Purpose: The purpose of this paper is to analyze the effects of condition-based maintenance based on unscheduled maintenance delays that were caused by ATA chapter 21 (air conditioning). The goal is to show the introduction of condition monitoring in aircraft systems. Design/methodology/approach: The research was done using the Airbus In-Service database to analyze the delay causes, delay length and to check if they are easy to detect via condition monitoring or not. These results were then combined with delay costs. Findings: Analysis shows that about 80 percent of the maintenance actions that cause departure delays can be prevented when additional sensors are introduced. With already existing sensors it is possible to avoid about 20 percent of the delay causing maintenance actions. Research limitations/implications: The research is limited on the data of the Airbus in-service database and on ATA chapter 21 (air conditioning). Practical implications: The research shows that delays can be prevented by using existing sensors in the air conditioning system for condition monitoring. More delays can be prevented by installing new sensors. Originality/value: The research focuses on the effect of the air conditioning system of an aircraft on the delay effects and the impact of condition monitoring on delays.

Isotype switch variants of the IgG3 secreting hybridoma BR55-2 were developed with γ1, γ2b and γ2a heavy chains. The variants have the same affinity for antigen and expected affinities for the Fc receptor. The Y antigen defined by MAb BR55-2 has a restricted distribution to breast, colorectal, pancreatic, gastric and small cell lung carcinomas. The MAb BR55-2 also bound to prostatic and laryngeal carcinomas. The BR55-2 defined epitope is expressed by gastrointestinal cancer cell lines as a glycolipid, while the breast carcinoma cells express the same epitope on glycoproteins. These differences may influence tumor cell susceptibility to lysis by MAb BR55-2 and its isotype switch variants.

This paper identifies several meaningful business opportunity cases in the area of aircraft cabin conversion and refurbishing and predicts the market volume and the world distribution for each of them: 1) international cabins, 2) domestic cabins, 3) aircraft on operating lease, 4) freighter conversions and 5) VIP completions. This implies the determination of cabin modification/conversion scenarios, along with their duration and frequency. Factors driving the cabin conversion and refurbishing are identified. Several aircraft databases, containing the current world feet as well as the forecasted fleet for the next years, are analyzed. The results are obtained by creating a program able to read and analyze the gathered data. It is shown that about 38000 cabin redesigns will be undertaken within the next 20 years. About 2500 conversions from jetliners into freighters and 25000 cabin modifications at VIP standards will emerge on the market. The North American and European markets will keep providing good business opportunities in this area. The Asian market, however, is growing fast, and its very strong influence on demand puts it in the front rank for the next 20 years.

Purpose: Provide good values for the tail volume coefficient and the lever arm as a percentage of the fuselage length. Provide a statistical method for dorsal fin layout. – Methodology: Based on an understanding of flight physics, the statistical correlation of real aircraft parameters is investigated. This is based on the firm conviction that high fidelity parameters for future aircraft need a checked against parameters of existing successful aircraft. – Findings: Typical tail volume coefficients are between 0.5 and 1.0 for the horizontal tail and between 0.03 and 0.08 for the vertical tail depending on aircraft category. Empennage statistics have clear trends. The often weak correlation shows that aircraft design allows for sufficient designer's choice. Only a minority of aircraft feature a dorsal fin. Designers see it as an added surface rather than as part of the vertical tail. It is used to limit the hypothetical risk of vertical tail stall due to high sideslip angles. – Research Limitations: Results obtained from statistics are close to reality, but not a proof to fulfill requirements. – Practical Implications: Methods from the paper can be used for quick initial sizing of a vertical tail with or without dorsal fin or sizing of a horizontal tail. These results can also be used as good starting values for optimization tools in aircraft design. – Originality: Estimation of the tail lever arm is necessary for sizing with the tail volume coefficient, but had not been investigated to any detail. A method for the layout of dorsal fins was missing.

Reacting ethoxycarbonyl triphenyl phosphorane with activated alkylhalides in chloroform gave the ylides 4 -12. They react smoothly and in general without racemisation with oc-amino aldehydes resulting in the dipeptide mimetics 15 - 25. Exceptions are the highly labile aldehydes pyridinoalaninal and serinal. Enantiospecificity is proven via enantioselective chromatography.

Unscheduled maintenance is a large cost driver for airlines, but condition monitoring and prognosis can reduce the number of unscheduled maintenance actions. This paper discusses how condition monitoring can be introduced into most systems by adopting a data-driven approach and using existing data sources. The goal is to forecast the remaining useful life (RUL) of a system based on various sensor inputs. Decision trees are used to learn the characteristics of a system. The data for the decision tree training and classification are processed by a generic parametric signal analysis. To obtain the best classification results for the decision tree, the parameters are optimised by a genetic algorithm. A forest of three different decision trees with different signal analysis parameters is used as a classifier. The proposed method is validated with data from an A320 aircraft from Etihad Airways. Validation shows that condition monitoring can classify the sample data into ten predetermined categories, representing the total useful life (TUL) in 10% steps. This is used to predict the RUL. There are 350 false classifications out of 850 samples. Noise reduction reduces the outliers to nearly zero, making it possible to correctly predict condition. It is also possible to use the classification output to detect a maintenance action in the validation data.