Statistically significant relational data mining :

Energy Technology Data Exchange (ETDEWEB)

Berry, Jonathan W.; Leung, Vitus Joseph; Phillips, Cynthia Ann; Pinar, Ali; Robinson, David Gerald; Berger-Wolf, Tanya; Bhowmick, Sanjukta; Casleton, Emily; Kaiser, Mark; Nordman, Daniel J.; Wilson, Alyson G.

2014-02-01

This report summarizes the work performed under the project (3z(BStatitically significant relational data mining.(3y (BThe goal of the project was to add more statistical rigor to the fairly ad hoc area of data mining on graphs. Our goal was to develop better algorithms and better ways to evaluate algorithm quality. We concetrated on algorithms for community detection, approximate pattern matching, and graph similarity measures. Approximate pattern matching involves finding an instance of a relatively small pattern, expressed with tolerance, in a large graph of data observed with uncertainty. This report gathers the abstracts and references for the eight refereed publications that have appeared as part of this work. We then archive three pieces of research that have not yet been published. The first is theoretical and experimental evidence that a popular statistical measure for comparison of community assignments favors over-resolved communities over approximations to a ground truth. The second are statistically motivated methods for measuring the quality of an approximate match of a small pattern in a large graph. The third is a new probabilistic random graph model. Statisticians favor these models for graph analysis. The new local structure graph model overcomes some of the issues with popular models such as exponential random graph models and latent variable models.

Common pitfalls in statistical analysis: "P" values, statistical significance and confidence intervals

Directory of Open Access Journals (Sweden)

Priya Ranganathan

2015-01-01

Full Text Available In the second part of a series on pitfalls in statistical analysis, we look at various ways in which a statistically significant study result can be expressed. We debunk some of the myths regarding the ′P′ value, explain the importance of ′confidence intervals′ and clarify the importance of including both values in a paper

Drivers and seasonal predictability of extreme wind speeds in the ECMWF System 4 and a statistical model

Science.gov (United States)

Walz, M. A.; Donat, M.; Leckebusch, G. C.

2017-12-01

As extreme wind speeds are responsible for large socio-economic losses in Europe, a skillful prediction would be of great benefit for disaster prevention as well as for the actuarial community. Here we evaluate patterns of large-scale atmospheric variability and the seasonal predictability of extreme wind speeds (e.g. >95th percentile) in the European domain in the dynamical seasonal forecast system ECMWF System 4, and compare to the predictability based on a statistical prediction model. The dominant patterns of atmospheric variability show distinct differences between reanalysis and ECMWF System 4, with most patterns in System 4 extended downstream in comparison to ERA-Interim. The dissimilar manifestations of the patterns within the two models lead to substantially different drivers associated with the occurrence of extreme winds in the respective model. While the ECMWF System 4 is shown to provide some predictive power over Scandinavia and the eastern Atlantic, only very few grid cells in the European domain have significant correlations for extreme wind speeds in System 4 compared to ERA-Interim. In contrast, a statistical model predicts extreme wind speeds during boreal winter in better agreement with the observations. Our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world, and therefore fails to provide reliable seasonal predictions for lead months 2-4. This is likely related to the unrealistic representation of large-scale patterns of atmospheric variability. Hence our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric dynamics.

Seasonal UK Drought Forecasting using Statistical Methods

Science.gov (United States)

Richardson, Doug; Fowler, Hayley; Kilsby, Chris; Serinaldi, Francesco

2016-04-01

In the UK drought is a recurrent feature of climate with potentially large impacts on public water supply. Water companies' ability to mitigate the impacts of drought by managing diminishing availability depends on forward planning and it would be extremely valuable to improve forecasts of drought on monthly to seasonal time scales. By focusing on statistical forecasting methods, this research aims to provide techniques that are simpler, faster and computationally cheaper than physically based models. In general, statistical forecasting is done by relating the variable of interest (some hydro-meteorological variable such as rainfall or streamflow, or a drought index) to one or more predictors via some formal dependence. These predictors are generally antecedent values of the response variable or external factors such as teleconnections. A candidate model is Generalised Additive Models for Location, Scale and Shape parameters (GAMLSS). GAMLSS is a very flexible class allowing for more general distribution functions (e.g. highly skewed and/or kurtotic distributions) and the modelling of not just the location parameter but also the scale and shape parameters. Additionally GAMLSS permits the forecasting of an entire distribution, allowing the output to be assessed in probabilistic terms rather than simply the mean and confidence intervals. Exploratory analysis of the relationship between long-memory processes (e.g. large-scale atmospheric circulation patterns, sea surface temperatures and soil moisture content) and drought should result in the identification of suitable predictors to be included in the forecasting model, and further our understanding of the drivers of UK drought.

Seasonality of Kawasaki Disease: A Global Perspective

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Burns, Jane C.; Herzog, Lauren; Fabri, Olivia; Tremoulet, Adriana H.; Rodó, Xavier; Uehara, Ritei; Burgner, David; Bainto, Emelia; Pierce, David; Tyree, Mary; Cayan, Daniel

2013-01-01

Background Understanding global seasonal patterns of Kawasaki disease (KD) may provide insight into the etiology of this vasculitis that is now the most common cause of acquired heart disease in children in developed countries worldwide. Methods Data from 1970-2012 from 25 countries distributed over the globe were analyzed for seasonality. The number of KD cases from each location was normalized to minimize the influence of greater numbers from certain locations. The presence of seasonal variation of KD at the individual locations was evaluated using three different tests: time series modeling, spectral analysis, and a Monte Carlo technique. Results A defined seasonal structure emerged demonstrating broad coherence in fluctuations in KD cases across the Northern Hemisphere extra-tropical latitudes. In the extra-tropical latitudes of the Northern Hemisphere, KD case numbers were highest in January through March and approximately 40% higher than in the months of lowest case numbers from August through October. Datasets were much sparser in the tropics and the Southern Hemisphere extra-tropics and statistical significance of the seasonality tests was weak, but suggested a maximum in May through June, with approximately 30% higher number of cases than in the least active months of February, March and October. The seasonal pattern in the Northern Hemisphere extra-tropics was consistent across the first and second halves of the sample period. Conclusion Using the first global KD time series, analysis of sites located in the Northern Hemisphere extra-tropics revealed statistically significant and consistent seasonal fluctuations in KD case numbers with high numbers in winter and low numbers in late summer and fall. Neither the tropics nor the Southern Hemisphere extra-tropics registered a statistically significant aggregate seasonal cycle. These data suggest a seasonal exposure to a KD agent that operates over large geographic regions and is concentrated during winter

Recent Changes in the Arctic Melt Season

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Stroeve, Julienne; Markus, Thorsten; Meier, Walter N.; Miller, Jeff

2007-01-01

Melt-season duration, melt-onset and freeze-up dates are derived from satellite passive microwave data and analyzed from 1979 to 2005 over Arctic sea ice. Results indicate a shift towards a longer melt season, particularly north of Alaska and Siberia, corresponding to large retreats of sea ice observed in these regions. Although there is large interannual and regional variability in the length of the melt season, the Arctic is experiencing an overall lengthening of the melt season at a rate of about 2 weeks decade(sup -1). In fact, all regions in the Arctic (except for the central Arctic) have statistically significant (at the 99% level or higher) longer melt seasons by greater than 1 week decade(sup -1). The central Arctic shows a statistically significant trend (at the 98% level) of 5.4 days decade(sup -1). In 2005 the Arctic experienced its longest melt season, corresponding with the least amount of sea ice since 1979 and the warmest temperatures since the 1880s. Overall, the length of the melt season is inversely correlated with the lack of sea ice seen in September north of Alaska and Siberia, with a mean correlation of -0.8.

Health significance and statistical uncertainty. The value of P-value.

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Consonni, Dario; Bertazzi, Pier Alberto

2017-10-27

The P-value is widely used as a summary statistics of scientific results. Unfortunately, there is a widespread tendency to dichotomize its value in "P0.05" ("statistically not significant"), with the former implying a "positive" result and the latter a "negative" one. To show the unsuitability of such an approach when evaluating the effects of environmental and occupational risk factors. We provide examples of distorted use of P-value and of the negative consequences for science and public health of such a black-and-white vision. The rigid interpretation of P-value as a dichotomy favors the confusion between health relevance and statistical significance, discourages thoughtful thinking, and distorts attention from what really matters, the health significance. A much better way to express and communicate scientific results involves reporting effect estimates (e.g., risks, risks ratios or risk differences) and their confidence intervals (CI), which summarize and convey both health significance and statistical uncertainty. Unfortunately, many researchers do not usually consider the whole interval of CI but only examine if it includes the null-value, therefore degrading this procedure to the same P-value dichotomy (statistical significance or not). In reporting statistical results of scientific research present effects estimates with their confidence intervals and do not qualify the P-value as "significant" or "not significant".

Predicting foraging wading bird populations in Everglades National Park from seasonal hydrologic statistics under different management scenarios

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Kwon, Hyun-Han; Lall, Upmanu; Engel, Vic

2011-09-01

The ability to map relationships between ecological outcomes and hydrologic conditions in the Everglades National Park (ENP) is a key building block for their restoration program, a primary goal of which is to improve conditions for wading birds. This paper presents a model linking wading bird foraging numbers to hydrologic conditions in the ENP. Seasonal hydrologic statistics derived from a single water level recorder are well correlated with water depths throughout most areas of the ENP, and are effective as predictors of wading bird numbers when using a nonlinear hierarchical Bayesian model to estimate the conditional distribution of bird populations. Model parameters are estimated using a Markov chain Monte Carlo (MCMC) procedure. Parameter and model uncertainty is assessed as a byproduct of the estimation process. Water depths at the beginning of the nesting season, the average dry season water level, and the numbers of reversals from the dry season recession are identified as significant predictors, consistent with the hydrologic conditions considered important in the production and concentration of prey organisms in this system. Long-term hydrologic records at the index location allow for a retrospective analysis (1952-2006) of foraging bird numbers showing low frequency oscillations in response to decadal fluctuations in hydroclimatic conditions. Simulations of water levels at the index location used in the Bayesian model under alternative water management scenarios allow the posterior probability distributions of the number of foraging birds to be compared, thus providing a mechanism for linking management schemes to seasonal rainfall forecasts.

Common pitfalls in statistical analysis: “P” values, statistical significance and confidence intervals

Science.gov (United States)

Ranganathan, Priya; Pramesh, C. S.; Buyse, Marc

2015-01-01

In the second part of a series on pitfalls in statistical analysis, we look at various ways in which a statistically significant study result can be expressed. We debunk some of the myths regarding the ‘P’ value, explain the importance of ‘confidence intervals’ and clarify the importance of including both values in a paper PMID:25878958

Understanding the Sampling Distribution and Its Use in Testing Statistical Significance.

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Breunig, Nancy A.

Despite the increasing criticism of statistical significance testing by researchers, particularly in the publication of the 1994 American Psychological Association's style manual, statistical significance test results are still popular in journal articles. For this reason, it remains important to understand the logic of inferential statistics. A…

Significance of cold-season respiration and photosynthesis in a subarctic heath ecosystem in Northern Sweden

DEFF Research Database (Denmark)

Larsen, Klaus Steenberg; Ibrom, Andreas; Jonasson, S.

2007-01-01

While substantial cold-season respiration has been documented in most arctic and alpine ecosystems in recent years, the significance of cold-season photosynthesis in these biomes is still believed to be small. In a mesic, subartic heath during both the cold and warm season, we measured in situ...... ecosystem respiration and photosynthesis with a chamber technique at ambient conditions and at artificially, increased frequency of freeze-thaw (FT) cycles during fall and spring. We fitted the measured ecosystem exchange rates to respiration and photosynthesis models with R-2-values ranging from 0.81 to 0.......85. As expected, estimated cold-season (October, November, April and May) respiration was significant and accounted for at least 22% of the annual respiratory CO2 flux. More surprisingly, estimated photosynthesis during this period accounted for up to 19% of the annual gross CO2 uptake, suggesting that cold...

Seasonality in the Austrian Economy: Common Seasonals and Forecasting

OpenAIRE

Kunst, Robert M.

1992-01-01

Abstract: Seasonal cointegration generalizes the idea of cointegration to processes with unit roots at frequencies different from 0. Here, also the dual notion of common trends, "common seasonals", is adopted for the seasonal case. Using a five-variable macroeconomic core system of the Austrian economy, it is demonstrated how common seasonals and seasonal cointegrating vectors look in practice. Statistical tests provide clear evidence on seasonal cointegration in the system. However, it is sh...

Statistical post-processing of seasonal multi-model forecasts: Why is it so hard to beat the multi-model mean?

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Siegert, Stefan

2017-04-01

Initialised climate forecasts on seasonal time scales, run several months or even years ahead, are now an integral part of the battery of products offered by climate services world-wide. The availability of seasonal climate forecasts from various modeling centres gives rise to multi-model ensemble forecasts. Post-processing such seasonal-to-decadal multi-model forecasts is challenging 1) because the cross-correlation structure between multiple models and observations can be complicated, 2) because the amount of training data to fit the post-processing parameters is very limited, and 3) because the forecast skill of numerical models tends to be low on seasonal time scales. In this talk I will review new statistical post-processing frameworks for multi-model ensembles. I will focus particularly on Bayesian hierarchical modelling approaches, which are flexible enough to capture commonly made assumptions about collective and model-specific biases of multi-model ensembles. Despite the advances in statistical methodology, it turns out to be very difficult to out-perform the simplest post-processing method, which just recalibrates the multi-model ensemble mean by linear regression. I will discuss reasons for this, which are closely linked to the specific characteristics of seasonal multi-model forecasts. I explore possible directions for improvements, for example using informative priors on the post-processing parameters, and jointly modelling forecasts and observations.

Swiss solar power statistics 2007 - Significant expansion

International Nuclear Information System (INIS)

Hostettler, T.

2008-01-01

This article presents and discusses the 2007 statistics for solar power in Switzerland. A significant number of new installations is noted as is the high production figures from newer installations. The basics behind the compilation of the Swiss solar power statistics are briefly reviewed and an overview for the period 1989 to 2007 is presented which includes figures on the number of photovoltaic plant in service and installed peak power. Typical production figures in kilowatt-hours (kWh) per installed kilowatt-peak power (kWp) are presented and discussed for installations of various sizes. Increased production after inverter replacement in older installations is noted. Finally, the general political situation in Switzerland as far as solar power is concerned are briefly discussed as are international developments.

Test for the statistical significance of differences between ROC curves

International Nuclear Information System (INIS)

Metz, C.E.; Kronman, H.B.

1979-01-01

A test for the statistical significance of observed differences between two measured Receiver Operating Characteristic (ROC) curves has been designed and evaluated. The set of observer response data for each ROC curve is assumed to be independent and to arise from a ROC curve having a form which, in the absence of statistical fluctuations in the response data, graphs as a straight line on double normal-deviate axes. To test the significance of an apparent difference between two measured ROC curves, maximum likelihood estimates of the two parameters of each curve and the associated parameter variances and covariance are calculated from the corresponding set of observer response data. An approximate Chi-square statistic with two degrees of freedom is then constructed from the differences between the parameters estimated for each ROC curve and from the variances and covariances of these estimates. This statistic is known to be truly Chi-square distributed only in the limit of large numbers of trials in the observer performance experiments. Performance of the statistic for data arising from a limited number of experimental trials was evaluated. Independent sets of rating scale data arising from the same underlying ROC curve were paired, and the fraction of differences found (falsely) significant was compared to the significance level, α, used with the test. Although test performance was found to be somewhat dependent on both the number of trials in the data and the position of the underlying ROC curve in the ROC space, the results for various significance levels showed the test to be reliable under practical experimental conditions

The value of model averaging and dynamical climate model predictions for improving statistical seasonal streamflow forecasts over Australia

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Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.

2013-10-01

Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.

Nongrowing season methane emissions-a significant component of annual emissions across northern ecosystems.

Science.gov (United States)

Treat, Claire C; Bloom, A Anthony; Marushchak, Maija E

2018-03-22

Wetlands are the single largest natural source of atmospheric methane (CH 4 ), a greenhouse gas, and occur extensively in the northern hemisphere. Large discrepancies remain between "bottom-up" and "top-down" estimates of northern CH 4 emissions. To explore whether these discrepancies are due to poor representation of nongrowing season CH 4 emissions, we synthesized nongrowing season and annual CH 4 flux measurements from temperate, boreal, and tundra wetlands and uplands. Median nongrowing season wetland emissions ranged from 0.9 g/m 2 in bogs to 5.2 g/m 2 in marshes and were dependent on moisture, vegetation, and permafrost. Annual wetland emissions ranged from 0.9 g m -2  year -1 in tundra bogs to 78 g m -2  year -1 in temperate marshes. Uplands varied from CH 4 sinks to CH 4 sources with a median annual flux of 0.0 ± 0.2 g m -2  year -1 . The measured fraction of annual CH 4 emissions during the nongrowing season (observed: 13% to 47%) was significantly larger than that was predicted by two process-based model ensembles, especially between 40° and 60°N (modeled: 4% to 17%). Constraining the model ensembles with the measured nongrowing fraction increased total nongrowing season and annual CH 4 emissions. Using this constraint, the modeled nongrowing season wetland CH 4 flux from >40° north was 6.1 ± 1.5 Tg/year, three times greater than the nongrowing season emissions of the unconstrained model ensemble. The annual wetland CH 4 flux was 37 ± 7 Tg/year from the data-constrained model ensemble, 25% larger than the unconstrained ensemble. Considering nongrowing season processes is critical for accurately estimating CH 4 emissions from high-latitude ecosystems, and necessary for constraining the role of wetland emissions in a warming climate. © 2018 John Wiley & Sons Ltd.

On detection and assessment of statistical significance of Genomic Islands

Directory of Open Access Journals (Sweden)

Chaudhuri Probal

2008-04-01

Full Text Available Abstract Background Many of the available methods for detecting Genomic Islands (GIs in prokaryotic genomes use markers such as transposons, proximal tRNAs, flanking repeats etc., or they use other supervised techniques requiring training datasets. Most of these methods are primarily based on the biases in GC content or codon and amino acid usage of the islands. However, these methods either do not use any formal statistical test of significance or use statistical tests for which the critical values and the P-values are not adequately justified. We propose a method, which is unsupervised in nature and uses Monte-Carlo statistical tests based on randomly selected segments of a chromosome. Such tests are supported by precise statistical distribution theory, and consequently, the resulting P-values are quite reliable for making the decision. Results Our algorithm (named Design-Island, an acronym for Detection of Statistically Significant Genomic Island runs in two phases. Some 'putative GIs' are identified in the first phase, and those are refined into smaller segments containing horizontally acquired genes in the refinement phase. This method is applied to Salmonella typhi CT18 genome leading to the discovery of several new pathogenicity, antibiotic resistance and metabolic islands that were missed by earlier methods. Many of these islands contain mobile genetic elements like phage-mediated genes, transposons, integrase and IS elements confirming their horizontal acquirement. Conclusion The proposed method is based on statistical tests supported by precise distribution theory and reliable P-values along with a technique for visualizing statistically significant islands. The performance of our method is better than many other well known methods in terms of their sensitivity and accuracy, and in terms of specificity, it is comparable to other methods.

Increasing the statistical significance of entanglement detection in experiments.

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Jungnitsch, Bastian; Niekamp, Sönke; Kleinmann, Matthias; Gühne, Otfried; Lu, He; Gao, Wei-Bo; Chen, Yu-Ao; Chen, Zeng-Bing; Pan, Jian-Wei

2010-05-28

Entanglement is often verified by a violation of an inequality like a Bell inequality or an entanglement witness. Considerable effort has been devoted to the optimization of such inequalities in order to obtain a high violation. We demonstrate theoretically and experimentally that such an optimization does not necessarily lead to a better entanglement test, if the statistical error is taken into account. Theoretically, we show for different error models that reducing the violation of an inequality can improve the significance. Experimentally, we observe this phenomenon in a four-photon experiment, testing the Mermin and Ardehali inequality for different levels of noise. Furthermore, we provide a way to develop entanglement tests with high statistical significance.

Testing the Difference of Correlated Agreement Coefficients for Statistical Significance

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Gwet, Kilem L.

2016-01-01

This article addresses the problem of testing the difference between two correlated agreement coefficients for statistical significance. A number of authors have proposed methods for testing the difference between two correlated kappa coefficients, which require either the use of resampling methods or the use of advanced statistical modeling…

Seasonal Variability of Airborne Particulate Matter and Bacterial Concentrations in Colorado Homes

Directory of Open Access Journals (Sweden)

Nicholas Clements

2018-04-01

Full Text Available Aerosol measurements were collected at fifteen homes over the course of one year in Colorado (USA to understand the temporal variability of indoor air particulate matter and bacterial concentrations and their relationship with home characteristics, inhabitant activities, and outdoor air particulate matter (PM. Indoor and outdoor PM2.5 concentrations averaged (±st. dev. 8.1 ± 8.1 μg/m3 and 6.8 ± 4.5 μg/m3, respectively. Indoor PM2.5 was statistically significantly higher during summer compared to spring and winter; outdoor PM2.5 was significantly higher for summer compared to spring and fall. The PM2.5 I/O ratio was 1.6 ± 2.4 averaged across all homes and seasons and was not statistically significantly different across the seasons. Average indoor PM10 was 15.4 ± 18.3 μg/m3 and was significantly higher during summer compared to all other seasons. Total suspended particulate bacterial biomass, as determined by qPCR, revealed very little seasonal differences across and within the homes. The qPCR I/O ratio was statistically different across seasons, with the highest I/O ratio in the spring and lowest in the summer. Using one-minute indoor PM10 data and activity logs, it was observed that elevated particulate concentrations commonly occurred when inhabitants were cooking and during periods with elevated outdoor concentrations.

Statistical Significance for Hierarchical Clustering

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Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Statistical Seasonal Rainfall Forecast in the Neuquén River Basin (Comahue Region, Argentina

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Marcela Hebe González

2015-05-01

Full Text Available A detailed statistical analysis was performed at the Neuquén river basin using precipitation data for 1980–2007. The hydrological year begins in March with a maximum in June associated with rainfall and another relative maximum in October derived from snow-break. General features of the rainy season and the excess or deficits thereof are analyzed using standardized precipitation index (SPI for a six-month period in the basin. The SPI has a significant cycle of 14.3 years; the most severe excess (SPI greater than 2 has a return period of 25 years, while the most severe droughts (SPI less than −2 have a return period of 10 years. The SPI corresponding to the rainy season (April–September (SPI9 has no significant trend and is used to classify wet/dry years. In order to establish the previous circulation patterns associated with interannual SPI9 variability, the composite fields of wet and dry years are compared. There is a tendency for wet (dry periods to take place during El Niño (La Niña years, when there are positive anomalies of precipitable water over the basin, when the zonal flow over the Pacific Ocean is weakened (intensified and/or when there are negative pressure anomalies in the southern part of the country and Antarctic sea. Some prediction schemes using multiple linear regressions were performed. One of the models derived using the forward stepwise method explained 42% of the SPI9 variance and retained two predictors related to circulation over the Pacific Ocean: one of them shows the relevance of the intensity of zonal flow in mid-latitudes, and the other is because of the influence of low pressure near the Neuquén River basin. The cross-validation used to prove model efficiency showed a correlation of 0.41 between observed and estimated SPI9; there was a probability of detection of wet (dry years of 80% (65% and a false alarm relation of 25% in both cases.

Seasonal variations of volcanic eruption frequencies

Science.gov (United States)

Stothers, Richard B.

1989-01-01

Do volcanic eruptions have a tendency to occur more frequently in the months of May and June? Some past evidence suggests that they do. The present study, based on the new eruption catalog of Simkin et al.(1981), investigates the monthly statistics of the largest eruptions, grouped according to explosive magnitude, geographical latitude, and year. At the 2-delta level, no month-to-month variations in eruption frequency are found to be statistically significant. Examination of previously published month-to-month variations suggests that they, too, are not statistically significant. It is concluded that volcanism, at least averaged over large portions of the globe, is probably not periodic on a seasonal or annual time scale.

Statistical significance of trends in monthly heavy precipitation over the US

KAUST Repository

Mahajan, Salil

2011-05-11

Trends in monthly heavy precipitation, defined by a return period of one year, are assessed for statistical significance in observations and Global Climate Model (GCM) simulations over the contiguous United States using Monte Carlo non-parametric and parametric bootstrapping techniques. The results from the two Monte Carlo approaches are found to be similar to each other, and also to the traditional non-parametric Kendall\\'s τ test, implying the robustness of the approach. Two different observational data-sets are employed to test for trends in monthly heavy precipitation and are found to exhibit consistent results. Both data-sets demonstrate upward trends, one of which is found to be statistically significant at the 95% confidence level. Upward trends similar to observations are observed in some climate model simulations of the twentieth century, but their statistical significance is marginal. For projections of the twenty-first century, a statistically significant upwards trend is observed in most of the climate models analyzed. The change in the simulated precipitation variance appears to be more important in the twenty-first century projections than changes in the mean precipitation. Stochastic fluctuations of the climate-system are found to be dominate monthly heavy precipitation as some GCM simulations show a downwards trend even in the twenty-first century projections when the greenhouse gas forcings are strong. © 2011 Springer-Verlag.

Statistical prediction of seasonal discharge in the Naryn basin for water resources planning in Central Asia

Science.gov (United States)

Apel, Heiko; Gafurov, Abror; Gerlitz, Lars; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Merkushkin, Aleksandr; Merz, Bruno

2016-04-01

The semi-arid regions of Central Asia crucially depend on the water resources supplied by the mountainous areas of the Tien-Shan and Pamirs. During the summer months the snow and glacier melt water of the rivers originating in the mountains provides the only water resource available for agricultural production but also for water collection in reservoirs for energy production in winter months. Thus a reliable seasonal forecast of the water resources is crucial for a sustainable management and planning of water resources.. In fact, seasonal forecasts are mandatory tasks of national hydro-meteorological services in the region. Thus this study aims at a statistical forecast of the seasonal water availability, whereas the focus is put on the usage of freely available data in order to facilitate an operational use without data access limitations. The study takes the Naryn basin as a test case, at which outlet the Toktogul reservoir stores the discharge of the Naryn River. As most of the water originates form snow and glacier melt, a statistical forecast model should use data sets that can serve as proxy data for the snow masses and snow water equivalent in late spring, which essentially determines the bulk of the seasonal discharge. CRU climate data describing the precipitation and temperature in the basin during winter and spring was used as base information, which was complemented by MODIS snow cover data processed through ModSnow tool, discharge during the spring and also GRACE gravimetry anomalies. For the construction of linear forecast models monthly as well as multi-monthly means over the period January to April were used to predict the seasonal mean discharge of May-September at the station Uchterek. An automatic model selection was performed in multiple steps, whereas the best models were selected according to several performance measures and their robustness in a leave-one-out cross validation. It could be shown that the seasonal discharge can be predicted with

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance.

Science.gov (United States)

Kramer, Karen L; Veile, Amanda; Otárola-Castillo, Erik

2016-01-01

Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger siblings can have on young children's growth. Additionally, inconsistent results might reflect that the biological significance associated with different growth trajectories is poorly understood. This paper addresses these concerns by tracking children's monthly gains in height and weight from weaning to age five in a high fertility Maya community. We predict that: 1) as an aggregate measure family size will not have a major impact on child growth during the post weaning period; 2) competition from young siblings will negatively impact child growth during the post weaning period; 3) however because of their economic value, older siblings will have a negligible effect on young children's growth. Accounting for parental condition, we use linear mixed models to evaluate the effects that family size, younger and older siblings have on children's growth. Congruent with our expectations, it is younger siblings who have the most detrimental effect on children's growth. While we find statistical evidence of a quantity/quality tradeoff effect, the biological significance of these results is negligible in early childhood. Our findings help to resolve why quantity/quality studies have had inconsistent results by showing that sibling competition varies with sibling age composition, not just family size, and that biological significance is distinct from statistical significance.

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance.

Directory of Open Access Journals (Sweden)

Karen L Kramer

Full Text Available Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger siblings can have on young children's growth. Additionally, inconsistent results might reflect that the biological significance associated with different growth trajectories is poorly understood. This paper addresses these concerns by tracking children's monthly gains in height and weight from weaning to age five in a high fertility Maya community. We predict that: 1 as an aggregate measure family size will not have a major impact on child growth during the post weaning period; 2 competition from young siblings will negatively impact child growth during the post weaning period; 3 however because of their economic value, older siblings will have a negligible effect on young children's growth. Accounting for parental condition, we use linear mixed models to evaluate the effects that family size, younger and older siblings have on children's growth. Congruent with our expectations, it is younger siblings who have the most detrimental effect on children's growth. While we find statistical evidence of a quantity/quality tradeoff effect, the biological significance of these results is negligible in early childhood. Our findings help to resolve why quantity/quality studies have had inconsistent results by showing that sibling competition varies with sibling age composition, not just family size, and that biological significance is distinct from statistical significance.

Increasing the statistical significance of entanglement detection in experiments

Energy Technology Data Exchange (ETDEWEB)

Jungnitsch, Bastian; Niekamp, Soenke; Kleinmann, Matthias; Guehne, Otfried [Institut fuer Quantenoptik und Quanteninformation, Innsbruck (Austria); Lu, He; Gao, Wei-Bo; Chen, Zeng-Bing [Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei (China); Chen, Yu-Ao; Pan, Jian-Wei [Hefei National Laboratory for Physical Sciences at Microscale and Department of Modern Physics, University of Science and Technology of China, Hefei (China); Physikalisches Institut, Universitaet Heidelberg (Germany)

2010-07-01

Entanglement is often verified by a violation of an inequality like a Bell inequality or an entanglement witness. Considerable effort has been devoted to the optimization of such inequalities in order to obtain a high violation. We demonstrate theoretically and experimentally that such an optimization does not necessarily lead to a better entanglement test, if the statistical error is taken into account. Theoretically, we show for different error models that reducing the violation of an inequality can improve the significance. We show this to be the case for an error model in which the variance of an observable is interpreted as its error and for the standard error model in photonic experiments. Specifically, we demonstrate that the Mermin inequality yields a Bell test which is statistically more significant than the Ardehali inequality in the case of a photonic four-qubit state that is close to a GHZ state. Experimentally, we observe this phenomenon in a four-photon experiment, testing the above inequalities for different levels of noise.

Reporting effect sizes as a supplement to statistical significance ...

African Journals Online (AJOL)

The purpose of the article is to review the statistical significance reporting practices in reading instruction studies and to provide guidelines for when to calculate and report effect sizes in educational research. A review of six readily accessible (online) and accredited journals publishing research on reading instruction ...

Statistical estimates of absenteeism attributable to seasonal and pandemic influenza from the Canadian Labour Force Survey

OpenAIRE

Zheng Hui; Schanzer Dena L; Gilmore Jason

2011-01-01

Abstract Background As many respiratory viruses are responsible for influenza like symptoms, accurate measures of the disease burden are not available and estimates are generally based on statistical methods. The objective of this study was to estimate absenteeism rates and hours lost due to seasonal influenza and compare these estimates with estimates of absenteeism attributable to the two H1N1 pandemic waves that occurred in 2009. Methods Key absenteeism variables were extracted from Statis...

Your Chi-Square Test Is Statistically Significant: Now What?

Science.gov (United States)

Sharpe, Donald

2015-01-01

Applied researchers have employed chi-square tests for more than one hundred years. This paper addresses the question of how one should follow a statistically significant chi-square test result in order to determine the source of that result. Four approaches were evaluated: calculating residuals, comparing cells, ransacking, and partitioning. Data…

Decreasing but still significant facilitation effect of cold-season macrophytes on wetlands purification function during cold winter.

Science.gov (United States)

Zou, Xiangxu; Zhang, Hui; Zuo, Jie; Wang, Penghe; Zhao, Dehua; An, Shuqing

2016-06-01

To identify the facilitation effect of a cool-season aquatic macrophyte (FEam) for use in effluent purification via constructed floating wetlands (CFWs) and to determine the possible pathways used during a winter period with an average temperature of less than 5 °C, pilot-scale CFWs were planted with the cold-season macrophyte Oenanthe clecumbens and were operated as batch systems. Although some leaves withered, the roots retained relatively high levels of activity during the winter, which had average air and water temperatures of 3.63 and 5.04 °C, respectively. The N and P removal efficiencies in CFWs decreased significantly in winter relative to those in late autumn. The presence of cool-season plants resulted in significant improvements in N and P removal, with a FEam of 15.23-25.86% in winter. Microbial N removal accounted for 71.57% of the total N removed in winter, and the decrease in plant uptake was the dominant factor in the wintertime decrease in N removal relative to that in late autumn. These results demonstrate the importance of cold-season plants in CFWs for the treatment of secondary effluent during cold winters.

Diurnal and Seasonal Statistical Characteristics of Well-formed Plasma Depletion and Enhancement Plumes under Quiet Solar Conditions

Science.gov (United States)

Haaser, R. A.

2011-12-01

The Ion Velocity Meter (IVM), a part of the Coupled Ion Neutral Dynamics Investigation (CINDI) aboard the Communication/ Navigation Outage Forecasting System (C/NOFS) satellite, is used to measure in situ ion densities and drifts at altitudes between 400 and 550 km during the nighttime hours from 2100 to 300 local time. A new approach to detecting and classifying well-formed ionospheric plasma depletion and enhancement plumes (bubbles and blobs) of scale sizes between 50 and 500 km is used to develop geophysical statistics for the summer, winter and equinox seasons of the quiet solar conditions during 2009 and 2010. Some diurnal and seasonal geomagnetic distribution characteristics confirm previous work on irregularities and scintillations, while others reveal new behaviors that require additional observations and modeling to promote full understanding.

Seasonal variation of radon concentrations in UK homes

International Nuclear Information System (INIS)

Miles, J C H; Howarth, C B; Hunter, N

2012-01-01

The patterns of seasonal variation of radon concentrations were measured in 91 homes in five regions of the UK over a period of two years. The results showed that there was no significant difference between the regions in the pattern or magnitude of seasonal variation in radon concentrations. The arithmetic mean variation was found to be close to that found previously in the UK national survey. Differences in the pattern between the two years of the study were not significant. Two-thirds of homes in the study followed the expected pattern of high radon in the winter and low radon in the summer. Most of the rest showed little seasonal variation, and a few showed a reversed seasonal pattern. The study does not provide any clear evidence for the recorded house characteristics having an effect on the seasonal variation in radon concentrations in UK homes, though the statistical power for determining such effects is limited in this study. The magnitude of the seasonal variation varied widely between homes. Analysis of the individual results from the homes showed that because of the wide variation in the amount of seasonal variation, applying seasonal correction factors to the results of three-month measurements can yield only relatively small improvements in the accuracy of estimates of annual mean concentrations.

Confidence intervals permit, but don't guarantee, better inference than statistical significance testing

Directory of Open Access Journals (Sweden)

Melissa Coulson

2010-07-01

Full Text Available A statistically significant result, and a non-significant result may differ little, although significance status may tempt an interpretation of difference. Two studies are reported that compared interpretation of such results presented using null hypothesis significance testing (NHST, or confidence intervals (CIs. Authors of articles published in psychology, behavioural neuroscience, and medical journals were asked, via email, to interpret two fictitious studies that found similar results, one statistically significant, and the other non-significant. Responses from 330 authors varied greatly, but interpretation was generally poor, whether results were presented as CIs or using NHST. However, when interpreting CIs respondents who mentioned NHST were 60% likely to conclude, unjustifiably, the two results conflicted, whereas those who interpreted CIs without reference to NHST were 95% likely to conclude, justifiably, the two results were consistent. Findings were generally similar for all three disciplines. An email survey of academic psychologists confirmed that CIs elicit better interpretations if NHST is not invoked. Improved statistical inference can result from encouragement of meta-analytic thinking and use of CIs but, for full benefit, such highly desirable statistical reform requires also that researchers interpret CIs without recourse to NHST.

Statistical-Dynamical Seasonal Forecasts of Central-Southwest Asian Winter Precipitation.

Science.gov (United States)

Tippett, Michael K.; Goddard, Lisa; Barnston, Anthony G.

2005-06-01

Interannual precipitation variability in central-southwest (CSW) Asia has been associated with East Asian jet stream variability and western Pacific tropical convection. However, atmospheric general circulation models (AGCMs) forced by observed sea surface temperature (SST) poorly simulate the region's interannual precipitation variability. The statistical-dynamical approach uses statistical methods to correct systematic deficiencies in the response of AGCMs to SST forcing. Statistical correction methods linking model-simulated Indo-west Pacific precipitation and observed CSW Asia precipitation result in modest, but statistically significant, cross-validated simulation skill in the northeast part of the domain for the period from 1951 to 1998. The statistical-dynamical method is also applied to recent (winter 1998/99 to 2002/03) multimodel, two-tier December-March precipitation forecasts initiated in October. This period includes 4 yr (winter of 1998/99 to 2001/02) of severe drought. Tercile probability forecasts are produced using ensemble-mean forecasts and forecast error estimates. The statistical-dynamical forecasts show enhanced probability of below-normal precipitation for the four drought years and capture the return to normal conditions in part of the region during the winter of 2002/03.May Kabul be without gold, but not without snow.—Traditional Afghan proverb

Testing statistical significance scores of sequence comparison methods with structure similarity

Directory of Open Access Journals (Sweden)

Leunissen Jack AM

2006-10-01

Full Text Available Abstract Background In the past years the Smith-Waterman sequence comparison algorithm has gained popularity due to improved implementations and rapidly increasing computing power. However, the quality and sensitivity of a database search is not only determined by the algorithm but also by the statistical significance testing for an alignment. The e-value is the most commonly used statistical validation method for sequence database searching. The CluSTr database and the Protein World database have been created using an alternative statistical significance test: a Z-score based on Monte-Carlo statistics. Several papers have described the superiority of the Z-score as compared to the e-value, using simulated data. We were interested if this could be validated when applied to existing, evolutionary related protein sequences. Results All experiments are performed on the ASTRAL SCOP database. The Smith-Waterman sequence comparison algorithm with both e-value and Z-score statistics is evaluated, using ROC, CVE and AP measures. The BLAST and FASTA algorithms are used as reference. We find that two out of three Smith-Waterman implementations with e-value are better at predicting structural similarities between proteins than the Smith-Waterman implementation with Z-score. SSEARCH especially has very high scores. Conclusion The compute intensive Z-score does not have a clear advantage over the e-value. The Smith-Waterman implementations give generally better results than their heuristic counterparts. We recommend using the SSEARCH algorithm combined with e-values for pairwise sequence comparisons.

Birth seasonality in Korean Prader-Willi syndrome with chromosome 15 microdeletion

Directory of Open Access Journals (Sweden)

Aram Yang

2015-03-01

Full Text Available PurposePrader-Willi syndrome (PWS is a well-known genetic disorder, and microdeletion on chromosome 15 is the most common causal mechanism. Several previous studies have suggested that various environmental factors might be related to the pathogenesis of microdeletion in PWS. In this study, we investigated birth seasonality in Korean PWS.MethodsA total of 211 PWS patients born from 1980 to 2014 were diagnosed by methylation polymerase chain reaction at Samsung Medical Center. Of the 211 patients, 138 were born from 2000-2013. Among them, the 74 patients of a deletion group and the 22 patients of a maternal uniparental disomy (UPD group were compared with general populations born from 2000 using the Walter and Elwood method and cosinor analysis.ResultsThere was no statistical significance in seasonal variation in births of the total 211 patients with PWS (χ2=7.2522, P=0.2982. However, a significant difference was found in the monthly variation between PWS with the deletion group and the at-risk general population (P<0.05. In the cosinor model, the peak month of birth for PWS patients in the deletion group was January, while the nadir occurred in July, with statistical significance (amplitude=0.23, phase=1.2, low point=7.2. The UPD group showed the peak birth month in spring; however, this result was not statistically significant (χ2=3.39, P=0.1836.ConclusionCorrelation with birth seasonality was identified in a deletion group of Korean PWS patients. Further studies are required to identify the mechanism related to seasonal effects of environmental factors on microdeletion on chromosome 15.

Statistical significance versus clinical relevance.

Science.gov (United States)

van Rijn, Marieke H C; Bech, Anneke; Bouyer, Jean; van den Brand, Jan A J G

2017-04-01

In March this year, the American Statistical Association (ASA) posted a statement on the correct use of P-values, in response to a growing concern that the P-value is commonly misused and misinterpreted. We aim to translate these warnings given by the ASA into a language more easily understood by clinicians and researchers without a deep background in statistics. Moreover, we intend to illustrate the limitations of P-values, even when used and interpreted correctly, and bring more attention to the clinical relevance of study findings using two recently reported studies as examples. We argue that P-values are often misinterpreted. A common mistake is saying that P < 0.05 means that the null hypothesis is false, and P ≥0.05 means that the null hypothesis is true. The correct interpretation of a P-value of 0.05 is that if the null hypothesis were indeed true, a similar or more extreme result would occur 5% of the times upon repeating the study in a similar sample. In other words, the P-value informs about the likelihood of the data given the null hypothesis and not the other way around. A possible alternative related to the P-value is the confidence interval (CI). It provides more information on the magnitude of an effect and the imprecision with which that effect was estimated. However, there is no magic bullet to replace P-values and stop erroneous interpretation of scientific results. Scientists and readers alike should make themselves familiar with the correct, nuanced interpretation of statistical tests, P-values and CIs. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Seasonal affective disorder and non-seasonal affective disorders : Results from the NESDA study

NARCIS (Netherlands)

Winthorst, Wim H; Roest, Annelieke M; Bos, Elisabeth H; Meesters, Ybe; Penninx, Brenda W J H; Nolen, Willem A; de Jonge, Peter

BACKGROUND: Seasonal affective disorder (SAD) is considered to be a subtype of depression. AIMS: To compare the clinical picture of SAD to non-seasonal affective disorders (non-SADs). METHOD: Diagnoses according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) were established

A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments

Science.gov (United States)

Schepen, Andrew; Zhao, Tongtiegang; Wang, Quan J.; Robertson, David E.

2018-03-01

Rainfall forecasts are an integral part of hydrological forecasting systems at sub-seasonal to seasonal timescales. In seasonal forecasting, global climate models (GCMs) are now the go-to source for rainfall forecasts. For hydrological applications however, GCM forecasts are often biased and unreliable in uncertainty spread, and calibration is therefore required before use. There are sophisticated statistical techniques for calibrating monthly and seasonal aggregations of the forecasts. However, calibration of seasonal forecasts at the daily time step typically uses very simple statistical methods or climate analogue methods. These methods generally lack the sophistication to achieve unbiased, reliable and coherent forecasts of daily amounts and seasonal accumulated totals. In this study, we propose and evaluate a Rainfall Post-Processing method for Seasonal forecasts (RPP-S), which is based on the Bayesian joint probability modelling approach for calibrating daily forecasts and the Schaake Shuffle for connecting the daily ensemble members of different lead times. We apply the method to post-process ACCESS-S forecasts for 12 perennial and ephemeral catchments across Australia and for 12 initialisation dates. RPP-S significantly reduces bias in raw forecasts and improves both skill and reliability. RPP-S forecasts are also more skilful and reliable than forecasts derived from ACCESS-S forecasts that have been post-processed using quantile mapping, especially for monthly and seasonal accumulations. Several opportunities to improve the robustness and skill of RPP-S are identified. The new RPP-S post-processed forecasts will be used in ensemble sub-seasonal to seasonal streamflow applications.

Seasonality in acute liver injury? Findings in two health care claims databases

Directory of Open Access Journals (Sweden)

Weinstein RB

2016-03-01

Full Text Available Rachel B Weinstein, Martijn J Schuemie, Patrick B Ryan, Paul E Stang Epidemiology, Janssen Research and Development, LLC, Titusville, NJ, USA Background: Presumed seasonal use of acetaminophen-containing products for relief of cold/influenza (“flu” symptoms suggests that there might also be a corresponding seasonal pattern for acute liver injury (ALI, a known clinical consequence of acetaminophen overdose. Objective: The objective of this study was to determine whether there were any temporal patterns in hospitalizations for ALI that would correspond to assumed acetaminophen use in cold/flu season. Methods: In the period 2002–2010, monthly hospitalization rates for ALI using a variety of case definitions were calculated. Data sources included Truven MarketScan® Commercial Claims and Encounters (CCAE and Medicare Supplemental and Coordination of Benefits (MDCR databases. We performed a statistical test for seasonality of diagnoses using the periodic generalized linear model. To validate that the test can distinguish seasonal from nonseasonal patterns, we included two positive controls (ie, diagnoses of the common cold [acute nasopharyngitis] and influenza, believed to change with seasons, and two negative controls (female breast cancer and diabetes, believed to be insensitive to season. Results: A seasonal pattern was observed in monthly rates for common cold and influenza diagnoses, but this pattern was not observed for monthly rates of ALI, with or without comorbidities (cirrhosis or hepatitis, breast cancer, or diabetes. The statistical test for seasonality was significant for positive controls (P<0.001 for each diagnosis in both databases and nonsignificant for ALI and negative controls. Conclusion: No seasonal pattern was observed in the diagnosis of ALI. The positive and negative controls showed the expected patterns, strengthening the validity of the statistical and visual tests used for detecting seasonality. Keywords: acute liver

Statistical significance of epidemiological data. Seminar: Evaluation of epidemiological studies

International Nuclear Information System (INIS)

Weber, K.H.

1993-01-01

In stochastic damages, the numbers of events, e.g. the persons who are affected by or have died of cancer, and thus the relative frequencies (incidence or mortality) are binomially distributed random variables. Their statistical fluctuations can be characterized by confidence intervals. For epidemiologic questions, especially for the analysis of stochastic damages in the low dose range, the following issues are interesting: - Is a sample (a group of persons) with a definite observed damage frequency part of the whole population? - Is an observed frequency difference between two groups of persons random or statistically significant? - Is an observed increase or decrease of the frequencies with increasing dose random or statistically significant and how large is the regression coefficient (= risk coefficient) in this case? These problems can be solved by sttistical tests. So-called distribution-free tests and tests which are not bound to the supposition of normal distribution are of particular interest, such as: - χ 2 -independence test (test in contingency tables); - Fisher-Yates-test; - trend test according to Cochran; - rank correlation test given by Spearman. These tests are explained in terms of selected epidemiologic data, e.g. of leukaemia clusters, of the cancer mortality of the Japanese A-bomb survivors especially in the low dose range as well as on the sample of the cancer mortality in the high background area in Yangjiang (China). (orig.) [de

A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments

Directory of Open Access Journals (Sweden)

A. Schepen

2018-03-01

Full Text Available Rainfall forecasts are an integral part of hydrological forecasting systems at sub-seasonal to seasonal timescales. In seasonal forecasting, global climate models (GCMs are now the go-to source for rainfall forecasts. For hydrological applications however, GCM forecasts are often biased and unreliable in uncertainty spread, and calibration is therefore required before use. There are sophisticated statistical techniques for calibrating monthly and seasonal aggregations of the forecasts. However, calibration of seasonal forecasts at the daily time step typically uses very simple statistical methods or climate analogue methods. These methods generally lack the sophistication to achieve unbiased, reliable and coherent forecasts of daily amounts and seasonal accumulated totals. In this study, we propose and evaluate a Rainfall Post-Processing method for Seasonal forecasts (RPP-S, which is based on the Bayesian joint probability modelling approach for calibrating daily forecasts and the Schaake Shuffle for connecting the daily ensemble members of different lead times. We apply the method to post-process ACCESS-S forecasts for 12 perennial and ephemeral catchments across Australia and for 12 initialisation dates. RPP-S significantly reduces bias in raw forecasts and improves both skill and reliability. RPP-S forecasts are also more skilful and reliable than forecasts derived from ACCESS-S forecasts that have been post-processed using quantile mapping, especially for monthly and seasonal accumulations. Several opportunities to improve the robustness and skill of RPP-S are identified. The new RPP-S post-processed forecasts will be used in ensemble sub-seasonal to seasonal streamflow applications.

Seasonal influence on water quality status of Temenggor Lake, Perak

International Nuclear Information System (INIS)

Wan Mohd Afiq Wan Abdul Khalik; Mohd Pauzi Abdullah; Mohd Pauzi Abdullah

2012-01-01

A study of the water quality in Temenggor Lake was conducted within two different seasons, namely wet season (November - January 2009) and dry season (March - July 2010). Thirteen sampling stations were selected representing open water body of the lake particularly surrounding Banding Island. Three depths layered sampling (surface, middle and bottom of lake) was performed at each sampling stations except in zone B. An average WQI for Temenggor Lake in wet season (90.49) is slightly higher than the average for dry season (88.87). This study indicates quite significant seasonal influence of rainfalls on environmental lake ecosystems by improving the quality through dilution effect on several parameters. Statistical analysis of two-way ANOVA test indicates that all measured parameters are affected by seasonal changes except for pH, turbidity, DO, BOD, oil and grease. Biochemical Oxygen Demand (BOD) and water hardness showed significant relationship with local community activities. Considering future development as eco tourism destination, the water quality of Temenggor Lake should be maintained thus some sort of integrated lake management system model on the integrated water resource management concept should be implemented. (author)

Understanding Flood Seasonality and Its Temporal Shifts within the Contiguous United States

Energy Technology Data Exchange (ETDEWEB)

Ye, Sheng [Institute of Hydrology and Water Resources, School of Civil Engineering, Zhejiang University, Hangzhou, China; Li, Hong-Yi [Pacific Northwest National Laboratory, Richland, Washington; Leung, L. Ruby [Pacific Northwest National Laboratory, Richland, Washington; Guo, Jiali [College of Civil and Hydropower Engineering, China Three Gorges University, Yichang, China; State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, China; Ran, Qihua [Institute of Hydrology and Water Resources, School of Civil Engineering, Zhejiang University, Hangzhou, China; Demissie, Yonas [Department of Civil and Environmental Engineering, Washington State University Tri-Cities, Richland, Washington; Sivapalan, Murugesu [Department of Geography and Geographic Information Science, University of Illinois at Urbana–Champaign, Champaign, Illinois; Department of Civil and Environmental Engineering, University of Illinois at Urbana–Champaign, Urbana, Illinois

2017-07-01

Understanding the causes of flood seasonality is critical for better flood management. This study examines the seasonality of annual maximum floods (AMF) and its changes before and after 1980 at over 250 natural catchments across the contiguous United States. Using circular statistics to define a seasonality index, our analysis focuses on the variability of the flood occurrence date. Generally, catchments with more synchronized seasonal water and energy cycles largely inherit their seasonality of AMF from that of annual maximum rainfall (AMR). In contrast, the seasonality of AMF in catchments with loosely synchronized water and energy cycles are more influenced by high antecedent storage, which is responsible for the amplification of the seasonality of AMF over that of AMR. This understanding then effectively explains a statistically significant shift of flood seasonality detected in some catchments in the recent decades. Catchments where the antecedent soil water storage has increased since 1980 exhibit increasing flood seasonality while catchments that have experienced increases in storm rainfall before the floods have shifted towards floods occurring more variably across the seasons. In the eastern catchments, a concurrent widespread increase in event rainfall magnitude and reduced soil water storage have led to a more variable timing of floods. Our findings of the role of antecedent storage and event rainfall on the flood seasonality provide useful insights for understanding future changes in flood seasonality as climate models projected changes in extreme precipitation and aridity over land.

Statistical Significance and Effect Size: Two Sides of a Coin.

Science.gov (United States)

Fan, Xitao

This paper suggests that statistical significance testing and effect size are two sides of the same coin; they complement each other, but do not substitute for one another. Good research practice requires that both should be taken into consideration to make sound quantitative decisions. A Monte Carlo simulation experiment was conducted, and a…

Publication of statistically significant research findings in prosthodontics & implant dentistry in the context of other dental specialties.

Science.gov (United States)

Papageorgiou, Spyridon N; Kloukos, Dimitrios; Petridis, Haralampos; Pandis, Nikolaos

2015-10-01

To assess the hypothesis that there is excessive reporting of statistically significant studies published in prosthodontic and implantology journals, which could indicate selective publication. The last 30 issues of 9 journals in prosthodontics and implant dentistry were hand-searched for articles with statistical analyses. The percentages of significant and non-significant results were tabulated by parameter of interest. Univariable/multivariable logistic regression analyses were applied to identify possible predictors of reporting statistically significance findings. The results of this study were compared with similar studies in dentistry with random-effects meta-analyses. From the 2323 included studies 71% of them reported statistically significant results, with the significant results ranging from 47% to 86%. Multivariable modeling identified that geographical area and involvement of statistician were predictors of statistically significant results. Compared to interventional studies, the odds that in vitro and observational studies would report statistically significant results was increased by 1.20 times (OR: 2.20, 95% CI: 1.66-2.92) and 0.35 times (OR: 1.35, 95% CI: 1.05-1.73), respectively. The probability of statistically significant results from randomized controlled trials was significantly lower compared to various study designs (difference: 30%, 95% CI: 11-49%). Likewise the probability of statistically significant results in prosthodontics and implant dentistry was lower compared to other dental specialties, but this result did not reach statistical significant (P>0.05). The majority of studies identified in the fields of prosthodontics and implant dentistry presented statistically significant results. The same trend existed in publications of other specialties in dentistry. Copyright © 2015 Elsevier Ltd. All rights reserved.

Significant Statistics: Viewed with a Contextual Lens

Science.gov (United States)

Tait-McCutcheon, Sandi

2010-01-01

This paper examines the pedagogical and organisational changes three lead teachers made to their statistics teaching and learning programs. The lead teachers posed the research question: What would the effect of contextually integrating statistical investigations and literacies into other curriculum areas be on student achievement? By finding the…

Seasonal rationalization of river water quality sampling locations: a comparative study of the modified Sanders and multivariate statistical approaches.

Science.gov (United States)

Varekar, Vikas; Karmakar, Subhankar; Jha, Ramakar

2016-02-01

The design of surface water quality sampling location is a crucial decision-making process for rationalization of monitoring network. The quantity, quality, and types of available dataset (watershed characteristics and water quality data) may affect the selection of appropriate design methodology. The modified Sanders approach and multivariate statistical techniques [particularly factor analysis (FA)/principal component analysis (PCA)] are well-accepted and widely used techniques for design of sampling locations. However, their performance may vary significantly with quantity, quality, and types of available dataset. In this paper, an attempt has been made to evaluate performance of these techniques by accounting the effect of seasonal variation, under a situation of limited water quality data but extensive watershed characteristics information, as continuous and consistent river water quality data is usually difficult to obtain, whereas watershed information may be made available through application of geospatial techniques. A case study of Kali River, Western Uttar Pradesh, India, is selected for the analysis. The monitoring was carried out at 16 sampling locations. The discrete and diffuse pollution loads at different sampling sites were estimated and accounted using modified Sanders approach, whereas the monitored physical and chemical water quality parameters were utilized as inputs for FA/PCA. The designed optimum number of sampling locations for monsoon and non-monsoon seasons by modified Sanders approach are eight and seven while that for FA/PCA are eleven and nine, respectively. Less variation in the number and locations of designed sampling sites were obtained by both techniques, which shows stability of results. A geospatial analysis has also been carried out to check the significance of designed sampling location with respect to river basin characteristics and land use of the study area. Both methods are equally efficient; however, modified Sanders

"What If" Analyses: Ways to Interpret Statistical Significance Test Results Using EXCEL or "R"

Science.gov (United States)

Ozturk, Elif

2012-01-01

The present paper aims to review two motivations to conduct "what if" analyses using Excel and "R" to understand the statistical significance tests through the sample size context. "What if" analyses can be used to teach students what statistical significance tests really do and in applied research either prospectively to estimate what sample size…

Forecasting infectious disease emergence subject to seasonal forcing.

Science.gov (United States)

Miller, Paige B; O'Dea, Eamon B; Rohani, Pejman; Drake, John M

2017-09-06

Despite high vaccination coverage, many childhood infections pose a growing threat to human populations. Accurate disease forecasting would be of tremendous value to public health. Forecasting disease emergence using early warning signals (EWS) is possible in non-seasonal models of infectious diseases. Here, we assessed whether EWS also anticipate disease emergence in seasonal models. We simulated the dynamics of an immunizing infectious pathogen approaching the tipping point to disease endemicity. To explore the effect of seasonality on the reliability of early warning statistics, we varied the amplitude of fluctuations around the average transmission. We proposed and analyzed two new early warning signals based on the wavelet spectrum. We measured the reliability of the early warning signals depending on the strength of their trend preceding the tipping point and then calculated the Area Under the Curve (AUC) statistic. Early warning signals were reliable when disease transmission was subject to seasonal forcing. Wavelet-based early warning signals were as reliable as other conventional early warning signals. We found that removing seasonal trends, prior to analysis, did not improve early warning statistics uniformly. Early warning signals anticipate the onset of critical transitions for infectious diseases which are subject to seasonal forcing. Wavelet-based early warning statistics can also be used to forecast infectious disease.

Statistical vs. Economic Significance in Economics and Econometrics: Further comments on McCloskey & Ziliak

DEFF Research Database (Denmark)

Engsted, Tom

I comment on the controversy between McCloskey & Ziliak and Hoover & Siegler on statistical versus economic significance, in the March 2008 issue of the Journal of Economic Methodology. I argue that while McCloskey & Ziliak are right in emphasizing 'real error', i.e. non-sampling error that cannot...... be eliminated through specification testing, they fail to acknowledge those areas in economics, e.g. rational expectations macroeconomics and asset pricing, where researchers clearly distinguish between statistical and economic significance and where statistical testing plays a relatively minor role in model...

Low-frequency variability of the atmospheric circulation: a comparison of statistical properties in both hemispheres and extreme seasons

International Nuclear Information System (INIS)

Buzzi, A.; Tosi, E.

