Comparative study of stock trend prediction using time delay, recurrent and probabilistic neural networks.

PubMed

Saad, E W; Prokhorov, D V; Wunsch, D C

1998-01-01

Three networks are compared for low false alarm stock trend predictions. Short-term trends, particularly attractive for neural network analysis, can be used profitably in scenarios such as option trading, but only with significant risk. Therefore, we focus on limiting false alarms, which improves the risk/reward ratio by preventing losses. To predict stock trends, we exploit time delay, recurrent, and probabilistic neural networks (TDNN, RNN, and PNN, respectively), utilizing conjugate gradient and multistream extended Kalman filter training for TDNN and RNN. We also discuss different predictability analysis techniques and perform an analysis of predictability based on a history of daily closing price. Our results indicate that all the networks are feasible, the primary preference being one of convenience.

Analysis of temperature trends in Northern Serbia

NASA Astrophysics Data System (ADS)

Tosic, Ivana; Gavrilov, Milivoj; Unkašević, Miroslava; Marković, Slobodan; Petrović, Predrag

2017-04-01

An analysis of air temperature trends in Northern Serbia for the annual and seasonal time series is performed for two periods: 1949-2013 and 1979-2013. Three data sets of surface air temperatures: monthly mean temperatures, monthly maximum temperatures, and monthly minimum temperatures are analyzed at 9 stations that have altitudes varying between 75 m and 102 m. Monthly mean temperatures are obtained as the average of the daily mean temperatures, while monthly maximum (minimum) temperatures are the maximum (minimum) values of daily temperatures in corresponding month. Positive trends were found in 29 out of 30 time series, and the negative trend was found only in winter during the period 1979-2013. Applying the Mann-Kendall test, significant positive trends were found in 15 series; 7 in the period 1949-2013 and 8 in the period 1979-2013; and no significant trend was found in 15 series. Significant positive trends are dominated during the year, spring, and summer, where it was found in 14 out of 18 cases. Significant positive trends were found 7, 5, and 3 times in mean, maximum and minimum temperatures, respectively. It was found that the positive temperature trends are dominant in Northern Serbia.

Analysis of reperfusion time trends in patients with ST-elevation myocardial infarction across New York State from 2004 to 2012.

PubMed

Al'Aref, Subhi J; Wong, S Chiu; Swaminathan, Rajesh V; McNair, Patrick; Feldman, Dmitriy N; Kim, Luke K; Singh, Harsimran S; Bergman, Geoffrey; Minutello, Robert M

2017-04-01

Registry-driven data have shown a significant decrease in door-to-balloon (DTB) times in patients with ST-elevation myocardial infarction (STEMI) receiving percutaneous coronary intervention (PCI). We sought to determine the trends in reperfusion times (symptom-onset to door (SOTD) and DTB times) in patients presenting with STEMI across New York State. We retrospectively examined 35,613 STEMI patients receiving PCI from 2004 to 2012 and compared median SOTD and DTB times across years. Patients with SOTD time >12h and DTB time >3h were excluded. There was a statistically significant trend towards shorter DTB times (median DTB time of 83min (IQR 53, 116) in 2004 to a median DTB time of 59min (IQR 40, 78) in 2012, P<0.01 for trend) and SOTD times (median SOTD time of 127min (IQR 64, 241) in 2004 to a median SOTD time of 116min (IQR 60, 205) in 2012, P<0.01 for trend). In subgroup analysis, demographics and the presence of co-morbid conditions did not influence the trend in reperfusion times. However, women had longer reperfusion times than men in 2012. After adjusting for confounding variables, DTB was a significant predictor of in-hospital mortality (HR=1.04 (per 10minutes), P<0.01). There was a significant decrease in reperfusion times from 2004 to 2012 in STEMI patients across New York State. This trend was significant regardless of the presence of co-morbid conditions, although a significant gap in reperfusion times persists between men and women. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of detrending methods for fluctuation analysis in hydrology

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Zhou, Yu; Singh, Vijay P.; Chen, Yongqin David

2011-03-01

SummaryTrends within a hydrologic time series can significantly influence the scaling results of fluctuation analysis, such as rescaled range (RS) analysis and (multifractal) detrended fluctuation analysis (MF-DFA). Therefore, removal of trends is important in the study of scaling properties of the time series. In this study, three detrending methods, including adaptive detrending algorithm (ADA), Fourier-based method, and average removing technique, were evaluated by analyzing numerically generated series and observed streamflow series with obvious relative regular periodic trend. Results indicated that: (1) the Fourier-based detrending method and ADA were similar in detrending practices, and given proper parameters, these two methods can produce similarly satisfactory results; (2) detrended series by Fourier-based detrending method and ADA lose the fluctuation information at larger time scales, and the location of crossover points is heavily impacted by the chosen parameters of these two methods; and (3) the average removing method has an advantage over the other two methods, i.e., the fluctuation information at larger time scales is kept well-an indication of relatively reliable performance in detrending. In addition, the average removing method performed reasonably well in detrending a time series with regular periods or trends. In this sense, the average removing method should be preferred in the study of scaling properties of the hydrometeorolgical series with relative regular periodic trend using MF-DFA.

Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology

NASA Technical Reports Server (NTRS)

Forkel, Matthias; Carvalhais, Nuno; Verbesselt, Jan; Mahecha, Miguel D.; Neigh, Christopher S.R.; Reichstein, Markus

2013-01-01

Changing trends in ecosystem productivity can be quantified using satellite observations of Normalized Difference Vegetation Index (NDVI). However, the estimation of trends from NDVI time series differs substantially depending on analyzed satellite dataset, the corresponding spatiotemporal resolution, and the applied statistical method. Here we compare the performance of a wide range of trend estimation methods and demonstrate that performance decreases with increasing inter-annual variability in the NDVI time series. Trend slope estimates based on annual aggregated time series or based on a seasonal-trend model show better performances than methods that remove the seasonal cycle of the time series. A breakpoint detection analysis reveals that an overestimation of breakpoints in NDVI trends can result in wrong or even opposite trend estimates. Based on our results, we give practical recommendations for the application of trend methods on long-term NDVI time series. Particularly, we apply and compare different methods on NDVI time series in Alaska, where both greening and browning trends have been previously observed. Here, the multi-method uncertainty of NDVI trends is quantified through the application of the different trend estimation methods. Our results indicate that greening NDVI trends in Alaska are more spatially and temporally prevalent than browning trends. We also show that detected breakpoints in NDVI trends tend to coincide with large fires. Overall, our analyses demonstrate that seasonal trend methods need to be improved against inter-annual variability to quantify changing trends in ecosystem productivity with higher accuracy.

Trend analysis of salt load and evaluation of the frequency of water-quality measurements for the Gunnison, the Colorado, and the Dolores rivers in Colorado and Utah

USGS Publications Warehouse

Kircher, J.E.; Dinicola, Richard S.; Middelburg, R.F.

1984-01-01

Monthly values were computed for water-quality constituents at four streamflow gaging stations in the Upper Colorado River basin for the determination of trends. Seasonal regression and seasonal Kendall trend analysis techniques were applied to two monthly data sets at each station site for four different time periods. A recently developed method for determining optimal water-discharge data-collection frequency was also applied to the monthly water-quality data. Trend analysis results varied with each monthly load computational method, period of record, and trend detection model used. No conclusions could be reached regarding which computational method was best to use in trend analysis. Time-period selection for analysis was found to be important with regard to intended use of the results. Seasonal Kendall procedures were found to be applicable to most data sets. Seasonal regression models were more difficult to apply and were sometimes of questionable validity; however, those results were more informative than seasonal Kendall results. The best model to use depends upon the characteristics of the data and the amount of trend information needed. The measurement-frequency optimization method had potential for application to water-quality data, but refinements are needed. (USGS)

How Have Cancer Clinical Trial Eligibility Criteria Evolved Over Time?

PubMed Central

Yaman, Anil; Chakrabarti, Shreya; Sen, Anando; Weng, Chunhua

2016-01-01

Knowledge reuse of cancer trial designs may benefit from a temporal understanding of the evolution of the target populations of cancer studies over time. Therefore, we conducted a retrospective analysis of the trends of cancer trial eligibility criteria between 1999 and 2014. The yearly distributions of eligibility concepts for chemicals and drugs, procedures, observations, and medical conditions extracted from free-text eligibility criteria of 32,000 clinical trials for 89 cancer types were analyzed. We identified the concepts that trend upwards or downwards in all or selected cancer types, and the concepts that show anomalous trends for some cancers. Later, concept trends were studied in a disease-specific manner and illustrated for breast cancer. Criteria trends observed in this study are also validated and interpreted using evidence from the existing medical literature. This study contributes a method for concept trend analysis and original knowledge of the trends in cancer clinical trial eligibility criteria. PMID:27570681

Estimating average annual per cent change in trend analysis

PubMed Central

Clegg, Limin X; Hankey, Benjamin F; Tiwari, Ram; Feuer, Eric J; Edwards, Brenda K

2009-01-01

Trends in incidence or mortality rates over a specified time interval are usually described by the conventional annual per cent change (cAPC), under the assumption of a constant rate of change. When this assumption does not hold over the entire time interval, the trend may be characterized using the annual per cent changes from segmented analysis (sAPCs). This approach assumes that the change in rates is constant over each time partition defined by the transition points, but varies among different time partitions. Different groups (e.g. racial subgroups), however, may have different transition points and thus different time partitions over which they have constant rates of change, making comparison of sAPCs problematic across groups over a common time interval of interest (e.g. the past 10 years). We propose a new measure, the average annual per cent change (AAPC), which uses sAPCs to summarize and compare trends for a specific time period. The advantage of the proposed AAPC is that it takes into account the trend transitions, whereas cAPC does not and can lead to erroneous conclusions. In addition, when the trend is constant over the entire time interval of interest, the AAPC has the advantage of reducing to both cAPC and sAPC. Moreover, because the estimated AAPC is based on the segmented analysis over the entire data series, any selected subinterval within a single time partition will yield the same AAPC estimate—that is it will be equal to the estimated sAPC for that time partition. The cAPC, however, is re-estimated using data only from that selected subinterval; thus, its estimate may be sensitive to the subinterval selected. The AAPC estimation has been incorporated into the segmented regression (free) software Joinpoint, which is used by many registries throughout the world for characterizing trends in cancer rates. Copyright © 2009 John Wiley & Sons, Ltd. PMID:19856324

Time-Series Analysis: A Cautionary Tale

NASA Technical Reports Server (NTRS)

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.

Non-parametric trend analysis of the aridity index for three large arid and semi-arid basins in Iran

NASA Astrophysics Data System (ADS)

Ahani, Hossien; Kherad, Mehrzad; Kousari, Mohammad Reza; van Roosmalen, Lieke; Aryanfar, Ramin; Hosseini, Seyyed Mashaallah

2013-05-01

Currently, an important scientific challenge that researchers are facing is to gain a better understanding of climate change at the regional scale, which can be especially challenging in an area with low and highly variable precipitation amounts such as Iran. Trend analysis of the medium-term change using ground station observations of meteorological variables can enhance our knowledge of the dominant processes in an area and contribute to the analysis of future climate projections. Generally, studies focus on the long-term variability of temperature and precipitation and to a lesser extent on other important parameters such as moisture indices. In this study the recent 50-year trends (1955-2005) of precipitation (P), potential evapotranspiration (PET), and aridity index (AI) in monthly time scale were studied over 14 synoptic stations in three large Iran basins using the Mann-Kendall non-parametric test. Additionally, an analysis of the monthly, seasonal and annual trend of each parameter was performed. Results showed no significant trends in the monthly time series. However, PET showed significant, mostly decreasing trends, for the seasonal values, which resulted in a significant negative trend in annual PET at five stations. Significant negative trends in seasonal P values were only found at a number of stations in spring and summer and no station showed significant negative trends in annual P. Due to the varied positive and negative trends in annual P and to a lesser extent PET, almost as many stations with negative as positive trends in annual AI were found, indicating that both drying and wetting trends occurred in Iran. Overall, the northern part of the study area showed an increasing trend in annual AI which meant that the region became wetter, while the south showed decreasing trends in AI.

Meta-epidemiologic study showed frequent time trends in summary estimates from meta-analyses of diagnostic accuracy studies.

PubMed

Cohen, Jérémie F; Korevaar, Daniël A; Wang, Junfeng; Leeflang, Mariska M; Bossuyt, Patrick M

2016-09-01

To evaluate changes over time in summary estimates from meta-analyses of diagnostic accuracy studies. We included 48 meta-analyses from 35 MEDLINE-indexed systematic reviews published between September 2011 and January 2012 (743 diagnostic accuracy studies; 344,015 participants). Within each meta-analysis, we ranked studies by publication date. We applied random-effects cumulative meta-analysis to follow how summary estimates of sensitivity and specificity evolved over time. Time trends were assessed by fitting a weighted linear regression model of the summary accuracy estimate against rank of publication. The median of the 48 slopes was -0.02 (-0.08 to 0.03) for sensitivity and -0.01 (-0.03 to 0.03) for specificity. Twelve of 96 (12.5%) time trends in sensitivity or specificity were statistically significant. We found a significant time trend in at least one accuracy measure for 11 of the 48 (23%) meta-analyses. Time trends in summary estimates are relatively frequent in meta-analyses of diagnostic accuracy studies. Results from early meta-analyses of diagnostic accuracy studies should be considered with caution. Copyright © 2016 Elsevier Inc. All rights reserved.

Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms

Treesearch

Robert E. Kennedy; Zhiqiang Yang; Warren B. Cohen

2010-01-01

We introduce and test LandTrendr (Landsat-based detection of Trends in Disturbance and Recovery), a new approach to extract spectral trajectories of land surface change from yearly Landsat time-series stacks (LTS). The method brings together two themes in time-series analysis of LTS: capture of short-duration events and smoothing of long-term trends. Our strategy is...

Methods for trend analysis: Examples with problem/failure data

NASA Technical Reports Server (NTRS)

Church, Curtis K.

1989-01-01

Statistics are emphasized as an important role in quality control and reliability. Consequently, Trend Analysis Techniques recommended a variety of statistical methodologies that could be applied to time series data. The major goal of the working handbook, using data from the MSFC Problem Assessment System, is to illustrate some of the techniques in the NASA standard, some different techniques, and to notice patterns of data. Techniques for trend estimation used are: regression (exponential, power, reciprocal, straight line) and Kendall's rank correlation coefficient. The important details of a statistical strategy for estimating a trend component are covered in the examples. However, careful analysis and interpretation is necessary because of small samples and frequent zero problem reports in a given time period. Further investigations to deal with these issues are being conducted.

Analysis of Zenith Tropospheric Delay above Europe based on long time series derived from the EPN data

NASA Astrophysics Data System (ADS)

Baldysz, Zofia; Nykiel, Grzegorz; Figurski, Mariusz; Szafranek, Karolina; Kroszczynski, Krzysztof; Araszkiewicz, Andrzej

2015-04-01

In recent years, the GNSS system began to play an increasingly important role in the research related to the climate monitoring. Based on the GPS system, which has the longest operational capability in comparison with other systems, and a common computational strategy applied to all observations, long and homogeneous ZTD (Zenith Tropospheric Delay) time series were derived. This paper presents results of analysis of 16-year ZTD time series obtained from the EPN (EUREF Permanent Network) reprocessing performed by the Military University of Technology. To maintain the uniformity of data, analyzed period of time (1998-2013) is exactly the same for all stations - observations carried out before 1998 were removed from time series and observations processed using different strategy were recalculated according to the MUT LAC approach. For all 16-year time series (59 stations) Lomb-Scargle periodograms were created to obtain information about the oscillations in ZTD time series. Due to strong annual oscillations which disturb the character of oscillations with smaller amplitude and thus hinder their investigation, Lomb-Scargle periodograms for time series with the deleted annual oscillations were created in order to verify presence of semi-annual, ter-annual and quarto-annual oscillations. Linear trend and seasonal components were estimated using LSE (Least Square Estimation) and Mann-Kendall trend test were used to confirm the presence of linear trend designated by LSE method. In order to verify the effect of the length of time series on the estimated size of the linear trend, comparison between two different length of ZTD time series was performed. To carry out a comparative analysis, 30 stations which have been operating since 1996 were selected. For these stations two periods of time were analyzed: shortened 16-year (1998-2013) and full 18-year (1996-2013). For some stations an additional two years of observations have significant impact on changing the size of linear trend - only for 4 stations the size of linear trend was exactly the same for two periods of time. In one case, the nature of the trend has changed from negative (16-year time series) for positive (18-year time series). The average value of a linear trends for 16-year time series is 1,5 mm/decade, but their spatial distribution is not uniform. The average value of linear trends for all 18-year time series is 2,0 mm/decade, with better spatial distribution and smaller discrepancies.

An operational definition of a statistically meaningful trend.

PubMed

Bryhn, Andreas C; Dimberg, Peter H

2011-04-28

Linear trend analysis of time series is standard procedure in many scientific disciplines. If the number of data is large, a trend may be statistically significant even if data are scattered far from the trend line. This study introduces and tests a quality criterion for time trends referred to as statistical meaningfulness, which is a stricter quality criterion for trends than high statistical significance. The time series is divided into intervals and interval mean values are calculated. Thereafter, r(2) and p values are calculated from regressions concerning time and interval mean values. If r(2) ≥ 0.65 at p ≤ 0.05 in any of these regressions, then the trend is regarded as statistically meaningful. Out of ten investigated time series from different scientific disciplines, five displayed statistically meaningful trends. A Microsoft Excel application (add-in) was developed which can perform statistical meaningfulness tests and which may increase the operationality of the test. The presented method for distinguishing statistically meaningful trends should be reasonably uncomplicated for researchers with basic statistics skills and may thus be useful for determining which trends are worth analysing further, for instance with respect to causal factors. The method can also be used for determining which segments of a time trend may be particularly worthwhile to focus on.

Investigation of the 16-year and 18-year ZTD Time Series Derived from GPS Data Processing

NASA Astrophysics Data System (ADS)

Bałdysz, Zofia; Nykiel, Grzegorz; Figurski, Mariusz; Szafranek, Karolina; KroszczyńSki, Krzysztof

2015-08-01

The GPS system can play an important role in activities related to the monitoring of climate. Long time series, coherent strategy, and very high quality of tropospheric parameter Zenith Tropospheric Delay (ZTD) estimated on the basis of GPS data analysis allows to investigate its usefulness for climate research as a direct GPS product. This paper presents results of analysis of 16-year time series derived from EUREF Permanent Network (EPN) reprocessing performed by the Military University of Technology. For 58 stations Lomb-Scargle periodograms were performed in order to obtain information about the oscillations in ZTD time series. Seasonal components and linear trend were estimated using Least Square Estimation (LSE) and Mann—Kendall trend test was used to confirm the presence of a linear trend designated by LSE method. In order to verify the impact of the length of time series on trend value, comparison between 16 and 18 years were performed.

Trends in precipitation and streamflow and changes in stream morphology in the Fountain Creek watershed, Colorado, 1939-99

USGS Publications Warehouse

Stogner, Sr., Robert W.

2000-01-01

The Fountain Creek watershed, located in and along the eastern slope of the Front Range section of the southern Rocky Mountains, drains approximately 930 square miles of parts of Teller, El Paso, and Pueblo Counties in eastern Colorado. Streamflow in the watershed is dominated by spring snowmelt runoff and storm runoff during the summer monsoon season. Flooding during the 1990?s has resulted in increased streambank erosion. Property loss and damage associated with flooding and bank erosion has cost area residents, businesses, utilities, municipalities, and State and Federal agencies millions of dollars. Precipitation (4 stations) and streamflow (6 stations) data, aerial photographs, and channel reconnaissance were used to evaluate trends in precipitation and streamflow and changes in channel morphology. Trends were evaluated for pre-1977, post-1976, and period-of-record time periods. Analysis revealed the lack of trend in total annual and seasonal precipitation during the pre-1977 time period. In general, the analysis also revealed the lack of trend in seasonal precipitation for all except the spring season during the post-1976 time period. Trend analysis revealed a significant upward trend in long-term (period of record) total annual and spring precipitation data, apparently due to a change in total annual precipitation throughout the Fountain Creek watershed. During the pre-1977 time period, precipitation was generally below average; during the post- 1976 time period, total annual precipitation was generally above average. During the post- 1976 time period, an upward trend in total annual and spring precipitation was indicated at two stations. Because two of four stations evaluated had upward trends for the post-1976 period and storms that produce the most precipitation are isolated convection storms, it is plausible that other parts of the watershed had upward precipitation trends that could affect trends in streamflow. Also, because of the isolated nature of convection storms that hit some areas of the watershed and not others, it is difficult to draw strong conclusions on relations between streamflow and precipitation. Trends in annual instantaneous peak streamflow, 70th percentile, 90th percentile, maximum daily-mean streamflow (100th percentile), 7-, 14-, and 30-day high daily-mean stream- flow duration, minimum daily-mean streamflow (0th percentile), 10th percentile, 30th percentile, and 7-, 14-, 30-day low daily-mean streamflow duration were evaluated. In general, instantaneous peak streamflow has not changed significantly at most of the stations evaluated. Trend analysis revealed the lack of a significant upward trend in streamflow at all stations for the pre-1977 time period. Trend tests indicated a significant upward trend in high and low daily-mean streamflow statistics for the post-1976 period. Upward trends in high daily-mean streamflow statistics may be an indication that changes in land use within the watershed have increased the rate and magnitude of runoff. Upward trends in low daily-mean 2 Trends in Precipitation and Streamflow and Changes in Stream Morphology in the Fountain Creek Watershed, Colorado, 1939-99 streamflow statistics may be related to changes in water use and management. An analysis of the relation between streamflow and precipitation indicated that changes in water management have had a marked effect on streamflow. Observable change in channel morphology and changes in distribution and density of vegetation varied with magnitude, duration, and frequency of large streamflow events, and increases in the magnitude and duration of low streamflows. Although more subtle, low stream- flows were an important component of day-to-day channel erosion. Substantial changes in channel morphology were most often associated with infrequent large or catastrophic streamflow events that erode streambed and banks, alter stream course, and deposit large amounts of sediment in the flood plain.

Changes in precipitation regime in the Baltic countries in 1966-2015

NASA Astrophysics Data System (ADS)

Jaagus, Jaak; Briede, Agrita; Rimkus, Egidijus; Sepp, Mait

2018-01-01

The aim of the study was to analyse trends and regime shifts in time series of monthly, seasonal and annual precipitation in the eastern Baltic countries (Lithuania, Latvia, Estonia) during 1966-2015. Data from 54 stations with nearly homogeneous series were used. The Mann-Kendall test was used for trend analysis and the Rodionov test for the analysis of regime shifts. Rather few statistically significant trends ( p < 0.05) and regime shifts were determined. The highest increase (by approximately 10 mm per decade) was observed in winter precipitation when a significant trend was found at the large majority of stations. For monthly precipitation, increasing trends were detected at many stations in January, February and June. Weak negative trends revealed at few stations in April and September. Annual precipitation has generally increased, but the trend is mostly insignificant. The analysis of regime shifts revealed some significant abrupt changes, the most important of which were upward shifts in winter, in January and February precipitation at many stations since 1990 or in some other years (1989, 1995). A return shift in the time series of February precipitation occurred since 2003. The most significant increase in precipitation was determined in Latvia and the weakest increase in Lithuania.

Gender, Time and Inequality: Trends in Women's and Men's Paid Work, Unpaid Work and Free Time

ERIC Educational Resources Information Center

Sayer, Liana C.

2005-01-01

This analysis uses nationally representative time diary data from 1965, 1975 and 1998 to examine trends and gender differences in time use. Women continue to do more household labor than men; however, men have substantially increased time in core household activities such as cooking, cleaning and daily child care. Nonetheless, a 30-minute-per-day…

Spatio-temporal analysis of recent groundwater-level trends in the Red River Delta, Vietnam

NASA Astrophysics Data System (ADS)

Bui, Duong Du; Kawamura, Akira; Tong, Thanh Ngoc; Amaguchi, Hideo; Nakagawa, Naoko

2012-12-01

A groundwater-monitoring network has been in operation in the Red River Delta, Vietnam, since 1995. Trends in groundwater level (1995-2009) in 57 wells in the Holocene unconfined aquifer and 63 wells in the Pleistocene confined aquifer were determined by applying the non-parametric Mann-Kendall trend test and Sen's slope estimator. At each well, 17 time series (e.g. annual, seasonal, monthly), computed from the original data, were analyzed. Analysis of the annual groundwater-level means revealed that 35 % of the wells in the unconfined aquifer showed downward trends, while about 21 % showed upward trends. On the other hand, confined-aquifer groundwater levels experienced downward trends in almost all locations. Spatial distributions of trends indicated that the strongly declining trends (>0.3 m/year) were mainly found in urban areas around Hanoi where there is intensive abstraction of groundwater. Although the trend results for most of the 17 time series at a given well were quite similar, different trend patterns were detected in several. The findings reflect unsustainable groundwater development and the importance of maintaining groundwater monitoring and a database in the Delta, particularly in urban areas.

Do climate model predictions agree with long-term precipitation trends in the arid southwestern United States?

NASA Astrophysics Data System (ADS)

Elias, E.; Rango, A.; James, D.; Maxwell, C.; Anderson, J.; Abatzoglou, J. T.

2016-12-01

Researchers evaluating climate projections across southwestern North America observed a decreasing precipitation trend. Aridification was most pronounced in the cold (non-monsoonal) season, whereas downward trends in precipitation were smaller in the warm (monsoonal) season. In this region, based upon a multimodel mean of 20 Coupled Model Intercomparison Project 5 models using a business-as-usual (Representative Concentration Pathway 8.5) trajectory, midcentury precipitation is projected to increase slightly during the monsoonal time period (July-September; 6%) and decrease slightly during the remainder of the year (October-June; -4%). We use observed long-term (1915-2015) monthly precipitation records from 16 weather stations to investigate how well measured trends corroborate climate model predictions during the monsoonal and non-monsoonal timeframe. Running trend analysis using the Mann-Kendall test for 15 to 101 year moving windows reveals that half the stations showed significant (p≤0.1), albeit small, increasing trends based on the longest term record. Trends based on shorter-term records reveal a period of significant precipitation decline at all stations representing the 1950s drought. Trends from 1930 to 2015 reveal significant annual, monsoonal and non-monsoonal increases in precipitation (Fig 1). The 1960 to 2015 time window shows no significant precipitation trends. The more recent time window (1980 to 2015) shows a slight, but not significant, increase in monsoonal precipitation and a larger, significant decline in non-monsoonal precipitation. GCM precipitation projections are consistent with more recent trends for the region. Running trends from the most recent time window (mid-1990s to 2015) at all stations show increasing monsoonal precipitation and decreasing Oct-Jun precipitation, with significant trends at 6 of 16 stations. Running trend analysis revealed that the long-term trends were not persistent throughout the series length, but depended on the period examined. Recent trends in Southwest precipitation are directionally consistent with anthropogenic climate change.

A New Trend-Following Indicator: Using SSA to Design Trading Rules

NASA Astrophysics Data System (ADS)

Leles, Michel Carlo Rodrigues; Mozelli, Leonardo Amaral; Guimarães, Homero Nogueira

Singular Spectrum Analysis (SSA) is a non-parametric approach that can be used to decompose a time-series as trends, oscillations and noise. Trend-following strategies rely on the principle that financial markets move in trends for an extended period of time. Moving Averages (MAs) are the standard indicator to design such strategies. In this study, SSA is used as an alternative method to enhance trend resolution in comparison with the traditional MA. New trading rules using SSA as indicator are proposed. This paper shows that for the Down Jones Industrial Average (DJIA) and Shangai Securities Composite Index (SSCI) time-series the SSA trading rules provided, in general, better results in comparison to MA trading rules.

Temporal trends in adolescents’ self-reported psychosomatic health complaints from 1980-2016: A systematic review and meta-analysis

PubMed Central

Potrebny, Thomas; Wiium, Nora; Lundegård, Margrethe Moss-Iversen

2017-01-01

Objective There is increasing concern that mental health may be deteriorating in recent generations of adolescents. It is unclear whether this is the case for self-reported psychosomatic health complaints (PSHC). Method We conducted a systematic review and meta-analysis of published primary studies on PSHC in the general adolescent population over time. The primary databases were MEDLINE, Embase and PsycINFO, which were searched from inception to November 2016. Studies were included if they involved an observational design, presented self-reported data from participants aged 10–19 years and included data from at least two time points, five years apart. Inclusion and study quality were assessed by two independent reviewers. Results Twenty-one studies were included; 18 reported trends on the prevalence of PSHC in a single country, while three studies reported on multiple countries. In total, over seven million adolescents from 36 countries in Europe, North America, Israel and New Zealand were represented, covering the period 1982–2013. In the descriptive analysis, 10 studies indicated a trend of increasing PSHC, eight showed a stable trend and three showed a decreasing trend at certain points in time. The results from the meta-analysis showed a mean odds ratio (OR) of 1.04 (K = 139, 95% CI 1.01–1.08) for PSHC from 1982 to 2013, thus indicating a minor increase in general. In the subgroup analysis, this minor increase was observed mainly between the 1980s and 2000s, while the trend appeared to be more stable between the 2000s and 2010s. Some differences were also found between multinational subregions. Findings from subgroup analysis, however, only supported a significant increasing trend in Northern Europe. Conclusion There may have been a minor increasing trend in adolescent self-rated PSHC between the 1980 and 2000s, but has become more stable since the 2010s, from a multinational perspective. Northern Europe was the only region to show a clearly significant minor increasing trend, without being the region with the highest total prevalence of PSHC at the present time. The discrepant trends regarding PSHC between regions and the reliance on self-reported data may reflect true changes in the occurrence of PSHC in the adolescent population. However, they may also reflect changes in how adolescents perceive and report health complaints. Other PROSPERO registration 2016: CRD42016048300. PMID:29182644

Trend assessment: applications for hydrology and climate research

NASA Astrophysics Data System (ADS)

Kallache, M.; Rust, H. W.; Kropp, J.

2005-02-01

The assessment of trends in climatology and hydrology still is a matter of debate. Capturing typical properties of time series, like trends, is highly relevant for the discussion of potential impacts of global warming or flood occurrences. It provides indicators for the separation of anthropogenic signals and natural forcing factors by distinguishing between deterministic trends and stochastic variability. In this contribution river run-off data from gauges in Southern Germany are analysed regarding their trend behaviour by combining a deterministic trend component and a stochastic model part in a semi-parametric approach. In this way the trade-off between trend and autocorrelation structure can be considered explicitly. A test for a significant trend is introduced via three steps: First, a stochastic fractional ARIMA model, which is able to reproduce short-term as well as long-term correlations, is fitted to the empirical data. In a second step, wavelet analysis is used to separate the variability of small and large time-scales assuming that the trend component is part of the latter. Finally, a comparison of the overall variability to that restricted to small scales results in a test for a trend. The extraction of the large-scale behaviour by wavelet analysis provides a clue concerning the shape of the trend.

Statistical approach to the analysis of olive long-term pollen season trends in southern Spain.

PubMed

García-Mozo, H; Yaezel, L; Oteros, J; Galán, C

2014-03-01

Analysis of long-term airborne pollen counts makes it possible not only to chart pollen-season trends but also to track changing patterns in flowering phenology. Changes in higher plant response over a long interval are considered among the most valuable bioindicators of climate change impact. Phenological-trend models can also provide information regarding crop production and pollen-allergen emission. The interest of this information makes essential the election of the statistical analysis for time series study. We analysed trends and variations in the olive flowering season over a 30-year period (1982-2011) in southern Europe (Córdoba, Spain), focussing on: annual Pollen Index (PI); Pollen Season Start (PSS), Peak Date (PD), Pollen Season End (PSE) and Pollen Season Duration (PSD). Apart from the traditional Linear Regression analysis, a Seasonal-Trend Decomposition procedure based on Loess (STL) and an ARIMA model were performed. Linear regression results indicated a trend toward delayed PSE and earlier PSS and PD, probably influenced by the rise in temperature. These changes are provoking longer flowering periods in the study area. The use of the STL technique provided a clearer picture of phenological behaviour. Data decomposition on pollination dynamics enabled the trend toward an alternate bearing cycle to be distinguished from the influence of other stochastic fluctuations. Results pointed to show a rising trend in pollen production. With a view toward forecasting future phenological trends, ARIMA models were constructed to predict PSD, PSS and PI until 2016. Projections displayed a better goodness of fit than those derived from linear regression. Findings suggest that olive reproductive cycle is changing considerably over the last 30years due to climate change. Further conclusions are that STL improves the effectiveness of traditional linear regression in trend analysis, and ARIMA models can provide reliable trend projections for future years taking into account the internal fluctuations in time series. Copyright © 2013 Elsevier B.V. All rights reserved.

Trend analysis and change point detection of annual and seasonal temperature series in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Suhaila, Jamaludin; Yusop, Zulkifli

2017-06-01

Most of the trend analysis that has been conducted has not considered the existence of a change point in the time series analysis. If these occurred, then the trend analysis will not be able to detect an obvious increasing or decreasing trend over certain parts of the time series. Furthermore, the lack of discussion on the possible factors that influenced either the decreasing or the increasing trend in the series needs to be addressed in any trend analysis. Hence, this study proposes to investigate the trends, and change point detection of mean, maximum and minimum temperature series, both annually and seasonally in Peninsular Malaysia and determine the possible factors that could contribute to the significance trends. In this study, Pettitt and sequential Mann-Kendall (SQ-MK) tests were used to examine the occurrence of any abrupt climate changes in the independent series. The analyses of the abrupt changes in temperature series suggested that most of the change points in Peninsular Malaysia were detected during the years 1996, 1997 and 1998. These detection points captured by Pettitt and SQ-MK tests are possibly related to climatic factors, such as El Niño and La Niña events. The findings also showed that the majority of the significant change points that exist in the series are related to the significant trend of the stations. Significant increasing trends of annual and seasonal mean, maximum and minimum temperatures in Peninsular Malaysia were found with a range of 2-5 °C/100 years during the last 32 years. It was observed that the magnitudes of the increasing trend in minimum temperatures were larger than the maximum temperatures for most of the studied stations, particularly at the urban stations. These increases are suspected to be linked with the effect of urban heat island other than El Niño event.

Analysis and generation of groundwater concentration time series

NASA Astrophysics Data System (ADS)

Crăciun, Maria; Vamoş, Călin; Suciu, Nicolae

2018-01-01

Concentration time series are provided by simulated concentrations of a nonreactive solute transported in groundwater, integrated over the transverse direction of a two-dimensional computational domain and recorded at the plume center of mass. The analysis of a statistical ensemble of time series reveals subtle features that are not captured by the first two moments which characterize the approximate Gaussian distribution of the two-dimensional concentration fields. The concentration time series exhibit a complex preasymptotic behavior driven by a nonstationary trend and correlated fluctuations with time-variable amplitude. Time series with almost the same statistics are generated by successively adding to a time-dependent trend a sum of linear regression terms, accounting for correlations between fluctuations around the trend and their increments in time, and terms of an amplitude modulated autoregressive noise of order one with time-varying parameter. The algorithm generalizes mixing models used in probability density function approaches. The well-known interaction by exchange with the mean mixing model is a special case consisting of a linear regression with constant coefficients.

[Breast cancer in México: a 10-year trend analysis on incidence and age at diagnosis].

PubMed

Salinas-Martínez, Ana María; Juárez-Ruiz, Abigail; Mathiew-Quirós, Álvaro; Guzmán-De la Garza, Francisco Javier; Santos-Lartigue, Adriana; Escobar-Moreno, César

2014-01-01

Breast cancer is an important public health problem. Some countries have achieved a downward trend while in others, continues ascending. In México, information on incidence and age at diagnosis is isolated in time, and knowledge on trend analysis is lacking. To examine the 2003-2012 trend of the incidence rate and age at diagnosis of breast cancer in the northeast of México. We also analyze the trend of positivity to nodes, hormone receptors and HER2; and its association with age at diagnosis. This is an epidemiological study of breast cancer patients in a tertiary care hospital in Monterrey, México (n = 3,488). Only new cases with a histology report were included; if this was not available, the cytology result was considered. Trend analysis was performed using the JoinPoint regression program Version 3.5. The breast cancer incidence rate increased from 26.7 to 49.8 per 100,000 between 2003 and 2011 (p < 0.05). The adjusted rate showed an annual percentage rate of change of +6.2% (95%CI 4.2, 8.2). The mean age was 55.7 ± 13.7 years and remained stable over time. Nodes, hormone receptors and HER2 positivity rate also remained stable over time. Age < 50 years increased twice the risk for positivity to nodes (OR 2.0, 95%CI 1.4, 2.7), ER-PR- (OR 1.8, 95% CI 1.4, 2.4) and ER-PR-HER2- (OR 1.9, 95%CI 1.5, 2.5). The 10-year analysis showed a significant upward trend. This study represents a first effort in our country, for determining patterns on incidence and age at diagnosis of breast cancer, as well as that of biomarkers.

Comparison of GPS tropospheric delays derived from two consecutive EPN reprocessing campaigns from the point of view of climate monitoring

NASA Astrophysics Data System (ADS)

Baldysz, Zofia; Nykiel, Grzegorz; Araszkiewicz, Andrzej; Figurski, Mariusz; Szafranek, Karolina

2016-09-01

The main purpose of this research was to acquire information about consistency of ZTD (zenith total delay) linear trends and seasonal components between two consecutive GPS reprocessing campaigns. The analysis concerned two sets of the ZTD time series which were estimated during EUREF (Reference Frame Sub-Commission for Europe) EPN (Permanent Network) reprocessing campaigns according to 2008 and 2015 MUT AC (Military University of Technology Analysis Centre) scenarios. Firstly, Lomb-Scargle periodograms were generated for 57 EPN stations to obtain a characterisation of oscillations occurring in the ZTD time series. Then, the values of seasonal components and linear trends were estimated using the LSE (least squares estimation) approach. The Mann-Kendall trend test was also carried out to verify the presence of linear long-term ZTD changes. Finally, differences in seasonal signals and linear trends between these two data sets were investigated. All these analyses were conducted for the ZTD time series of two lengths: a shortened 16-year series and a full 18-year one. In the case of spectral analysis, amplitudes of the annual and semi-annual periods were almost exactly the same for both reprocessing campaigns. Exceptions were found for only a few stations and they did not exceed 1 mm. The estimated trends were also similar. However, for the reprocessing performed in 2008, the trends values were usually higher. In general, shortening of the analysed time period by 2 years resulted in a decrease of the linear trends values of about 0.07 mm yr-1. This was confirmed by analyses based on two data sets.

Random forest meteorological normalisation models for Swiss PM10 trend analysis

NASA Astrophysics Data System (ADS)

Grange, Stuart K.; Carslaw, David C.; Lewis, Alastair C.; Boleti, Eirini; Hueglin, Christoph

2018-05-01

Meteorological normalisation is a technique which accounts for changes in meteorology over time in an air quality time series. Controlling for such changes helps support robust trend analysis because there is more certainty that the observed trends are due to changes in emissions or chemistry, not changes in meteorology. Predictive random forest models (RF; a decision tree machine learning technique) were grown for 31 air quality monitoring sites in Switzerland using surface meteorological, synoptic scale, boundary layer height, and time variables to explain daily PM10 concentrations. The RF models were used to calculate meteorologically normalised trends which were formally tested and evaluated using the Theil-Sen estimator. Between 1997 and 2016, significantly decreasing normalised PM10 trends ranged between -0.09 and -1.16 µg m-3 yr-1 with urban traffic sites experiencing the greatest mean decrease in PM10 concentrations at -0.77 µg m-3 yr-1. Similar magnitudes have been reported for normalised PM10 trends for earlier time periods in Switzerland which indicates PM10 concentrations are continuing to decrease at similar rates as in the past. The ability for RF models to be interpreted was leveraged using partial dependence plots to explain the observed trends and relevant physical and chemical processes influencing PM10 concentrations. Notably, two regimes were suggested by the models which cause elevated PM10 concentrations in Switzerland: one related to poor dispersion conditions and a second resulting from high rates of secondary PM generation in deep, photochemically active boundary layers. The RF meteorological normalisation process was found to be robust, user friendly and simple to implement, and readily interpretable which suggests the technique could be useful in many air quality exploratory data analysis situations.

Trend analysis of selected water-quality constituents in the Verde River Basin, central Arizona

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

Baldys, S.

1990-01-01

Temporal trends of eight water quality constituents at six data collection sites in the Verde River basin in central Arizona were investigated using seasonal Kendall tau and ordinary least-squares regression methods of analysis. The constituents are dissolved solids, dissolved sulfate, dissolved arsenic, total phosphorus, pH, total nitrite plus nitrate-nitrogen, dissolved iron, and fecal coliform bacteria. Increasing trends with time in dissolved-solids concentrations of 7 to 8 mg/L/yr at Verde River near Camp Verde were found at significant level. An increasing trend in dissolved-sulfate concentrations of 3.59 mg/L/yr was also found at Verde River near Camp Verde, although at nonsignificant levels.more » Statistically significant decreasing trends with time in dissolved-solids and dissolved-sulfate concentrations were found at Verde River above Horseshoe Reservoir, which is downstream from Verde River near Camp Verde. Observed trends in the other constituents do not indicate the emergence of water quality problems in the Verde River basin. Analysis of the eight water quality constituents generally indicate nonvarying concentration levels after adjustment for seasonality and streamflow were made.« less

Beyond linear methods of data analysis: time series analysis and its applications in renal research.

PubMed

Gupta, Ashwani K; Udrea, Andreea

2013-01-01

Analysis of temporal trends in medicine is needed to understand normal physiology and to study the evolution of disease processes. It is also useful for monitoring response to drugs and interventions, and for accountability and tracking of health care resources. In this review, we discuss what makes time series analysis unique for the purposes of renal research and its limitations. We also introduce nonlinear time series analysis methods and provide examples where these have advantages over linear methods. We review areas where these computational methods have found applications in nephrology ranging from basic physiology to health services research. Some examples include noninvasive assessment of autonomic function in patients with chronic kidney disease, dialysis-dependent renal failure and renal transplantation. Time series models and analysis methods have been utilized in the characterization of mechanisms of renal autoregulation and to identify the interaction between different rhythms of nephron pressure flow regulation. They have also been used in the study of trends in health care delivery. Time series are everywhere in nephrology and analyzing them can lead to valuable knowledge discovery. The study of time trends of vital signs, laboratory parameters and the health status of patients is inherent to our everyday clinical practice, yet formal models and methods for time series analysis are not fully utilized. With this review, we hope to familiarize the reader with these techniques in order to assist in their proper use where appropriate.

TREND ANALYSIS OF WATER QUALITY MONITORING DATA FOR COBB COUNTY, GEORGIA

EPA Science Inventory

The Cobb County Water Protection Division Water Quality Laboratory has conducted quarterly chemical monitoring from 1995-2005. Here we analyze these data for temporal trends in 20 Piedmont streams in the Chattahoochee and Etowah river basins. We found trends through time at mos...

Empirical Mode Decomposition and k-Nearest Embedding Vectors for Timely Analyses of Antibiotic Resistance Trends

PubMed Central

Teodoro, Douglas; Lovis, Christian

2013-01-01

Background Antibiotic resistance is a major worldwide public health concern. In clinical settings, timely antibiotic resistance information is key for care providers as it allows appropriate targeted treatment or improved empirical treatment when the specific results of the patient are not yet available. Objective To improve antibiotic resistance trend analysis algorithms by building a novel, fully data-driven forecasting method from the combination of trend extraction and machine learning models for enhanced biosurveillance systems. Methods We investigate a robust model for extraction and forecasting of antibiotic resistance trends using a decade of microbiology data. Our method consists of breaking down the resistance time series into independent oscillatory components via the empirical mode decomposition technique. The resulting waveforms describing intrinsic resistance trends serve as the input for the forecasting algorithm. The algorithm applies the delay coordinate embedding theorem together with the k-nearest neighbor framework to project mappings from past events into the future dimension and estimate the resistance levels. Results The algorithms that decompose the resistance time series and filter out high frequency components showed statistically significant performance improvements in comparison with a benchmark random walk model. We present further qualitative use-cases of antibiotic resistance trend extraction, where empirical mode decomposition was applied to highlight the specificities of the resistance trends. Conclusion The decomposition of the raw signal was found not only to yield valuable insight into the resistance evolution, but also to produce novel models of resistance forecasters with boosted prediction performance, which could be utilized as a complementary method in the analysis of antibiotic resistance trends. PMID:23637796

Population-based trend analysis of laparoscopic Nissen and Toupet fundoplications for gastroesophageal reflux disease.

PubMed

Zingg, U; Rosella, L; Guller, U

2010-12-01

The Nissen and Toupet fundoplications are the most commonly used techniques for surgical treatment of gastroesophageal reflux disease. To date, no population-based trend analysis has been reported examining the choice of procedure and short-term outcomes. This study was designed to analyze trends in the use of Nissen versus Toupet fundoplications, and corresponding short-term outcomes during a 10-year period between 1995 and 2004. A trend analysis was performed of 873 patients (Toupet: 254 patients, Nissen: 619 patients) prospectively enrolled in the database of the Swiss Association for Laparoscopic and Thoracoscopic Surgery. The frequency of the performed techniques remained stable during the observation period (p value for trend 0.206). The average postoperative and total length of hospital stay both significantly decreased during the 10-year period from 5.6 to 4.0 days and 6.8 to 4.8 days, respectively (both p values for trend <0.001). The average duration of surgery decreased significantly from 141 minutes to 121 minutes (p value for trend <0.001). There was a trend towards less complications in later years (2000-2004) compared to early years (1995-1999, p = 0.058). Conversion rates were significantly lower in later years compared with early years (p = 0.004). This is the first trend analysis in the literature reporting clinical outcomes of 873 prospectively enrolled patients undergoing Nissen and Toupet fundoplications during a 10-year period. The proportion of laparoscopic Nissen versus Toupet fundoplications remained stable over time, indicating that literature reports of the advantages of one procedure over the other had minimal influence on surgeons' choice of technique. Length of hospital stay, duration of surgery, morbidity, and conversion rate decreased over time, reflecting the learning curve. Clearly, patient outcomes have much improved during the 10-year observation period.

Time-trend analysis and developing a forecasting model for the prevalence of multiple sclerosis in Kohgiluyeh and Boyer-Ahmad Province, southwest of Iran.

PubMed

Mousavizadeh, A; Dastoorpoor, M; Naimi, E; Dohrabpour, K

2018-01-01

This study was designed and implemented to assess the current situation and to estimate the time trend of multiple sclerosis (MS), as well as to explain potential factors associated with such a trend. This longitudinal study was carried out based on analysis of the data from the monitoring and treatment surveillance system for 421 patients with MS in Kohgiluyeh and Boyer-Ahmad Province, Iran, from 1990 to 2015. To this end, curve estimation approach was used to investigate the changes in prevalence and incidence of the disease, and univariate time series model analysis was applied in order to estimate the disease incidence in the next 10 years. The mean and standard deviation of age were 29.78 and 8.5 years at the time of diagnosis, and the mean and 95% confidence interval of age were 29.18 (28.86-30.77) and 29.68 (28.06-31.30) at the time of diagnosis for women and men, respectively. The sex ratio (males to females) was estimated as 3.3, and the prevalence of the disease was estimated as 60.14 in 100,000 people. The diagram of the 35-year trend of the disease indicated three distinct patterns with a tendency to increase in recent years. The prevalence and incidence trend of the disease in the study population is consistent with regional and global changes. Climatic and environmental factors such as extreme weather changes, dust particles, expansion of the application of new industrial materials, and regional wars with potential use of banned weapons are among the issues that may, in part, be able to justify the global and regional changes of the disease. Predictive models indicate a growing trend of the disease, highlighting the need for more regular monitoring of the disease trend in upcoming years. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Market inefficiency identified by both single and multiple currency trends

NASA Astrophysics Data System (ADS)

Tokár, T.; Horváth, D.

2012-11-01

Many studies have shown that there are good reasons to claim very low predictability of currency returns; nevertheless, the deviations from true randomness exist which have potential predictive and prognostic power [J. James, Simple trend-following strategies in currency trading, Quantitative finance 3 (2003) C75-C77]. We analyze the local trends which are of the main focus of the technical analysis. In this article we introduced various statistical quantities examining role of single temporal discretized trend or multitude of grouped trends corresponding to different time delays. Our specific analysis based predominantly on Euro-dollar currency pair data at the one minute frequency suggests the importance of cumulative nonrandom effect of trends on the potential forecasting performance.

Modeling seasonal variation of hip fracture in Montreal, Canada.

PubMed

Modarres, Reza; Ouarda, Taha B M J; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2012-04-01

The investigation of the association of the climate variables with hip fracture incidences is important in social health issues. This study examined and modeled the seasonal variation of monthly population based hip fracture rate (HFr) time series. The seasonal ARIMA time series modeling approach is used to model monthly HFr incidences time series of female and male patients of the ages 40-74 and 75+ of Montreal, Québec province, Canada, in the period of 1993-2004. The correlation coefficients between meteorological variables such as temperature, snow depth, rainfall depth and day length and HFr are significant. The nonparametric Mann-Kendall test for trend assessment and the nonparametric Levene's test and Wilcoxon's test for checking the difference of HFr before and after change point are also used. The seasonality in HFr indicated sharp difference between winter and summer time. The trend assessment showed decreasing trends in HFr of female and male groups. The nonparametric test also indicated a significant change of the mean HFr. A seasonal ARIMA model was applied for HFr time series without trend and a time trend ARIMA model (TT-ARIMA) was developed and fitted to HFr time series with a significant trend. The multi criteria evaluation showed the adequacy of SARIMA and TT-ARIMA models for modeling seasonal hip fracture time series with and without significant trend. In the time series analysis of HFr of the Montreal region, the effects of the seasonal variation of climate variables on hip fracture are clear. The Seasonal ARIMA model is useful for modeling HFr time series without trend. However, for time series with significant trend, the TT-ARIMA model should be applied for modeling HFr time series. Copyright © 2011 Elsevier Inc. All rights reserved.

Using exogenous variables in testing for monotonic trends in hydrologic time series

USGS Publications Warehouse

Alley, William M.

1988-01-01

One approach that has been used in performing a nonparametric test for monotonic trend in a hydrologic time series consists of a two-stage analysis. First, a regression equation is estimated for the variable being tested as a function of an exogenous variable. A nonparametric trend test such as the Kendall test is then performed on the residuals from the equation. By analogy to stagewise regression and through Monte Carlo experiments, it is demonstrated that this approach will tend to underestimate the magnitude of the trend and to result in some loss in power as a result of ignoring the interaction between the exogenous variable and time. An alternative approach, referred to as the adjusted variable Kendall test, is demonstrated to generally have increased statistical power and to provide more reliable estimates of the trend slope. In addition, the utility of including an exogenous variable in a trend test is examined under selected conditions.

Comparison of Salmonella enteritidis phage types isolated from layers and humans in Belgium in 2005.

PubMed

Welby, Sarah; Imberechts, Hein; Riocreux, Flavien; Bertrand, Sophie; Dierick, Katelijne; Wildemauwe, Christa; Hooyberghs, Jozef; Van der Stede, Yves

2011-08-01

The aim of this study was to investigate the available results for Belgium of the European Union coordinated monitoring program (2004/665 EC) on Salmonella in layers in 2005, as well as the results of the monthly outbreak reports of Salmonella Enteritidis in humans in 2005 to identify a possible statistical significant trend in both populations. Separate descriptive statistics and univariate analysis were carried out and the parametric and/or non-parametric hypothesis tests were conducted. A time cluster analysis was performed for all Salmonella Enteritidis phage types (PTs) isolated. The proportions of each Salmonella Enteritidis PT in layers and in humans were compared and the monthly distribution of the most common PT, isolated in both populations, was evaluated. The time cluster analysis revealed significant clusters during the months May and June for layers and May, July, August, and September for humans. PT21, the most frequently isolated PT in both populations in 2005, seemed to be responsible of these significant clusters. PT4 was the second most frequently isolated PT. No significant difference was found for the monthly trend evolution of both PT in both populations based on parametric and non-parametric methods. A similar monthly trend of PT distribution in humans and layers during the year 2005 was observed. The time cluster analysis and the statistical significance testing confirmed these results. Moreover, the time cluster analysis showed significant clusters during the summer time and slightly delayed in time (humans after layers). These results suggest a common link between the prevalence of Salmonella Enteritidis in layers and the occurrence of the pathogen in humans. Phage typing was confirmed to be a useful tool for identifying temporal trends.

Spatial correlation in precipitation trends in the Brazilian Amazon

NASA Astrophysics Data System (ADS)

Buarque, Diogo Costa; Clarke, Robin T.; Mendes, Carlos Andre Bulhoes

2010-06-01

A geostatistical analysis of variables derived from Amazon daily precipitation records (trends in annual precipitation totals, trends in annual maximum precipitation accumulated over 1-5 days, trend in length of dry spell, trend in number of wet days per year) gave results that are consistent with those previously reported. Averaged over the Brazilian Amazon region as a whole, trends in annual maximum precipitations were slightly negative, the trend in the length of dry spell was slightly positive, and the trend in the number of wet days in the year was slightly negative. For trends in annual maximum precipitation accumulated over 1-5 days, spatial correlation between trends was found to extend up to a distance equivalent to at least half a degree of latitude or longitude, with some evidence of anisotropic correlation. Time trends in annual precipitation were found to be spatially correlated up to at least ten degrees of separation, in both W-E and S-N directions. Anisotropic spatial correlation was strongly evident in time trends in length of dry spell with much stronger evidence of spatial correlation in the W-E direction, extending up to at least five degrees of separation, than in the S-N. Because the time trends analyzed are shown to be spatially correlated, it is argued that methods at present widely used to test the statistical significance of climate trends over time lead to erroneous conclusions if spatial correlation is ignored, because records from different sites are assumed to be statistically independent.

Multi-Scale Analysis of Trends in Northeastern Temperate Forest Springtime Phenology

NASA Astrophysics Data System (ADS)

Moon, M.; Melaas, E. K.; Sulla-menashe, D. J.; Friedl, M. A.

2017-12-01

The timing of spring leaf emergence is highly variable in many ecosystems, exerts first-order control growing season length, and significantly modulates seasonally-integrated photosynthesis. Numerous studies have reported trends toward earlier spring phenology in temperate forests, with some papers indicating that this trend is also leading to increased carbon uptake. At broad spatial scales, however, most of these studies have used data from coarse spatial resolution instruments such as MODIS, which does not resolve ecologically important landscape-scale patterns in phenology. In this work, we examine how long-term trends in spring phenology differ across three data sources acquired at different scales of measurements at the Harvard Forest in central Massachusetts. Specifically, we compared trends in the timing of phenology based on long-term in-situ measurements of phenology, estimates based on eddy-covariance measurements of net carbon uptake transition dates, and from two sources of satellite-based remote sensing (MODIS and Landsat) land surface phenology (LSP) data. Our analysis focused on the flux footprint surrounding the Harvard Forest Environmental Measurements (EMS) tower. Our results reveal clearly defined trends toward earlier springtime phenology in Landsat LSP and in the timing of tower-based net carbon uptake. However, we find no statistically significant trend in springtime phenology measured from MODIS LSP data products, possibly because the time series of MODIS observations is relatively short (13 years). The trend in tower-based transition data exhibited a larger negative value than the trend derived from Landsat LSP data (-0.42 and -0.28 days per year for 21 and 28 years, respectively). More importantly, these results have two key implications regarding how changes in spring phenology are impacting carbon uptake at landscape-scale. First, long-term trends in spring phenology can be quite different, depending on what data source is used to estimate the trend, and 2) the response of carbon uptake to climate change may be more sensitive than the response of land surface phenology itself.

Including land cover change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from Guangzhou, China (2000–2014)

USGS Publications Warehouse

Zhu, Zhe; Fu, Yingchun; Woodcock, Curtis; Olofsson, Pontus; Vogelmann, James; Holden, Christopher; Wang, Min; Dai, Shu; Yu, Yang

2016-01-01

An assessment of the consistency of surface reflectance from Landsat 8 with past Landsat sensors indicates biases in the visible bands of Landsat 8, especially the blue band. Landsat 8 NDVI values were found to have a larger bias than the EVI values; therefore, EVI was used in the analysis of greenness trends for Guangzhou. In spite of massive amounts of development in Guangzhou from 2000 to 2014, greenness was found to increase, mostly as a result of gradual change. Comparison of the greening magnitudes estimated from the approach presented here and a Simple Linear Trend (SLT) method indicated large differences for certain time intervals as the SLT method does not include consideration for abrupt land cover changes. Overall, this analysis demonstrates the importance of considering land cover change when analyzing trends in greenness from satellite time series in areas where land cover change is common.

Variability of African Farming Systems from Phenological Analysis of NDVI Time Series

NASA Technical Reports Server (NTRS)

Vrieling, Anton; deBeurs, K. M.; Brown, Molly E.

2011-01-01

Food security exists when people have access to sufficient, safe and nutritious food at all times to meet their dietary needs. The natural resource base is one of the many factors affecting food security. Its variability and decline creates problems for local food production. In this study we characterize for sub-Saharan Africa vegetation phenology and assess variability and trends of phenological indicators based on NDVI time series from 1982 to 2006. We focus on cumulated NDVI over the season (cumNDVI) which is a proxy for net primary productivity. Results are aggregated at the level of major farming systems, while determining also spatial variability within farming systems. High temporal variability of cumNDVI occurs in semiarid and subhumid regions. The results show a large area of positive cumNDVI trends between Senegal and South Sudan. These correspond to positive CRU rainfall trends found and relate to recovery after the 1980's droughts. We find significant negative cumNDVI trends near the south-coast of West Africa (Guinea coast) and in Tanzania. For each farming system, causes of change and variability are discussed based on available literature (Appendix A). Although food security comprises more than the local natural resource base, our results can perform an input for food security analysis by identifying zones of high variability or downward trends. Farming systems are found to be a useful level of analysis. Diversity and trends found within farming system boundaries underline that farming systems are dynamic.

Comparison and covalidation of ozone anomalies and variability observed in SBUV(/2) and Umkehr northern midlatitude ozone profile estimates

NASA Astrophysics Data System (ADS)

Petropavlovskikh, I.; Ahn, Changwoo; Bhartia, P. K.; Flynn, L. E.

2005-03-01

This analysis presents comparisons of upper-stratosphere ozone information observed by two independent systems: the Solar Backscatter UltraViolet (SBUV and SBUV/2) satellite instruments, and ground-based Dobson spectrophotometers. Both the new SBUV Version 8 and the new UMK04 profile retrieval algorithms are optimized for studying long-term variability and trends in ozone. Trend analyses of the ozone time series from the SBUV(/2) data set are complex because of the multiple instruments involved, changes in the instruments' geo-location, and short periods of overlaps for inter-calibrations among different instruments. Three northern middle latitudes Dobson ground stations (Arosa, Boulder, and Tateno) are used in this analysis to validate the trend quality of the combined 25-year SBUV/2 time series, 1979 to 2003. Generally, differences between the satellite and ground-based data do not suggest any significant time-dependent shifts or trends. The shared features confirm the value of these data sets for studies of ozone variability.

Trend Switching Processes in Financial Markets

NASA Astrophysics Data System (ADS)

Preis, Tobias; Stanley, H. Eugene

For an intriguing variety of switching processes in nature, the underlying complex system abruptly changes at a specific point from one state to another in a highly discontinuous fashion. Financial market fluctuations are characterized by many abrupt switchings creating increasing trends ("bubble formation") and decreasing trends ("bubble collapse"), on time scales ranging from macroscopic bubbles persisting for hundreds of days to microscopic bubbles persisting only for very short time scales. Our analysis is based on a German DAX Future data base containing 13,991,275 transactions recorded with a time resolution of 10- 2 s. For a parallel analysis, we use a data base of all S&P500 stocks providing 2,592,531 daily closing prices. We ask whether these ubiquitous switching processes have quantifiable features independent of the time horizon studied. We find striking scale-free behavior of the volatility after each switching occurs. We interpret our findings as being consistent with time-dependent collective behavior of financial market participants. We test the possible universality of our result by performing a parallel analysis of fluctuations in transaction volume and time intervals between trades. We show that these financial market switching processes have features similar to those present in phase transitions. We find that the well-known catastrophic bubbles that occur on large time scales - such as the most recent financial crisis - are no outliers but in fact single dramatic representatives caused by the formation of upward and downward trends on time scales varying over nine orders of magnitude from the very large down to the very small.

Global Precipitation Analyses at Time Scales of Monthly to 3-Hourly

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Huffman, George; Curtis, Scott; Bolvin, David; Nelkin, Eric; Einaudi, Franco (Technical Monitor)

2002-01-01

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM (Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the Goodyear data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the Goodyear period. Monthly anomalies of precipitation are related to ENRON variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1 degree latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is described. Finally, a TRMM-based Based analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous OR observations and merges the various calibrated observations into a final, Baehr resolution map. This TRMM standard product will be available for the entire TRMM period (January Represent). A real-time version of this merged product is being produced and is available at 0.25 degree latitude-longitude resolution over the latitude range from 50 deg. N -50 deg. S. Examples will be shown, including its use in monitoring flood conditions.

Time series analysis of patients seeking orthodontic treatment at Seoul National University Dental Hospital over the past decade

PubMed Central

Lim, Hyun-Woo; Park, Ji-Hoon; Park, Hyun-Hee

2017-01-01

Objective This paper describes changes in the characteristics of patients seeking orthodontic treatment over the past decade and the treatment they received, to identify any seasonal variations or trends. Methods This single-center retrospective cohort study included all patients who presented to Seoul National University Dental Hospital for orthodontic diagnosis and treatment between January 1, 2005 and December 31, 2015. The study analyzed a set of heterogeneous variables grouped into the following categories: demographic (age, gender, and address), clinical (Angle Classification, anomaly, mode of orthodontic treatment, removable appliances for Phase 1 treatment, fixed appliances for Phase 2 treatment, orthognathic surgery, extraction, mini-plate, mini-implant, and patient transfer) and time-related variables (date of first visit and orthodontic treatment time). Time series analysis was applied to each variable. Results The sample included 14,510 patients with a median age of 19.5 years. The number of patients and their ages demonstrated a clear seasonal variation, which peaked in the summer and winter. Increasing trends were observed for the proportion of male patients, use of non-extraction treatment modality, use of ceramic brackets, patients from provinces outside the Seoul region at large, patients transferred from private practitioners, and patients who underwent orthognathic surgery performed by university surgeons. Decreasing trends included the use of metal brackets and orthodontic treatment time. Conclusions Time series analysis revealed a seasonal variation in some characteristics, and several variables showed changing trends over the past decade. PMID:28861391

Sources and preparation of data for assessing trends in concentrations of pesticides in streams of the United States, 1992–2010

USGS Publications Warehouse

Martin, Jeffrey D.; Eberle, Michael; Nakagaki, Naomi

2011-01-01

This report updates a previously published water-quality dataset of 44 commonly used pesticides and 8 pesticide degradates suitable for a national assessment of trends in pesticide concentrations in streams of the United States. Water-quality samples collected from January 1992 through September 2010 at stream-water sites of the U.S. Geological Survey (USGS) National Water-Quality Assessment (NAWQA) Program and the National Stream Quality Accounting Network (NASQAN) were compiled, reviewed, selected, and prepared for trend analysis. The principal steps in data review for trend analysis were to (1) identify analytical schedule, (2) verify sample-level coding, (3) exclude inappropriate samples or results, (4) review pesticide detections per sample, (5) review high pesticide concentrations, and (6) review the spatial and temporal extent of NAWQA pesticide data and selection of analytical methods for trend analysis. The principal steps in data preparation for trend analysis were to (1) select stream-water sites for trend analysis, (2) round concentrations to a consistent level of precision for the concentration range, (3) identify routine reporting levels used to report nondetections unaffected by matrix interference, (4) reassign the concentration value for routine nondetections to the maximum value of the long-term method detection level (maxLT-MDL), (5) adjust concentrations to compensate for temporal changes in bias of recovery of the gas chromatography/mass spectrometry (GCMS) analytical method, and (6) identify samples considered inappropriate for trend analysis. Samples analyzed at the USGS National Water Quality Laboratory (NWQL) by the GCMS analytical method were the most extensive in time and space and, consequently, were selected for trend analysis. Stream-water sites with 3 or more water years of data with six or more samples per year were selected for pesticide trend analysis. The selection criteria described in the report produced a dataset of 21,988 pesticide samples at 212 stream-water sites. Only 21,144 pesticide samples, however, are considered appropriate for trend analysis.

Visual Analysis among Novices: Training and Trend Lines as Graphic Aids

ERIC Educational Resources Information Center

Nelson, Peter M.; Van Norman, Ethan R.; Christ, Theodore J.

2017-01-01

The current study evaluated the degree to which novice visual analysts could discern trends in simulated time-series data across differing levels of variability and extreme values. Forty-five novice visual analysts were trained in general principles of visual analysis. One group received brief training on how to identify and omit extreme values.…

Untenable nonstationarity: An assessment of the fitness for purpose of trend tests in hydrology

NASA Astrophysics Data System (ADS)

Serinaldi, Francesco; Kilsby, Chris G.; Lombardo, Federico

2018-01-01

The detection and attribution of long-term patterns in hydrological time series have been important research topics for decades. A significant portion of the literature regards such patterns as 'deterministic components' or 'trends' even though the complexity of hydrological systems does not allow easy deterministic explanations and attributions. Consequently, trend estimation techniques have been developed to make and justify statements about tendencies in the historical data, which are often used to predict future events. Testing trend hypothesis on observed time series is widespread in the hydro-meteorological literature mainly due to the interest in detecting consequences of human activities on the hydrological cycle. This analysis usually relies on the application of some null hypothesis significance tests (NHSTs) for slowly-varying and/or abrupt changes, such as Mann-Kendall, Pettitt, or similar, to summary statistics of hydrological time series (e.g., annual averages, maxima, minima, etc.). However, the reliability of this application has seldom been explored in detail. This paper discusses misuse, misinterpretation, and logical flaws of NHST for trends in the analysis of hydrological data from three different points of view: historic-logical, semantic-epistemological, and practical. Based on a review of NHST rationale, and basic statistical definitions of stationarity, nonstationarity, and ergodicity, we show that even if the empirical estimation of trends in hydrological time series is always feasible from a numerical point of view, it is uninformative and does not allow the inference of nonstationarity without assuming a priori additional information on the underlying stochastic process, according to deductive reasoning. This prevents the use of trend NHST outcomes to support nonstationary frequency analysis and modeling. We also show that the correlation structures characterizing hydrological time series might easily be underestimated, further compromising the attempt to draw conclusions about trends spanning the period of records. Moreover, even though adjusting procedures accounting for correlation have been developed, some of them are insufficient or are applied only to some tests, while some others are theoretically flawed but still widely applied. In particular, using 250 unimpacted stream flow time series across the conterminous United States (CONUS), we show that the test results can dramatically change if the sequences of annual values are reproduced starting from daily stream flow records, whose larger sizes enable a more reliable assessment of the correlation structures.

Scaling Analysis of Alloy Solidification and Fluid Flow in a Rectangular Cavity

NASA Astrophysics Data System (ADS)

Plotkowski, A.; Fezi, K.; Krane, M. J. M.

A scaling analysis was performed to predict trends in alloy solidification in a side-cooled rectangular cavity. The governing equations for energy and momentum were scaled in order to determine the dependence of various aspects of solidification on the process parameters for a uniform initial temperature and an isothermal boundary condition. This work improved on previous analyses by adding considerations for the cooling bulk fluid flow. The analysis predicted the time required to extinguish the superheat, the maximum local solidification time, and the total solidification time. The results were compared to a numerical simulation for a Al-4.5 wt.% Cu alloy with various initial and boundary conditions. Good agreement was found between the simulation results and the trends predicted by the scaling analysis.

Assessment of trend and seasonality in road accident data: an Iranian case study.

PubMed

Razzaghi, Alireza; Bahrampour, Abbas; Baneshi, Mohammad Reza; Zolala, Farzaneh

2013-06-01

Road traffic accidents and their related deaths have become a major concern, particularly in developing countries. Iran has adopted a series of policies and interventions to control the high number of accidents occurring over the past few years. In this study we used a time series model to understand the trend of accidents, and ascertain the viability of applying ARIMA models on data from Taybad city. This study is a cross-sectional study. We used data from accidents occurring in Taybad between 2007 and 2011. We obtained the data from the Ministry of Health (MOH) and used the time series method with a time lag of one month. After plotting the trend, non-stationary data in mean and variance were removed using Box-Cox transformation and a differencing method respectively. The ACF and PACF plots were used to control the stationary situation. The traffic accidents in our study had an increasing trend over the five years of study. Based on ACF and PACF plots gained after applying Box-Cox transformation and differencing, data did not fit to a time series model. Therefore, neither ARIMA model nor seasonality were observed. Traffic accidents in Taybad have an upward trend. In addition, we expected either the AR model, MA model or ARIMA model to have a seasonal trend, yet this was not observed in this analysis. Several reasons may have contributed to this situation, such as uncertainty of the quality of data, weather changes, and behavioural factors that are not taken into account by time series analysis.

The error and bias of supplementing a short, arid climate, rainfall record with regional vs. global frequency analysis

NASA Astrophysics Data System (ADS)

Endreny, Theodore A.; Pashiardis, Stelios

2007-02-01

SummaryRobust and accurate estimates of rainfall frequencies are difficult to make with short, and arid-climate, rainfall records, however new regional and global methods were used to supplement such a constrained 15-34 yr record in Cyprus. The impact of supplementing rainfall frequency analysis with the regional and global approaches was measured with relative bias and root mean square error (RMSE) values. Analysis considered 42 stations with 8 time intervals (5-360 min) in four regions delineated by proximity to sea and elevation. Regional statistical algorithms found the sites passed discordancy tests of coefficient of variation, skewness and kurtosis, while heterogeneity tests revealed the regions were homogeneous to mildly heterogeneous. Rainfall depths were simulated in the regional analysis method 500 times, and then goodness of fit tests identified the best candidate distribution as the general extreme value (GEV) Type II. In the regional analysis, the method of L-moments was used to estimate location, shape, and scale parameters. In the global based analysis, the distribution was a priori prescribed as GEV Type II, a shape parameter was a priori set to 0.15, and a time interval term was constructed to use one set of parameters for all time intervals. Relative RMSE values were approximately equal at 10% for the regional and global method when regions were compared, but when time intervals were compared the global method RMSE had a parabolic-shaped time interval trend. Relative bias values were also approximately equal for both methods when regions were compared, but again a parabolic-shaped time interval trend was found for the global method. The global method relative RMSE and bias trended with time interval, which may be caused by fitting a single scale value for all time intervals.

Recent shifts in Himalayan vegetation activity trends in response to climatic change and environmental drivers

NASA Astrophysics Data System (ADS)

Mishra, N. B.; Mainali, K. P.

2016-12-01

Climatic changes along with anthropogenic disturbances are causing dramatic ecological impacts in mid to high latitude mountain vegetation including in the Himalayas which are ecologically sensitive environments. Given the challenges associated with in situ vegetation monitoring in the Himalayas, remote sensing based quantification of vegetation dynamics can provide essential ecological information on changes in vegetation activity that may consist of alternative sequence of greening and/or browning periods. This study utilized a trend break analysis procedure for detection of monotonic as well as abrupt (either interruption or reversal) trend changes in smoothed normalized difference vegetation index satellite time-series data over the Himalayas. Overall, trend breaks in vegetation greenness showed high spatio-temporal variability in distribution considering elevation, ecoregion and land cover/use stratifications. Interrupted greening was spatially most dominant in all Himalayan ecoregions followed by abrupt browning. Areas showing trend reversal and monotonic trends appeared minority. Trend type distribution was strongly dependent on elevation as majority of greening (with or without interruption) occurred at lower elevation areas at higher elevation were dominantly. Ecoregion based stratification of trend types highlighted some exception to this elevational dependence as high altitude ecoregions of western Himalayas showed significantly less browning compared to the ecoregions in eastern Himalaya. Land cover/use based analysis of trend distribution showed that interrupted greening was most dominant in closed needleleafed forest following by rainfed cropland and mosaic croplands while interrupted browning most dominant in closed to open herbaceous vegetation found at higher elevation areas followed by closed needleleafed forest and closed to open broad leafed evergreen forests. Spatial analysis of trend break timing showed that for majority of areas experiencing interrupted greening, break in trend occurred later compared to areas with interrupted browning where break trend was observed much earlier. These results have significant implications for environmental management in the context of climate change and ecosystem dynamics in the Himalayas.

Using Time Series Analysis to Predict Cardiac Arrest in a PICU.

PubMed

Kennedy, Curtis E; Aoki, Noriaki; Mariscalco, Michele; Turley, James P

2015-11-01

To build and test cardiac arrest prediction models in a PICU, using time series analysis as input, and to measure changes in prediction accuracy attributable to different classes of time series data. Retrospective cohort study. Thirty-one bed academic PICU that provides care for medical and general surgical (not congenital heart surgery) patients. Patients experiencing a cardiac arrest in the PICU and requiring external cardiac massage for at least 2 minutes. None. One hundred three cases of cardiac arrest and 109 control cases were used to prepare a baseline dataset that consisted of 1,025 variables in four data classes: multivariate, raw time series, clinical calculations, and time series trend analysis. We trained 20 arrest prediction models using a matrix of five feature sets (combinations of data classes) with four modeling algorithms: linear regression, decision tree, neural network, and support vector machine. The reference model (multivariate data with regression algorithm) had an accuracy of 78% and 87% area under the receiver operating characteristic curve. The best model (multivariate + trend analysis data with support vector machine algorithm) had an accuracy of 94% and 98% area under the receiver operating characteristic curve. Cardiac arrest predictions based on a traditional model built with multivariate data and a regression algorithm misclassified cases 3.7 times more frequently than predictions that included time series trend analysis and built with a support vector machine algorithm. Although the final model lacks the specificity necessary for clinical application, we have demonstrated how information from time series data can be used to increase the accuracy of clinical prediction models.

[Improved euler algorithm for trend forecast model and its application to oil spectrum analysis].

PubMed

Zheng, Chang-song; Ma, Biao

2009-04-01

The oil atomic spectrometric analysis technology is one of the most important methods for fault diagnosis and state monitoring of large machine equipment. The gray method is preponderant in the trend forecast at the same time. With the use of oil atomic spectrometric analysis result and combining the gray forecast theory, the present paper established a gray forecast model of the Fe/Cu concentration trend in the power-shift steering transmission. Aiming at the shortage of the gray method used in the trend forecast, the improved Euler algorithm was put forward for the first time to resolve the problem of the gray model and avoid the non-precision that the old gray model's forecast value depends on the first test value. This new method can make the forecast value more precision as shown in the example. Combined with the threshold value of the oil atomic spectrometric analysis, the new method was applied on the Fe/Cu concentration forecast and the premonition of fault information was obtained. So we can take steps to prevent the fault and this algorithm can be popularized to the state monitoring in the industry.

Interrupted time-series analysis: studying trends in neurosurgery.

PubMed

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.

Water-quality trends in the nation’s rivers and streams, 1972–2012—Data preparation, statistical methods, and trend results

USGS Publications Warehouse

Oelsner, Gretchen P.; Sprague, Lori A.; Murphy, Jennifer C.; Zuellig, Robert E.; Johnson, Henry M.; Ryberg, Karen R.; Falcone, James A.; Stets, Edward G.; Vecchia, Aldo V.; Riskin, Melissa L.; De Cicco, Laura A.; Mills, Taylor J.; Farmer, William H.

2017-04-04

Since passage of the Clean Water Act in 1972, Federal, State, and local governments have invested billions of dollars to reduce pollution entering rivers and streams. To understand the return on these investments and to effectively manage and protect the Nation’s water resources in the future, we need to know how and why water quality has been changing over time. As part of the National Water-Quality Assessment Project, of the U.S. Geological Survey’s National Water-Quality Program, data from the U.S. Geological Survey, along with multiple other Federal, State, Tribal, regional, and local agencies, have been used to support the most comprehensive assessment conducted to date of surface-water-quality trends in the United States. This report documents the methods used to determine trends in water quality and ecology because these methods are vital to ensuring the quality of the results. Specific objectives are to document (1) the data compilation and processing steps used to identify river and stream sites throughout the Nation suitable for water-quality, pesticide, and ecology trend analysis, (2) the statistical methods used to determine trends in target parameters, (3) considerations for water-quality, pesticide, and ecology data and streamflow data when modeling trends, (4) sensitivity analyses for selecting data and interpreting trend results with the Weighted Regressions on Time, Discharge, and Season method, and (5) the final trend results at each site. The scope of this study includes trends in water-quality concentrations and loads (nutrient, sediment, major ion, salinity, and carbon), pesticide concentrations and loads, and metrics for aquatic ecology (fish, invertebrates, and algae) for four time periods: (1) 1972–2012, (2) 1982–2012, (3) 1992–2012, and (4) 2002–12. In total, nearly 12,000 trends in concentration, load, and ecology metrics were evaluated in this study; there were 11,893 combinations of sites, parameters, and trend periods. The final trend results are presented with examples of how to interpret the results from each trend model. Interpretation of the trend results, such as causal analysis, is not included.

Evaluation of NASA's MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

NASA Technical Reports Server (NTRS)

Ashouri, Hamed; Sorooshian, Soroosh; Hsu, Kuo-Lin; Bosilovich, Michael G.; Lee, Jaechoul; Wehner, Michael F.; Collow, Allison

2016-01-01

This study evaluates the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979-2010. The Climate Prediction Center (CPC) U.S.Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scale patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRA tends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1) MERRA shows a spurious negative trend in Nebraska and Kansas, which is most likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over the Gulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. In addition, the increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.

Evaluation of NASA’s MERRA Precipitation Product in Reproducing the Observed Trend and Distribution of Extreme Precipitation Events in the United States

DOE PAGES

Ashouri, Hamed; Sorooshian, Soroosh; Hsu, Kuo-Lin; ...

2016-02-03

This study evaluates the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979-2010. The Climate Prediction Center (CPC)U.S.Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scalemore » patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRAtends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1)MERRAshows a spurious negative trend in Nebraska andKansas, which ismost likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over theGulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. The increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.« less

Detecting trend on ecological river status - how to deal with short incomplete bioindicator time series? Methodological and operational issues

NASA Astrophysics Data System (ADS)

Cernesson, Flavie; Tournoud, Marie-George; Lalande, Nathalie

2018-06-01

Among the various parameters monitored in river monitoring networks, bioindicators provide very informative data. Analysing time variations in bioindicator data is tricky for water managers because the data sets are often short, irregular, and non-normally distributed. It is then a challenging methodological issue for scientists, as it is in Saône basin (30 000 km2, France) where, between 1998 and 2010, among 812 IBGN (French macroinvertebrate bioindicator) monitoring stations, only 71 time series have got more than 10 data values and were studied here. Combining various analytical tools (three parametric and non-parametric statistical tests plus a graphical analysis), 45 IBGN time series were classified as stationary and 26 as non-stationary (only one of which showing a degradation). Series from sampling stations located within the same hydroecoregion showed similar trends, while river size classes seemed to be non-significant to explain temporal trends. So, from a methodological point of view, combining statistical tests and graphical analysis is a relevant option when striving to improve trend detection. Moreover, it was possible to propose a way to summarise series in order to analyse links between ecological river quality indicators and land use stressors.

Detecting dryland degradation through the use of Time Series Segmentation and Residual Trend analysis (TSS-RESTREND)

NASA Astrophysics Data System (ADS)

Burrell, A. L.; Evans, J. P.; Liu, Y.

2017-12-01

Dryland degradation is an issue of international significance as dryland regions play a substantial role in global food production. Remotely sensed data provide the only long term, large scale record of changes within dryland ecosystems. The Residual Trend, or RESTREND, method is applied to satellite observations to detect dryland degradation. Whilst effective in most cases, it has been shown that the RESTREND method can fail to identify degraded pixels if the relationship between vegetation and precipitation has broken-down as a result of severe or rapid degradation. This study presents an extended version of the RESTREND methodology that incorporates the Breaks For Additive Seasonal and Trend method to identify step changes in the time series that are related to significant structural changes in the ecosystem, e.g. land use changes. When applied to Australia, this new methodology, termed Time Series Segmentation and Residual Trend analysis (TSS-RESTREND), was able to detect degradation in 5.25% of pixels compared to only 2.0% for RESTREND alone. This modified methodology was then assessed in two regions with known histories of degradation where it was found to accurately capture both the timing and directionality of ecosystem change.

Trend Detection and Bivariate Frequency Analysis for Nonstrationary Rainfall Data

NASA Astrophysics Data System (ADS)

Joo, K.; Kim, H.; Shin, J. Y.; Heo, J. H.

2017-12-01

Multivariate frequency analysis has been developing for hydro-meteorological data such as rainfall, flood, and drought. Particularly, the copula has been used as a useful tool for multivariate probability model which has no limitation on deciding marginal distributions. The time-series rainfall data can be characterized to rainfall event by inter-event time definition (IETD) and each rainfall event has a rainfall depth and rainfall duration. In addition, nonstationarity in rainfall event has been studied recently due to climate change and trend detection of rainfall event is important to determine the data has nonstationarity or not. With the rainfall depth and duration of a rainfall event, trend detection and nonstationary bivariate frequency analysis has performed in this study. 62 stations from Korea Meteorological Association (KMA) over 30 years of hourly recorded data used in this study and the suitability of nonstationary copula for rainfall event has examined by the goodness-of-fit test.

AR(p) -based detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Alvarez-Ramirez, J.; Rodriguez, E.

2018-07-01

Autoregressive models are commonly used for modeling time-series from nature, economics and finance. This work explored simple autoregressive AR(p) models to remove long-term trends in detrended fluctuation analysis (DFA). Crude oil prices and bitcoin exchange rate were considered, with the former corresponding to a mature market and the latter to an emergent market. Results showed that AR(p) -based DFA performs similar to traditional DFA. However, the former DFA provides information on stability of long-term trends, which is valuable for understanding and quantifying the dynamics of complex time series from financial systems.

Space-time analysis of snow cover change in the Romanian Carpathians (2001-2016)

NASA Astrophysics Data System (ADS)

Micu, Dana; Cosmin Sandric, Ionut

2017-04-01

Snow cover is recognized as an essential climate variable, highly sensitive to the ongoing climate warming, which plays an important role in regulating mountain ecosystems. Evidence from the existing weather stations located above 800 m over the last 50 years points out that the climate of the Romanian Carpathians is visibly changing, showing an ongoing and consistent warming process. Quantifying and attributing the changes in snow cover on various spatial and temporal scales have a great environmental and socio-economic importance for this mountain region. The study is revealing the inter-seasonal changes in the timing and distribution of snow cover across the Romanian Carpathians, by combining gridded snow data (CARPATCLIM dataset, 1961-2010) and remote sensing data (2001-2016) in specific space-time assessment at regional scale. The geostatistical approach applied in this study, based on a GIS hotspot analysis, takes advantage of all the dimensions in the datasets, in order to understand the space-time trends in this climate variable at monthly time-scale. The MODIS AQUA and TERRA images available from 2001 to 2016 have been processed using ArcGIS for Desktop and Python programming language. All the images were masked out with the Carpathians boundary. Only the pixels with snow have been retained for analysis. The regional trends in snow cover distribution and timing have been analysed using Space-Time cube with ArcGIS for Desktop, according with Esri documentation using the Mann-Kendall trend test on every location with data as an independent bin time-series test. The study aimed also to assess the location of emerging hotspots of snow cover change in Carpathians. These hotspots have been calculated using Getis-Ord Gi* statistic for each bin using Hot Spot Analysis implemented in ArcGIS for Desktop. On regional scale, snow cover appear highly sensitive to the decreasing trends in air temperatures and land surface temperatures, combined with the decrease in seasonal precipitation, especially at lower elevations in all the three divisions of the Romanian Carpathians (generally below 1,700-1,800 m). The space-time patterns of snow cover change are dominated by a significant decreasing trend of snow days and earlier spring snow melt. The key findings of this study provides robust indication of a decreasing snow trends across the Carpathian Mountain region and could provide valuable spatial and temporal snow information for other related research fields as well as for an effective environmental monitoring in the mountain ecosystems of the Carpathian region

Non-target time trend screening: a data reduction strategy for detecting emerging contaminants in biological samples.

