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Preferential intracellular pH regulation is a common trait amongst fishes exposed to high environmental CO2
Article testing the hypothesis that preferential pHi regulation is a widespread strategy of acid–base regulation among fish by measuring pHi regulation in 10 different fish species that are broadly phylogenetically separated, spanning six orders, eight families and 10 genera.
Date:
June 17, 2019
Creator:
Shartau, R. B.; Baker, D. W.; Harter, T. S.; Aboagye, D. L.; Allen, P. J.; Val, A. L. et al.
Object Type:
Article
System:
The UNT Digital Library
Does the left aorta provide proton-rich blood to the gut when crocodilians digest a meal?
Article measuring blood parameters in the left aortae and atria of crocodilians. The findings do not support the hypothesis that a R–L shunt serves to deliver CO2 for the gastrointestinal system after feeding in crocodilians.
Date:
February 4, 2019
Creator:
Conner, Justin L.; Crossley, Janna; Elsey, Ruth M.; Nelson, Derek; Wang, Tobias & Crossley, Dane A., II
Object Type:
Article
System:
The UNT Digital Library
CAREER: Orbital-based Descriptors for Dynamical Properties of Quantum Defects
Data management plan for the grant, "CAREER: Orbital-based Descriptors for Dynamical Properties of Quantum Defects."
Date:
2024-04-01/2029-03-31
Creator:
Wang, Yuanxi
Object Type:
Text
System:
The UNT Digital Library
Analysis of the potential behavioral impact of methanol when used as a solvent: Dataset from zebrafish (Danio rerio) behavioral research
This article is a dataset that describes behavioral results in zebrafish (Danio rerio) individually exposed to methanol, a solvent which is capable of altering physiology and behavior high concentrations.
Date:
April 1, 2021
Creator:
Hamilton, Trevor J.; Szaszkiewicz, Joshua; Krook, Jeffrey & Burggren, Warren W.
Object Type:
Article
System:
The UNT Digital Library
Using uncertainty quantification and machine learning techniques to study the evolution of odor capture
Data management plan for the research grant, "Using uncertainty quantification and machine learning techniques to study the evolution of odor capture." This research proposes the application of uncertainty quantification (UQ) and machine learning (ML) to a CFD model of odor capture to understand the role of hair-array morphology, kinematics, and fluid environment in odor capture. The combination of CFD modeling and UQ&ML techniques can map out the performance space under which these chemosensory hair arrays operate and the relative sensitivity of each parameter of odor capture to construct a global, quantitative understanding of how parameters control odor-capture performance. Furthermore, this analysis can eliminate parameters that have no influence on odor capture, extracting the root principles of odor capture and providing a more efficient way to construct bioinspired devices for chemical detection. This work is of interest to the Army for extracting design principles that can be used for biomimetic and/or bioinspired devices for sensing hazardous chemicals in the environment (e.g. explosives).
Date:
2022-04-01/2025-03-31
Creator:
He, Yanyan & Waldrop, Lindsay D.
Object Type:
Text
System:
The UNT Digital Library
CAS: Highly Interacting Panchromatic Push-Pull Systems: Symmetry Breaking and Quantum Coherence in Electron Transfer
Data management plan for the grant, "CAS: Highly Interacting Panchromatic Push-Pull Systems: Symmetry Breaking and Quantum Coherence in Electron Transfer."
Date:
2024-04-01/2027-03-31
Creator:
Wang, Hong
Object Type:
Text
System:
The UNT Digital Library