How does the human circulatory system work?
Here is a brief overview of how the human circulatory system works:
The circulatory system transports blood throughout the body via the heart and blood vessels. It delivers oxygen and nutrients to the body's cells and removes waste products.
The heart is a muscular pump that drives circulation. It has four chambers - two upper atria and two lower ventricles.
Deoxygenated blood enters the right atrium, flows to the right ventricle, then is pumped through the pulmonary artery to the lungs to get oxygenated.
Oxygenated blood returns from the lungs to the left atrium, then fills the left ventricle. The left ventricle pumps the blood through the aorta and to the rest of the body.
Arteries carry oxygenated blood away from the heart to the tissues of the body. Capillaries are microscopic vessels that allow exchange of nutrients, gases, and wastes between the blood and tissues.
Veins return deoxygenated blood back to the heart. The vena cavae are the large veins that return blood from the body to the right atrium.
The cycle then repeats itself - deoxygenated blood returns to the heart, gets pumped to the lungs, oxygenated, then pumped back out to the body's tissues.
In addition to circulating blood, the circulatory system helps stabilize body temperature and pH. It also helps fight disease via white blood cells.
So in summary, the circulatory system transports blood in a continuous loop powered by the pumping heart, delivering oxygen and nutrients while removing waste.
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diff types of trees in dsa
Here are some of the main types of trees commonly used in data structures and algorithms:
Binary Tree - Each node has up to two child nodes. Includes binary search trees and binary heaps.
Binary Search Tree (BST) - binary tree where the values in each left subtree are less than or equal to the parent node, and the values in each right subtree are greater. Allows for very lookup, insertion and deletion.
AVL Tree - A self-balancing BST where the difference in height between left and right subtrees of each node is at most 1. Balancing improves worst-case lookup, insertion etc.
Red-Black Tree - A self-balancing BST where nodes have an extra color bit to ensure no path is more than twice as long as any other, balancing the tree.
B-Tree - A tree where each node can have many child nodes. B-trees are optimized for systems that read and write large blocks of data. Used commonly in databases.
Heap - A tree structure where parent nodes are ordered with respect to their children, allowing for fast extraction of minimum or. Used to implement priority queues. Trie - A tree where each node stores a character. Tries allow for very fast prefix-based lookups making them ideal for predictive text or autocomplete.
Suffix Tree - A trie of all suffixes of a text. Allows extremely fast substring queries.
Segment Tree - A binary tree storing intervals or segments allowing fast querying of intervals for properties like sum or minimum.