1988-01-01

A statistical investigation is presented of the main variables characterizing the tropospheric general circulation in both hemispheres and extreme season, Winter and Summer. This gives up the opportunity of comparing four distinct realizations of the planetary circulation, as function of different orographic and thermal forcing conditions. Our approach is made possible by the availability of 6 years of global daily analyses prepared by ECMWF (European Centre for Medium-range Weather Forecast). The variables taken into account are the zonal geostrophic wind, the zonal thermal wind and various large-scala wave components, averaged over the tropospheric depth between 1000 and 200 hPa. The mean properties of the analysed quantities in each hemisphere and season are compared and their principal characteristics are discussed. The probability density estimates for the same variables, filtered in order to eliminate the seasonal cycle and the high frequency 'noise', are then presented. The distributions are examined, in particular, with respect of their unimodal or multimodal nature and with reference to the recent discussion in the literature on the bimodality which has been found for some indicators of planetary wave activity in the Nothern Hemisphere Winter. Our results indicate the presence of nonunimodally distributed wave and zonal flow components in both hemispheres and extreme season. The most frequent occurrence of nonunimodal behaviour is found for those wave components which exhibit an almost vanishing zonal phase speed and a larger 'response' to orographic forcing

Seasonal forecasting of hydrological drought in the Limpopo Basin: a comparison of statistical methods

Science.gov (United States)

Seibert, Mathias; Merz, Bruno; Apel, Heiko

2017-03-01

The Limpopo Basin in southern Africa is prone to droughts which affect the livelihood of millions of people in South Africa, Botswana, Zimbabwe and Mozambique. Seasonal drought early warning is thus vital for the whole region. In this study, the predictability of hydrological droughts during the main runoff period from December to May is assessed using statistical approaches. Three methods (multiple linear models, artificial neural networks, random forest regression trees) are compared in terms of their ability to forecast streamflow with up to 12 months of lead time. The following four main findings result from the study. 1. There are stations in the basin at which standardised streamflow is predictable with lead times up to 12 months. The results show high inter-station differences of forecast skill but reach a coefficient of determination as high as 0.73 (cross validated). 2. A large range of potential predictors is considered in this study, comprising well-established climate indices, customised teleconnection indices derived from sea surface temperatures and antecedent streamflow as a proxy of catchment conditions. El Niño and customised indices, representing sea surface temperature in the Atlantic and Indian oceans, prove to be important teleconnection predictors for the region. Antecedent streamflow is a strong predictor in small catchments (with median 42 % explained variance), whereas teleconnections exert a stronger influence in large catchments. 3. Multiple linear models show the best forecast skill in this study and the greatest robustness compared to artificial neural networks and random forest regression trees, despite their capabilities to represent nonlinear relationships. 4. Employed in early warning, the models can be used to forecast a specific drought level. Even if the coefficient of determination is low, the forecast models have a skill better than a climatological forecast, which is shown by analysis of receiver operating characteristics

Bayesian analyses of seasonal runoff forecasts

Science.gov (United States)

Krzysztofowicz, R.; Reese, S.

1991-12-01

Forecasts of seasonal snowmelt runoff volume provide indispensable information for rational decision making by water project operators, irrigation district managers, and farmers in the western United States. Bayesian statistical models and communication frames have been researched in order to enhance the forecast information disseminated to the users, and to characterize forecast skill from the decision maker's point of view. Four products are presented: (i) a Bayesian Processor of Forecasts, which provides a statistical filter for calibrating the forecasts, and a procedure for estimating the posterior probability distribution of the seasonal runoff; (ii) the Bayesian Correlation Score, a new measure of forecast skill, which is related monotonically to the ex ante economic value of forecasts for decision making; (iii) a statistical predictor of monthly cumulative runoffs within the snowmelt season, conditional on the total seasonal runoff forecast; and (iv) a framing of the forecast message that conveys the uncertainty associated with the forecast estimates to the users. All analyses are illustrated with numerical examples of forecasts for six gauging stations from the period 1971 1988.

Impact of seasonal variation, age and smoking status on human semen parameters: The Massachusetts General Hospital experience

Science.gov (United States)

Chen, Zuying; Godfrey-Bailey, Linda; Schiff, Isaac; Hauser, Russ

2004-01-01

Background To investigate the relationship of human semen parameters with season, age and smoking status. Methods The present study used data from subjects recruited into an ongoing cross-sectional study on the relationship between environmental agents and semen characteristics. Our population consisted of 306 patients who presented to the Vincent Memorial Andrology Laboratory of Massachusetts General Hospital for semen evaluation. Sperm concentration and motility were measured with computer aided sperm analysis (CASA). Sperm morphology was scored using Tygerberg Kruger strict criteria. Regression analyses were used to investigate the relationships between semen parameters and season, age and smoking status, adjusting for abstinence interval. Results Sperm concentration in the spring was significantly higher than in winter, fall and summer (p seasons. There were no statistically significant relationships between semen parameters and smoking status, though current smokers tended to have lower sperm concentration. We also did not find a statistically significant relationship between age and semen parameters. Conclusions We found seasonal variations in sperm concentration and suggestive evidence of seasonal variation in sperm motility and percent sperm with normal morphology. Although smoking status was not a significant predictor of semen parameters, this may have been due to the small number of current smokers in the study. PMID:15507127

Distinguishing between statistical significance and practical/clinical meaningfulness using statistical inference.

Science.gov (United States)

Wilkinson, Michael

2014-03-01

Decisions about support for predictions of theories in light of data are made using statistical inference. The dominant approach in sport and exercise science is the Neyman-Pearson (N-P) significance-testing approach. When applied correctly it provides a reliable procedure for making dichotomous decisions for accepting or rejecting zero-effect null hypotheses with known and controlled long-run error rates. Type I and type II error rates must be specified in advance and the latter controlled by conducting an a priori sample size calculation. The N-P approach does not provide the probability of hypotheses or indicate the strength of support for hypotheses in light of data, yet many scientists believe it does. Outcomes of analyses allow conclusions only about the existence of non-zero effects, and provide no information about the likely size of true effects or their practical/clinical value. Bayesian inference can show how much support data provide for different hypotheses, and how personal convictions should be altered in light of data, but the approach is complicated by formulating probability distributions about prior subjective estimates of population effects. A pragmatic solution is magnitude-based inference, which allows scientists to estimate the true magnitude of population effects and how likely they are to exceed an effect magnitude of practical/clinical importance, thereby integrating elements of subjective Bayesian-style thinking. While this approach is gaining acceptance, progress might be hastened if scientists appreciate the shortcomings of traditional N-P null hypothesis significance testing.

Codon Deviation Coefficient: a novel measure for estimating codon usage bias and its statistical significance

Directory of Open Access Journals (Sweden)

Zhang Zhang

2012-03-01

Full Text Available Abstract Background Genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, and protein function through natural selection are all believed to lead to codon usage bias (CUB. Therefore, informative measurement of CUB is of fundamental importance to making inferences regarding gene function and genome evolution. However, extant measures of CUB have not fully accounted for the quantitative effect of background nucleotide composition and have not statistically evaluated the significance of CUB in sequence analysis. Results Here we propose a novel measure--Codon Deviation Coefficient (CDC--that provides an informative measurement of CUB and its statistical significance without requiring any prior knowledge. Unlike previous measures, CDC estimates CUB by accounting for background nucleotide compositions tailored to codon positions and adopts the bootstrapping to assess the statistical significance of CUB for any given sequence. We evaluate CDC by examining its effectiveness on simulated sequences and empirical data and show that CDC outperforms extant measures by achieving a more informative estimation of CUB and its statistical significance. Conclusions As validated by both simulated and empirical data, CDC provides a highly informative quantification of CUB and its statistical significance, useful for determining comparative magnitudes and patterns of biased codon usage for genes or genomes with diverse sequence compositions.

Statistics Refresher for Molecular Imaging Technologists, Part 2: Accuracy of Interpretation, Significance, and Variance.

Science.gov (United States)

Farrell, Mary Beth

2018-06-01

This article is the second part of a continuing education series reviewing basic statistics that nuclear medicine and molecular imaging technologists should understand. In this article, the statistics for evaluating interpretation accuracy, significance, and variance are discussed. Throughout the article, actual statistics are pulled from the published literature. We begin by explaining 2 methods for quantifying interpretive accuracy: interreader and intrareader reliability. Agreement among readers can be expressed simply as a percentage. However, the Cohen κ-statistic is a more robust measure of agreement that accounts for chance. The higher the κ-statistic is, the higher is the agreement between readers. When 3 or more readers are being compared, the Fleiss κ-statistic is used. Significance testing determines whether the difference between 2 conditions or interventions is meaningful. Statistical significance is usually expressed using a number called a probability ( P ) value. Calculation of P value is beyond the scope of this review. However, knowing how to interpret P values is important for understanding the scientific literature. Generally, a P value of less than 0.05 is considered significant and indicates that the results of the experiment are due to more than just chance. Variance, standard deviation (SD), confidence interval, and standard error (SE) explain the dispersion of data around a mean of a sample drawn from a population. SD is commonly reported in the literature. A small SD indicates that there is not much variation in the sample data. Many biologic measurements fall into what is referred to as a normal distribution taking the shape of a bell curve. In a normal distribution, 68% of the data will fall within 1 SD, 95% will fall within 2 SDs, and 99.7% will fall within 3 SDs. Confidence interval defines the range of possible values within which the population parameter is likely to lie and gives an idea of the precision of the statistic being

Systematic reviews of anesthesiologic interventions reported as statistically significant

DEFF Research Database (Denmark)

Imberger, Georgina; Gluud, Christian; Boylan, John

2015-01-01

statistically significant meta-analyses of anesthesiologic interventions, we used TSA to estimate power and imprecision in the context of sparse data and repeated updates. METHODS: We conducted a search to identify all systematic reviews with meta-analyses that investigated an intervention that may......: From 11,870 titles, we found 682 systematic reviews that investigated anesthesiologic interventions. In the 50 sampled meta-analyses, the median number of trials included was 8 (interquartile range [IQR], 5-14), the median number of participants was 964 (IQR, 523-1736), and the median number...

Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms

Science.gov (United States)

Xu, Kuan-Man

2006-01-01

A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.

Monthly to seasonal low flow prediction: statistical versus dynamical models

Science.gov (United States)

Ionita-Scholz, Monica; Klein, Bastian; Meissner, Dennis; Rademacher, Silke

2016-04-01

the Alfred Wegener Institute a purely statistical scheme to generate streamflow forecasts for several months ahead. Instead of directly using teleconnection indices (e.g. NAO, AO) the idea is to identify regions with stable teleconnections between different global climate information (e.g. sea surface temperature, geopotential height etc.) and streamflow at different gauges relevant for inland waterway transport. So-called stability (correlation) maps are generated showing regions where streamflow and climate variable from previous months are significantly correlated in a 21 (31) years moving window. Finally, the optimal forecast model is established based on a multiple regression analysis of the stable predictors. We will present current results of the aforementioned approaches with focus on the River Rhine (being one of the world's most frequented waterways and the backbone of the European inland waterway network) and the Elbe River. Overall, our analysis reveals the existence of a valuable predictability of the low flows at monthly and seasonal time scales, a result that may be useful to water resources management. Given that all predictors used in the models are available at the end of each month, the forecast scheme can be used operationally to predict extreme events and to provide early warnings for upcoming low flows.

P-Value, a true test of statistical significance? a cautionary note ...

African Journals Online (AJOL)

While it's not the intention of the founders of significance testing and hypothesis testing to have the two ideas intertwined as if they are complementary, the inconvenient marriage of the two practices into one coherent, convenient, incontrovertible and misinterpreted practice has dotted our standard statistics textbooks and ...

Observational evidence of seasonality in the timing of loop current eddy separation

Science.gov (United States)

Hall, Cody A.; Leben, Robert R.

2016-12-01

Observational datasets, reports and analyses over the time period from 1978 through 1992 are reviewed to derive pre-altimetry Loop Current (LC) eddy separation dates. The reanalysis identified 20 separation events in the 15-year record. Separation dates are estimated to be accurate to approximately ± 1.5 months and sufficient to detect statistically significant LC eddy separation seasonality, which was not the case for previously published records because of the misidentification of separation events and their timing. The reanalysis indicates that previously reported LC eddy separation dates, determined for the time period before the advent of continuous altimetric monitoring in the early 1990s, are inaccurate because of extensive reliance on satellite sea surface temperature (SST) imagery. Automated LC tracking techniques are used to derive LC eddy separation dates in three different altimetry-based sea surface height (SSH) datasets over the time period from 1993 through 2012. A total of 28-30 LC eddy separation events were identified in the 20-year record. Variations in the number and dates of eddy separation events are attributed to the different mean sea surfaces and objective-analysis smoothing procedures used to produce the SSH datasets. Significance tests on various altimetry and pre-altimetry/altimetry combined date lists consistently show that the seasonal distribution of separation events is not uniform at the 95% confidence level. Randomization tests further show that the seasonal peak in LC eddy separation events in August and September is highly unlikely to have occurred by chance. The other seasonal peak in February and March is less significant, but possibly indicates two seasons of enhanced probability of eddy separation centered near the spring and fall equinoxes. This is further quantified by objectively dividing the seasonal distribution into two seasons using circular statistical techniques and a k-means clustering algorithm. The estimated

Codon Deviation Coefficient: A novel measure for estimating codon usage bias and its statistical significance

KAUST Repository

Zhang, Zhang

2012-03-22

Background: Genetic mutation, selective pressure for translational efficiency and accuracy, level of gene expression, and protein function through natural selection are all believed to lead to codon usage bias (CUB). Therefore, informative measurement of CUB is of fundamental importance to making inferences regarding gene function and genome evolution. However, extant measures of CUB have not fully accounted for the quantitative effect of background nucleotide composition and have not statistically evaluated the significance of CUB in sequence analysis.Results: Here we propose a novel measure--Codon Deviation Coefficient (CDC)--that provides an informative measurement of CUB and its statistical significance without requiring any prior knowledge. Unlike previous measures, CDC estimates CUB by accounting for background nucleotide compositions tailored to codon positions and adopts the bootstrapping to assess the statistical significance of CUB for any given sequence. We evaluate CDC by examining its effectiveness on simulated sequences and empirical data and show that CDC outperforms extant measures by achieving a more informative estimation of CUB and its statistical significance.Conclusions: As validated by both simulated and empirical data, CDC provides a highly informative quantification of CUB and its statistical significance, useful for determining comparative magnitudes and patterns of biased codon usage for genes or genomes with diverse sequence compositions. 2012 Zhang et al; licensee BioMed Central Ltd.

Interpreting Statistical Significance Test Results: A Proposed New "What If" Method.

Science.gov (United States)

Kieffer, Kevin M.; Thompson, Bruce

As the 1994 publication manual of the American Psychological Association emphasized, "p" values are affected by sample size. As a result, it can be helpful to interpret the results of statistical significant tests in a sample size context by conducting so-called "what if" analyses. However, these methods can be inaccurate…

Measuring individual significant change on the Beck Depression Inventory-II through IRT-based statistics.

NARCIS (Netherlands)

Brouwer, D.; Meijer, R.R.; Zevalkink, D.J.

2013-01-01

Several researchers have emphasized that item response theory (IRT)-based methods should be preferred over classical approaches in measuring change for individual patients. In the present study we discuss and evaluate the use of IRT-based statistics to measure statistical significant individual

Seasonal effect on physiological, reproductive and fertility profiles in breeding mithun bulls

Directory of Open Access Journals (Sweden)

P Perumal

2017-01-01

Full Text Available Objective: To analyse the seasonal effect on physiological parameters, reproductive profiles and in vitro fertility in breeding mithun bulls.Methods: A total of ten adult mithun bulls age of 5 to 6 years old with good body condition (score 5-6 were selected from ICAR-NRC on Mithun, Jharnapani, Nagaland, India. The seasons were categorised into winter, spring, summer and autumn seasons based on the meteorological data and sunshine hours. The physiological parameters, reproductive profiles and in vitro fertility parameters were assessed during different seasons in mithun under the semi-intensive system of management.Results: The statistical analysis revealed that these experimental parameters were differed significantly (P<0.05 among the seasons and in overall spring and winter seasons were more beneficial in mithun breeding programme, although, the breeding in mithun occurred throughout the year with variation.Conclusions: It is concluded that collection & preservation of mithun semen and artificial insemination in mithun species during the season of spring and winter has significant beneficial effect in terms of semen production, freezability and fertility for artificial breeding programme in mithun under the semi-intensive system.

Seasonal changes in the digesta-adherent rumen bacterial communities of dairy cattle grazing pasture

DEFF Research Database (Denmark)

Noel, Samantha Joan; Attwood, G T; Rakonjac, J

2017-01-01

The complex microbiota that resides within the rumen is responsible for the break-down of plant fibre. The bacteria that attach to ingested plant matter within the rumen are thought to be responsible for initial fibre degradation. Most studies examining the ecology of this important microbiome only.......1%), followed by Bacteroidetes (11.8%). This community differed between the seasons, returning to close to that observed in the same season one year later. These seasonal differences were only small, but were statistically significant (p diet...

Strategies for Testing Statistical and Practical Significance in Detecting DIF with Logistic Regression Models

Science.gov (United States)

Fidalgo, Angel M.; Alavi, Seyed Mohammad; Amirian, Seyed Mohammad Reza

2014-01-01

This study examines three controversial aspects in differential item functioning (DIF) detection by logistic regression (LR) models: first, the relative effectiveness of different analytical strategies for detecting DIF; second, the suitability of the Wald statistic for determining the statistical significance of the parameters of interest; and…

Crop Yield Predictions - High Resolution Statistical Model for Intra-season Forecasts Applied to Corn in the US

Science.gov (United States)

Cai, Y.

2017-12-01

Accurately forecasting crop yields has broad implications for economic trading, food production monitoring, and global food security. However, the variation of environmental variables presents challenges to model yields accurately, especially when the lack of highly accurate measurements creates difficulties in creating models that can succeed across space and time. In 2016, we developed a sequence of machine-learning based models forecasting end-of-season corn yields for the US at both the county and national levels. We combined machine learning algorithms in a hierarchical way, and used an understanding of physiological processes in temporal feature selection, to achieve high precision in our intra-season forecasts, including in very anomalous seasons. During the live run, we predicted the national corn yield within 1.40% of the final USDA number as early as August. In the backtesting of the 2000-2015 period, our model predicts national yield within 2.69% of the actual yield on average already by mid-August. At the county level, our model predicts 77% of the variation in final yield using data through the beginning of August and improves to 80% by the beginning of October, with the percentage of counties predicted within 10% of the average yield increasing from 68% to 73%. Further, the lowest errors are in the most significant producing regions, resulting in very high precision national-level forecasts. In addition, we identify the changes of important variables throughout the season, specifically early-season land surface temperature, and mid-season land surface temperature and vegetation index. For the 2017 season, we feed 2016 data to the training set, together with additional geospatial data sources, aiming to make the current model even more precise. We will show how our 2017 US corn yield forecasts converges in time, which factors affect the yield the most, as well as present our plans for 2018 model adjustments.

Statistical methods for change-point detection in surface temperature records

Science.gov (United States)

Pintar, A. L.; Possolo, A.; Zhang, N. F.

2013-09-01

We describe several statistical methods to detect possible change-points in a time series of values of surface temperature measured at a meteorological station, and to assess the statistical significance of such changes, taking into account the natural variability of the measured values, and the autocorrelations between them. These methods serve to determine whether the record may suffer from biases unrelated to the climate signal, hence whether there may be a need for adjustments as considered by M. J. Menne and C. N. Williams (2009) "Homogenization of Temperature Series via Pairwise Comparisons", Journal of Climate 22 (7), 1700-1717. We also review methods to characterize patterns of seasonality (seasonal decomposition using monthly medians or robust local regression), and explain the role they play in the imputation of missing values, and in enabling robust decompositions of the measured values into a seasonal component, a possible climate signal, and a station-specific remainder. The methods for change-point detection that we describe include statistical process control, wavelet multi-resolution analysis, adaptive weights smoothing, and a Bayesian procedure, all of which are applicable to single station records.

Thresholds for statistical and clinical significance in systematic reviews with meta-analytic methods

DEFF Research Database (Denmark)

Jakobsen, Janus Christian; Wetterslev, Jorn; Winkel, Per

2014-01-01

BACKGROUND: Thresholds for statistical significance when assessing meta-analysis results are being insufficiently demonstrated by traditional 95% confidence intervals and P-values. Assessment of intervention effects in systematic reviews with meta-analysis deserves greater rigour. METHODS......: Methodologies for assessing statistical and clinical significance of intervention effects in systematic reviews were considered. Balancing simplicity and comprehensiveness, an operational procedure was developed, based mainly on The Cochrane Collaboration methodology and the Grading of Recommendations...... Assessment, Development, and Evaluation (GRADE) guidelines. RESULTS: We propose an eight-step procedure for better validation of meta-analytic results in systematic reviews (1) Obtain the 95% confidence intervals and the P-values from both fixed-effect and random-effects meta-analyses and report the most...

Seasonality in twin birth rates, Denmark, 1936-84.

Science.gov (United States)

Bonnelykke, B; Søgaard, J; Nielsen, J

1987-12-01

A study was made of seasonality in twin birth rate in Denmark between 1977 and 1984. We studied all twin births (N = 45,550) in all deliveries (N = 3,679,932) during that period. Statistical analysis using a simple harmonic sinusoidal model provided no evidence for seasonality. However, sequential polynomial analysis disclosed a significant fit to a fifth order polynomial curve with peaks in twin birth rates in May-June and December, along with troughs in February and September. A falling trend in twinning rate broke off in Denmark around 1970, and from 1970 to 1984 an increasing trend was found. The results are discussed in terms of possible environmental influences on twinning.

Temporal aspects of surface water quality variation using robust statistical tools.

Science.gov (United States)

Mustapha, Adamu; Aris, Ahmad Zaharin; Ramli, Mohammad Firuz; Juahir, Hafizan

2012-01-01

Robust statistical tools were applied on the water quality datasets with the aim of determining the most significance parameters and their contribution towards temporal water quality variation. Surface water samples were collected from four different sampling points during dry and wet seasons and analyzed for their physicochemical constituents. Discriminant analysis (DA) provided better results with great discriminatory ability by using five parameters with (P < 0.05) for dry season affording more than 96% correct assignation and used five and six parameters for forward and backward stepwise in wet season data with P-value (P < 0.05) affording 68.20% and 82%, respectively. Partial correlation results revealed that there are strong (r(p) = 0.829) and moderate (r(p) = 0.614) relationships between five-day biochemical oxygen demand (BOD(5)) and chemical oxygen demand (COD), total solids (TS) and dissolved solids (DS) controlling for the linear effect of nitrogen in the form of ammonia (NH(3)) and conductivity for dry and wet seasons, respectively. Multiple linear regression identified the contribution of each variable with significant values r = 0.988, R(2) = 0.976 and r = 0.970, R(2) = 0.942 (P < 0.05) for dry and wet seasons, respectively. Repeated measure t-test confirmed that the surface water quality varies significantly between the seasons with significant value P < 0.05.

Prediction of rainfall anomalies during the dry to wet transition season over the Southern Amazonia using machine learning tools

Science.gov (United States)

Shan, X.; Zhang, K.; Zhuang, Y.; Fu, R.; Hong, Y.

2017-12-01

Seasonal prediction of rainfall during the dry-to-wet transition season in austral spring (September-November) over southern Amazonia is central for improving planting crops and fire mitigation in that region. Previous studies have identified the key large-scale atmospheric dynamic and thermodynamics pre-conditions during the dry season (June-August) that influence the rainfall anomalies during the dry to wet transition season over Southern Amazonia. Based on these key pre-conditions during dry season, we have evaluated several statistical models and developed a Neural Network based statistical prediction system to predict rainfall during the dry to wet transition for Southern Amazonia (5-15°S, 50-70°W). Multivariate Empirical Orthogonal Function (EOF) Analysis is applied to the following four fields during JJA from the ECMWF Reanalysis (ERA-Interim) spanning from year 1979 to 2015: geopotential height at 200 hPa, surface relative humidity, convective inhibition energy (CIN) index and convective available potential energy (CAPE), to filter out noise and highlight the most coherent spatial and temporal variations. The first 10 EOF modes are retained for inputs to the statistical models, accounting for at least 70% of the total variance in the predictor fields. We have tested several linear and non-linear statistical methods. While the regularized Ridge Regression and Lasso Regression can generally capture the spatial pattern and magnitude of rainfall anomalies, we found that that Neural Network performs best with an accuracy greater than 80%, as expected from the non-linear dependence of the rainfall on the large-scale atmospheric thermodynamic conditions and circulation. Further tests of various prediction skill metrics and hindcasts also suggest this Neural Network prediction approach can significantly improve seasonal prediction skill than the dynamic predictions and regression based statistical predictions. Thus, this statistical prediction system could have

Lack of seasonal variation in bone mass and biochemical estimates of bone turnover

International Nuclear Information System (INIS)

Overgaard, K.; Nilas, L.; Johansen, J.S.; Christiansen, C.

1988-01-01

Three previous studies have indicated a seasonal variation in bone mineral content, with values during the summer being 1.7% to 7.5% higher than during the winter. We have examined the seasonal influence on both bone mass, biochemical estimates of bone turnover and vitamin D metabolites in 86 healthy women, aged 29-53 years. All participants were followed up for 2 years with examinations every 6 weeks or 3 months. Bone mineral content in the proximal and distal part of the forearm (single photon absorptiometry) did not reveal any significant seasonal variation, whereas bone mineral density of the lumbar spine (dual photon absorptiometry) indicated that the highest values occurred in winter. None of the biochemical parameters showed any statistically significant cyclical changes. Serum concentrations of 25-hydroxyvitamin D and 24,25-dihydroxyvitamin D3 showed a highly significant seasonal variation, whereas the serum 1,25-dihydroxyvitamin D concentration was virtually unchanged. We conclude that seasonal variation in bone mineral content and bone turnover should not be taken into account when interpreting data from longitudinal studies of healthy pre- and postmenopausal women on a sufficient vitamin D nutriture

NEW SEASON NEW HOPES: OFF-SEASON OPTIMISM

Directory of Open Access Journals (Sweden)

Oguz Ersan

2017-12-01

Full Text Available While literature on the relation between on-field sports performance and stock returns is ample, there is very limited evidence on off-season stage. Constituting around 3 months, off-seasons do not only occupy a significant part of the year but also represent totally different characteristics than on-seasons. They lack the periodic, unambiguous news events in on-seasons (match results, instead they are associated with highly uncertain transfer news and rumors. We show that this distinction has several impacts on the stock market performances of soccer clubs. Most notably, off-seasons generate substantially higher (excess returns. After controlling for other variables, the estimated effect of off-season periods is as high as 38.75%, annually. In line with several seminal studies, we link this fact to increased optimism and betting behavior through uncertain periods; and periods prior to the start of a new calendar (in our case, new season. For all of the examined 7 clubs (3 from Italy and 4 from Turkey, mean excess returns over the market are positive (negative in off-seasons (on-seasons. On-seasons are associated with increased trading activity due to more frequent news. Stocks of Italian clubs are evidently more volatile through off-seasons while volatility results for the stocks of Turkish clubs are not consistent.

Variability of aerobic abilities of football players during competition season

Directory of Open Access Journals (Sweden)

Novaković P.

2012-01-01

Full Text Available The purpose of this study is to determine whether there are differences in VO2max during one season in a team of semi-professional football players. This study will also determine the differences between groups, in relation to their position in the team, as well as in relation between the first team and the reserves. This study was conducted on a male football team, between 16 and 28 years of age and with no health problems, competing in a third-tier league. The technique employed is testing and the instrument is the Shuttle Run test that estimated their aerobic capacity. The testing was conducted indirectly during field tests at the beginning of the preparatory period, at the beginning of the competing period and at the end of the season. After a statistical analysis, it can be concluded that there are significant differences between the initial testing, control testing, and final testing. The initial testing was done at the beginning of the preparatory period and the results of the test ranged from 41.50 to 58.10 ml/kg/min. Then after six weeks, which was also right before the start of the competitive part of the season, the control testing was conducted and the results ranged from 46.90 to 62.30 ml/kg/min. Finally, at the end of the season, after all league matches had been played, the final testing was carried out and the results were obtained ranging from 43.80 to 62.00 ml/kg/min. All the testing was conducted on a sample of 31 players, where no relation was discovered between the status of the players at any of the three time points. However, there were some statistically significant differences from the aspect of the players' position but that is due to the goalkeepers being statistically different from the rest of the team. The cause of the differences in the obtained results are differences in intensity, volume and type of training depending on the stage of the season, as well as the specificity of training for the various positions in

Assessment and rationalization of water quality monitoring network: a multivariate statistical approach to the Kabbini River (India).

Science.gov (United States)

Mavukkandy, Musthafa Odayooth; Karmakar, Subhankar; Harikumar, P S

2014-09-01

The establishment of an efficient surface water quality monitoring (WQM) network is a critical component in the assessment, restoration and protection of river water quality. A periodic evaluation of monitoring network is mandatory to ensure effective data collection and possible redesigning of existing network in a river catchment. In this study, the efficacy and appropriateness of existing water quality monitoring network in the Kabbini River basin of Kerala, India is presented. Significant multivariate statistical techniques like principal component analysis (PCA) and principal factor analysis (PFA) have been employed to evaluate the efficiency of the surface water quality monitoring network with monitoring stations as the evaluated variables for the interpretation of complex data matrix of the river basin. The main objective is to identify significant monitoring stations that must essentially be included in assessing annual and seasonal variations of river water quality. Moreover, the significance of seasonal redesign of the monitoring network was also investigated to capture valuable information on water quality from the network. Results identified few monitoring stations as insignificant in explaining the annual variance of the dataset. Moreover, the seasonal redesign of the monitoring network through a multivariate statistical framework was found to capture valuable information from the system, thus making the network more efficient. Cluster analysis (CA) classified the sampling sites into different groups based on similarity in water quality characteristics. The PCA/PFA identified significant latent factors standing for different pollution sources such as organic pollution, industrial pollution, diffuse pollution and faecal contamination. Thus, the present study illustrates that various multivariate statistical techniques can be effectively employed in sustainable management of water resources. The effectiveness of existing river water quality monitoring

Understanding Seasonal Changes to Improve Good Practices in Livestock Management

Directory of Open Access Journals (Sweden)

Francesco Martelli

2018-06-01

Full Text Available Background and Aim: Food quality control techniques based on process control methods are increasingly adopted in livestock production systems to fulfill increasing market's expectations toward competitiveness and issues linked to One Health pillars (environment, animal, and human health. Control Charts allow monitoring and systematic investigation of sources of variability in dairy production parameters. These parameters, however, may be affected by seasonal variations that render impractical, biased or ineffective the use statistical control charts. A possible approach to this problem is to adapt seasonal adjustment methods used for the analysis of economic and demographic seasonal time series. The aim of the present work is to evaluate a seasonal decomposition technique called X-11 on milk parameters routinely collected also in small farms (fat, protein, and lactose content, solids-not-fat, freezing point, somatic cell count, total bacterial count and to test the efficacy of different seasonal removal methods to improve the effectiveness of statistical control charting.Method: Data collection was carried out for 3 years on routinely monitored bulk tank milk parameters of a small farm. Seasonality presence was statistically assessed on milk parameters and, for those parameters showing seasonality, control charts for individuals were applied on raw data, on X-11 seasonally adjusted data, and on data smoothed with a symmetric moving average filter. Correlation of seasonally influenced parameters with daily mean temperature was investigated.Results: Presence of seasonality in milk parameters was statistically assessed for fat, protein, and solids-non-fat components. The X-11 seasonally-adjusted control charts showed a reduced number of violations (false alarms with respect to non-seasonally adjusted control chart (from 5 to 1 violation for fat, from 17 to 1 violation for protein, and from 9 to none violation for solids-non-fat.. This result was

Seasonal variability of microbial biomass phosphorus in urban soils.

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Halecki, W; Gąsiorek, M

2015-01-01

Urban soils have been formed through human activities. Seasonal evaluation with time-control procedure are essential for plant, and activity of microorganisms. Therefore, these processes are crucial in the urban area due to geochemical changes in the past years. The purpose of this study was to investigate the changes of content of microbial biomass phosphorus (P) in the top layer of soils throughout the season. In this research, the concentration of microbial biomass P ranged from 0.01 to 6.29 mg·kg(-1). We used single-factor repeated-measure analysis of variance to test the effect of season on microbial biomass P content of selected urban soils. We found no statistically significant differences between the concentration of microbial biomass P in the investigated urban and sub-urban soils during the growing season. This analysis explicitly recognised that environmental urban conditions are steady. Specifically, we have studied how vegetation seasonality and ability of microbial biomass P are useful for detecting quality deviations, which affect the equilibrium of urban soil. In conclusion, seasonal variability of the stringency of assurance across the different compounds of soil reveals, as expected, the stable condition of the urban soils. Seasonal responses in microbial biomass P under urban soil use should establish a framework as a reference to the activity of the microorganisms. Copyright © 2014 Elsevier B.V. All rights reserved.

Intensive inpatient treatment for bulimia nervosa: Statistical and clinical significance of symptom changes.

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Diedrich, Alice; Schlegl, Sandra; Greetfeld, Martin; Fumi, Markus; Voderholzer, Ulrich

2018-03-01

This study examines the statistical and clinical significance of symptom changes during an intensive inpatient treatment program with a strong psychotherapeutic focus for individuals with severe bulimia nervosa. 295 consecutively admitted bulimic patients were administered the Structured Interview for Anorexic and Bulimic Syndromes-Self-Rating (SIAB-S), the Eating Disorder Inventory-2 (EDI-2), the Brief Symptom Inventory (BSI), and the Beck Depression Inventory-II (BDI-II) at treatment intake and discharge. Results indicated statistically significant symptom reductions with large effect sizes regarding severity of binge eating and compensatory behavior (SIAB-S), overall eating disorder symptom severity (EDI-2), overall psychopathology (BSI), and depressive symptom severity (BDI-II) even when controlling for antidepressant medication. The majority of patients showed either reliable (EDI-2: 33.7%, BSI: 34.8%, BDI-II: 18.1%) or even clinically significant symptom changes (EDI-2: 43.2%, BSI: 33.9%, BDI-II: 56.9%). Patients with clinically significant improvement were less distressed at intake and less likely to suffer from a comorbid borderline personality disorder when compared with those who did not improve to a clinically significant extent. Findings indicate that intensive psychotherapeutic inpatient treatment may be effective in about 75% of severely affected bulimic patients. For the remaining non-responding patients, inpatient treatment might be improved through an even stronger focus on the reduction of comorbid borderline personality traits.

Recent Literature on Whether Statistical Significance Tests Should or Should Not Be Banned.

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Deegear, James

This paper summarizes the literature regarding statistical significant testing with an emphasis on recent literature in various discipline and literature exploring why researchers have demonstrably failed to be influenced by the American Psychological Association publication manual's encouragement to report effect sizes. Also considered are…

Statistical analysis of arsenic contamination in drinking water in a city of Iran and its modeling using GIS.

Science.gov (United States)

Sadeghi, Fatemeh; Nasseri, Simin; Mosaferi, Mohammad; Nabizadeh, Ramin; Yunesian, Masud; Mesdaghinia, Alireza

2017-05-01

In this research, probable arsenic contamination in drinking water in the city of Ardabil was studied in 163 samples during four seasons. In each season, sampling was carried out randomly in the study area. Results were analyzed statistically applying SPSS 19 software, and the data was also modeled by Arc GIS 10.1 software. The maximum permissible arsenic concentration in drinking water defined by the World Health Organization and Iranian national standard is 10 μg/L. Statistical analysis showed 75, 88, 47, and 69% of samples in autumn, winter, spring, and summer, respectively, had concentrations higher than the national standard. The mean concentrations of arsenic in autumn, winter, spring, and summer were 19.89, 15.9, 10.87, and 14.6 μg/L, respectively, and the overall average in all samples through the year was 15.32 μg/L. Although GIS outputs indicated that the concentration distribution profiles changed in four consecutive seasons, variance analysis of the results showed that statistically there is no significant difference in arsenic levels in four seasons.

THE IMPACT OF SEASON OF BIRTH AND BREEDING OF BOARS OF POLISH LANDRACE BREED ON THEIR INSEMINATION EFFICIENCY

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Kazimierz Pokrywka

2014-09-01

Full Text Available The effectiveness of breeding boars in insemination depends mainly on the skill of optimal use of their reproductive potential. Nevertheless, their semen is highly variable in its quality and physical characteristics, which makes it difficult to organise semen production for artificial insemination purposes. The present study contains an analysis of semen collected from Polish Landrace breed boars - the most popular pigs bred in Poland. It demonstrates that there is a statistically significant interaction between season of birth and reproductive season of Polish Landrace boars. What is more, it proves that these significant differences between reproductive performances of boars are closely connected to their breeding season and seasons of their birth and life. The results also illustrate how to improve organisation of insemination centres and make them better financially efficient.

Seasonal trends in sleep-disordered breathing: evidence from Internet search engine query data.

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Ingram, David G; Matthews, Camilla K; Plante, David T

2015-03-01

The primary aim of the current study was to test the hypothesis that there is a seasonal component to snoring and obstructive sleep apnea (OSA) through the use of Google search engine query data. Internet search engine query data were retrieved from Google Trends from January 2006 to December 2012. Monthly normalized search volume was obtained over that 7-year period in the USA and Australia for the following search terms: "snoring" and "sleep apnea". Seasonal effects were investigated by fitting cosinor regression models. In addition, the search terms "snoring children" and "sleep apnea children" were evaluated to examine seasonal effects in pediatric populations. Statistically significant seasonal effects were found using cosinor analysis in both USA and Australia for "snoring" (p search term in Australia (p = 0.13). Seasonal patterns for "snoring children" and "sleep apnea children" were observed in the USA (p = 0.002 and p search volume to examine these search terms in Australia. All searches peaked in the winter or early spring in both countries, with the magnitude of seasonal effect ranging from 5 to 50 %. Our findings indicate that there are significant seasonal trends for both snoring and sleep apnea internet search engine queries, with a peak in the winter and early spring. Further research is indicated to determine the mechanisms underlying these findings, whether they have clinical impact, and if they are associated with other comorbid medical conditions that have similar patterns of seasonal exacerbation.

Seasonal variation in hemodialysis initiation: A single-center retrospective analysis.

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Yujiro Maeoka

Full Text Available The number of new dialysis patients has been increasing worldwide, particularly among elderly individuals. However, information on seasonal variation in hemodialysis initiation in recent decades is lacking, and the seasonal distribution of patients' conditions immediately prior to starting dialysis remains unclear. Having this information could help in developing a modifiable approach to improving pre-dialysis care. We retrospectively investigated the records of 297 patients who initiated hemodialysis at Hiroshima Prefectural Hospital from January 1st, 2009 to December 31st, 2013. Seasonal differences were assessed by χ2 or Kruskal-Wallis tests. Multiple comparison analysis was performed with the Steel test. The overall number of patients starting dialysis was greatest in winter (n = 85, 28.6%, followed by spring (n = 74, 24.9%, summer (n = 70, 23.6%, and autumn (n = 68, 22.9%, though the differences were not significant. However, there was a significant winter peak in dialysis initiation among patients aged ≥65 years, but not in those aged <65 years. Fluid overload assessed by clinicians was the most common uremic symptom among all patients, but a winter peak was only detected in patients aged ≥65 years. The body weight gain ratio showed a similar trend to fluid overload assessed by clinicians. Pulmonary edema was most pronounced in winter among patients aged ≥65 years compared with other seasons. The incidences of infection were modestly increased in summer and winter, but not statistically significant. Cardiac complications were similar in all seasons. This study demonstrated the existence of seasonal variation in dialysis initiation, with a winter peak among patients aged ≥65 years. The winter increment in dialysis initiation was mainly attributable to increased fluid overload. These findings suggest that elderly individuals should be monitored particularly closely during the winter.

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

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Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

2013-03-23

Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

Power, effects, confidence, and significance: an investigation of statistical practices in nursing research.

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Gaskin, Cadeyrn J; Happell, Brenda

2014-05-01

improvement. Most importantly, researchers should abandon the misleading practice of interpreting the results from inferential tests based solely on whether they are statistically significant (or not) and, instead, focus on reporting and interpreting effect sizes, confidence intervals, and significance levels. Nursing researchers also need to conduct and report a priori power analyses, and to address the issue of Type I experiment-wise error inflation in their studies. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Seasonal changes of vitamin A levels of serum in Khozestan Arab horses

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alireza ghadrdanmashhadi

2013-08-01

Full Text Available Vitamin A is one of the fat-soluble vitamins. Because of its particular role in different tissues and organs, various clinical signs are seen in deficiency conditions. In addition, sometimes marginal deficiency is present without obvious clinical signs but performance defects, such as infertility is seen. In present study seasonal changes of serum vitamin A in 22 Arab horses was investigated in Ahvaz. A simple and cheap method (spectrophotometrye was used for measuring vitamin A. The results were analyzed statistically by one- way analysis of variance (ANOVA. The results indicated that mean vitamin A values (20.37±1/21mg/dl were within normal range. The values of vitamin A in different seasons and two sexes were normal, too. Serum vitamin A value in spring was significantly higher than other seasons.

Cooking and season as risk factors for acute lower respiratory infections in African children: a cross-sectional multi-country analysis.

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Buchner, Hannes; Rehfuess, Eva A

2015-01-01

Acute lower respiratory infections (ALRI) are a leading cause of death among African children under five. A significant proportion of these are attributable to household air pollution from solid fuel use. We assessed the relationship between cooking practices and ALRI in pooled datasets of Demographic and Health Surveys conducted between 2000 and 2011 in countries of sub-Saharan Africa. The impacts of main cooking fuel, cooking location and stove ventilation were examined in 18 (n = 56,437), 9 (n = 23,139) and 6 countries (n = 14,561) respectively. We used a causal diagram and multivariable logistic mixed models to assess the influence of covariates at individual, regional and national levels. Main cooking fuel had a statistically significant impact on ALRI risk (pCooking location also emerged as a season-dependent statistically significant (p = 0.0070) determinant of ALRI, in particular cooking indoors without a separate kitchen during the rainy season (OR 1.80; CI: 1.30, 2.50). Due to infrequent use in Africa we could, however, not demonstrate an effect of stove ventilation. We found differential and season-dependent risks for different types of solid fuels and kerosene as well as cooking location on child ALRI. Future household air pollution studies should consider potential effect modification of cooking fuel by season.

Examining reproducibility in psychology : A hybrid method for combining a statistically significant original study and a replication

NARCIS (Netherlands)

Van Aert, R.C.M.; Van Assen, M.A.L.M.

2018-01-01

The unrealistically high rate of positive results within psychology has increased the attention to replication research. However, researchers who conduct a replication and want to statistically combine the results of their replication with a statistically significant original study encounter

A tutorial on hunting statistical significance by chasing N

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Denes Szucs

2016-09-01

Full Text Available There is increasing concern about the replicability of studies in psychology and cognitive neuroscience. Hidden data dredging (also called p-hacking is a major contributor to this crisis because it substantially increases Type I error resulting in a much larger proportion of false positive findings than the usually expected 5%. In order to build better intuition to avoid, detect and criticise some typical problems, here I systematically illustrate the large impact of some easy to implement and so, perhaps frequent data dredging techniques on boosting false positive findings. I illustrate several forms of two special cases of data dredging. First, researchers may violate the data collection stopping rules of null hypothesis significance testing by repeatedly checking for statistical significance with various numbers of participants. Second, researchers may group participants post-hoc along potential but unplanned independent grouping variables. The first approach 'hacks' the number of participants in studies, the second approach ‘hacks’ the number of variables in the analysis. I demonstrate the high amount of false positive findings generated by these techniques with data from true null distributions. I also illustrate that it is extremely easy to introduce strong bias into data by very mild selection and re-testing. Similar, usually undocumented data dredging steps can easily lead to having 20-50%, or more false positives.

Analysis of Spatiotemporal Statistical Properties of Rainfall in the Phoenix Metropolitan Area

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Mascaro, G.

2016-12-01

The analysis of the rainfall statistical properties at multiple spatiotemporal scales is a necessary preliminary step to support modeling of urban hydrology, including flood prediction and simulation of impacts of land use changes. In this contribution, the rainfall statistical properties are analyzed in the Phoenix Metropolitan area and its surroundings ( 29600 km2) in Arizona using observations from 310 gauges of the Flood Control District of the Maricopa County network. Different techniques are applied to investigate the rainfall properties at temporal scales from 1 min to years and to quantify the associated spatial variability. Results reveal the following. The rainfall regime is characterized by high interannual variability, which is partially explained by teleconnections with El Niño Southern Oscillation, and marked seasonality, with two maxima in the monsoon season from July to September and in winter from November to March. Elevation has a significant control on seasonal rainfall accumulation, strength of thermal convective activity during the monsoon, and peak occurrence of the rainfall diurnal cycle present in summer. The spatial correlation of wintertime rainfall is high even at short aggregation times (cells).

Seasonal dynamics of fecundity and recruitment of Temora longicornis in the Baltic Sea

DEFF Research Database (Denmark)

Dutz, J; van Beusekom, JEE; Hinrichs, R

2012-01-01

), female prosome length (PL) and weight-specific egg production (spEPR) were compared with the seasonal variations in temperature, salinity, and food concentration and composition. Females reproduced year round with maxima of 9.8 to 12.3 eggs female−1 d−1 in spring and low to moderate egg production during...... the remaining seasons. PL was maximal during spring, and %FS, sfEPR and spEPR paralleled egg production. HS was low during winter and increased in spring. The statistical analyses showed that mean egg production correlated with both sfEPR and %FS. While %FS was significantly related to food concentration, sf...

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

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

2015-08-01

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

A Principal Component Analysis (PCA Approach to Seasonal and Zooplankton Diversity Relationships in Fishing Grounds of Mannar Gulf, India

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Selvin J. PITCHAIKANI

2017-06-01

Full Text Available Principal component analysis (PCA is a technique used to emphasize variation and bring out strong patterns in a dataset. It is often used to make data easy to explore and visualize. The primary objective of the present study was to record information of zooplankton diversity in a systematic way and to study the variability and relationships among seasons prevailed in Gulf of Mannar. The PCA for the zooplankton seasonal diversity was investigated using the four seasonal datasets to understand the statistical significance among the four seasons. Two different principal components (PC were segregated in all the seasons homogeneously. PCA analyses revealed that Temora turbinata is an opportunistic species and zooplankton diversity was significantly different from season to season and principally, the zooplankton abundance and its dynamics in Gulf of Mannar is structured by seasonal current patterns. The factor loadings of zooplankton for different seasons in Tiruchendur coastal water (GOM is different compared with the Southwest coast of India; particularly, routine and opportunistic species were found within the positive and negative factors. The copepods Acrocalanus gracilis and Acartia erythrea were dominant in summer and Southwest monsoon due to the rainfall and freshwater discharge during the summer season; however, these species were replaced by Temora turbinata during Northeast monsoon season.

Trends and homogeneity of monthly, seasonal, and annual rainfall over arid region of Rajasthan, India

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Meena, Hari Mohan; Machiwal, Deepesh; Santra, Priyabrata; Moharana, Pratap Chandra; Singh, D. V.

2018-05-01

Knowledge of rainfall variability is important for regional-scale planning and management of water resources in agriculture. This study explores spatio-temporal variations, trends, and homogeneity in monthly, seasonal, and annual rainfall series of 62 stations located in arid region of Rajasthan, India using 55 year (1957-2011) data. Box-whisker plots indicate presence of outliers and extremes in annual rainfall, which made the distribution of annual rainfall right-skewed. Mean and coefficient of variation (CV) of rainfall reveals a high inter-annual variability (CV > 200%) in the western portion where the mean annual rainfall is very low. A general gradient of the mean monthly, seasonal, and annual rainfall is visible from northwest to southeast direction, which is orthogonal to the gradient of CV. The Sen's innovative trend test is found over-sensitive in evaluating statistical significance of the rainfall trends, while the Mann-Kendall test identifies significantly increasing rainfall trends in June and September. Rainfall in July shows prominently decreasing trends although none of them are found statistically significant. Monsoon and annual rainfall show significantly increasing trends at only four stations. The magnitude of trends indicates that the rainfall is increasing at a mean rate of 1.11, 2.85, and 2.89 mm year-1 in August, monsoon season, and annual series. The rainfall is found homogeneous over most of the area except for few stations situated in the eastern and northwest portions where significantly increasing trends are observed. Findings of this study indicate that there are few increasing trends in rainfall of this Indian arid region.

Season of birth and the risk of hip fracture in danish men and women aged 65+

DEFF Research Database (Denmark)

Abrahamsen, Bo; Heitmann, Berit L; Eiken, Pia Agnete

2012-01-01

calculated fracture rates and relative risks. The analysis covered 541,109 men and 691,522 women. In women, we observed a small but statistically significant difference between fracture rates by season of birth for all age intervals expect the youngest (age 65-69). A similar pattern was seen in men...... an epidemiological analysis of hip fracture rates as a function of season of birth, age, and sex. We retrieved information on all hip fractures in the 9-year period between 1997 and 2005 in all men and women aged 65-95, excluded hip fractures that occurred in current and recent prednisolone users, and subsequently......, but this was only statistically significant in the two oldest age groups (age 85-89 and 90-95). These findings suggest that vitamin D availability in the first and second trimester of intrauterine life could have a small but lasting impact on bone health and the risk of osteoporotic fractures. Further studies...

Seasonal variations of vivax and falciparum malaria: an observation at a tertiary care hospital

International Nuclear Information System (INIS)

Jamil, S.; Khan, M.N.

2012-01-01

Background: Malaria is a major public health problem in the malaria endemic zones of the world. Various factors influence the prevalence of malaria. This study was conducted to determine the variation in frequency of Plasmodium vivax and Plasmodium falciparum malaria in different seasons of the year in Khyber Teaching Hospital, Peshawar. Methods: A total of 411 patients were included in the study. All these febrile patients were reported to have trophozoites of either Plasmodium vivax or Plasmodium falciparum malaria on Giemsa stained thick and thin smears. The frequency of vivax and falciparum malaria was worked out and statistically analysed for different season of the year. The study was carried out from 2nd Jan 2004 till 31st December 2008. Results: Out of total 411 diagnosed malaria cases, total 134 (32.60%) presented in the autumn season (vivax=33.58%, and falciparum=66.42%), 37 (9%) in winter season (vivax=32.4%, and falciparum=67.6%), 76 (18.49%) in spring season (vivax=93.4% and falciparum 6.6%) and 164 (39.90%) in summer season (vivax=89.6, and falciparum=10.4%). The malaria showed a highly significant pattern in different seasons of the year (p=0.00) in a way that Plasmodium falciparum malaria reached its highest frequency in autumn and winter seasons while Plasmodium vivax malaria reached its peak frequency in spring and summer seasons. Conclusion: There was highly significant seasonal variation of vivax and falciparum malaria. There is arrival of Plasmodium falciparum in autumn which peaks in winter followed by arrival of Plasmodium vivax in spring till the end of summer. (author)

Trends in annual, seasonal, and monthly streamflow characteristics at 227 streamgages in the Missouri River watershed, water years 1960-2011

Science.gov (United States)

Norton, Parker A.; Anderson, Mark T.; Stamm, John F.

2014-01-01

The Missouri River and its tributaries are an important resource that serve multiple uses including agriculture, energy, recreation, and municipal water supply. Understanding historical streamflow characteristics provides relevant guidance to adaptive management of these water resources. Streamflow records in the Missouri River watershed were examined for trends in time series of annual, seasonal, and monthly streamflow. A total of 227 streamgages having continuous observational records for water years 1960–2011 were examined. Kendall’s tau nonparametric test was used to determine statistical significance of trends in annual, seasonal, and monthly streamflow. A trend was considered statistically significant for a probability value less than or equal to 0.10 that the Kendall’s tau value equals zero. Significant trends in annual streamflow were indicated for 101 out of a total of 227 streamgages. The Missouri River watershed was divided into six watershed regions and trends within regions were examined. The western and the southern parts of the Missouri River watershed had downward trends in annual streamflow (56 streamgages), whereas the eastern part of the watershed had upward trends in streamflow (45 streamgages). Seasonal and monthly streamflow trends reflected prevailing annual streamflow trends within each watershed region.

Light therapy for non-seasonal depression: systematic review and meta-analysis.

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Perera, Stefan; Eisen, Rebecca; Bhatt, Meha; Bhatnagar, Neera; de Souza, Russell; Thabane, Lehana; Samaan, Zainab

2016-03-01

Light therapy is a known treatment for patients with seasonal affective disorder. However, the efficacy of light therapy in treating patients with non-seasonal depression remains inconclusive. To provide the current state of evidence for efficacy of light therapy in non-seasonal depressive disorders. Systematic review of randomised controlled trials (RCTs) was conducted by searching MEDLINE, EMBASE, PsycINFO, CINAHL, and CENTRAL from their inception to September 2015. Study selection, data abstraction and risk of bias assessment were independently conducted in duplicate. Meta-analyses were performed to provide a summary statistic for the included RCTs. The reporting of this systematic review follows the PRISMA guidelines. A meta-analysis including 881 participants from 20 RCTs demonstrated a beneficial effect of light therapy in non-seasonal depression (standardised mean difference in depression score -0.41 (95% CI -0.64 to -0.18)). This estimate was associated with significant heterogeneity ( I 2 =60%, P =0.0003) that was not sufficiently explained by subgroup analyses. There was also high risk of bias in the included trials limiting the study interpretation. The overall quality of evidence is poor due to high risk of bias and inconsistency. However, considering that light therapy has minimal side-effects and our meta-analysis demonstrated that a significant proportion of patients achieved a clinically significant response, light therapy may be effective for patients with non-seasonal depression and can be a helpful additional therapeutic intervention for depression. None. © The Royal College of Psychiatrists 2016. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) licence.

Seasonality of absolute humidity explains seasonality of influenza-like illness in Vietnam.

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Thai, Pham Quang; Choisy, Marc; Duong, Tran Nhu; Thiem, Vu Dinh; Yen, Nguyen Thu; Hien, Nguyen Tran; Weiss, Daniel J; Boni, Maciej F; Horby, Peter

2015-12-01

Experimental and ecological studies have shown the role of climatic factors in driving the epidemiology of influenza. In particular, low absolute humidity (AH) has been shown to increase influenza virus transmissibility and has been identified to explain the onset of epidemics in temperate regions. Here, we aim to study the potential climatic drivers of influenza-like illness (ILI) epidemiology in Vietnam, a tropical country characterized by a high diversity of climates. We specifically focus on quantifying and explaining the seasonality of ILI. We used 18 years (1993-2010) of monthly ILI notifications aggregated by province (52) and monthly climatic variables (minimum, mean, maximum temperatures, absolute and relative humidities, rainfall and hours of sunshine) from 67 weather stations across Vietnam. Seasonalities were quantified from global wavelet spectra, using the value of the power at the period of 1 year as a measure of the intensity of seasonality. The 7 climatic time series were characterized by 534 summary statistics which were entered into a regression tree to identify factors associated with the seasonality of AH. Results were extrapolated to the global scale using simulated climatic times series from the NCEP/NCAR project. The intensity of ILI seasonality in Vietnam is best explained by the intensity of AH seasonality. We find that ILI seasonality is weak in provinces experiencing weak seasonal fluctuations in AH (annual power power >17.6). In Vietnam, AH and ILI are positively correlated. Our results identify a role for AH in driving the epidemiology of ILI in a tropical setting. However, in contrast to temperate regions, high rather than low AH is associated with increased ILI activity. Fluctuation in AH may be the climate factor that underlies and unifies the seasonality of ILI in both temperate and tropical regions. Alternatively, the mechanism of action of AH on disease transmission may be different in cold-dry versus hot-humid settings

Variability of thermal and precipitation conditions in the growing season in Poland in the years 1966-2015

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Tomczyk, Arkadiusz M.; Szyga-Pluta, Katarzyna

2018-03-01

The aim of the study was to identify the thermal and precipitation conditions and their changes in the growing season in Poland in the years 1966-2015. Data on average daily air temperature and daily precipitation totals for 30 stations from the period of 1966-2015 were used. The data were obtained from the collections of the Institute of Meteorology and Water Management—National Research Institute. The growing season was defined as the period of average daily air temperature ≥ 5 °C. The mathematical formulas proposed by Gumiński (1948) were used to determine its start and end dates. In the growing season in Poland in the years 1966-2015, there were more significant changes in the thermal conditions than there were in the precipitation conditions. In terms of long-term trends over the study period, thermal conditions during the growing season are characterised by an increase in mean air temperature, an increase in the sum of air temperatures and an increasing occurrence of seasons classified as above-normal seasons. Precipitation conditions of the growing season show large temporal and spatial variations in precipitation and a predominance of normal conditions. The changes in precipitation were not statistically significant, except for Świnoujście.

A critical discussion of null hypothesis significance testing and statistical power analysis within psychological research

DEFF Research Database (Denmark)

Jones, Allan; Sommerlund, Bo

2007-01-01

The uses of null hypothesis significance testing (NHST) and statistical power analysis within psychological research are critically discussed. The article looks at the problems of relying solely on NHST when dealing with small and large sample sizes. The use of power-analysis in estimating...... the potential error introduced by small and large samples is advocated. Power analysis is not recommended as a replacement to NHST but as an additional source of information about the phenomena under investigation. Moreover, the importance of conceptual analysis in relation to statistical analysis of hypothesis...

Alterations of white matter integrity related to the season of birth in schizophrenia: a DTI study.

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Stéphanie Giezendanner

Full Text Available In schizophrenia there is a consistent epidemiological finding of a birth excess in winter and spring. Season of birth is thought to act as a proxy indicator for harmful environmental factors during foetal maturation. There is evidence that prenatal exposure to harmful environmental factors may trigger pathologic processes in the neurodevelopment, which subsequently increase the risk of schizophrenia. Since brain white matter alterations have repeatedly been found in schizophrenia, the objective of this study was to investigate whether white matter integrity was related to the season of birth in patients with schizophrenia. Thirty-four patients with schizophrenia and 33 healthy controls underwent diffusion tensor imaging. Differences in the fractional anisotropy maps of schizophrenia patients and healthy controls born in different seasons were analysed with tract-based spatial statistics. A significant main effect of season of birth and an interaction of group and season of birth showed that patients born in summer had significantly lower fractional anisotropy in widespread white matter regions than those born in the remainder of the year. Additionally, later age of schizophrenia onset was found in patients born in winter months. The current findings indicate a relationship of season of birth and white matter alterations in schizophrenia and consequently support the neurodevelopmental hypothesis of early pathological mechanisms in schizophrenia.

