. An Alternative Framework for Time Series Decomposition and Forecastingand its Relevance for Portfolio Choice – A Comparative Study of the Indian Consumer Durable and Small Cap Sectors

    OpenAIRE

    SEN, Jaydip; DATTA CHAUDHURI, Tamal

    2016-01-01

    Abstract. One of the challenging research problems in the domain of time series analysis and forecasting is making efficient and robust prediction of stock market prices. With rapid development and evolution of sophisticated algorithms and with the availability of extremely fast computing platforms, it has now become possible to effectively extract, store, process and analyze high volume stock market time series data. Complex algorithms for forecasting are now available for speedy execution o...

  20. Three year progress report

    International Nuclear Information System (INIS)

    1977-07-01

    Progress is reported on the following studies: x-ray and uv effects in photosynthetic organisms; effects of alcohols and oxygen concentration on transforming DNA; free radical studies; sensitization by metal ions; role of the solvated electron in radiation damage to cells; effectiveness of organic and inorganic compounds in sensitizing bacterial spores to high energy radiation; oxygen effects; radiosensitivity of enzyme systems in Chlorella; and effects of pre-irradiation of solutions on spores

  1. Three-Year Improvements in Weight Status and Weight-Related Behaviors in Middle School Students: The Healthy Choices Study.

    Directory of Open Access Journals (Sweden)

    Karen E Peterson

    Full Text Available Few dissemination evaluations exist to document the effectiveness of evidence-based childhood obesity interventions outside the research setting.Evaluate Healthy Choices (HC, a multi-component obesity prevention program, by examining school-level changes in weight-related behaviors and weight status and the association of implementation components with odds of overweight/obesity.We compared baseline and Year 3 school-level behavioral and weight status outcomes with paired t-tests adjusted for schools' socio-demographic characteristics. We used generalized estimating equations to examine the odds of overweight/obesity associated with program components.Consecutive sample of 45 of 51 middle schools participating in the HC program with complete baseline and follow-up survey data including a subsample of 35 schools with measured anthropomentry for 5,665 7th grade students.Schools developed a multi-disciplinary team and implemented an obesity prevention curriculum, before and after school activities, environmental and policy changes and health promotions targeting a 5-2-1 theme: eat ≥ 5 servings/day of fruits and vegetables (FV, watch ≤ 2 hours of television (TV and participate in ≥ 1 hours/day of physical activity (PA on most days.1 School-level percent of students achieving targeted behaviors and percent overweight/obese; and 2 individual odds of overweight/obesity.The percent achieving behavioral goals over three years increased significantly for FV: 16.4 to 19.4 (p = 0.001, TV: 53.4 to 58.2 (p = 0.003 and PA: 37.1 to 39.9 (p = 0.02, adjusting for school size, baseline mean age and percent female, non-Hispanic White, and eligible for free and reduced price lunch. In 35 schools with anthropometry, the percent of overweight/obese 7th grade students decreased from 42.1 to 38.4 (p = 0.016. Having a team that met the HC definition was associated with lower odds of overweight/obesity (OR = 0.83, CI: 0.71-0.98.The HC multi-component intervention

  2. Multiple Indicator Stationary Time Series Models.

    Science.gov (United States)

    Sivo, Stephen A.

    2001-01-01

    Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

  3. Vehicle speed prediction via a sliding-window time series analysis and an evolutionary least learning machine: A case study on San Francisco urban roads

    Directory of Open Access Journals (Sweden)

    Ladan Mozaffari

    2015-06-01

    Full Text Available The main goal of the current study is to take advantage of advanced numerical and intelligent tools to predict the speed of a vehicle using time series. It is clear that the uncertainty caused by temporal behavior of the driver as well as various external disturbances on the road will affect the vehicle speed, and thus, the vehicle power demands. The prediction of upcoming power demands can be employed by the vehicle powertrain control systems to improve significantly the fuel economy and emission performance. Therefore, it is important to systems design engineers and automotive industrialists to develop efficient numerical tools to overcome the risk of unpredictability associated with the vehicle speed profile on roads. In this study, the authors propose an intelligent tool called evolutionary least learning machine (E-LLM to forecast the vehicle speed sequence. To have a practical evaluation regarding the efficacy of E-LLM, the authors use the driving data collected on the San Francisco urban roads by a private Honda Insight vehicle. The concept of sliding window time series (SWTS analysis is used to prepare the database for the speed forecasting process. To evaluate the performance of the proposed technique, a number of well-known approaches, such as auto regressive (AR method, back-propagation neural network (BPNN, evolutionary extreme learning machine (E-ELM, extreme learning machine (ELM, and radial basis function neural network (RBFNN, are considered. The performances of the rival methods are then compared in terms of the mean square error (MSE, root mean square error (RMSE, mean absolute percentage error (MAPE, median absolute percentage error (MDAPE, and absolute fraction of variances (R2 metrics. Through an exhaustive comparative study, the authors observed that E-LLM is a powerful tool for predicting the vehicle speed profiles. The outcomes of the current study can be of use for the engineers of automotive industry who have been

  4. International Work-Conference on Time Series

    CERN Document Server

    Pomares, Héctor; Valenzuela, Olga

    2017-01-01

    This volume of selected and peer-reviewed contributions on the latest developments in time series analysis and forecasting updates the reader on topics such as analysis of irregularly sampled time series, multi-scale analysis of univariate and multivariate time series, linear and non-linear time series models, advanced time series forecasting methods, applications in time series analysis and forecasting, advanced methods and online learning in time series and high-dimensional and complex/big data time series. The contributions were originally presented at the International Work-Conference on Time Series, ITISE 2016, held in Granada, Spain, June 27-29, 2016. The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting.  It focuses on interdisciplinary and multidisciplinary rese arch encompassing the disciplines of comput...

  5. Understanding the Steric Height Long Term Variability at the Bermuda Atlantic Time-Series Study (BATS) Site with a Neutral Density Approach

    Science.gov (United States)

    Goncalves Neto, A.; Johnson, R. J.; Bates, N. R.

    2016-02-01

    Rising sea level is one of the main concerns for human life in a scenario with global atmosphere and ocean warming, which is of particular concern for oceanic islands. Bermuda, located in the center of the Sargasso Sea, provides an ideal location to investigate sea level rise since it has a long term tide gauge (1933-present) and is in close proximity to deep ocean time-series sites, namely, Hydrostation `S' (1954-present) and the Bermuda Atlantic Time-Series Study site (1988-present). In this study, we use the monthly CTD deep casts at BATS to compute the contribution of steric height (SH) to the local sea surface height (SSH) for the past 24 years. To determine the relative contribution from the various water masses we first define 8 layers (Surface Layer, Upper Thermocline, Subtropical Mode-Water, Lower Thermocline, Antarctic Intermediate Water, Labrador Sea Water, Iceland-Scotland Overflow Water, Denmark Strait Overflow Water) based on neutral density criteria for which SH is computed. Additionally, we calculate the thermosteric and halosteric components for each of the defined neutral density layers. Surprisingly, the results show that, despite a 3.3mm/yr sea level rise observed at the Bermuda tide gauge, the steric contribution to the SSH at BATS has decreased at a rate of -1.1mm/yr during the same period. The thermal component is found to account for the negative trend in the steric height (-4.4mm/yr), whereas the halosteric component (3.3mm/yr) partially compensates the thermal signal and can be explained by an overall cooling and freshening at the BATS site. Although the surface layer and the upper thermocline waters are warming, all the subtropical and polar water masses, which represent most of the local water column, are cooling and therefore drive the overall SH contribution to the local SSH. Hence, it suggests that the mass contribution to the local SSH plays an important role in the sea level rise, for which we investigate with GRACE data.

  6. Unevenly spaced time series analysis: Case study using calcimetry data from BV-1 and BV-2 boreholesin Ljubljansko barje (central Slovenia

    Directory of Open Access Journals (Sweden)

    Mihael Brenčič

    2009-12-01

    Full Text Available Statistical analyses of calcimetric data from boreholes BV-1 (north of PodpeČ and BV-2 (south of ^rna vas on Ljubljansko barje in central Slovenia are given. The original data are represented as unevenly spaced time series that are translated into evenly spaced time series. To calculate the interpolation weighted influence function,amodel based on the power correlated influence is defined.Parameters electionisper formed basedon the maximum entropy principle. In the reconstructed time series, autocorrelation and Fourier power spectrum analyses are performed. In both time series, a transition from white noise to red noise was detected. Such behaviour can be describedby a Lorentz process. Red noise is the result of a stochastic process with long-term memory. This effect can be seen predominantly in the autocorrelation function of borehole BV-1. In the calcimetric time series of borehole BV-2, periodicity with a period between 10.0 m and 12.5 m was also detected. We suppose that this period reflects climatic fluctuations during the Quaternary Period.

  7. Physical Forcing-Driven Productivity and Sediment Flux to the Deep Basin of Northern South China Sea: A Decadal Time Series Study

    Directory of Open Access Journals (Sweden)

    Hon-Kit Lui

    2018-03-01

    Full Text Available Understanding the driving forces of absorption of anthropogenic CO2 by the oceans is critical for a sustainable ocean carbon cycle. Decadal sinking particle flux data collected at 1000 m, 2000 m, and 3500 m at the South East Asia Time Series Study (SEATS Station (18° N, 116° E, which was located in the northern South China Sea (nSCS, show that the fluxes undergo strong seasonal and interannual variability. Changes in the flux data are correlated with the satellite-derived chlorophyll-a concentration, indicating that the mass fluxes of the sinking particles are largely controlled by the export production at or near the SEATS station. The cooling of seawater and the strengthening of wind in winter increase the nutrient inventories in the euphotic zone, thus also increasing export production in the nSCS. This study reveals that the intrusion of low-nutrient seawater from the West Philippine Sea into the nSCS significantly reduces the productivity, and hence the flux, of sinking particles.

  8. Direct comparison of {sup 210}Po, {sup 234}Th and POC particle-size distributions and export fluxes at the Bermuda Atlantic Time-series Study (BATS) site

    Energy Technology Data Exchange (ETDEWEB)

    Stewart, Gillian, E-mail: gstewart@qc.cuny.ed [Queens College, CUNY Flushing, NY 11367 (United States); Moran, S. Bradley, E-mail: moran@gso.uri.ed [Graduate School of Oceanography, URI Narragansett, RI 02882 (United States); Lomas, Michael W., E-mail: Michael.Lomas@bios.ed [Bermuda Institute for Ocean Sciences, St. George' s, GE01 (Bermuda); Kelly, Roger P., E-mail: rokelly@gso.uri.ed [Graduate School of Oceanography, URI Narragansett, RI 02882 (United States)

    2011-05-15

    Particle-reactive, naturally occurring radionuclides are useful tracers of the sinking flux of organic matter from the surface to the deep ocean. Since the Joint Global Ocean Flux Study (JGOFS) began in 1987, the disequilibrium between {sup 234}Th and its parent {sup 238}U has become widely used as a technique to measure particle export fluxes from surface ocean waters. Another radionuclide pair, {sup 210}Po and {sup 210}Pb, can be used for the same purpose but has not been as widely adopted due to difficulty with accurately constraining the {sup 210}Po/{sup 210}Pb radiochemical balance in the ocean and because of the more time-consuming radiochemical procedures. Direct comparison of particle flux estimated in different ocean regions using these short-lived radionuclides is important in evaluating their utility and accuracy as tracers of particle flux. In this paper, we present paired {sup 234}Th/{sup 238}U and {sup 210}Po/{sup 210}Pb data from oligotrophic surface waters of the subtropical Northwest Atlantic and discuss their advantages and limitations. Vertical profiles of total and particle size-fractionated {sup 210}Po and {sup 234}Th activities, together with particulate organic carbon (POC) concentrations, were measured during three seasons at the Bermuda Atlantic Time-series Study (BATS) site. Both {sup 210}Po and {sup 234}Th reasonably predict sinking POC flux caught in sediment traps, and each tracer provides unique information about the magnitude and efficiency of the ocean's biological pump.

  9. An intercomparison of dissolved iron speciation at the Bermuda Atlantic Time-series Study (BATS site: Results from GEOTRACES Crossover Station A

    Directory of Open Access Journals (Sweden)

    Kristen Nicolle Buck

    2016-12-01

    Full Text Available The organic complexation of dissolved iron (Fe was determined in depth profile samples collected from GEOTRACES Crossover Station A, the Bermuda Atlantic Time-series Study (BATS site, as part of the Dutch and U.S. GEOTRACES North Atlantic programs in June 2010 and November 2011, respectively. The two groups employed distinct competitive ligand exchange-adsorptive cathodic stripping voltammetry (CLE-AdCSV methods, and resulting ligand concentrations and conditional stability constants from each profile were compared. Excellent agreement was found between the total ligand concentrations determined in June 2010 and the strongest, L1-type, ligand concentrations determined in November 2011. Yet a primary distinction between the datasets was the number of ligand classes observed: a single ligand class was characterized in the June 2010 profile while two ligand classes were observed in the November 2011 profile. To assess the role of differing interpretation approaches in determining final results, analysts exchanged titration data and accompanying parameters from the profiles for reinterpretation. The reinterpretation exercises highlighted the considerable influence of the sensitivity (S parameter applied on interpretation results, consistent with recent intercalibration work on interpretation of copper speciation titrations. The potential role of titration data structure, humic-type substances, differing dissolved Fe concentrations, and seasonality are also discussed as possible drivers of the one versus two ligand class determinations between the two profiles, leading to recommendations for future studies of Fe-binding ligand cycling in the oceans.

  10. "PCI Reading Program": The Final Report of a Three Year Experimental Study in Brevard Public Schools and Miami-Dade County Public Schools. Research Report

    Science.gov (United States)

    Toby, Megan; Jaciw, Andrew; Ma, Boya; Lipton, Akiko

    2011-01-01

    PCI Education conducted a three-year longitudinal study to determine the comparative effectiveness of the "PCI Reading Program" ("PCI") for students with severe disabilities as implemented in Florida's Brevard Public Schools and Miami-Dade County Public Schools. The primary question addressed by the study is whether students…

  11. Forecasting with nonlinear time series models

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl; Teräsvirta, Timo

    In this paper, nonlinear models are restricted to mean nonlinear parametric models. Several such models popular in time series econo- metrics are presented and some of their properties discussed. This in- cludes two models based on universal approximators: the Kolmogorov- Gabor polynomial model...... applied to economic fore- casting problems, is briefly highlighted. A number of large published studies comparing macroeconomic forecasts obtained using different time series models are discussed, and the paper also contains a small simulation study comparing recursive and direct forecasts in a partic...... and two versions of a simple artificial neural network model. Techniques for generating multi-period forecasts from nonlinear models recursively are considered, and the direct (non-recursive) method for this purpose is mentioned as well. Forecasting with com- plex dynamic systems, albeit less frequently...

  12. Reconstruction of tritium time series in precipitation

    International Nuclear Information System (INIS)

    Celle-Jeanton, H.; Gourcy, L.; Aggarwal, P.K.

    2002-01-01

    Tritium is commonly used in groundwaters studies to calculate the recharge rate and to identify the presence of a modern recharge. The knowledge of 3 H precipitation time series is then very important for the study of groundwater recharge. Rozanski and Araguas provided good information on precipitation tritium content in 180 stations of the GNIP network to the end of 1987, but it shows some lacks of measurements either within one chronicle or within one region (the Southern hemisphere for instance). Therefore, it seems to be essential to find a method to recalculate data for a region where no measurement is available.To solve this problem, we propose another method which is based on triangulation. It needs the knowledge of 3 H time series of 3 stations surrounding geographically the 4-th station for which tritium input curve has to be reconstructed

  13. Hospitalizations for varicella in children and adolescents in a referral hospital in Hong Kong, 2004 to 2008: A time series study

    Directory of Open Access Journals (Sweden)

    Chan WM

    2011-05-01

    Full Text Available Abstract Background Varicella accounts for significant morbidities and remains a public health issue worldwide. Climatic factors have been shown to associate with the incidence and transmission of various infectious diseases. We describe the epidemiology of varicella in paediatric patients hospitalized at a tertiary referral hospital in Hong Kong from 2004 to 2008, and to explore the possible association between the occurrence of varicella infection and various climatic factors. Methods The hospital discharge database of Princess Margaret Hospital was retrospectively analyzed for admissions associated with varicella from 2004 to 2008. Meteorological data were obtained from the monthly meteorological reports from the Hong Kong Observatory website. Time series analysis was performed with Poisson regression using a Generalized Estimating Equation (GEE approach. Results During the study period, 598 children were hospitalized for varicella. The mean age on admission was 57.6 months, and the mean duration of hospitalization was 3.7 days. The overall complication rate was 47%. The mean monthly relative humidity, especially in cool seasons, was inversely correlated with the monthly varicella cases of the same month. Conclusions Varicella can lead to serious complications and prolonged hospitalization, even in previously healthy children. Lower relative humidity in cool seasons is associated with higher number of paediatric varicella hospital admissions. These findings are useful for a better understanding of the pattern of paediatric varicella hospitalization in Hong Kong.

  14. Correlation and multifractality in climatological time series

    International Nuclear Information System (INIS)

    Pedron, I T

    2010-01-01

    Climate can be described by statistical analysis of mean values of atmospheric variables over a period. It is possible to detect correlations in climatological time series and to classify its behavior. In this work the Hurst exponent, which can characterize correlation and persistence in time series, is obtained by using the Detrended Fluctuation Analysis (DFA) method. Data series of temperature, precipitation, humidity, solar radiation, wind speed, maximum squall, atmospheric pressure and randomic series are studied. Furthermore, the multifractality of such series is analyzed applying the Multifractal Detrended Fluctuation Analysis (MF-DFA) method. The results indicate presence of correlation (persistent character) in all climatological series and multifractality as well. A larger set of data, and longer, could provide better results indicating the universality of the exponents.

  15. A Time Series Forecasting Method

    Directory of Open Access Journals (Sweden)

    Wang Zhao-Yu

    2017-01-01

    Full Text Available This paper proposes a novel time series forecasting method based on a weighted self-constructing clustering technique. The weighted self-constructing clustering processes all the data patterns incrementally. If a data pattern is not similar enough to an existing cluster, it forms a new cluster of its own. However, if a data pattern is similar enough to an existing cluster, it is removed from the cluster it currently belongs to and added to the most similar cluster. During the clustering process, weights are learned for each cluster. Given a series of time-stamped data up to time t, we divide it into a set of training patterns. By using the weighted self-constructing clustering, the training patterns are grouped into a set of clusters. To estimate the value at time t + 1, we find the k nearest neighbors of the input pattern and use these k neighbors to decide the estimation. Experimental results are shown to demonstrate the effectiveness of the proposed approach.

  16. A Course in Time Series Analysis

    CERN Document Server

    Peña, Daniel; Tsay, Ruey S

    2011-01-01

    New statistical methods and future directions of research in time series A Course in Time Series Analysis demonstrates how to build time series models for univariate and multivariate time series data. It brings together material previously available only in the professional literature and presents a unified view of the most advanced procedures available for time series model building. The authors begin with basic concepts in univariate time series, providing an up-to-date presentation of ARIMA models, including the Kalman filter, outlier analysis, automatic methods for building ARIMA models, a

  17. The association between improved quality diabetes indicators, health outcomes and costs: towards constructing a "business case" for quality of diabetes care--a time series study.

    Science.gov (United States)

    Wilf-Miron, Rachel; Bolotin, Arkadi; Gordon, Nesia; Porath, Avi; Peled, Ronit

    2014-12-01

    In primary health care systems where member's turnover is relatively low, the question, whether investment in quality of care improvement can make a business case, or is cost effective, has not been fully answered.The objectives of this study were: (1) to investigate the relationship between improvement in selected measures of diabetes (type 2) care and patients' health outcomes; and (2) to estimate the association between improvement in performance and direct medical costs. A time series study with three quality indicators - Hemoglobin A1c (HbA1c) testing, HbA1C and LDL- cholesterol (LDL-C) control - which were analyzed in patients with diabetes, insured by a large health fund. Health outcomes measures used: hospitalization days, Emergency Department (ED) visits and mortality. Poisson, GEE and Cox regression models were employed. Covariates: age, gender and socio-economic rank. 96,553 adult (age >18) patients with diabetes were analyzed. The performance of the study indicators, significantly and steadily improved during the study period (2003-2009). Poor HbA1C (>9%) and inappropriate LDL-C control (>100 mg/dl) were significantly associated with number of hospitalization days. ED visits did not achieve statistical significance. Improvement in HbA1C control was associated with an annual average of 2% reduction in hospitalization days, leading to substantial reduction in tertiary costs. The Hazard ratio for mortality, associated with poor HbA1C and LDL-C, control was 1.78 and 1.17, respectively. Our study demonstrates the effect of continuous improvement in quality care indicators, on health outcomes and resource utilization, among patients with diabetes. These findings support the business case for quality, especially in healthcare systems with relatively low enrollee turnover, where providers, in the long term, could "harvest" their investments in improving quality.

  18. Genomic epidemiology of a major Mycobacterium tuberculosis outbreak: Retrospective cohort study in a low incidence setting using sparse time-series sampling

    DEFF Research Database (Denmark)

    Folkvardsen, Dorte Bek; Norman, Anders; Andersen, Åse Bengård

    2017-01-01

    cases belonging to this outbreak via routine MIRU-VNTR typing. Here, we present a retrospective analysis of the C2/1112-15 dataset, based on whole-genome data from a sparse time-series consisting of five randomly selected isolates from each of the 23 years. Even if these data are derived from only 12...

  19. Causal strength induction from time series data.

    Science.gov (United States)

    Soo, Kevin W; Rottman, Benjamin M

    2018-04-01

    One challenge when inferring the strength of cause-effect relations from time series data is that the cause and/or effect can exhibit temporal trends. If temporal trends are not accounted for, a learner could infer that a causal relation exists when it does not, or even infer that there is a positive causal relation when the relation is negative, or vice versa. We propose that learners use a simple heuristic to control for temporal trends-that they focus not on the states of the cause and effect at a given instant, but on how the cause and effect change from one observation to the next, which we call transitions. Six experiments were conducted to understand how people infer causal strength from time series data. We found that participants indeed use transitions in addition to states, which helps them to reach more accurate causal judgments (Experiments 1A and 1B). Participants use transitions more when the stimuli are presented in a naturalistic visual format than a numerical format (Experiment 2), and the effect of transitions is not driven by primacy or recency effects (Experiment 3). Finally, we found that participants primarily use the direction in which variables change rather than the magnitude of the change for estimating causal strength (Experiments 4 and 5). Collectively, these studies provide evidence that people often use a simple yet effective heuristic for inferring causal strength from time series data. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  20. Fast-GPU-PCC: A GPU-Based Technique to Compute Pairwise Pearson's Correlation Coefficients for Time Series Data-fMRI Study.

    Science.gov (United States)

    Eslami, Taban; Saeed, Fahad

    2018-04-20

    Functional magnetic resonance imaging (fMRI) is a non-invasive brain imaging technique, which has been regularly used for studying brain’s functional activities in the past few years. A very well-used measure for capturing functional associations in brain is Pearson’s correlation coefficient. Pearson’s correlation is widely used for constructing functional network and studying dynamic functional connectivity of the brain. These are useful measures for understanding the effects of brain disorders on connectivities among brain regions. The fMRI scanners produce huge number of voxels and using traditional central processing unit (CPU)-based techniques for computing pairwise correlations is very time consuming especially when large number of subjects are being studied. In this paper, we propose a graphics processing unit (GPU)-based algorithm called Fast-GPU-PCC for computing pairwise Pearson’s correlation coefficient. Based on the symmetric property of Pearson’s correlation, this approach returns N ( N − 1 ) / 2 correlation coefficients located at strictly upper triangle part of the correlation matrix. Storing correlations in a one-dimensional array with the order as proposed in this paper is useful for further usage. Our experiments on real and synthetic fMRI data for different number of voxels and varying length of time series show that the proposed approach outperformed state of the art GPU-based techniques as well as the sequential CPU-based versions. We show that Fast-GPU-PCC runs 62 times faster than CPU-based version and about 2 to 3 times faster than two other state of the art GPU-based methods.

  1. The effect of stricter licensing on road traffic injury events involving 15 to 17-year-old moped drivers in Sweden: A time series intervention study.

    Science.gov (United States)

    Bonander, Carl; Andersson, Ragnar; Nilson, Finn

    2015-10-01

    This study aimed to evaluate and quantify the effect of the introduction of the AM driving license on non-fatal moped-related injuries in Sweden. With the introduction of the new license category in October 2009, prospective moped drivers are now required to pass a mandatory theory test following a practical and theoretical course. In addition, obtaining a license to operate a moped is now considerably more costly. Time series intervention analysis on monthly aggregated injury data (1st Jan 2007-31st Dec 2013) was performed using generalized additive models for location, shape and scale (GAMLSS) to quantify the effect size on injury events involving teenage (15-17 years) moped drivers, while controlling for trend and seasonality. Exposure was adjusted for by using the number of registered mopeds in traffic as a proxy. The introduction of AM license was associated with a 41% reduction in the rate of injury events involving 15-year-old moped drivers (IRR 0.59 [95% CI: 0.48-0.72]), and a 39% and 36% decrease in those involving 16-year-old (IRR 0.61 [95% CI: 0.48-0.79]) and 17-year-old drivers (IRR 0.64 [95% CI: 0.46-0.90]), respectively. The effect in the 15-year-old stratum was decreased roughly by half after adjusting for exposure, but remained significant, and the corresponding estimates in the other age groups did not change noticeably. This study provides quasi-experimental evidence of an effect on non-fatal moped-related injuries as a result of stricter licensing rules. Only part of the effect could be explained by a reduction in the number of mopeds in traffic, indicating that other mechanisms must be studied to fully understand the cause of the reduction in injuries. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Evaluation of four designs of short implants placed in atrophic areas with reduced bone height: a three-year, retrospective, clinical and radiographic study.

    Science.gov (United States)

    Lopez Torres, J A; Gehrke, S A; Calvo Guirado, J L; Aristazábal, L F R

    2017-09-01

    The aim of the present study was to evaluate retrospectively the clinical and radiographic behaviour of four commercially-available short implants with different macrodesigns and microdesigns in areas in which the height of the bone was reduced. We took into account the success and survival, peri-implant crestal bone loss, and the level of probing at which the gum bled. Patients were included if they had been given one or more short implants (≤8.5mm long) in the posterior jaws at least three years earlier. Three hundred and ninety-one short implants were placed in 170 subjects, and were divided in four groups based on the brand of implant. The implants were evaluated one, two, and three years after they had been inserted. Short implants had a three-year survival and success rate of 90% in all groups, and bone loss was acceptable after three years with no significant differences between them. These results support the use of short implants as an effective and safe treatment. However, within the limitations of this study, the design of the implant does seem to influence the behaviour of peri-implant bone at the crestal level. Copyright © 2017. Published by Elsevier Ltd.

  3. Emergency room visits for respiratory conditions in children increased after Guagua Pichincha volcanic eruptions in April 2000 in Quito, Ecuador Observational Study: Time Series Analysis

    Directory of Open Access Journals (Sweden)

    Jagai Jyotsna S

    2007-07-01

    Full Text Available Abstract Background This study documented elevated rates of emergency room (ER visits for acute upper and lower respiratory infections and asthma-related conditions in the children of Quito, Ecuador associated with the eruption of Guagua Pichincha in April of 2000. Methods We abstracted 5169 (43% females ER records with primary respiratory conditions treated from January 1 – December 27, 2000 and examined the change in pediatric ER visits for respiratory conditions before, during, and after exposure events of April, 2000. We applied a Poisson regression model adapted to time series of cases for three non-overlapping disease categories: acute upper respiratory infection (AURI, acute lower respiratory infection (ALRI, and asthma-related conditions in boys and girls for three age groups: 0–4, 5–9, and 10–15 years. Results At the main pediatric medical facility, the Baca Ortiz Pediatric Hospital, the rate of emergency room (ER visits due to respiratory conditions substantially increased in the three weeks after eruption (RR = 2.22, 95%CI = [1.95, 2.52] and RR = 1.72 95%CI = [1.49, 1.97] for lower and upper respiratory tract infections respectively. The largest impact of eruptions on respiratory distress was observed in children younger than 5 years (RR = 2.21, 95%CI = [1.79, 2.73] and RR = 2.16 95%CI = [1.67, 2.76] in boys and girls respectively. The rate of asthma and asthma-related diagnosis doubled during the period of volcano fumarolic activity (RR = 1.97, 95%CI = [1.19, 3.24]. Overall, 28 days of volcanic activity and ash releases resulted in 345 (95%CI = [241, 460] additional ER visits due to respiratory conditions. Conclusion The study has demonstrated strong relationship between ash exposure and respiratory effects in children.

  4. Emergency room visits for respiratory conditions in children increased after Guagua Pichincha volcanic eruptions in April 2000 in Quito, Ecuador observational study: time series analysis.

    Science.gov (United States)

    Naumova, Elena N; Yepes, Hugo; Griffiths, Jeffrey K; Sempértegui, Fernando; Khurana, Gauri; Jagai, Jyotsna S; Játiva, Edgar; Estrella, Bertha

    2007-07-24

    This study documented elevated rates of emergency room (ER) visits for acute upper and lower respiratory infections and asthma-related conditions in the children of Quito, Ecuador associated with the eruption of Guagua Pichincha in April of 2000. We abstracted 5169 (43% females) ER records with primary respiratory conditions treated from January 1-December 27, 2000 and examined the change in pediatric ER visits for respiratory conditions before, during, and after exposure events of April, 2000. We applied a Poisson regression model adapted to time series of cases for three non-overlapping disease categories: acute upper respiratory infection (AURI), acute lower respiratory infection (ALRI), and asthma-related conditions in boys and girls for three age groups: 0-4, 5-9, and 10-15 years. At the main pediatric medical facility, the Baca Ortiz Pediatric Hospital, the rate of emergency room (ER) visits due to respiratory conditions substantially increased in the three weeks after eruption (RR = 2.22, 95%CI = [1.95, 2.52] and RR = 1.72 95%CI = [1.49, 1.97] for lower and upper respiratory tract infections respectively. The largest impact of eruptions on respiratory distress was observed in children younger than 5 years (RR = 2.21, 95%CI = [1.79, 2.73] and RR = 2.16 95%CI = [1.67, 2.76] in boys and girls respectively). The rate of asthma and asthma-related diagnosis doubled during the period of volcano fumarolic activity (RR = 1.97, 95%CI = [1.19, 3.24]). Overall, 28 days of volcanic activity and ash releases resulted in 345 (95%CI = [241, 460]) additional ER visits due to respiratory conditions. The study has demonstrated strong relationship between ash exposure and respiratory effects in children.

  5. Time series analysis in the social sciences the fundamentals

    CERN Document Server

    Shin, Youseop

    2017-01-01

    Times Series Analysis in the Social Sciences is a practical and highly readable introduction written exclusively for students and researchers whose mathematical background is limited to basic algebra. The book focuses on fundamental elements of time series analysis that social scientists need to understand so they can employ time series analysis for their research and practice. Through step-by-step explanations and using monthly violent crime rates as case studies, this book explains univariate time series from the preliminary visual analysis through the modeling of seasonality, trends, and re

  6. The analysis of time series: an introduction

    National Research Council Canada - National Science Library

    Chatfield, Christopher

    1989-01-01

    .... A variety of practical examples are given to support the theory. The book covers a wide range of time-series topics, including probability models for time series, Box-Jenkins forecasting, spectral analysis, linear systems and system identification...

  7. Prediction and Geometry of Chaotic Time Series

    National Research Council Canada - National Science Library

    Leonardi, Mary

    1997-01-01

    This thesis examines the topic of chaotic time series. An overview of chaos, dynamical systems, and traditional approaches to time series analysis is provided, followed by an examination of state space reconstruction...

  8. Global Population Density Grid Time Series Estimates

    Data.gov (United States)

    National Aeronautics and Space Administration — Global Population Density Grid Time Series Estimates provide a back-cast time series of population density grids based on the year 2000 population grid from SEDAC's...

  9. Prognostic Factors of Returning to Work after Sick Leave due to Work-Related Common Mental Disorders: A One- and Three-Year Follow-Up Study.

    Science.gov (United States)

    Netterstrøm, Bo; Eller, Nanna Hurwitz; Borritz, Marianne

    2015-01-01

    The aim of this paper was to assess the prognostic factors of return to work (RTW) after one and three years among people on sick leave due to occupational stress. Methods. The study population comprised 223 completers on sick leave, who participated in a stress treatment program. Self-reported psychosocial work environment, life events during the past year, severity of the condition, occupational position, employment sector, marital status, and medication were assessed at baseline. RTW was assessed with data from a national compensation database (DREAM). Results. Self-reported high demands, low decision authority, low reward, low support from leaders and colleagues, bullying, high global symptom index, length of sick leave at baseline, and stressful negative life events during the year before baseline were associated with no RTW after one year. Low work ability and full-time sick leave at inclusion were predictors after three years too. Being single was associated with no RTW after three years. The type of treatment, occupational position, gender, age, and degree of depression were not associated with RTW after one or three years. Conclusion. The impact of the psychosocial work environment as predictor for RTW disappeared over time and only the severity of the condition was a predictor for RTW in the long run.

