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What are the best books to refer to while designing RC model aircraft?

For understanding the fundamentals of aerodynamics and airplane design/functioning:Model Aircraft Design by Jonathan DansieIt gives you a very thorough understanding of the fundamentals of aerodynamics in a simple and concise manner. Many of the question boxes also press you to think and understand the logic and reasoning behind different phenomenon. Definitely, the first book I would recommend to new enthusiasts.You can refer to the online pdf version here: (Free)http://www.concept2creation.com.au/xstd_files/Jon%20Dansie%20Model%20Aircraft%20Design.pdfFor a fabrication guide with step by step instructions on the practical aspects of construction:RC Build Fly by Naresh K.A more practical guide mentioning more details on the actual fabrication of the plane and its subsequent tuning for optimal performance. Gives information on the various components to be used and other practical details. I would recommend it to someone who has a thorough grasp of the fundamentals and is looking for a fabrication guide. Do note, it does not elaborate much on the fundamentals of aerodynamics and is much more of a "How To Guide".You can refer to the online pdf version here: (Free)http://rcbuildfly.weebly.com/uploads/1/0/5/3/10534852/rc_build_fly.pdf

What process happens in the brain when you "build intuition" for something?

Intuition is poorly understood from the perspective of brain processes. However if we piece together the current thinking in neuroscience, then we can get an approximate sense for what intuition-building means in the brain.What we call “intuition” can be roughly understood as the brain’s ability to form probabilistic beliefs automatically, without us having much introspective insight into the process the brain is using.The brain, through a complex array of neural circuits, is something of a statistical inferencing machine.The “highest” level of cognition, and the level possibly unique to humans, is the capacity for logical reasoning using symbols and conceptual constructs.The “lowest” levels of behavior are hard-wired reflexes and adaptive “conditioned responses,” for example avoiding foods that previously made you sick.Somewhere in between is a complex system located in the central region of the brain called the “basal ganglia” that is responsible for “habit formation”[1], and which is also likely responsible for what we call intuition.Habit formation is the development in the brain of statistical models for optimal perception and action based on reinforcement learning (finding out if you were right or wrong). This automatic action system works by using observed outcomes in conjunction with dopamine to refine a model for automatic behavior. The automatic behavior is a statistically optimal path to achieving an outcome based only on context and observation. What makes it automatic is that does not involve logic of voluntary control, but is rather a guided path through “perception-action space.” It is this system that is likely “learning” when we say we are building an intuition for something.Paul Cisek has a diagram that shows where intuition may be occurring in the brain (labeled here as “behavior biasing” in the basal ganglia) [2]:Intuition can involve overt behavior, like knowing the best thing to say to get someone to do what you want. But intuition can also involve perception and the “internal behavior” of thought, for example intuiting from observation that someone is “acting suspiciously.” Intuition can also be abstract, such as estimating the size of a crowd or knowing what strategy is likely to work to solve a problem.This diagram from [1] shows the “action-outcome (A-O) associative network” that may be responsible for building intuition in the brain (“DA neurons” refer to dopamine neurons):When we act on intuition, we may find out that we were right or wrong. The brain uses the neurotransmitter dopamine to distribute this feedback along the action path (or thought path) that led up to being right or wrong (the outcome). The neurotransmitter dopamine is believed to implement the statistical strategy of “temporal difference learning,” which is an optimization of reinforcement learning (reward-based learning). The “temporal difference” is a comparison between what you thought was going to happen and what actually happened. This prediction error is distributed along the thought steps that led to the outcome so that the next time you are in a similar situation, your thinking will unfold differently.The net of all this is that “building intuition” really amounts to using observation to train the brain’s statistical models for perception and action. We call it “intuition” because we have limited insight into what our brain is doing. The perceptions and beliefs that form during intuition happen automatically as far as we are concerned because the processes are occurring at the level of neural circuits rather than voluntary cognitive reasoning.The power of intuition is that it is automatic, which makes it effortless. However to strengthen intuition, we need to try new things and learn from our mistakes, since the way the brain builds intuition is to learn from the outcomes of new types of actions.So if you want a great intuition, you need to be willing to take risks and be wrong from time to time.- - - -[1] Yin & Knowlton (2006). The role of the basal ganglia in habit formation. Nature Reviews Neuroscience. (PDF)[2] Cisek & Kalaska (2010). Neural mechanisms for interacting with a world full of action choices. Annual Reviews of Neuroscience. (PDF)

What do physicists think of Christopher Langan's Cognitive-Theoretic Model of the Universe (CTMU)?

