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Echo01:06

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The human ear cannot distinguish between two sources of sound if they happen to reach within a specific time interval, typically 0.1 seconds apart. More than this, and they are perceived as separate sources.
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Hydronium and hydroxide ions are present both in pure water and in all aqueous solutions, and their concentrations are inversely proportional as determined by the ion product of water (Kw). The concentrations of these ions in a solution are often critical determinants of the solution’s properties and the chemical behaviors of its other solutes. Two different solutions can differ in their hydronium or hydroxide ion concentrations by a million, billion, or even trillion times. A common means of...
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Social psychologists analyze how groups influence one another, shaping social structures and interactions through both cooperation and competition. These dynamics manifest in various ways, ranging from economic partnerships to intergroup conflicts that shape societal structures and perceptions.Cooperation and Competition in Intergroup RelationsIntergroup relationships vary across contexts, sometimes fostering cooperation and mutual benefit while at other times leading to conflict and...
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Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)01:20

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Two NMR-active nuclei bonded to a central atom can be involved in geminal or two-bond coupling. Geminal coupling is commonly seen between diastereotopic protons in chiral molecules and unsymmetrical alkenes, among others.
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Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)01:22

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Vicinal or three-bond coupling is commonly observed between protons attached to adjacent carbons. Here, nuclear spin information is primarily transferred via electron spin interactions between adjacent C‑H bond orbitals. This generally favors the antiparallel arrangement of spins, so 3J values are usually positive.
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Scaling01:26

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In designing and analyzing filters, resonant circuits, or circuit analysis at large, working with standard element values like 1 ohm, 1 henry, or 1 farad can be convenient before scaling these values to more realistic figures. This approach is widely utilized by not employing realistic element values in numerous examples and problems; it simplifies mastering circuit analysis through convenient component values. The complexity of calculations is thereby reduced, with the understanding that...
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Updated: Feb 12, 2026

Coupling Carbon Capture from a Power Plant with Semi-automated Open Raceway Ponds for Microalgae Cultivation
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Semi-Automated Air-Coupled Impact-Echo Method for Large-Scale Parkade Structure.

Tyler Epp1, Dagmar Svecova2, Young-Jin Cha3

  • 1Department of Civil Engineering, University of Manitoba, Winnipeg, MB R3T 2N2, Canada. umeppt@myumanitoba.ca.

Sensors (Basel, Switzerland)
|March 30, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces an Artificial Neural Network (ANN) for faster structural health monitoring (SHM). The ANN efficiently detects damage in reinforced concrete structures using impact-echo data, reducing testing time.

Keywords:
artificial neural networkdamage detectionenergy impact factorimpact-echomachine learningreinforced concretewavelet transformation

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Area of Science:

  • Civil Engineering
  • Materials Science
  • Artificial Intelligence

Background:

  • Structural Health Monitoring (SHM) systems are increasingly data-intensive, employing diverse sensors for infrastructure assessment.
  • Large-scale structures like bridges and dams present challenges in terms of inspection time and scale.
  • Automated measurement systems are crucial for timely data acquisition in SHM.

Purpose of the Study:

  • To propose an Artificial Neural Network (ANN) application for identifying intact and damaged locations in reinforced concrete structures.
  • To utilize impact-echo data collected from both laboratory and field experiments for damage detection.
  • To reduce the time required for in situ damage detection testing in civil infrastructure.

Main Methods:

  • Implementation of an Artificial Neural Network (ANN) for data analysis.
  • Collection of impact-echo data using air-coupled microphones from reinforced concrete beams.
  • Conducting lab experiments and a field experiment in a parking garage, with semi-autonomous impact-echo testing.
  • Employing a least-square distance approach for classification, enhanced by the ANN to eliminate user-defined cutoff values.

Main Results:

  • The ANN successfully determines intact and damaged locations from a small training sample of impact-echo data.
  • The semi-autonomous field testing expedited the initial damage detection process.
  • The ANN's ability to forgo user-defined cutoff values streamlines the classification of structural integrity.

Conclusions:

  • The proposed ANN application shows significant potential for reducing testing time in SHM of large-scale civil reinforced concrete structures.
  • Automated systems, like the developed ANN, are key to overcoming the challenges of scale and time in infrastructure monitoring.
  • This approach contributes to more efficient and effective in situ damage detection.