Seasonal patterns of mixed species groups in large East African mammals.

Science.gov (United States)

Kiffner, Christian; Kioko, John; Leweri, Cecilia; Krause, Stefan

2014-01-01

Mixed mammal species groups are common in East African savannah ecosystems. Yet, it is largely unknown if co-occurrences of large mammals result from random processes or social preferences and if interspecific associations are consistent across ecosystems and seasons. Because species may exchange important information and services, understanding patterns and drivers of heterospecific interactions is crucial for advancing animal and community ecology. We recorded 5403 single and multi-species clusters in the Serengeti-Ngorongoro and Tarangire-Manyara ecosystems during dry and wet seasons and used social network analyses to detect patterns of species associations. We found statistically significant associations between multiple species and association patterns differed spatially and seasonally. Consistently, wildebeest and zebras preferred being associated with other species, whereas carnivores, African elephants, Maasai giraffes and Kirk's dik-diks avoided being in mixed groups. During the dry season, we found that the betweenness (a measure of importance in the flow of information or disease) of species did not differ from a random expectation based on species abundance. In contrast, in the wet season, we found that these patterns were not simply explained by variations in abundances, suggesting that heterospecific associations were actively formed. These seasonal differences in observed patterns suggest that interspecific associations may be driven by resource overlap when resources are limited and by resource partitioning or anti-predator advantages when resources are abundant. We discuss potential mechanisms that could drive seasonal variation in the cost-benefit tradeoffs that underpin the formation of mixed-species groups.

Timing of floods in southeastern China: Seasonal properties and potential causes

Science.gov (United States)

Zhang, Qiang; Gu, Xihui; Singh, Vijay P.; Shi, Peijun; Luo, Ming

2017-09-01

Flood hazards and flood risks in southeastern China have been causing increasing concerns due to dense population and highly-developed economy. This study attempted to address changes of seasonality, timing of peak floods and variability of occurrence date of peak floods using circular statistical methods and the modified Mann-Kendall trend detection method. The causes of peak flood changes were also investigated. Results indicated that: (1) floods were subject to more seasonality and temporal clustering when compared to precipitation extremes. However, seasonality of floods and extreme precipitation was subject to spatial heterogeneity in northern Guangdong. Similar changing patterns of peak floods and extreme precipitation were found in coastal regions; (2) significant increasing/decreasing seasonality, but no confirmed spatial patterns, were observed for peak floods and extreme precipitation. Peak floods in northern Guangdong province had decreasing variability, but had larger variability in coastal regions; (3) tropical cyclones had remarkable impacts on extreme precipitation changes in coastal regions of southeastern China, and peak floods as well. The landfalling of tropical cyclones was decreasing and concentrated during June-September; this is the major reason for earlier but enhanced seasonality of peak floods in coastal regions. This study sheds new light on flood behavior in coastal regions in a changing environment.

Statistical bias correction modelling for seasonal rainfall forecast for the case of Bali island

Science.gov (United States)

Lealdi, D.; Nurdiati, S.; Sopaheluwakan, A.

2018-04-01

Rainfall is an element of climate which is highly influential to the agricultural sector. Rain pattern and distribution highly determines the sustainability of agricultural activities. Therefore, information on rainfall is very useful for agriculture sector and farmers in anticipating the possibility of extreme events which often cause failures of agricultural production. This research aims to identify the biases from seasonal forecast products from ECMWF (European Centre for Medium-Range Weather Forecasts) rainfall forecast and to build a transfer function in order to correct the distribution biases as a new prediction model using quantile mapping approach. We apply this approach to the case of Bali Island, and as a result, the use of bias correction methods in correcting systematic biases from the model gives better results. The new prediction model obtained with this approach is better than ever. We found generally that during rainy season, the bias correction approach performs better than in dry season.

Statistical significance estimation of a signal within the GooFit framework on GPUs

Directory of Open Access Journals (Sweden)

Cristella Leonardo

2017-01-01

Full Text Available In order to test the computing capabilities of GPUs with respect to traditional CPU cores a high-statistics toy Monte Carlo technique has been implemented both in ROOT/RooFit and GooFit frameworks with the purpose to estimate the statistical significance of the structure observed by CMS close to the kinematical boundary of the J/ψϕ invariant mass in the three-body decay B+ → J/ψϕK+. GooFit is a data analysis open tool under development that interfaces ROOT/RooFit to CUDA platform on nVidia GPU. The optimized GooFit application running on GPUs hosted by servers in the Bari Tier2 provides striking speed-up performances with respect to the RooFit application parallelised on multiple CPUs by means of PROOF-Lite tool. The considerable resulting speed-up, evident when comparing concurrent GooFit processes allowed by CUDA Multi Process Service and a RooFit/PROOF-Lite process with multiple CPU workers, is presented and discussed in detail. By means of GooFit it has also been possible to explore the behaviour of a likelihood ratio test statistic in different situations in which the Wilks Theorem may or may not apply because its regularity conditions are not satisfied.

Statistical prediction of seasonal discharge in Central Asia for water resources management: development of a generic (pre-)operational modeling tool

Science.gov (United States)

Apel, Heiko; Baimaganbetov, Azamat; Kalashnikova, Olga; Gavrilenko, Nadejda; Abdykerimova, Zharkinay; Agalhanova, Marina; Gerlitz, Lars; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Gafurov, Abror

2017-04-01

The semi-arid regions of Central Asia crucially depend on the water resources supplied by the mountainous areas of the Tien-Shan and Pamirs. During the summer months the snow and glacier melt dominated river discharge originating in the mountains provides the main water resource available for agricultural production, but also for storage in reservoirs for energy generation during the winter months. Thus a reliable seasonal forecast of the water resources is crucial for a sustainable management and planning of water resources. In fact, seasonal forecasts are mandatory tasks of all national hydro-meteorological services in the region. In order to support the operational seasonal forecast procedures of hydromet services, this study aims at the development of a generic tool for deriving statistical forecast models of seasonal river discharge. The generic model is kept as simple as possible in order to be driven by available hydrological and meteorological data, and be applicable for all catchments with their often limited data availability in the region. As snowmelt dominates summer runoff, the main meteorological predictors for the forecast models are monthly values of winter precipitation and temperature as recorded by climatological stations in the catchments. These data sets are accompanied by snow cover predictors derived from the operational ModSnow tool, which provides cloud free snow cover data for the selected catchments based on MODIS satellite images. In addition to the meteorological data antecedent streamflow is used as a predictor variable. This basic predictor set was further extended by multi-monthly means of the individual predictors, as well as composites of the predictors. Forecast models are derived based on these predictors as linear combinations of up to 3 or 4 predictors. A user selectable number of best models according to pre-defined performance criteria is extracted automatically by the developed model fitting algorithm, which includes a test

Regional, Seasonal, and Temporal Variations in the Prevalence of Antimicrobial-Resistant Escherichia coli Isolated from Pigs at Slaughter in Denmark (1997-2005)

DEFF Research Database (Denmark)

Abatih, E. N.; Emborg, Hanne-Dorthe; Jensen, Vibeke Frøkjær

2009-01-01

The aim of this study was to analyze and discuss regional, seasonal, and temporal trends in the occurrence of antimicrobial-resistant Escherichia coli isolated from pigs at slaughter in Denmark between 1997 and 2005. Data on antimicrobial-resistant E. coli were obtained from the Danish Integrated...... Antimicrobial Resistance Monitoring and Research Programme database. The Cochran-Armitage trend test was used to detect the presence and evaluate the significance of regional, seasonal, and annual trends in the occurrence of antimicrobial-resistant E. coli for four drugs. Associations between resistance...... of resistant E. coli as compared to the other seasons of the year. Our study provides evidence of statistically significant regional, seasonal, and temporal variations for ampicillin- and streptomycin-resistant E. coli isolated from pigs at slaughter in Denmark between 1997 and 2005....

Preseason Aerobic Fitness Predicts In-Season Injury and Illness in Female Youth Athletes.

Science.gov (United States)

Watson, Andrew; Brickson, Stacey; Brooks, M Alison; Dunn, Warren

2017-09-01

Although preseason aerobic fitness has been suggested as a modifiable risk factor for injury in adult athletes, the relationship between aerobic fitness, injury, and illness in youth athletes is unknown. To determine whether preseason aerobic fitness predicts in-season injury and illness risk in female adolescent soccer players. Case-control study; Level of evidence, 3. Fifty-four female adolescent soccer players underwent preseason evaluation to determine years of experience, body mass index (BMI), maximal aerobic capacity (VO 2max ), and time to exhaustion (T max ) during cycle ergometer testing. All injuries and illnesses during the subsequent 20-week season were recorded. Variables were compared between individuals with and without a self-reported injury and individuals with and without a self-reported illness. Separate Poisson regression models were developed to predict number of injuries and illnesses for each individual by use of age, years of experience, BMI, VO 2max , and T max. Twenty-eight injuries and 38 illnesses in 23 individuals were recorded during the season. Although not a statistically significant finding, individuals who reported an in-season injury had lower VO 2max than those who did not (54.9 ± 7.3 vs 58.3 ± 8.5 mL/kg/min, P = .13). Individuals who reported an illness had significantly lower VO 2max than those who did not (54.5 ± 9.9 vs 58.8 ± 6.2 mL/kg/min, P = .014). With the Poisson regression models, VO 2max was a significant predictor of both injury (odds ratio [OR], 0.95; P = .046) and illness (OR, 0.94; P = .009), while no significant relationships were identified between injury or illness and age, years of experience, T max , or BMI (all P > .05). Among adolescent female soccer players, greater preseason aerobic fitness is associated with a reduced risk of in-season injury and illness. Off-season intervention to promote aerobic fitness may help reduce the risk of lost time during the season due to injury and illness.

Comparison of long-term Moscow and Danish NLC observations: statistical results

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P. Dalin

2006-11-01

Full Text Available Noctilucent clouds (NLC are the highest clouds in the Earth's atmosphere, observed close to the mesopause at 80–90 km altitudes. Systematic NLC observations conducted in Moscow for the period of 1962–2005 and in Denmark for 1983–2005 are compared and statistical results both for seasonally summarized NLC parameters and for individual NLC appearances are described. Careful attention is paid to the weather conditions during each season of observations. This turns out to be a very important factor both for the NLC case study and for long-term data set analysis. Time series of seasonal values show moderate similarity (taking into account the weather conditions but, at the same time, the comparison of individual cases of NLC occurrence reveals substantial differences. There are positive trends in the Moscow and Danish normalized NLC brightness as well as nearly zero trend in the Moscow normalized NLC occurrence frequency but these long-term changes are not statistically significant. The quasi-ten-year cycle in NLC parameters is about 1 year shorter than the solar cycle during the same period. The characteristic scale of NLC fields is estimated for the first time and it is found to be less than 800 km.

Is statistical significance clinically important?--A guide to judge the clinical relevance of study findings

NARCIS (Netherlands)

Sierevelt, Inger N.; van Oldenrijk, Jakob; Poolman, Rudolf W.

2007-01-01

In this paper we describe several issues that influence the reporting of statistical significance in relation to clinical importance, since misinterpretation of p values is a common issue in orthopaedic literature. Orthopaedic research is tormented by the risks of false-positive (type I error) and

Measuring the potential utility of seasonal climate predictions

Science.gov (United States)

Tippett, Michael K.; Kleeman, Richard; Tang, Youmin

2004-11-01

Variation of sea surface temperature (SST) on seasonal-to-interannual time-scales leads to changes in seasonal weather statistics and seasonal climate anomalies. Relative entropy, an information theory measure of utility, is used to quantify the impact of SST variations on seasonal precipitation compared to natural variability. An ensemble of general circulation model (GCM) simulations is used to estimate this quantity in three regions where tropical SST has a large impact on precipitation: South Florida, the Nordeste of Brazil and Kenya. We find the yearly variation of relative entropy is strongly correlated with shifts in ensemble mean precipitation and weakly correlated with ensemble variance. Relative entropy is also found to be related to measures of the ability of the GCM to reproduce observations.

Forecasting droughts in West Africa: Operational practice and refined seasonal precipitation forecasts

Science.gov (United States)

Bliefernicht, Jan; Siegmund, Jonatan; Seidel, Jochen; Arnold, Hanna; Waongo, Moussa; Laux, Patrick; Kunstmann, Harald

2016-04-01

Precipitation forecasts for the upcoming rainy seasons are one of the most important sources of information for an early warning of droughts and water scarcity in West Africa. The meteorological services in West Africa perform seasonal precipitation forecasts within the framework of PRESAO (the West African climate outlook forum) since the end of the 1990s. Various sources of information and statistical techniques are used by the individual services to provide a harmonized seasonal precipitation forecasts for decision makers in West Africa. In this study, we present a detailed overview of the operational practice in West Africa including a first statistical assessment of the performance of the precipitation forecasts for drought situations for the past 18 years (1998 to 2015). In addition, a long-term hindcasts (1982 to 2009) and a semi-operational experiment for the rainy season 2013 using statistical and/or dynamical downscaling are performed to refine the precipitation forecasts from the Climate Forecast System Version 2 (CFSv2), a global ensemble prediction system. This information is post-processed to provide user-oriented precipitation indices such as the onset of the rainy season for supporting water and land use management for rain-fed agriculture. The evaluation of the individual techniques is performed focusing on water-scarce regions of the Volta basin in Burkina Faso and Ghana. The forecasts of the individual techniques are compared to state-of-the-art global observed precipitation products and a novel precipitation database based on long-term daily rain-gage measurements provided by the national meteorological services. The statistical assessment of the PRESAO forecasts indicates skillful seasonal precipitation forecasts for many locations in the Volta basin, particularly for years with water deficits. The operational experiment for the rainy season 2013 illustrates the high potential of a physically-based downscaling for this region but still shows

Statistical significance of theoretical predictions: A new dimension in nuclear structure theories (I)

International Nuclear Information System (INIS)

DUDEK, J; SZPAK, B; FORNAL, B; PORQUET, M-G

2011-01-01

In this and the follow-up article we briefly discuss what we believe represents one of the most serious problems in contemporary nuclear structure: the question of statistical significance of parametrizations of nuclear microscopic Hamiltonians and the implied predictive power of the underlying theories. In the present Part I, we introduce the main lines of reasoning of the so-called Inverse Problem Theory, an important sub-field in the contemporary Applied Mathematics, here illustrated on the example of the Nuclear Mean-Field Approach.

Seasonal patterns of mixed species groups in large East African mammals.

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Christian Kiffner

Full Text Available Mixed mammal species groups are common in East African savannah ecosystems. Yet, it is largely unknown if co-occurrences of large mammals result from random processes or social preferences and if interspecific associations are consistent across ecosystems and seasons. Because species may exchange important information and services, understanding patterns and drivers of heterospecific interactions is crucial for advancing animal and community ecology. We recorded 5403 single and multi-species clusters in the Serengeti-Ngorongoro and Tarangire-Manyara ecosystems during dry and wet seasons and used social network analyses to detect patterns of species associations. We found statistically significant associations between multiple species and association patterns differed spatially and seasonally. Consistently, wildebeest and zebras preferred being associated with other species, whereas carnivores, African elephants, Maasai giraffes and Kirk's dik-diks avoided being in mixed groups. During the dry season, we found that the betweenness (a measure of importance in the flow of information or disease of species did not differ from a random expectation based on species abundance. In contrast, in the wet season, we found that these patterns were not simply explained by variations in abundances, suggesting that heterospecific associations were actively formed. These seasonal differences in observed patterns suggest that interspecific associations may be driven by resource overlap when resources are limited and by resource partitioning or anti-predator advantages when resources are abundant. We discuss potential mechanisms that could drive seasonal variation in the cost-benefit tradeoffs that underpin the formation of mixed-species groups.

Seasonal differences in leaf-level physiology give lianas a competitive advantage over trees in a tropical seasonal forest.

Science.gov (United States)

Cai, Zhi-Quan; Schnitzer, Stefan A; Bongers, Frans

2009-08-01

Lianas are an important component of most tropical forests, where they vary in abundance from high in seasonal forests to low in seasonal forests. We tested the hypothesis that the physiological ability of lianas to fix carbon (and thus grow) during seasonal drought may confer a distinct advantage in seasonal tropical forests, which may explain pan-tropical liana distributions. We compared a range of leaf-level physiological attributes of 18 co-occurring liana and 16 tree species during the wet and dry seasons in a tropical seasonal forest in Xishuangbanna, China. We found that, during the wet season, lianas had significantly higher CO(2) assimilation per unit mass (A(mass)), nitrogen concentration (N(mass)), and delta(13)C values, and lower leaf mass per unit area (LMA) than trees, indicating that lianas have higher assimilation rates per unit leaf mass and higher integrated water-use efficiency (WUE), but lower leaf structural investments. Seasonal variation in CO(2) assimilation per unit area (A(area)), phosphorus concentration per unit mass (P(mass)), and photosynthetic N-use efficiency (PNUE), however, was significantly lower in lianas than in trees. For instance, mean tree A(area) decreased by 30.1% from wet to dry season, compared with only 12.8% for lianas. In contrast, from the wet to dry season mean liana delta(13)C increased four times more than tree delta(13)C, with no reduction in PNUE, whereas trees had a significant reduction in PNUE. Lianas had higher A(mass) than trees throughout the year, regardless of season. Collectively, our findings indicate that lianas fix more carbon and use water and nitrogen more efficiently than trees, particularly during seasonal drought, which may confer a competitive advantage to lianas during the dry season, and thus may explain their high relative abundance in seasonal tropical forests.

Long-Term Changes in the Extreme Significant Wave Heights on the Western North Pacific: Impacts of Tropical Cyclone Activity and ENSO

Science.gov (United States)

Yang, Sinil; Oh, Jaiho

2018-02-01

Seasonal extreme wave statistics were reproduced by using the 25-km-grid global wave model of WAVEWATCH-III. The results showed that the simulated wave dataset for the present climate (1979-2009) was similar to Climate Forecast System Reanalysis (CFSR) wave data. Statistics such as the root mean squared error (RMSE) and correlation coefficient (CC) over the western North Pacific (WNP) basin were 0.5 m and 0.69 over the analysis domain. The largest trends and standard deviation were around the southern coast of Japan and western edge of the WNP. Linear regression analysis was employed to identify the relationship between the leading principal components (PCs) of significant wave heights (SWHs) in the peak season of July to September and sea surface temperature (SST) anomalies in the equatorial Pacific. The results indicated that the inter-annual variability of SWH can be associated with the El Niño-Southern Oscillation in the peak season. The CC between the first PC of the SWH and anomalies in the Nino 3.4 SST index was also significant at a 99% confidence level. Significant variations in the SWH are affected by tropical cyclones (TCs) caused by increased SST anomalies. The genesis and development of simulated TCs can be important to the variation in SWHs for the WNP in the peak season. Therefore, we can project the variability of SWHs through TC activity based on changes in SST conditions for the equatorial Pacific in the future.

Football goal distributions and extremal statistics

Science.gov (United States)

Greenhough, J.; Birch, P. C.; Chapman, S. C.; Rowlands, G.

2002-12-01

We analyse the distributions of the number of goals scored by home teams, away teams, and the total scored in the match, in domestic football games from 169 countries between 1999 and 2001. The probability density functions (PDFs) of goals scored are too heavy-tailed to be fitted over their entire ranges by Poisson or negative binomial distributions which would be expected for uncorrelated processes. Log-normal distributions cannot include zero scores and here we find that the PDFs are consistent with those arising from extremal statistics. In addition, we show that it is sufficient to model English top division and FA Cup matches in the seasons of 1970/71-2000/01 on Poisson or negative binomial distributions, as reported in analyses of earlier seasons, and that these are not consistent with extremal statistics.

Simulation-optimization framework for multi-site multi-season hybrid stochastic streamflow modeling

Science.gov (United States)

Srivastav, Roshan; Srinivasan, K.; Sudheer, K. P.

2016-11-01

A simulation-optimization (S-O) framework is developed for the hybrid stochastic modeling of multi-site multi-season streamflows. The multi-objective optimization model formulated is the driver and the multi-site, multi-season hybrid matched block bootstrap model (MHMABB) is the simulation engine within this framework. The multi-site multi-season simulation model is the extension of the existing single-site multi-season simulation model. A robust and efficient evolutionary search based technique, namely, non-dominated sorting based genetic algorithm (NSGA - II) is employed as the solution technique for the multi-objective optimization within the S-O framework. The objective functions employed are related to the preservation of the multi-site critical deficit run sum and the constraints introduced are concerned with the hybrid model parameter space, and the preservation of certain statistics (such as inter-annual dependence and/or skewness of aggregated annual flows). The efficacy of the proposed S-O framework is brought out through a case example from the Colorado River basin. The proposed multi-site multi-season model AMHMABB (whose parameters are obtained from the proposed S-O framework) preserves the temporal as well as the spatial statistics of the historical flows. Also, the other multi-site deficit run characteristics namely, the number of runs, the maximum run length, the mean run sum and the mean run length are well preserved by the AMHMABB model. Overall, the proposed AMHMABB model is able to show better streamflow modeling performance when compared with the simulation based SMHMABB model, plausibly due to the significant role played by: (i) the objective functions related to the preservation of multi-site critical deficit run sum; (ii) the huge hybrid model parameter space available for the evolutionary search and (iii) the constraint on the preservation of the inter-annual dependence. Split-sample validation results indicate that the AMHMABB model is

Statistical Significance of the Contribution of Variables to the PCA Solution: An Alternative Permutation Strategy

Science.gov (United States)

Linting, Marielle; van Os, Bart Jan; Meulman, Jacqueline J.

2011-01-01

In this paper, the statistical significance of the contribution of variables to the principal components in principal components analysis (PCA) is assessed nonparametrically by the use of permutation tests. We compare a new strategy to a strategy used in previous research consisting of permuting the columns (variables) of a data matrix…

Predictability of Seasonal Rainfall over the Greater Horn of Africa

Science.gov (United States)

Ngaina, J. N.

2016-12-01

The El Nino-Southern Oscillation (ENSO) is a primary mode of climate variability in the Greater of Africa (GHA). The expected impacts of climate variability and change on water, agriculture, and food resources in GHA underscore the importance of reliable and accurate seasonal climate predictions. The study evaluated different model selection criteria which included the Coefficient of determination (R2), Akaike's Information Criterion (AIC), Bayesian Information Criterion (BIC), and the Fisher information approximation (FIA). A forecast scheme based on the optimal model was developed to predict the October-November-December (OND) and March-April-May (MAM) rainfall. The predictability of GHA rainfall based on ENSO was quantified based on composite analysis, correlations and contingency tables. A test for field-significance considering the properties of finiteness and interdependence of the spatial grid was applied to avoid correlations by chance. The study identified FIA as the optimal model selection criterion. However, complex model selection criteria (FIA followed by BIC) performed better compared to simple approach (R2 and AIC). Notably, operational seasonal rainfall predictions over the GHA makes of simple model selection procedures e.g. R2. Rainfall is modestly predictable based on ENSO during OND and MAM seasons. El Nino typically leads to wetter conditions during OND and drier conditions during MAM. The correlations of ENSO indices with rainfall are statistically significant for OND and MAM seasons. Analysis based on contingency tables shows higher predictability of OND rainfall with the use of ENSO indices derived from the Pacific and Indian Oceans sea surfaces showing significant improvement during OND season. The predictability based on ENSO for OND rainfall is robust on a decadal scale compared to MAM. An ENSO-based scheme based on an optimal model selection criterion can thus provide skillful rainfall predictions over GHA. This study concludes that the

Statistics As Principled Argument

CERN Document Server

Abelson, Robert P

2012-01-01

In this illuminating volume, Robert P. Abelson delves into the too-often dismissed problems of interpreting quantitative data and then presenting them in the context of a coherent story about one's research. Unlike too many books on statistics, this is a remarkably engaging read, filled with fascinating real-life (and real-research) examples rather than with recipes for analysis. It will be of true interest and lasting value to beginning graduate students and seasoned researchers alike. The focus of the book is that the purpose of statistics is to organize a useful argument from quantitative

Sub-seasonal prediction over East Asia during boreal summer using the ECCC monthly forecasting system

Science.gov (United States)

Liang, Ping; Lin, Hai

2018-02-01

A useful sub-seasonal forecast is of great societal and economical value in the highly populated East Asian region, especially during boreal summer when frequent extreme events such as heat waves and persistent heavy rainfalls occur. Despite recent interest and development in sub-seasonal prediction, it is still unclear how skillful dynamical forecasting systems are in East Asia beyond 2 weeks. In this study we evaluate the sub-seasonal prediction over East Asia during boreal summer in the operational monthly forecasting system of Environment and Climate Change Canada (ECCC).Results show that the climatological intra-seasonal oscillation (CISO) of East Asian summer monsoonis reasonably well captured. Statistically significant forecast skill of 2-meter air temperature (T2m) is achieved for all lead times up to week 4 (days 26-32) over East China and Northeast Asia, which is consistent with the skill in 500 hPa geopotential height (Z500). Significant forecast skill of precipitation, however, is limited to the week of days 5-11. Possible sources of predictability on the sub-seasonal time scale are analyzed. The weekly mean T2m anomaly over East China is found to be linked to an eastward propagating extratropical Rossby wave from the North Atlantic across Europe to East Asia. The Madden-Julian Oscillation (MJO) and El Nino-Southern Oscillation (ENSO) are also likely to influence the forecast skill of T2m at the sub-seasonal timescale over East Asia.

Season-to-Season Variations of Physiological Fitness Within a Squad of Professional Male Soccer Players

Science.gov (United States)

Clark, Niall A.; Edwards, Andrew M.; Morton, R. Hugh; Butterly, Ronald J.

2008-01-01

The purpose of this study was to examine season-to-season variations in physiological fitness parameters among a 1st team squad of professional adult male soccer players for the confirmatory purposes of identifying normative responses (immediately prior to pre-season training (PPS), mid-season (MID), and end-of-season (EOS)). Test-retest data were collected from a student population on the primary dependent variables of anaerobic threshold (AT) and maximal aerobic power (VO2 max) to define meaningful measurement change in excess of test-retest technical error between test-to-test performances. Participants from a pool of 42 professional soccer players were tested over a set sequence of tests during the 3-year period: 1) basic anthropometry, 2) countermovement jump (CMJ) tests 3) a combined AT and VO2 max test. Over the 3-year period there were no test-to-test changes in mean VO2 max performance exceeding pre-defined limits of test agreement (mean of eight measures: 61.6 ± 0.6 ml·kg-1·min-1). In contrast, VO2 at AT was significantly higher at the MID test occasion in seasons 2 (+4.8%; p = 0.04, p elite cohort between test-to-test occasions, VO2 max values did not vary significantly over the study which supports previous short-term observations suggesting a general ‘elite’ threshold of 60 ml·kg-1 min. Interestingly, AT significantly varied where VO2 max was stable and these variations also coincided with on- and off-seasons suggesting that AT is a better indication of acute training state than VO2 max. Key points Maximal aerobic power remains fairly stable across inter- and intra-season measurements. Anaerobic threshold appears more sensitive of training state confirming our earlier observations. The professional players tended to attain optimal performances at the mid-season interval over the 3 seasons, presumably prior to the development of accumulative fatigue. PMID:24150149

Seasonal variations of equatorial spread-F

Directory of Open Access Journals (Sweden)

B. V. Krishna Murthy

Full Text Available The occurrence of spread-F at Trivandrum (8.5°N, 77°E, dip 0.5°N has been investigated on a seasonal basis in sunspot maximum and minimum years in terms of the growth rate of irregularities by the generalized collisional Rayleigh-Taylor (GRT instability mechanism which includes the gravitational and cross-field instability terms. The occurrence statistics of spread-F at Trivandrum have been obtained using quarter hourly ionograms. The nocturnal variations of the growth rate of irregularities by the GRT mechanism have been estimated for different seasons in sunspot maximum and minimum years at Trivandrum using h'F values and vertical drift velocities obtained from ionograms. It is found that the seasonal variation of spread-F occurrence at Trivandrum can, in general, be accounted for on the basis of the GRT mechanism.

Seasonal variations of equatorial spread-F

Directory of Open Access Journals (Sweden)

K. S. V. Subbarao

1994-01-01

Full Text Available The occurrence of spread-F at Trivandrum (8.5°N, 77°E, dip 0.5°N has been investigated on a seasonal basis in sunspot maximum and minimum years in terms of the growth rate of irregularities by the generalized collisional Rayleigh-Taylor (GRT instability mechanism which includes the gravitational and cross-field instability terms. The occurrence statistics of spread-F at Trivandrum have been obtained using quarter hourly ionograms. The nocturnal variations of the growth rate of irregularities by the GRT mechanism have been estimated for different seasons in sunspot maximum and minimum years at Trivandrum using h'F values and vertical drift velocities obtained from ionograms. It is found that the seasonal variation of spread-F occurrence at Trivandrum can, in general, be accounted for on the basis of the GRT mechanism.

A Note on Comparing the Power of Test Statistics at Low Significance Levels.

Science.gov (United States)

Morris, Nathan; Elston, Robert

2011-01-01

It is an obvious fact that the power of a test statistic is dependent upon the significance (alpha) level at which the test is performed. It is perhaps a less obvious fact that the relative performance of two statistics in terms of power is also a function of the alpha level. Through numerous personal discussions, we have noted that even some competent statisticians have the mistaken intuition that relative power comparisons at traditional levels such as α = 0.05 will be roughly similar to relative power comparisons at very low levels, such as the level α = 5 × 10 -8 , which is commonly used in genome-wide association studies. In this brief note, we demonstrate that this notion is in fact quite wrong, especially with respect to comparing tests with differing degrees of freedom. In fact, at very low alpha levels the cost of additional degrees of freedom is often comparatively low. Thus we recommend that statisticians exercise caution when interpreting the results of power comparison studies which use alpha levels that will not be used in practice.

CHARACTERIZATION OF MARAJÓ CHEESE, CREAM TYPE, IN TWO SEASONS:PHYSICOCHEMICAL AND MICROBIOLOGICAL ASPECTS

Directory of Open Access Journals (Sweden)

Vitória Nazaré Costa Seixas

2014-04-01

Full Text Available The Marajó cheese is an artisanal product derived from buffalo milk produced in Marajó Island-PA. The objectives of this research were to characterize through physicochemical and microbiological the Marajó cheese cream type and the effect of the season. The pH, the percentage of fat in dry matter and content of sodium chloride were attributes that proximate composition showed significant difference at 5% probability by Tukey test between the two seasons. Statistical difference was not found in the percentage of titratable acidity, moisture, fat, ash, total solids extract, proteins and water activity. As for microbiological characteristics, in general, there was an improvement in the results in the dry season as to coliformes and Staphylococcus aureus. However, the result of Escherichia coli has proved to be better in the rainy season, with all samples meeting the standard of legislation. On the count of aerobic mesophilic there was no difference between the periods of the year. The pathogens Listeria monocytogenes and Salmonella sp. were not detected in the Marajó cheese, cream type, within the four seasons of the year. The variability occurred in pH, %NaCl, GES and, between seasons, demonstrates the need for greater control of production aimed at standardizing and maintaining the identity of the product. Regarding the microbiological, standards were established in accordance with the current legislation.

The Impact of a Kinesthetic Approach to Teaching Earth's Seasons

Science.gov (United States)

Slater, Stephanie; Morrow, C. A.

2010-01-01

The AAAS Benchmarks and NRC National Science Education Standards clearly prescribe that all American middle school students should understand that Earth's seasons are caused by variations in the amount of sunlight that hits Earth's surface due to tilt. An explanation for the cause of the seasons that is consistent with a scientifically accurate viewpoint would involve how the amount of sunlight reaching Earth's surface at different latitudes and is directly related to the planet's tilt. However, the most common alternative explanation given is the changing distance between the Sun and Earth. Previous research, as well as common experience, indicates that conventional instructional approaches on the concept of seasons are rarely sufficient in achieving scientifically accurate or durable conceptual change. Given the highly spatial nature of the concept, and the highly socially nature of human beings, some curriculum developers have turned to kinesthetic instructional approaches as a means to develop students' spatial reasoning and problem solving skills while confronting misconceptions and allowing students to socially construct scientifically accurate models of the seasons. We report results from a quantitative study on the impact on understanding of ninth grade students using kinesthetic approach to instruction for the traditionally challenging topic of Earth's seasons. The guiding research question was: To what extent does the kinesthetic astronomy instructional approach assist students in correcting misconceptions about the cause of the seasons? Using a single-group, multiple measures quasi-experimental study design, data was collected pre- and post-instruction using written, student-supplied-response assessments. Additionally, a third assessment was conducted 8 weeks after instruction in an attempt to measure durability. The results showed that statistically significant conceptual change occurred across three subtopics supporting seasons and were stable over 8

Seasonal temperature extremes in Potsdam

Science.gov (United States)

Kundzewicz, Zbigniew; Huang, Shaochun

2010-12-01

The awareness of global warming is well established and results from the observations made on thousands of stations. This paper complements the large-scale results by examining a long time-series of high-quality temperature data from the Secular Meteorological Station in Potsdam, where observation records over the last 117 years, i.e., from January 1893 are available. Tendencies of change in seasonal temperature-related climate extremes are demonstrated. "Cold" extremes have become less frequent and less severe than in the past, while "warm" extremes have become more frequent and more severe. Moreover, the interval of the occurrence of frost has been decreasing, while the interval of the occurrence of hot days has been increasing. However, many changes are not statistically significant, since the variability of temperature indices at the Potsdam station has been very strong.

Assessing North American multimodel ensemble (NMME) seasonal forecast skill to assist in the early warning of hydrometeorological extremes over East Africa

Science.gov (United States)

Shukla, Shraddhanand; Roberts, Jason B.; Hoell. Andrew,; Funk, Chris; Robertson, Franklin R.; Kirtmann, Benjamin

2016-01-01

The skill of North American multimodel ensemble (NMME) seasonal forecasts in East Africa (EA), which encompasses one of the most food and water insecure areas of the world, is evaluated using deterministic, categorical, and probabilistic evaluation methods. The skill is estimated for all three primary growing seasons: March–May (MAM), July–September (JAS), and October–December (OND). It is found that the precipitation forecast skill in this region is generally limited and statistically significant over only a small part of the domain. In the case of MAM (JAS) [OND] season it exceeds the skill of climatological forecasts in parts of equatorial EA (Northern Ethiopia) [equatorial EA] for up to 2 (5) [5] months lead. Temperature forecast skill is generally much higher than precipitation forecast skill (in terms of deterministic and probabilistic skill scores) and statistically significant over a majority of the region. Over the region as a whole, temperature forecasts also exhibit greater reliability than the precipitation forecasts. The NMME ensemble forecasts are found to be more skillful and reliable than the forecast from any individual model. The results also demonstrate that for some seasons (e.g. JAS), the predictability of precipitation signals varies and is higher during certain climate events (e.g. ENSO). Finally, potential room for improvement in forecast skill is identified in some models by comparing homogeneous predictability in individual NMME models with their respective forecast skill.

Associations between abnormal ultrasound color Doppler measures and tendon pain symptoms in badminton players during a season: a prospective cohort study.

Science.gov (United States)

Boesen, Anders Ploug; Boesen, Morten Ilum; Torp-Pedersen, Soren; Christensen, Robin; Boesen, Lars; Hölmich, Per; Nielsen, Michael Bachmann; Koenig, Merete Juhl; Hartkopp, Andreas; Ellegaard, Karen; Bliddal, Henning; Langberg, Henning

2012-03-01

Color Doppler ultrasound is widely used to examine intratendinous flow in individuals with overuse tendon problems, but the association between color Doppler and pain is still unclear. Intratendinous flow is present and associated with pain in badminton players, and intratendinous flow and pain increase during a badminton season. Cohort study (prognosis); Level of evidence, 2. Ninety-five semiprofessional badminton players were included in the study at a tournament at the start of the badminton season. All players were interviewed regarding pain. The anterior knee tendons and Achilles tendons were studied. Each tendon was scored using a quantitative grading system (grades 0-5) and a qualitative scoring system (color fraction) using color Doppler ultrasound. Eight months later, 86 of the players (91%) were retested by the same investigators during an equivalent badminton tournament (including 1032 tendon regions; 86 players with 4 tendons each with 3 regions), thus forming the study group. At the start of the season, 24 players (28%) experienced pain in 37 tendons (11%), and at the end of the season, 31 players (36%) experienced pain in 51 tendons (15%), which was a statistically significant increase (P = .0002). Abnormal flow was found in 230 tendon regions in 71 players (83%) at the start of the season compared with 78 tendon regions in 41 players (48%) at the follow-up. The decrease in abnormal flow was statistically significant (P < .0001). Of the 37 painful tendons at the start of the season, 25 had abnormal flow (68%). In contrast, 131 tendons (85%) with abnormal flow at the start of the season were pain free. At the end of the season, 18 of the 51 painful tendons (35%) had abnormal flow. Ninety-six of the 131 pain-free tendons (73%) with abnormal flow at the start of the season were normalized (no pain and normal flow) at the end of the season. It was not possible to verify any association between intratendinous flow and pain at the start of the season or at

ClusterSignificance: A bioconductor package facilitating statistical analysis of class cluster separations in dimensionality reduced data

DEFF Research Database (Denmark)

Serviss, Jason T.; Gådin, Jesper R.; Eriksson, Per

2017-01-01

, e.g. genes in a specific pathway, alone can separate samples into these established classes. Despite this, the evaluation of class separations is often subjective and performed via visualization. Here we present the ClusterSignificance package; a set of tools designed to assess the statistical...... significance of class separations downstream of dimensionality reduction algorithms. In addition, we demonstrate the design and utility of the ClusterSignificance package and utilize it to determine the importance of long non-coding RNA expression in the identity of multiple hematological malignancies....

Seasonal Cycle in German Daily Precipitation Extremes

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Madlen Fischer

2018-01-01

Full Text Available The seasonal cycle of extreme precipitation in Germany is investigated by fitting statistical models to monthly maxima of daily precipitation sums for 2,865 rain gauges. The basis is a non-stationary generalized extreme value (GEV distribution variation of location and scale parameters. The negative log-likelihood serves as the forecast error for a cross validation to select adequate orders of the harmonic functions for each station. For nearly all gauges considered, the seasonal model is more appropriate to estimate return levels on a monthly scale than a stationary GEV used for individual months. The 100-year return-levels show the influence of cyclones in the western, and convective events in the eastern part of Germany. In addition to resolving the seasonality, we use a simulation study to show that annual return levels can be estimated more precisely from a monthly-resolved seasonal model than from a stationary model based on annual maxima.

Statistical significance versus clinical importance: trials on exercise therapy for chronic low back pain as example.

NARCIS (Netherlands)

van Tulder, M.W.; Malmivaara, A.; Hayden, J.; Koes, B.

2007-01-01

STUDY DESIGN. Critical appraisal of the literature. OBJECIVES. The objective of this study was to assess if results of back pain trials are statistically significant and clinically important. SUMMARY OF BACKGROUND DATA. There seems to be a discrepancy between conclusions reported by authors and

Application of Seasonal Trend Loess to GPS data in Cascadia

Science.gov (United States)

Bal, A.; Bartlow, N. M.

2016-12-01

Plate Boundary Observatory GPS stations provide crucial data for the study of slow slip events and volcanic hazards in the Cascadia region. However, these GPS stations also record seasonal changes in deformation caused by hydrologic, atmospheric, and other seasonal loading. Removing these signals is necessary for accurately modeling the tectonic sources of deformation. Traditionally, seasonal trends in data been accounted for by fitting and removing sine curves from the data. However, not all seasonal trends follow a sinusoidal shape. Seasonal Trend Loess, or STL, is a filtering procedure for a decomposing a time series into trend, seasonal, and remainder components (Cleveland et. al, Journal of Official Statistics, 1990). STL has a simple design that consists of a sequence of applications of the loess smoother which allows for fast computation of large amounts of trend and seasonal smoothing. STL allows for non-sinusoidal shapes in seasonal deformation signals, and allows for evolution of seasonal signals over time. We applied Seasonal Trend Loess to GPS data from the Cascadia region. We compared our results to a traditional sine wave fit for seasonal removal at selected stations, including stations with slow slip event and volcanic signals. We hope that the STL method may be able to more accurately differentiate seasonal and tectonic deformation signals.

Seasonal climate variation and caribou availability: Modeling sequential movement using satellite-relocation data

Science.gov (United States)

Nicolson, Craig; Berman, Matthew; West, Colin Thor; Kofinas, Gary P.; Griffith, Brad; Russell, Don; Dugan, Darcy

2013-01-01

Livelihood systems that depend on mobile resources must constantly adapt to change. For people living in permanent settlements, environmental changes that affect the distribution of a migratory species may reduce the availability of a primary food source, with the potential to destabilize the regional social-ecological system. Food security for Arctic indigenous peoples harvesting barren ground caribou (Rangifer tarandus granti) depends on movement patterns of migratory herds. Quantitative assessments of physical, ecological, and social effects on caribou distribution have proven difficult because of the significant interannual variability in seasonal caribou movement patterns. We developed and evaluated a modeling approach for simulating the distribution of a migratory herd throughout its annual cycle over a multiyear period. Beginning with spatial and temporal scales developed in previous studies of the Porcupine Caribou Herd of Canada and Alaska, we used satellite collar locations to compute and analyze season-by-season probabilities of movement of animals between habitat zones under two alternative weather conditions for each season. We then built a set of transition matrices from these movement probabilities, and simulated the sequence of movements across the landscape as a Markov process driven by externally imposed seasonal weather states. Statistical tests showed that the predicted distributions of caribou were consistent with observed distributions, and significantly correlated with subsistence harvest levels for three user communities. Our approach could be applied to other caribou herds and could be adapted for simulating the distribution of other ungulates and species with similarly large interannual variability in the use of their range.

Seasonal Climate Variation and Caribou Availability: Modeling Sequential Movement Using Satellite-Relocation Data

Directory of Open Access Journals (Sweden)

Craig Nicolson

2013-06-01

Full Text Available Livelihood systems that depend on mobile resources must constantly adapt to change. For people living in permanent settlements, environmental changes that affect the distribution of a migratory species may reduce the availability of a primary food source, with the potential to destabilize the regional social-ecological system. Food security for Arctic indigenous peoples harvesting barren ground caribou (Rangifer tarandus granti depends on movement patterns of migratory herds. Quantitative assessments of physical, ecological, and social effects on caribou distribution have proven difficult because of the significant interannual variability in seasonal caribou movement patterns. We developed and evaluated a modeling approach for simulating the distribution of a migratory herd throughout its annual cycle over a multiyear period. Beginning with spatial and temporal scales developed in previous studies of the Porcupine Caribou Herd of Canada and Alaska, we used satellite collar locations to compute and analyze season-by-season probabilities of movement of animals between habitat zones under two alternative weather conditions for each season. We then built a set of transition matrices from these movement probabilities, and simulated the sequence of movements across the landscape as a Markov process driven by externally imposed seasonal weather states. Statistical tests showed that the predicted distributions of caribou were consistent with observed distributions, and significantly correlated with subsistence harvest levels for three user communities. Our approach could be applied to other caribou herds and could be adapted for simulating the distribution of other ungulates and species with similarly large interannual variability in the use of their range.

Technical Efficiency of Wet Season Melon Farming

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Ananti Yekti

2017-03-01

Full Text Available Melon is one of high-value horticulture commodity which is cultivated widely in Kulon Progo regency. The nature of agricultural products is heavily dependent on the season, so it causes the prices of agricultural products always fluctuated every time. In wet season the price of agricultural products tends to be more expensive. Melon cultivation in wet season provide an opportunity to earn higher profits than in the dry season. The price of agricultural products tends to be more expensive in wet season, thus melon cultivation in wet season prospectively generate high profits. In order to achieve high profitability, melon farming has to be done efficiently. Objective of this study was to 1 determined the factors that influence melon production in wet season 2 measured technical efficiency of melon farming and 3 identified the factors that influanced technical efficiency. Data collected during April – June 2014. Location determined by multistage cluster sampling. 45 samples of farmers who cultivated melon during wet season obtained based on quota sampling technique. Technical efficiency was measured using Cobb-Douglas Stochastic Frontier. The result reveals that 1 land use, quantity of seed, K fertilizer contributed significantly increasing melon production, while N fertilizer decreased melon production significantly 2 technical efficiency indeces ranged from 0.40 to 0.99, with a mean of  0.77; 3 farmer’s experience gave significant influence to technical efficiency of melon farming in wet season.

Seasonal Adjustment with the R Packages x12 and x12GUI

OpenAIRE

Kowarik, Alexander; Meraner, Angelika; Templ, Matthias; Schopfhauser, Daniel

2014-01-01

The X-12-ARIMA seasonal adjustment program of the US Census Bureau extracts the different components (mainly: seasonal component, trend component, outlier component and irregular component) of a monthly or quarterly time series. It is the state-of-the- art technology for seasonal adjustment used in many statistical offices. It is possible to include a moving holiday effect, a trading day effect and user-defined regressors, and additionally incorporates automatic outlier detection. The procedu...

The effect of seasonality on burn incidence, severity and outcome in Central Malawi.

Science.gov (United States)

Tyson, Anna F; Gallaher, Jared; Mjuweni, Stephen; Cairns, Bruce A; Charles, Anthony G

2017-08-01

In much of the world, burns are more common in cold months. However, few studies have described the seasonality of burns in sub-Saharan Africa. This study examines the effect of seasonality on the incidence and outcome of burns in central Malawi. A retrospective analysis was performed at Kamuzu Central Hospital and included all patients admitted from May 2011 to August 2014. Demographic data, burn mechanism, total body surface area (%TBSA), and mortality were analyzed. Seasons were categorized as Rainy (December-February), Lush (March-May), Cold (June-August) and Hot (September-November). A negative binomial regression was used to assess the effect of seasonality on burn incidence. This was performed using both the raw and deseasonalized data in order to evaluate for trends not attributable to random fluctuation. A total of 905 patients were included. Flame (38%) and Scald (59%) burns were the most common mechanism. More burns occurred during the cold season (41% vs 19-20% in the other seasons). Overall mortality was 19%. Only the cold season had a statistically significant increase in burn . The incidence rate ratios (IRR) for the hot, lush, and cold seasons were 0.94 (CI 0.6-1.32), 1.02 (CI 0.72-1.45) and 1.6 (CI 1.17-2.19), respectively, when compared to the rainy season. Burn severity and mortality did not differ between seasons. The results of this study demonstrate the year-round phenomenon of burns treated at our institution, and highlights the slight predominance of burns during the cold season. These data can be used to guide prevention strategies, with special attention to the implications of the increased burn incidence during the cold season. Though burn severity and mortality remain relatively unchanged between seasons, recognizing the seasonal variability in incidence of burns is critical for resource allocation in this low-income setting. Copyright © 2017 Elsevier Ltd and ISBI. All rights reserved.

Seasonal variability of thermophilic Campylobacter spp. in raw milk sold by automatic vending machines in Lombardy Region

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Barbara Bertasi

2016-06-01

Full Text Available In temperate climates, a seasonal trend was observed in the incidence of human campylobacteriosis cases, with peaks reported in spring and autumn in some countries, or in summer in others; a similar trend was observed in Campylobacter spp. dairy cattle faecal shedding, suggesting that cattle may play a role in the seasonal peak of human infection. The objectives of this study were to assess if a seasonal trend in thermophilic Campylobacter spp. contamination of raw milk exists and to evaluate a possible relation between this and the increase of human campylobacteriosis incidence in summer months. The results showed a mean prevalence of 1.6% of milk samples positive for thermophilic Campylobacter spp. with a wide range (0.0-3.1% in different months during the three years considered. The statistical analysis showed a significant difference (PCampylobacter spp. between warmer and cooler months (2.3 vs 0.6%. The evidence of a seasonal trend in thermophilic Campylobacter spp. contamination of raw milk sold for direct consumption, with an increase of the prevalence in warmer months, may represent one of the possible links between seasonal trend in cattle faecal shedding and seasonal trend in human campylobacteriosis.

Theory of planned behaviour variables and objective walking behaviour do not show seasonal variation in a randomised controlled trial.

Science.gov (United States)

Williams, Stefanie L; French, David P

2014-02-05

Longitudinal studies have shown that objectively measured walking behaviour is subject to seasonal variation, with people walking more in summer compared to winter. Seasonality therefore may have the potential to bias the results of randomised controlled trials if there are not adequate statistical or design controls. Despite this there are no studies that assess the impact of seasonality on walking behaviour in a randomised controlled trial, to quantify the extent of such bias. Further there have been no studies assessing how season impacts on the psychological predictors of walking behaviour to date. The aim of the present study was to assess seasonal differences in a) objective walking behaviour and b) Theory of Planned Behaviour (TPB) variables during a randomised controlled trial of an intervention to promote walking. 315 patients were recruited to a two-arm cluster randomised controlled trial of an intervention to promote walking in primary care. A series of repeated measures ANCOVAs were conducted to examine the effect of season on pedometer measures of walking behaviour and TPB measures, assessed immediately post-intervention and six months later. Hierarchical regression analyses were conducted to assess whether season moderated the prediction of intention and behaviour by TPB measures. There were no significant differences in time spent walking in spring/summer compared to autumn/winter. There was no significant seasonal variation in most TPB variables, although the belief that there will be good weather was significantly higher in spring/summer (F = 19.46, p behaviour, or moderate the effects of TPB variables on intention or behaviour. Seasonality does not influence objectively measured walking behaviour or psychological variables during a randomised controlled trial. Consequently physical activity behaviour outcomes in trials will not be biased by the season in which they are measured. Previous studies may have overestimated the extent of

Spartial and seasonal variations in concentrations of polycyclic aromatic hydrocarbons in water and sediment of Kisumu City bay of Winam Gulf, Lake Victoria-Kenya.

Science.gov (United States)

Kwach, Bowa O; Lalah, Joseph O; Shem, Wandiga O

2009-11-01

Seasonal and offshore concentration variations for selected sixteen priority pollutant polycyclic aromatic hydrocarbons (PAHs) in surface sediments and water of Car Wash and Kisat areas of Winam Gulf, Lake Victoria, have been investigated. PAHs concentrations in sediments and water range from 0.4 to 31.95 microg/g dry weight and 3.32 to 55.8 microg/L, respectively. Statistical analysis of the PAHs concentrations showed that the most contaminated samples are found during rainy season (April, 2006), 5 m offshore for sediments and 10 m offshore for water. Dry season (October, 2005) generally recorded lower concentrations. The variations showed significant difference (p < or = 0.05) with season and distance of sampling from the shore.

Modeling and Statistical Analysis of the Spatio-Temporal Patterns of Seasonal Influenza in Israel

Science.gov (United States)

Katriel, Guy; Yaari, Rami; Roll, Uri; Stone, Lewi

2012-01-01

Background Seasonal influenza outbreaks are a serious burden for public health worldwide and cause morbidity to millions of people each year. In the temperate zone influenza is predominantly seasonal, with epidemics occurring every winter, but the severity of the outbreaks vary substantially between years. In this study we used a highly detailed database, which gave us both temporal and spatial information of influenza dynamics in Israel in the years 1998–2009. We use a discrete-time stochastic epidemic SIR model to find estimates and credible confidence intervals of key epidemiological parameters. Findings Despite the biological complexity of the disease we found that a simple SIR-type model can be fitted successfully to the seasonal influenza data. This was true at both the national levels and at the scale of single cities.The effective reproductive number Re varies between the different years both nationally and among Israeli cities. However, we did not find differences in Re between different Israeli cities within a year. R e was positively correlated to the strength of the spatial synchronization in Israel. For those years in which the disease was more “infectious”, then outbreaks in different cities tended to occur with smaller time lags. Our spatial analysis demonstrates that both the timing and the strength of the outbreak within a year are highly synchronized between the Israeli cities. We extend the spatial analysis to demonstrate the existence of high synchrony between Israeli and French influenza outbreaks. Conclusions The data analysis combined with mathematical modeling provided a better understanding of the spatio-temporal and synchronization dynamics of influenza in Israel and between Israel and France. Altogether, we show that despite major differences in demography and weather conditions intra-annual influenza epidemics are tightly synchronized in both their timing and magnitude, while they may vary greatly between years. The predominance of

Canary tomato export prices: comparison and relationships between daily seasonal patterns

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G. Martin-Rodriguez

2013-10-01

Full Text Available Statistical procedures are proposed to describe, compare and forecast the behaviour of seasonal variations in two daily price series of Canary tomato exported to German and British markets, respectively, over the last decade. These seasonal patterns are pseudo-periodic as the length of the seasonal period changes frequently in dependence of market conditions. Seasonal effect at a day in the harvesting period is defined as a spline function of the proportion of the length of such a period elapsed up to such a day. Then, seasonal patterns for the two series are compared in terms of the area between the corresponding spline functions. The ability of these models to capture the dynamic process of change in the seasonal pattern is useful to forecasting purpose. Furthermore, an analytical tool is also proposed to obtain forecasts of the seasonal pattern in one of these two series from the forecasts of the seasonal pattern in the other one. These procedures are useful for farmers in developing strategies related to the seasonal distribution of tomato production exported to each market.

Indirectional statistics and the significance of an asymmetry discovered by Birch

International Nuclear Information System (INIS)

Kendall, D.G.; Young, G.A.

1984-01-01

Birch (1982, Nature, 298, 451) reported an apparent 'statistical asymmetry of the Universe'. The authors here develop 'indirectional analysis' as a technique for investigating statistical effects of this kind and conclude that the reported effect (whatever may be its origin) is strongly supported by the observations. The estimated pole of the asymmetry is at RA 13h 30m, Dec. -37deg. The angular error in its estimation is unlikely to exceed 20-30deg. (author)

Global Analysis of Empirical Relationships Between Annual Climate and Seasonality of NDVI

Science.gov (United States)

Potter, C. S.

1997-01-01

This study describes the use of satellite data to calibrate a new climate-vegetation greenness function for global change studies. We examined statistical relationships between annual climate indexes (temperature, precipitation, and surface radiation) and seasonal attributes of the AVHRR Normalized Difference Vegetation Index (NDVI) time series for the mid-1980s in order to refine our empirical understanding of intraannual patterns and global abiotic controls on natural vegetation dynamics. Multiple linear regression results using global l(sup o) gridded data sets suggest that three climate indexes: growing degree days, annual precipitation total, and an annual moisture index together can account to 70-80 percent of the variation in the NDVI seasonal extremes (maximum and minimum values) for the calibration year 1984. Inclusion of the same climate index values from the previous year explained no significant additional portion of the global scale variation in NDVI seasonal extremes. The monthly timing of NDVI extremes was closely associated with seasonal patterns in maximum and minimum temperature and rainfall, with lag times of 1 to 2 months. We separated well-drained areas from l(sup o) grid cells mapped as greater than 25 percent inundated coverage for estimation of both the magnitude and timing of seasonal NDVI maximum values. Predicted monthly NDVI, derived from our climate-based regression equations and Fourier smoothing algorithms, shows good agreement with observed NDVI at a series of ecosystem test locations from around the globe. Regions in which NDVI seasonal extremes were not accurately predicted are mainly high latitude ecosystems and other remote locations where climate station data are sparse.

The concentrations of ambient Burkholderia pseudomallei during typhoon season in endemic area of melioidosis in Taiwan.

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Ya-Lei Chen

Full Text Available BACKGROUND: Melioidosis is a severe bacterial infection caused by Burkholderia pseudomallei with a high case-fatality rate. Epidemiological and animal studies show the possibility of inhalation transmission. However, no B. pseudomallei concentrations in ambient air have been researched. Here, we developed a method to quantify ambient B. pseudomallei and then measured concentrations of ambient B. pseudomallei during the typhoon season and the non-typhoon season to determine the factors influencing ambient B. pseudomallei levels. METHODS: We quantified ambient B. pseudomallei by using a filter/real-time qPCR method in the Zoynan Region in Kaohsiung, southern Taiwan. Twenty-four hour samples were collected at a sampling rate of 20 L/min every day from June 11 to December 21, 2012 including during the typhoon season (June to September and reference season (October to December. RESULTS: We successfully developed a filtration/real-time qPCR method to quantify ambient B. pseudomallei. To our knowledge, this is the first report describing concentrations of ambient B. pseudomallei. Ambient B. pseudomallei were only detected during the typhoon season when compared to the reference season. For the typhoons affecting the Zoynan Region, the positive rates of ambient B. pseudomallei were very high at 80% to 100%. During June to December, rainfall was positively correlated with ambient B. pseudomallei with a statistical significance. Sediment at a nearby pond significantly influenced the concentration of ambient B. pseudomallei. During the typhoon month, the typhoon was positively correlated with ambient B. pseudomallei whereas wind speed was reversely correlated with ambient B. pseudomallei. CONCLUSIONS: Our data suggest the possibility of transmission of B. pseudomallei via inhalation during the typhoon season.

The concentrations of ambient Burkholderia pseudomallei during typhoon season in endemic area of melioidosis in Taiwan.

