Elimination of some integration errors in pesticide residue analyses

1975 ◽  
Vol 47 (14) ◽  
pp. 2485-2486 ◽  
Author(s):  
J. M. Zehner ◽  
R. A. Simonaitis
Keyword(s):  
Pesticide Residue ◽  
Integration Errors

Symmetric Multistep Methods Revisited: II. Numerical Experiments

1999 ◽  
Vol 173 ◽  
pp. 309-314 ◽  
Author(s):  
T. Fukushima
Keyword(s):  
Multistep Methods ◽  
Computational Time ◽  
Integration Time ◽  
Implicit Methods ◽  
Symmetric Methods ◽  
Celestial Bodies ◽  
The Stability ◽  
Predictor Corrector ◽  
Symmetric Multistep Methods ◽  
Integration Errors

AbstractBy using the stability condition and general formulas developed by Fukushima (1998 = Paper I) we discovered that, just as in the case of the explicit symmetric multistep methods (Quinlan and Tremaine, 1990), when integrating orbital motions of celestial bodies, the implicit symmetric multistep methods used in the predictor-corrector manner lead to integration errors in position which grow linearly with the integration time if the stepsizes adopted are sufficiently small and if the number of corrections is sufficiently large, say two or three. We confirmed also that the symmetric methods (explicit or implicit) would produce the stepsize-dependent instabilities/resonances, which was discovered by A. Toomre in 1991 and confirmed by G.D. Quinlan for some high order explicit methods. Although the implicit methods require twice or more computational time for the same stepsize than the explicit symmetric ones do, they seem to be preferable since they reduce these undesirable features significantly.

178. Characterizing Pesticide Residue Transfer Efficiencies Using Fluorescent Tracer Imaging Techniques

2002 ◽  
Author(s):  
E. Cohen Hubal ◽  
J. Suggs ◽  
N. Tulve ◽  
M. Nishioka
Keyword(s):  
Pesticide Residue ◽  
Imaging Techniques ◽  
Fluorescent Tracer ◽  
Tracer Imaging

QMC integration errors and quasi-asymptotics

2020 ◽  
Vol 26 (3) ◽  
pp. 171-176
Author(s):  
Ilya M. Sobol ◽  
Boris V. Shukhman
Keyword(s):  
Monte Carlo ◽  
Error Estimate ◽  
Numerical Experiments ◽  
Probable Error ◽  
Quasi Monte Carlo ◽  
Integration Error ◽  
Asymptotic Error ◽  
Dimensional Cube ◽  
Integration Errors ◽  
Mc Method

AbstractA crude Monte Carlo (MC) method allows to calculate integrals over a d-dimensional cube. As the number N of integration nodes becomes large, the rate of probable error of the MC method decreases as {O(1/\sqrt{N})}. The use of quasi-random points instead of random points in the MC algorithm converts it to the quasi-Monte Carlo (QMC) method. The asymptotic error estimate of QMC integration of d-dimensional functions contains a multiplier {1/N}. However, the multiplier {(\ln N)^{d}} is also a part of the error estimate, which makes it virtually useless. We have proved that, in the general case, the QMC error estimate is not limited to the factor {1/N}. However, our numerical experiments show that using quasi-random points of Sobol sequences with {N=2^{m}} with natural m makes the integration error approximately proportional to {1/N}. In our numerical experiments, {d\leq 15}, and we used {N\leq 2^{40}} points generated by the SOBOLSEQ16384 code published in 2011. In this code, {d\leq 2^{14}} and {N\leq 2^{63}}.