  10. Effective Feature Preprocessing for Time Series Forecasting

    DEFF Research Database (Denmark)

    Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

    2006-01-01

    Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...... series forecasting models....

  11. Do restrictive omnibus immigration laws reduce enrollment in public health insurance by Latino citizen children? A comparative interrupted time series study.

    Science.gov (United States)

    Allen, Chenoa D; McNeely, Clea A

    2017-10-01

    In the United States, there is concern that recent state laws restricting undocumented immigrants' rights could threaten access to Medicaid and the Children's Health Insurance Program (CHIP) for citizen children of immigrant parents. Of particular concern are omnibus immigration laws, state laws that include multiple provisions increasing immigration enforcement and restricting rights for undocumented immigrants. These laws could limit Medicaid/CHIP access for citizen children in immigrant families by creating misinformation about their eligibility and fostering fear and mistrust of government among immigrant parents. This study uses nationally-representative data from the National Health Interview Survey (2005-2014; n = 70,187) and comparative interrupted time series methods to assess whether passage of state omnibus immigration laws reduced access to Medicaid/CHIP for US citizen Latino children. We found that law passage did not reduce enrollment for children with noncitizen parents and actually resulted in temporary increases in coverage among Latino children with at least one citizen parent. These findings are surprising in light of prior research. We offer potential explanations for this finding and conclude with a call for future research to be expanded in three ways: 1) examine whether policy effects vary for children of undocumented parents, compared to children whose noncitizen parents are legally present; 2) examine the joint effects of immigration-related policies at different levels, from the city or county to the state to the federal; and 3) draw on the large social movements and political mobilization literature that describes when and how Latinos and immigrants push back against restrictive immigration laws. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. A time series study on the effects of heat on mortality and evaluation of heterogeneity into European and Eastern-Southern Mediterranean cities: results of EU CIRCE project.

    Science.gov (United States)

    Leone, Michela; D'Ippoliti, Daniela; De Sario, Manuela; Analitis, Antonis; Menne, Bettina; Katsouyanni, Klea; De' Donato, Francesca K; Basagana, Xavier; Salah, Afif Ben; Casimiro, Elsa; Dörtbudak, Zeynep; Iñiguez, Carmen; Peretz, Chava; Wolf, Tanja; Michelozzi, Paola

    2013-07-03

    The Mediterranean region is particularly vulnerable to the effect of summer temperature.Within the CIRCE project this time-series study aims to quantify for the first time the effect of summer temperature in Eastern-Southern Mediterranean cities and compared it with European cities around the Mediterranean basin, evaluating city characteristics that explain between-city heterogeneity. The city-specific effect of maximum apparent temperature (Tappmax) was assessed by Generalized Estimation Equations, assuming a linear threshold model. Then, city-specific estimates were included in a random effect meta-regression analysis to investigate the effect modification by several city characteristics. Heterogeneity in the temperature-mortality relationship was observed among cities. Thresholds recorded higher values in the warmest cities of Tunis (35.5°C) and Tel-Aviv (32.8°C) while the effect of Tappmax above threshold was greater in the European cities. In Eastern-Southern Mediterranean cities a higher effect was observed among younger age groups (0-14 in Tunis and 15-64 in Tel-Aviv and Istanbul) in contrast with the European cities where the elderly population was more vulnerable. Climate conditions explained most of the observed heterogeneity and among socio-demographic and economic characteristics only health expenditure and unemployment rate were identified as effect modifiers. The high vulnerability observed in the young populations in Eastern-Southern Mediterranean cities represent a major public health problem. Considering the large political and economic changes occurring in this region as well future temperature increase due to climate change, it is important to strengthen research and public health efforts in these Mediterranean countries.

  13. Proximal Neuromuscular Control Protects Against Hamstring Injuries in Male Soccer Players: A Prospective Study With Electromyography Time-Series Analysis During Maximal Sprinting.

    Science.gov (United States)

    Schuermans, Joke; Danneels, Lieven; Van Tiggelen, Damien; Palmans, Tanneke; Witvrouw, Erik

    2017-05-01

    With their unremittingly high incidence rate and detrimental functional repercussions, hamstring injuries remain a substantial problem in male soccer. Proximal neuromuscular control ("core stability") is considered to be of key importance in primary and secondary hamstring injury prevention, although scientific evidence and insights on the exact nature of the core-hamstring association are nonexistent at present. The muscle activation pattern throughout the running cycle would not differ between participants based on injury occurrence during follow-up. Case-control study; Level of evidence, 3. Sixty amateur soccer players participated in a multimuscle surface electromyography (sEMG) assessment during maximal acceleration to full-speed sprinting. Subsequently, hamstring injury occurrence was registered during a 1.5-season follow-up period. Hamstring, gluteal, and trunk muscle activity time series during the airborne and stance phases of acceleration were evaluated and statistically explored for a possible causal association with injury occurrence and absence from sport during follow-up. Players who did not experience a hamstring injury during follow-up had significantly higher amounts of gluteal muscle activity during the front swing phase ( P = .027) and higher amounts of trunk muscle activity during the backswing phase of sprinting ( P = .042). In particular, the risk of sustaining a hamstring injury during follow-up lowered by 20% and 6%, with a 10% increment in normalized muscle activity of the gluteus maximus during the front swing and the trunk muscles during the backswing, respectively ( P hamstring injury occurrence in male soccer players. Higher amounts of gluteal and trunk muscle activity during the airborne phases of sprinting were associated with a lower risk of hamstring injuries during follow-up. Hence, the present results provide a basis for improved, evidence-based rehabilitation and prevention, particularly focusing on increasing neuromuscular

  14. Towards Slow-Moving Landslide Monitoring by Integrating Multi-Sensor InSAR Time Series Datasets: The Zhouqu Case Study, China

    Directory of Open Access Journals (Sweden)

    Qian Sun

    2016-11-01

    Full Text Available Although the past few decades have witnessed the great development of Synthetic Aperture Radar Interferometry (InSAR technology in the monitoring of landslides, such applications are limited by geometric distortions and ambiguity of 1D Line-Of-Sight (LOS measurements, both of which are the fundamental weakness of InSAR. Integration of multi-sensor InSAR datasets has recently shown its great potential in breaking through the two limits. In this study, 16 ascending images from the Advanced Land Observing Satellite (ALOS and 18 descending images from the Environmental Satellite (ENVISAT have been integrated to characterize and to detect the slow-moving landslides in Zhouqu, China between 2008 and 2010. Geometric distortions are first mapped by using the imaging geometric parameters of the used SAR data and public Digital Elevation Model (DEM data of Zhouqu, which allow the determination of the most appropriate data assembly for a particular slope. Subsequently, deformation rates along respective LOS directions of ALOS ascending and ENVISAT descending tracks are estimated by conducting InSAR time series analysis with a Temporarily Coherent Point (TCP-InSAR algorithm. As indicated by the geometric distortion results, 3D deformation rates of the Xieliupo slope at the east bank of the Pai-lung River are finally reconstructed by joint exploiting of the LOS deformation rates from cross-heading datasets based on the surface–parallel flow assumption. It is revealed that the synergistic results of ALOS and ENVISAT datasets provide a more comprehensive understanding and monitoring of the slow-moving landslides in Zhouqu.

  15. Empathetic attitudes of undergraduate paramedic and nursing students towards four medical conditions: a three-year longitudinal study.

    Science.gov (United States)

    Williams, Brett; Boyle, Malcolm; Fielder, Chris

    2015-02-01

    In the healthcare context empathy is the cognitive ability to understand a patient's perspectives and experiences and to convey that understanding back to the patient. Some medical conditions are frequently stigmatised or otherwise detrimentally stereotyped with patients often describing healthcare practitioners as intolerant, prejudiced and discriminatory. The purpose of this study was to find how a group of paramedic students and nursing/paramedic double-degree students regard these types of patients and to note any changes that may occur as those students continued through their education. The 11-questions, 6-point Likert scale version of the Medical Condition Regard Scale was used in this prospective cross-sectional longitudinal study. This study included paramedic students enrolled in first, second, third and fourth year of an undergraduate paramedic or paramedic/nursing program from Monash University. A total of 554 students participated. Statistically significant differences were found between double-degree and single-degree students (pintellectual disability and attempted suicide. No statistically significant results were found for acute mental illness. This study has demonstrated significant differences in empathy between paramedic and nursing/paramedic double-degree students in regard to patients with these complex medical conditions. Paramedic/nursing students generally showed a positive change in empathy towards these complex patients by their third year of study; however, they also showed some alarming drops in empathy between second and third year. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. Clinical study of Tinea capitis in Northern Karnataka: A three-year experience at a single institute

    Directory of Open Access Journals (Sweden)

    Varadraj V Pai

    2013-01-01

    Full Text Available Background: Tinea capitis is a superficial fungal infection of the hair follicle of scalp. Most of the dermatophytosis do not have such age propensity as tinea capitis which almost invariably involves the paediatric age group. The exact incidence of tinea capitis is not known. This study is done in order to isolate the species variation in an area, to know the changing patterns of occurrence of different species and their association with clinical pattern Materials and Methods: All clinically diagnosed cases of tinea capitis which presented to our out patient department over a period of one year were included in the study. Results: 70 cases of Tinea capitis were studied. Discussion: Tinea capitis is a disease of prepubertal children with common in age group of 5- 15 years. The incidence varies from 0.5% to 10%. Most common presenting feature was alopecia.

  17. A Three-Year Study of Ichyoplankton in Coastal Plains Reaches of the Savannah River Site and its Tributaries

    Energy Technology Data Exchange (ETDEWEB)

    Martin, D.

    2007-03-05

    Altering flow regimes of rivers has large effects on native floras and faunas because native species are adapted to the natural flow regime, many species require lateral connectivity with floodplain habitat for feeding or spawning, and the change in regime often makes it possible for invasive species to replace natives (Bunn & Arthington 2002). Floodplain backwaters, both permanent and temporary, are nursery areas for age 0+ fish and stable isotope studies indicate that much of the productivity that supports fish larvae is autochthonous to these habitats (Herwig et al. 2004). Limiting access by fish to floodplain habitat for feeding, spawning and nursery habitat is one of the problems noted with dams that regulate flow in rivers and is considered to be important as an argument to remove dams and other flow regulating structures from rivers (Shuman 1995; Bednarek 2001). While there have been a number of studies in the literature about the use of floodplain habitat for fish reproduction (Copp 1989; Killgore & Baker 1996; Humphries, et al. 1999; Humphries and Lake 2000; Crain et al. 2004; King 2004) there have been only a few studies that examined this aspect of stream ecology in more than a cursory way. The study reported here was originally designed to determine whether the Department of Energy's (DOE) Savannah River Site was having a negative effect on fish reproduction in the Savannah River but its experimental design allowed examination of the interactions between the river, the floodplain and the tributaries entering the Savannah River across this floodplain. This study is larger in length of river covered than most in the literature and because of its landscape scale may be in important indicator of areas where further study is required.

  18. Burnout and psychiatric morbidity among medical students entering clinical training: a three year prospective questionnaire and interview-based study

    Directory of Open Access Journals (Sweden)

    Runeson Bo

    2007-04-01

    Full Text Available Abstract Background Mental distress among medical students is often reported. Burnout has not been studied frequently and studies using interviewer-rated diagnoses as outcomes are rarely employed. The objective of this prospective study of medical students was to examine clinically significant psychiatric morbidity and burnout at 3rd year of medical school, considering personality and study conditions measured at 1st year. Methods Questionnaires were sent to 127 first year medical students who were then followed-up at 3rd year of medical school. Eighty-one of 3rd year respondents participated in a diagnostic interview. Personality (HP5-i and Performance-based self-esteem (PBSE-scale were assessed at first year, Study conditions (HESI, Burnout (OLBI, Depression (MDI at 1st and 3rd years. Diagnostic interviews (MINI were used at 3rd year to assess psychiatric morbidity. High and low burnout at 3rd year was defined by cluster analysis. Logistic regressions were used to identify predictors of high burnout and psychiatric morbidity, controlling for gender. Results 98 (77% responded on both occasions, 80 (63% of these were interviewed. High burnout was predicted by Impulsivity trait, Depressive symptoms at 1st year and Financial concerns at 1st year. When controlling for 3rd year study conditions, Impulsivity and concurrent Workload remained. Of the interviewed sample 21 (27% had a psychiatric diagnosis, 6 of whom had sought help. Unadjusted analyses showed that psychiatric morbidity was predicted by high Performance-based self-esteem, Disengagement and Depression at 1st year, only the later remained significant in the adjusted analysis. Conclusion Psychiatric morbidity is common in medical students but few seek help. Burnout has individual as well as environmental explanations and to avoid it, organisational as well as individual interventions may be needed. Early signs of depressive symptoms in medical students may be important to address. Students

  19. What Is Not Working in Working Memory of Children with Literacy Disorders? Evidence from a Three-Year-Longitudinal Study

    Science.gov (United States)

    Fischbach, Anne; Könen, Tanja; Rietz, Chantal S.; Hasselhorn, Marcus

    2014-01-01

    The goals of this study were to explore the deficits in working memory associated with literacy disorders (i.e. developmental disorders of reading and/or spelling) and the developmental trajectories of these working memory deficits. The performance of 28 children with literacy disorders was compared to a non-disabled control group with the same…

  20. Maternal Employment and Child Cognitive Outcomes in the First Three Years of Life: The NICHD Study of Early Child Care.

    Science.gov (United States)

    Brooks-Gunn, Jeanne; Han, Wen-Jui; Waldfogel, Jane

    2002-01-01

    Examined data on 900 European American children from the NICHD Study of Early Child Care to explore links between maternal employment during the child's first year and child cognitive outcomes. Found that maternal employment by the child's ninth month related to lower school readiness scores at 36 months, with more pronounced effects for certain…

  1. Effects of Viewing Relational Aggression on Television on Aggressive Behavior in Adolescents: A Three-Year Longitudinal Study

    Science.gov (United States)

    Coyne, Sarah M.

    2016-01-01

    Most researchers on media and aggression have examined the behavioral effects of viewing physical aggression in the media. Conversely, in the current study, I examined longitudinal associations between viewing "relational aggression" on TV and subsequent aggressive behavior. Participants included 467 adolescents who completed a number of…

  2. Can job crafting reduce job boredom and increase work engagement? A three-year cross-lagged panel study

    NARCIS (Netherlands)

    Harju, Lotta K.; Hakanen, Jari J.; Schaufeli, Wilmar B.|info:eu-repo/dai/nl/073779563

    2016-01-01

    Building upon the Conservation of Resources (COR) theory, this longitudinal study examined whether job crafting behaviors (i.e. increasing structural and social job resources and increasing challenges) predict less job boredom and more work engagement. We also tested the reverse causation effects of

  3. The Prediction of Teacher Turnover Employing Time Series Analysis.

    Science.gov (United States)

    Costa, Crist H.

    The purpose of this study was to combine knowledge of teacher demographic data with time-series forecasting methods to predict teacher turnover. Moving averages and exponential smoothing were used to forecast discrete time series. The study used data collected from the 22 largest school districts in Iowa, designated as FACT schools. Predictions…

  4. Factors associated with Clostridium difficile infection: A nested case-control study in a three year prospective cohort.

    Science.gov (United States)

    Khanafer, Nagham; Vanhems, Philippe; Barbut, Frédéric; Luxemburger, Christine

    2017-04-01

    Clostridium difficile infection (CDI) is a serious medical condition that is associated with substantial morbidity and mortality. Identification of risk factors associated with CDI and prompt recognition of patients at risk is key to successfully preventing CDI. A 3-year prospective, observational, cohort study was conducted in a French university hospital and a nested case-control study was performed to identify risk factors for CDI. Inpatients aged 18 years or older, suffering from diarrhea suspected to be related to CDI, were asked to participate. A total of 945 patients were included, of which 233 cases had a confirmed CDI. CDI infection was more common in men (58.4%) (P = 0.04) compared with patients with diarrhea not related to C. difficile. Previous hospitalization (P infection control issues. In future, these "high-risk" patients may benefit from novel agents being developed to prevent CDI. Copyright © 2017 Elsevier Ltd. All rights reserved.

  5. Monitoring mangrove forests after aquaculture abandonment using time series of very high spatial resolution satellite images: A case study from the Perancak estuary, Bali, Indonesia.

    Science.gov (United States)

    Proisy, Christophe; Viennois, Gaëlle; Sidik, Frida; Andayani, Ariani; Enright, James Anthony; Guitet, Stéphane; Gusmawati, Niken; Lemonnier, Hugues; Muthusankar, Gowrappan; Olagoke, Adewole; Prosperi, Juliana; Rahmania, Rinny; Ricout, Anaïs; Soulard, Benoit; Suhardjono

    2018-06-01

    Revegetation of abandoned aquaculture regions should be a priority for any integrated coastal zone management (ICZM). This paper examines the potential of a matchless time series of 20 very high spatial resolution (VHSR) optical satellite images acquired for mapping trends in the evolution of mangrove forests from 2001 to 2015 in an estuary fragmented into aquaculture ponds. Evolution of mangrove extent was quantified through robust multitemporal analysis based on supervised image classification. Results indicated that mangroves are expanding inside and outside ponds and over pond dykes. However, the yearly expansion rate of vegetation cover greatly varied between replanted ponds. Ground truthing showed that only Rhizophora species had been planted, whereas natural mangroves consist of Avicennia and Sonneratia species. In addition, the dense Rhizophora plantations present very low regeneration capabilities compared with natural mangroves. Time series of VHSR images provide comprehensive and intuitive level of information for the support of ICZM. Copyright © 2017 Elsevier Ltd. All rights reserved.

  6. Cortical thickness in adolescent marijuana and alcohol users: A three-year prospective study from adolescence to young adulthood

    Directory of Open Access Journals (Sweden)

    Joanna Jacobus

    2015-12-01

    Full Text Available Studies suggest marijuana impacts gray and white matter neural tissue development, however few prospective studies have determined the relationship between cortical thickness and cannabis use spanning adolescence to young adulthood. This study aimed to understand how heavy marijuana use influences cortical thickness trajectories across adolescence. Subjects were adolescents with heavy marijuana use and concomitant alcohol use (MJ + ALC, n = 30 and controls (CON, n = 38 with limited substance use histories. Participants underwent magnetic resonance imaging and comprehensive substance use assessment at three independent time points. Repeated measures analysis of covariance was used to look at main effects of group, time, and Group × Time interactions on cortical thickness. MJ + ALC showed thicker cortical estimates across the brain (23 regions, particularly in frontal and parietal lobes (ps < .05. More cumulative marijuana use was associated with increased thickness estimates by 3-year follow-up (ps < .05. Heavy marijuana use during adolescence and into young adulthood may be associated with altered neural tissue development and interference with neuromaturation that can have neurobehavioral consequences. Continued follow-up of adolescent marijuana users will help understand ongoing neural changes that are associated with development of problematic use into adulthood, as well as potential for neural recovery with cessation of use.

  7. Cortical thickness in adolescent marijuana and alcohol users: A three-year prospective study from adolescence to young adulthood.

    Science.gov (United States)

    Jacobus, Joanna; Squeglia, Lindsay M; Meruelo, Alejandro D; Castro, Norma; Brumback, Ty; Giedd, Jay N; Tapert, Susan F

    2015-12-01

    Studies suggest marijuana impacts gray and white matter neural tissue development, however few prospective studies have determined the relationship between cortical thickness and cannabis use spanning adolescence to young adulthood. This study aimed to understand how heavy marijuana use influences cortical thickness trajectories across adolescence. Subjects were adolescents with heavy marijuana use and concomitant alcohol use (MJ+ALC, n=30) and controls (CON, n=38) with limited substance use histories. Participants underwent magnetic resonance imaging and comprehensive substance use assessment at three independent time points. Repeated measures analysis of covariance was used to look at main effects of group, time, and Group × Time interactions on cortical thickness. MJ+ALC showed thicker cortical estimates across the brain (23 regions), particularly in frontal and parietal lobes (psadolescence and into young adulthood may be associated with altered neural tissue development and interference with neuromaturation that can have neurobehavioral consequences. Continued follow-up of adolescent marijuana users will help understand ongoing neural changes that are associated with development of problematic use into adulthood, as well as potential for neural recovery with cessation of use. Published by Elsevier Ltd.

  8. Mental health status of Sri Lanka Navy personnel three years after end of combat operations: a follow up study.

    Directory of Open Access Journals (Sweden)

    Raveen Hanwella

    Full Text Available The main aim of this study was to assess the mental health status of the Navy Special Forces and regular forces three and a half years after the end of combat operations in mid 2009, and compare it with the findings in 2009. This cross sectional study was carried out in the Sri Lanka Navy (SLN, three and a half years after the end of combat operations. Representative samples of SLN Special Forces and regular forces deployed in combat areas were selected using simple random sampling. Only personnel who had served continuously in combat areas during the one year period prior to the end of combat operations were included in the study. The sample consisted of 220 Special Forces and 275 regular forces personnel. Compared to regular forces a significantly higher number of Special Forces personnel had experienced potentially traumatic events. Compared to the period immediately after end of combat operations, in the Special Forces, prevalence of psychological distress and fatigue showed a marginal increase while hazardous drinking and multiple physical symptoms showed a marginal decrease. In the regular forces, the prevalence of psychological distress, fatigue and multiple somatic symptoms declined and prevalence of hazardous drinking increased from 16.5% to 25.7%. During the same period prevalence of smoking doubled in both Special Forces and regular forces. Prevalence of PTSD reduced from 1.9% in Special Forces to 0.9% and in the regular forces from 2.07% to 1.1%. Three and a half years after the end of combat operations mental health problems have declined among SLN regular forces while there was no significant change among Special Forces. Hazardous drinking among regular forces and smoking among both Special Forces and regular forces have increased.

  9. Mental health status of Sri Lanka Navy personnel three years after end of combat operations: a follow up study.

    Science.gov (United States)

    Hanwella, Raveen; Jayasekera, Nicholas E L W; de Silva, Varuni A

    2014-01-01

    The main aim of this study was to assess the mental health status of the Navy Special Forces and regular forces three and a half years after the end of combat operations in mid 2009, and compare it with the findings in 2009. This cross sectional study was carried out in the Sri Lanka Navy (SLN), three and a half years after the end of combat operations. Representative samples of SLN Special Forces and regular forces deployed in combat areas were selected using simple random sampling. Only personnel who had served continuously in combat areas during the one year period prior to the end of combat operations were included in the study. The sample consisted of 220 Special Forces and 275 regular forces personnel. Compared to regular forces a significantly higher number of Special Forces personnel had experienced potentially traumatic events. Compared to the period immediately after end of combat operations, in the Special Forces, prevalence of psychological distress and fatigue showed a marginal increase while hazardous drinking and multiple physical symptoms showed a marginal decrease. In the regular forces, the prevalence of psychological distress, fatigue and multiple somatic symptoms declined and prevalence of hazardous drinking increased from 16.5% to 25.7%. During the same period prevalence of smoking doubled in both Special Forces and regular forces. Prevalence of PTSD reduced from 1.9% in Special Forces to 0.9% and in the regular forces from 2.07% to 1.1%. Three and a half years after the end of combat operations mental health problems have declined among SLN regular forces while there was no significant change among Special Forces. Hazardous drinking among regular forces and smoking among both Special Forces and regular forces have increased.

  10. A Three-Year Longitudinal Study of Reading and Spelling Difficulty in Chinese Developmental Dyslexia: The Matter of Morphological Awareness.

    Science.gov (United States)

    Tong, Xiuhong; McBride, Catherine; Lo, Jason Chor Ming; Shu, Hua

    2017-11-01

    In the present study, we used a three-time point longitudinal design to investigate the associations of morphological awareness to word reading and spelling in a small group of those with and without dyslexia taken from a larger sample of 164 Hong Kong Chinese children who remained in a longitudinal study across ages 6, 7 and 8. Among those 164 children, 15 had been diagnosed as having dyslexia by professional psychologists, and 15 other children manifested average reading ability and had been randomly selected from the sample for comparison. All children were administered a battery of tasks including Chinese character recognition, word dictation, morphological awareness, phonological awareness and rapid automatized naming. Multivariate analysis of variance and predictive discriminate analysis were performed to examine whether the dyslexic children showed differences in the cognitive-linguistic tasks in comparison with controls. Results suggested that the dyslexic groups had poorer performance in morphological awareness and RAN across all 3 years. However, phonological awareness was not stable in distinguishing the groups. Findings suggest that morphological awareness is a relatively strong correlate of spelling difficulties in Chinese, but phonological awareness is not. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  11. The relationship between oral and written narratives: A three-year longitudinal study of narrative cohesion, coherence, and structure.

    Science.gov (United States)

    Pinto, Giuliana; Tarchi, Christian; Bigozzi, Lucia

    2015-12-01

    The relationship between oral language and the writing process at early acquisition stages and the ways the former can enhance or limit the latter has not been researched extensively. The predictive relationship between kindergarten oral narrative competence and the first- and second-grade written narrative competence was explored in a 3-year longitudinal study. Among the first and second graders, the relationship between orthographic competence and narrative competence in written productions was also analysed. One hundred and nine Italian children participated in this study. Kindergarteners produced an oral narrative, whereas the first and second graders produced a written narrative. The oral and written narratives were analysed in terms of cohesion, coherence, and structure. The first-grade orthographic competence was assessed via a dictation task. Multiple linear regression and mediational analyses were performed. Kindergarten oral narrative competence affected the first- and second-grade written narrative competence via a mediational effect of orthographic competence. The results suggest the importance of practicing oral narrative competence in kindergarten and first grade and the value of composition quality independent of orthographic text accuracy. © 2015 The British Psychological Society.

  12. Kolmogorov Space in Time Series Data

    OpenAIRE

    Kanjamapornkul, K.; Pinčák, R.

    2016-01-01

    We provide the proof that the space of time series data is a Kolmogorov space with $T_{0}$-separation axiom using the loop space of time series data. In our approach we define a cyclic coordinate of intrinsic time scale of time series data after empirical mode decomposition. A spinor field of time series data comes from the rotation of data around price and time axis by defining a new extradimension to time series data. We show that there exist hidden eight dimensions in Kolmogorov space for ...

  13. Time Series Analysis and Forecasting by Example

    CERN Document Server

    Bisgaard, Soren

    2011-01-01

    An intuition-based approach enables you to master time series analysis with ease Time Series Analysis and Forecasting by Example provides the fundamental techniques in time series analysis using various examples. By introducing necessary theory through examples that showcase the discussed topics, the authors successfully help readers develop an intuitive understanding of seemingly complicated time series models and their implications. The book presents methodologies for time series analysis in a simplified, example-based approach. Using graphics, the authors discuss each presented example in

  14. Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016

    Science.gov (United States)

    Peltoniemi, Mikko; Aurela, Mika; Böttcher, Kristin; Kolari, Pasi; Loehr, John; Karhu, Jouni; Linkosalmi, Maiju; Melih Tanis, Cemal; Tuovinen, Juha-Pekka; Nadir Arslan, Ali

    2018-01-01

    In recent years, monitoring of the status of ecosystems using low-cost web (IP) or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1-3 cameras. Here, we document the network, basic camera information and access to images in the permanent data repository (http://www.zenodo.org/communities/phenology_camera/). Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 (https://doi.org/10.5281/zenodo.1066862). Additionally, we present an example of a colour index time series derived from images from two contrasting sites.

  15. Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study

    Directory of Open Access Journals (Sweden)

    Alessandro Chiaudani

    2017-11-01

    Full Text Available In this research, univariate and bivariate statistical methods were applied to rainfall, river and piezometric level datasets belonging to 24-year time series (1986–2009. These methods, which often are used to understand the effects of precipitation on rivers and karstic springs discharge, have been used to assess piezometric level response to rainfall and river level fluctuations in a porous aquifer. A rain gauge, a river level gauge and three wells, located in Central Italy along the lower Pescara River valley in correspondence of its important alluvial aquifer, provided the data. Statistical analysis has been used within a known hydrogeological framework, which has been refined by mean of a photo-interpretation and a GPS survey. Water–groundwater relationships were identified following the autocorrelation and cross-correlation analyses. Spectral analysis and mono-fractal features of time series were assessed to provide information on multi-year variability, data distributions, their fractal dimension and the distribution return time within the historical time series. The statistical–mathematical results were interpreted through fieldwork that identified distinct groundwater flowpaths within the aquifer and enabled the implementation of a conceptual model, improving the knowledge on water resources management tools.

  16. Webcam network and image database for studies of phenological changes of vegetation and snow cover in Finland, image time series from 2014 to 2016

    Directory of Open Access Journals (Sweden)

    M. Peltoniemi

    2018-01-01

    Full Text Available In recent years, monitoring of the status of ecosystems using low-cost web (IP or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1–3 cameras. Here, we document the network, basic camera information and access to images in the permanent data repository (http://www.zenodo.org/communities/phenology_camera/. Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 (https://doi.org/10.5281/zenodo.1066862. Additionally, we present an example of a colour index time series derived from images from two contrasting sites.

  17. Three-Year Outcomes of a Canadian Multicenter Study of Accelerated Partial Breast Irradiation Using Conformal Radiation Therapy

    Energy Technology Data Exchange (ETDEWEB)

    Berrang, Tanya S., E-mail: tberrang@bccancer.bc.ca [British Columbia Cancer Agency-Vancouver Island, BC (Canada); University of British Columbia, BC (Canada); Olivotto, Ivo [British Columbia Cancer Agency-Vancouver Island, BC (Canada); University of British Columbia, BC (Canada); Kim, Do-Hoon [Juravinski Cancer Centre, Ontario (Canada); McMaster University, Ontario (Canada); Nichol, Alan [British Columbia Cancer Agency-Vancouver Centre, BC (Canada); University of British Columbia, BC (Canada); Cho, B.C. John [Princess Margaret Hospital, Ontario (Canada); University of Toronto, Ontario (Canada); Mohamed, Islam G. [British Columbia Cancer Agency-Southern Interior, BC (Canada); University of British Columbia, BC (Canada); Parhar, Tarnjit [British Columbia Cancer Agency-Vancouver Centre, BC (Canada); University of British Columbia, BC (Canada); Wright, J.R. [Juravinski Cancer Centre, Ontario (Canada); McMaster University, Ontario (Canada); Truong, Pauline [British Columbia Cancer Agency-Vancouver Island, BC (Canada); University of British Columbia, BC (Canada); Tyldesley, Scott [British Columbia Cancer Agency-Vancouver Centre, BC (Canada); University of British Columbia, BC (Canada); Sussman, Jonathan [Juravinski Cancer Centre, Ontario (Canada); McMaster University, Ontario (Canada); Wai, Elaine [British Columbia Cancer Agency-Vancouver Island, BC (Canada); University of British Columbia, BC (Canada); Whelan, Tim [Juravinski Cancer Centre, Ontario (Canada); McMaster University, Ontario (Canada)

    2011-12-01

    Purpose: To report 3-year toxicity, cosmesis, and efficacy of a multicenter study of external beam, accelerated partial breast irradiation (APBI) for early-stage breast cancer. Methods and Materials: Between March 2005 and August 2006, 127 women aged {>=}40 years with ductal carcinoma in situ or node-negative invasive breast cancer {<=}3 cm in diameter, treated with breast-conserving surgery achieving negative margins, were accrued to a prospective study involving five Canadian cancer centers. Women meeting predefined dose constraints were treated with APBI using 3 to 5 photon beams, delivering 35 to 38.5 Gy in 10 fractions, twice a day, over 1 week. Patients were assessed for treatment-related toxicities, cosmesis, and efficacy before APBI and at specified time points for as long as 3 years after APBI. Results: 104 women had planning computed tomography scans showing visible seromas, met dosimetric constraints, and were treated with APBI to doses of 35 Gy (n = 9), 36 Gy (n = 33), or 38.5 Gy (n = 62). Eighty-seven patients were evaluated with minimum 3-year follow-up after APBI. Radiation dermatitis, breast edema, breast induration, and fatigue decreased from baseline levels or stabilized by the 3-year follow-up. Hypopigmentation, hyperpigmentation, breast pain, and telangiectasia slightly increased from baseline levels. Most toxicities at 3 years were Grade 1. Only 1 patient had a Grade 3 toxicity with telangiectasia in a skin fold inside the 95% isodose. Cosmesis was good to excellent in 86% (89/104) of women at baseline and 82% (70/85) at 3 years. The 3-year disease-free survival was 97%, with only one local recurrence that occurred in a different quadrant away from the treated site and two distant recurrences. Conclusions: At 3 years, toxicity and cosmesis were acceptable, and local control and disease-free survival were excellent, supporting continued accrual to randomized APBI trials.

  18. Neuropsychological performance in adolescent marijuana users with co-occurring alcohol use: A three-year longitudinal study.