Science.gov (United States)

Chen, Ya-Lei; Yen, Yu-Chuan; Yang, Chun-Yuh; Lee, Min Sheng; Ho, Chi-Kung; Mena, Kristina D; Wang, Peng-Yau; Chen, Pei-Shih

2014-01-01

Melioidosis is a severe bacterial infection caused by Burkholderia pseudomallei with a high case-fatality rate. Epidemiological and animal studies show the possibility of inhalation transmission. However, no B. pseudomallei concentrations in ambient air have been researched. Here, we developed a method to quantify ambient B. pseudomallei and then measured concentrations of ambient B. pseudomallei during the typhoon season and the non-typhoon season to determine the factors influencing ambient B. pseudomallei levels. We quantified ambient B. pseudomallei by using a filter/real-time qPCR method in the Zoynan Region in Kaohsiung, southern Taiwan. Twenty-four hour samples were collected at a sampling rate of 20 L/min every day from June 11 to December 21, 2012 including during the typhoon season (June to September) and reference season (October to December). We successfully developed a filtration/real-time qPCR method to quantify ambient B. pseudomallei. To our knowledge, this is the first report describing concentrations of ambient B. pseudomallei. Ambient B. pseudomallei were only detected during the typhoon season when compared to the reference season. For the typhoons affecting the Zoynan Region, the positive rates of ambient B. pseudomallei were very high at 80% to 100%. During June to December, rainfall was positively correlated with ambient B. pseudomallei with a statistical significance. Sediment at a nearby pond significantly influenced the concentration of ambient B. pseudomallei. During the typhoon month, the typhoon was positively correlated with ambient B. pseudomallei whereas wind speed was reversely correlated with ambient B. pseudomallei. Our data suggest the possibility of transmission of B. pseudomallei via inhalation during the typhoon season.

Characterization of water quality and suspended sediment during cold-season flows, warm-season flows, and stormflows in the Fountain and Monument Creek watersheds, Colorado, 2007–2015

Science.gov (United States)

Miller, Lisa D.; Stogner, Sr., Robert W.

2017-09-01

-quality standard for total arsenic of 50 micrograms per liter. All concentrations of dissolved copper, selenium, and zinc measured in samples were below the water-quality standard.Concentrations of dissolved nitrate plus nitrite generally increased from upstream to downstream during all flow periods. The largest downstream increase in dissolved nitrate plus nitrite concentration was measured between sites 07103970 and 07104905 on Monument Creek. All but one tributary that drain into Monument Creek between the two sites had higher median nitrate plus nitrite concentrations than the nearest upstream site on Monument Creek, site 07103970 (MoCr_Woodmen). Increases in the concentration of dissolved nitrate plus nitrite were also evident below wastewater treatment plants located on Fountain Creek.Most stormflow concentrations of dissolved trace elements were smaller than concentrations from cold-season flow or warm-season samples. However, median concentrations of total arsenic, lead, manganese, nickel, and zinc generally were much larger during periods of stormflow than during cold-season flow or warm-season fl. Median concentrations of total arsenic, total copper, total lead, dissolved and total manganese, total nickel, dissolved and total selenium, and dissolved and total zinc concentrations increased from 1.5 to 28.5 times from site 07103700 (FoCr_Manitou) to 07103707 (FoCr_8th) during cold-season and warm-season flows, indicating a large source of trace elements between these two sites. Both of these sites are located on Fountain Creek, upstream from the confluence with Monument Creek.Median suspended-sediment concentrations and median suspended-sediment loads increased in the downstream direction during all streamflow regimes between Monument Creek sites 07103970 (MoCr_Woodmen) and 07104905 (MoCr_Bijou); however, statistically significant increase (p-value less than 0.05) were only present during warm-season flow and stormflow. Significant increases in median suspended sediment

Seasonal variation in plasma lipids and lipases in young healthy humans.

Science.gov (United States)

Cambras, Trinitat; Baena-Fustegueras, Juan A; Pardina, Eva; Ricart-Jané, David; Rossell, Joana; Díez-Noguera, Antoni; Peinado-Onsurbe, Julia

2017-01-01

Although intermediate metabolism is known to follow circadian rhythms, little information is available on the variation in lipase activities (lipoprotein and hepatic lipase, LPL and HL, respectively) and lipids throughout the year. In a cross-sectional study, we collected and analysed blood from 245 healthy students (110 men and 135 women) between 18 and 25 years old from the University of Barcelona throughout the annual campaign (March, May, October and December) of the blood bank. All subjects gave their written informed consent to participate. All blood samples were taken after breakfast at 8:00 and 11:00 am. Plasma glucose, total plasma protein, triacylglycerides (TAG), free fatty acids (FFA), free cholesterol and esterified cholesterol (FC and TC, respectively), cholesterol in low-density lipoproteins (cLDL), cholesterol in high-density lipoproteins (cHDL), phospholipids (PL) and lipase activities (LPL and HL) were determined. Cosinor analysis was used to evaluate the presence (significance of fit cosine curve to data and variance explained by rhythm) and characteristics of possible 12-month rhythms (acrophase, MESOR and amplitude). Statistically significant seasonal rhythms were detected for all the variables studied except proteins, with most of them peaking in the winter season. The lowest value for cLDL and the HL occurs in summer, while for cHDL and the LPL it is in winter. These findings demonstrate for the first time that in physiological conditions, plasma LPL and HL activities and lipids follow seasonal rhythms. The metabolic significance of this pattern is discussed.

Seasonality of runoff and precipitation regimes along transects in Peru and Austria

OpenAIRE

Gaudry Maria M. Cárdenas; Gutknecht Dieter; Parajka Juraj; Perdigão Rui A.P.; Blöschl Günter

2017-01-01

The aim of this study is to understand the seasonalities of runoff and precipitation and their controls along two transects in Peru and one transect in Austria. The analysis is based on daily precipitation data at 111 and 61 stations in Peru and Austria, respectively, and daily discharge data at 51 and 110 stations. The maximum Pardé coefficient is used to quantify the strength of the seasonalities of monthly precipitation and runoff. Circular statistics are used to quantify the seasonalities...

World offshore energy loss statistics

International Nuclear Information System (INIS)

Kaiser, Mark J.

2007-01-01

Offshore operations present a unique set of environmental conditions and adverse exposure not observed in a land environment taking place in a confined space in a hostile environment under the constant danger of catastrophe and loss. It is possible to engineer some risks to a very low threshold of probability, but losses and unforeseen events can never be entirely eliminated because of cost considerations, the human factor, and environmental uncertainty. Risk events occur infrequently but have the potential of generating large losses, as evident by the 2005 hurricane season in the Gulf of Mexico, which was the most destructive and costliest natural disaster in the history of offshore production. The purpose of this paper is to provide a statistical assessment of energy losses in offshore basins using the Willis Energy Loss database. A description of the loss categories and causes of property damage are provided, followed by a statistical assessment of damage and loss broken out by region, cause, and loss category for the time horizon 1970-2004. The impact of the 2004-2005 hurricane season in the Gulf of Mexico is summarized

Statistical analyses to support guidelines for marine avian sampling. Final report

Science.gov (United States)

Kinlan, Brian P.; Zipkin, Elise; O'Connell, Allan F.; Caldow, Chris

2012-01-01

distribution to describe counts of a given species in a particular region and season. 4. Using a large database of historical at-sea seabird survey data, we applied this technique to identify appropriate statistical distributions for modeling a variety of species, allowing the distribution to vary by season. For each species and season, we used the selected distribution to calculate and map retrospective statistical power to detect hotspots and coldspots, and map pvalues from Monte Carlo significance tests of hotspots and coldspots, in discrete lease blocks designated by the U.S. Department of Interior, Bureau of Ocean Energy Management (BOEM). 5. Because our definition of hotspots and coldspots does not explicitly include variability over time, we examine the relationship between the temporal scale of sampling and the proportion of variance captured in time series of key environmental correlates of marine bird abundance, as well as available marine bird abundance time series, and use these analyses to develop recommendations for the temporal distribution of sampling to adequately represent both shortterm and long-term variability. We conclude by presenting a schematic “decision tree” showing how this power analysis approach would fit in a general framework for avian survey design, and discuss implications of model assumptions and results. We discuss avenues for future development of this work, and recommendations for practical implementation in the context of siting and wildlife assessment for offshore renewable energy development projects.

Seasonal Differences in Determinants of Time Location Patterns in an Urban Population: A Large Population-Based Study in Korea.

Science.gov (United States)

Lee, Sewon; Lee, Kiyoung

2017-06-22

Time location patterns are a significant factor for exposure assessment models of air pollutants. Factors associated with time location patterns in urban populations are typically due to high air pollution levels in urban areas. The objective of this study was to determine the seasonal differences in time location patterns in two urban cities. A Time Use Survey of Korean Statistics (KOSTAT) was conducted in the summer, fall, and winter of 2014. Time location data from Seoul and Busan were collected, together with demographic information obtained by diaries and questionnaires. Determinants of the time spent at each location were analyzed by multiple linear regression and the stepwise method. Seoul and Busan participants had similar time location profiles over the three seasons. The time spent at own home, other locations, workplace/school and during walk were similar over the three seasons in both the Seoul and Busan participants. The most significant time location pattern factors were employment status, age, gender, monthly income, and spouse. Season affected the time spent at the workplace/school and other locations in the Seoul participants, but not in the Busan participants. The seasons affected each time location pattern of the urban population slightly differently, but overall there were few differences.

Seasonal Differences in Determinants of Time Location Patterns in an Urban Population: A Large Population-Based Study in Korea

Directory of Open Access Journals (Sweden)

Sewon Lee

2017-06-01

Full Text Available Time location patterns are a significant factor for exposure assessment models of air pollutants. Factors associated with time location patterns in urban populations are typically due to high air pollution levels in urban areas. The objective of this study was to determine the seasonal differences in time location patterns in two urban cities. A Time Use Survey of Korean Statistics (KOSTAT was conducted in the summer, fall, and winter of 2014. Time location data from Seoul and Busan were collected, together with demographic information obtained by diaries and questionnaires. Determinants of the time spent at each location were analyzed by multiple linear regression and the stepwise method. Seoul and Busan participants had similar time location profiles over the three seasons. The time spent at own home, other locations, workplace/school and during walk were similar over the three seasons in both the Seoul and Busan participants. The most significant time location pattern factors were employment status, age, gender, monthly income, and spouse. Season affected the time spent at the workplace/school and other locations in the Seoul participants, but not in the Busan participants. The seasons affected each time location pattern of the urban population slightly differently, but overall there were few differences.

Seasonal Variation of Total Mercury Burden in the American Alligator (Alligator Mississippiensis) at Merritt Island National Wildlife Refuge (MINWR), Florida

Science.gov (United States)

Nilsen, Frances M.; Dorsey, Jonathan E.; Long, Stephen E.; Schock, Tracey B.; Bowden, John A.; Lowers, Russell H.; Guillette, Louis J., Jr.

2016-01-01

Seasonal variation of mercury (Hg) is not well studied in free-ranging wildlife. Atmospheric deposition patterns of Hg have been studied in detail and have been modeled for both global and specific locations with great accuracy and correlates to environment impact. However, monitoring these trends in wildlife is complicated due to local environmental parameters (e.g., rainfall, humidity, pH, bacterial composition) that can affect the transformation of atmospheric Hg to the biologically available forms. Here, we utilized an abundant and healthy population of American alligators (Alligator mississippiensis) at Merritt Island National Wildlife Refuge (MINWR), FL, and assessed Hg burden in whole blood samples over a span of 7 years (2007 2014; n 174) in an effort to assess seasonal variation of total [Hg]. While the majority of this population is assumed healthy, 18 individuals with low body mass indices (BMI, defined in this study) were captured throughout the 7 year sampling period. These individual alligators exhibited [Hg] that were not consistent with the observed overall seasonal [Hg] variation, and were statistically different from the healthy population of alligators. The alligators with low BMI had elevated concentrations of Hg compared to their age/sex/season matched counterparts with normal BMI. Statistically significant differences were found between the winter and spring seasons for animals with normal BMI. The data in this report supports the conclusion that organismal total [Hg] do fluctuate directly with seasonal deposition rates as well as other seasonal environmental parameters, such as average rainfall and prevailing wind direction. This study highlights the unique environment of MINWR to permit annual assessment of apex predators, such as the American alligator, to determine detailed environmental impact of contaminants of concern.

Little evidence of seasonal variation of natural infection by Leishmania infantum in dogs in Spain.

Science.gov (United States)

Fernández-Bellon, H; Solano-Gallego, L; Rodríguez-Cortés, A; Ferrer, L; Gallego, M; Alberola, J; Ramis, A

2008-08-01

Leishmania infantum, the etiological agent of canine leishmaniosis in the Mediterranean region, is vectored by Phlebotomus spp sandflies, which are active during the warmer months of the year. In order to determine whether seasonality in transmission induces seasonal changes in the prevalence of infection by L. infantum and of parasite-specific immune response, two groups of dogs, one in February (n=37) and another in October (n=42), were studied. Clinical signs compatible with leishmaniosis, as well as presence of microscopic skin lesions in the muzzle were recorded for all dogs. Assays were also performed for detection of L. infantum parasites in muzzle skin samples (PCR, immunohistochemistry and culture), specific serum antibodies (ELISA), and specific lymphocyte proliferation and interferon-gamma production. Although prevalence of non-specific clinical signs increased significantly after the sandfly season, this was not the case for Leishmania-specific markers: positivity by PCR (24% vs. 21%) or immunohistochemistry (3% vs. 2%) of muzzle skin samples, as well as lymphocyte proliferation (59% vs. 50%) or interferon-gamma production (21% vs. 27%) were similar in February and in October. Only prevalence of positive specific antibody titers increased noticeably in October (8% vs. 20%), although this was not statistically significant. Overall, the sandfly season did not have a marked impact on the prevalence L. infantum infection or parasite-specific immune responses analyzed in this study.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry.

Science.gov (United States)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y; Drake, Steven K; Gucek, Marjan; Sacks, David B; Yu, Yi-Kuo

2018-06-05

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html . Graphical Abstract ᅟ.

An integrated, probabilistic model for improved seasonal forecasting of agricultural crop yield under environmental uncertainty

Directory of Open Access Journals (Sweden)

Nathaniel K. Newlands

2014-06-01

Full Text Available We present a novel forecasting method for generating agricultural crop yield forecasts at the seasonal and regional-scale, integrating agroclimate variables and remotely-sensed indices. The method devises a multivariate statistical model to compute bias and uncertainty in forecasted yield at the Census of Agricultural Region (CAR scale across the Canadian Prairies. The method uses robust variable-selection to select the best predictors within spatial subregions. Markov-Chain Monte Carlo (MCMC simulation and random forest-tree machine learning techniques are then integrated to generate sequential forecasts through the growing season. Cross-validation of the model was performed by hindcasting/backcasting it and comparing its forecasts against available historical data (1987-2011 for spring wheat (Triticum aestivum L.. The model was also validated for the 2012 growing season by comparing its forecast skill at the CAR, provincial and Canadian Prairie region scales against available statistical survey data. Mean percent departures between wheat yield forecasted were under-estimated by 1-4 % in mid-season and over-estimated by 1 % at the end of the growing season. This integrated methodology offers a consistent, generalizable approach for sequentially forecasting crop yield at the regional-scale. It provides a statistically robust, yet flexible way to concurrently adjust to data-rich and data-sparse situations, adaptively select different predictors of yield to changing levels of environmental uncertainty, and to update forecasts sequentially so as to incorporate new data as it becomes available. This integrated method also provides additional statistical support for assessing the accuracy and reliability of model-based crop yield forecasts in time and space.

[Influence of gender, age and season on thyroid hormone reference interval].

Science.gov (United States)

Qiu, L; Wang, D C; Xu, T; Cheng, X Q; Sun, Q; Hu, Y Y; Liu, H C; Lu, S Y; Yang, G H; Wang, Z J

2018-05-29

Objective: Using clinical "big data" , to investigate the factors that affect the levels of thyroid hormones, and to explore the partitioning criteria for reference intervals (RI) of these hormones. Methods: An observation study was conducted. Information of 107 107 individuals undergoing routine physical examination in Peking Union Medical College Hospital from September 1(st,) 2013 to August 31(st,) 2016 was collected, thyroid hormone of these subjects were detected. To explore the test results distribution and differences of TSH, FT4 and FT3 by gender and age; according to the seasonal division standard of China Meteorological Administration, the study period was divided into four seasons, and the seasonal fluctuation on TSH was analyzed.To define the appropriate partition by gender, age and season according to significant difference analysis. Results: In male and female, the distributions of TSH were 1.779(0.578-4.758), 2.023(0.420-5.343)mU/L, respectively, and the level of TSH in female was higher than in male ( Z =-37.600, P groups by 65 years old and female were divided by 50 years old, respectively, and the distributions of TSH in male and female of older group were 1.818(0.528-5.240), 2.111(0.348-5.735)mU/L, in younger group were 1.778(0.582-4.696), 1.991(0.427-5.316)mU/L. The level of TSH in older group was significantly higher than in younger group ( Z =-2.269, -10.400, all P group was much wider than in younger. The distribution of whole in spring, summer and autumn was 1.869( 0.510-5.042)mU/L, in winter was 1.978(0.527-5.250) mU/L, and the difference between them had statistical significance ( Z =-15.000, P age significantly affect the serum levels of TSH, FT4, and FT3, the distribution of TSH in female and elder group are wider than in male, and that of FT4, FT3 are lower.Seasons significantly affect the serum TSH level, the peak value is observed in winter. There are obviously differences between "rough" RIs and manufacture recommended RIs. Each

Impact of Soil Moisture Initialization on Seasonal Weather Prediction

Science.gov (United States)

Koster, Randal D.; Suarez, Max J.; Houser, Paul (Technical Monitor)

2002-01-01

The potential role of soil moisture initialization in seasonal forecasting is illustrated through ensembles of simulations with the NASA Seasonal-to-Interannual Prediction Project (NSIPP) model. For each boreal summer during 1997-2001, we generated two 16-member ensembles of 3-month simulations. The first, "AMIP-style" ensemble establishes the degree to which a perfect prediction of SSTs would contribute to the seasonal prediction of precipitation and temperature over continents. The second ensemble is identical to the first, except that the land surface is also initialized with "realistic" soil moisture contents through the continuous prior application (within GCM simulations leading up to the start of the forecast period) of a daily observational precipitation data set and the associated avoidance of model drift through the scaling of all surface prognostic variables. A comparison of the two ensembles shows that soil moisture initialization has a statistically significant impact on summertime precipitation and temperature over only a handful of continental regions. These regions agree, to first order, with regions that satisfy three conditions: (1) a tendency toward large initial soil moisture anomalies, (2) a strong sensitivity of evaporation to soil moisture, and (3) a strong sensitivity of precipitation to evaporation. The degree to which the initialization improves forecasts relative to observations is mixed, reflecting a critical need for the continued development of model parameterizations and data analysis strategies.

Season-independent cognitive deficits in seasonal affective disorder and their relation to depressive symptoms

DEFF Research Database (Denmark)

Hjordt, Liv Vadskjær; Stenbæk, Dea Siggaard; Ozenne, Brice

2017-01-01

Modalities Test (SDMT) and the Simple Reaction Time (SRT) twice; in summer and in winter. Compared to controls, SAD individuals showed significant season-independent impairments in tasks measuring working memory (LNS), cognitive processing speed (SDMT) and motor speed (SRT). In SAD individuals, cognitive...... processing speed was significantly negatively associated with the seasonal change in SAD depressive symptoms. We present novel evidence that in SAD individuals, working memory, cognitive processing- and motor speed is not only impaired in the winter but also in the summer. This suggests that certain...

Seasonal variation in Internet searches for vitamin D.

Science.gov (United States)

Moon, Rebecca J; Curtis, Elizabeth M; Davies, Justin H; Cooper, Cyrus; Harvey, Nicholas C

2017-12-01

Internet search rates for "vitamin D" were explored using Google Trends. Search rates increased from 2004 until 2010 and thereafter displayed a seasonal pattern peaking in late winter. This knowledge could help guide the timing of public health interventions aimed at managing vitamin D deficiency. The Internet is an important source of health information. Analysis of Internet search activity rates can provide information on disease epidemiology, health related behaviors and public interest. We explored Internet search rates for vitamin D to determine whether this reflects the increasing scientific interest in this topic. Google Trends is a publically available tool that provides data on Internet searches using Google. Search activity for the term "vitamin D" from 1st January 2004 until 31st October 2016 was obtained. Comparison was made to other bone and nutrition related terms. Worldwide, searches for "vitamin D" increased from 2004 until 2010 and thereafter a statistically significant (p Internet search activity, did increase from 2004 to 2010, likely reflecting the growing scientific interest, but now displays a seasonal pattern with peak interest during late winter. This information could be used to guide public health approaches to managing vitamin D deficiency.

Seasonal Changes in Central England Temperatures

DEFF Research Database (Denmark)

Proietti, Tommaso; Hillebrand, Eric

The aim of this paper is to assess how climate change is reflected in the variation of the seasonal patterns of the monthly Central England Temperature time series between 1772 and 2013. In particular, we model changes in the amplitude and phase of the seasonal cycle. Starting from the seminal work...... by Thomson (“The Seasons, Global Temperature and Precession”, Science, 7 April 1995, vol 268, p. 59–68), a number of studies have documented a shift in the phase of the annual cycle implying an earlier onset of the spring season at various European locations. A significant reduction in the amplitude...... and stochastic trends, as well as seasonally varying autocorrelation and residual variances. The model can be summarized as containing a permanent and a transitory component, where global warming is captured in the permanent component, on which the seasons load differentially. The phase of the seasonal cycle...

Influenza Seasonal Summary, 2014-2015 Season

Science.gov (United States)

2015-08-14

Influenza Seasonal Summarv 2014-2015 Season EpiData Center Department Communicable Disease Division NMCPHC-EDC-TR-394-2015 REPORT DOCUMENTATION... Influenza Seasonal Summary, 2014-2015 Season Sb. GRANT NUMBER $c. PROGRAM ELEMENT NUMBER 6. AUTHORjS) Sd. PROJECT NUMBER Ashleigh K McCabe, Kristen R...SUPPLEMENTARY NOTES 1<l. ABSTRACT This report summartzes influenza activity among Department of Navy (DON) and Depar1ment of Defense (DOD

Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data.

Science.gov (United States)

Kim, Sung-Min; Choi, Yosoon

2017-06-18

To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z -score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF) analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES) data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z -scores: high content with a high z -score (HH), high content with a low z -score (HL), low content with a high z -score (LH), and low content with a low z -score (LL). The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1-4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required.

Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data

Directory of Open Access Journals (Sweden)

Sung-Min Kim

2017-06-01

Full Text Available To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z-score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z-scores: high content with a high z-score (HH, high content with a low z-score (HL, low content with a high z-score (LH, and low content with a low z-score (LL. The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1–4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required.

Statistical Methods for Stochastic Differential Equations

CERN Document Server

Kessler, Mathieu; Sorensen, Michael

2012-01-01

The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to the topic at hand and builds gradually towards discussing recent research. The book covers Wiener-driven equations as well as stochastic differential equations with jumps, including continuous-time ARMA processes and COGARCH processes. It presents a sp

Seasonal Variability of Thermophilic Campylobacter Spp. in Raw Milk Sold by Automatic Vending Machines in Lombardy Region.

Science.gov (United States)

Bertasi, Barbara; Losio, Marina Nadia; Daminelli, Paolo; Finazzi, Guido; Serraino, Andrea; Piva, Silvia; Giacometti, Federica; Massella, Elisa; Ostanello, Fabio

2016-06-03

In temperate climates, a seasonal trend was observed in the incidence of human campylobacteriosis cases, with peaks reported in spring and autumn in some countries, or in summer in others; a similar trend was observed in Campylobacter spp. dairy cattle faecal shedding, suggesting that cattle may play a role in the seasonal peak of human infection. The objectives of this study were to assess if a seasonal trend in thermophilic Campylobacter spp. contamination of raw milk exists and to evaluate a possible relation between this and the increase of human campylobacteriosis incidence in summer months. The results showed a mean prevalence of 1.6% of milk samples positive for thermophilic Campylobacter spp. with a wide range (0.0-3.1%) in different months during the three years considered. The statistical analysis showed a significant difference (P<0.01) of the prevalence of positive samples for thermophilic Campylobacter spp. between warmer and cooler months (2.3 vs 0.6%). The evidence of a seasonal trend in thermophilic Campylobacter spp. contamination of raw milk sold for direct consumption, with an increase of the prevalence in warmer months, may represent one of the possible links between seasonal trend in cattle faecal shedding and seasonal trend in human campylobacteriosis.

Study on process control and acceptability of irradiated seasonings

International Nuclear Information System (INIS)

Chen Qixun; Xu Peishu; Chen Hao; Chen Lihua; Dong Shaobin

1993-01-01

This paper studied the process control and quality control of irradiated seasonings for commercial purposes, market test and consumers' acceptability. The results showed that the rate of relative deviation of dose was less than 2 and the uniformity was better than 1.31 and the number of microbes decreased by 3-4 orders of magnitude after treatment with 8 kGy. No pathogenic bacteria were discovered and sensory evaluation as well as quality analysis were not changed. 110 tons of irradiated seasonings have been supplied to domestic markets and stores since 1990. The statistic data of 2045 consumers investigated showed that 67% of consumers heard about food irradiation. 72% of persons and 67% of families were willing to buy irradiated seasonings. (author)

Seasonal variation of serum biochemical values of Amazonian snakes (Boa constrictor constrictor kept in captivity

Directory of Open Access Journals (Sweden)

Dennis José da Silva Lima

2012-11-01

Full Text Available In northern Brazil, the seasons are not well defined compared to the South and Southeast regions, due to a hot and humid equatorial climate with a rainy season, known as the Amazonian winter, and a period with less rain, known as the Amazonian summer. The goal of this study was to evaluate the biochemical variation of serum from the Amazon Boa constrictor by correlating the values with the seasons of the region. A biochemical analysis of the serum was performed (AST, ALT, LDH, ALP, calcium, uric acid, phosphorus, total protein, albumin and globulin using 31 individuals of Boa constrictor constrictor, which were kept in captivity. It was observed that eight of the ten parameters were higher in the winter compared to the summer (total protein, albumin, globulin, ALT, AST, ALP, LDH and calcium. The ALT, AST and calcium values had statistically significant differences for the summer and winter, while the other parameters appear to be influenced by seasonality. This was the first study of snakes kept in captivity that analyzed the serum chemistry profile of Boa constrictor constrictor from the state of Pará, Brazil.

Statistically significant faunal differences among Middle Ordovician age, Chickamauga Group bryozoan bioherms, central Alabama

Energy Technology Data Exchange (ETDEWEB)

Crow, C.J.

1985-01-01

Middle Ordovician age Chickamauga Group carbonates crop out along the Birmingham and Murphrees Valley anticlines in central Alabama. The macrofossil contents on exposed surfaces of seven bioherms have been counted to determine their various paleontologic characteristics. Twelve groups of organisms are present in these bioherms. Dominant organisms include bryozoans, algae, brachiopods, sponges, pelmatozoans, stromatoporoids and corals. Minor accessory fauna include predators, scavengers and grazers such as gastropods, ostracods, trilobites, cephalopods and pelecypods. Vertical and horizontal niche zonation has been detected for some of the bioherm dwelling fauna. No one bioherm of those studied exhibits all 12 groups of organisms; rather, individual bioherms display various subsets of the total diversity. Statistical treatment (G-test) of the diversity data indicates a lack of statistical homogeneity of the bioherms, both within and between localities. Between-locality population heterogeneity can be ascribed to differences in biologic responses to such gross environmental factors as water depth and clarity, and energy levels. At any one locality, gross aspects of the paleoenvironments are assumed to have been more uniform. Significant differences among bioherms at any one locality may have resulted from patchy distribution of species populations, differential preservation and other factors.

Detecting Statistically Significant Communities of Triangle Motifs in Undirected Networks

Science.gov (United States)

2016-04-26

Systems, Statistics & Management Science, University of Alabama, USA. 1 DISTRIBUTION A: Distribution approved for public release. Contents 1 Summary 5...13 5 Application to Real Networks 18 5.1 2012 FBS Football Schedule Network... football schedule network. . . . . . . . . . . . . . . . . . . . . . 21 14 Stem plot of degree-ordered vertices versus the degree for college football

Seasonal Changes in Microbial Community Structure in Freshwater Stream Sediment in a North Carolina River Basin

Directory of Open Access Journals (Sweden)

John P. Bucci

2014-01-01

Full Text Available This study examined seasonal differences in microbial community structure in the sediment of three streams in North Carolina’s Neuse River Basin. Microbes that reside in sediment are at the base of the food chain and have a profound influence on the health of freshwater stream environments. Terminal-Restriction Fragment Length Polymorphism (T-RFLP, molecular fingerprint analysis of 16S rRNA genes was used to examine the diversity of bacterial species in stream sediment. Sediment was sampled in both wet and dry seasons from an agricultural (Bear, mixed urban (Crabtree and forested (Marks Creek, and the microbiota examined. Gamma, Alpha and Beta proteobacteria were prevalent species of microbial taxa represented among all sites. Actinobacteria was the next most prevalent species observed, with greater occurrence in dry compared to the wet season. Discernable clustering was observed of Marks and Bear Creek samples collected during the wetter period (September–April, which corresponded with a period of higher precipitation and cooler surface water temperatures. Although not statistically significant, microbial community structure appeared different between season (ANOSIM, R = 0.60; p < 0.10. Principal components analysis confirmed this pattern and showed that the bacterial groups were separated by wet and dry seasonal periods. These results suggest seasonal differences among the microbial community structure in sediment of freshwater streams and that these communities may respond to changes in precipitation during wetter periods.

Seasonal and spatial variations of atmospheric trace elemental deposition in the Aliaga industrial region, Turkey

Science.gov (United States)

Kara, Melik; Dumanoglu, Yetkin; Altiok, Hasan; Elbir, Tolga; Odabasi, Mustafa; Bayram, Abdurrahman

2014-11-01

Atmospheric bulk deposition (wet + dry deposition) samples (n = 40) were collected concurrently at ten sites in four seasons between June 2009 and April 2010 in the Aliaga heavily industrialized region, Turkey, containing a number of significant air pollutant sources. Analyses of trace elements were carried out using inductively coupled plasma-mass spectrometry (ICP-MS). While there were significant differences in the particulate matter (PM) deposition fluxes among the sampling sites, seasonal variations were not statistically significant (Kruskal-Wallis test, p < 0.05). Both PM deposition and elemental fluxes were increased at the sampling sites in the vicinity of industrial activities. The crustal elements (i.e., Ca, Mg) and some anthropogenic elements (such as Fe, Zn, Mn, Pb, Cu, and Cr) were high, and the highest fluxes were mostly measured in summer and winter seasons. The enrichment factor (EF) and principal component analysis (PCA) was applied to the data to determine the possible sources in the study area. High EF values were obtained for the anthropogenic elements such as Ag, Cd, Zn, Pb, Cu and Sb. The possible sources were identified as anthropogenic sources (i.e., iron-steel production) (45.4%), crustal and re-suspended dust (27.1%), marine aerosol (7.9%), and coal and wood combustion (8.2%). Thus, the iron-steel production and its related activities were found to be the main pollutant sources for this region.

The classification of PM10 concentrations in Johor Based on Seasonal Monsoons

Science.gov (United States)

Hamid, Hazrul Abdul; Hanafi Rahmat, Muhamad; Aisyah Sapani, Siti

2018-04-01

Air is the most important living resource in life. Contaminated air could adversely affect human health and the environment, especially during the monsoon season. Contamination occurs as a result of human action and haze. There are several pollutants present in the air where one of them is PM10. Secondary data was obtained from the Department of Environment from 2010 until 2014 and was analyzed using the hourly average of PM10 concentrations. This paper examined the relation between PM10 concentrations and the monsoon seasons (Northeast Monsoon and Southwest Monsoon) in Larkin and Pasir Gudang. It was expected that the concentration of PM10 would be higher during the Southwest Monsoon as it is a dry season. The data revealed that the highest PM10 concentrations were recorded between 2010 to 2014 during this particular monsoon season. The characteristics of PM10 concentration were compared using descriptive statistics based on the monsoon seasons and classified using the hierarchical cluster analysis (Ward Methods). The annual average of PM10 concentration during the Southwest Monsoon had exceeded the standard set by the Malaysia Ambient Air Quality Guidelines (50 μg/m3) while the PM10 concentration during the Northeast Monsoon was below the acceptable level for both stations. The dendrogram displayed showed two clusters for each monsoon season for both stations excepted for the PM10 concentration during the Northeast Monsoon in Larkin which was classified into three clusters due to the haze in 2010. Overall, the concentration of PM10 in 2013 was higher based on the clustering shown for every monsoon season at both stations according to the characteristics in the descriptive statistics.

Seasonal activity of Leptoiulus trilineatus (C.L. Koch, 1847) and Megaphyllum trassylvanicum (Verhoeff, 1897) (Diplopoda: Julida: Julidae)

Science.gov (United States)

Bachvarova, Darina; Doichinov, Aleksandar; Abdulova, Rayme

2018-03-01

The article presents the results of a study of the soil surface seasonal activity of two species of julidae, widely spread in the Balkan Peninsula: Leptoiulus trilineatus (C.L. Koch, 1847) and Megaphyllum trassylvanicum (Verhoeff, 1897). The material was collected by means of pitfall traps between May 2007 and May 2009 in natural and urban habitats exposed to varying degrees of anthropogenic pressure. In the study period 1474 specimens of L. trilineatus and 618 specimens of M. transsylvanicum were collected. The impact of the soil and air temperature and humidity on the seasonal activity of both species was measured through statistical analysis. The statistical data processing was conducted using SPSS 9.0 and StatPlus 3.5.3 software packages. L. trilineatus and M. trassylvanicum are polytopic, mesophilic and mesotermic species with year-round activity in the studied area. There is no statistically significant correlation between the degree of anthropogenic impact and the activity of the two species. Leptoiulus trilineatus shows equal preference for both urban and natural habitats in the studied area. The species demonstrates the typical of all millipedes bimodal activity, which is the highest in spring and the beginning of winter - in the periods from March to May and from November to December. The coefficients of correlation dependence of L. trilineatus activity on the tested abiotic environmental factors are not statistically significant. The Pearson-Brave coefficient which measures the effect of soil humidity on species activity is 0.417, which shows a positive correlation. M. trassylvanicum has the highest frequency in urban biotops such as parks in the urban and suburban areas of Shumen and in the coniferous habitats on the Shumen Plateau. In this area the species demonstrates its highest activity in spring and summer (from February to July). The abiotic factors with statistically significant effect on the soil surface activity of M. trassylvanicum are the

Observed decreases in the Canadian outdoor skating season due to recent winter warming

International Nuclear Information System (INIS)

Damyanov, Nikolay N; Mysak, Lawrence A; Damon Matthews, H

2012-01-01

Global warming has the potential to negatively affect one of Canada’s primary sources of winter recreation: hockey and ice skating on outdoor rinks. Observed changes in winter temperatures in Canada suggest changes in the meteorological conditions required to support the creation and maintenance of outdoor skating rinks; while there have been observed increases in the ice-free period of several natural water bodies, there has been no study of potential trends in the duration of the season supporting the construction of outdoor skating rinks. Here we show that the outdoor skating season (OSS) in Canada has significantly shortened in many regions of the country as a result of changing climate conditions. We first established a meteorological criterion for the beginning, and a proxy for the length of the OSS. We extracted this information from daily maximum temperature observations from 1951 to 2005, and tested it for significant changes over time due to global warming as well as due to changes in patterns of large-scale natural climate variability. We found that many locations have seen a statistically significant decrease in the OSS length, particularly in Southwest and Central Canada. This suggests that future global warming has the potential to significantly compromise the viability of outdoor skating in Canada. (letter)

Observed decreases in the Canadian outdoor skating season due to recent winter warming

Science.gov (United States)

Damyanov, Nikolay N.; Damon Matthews, H.; Mysak, Lawrence A.

2012-03-01

Global warming has the potential to negatively affect one of Canada’s primary sources of winter recreation: hockey and ice skating on outdoor rinks. Observed changes in winter temperatures in Canada suggest changes in the meteorological conditions required to support the creation and maintenance of outdoor skating rinks; while there have been observed increases in the ice-free period of several natural water bodies, there has been no study of potential trends in the duration of the season supporting the construction of outdoor skating rinks. Here we show that the outdoor skating season (OSS) in Canada has significantly shortened in many regions of the country as a result of changing climate conditions. We first established a meteorological criterion for the beginning, and a proxy for the length of the OSS. We extracted this information from daily maximum temperature observations from 1951 to 2005, and tested it for significant changes over time due to global warming as well as due to changes in patterns of large-scale natural climate variability. We found that many locations have seen a statistically significant decrease in the OSS length, particularly in Southwest and Central Canada. This suggests that future global warming has the potential to significantly compromise the viability of outdoor skating in Canada.

Methodological basis of the analysis and forecasting of trend-seasonal fluctuations in navigation maintenance in the sea of Аzov

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Андрій Олександрович Лисий

2015-11-01

Full Text Available The necessity to use trend-seasonal processes analysis and forecasting to manage seaports activities have been shown in the article. The statistic data showing the sea of Аzov ports freight turnover essential reduction in ice conditions is cited. The cited data has shown that in ice conditions the Azov sea ports freight turnover reduces considerably; in case of poor weather conditions and storm warnings the vessels arriving at ports can’t be loaded and unloaded in time. The concept of seasonal prevalence which is understood as regular periodical changes in weather conditions resulting from season change has been defined. Seasonal fluctuations are rather complicated -they are generated in one navigation area, transmitted to others, transformed and keep moving on calling forth subsequent fluctuations and interfering with sea transportation. From the point of view of this analysis seasonal prevalence is expressed in the form of oscillatory processes. In statistical researches seasonal prevalence indices and factors are used to describe seasonal fluctuations. Various models forecasting seasonal time series have been studied. A special approach to forming the information base and, considering all the activities of the port in the ice conditions, meeting the demands of continuous planning and regulation has been developed. Statistical forecasting including all stages of dynamic series processing has been offered and improved: the analysis of seasonal processes and forecasting of a seasonal wave. Such approach to forecasting can be applied to a wide range of the problems concerning the scheduling of fleet and ports

Seasonal and annual precipitation time series trend analysis in North Carolina, United States

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Sayemuzzaman, Mohammad; Jha, Manoj K.

2014-02-01

The present study performs the spatial and temporal trend analysis of the annual and seasonal time-series of a set of uniformly distributed 249 stations precipitation data across the state of North Carolina, United States over the period of 1950-2009. The Mann-Kendall (MK) test, the Theil-Sen approach (TSA) and the Sequential Mann-Kendall (SQMK) test were applied to quantify the significance of trend, magnitude of trend, and the trend shift, respectively. Regional (mountain, piedmont and coastal) precipitation trends were also analyzed using the above-mentioned tests. Prior to the application of statistical tests, the pre-whitening technique was used to eliminate the effect of autocorrelation of precipitation data series. The application of the above-mentioned procedures has shown very notable statewide increasing trend for winter and decreasing trend for fall precipitation. Statewide mixed (increasing/decreasing) trend has been detected in annual, spring, and summer precipitation time series. Significant trends (confidence level ≥ 95%) were detected only in 8, 7, 4 and 10 nos. of stations (out of 249 stations) in winter, spring, summer, and fall, respectively. Magnitude of the highest increasing (decreasing) precipitation trend was found about 4 mm/season (- 4.50 mm/season) in fall (summer) season. Annual precipitation trend magnitude varied between - 5.50 mm/year and 9 mm/year. Regional trend analysis found increasing precipitation in mountain and coastal regions in general except during the winter. Piedmont region was found to have increasing trends in summer and fall, but decreasing trend in winter, spring and on an annual basis. The SQMK test on "trend shift analysis" identified a significant shift during 1960 - 70 in most parts of the state. Finally, the comparison between winter (summer) precipitations with the North Atlantic Oscillation (Southern Oscillation) indices concluded that the variability and trend of precipitation can be explained by the

Seasonal dependence of large-scale Birkeland currents

International Nuclear Information System (INIS)

Fujii, R.; Iijima, T.; Potemra, T.A.; Sugiura, M.

1981-01-01

The seasonal dependence of large-scale Birkeland currents has been determined from the analysis of vector magnetic field data acquired by the TRIAD satellite in the northern hemisphere. Statistical characteristics of single sheet (i.e., net currents) and double sheet Birkeland currents were determined from 555 TRIAD passes during the summer, and 408 passes during the winter (more complicated multiple-sheet current systems were not included in this study). The average K/sub p/ value for the summer events is 1.9 and for the winter events is 2.0. The principal results include the following: (1) The single sheet Birkeland currents are statistically observed more often than the double sheet currents in the dayside of the auroral zone during any season. The single sheet currents are also observed more often in the summer than in the winter (as much as 2 to 3 times as often depending upon the MLT sector). (2) The intensities of the single and double sheet Birkeland currents on the dayside, from approximately 1000 MLT to 1800 MLT, are larger during the summer (in comparison to winter) by a factor of about 2. (3) The intensities of the double sheet Birkeland currents in the nightside (the dominant system in this local time) do not show a significant difference from summer to winter. (4) The single and double sheet currents in the dayside (between 0600 and 1800 MLT) appear at higher latitudes (by about 1 0 to 3 0 ) during the summer in comparison to the winter. These characterisctis suggest that the Birkeland current intensities are controlled by the ionosphere conductivity in the polar region. The greater occurrence of single sheet Birkeland currents during the summertime supports the suggestion that these currents close via the polar cap when the conductivity there is sufficiently high to permit it

Seasonal variation in the number of captures of Artibeus lituratus (Olfers, 1818 and Sturnira lilium (E. Geoffroy, 1810 (Chiroptera: Phyllostomidae in the upper strata of an Atlantic Forest remnant in southern Brazil

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Fernando Carvalho

2014-09-01

Full Text Available This study aimed to analyze the occurrence of seasonal variations in the number of captures of Artibeus lituratus and Sturnira lilium in the upper strata of an Atlantic Forest remnant in southern Brazil. It was conducted in the town of Pedras Grandes, in the southern end of Santa Catarina. The chiropterans were captured with mist nets installed in the canopy and subcanopy. To check whether there were differences in the number of captures between seasons, we used the chi-square test (χ2, with a significance level of 0.05, and, whenever needed, partial χ2 tests. Artibeus lituratus showed significant differences between seasons, and the largest number of captures occurs in autumn. For S. lilium we did not observe statistically significant differences. The seasonal variation found out for A. lituratus may be related to its diet, which is based on fruits whose availability has seasonal variations. For S. lilium, besides the diet, mainly based on plants that do not have seasonal variations with regard to fruit availability, the altitude of the study area and its variations in temperature also seem to explain the absence of seasonal variation.

Seasonality in Violent and Nonviolent Methods of Suicide Attempts: A Cross-Sectional Study on Systematic Registry Data.

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Veisani, Yousef; Delpisheh, Ali; Sayehmiri, Kourosh; Moradi, Ghobad; Hassanzadeh, Jafar

2017-08-01

Little attention has been paid to seasonality in suicide in Iran. Time pattern in suicide deaths and suicide attempts for some related factors such as gender, mental disorders has been found. In present study, we focus on suicide methods and the association with seasonality and other putative covariates such as gender. Through a cross-sectional study, overall identified suicide attempts and suicide deaths in the province of Ilam from 1 January 2010 and 31 December 2014 were enrolled. We used Edwards' test for test of seasonality in suicide methods. Seasonal effect (peak/trough seasons) and (deaths/attempts suicide) was explored by ratio statistics, the null hypothesis being that the attempted suicides in each method group are evenly distributed over a year. More suicide attempts by hanging 29.4% and self-immolation 41.4% were observed in spring and differ by season pattern in both genders. The overall distribution of suicides by violent and non-violent methods was (males x2=6.3, P=0.041, females x2=7.7, P=0.021) and (males x2=44.5, P=0.001, females x2=104.7, P=0.001), respectively. The peak and trough seasons was observed in taking medications and self-poisoning for spring and winter. Suicide with alcohol was no differ by season pattern (x2=1.0, P=0.460). Suicide in Ilam illustrates a significant seasonality for both violent and non-violent methods of suicide, in both genders, the two peaks were observed in spring and autumn for violent suicides, and spring and summer in non-violent suicides.

Diurnal and seasonal variations of greenhouse gas emissions from a naturally ventilated dairy barn in a cold region

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Huang, Dandan; Guo, Huiqing

2018-01-01

Carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) emissions were quantified for a naturally ventilated free-stall dairy barn in the Canadian Prairies climate through continuous measurements for a year from February 2015 to January 2016, with ventilation rate estimated by a CO2 mass balance method. The results were categorized into seasonal emission profiles with monthly data measured on a typical day, and diurnal profiles in cold (January), warm (July), and mild seasons (October) of all three gases. Seasonal CO2, CH4, and N2O concentrations greatly fluctuated within ranges of 593-2433 ppm, 15-152 ppm, and 0.32-0.40 ppm, respectively, with obviously higher concentrations in the cold season. Emission factors of the three gases were summarized: seasonal N2O emission varied between 0.5 and 10 μg s-1 AU-1 with lower emission in the cold season, while seasonal CO2 and CH4 emissions were within narrow ranges of 112-119 mg s-1 AU-1 and 2.5-3.5 mg s-1 AU-1. The result suggested a lower enteric CH4 emission for dairy cows than that estimated by Environment Canada (2014). Significant diurnal effects (P 0.05), but obvious diurnal variations in all seasons. In comparison with previous studies, it was found that the dairy barn in a cold region climate with smaller vent openings had relatively higher indoor CO2 and CH4 concentrations, but comparable CO2 and CH4 emissions to most previous studies. Besides, ventilation rate, temperature, and relative humidity all significantly affected the three gas concentrations with the outdoor temperature being the most relevant factor (P < 0.01); however, they showed less or no statistical relations to emissions.

Seasonal variations of indoor microbial exposures and their relation to temperature, relative humidity, and air exchange rate.

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Frankel, Mika; Bekö, Gabriel; Timm, Michael; Gustavsen, Sine; Hansen, Erik Wind; Madsen, Anne Mette

2012-12-01

Indoor microbial exposure has been related to adverse pulmonary health effects. Exposure assessment is not standardized, and various factors may affect the measured exposure. The aim of this study was to investigate the seasonal variation of selected microbial exposures and their associations with temperature, relative humidity, and air exchange rates in Danish homes. Airborne inhalable dust was sampled in five Danish homes throughout the four seasons of 1 year (indoors, n = 127; outdoors, n = 37). Measurements included culturable fungi and bacteria, endotoxin, N-acetyl-beta-d-glucosaminidase, total inflammatory potential, particles (0.75 to 15 μm), temperature, relative humidity, and air exchange rates. Significant seasonal variation was found for all indoor microbial exposures, excluding endotoxin. Indoor fungi peaked in summer (median, 235 CFU/m(3)) and were lowest in winter (median, 26 CFU/m(3)). Indoor bacteria peaked in spring (median, 2,165 CFU/m(3)) and were lowest in summer (median, 240 CFU/m(3)). Concentrations of fungi were predominately higher outdoors than indoors, whereas bacteria, endotoxin, and inhalable dust concentrations were highest indoors. Bacteria and endotoxin correlated with the mass of inhalable dust and number of particles. Temperature and air exchange rates were positively associated with fungi and N-acetyl-beta-d-glucosaminidase and negatively with bacteria and the total inflammatory potential. Although temperature, relative humidity, and air exchange rates were significantly associated with several indoor microbial exposures, they could not fully explain the observed seasonal variations when tested in a mixed statistical model. In conclusion, the season significantly affects indoor microbial exposures, which are influenced by temperature, relative humidity, and air exchange rates.

Conducting tests for statistically significant differences using forest inventory data

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James A. Westfall; Scott A. Pugh; John W. Coulston

2013-01-01

Many forest inventory and monitoring programs are based on a sample of ground plots from which estimates of forest resources are derived. In addition to evaluating metrics such as number of trees or amount of cubic wood volume, it is often desirable to make comparisons between resource attributes. To properly conduct statistical tests for differences, it is imperative...

Determination of beta-carotene and vitamin A contents of serum and liver of sheep slaughtered in Ahvaz abattoir during different seasons of the year

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N Hedayat

2016-11-01

Full Text Available Because of the particular role of vitamin A in different tissues and organs, various clinical signs are seen in its deficiency. Additionally, marginal deficiency of vitamin A without the presence of clinical signs leads to performance defects such as infertility. In this study, the seasonal changes of β-carotene and vitamin A of serum and liver of slaughtered sheep in Ahvaz abattoir were investigated. A total of 360 sheep were sampled from October 2013 to June 2014. Spectrophotometry was used for measuring values. The results were analyzed statistically with student t-test. The mean ±SE concentration of β-carotene and vitamin A of serum and liver were 209/9±1/5, 98±0/9 (µg/dl, 19/8±0/4, 32/3±0/8(µg/g, respectively. Although there wasn't significant difference in levels of the measured parameters in two age groups(sheep only with immature teeth and sheep with a minimum mature tooth but there was a significant difference in vitamin A of serum and liver in the two sexes. The serumic levels of vitamin A in male sheep was more than the females while the concentration of vitamin A in the liver of female sheep was more than the males. The difference between seasons in vitamin A of serum was also statistically different with higher concentrations observed in warm seasons in comparison to milder seasons.

Potential for western US seasonal snowpack prediction

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Kapnick, Sarah B.; Yang, Xiaosong; Vecchi, Gabriel A.; Delworth, Thomas L.; Gudgel, Rich; Malyshev, Sergey; Milly, Paul C. D.; Shevliakova, Elena; Underwood, Seth; Margulis, Steven A.

2018-01-01

Western US snowpack—snow that accumulates on the ground in the mountains—plays a critical role in regional hydroclimate and water supply, with 80% of snowmelt runoff being used for agriculture. While climate projections provide estimates of snowpack loss by the end of th ecentury and weather forecasts provide predictions of weather conditions out to 2 weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), crucial for regional agricultural decisions (e.g., plant choice and quantity). Seasonal predictions with climate models first took the form of El Niño predictions 3 decades ago, with hydroclimate predictions emerging more recently. While the field has been focused on single-season predictions (3 months or less), we are now poised to advance our predictions beyond this timeframe. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate the feasibility of seasonal snowpack predictions and quantify the limits of predictive skill 8 month sin advance. This physically based dynamic system outperforms observation-based statistical predictions made on July 1 for March snowpack everywhere except the southern Sierra Nevada, a region where prediction skill is nonexistent for every predictor presently tested. Additionally, in the absence of externally forced negative trends in snowpack, narrow maritime mountain ranges with high hydroclimate variability pose a challenge for seasonal prediction in our present system; natural snowpack variability may inherently be unpredictable at this timescale. This work highlights present prediction system successes and gives cause for optimism for developing seasonal predictions for societal needs.

Role of season, temperature and humidity on the incidence of epistaxis in Alberta, Canada

Science.gov (United States)

2014-01-01

Background Classical dogma holds that epistaxis is more common in winter months but there is significant variability reported in the literature. No study has yet examined the effect of season, humidity and temperature on epistaxis in a location with as severe weather extremes as seen in Alberta, Canada. The objective of the study is to evaluate for an effect of these meteorological factors on the incidence of epistaxis in Alberta. Method A retrospective review of consecutive adult patients presenting to the Emergency room (ER) in Edmonton and Calgary, Alberta over a three-year period was performed. Daily temperature and humidity data was recorded from the respective airports. Statistical analysis with Pearson’s correlation coefficient was performed. Results 4315 patients presented during the study period. Mean daily temperatures ranged from a low of -40°C to a high of +23°C. A significant negative correlation was found for mean monthly temperature with epistaxis (Pearson’s r = -0.835, p = 0.001). A significant correlation was also present for daily temperature and epistaxis presentation (Pearson’s r = -0.55, p = 0.018, range 1.8 to 2.2 events/day). No correlation was identified with humidity and no significant seasonal variation was present. Conclusions A negative correlation was found to exist for both daily and mean monthly temperature with rates of epistaxis. A seasonal variation was seen in Edmonton but not in Calgary. No correlation was found for humidity when compared to both presentation rates and admissions. PMID:24755112

The seasonal influence of climate and environment on yellow fever transmission across Africa.

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Hamlet, Arran; Jean, Kévin; Perea, William; Yactayo, Sergio; Biey, Joseph; Van Kerkhove, Maria; Ferguson, Neil; Garske, Tini

2018-03-01

Yellow fever virus (YFV) is a vector-borne flavivirus endemic to Africa and Latin America. Ninety per cent of the global burden occurs in Africa where it is primarily transmitted by Aedes spp, with Aedes aegypti the main vector for urban yellow fever (YF). Mosquito life cycle and viral replication in the mosquito are heavily dependent on climate, particularly temperature and rainfall. We aimed to assess whether seasonal variations in climatic factors are associated with the seasonality of YF reports. We constructed a temperature suitability index for YFV transmission, capturing the temperature dependence of mosquito behaviour and viral replication within the mosquito. We then fitted a series of multilevel logistic regression models to a dataset of YF reports across Africa, considering location and seasonality of occurrence for seasonal models, against the temperature suitability index, rainfall and the Enhanced Vegetation Index (EVI) as covariates alongside further demographic indicators. Model fit was assessed by the Area Under the Curve (AUC), and models were ranked by Akaike's Information Criterion which was used to weight model outputs to create combined model predictions. The seasonal model accurately captured both the geographic and temporal heterogeneities in YF transmission (AUC = 0.81), and did not perform significantly worse than the annual model which only captured the geographic distribution. The interaction between temperature suitability and rainfall accounted for much of the occurrence of YF, which offers a statistical explanation for the spatio-temporal variability in transmission. The description of seasonality offers an explanation for heterogeneities in the West-East YF burden across Africa. Annual climatic variables may indicate a transmission suitability not always reflected in seasonal interactions. This finding, in conjunction with forecasted data, could highlight areas of increased transmission and provide insights into the occurrence of

Seasonal patterns of seismicity and deformation at the Alutu geothermal reservoir, Ethiopia, induced by hydrological loading

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Birhanu, Yelebe; Wilks, Matthew; Biggs, Juliet; Kendall, J.-Michael; Ayele, Atalay; Lewi, Elias

2018-05-01

Seasonal variations in the seismicity of volcanic and geothermal reservoirs are usually attributed to the hydrological cycle. Here, we focus on the Aluto-Langano geothermal system, Ethiopia, where the climate is monsoonal and there is abundant shallow seismicity. We deployed temporary networks of seismometers and GPS receivers to understand the drivers of unrest. First, we show that a statistically significant peak in seismicity occurred 2-3 months after the main rainy season, with a second, smaller peak of variable timing. Seasonal seismicity is commonly attributed to variations in either surface loading or reservoir pore pressure. As loading will cause subsidence and overpressure will cause uplift, comparing seismicity rates with continuous GPS, enables us to distinguish between mechanisms. At Aluto, the major peak in seismicity is coincident with the high stand of nearby lakes and maximum subsidence, indicating that it is driven by surface loading. The magnitude of loading is insufficient to trigger widespread crustal seismicity but the geothermal reservoir at Aluto is likely sensitive to small perturbations in the stress field. Thus we demonstrate that monsoonal loading can produce seismicity in geothermal reservoirs, and the likelihood of both triggered and induced seismicity varies seasonally.

Detecting seasonal and cyclical trends in agricultural runoff water quality-hypothesis tests and block bootstrap power analysis.

Science.gov (United States)

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.

Statistical uncertainty of extreme wind storms over Europe derived from a probabilistic clustering technique

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Walz, Michael; Leckebusch, Gregor C.

2016-04-01

Extratropical wind storms pose one of the most dangerous and loss intensive natural hazards for Europe. However, due to only 50 years of high quality observational data, it is difficult to assess the statistical uncertainty of these sparse events just based on observations. Over the last decade seasonal ensemble forecasts have become indispensable in quantifying the uncertainty of weather prediction on seasonal timescales. In this study seasonal forecasts are used in a climatological context: By making use of the up to 51 ensemble members, a broad and physically consistent statistical base can be created. This base can then be used to assess the statistical uncertainty of extreme wind storm occurrence more accurately. In order to determine the statistical uncertainty of storms with different paths of progression, a probabilistic clustering approach using regression mixture models is used to objectively assign storm tracks (either based on core pressure or on extreme wind speeds) to different clusters. The advantage of this technique is that the entire lifetime of a storm is considered for the clustering algorithm. Quadratic curves are found to describe the storm tracks most accurately. Three main clusters (diagonal, horizontal or vertical progression of the storm track) can be identified, each of which have their own particulate features. Basic storm features like average velocity and duration are calculated and compared for each cluster. The main benefit of this clustering technique, however, is to evaluate if the clusters show different degrees of uncertainty, e.g. more (less) spread for tracks approaching Europe horizontally (diagonally). This statistical uncertainty is compared for different seasonal forecast products.

The Relationship between an Invasive Shrub and Soil Moisture: Seasonal Interactions and Spatially Covarying Relations

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Yuhong He

2014-09-01

Full Text Available Recent studies indicate that positive relationships between invasive plants and soil can contribute to further plant invasions. However, it remains unclear whether these relations remain unchanged throughout the growing season. In this study, spatial sequences of field observations along a transect were used to reveal seasonal interactions and spatially covarying relations between one common invasive shrub (Tartarian Honeysuckle, Lonicera tatarica and soil moisture in a tall grassland habitat. Statistical analysis over the transect shows that the contrast between soil moisture in shrub and herbaceous patches vary with season and precipitation. Overall, a negatively covarying relationship between shrub and soil moisture (i.e., drier surface soils at shrub microsites exists during the very early growing period (e.g., May, while in summer a positively covarying phenomenon (i.e., wetter soils under shrubs is usually evident, but could be weakened or vanish during long precipitation-free periods. If there is sufficient rainfall, surface soil moisture and leaf area index (LAI often spatially covary with significant spatial oscillations at an invariant scale (which is governed by the shrub spatial pattern and is about 8 m, but their phase relation in space varies with season, consistent with the seasonal variability of the co-varying phenomena between shrub invasion and soil water content. The findings are important for establishing a more complete picture of how shrub invasion affects soil moisture.

Seasonal Variation in Group Size Is Related to Seasonal Variation in Neuropeptide Receptor Density.

