Zooplankton Sample Variation on the Scotian Shelf

1978 ◽  
Vol 35 (9) ◽  
pp. 1207-1222 ◽  
Author(s):  
D. D. Sameoto
Keyword(s):  
Time Series ◽  
Fish Larvae ◽  
Geographic Area ◽  
Scotian Shelf ◽  
Tidal Cycles ◽  
Zooplankton Sample ◽  
Single Station ◽  
The Mean ◽  
One Year ◽  
Abundance And Distribution

Zooplankton sampling experiments on the Scotian Shelf during September 1973 and August 1974 using vertical tows demonstrated that numbers of many zooplankton species had a periodic fluctuation over 26 h. The fluctuations appeared related to the tide during 1974 but not in 1973. The periodic fluctuations accounted for a major portion of the sample variation in many species during both years. The mean numbers of small forms of zooplankton (copepods) obtained from the 26-h time series on a single station were very similar to means obtained during the same cruise over a wide area of the shelf. This suggested that a single station sampled over a period of two tidal cycles may be representative of the sample variation encountered over a wide geographic area of many hundreds of kilometres. Only Calanus and Pseudocalanus were correlated during all the experiments and from year to year. The abundance and distribution of the other species of zooplankton compared from one year to the next were not significantly correlated. This suggested the species populations were independent of one another. Key words: zooplankton, sample variation, time series, Scotian Shelf, fish larvae, Copepoda, tide

Methods for determining "reference changes" from serial measurements: plasma lipid-bound sialic acid.

1989 ◽  
Vol 35 (6) ◽  
pp. 972-974 ◽  
Author(s):  
S Shahangian ◽  
H A Fritsche ◽  
J I Hughes ◽  
D A Johnston
Keyword(s):  
Time Series ◽  
Sialic Acid ◽  
Healthy Subjects ◽  
Plasma Lipid ◽  
Autoregressive Time Series ◽  
The Mean ◽  
One Year ◽  
Mean Variance ◽  
Serial Measurements ◽  
Colorectal Adenocarcinomas

Abstract Lipid-bound sialic (neuraminic) acid (LSA) was measured in EDTA-treated plasma of 26 healthy subjects at three-month intervals for up to one year. The change in LSA concentration for consecutive measurements ranged from -54 to 42 mg/L (mean, -2.1 mg/L; SD, 19.6 mg/L; n = 56). The "reference change" for plasma LSA (+/- 2 SD), calculated from distribution of the differences, was +/- 39 mg/L. The 88th percentile of the intra-individual variance was 338 mg2/L2 and the mean variance was 159 mg2/L2. Using the homeostatic, autoregressive time-series model, a reference change of +/- 51 mg/L between two consecutive measurements was determined to be statistically significant (i.e., expected by chance no more than 5% of the time) in 88% of the healthy subjects. Only 73% of the healthy subjects would have had intra-individual variances corresponding to the reference change of +/- 39 mg/L according to the autoregressive model. The concentration of LSA in plasma was significantly decreased upon surgery in five of 10 patients with colorectal adenocarcinomas of Dukes stages A-C when we used +/- 39 mg/L as the reference change, but in only two of the 10 when we used +/- 51 mg/L as the reference change.

scholarly journals Time Series Analysis of Mean Monthly Temperature in the Far Western Ethiopia, Assosa District

2020 ◽  
Author(s):  
Tigabu Hailu Kassa ◽  
Shewayiref Geremew Gebremichael
Keyword(s):  
Time Series ◽  
Arima Model ◽  
Descriptive Statistics ◽  
Mean Annual Temperature ◽  
Temperature Pattern ◽  
First Order ◽  
Monthly Temperature ◽  
The Mean ◽  
One Year ◽  
Western Ethiopia