PubMed

Plassmann, Merle M; Tengstrand, Erik; Åberg, K Magnus; Benskin, Jonathan P

2016-06-01

Non-targeted mass spectrometry-based approaches for detecting novel xenobiotics in biological samples are hampered by the occurrence of naturally fluctuating endogenous substances, which are difficult to distinguish from environmental contaminants. Here, we investigate a data reduction strategy for datasets derived from a biological time series. The objective is to flag reoccurring peaks in the time series based on increasing peak intensities, thereby reducing peak lists to only those which may be associated with emerging bioaccumulative contaminants. As a result, compounds with increasing concentrations are flagged while compounds displaying random, decreasing, or steady-state time trends are removed. As an initial proof of concept, we created artificial time trends by fortifying human whole blood samples with isotopically labelled standards. Different scenarios were investigated: eight model compounds had a continuously increasing trend in the last two to nine time points, and four model compounds had a trend that reached steady state after an initial increase. Each time series was investigated at three fortification levels and one unfortified series. Following extraction, analysis by ultra performance liquid chromatography high-resolution mass spectrometry, and data processing, a total of 21,700 aligned peaks were obtained. Peaks displaying an increasing trend were filtered from randomly fluctuating peaks using time trend ratios and Spearman's rank correlation coefficients. The first approach was successful in flagging model compounds spiked at only two to three time points, while the latter approach resulted in all model compounds ranking in the top 11 % of the peak lists. Compared to initial peak lists, a combination of both approaches reduced the size of datasets by 80-85 %. Overall, non-target time trend screening represents a promising data reduction strategy for identifying emerging bioaccumulative contaminants in biological samples. Graphical abstract Using time trends to filter out emerging contaminants from large peak lists.

Precipitation trends in the Canary Islands

NASA Astrophysics Data System (ADS)

García-Herrera, Ricardo; Gallego, David; Hernández, Emiliano; Gimeno, Luis; Ribera, Pedro; Calvo, Natalia

2003-02-01

A strong decreasing trend in the Canary Islands' precipitation is detected by studying daily rainfall time series for the second half of the 20th century. An analysis of the extreme events shows that this trend is due mainly to a decrease in the upper percentiles of the precipitation distribution. The results suggest that local factors play a fundamental role on extreme event behaviour.

Temporal correlations in population trends: Conservation implications from time-series analysis of diverse animal taxa

Treesearch

David Keith; H. Resit Akcakaya; Stuart H.M. Butchart; Ben Collen; Nicholas K. Dulvy; Elizabeth E. Holmes; Jeffrey A. Hutchings; Doug Keinath; Michael K. Schwartz; Andrew O. Shelton; Robin S. Waples

2015-01-01

Population trends play a large role in species risk assessments and conservation planning, and species are often considered threatened if their recent rate of decline meets certain thresholds, regardless how large the population is. But how reliable an indicator of extinction risk is a single estimate of population trend? Given the integral role this decline-...

Exploring the Link Between Streamflow Trends and Climate Change in Indiana, USA

NASA Astrophysics Data System (ADS)

Kumar, S.; Kam, J.; Thurner, K.; Merwade, V.

2007-12-01

Streamflow trends in Indiana are evaluated for 85 USGS streamflow gaging stations that have continuous unregulated streamflow records varying from 10 to 80 years. The trends are analyzed by using the non-parametric Mann-Kendall test with prior trend-free pre-whitening to remove serial correlation in the data. Bootstrap method is used to establish field significance of the results. Trends are computed for 12 streamflow statistics to include low-, medium- (median and mean flow), and high-flow conditions on annual and seasonal time step. The analysis is done for six study periods, ranging from 10 years to more than 65 years, all ending in 2003. The trends in annual average streamflow, for 50 years study period, are compared with annual average precipitation trends from 14 National Climatic Data Center (NCDC) stations in Indiana, that have 50 years of continuous daily record. The results show field significant positive trends in annual low and medium streamflow statistics at majority of gaging stations for study periods that include 40 or more years of records. In seasonal analysis, all flow statistics in summer and fall (low flow seasons), and only low flow statistics in winter and spring (high flow seasons) are showing positive trends. No field significant trends in annual and seasonal flow statistics are observed for study periods that include 25 or fewer years of records, except for northern Indiana where localized negative trends are observed in 10 and 15 years study periods. Further, stream flow trends are found to be highly correlated with precipitation trends on annual time step. No apparent climate change signal is observed in Indiana stream flow records.

Analysis of rainfall and temperature time series to detect long-term climatic trends and variability over semi-arid Botswana

NASA Astrophysics Data System (ADS)

Byakatonda, Jimmy; Parida, B. P.; Kenabatho, Piet K.; Moalafhi, D. B.

2018-03-01

Arid and semi-arid environments have been identified with locations prone to impacts of climate variability and change. Investigating long-term trends is one way of tracing climate change impacts. This study investigates variability through annual and seasonal meteorological time series. Possible inhomogeneities and years of intervention are analysed using four absolute homogeneity tests. Trends in the climatic variables were determined using Mann-Kendall and Sen's Slope estimator statistics. Association of El Niño Southern Oscillation (ENSO) with local climate is also investigated through multivariate analysis. Results from the study show that rainfall time series are fully homogeneous with 78.6 and 50% of the stations for maximum and minimum temperature, respectively, showing homogeneity. Trends also indicate a general decrease of 5.8, 7.4 and 18.1% in annual, summer and winter rainfall, respectively. Warming trends are observed in annual and winter temperature at 0.3 and 1.5% for maximum temperature and 1.7 and 6.5% for minimum temperature, respectively. Rainfall reported a positive correlation with Southern Oscillation Index (SOI) and at the same time negative association with Sea Surface Temperatures (SSTs). Strong relationships between SSTs and maximum temperature are observed during the El Niño and La Niña years. These study findings could facilitate planning and management of agricultural and water resources in Botswana.

Elderly suicide trends in the context of transforming China, 1987–2014

PubMed Central

Zhong, Bao-Liang; Chiu, Helen F. K.; Conwell, Yeates

2016-01-01

In the context of rapid ageing, understanding the time-trend of elderly suicide (ES) could inform China’s efforts on suicide prevention. We examined time-trends in Chinese ES rates (ESRs) from 1987 to 2014, a period of profound social changes. Suicide rates by residence (rural/urban), gender, and 5-year age-group (65+) in 1987–2014 were provided by the Chinese Ministry of Health. Time-trends were analyzed with joinpoint analysis. The time-trend of national ESRs was downward (average annual percent change [AAPC] = −3.7, P < 0.001): 76.6/100000 in 1987 and 30.2/100000 in 2014. However, the time-trend of corresponding percentages of ESs among the total suicides was monotonically increasing (AAPC = 3.4, P < 0.001): 16.9% in 1987 to 41.2% in 2014. The time-trends in ESRs of both rural and urban men and women were decreasing, but only the rural trends were significant (P < 0.001). Rural-urban and male-female differences in ESRs were decreasing over time (slope = −4.2 and −3.0, P ≤ 0.006), but the rural-urban and male-female ESR differences in 2014 remained large (16.3/100000 and 9.8/100000, P < 0.001). While national ESRs decreased significantly during the past three decades, the current ESR remains high in China. Further, the age-pattern of Chinese suicide is transitioning to elderly predominance. ES, particularly rural ES, should be a public health priority in China. PMID:27886219

Time Trend Analysis of Oral Cancer in Iran from 2005 to 2010.

PubMed

Iranfar, Khosro; Mokhayeri, Yaser; Mohammadi, Gohar

2016-01-01

There is a considerable lack of understanding of oral cancer incidence, especially its time trend in Iran. In this study, the authors aimed to analyze time trend of oral cancer incidence with a focus on differences by gender in a period of six years - from 2005 to 2010. Both population-based cancer registry and national cancer registry (NCR) data based on pathologic reports from 2005 to 2010 were obtained from the Ministry of Health and Medical Education (MOHME). Population data were also received from Statistical Centre of Iran. Age-standardized incidence rates (ASRs) based on the World Standard Population were then calculated. Finally, Negative Binomial regression was run for time trend analysis. The maximum ASR for males was calculated as 2.5 per 100,000 person-years in 2008 and the minimum was observed as 1.9 per 100,000 person-years in 2005 and 2006. Meanwhile, the maximum ASR for females was estimated as 1.8 per 100,000 person-years in 2009 and the minimum was calculated as 1.6 per 100,000 person-years in 2005 and 2006. Additionally, in females, incidence risk ratio (IRR) did not show a clear decreasing or increasing trend during the six years. Nevertheless, in males an increasing trend was observed. The maximum IRR adjusted for age group and province, for females was reported in 2009 (IRR=1.05 95% CI: 0.90-1.23), and for males was estimated in 2010 (IRR=1/2 95% CI: 1.04 - 1.38). Our findings highlight disparities between oral cancer incidence trends in males and females over the six years from 2005 to 2010.

Time-series analysis of delta13C from tree rings. I. Time trends and autocorrelation.

PubMed

Monserud, R A; Marshall, J D

2001-09-01

Univariate time-series analyses were conducted on stable carbon isotope ratios obtained from tree-ring cellulose. We looked for the presence and structure of autocorrelation. Significant autocorrelation violates the statistical independence assumption and biases hypothesis tests. Its presence would indicate the existence of lagged physiological effects that persist for longer than the current year. We analyzed data from 28 trees (60-85 years old; mean = 73 years) of western white pine (Pinus monticola Dougl.), ponderosa pine (Pinus ponderosa Laws.), and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. glauca) growing in northern Idaho. Material was obtained by the stem analysis method from rings laid down in the upper portion of the crown throughout each tree's life. The sampling protocol minimized variation caused by changing light regimes within each tree. Autoregressive moving average (ARMA) models were used to describe the autocorrelation structure over time. Three time series were analyzed for each tree: the stable carbon isotope ratio (delta(13)C); discrimination (delta); and the difference between ambient and internal CO(2) concentrations (c(a) - c(i)). The effect of converting from ring cellulose to whole-leaf tissue did not affect the analysis because it was almost completely removed by the detrending that precedes time-series analysis. A simple linear or quadratic model adequately described the time trend. The residuals from the trend had a constant mean and variance, thus ensuring stationarity, a requirement for autocorrelation analysis. The trend over time for c(a) - c(i) was particularly strong (R(2) = 0.29-0.84). Autoregressive moving average analyses of the residuals from these trends indicated that two-thirds of the individual tree series contained significant autocorrelation, whereas the remaining third were random (white noise) over time. We were unable to distinguish between individuals with and without significant autocorrelation beforehand. Significant ARMA models were all of low order, with either first- or second-order (i.e., lagged 1 or 2 years, respectively) models performing well. A simple autoregressive (AR(1)), model was the most common. The most useful generalization was that the same ARMA model holds for each of the three series (delta(13)C, delta, c(a) - c(i)) for an individual tree, if the time trend has been properly removed for each series. The mean series for the two pine species were described by first-order ARMA models (1-year lags), whereas the Douglas-fir mean series were described by second-order models (2-year lags) with negligible first-order effects. Apparently, the process of constructing a mean time series for a species preserves an underlying signal related to delta(13)C while canceling some of the random individual tree variation. Furthermore, the best model for the overall mean series (e.g., for a species) cannot be inferred from a consensus of the individual tree model forms, nor can its parameters be estimated reliably from the mean of the individual tree parameters. Because two-thirds of the individual tree time series contained significant autocorrelation, the normal assumption of a random structure over time is unwarranted, even after accounting for the time trend. The residuals of an appropriate ARMA model satisfy the independence assumption, and can be used to make hypothesis tests.

A correction method for systematic error in (1)H-NMR time-course data validated through stochastic cell culture simulation.

PubMed

Sokolenko, Stanislav; Aucoin, Marc G

2015-09-04

The growing ubiquity of metabolomic techniques has facilitated high frequency time-course data collection for an increasing number of applications. While the concentration trends of individual metabolites can be modeled with common curve fitting techniques, a more accurate representation of the data needs to consider effects that act on more than one metabolite in a given sample. To this end, we present a simple algorithm that uses nonparametric smoothing carried out on all observed metabolites at once to identify and correct systematic error from dilution effects. In addition, we develop a simulation of metabolite concentration time-course trends to supplement available data and explore algorithm performance. Although we focus on nuclear magnetic resonance (NMR) analysis in the context of cell culture, a number of possible extensions are discussed. Realistic metabolic data was successfully simulated using a 4-step process. Starting with a set of metabolite concentration time-courses from a metabolomic experiment, each time-course was classified as either increasing, decreasing, concave, or approximately constant. Trend shapes were simulated from generic functions corresponding to each classification. The resulting shapes were then scaled to simulated compound concentrations. Finally, the scaled trends were perturbed using a combination of random and systematic errors. To detect systematic errors, a nonparametric fit was applied to each trend and percent deviations calculated at every timepoint. Systematic errors could be identified at time-points where the median percent deviation exceeded a threshold value, determined by the choice of smoothing model and the number of observed trends. Regardless of model, increasing the number of observations over a time-course resulted in more accurate error estimates, although the improvement was not particularly large between 10 and 20 samples per trend. The presented algorithm was able to identify systematic errors as small as 2.5 % under a wide range of conditions. Both the simulation framework and error correction method represent examples of time-course analysis that can be applied to further developments in (1)H-NMR methodology and the more general application of quantitative metabolomics.

Space-time patterns of trends in stratospheric constituents derived from UARS measurements

NASA Astrophysics Data System (ADS)

Randel, William J.; Wu, Fei; Russell, James M.; Waters, Joe

1999-02-01

The spatial and temporal behavior of low-frequency changes (trends) in stratospheric constituents measured by instruments on the Upper Atmosphere Research Satellite (UARS) during 1991-98 is investigated. The data include CH4, H2O, HF, HCl, O3, and NO2 from the Halogen Occultation Experiment (HALOE), and O3, ClO, and HNO3 from the Microwave Limb Sounder (MLS). Time series of global anomalies are analyzed by linear regression and empirical orthogonal function analysis. Each of the constituents show significant linear trends over at least some region of the stratosphere, and the spatial patterns exhibit coupling between the different species. Several of the constituents (namely CH4, H2O, HF, HCl, O3, and NO2) exhibit a temporal change in trend rates, with strong changes prior to 1996 and weaker (or reversed) trends thereafter. Positive trends are observed in upper stratospheric ClO, with a percentage rate during 1993-97 consistent with stratospheric HCl increases and with tropospheric chlorine emission rates. Significant negative trends in ozone in the tropical middle stratosphere are found in both HALOE and MLS data during 1993-97, together with positive trends in the tropics near 25 km. These trends are very different from the decadal-scale ozone trends observed since 1979, and this demonstrates the variability of trends calculated over short time periods. Positive trends in NO2 are found in the tropical middle stratosphere, and spatial coincidence to the observed ozone decreases suggests the ozone is responding to the NO2 increase. Significant negative trends in HNO3 are found in the lower stratosphere of both hemispheres. These coupled signatures offer a fingerprint of chemical evolution in the stratosphere for the UARS time frame.

An introduction to modeling longitudinal data with generalized additive models: applications to single-case designs.

PubMed

Sullivan, Kristynn J; Shadish, William R; Steiner, Peter M

2015-03-01

Single-case designs (SCDs) are short time series that assess intervention effects by measuring units repeatedly over time in both the presence and absence of treatment. This article introduces a statistical technique for analyzing SCD data that has not been much used in psychological and educational research: generalized additive models (GAMs). In parametric regression, the researcher must choose a functional form to impose on the data, for example, that trend over time is linear. GAMs reverse this process by letting the data inform the choice of functional form. In this article we review the problem that trend poses in SCDs, discuss how current SCD analytic methods approach trend, describe GAMs as a possible solution, suggest a GAM model testing procedure for examining the presence of trend in SCDs, present a small simulation to show the statistical properties of GAMs, and illustrate the procedure on 3 examples of different lengths. Results suggest that GAMs may be very useful both as a form of sensitivity analysis for checking the plausibility of assumptions about trend and as a primary data analysis strategy for testing treatment effects. We conclude with a discussion of some problems with GAMs and some future directions for research on the application of GAMs to SCDs. (c) 2015 APA, all rights reserved).

Disentangling forest change from forest inventory change: A case study from the US Interior West

Treesearch

Sara A. Goeking

2015-01-01

Long-term trends in forest attributes are typically assessed using strategic inventories such as the US Department of Agriculture (USDA) Forest Service’s Forest Inventory and Analysis (FIA) program. The implicit assumption of any trend analysis is that data are comparable over time. The 1998 Farm Bill tasked FIA with implementing nationally consistent protocols,...

Trends in Ph.D. Productivity and Diversity in Top-50 U.S. Chemistry Departments: An Institutional Analysis

ERIC Educational Resources Information Center

Laursen, Sandra L.; Weston, Timothy J.

2014-01-01

The education of doctoral chemists contributes to the chemical research enterprise and thus to innovation as an engine of the economy. This quantitative analysis describes trends in the production and diversity of chemistry Ph.D. degrees in the top-50 U.S. Ph.D.-granting departments in the past two decades. Time series data for individual…

STATISTICAL METHOD FOR DETECTION OF A TREND IN ATMOSPHERIC SULFATE

EPA Science Inventory

Daily atmospheric concentrations of sulfate collected in northeastern Pennsylvania are regressed against meteorological factors, ozone, and time in order to determine if a significant trend in sulfate can be detected. he data used in this analysis were collected during the Sulfat...

Epileptic seizure prediction by non-linear methods

DOEpatents

Hively, Lee M.; Clapp, Ned E.; Daw, C. Stuart; Lawkins, William F.

1999-01-01

Methods and apparatus for automatically predicting epileptic seizures monitor and analyze brain wave (EEG or MEG) signals. Steps include: acquiring the brain wave data from the patient; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis tools; obtaining time serial trends in the nonlinear measures; comparison of the trend to known seizure predictors; and providing notification that a seizure is forthcoming.

Identifying trends in sediment discharge from alterations in upstream land use

USGS Publications Warehouse

Parker, R.S.; Osterkamp, W.R.

1995-01-01

Environmental monitoring is a primary reason for collecting sediment data. One emphasis of this monitoring is identification of trends in suspended sediment discharge. A stochastic equation was used to generate time series of annual suspended sediment discharges using statistics from gaging stations with drainage areas between 1606 and 1 805 230 km2. Annual sediment discharge was increased linearly to yield a given increase at the end of a fixed period and trend statistics were computed for each simulation series using Kendal's tau (at 0.05 significance level). A parameter was calculated from two factors that control trend detection time: (a) the magnitude of change in sediment discharge, and (b) the natural variability of sediment discharge. In this analysis the detection of a trend at most stations is well over 100 years for a 20% increase in sediment discharge. Further research is needed to assess the sensitivity of detecting trends at sediment stations.

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

Ashouri, Hamed; Sorooshian, Soroosh; Hsu, Kuo-Lin

This study evaluates the performance of NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) precipitation product in reproducing the trend and distribution of extreme precipitation events. Utilizing the extreme value theory, time-invariant and time-variant extreme value distributions are developed to model the trends and changes in the patterns of extreme precipitation events over the contiguous United States during 1979-2010. The Climate Prediction Center (CPC)U.S.Unified gridded observation data are used as the observational dataset. The CPC analysis shows that the eastern and western parts of the United States are experiencing positive and negative trends in annual maxima, respectively. The continental-scalemore » patterns of change found in MERRA seem to reasonably mirror the observed patterns of change found in CPC. This is not previously expected, given the difficulty in constraining precipitation in reanalysis products. MERRA tends to overestimate the frequency at which the 99th percentile of precipitation is exceeded because this threshold tends to be lower in MERRA, making it easier to be exceeded. This feature is dominant during the summer months. MERRAtends to reproduce spatial patterns of the scale and location parameters of the generalized extreme value and generalized Pareto distributions. However, MERRA underestimates these parameters, particularly over the Gulf Coast states, leading to lower magnitudes in extreme precipitation events. Two issues in MERRA are identified: 1)MERRAshows a spurious negative trend in Nebraska andKansas, which ismost likely related to the changes in the satellite observing system over time that has apparently affected the water cycle in the central United States, and 2) the patterns of positive trend over theGulf Coast states and along the East Coast seem to be correlated with the tropical cyclones in these regions. The analysis of the trends in the seasonal precipitation extremes indicates that the hurricane and winter seasons are contributing the most to these trend patterns in the southeastern United States. The increasing annual trend simulated by MERRA in the Gulf Coast region is due to an incorrect trend in winter precipitation extremes.« less

Trends in pesticide concentrations in corn-belt streams, 1996-2006

USGS Publications Warehouse

Sullivan, Daniel J.; Vecchia, Aldo V.; Lorenz, David L.; Gilliom, Robert J.; Martin, Jeffrey D.

2009-01-01

Trends in the concentrations of commonly occurring pesticides in the Corn Belt of the United States were assessed, and the performance and application of several statistical methods for trend analysis were evaluated. Trends in the concentrations of 11 pesticides with sufficient data for trend assessment were assessed at up to 31 stream sites for two time periods: 1996–2002 and 2000–2006. Pesticides included in the trend analyses were atrazine, acetochlor, metolachlor, alachlor, cyanazine, EPTC, simazine, metribuzin, prometon, chlorpyrifos, and diazinon.The statistical methods applied and compared were (1) a modified version of the nonparametric seasonal Kendall test (SEAKEN), (2) a modified version of the Regional Kendall test, (3) a parametric regression model with seasonal wave (SEAWAVE), and (4) a version of SEAWAVE with adjustment for streamflow (SEAWAVE-Q). The SEAKEN test is a statistical hypothesis test for detecting monotonic trends in seasonal time-series data such as pesticide concentrations at a particular site. Trends across a region, represented by multiple sites, were evaluated using the regional seasonal Kendall test, which computes a test for an overall trend within a region by computing a score for each season at each site and adding the scores to compute the total for the region. The SEAWAVE model is a parametric regression model specifically designed for analyzing seasonal variability and trends in pesticide concentrations. The SEAWAVE-Q model accounts for the effect of changing flow conditions in order to separate changes caused by hydrologic trends from changes caused by other factors, such as pesticide use.There was broad, general agreement between unadjusted trends (no adjustment for streamflow effects) identified by the SEAKEN and SEAWAVE methods, including the regional seasonal Kendall test. Only about 10 percent of the paired comparisons between SEAKEN and SEAWAVE indicated a difference in the direction of trend, and none of these had differences significant at the 10-percent significance level. This consistency of results supports the validity and robustness of all three approaches as trend analysis tools. The SEAWAVE method is favored, however, because it has less restrictive data requirements, enabling analysis for more site/pesticide combinations, and can incorporate adjustment for streamflow (SEAWAVE-Q) with substantially fewer measurements than the flow-adjustment procedure used with SEAKEN.Analysis of flow-adjusted trends is preferable to analysis of non-adjusted trends for evaluating potential effects of changes in pesticide use or management practices because flow-adjusted trends account for the influence of flow-related variability.Analysis of flow-adjusted trends by SEAWAVE-Q showed that all of the pesticides assessed, except simazine and acetochlor, were dominated by varying degrees of concentration downtrends in one or both analysis periods. Atrazine, metolachlor, alachlor, cyanazine, EPTC, and metribuzin—all major corn herbicides, as well as prometon and chlorpyrifos, showed more prevalent concentration downtrends during 1996–2002 compared to 2000–2006. Diazinon had no clear trends during 1996–2002, but had predominantly downward trends during 2000–2006. Acetochlor trends were mixed during 1996–2002 and slightly upward during 2000–2006, but most of the trends were not statistically significant. Simazine concentrations trended upward at most sites during both 1996–2002 and 2000–2006.Comparison of concentration trends to agricultural-use trends indicated similarity in direction and magnitude for acetochlor, metolachlor, alachlor, cyanazine, EPTC, and metribuzin. Concentration downtrends for atrazine, chlorpyrifos, and diazinon were steeper than agricultural-use downtrends at some sites, indicating the possibility that agricultural management practices may have increasingly reduced transport to streams (particularly atrazine) or, for chlorpyrifos and diazinon, that nonagricultural uses declined substantially. Concentration uptrends for simazine generally were steeper than agricultural-use uptrends, indicating the possibility that nonagricultural uses of this herbicide increased during the study period.

Rainfall trends in the South Asian summer monsoon and its related large-scale dynamics with focus over Pakistan

NASA Astrophysics Data System (ADS)

Latif, M.; Syed, F. S.; Hannachi, A.

2017-06-01

The study of regional rainfall trends over South Asia is critically important for food security and economy, as both these factors largely depend on the availability of water. In this study, South Asian summer monsoon rainfall trends on seasonal and monthly (June-September) time scales have been investigated using three observational data sets. Our analysis identify a dipole-type structure in rainfall trends over the region north of the Indo-Pak subcontinent, with significant increasing trends over the core monsoon region of Pakistan and significant decreasing trends over the central-north India and adjacent areas. The dipole is also evident in monthly rainfall trend analyses, which is more prominent in July and August. We show, in particular, that the strengthening of northward moisture transport over the Arabian Sea is a likely reason for the significant positive trend of rainfall in the core monsoon region of Pakistan. In contrast, over the central-north India region, the rainfall trends are significantly decreasing due to the weakening of northward moisture transport over the Bay of Bengal. The leading empirical orthogonal functions clearly show the strengthening (weakening) patterns of vertically integrated moisture transport over the Arabian Sea (Bay of Bengal) in seasonal and monthly interannual time scales. The regression analysis between the principal components and rainfall confirm the dipole pattern over the region. Our results also suggest that the extra-tropical phenomena could influence the mean monsoon rainfall trends over Pakistan by enhancing the cross-equatorial flow of moisture into the Arabian Sea.

Age-period-cohort analysis of suicides among Japanese 1950-2003: a Bayesian cohort model analysis.

PubMed

Ooe, Yosuke; Ohno, Yuko; Nakamura, Takashi

2009-07-01

The suicide rate in Japan is one of the highest in the world and presents us with a considerable challenge. Demographic statistics show that the number of suicides is on the rise, and at roughly 30,000 people per year have committed suicide since 1998. Suicide trends are not only related to economic boom and bust but also to certain generations and age groups. During the 1950s, there was a remarkably high suicide rate among people in their 20s, and this cohort was identical to that of the middle-age generation in the 1980s. It is important to separately understand both the trend of suicide rates and the numbers analyzed to determine the different factors that influence suicide. These include age, time period, cohort, interaction between age and time period, and changes in population composition. We performed an age-period-cohort analysis of annual trends of suicide rates by age group in Japan using a Bayesian cohort model. With the help of the Nakamura method, we have been able to break down the effects of age, time period, cohort, and the age-by-period interaction. The cohort comprised of people born in the 1930s demonstrated a relatively high suicide rate. Men currently in their 50s also belong to a high suicide rate cohort. Regarding the period effect, business cycles and by-period interaction effect, it became apparent that the high suicide rate among young adults in their early 20s around 1960 was slowing, especially among men. Instead, there was an obvious recent trend for men in their late 50s to have the highest suicide rate. This study confirmed that age-period-cohort analysis can describe these trends of suicide mortality of the Japanese.

Analysis of geographical disparities in temporal trends of health outcomes using space-time joinpoint regression

NASA Astrophysics Data System (ADS)

Goovaerts, Pierre

2013-06-01

Analyzing temporal trends in health outcomes can provide a more comprehensive picture of the burden of a disease like cancer and generate new insights about the impact of various interventions. In the United States such an analysis is increasingly conducted using joinpoint regression outside a spatial framework, which overlooks the existence of significant variation among U.S. counties and states with regard to the incidence of cancer. This paper presents several innovative ways to account for space in joinpoint regression: (1) prior filtering of noise in the data by binomial kriging and use of the kriging variance as measure of reliability in weighted least-square regression, (2) detection of significant boundaries between adjacent counties based on tests of parallelism of time trends and confidence intervals of annual percent change of rates, and (3) creation of spatially compact groups of counties with similar temporal trends through the application of hierarchical cluster analysis to the results of boundary analysis. The approach is illustrated using time series of proportions of prostate cancer late-stage cases diagnosed yearly in every county of Florida since 1980s. The annual percent change (APC) in late-stage diagnosis and the onset years for significant declines vary greatly across Florida. Most counties with non-significant average APC are located in the north-western part of Florida, known as the Panhandle, which is more rural than other parts of Florida. The number of significant boundaries peaked in the early 1990s when prostate-specific antigen (PSA) test became widely available, a temporal trend that suggests the existence of geographical disparities in the implementation and/or impact of the new screening procedure, in particular as it began available.

Analysis of reference evapotranspiration (ET0) trends under climate change in Bangladesh using observed and CMIP5 data sets

NASA Astrophysics Data System (ADS)

Rahman, Mohammad Atiqur; Yunsheng, Lou; Sultana, Nahid; Ongoma, Victor

2018-03-01

ET0 is an important hydro-meteorological phenomenon, which is influenced by changing climate like other climatic parameters. This study investigates the present and future trends of ET0 in Bangladesh using 39 years' historical and downscaled CMIP5 daily climatic data for the twenty-first century. Statistical Downscaling Model (SDSM) was used to downscale the climate data required to calculate ET0. Penman-Monteith formula was applied in ET0 calculation for both the historical and modelled data. To analyse ET0 trends and trend changing patterns, modified Mann-Kendall and Sequential Mann-Kendall tests were, respectively, done. Spatial variations of ET0 trends are presented by inverse distance weighting interpolation using ArcGIS 10.2.2. Results show that RCP8.5 (2061-2099) will experience the highest amount of ET0 totals in comparison to the historical and all other scenarios in the same time span of 39 years. Though significant positive trends were observed in the mid and last months of year from month-wise trend analysis of representative concentration pathways, significant negative trends were also found for some months using historical data in similar analysis. From long-term annual trend analysis, it was found that major part of the country represents decreasing trends using historical data, but increasing trends were observed for modelled data. Theil-Sen estimations of ET0 trends in the study depict a good consistency with the Mann-Kendall test results. The findings of the study would contribute in irrigation water management and planning of the country and also in furthering the climate change study using modelled data in the context of Bangladesh.

Analysis of Water-Quality Trends for Selected Streams in the Water Chemistry Monitoring Program, Michigan, 1998-2005

USGS Publications Warehouse

Hoard, C.J.; Fuller, Lori M.; Fogarty, Lisa R.

2009-01-01

In 1998, the Michigan Department of Environmental Quality and the U.S. Geological Survey began a long-term monitoring program to evaluate the water quality of most watersheds in Michigan. Major goals of this Water-Chemistry Monitoring Program were to identify streams exceeding or not meeting State or Federal water-quality standards and to assess if constituent concentrations reflecting water quality in these streams were increasing or decreasing over time. As part of this program, water-quality data collected from 1998 to 2005 were analyzed to identify potential trends. Sixteen water-quality constituents were analyzed at 31 sites across Michigan, 28 of which had sufficient data to analyze for trends. Trend analysis on the various water-quality data was done using the uncensored Seasonal Kendall test within the computer program ESTREND. The most prevalent trend detected throughout the state was for chloride. Chloride trends were detected at 8 of the 28 sites; trends at 7 sites were increasing and the trend at 1 site was decreasing. Although no trends were detected for various nitrogen species or phosphorus, these constituents were detected at levels greater than the U.S. Environmental Protection Agency recommendations for nutrients in water. The results of the trend analysis will help to establish a baseline to evaluate future changes in water quality in Michigan streams.

Analysis options for estimating status and trends in long-term monitoring

USGS Publications Warehouse

Bart, Jonathan; Beyer, Hawthorne L.

2012-01-01

This chapter describes methods for estimating long-term trends in ecological parameters. Other chapters in this volume discuss more advanced methods for analyzing monitoring data, but these methods may be relatively inaccessible to some readers. Therefore, this chapter provides an introduction to trend analysis for managers and biologists while also discussing general issues relevant to trend assessment in any long-term monitoring program. For simplicity, we focus on temporal trends in population size across years. We refer to the survey results for each year as the “annual means” (e.g. mean per transect, per plot, per time period). The methods apply with little or no modification, however, to formal estimates of population size, other temporal units (e.g. a month), to spatial or other dimensions such as elevation or a north–south gradient, and to other quantities such as chemical or geological parameters. The chapter primarily discusses methods for estimating population-wide parameters rather than studying variation in trend within the population, which can be examined using methods presented in other chapters (e.g. Chapters 7, 12, 20). We begin by reviewing key concepts related to trend analysis. We then describe how to evaluate potential bias in trend estimates. An overview of the statistical models used to quantify trends is then presented. We conclude by showing ways to estimate trends using simple methods that can be implemented with spreadsheets.

A trend analysis of surgical operations under a global payment system in Tehran, Iran (2005–2015)

PubMed Central

Goudari, Faranak Behzadi; Rashidian, Arash; Arab, Mohammad; Mahmoudi, Mahmood

2018-01-01

Background Global payment system is a first example of per-case payment system that contains 60 commonly used surgical operations for which payment is based on the average cost per case in Iran. Objective The aim of the study was to determine the amount of reduction, increase or no change in the trend of global operations. Methods In this retrospective longitudinal study, data on the 60 primary global surgery codes was gathered from Tehran Health Insurance Organization within the ten-year period of 2005–2015 separately, for each month. Out of 60 surgery codes, only acceptable data for 46 codes were available based on the insurance documents sent by medical centers. A quantitative analysis of time series through Regression Analysis Model using STATA software v.11 was performed. Results Some global surgery codes had an upward trend and some were downwards. Of N Codes, N83, N20, N28, N63, and N93 had an upward trend (p<0.05) and N32, N43, N81 and N90 showed a significant downward trend (p<0.05). Similarly, all H Codes except for H18 had a significant upward trend (p<0.000). As such, K Codes including K45, K56 and K81 had an increasing movement. S Codes also experienced both increasing and decreasing trends. However, none of the O Codes changed according to time. Other global surgical codes like C61, E07, M51, L60, J98 (p<0.000), I84 (p<0.031) and I86 (p<0.000) shown upward and downward trends. Total global surgeries trend was significantly upwards (B=24.26109, p<0.000). Conclusion The varying trend of global surgeries can partly reflect the behavior of service providers in order to increase their profits and minimize their costs. PMID:29765576

Changes in Land Use Intensity Within the Don and Dnieper River Basins Following the Collapse of the Soviet Union as Revealed by Spatio-temporal Trend Analysis

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Henebry, G.

2007-12-01

We analyzed changes in trends of land surface phenology (LSP) within two major river basins in Western Eurasia. The basins of Don and Dnieper Rivers extend over 862,000 ha and include 17% of the impounded water surface area in the former Soviet Union. Major changes in agricultural practices occurring after 1991 led to some time drastic reductions in the cultivated area receiving fertilizers and the amount of water consumed for irrigation in addition to other macro-indicators of agricultural sector land use intensity. Image time series analysis can localize the extent, direction, and intensity of changes during the 1990s. Using vegetation index data from the AVHRR PAL and GIMMS datasets from 1982-1988 (Soviet period) and 1995-2000 (post-Soviet period) coupled with contemporary land cover maps from MODIS, we identified the spatial extent of temporal trends and assess their significance using seasonal Mann-Kendall tests adjusted for first-order autocorrelation. Roughly 90% of croplands and forested land in Dnieper Basin exhibited no significant trends during the Soviet period. The Don Basin had more significant positive trends during the Soviet period than the Dnieper Basin. There was a substantial disagreement between datasets on the extent of significant positive trends in Don croplands (35% for GIMMS vs. 8% for PAL) and in Don forests during Soviet period (38% for GIMMS vs. 27% for PAL). Although very little area in either basins showed significant negative trends during the Soviet period, substantial areas fell under significant negative trends during the post-Soviet period. We also found major disagreement on extent of significant negative trends in Don forests during post-Soviet period (6% for GIMMS vs. 24% for PAL). Even though, there are some significant disagreements between the datasets, there is no evidence of a consistent bias in the change analysis. Changes in irrigation water use may account for some of the changes in trend direction.

Letters from a suicide: Van Gogh and his sister.

PubMed

Lester, David

2010-04-01

An analysis of trends over a 3-yr. period in the letters of Vincent Van Gogh to his sister as the time of his suicide approached identified 8 trends, including an increase in words concerned with anxiety and words concerned with the past.

Analysis of the eight-year trend in ozone depletion from empirical models of solar backscattered ultraviolet instrument degradation

NASA Technical Reports Server (NTRS)

Herman, J. R.; Hudson, R. D.; Serafino, G.

1990-01-01

Arguments are presented showing that the basic empirical model of the solar backscatter UV (SBUV) instrument degradation used by Cebula et al. (1988) in their analysis of the SBUV data is likely to lead to an incorrect estimate of the ozone trend. A correction factor is given as a function of time and altitude that brings the SBUV data into approximate agreement with the SAGE, SME, and Dobson network ozone trends. It is suggested that the currently archived SBUV ozone data should be used with caution for periods of analysis exceeding 1 yr, since it is likely that the yearly decreases contained in the archived data are too large.

A Content Analysis of Quantitative Research in Journal of Marital and Family Therapy: A 10-Year Review.

PubMed

Parker, Elizabeth O; Chang, Jennifer; Thomas, Volker

2016-01-01

We examined the trends of quantitative research over the past 10 years in the Journal of Marital and Family Therapy (JMFT). Specifically, within the JMFT, we investigated the types and trends of research design and statistical analysis within the quantitative research that was published in JMFT from 2005 to 2014. We found that while the amount of peer-reviewed articles have increased over time, the percentage of quantitative research has remained constant. We discussed the types and trends of statistical analysis and the implications for clinical work and training programs in the field of marriage and family therapy. © 2016 American Association for Marriage and Family Therapy.

The National Water-Quality Assessment Program of the United States: Strategies for Monitoring Trends and Results from the First Two Decades of Study: 1991-2011

NASA Astrophysics Data System (ADS)

Lindsey, B.; McMahon, P.; Rupert, M.; Tesoriero, J.; Starn, J.; Anning, D.; Green, C.

2012-04-01

The U.S. Geological Survey National Water-Quality Assessment (NAWQA) Program was implemented in 1991 to provide long-term, consistent, and comparable information on the quality of surface and groundwater resources of the United States. Findings are used to support national, regional, state, and local information needs with respect to water quality. The three main goals of the program are to 1) assess the condition of the nation's streams, rivers, groundwater, and aquatic systems; 2) assess how conditions are changing over time; and 3) determine how natural features and human activities affect these conditions, and where those effects are most pronounced. As data collection progressed into the second decade, the emphasis of the interpretation of the data has shifted from primarily understanding status, to evaluation of trends. The program has conducted national and regional evaluations of change in the quality of water in streams, rivers, groundwater, and health of aquatic systems. Evaluating trends in environmental systems requires complex analytical and statistical methods, and a periodic re-evaluation of the monitoring methods used to collect these data. Examples given herein summarize the lessons learned from the evaluation of changes in water quality during the past two decades with an emphasis on the finding with respect to groundwater. The analysis of trends in groundwater is based on 56 well networks located in 22 principal aquifers of the United States. Analysis has focused on 3 approaches: 1) a statistical analysis of results of sampling over various time scales, 2) studies of factors affecting trends in groundwater quality, and 3) use of models to simulate groundwater trends and forecast future trends. Data collection for analysis of changes in groundwater-quality has focused on decadal resampling of wells. Understanding the trends in groundwater quality and the factors affecting those trends has been conducted using quarterly sampling, biennial sampling, and more recently continuous monitoring of selected parameters in a small number of wells. Models such as MODFLOW have been used for simulation and forecasting of future trends. Important outcomes from the groundwater-trends studies include issues involving statistics, sampling frequency, changes in laboratory analytical methods over time, the need for groundwater age-dating information, the value of understanding geochemical conditions and contaminant degradation, the need to understand groundwater-surface water interaction, and the value of modeling in understanding trends and forecasting potential future conditions. Statistically significant increases in chloride, dissolved solids, and nitrate concentrations were found in a large number of well networks over the first decadal sampling period. Statistically significant decreases of chloride, dissolved solids, and nitrate concentrations were found in a very small number of networks. Trends in surface-water are analyzed within 8 large major river basins within the United States with a focus on issues of regional importance. Examples of regional surface-water issues include an analysis of trends in dissolved solids in the Southeastern United States, trends in pesticides in the north-central United States, and trends in nitrate in the Mississippi River Basin. Evaluations of ecological indicators of water quality include temporal changes in stream habitat, and aquatic-invertebrate and fish assemblages.

Trends in public perceptions and preferences on energy and environmental policy

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

Farhar, B.C.

1993-02-01

This report presents selected results from a secondary analysis of public opinion surveys, taken at the national and state/local levels, relevant to energy and environmental policy choices. The data base used in the analysis includes about 2000 items from nearly 600 separate surveys conducted between 1979 and 1992. Answers to word-for-word questions were traced over time, permitting trend analysis. Patterns of response were also identified for findings from similarly worded survey items. The analysis identifies changes in public opinion concerning energy during the past 10 to 15 years.

Tropospheric temperature climatology and trends observed over the Middle East

NASA Astrophysics Data System (ADS)

Basha, Ghouse; Marpu, P. R.; Ouarda, T. B. M. J.

2015-10-01

In this study, we report for the first time, the upper air temperature climatology, and trends over the Middle East, which seem to be significantly affected by the changes associated with hot summer and low precipitation. Long term (1985-2012) radiosonde data from 12 stations are used to derive the mean temperature climatology and vertical trends. The study was performed by analyzing the data at different latitudes. The vertical profiles of air temperature show distinct behavior in terms of vertical and seasonal variability at different latitudes. The seasonal cycle of temperature at the 100 hPa, however, shows an opposite pattern compared to the 200 hPa levels. The temperature at 100 hPa shows a maximum during winter and minimum in summer. Spectral analysis shows that the annual cycle is dominant in comparison with the semiannual cycle. The time-series of temperature data was analyzed using the Bayesian change point analysis and cumulative sum method to investigate the changes in temperature trends. Temperature shows a clear change point during the year 1999 at all stations. Further, Modified Mann-Kendall test was applied to study the vertical trend, and analysis shows statistically significant lower tropospheric warming and cooling in upper troposphere after the year 1999. In general, the magnitude of the trend decreases with altitude in the troposphere. In all the latitude bands in lower troposphere, significant warming is observed, whereas at higher altitudes cooling is noticed based on 28 years temperature observations over the Middle East.

Epileptic seizure prediction by non-linear methods

DOEpatents

Hively, L.M.; Clapp, N.E.; Day, C.S.; Lawkins, W.F.

1999-01-12

This research discloses methods and apparatus for automatically predicting epileptic seizures monitor and analyze brain wave (EEG or MEG) signals. Steps include: acquiring the brain wave data from the patient; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis tools; obtaining time serial trends in the nonlinear measures; comparison of the trend to known seizure predictors; and providing notification that a seizure is forthcoming. 76 figs.

Evaluation of CMIP5 Ability to Reproduce 20th Century Regional Trends in Surface Air Temperature and Precipitation over CONUS

NASA Astrophysics Data System (ADS)

Lee, J.; Waliser, D. E.; Lee, H.; Loikith, P. C.; Kunkel, K.

2017-12-01

Monitoring temporal changes in key climate variables, such as surface air temperature and precipitation, is an integral part of the ongoing efforts of the United States National Climate Assessment (NCA). Climate models participating in CMIP5 provide future trends for four different emissions scenarios. In order to have confidence in the future projections of surface air temperature and precipitation, it is crucial to evaluate the ability of CMIP5 models to reproduce observed trends for three different time periods (1895-1939, 1940-1979, and 1980-2005). Towards this goal, trends in surface air temperature and precipitation obtained from the NOAA nClimGrid 5 km gridded station observation-based product are compared during all three time periods to the 206 CMIP5 historical simulations from 48 unique GCMs and their multi-model ensemble (MME) for NCA-defined climate regions during summer (JJA) and winter (DJF). This evaluation quantitatively examines the biases of simulated trends of the spatially averaged temperature and precipitation in the NCA climate regions. The CMIP5 MME reproduces historical surface air temperature trends for JJA for all time period and all regions, except the Northern Great Plains from 1895-1939 and Southeast during 1980-2005. Likewise, for DJF, the MME reproduces historical surface air temperature trends across all time periods over all regions except the Southeast from 1895-1939 and the Midwest during 1940-1979. The Regional Climate Model Evaluation System (RCMES), an analysis tool which supports the NCA by providing access to data and tools for regional climate model validation, facilitates the comparisons between the models and observation. The RCMES Toolkit is designed to assist in the analysis of climate variables and the procedure of the evaluation of climate projection models to support the decision-making processes. This tool is used in conjunction with the above analysis and results will be presented to demonstrate its capability to access observation and model datasets, calculate evaluation metrics, and visualize the results. Several other examples of the RCMES capabilities can be found at https://rcmes.jpl.nasa.gov.

Adjustment of pesticide concentrations for temporal changes in analytical recovery, 1992–2010

USGS Publications Warehouse

Martin, Jeffrey D.; Eberle, Michael

2011-01-01

Recovery is the proportion of a target analyte that is quantified by an analytical method and is a primary indicator of the analytical bias of a measurement. Recovery is measured by analysis of quality-control (QC) water samples that have known amounts of target analytes added ("spiked" QC samples). For pesticides, recovery is the measured amount of pesticide in the spiked QC sample expressed as a percentage of the amount spiked, ideally 100 percent. Temporal changes in recovery have the potential to adversely affect time-trend analysis of pesticide concentrations by introducing trends in apparent environmental concentrations that are caused by trends in performance of the analytical method rather than by trends in pesticide use or other environmental conditions. This report presents data and models related to the recovery of 44 pesticides and 8 pesticide degradates (hereafter referred to as "pesticides") that were selected for a national analysis of time trends in pesticide concentrations in streams. Water samples were analyzed for these pesticides from 1992 through 2010 by gas chromatography/mass spectrometry. Recovery was measured by analysis of pesticide-spiked QC water samples. Models of recovery, based on robust, locally weighted scatterplot smooths (lowess smooths) of matrix spikes, were developed separately for groundwater and stream-water samples. The models of recovery can be used to adjust concentrations of pesticides measured in groundwater or stream-water samples to 100 percent recovery to compensate for temporal changes in the performance (bias) of the analytical method.

Global Search Trends of Oral Problems using Google Trends from 2004 to 2016: An Exploratory Analysis.

PubMed

Patthi, Basavaraj; Kumar, Jishnu Krishna; Singla, Ashish; Gupta, Ritu; Prasad, Monika; Ali, Irfan; Dhama, Kuldeep; Niraj, Lav Kumar

2017-09-01

Oral diseases are pandemic cause of morbidity with widespread geographic distribution. This technology based era has brought about easy knowledge transfer than traditional dependency on information obtained from family doctors. Hence, harvesting this system of trends can aid in oral disease quantification. To conduct an exploratory analysis of the changes in internet search volumes of oral diseases by using Google Trends © (GT © ). GT © were utilized to provide real world facts based on search terms related to categories, interest by region and interest over time. Time period chosen was from January 2004 to December 2016. Five different search terms were explored and compared based on the highest relative search volumes along with comma separated value files to obtain an insight into highest search traffic. The search volume measured over the time span noted the term "Dental caries" to be the most searched in Japan, "Gingivitis" in Jordan, "Oral Cancer" in Taiwan, "No Teeth" in Australia, "HIV symptoms" in Zimbabwe, "Broken Teeth" in United Kingdom, "Cleft palate" in Philippines, "Toothache" in Indonesia and the comparison of top five searched terms provided the "Gingivitis" with highest search volume. The results from the present study offers an insight into a competent tool that can analyse and compare oral diseases over time. The trend research platform can be used on emerging diseases and their drift in geographic population with great acumen. This tool can be utilized in forecasting, modulating marketing strategies and planning disability limitation techniques.

Operating Room Efficiency before and after Entrance in a Benchmarking Program for Surgical Process Data.

PubMed

Pedron, Sara; Winter, Vera; Oppel, Eva-Maria; Bialas, Enno

2017-08-23

Operating room (OR) efficiency continues to be a high priority for hospitals. In this context the concept of benchmarking has gained increasing importance as a means to improve OR performance. The aim of this study was to investigate whether and how participation in a benchmarking and reporting program for surgical process data was associated with a change in OR efficiency, measured through raw utilization, turnover times, and first-case tardiness. The main analysis is based on panel data from 202 surgical departments in German hospitals, which were derived from the largest database for surgical process data in Germany. Panel regression modelling was applied. Results revealed no clear and univocal trend of participation in a benchmarking and reporting program for surgical process data. The largest trend was observed for first-case tardiness. In contrast to expectations, turnover times showed a generally increasing trend during participation. For raw utilization no clear and statistically significant trend could be evidenced. Subgroup analyses revealed differences in effects across different hospital types and department specialties. Participation in a benchmarking and reporting program and thus the availability of reliable, timely and detailed analysis tools to support the OR management seemed to be correlated especially with an increase in the timeliness of staff members regarding first-case starts. The increasing trend in turnover time revealed the absence of effective strategies to improve this aspect of OR efficiency in German hospitals and could have meaningful consequences for the medium- and long-run capacity planning in the OR.

Upward trend in vehicle-miles resumed during 2009 : a time series analysis

DOT National Transportation Integrated Search

2010-04-01

After a 2-year interruption to a long-term upward trend, the : number of vehicle-miles traveled (VMT) on the Nations highways : appears to have resumed a pattern of upward growth in : 2009. While VMT rises and falls seasonally, the years 2007 : an...

Modeling the Trajectory of Analgesic Demand Over Time After Total Knee Arthroplasty Using the Latent Curve Analysis.

PubMed

Lo, Po-Han; Tsou, Mei-Yung; Chang, Kuang-Yi

2015-09-01

Patient-controlled epidural analgesia (PCEA) is commonly used for pain relief after total knee arthroplasty (TKA). This study aimed to model the trajectory of analgesic demand over time after TKA and explore its influential factors using latent curve analysis. Data were retrospectively collected from 916 patients receiving unilateral or bilateral TKA and postoperative PCEA. PCEA demands during 12-hour intervals for 48 hours were directly retrieved from infusion pumps. Potentially influential factors of PCEA demand, including age, height, weight, body mass index, sex, and infusion pump settings, were also collected. A latent curve analysis with 2 latent variables, the intercept (baseline) and slope (trend), was applied to model the changes in PCEA demand over time. The effects of influential factors on these 2 latent variables were estimated to examine how these factors interacted with time to alter the trajectory of PCEA demand over time. On average, the difference in analgesic demand between the first and second 12-hour intervals was only 15% of that between the first and third 12-hour intervals. No significant difference in PCEA demand was noted between the third and fourth 12-hour intervals. Aging tended to decrease the baseline PCEA demand but body mass index and infusion rate were positively correlated with the baseline. Only sex significantly affected the trend parameter and male individuals tended to have a smoother decreasing trend of analgesic demands over time. Patients receiving bilateral procedures did not consume more analgesics than their unilateral counterparts. Goodness of fit analysis indicated acceptable model fit to the observed data. Latent curve analysis provided valuable information about how analgesic demand after TKA changed over time and how patient characteristics affected its trajectory.

Trend analysis of time-series phenology of North America derived from satellite data

USGS Publications Warehouse

Reed, B.C.

2006-01-01

Remote sensing information has been used in studies of the seasonal dynamics (phenology) of the land surface since the 1980s. While our understanding of remote sensing phenology is still in development, it is regarded as a key to understanding land-surface processes over large areas. Phenologic metrics, including start of season, end of season, duration of season, and seasonally integrated greenness, were derived from 8 km advanced very high resolution radiometer (AVHRR) data over North America spanning the years 1982-2003. Trend analysis was performed on annual summaries of the metrics to determine areas with increasing or decreasing growing season trends for the time period under study. Results show a trend toward earlier starts of season in limited areas of the mixed boreal forest, and a trend toward later end of season in well-defined areas of New England and southeastern Canada. Results in Saskatchewan, Canada, include a trend toward longer duration of season over a well-defined area, principally as a result of regional changes in land use practices. Changing seasonality appears to be an integrated response to a complex of factors, including climate change, but also, in many places, changes in land use practices. Copyright ?? 2006 by V. H. Winston & Son, Inc. All rights reserved.

Trends and Solar Cycle Effects in Temperature Versus Altitude From the Halogen Occultation Experiment for the Mesosphere and Upper Stratosphere

NASA Technical Reports Server (NTRS)

Remsberg, Ellis E.

2009-01-01

Fourteen-year time series of mesospheric and upper stratospheric temperatures from the Halogen Occultation Experiment (HALOE) are analyzed and reported. The data have been binned according to ten-degree wide latitude zones from 40S to 40N and at 10 altitudes from 43 to 80 km-a total of 90 separate time series. Multiple linear regression (MLR) analysis techniques have been applied to those time series. This study focuses on resolving their 11-yr solar cycle (or SC-like) responses and their linear trend terms. Findings for T(z) from HALOE are compared directly with published results from ground-based Rayleigh lidar and rocketsonde measurements. SC-like responses from HALOE compare well with those from lidar station data at low latitudes. The cooling trends from HALOE also agree reasonably well with those from the lidar data for the concurrent decade. Cooling trends of the lower mesosphere from HALOE are not as large as those from rocketsondes and from lidar station time series of the previous two decades, presumably because the changes in the upper stratospheric ozone were near zero during the HALOE time period and did not affect those trends.

Persistence of space radiation induced cytogenetic damage in the blood lymphocytes of astronauts.

PubMed

George, K; Chappell, L J; Cucinotta, F A

2010-08-14

Cytogenetic damage was assessed in blood lymphocytes from 16 astronauts before and after they participated in long-duration space missions of 3 months or more. The frequency of chromosome damage was measured by fluorescence in situ hybridization (FISH) chromosome painting before flight and at various intervals from a few days to many months after return from the mission. For all individuals, the frequency of chromosome exchanges measured within a month of return from space was higher than their preflight yield. However, some individuals showed a temporal decline in chromosome damage with time after flight. Statistical analysis using combined data for all astronauts indicated a significant overall decreasing trend in total chromosome exchanges with time after flight, although this trend was not seen for all astronauts and the yield of chromosome damage in some individuals actually increased with time after flight. The decreasing trend in total exchanges was slightly more significant when statistical analysis was restricted to data collected more than 220 days after return from flight. When analysis was restricted to data collected within 220 days of return from the mission there was no relationship between total exchanges and time. Translocation yields varied more between astronauts and there was only a slight non-significant decrease with time after flight that was similar for both later and earlier sampling times. Copyright (c) 2010. Published by Elsevier B.V.

Nonlinear analysis of gait kinematics to track changes in oxygen consumption in prolonged load carriage walking: a pilot study.

PubMed

Schiffman, Jeffrey M; Chelidze, David; Adams, Albert; Segala, David B; Hasselquist, Leif

2009-09-18

Linking human mechanical work to physiological work for the purpose of developing a model of physical fatigue is a complex problem that cannot be solved easily by conventional biomechanical analysis. The purpose of the study was to determine if two nonlinear analysis methods can address the fundamental issue of utilizing kinematic data to track oxygen consumption from a prolonged walking trial: we evaluated the effectiveness of dynamical systems and fractal analysis in this study. Further, we selected, oxygen consumption as a measure to represent the underlying physiological measure of fatigue. Three male US Army Soldier volunteers (means: 23.3 yr; 1.80 m; 77.3 kg) walked for 120 min at 1.34 m/s with a 40-kg load on a level treadmill. Gait kinematic data and oxygen consumption (VO(2)) data were collected over the 120-min period. For the fractal analysis, utilizing stride interval data, we calculated fractal dimension. For the dynamical systems analysis, kinematic angle time series were used to estimate phase space warping based features at uniform time intervals: smooth orthogonal decomposition (SOD) was used to extract slowly time-varying trends from these features. Estimated fractal dimensions showed no apparent trend or correlation with independently measured VO(2). While inter-individual difference did exist in the VO(2) data, dominant SOD time trends tracked and correlated with the VO(2) for all volunteers. Thus, dynamical systems analysis using gait kinematics may be suitable to develop a model to predict physiologic fatigue based on biomechanical work.

Reevaluation of Stratospheric Ozone Trends From SAGE II Data Using a Simultaneous Temporal and Spatial Analysis

NASA Technical Reports Server (NTRS)

Damadeo, R. P.; Zawodny, J. M.; Thomason, L. W.

2014-01-01

This paper details a new method of regression for sparsely sampled data sets for use with time-series analysis, in particular the Stratospheric Aerosol and Gas Experiment (SAGE) II ozone data set. Non-uniform spatial, temporal, and diurnal sampling present in the data set result in biased values for the long-term trend if not accounted for. This new method is performed close to the native resolution of measurements and is a simultaneous temporal and spatial analysis that accounts for potential diurnal ozone variation. Results show biases, introduced by the way data is prepared for use with traditional methods, can be as high as 10%. Derived long-term changes show declines in ozone similar to other studies but very different trends in the presumed recovery period, with differences up to 2% per decade. The regression model allows for a variable turnaround time and reveals a hemispheric asymmetry in derived trends in the middle to upper stratosphere. Similar methodology is also applied to SAGE II aerosol optical depth data to create a new volcanic proxy that covers the SAGE II mission period. Ultimately this technique may be extensible towards the inclusion of multiple data sets without the need for homogenization.

Trends in Average Living Children at the Time of Terminal Contraception: A Time Series Analysis Over 27 Years Using ARIMA (p, d, q) Nonseasonal Model.

PubMed

Mumbare, Sachin S; Gosavi, Shriram; Almale, Balaji; Patil, Aruna; Dhakane, Supriya; Kadu, Aniruddha

2014-10-01

India's National Family Welfare Programme is dominated by sterilization, particularly tubectomy. Sterilization, being a terminal method of contraception, decides the final number of children for that couple. Many studies have shown the declining trend in the average number of living children at the time of sterilization over a short period of time. So this study was planned to do time series analysis of the average children at the time of terminal contraception, to do forecasting till 2020 for the same and to compare the rates of change in various subgroups of the population. Data was preprocessed in MS Access 2007 by creating and running SQL queries. After testing stationarity of every series with augmented Dickey-Fuller test, time series analysis and forecasting was done using best-fit Box-Jenkins ARIMA (p, d, q) nonseasonal model. To compare the rates of change of average children in various subgroups, at sterilization, analysis of covariance (ANCOVA) was applied. Forecasting showed that the replacement level of 2.1 total fertility rate (TFR) will be achieved in 2018 for couples opting for sterilization. The same will be achieved in 2020, 2016, 2018, and 2019 for rural area, urban area, Hindu couples, and Buddhist couples, respectively. It will not be achieved till 2020 in Muslim couples. Every stratum of population showed the declining trend. The decline for male children and in rural area was significantly faster than the decline for female children and in urban area, respectively. The decline was not significantly different in Hindu, Muslim, and Buddhist couples.

Projection of landfill stabilization period by time series analysis of leachate quality and transformation trends of VOCs.

PubMed

Sizirici, Banu; Tansel, Berrin

2010-01-01

The purpose of this study was to evaluate suitability of using the time series analysis for selected leachate quantity and quality parameters to forecast the duration of post closure period of a closed landfill. Selected leachate quality parameters (i.e., sodium, chloride, iron, bicarbonate, total dissolved solids (TDS), and ammonium as N) and volatile organic compounds (VOCs) (i.e., vinyl chloride, 1,4-dichlorobenzene, chlorobenzene, benzene, toluene, ethyl benzene, xylenes, total BTEX) were analyzed by the time series multiplicative decomposition model to estimate the projected levels of the parameters. These parameters were selected based on their detection levels and consistency of detection in leachate samples. In addition, VOCs detected in leachate and their chemical transformations were considered in view of the decomposition stage of the landfill. Projected leachate quality trends were analyzed and compared with the maximum contaminant level (MCL) for the respective parameters. Conditions that lead to specific trends (i.e., increasing, decreasing, or steady) and interactions of leachate quality parameters were evaluated. Decreasing trends were projected for leachate quantity, concentrations of sodium, chloride, TDS, ammonia as N, vinyl chloride, 1,4-dichlorobenzene, benzene, toluene, ethyl benzene, xylenes, and total BTEX. Increasing trends were projected for concentrations of iron, bicarbonate, and chlorobenzene. Anaerobic conditions in landfill provide favorable conditions for corrosion of iron resulting in higher concentrations over time. Bicarbonate formation as a byproduct of bacterial respiration during waste decomposition and the lime rock cap system of the landfill contribute to the increasing levels of bicarbonate in leachate. Chlorobenzene is produced during anaerobic biodegradation of 1,4-dichlorobenzene, hence, the increasing trend of chlorobenzene may be due to the declining trend of 1,4-dichlorobenzene. The time series multiplicative decomposition model in general provides an adequate forecast for future planning purposes for the parameters monitored in leachate. The model projections for 1,4-dichlorobenzene were relatively less accurate in comparison to the projections for vinyl chloride and chlorobenzene. Based on the trends observed, future monitoring needs for the selected leachate parameters were identified.

Prevalence of smoking in movies as perceived by teenagers longitudinal trends and predictors.

PubMed

Choi, Kelvin; Forster, Jean L; Erickson, Darin J; Lazovich, Deann; Southwell, Brian G

2011-08-01

Smoking in movies is prevalent. However, use of content analysis to describe trends in smoking in movies has provided mixed results and has not tapped what adolescents actually perceive. To assess the prospective trends in the prevalence of smoking in movies as perceived by teenagers and identify predictors associated with these trends. Using data from the Minnesota Adolescent Community Cohort Study collected during 2000-2006 when participants were aged between 12 and 18 years (N=4735), latent variable growth models were employed to describe the longitudinal trends in the perceived prevalence of smoking in movies using a four-level scale (never to most of the time) measured every 6 months, and examined associations between these trends and demographic, smoking-related attitudinal and socio-environmental predictors. Analysis was conducted in 2009. At baseline, about 50% of participants reported seeing smoking in movies some of the time, and another 36% reported most of the time. The prevalence of smoking in movies as perceived by teenagers declined over time, and the decline was steeper in those who were aged 14-16 years than those who were younger at baseline (p≤0.05). Despite the decline, teenagers still reported seeing smoking in movies some of the time. Teenagers who reported more close friends who smoked also reported a higher prevalence of smoking in movies at baseline (regression coefficients=0.04-0.18, p<0.01). Teenagers' perception of the prevalence of smoking in movies declined over time, which may be attributable to changes made by the movie industry. Despite the decline, teenagers were still exposed to a moderate amount of smoking imagery. Interventions that further reduce teenage exposure to smoking in movies may be needed to have an effect on adolescent smoking. Copyright © 2011 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

The prevalence of cardiovascular disease risk factors and the Framingham Risk Score in patients undergoing percutaneous intervention over the last 17 years by gender: time-trend analysis from the Mayo Clinic PCI Registry.

PubMed

Lee, Moo-Sik; Flammer, Andreas J; Kim, Hyun-Soo; Hong, Jee-Young; Li, Jing; Lennon, Ryan J; Lerman, Amir

2014-07-01

This study aims to investigate trends of cardiovascular disease (CVD) risk factor profiles over 17 years in percutaneous coronary intervention (PCI) patients at the Mayo Clinic. We performed a time-trend analysis within the Mayo Clinic PCI Registry from 1994 to 2010. Results were the incidence and prevalence of CVD risk factors as estimate by the Framingham risk score. Between 1994 and 2010, 25 519 patients underwent a PCI. During the time assessed, the mean age at PCI became older, but the gender distribution did not change. A significant trend towards higher body mass index and more prevalent hypercholesterolemia, hypertension, and diabetes was found over time. The prevalence of current smokers remained unchanged. The prevalence of ever-smokers decreased among males, but increased among females. However, overall CVD risk according to the Framingham risk score (FRS) and 10-year CVD risk significantly decreased. The use of most of medications elevated from 1994 to 2010, except for β-blockers and angiotensin converting enzyme inhibitors decreased after 2007 and 2006 in both baseline and discharge, respectively. Most of the major risk factors improved and the FRS and 10-year CVD risk declined in this population of PCI patients. However, obesity, history of hypercholesterolemia, hypertension, diabetes, and medication use increased substantially. Improvements to blood pressure and lipid profile management because of medication use may have influenced the positive trends. This study aims to investigate trends of cardiovascular disease (CVD) risk factor profiles over 17 years in percutaneous coronary intervention (PCI) patients at the Mayo Clinic. We performed a time-trend analysis within the Mayo Clinic PCI Registry from 1994 to 2010. Results were the incidence and prevalence of CVD risk factors as estimate by the Framingham risk score. Between 1994 and 2010, 25 519 patients underwent a PCI. During the time assessed, the mean age at PCI became older, but the gender distribution did not change. A significant trend towards higher body mass index and more prevalent hypercholesterolemia, hypertension, and diabetes was found over time. The prevalence of current smokers remained unchanged. The prevalence of ever-smokers decreased among males, but increased among females. However, overall CVD risk according to the Framingham risk score (FRS) and 10-year CVD risk significantly decreased. The use of most of medications elevated from 1994 to 2010, except for β-blockers and angiotensin converting enzyme inhibitors decreased after 2007 and 2006 in both baseline and discharge, respectively. Most of the major risk factors improved and the FRS and 10-year CVD risk declined in this population of PCI patients. However, obesity, history of hypercholesterolemia, hypertension, diabetes, and medication use increased substantially. Improvements to blood pressure and lipid profile management because of medication use may have influenced the positive trends.

VizieR Online Data Catalog: Fermi/GBM GRB time-resolved spectral catalog (Yu+, 2016)

NASA Astrophysics Data System (ADS)

Yu, H.-F.; Preece, R. D.; Greiner, J.; Bhat, P. N.; Bissaldi, E.; Briggs, M. S.; Cleveland, W. H.; Connaughton, V.; Goldstein, A.; von Kienlin; A.; Kouveliotou, C.; Mailyan, B.; Meegan, C. A.; Paciesas, W. S.; Rau, A.; Roberts, O. J.; Veres, P.; Wilson-Hodge, C.; Zhang, B.-B.; van Eerten, H. J.

2016-01-01

Time-resolved spectral analysis results of BEST models: for each spectrum GRB name using the Fermi GBM trigger designation, spectrum number within individual burst, start time Tstart and end time Tstop for the time bin, BEST model, best-fit parameters of the BEST model, value of CSTAT per degrees of freedom, 10keV-1MeV photon and energy flux are given. Ep evolutionary trends: for each burst GRB name, number of spectra with Ep, Spearman's Rank Correlation Coefficients between Ep_ and photon flux and 90%, 95%, and 99% confidence intervals, Spearman's Rank Correlation Coefficients between Ep and energy flux and 90%, 95%, and 99% confidence intervals, Spearman's Rank Correlation Coefficient between Ep and time and 90%, 95%, and 99% confidence intervals, trends as determined by computer for 90%, 95%, and 99% confidence intervals, trends as determined by human eyes are given. (2 data files).

Homosexual Pornography: Trends in Content and Form over a Twenty-Five Year Period.

ERIC Educational Resources Information Center

Celline, Harold B.; Duncan, David F.

1988-01-01

Conducted qualitative content analysis to examine homosexual pornography on sale in adult bookstores during four time periods: 1960-1969, 1970-1974, 1975-1979, and 1980-1984. Results revealed four trends: less tendency to disguise homosexual pornography, increasingly explicit sexual content, increasing emphasis on physical attractiveness of…

Statistical analysis of strait time index and a simple model for trend and trend reversal

NASA Astrophysics Data System (ADS)

Chen, Kan; Jayaprakash, C.

2003-06-01

We analyze the daily closing prices of the Strait Time Index (STI) as well as the individual stocks traded in Singapore's stock market from 1988 to 2001. We find that the Hurst exponent is approximately 0.6 for both the STI and individual stocks, while the normal correlation functions show the random walk exponent of 0.5. We also investigate the conditional average of the price change in an interval of length T given the price change in the previous interval. We find strong correlations for price changes larger than a threshold value proportional to T; this indicates that there is no uniform crossover to Gaussian behavior. A simple model based on short-time trend and trend reversal is constructed. We show that the model exhibits statistical properties and market swings similar to those of the real market.

Is the virulence of HIV changing? A meta-analysis of trends in prognostic markers of HIV disease progression and transmission

PubMed Central

Herbeck, Joshua T.; Müller, Viktor; Maust, Brandon S.; Ledergerber, Bruno; Torti, Carlo; Di Giambenedetto, Simona; Gras, Luuk; Günthard, Huldrych F.; Jacobson, Lisa P.; Mullins, James I.; Gottlieb, Geoffrey S.

2013-01-01

Objective The potential for changing HIV-1 virulence has significant implications for the AIDS epidemic, including changing HIV transmission rates, rapidity of disease progression, and timing of ART. Published data to date have provided conflicting results. Design We conducted a meta-analysis of changes in baseline CD4+ T-cell counts and set point plasma viral RNA load over time in order to establish whether summary trends are consistent with changing HIV-1 virulence. Methods We searched PubMed for studies of trends in HIV-1 prognostic markers of disease progression and supplemented findings with publications referenced in epidemiological or virulence studies. We identified 12 studies of trends in baseline CD4+ T-cell counts (21 052 total individuals), and eight studies of trends in set point viral loads (10 785 total individuals), spanning the years 1984–2010. Using random-effects meta-analysis, we estimated summary effect sizes for trends in HIV-1 plasma viral loads and CD4+ T-cell counts. Results Baseline CD4+ T-cell counts showed a summary trend of decreasing cell counts [effect=−4.93 cells/µl per year, 95% confidence interval (CI) −6.53 to −3.3]. Set point viral loads showed a summary trend of increasing plasma viral RNA loads (effect=0.013 log10 copies/ml per year, 95% CI −0.001 to 0.03). The trend rates decelerated in recent years for both prognostic markers. Conclusion Our results are consistent with increased virulence of HIV-1 over the course of the epidemic. Extrapolating over the 30 years since the first description of AIDS, this represents a CD4+ T cells loss of approximately 148 cells/µl and a gain of 0.39 log10 copies/ml of viral RNA measured during early infection. These effect sizes would predict increasing rates of disease progression, and need for ART as well as increasing transmission risk. PMID:22089381

Spatial analysis of precipitation time series over the Upper Indus Basin

NASA Astrophysics Data System (ADS)

Latif, Yasir; Yaoming, Ma; Yaseen, Muhammad

2018-01-01

The upper Indus basin (UIB) holds one of the most substantial river systems in the world, contributing roughly half of the available surface water in Pakistan. This water provides necessary support for agriculture, domestic consumption, and hydropower generation; all critical for a stable economy in Pakistan. This study has identified trends, analyzed variability, and assessed changes in both annual and seasonal precipitation during four time series, identified herein as: (first) 1961-2013, (second) 1971-2013, (third) 1981-2013, and (fourth) 1991-2013, over the UIB. This study investigated spatial characteristics of the precipitation time series over 15 weather stations and provides strong evidence of annual precipitation by determining significant trends at 6 stations (Astore, Chilas, Dir, Drosh, Gupis, and Kakul) out of the 15 studied stations, revealing a significant negative trend during the fourth time series. Our study also showed significantly increased precipitation at Bunji, Chitral, and Skardu, whereas such trends at the rest of the stations appear insignificant. Moreover, our study found that seasonal precipitation decreased at some locations (at a high level of significance), as well as periods of scarce precipitation during all four seasons. The observed decreases in precipitation appear stronger and more significant in autumn; having 10 stations exhibiting decreasing precipitation during the fourth time series, with respect to time and space. Furthermore, the observed decreases in precipitation appear robust and more significant for regions at high elevation (>1300 m). This analysis concludes that decreasing precipitation dominated the UIB, both temporally and spatially including in the higher areas.

Econophysics — complex correlations and trend switchings in financial time series

NASA Astrophysics Data System (ADS)

Preis, T.

2011-03-01

This article focuses on the analysis of financial time series and their correlations. A method is used for quantifying pattern based correlations of a time series. With this methodology, evidence is found that typical behavioral patterns of financial market participants manifest over short time scales, i.e., that reactions to given price patterns are not entirely random, but that similar price patterns also cause similar reactions. Based on the investigation of the complex correlations in financial time series, the question arises, which properties change when switching from a positive trend to a negative trend. An empirical quantification by rescaling provides the result that new price extrema coincide with a significant increase in transaction volume and a significant decrease in the length of corresponding time intervals between transactions. These findings are independent of the time scale over 9 orders of magnitude, and they exhibit characteristics which one can also find in other complex systems in nature (and in physical systems in particular). These properties are independent of the markets analyzed. Trends that exist only for a few seconds show the same characteristics as trends on time scales of several months. Thus, it is possible to study financial bubbles and their collapses in more detail, because trend switching processes occur with higher frequency on small time scales. In addition, a Monte Carlo based simulation of financial markets is analyzed and extended in order to reproduce empirical features and to gain insight into their causes. These causes include both financial market microstructure and the risk aversion of market participants.

SWiFT site atmospheric characterization

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

Kelley, Christopher Lee; Ennis, Brandon Lee

2016-01-01

Historical meteorological tall tower data are analyzed from the Texas Tech University 200 m tower to characterize the atmospheric trends of the Scaled Wind Farm Technologies (SWiFT) site. In this report the data are analyzed to reveal bulk atmospheric trends, temporal trends and correlations of atmospheric variables. Through this analysis for the SWiFT turbines the site International Electrotechnical Commission (IEC) classification is determined to be class III-C. Averages and distributions of atmospheric variables are shown, revealing large fluctuations and the importance of understanding the actual site trends as opposed to simply using averages. The site is significantly directional with themore » average wind speed from the south, and particularly so in summer and fall. Site temporal trends are analyzed from both seasonal (time of the year) to daily (hour of the day) perspectives. Atmospheric stability is seen to vary most with time of day and less with time of year. Turbulence intensity is highly correlated with stability, and typical daytime unstable conditions see double the level of turbulence intensity versus that experienced during the average stable night. Shear, veer and atmospheric stability correlations are shown, where shear and veer are both highest for stable atmospheric conditions. An analysis of the Texas Tech University tower anemometer measurements is performed which reveals the extent of the tower shadow effects and sonic tilt misalignment.« less

Temporal changes in aquatic-invertebrate and fish assemblages in streams of the north-central and northeastern U.S.

USGS Publications Warehouse

Kennen, Jonathan G.; Sullivan, Daniel J.; May, Jason T.; Bell, Amanda H.; Beaulieu, Karen M.; Rice, Donald E.

2012-01-01

Many management agencies seek to evaluate temporal changes in aquatic assemblages at monitoring sites, but few have sites with ecological time series that are long enough for this purpose. Trends in aquatic-invertebrate and fish assemblage composition were assessed at 27 long-term monitoring sites in the north-central and northeastern United States. Temporal changes were identified using serial trend analysis. Sites with significant serial trends were further evaluated by relating explanatory environmental variables (e.g., streamflow, habitat, and water chemistry) to changes in assemblage composition. Significant trends were found at 19 of 27 study sites; however, differences in the sensitivity of the aquatic fauna to environmental stressors were identified. For example, significant trends in fish assemblages were found at more sites (15 of 27) than for aquatic-invertebrate assemblages (10 of 27 sites). In addition, trends in the invertebrate assemblage were most often explained by changes in streamflow processes (e.g., duration and magnitude of low- and high-flows, streamflow variability, and annual rates of change), whereas trends in the fish assemblage were more related to changes in water chemistry. Results illustrate the value of long-term monitoring for the purpose of assessing temporal trends in aquatic assemblages. The ability to detect trends in assemblage composition and to attribute these changes to environmental factors is necessary to understand mechanistic pathways and to further our understanding of how incremental anthropogenic alterations modify aquatic assemblages over time. Finally, this study's approach to trends analysis can be used to better inform the design of monitoring programs as well as support the ongoing management needs of stakeholders, water-resource agencies, and policy makers.

Migration of Undergraduate First-Time Transfers: Snapshot Analysis 2006-2008

ERIC Educational Resources Information Center

South Carolina Commission on Higher Education, 2010

2010-01-01

The Commission on Higher Education had a student intern from USC-Columbia initiate an analysis of data on the migration of undergraduate first-time transfers to compare trends, growth, and proportions of transfers to and from various sectors and institution types over a three-year period, from 2006-2008. Staff have refined the analysis and…

Apparatus and method for epileptic seizure detection using non-linear techniques

DOEpatents

Hively, Lee M.; Clapp, Ned E.; Daw, C. Stuart; Lawkins, William F.

1998-01-01

Methods and apparatus for automatically detecting epileptic seizures by monitoring and analyzing brain wave (EEG or MEG) signals. Steps include: acquiring the brain wave data from the patient; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis; obtaining time serial trends in the nonlinear measures; determining that one or more trends in the nonlinear measures indicate a seizure, and providing notification of seizure occurrence.

Integrated method for chaotic time series analysis

DOEpatents

Hively, Lee M.; Ng, Esmond G.

1998-01-01

Methods and apparatus for automatically detecting differences between similar but different states in a nonlinear process monitor nonlinear data. Steps include: acquiring the data; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis; obtaining time serial trends in the nonlinear measures; and determining by comparison whether differences between similar but different states are indicated.

Analysis of trend in temperature and rainfall time series of an Indian arid region: comparative evaluation of salient techniques

NASA Astrophysics Data System (ADS)

Machiwal, Deepesh; Gupta, Ankit; Jha, Madan Kumar; Kamble, Trupti

2018-04-01

This study investigated trends in 35 years (1979-2013) temperature (maximum, Tmax and minimum, Tmin) and rainfall at annual and seasonal (pre-monsoon, monsoon, post-monsoon, and winter) scales for 31 grid points in a coastal arid region of India. Box-whisker plots of annual temperature and rainfall time series depict systematic spatial gradients. Trends were examined by applying eight tests, such as Kendall rank correlation (KRC), Spearman rank order correlation (SROC), Mann-Kendall (MK), four modified MK tests, and innovative trend analysis (ITA). Trend magnitudes were quantified by Sen's slope estimator, and a new method was adopted to assess the significance of linear trends in MK-test statistics. It was found that the significant serial correlation is prominent in the annual and post-monsoon Tmax and Tmin, and pre-monsoon Tmin. The KRC and MK tests yielded similar results in close resemblance with the SROC test. The performance of two modified MK tests considering variance-correction approaches was found superior to the KRC, MK, modified MK with pre-whitening, and ITA tests. The performance of original MK test is poor due to the presence of serial correlation, whereas the ITA method is over-sensitive in identifying trends. Significantly increasing trends are more prominent in Tmin than Tmax. Further, both the annual and monsoon rainfall time series have a significantly increasing trend of 9 mm year-1. The sequential significance of linear trend in MK test-statistics is very strong (R 2 ≥ 0.90) in the annual and pre-monsoon Tmin (90% grid points), and strong (R 2 ≥ 0.75) in monsoon Tmax (68% grid points), monsoon, post-monsoon, and winter Tmin (respectively 65, 55, and 48% grid points), as well as in the annual and monsoon rainfalls (respectively 68 and 61% grid points). Finally, this study recommends use of variance-corrected MK test for the precise identification of trends. It is emphasized that the rising Tmax may hamper crop growth due to enhanced metabolic-activities and shortened crop-duration. Likewise, increased Tmin may result in lesser crop and biomass yields owing to the increased respiration.

Seventeen-year time trend in poor self-rated health in older adults: changing contributions of chronic diseases and disability.

PubMed

Galenkamp, Henrike; Braam, Arjan W; Huisman, Martijn; Deeg, Dorly J H

2013-06-01

Studies on trends in the self-rated health (SRH) of older people have shown conflicting results, which might partly be explained by changing associations between SRH and indicators of other health dimensions over time. Therefore, this study investigates 17-year time trends in older adults' poor SRH, in the context of trends in chronic diseases and disability, between 1992 and 2009. Data originate from six measurement waves of the Longitudinal Aging Study Amsterdam (N = 4009, ages 60-85 years). SRH was assessed with the question 'How is your health in general?' The presence of lung disease, cardiac disease, peripheral arterial disease, diabetes mellitus, stroke, arthritis and cancer was assessed by self-report. Two severity levels of disability were assessed with six questions on physical functioning. Generalized Estimating Equations (GEE) analysis was applied to assess statistical significance in each time trend. There was a stable trend in the prevalence of poor SRH and severe disability, while the mean number of chronic diseases (1.3-1.8) and the prevalence of mild disability (20.5-32.1%) increased between 1992 and 2009. The association between poor SRH and chronic diseases became weaker, whereas the association between poor SRH and severe disability became stronger over time. Most unfavourable trends were observed in the older old and the lower educated. Our results suggest that the seeming stability of poor SRH hides underlying increases in chronic diseases and disability: over time, people may attach importance to different aspects of health when rating their overall health.

Sea-Level Trend Uncertainty With Pacific Climatic Variability and Temporally-Correlated Noise

NASA Astrophysics Data System (ADS)

Royston, Sam; Watson, Christopher S.; Legrésy, Benoît; King, Matt A.; Church, John A.; Bos, Machiel S.

2018-03-01

Recent studies have identified climatic drivers of the east-west see-saw of Pacific Ocean satellite altimetry era sea level trends and a number of sea-level trend and acceleration assessments attempt to account for this. We investigate the effect of Pacific climate variability, together with temporally-correlated noise, on linear trend error estimates and determine new time-of-emergence (ToE) estimates across the Indian and Pacific Oceans. Sea-level trend studies often advocate the use of auto-regressive (AR) noise models to adequately assess formal uncertainties, yet sea level often exhibits colored but non-AR(1) noise. Standard error estimates are over- or under-estimated by an AR(1) model for much of the Indo-Pacific sea level. Allowing for PDO and ENSO variability in the trend estimate only reduces standard errors across the tropics and we find noise characteristics are largely unaffected. Of importance for trend and acceleration detection studies, formal error estimates remain on average up to 1.6 times those from an AR(1) model for long-duration tide gauge data. There is an even chance that the observed trend from the satellite altimetry era exceeds the noise in patches of the tropical Pacific and Indian Oceans and the south-west and north-east Pacific gyres. By including climate indices in the trend analysis, the time it takes for the observed linear sea-level trend to emerge from the noise reduces by up to 2 decades.

Sources and preparation of data for assessing trends in concentrations of pesticides in streams of the United States, 1992-2006

USGS Publications Warehouse

Martin, Jeffrey D.