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Wilson, Leah C; Goodson, James L; Kingsbury, Marcy A

2016-01-01

In many species, seasonal variation in grouping behavior is widespread, with shifts towards territoriality in the breeding season and grouping in the winter. Compared to the hormonal and neural mechanisms of seasonal territorial aggression, the mechanisms that promote seasonal grouping have received little attention. We collected brains in spring and winter from wild-caught males of two species of emberizid sparrows that seasonally flock (the field sparrow, Spizella pusilla, and the dark-eyed junco, Junco hyemalis) and two species that do not seasonally flock (the song sparrow, Melospiza melodia, and the eastern towhee, Pipilo erythrophthalmus). We used receptor autoradiography to quantify seasonal plasticity in available binding sites for three neuropeptides known to influence social behavior. We examined binding sites for 125I-vasoactive intestinal polypeptide (VIP), 125I-sauvagine (SG, a ligand for corticotropin-releasing hormone receptors) and 125I-ornithine vasotocin analog (OVTA, a ligand for the VT3 nonapeptide). For all species and ligands, brain areas that exhibited a seasonal pattern in binding density were characterized by a winter increase. Compared to nonflocking species, seasonally flocking species showed different binding patterns in multiple brain areas. Furthermore, we found that winter flocking was associated with elevated winter 125I-VIP binding density in the medial amygdala, as well as 125I-VIP and 125I-OVTA binding density in the rostral arcopallium. While the functional significance of the avian rostral arcopallium is unclear, it may incorporate parts of the pallial amygdala. Our results point to this previously undescribed area as a likely hot spot of social modulation. © 2016 S. Karger AG, Basel.

New England observed and predicted growing season maximum stream/river temperature points

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U.S. Environmental Protection Agency — The shapefile contains points with associated observed and predicted growing season maximum stream/river temperatures in New England based on a spatial statistical...

Coupled effects of natural and anthropogenic controls on seasonal and spatial variations of river water quality during baseflow in a coastal watershed of Southeast China.

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Jinliang Huang

Full Text Available Surface water samples of baseflow were collected from 20 headwater sub-watersheds which were classified into three types of watersheds (natural, urban and agricultural in the flood, dry and transition seasons during three consecutive years (2010-2012 within a coastal watershed of Southeast China. Integrating spatial statistics with multivariate statistical techniques, river water quality variations and their interactions with natural and anthropogenic controls were examined to identify the causal factors and underlying mechanisms governing spatiotemporal patterns of water quality. Anthropogenic input related to industrial effluents and domestic wastewater, agricultural activities associated with the precipitation-induced surface runoff, and natural weathering process were identified as the potential important factors to drive the seasonal variations in stream water quality for the transition, flood and dry seasons, respectively. All water quality indicators except SRP had the highest mean concentrations in the dry and transition seasons. Anthropogenic activities and watershed characteristics led to the spatial variations in stream water quality in three types of watersheds. Concentrations of NH(4(+-N, SRP, K(+, COD(Mn, and Cl- were generally highest in urban watersheds. NO3(-N Concentration was generally highest in agricultural watersheds. Mg(2+ concentration in natural watersheds was significantly higher than that in agricultural watersheds. Spatial autocorrelations analysis showed similar levels of water pollution between the neighboring sub-watersheds exhibited in the dry and transition seasons while non-point source pollution contributed to the significant variations in water quality between neighboring sub-watersheds. Spatial regression analysis showed anthropogenic controls played critical roles in variations of water quality in the JRW. Management implications were further discussed for water resource management. This research

Seasonal variation in the prevalence of preeclampsia

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Fatemeh Janani

2017-01-01

Full Text Available Introduction: Hypertension in pregnancy is one of the three factors of maternal mortality. Etiology of the disease is unknown, but the many factors contributing to the identification and control of it can be taken a step to prevent and reduce the symptoms of the disease. The purpose of this study was to determine the prevalence of preeclampsia (high-blood pressure in different seasons of the year. Methods: The present retrospective cross-sectional study was conducted on more than 8,000 pregnant women visiting Assali specialized hospital from 2011 to 2013. Required data was collected through questionnaire checklist. The Chi-square test with multiple comparisons was used to compare the frequencies of pregnancy-induced hypertension (PIH according to the month of year, and adjustment of multiplicity was conducted using Bonferroni's method. Student's t-test was used to compare the means of PIH prevalence rates. In all analyses, P < 0.05 was taken to indicate statistical significance. Results: In these 8000 woman admitted to labor, overall prevalence of PIH was 3.8 ± 0.6%. The prevalence rate of PIH was highest in the summer (4.5% and lowest frequent in the winter (2.7%, respectively. In July, the prevalence rate was significantly higher than those for any other month (4.7%, and in March, it was lower prevalence than for any month (2.2%, respectively. Using the Chi-square test, a significant difference between the incidence of disease was observed in summer and winter (P < 0.001. Conclusion: The prevalence rate of PIH was higher for delivery in summer and early spring and lowest for winter delivery among Khorramabad women based on these results; it seems that changes in temperature and humidity in different seasons can affect preeclampsia, and preeclampsia increases with increasing frequency temperature.

The distribution of P-values in medical research articles suggested selective reporting associated with statistical significance.

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Perneger, Thomas V; Combescure, Christophe

2017-07-01

Published P-values provide a window into the global enterprise of medical research. The aim of this study was to use the distribution of published P-values to estimate the relative frequencies of null and alternative hypotheses and to seek irregularities suggestive of publication bias. This cross-sectional study included P-values published in 120 medical research articles in 2016 (30 each from the BMJ, JAMA, Lancet, and New England Journal of Medicine). The observed distribution of P-values was compared with expected distributions under the null hypothesis (i.e., uniform between 0 and 1) and the alternative hypothesis (strictly decreasing from 0 to 1). P-values were categorized according to conventional levels of statistical significance and in one-percent intervals. Among 4,158 recorded P-values, 26.1% were highly significant (P values values equal to 1, and (3) about twice as many P-values less than 0.05 compared with those more than 0.05. The latter finding was seen in both randomized trials and observational studies, and in most types of analyses, excepting heterogeneity tests and interaction tests. Under plausible assumptions, we estimate that about half of the tested hypotheses were null and the other half were alternative. This analysis suggests that statistical tests published in medical journals are not a random sample of null and alternative hypotheses but that selective reporting is prevalent. In particular, significant results are about twice as likely to be reported as nonsignificant results. Copyright © 2017 Elsevier Inc. All rights reserved.

Modelagem estatística da precipitação mensal e anual e no período seco para o estado de Minas Gerais Statistical modeling of monthly, annual and dry season mean precipitation for the State of Minas Gerais

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Carlos R. de Mello

2009-02-01

Full Text Available Objetivou-se, com o presente estudo, ajustar modelos lineares para predição da precipitação média mensal (no período úmido e anual e no período seco, baseados nas coordenadas geográficas (latitude e longitude e altitude para o Estado de Minas Gerais. Aplicaram-se dados diários de precipitação, provenientes da Agência Nacional de Águas (ANA de 209 estações meteorológicas, das quais 197 foram usadas para ajuste dos modelos e 12 para sua validação final. O coeficiente de determinação ajustado (r², o erro médio absoluto (%, a tendência das estimativas (% e significância dos parâmetros, foram considerados na avaliação dos modelos. De maneira geral, os modelos apresentaram bons parâmetros estatísticos de validação, com r² maior que 0,70, erro médio menor que 10% e tendência não significativa (This study aimed at adjusting statistical linear models for prediction of total mean precipitation associated to monthly (in the wet season, annual and dry season periods, based on geographical coordinates (latitude and longitude and altitude for the State of Minas Gerais, Brazil. Daily precipitation data from the "Agência Nacional de Águas" (ANA for 209 pluviometric stations were applied, 197 for modeling adjustment and 12 for final validation. Coefficient of determination adjusted (r², mean absolute error (%, prediction bias (% and estimated parameters significance were considered for evaluation of models. The monthly and annual precipitation models presented good statistical validation coefficients, with r² greater than 0.70, mean error smaller than 10% and bias not significant (< 2% in relation to mean value. However, the dry season model presented an overestimation of precipitation, showing that more variables associated to topographic characteristics would be necessary to produce a more accurate model. Nevertheless, the adjusted models present good conditions for practical applications, forming an important tool for

Epidemiology and socioeconomic impact of seasonal affective disorder in Austria.

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Pjrek, E; Baldinger-Melich, P; Spies, M; Papageorgiou, K; Kasper, S; Winkler, D

2016-02-01

Seasonal affective disorder (SAD) is a subtype of recurrent depressive or bipolar disorder that is characterized by regular onset and remission of affective episodes at the same time of the year. The aim of the present study was to provide epidemiological data and data on the socioeconomic impact of SAD in the general population of Austria. We conducted a computer-assisted telephone interview in 910 randomly selected subjects (577 females and 333 males) using the Seasonal Health Questionnaire (SHQ), the Seasonal Pattern Assessment Questionnaire (SPAQ), and the Sheehan Disability Scale (SDS). Telephone numbers were randomly drawn from all Austrian telephone books and transformed using the random last digits method. The last birthday method was employed to choose the target person for the interviews. Out of our subjects, 2.5% fulfilled criteria for the seasonal pattern specifier according to DSM-5 and 2.4% (95% CI=1.4-3.5%) were diagnosed with SAD. When applying the ICD-10 criteria 1.9% (95% CI=0.9-2.8%) fulfilled SAD diagnostic criteria. The prevalence of fall-winter depression according to the Kasper-Rosenthal criteria was determined to be 3.5%. The criteria was fulfilled by 15.1% for subsyndromal SAD (s-SAD). We did not find any statistically significant gender differences in prevalence rates. When using the DSM-5 as a gold standard for the diagnosis of SAD, diagnosis derived from the SPAQ yielded a sensitivity of 31.8% and a specificity of 97.2%. Subjects with SAD had significantly higher scores on the SDS and higher rates of sick leave and days with reduced productivity than healthy subjects. Prevalence estimates for SAD with the SHQ are lower than with the SPAQ. Our data are indicative of the substantial burden of disease and the socioeconomic impact of SAD. This epidemiological data shows a lack of gender differences in SAD prevalence. The higher rates of females in clinical SAD samples might, at least in part, be explained by lower help seeking behaviour in

Seasonally and regionally determined indication potential of bioassays in contaminated river sediments.

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Hilscherová, Klára; Dusek, Ladislav; Sídlová, Tereza; Jálová, Veronika; Cupr, Pavel; Giesy, John P; Nehyba, Slavomír; Jarkovský, Jirí; Klánová, Jana; Holoubek, Ivan

2010-03-01

River sediments are a dynamic system, especially in areas where floods occur frequently. In the present study, an integrative approach is used to investigate the seasonal and spatial dynamics of contamination of sediments from a regularly flooded industrial area in the Czech Republic, which presents a suitable model ecosystem for pollutant distribution research at a regional level. Surface sediments were sampled repeatedly to represent two different hydrological situations: spring (after the peak of high flow) and autumn (after longer period of low flow). Samples were characterized for abiotic parameters and concentrations of priority organic pollutants. Toxicity was assessed by Microtox test; genotoxicity by SOS-chromotest and green fluorescent protein (GFP)-yeast test; and the presence of compounds with specific mode of action by in vitro bioassays for dioxin-like activity, anti-/androgenicity, and anti-/estrogenicity. Distribution of organic contaminants varied among regions and seasonally. Although the results of Microtox and genotoxicity tests were relatively inconclusive, all other specific bioassays led to statistically significant regional and seasonal differences in profiles and allowed clear separation of upstream and downstream regions. The outcomes of these bioassays indicated an association with concentrations of polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) as master variables. There were significant interrelations among dioxin-like activity, antiandrogenicity and content of organic carbon, clay, and concentration of PAHs and PCBs, which documents the significance of abiotic factors in accumulation of pollutants. The study demonstrates the strength of the specific bioassays in indicating the changes in contamination and emphasizes the crucial role of a well-designed sampling plan, in which both spatial and temporal dynamics should be taken into account, for the correct interpretations of information in risk assessments.

Seasonal variation in sports participation.

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Schüttoff, Ute; Pawlowski, Tim

2018-02-01

This study explores indicators describing socio-demographics, sports participation characteristics and motives which are associated with variation in sports participation across seasons. Data were drawn from the German Socio-Economic Panel which contains detailed information on the sports behaviour of adults in Germany. Overall, two different measures of seasonal variation are developed and used as dependent variables in our regression models. The first variable measures the coefficient of (seasonal) variation in sport-related energy expenditure per week. The second variable measures whether activity drops below the threshold as defined by the World Health Organization (WHO). Results suggest that the organisational setting, the intensity and number of sports practised, and the motive for participation are strongly correlated with the variation measures used. For example, both, participation in a sports club and a commercial facility, are associated with reduced seasonal variation and a significantly higher probability of participating at a volume above the WHO threshold across all seasons. These findings give some impetus for policymaking and the planning of sports programmes as well as future research directions.

Effects of seasonal variations on thermoregulation of ostrich

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Basuony, H.A.M.

2011-01-01

Twelve ostrich aged 7 months old were used during summer and winter from the breeding flock of the ostrich farm, at the Nuclear Research Center in Inshas, of Atomic Energy Authority, Egypt. In the study all birds were exposed to ambient temperatures in summer and winter, and the birds were fed grower ration ad libitum (19% protein and 2450 K cal ME /Kg).The present study was carried out to evaluate the effect of temperature variation during summer and winter seasons and diurnal effect on changes in some physiological and blood chemical parameters, the daily feed consumption (g/bird/day) and water consumption (ml/bird/day) these parameters were measured during 7 days in each season. Cloacal temperatures was measured and blood samples were taken twice, one in the morning at 7 am and once in the afternoon at 3 pm during a representative 7 hot days of June (40±2 degree C) (summer) and the 7 cold days of January (18±2 degree C) (winter). Red blood cell (RBCs) counts and total white blood cell (WBCs) counts, hemoglobin concentration (Hb) and packed cell volume (PCV) were determined. Mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH) and mean corpuscular hemoglobin concentrations (MCHC) were calculated. Serum, total protein (TP), albumen (A) and globulin (G) concentrations were measured. Furthermore, serum alanine transaminase (ALT), aspartate transaminase (AST), glucose and triglycerides concentrations were determined. Also, serum triiodothyronine (T 3 ), and aldosterone levels were estimated. Also, the amount of total body water was determined by the antipyren method. Finally, serum protein profile it was conducted by Native-PAGE method (Native polyacrylamide gel electrophoresis) on vertical slab gel to determine protein profiles in blood proteins of ostrich. Results indicated that feed consumption unlike water consumption was significantly increased during winter than in summer season. Moreover, body temperature increased significantly during the

Comparison of seasonal variation in the fasting respiratory quotient of young Japanese, Polish and Thai women in relation to seasonal change in their percent body fat

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Morinaka Tomoko

2012-05-01

Full Text Available Abstract Background From the viewpoint of human physiological adaptability, we previously investigated seasonal variation in the amount of unabsorbed dietary carbohydrates from the intestine after breakfast in Japanese, Polish and Thai participants. In this investigation we found that there were significant seasonal variations in the amount of unabsorbed dietary carbohydrates in Japanese and Polish participants, while we could not find significant seasonal variation in Thai participants. These facts prompted us to examine seasonal variations in the respiratory quotient after an overnight fast (an indicator of the ratio of carbohydrate and fat oxidized after the last meal with female university students living in Osaka (Japan, Poznan (Poland and Chiang Mai (Thailand. Methods We enrolled 30, 33 and 32 paid participants in Japan, Poland and Thailand, respectively, and measurements were taken over the course of one full year. Fasting respiratory quotient was measured with the participants in their postabsorptive state (after 12 hours or more fasting before respiratory quotient measurement. Respiratory quotient measurements were carried out by means of indirect calorimetry using the mixing chamber method. The percent body fat was measured using an electric bioelectrical impedance analysis scale. Food intake of the participants in Osaka and Poznan were carried out by the Food Frequency Questionnaire method. Results There were different seasonal variations in the fasting respiratory quotient values in the three different populations; with a significant seasonal variation in the fasting respiratory quotient values in Japanese participants, while those in Polish and Thai participants were non-significant. We found that there were significant seasonal changes in the percent body fat in the three populations but we could not find any significant correlation between the fasting respiratory quotient values and the percent body fat. Conclusions There were

Gluteus medius activation during running is a risk factor for season hamstring injuries in elite footballers.

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Franettovich Smith, Melinda M; Bonacci, Jason; Mendis, M Dilani; Christie, Craig; Rotstein, Andrew; Hides, Julie A

2017-02-01

To investigate if size and activation of the gluteal muscles is a risk factor for hamstring injuries in elite AFL players. Prospective cohort study. Twenty-six elite male footballers from a professional Australian Football League (AFL) club participated in the study. At the beginning of the season bilateral gluteus medius (GMED) and gluteus maximus (GMAX) muscle volume was measured from magnetic resonance images and electromyographic recordings of the same muscles were obtained during running. History of hamstring injury in the pre-season and incidence of hamstring injury during the season were determined from club medical data. Nine players (35%) incurred a hamstring injury during the season. History of hamstring injury was comparable between those players who incurred a season hamstring injury (2/9 players; 22%) and those who did not (3/17 players; 18%). Higher GMED muscle activity during running was a risk factor for hamstring injury (p=0.03, effect sizes 1.1-1.5). There were no statistically significant differences observed for GMED volume, GMAX volume and GMAX activation (P>0.05). This study identified higher activation of the GMED muscle during running in players who sustained a season hamstring injury. Whilst further research is required to understand the mechanism of altered muscle control, the results of this study contribute to the developing body of evidence that the lumbo-pelvic muscles may be important to consider in hamstring injury prevention and management. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Validation of inverse seasonal peak mortality in medieval plagues, including the Black Death, in comparison to modern Yersinia pestis-variant diseases.

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Mark R Welford

Full Text Available BACKGROUND: Recent studies have noted myriad qualitative and quantitative inconsistencies between the medieval Black Death (and subsequent "plagues" and modern empirical Y. pestis plague data, most of which is derived from the Indian and Chinese plague outbreaks of A.D. 1900+/-15 years. Previous works have noted apparent differences in seasonal mortality peaks during Black Death outbreaks versus peaks of bubonic and pneumonic plagues attributed to Y. pestis infection, but have not provided spatiotemporal statistical support. Our objective here was to validate individual observations of this seasonal discrepancy in peak mortality between historical epidemics and modern empirical data. METHODOLOGY/PRINCIPAL FINDINGS: We compiled and aggregated multiple daily, weekly and monthly datasets of both Y. pestis plague epidemics and suspected Black Death epidemics to compare seasonal differences in mortality peaks at a monthly resolution. Statistical and time series analyses of the epidemic data indicate that a seasonal inversion in peak mortality does exist between known Y. pestis plague and suspected Black Death epidemics. We provide possible explanations for this seasonal inversion. CONCLUSIONS/SIGNIFICANCE: These results add further evidence of inconsistency between historical plagues, including the Black Death, and our current understanding of Y. pestis-variant disease. We expect that the line of inquiry into the disputed cause of the greatest recorded epidemic will continue to intensify. Given the rapid pace of environmental change in the modern world, it is crucial that we understand past lethal outbreaks as fully as possible in order to prepare for future deadly pandemics.

Using Accretionary Hard Parts to Study Changes in Seasonality over Geologic Time

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Ivany, L. C.; Judd, E. J.

2017-12-01

subtropics, cooling MAT is driven by a statistically significant decline in winter temperatures; summer temperatures are effectively constant through time. This is opposite to that seen in the polar Antarctic section, revealing causal mechanisms and pointing to latitudinal differences in the marine manifestation of climate change.

Seasonality of suicide deaths in Serbia, 1990-2012

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Penev Goran

2014-01-01

Full Text Available Background: In the period from 1990 to 2012, there were 32,855 suicides registered in Serbia, i.e. an average of 1428 deaths per year (18.9 per 100.000 inhabitants. The suicides were the most frequent in the early 1990s, less frequent during the 2000s, and least frequent in the last three years of the observed period (2010-2012 - an average of 1237 suicides per year. Objective: The goal of this paper is to evaluate the seasonal variations of suicides in Serbia in the period of 1990-2012, their changes, as well as the accordance with findings from other countries. Method: In the paper are used "classical" statistical methods of evaluating cyclical variations (χ2-test, Edwards' test as well as some frequently used newer methods (e.g. the peak-low ratio. It also introduces a new indicator of the intensity of monthly variations in suicides (the magnitude of trimester variations of /12/ moving consecutive months index - the MtMV index. Seasonality of suicides is also observed by sex. Results: The results of the research of seasonality confirm that certain cyclical variations in mortality due to suicide are also present in Serbia. Observed by season, suicides are most frequent in spring and summer and less in winter. The cyclical nature was also clearly confirmed by month. Suicides are most frequent in "warm" months (April-August and far less frequent in "cold" months (December-February. By month, suicides are most frequent in May, while the maximal average number of suicides per day was calculated for June (21 % higher than the average for 1990-2012. December is singled out as the month with the lowest number as well as lowest daily average of suicides (25 % lower than the average. Conclusion: The cyclical nature of suicides is clearly notable during the entire observed period and no significant fluctuations or decrease in the intensity of the variation were observed. Regardless of the method of analysis, the resulting conclusions are identical

Seasonality of selected surface water constituents in the Indian River Lagoon, Florida.

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Qian, Y; Migliaccio, K W; Wan, Y; Li, Y C; Chin, D

2007-01-01

Seasonality is often the major exogenous effect that must be compensated for or removed to discern trends in water quality. Our objective was to provide a methodological example of trend analysis using water quality data with seasonality. Selected water quality constituents from 1979 to 2004 at three monitoring stations in southern Florida were evaluated for seasonality. The seasonal patterns of flow-weighted and log-transformed concentrations were identified by applying side-by-side boxplots and the Wilcoxon signed-rank test (p turbidity, color, and chloride), except for turbidity at Station C24S49, exhibited significant seasonal patterns. Almost all nutrient species (NO(2)-N, NH(4)-N, total Kjeldahl N, PO(4)-P, and total P) had an identical seasonal pattern of concentrations significantly greater in the wet than in the dry season. Some water quality constituents were observed to exhibit significant annual or seasonal trends. In some cases, the overall annual trend was insignificant while opposing trends were present in different seasons. By evaluating seasonal trends separately from all data, constituents can be assessed providing a more accurate interpretation of water quality trends.

Seasonal variation in the intensity of movements by the estuarine dolphin, Sotalia guianensis (Cetacea: Delphinidae, in the North Bay, Santa Catarina Island

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Paulo César Simões-Lopes

2004-05-01

Full Text Available The resident population of estuarine dolphins (Sotalia guianensis in the North Bay, Santa Catarina Island, southern Brazil, was studied from September 2001 until July 2003 through periodical boat surveys. Using focal-group and sequential sampling, information such as geographical position and behavioral patterns were registered at 5-minute intervals. All the information collected was insert in a GIS database of the study area. Since patterns of seasonal variation concerning home range and behavior had been established in previous work, we aimed at evaluating the existence of seasonal intensity of movements, therefore strengthening the proposed hypothesis of higher spatial requirements when food resources are low. The daily mean speed of the dolphin’s group was used as an index of the intensity of movements, and its seasonal variation throughout the study period was analyzed. We found a statistically significant seasonal variation in the intensity of movement. The dolphins tended to move more in the cold seasons, in contrast with the hot seasons when the dolphins tended to move less. Thus, previous studies are corroborated, supporting the hypothesis og higher spatial requirements when there are fewer food resources.

A statistical analysis of the body condition of cows from two veterinary stations in Zimbabwe

International Nuclear Information System (INIS)

Saporu, F.W.O.

2003-12-01

The improvement of livestock production is important for Zimbabwe's agriculturally base economy. This paper examines the relationship between the body condition and metabolic parameters of female cows, for the better understanding of traditional livestock farming in Zimbabwe. The data analysed are part of the baseline data on the improvement of livestock production, collected from two sites Chinamora and Bulawayo. Body condition is indexed by body score. Thirty-five variables are examined. The variable selection method employed is stepwise regression. Regression model assumptions of normality and independent observations are checked using normal probability plot and Durbin-Watson statistics for autocorrelation of residuals. Collinearity and outlier problems are examined using eigenanalysis and influence statistics. The effect of some factors, such as, site, which relates to livestock management, parity and season, categorized by the quality of forage available for grazing, are also studied. The data are analysed using SAS statistical package on a Personal Computer. The results show that only about four variables substantially influence the relationship in each of the two sites considered. For the better managed site, Bulawayo, these are PCV, Calcium and WBC. Strongyles, Progesterone Level, Phosphate and HB are obtained in Chinamora. Negative correlation coefficient corresponds to strongyles only. That is, the effect of stronglyes is to reduce the value of bodyscore. For other variables, an improvement in their respective values will bring about improved body condition. Site difference is identified as a factor affecting the relationship. This emphasizes the role of good management in livestock production. Parity and season are also identified. Only two interactions are significant; site-season and a progesterone level-season interaction. The latter is obtained only in Chinamora site and it can be deduced that the cyclic cows are exposed to the risk of loosing their

Application of seasonal rainfall forecasts and satellite rainfall observations to crop yield forecasting for Africa

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Greatrex, H. L.; Grimes, D. I. F.; Wheeler, T. R.

2009-04-01

Rain-fed agriculture is of utmost importance in sub-Saharan Africa; the FAO estimates that over 90% of food consumed in the region is grown in rain-fed farming systems. As the climate in sub-Saharan Africa has a high interannual variability, this dependence on rainfall can leave communities extremely vulnerable to food shortages, especially when coupled with a lack of crop management options. The ability to make a regional forecast of crop yield on a timescale of months would be of enormous benefit; it would enable both governmental and non-governmental organisations to be alerted in advance to crop failure and could facilitate national and regional economic planning. Such a system would also enable individual communities to make more informed crop management decisions, increasing their resilience to climate variability and change. It should be noted that the majority of crops in the region are rainfall limited, therefore the ability to create a seasonal crop forecast depends on the ability to forecast rainfall at a monthly or seasonal timescale and to temporally downscale this to a daily time-series of rainfall. The aim of this project is to develop a regional-scale seasonal forecast for sub-Saharan crops, utilising the General Large Area Model for annual crops (GLAM). GLAM would initially be driven using both dynamical and statistical seasonal rainfall forecasts to provide an initial estimate of crop yield. The system would then be continuously updated throughout the season by replacing the seasonal rainfall forecast with daily weather observations. TAMSAT satellite rainfall estimates are used rather than rain-gauge data due to the scarcity of ground based observations. An important feature of the system is the use of the geo-statistical method of sequential simulation to create an ensemble of daily weather inputs from both the statistical seasonal rainfall forecasts and the satellite rainfall estimates. This allows a range of possible yield outputs to be

Regional seasonal warming anomalies and land-surface feedbacks

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Coffel, E.; Horton, R. M.

2017-12-01

Significant seasonal variations in warming are projected in some regions, especially central Europe, the southeastern U.S., and central South America. Europe in particular may experience up to 2°C more warming during June, July, and August than in the annual mean, enhancing the risk of extreme summertime heat. Previous research has shown that heat waves in Europe and other regions are tied to seasonal soil moisture variations, and that in general land-surface feedbacks have a strong effect on seasonal temperature anomalies. In this study, we show that the seasonal anomalies in warming are also due in part to land-surface feedbacks. We find that in regions with amplified warming during the hot season, surface soil moisture levels generally decline and Bowen ratios increase as a result of a preferential partitioning of incoming energy into sensible vs. latent. The CMIP5 model suite shows significant variability in the strength of land-atmosphere coupling and in projections of future precipitation and soil moisture. Due to the dependence of seasonal warming on land-surface processes, these inter-model variations influence the projected summertime warming amplification and contribute to the uncertainty in projections of future extreme heat.

Variation of microorganism concentrations in urban stormwater runoff with land use and seasons.

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Selvakumar, Ariamalar; Borst, Michael

2006-03-01

Stormwater runoff samples were collected from outfalls draining small municipal separate storm sewer systems. The samples were collected from three different land use areas based on local designation (high-density residential, low-density residential and landscaped commercial). The concentrations of microorganisms in the stormwater runoff were found to be similar in magnitude to, but less variable than, those reported in the stormwater National Pollutant Discharge Elimination System (NPDES) database. Microorganism concentrations from high-density residential areas were higher than those associated with low-density residential and landscaped commercial areas. Since the outfalls were free of sanitary wastewater cross-connections, the major sources of microorganisms to the stormwater runoff were most likely from the feces of domestic animals and wildlife. Concentrations of microorganisms were significantly affected by the season during which the samples were collected. The lowest concentrations were observed during winter except for Staphylococcus aureus. The Pearson correlation coefficients among different indicators showed weak linear relationships and the relationships were statistically significant. However, the relationships between indicators and pathogens were poorly correlated and were not statistically significant, suggesting the use of indicators as evidence of the presence of pathogens is not appropriate. Further, the correlation between the concentration of the traditionally monitored indicators (total coliforms and fecal coliforms) and the suggested substitutes (enterococci and E. coli) is weak, but statistically significant, suggesting that historical time series will be only a qualitative indicator of impaired waters under the revised criteria for recreational water quality by the US EPA.

Seasonal forecasting of discharge for the Raccoon River, Iowa

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Slater, Louise; Villarini, Gabriele; Bradley, Allen; Vecchi, Gabriel

2016-04-01

The state of Iowa (central United States) is regularly afflicted by severe natural hazards such as the 2008/2013 floods and the 2012 drought. To improve preparedness for these catastrophic events and allow Iowans to make more informed decisions about the most suitable water management strategies, we have developed a framework for medium to long range probabilistic seasonal streamflow forecasting for the Raccoon River at Van Meter, a 8900-km2 catchment located in central-western Iowa. Our flow forecasts use statistical models to predict seasonal discharge for low to high flows, with lead forecasting times ranging from one to ten months. Historical measurements of daily discharge are obtained from the U.S. Geological Survey (USGS) at the Van Meter stream gage, and used to compute quantile time series from minimum to maximum seasonal flow. The model is forced with basin-averaged total seasonal precipitation records from the PRISM Climate Group and annual row crop production acreage from the U.S. Department of Agriculture's National Agricultural Statistics Services database. For the forecasts, we use corn and soybean production from the previous year (persistence forecast) as a proxy for the impacts of agricultural practices on streamflow. The monthly precipitation forecasts are provided by eight Global Climate Models (GCMs) from the North American Multi-Model Ensemble (NMME), with lead times ranging from 0.5 to 11.5 months, and a resolution of 1 decimal degree. Additionally, precipitation from the month preceding each season is used to characterize antecedent soil moisture conditions. The accuracy of our modelled (1927-2015) and forecasted (2001-2015) discharge values is assessed by comparison with the observed USGS data. We explore the sensitivity of forecast skill over the full range of lead times, flow quantiles, forecast seasons, and with each GCM. Forecast skill is also examined using different formulations of the statistical models, as well as NMME forecast

Seasonal precipitation extreme indices in mainland Portugal: trends and variability in the period 1941-2007

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Santo, Fátima E.; Ramos, Alexandre M.; de Lima, M. Isabel P.; Trigo, Ricardo M.

2013-04-01

Changes in the precipitation regimes are expected to be accompanied by variations in the occurrence of extreme events, which in turn could be related to low frequency variability. The impact on the society and environment requires that the regional specificities are understood. For mainland Portugal, this work reports the results of the analysis of trends in selected precipitation indices calculated from daily precipitation data from 57 meteorological stations, recorded in the period 1941-2007; additionally we have also investigated the correlations between these indices and several modes of low frequency variability over the area. We focus on exploring regional differences and seasonal variations in the intensity, frequency and duration of extreme precipitation events. The precipitation indices were assessed at the seasonal scale and calculated at both the station and regional scales. Results sometimes highlight marked changes in seasonal precipitation and show that: i) trends in spring and autumn have opposite signals: statistically significant drying trends in the spring are accompanied by a reduction in precipitation extremes; in autumn, wetting trends are detected for all precipitation indices, although overall they are not significant at the 5% level; ii) there seems to be a tendency for a reduction in the duration of the rainy season; iii) the North Atlantic Oscillation (NAO) is the mode of variability that has the highest influence on precipitation extremes over mainland Portugal, particularly in the winter and autumn, and is one of the most important teleconnection patterns in all seasons. This work was partially supported by FEDER (Fundo Europeu de Desenvolvimento Regional) funds through the COMPETE (Programa Operacional Factores de Competitividade) and by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) through project STORMEx FCOMP-01-0124-FEDER-019524 (PTDC/AAC-CLI/121339/2010).

Statistical forecast of seasonal discharge in Central Asia using observational records: development of a generic linear modelling tool for operational water resource management

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Apel, Heiko; Abdykerimova, Zharkinay; Agalhanova, Marina; Baimaganbetov, Azamat; Gavrilenko, Nadejda; Gerlitz, Lars; Kalashnikova, Olga; Unger-Shayesteh, Katy; Vorogushyn, Sergiy; Gafurov, Abror

2018-04-01

The semi-arid regions of Central Asia crucially depend on the water resources supplied by the mountainous areas of the Tien Shan and Pamir and Altai mountains. During the summer months the snow-melt- and glacier-melt-dominated river discharge originating in the mountains provides the main water resource available for agricultural production, but also for storage in reservoirs for energy generation during the winter months. Thus a reliable seasonal forecast of the water resources is crucial for sustainable management and planning of water resources. In fact, seasonal forecasts are mandatory tasks of all national hydro-meteorological services in the region. In order to support the operational seasonal forecast procedures of hydro-meteorological services, this study aims to develop a generic tool for deriving statistical forecast models of seasonal river discharge based solely on observational records. The generic model structure is kept as simple as possible in order to be driven by meteorological and hydrological data readily available at the hydro-meteorological services, and to be applicable for all catchments in the region. As snow melt dominates summer runoff, the main meteorological predictors for the forecast models are monthly values of winter precipitation and temperature, satellite-based snow cover data, and antecedent discharge. This basic predictor set was further extended by multi-monthly means of the individual predictors, as well as composites of the predictors. Forecast models are derived based on these predictors as linear combinations of up to four predictors. A user-selectable number of the best models is extracted automatically by the developed model fitting algorithm, which includes a test for robustness by a leave-one-out cross-validation. Based on the cross-validation the predictive uncertainty was quantified for every prediction model. Forecasts of the mean seasonal discharge of the period April to September are derived every month from

Statistical forecast of seasonal discharge in Central Asia using observational records: development of a generic linear modelling tool for operational water resource management

Directory of Open Access Journals (Sweden)

H. Apel

2018-04-01

Full Text Available The semi-arid regions of Central Asia crucially depend on the water resources supplied by the mountainous areas of the Tien Shan and Pamir and Altai mountains. During the summer months the snow-melt- and glacier-melt-dominated river discharge originating in the mountains provides the main water resource available for agricultural production, but also for storage in reservoirs for energy generation during the winter months. Thus a reliable seasonal forecast of the water resources is crucial for sustainable management and planning of water resources. In fact, seasonal forecasts are mandatory tasks of all national hydro-meteorological services in the region. In order to support the operational seasonal forecast procedures of hydro-meteorological services, this study aims to develop a generic tool for deriving statistical forecast models of seasonal river discharge based solely on observational records. The generic model structure is kept as simple as possible in order to be driven by meteorological and hydrological data readily available at the hydro-meteorological services, and to be applicable for all catchments in the region. As snow melt dominates summer runoff, the main meteorological predictors for the forecast models are monthly values of winter precipitation and temperature, satellite-based snow cover data, and antecedent discharge. This basic predictor set was further extended by multi-monthly means of the individual predictors, as well as composites of the predictors. Forecast models are derived based on these predictors as linear combinations of up to four predictors. A user-selectable number of the best models is extracted automatically by the developed model fitting algorithm, which includes a test for robustness by a leave-one-out cross-validation. Based on the cross-validation the predictive uncertainty was quantified for every prediction model. Forecasts of the mean seasonal discharge of the period April to September are derived

Factors influencing medical informatics examination grade--can biorhythm, astrological sign, seasonal aspect, or bad statistics predict outcome?

Science.gov (United States)

Petrovecki, Mladen; Rahelić, Dario; Bilić-Zulle, Lidija; Jelec, Vjekoslav

2003-02-01

To investigate whether and to what extent various parameters, such as individual characteristics, computer habits, situational factors, and pseudoscientific variables, influence Medical Informatics examination grade, and how inadequate statistical analysis can lead to wrong conclusions. The study included a total of 382 second-year undergraduate students at the Rijeka University School of Medicine in the period from 1996/97 to 2000/01 academic year. After passing the Medical Informatics exam, students filled out an anonymous questionnaire about their attitude toward learning medical informatics. They were asked to grade the course organization and curriculum content, and provide their date of birth; sex; study year; high school grades; Medical Informatics examination grade, type, and term; and describe their computer habits. From these data, we determined their zodiac signs and biorhythm. Data were compared by the use of t-test, one-way ANOVA with Tukey's honest significance difference test, and randomized complete block design ANOVA. Out of 21 variables analyzed, only 10 correlated with the average grade. Students taking Medical Informatics examination in the 1998/99 academic year earned lower average grade than any other generation. Significantly higher Medical Informatics exam grade was earned by students who finished a grammar high school; owned and regularly used a computer, Internet, and e-mail (pzodiac sign, zodiac sign quality, or biorhythm cycles, except when intentionally inadequate statistics was used for data analysis. Medical Informatics examination grades correlated with general learning capacity and computer habits of students, but showed no relation to other investigated parameters, such as examination term or pseudoscientific parameters. Inadequate statistical analysis can always confirm false conclusions.

Impacts of Land Cover and Seasonal Variation on Maximum Air Temperature Estimation Using MODIS Imagery

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Yulin Cai

2017-03-01

Full Text Available Daily maximum surface air temperature (Tamax is a crucial factor for understanding complex land surface processes under rapid climate change. Remote detection of Tamax has widely relied on the empirical relationship between air temperature and land surface temperature (LST, a product derived from remote sensing. However, little is known about how such a relationship is affected by the high heterogeneity in landscapes and dynamics in seasonality. This study aims to advance our understanding of the roles of land cover and seasonal variation in the estimation of Tamax using the MODIS (Moderate Resolution Imaging Spectroradiometer LST product. We developed statistical models to link Tamax and LST in the middle and lower reaches of the Yangtze River in China for five major land-cover types (i.e., forest, shrub, water, impervious surface, cropland, and grassland and two seasons (i.e., growing season and non-growing season. Results show that the performance of modeling the Tamax-LST relationship was highly dependent on land cover and seasonal variation. Estimating Tamax over grasslands and water bodies achieved superior performance; while uncertainties were high over forested lands that contained extensive heterogeneity in species types, plant structure, and topography. We further found that all the land-cover specific models developed for the plant non-growing season outperformed the corresponding models developed for the growing season. Discrepancies in model performance mainly occurred in the vegetated areas (forest, cropland, and shrub, suggesting an important role of plant phenology in defining the statistical relationship between Tamax and LST. For impervious surfaces, the challenge of capturing the high spatial heterogeneity in urban settings using the low-resolution MODIS data made Tamax estimation a difficult task, which was especially true in the growing season.

Seasonal adjustment methods and real time trend-cycle estimation

CERN Document Server

Bee Dagum, Estela

2016-01-01

This book explores widely used seasonal adjustment methods and recent developments in real time trend-cycle estimation. It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATS and STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate each method and real data examples can be followed throughout the text. The trend-cycle estimation is presented using nonparametric techniques based on moving averages, linear filters and reproducing kernel Hilbert spaces, taking recent advances into account. The book provides a systematical treatment of results that to date have been scattered throughout the literature. Seasonal adjustment and real time trend-cycle prediction play an essential part at all levels of activity in modern economies. They are used by governments to counteract cyclical recessions, by central banks to control inflation, by decision makers for better modeling and planning and by hospitals, manufacturers, builders, transportat...

Evaluation of physiological and biochemical responses in different seasons in Surti buffaloes

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Sandhya S. Chaudhary

2015-06-01

Full Text Available Aim: This study was conducted to evaluate the impact of hot dry, hot humid and comfortable season on physiological, hematological, biochemical, and oxidative stress parameters in Surti buffaloes. Materials and Methods: Ten lactating Surti buffaloes of similar physiological status were selected. Based on the temperature-humidity index (THI, their natural exposure to the environment was categorized as hot dry (THI1, hot humid (THI2 and moderate winter/comfort season (THI3. Blood/serum samples were collected and analyzed for physiological, hematological, biochemical, and oxidative stress parameters. The results were analyzed using standard statistical methods. Results: With increase in THI, significant rise in physiological parameters such as respiration rate (RR, hematological parameters such as red blood cell (RBC, hematocrit, hemoglobin (Hb and mean cell Hb concentration (MCHC, biochemical parameters such as alanine aminotransferase (ALT, Na, K, creatinine, blood urea nitrogen, Mn, Cu and Zn, hormones such as cortisol and oxidative stress parameters such as glutathione peroxidase (GPx, superoxide dismutase (SOD, lipid peroxide (LPO and total antioxidant status (TAS and significant decline in glucose, cholesterol and triiodothyronine (T3 was observed. Conclusion: It was concluded that THI is a sensitive indicator of heat stress and is impacted by ambient temperature more than the relative humidity in buffaloes. Higher THI is associated with significantly increased RR, total RBC count, Hb, hematocrit, MCHC, ALT, urea, sodium, creatinine, triiodothyronine, SOD, GPx, LPO and TAS and with significant decrease in glucose, cholesterol and triiodothyronine (T3.

[Seasonal distribution of clinical case codes (DOC study)].

Science.gov (United States)

von Dercks, N; Melz, R; Hepp, P; Theopold, J; Marquass, B; Josten, C

2017-02-01

The German diagnosis-related groups remuneration system (G-DRG) was implemented in 2004 and patient-related diagnoses and procedures lead to allocation to specific DRGs. This system includes several codes, such as case mix (CM), case mix index (CMI) and number of cases. Seasonal distribution of these codes as well as distribution of diagnoses and DRGs may lead to logistical consequences for clinical management. From 2004 to 2013 all the main diagnoses and DRGs for inpatients were recorded. Monthly and seasonal distributions were analyzed using ANOVA. The average monthly number of cases was 265 ± 25 cases, the average CM was 388.50 ± 51.75 and the average CMI was 1.46 ± 0.15 with no significant seasonal differences (p > 0.1). Concussion was the most frequently occurring main diagnosis (3739 cases) followed by fractures of the humeral head (699). Significant distribution differences could be shown for humeral head fractures in monthly (p = 0.018) and seasonal comparisons (p = 0.006) with a maximum in winter. Radius (p = 0.01) and ankle fractures (p ≤ 0.001) also occurred most frequently in winter. Non-bony lesions of the shoulder were significantly less in spring (p = 0.04). The DRGs showed no evidence of a monthly or seasonal clustering (p > 0.1). The significant clustering of injuries in specific months and seasons should lead to logistic consequences (e.g. operating room slots, availability of nursing and anesthesia staff). For a needs assessment the analysis of main diagnoses is more appropriate than DRGs.

An application of seasonal ARIMA models on group commodities to forecast Philippine merchandise exports performance

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Natividad, Gina May R.; Cawiding, Olive R.; Addawe, Rizavel C.

2017-11-01

The increase in the merchandise exports of the country offers information about the Philippines' trading role within the global economy. Merchandise exports statistics are used to monitor the country's overall production that is consumed overseas. This paper investigates the comparison between two models obtained by a) clustering the commodity groups into two based on its proportional contribution to the total exports, and b) treating only the total exports. Different seasonal autoregressive integrated moving average (SARIMA) models were then developed for the clustered commodities and for the total exports based on the monthly merchandise exports of the Philippines from 2011 to 2016. The data set used in this study was retrieved from the Philippine Statistics Authority (PSA) which is the central statistical authority in the country responsible for primary data collection. A test for significance of the difference between means at 0.05 level of significance was then performed on the forecasts produced. The result indicates that there is a significant difference between the mean of the forecasts of the two models. Moreover, upon a comparison of the root mean square error (RMSE) and mean absolute error (MAE) of the models, it was found that the models used for the clustered groups outperform the model for the total exports.

Seasonal variation and solar activity dependence of the quiet-time ionospheric trough

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Ishida, T.; Ogawa, Y.; Kadokura, A.; Hiraki, Y.; Häggström, I.

2014-08-01

We have conducted a statistical analysis of the ionospheric F region trough, focusing on its seasonal variation and solar activity dependence under geomagnetically quiet and moderate conditions, using plasma parameter data obtained via Common Program 3 observations performed by the European Incoherent Scatter (EISCAT) radar between 1982 and 2011. We have confirmed that there is a major difference in frictional heating between the high- and low-latitude sides of the EISCAT field of view (FOV) at ~73°0'N-60°5'N (geomagnetic latitude) at an altitude of 325 km, which is associated with trough formation. Our statistical results show that the high-latitude and midlatitude troughs occur on the high- and low-latitude sides of the FOV, respectively. Seasonal variations indicate that dissociative recombination accompanied by frictional heating is a main cause of trough formation in sunlit regions. During summer, therefore, the occurrence rate is maintained at 80-90% in the postmidnight high-latitude region owing to frictional heating by eastward return flow. Solar activity dependence on trough formation indicates that field-aligned currents modulate the occurrence rate of the trough during the winter and equinox seasons. In addition, the trough becomes deeper via dissociative recombination caused by an increased ion temperature with F10.7, at least in the equinox and summer seasons but not in winter.

A study on seasonal variation of skin parameters in Korean males.

Science.gov (United States)

Song, E J; Lee, J A; Park, J J; Kim, H J; Kim, N S; Byun, K S; Choi, G S; Moon, T K

2015-02-01

The physiological characteristics of the skin are varied greatly, depending on gender, age, region and race, and many dermatologic researches have been performed through various research methods. This study aimed to examine how Korean men's skin conditions were influenced by temperature or humidity changes caused by seasonal rotations. A total of 100 healthy Korean men, age range 20-59 years, participated in the study for both summer and winter. We compared on the characteristics of skin between summer and winter. The skin hydration, skin pH and TEWL were evaluated on the forehead, cheek and forearm. The skin sebum content of the glabella, nasal ala and cheek was measured using Sebumeter(®) (SM810, Courage+Khazaka, Germany). Cutometer(®) (MPA 580 Courage+Khazaka, Germany) the elasticity was measured by on the cheeks, and PRIMOS lite(®) (Phase shift Rapid in vivo Measurement of Skin, GFMesstechnik GmbH, Germany) was used to evaluate wrinkles on crow's feet. Lastly, in addition, the skin pore of the face was measured using the Janus(®) (PSI, Korea) which is a facial analysis system. The results were as follows: the comparison of hydration in summer and winter shows significant differences in their forehead, cheeks and forearm. The pH values of the skin surface were generally higher in winter, and significantly different on each site, and the sebum content was higher in summer than in winter. As a result of the pore measurement, the summer showed more pores compared to the winter, and there was a statistically significant difference in skin pores between summer and winter. The sensitivity measured by stinging test increases significantly more in winter than in summer. However, there were no seasonal differences in wrinkles and skin brightness. The skin surface pH, TEWL, sebum content, hydration, elasticity, wrinkles, skin pore and skin sensitivity vary with seasons and body regions in Korean men. © 2014 Society of Cosmetic Scientists and the Société Fran

Analyzing seasonality of tuberculosis across Indian states and union territories

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Pankaj Narula

2015-12-01

Full Text Available A significant seasonal variation in tuberculosis (TB is observed in north India during 2006–2011, particularly in states like Himachal Pradesh, Haryana and Rajasthan. To quantify the seasonal variation, we measure average amplitude (peak to trough distance across seasons in smear positive cases of TB and observe that it is maximum for Himachal Pradesh (40.01% and minimum for Maharashtra (3.87%. In north India, smear positive cases peak in second quarter (April–June and reach a trough in fourth quarter (October–December, however low seasonal variation is observed in southern region of the country. The significant correlations as 0.64 (p-value < 0.001, 0.54 (p-value < 0.01 and 0.42 (p-value < 0.05 are observed between minimum temperature and seasonality of TB at lag-1 in north, central and northeast India respectively. However, in south India, this correlation is not significant.

Seasonal variation of diclofenac concentration and its relation with wastewater characteristics at two municipal wastewater treatment plants in Turkey.

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Sari, Sevgi; Ozdemir, Gamze; Yangin-Gomec, Cigdem; Zengin, Gulsum Emel; Topuz, Emel; Aydin, Egemen; Pehlivanoglu-Mantas, Elif; Okutman Tas, Didem

2014-05-15

The pharmaceutically active compound diclofenac has been monitored during one year at separate treatment units of two municipal wastewater treatment plants (WWTPs) to evaluate its seasonal variation and the removal efficiency. Conventional wastewater characterization was also performed to assess the possible relationship between conventional parameters and diclofenac. Diclofenac concentrations in the influent and effluent of both WWTPs were detected in the range of 295-1376 and 119-1012ng/L, respectively. Results indicated that the higher diclofenac removal efficiency was observed in summer season in both WWTPs. Although a consistency in diclofenac removal was observed in WWTP_1, significant fluctuation was observed at WWTP_2 based on seasonal evaluation. The main removal mechanism of diclofenac in the WWTPs was most often biological (55%), followed by UV disinfection (27%). When diclofenac removal was evaluated in terms of the treatment units in WWTPs, a significant increase was achieved at the treatment plant including UV disinfection unit. Based on the statistical analysis, higher correlation was observed between diclofenac and suspended solids concentrations among conventional parameters in the influent whereas the removal of diclofenac was highly correlated with nitrogen removal efficiency. Copyright © 2014 Elsevier B.V. All rights reserved.

Influence of season, age and management on scrotal thermal profile in Murrah bulls using scrotal infrared digital thermography

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Ahirwar, Maneesh Kumar; Kataktalware, Mukund Amritrao; Ramesha, Kerekoppa Puttaiah; Pushpadass, Heartwin Amaladhas; Jeyakumar, Sakthivel; Revanasiddu, Deginal; Kour, Reen Jagish; Nath, Sapna; Nagaleekar, Anand Kumar; Nazar, Sayyad

2017-12-01

The aim of the present study was to examine the effects of non-genetic factors on scrotal thermographic profile viz., proximal pole temperature (PPT °C), mid pole temperature (MPT °C), distal pole temperature (DPT °C) and ocular temperature (OcT) of Murrah ( Bubalus bubalis) breeding bulls. A total of 109 buffalo bulls, maintained at three semen stations (SS), were monitored for scrotal surface and ocular temperatures using infrared thermography twice daily during rainy, winter and summer seasons using an FLIR i5 infrared camera and temperatures were measured. Thermograms were analysed by FLIR QuickReport v.1.2 SP2 software. Statistical analysis revealed that semen station, season, temperature humidity index (THI), housing system and timing of observations had significant ( P 80.88; system and timing of observations had a significant influence on scrotal surface temperature. The monitoring of scrotal surface temperature by infrared thermography was found to be useful in evaluating the effects of thermal stress on physiology and health of buffalo bulls.

Eddies in the Red Sea: A statistical and dynamical study

KAUST Repository

Zhan, Peng

2014-06-01

Sea level anomaly (SLA) data spanning 1992–2012 were analyzed to study the statistical properties of eddies in the Red Sea. An algorithm that identifies winding angles was employed to detect 4998 eddies propagating along 938 unique eddy tracks. Statistics suggest that eddies are generated across the entire Red Sea but that they are prevalent in certain regions. A high number of eddies is found in the central basin between 18°N and 24°N. More than 87% of the detected eddies have a radius ranging from 50 to 135 km. Both the intensity and relative vorticity scale of these eddies decrease as the eddy radii increase. The averaged eddy lifespan is approximately 6 weeks. AEs and cyclonic eddies (CEs) have different deformation features, and those with stronger intensities are less deformed and more circular. Analysis of long-lived eddies suggests that they are likely to appear in the central basin with AEs tending to move northward. In addition, their eddy kinetic energy (EKE) increases gradually throughout their lifespans. The annual cycles of CEs and AEs differ, although both exhibit significant seasonal cycles of intensity with the winter and summer peaks appearing in February and August, respectively. The seasonal cycle of EKE is negatively correlated with stratification but positively correlated with vertical shear of horizontal velocity and eddy growth rate, suggesting that the generation of baroclinic instability is responsible for the activities of eddies in the Red Sea.

Enhancing Seasonal Water Outlooks: Needs and Opportunities in the Critical Runoff Season

Science.gov (United States)

Ray, A. J.; Barsugli, J. J.; Yocum, H.; Stokes, M.; Miskus, D.

2017-12-01

The runoff season is a critical period for the management of water supply in the western U.S., where in many places over 70% of the annual runoff occurs in the snowmelt period. Managing not only the volume, but the intra-seasonal timing of the runoff is important for optimizing storage, as well as achieving other goals such as mitigating flood risk, and providing peak flows for riparian habitat management, for example, for endangered species. Western river forecast centers produce volume forecasts for western reservoirs that are key input into many water supply decisions, and also short term river forecasts out to 10 days. The early volume forecasts each year typically begin in December, and are updated throughout the winter and into the runoff season (April-July for many areas, but varies). This presentation will discuss opportunities for enhancing this existing suite of RFC water outlooks, including the needs for and potential use for "intraseasonal" products beyond those provided by the Ensemble Streamflow Prediction system and the volume forecasts. While precipitation outlooks have little skill for many areas and seasons, and may not contribute significantly to the outlook, late winter and spring temperature forecasts have meaningful skill in certain areas and sub-seasonal to seasonal time scales. This current skill in CPC temperature outlooks is an opportunity to translate these products into information about the snowpack and potential runoff timing, even where the skill in precipitation is low. Temperature is important for whether precipitation falls as snow or rain, which is critical for streamflow forecasts, especially in the melt season in snowpack-dependent watersheds. There is a need for better outlooks of the evolution of snowpack, conditions influencing the April-July runoff, and the timing of spring peak or shape of the spring hydrograph. The presentation will also discuss a our work with stakeholders of the River Forecast Centers and the NIDIS

Modeling seasonality: An extension of the HEGY approach in the presence of two structural breaks

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Tasseven Ozlem

2008-01-01

Full Text Available In this paper the HEGY testing procedure (Hylleberg et al. 1990 of analyzing seasonal unit roots is tried to be re-examined by allowing for seasonal mean shifts with exogenous break points. Using some Monte Carlo experiments the distribution of the HEGY and the extended HEGY tests for seasonal unit roots subject to mean shifts and the small sample behavior of the test statistics have been investigated. Based on an empirical analysis upon the conventional money demand relationships in the Turkish economy, our results indicate that seasonal unit roots appear for the GDP deflator, real M2 and the expected inflation variables while seasonal unit roots at annual frequency seem to be disappear for the real M1 balances when the possible structural changes in one or more seasons at 1994 and 2001 crisis years have been taken into account. .

Seasonal predictability of Kiremt rainfall in coupled general circulation models

Science.gov (United States)

Gleixner, Stephanie; Keenlyside, Noel S.; Demissie, Teferi D.; Counillon, François; Wang, Yiguo; Viste, Ellen

2017-11-01

The Ethiopian economy and population is strongly dependent on rainfall. Operational seasonal predictions for the main rainy season (Kiremt, June-September) are based on statistical approaches with Pacific sea surface temperatures (SST) as the main predictor. Here we analyse dynamical predictions from 11 coupled general circulation models for the Kiremt seasons from 1985-2005 with the forecasts starting from the beginning of May. We find skillful predictions from three of the 11 models, but no model beats a simple linear prediction model based on the predicted Niño3.4 indices. The skill of the individual models for dynamically predicting Kiremt rainfall depends on the strength of the teleconnection between Kiremt rainfall and concurrent Pacific SST in the models. Models that do not simulate this teleconnection fail to capture the observed relationship between Kiremt rainfall and the large-scale Walker circulation.

Sigsearch: a new term for post hoc unplanned search for statistically significant relationships with the intent to create publishable findings.

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Hashim, Muhammad Jawad

2010-09-01

Post-hoc secondary data analysis with no prespecified hypotheses has been discouraged by textbook authors and journal editors alike. Unfortunately no single term describes this phenomenon succinctly. I would like to coin the term "sigsearch" to define this practice and bring it within the teaching lexicon of statistics courses. Sigsearch would include any unplanned, post-hoc search for statistical significance using multiple comparisons of subgroups. It would also include data analysis with outcomes other than the prespecified primary outcome measure of a study as well as secondary data analyses of earlier research.

Association between the Brain Laterality, Gender and Birth Season

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A Baghdasarians

2008-08-01

Full Text Available Objective: in recent years different hypotheses with respect to the formation of cerebral laterality were proposed. Some of the researchers claim that cerebral dominance and laterality are determined by genetic factors, just as the case with eye color and blood type. However, another group states that in addition to genetic factors, environmental factors, too, have a remarkable role in hemispheric dominance and lateral dominance. Hence, the present research was designed to study the relationship between 1- lateral dominance and birth season 2- lateral dominance and gender. "n "nMethod:1355(girls and boys fifth graders from the 19 educational regions of Tehran were selected using multi stage cluster sampling in the 2003-2004 school year. Coren lateral preference and personal information questionnaire were applied. "nResults:The following results were obtained at the level of ل=0.05 and probability of 95%. There were significant association between lateral dominance and birth season, between lateral dominance and gender, between ambidexterity and birth season, between non-genetic sinistrality and birth season, between dexterality and gender, between ambidexterity and gender, between genetic sinistrality and gender. There were no significant associations between dexterality and birth season, genetic sinistrality and birth season, between non-genetic sinistrality and gender. "nConclusion: The gestational environmental factors can have significant effect on the formation of lateral dominance and cerebral laterality.

Numerical and Qualitative Contrasts of Two Statistical Models for Water Quality Change in Tidal Waters

Science.gov (United States)

Two statistical approaches, weighted regression on time, discharge, and season and generalized additive models, have recently been used to evaluate water quality trends in estuaries. Both models have been used in similar contexts despite differences in statistical foundations and...

