Rat Insulin ELISA Kit (DEIA1875)

Regulatory status: For research use only, not for use in diagnostic procedures.

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Size
96T
Sample
serum, plasma
Species Reactivity
Rat
Intended Use
The Rat Insulin ELISA Kit provides a method for the quantitative determination of insulin in rat serum or plasma.
Contents of Kit
1. 1 plate, 96 wells, Ready for use.
2. Standards 1, 2, 3, 4, 5, 5 vials, 500 μL, Ready for use
3. Standard 0, 1 vial, 5 mL, Ready for use, Color coded yellow.
4. Enzyme Conjugate 11X, 1 vial, 600 μL, Preparation, see below
5. Enzyme Conjugate Buffer, 1 vial, 6 mL, Ready for use. Color coded blue.
6. Wash Buffer 21X, 1 bottle, 40 mL, Dilute 1+20 with 800 mL redistilled water.
7. Substrate TMB, 1 vialm 22 mLm Ready for use.
8. Stop Solution, 1 vial, 7 mL, Ready for use.
Storage
Store kit at 2-8°C or -20°C upon arrival up to the expiration date. Avoid multiple freeze/thaw cycles. For more detailed information, please download the following document on our website.
Precision
Each sample was analysed in 4-replicates on five different occasions.
Detection Range
The detection limit is 1.5 μg/l calculated as two standard deviations above the zero standard.
Standard Curve

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References


Squeezing Position Updates for Enhanced Estimation of Land Vehicles Aided INS

IEEE SENSORS JOURNAL

Authors: Klein, Itzik; Lipman, Yeshaya; Vaknin, Eliav

The case of a land vehicle traveling in a straight and leveled trajectory with a position aided inertial navigation system (INS) is considered. In such a scenario, the heading angle and some of the inertial sensors error states are not observable. To circumvent this problem, we propose a method to extract attitude information from position measurements history provided by the external sensor. Simultaneously utilizing the attitude information and position updates in the navigation filter enables the estimation of the heading angle and all of the inertial sensors error states. That is, using the proposed approach the system becomes completely observable. Simulation and field experiment results are provided to show the navigation solution performance when applying the proposed approach.

A Deep Fusion Method Based on INS/SAR Integrated Navigation and SAR Bias Estimation

IEEE SENSORS JOURNAL

Authors: Lu, Jiazhen; Ye, Lili; Han, Songlai

Due to the need of providing navigation information around the clock independently, the Inertial Navigation System (INS)/Synthetic Aperture Radar (SAR) integrated navigation system is a hot topic currently. This paper proposes a deep fusion method based on INS/SAR integrated navigation. Different from the conventional INS/SAR integrated navigation system, the state equation and the measurement equation are established, regarding the SAR pseudo-range and pseudo-range rate bias error as independent state variables. A result of qualitative analysis is provided, by comparing the one side of distribution and the two sides of distribution of measurement points. The simulation result shows that the position error of two sides of distribution greatly reduces. Compared with the one side of distribution, the accuracy improves approximately 78%. The pseudo-range and pseudo-range rate bias error can be estimated effectively with two sides of distribution, of which the accuracy is 69% and 76% approximately, improving 39% and 64% respectively compared with the one side of distribution. The result of flight experiments verifies the effectiveness of the proposed method. The position accuracy of measurement points based on two sides of the distribution is better than that of the distribution of one side, which improves the actual accuracy of SAR, and is consistent with the simulation results.

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