2009-01-01

This report provides a water-quality data set of 44 commonly used pesticides and 8 pesticide degradates suitable for a national assessment of trends in pesticide concentrations in streams of the United States. Water-quality samples collected from January 1992 through August 2006 at stream-water sites of the U.S. Geological Survey National Water-Quality Assessment Program and the National Stream Quality Accounting Network Program were compiled, reviewed, selected, and prepared for trend analysis as described in this report. Samples analyzed at the U.S. Geological Survey National Water Quality Laboratory by a gas chromatography/mass spectrometry analytical method were the most extensive in time and space and were selected for national trend analysis. The selection criteria described in the report produced a trend data set of 16,869 pesticide samples at 201 stream and river sites.

Analysis of the Capacity of Google Trends to Measure Interest in Conservation Topics and the Role of Online News

PubMed Central

Nghiem, Le T. P.; Papworth, Sarah K.; Lim, Felix K. S.; Carrasco, Luis R.

2016-01-01

With the continuous growth of internet usage, Google Trends has emerged as a source of information to investigate how social trends evolve over time. Knowing how the level of interest in conservation topics—approximated using Google search volume—varies over time can help support targeted conservation science communication. However, the evolution of search volume over time and the mechanisms that drive peaks in searches are poorly understood. We conducted time series analyses on Google search data from 2004 to 2013 to investigate: (i) whether interests in selected conservation topics have declined and (ii) the effect of news reporting and academic publishing on search volume. Although trends were sensitive to the term used as benchmark, we did not find that public interest towards conservation topics such as climate change, ecosystem services, deforestation, orangutan, invasive species and habitat loss was declining. We found, however, a robust downward trend for endangered species and an upward trend for ecosystem services. The quantity of news articles was related to patterns in Google search volume, whereas the number of research articles was not a good predictor but lagged behind Google search volume, indicating the role of news in the transfer of conservation science to the public. PMID:27028399

Analysis of the Capacity of Google Trends to Measure Interest in Conservation Topics and the Role of Online News.

PubMed

Nghiem, Le T P; Papworth, Sarah K; Lim, Felix K S; Carrasco, Luis R

2016-01-01

With the continuous growth of internet usage, Google Trends has emerged as a source of information to investigate how social trends evolve over time. Knowing how the level of interest in conservation topics--approximated using Google search volume--varies over time can help support targeted conservation science communication. However, the evolution of search volume over time and the mechanisms that drive peaks in searches are poorly understood. We conducted time series analyses on Google search data from 2004 to 2013 to investigate: (i) whether interests in selected conservation topics have declined and (ii) the effect of news reporting and academic publishing on search volume. Although trends were sensitive to the term used as benchmark, we did not find that public interest towards conservation topics such as climate change, ecosystem services, deforestation, orangutan, invasive species and habitat loss was declining. We found, however, a robust downward trend for endangered species and an upward trend for ecosystem services. The quantity of news articles was related to patterns in Google search volume, whereas the number of research articles was not a good predictor but lagged behind Google search volume, indicating the role of news in the transfer of conservation science to the public.

Statistical power for detecting trends with applications to seabird monitoring

USGS Publications Warehouse

Hatch, Shyla A.

2003-01-01

Power analysis is helpful in defining goals for ecological monitoring and evaluating the performance of ongoing efforts. I examined detection standards proposed for population monitoring of seabirds using two programs (MONITOR and TRENDS) specially designed for power analysis of trend data. Neither program models within- and among-years components of variance explicitly and independently, thus an error term that incorporates both components is an essential input. Residual variation in seabird counts consisted of day-to-day variation within years and unexplained variation among years in approximately equal parts. The appropriate measure of error for power analysis is the standard error of estimation (S.E.est) from a regression of annual means against year. Replicate counts within years are helpful in minimizing S.E.est but should not be treated as independent samples for estimating power to detect trends. Other issues include a choice of assumptions about variance structure and selection of an exponential or linear model of population change. Seabird count data are characterized by strong correlations between S.D. and mean, thus a constant CV model is appropriate for power calculations. Time series were fit about equally well with exponential or linear models, but log transformation ensures equal variances over time, a basic assumption of regression analysis. Using sample data from seabird monitoring in Alaska, I computed the number of years required (with annual censusing) to detect trends of -1.4% per year (50% decline in 50 years) and -2.7% per year (50% decline in 25 years). At ??=0.05 and a desired power of 0.9, estimated study intervals ranged from 11 to 69 years depending on species, trend, software, and study design. Power to detect a negative trend of 6.7% per year (50% decline in 10 years) is suggested as an alternative standard for seabird monitoring that achieves a reasonable match between statistical and biological significance.

Latent fluctuation periods and long-term forecasting of the level of Markakol lake

NASA Astrophysics Data System (ADS)

Madibekov, A. S.; Babkin, A. V.; Musakulkyzy, A.; Cherednichenko, A. V.

2018-01-01

The analysis of time series of the level of Markakol Lake by the method of “Periodicities” reveals in its variations the harmonics with the periods of 12 and 14 years, respectively. The verification forecasts of the lake level by the trend tendency and by its combination with these sinusoids were computed with the lead time of 5 and 10 years. The estimation of the forecast results by the new independent data permitted to conclude that forecasts by the combination of the sinusoids and trend tendency are better than by the trend tendency only. They are no worse than the mean value prediction.

Extensive mapping of coastal change in Alaska by Landsat time-series analysis, 1972-2013 (Invited)

NASA Astrophysics Data System (ADS)

Macander, M. J.; Swingley, C. S.; Reynolds, J.

2013-12-01

The landscape-scale effects of coastal storms on Alaska's Bering Sea and Gulf of Alaska coasts includes coastal erosion, migration of spits and barrier islands, breaching of coastal lakes and lagoons, and inundation and salt-kill of vegetation. Large changes in coastal storm frequency and intensity are expected due to climate change and reduced sea-ice extent. Storms have a wide range of impacts on carbon fluxes and on fish and wildlife resources, infrastructure siting and operation, and emergency response planning. In areas experiencing moderate to large effects, changes can be mapped by analyzing trends in time series of Landsat imagery from Landsat 1 through Landsat 8. ABR, Inc.--Environmental Research & Services and the Western Alaska Landscape Conservation Cooperative are performing a time-series trend analysis for over 22,000 kilometers of coastline along the Bering Sea and Gulf of Alaska. The archive of Landsat imagery covers the time period 1972-present. For a pilot study area in Kotzebue Sound, we conducted a regression analysis of changes in near-infrared reflectance to identify areas with significant changes in coastal features, 1972-2011. Suitable ice- and cloud-free Landsat imagery was obtained for 28 of the 40 years during the period. The approach captured several coastal changes over the 40-year study period, including coastal erosion exceeding the 60-m pixel resolution of the Multispectral Scanner (MSS) data and migrations of coastal spits and estuarine channels. In addition several lake drainage events were identified, mostly inland from the coastal zone. Analysis of shorter, decadal time periods produced noisier results that were generally consistent with the long-term trend analysis. Unusual conditions at the start or end of the time-series can strongly influence decadal results. Based on these results the study is being scaled up to map coastal change for over 22,000 kilometers of coastline along the Bering Sea and Gulf of Alaska coast. The Landsat imagery archive compiled to perform the coastal change analysis can also be used for other applications including monitoring lake drainage, fire, and vegetation transitions; and characterizing snow persistence patterns and seasonal water level changes. Landsat trend analysis results (1972-2011) for pilot study area in Kotzebue Sound, Alaska.

Global Warming Estimation from MSU

NASA Technical Reports Server (NTRS)

Prabhakara, C.; Iacovazzi, Robert; Yoo, Jung-Moon

1998-01-01

Microwave Sounding Unit (MSU) radiometer observations in Ch 2 (53.74 GHz) from sequential, sun-synchronous, polar-orbiting NOAA satellites contain small systematic errors. Some of these errors are time-dependent and some are time-independent. Small errors in Ch 2 data of successive satellites arise from calibration differences. Also, successive NOAA satellites tend to have different Local Equatorial Crossing Times (LECT), which introduce differences in Ch 2 data due to the diurnal cycle. These two sources of systematic error are largely time independent. However, because of atmospheric drag, there can be a drift in the LECT of a given satellite, which introduces time-dependent systematic errors. One of these errors is due to the progressive chance in the diurnal cycle and the other is due to associated chances in instrument heating by the sun. In order to infer global temperature trend from the these MSU data, we have eliminated explicitly the time-independent systematic errors. Both of the time-dependent errors cannot be assessed from each satellite. For this reason, their cumulative effect on the global temperature trend is evaluated implicitly. Christy et al. (1998) (CSL). based on their method of analysis of the MSU Ch 2 data, infer a global temperature cooling trend (-0.046 K per decade) from 1979 to 1997, although their near nadir measurements yield near zero trend (0.003 K/decade). Utilising an independent method of analysis, we infer global temperature warmed by 0.12 +/- 0.06 C per decade from the observations of the MSU Ch 2 during the period 1980 to 1997.

Seasonal trend analysis and ARIMA modeling of relative humidity and wind speed time series around Yamula Dam

NASA Astrophysics Data System (ADS)

Eymen, Abdurrahman; Köylü, Ümran

2018-02-01

Local climate change is determined by analysis of long-term recorded meteorological data. In the statistical analysis of the meteorological data, the Mann-Kendall rank test, which is one of the non-parametrical tests, has been used; on the other hand, for determining the power of the trend, Theil-Sen method has been used on the data obtained from 16 meteorological stations. The stations cover the provinces of Kayseri, Sivas, Yozgat, and Nevşehir in the Central Anatolia region of Turkey. Changes in land-use affect local climate. Dams are structures that cause major changes on the land. Yamula Dam is located 25 km northwest of Kayseri. The dam has huge water body which is approximately 85 km2. The mentioned tests have been used for detecting the presence of any positive or negative trend in meteorological data. The meteorological data in relation to the seasonal average, maximum, and minimum values of the relative humidity and seasonal average wind speed have been organized as time series and the tests have been conducted accordingly. As a result of these tests, the following have been identified: increase was observed in minimum relative humidity values in the spring, summer, and autumn seasons. As for the seasonal average wind speed, decrease was detected for nine stations in all seasons, whereas increase was observed in four stations. After the trend analysis, pre-dam mean relative humidity time series were modeled with Autoregressive Integrated Moving Averages (ARIMA) model which is statistical modeling tool. Post-dam relative humidity values were predicted by ARIMA models.

Patterns in Patient Access and Utilization of Online Medical Records: Analysis of MyChart

PubMed Central

2018-01-01

Background Electronic patient portals provide a new method for sharing personal medical information with individual patients. Objective Our aim was to review utilization patterns of the largest online patient portal in Canada's largest city. Methods We conducted a 4-year time-trend analysis of aggregated anonymous utilization data of the MyChart patient portal at Sunnybrook Health Sciences Centre in Ontario, Canada, from January 1, 2012, through December 31, 2015. Prespecified analyses examined trends related to day (weekend vs weekday), season (July vs January), year (2012 vs 2015), and an extreme adverse weather event (ice storm of December 20-26, 2013). Primary endpoints included three measures of patient portal activity: registrations, logins, and pageviews. Results We identified 32,325 patients who registered for a MyChart account during the study interval. Time-trend analysis showed no sign of attenuating registrations over time. Logins were frequent, averaged 734 total per day, and showed an increasing trend over time. Pageviews mirrored logins, averaged about 3029 total per day, and equated to about 5 pageviews during the average login. The most popular pageviews were clinical notes, followed by laboratory results and medical imaging reports. All measures of patient activity were lower on weekends compared to weekdays (P<.001) yet showed no significant changes related to seasons or extreme weather. No major security breach, malware attack, or software failure occurred during the study. Conclusions Online patient portals can provide a popular and reliable system for distributing personal medical information to active patients and may merit consideration for hospitals. PMID:29410386

Regional Landslide Mapping Aided by Automated Classification of SqueeSAR™ Time Series (Northern Apennines, Italy)

NASA Astrophysics Data System (ADS)

Iannacone, J.; Berti, M.; Allievi, J.; Del Conte, S.; Corsini, A.

2013-12-01

Space borne InSAR has proven to be very valuable for landslides detection. In particular, extremely slow landslides (Cruden and Varnes, 1996) can be now clearly identified, thanks to the millimetric precision reached by recent multi-interferometric algorithms. The typical approach in radar interpretation for landslides mapping is based on average annual velocity of the deformation which is calculated over the entire times series. The Hotspot and Cluster Analysis (Lu et al., 2012) and the PSI-based matrix approach (Cigna et al., 2013) are examples of landslides mapping techniques based on average annual velocities. However, slope movements can be affected by non-linear deformation trends, (i.e. reactivation of dormant landslides, deceleration due to natural or man-made slope stabilization, seasonal activity, etc). Therefore, analyzing deformation time series is crucial in order to fully characterize slope dynamics. While this is relatively simple to be carried out manually when dealing with small dataset, the time series analysis over regional scale dataset requires automated classification procedures. Berti et al. (2013) developed an automatic procedure for the analysis of InSAR time series based on a sequence of statistical tests. The analysis allows to classify the time series into six distinctive target trends (0=uncorrelated; 1=linear; 2=quadratic; 3=bilinear; 4=discontinuous without constant velocity; 5=discontinuous with change in velocity) which are likely to represent different slope processes. The analysis also provides a series of descriptive parameters which can be used to characterize the temporal changes of ground motion. All the classification algorithms were integrated into a Graphical User Interface called PSTime. We investigated an area of about 2000 km2 in the Northern Apennines of Italy by using SqueeSAR™ algorithm (Ferretti et al., 2011). Two Radarsat-1 data stack, comprising of 112 scenes in descending orbit and 124 scenes in ascending orbit, were processed. The time coverage lasts from April 2003 to November 2012, with an average temporal frequency of 1 scene/month. Radar interpretation has been carried out by considering average annual velocities as well as acceleration/deceleration trends evidenced by PSTime. Altogether, from ascending and descending geometries respectively, this approach allowed detecting of 115 and 112 potential landslides on the basis of average displacement rate and 77 and 79 landslides on the basis of acceleration trends. In conclusion, time series analysis resulted to be very valuable for landslide mapping. In particular it highlighted areas with marked acceleration in a specific period in time while still being affected by low average annual velocity over the entire analysis period. On the other hand, even in areas with high average annual velocity, time series analysis was of primary importance to characterize the slope dynamics in terms of acceleration events.

Intelligent trend analysis for a solar thermal energy collector field

NASA Astrophysics Data System (ADS)

Juuso, E. K.

2018-03-01

Solar thermal power plants collect available solar energy in a usable form at a temperature range which is adapted to the irradiation levels and seasonal variations. Solar energy can be collected only when the irradiation is high enough to produce the required temperatures. During the operation, a trade-off of the temperature and the flow is needed to achieve a good level for the collected power. The scaling approach brings temporal analysis to all measurements and features: trend indices are calculated by comparing the averages in the long and short time windows, a weighted sum of the trend index and its derivative detects the trend episodes and severity of the trend is estimated by including also the variable level in the sum. The trend index, trend episodes and especially, the deviation index reveal early evolving changes in the operating conditions, including cloudiness and load disturbances. The solution is highly compact: all variables, features and indices are transformed to the range [-2, 2] and represented in natural language which is important in integrating data-driven solutions with domain expertise. The special situations detected during the test campaigns are explained well.

Trends in job satisfaction among German nurses from 1990 to 2012.

PubMed

Alameddine, Mohamad; Bauer, Jan Michael; Richter, Martin; Sousa-Poza, Alfonso

2016-04-01

Improving the job satisfaction of nurses is essential to enhance their productivity and retention and to improve patient care. Our aim was to analyse trends in German nurses' job satisfaction to enhance understanding of the nursing labour market and inform future policies. We used 1990-2012 German Socioeconomic Panel data for trends in nurses' job satisfaction. Comparisons were drawn with doctors, other health care workers, and employees in other sectors of employment. Analysis explored associations between job satisfaction trends and other aspects of employment, such as whether full time or part time and pay. To account for fluctuations across the period of analysis, linear trends were generated using ordinary least squares. Over 23 years, job satisfaction of German nurses underwent a steady and gradual decline, dropping by an average 7.5%, whereas that of doctors and other health care workers increased by 14.4% and 1%, respectively. The decline for part-time nurses (13%) was more pronounced than that for full-time nurses (3%). At the same time, nurses' pay rose by only 3.8% compared to a 23.8% increase for doctors. The steady decline in nurses' job satisfaction over the last two decades may be attributable to the multiple reforms and associated policy changes that generally disadvantaged nurses. Contributing factors to job satisfaction decline include lower pay and the demanding and strenuous work environment. Irrespective of the reason, health services researchers, leaders, and policy makers should investigate the reasons for this decline given the forecast growth in work load and complexity of care. Supportive policies for nurses would help enhance the quality and sustainability of German health care. © The Author(s) 2015.

What Could Be Causing Global Ozone Depletion

NASA Technical Reports Server (NTRS)

Singer, S. Fred

1990-01-01

The reported decline trend in global ozone between 1970 and 1986 may be in part an artifact of the analysis; the trend value appears to depend on the time interval selected for analysis--in relation to the 11-year solar cycle. If so, then the decline should diminish as one approaches solar maximum and includes data from 1987 to 1990. If the decline is real, its cause could be the result of natural and human factors other than just chlorofluorocarbons.

Global Search Trends of Oral Problems using Google Trends from 2004 to 2016: An Exploratory Analysis

PubMed Central

Patthi, Basavaraj; Singla, Ashish; Gupta, Ritu; Prasad, Monika; Ali, Irfan; Dhama, Kuldeep; Niraj, Lav Kumar

2017-01-01

Introduction Oral diseases are pandemic cause of morbidity with widespread geographic distribution. This technology based era has brought about easy knowledge transfer than traditional dependency on information obtained from family doctors. Hence, harvesting this system of trends can aid in oral disease quantification. Aim To conduct an exploratory analysis of the changes in internet search volumes of oral diseases by using Google Trends© (GT©). Materials and Methods GT© were utilized to provide real world facts based on search terms related to categories, interest by region and interest over time. Time period chosen was from January 2004 to December 2016. Five different search terms were explored and compared based on the highest relative search volumes along with comma separated value files to obtain an insight into highest search traffic. Results The search volume measured over the time span noted the term “Dental caries” to be the most searched in Japan, “Gingivitis” in Jordan, “Oral Cancer” in Taiwan, “No Teeth” in Australia, “HIV symptoms” in Zimbabwe, “Broken Teeth” in United Kingdom, “Cleft palate” in Philippines, “Toothache” in Indonesia and the comparison of top five searched terms provided the “Gingivitis” with highest search volume. Conclusion The results from the present study offers an insight into a competent tool that can analyse and compare oral diseases over time. The trend research platform can be used on emerging diseases and their drift in geographic population with great acumen. This tool can be utilized in forecasting, modulating marketing strategies and planning disability limitation techniques. PMID:29207825

Long-term stormwater quantity and quality analysis using continuous measurements in a French urban catchment.

PubMed

Sun, Siao; Barraud, Sylvie; Castebrunet, Hélène; Aubin, Jean-Baptiste; Marmonier, Pierre

2015-11-15

The assessment of urban stormwater quantity and quality is important for evaluating and controlling the impact of the stormwater to natural water and environment. This study mainly addresses long-term evolution of stormwater quantity and quality in a French urban catchment using continuous measured data from 2004 to 2011. Storm event-based data series are obtained (716 rainfall events and 521 runoff events are available) from measured continuous time series. The Mann-Kendall test is applied to these event-based data series for trend detection. A lack of trend is found in rainfall and an increasing trend in runoff is detected. As a result, an increasing trend is present in the runoff coefficient, likely due to growing imperviousness of the catchment caused by urbanization. The event mean concentration of the total suspended solid (TSS) in stormwater does not present a trend, whereas the event load of TSS has an increasing tendency, which is attributed to the increasing event runoff volume. Uncertainty analysis suggests that the major uncertainty in trend detection results lies in uncertainty due to available data. A lack of events due to missing data leads to dramatically increased uncertainty in trend detection results. In contrast, measurement uncertainty in time series data plays a trivial role. The intra-event distribution of TSS is studied based on both M(V) curves and pollutant concentrations of absolute runoff volumes. The trend detection test reveals no significant change in intra-event distributions of TSS in the studied catchment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of Engineering Discipline Grade Trends

ERIC Educational Resources Information Center

McAllister, Charles D.; Jiang, Xiaoyue; Aghazadeh, Fereydoun

2008-01-01

Among the academic community, there is a perception that there is an upward shift in grade point average over an extended period of time without a corresponding increase in achievement. This trend has become an alarming topic among educators, industry and the general public. Some attribute increases in GPA to improvements in student quality while…

Short-Term Enrollment Forecasting for Accurate Budget Planning.

ERIC Educational Resources Information Center

Salley, Charles D.

1979-01-01

Reliance on enrollment trend models for revenue projections has led to a scenario of alternating overbudgeted and underbudgeted years. A study of a large, public university indicates that time series analysis should be used instead to anticipate the orderly seasonal and cyclical patterns that are visible in a period of moderate trend growth.…

Apparatus and method for epileptic seizure detection using non-linear techniques

DOEpatents

Hively, L.M.; Clapp, N.E.; Daw, C.S.; Lawkins, W.F.

1998-04-28

Methods and apparatus are disclosed for automatically detecting epileptic seizures by monitoring and analyzing brain wave (EEG or MEG) signals. Steps include: acquiring the brain wave data from the patient; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis; obtaining time serial trends in the nonlinear measures; determining that one or more trends in the nonlinear measures indicate a seizure, and providing notification of seizure occurrence. 76 figs.

Trends in Surface Level Ozone Observations from Human-health Relevant Metrics: Results from the Tropospheric Ozone Assessment Report (TOAR)

NASA Astrophysics Data System (ADS)

Fleming, Z. L.; von Schneidemesser, E.; Doherty, R. M.; Malley, C.; Cooper, O. R.; Pinto, J. P.; Colette, A.; Xu, X.; Simpson, D.; Schultz, M.; Hamad, S.; Moola, R.; Solberg, S.; Feng, Z.

2017-12-01

Ozone is an air pollutant formed in the atmosphere from precursor species (NOx, VOCs, CH4, CO) that is detrimental to human health and ecosystems. The global Tropospheric Ozone Assessment Report (TOAR) initiative has assembled a global database of surface ozone observations and generated ozone exposure metrics at thousands of measurement sites around the world. This talk will present results from the assessment focused on those indicators most relevant to human health. Specifically, the trends in ozone, comparing different time periods and patterns across regions and among metrics will be addressed. In addition, the fraction of population exposed to high ozone levels and how this has changed between 2000 and 2014 will also be discussed. The core time period analyzed for trends was 2000-2014, selected to include a greater number of sites in East Asia. Negative trends were most commonly observed at many US and some European sites, whereas many sites in East Asia showed positive trends, while sites in Japan showed more of a mix of positive and negative trends. More than half of the sites showed a common direction and significance in the trends for all five human-health relevant metrics. The peak ozone metrics indicate a reduction in exposure to peak levels of ozone related to photochemical episodes in Europe and the US. A considerable number of European countries and states within the US have shown a decrease in population-weighted ozone over time. The 2000-2014 results will be augmented and compared to the trend analysis for additional time periods that cover a greater number of years, but by necessity are based on fewer sites. Trends are found to be statistically significant at a larger fraction of sites with longer time series, compared to the shorter (2000-2014) time series.

Long-Term Warming Trends in Korea and Contribution of Urbanization: An Updated Assessment

NASA Astrophysics Data System (ADS)

Park, Bo-Joung; Kim, Yeon-Hee; Min, Seung-Ki; Kim, Maeng-Ki; Choi, Youngeun; Boo, Kyung-On; Shim, Sungbo

2017-10-01

This study conducted an updated analysis of the long-term temperature trends over South Korea and reassessed the contribution of the urbanization effect to the local warming trends. Linear trends were analyzed for three different periods over South Korea in order to consider possible inhomogeneity due to changes in the number of available stations: recent 103 years (1912-2014), 61 years (1954-2014), and 42 years (1973-2014). The local temperature has increased by 1.90°C, 1.35°C, and 0.99°C during the three periods, respectively, which are found 1.4-2.6 times larger than the global land mean trends. The countries located in the northern middle and high latitudes exhibit similar warming trends (about 1.5 times stronger than the global mean), suggesting a weak influence of urbanization on the local warming over South Korea. Urbanization contribution is assessed using two methods. First, results from "city minus rural" methods showed that 30-45% of the local warming trends during recent four decades are likely due to the urbanization effect, depending on station classification methods and analysis periods. Results from an "observation minus reanalysis" method using the Twentieth Century Reanalysis (20CR) data sets (v2 and v2c) indicated about 25-30% contribution of the urbanization effect to the local warming trend during the recent six decades. However, the urbanization contribution was estimated as low as 3-11% when considering the century-long period. Our results confirm large uncertainties in the estimation of urbanization contribution when using shorter-term periods and suggest that the urbanization contribution to the century-long warming trends could be much lower.

Using Functional Data Analysis Models to Estimate Future Time Trends in Age-Specific Breast Cancer Mortality for the United States and England–Wales

PubMed Central

Erbas, Bircan; Akram, Muhammed; Gertig, Dorota M; English, Dallas; Hopper, John L.; Kavanagh, Anne M; Hyndman, Rob

2010-01-01

Background Mortality/incidence predictions are used for allocating public health resources and should accurately reflect age-related changes through time. We present a new forecasting model for estimating future trends in age-related breast cancer mortality for the United States and England–Wales. Methods We used functional data analysis techniques both to model breast cancer mortality-age relationships in the United States from 1950 through 2001 and England–Wales from 1950 through 2003 and to estimate 20-year predictions using a new forecasting method. Results In the United States, trends for women aged 45 to 54 years have continued to decline since 1980. In contrast, trends in women aged 60 to 84 years increased in the 1980s and declined in the 1990s. For England–Wales, trends for women aged 45 to 74 years slightly increased before 1980, but declined thereafter. The greatest age-related changes for both regions were during the 1990s. For both the United States and England–Wales, trends are expected to decline and then stabilize, with the greatest decline in women aged 60 to 70 years. Forecasts suggest relatively stable trends for women older than 75 years. Conclusions Prediction of age-related changes in mortality/incidence can be used for planning and targeting programs for specific age groups. Currently, these models are being extended to incorporate other variables that may influence age-related changes in mortality/incidence trends. In their current form, these models will be most useful for modeling and projecting future trends of diseases for which there has been very little advancement in treatment and minimal cohort effects (eg. lethal cancers). PMID:20139657

Integrated method for chaotic time series analysis

DOEpatents

Hively, L.M.; Ng, E.G.

1998-09-29

Methods and apparatus for automatically detecting differences between similar but different states in a nonlinear process monitor nonlinear data are disclosed. Steps include: acquiring the data; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis; obtaining time serial trends in the nonlinear measures; and determining by comparison whether differences between similar but different states are indicated. 8 figs.

Analysis of longitudinal "time series" data in toxicology.

PubMed

Cox, C; Cory-Slechta, D A

1987-02-01

Studies focusing on chronic toxicity or on the time course of toxicant effect often involve repeated measurements or longitudinal observations of endpoints of interest. Experimental design considerations frequently necessitate between-group comparisons of the resulting trends. Typically, procedures such as the repeated-measures analysis of variance have been used for statistical analysis, even though the required assumptions may not be satisfied in some circumstances. This paper describes an alternative analytical approach which summarizes curvilinear trends by fitting cubic orthogonal polynomials to individual profiles of effect. The resulting regression coefficients serve as quantitative descriptors which can be subjected to group significance testing. Randomization tests based on medians are proposed to provide a comparison of treatment and control groups. Examples from the behavioral toxicology literature are considered, and the results are compared to more traditional approaches, such as repeated-measures analysis of variance.

Quantifying trends in disease impact to produce a consistent and reproducible definition of an emerging infectious disease.

PubMed

Funk, Sebastian; Bogich, Tiffany L; Jones, Kate E; Kilpatrick, A Marm; Daszak, Peter

2013-01-01

The proper allocation of public health resources for research and control requires quantification of both a disease's current burden and the trend in its impact. Infectious diseases that have been labeled as "emerging infectious diseases" (EIDs) have received heightened scientific and public attention and resources. However, the label 'emerging' is rarely backed by quantitative analysis and is often used subjectively. This can lead to over-allocation of resources to diseases that are incorrectly labelled "emerging," and insufficient allocation of resources to diseases for which evidence of an increasing or high sustained impact is strong. We suggest a simple quantitative approach, segmented regression, to characterize the trends and emergence of diseases. Segmented regression identifies one or more trends in a time series and determines the most statistically parsimonious split(s) (or joinpoints) in the time series. These joinpoints in the time series indicate time points when a change in trend occurred and may identify periods in which drivers of disease impact change. We illustrate the method by analyzing temporal patterns in incidence data for twelve diseases. This approach provides a way to classify a disease as currently emerging, re-emerging, receding, or stable based on temporal trends, as well as to pinpoint the time when the change in these trends happened. We argue that quantitative approaches to defining emergence based on the trend in impact of a disease can, with appropriate context, be used to prioritize resources for research and control. Implementing this more rigorous definition of an EID will require buy-in and enforcement from scientists, policy makers, peer reviewers and journal editors, but has the potential to improve resource allocation for global health.

A statistical package for computing time and frequency domain analysis

NASA Technical Reports Server (NTRS)

Brownlow, J.

1978-01-01

The spectrum analysis (SPA) program is a general purpose digital computer program designed to aid in data analysis. The program does time and frequency domain statistical analyses as well as some preanalysis data preparation. The capabilities of the SPA program include linear trend removal and/or digital filtering of data, plotting and/or listing of both filtered and unfiltered data, time domain statistical characterization of data, and frequency domain statistical characterization of data.

Trend analysis of long-term temperature time series in the Greater Toronto Area (GTA)

NASA Astrophysics Data System (ADS)

Mohsin, Tanzina; Gough, William A.

2010-08-01

As the majority of the world’s population is living in urban environments, there is growing interest in studying local urban climates. In this paper, for the first time, the long-term trends (31-162 years) of temperature change have been analyzed for the Greater Toronto Area (GTA). Annual and seasonal time series for a number of urban, suburban, and rural weather stations are considered. Non-parametric statistical techniques such as Mann-Kendall test and Theil-Sen slope estimation are used primarily for the assessing of the significance and detection of trends, and the sequential Mann test is used to detect any abrupt climate change. Statistically significant trends for annual mean and minimum temperatures are detected for almost all stations in the GTA. Winter is found to be the most coherent season contributing substantially to the increase in annual minimum temperature. The analyses of the abrupt changes in temperature suggest that the beginning of the increasing trend in Toronto started after the 1920s and then continued to increase to the 1960s. For all stations, there is a significant increase of annual and seasonal (particularly winter) temperatures after the 1980s. In terms of the linkage between urbanization and spatiotemporal thermal patterns, significant linear trends in annual mean and minimum temperature are detected for the period of 1878-1978 for the urban station, Toronto, while for the rural counterparts, the trends are not significant. Also, for all stations in the GTA that are situated in all directions except south of Toronto, substantial temperature change is detected for the periods of 1970-2000 and 1989-2000. It is concluded that the urbanization in the GTA has significantly contributed to the increase of the annual mean temperatures during the past three decades. In addition to urbanization, the influence of local climate, topography, and larger scale warming are incorporated in the analysis of the trends.

Multivariate time series clustering on geophysical data recorded at Mt. Etna from 1996 to 2003

NASA Astrophysics Data System (ADS)

Di Salvo, Roberto; Montalto, Placido; Nunnari, Giuseppe; Neri, Marco; Puglisi, Giuseppe

2013-02-01

Time series clustering is an important task in data analysis issues in order to extract implicit, previously unknown, and potentially useful information from a large collection of data. Finding useful similar trends in multivariate time series represents a challenge in several areas including geophysics environment research. While traditional time series analysis methods deal only with univariate time series, multivariate time series analysis is a more suitable approach in the field of research where different kinds of data are available. Moreover, the conventional time series clustering techniques do not provide desired results for geophysical datasets due to the huge amount of data whose sampling rate is different according to the nature of signal. In this paper, a novel approach concerning geophysical multivariate time series clustering is proposed using dynamic time series segmentation and Self Organizing Maps techniques. This method allows finding coupling among trends of different geophysical data recorded from monitoring networks at Mt. Etna spanning from 1996 to 2003, when the transition from summit eruptions to flank eruptions occurred. This information can be used to carry out a more careful evaluation of the state of volcano and to define potential hazard assessment at Mt. Etna.

Sirenomelia in Argentina: Prevalence, geographic clusters and temporal trends analysis.

PubMed

Groisman, Boris; Liascovich, Rosa; Gili, Juan Antonio; Barbero, Pablo; Bidondo, María Paz

2016-07-01

Sirenomelia is a severe malformation of the lower body characterized by a single medial lower limb and a variable combination of visceral abnormalities. Given that Sirenomelia is a very rare birth defect, epidemiological studies are scarce. The aim of this study is to evaluate prevalence, geographic clusters and time trends of sirenomelia in Argentina, using data from the National Network of Congenital Anomalies of Argentina (RENAC) from November 2009 until December 2014. This is a descriptive study using data from the RENAC, a hospital-based surveillance system for newborns affected with major morphological congenital anomalies. We calculated sirenomelia prevalence throughout the period, searched for geographical clusters, and evaluated time trends. The prevalence of confirmed cases of sirenomelia throughout the period was 2.35 per 100,000 births. Cluster analysis showed no statistically significant geographical aggregates. Time-trends analysis showed that the prevalence was higher in years 2009 to 2010. The observed prevalence was higher than the observed in previous epidemiological studies in other geographic regions. We observed a likely real increase in the initial period of our study. We used strict diagnostic criteria, excluding cases that only had clinical diagnosis of sirenomelia. Therefore, real prevalence could be even higher. This study did not show any geographic clusters. Because etiology of sirenomelia has not yet been established, studies of epidemiological features of this defect may contribute to define its causes. Birth Defects Research (Part A) 106:604-611, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Impact of climate change on potential evapotranspiration (case study: west and NW of Iran)

NASA Astrophysics Data System (ADS)

Dinpashoh, Y.; Jahanbakhsh-Asl, S.; Rasouli, A. A.; Foroughi, M.; Singh, V. P.

2018-04-01

Potential evapotranspiration (ET0) is one of the main elements when computing agricultural irrigation requirements and scheduling. All climatic parameters as well as ET0 are influenced by climate change. The aim of this study is trend analysis of monthly and annual ET0 time series in the west and NW of Iran. Values of ET0 are estimated at 36 selected stations, using the FAO-56 Penman-Monteith (FAO-56 PM) method. Then, the non-parametric Mann-Kendall (MK) method was used to detect trends. The slopes of trend lines are estimated using Sen's estimator approach. Results showed that about 86%of the monthly ET0 time series had upward trends of which 35.6 and 43% were significant at 0.01 and 0.05 levels, respectively, 47.4% exhibited a significant upward trend at the 10% level. In contrast, less than 0.7% of the whole monthly ET0 time series showed a significant downward trend (α < 0.01). Only 1.1% of the monthly ET0 time series had significant downward trends (α < 0.10). The strongest positive upward trend (significant at the 0.01 level) was detected in August at the Kermanshah station. However, the strongest negative downward trend belonged to the Khodabandeh station. The steepest upward and downward monthly ET0 slopes were observed at Maragheh and Khodabandeh stations. The magnitude of trends for these two stations are estimated as 2.33 and - 2.01 mm/year, respectively. On an annual timescale, above 94% of the stations had upward trend slopes. About 67% of the total stations exhibited significant trends at the 10% level. Very few sites (2.7%) showed downward annual ET0 trends (α < 0.10). At the annual scale, the first three strongest upward trends belonged to the Kermanshah, Urmia, and Tabriz stations, respectively (α < 0.01). It can be concluded that ET0 in the west and NW of Iran have an increasing trend for most of the stations. Therefore, it is important to use water in a prudent manner in this area.

Trends in nitrate and dissolved-solids concentrations in ground water, Carson Valley, Douglas County, Nevada, 1985-2001

USGS Publications Warehouse

Rosen, Michael R.

2003-01-01

Analysis of trends in nitrate and total dissolved-solids concentrations over time in Carson Valley, Nevada, indicates that 56 percent of 27 monitoring wells that have long-term records of nitrate concentrations show increasing trends, 11 percent show decreasing trends, and 33 percent have not changed. Total dissolved-solids concentrations have increased in 52 percent of these wells and are stable in 48 percent. None of these wells show decreasing trends in total dissolved-solids concentrations. The wells showing increasing trends in nitrate and total dissolved-solids concentrations were always in areas that use septic waste-disposal systems. Therefore, the primary cause of these increases is likely the increase in septic-tank usage over the past 40 years.

[Trends of Tobacco and Alcohol Consumption over 65 Years in Germany].

PubMed

John, Ulrich; Hanke, Monika

2018-02-01

No estimation was available for tobacco and for alcohol consumption in Germany based on sales data that were provided for public use and suited for time trend analysis. To estimate trends of tobacco and alcohol consumption rates for the years 1950-2014. Data on tobacco and alcohol consumption in the nation were retrieved from reports made by producers of beer, wine, or spirits to the Federal Statistics Office of Germany. Time trends over the 65 years were calculated using the program Joinpoint. Tobacco consumption rose from 1950 to 1972. Thereafter it decreased, mostly by 1.2-6.9 percentage points per year. Alcohol consumption rose until the year 1974 and decreased thereafter by 1.0 percentage points annually until the end of the time period under analysis in 2014. The findings may be explained, among others, by changes of social norms according to smoking and alcohol consumption after tax increases, nonsmoker and youth protection laws, and legislative measures against driving under the influence of alcohol. A steepening of the decrease in tobacco consumption occurred after laws including tax increases had come into effect. However, the tobacco and alcohol consumption levels were still high at the end of the observation period in 2014. Eigentümer und Copyright ©Georg Thieme Verlag KG 2018.

Global Precipitation Analyses (3-Hourly to Monthly) Using TRMM, SSM/I and other Satellite Information

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Huffman, George; Curtis, Scott; Bolvin, David; Nelkin, Eric

2002-01-01

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM(Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the 20-year data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the 20 year period. Monthly anomalies of precipitation are related to ENS0 variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1 deg. latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is discussed. Finally, a TRMM-based 3-hr analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous IR observations and merges the various calibrated observations into a final, 3-hr resolution map. This TRMM standard product will be available for the entire TRMM period (January 1998-present). A real-time version of this merged product is being produced and is available at 0.25 deg. latitude-longitude resolution over the latitude range from 5O deg. N-50 deg. S. Examples are shown, including its use in monitoring flood conditions.

Effects of Author Contribution Disclosures and Numeric Limitations on Authorship Trends

PubMed Central

McDonald, Robert J.; Neff, Kevin L.; Rethlefsen, Melissa L.; Kallmes, David F.

2010-01-01

OBJECTIVE: To determine whether editorial policies designed to eliminate gratuitous authorship (globally referred to as authorship limitation policies), including author contribution disclosures and/or numeric restrictions, have significantly affected authorship trends during a 20-year period. METHODS: We used a custom PERL-based algorithm to extract data, including number of authors, publication date, and article subtype, from articles published from January 1, 1986, through December 31, 2006, in 16 medical journals (8 with explicit authorship guidelines restricting authorship and 8 without formal authorship policies), comprising 307,190 articles. Trends in the mean number of authors per article, sorted by journal type, article subtype, and presence of authorship limitations, were determined using Sen's slope analysis and compared using analysis of variance and matched-pair analysis. Trend data were compared among the journals that had implemented 1 or both of these formal restrictive authorship policies and those that had not in order to determine their effect on authorship over time. RESULTS: The number of authors per article has been increasing among all journals at a mean ± SD rate of 0.076±0.057 authors per article per year. No significant differences in authorship rate were observed between journals with and without authorship limits before enforcement (F=1.097; P=.30). After enforcement, no significant change in authorship rates was observed (matched pair: F=0.425; P=.79). CONCLUSION: Implementation of authorship limitation policies does not slow the trend of increasing numbers of authors per article over time. PMID:20884825

Hot spots, hot moments and time-span of changes in drivers and their responses on carbon cycling in Europe

NASA Astrophysics Data System (ADS)

Tomelleri, E.; Forkel, M.; Fuchs, R.; Jung, M.; Mahecha, M. D.; Reichstein, M.; Weber, U.

2012-12-01

The objective of this study is to provide a complete quantitative assessment of the annual to decadal variability, hotspots of changes and the temporal magnitude of regional trends and variability for the main drivers of carbon cycle like climate and land use and their responses for Europe. For this purpose we used an harmonized climatic data set (ERA Interim and WATCH) and an historical land-use change reconstruction (HILDAv1, Fuchs in prep.). Both the data sets cover the period 1900-2010 and have a 0.25 deg spatial resolution. As driver response we used two different empirically up-scaled GPP fields: the first (MTE) obtained by the application of model trees (Jung et al. 2009) and a second (LUE) based on a light use efficiency model (Tomelleri in prep.). Both the approaches are based on the up-scaling of Fluxnet observations. The response fields have monthly temporal resolution and are limited to the period 1982-2011. We estimated break-points in time series of driver and response variables based on the method of Bai and Perron (2003) to identify changes in trends. This method was implemented in Verbesselt et al. 2010 and applied by deJong et al. 2011 to detect phenological and abrupt changes and trends in vegetation activity based on satellite-derived vegetation index time series. The analysis of drivers and responses allowed to identify the dominant factors driving the biosphere-atmosphere carbon exchange. The synchronous analysis of climatic drivers and land use change allowed us to explain most of the temporal and spatial variability showing that in the regions and time period where the most land use change occurred the climatic drivers are not sufficient to explain trends and oscillation in carbon cycling. The comparison of our analysis for the up-scaling methods shows some agreement: we found inconsistency in the spatial and temporal patterns in regions where the Fluxnet network is less dense. This can be explained by the conceptual difference in the up-scaling methods: while one is on pixel basis (MTE) the other (LUE) is up-scaling model parameters by bioclimatic regions. Our study shows the value of up-scaling methods for understanding the spatial-temporal variability of carbon cycling and how these are a valuable tool for spatial and temporal analysis. Furthermore, the use of climatic drivers and land-use change demonstrated the need of taking natural and anthropogenic drivers into consideration for explaining trends and oscillations. Possibly a further analysis including detailed management practices for forestry and agriculture would help in explaining the remaining variance. References: Bai, J., Perron, P.: Computation and analysis of multiple structural change models. Journal of Applied Econometrics, 18(1), 2003. Jung, M., Reichstein, M., and Bondeau, A.: Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model. Biogeosciences, 6, 2009. Verbesselt, J., Hyndman, R., Newnham, G., Culvenor, D.: Detecting trend and seasonal changes in satellite image time series. Remote Sensing of Environment,114(1), 2010. de Jong, R., Verbesselt, J., Schaepman, M.E., Bruin, S.: Trend changes in global greening and browning: contribution of short-term trends to longer-term change. Global Change Biology, 18, 2011.

Trends in stratospheric ozone profiles using functional mixed models

NASA Astrophysics Data System (ADS)

Park, A. Y.; Guillas, S.; Petropavlovskikh, I.

2013-05-01

This paper is devoted to the modeling of altitude-dependent patterns of ozone variations over time. Umkher ozone profiles (quarter of Umkehr layer) from 1978 to 2011 are investigated at two locations: Boulder (USA) and Arosa (Switzerland). The study consists of two statistical stages. First we approximate ozone profiles employing an appropriate basis. To capture primary modes of ozone variations without losing essential information, a functional principal component analysis is performed as it penalizes roughness of the function and smooths excessive variations in the shape of the ozone profiles. As a result, data driven basis functions are obtained. Secondly we estimate the effects of covariates - month, year (trend), quasi biennial oscillation, the Solar cycle, arctic oscillation and the El Niño/Southern Oscillation cycle - on the principal component scores of ozone profiles over time using generalized additive models. The effects are smooth functions of the covariates, and are represented by knot-based regression cubic splines. Finally we employ generalized additive mixed effects models incorporating a more complex error structure that reflects the observed seasonality in the data. The analysis provides more accurate estimates of influences and trends, together with enhanced uncertainty quantification. We are able to capture fine variations in the time evolution of the profiles such as the semi-annual oscillation. We conclude by showing the trends by altitude over Boulder. The strongly declining trends over 2003-2011 for altitudes of 32-64 hPa show that stratospheric ozone is not yet fully recovering.

Accounting for variation in designing greenhouse experiments with special reference to greenhouses containing plants on conveyor systems

PubMed Central

2013-01-01

Background There are a number of unresolved issues in the design of experiments in greenhouses. They include whether statistical designs should be used and, if so, which designs should be used. Also, are there thigmomorphogenic or other effects arising from the movement of plants on conveyor belts within a greenhouse? A two-phase, single-line wheat experiment involving four tactics was conducted in a conventional greenhouse and a fully-automated phenotyping greenhouse (Smarthouse) to investigate these issues. Results and discussion Analyses of our experiment show that there was a small east–west trend in total area of the plants in the Smarthouse. Analyses of the data from three multiline experiments reveal a large north–south trend. In the single-line experiment, there was no evidence of differences between trios of lanes, nor of movement effects. Swapping plant positions during the trial was found to decrease the east–west trend, but at the cost of increased error variance. The movement of plants in a north–south direction, through a shaded area for an equal amount of time, nullified the north–south trend. An investigation of alternative experimental designs for equally-replicated experiments revealed that generally designs with smaller blocks performed best, but that (nearly) trend-free designs can be effective when blocks are larger. Conclusions To account for variation in microclimate in a greenhouse, using statistical design and analysis is better than rearranging the position of plants during the experiment. For the relocation of plants to be successful requires that plants spend an equal amount of time in each microclimate, preferably during comparable growth stages. Even then, there is no evidence that this will be any more precise than statistical design and analysis of the experiment, and the risk is that it will not be successful at all. As for statistical design and analysis, it is best to use either (i) smaller blocks, (ii) (nearly) trend-free arrangement of treatments with a linear trend term included in the analysis, or, as a last resort, (iii) blocks of several complete rows with trend terms in the analysis. Also, we recommend that the greenhouse arrangement parallel that in the Smarthouse, but with randomization where appropriate. PMID:23391282

Impact of Ten-Valent Pneumococcal Conjugate Vaccine Introduction on Serotype Distribution Trends in Colombia: An Interrupted Time-Series Analysis

PubMed Central

Leal, Aura Lucia; Montañez, Anita Maria; Buitrago, Giancarlo; Patiño, Jaime; Camacho, German; Moreno, Vivian Marcela; Colombia, Red Neumo

2017-01-01

Abstract Background Trends in distribution of S. pneumoniae capsular serotypes are associated with the introduction of pneumococcal conjugate vaccines (PCV) among population. In Colombia, 10-valent PCV (PCV10) has been included in the national vaccination program since 2011. As a part of the pneumococcal surveillance network (SIREVA), Colombia has gathered data of serotype distribution since 1993. The aim of this work is to determine the effect of PCV10 introduction on non-coverage serotypes by PCV10 in Colombia, specifically, the effect on 6A, 19A and 3 serotypes. Methods Information was obtained from the national surveillance program since 1993 to 2016 in children under 5 years. The isolates came from sterile sites (blood, cerebrospinal fluid, pleural fluid, articular and peritoneal fluids). All the isolates were serotyping by National Institute of Health. An interrupted time series analysis was performed to determine the effect of the PCV10 introduction on the 6A, 19A and 3 serotypes (ARIMA model). Results Serotyping was performed in 4683 isolates. The annual proportion trend of the 6A, 19A and 3 serotypes remained constant until 2012. An increase of double in the serotype proportion trends was observed after 2012 (Figure). The interrupted time-series analysis showed a positive effect of the PCV10 introduction on trends of 19A and 3 serotypes, with coefficients 20.92 (P = 0.00, ARIMA(2,0,1)) and 6.32 (P = 0.00, ARIMA(2,1,1), respectively. There was no significant effect on 6A serotype trend. Conclusion The introduction of PCV10 in the national vaccination program in Colombia, affected the distribution of PVC 13 capsular types non included in the PCV 7 and PCV 10 in children under 5 years. This information emphasizes the importance to surveillance the changes in serotype distributions to guide prevention strategies in children under 5 years in Colombia. Figure. 1 Trends in distribution of serotypes 19A, 3 and 6A in children under 5 years. Colombia. Disclosures All authors: No reported disclosures.

Using NASA's Giovanni System to Simulate Time-Series Stations in the Outflow Region of California's Eel River

NASA Technical Reports Server (NTRS)

Acker, James G.; Shen, Suhung; Leptoukh, Gregory G.; Lee, Zhongping

2012-01-01

Oceanographic time-series stations provide vital data for the monitoring of oceanic processes, particularly those associated with trends over time and interannual variability. There are likely numerous locations where the establishment of a time-series station would be desirable, but for reasons of funding or logistics, such establishment may not be feasible. An alternative to an operational time-series station is monitoring of sites via remote sensing. In this study, the NASA Giovanni data system is employed to simulate the establishment of two time-series stations near the outflow region of California s Eel River, which carries a high sediment load. Previous time-series analysis of this location (Acker et al. 2009) indicated that remotely-sensed chl a exhibits a statistically significant increasing trend during summer (low flow) months, but no apparent trend during winter (high flow) months. Examination of several newly-available ocean data parameters in Giovanni, including 8-day resolution data, demonstrates the differences in ocean parameter trends at the two locations compared to regionally-averaged time-series. The hypothesis that the increased summer chl a values are related to increasing SST is evaluated, and the signature of the Eel River plume is defined with ocean optical parameters.

Leukemia in Iran: Epidemiology and Morphology Trends.

PubMed

Koohi, Fatemeh; Salehiniya, Hamid; Shamlou, Reza; Eslami, Soheyla; Ghojogh, Ziyaeddin Mahery; Kor, Yones; Rafiemanesh, Hosein

2015-01-01

Leukemia accounts for 8% of total cancer cases and involves all age groups with different prevalence and incidence rates in Iran and the entire world and causes a significant death toll and heavy expenses for diagnosis and treatment processes. This study was done to evaluate epidemiology and morphology of blood cancer during 2003-2008. This cross- sectional study was carried out based on re- analysis of the Cancer Registry Center report of the Health Deputy in Iran during a 6-year period (2003 - 2008). Statistical analysis for incidence time trends and morphology change percentage was performed with joinpoint regression analysis using the software Joinpoint Regression Program. During the studied years a total of 18,353 hematopoietic and reticuloendothelial system cancers were recorded. Chi square test showed significant difference between sex and morphological types of blood cancer (P-value<0.001). Joinpoint analysis showed a significant increasing trend for the adjusted standard incidence rate (ASIR) for both sexes (P-value<0.05). Annual percent changes (APC) for women and men were 18.7 and 19.9, respectively. The most common morphological blood cancers were ALL, ALM, MM and CLL which accounted for 60% of total hematopoietic system cancers. Joinpoint analyze showed a significant decreasing trend for ALM in both sexes (P-value<0.05). Hematopoietic system cancers in Iran demonstrate an increasing trend for incidence rate and decreasing trend for ALL, ALM and CLL morphology.

Modern trends in Class III orthognathic treatment: A time series analysis.

PubMed

Lee, Chang-Hoon; Park, Hyun-Hee; Seo, Byoung-Moo; Lee, Shin-Jae

2017-03-01

To examine the current trends in surgical-orthodontic treatment for patients with Class III malocclusion using time-series analysis. The records of 2994 consecutive patients who underwent orthognathic surgery from January 1, 2004, through December 31, 2015, at Seoul National University Dental Hospital, Seoul, Korea, were reviewed. Clinical data from each surgical and orthodontic treatment record included patient's sex, age at the time of surgery, malocclusion classification, type of orthognathic surgical procedure, place where the orthodontic treatment was performed, orthodontic treatment modality, and time elapsed for pre- and postoperative orthodontic treatment. Out of the orthognathic surgery patients, 86% had Class III malocclusion. Among them, two-jaw surgeries have become by far the most common orthognathic surgical treatment these days. The age at the time of surgery and the number of new patients had seasonal variations, which demonstrated opposing patterns. There was neither positive nor negative correlation between pre- and postoperative orthodontic treatment time. Elapsed orthodontic treatment time for both before and after Class III orthognathic surgeries has been decreasing over the years. Results of the time series analysis might provide clinicians with some insights into current surgical and orthodontic management.

Estimation of trends

NASA Technical Reports Server (NTRS)

1981-01-01

The application of statistical methods to recorded ozone measurements. The effects of a long term depletion of ozone at magnitudes predicted by the NAS is harmful to most forms of life. Empirical prewhitening filters the derivation of which is independent of the underlying physical mechanisms were analyzed. Statistical analysis performs a checks and balances effort. Time series filters variations into systematic and random parts, errors are uncorrelated, and significant phase lag dependencies are identified. The use of time series modeling to enhance the capability of detecting trends is discussed.

Launch commit criteria performance trending analysis, phase 1, revision A. SRM and QA mission services

NASA Technical Reports Server (NTRS)

1989-01-01

An assessment of quantitative methods and measures for measuring launch commit criteria (LCC) performance measurement trends is made. A statistical performance trending analysis pilot study was processed and compared to STS-26 mission data. This study used four selected shuttle measurement types (solid rocket booster, external tank, space shuttle main engine, and range safety switch safe and arm device) from the five missions prior to mission 51-L. After obtaining raw data coordinates, each set of measurements was processed to obtain statistical confidence bounds and mean data profiles for each of the selected measurement types. STS-26 measurements were compared to the statistical data base profiles to verify the statistical capability of assessing occurrences of data trend anomalies and abnormal time-varying operational conditions associated with data amplitude and phase shifts.

SWMPr: An R Package for Retrieving, Organizing, and ...

EPA Pesticide Factsheets

The System-Wide Monitoring Program (SWMP) was implemented in 1995 by the US National Estuarine Research Reserve System. This program has provided two decades of continuous monitoring data at over 140 fixed stations in 28 estuaries. However, the increasing quantity of data provided by the monitoring network has complicated broad-scale comparisons between systems and, in some cases, prevented simple trend analysis of water quality parameters at individual sites. This article describes the SWMPr package that provides several functions that facilitate data retrieval, organization, andanalysis of time series data in the reserve estuaries. Previously unavailable functions for estuaries are also provided to estimate rates of ecosystem metabolism using the open-water method. The SWMPr package has facilitated a cross-reserve comparison of water quality trends and links quantitative information with analysis tools that have use for more generic applications to environmental time series. The manuscript describes a software package that was recently developed to retrieve, organize, and analyze monitoring data from the National Estuarine Research Reserve System. Functions are explained in detail, including recent applications for trend analysis of ecosystem metabolism.

Anomaly Trends for Missions to Mars: Mars Global Surveyor and Mars Odyssey

NASA Technical Reports Server (NTRS)

Green, Nelson W.; Hoffman, Alan R.

2008-01-01

The long term flight operations of the Mars Global Surveyor and Mars Odyssey spacecraft give us an excellent chance to examine the operations of two long lived spacecraft in orbit around Mars during overlapping time periods. This study examined the anomalies for each mission maintained for NASA at the Jet Propulsion Laboratory. By examining the anomalies each mission encountered during their multiyear missions, trends were identified related to when anomalies occurred during each mission, the types of anomalies encountered, and corrective actions taken to mitigate the effects of the anomalies. As has been discovered in previous studies the numbers of anomalies directly correlate with mission activity and show a decreasing trend with elapsed mission time. Trend analysis also identified a heavy emphasis on software as the source or solution to anomalies for both missions.

Applying the Pseudo-Panel Approach to International Large-Scale Assessments: A Methodology for Analyzing Subpopulation Trend Data

ERIC Educational Resources Information Center

Hooper, Martin

2017-01-01

TIMSS and PIRLS assess representative samples of students at regular intervals, measuring trends in student achievement and student contexts for learning. Because individual students are not tracked over time, analysis of international large-scale assessment data is usually conducted cross-sectionally. Gustafsson (2007) proposed examining the data…

Old Words, New Meanings: A Study of Trends in Science Librarian Job Ads

ERIC Educational Resources Information Center

Bychowski, Brenna K. H.; Caffrey, Carolyn M.; Costa, Mia C.; Moore, Angela D.; Sudhakaran, Jessamyn; Zhang, Yuening

2010-01-01

Job ads are supposed to provide careful descriptions of the positions being advertised. Based on this premise, an analysis of job ads over time should reveal emerging trends and changes in a profession. The existing literature on science librarianship emphasizes that there are fluctuations in the demand for subject expertise and technology skills…

77 FR 47383 - Annual Assessment of the Status of Competition in the Market for the Delivery of Video Programming

Federal Register 2010, 2011, 2012, 2013, 2014

2012-08-08

... monitor trends on an annual basis. To continue our time-series analysis, we request data as of June 30... information and time- series data we should collect for the analysis of various MVPD performance metrics. In... revenues, cash flows, and margins. To the extent possible, we seek five-year time-series data to allow us...

Time for children: trends in the employment patterns of parents, 1967-2009.

PubMed

Fox, Liana; Han, Wen-Jui; Ruhm, Christopher; Waldfogel, Jane

2013-02-01

Using data from the 1967-2009 years of the March Current Population Surveys (CPS), we examine two important resources for children's well-being: time and money. We document trends in parental employment, from the perspective of children, and show what underlies these trends. We find that increases in family work hours mainly reflect movements into jobs by parents-particularly mothers, who in prior decades would have remained at home. This increase in market work has raised incomes for children in the typical two-parent family but not for those in lone-parent households. Time use data from 1975 and 2003-2008 reveal that working parents spend less time engaged in primary childcare than their counterparts without jobs but more than employed peers in previous cohorts. Analysis of 2004 work schedule data suggests that non-daytime work provides an alternative method of coordinating employment schedules for some dual-earner families.

Real-time on-line space research laboratory environment monitoring with off-line trend and prediction analysis

NASA Astrophysics Data System (ADS)

Jules, Kenol; Lin, Paul P.

2007-06-01

With the International Space Station currently operational, a significant amount of acceleration data is being down-linked, processed and analyzed daily on the ground on a continuous basis for the space station reduced gravity environment characterization, the vehicle design requirements verification and science data collection. To help understand the impact of the unique spacecraft environment on the science data, an artificial intelligence monitoring system was developed, which detects in near real time any change in the reduced gravity environment susceptible to affect the on-going experiments. Using a dynamic graphical display, the monitoring system allows science teams, at any time and any location, to see the active vibration disturbances, such as pumps, fans, compressor, crew exercise, re-boost and extra-vehicular activities that might impact the reduced gravity environment the experiments are exposed to. The monitoring system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many increments (an increment usually lasts 6 months) collected onboard the station for selected disturbances. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential systems failures. The monitoring system has two operating modes: online and offline. Both near real-time on-line vibratory disturbance detection and off-line detection and trend analysis are discussed in this paper.

Trends in mouth cancer incidence in Mumbai, India (1995-2009): An age-period-cohort analysis.

PubMed

Shridhar, Krithiga; Rajaraman, Preetha; Koyande, Shravani; Parikh, Purvish M; Chaturvedi, Pankaj; Dhillon, Preet K; Dikshit, Rajesh P

2016-06-01

Despite tobacco control and health promotion efforts, the incidence rates of mouth cancer are increasing across most regions in India. Analysing the influence of age, time period and birth cohort on these secular trends can point towards underlying factors and help identify high-risk populations for improved cancer control programmes. We evaluated secular changes in mouth cancer incidence among men and women aged 25-74 years in Mumbai between 1995 and 2009 by calculating age-specific and age-standardized incidence rates (ASR). We estimated the age-adjusted linear trend for annual percent change (EAPC) using the drift parameter, and conducted an age-period-cohort (APC) analysis to quantify recent time trends and to evaluate the significance of birth cohort and calendar period effects. Over the 15-year period, age-standardized incidence rates of mouth cancer in men in Mumbai increased by 2.7% annually (95% CI:1.9 to 3.4), p<0.0001) while rates among women decreased (EAPC=-0.01% (95% CI:-0.02 to -0.002), p=0.03). APC analysis revealed significant non-linear positive period and cohort effects in men, with higher effects among younger men (25-49 years). Non-significant increasing trends were observed in younger women (25-49 years). APC analyses from the Mumbai cancer registry indicate a significant linear increase of mouth cancer incidence from 1995 to 2009 in men, which was driven by younger men aged 25-49 years, and a non-significant upward trend in similarly aged younger women. Health promotion efforts should more effectively target younger cohorts. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Statistical evaluation of rainfall time series in concurrence with agriculture and water resources of Ken River basin, Central India (1901-2010)

NASA Astrophysics Data System (ADS)

Meshram, Sarita Gajbhiye; Singh, Sudhir Kumar; Meshram, Chandrashekhar; Deo, Ravinesh C.; Ambade, Balram

2017-12-01

Trend analysis of long-term rainfall records can be used to facilitate better agriculture water management decision and climate risk studies. The main objective of this study was to identify the existing trends in the long-term rainfall time series over the period 1901-2010 utilizing 12 hydrological stations located at the Ken River basin (KRB) in Madhya Pradesh, India. To investigate the different trends, the rainfall time series data were divided into annual and seasonal (i.e., pre-monsoon, monsoon, post-monsoon, and winter season) sub-sets, and a statistical analysis of data using the non-parametric Mann-Kendall (MK) test and the Sen's slope approach was applied to identify the nature of the existing trends in rainfall series for the Ken River basin. The obtained results were further interpolated with the aid of the Quantum Geographic Information System (GIS) approach employing the inverse distance weighted approach. The results showed that the monsoon and the winter season exhibited a negative trend in rainfall changes over the period of study, and this was true for all stations, although the changes during the pre- and the post-monsoon seasons were less significant. The outcomes of this research study also suggest significant decreases in the seasonal and annual trends of rainfall amounts in the study period. These findings showing a clear signature of climate change impacts on KRB region potentially have implications in terms of climate risk management strategies to be developed during major growing and harvesting seasons and also to aid in the appropriate water resource management strategies that must be implemented in decision-making process.

Patterns in Patient Access and Utilization of Online Medical Records: Analysis of MyChart.

PubMed

Redelmeier, Donald A; Kraus, Nicole C

2018-02-06

Electronic patient portals provide a new method for sharing personal medical information with individual patients. Our aim was to review utilization patterns of the largest online patient portal in Canada's largest city. We conducted a 4-year time-trend analysis of aggregated anonymous utilization data of the MyChart patient portal at Sunnybrook Health Sciences Centre in Ontario, Canada, from January 1, 2012, through December 31, 2015. Prespecified analyses examined trends related to day (weekend vs weekday), season (July vs January), year (2012 vs 2015), and an extreme adverse weather event (ice storm of December 20-26, 2013). Primary endpoints included three measures of patient portal activity: registrations, logins, and pageviews. We identified 32,325 patients who registered for a MyChart account during the study interval. Time-trend analysis showed no sign of attenuating registrations over time. Logins were frequent, averaged 734 total per day, and showed an increasing trend over time. Pageviews mirrored logins, averaged about 3029 total per day, and equated to about 5 pageviews during the average login. The most popular pageviews were clinical notes, followed by laboratory results and medical imaging reports. All measures of patient activity were lower on weekends compared to weekdays (P<.001) yet showed no significant changes related to seasons or extreme weather. No major security breach, malware attack, or software failure occurred during the study. Online patient portals can provide a popular and reliable system for distributing personal medical information to active patients and may merit consideration for hospitals. ©Donald A Redelmeier, Nicole C Kraus. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 06.02.2018.

Linear and nonlinear trending and prediction for AVHRR time series data

NASA Technical Reports Server (NTRS)

Smid, J.; Volf, P.; Slama, M.; Palus, M.

1995-01-01

The variability of AVHRR calibration coefficient in time was analyzed using algorithms of linear and non-linear time series analysis. Specifically we have used the spline trend modeling, autoregressive process analysis, incremental neural network learning algorithm and redundancy functional testing. The analysis performed on available AVHRR data sets revealed that (1) the calibration data have nonlinear dependencies, (2) the calibration data depend strongly on the target temperature, (3) both calibration coefficients and the temperature time series can be modeled, in the first approximation, as autonomous dynamical systems, (4) the high frequency residuals of the analyzed data sets can be best modeled as an autoregressive process of the 10th degree. We have dealt with a nonlinear identification problem and the problem of noise filtering (data smoothing). The system identification and filtering are significant problems for AVHRR data sets. The algorithms outlined in this study can be used for the future EOS missions. Prediction and smoothing algorithms for time series of calibration data provide a functional characterization of the data. Those algorithms can be particularly useful when calibration data are incomplete or sparse.

Time-dependent analysis of dosage delivery information for patient-controlled analgesia services.

PubMed

Kuo, I-Ting; Chang, Kuang-Yi; Juan, De-Fong; Hsu, Steen J; Chan, Chia-Tai; Tsou, Mei-Yung

2018-01-01

Pain relief always plays the essential part of perioperative care and an important role of medical quality improvement. Patient-controlled analgesia (PCA) is a method that allows a patient to self-administer small boluses of analgesic to relieve the subjective pain. PCA logs from the infusion pump consisted of a lot of text messages which record all events during the therapies. The dosage information can be extracted from PCA logs to provide easily understanding features. The analysis of dosage information with time has great help to figure out the variance of a patient's pain relief condition. To explore the trend of pain relief requirement, we developed a PCA dosage information generator (PCA DIG) to extract meaningful messages from PCA logs during the first 48 hours of therapies. PCA dosage information including consumption, delivery, infusion rate, and the ratio between demand and delivery is presented with corresponding values in 4 successive time frames. Time-dependent statistical analysis demonstrated the trends of analgesia requirements decreased gradually along with time. These findings are compatible with clinical observations and further provide valuable information about the strategy to customize postoperative pain management.

The Use of Categorized Time-Trend Reporting of Radiation Oncology Incidents: A Proactive Analytical Approach to Improving Quality and Safety Over Time

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

Arnold, Anthony, E-mail: anthony.arnold@sesiahs.health.nsw.gov.a; Delaney, Geoff P.; Cassapi, Lynette

Purpose: Radiotherapy is a common treatment for cancer patients. Although incidence of error is low, errors can be severe or affect significant numbers of patients. In addition, errors will often not manifest until long periods after treatment. This study describes the development of an incident reporting tool that allows categorical analysis and time trend reporting, covering first 3 years of use. Methods and Materials: A radiotherapy-specific incident analysis system was established. Staff members were encouraged to report actual errors and near-miss events detected at prescription, simulation, planning, or treatment phases of radiotherapy delivery. Trend reporting was reviewed monthly. Results: Reportsmore » were analyzed for the first 3 years of operation (May 2004-2007). A total of 688 reports was received during the study period. The actual error rate was 0.2% per treatment episode. During the study period, the actual error rates reduced significantly from 1% per year to 0.3% per year (p < 0.001), as did the total event report rates (p < 0.0001). There were 3.5 times as many near misses reported compared with actual errors. Conclusions: This system has allowed real-time analysis of events within a radiation oncology department to a reduced error rate through focus on learning and prevention from the near-miss reports. Plans are underway to develop this reporting tool for Australia and New Zealand.« less

Recent Decline in Extratropical Lower Stratospheric Ozone Attributed to Circulation Changes

NASA Astrophysics Data System (ADS)

Wargan, Krzysztof; Orbe, Clara; Pawson, Steven; Ziemke, Jerald R.; Oman, Luke D.; Olsen, Mark A.; Coy, Lawrence; Emma Knowland, K.

2018-05-01

The 1998-2016 ozone trends in the lower stratosphere are examined using the Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) and related National Aeronautics and Space Administration products. After removing biases resulting from step changes in the MERRA-2 ozone observations, a discernible negative trend of -1.67 ± 0.54 Dobson units per decade (DU/decade) is found in the 10-km layer above the tropopause between 20°N and 60°N. A weaker but statistically significant trend of -1.17 ± 0.33 DU/decade exists between 50°S and 20°S. In the Tropics, a positive trend is seen in a 5-km layer above the tropopause. Analysis of an idealized tracer in a model simulation constrained by MERRA-2 meteorological fields provides strong evidence that these trends are driven by enhanced isentropic transport between the tropical (20°S-20°N) and extratropical lower stratosphere in the past two decades. This is the first time that a reanalysis data set has been used to detect and attribute trends in lower stratospheric ozone.

Trends in Condom Use and Risk Behaviours after Sexual Exposure to HIV: A Seven-Year Observational Study

PubMed Central

Casalino, Enrique; Choquet, Christophe; Leleu, Agathe; Hellmann, Romain; Wargon, Mathias; Juillien, Gaelle; Yazdanpanah, Yazdan; Bouvet, Elisabeth

2014-01-01

Objective We aimed to determine the trends in numbers and percentages of sexually exposed persons to HIV (SE) consulting an ED for post-exposure prophylaxis (PEP), as well as predictors of condom use. Study Design We conducted a prospective-observational study. Methods We included all SE attendances in our Emergency Department (ED) during a seven-year study-period (2006–2012). Trends were analyzed using time-series analysis. Logistic Regression was used to define indicators of condom use. Results We enrolled 1851 SE: 45.7% reported intercourse without condom-use and 12.2% with an HIV-infected partner. Significant (p<0.01) rising trends were observed in the overall number of SE visits (+75%), notably among men having sex with men (MSM) (+126%). There were rising trends in the number and percentage of those reporting intercourse without condom-use in the entire population +91% (p<0.001) and +1% (p>0.05), in MSM +228% (p<0.001) and +49% (p<0.001), in Heterosexuals +68% (p<0.001) and +10% (p = 0.08). Among MSM, significant rising trends were found in those reporting high-risk behaviours: anal receptive (+450% and +76%) and anal insertive (+l33% and +70%) intercourses. In a multivariate logistic regression analysis, heterosexuals, vaginal intercourse, visit during the night-shift and short time delay between SE and ED visit, were significantly associated with condom-use. Conclusion We report an increasing trend in the number of SE, mainly among MSM, and rising trends in high-risk behaviours and unprotected sexual intercourses among MSM. Our results indicate that SE should be considered as a high-risk population for HIV and sexually transmitted diseases. PMID:25157477

Estimating Water Levels with Google Earth Engine

NASA Astrophysics Data System (ADS)

Lucero, E.; Russo, T. A.; Zentner, M.; May, J.; Nguy-Robertson, A. L.

2016-12-01

Reservoirs serve multiple functions and are vital for storage, electricity generation, and flood control. For many areas, traditional ground-based reservoir measurements may not be available or data dissemination may be problematic. Consistent monitoring of reservoir levels in data-poor areas can be achieved through remote sensing, providing information to researchers and the international community. Estimates of trends and relative reservoir volume can be used to identify water supply vulnerability, anticipate low power generation, and predict flood risk. Image processing with automated cloud computing provides opportunities to study multiple geographic areas in near real-time. We demonstrate the prediction capability of a cloud environment for identifying water trends at reservoirs in the US, and then apply the method to data-poor areas in North Korea, Iran, Azerbaijan, Zambia, and India. The Google Earth Engine cloud platform hosts remote sensing data and can be used to automate reservoir level estimation with multispectral imagery. We combine automated cloud-based analysis from Landsat image classification to identify reservoir surface area trends and radar altimetry to identify reservoir level trends. The study estimates water level trends using three years of data from four domestic reservoirs to validate the remote sensing method, and five foreign reservoirs to demonstrate the method application. We report correlations between ground-based reservoir level measurements in the US and our remote sensing methods, and correlations between the cloud analysis and altimetry data for reservoirs in data-poor areas. The availability of regular satellite imagery and an automated, near real-time application method provides the necessary datasets for further temporal analysis, reservoir modeling, and flood forecasting. All statements of fact, analysis, or opinion are those of the author and do not reflect the official policy or position of the Department of Defense or any of its components or the U.S. Government

Precipitation climatology over India: validation with observations and reanalysis datasets and spatial trends

NASA Astrophysics Data System (ADS)

Kishore, P.; Jyothi, S.; Basha, Ghouse; Rao, S. V. B.; Rajeevan, M.; Velicogna, Isabella; Sutterley, Tyler C.

2016-01-01

Changing rainfall patterns have significant effect on water resources, agriculture output in many countries, especially the country like India where the economy depends on rain-fed agriculture. Rainfall over India has large spatial as well as temporal variability. To understand the variability in rainfall, spatial-temporal analyses of rainfall have been studied by using 107 (1901-2007) years of daily gridded India Meteorological Department (IMD) rainfall datasets. Further, the validation of IMD precipitation data is carried out with different observational and different reanalysis datasets during the period from 1989 to 2007. The Global Precipitation Climatology Project data shows similar features as that of IMD with high degree of comparison, whereas Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation data show similar features but with large differences, especially over northwest, west coast and western Himalayas. Spatially, large deviation is observed in the interior peninsula during the monsoon season with National Aeronautics Space Administration-Modern Era Retrospective-analysis for Research and Applications (NASA-MERRA), pre-monsoon with Japanese 25 years Re Analysis (JRA-25), and post-monsoon with climate forecast system reanalysis (CFSR) reanalysis datasets. Among the reanalysis datasets, European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) shows good comparison followed by CFSR, NASA-MERRA, and JRA-25. Further, for the first time, with high resolution and long-term IMD data, the spatial distribution of trends is estimated using robust regression analysis technique on the annual and seasonal rainfall data with respect to different regions of India. Significant positive and negative trends are noticed in the whole time series of data during the monsoon season. The northeast and west coast of the Indian region shows significant positive trends and negative trends over western Himalayas and north central Indian region.

Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks

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

Jin, R; McCallen, S; Almaas, E

2007-05-28

Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of complex networks have mainly focused on their network topology. However, in many real world applications, the edges and vertices have associated attributes that are frequently represented as vertex or edge weights. Furthermore, these weights are often not static, instead changing with time and forming a time series. Hence, to fully understand the dynamics of the complex network, we have to consider both network topology and related time series data. In this work, we propose a motifmore » mining approach to identify trend motifs for such purposes. Simply stated, a trend motif describes a recurring subgraph where each of its vertices or edges displays similar dynamics over a userdefined period. Given this, each trend motif occurrence can help reveal significant events in a complex system; frequent trend motifs may aid in uncovering dynamic rules of change for the system, and the distribution of trend motifs may characterize the global dynamics of the system. Here, we have developed efficient mining algorithms to extract trend motifs. Our experimental validation using three disparate empirical datasets, ranging from the stock market, world trade, to a protein interaction network, has demonstrated the efficiency and effectiveness of our approach.« less

Prevalence of Smoking in Movies As Perceived by Teenagers

PubMed Central

Choi, Kelvin; Forster, Jean L.; Erickson, Darin J.; Lazovich, DeAnn; Southwell, Brian G.

2011-01-01

Background Smoking in movies is prevalent. However, use of content analysis to describe trends in smoking in movies has provided mixed results and has not tapped what adolescents actually perceive. Purpose To assess the prospective trends in the prevalence of smoking in movies as perceived by teenagers, and identify predictors associated with these trends. Methods Using data from the Minnesota Adolescent Community Cohort Study collected during 2000–2006 when participants were aged between 12 and 18 years (N=4735), latent variable growth models were employed to describe the longitudinal trends in the perceived prevalence of smoking in movies using a 4-level scale (never to most of the time) measured every 6 months, and examined associations between these trends and demographic, smoking-related attitudinal and socio-environmental predictors. Analysis was conducted in 2009. Results At baseline, about 50% of participants reported seeing smoking in movies “some of the time”, and another 36% reported “most of the time”. The prevalence of smoking in movies as perceived by teenagers declined over time, and the decline was steeper in those who were aged 14–16 years than those who were younger at baseline (p≤0.05). Despite the decline, teenagers still reported seeing smoking in movies some of the time. Teenagers who reported more close friends who smoked also reported a higher prevalence of smoking in movies at baseline (regression coefficients: 0.04–0.18, p<0.01). Conclusions Teenagers' perception of the prevalence of smoking in movies declined over time, which may be attributable to changes made by the movie industry. Despite the decline, teenagers were still exposed to a moderate amount of smoking imagery. Interventions that further reduce teenage exposure to smoking in movies may be needed to have an effect on adolescent smoking. PMID:21767724

Recent lung cancer mortality trends in Europe: effect of national smoke-free legislation strengthening.

PubMed

López-Campos, Jose L; Ruiz-Ramos, Miguel; Fernandez, Esteve; Soriano, Joan B

2018-07-01

The impact of smoke-free legislation within European Union (EU) countries on lung cancer mortality has not been evaluated to date. We aimed to determine lung cancer mortality trends in the EU-27 by sex, age, and calendar year for the period of 1994 and 2012, and relate them with changes in tobacco legislation at the national level. Deaths by Eurostat in each European country were analyzed, focusing on ICD-10 codes C33 and C34 from the years 1994 to 2012. Age-standardized mortality rates (ASR) were estimated separately for women and men in the EU-27 total and within country for each one of the years studied, and the significance of changing trends was estimated by joinpoint regression analysis, exploring lag times after initiation of smoke-free legislation in every country, if any. From 1994 to 2012, there were 4 681 877 deaths from lung cancer in Europe (3 491 607 in men and 1 190 180 in women) and a nearly linear decrease in mortality rates because of lung cancer in men from was observed1994 to 2012, mirrored in women by an upward trend, narrowing the sex gap during the study period from 5.1 in 1994 to 2.8 in 2012. Joinpoint regression analysis identified a number of trend changes over time, but it appears that they were unrelated to the implementation of smoke-free legislations. A few years after the introduction of smoke-free legislations across Europe, trends of lung cancer mortality trends have not changed.

Water-quality trends in the nation's rivers

USGS Publications Warehouse

Smith, R.A.; Alexander, R.B.; Wolman, M.G.

1987-01-01

Water-quality records from two nationwide sampling networks now permit nationally consistent analysis of long-term water-quality trends at more than 300 locations on major U.S. rivers. Observed trends in 24 measures of water quality for the period from 1974 to 1981 provide new insight into changes in stream quality that occurred during a time of major changes in both terrestrial and atmospheric influences on surface waters. Particularly noteworthy are widespread decreases in fecal bacteria and lead concentrations and widespread increases in nitrate, chloride, arsenic, and cadmium concentrations. Recorded increases in municipal waste treatment, use of salt on highways, and nitrogen fertilizer application, along with decreases in leaded gasoline consumption and regionally variable trends in coal production and combustion during the period appear to be reflected in water-quality changes.Water-quality records from two nationwide sampling networks now permit nationally consistent analysis of long-term water-quality trends at more than 300 locations on major U. S. rivers. Observed trends in 24 measures of water quality for the period from 1974 to 1981 provide new insight into changes in stream quality that occurred during a time of major changes in both terrestrial and atmospheric influences on surface waters. Particularly noteworthy are widespread decreases in fecal bacteria and lead concentrations and widespread increases in nitrate, chloride, arsenic, and cadmium concentrations. Recorded increases in municipal waste treatment, use of salt on highways, and nitrogen fertilizer application, along with decreases in leaded gasoline consumption and regionally variable trends in coal production and combustion during the period appear to be reflected in water-quality changes.

50 CFR 600.315 - National Standard 2-Scientific Information.

Code of Federal Regulations, 2014 CFR

2014-10-01

...., abundance, environmental, catch statistics, market and trade trends) provide time-series information on... comment should be solicited at appropriate times during the review of scientific information... information or the promise of future data collection or analysis. In some cases, due to time constraints...

Dry spell trend analysis in Kenya and the Murray Darling Basin using daily rainfall

NASA Astrophysics Data System (ADS)

Muita, R. R.; van Ogtrop, F. F.; Vervoort, R. W.

2012-04-01

Important agricultural areas in Kenya and the Murray Darling Basin (MDB) in Australia are largely semi-arid to arid. Persistent dry periods and timing of dry spells directly impact the availability of soil moisture and hence crop production in these regions. Most studies focus on the analysis of dry spell lengths at an annual scale. However, timing and length of dry spells at finer temporal scales is more beneficial for cropping when considering a trade-off between the time scale and the ability to analyse dry spell length. The aim of this study was to analyse the interannual and intra annual variations in dry spell lengths in the regions to inform crop management. This study analysed monthly dry spells based on daily rainfall for 1961-2010 on a limited dataset of 13 locations in Kenya and 17 locations in the MDB. This dataset was the most consistent across both regions and future analysis will incorporate more stations and longer time periods where available. Dry spell lengths were analysed by month and year and trends in monthly and annual dry spell lengths were analysed using Generalised Linear Models (GLM) and the Mann Kendall test (MK). Overall, monthly dryspell lengths are right skewed with higher frequency of shorter dryspells (3-25 days). In Kenya, significant increases in mean dry spell lengths (p≤0.02) are observed in inland arid-to semi humid locations but this temporal trend appears to decrease in highland and the coastal regions. Analysis of the MDB stations suggests changes in seasonality. For example, spatial trends suggest a North-South increase in dry spell length in summer (December - February), but a shortening after February. Generally, the GLM and MK results are similar in the two regions but the MK test tends to give higher values of positive slope coefficients and lower values for negative coefficients compared to GLM. This may limit the ability of finding the best estimates for model coefficients. Previous studies in Australia and Kenya have relied on continuous climatic indices based on global climate models and stochastic processes resulting in limited and mixed results. For agronomical purposes, our results show that direct assessment of dry spells lengths from daily rainfall also indicates changes in dry spells trends in Kenya and the MDB and that such an analysis is easy to use and requires limited assumptions. This initial analysis identifies significant increasing trends in the dry spell lengths in some areas and periods in Kenya and the MDB. This has major implications for crop production in these regions and it is recommended that this information be incorporated in the regions' management decisions. KEY WORDS: monthly dry spell length; Generalized Linear Models; Mann -Kendall test; month; Kenya, Murray Darling Basin (MDB).

Analysis of satellite precipitation over East Africa during last decades

NASA Astrophysics Data System (ADS)

Cattani, Elsa; Wenhaji Ndomeni, Claudine; Merino, Andrés; Levizzani, Vincenzo

2016-04-01

Daily accumulated precipitation time series from satellite retrieval algorithms (e.g., ARC2 and TAMSAT) are exploited to extract the spatial and temporal variability of East Africa (EA - 5°S-20°N, 28°E-52°E) precipitation during last decades (1983-2013). The Empirical Orthogonal Function (EOF) analysis is applied to precipitation time series to investigate the spatial and temporal variability in particular for October-November-December referred to as the short rain season. Moreover, the connection among EA's precipitation, sea surface temperature, and soil moisture is analyzed through the correlation with the dominant EOF modes of variability. Preliminary results concern the first two EOF's modes for the ARC2 data set. EOF1 is characterized by an inter-annual variability and a positive correlation between precipitation and El Niño, positive Indian Ocean Dipole mode, and soil moisture, while EOF2 shows a dipole structure of spatial variability associated with a longer scale temporal variability. This second dominant mode is mostly linked to sea surface temperature variations in the North Atlantic Ocean. Further analyses are carried out by computing the time series of the joint CCI/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI, http://etccdi.pacificclimate.org/index.shtml), i.e. RX1day, RX5day, CDD, CDD, CWD, SDII, PRCPTOT, R10, R20. The purpose is to identify the occurrenes of extreme events (droughts and floods) and extract precipitation temporal variation by trend analysis (Mann-Kendall technique). Results for the ARC2 data set demonstrate the existence of a dipole spatial pattern in the linear trend of the time series of PRCPTOT (annual precipitation considering days with a rain rate > 1 mm) and SDII (average precipitation on wet days over a year). A negative trend is mainly present over West Ethiopia and Sudan, whereas a positive trend is exhibited over East Ethiopia and Somalia. CDD (maximum number of consecutive dry days) and CWD (maximum number of consecutive wet days) time series do not exhibit a similar behavior and trends are generally weaker with a lower significance level with respect to PRCPTOT and SDII.

