Respuesta: Los caracteres adquiridos no se transmiten genéticamente porque no modifican el ADN de los organismos
Explicación:
Jean-Baptiste Lamarck al igual que Charles Darwin, propuso una teoría sobre la evolución que explicaba cambios en los organismos a través del tiempo. La teoría de Lamarck se enfocaba en condiciones en el ambiente que propiciaban cambios en los organismos. Un ejemplo de esto son las jirafas, que de acurdo a Lamarck tenían cuellos largos debido al esfuerzo continuado para comer hojas de árboles altos. Esto significa que la característica de cuello largo era adquirido por las jirafas durante su vida y según Lamarck se transmitiría a sus descendientes.
Sin embargo, se ha comprobado que los caracteres adquiridos no modifican el ADN de los organismos, por ejemplo las cirugías estéticas no cambian el ADN de una persona y por esta razón no son transmitidos a sus descendientes. Por el contrario, en las poblaciones de organismos ciertas características prevalencen en el tiempo debido a la selección natural. Esto significa que el cuello de las jirafas es el resultado que el cuello largo sea una característica beneficiosa que ha prevalecido debido a la selección natural y no de características adquiridas que son transmitidas a descendientes.
Answer:
Check explanation
Explanation:
Two stacks can make use of one array by utilizing various stack pointers that begins from different ends of an array. Looking at the array A[1...
], the first stack will drive elements that starts from position 1 as well as to move its' pointer to .
The Second stack will begin at the position and motion its' pointer to 1. The best likely divide is to offer each stack a half of an array. whenever any of two stacks transverse the half-point, an overflow can happen but for that overall number of elements, it must be
Answer:
Option A, Font Dialog Box
Explanation:
In order to make changes in the text formatting, the font setting in the dialog box can be used on the Ribbon's Home tab.
From the font settings in Word 2016, one can change the following change font color, size, style etc.
Hence, option A is correct
Answer:
It we were asked to develop a new data compression tool, it is recommended to use Huffman coding since it is easy to implement and it is widely used.
Explanation:
The pros and the cons of Huffman coding
Huffman coding is one of the most simple compressing encoding schemes and can be implemented easily and efficiently. It also has the advantage of not being patented like other methods (e.g. arithmetic codingfor example) which however are superior to Huffman coding in terms of resulting code length.
One thing not mentioned so far shall not be kept secret however: to decode our 96 bit of “brief wit” the potential receiver of the bit sequence does need the codes for all letters! In fact he doesn’t even know which letters are encoded at all! Adding this information, which is also called the “Huffman table” might use up more space than the original uncompressed sentence!
However: for longer texts the savings outweigh the added Huffman table length. One can also agree on a Huffman table to use that isn’t optimized for the exact text to be transmitted but is good in general. In the English language for example the letters “e” and “t” occur most often while “q” and “z” make up the least part of an average text and one can agree on one Huffman table to use that on average produces a good (=short) result. Once agreed upon it doesn’t have to be transmitted with every encoded text again.
One last thing to remember is that Huffman coding is not restricted to letters and text: it can be used for just any symbols, numbers or “abstract things” that can be assigned a bit sequence to. As such Huffman coding plays an important role in other compression algorithms like JPG compression for photos and MP3 for audio files.
The pros and the cons of Lempel-Ziv-Welch
The size of files usually increases to a great extent when it includes lots of repetitive data or monochrome images. LZW compression is the best technique for reducing the size of files containing more repetitive data. LZW compression is fast and simple to apply. Since this is a lossless compression technique, none of the contents in the file are lost during or after compression. The decompression algorithm always follows the compression algorithm. LZW algorithm is efficient because it does not need to pass the string table to the decompression code. The table can be recreated as it was during compression, using the input stream as data. This avoids insertion of large string translation table with the compression data.
