A4 Fold

[Cyndi Barca]

Atip to keep your hands and counter clean: wet your hands often with water, pausing periodically through the kneading process. Keeping them mostly nonstick will help avoid excessive dough tearing. Additionally, use a plastic scraper to occasionally stop and scrape the counter clean, reincorporating any stuck bits back into the mass (you can see me do this in the video below).

The slap and fold kneading technique, also called French fold, is a method for strengthening bread dough (and, more specifically, the gluten in bread dough) during the mixing phase before the start of bulk fermentation.

You can slap and fold for a few minutes after incorporating just the flour, water, and sourdough, then add the salt and withheld water and do another slap and fold until strengthened to the desired amount. Or, you can slap and fold only once before the salt or after everything is incorporated. This is up to you and your preference.

Excessive dough hydration can make the slap and fold process a little messier and sometimes even very difficult. If your dough is highly hydrated, it can help to split mixing up into stages or even do a bassinage type mix, slowly adding water through the mix to avoid a very sloppy dough in the beginning.

For instance, hold back some of the mixing water and begin slap and fold without the reserved water. Once the dough builds some strength, add a little more to the dough in the mixing bowl and continue strengthening in a second slap and fold session on the counter.

In the image above, you can see the quick fold over after the slap and stretch. This motion folds the dough into a tight little package, picked up again at the right side with the pincher grip, repeating the process.

Yes. The fold still exists and still applies. Even though the exact location of the fold will differ between devices, it exists for every single user on every single screen. From a technical standpoint, the fold for the most common device sizes can be determined by looking at web traffic and at device and browser statistics. A responsive design may have 2, 3, 4, or more different folds, specific to the devices and screen sizes that the design was optimized for. Each target device has its own fold to consider.

Webpages need to build a solid story. Users can be encouraged to scroll by giving them good reason to do so. Visual elements can draw the eye down the page. Compelling content can draw the user in. If the most interesting information is at the top of the page, users may be enticed to visit the bottom of the page as well.

The fold will always matter because scrolling is an extra action that users need to take to access content. Just like waiting for a page to load, flipping through a carousel, or opening an accordion to view text, scrolling adds an extra step that users must take to accomplish their goal.

The following heatmap aggregates all the sites in our study (excluding search engines and search pages). Content below the fold does gather some looks, but not nearly as many as the content above the fold.

The initial decision is how you hold your slice, more specifically, the way you fold it. Also, I feel like this is a good time to mention that I did not realize how exposed my chest was in this photoshoot, AND I AM TOTALLY FINE WITH IT. Here are a few approaches to folding a slice:

The Flop

Speaking of more delicate slices, if you hold a slice without bending the crust, the tip will droop. In this scenario, you can hold the slice higher than your face and let it fall right into your mouth like a pizza waterfall.

Red Pepper Flakes

Red pepper flakes are the Lebron James or the Serena Williams or Meryl Streep of the 11th hour pizza topping game. They are all the best in the history of their respective fields. I will put red pepper flakes on my slice 93.3% of the time. The 6.7% of the time I do not is if the slice already has a spice component. That little bit of dry heat is exactly what a plain slice is asking for.

Freshly Ground Black Pepper

lack pepper is the most underrated table topping in the game, especially when it comes to a white slice. Think about how much you love cacio e pepe. Now think about turning your pizza into cacio e pepe. That pepper needs to be freshly ground though.

In functional programming, fold (also termed reduce, accumulate, aggregate, compress, or inject) refers to a family of higher-order functions that analyze a recursive data structure and through use of a given combining operation, recombine the results of recursively processing its constituent parts, building up a return value. Typically, a fold is presented with a combining function, a top node of a data structure, and possibly some default values to be used under certain conditions. The fold then proceeds to combine elements of the data structure's hierarchy, using the function in a systematic way.