Statistical trend analysis and extreme distribution of significant wave height from 1958 to 1999 - an application to the Italian Seas

NASA Astrophysics Data System (ADS)

Martucci, G.; Carniel, S.; Chiggiato, J.; Sclavo, M.; Lionello, P.; Galati, M. B.

2009-09-01

The study is a statistical analysis of sea states timeseries derived using the wave model WAM forced by the ERA-40 dataset in selected areas near the Italian coasts. For the period 1 January 1958 to 31 December 1999 the analysis yields: (i) the existence of a negative trend in the annual- and winter-averaged sea state heights; (ii) the existence of a turning-point in late 70's in the annual-averaged trend of sea state heights at a site in the Northern Adriatic Sea; (iii) the overall absence of a significant trend in the annual-averaged mean durations of sea states over thresholds; (iv) the assessment of the extreme values on a time-scale of thousand years. The analysis uses two methods to obtain samples of extremes from the independent sea states: the r-largest annual maxima and the peak-over-threshold. The two methods show statistical differences in retrieving the return values and more generally in describing the significant wave field. The study shows the existence of decadal negative trends in the significant wave heights and by this it conveys useful information on the wave climatology of the Italian seas during the second half of the 20th century.

Recent trends in analytical procedures in forensic toxicology.

PubMed

Van Bocxlaer, Jan F

2005-12-01

Forensic toxicology is a very demanding discipline,heavily dependent on good analytical techniques. That is why new trends appear continuously. In the past years. LC-MS has revolutionized target compound analysis and has become the trend, also in toxicology. In LC-MS screening analysis, things are less straightforward and several approaches exist. One promising approach based on accurate LC-MSTOF mass measurements and elemental formula based library searches is discussed. This way of screening has already proven its applicability but at the same time it became obvious that a single accurate mass measurement lacks some specificity when using large compound libraries. CE too is a reemerging approach. The increasingly polar and ionic molecules encountered make it a worthwhile addition to e.g. LC, as illustrated for the analysis of GHB. A third recent trend is the use of MALDI mass spectrometry for small molecules. It is promising for its ease-of-use and high throughput. Unfortunately, re-ports of disappointment but also accomplishment, e.g. the quantitative analysis of LSD as discussed here, alternate, and it remains to be seen whether MALDI really will establish itself. Indeed, not all new trends will prove themselves but the mere fact that many appear in the world of analytical toxicology nowadays is, in itself, encouraging for the future of (forensic) toxicology.

Hierarchical model analysis of the Atlantic Flyway Breeding Waterfowl Survey

USGS Publications Warehouse

Sauer, John R.; Zimmerman, Guthrie S.; Klimstra, Jon D.; Link, William A.

2014-01-01

We used log-linear hierarchical models to analyze data from the Atlantic Flyway Breeding Waterfowl Survey. The survey has been conducted by state biologists each year since 1989 in the northeastern United States from Virginia north to New Hampshire and Vermont. Although yearly population estimates from the survey are used by the United States Fish and Wildlife Service for estimating regional waterfowl population status for mallards (Anas platyrhynchos), black ducks (Anas rubripes), wood ducks (Aix sponsa), and Canada geese (Branta canadensis), they are not routinely adjusted to control for time of day effects and other survey design issues. The hierarchical model analysis permits estimation of year effects and population change while accommodating the repeated sampling of plots and controlling for time of day effects in counting. We compared population estimates from the current stratified random sample analysis to population estimates from hierarchical models with alternative model structures that describe year to year changes as random year effects, a trend with random year effects, or year effects modeled as 1-year differences. Patterns of population change from the hierarchical model results generally were similar to the patterns described by stratified random sample estimates, but significant visibility differences occurred between twilight to midday counts in all species. Controlling for the effects of time of day resulted in larger population estimates for all species in the hierarchical model analysis relative to the stratified random sample analysis. The hierarchical models also provided a convenient means of estimating population trend as derived statistics from the analysis. We detected significant declines in mallard and American black ducks and significant increases in wood ducks and Canada geese, a trend that had not been significant for 3 of these 4 species in the prior analysis. We recommend using hierarchical models for analysis of the Atlantic Flyway Breeding Waterfowl Survey.

Attribution of trends in global vegetation greenness from 1982 to 2011

NASA Astrophysics Data System (ADS)

Zhu, Z.; Xu, L.; Bi, J.; Myneni, R.; Knyazikhin, Y.

2012-12-01

Time series of remotely sensed vegetation indices data provide evidence of changes in terrestrial vegetation activity over the past decades in the world. However, it is difficult to attribute cause-and-effect to vegetation trends because variations in vegetation productivity are driven by various factors. This study investigated changes in global vegetation productivity first, and then attributed the global natural vegetation with greening trend. Growing season integrated normalized difference vegetation index (GSI NDVI) derived from the new GIMMS NDVI3g dataset (1982-2011was analyzed. A combined time series analysis model, which was developed from simper linear trend model (SLT), autoregressive integrated moving average model (ARIMA) and Vogelsang's t-PST model shows that productivity of all vegetation types except deciduous broadleaf forest predominantly showed increasing trends through the 30-year period. The evolution of changes in productivity in the last decade was also investigated. Area of greening vegetation monotonically increased through the last decade, and both the browning and no change area monotonically decreased. To attribute the predominant increase trend of productivity of global natural vegetation, trends of eight climate time series datasets (three temperature, three precipitation and two radiation datasets) were analyzed. The attribution of trends in global vegetation greenness was summarized as relaxation of climatic constraints, fertilization and other unknown reasons. Result shows that nearly all the productivity increase of global natural vegetation was driven by relaxation of climatic constraints and fertilization, which play equally important role in driving global vegetation greenness.; Area fraction and productivity change fraction of IGBP vegetation land cover classes showing statistically significant (10% level) trend in GSI NDVIt;

Modelling uncertainties and possible future trends of precipitation and temperature for 10 sub-basins in Columbia River Basin (CRB)

NASA Astrophysics Data System (ADS)

Ahmadalipour, A.; Rana, A.; Qin, Y.; Moradkhani, H.

2014-12-01

Trends and changes in future climatic parameters, such as, precipitation and temperature have been a central part of climate change studies. In the present work, we have analyzed the seasonal and yearly trends and uncertainties of prediction in all the 10 sub-basins of Columbia River Basin (CRB) for future time period of 2010-2099. The work is carried out using 2 different sets of statistically downscaled Global Climate Model (GCMs) projection datasets i.e. Bias correction and statistical downscaling (BCSD) generated at Portland State University and The Multivariate Adaptive Constructed Analogs (MACA) generated at University of Idaho. The analysis is done for with 10 GCM downscaled products each from CMIP5 daily dataset totaling to 40 different downscaled products for robust analysis. Summer, winter and yearly trend analysis is performed for all the 10 sub-basins using linear regression (significance tested by student t test) and Mann Kendall test (0.05 percent significance level), for precipitation (P), temperature maximum (Tmax) and temperature minimum (Tmin). Thereafter, all the parameters are modelled for uncertainty, across all models, in all the 10 sub-basins and across the CRB for future scenario periods. Results have indicated in varied degree of trends for all the sub-basins, mostly pointing towards a significant increase in all three climatic parameters, for all the seasons and yearly considerations. Uncertainty analysis have reveled very high change in all the parameters across models and sub-basins under consideration. Basin wide uncertainty analysis is performed to corroborate results from smaller, sub-basin scale. Similar trends and uncertainties are reported on the larger scale as well. Interestingly, both trends and uncertainties are higher during winter period than during summer, contributing to large part of the yearly change.

Spatio-temporal monitoring of vegetation phenology in the dry sub-humid region of Nigeria using time series of AVHRR NDVI and TAMSAT datasets

NASA Astrophysics Data System (ADS)

Osunmadewa, Babatunde Adeniyi; Gebrehiwot, Worku Zewdie; Csaplovics, Elmar; Adeofun, Olabinjo Clement

2018-03-01

Time series data are of great importance for monitoring vegetation phenology in the dry sub-humid regions where change in land cover has influence on biomass productivity. However few studies have inquired into examining the impact of rainfall and land cover change on vegetation phenology. This study explores Seasonal Trend Analysis (STA) approach in order to investigate overall greenness, peak of annual greenness and timing of annual greenness in the seasonal NDVI cycle. Phenological pattern for the start of season (SOS) and end of season (EOS) was also examined across different land cover types in four selected locations. A significant increase in overall greenness (amplitude 0) and a significant decrease in other greenness trend maps (amplitude 1 and phase 1) was observed over the study period. Moreover significant positive trends in overall annual rainfall (amplitude 0) was found which follows similar pattern with vegetation trend. Variation in the timing of peak of greenness (phase 1) was seen in the four selected locations, this indicate a change in phenological trend. Additionally, strong relationship was revealed by the result of the pixel-wise regression between NDVI and rainfall. Change in vegetation phenology in the study area is attributed to climatic variability than anthropogenic activities.

Maternal exposures in the National Birth Defects Prevention Study: time trends of selected exposures

PubMed Central

Dawson, April L.; Razzaghi, Hilda; Arth, Annelise; Canfield, Mark A.; Parker, Samantha E.; Reefhuis, Jennita

2015-01-01

Background Our objective was to describe time trends in selected pregnancy exposures in the National Birth Defects Prevention Study (NBDPS). Methods We analyzed data from the NBDPS, a multi-site case-control study of major birth defects, for mothers of live-born infants without birth defects (controls), with an expected date of delivery (EDD) from 1998 –2011. Mothers from the 10 participating centers across the United States were interviewed by phone between six weeks and two years after the EDD. We focused on maternal race/ethnicity and five maternal risk factors: obesity, use of folic acid-containing multivitamins, opioid analgesics, selective serotonin reuptake inhibitors (SSRIs), and loratadine because of their prevalence of use and some reports of associations with major birth defects. Prevalence time trends were examined using the Kendall’s τβ test statistic. Results The exposure trend analysis included 11,724 control mothers with EDDs from 1998–2011. We observed a significant increase in obesity prevalence among control mothers, as well as use of SSRIs and loratadine. We also observed an increase in periconceptional use of folic acid-containing multivitamins. Some of the time trends varied by race/ethnicity. No remarkable trend in the overall use of opioid analgesics was observed. The racial/ethnic distribution of mothers changed slightly during the study period. Conclusions Long-term, population-based case-control studies continue to be an effective way to assess exposure-birth defects associations and provide guidance to health care providers. However, investigators examining rare outcomes covering many years of data collection need to be cognizant of time trends in exposures. PMID:25884728

Maternal exposures in the National Birth Defects Prevention Study: Time trends of selected exposures.

PubMed

Dawson, April L; Razzaghi, Hilda; Arth, Annelise; Canfield, Mark A; Parker, Samantha E; Reefhuis, Jennita

2015-08-01

Our objective was to describe time trends in selected pregnancy exposures in the National Birth Defects Prevention Study (NBDPS). We analyzed data from the NBDPS, a multi-site case-control study of major birth defects, for mothers of live-born infants without birth defects (controls), with an expected date of delivery (EDD) from 1998 to 2011. Mothers from the 10 participating centers across the United States were interviewed by phone between 6 weeks and 2 years after the EDD. We focused on maternal race/ethnicity and five maternal risk factors: obesity, use of folic acid-containing multivitamins, opioid analgesics, selective serotonin reuptake inhibitors, and loratadine because of their prevalence of use and some reports of associations with major birth defects. Prevalence time trends were examined using the Kendall's τβ test statistic. The exposure trend analysis included 11,724 control mothers with EDDs from 1998 to 2011. We observed a significant increase in obesity prevalence among control mothers, as well as use of selective serotonin reuptake inhibitors and loratadine. We also observed an increase in periconceptional use of folic acid-containing multivitamins. Some of the time trends varied by race/ethnicity. No remarkable trend in the overall use of opioid analgesics was observed. The racial/ethnic distribution of mothers changed slightly during the study period. Long-term, population-based case-control studies continue to be an effective way to assess exposure-birth defects associations and provide guidance to health care providers. However, investigators examining rare outcomes covering many years of data collection need to be cognizant of time trends in exposures. © 2015 Wiley Periodicals, Inc.

Does Increasing Hours of Schooling Lead to Improvements in Student Learning? Policy Brief No. 1

ERIC Educational Resources Information Center

Sandoval-Hernandez, Andres; Aghakasiri, Parisa; Wild, Justin; Rutkowski, David

2013-01-01

Increasing the number of hours students spend in school each year, on the assumption that this will improve student achievement, has become a widespread trend. However, the analysis reported here suggests that this trend can be misguided: the time students spend in the classroom is not always positively related to their academic achievement.…

Spatio-temporal Trends of Climate Variability in North Carolina

NASA Astrophysics Data System (ADS)

Sayemuzzaman, Mohammad

Climatic trends in spatial and temporal variability of maximum temperature (Tmax), minimum temperature (Tmin), mean temperature (Tmean) and precipitation were evaluated for 249 ground-based stations in North Carolina for 1950-2009. The Mann-Kendall (MK), the Theil-Sen Approach (TSA) and the Sequential Mann-Kendall (SQMK) tests were applied to quantify the significance of trend, magnitude of trend and the trend shift, respectively. The lag-1 serial correlation and double mass curve techniques were used to address the data independency and homogeneity. The pre-whitening technique was used to eliminate the effect of auto correlation of the data series. The difference between minimum and maximum temperatures, and so the diurnal temperature range (DTR), at some stations was found to be decreasing on both an annual and a seasonal basis, with an overall increasing trend in the mean temperature. For precipitation, a statewide increasing trend in fall (highest in November) and decreasing trend in winter (highest in February) were detected. No pronounced increasing/decreasing trends were detected in annual, spring, and summer precipitation time series. Trend analysis on a spatial scale (for three physiographic regions: mountain, piedmont and coastal) revealed mixed results. Coastal zone exhibited increasing mean temperature (warming) trend as compared to other locations whereas mountain zone showed decreasing trend (cooling). Three main moisture components (precipitation, total cloud cover, and soil moisture) and the two major atmospheric circulation modes (North Atlantic Oscillation and Southern Oscillation) were used for correlative analysis purposes with the temperature (specifically with DTR) and precipitation trends. It appears that the moisture components are associated with DTR more than the circulation modes in North Carolina.

Data for Figures and Tables in Journal Article Assessment of the Effects of Horizontal Grid Resolution on Long-Term Air Quality Trends using Coupled WRF-CMAQ Simulations, doi:10.1016/j.atmosenv.2016.02.036

EPA Pesticide Factsheets

The dataset represents the data depicted in the Figures and Tables of a Journal Manuscript with the following abstract: The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental United State are performed over the 2001 to 2010 time period at two different horizontal resolutions of 12 and 36 km. Both simulations used the same emission inventory and model configurations. Model results are compared both in space and time to assess the potential weaknesses and strengths of using coarse resolution in long-term air quality applications. The results show that the 36 km and 12 km simulations are comparable in terms of trends analysis for both pollutant concentrations and radiation variables. The advantage of using the coarser 36 km resolution is a significant reduction of computational cost, time and storage requirement which are key considerations when performing multiple years of simulations for trend analysis. However, if such simulations are to be used for local air quality analysis, finer horizontal resolution may be beneficial since it can provide information on local gradients. In particular, divergences between the two simulations are noticeable in urban, complex terrain and coastal regions.This dataset is associated with the following publication

Analysis and interpretation of water-quality trends in major U.S. rivers, 1974-81

USGS Publications Warehouse

Smith, Richard A.; Alexander, Richard B.; Wolman, M. Gordon

1987-01-01

Water-quality records from two nationwide sampling networks are now of sufficient length to permit nationally consistent analysis of long-term water-quality trends at more than 300 locations on major U.S. rivers. Observed trends in 24 water-quality measures for the period 1974--81 provide evidence of both improvement and deterioration in stream quality during a time of major changes in atmospheric and terrestrial influences on surface waters. Particularly noteworthy are widespread decreases in lead and fecal bacteria concentrations and widespread increases in nitrate, arsenic, and cadmium concentrations. Changes in municipal waste treatment, leaded-gasoline consumption, highway-salt use, and nitrogen-fertilizer application, and regionally variable trends in coal production and combustion during the period, appear to be reflected in water-quality changes. There is evidence that atmospheric deposition of a variety of substances has played a surprisingly large role in water-quality changes.

Summary and trend analysis of water-quality data for the Oakes Test Area, southeastern North Dakota, 1984-2004

USGS Publications Warehouse

Ryberg, Karen R.

2007-01-01

The Oakes Test Area is operated and maintained by the Garrison Diversion Conservancy District, under a cooperative agreement with the Bureau of Reclamation, to evaluate the effectiveness and environmental consequences of irrigation. As part of the evaluation, the Bureau of Reclamation collected water-quality samples from seven sites on the James River and the Oakes Test Area. The data were summarized and examined for trends in concentration. A nonparametric statistical test was used to test whether each concentration was increasing or decreasing with time for selected physical properties and constituents, and a trend slope was estimated for each constituent at each site. Trends were examined for two time periods, 1988-2004 and 1994-2004. Results varied by site and by constituent. All sites and all constituents tested had at least one statistically significant trend in the period 1988-2004. Sulfate, total dissolved solids, nitrate, and orthophosphate have significant positive trends at multiple sites with no significant negative trend at any site. Alkalinity and arsenic have single significant positive trends. Hardness, calcium, magnesium, sodium, sodium-adsorption ratio, potassium, and chloride have both significant positive and negative trends. Ammonia has a single significant negative trend. Fewer significant trends were identified in 1994-2004, and all but one were positive. The contribution to the James River from Oakes Test Area drainage appears to have little effect on water quality in the James River.

Analysis of electrochemical noise (ECN) data in time and frequency domain for comparison corrosion inhibition of some azole compounds on Cu in 1.0 M H2SO4 solution

NASA Astrophysics Data System (ADS)

Ramezanzadeh, B.; Arman, S. Y.; Mehdipour, M.; Markhali, B. P.

2014-01-01

In this study, the corrosion inhibition properties of two similar heterocyclic compounds namely benzotriazole (BTA) and benzothiazole (BNS) inhibitors on copper in 1.0 M H2SO4 solution were studied by electrochemical techniques as well as surface analysis. The results showed that corrosion inhibition of copper largely depends on the molecular structure and concentration of the inhibitors. The effect of DC trend on the interpretation of electrochemical noise (ECN) results in time domain was evaluated by moving average removal (MAR) method. Accordingly, the impact of square and Hanning window functions as drift removal methods in frequency domain was studied. After DC trend removal, a good trend was observed between electrochemical noise (ECN) data and the results obtained from EIS and potentiodynamic polarization. Furthermore, the shot noise theory in frequency domain was applied to approach the charge of each electrochemical event (q) from the potential and current noise signals.

Hospitalization for primary care susceptible conditions, health spending and Family Health Strategy: an analysis of trends.

PubMed

Morimoto, Tissiani; Costa, Juvenal Soares Dias da

2017-03-01

The goal of this study was to analyze the trend over time of hospitalizations due to conditions susceptible to primary healthcare (HCSPC), and how it relates to healthcare spending and Family Health Strategy (FHS) coverage in the city of São Leopoldo, Rio Grande do Sul State, Brazil, between 2003 and 2012. This is an ecological, time-trend study. We used secondary data available in the Unified Healthcare System Hospital Data System, the Primary Care Department and Public Health Budget Data System. The analysis compared HCSPC using three-year moving averages and Poisson regressions or negative binomials. We found no statistical significance in decreasing HCSPC indicators and primary care spending in the period analyzed. Healthcare spending, per-capita spending and FHS coverage increased significantly, but we found no correlation with HCSPC. The results show that, despite increases in the funds invested and population covered by FHS, they are still insufficient to deliver the level of care the population requires.

Bi-scale analysis of multitemporal land cover fractions for wetland vegetation mapping

NASA Astrophysics Data System (ADS)

Michishita, Ryo; Jiang, Zhiben; Gong, Peng; Xu, Bing

2012-08-01

Land cover fractions (LCFs) derived through spectral mixture analysis are useful in understanding sub-pixel information. However, few studies have been conducted on the analysis of time-series LCFs. Although multi-scale comparisons of spectral index, hard classification, and land surface temperature images have received attention, rarely have these approaches been applied to LCFs. This study compared the LCFs derived through Multiple Endmember Spectral Mixture Analysis (MESMA) using the time-series Landsat Thematic Mapper (TM) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired in the Poyang Lake area, China between 2004 and 2005. Specifically, we aimed to: (1) propose an approach for optimal endmember (EM) selection in time-series MESMA; (2) understand the trends in time-series LCFs derived from the TM and MODIS data; and (3) examine the trends in the correlation between the bi-scale LCFs derived from the time-series TM and MODIS data. Our results indicated: (1) the EM spectra chosen according to the proposed hierarchical three-step approach (overall, seasonal, and individual) accurately modeled the both the TM and MODIS images; (2) green vegetation (GV) and NPV/soil/impervious surface (N/S/I) classes followed sine curve trends in the overall area, while the two water classes displayed the water level change pattern in the areas primarily covered with wetland vegetation; and (3) GV, N/S/I, and bright water classes indicated a moderately high agreement between the TM and MODIS LCFs in the whole area (adjusted R2 ⩾ 0.6). However, low levels of correlations were found in the areas primarily dominated by wetland vegetation for all land cover classes.

Trends in surface ozone over Europe, 1978-1990

NASA Technical Reports Server (NTRS)

Low, Pak Sum; Kelly, P. Michael; Davies, Trevor D.

1994-01-01

It has been suggested that surface ozone concentrations in rural areas of Europe have been increasing at a rate of 1 to 3 percent per year over the past two to three decades, presumably due to human influences (Feister and Warmbt, 1987; Bojkov, 1988; Penkett, 1989). Recently, we have analyzed surface ozone data from 20 European stations of differing character (remote, rural, suburban and urban) for a common period of 1978-1988 (Low et al., 1992). It was found that there were pronounced annual and seasonal variations in the linear trends in different areas, and there was no dominant region-wide trend. In spring and, most notably, summer, stations on the maritime fringe of the network generally exhibited negative trends whilst those located further into the continental interior exhibited positive trends. In winter, most of the stations in the network exhibited positive trends. Relatively few of these trends were statistically significant. This paper updates our earlier analysis by extending the data sets of the network up to the year 1990. The spatial variations in surface ozone trends over the extended period 1978-1990 are examined and discussed in comparison to the 1978-1988 patterns. The update confirms the overall conclusions of the earlier analysis, specifically that caution should be exercised in interpreting the results of trend analyses based on station data representative of a limited period of time and/or geographical area.

National Trends in Trace Metals Concentrations in Ambient Particulate Matter

NASA Astrophysics Data System (ADS)

McCarthy, M. C.; Hafner, H. R.; Charrier, J. G.

2007-12-01

Ambient measurements of trace metals identified as hazardous air pollutants (HAPs, air toxics) collected in the United States from 1990 to 2006 were analyzed for long-term trends. Trace metals analyzed include lead, manganese, arsenic, chromium, nickel, cadmium, and selenium. Visual and statistical analyses were used to identify and quantify temporal variations in air toxics at national and regional levels. Trend periods were required to be at least five years. Lead particles decreased in concentration at most monitoring sites, but trends in other metals were not consistent over time or spatially. In addition, routine ambient monitoring methods had method detection limits (MDLs) too high to adequately measure concentrations for trends analysis. Differences between measurement methods at urban and rural sites also confound trends analyses. Improvements in MDLs, and a better understanding of comparability between networks, are needed to better quantify trends in trace metal concentrations in the future.

Tipping point analysis of ocean acoustic noise

NASA Astrophysics Data System (ADS)

Livina, Valerie N.; Brouwer, Albert; Harris, Peter; Wang, Lian; Sotirakopoulos, Kostas; Robinson, Stephen

2018-02-01

We apply tipping point analysis to a large record of ocean acoustic data to identify the main components of the acoustic dynamical system and study possible bifurcations and transitions of the system. The analysis is based on a statistical physics framework with stochastic modelling, where we represent the observed data as a composition of deterministic and stochastic components estimated from the data using time-series techniques. We analyse long-term and seasonal trends, system states and acoustic fluctuations to reconstruct a one-dimensional stochastic equation to approximate the acoustic dynamical system. We apply potential analysis to acoustic fluctuations and detect several changes in the system states in the past 14 years. These are most likely caused by climatic phenomena. We analyse trends in sound pressure level within different frequency bands and hypothesize a possible anthropogenic impact on the acoustic environment. The tipping point analysis framework provides insight into the structure of the acoustic data and helps identify its dynamic phenomena, correctly reproducing the probability distribution and scaling properties (power-law correlations) of the time series.

Analysis of childhood leukemia mortality trends in Brazil, from 1980 to 2010.

PubMed

Silva, Franciane F; Zandonade, Eliana; Zouain-Figueiredo, Glaucia P

2014-01-01

Leukemias comprise the most common group of cancers in children and adolescents. Studies conducted in other countries and Brazil have observed a decrease in their mortality.This study aimed to evaluate the trend of mortality from leukemia in children under 19 years of age in Brazil, from 1980 to 2010. This was an ecological study, using retrospective time series data from the Mortality Information System, from 1980 to 2010. Calculations of mortality rates were performed, including gross, gender-specific, and age-based. For trend analysis, linear and semi-log regression models were used. The significance level was 5%. Mortality rates for lymphoid and myeloid leukemias presented a growth trend, with the exception of lymphoid leukemia among children under 4 years of age (percentage decrease: 1.21% annually), while in the sub-group "Other types of leukemia", a downward trend was observed. Overall, mortality from leukemia tended to increase for boys and girls, especially in the age groups 10-14 years (annual percentage increase of 1.23% for males and 1.28% for females) and 15-19 years (annual percentage increase of 1.40% for males and 1.62% for females). The results for leukemia generally corroborate the results of other similar studies. A detailed analysis by subgroup of leukemia, age, and gender revealed no trends shown in other studies, thus indicating special requirements for each variable in the analysis. Copyright © 2014 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

HYPE: a WFD tool for the identification of significant and sustained upward trends in groundwater time series

NASA Astrophysics Data System (ADS)

Lopez, Benjamin; Croiset, Nolwenn; Laurence, Gourcy

2014-05-01

The Water Framework Directive 2006/11/CE (WFD) on the protection of groundwater against pollution and deterioration asks Member States to identify significant and sustained upward trends in all bodies or groups of bodies of groundwater that are characterised as being at risk in accordance with Annex II to Directive 2000/60/EC. The Directive indicates that the procedure for the identification of significant and sustained upward trends must be based on a statistical method. Moreover, for significant increases of concentrations of pollutants, trend reversals are identified as being necessary. This means to be able to identify significant trend reversals. A specific tool, named HYPE, has been developed in order to help stakeholders working on groundwater trend assessment. The R encoded tool HYPE provides statistical analysis of groundwater time series. It follows several studies on the relevancy of the use of statistical tests on groundwater data series (Lopez et al., 2011) and other case studies on the thematic (Bourgine et al., 2012). It integrates the most powerful and robust statistical tests for hydrogeological applications. HYPE is linked to the French national database on groundwater data (ADES). So monitoring data gathered by the Water Agencies can be directly processed. HYPE has two main modules: - a characterisation module, which allows to visualize time series. HYPE calculates the main statistical characteristics and provides graphical representations; - a trend module, which identifies significant breaks, trends and trend reversals in time series, providing result table and graphical representation (cf figure). Additional modules are also implemented to identify regional and seasonal trends and to sample time series in a relevant way. HYPE has been used successfully in 2012 by the French Water Agencies to satisfy requirements of the WFD, concerning characterization of groundwater bodies' qualitative status and evaluation of the risk of non-achievement of good status. Bourgine B. et al. 2012, Ninth International Geostatistics Congress, Oslo, Norway June 11 - 15. Lopez B. et al. 2011, Final Report BRGM/RP-59515-FR. 166p.

Application of modern tests for stationarity to single-trial MEG data: transferring powerful statistical tools from econometrics to neuroscience.

PubMed

Kipiński, Lech; König, Reinhard; Sielużycki, Cezary; Kordecki, Wojciech

2011-10-01

Stationarity is a crucial yet rarely questioned assumption in the analysis of time series of magneto- (MEG) or electroencephalography (EEG). One key drawback of the commonly used tests for stationarity of encephalographic time series is the fact that conclusions on stationarity are only indirectly inferred either from the Gaussianity (e.g. the Shapiro-Wilk test or Kolmogorov-Smirnov test) or the randomness of the time series and the absence of trend using very simple time-series models (e.g. the sign and trend tests by Bendat and Piersol). We present a novel approach to the analysis of the stationarity of MEG and EEG time series by applying modern statistical methods which were specifically developed in econometrics to verify the hypothesis that a time series is stationary. We report our findings of the application of three different tests of stationarity--the Kwiatkowski-Phillips-Schmidt-Schin (KPSS) test for trend or mean stationarity, the Phillips-Perron (PP) test for the presence of a unit root and the White test for homoscedasticity--on an illustrative set of MEG data. For five stimulation sessions, we found already for short epochs of duration of 250 and 500 ms that, although the majority of the studied epochs of single MEG trials were usually mean-stationary (KPSS test and PP test), they were classified as nonstationary due to their heteroscedasticity (White test). We also observed that the presence of external auditory stimulation did not significantly affect the findings regarding the stationarity of the data. We conclude that the combination of these tests allows a refined analysis of the stationarity of MEG and EEG time series.

A climate trend analysis of Uganda

USGS Publications Warehouse

Funk, Christopher C.; Rowland, Jim; Eilerts, Gary; White, Libby

2012-01-01

This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), identifies observed changes in rainfall and temperature in Uganda, based on an analysis of a quality-controlled, long time series of station observations throughout Uganda. Extending recent trends forward, it also provides a current and near-future context for understanding the actual nature of climate change impacts in the country, and a basis for identifying climate adaptations that may protect and improve the country's food security.

Global Warming Estimation From Microwave Sounding Unit

NASA Technical Reports Server (NTRS)

Prabhakara, C.; Iacovazzi, R., Jr.; Yoo, J.-M.; Dalu, G.

1998-01-01

Microwave Sounding Unit (MSU) Ch 2 data sets, collected from sequential, polar-orbiting, Sun-synchronous National Oceanic and Atmospheric Administration operational satellites, contain systematic calibration errors that are coupled to the diurnal temperature cycle over the globe. Since these coupled errors in MSU data differ between successive satellites, it is necessary to make compensatory adjustments to these multisatellite data sets in order to determine long-term global temperature change. With the aid of the observations during overlapping periods of successive satellites, we can determine such adjustments and use them to account for the coupled errors in the long-term time series of MSU Ch 2 global temperature. In turn, these adjusted MSU Ch 2 data sets can be used to yield global temperature trend. In a pioneering study, Spencer and Christy (SC) (1990) developed a procedure to derive the global temperature trend from MSU Ch 2 data. Such a procedure can leave unaccounted residual errors in the time series of the temperature anomalies deduced by SC, which could lead to a spurious long-term temperature trend derived from their analysis. In the present study, we have developed a method that avoids the shortcomings of the SC procedure, the magnitude of the coupled errors is not determined explicitly. Furthermore, based on some assumptions, these coupled errors are eliminated in three separate steps. Such a procedure can leave unaccounted residual errors in the time series of the temperature anomalies deduced by SC, which could lead to a spurious long-term temperature trend derived from their analysis. In the present study, we have developed a method that avoids the shortcomings of the SC procedures. Based on our analysis, we find there is a global warming of 0.23+/-0.12 K between 1980 and 1991. Also, in this study, the time series of global temperature anomalies constructed by removing the global mean annual temperature cycle compares favorably with a similar time series obtained from conventional observations of temperature.

Late Maternal Deaths and Deaths from Sequelae of Obstetric Causes in the Americas from 1999 to 2013: A Trend Analysis.

PubMed

de Cosio, Federico G; Jiwani, Safia S; Sanhueza, Antonio; Soliz, Patricia N; Becerra-Posada, Francisco; Espinal, Marcos A

2016-01-01

Data on maternal deaths occurring after the 42 days postpartum reference time is scarce; the objective of this analysis is to explore the trend and magnitude of late maternal deaths and deaths from sequelae of obstetric causes in the Americas between 1999 and 2013, and to recommend including these deaths in the monitoring of the Sustainable Development Goals (SDGs). Exploratory data analysis enabled analyzing the magnitude and trend of late maternal deaths and deaths from sequelae of obstetric causes for seven countries of the Americas: Argentina, Brazil, Canada, Colombia, Cuba, Mexico and the United States. A Poisson regression model was developed to compare trends of late maternal deaths and deaths from sequelae of obstetric causes between two periods of time: 1999 to 2005 and 2006 to 2013; and to estimate the relative increase of these deaths in the two periods of time. The proportion of late maternal deaths and deaths from sequelae of obstetric causes ranged between 2.40% (CI 0.85% - 5.48%) and 18.68% (CI 17.06% - 20.47%) in the seven countries. The ratio of late maternal deaths and deaths from sequelae of obstetric causes per 100,000 live births has increased by two times in the region of the Americas in the period 2006-2013 compared to the period 1999-2005. The regional relative increase of late maternal death was 2.46 (p<0.0001) times higher in the second period compared to the first. Ascertainment of late maternal deaths and deaths from sequelae of obstetric causes has improved in the Americas since the early 2000's due to improvements in the quality of information and the obstetric transition. Late and obstetric sequelae maternal deaths should be included in the monitoring of the SDGs as well as in the revision of the International Classification of Diseases' 11th version (ICD-11).

Late Maternal Deaths and Deaths from Sequelae of Obstetric Causes in the Americas from 1999 to 2013: A Trend Analysis

PubMed Central

de Cosio, Federico G.; Sanhueza, Antonio; Soliz, Patricia N.; Becerra-Posada, Francisco; Espinal, Marcos A.

2016-01-01

Background Data on maternal deaths occurring after the 42 days postpartum reference time is scarce; the objective of this analysis is to explore the trend and magnitude of late maternal deaths and deaths from sequelae of obstetric causes in the Americas between 1999 and 2013, and to recommend including these deaths in the monitoring of the Sustainable Development Goals (SDGs). Methods Exploratory data analysis enabled analyzing the magnitude and trend of late maternal deaths and deaths from sequelae of obstetric causes for seven countries of the Americas: Argentina, Brazil, Canada, Colombia, Cuba, Mexico and the United States. A Poisson regression model was developed to compare trends of late maternal deaths and deaths from sequelae of obstetric causes between two periods of time: 1999 to 2005 and 2006 to 2013; and to estimate the relative increase of these deaths in the two periods of time. Findings The proportion of late maternal deaths and deaths from sequelae of obstetric causes ranged between 2.40% (CI 0.85% – 5.48%) and 18.68% (CI 17.06% – 20.47%) in the seven countries. The ratio of late maternal deaths and deaths from sequelae of obstetric causes per 100,000 live births has increased by two times in the region of the Americas in the period 2006-2013 compared to the period 1999-2005. The regional relative increase of late maternal death was 2.46 (p<0.0001) times higher in the second period compared to the first. Interpretation Ascertainment of late maternal deaths and deaths from sequelae of obstetric causes has improved in the Americas since the early 2000’s due to improvements in the quality of information and the obstetric transition. Late and obstetric sequelae maternal deaths should be included in the monitoring of the SDGs as well as in the revision of the International Classification of Diseases’ 11th version (ICD-11). PMID:27626277

Characteristics and trends of radiology research: a survey of original articles published in AJR and Radiology between 2001 and 2010.

PubMed

Lim, Kyoung Ja; Yoon, Dae Young; Yun, Eun Joo; Seo, Young Lan; Baek, Sora; Gu, Dong Hyeon; Yoon, Soo Jeong; Han, Ari; Ku, You Jin; Kim, Sam Soo

2012-09-01

To determine the characteristics and trends of the original articles published in two major American radiology journals, AJR American Journal of Roentgenology (AJR) and Radiology, between 2001 and 2010. This was a retrospective bibliometric analysis that did not involve human subjects and was exempt from institutional review board approval. All 6542 original articles published in AJR and Radiology between 2001 and 2010 were evaluated. The following information was abstracted from each article: radiologic subspecialty, radiologic technique used, type of research, sample size, study design, statistical analysis, study outcome, declared funding, number of authors, affiliation of the first author, and country of the first author. In addition, all the variables examined were presented along with the trend over time. The most common subspecialty of study was abdominal (1219 of 6542, 18.6%), followed by vascular/interventional (804 of 6542, 12.3%). A total of 3744 (57.2%) original articles used magnetic resonance (MR) imaging or computed tomography (CT), 5495 (84.1%) were clinical research articles, 3060 (46.8%) had sample size of more than 50, 4087 (62.5%) were retrospective, 4714 (72.1%) performed statistical analysis, 6225 (95.2%) showed positive study outcome, 4784 (73.1%) were not funded, 3942 (60.3%) had four to seven authors, and 5731 (87.6%) were written by the primary author who was from a department of radiology or radiology-related specialties. The United States published 45.5% (2975 of 6542) of the articles, followed by Japan (n = 525, 8.0%), Germany (n = 485, 7.4%), and South Korea (n = 455, 7.0%). In the time trend analysis, the following variables showed a significantly positive trend: cardiac subspecialty, CT and MR imaging as the radiologic techniques, type of research as other (nonbasic, nonclinical), sample size of more than 50, four to seven as the number of authors, medicine-related department of the first author, and South Korea and Italy as countries of the first author. On the other hand, pediatric subspecialty, combined (basic and clinical) type of research, and number of authors fewer than four showed a significantly negative trend. The bibliometric analysis of the AJR and Radiology journals with articles published between 2001 and 2010 revealed characteristics and trends of the current radiology research that may provide useful information to researchers and editorial staff in radiology. © RSNA, 2012

Multiple long-term trends and trend reversals dominate environmental conditions in a man-made freshwater reservoir.

PubMed

Znachor, Petr; Nedoma, Jiří; Hejzlar, Josef; Seďa, Jaromír; Kopáček, Jiří; Boukal, David; Mrkvička, Tomáš

2018-05-15

Man-made reservoirs are common across the world and provide a wide range of ecological services. Environmental conditions in riverine reservoirs are affected by the changing climate, catchment-wide processes and manipulations with the water level, and water abstraction from the reservoir. Long-term trends of environmental conditions in reservoirs thus reflect a wider range of drivers in comparison to lakes, which makes the understanding of reservoir dynamics more challenging. We analysed a 32-year time series of 36 environmental variables characterising weather, land use in the catchment, reservoir hydrochemistry, hydrology and light availability in the small, canyon-shaped Římov Reservoir in the Czech Republic to detect underlying trends, trend reversals and regime shifts. To do so, we fitted linear and piecewise linear regression and a regime shift model to the time series of mean annual values of each variable and to principal components produced by Principal Component Analysis. Models were weighted and ranked using Akaike information criterion and the model selection approach. Most environmental variables exhibited temporal changes that included time-varying trends and trend reversals. For instance, dissolved organic carbon showed a linear increasing trend while nitrate concentration or conductivity exemplified trend reversal. All trend reversals and cessations of temporal trends in reservoir hydrochemistry (except total phosphorus concentrations) occurred in the late 1980s and during 1990s as a consequence of dramatic socioeconomic changes. After a series of heavy rains in the late 1990s, an administrative decision to increase the flood-retention volume of the reservoir resulted in a significant regime shift in reservoir hydraulic conditions in 1999. Our analyses also highlight the utility of the model selection framework, based on relatively simple extensions of linear regression, to describe temporal trends in reservoir characteristics. This approach can provide a solid basis for a better understanding of processes in freshwater reservoirs. Copyright © 2017 Elsevier B.V. All rights reserved.

Providing web-based tools for time series access and analysis

NASA Astrophysics Data System (ADS)

Eberle, Jonas; Hüttich, Christian; Schmullius, Christiane

2014-05-01

Time series information is widely used in environmental change analyses and is also an essential information for stakeholders and governmental agencies. However, a challenging issue is the processing of raw data and the execution of time series analysis. In most cases, data has to be found, downloaded, processed and even converted in the correct data format prior to executing time series analysis tools. Data has to be prepared to use it in different existing software packages. Several packages like TIMESAT (Jönnson & Eklundh, 2004) for phenological studies, BFAST (Verbesselt et al., 2010) for breakpoint detection, and GreenBrown (Forkel et al., 2013) for trend calculations are provided as open-source software and can be executed from the command line. This is needed if data pre-processing and time series analysis is being automated. To bring both parts, automated data access and data analysis, together, a web-based system was developed to provide access to satellite based time series data and access to above mentioned analysis tools. Users of the web portal are able to specify a point or a polygon and an available dataset (e.g., Vegetation Indices and Land Surface Temperature datasets from NASA MODIS). The data is then being processed and provided as a time series CSV file. Afterwards the user can select an analysis tool that is being executed on the server. The final data (CSV, plot images, GeoTIFFs) is visualized in the web portal and can be downloaded for further usage. As a first use case, we built up a complimentary web-based system with NASA MODIS products for Germany and parts of Siberia based on the Earth Observation Monitor (www.earth-observation-monitor.net). The aim of this work is to make time series analysis with existing tools as easy as possible that users can focus on the interpretation of the results. References: Jönnson, P. and L. Eklundh (2004). TIMESAT - a program for analysing time-series of satellite sensor data. Computers and Geosciences 30, 833-845. Verbesselt, J., R. Hyndman, G. Newnham and D. Culvenor (2010). Detecting trend and seasonal changes in satellite image time series. Remote Sensing of Environment, 114, 106-115. DOI: 10.1016/j.rse.2009.08.014 Forkel, M., N. Carvalhais, J. Verbesselt, M. Mahecha, C. Neigh and M. Reichstein (2013). Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology. Remote Sensing 5, 2113-2144.

Satellite-Based Evidence for Shrub and Graminoid Tundra Expansion in Northern Quebec from 1986-2010

NASA Technical Reports Server (NTRS)

McManus, K. M.; Morton, D. C.; Masek, J. G.; Wang, D.; Sexton, J. O.; Nagol, J.; Ropars, P.; Boudreau, S.

2012-01-01

Global vegetation models predict rapid poleward migration of tundra and boreal forest vegetation in response to climate warming. Local plot and air-photo studies have documented recent changes in high-latitude vegetation composition and structure, consistent with warming trends. To bridge these two scales of inference, we analyzed a 24-year (1986-2010) Landsat time series in a latitudinal transect across the boreal forest-tundra biome boundary in northern Quebec province, Canada. This region has experienced rapid warming during both winter and summer months during the last forty years. Using a per-pixel (30 m) trend analysis, 30% of the observable (cloud-free) land area experienced a significant (p < 0.05) positive trend in the Normalized Difference Vegetation Index (NDVI). However, greening trends were not evenly split among cover types. Low shrub and graminoid tundra contributed preferentially to the greening trend, while forested areas were less likely to show significant trends in NDVI. These trends reflect increasing leaf area, rather than an increase in growing season length, because Landsat data were restricted to peak-summer conditions. The average NDVI trend (0.007/yr) corresponds to a leaf-area index (LAI) increase of 0.6 based on the regional relationship between LAI and NDVI from the Moderate Resolution Spectroradiometer (MODIS). Across the entire transect, the area-averaged LAI increase was 0.2 during 1986-2010. A higher area-averaged LAI change (0.3) within the shrub-tundra portion of the transect represents a 20-60% relative increase in LAI during the last two decades. Our Landsat-based analysis subdivides the overall high-latitude greening trend into changes in peak-summer greenness by cover type. Different responses within and among shrub, graminoid, and tree-dominated cover types in this study indicate important fine-scale heterogeneity in vegetation growth. Although our findings are consistent with community shifts in low-biomass vegetation types over multi-decadal time scales, the response in tundra and forest ecosystems to recent warming was not uniform.

A User-Oriented Methodology for DInSAR Time Series Analysis and Interpretation: Landslides and Subsidence Case Studies

NASA Astrophysics Data System (ADS)

Notti, Davide; Calò, Fabiana; Cigna, Francesca; Manunta, Michele; Herrera, Gerardo; Berti, Matteo; Meisina, Claudia; Tapete, Deodato; Zucca, Francesco

2015-11-01

Recent advances in multi-temporal Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) have greatly improved our capability to monitor geological processes. Ground motion studies using DInSAR require both the availability of good quality input data and rigorous approaches to exploit the retrieved Time Series (TS) at their full potential. In this work we present a methodology for DInSAR TS analysis, with particular focus on landslides and subsidence phenomena. The proposed methodology consists of three main steps: (1) pre-processing, i.e., assessment of a SAR Dataset Quality Index (SDQI) (2) post-processing, i.e., application of empirical/stochastic methods to improve the TS quality, and (3) trend analysis, i.e., comparative implementation of methodologies for automatic TS analysis. Tests were carried out on TS datasets retrieved from processing of SAR imagery acquired by different radar sensors (i.e., ERS-1/2 SAR, RADARSAT-1, ENVISAT ASAR, ALOS PALSAR, TerraSAR-X, COSMO-SkyMed) using advanced DInSAR techniques (i.e., SqueeSAR™, PSInSAR™, SPN and SBAS). The obtained values of SDQI are discussed against the technical parameters of each data stack (e.g., radar band, number of SAR scenes, temporal coverage, revisiting time), the retrieved coverage of the DInSAR results, and the constraints related to the characterization of the investigated geological processes. Empirical and stochastic approaches were used to demonstrate how the quality of the TS can be improved after the SAR processing, and examples are discussed to mitigate phase unwrapping errors, and remove regional trends, noise and anomalies. Performance assessment of recently developed methods of trend analysis (i.e., PS-Time, Deviation Index and velocity TS) was conducted on two selected study areas in Northern Italy affected by land subsidence and landslides. Results show that the automatic detection of motion trends enhances the interpretation of DInSAR data, since it provides an objective picture of the deformation behaviour recorded through TS and therefore contributes to the understanding of the on-going geological processes.

Onabotulinum toxin A dosage trends over time for adductor spasmodic dysphonia: A 15-year experience.

PubMed

Tang, Christopher G; Novakovic, Daniel; Mor, Niv; Blitzer, Andrew

2016-03-01

Although onabotulinum neurotoxin A (BoNTA) has been used for over three decades for the treatment of adductor spasmodic dysphonia, no study has been performed to look at the trend of BoNTA dosages across time. The goal of this study is to evaluate the dosage trends to determine if the dosage necessary for voice improvement in patients increases over time. Charts were reviewed for patients with 15 years or more of experience. Linear regression analysis was performed to determine correlation coefficients and trends. Fifty-five patients receiving BoNTA injections by the senior author (a.b.) for over 15 years were evaluated. Thirty-nine patients (82% female) met inclusion criteria. Patients received injections over an average of 18.6 years ± 1.36 years, with the longest follow-up of 21.5 years. Of 39 patients, 16 (41%) had a negative correlation coefficient (Pearson's r) suggesting a decrease over time, whereas 23 (59%) had a positive correlation coefficient suggesting an increase over time. The mean correlation coefficient was 0.139 ± 0.534 and P < 0.05 in 19 patients and P > 0.05 in 20 patients. R(2) for all patients were less than 0.75. Onabotulinum neurotoxin A injection dosage trends vary depending on the individual over time. Overall, the dose range appears to be stable in the majority of patients, suggesting that tolerance does not play a significant part in dose variation over time. 4. Laryngoscope, 126:678-681, 2016. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

Detecting long-term growth trends using tree rings: a critical evaluation of methods.

PubMed

Peters, Richard L; Groenendijk, Peter; Vlam, Mart; Zuidema, Pieter A

2015-05-01

Tree-ring analysis is often used to assess long-term trends in tree growth. A variety of growth-trend detection methods (GDMs) exist to disentangle age/size trends in growth from long-term growth changes. However, these detrending methods strongly differ in approach, with possible implications for their output. Here, we critically evaluate the consistency, sensitivity, reliability and accuracy of four most widely used GDMs: conservative detrending (CD) applies mathematical functions to correct for decreasing ring widths with age; basal area correction (BAC) transforms diameter into basal area growth; regional curve standardization (RCS) detrends individual tree-ring series using average age/size trends; and size class isolation (SCI) calculates growth trends within separate size classes. First, we evaluated whether these GDMs produce consistent results applied to an empirical tree-ring data set of Melia azedarach, a tropical tree species from Thailand. Three GDMs yielded similar results - a growth decline over time - but the widely used CD method did not detect any change. Second, we assessed the sensitivity (probability of correct growth-trend detection), reliability (100% minus probability of detecting false trends) and accuracy (whether the strength of imposed trends is correctly detected) of these GDMs, by applying them to simulated growth trajectories with different imposed trends: no trend, strong trends (-6% and +6% change per decade) and weak trends (-2%, +2%). All methods except CD, showed high sensitivity, reliability and accuracy to detect strong imposed trends. However, these were considerably lower in the weak or no-trend scenarios. BAC showed good sensitivity and accuracy, but low reliability, indicating uncertainty of trend detection using this method. Our study reveals that the choice of GDM influences results of growth-trend studies. We recommend applying multiple methods when analysing trends and encourage performing sensitivity and reliability analysis. Finally, we recommend SCI and RCS, as these methods showed highest reliability to detect long-term growth trends. © 2014 John Wiley & Sons Ltd.

Investigating the usefulness of a cluster-based trend analysis to detect visual field progression in patients with open-angle glaucoma.

PubMed

Aoki, Shuichiro; Murata, Hiroshi; Fujino, Yuri; Matsuura, Masato; Miki, Atsuya; Tanito, Masaki; Mizoue, Shiro; Mori, Kazuhiko; Suzuki, Katsuyoshi; Yamashita, Takehiro; Kashiwagi, Kenji; Hirasawa, Kazunori; Shoji, Nobuyuki; Asaoka, Ryo

2017-12-01

To investigate the usefulness of the Octopus (Haag-Streit) EyeSuite's cluster trend analysis in glaucoma. Ten visual fields (VFs) with the Humphrey Field Analyzer (Carl Zeiss Meditec), spanning 7.7 years on average were obtained from 728 eyes of 475 primary open angle glaucoma patients. Mean total deviation (mTD) trend analysis and EyeSuite's cluster trend analysis were performed on various series of VFs (from 1st to 10th: VF1-10 to 6th to 10th: VF6-10). The results of the cluster-based trend analysis, based on different lengths of VF series, were compared against mTD trend analysis. Cluster-based trend analysis and mTD trend analysis results were significantly associated in all clusters and with all lengths of VF series. Between 21.2% and 45.9% (depending on VF series length and location) of clusters were deemed to progress when the mTD trend analysis suggested no progression. On the other hand, 4.8% of eyes were observed to progress using the mTD trend analysis when cluster trend analysis suggested no progression in any two (or more) clusters. Whole field trend analysis can miss local VF progression. Cluster trend analysis appears as robust as mTD trend analysis and useful to assess both sectorial and whole field progression. Cluster-based trend analyses, in particular the definition of two or more progressing cluster, may help clinicians to detect glaucomatous progression in a timelier manner than using a whole field trend analysis, without significantly compromising specificity. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Analysis of phosphorus trends and evaluation of sampling designs in the Quinebaug River Basin, Connecticut

USGS Publications Warehouse

Todd Trench, Elaine C.

2004-01-01

A time-series analysis approach developed by the U.S. Geological Survey was used to analyze trends in total phosphorus and evaluate optimal sampling designs for future trend detection, using long-term data for two water-quality monitoring stations on the Quinebaug River in eastern Connecticut. Trend-analysis results for selected periods of record during 1971?2001 indicate that concentrations of total phosphorus in the Quinebaug River have varied over time, but have decreased significantly since the 1970s and 1980s. Total phosphorus concentrations at both stations increased in the late 1990s and early 2000s, but were still substantially lower than historical levels. Drainage areas for both stations are primarily forested, but water quality at both stations is affected by point discharges from municipal wastewater-treatment facilities. Various designs with sampling frequencies ranging from 4 to 11 samples per year were compared to the trend-detection power of the monthly (12-sample) design to determine the most efficient configuration of months to sample for a given annual sampling frequency. Results from this evaluation indicate that the current (2004) 8-sample schedule for the two Quinebaug stations, with monthly sampling from May to September and bimonthly sampling for the remainder of the year, is not the most efficient 8-sample design for future detection of trends in total phosphorus. Optimal sampling schedules for the two stations differ, but in both cases, trend-detection power generally is greater among 8-sample designs that include monthly sampling in fall and winter. Sampling designs with fewer than 8 samples per year generally provide a low level of probability for detection of trends in total phosphorus. Managers may determine an acceptable level of probability for trend detection within the context of the multiple objectives of the state?s water-quality management program and the scientific understanding of the watersheds in question. Managers may identify a threshold of probability for trend detection that is high enough to justify the agency?s investment in the water-quality sampling program. Results from an analysis of optimal sampling designs can provide an important component of information for the decision-making process in which sampling schedules are periodically reviewed and revised. Results from the study described in this report and previous studies indicate that optimal sampling schedules for trend detection may differ substantially for different stations and constituents. A more comprehensive statewide evaluation of sampling schedules for key stations and constituents could provide useful information for any redesign of the schedule for water-quality monitoring in the Quinebaug River Basin and elsewhere in the state.

Techniques for analyses of trends in GRUAN data

NASA Astrophysics Data System (ADS)

Bodeker, G. E.; Kremser, S.

2015-04-01

The Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) provides reference quality RS92 radiosonde measurements of temperature, pressure and humidity. A key attribute of reference quality measurements, and hence GRUAN data, is that each datum has a well characterized and traceable estimate of the measurement uncertainty. The long-term homogeneity of the measurement records, and their well characterized uncertainties, make these data suitable for reliably detecting changes in global and regional climate on decadal time scales. Considerable effort is invested in GRUAN operations to (i) describe and analyse all sources of measurement uncertainty to the extent possible, (ii) quantify and synthesize the contribution of each source of uncertainty to the total measurement uncertainty, and (iii) verify that the evaluated net uncertainty is within the required target uncertainty. However, if the climate science community is not sufficiently well informed on how to capitalize on this added value, the significant investment in estimating meaningful measurement uncertainties is largely wasted. This paper presents and discusses the techniques that will need to be employed to reliably quantify long-term trends in GRUAN data records. A pedagogical approach is taken whereby numerical recipes for key parts of the trend analysis process are explored. The paper discusses the construction of linear least squares regression models for trend analysis, boot-strapping approaches to determine uncertainties in trends, dealing with the combined effects of autocorrelation in the data and measurement uncertainties in calculating the uncertainty on trends, best practice for determining seasonality in trends, how to deal with co-linear basis functions, and interpreting derived trends. Synthetic data sets are used to demonstrate these concepts which are then applied to a first analysis of temperature trends in RS92 radiosonde upper air soundings at the GRUAN site at Lindenberg, Germany (52.21° N, 14.12° E).

Techniques for analyses of trends in GRUAN data

NASA Astrophysics Data System (ADS)

Bodeker, G. E.; Kremser, S.

2014-12-01

The Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) provides reference quality RS92 radiosonde measurements of temperature, pressure and humidity. A key attribute of reference quality measurements, and hence GRUAN data, is that each datum has a well characterised and traceable estimate of the measurement uncertainty. The long-term homogeneity of the measurement records, and their well characterised uncertainties, make these data suitable for reliably detecting changes in global and regional climate on decadal time scales. Considerable effort is invested in GRUAN operations to (i) describe and analyse all sources of measurement uncertainty to the extent possible, (ii) quantify and synthesize the contribution of each source of uncertainty to the total measurement uncertainty, and (iii) verify that the evaluated net uncertainty is within the required target uncertainty. However, if the climate science community is not sufficiently well informed on how to capitalize on this added value, the significant investment in estimating meaningful measurement uncertainties is largely wasted. This paper presents and discusses the techniques that will need to be employed to reliably quantify long-term trends in GRUAN data records. A pedagogical approach is taken whereby numerical recipes for key parts of the trend analysis process are explored. The paper discusses the construction of linear least squares regression models for trend analysis, boot-strapping approaches to determine uncertainties in trends, dealing with the combined effects of autocorrelation in the data and measurement uncertainties in calculating the uncertainty on trends, best practice for determining seasonality in trends, how to deal with co-linear basis functions, and interpreting derived trends. Synthetic data sets are used to demonstrate these concepts which are then applied to a first analysis of temperature trends in RS92 radiosonde upper air soundings at the GRUAN site at Lindenberg, Germany (52.21° N, 14.12° E).

Spatio-Temporal Trends and Risk Factors for Shigella from 2001 to 2011 in Jiangsu Province, People's Republic of China

PubMed Central

Bao, Changjun; Hu, Jianli; Liu, Wendong; Liang, Qi; Wu, Ying; Norris, Jessie; Peng, Zhihang; Yu, Rongbin; Shen, Hongbing; Chen, Feng

2014-01-01

Objective This study aimed to describe the spatial and temporal trends of Shigella incidence rates in Jiangsu Province, People's Republic of China. It also intended to explore complex risk modes facilitating Shigella transmission. Methods County-level incidence rates were obtained for analysis using geographic information system (GIS) tools. Trend surface and incidence maps were established to describe geographic distributions. Spatio-temporal cluster analysis and autocorrelation analysis were used for detecting clusters. Based on the number of monthly Shigella cases, an autoregressive integrated moving average (ARIMA) model successfully established a time series model. A spatial correlation analysis and a case-control study were conducted to identify risk factors contributing to Shigella transmissions. Results The far southwestern and northwestern areas of Jiangsu were the most infected. A cluster was detected in southwestern Jiangsu (LLR = 11674.74, P<0.001). The time series model was established as ARIMA (1, 12, 0), which predicted well for cases from August to December, 2011. Highways and water sources potentially caused spatial variation in Shigella development in Jiangsu. The case-control study confirmed not washing hands before dinner (OR = 3.64) and not having access to a safe water source (OR = 2.04) as the main causes of Shigella in Jiangsu Province. Conclusion Improvement of sanitation and hygiene should be strengthened in economically developed counties, while access to a safe water supply in impoverished areas should be increased at the same time. PMID:24416167

Evaluating abundance and trends in a Hawaiian avian community using state-space analysis

USGS Publications Warehouse

Camp, Richard J.; Brinck, Kevin W.; Gorresen, P.M.; Paxton, Eben H.

2016-01-01

Estimating population abundances and patterns of change over time are important in both ecology and conservation. Trend assessment typically entails fitting a regression to a time series of abundances to estimate population trajectory. However, changes in abundance estimates from year-to-year across time are due to both true variation in population size (process variation) and variation due to imperfect sampling and model fit. State-space models are a relatively new method that can be used to partition the error components and quantify trends based only on process variation. We compare a state-space modelling approach with a more traditional linear regression approach to assess trends in uncorrected raw counts and detection-corrected abundance estimates of forest birds at Hakalau Forest National Wildlife Refuge, Hawai‘i. Most species demonstrated similar trends using either method. In general, evidence for trends using state-space models was less strong than for linear regression, as measured by estimates of precision. However, while the state-space models may sacrifice precision, the expectation is that these estimates provide a better representation of the real world biological processes of interest because they are partitioning process variation (environmental and demographic variation) and observation variation (sampling and model variation). The state-space approach also provides annual estimates of abundance which can be used by managers to set conservation strategies, and can be linked to factors that vary by year, such as climate, to better understand processes that drive population trends.

[Current Situation and Prospects of Emergency Medical Equipment in Our Country].

PubMed

Qi, Lijing; Cheng, Feng

2016-03-01

This article analyzes the new demand of emergency medical equipment in the current development trend based on the analysis of the development and current situation of emergency medicine in our country. At the same time it introduces the current industrial characteristics of our country. Finally it analyzes the development trend of this kind of equipment in the new emergency medicine field.

Estimating equations estimates of trends

USGS Publications Warehouse

Link, W.A.; Sauer, J.R.

1994-01-01

The North American Breeding Bird Survey monitors changes in bird populations through time using annual counts at fixed survey sites. The usual method of estimating trends has been to use the logarithm of the counts in a regression analysis. It is contended that this procedure is reasonably satisfactory for more abundant species, but produces biased estimates for less abundant species. An alternative estimation procedure based on estimating equations is presented.

Time distortion associated with smartphone addiction: Identifying smartphone addiction via a mobile application (App).

PubMed

Lin, Yu-Hsuan; Lin, Yu-Cheng; Lee, Yang-Han; Lin, Po-Hsien; Lin, Sheng-Hsuan; Chang, Li-Ren; Tseng, Hsien-Wei; Yen, Liang-Yu; Yang, Cheryl C H; Kuo, Terry B J

2015-06-01

Global smartphone penetration has brought about unprecedented addictive behaviors. We report a proposed diagnostic criteria and the designing of a mobile application (App) to identify smartphone addiction. We used a novel empirical mode decomposition (EMD) to delineate the trend in smartphone use over one month. The daily use count and the trend of this frequency are associated with smartphone addiction. We quantify excessive use by daily use duration and frequency, as well as the relationship between the tolerance symptoms and the trend for the median duration of a use epoch. The psychiatrists' assisted self-reporting use time is significant lower than and the recorded total smartphone use time via the App and the degree of underestimation was positively correlated with actual smartphone use. Our study suggests the identification of smartphone addiction by diagnostic interview and via the App-generated parameters with EMD analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multiple time scale analysis of sediment and runoff changes in the Lower Yellow River

NASA Astrophysics Data System (ADS)

Chi, Kaige; Gang, Zhao; Pang, Bo; Huang, Ziqian

2018-06-01

Sediment and runoff changes of seven hydrological stations along the Lower Yellow River (LYR) (Huayuankou Station, Jiahetan Station, Gaocun Station, Sunkou Station, Ai Shan Station, Qikou Station and Lijin Station) from 1980 to 2003 were alanyzed at multiple time scale. The maximum value of monthly, daily and hourly sediment load and runoff conservations were also analyzed with the annually mean value. Mann-Kendall non-parametric mathematics correlation test and Hurst coefficient method were adopted in the study. Research results indicate that (1) the runoff of seven hydrological stations was significantly reduced in the study period at different time scales. However, the trends of sediment load in these stations were not obvious. The sediment load of Huayuankou, Jiahetan and Aishan stations even slightly increased with the runoff decrease. (2) The trends of the sediment load with different time scale showed differences at Luokou and Lijin stations. Although the annually and monthly sediment load were broadly flat, the maximum hourly sediment load showed decrease trend. (3) According to the Hurst coefficients, the trend of sediment and runoff will be continue without taking measures, which proved the necessary of runoff-sediment regulation scheme.

Authorship, collaboration, and funding trends in implantology literature: analysis of five journals from 2005 to 2009.

PubMed

Barão, Valentim Adelino Ricardo; Shyamsunder, Nodesh; Yuan, Judy Chia-Chun; Lee, Damian J; Assunção, Wirley Gonçalves; Sukotjo, Cortino

2011-02-01

To identify the trend of authorship in dental implant by exploring the prevalence of coauthored articles and to investigate the collaboration efforts, trends in funding involved in original articles, and their relationships. Articles published in the Clinical Oral Implants Research, International Journal of Oral & Maxillofacial Implants, Clinical Implant Dentistry and Related Research, Implant Dentistry, and Journal of Oral Implantology from 2005 to 2009 were reviewed. Nonoriginal articles were excluded. For each included articles, number of authors, collaboration efforts, and extramural funding were recorded. Descriptive and analytical statistics (α = 0.05), including logistic regression analysis and χ² test, were used. From a total of 2085 articles, 1503 met the inclusion criteria. Publications with 5 or more authors increased over time (P = 0.813). The amount of collaboration among different disciplines, institutions, and countries all increased. The greatest increase of collaboration was seen among institutions (P = 0.09). Nonfunding studies decreased over time (P = 0.031). There was a strong association between collaboration and funding for the manuscripts during the years studied (OR, 1.5). The number of authors per articles and collaborative studies increased over time in implant-related journals. Collaborative studies were more likely to be funded.

Nonlinear stratospheric variability: multifractal de-trended fluctuation analysis and singularity spectra

PubMed Central

Domeisen, Daniela I. V.

2016-01-01

Characterizing the stratosphere as a turbulent system, temporal fluctuations often show different correlations for different time scales as well as intermittent behaviour that cannot be captured by a single scaling exponent. In this study, the different scaling laws in the long-term stratospheric variability are studied using multifractal de-trended fluctuation analysis (MF-DFA). The analysis is performed comparing four re-analysis products and different realizations of an idealized numerical model, isolating the role of topographic forcing and seasonal variability, as well as the absence of climate teleconnections and small-scale forcing. The Northern Hemisphere (NH) shows a transition of scaling exponents for time scales shorter than about 1 year, for which the variability is multifractal and scales in time with a power law corresponding to a red spectrum, to longer time scales, for which the variability is monofractal and scales in time with a power law corresponding to white noise. Southern Hemisphere (SH) variability also shows a transition at annual scales. The SH also shows a narrower dynamical range in multifractality than the NH, as seen in the generalized Hurst exponent and in the singularity spectra. The numerical integrations show that the models are able to reproduce the low-frequency variability but are not able to fully capture the shorter term variability of the stratosphere. PMID:27493560

Trend Estimation and Regression Analysis in Climatological Time Series: An Application of Structural Time Series Models and the Kalman Filter.

NASA Astrophysics Data System (ADS)

Visser, H.; Molenaar, J.

1995-05-01

The detection of trends in climatological data has become central to the discussion on climate change due to the enhanced greenhouse effect. To prove detection, a method is needed (i) to make inferences on significant rises or declines in trends, (ii) to take into account natural variability in climate series, and (iii) to compare output from GCMs with the trends in observed climate data. To meet these requirements, flexible mathematical tools are needed. A structural time series model is proposed with which a stochastic trend, a deterministic trend, and regression coefficients can be estimated simultaneously. The stochastic trend component is described using the class of ARIMA models. The regression component is assumed to be linear. However, the regression coefficients corresponding with the explanatory variables may be time dependent to validate this assumption. The mathematical technique used to estimate this trend-regression model is the Kaiman filter. The main features of the filter are discussed.Examples of trend estimation are given using annual mean temperatures at a single station in the Netherlands (1706-1990) and annual mean temperatures at Northern Hemisphere land stations (1851-1990). The inclusion of explanatory variables is shown by regressing the latter temperature series on four variables: Southern Oscillation index (SOI), volcanic dust index (VDI), sunspot numbers (SSN), and a simulated temperature signal, induced by increasing greenhouse gases (GHG). In all analyses, the influence of SSN on global temperatures is found to be negligible. The correlations between temperatures and SOI and VDI appear to be negative. For SOI, this correlation is significant, but for VDI it is not, probably because of a lack of volcanic eruptions during the sample period. The relation between temperatures and GHG is positive, which is in agreement with the hypothesis of a warming climate because of increasing levels of greenhouse gases. The prediction performance of the model is rather poor, and possible explanations are discussed.

Increased trend in extracorporeal membrane oxygenation use by adults in the United States since 2007.

PubMed

Gerke, Alicia K; Tang, Fan; Cavanaugh, Joseph E; Doerschug, Kevin C; Polgreen, Philip M

2015-11-18

Extracorporeal membrane oxygenation (ECMO) has been increasingly studied as a life support modality, but it is unclear if its use has changed over time. Recent publication shows no significant trend in use of ECMO over time; however, this report does not include more recent data. We performed trend analysis to determine if and when the use of ECMO changed in the past decade. We identified hospitalizations (2000-2011) in the Nationwide Inpatient Sample during which ECMO was recorded. We used a segmented linear regression model to determine trend and to identify a temporal change point when rate of ECMO use increased. ECMO use gradually grew until 2007, at which time there was a dramatic increase in the rate (p = 0.0003). There was no difference in mortality after 2007 (p = 0.3374), but there was longer length of stay (p = 0.0001) and smaller percentage of women (p = 0.005). There has been a marked increase in ECMO use since 2007. As ECMO use becomes more common, further study regarding indications, cost-effectiveness, and outcomes is warranted to guide optimal use.

Statistical trend analysis and extreme distribution of significant wave height from 1958 to 1999 - an application to the Italian Seas

NASA Astrophysics Data System (ADS)

Martucci, G.; Carniel, S.; Chiggiato, J.; Sclavo, M.; Lionello, P.; Galati, M. B.

2010-06-01

The study is a statistical analysis of sea states timeseries derived using the wave model WAM forced by the ERA-40 dataset in selected areas near the Italian coasts. For the period 1 January 1958 to 31 December 1999 the analysis yields: (i) the existence of a negative trend in the annual- and winter-averaged sea state heights; (ii) the existence of a turning-point in late 80's in the annual-averaged trend of sea state heights at a site in the Northern Adriatic Sea; (iii) the overall absence of a significant trend in the annual-averaged mean durations of sea states over thresholds; (iv) the assessment of the extreme values on a time-scale of thousand years. The analysis uses two methods to obtain samples of extremes from the independent sea states: the r-largest annual maxima and the peak-over-threshold. The two methods show statistical differences in retrieving the return values and more generally in describing the significant wave field. The r-largest annual maxima method provides more reliable predictions of the extreme values especially for small return periods (<100 years). Finally, the study statistically proves the existence of decadal negative trends in the significant wave heights and by this it conveys useful information on the wave climatology of the Italian seas during the second half of the 20th century.

Analysis of soybean production and import trends and its import factors in Indonesia

NASA Astrophysics Data System (ADS)

Ningrum, I. H.; Irianto, H.; Riptanti, E. W.

2018-03-01

This study aims to analyze the factors affecting soybean imports in Indonesia and to know the trend and projection of Indonesian soybean production as well as the import in 2016-2020. The basic method used in this research is the description analysis method. The data used are secondary data in the form of time series data from 1979-2015. Methods of data analysis using simultaneous equations model with 2SLS (Two Stage Least Square) method and Trend analysis. The results showed that the factors affecting soybean imports in Indonesia are consumption and production. Consumption has positive effect while production is negatively affected. The percentage changed in soybean imports is greater than the percentage change in consumption and production of soybeans. Consumption is positively influenced by imports and production, while production is influenced positively by consumption and negative by imports. The production trend of soybean in 2016-2020 has a tendency to increase with a percentage of 11.18% per year. Production in 2016 is projected at 1.110.537 tons while in 2020 it will increase to 1,721,350 tons. The import trend in 2016-2020 has a tendency to increase with an average percentage of 4.13% per year. Import in 2016 is projected at 2.224.188 tons while in 2020 it will increase to 2.611.270 tons.

Geographical, temporal and racial disparities in late-stage prostate cancer incidence across Florida: A multiscale joinpoint regression analysis

PubMed Central

2011-01-01

Background Although prostate cancer-related incidence and mortality have declined recently, striking racial/ethnic differences persist in the United States. Visualizing and modelling temporal trends of prostate cancer late-stage incidence, and how they vary according to geographic locations and race, should help explaining such disparities. Joinpoint regression is increasingly used to identify the timing and extent of changes in time series of health outcomes. Yet, most analyses of temporal trends are aspatial and conducted at the national level or for a single cancer registry. Methods Time series (1981-2007) of annual proportions of prostate cancer late-stage cases were analyzed for non-Hispanic Whites and non-Hispanic Blacks in each county of Florida. Noise in the data was first filtered by binomial kriging and results were modelled using joinpoint regression. A similar analysis was also conducted at the state level and for groups of metropolitan and non-metropolitan counties. Significant racial differences were detected using tests of parallelism and coincidence of time trends. A new disparity statistic was introduced to measure spatial and temporal changes in the frequency of racial disparities. Results State-level percentage of late-stage diagnosis decreased 50% since 1981; a decline that accelerated in the 90's when Prostate Specific Antigen (PSA) screening was introduced. Analysis at the metropolitan and non-metropolitan levels revealed that the frequency of late-stage diagnosis increased recently in urban areas, and this trend was significant for white males. The annual rate of decrease in late-stage diagnosis and the onset years for significant declines varied greatly among counties and racial groups. Most counties with non-significant average annual percent change (AAPC) were located in the Florida Panhandle for white males, whereas they clustered in South-eastern Florida for black males. The new disparity statistic indicated that the spatial extent of racial disparities reached a peak in 1990 because of an early decline in frequency of late-stage diagnosis observed for black males. Conclusions Analyzing temporal trends in cancer incidence and mortality rates outside a spatial framework is unsatisfactory, since it leads one to overlook significant geographical variation which can potentially generate new insights about the impact of various interventions. Differences observed among nested geographies in Florida show how the modifiable areal unit problem (MAUP) also impacts the analysis of temporal changes. PMID:22142274

Geographical, temporal and racial disparities in late-stage prostate cancer incidence across Florida: a multiscale joinpoint regression analysis.

PubMed

Goovaerts, Pierre; Xiao, Hong

2011-12-05

Although prostate cancer-related incidence and mortality have declined recently, striking racial/ethnic differences persist in the United States. Visualizing and modelling temporal trends of prostate cancer late-stage incidence, and how they vary according to geographic locations and race, should help explaining such disparities. Joinpoint regression is increasingly used to identify the timing and extent of changes in time series of health outcomes. Yet, most analyses of temporal trends are aspatial and conducted at the national level or for a single cancer registry. Time series (1981-2007) of annual proportions of prostate cancer late-stage cases were analyzed for non-Hispanic Whites and non-Hispanic Blacks in each county of Florida. Noise in the data was first filtered by binomial kriging and results were modelled using joinpoint regression. A similar analysis was also conducted at the state level and for groups of metropolitan and non-metropolitan counties. Significant racial differences were detected using tests of parallelism and coincidence of time trends. A new disparity statistic was introduced to measure spatial and temporal changes in the frequency of racial disparities. State-level percentage of late-stage diagnosis decreased 50% since 1981; a decline that accelerated in the 90's when Prostate Specific Antigen (PSA) screening was introduced. Analysis at the metropolitan and non-metropolitan levels revealed that the frequency of late-stage diagnosis increased recently in urban areas, and this trend was significant for white males. The annual rate of decrease in late-stage diagnosis and the onset years for significant declines varied greatly among counties and racial groups. Most counties with non-significant average annual percent change (AAPC) were located in the Florida Panhandle for white males, whereas they clustered in South-eastern Florida for black males. The new disparity statistic indicated that the spatial extent of racial disparities reached a peak in 1990 because of an early decline in frequency of late-stage diagnosis observed for black males. Analyzing temporal trends in cancer incidence and mortality rates outside a spatial framework is unsatisfactory, since it leads one to overlook significant geographical variation which can potentially generate new insights about the impact of various interventions. Differences observed among nested geographies in Florida show how the modifiable areal unit problem (MAUP) also impacts the analysis of temporal changes.

Trends in US home food preparation and consumption: analysis of national nutrition surveys and time use studies from 1965-1966 to 2007-2008.

PubMed

Smith, Lindsey P; Ng, Shu Wen; Popkin, Barry M

2013-04-11

It has been well-documented that Americans have shifted towards eating out more and cooking at home less. However, little is known about whether these trends have continued into the 21st century, and whether these trends are consistent amongst low-income individuals, who are increasingly the target of public health programs that promote home cooking. The objective of this study is to examine how patterns of home cooking and home food consumption have changed from 1965 to 2008 by socio-demographic groups. This is a cross-sectional analysis of data from 6 nationally representative US dietary surveys and 6 US time-use studies conducted between 1965 and 2008. Subjects are adults aged 19 to 60 years (n= 38,565 for dietary surveys and n=55,424 for time-use surveys). Weighted means of daily energy intake by food source, proportion who cooked, and time spent cooking were analyzed for trends from 1965-1966 to 2007-2008 by gender and income. T-tests were conducted to determine statistical differences over time. The percentage of daily energy consumed from home food sources and time spent in food preparation decreased significantly for all socioeconomic groups between 1965-1966 and 2007-2008 (p ≤ 0.001), with the largest declines occurring between 1965 and 1992. In 2007-2008, foods from the home supply accounted for 65 to 72% of total daily energy, with 54 to 57% reporting cooking activities. The low income group showed the greatest decline in the proportion cooking, but consumed more daily energy from home sources and spent more time cooking than high income individuals in 2007-2008 (p ≤ 0.001). US adults have decreased consumption of foods from the home supply and reduced time spent cooking since 1965, but this trend appears to have leveled off, with no substantial decrease occurring after the mid-1990's. Across socioeconomic groups, people consume the majority of daily energy from the home food supply, yet only slightly more than half spend any time cooking on a given day. Efforts to boost the healthfulness of the US diet should focus on promoting the preparation of healthy foods at home while incorporating limits on time available for cooking.

Trends in US home food preparation and consumption: analysis of national nutrition surveys and time use studies from 1965–1966 to 2007–2008

PubMed Central

2013-01-01

Background It has been well-documented that Americans have shifted towards eating out more and cooking at home less. However, little is known about whether these trends have continued into the 21st century, and whether these trends are consistent amongst low-income individuals, who are increasingly the target of public health programs that promote home cooking. The objective of this study is to examine how patterns of home cooking and home food consumption have changed from 1965 to 2008 by socio-demographic groups. Methods This is a cross-sectional analysis of data from 6 nationally representative US dietary surveys and 6 US time-use studies conducted between 1965 and 2008. Subjects are adults aged 19 to 60 years (n= 38,565 for dietary surveys and n=55,424 for time-use surveys). Weighted means of daily energy intake by food source, proportion who cooked, and time spent cooking were analyzed for trends from 1965–1966 to 2007–2008 by gender and income. T-tests were conducted to determine statistical differences over time. Results The percentage of daily energy consumed from home food sources and time spent in food preparation decreased significantly for all socioeconomic groups between 1965–1966 and 2007–2008 (p ≤ 0.001), with the largest declines occurring between 1965 and 1992. In 2007–2008, foods from the home supply accounted for 65 to 72% of total daily energy, with 54 to 57% reporting cooking activities. The low income group showed the greatest decline in the proportion cooking, but consumed more daily energy from home sources and spent more time cooking than high income individuals in 2007–2008 (p ≤ 0.001). Conclusions US adults have decreased consumption of foods from the home supply and reduced time spent cooking since 1965, but this trend appears to have leveled off, with no substantial decrease occurring after the mid-1990’s. Across socioeconomic groups, people consume the majority of daily energy from the home food supply, yet only slightly more than half spend any time cooking on a given day. Efforts to boost the healthfulness of the US diet should focus on promoting the preparation of healthy foods at home while incorporating limits on time available for cooking. PMID:23577692

Principal regression analysis and the index leverage effect

NASA Astrophysics Data System (ADS)

Reigneron, Pierre-Alain; Allez, Romain; Bouchaud, Jean-Philippe

2011-09-01

We revisit the index leverage effect, that can be decomposed into a volatility effect and a correlation effect. We investigate the latter using a matrix regression analysis, that we call ‘Principal Regression Analysis' (PRA) and for which we provide some analytical (using Random Matrix Theory) and numerical benchmarks. We find that downward index trends increase the average correlation between stocks (as measured by the most negative eigenvalue of the conditional correlation matrix), and makes the market mode more uniform. Upward trends, on the other hand, also increase the average correlation between stocks but rotates the corresponding market mode away from uniformity. There are two time scales associated to these effects, a short one on the order of a month (20 trading days), and a longer time scale on the order of a year. We also find indications of a leverage effect for sectorial correlations as well, which reveals itself in the second and third mode of the PRA.

Economic growth and obesity in South African adults: an ecological analysis between 1994 and 2014.

PubMed

Pisa, Pedro T; Pisa, Noleen M

2017-06-01

To assess the trend associations between South Africa's economic growth using various economic growth indicators (EGIs) with adult obesity prevalence over a specified period of time. Data for obesity levels reported were obtained from national surveys conducted in South African adults in 1998, 2003 and 2012. EGIs incorporated in the current analysis were obtained from the World Bank and IHS Global insight databases. Obesity prevalence is presented by gender, urbanisation level and ethnicity. EGIs congruent to the time points where obesity data are available are presented. Unadjusted time trend plots were applied to assess associations between obesity prevalence and EGIs by gender, urbanisation level and ethnicity. Females present higher levels of obesity relative to males for all time points. For both males and females, an overall increase in prevalence was observed in both rural and urban settings over-time, with urban dwellers presenting higher obesity levels. An overall increase in Gross Domestic Product (GDP) per capita and Household Final Consumption Expenditure (HFCE) per capita was observed. The Gini coefficient for all ethnicities except the White population increased between 1998 and 2003 but declined by 2012. Overtime per capita GDP and HFCE increased with increasing obesity prevalence in both genders. The trend association between the Gini coefficient for all ethnicities and obesity prevalence was similar for both genders in that as the Gini coefficient increased obesity prevalence declined, and when the coefficient decreased obesity prevalence increased. Trend associations exist between South Africa's economic growth and adult obesity. © The Author 2016. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Unemployment and prostate cancer mortality in the OECD, 1990–2009

PubMed Central

Maruthappu, Mahiben; Watkins, Johnathan; Taylor, Abigail; Williams, Callum; Ali, Raghib; Zeltner, Thomas; Atun, Rifat

2015-01-01

The global economic downturn has been associated with increased unemployment in many countries. Insights into the impact of unemployment on specific health conditions remain limited. We determined the association between unemployment and prostate cancer mortality in members of the Organisation for Economic Co-operation and Development (OECD). We used multivariate regression analysis to assess the association between changes in unemployment and prostate cancer mortality in OECD member states between 1990 and 2009. Country-specific differences in healthcare infrastructure, population structure, and population size were controlled for and lag analyses conducted. Several robustness checks were also performed. Time trend analyses were used to predict the number of excess deaths from prostate cancer following the 2008 global recession. Between 1990 and 2009, a 1% rise in unemployment was associated with an increase in prostate cancer mortality. Lag analysis showed a continued increase in mortality years after unemployment rises. The association between unemployment and prostate cancer mortality remained significant in robustness checks with 46 controls. Eight of the 21 OECD countries for which a time trend analysis was conducted, exhibited an estimated excess of prostate cancer deaths in at least one of 2008, 2009, or 2010, based on 2000–2007 trends. Rises in unemployment are associated with significant increases in prostate cancer mortality. Initiatives that bolster employment may help to minimise prostate cancer mortality during times of economic hardship. PMID:26045715

Assessment of the effects of horizontal grid resolution on long ...

EPA Pesticide Factsheets

The objective of this study is to determine the adequacy of using a relatively coarse horizontal resolution (i.e. 36 km) to simulate long-term trends of pollutant concentrations and radiation variables with the coupled WRF-CMAQ model. WRF-CMAQ simulations over the continental United State are performed over the 2001 to 2010 time period at two different horizontal resolutions of 12 and 36 km. Both simulations used the same emission inventory and model configurations. Model results are compared both in space and time to assess the potential weaknesses and strengths of using coarse resolution in long-term air quality applications. The results show that the 36 km and 12 km simulations are comparable in terms of trends analysis for both pollutant concentrations and radiation variables. The advantage of using the coarser 36 km resolution is a significant reduction of computational cost, time and storage requirement which are key considerations when performing multiple years of simulations for trend analysis. However, if such simulations are to be used for local air quality analysis, finer horizontal resolution may be beneficial since it can provide information on local gradients. In particular, divergences between the two simulations are noticeable in urban, complex terrain and coastal regions. The National Exposure Research Laboratory’s Atmospheric Modeling Division (AMAD) conducts research in support of EPA’s mission to protect human health and the environment.

Unemployment and prostate cancer mortality in the OECD, 1990-2009.