Abstract BackgroundThis study investigated the mean monthly temperature pattern of the Assosa district, Western Ethiopia. The objective of this study was to analyze the mean monthly temperature patterns in the Assosa district for the period from January 2012 to December 2016 based on data from meteorological stations in the Assosa district.MethodsDescriptive statistics and univariate Box-Jenkins methodology to build the seasonal ARIMA model were used.ResultsThe results showed that the mean annual temperature of Assosa was 28.025 degree Celsius. The original series was found to be seasonally non-stationary, as indicated by the ACF plot of the series. After using first-order seasonal differencing, the series was found to be stationary. A time-series model for the Assosa station was adjusted, processed, diagnostically checked, and finally, an ARIMA (3.0.1) model is established and this model is used to forecast one-year mean monthly temperature values. ConclusionThe forecasted mean temperature values showed a similar pattern to previous recordings.

scholarly journals Time-variability of the fraction of young water in a small headwater catchment

2019 ◽  
Author(s):  
Michael P. Stockinger ◽  
Heye R. Bogena ◽  
Andreas Lücke ◽  
Christine Stumpp ◽  
Harry Vereecken
Keyword(s):  
Time Series ◽  
Time Window ◽  
High Sensitivity ◽  
Annual Runoff ◽  
Nutrient Loss ◽  
Time Variability ◽  
Short Term ◽  
Sampling Campaign ◽  
The Mean ◽  
One Year

Abstract. The time precipitation needs to travel through a catchment to its outlet is an important descriptor of a catchment's susceptibility to pollutant contamination, nutrient loss and hydrological functioning. The fast component of total water flow can be estimated by the fraction of young water (Fyw) which is the percentage of streamflow younger than three months. Fyw is calculated by comparing the amplitudes of sine waves fitted to seasonal precipitation and streamflow tracer signals. This is usually done for the complete tracer time series available neglecting annual differences in the amplitudes of longer time series. Considering inter-annual amplitude differences, we here employed a moving time window of one-year length in weekly time steps over a 4.5-years δ18O tracer time series to calculate 189 Fyw results. The results were then tested against the following null hypotheses, defining 2 % difference in Fyw as significant based on results of previous studies: (1) Fyw does not deviate more than ±2% from the mean of all Fyw results indicating long-term invariance. Larger deviations would indicate either flow path changes or a change in the relative contribution of different flow paths; (2) for any four-week window Fyw does not change more than ±2 % indicating short-term invariance. Larger deviations would indicate a high sensitivity of Fyw to a 1–4 weeks shift in the start of a one-year sampling campaign; (3) for a given calendar month Fyw does not change more than ±2 % indicating seasonal invariance of Fyw. In our study, all three null hypotheses were rejected. Thus, the Fyw results were time-variable, showed a high variability in the chosen sampling time and had no pronounced seasonality. Based on high short-term variability of Fyw when the mean adjusted R² was below 0.2 we recommend that a low R2 should be regarded as indicating potentially highly uncertain Fyw results. Furthermore, while investigated individual meteorological factors could not sufficiently explain variations of Fyw, the runoff coefficient showed a moderate negative correlation of r = −0.54 with Fyw. This indicated that when annual runoff exceeded precipitation the catchment received the water deficit from storage which is old water causing a decrease in Fyw. The results of this study suggest that care must be taken when comparing Fyw of catchments that were based on different calculation time periods.

Der Sommer und Herbst 2003 aus phänologischer Sicht | Summer and autumn 2003 from a phenological point of view

2004 ◽  
Vol 155 (5) ◽  
pp. 142-145 ◽  
Author(s):  
Claudio Defila
Keyword(s):  
Time Series ◽  
New Record ◽  
Point Of View ◽  
Late Spring ◽  
Mean Deviation ◽  
Leaf Shedding ◽  
The Mean ◽  
Very High ◽  
Selection Of

The record-breaking heatwave of 2003 also had an impact on the vegetation in Switzerland. To examine its influences seven phenological late spring and summer phases were evaluated together with six phases in the autumn from a selection of stations. 30% of the 122 chosen phenological time series in late spring and summer phases set a new record (earliest arrival). The proportion of very early arrivals is very high and the mean deviation from the norm is between 10 and 20 days. The situation was less extreme in autumn, where 20% of the 103 time series chosen set a new record. The majority of the phenological arrivals were found in the class «normal» but the class«very early» is still well represented. The mean precocity lies between five and twenty days. As far as the leaf shedding of the beech is concerned, there was even a slight delay of around six days. The evaluation serves to show that the heatwave of 2003 strongly influenced the phenological events of summer and spring.

