Shadow Area where light is blocked by an object Shadows of visitors to the Eiffel Tower, viewed from the first platform Park fence shadow is distorted by an uneven snow surface Shadows from cumulus clouds thick enough to block sunlight Point and non-point light sources[edit] A point source of light casts only a simple shadow, called an "umbra". The outlines of the shadow zones can be found by tracing the rays of light emitted by the outermost regions of the extended light source. By contrast, the penumbra is illuminated by some parts of the light source, giving it an intermediate level of light intensity. The absence of diffusing atmospheric effects in the vacuum of outer space produces shadows that are stark and sharply delineated by high-contrast boundaries between light and dark. For a person or object touching the surface where the shadow is projected (e.g. a person standing on the ground, or a pole in the ground) the shadows converge at the point of contact. Astronomy[edit] Lotus clour[edit]
Animal Kingdom of living things Etymology The word animal comes from the Latin noun animal of the same meaning, which is itself derived from Latin animalis 'having breath or soul'.[6] The biological definition includes all members of the kingdom Animalia.[7] In colloquial usage, the term animal is often used to refer only to nonhuman animals.[8][9][10][11] The term metazoa is derived from Ancient Greek μετα meta 'after' (in biology, the prefix meta- stands for 'later') and ζῷᾰ zōia 'animals', plural of ζῷον zōion 'animal'.[12] A metazoan is any member of the group Metazoa.[13] Characteristics Animals have several characteristics that they share with other living things. Structural features Animals have structural characteristics that set them apart from all other living things: motility[22] i.e. able to spontaneously move their bodies during at least part of their life cycle.a blastula stage during embryonic development[23] Development Reproduction Ecology Diversity Size Evolutionary origin Phylogeny Notes
Rapatronic Camera: An Atomic Blast Shot at 1/100,000,000th of a Second | PetaPixel This is a photo of an atomic bomb milliseconds after detonation, shot by Harold ‘Doc’ Edgerton in 1952 through his Rapatronic (Rapid Action Electronic) Camera. The photo was shot at night through a 10 foot lens, situated 7 miles away from the blast, atop a 75 foot tower. Edgerton systematically turned on and off magnetic fields acting as the camera’s shutter, as opposed to a conventional, mechanical close. How fast was the magnetic field shutter? For comparison, a manual 35mm camera has a ‘top speed’ of maybe 1/3200. This is 1/100,000,000th of a second after the first photo. This isn’t the normal funny, Mike – why would you post something like this? As a photographer, I’m inspired by odd things. As a human, It’s hard for me to fathom that something so horrible and destructive could be so mesmerizingly beautiful. Another 1/100,000,000th of a second later, and you can see the Joshua Trees with the front row seat to Doomstown. When I see the pics, I kind of zone out.
Nociceptors: the sensors of the pain pathway Machine Learning 101: The What, Why, and How of Weighting - KDnuggets By Eric Hart, Altair. Introduction One thing I get asked about a lot is weighting. What is it? Model Basics Before we talk about weighting, we should all get on the same page about what a model is, what they are used for, and some of the common issues that modelers run into. If you’re building a model to make predictions, you’re going to need a way to measure how good that model is at making predictions. Let’s jump into an example. The 2019 world series took place between the Washington Nationals and the Houston Astros Let’s investigate some models. Apparently, I was pretty high on the Nationals. It’s worth noting: these are individual game predictions, made in advance of each game if it was going to happen; these are not predictions for the series as a whole. These predictions are based on things like team strength, home field advantage, and specifics of which pitcher is starting each game. Anyway, let’s spoil the series, see what happened, and compare accuracy. My result: Now define:
Weighted arithmetic mean Statistical amount The weighted arithmetic mean is similar to an ordinary arithmetic mean (the most common type of average), except that instead of each of the data points contributing equally to the final average, some data points contribute more than others. The notion of weighted mean plays a role in descriptive statistics and also occurs in a more general form in several other areas of mathematics. If all the weights are equal, then the weighted mean is the same as the arithmetic mean. While weighted means generally behave in a similar fashion to arithmetic means, they do have a few counterintuitive properties, as captured for instance in Simpson's paradox. Examples[edit] Basic example[edit] Given two school classes — one with 20 students, one with 30 students — and test grades in each class as follows: Morning class = {62, 67, 71, 74, 76, 77, 78, 79, 79, 80, 80, 81, 81, 82, 83, 84, 86, 89, 93, 98} The mean for the morning class is 80 and the mean of the afternoon class is 90. is . . With
Weighting Confusion Matrices by Outcomes and Observations - Bryan Shalloway's Blog Weighting in predictive modeling may take multiple forms and occur at different steps in the model building process. When selecting observations to be used in model trainingDuring model trainingAfter model training, during model evaluation The focus of this post is on the last stage. I will describe two types of weighting that can be applied in late stage model evaluation: Specifically with the aim of identifying ideal cut-points for making class predictions. (See Weights of Observations During and Prior to Modeling in the Appendix for a brief discussion on forms of weighting applied at other steps in predictive modeling.) Most common metrics used in classification problems – e.g. accuracy, precision, recall/sensitivity, specificity, Area Under the ROC curve (AUC) or Precision-Recall curve – come down to the relationship between the true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN) at a particular decision threshold or across all thresholds.