    Science.gov (United States)

    Jacobus, Joanna; Squeglia, Lindsay M; Infante, M Alejandra; Castro, Norma; Brumback, Ty; Meruelo, Alejandro D; Tapert, Susan F

    2015-11-01

    The effect of adolescent marijuana use on brain development remains unclear despite relaxing legal restrictions, decreased perceived harm, and increasing use rates among youth. The aim of this 3-year prospective study was to evaluate the long-term neurocognitive effects of adolescent marijuana use. Adolescent marijuana users with concomitant alcohol use (MJ + ALC, n = 49) and control teens with limited substance use histories (CON, n = 59) were given neuropsychological and substance use assessments at project baseline, when they were ages 16-19. They were then reassessed 18 and 36 months later. Changes in neuropsychological measures were evaluated with repeated measures analysis of covariance (ANCOVA), controlling for lifetime alcohol use, and examined the effects of group, time, and group by time interactions on cognitive functioning. MJ + ALC users performed significantly worse than controls, across time points, in the domains of complex attention, memory, processing speed, and visuospatial functioning (ps marijuana use onset was associated with poorer processing speed and executive functioning by the 3-year follow-up (ps ≤.02). Frequent marijuana use throughout adolescence and into young adulthood appeared linked to worsened cognitive performance. Earlier age of onset appears to be associated with poorer neurocognitive outcomes that emerge by young adulthood, providing further support for the notion that the brain may be uniquely sensitive to frequent marijuana exposure during the adolescent phase of neurodevelopment. Continued follow-up of adolescent marijuana users will determine the extent of neural recovery that may occur if use abates. (c) 2015 APA, all rights reserved).

  19. A three year retrospective study on seroprevalence of syphilis among pregnant women at Gondar University Teaching Hospital, Ethiopia.

    Science.gov (United States)

    Assefa, Abate

    2014-03-01

    Sexually transmitted infections (STIs) are a serious public health problem in low income countries, including Ethiopia. Syphilis caused by Treponema pallidum remains a major cause of reproductive morbidity and poor pregnancy outcomes in low income countries. Stillbirth, perinatal death, serious neonatal infection and low-birth weight babies are common among seropositive mothers. To assess the seroprevalence of syphilis and risk factor correlates of this infection at Gondar University Teaching Hospital, Ethiopia. The study was done on 2385 pregnant women attending the antenatal care clinic (ANC) from January 2009 to December 2011. Data was abstracted from the antenatal care clinic medical database. Chi-square test was used, using SPSS version 16 and significance level was chosen at 0.05 level with a two-tailed test. Of the total, 69(2. 9%) of pregnant women were confirmed as seropositive for syphilis. Pregnant women with an age group of 21-25 years of old were the most seropositive (3.4%), followed by 26-30 years of old (3.1%). The prevalence of syphilis infection was 3.2% in urban and 2.2% in rural pregnant women. Relatively high prevalence of syphilis infection were identified among students (4.2%) followed by governmental employees (3.8%). The seroprevalence of syphilis among pregnant women attending ANC is declining. However, syphilis is more prevalent in the young and urban pregnant women. Emphasis on education to young people on STI risk behavioral change and partner follow up and notification for exposure to syphilis and treatment should be given.

  20. Estimating High-Dimensional Time Series Models

    DEFF Research Database (Denmark)

    Medeiros, Marcelo C.; Mendes, Eduardo F.

    We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume both the number of covariates in the model and candidate variables can increase with the number of observations and the number of candidate variables is, possibly......, larger than the number of observations. We show the adaLASSO consistently chooses the relevant variables as the number of observations increases (model selection consistency), and has the oracle property, even when the errors are non-Gaussian and conditionally heteroskedastic. A simulation study shows...

  1. Inverse statistical approach in heartbeat time series

    International Nuclear Information System (INIS)

    Ebadi, H; Shirazi, A H; Mani, Ali R; Jafari, G R

    2011-01-01

    We present an investigation on heart cycle time series, using inverse statistical analysis, a concept borrowed from studying turbulence. Using this approach, we studied the distribution of the exit times needed to achieve a predefined level of heart rate alteration. Such analysis uncovers the most likely waiting time needed to reach a certain change in the rate of heart beat. This analysis showed a significant difference between the raw data and shuffled data, when the heart rate accelerates or decelerates to a rare event. We also report that inverse statistical analysis can distinguish between the electrocardiograms taken from healthy volunteers and patients with heart failure

  2. Improving Neuromuscular Monitoring and Reducing Residual Neuromuscular Blockade With E-Learning: Protocol for the Multicenter Interrupted Time Series INVERT Study.

    Science.gov (United States)

    Thomsen, Jakob Louis Demant; Mathiesen, Ole; Hägi-Pedersen, Daniel; Skovgaard, Lene Theil; Østergaard, Doris; Engbaek, Jens; Gätke, Mona Ring

    2017-10-06

    Muscle relaxants facilitate endotracheal intubation under general anesthesia and improve surgical conditions. Residual neuromuscular blockade occurs when the patient is still partially paralyzed when awakened after surgery. The condition is associated with subjective discomfort and an increased risk of respiratory complications. Use of an objective neuromuscular monitoring device may prevent residual block. Despite this, many anesthetists refrain from using the device. Efforts to increase the use of objective monitoring are time consuming and require the presence of expert personnel. A neuromuscular monitoring e-learning module might support consistent use of neuromuscular monitoring devices. The aim of the study is to assess the effect of a neuromuscular monitoring e-learning module on anesthesia staff's use of objective neuromuscular monitoring and the incidence of residual neuromuscular blockade in surgical patients at 6 Danish teaching hospitals. In this interrupted time series study, we are collecting data repeatedly, in consecutive 3-week periods, before and after the intervention, and we will analyze the effect using segmented regression analysis. Anesthesia departments in the Zealand Region of Denmark are included, and data from all patients receiving a muscle relaxant are collected from the anesthesia information management system MetaVision. We will assess the effect of the module on all levels of potential effect: staff's knowledge and skills, patient care practice, and patient outcomes. The primary outcome is use of neuromuscular monitoring in patients according to the type of muscle relaxant received. Secondary outcomes include last recorded train-of-four value, administration of reversal agents, and time to discharge from the postanesthesia care unit as well as a multiple-choice test to assess knowledge. The e-learning module was developed based on a needs assessment process, including focus group interviews, surveys, and expert opinions. The e

  3. Short-term exposure to fine and coarse particles and mortality: A multicity time-series study in East Asia

    International Nuclear Information System (INIS)

    Lee, Hyewon; Honda, Yasushi; Hashizume, Masahiro; Guo, Yue Leon; Wu, Chang-Fu; Kan, Haidong; Jung, Kweon; Lim, Youn-Hee; Yi, Seungmuk; Kim, Ho

    2015-01-01

    Few studies on size-specific health effects of particulate matter have been conducted in Asia. We examined the association between both fine and coarse particles (PM_2_._5 and PM_1_0_−_2_._5) and mortality across 11 East Asian cities from 4 countries (Korea, Japan, Taiwan, and China). We performed a two-stage analysis: we generated city-specific estimates using a time-series analysis with a generalized additive model (Quasi-Poisson distribution), and estimated the overall effects by conducting a meta-analysis. Each 10−μg/m"3 increase in PM_2_._5 (lag01) was associated with an increase of 0.38% (95% confidence interval = 0.21%–0.55%) in all causes mortality, 0.96% (0.46%–1.46%) in cardiovascular mortality, and 1% (0.23%–1.78%) in respiratory mortality. Each 10−μg/m"3 increase in PM_1_0_−_2_._5 (lag01) was associated with cardiovascular mortality (0.69%, [0.05%–1.33%]), although this association attenuated after controlling for other pollutants, especially PM_2_._5. Increased mortality was associated with increasing PM_2_._5 and PM_1_0_−_2_._5 concentrations over 11 East Asian cities. - Highlights: • Few studies on size-specific health effects of PM have been conducted in East Asia. • We estimated size-specific PM effects on mortality over 11 East Asian cities. • Both fine and coarse particles were associated with mortality in East Asian cites. • Effect estimates for fine particles were higher than those for coarse particles. - Short-term exposure to PM_2_._5 and PM_1_0_−_2_._5 was associated with an increased risk of mortality in East Asian cities, and PM_2_._5 effect estimates were higher than PM_1_0_−_2_._5.

  4. Metagenomics meets time series analysis: unraveling microbial community dynamics

    NARCIS (Netherlands)

    Faust, K.; Lahti, L.M.; Gonze, D.; Vos, de W.M.; Raes, J.

    2015-01-01

    The recent increase in the number of microbial time series studies offers new insights into the stability and dynamics of microbial communities, from the world's oceans to human microbiota. Dedicated time series analysis tools allow taking full advantage of these data. Such tools can reveal periodic

  5. Small Sample Properties of Bayesian Multivariate Autoregressive Time Series Models

    Science.gov (United States)

    Price, Larry R.

    2012-01-01

    The aim of this study was to compare the small sample (N = 1, 3, 5, 10, 15) performance of a Bayesian multivariate vector autoregressive (BVAR-SEM) time series model relative to frequentist power and parameter estimation bias. A multivariate autoregressive model was developed based on correlated autoregressive time series vectors of varying…

  6. Time series prediction of apple scab using meteorological ...

    African Journals Online (AJOL)

    A new prediction model for the early warning of apple scab is proposed in this study. The method is based on artificial intelligence and time series prediction. The infection period of apple scab was evaluated as the time series prediction model instead of summation of wetness duration. Also, the relations of different ...

  7. Measurements of spatial population synchrony: influence of time series transformations.

    Science.gov (United States)

    Chevalier, Mathieu; Laffaille, Pascal; Ferdy, Jean-Baptiste; Grenouillet, Gaël

    2015-09-01

    Two mechanisms have been proposed to explain spatial population synchrony: dispersal among populations, and the spatial correlation of density-independent factors (the "Moran effect"). To identify which of these two mechanisms is driving spatial population synchrony, time series transformations (TSTs) of abundance data have been used to remove the signature of one mechanism, and highlight the effect of the other. However, several issues with TSTs remain, and to date no consensus has emerged about how population time series should be handled in synchrony studies. Here, by using 3131 time series involving 34 fish species found in French rivers, we computed several metrics commonly used in synchrony studies to determine whether a large-scale climatic factor (temperature) influenced fish population dynamics at the regional scale, and to test the effect of three commonly used TSTs (detrending, prewhitening and a combination of both) on these metrics. We also tested whether the influence of TSTs on time series and population synchrony levels was related to the features of the time series using both empirical and simulated time series. For several species, and regardless of the TST used, we evidenced a Moran effect on freshwater fish populations. However, these results were globally biased downward by TSTs which reduced our ability to detect significant signals. Depending on the species and the features of the time series, we found that TSTs could lead to contradictory results, regardless of the metric considered. Finally, we suggest guidelines on how population time series should be processed in synchrony studies.

  8. Effectiveness of anonymised information sharing and use in health service, police, and local government partnership for preventing violence related injury: experimental study and time series analysis

    Science.gov (United States)

    Florence, Curtis; Brennan, Iain; Simon, Thomas

    2011-01-01

    Objective To evaluate the effectiveness of anonymised information sharing to prevent injury related to violence. Design Experimental study and time series analysis of a prototype community partnership between the health service, police, and local government partners designed to prevent violence. Setting Cardiff, Wales, and 14 comparison cities designated “most similar” by the Home Office in England and Wales. Intervention After a 33 month development period, anonymised data relevant to violence prevention (precise violence location, time, days, and weapons) from patients attending emergency departments in Cardiff and reporting injury from violence were shared over 51 months with police and local authority partners and used to target resources for violence prevention. Main outcome measures Health service records of hospital admissions related to violence and police records of woundings and less serious assaults in Cardiff and other cities after adjustment for potential confounders. Results Information sharing and use were associated with a substantial and significant reduction in hospital admissions related to violence. In the intervention city (Cardiff) rates fell from seven to five a month per 100 000 population compared with an increase from five to eight in comparison cities (adjusted incidence rate ratio 0.58, 95% confidence interval 0.49 to 0.69). Average rate of woundings recorded by the police changed from 54 to 82 a month per 100 000 population in Cardiff compared with an increase from 54 to 114 in comparison cities (adjusted incidence rate ratio 0.68, 0.61 to 0.75). There was a significant increase in less serious assaults recorded by the police, from 15 to 20 a month per 100 000 population in Cardiff compared with a decrease from 42 to 33 in comparison cities (adjusted incidence rate ratio 1.38, 1.13 to 1.70). Conclusion An information sharing partnership between health services, police, and local government in Cardiff, Wales, altered policing

  9. Socioeconomic inequalities in adolescent health 2002-2010: a time-series analysis of 34 countries participating in the Health Behaviour in School-aged Children study.

    Science.gov (United States)

    Elgar, Frank J; Pförtner, Timo-Kolja; Moor, Irene; De Clercq, Bart; Stevens, Gonneke W J M; Currie, Candace

    2015-05-23

    Information about trends in adolescent health inequalities is scarce, especially at an international level. We examined secular trends in socioeconomic inequality in five domains of adolescent health and the association of socioeconomic inequality with national wealth and income inequality. We undertook a time-series analysis of data from the Health Behaviour in School-aged Children study, in which cross-sectional surveys were done in 34 North American and European countries in 2002, 2006, and 2010 (pooled n 492,788). We used individual data for socioeconomic status (Health Behaviour in School-aged Children Family Affluence Scale) and health (days of physical activity per week, body-mass index Z score [zBMI], frequency of psychological and physical symptoms on 0-5 scale, and life satisfaction scored 0-10 on the Cantril ladder) to examine trends in health and socioeconomic inequalities in health. We also investigated whether international differences in health and health inequalities were associated with per person income and income inequality. From 2002 to 2010, average levels of physical activity (3·90 to 4·08 days per week; pInequalities between socioeconomic groups increased in physical activity (-0·79 to -0·83 days per week difference between most and least affluent groups; p=0·0008), zBMI (0·15 to 0·18; pinequality fall during this period (-0·98 to -0·95; p=0·0198). Internationally, the higher the per person income, the better and more equal health was in terms of physical activity (0·06 days per SD increase in income; pincome inequality uniquely related to fewer days of physical activity (-0·05 days; p=0·0295), higher zBMI (0·06; pinequalities between socioeconomic groups in psychological (0·13; p=0·0080) and physical (0·07; p=0·0022) symptoms, and life satisfaction (-0·10; p=0·0092). Socioeconomic inequality has increased in many domains of adolescent health. These trends coincide with unequal distribution of income between rich and poor

  10. Effectiveness of employer financial incentives in reducing time to report worker injury: an interrupted time series study of two Australian workers' compensation jurisdictions.

    Science.gov (United States)

    Lane, Tyler J; Gray, Shannon; Hassani-Mahmooei, Behrooz; Collie, Alex

    2018-01-05

    Early intervention following occupational injury can improve health outcomes and reduce the duration and cost of workers' compensation claims. Financial early reporting incentives (ERIs) for employers may shorten the time between injury and access to compensation benefits and services. We examined ERI effect on time spent in the claim lodgement process in two Australian states: South Australia (SA), which introduced them in January 2009, and Tasmania (TAS), which introduced them in July 2010. Using administrative records of 1.47 million claims lodged between July 2006 and June 2012, we conducted an interrupted time series study of ERI impact on monthly median days in the claim lodgement process. Time periods included claim reporting, insurer decision, and total time. The 18-month gap in implementation between the states allowed for a multiple baseline design. In SA, we analysed periods within claim reporting: worker and employer reporting times (similar data were not available in TAS). To account for external threats to validity, we examined impact in reference to a comparator of other Australian workers' compensation jurisdictions. Total time in the process did not immediately change, though trend significantly decreased in both jurisdictions (SA: -0.36 days per month, 95% CI -0.63 to -0.09; TAS: 0.35, -0.50 to -0.20). Claim reporting time also decreased in both (SA: -1.6 days, -2.4 to -0.8; TAS: -5.4, -7.4 to -3.3). In TAS, there was a significant increase in insurer decision time (4.6, 3.9 to 5.4) and a similar but non-significant pattern in SA. In SA, worker reporting time significantly decreased (-4.7, -5.8 to -3.5), but employer reporting time did not (-0.3, -0.8 to 0.2). The results suggest that ERIs reduced claim lodgement time and, in the long-term, reduced total time in the claim lodgement process. However, only worker reporting time significantly decreased in SA, indicating that ERIs may not have shortened the process through the intended target of

  11. Are Anxiety and Depression Just as Stable as Personality During Late Adolescence? Results From a Three-Year Longitudinal Latent Variable Study

    Science.gov (United States)

    Prenoveau, Jason M.; Craske, Michelle G.; Zinbarg, Richard E.; Mineka, Susan; Rose, Raphael D.; Griffith, James W.

    2012-01-01

    Although considerable evidence shows that affective symptoms and personality traits demonstrate moderate to high relative stabilities during adolescence and early adulthood, there has been little work done to examine differential stability among these constructs or to study the manner in which the stability of these constructs is expressed. The present study used a three-year longitudinal design in an adolescent/young adult sample to examine the stability of depression symptoms, social phobia symptoms, specific phobia symptoms, neuroticism, and extraversion. When considering one-, two-, and three-year durations, anxiety and personality stabilities were generally similar and typically greater than the stability of depression. Comparison of various representations of a latent variable trait-state-occasion (TSO) model revealed that whereas the full TSO model was the best representation for depression, a trait stability model was the most parsimonious of the best-fitting models for the anxiety and personality constructs. Over three years, the percentages of variance explained by the trait component for the anxiety and personality constructs (73– 84%) were significantly greater than that explained by the trait component for depression (46%). These findings indicate that symptoms of depression are more episodic in nature, whereas symptoms of anxiety are more similar to personality variables in their expression of stability. PMID:21604827

  12. Clinical Evaluation of Efficacy and Performance of All-Poly Tibial Freedom® Total Knee System for Treating Osteoarthritis Patients: Three-Year Follow Up Study.

    Science.gov (United States)

    Singh, Avatar; Singh, Kanwar Kulwinder

    2017-09-01

    Advancement in technology in terms of design and building materials has made Total Knee Replacement (TKR) a highly effective, safe, and predictable orthopedic procedure. To review the clinical outcomes for efficacy and performance of Freedom Total Knee System for the management of Osteoarthritis (OA), at a minimum of three years follow up. For this retrospective, post-marketing study, clinical data of patients treated with Freedom Total Knee System was retrieved from the clinical records after approval from the Institutional Ethics Committee . All the patients above the age of 18 years who completed at least three years after TKR were observed for the study purpose. Patients treated for OA were included while the patients who received the implant for treatment of rheumatoid arthritis and traumatic injury were excluded. Factors such as aseptic loosening, implant failure, and need for revision surgery were observed to evaluate implant performance. Cases were recruited for clinical assessment of primary efficacy endpoint in terms of post-surgery maximun range of motion. Secondary efficacy endpoint was to determine the clinical and social quality of life as per the American Knee Society Score (AKSS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain and stiffness scores. A total of 158 patients who had 191 TKR were observed for performance. The mean age of the patients was 67.67 years; mean BMI was 28.97±3.33, and the group comprised of 43% men and 57% women. Telephonic follow up at three years of 158 patients identified that none of them required revision surgery or had aseptic loosening suggesting excellent performance. Final clinical follow up at three years was available for only 35 patients (41 knee implants). The range of motion significantly improved from preoperative 104°±5.67° (range, 85°-119°) to 119.8°±11.05° (98°-123°) at follow-up (ppain, and improved functionality.

  13. Time series analysis of satellite multi-sensors imagery to study the recursive abnormal grow of floating macrophyte in the lake victoria (central Africa)

    Science.gov (United States)

    Fusilli, Lorenzo; Cavalli, Rosa Maria; Laneve, Giovanni; Pignatti, Stefano; Santilli, Giancarlo; Santini, Federico

    2010-05-01

    Remote sensing allows multi-temporal mapping and monitoring of large water bodies. The importance of remote sensing for wetland and inland water inventory and monitoring at all scales was emphasized several times by the Ramsar Convention on Wetlands and from EU projects like SALMON and ROSALMA, e.g. by (Finlayson et al., 1999) and (Lowry and Finlayson, 2004). This paper aims at assessing the capability of time series of satellite imagery to provide information suitable for enhancing the understanding of the temporal cycles shown by the macrophytes growing in order to support the monitor and management of the lake Victoria water resources. The lake Victoria coastal areas are facing a number of challenges related to water resource management which include growing population, water scarcity, climate variability and water resource degradation, invasive species, water pollution. The proliferation of invasive plants and aquatic weeds, is of growing concern. In particular, let us recall some of the problems caused by the aquatic weeds growing: Ø interference with human activities such as fishing, and boating; Ø inhibition or interference with a balanced fish population; Ø fish killing due to removal of too much oxygen from the water; Ø production of quiet water areas that are ideal for mosquito breeding. In this context, an integrated use of medium/high resolution images from sensors like MODIS, ASTER, LANDSAT/TM and whenever available CHRIS offers the possibility of creating a congruent time series allowing the analysis of the floating vegetation dynamic on an extended temporal basis. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution, further its spatial resolution can results not always adequate to map the extension of floating plants. Therefore, the integrated use of sensors with different spatial resolution, were used to map across seasons the evolution of the phenomena. The

  14. International Work-Conference on Time Series

    CERN Document Server

    Pomares, Héctor

    2016-01-01

    This volume presents selected peer-reviewed contributions from The International Work-Conference on Time Series, ITISE 2015, held in Granada, Spain, July 1-3, 2015. It discusses topics in time series analysis and forecasting, advanced methods and online learning in time series, high-dimensional and complex/big data time series as well as forecasting in real problems. The International Work-Conferences on Time Series (ITISE) provide a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.

  15. The association between ambient inhalable particulate matter and the disease burden of respiratory disease: An ecological study based on ten-year time series data in Tianjin, China.

    Science.gov (United States)

    Zeng, Qiang; Wu, Ziting; Jiang, Guohong; Wu, Xiaoyin; Li, Pei; Ni, Yang; Xiong, Xiuqin; Wang, Xinyan; Parasat; Li, Guoxing; Pan, Xiaochuan

    2017-08-01

    There is limited evidence available worldwide about the quantitative relationship between particulate matter with an aerodynamic diameter of less than 10µm (PM 10 ) and years of life lost (YLL) caused by respiratory diseases (RD), especially regarding long-term time series data. We investigated the quantitative exposure-response association between PM 10 and the disease burden of RD. We obtained the daily concentration of ambient pollutants (PM 10 , nitrogen dioxide and sulphur dioxide), temperature and relative humidity data, as well as the death monitoring data from 2001 to 2010 in Tianjin. Then, a time series database was built after the daily YLL of RD was calculated. We applied a generalized additive model (GAM) to estimate the burden of PM 10 on daily YLL of RD and to determine the effect (the increase of daily YLL) of every 10μg/m 3 increase in PM 10 on health. We found that every 10μg/m 3 increase in PM 10 was associated with the greatest increase in YLL of 0.84 (95% CI: 0.45, 1.23) years at a 2-day (current day and previous day, lag01) moving average PM 10 concentration for RD. The association between PM 10 and YLL was stronger in females and the elderly (≥65 years of age). The association between PM 10 and YLL of RD differed according to district. These findings also provide new epidemiological evidence for respiratory disease prevention. Copyright © 2017 Elsevier Inc. All rights reserved.

  16. BRITS: Bidirectional Recurrent Imputation for Time Series

    OpenAIRE

    Cao, Wei; Wang, Dong; Li, Jian; Zhou, Hao; Li, Lei; Li, Yitan

    2018-01-01

    Time series are widely used as signals in many classification/regression tasks. It is ubiquitous that time series contains many missing values. Given multiple correlated time series data, how to fill in missing values and to predict their class labels? Existing imputation methods often impose strong assumptions of the underlying data generating process, such as linear dynamics in the state space. In this paper, we propose BRITS, a novel method based on recurrent neural networks for missing va...

  17. Geometric noise reduction for multivariate time series.

    Science.gov (United States)

    Mera, M Eugenia; Morán, Manuel

    2006-03-01

    We propose an algorithm for the reduction of observational noise in chaotic multivariate time series. The algorithm is based on a maximum likelihood criterion, and its goal is to reduce the mean distance of the points of the cleaned time series to the attractor. We give evidence of the convergence of the empirical measure associated with the cleaned time series to the underlying invariant measure, implying the possibility to predict the long run behavior of the true dynamics.

  18. Frontiers in Time Series and Financial Econometrics

    OpenAIRE

    Ling, S.; McAleer, M.J.; Tong, H.

    2015-01-01

    __Abstract__ Two of the fastest growing frontiers in econometrics and quantitative finance are time series and financial econometrics. Significant theoretical contributions to financial econometrics have been made by experts in statistics, econometrics, mathematics, and time series analysis. The purpose of this special issue of the journal on “Frontiers in Time Series and Financial Econometrics” is to highlight several areas of research by leading academics in which novel methods have contrib...

  19. Neural Network Models for Time Series Forecasts

    OpenAIRE

    Tim Hill; Marcus O'Connor; William Remus

    1996-01-01

    Neural networks have been advocated as an alternative to traditional statistical forecasting methods. In the present experiment, time series forecasts produced by neural networks are compared with forecasts from six statistical time series methods generated in a major forecasting competition (Makridakis et al. [Makridakis, S., A. Anderson, R. Carbone, R. Fildes, M. Hibon, R. Lewandowski, J. Newton, E. Parzen, R. Winkler. 1982. The accuracy of extrapolation (time series) methods: Results of a ...

  20. Study of a sample of faint Be stars in the exofield of CoRoT. II. Pulsation and outburst events: Time series analysis of photometric variations

    Science.gov (United States)

    Semaan, T.; Hubert, A. M.; Zorec, J.; Gutiérrez-Soto, J.; Frémat, Y.; Martayan, C.; Fabregat, J.; Eggenberger, P.

    2018-06-01

    Context. The class of Be stars are the epitome of rapid rotators in the main sequence. These stars are privileged candidates for studying the incidence of rotation on the stellar internal structure and on non-radial pulsations. Pulsations are considered possible mechanisms to trigger mass-ejection phenomena required to build up the circumstellar disks of Be stars. Aims: Time series analyses of the light curves of 15 faint Be stars observed with the CoRoT satellite were performed to obtain the distribution of non-radial pulsation (NRP) frequencies in their power spectra at epochs with and without light outbursts and to discriminate pulsations from rotation-related photometric variations. Methods: Standard Fourier techniques were employed to analyze the CoRoT light curves. Fundamental parameters corrected for rapid-rotation effects were used to study the power spectrum as a function of the stellar location in the instability domains of the Hertzsprung-Russell (H-R) diagram. Results: Frequencies are concentrated in separate groups as predicted for g-modes in rapid B-type rotators, except for the two stars that are outside the H-R instability domain. In five objects the variations in the power spectrum are correlated with the time-dependent outbursts characteristics. Time-frequency analysis showed that during the outbursts the amplitudes of stable main frequencies within 0.03 c d-1 intervals strongly change, while transients and/or frequencies of low amplitude appear separated or not separated from the stellar frequencies. The frequency patterns and activities depend on evolution phases: (i) the average separations between groups of frequencies are larger in the zero-age main sequence (ZAMS) than in the terminal age main sequence (TAMS) and are the largest in the middle of the MS phase; (ii) a poor frequency spectrum with f ≲ 1 cd-1 of low amplitude characterizes the stars beyond the TAMS; and (iii) outbursts are seen in stars hotter than B4 spectral type and in the

  1. Anomaly on Superspace of Time Series Data

    Science.gov (United States)

    Capozziello, Salvatore; Pincak, Richard; Kanjamapornkul, Kabin

    2017-11-01

    We apply the G-theory and anomaly of ghost and antighost fields in the theory of supersymmetry to study a superspace over time series data for the detection of hidden general supply and demand equilibrium in the financial market. We provide proof of the existence of a general equilibrium point over 14 extradimensions of the new G-theory compared with the M-theory of the 11 dimensions model of Edward Witten. We found that the process of coupling between nonequilibrium and equilibrium spinor fields of expectation ghost fields in the superspace of time series data induces an infinitely long exact sequence of cohomology from a short exact sequence of moduli state space model. If we assume that the financial market is separated into two topological spaces of supply and demand as the D-brane and anti-D-brane model, then we can use a cohomology group to compute the stability of the market as a stable point of the general equilibrium of the interaction between D-branes of the market. We obtain the result that the general equilibrium will exist if and only if the 14th Batalin-Vilkovisky cohomology group with the negative dimensions underlying 14 major hidden factors influencing the market is zero.

  2. GENDER SPECIFIC DIFFERENCES IN NEURODEVELOPMENTAL EFFECTS OF PRENATAL EXPOSURE TO VERY LOW-LEAD LEVELS: THE PROSPECTIVE COHORT STUDY IN THREE-YEAR OLDS

    OpenAIRE

    Jedrychowski, Wieslaw; Perera, Frederica; Jankowski, Jeffery; Mrozek-Budzyn, Dorota; Mroz, Elzbieta; Flak, Elzbieta; Edwards, Susan; Skarupa, Anita; Lisowska-Miszczyk, Ilona

    2009-01-01

    The primary purpose of this study was to assess the relationship between very low-level of prenatal lead exposure measured in the cord blood (1.67µg/dL) compared with the lowest quartile of exposure (beta coeff. = −6.2, p = 0.002), but the effect in girls was insignificant (beta coeff = −0.74, p = 0.720). The average deficit of cognitive function in the total sample over the first three years of life (GEE model) associated with higher prenatal lead exposure was also significant (beta coeffici...

  3. Software for the nuclear reactor dynamics study using time series processing; Software para el estudio de la dinamica de reactores nucleares mediante el procesamiento de series temporales

    Energy Technology Data Exchange (ETDEWEB)

    Valero, Esbel T.; Montesino, Maria E. [Instituto Superior de Ciencia y Tecnologia Nuclear (ISCTN), La Habana (Cuba)

    1997-12-01

    The parametric monitoring in Nuclear Power Plant (NPP) permits the operational surveillance of nuclear reactor. The methods employed in order to process this information such as FFT, autoregressive models and other, have some limitations when those regimens in which appear strongly non-linear behaviors are analyzed. In last years the chaos theory has offered new ways in order to explain complex dynamic behaviors. This paper describes a software (ECASET) that allow, by time series processing from NPP`s acquisition system, to characterize the nuclear reactor dynamic as a complex dynamical system. Here we show using ECASET`s results the possibility of classifying the different regimens appearing in nuclear reactors. The results of several temporal series processing from real systems are introduced. This type of analysis complements the results obtained with traditional methods and can constitute a new tool for monitoring nuclear reactors. (author). 13 refs., 3 figs.

  4. Drought Forecasting Using Adaptive Neuro-Fuzzy Inference Systems (ANFIS, Drought Time Series and Climate Indices For Next Coming Year, (Case Study: Zahedan

    Directory of Open Access Journals (Sweden)

    Hossein Hosseinpour Niknam

    2012-07-01

    Full Text Available In this research in order to forecast drought for the next coming year in Zahedan, using previous Standardized Precipitation Index (SPI data and 19 other climate indices were used.  For this purpose Adaptive Neuro-Fuzzy Inference System (ANFIS was applied to build the predicting model and SPI drought index for drought quantity.  At first calculating correlation approach for analysis between droughts and climate indices was used and the most suitable indices were selected. In the next stage drought prediction for period of 12 months was done. Different combinations among input variables in ANFIS models were entered. SPI drought index was the output of the model.  The results showed that just using time series like the previous year drought SPI index in forecasting the 12 month drought was effective. However among all climate indices that were used, Nino4 showed the most suitable results.

  5. Current Market Top Business Scopes Trend—A Concurrent Text and Time Series Active Learning Study of NASDAQ and NYSE Stocks from 2012 to 2017

    Directory of Open Access Journals (Sweden)

    Xiaoping Du

    2018-05-01

    Full Text Available As information technologies evolve, it has become necessary to examine the changes which have taken place in the top business scopes for both investors and entrepreneurs. To provide an understanding for the trends of the top business scopes in the current market, this article conducts a concurrent text and time series methodology to analyze the stocks in the New York Stock Exchange (NYSE and the National Association of Securities Dealers Automated Quotations (NASDAQ from 2012 to 2017. There is evidence that artificial intelligence and blockchains gained increasing importance for companies during that period. The authors contend that their findings in this paper question the status quo of promising business scopes for companies in the U.S. market.

  6. Urease activity in dental plaque and saliva of children during a three-year study period and its relationship with other caries risk factors

    Science.gov (United States)

    Morou-Bermudez, E; Elias-Boneta, A; Billings, RJ; Burne, RA; Garcia-Rivas, V; Brignoni-Nazario, V; Suarez-Perez, E

    2011-01-01

    Bacterial urease activity in dental plaque and in saliva generates ammonia, which can increase the plaque pH and can protect acid-sensitive oral bacteria. Recent cross-sectional studies suggest that reduced ability to generate ammonia from urea in dental plaque can be an important caries risk factor. In spite of this proposed important clinical role, there is currently no information available regarding important clinical aspects of oral ureolysis in children. OBJECTIVE The objective of this study was to evaluate the distribution and pattern of urease activity in the dental plaque and in the saliva of children during a three-year period, and to examine the relationship of urease with some important caries risk factors. METHODS A longitudinal study was conducted with repeated measures over a three-year period on a panel of 80 children, ages three to six years at recruitment. The dynamics of change in urease activity were described and associated with clinical, biological, and behavioral caries risk factors. RESULTS Urease activity in plaque showed a trend to remain stable during the study period and was negatively associated with sugar consumption (PUrease activity in unstimulated saliva increased with age, and it was positively associated with the levels of mutans streptococci in saliva and with the educational level of the parents (Purease activity and some important caries risk factors. Urease activity in saliva could be an indicator of mutans infection in children. PMID:21616477

  7. The foundations of modern time series analysis

    CERN Document Server

    Mills, Terence C

    2011-01-01

    This book develops the analysis of Time Series from its formal beginnings in the 1890s through to the publication of Box and Jenkins' watershed publication in 1970, showing how these methods laid the foundations for the modern techniques of Time Series analysis that are in use today.

