Human CCP Antibody ELISA Kit (DEIA1227)

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

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culture supernatants, serum, plasma, tissues
Species Reactivity
Intended Use
The Human CCP Antibody ELISA kit is designed to detect and quantify the level of human CCP Antibody in cell culture supernatant, serum, plasma and tissue.
Contents of Kit
1. Human CCP Ag Coated Wells, 96-well polystyrene microplate (12 strips of 8 wells): 1 plate
2. Standard 1(1600 RU/ml), 1 mL per bottle: 1 bottle
3. Standard 2(400 RU/ml), 1 mL per bottle: 1 bottle
4. Standard 3(200 RU/ml), 1 mL per bottle: 1 bottle
5. Standard 4(50 RU/ml), 1 mL per bottle: 1 bottle
6. Standard 5(25 RU/ml), 1 mL per bottle: 1 bottle
7. Positive control, 1 mL per bottle: 1 bottle
8. Negative control, 1 mL per bottle: 1 bottle
9. HRP-conjugate reagent, 15 mL per bottle with preservatives: 1 bottle
10. Assay Solution, 60 mL per bottle with preservatives: 1 bottle
11. Wash Solution Concentrate (10x), 60 mL with preservatives: 1 bottle
12. Chromogen Solution A, 10 mL per bottle: 1 bottle
13. Chromogen Solution B, 10 mL per bottle: 1 bottle
14. Stop Solution, 10 mL per bottle: 1 bottle
All kit components of this kit are stable at 2-8°C. For more detailed information, please download the following document on our website.
The sensitivity is defined as the probability of the assay of scoring positive in the presence of the specific analyte. It is 82%.


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Just-in-time customer churn prediction in the telecommunication sector


Authors: Amin, Adnan; Al-Obeidat, Feras; Shah, Babar; Al Tae, May; Khan, Changez; Durrani, Hamood Ur Rehman; Anwar, Sajid

Due to the exponential growth in technologies and a greater number of competitors in the telecom sector, the companies are facing a rigorous problem of customer churns. The customer churn is a phenomenon that highlights the customer's intention who may switch from a certain service or even the service provider company. Many customer churn prediction (CCP) techniques are developed by academics and practitioners to handle the customer churn in order to resolve the problems pertaining to customer retention. However, CCP is not widely studied in the scenario where the company is not having enough historical data due to either been a newly established company or due to the recent start of a new technology or even because of the loss of the historical data. The just-in-time (JIT) approach can be a more practical alternative to address this issue as compared to state-of-the-art CCP techniques. Unfortunately, similar to traditional churn prediction models, JIT also requires enough historical data. To address this gap in the traditional CCP models, this study uses the cross-company data, i.e., data from another company, in the context of JIT for addressing CCP problems in the telecom sector. We empirically evaluated the performance of the proposed model using publicly available datasets of two telecom companies. It is found from the empirical evaluation that in the JIT-CCP context: (i) it is possible to evaluate the performance of the predictive model using cross-company dataset for training purposes and (ii) it is evident that heterogeneous ensemble-based JIT-CCP model is more suitable approach to use as compared to individual classifier or homogeneous ensemble-based technique.

CCP-WSI Blind Test Series 3: A Nonlinear Froude-Krylov Modeling Approach


Authors: Giorgi, Giuseppe

Mathematical models are essential for the effective design of wave energy converters and hence for the achievement of economic viability and industrial feasibility. Despite the fact that the wave energy field is at least 45 years old, there is still a clear lack of standardization of modeling techniques and a large amount of room for increasing confidence in hydrodynamic models. The Collaborative Computational Project in Wave-Structure Interaction (CCP-WSI) project aims to define a level playing field of comparison for a plurality of models, evaluating their performance. This paper implements a computationally convenient approach to represent nonlinear Froude-Krylov forces, along with the inclusion of nonlinear kinematics.

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