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?
Ever since the ancient Greeks, animals in general and insects in particular have been considered automata, or robots: if one only knew all their input variables, one could predict the motor output they would produce. However, even under constant environmental conditions, animals generate variable behavioral output. The question of whether such intrinsic behavioral variability reflects random noise (disorder) in otherwise deterministic input/output systems or an intrinsic, adaptive indeterminacy trait (order) is central for the basic understanding of brain function. Here we show that spontaneously generated search algorithms (Lévy flights), but not random noise can account for the temporal structure in spontaneous yaw torque fluctuations in tethered Drosophila. Lévy flights are evolutionary conserved probabilistic behavior patterns, suggesting a general neural mechanism underlying spontaneous behavior. Further analysis suggests nonlinear mechanisms to be involved in generating these patterns, indicating a built-in, evolutionarily conserved spontaneity generator in the brain. We hypothesize that this generator can function independently of environmental input and that it evolved to generate flexible behavior in a complex world. Indeed, such flexible behavior patterns have been shown to outcompete random and deterministic patterns in a number of ecological situations. In the real world, predator avoidance and prey catching behavior spring to mind as other obvious beneficiaries from indeterminacy. One can easily conceive how “getting out of a rut” would also be difficult with only pre-programmed “responses”. Our findings imply that both general models of brain function and autonomous agents (robots or brain-based devices) must include relevant nonlinear, endogenous mechanisms if they strive to realistically simulate biological brains. It is a tempting analogy to imagine all spontaneity being based on nonlinear feedback mechanisms in the brain.
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