scholarly journals Optimal Sampling and Christoffel Functions on General Domains

2021 ◽  
Author(s):  
Matthieu Dolbeault ◽  
Albert Cohen
Keyword(s):  
Optimal Sampling ◽  
Christoffel Functions

The comparison of the diversity of activated sludge plants

1998 ◽  
Vol 37 (4-5) ◽  
pp. 71-78 ◽  
Author(s):  
Thomas P. Curtis ◽  
Noel G. Craine
Keyword(s):  
Cluster Analysis ◽  
Activated Sludge ◽  
Treatment Process ◽  
Denaturing Gradient Gel Electrophoresis ◽  
Optimal Sampling ◽  
Bacterial Populations ◽  
Large Numbers ◽  
Probable Presence ◽  
Gradient Gel Electrophoresis ◽  
Sampling Regime

The explicit engineering of bacterial populations requires that we know which organisms perform which tasks. The comparison of the bacterial diversity of activated sludge plants may give important information about the functions of different bacteria. This difficult task may be made easier by the use of technologies based on 16S rRNA based techniques. In this study we have used denaturing gradient gel electrophoresis (DGGE) to determine the optimal sampling regime for comparative studies and used cluster analysis to show how plants may be quantitatively compared. We sought evidence of spatial, diurnal and intrasample variation in a number of sites. No evidence for variation was found in the plants studied and we concluded that a single sample of an activated sludge plant was sufficient for a plant to plant comparison. The cluster analysis was able to distinguish between plants, though further work is required to find the most appropriate basis for such comparisons. We found organisms from raw sewage in the mixed liquor samples, these organisms may have no functional significance in the treatment process and thus complicate plant to plant comparisons as will the probable presence of heteroduplex rDNA products. Nevertheless we believe that these drawbacks do not outweigh the advantages of being able to take and compare relatively large numbers of samples.

scholarly journals Optimal sampling of dynamical large deviations via matrix product states

2021 ◽  
Vol 103 (6) ◽  
Author(s):  
Luke Causer ◽  
Mari Carmen Bañuls ◽  
Juan P. Garrahan
Keyword(s):  
Large Deviations ◽  
Matrix Product ◽  
Optimal Sampling ◽  
Matrix Product States

scholarly journals Log-concave polynomials IV: approximate exchange, tight mixing times, and near-optimal sampling of forests

2021 ◽  
Author(s):  
Nima Anari ◽  
Kuikui Liu ◽  
Shayan Oveis Gharan ◽  
Cynthia Vinzant ◽  
Thuy-Duong Vuong
Keyword(s):  
Optimal Sampling ◽  
Mixing Times

scholarly journals A Review of Precision Technologies for Optimising Pasture Measurement on Irish Grassland

Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 600
Author(s):  
Darren J. Murphy ◽  
Michael D. Murphy ◽  
Bernadette O’Brien ◽  
Michael O’Donovan
Keyword(s):  
Remote Sensing ◽  
Precise Measurement ◽  
Production Systems ◽  
Measurement Techniques ◽  
Grassland Management ◽  
Management Systems ◽  
Sampling Techniques ◽  
Optimal Sampling ◽  
Labour Costs ◽  
Grassland Production

The development of precision grass measurement technologies is of vital importance to securing the future sustainability of pasture-based livestock production systems. There is potential to increase grassland production in a sustainable manner by achieving a more precise measurement of pasture quantity and quality. This review presents an overview of the most recent seminal research pertaining to the development of precision grass measurement technologies. One of the main obstacles to precision grass measurement, sward heterogeneity, is discussed along with optimal sampling techniques to address this issue. The limitations of conventional grass measurement techniques are outlined and alternative new terrestrial, proximal, and remote sensing technologies are presented. The possibilities of automating grass measurement and reducing labour costs are hypothesised and the development of holistic online grassland management systems that may facilitate these goals are further outlined.

scholarly journals Optimal Sampling Strategies for Detecting Zoonotic Disease Epidemics

2014 ◽  
Vol 10 (6) ◽  
pp. e1003668 ◽  
Author(s):  
Jake M. Ferguson ◽  
Jessica B. Langebrake ◽  
Vincent L. Cannataro ◽  
Andres J. Garcia ◽  
Elizabeth A. Hamman ◽  
...  
Keyword(s):  
Zoonotic Disease ◽  
Optimal Sampling ◽  
Sampling Strategies ◽  
Disease Epidemics
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