IIRC, the front of the car is to the right in this diagram, I'm not quite sure anymore. But yes, the numbers coincide with the cylinders, so there is a way in which you can align the diagram with your engine.
Anonymous on 23 Apr : 21:10
Hey Bjoern. I have a question about your wiring diagram on the MAF conversion. Is the diagram of the injector wiring from the top view of the engine? Because I'm guessing the injector numbers don't coinside with the cylinder numbers? Thanks
The auto tranny is a problem, because you have a very limited choice of computers. Unfortunately, I have no idea about auto trannies and can't help you there. Conversion to standard is a big deal and not for the faint of heart. I bought a book on Ford EFI which I found to be very helpful and I learned a lot from it. I think it was this one: [link]
hey bjoern, ive had your maf conversion in my favorites forever... i finally rebuilt the engine, but put in a lumpier cam, along with some other minor mods, so now basically, it runs, but with the old map sensor, not so good. thats alot of technical words, and all ive worked on up to this point is oldies with carbs and no EFI, but im learning alot and im loving it. i have one difference, but i dont think it bothers anything, i have an automatic transmission, so if i install the maf system out of a newer pickup it may want to read the e40d when i just have an aod... unless maybe i can find one with a standard transmission?? i dunno, im getting so confused with all this technology, i would like to do it step by step just as you did. can you help me somehow?
We have used a genetically tractable model system, the fruit fly Drosophila melanogaster to study the interdependence between sensory processing and associative processing on learning performance. We investigated the influence of variations in the physical and predictive properties of color stimuli in several different operant-conditioning procedures on the subsequent learning performance. These procedures included context and stimulus generalization as well as color, compound, and conditional discrimination (colors and patterns). A surprisingly complex dependence of the learning performance on the colors’ physical and predictive properties emerged, which was clarified by taking into account the fly-subjective perception of the color stimuli. Based on estimates of the stimuli’s color and brightness values, we propose that the different tasks are supported by different parameters of the color stimuli; generalization occurs only if the chromaticity is sufficiently similar, whereas discrimination learning relies on brightness differences. Brembs, B and Hempel de Ibarra, N (2006): Different parameters support generalization and discrimination learning in Drosophila at the flight simulator. Learn. Mem. 13: 629-63
feedburner.com
