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Related Concept Videos

Computed Tomography01:10

Computed Tomography

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Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
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Design Example: Traverse Angle Computations01:25

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Traverse angle computations are a critical component of surveying, used to compute the internal angles within a closed traverse. A traverse consists of a series of connected lines forming a closed loop, often used for land boundary delineation or mapping. Calculating the internal angles ensures accuracy in the traverse geometry and is essential for checking survey data integrity.The process begins with known azimuths and bearings of the traverse sides. Internal angles at each vertex are...
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Area Computation by the Alternative Coordinate Method01:24

Area Computation by the Alternative Coordinate Method

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The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
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Imaging Studies III: Computed Tomography01:27

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DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...
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The Role of Ion Channels in Neuronal Computation01:19

The Role of Ion Channels in Neuronal Computation

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A postsynaptic neuron usually receives numerous impulses from several other presynaptic neurons. The axon hillock of the postsynaptic neuron integrates all these signals and determines the likelihood of firing an action potential.
Sometimes a single EPSP is strong enough to induce an action potential in the postsynaptic neuron. However, multiple presynaptic inputs must often create EPSPs around the same time for the postsynaptic neuron to be sufficiently depolarized to fire an action potential....
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What is Conservation Biology?01:57

What is Conservation Biology?

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Conservation biology is a scientific field that focuses on the preservation of biodiversity in order to protect ecosystems while meeting the needs of the human population. Humans require properly functioning ecosystems to maintain our supply of natural resources, including food, medicines, and building materials.
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Updated: Jan 26, 2026

Neutron Radiography and Computed Tomography of Biological Systems at the Oak Ridge National Laboratory's High Flux Isotope Reactor
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Exascale Computing: A New Dawn for Computational Biology.

Christopher T Lee1, Rommie E Amaro1

  • 1University of California San Diego.

Computing in Science & Engineering
|April 16, 2019
PubMed
Summary
This summary is machine-generated.

Computational analysis and modeling are vital for understanding complex biological systems. Exascale computing will drive new predictive models, advancing organism and ecosystem research for future innovations.

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Area of Science:

  • Biology
  • Computational Science
  • Ecology

Background:

  • Biological systems are increasingly recognized for their complexity.
  • Computational data analysis and modeling are essential tools for modern biological research.

Purpose of the Study:

  • To highlight the critical role of computational approaches in understanding complex biological systems.
  • To explore the potential of exascale computing in advancing biological research.

Main Methods:

  • Review of current trends in computational biology.
  • Discussion of the capabilities and implications of exascale computing.

Main Results:

  • Exascale computing will facilitate the creation of advanced predictive multiscale models.
  • These models will transform the study of organism and ecosystem behaviors.

Conclusions:

  • Computational data analysis and modeling are indispensable for biological discovery.
  • Exascale computing promises to unlock new frontiers in understanding life and ecosystems.