PubMed

Maruthappu, Mahiben; Watkins, Johnathan; Taylor, Abigail; Williams, Callum; Ali, Raghib; Zeltner, Thomas; Atun, Rifat

2015-01-01

The global economic downturn has been associated with increased unemployment in many countries. Insights into the impact of unemployment on specific health conditions remain limited. We determined the association between unemployment and prostate cancer mortality in members of the Organisation for Economic Co-operation and Development (OECD). We used multivariate regression analysis to assess the association between changes in unemployment and prostate cancer mortality in OECD member states between 1990 and 2009. Country-specific differences in healthcare infrastructure, population structure, and population size were controlled for and lag analyses conducted. Several robustness checks were also performed. Time trend analyses were used to predict the number of excess deaths from prostate cancer following the 2008 global recession. Between 1990 and 2009, a 1% rise in unemployment was associated with an increase in prostate cancer mortality. Lag analysis showed a continued increase in mortality years after unemployment rises. The association between unemployment and prostate cancer mortality remained significant in robustness checks with 46 controls. Eight of the 21 OECD countries for which a time trend analysis was conducted, exhibited an estimated excess of prostate cancer deaths in at least one of 2008, 2009, or 2010, based on 2000-2007 trends. Rises in unemployment are associated with significant increases in prostate cancer mortality. Initiatives that bolster employment may help to minimise prostate cancer mortality during times of economic hardship.

Comparison of trends and abrupt changes of the South Asia high from 1979 to 2014 in reanalysis and radiosonde datasets

NASA Astrophysics Data System (ADS)

Shi, Chunhua; Huang, Ying; Guo, Dong; Zhou, Shunwu; Hu, Kaixi; Liu, Yu

2018-05-01

The South Asian High (SAH) has an important influence on atmospheric circulation and the Asian climate in summer. However, current comparative analyses of the SAH are mostly between reanalysis datasets and there is a lack of sounding data. We therefore compared the climatology, trends and abrupt changes in the SAH in the Japanese 55-year Reanalysis (JRA-55) dataset, the National Centers for Environmental Prediction Climate Forecast System Reanalysis (NCEP-CFSR) dataset, the European Center for Medium-Range Weather Forecasts Reanalysis Interim (ERA-interim) dataset and radiosonde data from China using linear analysis and a sliding t-test. The trends in geopotential height in the control area of the SAH were positive in the JRA-55, NCEP-CFSR and ERA-interim datasets, but negative in the radiosonde data in the time period 1979-2014. The negative trends for the SAH were significant at the 90% confidence level in the radiosonde data from May to September. The positive trends in the NCEP-CFSR dataset were significant at the 90% confidence level in May, July, August and September, but the positive trends in the JRA-55 and ERA-Interim were only significant at the 90% confidence level in September. The reasons for the differences in the trends of the SAH between the radiosonde data and the three reanalysis datasets in the time period 1979-2014 were updates to the sounding systems, changes in instrumentation and improvements in the radiation correction method for calculations around the year 2000. We therefore analyzed the trends in the two time periods of 1979-2000 and 2001-2014 separately. From 1979 to 2000, the negative SAH trends in the radiosonde data mainly agreed with the negative trends in the NCEP-CFSR dataset, but were in contrast with the positive trends in the JRA-55 and ERA-Interim datasets. In 2001-2014, however, the trends in the SAH were positive in all four datasets and most of the trends in the radiosonde and NCEP-CFSR datasets were significant. It is therefore better to use the NCEP-CFSR dataset than the JRA-55 and ERA-Interim datasets when discussing trends in the SAH.

Stratospheric Ozone Trends and Variability as Seen by SCIAMACHY from 2002 to 2012

NASA Technical Reports Server (NTRS)

Gebhardt, C.; Rozanov, A.; Hommel, R.; Weber, M.; Bovensmann, H.; Burrows, J. P.; Degenstein, D.; Froidevaux, L.; Thompson, A. M.

2014-01-01

Vertical profiles of the rate of linear change (trend) in the altitude range 15-50 km are determined from decadal O3 time series obtained from SCIAMACHY/ENVISAT measurements in limb-viewing geometry. The trends are calculated by using a multivariate linear regression. Seasonal variations, the quasi-biennial oscillation, signatures of the solar cycle and the El Nino-Southern Oscillation are accounted for in the regression. The time range of trend calculation is August 2002-April 2012. A focus for analysis are the zonal bands of 20 deg N - 20 deg S (tropics), 60 - 50 deg N, and 50 - 60 deg S (midlatitudes). In the tropics, positive trends of up to 5% per decade between 20 and 30 km and negative trends of up to 10% per decade between 30 and 38 km are identified. Positive O3 trends of around 5% per decade are found in the upper stratosphere in the tropics and at midlatitudes. Comparisons between SCIAMACHY and EOS MLS show reasonable agreement both in the tropics and at midlatitudes for most altitudes. In the tropics, measurements from OSIRIS/Odin and SHADOZ are also analysed. These yield rates of linear change of O3 similar to those from SCIAMACHY. However, the trends from SCIAMACHY near 34 km in the tropics are larger than MLS and OSIRIS by a factor of around two.

Evidence for an earlier greenhouse cooling effect in the stratosphere before the 1980s over the Northern Hemisphere

NASA Astrophysics Data System (ADS)

Zerefos, C. S.; Tourpali, K.; Zanis, P.; Eleftheratos, K.; Repapis, C.; Goodman, A.; Wuebbles, D.; Isaksen, I. S. A.; Luterbacher, J.

2014-01-01

This study provides a new look at the observed and calculated long-term temperature changes since 1958 for the region extending from the lower troposphere up to the lower stratosphere of the Northern Hemisphere. The analysis is mainly based on monthly layer mean temperatures derived from geopotential height thicknesses between specific pressure levels. Layer mean temperatures from thickness improve homogeneity in both space and time and reduce uncertainties in the trend analysis. Datasets used include the NCEP/NCAR I reanalysis, the Free University of Berlin (FU-Berlin) and the RICH radiosonde datasets as well as historical simulations with the CESM1-WACCM global model participating in CMIP5. After removing the natural variability with an autoregressive multiple regression model our analysis shows that the time interval of our study 1958-2011 can be divided in two distinct sub-periods of long term temperature variability and trends; before and after 1980s. By calculating trends for the summer time to reduce interannual variability, the two periods are as follows. From 1958 until 1979, non-significant trends or slight cooling trends prevail in the lower troposphere (0.06 ± 0.06 °C decade-1 for NCEP and -0.12 ± 0.06 °C decade-1 for RICH). The second period from 1980 to the end of the records shows significant warming trends (0.25 ± 0.05 °C decade-1 for both NCEP and RICH). Above the tropopause a persistent cooling trend is clearly seen in the lower stratosphere both in the pre-1980s period (-0.58 ± 0.17 °C decade-1 for NCEP, -0.30 ± 0.16 °C decade-1 for RICH and -0.48 ± 0.20 °C decade-1 for FU-Berlin) and the post-1980s period (-0.79 ± 0.18 °C decade-1 for NCEP, -0.66 ± 0.16 °C decade-1 for RICH and -0.82 ± 0.19 °C decade-1 for FU-Berlin). The cooling in the lower stratosphere is a persistent feature from the tropics up to 60 north for all months. At polar latitudes competing dynamical and radiative processes are reducing the statistical significance of these trends. Model results are in line with re-analysis and the observations, indicating a persistent cooling in the lower stratosphere during summer before and after the 1980s by -0.33 °C decade-1; a feature that is also seen throughout the year. However, the lower stratosphere modelled trends are generally lower than re-analysis and the observations. The contrasting effects of ozone depletion at polar latitudes in winter/spring and the anticipated strengthening of the Brewer Dobson circulation from man-made global warming at polar latitudes are discussed. Our results provide additional evidence for an early greenhouse cooling signal in the lower stratosphere before the 1980s, which it appears well in advance relative to the tropospheric greenhouse warming signal. Hence it may be postulated that the stratosphere could have provided an early warning of man-made climate change. The suitability for early warning signals in the stratosphere relative to the troposphere is supported by the fact that the stratosphere is less sensitive to changes due to cloudiness, humidity and man-made aerosols. Our analysis also indicates that the relative contribution of the lower stratosphere vs. the upper troposphere low frequency variability is important for understanding the added value of the long term tropopause variability related to human induced global warming.

Cone-Beam Computed Tomography–Guided Positioning of Laryngeal Cancer Patients with Large Interfraction Time Trends in Setup and Nonrigid Anatomy Variations

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

Gangsaas, Anne, E-mail: a.gangsaas@erasmusmc.nl; Astreinidou, Eleftheria; Quint, Sandra

2013-10-01

Purpose: To investigate interfraction setup variations of the primary tumor, elective nodes, and vertebrae in laryngeal cancer patients and to validate protocols for cone beam computed tomography (CBCT)-guided correction. Methods and Materials: For 30 patients, CBCT-measured displacements in fractionated treatments were used to investigate population setup errors and to simulate residual setup errors for the no action level (NAL) offline protocol, the extended NAL (eNAL) protocol, and daily CBCT acquisition with online analysis and repositioning. Results: Without corrections, 12 of 26 patients treated with radical radiation therapy would have experienced a gradual change (time trend) in primary tumor setup ≥4more » mm in the craniocaudal (CC) direction during the fractionated treatment (11/12 in caudal direction, maximum 11 mm). Due to these trends, correction of primary tumor displacements with NAL resulted in large residual CC errors (required margin 6.7 mm). With the weekly correction vector adjustments in eNAL, the trends could be largely compensated (CC margin 3.5 mm). Correlation between movements of the primary and nodal clinical target volumes (CTVs) in the CC direction was poor (r{sup 2}=0.15). Therefore, even with online setup corrections of the primary CTV, the required CC margin for the nodal CTV was as large as 6.8 mm. Also for the vertebrae, large time trends were observed for some patients. Because of poor CC correlation (r{sup 2}=0.19) between displacements of the primary CTV and the vertebrae, even with daily online repositioning of the vertebrae, the required CC margin around the primary CTV was 6.9 mm. Conclusions: Laryngeal cancer patients showed substantial interfraction setup variations, including large time trends, and poor CC correlation between primary tumor displacements and motion of the nodes and vertebrae (internal tumor motion). These trends and nonrigid anatomy variations have to be considered in the choice of setup verification protocol and planning target volume margins. eNAL could largely compensate time trends with minor prolongation of fraction time.« less

Spatial and temporal trends of drought effects in a heterogeneous semi-arid forest ecosystem

USGS Publications Warehouse

Assal, Timothy J.; Anderson, Patrick J.; Sibold, Jason

2016-01-01

Drought has long been recognized as a driving mechanism in the forests of western North America and drought-induced mortality has been documented across genera in recent years. Given the frequency of these events are expected to increase in the future, understanding patterns of mortality and plant response to severe drought is important to resource managers. Drought can affect the functional, physiological, structural, and demographic properties of forest ecosystems. Remote sensing studies have documented changes in forest properties due to direct and indirect effects of drought; however, few studies have addressed this at local scales needed to characterize highly heterogeneous ecosystems in the forest-shrubland ecotone. We analyzed a 22-year Landsat time series (1985–2012) to determine changes in forest in an area that experienced a relatively dry decade punctuated by two years of extreme drought. We assessed the relationship between several vegetation indices and field measured characteristics (e.g. plant area index and canopy gap fraction) and applied these indices to trend analysis to uncover the location, direction and timing of change. Finally, we assessed the interaction of climate and topography by forest functional type. The Normalized Difference Moisture Index (NDMI), a measure of canopy water content, had the strongest correlation with short-term field measures of plant area index (R2 = 0.64) and canopy gap fraction (R2 = 0.65). Over the entire time period, 25% of the forested area experienced a significant (p-value < 0.05) negative trend in NDMI, compared to less than 10% in a positive trend. Coniferous forests were more likely to be associated with a negative NDMI trend than deciduous forest. Forests on southern aspects were least likely to exhibit a negative trend while north aspects were most prevalent. Field plots with a negative trend had a lower live density, and higher amounts of standing dead and down trees compared to plots with no trend. Our analysis identifies spatially explicit patterns of long-term trends anchored with ground based evidence to highlight areas of forest that are resistant, persistent or vulnerable to severe drought. The results provide a long-term perspective for the resource management of this area and can be applied to similar ecosystems throughout western North America.

Trends in biomedical informatics: automated topic analysis of JAMIA articles

PubMed Central

Wang, Shuang; Jiang, Chao; Jiang, Xiaoqian; Kim, Hyeon-Eui; Sun, Jimeng; Ohno-Machado, Lucila

2015-01-01

Biomedical Informatics is a growing interdisciplinary field in which research topics and citation trends have been evolving rapidly in recent years. To analyze these data in a fast, reproducible manner, automation of certain processes is needed. JAMIA is a “generalist” journal for biomedical informatics. Its articles reflect the wide range of topics in informatics. In this study, we retrieved Medical Subject Headings (MeSH) terms and citations of JAMIA articles published between 2009 and 2014. We use tensors (i.e., multidimensional arrays) to represent the interaction among topics, time and citations, and applied tensor decomposition to automate the analysis. The trends represented by tensors were then carefully interpreted and the results were compared with previous findings based on manual topic analysis. A list of most cited JAMIA articles, their topics, and publication trends over recent years is presented. The analyses confirmed previous studies and showed that, from 2012 to 2014, the number of articles related to MeSH terms Methods, Organization & Administration, and Algorithms increased significantly both in number of publications and citations. Citation trends varied widely by topic, with Natural Language Processing having a large number of citations in particular years, and Medical Record Systems, Computerized remaining a very popular topic in all years. PMID:26555018

Timescales for determining temperature and dissolved oxygen trends in the Long Island Sound (LIS) estuary

NASA Astrophysics Data System (ADS)

Staniec, Allison; Vlahos, Penny

2017-12-01

Long-term time series represent a critical part of the oceanographic community's efforts to discern natural and anthropogenically forced variations in the environment. They provide regular measurements of climate relevant indicators including temperature, oxygen concentrations, and salinity. When evaluating time series, it is essential to isolate long-term trends from autocorrelation in data and noise due to natural variability. Herein we apply a statistical approach, well-established in atmospheric time series, to key parameters in the U.S. east coast's Long Island Sound estuary (LIS). Analysis shows that the LIS time series (established in the early 1990s) is sufficiently long to detect significant trends in physical-chemical parameters including temperature (T) and dissolved oxygen (DO). Over the last two decades, overall (combined surface and deep) LIS T has increased at an average rate of 0.08 ± 0.03 °C yr-1 while overall DO has dropped at an average rate of 0.03 ± 0.01 mg L-1yr-1 since 1994 at the 95% confidence level. This trend is notably faster than the global open ocean T trend (0.01 °C yr-1), as might be expected for a shallower estuarine system. T and DO trends were always significant for the existing time series using four month data increments. Rates of change of DO and T in LIS are strongly correlated and the rate of decrease of DO concentrations is consistent with the expected reduced solubility of DO at these higher temperatures. Thus, changes in T alone, across decadal timescales can account for between 33 and 100% of the observed decrease in DO. This has significant implications for other dissolved gases and the long-term management of LIS hypoxia.

A Methodological Framework for Model Selection in Interrupted Time Series Studies.

PubMed

Lopez Bernal, J; Soumerai, S; Gasparrini, A

2018-06-06

Interrupted time series is a powerful and increasingly popular design for evaluating public health and health service interventions. The design involves analysing trends in the outcome of interest and estimating the change in trend following an intervention relative to the counterfactual (the expected ongoing trend if the intervention had not occurred). There are two key components to modelling this effect: first, defining the counterfactual; second, defining the type of effect that the intervention is expected to have on the outcome, known as the impact model. The counterfactual is defined by extrapolating the underlying trends observed before the intervention to the post-intervention period. In doing this, authors must consider the pre-intervention period that will be included, any time varying confounders, whether trends may vary within different subgroups of the population and whether trends are linear or non-linear. Defining the impact model involves specifying the parameters that model the intervention, including for instance whether to allow for an abrupt level change or a gradual slope change, whether to allow for a lag before any effect on the outcome, whether to allow a transition period during which the intervention is being implemented and whether a ceiling or floor effect might be expected. Inappropriate model specification can bias the results of an interrupted time series analysis and using a model that is not closely tailored to the intervention or testing multiple models increases the risk of false positives being detected. It is important that authors use substantive knowledge to customise their interrupted time series model a priori to the intervention and outcome under study. Where there is uncertainty in model specification, authors should consider using separate data sources to define the intervention, running limited sensitivity analyses or undertaking initial exploratory studies. Copyright © 2018. Published by Elsevier Inc.

Internet search trends analysis tools can provide real-time data on kidney stone disease in the United States.

PubMed

Willard, Scott D; Nguyen, Mike M

2013-01-01

To evaluate the utility of using Internet search trends data to estimate kidney stone occurrence and understand the priorities of patients with kidney stones. Internet search trends data represent a unique resource for monitoring population self-reported illness and health information-seeking behavior. The Google Insights for Search analysis tool was used to study searches related to kidney stones, with each search term returning a search volume index (SVI) according to the search frequency relative to the total search volume. SVIs for the term, "kidney stones," were compiled by location and time parameters and compared with the published weather and stone prevalence data. Linear regression analysis was performed to determine the association of the search interest score with known epidemiologic variations in kidney stone disease, including latitude, temperature, season, and state. The frequency of the related search terms was categorized by theme and qualitatively analyzed. The SVI correlated significantly with established kidney stone epidemiologic predictors. The SVI correlated with the state latitude (R-squared=0.25; P<.001), the state mean annual temperature (R-squared=0.24; P<.001), and state combined sex prevalence (R-squared=0.25; P<.001). Female prevalence correlated more strongly than did male prevalence (R-squared=0.37; P<.001, and R-squared=0.17; P=.003, respectively). The national SVI correlated strongly with the average U.S. temperature by month (R-squared=0.54; P=.007). The search term ranking suggested that Internet users are most interested in the diagnosis, followed by etiology, infections, and treatment. Geographic and temporal variability in kidney stone disease appear to be accurately reflected in Internet search trends data. Internet search trends data might have broader applications for epidemiologic and urologic research. Copyright © 2013 Elsevier Inc. All rights reserved.

Deregulation of sale of over-the-counter drugs outside of pharmacies in the Republic of Korea: interrupted-time-series analysis of outpatient visits before and after the policy.

PubMed

Chun, Sung-Youn; Park, Hye-Ki; Han, Kyu-Tae; Kim, Woorim; Lee, Hyo-Jung; Park, Eun-Cheol

2017-07-12

We evaluated the effectiveness of a policy allowing for the sale of over-the-counter drugs outside of pharmacies by examining its effect on number of monthly outpatient visits for acute upper respiratory infections, dyspepsia, and migraine. We used medical claims data extracted from the Korean National Health Insurance Cohort Database from 2009 to 2013. The Korean National Health Insurance Cohort Database comprises a nationally representative sample of claims - about 2% of the entire population - obtained from the medical record data held by the Korean National Health Insurance Corporation (which has data on the entire nation). The analysis included26,284,706 person-months of 1,042,728 individuals. An interrupted-time series analysis was performed. Outcome measures were monthly outpatient visits for acute upper respiratory infections, dyspepsia, and migraine. To investigate the effect of the policy, we compared the number of monthly visits before and after the policy's implementation in 2012. For acute upper respiratory infections, monthly outpatient visits showed a decreasing trend before the policy (ß = -0.0003);after it, a prompt change and increasing trend in monthly outpatient visits were observed, but these were non-significant. For dyspepsia, the trend was increasing before implementation (ß = -0.0101), but this reversed after implementation(ß = -0.007). For migraine, an increasing trend was observed before the policy (ß = 0.0057). After it, we observed a significant prompt change (ß = -0.0314) but no significant trend. Deregulation of selling over-the-counter medication outside of pharmacies reduced monthly outpatient visits for dyspepsia and migraine symptoms, but not acute upper respiratory infections.

Longitudinal data analysis in support of functional stability concepts for leachate management at closed municipal landfills

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

Gibbons, Robert D., E-mail: rdg@uchicago.edu; Morris, Jeremy W.F., E-mail: jmorris@geosyntec.com; Prucha, Christopher P., E-mail: cprucha@wm.com

2014-09-15

Highlights: • Longitudinal data analysis using a mixed-effects regression model. • Dataset consisted of a total of 1402 samples from 101 closed municipal landfills. • Target analytes and classes generally showed predictable degradation trends. • Validates historical studies focused on macro organic indicators such as BOD. • BOD can serve as “gateway” indicator for planning leachate management. - Abstract: Landfill functional stability provides a target that supports no environmental threat at the relevant point of exposure in the absence of active control systems. With respect to leachate management, this study investigates “gateway” indicators for functional stability in terms of themore » predictability of leachate characteristics, and thus potential threat to water quality posed by leachate emissions. Historical studies conducted on changes in municipal solid waste (MSW) leachate concentrations over time (longitudinal analysis) have concentrated on indicator compounds, primarily chemical oxygen demand (COD) and biochemical oxygen demand (BOD). However, validation of these studies using an expanded database and larger constituent sets has not been performed. This study evaluated leachate data using a mixed-effects regression model to determine the extent to which leachate constituent degradation can be predicted based on waste age or operational practices. The final dataset analyzed consisted of a total of 1402 samples from 101 MSW landfills. Results from the study indicated that all leachate constituents exhibit a decreasing trend with time in the post-closure period, with 16 of the 25 target analytes and aggregate classes exhibiting a statistically significant trend consistent with well-studied indicators such as BOD. Decreasing trends in BOD concentration after landfill closure can thus be considered representative of trends for many leachate constituents of concern.« less

The increase in symptoms of anxiety and depressed mood among Icelandic adolescents: time trend between 2006 and 2016.

PubMed

Thorisdottir, Ingibjorg E; Asgeirsdottir, Bryndis B; Sigurvinsdottir, Rannveig; Allegrante, John P; Sigfusdottir, Inga D

2017-10-01

Both research and popular media reports suggest that adolescent mental health has been deteriorating across societies with advanced economies. This study sought to describe the trends in self-reported symptoms of depressed mood and anxiety among Icelandic adolescents. Data for this study come from repeated, cross-sectional, population-based school surveys of 43 482 Icelandic adolescents in 9th and 10th grade, with six waves of pooled data from 2006 to 2016. We used analysis of variance, linear regression and binomial logistic regression to examine trends in symptom scores of anxiety and depressed mood over time. Gender differences in trends of high symptoms were also tested for interactions. Linear regression analysis showed a significant linear increase over the course of the study period in mean symptoms of anxiety and depressed mood for girls only; however, symptoms of anxiety among boys decreased. The proportion of adolescents reporting high depressive symptoms increased by 1.6% for boys and 6.8% for girls; the proportion of those reporting high anxiety symptoms increased by 1.3% for boys and 8.6% for girls. Over the study period, the odds for reporting high depressive symptoms and high anxiety symptoms were significantly higher for both genders. Girls were more likely to report high symptoms of anxiety and depressed mood than boys. Self-reported symptoms of anxiety and depressed mood have increased over time among Icelandic adolescents. Our findings suggest that future research needs to look beyond mean changes and examine the trends among those adolescents who report high symptoms of emotional distress. © The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Extreme events in total ozone over Arosa - Part 2: Fingerprints of atmospheric dynamics and chemistry and effects on mean values and long-term changes

NASA Astrophysics Data System (ADS)

Rieder, H. E.; Staehelin, J.; Maeder, J. A.; Peter, T.; Ribatet, M.; Davison, A. C.; Stübi, R.; Weihs, P.; Holawe, F.

2010-10-01

In this study the frequency of days with extreme low (termed ELOs) and extreme high (termed EHOs) total ozone values and their influence on mean values and trends are analyzed for the world's longest total ozone record (Arosa, Switzerland). The results show (i) an increase in ELOs and (ii) a decrease in EHOs during the last decades and (iii) that the overall trend during the 1970s and 1980s in total ozone is strongly dominated by changes in these extreme events. After removing the extremes, the time series shows a strongly reduced trend (reduction by a factor of 2.5 for trend in annual mean). Excursions in the frequency of extreme events reveal "fingerprints" of dynamical factors such as ENSO or NAO, and chemical factors, such as cold Arctic vortex ozone losses, as well as major volcanic eruptions of the 20th century (Gunung Agung, El Chichón, Mt. Pinatubo). Furthermore, atmospheric loading of ozone depleting substances leads to a continuous modification of column ozone in the Northern Hemisphere also with respect to extreme values (partly again in connection with polar vortex contributions). Application of extreme value theory allows the identification of many more such "fingerprints" than conventional time series analysis of annual and seasonal mean values. The analysis shows in particular the strong influence of dynamics, revealing that even moderate ENSO and NAO events have a discernible effect on total ozone. Overall the approach to extremal modelling provides new information on time series properties, variability, trends and the influence of dynamics and chemistry, complementing earlier analyses focusing only on monthly (or annual) mean values.

Extreme events in total ozone over Arosa - Part 2: Fingerprints of atmospheric dynamics and chemistry and effects on mean values and long-term changes

NASA Astrophysics Data System (ADS)

Rieder, H. E.; Staehelin, J.; Maeder, J. A.; Peter, T.; Ribatet, M.; Davison, A. C.; Stübi, R.; Weihs, P.; Holawe, F.

2010-05-01

In this study the frequency of days with extreme low (termed ELOs) and extreme high (termed EHOs) total ozone values and their influence on mean values and trends are analyzed for the world's longest total ozone record (Arosa, Switzerland). The results show (a) an increase in ELOs and (b) a decrease in EHOs during the last decades and (c) that the overall trend during the 1970s and 1980s in total ozone is strongly dominated by changes in these extreme events. After removing the extremes, the time series shows a strongly reduced trend (reduction by a factor of 2.5 for trend in annual mean). Excursions in the frequency of extreme events reveal "fingerprints" of dynamical factors such as ENSO or NAO, and chemical factors, such as cold Arctic vortex ozone losses, as well as major volcanic eruptions of the 20th century (Gunung Agung, El Chichón, Mt. Pinatubo). Furthermore, atmospheric loading of ozone depleting substances leads to a continuous modification of column ozone in the Northern Hemisphere also with respect to extreme values (partly again in connection with polar vortex contributions). Application of extreme value theory allows the identification of many more such "fingerprints" than conventional time series analysis of annual and seasonal mean values. The analysis shows in particular the strong influence of dynamics, revealing that even moderate ENSO and NAO events have a discernible effect on total ozone. Overall the approach to extremal modelling provides new information on time series properties, variability, trends and the influence of dynamics and chemistry, complementing earlier analyses focusing only on monthly (or annual) mean values.

A multiyear, global gridded fossil fuel CO2 emission data product: Evaluation and analysis of results

NASA Astrophysics Data System (ADS)

Asefi-Najafabady, S.; Rayner, P. J.; Gurney, K. R.; McRobert, A.; Song, Y.; Coltin, K.; Huang, J.; Elvidge, C.; Baugh, K.

2014-09-01

High-resolution, global quantification of fossil fuel CO2 emissions is emerging as a critical need in carbon cycle science and climate policy. We build upon a previously developed fossil fuel data assimilation system (FFDAS) for estimating global high-resolution fossil fuel CO2 emissions. We have improved the underlying observationally based data sources, expanded the approach through treatment of separate emitting sectors including a new pointwise database of global power plants, and extended the results to cover a 1997 to 2010 time series at a spatial resolution of 0.1°. Long-term trend analysis of the resulting global emissions shows subnational spatial structure in large active economies such as the United States, China, and India. These three countries, in particular, show different long-term trends and exploration of the trends in nighttime lights, and population reveal a decoupling of population and emissions at the subnational level. Analysis of shorter-term variations reveals the impact of the 2008-2009 global financial crisis with widespread negative emission anomalies across the U.S. and Europe. We have used a center of mass (CM) calculation as a compact metric to express the time evolution of spatial patterns in fossil fuel CO2 emissions. The global emission CM has moved toward the east and somewhat south between 1997 and 2010, driven by the increase in emissions in China and South Asia over this time period. Analysis at the level of individual countries reveals per capita CO2 emission migration in both Russia and India. The per capita emission CM holds potential as a way to succinctly analyze subnational shifts in carbon intensity over time. Uncertainties are generally lower than the previous version of FFDAS due mainly to an improved nightlight data set.

Explaining Changes in the Patterns of Black Suicide in the United States from 1981 to 2002: An Age, Cohort, and Period Analysis

ERIC Educational Resources Information Center

Joe, Sean

2006-01-01

To explore the different trends of suicide incidence among Blacks and possible contributing factors, the current study compared national epidemiologic data of suicide in the United States from 1981 to 2002. For the first time, period and birth-cohort effects on the incidence trends of Black suicide were evaluated using an age-period-cohort…

Changes toward earlier streamflow timing across western North America

USGS Publications Warehouse

Stewart, I.T.; Cayan, D.R.; Dettinger, M.D.

2005-01-01

The highly variable timing of streamflow in snowmelt-dominated basins across western North America is an important consequence, and indicator, of climate fluctuations. Changes in the timing of snowmelt-derived streamflow from 1948 to 2002 were investigated in a network of 302 western North America gauges by examining the center of mass for flow, spring pulse onset dates, and seasonal fractional flows through trend and principal component analyses. Statistical analysis of the streamflow timing measures with Pacific climate indicators identified local and key large-scale processes that govern the regionally coherent parts of the changes and their relative importance. Widespread and regionally coherent trends toward earlier onsets of springtime snowmelt and streamflow have taken place across most of western North America, affecting an area that is much larger than previously recognized. These timing changes have resulted in increasing fractions of annual flow occurring earlier in the water year by 1-4 weeks. The immediate (or proximal) forcings for the spatially coherent parts of the year-to-year fluctuations and longer-term trends of streamflow timing have been higher winter and spring temperatures. Although these temperature changes are partly controlled by the decadal-scale Pacific climate mode [Pacific decadal oscillation (PDO)], a separate and significant part of the variance is associated with a springtime warming trend that spans the PDO phases. ?? 2005 American Meteorological Society.

Long-term forecasting of internet backbone traffic.

PubMed

Papagiannaki, Konstantina; Taft, Nina; Zhang, Zhi-Li; Diot, Christophe

2005-09-01

We introduce a methodology to predict when and where link additions/upgrades have to take place in an Internet protocol (IP) backbone network. Using simple network management protocol (SNMP) statistics, collected continuously since 1999, we compute aggregate demand between any two adjacent points of presence (PoPs) and look at its evolution at time scales larger than 1 h. We show that IP backbone traffic exhibits visible long term trends, strong periodicities, and variability at multiple time scales. Our methodology relies on the wavelet multiresolution analysis (MRA) and linear time series models. Using wavelet MRA, we smooth the collected measurements until we identify the overall long-term trend. The fluctuations around the obtained trend are further analyzed at multiple time scales. We show that the largest amount of variability in the original signal is due to its fluctuations at the 12-h time scale. We model inter-PoP aggregate demand as a multiple linear regression model, consisting of the two identified components. We show that this model accounts for 98% of the total energy in the original signal, while explaining 90% of its variance. Weekly approximations of those components can be accurately modeled with low-order autoregressive integrated moving average (ARIMA) models. We show that forecasting the long term trend and the fluctuations of the traffic at the 12-h time scale yields accurate estimates for at least 6 months in the future.

Hydro-meteorological trends in the Gidabo catchment of the Rift Valley Lakes Basin of Ethiopia

NASA Astrophysics Data System (ADS)

Belihu, Mamuye; Abate, Brook; Tekleab, Sirak; Bewket, Woldeamlak

2018-04-01

The global and regional variability and changes of climate and stream flows are likely to have significant influence on water resource availability. The magnitude and impacts of climate variability and change differs spatially and temporally. This study examines the long term hydroclimatic changes, analyses of the hydro-climate variability and detect whether there exist significant trend or not in the Gidabo catchment, rift valley lakes basin of Ethiopia. Precipitation, temperature and stream flow time series data were used in monthly, seasonal and annual time scales. The precipitation and temperature data span is between 1982 and 2014 and that of stream flow is between 1976 and 2006. To detect trends the analysis were done by using Mann Kendal (MK), Sen's graphical method and to detect change point using the Pettit test. The comparison of trend analysis between MK trend test and Sen graphical method results depict mostly similar pattern. The annual rainfall trends exhibited a significant decrease by about 12 mm per year in the upstream, which is largely driven by the significant decrease in the peak season rainfall. The Pettit test revealed that the years 1997 and 2007 were the change points. It is noted that the rise of temperature over a catchment might have decreased the availability of soil moisture which resulted in less runoff. The temperature analyses also revealed that the catchment was getting warmer; particularly in the upstream. The minimum temperature trend showed a significant increase about 0.08°c per annum. There is generally a decreasing trend in stream flow. The monthly stream flow also exhibited a decreasing trend in February, March and September. The decline in annual and seasonal rainfall and the increase in temperature lead to more evaporation and directly affecting the stream flow negatively. This trend compounded with the growth of population and increasing demand for irrigation water exacerbates the competing demand for water resources. It thus calls for prudence in devising appropriate intervention in the planning and sustainable development of the basin water resources.

Time series analysis and mortality model of dog bite victims presented for treatment at a referral clinic for rabies exposure in Monrovia, Liberia, 2010-2013.

PubMed

Olarinmoye, Ayodeji O; Ojo, Johnson F; Fasunla, Ayotunde J; Ishola, Olayinka O; Dakinah, Fahnboah G; Mulbah, Charles K; Al-Hezaimi, Khalid; Olugasa, Babasola O

2017-08-01

We developed time trend model, determined treatment outcome and estimated annual human deaths among dog bite victims (DBVs) from 2010 to 2013 in Monrovia, Liberia. Data obtained from clinic records included victim's age, gender and site of bite marks, site name of residence of rabies-exposed patients, promptness of care sought, initial treatment and post-exposure-prophylaxis (PEP) compliance. We computed DBV time-trend plot, seasonal index and year 2014 case forecast. Associated annual human death (AHD) was estimated using a standardized decision tree model. Of the 775 DBVs enlisted, care seeking time was within 24h of injury in 328 (42.32%) DBVs. Victim's residential location, site of bite mark, and time dependent variables were significantly associated with treatment outcome (p< 0.05). The equation X^ t =28.278-0.365t models the trend of DBVs. The high (n=705, 90.97%) defaulted PEP and average 155 AHD from rabies implied urgent need for policy formulation on national programme for rabies prevention in Liberia. Copyright © 2017 Elsevier Ltd. All rights reserved.

Agricultural sectoral demand and crop productivity response across the world

NASA Astrophysics Data System (ADS)

Johnston, M.; Ray, D. K.; Cassidy, E. S.; Foley, J. A.

2013-12-01

With an increasing and increasingly affluent population, humans will need to roughly double agricultural production by 2050. Continued yield growth forms the foundation of all future strategies aiming to increase agricultural production while slowing or eliminating cropland expansion. However, a recent analysis by one of our co-authors has shown that yield trends in many important maize, wheat and rice growing regions have begun stagnating or declining from the highs seen during the green revolution (Ray et al. 2013). Additional research by our group has shown that nearly 50% of new agricultural production since the 1960s has gone not to direct human consumption, but instead to animal feed and other industrial uses. Our analysis for GLP looks at the convergence of these two trends by examining time series utilization data for 16 of the biggest crops to determine how demand from different sectors has shaped our land-use and intensification strategies around the world. Before rushing headlong into the next agricultural doubling, it would be prudent to first consult our recent agricultural history to better understand what was driving past changes in production. Using newly developed time series dataset - a fusion of cropland maps with historic agricultural census data gathered from around the world - we can examine yield and harvested area trends over the last half century for 16 top crops. We combine this data with utilization rates from the FAO Food Balance Sheet to see how demand from different sectors - food, feed, and other - has influenced long-term growth trends from the green revolution forward. We will show how intensification trends over time and across regions have grown or contracted depending on what is driving the change in production capacity. Ray DK, Mueller ND, West PC, Foley JA (2013) Yield Trends Are Insufficient to Double Global Crop Production by 2050. PLoS ONE 8(6): e66428. doi:10.1371/journal.pone.0066428

An institutional six-year trend analysis of the neurological outcome after lateral lumbar interbody fusion: a 6-year trend analysis of a single institution.

PubMed

Aichmair, Alexander; Lykissas, Marios G; Girardi, Federico P; Sama, Andrew A; Lebl, Darren R; Taher, Fadi; Cammisa, Frank P; Hughes, Alexander P

2013-11-01

Retrospective case series. To evaluate the proportional trend over time of neurological deficits after lateral lumbar interbody fusion (LLIF) at a single institution. Because lumbar nerve roots converge to run as the lumbar plexus within or less frequently underneath the posterior part of the psoas muscle, they are prone to iatrogenic damage during the transpsoas approach in LLIF, and adverse postoperative neurological sequelae remain a major concern. The electronic medical records and office notes of 451 patients who had consecutively undergone LLIF between March 2006 and April 2012 at a single institution were retrospectively reviewed for reports on postoperative neurological deficits. A total of 293 patients (173 females and 120 males) met the study inclusion criteria and were followed postoperatively for a mean period of 15.4 ± 9.2 months (range: 6-53 mo). The number of included patients who underwent LLIF at our institution was 47 in the years 2006 to 2008 (group A), 155 in 2009 to 2010 (group B), and 91 in 2011 to 2012 (group C). Our data indicate a decreasing proportional trend during the past 6 years for postoperative sensory deficits (SDs), motor deficits (MDs), and anterior thigh pain (TP). The decreasing trends were statistically significant for the proportion of SDs in the immediate postoperative setting (P = 0.018) and close to statistically significant for SDs at last follow-up (P = 0.126), TP immediately after surgery (P = 0.098), and TP at last follow-up (P = 0.136). To the authors' best knowledge, this study constitutes the largest series of this sort to date, with regard to both sample size and study period. The present data indicate a decreasing proportional trend over time for SDs, MDs, and anterior TP, which can be considered a representation of an institutional learning curve during a 6-year time period of performing LLIF.

Long-term trend analysis on total and extreme precipitation over Shasta Dam watershed.

PubMed

Toride, Kinya; Cawthorne, Dylan L; Ishida, Kei; Kavvas, M Levent; Anderson, Michael L

2018-06-01

California's interconnected water system is one of the most advanced water management systems in the world, and understanding of long-term trends in atmospheric and hydrologic behavior has increasingly being seen as vital to its future well-being. Knowledge of such trends is hampered by the lack of long-period observation data and the uncertainty surrounding future projections of atmospheric models. This study examines historical precipitation trends over the Shasta Dam watershed (SDW), which lies upstream of one of the most important components of California's water system, Shasta Dam, using a dynamical downscaling methodology that can produce atmospheric data at fine time-space scales. The Weather Research and Forecasting (WRF) model is employed to reconstruct 159years of long-term hourly precipitation data at 3km spatial resolution over SDW using the 20th Century Reanalysis Version 2c dataset. Trend analysis on this data indicates a significant increase in total precipitation as well as a growing intensity of extreme events such as 1, 6, 12, 24, 48, and 72-hour storms over the period of 1851 to 2010. The turning point of the increasing trend and no significant trend periods is found to be 1940 for annual precipitation and the period of 1950 to 1960 for extreme precipitation using the sequential Mann-Kendall test. Based on these analysis, we find the trends at the regional scale do not necessarily apply to the watershed-scale. The sharp increase in the variability of annual precipitation since 1970s is also detected, which implies an increase in the occurrence of extreme wet and dry conditions. These results inform long-term planning decisions regarding the future of Shasta Dam and California's water system. Copyright © 2018 Elsevier B.V. All rights reserved.

Twenty-five year socioeconomic trends in leisure-time and commuting physical activity among employed Finns.

PubMed

Mäkinen, T; Borodulin, K; Laatikainen, T; Fogelholm, M; Prättälä, R

2009-04-01

The trend of socioeconomic differences in physical activity is largely unknown in Finland. In this study, we examined socioeconomic trends in leisure-time and commuting physical activity among Finns in 1978-2002. Nationwide data were derived from an annually repeated cross-sectional Finnish Adult Health Behavior Survey. People under the age of 25, students, the unemployed, and retirees were excluded from the analysis. The final data set included 25 513 women and 25 302 men. Socioeconomic variables included education, occupation, and household income. Odds ratios for being physically active and 95% confidence intervals were calculated. People with the lowest income were less leisure-time and commuting physically active. Among women, low occupational status was associated with high commuting physical activity whereas among men such an association was not found. No educational differences among men in leisure-time and commuting physical activity over time were found. Some indications were found that educational differences in leisure-time physical activity among women might have been reversed. Our data suggest that socioeconomic differences in leisure-time and commuting physical activity are quite small and have remained similar between 1978 and 2002.

Cost-effectiveness research in cancer therapy: a systematic review of literature trends, methods and the influence of funding

PubMed Central

Al-Badriyeh, Daoud; Alameri, Marwah; Al-Okka, Randa

2017-01-01

Objective To perform a first-time analysis of the cost-effectiveness (CE) literature on chemotherapies, of all types, in cancer, in terms of trends and change over time, including the influence of industry funding. Design Systematic review. Setting A wide range of cancer-related research settings within healthcare, including health systems, hospitals and medical centres. Participants All literature comparative CE research of drug-based cancer therapies in the period 1986 to 2015. Primary and secondary outcome measures Primary outcomes are the literature trends in relation to journal subject category, authorship, research design, data sources, funds and consultation involvement. An additional outcome measure is the association between industry funding and study outcomes. Analysis Descriptive statistics and the χ2, Fisher exact or Somer's D tests were used to perform non-parametric statistics, with a p value of <0.05 as the statistical significance measure. Results Total 574 publications were analysed. The drug-related CE literature expands over time, with increased publishing in the healthcare sciences and services journal subject category (p<0.001). The retrospective data collection in studies increased over time (p<0.001). The usage of prospective data, however, has been decreasing (p<0.001) in relation to randomised clinical trials (RCTs), but is unchanging for non-RCT studies. The industry-sponsored CE studies have especially been increasing (p<0.001), in contrast to those sponsored by other sources. While paid consultation involvement grew throughout the years, the declaration of funding for this is relatively limited. Importantly, there is evidence that industry funding is associated with favourable result to the sponsor (p<0.001). Conclusions This analysis demonstrates clear trends in how the CE cancer research is presented to the practicing community, including in relation to journals, study designs, authorship and consultation, together with increased financial sponsorship by pharmaceutical industries, which may be more influencing study outcomes than other funding sources. PMID:28131999

CrazyEgg Reports for Single Page Analysis

EPA Pesticide Factsheets

CrazyEgg provides an in depth look at visitor behavior on one page. While you can use GA to do trend analysis of your web area, CrazyEgg helps diagnose the design of a single Web page by visually displaying all visitor clicks during a specified time.

Did the English strategy reduce inequalities in health? A difference-in-difference analysis comparing England with three other European countries.

PubMed

Hu, Yannan; van Lenthe, Frank J; Judge, Ken; Lahelma, Eero; Costa, Giuseppe; de Gelder, Rianne; Mackenbach, Johan P

2016-08-24

Between 1997 and 2010, the English government pursued an ambitious programme to reduce health inequalities, the explicit and sustained commitment of which was historically and internationally unique. Previous evaluations have produced mixed results. None of these evaluations have, however, compared the trends in health inequalities within England with those in other European countries. We carried out an innovative analysis to assess whether changes in trends in health inequalities observed in England after the implementation of its programme, have been more favourable than those in other countries without such a programme. Data were obtained from nationally representative surveys carried out in England, Finland, the Netherlands and Italy for years around 1990, 2000 and 2010. A modified difference-in-difference approach was used to assess whether trends in health inequalities in 2000-2010 were more favourable as compared to the period 1990-2000 in England, and the changes in trends in inequalities after 2000 in England were then compared to those in the three comparison countries. Health outcomes were self-assessed health, long-standing health problems, smoking status and obesity. Education was used as indicator of socioeconomic position. After the implementation of the English strategy, more favourable trends in some health indicators were observed among low-educated people, but trends in health inequalities in 2000-2010 in England were not more favourable than those observed in the period 1990-2000. For most health indicators, changes in trends of health inequalities after 2000 in England were also not significantly different from those seen in the other countries. In this rigorous analysis comparing trends in health inequalities in England both over time and between countries, we could not detect a favourable effect of the English strategy. Our analysis illustrates the usefulness of a modified difference-in-difference approach for assessing the impact of policies on population-level health inequalities.

Trends analysis of PM source contributions and chemical tracers in NE Spain during 2004-2014: a multi-exponential approach

NASA Astrophysics Data System (ADS)

Pandolfi, Marco; Alastuey, Andrés; Pérez, Noemi; Reche, Cristina; Castro, Iria; Shatalov, Victor; Querol, Xavier

2016-09-01

In this work for the first time data from two twin stations (Barcelona, urban background, and Montseny, regional background), located in the northeast (NE) of Spain, were used to study the trends of the concentrations of different chemical species in PM10 and PM2.5 along with the trends of the PM10 source contributions from the positive matrix factorization (PMF) model. Eleven years of chemical data (2004-2014) were used for this study. Trends of both species concentrations and source contributions were studied using the Mann-Kendall test for linear trends and a new approach based on multi-exponential fit of the data. Despite the fact that different PM fractions (PM2.5, PM10) showed linear decreasing trends at both stations, the contributions of specific sources of pollutants and of their chemical tracers showed exponential decreasing trends. The different types of trends observed reflected the different effectiveness and/or time of implementation of the measures taken to reduce the concentrations of atmospheric pollutants. Moreover, the trends of the contributions of specific sources such as those related with industrial activities and with primary energy consumption mirrored the effect of the financial crisis in Spain from 2008. The sources that showed statistically significant downward trends at both Barcelona (BCN) and Montseny (MSY) during 2004-2014 were secondary sulfate, secondary nitrate, and V-Ni-bearing source. The contributions from these sources decreased exponentially during the considered period, indicating that the observed reductions were not gradual and consistent over time. Conversely, the trends were less steep at the end of the period compared to the beginning, thus likely indicating the attainment of a lower limit. Moreover, statistically significant decreasing trends were observed for the contributions to PM from the industrial/traffic source at MSY (mixed metallurgy and road traffic) and from the industrial (metallurgy mainly) source at BCN. These sources were clearly linked with anthropogenic activities, and the observed decreasing trends confirmed the effectiveness of pollution control measures implemented at European or regional/local levels. Conversely, at regional level, the contributions from sources mostly linked with natural processes, such as aged marine and aged organics, did not show statistically significant trends. The trends observed for the PM10 source contributions reflected the trends observed for the chemical tracers of these pollutant sources well.

Human Migration and Agricultural Expansion: An Impending Threat to the Maya Biosphere Reserve

NASA Technical Reports Server (NTRS)

Sader, Steven; Reining, Conard; Sever, Thomas L.; Soza, Carlos

1997-01-01

Evidence is presented of the current threats to the Maya Biosphere Reserve in northern Guatemala as derived through time-series Landsat Thematic Mapper observations and analysis. Estimates of deforestation rates and trends are examined for different management units within the reserve and buffer zones. The satellite imagery was used to quantify and monitor rates, patterns, and trends of forest clearing during a time period corresponding to new road construction and significant human migration into the newly accessible forest region. Satellite imagery is appropriate technology in a vast and remote tropical region where aerial photography and extensive field-based methods are not cost-effective and current, timely data is essential for establishing conservation priorities.

Direct oral anticoagulants: analysis of worldwide use and popularity using Google Trends.

PubMed

Lippi, Giuseppe; Mattiuzzi, Camilla; Cervellin, Gianfranco; Favaloro, Emmanuel J

2017-08-01

Four direct oral anticoagulants (DOACs) have been approved for clinical use by many medicines regulatory agencies around the world. Due to increasing use of these drugs in routine practice, we planned an original study to investigate their worldwide diffusion using a popular Web-search engine. Two electronic searches were performed using Google Trends, the former using the keywords "warfarin" AND "heparin" AND "fondaparinux", and the latter using the keywords "warfarin" AND "dabigatran" AND "rivaroxaban" AND "apixaban" AND "edoxaban", both using the search criterion "prescription drug". No language restriction was applied, and the searches were carried out from the first date available in Google Trends (January 1 st , 2004) to present time (June 1 st , 2017). The median Google Trends score of warfarin (i.e., 86) was consistently higher than that of heparin (54; P<0.001), fondaparinux (6; P<0.001), dabigatran (11; P<0.001), rivaroxaban (5; P<0.001), apixaban (1; P<0.001) and edoxaban (1; P<0.001). Specific analysis of the trends shows that the score of warfarin exhibits a highly significant decrease over time (r=-0.40; P<0.001), whilst that of heparin has remained virtually unchanged (r=0.12; P=0.127), and that of fondaparinux has marginally increased (r=0.16; P=0.038). As regards DOACs, the scores of these drugs significantly increased during the search period (dabigatran, r=0.79; rivaroxaban, r=0.99; apixaban, r=0.98; edoxaban, r=0.78; all P<0.001). When the analysis was limited to the past five years, the dabigatran score significantly decreased (r=-0.57; P<0.001), whereas that of the other DOACs exhibited an even sharper increase. Most Google searches for DOACs were performed in North America, central-eastern Europe and Australia. The results of our analysis suggest that the popularity of DOACs is constantly increasing around the world, whereas that of warfarin has exhibited a constant and inexorable decline.

Secular trends in Cherokee cranial morphology: Eastern vs Western bands.

PubMed

Sutphin, Rebecca; Ross, Ann H; Jantz, Richard L

2014-01-01

The research objective was to examine if secular trends can be identified for cranial data commissioned by Boas in 1892, specifically for cranial breadth and cranial length of the Eastern and Western band Cherokee who experienced environmental hardships. Multiple regression analysis was used to test the degree of relationship between each of the cranial measures: cranial length, cranial breadth and cephalic index, along with predictor variables (year-of-birth, location, sex, admixture); the model revealed a significant difference for all craniometric variables. Additional regression analysis was performed with smoothing Loess plots to observe cranial length and cranial breadth change over time (year-of-birth) separately for Eastern and Western Cherokee band females and males born between 1783-1874. This revealed the Western and Eastern bands show a decrease in cranial length over time. Eastern band individuals maintain a relatively constant head breadth, while Western Band individuals show a sharp decline beginning around 1860. These findings support negative secular trend occurring for both Cherokee bands where the environment made a detrimental impact; this is especially marked with the Western Cherokee band.

Secular trend, seasonality and effects of a community-based intervention on neonatal mortality: follow-up of a cluster-randomised trial in Quang Ninh province, Vietnam.

PubMed

Eriksson, Leif; Nga, Nguyen T; Hoa, Dinh T Phuong; Duc, Duong M; Bergström, Anna; Wallin, Lars; Målqvist, Mats; Ewald, Uwe; Huy, Tran Q; Thuy, Nguyen T; Do, Tran Thanh; Lien, Pham T L; Persson, Lars-Åke; Selling, Katarina Ekholm

2018-05-15

Little is know about whether the effects of community engagement interventions for child survival in low-income and middle-income settings are sustained. Seasonal variation and secular trend may blur the data. Neonatal mortality was reduced in a cluster-randomised trial in Vietnam where laywomen facilitated groups composed of local stakeholders employing a problem-solving approach for 3 years. In this analysis, we aim at disentangling the secular trend, the seasonal variation and the effect of the intervention on neonatal mortality during and after the trial. In Quang Ninh province, 44 communes were allocated to intervention and 46 to control. Births and neonatal deaths were assessed in a baseline survey in 2005, monitored during the trial in 2008-2011 and followed up by a survey in 2014. Time series analyses were performed on monthly neonatal mortality data. There were 30 187 live births and 480 neonatal deaths. The intervention reduced the neonatal mortality from 19.1 to 11.6 per 1000 live births. The reduction was sustained 3 years after the trial. The control areas reached a similar level at the time of follow-up. Time series decomposition analysis revealed a downward trend in the intervention areas during the trial that was not found in the control areas. Neonatal mortality peaked in the hot and wet summers. A community engagement intervention resulted in a lower neonatal mortality rate that was sustained but not further reduced after the end of the trial. When decomposing time series of neonatal mortality, a clear downward trend was demonstrated in intervention but not in control areas. ISRCTN44599712, Post-results. © 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.

Forecast models for suicide: Time-series analysis with data from Italy.

PubMed

Preti, Antonio; Lentini, Gianluca

2016-01-01

The prediction of suicidal behavior is a complex task. To fine-tune targeted preventative interventions, predictive analytics (i.e. forecasting future risk of suicide) is more important than exploratory data analysis (pattern recognition, e.g. detection of seasonality in suicide time series). This study sets out to investigate the accuracy of forecasting models of suicide for men and women. A total of 101 499 male suicides and of 39 681 female suicides - occurred in Italy from 1969 to 2003 - were investigated. In order to apply the forecasting model and test its accuracy, the time series were split into a training set (1969 to 1996; 336 months) and a test set (1997 to 2003; 84 months). The main outcome was the accuracy of forecasting models on the monthly number of suicides. These measures of accuracy were used: mean absolute error; root mean squared error; mean absolute percentage error; mean absolute scaled error. In both male and female suicides a change in the trend pattern was observed, with an increase from 1969 onwards to reach a maximum around 1990 and decrease thereafter. The variances attributable to the seasonal and trend components were, respectively, 24% and 64% in male suicides, and 28% and 41% in female ones. Both annual and seasonal historical trends of monthly data contributed to forecast future trends of suicide with a margin of error around 10%. The finding is clearer in male than in female time series of suicide. The main conclusion of the study is that models taking seasonality into account seem to be able to derive information on deviation from the mean when this occurs as a zenith, but they fail to reproduce it when it occurs as a nadir. Preventative efforts should concentrate on the factors that influence the occurrence of increases above the main trend in both seasonal and cyclic patterns of suicides.

Revisiting Southern Hemisphere polar stratospheric temperature trends in WACCM: The role of dynamical forcing

NASA Astrophysics Data System (ADS)

Calvo, N.; Garcia, R. R.; Kinnison, D. E.

2017-04-01

The latest version of the Whole Atmosphere Community Climate Model (WACCM), which includes a new chemistry scheme and an updated parameterization of orographic gravity waves, produces temperature trends in the Antarctic lower stratosphere in excellent agreement with radiosonde observations for 1969-1998 as regards magnitude, location, timing, and persistence. The maximum trend, reached in November at 100 hPa, is -4.4 ± 2.8 K decade-1, which is a third smaller than the largest trend in the previous version of WACCM. Comparison with a simulation without the updated orographic gravity wave parameterization, together with analysis of the model's thermodynamic budget, reveals that the reduced trend is due to the effects of a stronger Brewer-Dobson circulation in the new simulations, which warms the polar cap. The effects are both direct (a trend in adiabatic warming in late spring) and indirect (a smaller trend in ozone, hence a smaller reduction in shortwave heating, due to the warmer environment).

Trends in extremes of temperature, dew point, and precipitation from long instrumental series from central Europe

NASA Astrophysics Data System (ADS)

Kürbis, K.; Mudelsee, M.; Tetzlaff, G.; Brázdil, R.

2009-09-01

For the analysis of trends in weather extremes, we introduce a diagnostic index variable, the exceedance product, which combines intensity and frequency of extremes. We separate trends in higher moments from trends in mean or standard deviation and use bootstrap resampling to evaluate statistical significances. The application of the concept of the exceedance product to daily meteorological time series from Potsdam (1893 to 2005) and Prague-Klementinum (1775 to 2004) reveals that extremely cold winters occurred only until the mid-20th century, whereas warm winters show upward trends. These changes were significant in higher moments of the temperature distribution. In contrast, trends in summer temperature extremes (e.g., the 2003 European heatwave) can be explained by linear changes in mean or standard deviation. While precipitation at Potsdam does not show pronounced trends, dew point does exhibit a change from maximum extremes during the 1960s to minimum extremes during the 1970s.

Detecting temporal change in freshwater fisheries surveys: statistical power and the important linkages between management questions and monitoring objectives

USGS Publications Warehouse

Wagner, Tyler; Irwin, Brian J.; James R. Bence,; Daniel B. Hayes,

2016-01-01

Monitoring to detect temporal trends in biological and habitat indices is a critical component of fisheries management. Thus, it is important that management objectives are linked to monitoring objectives. This linkage requires a definition of what constitutes a management-relevant “temporal trend.” It is also important to develop expectations for the amount of time required to detect a trend (i.e., statistical power) and for choosing an appropriate statistical model for analysis. We provide an overview of temporal trends commonly encountered in fisheries management, review published studies that evaluated statistical power of long-term trend detection, and illustrate dynamic linear models in a Bayesian context, as an additional analytical approach focused on shorter term change. We show that monitoring programs generally have low statistical power for detecting linear temporal trends and argue that often management should be focused on different definitions of trends, some of which can be better addressed by alternative analytical approaches.

Recent changes in the trends of teen birth rates, 1981-2006.

PubMed

Wingo, Phyllis A; Smith, Ruben A; Tevendale, Heather D; Ferré, Cynthia

2011-03-01

To explore trends in teen birth rates by selected demographics. We used birth certificate data and joinpoint regression to examine trends in teen birth rates by age (10-14, 15-17, and 18-19 years) and race during 1981-2006 and by age and Hispanic origin during 1990-2006. Joinpoint analysis describes changing trends over successive segments of time and uses annual percentage change (APC) to express the amount of increase or decrease within each segment. For teens younger than 18 years, the decline in birth rates began in 1994 and ended in 2003 (APC: -8.03% per year for ages 10-14 years; APC: -5.63% per year for ages 15-17 years). The downward trend for 18- and 19-year-old teens began earlier (1991) and ended 1 year later (2004) (APC: -2.37% per year). For each study population, the trend was approximately level during the most recent time segment, except for continuing declines for 18- and 19-year-old white and Asian/Pacific Islander teens. The only increasing trend in the most recent time segment was for 18- and 19-year-old Hispanic teens. During these declines, the age distribution of teens who gave birth shifted to slightly older ages, and the percentage whose current birth was at least their second birth decreased. Teen birth rates were generally level during 2003/2004-2006 after the long-term declines. Rates increased among older Hispanic teens. These results indicate a need for renewed attention to effective teen pregnancy prevention programs in specific populations. Copyright © 2011. Published by Elsevier Inc.

Classifying geometric variability by dominant eigenmodes of deformation in regressing tumours during active breath-hold lung cancer radiotherapy

NASA Astrophysics Data System (ADS)

Badawi, Ahmed M.; Weiss, Elisabeth; Sleeman, William C., IV; Hugo, Geoffrey D.

2012-01-01

The purpose of this study is to develop and evaluate a lung tumour interfraction geometric variability classification scheme as a means to guide adaptive radiotherapy and improve measurement of treatment response. Principal component analysis (PCA) was used to generate statistical shape models of the gross tumour volume (GTV) for 12 patients with weekly breath hold CT scans. Each eigenmode of the PCA model was classified as ‘trending’ or ‘non-trending’ depending on whether its contribution to the overall GTV variability included a time trend over the treatment course. Trending eigenmodes were used to reconstruct the original semi-automatically delineated GTVs into a reduced model containing only time trends. Reduced models were compared to the original GTVs by analyzing the reconstruction error in the GTV and position. Both retrospective (all weekly images) and prospective (only the first four weekly images) were evaluated. The average volume difference from the original GTV was 4.3% ± 2.4% for the trending model. The positional variability of the GTV over the treatment course, as measured by the standard deviation of the GTV centroid, was 1.9 ± 1.4 mm for the original GTVs, which was reduced to 1.2 ± 0.6 mm for the trending-only model. In 3/13 cases, the dominant eigenmode changed class between the prospective and retrospective models. The trending-only model preserved GTV and shape relative to the original GTVs, while reducing spurious positional variability. The classification scheme appears feasible for separating types of geometric variability by time trend.

Statistical analysis of stratospheric temperature and ozone profile data for trends and model comparison

NASA Technical Reports Server (NTRS)

Tiao, G. C.

1992-01-01

Work performed during the project period July 1, 1990 to June 30, 1992 on the statistical analysis of stratospheric temperature data, rawinsonde temperature data, and ozone profile data for the detection of trends is described. Our principal topics of research are trend analysis of NOAA stratospheric temperature data over the period 1978-1989; trend analysis of rawinsonde temperature data for the period 1964-1988; trend analysis of Umkehr ozone profile data for the period 1977-1991; and comparison of observed ozone and temperature trends in the lower stratosphere. Analysis of NOAA stratospheric temperature data indicates the existence of large negative trends at 0.4 mb level, with magnitudes increasing with latitudes away from the equator. Trend analysis of rawinsonde temperature data over 184 stations shows significant positive trends about 0.2 C per decade at surface to 500 mb range, decreasing to negative trends about -0.3 C at 100 to 50 mb range, and increasing slightly at 30 mb level. There is little evidence of seasonal variation in trends. Analysis of Umkehr ozone data for 12 northern hemispheric stations shows significant negative trends about -.5 percent per year in Umkehr layers 7-9 and layer 3, but somewhat less negative trends in layers 4-6. There is no pronounced seasonal variation in trends, especially in layers 4-9. A comparison was made of empirical temperature trends from rawinsonde data in the lower stratosphere with temperature changes determined from a one-dimensional radiative transfer calculation that prescribed a given ozone change over the altitude region, surface to 50 km, obtained from trend analysis of ozonsonde and Umkehr profile data. The empirical and calculated temperature trends are found in substantive agreement in profile shape and magnitude.

Growth Dynamics of Patient-Provider Internet Communication: Trend Analysis Using the Health Information National Trends Survey (2003 to 2013)

PubMed Central

Tarver, Will L; Menser, Terri; Hesse, Bradford W; Johnson, Tyler J; Beckjord, Ellen; Ford, Eric W

2018-01-01

Background Communication is key in chronic disease management, and the internet has altered the manner in which patients and providers can exchange information. Adoption of secure messaging differs among patients due to the digital divide that keeps some populations from having effective access to online resources. Objective This study aimed to examine the current state of online patient-provider communication, exploring trends over time in the use of online patient-provider communication tools. Methods A 3-part analytic process was used to study the following: (1) reanalysis, (2) close replication across years, and (3) trend analysis extension. During the reanalysis stage, the publicly available Health Information National Trends Survey (HINTS) 1 and 2 data were used with the goal of identifying the precise analytic methodology used in a prior study, published in 2007. The original analysis was extended to add 3 additional data years (ie, 2008, 2011, and 2013) using the original analytical approach with the purpose of identifying trends over time. Multivariate logistic regression was used to analyze pooled data across all years, with year as an added predictor, in addition to a model for each individual data year. Results The odds of internet users to communicate online with health care providers was significantly and increasingly higher year-over-year, starting in 2003 (2005: odds ratio [OR] 1.31, 95% CI 1.03-1.68; 2008: OR 2.14, 95% CI 1.76-2.59; 2011: OR 2.92, 95% CI 2.33-3.66; and 2013: OR 5.77; 95% CI 4.62-7.20). Statistically significant socio-economic factors found to be associated with internet users communicating online with providers included age, having health insurance, having a history of cancer, and living in an urban area of residence. Conclusions The proportion of internet users communicating online with their health care providers has significantly increased since 2003. Although these trends are encouraging, access challenges still exist for some groups, potentially giving rise to a new set of health disparities related to communication. PMID:29599107

Landbird trends in national parks of the North Coast and Cascades Network, 2005-12

USGS Publications Warehouse

Saracco, James F.; Holmgren, Amanda L.; Wilkerson, Robert L.; Siegel, Rodney B.; Kuntz, Robert C.; Jenkins, Kurt J.; Happe, Patricia J.; Boetsch, John R.; Huff, Mark H.

2014-01-01

National parks in the North Coast and Cascades Network (NCCN) can fulfill vital roles as refuges for bird species dependent on late-successional forest conditions and as reference sites for assessing the effects of land-use and land-cover changes on bird populations throughout the larger Pacific Northwest region. Additionally, long-term monitoring of landbirds throughout the NCCN provides information that can inform decisions about important management issues in the parks, including visitor impacts, fire management, and the effects of introduced species. In 2005, the NCCN began implementing a network-wide Landbird Monitoring Project as part of the NPS Inventory and Monitoring Program. In this report, we discuss 8-year trends (2005–12) of bird populations in the NCCN, based on a sampling framework of point counts established in three large wilderness parks (Mount Rainier, North Cascades, and Olympic National Parks), 7-year trends at Lewis and Clark National Historical Park (sampled in 2006, 2008, 2010, and 2012), and 5-year trends at San Juan Islands National Historical Park (sampled in 2007, 2009, and 2011). Our analysis encompasses a fairly short time span for this long-term monitoring program. The first 2 years of the time series (2005 and 2006) were implemented as part of a limited pilot study that included only a small subset of the transects. The subsequent 6 years (2007–12) represent just a single cycle through 5 years of alternating panels of transects in the large parks, with the first of five alternating panels revisited for the first time in 2012. Of 204 transects that comprise the six sampling panels in the large parks, only 68 (one-third) have thus been eligible for revisit surveys (34 during every year after 2005, and an additional 34 only in 2012) and can contribute to our current trend estimates. We therefore initiated the current analysis with a primary goal of testing our analytical procedures rather than detecting trends that might be strong enough to drive conservation or management decisions in the parks or elsewhere. We expect that aggregated trend detection results may change substantially over the next several years, as the number of transects with revisit histories triples and the spatial dispersion of transects contributing to trend estimates also improves greatly. In the meantime, caution should be exercised in interpreting the importance of trends, as individual years can have very large influences on the direction and magnitude of trends in a time series of such limited duration (and limited numbers of repeat visits at the small parks). Nevertheless, we estimated trends for 43 species at Mount Rainier National Park, 53 species at North Cascades National Park Complex, and 41 species at Olympic National Park. Of 137 park-species combinations (including combined-park analyses), we found 16 significant decreases (12 percent) and five significant increases (4 percent). We identify several limitations of the current analytical framework for trend assessment but suggest that the overall sampling design is strong and amenable to analysis by more recently developed model-based methods. These could provide a more flexible framework for examining trends and other population parameters of interest, as well as testing hypotheses that relate the distribution and abundance of species to environmental covariates. A model-based approach would allow for modeling various components of the detection process and analyzing observations (detection process), population state (occupancy, population size, density), and change (trend, local extinction and colonization rates turnover) simultaneously. Finally, we also evaluate operational aspects of NCCN Landbird Monitoring Project, and conclude that our robust, multi-party partnership is successfully implementing the project as it was envisioned.

Recent tree die-off has little effect on streamflow in contrast to expected increases from historical studies

NASA Astrophysics Data System (ADS)

Biederman, Joel A.; Somor, Andrew J.; Harpold, Adrian A.; Gutmann, Ethan D.; Breshears, David D.; Troch, Peter A.; Gochis, David J.; Scott, Russell L.; Meddens, Arjan J. H.; Brooks, Paul D.

2015-12-01

Recent bark beetle epidemics have caused regional-scale tree mortality in many snowmelt-dominated headwater catchments of western North America. Initial expectations of increased streamflow have not been supported by observations, and the basin-scale response of annual streamflow is largely unknown. Here we quantified annual streamflow responses during the decade following tree die-off in eight infested catchments in the Colorado River headwaters and one nearby control catchment. We employed three alternative empirical methods: (i) double-mass comparison between impacted and control catchments, (ii) runoff ratio comparison before and after die-off, and (iii) time-trend analysis using climate-driven linear models. In contrast to streamflow increases predicted by historical paired catchment studies and recent modeling, we did not detect streamflow changes in most basins following die-off, while one basin consistently showed decreased streamflow. The three analysis methods produced generally consistent results, with time-trend analysis showing precipitation was the strongest predictor of streamflow variability (R2 = 74-96%). Time-trend analysis revealed post-die-off streamflow decreased in three catchments by 11-29%, with no change in the other five catchments. Although counter to initial expectations, these results are consistent with increased transpiration by surviving vegetation and the growing body of literature documenting increased snow sublimation and evaporation from the subcanopy following die-off in water-limited, snow-dominated forests. The observations presented here challenge the widespread expectation that streamflow will increase following beetle-induced forest die-off and highlight the need to better understand the processes driving hydrologic response to forest disturbance.

Time Series Analysis of Onchocerciasis Data from Mexico: A Trend towards Elimination

PubMed Central

Pérez-Rodríguez, Miguel A.; Adeleke, Monsuru A.; Orozco-Algarra, María E.; Arrendondo-Jiménez, Juan I.; Guo, Xianwu

2013-01-01

Background In Latin America, there are 13 geographically isolated endemic foci distributed among Mexico, Guatemala, Colombia, Venezuela, Brazil and Ecuador. The communities of the three endemic foci found within Mexico have been receiving ivermectin treatment since 1989. In this study, we predicted the trend of occurrence of cases in Mexico by applying time series analysis to monthly onchocerciasis data reported by the Mexican Secretariat of Health between 1988 and 2011 using the software R. Results A total of 15,584 cases were reported in Mexico from 1988 to 2011. The data of onchocerciasis cases are mainly from the main endemic foci of Chiapas and Oaxaca. The last case in Oaxaca was reported in 1998, but new cases were reported in the Chiapas foci up to 2011. Time series analysis performed for the foci in Mexico showed a decreasing trend of the disease over time. The best-fitted models with the smallest Akaike Information Criterion (AIC) were Auto-Regressive Integrated Moving Average (ARIMA) models, which were used to predict the tendency of onchocerciasis cases for two years ahead. According to the ARIMA models predictions, the cases in very low number (below 1) are expected for the disease between 2012 and 2013 in Chiapas, the last endemic region in Mexico. Conclusion The endemic regions of Mexico evolved from high onchocerciasis-endemic states to the interruption of transmission due to the strategies followed by the MSH, based on treatment with ivermectin. The extremely low level of expected cases as predicted by ARIMA models for the next two years suggest that the onchocerciasis is being eliminated in Mexico. To our knowledge, it is the first study utilizing time series for predicting case dynamics of onchocerciasis, which could be used as a benchmark during monitoring and post-treatment surveillance. PMID:23459370

Long-term warming trends in Korea and contribution of urbanization

NASA Astrophysics Data System (ADS)

Park, B.; Min, S. K.; Kim, Y. H.; Kim, M. K.; Choi, Y.; Boo, K. O.

2016-12-01

This study provides a systematic investigation of the long-term temperature trends over Korean peninsula in comparison with global temperature trends and presents an updated assessment of the contribution of urban effect. Linear trends are analyzed for three different periods over South Korea in order to consider inhomogeneity due to changes in number of stations: recent 103 years (1912-2014, 6 stations), 61 years (1954-2014, 12 stations) and 42 years (1973-2014, 48 stations). HadCRUT4, MLOST and GISS datasets are used to obtain temperature trends in global mean and each country scales for the same periods. The temperature over South Korea has increased by 1.90°C, 1.35°C, and 0.99°C during 103, 61, and 42 years, respectively. This is equivalent to 1.4-2.6 times larger warming than the global mean trends. The countries located in the Northern mid latitudes exhibit slightly weaker warming trends to Korea (about 1.5 times stronger than of global means), suggesting a considerable impact of urbanization on the local warming over Korea. Updated analyses of the urbanization effect on temperature trends over South Korea suggest that 10-45% of the warming trends are due to urbanization effect, with stronger contributions during the recent decades. First, we compared the recent 42-year temperature trends between city and rural stations using the two approaches based on previous studies. Results show that urbanization effect has contributed to 30-45% of the temperature trends. Secondly, the contribution of urbanization to the temperature increase over Korea has been indirectly estimated using 56 ensemble members of 20CRv2 reanalysis data that include no influence of urbanization. Analysis results for the three periods indicate that urbanization effect could have contributed to the local warming over Korea by 10-25%.

Space Radiation Induced Cytogenetic Damage in the Blood Lymphocytes of Astronauts: Persistence of Damage After Flight and the Effects of Repeat Long Duration Missions

NASA Technical Reports Server (NTRS)

George, Kerry; Rhone, Jordan; Chappell, L. J.; Cucinotta, F. A.

2010-01-01

Cytogenetic damage was assessed in blood lymphocytes from astronauts before and after they participated in long-duration space missions of three months or more. The frequency of chromosome damage was measured by fluorescence in situ hybridization (FISH) chromosome painting before flight and at various intervals from a few days to many months after return from the mission. For all individuals, the frequency of chromosome exchanges measured within a month of return from space was higher than their prefight yield. However, some individuals showed a temporal decline in chromosome damage with time after flight. Statistical analysis using combined data for all astronauts indicated a significant overall decreasing trend in total chromosome exchanges with time after flight, although this trend was not seen for all astronauts and the yield of chromosome damage in some individuals actually increased with time after flight. The decreasing trend in total exchanges was slightly more significant when statistical analysis was restricted to data collected more than 220 days after return from flight. In addition, limited data on multiple flights show a lack of correlation between time in space and translocation yields. Data from three crewmembers who has participated in two separate long-duration space missions provide limited information on the effect of repeat flights and show a possible adaptive response to space radiation exposure.

A time series analysis performed on a 25-year period of kidney transplantation activity in a single center.

PubMed

Santori, G; Fontana, I; Bertocchi, M; Gasloli, G; Valente, U

2010-05-01

Following the example of many Western countries, where a "minimum volume rule" policy has been adopted as a quality parameter for complex surgical procedures, the Italian National Transplant Centre set the minimum number of kidney transplantation procedures/y at 30/center. The number of procedures performed in a single center over a large period may be treated as a time series to evaluate trends, seasonal cycles, and nonsystematic fluctuations. Between January 1, 1983, and December 31, 2007, we performed 1376 procedures in adult or pediatric recipients from living or cadaveric donors. The greatest numbers of cases/y were performed in 1998 (n = 86) followed by 2004 (n = 82), 1996 (n = 75), and 2003 (n = 73). A time series analysis performed using R Statistical Software (Foundation for Statistical Computing, Vienna, Austria), a free software environment for statistical computing and graphics, showed a whole incremental trend after exponential smoothing as well as after seasonal decomposition. However, starting from 2005, we observed a decreased trend in the series. The number of kidney transplants expected to be performed for 2008 by using the Holt-Winters exponential smoothing applied to the period 1983 to 2007 suggested 58 procedures, while in that year there were 52. The time series approach may be helpful to establish a minimum volume/y at a single-center level. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Sports participation increased in Spain: a population-based time trend study of 21 381 adults in the years 2000, 2005 and 2010.

PubMed

Palacios-Ceña, Domingo; Fernandez-de-Las-Peñas, Cesar; Hernández-Barrera, Valentín; Jiménez-Garcia, Rodrigo; Alonso-Blanco, Cristina; Carrasco-Garrido, Pilar

2012-12-01

To assess the trend in prevalence of Spanish adults who engaged in sports activities from 2000 to 2010. Retrospective analysis of three population-based cross-sectional surveys conducted on a representative sample of Spanish adults: 2000 (N=5160), 2005 (N=8170) and 2010 (N=8925). The overall prevalence of sport-active men increased from 45.8% to 52.12% between 2000 and 2010. Among women the prevalence also increased from 27.26% to 33.27% (adjusted OR 1.03 95% CI 1.02 to 1.04). A significant decrease in the prevalence of sport-active subjects was found as the age increases. Adjusted time trends analysis showed that the prevalence of sport-active women and men increased over time in all age groups, with exception of women aged 15-25 years (adjusted OR 0.99, 0.97 to 1.01). Higher educational level was associated with more sport activity. The first reason for not practising sport was 'I have no time due to working or studying'. Less than 10% of women and men reported health problems as the reason for not practising any sport. Sports participation in Spain has increased between 2000 and 2010 among young-aged and middle-aged adults and decreased among older people. Women showed lower prevalence of sport activity as compared to men.

Trend analysis of precipitation in Jharkhand State, India. Investigating precipitation variability in Jharkhand State

NASA Astrophysics Data System (ADS)

Chandniha, Surendra Kumar; Meshram, Sarita Gajbhiye; Adamowski, Jan Franklin; Meshram, Chandrashekhar

2017-10-01

Jharkhand is one of the eastern states of India which has an agriculture-based economy. Uncertain and erratic distribution of precipitation as well as a lack of state water resources planning is the major limitation to crop growth in the region. In this study, the spatial and temporal variability in precipitation in the state was examined using a monthly precipitation time series of 111 years (1901-2011) from 18 meteorological stations. Autocorrelation and Mann-Kendall/modified Mann-Kendall tests were utilized to detect possible trends, and the Theil and Sen slope estimator test was used to determine the magnitude of change over the entire time series. The most probable change year (change point) was detected using the Pettitt-Mann-Whitney test, and the entire time series was sub-divided into two parts: before and after the change point. Arc-Map 9.3 software was utilized to assess the spatial patterns of the trends over the entire state. Annual precipitation exhibited a decreasing trend in 5 out of 18 stations during the whole period. For annual, monsoon and winter periods of precipitation, the slope test indicated a decreasing trend for all stations during 1901-2011. The highest variability was observed in post-monsoon precipitation (77.87 %) and the lowest variability was observed in the annual series (15.76 %) over the 111 years. An increasing trend in precipitation in the state was found during the period 1901-1949, which was reversed during the subsequent period (1950-2011).

Analysis of Patent Activity in the Field of Quantum Information Processing

NASA Astrophysics Data System (ADS)

Winiarczyk, Ryszard; Gawron, Piotr; Miszczak, Jarosław Adam; Pawela, Łukasz; Puchała, Zbigniew

2013-03-01

This paper provides an analysis of patent activity in the field of quantum information processing. Data from the PatentScope database from the years 1993-2011 was used. In order to predict the future trends in the number of filed patents time series models were used.

A power analysis for multivariate tests of temporal trend in species composition.

PubMed

Irvine, Kathryn M; Dinger, Eric C; Sarr, Daniel

2011-10-01

Long-term monitoring programs emphasize power analysis as a tool to determine the sampling effort necessary to effectively document ecologically significant changes in ecosystems. Programs that monitor entire multispecies assemblages require a method for determining the power of multivariate statistical models to detect trend. We provide a method to simulate presence-absence species assemblage data that are consistent with increasing or decreasing directional change in species composition within multiple sites. This step is the foundation for using Monte Carlo methods to approximate the power of any multivariate method for detecting temporal trends. We focus on comparing the power of the Mantel test, permutational multivariate analysis of variance, and constrained analysis of principal coordinates. We find that the power of the various methods we investigate is sensitive to the number of species in the community, univariate species patterns, and the number of sites sampled over time. For increasing directional change scenarios, constrained analysis of principal coordinates was as or more powerful than permutational multivariate analysis of variance, the Mantel test was the least powerful. However, in our investigation of decreasing directional change, the Mantel test was typically as or more powerful than the other models.

Trends in income-related inequality in untreated caries among children in the United States: findings from NHANES I, NHANES III, and NHANES 1999-2004.

PubMed

Capurro, Diego Alberto; Iafolla, Timothy; Kingman, Albert; Chattopadhyay, Amit; Garcia, Isabel

2015-12-01

The goal of this analysis was to describe income-related inequality in untreated caries among children in the United States over time. The analysis focuses on children ages 2-12 years in three nationally representative U.S. surveys: the National Health and Nutrition Examination Survey (NHANES) 1971-1974, NHANES 1988-1994, and NHANES 1999-2004. The outcome of interest is untreated dental caries. Various methods are employed to measure absolute and relative inequality within each survey such as pair-wise comparisons, measures of association (odds ratios), and three summary measures of overall inequality: the slope index of inequality, the relative index of inequality, and the concentration index. Inequality trends are then assessed by comparing these estimates across the three surveys. Inequality was present in each of the three surveys analyzed. Whether measured on an absolute or relative scale, untreated caries disproportionately affected those with lower income. Trend analysis shows that, despite population-wide reductions in untreated caries between NHANES I and NHANES III, overall absolute inequality slightly increased, while overall relative inequality significantly increased. Between NHANES III and NHANES 1999-2004, both absolute and relative inequality tended to decrease; however, these changes were not statistically significant. Socioeconomic inequality in oral health is an important measure of progress in overall population health and a key input to inform health policies. This analysis shows the presence of socioeconomic inequality in oral health in the American child population, as well as changes in its magnitude over time. Further research is needed to determine the factors related to these changes and their relative contribution to inequality trends. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Variation in vulnerability to extreme-temperature-related mortality in Japan: A 40-year time-series analysis.

PubMed

Onozuka, Daisuke; Hagihara, Akihito

2015-07-01

Although the impact of extreme heat and cold on mortality has been documented in recent years, few studies have investigated whether variation in susceptibility to extreme temperatures has changed in Japan. We used data on daily total mortality and mean temperatures in Fukuoka, Japan, for 1973-2012. We used time-series analysis to assess the effects of extreme hot and low temperatures on all-cause mortality, stratified by decade, gender, and age, adjusting for time trends. We used a multivariate meta-analysis with a distributed lag non-linear model to estimate pooled non-linear lag-response relationships associated with extreme temperatures on mortality. The relative risk of mortality increased during heat extremes in all decades, with a declining trend over time. The mortality risk was higher during cold extremes for the entire study period, with a dispersed pattern across decades. Meta-analysis showed that both heat and cold extremes increased the risk of mortality. Cold effects were delayed and lasted for several days, whereas heat effects appeared quickly and did not last long. Our study provides quantitative evidence that extreme heat and low temperatures were significantly and non-linearly associated with the increased risk of mortality with substantial variation. Our results suggest that timely preventative measures are important for extreme high temperatures, whereas several days' protection should be provided for extreme low temperatures. Copyright © 2015 Elsevier Inc. All rights reserved.

Impact of infection control interventions on rates of Staphylococcus aureus bacteraemia in National Health Service acute hospitals, East Midlands, UK, using interrupted time-series analysis.

PubMed

Newitt, S; Myles, P R; Birkin, J A; Maskell, V; Slack, R C B; Nguyen-Van-Tam, J S; Szatkowski, L

2015-05-01

Reducing healthcare-associated infection (HCAI) is a UK national priority. Multiple national and regional interventions aimed at reduction have been implemented in National Health Service acute hospitals, but assessment of their effectiveness is methodologically challenging. To assess the effectiveness of national and regional interventions undertaken between 2004 and 2008 on rates of meticillin-resistant Staphylococcus aureus (MRSA) and meticillin-sensitive Staphylococcus aureus (MSSA) bacteraemia within acute hospitals in the East Midlands, using interrupted time-series analysis. We used segmented regression to compare rates of MRSA and MSSA bacteraemia in the pre-intervention, implementation, and post-intervention phases for combined intervention packages in eight acute hospitals. Most of the change in MSSA and MRSA rates occurred during the implementation phase. During this phase, there were significant downward trends in MRSA rates for seven of eight acute hospital groups; in four, this was a steeper quarter-on-quarter decline compared with the pre-intervention phase, and, in one, an upward trend in the pre-intervention phase was reversed. Regarding MSSA, there was a significant positive effect in four hospital groups: one upward trend during the pre-intervention phase was reversed, two upward trends plateaued, and in one hospital group an indeterminate trend decreased significantly. However, there were significant increasing trends in quarterly MSSA rates in four hospital groups during the implementation or post-intervention periods. The impact of interventions varied by hospital group but the overall results suggest that national and regional campaigns had a beneficial impact on MRSA and MSSA bacteraemia within the East Midlands. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

What is the impact of interventions that prevent fetal mortality on the increase of preterm live births in the State of Sao Paulo, Brazil?