Fitting Brownian motion · Phylogenetic Comparative Methods Section 4.1: Introduction Mammals come in a wide variety of shapes and sizes. Some species are incredibly tiny. Sometimes one might be interested in calculating the rate of evolution of a particular character like body size in a certain clade, say, mammals. Box 4.1: Biology under the log One general rule for continuous traits in biology is to carry out a log-transformation (usually natural log, base e, denoted ln) of your data before undertaking any analysis. Section 4.2: Estimating rates using independent contrasts The information required to estimate evolutionary rates is efficiently summarized in the early (but still useful) phylogenetic comparative method of independent contrasts (Felsenstein 1985). We can understand the basic idea behind independent contrasts if we think about the branches in the phylogenetic tree as the historical “pathways” of evolution. Figure 4.1. Box 4.2: Algorithm for PICs One can calculate PICs using the algorithm from Felsenstein (1985). Figure 4.2. (eq. 4.4)
Python Tutor - Visualize Python, Java, C, C++, JavaScript, TypeScript, and Ruby code execution Floor and Ceiling Functions The floor and ceiling functions give us the nearest integer up or down. Example: What is the floor and ceiling of 2.31? The Floor of 2.31 is 2 The Ceiling of 2.31 is 3 Floor and Ceiling of Integers What if we want the floor or ceiling of a number that is already an integer? That's easy: no change! Example: What is the floor and ceiling of 5? The Floor of 5 is 5 The Ceiling of 5 is 5 Here are some example values for you: Symbols The symbols for floor and ceiling are like the square brackets [ ] with the top or bottom part missing: But I prefer to use the word form: floor(x) and ceil(x) Definitions How do we give this a formal definition? Example: How do we define the floor of 2.31? Well, it has to be an integer ... ... and it has to be less than (or maybe equal to) 2.31, right? 2 is less than 2.31 ... Oh no! So which one do we choose? Choose the greatest one (which is 2 in this case) So we get: The greatest integer that is less than (or equal to) 2.31 is 2 Which leads to our definition: As A Graph
Floor and ceiling functions Nearest integers from a number Floor function Ceiling function For example, ⌊2.4⌋ = 2, ⌊−2.4⌋ = −3, ⌈2.4⌉ = 3, and ⌈−2.4⌉ = −2. Historically, the floor of x has been–and still is–called the integral part or integer part of x, often denoted [x] (as well as a variety of other notations).[2] Some authors[citation needed] may define the integral part [x] as ⌊x⌋ if x is nonnegative, and ⌈x⌉ otherwise: for example, [2.4] = 2 and [−2.4] = −2. For n an integer, ⌊n⌋ = ⌈n⌉ = [n] = n. Notation[edit] The integral part or integer part of a number (partie entière in the original) was first defined in 1798 by Adrien-Marie Legendre in his proof of the Legendre's formula. Carl Friedrich Gauss introduced the square bracket notation [x] in his third proof of quadratic reciprocity (1808).[3] This remained the standard[4] in mathematics until Kenneth E. The fractional part is the sawtooth function, denoted by {x} for real x and defined by the formula {x} = x − ⌊x⌋[9] For all x, 0 ≤ {x} < 1. where and Equivalences[edit]
The Knights Templar - The Rise and Fall of the Greatest Crusader Order A crimson cross emblazoned on a white background; a simple design, perhaps, but behind it lies one of the most remarkable stories in the history of the medieval world. It’s a saga that began in the city of Nablus, in the aftermath of the First Crusade. That same saga came to a sudden end in 1307, two centuries later. As the sun rose over Paris on Friday the 13th of November, the doom of the Knights Templar was sealed. Almost two hundred years before that fateful morning, however, no one could have imagined what was to come. However, the road that ran inland from the coastal ports was plagued with bandits and raiders. It was at this point that a French knight named Hugues de Payens proposed a solution. The new order was given a headquarters on the Temple Mount, within the royal palace itself. Initially, the group consisted of only nine knights, and without any real funds of their own, they relied heavily on donations from the church and nobility. Not that it mattered, of course.
Bladeless Turbines: Colossal Vibrators Produce Energy? | IE Gigantic windfarms lining hills and coastlines around the world have become commonplace, but there might be another way — a bladeless way — to harness the wind, according to a green energy company that claims to have reinvented wind power by removing turbine towers, blades, and the wind itself. However, while the six-person startup Vortex Bladeless has published its own study on the new energy-generating design, its proof-of-concept has yet to appear in a peer-reviewed journal — although it is currently receiving funding from the European Union, and a Norwegian state energy company. So, take this arguably phallic alternative to bladed turbines with a grain of salt. Giant vibrators with bladeless turbines attract oddly specific attention "We are not against traditional windfarms," said inventor of Vortex Bladeless David Yáñez, in a report from The Guardian. The new design has received interest on Reddit, where it was compared to a colossal sex toy, or "skybrator."