  8. Forecasting Enrollments with Fuzzy Time Series.

    Science.gov (United States)

    Song, Qiang; Chissom, Brad S.

    The concept of fuzzy time series is introduced and used to forecast the enrollment of a university. Fuzzy time series, an aspect of fuzzy set theory, forecasts enrollment using a first-order time-invariant model. To evaluate the model, the conventional linear regression technique is applied and the predicted values obtained are compared to the…

  9. Lag space estimation in time series modelling

    DEFF Research Database (Denmark)

    Goutte, Cyril

    1997-01-01

    The purpose of this article is to investigate some techniques for finding the relevant lag-space, i.e. input information, for time series modelling. This is an important aspect of time series modelling, as it conditions the design of the model through the regressor vector a.k.a. the input layer...

  10. Statistical criteria for characterizing irradiance time series.

    Energy Technology Data Exchange (ETDEWEB)

    Stein, Joshua S.; Ellis, Abraham; Hansen, Clifford W.

    2010-10-01

    We propose and examine several statistical criteria for characterizing time series of solar irradiance. Time series of irradiance are used in analyses that seek to quantify the performance of photovoltaic (PV) power systems over time. Time series of irradiance are either measured or are simulated using models. Simulations of irradiance are often calibrated to or generated from statistics for observed irradiance and simulations are validated by comparing the simulation output to the observed irradiance. Criteria used in this comparison should derive from the context of the analyses in which the simulated irradiance is to be used. We examine three statistics that characterize time series and their use as criteria for comparing time series. We demonstrate these statistics using observed irradiance data recorded in August 2007 in Las Vegas, Nevada, and in June 2009 in Albuquerque, New Mexico.

  11. Sensor-Generated Time Series Events: A Definition Language

    Science.gov (United States)

    Anguera, Aurea; Lara, Juan A.; Lizcano, David; Martínez, Maria Aurora; Pazos, Juan

    2012-01-01

    There are now a great many domains where information is recorded by sensors over a limited time period or on a permanent basis. This data flow leads to sequences of data known as time series. In many domains, like seismography or medicine, time series analysis focuses on particular regions of interest, known as events, whereas the remainder of the time series contains hardly any useful information. In these domains, there is a need for mechanisms to identify and locate such events. In this paper, we propose an events definition language that is general enough to be used to easily and naturally define events in time series recorded by sensors in any domain. The proposed language has been applied to the definition of time series events generated within the branch of medicine dealing with balance-related functions in human beings. A device, called posturograph, is used to study balance-related functions. The platform has four sensors that record the pressure intensity being exerted on the platform, generating four interrelated time series. As opposed to the existing ad hoc proposals, the results confirm that the proposed language is valid, that is generally applicable and accurate, for identifying the events contained in the time series.

  12. Time series analysis of temporal networks

    Science.gov (United States)

    Sikdar, Sandipan; Ganguly, Niloy; Mukherjee, Animesh

    2016-01-01

    A common but an important feature of all real-world networks is that they are temporal in nature, i.e., the network structure changes over time. Due to this dynamic nature, it becomes difficult to propose suitable growth models that can explain the various important characteristic properties of these networks. In fact, in many application oriented studies only knowing these properties is sufficient. For instance, if one wishes to launch a targeted attack on a network, this can be done even without the knowledge of the full network structure; rather an estimate of some of the properties is sufficient enough to launch the attack. We, in this paper show that even if the network structure at a future time point is not available one can still manage to estimate its properties. We propose a novel method to map a temporal network to a set of time series instances, analyze them and using a standard forecast model of time series, try to predict the properties of a temporal network at a later time instance. To our aim, we consider eight properties such as number of active nodes, average degree, clustering coefficient etc. and apply our prediction framework on them. We mainly focus on the temporal network of human face-to-face contacts and observe that it represents a stochastic process with memory that can be modeled as Auto-Regressive-Integrated-Moving-Average (ARIMA). We use cross validation techniques to find the percentage accuracy of our predictions. An important observation is that the frequency domain properties of the time series obtained from spectrogram analysis could be used to refine the prediction framework by identifying beforehand the cases where the error in prediction is likely to be high. This leads to an improvement of 7.96% (for error level ≤20%) in prediction accuracy on an average across all datasets. As an application we show how such prediction scheme can be used to launch targeted attacks on temporal networks. Contribution to the Topical Issue

  13. Transmission of linear regression patterns between time series: from relationship in time series to complex networks.

    Science.gov (United States)

    Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

    2014-07-01

    The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.

  14. Unsupervised land cover change detection: meaningful sequential time series analysis

    CSIR Research Space (South Africa)

    Salmon, BP

    2011-06-01

    Full Text Available An automated land cover change detection method is proposed that uses coarse spatial resolution hyper-temporal earth observation satellite time series data. The study compared three different unsupervised clustering approaches that operate on short...

  15. Variations in the phytochemical contents and antioxidant capacity of organically and conventionally grown Italian cauliflower (Brassica oleracea L. subsp. botrytis): results from a three-year field study.

    Science.gov (United States)

    Lo Scalzo, Roberto; Picchi, Valentina; Migliori, Carmela Anna; Campanelli, Gabriele; Leteo, Fabrizio; Ferrari, Valentino; Di Cesare, Luigi Francesco

    2013-10-30

    A three-year field study (2009-2011) was performed to evaluate phytochemicals and antioxidant capacities of two genotypes (HF1 Emeraude and the local variety, Velox) of green cauliflower grown under organic and conventional management. The conventional system increased yield, but had little effect on the dry matter, whereas the organic system increased the soluble solids. Phytochemicals and antioxidant capacity showed significant year-to-year variability. During the third year, the scarce rainfall determined a significant increase of total glucosinolates and a general decrease of antioxidants in all samples. Interestingly, in the same year organic plants were less affected by the unfavorable climatic conditions, as they increased ascorbic acid, polyphenols, and carotenoids with respect to conventional ones. The overall results for the three years showed that the two genotypes responded differently. Compared to the conventional system, Velox showed 24, 21, 13, 48, and 44% higher content of ascorbic acid, polyphenols, carotenoids, volatiles, and antioxidant capacity, respectively. In contrast, no significant increase in the phytochemicals or the antioxidant potential was found in organic Emeraude, with the exception of total volatiles (+41%). These findings suggest that organic cultivation may be highly effective for particular cauliflower genotypes.

  16. Deconvolution of time series in the laboratory

    Science.gov (United States)

    John, Thomas; Pietschmann, Dirk; Becker, Volker; Wagner, Christian

    2016-10-01

    In this study, we present two practical applications of the deconvolution of time series in Fourier space. First, we reconstruct a filtered input signal of sound cards that has been heavily distorted by a built-in high-pass filter using a software approach. Using deconvolution, we can partially bypass the filter and extend the dynamic frequency range by two orders of magnitude. Second, we construct required input signals for a mechanical shaker in order to obtain arbitrary acceleration waveforms, referred to as feedforward control. For both situations, experimental and theoretical approaches are discussed to determine the system-dependent frequency response. Moreover, for the shaker, we propose a simple feedback loop as an extension to the feedforward control in order to handle nonlinearities of the system.

  17. Making sense of gender from digital game play in three-year-old children’s everyday lives: An ethnographic case study

    Directory of Open Access Journals (Sweden)

    Youn Jung Huh

    2015-06-01

    Full Text Available This study explores very young children performing and talking about game characters in their everyday life. In this study, young children’s digital game play is considered as a hybrid and complex site for the children to meet popular culture and their everyday family experiences. This article represents a case study of six three-year-old children and their families, which combines ethnographic methods (spending time with the families, being a participant observer and critical perspectives analysis with Bakhtinian perspectives to construct analyses that have the potential to understand how young children make sense of their everyday roles as a boy or a girl through their game play. This study shows that young children do not directly receive ideological messages from the game media, but they make sense of the messages by decoding and interpreting the game media based on their own theories of everyday life.

  18. Stacked Heterogeneous Neural Networks for Time Series Forecasting

    Directory of Open Access Journals (Sweden)

    Florin Leon

    2010-01-01

    Full Text Available A hybrid model for time series forecasting is proposed. It is a stacked neural network, containing one normal multilayer perceptron with bipolar sigmoid activation functions, and the other with an exponential activation function in the output layer. As shown by the case studies, the proposed stacked hybrid neural model performs well on a variety of benchmark time series. The combination of weights of the two stack components that leads to optimal performance is also studied.

  19. Climatic factors and community - associated methicillin-resistant Staphylococcus aureus skin and soft-tissue infections - a time-series analysis study.

    Science.gov (United States)

    Sahoo, Krushna Chandra; Sahoo, Soumyakanta; Marrone, Gaetano; Pathak, Ashish; Lundborg, Cecilia Stålsby; Tamhankar, Ashok J

    2014-08-29

    Skin and soft tissue infections caused by Staphylococcus aureus (SA-SSTIs) including methicillin-resistant Staphylococcus aureus (MRSA) have experienced a significant surge all over the world. Changing climatic factors are affecting the global burden of dermatological infections and there is a lack of information on the association between climatic factors and MRSA infections. Therefore, association of temperature and relative humidity (RH) with occurrence of SA-SSTIs (n = 387) and also MRSA (n = 251) was monitored for 18 months in the outpatient clinic at a tertiary care hospital located in Bhubaneswar, Odisha, India. The Kirby-Bauer disk diffusion method was used for antibiotic susceptibility testing. Time-series analysis was used to investigate the potential association of climatic factors (weekly averages of maximum temperature, minimum temperature and RH) with weekly incidence of SA-SSTIs and MRSA infections. The analysis showed that a combination of weekly average maximum temperature above 33 °C coinciding with weekly average RH ranging between 55% and 78%, is most favorable for the occurrence of SA-SSTIs and MRSA and within these parameters, each unit increase in occurrence of MRSA was associated with increase in weekly average maximum temperature of 1.7 °C (p = 0.044) and weekly average RH increase of 10% (p = 0.097).

  20. Climatic Factors and Community — Associated Methicillin-Resistant Staphylococcus aureus Skin and Soft-Tissue Infections — A Time-Series Analysis Study

    Directory of Open Access Journals (Sweden)

    Krushna Chandra Sahoo

    2014-08-01

    Full Text Available Skin and soft tissue infections caused by Staphylococcus aureus (SA-SSTIs including methicillin-resistant Staphylococcus aureus (MRSA have experienced a significant surge all over the world. Changing climatic factors are affecting the global burden of dermatological infections and there is a lack of information on the association between climatic factors and MRSA infections. Therefore, association of temperature and relative humidity (RH with occurrence of SA-SSTIs (n = 387 and also MRSA (n = 251 was monitored for 18 months in the outpatient clinic at a tertiary care hospital located in Bhubaneswar, Odisha, India. The Kirby-Bauer disk diffusion method was used for antibiotic susceptibility testing. Time-series analysis was used to investigate the potential association of climatic factors (weekly averages of maximum temperature, minimum temperature and RH with weekly incidence of SA-SSTIs and MRSA infections. The analysis showed that a combination of weekly average maximum temperature above 33 °C coinciding with weekly average RH ranging between 55% and 78%, is most favorable for the occurrence of SA-SSTIs and MRSA and within these parameters, each unit increase in occurrence of MRSA was associated with increase in weekly average maximum temperature of 1.7 °C (p = 0.044 and weekly average RH increase of 10% (p = 0.097.

  1. Implementation and impact of an audit and feedback antimicrobial stewardship intervention in the orthopaedics department of a tertiary-care hospital: a controlled interrupted time series study.

    Science.gov (United States)

    Tavares, Margarida; Carvalho, Ana Cláudia; Almeida, José Pedro; Andrade, Paulo; São-Simão, Ricardo; Soares, Pedro; Alves, Carlos; Pinto, Rui; Fontanet, Arnaud; Watier, Laurence

    2018-06-01

    A prospective audit and feedback antimicrobial stewardship intervention conducted in the Orthopaedics Department of a university hospital in Portugal was evaluated by comparing an interrupted time series in the intervention group with a non-intervention (control) group. Monthly antibiotic use (except cefazolin) was measured as the World Health Organization's Anatomical Therapeutic Chemical defined daily doses (ATC-DDD) from January 2012 to September 2016, excluding the 6-month phase of intervention implementation starting on 1 January 2015. Compared with the control group, the intervention group had a monthly decrease in the use of fluoroquinolones by 2.3 DDD/1000 patient-days [95% confidence interval (CI) -3.97 to -0.63]. An increase in the use of penicillins by 103.3 DDD/1000 patient-days (95% CI 47.42 to 159.10) was associated with intervention implementation, followed by a decrease during the intervention period (slope = -5.2, 95% CI -8.56 to -1.82). In the challenging scenario of treatment of osteoarticular and prosthetic joint infections, an audit and feedback intervention reduced antibiotic exposure and spectrum. Copyright © 2018 Elsevier B.V. and International Society of Chemotherapy. All rights reserved.

  2. Time series modeling, computation, and inference

    CERN Document Server

    Prado, Raquel

    2010-01-01

    The authors systematically develop a state-of-the-art analysis and modeling of time series. … this book is well organized and well written. The authors present various statistical models for engineers to solve problems in time series analysis. Readers no doubt will learn state-of-the-art techniques from this book.-Hsun-Hsien Chang, Computing Reviews, March 2012My favorite chapters were on dynamic linear models and vector AR and vector ARMA models.-William Seaver, Technometrics, August 2011… a very modern entry to the field of time-series modelling, with a rich reference list of the current lit

  3. Time Series Analysis Forecasting and Control

    CERN Document Server

    Box, George E P; Reinsel, Gregory C

    2011-01-01

    A modernized new edition of one of the most trusted books on time series analysis. Since publication of the first edition in 1970, Time Series Analysis has served as one of the most influential and prominent works on the subject. This new edition maintains its balanced presentation of the tools for modeling and analyzing time series and also introduces the latest developments that have occurred n the field over the past decade through applications from areas such as business, finance, and engineering. The Fourth Edition provides a clearly written exploration of the key methods for building, cl

  4. Evaluation of total alloplastic temporo-mandibular joint replacement with two different types of prostheses: A three-year prospective study.

    Science.gov (United States)

    Gonzalez-Perez, L-M; Gonzalez-Perez-Somarriba, B; Centeno, G; Vallellano, C; Montes-Carmona, J-F

    2016-11-01

    Temporo-Mandibular Joint (TMJ) replacement has been used clinically for years. The objective of this study was to evaluate outcomes achieved in patients with two different categories of TMJ prostheses. All patients who had a TMJ replacement (TMJR) implanted during the study period from 2006 through 2012 were included in this 3-year prospective study. All procedures were performed using the Biomet Microfixation TMJ Replacement System, and all involved replacing both the skull base component (glenoid fossa) and the mandibular condyle. Fifty-seven patients (38 females and 19 males), involving 75 TMJs with severe disease requiring reconstruction (39 unilateral, 18 bilateral) were operated on consecutively, and 68 stock prostheses and 7 custom-made prostheses were implanted. The mean age at surgery was 52.6±11.5 years in the stock group and 51.8±11.7 years in the custom-made group. In the stock group, after three years of TMJR, results showed a reduction in pain intensity from 6.4±1.4 to 1.6±1.2 (p<0.001), and an improvement in jaw opening from 2.7±0.9 cm to 4.2±0.7 cm (p<0.001). In the custom-made group, after three years of TMJR, results showed a reduction in pain intensity from 6.0±1.6 to 2.2±0.4 (p<0.001), and an improvement in jaw opening from 1.5±0.5 cm to 4.3±0.6 cm (p<0.001). No statistically significant differences between two groups were detected. The results of this three-year prospective study support the surgical placement of TMJ prostheses (stock prosthetic, and custom-made systems), and show that the approach is efficacious and safe, reduces pain, and improves maximum mouth opening movement, with few complications. As such, TMJR represents a viable technique and a stable long-term solution for cranio-mandibular reconstruction in patients with irreversible end-stage TMJ disease. Comparing stock and custom-made groups, no statistically significant differences were detected with respect to pain intensity reduction and maximum mouth opening

  5. Urease activity in dental plaque and saliva of children during a three-year study period and its relationship with other caries risk factors.

    Science.gov (United States)

    Morou-Bermudez, E; Elias-Boneta, A; Billings, R J; Burne, R A; Garcia-Rivas, V; Brignoni-Nazario, V; Suarez-Perez, E

    2011-11-01

    Bacterial urease activity in dental plaque and in saliva generates ammonia, which can increase the plaque pH and can protect acid-sensitive oral bacteria. Recent cross-sectional studies suggest that reduced ability to generate ammonia from urea in dental plaque can be an important caries risk factor. In spite of this proposed important clinical role, there is currently no information available regarding important clinical aspects of oral ureolysis in children. The objective of this study was to evaluate the distribution and pattern of urease activity in the dental plaque and in the saliva of children during a three-year period, and to examine the relationship of urease with some important caries risk factors. A longitudinal study was conducted with repeated measures over a three-year period on a panel of 80 children, aged 3-6 years at recruitment. The dynamics of change in urease activity were described and associated with clinical, biological, and behavioural caries risk factors. Urease activity in plaque showed a trend to remain stable during the study period and was negatively associated with sugar consumption (P<0.05). Urease activity in unstimulated saliva increased with age, and it was positively associated with the levels of mutans streptococci in saliva and with the educational level of the parents (P<0.05). The results of this study reveal interesting and complex interactions between oral urease activity and some important caries risk factors. Urease activity in saliva could be an indicator of mutans infection in children. Copyright © 2011 Elsevier Ltd. All rights reserved.

  6. Screenings of lung cancer with low dose spiral CT: results of a three year pilot study and design of the randomised controlled trial Italung-CT

    International Nuclear Information System (INIS)

    Picozzi, Giulia; Paci, Enrico; Lopes Pegna, Andrea

    2005-01-01

    Purpose: To report the results of a three-year observational pilot study of lung cancer screening with low dose computed tomography (CT) and to present the study design of a randomised clinical trial named as Italung CT. Materials and methods: Sixty (47 males and 13 females, mean age 64±4.5 years) heavy smokers (at least 20 packs-year) underwent three low-dose spiral CT screening tests one year apart on a single slice or multislice CT scanner. Indeterminate nodules were managed according to the recommendations of the Early Lung Cancer Action Project. Results: Indeterminate nodules were observed in 33 (55%) of the subjects (60% at the baseline screening test, 24% at the first annual test and 16% at the second annual test). The size of the largest indeterminate nodule was [it

  7. Urease activity as a risk factor for caries development in children during a three-year study period: a survival analysis approach

    Science.gov (United States)

    Morou-Bermudez, E; Elias-Boneta, A; Billings, RJ; Burne, RA; Garcia-Rivas, V; Brignoni-Nazario, V; Suárez-Pérez, E

    2011-01-01

    Recent cross-sectional studies suggest that reduced ability to generate alkali via the urease pathway in dental plaque may be an important caries risk factor, but it has not been assessed prospectively. OBJECTIVE To evaluate the effect of plaque and saliva urease activity on the risk for developing new caries over a three-year period in children. METHODS A panel of 80 children, three to six years of age at recruitment, was followed prospectively for three years. Plaque urease activity, saliva urease activity and dental caries were measured every six months. Survival analysis methodology was used to evaluate the effect of urease on caries development during the study period adjusted for gender, age, baseline caries levels, sugar consumption, amount of plaque, and mutans streptococci levels. RESULTS The risk for developing new caries increased in a dose-responsive manner with increasing levels of urease activity in saliva (adjusted HRQ4 vs. Q1: 4.98; 95%CI: 1.33, 18.69) and with decreasing urease activity in plaque (adjusted HRQ4 vs. Q1: 0.29; 95%CI: 0.11, 0.76). Multiple measurements of urease activity were conducted to overcome the variability of urease activity in this study. Baseline caries and mutans streptococci in saliva were also important predictors of caries risk. CONCLUSIONS Increased urease activity in saliva can be an indicator of increased caries risk in children, while increased urease activity in plaque may be associated with reduced caries risk. The reproducibility of urease measurements must be improved before these findings can be further tested and clinically applied. PMID:21784411

  8. Detecting nonlinear structure in time series

    International Nuclear Information System (INIS)

    Theiler, J.

    1991-01-01

    We describe an approach for evaluating the statistical significance of evidence for nonlinearity in a time series. The formal application of our method requires the careful statement of a null hypothesis which characterizes a candidate linear process, the generation of an ensemble of ''surrogate'' data sets which are similar to the original time series but consistent with the null hypothesis, and the computation of a discriminating statistic for the original and for each of the surrogate data sets. The idea is to test the original time series against the null hypothesis by checking whether the discriminating statistic computed for the original time series differs significantly from the statistics computed for each of the surrogate sets. While some data sets very cleanly exhibit low-dimensional chaos, there are many cases where the evidence is sketchy and difficult to evaluate. We hope to provide a framework within which such claims of nonlinearity can be evaluated. 5 refs., 4 figs

  9. Nonparametric factor analysis of time series

    OpenAIRE

    Rodríguez-Poo, Juan M.; Linton, Oliver Bruce

    1998-01-01

    We introduce a nonparametric smoothing procedure for nonparametric factor analaysis of multivariate time series. The asymptotic properties of the proposed procedures are derived. We present an application based on the residuals from the Fair macromodel.

  10. Measuring multiscaling in financial time-series

    International Nuclear Information System (INIS)

    Buonocore, R.J.; Aste, T.; Di Matteo, T.

    2016-01-01

    We discuss the origin of multiscaling in financial time-series and investigate how to best quantify it. Our methodology consists in separating the different sources of measured multifractality by analyzing the multi/uni-scaling behavior of synthetic time-series with known properties. We use the results from the synthetic time-series to interpret the measure of multifractality of real log-returns time-series. The main finding is that the aggregation horizon of the returns can introduce a strong bias effect on the measure of multifractality. This effect can become especially important when returns distributions have power law tails with exponents in the range (2, 5). We discuss the right aggregation horizon to mitigate this bias.

  11. Entropic Analysis of Electromyography Time Series

    Science.gov (United States)

    Kaufman, Miron; Sung, Paul

    2005-03-01

    We are in the process of assessing the effectiveness of fractal and entropic measures for the diagnostic of low back pain from surface electromyography (EMG) time series. Surface electromyography (EMG) is used to assess patients with low back pain. In a typical EMG measurement, the voltage is measured every millisecond. We observed back muscle fatiguing during one minute, which results in a time series with 60,000 entries. We characterize the complexity of time series by computing the Shannon entropy time dependence. The analysis of the time series from different relevant muscles from healthy and low back pain (LBP) individuals provides evidence that the level of variability of back muscle activities is much larger for healthy individuals than for individuals with LBP. In general the time dependence of the entropy shows a crossover from a diffusive regime to a regime characterized by long time correlations (self organization) at about 0.01s.

  12. Time series prediction: statistical and neural techniques

    Science.gov (United States)

    Zahirniak, Daniel R.; DeSimio, Martin P.

    1996-03-01

    In this paper we compare the performance of nonlinear neural network techniques to those of linear filtering techniques in the prediction of time series. Specifically, we compare the results of using the nonlinear systems, known as multilayer perceptron and radial basis function neural networks, with the results obtained using the conventional linear Wiener filter, Kalman filter and Widrow-Hoff adaptive filter in predicting future values of stationary and non- stationary time series. Our results indicate the performance of each type of system is heavily dependent upon the form of the time series being predicted and the size of the system used. In particular, the linear filters perform adequately for linear or near linear processes while the nonlinear systems perform better for nonlinear processes. Since the linear systems take much less time to be developed, they should be tried prior to using the nonlinear systems when the linearity properties of the time series process are unknown.

  13. A prospective interrupted time series study of interventions to improve the quality, rating, framing and structure of goal-setting in community-based brain injury rehabilitation.

    Science.gov (United States)

    Hassett, Leanne; Simpson, Grahame; Cotter, Rachel; Whiting, Diane; Hodgkinson, Adeline; Martin, Diane

    2015-04-01

    To investigate whether the introduction of an electronic goals system followed by staff training improved the quality, rating, framing and structure of goals written by a community-based brain injury rehabilitation team. Interrupted time series design. Two interventions were introduced six months apart. The first intervention comprised the introduction of an electronic goals system. The second intervention comprised a staff goal training workshop. An audit protocol was devised to evaluate the goals. A random selection of goal statements from the 12 months prior to the interventions (Time 1 baseline) were compared with all goal statements written after the introduction of the electronic goals system (Time 2) and staff training (Time 3). All goals were de-identified for client and time-period, and randomly ordered. A total of 745 goals (Time 1 n = 242; Time 2 n = 283; Time 3 n = 220) were evaluated. Compared with baseline, the introduction of the electronic goals system alone significantly increased goal rating, framing and structure (χ(2) tests 144.7, 18.9, 48.1, respectively, p goal quality, which was only a trend at Time 2, was statistically significant at Time 3 (χ(2) 15.0, p ≤ 001). The training also led to a further significant increase in the framing and structuring of goals over the electronic goals system (χ(2) 11.5, 12.5, respectively, p ≤ 0.001). An electronic goals system combined with staff training improved the quality, rating, framing and structure of goal statements. © The Author(s) 2014.

  14. Gene Expression Profile in the Early Stage of Angiotensin II-induced Cardiac Remodeling: a Time Series Microarray Study in a Mouse Model

    Directory of Open Access Journals (Sweden)

    Meng-Qiu Dang

    2015-01-01

    Full Text Available Background/Aims: Angiotensin II (Ang II plays a critical role in the cardiac remodeling contributing to heart failure. However, the gene expression profiles induced by Ang II in the early stage of cardiac remodeling remain unknown. Methods: Wild-type male mice (C57BL/6 background, 10-weeek-old were infused with Ang II (1500 ng/kg/min for 7 days. Blood pressure was measured. Cardiac function and remodeling were examined by echocardiography, H&E and Masson staining. The time series microarrays were then conducted to detected gene expression profiles. Results: Microarray results identified that 1,489 genes were differentially expressed in the hearts at day 1, 3 and 7 of Ang II injection. These genes were further classified into 26 profiles by hierarchical cluster analysis. Of them, 4 profiles were significant (No. 19, 8, 21 and 22 and contained 904 genes. Gene Ontology showed that these genes mainly participate in metabolic process, oxidation-reduction process, extracellular matrix organization, apoptotic process, immune response, and others. Significant pathways included focal adhesion, ECM-receptor interaction, cytokine-cytokine receptor interaction, MAPK and insulin signaling pathways, which were known to play important roles in Ang II-induced cardiac remodeling. Moreover, gene co-expression networks analysis suggested that serine/cysteine peptidase inhibitor, member 1 (Serpine1, also known as PAI-1 localized in the core of the network. Conclusions: Our results indicate that many genes are mainly involved in metabolism, inflammation, cardiac fibrosis and hypertrophy. Serpine1 may play a central role in the development of Ang II-induced cardiac remodeling at the early stage.

  15. The effect of health insurance and health facility-upgrades on hospital deliveries in rural Nigeria: a controlled interrupted time-series study.

    Science.gov (United States)

    Brals, Daniëlla; Aderibigbe, Sunday A; Wit, Ferdinand W; van Ophem, Johannes C M; van der List, Marijn; Osagbemi, Gordon K; Hendriks, Marleen E; Akande, Tanimola M; Boele van Hensbroek, Michael; Schultsz, Constance

    2017-09-01

    Access to quality obstetric care is considered essential to reducing maternal and new-born mortality. We evaluated the effect of the introduction of a multifaceted voluntary health insurance programme on hospital deliveries in rural Nigeria. We used an interrupted time-series design, including a control group. The intervention consisted of providing voluntary health insurance covering primary and secondary healthcare, including antenatal and obstetric care, combined with improving the quality of healthcare facilities. We compared changes in hospital deliveries from 1 May 2005 to 30 April 2013 between the programme area and control area in a difference-in-differences analysis with multiple time periods, adjusting for observed confounders. Data were collected through household surveys. Eligible households ( n = 1500) were selected from a stratified probability sample of enumeration areas. All deliveries during the 4-year baseline period ( n = 460) and 4-year follow-up period ( n = 380) were included. Insurance coverage increased from 0% before the insurance was introduced to 70.2% in April 2013 in the programme area. In the control area insurance coverage remained 0% between May 2005 and April 2013. Although hospital deliveries followed a common stable trend over the 4 pre-programme years ( P = 0.89), the increase in hospital deliveries during the 4-year follow-up period in the programme area was 29.3 percentage points (95% CI: 16.1 to 42.6; P health insurance but who could make use of the upgraded care delivered significantly more often in a hospital during the follow-up period than women living in the control area ( P = 0.04). Voluntary health insurance combined with quality healthcare services is highly effective in increasing hospital deliveries in rural Nigeria, by improving access to healthcare for insured and uninsured women in the programme area. © The Author 2017. Published by Oxford University Press in association with The London School of Hygiene and

  16. Three-year comparative study of polyphenol contents and antioxidant capacities in fruits of tomato (Lycopersicon esculentum Mill.) cultivars grown under organic and conventional conditions.

    Science.gov (United States)

    Anton, Dea; Matt, Darja; Pedastsaar, Priit; Bender, Ingrid; Kazimierczak, Renata; Roasto, Mati; Kaart, Tanel; Luik, Anne; Püssa, Tõnu

    2014-06-04

    In the present study, four tomato cultivars were grown under organic and conventional conditions in separate unheated greenhouses in three consecutive years. The objective was to assess the influence of the cultivation system on the content of individual polyphenols, total phenolics, and antioxidant capacity of tomatoes. The fruits were analyzed for total phenolic content by the Folin-Ciocalteau method and antioxidant capacity by the DPPH free radical scavenging assay. Individual phenolic compounds were analyzed using HPLC-DAD-MS/MS. Among 30 identified and quantified polyphenols, significantly higher contents of apigenin acetylhexoside, caffeic acid hexoside I, and phloretin dihexoside were found in all organic samples. The content of polyphenols was more dependent on year and cultivar than on cultivation conditions. Generally, the cultivation system had minor impact on polyphenols content, and only a few compounds were influenced by the mode of cultivation in all tested cultivars during all three years.

  17. Long-term relationships between perceived social support and posttraumatic stress after the 2011 Oslo bombing: A three-year longitudinal study.

    Science.gov (United States)

    Birkeland, Marianne Skogbrott; Knatten, Charlotte Kristensen; Hansen, Marianne Bang; Hem, Camilla; Heir, Trond

    2016-09-15

    After traumatic events, social support and posttraumatic stress are interrelated, but little is known about the underlying dynamics behind this association. Levels of social support and posttraumatic stress may change and affect each other over time, but there are also stable time-invariant individual differences in both constructs. The present study aimed to determine the amount of variance explained by stable individual differences in levels of social support and posttraumatic stress across three years, and to determine whether and to what extent social support and posttraumatic stress may affect one another when these stable individual differences are controlled for. We used data from ministerial employees present in the Governmental district during the 2011 Oslo bombing attack (N=255). Data was collected ten months, two years, and three years after the terror attack. Using a random intercept cross lagged panel model (RI-CLPM), we tested the possible directional effects between social support and posttraumatic stress within persons when variance between persons was taken into account. The intraclass correlations of the three measures of posttraumatic stress and social support were.83 and.74, respectively. The remaining variation within persons could not be explained by change in either of these constructs. We have no information on the processes that might have occurred before 10 months after the incident. Our findings indicate that the long-term longitudinal linkage between social support and posttraumatic stress may be best explained by stable individual differences rather than causal processes operating within persons. Copyright © 2016 Elsevier B.V. All rights reserved.

  18. Diabetes mellitus and abnormal glucose tolerance development after gestational diabetes: A three-year, prospective, randomized, clinical-based, Mediterranean lifestyle interventional study with parallel groups.

    Science.gov (United States)

    Pérez-Ferre, Natalia; Del Valle, Laura; Torrejón, Maria José; Barca, Idoya; Calvo, María Isabel; Matía, Pilar; Rubio, Miguel A; Calle-Pascual, Alfonso L

    2015-08-01

    Women with prior gestational diabetes mellitus (GDM) have a high risk of developing type 2 diabetes mellitus (DM2) in later life. The study aim was to evaluate the efficacy of a lifestyle intervention for the prevention of glucose disorders (impaired fasting glucose, impaired glucose tolerance or DM2) in women with prior GDM. A total of 260 women with prior GDM who presented with normal fasting plasma glucose at six to twelve weeks postpartum were randomized into two groups: a Mediterranean lifestyle intervention group (n = 130) who underwent an educational program on nutrition and a monitored physical activity program and a control group (n = 130) with a conventional follow-up. A total of 237 women completed the three-year follow-up (126 in the intervention group and 111 in the control group). Their glucose disorders rates, clinical and metabolic changes and rates of adherence to the Mediterranean lifestyle were analyzed. Less women in the intervention group (42.8%) developed glucose disorders at the end of the three-year follow-up period compared with the control group (56.75%), p Lifestyle intervention was effective for the prevention of glucose disorders in women with prior GDM. Body weight gain and an unhealthy fat intake pattern were found to be the most predictive factors for the development of glucose disorders. Current Controlled trials: ISRCTN24165302. http://www.controlled-trials.com/isrctn/pf/24165302. Copyright © 2014 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

  19. Scale-dependent intrinsic entropies of complex time series.

    Science.gov (United States)

    Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

    2016-04-13

    Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).

