Here's the biology explanation:
Most of the energy expended by a cell in active transport is used to pump ions out of the cell across the plasma membrane.
Answer:
Greedy is an algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. Greedy algorithms are used for optimization problems. An optimization problem can be solved using Greedy if the problem has the following property: At every step, we can make a choice that looks best at the moment, and we get the optimal solution of the complete problem.
If a Greedy Algorithm can solve a problem, then it generally becomes the best method to solve that problem as the Greedy algorithms are in general more efficient than other techniques like Dynamic Programming. But Greedy algorithms cannot always be applied. For example, the Fractional Knapsack problem (See this) can be solved using Greedy, but 0-1 Knapsack cannot be solved using Greedy.
The following are some standard algorithms that are Greedy algorithms.
1) Kruskal’s Minimum Spanning Tree (MST): In Kruskal’s algorithm, we create an MST by picking edges one by one. The Greedy Choice is to pick the smallest weight edge that doesn’t cause a cycle in the MST constructed so far.
2) Prim’s Minimum Spanning Tree: In Prim’s algorithm also, we create an MST by picking edges one by one. We maintain two sets: a set of the vertices already included in MST and the set of the vertices not yet included. The Greedy Choice is to pick the smallest weight edge that connects the two sets.
3) Dijkstra’s Shortest Path: Dijkstra’s algorithm is very similar to Prim’s algorithm. The shortest-path tree is built up, edge by edge. We maintain two sets: a set of the vertices already included in the tree and the set of the vertices not yet included. The Greedy Choice is to pick the edge that connects the two sets and is on the smallest weight path from source to the set that contains not yet included vertices.
4) Huffman Coding: Huffman Coding is a loss-less compression technique. It assigns variable-length bit codes to different characters. The Greedy Choice is to assign the least bit length code to the most frequent character. The greedy algorithms are sometimes also used to get an approximation for Hard optimization problems. For example, the Traveling Salesman Problem is an NP-Hard problem. A Greedy choice for this problem is to pick the nearest unvisited city from the current city at every step. These solutions don’t always produce the best optimal solution but can be used to get an approximately optimal solution.
If an iphone go to the open book icon then go to history and clear from there if on a laptop go to the top right and look at the three ... press it and go to history and press clear history I don’t remember about android
Well it depends on the topic he is doing. if it is a list then a plain doc with a list of numbers. if he is writing a letter then he should use the letter template.
Answer:
a. at least once
Explanation:
A loop is a code snippet that uses a condition to run repeatedly for multiple times which could be zero, one or more times. As long as the condition is true, the loop statement executes over and over again. Three common types of loop are;
i. for loop
ii. while loop
iii. do while loop
In a for or while loop, the condition for the loop is first tested before the statements in the loop are executed. Statements in the body of the loop are executed zero or more times. i.e the loop statement (statement in the body of the loop) may or may not be executed.
In a do..while loop, the statements in the loop are executed first before the condition of the loop is tested. In this case, the statements in the body of the loop are executed one or more times. i.e the loop statement is executed at least once.
