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  2. Microsoft Excel - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Excel

    Excel 2016 has 484 functions. [16] Of these, 360 existed prior to Excel 2010. Microsoft classifies these functions into 14 categories. Of the 484 current functions, 386 may be called from VBA as methods of the object "WorksheetFunction" [17] and 44 have the same names as VBA functions.

  3. Homopolar generator - Wikipedia

    en.wikipedia.org/wiki/Homopolar_generator

    A homopolar generator is a DC electrical generator comprising an electrically conductive disc or cylinder rotating in a plane perpendicular to a uniform static magnetic field. A potential difference is created between the center of the disc and the rim (or ends of the cylinder) with an electrical polarity that depends on the direction of ...

  4. Federal taxation and spending by state - Wikipedia

    en.wikipedia.org/wiki/Federal_taxation_and...

    The ability of the United States government to tax and spend in specific regions has large implications to economic activity and performance. Taxes are indexed to wages and profits and therefore areas of high taxation are correlated with areas of higher per capita income and more economic activity.

  5. Thermoelectric generator - Wikipedia

    en.wikipedia.org/wiki/Thermoelectric_generator

    A thermoelectric generator (TEG), also called a Seebeck generator, is a solid state device that converts heat (driven by temperature differences) directly into electrical energy through a phenomenon called the Seebeck effect [1] (a form of thermoelectric effect).

  6. Marx generator - Wikipedia

    en.wikipedia.org/wiki/Marx_generator

    A small demonstration Marx generator (tower on the right). It is a ten stage generator. The main discharge is on the left. The nine smaller sparks that can be seen in the image are the spark gaps that connect the charged capacitors in series. A Marx generator is an electrical circuit first described by Erwin Otto Marx in 1924. [1]

  7. Pseudorandom number generator - Wikipedia

    en.wikipedia.org/wiki/Pseudorandom_number_generator

    It can be shown that if is a pseudo-random number generator for the uniform distribution on (,) and if is the CDF of some given probability distribution , then is a pseudo-random number generator for , where : (,) is the percentile of , i.e. ():= {: ()}. Intuitively, an arbitrary distribution can be simulated from a simulation of the standard ...

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