  20. Quantifying memory in complex physiological time-series.

    Science.gov (United States)

    Shirazi, Amir H; Raoufy, Mohammad R; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R; Amodio, Piero; Jafari, G Reza; Montagnese, Sara; Mani, Ali R

    2013-01-01

    In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are 'forgotten' quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations.

  1. Effectiveness of Multivariate Time Series Classification Using Shapelets

    Directory of Open Access Journals (Sweden)

    A. P. Karpenko

    2015-01-01

    Full Text Available Typically, time series classifiers require signal pre-processing (filtering signals from noise and artifact removal, etc., enhancement of signal features (amplitude, frequency, spectrum, etc., classification of signal features in space using the classical techniques and classification algorithms of multivariate data. We consider a method of classifying time series, which does not require enhancement of the signal features. The method uses the shapelets of time series (time series shapelets i.e. small fragments of this series, which reflect properties of one of its classes most of all.Despite the significant number of publications on the theory and shapelet applications for classification of time series, the task to evaluate the effectiveness of this technique remains relevant. An objective of this publication is to study the effectiveness of a number of modifications of the original shapelet method as applied to the multivariate series classification that is a littlestudied problem. The paper presents the problem statement of multivariate time series classification using the shapelets and describes the shapelet–based basic method of binary classification, as well as various generalizations and proposed modification of the method. It also offers the software that implements a modified method and results of computational experiments confirming the effectiveness of the algorithmic and software solutions.The paper shows that the modified method and the software to use it allow us to reach the classification accuracy of about 85%, at best. The shapelet search time increases in proportion to input data dimension.

  2. Multifractal analysis of visibility graph-based Ito-related connectivity time series.

    Science.gov (United States)

    Czechowski, Zbigniew; Lovallo, Michele; Telesca, Luciano

    2016-02-01

    In this study, we investigate multifractal properties of connectivity time series resulting from the visibility graph applied to normally distributed time series generated by the Ito equations with multiplicative power-law noise. We show that multifractality of the connectivity time series (i.e., the series of numbers of links outgoing any node) increases with the exponent of the power-law noise. The multifractality of the connectivity time series could be due to the width of connectivity degree distribution that can be related to the exit time of the associated Ito time series. Furthermore, the connectivity time series are characterized by persistence, although the original Ito time series are random; this is due to the procedure of visibility graph that, connecting the values of the time series, generates persistence but destroys most of the nonlinear correlations. Moreover, the visibility graph is sensitive for detecting wide "depressions" in input time series.

  3. Three-year data from the XIENCE V® INDIA study: Safety and efficacy of XIENCE V® in 1000 real world Indian patients

    Directory of Open Access Journals (Sweden)

    Ashok Seth

    2014-05-01

    Conclusion: Despite the high risk population of coronary artery disease, the use of XIENCE V® in 'real world' Indian patients was associated with very low clinical event rates upto three years of follow up.

  4. Highly comparative time-series analysis: the empirical structure of time series and their methods.

    Science.gov (United States)

    Fulcher, Ben D; Little, Max A; Jones, Nick S

    2013-06-06

    The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines.

  5. Visibility Graph Based Time Series Analysis.

    Science.gov (United States)

    Stephen, Mutua; Gu, Changgui; Yang, Huijie

    2015-01-01

    Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

  6. Visibility Graph Based Time Series Analysis.

    Directory of Open Access Journals (Sweden)

    Mutua Stephen

    Full Text Available Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

  7. Detecting chaos in irregularly sampled time series.

    Science.gov (United States)

    Kulp, C W

    2013-09-01

    Recently, Wiebe and Virgin [Chaos 22, 013136 (2012)] developed an algorithm which detects chaos by analyzing a time series' power spectrum which is computed using the Discrete Fourier Transform (DFT). Their algorithm, like other time series characterization algorithms, requires that the time series be regularly sampled. Real-world data, however, are often irregularly sampled, thus, making the detection of chaotic behavior difficult or impossible with those methods. In this paper, a characterization algorithm is presented, which effectively detects chaos in irregularly sampled time series. The work presented here is a modification of Wiebe and Virgin's algorithm and uses the Lomb-Scargle Periodogram (LSP) to compute a series' power spectrum instead of the DFT. The DFT is not appropriate for irregularly sampled time series. However, the LSP is capable of computing the frequency content of irregularly sampled data. Furthermore, a new method of analyzing the power spectrum is developed, which can be useful for differentiating between chaotic and non-chaotic behavior. The new characterization algorithm is successfully applied to irregularly sampled data generated by a model as well as data consisting of observations of variable stars.

  8. Similarity estimators for irregular and age uncertain time series

    Science.gov (United States)

    Rehfeld, K.; Kurths, J.

    2013-09-01

    contributes less, particularly for the adapted Gaussian-kernel based estimators and the event synchronization function. The introduced link strength concept summarizes the hypothesis test results and balances the individual strengths of the estimators: while gXCF is particularly suitable for short and irregular time series, gMI and the ESF can identify nonlinear dependencies. ESF could, in particular, be suitable to study extreme event dynamics in paleoclimate records. Programs to analyze paleoclimatic time series for significant dependencies are included in a freely available software toolbox.

  9. Similarity estimators for irregular and age-uncertain time series

    Science.gov (United States)

    Rehfeld, K.; Kurths, J.

    2014-01-01

    contributes less, particularly for the adapted Gaussian-kernel-based estimators and the event synchronization function. The introduced link strength concept summarizes the hypothesis test results and balances the individual strengths of the estimators: while gXCF is particularly suitable for short and irregular time series, gMI and the ESF can identify nonlinear dependencies. ESF could, in particular, be suitable to study extreme event dynamics in paleoclimate records. Programs to analyze paleoclimatic time series for significant dependencies are included in a freely available software toolbox.

  10. Efficient Approximate OLAP Querying Over Time Series

    DEFF Research Database (Denmark)

    Perera, Kasun Baruhupolage Don Kasun Sanjeewa; Hahmann, Martin; Lehner, Wolfgang

    2016-01-01

    The ongoing trend for data gathering not only produces larger volumes of data, but also increases the variety of recorded data types. Out of these, especially time series, e.g. various sensor readings, have attracted attention in the domains of business intelligence and decision making. As OLAP...... queries play a major role in these domains, it is desirable to also execute them on time series data. While this is not a problem on the conceptual level, it can become a bottleneck with regards to query run-time. In general, processing OLAP queries gets more computationally intensive as the volume...... of data grows. This is a particular problem when querying time series data, which generally contains multiple measures recorded at fine time granularities. Usually, this issue is addressed either by scaling up hardware or by employing workload based query optimization techniques. However, these solutions...

  11. Introduction to time series analysis and forecasting

    CERN Document Server

    Montgomery, Douglas C; Kulahci, Murat

    2008-01-01

    An accessible introduction to the most current thinking in and practicality of forecasting techniques in the context of time-oriented data. Analyzing time-oriented data and forecasting are among the most important problems that analysts face across many fields, ranging from finance and economics to production operations and the natural sciences. As a result, there is a widespread need for large groups of people in a variety of fields to understand the basic concepts of time series analysis and forecasting. Introduction to Time Series Analysis and Forecasting presents the time series analysis branch of applied statistics as the underlying methodology for developing practical forecasts, and it also bridges the gap between theory and practice by equipping readers with the tools needed to analyze time-oriented data and construct useful, short- to medium-term, statistically based forecasts.

  12. A three year study of metal levels in skin biopsies of whales in the Gulf of Mexico after the Deepwater Horizon oil crisis.

    Science.gov (United States)

    Wise, John Pierce; Wise, James T F; Wise, Catherine F; Wise, Sandra S; Gianios, Christy; Xie, Hong; Walter, Ron; Boswell, Mikki; Zhu, Cairong; Zheng, Tongzhang; Perkins, Christopher; Wise, John Pierce

    2018-02-01

    In response to the explosion of the Deepwater Horizon and the massive release of oil that followed, we conducted three annual research voyages to investigate how the oil spill would impact the marine offshore environment. Most investigations into the ecological and toxicological impacts of the Deepwater Horizon Oil crisis have mainly focused on the fate of the oil and dispersants, but few have considered the release of metals into the environment. From studies of previous oil spills, other marine oil industries, and analyses of oil compositions, it is evident that metals are frequently encountered. Several metals have been reported in the MC252 oil from the Deepwater Horizon oil spill, including the nonessential metals aluminum, arsenic, chromium, nickel, and lead; genotoxic metals, such as these are able to damage DNA and can bioaccumulate in organisms resulting in persistent exposure. In the Gulf of Mexico, whales are the apex species; hence we collected skin biopsies from sperm whales (Physeter macrocephalus), short-finned pilot whales (Globicephala macrorhynchus), and Bryde's whales (Balaenoptera edeni). The results from our three-year study of monitoring metal levels in whale skin show (1) genotoxic metals at concentrations higher than global averages previously reported and (2) patterns for MC252-relevant metal concentrations decreasing with time from the oil spill. Copyright © 2017 Elsevier Inc. All rights reserved.

  13. Stability of normative data for the SF-36: results of a three-year prospective study in middle-aged Canadians.

    Science.gov (United States)

    Hopman, Wilma M; Berger, Claudie; Joseph, Lawrence; Towheed, Tanveer; vandenKerkhof, Elizabeth; Anastassiades, Tassos; Cranney, Ann; Adachi, Jonathan D; Loannidis, George; Poliquin, Suzette; Brown, Jacques P; Murray, Timothy M; Hanley, David A; Papadimitropoulos, Emmanuel A; Tenenhouse, Alan

    2004-01-01

    The SF-36 is widely used to assess health-related quality of life (HRQOL), but with few longitudinal studies in healthy populations, it is difficult to quantify its natural history. This is important because any measure of change following an intervention may be confounded by natural changes in HRQOL. This paper assesses mean changes in SF-36 scores over a 3-year period in men and women between the ages of 40 and 59 years at baseline. Subjects were randomly selected from nine Canadian cities. Mean SF-36 changes over a 3-year period (1996/1997-1999/2000) were calculated for each gender within 5-year age categories. Multiple imputation was used to correct for potential bias due to missing data. The baseline cohort included 1,974 women and 975 men between 40 and 59 years. Mean changes in HRQOL tended to be small. Women demonstrated small average declines in 22 of the 32 age and domain groupings (4 age groups, 8 SF-36 domains) while men showed declines in 14/32. Most participants stayed within 10 points of their original baseline score. Mean SF-36 scores change only slightly over three years in middle-aged Canadians, although there is much individual variation. It may be necessary to adjust for the natural evolution of SF-36 scores when interpreting results from longitudinal studies.

  14. Time series clustering in large data sets

    Directory of Open Access Journals (Sweden)

    Jiří Fejfar

    2011-01-01

    Full Text Available The clustering of time series is a widely researched area. There are many methods for dealing with this task. We are actually using the Self-organizing map (SOM with the unsupervised learning algorithm for clustering of time series. After the first experiment (Fejfar, Weinlichová, Šťastný, 2009 it seems that the whole concept of the clustering algorithm is correct but that we have to perform time series clustering on much larger dataset to obtain more accurate results and to find the correlation between configured parameters and results more precisely. The second requirement arose in a need for a well-defined evaluation of results. It seems useful to use sound recordings as instances of time series again. There are many recordings to use in digital libraries, many interesting features and patterns can be found in this area. We are searching for recordings with the similar development of information density in this experiment. It can be used for musical form investigation, cover songs detection and many others applications.The objective of the presented paper is to compare clustering results made with different parameters of feature vectors and the SOM itself. We are describing time series in a simplistic way evaluating standard deviations for separated parts of recordings. The resulting feature vectors are clustered with the SOM in batch training mode with different topologies varying from few neurons to large maps.There are other algorithms discussed, usable for finding similarities between time series and finally conclusions for further research are presented. We also present an overview of the related actual literature and projects.

  15. Introduction to time series analysis and forecasting

    CERN Document Server

    Montgomery, Douglas C; Kulahci, Murat

    2015-01-01

    Praise for the First Edition ""…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics."" -MAA Reviews Thoroughly updated throughout, Introduction to Time Series Analysis and Forecasting, Second Edition presents the underlying theories of time series analysis that are needed to analyze time-oriented data and construct real-world short- to medium-term statistical forecasts.    Authored by highly-experienced academics and professionals in engineering statistics, the Second Edition features discussions on both

  16. Building Chaotic Model From Incomplete Time Series

    Science.gov (United States)

    Siek, Michael; Solomatine, Dimitri

    2010-05-01

    This paper presents a number of novel techniques for building a predictive chaotic model from incomplete time series. A predictive chaotic model is built by reconstructing the time-delayed phase space from observed time series and the prediction is made by a global model or adaptive local models based on the dynamical neighbors found in the reconstructed phase space. In general, the building of any data-driven models depends on the completeness and quality of the data itself. However, the completeness of the data availability can not always be guaranteed since the measurement or data transmission is intermittently not working properly due to some reasons. We propose two main solutions dealing with incomplete time series: using imputing and non-imputing methods. For imputing methods, we utilized the interpolation methods (weighted sum of linear interpolations, Bayesian principle component analysis and cubic spline interpolation) and predictive models (neural network, kernel machine, chaotic model) for estimating the missing values. After imputing the missing values, the phase space reconstruction and chaotic model prediction are executed as a standard procedure. For non-imputing methods, we reconstructed the time-delayed phase space from observed time series with missing values. This reconstruction results in non-continuous trajectories. However, the local model prediction can still be made from the other dynamical neighbors reconstructed from non-missing values. We implemented and tested these methods to construct a chaotic model for predicting storm surges at Hoek van Holland as the entrance of Rotterdam Port. The hourly surge time series is available for duration of 1990-1996. For measuring the performance of the proposed methods, a synthetic time series with missing values generated by a particular random variable to the original (complete) time series is utilized. There exist two main performance measures used in this work: (1) error measures between the actual

  17. Marihuana in Man: Three Years Later

    Science.gov (United States)

    Hollister, Leo E.

    1971-01-01

    Reviews three years of research on the effects of marihuana in man. Previously known clinical mental and physical effects have been confirmed. Causes and mechanisms of these effects generally remain undetermined in man and animals. Social implications and long term effects require additional study, although usage appears detrimental. (JM)

  18. Who is accessing public-sector anti-retroviral treatment in the Free State, South Africa? An exploratory study of the first three years of programme implementation

    Directory of Open Access Journals (Sweden)

    Booysen Frederik

    2010-07-01

    Full Text Available Abstract Background Although South Africa has the largest public-sector anti-retroviral treatment (ART programme in the world, anti-retroviral coverage in adults was only 40.2% in 2008. However, longitudinal studies of who is accessing the South African public-sector ART programme are scarce. This study therefore had one main research question: who is accessing public-sector ART in the Free State Province, South Africa? The study aimed to extend the current literature by investigating, in a quantitative manner and using a longitudinal study design, the participants enrolled in the public-sector ART programme in the period 2004-2006 in the Free State Province of South Africa. Methods Differences in the demographic (age, sex, population group and marital status socio-economic (education, income, neo-material indicators, geographic (travel costs, relocation for ART, and medical characteristics (CD4, viral load, time since first diagnosis, treatment status among 912 patients enrolled in the Free State public-sector ART programme between 2004 and 2006 were assessed with one-way analysis of variance, Bonferroni post-hoc analysis, and cross tabulations with the chi square test. Results The patients accessing treatment tended to be female (71.1% and unemployed (83.4%. However, although relatively poor, those most likely to access ART services were not the most impoverished patients. The proportion of female patients increased (P P P P P Conclusions Our analysis showed significant changes in the demographic, socio-economic, geographic, and medical characteristics of the patients during the first three years of the programme. Knowledge of the characteristics of these patients can assist policy makers in developing measures to retain them in care. The information reported here can also be usefully applied to target patient groups that are currently not reached in the implementation of the ART programme.

  19. Complex dynamic in ecological time series

    Science.gov (United States)

    Peter Turchin; Andrew D. Taylor

    1992-01-01

    Although the possibility of complex dynamical behaviors-limit cycles, quasiperiodic oscillations, and aperiodic chaos-has been recognized theoretically, most ecologists are skeptical of their importance in nature. In this paper we develop a methodology for reconstructing endogenous (or deterministic) dynamics from ecological time series. Our method consists of fitting...

  20. On modeling panels of time series

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans)

    2002-01-01

    textabstractThis paper reviews research issues in modeling panels of time series. Examples of this type of data are annually observed macroeconomic indicators for all countries in the world, daily returns on the individual stocks listed in the S&P500, and the sales records of all items in a

  1. Layered Ensemble Architecture for Time Series Forecasting.

    Science.gov (United States)

    Rahman, Md Mustafizur; Islam, Md Monirul; Murase, Kazuyuki; Yao, Xin

    2016-01-01

    Time series forecasting (TSF) has been widely used in many application areas such as science, engineering, and finance. The phenomena generating time series are usually unknown and information available for forecasting is only limited to the past values of the series. It is, therefore, necessary to use an appropriate number of past values, termed lag, for forecasting. This paper proposes a layered ensemble architecture (LEA) for TSF problems. Our LEA consists of two layers, each of which uses an ensemble of multilayer perceptron (MLP) networks. While the first ensemble layer tries to find an appropriate lag, the second ensemble layer employs the obtained lag for forecasting. Unlike most previous work on TSF, the proposed architecture considers both accuracy and diversity of the individual networks in constructing an ensemble. LEA trains different networks in the ensemble by using different training sets with an aim of maintaining diversity among the networks. However, it uses the appropriate lag and combines the best trained networks to construct the ensemble. This indicates LEAs emphasis on accuracy of the networks. The proposed architecture has been tested extensively on time series data of neural network (NN)3 and NN5 competitions. It has also been tested on several standard benchmark time series data. In terms of forecasting accuracy, our experimental results have revealed clearly that LEA is better than other ensemble and nonensemble methods.

  2. 25 years of time series forecasting

    NARCIS (Netherlands)

    de Gooijer, J.G.; Hyndman, R.J.

    2006-01-01

    We review the past 25 years of research into time series forecasting. In this silver jubilee issue, we naturally highlight results published in journals managed by the International Institute of Forecasters (Journal of Forecasting 1982-1985 and International Journal of Forecasting 1985-2005). During

  3. Introduction to time series and forecasting

    CERN Document Server

    Brockwell, Peter J

    2016-01-01

    This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space mod...

  4. Nonlinear Time Series Analysis via Neural Networks

    Science.gov (United States)

    Volná, Eva; Janošek, Michal; Kocian, Václav; Kotyrba, Martin

    This article deals with a time series analysis based on neural networks in order to make an effective forex market [Moore and Roche, J. Int. Econ. 58, 387-411 (2002)] pattern recognition. Our goal is to find and recognize important patterns which repeatedly appear in the market history to adapt our trading system behaviour based on them.

  5. Markov Trends in Macroeconomic Time Series

    NARCIS (Netherlands)

    R. Paap (Richard)

    1997-01-01

    textabstractMany macroeconomic time series are characterised by long periods of positive growth, expansion periods, and short periods of negative growth, recessions. A popular model to describe this phenomenon is the Markov trend, which is a stochastic segmented trend where the slope depends on the

  6. Modeling Time Series Data for Supervised Learning

    Science.gov (United States)

    Baydogan, Mustafa Gokce

    2012-01-01

    Temporal data are increasingly prevalent and important in analytics. Time series (TS) data are chronological sequences of observations and an important class of temporal data. Fields such as medicine, finance, learning science and multimedia naturally generate TS data. Each series provide a high-dimensional data vector that challenges the learning…

  7. Modeling vector nonlinear time series using POLYMARS

    NARCIS (Netherlands)

    de Gooijer, J.G.; Ray, B.K.

    2003-01-01

    A modified multivariate adaptive regression splines method for modeling vector nonlinear time series is investigated. The method results in models that can capture certain types of vector self-exciting threshold autoregressive behavior, as well as provide good predictions for more general vector

  8. Modeling seasonality in bimonthly time series

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans)

    1992-01-01

    textabstractA recurring issue in modeling seasonal time series variables is the choice of the most adequate model for the seasonal movements. One selection method for quarterly data is proposed in Hylleberg et al. (1990). Market response models are often constructed for bimonthly variables, and

  9. Time Series Modelling using Proc Varmax

    DEFF Research Database (Denmark)

    Milhøj, Anders

    2007-01-01

    In this paper it will be demonstrated how various time series problems could be met using Proc Varmax. The procedure is rather new and hence new features like cointegration, testing for Granger causality are included, but it also means that more traditional ARIMA modelling as outlined by Box...

  10. On clustering fMRI time series

    DEFF Research Database (Denmark)

    Goutte, Cyril; Toft, Peter Aundal; Rostrup, E.

    1999-01-01

    Analysis of fMRI time series is often performed by extracting one or more parameters for the individual voxels. Methods based, e.g., on various statistical tests are then used to yield parameters corresponding to probability of activation or activation strength. However, these methods do...

  11. Forecasting autoregressive time series under changing persistence

    DEFF Research Database (Denmark)

    Kruse, Robinson

    Changing persistence in time series models means that a structural change from nonstationarity to stationarity or vice versa occurs over time. Such a change has important implications for forecasting, as negligence may lead to inaccurate model predictions. This paper derives generally applicable...

  12. Robust Control Charts for Time Series Data

    NARCIS (Netherlands)

    Croux, C.; Gelper, S.; Mahieu, K.

    2010-01-01

    This article presents a control chart for time series data, based on the one-step- ahead forecast errors of the Holt-Winters forecasting method. We use robust techniques to prevent that outliers affect the estimation of the control limits of the chart. Moreover, robustness is important to maintain

  13. Optimal transformations for categorical autoregressive time series

    NARCIS (Netherlands)

    Buuren, S. van

    1996-01-01

    This paper describes a method for finding optimal transformations for analyzing time series by autoregressive models. 'Optimal' implies that the agreement between the autoregressive model and the transformed data is maximal. Such transformations help 1) to increase the model fit, and 2) to analyze

  14. Lecture notes for Advanced Time Series Analysis

    DEFF Research Database (Denmark)

    Madsen, Henrik; Holst, Jan

    1997-01-01

    A first version of this notes was used at the lectures in Grenoble, and they are now extended and improved (together with Jan Holst), and used in Ph.D. courses on Advanced Time Series Analysis at IMM and at the Department of Mathematical Statistics, University of Lund, 1994, 1997, ...

  15. Forecasting with periodic autoregressive time series models

    NARCIS (Netherlands)

    Ph.H.B.F. Franses (Philip Hans); R. Paap (Richard)

    1999-01-01

    textabstractThis paper is concerned with forecasting univariate seasonal time series data using periodic autoregressive models. We show how one should account for unit roots and deterministic terms when generating out-of-sample forecasts. We illustrate the models for various quarterly UK consumption

  16. Three-Year Outcomes in Kidney Transplant Patients Randomized to Steroid-Free Immunosuppression or Steroid Withdrawal, with Enteric-Coated Mycophenolate Sodium and Cyclosporine: The Infinity Study

    Directory of Open Access Journals (Sweden)

    A. Thierry

    2014-01-01

    Full Text Available In a six-month, multicenter, open-label trial, de novo kidney transplant recipients at low immunological risk were randomized to steroid avoidance or steroid withdrawal with IL-2 receptor antibody (IL-2RA induction, enteric-coated mycophenolate sodium (EC-MPS: 2160 mg/day to week 6, 1440 mg/day thereafter, and cyclosporine. Results from a 30-month observational follow-up study are presented. Of 166 patients who completed the core study on treatment, 131 entered the follow-up study (70 steroid avoidance, 61 steroid withdrawal. The primary efficacy endpoint of treatment failure (clinical biopsy-proven acute rejection (BPAR graft loss, death, or loss to follow-up occurred in 21.4% (95% CI 11.8–31.0% of steroid avoidance patients and 16.4% (95% CI 7.1–25.7% of steroid withdrawal patients by month 36 (P=0.46. BPAR had occurred in 20.0% and 11.5%, respectively (P=0.19. The incidence of adverse events with a suspected relation to steroids during months 6–36 was 22.9% versus 37.1% (P=0.062. By month 36, 32.4% and 51.7% of patients in the steroid avoidance and steroid withdrawal groups, respectively, were receiving oral steroids. In conclusion, IL-2RA induction with early intensified EC-MPS dosing and CNI therapy in de novo kidney transplant patients at low immunological risk may achieve similar three-year efficacy regardless of whether oral steroids are withheld for at least three months.

  17. Development of non-profit organisations providing health and social services in rural South Africa: a three-year longitudinal study.

    Directory of Open Access Journals (Sweden)

    Mosa Moshabela

    Full Text Available In an effort to increase understanding of formation of the community and home-based care economy in South Africa, we investigated the origin and development of non-profit organisations (NPOs providing home- and community-based care for health and social services in a remote rural area of South Africa.Over a three-year period (2010-12, we identified and tracked all NPOs providing health care and social services in Bushbuckridge sub-district through the use of local government records, snowballing techniques, and attendance at NPO networking meetings--recording both existing and new NPOs. NPO founders and managers were interviewed in face-to-face in-depth interviews, and their organisational records were reviewed.Forty-seven NPOs were formed prior to the study period, and 14 during the study period--six in 2010, six in 2011 and two in 2012, while four ceased operation, representing a 22% growth in the number of NPOs during the study period. Histories of NPOs showed a steady rise in the NPO formation over a 20-year period, from one (1991-1995 to 12 (1996-2000, 16 (2001-2005 and 24 (2006-2010 new organisations formed in each period. Furthermore, the histories of formation revealed three predominant milestones--loose association, formal formation and finally registration. Just over one quarter (28% of NPOs emerged from a long-standing community based programme of 'care groups' of women. Founders of NPOs were mostly women (62%, with either a religious motivation or a nursing background, but occasionally had an entrepreneurial profile.We observed rapid growth of the NPO sector providing community based health and social services. Women dominated the rural NPO sector, which is being seen as creating occupation and employment opportunities. The implications of this growth in the NPO sector providing community based health and social services needs to be further explored and suggests the need for greater coordination and possibly regulation.

  18. Neuroprotective body hypothermia among newborns with hypoxic ischemic encephalopathy: three-year experience in a tertiary university hospital. A retrospective observational study.

    Science.gov (United States)

    Magalhães, Mauricio; Rodrigues, Francisco Paulo Martins; Chopard, Maria Renata Tollio; Melo, Victoria Catarina de Albuquerque; Melhado, Amanda; Oliveira, Inez; Gallacci, Clery Bernardi; Pachi, Paulo Roberto; Lima Neto, Tabajara Barbosa

    2015-01-01

    Neonatal hypoxic-ischemic encephalopathy is associated with high morbidity and mortality. Studies have shown that therapeutic hypothermia decreases neurological sequelae and death. Our aim was therefore to report on a three-year experience of therapeutic hypothermia among asphyxiated newborns. Retrospective study, conducted in a university hospital. Thirty-five patients with perinatal asphyxia undergoing body cooling between May 2009 and November 2012 were evaluated. Thirty-nine infants fulfilled the hypothermia protocol criteria. Four newborns were removed from study due to refractory septic shock, non-maintenance of temperature and severe coagulopathy. The median Apgar scores at 1 and 5 minutes were 2 and 5. The main complication was infection, diagnosed in seven mothers (20%) and 14 newborns (40%). Convulsions occurred in 15 infants (43%). Thirty-one patients (88.6%) required mechanical ventilation and 14 of them (45%) were extubated within 24 hours. The duration of mechanical ventilation among the others was 7.7 days. The cooling protocol was started 1.8 hours after birth. All patients showed elevated levels of creatine phosphokinase, creatine phosphokinase- MB and lactate dehydrogenase. There was no severe arrhythmia; one newborn (2.9%) presented controlled coagulopathy. Four patients (11.4%) presented controlled hypotension. Twenty-nine patients (82.9%) underwent cerebral ultrasonography and 10 of them (34.5%) presented white matter hyper-echogenicity. Brain magnetic resonance imaging was performed on 33 infants (94.3%) and 11 of them (33.3%) presented hypoxic-ischemic changes. The hospital stay was 23 days. All newborns were discharged. Two patients (5.8%) needed gastrostomy. Hypothermia as therapy for asphyxiated newborns was shown to be safe.

  19. Neuroprotective body hypothermia among newborns with hypoxic ischemic encephalopathy: three-year experience in a tertiary university hospital. A retrospective observational study

    Directory of Open Access Journals (Sweden)

    Mauricio Magalhães

    Full Text Available CONTEXT AND OBJECTIVE:Neonatal hypoxic-ischemic encephalopathy is associated with high morbidity and mortality. Studies have shown that therapeutic hypothermia decreases neurological sequelae and death. Our aim was therefore to report on a three-year experience of therapeutic hypothermia among asphyxiated newborns.DESIGN AND SETTING:Retrospective study, conducted in a university hospital.METHODS:Thirty-five patients with perinatal asphyxia undergoing body cooling between May 2009 and November 2012 were evaluated.RESULTS:Thirty-nine infants fulfilled the hypothermia protocol criteria. Four newborns were removed from study due to refractory septic shock, non-maintenance of temperature and severe coagulopathy. The median Apgar scores at 1 and 5 minutes were 2 and 5. The main complication was infection, diagnosed in seven mothers (20% and 14 newborns (40%. Convulsions occurred in 15 infants (43%. Thirty-one patients (88.6% required mechanical ventilation and 14 of them (45% were extubated within 24 hours. The duration of mechanical ventilation among the others was 7.7 days. The cooling protocol was started 1.8 hours after birth. All patients showed elevated levels of creatine phosphokinase, creatine phosphokinase- MB and lactate dehydrogenase. There was no severe arrhythmia; one newborn (2.9% presented controlled coagulopathy. Four patients (11.4% presented controlled hypotension. Twenty-nine patients (82.9% underwent cerebral ultrasonography and 10 of them (34.5% presented white matter hyper-echogenicity. Brain magnetic resonance imaging was performed on 33 infants (94.3% and 11 of them (33.3% presented hypoxic-ischemic changes. The hospital stay was 23 days. All newborns were discharged. Two patients (5.8% needed gastrostomy.CONCLUSION:Hypothermia as therapy for asphyxiated newborns was shown to be safe.

  20. Gender specific differences in neurodevelopmental effects of prenatal exposure to very low-lead levels: the prospective cohort study in three-year olds.

    Science.gov (United States)

    Jedrychowski, Wieslaw; Perera, Frederica; Jankowski, Jeffery; Mrozek-Budzyn, Dorota; Mroz, Elzbieta; Flak, Elzbieta; Edwards, Susan; Skarupa, Anita; Lisowska-Miszczyk, Ilona

    2009-08-01

    The primary purpose of this study was to assess the relationship between very low-level of prenatal lead exposure measured in the cord blood (cognitive deficits in the course of the first three years of life. The accumulated lead dose in infants over the pregnancy period was measured by the cord blood lead level (BLL) and cognitive deficits were assessed by the Bayley Mental Development Index (MDI). The study sample consisted of 457 children born to non-smoking women living in the inner city and the outlying residential areas of Krakow. The relationship between prenatal lead exposure and MDI scores measured at 12, 24 and 36 months of age and adjusted to a set of important covariates (gender of child, maternal education, parity, breastfeeding, prenatal and postnatal environmental tobacco smoke) was evaluated with linear multivariate regression, and the Generalized Estimating Equations (GEE) longitudinal panel model. The median of lead level in cord blood was 1.21 microg/dL with the range of values from 0.44 to 4.60 microg/dL. Neither prenatal BLL (dichotomized by median) nor other covariates affected MDI score at 12 months of age. Subsequent testing of children at 24 months of age showed a borderline significant inverse association of lead exposure and mental function (beta coefficient=-2.42, 95%CI: -4.90 to 0.03), but the interaction term (BLL x male gender) was not significant. At 36 months, prenatal lead exposure was inversely and significantly associated with cognitive function in boys (Spearman correlation coefficient=-0.239, p=0.0007) but not girls (r=-0.058, p=0.432) and the interaction between BLL and male gender was significant (beta coefficient=-4.46; 95%CI: -8.28 to -0.63). Adjusted estimates of MDI deficit in boys at 36 months confirmed very strong negative impact of prenatal lead exposure (BLL>1.67 microg/dL) compared with the lowest quartile of exposure (beta coefficient=-6.2, p=0.002), but the effect in girls was insignificant (beta coefficient=-0

  1. Multiresolution analysis of Bursa Malaysia KLCI time series

    Science.gov (United States)

    Ismail, Mohd Tahir; Dghais, Amel Abdoullah Ahmed

    2017-05-01

    In general, a time series is simply a sequence of numbers collected at regular intervals over a period. Financial time series data processing is concerned with the theory and practice of processing asset price over time, such as currency, commodity data, and stock market data. The primary aim of this study is to understand the fundamental characteristics of selected financial time series by using the time as well as the frequency domain analysis. After that prediction can be executed for the desired system for in sample forecasting. In this study, multiresolution analysis which the assist of discrete wavelet transforms (DWT) and maximal overlap discrete wavelet transform (MODWT) will be used to pinpoint special characteristics of Bursa Malaysia KLCI (Kuala Lumpur Composite Index) daily closing prices and return values. In addition, further case study discussions include the modeling of Bursa Malaysia KLCI using linear ARIMA with wavelets to address how multiresolution approach improves fitting and forecasting results.