It’s awfully tempting to say “BS” and just move on. But let’s give the man a fair go.Okay. Let’s look at two things:Your (apparent) advocacy;Some of what he’s written.First things first. IQ is irrelevant (IQ testing was devised to identify those with cognitive difficulties; use of the other end of the ‘scale’ is daft extrapolation. And it works poorly). Good mathematicians and physicists achieve their greatness not only through passion about their subject but through fucking hard work. Chris appears to be passionate about horses (good for him!) but I can find little or no evidence of the required slog.Good mathematicians and physicists largely build on the work of those who came before them, and learn the language so they can express their ideas clearly. So let’s look at what he has to say. The following is the abstract of a rather large PDF he’s published. (If this turns you off, read the first few sentences and skip to the punchline below :)“Inasmuch as science is observational or perceptual in nature, the goal of providing a scientific model and mechanism for the evolution of complex systems ultimately requires a supporting theory of reality of which perception itself is the model (or theory-to-universe mapping). Where information is the abstract currency of perception, such a theory must incorporate the theory of information while extending the information concept to incorporate reflexive self-processing in order to achieve an intrinsic (self-contained) description of reality. This extension is associated with a limiting formulation of model theory identifying mental and physical reality, resulting in a reflexively self-generating, self-modeling theory of reality identical to its universe on the syntactic level. By the nature of its derivation, this theory, the Cognitive Theoretic Model of the Universe or CTMU, can be regarded as a supertautological reality-theoretic extension of logic. Uniting the theory of reality with an advanced form of computational language theory, the CTMU describes reality as a Self-Configuring Self-Processing Language or SCSPL, a reflexive intrinsic language characterized not only by self-reference and recursive self-definition, but full self-configuration and selfexecution (reflexive read-write functionality). SCSPL reality embodies a dual-aspect monism consisting of infocognition, self-transducing information residing in self-recognizing SCSPL elements called syntactic operators. The CTMU identifies itself with the structure of these operators and thus with the distributive syntax of its self-modeling SCSPL universe, including the reflexive grammar by which the universe refines itself from unbound telesis or UBT, a primordial realm of infocognitive potential free of informational constraint. Under the guidance of a limiting (intrinsic) form of anthropic principle called the Telic Principle, SCSPL evolves by telic recursion, jointly configuring syntax and state while maximizing a generalized selfselection parameter and adjusting on the fly to freely-changing internal conditions. SCSPL relates space, time and object by means of conspansive duality and conspansion, an SCSPL-grammatical process featuring an alternation between dual phases of existence associated with design and actualization and related to the familiar wave-particle duality of quantum mechanics. By distributing the design phase of reality over the actualization phase, conspansive spacetime also provides a distributed mechanism for Intelligent Design, adjoining to the restrictive principle of natural selection a basic means of generating information and complexity. Addressing physical evolution on not only the biological but cosmic level, the CTMU addresses the most evident deficiencies and paradoxes associated with conventional discrete and continuum models of reality, including temporal directionality and accelerating cosmic expansion, while preserving virtually all of the major benefits of current scientific and mathematical paradigms.”Time for a true confession. I’m aided in understanding this because I spend a fair bit of time proofreading poor English translations of Japanese academic manuscripts in Medicine and Computer Science. (You develop a keen eye for waffle and bullshit).Punchline: This is bullshit. The above condenses to something like:“Look at how smart I am. Assuming the mind and physical reality are one, I have this strange idea that therefore the universe can continually re-invent itself in a way that transcends any idea of physical laws. Simplistic references to computer science and quantum mechanics make me sound smart [But I provide no way to test my ‘ideas’]”I glanced through the rest of the manuscript. Where’s the math? Gosh, this is bad.My 2c: Don’t waste your time.Jo.P.S. The cartoon is from xkcd: Impostor

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