Ajustement statistique des simulations climatiques : l'exemple des précipitations saisonnières de l'Amérique tropicaleStatistical adjustment of simulated climate: example of seasonal rainfall of tropical America.

Science.gov (United States)

Moron, Vincent; Navarra, Antonio

2000-05-01

This study presents the skill of the seasonal rainfall of tropical America from an ensemble of three 34-year general circulation model (ECHAM 4) simulations forced with observed sea surface temperature between 1961 and 1994. The skill gives a first idea of the amount of potential predictability if the sea surface temperatures are perfectly known some time in advance. We use statistical post-processing based on the leading modes (extracted from Singular Value Decomposition of the covariance matrix between observed and simulated rainfall fields) to improve the raw skill obtained by simple comparison between observations and simulations. It is shown that 36-55 % of the observed seasonal variability is explained by the simulations on a regional basis. Skill is greatest for Brazilian Nordeste (March-May), but also for northern South America or the Caribbean basin in June-September or northern Amazonia in September-November for example.

Quantifying the impact of daily and seasonal variation in sap pH on xylem dissolved inorganic carbon estimates in plum trees.

Science.gov (United States)

Erda, F G; Bloemen, J; Steppe, K

2014-01-01

In studies on internal CO2 transport, average xylem sap pH (pH(x)) is one of the factors used for calculation of the concentration of dissolved inorganic carbon in the xylem sap ([CO2 *]). Lack of detailed pH(x) measurements at high temporal resolution could be a potential source of error when evaluating [CO2*] dynamics. In this experiment, we performed continuous measurements of CO2 concentration ([CO2]) and stem temperature (T(stem)), complemented with pH(x) measurements at 30-min intervals during the day at various stages of the growing season (Day of the Year (DOY): 86 (late winter), 128 (mid-spring) and 155 (early summer)) on a plum tree (Prunus domestica L. cv. Reine Claude d'Oullins). We used the recorded pH(x) to calculate [CO2*] based on T(stem) and the corresponding measured [CO2]. No statistically significant difference was found between mean [CO2*] calculated with instantaneous pH(x) and daily average pH(x). However, using an average pH(x) value from a different part of the growing season than the measurements of [CO2] and T(stem) to estimate [CO2*] led to a statistically significant error. The error varied between 3.25 ± 0.01% under-estimation and 3.97 ± 0.01% over-estimation, relative to the true [CO2*] data. Measured pH(x) did not show a significant daily variation, unlike [CO2], which increased during the day and declined at night. As the growing season progressed, daily average [CO2] (3.4%, 5.3%, 7.4%) increased and average pH(x) (5.43, 5.29, 5.20) decreased. Increase in [CO2] will increase its solubility in xylem sap according to Henry's law, and the dissociation of [CO2*] will negatively affect pH(x). Our results are the first quantifying the error in [CO2*] due to the interaction between [CO2] and pH(x) on a seasonal time scale. We found significant changes in pH(x) across the growing season, but overall the effect on the calculation of [CO2*] remained within an error range of 4%. However, it is possible that the error could be more

Seasonality in hospital admissions of Crimean-Congo hemorrhagic fever and its dependence on ambient temperature—empirical evidence from Pakistan

Science.gov (United States)

Abbas, Tariq; Xu, Zhiwei; Younus, Muhammad; Qayyum, Abdul; Riaz, Muhammad T.

2017-11-01

Crimean-Congo hemorrhagic fever (CCHF) has been reported from all provinces of Pakistan. Little is known about the seasonal variations in the disease and its association with weather conditions. In this study, we explored time-series data about monthly number of CCHF admissions (2007-2010) in three public sector hospitals of Quetta—the capital city of Baluchistan province of Pakistan. Cosinor analysis was carried out to investigate seasonality in the data. To assess the effect of average monthly ambient temperature (°C) on disease, a distributed lag nonlinear model (DLNM) was applied. Cosinor model revealed statistically significant seasonality in monthly number of CCHF patients admitted to the study hospitals. The estimated amplitude was 3.24 cases per month with phase in mid-June and low point in mid-December. DLNM confirmed nonlinear and delayed effect of temperature on hospital admissions. At a lag of 2 months, the cumulative relative risk was more than 1 at temperature at 18.37 °C and above. In addition, relative risk was significantly high at 60th (21.98 °C), 70th (24.50 °C), 80th (27.33 °C), and 90th (29.25 °C) percentiles of temperature (relative to median value, 18.37 °C). Inclusion of Eid-al-Adha as a predictor did not improve the fitness of DLNM. Based on our analysis, we concluded significant seasonality in CCHF hospital admissions. Our findings also suggested average monthly ambient temperature (°C) as a significant predictor of CCHF hospitalizations. DLNM presented in this study may be improved with inclusion of other possible time-varying predictors particularly meteorological conditions of this region.

Biodiversity and Seasonal Changes of the Microbiome in Chernozem Agroecosystem

Science.gov (United States)

Kutovaya, Olga; Chernov, Timofey; Tkhakakhova, Azida; Ivanova, Ekaterina

2016-04-01

Studies of the influence of different agricultural technologies on the soil microbiome are widespread; they are important for understanding the dependence of the microbiome on environmental and soil factors and solution of practical problems related to the control of biochemical processes in soils used in agriculture. The seasonal variability (spring-summer-autumn) of the taxonomic structure of prokaryotic microbiomes in chernozems was studied using sequencing of the 16S rRNA gene. The DNA preparation was used as the matrix for a polymerase chain reaction with the use of a pair of universal primers to the variable region V4 of the 16S rRNA gene - F515 (GTGCCAGCMGCCGCGGTAA) and R806 (GGACTACVSGGGTATCTAAT). The preparation of the samples and sequencing were made on a GS Junior. The samples were collected from the topsoil (0-20 cm) horizons of a long-term fallow and croplands differing in the rates of application of mineral fertilizers (NPK). The results of the weighted UniFrac analysis show that the microbiomes of the fallow and field were distinctly distinguished and that the type of land use significantly affected the structure of the microbial community. The most sensitive to the type of land use were the representatives of the Firmicutes, Gemmatiomonades, and Verrucomicrobia phyla. The type of vegetation and aeration of the root-dwelling soil layer seem to be key factors of this influence. The microbiomes analyzed also differed by seasons: in the autumn samples, they were closer to the spring ones than to the summer ones. This fact evidences that the seasonal differences in the microbiomes are not simple gradual temporal changes; they reflect the influence of some ecological factors transforming the phylogenetic structure of prokaryotic communities. As the seasonal shift was equally expressed in the microbiomes of the field and fallow, it is logical to assume that it was caused by the factors common for two systems of land use. Statistically sensitive to seasonal

Suicide Mortality Among Retired National Football League Players Who Played 5 or More Seasons.

Science.gov (United States)

Lehman, Everett J; Hein, Misty J; Gersic, Christine M

2016-10-01

There is current disagreement in the scientific literature about the relationship between playing football and suicide risk, particularly among professional players in the National Football League (NFL). While some research indicates players are at high risk of football-related concussions, which may lead to chronic traumatic encephalopathy and suicide, other research finds such a connection to be speculative and unsupported by methodologically sound research. To compare the suicide mortality of a cohort of NFL players to what would be expected in the general population of the United States. Cohort study; Level of evidence, 3. A cohort of 3439 NFL players with at least 5 credited playing seasons between 1959 and 1988 was assembled for statistical analysis. The vital status for this cohort was updated through 2013. Standardized mortality ratios (SMRs), the ratio of observed deaths to expected deaths, and 95% CIs were computed for the cohort; 95% CIs that excluded unity were considered statistically significant. For internal comparison purposes, standardized rate ratios were calculated to compare mortality results between players stratified into speed and nonspeed position types. Suicide among this cohort of professional football players was significantly less than would be expected in comparison with the United States population (SMR = 0.47; 95% CI, 0.24-0.82). There were no significant differences in suicide mortality between speed and nonspeed position players. There is no indication of elevated suicide risk in this cohort of professional football players with 5 or more credited seasons of play. Because of the unique nature of this cohort, these study results may not be applicable to professional football players who played fewer than 5 years or to college or high school players. © 2016 The Author(s).

Temporal distribution of gastroenteritis viruses in Ouagadougou, Burkina Faso: seasonality of rotavirus

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Nafissatou Ouedraogo

2017-03-01

Full Text Available Abstract Background Acute gastroenteritis is one of the most common diseases among children and adults, and continues to cause a major problem of public health in Burkina Faso. The temporal pattern of rotavirus, norovirus, sapovirus, astrovirus, adenovirus and Aichivirus A was studied by examining prevalence of gastroenteritis viruses in association with meteorological variables in Ouagadougou, Burkina Faso. Methods Stool samples from 263 children under 5 years of age and 170 older children patients, adolescent and adults with gastroenteritis were collected in Ouagadougou, Burkina Faso from November 2011 to September 2012. Enteric viruses were detected using real-time or end-point (RT- PCR. Temperature, humidity and monthly rainfall were recorded from the National Meteorological Direction. Categorical data were compared by Chi-square tests and the effect of weather variables and monthly prevalence were analyzed using Pearson Correlation Coefficient test. Results The prevalence of rotavirus infections was significantly higher in the dry season (Season S1 compared to the wet season (season S2 (p = 0.03 among the population of children under 5 years of age. No statistically significant difference was observed regarding other gastroenteritis viruses comparing the dry season and the wet season. Positive cases of rotavirus, norovirus, adenovirus and sapovirus in children under 5 years of age were correlated with temperature (r = −0.68, p = 0.01; r = −0.74, p < 0.001; r = −0.68, p = 0.01; r = −0.65, p = 0.02, respectively and only rotavirus, adenovirus and astrovirus were correlated with relative humidity (r = −0.61, p = 0.04; r = −0.54, p = 0.08; r = −0.51, p = 0.1 respectively. No correlation was observed with rainfall. In older children, adolescent and adults patients, rotavirus and norovirus correlated with relative humidity (r = −0.58, p = 0.05; r = 0.54, p�

CHANGES OF GLYCEROL CONTENT IN DIAPAUSE LARVAEOF THE ORANGE WHEAT BLOSSOM MIDGE, SITODIPLOSIS MOSELLANA （GEHIN） IN VARIOUS SEASONS

Institute of Scientific and Technical Information of China (English)

Jun-xiangWu; FengYuan

2004-01-01

The glycerol contents in diapause larvae of the orange wheat blossom midge, Sitodiplosis mosellana (Gehin), collected from various seasons, were measured. The results showed that there was less glycerol content in larvae during living on the wheat head. Content of glycerol began to increase significantly when the larvae left the wheat head and entered the soil. A change trend of upper- lower- upper- lower in larvae glycerol contents during diapause in soil was observed from June to April of next year. More glycerol could be examined in larvae collected in summer and winter than in spring and autumn. There was not more glycerol in cocooned larvae than that in non-cocooned larvae during various seasons from the point of statistics. Comparing the glycerol content of larvae being diapause in the first year with that of larvae in the second year, there was yet no obvious difference when larvae were collected in the same season belonged to different years. Therefore, it is shown that the content of glycerol in larvae of the wheat midge in diapause is affected mainly by the seasons or diapause intensity.

Causes of seasonal variations of Cs-134/137 activity concentrations in surface air

International Nuclear Information System (INIS)

Hoetzl, H.; Winkler, R.

1993-01-01

In winter months maxima of Cs-134/137 activity concentrations in air are observed at several locations in Europe. To clarify this phenomenon, from October 1991 to November 1992 we performed a program for aerosol collection on a short-term scale based on collecting intervals of 48-72 hours. The local meteorological parameters were determined simultaneously. Statistical analysis of these observations reveiled a highly significant positive correlation between Cs-137 activity concentration and the so-called 'Stagnationsindex'. Based on this relationship the seasonal variations of Cs-134/137 concentrations in ground-level air can be explained by atmospheric inversion conditions frequently occurring during fall- and wintermonths. (orig.) [de

Seasonal variation of air pollution in Warsaw conurbation

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Katarzyna Rozbicka

2014-09-01

Full Text Available Long term research shows many substances in the atmosphere are in concentration dangerous for human health and welfare and even for human life. The work presents time and spatial variation of tropospheric ozone and nitrogen dioxide concentrations. Analysis was carried out on the base of hourly values of mentioned pollutants (O3 and NO2 concentrations. Data used in the analysis comes from atmospheric monitoring stations situated in various parts of Warsaw and concerns the period 2008–2011. The influence of meteorological elements on concentration of analyzed pollutants was stated by the use of correlation and multiple regression analysis for months and seasonal periods. On this base results of statistical analysis strong correlation between tropospheric ozone, nitrogen dioxide concentration and meteorological elements is stated. In case of ozone and nitrogen dioxide the relationships with air temperature, relative humidity and solar radiation are most significant.

Seasonal and Long-term Variations in 137Cs Among Adults from Swedish Hunter Families

International Nuclear Information System (INIS)

Agren, G.

2001-01-01

To study seasonal variations in 137 Cs, whole-body content measurements of adults from Swedish hunter families have been performed in autumn 1997 and spring 1998. Measurements were performed in three locations, By, Harbo and Gavle, geographically close (within 100 km of each other) but with large differences in ground deposition levels. The hunter families at these three locations were previously measured in 1994. The measured persons were also asked for their frequency of intake of moose, roe-deer, freshwater fish, mushrooms and berries. A statistically significant lower frequency of intake of mushrooms and berries in By, moose, roe-deer and mushrooms in Harbo, and moose in Gavle was found in springtime compared to autumn. In one of the locations, there was a statistically significant lower average 137 Cs whole-body content in spring 1998 than in autumn 1997 while in the other two locations no such effects could be seen. The 137 Cs whole-body content has decreased by 37% from 1994 and to 1998 (including physical decay) correlated to an effective ecological half time of 6 years. (author)

Intelligent system for statistically significant expertise knowledge on the basis of the model of self-organizing nonequilibrium dissipative system

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E. A. Tatokchin

2017-01-01

Full Text Available Development of the modern educational technologies caused by broad introduction of comput-er testing and development of distant forms of education does necessary revision of methods of an examination of pupils. In work it was shown, need transition to mathematical criteria, exami-nations of knowledge which are deprived of subjectivity. In article the review of the problems arising at realization of this task and are offered approaches for its decision. The greatest atten-tion is paid to discussion of a problem of objective transformation of rated estimates of the ex-pert on to the scale estimates of the student. In general, the discussion this question is was con-cluded that the solution to this problem lies in the creation of specialized intellectual systems. The basis for constructing intelligent system laid the mathematical model of self-organizing nonequilibrium dissipative system, which is a group of students. This article assumes that the dissipative system is provided by the constant influx of new test items of the expert and non-equilibrium – individual psychological characteristics of students in the group. As a result, the system must self-organize themselves into stable patterns. This patern will allow for, relying on large amounts of data, get a statistically significant assessment of student. To justify the pro-posed approach in the work presents the data of the statistical analysis of the results of testing a large sample of students (> 90. Conclusions from this statistical analysis allowed to develop intelligent system statistically significant examination of student performance. It is based on data clustering algorithm (k-mean for the three key parameters. It is shown that this approach allows you to create of the dynamics and objective expertise evaluation.

Extended season for northern butterflies.

Science.gov (United States)

Karlsson, Bengt

2014-07-01

Butterflies are like all insects in that they are temperature sensitive and a changing climate with higher temperatures might effect their phenology. Several studies have found support for earlier flight dates among the investigated species. A comparative study with data from a citizen science project, including 66 species of butterflies in Sweden, was undertaken, and the result confirms that most butterfly species now fly earlier during the season. This is especially evident for butterflies overwintering as adults or as pupae. However, the advancement in phenology is correlated with flight date, and some late season species show no advancement or have even postponed their flight dates and are now flying later in the season. The results also showed that latitude had a strong effect on the adult flight date, and most of the investigated species showed significantly later flights towards the north. Only some late flying species showed an opposite trend, flying earlier in the north. A majority of the investigated species in this study showed a general response to temperature and advanced their flight dates with warmer temperatures (on average they advanced their flight dates by 3.8 days/°C), although not all species showed this response. In essence, a climate with earlier springs and longer growing seasons seems not to change the appearance patterns in a one-way direction. We now see butterflies on the wings both earlier and later in the season and some consequences of these patterns are discussed. So far, studies have concentrated mostly on early season butterfly-plant interactions but also late season studies are needed for a better understanding of long-term population consequences.

Studies on seasonal pollution of heavy metals in water, sediment, fish and oyster from the Meiliang Bay of Taihu Lake in China.

Science.gov (United States)

Rajeshkumar, Sivakumar; Liu, Yang; Zhang, Xiangyang; Ravikumar, Boopalan; Bai, Ge; Li, Xiaoyu

2018-01-01

The present study, seasonal pollution of heavy metals (Pb, Cd, Cr and Cu) in water, sediment, tissues of fish Carassius carassius and oyster Crassostrea gigas were determined at seven sampling sites from Meiliang Bay, Taihu Lake during one year calendar, 2016. The total heavy metal concentrations in water samples were higher in winter and summer than in spring and autumn season, whereas in sediment they were higher in winter and summer seasons, respectively. The trend of metal mean contents found in the fish and oyster were in decreasing order of Pb > Cu > Cr > Cd and Pb > Cu > Cr > Cd, respectively. The tissues of fish and oyster captured during winter and summer accumulated a higher significant different amount of metals relative to other season, which was attributed to a higher influx of agricultural waste, sewage and sludge by heavy rainfall and floods. In addition, the pollution load index (PLI) values were above one (>1), indicating an advanced decline of the sediment quality, and contamination factor (CF) confirmed that the sediment samples were moderate to high contamination by Pb and Cr. Thus, comparative studies with seasonal pollution of heavy metals in Meiliang Bay of Lake Taihu regions indicate considerable heavy metal enrichment in water, sediments as well as in various organs of fish and oyster. Finally, our results indicated that the metal concentration values increased statistically significant different related to season (p heavy metal stress biomarkers in fish along with seasonal variations may serve as a convenient approach during pollution bio-monitoring programme. Copyright © 2017 Elsevier Ltd. All rights reserved.

Season of birth is different in Inuit suicide victims born into Traditional than into Modern Lifestyle

DEFF Research Database (Denmark)

Björkstén, Karin S; Bjerregaard, Peter

2015-01-01

BACKGROUND: There is growing evidence that living conditions at birth play a role in medical conditions later in life. Population-based studies from the Northern Hemisphere have shown that persons born in the spring or summer are at greater risk of committing suicide. A statistical correlation...... with light availability at birth has been observed in past research, but the cause remains unknown. Greenland is one of the most extreme of natural human habitats with regard to seasonal changes in light. The combination of rapid social changes and reliable population statistics offers a unique opportunity....... The suicide rate increased from very low rates to about 140 suicides/100 000 person-years in the 1980s. CONCLUSIONS: The reason behind a variation in season of birth in suicide victims born into the old lifestyle is unknown. It is also unknown why the seasonal difference had disappeared with modern lifestyle...

The Importance of Integrating Clinical Relevance and Statistical Significance in the Assessment of Quality of Care--Illustrated Using the Swedish Stroke Register.

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Anita Lindmark

Full Text Available When profiling hospital performance, quality inicators are commonly evaluated through hospital-specific adjusted means with confidence intervals. When identifying deviations from a norm, large hospitals can have statistically significant results even for clinically irrelevant deviations while important deviations in small hospitals can remain undiscovered. We have used data from the Swedish Stroke Register (Riksstroke to illustrate the properties of a benchmarking method that integrates considerations of both clinical relevance and level of statistical significance.The performance measure used was case-mix adjusted risk of death or dependency in activities of daily living within 3 months after stroke. A hospital was labeled as having outlying performance if its case-mix adjusted risk exceeded a benchmark value with a specified statistical confidence level. The benchmark was expressed relative to the population risk and should reflect the clinically relevant deviation that is to be detected. A simulation study based on Riksstroke patient data from 2008-2009 was performed to investigate the effect of the choice of the statistical confidence level and benchmark value on the diagnostic properties of the method.Simulations were based on 18,309 patients in 76 hospitals. The widely used setting, comparing 95% confidence intervals to the national average, resulted in low sensitivity (0.252 and high specificity (0.991. There were large variations in sensitivity and specificity for different requirements of statistical confidence. Lowering statistical confidence improved sensitivity with a relatively smaller loss of specificity. Variations due to different benchmark values were smaller, especially for sensitivity. This allows the choice of a clinically relevant benchmark to be driven by clinical factors without major concerns about sufficiently reliable evidence.The study emphasizes the importance of combining clinical relevance and level of statistical

The Importance of Integrating Clinical Relevance and Statistical Significance in the Assessment of Quality of Care--Illustrated Using the Swedish Stroke Register.

Science.gov (United States)

Lindmark, Anita; van Rompaye, Bart; Goetghebeur, Els; Glader, Eva-Lotta; Eriksson, Marie

2016-01-01

When profiling hospital performance, quality inicators are commonly evaluated through hospital-specific adjusted means with confidence intervals. When identifying deviations from a norm, large hospitals can have statistically significant results even for clinically irrelevant deviations while important deviations in small hospitals can remain undiscovered. We have used data from the Swedish Stroke Register (Riksstroke) to illustrate the properties of a benchmarking method that integrates considerations of both clinical relevance and level of statistical significance. The performance measure used was case-mix adjusted risk of death or dependency in activities of daily living within 3 months after stroke. A hospital was labeled as having outlying performance if its case-mix adjusted risk exceeded a benchmark value with a specified statistical confidence level. The benchmark was expressed relative to the population risk and should reflect the clinically relevant deviation that is to be detected. A simulation study based on Riksstroke patient data from 2008-2009 was performed to investigate the effect of the choice of the statistical confidence level and benchmark value on the diagnostic properties of the method. Simulations were based on 18,309 patients in 76 hospitals. The widely used setting, comparing 95% confidence intervals to the national average, resulted in low sensitivity (0.252) and high specificity (0.991). There were large variations in sensitivity and specificity for different requirements of statistical confidence. Lowering statistical confidence improved sensitivity with a relatively smaller loss of specificity. Variations due to different benchmark values were smaller, especially for sensitivity. This allows the choice of a clinically relevant benchmark to be driven by clinical factors without major concerns about sufficiently reliable evidence. The study emphasizes the importance of combining clinical relevance and level of statistical confidence when

Adaptive selection of diurnal minimum variation: a statistical strategy to obtain representative atmospheric CO2 data and its application to European elevated mountain stations

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Y. Yuan

2018-03-01

Full Text Available Critical data selection is essential for determining representative baseline levels of atmospheric trace gases even at remote measurement sites. Different data selection techniques have been used around the world, which could potentially lead to reduced compatibility when comparing data from different stations. This paper presents a novel statistical data selection method named adaptive diurnal minimum variation selection (ADVS based on CO2 diurnal patterns typically occurring at elevated mountain stations. Its capability and applicability were studied on records of atmospheric CO2 observations at six Global Atmosphere Watch stations in Europe, namely, Zugspitze-Schneefernerhaus (Germany, Sonnblick (Austria, Jungfraujoch (Switzerland, Izaña (Spain, Schauinsland (Germany, and Hohenpeissenberg (Germany. Three other frequently applied statistical data selection methods were included for comparison. Among the studied methods, our ADVS method resulted in a lower fraction of data selected as a baseline with lower maxima during winter and higher minima during summer in the selected data. The measured time series were analyzed for long-term trends and seasonality by a seasonal-trend decomposition technique. In contrast to unselected data, mean annual growth rates of all selected datasets were not significantly different among the sites, except for the data recorded at Schauinsland. However, clear differences were found in the annual amplitudes as well as the seasonal time structure. Based on a pairwise analysis of correlations between stations on the seasonal-trend decomposed components by statistical data selection, we conclude that the baseline identified by the ADVS method is a better representation of lower free tropospheric (LFT conditions than baselines identified by the other methods.

Adaptive selection of diurnal minimum variation: a statistical strategy to obtain representative atmospheric CO2 data and its application to European elevated mountain stations

Science.gov (United States)

Yuan, Ye; Ries, Ludwig; Petermeier, Hannes; Steinbacher, Martin; Gómez-Peláez, Angel J.; Leuenberger, Markus C.; Schumacher, Marcus; Trickl, Thomas; Couret, Cedric; Meinhardt, Frank; Menzel, Annette

2018-03-01

Critical data selection is essential for determining representative baseline levels of atmospheric trace gases even at remote measurement sites. Different data selection techniques have been used around the world, which could potentially lead to reduced compatibility when comparing data from different stations. This paper presents a novel statistical data selection method named adaptive diurnal minimum variation selection (ADVS) based on CO2 diurnal patterns typically occurring at elevated mountain stations. Its capability and applicability were studied on records of atmospheric CO2 observations at six Global Atmosphere Watch stations in Europe, namely, Zugspitze-Schneefernerhaus (Germany), Sonnblick (Austria), Jungfraujoch (Switzerland), Izaña (Spain), Schauinsland (Germany), and Hohenpeissenberg (Germany). Three other frequently applied statistical data selection methods were included for comparison. Among the studied methods, our ADVS method resulted in a lower fraction of data selected as a baseline with lower maxima during winter and higher minima during summer in the selected data. The measured time series were analyzed for long-term trends and seasonality by a seasonal-trend decomposition technique. In contrast to unselected data, mean annual growth rates of all selected datasets were not significantly different among the sites, except for the data recorded at Schauinsland. However, clear differences were found in the annual amplitudes as well as the seasonal time structure. Based on a pairwise analysis of correlations between stations on the seasonal-trend decomposed components by statistical data selection, we conclude that the baseline identified by the ADVS method is a better representation of lower free tropospheric (LFT) conditions than baselines identified by the other methods.

Seasonal variation in heavy metal concentration in mangrove foliage

Digital Repository Service at National Institute of Oceanography (India)

Untawale, A.G.; Wafar, S.; Bhosle, N.B.

Seasonal variation in the concentration of some heavy metals in the leaves of seven species of mangrove vegetation from Goa, revealed that maximum concentration of iron and manganese occurs during the monsoon season without any significant toxic...

Detection of Clostridium difficile infection clusters, using the temporal scan statistic, in a community hospital in southern Ontario, Canada, 2006-2011.

Science.gov (United States)

Faires, Meredith C; Pearl, David L; Ciccotelli, William A; Berke, Olaf; Reid-Smith, Richard J; Weese, J Scott

2014-05-12

In hospitals, Clostridium difficile infection (CDI) surveillance relies on unvalidated guidelines or threshold criteria to identify outbreaks. This can result in false-positive and -negative cluster alarms. The application of statistical methods to identify and understand CDI clusters may be a useful alternative or complement to standard surveillance techniques. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting CDI clusters and determine if there are significant differences in the rate of CDI cases by month, season, and year in a community hospital. Bacteriology reports of patients identified with a CDI from August 2006 to February 2011 were collected. For patients detected with CDI from March 2010 to February 2011, stool specimens were obtained. Clostridium difficile isolates were characterized by ribotyping and investigated for the presence of toxin genes by PCR. CDI clusters were investigated using a retrospective temporal scan test statistic. Statistically significant clusters were compared to known CDI outbreaks within the hospital. A negative binomial regression model was used to identify associations between year, season, month and the rate of CDI cases. Overall, 86 CDI cases were identified. Eighteen specimens were analyzed and nine ribotypes were classified with ribotype 027 (n = 6) the most prevalent. The temporal scan statistic identified significant CDI clusters at the hospital (n = 5), service (n = 6), and ward (n = 4) levels (P ≤ 0.05). Three clusters were concordant with the one C. difficile outbreak identified by hospital personnel. Two clusters were identified as potential outbreaks. The negative binomial model indicated years 2007-2010 (P ≤ 0.05) had decreased CDI rates compared to 2006 and spring had an increased CDI rate compared to the fall (P = 0.023). Application of the temporal scan statistic identified several clusters, including potential outbreaks not detected by hospital

Seasonal and Altitudinal Prevalence of Fascioliasis in Buffalo in Eastern Nepal

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Ramesh Prasad Sah

2018-05-01

Full Text Available Buffalo is the most important livestock commodities for milk, meat production and several other multipurpose uses distributed densely from southern tarai to northern mid-hills in Nepal. Among several internal parasitic diseases fascioliasis is highly economic one caused by Fasciola in buffaloes. However, there are only few studies carried on prevalence of fascioliasis emphasizing buffaloes in relation to seasonal (summer and rainy, and winter and altitudinal variations. Therefore, we examined prevalence of fascioliasis seasonally and vertically. For the purpose, we selected two districts of eastern Nepal and sampled from low altitude area known as Madhesha ranging from 175-200, Dhankuta from 800-1200 m, and Murtidhunga from 1800-2200 m elevation from the sea level, representing tarai, mid hills and high hills, respectively. Altogether from February 2013 to January 2014 at every two months interval we collected 798 fecal samples from buffaloes; 282 from Murtidhunga, 239 from Dhankuta and 277 from Madhesha. The samples were examined microscopically for the presence of Fasciola eggs using sedimentation technique. Results showed that overall prevalence of fascioliasis in buffaloes was 39.9% (319/798, ranging highest 42.6%in Madhesha followed by 39.7% in Murtidhunga and 37.2% in Dhankuta, respectively. The prevalence of fascioliasis was found to be significantly (p <0.05 high in winter (44.9% comparing to rainy season (34.4%. The prevalence of fascioliasis in buffaloes was relatively higher in low altitude than high altitude, although it was not statistically significant (p <0.05. In our findings the female buffaloes showed higher prevalence for fascioliasis than in male. Since the fascioliasis in buffaloes is highly endemic, thus strategic deworming in high risk period is recommended along with measure to prevent pasture contamination with buffalo feces.

Seasonal variations of agar extracted from different life stages of ...

African Journals Online (AJOL)

Seasonality in yield, physical and chemical properties of the native agar from different life stages of Gracilaria cliftonii was investigated over a period of six seasons (autumn 2008–winter 2009). Agar yield and its properties varied as a function of seasons and life stages but there was no significant correlation between ...

Estimates of statistical significance for comparison of individual positions in multiple sequence alignments

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Sadreyev Ruslan I

2004-08-01

Full Text Available Abstract Background Profile-based analysis of multiple sequence alignments (MSA allows for accurate comparison of protein families. Here, we address the problems of detecting statistically confident dissimilarities between (1 MSA position and a set of predicted residue frequencies, and (2 between two MSA positions. These problems are important for (i evaluation and optimization of methods predicting residue occurrence at protein positions; (ii detection of potentially misaligned regions in automatically produced alignments and their further refinement; and (iii detection of sites that determine functional or structural specificity in two related families. Results For problems (1 and (2, we propose analytical estimates of P-value and apply them to the detection of significant positional dissimilarities in various experimental situations. (a We compare structure-based predictions of residue propensities at a protein position to the actual residue frequencies in the MSA of homologs. (b We evaluate our method by the ability to detect erroneous position matches produced by an automatic sequence aligner. (c We compare MSA positions that correspond to residues aligned by automatic structure aligners. (d We compare MSA positions that are aligned by high-quality manual superposition of structures. Detected dissimilarities reveal shortcomings of the automatic methods for residue frequency prediction and alignment construction. For the high-quality structural alignments, the dissimilarities suggest sites of potential functional or structural importance. Conclusion The proposed computational method is of significant potential value for the analysis of protein families.

Seasonal Prediction of Taiwan's Streamflow Using Teleconnection Patterns

Science.gov (United States)

Chen, Chia-Jeng; Lee, Tsung-Yu

2017-04-01

Seasonal streamflow as an integrated response to complex hydro-climatic processes can be subject to activity of prevailing weather systems potentially modulated by large-scale climate oscillations (e.g., El Niño-Southern Oscillation, ENSO). To develop a seamless seasonal forecasting system in Taiwan, this study assesses how significant Taiwan's precipitation and streamflow in different seasons correlate with selected teleconnection patterns. Long-term precipitation and streamflow data in three major precipitation seasons, namely the spring rains (February to April), Mei-Yu (May and June), and typhoon (July to September) seasons, are derived at 28 upstream and 13 downstream catchments in Taiwan. The three seasons depict a complete wet period of Taiwan as well as many regions bearing similar climatic conditions in East Asia. Lagged correlation analysis is then performed to investigate how the precipitation and streamflow data correlate with predominant teleconnection indices at varied lead times. Teleconnection indices are selected only if they show certain linkage with weather systems and activity in the three seasons based on previous literature. For instance, the ENSO and Quasi-Biennial Oscillation, proven to influence East Asian climate across seasons and summer typhoon activity, respectively, are included in the list of climate indices for correlation analysis. Significant correlations found between Taiwan's precipitation and streamflow and teleconnection indices are further examined by a climate regime shift (CRS) test to identify any abrupt changes in the correlations. The understanding of existing CRS is useful for informing the forecasting system of the changes in the predictor-predictand relationship. To evaluate prediction skill in the three seasons and skill differences between precipitation and streamflow, hindcasting experiments of precipitation and streamflow are conducted using stepwise linear regression models. Discussion and suggestions for coping

Effects of Soccer Training on Anthropometry, Body Composition, and Physical Fitness during a Soccer Season in Female Elite Young Athletes: A Prospective Cohort Study

Science.gov (United States)

Lesinski, Melanie; Prieske, Olaf; Helm, Norman; Granacher, Urs

2017-01-01

The objectives of this study were to (i) describe soccer training (e.g., volume, types), anthropometry, body composition, and physical fitness and (ii) compute associations between soccer training data and relative changes of anthropometry, body composition, and physical fitness during a soccer season in female elite young athletes. Seasonal training (i.e., day-to-day training volume/types) as well as variations in anthropometry (e.g., body height/mass), body composition (e.g., lean body/fat mass), and physical fitness (e.g., muscle strength/power, speed, balance) were collected from 17 female elite young soccer players (15.3 ± 0.5 years) over the training periods (i.e., preparation, competition, transition) of a soccer season that resulted in the German championship title in under-17 female soccer. Training volume/types, anthropometrics, body composition, and physical fitness significantly varied over a soccer season. During the two preparation periods, higher volumes in resistance and endurance training were performed (2.00 ≤ d ≤ 18.15; p < 0.05), while higher sprint and tactical training volumes were applied during the two competition periods (2.22 ≤ d ≤ 11.18; p < 0.05). Body height and lean body mass increased over the season (2.50 ≤ d ≤ 3.39; p < 0.01). In terms of physical fitness, significant performance improvements were found over the soccer season in measures of balance, endurance, and sport-specific performance (2.52 ≤ d ≤ 3.95; p < 0.05). In contrast, no statistically significant changes were observed for measures of muscle power/endurance, speed, and change-of-direction speed. Of note, variables of muscle strength (i.e., leg extensors) significantly decreased (d = 2.39; p < 0.01) over the entire season. Our period-specific sub-analyses revealed significant performance improvements during the first round of the season for measures of muscle power/endurance, and balance (0.89 ≤ d ≤ 4.01; p < 0.05). Moreover, change

Effects of Soccer Training on Anthropometry, Body Composition, and Physical Fitness during a Soccer Season in Female Elite Young Athletes: A Prospective Cohort Study

Directory of Open Access Journals (Sweden)

Melanie Lesinski

2017-12-01

Full Text Available The objectives of this study were to (i describe soccer training (e.g., volume, types, anthropometry, body composition, and physical fitness and (ii compute associations between soccer training data and relative changes of anthropometry, body composition, and physical fitness during a soccer season in female elite young athletes. Seasonal training (i.e., day-to-day training volume/types as well as variations in anthropometry (e.g., body height/mass, body composition (e.g., lean body/fat mass, and physical fitness (e.g., muscle strength/power, speed, balance were collected from 17 female elite young soccer players (15.3 ± 0.5 years over the training periods (i.e., preparation, competition, transition of a soccer season that resulted in the German championship title in under-17 female soccer. Training volume/types, anthropometrics, body composition, and physical fitness significantly varied over a soccer season. During the two preparation periods, higher volumes in resistance and endurance training were performed (2.00 ≤ d ≤ 18.15; p < 0.05, while higher sprint and tactical training volumes were applied during the two competition periods (2.22 ≤ d ≤ 11.18; p < 0.05. Body height and lean body mass increased over the season (2.50 ≤ d ≤ 3.39; p < 0.01. In terms of physical fitness, significant performance improvements were found over the soccer season in measures of balance, endurance, and sport-specific performance (2.52 ≤ d ≤ 3.95; p < 0.05. In contrast, no statistically significant changes were observed for measures of muscle power/endurance, speed, and change-of-direction speed. Of note, variables of muscle strength (i.e., leg extensors significantly decreased (d = 2.39; p < 0.01 over the entire season. Our period-specific sub-analyses revealed significant performance improvements during the first round of the season for measures of muscle power/endurance, and balance (0.89 ≤ d ≤ 4.01; p < 0.05. Moreover, change

An intercomparison of approaches for improving operational seasonal streamflow forecasts

Science.gov (United States)

Mendoza, Pablo A.; Wood, Andrew W.; Clark, Elizabeth; Rothwell, Eric; Clark, Martyn P.; Nijssen, Bart; Brekke, Levi D.; Arnold, Jeffrey R.

2017-07-01

For much of the last century, forecasting centers around the world have offered seasonal streamflow predictions to support water management. Recent work suggests that the two major avenues to advance seasonal predictability are improvements in the estimation of initial hydrologic conditions (IHCs) and the incorporation of climate information. This study investigates the marginal benefits of a variety of methods using IHCs and/or climate information, focusing on seasonal water supply forecasts (WSFs) in five case study watersheds located in the US Pacific Northwest region. We specify two benchmark methods that mimic standard operational approaches - statistical regression against IHCs and model-based ensemble streamflow prediction (ESP) - and then systematically intercompare WSFs across a range of lead times. Additional methods include (i) statistical techniques using climate information either from standard indices or from climate reanalysis variables and (ii) several hybrid/hierarchical approaches harnessing both land surface and climate predictability. In basins where atmospheric teleconnection signals are strong, and when watershed predictability is low, climate information alone provides considerable improvements. For those basins showing weak teleconnections, custom predictors from reanalysis fields were more effective in forecast skill than standard climate indices. ESP predictions tended to have high correlation skill but greater bias compared to other methods, and climate predictors failed to substantially improve these deficiencies within a trace weighting framework. Lower complexity techniques were competitive with more complex methods, and the hierarchical expert regression approach introduced here (hierarchical ensemble streamflow prediction - HESP) provided a robust alternative for skillful and reliable water supply forecasts at all initialization times. Three key findings from this effort are (1) objective approaches supporting methodologically

Test the Overall Significance of p-values by Using Joint Tail Probability of Ordered p-values as Test Statistic

NARCIS (Netherlands)

Fang, Yongxiang; Wit, Ernst

2008-01-01

Fisher’s combined probability test is the most commonly used method to test the overall significance of a set independent p-values. However, it is very obviously that Fisher’s statistic is more sensitive to smaller p-values than to larger p-value and a small p-value may overrule the other p-values

Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods

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Mustafa Akpinar

2016-09-01

Full Text Available Consumption of natural gas, a major clean energy source, increases as energy demand increases. We studied specifically the Turkish natural gas market. Turkey’s natural gas consumption increased as well in parallel with the world‘s over the last decade. This consumption growth in Turkey has led to the formation of a market structure for the natural gas industry. This significant increase requires additional investments since a rise in consumption capacity is expected. One of the reasons for the consumption increase is the user-based natural gas consumption influence. This effect yields imbalances in demand forecasts and if the error rates are out of bounds, penalties may occur. In this paper, three univariate statistical methods, which have not been previously investigated for mid-term year-ahead monthly natural gas forecasting, are used to forecast natural gas demand in Turkey’s Sakarya province. Residential and low-consumption commercial data is used, which may contain seasonality. The goal of this paper is minimizing more or less gas tractions on mid-term consumption while improving the accuracy of demand forecasting. In forecasting models, seasonality and single variable impacts reinforce forecasts. This paper studies time series decomposition, Holt-Winters exponential smoothing and autoregressive integrated moving average (ARIMA methods. Here, 2011–2014 monthly data were prepared and divided into two series. The first series is 2011–2013 monthly data used for finding seasonal effects and model requirements. The second series is 2014 monthly data used for forecasting. For the ARIMA method, a stationary series was prepared and transformation process prior to forecasting was done. Forecasting results confirmed that as the computation complexity of the model increases, forecasting accuracy increases with lower error rates. Also, forecasting errors and the coefficients of determination values give more consistent results. Consequently

Varicella-Zoster Virus in Perth, Western Australia: Seasonality and Reactivation.

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Igor A Korostil

Full Text Available Identification of the factors affecting reactivation of varicella-zoster virus (VZV largely remains an open question. Exposure to solar ultra violet (UV radiation is speculated to facilitate reactivation. Should the role of UV in reactivation be significant, VZV reactivation patterns would generally be expected to be synchronous with seasonal UV profiles in temperate climates.We analysed age and gender specific VZV notification time series data from Perth, Western Australia (WA. This city has more daily sunshine hours than any other major Australian city. Using the cosinor and generalized linear models, we tested these data for seasonality and correlation with UV and temperature.We established significant seasonality of varicella notifications and showed that while herpes-zoster (HZ was not seasonal it had a more stable seasonal component in males over 60 than in any other subpopulation tested. We also detected significant association between HZ notifications and UV for the entire Perth population as well as for females and males separately. In most cases, temperature proved to be a significant factor as well.Our findings suggest that UV radiation may be important for VZV reactivation, under the assumption that notification data represent an acceptably accurate qualitative measure of true VZV incidence.

Statistical analysis of corn yields responding to climate variability at various spatio-temporal resolutions

Science.gov (United States)

Jiang, H.; Lin, T.

2017-12-01

Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.

On long-term evolution of seasonal precipitation in southwestern Europe

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F. Valero

1996-09-01

Full Text Available Annual cycles in long time series of precipitation from sixteen southwest European observatories have been analysed using complex demodulation. The stations have been clustered into two distinct regions and a hybrid one. They are referred to as the southwestern Europe precipitation Atlantic regime (SEPAR and the southwestern Europe precipitation Mediterranean regime (SEPMER, with the hybrid regime referred to in terms of the mean amplitude ratios between semiannual and annual rainfall components. Some evidence of linking between seasonal cycle harmonic amplitudes and the zonal circulation has been found for SEPAR stations and a more obscured relationship for the SEPMER region. Within the SEPAR region the strength of the relationship is diminished towards the north. A trend analysis of the amplitudes against time since 1920 has also been carried out and the results reveal a divergent pattern in trends between annual and semiannual component amplitudes for the SEPAR region. In fact, both an increasing annual-amplitude trend and a decreasing semiannual-amplitude trend are observed, in each case statistically significant. The fact that the seasonal cycle variability of rainfall in southwestern Europe becomes more sensitive southwards to changes in atmospheric zonal circulation over the North Atlantic might, in our opinion, be related to the swing of the circumpolar vortex.

Season and humidity dependence of the effects of air pollution on COPD hospitalizations in Hong Kong

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Qiu, Hong; Yu, Ignatius Tak Sun; Wang, Xiaorong; Tian, Linwei; Tse, Lap Ah; Wong, Tze Wai

2013-09-01

Associations between ambient pollution and respiratory morbidity including chronic obstructive pulmonary disease (COPD) have been confirmed. Weather factors, such as temperature, season and relative humidity (RH), may modify the effects of air pollution. This time series study was conducted to examine whether the effects of air pollution on emergency COPD hospital admissions in Hong Kong varied across seasons and RH levels, and explore the possible joint modification of season and RH on the effects of pollution. Data of daily air pollution concentrations mean temperature and RH, and COPD hospital admissions from 1998 to 2007 were collected. Generalized additive Poisson models with interaction terms were used to estimate the effects of pollution across seasons and RH levels. We observed an increase in the detrimental effects of air pollution in the cool season and on low humidity days. On the cool and dry days, a 10 μg m-3 increment of lag03 exposure was associated with an increase in emergency COPD admissions by 1.76% (95%CI: 1.19-2.34%), 3.43% (95%CI: 2.80-4.07%), and 1.99% (95%CI: 0.90-3.09%) for nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2), respectively, all of which were statistically significantly higher than those on the other days. No consistent modification of weather factors was found for the effects of particles with an aerodynamic diameter less than 10 μm (PM10). The results suggested that season and RH jointly modified the effects of gaseous pollutants, resulting in increased emergency COPD hospitalizations on the cool and dry days.

Seasonal Variations in Physical Fitness and Performance Indices of Elite Soccer Players

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Yoav Meckel

2018-02-01

Full Text Available The aim of the study was to investigate seasonal variations in fitness and performance indices of professional male soccer players. Eighteen professional male soccer players (age range 22–32 years completed three similar sets of tests at three stages of the season: before preseason; after preseason and the middle of the competitive in-season. A significant decrease in body mass and percent fat was found during the preseason. A significant improvement (p < 0.05 was found in the vertical jump (preseason: 37.0 ± 5.3, post-preseason: 39.0 ± 4.8, mid-season: 40.3 ± 5.5 cm, the 4 × 10-m agility test (preseason: 8.1 ± 0.2, post-preseason: 7.9 ± 0.2, mid-season: 8.1 ± 0.3 s, flexibility (preseason: 45.2 ± 8.8, post-preseason: 48.2 ± 7.0, mid-season: 49.9 ± 6.9 cm and aerobic capacity (preseason: 52.7 ± 6.6, post-preseason: 56.4 ± 6.0, mid-season: 57.4 ± 5.4 mL/kg/min during preseason, with no further change during mid-season. Repeated sprint test (RST (6 × 30-m performance indices showed significant deterioration (p < 0.05 in ideal sprint time (IS; preseason: 21.8 ± 1.0, post-preseason: 23.0 ± 0.8, mid-season: 23.2 ± 0.8 s and total sprint time (TS; preseason: 22.5 ± 0.7, post-preseason: 23.5 ± 0.6, mid-season: 23.8 ± 0.6 s during preseason, with no further changes during mid-season. However, performance decrement (PD significantly decreased during the preseason with no change during mid-season. The findings suggest that while power training was probably responsible for the anaerobic fitness improvement, the high-volume training led to improvement in aerobic fitness during the preseason. However, the low-intensity aerobic-type training, coupled with the high total training load, may have led to fatigue and decreases in IS and TS during the preseason.

Boll weevil within season and off-season activity monitored using a pheromone-and-glue reusable tube trap

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Robério Carlos dos Santos Neves

Full Text Available ABSTRACT: The boll weevil colonizes cotton fields as early as cotton squaring, causing significant losses due to feeding and protected development inside fruiting structures throughout crop phenology. Successful control depends on control of adults and their accurate detection when they colonize the crops. The commercial trap and boll weevil attract-and-control tubes (BWACT are the only available tools to monitor and attract-and-kill boll weevil, despite limitation in efficacy, and insecticide in BWACT is not allowed in organic production. A grandlure-and-glue reusable and insecticide-free tube (GGT made with polyvinyl chloride tube, smeared with entomological glue, and lured with pheromone was tested to detect boll weevil activity across various seasons. Boll weevil showed activity during growing season and off-season from 2009 to 2012 in the Semiarid and with higher numbers captured in GGT in comparisons to commercial traps. GGT was able to detect early weevils in the field right after planting. Further, the overall averages resulted in 34-, 16.8-, and 7.5-times more weevils captured in GGTs compared to the traps during stalk destruction in the Semiarid 2011 and Cerrado season 2012/13 and during the harvesting period in the Cerrado season 2011/12, respectively. Therefore, boll weevils were captured actively during season and off-season and early captures obtained in GGT compared to traps showed a better correlation between captures and square damage.

Statistical determination of significant curved I-girder bridge seismic response parameters

Science.gov (United States)

Seo, Junwon

2013-06-01

Curved steel bridges are commonly used at interchanges in transportation networks and more of these structures continue to be designed and built in the United States. Though the use of these bridges continues to increase in locations that experience high seismicity, the effects of curvature and other parameters on their seismic behaviors have been neglected in current risk assessment tools. These tools can evaluate the seismic vulnerability of a transportation network using fragility curves. One critical component of fragility curve development for curved steel bridges is the completion of sensitivity analyses that help identify influential parameters related to their seismic response. In this study, an accessible inventory of existing curved steel girder bridges located primarily in the Mid-Atlantic United States (MAUS) was used to establish statistical characteristics used as inputs for a seismic sensitivity study. Critical seismic response quantities were captured using 3D nonlinear finite element models. Influential parameters from these quantities were identified using statistical tools that incorporate experimental Plackett-Burman Design (PBD), which included Pareto optimal plots and prediction profiler techniques. The findings revealed that the potential variation in the influential parameters included number of spans, radius of curvature, maximum span length, girder spacing, and cross-frame spacing. These parameters showed varying levels of influence on the critical bridge response.

Seasonal variation in bacterial heavy metal bio sorption in water samples from Eziama river near soap and brewery industries and environmental health implications

International Nuclear Information System (INIS)

Kanu, I.; Achi, O. K.; Ezeronye, O. U.; Anyanwu, E. C.

2006-01-01

Seasonal variation in bacterial heavy metals bio sorption from soap and brewery industrial effluent samples from Eziama River in Abia State were analyzed for Pb, Hg, Fe, Zn, As, and Mn, using atomic absorption spectrophotometry. Bioaccumulation of the metals by bacteria showed the following trend > Fe >Zn >As > Pb > Mn (Rainy Season) and Zn > Fe > Mn > As > Hg > Pb (Dry season). Statistical analysis using of variance (ANOVA) showed significant differences in concentrations of Pb, Hg, Fe, Zn, As, and Mn level between the sampling zones at Eziama River. Seasonal changes in heavy metal concentrations, showed increases in Pb, Fe, and As from 1.32 x 10 5m g/L in the rainy season to 1.42 x 10 5m g/L in the dry season. Fe increased from 40.35 x 10 5m g/L to 42.1 x 10 5m g/L while As increased from 2.32 to 2.48 x 10 5m g/L with a net increases of +56 and + 69 x 10 5m g/L respectively. However, Hg, Zn, and Mn concentrations decreased in the rainy season from 40.54 x 10 5m g/L to 39.24 x l0 5m g/L 1.65 to 0.62 x l0 5m g/L respectively

Marked seasonal variation in the wild mouse gut microbiota.

Science.gov (United States)

Maurice, Corinne F; Knowles, Sarah C L; Ladau, Joshua; Pollard, Katherine S; Fenton, Andy; Pedersen, Amy B; Turnbaugh, Peter J

2015-11-01

Recent studies have provided an unprecedented view of the microbial communities colonizing captive mice; yet the host and environmental factors that shape the rodent gut microbiota in their natural habitat remain largely unexplored. Here, we present results from a 2-year 16 S ribosomal RNA gene sequencing-based survey of wild wood mice (Apodemus sylvaticus) in two nearby woodlands. Similar to other mammals, wild mice were colonized by 10 bacterial phyla and dominated by the Firmicutes, Bacteroidetes and Proteobacteria. Within the Firmicutes, the Lactobacillus genus was most abundant. Putative bacterial pathogens were widespread and often abundant members of the wild mouse gut microbiota. Among a suite of extrinsic (environmental) and intrinsic (host-related) factors examined, seasonal changes dominated in driving qualitative and quantitative differences in the gut microbiota. In both years examined, we observed a strong seasonal shift in gut microbial community structure, potentially due to the transition from an insect- to a seed-based diet. This involved decreased levels of Lactobacillus, and increased levels of Alistipes (Bacteroidetes phylum) and Helicobacter. We also detected more subtle but statistically significant associations between the gut microbiota and biogeography, sex, reproductive status and co-colonization with enteric nematodes. These results suggest that environmental factors have a major role in shaping temporal variations in microbial community structure within natural populations.

Impact of shade on outdoor thermal comfort—a seasonal field study in Tempe, Arizona

Science.gov (United States)

Middel, Ariane; Selover, Nancy; Hagen, Björn; Chhetri, Nalini

2016-12-01

Shade plays an important role in designing pedestrian-friendly outdoor spaces in hot desert cities. This study investigates the impact of photovoltaic canopy shade and tree shade on thermal comfort through meteorological observations and field surveys at a pedestrian mall on Arizona State University's Tempe campus. During the course of 1 year, on selected clear calm days representative of each season, we conducted hourly meteorological transects from 7:00 a.m. to 6:00 p.m. and surveyed 1284 people about their thermal perception, comfort, and preferences. Shade lowered thermal sensation votes by approximately 1 point on a semantic differential 9-point scale, increasing thermal comfort in all seasons except winter. Shade type (tree or solar canopy) did not significantly impact perceived comfort, suggesting that artificial and natural shades are equally efficient in hot dry climates. Globe temperature explained 51 % of the variance in thermal sensation votes and was the only statistically significant meteorological predictor. Important non-meteorological factors included adaptation, thermal comfort vote, thermal preference, gender, season, and time of day. A regression of subjective thermal sensation on physiological equivalent temperature yielded a neutral temperature of 28.6 °C. The acceptable comfort range was 19.1 °C-38.1 °C with a preferred temperature of 20.8 °C. Respondents exposed to above neutral temperature felt more comfortable if they had been in air-conditioning 5 min prior to the survey, indicating a lagged response to outdoor conditions. Our study highlights the importance of active solar access management in hot urban areas to reduce thermal stress.

Household transmission of influenza A(H1N1pdm09 in the pandemic and post-pandemic seasons.

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Itziar Casado

Full Text Available The transmission of influenza viruses occurs person to person and is facilitated by contacts within enclosed environments such as households. The aim of this study was to evaluate secondary attack rates and factors associated with household transmission of laboratory-confirmed influenza A(H1N1pdm09 in the pandemic and post-pandemic seasons.During the 2009-2010 and 2010-2011 influenza seasons, 76 sentinel physicians in Navarra, Spain, took nasopharyngeal and pharyngeal swabs from patients diagnosed with influenza-like illness. A trained nurse telephoned households of those patients who were laboratory-confirmed for influenza A(H1N1pdm09 to ask about the symptoms, risk factors and vaccination status of each household member.In the 405 households with a patient laboratory-confirmed for influenza A(H1N1pdm09, 977 susceptible contacts were identified; 16% of them (95% CI 14-19% presented influenza-like illness and were considered as secondary cases. The secondary attack rate was 14% in 2009-2010 and 19% in the 2010-2011 season (p=0.049, an increase that mainly affected persons with major chronic conditions. In the multivariate logistic regression analysis, the risk of being a secondary case was higher in the 2010-2011 season than in the 2009-2010 season (adjusted odds ratio: 1.72; 95% CI 1.17-2.54, and in children under 5 years, with a decreasing risk in older contacts. Influenza vaccination was associated with lesser incidence of influenza-like illness near to statistical significance (adjusted odds ratio: 0.29; 95% CI 0.08-1.03.The secondary attack rate in households was higher in the second season than in the first pandemic season. Children had a greater risk of infection. Preventive measures should be maintained in the second pandemic season, especially in high-risk persons.

Attribution of Large-Scale Climate Patterns to Seasonal Peak-Flow and Prospects for Prediction Globally

Science.gov (United States)

Lee, Donghoon; Ward, Philip; Block, Paul

2018-02-01

Flood-related fatalities and impacts on society surpass those from all other natural disasters globally. While the inclusion of large-scale climate drivers in streamflow (or high-flow) prediction has been widely studied, an explicit link to global-scale long-lead prediction is lacking, which can lead to an improved understanding of potential flood propensity. Here we attribute seasonal peak-flow to large-scale climate patterns, including the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), and Atlantic Multidecadal Oscillation (AMO), using streamflow station observations and simulations from PCR-GLOBWB, a global-scale hydrologic model. Statistically significantly correlated climate patterns and streamflow autocorrelation are subsequently applied as predictors to build a global-scale season-ahead prediction model, with prediction performance evaluated by the mean squared error skill score (MSESS) and the categorical Gerrity skill score (GSS). Globally, fair-to-good prediction skill (20% ≤ MSESS and 0.2 ≤ GSS) is evident for a number of locations (28% of stations and 29% of land area), most notably in data-poor regions (e.g., West and Central Africa). The persistence of such relevant climate patterns can improve understanding of the propensity for floods at the seasonal scale. The prediction approach developed here lays the groundwork for further improving local-scale seasonal peak-flow prediction by identifying relevant global-scale climate patterns. This is especially attractive for regions with limited observations and or little capacity to develop flood early warning systems.

Spatio-temporal statistical models with applications to atmospheric processes

International Nuclear Information System (INIS)

Wikle, C.K.

1996-01-01

This doctoral dissertation is presented as three self-contained papers. An introductory chapter considers traditional spatio-temporal statistical methods used in the atmospheric sciences from a statistical perspective. Although this section is primarily a review, many of the statistical issues considered have not been considered in the context of these methods and several open questions are posed. The first paper attempts to determine a means of characterizing the semiannual oscillation (SAO) spatial variation in the northern hemisphere extratropical height field. It was discovered that the midlatitude SAO in 500hPa geopotential height could be explained almost entirely as a result of spatial and temporal asymmetries in the annual variation of stationary eddies. It was concluded that the mechanism for the SAO in the northern hemisphere is a result of land-sea contrasts. The second paper examines the seasonal variability of mixed Rossby-gravity waves (MRGW) in lower stratospheric over the equatorial Pacific. Advanced cyclostationary time series techniques were used for analysis. It was found that there are significant twice-yearly peaks in MRGW activity. Analyses also suggested a convergence of horizontal momentum flux associated with these waves. In the third paper, a new spatio-temporal statistical model is proposed that attempts to consider the influence of both temporal and spatial variability. This method is mainly concerned with prediction in space and time, and provides a spatially descriptive and temporally dynamic model

Seasonal primary amebic meningoencephalitis (PAM) in the south: summertime is PAM time.