scholarly journals The influence of solar wind on extratropical cyclones – Part 1: Wilcox effect revisited

2009 ◽  
Vol 27 (1) ◽  
pp. 1-30 ◽  
Author(s):  
P. Prikryl ◽  
V. Rušin ◽  
M. Rybanský
Keyword(s):  
Time Series ◽  
Solar Wind ◽  
Northern Hemisphere ◽  
High Speed ◽  
Coronal Holes ◽  
Extratropical Cyclones ◽  
Sector Boundary ◽  
Speed Solar Wind ◽  
The Mean ◽  
High Speed Solar Wind

Abstract. A sun-weather correlation, namely the link between solar magnetic sector boundary passage (SBP) by the Earth and upper-level tropospheric vorticity area index (VAI), that was found by Wilcox et al. (1974) and shown to be statistically significant by Hines and Halevy (1977) is revisited. A minimum in the VAI one day after SBP followed by an increase a few days later was observed. Using the ECMWF ERA-40 re-analysis dataset for the original period from 1963 to 1973 and extending it to 2002, we have verified what has become known as the "Wilcox effect" for the Northern as well as the Southern Hemisphere winters. The effect persists through years of high and low volcanic aerosol loading except for the Northern Hemisphere at 500 mb, when the VAI minimum is weak during the low aerosol years after 1973, particularly for sector boundaries associated with south-to-north reversals of the interplanetary magnetic field (IMF) BZ component. The "disappearance" of the Wilcox effect was found previously by Tinsley et al. (1994) who suggested that enhanced stratospheric volcanic aerosols and changes in air-earth current density are necessary conditions for the effect. The present results indicate that the Wilcox effect does not require high aerosol loading to be detected. The results are corroborated by a correlation with coronal holes where the fast solar wind originates. Ground-based measurements of the green coronal emission line (Fe XIV, 530.3 nm) are used in the superposed epoch analysis keyed by the times of sector boundary passage to show a one-to-one correspondence between the mean VAI variations and coronal holes. The VAI is modulated by high-speed solar wind streams with a delay of 1–2 days. The Fourier spectra of VAI time series show peaks at periods similar to those found in the solar corona and solar wind time series. In the modulation of VAI by solar wind the IMF BZ seems to control the phase of the Wilcox effect and the depth of the VAI minimum. The mean VAI response to SBP associated with the north-to-south reversal of BZ is leading by up to 2 days the mean VAI response to SBP associated with the south-to-north reversal of BZ. For the latter, less geoeffective events, the VAI minimum deepens (with the above exception of the Northern Hemisphere low-aerosol 500-mb VAI) and the VAI maximum is delayed. The phase shift between the mean VAI responses obtained for these two subsets of SBP events may explain the reduced amplitude of the overall Wilcox effect. In a companion paper, Prikryl et al. (2009) propose a new mechanism to explain the Wilcox effect, namely that solar-wind-generated auroral atmospheric gravity waves (AGWs) influence the growth of extratropical cyclones. It is also observed that severe extratropical storms, explosive cyclogenesis and significant sea level pressure deepenings of extratropical storms tend to occur within a few days of the arrival of high-speed solar wind. These observations are discussed in the context of the proposed AGW mechanism as well as the previously suggested atmospheric electrical current (AEC) model (Tinsley et al., 1994), which requires the presence of stratospheric aerosols for a significant (Wilcox) effect.

scholarly journals Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores

2019 ◽  
Vol 23 (10) ◽  
pp. 4323-4331 ◽  
Author(s):  
Wouter J. M. Knoben ◽  
Jim E. Freer ◽  
Ross A. Woods
Keyword(s):  
Time Series ◽  
Coefficient Of Variation ◽  
Ad Hoc ◽  
Model Performance ◽  
Technical Note ◽  
Mean Flow ◽  
Model Adequacy ◽  
Robust Model ◽  
The Mean ◽  
Adequacy Assessment