  2. [Clinical features and course of Kawasaki disease in central Tunisia: a study about 14 cases collected over a period of three years (2000-2002)].

    Science.gov (United States)

    Chemli, Jalel; Kchaou, Habib; Amri, Fethi; Belkadhi, Adel; Essoussi, Ahmed Sahloul; Gueddiche, Neji; Harbi, Abdelaziz

    2005-08-01

    To analyze the clinical features and course of Kawasaki disease in central Tunisia. We studied retrospectively 14 cases of children with Kawasaki disease collected in tunisian center during three years (2000-2002). The study is about 11 boys and 3 girls (sex - ratio: 3.6/1) aged from 6 months to 8 years (mean age : 4 years). Twelve patients had at least 5 diagnostic criteria of the illness, the two others had an incomplete form. We noted cardiac complications in seven patients treated belatedly, beyond 10 days of progression, because of atypical clinical presentations. All patients had all a middle caliber coronary aneurysm that was complicated by a thrombus in three cases, associated with pericarditis and minimal mitral insufficiency in a case and with a cardiac rhythm disturbance (block of branch) in another case. Besides the cardiac complications, several other visceral manifestation could be noted: joint symptoms in five cases, GI tract symptomes in three cases, neuro-meningeal in two cases and urinary trad symptomes in two other cases. Specific treatment (aspirin with antiinflammatory dose and intravenous immune globulin (IVIG)) has been instituted in all patients. The course was favorable for 12 patients with fast regression of clinical manifestation and progressive normalisation of biologic values. Two patients did not respond to the initial IVIG treatment, and had to recense received an additional course of IGIV but without clinical nor biological improvement. These two patients were treated with corticosteroids. Cardiac lesions disappeared completely in all patients even for those with thrombosis and in patients with IVIG-resistant Kawasaki disease. Only one patient had kept neurologic sequellae: aphasia, bevavioral problemes and partial epilepsy. Kawasaki disease is not rare in our region. Incomplete or atypical presentations are frequent and are a source of diagnostic delay. Coronary aneurysm due to the delay of treatment often regresses even in patients

  3. Self-affinity in the dengue fever time series

    Science.gov (United States)

    Azevedo, S. M.; Saba, H.; Miranda, J. G. V.; Filho, A. S. Nascimento; Moret, M. A.

    2016-06-01

    Dengue is a complex public health problem that is common in tropical and subtropical regions. This disease has risen substantially in the last three decades, and the physical symptoms depict the self-affine behavior of the occurrences of reported dengue cases in Bahia, Brazil. This study uses detrended fluctuation analysis (DFA) to verify the scale behavior in a time series of dengue cases and to evaluate the long-range correlations that are characterized by the power law α exponent for different cities in Bahia, Brazil. The scaling exponent (α) presents different long-range correlations, i.e. uncorrelated, anti-persistent, persistent and diffusive behaviors. The long-range correlations highlight the complex behavior of the time series of this disease. The findings show that there are two distinct types of scale behavior. In the first behavior, the time series presents a persistent α exponent for a one-month period. For large periods, the time series signal approaches subdiffusive behavior. The hypothesis of the long-range correlations in the time series of the occurrences of reported dengue cases was validated. The observed self-affinity is useful as a forecasting tool for future periods through extrapolation of the α exponent behavior. This complex system has a higher predictability in a relatively short time (approximately one month), and it suggests a new tool in epidemiological control strategies. However, predictions for large periods using DFA are hidden by the subdiffusive behavior.

  4. Nonlinear time series analysis of the human electrocardiogram

    International Nuclear Information System (INIS)

    Perc, Matjaz

    2005-01-01

    We analyse the human electrocardiogram with simple nonlinear time series analysis methods that are appropriate for graduate as well as undergraduate courses. In particular, attention is devoted to the notions of determinism and stationarity in physiological data. We emphasize that methods of nonlinear time series analysis can be successfully applied only if the studied data set originates from a deterministic stationary system. After positively establishing the presence of determinism and stationarity in the studied electrocardiogram, we calculate the maximal Lyapunov exponent, thus providing interesting insights into the dynamics of the human heart. Moreover, to facilitate interest and enable the integration of nonlinear time series analysis methods into the curriculum at an early stage of the educational process, we also provide user-friendly programs for each implemented method

  5. Impact of the 13-Valent Pneumococcal Conjugate Vaccine on Clinical and Hypoxemic Childhood Pneumonia over Three Years in Central Malawi: An Observational Study

    Science.gov (United States)

    McCollum, Eric D.; Nambiar, Bejoy; Deula, Rashid; Zadutsa, Beatiwel; Bondo, Austin; King, Carina; Beard, James; Liyaya, Harry; Mankhambo, Limangeni; Lazzerini, Marzia; Makwenda, Charles; Masache, Gibson; Bar-Zeev, Naor; Kazembe, Peter N.; Mwansambo, Charles; Lufesi, Norman; Costello, Anthony; Armstrong, Ben

    2017-01-01

    Background The pneumococcal conjugate vaccine’s (PCV) impact on childhood pneumonia during programmatic conditions in Africa is poorly understood. Following PCV13 introduction in Malawi in November 2011, we evaluated the case burden and rates of childhood pneumonia. Methods and Findings Between January 1, 2012-June 30, 2014 we conducted active pneumonia surveillance in children pneumonia per Malawi guidelines, defined as fast breathing only, chest indrawing +/- fast breathing, or, ≥1 clinical danger sign. Since pulse oximetry was not in the Malawi guidelines, oxygenation pneumonia, a distinct category from clinical pneumonia. We quantified the pneumonia case burden and rates in two ways. We compared the period immediately following vaccine introduction (early) to the period with >75% three-dose PCV13 coverage (post). We also used multivariable time-series regression, adjusting for autocorrelation and exploring seasonal variation and alternative model specifications in sensitivity analyses. The early versus post analysis showed an increase in cases and rates of total, fast breathing, and indrawing pneumonia and a decrease in danger sign and hypoxemic pneumonia, and pneumonia mortality. At 76% three-dose PCV13 coverage, versus 0%, the time-series model showed a non-significant increase in total cases (+47%, 95% CI: -13%, +149%, p = 0.154); fast breathing cases increased 135% (+39%, +297%, p = 0.001), however, hypoxemia fell 47% (-5%, -70%, p = 0.031) and hospital deaths decreased 36% (-1%, -58%, p = 0.047) in children pneumonia, including hypoxemia and death, have markedly decreased. PMID:28052071

  6. What marketing scholars should know about time series analysis : time series applications in marketing

    NARCIS (Netherlands)

    Horváth, Csilla; Kornelis, Marcel; Leeflang, Peter S.H.

    2002-01-01

    In this review, we give a comprehensive summary of time series techniques in marketing, and discuss a variety of time series analysis (TSA) techniques and models. We classify them in the sets (i) univariate TSA, (ii) multivariate TSA, and (iii) multiple TSA. We provide relevant marketing

  7. Soil CH4 and N2O Emissions from Rice Paddy Fields in Southern Brazil as Affected by Crop Management Levels: a Three-Year Field Study

    Directory of Open Access Journals (Sweden)

    Tiago Zschornack

    2018-05-01

    Full Text Available ABSTRACT Rice yield increases in response to improvements in crop management, but the impact on greenhouse gas (GHG emissions in the subtropical region of Southern Brazil remains unknown. A three-year field study was developed aiming to evaluate the impact that an increase in crop management levels (high and very high has on soil methane (CH4 and nitrous oxide (N2O emissions, as compared to the level (medium currently adopted by farmers in Southern Brazil. Differences in crop management included seed and fertilizer rates, irrigation, and pesticide use. The effect of crop management levels on the annual partial global warming potential (pGWP = CH4 × 25 + N2O × 298 ranged from 7,547 to 17,711 kg CO2eq ha−1 and this effect was larger than on the rice grain yield (9,280 to 12,260 kg ha−1, resulting in approximately 60 % higher yield-scaled GHG with the high crop management level compared to the current level. Soil CH4 emissions accounted for 98 % of pGWP in the flooded rice season, whereas N2O prevailed during the drained non-rice season (≈65 %. Although it was impossible to relate emissions to any individual input or practice, soil CH4 emissions in the rice season were linearly related to the biomass produced by the rice crop (p<0.01 and by ryegrass in the previous non-rice season (p<0.1, both of which were possibly related to the supply of labile C for methanogenesis. A future increase in rice yield as a result of the adoption of improved crop management may require additional agricultural practices (e.g., intermittent irrigation to offset the increased GHG emissions.

  8. Impact of Indian Total Sanitation Campaign on latrine coverage and use: a cross-sectional study in Orissa three years following programme implementation.

    Directory of Open Access Journals (Sweden)

    Sharmani Barnard

    Full Text Available BACKGROUND: Faced with a massive shortfall in meeting sanitation targets, some governments have implemented campaigns that use subsidies focused on latrine construction to overcome income constraints and rapidly expand coverage. In settings like rural India where open defecation is common, this may result in sub-optimal compliance (use, thereby continuing to leave the population exposed to human excreta. METHODS: We conducted a cross-sectional study to investigate latrine coverage and use among 20 villages (447 households, 1933 individuals in Orissa, India where the Government of India's Total Sanitation Campaign had been implemented at least three years previously. We defined coverage as the proportion of households that had a latrine; for use we identified the proportion of households with at least one reported user and among those, the extent of reported use by each member of the household. RESULTS: Mean latrine coverage among the villages was 72% (compared to <10% in comparable villages in the same district where the Total Sanitation Campaign had not yet been implemented, though three of the villages had less than 50% coverage. Among these households with latrines, more than a third (39% were not being used by any member of the household. Well over a third (37% of the members of households with latrines reported never defecating in their latrines. Less than half (47% of the members of such households reported using their latrines at all times for defecation. Combined with the 28% of households that did not have latrines, it appears that most defecation events in these communities are still practiced in the open. CONCLUSION: A large-scale campaign to implement sanitation has achieved substantial gains in latrine coverage in this population. Nevertheless, gaps in coverage and widespread continuation of open defecation will result in continued exposure to human excreta, reducing the potential for health gains.

  9. Temperature, salinity and and pigment data from CTD and bottle samples from the Bermuda Time Series (BATS/JGOFS) study area, Oct 1988 - Sep 1990 (NODC Accession 9200088)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Joint Global Ocean Flux Study (JGOFS) is an international and multi- disciplinary study with a primary objective of understanding global oceanic carbon and...

  10. Neural network versus classical time series forecasting models

    Science.gov (United States)

    Nor, Maria Elena; Safuan, Hamizah Mohd; Shab, Noorzehan Fazahiyah Md; Asrul, Mohd; Abdullah, Affendi; Mohamad, Nurul Asmaa Izzati; Lee, Muhammad Hisyam

    2017-05-01

    Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.

  11. Three-year study of fast-growing trees in degraded soils amended with composts: Effects on soil fertility and productivity.

    Science.gov (United States)

    Madejón, Paula; Alaejos, Joaquin; García-Álbala, José; Fernández, Manuel; Madejón, Engracia

    2016-03-15

    Currently, worries about the effects of intensive plantations on long-term nutrient supply and a loss of productivity have risen. In this study two composts were added to degraded soils where this type of intensive crops were growing, to avoid the soil fertility decrease and try to increase biomass production. For the experiment, two degraded soils in terms of low organic carbon content and low pH were selected in South-West Spain: La Rábida (RA) and Villablanca (VI) sites. Both study sites were divided into 24 plots. In RA, half of the plots were planted with Populus x canadensis "I-214"; the other half was planted with Eucalyptus globulus. At the VI site, half of the plots were planted with Paulownia fortunei, and the other plots were planted with Eucalyptus globulus. For each tree and site, three treatments were established (two organic composts and a control without compost), with four replications per treatment. The organic amendments were "alperujo" compost, AC, a solid by-product from the extraction of olive oil, and BC, biosolid compost. During the three years of experimentation, samples of soils and plants were analyzed for studying chemical and biochemical properties of soil, plant growth and plant nutritional status and biomass production. The composts increased total organic carbon, water-soluble carbon, nutrients and pH of soil only in the most acidic soil. Soil biochemical quality was calculated with the geometric mean of the enzymatic activities (Dehydrogenase, β-glucosidase, Phosphatase and Urease activities) determined in soils. The results showed a beneficial improvement in comparison with soils without compost. However, the best results were found in the growth and biomass production of the studied trees, especially in Eucalyptus. Nutritional levels of leaves of the trees were, in general, in the normal established range for each species, although no clear effect of the composts was observed. The results of this study justify the addition of

  12. Data imputation analysis for Cosmic Rays time series

    Science.gov (United States)

    Fernandes, R. C.; Lucio, P. S.; Fernandez, J. H.

    2017-05-01

    The occurrence of missing data concerning Galactic Cosmic Rays time series (GCR) is inevitable since loss of data is due to mechanical and human failure or technical problems and different periods of operation of GCR stations. The aim of this study was to perform multiple dataset imputation in order to depict the observational dataset. The study has used the monthly time series of GCR Climax (CLMX) and Roma (ROME) from 1960 to 2004 to simulate scenarios of 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% and 90% of missing data compared to observed ROME series, with 50 replicates. Then, the CLMX station as a proxy for allocation of these scenarios was used. Three different methods for monthly dataset imputation were selected: AMÉLIA II - runs the bootstrap Expectation Maximization algorithm, MICE - runs an algorithm via Multivariate Imputation by Chained Equations and MTSDI - an Expectation Maximization algorithm-based method for imputation of missing values in multivariate normal time series. The synthetic time series compared with the observed ROME series has also been evaluated using several skill measures as such as RMSE, NRMSE, Agreement Index, R, R2, F-test and t-test. The results showed that for CLMX and ROME, the R2 and R statistics were equal to 0.98 and 0.96, respectively. It was observed that increases in the number of gaps generate loss of quality of the time series. Data imputation was more efficient with MTSDI method, with negligible errors and best skill coefficients. The results suggest a limit of about 60% of missing data for imputation, for monthly averages, no more than this. It is noteworthy that CLMX, ROME and KIEL stations present no missing data in the target period. This methodology allowed reconstructing 43 time series.

  13. Minimum entropy density method for the time series analysis

    Science.gov (United States)

    Lee, Jeong Won; Park, Joongwoo Brian; Jo, Hang-Hyun; Yang, Jae-Suk; Moon, Hie-Tae

    2009-01-01

    The entropy density is an intuitive and powerful concept to study the complicated nonlinear processes derived from physical systems. We develop the minimum entropy density method (MEDM) to detect the structure scale of a given time series, which is defined as the scale in which the uncertainty is minimized, hence the pattern is revealed most. The MEDM is applied to the financial time series of Standard and Poor’s 500 index from February 1983 to April 2006. Then the temporal behavior of structure scale is obtained and analyzed in relation to the information delivery time and efficient market hypothesis.

  14. Bootstrap Power of Time Series Goodness of fit tests

    Directory of Open Access Journals (Sweden)

    Sohail Chand

    2013-10-01

    Full Text Available In this article, we looked at power of various versions of Box and Pierce statistic and Cramer von Mises test. An extensive simulation study has been conducted to compare the power of these tests. Algorithms have been provided for the power calculations and comparison has also been made between the semi parametric bootstrap methods used for time series. Results show that Box-Pierce statistic and its various versions have good power against linear time series models but poor power against non linear models while situation reverses for Cramer von Mises test. Moreover, we found that dynamic bootstrap method is better than xed design bootstrap method.

  15. Trends in hospital admissions and surgical procedures for degenerative lumbar spine disease in England: a 15-year time-series study

    Science.gov (United States)

    Sivasubramaniam, Vinothan; Patel, Hitesh C; Ozdemir, Baris A; Papadopoulos, Marios C

    2015-01-01

    Objectives Low back pain (LBP), from degenerative lumbar spine disease, represents a significant burden on healthcare resources. Studies worldwide report trends attributable to their country's specific demographics and healthcare system. Considering England's specific medico-socioeconomic conditions, we investigate recent trends in hospital admissions and procedures for LBP, and discuss the implications for the allocation of healthcare resources. Design Retrospective cohort study using Hospital Episode Statistics data relating to degenerative lumbar spine disease in England, between 1999 and 2013. Regression models were used to analyse trends. Outcome measures Trends in the number of admissions and procedures for LBP, mean patient age, gender and length of stay. Results Hospital admissions and procedures have increased significantly over the study period, from 127.09 to 216.16 and from 24.5 to 48.83 per 100 000, respectively, (pdisease, and highlight the need for services capable of dealing with the increased comorbidity burden associated with an ageing patient group. PMID:26671956

  16. The role of high-involvement work practices and professional self-image in nursing recruits' turnover: A three-year prospective study.

    Science.gov (United States)

    Chênevert, Denis; Jourdain, Geneviève; Vandenberghe, Christian

    2016-01-01

    The retention of young graduate nurses has become a major management challenge among hospitals in Western countries, which is amplified in a context of aging of populations and an increasing demand for services from patients. Moreover, as it has been reported that 50% of experienced nurses do not recommend a career in nursing, it is likely that retention problems occur not only at the level of the organization, but also at the level of the nursing profession. Although research has identified some predictors of nurse turnover, it is unclear which factors influence nurses' turnover from the organization and from the profession and how these factors interrelate with one another over time. The present study extends previous research on nurse turnover by looking at the combined effects of nurses' pre-entry expectations, perceived high-involvement work practices, and professional self-image, on intended and actual turnover from the organization and the profession. A prospective, longitudinal study of a sample of 160 graduated nurses affiliated with the Quebec Nurses' Association, Canada, was conducted. Participants were surveyed at three points in time, spread over a 3-year period. Graduated nurses' pre-entry expectations and professional self-image were surveyed at graduation (Time 1), while perceived high-involvement work practices, professional self-image, and intention to leave the organization and the profession were captured six months following nurses' entry into the labor market (Time 2). Finally, participants were surveyed with respect to organizational and professional turnover three years after the Time 2 survey (Time 3). Structural equations modeling was used to examine the structure of the measures and the relationships among the constructs. Although pre-entry expectations had no effect, perceived high-involvement work practices were positively related to Time 2, professional self-image (controlling for pre-entry professional self-image). Moreover, high

  17. HPLC-MS analysis of secondary metabolites in leaves from orange trees infected with Huanglongbing: A 9-month time series study

    Science.gov (United States)

    Huanglongbing (HLB) disease, presumably caused by Canditatus Liberibacter asiaticus (CLas), is threatening one million acres of commercial citrus groves that have an annual production value of approximately $3 billion across the U.S. The objectives of this study were to identify the earliest signifi...

  18. Predicting Rehabilitation Success Rate Trends among Ethnic Minorities Served by State Vocational Rehabilitation Agencies: A National Time Series Forecast Model Demonstration Study

    Science.gov (United States)

    Moore, Corey L.; Wang, Ningning; Washington, Janique Tynez

    2017-01-01

    Purpose: This study assessed and demonstrated the efficacy of two select empirical forecast models (i.e., autoregressive integrated moving average [ARIMA] model vs. grey model [GM]) in accurately predicting state vocational rehabilitation agency (SVRA) rehabilitation success rate trends across six different racial and ethnic population cohorts…

  19. Visibility graphlet approach to chaotic time series

    Energy Technology Data Exchange (ETDEWEB)

    Mutua, Stephen [Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China); Computer Science Department, Masinde Muliro University of Science and Technology, P.O. Box 190-50100, Kakamega (Kenya); Gu, Changgui, E-mail: gu-changgui@163.com, E-mail: hjyang@ustc.edu.cn; Yang, Huijie, E-mail: gu-changgui@163.com, E-mail: hjyang@ustc.edu.cn [Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China)

    2016-05-15

    Many novel methods have been proposed for mapping time series into complex networks. Although some dynamical behaviors can be effectively captured by existing approaches, the preservation and tracking of the temporal behaviors of a chaotic system remains an open problem. In this work, we extended the visibility graphlet approach to investigate both discrete and continuous chaotic time series. We applied visibility graphlets to capture the reconstructed local states, so that each is treated as a node and tracked downstream to create a temporal chain link. Our empirical findings show that the approach accurately captures the dynamical properties of chaotic systems. Networks constructed from periodic dynamic phases all converge to regular networks and to unique network structures for each model in the chaotic zones. Furthermore, our results show that the characterization of chaotic and non-chaotic zones in the Lorenz system corresponds to the maximal Lyapunov exponent, thus providing a simple and straightforward way to analyze chaotic systems.

  20. Time-Series Analysis: A Cautionary Tale

    Science.gov (United States)

    Damadeo, Robert

    2015-01-01

    Time-series analysis has often been a useful tool in atmospheric science for deriving long-term trends in various atmospherically important parameters (e.g., temperature or the concentration of trace gas species). In particular, time-series analysis has been repeatedly applied to satellite datasets in order to derive the long-term trends in stratospheric ozone, which is a critical atmospheric constituent. However, many of the potential pitfalls relating to the non-uniform sampling of the datasets were often ignored and the results presented by the scientific community have been unknowingly biased. A newly developed and more robust application of this technique is applied to the Stratospheric Aerosol and Gas Experiment (SAGE) II version 7.0 ozone dataset and the previous biases and newly derived trends are presented.

  1. Time Series Analysis Using Geometric Template Matching.

    Science.gov (United States)

    Frank, Jordan; Mannor, Shie; Pineau, Joelle; Precup, Doina

    2013-03-01

    We present a novel framework for analyzing univariate time series data. At the heart of the approach is a versatile algorithm for measuring the similarity of two segments of time series called geometric template matching (GeTeM). First, we use GeTeM to compute a similarity measure for clustering and nearest-neighbor classification. Next, we present a semi-supervised learning algorithm that uses the similarity measure with hierarchical clustering in order to improve classification performance when unlabeled training data are available. Finally, we present a boosting framework called TDEBOOST, which uses an ensemble of GeTeM classifiers. TDEBOOST augments the traditional boosting approach with an additional step in which the features used as inputs to the classifier are adapted at each step to improve the training error. We empirically evaluate the proposed approaches on several datasets, such as accelerometer data collected from wearable sensors and ECG data.

  2. Nonlinear time series analysis with R

    CERN Document Server

    Huffaker, Ray; Rosa, Rodolfo

    2017-01-01

    In the process of data analysis, the investigator is often facing highly-volatile and random-appearing observed data. A vast body of literature shows that the assumption of underlying stochastic processes was not necessarily representing the nature of the processes under investigation and, when other tools were used, deterministic features emerged. Non Linear Time Series Analysis (NLTS) allows researchers to test whether observed volatility conceals systematic non linear behavior, and to rigorously characterize governing dynamics. Behavioral patterns detected by non linear time series analysis, along with scientific principles and other expert information, guide the specification of mechanistic models that serve to explain real-world behavior rather than merely reproducing it. Often there is a misconception regarding the complexity of the level of mathematics needed to understand and utilize the tools of NLTS (for instance Chaos theory). However, mathematics used in NLTS is much simpler than many other subjec...

  3. A time-series study of sick building syndrome: chronic, biotoxin-associated illness from exposure to water-damaged buildings.

    Science.gov (United States)

    Shoemaker, Ritchie C; House, Dennis E

    2005-01-01

    The human health risk for chronic illnesses involving multiple body systems following inhalation exposure to the indoor environments of water-damaged buildings (WDBs) has remained poorly characterized and the subject of intense controversy. The current study assessed the hypothesis that exposure to the indoor environments of WDBs with visible microbial colonization was associated with illness. The study used a cross-sectional design with assessments at five time points, and the interventions of cholestyramine (CSM) therapy, exposure avoidance following therapy, and reexposure to the buildings after illness resolution. The methodological approach included oral administration of questionnaires, medical examinations, laboratory analyses, pulmonary function testing, and measurements of visual function. Of the 21 study volunteers, 19 completed assessment at each of the five time points. Data at Time Point 1 indicated multiple symptoms involving at least four organ systems in all study participants, a restrictive respiratory condition in four participants, and abnormally low visual contrast sensitivity (VCS) in 18 participants. Serum leptin levels were abnormally high and alpha melanocyte stimulating hormone (MSH) levels were abnormally low. Assessments at Time Point 2, following 2 weeks of CSM therapy, indicated a highly significant improvement in health status. Improvement was maintained at Time Point 3, which followed exposure avoidance without therapy. Reexposure to the WDBs resulted in illness reacquisition in all participants within 1 to 7 days. Following another round of CSM therapy, assessments at Time Point 5 indicated a highly significant improvement in health status. The group-mean number of symptoms decreased from 14.9+/-0.8 S.E.M. at Time Point 1 to 1.2+/-0.3 S.E.M., and the VCS deficit of approximately 50% at Time Point 1 was fully resolved. Leptin and MSH levels showed statistically significant improvement. The results indicated that CSM was an effective

  4. Ambient Levels of Primary and Secondary Pollutants in a Residential Area: Population Risk and Hazard Index Calculation over a Three Years Study Period

    OpenAIRE

    S. Al-Salem; A. Al-Fadhlee

    2007-01-01

    This paper aims at presenting data collected over the period of three years (2004-2006) in a residential area in the state of Kuwait. The data collected include ambient levels of primary and secondary pollutants with a number of metrological parameters. A series of unfiltered and filtered concentration roses were plotted to determine the predominant sources as well as the prevailing winds affecting the area under investigation. Local and international air quality regulations were cross refere...

  5. Turbulencelike Behavior of Seismic Time Series

    International Nuclear Information System (INIS)

    Manshour, P.; Saberi, S.; Sahimi, Muhammad; Peinke, J.; Pacheco, Amalio F.; Rahimi Tabar, M. Reza

    2009-01-01

    We report on a stochastic analysis of Earth's vertical velocity time series by using methods originally developed for complex hierarchical systems and, in particular, for turbulent flows. Analysis of the fluctuations of the detrended increments of the series reveals a pronounced transition in their probability density function from Gaussian to non-Gaussian. The transition occurs 5-10 hours prior to a moderate or large earthquake, hence representing a new and reliable precursor for detecting such earthquakes

  6. Time Series Forecasting with Missing Values

    OpenAIRE

    Shin-Fu Wu; Chia-Yung Chang; Shie-Jue Lee

    2015-01-01

    Time series prediction has become more popular in various kinds of applications such as weather prediction, control engineering, financial analysis, industrial monitoring, etc. To deal with real-world problems, we are often faced with missing values in the data due to sensor malfunctions or human errors. Traditionally, the missing values are simply omitted or replaced by means of imputation methods. However, omitting those missing values may cause temporal discontinuity. Imputation methods, o...

  7. Time series analysis of barometric pressure data

    International Nuclear Information System (INIS)

    La Rocca, Paola; Riggi, Francesco; Riggi, Daniele

    2010-01-01

    Time series of atmospheric pressure data, collected over a period of several years, were analysed to provide undergraduate students with educational examples of application of simple statistical methods of analysis. In addition to basic methods for the analysis of periodicities, a comparison of two forecast models, one based on autoregression algorithms, and the other making use of an artificial neural network, was made. Results show that the application of artificial neural networks may give slightly better results compared to traditional methods.

  8. Investigation of Relationship Between Hydrologic Processes of Precipitation, Evaporation and Stream Flow Using Linear Time Series Models (Case study: Western Basins of Lake Urmia)

    OpenAIRE

    M. Moravej; K. Khalili; J. Behmanesh

    2016-01-01

    Introduction: Studying the hydrological cycle, especially in large scales such as water catchments, is difficult and complicated despite the fact that the numbers of hydrological components are limited. This complexity rises from complex interactions between hydrological components and environment. Recognition, determination and modeling of all interactive processes are needed to address this issue, but it's not feasible for dealing with practical engineering problems. So, it is more convenie...

  9. Do romantic partners influence each other's heavy episodic drinking? Support for the partner influence hypothesis in a three-year longitudinal study.

    Science.gov (United States)

    Bartel, Sara J; Sherry, Simon B; Molnar, Danielle S; Mushquash, Aislin R; Leonard, Kenneth E; Flett, Gordon L; Stewart, Sherry H

    2017-06-01

    Approximately one in five adults engage in heavy episodic drinking (HED), a behavior with serious health and social consequences. Environmental, intrapersonal, and interpersonal factors contribute to and perpetuate HED. Prior research supports the partner influence hypothesis where partners influence each other's HED. We examined the partner influence hypothesis longitudinally over three years in heterosexual couples in serious romantic relationships, while exploring possible sex differences in the magnitude of partner influence. One-hundred-and-seventy-nine heterosexual couples in serious relationships (38.5% married at baseline) completed a measure of HED at baseline and again three years later. Using actor-partner interdependence modelling, results showed actor effects for both men and women, with HED remaining stable for each partner from baseline to follow-up. Significant partner effects were found for both men and women, who both positively influenced their partners' HED over the three-year follow-up. The partner influence hypothesis was supported. Results indicated partner influences on HED occur over the longer term and apply to partners in varying stages of serious romantic relationships (e.g., cohabiting, engaged, married). Women were found to influence their partners' HED just as much as men influence their partners' HED. Findings suggest HED should be assessed and treated as a couples' issue rather than simply as an individual risky behavior. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. Time Series of Landscape Fragmentation Caused by Transportation Infrastructure and Urban Development: a Case Study from Baden-Württemberg, Germany

    Directory of Open Access Journals (Sweden)

    Jochen A. G. Jaeger

    2007-06-01

    Full Text Available Landscape fragmentation is increasingly considered an important environmental indicator in the fields of sustainable land use and biodiversity. To set goals for future development and to plan appropriate measures, suitable empirical data on the degree of landscape fragmentation are needed to identify trends and compare different regions. However, there is still a significant lack of data on landscape fragmentation as an indicator, despite the substantial scientific literature on this topic, likely because of confusion over the definition of "fragmentation," questions associated with scale and data issues, and lack of general agreement on a fragmentation measure. This study presents a state-wide quantitative analysis of landscape fragmentation in Baden-Württemberg, Germany, by means of the "effective mesh size" (meff, which characterizes the anthropogenic penetration of landscapes from a geometric point of view and is based on the probability that two randomly chosen points in a landscape are connected, i.e., not separated by barriers such as roads, railroads, or urban areas. Baden-Württemberg is fragmented to a far greater extent than indicated by previous studies. The meff has decreased by 40% since 1930. This development is strongly related to the growing number of inhabitants, the increased use of motorized vehicles, and the hierarchical regional planning system based on the central place theory. To illustrate the suitability of the meff method for environmental monitoring, as a planning instrument and as an assessment instrument for impact assessment studies, we explored several variations of applying the method with regard to choice of fragmenting elements, consideration of noise bands, spatial differentiation (e.g., administrative districts vs. ecoregions, and way of dealing with patches at the boundaries of the reporting units. Depending on the objectives of the investigation (e.g., recreational quality vs. suitability for wildlife

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

    Science.gov (United States)

    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.

  12. Interpretable Categorization of Heterogeneous Time Series Data

    Science.gov (United States)

    Lee, Ritchie; Kochenderfer, Mykel J.; Mengshoel, Ole J.; Silbermann, Joshua

    2017-01-01

    We analyze data from simulated aircraft encounters to validate and inform the development of a prototype aircraft collision avoidance system. The high-dimensional and heterogeneous time series dataset is analyzed to discover properties of near mid-air collisions (NMACs) and categorize the NMAC encounters. Domain experts use these properties to better organize and understand NMAC occurrences. Existing solutions either are not capable of handling high-dimensional and heterogeneous time series datasets or do not provide explanations that are interpretable by a domain expert. The latter is critical to the acceptance and deployment of safety-critical systems. To address this gap, we propose grammar-based decision trees along with a learning algorithm. Our approach extends decision trees with a grammar framework for classifying heterogeneous time series data. A context-free grammar is used to derive decision expressions that are interpretable, application-specific, and support heterogeneous data types. In addition to classification, we show how grammar-based decision trees can also be used for categorization, which is a combination of clustering and generating interpretable explanations for each cluster. We apply grammar-based decision trees to a simulated aircraft encounter dataset and evaluate the performance of four variants of our learning algorithm. The best algorithm is used to analyze and categorize near mid-air collisions in the aircraft encounter dataset. We describe each discovered category in detail and discuss its relevance to aircraft collision avoidance.

  13. Association between Ambient Temperatures and Mental Disorder Hospitalizations in a Subtropical City: A Time-Series Study of Hong Kong Special Administrative Region.