Property-based sensitivity analysis: An approach to identify model implementation and integration errors

2021 ◽  
pp. 105013
Author(s):  
Takuya Iwanaga ◽  
Xifu Sun ◽  
Qian Wang ◽  
Joseph H.A. Guillaume ◽  
Barry F.W. Croke ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Integration Errors

Post-harvest recognition of various fungicide treatments for downy mildew of hops using comprehensive pesticide residue monitoring

2020 ◽  
pp. 1-11
Author(s):  
Martin Dušek ◽  
Josef Vostřel ◽  
Vladimíra Jandovská ◽  
Alexandr Mikyška
Keyword(s):  
Downy Mildew ◽  
Pesticide Residue ◽  
Post Harvest

scholarly journals Spatiotemporal Visualization of Insecticides and Fungicides within Fruits and Vegetables Using Gold Nanoparticle-Immersed Paper Imprinting Mass Spectrometry Imaging

Nanomaterials ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1327
Author(s):  
Run Qin ◽  
Ping Li ◽  
Mingyi Du ◽  
Lianlian Ma ◽  
Yudi Huang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Food Safety ◽  
Gold Nanoparticle ◽  
Pesticide Residue ◽  
Rational Design ◽  
Mass Spectrometry Imaging ◽  
Fruits And Vegetables ◽  
Detection Methods ◽  
Safety Issues ◽  
Spatiotemporal Visualization

Food safety issues caused by pesticide residue have exerted far-reaching impacts on human daily life, yet the available detection methods normally focus on surface residue rather than pesticide penetration to the internal area of foods. Herein, we demonstrated gold nanoparticle (AuNP)-immersed paper imprinting mass spectrometry imaging (MSI) for monitoring pesticide migration behaviors in various fruits and vegetables (i.e., apple, cucumber, pepper, plum, carrot, and strawberry). By manually stamping food tissues onto AuNP-immersed paper, this method affords the spatiotemporal visualization of insecticides and fungicides within fruits and vegetables, avoiding tedious and time-consuming sample preparation. Using the established MSI platform, we can track the migration of insecticides and fungicides into the inner region of foods. The results revealed that both the octanol-water partition coefficient of pesticides and water content of garden stuffs could influence the discrepancy in the migration speed of pesticides into food kernels. Taken together, this nanopaper imprinting MSI is poised to be a powerful tool because of its simplicity, rapidity, and easy operation, offering the potential to facilitate further applications in food analysis. Moreover, new perspectives are given to provide guidelines for the rational design of novel pesticide candidates, reducing the risk of food safety issues caused by pesticide residue.

scholarly journals A high-fidelity realization of the Euclid code comparison N-body simulation with Abacus

2019 ◽  
Vol 485 (3) ◽  
pp. 3370-3377 ◽  
Author(s):  
Lehman H Garrison ◽  
Daniel J Eisenstein ◽  
Philip A Pinto
Keyword(s):  
Power Spectrum ◽  
High Performance ◽  
High Fidelity ◽  
Step Size ◽  
Time Step ◽  
Code Comparison ◽  
Force Accuracy ◽  
Integration Errors ◽  
Better Than ◽  
Good Agreement

Abstract We present a high-fidelity realization of the cosmological N-body simulation from the Schneider et al. code comparison project. The simulation was performed with our AbacusN-body code, which offers high-force accuracy, high performance, and minimal particle integration errors. The simulation consists of 20483 particles in a $500\ h^{-1}\, \mathrm{Mpc}$ box for a particle mass of $1.2\times 10^9\ h^{-1}\, \mathrm{M}_\odot$ with $10\ h^{-1}\, \mathrm{kpc}$ spline softening. Abacus executed 1052 global time-steps to z = 0 in 107 h on one dual-Xeon, dual-GPU node, for a mean rate of 23 million particles per second per step. We find Abacus is in good agreement with Ramses and Pkdgrav3 and less so with Gadget3. We validate our choice of time-step by halving the step size and find sub-percent differences in the power spectrum and 2PCF at nearly all measured scales, with ${\lt }0.3{{\ \rm per\ cent}}$ errors at $k\lt 10\ \mathrm{Mpc}^{-1}\, h$. On large scales, Abacus reproduces linear theory better than 0.01 per cent. Simulation snapshots are available at http://nbody.rc.fas.harvard.edu/public/S2016.

scholarly journals Rapid Separation of Fat for Pesticide Residue Analysis of Milk Products

1964 ◽  
Vol 47 (9) ◽  
pp. 1013-1014 ◽  
Author(s):  
Lincoln M. Lampert
Keyword(s):  
Pesticide Residue ◽  
Residue Analysis ◽  
Pesticide Residue Analysis ◽  
Rapid Separation ◽  
Milk Products
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