Science.gov (United States)

Diaz, James

2012-01-01

Primary amebic meningoencephalitis (PAM), a typically fatal, free-living amebic infection of the central nervous system (CNS), is caused by the thermophilic, freshwater protozoan, Naegleria fowleri. More than 145 cases of PAM have been reported worldwide, with most reported cases in the United States (US). Since annual PAM case clusters in the US and worldwide have demonstrated recent increases over background cases, the objectives of this investigation included (1) an epidemiological and statistical analysis of a 2007 cluster of six PAM cases in the southern US, nested in a retrospective review of 121 confirmed US cases of PAM over the period, 1937 to 2007; and (2) a statistical analysis of all existing demographic, temporal, and behavioral risk factors for PAM. Significant risk factors for PAM in the United States included male sex and warm recreational freshwater exposures in seasonal patterns (July - August) in southern tier states, including Louisiana. Although there have been a few recent survivors of PAM treated with combinations of intensive critical care, antifungals, and synergistic antibiotics, case fatality rates for PAM remain very high. PAM is best prevented by combinations of public health educational and behavioral modification strategies. Further investigations will be required to determine the significance of freshwater wakeboarding as a significant risk factor for PAM and to determine any dose-response effects of global warming on rising freshwater temperatures and the growth of aquatic Naegleria fowleri.

Evaluation of the influence of seasonality and landscape on the physicochemical characteristics of propolis

Directory of Open Access Journals (Sweden)

Elaine Maria Loureiro

2013-12-01

Full Text Available This study aimed at verifying the influence of the seasonality and landscape of the place of apiaries in the production and physicochemical quality of propolis produced in Cáceres-MT. Within August/2006 and July/2007 twenty-three propolis samples were collected monthly. The physicochemical quality of propolis was determined by the characteristic: loss by drying, wax, mechanical mass, oxidation activity, dry extract, flavonoids and total phenolics. The production of propolis was analyzed through correlation with seasonality (dry and wet. The same statistic model was used to correlate the production with the landscape (highland and flood plain. For each physicochemical characteristic were used statistic model of correlation described for the production of propolis. The seasonality did not influence on propolis production and on physicochemical quality. The landscape did not influence on propolis production and physicochemical quality loss by drying and mechanical mass, however, it determined the physicochemical quality for wax (x=22.44%, oxidation activity (x=9.73'', dry extract (x=22.31%, flavonoids (x=1.94% and total phenolics (x=0.02% in the highland of the Pantanal of Cáceres. This way it concludes that the production and physicochemical quality of propolis were not influenced by seasonality. The landscape influenced positively on physicochemical quality of propolis in the highland of the Pantanal of Cáceres.

Statistical Analysis of Categorical Time Series of Atmospheric Elementary Circulation Mechanisms - Dzerdzeevski Classification for the Northern Hemisphere.

Science.gov (United States)

Brenčič, Mihael

2016-01-01

Northern hemisphere elementary circulation mechanisms, defined with the Dzerdzeevski classification and published on a daily basis from 1899-2012, are analysed with statistical methods as continuous categorical time series. Classification consists of 41 elementary circulation mechanisms (ECM), which are assigned to calendar days. Empirical marginal probabilities of each ECM were determined. Seasonality and the periodicity effect were investigated with moving dispersion filters and randomisation procedure on the ECM categories as well as with the time analyses of the ECM mode. The time series were determined as being non-stationary with strong time-dependent trends. During the investigated period, periodicity interchanges with periods when no seasonality is present. In the time series structure, the strongest division is visible at the milestone of 1986, showing that the atmospheric circulation pattern reflected in the ECM has significantly changed. This change is result of the change in the frequency of ECM categories; before 1986, the appearance of ECM was more diverse, and afterwards fewer ECMs appear. The statistical approach applied to the categorical climatic time series opens up new potential insight into climate variability and change studies that have to be performed in the future.

Game statistics for the island of Olkiluoto in 2010-2011

International Nuclear Information System (INIS)

Nieminen, M.; Niemi, M.; Jussila, I.

2011-10-01

The game statistics for the island of Olkiluoto were updated in the summer 2011 and compared with earlier statistics. Population size estimates are based on interviews of the local hunters. No moose or deer inventories were made in the winter 2010-2011. The moose population is stable when compared with the previous year. The white-tailed deer population is stable or slightly increasing when compared with the previous year. The changes in the roe deer population are not accurately known, but population size varies somewhat from year to year. The number of hunted raccoon dogs approximately doubled in the latest hunting season. Altogether two waterfowl were hunted in 2010 (17 in the previous year). The populations of mountain hare and red squirrel are abundant, and the number of hunted mountain hares approximately doubled when compared with the previous hunting season. The brown hare population is still small. In the winter, there were observations of one lynx spending time in the area. (orig.)

Game statistics for the island of Olkiluoto in 2010-2011

Energy Technology Data Exchange (ETDEWEB)

Nieminen, M. [Faunatica Oy, Espoo (Finland); Niemi, M. [Helsinki Univ. (Finland), Dept. of Forest Sciences; Jussila, I. [Turku Univ. (Finland), Satakunta Environmental Research Inst.

2011-10-15

The game statistics for the island of Olkiluoto were updated in the summer 2011 and compared with earlier statistics. Population size estimates are based on interviews of the local hunters. No moose or deer inventories were made in the winter 2010-2011. The moose population is stable when compared with the previous year. The white-tailed deer population is stable or slightly increasing when compared with the previous year. The changes in the roe deer population are not accurately known, but population size varies somewhat from year to year. The number of hunted raccoon dogs approximately doubled in the latest hunting season. Altogether two waterfowl were hunted in 2010 (17 in the previous year). The populations of mountain hare and red squirrel are abundant, and the number of hunted mountain hares approximately doubled when compared with the previous hunting season. The brown hare population is still small. In the winter, there were observations of one lynx spending time in the area. (orig.)

Analysis of Seasonal Soil Organic Carbon Content at Bukit Jeriau Forest, Fraser Hill, Pahang

International Nuclear Information System (INIS)

Ahmad Adnan Mohamed; Ahmad Adnan Mohamed; Sahibin Abd Rahim; David Allan Aitman; Mohd Khairul Amri Kamarudin; Mohd Khairul Amri Kamarudin

2016-01-01

Soil carbon is the carbon held within the soil, primarily in association with its organic content. The total soil organic carbon study was determined in a plot at Bukit Jeriau forest in Bukit Fraser, Pahang, Malaysia. The aim of this study is to determine the changing of soil organic carbon between wet season and dry season. Soil organic carbon was fined out using titrimetric determination. The soil organic carbon content in wet season is 223.24 t/ ha while dry season is 217.90 t/ ha. The soil pH range in wet season is between 4.32 to 4.45 and in dry season in 3.95 to 4.08 which is considered acidic. Correlation analysis showed that soil organic carbon value is influenced by pH value and climate. Correlation analysis between clay and soil organic carbon with depth showed positively significant differences and clay are very much influenced soil organic carbon content. Correlation analysis between electrical conductivity and soil organic carbon content showed negative significantly difference on wet season and positively significant different in dry season. (author)

Seasonal mood changes in patients with obsessive-compulsive disorder.

Science.gov (United States)

Tan, Oğuz; Metin, Barış; Ünsalver, Barış Önen; Sayar, Gökben Hızlı

2017-12-01

Obsessive-compulsive disorder (OCD) is frequently associated with mood disorders. However, to date, the co-occurrence of OCD with seasonal affective disorder (SAD) has not been investigated. We have aimed to estimate the prevalence of seasonal mood changes in patients with OCD and explore the contribution of seasonality in mood to the severity of OCD. The Seasonal Pattern Assessment Questionnaire (SPAQ), the Yale-Brown Obsession and Compulsion Scale (Y-BOCS), the Hamilton Depression Rating Scale-17 Items (HDRS-17), and the Beck Anxiety Inventory (BAI) were administered to patients with OCD (n=104) and controls (n=125). The degree of seasonality was measured by the Global Seasonality Score (GSS) calculated from the SPAQ. SAD and subsyndromal seasonal affective disorder (S-SAD) were significantly more prevalent in patients with OCD (53%, n=55) than controls (25%, n=31). When patients were assessed in the season in which SAD occurs, depression and compulsions (but not obsessions, OCD or anxiety) were more severe than those assessed in a season during which SAD does not occur. SAD frequently co-occurs with OCD and, given this co-occurrence, depression symptoms in some patients with OCD might be expected to vary on a seasonal basis. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Does the Dietary Pattern of Shanghai Residents  Change across Seasons and Area of Residence:  Assessing Dietary Quality Using the Chinese Diet  Balance Index (DBI).

Science.gov (United States)

Zang, Jiajie; Yu, Huiting; Zhu, Zhenni; Lu, Ye; Liu, Changhe; Yao, Chunxia; Bai, Pinqing; Guo, Changyi; Jia, Xiaodong; Zou, Shurong; Wu, Fan

2017-03-08

Few studies have applied the Chinese Diet Balance Index (DBI) in evaluating dietary quality across seasons. The Shanghai Diet and Health Survey (SDHS) included 1680 participants from all districts of Shanghai from 2012 to 2013. Dietary data were obtained using three-day 24-h recall in spring, summer, fall, and winter. Higher bound score (HBS), lower bound score (LBS) and diet quality distance (DQD) were calculated according to compliance with the dietary guidelines and based on the recommendations for consumption within the main food groups. HBS, LBS, and DQD represent over-intake, under-intake, and overall imbalance of the diet, respectively. 836 males and 844 females were included. The HBS indicated that 10.08%, 11.84%, 10.31%, and 12.73% people have moderate or high levels of over-intake of food in spring, summer, fall, and winter, respectively; and 74.04%, 37.61%, 53.09%, and 42.72% people have moderate or high levels of deficit food intake for each of the four seasons. The mean HBS and LBS among the four seasons were statistically significant difference (p < 0.001). The mean (SD) DQD was 43.27 (10.21), 35.67 (9.71), 39.19 (9.36), and 36.84 (9.45) in each season. A multivariable model showed statistically significant differences in DQD according to age, gender, occupational status, education, smoking, drinking status, season, and residency (p < 0.001). An unbalanced diet is common among people living in Shanghai. Seasonality and area of residence were found to be two significant predictors. Strengthening the accessibility and the supply of food across seasons and regions should be considered.

Does the Dietary Pattern of Shanghai Residents  Change across Seasons and Area of Residence:  Assessing Dietary Quality Using the Chinese Diet  Balance Index (DBI

Directory of Open Access Journals (Sweden)

Jiajie Zang

2017-03-01

Full Text Available Background: Few studies have applied the Chinese Diet Balance Index (DBI in evaluating dietary quality across seasons. Method: The Shanghai Diet and Health Survey (SDHS included 1680 participants from all districts of Shanghai from 2012 to 2013. Dietary data were obtained using three‐day 24‐h recall in spring, summer, fall, and winter. Higher bound score (HBS, lower bound score (LBS and diet quality distance (DQD were calculated according to compliance with the dietary guidelines and based on the recommendations for consumption within the main food groups. HBS, LBS, and DQD represent over‐intake, under‐intake, and overall imbalance of the diet, respectively. Results: 836 males and 844 females were included. The HBS indicated that 10.08%, 11.84%, 10.31%, and 12.73% people have moderate or high levels of over‐intake of food in spring, summer, fall, and winter, respectively; and 74.04%, 37.61%, 53.09%, and 42.72% people have moderate or high levels of deficit food intake for each of the four seasons. The mean HBS and LBS among the four seasons were statistically significant difference (p < 0.001. The mean (SD DQD was 43.27 (10.21, 35.67 (9.71, 39.19 (9.36, and 36.84 (9.45 in each season. A multivariable model showed statistically significant differences in DQD according to age, gender, occupational status, education, smoking, drinking status, season, and residency (p < 0.001. Conclusion: An unbalanced diet is common among people living in Shanghai. Seasonality and area of residence were found to be two significant predictors. Strengthening the accessibility and the supply of food across seasons and regions should be considered.

Indo-Pacific sea surface temperature influences on failed consecutive rainy seasons over eastern Africa

Science.gov (United States)

Hoell, Andrew; Funk, Christopher C.

2014-01-01

Rainfall over eastern Africa (10°S–10°N; 35°E–50°E) is bimodal, with seasonal maxima during the "long rains" of March–April–May (MAM) and the "short rains" of October–November–December (OND). Below average precipitation during consecutive long and short rains seasons over eastern Africa can have devastating long-term impacts on water availability and agriculture. Here, we examine the forcing of drought during consecutive long and short rains seasons over eastern Africa by Indo-Pacific sea surface temperatures (SSTs). The forcing of eastern Africa precipitation and circulation by SSTs is tested using ten ensemble simulations of a global weather forecast model forced by 1950–2010 observed global SSTs. Since the 1980s, Indo-Pacific SSTs have forced more frequent droughts spanning consecutive long and short rains seasons over eastern Africa. The increased frequency of dry conditions is linked to warming SSTs over the Indo-west Pacific and to a lesser degree to Pacific Decadal Variability. During MAM, long-term warming of tropical west Pacific SSTs from 1950–2010 has forced statistically significant precipitation reductions over eastern Africa. The warming west Pacific SSTs have forced changes in the regional lower tropospheric circulation by weakening the Somali Jet, which has reduced moisture and rainfall over the Horn of Africa. During OND, reductions in precipitation over recent decades are oftentimes overshadowed by strong year-to-year precipitation variability forced by the Indian Ocean Dipole and the El Niño–Southern Oscillation.

An empirical system for probabilistic seasonal climate prediction

Science.gov (United States)

Eden, Jonathan; van Oldenborgh, Geert Jan; Hawkins, Ed; Suckling, Emma

2016-04-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961-2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño-Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

Long lead statistical forecasts of area burned in western U.S. wildfires by ecosystem province

Science.gov (United States)

Westerling, A.L.; Gershunov, A.; Cayan, D.R.; Barnett, T.P.

2002-01-01

A statistical forecast methodology exploits large-scale patterns in monthly U.S. Climatological Division Palmer Drought Severity Index (PDSI) values over a wide region and several seasons to predict area burned in western U.S. wildfires by ecosystem province a season in advance. The forecast model, which is based on canonical correlations, indicates that a few characteristic patterns determine predicted wildfire season area burned. Strong negative associations between anomalous soil moisture (inferred from PDSI) immediately prior to the fire season and area burned dominate in most higher elevation forested provinces, while strong positive associations between anomalous soil moisture a year prior to the fire season and area burned dominate in desert and shrub and grassland provinces. In much of the western U.S., above- and below-normal fire season forecasts were successful 57% of the time or better, as compared with a 33% skill for a random guess, and with a low probability of being surprised by a fire season at the opposite extreme of that forecast.

Spectral discrimination of macrophyte species during different seasons in a tropical wetland using in-situ hyperspectral remote sensing

Science.gov (United States)

Saluja, Ridhi; Garg, J. K.

2017-10-01

Wetlands, one of the most productive ecosystems on Earth, perform myriad ecological functions and provide a host of ecological services. Despite their ecological and economic values, wetlands have experienced significant degradation during the last century and the trend continues. Hyperspectral sensors provide opportunities to map and monitor macrophyte species within wetlands for their management and conservation. In this study, an attempt has been made to evaluate the potential of narrowband spectroradiometer data in discriminating wetland macrophytes during different seasons. main objectives of the research were (1) to determine whether macrophyte species could be discriminated based on in-situ hyperspectral reflectance collected over different seasons and at each measured waveband (400-950nm), (2) to compare the effectiveness of spectral reflectance and spectral indices in discriminating macrophyte species, and (3) to identify spectral wavelengths that are most sensitive in discriminating macrophyte species. Spectral characteristics of dominant wetland macrophyte species were collected seasonally using SVC GER 1500 portable spectroradiometer over the 400 to 1050nm spectral range at 1.5nm interval, at the Bhindawas wetland in the state of Haryana, India. Hyperspectral observations were pre-processed and subjected to statistical analysis, which involved a two-step approach including feature selection (ANOVA and KW test) and feature extraction (LDA and PCA). Statistical analysis revealed that the most influential wavelengths for discrimination were distributed along the spectral profile from visible to the near-infrared regions. The results suggest that hyperspectral data can be used discriminate wetland macrophyte species working as an effective tool for advanced mapping and monitoring of wetlands.

Recent Changes in Arctic Sea Ice Melt Onset, Freeze-Up, and Melt Season Length

Science.gov (United States)

Markus, Thorsten; Stroeve, Julienne C.; Miller, Jeffrey

2010-01-01

In order to explore changes and trends in the timing of Arctic sea ice melt onset and freeze-up and therefore melt season length, we developed a method that obtains this information directly from satellite passive microwave data, creating a consistent data set from 1979 through present. We furthermore distinguish between early melt (the first day of the year when melt is detected) and the first day of continuous melt. A similar distinction is made for the freeze-up. Using this method we analyze trends in melt onset and freeze-up for 10 different Arctic regions. In all regions except for the Sea of Okhotsk, which shows a very slight and statistically insignificant positive trend (O.4 days/decade), trends in melt onset are negative, i.e. towards earlier melt. The trends range from -1.0day/decade for the Bering Sea to -7.3 days/decade for the East Greenland Sea. Except for the Sea of Okhotsk all areas also show a trend towards later autumn freeze onset. The Chukchi/Beaufort Seas and Laptev/East Siberian Seas observe the strongest trends with 7 days/decade. For the entire Arctic, the melt season length has increased by about 20 days over the last 30 years. Largest trends of over 1O days/decade are seen for Hudson Bay, the East Greenland Sea the Laptev/East Siberian Seas, and the Chukchi/Beaufort Seas. Those trends are statistically significant a1 the 99% level.

PRODUCTIVITY OF MAIZE (ZEA MAYS) BASED INTERCROPPING SYSTEM DURING KHARIF SEASON UNDER RED AND LATERITIC TRACT OF WEST BENGAL

OpenAIRE

M K MANDAL; M BANERJEE; H BANERJEE; A ALIPATRA; G C MALIK

2014-01-01

A FIELD EXPERIMENT WAS CARRIED OUT DURING KHARIF SEASON OF 2010 AND 2011 AT SRINIKETAN RESEARCH FARM, VISVA BHARTI, WEST BENGAL. THE GRAIN YILED AND STOVER YIELD OF MAIZE WERE SIGNIFICANTLY HIGHER IN CASE OF PURE STAND OF MAIZE THAN EITHER OF ITS INTERCROPPING SYSTEMS WITH LEGUMES, WHILE THE COB YILED WAS HIGHEST IN THE MAIZE WITH SOYBEAN (1:2) INTERCROPPING SYSTEM AND IT WAS STATISTICALLY AT PAR WITH THE YIELD OBTAINED IN SOLE MAIZE. THE GRAIN YIELD OF LEGUMES WAS HIGHEST IN MAIZE WITH GROUN...

Seasonality of the activity pattern of Callithrix penicillata (Primates, Callitrichidae in the cerrado (scrub savanna vegetation

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S. L. Vilela

Full Text Available Two wild groups of Callithrix penicillata, the Black Pincelled Marmoset, were observed from January to September 1998, in two areas, one an area of dense scrub savanna vegetation (cerrado and the other, a semidecidual woodland (cerradão, both within the boundaries of the Ecological Reserve of IBGE (Brazilian Institute of Geography and Statistics, in an environmentally protected area, the APA (Portuguese abbreviation for "environmental protected area" Gama/Cabeça-de-Veado, Brasília, DF. The behavioral data collected during the rainy (January 15 to April 15 and dry season (June 1 to September 15 were compared. Because of the proximity to the Reserve facilities, the group from the dense scrub savanna vegetation (CD was submitted to antropic impacts different from the group in the semidecidual woodland (CE, which was using as territory an area that had been suffering from man-made fires every two years as part of a long-term experimental project on fire impacts. The behavioral data was quantified by instantaneous cross-section ("scan sampling" every ten minutes with records of locomotion, rest, foraging for insects, use of exudate, and feeding. During the whole year, the greatest percentage of time spent by CE and CD was in foraging for insects, with 44% and 39%, respectively. It was evident when comparing the data for the two seasons that, for both groups, foraging for insects was more intense during the dry season, possibly to complement the shortage of food, and locomotion increased during the rainy season. The greater the availability and distribution of fruit in the areas, the greater the locomotion of the groups to obtain these resources. None of the other behavioral patterns, including the use of exudates, presented significant differences between the two seasons. Both groups foraged more frequently during the dry season and locomoted more during the rainy one.

Entropy of stable seasonal rainfall distribution in Kelantan

Science.gov (United States)

Azman, Muhammad Az-zuhri; Zakaria, Roslinazairimah; Satari, Siti Zanariah; Radi, Noor Fadhilah Ahmad

2017-05-01

Investigating the rainfall variability is vital for any planning and management in many fields related to water resources. Climate change can gives an impact of water availability and may aggravate water scarcity in the future. Two statistics measurements which have been used by many researchers to measure the rainfall variability are variance and coefficient of variation. However, these two measurements are insufficient since rainfall distribution in Malaysia especially in the East Coast of Peninsular Malaysia is not symmetric instead it is positively skewed. In this study, the entropy concept is used as a tool to measure the seasonal rainfall variability in Kelantan and ten rainfall stations were selected. In previous studies, entropy of stable rainfall (ESR) and apportionment entropy (AE) were used to describe the rainfall amount variability during years for Australian rainfall data. In this study, the entropy of stable seasonal rainfall (ESSR) is suggested to model rainfall amount variability during northeast monsoon (NEM) and southwest monsoon (SWM) seasons in Kelantan. The ESSR is defined to measure the long-term average seasonal rainfall amount variability within a given year (1960-2012). On the other hand, the AE measures the rainfall amounts variability across the months. The results of ESSR and AE values show that stations in east coastline are more variable as compared to other stations inland for Kelantan rainfall. The contour maps of ESSR for Kelantan rainfall stations are also presented.

Statistically significant dependence of the Xaa-Pro peptide bond conformation on secondary structure and amino acid sequence

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Leitner Dietmar

2005-04-01

Full Text Available Abstract Background A reliable prediction of the Xaa-Pro peptide bond conformation would be a useful tool for many protein structure calculation methods. We have analyzed the Protein Data Bank and show that the combined use of sequential and structural information has a predictive value for the assessment of the cis versus trans peptide bond conformation of Xaa-Pro within proteins. For the analysis of the data sets different statistical methods such as the calculation of the Chou-Fasman parameters and occurrence matrices were used. Furthermore we analyzed the relationship between the relative solvent accessibility and the relative occurrence of prolines in the cis and in the trans conformation. Results One of the main results of the statistical investigations is the ranking of the secondary structure and sequence information with respect to the prediction of the Xaa-Pro peptide bond conformation. We observed a significant impact of secondary structure information on the occurrence of the Xaa-Pro peptide bond conformation, while the sequence information of amino acids neighboring proline is of little predictive value for the conformation of this bond. Conclusion In this work, we present an extensive analysis of the occurrence of the cis and trans proline conformation in proteins. Based on the data set, we derived patterns and rules for a possible prediction of the proline conformation. Upon adoption of the Chou-Fasman parameters, we are able to derive statistically relevant correlations between the secondary structure of amino acid fragments and the Xaa-Pro peptide bond conformation.

No evidence of seasonality of birth in adult type 2 diabetes in Denmark

DEFF Research Database (Denmark)

Jensen, Camilla Bjørn; Zimmermann, Esther; Gamborg, M

2015-01-01

on the risk of type 2 diabetes was assessed using Cox regression, with month or season of birth as the predictor. The underlying time variable was age, and follow-up started in 1977 or at age 30 years. RESULTS: The study population consisted of 223,099 people, of whom 12,486 developed adult type 2 diabetes......AIMS/HYPOTHESIS: The season of birth might influence prenatal circumstances, which may influence the risk of developing type 2 diabetes. The aim of this study was to determine whether the diagnosis of type 2 diabetes in Denmark changed with the season of birth. METHODS: This study used data from....... Using January as the reference month, the risk of type 2 diabetes by month of birth was not statistically different for any of the 11 comparative birth months. Grouping month of birth into seasons (spring was the reference) gave essentially similar results, showing no difference in the risk of type 2...

Seasonal Nitrogen Cycles on Pluto

Science.gov (United States)

Hansen, Candice J.; Paige, David A.

1996-01-01

A thermal model, developed to predict seasonal nitrogen cycles on Triton, has been modified and applied to Pluto. The model was used to calculate the partitioning of nitrogen between surface frost deposits and the atmosphere, as a function of time for various sets of input parameters. Volatile transport was confirmed to have a significant effect on Pluto's climate as nitrogen moved around on a seasonal time scale between hemispheres, and sublimed into and condensed out of the atmosphere. Pluto's high obliquity was found to have a significant effect on the distribution of frost on its surface. Conditions that would lead to permanent polar caps on Triton were found to lead to permanent zonal frost bands on Pluto. In some instances, frost sublimed from the middle of a seasonal cap outward, resulting in a "polar bald spot". Frost which was darker than the substrate did not satisfy observables on Pluto, in contrast to our findings for Triton. Bright frost (brighter than the substrate) came closer to matching observables. Atmospheric pressure varied seasonally. The amplitudes, and to a lesser extent the phase, of the variation depended significantly on frost and substrate properties. Atmospheric pressure was found to be determined both by Pluto's distance from the sun and by the subsolar latitude. In most cases two peaks in atmospheric pressure were observed annually: a greater one associated with the sublimation of the north polar cap just as Pluto receded from perihelion, and a lesser one associated with the sublimation of the south polar cap as Pluto approached perihelion. Our model predicted frost-free dark substrate surface temperatures in the 50 to 60 K range, while frost temperatures typically ranged between 30 to 40 K. Temporal changes in frost coverage illustrated by our results, and changes in the viewing geometry of Pluto from the Earth, may be important for interpretation of ground-based measurements of Pluto's thermal emission.

Seasonal Drought Prediction: Advances, Challenges, and Future Prospects

Science.gov (United States)

Hao, Zengchao; Singh, Vijay P.; Xia, Youlong

2018-03-01

Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.

Study of Seasonal Variation in Groundwater Quality of Sagar City (India by Principal Component Analysis

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Hemant Pathak

2011-01-01

Full Text Available Groundwater is one of the major resources of the drinking water in Sagar city (India.. In this study 15 sampling station were selected for the investigations on 14 chemical parameters. The work was carried out during different months of the pre-monsoon, monsoon and post-monsoon seasons in June 2009 to June 2010. The multivariate statistics such as principal component and cluster analysis were applied to the datasets to investigate seasonal variations in groundwater quality. Principal axis factoring has been used to observe the mode of association of parameters and their interrelationships, for evaluating water quality. Average value of BOD, COD, ammonia and iron was high during entire study period. Elevated values of BOD and ammonia in monsoon, slightly more value of BOD in post-monsoon, BOD, ammonia and iron in pre-monsoon period reflected contribution on temporal effect on groundwater. Results of principal component analysis evinced that all the parameters equally and significantly contribute to groundwater quality variations. Factor 1 and factor 2 analysis revealed the DO value deteriorate due to organic load (BOD/Ammonia in different seasons. Hierarchical cluster analysis grouped 15 stations into four clusters in monsoon, five clusters in post-monsoon and five clusters in pre-monsoon with similar water quality features. Clustered group at monsoon, post-monsoon and pre-monsoon consisted one station exhibiting significant spatial variation in physicochemical composition. The anthropogenic nitrogenous species, as fallout from modernization activities. The study indicated that the groundwater sufficiently well oxygenated and nutrient-rich in study places.

Seasonal variation of mood and behaviour in a healthy middle-aged population in Japan.

Science.gov (United States)

Okawa, M; Shirakawa, S; Uchiyama, M; Oguri, M; Kohsaka, M; Mishima, K; Sakamoto, K; Inoue, H; Kamei, K; Takahashi, K

1996-10-01

A population survey of seasonality in six representative cities in Japan was conducted using the Japanese version of the Seasonal Pattern Assessment Questionnaire (SPAQ). The questionnaires were given to 951 parents (male: female ratio 1:1 age range 34-59 years) of high-school students. Significant regional differences in seasonal variations of mood, length of sleep, and weight were observed; the proportion of individuals reporting high seasonality in the two northern cities was significantly higher than that in the other areas. These results provide evidence for a northern predominance in the prevalence of seasonal affective disorder in Japan.

CONFIDENCE LEVELS AND/VS. STATISTICAL HYPOTHESIS TESTING IN STATISTICAL ANALYSIS. CASE STUDY

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ILEANA BRUDIU

2009-05-01

Full Text Available Estimated parameters with confidence intervals and testing statistical assumptions used in statistical analysis to obtain conclusions on research from a sample extracted from the population. Paper to the case study presented aims to highlight the importance of volume of sample taken in the study and how this reflects on the results obtained when using confidence intervals and testing for pregnant. If statistical testing hypotheses not only give an answer "yes" or "no" to some questions of statistical estimation using statistical confidence intervals provides more information than a test statistic, show high degree of uncertainty arising from small samples and findings build in the "marginally significant" or "almost significant (p very close to 0.05.

An intercomparison of approaches for improving operational seasonal streamflow forecasts

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P. A. Mendoza

2017-07-01

Full Text Available For much of the last century, forecasting centers around the world have offered seasonal streamflow predictions to support water management. Recent work suggests that the two major avenues to advance seasonal predictability are improvements in the estimation of initial hydrologic conditions (IHCs and the incorporation of climate information. This study investigates the marginal benefits of a variety of methods using IHCs and/or climate information, focusing on seasonal water supply forecasts (WSFs in five case study watersheds located in the US Pacific Northwest region. We specify two benchmark methods that mimic standard operational approaches – statistical regression against IHCs and model-based ensemble streamflow prediction (ESP – and then systematically intercompare WSFs across a range of lead times. Additional methods include (i statistical techniques using climate information either from standard indices or from climate reanalysis variables and (ii several hybrid/hierarchical approaches harnessing both land surface and climate predictability. In basins where atmospheric teleconnection signals are strong, and when watershed predictability is low, climate information alone provides considerable improvements. For those basins showing weak teleconnections, custom predictors from reanalysis fields were more effective in forecast skill than standard climate indices. ESP predictions tended to have high correlation skill but greater bias compared to other methods, and climate predictors failed to substantially improve these deficiencies within a trace weighting framework. Lower complexity techniques were competitive with more complex methods, and the hierarchical expert regression approach introduced here (hierarchical ensemble streamflow prediction – HESP provided a robust alternative for skillful and reliable water supply forecasts at all initialization times. Three key findings from this effort are (1 objective approaches supporting

Short Term Prediction of PM10 Concentrations Using Seasonal Time Series Analysis

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Hamid Hazrul Abdul

2016-01-01

Full Text Available Air pollution modelling is one of an important tool that usually used to make short term and long term prediction. Since air pollution gives a big impact especially to human health, prediction of air pollutants concentration is needed to help the local authorities to give an early warning to people who are in risk of acute and chronic health effects from air pollution. Finding the best time series model would allow prediction to be made accurately. This research was carried out to find the best time series model to predict the PM10 concentrations in Nilai, Negeri Sembilan, Malaysia. By considering two seasons which is wet season (north east monsoon and dry season (south west monsoon, seasonal autoregressive integrated moving average model were used to find the most suitable model to predict the PM10 concentrations in Nilai, Negeri Sembilan by using three error measures. Based on AIC statistics, results show that ARIMA (1, 1, 1 × (1, 0, 012 is the most suitable model to predict PM10 concentrations in Nilai, Negeri Sembilan.

ASPECTS OF SEASONALITY TOURISTIC ACTIVITY SPECIFIC TO MAMAIA STATION

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Mariana C. JUGANARU

2017-05-01

Full Text Available The study of phenomena and social-economic processes under the aspect of their evolution in time, mainly on a short term or intra-annual represents a preoccupation at a micro and macroeconomic level. For the tourism operators, this process includes knowing the touristic market and the anticipations of its evolution, as an important condition for taking decisions in their activity. The aim of this work is to analyze the touristic activity according to seasonality in Mamaia station, using qualitative and quantitative research methods. The study is important through the aspects that emphasize the specific evolution of the touristic activity from this station. For this aim, a database was formed by the monthly values of three indicators of the touristic activity (number of arrivals, number of overnights and the average duration of the stay from the period 2010-2016, using a series of statistic and econometric instruments. The results of the research can be proved by the units that maintain or are connected to the touristic activity, but also to the local administration, in making up the attenuation strategy of the touristic activity concerning the seasonality of Mamaia. Also, the work is a case study for the work with the students (especially, for tourism economy, applied statistics in tourism and marketing.

Seasonal Influenza: An Overview

Science.gov (United States)

Li, Christina; Freedman, Marian

2009-01-01

Seasonal influenza is a major cause of morbidity and mortality in the United States. It also has major social and economic consequences in the form of high rates of absenteeism from school and work as well as significant treatment and hospitalization costs. In fact, annual influenza epidemics and the resulting deaths and lost days of productivity…

Increased health risk in subjects with high self-reported seasonality.

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Nicolas M Øyane

Full Text Available BACKGROUND: Seasonal variations in mood and behaviour, termed seasonality, are commonly reported in the general population. As a part of a large cross-sectional health survey in Hordaland, Norway, we investigated the relationship between seasonality, objective health measurements and health behaviours. METHODOLOGY/PRINCIPAL FINDINGS: A total of 11,545 subjects between 40-44 years old participated, completing the Global Seasonality Score, measuring seasonality. Waist/hip circumference, BMI and blood pressure were measured, and blood samples were analyzed for total cholesterol, HDL cholesterol, triglycerides and glucose. Subjects also completed a questionnaire on miscellaneous health behaviours (exercise, smoking, alcohol consumption. Hierarchical linear regression analyses were used to investigate associations between seasonality and objective health measurements, while binary logistic regression was used for analysing associations between seasonality and health behaviours. Analyses were adjusted for sociodemographic factors, month of questionnaire completion and sleep duration. Seasonality was positively associated with high waist-hip-ratio, BMI, triglyceride levels, and in men high total cholesterol. Seasonality was negatively associated with HDL cholesterol. In women seasonality was negatively associated with prevalence of exercise and positively associated with daily cigarette smoking. CONCLUSIONS/SIGNIFICANCE: High seasonality was associated with objective health risk factors and in women also with health behaviours associated with an increased risk for cardiovascular disease.

Soil Dust Aerosols and Wind as Predictors of Seasonal Meningitis Incidence in Niger

Science.gov (United States)

Perez Garcia Pando, Carlos; Stanton, Michelle C.; Diggle, Peter J.; Trzaska, Sylwia; Miller, Ron L.; Perlwitz, Jan P.; Baldasano, Jose M.; Cuevas, Emilio; Ceccato, Pietro; Yaka, Pascal;

Economic burden of malaria in rural Tanzania: variations by socioeconomic status and season.

Science.gov (United States)

Somi, Masha F; Butler, James R G; Vahid, Farshid; Njau, Joseph D; Kachur, S Patrick; Abdulla, Salim

2007-10-01

To determine the economic burden of malaria in a rural Tanzanian setting and identify any differences by socioeconomic status and season. Interviews of 557 households in south eastern Tanzania between May and December 2004, on consumption and malaria-related costs. Malaria-related expenses were significantly higher in the dry, non-malarious season than in the rainy season. Households sought treatment more frequently and from more expensive service providers in the dry season, when they have more money. Malaria expenses did not vary significantly across socioeconomic status quintiles, but poorer households spent a higher proportion of their consumption in both seasons. Poorer households bear a greater economic burden from malaria relative to their consumption than better-off households. Households are particularly vulnerable to malaria in the rainy season, when malaria prevalence is highest but liquidity is lower. Alternative strategies to assist households to cope with seasonal liquidity issues, including insurance, should be investigated.

Secular and seasonal trends of Neospora abortion in California dairy cows.

Science.gov (United States)

Thurmond, M C; Anderson, M L; Blanchard, P C

1995-06-01

This study was undertaken to determine if the proportion of dairy cow abortions attributable to Neospora sp. infection increased or occurred in a seasonal cycle during a 6-yr period. Abortions caused by Neospora sp. were tallied for all fetuses submitted to the Tulare branch of the California Veterinary Diagnostic Laboratory between January 1985 and December 1990. Regression analysis of 221 cases of Neospora among 762 fetuses submitted showed a weak increasing secular trend (P = 0.053, r2 = 0.05), with predicted monthly proportions at the beginning and end of the 6 yr of 0.16 and 0.33, respectively. Using a Kolmogorov-Smirnov-type statistic, comparison of the 12-mo distribution of Neospora sp. cases and a hypothetical distribution of cows at risk of aborting found about 16% of variation in cases was attributable to season (P fall. Results indicate that Neospora sp. abortion in California dairy cows is not new or recently emerging and that seasonally related factors influence some of the risk of abortion. Results suggest that Neospora sp. has contributed to the high dairy cow abortion rate for many years, and that seasonally varying exposures may predispose to transmission or recrudescence of infection.

Out-of-season recollection of drug use for seasonal IgE-mediated rhinitis

DEFF Research Database (Denmark)

Bødtger, Uffe; Malling, Hans-Jørgen; Poulsen, Lars K

2005-01-01

in a double-blind study. Drug use was recorded daily during the season 2000 and out-seasonally 6 months after the seasons 1999 and 2000. The mean daily drug use was transformed into a 4-point categorical scale for simplicity and was calculated for the out-seasonal rating and for 6 in-seasonal periods...

Seasonal variation of leaf ecophysiological traits of Iris variegata observed in two consecutive years in natural habitats with contrasting light conditions

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Živković Uroš

2015-01-01

Full Text Available The amount and pattern of individual phenotypic responses to seasonal changes in environmental conditions were determined in clones of Iris variegata growing in differing light habitats. For the purpose of the study, 97 clonal plants of the rhizomatous herb I. variegata that experienced different light conditions in their two native habitats were selected: one along the top and slope of sand dunes and one in woodland understories. Two fully expanded leaves that had developed during spring, summer and fall in two consecutive years were sampled from each of these clones. Six leaf traits affecting the photosynthetic rate of a plant − morphological (specific leaf area, anatomical (stomatal density and physiological (total chlorophyll concentration, chlorophyll a/chlorophyll b ratio, carotenoid concentration, chlorophyll a/carotenoid ratio exhibited significant plastic responses in the two different light habitats. To test whether these traits differ between exposed and shaded habitats as well as during different vegetation periods, we used the repeated model analysis of variance (ANOVA. Results of the repeated ANOVA revealed statistically significant effects of year, habitat and period of vegetation season. Patterns of changes during growing seasons were year-specific for almost all analyzed traits. [Projekat Ministarstva nauke Republike Srbije, br. OI 173025: Evolution in heterogeneous environments: mechanisms of adaptation, biomonitoring and conservation of biodiversity

Assets. Biological Assets. The Seasonal Model in Agriculture

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Atanasiu Pop

2008-07-01

Full Text Available In order to support the agricultural exploitation we tried in this paper to develop a model that involves a seasonal component at entity’s level. Consequently, we made a study to an exploitation acting in the vegetal field by collecting accounting informations from the data base entity and by informations that were processed using different statistical functions. So, through the proposed model we try to make certain previsions taking into account the economic situation in which the agricultural exploitation works.

Impact of shade on outdoor thermal comfort-a seasonal field study in Tempe, Arizona.

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Middel, Ariane; Selover, Nancy; Hagen, Björn; Chhetri, Nalini

2016-12-01

Shade plays an important role in designing pedestrian-friendly outdoor spaces in hot desert cities. This study investigates the impact of photovoltaic canopy shade and tree shade on thermal comfort through meteorological observations and field surveys at a pedestrian mall on Arizona State University's Tempe campus. During the course of 1 year, on selected clear calm days representative of each season, we conducted hourly meteorological transects from 7:00 a.m. to 6:00 p.m. and surveyed 1284 people about their thermal perception, comfort, and preferences. Shade lowered thermal sensation votes by approximately 1 point on a semantic differential 9-point scale, increasing thermal comfort in all seasons except winter. Shade type (tree or solar canopy) did not significantly impact perceived comfort, suggesting that artificial and natural shades are equally efficient in hot dry climates. Globe temperature explained 51 % of the variance in thermal sensation votes and was the only statistically significant meteorological predictor. Important non-meteorological factors included adaptation, thermal comfort vote, thermal preference, gender, season, and time of day. A regression of subjective thermal sensation on physiological equivalent temperature yielded a neutral temperature of 28.6 °C. The acceptable comfort range was 19.1 °C-38.1 °C with a preferred temperature of 20.8 °C. Respondents exposed to above neutral temperature felt more comfortable if they had been in air-conditioning 5 min prior to the survey, indicating a lagged response to outdoor conditions. Our study highlights the importance of active solar access management in hot urban areas to reduce thermal stress.

An evaluation of the seasonality of veterinary treatments for lameness in UK dairy cattle.

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Laven, R A; Lawrence, K R

2006-10-01

Of the 4 main diseases causing lameness in UK dairy cattle, 2 (digital dermatitis and foul-in-the-foot, or interdigital necrobacillosis) are infectious diseases that are commonly associated with similar underfoot conditions, and 2 (sole ulcer and white-line disease) result from subclinical laminitis. Comparison of the seasonality of these 2 diseases can identify whether their own unique risk factors are more important than the risk factors they share. Using a database from 46 veterinarians distributed across the United Kingdom, the seasonality of treatments for these 4 diseases was evaluated. This analysis showed that the seasonality of lameness in UK dairy cattle was significantly reduced in comparison with previous reports from the 1980s. This was primarily due to 1) a reduction in the seasonality of digital dermatitis (outbreaks of which accounted for 6.7% of veterinary reports), with only 60% of reports during the winter as opposed to 72% in earlier studies, and 2) a change in the seasonality of white-line disease from a disease that was most commonly seen in the winter (55% of reports) to a disease that was most commonly reported in the late summer or early autumn, with significantly more reports in August and October than in February. Comparison of the seasonality of digital dermatitis and foul-in-the-foot showed a significant difference in the seasonality of the 2 diseases, with foul-in-the-foot being significantly more common compared with digital dermatitis in June and August. This implies that significant risk factors exist for digital dermatitis that are not as important for foul-in-the-foot. The difference in the seasonality of sole ulcer and white-line disease was even more marked, with white-line disease being significantly more common than sole ulcer from August to October, despite these diseases being more closely linked in the literature than digital dermatitis and foul-in-the-foot. This comparison shows that the seasonality of lameness has changed

Seasonal Strength Performance and Its Relationship with Training Load on Elite Runners

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Carlos Balsalobre-Fernández

2015-01-01

Full Text Available The aim of this study was to analyze the time-course of force production of elite middle and long-distance runners throughout an entire season and at the end of the off-season, as well as its relationships with training load and hormonal responses. Training load was recorded daily throughout an entire season by measuring and evaluating the session distance (km, training zone and session-RPE in a group of 15 elite middle and long-distance runners (12 men, 3 women; age = 26.3 ± 5.1yrs, BMI = 19.7 ± 1.1. Also, basal salivary-free cortisol levels were measured weekly, and 50-metre sprints, mean propulsive velocity (MPV, mean propulsive power (MPP, repetition maximum (RM and peak rate of force development (RFD of half-squats were measured 4 times during the season, and once more after the off-season break. There were no significant variations in force production during the season or after the off-season break, except for the RFD (-30.2%, p = 0.005 values, which changed significantly from the beginning to the end of the season. Significant correlations were found between session-RPE and MPV (r = -0.650, p = 0.004, MPP (r = -0.602, p = 0.009, RM (r = -0.650, p = 0.004, and the 50-metre sprint (r = 0.560, p = 0.015. Meanwhile, salivary-free cortisol correlated significantly with the 50-metre sprint (r = 0.737, p < 0.001 and the RM ( r = -0.514, p = 0.025. Finally, the training zone correlated with the 50-metre sprint (r = -0.463, p = 0.041. Session-RPE, training zone and salivary-free cortisol levels are related to force production in elite middle and long-distance runners. Monitoring these variables could be a useful tool in controlling the training programs of elite athletes.

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

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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.

Seasonal prolactin secretion and its role in seasonal reproduction: a review.

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Curlewis, J D

1992-01-01

The majority of seasonally breeding mammals show a seasonal pattern of prolactin secretion with peak concentrations in spring or summer and a nadir in autumn or winter. Photoperiod influences prolactin secretion via its effects on the secretion of the pineal hormone melatonin. Preliminary evidence suggests that the effects of melatonin on both prolactin and gonadotrophin secretion are via a common target area, possibly within the anterior hypothalamus, and that differences in response to photoperiod may be due to differences in the processing and/or interpretation of the melatonin signal. In contrast to seasonal gonadotrophin secretion, the seasonal changes in prolactin are not due to changes in the sensitivity of a feedback loop and so must be due to direct effects on the hypothalamic pathways that control prolactin secretion. Little else can be said with confidence about the neuroendocrine mechanisms that lead to the seasonal changes in prolactin secretion. Dopamine and noradrenaline turnover in the arcuate nucleus and median eminence decrease under short daylength. If catecholamine turnover in these structures is positively correlated with catecholamine concentrations in the long or short hypophysial portal vessels, it is unlikely that the decrease in prolactin concentration in winter is due to the effects of increased concentrations of dopamine or noradrenaline in the portal vessels. There is, however, evidence for increased pituitary sensitivity to dopamine under short daylength, so increased dopamine concentrations may not be required for suppression of prolactin secretion at this time. In addition to the diminished secretion of prolactin under short daylength, rate of prolactin synthesis and pituitary content of prolactin also decline although the mechanisms that regulate these changes are poorly understood. Although all seasonal breeders show a seasonal change in prolactin secretion, there are continuously breeding species in which prolactin secretion is

Seasonal variation in child mortality in rural Guinea-Bissau.

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Nielsen, Bibi Uhre; Byberg, Stine; Aaby, Peter; Rodrigues, Amabelia; Benn, Christine Stabell; Fisker, Ane Baerent

2017-07-01

In many African countries, child mortality is higher in the rainy season than in the dry season. We investigated the effect of season on child mortality by time periods, sex and age in rural Guinea-Bissau. Bandim health project follows children under-five in a health and demographic surveillance system in rural Guinea-Bissau. We compared the mortality in the rainy season (June to November) between 1990 and 2013 with the mortality in the dry season (December to May) in Cox proportional hazards models providing rainy vs. dry season mortality rate ratios (r/d-mrr). Seasonal effects were estimated in strata defined by time periods with different frequency of vaccination campaigns, sex and age (<1 month, 1-11 months, 12-59 months). Verbal autopsies were interpreted using InterVa-4 software. From 1990 to 2013, overall mortality was declined by almost two-thirds among 81 292 children (10 588 deaths). Mortality was 51% (95% ci: 45-58%) higher in the rainy season than in the dry season throughout the study period. The seasonal difference increased significantly with age, the r/d-mrr being 0.94 (0.86-1.03) among neonates, 1.57 (1.46-1.69) in post-neonatal infants and 1.83 (1.72-1.95) in under-five children (P for same effect <0.001). According to the InterVa, malaria deaths were the main reason for the seasonal mortality difference, causing 50% of all deaths in the rainy season, but only if the InterVa included season of death, making the argument self-confirmatory. The mortality declined throughout the study, yet rainy season continued to be associated with 51% higher overall mortality. © 2017 The Authors. Tropical Medicine & International Health Published by John Wiley & Sons Ltd.

Seasonal Prediction of Regional Surface Air Temperature and First-flowering Date in South Korea using Dynamical Downscaling

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Ahn, J. B.; Hur, J.

2015-12-01

The seasonal prediction of both the surface air temperature and the first-flowering date (FFD) over South Korea are produced using dynamical downscaling (Hur and Ahn, 2015). Dynamical downscaling is performed using Weather Research and Forecast (WRF) v3.0 with the lateral forcing from hourly outputs of Pusan National University (PNU) coupled general circulation model (CGCM) v1.1. Gridded surface air temperature data with high spatial (3km) and temporal (daily) resolution are obtained using the physically-based dynamical models. To reduce systematic bias, simple statistical correction method is then applied to the model output. The FFDs of cherry, peach and pear in South Korea are predicted for the decade of 1999-2008 by applying the corrected daily temperature predictions to the phenological thermal-time model. The WRF v3.0 results reflect the detailed topographical effect, despite having cold and warm biases for warm and cold seasons, respectively. After applying the correction, the mean temperature for early spring (February to April) well represents the general pattern of observation, while preserving the advantages of dynamical downscaling. The FFD predictabilities for the three species of trees are evaluated in terms of qualitative, quantitative and categorical estimations. Although FFDs derived from the corrected WRF results well predict the spatial distribution and the variation of observation, the prediction performance has no statistical significance or appropriate predictability. The approach used in the study may be helpful in obtaining detailed and useful information about FFD and regional temperature by accounting for physically-based atmospheric dynamics, although the seasonal predictability of flowering phenology is not high enough. Acknowledgements This work was carried out with the support of the Rural Development Administration Cooperative Research Program for Agriculture Science and Technology Development under Grant Project No. PJ009953 and

Pupal productivity in rainy and dry seasons: findings from the impact survey of a randomised controlled trial of dengue prevention in Guerrero, Mexico

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Abel Jiménez-Alejo

2017-05-01

Full Text Available Abstract Background The follow-up survey of a cluster-randomised controlled trial of evidence-based community mobilisation for dengue control in Nicaragua and Mexico included entomological information from the 2012 rainy and dry seasons. We used data from the Mexican arm of the trial to assess the impact of the community action on pupal production of the dengue vector Aedes aegypti in both rainy and dry seasons. Methods Trained field workers inspected household water containers in 90 clusters and collected any pupae or larvae present for entomological examination. We calculated indices of pupae per person and pupae per household, and traditional entomological indices of container index, household index and Breteau index, and compared these between rainy and dry seasons and between intervention and control clusters, using a cluster t-test to test significance of differences. Results In 11,933 houses in the rainy season, we inspected 40,323 containers and found 7070 Aedes aegypti pupae. In the dry season, we inspected 43,461 containers and counted 6552 pupae. All pupae and entomological indices were lower in the intervention clusters (IC than in control clusters (CC in both the rainy season (RS and the dry season (DS: pupae per container 0.12 IC and 0.24 CC in RS, and 0.10 IC and 0.20 CC in DS; pupae per household 0.46 IC and 0.82 CC in RS, and 0.41 IC and 0.83 CC in DS; pupae per person 0.11 IC and 0.19 CC in RS, and 0.10 IC and 0.20 CC in DS; household index 16% IC and 21% CC in RS, and 12.1% IC and 17.9% CC in DS; container index 7.5% IC and 11.5% CC in RS, and 4.6% IC and 7.1% CC in DS; Breteau index 27% IC and 36% CC in RS, and 19% IC and 29% CC in DS. All differences between the intervention and control clusters were statistically significant, taking into account clustering. Conclusions The trial intervention led to significant decreases in pupal and conventional entomological indices in both rainy and dry seasons. Trial registration ISRCTN

SEASONAL AVERAGE FLOW IN RÂUL NEGRU HYDROGRAPHIC BASIN

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VIGH MELINDA

2015-03-01

Full Text Available The Râul Negru hydrographic basin is a well individualised physical-geographical unit inside the Braşov Depression. The flow is controlled by six hydrometric stations placed on the main river and on two important tributaries. The data base for seasonal flow analysis contains the discharges from 1950-2012. The results of data analysis show that there significant space-time differences between multiannual seasonal averages. Some interesting conclusions can be obtained by comparing abundant and scarce periods. Flow analysis was made using seasonal charts Q = f(T. The similarities come from the basin’s relative homogeneity, and the differences from flow’s evolution and trend. Flow variation is analysed using variation coefficient. In some cases appear significant Cv values differences. Also, Cv values trends are analysed according to basins’ average altitude.

Seasonal biochemical changes in composition of body wall tissues of sea cucumber Apostichopus japonicus

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Gao, Fei; Xu, Qiang; Yang, Hongsheng

2011-03-01

Seasonal Variation in proximate, amino acid and fatty acid composition of the body wall of sea cucumber Apostichopus japonicus was evaluated. The proximate composition, except for ash content, changed significantly among seasons ( P<0.05). Alanine, glycine, glutamic acid and asparagic acid were the most abundant amino acids. Total amino acid and essential amino acid Contents both varied clearly with seasons ( P<0.05). 16:0 and 16:ln7 were the primary saturated fatty acid (SFA) and monounsaturated fatty acid (MUFA) respectively for all months. EPA (20:5n-3), AA (20:4n-6) and DHA (22:6n-3) were the major polyunsaturated fatty acids (PUFA). The proportions of SFA and PUFA yielded significant seasonal variations ( P<0.001), but MUFA did not changed significantly. The results indicated that the biochemical compositions of the body wall in A. japonicus were significantly influenced by seasons and that the body wall tissue is an excellent source of protein, MUFA and n-3 PUFA for humans.

Seasonality patterns of mood and behavior in the Old Order Amish.

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Patel, Falguni; Postolache, Nadine; Mohyuddin, Hira; Vaswani, Dipika; Balis, Theodora; Raheja, Uttam K; Postolache, Teodor T

2012-12-01

Although humans have become partially isolated from physical seasonal environmental changes through artificial lighting and temperature control, seasonal changes in mood and behavior have been described across hemispheres, continents, ethnicities and occupations. The Old Order Amish are more exposed than the general population to environmental seasonal changes both occupationally as well as through their limited use of electric light in the winter and air conditioning in the summer; yet, their seasonal changes in mood and behavior have not been previously studied. The aim of this study was to analyze seasonal patterns in mood and behavior in the Old Order Amish of Lancaster County, Pennsylvania, who returned completed Seasonal Pattern Assessment Questionnaires (SPAQ). Monthly seasonal patterns were analyzed with repeated measures ANOVAs, followed by a post hoc t-test if significant. The χ 2 was used for presence or absence of seasonal patterns for each item. More than 75% of the participants reported at least one seasonal change. More than 75 % endorsed seasonality in "feeling best" but only populations.

Consumer Acceptance Comparison Between Seasoned and Unseasoned Vegetables.

Science.gov (United States)

Feng, Yiming; Albiol Tapia, Marta; Okada, Kyle; Castaneda Lazo, Nuria Blanca; Chapman-Novakofski, Karen; Phillips, Carter; Lee, Soo-Yeun

2018-02-01

Recent findings show that approximately 87% of the U.S. population fail to meet the vegetable intake recommendations, with unpleasant taste of vegetables being listed as the primary reason for this shortfall. In this study, spice and herb seasoning was used to enhance palatability of vegetables, in order to increase consumer acceptance. In total, 749 panelists were screened and recruited as specific vegetable likers of the vegetable being tested or general vegetable likers. Four sessions were designed to evaluate the effect of seasoning within each type of vegetable, including broccoli, cauliflower, carrot, and green bean. Each panelist was only allowed to participate in one test session to evaluate only one vegetable type, so as to mitigate potential learning effect. Overall, the results showed that seasoned vegetables were significantly preferred over unseasoned vegetables (P trend of seasoned vegetable being preferred remained. The findings from this study demonstrate the effect of seasoning in enhancing consumer liking of vegetables, which may lead to increased consumption to be assessed in future studies. To improve the sensory properties of vegetables, masking the bitter taste of vegetables using spice and herb seasoning are gaining increasing attention. Our findings suggest that the overall liking of vegetables could be improved by incorporating spice and herb seasonings that are specifically formulated for each vegetable. Ultimately, developing and commercializing spice and herb seasonings may aid to increase vegetable consumption, as well as expanding the vegetable seasoning market. © 2018 The Authors Journal of Food Science published by Wiley Periodicals, Inc. on behalf of Institute of Food Technologists.

Changing Seasonality and the Role of the Shoulder Season - Evidence from Denamrk

DEFF Research Database (Denmark)

Sørensen, Nils Karl

2009-01-01

the issue of the shoulder season in a time series framework. Departing from a discussion of the nature of types of seasonal variation, a test is set up in order to examine the impact of the shoulder season. The test examines the impact on the mean share of hotel nights in the shoulder season months in two...

Simulation of gas supply and consumption during heating season; Simulacija opskrbe potrosaca plinom tijekom ogrjevne sezone

Energy Technology Data Exchange (ETDEWEB)

Oklopcic, Z [INA-Naftaplin, Zagreb (Croatia)

1997-12-31

In this paper stochastic simulation model of gas supply and consumption during heating season is described. The simulation of gas supply is based on constant import and domestic production and varying production of underground storage which depends on current needs and quantity of gas in the storage. The basis for consumption simulation is the stochastic relationship between gas consumption and mean daily air temperature and type of the day, expressed in the form of linear regression model. Mean daily air temperatures, as one of basic causes of daily gas consumption variations, are simulated, on the basis of statistical characteristics and own air temperature measurements, as a first order autoregression model. By using the developed simulation model the statistical characteristics (expectation, standard deviation) of daily gas consumption and the difference between maximum possible daily supply and consumption (delivery safety margin) are derived for all days in the season. The definition of gas delivery safety is given and critical delivery probabilities for all days in the season and different safety margins are determined. Also, statistical characteristics of critical delivery duration depending on gas reserves status for underground storage is predicted. Predicted gas storage delivery rate is compared against predicted requirements, and on the basis of this comparison possible bottlenecks in gas delivery to consumers and course of future actions are indicated. (author). 3 tabs., 10 figs., 6 refs.

The Impact of Ocean Observations in Seasonal Climate Prediction

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Rienecker, Michele; Keppenne, Christian; Kovach, Robin; Marshak, Jelena

2010-01-01

The ocean provides the most significant memory for the climate system. Hence, a critical element in climate forecasting with coupled models is the initialization of the ocean with states from an ocean data assimilation system. Remotely-sensed ocean surface fields (e.g., sea surface topography, SST, winds) are now available for extensive periods and have been used to constrain ocean models to provide a record of climate variations. Since the ocean is virtually opaque to electromagnetic radiation, the assimilation of these satellite data is essential to extracting the maximum information content. More recently, the Argo drifters have provided unprecedented sampling of the subsurface temperature and salinity. Although the duration of this observation set has been too short to provide solid statistical evidence of its impact, there are indications that Argo improves the forecast skill of coupled systems. This presentation will address the impact these different observations have had on seasonal climate predictions with the GMAO's coupled model.