    Science.gov (United States)

    Chan, Emily Y Y; Lam, Holly C Y; So, Suzanne H W; Goggins, William B; Ho, Janice Y; Liu, Sida; Chung, Phoebe P W

    2018-04-14

    Background : Mental disorders have been found to be positively associated with temperature in cool to cold climatic regions but the association in warmer regions is unclear. This study presented the short-term association between temperatures and mental disorder hospitalizations in a subtropical city with a mean annual temperature over 21 °C. Methods : Using Poisson-generalized additive models and distributed-lagged nonlinear models, daily mental disorder hospitalizations between 2002 and 2011 in Hong Kong were regressed on daily mean temperature, relative humidity, and air pollutants, adjusted for seasonal trend, long-term trend, day-of-week, and holiday. Analyses were stratified by disease class, gender and age-group. Results : 44,600 admissions were included in the analysis. Temperature was positively associated with overall mental-disorder hospitalizations (cumulative relative risk at 28 °C vs. 19.4 °C (interquartile range, lag 0-2 days) = 1.09 (95% confidence interval 1.03, 1.15)), with the strongest effect among the elderly (≥75 years old). Transient mental disorders due to conditions classified elsewhere and episodic mood disorders also showed strong positive associations with temperature. Conclusion : This study found a positive temperature-mental-disorder admissions association in a warm subtropical region and the association was most prominent among older people. With the dual effect of global warming and an aging population, targeted strategies should be designed to lower the disease burden.

  14. Short-term association between ambient air pollution and pneumonia in children: A systematic review and meta-analysis of time-series and case-crossover studies.

    Science.gov (United States)

    Nhung, Nguyen Thi Trang; Amini, Heresh; Schindler, Christian; Kutlar Joss, Meltem; Dien, Tran Minh; Probst-Hensch, Nicole; Perez, Laura; Künzli, Nino

    2017-11-01

    Ambient air pollution has been associated with respiratory diseases in children. However, its effects on pediatric pneumonia have not been meta-analyzed. We conducted a systematic review and meta-analysis of the short-term association between ambient air pollution and hospitalization of children due to pneumonia. We searched the Web of Science and PubMed for indexed publications up to January 2017. Pollutant-specific excess risk percentage (ER%) and confidence intervals (CI) were estimated using random effect models for particulate matter (PM) with diameter ≤ 10 (PM 10 ) and ≤2.5 μm (PM 2.5 ), sulfur dioxide (SO 2 ), ozone (O 3 ), nitrogen dioxide (NO 2 ), and carbon monoxide (CO). Results were further stratified by subgroups (children under five, emergency visits versus hospital admissions, income level of study location, and exposure period). Seventeen studies were included in the meta-analysis. The ER% per 10 μg/m 3 increase of pollutants was 1.5% (95% CI: 0.6%-2.4%) for PM 10 and 1.8% (95% CI: 0.5%-3.1%) for PM 2.5 . The corresponding values per 10 ppb increment of gaseous pollutants were 2.9% (95% CI: 0.4%-5.3%) for SO 2 , 1.7% (95% CI: 0.5%-2.8%) for O 3 , and 1.4% (95% CI: 0.4%-2.4%) for NO 2 . ER% per 1000 ppb increment of CO was 0.9% (95% CI: 0.0%-1.9%). Associations were not substantially different between subgroups. This meta-analysis shows a positive association between daily levels of ambient air pollution markers and hospitalization of children due to pneumonia. However, lack of studies from low-and middle-income countries limits the quantitative generalizability given that susceptibilities to the adverse effects of air pollution may be different in those populations. The meta-regression in our analysis further demonstrated a strong effect of country income level on heterogeneity. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Association between high temperature and mortality in metropolitan areas of four cities in various climatic zones in China: a time-series study.

    Science.gov (United States)

    Li, Yonghong; Cheng, Yibin; Cui, Guoquan; Peng, Chaoqiong; Xu, Yan; Wang, Yulin; Liu, Yingchun; Liu, Jingyi; Li, Chengcheng; Wu, Zhen; Bi, Peng; Jin, Yinlong

    2014-08-07

    Numerous studies have reported on the associations between ambient temperatures and mortality. However, few multi-city studies have been conducted in developing countries including China. This study aimed to examine the association between high temperature and mortality outcomes in four cities with different climatic characteristics in China to identify the most vulnerable population, detect the threshold temperatures, and provide scientific evidence for public health policy implementations to respond to challenges from extreme heat. A semi-parametric generalized additive model (GAM) with a Poisson distribution was used to analyze the impacts of the daily maximum temperature over the threshold on mortality after controlling for covariates including time trends, day of the week (DOW), humidity, daily temperature range, and outdoor air pollution. The temperature thresholds for all-cause mortality were 29°C, 35°C, 33°C and 34°C for Harbin, Nanjing, Shenzhen and Chongqing, respectively. After adjusting for potential confounders including air pollution, strong associations between daily maximum temperature and daily mortality from all-cause, cardiovascular, endocrine and metabolic outcomes, and particularly diabetes, were observed in different geographical cities, with increases of 3.2-5.5%, 4.6-7.5% and 12.5-31.9% (with 14.7-29.2% in diabetes), respectively, with each 1°C increment in the daily maximum temperature over the threshold. A stronger temperature-associated mortality was detected in females compared to males. Additionally, both the population over 55 years and younger adults aged 30 to 54 years reported significant heat-mortality associations. Extreme heat is becoming a huge threat to public health and human welfare due to the strong temperature-mortality associations in China. Climate change with increasing temperatures may make the situation worse. Relevant public health strategies and an early extreme weather and health warning system should be

  16. Short-term effects of fine particulate air pollution on cardiovascular hospital emergency room visits: a time-series study in Beijing, China.

    Science.gov (United States)

    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

  17. Vegetation fire smoke, indigenous status and cardio-respiratory hospital admissions in Darwin, Australia, 1996–2005: a time-series study

    Directory of Open Access Journals (Sweden)

    Hanigan Ivan C

    2008-08-01

    Full Text Available Abstract Background Air pollution in Darwin, Northern Australia, is dominated by smoke from seasonal fires in the surrounding savanna that burn during the dry season from April to November. Our aim was to study the association between particulate matter less than or equal to 10 microns diameter (PM10 and daily emergency hospital admissions for cardio-respiratory diseases for each fire season from 1996 to 2005. We also investigated whether the relationship differed in indigenous Australians; a disadvantaged population sub-group. Methods Daily PM10 exposure levels were estimated for the population of the city from visibility data using a previously validated model. We used over-dispersed Poisson generalized linear models with parametric smoothing functions for time and meteorology to examine the association between admissions and PM10 up to three days prior. An interaction between indigenous status and PM10 was included to examine differences in the impact on indigenous people. Results We found both positive and negative associations and our estimates had wide confidence intervals. There were generally positive associations between respiratory disease and PM10 but not with cardiovascular disease. An increase of 10 μg/m3 in same-day estimated ambient PM10 was associated with a 4.81% (95%CI: -1.04%, 11.01% increase in total respiratory admissions. When the interaction between indigenous status and PM10 was assessed a statistically different association was found between PM10 and admissions three days later for respiratory infections of indigenous people (15.02%; 95%CI: 3.73%, 27.54% than for non-indigenous people (0.67%; 95%CI: -7.55%, 9.61%. There were generally negative estimates for cardiovascular conditions. For non-indigenous admissions the estimated association with total cardiovascular admissions for same day ambient PM10 and admissions was -3.43% (95%CI: -9.00%, 2.49% and the estimate for indigenous admissions was -3.78% (95%CI: -13.4%, 6

  18. Nineteen-year time-series sediment trap study of Coccolithus pelagicus and Emiliania huxleyi (calcareous nannoplankton) fluxes in the Bering Sea and subarctic Pacific Ocean

    Science.gov (United States)

    Tsutsui, Hideto; Takahashi, Kozo; Asahi, Hirofumi; Jordan, Richard W.; Nishida, Shiro; Nishiwaki, Niichi; Yamamoto, Sumito

    2016-03-01

    Coccolithophore fluxes at two sediment trap stations, Station AB in the Bering Sea and Station SA in the subarctic Pacific Ocean, were studied over a nineteen-year (August 1990-July 2009) interval. Two major species, Coccolithus pelagicus and Emiliania huxleyi, occur at both stations, with Gephyrocapsa oceanica, Umbilicosphaera sibogae, Braarudosphaera bigelowii, and Syracosphaera spp. as minor components. The mean coccolithophore fluxes at Stations AB and SA increased from 28.9×106 m2 d-1 and 61.9×106 m2 d-1 in 1990-1999 to 54.4×106 m2 d-1 and 130.2×106 m2 d-1 in 2002-2009, respectively. Furthermore, in late 1999 to early 2000, there was a significant shift in the most dominant species from E. huxleyi to C. pelagicus. High abundances of E. huxleyi correspond to the positive mode of the Pacific Decadal Oscillation (PDO), while those of C. pelagicus respond to the PDO negative mode and are related to water temperature changes at huxleyi. At both stations the mean seawater temperature in the top 45 m from August to October increased ca. 1 °C with linear recurrence from 1990 to 2008. The coccosphere fluxes after Year 2000 at Stations AB and SA, and the shift in species dominance, may have been influenced by this warming.

  19. The IPM Wheat Model--results of a three-year study in North Rhine-Westphalia, Lower Saxony and Schleswig-Holstein.

    Science.gov (United States)

    Verreet, J A; Heger, M; Oerke, E; Dehne, H W; Finger, I; Busse, C; Klink, H

    2003-01-01

    Under the primary utilisation of phytosanitary production factors such as selection of variety, crop rotation and N fertilisation according to plant requirements, the IPM Wheat Model comprises the elements diagnosis (qualitative = type of pathogen, quantitative = disease severity), scientifically grounded treatment thresholds which, as critical values in pathogen development, can be applied to define the optimum time of fungicide application, and pathogen-specific effective fungicides and application amounts. This leads to the location and year-specific optimised control of the pathogen and of the associated yield performance. After several years of development in Bavaria (from 1985 on) and Schleswig-Holstein (1993-1999), the model was tested as part of a project involving the Universities of Bonn and Kiel and the plant protection services of the German states of Lower Saxony, North Rhine-Westphalia and Schleswig-Holstein in a three-year study (1999-2001) in interregional locations (usually nine per state) with the winter wheat variety Ritmo (interregional indicator variety) and a further variety of regional importance in different variations (untreated control, three to four times growth stage-oriented variants for the determination of the absolute damage potential, IPM-variant). In exact records (approx. 12 dates per vegetation period), the disease epidemics were recorded weekly. With the genetically uniform indicator variety Ritmo, the results documented substantially differing year- and location-specific disease and yield patterns. Interregionally, a broad wheat pathogen spectrum (Puccinia striiformis, P. recondita, Septoria tritici, Stagonospora (syn. Septoria) nodorum, Blumeria (syn. Erysiphe) graminis, Pseudocercosporella herpotrichoides, Drechslera tritici-repentis) in differing composition, disease severity and damage effect was demonstrated. The heterogeneity of the infection and damage patterns was increased in the case of the second variety, in

  20. The association between diurnal temperature range and emergency room admissions for cardiovascular, respiratory, digestive and genitourinary disease among the elderly: a time series study.

    Science.gov (United States)

    Wang, Min-zhen; Zheng, Shan; He, Shi-lin; Li, Bei; Teng, Huai-jin; Wang, Shi-gong; Yin, Ling; Shang, Ke-zheng; Li, Tan-shi

    2013-07-01

    To evaluate the short-term effect of diurnal temperature range (DTR) on emergency room (ER) admissions among elderly adults in Beijing. After controlling the long-time and seasonal trend, weather, air pollution and other confounding factors, a semi-parametric generalized additive model (GAM) was used to analyze the exposure-effect relationship between DTR and daily ER admissions among elderly adults with different lag structures from 2009 to 2011 in Beijing. We examined the effects of DTR for stratified groups by age and gender, and conducted the modifying effect of season on DTR to test the possible interaction. Significant associations were found between DTR and four major causes of daily ER admissions among elderly adults in Beijing. A 1 °C increase in the 8-day moving average of DTR (lag 07) corresponded to an increase of 2.08% (95% CI: 0.88%-3.29%) in respiratory ER admissions and 2.14% (95% CI: 0.71%-3.59%) in digestive ER admissions. A 1 °C increase in the 3-day and 6-day moving average of DTR (lag 02 and lag 05) corresponded to a 0.76% (95% CI: 0.07%-1.46%) increase in cardiovascular ER admissions, and 1.81% (95% CI: 0.21%-3.45%) increase in genitourinary ER admissions, respectively. The people aged 75 years and older were associated more strongly with DTR than the 65-74 age group. The modifying effect of season on DTR was observed and it was various in four causes. This study strengthens the evidence that DTR is an independent risk factor for ER admissions among elderly persons. Some prevention programs that target the elderly and other high risk subgroups for impending large temperature changes may reduce the impact of DTR on people's health. Copyright © 2013 Elsevier B.V. All rights reserved.

  1. Multi-site time series analysis of acute effects of multiple air pollutants on respiratory mortality: a population-based study in Beijing, China.

    Science.gov (United States)

    Yang, Yang; Cao, Yang; Li, Wenjing; Li, Runkui; Wang, Meng; Wu, Zhenglai; Xu, Qun

    2015-03-01

    In large cities in China, the traffic-related air pollution has become the focus of attention, and its adverse effects on health have raised public concerns. We conducted a study to quantify the association between exposure to three major traffic-related pollutants - particulate matter respiratory mortality in Beijing, China at a daily spatiotemporal resolution. We used the generalized additive models (GAM) with natural splines and principal component regression method to associate air pollutants with daily respiratory mortality, covariates and confounders. The GAM analysis adjusting for the collinearity among pollutants indicated that PM10, CO and NO2 had significant effects on daily respiratory mortality in Beijing. An interquartile range increase in 2-day moving averages concentrations of day 0 and day 1 of PM10, CO and NO2 corresponded to 0.99 [95% confidence interval (CI): 0.30, 1.67], 0.89 (95% CI: 0.27, 1.51) and 0.95 (95% CI: 0.29, 1.61) percent increase in daily respiratory mortality, respectively. The effects were varied across the districts. The strongest effects were found in two rural districts and one suburban district but significant in only one district. In conclusion, high level of several traffic-related air pollutants is associated with an increased risk of respiratory mortality in Beijing over a short-time period. The high risk found in rural areas suggests a potential susceptible sub-population with undiagnosed respiratory diseases in these areas. Although the rural areas have relatively lower air pollution levels, they deserve more attention to respiratory disease prevention and air pollution reduction. Copyright © 2014 Elsevier B.V. All rights reserved.

  2. The Short-Term Effects of Visibility and Haze on Mortality in a Coastal City of China: A Time-Series Study

    Directory of Open Access Journals (Sweden)

    Shaohua Gu

    2017-11-01

    Full Text Available Few studies have been conducted to investigate the acute health effects of visibility and haze, which may be regarded as proxy indicators of ambient air pollution. We used a distributed lag non-linear model (DLNM combined with quasi-Poisson regression to estimate the relationship between visibility, haze and mortality in Ningbo, a coastal city of China. We found that the mortality risk of visibility was statistically significant only on the current day, while the risk of haze and PM10 peaked on the second day and could last for three days. When the visibility was less than 10 km, each 1 km decrease of visibility at lag 0 day was associated with a 0.78% (95% CI: 0.22–1.36% increase in total mortality and a 1.61% (95% CI: 0.39–2.85% increase in respiratory mortality. The excess risk of haze at lag 0–2 days on total mortality, cardiovascular and respiratory mortality was 7.76% (95% CI: 3.29–12.42%, 7.73% (95% CI: 0.12–15.92% and 17.77% (95% CI: 7.64–28.86%, respectively. Greater effects of air pollution were observed during the cold season than in the warm season, and the elderly were at higher risk compared to youths. The effects of visibility and haze were attenuated by single pollutants. These findings suggest that visibility and haze could be used as surrogates of air quality where pollutant data are scarce, and strengthen the evidence to develop policy to control air pollution and protect vulnerable populations.

  3. Part 4. Interaction between air pollution and respiratory viruses: time-series study of daily mortality and hospital admissions in Hong Kong.

    Science.gov (United States)

    Wong, Chit-Ming; Thach, Thuan Quoc; Chau, Patsy Yuen Kwan; Chan, Eric King Pan; Chung, Roger Yat-nork; Ou, Chun-Quan; Yang, Lin; Peiris, Joseph Sriyal Malik; Thomas, Graham Neil; Lam, Tai-Hing; Wong, Tze-Wai; Hedley, Anthony Johnson

    2010-11-01

    years and older than in the all-ages group and were consistent with other studies. The biggest health impacts were seen at the extremes of the age range. The three measures employed for influenza activity based on virologic data-one based on a proportion and the other two using frequencies of positive influenza isolates-were found to produce consistent health impact estimates, in terms of statistical significance. In general, we found that adjustment for influenza activity in air pollution health effect estimations took account of relatively small confounding effects. However, we conclude that it is worthwhile to make the adjustment in a sensitivity analysis and to obtain the best possible range of effect estimates from the data, especially for respiratory hospitalization. Interestingly, interaction effects were found between influenza activity and air pollution in the estimated risks for hospitalization for RD, particularly for 03. These results could be explained in terms of the detrimental effects of both influenza viruses and air pollutants, which may be synergistic or competing with each other, though the mechanism is still unknown. The results deserve further study and the attention of both public health policy makers and virologists in considering prevention strategies. IMPLICATIONS In Hong Kong, where air pollution may pose more of a health threat than in North American and Western European cities, the effects of air pollution also interact with influenza and with residence in socially deprived areas, potentially leading to additional harm. Asian governments should be aware of the combined risks to the health of the population when considering environmental protection and management in the context of economic, urban, and infrastructure development. This is the first study in Asia to examine the interactions between air pollution, influenza, and social deprivation from an epidemiologic perspective. The biologic mechanisms are still unclear, and further research

  4. Aerosol climate time series from ESA Aerosol_cci (Invited)

    Science.gov (United States)

    Holzer-Popp, T.

    2013-12-01

    developed further, to evaluate the datasets and their regional and seasonal merits. The validation showed that most datasets have improved significantly and in particular PARASOL (ocean only) provides excellent results. The metrics for AATSR (land and ocean) datasets are similar to those of MODIS and MISR, with AATSR better in some land regions and less good in some others (ocean). However, AATSR coverage is smaller than that of MODIS due to swath width. The MERIS dataset provides better coverage than AATSR but has lower quality (especially over land) than the other datasets. Also the synergetic AATSR/SCIAMACHY dataset has lower quality. The evaluation of the pixel uncertainties shows first good results but also reveals that more work needs to be done to provide comprehensive information for data assimilation. Users (MACC/ECMWF, AEROCOM) confirmed the relevance of this additional information and encouraged Aerosol_cci to release the current uncertainties. The paper will summarize and discuss the results of three year work in Aerosol_cci, extract the lessons learned and conclude with an outlook to the work proposed for the next three years. In this second phase a cyclic effort of algorithm evolution, dataset generation, validation and assessment will be applied to produce and further improve complete time series from all sensors under investigation, new sensors will be added (e.g. IASI), and preparation for the Sentinel missions will be made.

  5. Interpretation of a compositional time series

    Science.gov (United States)

    Tolosana-Delgado, R.; van den Boogaart, K. G.

    2012-04-01

    Common methods for multivariate time series analysis use linear operations, from the definition of a time-lagged covariance/correlation to the prediction of new outcomes. However, when the time series response is a composition (a vector of positive components showing the relative importance of a set of parts in a total, like percentages and proportions), then linear operations are afflicted of several problems. For instance, it has been long recognised that (auto/cross-)correlations between raw percentages are spurious, more dependent on which other components are being considered than on any natural link between the components of interest. Also, a long-term forecast of a composition in models with a linear trend will ultimately predict negative components. In general terms, compositional data should not be treated in a raw scale, but after a log-ratio transformation (Aitchison, 1986: The statistical analysis of compositional data. Chapman and Hill). This is so because the information conveyed by a compositional data is relative, as stated in their definition. The principle of working in coordinates allows to apply any sort of multivariate analysis to a log-ratio transformed composition, as long as this transformation is invertible. This principle is of full application to time series analysis. We will discuss how results (both auto/cross-correlation functions and predictions) can be back-transformed, viewed and interpreted in a meaningful way. One view is to use the exhaustive set of all possible pairwise log-ratios, which allows to express the results into D(D - 1)/2 separate, interpretable sets of one-dimensional models showing the behaviour of each possible pairwise log-ratios. Another view is the interpretation of estimated coefficients or correlations back-transformed in terms of compositions. These two views are compatible and complementary. These issues are illustrated with time series of seasonal precipitation patterns at different rain gauges of the USA

  6. Trends in the utilization of dental outpatient services affected by the expansion of health care benefits in South Korea to include scaling: a 6-year interrupted time-series study.

    Science.gov (United States)

    Park, Hee-Jung; Lee, Jun Hyup; Park, Sujin; Kim, Tae-Il

    2018-02-01

    This study utilized a strong quasi-experimental design to test the hypothesis that the implementation of a policy to expand dental care services resulted in an increase in the usage of dental outpatient services. A total of 45,650,000 subjects with diagnoses of gingivitis or advanced periodontitis who received dental scaling were selected and examined, utilizing National Health Insurance claims data from July 2010 through November 2015. We performed a segmented regression analysis of the interrupted time-series to analyze the time-series trend in dental costs before and after the policy implementation, and assessed immediate changes in dental costs. After the policy change was implemented, a statistically significant 18% increase occurred in the observed total dental cost per patient, after adjustment for age, sex, and residence area. In addition, the dental costs of outpatient gingivitis treatment increased immediately by almost 47%, compared with a 15% increase in treatment costs for advanced periodontitis outpatients. This policy effect appears to be sustainable. The introduction of the new policy positively impacted the immediate and long-term outpatient utilization of dental scaling treatment in South Korea. While the policy was intended to entice patients to prevent periodontal disease, thus benefiting the insurance system, our results showed that the policy also increased treatment accessibility for potential periodontal disease patients and may improve long-term periodontal health in the South Korean population.

  7. Trends in the utilization of dental outpatient services affected by the expansion of health care benefits in South Korea to include scaling: a 6-year interrupted time-series study

    Science.gov (United States)

    2018-01-01

    Purpose This study utilized a strong quasi-experimental design to test the hypothesis that the implementation of a policy to expand dental care services resulted in an increase in the usage of dental outpatient services. Methods A total of 45,650,000 subjects with diagnoses of gingivitis or advanced periodontitis who received dental scaling were selected and examined, utilizing National Health Insurance claims data from July 2010 through November 2015. We performed a segmented regression analysis of the interrupted time-series to analyze the time-series trend in dental costs before and after the policy implementation, and assessed immediate changes in dental costs. Results After the policy change was implemented, a statistically significant 18% increase occurred in the observed total dental cost per patient, after adjustment for age, sex, and residence area. In addition, the dental costs of outpatient gingivitis treatment increased immediately by almost 47%, compared with a 15% increase in treatment costs for advanced periodontitis outpatients. This policy effect appears to be sustainable. Conclusions The introduction of the new policy positively impacted the immediate and long-term outpatient utilization of dental scaling treatment in South Korea. While the policy was intended to entice patients to prevent periodontal disease, thus benefiting the insurance system, our results showed that the policy also increased treatment accessibility for potential periodontal disease patients and may improve long-term periodontal health in the South Korean population. PMID:29535886

  8. Time series prediction with simple recurrent neural networks ...

    African Journals Online (AJOL)

    A hybrid of the two called Elman-Jordan (or Multi-recurrent) neural network is also being used. In this study, we evaluated the performance of these neural networks on three established bench mark time series prediction problems. Results from the experiments showed that Jordan neural network performed significantly ...

  9. Single-Index Additive Vector Autoregressive Time Series Models

    KAUST Repository

    LI, YEHUA; GENTON, MARC G.

    2009-01-01

    We study a new class of nonlinear autoregressive models for vector time series, where the current vector depends on single-indexes defined on the past lags and the effects of different lags have an additive form. A sufficient condition is provided

  10. Daily time series evapotranspiration maps for Oklahoma and Texas panhandle

    Science.gov (United States)

    Evapotranspiration (ET) is an important process in ecosystems’ water budget and closely linked to its productivity. Therefore, regional scale daily time series ET maps developed at high and medium resolutions have large utility in studying the carbon-energy-water nexus and managing water resources. ...

  11. Empirical method to measure stochasticity and multifractality in nonlinear time series

    Science.gov (United States)

    Lin, Chih-Hao; Chang, Chia-Seng; Li, Sai-Ping

    2013-12-01

    An empirical algorithm is used here to study the stochastic and multifractal nature of nonlinear time series. A parameter can be defined to quantitatively measure the deviation of the time series from a Wiener process so that the stochasticity of different time series can be compared. The local volatility of the time series under study can be constructed using this algorithm, and the multifractal structure of the time series can be analyzed by using this local volatility. As an example, we employ this method to analyze financial time series from different stock markets. The result shows that while developed markets evolve very much like an Ito process, the emergent markets are far from efficient. Differences about the multifractal structures and leverage effects between developed and emergent markets are discussed. The algorithm used here can be applied in a similar fashion to study time series of other complex systems.

  12. [A three-year follow-up study on the transfer of mild cognitive impairment to Alzheimer's disease among the elderly in Taiyuan city].

    Science.gov (United States)

    Wang, Yan-ping; Zhai, Jing-bo; Zhu, Fang; Zhang, Wen-wen; Yang, Xiao-juan; Qu, Cheng-yi

    2011-02-01

    To explore the incidence rate of people with mild cognitive impairment (MCI) which transferred to Alzheimer's disease (AD) and to study the related influencing factors. 600 MCI aged people were experienced screening test which was conducted by WHO-BCA, MMSE and DCR. A three-year follow-up study was conducted to get the information on the aged people with MCI. Data related to demography, behavior, chronic diseases and perception of the elderly with MCI were collected through face to face interview. Characteristics of the elderly with MCI aged people were tested by 16PF. The content of Apoe was tested by PCR. People with NC were investigated by telephone to get the progression and the time to AD. Methodologies on statistics were log-rank test and Cox proportional hazards regression model. The incidence rate of MCI to AD was 6.53% person-years. The incidence rate of the normal people to AD was 1.24% person-years. The hazard of MCI to AD was 5.27 times (95%CI: 3.01 - 9.82) of the normal people to AD. The result of Cox proportional hazards regression model displayed that:older age (RR = 3.14, 95%CI: 2.98 - 7.46), hypertension (RR = 3.28, 95%CI: 3.02 - 8.48), hyperlipemia (RR = 2.22, 95%CI: 1.29 - 3.82), diabetes (RR = 4.87, 95%CI: 2.56 - 9.25), lack of sports (RR = 2.02, 95%CI: 1.29-3.14), anxiety (RR = 4.46, 95%CI: 3.07 - 8.14), dread fullness (RR = 4.08, 95%CI: 3.52 - 5.25), loneliness (RR = 1.89, 95%CI: 1.13 - 3.16), characteristics of anxiety (RR = 5.07, 95%CI: 2.56 - 10.04, introvert characteristics (RR = 2.05, 95%CI: 1.33 - 3.15) and ApoE4 (RR = 1.73, 95%CI: 1.15 - 2.63) were the risk factors of MCI to AD. Higher education (RR = 0.29, 95%CI: 0.07 - 0.43), intellectual work (RR = 0.14, 95%CI: 0.05 - 0.32), often reading books (RR = 0.30, 95%CI: 0.15 - 0.58), often taking part in recreational activities (RR = 0.41, 95%CI: 0.23 - 0.75) seemed to be the protective of MCI to AD. The rate of the elderly with MCI that developing to AD was high, suggesting further study

  13. Quantifying Selection with Pool-Seq Time Series Data.

    Science.gov (United States)

    Taus, Thomas; Futschik, Andreas; Schlötterer, Christian

    2017-11-01

    Allele frequency time series data constitute a powerful resource for unraveling mechanisms of adaptation, because the temporal dimension captures important information about evolutionary forces. In particular, Evolve and Resequence (E&R), the whole-genome sequencing of replicated experimentally evolving populations, is becoming increasingly popular. Based on computer simulations several studies proposed experimental parameters to optimize the identification of the selection targets. No such recommendations are available for the underlying parameters selection strength and dominance. Here, we introduce a highly accurate method to estimate selection parameters from replicated time series data, which is fast enough to be applied on a genome scale. Using this new method, we evaluate how experimental parameters can be optimized to obtain the most reliable estimates for selection parameters. We show that the effective population size (Ne) and the number of replicates have the largest impact. Because the number of time points and sequencing coverage had only a minor effect, we suggest that time series analysis is feasible without major increase in sequencing costs. We anticipate that time series analysis will become routine in E&R studies. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  14. A window-based time series feature extraction method.

    Science.gov (United States)

    Katircioglu-Öztürk, Deniz; Güvenir, H Altay; Ravens, Ursula; Baykal, Nazife

    2017-10-01

    This study proposes a robust similarity score-based time series feature extraction method that is termed as Window-based Time series Feature ExtraCtion (WTC). Specifically, WTC generates domain-interpretable results and involves significantly low computational complexity thereby rendering itself useful for densely sampled and populated time series datasets. In this study, WTC is applied to a proprietary action potential (AP) time series dataset on human cardiomyocytes and three precordial leads from a publicly available electrocardiogram (ECG) dataset. This is followed by comparing WTC in terms of predictive accuracy and computational complexity with shapelet transform and fast shapelet transform (which constitutes an accelerated variant of the shapelet transform). The results indicate that WTC achieves a slightly higher classification performance with significantly lower execution time when compared to its shapelet-based alternatives. With respect to its interpretable features, WTC has a potential to enable medical experts to explore definitive common trends in novel datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

  15. Time Series, Stochastic Processes and Completeness of Quantum Theory

    International Nuclear Information System (INIS)

    Kupczynski, Marian

    2011-01-01

    Most of physical experiments are usually described as repeated measurements of some random variables. Experimental data registered by on-line computers form time series of outcomes. The frequencies of different outcomes are compared with the probabilities provided by the algorithms of quantum theory (QT). In spite of statistical predictions of QT a claim was made that it provided the most complete description of the data and of the underlying physical phenomena. This claim could be easily rejected if some fine structures, averaged out in the standard descriptive statistical analysis, were found in time series of experimental data. To search for these structures one has to use more subtle statistical tools which were developed to study time series produced by various stochastic processes. In this talk we review some of these tools. As an example we show how the standard descriptive statistical analysis of the data is unable to reveal a fine structure in a simulated sample of AR (2) stochastic process. We emphasize once again that the violation of Bell inequalities gives no information on the completeness or the non locality of QT. The appropriate way to test the completeness of quantum theory is to search for fine structures in time series of the experimental data by means of the purity tests or by studying the autocorrelation and partial autocorrelation functions.

  16. Algorithm for Compressing Time-Series Data

    Science.gov (United States)

    Hawkins, S. Edward, III; Darlington, Edward Hugo

    2012-01-01

    An algorithm based on Chebyshev polynomials effects lossy compression of time-series data or other one-dimensional data streams (e.g., spectral data) that are arranged in blocks for sequential transmission. The algorithm was developed for use in transmitting data from spacecraft scientific instruments to Earth stations. In spite of its lossy nature, the algorithm preserves the information needed for scientific analysis. The algorithm is computationally simple, yet compresses data streams by factors much greater than two. The algorithm is not restricted to spacecraft or scientific uses: it is applicable to time-series data in general. The algorithm can also be applied to general multidimensional data that have been converted to time-series data, a typical example being image data acquired by raster scanning. However, unlike most prior image-data-compression algorithms, this algorithm neither depends on nor exploits the two-dimensional spatial correlations that are generally present in images. In order to understand the essence of this compression algorithm, it is necessary to understand that the net effect of this algorithm and the associated decompression algorithm is to approximate the original stream of data as a sequence of finite series of Chebyshev polynomials. For the purpose of this algorithm, a block of data or interval of time for which a Chebyshev polynomial series is fitted to the original data is denoted a fitting interval. Chebyshev approximation has two properties that make it particularly effective for compressing serial data streams with minimal loss of scientific information: The errors associated with a Chebyshev approximation are nearly uniformly distributed over the fitting interval (this is known in the art as the "equal error property"); and the maximum deviations of the fitted Chebyshev polynomial from the original data have the smallest possible values (this is known in the art as the "min-max property").