Folds are in a sense dual to unfolds, which take a seed value and apply a function corecursively to decide how to progressively construct a corecursive data structure, whereas a fold recursively breaks that structure down, replacing it with the results of applying a combining function at each node on its terminal values and the recursive results (catamorphism, versus anamorphism of unfolds).

These pictures illustrate right and left fold of a list visually. They also highlight the fact that foldr (:) [] is the identity function on lists (a shallow copy in Lisp parlance), as replacing cons with cons and nil with nil will not change the result. The left fold diagram suggests an easy way to reverse a list, foldl (flip (:)) []. Note that the parameters to cons must be flipped, because the element to add is now the right hand parameter of the combining function. Another easy result to see from this vantage-point is to write the higher-order map function in terms of foldr, by composing the function to act on the elements with cons, as:

This way of looking at things provides a simple route to designing fold-like functions on other algebraic data types and structures, like various sorts of trees. One writes a function which recursively replaces the constructors of the datatype with provided functions, and any constant values of the type with provided values. Such a function is generally referred to as a catamorphism.

Whereas linear folds are node-oriented and operate in a consistent manner for each node of a list, tree-like folds are whole-list oriented and operate in a consistent manner across groups of nodes.

One often wants to choose the identity element of the operation f as the initial value z. When no initial value seems appropriate, for example, when one wants to fold the function which computes the maximum of its two parameters over a non-empty list to get the maximum element of the list, there are variants of foldr and foldl which use the last and first element of the list respectively as the initial value. In Haskell and several other languages, these are called foldr1 and foldl1, the 1 making reference to the automatic provision of an initial element, and the fact that the lists they are applied to must have at least one element.

These folds use type-symmetrical binary operation: the types of both its arguments, and its result, must be the same. Richard Bird in his 2010 book proposes[2] "a general fold function on non-empty lists" foldrn which transforms its last element, by applying an additional argument function to it, into a value of the result type before starting the folding itself, and is thus able to use type-asymmetrical binary operation like the regular foldr to produce a result of type different from the list's elements type.

In the case of foldi function, to avoid its runaway evaluation on indefinitely defined lists the function f must not always demand its second argument's value, at least not all of it, or not immediately (see example below).

Having reached the end of the list, an expression is in effect built by foldl of nested left-deepening f-applications, which is then presented to the caller to be evaluated. Were the function f to refer to its second argument first here, and be able to produce some part of its result without reference to the recursive case (here, on its left i.e., in its first argument), then the recursion would stop. This means that while foldr recurses on the right, it allows for a lazy combining function to inspect list's elements from the left; and conversely, while foldl recurses on the left, it allows for a lazy combining function to inspect list's elements from the right, if it so chooses (e.g., last == foldl (\a b->b) (error "empty list")).

Another technical point is that, in the case of left folds using lazy evaluation, the new initial parameter is not being evaluated before the recursive call is made. This can lead to stack overflows when one reaches the end of the list and tries to evaluate the resulting potentially gigantic expression. For this reason, such languages often provide a stricter variant of left folding which forces the evaluation of the initial parameter before making the recursive call. In Haskell this is the foldl' (note the apostrophe, pronounced 'prime') function in the Data.List library (one needs to be aware of the fact though that forcing a value built with a lazy data constructor won't force its constituents automatically by itself). Combined with tail recursion, such folds approach the efficiency of loops, ensuring constant space operation, when lazy evaluation of the final result is impossible or undesirable.

When we first opened our cart in 2011, we had no vanilla flavor on the menu. Still, we quickly added it after learning that professional ice cream tasters first sample vanilla to assess the butterfat sensation, milk flavor, and sweetness. This flavor has been a classic since our first shop opened in 2011. We use vanilla beans in two ways: a "double-fold" extract, which uses twice the amount of beans, and the beans themselves for added flavor and visual appeal. Specifically, a double-fold extract uses about 26.7 oz of vanilla beans per gallon of alcohol. We love using Singing Dog Vanilla for its delicious flavor and commitment to supporting vanilla farmers.

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