Solar and seasonal dependence of ion frictional heating

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J. A. Davies

1999-05-01

Full Text Available Ion frictional heating constitutes one of the principal mechanisms whereby energy, originating in the solar wind, is deposited into the Earth's ionosphere and ultimately the neutral atmosphere. Common programme observations by the EISCAT UHF radar system, spanning the years 1984 to 1995, provide the basis for a comprehensive statistical study of ion frictional heating, results of which are documented in this and a previous paper by the authors. In the present work, the authors demonstrate the solar and seasonal dependence of the universal time distribution of frictional heating, and explain these results with reference to corresponding dependences of the ion velocity. Although EISCAT observes a significant increase in the occurrence of enhanced ion velocities associated with increased solar activity, the latter characterised according to the prevailing 10.7 cm solar flux, this is not reflected to such an extent in the occurrence of frictional heating. It is suggested that this is a consequence of the decreased neutral atmosphere response times associated with active solar conditions, resulting from the higher ionospheric plasma densities present. Seasonal effects on the diurnal distribution of ion frictional heating are well explained by corresponding variations in ionospheric convection, the latter principally a result of geometrical factors. It is noted that, over the entire dataset, the variations in the unperturbed F-region ion temperature, required to implement the identification criterion for ion heating, are highly correlated with model values of thermospheric temperature.Keywords. Ionosphere (auroral ionosphere; ionosphere-atmosphere interactions; plasma temperature and density

Statistical approaches to forecast gamma dose rates by using measurements from the atmosphere

International Nuclear Information System (INIS)

Jeong, H.J.; Hwang, W. T.; Kim, E.H.; Han, M.H.

2008-01-01

In this paper, the results obtained by inter-comparing several statistical techniques for estimating gamma dose rates, such as an exponential moving average model, a seasonal exponential smoothing model and an artificial neural networks model, are reported. Seven years of gamma dose rates data measured in Daejeon City, Korea, were divided into two parts to develop the models and validate the effectiveness of the generated predictions by the techniques mentioned above. Artificial neural networks model shows the best forecasting capability among the three statistical models. The reason why the artificial neural networks model provides a superior prediction to the other models would be its ability for a non-linear approximation. To replace the gamma dose rates when missing data for an environmental monitoring system occurs, the moving average model and the seasonal exponential smoothing model can be better because they are faster and easier for applicability than the artificial neural networks model. These kinds of statistical approaches will be helpful for a real-time control of radio emissions or for an environmental quality assessment. (authors)

The use of long-term and seasonal trends of elemental compounds as an aid to the identification of sources of airborne pollutants

International Nuclear Information System (INIS)

Kleinman, M.T.

1980-01-01

New York City data indicate that seasonal and annual variations in dispersion-normalized air pollutant concentrations appear to accurately reflect changes in source emission patterns. The normalized concentrations make it possible to observe the impact of regulatory changes on ambient air quality without these impacts being obscured by meteorological fluctuations. It is found that numerical modeling techniques and regression analysis can be powerful tools for extracting information from large sets of air quality data. The use of differential, as opposed to absolute, pollutant concentration values will reduce artifact correlations caused by seasonal, weekly, or daily meteorological fluctuations and will permit more accurate estimation of the regression coefficients. This technique was successfully applied to a set of daily pollution measurements whose absolute concentrations were found not to yield a statistically significant fit by multiple regression

Seasonal Synchronization of a Simple Stochastic Dynamical Model Capturing El Niño Diversity

Science.gov (United States)

Thual, S.; Majda, A.; Chen, N.

2017-12-01

The El Niño-Southern Oscillation (ENSO) has significant impact on global climate and seasonal prediction. Recently, a simple ENSO model was developed that automatically captures the ENSO diversity and intermittency in nature, where state-dependent stochastic wind bursts and nonlinear advection of sea surface temperature (SST) are coupled to simple ocean-atmosphere processes that are otherwise deterministic, linear and stable. In the present article, it is further shown that the model can reproduce qualitatively the ENSO synchronization (or phase-locking) to the seasonal cycle in nature. This goal is achieved by incorporating a cloud radiative feedback that is derived naturally from the model's atmosphere dynamics with no ad-hoc assumptions and accounts in simple fashion for the marked seasonal variations of convective activity and cloud cover in the eastern Pacific. In particular, the weak convective response to SSTs in boreal fall favors the eastern Pacific warming that triggers El Niño events while the increased convective activity and cloud cover during the following spring contributes to the shutdown of those events by blocking incoming shortwave solar radiations. In addition to simulating the ENSO diversity with realistic non-Gaussian statistics in different Niño regions, both the eastern Pacific moderate and super El Niño, the central Pacific El Niño as well as La Niña show a realistic chronology with a tendency to peak in boreal winter as well as decreased predictability in spring consistent with the persistence barrier in nature. The incorporation of other possible seasonal feedbacks in the model is also documented for completeness.

Seasonal variation and sources of atmospheric gravity waves in the Antarctic

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Kaoru Sato

2010-12-01

Full Text Available In the last recent ten years, our knowledge of gravity waves in the Antarctic has been significantly improved through numerous studies using balloon and satellite observations and high-resolution model simulations. In this report, we introduce results from two studies which were performed as a part of the NIPR project "Integrated analysis of the material circulation in the Antarctic atmosphere-cryosphere-ocean" (2004-2009, i.e., Yoshiki et al. (2004 and Sato and Yoshiki (2008. These two studies focused on the seasonal variation and sources of the gravity waves in the Antarctic, because horizontal wavelengths and phase velocities depend largely on the wave sources. The former study used original high-resolution data from operational radiosonde observations at Syowa Station. In the lowermost stratosphere, gravity waves do not exhibit characteristic seasonal variation; instead, the wave energy is intensified when lower latitude air intrudes into the area near Syowa Station in the upper troposphere. This intrusion is associated with blocking events or developed synoptic-scale waves. In the lower and middle stratosphere, the gravity wave energy is maximized in spring and particularly intensified when the axis of the polar night jet approaches Syowa Station. The latter study is based on intensive radiosonde observation campaigns that were performed in 2002 at Syowa Station as an activity of JARE-43. Gravity wave propagation was statistically examined using two dimensional (i.e., vertical wavenumber versus frequency spectra in each season. It was shown that the gravity waves are radiated upward and downward from an unbalanced region of the polar night jet. This feature is consistent with the gravity-wave resolving GCM simulation.

A distinction between summer rainy season and summer monsoon season over the Central Highlands of Vietnam

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Ngo-Thanh, Huong; Ngo-Duc, Thanh; Nguyen-Hong, Hanh; Baker, Peter; Phan-Van, Tan

2018-05-01

The daily rainfall data at 13 stations over the Central Highlands (CH) Vietnam were collected for the period 1981-2014. Two different sets of criteria using daily observed rainfall and 850 hPa daily reanalysis wind data were applied to determine the onset (retreat) dates of the summer rainy season (RS) and summer monsoon (SM) season, respectively. Over the study period, the mean RS and SM onset dates were April 20 and May 13 with standard deviations of 17.4 and 17.8 days, respectively. The mean RS and SM retreat dates were November 1 and September 30 with standard deviations of 17.9 and 10.2 days, respectively . The year-to-year variations of the onset dates and the rainfall amount within the RS and SM season were closely linked with the preceding winter and spring sea surface temperature in the central-eastern and western Pacific. It was also found that the onset dates were significantly correlated with the RS and SM rainfall amount.

Effects of seasonal and climate variations on calves' thermal comfort and behaviour.

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Tripon, Iulian; Cziszter, Ludovic Toma; Bura, Marian; Sossidou, Evangelia N

2014-09-01

The aim of this study was to measure the effect of season and climate variations on thermal comfort and behaviour of 6-month-old dairy calves housed in a semi-opened shelter to develop animal-based indicators for assessing animal thermal comfort. The ultimate purpose was to further exploit the use of those indicators to prevent thermal stress by providing appropriate care to the animals. Measurements were taken for winter and summer seasons. Results showed that season significantly influenced (P ≤ 0.01) the lying down behaviour of calves by reducing the time spent lying, from 679.9 min in winter to 554.1 min in summer. Moreover, season had a significant influence (P ≤ 0.01) on feeding behaviour. In detail, the total length of feeding periods was shorter in winter, 442.1 min in comparison to 543.5 min in summer. Time spent drinking increased significantly (P ≤ 0.001), from 11.9 min in winter to 26.9 min in summer. Furthermore, season had a significant influence (P ≤ 0.001) on self grooming behaviour which was 5.5 times longer in duration in winter than in summer (1,336 s vs 244 s). It was concluded that calves' thermal comfort is affected by seasonal and climate variations and that this can be assessed by measuring behaviour with animal-based indicators, such as lying down, resting, standing up, feeding, rumination, drinking and self grooming. The indicators developed may be a useful tool to prevent animal thermal stress by providing appropriate housing and handling to calves under seasonal and climate challenge.

Small mammal use of native warm-season and non-native cool-season grass forage fields

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Ryan L Klimstra,; Christopher E Moorman,; Converse, Sarah J.; Royle, J. Andrew; Craig A Harper,

2015-01-01

Recent emphasis has been put on establishing native warm-season grasses for forage production because it is thought native warm-season grasses provide higher quality wildlife habitat than do non-native cool-season grasses. However, it is not clear whether native warm-season grass fields provide better resources for small mammals than currently are available in non-native cool-season grass forage production fields. We developed a hierarchical spatially explicit capture-recapture model to compare abundance of hispid cotton rats (Sigmodon hispidus), white-footed mice (Peromyscus leucopus), and house mice (Mus musculus) among 4 hayed non-native cool-season grass fields, 4 hayed native warm-season grass fields, and 4 native warm-season grass-forb ("wildlife") fields managed for wildlife during 2 summer trapping periods in 2009 and 2010 of the western piedmont of North Carolina, USA. Cotton rat abundance estimates were greater in wildlife fields than in native warm-season grass and non-native cool-season grass fields and greater in native warm-season grass fields than in non-native cool-season grass fields. Abundances of white-footed mouse and house mouse populations were lower in wildlife fields than in native warm-season grass and non-native cool-season grass fields, but the abundances were not different between the native warm-season grass and non-native cool-season grass fields. Lack of cover following haying in non-native cool-season grass and native warm-season grass fields likely was the key factor limiting small mammal abundance, especially cotton rats, in forage fields. Retention of vegetation structure in managed forage production systems, either by alternately resting cool-season and warm-season grass forage fields or by leaving unharvested field borders, should provide refugia for small mammals during haying events.

Seasonal versus perennial immunotherapy: evaluation after three years of treatment.

Science.gov (United States)

Muñoz Lejarazu, D; Bernaola, G; Fernández, E; Audícana, M; Ventas, P; Martín, S; Fernández de Corres, L

1993-01-01

We have performed a comparative study to evaluate seasonal and perennial schedules after 3 years of immunotherapy. Sixty patients suffering from rhinitis and/or asthma due to grass pollen sensitization were randomly allocated to receive a semi-depot extract of Phleum pratense according to a perennial or seasonal schedule. The last year of the study, 14 patients were recruited as a control group without immunotherapy. The cumulative dose was 602 BU in the perennial group and 372 BU in the seasonal group. The frequency and severity of side-effects were similar and very low in both treated groups. The IgE level was significantly lower after perennial immunotherapy at the end of the first 2 years. A seasonal decrease in specific IgG levels was observed in patients who interrupted immunotherapy, while this was not observed in patients under the perennial schedule. Symptoms and medication scores did not show differences between groups. Nevertheless, we found a significant difference between treated patients and the control group.

Evaluation of CFSV2 Forecast Skill for Indian Summer Monsoon Sub-Seasonal Characteristics

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S, S. A.; Ghosh, S.

2015-12-01

Prediction of sub seasonal monsoon characteristics of Indian Summer Monsoon (ISM) is highly crucial for agricultural planning and water resource management. The Climate forecast System version 2 (CFS V2), the state of the art coupled climate model developed by NCEP, is currently being employed for the seasonal and extended range forecasts of ISM. Even though CFSV2 is a fully coupled ocean- atmosphere- land model with advanced physics, increased resolution and refined initialisation, its ISM forecasts, in terms of seasonal mean and variability needs improvement. Numerous works have been done for verifying the CFSV2 forecasts in terms of the seasonal mean, its mean and variability, active and break spells, and El Nino Southern Oscillation (ENSO) - monsoon interactions. Most of these works are based on either rain fall strength or rainfall based indices. Here we evaluate the skill of CFS v2 model in forecasting the various sub seasonal features of ISM, viz., the onset and withdrawal days of monsoon that are determined using circulation based indices, the Monsoon Intra Seasonal Oscillations (MISO), and Indian Ocean and Pacific Ocean sea surface temperatures. The MISO index, we use here, is based on zonal wind at 850 hPa and Outgoing Long wave Radiation (OLR) anomalies. With this work, we aim at assessing the skill of the model in simulating the large scale circulation patterns and their variabilities within the monsoon season. Variabilities in these large scale circulation patterns are primarily responsible for the variabilities in the seasonal monsoon strength and its temporal distribution across the season. We find that the model can better forecast the large scale circulation and than the actual precipitation. Hence we suggest that seasonal rainfall forecasts can be improved by the statistical downscaling of CFSV2 forecasts by incorporating the established relationships between the well forecasted large scale variables and monsoon precipitation.

A Study on Living Conditions of the Seasonal Agricultural Workers: Hilvan County (Şanlıurfa Sample

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Sedat Benek

2011-12-01

Full Text Available This study is carried out to identify living standards of seasonal agricultural workers in Hilvan County of Şanlıurfa that largely rely on agriculture and have sufficient or little cultivable lands. Study sample is composed of families of the students who attend schools affiliated to Hilvan County Directorate of National Education and are involved in temporary migration before the school term ends in a year. “Face to face” interviews were held with and questionnaires were applied to heads of 523 families which live on seasonal agricultural labor. The results were assessed by using SPSS (Statistical Package for Social Science through various statistical techniques required for the study purpose. Majority of the children of families who

A global empirical system for probabilistic seasonal climate prediction

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Eden, J. M.; van Oldenborgh, G. J.; Hawkins, E.; Suckling, E. B.

2015-12-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961-2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño-Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

IMF BY and the seasonal dependences of the electric field in the inner magnetosphere

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H. Matsui

2005-10-01

Full Text Available It is known that the electric field pattern at high latitudes depends on the polarity of the Y component of the interplanetary magnetic field (IMF BY and season. In this study, we investigate the seasonal and BY dependences in the inner magnetosphere using the perigee (4seasons or hemispheres. It is demonstrated from our statistics that the electric fields in the inner magnetosphere depend on these quantities. The following three points are inferred: 1 The electric fields exhibit some differences statistically between Cluster locations at the Northern and Southern Hemispheres with the same dipole L and magnetic local time (MLT values and during the same IMF conditions. These differences in the electric fields might result from hemispherical differences in magnetic field geometry and/or those in field-aligned potential difference. 2 The IMF BY and seasonal dependence of the dawnside and duskside electric fields at 4season into a realistic model of the inner magnetospheric convection electric field. Keywords. Magnetospheric physics (Electric fields; Magnetosphere-ionosphere interactions; Solar windmagnetosphere interactions

Modeling seasonal water balance based on catchments' hedging strategy on evapotranspiration for climate seasonality

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Wu, S.; Zhao, J.; Wang, H.

2017-12-01

This paper develops a seasonal water balance model based on the hypothesis that natural catchments utilize hedging strategy on evapotranspiration for climate seasonality. According to the monthly aridity index, one year is split into wet season and dry season. A seasonal water balance model is developed by analogy to a two-stage reservoir operation model, in which seasonal rainfall infiltration, evapotranspiration and saturation-excess runoff is corresponding to the inflow, release and surplus of the catchment system. Then the optimal hedging between wet season and dry season evapotranspiration is analytically derived with marginal benefit principle. Water budget data sets of 320 catchments in the United States covering the period from 1980 to 2010 are used to evaluate the performance of this model. The Nash-Sutcliffe Efficiency coefficient for evapotranspiration is higher than 0.5 in 84% of the study catchments; while the runoff is 87%. This paper validates catchments' hedging strategy on evapotranspiration for climate seasonality and shows its potential application for seasonal water balance, which is valuable for water resources planning and management.

Survival during the Breeding Season: Nest Stage, Parental Sex, and Season Advancement Affect Reed Warbler Survival.

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Kaja Wierucka

Full Text Available Avian annual survival has received much attention, yet little is known about seasonal patterns in survival, especially of migratory passerines. In order to evaluate survival rates and timing of mortality within the breeding season of adult reed warblers (Acrocephalus scirpaceus, mark-recapture data were collected in southwest Poland, between 2006 and 2012. A total of 612 individuals (304 females and 308 males were monitored throughout the entire breeding season, and their capture-recapture histories were used to model survival rates. Males showed higher survival during the breeding season (0.985, 95% CI: 0.941-0.996 than females (0.869, 95% CI: 0.727-0.937. Survival rates of females declined with the progression of the breeding season (from May to August, while males showed constant survival during this period. We also found a clear pattern within the female (but not male nesting cycle: survival was significantly lower during the laying, incubation, and nestling periods (0.934, 95% CI: 0.898-0.958, when birds spent much time on the nest, compared to the nest building and fledgling periods (1.000, 95% CI: 1.00-1.000, when we did not record any female mortality. These data (coupled with some direct evidence, like bird corpses or blood remains found next to/on the nest may suggest that the main cause of adult mortality was on-nest predation. The calculated survival rates for both sexes during the breeding season were high compared to annual rates reported for this species, suggesting that a majority of mortality occurs at other times of the year, during migration or wintering. These results have implications for understanding survival variation within the reproductive period as well as general trends of avian mortality.

Inferring species richness and turnover by statistical multiresolution texture analysis of satellite imagery.

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Matteo Convertino

richness, or [Formula: see text] diversity, based on the Shannon entropy of pixel intensity.To test our approach, we specifically use the green band of Landsat images for a water conservation area in the Florida Everglades. We validate our predictions against data of species occurrences for a twenty-eight years long period for both wet and dry seasons. Our method correctly predicts 73% of species richness. For species turnover, the newly proposed KL divergence prediction performance is near 100% accurate. This represents a significant improvement over the more conventional Shannon entropy difference, which provides 85% accuracy. Furthermore, we find that changes in soil and water patterns, as measured by fluctuations of the Shannon entropy for the red and blue bands respectively, are positively correlated with changes in vegetation. The fluctuations are smaller in the wet season when compared to the dry season. CONCLUSIONS/SIGNIFICANCE: Texture-based statistical multiresolution image analysis is a promising method for quantifying interseasonal differences and, consequently, the degree to which vegetation, soil, and water patterns vary. The proposed automated method for quantifying species richness and turnover can also provide analysis at higher spatial and temporal resolution than is currently obtainable from expensive monitoring campaigns, thus enabling more prompt, more cost effective inference and decision making support regarding anomalous variations in biodiversity. Additionally, a matrix-based visualization of the statistical multiresolution analysis is presented to facilitate both insight and quick recognition of anomalous data.

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

Science.gov (United States)

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

Seasonal Forecast Skill And Teleconnections Over East Africa

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MacLeod, D.; Palmer, T.

2017-12-01

Many people living in East Africa are significantly exposed to risks arising from climate variability. The region experiences two rainy seasons and poor performance of either or both of these (such as seen recently in 2016/17) reduces agricultural productivity and threatens food security. In combination with other factors this can lead to famine. By utilizing seasonal climate forecasts, preparatory actions can be taken in order to mitigate the risks arising from such climate variability. As part of the project ForPAc: "Towards forecast-based preparedness action", we are working with humanitarian agencies in Kenya to build such early warning systems on subseasonal-to-seasonal timescales. Here, the seasonal predictability and forecast skill of the two East African rainy seasons will be presented. Results from the new ECMWF operational forecasting system SEAS5 will be shown and compared to the previous System 4. Analysis of a new 110 year long atmosphere-only simulation will also be discussed, demonstrating impacts of atmosphere-ocean coupling as well as putting operational forecast skill in a long-term context. Particular focus will be given to the model representation of teleconnections of seasonal climate with global sea surface temperatures; highlighting sources of forecast error and informing future model development.

Wildfire Dynamics and Occasional Precipitation during Active Fire Season in Tropical Lowland of Nepal

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Krishna Bahadur Bhujel

2017-10-01

Full Text Available Occasional precipitation plays a vital role in reducing the effect of wildfire. This precipitation is especially important for countries like Nepal, where wildfires are a common seasonal event. Approximately 0.1 million hectare of forest area is affected annually due to wildfires in active fire season. The study on the relation of these forms of occasional precipitation with wildfire incidence is still lacking. This research was objectively carried out to examine the correlation of occasional precipitation with wildfire incidence and burnt area. The Moderate Resolution Imaging Spector-Radiometer (MODIS satellite images and precipitation records for 15 years gathered from Department of Hydrology and Metrology were used as input data for this study. The images were analyzed by using ArcGIS function while the precipitation records were analyzed by using Statistical Package for the Social Science (SPSS program. The linear regression model was applied to find correlation of occasional precipitation with wildfire incidence and burnt area. Analysis revealed decreasing trend of precipitation in study area. We found significant correlation (p<0.05 of precipitation with wildfire incidence and burnt area. Findings will be useful for policy makers, implementers and researchers to manage wildfire in sustainable basis.

Influence of season and sex on hemato-biochemical traits in adult turkeys under arid tropical environment

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Anil Gattani

2016-05-01

Full Text Available Aim: The objective of this study was to evaluate the effect of season and sex on hemato-biochemical parameters of turkey (Meleagris gallopavo in the arid tropical environment. Materials and Methods: The experiment was conducted on 20-week old turkeys consisting of 20 males and 20 females. Blood was collected from all turkeys during January and May. Hemoglobin (Hb, red blood cell (RBC, packed cell volume (PCV, mean corpuscular volume (MCV, mean corpuscular hemoglobin (MCH, and mean corpuscular hemoglobin concentration (MCHC were estimated in whole blood and glucose, protein, albumin, globulin, A/G ratio, calcium, phosphorus, alanine aminotransferase (ALT, and aspartate aminotransferase (AST in serum. Result: Season has significant (p<0.05 effect on Hb concentration, RBC, and PCV in both male and female. Male has significantly higher (p<0.05 Hb concentration, RBC, and PCV. There is no significant effect of sex, and season was observed on MCV, MCH, and MCHC. Glucose, protein, albumin, globulin, and A/G ratio were significantly (p<0.05 affected by season and sex. AST and ALT were significantly (p<0.05 affected by season in both sexes. There is no significant difference was recorded on calcium, phosphorus due to season and sex. Conclusion: Under arid tropical environment, turkey hemato-biochemical parameters are influenced by both sex and season.

Understanding Short-Term Nonmigrating Tidal Variability in the Ionospheric Dynamo Region from SABER Using Information Theory and Bayesian Statistics

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Kumari, K.; Oberheide, J.

2017-12-01

Nonmigrating tidal diagnostics of SABER temperature observations in the ionospheric dynamo region reveal a large amount of variability on time-scales of a few days to weeks. In this paper, we discuss the physical reasons for the observed short-term tidal variability using a novel approach based on Information theory and Bayesian statistics. We diagnose short-term tidal variability as a function of season, QBO, ENSO, and solar cycle and other drivers using time dependent probability density functions, Shannon entropy and Kullback-Leibler divergence. The statistical significance of the approach and its predictive capability is exemplified using SABER tidal diagnostics with emphasis on the responses to the QBO and solar cycle. Implications for F-region plasma density will be discussed.

Determining coding CpG islands by identifying regions significant for pattern statistics on Markov chains.

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Singer, Meromit; Engström, Alexander; Schönhuth, Alexander; Pachter, Lior

2011-09-23

Recent experimental and computational work confirms that CpGs can be unmethylated inside coding exons, thereby showing that codons may be subjected to both genomic and epigenomic constraint. It is therefore of interest to identify coding CpG islands (CCGIs) that are regions inside exons enriched for CpGs. The difficulty in identifying such islands is that coding exons exhibit sequence biases determined by codon usage and constraints that must be taken into account. We present a method for finding CCGIs that showcases a novel approach we have developed for identifying regions of interest that are significant (with respect to a Markov chain) for the counts of any pattern. Our method begins with the exact computation of tail probabilities for the number of CpGs in all regions contained in coding exons, and then applies a greedy algorithm for selecting islands from among the regions. We show that the greedy algorithm provably optimizes a biologically motivated criterion for selecting islands while controlling the false discovery rate. We applied this approach to the human genome (hg18) and annotated CpG islands in coding exons. The statistical criterion we apply to evaluating islands reduces the number of false positives in existing annotations, while our approach to defining islands reveals significant numbers of undiscovered CCGIs in coding exons. Many of these appear to be examples of functional epigenetic specialization in coding exons.

Establishing native warm season grasses on Eastern Kentucky strip mines

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Barnes, T.G.; Larkin, J.L.; Arnett, M.B. [Univ. of Kentucky, Lexington, KY (United States). Dept. of Forestry

1998-12-31

The authors evaluated various methods of establishing native warm season grasses on two reclaimed Eastern Kentucky mines from 1994--1997. Most current reclamation practices incorporate the use of tall fescue (Festuca arundinacea) and other cool-season grasses/legumes that provide little wildlife habitats. The use of native warm season grasses will likely improve wildlife habitat on reclaimed strip mines. Objectives of this study were to compare the feasibility of establishing these grasses during fall, winter, or spring using a native rangeland seeder or hydroseeding; a fertilizer application at planting; or cold-moist stratification prior to hydroseeding. Vegetative cover, bare ground, species richness, and biomass samples were collected at the end of each growing season. Native warm season grass plantings had higher plant species richness compared to cool-season reclamation mixtures. There was no difference in establishment of native warm season grasses as a result of fertilization or seeding technique. Winter native warm season grass plantings were failures and cold-moist stratification did not increase plant establishment during any season. As a result of a drought during 1997, both cool-season and warm season plantings were failures. Cool-season reclamation mixtures had significantly more vegetative cover and biomass compared to native warm season grass mixtures and the native warm season grass plantings did not meet vegetative cover requirements for bond release. Forbs and legumes that established well included pale purple coneflower (Echinacea pallida), lance-leaf coreopsis (Coreopsis lanceolata), round-headed lespedeza (Lespedeza capitata), partridge pea (Cassia fasiculata), black-eyed susan (Rudbeckia hirta), butterfly milkweed (Asclepias tuberosa), and bergamot (Monarda fistulosa). Results from two demonstration plots next to research plots indicate it is possible to establish native warm season grasses on Eastern Kentucky strip mines for wildlife habitat.

Establishing native warm season grasses on Eastern Kentucky strip mines

International Nuclear Information System (INIS)

Barnes, T.G.; Larkin, J.L.; Arnett, M.B.

1998-01-01

The authors evaluated various methods of establishing native warm season grasses on two reclaimed Eastern Kentucky mines from 1994--1997. Most current reclamation practices incorporate the use of tall fescue (Festuca arundinacea) and other cool-season grasses/legumes that provide little wildlife habitats. The use of native warm season grasses will likely improve wildlife habitat on reclaimed strip mines. Objectives of this study were to compare the feasibility of establishing these grasses during fall, winter, or spring using a native rangeland seeder or hydroseeding; a fertilizer application at planting; or cold-moist stratification prior to hydroseeding. Vegetative cover, bare ground, species richness, and biomass samples were collected at the end of each growing season. Native warm season grass plantings had higher plant species richness compared to cool-season reclamation mixtures. There was no difference in establishment of native warm season grasses as a result of fertilization or seeding technique. Winter native warm season grass plantings were failures and cold-moist stratification did not increase plant establishment during any season. As a result of a drought during 1997, both cool-season and warm season plantings were failures. Cool-season reclamation mixtures had significantly more vegetative cover and biomass compared to native warm season grass mixtures and the native warm season grass plantings did not meet vegetative cover requirements for bond release. Forbs and legumes that established well included pale purple coneflower (Echinacea pallida), lance-leaf coreopsis (Coreopsis lanceolata), round-headed lespedeza (Lespedeza capitata), partridge pea (Cassia fasiculata), black-eyed susan (Rudbeckia hirta), butterfly milkweed (Asclepias tuberosa), and bergamot (Monarda fistulosa). Results from two demonstration plots next to research plots indicate it is possible to establish native warm season grasses on Eastern Kentucky strip mines for wildlife habitat

Sister chromatid exchanges and high-frequency cells in men environmentally and occupationally exposed to ambient air pollutants. An intergroup comparison with respect to seasonal changes and smoking habit

Energy Technology Data Exchange (ETDEWEB)

Pendzich, Joanna; Motykiewicz, Grazyna; Michalska, Jadwiga; Kostowska, Alina; Chorazy, Mieczyslaw [Department of Tumor Biology, Institute of Oncology, Gliwice (Poland); Wang, Li You [Graduate Institute of Epidemiology, College of Public Health, National Taiwan University, Taipei (Taiwan, Province of China)

1997-11-28

Sister chromatid exchanges (SCE) and high-frequency cells (HFC) were measured in peripheral blood lymphocytes from men environmentally and occupationally exposed to a mixture of ambient air pollutants. The environmentally exposed individuals were inhabitants of the industrial region of Upper Silesia; those occupationally exposed were Silesian cokery or steel plant workers, while the control group consisted of rural region residents. A total of 147 males were enrolled in the study. Blood samples were collected in winter (February) and summer (September) seasons. Three major areas were investigated during the study: exposure-based dose dependency, seasonal changes, and influence of smoking habits on the SCE frequencies. The latter is frequently reported as a confounding factor in SCE analyses. In both winter and summer samples, statistically significant increases of SCE were observed in the environmentally and occupationally exposed groups compared to the controls (p<0.001). The difference between both exposed groups was also significant (p<0.001). An intergroup comparison was based on ANOVA after adjustment for smoking status. In all three groups of interest, a seasonal variation was found with higher levels in winter. However, in a part of the study in which each donor served as his own control, statistical differences were only found within the exposed groups. Control region inhabitants did not have significantly higher frequencies of SCE in winter, compared to summer samples. The impact of two major confounders, age of the donor and smoking habit, was investigated by multiple regression analysis. Smoking was a major factor influencing the level of SCE. Nevertheless, the effect was seen in winter samples only, which suggests an additive response and adds new information to this known effect

7 CFR 5.5 - Publication of season average, calendar year, and parity price data.

Science.gov (United States)

2010-01-01

... cases where preliminary marketing season average price data are used in estimating the adjusted base... Statistics Service, after consultation with the Agricultural Marketing Service, the Farm Service Agency, and... parity price data. 5.5 Section 5.5 Agriculture Office of the Secretary of Agriculture DETERMINATION OF...

Characterisation of seasonal flood types according to timescales in mixed probability distributions

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Fischer, Svenja; Schumann, Andreas; Schulte, Markus

2016-08-01

When flood statistics are based on annual maximum series (AMS), the sample often contains flood peaks, which differ in their genesis. If the ratios among event types change over the range of observations, the extrapolation of a probability distribution function (pdf) can be dominated by a majority of events that belong to a certain flood type. If this type is not typical for extraordinarily large extremes, such an extrapolation of the pdf is misleading. To avoid this breach of the assumption of homogeneity, seasonal models were developed that differ between winter and summer floods. We show that a distinction between summer and winter floods is not always sufficient if seasonal series include events with different geneses. Here, we differentiate floods by their timescales into groups of long and short events. A statistical method for such a distinction of events is presented. To demonstrate their applicability, timescales for winter and summer floods in a German river basin were estimated. It is shown that summer floods can be separated into two main groups, but in our study region, the sample of winter floods consists of at least three different flood types. The pdfs of the two groups of summer floods are combined via a new mixing model. This model considers that information about parallel events that uses their maximum values only is incomplete because some of the realisations are overlaid. A statistical method resulting in an amendment of statistical parameters is proposed. The application in a German case study demonstrates the advantages of the new model, with specific emphasis on flood types.

Impacts of the seasonal distribution of rainfall on vegetation productivity across the Sahel

Science.gov (United States)

Zhang, Wenmin; Brandt, Martin; Tong, Xiaoye; Tian, Qingjiu; Fensholt, Rasmus

2018-01-01

Climate change in drylands has caused alterations in the seasonal distribution of rainfall including increased heavy-rainfall events, longer dry spells, and a shifted timing of the wet season. Yet the aboveground net primary productivity (ANPP) in drylands is usually explained by annual-rainfall sums, disregarding the influence of the seasonal distribution of rainfall. This study tested the importance of rainfall metrics in the wet season (onset and cessation of the wet season, number of rainy days, rainfall intensity, number of consecutive dry days, and heavy-rainfall events) for growing season ANPP. We focused on the Sahel and northern Sudanian region (100-800 mm yr-1) and applied daily satellite-based rainfall estimates (CHIRPS v2.0) and growing-season-integrated normalized difference vegetation index (NDVI; MODIS) as a proxy for ANPP over the study period: 2001-2015. Growing season ANPP in the arid zone (100-300 mm yr-1) was found to be rather insensitive to variations in the seasonal-rainfall metrics, whereas vegetation in the semi-arid zone (300-700 mm yr-1) was significantly impacted by most metrics, especially by the number of rainy days and timing (onset and cessation) of the wet season. We analysed critical breakpoints for all metrics to test if vegetation response to changes in a given rainfall metric surpasses a threshold beyond which vegetation functioning is significantly altered. It was shown that growing season ANPP was particularly negatively impacted after > 14 consecutive dry days and that a rainfall intensity of ˜ 13 mm day-1 was detected for optimum growing season ANPP. We conclude that the number of rainy days and the timing of the wet season are seasonal-rainfall metrics that are decisive for favourable vegetation growth in the semi-arid Sahel and need to be considered when modelling primary productivity from rainfall in the drylands of the Sahel and elsewhere.

Seasonal Trends in Lithuanian Stock Market

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Žaneta Simanavičienė

2013-11-01

Full Text Available Purpose of the article is to disentangle different calendar effects which leave efficiency holes in Lithuanian market. This paper presents and tests if commonly described seasonal patterns exist in Lithuanian stock market. Analysis of three different sections: period-of-the-year; week-of-the-month and day-of-the-week, suggests that calendar effects do exist in this market. The multitude of explanations for the seasonal effect leaves the reader confused about its primary cause(s: is it tax-loss selling, window dressing, information, bid-ask bounce, or a combination of these causes? The confusion arises, in part, because evidence has generally been presented in support of a particular hypothesis though the same evidence may be consistent with another hypothesis. Methodology/methods are logical and systemic analysis of research literature based on the comparative and generalization methods as well as statistical methods. Scientific aim of the article is the lack of arguments questioning if market prices operating system is fully effective. Novelty of the paper is to the answer to the question what seasonal anomalies are also present in the stock market of new open economy countries. Findings show that using this modified strategy investor could achieve 20.7% compounded annual growth rate versus 7.8% achieved using simply holding stocks throughout. The hypothesis asserts that returns generally will be greater following the “January effect”. There is limited amount of data for constructing robust seasonal strategies so we modified Buy and Hold strategy with simple rules of using best and worst months to show how they influence OMXV index performance. In the conclusions, empirical results using stock index returns for 2000 - 2010 support the hypothesis in Lithuaian stock market. Abnormal activity of OMXV index’s performance is found in the end of summer and throughout autumn. August is best performer of the year while October is

Seasonal isotope hydrology of a coffee agroforestry watershed in Costa Rica

Science.gov (United States)

Welsh Unwala, K.; Boll, J.; Roupsard, O.

2014-12-01

Improved information of seasonal variations in watershed hydrology in the tropics can strengthen models and understanding of hydrology of these areas. Seasonality in the tropics produces rainy seasons versus dry seasons, leading to different hydrologic and water quality processes throughout the year. We questioned whether stable isotopes in water can be used to trace the seasonality in this region, despite experiencing a "drier" season, such as in a Tropical Humid location. This study examines the fluctuations of stable isotope compositions (δ18O and δD) in water balance components in a small (deep groundwater system contributes significantly to baseflow, although a shallow, spring-driven system also contributes to stream water within the watershed. During storm events, precipitation contributes to stormflow in the short-term, confirming the role of superficial runoff. These results indicate that isotopes are helpful to partition the water balance even in a Tropical Humid situation where the rainfall seasonality is weak.

Season of birth and primary central nervous system tumors: a systematic review of the literature with critical appraisal of underlying mechanisms.

Science.gov (United States)

Georgakis, Marios K; Ntinopoulou, Erato; Chatzopoulou, Despoina; Petridou, Eleni Th

2017-09-01

Season of birth has been considered a proxy of seasonally varying exposures around perinatal period, potentially implicated in the etiology of several health outcomes, including malignancies. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we have systematically reviewed published literature on the association of birth seasonality with risk of central nervous system tumors in children and adults. Seventeen eligible studies using various methodologies were identified, encompassing 20,523 cases. Eight of 10 studies in children versus four of eight in adults showed some statistically significant associations between birth seasonality and central nervous system tumor or tumor subtype occurrence, pointing to a clustering of births mostly in fall and winter months, albeit no consistent pattern was identified by histologic subtype. A plethora of perinatal factors might underlie or confound the associations, such as variations in birth weight, maternal diet during pregnancy, perinatal vitamin D levels, pesticides, infectious agents, immune system maturity, and epigenetic modifications. Inherent methodological weaknesses of to-date published individual investigations, including mainly underpowered size to explore the hypothesis by histological subtype, call for more elegant concerted actions using primary data of large datasets taking also into account the interplay between the potential underlying etiologic factors. Copyright © 2017 Elsevier Inc. All rights reserved.

Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

Science.gov (United States)

Zhang, Ying; Moges, Semu; Block, Paul

2018-01-01

Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

Seasonal variation of deep-sea bioluminescence in the Ionian Sea

International Nuclear Information System (INIS)

Craig, Jessica; Jamieson, Alan J.; Bagley, Philip M.; Priede, Imants G.

2011-01-01

The ICDeep (Image Intensified Charge Coupled Device for Deep sea research) profiler was used to measure the density of deep bioluminescent animals (BL) through the water column in the east, west and mid-Ionian Sea and in the Algerian Basin. A west to east decrease in BL density was found. Generalized additive modelling was used to investigate seasonal variation in the east and west Ionian Sea (NESTOR and NEMO neutrino telescope sites, respectively) from BL measurements in autumn 2008 and spring 2009. A significant seasonal effect was found in the west Ionian Sea (p<0.001), where a deep autumnal peak in BL density occurred between 500 and 2400 m. No significant seasonal variation in BL density was found in the east Ionian Sea (p=0.07). In both spring and autumn, significant differences in BL density were found through the water column between the east and west Ionian Sea (p<0.001).

Seasonal variation of deep-sea bioluminescence in the Ionian Sea

Energy Technology Data Exchange (ETDEWEB)

Craig, Jessica, E-mail: j.craig@abdn.ac.u [University of Aberdeen, Oceanlab, Main Street, Newburgh, Aberdeenshire, AB41 6AA (United Kingdom); Jamieson, Alan J.; Bagley, Philip M.; Priede, Imants G. [University of Aberdeen, Oceanlab, Main Street, Newburgh, Aberdeenshire, AB41 6AA (United Kingdom)

2011-01-21

The ICDeep (Image Intensified Charge Coupled Device for Deep sea research) profiler was used to measure the density of deep bioluminescent animals (BL) through the water column in the east, west and mid-Ionian Sea and in the Algerian Basin. A west to east decrease in BL density was found. Generalized additive modelling was used to investigate seasonal variation in the east and west Ionian Sea (NESTOR and NEMO neutrino telescope sites, respectively) from BL measurements in autumn 2008 and spring 2009. A significant seasonal effect was found in the west Ionian Sea (p<0.001), where a deep autumnal peak in BL density occurred between 500 and 2400 m. No significant seasonal variation in BL density was found in the east Ionian Sea (p=0.07). In both spring and autumn, significant differences in BL density were found through the water column between the east and west Ionian Sea (p<0.001).

Seasonality, mobility, and livability.

Science.gov (United States)

2012-01-31

Signature project 4a, Seasonality, Mobility, and Livability investigated the effects of weather, season, built environment, community amenities, attitudes, and demographics on mobility and quality of life (QOL). A four season panel survey exami...

Variability of cold season surface air temperature over northeastern China and its linkage with large-scale atmospheric circulations

Science.gov (United States)

Zhuang, Yuanhuang; Zhang, Jingyong; Wang, Lin

2018-05-01

Cold temperature anomalies and extremes have profound effects on the society, the economy, and the environment of northeastern China (NEC). In this study, we define the cold season as the months from October to April, and investigate the variability of cold season surface air temperature (CSAT) over NEC and its relationships with large-scale atmospheric circulation patterns for the period 1981-2014. The empirical orthogonal function (EOF) analysis shows that the first EOF mode of the CSAT over NEC is characterized by a homogeneous structure that describes 92.2% of the total variance. The regionally averaged CSAT over NEC is closely linked with the Arctic Oscillation ( r = 0.62, 99% confidence level) and also has a statistically significant relation with the Polar/Eurasian pattern in the cold season. The positive phases of the Arctic Oscillation and the Polar/Eurasian pattern tend to result in a positive geopotential height anomaly over NEC and a weakened East Asian winter monsoon, which subsequently increase the CSAT over NEC by enhancing the downward solar radiation, strengthening the subsidence warming and warm air advection. Conversely, the negative phases of these two climate indices result in opposite regional atmospheric circulation anomalies and decrease the CSAT over NEC.

seasonal variation in chromium hexavalent and copper

African Journals Online (AJOL)

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Seasonal variation in heavy metal contamination of groundwater in the Jimeta- Yola area ... animal feedlots, industrial waste and food processing ...... and conservation of groundwater quality; a) ... significant role of hydrous Mn and Fe oxides.

Seasonal and demographic factors influencing gastrointestinal parasitism in ungulates of Etosha National Park.

Science.gov (United States)

Turner, Wendy C; Getz, Wayne M

2010-10-01

Host-parasite dynamics can be strongly affected by seasonality and age-related host immune responses. We investigated how observed variation in the prevalence and intensity of parasite egg or oocyst shedding in four co-occurring ungulate species may reflect underlying seasonal variation in transmission and host immunity. This study was conducted July 2005-October 2006 in Etosha National Park, Namibia, using indices of parasitism recorded from 1,022 fecal samples collected from plains zebra (Equus quagga), springbok (Antidorcas marsupialis), blue wildebeest (Connochaetes taurinus), and gemsbok (Oryx gazella). The presence and intensity of strongyle nematodes, Strongyloides spp. and Eimeria spp. parasites, were strongly seasonal for most host-parasite combinations, with more hosts infected in the wet season than the dry season. Strongyle intensity in zebra was significantly lower in juveniles than adults, and in springbok hosts, Eimeria spp. intensity was significantly greater in juveniles than adults. These results provide evidence that acquired immunity is less protective against strongyle nematodes than Eimeria spp. infections. The seasonal patterns in parasitism further indicate that the long dry season may limit development and survival of parasite stages in the environment and, as a result, host contact and parasite transmission.

Final Scientific/Technical Report for Subseasonal to Seasonal Prediction of Extratropical Storm Track Activity over the U.S. using NMME data

Energy Technology Data Exchange (ETDEWEB)

Chang, Edmund Kar-Man [Stony Brook Univ., NY (United States)

2017-10-30

The goals of the project are: 1) To develop and assess subseasonal to seasonal prediction products for storm track activity derived from NMME data; 2) Assess how much of the predictable signal can be associated with ENSO and other modes of large scale low frequency atmosphere-ocean variability; and 3) Further explore the link between storm track variations and extreme weather statistics. Significant findings of this project include the followings: 1) Our assessment of NMME reforecasts of storm track variability has demonstrated that NMME models have substantial skill in predicting storm track activity in the vicinity of North America - Subseasonal skill is high only for leads of less than 1 month. However, seasonal (winter) prediction skill near North America is high even out to 4 to 5 months lead - Much of the skill for leads of 1 month or longer is related to the influence of ENSO - Nevertheless, lead 0 NMME predictions are significantly more skillful than those based on ENSO influence 2) Our results have demonstrated that storm track variations highly modulate the frequency of occurrence of weather extremes - Extreme cold, high wind, and extreme precipitation events in winter - Extreme heat events in summer - These results suggest that NMME storm track predictions can be developed to serve as a useful guidance to assist the formulation of monthly/seasonal outlooks

Impact of seasonal forcing on reactive ecological systems.

Science.gov (United States)

Vesipa, Riccardo; Ridolfi, Luca

2017-04-21

Our focus is on the short-term dynamics of reactive ecological systems which are stable in the long term. In these systems, perturbations can exhibit significant transient amplifications before asymptotically decaying. This peculiar behavior has attracted increasing attention. However, reactive systems have so far been investigated assuming that external environmental characteristics remain constant, although environmental conditions (e.g., temperature, moisture, water availability, etc.) can undergo substantial changes due to seasonal cycles. In order to fill this gap, we propose applying the adjoint non-modal analysis to study the impact of seasonal variations of environmental conditions on reactive systems. This tool allows the transient dynamics of a perturbation affecting non-autonomous ecological systems to be described. To show the potential of this approach, a seasonally forced prey-predator model with a Holling II type functional response is studied as an exemplifying case. We demonstrate that seasonalities can greatly affect the transient dynamics of the system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of base flows to selected streamflow statistics representative of 1930-2002 in West Virginia

Science.gov (United States)

Wiley, Jeffrey B.

2012-01-01

Base flows were compared with published streamflow statistics to assess climate variability and to determine the published statistics that can be substituted for annual and seasonal base flows of unregulated streams in West Virginia. The comparison study was done by the U.S. Geological Survey, in cooperation with the West Virginia Department of Environmental Protection, Division of Water and Waste Management. The seasons were defined as winter (January 1-March 31), spring (April 1-June 30), summer (July 1-September 30), and fall (October 1-December 31). Differences in mean annual base flows for five record sub-periods (1930-42, 1943-62, 1963-69, 1970-79, and 1980-2002) range from -14.9 to 14.6 percent when compared to the values for the period 1930-2002. Differences between mean seasonal base flows and values for the period 1930-2002 are less variable for winter and spring, -11.2 to 11.0 percent, than for summer and fall, -47.0 to 43.6 percent. Mean summer base flows (July-September) and mean monthly base flows for July, August, September, and October are approximately equal, within 7.4 percentage points of mean annual base flow. The mean of each of annual, spring, summer, fall, and winter base flows are approximately equal to the annual 50-percent (standard error of 10.3 percent), 45-percent (error of 14.6 percent), 75-percent (error of 11.8 percent), 55-percent (error of 11.2 percent), and 35-percent duration flows (error of 11.1 percent), respectively. The mean seasonal base flows for spring, summer, fall, and winter are approximately equal to the spring 50- to 55-percent (standard error of 6.8 percent), summer 45- to 50-percent (error of 6.7 percent), fall 45-percent (error of 15.2 percent), and winter 60-percent duration flows (error of 8.5 percent), respectively. Annual and seasonal base flows representative of the period 1930-2002 at unregulated streamflow-gaging stations and ungaged locations in West Virginia can be estimated using previously published

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

Science.gov (United States)

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.

Adaptability and stability of soybean genotypes in off-season cultivation.

Science.gov (United States)

Batista, R O; Hamawaki, R L; Sousa, L B; Nogueira, A P O; Hamawaki, O T

2015-08-14

The oil and protein contents of soybean grains are important quantitative traits for use in breeding. However, few breeding programs perform selection based on these traits in different environments. This study assessed the adaptability and stability of 14 elite early soybean breeding lines in off-season cultivation with respect to yield, and oil and protein contents. A range of statistical methods was applied and these analyses indicated that for off-season cultivation, the lines UFUS 5 and UFUS 10 could be recommended due to their superior performance in grain yield, oil content, and specific adaptability to unfavorable environments along with high stability in these characteristics. Also recommended were UFUS 06, which demonstrated superior performance in all three tested characteristics and showed adaptation to favorable environments, and UFUS 13, which showed high adaptability and stability and a superior performance for protein content.

Behavioral characteristics of Hanwoo ( steers at different growth stages and seasons

Directory of Open Access Journals (Sweden)

Na Yeon Kim

2017-10-01

Full Text Available Objective This research analyzed behavioral characteristics of Hanwoo (Bos taurus coreanae steers during each season and growth stage to enable measurement of the animals’ welfare level for precision livestock farming. Methods A hundred-eight beef steers were divided into three equal groups at a Hanwoo farm according to their growth stage: growing stage (GS, 8 months; early-fattening stage (EFS, 19 months; and late-fattening stage (LFS, 30 months. Twelve behavioral categories were continuously recorded for 13 day-time hours in each four seasons with three replications. Results Time spent standing was found to be significantly longer in summer at all growth stages (p<0.05. Hanwoos at the GS spent significantly longer standing time in spring and summer than those at the EFS and LFS (p<0.05. Lying time in summer was the shortest for all growth stages (p<0.05. Steers at the LFS spent significantly longer lying time than that at the GS (p<0.05 in summer. For GS and EFS, time spent eating in spring and autumn were longer than in summer and winter (p<0.05. Eating time was the longest for the GS in spring, autumn, and winter, excluding for the LFS in winter (p<0.05. Regarding ruminating, steers at the LFS spent significantly shorter time than those at other stages in all seasons (p<0.05. GS and EFS steers showed the longest walking time in summer compared with other seasons (p<0.05. At GS and LFS, drinking time in summer was the longest of all seasons (p<0.05. Sleeping time was significantly shorter in summer compared with the other seasons (p<0.05. Self-grooming time was the longest in winter for all growth stages (p<0.05. Conclusion Steers were found to have more variable behavioral patterns during summer and the GS and less active behaviors during the LFS, thus extra care seems necessary during the GS, LFS, and summer period.

Detrending career statistics in professional baseball: Accounting for the steroids era and beyond

OpenAIRE

Petersen, Alexander M.; Penner, Orion; Stanley, H. Eugene

2010-01-01

There is a long standing debate over how to objectively compare the career achievements of professional athletes from different historical eras. Developing an objective approach will be of particular importance over the next decade as Major League Baseball (MLB) players from the "steroids era" become eligible for Hall of Fame induction. Here we address this issue, as well as the general problem of comparing statistics from distinct eras, by detrending the seasonal statistics of professional b...

Maize response to time of nitrogen application and planting seasons

Directory of Open Access Journals (Sweden)

Parbati Adhikari

2016-12-01

Full Text Available Nitrogen (N response by maize differs due to growing seasons, growth stages, duration and growing domain as N losses is higher due to leaching as well as volatilization. Objective of this study was to know the response of split applications of N and growing seasons on maize under Chitwan environments. Field experiments were conducted for two consecutive years at the research field of NMRP Rampur during the winter, spring, and summer seasons of 2012/013 and 2013/014. Experiments were laid out in factorial randomized complete block design with four replications for all the seasons. Early maturing maize genotype Arun-1 EV was used for the experiments. Five splits of recommended dose of N were tested. Grain yield, days to flowering, plant height, ear height, kernel rows per ear, no. of kernels per row, ear length and thousand grain weight significantly differed due to growing seasons and split applications of N. Significantly higher grain yield (3911 kg ha-1 was obtained with the application of 30 kg N ha-1 each at 30, 45, 60, and 75 days after sowing as compared to control (2801 kg ha-1. Regarding the growing seasons, highest grain yield was obtained in winter (4393 kg ha-1 followed by spring (3791 kg ha-1 and summer (2468 kg ha-1 season, respectively. Results of these studies revealed that four splits of N viz. application of 30 kg N each at 30, 45, 60, and 75 days after sowing respectively, would be more economical to minimize N losses from the soil and efficient use of N at critical growth and development stages of maize.

Variations of Pb in a mine-impacted tropical river, Taxco, Mexico: Use of geochemical, isotopic and statistical tools

Energy Technology Data Exchange (ETDEWEB)

Arcega-Cabrera, F. [Unidad de Quimica en Sisal, Facultad de Quimica, UNAM, Sisal 97355 (Mexico)], E-mail: arcega@icmyl.unam.mx; Armienta, M.A. [Instituto de Geofisica, UNAM, Mexico 04510 (Mexico); Daessle, L.W. [Instituto de Investigaciones Oceanologicas, UABC, Ensenada 22870 (Mexico); Castillo-Blum, S.E. [Facultad de Quimica, UNAM, Mexico 04510 (Mexico); Talavera, O. [Escuela de Ciencias de la Tierra, UAG, Taxco Viejo 40201 (Mexico); Dotor, A. [Instituto de Geofisica, UNAM, Mexico 04510 (Mexico)

2009-01-15

The potential environmental threat from Pb in Mexican rivers impacted by historic mining activities was studied using geochemical, isotopic and statistical methods. Lead geochemical fractionation and factor analysis of fractionated and total Pb indicate that anthropogenic sources have contributed significantly to Pb concentrations, while natural sources have contributed only small amounts. The analyses also indicate that two main processes are controlling the total Pb variation throughout the year in both rivers: erosion with discharge processes, and proportional dilution related to differences in grain-size distribution processes. Bio-available Pb in riverbed sediments was greater than 50% in 80% of the sampling stations indicating a high potential environmental risk, according to the risk assessment criteria (RAC). Nevertheless, based on the environmental chemistry of Pb and on multivariate statistical analysis, these criteria did not apply in this particular case. Significant differences (p < 0.05) in total Pb concentrations (from 50 to 5820 mg kg{sup -1}) and in the geochemical fractionation were observed as a function of seasonality and location along the river flow path. In the Cacalotenango and Taxco rivers, the highest concentrations of total Pb were found at stations close to tailings during the rainy and post-rainy seasons. The geochemistry of Pb was mainly controlled, during the dry and post-rainy seasons by the organic matter and carbonate content, and in the rainy season by hydrological conditions (e.g., the increase in river flux), hydrological basin erosion, and the suspended solids concentration. Isotopic analyses of the {sup 210}Pb/{sup 214}Pb ratio showed three processes in the Cacalotenango and Taxco rivers. First, the accumulation of atmospheric excess {sup 210}Pb, favoured during calmer hydrodynamic conditions in the river basin commonly during dry periods, is recorded by a {sup 210}Pb/{sup 214}Pb ratio of >1. In the case of the Cacalotenango

Seasonal variation of bacterial endophytes in urban trees

Directory of Open Access Journals (Sweden)

Shu Yi eShen

2015-05-01

Full Text Available Bacterial endophytes, non-pathogenic bacteria residing within plants, contribute to the growth and development of plants and their ability to adapt to adverse conditions. In order to fully exploit the capabilities of these bacteria, it is necessary to understand the extent to which endophytic communities vary between species and over time. The endophytes of Acer negundo, Ulmus pumila and Ulmus parvifolia were sampled over three seasons and analyzed using culture dependent and independent methods (culture on two media, terminal restriction fragment length polymorphism, and tagged pyrosequencing of 16S ribosomal amplicons. The majority of culturable endophytes isolated were Actinobacteria, and all the samples harbored Bacillus, Curtobacterium, Frigoribacterium, Methylobacterium, Paenibacilllus and Sphingomonas species. Regardless of culture medium used, only the culturable communities obtained in the winter for A. negundo could be distinguished from those of Ulmus spp.. In contrast, the nonculturable communities were dominated by Proteobacteria and Actinobacteria, particularly Erwinia, Ralstonia and Sanguibacter spp.. The presence and abundance of various bacterial classes and phyla changed with the changing seasons. Multivariate analysis on the culture independent data revealed significant community differences between the endophytic communities of A. negundo and Ulmus spp., but overall season was the main determinant of endophytic community structure. This study suggests investigations of the studies ofendophytic populations of urban trees should expect to find significant seasonal and species-specific community differences and sampling should proceed accordingly.

Seasonal Allergies (Hay Fever)

Science.gov (United States)

... Safe Videos for Educators Search English Español Seasonal Allergies (Hay Fever) KidsHealth / For Parents / Seasonal Allergies (Hay ... español Alergia estacional (fiebre del heno) About Seasonal Allergies "Achoo!" It's your son's third sneezing fit of ...

Seasonal prediction of precipitation over Nigeria | Adeniyi | Journal ...

African Journals Online (AJOL)

While for the training and verification periods of 1986-2012, correlations are not gener-ally significant although some were found to be above the significant level of 5%. For the recon-structed seasonal precipitation, correlations of ten stations were found to be significant at 5 %, but at 10 % level, their number increased to 13.

Seasonal reproduction of vampire bats and its relation to seasonality of bovine rabies.

Science.gov (United States)

Lord, R D

1992-04-01

Studies of pregnancy and lactation in vampire bats (Desmodus rotundus) in northern Argentina over a 4 yr period showed an inverse relationship between prevalence of pregnancy and lactation, the consequence of birth and onset of lactation, which was correlated with the wet season. The seasonal influx of young susceptibles into the vampire population in the wet season coincided with the well known increase in vampire transmitted rabies in that season.

Statistical evaluation of the feasibility of satellite-retrieved cloud parameters as indicators of PM2.5 levels.

Science.gov (United States)

Yu, Chao; Di Girolamo, Larry; Chen, Liangfu; Zhang, Xueying; Liu, Yang

2015-01-01

The spatial and temporal characteristics of fine particulate matter (PM2.5, particulate matter research has been conducted on the association between cloud properties and PM2.5 levels. In this study, we analyzed the relationships between ground PM2.5 concentrations and two satellite-retrieved cloud parameters using data from the Southeastern Aerosol Research and Characterization (SEARCH) Network during 2000-2010. We found that both satellite-retrieved cloud fraction (CF) and cloud optical thickness (COT) are negatively associated with PM2.5 levels. PM2.5 speciation and meteorological analysis suggested that the main reason for these negative relationships might be the decreased secondary particle generation. Stratified analyses by season, land use type, and site location showed that seasonal impacts on this relationship are significant. These associations do not vary substantially between urban and rural sites or inland and coastal sites. The statistically significant negative associations of PM2.5 mass concentrations with CF and COT suggest that satellite-retrieved cloud parameters have the potential to serve as predictors to fill the data gap left by satellite aerosol optical depth in satellite-driven PM2.5 models.