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Liver cytology is the branch of cytology that studies the liver cells and its functions. The liver is a vital organ, in charge of almost all the body’s metabolism. Main liver cells are hepatocytes, Kupffer cells, and hepatic stellate cells; each one with a specific function.
A hepatocyte is a cell of the main parenchymal tissue of the liver. Hepatocytes make up 80% of the liver's mass. Hepatocytes make up 80% of the liver's mass. These cells are involved in:
In histology (microscopic anatomy), the lobules of liver, or hepatic lobules, are small divisions of the liver defined at the microscopic scale. The hepatic lobule is a building block of the liver tissue, consisting of portal triads, hepatocytes arranged in linear cords between a capillary network, and a central vein.
Fig. 1: A binary search tree of size 9 and depth 3, with 8 at the root. In computer science, a binary search tree (BST), also called an ordered or sorted binary tree, is a rooted binary tree data structure with the key of each internal node being greater than all the keys in the respective node's left subtree and less than the ones in its right subtree.
In computer science, an optimal binary search tree (Optimal BST), sometimes called a weight-balanced binary tree, [1] is a binary search tree which provides the smallest possible search time (or expected search time) for a given sequence of accesses (or access probabilities). Optimal BSTs are generally divided into two types: static and dynamic.
Associative arrays may also be stored in unbalanced binary search trees or in data structures specialized to a particular type of keys such as radix trees, tries, Judy arrays, or van Emde Boas trees, though the relative performance of these implementations varies.
Seen as harbingers of death and disease, staples of horror films and Halloween decor, vultures actually play an important role in nature.
Dynamic problem For an initial set of N numbers, dynamically maintain the maximal one when insertion and deletions are allowed. A well-known solution for this problem is using a self-balancing binary search tree. It takes space O(N), may be initially constructed in time O(N log N) and provides insertion, deletion and query times in O(log N).