PubMed

Alencar, Gizelton Pereira; da Silva, Zilda Pereira; Santos, Patrícia Carla; Raspantini, Priscila Ribeiro; Moura, Barbara Laisa Alves; de Almeida, Marcia Furquim; do Nascimento, Felipe Parra; Rodrigues, Laura C

2015-07-23

There is a global growing trend of preterm births and a decline trend of fetal deaths. Is there an impact of the decline of fetal mortality on the increase of preterm live births in State of Sao Paulo, Brazil? The time trends were evaluated by gestational age through exponential regression analysis. Data analyzed included the fetal mortality ratio, proportion of preterm live births, fertility rate of women 35 years and over, prenatal care, mother's education, multiple births and cesarean section deliveries. A survival analysis was carried out for 2000 and 2010. Preterm births showed the highest annual increase (3.2%) in the less than 28 weeks of gestation group and fetal mortality ratio decreased (7.4%) in the same gestational age group. There was an increase of cesarean section births and it was higher in the < 28 weeks group (6.1%). There was a decreased annual trend of mothers with inadequate prenatal care (6.1%) and low education (8.8%) and an increased trend in multiple births and fertility rates of women of 35 years and over. The variables were highly correlated to which other over time. In 2000, 8.2% of all pregnancies resulted in preterm births (0.9% in fetal deaths and 7.3% in live births). In 2010, the preterm birth increased to 9.4% (0.8% were preterm fetal deaths and 8.6% preterm live births). The results suggest that 45.2% could be the maximum contribution of successful interventions to prevent a fetal death on the increase in preterm live births. This increasing trend is also related to changes of the women reproductive profile with the change of the women reproductive profile and access to prenatal care.

Trends of geographic inequalities in the distribution of human resources in healthcare system: the case of Iran.

PubMed

Sefiddashti, Sara Emamgholipour; Arab, Mohammad; Ghazanfari, Sadegh; Kazemi, Zhila; Rezaei, Satar; Karyani, Ali Kazemi

2016-07-01

Considering the scarcity of skilled workers in the health sector, the appropriate distribution of human resources in this sector is very important for improving people's health. Having information about the degree of equality in the distribution of health human resources and their time trends is necessary for better planning and efficient use of these resources. The aim of this study was to determine the trend of inequality in the allocation of human resources in the health sector in Tehran between 2007 and 2013. This cross-sectional study was conducted in Tehran Province in Iran. The inequality in the distribution of human resources (specialists, general practitioners, pharmacists, paramedics, dentists, nurses and community health workers (Behvarz)) in 10 cities in Tehran Province was investigated using the Gini coefficient and the dissimilarity index. The time trend of inequality was examined by regression analysis. The required data were collected from the statistical yearbook of the Iran Statistics Center (ISC). The highest value of the Gini coefficient (GC) was related to nurses (GC = 0.291) in 2007. The highest value of the Gini coefficient was related to nurses and Behvarzs in 2008 and 2009, respectively. The distribution of specialists had the highest inequality in 2010 (GC = 0.298), 2011 (GC = 0.300) and 2013 (GC = 0.316). General practitioners had the lowest Gini coefficient for 2007, 2008 and 2012. Nurses for 2009 and Behvarzs for 2010, 2011 and 2013 had the lowest value of Gini coefficient. The dissimilarity indexes for specialists and general practitioners were 26.64 and 8.72 in 2013, respectively. The means of this index for included resources were 31.35, 18.27, 16.91, 22.32, 15.82, 26.74, and 24.33, respectively. The time trend analysis showed that the coefficient of time was positive for all of the human resources, except Behvarzes, and only the coefficient of general practitioners was statistically significant ( p<0.01). Over time, inequalities in the distribution of resources in the health sector have been increasing. By developing the private sector and considering the trend of this sector to operate in the more developed regions, health policy makers should continually evaluate the distribution of human resources, and they should arrange a specific plan for the allocation of human resources in the health sector.

Trends in selected streamflow statistics at 19 long-term streamflow-gaging stations indicative of outflows from Texas to Arkansas, Louisiana, Galveston Bay, and the Gulf of Mexico, 1922-2009

USGS Publications Warehouse

Barbie, Dana L.; Wehmeyer, Loren L.

2012-01-01

Trends in selected streamflow statistics during 1922-2009 were evaluated at 19 long-term streamflow-gaging stations considered indicative of outflows from Texas to Arkansas, Louisiana, Galveston Bay, and the Gulf of Mexico. The U.S. Geological Survey, in cooperation with the Texas Water Development Board, evaluated streamflow data from streamflow-gaging stations with more than 50 years of record that were active as of 2009. The outflows into Arkansas and Louisiana were represented by 3 streamflow-gaging stations, and outflows into the Gulf of Mexico, including Galveston Bay, were represented by 16 streamflow-gaging stations. Monotonic trend analyses were done using the following three streamflow statistics generated from daily mean values of streamflow: (1) annual mean daily discharge, (2) annual maximum daily discharge, and (3) annual minimum daily discharge. The trend analyses were based on the nonparametric Kendall's Tau test, which is useful for the detection of monotonic upward or downward trends with time. A total of 69 trend analyses by Kendall's Tau were computed - 19 periods of streamflow multiplied by the 3 streamflow statistics plus 12 additional trend analyses because the periods of record for 2 streamflow-gaging stations were divided into periods representing pre- and post-reservoir impoundment. Unless otherwise described, each trend analysis used the entire period of record for each streamflow-gaging station. The monotonic trend analysis detected 11 statistically significant downward trends, 37 instances of no trend, and 21 statistically significant upward trends. One general region studied, which seemingly has relatively more upward trends for many of the streamflow statistics analyzed, includes the rivers and associated creeks and bayous to Galveston Bay in the Houston metropolitan area. Lastly, the most western river basins considered (the Nueces and Rio Grande) had statistically significant downward trends for many of the streamflow statistics analyzed.

On signals faint and sparse: The ACICA algorithm for blind de-trending of exoplanetary transits with low signal-to-noise

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

Waldmann, I. P., E-mail: ingo@star.ucl.ac.uk

2014-01-01

Independent component analysis (ICA) has recently been shown to be a promising new path in data analysis and de-trending of exoplanetary time series signals. Such approaches do not require or assume any prior or auxiliary knowledge about the data or instrument in order to de-convolve the astrophysical light curve signal from instrument or stellar systematic noise. These methods are often known as 'blind-source separation' (BSS) algorithms. Unfortunately, all BSS methods suffer from an amplitude and sign ambiguity of their de-convolved components, which severely limits these methods in low signal-to-noise (S/N) observations where their scalings cannot be determined otherwise. Here wemore » present a novel approach to calibrate ICA using sparse wavelet calibrators. The Amplitude Calibrated Independent Component Analysis (ACICA) allows for the direct retrieval of the independent components' scalings and the robust de-trending of low S/N data. Such an approach gives us an unique and unprecedented insight in the underlying morphology of a data set, which makes this method a powerful tool for exoplanetary data de-trending and signal diagnostics.« less

Statistical analysis of long-term monitoring data for persistent organic pollutants in the atmosphere at 20 monitoring stations broadly indicates declining concentrations.

PubMed

Kong, Deguo; MacLeod, Matthew; Hung, Hayley; Cousins, Ian T

2014-11-04

During recent decades concentrations of persistent organic pollutants (POPs) in the atmosphere have been monitored at multiple stations worldwide. We used three statistical methods to analyze a total of 748 time series of selected POPs in the atmosphere to determine if there are statistically significant reductions in levels of POPs that have had control actions enacted to restrict or eliminate manufacture, use and emissions. Significant decreasing trends were identified in 560 (75%) of the 748 time series collected from the Arctic, North America, and Europe, indicating that the atmospheric concentrations of these POPs are generally decreasing, consistent with the overall effectiveness of emission control actions. Statistically significant trends in synthetic time series could be reliably identified with the improved Mann-Kendall (iMK) test and the digital filtration (DF) technique in time series longer than 5 years. The temporal trends of new (or emerging) POPs in the atmosphere are often unclear because time series are too short. A statistical detrending method based on the iMK test was not able to identify abrupt changes in the rates of decline of atmospheric POP concentrations encoded into synthetic time series.

Statistical assessment of changes in extreme maximum temperatures over Saudi Arabia, 1985-2014

NASA Astrophysics Data System (ADS)

Raggad, Bechir

2018-05-01

In this study, two statistical approaches were adopted in the analysis of observed maximum temperature data collected from fifteen stations over Saudi Arabia during the period 1985-2014. In the first step, the behavior of extreme temperatures was analyzed and their changes were quantified with respect to the Expert Team on Climate Change Detection Monitoring indices. The results showed a general warming trend over most stations, in maximum temperature-related indices, during the period of analysis. In the second step, stationary and non-stationary extreme-value analyses were conducted for the temperature data. The results revealed that the non-stationary model with increasing linear trend in its location parameter outperforms the other models for two-thirds of the stations. Additionally, the 10-, 50-, and 100-year return levels were found to change with time considerably and that the maximum temperature could start to reappear in the different T-year return period for most stations. This analysis shows the importance of taking account the change over time in the estimation of return levels and therefore justifies the use of the non-stationary generalized extreme value distribution model to describe most of the data. Furthermore, these last findings are in line with the result of significant warming trends found in climate indices analyses.

Long-term trend of foE in European higher middle latitudes

NASA Astrophysics Data System (ADS)

Laštovička, Jan

2016-04-01

Long-term changes and trends have been observed in the whole ionosphere below its maximum. As concerns the E region, historical global data (Bremer, 2008) provide predominantly slightly positive trend, even though some stations provide a negative trend. Here we use data of two European stations with the best long data series of parameters of the ionospheric E layer, Slough/Chilton and Juliusruh over 1975-2014 (40 years). Noon-time medians (10-14 LT) are analyzed. The trend pattern after removing solar influence is complex. For yearly average values for Chilton first foE is decreasing in 1975-1990 by about 0.1 MHz, then the trend levels off or a little increase occurs in 1990-2004, and finally in 2004-2014 again a decrease is observed (again by about 0.1 MHz but over shorter period). Juliusruh yields a similar pattern. Similar analysis is also done for some months to check seasonal dependence of trends. The stability of relation between solar activity and foE is tested to clarify potential role of this factor in apparent trend of foE.

Universal fractal scaling in stream chemistry and its implications for solute transport and water quality trend detection

NASA Astrophysics Data System (ADS)

Kirchner, James W.; Neal, Colin

2013-07-01

The chemical dynamics of lakes and streams affect their suitability as aquatic habitats and as water supplies for human needs. Because water quality is typically monitored only weekly or monthly, however, the higher-frequency dynamics of stream chemistry have remained largely invisible. To illuminate a wider spectrum of water quality dynamics, rainfall and streamflow were sampled in two headwater catchments at Plynlimon, Wales, at 7-h intervals for 1-2 y and weekly for over two decades, and were analyzed for 45 solutes spanning the periodic table from H+ to U. Here we show that in streamflow, all 45 of these solutes, including nutrients, trace elements, and toxic metals, exhibit fractal 1/fα scaling on time scales from hours to decades (α = 1.05 ± 0.15, mean ± SD). We show that this fractal scaling can arise through dispersion of random chemical inputs distributed across a catchment. These 1/f time series are non-self-averaging: monthly, yearly, or decadal averages are approximately as variable, one from the next, as individual measurements taken hours or days apart, defying naive statistical expectations. (By contrast, stream discharge itself is nonfractal, and self-averaging on time scales of months and longer.) In the solute time series, statistically significant trends arise much more frequently, on all time scales, than one would expect from conventional t statistics. However, these same trends are poor predictors of future trends-much poorer than one would expect from their calculated uncertainties. Our results illustrate how 1/f time series pose fundamental challenges to trend analysis and change detection in environmental systems.

Quantile regression and clustering analysis of standardized precipitation index in the Tarim River Basin, Xinjiang, China

NASA Astrophysics Data System (ADS)

Yang, Peng; Xia, Jun; Zhang, Yongyong; Han, Jian; Wu, Xia

2017-11-01

Because drought is a very common and widespread natural disaster, it has attracted a great deal of academic interest. Based on 12-month time scale standardized precipitation indices (SPI12) calculated from precipitation data recorded between 1960 and 2015 at 22 weather stations in the Tarim River Basin (TRB), this study aims to identify the trends of SPI and drought duration, severity, and frequency at various quantiles and to perform cluster analysis of drought events in the TRB. The results indicated that (1) both precipitation and temperature at most stations in the TRB exhibited significant positive trends during 1960-2015; (2) multiple scales of SPIs changed significantly around 1986; (3) based on quantile regression analysis of temporal drought changes, the positive SPI slopes indicated less severe and less frequent droughts at lower quantiles, but clear variation was detected in the drought frequency; and (4) significantly different trends were found in drought frequency probably between severe droughts and drought frequency.

Spatial and temporal trends in runoff at long-term streamgages within and near the Chesapeake Bay Watershed

USGS Publications Warehouse

Rice, Karen C.; Hirsch, Robert M.

2012-01-01

Long-term streamflow data within the Chesapeake Bay watershed and surrounding area were analyzed in an attempt to identify trends in streamflow. Data from 30 streamgages near and within the Chesapeake Bay watershed were selected from 1930 through 2010 for analysis. Streamflow data were converted to runoff and trend slopes in percent change per decade were calculated. Trend slopes for three runoff statistics (the 7-day minimum, the mean, and the 1-day maximum) were analyzed annually and seasonally. The slopes also were analyzed both spatially and temporally. The spatial results indicated that trend slopes in the northern half of the watershed were generally greater than those in the southern half. The temporal analysis was done by splitting the 80-year flow record into two subsets; records for 28 streamgages were analyzed for 1930 through 1969 and records for 30 streamgages were analyzed for 1970 through 2010. The mean of the data for all sites for each year were plotted so that the following datasets were analyzed: the 7-day minimum runoff for the north, the 7-day minimum runoff for the south, the mean runoff for the north, the mean runoff for the south, the 1-day maximum runoff for the north, and the 1-day maximum runoff for the south. Results indicated that the period 1930 through 1969 was statistically different from the period 1970 through 2010. For the 7-day minimum runoff and the mean runoff, the latter period had significantly higher streamflow than did the earlier period, although within those two periods no significant linear trends were identified. For the 1-day maximum runoff, no step trend or linear trend could be shown to be statistically significant for the north, although the south showed a mixture of an upward step trend accompanied by linear downtrends within the periods. In no case was a change identified that indicated an increasing rate of change over time, and no general pattern was identified of hydrologic conditions becoming "more extreme" over time.

Functional network mediates age-related differences in reaction time: a replication and extension study

PubMed Central

Gazes, Yunglin; Habeck, Christian; O'Shea, Deirdre; Razlighi, Qolamreza R; Steffener, Jason; Stern, Yaakov

2015-01-01

Introduction A functional activation (i.e., ordinal trend) pattern was previously identified in both young and older adults during task-switching performance, the expression of which correlated with reaction time. The current study aimed to (1) replicate this functional activation pattern in a new group of fMRI activation data, and (2) extend the previous study by specifically examining whether the effect of aging on reaction time can be explained by differences in the activation of the functional activation pattern. Method A total of 47 young and 50 older participants were included in the extension analysis. Participants performed task-switching as the activation task and were cued by the color of the stimulus for the task to be performed in each block. To test for replication, two approaches were implemented. The first approach tested the replicability of the predictive power of the previously identified functional activation pattern by forward applying the pattern to the Study II data and the second approach was rederivation of the activation pattern in the Study II data. Results Both approaches showed successful replication in the new data set. Using mediation analysis, expression of the pattern from the first approach was found to partially mediate age-related effects on reaction time such that older age was associated with greater activation of the brain pattern and longer reaction time, suggesting that brain activation efficiency (defined as “the rate of activation increase with increasing task difficulty” in Neuropsychologia 47, 2009, 2015) of the regions in the Ordinal trend pattern directly accounts for age-related differences in task performance. Discussion The successful replication of the functional activation pattern demonstrates the versatility of the Ordinal Trend Canonical Variates Analysis, and the ability to summarize each participant's brain activation map into one number provides a useful metric in multimodal analysis as well as cross-study comparisons. PMID:25874162

Day of the week lost time occupational injury trends in the US by gender and industry and their implications for work scheduling.

PubMed

Brogmus, G E

2007-03-01

While there is a growing body of research on the impact of work schedules on the risk of occupational injuries, there has been little investigation into the impact that the day of the week might have. The present research was completed to explore day of the week trends, reasons for such trends and the corresponding implications for work scheduling. Data for the number of injuries and illnesses involving days away from work (lost time; LT) in 2004 were provided by the US Bureau of Labor Statistics Office of Safety and Health Statistics. Data from the American Time Use Survey database were used to estimate work hours in 2004. From these two data sources, the rate of LT injuries and illnesses (per 200 000 work hours) by day of the week, industry sector and gender were estimated. The analysis revealed clear differences by day of the week, gender and major industry sector. Sundays had the highest rate overall--nearly 37% higher than the average of the remaining days, Monday to Saturday. Mondays had the next highest rate followed closely by Saturdays. This pattern was not the same for males and females. For males, Mondays had the highest LT rate (27% higher than the average of all other days) with all remaining days having essentially the same rate. For females, Sundays and Saturdays had much higher LT rates--122% and 60% higher, respectively, than the average weekday rate. There were also differences by industry and differences between genders by industry. The present analysis suggests that several factors may be contributing to the weekend and Monday trends observed. Lower-tenured (and younger) workers on the weekends, lower female management/supervision and second jobs on the weekend seem to be contributors to the high Saturday and Sunday LT rates. Differences in day of the week employment by industry did not account for the trends observed. Fraud and overtime also could not be confirmed as contributing to these trends. Monday trends were more complex to explain, with possible explanations including non-work-related weekend injuries being reported on Mondays, soft-tissue symptoms becoming more noticeable on Mondays, greater Monday morning flexion risk and reduced supervision in the construction industry on Mondays. Interpretation of these trends and the implications for work scheduling are discussed.

Assessing the fitness-for-purpose of satellite multi-mission ocean color climate data records: A protocol applied to OC-CCI chlorophyll-a data.

PubMed

Mélin, F; Vantrepotte, V; Chuprin, A; Grant, M; Jackson, T; Sathyendranath, S

2017-12-15

In this work, trend estimates are used as indicators to compare the multi-annual variability of different satellite chlorophyll- a (Chl a ) data and to assess the fitness-for-purpose of multi-mission Chl a products as climate data records (CDR). Under the assumption that single-mission products are free from spurious temporal artifacts and can be used as benchmark time series, multi-mission CDRs should reproduce the main trend patterns observed by single-mission series when computed over their respective periods. This study introduces and applies quantitative metrics to compare trend distributions from different data records. First, contingency matrices compare the trend diagnostics associated with two satellite products when expressed in binary categories such as existence, significance and signs of trends. Contingency matrices can be further summarized by metrics such as Cohen's κ index that rates the overall agreement between the two distributions of diagnostics. A more quantitative measure of the discrepancies between trends is provided by the distributions of differences between trend slopes. Thirdly, maps of the level of significance P of a t -test quantifying the degree to which two trend estimates differ provide a statistical, spatially-resolved, evaluation. The proposed methodology is applied to the multi-mission Ocean Colour-Climate Change Initiative (OC-CCI) Chl a data. The agreement between trend distributions associated with OC-CCI data and single-mission products usually appears as good as when single-mission products are compared. As the period of analysis is extended beyond 2012 to 2015, the level of agreement tends to be degraded, which might be at least partly due to the aging of the MODIS sensor on-board Aqua. On the other hand, the trends displayed by the OC-CCI series over the short period 2012-2015 are very consistent with those observed with VIIRS. These results overall suggest that the OC-CCI Chl a data can be used for multi-annual time series analysis (including trend detection), but with some caution required if recent years are included, particularly in the central tropical Pacific. The study also recalls the challenges associated with creating a multi-mission ocean color data record suitable for climate research.

Study of twenty preparations of human albumin solution which failed in quality control testing due to elevated sodium content, a poor internal quality control at manufacturing unit.

PubMed

Prasad, J P; Madhu, Y; Singh, Surinder; Soni, G R; Agnihotri, N; Singh, Varsha; Kumar, Pradeep; Jain, Nidhi; Prakash, Anu; Singh, Varun

2016-11-01

Current study is conducted in our laboratory due to failure in quality control testing of twenty batches of Human Albumin solution in which sodium content is higher than the prescribed limit. These batches are received in short duration from indigenous manufacturer and is the first incident of failure of Human albumin preparation in sodium content of manufacturer. On request of manufacturer, study is conducted to rule out the cause. Repeat testing of each out of specification batch is conducted and a trend analysis is drawn between our findings and manufacturer's results, also study of trend analysis of manufacturer for the last one year. Trend analysis data indicated towards poor consistency of batches with major shift at various time intervals in sodium content of human albumin preparation. Further analysis rule out that non-traceable quality of standard used in the internal quality control testing by manufacturer is the root cause of the problem. Copyright © 2016 International Alliance for Biological Standardization. Published by Elsevier Ltd. All rights reserved.

Rapid, Real-time Methane Detection in Ground Water Using a New Gas-Water Equilibrator Design

NASA Astrophysics Data System (ADS)

Ruybal, C. J.; DiGiulio, D. C.; Wilkin, R. T.; Hargrove, K. D.; McCray, J. E.

2014-12-01

Recent increases in unconventional gas development have been accompanied by public concern for methane contamination in drinking water wells near production areas. Although not a regulated pollutant, methane may be a marker contaminant for others that are less mobile in groundwater and thus may be detected later, or at a location closer to the source. In addition, methane poses an explosion hazard if exsolved concentrations reach 5 - 15% volume in air. Methods for determining dissolved gases, such as methane, have evolved over 60 years. However, the response time of these methods is insufficient to monitor trends in methane concentration in real-time. To enable rapid, real-time monitoring of aqueous methane concentrations during ground water purging, a new gas-water equilibrator (GWE) was designed that increases gas-water mass exchange rates of methane for measurement. Monitoring of concentration trends allows a comparison of temporal trends between sampling events and comparison of baseline conditions with potential post-impact conditions. These trends may be a result of removal of stored casing water, pre-purge ambient borehole flow, formation physical and chemical heterogeneity, or flow outside of well casing due to inadequate seals. Real-time information in the field can help focus an investigation, aid in determining when to collect a sample, save money by limiting costs (e.g. analytical, sample transport and storage), and provide an immediate assessment of local methane concentrations. Four domestic water wells, one municipal water well, and one agricultural water well were sampled for traditional laboratory analysis and compared to the field GWE results. Aqueous concentrations measured on the GWE ranged from non-detect to 1,470 μg/L methane. Some trends in aqueous methane concentrations measured on the GWE were observed during purging. Applying a paired t-test comparing the new GWE method and traditional laboratory analysis yielded a p-value 0.383, suggesting no significant difference between the two methods for the current study. Additional field and laboratory experimentation are necessary to justify use beyond screening. However, early GWE use suggests promising results and applications.

Nonstationarity of low flows and their timing in the eastern United States

NASA Astrophysics Data System (ADS)

Sadri, S.; Kam, J.; Sheffield, J.

2016-02-01

The analysis of the spatial and temporal patterns of low flows as well as their generation mechanisms over large geographic regions can provide valuable insights and understanding for climate change impacts, regional frequency analysis, risk assessment of extreme events, and decision-making regarding allowable withdrawals. The goal of this paper is to examine nonstationarity in low flow generation across the eastern US and explore the potential anthropogenic influences or climate drivers. We use nonparametric tests to identify abrupt and gradual changes in time series of low flows and their timing for 508 USGS streamflow gauging sites in the eastern US with more than 50 years of daily data, to systematically distinguish the effects of human intervention from those of climate variability. A time series decomposition algorithm was applied to 1-day, 7-day, 30-day, and 90-day annual low flow time series that combines the Box-Ljung test for detection of autocorrelation, the Pettitt test for abrupt step changes and the Mann-Kendall test for monotonic trends. Examination of the USGS notes for each site showed that many of the sites with step changes and around half of the sites with an increasing trend have been documented as having some kind of regulation. Sites with decreasing or no trend are less likely to have documented influences on flows. Overall, a general pattern of increasing low flows in the northeast and decreasing low flows in the southeast is evident over a common time period (1951-2005), even when discarding sites with significant autocorrelation, documented regulation or other human impacts. The north-south pattern of trends is consistent with changes in antecedent precipitation. The main exception is along the mid-Atlantic coastal aquifer system from eastern Virginia northwards, where low flows have decreased despite increasing precipitation, and suggests that declining groundwater levels due to pumping may have contributed to decreased low flows. For most sites, the majority of low flows occur in one season in the late summer to fall, as driven by the lower precipitation and higher evaporative demand in this season, but this is complicated in many regions because of the presence of a secondary low flow season in the winter for sites in the extreme northeast and in the spring for sites in Florida. Trends in low flow timing are generally undetectable, although abrupt step changes appear to be associated with regulation.

Nonstationarity of low flows and their timing in the eastern United States

NASA Astrophysics Data System (ADS)

Sadri, S.; Kam, J.; Sheffield, J.

2015-03-01

The analysis of the spatial and temporal patterns of low flows as well as their generation mechanisms over large geographic regions can provide valuable insights and understanding for climate change impacts, regional frequency analysis, risk assessment of extreme events, and decision-making regarding allowable withdrawals. We use nonparametric tests to identify abrupt and gradual changes in time series of low flows and their timing for 508 USGS streamflow gauging sites in the eastern US with more than 50 years of daily data, to systematically distinguish the effects of human intervention from those of climate variability. A time series decomposition algorithm was applied to 1 day, 7 day, 30 day, and 90 day annual low flow time series that combines the Box-Ljung test for detection of autocorrelation, the Pettitt test for abrupt step changes and the Mann-Kendall test for monotonic trends. Examination of the USGS notes for each site confirmed that many of the step changes and around half of the sites with an increasing trend were associated with regulation. Around a third of the sites with a decreasing trend were associated with a change of gauge datum. Overall, a general pattern of increasing low flows in the northeast and decreasing low flows in the southeast is evident over a common time period (1951-2005), even when discarding sites with significant autocorrelation, documented regulation or other human impacts. The north-south pattern of trends is consistent with changes in antecedent precipitation. The main exception is along the mid-Atlantic coastal aquifer system from eastern Virginia northwards, where low flows have decreased despite increasing precipitation, and suggests that declining groundwater levels due to pumping may have contributed to decreased low flows. For most sites, the majority of low flows occur in one season in the late summer to autumn, as driven by the lower precipitation and higher evaporative demand in this season, but this is complicated in many regions because of the presence of a secondary low flow season in the winter for sites in the extreme northeast and in the spring for sites in Florida. Trends in low flow timing are generally undetectable, although abrupt step changes appear to be associated with regulation.

Per capita alcohol consumption in Australia: will the real trend please step forward?

PubMed

Chikritzhs, Tanya N; Allsop, Steve J; Moodie, A Rob; Hall, Wayne D

2010-11-15

To estimate the national trend in per capita consumption (PCC) of alcohol for Australians aged 15 years and older for the financial years 1990-91 to 2008-09. With the use of data obtained from Australian Bureau of Statistics' catalogues and World Advertising Research Centre reports, three alternative series of annual totals of PCC of alcohol for the past 20 years (1990-91 to 2008-09) were estimated based on different assumptions about the alcohol content of wine. For the "old" series, the alcohol content of wine was assumed to have been stable over time. For the "new" series, the alcohol content of wine was assumed to have increased once in 2004-05 and then to have remained stable to 2008-09. For the "adjusted" series, the alcohol content of wine was assumed to have gradually increased over time, beginning in 1998-99. Linear trend analysis was applied to identify significant trends. National trend in annual PCC of alcohol 1990-91 to 2008-09. The new and adjusted series of annual totals of PCC of alcohol showed increasing trends; the old series was stable. Until recently, official national annual totals of PCC of alcohol were underestimated and led to the mistaken impression that levels of alcohol consumption had been stable since the early 1990s. In fact, Australia's total PCC has been increasing significantly over time because of a gradual increase in the alcohol content and market share of wine and is now at one of its highest points since 1991-92. This new information is consistent with evidence of increasing alcohol-related harm and highlights the need for timely and accurate data on alcohol sales and harms across Australia.

Skin Cancer, Irradiation, and Sunspots: The Solar Cycle Effect

PubMed Central

Zurbenko, Igor

2014-01-01

Skin cancer is diagnosed in more than 2 million individuals annually in the United States. It is strongly associated with ultraviolet exposure, with melanoma risk doubling after five or more sunburns. Solar activity, characterized by features such as irradiance and sunspots, undergoes an 11-year solar cycle. This fingerprint frequency accounts for relatively small variation on Earth when compared to other uncorrelated time scales such as daily and seasonal cycles. Kolmogorov-Zurbenko filters, applied to the solar cycle and skin cancer data, separate the components of different time scales to detect weaker long term signals and investigate the relationships between long term trends. Analyses of crosscorrelations reveal epidemiologically consistent latencies between variables which can then be used for regression analysis to calculate a coefficient of influence. This method reveals that strong numerical associations, with correlations >0.5, exist between these small but distinct long term trends in the solar cycle and skin cancer. This improves modeling skin cancer trends on long time scales despite the stronger variation in other time scales and the destructive presence of noise. PMID:25126567

Observed SWE trends and climate analysis for Northwest Pacific North America: validation for future projection of SWE using the CRCM and VIC

NASA Astrophysics Data System (ADS)

Bennett, K. E.; Bronaugh, D.; Rodenhuis, D.

2008-12-01

Observational databases of snow water equivalent (SWE) have been collected from Alaska, western US states and the Canadian provinces of British Columbia, Alberta, Saskatchewan, and territories of NWT, and the Yukon. These databases were initially validated to remove inconsistencies and errors in the station records, dates or the geographic co-ordinates of the station. The cleaned data was then analysed for historical (1950 to 2006) trend using emerging techniques for trend detection based on (first of the month) estimates for January to June. Analysis of SWE showed spatial variability in the count of records across the six month time period, and this study illustrated differences between Canadian and US (or the north and south) collection. Two different data sets (one gridded and one station) were then used to analyse April 1st records, for which there was the greatest spatial spread of station records for analysis with climate information. Initial results show spatial variability (in both magnitude and direction of trend) for trend results, and climate correlations and principal components indicate different drivers of change in SWE across the western US, Canada and north to Alaska. These results will be used to validate future predictions of SWE that are being undertaken using the Canadian Regional Climate Model (CRCM) and the Variable Infiltration Capacity (VIC) hydrologic model for Western Northern America (CRCM) and British Columbia (VIC).

Trends in biomedical informatics: automated topic analysis of JAMIA articles.

PubMed

Han, Dong; Wang, Shuang; Jiang, Chao; Jiang, Xiaoqian; Kim, Hyeon-Eui; Sun, Jimeng; Ohno-Machado, Lucila

2015-11-01

Biomedical Informatics is a growing interdisciplinary field in which research topics and citation trends have been evolving rapidly in recent years. To analyze these data in a fast, reproducible manner, automation of certain processes is needed. JAMIA is a "generalist" journal for biomedical informatics. Its articles reflect the wide range of topics in informatics. In this study, we retrieved Medical Subject Headings (MeSH) terms and citations of JAMIA articles published between 2009 and 2014. We use tensors (i.e., multidimensional arrays) to represent the interaction among topics, time and citations, and applied tensor decomposition to automate the analysis. The trends represented by tensors were then carefully interpreted and the results were compared with previous findings based on manual topic analysis. A list of most cited JAMIA articles, their topics, and publication trends over recent years is presented. The analyses confirmed previous studies and showed that, from 2012 to 2014, the number of articles related to MeSH terms Methods, Organization & Administration, and Algorithms increased significantly both in number of publications and citations. Citation trends varied widely by topic, with Natural Language Processing having a large number of citations in particular years, and Medical Record Systems, Computerized remaining a very popular topic in all years. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Survival Trends in Pediatric In-Hospital Cardiac Arrests: An Analysis from Get With The Guidelines-Resuscitation

PubMed Central

Girotra, Saket; Spertus, John A.; Li, Yan; Berg, Robert A.; Nadkarni, Vinay M.; Chan, Paul S.

2013-01-01

BACKGROUND Despite ongoing efforts to improve the quality of pediatric resuscitation, it remains unknown whether survival in children with in-hospital cardiac arrest has improved. METHODS & RESULTS Between 2000 and 2009, we identified children (<18 years) with an in-hospital cardiac arrest at hospitals with ≥ 3 years of participation and ≥ 5 cases annually within the national Get With The Guidelines-Resuscitation registry. Multivariable logistic regression was used to examine temporal trends in survival to discharge. We also explored whether trends in survival were due to improvement in acute resuscitation or post-resuscitation care and examined trends in neurological disability among survivors. Among 1031 children at 12 hospitals, the initial cardiac arrest rhythm was asystole and pulseless electrical activity in 874 children (84.8%) and ventricular fibrillation and pulseless ventricular tachycardia in 157 children (15.2%), with an increase in cardiac arrests due to asystole and pulseless electrical activity over time (P for trend <0.001). Risk-adjusted rates of survival to discharge increased from 14.3% in 2000 to 43.4% in 2009 (adjusted rate ratio per 1-year 1.08; 95% CI [1.01,1.16]; P for trend 0.02). Improvement in survival was largely driven by an improvement in acute resuscitation survival (risk adjusted rates: 42.9% in 2000, 81.2% in 2009; adjusted rate ratio per 1-year: 1.04; 95% CI [1.01,1.08]; P for trend 0.006). Moreover, survival trends were not accompanied by higher rates of neurological disability among survivors over time (unadjusted P for trend 0.32), suggesting an overall increase in the number of survivors without neurological disability over time. CONCLUSION Rates of survival to hospital discharge in children with in-hospital cardiac arrests have improved over the past decade without higher rates of neurological disability among survivors. PMID:23250980

Trends in HFE Methods and Tools and Their Applicability to Safety Reviews

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

O'Hara, J.M.; Plott, C.; Milanski, J.

2009-09-30

The U.S. Nuclear Regulatory Commission's (NRC) conducts human factors engineering (HFE) safety reviews of applicant submittals for new plants and for changes to existing plants. The reviews include the evaluation of the methods and tools (M&T) used by applicants as part of their HFE program. The technology used to perform HFE activities has been rapidly evolving, resulting in a whole new generation of HFE M&Ts. The objectives of this research were to identify the current trends in HFE methods and tools, determine their applicability to NRC safety reviews, and identify topics for which the NRC may need additional guidance tomore » support the NRC's safety reviews. We conducted a survey that identified over 100 new HFE M&Ts. The M&Ts were assessed to identify general trends. Seven trends were identified: Computer Applications for Performing Traditional Analyses, Computer-Aided Design, Integration of HFE Methods and Tools, Rapid Development Engineering, Analysis of Cognitive Tasks, Use of Virtual Environments and Visualizations, and Application of Human Performance Models. We assessed each trend to determine its applicability to the NRC's review by considering (1) whether the nuclear industry is making use of M&Ts for each trend, and (2) whether M&Ts reflecting the trend can be reviewed using the current design review guidance. We concluded that M&T trends that are applicable to the commercial nuclear industry and are expected to impact safety reviews may be considered for review guidance development. Three trends fell into this category: Analysis of Cognitive Tasks, Use of Virtual Environments and Visualizations, and Application of Human Performance Models. The other trends do not need to be addressed at this time.« less

Spring onset variations and long-term trends from new hemispheric-scale products and remote sensing

NASA Astrophysics Data System (ADS)

Dye, D. G.; Li, X.; Ault, T.; Zurita-Milla, R.; Schwartz, M. D.

2015-12-01

Spring onset is commonly characterized by plant phenophase changes among a variety of biophysical transitions and has important implications for natural and man-managed ecosystems. Here, we present a new integrated analysis of variability in gridded Northern Hemisphere spring onset metrics. We developed a set of hemispheric temperature-based spring indices spanning 1920-2013. As these were derived solely from meteorological data, they are used as a benchmark for isolating the climate system's role in modulating spring "green up" estimated from the annual cycle of normalized difference vegetation index (NDVI). Spatial patterns of interannual variations, teleconnections, and long-term trends were also analyzed in all metrics. At mid-to-high latitudes, all indices exhibit larger variability at interannual to decadal time scales than at spatial scales of a few kilometers. Trends of spring onset vary across space and time. However, compared to long-term trend, interannual to decadal variability generally accounts for a larger portion of the total variance in spring onset timing. Therefore, spring onset trends identified from short existing records may be aliased by decadal climate variations due to their limited temporal depth, even when these records span the entire satellite era. Based on our findings, we also demonstrated that our indices have skill in representing ecosystem-level spring phenology and may have important implications in understanding relationships between phenology, atmosphere dynamics and climate variability.

Changes of the time-varying percentiles of daily extreme temperature in China

NASA Astrophysics Data System (ADS)

Li, Bin; Chen, Fang; Xu, Feng; Wang, Xinrui

2017-11-01

Identifying the air temperature frequency distributions and evaluating the trends in time-varying percentiles are very important for climate change studies. In order to get a better understanding of the recent temporal and spatial pattern of the temperature changes in China, we have calculated the trends in temporal-varying percentiles of the daily extreme air temperature firstly. Then we divide all the stations to get the spatial patterns for the percentile trends using the average linkage cluster analysis method. To make a comparison, the shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 are also examined. Important results in three aspects have been achieved: (1) In terms of the trends in temporal-varying percentiles of the daily extreme air temperature, the most intense warming for daily maximum air temperature (Tmax) was detected in the upper percentiles with a significant increasing tendency magnitude (>2.5 °C/50year), and the greatest warming for daily minimum air temperature (Tmin) occurred with very strong trends exceeding 4 °C/50year. (2) The relative coherent spatial patterns for the percentile trends were found, and stations for the whole country had been divided into three clusters. The three primary clusters were distributed regularly to some extent from north to south, indicating the possible large influence of the latitude. (3) The most significant shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 was found in Tmax. More than half part of the frequency distribution show negative trends less than -0.5 °C/50year in 1961-1985, while showing trends less than 2.5 °C/50year in 1986-2010.

Towards understanding temporal and spatial dynamics of seagrass landscapes using time-series remote sensing

NASA Astrophysics Data System (ADS)

Lyons, Mitchell B.; Roelfsema, Chris M.; Phinn, Stuart R.

2013-03-01

The spatial and temporal dynamics of seagrasses have been well studied at the leaf to patch scales, however, the link to large spatial extent landscape and population dynamics is still unresolved in seagrass ecology. Traditional remote sensing approaches have lacked the temporal resolution and consistency to appropriately address this issue. This study uses two high temporal resolution time-series of thematic seagrass cover maps to examine the spatial and temporal dynamics of seagrass at both an inter- and intra-annual time scales, one of the first globally to do so at this scale. Previous work by the authors developed an object-based approach to map seagrass cover level distribution from a long term archive of Landsat TM and ETM+ images on the Eastern Banks (≈200 km2), Moreton Bay, Australia. In this work a range of trend and time-series analysis methods are demonstrated for a time-series of 23 annual maps from 1988 to 2010 and a time-series of 16 monthly maps during 2008-2010. Significant new insight was presented regarding the inter- and intra-annual dynamics of seagrass persistence over time, seagrass cover level variability, seagrass cover level trajectory, and change in area of seagrass and cover levels over time. Overall we found that there was no significant decline in total seagrass area on the Eastern Banks, but there was a significant decline in seagrass cover level condition. A case study of two smaller communities within the Eastern Banks that experienced a decline in both overall seagrass area and condition are examined in detail, highlighting possible differences in environmental and process drivers. We demonstrate how trend and time-series analysis enabled seagrass distribution to be appropriately assessed in context of its spatial and temporal history and provides the ability to not only quantify change, but also describe the type of change. We also demonstrate the potential use of time-series analysis products to investigate seagrass growth and decline as well as the processes that drive it. This study demonstrates clear benefits over traditional seagrass mapping and monitoring approaches, and provides a proof of concept for the use of trend and time-series analysis of remotely sensed seagrass products to benefit current endeavours in seagrass ecology.

Towards homoscedastic nonlinear cointegration for structural health monitoring

NASA Astrophysics Data System (ADS)

Zolna, Konrad; Dao, Phong B.; Staszewski, Wieslaw J.; Barszcz, Tomasz

2016-06-01

The paper presents the homoscedastic nonlinear cointegration. The method leads to stable variances in nonlinear cointegration residuals. The adapted Breusch-Pagan test procedure is developed to test for the presence of heteroscedasticity (or homoscedasticity) in the cointegration residuals obtained from the nonlinear cointegration analysis. Three different time series - i.e. one with a nonlinear quadratic deterministic trend, simulated vibration data and experimental wind turbine data - are used to illustrate the application of the proposed method. The proposed approach can be used for effective removal of nonlinear trends from various types of data and for reliable structural damage detection based on data that are corrupted by environmental and/or operational nonlinear trends.

Persistent collective trend in stock markets

NASA Astrophysics Data System (ADS)

Balogh, Emeric; Simonsen, Ingve; Nagy, Bálint Zs.; Néda, Zoltán

2010-12-01

Empirical evidence is given for a significant difference in the collective trend of the share prices during the stock index rising and falling periods. Data on the Dow Jones Industrial Average and its stock components are studied between 1991 and 2008. Pearson-type correlations are computed between the stocks and averaged over stock pairs and time. The results indicate a general trend: whenever the stock index is falling the stock prices are changing in a more correlated manner than in case the stock index is ascending. A thorough statistical analysis of the data shows that the observed difference is significant, suggesting a constant fear factor among stockholders.

Prevalence and Trends in Domestic Violence in South Korea: Findings From National Surveys.

PubMed

Kim, Jae Yop; Oh, Sehun; Nam, Seok In

2016-05-01

To examine trends in the prevalence of domestic violence since 1997, 1 year prior to the introduction of legislative countermeasures and accompanying services in South Korea, and to analyze what socio-demographic characteristics of perpetrators contribute to spousal violence and whether there were any changes in risk factors over time. This study used two sets of nationally representative household samples: married or cohabiting couples of 1,540 from the 1999 national survey and 3,269 from the 2010 National Survey of Domestic Violence. Frequency analysis was used to measure the prevalence of intimate partner violence (IPV), and cross-tabulation, correlation, and logistic regression analyses were used to look for socio-demographic risk factors of spousal physical violence and patterns of change over time. The frequency analysis showed that the IPV prevalence dropped by approximately 50%, from 34.1% in 1999 to 16.5% in 2010, though it was still higher than many other countries. The cross-tabulation and logistic regression analyses suggested that men with low socio-demographic characteristics were generally more violent, though this tendency did not apply to women. Instead, younger women seemed to be more violent than older women. Last, different levels of household income were associated with different levels of IPV in 2010, but no linear trend was detected. In this study, IPV prevalence trends and risk factors of two different time periods were discussed to provide implications for tackling the IPV problem. Future countermeasures must build on understanding about men with low socio-demographic status and younger women, who were more violent in marital relationships. © The Author(s) 2015.

Impact of the Economic Downturn on Elective Lumbar Spine Surgery in the United States: A National Trend Analysis, 2003 to 2013.

PubMed

Bernstein, David N; Brodell, David; Li, Yue; Rubery, Paul T; Mesfin, Addisu

2017-05-01

Retrospective database analysis. The impact of the 2008-2009 economic downtown on elective lumbar spine surgery is unknown. Our objective was to investigate the effect of the economic downturn on the overall trends of elective lumbar spine surgery in the United States. The Nationwide Inpatient Sample (NIS) was used in conjunction with US Census and macroeconomic data to determine historical trends. The economic downturn was defined as 2008 to 2009. Codes from the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), were used in order to identify appropriate procedures. Confidence intervals were determined using subgroup analysis techniques. From 2003 to 2012, there was a 19.8% and 26.1% decrease in the number of lumbar discectomies and laminectomies, respectively. Over the same time period, there was a 56.4% increase in the number of lumbar spinal fusions. The trend of elective lumbar spine surgeries per 100 000 persons in the US population remained consistent from 2008 to 2009. The number of procedures decreased by 4.5% from 2010 to 2011, 7.6% from 2011 to 2012, and 3.1% from 2012 to 2013. The R 2 value between the number of surgeries and the S&P 500 Index was statistically significant ( P ≤ .05). The economic downturn did not affect elective lumbar fusions, which increased in total from 2003 to 2013. The relationship between the S&P 500 Index and surgical trends suggests that during recessions, individuals may utilize other means, such as insurance, to cover procedural costs and reduce out-of-pocket expenditures, accounting for no impact of the economic downturn on surgical trends. These findings can assist multiple stakeholders in better understanding the interconnectedness of macroeconomics, policy, and elective lumbar spine surgery trends.

Evaluation of empirical relationships between extreme rainfall and daily maximum temperature in Australia

NASA Astrophysics Data System (ADS)

Herath, Sujeewa Malwila; Sarukkalige, Ranjan; Nguyen, Van Thanh Van

2018-01-01

Understanding the relationships between extreme daily and sub-daily rainfall events and their governing factors is important in order to analyse the properties of extreme rainfall events in a changing climate. Atmospheric temperature is one of the dominant climate variables which has a strong relationship with extreme rainfall events. In this study, a temperature-rainfall binning technique is used to evaluate the dependency of extreme rainfall on daily maximum temperature. The Clausius-Clapeyron (C-C) relation was found to describe the relationship between daily maximum temperature and a range of rainfall durations from 6 min up to 24 h for seven Australian weather stations, the stations being located in Adelaide, Brisbane, Canberra, Darwin, Melbourne, Perth and Sydney. The analysis shows that the rainfall - temperature scaling varies with location, temperature and rainfall duration. The Darwin Airport station shows a negative scaling relationship, while the other six stations show a positive relationship. To identify the trend in scaling relationship over time the same analysis is conducted using data covering 10 year periods. Results indicate that the dependency of extreme rainfall on temperature also varies with the analysis period. Further, this dependency shows an increasing trend for more extreme short duration rainfall and a decreasing trend for average long duration rainfall events at most stations. Seasonal variations of the scale changing trends were analysed by categorizing the summer and autumn seasons in one group and the winter and spring seasons in another group. Most of 99th percentile of 6 min, 1 h and 24 h rain durations at Perth, Melbourne and Sydney stations show increasing trend for both groups while Adelaide and Darwin show decreasing trend. Furthermore, majority of scaling trend of 50th percentile are decreasing for both groups.

Trend analysis of evapotranspiration over India: Observed from long-term satellite measurements

NASA Astrophysics Data System (ADS)

Goroshi, Sheshakumar; Pradhan, Rohit; Singh, Raghavendra P.; Singh, K. K.; Parihar, Jai Singh

2017-12-01

Owing to the lack of consistent spatial time series data on actual evapotranspiration ( ET), very few studies have been conducted on the long-term trend and variability in ET at a national scale over the Indian subcontinent. The present study uses biome specific ET data derived from NOAA satellite's advanced very high resolution radiometer to investigate the trends and variability in ET over India from 1983 to 2006. Trend analysis using the non-parametric Mann-Kendall test showed that the domain average ET decreased during the period at a rate of 0.22 mm year^{-1}. A strong decreasing trend (m = -1.75 mm year^{-1}, F = 17.41, P 0.01) was observed in forest regions. Seasonal analyses indicated a decreasing trend during southwest summer monsoon (m= -0.320 mm season^{-1} year^{-1}) and post-monsoon period (m= -0.188 mm season^{-1 } year^{-1}). In contrast, an increasing trend was observed during northeast winter monsoon (m = 0.156 mm season^{-1 } year^{-1}) and pre-monsoon (m = 0.068 mm season^{-1 } year^{-1}) periods. Despite an overall net decline in the country, a considerable increase ( 4 mm year^{-1}) was observed over arid and semi-arid regions. Grid level correlation with various climatic parameters exhibited a strong positive correlation (r >0.5) of ET with soil moisture and precipitation over semi-arid and arid regions, whereas a negative correlation (r -0.5) occurred with temperature and insolation in dry regions of western India. The results of this analysis are useful for understanding regional ET dynamics and its relationship with various climatic parameters over India. Future studies on the effects of ET changes on the hydrological cycle, carbon cycle, and energy partitioning are needed to account for the feedbacks to the climate.

76 FR 25345 - Annual Assessment of the Status of Competition in the Market for the Delivery of Video Programming

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-04

... as of June 30 of the relevant year to monitor trends on an annual basis. To continue our time-series... video programming? 24. MVPD Performance. We seek comment on the information and time- series data we... Television Performance. We seek information and time- series data for the analysis of various performance...

EO-1 Hyperion reflectance time series at calibration and validation sites: stability and sensitivity to seasonal dynamics

Treesearch

Petya K. Entcheva Campbell; Elizabeth M. Middleton; Kurt J. Thome; Raymond F. Kokaly; Karl Fred Huemmrich; David Lagomasino; Kimberly A. Novick; Nathaniel A. Brunsell

2013-01-01

This study evaluated Earth Observing 1 (EO-1) Hyperion reflectance time series at established calibration sites to assess the instrument stability and suitability for monitoring vegetation functional parameters. Our analysis using three pseudo-invariant calibration sites in North America indicated that the reflectance time series are devoid of apparent spectral trends...

Monitoring Springs in the Mojave Desert Using Landsat Time Series Analysis

NASA Technical Reports Server (NTRS)

Potter, Christopher S.

2018-01-01

The purpose of this study, based on Landsat satellite data was to characterize variations and trends over 30 consecutive years (1985-2016) in perennial vegetation green cover at over 400 confirmed Mojave Desert spring locations. These springs were surveyed between in 2015 and 2016 on lands managed in California by the U.S. Bureau of Land Management (BLM) and on several land trusts within the Barstow, Needles, and Ridgecrest BLM Field Offices. The normalized difference vegetation index (NDVI) from July Landsat images was computed at each spring location and a trend model was first fit to the multi-year NDVI time series using least squares linear regression.Â

An analysis of surface air temperature trends and variability along the Andes

NASA Astrophysics Data System (ADS)

Franquist, Eric S.

Climate change is difficult to study in mountainous regions such as the Andes since steep changes in elevation cannot always be resolved by climate models. However, it is important to examine temperature trends in this region as rises in surface air temperature are leading to the melting of tropical glaciers. Local communities rely on the glacier-fed streamflow to get their water for drinking, irrigation, and livestock. Moreover, communities also rely on the tourism of hikers who come to the region to view the glaciers. As the temperatures increase, these glaciers are no longer in equilibrium with their current climate and are receding rapidly and decreasing the streamflow. This thesis examines surface air temperature from 858 weather stations across Ecuador, Peru, and Chile in order to analyze changes in trends and variability. Three time periods were studied: 1961--1990, 1971--2000, and 1981--2010. The greatest warming occurred during the period of 1971--2000 with 92% of the stations experiencing positive trends with a mean of 0.24°C/decade. There was a clear shift toward cooler temperatures at all latitudes and below elevations of 500 m during the most recent time period studied (1981--2010). Station temperatures were more strongly correlated with the El Nino Southern Oscillation (ENSO), than the Pacific Decadal Oscillation (PDO), and the Southern Annular Mode (SAM). A principal component analysis confirmed ENSO as the main contributor of variability with the most influence in the lower latitudes. There were clear multidecadal changes in correlation strength for the PDO. The PDO contributed the most to the increases in station temperature trends during the 1961--1990 period, consistent with the PDO shift to the positive phase in the middle of this period. There were many strong positive trends at individual stations during the 1971--2000 period; however, these trends could not fully be attributed to ENSO, PDO, or SAM, indicating anthropogenic effects of greenhouse gas emissions as the most likely cause.

Recent Northern Hemisphere snow cover extent trends and implications for the snow-albedo feedback

NASA Astrophysics Data System (ADS)

Déry, Stephen J.; Brown, Ross D.

2007-11-01

Monotonic trend analysis of Northern Hemisphere snow cover extent (SCE) over the period 1972-2006 with the Mann-Kendall test reveals significant declines in SCE during spring over North America and Eurasia, with lesser declines during winter and some increases in fall SCE. The weekly mean trend attains -1.28, -0.78, and -0.48 × 106 km2 (35 years)-1 over the Northern Hemisphere, North America, and Eurasia, respectively. The standardized SCE time series vary and trend coherently over Eurasia and North America, with evidence of a poleward amplification of decreasing SCE trends during spring. Multiple linear regression analyses reveal a significant dependence of the retreat of the spring continental SCE on latitude and elevation. The poleward amplification is consistent with an enhanced snow-albedo feedback over northern latitudes that acts to reinforce an initial anomaly in the cryospheric system.

Detecting trends in landscape pattern metrics over a 20-year period using a sampling-based monitoring programme

USGS Publications Warehouse

Griffith, J.A.; Stehman, S.V.; Sohl, Terry L.; Loveland, Thomas R.

2003-01-01

Temporal trends in landscape pattern metrics describing texture, patch shape and patch size were evaluated in the US Middle Atlantic Coastal Plain Ecoregion. The landscape pattern metrics were calculated for a sample of land use/cover data obtained for four points in time from 1973-1992. The multiple sampling dates permit evaluation of trend, whereas availability of only two sampling dates allows only evaluation of change. Observed statistically significant trends in the landscape pattern metrics demonstrated that the sampling-based monitoring protocol was able to detect a trend toward a more fine-grained landscape in this ecoregion. This sampling and analysis protocol is being extended spatially to the remaining 83 ecoregions in the US and temporally to the year 2000 to provide a national and regional synthesis of the temporal and spatial dynamics of landscape pattern covering the period 1973-2000.

A bootstrap method for estimating uncertainty of water quality trends

USGS Publications Warehouse

Hirsch, Robert M.; Archfield, Stacey A.; DeCicco, Laura

2015-01-01

Estimation of the direction and magnitude of trends in surface water quality remains a problem of great scientific and practical interest. The Weighted Regressions on Time, Discharge, and Season (WRTDS) method was recently introduced as an exploratory data analysis tool to provide flexible and robust estimates of water quality trends. This paper enhances the WRTDS method through the introduction of the WRTDS Bootstrap Test (WBT), an extension of WRTDS that quantifies the uncertainty in WRTDS-estimates of water quality trends and offers various ways to visualize and communicate these uncertainties. Monte Carlo experiments are applied to estimate the Type I error probabilities for this method. WBT is compared to other water-quality trend-testing methods appropriate for data sets of one to three decades in length with sampling frequencies of 6–24 observations per year. The software to conduct the test is in the EGRETci R-package.

Long-term trends of suicide by choice of method in Norway: a joinpoint regression analysis of data from 1969 to 2012.

PubMed

Puzo, Quirino; Qin, Ping; Mehlum, Lars

2016-03-11

Suicide mortality and the rates by specific methods in a population may change over time in response to concurrent changes in relevant factors in society. This study aimed to identify significant changing points in method-specific suicide mortality from 1969 to 2012 in Norway. Data on suicide mortality by specific methods and by sex and age were retrieved from the Norwegian Cause-of-Death Register. Long-term trends in age-standardized rates of suicide mortality were analyzed by using joinpoint regression analysis. The most frequently used suicide method in the total population was hanging, followed by poisoning and firearms. Men chose suicide by firearms more often than women, whereas poisoning and drowning were more frequently used by women. The joinpoint analysis revealed that the overall trend of suicide mortality significantly changed twice along the period of 1969 to 2012 for both sexes. The male age-standardized suicide rate increased by 3.1% per year until 1989, and decreased by 1.2% per year between 1994 and 2012. Among females the long-term suicide rate increased by 4.0% per year until 1988, decreased by 5.5% through 1995, and then stabilized. Both sexes experienced an upward trend for suicide by hanging during the 44-year observation period, with a particularly significant increase in 15-24 year old males. The most distinct change among men was seen for firearms after 1988 with a significant decrease through 2012 of around 5% per year. For women, significant reductions since 1985-88 were observed for suicide by drowning and poisoning. The present study demonstrates different time trends for different suicide methods with significant reductions in suicide by firearms, drowning and poisoning after the peak in the suicide rate in the late 1980s. Suicide by means of hanging continuously increased, but did not fully compensate for the reduced use of other methods. This lends some support for the effectiveness of method-specific suicide preventive measures, such as restrictions to the access to firearms, which had been implemented in Norway during the relevant time period.

Longitudinal data analysis in support of functional stability concepts for leachate management at closed municipal landfills.

PubMed

Gibbons, Robert D; Morris, Jeremy W F; Prucha, Christopher P; Caldwell, Michael D; Staley, Bryan F

2014-09-01

Landfill functional stability provides a target that supports no environmental threat at the relevant point of exposure in the absence of active control systems. With respect to leachate management, this study investigates "gateway" indicators for functional stability in terms of the predictability of leachate characteristics, and thus potential threat to water quality posed by leachate emissions. Historical studies conducted on changes in municipal solid waste (MSW) leachate concentrations over time (longitudinal analysis) have concentrated on indicator compounds, primarily chemical oxygen demand (COD) and biochemical oxygen demand (BOD). However, validation of these studies using an expanded database and larger constituent sets has not been performed. This study evaluated leachate data using a mixed-effects regression model to determine the extent to which leachate constituent degradation can be predicted based on waste age or operational practices. The final dataset analyzed consisted of a total of 1402 samples from 101 MSW landfills. Results from the study indicated that all leachate constituents exhibit a decreasing trend with time in the post-closure period, with 16 of the 25 target analytes and aggregate classes exhibiting a statistically significant trend consistent with well-studied indicators such as BOD. Decreasing trends in BOD concentration after landfill closure can thus be considered representative of trends for many leachate constituents of concern. Copyright © 2014 Elsevier Ltd. All rights reserved.

A comparison of extreme rainfall characteristics in the Brazilian Amazon derived from two gridded data sets and a national rain gauge network

NASA Astrophysics Data System (ADS)

Clarke, Robin T.; Bulhoes Mendes, Carlos Andre; Costa Buarque, Diogo

2010-07-01

Two issues of particular importance for the Amazon watershed are: whether annual maxima obtained from reanalysis and raingauge records agree well enough for the former to be useful in extending records of the latter; and whether reported trends in Amazon annual rainfall are reflected in the behavior of annual extremes in precipitation estimated from reanalyses and raingauge records. To explore these issues, three sets of daily precipitation data (1979-2001) from the Brazilian Amazon were analyzed (NCEP/NCAR and ERA-40 reanalyses, and records from the raingauge network of the Brazilian water resources agency - ANA), using the following variables: (1) mean annual maximum precipitation totals, accumulated over one, two, three and five days; (2) linear trends in these variables; (3) mean length of longest within-year "dry" spell; (4) linear trends in these variables. Comparisons between variables obtained from all three data sources showed that reanalyses underestimated time-trends and mean annual maximum precipitation (over durations of one to five days), and the correlations between reanalysis and spatially-interpolated raingauge estimates were small for these two variables. Both reanalyses over-estimated mean lengths of dry period relative to the mean length recorded by the raingauge network. Correlations between the trends calculated from all three data sources were small. Time-trends averaged over the reanalysis grid-squares, and spatially-interpolated time trends from raingauge data, were all clustered around zero. In conclusion, although the NCEP/NCAR and ERA-40 gridded data-sets may be valuable for studies of inter-annual variability in precipitation totals, they were found to be inappropriate for analysis of precipitation extremes.

Trend detection in river flow indices in Poland

NASA Astrophysics Data System (ADS)

Piniewski, Mikołaj; Marcinkowski, Paweł; Kundzewicz, Zbigniew W.

2018-02-01

The issue of trend detection in long time series of river flow records is of vast theoretical interest and considerable practical relevance. Water management is based on the assumption of stationarity; hence, it is crucial to check whether taking this assumption is justified. The objective of this study is to analyse long-term trends in selected river flow indices in small- and medium-sized catchments with relatively unmodified flow regime (semi-natural catchments) in Poland. The examined indices describe annual and seasonal average conditions as well as annual extreme conditions—low and high flows. The special focus is on the spatial analysis of trends, carried out on a comprehensive, representative data set of flow gauges. The present paper is timely, as no spatially comprehensive studies (i.e. covering the entire Poland or its large parts) on trend detection in time series of river flow have been done in the recent 15 years or so. The results suggest that there is a strong random component in the river flow process, the changes are weak and the spatial pattern is complex. Yet, the results of trend detection in different indices of river flow in Poland show that there exists a spatial divide that seems to hold quite generally for various indices (annual, seasonal, as well as low and high flow). Decreases of river flow dominate in the northern part of the country and increases usually in the southern part. Stations in the central part show mostly `no trend' results. However, the spatial gradient is apparent only for the data for the period 1981-2016 rather than for 1956-2016. It seems also that the magnitude of increases of river flow is generally lower than that of decreases.

Analysis of long-term changes in extreme climatic indices: a case study of the Mediterranean climate, Marmara Region, Turkey

NASA Astrophysics Data System (ADS)

Abbasnia, Mohsen; Toros, Hüseyin

2018-05-01

This study aimed to analyze extreme temperature and precipitation indices at seven stations in the Marmara Region of Turkey for the period 1961-2016. The trend of temperature indices showed that the warm-spell duration and the numbers of summer days, tropical nights, warm nights, and warm days have increased, while the cold-spell duration and number of ice days, cool nights, and cool days have decreased across the Marmara Region. Additionally, the diurnal temperature range has slightly increased at most of the stations. A majority of stations have shown significant warming trends for warm days and warm nights throughout the study area, whereas warm extremes and night-time based temperature indices have shown stronger trends compared to cold extremes and day-time indices. The analysis of precipitation indices has mostly shown increasing trends in consecutive dry days and increasing trends in annual rainfall, rainfall intensity for inland and urban stations, especially for stations in Sariyer and Edirne, which are affected by a fast rate of urbanization. Overall, a large proportion of study stations have experienced an increase in annual precipitation and heavy precipitation events, although there was a low percentage of results that was significant. Therefore, it is expected that the rainfall events will tend to become shorter and more intense, the occurrence of temperature extremes will become more pronounced in favor of hotter events, and there will be an increase in the atmospheric moisture content over the Marmara Region. This provides regional evidence for the importance of ongoing research on climate change.

Use of seasonal trend decomposition to understand groundwater behaviour in the Permo-Triassic Sandstone aquifer, Eden Valley, UK

NASA Astrophysics Data System (ADS)

Lafare, Antoine E. A.; Peach, Denis W.; Hughes, Andrew G.

2016-02-01

The daily groundwater level (GWL) response in the Permo-Triassic Sandstone aquifers in the Eden Valley, England (UK), has been studied using the seasonal trend decomposition by LOESS (STL) technique. The hydrographs from 18 boreholes in the Permo-Triassic Sandstone were decomposed into three components: seasonality, general trend and remainder. The decomposition was analysed first visually, then using tools involving a variance ratio, time-series hierarchical clustering and correlation analysis. Differences and similarities in decomposition pattern were explained using the physical and hydrogeological information associated with each borehole. The Penrith Sandstone exhibits vertical and horizontal heterogeneity, whereas the more homogeneous St Bees Sandstone groundwater hydrographs characterize a well-identified seasonality; however, exceptions can be identified. A stronger trend component is obtained in the silicified parts of the northern Penrith Sandstone, while the southern Penrith, containing Brockram (breccias) Formation, shows a greater relative variability of the seasonal component. Other boreholes drilled as shallow/deep pairs show differences in responses, revealing the potential vertical heterogeneities within the Penrith Sandstone. The differences in bedrock characteristics between and within the Penrith and St Bees Sandstone formations appear to influence the GWL response. The de-seasonalized and de-trended GWL time series were then used to characterize the response, for example in terms of memory effect (autocorrelation analysis). By applying the STL method, it is possible to analyse GWL hydrographs leading to better conceptual understanding of the groundwater flow. Thus, variation in groundwater response can be used to gain insight into the aquifer physical properties and understand differences in groundwater behaviour.

Pedagogy and the PC: Trends in the AIS Curriculum

ERIC Educational Resources Information Center

Badua, Frank

2008-01-01

The author investigated the array of course topics in accounting information systems (AIS), as course syllabi embody. The author (a) used exploratory data analysis to determine the topics that AIS courses most frequently offered and (b) used descriptive statistics and econometric analysis to trace the diversity of course topics through time,…

Holocene Faunal Trends in West Siberia and Their Causes

NASA Astrophysics Data System (ADS)

Gashev, S. N.; Aleshina, A. O.; Zuban, I. A.; Lupinos, M. Y.; Mardonova, L. B.; Mitropolskiy, M. G.; Selyukov, A. G.; Sorokina, N. V.; Stolbov, V. A.; Shapovalov, S. I.

2017-12-01

Based on an analysis of the transformation of vertebrate and invertebrate fauna of West Siberia in the Holocene, the classification and periodization of the main faunal trends are presented. Against the background of changing environmental conditions, the key regularities of the faunal dynamics, and the ways some species penetrate into the territory of the region and others disappear from the beginning of the Holocene to the present time have been indicated. Three global and four fluctuating trends are identified. The anthropogenic trend is ascertained separately. A conclusion is made about the prevailing causes of these changes, associated primarily with periodic climatic processes of different levels, determined by planetary geological and cosmic cycles. It is emphasized that, in the historical period, anthropogenic factors play a significant role in the regional faunal dynamics.

The Smoking Habits of Three U. S. Newsmagazines: Surgeon General Be Damned?

ERIC Educational Resources Information Center

Tsien, Ay-Ling; Ostman, Ronald E.

A trend analysis was conducted to determine the characteristics of news articles, editorials, and advertisements about tobacco that appeared in the magazines "Newsweek,""Time," and "U. S. News and World Report." Nine time periods in three intervals were studied: 1959-1961-1963, 1965-1967-1969, and 1973-1975-1977. An…

American Newspaper Editorials on the Vietnam War: An Experimental Approach to Editorial Content Analysis.

ERIC Educational Resources Information Center

Elias, Stephen N.

The editorials about four Vietnam War news events that appeared in five newspapers were examined for content, tone, page placement, and length to discover what trends in editorial coverage occurred. The 131 editorials that were examined appeared in the "New York Times," the "Los Angeles Times," the "Wall Street…

Recent trends in water analysis triggering future monitoring of organic micropollutants.

PubMed

Schmidt, Torsten C

2018-03-21

Water analysis has been an important area since the beginning of analytical chemistry. The focus though has shifted substantially: from minerals and the main constituents of water in the time of Carl Remigius Fresenius to a multitude of, in particular, organic compounds at concentrations down to the sub-nanogram per liter level nowadays. This was possible only because of numerous innovations in instrumentation in recent decades, drivers of which are briefly discussed. In addition to the high demands on sensitivity, high throughput by automation and short analysis times are major requirements. In this article, some recent developments in the chemical analysis of organic micropollutants (OMPs) are presented. These include the analysis of priority pollutants in whole water samples, extension of the analytical window, in particular to encompass highly polar compounds, the trend toward more than one separation dimension before mass spectrometric detection, and ways of coping with unknown analytes by suspect and nontarget screening approaches involving high-resolution mass spectrometry. Furthermore, beyond gathering reliable concentration data for many OMPs, the question of the relevance of such data for the aquatic system under scrutiny is becoming ever more important. To that end, effect-based analytics can be used and may become part of future routine monitoring, mostly with a focus on adverse effects of OMPs in specific test systems mimicking environmental impacts. Despite advances in the field of water analysis in recent years, there are still many challenges for further analytical research. Graphical abstract Recent trends in water analysis of organic micropollutants that open new opportunities in future water monitoring. HRMS high-resolution mass spectrometry, PMOC persistent mobile organic compounds.

Eurodelta-Trends, a Multi-Model Experiment of Air Quality Hindcast in Europe over 1990-2010. Experiment Design and Key Findings

NASA Astrophysics Data System (ADS)

Colette, A.; Ciarelli, G.; Otero, N.; Theobald, M.; Solberg, S.; Andersson, C.; Couvidat, F.; Manders-Groot, A.; Mar, K. A.; Mircea, M.; Pay, M. T.; Raffort, V.; Tsyro, S.; Cuvelier, K.; Adani, M.; Bessagnet, B.; Bergstrom, R.; Briganti, G.; Cappelletti, A.; D'isidoro, M.; Fagerli, H.; Ojha, N.; Roustan, Y.; Vivanco, M. G.

2017-12-01

The Eurodelta-Trends multi-model chemistry-transport experiment has been designed to better understand the evolution of air pollution and its drivers for the period 1990-2010 in Europe. The main objective of the experiment is to assess the efficiency of air pollutant emissions mitigation measures in improving regional scale air quality. The experiment is designed in three tiers with increasing degree of computational demand in order to facilitate the participation of as many modelling teams as possible. The basic experiment consists of simulations for the years 1990, 2000 and 2010. Sensitivity analysis for the same three years using various combinations of (i) anthropogenic emissions, (ii) chemical boundary conditions and (iii) meteorology complements it. The most demanding tier consists in two complete time series from 1990 to 2010, simulated using either time varying emissions for corresponding years or constant emissions. Eight chemistry-transport models have contributed with calculation results to at least one experiment tier, and six models have completed the 21-year trend simulations. The modelling results are publicly available for further use by the scientific community. We assess the skill of the models in capturing observed air pollution trends for the 1990-2010 time period. The average particulate matter relative trends are well captured by the models, even if they display the usual lower bias in reproducing absolute levels. Ozone trends are also well reproduced, yet slightly overestimated in the 1990s. The attribution study emphasizes the efficiency of mitigation measures in reducing air pollution over Europe, although a strong impact of long range transport is pointed out for ozone trends. Meteorological variability is also an important factor in some regions of Europe. The results of the first health and ecosystem impact studies impacts building upon a regional scale multi-model ensemble over a 20yr time period will also be presented.

Intra-national variation in trends in overweight and leisure time physical activities in The Netherlands since 1980: stratification according to sex, age and urbanisation degree.

PubMed

Gast, G C M; Gast, G-C M; Frenken, F J M; van Leest, L A T M; Wendel-Vos, G C W; Bemelmans, W J E

2007-03-01

To investigate time trends in overweight and Leisure Time Physical Activities (LTPA) in The Netherlands since 1980. Intra-national differences were examined stratified for sex, age and urbanisation degree. We used a random sample of about 140,000 respondents aged 20-69 years from the Health Interview Survey (Nethhis) and subsequent Permanent Survey on Living Conditions (POLS). Self-reported data on weight and height and demographic characteristics were gathered through interviews (every year) and data on LTPA were collected by self-administered questionnaires (1990-1997, 2001-2004). Linear regression analysis was performed for trend analyses. During 1981-2004, mean body mass index (BMI) increased significantly by 1.0 kg/m(2) (average per year=0.05 kg/m(2)). Trends were similar across sex and different degrees of urbanisation, but varied across age groups. In 20-to 39-year-old women, mean BMI increased by 1.7 kg/m(2), which was more than in older age groups (P

Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios

PubMed Central

Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

2015-01-01

This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. PMID:26593919

Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios.

PubMed

Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

2015-11-17

This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.

A Proof of Concept Study of Function-Based Statistical Analysis of fNIRS Data: Syntax Comprehension in Children with Specific Language Impairment Compared to Typically-Developing Controls.

PubMed

Fu, Guifang; Wan, Nicholas J A; Baker, Joseph M; Montgomery, James W; Evans, Julia L; Gillam, Ronald B

2016-01-01

Functional near infrared spectroscopy (fNIRS) is a neuroimaging technology that enables investigators to indirectly monitor brain activity in vivo through relative changes in the concentration of oxygenated and deoxygenated hemoglobin. One of the key features of fNIRS is its superior temporal resolution, with dense measurements over very short periods of time (100 ms increments). Unfortunately, most statistical analysis approaches in the existing literature have not fully utilized the high temporal resolution of fNIRS. For example, many analysis procedures are based on linearity assumptions that only extract partial information, thereby neglecting the overall dynamic trends in fNIRS trajectories. The main goal of this article is to assess the ability of a functional data analysis (FDA) approach for detecting significant differences in hemodynamic responses recorded by fNIRS. Children with and without SLI wore two, 3 × 5 fNIRS caps situated over the bilateral parasylvian areas as they completed a language comprehension task. FDA was used to decompose the high dimensional hemodynamic curves into the mean function and a few eigenfunctions to represent the overall trend and variation structures over time. Compared to the most popular GLM, we did not assume any parametric structure and let the data speak for itself. This analysis identified significant differences between the case and control groups in the oxygenated hemodynamic mean trends in the bilateral inferior frontal and left inferior posterior parietal brain regions. We also detected significant group differences in the deoxygenated hemodynamic mean trends in the right inferior posterior parietal cortex and left temporal parietal junction. These findings, using dramatically different approaches, experimental designs, data sets, and foci, were consistent with several other reports, confirming group differences in the importance of these two areas for syntax comprehension. The proposed FDA was consistent with the temporal characteristics of fNIRS, thus providing an alternative methodology for fNIRS analyses.

Detecting seasonal and cyclical trends in agricultural runoff water quality-hypothesis tests and block bootstrap power analysis.

PubMed

Uddameri, Venkatesh; Singaraju, Sreeram; Hernandez, E Annette

2018-02-21

Seasonal and cyclic trends in nutrient concentrations at four agricultural drainage ditches were assessed using a dataset generated from a multivariate, multiscale, multiyear water quality monitoring effort in the agriculturally dominant Lower Rio Grande Valley (LRGV) River Watershed in South Texas. An innovative bootstrap sampling-based power analysis procedure was developed to evaluate the ability of Mann-Whitney and Noether tests to discern trends and to guide future monitoring efforts. The Mann-Whitney U test was able to detect significant changes between summer and winter nutrient concentrations at sites with lower depths and unimpeded flows. Pollutant dilution, non-agricultural loadings, and in-channel flow structures (weirs) masked the effects of seasonality. The detection of cyclical trends using the Noether test was highest in the presence of vegetation mainly for total phosphorus and oxidized nitrogen (nitrite + nitrate) compared to dissolved phosphorus and reduced nitrogen (total Kjeldahl nitrogen-TKN). Prospective power analysis indicated that while increased monitoring can lead to higher statistical power, the effect size (i.e., the total number of trend sequences within a time-series) had a greater influence on the Noether test. Both Mann-Whitney and Noether tests provide complementary information on seasonal and cyclic behavior of pollutant concentrations and are affected by different processes. The results from these statistical tests when evaluated in the context of flow, vegetation, and in-channel hydraulic alterations can help guide future data collection and monitoring efforts. The study highlights the need for long-term monitoring of agricultural drainage ditches to properly discern seasonal and cyclical trends.

Drought analysis and water resource availability using standardised precipitation evapotranspiration index

NASA Astrophysics Data System (ADS)

Hui-Mean, Foo; Yusop, Zulkifli; Yusof, Fadhilah

2018-03-01

Trend analysis for potential evapotranspiration (PET) and climatic water balance (CWB) is critical in identifying the wetness or dryness episodes with respect to the water surplus or deficit. The PET is computed based on the monthly average temperature for the entire Peninsular Malaysia using Thornthwaite parameterization. The trends and slope's magnitude for the PET and CWB were then investigated using Mann-Kendall, Spearman's rho tests and Thiel-Sen estimator. The 1-, 3-, 6- and 12-month standardised precipitation evapotranspiration index (SPEI) is applied to determine the drought episodes and the average recurrence interval are calculated based on the SPEI. The results indicate that most of the stations show an upward trend in annual and monthly PET while majority of the regions show an upward trend in annual CWB except for the Pahang state. The increasing trends detected in the CWB describe water is in excess especially during the northeast monsoons while the decreasing trends imply water insufficiency. The excess water is observed mostly in January especially in the west coast, east coast and southwest regions that suggest more water is available for crop requirement. The average recurrence interval for drought episodes is almost the same for the smaller severity with various time scale of SPEI and high probability of drought occurrence is observed for some regions. The findings are useful for policymakers and practitioners to improve water resources planning and management, in particular to minimise drought effects in the future. Future research shall address the influence of topography on drought behaviour using more meteorological stations and to include east Malaysia in the analysis.

The long-term changes in total ozone, as derived from Dobson measurements at Arosa (1948-2001)

NASA Astrophysics Data System (ADS)

Krzyscin, J. W.

2003-04-01

The longest possible total ozone time series (Arosa, Switzerland) is examined for a detection of trends. Two-step procedure is proposed to estimate the long-term (decadal) variations in the ozone time series. The first step consists of a standard least-squares multiple regression applied to the total ozone monthly means to parameterize "natural" (related to the oscillations in the atmospheric dynamics) variations in the analyzed time series. The standard proxies for the dynamical ozone variations are used including; the 11-year solar activity cycle, and indices of QBO, ENSO and NAO. We use the detrended time series of temperature at 100 hPa and 500 hPa over Arosa to parameterize short-term variations (with time periods<1 year) in total ozone related to local changes in the meteorological conditions over the station. The second step consists of a smooth-curve fitting to the total ozone residuals (original minus modeled "natural" time series), the time derivation applied to this curve to obtain local trends, and bootstrapping of the residual time series to estimate the standard error of local trends. Locally weighted regression and the wavelet analysis methodology are used to extract the smooth component out of the residual time series. The time integral over the local trend values provides the cumulative long-term change since the data beginning. Examining the pattern of the cumulative change we see the periods with total ozone loss (the end of 50s up to early 60s - probably the effect of the nuclear bomb tests), recovery (mid 60s up to beginning of 70s), apparent decrease (beginning of 70s lasting to mid 90s - probably the effect of the atmosphere contamination by anthropogenic substances containing chlorine), and with a kind of stabilization or recovery (starting in the mid of 90s - probably the effect of the Montreal protocol to eliminate substances reducing the ozone layer). We can also estimate that a full ozone recovery (return to the undisturbed total ozone level from the beginning of 70s) is expected around 2050. We propose to calculate both time series of local trends and the cumulative long-term change instead single trend value derived as a slope of straight line fit to the data.

A Comprehensive Analysis of Authorship in Radiology Journals.

PubMed

Dang, Wilfred; McInnes, Matthew D F; Kielar, Ania Z; Hong, Jiho

2015-01-01

The purpose of our study was to investigate authorship trends in radiology journals, and whether International Committee of Medical Journal Editors (ICMJE) recommendations have had an impact on these trends. A secondary objective was to explore other variables associated with authorship trends. A retrospective, bibliometric analysis of 49 clinical radiology journals published from 1946-2013 was conducted. The following data was exported from MEDLINE (1946 to May 2014) for each article: authors' full name, year of publication, primary author institution information, language of publication and publication type. Microsoft Excel Visual Basics for Applications scripts were programmed to categorize extracted data. Statistical analysis was performed to determine the overall mean number of authors per article over time, impact of ICMJE guidelines, authorship frequency per journal, country of origin, article type and language of publication. 216,271 articles from 1946-2013 were included. A univariate analysis of the mean authorship frequency per year of all articles yielded a linear relationship between time and authorship frequency. The mean number of authors per article in 1946 (1.42) was found to have increased consistently by 0.07 authors/ article per year (R² = 0.9728, P<0.001) to 5.79 authors/article in 2013. ICMJE guideline dissemination did not have an impact on this rise in authorship frequency. There was considerable variability in mean authors per article and change over time between journals, country of origin, language of publication and article type. Overall authorship for 49 radiology journals across 68 years has increased markedly with no demonstrated impact from ICMJE guidelines. A higher number of authors per article was seen in articles from: higher impact journals, European and Asian countries, original research type, and those journals who explicitly endorse the ICMJE guidelines.

A Comprehensive Analysis of Authorship in Radiology Journals

PubMed Central

Dang, Wilfred; McInnes, Matthew D. F.; Kielar, Ania Z.; Hong, Jiho

2015-01-01

Objectives The purpose of our study was to investigate authorship trends in radiology journals, and whether International Committee of Medical Journal Editors (ICMJE) recommendations have had an impact on these trends. A secondary objective was to explore other variables associated with authorship trends. Methods A retrospective, bibliometric analysis of 49 clinical radiology journals published from 1946–2013 was conducted. The following data was exported from MEDLINE (1946 to May 2014) for each article: authors’ full name, year of publication, primary author institution information, language of publication and publication type. Microsoft Excel Visual Basics for Applications scripts were programmed to categorize extracted data. Statistical analysis was performed to determine the overall mean number of authors per article over time, impact of ICMJE guidelines, authorship frequency per journal, country of origin, article type and language of publication. Results 216,271 articles from 1946–2013 were included. A univariate analysis of the mean authorship frequency per year of all articles yielded a linear relationship between time and authorship frequency. The mean number of authors per article in 1946 (1.42) was found to have increased consistently by 0.07 authors/ article per year (R² = 0.9728, P<0.001) to 5.79 authors/article in 2013. ICMJE guideline dissemination did not have an impact on this rise in authorship frequency. There was considerable variability in mean authors per article and change over time between journals, country of origin, language of publication and article type. Conclusion Overall authorship for 49 radiology journals across 68 years has increased markedly with no demonstrated impact from ICMJE guidelines. A higher number of authors per article was seen in articles from: higher impact journals, European and Asian countries, original research type, and those journals who explicitly endorse the ICMJE guidelines. PMID:26407072

Using machine learning to identify structural breaks in single-group interrupted time series designs.

PubMed

Linden, Ariel; Yarnold, Paul R

2016-12-01

Single-group interrupted time series analysis (ITSA) is a popular evaluation methodology in which a single unit of observation is being studied, the outcome variable is serially ordered as a time series and the intervention is expected to 'interrupt' the level and/or trend of the time series, subsequent to its introduction. Given that the internal validity of the design rests on the premise that the interruption in the time series is associated with the introduction of the treatment, treatment effects may seem less plausible if a parallel trend already exists in the time series prior to the actual intervention. Thus, sensitivity analyses should focus on detecting structural breaks in the time series before the intervention. In this paper, we introduce a machine-learning algorithm called optimal discriminant analysis (ODA) as an approach to determine if structural breaks can be identified in years prior to the initiation of the intervention, using data from California's 1988 voter-initiated Proposition 99 to reduce smoking rates. The ODA analysis indicates that numerous structural breaks occurred prior to the actual initiation of Proposition 99 in 1989, including perfect structural breaks in 1983 and 1985, thereby casting doubt on the validity of treatment effects estimated for the actual intervention when using a single-group ITSA design. Given the widespread use of ITSA for evaluating observational data and the increasing use of machine-learning techniques in traditional research, we recommend that structural break sensitivity analysis is routinely incorporated in all research using the single-group ITSA design. © 2016 John Wiley & Sons, Ltd.

Estimating time-based instantaneous total mortality rate based on the age-structured abundance index

NASA Astrophysics Data System (ADS)

Wang, Yingbin; Jiao, Yan

2015-05-01

The instantaneous total mortality rate ( Z) of a fish population is one of the important parameters in fisheries stock assessment. The estimation of Z is crucial to fish population dynamics analysis, abundance and catch forecast, and fisheries management. A catch curve-based method for estimating time-based Z and its change trend from catch per unit effort (CPUE) data of multiple cohorts is developed. Unlike the traditional catch-curve method, the method developed here does not need the assumption of constant Z throughout the time, but the Z values in n continuous years are assumed constant, and then the Z values in different n continuous years are estimated using the age-based CPUE data within these years. The results of the simulation analyses show that the trends of the estimated time-based Z are consistent with the trends of the true Z, and the estimated rates of change from this approach are close to the true change rates (the relative differences between the change rates of the estimated Z and the true Z are smaller than 10%). Variations of both Z and recruitment can affect the estimates of Z value and the trend of Z. The most appropriate value of n can be different given the effects of different factors. Therefore, the appropriate value of n for different fisheries should be determined through a simulation analysis as we demonstrated in this study. Further analyses suggested that selectivity and age estimation are also two factors that can affect the estimated Z values if there is error in either of them, but the estimated change rates of Z are still close to the true change rates. We also applied this approach to the Atlantic cod ( Gadus morhua) fishery of eastern Newfoundland and Labrador from 1983 to 1997, and obtained reasonable estimates of time-based Z.

