scholarly journals Automated flight-interception traps for interval sampling of insects

PLoS ONE ◽  
2020 ◽  
Vol 15 (7) ◽  
pp. e0229476
Author(s):  
Janine Bolliger ◽  
Marco Collet ◽  
Michael Hohl ◽  
Martin K. Obrist
Keyword(s):  
Interval Sampling

scholarly journals Online Doppler Effect Elimination Based on Unequal Time Interval Sampling for Wayside Acoustic Bearing Fault Detecting System

Sensors ◽  
2015 ◽  
Vol 15 (9) ◽  
pp. 21075-21098 ◽  
Author(s):  
Kesai Ouyang ◽  
Siliang Lu ◽  
Shangbin Zhang ◽  
Haibin Zhang ◽  
Qingbo He ◽  
...  
Keyword(s):  
Doppler Effect ◽  
Time Interval ◽  
Bearing Fault ◽  
Interval Sampling

Temporal aggregation of random walk processes and implications for economic analysis

2019 ◽  
Vol 24 (2) ◽  
Author(s):  
Yamin S Ahmad ◽  
Ivan Paya
Keyword(s):  
Random Walk ◽  
Autoregressive Process ◽  
Potential Effect ◽  
Temporal Aggregation ◽  
Time Averaging ◽  
Fat Tails ◽  
Data Generating Process ◽  
Variance Ratios ◽  
Interval Sampling ◽  
The Impact

AbstractThis paper examines the impact of time averaging and interval sampling data assuming that the data generating process for a given series follows a random walk with iid errors. We provide exact expressions for the corresponding variances, and covariances, for both levels and higher order differences of the aggregated series, as well as that for the variance ratio, demonstrating exactly how the degree of temporal aggregation impacts these properties. We empirically investigate this issue on exchange rates and find that the values of the variance ratios and autocorrelation coefficients at different frequencies are consistent with our theoretical results. We also conduct a simulation exercise that illustrates the potential effect that conditional heteroskedasticity and fat tails may have on the temporal aggregation of a random walk and of a highly persistent autoregressive process.

scholarly journals Finger Sweat Analysis Enables Short Interval Metabolic Biomonitoring in Humans

2020 ◽  
Author(s):  
Julia Brunmair ◽  
Laura Niederstaetter ◽  
Benjamin Neuditschko ◽  
Andrea Bileck ◽  
Astrid Slany ◽  
...  
Keyword(s):  
Time Course ◽  
Biomarker Discovery ◽  
Short Interval ◽  
Coffee Consumption ◽  
Medical Diagnostics ◽  
Clinical Routine ◽  
Non Invasive ◽  
Sweat Production ◽  
Interval Sampling ◽  
Sampling Procedures

AbstractMetabolic biomonitoring in humans is typically based on the sampling of blood, plasma or urine. Although established in the clinical routine, these sampling procedures are often associated with a variety of compliance issues and are impractical for performing time-course studies. The analysis of the minute amounts of sweat sampled from the fingertip enables a solution to this challenge. Sweat sampling from the fingertip is non-invasive and robust and can be accomplished repeatedly by untrained personnel. This matrix represents a rich source for metabolomic phenotyping, which is exemplified by the detection of roughly 50’000 features per sample. Moreover, the determined limits of detection demonstrate that the ingestion of 200 μg of a xenobiotic may be sufficient for its detection in sweat from the fingertip. The feasibility of short interval sampling of sweat from the fingertips was confirmed in three time-course studies after coffee consumption or ingestion of a caffeine capsule, successfully monitoring all known caffeine metabolites. Fluctuations in the rate of sweat production were accounted for by mathematical modelling to reveal individual rates of caffeine uptake, metabolism and clearance. Biomonitoring using sweat from the fingertip has far reaching implications for personalised medical diagnostics and biomarker discovery.

Estimation of Parameters of Zero-One Processes by Interval Sampling

1977 ◽  
Vol 25 (3) ◽  
pp. 493-505 ◽  
Author(s):  
M. Brown ◽  
H. Solomon ◽  
M. A. Stephens
Keyword(s):  
Estimation Of Parameters ◽  
Interval Sampling

scholarly journals Technique to study the impact of large herbivores on woody vegetation within piospheres

Koedoe ◽  
2000 ◽  
Vol 43 (2) ◽  
Author(s):  
J. Brits ◽  
M.W. Van Rooyen ◽  
N. Van Rooyen
Keyword(s):  
Soil Type ◽  
Environmental Heterogeneity ◽  
Original Data ◽  
Logistic Function ◽  
Woody Vegetation ◽  
Large Herbivores ◽  
Structural Variables ◽  
Interval Sampling ◽  
The Impact ◽  
Made In

A continuously sampled transect away from a watering point provides good results in situations where geology and soil type remain constant, but is unsuitable to apply where regular changes in soil type occur. A comparison was made between a continuously sampled transect and sampling taken at intervals along the transect. An analysis of variance indicated no significant differences in any of the variables obtained by means of the two sampling methods. The advantage of interval sampling is that, within each zone, areas with the same soil type can be selected in order to avoid environmental heterogeneity. A comparison between transects made in different directions from the watering point yielded no significant differences in any of the structural variables of the woody vegetation at the same distance from the watering point. Therefore, combining transects from different directions to attain a representative sample away from the watering point was an acceptable practice. It is recommended that the original data be smoothed and the logistic function used to model the impact of large herbivores on the structure of the woody vegetation around watering points.

Synchronization ofE. coliO157 shedding in a grass-fed beef herd: a longitudinal study

2015 ◽  
Vol 143 (15) ◽  
pp. 3244-3255 ◽  
Author(s):  
G. A. C. LAMMERS ◽  
C. S. McCONNEL ◽  
D. JORDAN ◽  
M. S. AYTON ◽  
S. MORRIS ◽  
...  
Keyword(s):  
Risk Factors ◽  
Temporal Dynamics ◽  
Short Interval ◽  
Beef Cows ◽  
E Coli ◽  
Faecal Samples ◽  
Sampling Points ◽  
Negative Effect ◽  
Beef Herd ◽  
Interval Sampling

SUMMARYThis study aims to describe in detail the temporal dynamics ofE. coliO157 shedding and risk factors for shedding in a grass-fed beef herd. During a 9-month period, 23 beef cows were sampled twice a week (58 sampling points) andE. coliO157 was enumerated from faecal samples. Isolates were screened by PCR for presence ofrfbE,stx1andstx2. The prevalence per sampling day ranged from 0% to 57%. This study demonstrates that many members of the herd were concurrently sheddingE. coliO157. Occurrence of rainfall (P< 0·01), feeding silage (P< 0·01) and lactating (P< 0·01) were found to be predictors of shedding. Moving cattle to a new paddock had a negative effect on shedding. This approach, based on short-interval sampling, confirms the known variability of shedding within a herd and highlights that high shedding events are rare.

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