Abstract. A traditional metric used in hydrology to summarize model performance is the Nash–Sutcliffe efficiency (NSE). Increasingly an alternative metric, the Kling–Gupta efficiency (KGE), is used instead. When NSE is used, NSE = 0 corresponds to using the mean flow as a benchmark predictor. The same reasoning is applied in various studies that use KGE as a metric: negative KGE values are viewed as bad model performance, and only positive values are seen as good model performance. Here we show that using the mean flow as a predictor does not result in KGE = 0, but instead KGE =1-√2≈-0.41. Thus, KGE values greater than −0.41 indicate that a model improves upon the mean flow benchmark – even if the model's KGE value is negative. NSE and KGE values cannot be directly compared, because their relationship is non-unique and depends in part on the coefficient of variation of the observed time series. Therefore, modellers who use the KGE metric should not let their understanding of NSE values guide them in interpreting KGE values and instead develop new understanding based on the constitutive parts of the KGE metric and the explicit use of benchmark values to compare KGE scores against. More generally, a strong case can be made for moving away from ad hoc use of aggregated efficiency metrics and towards a framework based on purpose-dependent evaluation metrics and benchmarks that allows for more robust model adequacy assessment.

scholarly journals Incomplete Kawasaki disease - a diagnostic and therapeutic challenge

2014 ◽  
Vol 9 (4) ◽  
pp. 30-35
Author(s):  
S Datta ◽  
S Maiti ◽  
G Das ◽  
A Chatterjee ◽  
P Ghosh
Keyword(s):  
Kawasaki Disease ◽  
Intravenous Immunoglobulin ◽  
Incomplete Kawasaki Disease ◽  
Duration Of Symptoms ◽  
Clinical Criteria ◽  
Echocardiographic Finding ◽  
2D Echocardiography ◽  
Acquired Heart Disease ◽  
The Mean ◽  
One Year

Background The diagnosis of classical Kawasaki Disease was based on clinical criteria. The conventional criteria is particularly useful in preventing over diagnosis, but at the same time it may result in failure to recognize the incomplete form of Kawasaki Disease. Objective To suspect incomplete Kawasaki Disease, because early diagnosis and proper treatment may reduce substantial risk of developing coronary artery abnormality which is one of the leading causes of acquired heart disease in children. Method Nine cases of incomplete Kawasaki Disease were diagnosed over a period of one year. The diagnosis of incomplete Kawasaki Disease was based on fever for five days with less than four classical clinical features and cardiac abnormality detected by 2D- echocardiography. A repeat echocardiography was done after 6 weeks of onset of illness. The patients were treated with Intravenous Immunoglobulin and/or aspirin. Result The mean age of the patients was 3.83 years and the mean duration of symptoms before diagnosis was 12.1 days. Apart from other criteria all of our patients had edema and extreme irritability. All the patients had abnormal echocardiographic finding. Five patients received only aspirin due to nonaffordability of Intravenous Immunoglobulin and four patients received both aspirin and Intravenous Immunoglobulin, but the outcome was excellent in all the cases. Conclusion Incomplete Kawasaki Disease can be diagnosed with more awareness and aspirin alone may be used as a second line therapy in case of non affordability of Intravenous Immunoglobulin. Journal of College of Medical Sciences-Nepal, 2013, Vol-9, No-4, 30-35 DOI: http://dx.doi.org/10.3126/jcmsn.v9i4.10234

scholarly journals Modeling of Lake Malombe Annual Fish Landings and Catch per Unit Effort (CPUE)

Forecasting ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 39-55
Author(s):  
Rodgers Makwinja ◽  
Seyoum Mengistou ◽  
Emmanuel Kaunda ◽  
Tena Alemiew ◽  
Titus Bandulo Phiri ◽  
...  
Keyword(s):  
Time Series ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Efficiency Coefficient ◽  
Arima Models ◽  
Catch Per Unit Effort ◽  
Annual Fish ◽  
Unit Effort ◽  
The Mean

Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with increased reliability and precision. In this paper, ARIMA models were applied to predict Lake Malombe annual fish landings and catch per unit effort (CPUE). The annual fish landings and CPUE trends were first observed and both were non-stationary. The first-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), Akaike information criterion (AIC), Bayesian information criterion (BIC), square root of the mean square error (RMSE), the mean absolute error (MAE), percentage standard error of prediction (SEP), average relative variance (ARV), Gaussian maximum likelihood estimation (GMLE) algorithm, efficiency coefficient (E2), coefficient of determination (R2), and persistent index (PI) were estimated, which led to the identification and construction of ARIMA models, suitable in explaining the time series and forecasting. According to the measures of forecasting accuracy, the best forecasting models for fish landings and CPUE were ARIMA (0,1,1) and ARIMA (0,1,0). These models had the lowest values AIC, BIC, RMSE, MAE, SEP, ARV. The models further displayed the highest values of GMLE, PI, R2, and E2. The “auto. arima ()” command in R version 3.6.3 further displayed ARIMA (0,1,1) and ARIMA (0,1,0) as the best. The selected models satisfactorily forecasted the fish landings of 2725.243 metric tons and CPUE of 0.097 kg/h by 2024.

scholarly journals Development of Perceptual Inhibition in Adolescents—a Critical Period?

Symmetry ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 457
Author(s):  
Isabel María Introzzi ◽  
María Marta Richard’s ◽  
Yesica Aydmune ◽  
Eliana Vanesa Zamora ◽  
Florencia Stelzer ◽  
...  
Keyword(s):  
Response Time ◽  
Executive Functions ◽  
Critical Period ◽  
Search Task ◽  
Probability Distributions ◽  
Linear Trajectory ◽  
Gaussian Functions ◽  
Mean Response Time ◽  
The Mean ◽  
One Year

Recent studies suggest that the developmental curves in adolescence, related to the development of executive functions, could be fitted to a non-linear trajectory of development with progressions and retrogressions. Therefore, the present study proposes to analyze the pattern of development in Perceptual Inhibition (PI), considering all stages of adolescence (early, middle, and late) in intervals of one year. To this aim, we worked with a sample of 275 participants between 10 and 25 years, who performed a joint visual and search task (to measure PI). We have fitted ex-Gaussian functions to the probability distributions of the mean response time across the sample and performed a covariance analysis (ANCOVA). The results showed that the 10- to 13-year-old groups performed similarly in the task and differ from the 14- to 19-year-old participants. We found significant differences between the older group and all the rest of the groups. We discuss the important changes that can be observed in relation to the nonlinear trajectory of development that would show the PI during adolescence.

scholarly journals Distance variable improvement of time-series big data stream evaluation

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Ari Wibisono ◽  
Petrus Mursanto ◽  
Jihan Adibah ◽  
Wendy D. W. T. Bayu ◽  
May Iffah Rizki ◽  
...  
Keyword(s):  
Time Series ◽  
Standard Deviation ◽  
Standard Method ◽  
Time Series Data ◽  
Series Data ◽  
Percentage Error ◽  
Traffic Demand ◽  
Incremental Model ◽  
Chernoff Bound ◽  
The Mean

Abstract Real-time information mining of a big dataset consisting of time series data is a very challenging task. For this purpose, we propose using the mean distance and the standard deviation to enhance the accuracy of the existing fast incremental model tree with the drift detection (FIMT-DD) algorithm. The standard FIMT-DD algorithm uses the Hoeffding bound as its splitting criterion. We propose the further use of the mean distance and standard deviation, which are used to split a tree more accurately than the standard method. We verify our proposed method using the large Traffic Demand Dataset, which consists of 4,000,000 instances; Tennet’s big wind power plant dataset, which consists of 435,268 instances; and a road weather dataset, which consists of 30,000,000 instances. The results show that our proposed FIMT-DD algorithm improves the accuracy compared to the standard method and Chernoff bound approach. The measured errors demonstrate that our approach results in a lower Mean Absolute Percentage Error (MAPE) in every stage of learning by approximately 2.49% compared with the Chernoff Bound method and 19.65% compared with the standard method.

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