Analysis of spatial and temporal rainfall trends in Sicily during the 1921-2012 period

NASA Astrophysics Data System (ADS)

Liuzzo, Lorena; Bono, Enrico; Sammartano, Vincenzo; Freni, Gabriele

2016-10-01

Precipitation patterns worldwide are changing under the effects of global warming. The impacts of these changes could dramatically affect the hydrological cycle and, consequently, the availability of water resources. In order to improve the quality and reliability of forecasting models, it is important to analyse historical precipitation data to account for possible future changes. For these reasons, a large number of studies have recently been carried out with the aim of investigating the existence of statistically significant trends in precipitation at different spatial and temporal scales. In this paper, the existence of statistically significant trends in rainfall from observational datasets, which were measured by 245 rain gauges over Sicily (Italy) during the 1921-2012 period, was investigated. Annual, seasonal and monthly time series were examined using the Mann-Kendall non-parametric statistical test to detect statistically significant trends at local and regional scales, and their significance levels were assessed. Prior to the application of the Mann-Kendall test, the historical dataset was completed using a geostatistical spatial interpolation technique, the residual ordinary kriging, and then processed to remove the influence of serial correlation on the test results, applying the procedure of trend-free pre-whitening. Once the trends at each site were identified, the spatial patterns of the detected trends were examined using spatial interpolation techniques. Furthermore, focusing on the 30 years from 1981 to 2012, the trend analysis was repeated with the aim of detecting short-term trends or possible changes in the direction of the trends. Finally, the effect of climate change on the seasonal distribution of rainfall during the year was investigated by analysing the trend in the precipitation concentration index. The application of the Mann-Kendall test to the rainfall data provided evidence of a general decrease in precipitation in Sicily during the 1921-2012 period. Downward trends frequently occurred during the autumn and winter months. However, an increase in total annual precipitation was detected during the period from 1981 to 2012.

Temporal Methods to Detect Content-Based Anomalies in Social Media

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

Skryzalin, Jacek; Field, Jr., Richard; Fisher, Andrew N.

Here, we develop a method for time-dependent topic tracking and meme trending in social media. Our objective is to identify time periods whose content differs signifcantly from normal, and we utilize two techniques to do so. The first is an information-theoretic analysis of the distributions of terms emitted during different periods of time. In the second, we cluster documents from each time period and analyze the tightness of each clustering. We also discuss a method of combining the scores created by each technique, and we provide ample empirical analysis of our methodology on various Twitter datasets.

Space-time latent component modeling of geo-referenced health data.

PubMed

Lawson, Andrew B; Song, Hae-Ryoung; Cai, Bo; Hossain, Md Monir; Huang, Kun

2010-08-30

Latent structure models have been proposed in many applications. For space-time health data it is often important to be able to find the underlying trends in time, which are supported by subsets of small areas. Latent structure modeling is one such approach to this analysis. This paper presents a mixture-based approach that can be applied to component selection. The analysis of a Georgia ambulatory asthma county-level data set is presented and a simulation-based evaluation is made. Copyright (c) 2010 John Wiley & Sons, Ltd.

Climate driven variability and detectability of temporal trends in low flow indicators for Ireland

NASA Astrophysics Data System (ADS)

Hall, Julia; Murphy, Conor; Harrigan, Shaun

2013-04-01

Observational data from hydrological monitoring programs plays an important role in informing decision makers of changes in key hydrological variables. To analyse how changes in climate influence stream flow, undisturbed river basins with near-natural conditions limited from human influences are needed. This study analyses low flow indicators derived from observations from the Irish Reference Network. Within the trend analysis approach the influence of individual years or sub-periods on the detected trend are analysed using sequential trend tests on all possible periods (of at least 10 years in length) by varying the start and end dates of records for various indicators. Results from this study highlight that the current standard approach using fixed periods to determine long term trends is not appropriate as statistical significance and direction of trends from short term records do not persist continuously over entire record and can be heavily influenced by extremes within the record. The importance of longer records in contextualising short term trends derived from fixed-periods influenced by natural annual, inter-annual and multi-decadal variability is highlighted. Due to the low signal (trend) to noise (variability) ratio, the apparent trends derived from the low flow indicators cannot be used as confident guides to inform future water resources planning and decision making on climate change. Infact, some derived trends contradict expected climate change impacts and even small changes in study design can change the outcomes to a high degree. Therefore it is important not only to evaluate the magnitude of trends derived from monitoring data but also when a trend of a certain magnitude in a given indicator will be detectable to inform decision making or what changes might be required to detect trends for a certain significance level. In this study, the influence of observed variance in the monitoring records on the expected detection times for trends with a fixed magnitude are presented. Depending on the indicator selected, the sample variance and trend magnitude very different detection time estimates are obtained and in most cases not within the time required for anticipatory adaptation in the water resources sector. Additionally, the minimum changes in low flow indicators required to be detectable are large and changes are unlikely to be statistically detectable for many years. This means that water management and planning for anticipated future climatic changes will be required to take place without these changes being formally statistically detectable.Waiting for these trends to become formally detectable with the traditional statistical methods might not be an option for water resources management. Within the monitoring network, a considerable difference is apparent between stations in terms of detection times and changes required for detection. The existence of flow monitoring stations showing short detection times for specific indicators confirms the potential for identifying stations that may be first responders to climate induced changes. Identifying sentinel stations can increase the ability to more effectively optimise the deployment of resources for monitoring the influences of climatic change in a hydrometric reference network.

Water-quality trend analysis and sampling design for the Souris River, Saskatchewan, North Dakota, and Manitoba

USGS Publications Warehouse

Vecchia, Aldo V.

2000-01-01

The Souris River Basin is a 24,600-square-mile basin located in southeast Saskatchewan, north-central North Dakota, and southwest Manitoba.  The Souris River Bilateral Water Quality Monitoring Group, formed in 1989 by the governments of Canada and the United States, is responsible for documenting trends in water quality in the Souris River and making recommendations for monitoring future water-quality conditions.  This report presents results of a study conducted for the Bilateral Water Quality Monitoring Group by the U.S. Geological Survey, in cooperation with the North Dakota Department of Health, to analyze historic trends in water quality in the Souris River and to determine efficient sampling designs for monitoring future trends.  U.S. Geological Survey and Environment Canada water-quality data collected during 1977-96 from four sites near the boundary crossings between Canada and the United States were included in the trend analysis. A parametric time-series model was developed for detecting trends in historic constituent concentration data.  The model can be applied to constituents that have at least 90 percent of observations above detection limits of the analyses, which, for the Souris River, includes most major ions and nutrients and many trace elements.  The model can detect complex nonmonotonic trends in concentration in the presence of complex interannual and seasonal variability in daily discharge.  A key feature of the model is its ability to handle highly irregular sampling intervals.  For example, the intervals between concentration measurements may be be as short as 10 days to as long as several months, and the number of samples in any given year can range from zero to 36. Results from the trend analysis for the Souris River indicated numerous trends in constituent concentration.  The most significant trends at the two sites located near the upstream boundary crossing between Saskatchewan and North Dakota consisted of increases in concentrations of most major ions, dissolved boron, and dissolved arsenic during 1987-91 and decreases in concentrations of the same constituents during 1992-96.  Significant trends at the two sites located near the downstream boundary crossing between North Dakota and Manitoba included increases in dissolved sodium, dissolved chloride, and total phosphorus during 1977-86, decreases in dissolved oxygen and dissolved boron and increases in total phosphorus and dissolved iron during 1987-91, and a decrease in total phosphorus during 1992-96. The time-series model also was used to determine the sensitivity of various sampling designs for monitoring future water-quality trends in the Souris River.  It was determined that at least two samples per year are required in each of three seasons--March through June, July through October, and November through February--to obtain reasonable sensitivity for detecting trends in each season.  In addition, substantial improvements occurred in sensitivity for detecting trends by adding a third sample for major ions and trace elements in March through June, adding a third sample for nutrients in July through October, and adding a third sample for nutrients, trace elements, and dissolved oxygen in November through February.

Forecasting of particulate matter time series using wavelet analysis and wavelet-ARMA/ARIMA model in Taiyuan, China.

PubMed

Zhang, Hong; Zhang, Sheng; Wang, Ping; Qin, Yuzhe; Wang, Huifeng

2017-07-01

Particulate matter with aerodynamic diameter below 10 μm (PM 10 ) forecasting is difficult because of the uncertainties in describing the emission and meteorological fields. This paper proposed a wavelet-ARMA/ARIMA model to forecast the short-term series of the PM 10 concentrations. It was evaluated by experiments using a 10-year data set of daily PM 10 concentrations from 4 stations located in Taiyuan, China. The results indicated the following: (1) PM 10 concentrations of Taiyuan had a decreasing trend during 2005 to 2012 but increased in 2013. PM 10 concentrations had an obvious seasonal fluctuation related to coal-fired heating in winter and early spring. (2) Spatial differences among the four stations showed that the PM 10 concentrations in industrial and heavily trafficked areas were higher than those in residential and suburb areas. (3) Wavelet analysis revealed that the trend variation and the changes of the PM 10 concentration of Taiyuan were complicated. (4) The proposed wavelet-ARIMA model could be efficiently and successfully applied to the PM 10 forecasting field. Compared with the traditional ARMA/ARIMA methods, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. Wavelet analysis can filter noisy signals and identify the variation trend and the fluctuation of the PM 10 time-series data. Wavelet decomposition and reconstruction reduce the nonstationarity of the PM 10 time-series data, and thus improve the accuracy of the prediction. This paper proposed a wavelet-ARMA/ARIMA model to forecast the PM 10 time series. Compared with the traditional ARMA/ARIMA method, this wavelet-ARMA/ARIMA method could effectively reduce the forecasting error, improve the prediction accuracy, and realize multiple-time-scale prediction. The proposed model could be efficiently and successfully applied to the PM 10 forecasting field.

Real-time open-loop frequency response analysis of flight test data

NASA Technical Reports Server (NTRS)

Bosworth, J. T.; West, J. C.

1986-01-01

A technique has been developed to compare the open-loop frequency response of a flight test aircraft real time with linear analysis predictions. The result is direct feedback to the flight control systems engineer on the validity of predictions and adds confidence for proceeding with envelope expansion. Further, gain and phase margins can be tracked for trends in a manner similar to the techniques used by structural dynamics engineers in tracking structural modal damping.

Std trends in chengalpattu hospital.

PubMed

Krishnamurthy, V R; Ramachandran, V

1996-01-01

A retrospective data analysis was carried out to find the trends in frequency and distribution of different STDs at Chengalpattu during 1988-1994. Of the 4549 patients who attended the clinic 3621 (79.6%) were males and 928 (20.4%) were females. The commonest STD was Chancroid (24.4%) in men and Syphillis (29%) in women. Balanoposthitis (11.4%) ranked third among STDs in males. Though the STD attendance showed a declining trend, most diseases showed a constant distribution. The percentage composition of secondary and latent syphillis, Genital Warts, Genital Herpes and the Non-Venereal group showed an increased composition in recent years. Primary syphillis in females showed a definite declining trend. The HIV sero-positive detection rate was 2.06%. Of the 1116 patients screened for HIV antibody, 23 patients were detected sero-positive. Time Series Regression Analysis was used to predict the number of patients who would attend the STD clinic with various STDs in 1995 and 1996 to help in the understanding of the disease load and pattern in future, in resources management and in developing and evaluating preventive measures.

Exploiting mineral data: applications to the diversity, distribution, and social networks of copper mineral

NASA Astrophysics Data System (ADS)

Morrison, S. M.; Downs, R. T.; Golden, J. J.; Pires, A.; Fox, P. A.; Ma, X.; Zednik, S.; Eleish, A.; Prabhu, A.; Hummer, D. R.; Liu, C.; Meyer, M.; Ralph, J.; Hystad, G.; Hazen, R. M.

2016-12-01

We have developed a comprehensive database of copper (Cu) mineral characteristics. These data include crystallographic, paragenetic, chemical, locality, age, structural complexity, and physical property information for the 689 Cu mineral species approved by the International Mineralogical Association (rruff.info/ima). Synthesis of this large, varied dataset allows for in-depth exploration of statistical trends and visualization techniques. With social network analysis (SNA) and cluster analysis of minerals, we create sociograms and chord diagrams. SNA visualizations illustrate the relationships and connectivity between mineral species, which often form cliques associated with rock type and/or geochemistry. Using mineral ecology statistics, we analyze mineral-locality frequency distribution and predict the number of missing mineral species, visualized with accumulation curves. By assembly of 2-dimensional KLEE diagrams of co-existing elements in minerals, we illustrate geochemical trends within a mineral system. To explore mineral age and chemical oxidation state, we create skyline diagrams and compare trends with varying chemistry. These trends illustrate mineral redox changes through geologic time and correlate with significant geologic occurrences, such as the Great Oxidation Event (GOE) or Wilson Cycles.

Measurements of the Solar Spectral Irradiance Variability over Solar Cycles 21 to 24

NASA Astrophysics Data System (ADS)

Woods, T. N.

2017-12-01

The solar irradiance is the primary natural energy input into Earth's atmosphere and climate system. Understanding the long-term variations of the solar spectral irradiance (SSI) over time scales of the 11-year solar activity cycle and longer is critical for most Sun-climate research topics. There are satellite measurements of the SSI since the 1970s that contribute to understanding the solar cycle variability over Solar Cycles 21 to 24. A limiting factor for the accuracy of these results is the uncertainties for the instrument degradation corrections, for which there are fairly large corrections relative to the amount of solar cycle variability at some wavelengths. A summary of these satellite SSI measurements, which are primarily in the ultraviolet and only recently in the visible and near infrared, will be presented. Examining SSI trends using a new analysis technique is helping to identify some uncorrected instrumental trends, which once applied to the SSI trends has the potential to provide more accurate solar cycle variability results. This new technique examines the SSI trends at different levels of solar activity to provide long-term trends in a SSI record, and one of the most common components of these derived long-term trends is a downward trend that we attribute to being most likely from uncorrected instrument degradation. Examples of this analysis will be presented for some of the satellite SSI measurements to demonstrate this new technique and how it has potential to improve the understanding of solar cycle variability and to clarify the uncertainties of the trends.

Revisiting AVHRR Tropospheric Aerosol Trends Using Principal Component Analysis

NASA Technical Reports Server (NTRS)

Li, Jing; Carlson, Barbara E.; Lacis, Andrew A.

2014-01-01

The advanced very high resolution radiometer (AVHRR) satellite instruments provide a nearly 25 year continuous record of global aerosol properties over the ocean. It offers valuable insights into the long-term change in global aerosol loading. However, the AVHRR data record is heavily influenced by two volcanic eruptions, El Chichon on March 1982 and Mount Pinatubo on June 1991. The gradual decay of volcanic aerosols may last years after the eruption, which potentially masks the estimation of aerosol trends in the lower troposphere, especially those of anthropogenic origin. In this study, we show that a principal component analysis approach effectively captures the bulk of the spatial and temporal variability of volcanic aerosols into a single mode. The spatial pattern and time series of this mode provide a good match to the global distribution and decay of volcanic aerosols. We further reconstruct the data set by removing the volcanic aerosol component and reestimate the global and regional aerosol trends. Globally, the reconstructed data set reveals an increase of aerosol optical depth from 1985 to 1990 and decreasing trend from 1994 to 2006. Regionally, in the 1980s, positive trends are observed over the North Atlantic and North Arabian Sea, while negative tendencies are present off the West African coast and North Pacific. During the 1994 to 2006 period, the Gulf of Mexico, North Atlantic close to Europe, and North Africa exhibit negative trends, while the coastal regions of East and South Asia, the Sahel region, and South America show positive trends.

Nordic Sea Level - Analysis of PSMSL RLR Tide Gauge data

NASA Astrophysics Data System (ADS)

Knudsen, Per; Andersen, Ole

2015-04-01

Tide gauge data from the Nordic region covering a period of time from 1920 to 2000 are evaluated. 63 stations having RLR data for at least 40 years have been used. Each tide gauge data record was averaged to annual averages after the monthly average seasonal anomalies were removed. Some stations lack data, especially before around 1950. Hence, to compute representative sea level trends for the 1920-2000 period a procedure for filling in estimated sea level values in the voids, is needed. To fill in voids in the tide gauge data records a reconstruction method was applied that utilizes EOF.s in an iterative manner. Subsequently the trends were computed. The estimated trends range from about -8 mm/year to 2 mm/year reflecting both post-glacial uplift and sea level rise. An evaluation of the first EOFs show that the first EOF clearly describes the trends in the time series. EOF #2 and #3 describe differences in the inter-annual sea level variability with-in the Baltic Sea and differences between the Baltic and the North Atlantic / Norwegian seas, respectively.

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

Ghosh, Subimal; Das, Debasish; Kao, Shih-Chieh

Recent studies disagree on how rainfall extremes over India have changed in space and time over the past half century, as well as on whether the changes observed are due to global warming or regional urbanization. Although a uniform and consistent decrease in moderate rainfall has been reported, a lack of agreement about trends in heavy rainfall may be due in part to differences in the characterization and spatial averaging of extremes. Here we use extreme value theory to examine trends in Indian rainfall over the past half century in the context of long-term, low-frequency variability.We show that when generalizedmore » extreme value theory is applied to annual maximum rainfall over India, no statistically significant spatially uniform trends are observed, in agreement with previous studies using different approaches. Furthermore, our space time regression analysis of the return levels points to increasing spatial variability of rainfall extremes over India. Our findings highlight the need for systematic examination of global versus regional drivers of trends in Indian rainfall extremes, and may help to inform flood hazard preparedness and water resource management in the region.« less

Variability of Solar Radiation under Cloud-Free Skies in China: The Role of Aerosols

NASA Technical Reports Server (NTRS)

Qian, Yun; Wang, Weiguo; Leung, L. ruby; Kaiser, Dale P.

2007-01-01

In this study, we analyzed long-term surface global and diffuse solar radiation, aerosol single scattering albedo (SSA), and relative humidity (RH) from China. Our analysis reveals that much of China experienced significant decreases in global solar radiation (GSR) and increases in diffuse solar radiation under cloud-free skies between the 1960s and 1980s. With RH and aerosol SSA being rather constant during that time period, we suggest that the increasing aerosol loading from emission of pollutants is responsible for the observed reduced GSR and increased diffuse radiation in cloud-free skies. Although pollutant emissions continue to increase after the 1980s, the increment of aerosol SSA since 1980s can partly explain the transition of GSR from a decreasing trend to no apparent trend around that time. Preliminary analysis is also provided on the potential role of RH in affecting the global and diffuse solar radiation reaching the earth surface.

Understanding the Changes to Biomass Surface Characteristics after Ammonia and Organosolv Pretreatments by Using Time-of-Flight Secondary-Ion Mass Spectrometry (TOF-SIMS)

DOE PAGES

Tolbert, Allison K.; Yoo, Chang Geun; Ragauskas, Arthur J.

2017-03-20

Surface characteristic changes to poplar after ammonia and organosolv pretreatments were investigated by means of time-of-flight secondary-ion mass spectrometry (TOF-SIMS) analysis. Whereas normalized total polysaccharides and lignin contents on the surface differed from bulk chemical compositions, the surface cellulose ions detected by TOF-SIMS showed the same value trend as the cellulose content in the biomass. In addition, the lignin syringyl/guaiacyl ratio according to TOF-SIMS results showed the same trend as the ratio measured by means of NMR spectroscopic analysis, even though the ratio scales for each method were different. A similar correlation was determined between the surface cellulose and glucosemore » release after enzymatic hydrolysis. Lastly, these results demonstrate that surface characterization using TOF-SIMS can provide important information about the effects of pretreatment on biomass properties and its hydrolysis.« less

Analysis of new workers' compensation claims in the Department of Defense civilian workforce, 2000-2012.

PubMed

Nelson, Cameron J L; Bigley, Daniel P; Mallon, Timothy M

2015-03-01

This study of Department of Defense (DoD) civilian employees Workers' Compensation (WC) claims for chargeback year 2000 through 2012 aimed to analyze the frequency, rates, and costs of WC claims representing 5% of the DoD annual personnel budget. A multiyear cross-sectional study of WC claims data identified the top five most frequent causes, natures, and anatomical sites; changes in frequency, worker age, costs, and time were evaluated for trends. The annual frequency and rate of new DoD WC claims decreased over time, whereas costs per new claim have increased. New claim frequencies, rates, and costs aggregated in older age groups. The increasing trend in costs of each claim and the overall program costs presents a need for case management. Analysis of WC claims data is necessary to help target injury prevention efforts and reduce program costs.

Understanding the Changes to Biomass Surface Characteristics after Ammonia and Organosolv Pretreatments by Using Time-of-Flight Secondary-Ion Mass Spectrometry (TOF-SIMS)

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

Tolbert, Allison K.; Yoo, Chang Geun; Ragauskas, Arthur J.

Surface characteristic changes to poplar after ammonia and organosolv pretreatments were investigated by means of time-of-flight secondary-ion mass spectrometry (TOF-SIMS) analysis. Whereas normalized total polysaccharides and lignin contents on the surface differed from bulk chemical compositions, the surface cellulose ions detected by TOF-SIMS showed the same value trend as the cellulose content in the biomass. In addition, the lignin syringyl/guaiacyl ratio according to TOF-SIMS results showed the same trend as the ratio measured by means of NMR spectroscopic analysis, even though the ratio scales for each method were different. A similar correlation was determined between the surface cellulose and glucosemore » release after enzymatic hydrolysis. Lastly, these results demonstrate that surface characterization using TOF-SIMS can provide important information about the effects of pretreatment on biomass properties and its hydrolysis.« less

Reduction in outpatient antibiotic sales for pre-school children: interrupted time series analysis of weekly antibiotic sales data in Sweden 1992-2002.

PubMed

Högberg, Liselotte; Oke, Thimothy; Geli, Patricia; Lundborg, Cecilia Stålsby; Cars, Otto; Ekdahl, Karl

2005-07-01

The aim of this study was to use detailed weekly data on outpatient antibiotic sales for pre-school children in Sweden to test for the significance of trends during 1992-2002. We also report on the special features found in weekly antibiotic data, and how the interrupted time series (ITS) design can adjust for this. Weekly data on the total number of dispensed outpatient antibiotic prescriptions to pre-school children were studied, as well as the individual subgroups commonly used to treat respiratory tract infections in children: narrow-spectrum penicillins, broad-spectrum penicillins and macrolides. In parallel, monthly data of paracetamol sales of paediatric dosages were analysed to reflect trends in symptomatic treatment. An ITS model controlling for seasonality and autocorrelation was used to examine the datasets for significant level and trend shifts. A significant increase in mean and change in level could be found in the total antibiotic data in 1997, also reflected in broad-spectrum penicillin data where a similar trend break occurred in 1996. For macrolides, a trend break with a decrease in mean was noted in 1996, but no trend breaks were found in narrow-spectrum penicillin data. In contrast to the general decreasing trends in antibiotic sales, the yearly over-the-counter sales of paracetamol in paediatric preparations increased during the same period, with no identified trend breaks. The overall decrease in antibiotic sales and increase in paediatric paracetamol sales might suggest that symptomatic treatment in the home has increased, as antibiotics are less commonly prescribed.

The Relationship of Housing and Population Health: A 30-Year Retrospective Analysis

PubMed Central

Jacobs, David E.; Wilson, Jonathan; Dixon, Sherry L.; Smith, Janet; Evens, Anne

2009-01-01

Objective We analyzed the relationship between health status and housing quality over time. Methods We combined data from two nationally representative longitudinal surveys of the U.S. population and its housing, the National Health and Nutrition Examination Survey and the American Housing Survey, respectively. We identified housing and health trends from approximately 1970 to 2000, after excluding those trends for which data were missing or where we found no plausible association or change in trend. Results Changes in housing include construction type, proportion of rental versus home ownership, age, density, size, moisture, pests, broken windows, ventilation and air conditioning, and water leaks. Changes in health measures include asthma, respiratory illness, obesity and diabetes, and lead poisoning, among others. The results suggest ecologic trends in childhood lead poisoning follow housing age, water leaks, and ventilation; asthma follows ventilation, windows, and age; overweight trends follow ventilation; blood pressure trends follow community measures; and health disparities have not changed greatly. Conclusions Housing trends are consistent with certain health trends over time. Future national longitudinal surveys should include health, housing, and community metrics within a single integrated design, instead of separate surveys, in order to develop reliable indicators of how housing changes affect population health and how to best target resources. Little progress has been made in reducing the health and housing disparities of disadvantaged groups, with the notable exception of childhood lead poisoning caused by exposure to lead-based paint hazards. Use of these and other data sets to create reliable integrated indicators of health and housing quality are needed. PMID:19440499

Long-term trends in sunshine duration and its association with schizophrenia birth rates and age at first registration--data from Australia and the Netherlands.

PubMed

McGrath, John; Selten, Jean-Paul; Chant, David

2002-04-01

Based on the well-described excess of schizophrenia births in winter and spring, we hypothesised that individuals with schizophrenia (a) would be more likely to be born during periods of decreased perinatal sunshine, and (b) those born during periods of less sunshine would have an earlier age of first registration. We undertook an ecological analysis of long-term trends in perinatal sunshine duration and schizophrenia birth rates based on two mental health registers (Queensland, Australia n=6630; The Netherlands n=24,474). For each of the 480 months between 1931 and 1970, the agreement between slopes of the trends in psychosis and long-term sunshine duration series were assessed. Age at first registration was assessed by quartiles of long-term trends in perinatal sunshine duration. Males and females were assessed separately. Both the Dutch and Australian data showed a statistically significant association between falling long-term trends in sunshine duration around the time of birth and rising schizophrenia birth rates for males only. In both the Dutch and Australian data there were significant associations between earlier age of first registration and reduced long-term trends in sunshine duration around the time of birth for both males and females. A measure of long-term trends in perinatal sunshine duration was associated with two epidemiological features of schizophrenia in two separate data sets. Exposures related to sunshine duration warrant further consideration in schizophrenia research.

Temporal change and its spatial variety on land surface temperature and land use changes in the Red River Delta, Vietnam, using MODIS time-series imagery.

PubMed

Van Nguyen, On; Kawamura, Kensuke; Trong, Dung Phan; Gong, Zhe; Suwandana, Endan

2015-07-01

Temporal changes in the land surface temperature (LST) in urbanization areas are important for studying an urban heat island (UHI) and regional climate change. This study examined the LST trends under different land use categories in the Red River Delta, Vietnam, using the Moderate Resolution Imaging Spectroradiometer (MODIS) LST product (MOD11A2) and land cover type product (MCD12Q1) for 11 years (2002-2012). Smoothened time-series MODIS LST data were reconstructed by the Harmonic Analysis of Time Series (HANTS) algorithm. The reconstructed LST (maximum and minimum temperatures) was assessed using the hourly air temperature dataset in two land-based meteorological stations provided by the National Climatic Data Center (NCDC). Significant correlation was obtained between MODIS LST and the air temperature for the daytime (R (2) = 0.73, root mean square error [RMSE] = 1.66 °C) and night time (R (2) = 0.84, RMSE = 1.79 °C). Statistical analysis also showed that LST trends vary strongly depending on the land cover type. Forest, wetland, and cropland had a slight tendency to decline, whereas cropland and urban had sharper increases. In urbanized areas, these increasing trends are even more obvious. This is undeniable evidence of the negative impact of urbanization on a surface urban heat island (SUHI) and global warming.

Models for forecasting hospital bed requirements in the acute sector.

PubMed Central

Farmer, R D; Emami, J

1990-01-01

STUDY OBJECTIVE--The aim was to evaluate the current approach to forecasting hospital bed requirements. DESIGN--The study was a time series and regression analysis. The time series for mean duration of stay for general surgery in the age group 15-44 years (1969-1982) was used in the evaluation of different methods of forecasting future values of mean duration of stay and its subsequent use in the formation of hospital bed requirements. RESULTS--It has been suggested that the simple trend fitting approach suffers from model specification error and imposes unjustified restrictions on the data. Time series approach (Box-Jenkins method) was shown to be a more appropriate way of modelling the data. CONCLUSION--The simple trend fitting approach is inferior to the time series approach in modelling hospital bed requirements. PMID:2277253

The Trend-in-trend Research Design for Causal Inference.

PubMed

Ji, Xinyao; Small, Dylan S; Leonard, Charles E; Hennessy, Sean

2017-07-01

Cohort studies can be biased by unmeasured confounding. We propose a hybrid ecologic-epidemiologic design called the trend-in-trend design, which requires a strong time trend in exposure, but is unbiased unless there are unmeasured factors affecting outcome for which there are time trends in prevalence that are correlated with time trends in exposure across strata with different exposure trends. Thus, the conditions under which the trend-in-trend study is biased are a subset of those under which a cohort study is biased. The trend-in-trend design first divides the study population into strata based on the cumulative probability of exposure given covariates, which effectively stratifies on time trend in exposure, provided there is a trend. Next, a covariates-free maximum likelihood model estimates the odds ratio (OR) using data on exposure prevalence and outcome frequency within cumulative probability of exposure strata, across multiple periods. In simulations, the trend-in-trend design produced ORs with negligible bias in the presence of unmeasured confounding. In empiric applications, trend-in-trend reproduced the known positive association between rofecoxib and myocardial infarction (observed OR: 1.2, 95% confidence interval: 1.1, 1.4), and known null associations between rofecoxib and severe hypoglycemia (OR = 1.1 [0.92, 1.3]) and nonvertebral fracture (OR = 0.84 [0.64, 1.1]). The trend-in-trend method may be useful in settings where there is a strong time trend in exposure, such as a newly approved drug or other medical intervention. See video abstract at, http://links.lww.com/EDE/B178.

Spatial heterogeneity in statistical power to detect changes in lake area in Alaskan National Wildlife Refuges

USGS Publications Warehouse

Nicol, Samuel; Roach, Jennifer K.; Griffith, Brad

2013-01-01

Over the past 50 years, the number and size of high-latitude lakes have decreased throughout many regions; however, individual lake trends have been variable in direction and magnitude. This spatial heterogeneity in lake change makes statistical detection of temporal trends challenging, particularly in small analysis areas where weak trends are difficult to separate from inter- and intra-annual variability. Factors affecting trend detection include inherent variability, trend magnitude, and sample size. In this paper, we investigated how the statistical power to detect average linear trends in lake size of 0.5, 1.0 and 2.0 %/year was affected by the size of the analysis area and the number of years of monitoring in National Wildlife Refuges in Alaska. We estimated power for large (930–4,560 sq km) study areas within refuges and for 2.6, 12.9, and 25.9 sq km cells nested within study areas over temporal extents of 4–50 years. We found that: (1) trends in study areas could be detected within 5–15 years, (2) trends smaller than 2.0 %/year would take >50 years to detect in cells within study areas, and (3) there was substantial spatial variation in the time required to detect change among cells. Power was particularly low in the smallest cells which typically had the fewest lakes. Because small but ecologically meaningful trends may take decades to detect, early establishment of long-term monitoring will enhance power to detect change. Our results have broad applicability and our method is useful for any study involving change detection among variable spatial and temporal extents.

The effect of the late 2000s financial crisis on suicides in Spain: an interrupted time-series analysis.

PubMed

Lopez Bernal, James A; Gasparrini, Antonio; Artundo, Carlos M; McKee, Martin

2013-10-01

The current financial crisis is having a major impact on European economies, especially that of Spain. Past evidence suggests that adverse macro-economic conditions exacerbate mental illness, but evidence from the current crisis is limited. This study analyses the association between the financial crisis and suicide rates in Spain. An interrupted time-series analysis of national suicides data between 2005 and 2010 was used to establish whether there has been any deviation in the underlying trend in suicide rates associated with the financial crisis. Segmented regression with a seasonally adjusted quasi-Poisson model was used for the analysis. Stratified analyses were performed to establish whether the effect of the crisis on suicides varied by region, sex and age group. The mean monthly suicide rate in Spain during the study period was 0.61 per 100 000 with an underlying trend of a 0.3% decrease per month. We found an 8.0% increase in the suicide rate above this underlying trend since the financial crisis (95% CI: 1.009-1.156; P = 0.03); this was robust to sensitivity analysis. A control analysis showed no change in deaths from accidental falls associated with the crisis. Stratified analyses suggested that the association between the crisis and suicide rates is greatest in the Mediterranean and Northern areas, in males and amongst those of working age. The financial crisis in Spain has been associated with a relative increase in suicides. Males and those of working age may be at particular risk of suicide associated with the crisis and may benefit from targeted interventions.

Variability of rainfall over Lake Kariba catchment area in the Zambezi river basin, Zimbabwe

NASA Astrophysics Data System (ADS)

Muchuru, Shepherd; Botai, Joel O.; Botai, Christina M.; Landman, Willem A.; Adeola, Abiodun M.

2016-04-01

In this study, average monthly and annual rainfall totals recorded for the period 1970 to 2010 from a network of 13 stations across the Lake Kariba catchment area of the Zambezi river basin were analyzed in order to characterize the spatial-temporal variability of rainfall across the catchment area. In the analysis, the data were subjected to intervention and homogeneity analysis using the Cumulative Summation (CUSUM) technique and step change analysis using rank-sum test. Furthermore, rainfall variability was characterized by trend analysis using the non-parametric Mann-Kendall statistic. Additionally, the rainfall series were decomposed and the spectral characteristics derived using Cross Wavelet Transform (CWT) and Wavelet Coherence (WC) analysis. The advantage of using the wavelet-based parameters is that they vary in time and can therefore be used to quantitatively detect time-scale-dependent correlations and phase shifts between rainfall time series at various localized time-frequency scales. The annual and seasonal rainfall series were homogeneous and demonstrated no apparent significant shifts. According to the inhomogeneity classification, the rainfall series recorded across the Lake Kariba catchment area belonged to category A (useful) and B (doubtful), i.e., there were zero to one and two absolute tests rejecting the null hypothesis (at 5 % significance level), respectively. Lastly, the long-term variability of the rainfall series across the Lake Kariba catchment area exhibited non-significant positive and negative trends with coherent oscillatory modes that are constantly locked in phase in the Morlet wavelet space.

Providing long-term trend and gravimetric factor at Chandler period from superconducting gravimeter records by using Singular Spectrum Analysis along with its multivariate extension

NASA Astrophysics Data System (ADS)

Gruszczynska, M.; Rosat, S.; Klos, A.; Bogusz, J.

2017-12-01

In this study, Singular Spectrum Analysis (SSA) along with its multivariate extension MSSA (Multichannel SSA) were used to estimate long-term trend and gravimetric factor at the Chandler wobble frequency from superconducting gravimeter (SG) records. We have used data from seven stations located worldwide and contributing to the International Geodynamics and Earth Tides Service (IGETS). The timespan ranged from 15 to 19 years. Before applying SSA and MSSA, we had removed local tides, atmospheric (ECMWF data), hydrological (MERRA2 products) loadings and non-tidal ocean loading (ECCO2 products) effects. In the first part of analysis, we used the SSA approach in order to estimate the long-term trends from SG observations. We use the technique based on the classical Karhunen-Loève spectral decomposition of time series into long-term trend, oscillations and noise. In the second part, we present the determination of common time-varying pole tide (annual and Chandler wobble) to estimate gravimetric factor from SG time series using the MSSA approach. The presented method takes advantage over traditional methods like Least Squares Estimation by determining common modes of variability which reflect common geophysical field. We adopted a 6-year lag-window as the optimal length to extract common seasonal signals and the Chandler components of the Earth polar motion. The signals characterized by annual and Chandler wobble account for approximately 62% of the total variance of residual SG data. Then, we estimated the amplitude factors and phase lags of Chandler wobble with respect to the IERS (International Earth Rotation and Reference Systems Service) polar motion observations. The resulting gravimetric factors at the Chandler Wobble period are finally compared with previously estimates. A robust estimate of the gravimetric Earth response to the Chandlerian component of the polar motion is required to better constrain the mantle anelasticity at this frequency and hence the attenuation models of the Earth interior.

A comprehensive analysis of high-magnitude streamflow and trends in the Central Valley, California

NASA Astrophysics Data System (ADS)

Kocis, T. N.; Dahlke, H. E.

2017-12-01

California's climate is characterized by the largest precipitation and streamflow variability observed within the conterminous US. This, combined with chronic groundwater overdraft of 0.6-3.5 km3 yr-1, creates the need to identify additional surface water sources available for groundwater recharge using methods such as agricultural groundwater banking, aquifer storage and recovery, and spreading basins. High-magnitude streamflow, i.e. flow above the 90th percentile, that exceeds environmental flow requirements and current surface water allocations under California water rights, could be a viable source of surface water for groundwater banking. Here, we present a comprehensive analysis of the magnitude, frequency, duration and timing of high-magnitude streamflow (HMF "metrics") over multiple time periods for 93 stream gauges covering the Sacramento, San Joaquin and Tulare basins in California. In addition, we present trend analyses conducted on the same dataset and all HMF metrics using generalized additive models, the Mann-Kendall trend test, and the Signal to Noise Ratio test. The results of the comprehensive analysis show, in short, that in an average year with HMF approximately 3.2 km3 of high-magnitude flow is exported from the entire Central Valley to the Sacramento-San Joaquin Delta, often at times when environmental flow requirements of the Delta and major rivers are exceeded. High-magnitude flow occurs, on average, during 7 and 4.7 out of 10 years in the Sacramento River and the San Joaquin-Tulare Basins, respectively, from just a few storm events (5-7 1-day peak events) lasting for a total of 25-30 days between November and April. Preliminary trend tests suggest that all HMF metrics show limited change over the last 50 years. As a whole, the results suggest that there is sufficient unmanaged surface water physically available to mitigate long-term groundwater overdraft in the Central Valley.

Associations between dietary patterns, physical activity (leisure-time and occupational) and television viewing in middle-aged French adults.

PubMed

Charreire, Hélène; Kesse-Guyot, Emmanuelle; Bertrais, Sandrine; Simon, Chantal; Chaix, Basile; Weber, Christiane; Touvier, Mathilde; Galan, Pilar; Hercberg, Serge; Oppert, Jean-Michel

2011-03-01

Diet and physical activity are considered to be major components of a healthy lifestyle. However, few studies have examined in detail the relationships between specific types of physical activity, sedentary behaviour and diet in adults. The objective of the present study was to assess differential relationships between dietary patterns, leisure-time and occupational physical activities and time spent watching television (TV), as an indicator of sedentary behaviour, in middle-aged French subjects. We performed a cross-sectional analysis using data from 1359 participants in the SUpplémentation en VItamines et Minéraux AntioXydants study, who completed a detailed physical activity questionnaire and at least six 24 h dietary records. Sex-specific dietary patterns were derived using factor analysis; their relationships with leisure-time and occupational physical activities and TV viewing were assessed using ANCOVA, after adjustment for age, educational level and smoking status. Three dietary patterns were identified in each sex. After adjustment for potential confounders, leisure-time physical activity was positively associated with a 'healthy' food pattern in both men (P for trend < 0·01) and women (P for trend < 0·03) and negatively associated with an 'alcohol/meat' pattern in men (P for trend < 0·01). TV viewing was positively associated with a 'convenience' pattern in men and with a 'alcohol-appetiser' pattern in women. In conclusion, identification of relationships between dietary patterns, physical activity and sedentary behaviour can enable identification of different types of lifestyle and should help to target at-risk groups in nutrition prevention programmes.

Assessing and Evaluating Department of Defense Efforts to Inform, Influence, and Persuade: Work Example

DTIC Science & Technology

2017-01-01

reviewing and refining their initial objectives to ensure that these objectives are SMART: specific, measurable, achievable, relevant, and time -bound...should not conflate exposure and effectiveness where messaging is concerned, and they should aim to capture trends over time . Assessors should use...specific, measurable, achievable, relevant, and time -bound TAA target audience analysis TCO transnational criminal organization UN United Nations VEO

Multi-decade Measurements of the Long-Term Trends of Atmospheric Species by High-Spectral-Resolution Infrared Solar Absorption Spectroscopy

NASA Technical Reports Server (NTRS)

Rinsland, Curtis P.; Chiou, Linda; Goldman, Aaron; Hannigan, James W.

2010-01-01

Solar absorption spectra were recorded for the first time in 5 years with the McMath Fourier transform spectrometer at the US National solar Observatory on Kitt Peak in southern Arizona, USA (31.91 N latitude, 111.61 W longitude, 2.09 km altitude). The solar absorption spectra cover 750-1300 and 1850-5000 cm(sup -1) and were recorded on 20 days during March-June 2009. The measurements mark the continuation of a long-term record of atmospheric chemical composition measurements that have been used to quantify seasonal cycles and long-term trends of both tropospheric and stratospheric species from observations that began i 1977. Fits to the measured spectra have been performed, and they indicate the spectra obtained since return to operational status are nearly free of channeling and the instrument line shape function is well reproduced taking into account the measurement parameters. We report updated time series measurements of total columns for six atmospheric species and their analysis for seasonal cycles and long-term trends. An sn example, the time series fit shows a decrease in the annual increase rate i Montreal-Protocol-regulated chlorofluorocarbon CCL2F2 from 1.51 plus or minus 0.38% yr(sup -1) at the beginning of the time span to -1.54 plus or minus 1.28 yr(sup -1) at the end of the time span, 1 sigma, and hence provides evidence for the impact of those regulations on the trend.

Trends of brominated diphenyl ethers in fresh and archived Great Lakes fish (1979-2005)

USGS Publications Warehouse

Batterman, Stuart; Chernyak, Sergei; Gwynn, Erica; Cantonwine, David; Jia, Chunrong; Begnoche, Linda J.; Hickey, James P.

2007-01-01

While few environmental measurements of brominated diphenyl ethers (BDEs) were completed prior to the mid-1990s, analysis of appropriately archived samples might enable the determination of contaminant trends back to the introduction of these chemicals. In this paper, we first investigate the stability of BDEs in archived frozen and extracted fish samples, and then characterize trends of these chemicals in rainbow smelt (Osmerus mordax) and lake trout (Salvelinus namaycush) in each of the Great Lakes between 1979 and 2005. We focus on the four most common congeners (BDE-47, 100, 99 and 153) and use a change-point analysis to detect shifts in trends. Analyses of archived fish samples yielded precise BDE concentration measurements with only small losses (0.8% per year in frozen fish tissues, 2.2% per year in refrigerated extracts). Trends in fish from all Great Lakes showed large increases in BDE concentrations that started in the early to mid-1980s with fairly consistent doubling times (generally 2–4 years except in Lake Erie smelt where levels increased very slowly), though concentrations and trends show differences by congener, fish species and lake. The most recent data show that accumulation rates are slowing, and concentrations of penta- and hexa-congeners in trout from Lakes Ontario and Michigan and smelt from Lake Ontario started to decrease in the mid-1990s. Trends in smelt and trout are evolving somewhat differently, and trout concentrations in the five lakes are now ranked as Michigan > Superior = Ontario > Huron = Erie, and smelt concentrations as Michigan > Ontario > Huron > Superior > Erie. The analysis of properly archived samples permits the reconstruction of historical trends, congener distributions, biomagnification and other information that can aid the understanding and management of these contaminants.

Detecting drought and human-induced land degradation using time series trend analysis in Northeastern Brazil drylands

NASA Astrophysics Data System (ADS)

Mariano, D. A.; Costa dos Santos, C. A.; Wardlow, B.

2017-12-01

Land degradation (LD) is one of the most catastrophic outcomes of long-lasting drought events and anthropogenic activities. Assessing climate and human-induced impacts on land can provide information for decision makers to mitigate the effects associated to thereof. The Northeastern region of Brazil (NEB) is the most populous dryland on the planet, making it a highly vulnerable ecosystem especially when considering the lingering drought that started in 2012. The present work consisted on detecting trends in biomass [gross primary productivity (GPP)] and albedo anomalies as indicators of land degradation in NEB. Both GPP and albedo data were derived from MODIS/Terra sensor at 8-day temporal and 500m spatial resolutions. For precipitation z-scores, we relied on CHIRPS-v2 10-day temporal and 5km spatial resolution data. For detecting trends, we applied linear regressions on time series of MODIS GPP and albedo images. Trend analysis was performed for the periods ranging from 2002-2012 (no severe droughts) and 2002-2016 (includes the last drought). The first analysis highlights the human-induced LD whereas the last detected drought induced LD. About 4.5% of the area undergone human-induced degradation whereas drought was responsible for 13%, although, not mutually exclusive. As reported in the literature and official data, grazing intensification was the main driver for human-induced LD. GPP trends were more pronounced and had a stronger signal than albedo, thus, is considered more efficient on mapping LD. Finally, the effects of LD on evapotranspiration anomalies [evaporative stress index (ESI)] were assessed as a way to link it to the hydrological cycle. GPP and ET relations are very site-specific; thus, we found that these variables are highly correlated in regions where LD was intense. We conclude that, in fact, drought led to severe LD in NEB and, the degradation cycle has a positive feedback derived from ET reduction resulting in an increased net moisture deficit. The study warns of the desertification risk that NEB is facing and the need for the authorities to take action to stop these trends.

Observed changes in relative humidity and dew point temperature in coastal regions of Iran

NASA Astrophysics Data System (ADS)

Hosseinzadeh Talaee, P.; Sabziparvar, A. A.; Tabari, Hossein

2012-12-01

The analysis of trends in hydroclimatic parameters and assessment of their statistical significance have recently received a great concern to clarify whether or not there is an obvious climate change. In the current study, parametric linear regression and nonparametric Mann-Kendall tests were applied for detecting annual and seasonal trends in the relative humidity (RH) and dew point temperature ( T dew) time series at ten coastal weather stations in Iran during 1966-2005. The serial structure of the data was considered, and the significant serial correlations were eliminated using the trend-free pre-whitening method. The results showed that annual RH increased by 1.03 and 0.28 %/decade at the northern and southern coastal regions of the country, respectively, while annual T dew increased by 0.29 and 0.15°C per decade at the northern and southern regions, respectively. The significant trends were frequent in the T dew series, but they were observed only at 2 out of the 50 RH series. The results showed that the difference between the results of the parametric and nonparametric tests was small, although the parametric test detected larger significant trends in the RH and T dew time series. Furthermore, the differences between the results of the trend tests were not related to the normality of the statistical distribution.

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

NASA Astrophysics Data System (ADS)

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.

Temporal trends in postseroconversion CD4 cell count and HIV load: the Concerted Action on Seroconversion to AIDS and Death in Europe Collaboration, 1985-2002.

PubMed

Dorrucci, Maria; Rezza, Giovanni; Porter, Kholoud; Phillips, Andrew

2007-02-15

To determine whether early postseroconversion CD4 cell counts and human immunodeficiency virus (HIV) loads have changed over time. Our analysis was based on 22 cohorts of people with known dates of seroconversion from Europe, Australia, and Canada (Concerted Action on Seroconversion to AIDS and Death in Europe Collaboration). We focused on individuals seroconverting between 1985 and 2002 who had the first CD4 cell count (n=3687) or HIV load (n=1584) measured within 2 years of seroconversion and before antiretroviral use. Linear regression models were used to assess time trends in postseroconversion CD4 cell count and HIV load. Trends in time to key thresholds were also assessed, using survival analysis. The overall median initial CD4 cell count was 570 cells/ microL (interquartile range [IQR], 413-780 cells/ microL). The median initial HIV load was 35,542 copies/mL (IQR, 7600-153,050 copies/mL; on log(10) scale, 3.9-5.2 log(10) copies/mL). The postseroconversion CD4 cell count changed by an average of -6.33 cells/ microL/year (95% confidence interval [CI], -8.47 to -4.20 cells/ microL/year; P<.001), whereas an increase was observed in log(10) HIV load (+0.044 log(10) copies/mL/year; 95% CI, +0.034 to +0.053 log(10) copies/mL/year). These trends remained after adjusting for potential confounders. The probability of progressing to a CD4 cell count of <500 cells/ microL by 24 months from seroconversion increased from 0.66 (95% CI, 0.63-0.69) for individuals who seroconverted before 1991 to 0.80 (95% CI, 0.75-0.84) for those who seroconverted during 1999-2002. These data suggest that, in Europe, there has been a trend of decrease in the early CD4 cell count and of increase in the early HIV load. Additional research will be necessary to determine whether similar trends exist in other geographical areas.

Increasing prominence of implantology research: a chronological trend analysis of 100 top-cited articles in periodontal journals.

PubMed

Chiang, Ho-Sheng; Huang, Ren-Yeong; Weng, Pei-Wei; Mau, Lian-Ping; Su, Chi-Chun; Tsai, Yi-Wen Cathy; Wu, Yu-Chiao; Chung, Chi-Hsiang; Shieh, Yi-Shing; Cheng, Wan-Chien

To identify 100 top-cited articles published in periodontal journals and analyse the research trends by using citation analysis. 100 top-cited articles published in periodontal journals were retrieved by searching the database of the ISI Web of Science and Journal Citation reports. For each article, the following principal bibliometric parameters: authorship, geographic and institute origin, manuscript type, study design, scope of study, and citation count of each time period were analysed from 1965 to 2015. The identified 100 top-cited articles were retrieved from five periodontal journals and citation counts were recorded between 262 and 1,693 times. For the institute of origin, the most productive institute, in terms of the number of 100 top-cited articles published, was the University of Gothenburg (Sweden) (n = 19), followed by the Forsyth Dental Center (USA) (n = 15). Most manuscripts were original research (n = 74), and the inflammatory periodontal disease (n = 59) was the most frequent topic studied. Interestingly, the trend of increase average citation reached significance for implantology (β = 26.75, P = 0.003) and systemic interactions (β = 29.83, P = 0.005), but not for inflammatory disease (β = -10.30, P = 0.248) and tissue regeneration (β = 9.04, P = 0.081). By using multivariable linear regression in a generalised linear model, suitable published journal (Journal of Clinical Periodontology), geographic regions (Europe), more intense international collaboration, adequate manuscript type (review article) and study design (systematic review) could be attributed to escalating average citation counts in implantology (all P < 0.05). However, for systemic interactions, only geographic region and study design were significantly associated with the increasing citation trend. These principal bibliometric characteristics revealed escalated trends in average citation count in implantology throughout time. Conflict-of-interest statement The authors have stated explicitly that there are no conflicts of interest in connection with this article. The study was self-funded by the authors and their institution.

Predictors of Suicide and Accident Death in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

PubMed Central

Schoenbaum, Michael; Kessler, Ronald C.; Gilman, Stephen E.; Colpe, Lisa J.; Heeringa, Steven G.; Stein, Murray B.; Ursano, Robert J.; Cox, Kenneth L.

2014-01-01

IMPORTANCE The Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) is a multicomponent study designed to generate actionable recommendations to reduce Army suicides and increase knowledge of risk and resilience factors for suicidality. OBJECTIVES To present data on prevalence, trends, and basic sociodemographic and Army experience correlates of suicides and accident deaths among active duty Regular Army soldiers between January 1, 2004, and December 31, 2009, and thereby establish a foundation for future Army STARRS investigations. DESIGN, SETTING, AND PARTICIPANTS Analysis of trends and predictors of suicide and accident deaths using Army and Department of Defense administrative data systems. Participants were all members of the US Regular Army serving at any time between 2004 and 2009. MAIN OUTCOMES AND MEASURES Death by suicide or accident during active Army service. RESULTS The suicide rate rose between 2004 and 2009 among never deployed and currently and previously deployed Regular Army soldiers. The accident death rate fell sharply among currently deployed soldiers, remained constant among the previously deployed, and trended upward among the never deployed. Increased suicide risk was associated with being a man (or a woman during deployment), white race/ethnicity, junior enlisted rank, recent demotion, and current or previous deployment. Sociodemographic and Army experience predictors were generally similar for suicides and accident deaths. Time trends in these predictors and in the Army’s increased use of accession waivers (which relaxed some qualifications for new soldiers) do not explain the rise in Army suicides. CONCLUSIONS AND RELEVANCE Predictors of Army suicides were largely similar to those reported elsewhere for civilians, although some predictors distinct to Army service emerged that deserve more in-depth analysis. The existence of a time trend in suicide risk among never-deployed soldiers argues indirectly against the view that exposure to combat-related trauma is the exclusive cause of the increase in Army suicides. PMID:24590048

Effects of advanced treatment of municipal wastewater on the White River near Indianapolis, Indiana; trends in water quality, 1978-86

USGS Publications Warehouse

Crawford, Charles G.; Wangsness, David J.

1993-01-01

The City of Indianapolis has constructed state-of-the-art advanced municipal wastewater-treatment systems to enlarge and upgrade the existing secondary-treatment processes at its Belmont and Southport treatment plants. These new advanced-wastewater-treatment plants became operational in 1983. A nonparametric statistical procedure--a modified form of the Wilcoxon-Mann-Whitney rank-sum test--was used to test for trends in time-series water-quality data from four sites on the White River and from the Belmont and Southport wastewater-treatment plants. Time-series data representative of pre-advanced- (1978-1980) and post-advanced- (1983--86) wastewater-treatment conditions were tested for trends, and the results indicate substantial changes in water quality of treated effluent and of the White River downstream from Indianapolis after implementation of advanced wastewater treatment. Water quality from 1981 through 1982 was highly variable due to plant construction. Therefore, this time period was excluded from the analysis. Water quality at sample sites located upstream from the wastewater-treatment plants was relatively constant during the period of study (1978-86). Analysis of data from the two plants and downstream from the plants indicates statistically significant decreasing trends in effluent concentrations of total ammonia, 5-day biochemical-oxygen demand, fecal-coliform bacteria, total phosphate, and total solids at all sites where sufficient data were available for testing. Because of in-plant nitrification, increases in nitrate concentration were statistically significant in the two plants and in the White River. The decrease in ammonia concentrations and 5-day biochemical-oxygen demand in the White River resulted in a statistically significant increasing trend in dissolved-oxygen concentration in the river because of reduced oxygen demand for nitrification and biochemical oxidation processes. Following implementation of advanced wastewater treatment, the number of river-quality samples that failed to meet the water-quality standards for ammonia and dissolved oxygen that apply to the White River decreased substantially.

Changing stream temperatures in a changing world: evaluating spatio-temporal patterns and trends across the eastern US

NASA Astrophysics Data System (ADS)

Kelleher, C.; Archfield, S. A.

2016-12-01

Stream temperatures drive biogeochemical processes and influence ecosystem health and extent, with patterns of stream temperature arising from complex interactions between climate, land cover, and in-stream diversions and dams. While each of these individual drivers may have well-understood implications for changing stream temperatures, considering the concomitant impacts of these drivers along the stream network is much more difficult. This is true especially for the eastern United States, where downstream temperature integrates many different upstream impacts. To begin to decipher the influence of these different drivers on changing stream temperatures and how these impacts may manifest through time, we examined trends for 66 sites with continuous stream temperature measurements across the eastern United States. Stream temperature records were summarized as daily mean, maximum, and mimimum values, and sites consisting of 15 or more years of data were selected for analysis. While annual stream temperatures at 53 locations were warming, a few sites on larger rivers (n = 13) have been cooling. To explore the timing of these changes as well as their implications for aquatic species, we calculated trends for seasonal extremes (average of the five warmest and coolest daily stream temperatures) during spring, summer, and fall. Interestingly, while some streams displayed strong warming trends in peak summer temperatures (n = 43), many streams also displayed cooling trends (n = 23). We also found that peak stream temperatures were warming faster in fall than in summer for many locations (n = 36). Results of this analysis show that warming (and cooling) happens at different times in different places, as a function of climate and anthropogenic impacts. Finally, we explore potential drivers of these different patterns, to determine the relative impacts of climate, land cover, and in-stream water diversions on stream temperature change. Given that the number of regulated stream miles is only increasing, improving our understanding of linkages between landscape drivers and stream temperature variation may have important outcomes for river management in a changing world.

Water-quality trend analysis and sampling design for streams in the Red River of the North Basin, Minnesota, North Dakota, and South Dakota, 1970-2001

USGS Publications Warehouse

Vecchia, Aldo V.

2005-01-01

The Bureau of Reclamation is considering several alternatives to meet the future municipal, rural, and industrial water-supply needs in the Red River of the North (Red River) Basin, and an environmental impact statement is being prepared to evaluate the potential effects of the various alternatives on the water quality and aquatic health in the basin in relation to the historical variability of streamflow and constituent concentration. Therefore, a water-quality trend analysis was needed to determine the amount of natural water-quality variability that can be expected to occur in the basin, to determine if significant water-quality changes have occurred as a result of human activities, to explore potential causal mechanisms for water-quality changes, and to establish a baseline from which to monitor future water-quality trends. This report presents the results of a study conducted by the U.S. Geological Survey, in cooperation with the Bureau of Reclamation, to analyze historical water-quality trends in two dissolved major ions, dissolved solids, three nutrients, and two dissolved trace metals for nine streamflow-gaging stations in the basin. Annual variability in streamflow in the Red River Basin was high during the trend-analysis period (1970-2001). The annual variability affects constituent concentrations in individual tributaries to the Red River and, in turn, affects constituent concentrations in the main stem of the Red River because of the relative streamflow contribution from the tributaries to the main stem. Therefore, an annual concentration anomaly, which is an estimate of the interannual variability in concentration that can be attributed to long-term variability in streamflow, was used to analyze annual streamflow-related variability in constituent concentrations. The concentration trend is an estimate of the long-term systematic changes in concentration that are unrelated to seasonal or long-term variability in streamflow. Concentrations that have both the seasonal and annual variability removed are called standardized concentrations. Numerous changes that could not be attributed to natural streamflow-related variability occurred in the standardized concentrations during the trend-analysis period. During various times from the late 1970's to the mid-1990's, significant increases occurred in standardized dissolved sulfate, dissolved chloride, and dissolved- solids concentrations for eight of the nine stations for which water-quality trends were analyzed. Significant increases also occurred from the early 1980's to the mid-1990's for standardized dissolved nitrite plus nitrate concentrations for the main-stem stations. The increasing concentrations for the main-stem stations indicate the upward trends may have been caused by human activities along the main stem of the Red River. Significant trends for standardized total ammonia plus organic nitrogen concentrations occurred for most stations. The fitted trends for standardized total phosphorus concentrations for one tributary station increased from the late 1970's to the early 1980's and decreased from the early 1980's to the mid-1990's. Small but insignificant increases occurred for two main-stem stations. No trends were detected for standardized dissolved iron or dissolved manganese concentrations. However, the combination of extreme high-frequency variability, few data, and the number of censored values may have disguised the streamflow-related variability for iron. The time-series model used to detect historical concentration trends also was used to evaluate sampling designs to monitor future water-quality trends. Various sampling designs were evaluated with regard to their sensitivity to detect both annual and seasonal trends during three 4-month seasons. A reasonable overall design for detecting trends for all stations and constituents consisted of eight samples per year, with monthly sampling from April to August and bimonthly sampling from October to February.

A comparison of estimators from self-controlled case series, case-crossover design, and sequence symmetry analysis for pharmacoepidemiological studies.

PubMed

Takeuchi, Yoshinori; Shinozaki, Tomohiro; Matsuyama, Yutaka

2018-01-08

Despite the frequent use of self-controlled methods in pharmacoepidemiological studies, the factors that may bias the estimates from these methods have not been adequately compared in real-world settings. Here, we comparatively examined the impact of a time-varying confounder and its interactions with time-invariant confounders, time trends in exposures and events, restrictions, and misspecification of risk period durations on the estimators from three self-controlled methods. This study analyzed self-controlled case series (SCCS), case-crossover (CCO) design, and sequence symmetry analysis (SSA) using simulated and actual electronic medical records datasets. We evaluated the performance of the three self-controlled methods in simulated cohorts for the following scenarios: 1) time-invariant confounding with interactions between the confounders, 2) time-invariant and time-varying confounding without interactions, 3) time-invariant and time-varying confounding with interactions among the confounders, 4) time trends in exposures and events, 5) restricted follow-up time based on event occurrence, and 6) patient restriction based on event history. The sensitivity of the estimators to misspecified risk period durations was also evaluated. As a case study, we applied these methods to evaluate the risk of macrolides on liver injury using electronic medical records. In the simulation analysis, time-varying confounding produced bias in the SCCS and CCO design estimates, which aggravated in the presence of interactions between the time-invariant and time-varying confounders. The SCCS estimates were biased by time trends in both exposures and events. Erroneously short risk periods introduced bias to the CCO design estimate, whereas erroneously long risk periods introduced bias to the estimates of all three methods. Restricting the follow-up time led to severe bias in the SSA estimates. The SCCS estimates were sensitive to patient restriction. The case study showed that although macrolide use was significantly associated with increased liver injury occurrence in all methods, the value of the estimates varied. The estimations of the three self-controlled methods depended on various underlying assumptions, and the violation of these assumptions may cause non-negligible bias in the resulting estimates. Pharmacoepidemiologists should select the appropriate self-controlled method based on how well the relevant key assumptions are satisfied with respect to the available data.

SWMPrats.net: A Web-Based Resource for Exploring SWMP ...

EPA Pesticide Factsheets

SWMPrats.net is a web-based resource that provides accessible approaches to using SWMP data. The website includes a user forum with instructional ‘Plots of the Month’; links to workshop content; and a description of the SWMPr data analysis package for R. Interactive “widgets” allow users to skip the boring parts of data analysis and get right to the fun: visualization and exploration! There are three widgets, each performing a different analysis: system-wide overviews, detailed temporal summaries of a single variable at a single site, and inter-comparisons between sites or variables through time. Users can visually explore system-wide trends in data using the Trends Map widget. For a more detailed analysis, users can create monthly and annual graphs of single variables and locations in the Summary Plot widget. Lastly, users can compare two variables or NERRS locations through time using the Aggregation widget. For all widgets, users can adjust the time period of interest. Plots and tables can also be downloaded for use in outreach, education, or further analysis. The tools and forums are meant to build a community of practice to move SWMP data analysis forward. All widgets will be demonstrated live at the poster session. This abstract is for a poster presentation at the 2016 annual meeting for the National Estuarine Research Reserve System, Nov. 13-18. We will describe our online web resources for the analysis and interpretation of monitoring da

Prophylaxis usage, bleeding rates, and joint outcomes of hemophilia, 1999 to 2010: a surveillance project

PubMed Central

Soucie, J. Michael; Gill, Joan Cox

2017-01-01

This analysis of the US Hemophilia Treatment Center Network and the Centers for Disease Control and Prevention surveillance registry assessed trends in prophylaxis use and its impact on key indicators of arthropathy across the life-span among participants with severe hemophilia A. Data on demographics, clinical characteristics, and outcomes were collected prospectively between 1999 and 2010 at annual clinical visits to 134 hemophilia treatment centers. Trends in treatment and outcomes were evaluated using cross-sectional and longitudinal analyses. Data analyzed included 26 614 visits for 6196 males; mean age at first registry visit was 17.7 years; and median was 14 (range, 2 to 69). During this time, prophylaxis use increased from 31% to 59% overall, and by 2010, 75% of children and youths <20 years were on prophylaxis. On cross-sectional analysis, bleeding rates decreased dramatically for the entire population (P < .001) in parallel with increased prophylaxis usage, possibly because frequent bleeders adopted prophylaxis. Joint bleeding decreased proportionately with prophylaxis (22%) and nonprophylaxis (23%), and target joints decreased more with prophylaxis (80% vs 61%). Joint, total, and target joint bleeding on prophylaxis were 33%, 41%, and 27%, respectively, compared with nonprophylaxis. On longitudinal analysis of individuals over time, prophylaxis predicted decreased bleeding at any age (P < .001), but only prophylaxis initiation prior to age 4 years and nonobesity predicted preservation of joint motion (P < .001 for each). Using a national registry, care providers in a specialized health care network for a rare disorder were able to detect and track trends in outcomes over time. PMID:28183693

Generic trending and analysis system

NASA Technical Reports Server (NTRS)

Keehan, Lori; Reese, Jay

1994-01-01

The Generic Trending and Analysis System (GTAS) is a generic spacecraft performance monitoring tool developed by NASA Code 511 and Loral Aerosys. It is designed to facilitate quick anomaly resolution and trend analysis. Traditionally, the job of off-line analysis has been performed using hardware and software systems developed for real-time spacecraft contacts; then, the systems were supplemented with a collection of tools developed by Flight Operations Team (FOT) members. Since the number of upcoming missions is increasing, NASA can no longer afford to operate in this manner. GTAS improves control center productivity and effectiveness because it provides a generic solution across multiple missions. Thus, GTAS eliminates the need for each individual mission to develop duplicate capabilities. It also allows for more sophisticated tools to be developed because it draws resources from several projects. In addition, the GTAS software system incorporates commercial off-the-shelf tools software (COTS) packages and reuses components of other NASA-developed systems wherever possible. GTAS has incorporated lessons learned from previous missions by involving the users early in the development process. GTAS users took a proactive role in requirements analysis, design, development, and testing. Because of user involvement, several special tools were designed and are now being developed. GTAS users expressed considerable interest in facilitating data collection for long term trending and analysis. As a result, GTAS provides easy access to large volumes of processed telemetry data directly in the control center. The GTAS archival and retrieval capabilities are supported by the integration of optical disk technology and a COTS relational database management system.

Time trends in lifetime incidence rates of first-time diagnosed anorexia nervosa and bulimia nervosa across 16 years in a Danish nationwide psychiatric registry study.

PubMed

Steinhausen, Hans-Christoph; Jensen, Christina Mohr

2015-11-01

To study recent time trends in the incidence of diagnosed anorexia nervosa (AN) and bulimia nervosa (BN) based on nationwide psychiatric register data. The Danish Psychiatric Central Research Registry was used to identify the incidence of diagnosed cases with AN and BN at the ages of 4-65 years from 1995 to 2010. Age- and sex-adjusted incidence rates per 100,000 person-years were calculated and were adjusted for time trends in the total number of people diagnosed in psychiatry. Time trends were analyzed using JoinPoint regression analysis. A total of N = 5,902 persons had a first-time incidence of AN, and a total of N = 5,113 had first-time incidence of BN. Incidence rates increased for AN from 6.4 to 12.6 per 100,000 person-years, and for BN from 6.3 to 7.2 per 100,000 person-years. In 2010, the male-to-female ratio was 1:8 for AN, and 1:20 for BN. There was an earlier onset for AN than for BN, and age at incidence decreased during the observation period for AN but not for BN. A sizeable part of the increasing incidence rates for AN and in particular, the younger AN age groups, could be attributed to an increase in the total number of N = 249,607 persons with first-time diagnoses in psychiatry. Incidence rates had increased slightly for AN, but were stable for BN across 16 years in this nationwide study and to a large extent were reflective of a general increase in diagnosed mental disorders. © 2015 Wiley Periodicals, Inc.

Trends in marriage and time spent single in sub-Saharan Africa: a comparative analysis of six population-based cohort studies and nine Demographic and Health Surveys.

PubMed

Marston, M; Slaymaker, E; Cremin, I; Floyd, S; McGrath, N; Kasamba, I; Lutalo, T; Nyirenda, M; Ndyanabo, A; Mupambireyi, Z; Zaba, B

2009-04-01

To describe trends in age at first sex (AFS), age at first marriage (AFM) and time spent single between events and to compare age-specific trends in marital status in six cohort studies. Cohort data from Uganda, Tanzania, South Africa, Zimbabwe and Malawi and Demographic and Health Survey (DHS) data from Uganda, Tanzania and Zimbabwe were analysed. Life table methods were used to calculate median AFS, AFM and time spent single. In each study, two surveys were chosen to compare marital status by age and identify changes over time. Median AFM was much higher in South Africa than in the other sites. Between the other populations there were considerable differences in median AFS and AFM (AFS 17-19 years for men and 16-19 years for women, AFM 21-24 years and 18-19 years, respectively, for the 1970-9 birth cohort). In all surveys, men reported a longer time spent single than women (median 4-7 years for men and 0-2 years for women). Median years spent single for women has increased, apart from in Manicaland. For men in Rakai it has decreased slightly over time but increased in Kisesa and Masaka. The DHS data showed similar trends to those in the cohort data. The age-specific proportion of married individuals has changed little over time. Median AFS, AFM and time spent single vary considerably among these populations. These three measures are underlying determinants of sexual risk and HIV infection, and they may partially explain the variation in HIV prevalence levels between these populations.

Trends in marriage and time spent single in sub-Saharan Africa: a comparative analysis of six population-based cohort studies and nine Demographic and Health Surveys

PubMed Central

Marston, M; Slaymaker, E; Cremin, I; Floyd, S; McGrath, N; Kasamba, I; Lutalo, T; Nyirenda, M; Ndyanabo, A; Mupambireyi, Z; Żaba, B

2009-01-01

Objectives: To describe trends in age at first sex (AFS), age at first marriage (AFM) and time spent single between events and to compare age-specific trends in marital status in six cohort studies. Methods: Cohort data from Uganda, Tanzania, South Africa, Zimbabwe and Malawi and Demographic and Health Survey (DHS) data from Uganda, Tanzania and Zimbabwe were analysed. Life table methods were used to calculate median AFS, AFM and time spent single. In each study, two surveys were chosen to compare marital status by age and identify changes over time. Results: Median AFM was much higher in South Africa than in the other sites. Between the other populations there were considerable differences in median AFS and AFM (AFS 17–19 years for men and 16–19 years for women, AFM 21–24 years and 18–19 years, respectively, for the 1970–9 birth cohort). In all surveys, men reported a longer time spent single than women (median 4–7 years for men and 0–2 years for women). Median years spent single for women has increased, apart from in Manicaland. For men in Rakai it has decreased slightly over time but increased in Kisesa and Masaka. The DHS data showed similar trends to those in the cohort data. The age-specific proportion of married individuals has changed little over time. Conclusions: Median AFS, AFM and time spent single vary considerably among these populations. These three measures are underlying determinants of sexual risk and HIV infection, and they may partially explain the variation in HIV prevalence levels between these populations. PMID:19307343

Detection of Functional Change Using Cluster Trend Analysis in Glaucoma.

PubMed

Gardiner, Stuart K; Mansberger, Steven L; Demirel, Shaban

2017-05-01

Global analyses using mean deviation (MD) assess visual field progression, but can miss localized changes. Pointwise analyses are more sensitive to localized progression, but more variable so require confirmation. This study assessed whether cluster trend analysis, averaging information across subsets of locations, could improve progression detection. A total of 133 test-retest eyes were tested 7 to 10 times. Rates of change and P values were calculated for possible re-orderings of these series to generate global analysis ("MD worsening faster than x dB/y with P < y"), pointwise and cluster analyses ("n locations [or clusters] worsening faster than x dB/y with P < y") with specificity exactly 95%. These criteria were applied to 505 eyes tested over a mean of 10.5 years, to find how soon each detected "deterioration," and compared using survival models. This was repeated including two subsequent visual fields to determine whether "deterioration" was confirmed. The best global criterion detected deterioration in 25% of eyes in 5.0 years (95% confidence interval [CI], 4.7-5.3 years), compared with 4.8 years (95% CI, 4.2-5.1) for the best cluster analysis criterion, and 4.1 years (95% CI, 4.0-4.5) for the best pointwise criterion. However, for pointwise analysis, only 38% of these changes were confirmed, compared with 61% for clusters and 76% for MD. The time until 25% of eyes showed subsequently confirmed deterioration was 6.3 years (95% CI, 6.0-7.2) for global, 6.3 years (95% CI, 6.0-7.0) for pointwise, and 6.0 years (95% CI, 5.3-6.6) for cluster analyses. Although the specificity is still suboptimal, cluster trend analysis detects subsequently confirmed deterioration sooner than either global or pointwise analyses.

Direct oral anticoagulants: analysis of worldwide use and popularity using Google Trends

PubMed Central

Mattiuzzi, Camilla; Cervellin, Gianfranco; Favaloro, Emmanuel J.

2017-01-01

Background Four direct oral anticoagulants (DOACs) have been approved for clinical use by many medicines regulatory agencies around the world. Due to increasing use of these drugs in routine practice, we planned an original study to investigate their worldwide diffusion using a popular Web-search engine. Methods Two electronic searches were performed using Google Trends, the former using the keywords “warfarin” AND “heparin” AND “fondaparinux”, and the latter using the keywords “warfarin” AND “dabigatran” AND “rivaroxaban” AND “apixaban” AND “edoxaban”, both using the search criterion “prescription drug”. No language restriction was applied, and the searches were carried out from the first date available in Google Trends (January 1st, 2004) to present time (June 1st, 2017). Results The median Google Trends score of warfarin (i.e., 86) was consistently higher than that of heparin (54; P<0.001), fondaparinux (6; P<0.001), dabigatran (11; P<0.001), rivaroxaban (5; P<0.001), apixaban (1; P<0.001) and edoxaban (1; P<0.001). Specific analysis of the trends shows that the score of warfarin exhibits a highly significant decrease over time (r=−0.40; P<0.001), whilst that of heparin has remained virtually unchanged (r=0.12; P=0.127), and that of fondaparinux has marginally increased (r=0.16; P=0.038). As regards DOACs, the scores of these drugs significantly increased during the search period (dabigatran, r=0.79; rivaroxaban, r=0.99; apixaban, r=0.98; edoxaban, r=0.78; all P<0.001). When the analysis was limited to the past five years, the dabigatran score significantly decreased (r=−0.57; P<0.001), whereas that of the other DOACs exhibited an even sharper increase. Most Google searches for DOACs were performed in North America, central-eastern Europe and Australia. Conclusions The results of our analysis suggest that the popularity of DOACs is constantly increasing around the world, whereas that of warfarin has exhibited a constant and inexorable decline. PMID:28861419

Automatic Promotion and Student Dropout: Evidence from Uganda, Using Propensity Score in Difference in Differences Model

ERIC Educational Resources Information Center

Okurut, Jeje Moses

2018-01-01

The impact of automatic promotion practice on students dropping out of Uganda's primary education was assessed using propensity score in difference in differences analysis technique. The analysis strategy was instrumental in addressing the selection bias problem, as well as biases arising from common trends over time, and permanent latent…

Analysis of high-resolution foreign exchange data of USD-JPY for 13 years

NASA Astrophysics Data System (ADS)

Mizuno, Takayuki; Kurihara, Shoko; Takayasu, Misako; Takayasu, Hideki

2003-06-01

We analyze high-resolution foreign exchange data consisting of 20 million data points of USD-JPY for 13 years to report firm statistical laws in distributions and correlations of exchange rate fluctuations. A conditional probability density analysis clearly shows the existence of trend-following movements at time scale of 8-ticks, about 1 min.

Trends in socioeconomic inequalities in mortality in small areas of 33 Spanish cities.

PubMed

Marí-Dell'Olmo, Marc; Gotsens, Mercè; Palència, Laia; Rodríguez-Sanz, Maica; Martinez-Beneito, Miguel A; Ballesta, Mónica; Calvo, Montse; Cirera, Lluís; Daponte, Antonio; Domínguez-Berjón, Felicitas; Gandarillas, Ana; Goñi, Natividad Izco; Martos, Carmen; Moreno-Iribas, Conchi; Nolasco, Andreu; Salmerón, Diego; Taracido, Margarita; Borrell, Carme

2016-07-29

In Spain, several ecological studies have analyzed trends in socioeconomic inequalities in mortality from all causes in urban areas over time. However, the results of these studies are quite heterogeneous finding, in general, that inequalities decreased, or remained stable. Therefore, the objectives of this study are: (1) to identify trends in geographical inequalities in all-cause mortality in the census tracts of 33 Spanish cities between the two periods 1996-1998 and 2005-2007; (2) to analyse trends in the relationship between these geographical inequalities and socioeconomic deprivation; and (3) to obtain an overall measure which summarises the relationship found in each one of the cities and to analyse its variation over time. Ecological study of trends with 2 cross-sectional cuts, corresponding to two periods of analysis: 1996-1998 and 2005-2007. Units of analysis were census tracts of the 33 Spanish cities. A deprivation index calculated for each census tracts in all cities was included as a covariate. A Bayesian hierarchical model was used to estimate smoothed Standardized Mortality Ratios (sSMR) by each census tract and period. The geographical distribution of these sSMR was represented using maps of septiles. In addition, two different Bayesian hierarchical models were used to measure the association between all-cause mortality and the deprivation index in each city and period, and by sex: (1) including the association as a fixed effect for each city; (2) including the association as random effects. In both models the data spatial structure can be controlled within each city. The association in each city was measured using relative risks (RR) and their 95 % credible intervals (95 % CI). For most cities and in both sexes, mortality rates decline over time. For women, the mortality and deprivation patterns are similar in the first period, while in the second they are different for most cities. For men, RRs remain stable over time in 29 cities, in 3 diminish and in 1 increase. For women, in 30 cities, a non-significant change over time in RR is observed. However, in 4 cities RR diminishes. In overall terms, inequalities decrease (with a probability of 0.9) in both men (RR = 1.13, 95 % CI = 1.12-1.15 in the 1st period; RR = 1.11, 95 % CI = 1.09-1.13 in the 2nd period) and women (RR = 1.07, 95 % CI = 1.05-1.08 in the 1st period; RR = 1.04, 95 % CI = 1.02-1.06 in the 2nd period). In the future, it is important to conduct further trend studies, allowing to monitoring trends in socioeconomic inequalities in mortality and to identify (among other things) temporal factors that may influence these inequalities.

Long-Term Trends and Variability in Spring Development of Calanus finmarchicus in the Southeastern Norwegian Sea during 1996-2012

NASA Astrophysics Data System (ADS)

Dupont, N.; Bagøien, E.; Melle, W.

2016-02-01

Calanus finmarchicus is the dominant copepod species in the Norwegian Sea in terms of biomass, playing a key role in the ecosystem by transferring energy from primary producers to higher trophic levels. This study analyses the long-term trend of a 17-year time series (1996-2012) on abundance of adult Calanus finmarchicus in the Atlantic water-mass of the southern Norwegian Sea during spring. The long-term trend in spring abundance was assessed by using Generalised Additive Models, while simultaneously accounting for both general population development and inter-annual variation in population development throughout the study period. In one model, we focus on inter-annual changes in timing of the Calanus spring seasonal development by including Mean Stage Composition as a measure for state of population development. Following a short increase during the years 1996 to 2000, the abundance of Calanus finmarchicus decreased strongly until about the year 2010. For the two last years of the studied period, 2011-2012, increasing population abundances are suggested but with less certainty. The model results suggest that the analysis is capturing the G0 generation, displaying a peak for the adults in about mid-April. Inter-annual differences in spring seasonal development, with the peak of adults shifting towards earlier in the season as well as a shorter generation time are suggested. Considering the importance of Calanus finmarchicus as food for planktivorous predators in the Norwegian Sea, our time series analysis suggests relevant changes both with respect to the spring abundance and timing of this food source. The next step is to relate variation in the Calanus time series to environmental factors with special emphasis on climatic drivers.

The New York Times Report on Teenage Reading Tastes and Habits.

ERIC Educational Resources Information Center

Freiberger, Rema

In order to learn whether teenagers are reading books and, if so, which books they choose, "The New York Times" conducted a fact-finding project. Questionnaires were mailed to the school librarians and English chairmen of 7000 secondary and intermediate schools. The wide variety of answers to observable trends necessitated the analysis of a random…

High School Grade Inflation from 2004 to 2011. ACT Research Report Series, 2013 (3)

ERIC Educational Resources Information Center

Zhang, Qian; Sanchez, Edgar I.

2013-01-01

This study explores inflation in high school grade point average (HSGPA), defined as trend over time in the conditional average of HSGPA, given ACT® Composite score. The time period considered is 2004 to 2011. Using hierarchical linear modeling, the study updates a previous analysis of Woodruff and Ziomek (2004). The study also investigates…

Environmental science: Trends in ecosystem recovery from drought

NASA Astrophysics Data System (ADS)

Seneviratne, Sonia I.; Ciais, Philippe

2017-08-01

An analysis suggests that the time taken for ecosystems to recover from drought increased during the twentieth century. If the frequency of drought events rises, some ecosystems might never have the chance to fully recover. See Letter p.202

Predicting and analyzing the trend of traffic accidents deaths in Iran in 2014 and 2015.

PubMed

Mehmandar, Mohammadreza; Soori, Hamid; Mehrabi, Yadolah

2016-01-01

Predicting the trend in traffic accidents deaths and its analysis can be a useful tool for planning and policy-making, conducting interventions appropriate with death trend, and taking the necessary actions required for controlling and preventing future occurrences. Predicting and analyzing the trend of traffic accidents deaths in Iran in 2014 and 2015. It was a cross-sectional study. All the information related to fatal traffic accidents available in the database of Iran Legal Medicine Organization from 2004 to the end of 2013 were used to determine the change points (multi-variable time series analysis). Using autoregressive integrated moving average (ARIMA) model, traffic accidents death rates were predicted for 2014 and 2015, and a comparison was made between this rate and the predicted value in order to determine the efficiency of the model. From the results, the actual death rate in 2014 was almost similar to that recorded for this year, while in 2015 there was a decrease compared with the previous year (2014) for all the months. A maximum value of 41% was also predicted for the months of January and February, 2015. From the prediction and analysis of the death trends, proper application and continuous use of the intervention conducted in the previous years for road safety improvement, motor vehicle safety improvement, particularly training and culture-fostering interventions, as well as approval and execution of deterrent regulations for changing the organizational behaviors, can significantly decrease the loss caused by traffic accidents.

Partition of genetic trends by origin in Landrace and Large-White pigs.

PubMed

Škorput, D; Gorjanc, G; Kasap, A; Luković, Z

2015-10-01

The objective of this study was to analyse the effectiveness of genetic improvement via domestic selection and import for backfat thickness and time on test in a conventional pig breeding programme for Landrace (L) and Large-White (LW) breeds. Phenotype data was available for 25 553 L and 10 432 LW pigs born between 2002 and 2012 from four large-scale farms and 72 family farms. Pedigree information indicated whether each animal was born and registered within the domestic breeding programme or has been imported. This information was used for defining the genetic groups of unknown parents in a pedigree and the partitioning analysis. Breeding values were estimated using a Bayesian analysis of an animal model with and without genetic groups. Such analysis enabled full Bayesian inference of the genetic trends and their partitioning by the origin of germplasm. Estimates of genetic group indicated that imported germplasm was overall better than domestic and substantial changes in estimates of breeding values was observed when genetic group were fitted. The estimated genetic trends in L were favourable and significantly different from zero by the end of the analysed period. Overall, the genetic trends in LW were not different from zero. The relative contribution of imported germplasm to genetic trends was large, especially towards the end of analysed period with 78% and 67% in L and from 50% to 67% in LW. The analyses suggest that domestic breeding activities and sources of imported animals need to be re-evaluated, in particular in LW breed.

Analysis of trends in water-quality data for water conservation area 3A, the Everglades, Florida

USGS Publications Warehouse

Mattraw, H.C.; Scheidt, D.J.; Federico, A.C.