  17. Fourier analysis of time series an introduction

    CERN Document Server

    Bloomfield, Peter

    2000-01-01

    A new, revised edition of a yet unrivaled work on frequency domain analysis Long recognized for his unique focus on frequency domain methods for the analysis of time series data as well as for his applied, easy-to-understand approach, Peter Bloomfield brings his well-known 1976 work thoroughly up to date. With a minimum of mathematics and an engaging, highly rewarding style, Bloomfield provides in-depth discussions of harmonic regression, harmonic analysis, complex demodulation, and spectrum analysis. All methods are clearly illustrated using examples of specific data sets, while ample

  18. The Statistical Analysis of Time Series

    CERN Document Server

    Anderson, T W

    2011-01-01

    The Wiley Classics Library consists of selected books that have become recognized classics in their respective fields. With these new unabridged and inexpensive editions, Wiley hopes to extend the life of these important works by making them available to future generations of mathematicians and scientists. Currently available in the Series: T. W. Anderson Statistical Analysis of Time Series T. S. Arthanari & Yadolah Dodge Mathematical Programming in Statistics Emil Artin Geometric Algebra Norman T. J. Bailey The Elements of Stochastic Processes with Applications to the Natural Sciences George

  19. Inferring causality from noisy time series data

    DEFF Research Database (Denmark)

    Mønster, Dan; Fusaroli, Riccardo; Tylén, Kristian

    2016-01-01

    Convergent Cross-Mapping (CCM) has shown high potential to perform causal inference in the absence of models. We assess the strengths and weaknesses of the method by varying coupling strength and noise levels in coupled logistic maps. We find that CCM fails to infer accurate coupling strength...... and even causality direction in synchronized time-series and in the presence of intermediate coupling. We find that the presence of noise deterministically reduces the level of cross-mapping fidelity, while the convergence rate exhibits higher levels of robustness. Finally, we propose that controlled noise...

  20. Useful Pattern Mining on Time Series

    DEFF Research Database (Denmark)

    Goumatianos, Nikitas; Christou, Ioannis T; Lindgren, Peter

    2013-01-01

    We present the architecture of a “useful pattern” mining system that is capable of detecting thousands of different candlestick sequence patterns at the tick or any higher granularity levels. The system architecture is highly distributed and performs most of its highly compute-intensive aggregation...... calculations as complex but efficient distributed SQL queries on the relational databases that store the time-series. We present initial results from mining all frequent candlestick sequences with the characteristic property that when they occur then, with an average at least 60% probability, they signal a 2...

  1. Stochastic modeling of hourly rainfall times series in Campania (Italy)

    Science.gov (United States)

    Giorgio, M.; Greco, R.

    2009-04-01

    Occurrence of flowslides and floods in small catchments is uneasy to predict, since it is affected by a number of variables, such as mechanical and hydraulic soil properties, slope morphology, vegetation coverage, rainfall spatial and temporal variability. Consequently, landslide risk assessment procedures and early warning systems still rely on simple empirical models based on correlation between recorded rainfall data and observed landslides and/or river discharges. Effectiveness of such systems could be improved by reliable quantitative rainfall prediction, which can allow gaining larger lead-times. Analysis of on-site recorded rainfall height time series represents the most effective approach for a reliable prediction of local temporal evolution of rainfall. Hydrological time series analysis is a widely studied field in hydrology, often carried out by means of autoregressive models, such as AR, ARMA, ARX, ARMAX (e.g. Salas [1992]). Such models gave the best results when applied to the analysis of autocorrelated hydrological time series, like river flow or level time series. Conversely, they are not able to model the behaviour of intermittent time series, like point rainfall height series usually are, especially when recorded with short sampling time intervals. More useful for this issue are the so-called DRIP (Disaggregated Rectangular Intensity Pulse) and NSRP (Neymann-Scott Rectangular Pulse) model [Heneker et al., 2001; Cowpertwait et al., 2002], usually adopted to generate synthetic point rainfall series. In this paper, the DRIP model approach is adopted, in which the sequence of rain storms and dry intervals constituting the structure of rainfall time series is modeled as an alternating renewal process. Final aim of the study is to provide a useful tool to implement an early warning system for hydrogeological risk management. Model calibration has been carried out with hourly rainfall hieght data provided by the rain gauges of Campania Region civil

  2. Multiscale multifractal multiproperty analysis of financial time series based on Rényi entropy

    Science.gov (United States)

    Yujun, Yang; Jianping, Li; Yimei, Yang

    This paper introduces a multiscale multifractal multiproperty analysis based on Rényi entropy (3MPAR) method to analyze short-range and long-range characteristics of financial time series, and then applies this method to the five time series of five properties in four stock indices. Combining the two analysis techniques of Rényi entropy and multifractal detrended fluctuation analysis (MFDFA), the 3MPAR method focuses on the curves of Rényi entropy and generalized Hurst exponent of five properties of four stock time series, which allows us to study more universal and subtle fluctuation characteristics of financial time series. By analyzing the curves of the Rényi entropy and the profiles of the logarithm distribution of MFDFA of five properties of four stock indices, the 3MPAR method shows some fluctuation characteristics of the financial time series and the stock markets. Then, it also shows a richer information of the financial time series by comparing the profile of five properties of four stock indices. In this paper, we not only focus on the multifractality of time series but also the fluctuation characteristics of the financial time series and subtle differences in the time series of different properties. We find that financial time series is far more complex than reported in some research works using one property of time series.

  3. Analysis of JET ELMy time series

    International Nuclear Information System (INIS)

    Zvejnieks, G.; Kuzovkov, V.N.

    2005-01-01

    Full text: Achievement of the planned operational regime in the next generation tokamaks (such as ITER) still faces principal problems. One of the main challenges is obtaining the control of edge localized modes (ELMs), which should lead to both long plasma pulse times and reasonable divertor life time. In order to control ELMs the hypothesis was proposed by Degeling [1] that ELMs exhibit features of chaotic dynamics and thus a standard chaos control methods might be applicable. However, our findings which are based on the nonlinear autoregressive (NAR) model contradict this hypothesis for JET ELMy time-series. In turn, it means that ELM behavior is of a relaxation or random type. These conclusions coincide with our previous results obtained for ASDEX Upgrade time series [2]. [1] A.W. Degeling, Y.R. Martin, P.E. Bak, J. B.Lister, and X. Llobet, Plasma Phys. Control. Fusion 43, 1671 (2001). [2] G. Zvejnieks, V.N. Kuzovkov, O. Dumbrajs, A.W. Degeling, W. Suttrop, H. Urano, and H. Zohm, Physics of Plasmas 11, 5658 (2004)

  4. Changes in white matter as determinant of global functional decline in older independent outpatients: three year follow-up of LADIS (leukoaraiosis and disability) study cohort

    DEFF Research Database (Denmark)

    Inzitari, Domenico; Pracucci, Giovanni; Poggesi, Anna

    2009-01-01

    cerebral infarcts and atrophy. MAIN OUTCOME MEASURE: Transition from no disability (defined as a score of 0 or 1 on the instrumental activities of daily living scale) to disability (score >/=2) or death over three year follow-up. Secondary outcomes were incident dementia and stroke. RESULTS: Over a mean...... follow-up period of 2.42 years (SD 0.97, median 2.94 years), information on the main outcome was available for 633 patients. The annual rate of transition or death was 10.5%, 15.1%, and 29.5%, respectively, for patients with mild, moderate, or severe age related changes in white matter (Kaplan-Meier log...

  5. Changes in white matter as determinant of global functional decline in older independent outpatients: three year follow-up of LADIS (leukoaraiosis and disability) study cohort

    DEFF Research Database (Denmark)

    Inzitari, Domenico; Pracucci, Giovanni; Poggesi, Anna

    2009-01-01

    OBJECTIVE: To assess the impairment in daily living activities in older people with age related changes in white matter according to the severity of these changes. DESIGN: Observational data collection and follow-up of a cohort of older people undergoing brain magnetic resonance imaging after non-disabling...... complaints. SETTING: 11 European centres. PARTICIPANTS: 639 non-disabled older patients (mean age 74.1 (SD 5.0), 45.1% men) in whom brain magnetic resonance imaging showed mild, moderate, or severe age related changes in white matter (Fazekas scale). Magnetic resonance imaging assessment also included...... cerebral infarcts and atrophy. MAIN OUTCOME MEASURE: Transition from no disability (defined as a score of 0 or 1 on the instrumental activities of daily living scale) to disability (score >/=2) or death over three year follow-up. Secondary outcomes were incident dementia and stroke. RESULTS: Over a mean...

  6. The Gerici project: management of risks related to climate change for infrastructures. First lessons of three years of vulnerability study experience

    International Nuclear Information System (INIS)

    Guerard, H.; Ray, M.

    2007-01-01

    Climate change considerably modifies the vulnerability of infrastructures, and such concepts as the 'hundred-year flood' can even become dangerous in this new context. Interesting conclusions were reached for contracting authorities and a specific tool developed for infrastructure operators resulting from three years of research carried out after labelling by the RGCU (civil engineering and urban network) and with co-financing by the public works ministry. This project, managed by Egis (Scetauroute and Bceom) groups Sanef, ASF, Meteo-France, LCPC and Esri France. The article describes the stages in the procedure and the geographical information system (SIG), a user-friendly and transposable support tool for technical and strategic investigations. (authors)

  7. A simulation study to evaluate the performance of five statistical monitoring methods when applied to different time-series components in the context of control programs for endemic diseases

    DEFF Research Database (Denmark)

    Lopes Antunes, Ana Carolina; Jensen, Dan; Hisham Beshara Halasa, Tariq

    2017-01-01

    Disease monitoring and surveillance play a crucial role in control and eradication programs, as it is important to track implemented strategies in order to reduce and/or eliminate a specific disease. The objectives of this study were to assess the performance of different statistical monitoring......, decreases and constant sero-prevalence levels (referred as events). Two space-state models were used to model the time series, and different statistical monitoring methods (such as univariate process control algorithms–Shewart Control Chart, Tabular Cumulative Sums, and the V-mask- and monitoring...... of noise in the baseline was greater for the Shewhart Control Chart and Tabular Cumulative Sums than for the V-Mask and trend-based methods. The performance of the different statistical monitoring methods varied when monitoring increases and decreases in disease sero-prevalence. Combining two of more...

  8. A simulation study to evaluate the performance of five statistical monitoring methods when applied to different time-series components in the context of control programs for endemic diseases

    DEFF Research Database (Denmark)

    Lopes Antunes, Ana Carolina; Jensen, Dan; Hisham Beshara Halasa, Tariq

    2017-01-01

    , decreases and constant sero-prevalence levels (referred as events). Two space-state models were used to model the time series, and different statistical monitoring methods (such as univariate process control algorithms–Shewart Control Chart, Tabular Cumulative Sums, and the V-mask- and monitoring......Disease monitoring and surveillance play a crucial role in control and eradication programs, as it is important to track implemented strategies in order to reduce and/or eliminate a specific disease. The objectives of this study were to assess the performance of different statistical monitoring...... of noise in the baseline was greater for the Shewhart Control Chart and Tabular Cumulative Sums than for the V-Mask and trend-based methods. The performance of the different statistical monitoring methods varied when monitoring increases and decreases in disease sero-prevalence. Combining two of more...

  9. Rice-planted area extraction by time series analysis of ENVISAT ASAR WS data using a phenology-based classification approach: A case study for Red River Delta, Vietnam

    Science.gov (United States)

    Nguyen, D.; Wagner, W.; Naeimi, V.; Cao, S.

    2015-04-01

    Recent studies have shown the potential of Synthetic Aperture Radars (SAR) for mapping of rice fields and some other vegetation types. For rice field classification, conventional classification techniques have been mostly used including manual threshold-based and supervised classification approaches. The challenge of the threshold-based approach is to find acceptable thresholds to be used for each individual SAR scene. Furthermore, the influence of local incidence angle on backscatter hinders using a single threshold for the entire scene. Similarly, the supervised classification approach requires different training samples for different output classes. In case of rice crop, supervised classification using temporal data requires different training datasets to perform classification procedure which might lead to inconsistent mapping results. In this study we present an automatic method to identify rice crop areas by extracting phonological parameters after performing an empirical regression-based normalization of the backscatter to a reference incidence angle. The method is evaluated in the Red River Delta (RRD), Vietnam using the time series of ENVISAT Advanced SAR (ASAR) Wide Swath (WS) mode data. The results of rice mapping algorithm compared to the reference data indicate the Completeness (User accuracy), Correctness (Producer accuracy) and Quality (Overall accuracies) of 88.8%, 92.5 % and 83.9 % respectively. The total area of the classified rice fields corresponds to the total rice cultivation areas given by the official statistics in Vietnam (R2  0.96). The results indicates that applying a phenology-based classification approach using backscatter time series in optimal incidence angle normalization can achieve high classification accuracies. In addition, the method is not only useful for large scale early mapping of rice fields in the Red River Delta using the current and future C-band Sentinal-1A&B backscatter data but also might be applied for other rice

  10. Implementation of image-guided intensity-modulated accelerated partial breast irradiation. Three-year results of a phase II clinical study

    Energy Technology Data Exchange (ETDEWEB)

    Meszaros, Norbert; Major, Tibor; Stelczer, Gabor; Zaka, Zoltan; Takacsi-Nagy, Zoltan; Fodor, Janos; Polgar, Csaba [National Institute of Oncology, Center of Radiotherapy, Budapest (Hungary); Mozsa, Emoke [National Institute of Oncology, Center of Radiotherapy, Budapest (Hungary); Landesklinikum, Department of Radiooncology and Radiotherapy, Wiener Neustadt (Austria); Pukancsik, David [National Institute of Oncology, Department of Breast and Sarcoma Surgery, Budapest (Hungary)

    2017-01-15

    To report 3-year results of accelerated partial breast irradiation (APBI) using image-guided intensity-modulated radiotherapy (IG-IMRT) following breast conserving surgery (BCS) for low-risk early invasive breast cancer. Between July 2011 and March 2014, 60 patients with low-risk early invasive breast cancer underwent BCS and were enrolled in this phase II prospective study. The total dose was 36.9 Gy (9 fractions of 4.1 Gy, two fractions/day). Patient setup errors were detected in LAT, LONG and VERT directions. Local tumour control, survival results, early and late side effects and cosmetic outcome were assessed. At a median follow-up of 39 months, all patients were alive and neither locoregional nor distant failure occurred. One contralateral breast cancer and two new primary malignancies outside the breast were observed. No grade (G) 3-4 acute toxicity was detected. G1 and G2 erythema occurred in 21 (35%) and 2 (3.3%) patients, respectively; while G1 oedema was observed in 23 (38.8%) cases. G1 and G2 pain was reported by 6 (10%) and 2 (3.3%) patients, respectively. Among the late radiation side effects, G1 pigmentation or telangiectasia, G1 fibrosis and G1 asymptomatic fat necrosis occurred in 10 (16.7%), 7 (11.7%) and 3 (5%) patients, respectively. No ≥ G2 late toxicity was detected. Cosmetic outcome was excellent in 43 (71.7%) and good in 17 (28.3%) patients. IG-IMRT is a reproducible and feasible technique for delivery of external beam APBI following BCS for treatment of low-risk, early-stage invasive breast carcinoma. In order to avoid toxicity, image guidance performed before each radiation fraction is necessary to minimize the PTV. Three-year results are promising, early and late radiation side-effects are minimal, and cosmetic results are excellent to good. (orig.) [German] Evaluierung der 3-Jahres-Ergebnisse der Teilbrustbestrahlung (APBI) mittels bildgefuehrter intensitaetsmodulierter Strahlentherapie (IG-IMRT) nach brusterhaltender Operation (BCS

  11. Three-year colonoscopy surveillance after polypectomy in Korea: a Korean Association for the Study of Intestinal Diseases (KASID multicenter prospective study

    Directory of Open Access Journals (Sweden)

    Won Seok Choi

    2018-01-01

    Full Text Available Background/Aims: Colonoscopic surveillance is currently recommended after polypectomy owing to the risk of newly developed colonic neoplasia. However, few studies have investigated colonoscopy surveillance in Asia. This multicenter and prospective study was undertaken to assess the incidence of advanced adenoma based on baseline adenoma findings at 3 years after colonoscopic polypectomy. Methods: A total of 1,323 patients undergoing colonoscopic polypectomy were prospectively assigned to 3-year colonoscopy surveillance at 11 tertiary endoscopic centers. Relative risks for advanced adenoma after 3 years were calculated according to baseline adenoma characteristics. Results: Among 1,323 patients enrolled, 387 patients (29.3% were followed up, and the mean follow-up interval was 31.0±9.8 months. The percentage of patients with advanced adenoma on baseline colonoscopy was higher in the surveillance group compared to the non-surveillance group (34.4% vs. 25.7%. Advanced adenoma recurrence was observed in 17 patients (4.4% at follow-up. The risk of advanced adenoma recurrence was 2 times greater in patients with baseline advanced adenoma than in those with baseline non-advanced adenoma, though the difference was not statistically significant (6.8% [9/133] vs. 3.1% [8/254], P=0.09. Advanced adenoma recurrence was observed only in males and in subjects aged ≥50 years. In contrast, adenoma recurrence was observed in 187 patients (48.3% at follow-up. Male sex, older age (≥50 years, and multiple adenomas (≥3 at baseline were independent risk factors for adenoma recurrence. Conclusions: A colonoscopy surveillance interval of 3 years in patients with baseline advanced adenoma can be considered appropriate.

  12. Palmprint Verification Using Time Series Method

    Directory of Open Access Journals (Sweden)

    A. A. Ketut Agung Cahyawan Wiranatha

    2013-11-01

    Full Text Available The use of biometrics as an automatic recognition system is growing rapidly in solving security problems, palmprint is one of biometric system which often used. This paper used two steps in center of mass moment method for region of interest (ROI segmentation and apply the time series method combined with block window method as feature representation. Normalized Euclidean Distance is used to measure the similarity degrees of two feature vectors of palmprint. System testing is done using 500 samples palms, with 4 samples as the reference image and the 6 samples as test images. Experiment results show that this system can achieve a high performance with success rate about 97.33% (FNMR=1.67%, FMR=1.00 %, T=0.036.

  13. Tool Wear Monitoring Using Time Series Analysis

    Science.gov (United States)

    Song, Dong Yeul; Ohara, Yasuhiro; Tamaki, Haruo; Suga, Masanobu

    A tool wear monitoring approach considering the nonlinear behavior of cutting mechanism caused by tool wear and/or localized chipping is proposed, and its effectiveness is verified through the cutting experiment and actual turning machining. Moreover, the variation in the surface roughness of the machined workpiece is also discussed using this approach. In this approach, the residual error between the actually measured vibration signal and the estimated signal obtained from the time series model corresponding to dynamic model of cutting is introduced as the feature of diagnosis. Consequently, it is found that the early tool wear state (i.e. flank wear under 40µm) can be monitored, and also the optimal tool exchange time and the tool wear state for actual turning machining can be judged by this change in the residual error. Moreover, the variation of surface roughness Pz in the range of 3 to 8µm can be estimated by the monitoring of the residual error.

  14. Outlier Detection in Structural Time Series Models

    DEFF Research Database (Denmark)

    Marczak, Martyna; Proietti, Tommaso

    investigate via Monte Carlo simulations how this approach performs for detecting additive outliers and level shifts in the analysis of nonstationary seasonal time series. The reference model is the basic structural model, featuring a local linear trend, possibly integrated of order two, stochastic seasonality......Structural change affects the estimation of economic signals, like the underlying growth rate or the seasonally adjusted series. An important issue, which has attracted a great deal of attention also in the seasonal adjustment literature, is its detection by an expert procedure. The general......–to–specific approach to the detection of structural change, currently implemented in Autometrics via indicator saturation, has proven to be both practical and effective in the context of stationary dynamic regression models and unit–root autoregressions. By focusing on impulse– and step–indicator saturation, we...

  15. Using entropy to cut complex time series

    Science.gov (United States)

    Mertens, David; Poncela Casasnovas, Julia; Spring, Bonnie; Amaral, L. A. N.

    2013-03-01

    Using techniques from statistical physics, physicists have modeled and analyzed human phenomena varying from academic citation rates to disease spreading to vehicular traffic jams. The last decade's explosion of digital information and the growing ubiquity of smartphones has led to a wealth of human self-reported data. This wealth of data comes at a cost, including non-uniform sampling and statistically significant but physically insignificant correlations. In this talk I present our work using entropy to identify stationary sub-sequences of self-reported human weight from a weight management web site. Our entropic approach-inspired by the infomap network community detection algorithm-is far less biased by rare fluctuations than more traditional time series segmentation techniques. Supported by the Howard Hughes Medical Institute

  16. Normalizing the causality between time series

    Science.gov (United States)

    Liang, X. San

    2015-08-01

    Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market.

  17. Time Series Based for Online Signature Verification

    Directory of Open Access Journals (Sweden)

    I Ketut Gede Darma Putra

    2013-11-01

    Full Text Available Signature verification system is to match the tested signature with a claimed signature. This paper proposes time series based for feature extraction method and dynamic time warping for match method. The system made by process of testing 900 signatures belong to 50 participants, 3 signatures for reference and 5 signatures from original user, simple imposters and trained imposters for signatures test. The final result system was tested with 50 participants with 3 references. This test obtained that system accuracy without imposters is 90,44897959% at threshold 44 with rejection errors (FNMR is 5,2% and acceptance errors (FMR is 4,35102%, when with imposters system accuracy is 80,1361% at threshold 27 with error rejection (FNMR is 15,6% and acceptance errors (average FMR is 4,263946%, with details as follows: acceptance errors is 0,391837%, acceptance errors simple imposters is 3,2% and acceptance errors trained imposters is 9,2%.

  18. Modeling Philippine Stock Exchange Composite Index Using Time Series Analysis

    Science.gov (United States)

    Gayo, W. S.; Urrutia, J. D.; Temple, J. M. F.; Sandoval, J. R. D.; Sanglay, J. E. A.

    2015-06-01

    This study was conducted to develop a time series model of the Philippine Stock Exchange Composite Index and its volatility using the finite mixture of ARIMA model with conditional variance equations such as ARCH, GARCH, EG ARCH, TARCH and PARCH models. Also, the study aimed to find out the reason behind the behaviorof PSEi, that is, which of the economic variables - Consumer Price Index, crude oil price, foreign exchange rate, gold price, interest rate, money supply, price-earnings ratio, Producers’ Price Index and terms of trade - can be used in projecting future values of PSEi and this was examined using Granger Causality Test. The findings showed that the best time series model for Philippine Stock Exchange Composite index is ARIMA(1,1,5) - ARCH(1). Also, Consumer Price Index, crude oil price and foreign exchange rate are factors concluded to Granger cause Philippine Stock Exchange Composite Index.

  19. Study of the dependence of resolution temporal activity for a Philips gemini TF PET/CT scanner by applying a statistical analysis of time series; Estudio de la dependencia de la resolucion temporal con la actividad para un escaner PET-TAC philips gemini TF aplicando un analisis estadistico de series temporales

    Energy Technology Data Exchange (ETDEWEB)

    Sanchez Merino, G.; Cortes Rpdicio, J.; Lope Lope, R.; Martin Gonzalez, T.; Garcia Fidalgo, M. A.

    2013-07-01

    The aim of the present work is to study the dependence of temporal resolution with the activity using statistical techniques applied to the series of values time series measurements of temporal resolution during daily equipment checks. (Author)

  20. Time series modeling for syndromic surveillance

    Directory of Open Access Journals (Sweden)

    Mandl Kenneth D

    2003-01-01

    Full Text Available Abstract Background Emergency department (ED based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates. Methods Using time-series methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks. Results Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity. Conclusions Time series methods applied to historical ED utilization data are an important tool

  1. Time Series Analysis, Modeling and Applications A Computational Intelligence Perspective

    CERN Document Server

    Chen, Shyi-Ming

    2013-01-01

    Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams of data coming from numerous sensors, data feeds, recordings associated with numerous areas of application embracing physical and human-generated phenomena (environmental data, financial markets, Internet activities, etc.). A quest for a thorough analysis, interpretation, modeling and prediction of time series comes with an ongoing challenge for developing models that are both accurate and user-friendly (interpretable). The volume is aimed to exploit the conceptual and algorithmic framework of Computational Intelligence (CI) to form a cohesive and comprehensive environment for building models of time series. The contributions covered in the volume are fully reflective of the wealth of the CI technologies by bringing together ideas, algorithms, and numeric studies, which convincingly demonstrate their relevance, maturity and visible usefulness. It reflects upon the truly remarkable diversity of methodological a...

  2. Time series prediction by feedforward neural networks - is it difficult?

    International Nuclear Information System (INIS)

    Rosen-Zvi, Michal; Kanter, Ido; Kinzel, Wolfgang

    2003-01-01

    The difficulties that a neural network faces when trying to learn from a quasi-periodic time series are studied analytically using a teacher-student scenario where the random input is divided into two macroscopic regions with different variances, 1 and 1/γ 2 (γ >> 1). The generalization error is found to decrease as ε g ∝ exp(-α/γ 2 ), where α is the number of examples per input dimension. In contradiction to this very slow vanishing generalization error, the next output prediction is found to be almost free of mistakes. This picture is consistent with learning quasi-periodic time series produced by feedforward neural networks, which is dominated by enhanced components of the Fourier spectrum of the input. Simulation results are in good agreement with the analytical results

  3. Deviations from uniform power law scaling in nonstationary time series

    Science.gov (United States)

    Viswanathan, G. M.; Peng, C. K.; Stanley, H. E.; Goldberger, A. L.

    1997-01-01

    A classic problem in physics is the analysis of highly nonstationary time series that typically exhibit long-range correlations. Here we test the hypothesis that the scaling properties of the dynamics of healthy physiological systems are more stable than those of pathological systems by studying beat-to-beat fluctuations in the human heart rate. We develop techniques based on the Fano factor and Allan factor functions, as well as on detrended fluctuation analysis, for quantifying deviations from uniform power-law scaling in nonstationary time series. By analyzing extremely long data sets of up to N = 10(5) beats for 11 healthy subjects, we find that the fluctuations in the heart rate scale approximately uniformly over several temporal orders of magnitude. By contrast, we find that in data sets of comparable length for 14 subjects with heart disease, the fluctuations grow erratically, indicating a loss of scaling stability.

  4. Stochastic generation of hourly wind speed time series

    International Nuclear Information System (INIS)

    Shamshad, A.; Wan Mohd Ali Wan Hussin; Bawadi, M.A.; Mohd Sanusi, S.A.

    2006-01-01

    In the present study hourly wind speed data of Kuala Terengganu in Peninsular Malaysia are simulated by using transition matrix approach of Markovian process. The wind speed time series is divided into various states based on certain criteria. The next wind speed states are selected based on the previous states. The cumulative probability transition matrix has been formed in which each row ends with 1. Using the uniform random numbers between 0 and 1, a series of future states is generated. These states have been converted to the corresponding wind speed values using another uniform random number generator. The accuracy of the model has been determined by comparing the statistical characteristics such as average, standard deviation, root mean square error, probability density function and autocorrelation function of the generated data to those of the original data. The generated wind speed time series data is capable to preserve the wind speed characteristics of the observed data

  5. Analyses of GIMMS NDVI Time Series in Kogi State, Nigeria

    Science.gov (United States)

    Palka, Jessica; Wessollek, Christine; Karrasch, Pierre

    2017-10-01

    The value of remote sensing data is particularly evident where an areal monitoring is needed to provide information on the earth's surface development. The use of temporal high resolution time series data allows for detecting short-term changes. In Kogi State in Nigeria different vegetation types can be found. As the major population in this region is living in rural communities with crop farming the existing vegetation is slowly being altered. The expansion of agricultural land causes loss of natural vegetation, especially in the regions close to the rivers which are suitable for crop production. With regard to these facts, two questions can be dealt with covering different aspects of the development of vegetation in the Kogi state, the determination and evaluation of the general development of the vegetation in the study area (trend estimation) and analyses on a short-term behavior of vegetation conditions, which can provide information about seasonal effects in vegetation development. For this purpose, the GIMMS-NDVI data set, provided by the NOAA, provides information on the normalized difference vegetation index (NDVI) in a geometric resolution of approx. 8 km. The temporal resolution of 15 days allows the already described analyses. For the presented analysis data for the period 1981-2012 (31 years) were used. The implemented workflow mainly applies methods of time series analysis. The results show that in addition to the classical seasonal development, artefacts of different vegetation periods (several NDVI maxima) can be found in the data. The trend component of the time series shows a consistently positive development in the entire study area considering the full investigation period of 31 years. However, the results also show that this development has not been continuous and a simple linear modeling of the NDVI increase is only possible to a limited extent. For this reason, the trend modeling was extended by procedures for detecting structural breaks in

  6. Phase correlation of foreign exchange time series

    Science.gov (United States)

    Wu, Ming-Chya

    2007-03-01

    Correlation of foreign exchange rates in currency markets is investigated based on the empirical data of USD/DEM and USD/JPY exchange rates for a period from February 1 1986 to December 31 1996. The return of exchange time series is first decomposed into a number of intrinsic mode functions (IMFs) by the empirical mode decomposition method. The instantaneous phases of the resultant IMFs calculated by the Hilbert transform are then used to characterize the behaviors of pricing transmissions, and the correlation is probed by measuring the phase differences between two IMFs in the same order. From the distribution of phase differences, our results show explicitly that the correlations are stronger in daily time scale than in longer time scales. The demonstration for the correlations in periods of 1986-1989 and 1990-1993 indicates two exchange rates in the former period were more correlated than in the latter period. The result is consistent with the observations from the cross-correlation calculation.

  7. Fisher information framework for time series modeling

    Science.gov (United States)

    Venkatesan, R. C.; Plastino, A.

    2017-08-01

    A robust prediction model invoking the Takens embedding theorem, whose working hypothesis is obtained via an inference procedure based on the minimum Fisher information principle, is presented. The coefficients of the ansatz, central to the working hypothesis satisfy a time independent Schrödinger-like equation in a vector setting. The inference of (i) the probability density function of the coefficients of the working hypothesis and (ii) the establishing of constraint driven pseudo-inverse condition for the modeling phase of the prediction scheme, is made, for the case of normal distributions, with the aid of the quantum mechanical virial theorem. The well-known reciprocity relations and the associated Legendre transform structure for the Fisher information measure (FIM, hereafter)-based model in a vector setting (with least square constraints) are self-consistently derived. These relations are demonstrated to yield an intriguing form of the FIM for the modeling phase, which defines the working hypothesis, solely in terms of the observed data. Cases for prediction employing time series' obtained from the: (i) the Mackey-Glass delay-differential equation, (ii) one ECG signal from the MIT-Beth Israel Deaconess Hospital (MIT-BIH) cardiac arrhythmia database, and (iii) one ECG signal from the Creighton University ventricular tachyarrhythmia database. The ECG samples were obtained from the Physionet online repository. These examples demonstrate the efficiency of the prediction model. Numerical examples for exemplary cases are provided.

  8. Quality Control Procedure Based on Partitioning of NMR Time Series

    Directory of Open Access Journals (Sweden)

    Michał Staniszewski

    2018-03-01

    Full Text Available The quality of the magnetic resonance spectroscopy (MRS depends on the stability of magnetic resonance (MR system performance and optimal hardware functioning, which ensure adequate levels of signal-to-noise ratios (SNR as well as good spectral resolution and minimal artifacts in the spectral data. MRS quality control (QC protocols and methodologies are based on phantom measurements that are repeated regularly. In this work, a signal partitioning algorithm based on a dynamic programming (DP method for QC assessment of the spectral data is described. The proposed algorithm allows detection of the change points—the abrupt variations in the time series data. The proposed QC method was tested using the simulated and real phantom data. Simulated data were randomly generated time series distorted by white noise. The real data were taken from the phantom quality control studies of the MRS scanner collected for four and a half years and analyzed by LCModel software. Along with the proposed algorithm, performance of various literature methods was evaluated for the predefined number of change points based on the error values calculated by subtracting the mean values calculated for the periods between the change-points from the original data points. The time series were checked using external software, a set of external methods and the proposed tool, and the obtained results were comparable. The application of dynamic programming in the analysis of the phantom MRS data is a novel approach to QC. The obtained results confirm that the presented change-point-detection tool can be used either for independent analysis of MRS time series (or any other or as a part of quality control.

  9. Topological data analysis of financial time series: Landscapes of crashes

    Science.gov (United States)

    Gidea, Marian; Katz, Yuri

    2018-02-01

    We explore the evolution of daily returns of four major US stock market indices during the technology crash of 2000, and the financial crisis of 2007-2009. Our methodology is based on topological data analysis (TDA). We use persistence homology to detect and quantify topological patterns that appear in multidimensional time series. Using a sliding window, we extract time-dependent point cloud data sets, to which we associate a topological space. We detect transient loops that appear in this space, and we measure their persistence. This is encoded in real-valued functions referred to as a 'persistence landscapes'. We quantify the temporal changes in persistence landscapes via their Lp-norms. We test this procedure on multidimensional time series generated by various non-linear and non-equilibrium models. We find that, in the vicinity of financial meltdowns, the Lp-norms exhibit strong growth prior to the primary peak, which ascends during a crash. Remarkably, the average spectral density at low frequencies of the time series of Lp-norms of the persistence landscapes demonstrates a strong rising trend for 250 trading days prior to either dotcom crash on 03/10/2000, or to the Lehman bankruptcy on 09/15/2008. Our study suggests that TDA provides a new type of econometric analysis, which complements the standard statistical measures. The method can be used to detect early warning signals of imminent market crashes. We believe that this approach can be used beyond the analysis of financial time series presented here.

  10. Forecasting and analyzing high O3 time series in educational area through an improved chaotic approach

    Science.gov (United States)

    Hamid, Nor Zila Abd; Adenan, Nur Hamiza; Noorani, Mohd Salmi Md

    2017-08-01

    Forecasting and analyzing the ozone (O3) concentration time series is important because the pollutant is harmful to health. This study is a pilot study for forecasting and analyzing the O3 time series in one of Malaysian educational area namely Shah Alam using c