1987-01-01

Rainfall and water quality data bases from the South Florida Water Management District were used to evaluate water quality trends at 10 locations near or in Water Conservation Area 3A in The Everglades. The Seasonal Kendall test was applied to specific conductance, orthophosphate-phosphorus, nitrate-nitrogen, total Kjeldahl nitrogen, and total nitrogen regression residuals for the period 1978-82. Residuals of orthophosphate and nitrate quadratic models, based on antecedent 7-day rainfall at inflow gate S-11B, were the only two constituent-structure pairs that showed apparent significant (p < 0.05) increases in constituent concentrations. Elimination of regression models with distinct residual patterns and data outlines resulted in 17 statistically significant station water quality combinations for trend analysis. No water quality trends were observed. The 1979 Memorandum of Agreement outlining the water quality monitoring program between the Everglades National Park and the U.S. Army Corps of Engineers stressed collection four times a year at three stations, and extensive coverage of water quality properties. Trend analysis and other rigorous statistical evaluation programs are better suited to data monitoring programs that include more frequent sampling and that are organized in a water quality data management system. Pronounced areal differences in water quality suggest that a water quality monitoring system for Shark River Slough in Everglades National Park include collection locations near the source of inflow to Water Conservation Area 3A. (Author 's abstract)

Tuning the Voices of a Choir: Detecting Ecological Gradients in Time-Series Populations.

PubMed

Buras, Allan; van der Maaten-Theunissen, Marieke; van der Maaten, Ernst; Ahlgrimm, Svenja; Hermann, Philipp; Simard, Sonia; Heinrich, Ingo; Helle, Gerd; Unterseher, Martin; Schnittler, Martin; Eusemann, Pascal; Wilmking, Martin

2016-01-01

This paper introduces a new approach-the Principal Component Gradient Analysis (PCGA)-to detect ecological gradients in time-series populations, i.e. several time-series originating from different individuals of a population. Detection of ecological gradients is of particular importance when dealing with time-series from heterogeneous populations which express differing trends. PCGA makes use of polar coordinates of loadings from the first two axes obtained by principal component analysis (PCA) to define groups of similar trends. Based on the mean inter-series correlation (rbar) the gain of increasing a common underlying signal by PCGA groups is quantified using Monte Carlo Simulations. In terms of validation PCGA is compared to three other existing approaches. Focusing on dendrochronological examples, PCGA is shown to correctly determine population gradients and in particular cases to be advantageous over other considered methods. Furthermore, PCGA groups in each example allowed for enhancing the strength of a common underlying signal and comparably well as hierarchical cluster analysis. Our results indicate that PCGA potentially allows for a better understanding of mechanisms causing time-series population gradients as well as objectively enhancing the performance of climate transfer functions in dendroclimatology. While our examples highlight the relevance of PCGA to the field of dendrochronology, we believe that also other disciplines working with data of comparable structure may benefit from PCGA.

Tuning the Voices of a Choir: Detecting Ecological Gradients in Time-Series Populations

PubMed Central

Buras, Allan; van der Maaten-Theunissen, Marieke; van der Maaten, Ernst; Ahlgrimm, Svenja; Hermann, Philipp; Simard, Sonia; Heinrich, Ingo; Helle, Gerd; Unterseher, Martin; Schnittler, Martin; Eusemann, Pascal; Wilmking, Martin

2016-01-01

This paper introduces a new approach–the Principal Component Gradient Analysis (PCGA)–to detect ecological gradients in time-series populations, i.e. several time-series originating from different individuals of a population. Detection of ecological gradients is of particular importance when dealing with time-series from heterogeneous populations which express differing trends. PCGA makes use of polar coordinates of loadings from the first two axes obtained by principal component analysis (PCA) to define groups of similar trends. Based on the mean inter-series correlation (rbar) the gain of increasing a common underlying signal by PCGA groups is quantified using Monte Carlo Simulations. In terms of validation PCGA is compared to three other existing approaches. Focusing on dendrochronological examples, PCGA is shown to correctly determine population gradients and in particular cases to be advantageous over other considered methods. Furthermore, PCGA groups in each example allowed for enhancing the strength of a common underlying signal and comparably well as hierarchical cluster analysis. Our results indicate that PCGA potentially allows for a better understanding of mechanisms causing time-series population gradients as well as objectively enhancing the performance of climate transfer functions in dendroclimatology. While our examples highlight the relevance of PCGA to the field of dendrochronology, we believe that also other disciplines working with data of comparable structure may benefit from PCGA. PMID:27467508

[Visual field progression in glaucoma: cluster analysis].

PubMed

Bresson-Dumont, H; Hatton, J; Foucher, J; Fonteneau, M

2012-11-01

Visual field progression analysis is one of the key points in glaucoma monitoring, but distinction between true progression and random fluctuation is sometimes difficult. There are several different algorithms but no real consensus for detecting visual field progression. The trend analysis of global indices (MD, sLV) may miss localized deficits or be affected by media opacities. Conversely, point-by-point analysis makes progression difficult to differentiate from physiological variability, particularly when the sensitivity of a point is already low. The goal of our study was to analyse visual field progression with the EyeSuite™ Octopus Perimetry Clusters algorithm in patients with no significant changes in global indices or worsening of the analysis of pointwise linear regression. We analyzed the visual fields of 162 eyes (100 patients - 58 women, 42 men, average age 66.8 ± 10.91) with ocular hypertension or glaucoma. For inclusion, at least six reliable visual fields per eye were required, and the trend analysis (EyeSuite™ Perimetry) of visual field global indices (MD and SLV), could show no significant progression. The analysis of changes in cluster mode was then performed. In a second step, eyes with statistically significant worsening of at least one of their clusters were analyzed point-by-point with the Octopus Field Analysis (OFA). Fifty four eyes (33.33%) had a significant worsening in some clusters, while their global indices remained stable over time. In this group of patients, more advanced glaucoma was present than in stable group (MD 6.41 dB vs. 2.87); 64.82% (35/54) of those eyes in which the clusters progressed, however, had no statistically significant change in the trend analysis by pointwise linear regression. Most software algorithms for analyzing visual field progression are essentially trend analyses of global indices, or point-by-point linear regression. This study shows the potential role of analysis by clusters trend. However, for best results, it is preferable to compare the analyses of several tests in combination with morphologic exam. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Assessment of Precipitation Trends over Europe by Comparing ERA-20C with a New Homogenized Observational GPCC Dataset

NASA Astrophysics Data System (ADS)

Rustemeier, E.; Ziese, M.; Meyer-Christoffer, A.; Finger, P.; Schneider, U.; Becker, A.

2015-12-01

Reliable data is essential for robust climate analysis. The ERA-20C reanalysis was developed during the projects ERA-CLIM and ERA-CLIM2. These projects focus on multi-decadal reanalyses of the global climate system. To ensure data quality and provide end users with information about uncertainties in these products, the 4th work package of ERA_CLIM2 deals with the quality assessment of the products including quality control and error estimation.In doing so, the monthly totals of the ERA-20C reanalysis are compared to two corresponding Global Precipitation Climatology Centre (GPCC) products; the Full Data Reanalysis Version 7 and the new HOMogenized PRecipitation Analysis of European in-situ data (HOMPRA Europe).ERA-20C reanalysis was produced based on ECMWFs IFS version Cy38r1 with a spatial resolution of about 125 km. It covers the time period 1900 to 2010. Only surface observations are assimilated namely marine winds and pressure. This allows the comparison with independent, not assimilated data. The GPCC Full Data Reanalysis Version 7 comprises monthly land-surface precipitation from approximately 75,000 rain-gauges covering the time period 1901-2013. For this paper, the version with 1° resolution is utilized. For trend analysis, a monthly European subset of the ERA-20C reanalysis is investigated spanning the years 1951-2005. The European subset will be compared to a new homogenized GPCC data set HOMPRA Europe. The latter is based on a collective of 5373 homogenized monthly rain gauge time series, carefully chosen from the GPCC archive of precipitation data.For the spatial and temporal evaluation of ERA-20C, global scores on monthly, seasonal and annual time scales are calculated. These include contingency table scores, correlation, along with spatial scores such as the fractional skill score. Unsurprisingly regions with strongest deviations are those of data scarcity, mountainous regions with their luv and lee effects, and monsoon regions. They all exhibit strong biases throughout their series, and severe shifts in the means. The new HOMPRA Europe data set is useful in particular for trend analysis. Therefore it is compared to a monthly European subset of the ERA-20C reanalysis for the same period, i.e. the years 1951-2005, to study the ERA-20C capability in reproducing observed trends across Europe.

Detection of temperature trends within the course of the year using "shifting subseasons"

NASA Astrophysics Data System (ADS)

Cahynova, Monika; Pokorna, Lucie

2015-04-01

Recent global warming has not been ubiquitous - there are seasons, regions, and time periods with clearly discernible zero or downward air temperature trends. Regions that are not warming or are even cooling - also known as "warming holes" - have been previously detected mainly in autumn in the second half of the 20th century in large parts of North America as well as in Central and Eastern Europe. Daily maximum and minimum temperature (TX and TN, respectively) and daily temperature range (DTR) at 136 stations in Europe during the period 1961-2000 are employed to precisely locate the seasonal and subseasonal trends within the course of the year. Linear trends are calculated for moving "subseasons" of differing lengths (10, 20, 30, 60, and 90 days), each shifted by one day. Cluster analysis of the annual course of "shifting trends" reveals relatively well-defined regions with similar trend behavior. Over most of Europe, the observed warming is greatest in winter, and the highest trend magnitudes are reached by TN in Eastern Europe. Two regions stand out: in Iceland and the Eastern Mediterranean, the trends during the year are weak, positive in summer and mostly negative in winter, reaching statistical significance at only few stations. Significant autumn cooling centered on mid-November was found in Eastern and Southeastern Europe for both TX and TN; in many other regions trends are close to zero in the same period. Other clearly non-warming (or even cooling) periods occur in Western and Central Europe in February, April, and late June. Trends of DTR are largely inconclusive and no general picture can be drawn. Our results suggest that using different time scales, apart from the conventional three-month seasons or common months, is highly desirable for a proper location of trends within the course of the year.

Robust analysis of trends in noisy tokamak confinement data using geodesic least squares regression

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

Verdoolaege, G., E-mail: geert.verdoolaege@ugent.be; Laboratory for Plasma Physics, Royal Military Academy, B-1000 Brussels; Shabbir, A.

Regression analysis is a very common activity in fusion science for unveiling trends and parametric dependencies, but it can be a difficult matter. We have recently developed the method of geodesic least squares (GLS) regression that is able to handle errors in all variables, is robust against data outliers and uncertainty in the regression model, and can be used with arbitrary distribution models and regression functions. We here report on first results of application of GLS to estimation of the multi-machine scaling law for the energy confinement time in tokamaks, demonstrating improved consistency of the GLS results compared to standardmore » least squares.« less

The observational case for Jupiter being a typical massive planet.

PubMed

Lineweaver, Charles H; Grether, Daniel

2002-01-01

We identify a subsample of the recently detected extrasolar planets that is minimally affected by the selection effects of the Doppler detection method. With a simple analysis we quantify trends in the surface density of this subsample in the period-Msin(i) plane. A modest extrapolation of these trends puts Jupiter in the most densely occupied region of this parameter space, thus indicating that Jupiter is a typical massive planet rather than an outlier. Our analysis suggests that Jupiter is more typical than indicated by previous analyses. For example, instead of MJup mass exoplanets being twice as common as 2 MJup exoplanets, we find they are three times as common.

Heavy smoking rate trends and related factors in Korean occupational groups: analysis of KNHANES 2007-2012 data.

PubMed

Kim, Bo-Guen; Pang, Do-Dam; Park, Young-Jun; Lee, Jong-In; Kim, Hyoung-Ryoul; Myong, Jun-Pyo; Jang, Tae-Won

2015-11-12

The present study was designed to investigate the smoking and heavy smoking trends and identify possible related factors among Korean male workers from 2007 to 2012 by occupational groups. The data were derived from the fourth (2007-2009) and fifth (2010-2012) waves of the Korean National Health and Nutrition Examination Survey (KNHANES). Occupational groups were categorised into three groups, which were non-manual, manual and service and sales groups. Age-adjusted prevalence rates of smoking and heavy smoking (>20 cigarettes/day) in men aged 25-64 years were calculated. Factors associated with heavy smoking were investigated using logistic regression analyses. Smoking rate in manual workers decreased gradually over time (p for trend <0.0001). Smoking rate was higher in manual than non-manual workers, but the difference reduced over time (p for trend <0.0001). Heavy smoking rate decreased from 2007 to 2012 (p for trend <0.0001). Heavy smoking rate was higher in manual than non-manual workers; however, this difference increased over time. Stress, depressive mood and long working hours (≥60 h/week) were associated with heavy smoking. Antismoking policy should focus on current and heavy smokers. Workplace antismoking programmes should consider working hours and stress, especially in manual workers. 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/

Comparison of Mean Climate Trends in the Northern Hemisphere Between N.C.E.P. and Two Atmosphere-Ocean Model Forced Runs

NASA Technical Reports Server (NTRS)

Lucarini, Valerio; Russell, Gary L.; Hansen, James E. (Technical Monitor)

2002-01-01

Results are presented for two greenhouse gas experiments of the Goddard Institute for Space Studies Atmosphere-Ocean Model (AOM). The computed trends of surface pressure, surface temperature, 850, 500 and 200 mb geopotential heights and related temperatures of the model for the time frame 1960-2000 are compared to those obtained from the National Centers for Environmental Prediction observations. A spatial correlation analysis and mean value comparison are performed, showing good agreement. A brief general discussion about the statistics of trend detection is presented. The domain of interest is the Northern Hemisphere (NH) because of the higher reliability of both the model results and the observations. The accuracy that this AOM has in describing the observed regional and NH climate trends makes it reliable in forecasting future climate changes.

Suicide in Greece 1992-2012: A time-series analysis.

PubMed

Papaslanis, Theodoros; Kontaxakis, Vassilis; Christodoulou, Christos; Konstantakopoulos, George; Kontaxaki, Maria-Irini; Papadimitriou, George N

2016-08-01

Since 2008, Greece has entered a long period of economic crisis with adverse effects on various aspects of daily life. In this frame, it is quite important to examine the suicide trends in Greece. Our analysis covered the period 1992-2012. 2012 was the last year for which official suicide data were available. The inclusion of data for pre-crisis period enabled us to assess trends in suicide preceding the economic crisis, starting in 2008. Trends in sex- and age-adjusted standardized suicide rates (SSR) were analyzed using joinpoint regression. Total SSR presented statistically significant annual decrease of 0.89% (95% confidence interval (CI): -1.7, -0.1) during the period 1992-2008. After 2009, the trend in total SSR increased statistically significant annual increase (12.48%; 95% CI: 0.3%, 26.1%). SSR in males presented an initial period of modest annual decrease (-0.84%; 95% CI: -1.6%, -0.1%), during the period 1992-2008. After 2009, an annual increase by 9.25% (95% CI: 2.7%, 16.3%) was revealed. No change in female SSR trend was observed during the studied period. According to the results of this study, there is clear evidence of an increase in the overall SSR and male SSR in Greece during the period of the current financial crisis. © The Author(s) 2016.

Forty-year trends in the flux and concentration of phosphorus in British rivers

NASA Astrophysics Data System (ADS)

Civan, Aylin; Worrall, Fred; Jarvie, Helen P.; Howden, Nicholas J. K.; Burt, Tim P.

2018-03-01

Given the importance of phosphorus (P) in the eutrophication of natural waters, this study considered the long-term time series of total phosphorus (TP) and total reactive phosphorus (TRP) in British rivers from 1974 to 2012. The approach included not only trend analysis of fluxes and concentrations but also change point analysis. TP and TRP concentrations and fluxes in British rivers have declined since the mid-1980s. Over the last decade of the record the majority of individual sites did show significant downward trends in TP and TRP concentrations but, in 28% of cases for TRP concentration and 14% of cases for TP concentration, the decadal trend was a significant increase. Out of 230 sites, 136 showed a significant step decrease in TRP concentration; no sites showed a significant step increase. The modal year for the step changes for both TRP concentration and flux was 1997. Step changes are likely associated with improvements made at sewage treatment works to comply with the Urban Waste Water Treatment Directive (91/271/EEC). The decrease in TRP concentration due to the step change were in the range of 0.68% and 89% with a geometric mean of 22%, with the rest of the decrease accounted by long-term, persistent downward trend.

Detecting temporal trends in species assemblages with bootstrapping procedures and hierarchical models

USGS Publications Warehouse

Gotelli, Nicholas J.; Dorazio, Robert M.; Ellison, Aaron M.; Grossman, Gary D.

2010-01-01

Quantifying patterns of temporal trends in species assemblages is an important analytical challenge in community ecology. We describe methods of analysis that can be applied to a matrix of counts of individuals that is organized by species (rows) and time-ordered sampling periods (columns). We first developed a bootstrapping procedure to test the null hypothesis of random sampling from a stationary species abundance distribution with temporally varying sampling probabilities. This procedure can be modified to account for undetected species. We next developed a hierarchical model to estimate species-specific trends in abundance while accounting for species-specific probabilities of detection. We analysed two long-term datasets on stream fishes and grassland insects to demonstrate these methods. For both assemblages, the bootstrap test indicated that temporal trends in abundance were more heterogeneous than expected under the null model. We used the hierarchical model to estimate trends in abundance and identified sets of species in each assemblage that were steadily increasing, decreasing or remaining constant in abundance over more than a decade of standardized annual surveys. Our methods of analysis are broadly applicable to other ecological datasets, and they represent an advance over most existing procedures, which do not incorporate effects of incomplete sampling and imperfect detection.

Laparoscopic Colorectal Surgery in the Emergency Setting: Trends in the Province of Ontario.

PubMed

Musselman, Reilly P; Gomes, Tara; Chan, Beverley P; Auer, Rebecca C; Moloo, Husein; Mamdani, Muhammad; Al-Omran, Mohammed; Al-Obeed, Omar; Boushey, Robin P

2015-10-01

The purpose of this study was to examine the adoption trends of emergency laparoscopic colorectal surgery in the province of Ontario. We conducted a retrospective time-series analysis examining rates of emergency colorectal surgery among 10.5 million adults in Ontario, Canada from April 1, 2002 to December 31, 2009. We linked administrative claims databases and the Ontario Cancer Registry to assess procedure rates over time. Procedure trends were assessed using time-series analysis. Over the 8-year period, 29,676 emergency colorectal procedures were identified. A total of 2582 (8.7%) were performed laparoscopically and 27,094 (91.3%) were open. Open and laparoscopic patients were similar with respect age, sex, and Charlson Comorbidity Index. The proportion of surgery for benign (63.8% of open cases vs. 65.6% laparoscopic, standardized difference=0.04) and malignant disease (36.2% open vs. 34.4% laparoscopic, standardized difference=0.04) was equal between groups. The percentage of emergency colorectal surgery performed laparoscopically increased from 5.7% in 2002 to 12.0% in 2009 (P<0.01). The use of laparoscopy increased for both benign and malignant disease. Statistically significant upward trends in laparoscopic surgery were seen for inflammatory bowel disease (P<0.01), obstruction (P<0.01), and colon cancer (P<0.01). From 2002 to 2009, annual procedure rates increased at a greater rate in nonacademic centers (P<0.01). Laparoscopic emergency colorectal surgery has increased significantly between 2002 and 2009 for both benign and malignant disease and for a wide range of diagnoses. This was driven in part by steadily rising usage of laparoscopy in nonacademic centers.

Unabated global surface temperature warming: evaluating the evidence

NASA Astrophysics Data System (ADS)

Karl, T. R.; Arguez, A.

2015-12-01

New insights related to time-dependent bias corrections in global surface temperatures have led to higher rates of warming over the past few decades than previously reported in the IPCC Fifth Assessment Report (2014). Record high global temperatures in the past few years have also contributed to larger trends. The combination of these factors and new analyses of the rate of temperature change show unabated global warming since at least the mid-Twentieth Century. New time-dependent bias corrections account for: (1) differences in temperatures measured from ships and drifting buoys; (2) improved corrections to ship measured temperatures; and (3) the larger rates of warming in polar regions (particularly the Arctic). Since 1951, the period over which IPCC (2014) attributes over half of the observed global warming to human causes, it is shown that there has been a remarkably robust and sustained warming, punctuated with inter-annual and decadal variability. This finding is confirmed through simple trend analysis and Empirical Mode Decomposition (EMD). Trend analysis however, especially for decadal trends, is sensitive to selection bias of beginning and ending dates. EMD has no selection bias. Additionally, it can highlight both short- and long-term processes affecting the global temperature times series since it addresses both non-linear and non-stationary processes. For the new NOAA global temperature data set, our analyses do not support the notion of a hiatus or slowing of long-term global warming. However, sub-decadal periods of little (or no warming) and rapid warming can also be found, clearly showing the impact of inter-annual and decadal variability that previously has been attributed to both natural and human-induced non-greenhouse forcings.

Depth-time interpolation of feature trends extracted from mobile microelectrode data with kernel functions.

PubMed

Wong, Stephen; Hargreaves, Eric L; Baltuch, Gordon H; Jaggi, Jurg L; Danish, Shabbar F

2012-01-01

Microelectrode recording (MER) is necessary for precision localization of target structures such as the subthalamic nucleus during deep brain stimulation (DBS) surgery. Attempts to automate this process have produced quantitative temporal trends (feature activity vs. time) extracted from mobile MER data. Our goal was to evaluate computational methods of generating spatial profiles (feature activity vs. depth) from temporal trends that would decouple automated MER localization from the clinical procedure and enhance functional localization in DBS surgery. We evaluated two methods of interpolation (standard vs. kernel) that generated spatial profiles from temporal trends. We compared interpolated spatial profiles to true spatial profiles that were calculated with depth windows, using correlation coefficient analysis. Excellent approximation of true spatial profiles is achieved by interpolation. Kernel-interpolated spatial profiles produced superior correlation coefficient values at optimal kernel widths (r = 0.932-0.940) compared to standard interpolation (r = 0.891). The choice of kernel function and kernel width resulted in trade-offs in smoothing and resolution. Interpolation of feature activity to create spatial profiles from temporal trends is accurate and can standardize and facilitate MER functional localization of subcortical structures. The methods are computationally efficient, enhancing localization without imposing additional constraints on the MER clinical procedure during DBS surgery. Copyright © 2012 S. Karger AG, Basel.

Could Google Trends Be Used to Predict Methamphetamine-Related Crime? An Analysis of Search Volume Data in Switzerland, Germany, and Austria.

PubMed

Gamma, Alex; Schleifer, Roman; Weinmann, Wolfgang; Buadze, Anna; Liebrenz, Michael

2016-01-01

To compare the time trends of Google search interest in methamphetamine and criminal offences related to this drug. Google Trends data for the search term "meth" was compared to methamphetamine-related crime statistics (incl. use, possession, and dealing) in Switzerland, Germany, and Austria for the years 2004-2016. Google data was availably monthly. Crime data was available yearly, and monthly values were imputed. On the country level, internet search trends for "meth" roughly paralleled relevant criminal activity. State-level data, which was available for Austria, showed more heterogeneity. Cross-correlations for yearly data almost always peaked at a lag time of 0 and coefficients were mostly between 0.7 and 1.0 on the country level, and between 0.5 to 1.0 on the state level. Monthly cross-correlations based on imputed values were substantially lower, ranging from 0 to 0.6. These results encourage the further evaluation by law enforcement authorities of Google search activity as a possible predictor of methamphetamine-related crime. However, several limitations, in particular the crude temporal resolution of available crime data, precluded a detailed assessment of the relationship between internet search trends and the development of methamphetamine-related crime in central Europe.

Global trends in vegetation phenology from 32-year GEOV1 leaf area index time series

NASA Astrophysics Data System (ADS)

Verger, Aleixandre; Baret, Frédéric; Weiss, Marie; Filella, Iolanda; Peñuelas, Josep

2013-04-01

Phenology is a critical component in understanding ecosystem response to climate variability. Long term data records from global mapping satellite platforms are valuable tools for monitoring vegetation responses to climate change at the global scale. Phenology satellite products and trend detection from satellite time series are expected to contribute to improve our understanding of climate forcing on vegetation dynamics. The capacity of monitoring ecosystem responses to global climate change was evaluated in this study from the 32-year time series of global Leaf Area Index (LAI) which have been recently produced within the geoland2 project. The long term GEOV1 LAI products were derived from NOAA/AVHRR (1981 to 2000) and SPOT/VGT (1999 to the present) with specific emphasis on consistency and continuity. Since mid-November, GEOV1 LAI products are freely available to the scientific community at geoland2 portal (www.geoland2.eu/core-mapping-services/biopar.html). These products are distributed at a dekadal time step for the period 1981-2000 and 2000-2012 at 0.05° and 1/112°, respectively. The use of GEOV1 data covering a long time period and providing information at dense time steps are expected to increase the reliability of trend detection. In this study, GEOV1 LAI time series aggregated at 0.5° spatial resolution are used. The CACAO (Consistent Adjustment of the Climatology to Actual Observations) method (Verger et al, 2013) was applied to characterize seasonal anomalies as well as identify trends. For a given pixel, CACAO computes, for each season, the time shift and the amplitude difference between the current temporal profile and the climatology computed over the 32 years. These CACAO parameters allow quantifying shifts in the timing of seasonal phenology and inter-annual variations in magnitude as compared to the average climatology. Interannual variations in the timing of the Start of Season and End of Season, Season Length and LAI level in the peak of the growing season are analyzed. Trend analysis with robust statistical test of significance is conducted. Climate variables (precipitation, temperature, radiation) are then used to interpret the anomaly patterns detected in vegetation response.

A Bibliometric Analysis of Research on Supported Ionic Liquid Membranes during the 1995–2015 Period: Study of the Main Applications and Trending Topics

PubMed Central

Abejón, Ricardo; Pérez-Acebo, Heriberto; Garea, Aurora

2017-01-01

A bibliometric analysis based on Scopus database was performed to identify the global research trends related to Supported Ionic Liquid Membranes (SILMs) during the time period from 1995 to 2015. This work tries to improve the understanding of the most relevant research topics and applications. The results from the analysis reveal that only after 2005 the research efforts focused on SILMs became significant, since the references found before that year are scarce. The most important research works on the four main application groups for SILMs defined in this work (carbon dioxide separation, other gas phase separations, pervaporation and liquid phase separations) were summarized in this paper. Carbon dioxide separation appeared as the application that has received by far the most attention according to the research trends during the analysed period. Comments about other significant applications that are gaining attention, such as the employment of SILMs in analytical tasks or their consideration for the production of fuel cells, have been included. PMID:29112172

The Changing Impact of Gastroesophageal Reflux Disease in Clinical Practice.

PubMed

Akst, Lee M; Haque, Omar J; Clarke, John O; Hillel, Alexander T; Best, Simon R A; Altman, Kenneth W

2017-03-01

The National Ambulatory Medical Care Survey (NAMCS) database was utilized to understand evolving national trends in diagnosis and management of reflux. The NAMCS database was queried for visits related to gastroesophageal reflux diagnosis and management. Analysis performed for time periods 1998-2001, 2002-2005, and 2006-2009 was weighted to provide national estimates of care. Results were compared to previously reported time periods from 1990 to 2001 to evaluate patterns in overall visits, age and ethnicity of patients, provider type, and prescriptions provided. The number of ambulatory visits for reflux increased from 8 684 000 in 1998-2001 to 15 750 000 in 2006-2009. Visits increased across each time period for internal medicine, family, and gastroenterology physicians. Among otolaryngologists, absolute visits increased from 1998-2001 to 2002-2005 but decreased in 2006-2009; difference between these time periods did not reach statistical significance. From 1998-2001 to 2006-2009, reflux medication use increased 233%, with continuing trends toward increased proton pump inhibitor use. Reflux visits have increased across all demographic subgroups studied. Knowledge of these trends may inform further paradigm shifts in diagnosis and management of reflux.

Estimating terrestrial water storage changes in the Tarim River Basin using GRACE data

NASA Astrophysics Data System (ADS)

Zhao, Kefei; Li, Xia

2017-12-01

Terrestrial water storage (TWS) plays a fundamental role in the arid Tarim River Basin, which is mainly fed by glacier and snow melt water. However, the significant scarcity of ground-based observations, especially in the high-altitude mountain areas, limits our understanding of TWS changes in this region. In this study, TWS variations in the Tarim River Basin were estimated using monthly GRACE Level 2 Release 5 (RL05) products from 2002 to August 2015. The GRACE results were validated against outputs of Global Land Data Assimilation System (GLDAS) including spatial and temporal correlation analysis. The correlation between the regional TWS time-series of GRACE and GLDAS is 0.7777. It was found that GRACE TWS shows a slightly decreasing trend of -1.4069 ± 0.5060 mm yr-1 in the entire Tarim River Basin during the study period and a significant spatial difference over the study area. An apparent decreasing trend in Tien Shan and the Taklamakan Desert, and a significant increasing trend in the Kunlun Mountains and eastern Pamirs Plateau were also detected. Moreover, seasonal analysis of regional TWS time-series, precipitation and the 0 °C isotherm height in summer showed that detrended TWS variations were consistent with precipitation while long-term trends of TWS were contrary to that of the 0 °C isotherm height in summer. It implied that the interannual TWS variations were dominated by precipitation and the long-term trend of TWS changes was affected by changes of the 0 °C isotherm height in summer. This information could enrich our knowledge about water storage changes, including glacier mass balance and groundwater, and its response to climate change in this vast but sparse in-situ measurements area.

Mortality from idiopathic pulmonary fibrosis: a temporal trend analysis in Brazil, 1979-2014

PubMed Central

Algranti, Eduardo; Saito, Cézar Akiyoshi; Silva, Diego Rodrigues Mendonça e; Carneiro, Ana Paula Scalia; Bussacos, Marco Antonio

2017-01-01

ABSTRACT Objective: To analyze mortality from idiopathic pulmonary fibrosis (IPF) in Brazil over the period 1979-2014. Methods: Microdata were extracted from the Brazilian National Ministry of Health Mortality Database. Only deaths for which the underlying cause was coded as International Classification of Diseases version 9 (ICD-9) 515 or 516.3 (until 1995) or as ICD version 10 (ICD-10) J84.1 (from 1996 onward) were included in our analysis. Standardized mortality rates were calculated for the 2010 Brazilian population. The annual trend in mortality rates was analyzed by joinpoint regression. We calculated risk ratios (RRs) by age group, time period of death, and gender, using a person-years denominator. Results: A total of 32,092 deaths were recorded in the study period. Standardized mortality rates trended upward, rising from 0.24/100,000 population in 1979 to 1.10/100,000 population in 2014. The annual upward trend in mortality rates had two inflection points, in 1992 and 2008, separating three distinct time segments with an annual growth of 2.2%, 6.8%, and 2.4%, respectively. The comparison of RRs for the age groups, using the 50- to 54-year age group as a reference, and for the study period, using 1979-1984 as a reference, were 16.14 (14.44-16.36) and 6.71 (6.34-7.12), respectively. Men compared with women had higher standardized mortality rates (per 100,000 person-years) in all age groups. Conclusion: Brazilian IPF mortality rates are lower than those of other countries, suggesting underdiagnosis or underreporting. The temporal trend is similar to those reported in the literature and is not explained solely by population aging. PMID:29340493

Dynamic factor analysis of long-term growth trends of the intertidal seagrass Thalassia hemprichii in southern Taiwan

NASA Astrophysics Data System (ADS)

Kuo, Yi-Ming; Lin, Hsing-Juh

2010-01-01

We examined environmental factors which are most responsible for the 8-year temporal dynamics of the intertidal seagrass Thalassia hemprichii in southern Taiwan. A dynamic factor analysis (DFA), a dimension-reduction technique, was applied to identify common trends in a multivariate time series and the relationships between this series and interacting environmental variables. The results of dynamic factor models (DFMs) showed that the leaf growth rate of the seagrass was mainly influenced by salinity (Sal), tidal range (TR), turbidity ( K), and a common trend representing an unexplained variability in the observed time series. Sal was the primary variable that explained the temporal dynamics of the leaf growth rate compared to TR and K. K and TR had larger influences on the leaf growth rate in low- than in high-elevation beds. In addition to K, TR, and Sal, UV-B radiation (UV-B), sediment depth (SD), and a common trend accounted for long-term temporal variations of the above-ground biomass. Thus, K, TR, Sal, UV-B, and SD are the predominant environmental variables that described temporal growth variations of the intertidal seagrass T. hemprichii in southern Taiwan. In addition to environmental variables, human activities may be contributing to negative impacts on the seagrass beds; this human interference may have been responsible for the unexplained common trend in the DFMs. Due to successfully applying the DFA to analyze complicated ecological and environmental data in this study, important environmental variables and impacts of human activities along the coast should be taken into account when managing a coastal environment for the conservation of intertidal seagrass beds.

Effects of linear trends on estimation of noise in GNSS position time-series

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

Dmitrieva, K.; Segall, P.; Bradley, A. M.

A thorough understanding of time-dependent noise in Global Navigation Satellite System (GNSS) position time-series is necessary for computing uncertainties in any signals found in the data. However, estimation of time-correlated noise is a challenging task and is complicated by the difficulty in separating noise from signal, the features of greatest interest in the time-series. In this study, we investigate how linear trends affect the estimation of noise in daily GNSS position time-series. We use synthetic time-series to study the relationship between linear trends and estimates of time-correlated noise for the six most commonly cited noise models. We find that themore » effects of added linear trends, or conversely de-trending, vary depending on the noise model. The commonly adopted model of random walk (RW), flicker noise (FN) and white noise (WN) is the most severely affected by de-trending, with estimates of low-amplitude RW most severely biased. FN plus WN is least affected by adding or removing trends. Non-integer power-law noise estimates are also less affected by de-trending, but are very sensitive to the addition of trend when the spectral index is less than one. We derive an analytical relationship between linear trends and the estimated RW variance for the special case of pure RW noise. Finally, overall, we find that to ascertain the correct noise model for GNSS position time-series and to estimate the correct noise parameters, it is important to have independent constraints on the actual trends in the data.« less

Effects of linear trends on estimation of noise in GNSS position time-series

NASA Astrophysics Data System (ADS)

Dmitrieva, K.; Segall, P.; Bradley, A. M.

2017-01-01

A thorough understanding of time-dependent noise in Global Navigation Satellite System (GNSS) position time-series is necessary for computing uncertainties in any signals found in the data. However, estimation of time-correlated noise is a challenging task and is complicated by the difficulty in separating noise from signal, the features of greatest interest in the time-series. In this paper, we investigate how linear trends affect the estimation of noise in daily GNSS position time-series. We use synthetic time-series to study the relationship between linear trends and estimates of time-correlated noise for the six most commonly cited noise models. We find that the effects of added linear trends, or conversely de-trending, vary depending on the noise model. The commonly adopted model of random walk (RW), flicker noise (FN) and white noise (WN) is the most severely affected by de-trending, with estimates of low-amplitude RW most severely biased. FN plus WN is least affected by adding or removing trends. Non-integer power-law noise estimates are also less affected by de-trending, but are very sensitive to the addition of trend when the spectral index is less than one. We derive an analytical relationship between linear trends and the estimated RW variance for the special case of pure RW noise. Overall, we find that to ascertain the correct noise model for GNSS position time-series and to estimate the correct noise parameters, it is important to have independent constraints on the actual trends in the data.

Effects of linear trends on estimation of noise in GNSS position time-series

DOE PAGES

Dmitrieva, K.; Segall, P.; Bradley, A. M.

2016-10-20

A thorough understanding of time-dependent noise in Global Navigation Satellite System (GNSS) position time-series is necessary for computing uncertainties in any signals found in the data. However, estimation of time-correlated noise is a challenging task and is complicated by the difficulty in separating noise from signal, the features of greatest interest in the time-series. In this study, we investigate how linear trends affect the estimation of noise in daily GNSS position time-series. We use synthetic time-series to study the relationship between linear trends and estimates of time-correlated noise for the six most commonly cited noise models. We find that themore » effects of added linear trends, or conversely de-trending, vary depending on the noise model. The commonly adopted model of random walk (RW), flicker noise (FN) and white noise (WN) is the most severely affected by de-trending, with estimates of low-amplitude RW most severely biased. FN plus WN is least affected by adding or removing trends. Non-integer power-law noise estimates are also less affected by de-trending, but are very sensitive to the addition of trend when the spectral index is less than one. We derive an analytical relationship between linear trends and the estimated RW variance for the special case of pure RW noise. Finally, overall, we find that to ascertain the correct noise model for GNSS position time-series and to estimate the correct noise parameters, it is important to have independent constraints on the actual trends in the data.« less

Trends in ischemic heart disease mortality in Korea, 1985-2009: an age-period-cohort analysis.

PubMed

Lee, Hye Ah; Park, Hyesook

2012-09-01

Economic growth and development of medical technology help to improve the average life expectancy, but the western diet and rapid conversions to poor lifestyles lead an increasing risk of major chronic diseases. Coronary heart disease mortality in Korea has been on the increase, while showing a steady decline in the other industrialized countries. An age-period-cohort analysis can help understand the trends in mortality and predict the near future. We analyzed the time trends of ischemic heart disease mortality, which is on the increase, from 1985 to 2009 using an age-period-cohort model to characterize the effects of ischemic heart disease on changes in the mortality rate over time. All three effects on total ischemic heart disease mortality were statistically significant. Regarding the period effect, the mortality rate was decreased slightly in 2000 to 2004, after it had continuously increased since the late 1980s that trend was similar in both sexes. The expected age effect was noticeable, starting from the mid-60's. In addition, the age effect in women was more remarkable than that in men. Women born from the early 1900s to 1925 observed an increase in ischemic heart mortality. That cohort effect showed significance only in women. The future cohort effect might have a lasting impact on the risk of ischemic heart disease in women with the increasing elderly population, and a national prevention policy is need to establish management of high risk by considering the age-period-cohort effect.

Site 765: Sedimentology

USGS Publications Warehouse

,

1990-01-01

Various techniques were used to decipher the sedimentation history of Site 765, including Markov chain analysis of facies transitions, XRD analysis of clay and other minerals, and multivariate analysis of smear-slide data, in addition to the standard descriptive procedures employed by the shipboard sedimentologist. This chapter presents brief summaries of methodology and major findings of these three techniques, a summary of the sedimentation history, and a discussion of trends in sedimentation through time.

Long-term trends of surface ozone and its influencing factors at the Mt Waliguan GAW station, China - Part 2: The roles of anthropogenic emissions and climate variability

NASA Astrophysics Data System (ADS)

Xu, Wanyun; Xu, Xiaobin; Lin, Meiyun; Lin, Weili; Tarasick, David; Tang, Jie; Ma, Jianzhong; Zheng, Xiangdong

2018-01-01

Inter-annual variability and long-term trends in tropospheric ozone are both environmental and climate concerns. Ozone measured at Mt Waliguan Observatory (WLG, 3816 m a.s.l.) on the Tibetan Plateau over the period of 1994-2013 has increased significantly by 0.2-0.3 ppbv yr-1 during spring and autumn but shows a much smaller trend in winter and no significant trend in summer. Here we explore the factors driving the observed ozone changes at WLG using backward trajectory analysis, chemistry-climate model hindcast simulations (GFDL AM3), a trajectory-mapped ozonesonde data set, and several climate indices. A stratospheric ozone tracer implemented in GFDL AM3 indicates that stratosphere-to-troposphere transport (STT) can explain ˜ 60 % of the simulated springtime ozone increase at WLG, consistent with an increase in the NW air-mass frequency inferred from the trajectory analysis. Enhanced STT associated with the strengthening of the mid-latitude jet stream contributes to the observed high ozone anomalies at WLG during the springs of 1999 and 2012. During autumn, observations at WLG are more heavily influenced by polluted air masses originating from South East Asia than in the other seasons. Rising Asian anthropogenic emissions of ozone precursors are the key driver of increasing autumnal ozone observed at WLG, as supported by the GFDL AM3 model with time-varying emissions, which captures the observed ozone increase (0.26 ± 0.11 ppbv yr-1). AM3 simulates a greater ozone increase of 0.38 ± 0.11 ppbv yr-1 at WLG in autumn under conditions with strong transport from South East Asia and shows no significant ozone trend in autumn when anthropogenic emissions are held constant in time. During summer, WLG is mostly influenced by easterly air masses, but these trajectories do not extend to the polluted regions of eastern China and have decreased significantly over the last 2 decades, which likely explains why summertime ozone measured at WLG shows no significant trend despite ozone increases in eastern China. Analysis of the Trajectory-mapped Ozonesonde data set for the Stratosphere and Troposphere (TOST) and trajectory residence time reveals increases in direct ozone transport from the eastern sector during autumn, which adds to the autumnal ozone increase. We further examine the links of ozone variability at WLG to the quasi-biennial oscillation (QBO), the East Asian summer monsoon (EASM), and the sunspot cycle. Our results suggest that the 2-3-, 3-7-, and 11-year periodicities are linked to the QBO, EASM index, and sunspot cycle, respectively. A multivariate regression analysis is performed to quantify the relative contributions of various factors to surface ozone concentrations at WLG. Through an observational and modelling analysis, this study demonstrates the complex relationships between surface ozone at remote locations and its dynamical and chemical influencing factors.

Land degradation and Poverty in maize producing areas of Kenya - Development of an interdisciplinary analysis framework using GIS and remote sensing

NASA Astrophysics Data System (ADS)

Graw, Valerie; Nkonya, Ephraim; Menz, Gunter

2014-05-01

Land degradation causes poverty and vice versa. But both processes are highly complex, hard to predict and to mitigate, and need insights from different perspectives. Therefore an interdisciplinary framework for the understanding of land degradation processes by linking biophysical data with socio-economic trends is necessary. Agricultural systems in Kenya are affected by land degradation and especially recent developments such as agricultural innovations including the use of hybrid seeds and chemical fertilizer have an impact on the environment. Vegetation analysis, used as a proxy indicator for the status of land is carried out to monitor environmental changes in maize producing areas of western Kenya. One of the methods used in this study includes time series analysis of vegetation data from 2001 to 2010 based on MODIS NDVI data with 250m and 500m resolution. Occurring trends are linked to rainfall estimation data and annually classified land use cover data with 500m resolution based on MODIS within the same time period. Analysis of significant trends in combination with land cover information show recent land change dynamics. As these changes are not solely biophysically driven, socio-economic variables representing marginality - defined as the root cause of poverty- are also considered. The most poor are primarily facing the most vulnerable and thereby less fertile soils. Moreover they are lacking access to information to eventually use existing potential. This makes the analysis of changing environmental processes and household characteristics in the interplay important to understand in order to highlight the most influencing variables. Within the new interdisciplinary analysis framework the concept of marginality includes different dimensions referring to certain livelihood characteristics such as health and education which describe a more diverse picture of poverty than the known economic perspective. Household surveys and census data from different time periods allow the analysis of socio-economic trends and link this information to biophysical factors. If relationships between certain variables are understood, adapted land management strategies can be developed. This study aims at linking pixel-level information with established remote sensing methods to the socio-economic concept of marginality based on household surveys and census data on administrative levels. Besides remote sensing and statistical analysis of socio-economic data a GIS is used for geospatial analysis. As most studies on land degradation focus on biophysical aspects such as vegetation or soil degradation this study uses an innovative approach by integrating biophysical analysis without neglecting a human oriented approach which plays a key role in environmental systems nowadays. This interdisciplinary research helps to get closer to the right and adapted policies and land management strategies as land degradation processes do not stick to administrative boundaries but policy advice does.

A Monte Carlo Uncertainty Analysis of Ozone Trend Predictions in a Two Dimensional Model. Revision

NASA Technical Reports Server (NTRS)

Considine, D. B.; Stolarski, R. S.; Hollandsworth, S. M.; Jackman, C. H.; Fleming, E. L.

1998-01-01

We use Monte Carlo analysis to estimate the uncertainty in predictions of total O3 trends between 1979 and 1995 made by the Goddard Space Flight Center (GSFC) two-dimensional (2D) model of stratospheric photochemistry and dynamics. The uncertainty is caused by gas-phase chemical reaction rates, photolysis coefficients, and heterogeneous reaction parameters which are model inputs. The uncertainty represents a lower bound to the total model uncertainty assuming the input parameter uncertainties are characterized correctly. Each of the Monte Carlo runs was initialized in 1970 and integrated for 26 model years through the end of 1995. This was repeated 419 times using input parameter sets generated by Latin Hypercube Sampling. The standard deviation (a) of the Monte Carlo ensemble of total 03 trend predictions is used to quantify the model uncertainty. The 34% difference between the model trend in globally and annually averaged total O3 using nominal inputs and atmospheric trends calculated from Nimbus 7 and Meteor 3 total ozone mapping spectrometer (TOMS) version 7 data is less than the 46% calculated 1 (sigma), model uncertainty, so there is no significant difference between the modeled and observed trends. In the northern hemisphere midlatitude spring the modeled and observed total 03 trends differ by more than 1(sigma) but less than 2(sigma), which we refer to as marginal significance. We perform a multiple linear regression analysis of the runs which suggests that only a few of the model reactions contribute significantly to the variance in the model predictions. The lack of significance in these comparisons suggests that they are of questionable use as guides for continuing model development. Large model/measurement differences which are many multiples of the input parameter uncertainty are seen in the meridional gradients of the trend and the peak-to-peak variations in the trends over an annual cycle. These discrepancies unambiguously indicate model formulation problems and provide a measure of model performance which can be used in attempts to improve such models.

Volumetric Trends Associated with MR-guided Stereotactic Laser Amygdalohippocampectomy in Mesial Temporal Lobe Epilepsy

PubMed Central

Patel, Nitesh V; Sundararajan, Sri; Keller, Irwin; Danish, Shabbar

2018-01-01

Objective: Magnetic resonance (MR)-guided stereotactic laser amygdalohippocampectomy is a minimally invasive procedure for the treatment of refractory epilepsy in patients with mesial temporal sclerosis. Limited data exist on post-ablation volumetric trends associated with the procedure. Methods: 10 patients with mesial temporal sclerosis underwent MR-guided stereotactic laser amygdalohippocampectomy. Three independent raters computed ablation volumes at the following time points: pre-ablation (PreA), immediate post-ablation (IPA), 24 hours post-ablation (24PA), first follow-up post-ablation (FPA), and greater than three months follow-up post-ablation (>3MPA), using OsiriX DICOM Viewer (Pixmeo, Bernex, Switzerland). Statistical trends in post-ablation volumes were determined for the time points. Results: MR-guided stereotactic laser amygdalohippocampectomy produces a rapid rise and distinct peak in post-ablation volume immediately following the procedure. IPA volumes are significantly higher than all other time points. Comparing individual time points within each raters dataset (intra-rater), a significant difference was seen between the IPA time point and all others. There was no statistical difference between the 24PA, FPA, and >3MPA time points. A correlation analysis demonstrated the strongest correlations at the 24PA (r=0.97), FPA (r=0.95), and 3MPA time points (r=0.99), with a weaker correlation at IPA (r=0.92). Conclusion: MR-guided stereotactic laser amygdalohippocampectomy produces a maximal increase in post-ablation volume immediately following the procedure, which decreases and stabilizes at 24 hours post-procedure and beyond three months follow-up. Based on the correlation analysis, the lower inter-rater reliability at the IPA time point suggests it may be less accurate to assess volume at this time point. We recommend post-ablation volume assessments be made at least 24 hours post-selective ablation of the amygdalohippocampal complex (SLAH).

Habitat availability is a more plausible explanation than insecticide acute toxicity for U.S. grassland bird species declines

USGS Publications Warehouse

Hill, Jason M.; Egan, J. Franklin; Stauffer, Glenn E.; Diefenbach, Duane R.

2014-01-01

Grassland bird species have experienced substantial declines in North America. These declines have been largely attributed to habitat loss and degradation, especially from agricultural practices and intensification (the habitat-availability hypothesis). A recent analysis of North American Breeding Bird Survey (BBS) “grassland breeding” bird trends reported the surprising conclusion that insecticide acute toxicity was a better correlate of grassland bird declines in North America from 1980–2003 (the insecticide-acute-toxicity hypothesis) than was habitat loss through agricultural intensification. In this paper we reached the opposite conclusion. We used an alternative statistical approach with additional habitat covariates to analyze the same grassland bird trends over the same time frame. Grassland bird trends were positively associated with increases in area of Conservation Reserve Program (CRP) lands and cropland used as pasture, whereas the effect of insecticide acute toxicity on bird trends was uncertain. Our models suggested that acute insecticide risk potentially has a detrimental effect on grassland bird trends, but models representing the habitat-availability hypothesis were 1.3–21.0 times better supported than models representing the insecticide-acute-toxicity hypothesis. Based on point estimates of effect sizes, CRP area and agricultural intensification had approximately 3.6 and 1.6 times more effect on grassland bird trends than lethal insecticide risk, respectively. Our findings suggest that preserving remaining grasslands is crucial to conserving grassland bird populations. The amount of grassland that has been lost in North America since 1980 is well documented, continuing, and staggering whereas insecticide use greatly declined prior to the 1990s. Grassland birds will likely benefit from the de-intensification of agricultural practices and the interspersion of pastures, Conservation Reserve Program lands, rangelands and other grassland habitats into existing agricultural landscapes.

Habitat availability is a more plausible explanation than insecticide acute toxicity for U.S. grassland bird species declines.

PubMed

Hill, Jason M; Egan, J Franklin; Stauffer, Glenn E; Diefenbach, Duane R

2014-01-01

Grassland bird species have experienced substantial declines in North America. These declines have been largely attributed to habitat loss and degradation, especially from agricultural practices and intensification (the habitat-availability hypothesis). A recent analysis of North American Breeding Bird Survey (BBS) "grassland breeding" bird trends reported the surprising conclusion that insecticide acute toxicity was a better correlate of grassland bird declines in North America from 1980-2003 (the insecticide-acute-toxicity hypothesis) than was habitat loss through agricultural intensification. In this paper we reached the opposite conclusion. We used an alternative statistical approach with additional habitat covariates to analyze the same grassland bird trends over the same time frame. Grassland bird trends were positively associated with increases in area of Conservation Reserve Program (CRP) lands and cropland used as pasture, whereas the effect of insecticide acute toxicity on bird trends was uncertain. Our models suggested that acute insecticide risk potentially has a detrimental effect on grassland bird trends, but models representing the habitat-availability hypothesis were 1.3-21.0 times better supported than models representing the insecticide-acute-toxicity hypothesis. Based on point estimates of effect sizes, CRP area and agricultural intensification had approximately 3.6 and 1.6 times more effect on grassland bird trends than lethal insecticide risk, respectively. Our findings suggest that preserving remaining grasslands is crucial to conserving grassland bird populations. The amount of grassland that has been lost in North America since 1980 is well documented, continuing, and staggering whereas insecticide use greatly declined prior to the 1990s. Grassland birds will likely benefit from the de-intensification of agricultural practices and the interspersion of pastures, Conservation Reserve Program lands, rangelands and other grassland habitats into existing agricultural landscapes.

Habitat Availability Is a More Plausible Explanation than Insecticide Acute Toxicity for U.S. Grassland Bird Species Declines

PubMed Central

Hill, Jason M.; Egan, J. Franklin; Stauffer, Glenn E.; Diefenbach, Duane R.

2014-01-01

Grassland bird species have experienced substantial declines in North America. These declines have been largely attributed to habitat loss and degradation, especially from agricultural practices and intensification (the habitat-availability hypothesis). A recent analysis of North American Breeding Bird Survey (BBS) “grassland breeding” bird trends reported the surprising conclusion that insecticide acute toxicity was a better correlate of grassland bird declines in North America from 1980–2003 (the insecticide-acute-toxicity hypothesis) than was habitat loss through agricultural intensification. In this paper we reached the opposite conclusion. We used an alternative statistical approach with additional habitat covariates to analyze the same grassland bird trends over the same time frame. Grassland bird trends were positively associated with increases in area of Conservation Reserve Program (CRP) lands and cropland used as pasture, whereas the effect of insecticide acute toxicity on bird trends was uncertain. Our models suggested that acute insecticide risk potentially has a detrimental effect on grassland bird trends, but models representing the habitat-availability hypothesis were 1.3–21.0 times better supported than models representing the insecticide-acute-toxicity hypothesis. Based on point estimates of effect sizes, CRP area and agricultural intensification had approximately 3.6 and 1.6 times more effect on grassland bird trends than lethal insecticide risk, respectively. Our findings suggest that preserving remaining grasslands is crucial to conserving grassland bird populations. The amount of grassland that has been lost in North America since 1980 is well documented, continuing, and staggering whereas insecticide use greatly declined prior to the 1990s. Grassland birds will likely benefit from the de-intensification of agricultural practices and the interspersion of pastures, Conservation Reserve Program lands, rangelands and other grassland habitats into existing agricultural landscapes. PMID:24846309

Instructional Time Trends. Education Trends

ERIC Educational Resources Information Center

Woods, Julie Rowland

2015-01-01

For more than 30 years, Education Commission of the States has tracked instructional time and frequently receives requests for information about policies and trends. In this Education Trends report, Education Commission of the States addresses some of the more frequent questions, including the impact of instructional time on achievement, variation…

Efficient hemodynamic event detection utilizing relational databases and wavelet analysis

NASA Technical Reports Server (NTRS)

Saeed, M.; Mark, R. G.

2001-01-01

Development of a temporal query framework for time-oriented medical databases has hitherto been a challenging problem. We describe a novel method for the detection of hemodynamic events in multiparameter trends utilizing wavelet coefficients in a MySQL relational database. Storage of the wavelet coefficients allowed for a compact representation of the trends, and provided robust descriptors for the dynamics of the parameter time series. A data model was developed to allow for simplified queries along several dimensions and time scales. Of particular importance, the data model and wavelet framework allowed for queries to be processed with minimal table-join operations. A web-based search engine was developed to allow for user-defined queries. Typical queries required between 0.01 and 0.02 seconds, with at least two orders of magnitude improvement in speed over conventional queries. This powerful and innovative structure will facilitate research on large-scale time-oriented medical databases.

Climate change in Bangladesh: a spatio-temporal analysis and simulation of recent temperature and rainfall data using GIS and time series analysis model

NASA Astrophysics Data System (ADS)

Rahman, Md. Rejaur; Lateh, Habibah

2017-04-01

In this paper, temperature and rainfall data series were analysed from 34 meteorological stations distributed throughout Bangladesh over a 40-year period (1971 to 2010) in order to evaluate the magnitude of these changes statistically and spatially. Linear regression, coefficient of variation, inverse distance weighted interpolation techniques and geographical information systems were performed to analyse the trends, variability and spatial patterns of temperature and rainfall. Autoregressive integrated moving average time series model was used to simulate the temperature and rainfall data. The results confirm a particularly strong and recent climate change in Bangladesh with a 0.20 °C per decade upward trend of mean temperature. The highest upward trend in minimum temperature (range of 0.80-2.4 °C) was observed in the northern, northwestern, northeastern, central and central southern parts while greatest warming in the maximum temperature (range of 1.20-2.48 °C) was found in the southern, southeastern and northeastern parts during 1971-2010. An upward trend of annual rainfall (+7.13 mm per year) and downward pre-monsoon (-0.75 mm per year) and post-monsoon rainfall (-0.55 mm per year) trends were observed during this period. Rainfall was erratic in pre-monsoon season and even more so during the post-monsoon season (variability of 44.84 and 85.25 % per year, respectively). The mean forecasted temperature exhibited an increase of 0.018 °C per year in 2011-2020, and if this trend continues, this would lead to approximately 1.0 °C warmer temperatures in Bangladesh by 2020, compared to that of 1971. A greater rise is projected for the mean minimum (0.20 °C) than the mean maximum (0.16 °C) temperature. Annual rainfall is projected to decline 153 mm from 2011 to 2020, and a drying condition will persist in the northwestern, western and southwestern parts of the country during the pre- and post-monsoonal seasons.

Counties eliminating racial disparities in colorectal cancer mortality.

PubMed

Rust, George; Zhang, Shun; Yu, Zhongyuan; Caplan, Lee; Jain, Sanjay; Ayer, Turgay; McRoy, Luceta; Levine, Robert S

2016-06-01

Although colorectal cancer (CRC) mortality rates are declining, racial-ethnic disparities in CRC mortality nationally are widening. Herein, the authors attempted to identify county-level variations in this pattern, and to characterize counties with improving disparity trends. The authors examined 20-year trends in US county-level black-white disparities in CRC age-adjusted mortality rates during the study period between 1989 and 2010. Using a mixed linear model, counties were grouped into mutually exclusive patterns of black-white racial disparity trends in age-adjusted CRC mortality across 20 three-year rolling average data points. County-level characteristics from census data and from the Area Health Resources File were normalized and entered into a principal component analysis. Multinomial logistic regression models were used to test the relation between these factors (clusters of related contextual variables) and the disparity trend pattern group for each county. Counties were grouped into 4 disparity trend pattern groups: 1) persistent disparity (parallel black and white trend lines); 2) diverging (widening disparity); 3) sustained equality; and 4) converging (moving from disparate outcomes toward equality). The initial principal component analysis clustered the 82 independent variables into a smaller number of components, 6 of which explained 47% of the county-level variation in disparity trend patterns. County-level variation in social determinants, health care workforce, and health systems all were found to contribute to variations in cancer mortality disparity trend patterns from 1990 through 2010. Counties sustaining equality over time or moving from disparities to equality in cancer mortality suggest that disparities are not inevitable, and provide hope that more communities can achieve optimal and equitable cancer outcomes for all. Cancer 2016;122:1735-48. © 2016 American Cancer Society. © 2016 American Cancer Society.

Variable Trends in High Peak Flow Generation Across the Swedish Sub-Arctic

NASA Astrophysics Data System (ADS)

Matti, B.; Dahlke, H. E.; Lyon, S. W.

2015-12-01

There is growing concern about increased frequency and severity of floods and droughts globally in recent years. Improving knowledge on the complexity of hydrological systems and their interactions with climate is essential to be able to determine drivers of these extreme events and to predict changes in these drivers under altered climate conditions. This is particularly true in cold regions such as the Swedish Sub-Arctic where independent shifts in both precipitation and temperature can have significant influence on extremes. This study explores changes in the magnitude and timing of the annual maximum daily flows in 18 Swedish sub-arctic catchments. The Mann-Kendall trend test was used to estimate changes in selected hydrological signatures. Further, a flood frequency analysis was conducted by fitting a Gumbel (Extreme Value type I) distribution whereby selected flood percentiles were tested for stationarity using a generalized least squares regression approach. Our results showed that hydrological systems in cold climates have complex, heterogeneous interactions with climate. Shifts from a snowmelt-dominated to a rainfall-dominated flow regime were evident with all significant trends pointing towards (1) lower flood magnitudes in the spring flood; (2) earlier flood occurrence; (3) earlier snowmelt onset; and (4) decreasing mean summer flows. Decreasing trends in flood magnitude and mean summer flows suggest permafrost thawing and are in agreement with the increasing trends in annual minimum flows. Trends in the selected flood percentiles showed an increase in extreme events over the entire period of record, while trends were variable under shorter periods. A thorough uncertainty analysis emphasized that the applied trend test is highly sensitive to the period of record considered. As such, no clear overall regional pattern could be determined suggesting that how catchments are responding to changes in climatic drivers is strongly influenced by their physical characteristics.

Subseasonal climate variability for North Carolina, United States

NASA Astrophysics Data System (ADS)

Sayemuzzaman, Mohammad; Jha, Manoj K.; Mekonnen, Ademe; Schimmel, Keith A.

2014-08-01

Subseasonal trends in climate variability for maximum temperature (Tmax), minimum temperature (Tmin) and precipitation were evaluated for 249 ground-based stations in North Carolina for 1950-2009. The magnitude and significance of the trends at all stations were determined using the non-parametric Theil-Sen Approach (TSA) and the Mann-Kendall (MK) test, respectively. The Sequential Mann-Kendall (SQMK) test was also applied to find the initiation of abrupt trend changes. The lag-1 serial correlation and double mass curve were employed to address the data independency and homogeneity. Using the MK trend test, statistically significant (confidence level ≥ 95% in two-tailed test) decreasing (increasing) trends by 44% (45%) of stations were found in May (June). In general, trends were decreased in Tmax and increased in Tmin data series in subseasonal scale. Using the TSA method, the magnitude of lowest (highest) decreasing (increasing) trend in Tmax is - 0.050 °C/year (+ 0.052 °C/year) in the monthly series for May (March) and for Tmin is - 0.055 °C/year (+ 0.075 °C/year) in February (December). For the precipitation time series using the TSA method, it was found that the highest (lowest) magnitude of 1.00 mm/year (- 1.20 mm/year) is in September (February). The overall trends in precipitation data series were not significant at the 95% confidence level except that 17% of stations were found to have significant (confidence level ≥ 95% in two-tailed test) decreasing trends in February. The statistically significant trend test results were used to develop a spatial distribution of trends: May for Tmax, June for Tmin, and February for precipitation. A correlative analysis of significant temperature and precipitation trend results was examined with respect to large scale circulation modes (North Atlantic Oscillation (NAO) and Southern Oscillation Index (SOI). A negative NAO index (positive-El Niño Southern Oscillation (ENSO) index) was found to be associated with the decreasing precipitation in February during 1960-1980 (2000-2009). The incremental trend in Tmin in the inter-seasonal (April-October) time scale can be associated with the positive NAO index during 1970-2000.

Evaluation of Health Economics in Radiation Oncology: A Systematic Review

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

Nguyen, Timothy K.; Goodman, Chris D.; Boldt, R. Gabriel

Purpose: Despite the rising costs in radiation oncology, the impact of health economics research on radiation therapy practice analysis patterns is unclear. We performed a systematic review of cost-effectiveness analyses (CEAs) and cost-utility analyses (CUAs) to identify trends in reporting quality in the radiation oncology literature over time. Methods and Materials: A systematic review of radiation oncology economic evaluations up to 2014 was performed, using MEDLINE and EMBASE databases. The Consolidated Health Economic Evaluation Reporting Standards guideline informed data abstraction variables including study demographics, economic parameters, and methodological details. Tufts Medical Center CEA registry quality scores provided a basis formore » qualitative assessment of included studies. Studies were stratified by 3 time periods (1995-2004, 2005-2009, and 2010-2014). The Cochran-Armitage trend test and linear trend test were used to identify trends over time. Results: In total, 102 articles were selected for final review. Most studies were in the context of a model (61%) or clinical trial (28%). Many studies lacked a conflict of interest (COI) statement (67%), a sponsorship statement (48%), a reported study time horizon (35%), and the use of discounting (29%). There was a significant increase over time in the reporting of a COI statement (P<.001), health care payer perspective (P=.019), sensitivity analyses using multivariate (P=.043) or probabilistic methods (P=.011), incremental cost-effectiveness threshold (P<.001), secondary source utility weights (P=.010), and cost effectiveness acceptability curves (P=.049). There was a trend toward improvement in Tuft scores over time (P=.065). Conclusions: Recent reports demonstrate improved reporting rates in economic evaluations; however, there remains significant room for improvement as reporting rates are still suboptimal. As fiscal pressures rise, we will rely on economic assessments to guide our practice decisions and policies. We recommend improved adherence to published guidelines and further research to determine the clinical implications of our findings.« less

The construction of a Central Netherlands temperature

NASA Astrophysics Data System (ADS)

van der Schrier, G.; van Ulden, A.; van Oldenborgh, G. J.

2011-05-01

The Central Netherlands Temperature (CNT) is a monthly daily mean temperature series constructed from homogenized time series from the centre of the Netherlands. The purpose of this series is to offer a homogeneous time series representative of a larger area in order to study large-scale temperature changes. It will also facilitate a comparison with climate models, which resolve similar scales. From 1906 onwards, temperature measurements in the Netherlands have been sufficiently standardized to construct a high-quality series. Long time series have been constructed by merging nearby stations and using the overlap to calibrate the differences. These long time series and a few time series of only a few decades in length have been subjected to a homogeneity analysis in which significant breaks and artificial trends have been corrected. Many of the detected breaks correspond to changes in the observations that are documented in the station metadata. This version of the CNT, to which we attach the version number 1.1, is constructed as the unweighted average of four stations (De Bilt, Winterswijk/Hupsel, Oudenbosch/Gilze-Rijen and Gemert/Volkel) with the stations Eindhoven and Deelen added from 1951 and 1958 onwards, respectively. The global gridded datasets used for detecting and attributing climate change are based on raw observational data. Although some homogeneity adjustments are made, these are not based on knowledge of local circumstances but only on statistical evidence. Despite this handicap, and the fact that these datasets use grid boxes that are far larger then the area associated with that of the Central Netherlands Temperature, the temperature interpolated to the CNT region shows a warming trend that is broadly consistent with the CNT trend in all of these datasets. The actual trends differ from the CNT trend up to 30 %, which highlights the need to base future global gridded temperature datasets on homogenized time series.

Evaluation of Health Economics in Radiation Oncology: A Systematic Review.

PubMed

Nguyen, Timothy K; Goodman, Chris D; Boldt, R Gabriel; Warner, Andrew; Palma, David A; Rodrigues, George B; Lock, Michael I; Mishra, Mark V; Zaric, Gregory S; Louie, Alexander V

2016-04-01

Despite the rising costs in radiation oncology, the impact of health economics research on radiation therapy practice analysis patterns is unclear. We performed a systematic review of cost-effectiveness analyses (CEAs) and cost-utility analyses (CUAs) to identify trends in reporting quality in the radiation oncology literature over time. A systematic review of radiation oncology economic evaluations up to 2014 was performed, using MEDLINE and EMBASE databases. The Consolidated Health Economic Evaluation Reporting Standards guideline informed data abstraction variables including study demographics, economic parameters, and methodological details. Tufts Medical Center CEA registry quality scores provided a basis for qualitative assessment of included studies. Studies were stratified by 3 time periods (1995-2004, 2005-2009, and 2010-2014). The Cochran-Armitage trend test and linear trend test were used to identify trends over time. In total, 102 articles were selected for final review. Most studies were in the context of a model (61%) or clinical trial (28%). Many studies lacked a conflict of interest (COI) statement (67%), a sponsorship statement (48%), a reported study time horizon (35%), and the use of discounting (29%). There was a significant increase over time in the reporting of a COI statement (P<.001), health care payer perspective (P=.019), sensitivity analyses using multivariate (P=.043) or probabilistic methods (P=.011), incremental cost-effectiveness threshold (P<.001), secondary source utility weights (P=.010), and cost effectiveness acceptability curves (P=.049). There was a trend toward improvement in Tuft scores over time (P=.065). Recent reports demonstrate improved reporting rates in economic evaluations; however, there remains significant room for improvement as reporting rates are still suboptimal. As fiscal pressures rise, we will rely on economic assessments to guide our practice decisions and policies. We recommend improved adherence to published guidelines and further research to determine the clinical implications of our findings. Copyright © 2016 Elsevier Inc. All rights reserved.

How well do CMIP5 climate simulations replicate historical trends and patterns of droughts?

DOE PAGES

Nasrollahi, Nasrin; AghaKouchak, Amir; Cheng, Linyin; ...

2015-04-26

Assessing the uncertainties and understanding the deficiencies of climate models are fundamental to developing adaptation strategies. The objective of this study is to understand how well Coupled Model Intercomparison-Phase 5 (CMIP5) climate model simulations replicate ground-based observations of continental drought areas and their trends. The CMIP5 multimodel ensemble encompasses the Climatic Research Unit (CRU) ground-based observations of area under drought at all time steps. However, most model members overestimate the areas under extreme drought, particularly in the Southern Hemisphere (SH). Furthermore, the results show that the time series of observations and CMIP5 simulations of areas under drought exhibit more variabilitymore » in the SH than in the Northern Hemisphere (NH). The trend analysis of areas under drought reveals that the observational data exhibit a significant positive trend at the significance level of 0.05 over all land areas. The observed trend is reproduced by about three-fourths of the CMIP5 models when considering total land areas in drought. While models are generally consistent with observations at a global (or hemispheric) scale, most models do not agree with observed regional drying and wetting trends. Over many regions, at most 40% of the CMIP5 models are in agreement with the trends of CRU observations. The drying/wetting trends calculated using the 3 months Standardized Precipitation Index (SPI) values show better agreement with the corresponding CRU values than with the observed annual mean precipitation rates. As a result, pixel-scale evaluation of CMIP5 models indicates that no single model demonstrates an overall superior performance relative to the other models.« less

Cohort Measures of Internal Migration: Understanding Long-Term Trends.

PubMed

Bernard, Aude

2017-12-01

Internal migration intensities fluctuate over time, but both migration levels and trends show great diversity. The dynamics underpinning these trends remain poorly understood because they are analyzed almost exclusively by applying period measures to cross-sectional data. This article proposes 10 cohort measures that can be applied to both prospective and retrospective data to systematically examine long-term trends. To demonstrate their benefits, the proposed measures are applied to retrospective survey data for England that provide residential histories from birth to age 50 for cohorts born between 1918 and 1957. The analysis reveals stable lifetime migration for men but increased lifetime migration for women associated with earlier ages at moving in adulthood and a compression of intervals between consecutive moves. The proposed cohort measures provide a more comprehensive picture of migration behavior and should be used to complement period measures in exploring long-term trends. Increasing availability of retrospective and longitudinal survey data means that researchers can now apply the proposed measures to a wide range of countries.

Farallon de Medinilla seabird and Tinian moorhen analyses

USGS Publications Warehouse

Camp, Richard J.; Leopold, Christina R.; Brinck, Kevin W.; Juola, Franz

2015-01-01

This report assesses the trends in brown booby (Sula leucogaster), masked booby (S. dactylatra), and red-footed booby (S. sula) counts collected on Farallon de Medinilla and Mariana common moorhen (Gallinula chloropus guami) counts on Tinian, Commonwealth of the Northern Mariana Islands to help elucidate patterns in bird numbers. During either monthly or quarterly surveys between 1997 and 2014 counts of all four bird species were recorded, generating a relatively noisy time series revealing inter-annual variation in index counts by as much as 1,000%. For the purposes of assessing long-term population trends across years we chose a single, species-specific month to assess trends. Doing so reduces the effect of intra-annual variation allowing the analysis to focus on inter-annual variation important to long-term trends assessment. There are clear fluctuations in the counts of all four species. Although the trends were non-significant, there is some evidence that masked and red-footed booby species have declined while brown booby and moorhen have increased.

Efficacy and safety of flavocoxid compared with naproxen in subjects with osteoarthritis of the knee- a subset analysis.

PubMed

Levy, Robert; Khokhlov, Alexander; Kopenkin, Sergey; Bart, Boris; Ermolova, Tatiana; Kantemirova, Raiasa; Mazurov, Vadim; Bell, Marjorie; Caldron, Paul; Pillai, Lakshmi; Burnett, Bruce

2010-12-01

twice-daily flavocoxid, a cyclooxygenase and 5-lipoxygenase inhibitor with potent antioxidant activity of botanical origin, was evaluated for 12 weeks in a randomized, double-blind, active-comparator study against naproxen in 220 subjects with moderate-severe osteoarthritis (OA) of the knee. As previously reported, both groups noted a significant reduction in the signs and symptoms of OA with no detectable differences in efficacy between the groups when the entire intent-to-treat population was considered. This post-hoc analysis compares the efficacy of flavocoxid to naproxen in different subsets of patients, specifically those related to age, gender, and disease severity as reported at baseline for individual response parameters. in the original randomized, double-blind study, 220 subjects were assigned to receive either flavocoxid (500 mg twice daily) or naproxen (500 mg twice daily) for 12 weeks. In this subgroup analysis, primary outcome measures including the Western Ontario and McMaster Universities OA index and subscales, timed walk, and secondary efficacy variables, including investigator global assessment for disease and global response to treatment, subject visual analog scale for discomfort, overall disease activity, global response to treatment, index joint tenderness and mobility, were evaluated for differing trends between the study groups. subset analyses revealed some statistically significant differences and some notable trends in favor of the flavocoxid group. These trends became stronger the longer the subjects continued on therapy. These observations were specifically noted in older subjects (>60 years), males and in subjects with milder disease, particularly those with lower subject global assessment of disease activity and investigator global assessment for disease and faster walking times at baseline. initial analysis of the entire intent-to-treat population revealed that flavocoxid was as effective as naproxen in managing the signs and symptoms of OA of the knee. Detailed analyses of subject subsets demonstrated distinct trends in favor of flavocoxid for specific groups of subjects.

Design of a Real-Time Ground-Water Level Monitoring Network and Portrayal of Hydrologic Data in Southern Florida

USGS Publications Warehouse

Prinos, Scott T.; Lietz, A.C.; Irvin, R.B.

2002-01-01

Ground-water resources in southern Florida are under increasing stress caused by a rapid growth in population. As a result of increased demands on aquifers, water managers need more timely and accurate assessments of ground-water conditions in order to avoid or reduce adverse effects such as saltwater intrusion, loss of pumpage in residential water-supply wells, land-surface subsidence, and aquifer compaction. Hydrologic data were analyzed from three aquifer systems in southern Florida: the surficial aquifer system, which includes the Biscayne aquifer; the intermediate aquifer system, which includes the sandstone and mid-Hawthorn aquifers; and the Florida aquifer system represented by the lower Hawthorn producing zone. Long-term water-level trends were analyzed using the Seasonal Kendall trend test in 83 monitoring wells with a daily-value record spanning 26 years (1974-99). The majority of the wells with data for this period were in the Biscayne aquifer in southeastern Florida. Only 14 wells in southwestern Florida aquifers and 9 in the surficial aquifer system of Martin and Palm Beach Counties had data for the full period. Because many monitoring wells did not have data for this full period, several shorter periods were evaluated as well. The trend tests revealed small but statistically significant upward trends in most aquifers, but large and localized downward trends in the sandstone and mid-Hawthorn aquifers. Monthly means of maximum daily water levels from 246 wells were compared to monthly rainfall totals from rainfall stations in southwestern and southeastern Florida in order to determine which monitoring wells most clearly indicated decreases in water levels that corresponded to prolonged rainfall shortages. Of this total, 104 wells had periods of record over 20 years (after considering missing record) and could be compared against several drought periods. After factors such as lag, seasonal cyclicity, and cumulative functions were considered, the timing of minimum values of water level from 15 ground-water monitoring wells and average minimum rainfall values agreed 57 to 62 percent of the time over a 20 to 26 year period. On average, the timing of water-level minimums and rainfall minimums agreed about 52 percent of the time, and in some cases only agreed 29 percent of the time. A regression analysis was used to evaluate daily water levels from 203 monitoring wells that are currently, or recently had been, part of the network to determine which wells were most representative of each aquifer. The regression also was used to determine which wells provided data that could be used to provide estimations of water levels at other wells in the aquifer with a coefficient of determination (R2 value) from the regression of 0.64 or greater. In all, the regression analysis alone indicated that 35 wells, generally with 10 years or more of data, could be used to directly monitor water levels or to estimate water levels at 180 of 203 wells (89 percent of the network). Ultimately, factors such as existing instrumentation, well construction, long-term water-level trends, and variations of water level and chloride concentration were considered together with the R2 results in designing the final network. The Seasonal Kendall trend test was used to examine trends in ground-water chloride concentrations in 113 wells. Of these wells, 61 showed statistically significant trends. Fifty-six percent (34 of 61 wells) of the observed trends in chloride concentration were upward and 44 percent (27 of 61 wells) were downward. The relation between water level and chloride concentration in 114 ground-water wells was examined using Spearman's r and Pearson's r correlation coefficients. Statistically significant results showed both positive and negative relations. Based on the results of statistical analyses, period of record, well construction, and existing satellite telemetry, 33 monitoring wells were selected that could be used to a

Adjustment of Pesticide Concentrations for Temporal Changes in Analytical Recovery, 1992-2006

USGS Publications Warehouse

Martin, Jeffrey D.; Stone, Wesley W.; Wydoski, Duane S.; Sandstrom, Mark W.

2009-01-01

Recovery is the proportion of a target analyte that is quantified by an analytical method and is a primary indicator of the analytical bias of a measurement. Recovery is measured by analysis of quality-control (QC) water samples that have known amounts of target analytes added ('spiked' QC samples). For pesticides, recovery is the measured amount of pesticide in the spiked QC sample expressed as percentage of the amount spiked, ideally 100 percent. Temporal changes in recovery have the potential to adversely affect time-trend analysis of pesticide concentrations by introducing trends in environmental concentrations that are caused by trends in performance of the analytical method rather than by trends in pesticide use or other environmental conditions. This report examines temporal changes in the recovery of 44 pesticides and 8 pesticide degradates (hereafter referred to as 'pesticides') that were selected for a national analysis of time trends in pesticide concentrations in streams. Water samples were analyzed for these pesticides from 1992 to 2006 by gas chromatography/mass spectrometry. Recovery was measured by analysis of pesticide-spiked QC water samples. Temporal changes in pesticide recovery were investigated by calculating robust, locally weighted scatterplot smooths (lowess smooths) for the time series of pesticide recoveries in 5,132 laboratory reagent spikes; 1,234 stream-water matrix spikes; and 863 groundwater matrix spikes. A 10-percent smoothing window was selected to show broad, 6- to 12-month time scale changes in recovery for most of the 52 pesticides. Temporal patterns in recovery were similar (in phase) for laboratory reagent spikes and for matrix spikes for most pesticides. In-phase temporal changes among spike types support the hypothesis that temporal change in method performance is the primary cause of temporal change in recovery. Although temporal patterns of recovery were in phase for most pesticides, recovery in matrix spikes was greater than recovery in reagent spikes for nearly every pesticide. Models of recovery based on matrix spikes are deemed more appropriate for adjusting concentrations of pesticides measured in groundwater and stream-water samples than models based on laboratory reagent spikes because (1) matrix spikes are expected to more closely match the matrix of environmental water samples than are reagent spikes and (2) method performance is often matrix dependent, as was shown by higher recovery in matrix spikes for most of the pesticides. Models of recovery, based on lowess smooths of matrix spikes, were developed separately for groundwater and stream-water samples. The models of recovery can be used to adjust concentrations of pesticides measured in groundwater or stream-water samples to 100 percent recovery to compensate for temporal changes in the performance (bias) of the analytical method.

Testing for intracycle determinism in pseudoperiodic time series.

PubMed

Coelho, Mara C S; Mendes, Eduardo M A M; Aguirre, Luis A

2008-06-01

A determinism test is proposed based on the well-known method of the surrogate data. Assuming predictability to be a signature of determinism, the proposed method checks for intracycle (e.g., short-term) determinism in the pseudoperiodic time series for which standard methods of surrogate analysis do not apply. The approach presented is composed of two steps. First, the data are preprocessed to reduce the effects of seasonal and trend components. Second, standard tests of surrogate analysis can then be used. The determinism test is applied to simulated and experimental pseudoperiodic time series and the results show the applicability of the proposed test.

Bibliometric analysis of authorship trends and collaboration dynamics over the past three decades of BONE's publication history.

PubMed

Khan, Faisal; Sandelski, Morgan M; Rytlewski, Jeffrey D; Lamb, Jennifer; Pedro, Christina; Adjei, Michael B N; Lunsford, Shatoria; Fischer, James P; Wininger, Austin E; Whipple, Elizabeth C; Loder, Randall T; Kacena, Melissa A

2018-02-01

The existence of a gender gap in academia has been a hotly debated topic over the past several decades. It has been argued that due to the gender gap, it is more difficult for women to obtain higher positions. Manuscripts serve as an important measurement of one's accomplishments within a particular field of academia. Here, we analyzed, over the past 3 decades, authorship and other trends in manuscripts published in BONE, one of the premier journals in the field of bone and mineral metabolism. For this study, one complete year of manuscripts was evaluated (e.g. 1985, 1995, 2005, 2015) for each decade. A bibliometric analysis was then performed of authorship trends for those manuscripts. Analyzed fields included: average number of authors per manuscript, numerical position of the corresponding author, number of institutions collaborating on each manuscript, number of countries involved with each manuscript, number of references, and number of citations per manuscript. Each of these fields increased significantly over the 30-year time frame (p<10 -6 ). The gender of both the first and corresponding authors was identified and analyzed over time and by region. There was a significant increase in the percentage of female first authors from 23.4% in 1985 to 47.8% in 2015 (p=0.001). The percentage of female corresponding authors also increased from 21.2% in 1985 to 35.4% in 2015 although it was not significant (p=0.07). With such a substantial emphasis being placed on publishing in academic medicine, it is crucial to comprehend the changes in publishing characteristics over time and geographical region. These findings highlight authorship trends in BONE over time as well as by region. Importantly, these findings also highlight where challenges still exist. Copyright © 2017 Elsevier Inc. All rights reserved.

Bibliometric Analysis of Gender Authorship Trends and Collaboration Dynamics Over 30 Years of Spine 1985 to 2015.

PubMed

Brinker, Alexander R; Liao, Jane L; Kraus, Kent R; Young, Jocelyn; Sandelski, Morgan; Mikesell, Carter; Robinson, Daniel; Adjei, Michael; Lunsford, Shatoria D; Fischer, James; Kacena, Melissa A; Whipple, Elizabeth C; Loder, Randall T

2018-07-15

A bibliometric analysis. The aim of this article was to study bibliometric changes over the last 30 years of Spine. These trends are important regarding academic publication productivity. Inflation in authorship number and other bibliometric variables has been described in the scientific literature. The issue of author gender is taking on increasing importance, as efforts are being made to close the gender gap. From 1985 to 2015, 10-year incremental data for several bibliometric variables were collected, including author gender. Standard bivariate statistical analyses were performed. Trends over time were assessed by the Cochran linear trend. A P < 0.05 was considered statistically significant. Inclusion criteria were met for 1566 manuscripts. The majority of the manuscripts were from North America (51.2%), Europe (25.2%), and Asia (20.8%). The number of manuscripts, authors, countries, pages, and references all increased from 1985 to 2015. There was a slight increase in female first authors over time (17.5% to 18.4%, P = 0.048). There was no gender change over time for corresponding authors (14.3% to 14.0%, P = 0.29). There was an 88% increase in the percentage of female first authors having male corresponding authors (P = 0.00004), and a 123% increase in male first authors having female corresponding authors (P = 0.0002). The 14% to 18% of female authors in Spine is higher than the ∼5% female membership of the Scoliosis Research Society and North American Spine Society. Manuscripts in Spine over the past 30 years have shown a significant increase in the number of authors, collaborating institutions and countries, printed pages, references, and number of times each manuscript was cited. There has been a mild increase in female first authorship, but none in corresponding authorship. Increases in female authorship will likely require recruitment of more females into the discipline rather than providing females in the discipline with authorship opportunities. N/A.

Measuring trends in age at first sex and age at marriage in Manicaland, Zimbabwe.

PubMed

Cremin, I; Mushati, P; Hallett, T; Mupambireyi, Z; Nyamukapa, C; Garnett, G P; Gregson, S

2009-04-01

To identify reporting biases and to determine the influence of inconsistent reporting on observed trends in the timing of age at first sex and age at marriage. Longitudinal data from three rounds of a population-based cohort in eastern Zimbabwe were analysed. Reports of age at first sex and age at marriage from 6837 individuals attending multiple rounds were classified according to consistency. Survival analysis was used to identify trends in the timing of first sex and marriage. In this population, women initiate sex and enter marriage at younger ages than men but spend much less time between first sex and marriage. Among those surveyed between 1998 and 2005, median ages at first sex and first marriage were 18.5 years and 21.4 years for men and 18.2 years and 18.5 years, respectively, for women aged 15-54 years. High levels of reports of both age at first sex and age at marriage among those attending multiple surveys were found to be unreliable. Excluding reports identified as unreliable from these analyses did not alter the observed trends in either age at first sex or age at marriage. Tracing birth cohorts as they aged revealed reporting biases, particularly among the youngest cohorts. Comparisons by birth cohorts, which span a period of >40 years, indicate that median age at first sex has remained constant over time for women but has declined gradually for men. Although many reports of age at first sex and age at marriage were found to be unreliable, inclusion of such reports did not result in artificial generation or suppression of trends.