Hemoglobin structure and allosteric mechanism

Hemoglobin ◽  
2018 ◽  
pp. 58-93
Author(s):  
Jay F. Storz
Keyword(s):  
Experimental Data ◽  
Nuclear Magnetic Resonance ◽  
Ligand Binding ◽  
Atomic Level ◽  
Operating Conditions ◽  
X Ray Crystallography ◽  
Binding Behavior ◽  
Mechanistic Basis ◽  
Structural Mechanisms ◽  
Dynamic Interplay

Chapter 4 provides an overview of hemoglobin structure and explains the mechanistic basis of ligand-binding dynamics and allosteric effects. The chapter provides an overview of decades of research on structure-function relationships based on X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy. This body of work has provided atomic level insights into the structural mechanisms underlying key functional properties. The chapter also reviews experimental data on the ligand-binding behavior of hemoglobin, and discusses how the oxygenation properties of blood reflect a complex and dynamic interplay between the intrinsic O2-binding properties of hemoglobin and its operating conditions in the chemical milieu of the red blood cell.

Modeling and Experimental Validation of the Effective Bulk Modulus of a Mixture of Hydraulic Oil and Air

2014 ◽  
Vol 136 (5) ◽  
Author(s):  
Hossein Gholizadeh ◽  
Doug Bitner ◽  
Richard Burton ◽  
Greg Schoenau
Keyword(s):  
Experimental Data ◽  
Bulk Modulus ◽  
Theoretical Models ◽  
Operating Conditions ◽  
Air Bubbles ◽  
Pressure Sensitivity ◽  
Hydraulic Oil ◽  
Effective Bulk Modulus ◽  
Experimental Apparatus ◽  
Major Factors

It is well known that the presence of entrained air bubbles in hydraulic oil can significantly reduce the effective bulk modulus of hydraulic oil. The effective bulk modulus of a mixture of oil and air as pressure changes is considerably different than when the oil and air are not mixed. Theoretical models have been proposed in the literature to simulate the pressure sensitivity of the effective bulk modulus of this mixture. However, limited amounts of experimental data are available to prove the validity of the models under various operating conditions. The major factors that affect pressure sensitivity of the effective bulk modulus of the mixture are the amount of air bubbles, their size and the distribution, and rate of compression of the mixture. An experimental apparatus was designed to investigate the effect of these variables on the effective bulk modulus of the mixture. The experimental results were compared with existing theoretical models, and it was found that the theoretical models only matched the experimental data under specific conditions. The purpose of this paper is to specify the conditions in which the current theoretical models can be used to represent the real behavior of the pressure sensitivity of the effective bulk modulus of the mixture. Additionally, a new theoretical model is proposed for situations where the current models fail to truly represent the experimental data.

Performance Characterization of a Twin Scroll Volute for Turbocharging Applications

2018 ◽  
Author(s):  
Carlo Cravero ◽  
Mario La Rocca ◽  
Andrea Ottonello
Keyword(s):  
Experimental Data ◽  
Scientific Literature ◽  
Aerodynamic Performance ◽  
Operating Conditions ◽  
Automatic Design ◽  
Cfd Model ◽  
Radial Turbine ◽  
Wide Range ◽  
Partial Admission

The use of twin scroll volutes in radial turbine for turbocharging applications has several advantages over single passage volute related to the engine matching and to the overall compactness. Twin scroll volutes are of increasing interest in power unit development but the open scientific literature on their performance and modelling is still quite limited. In the present work the performance of a twin scroll volute for a turbocharger radial turbine are investigated in some detail in a wide range of operating conditions at both full and partial admission. A CFD model for the volute have been developed and preliminary validated against experimental data available for the radial turbine. Then the numerical model has been used to generate the database of solutions that have been investigated and used to extract the performance. Different parameters and indices are introduced to describe the volute aerodynamic performance in the wide range of operating conditions chosen. The above parameters can be used for volute development or matching with a given rotor or efficiently implemented in automatic design optimization strategies.

scholarly journals Unraveling the long-pursued Au144 structure by x-ray crystallography

2018 ◽  
Vol 4 (10) ◽  
pp. eaat7259 ◽  
Author(s):  
Nan Yan ◽  
Nan Xia ◽  
Lingwen Liao ◽  
Min Zhu ◽  
Fengming Jin ◽  
...  
Keyword(s):  
Metal Nanoparticles ◽  
Weak Interactions ◽  
Gold Nanoclusters ◽  
Atomic Level ◽  
High Quality ◽  
X Ray ◽  
X Ray Crystallography ◽  
Quantum Size ◽  
First Time

The transition from nanocluster to nanocrystal is a central issue in nanoscience. The atomic structure determination of metal nanoparticles in the transition size range is challenging and particularly important in understanding the quantum size effect at the atomic level. On the basis of the rationale that the intra- and interparticle weak interactions play critical roles in growing high-quality single crystals of metal nanoparticles, we have reproducibly obtained ideal crystals of Au144(SR)60 and successfully solved its structure by x-ray crystallography (XRC); this structure was theoretically predicted a decade ago and has long been pursued experimentally but without success until now. Here, XRC reveals an interesting Au12 hollow icosahedron in thiolated gold nanoclusters for the first time. The Au–Au bond length, close to that of bulk gold, shows better thermal extensibility than the other Au–Au bond lengths in Au144(SR)60, providing an atomic-level perspective because metal generally shows better thermal extensibility than nonmetal materials. Thus, our work not only reveals the mysterious, long experimentally pursued structure of a transition-sized nanoparticle but also has important implications for the growth of high-quality, single-crystal nanoparticles, as well as for the understanding of the thermal extensibility of metals from the perspective of chemical bonding.

NUMERICAL ESTIMATION OF MOISTURE CONTENT IN SPRAY DRIED JUICE POWDER

2016 ◽  
Vol 78 (8-3) ◽  
Author(s):  
Aliyu Bello A. ◽  
Arshad Ahmad ◽  
Adnan Ripin ◽  
Olagoke Oladokun
Keyword(s):  
Experimental Data ◽  
Moisture Content ◽  
Diffusion Model ◽  
Process Model ◽  
Small Error ◽  
Operating Conditions ◽  
Balance Model ◽  
Pineapple Juice ◽  
Droplet Drying ◽  
Spray Dried

The moisture contents of powders is an important parameter that affects the quality and commercial value of spray dried products. The utility of predicted moisture content values from two droplet drying models were compared with experimental data for spray dried pineapple juice, using the Ranz-Marshal and its modified variants for the heat and mass transfer correlations. The droplet Diffusion model, using the Zhifu correlation, gave estimates with errors of about 8% at 165 oC, 9% at 171 oC, 26% at 179 oC and 2% at 185 oC. The Ranz-Marshal correlation also gave comparable results with this model while results using the Downing and modified Ranz-Marshall correlations widely diverged. The Energy balance model predicted completely dried juice particles, and short drying times, in contrast to the experimental data. The small error sizes of the Diffusion model improves on the wide error sizes of an earlier process model, making is useful as a first approximation choice, for spray drier design and simulation, especially for juices under comparable operating conditions.

KNT-artificial neural network model for flux prediction of ultrafiltration membrane producing drinking water

2004 ◽  
Vol 50 (8) ◽  
pp. 103-110 ◽  
Author(s):  
H.K. Oh ◽  
M.J. Yu ◽  
E.M. Gwon ◽  
J.Y. Koo ◽  
S.G. Kim ◽  
...  
Keyword(s):  
Neural Network ◽  
Experimental Data ◽  
Artificial Neural Network ◽  
Correlation Coefficient ◽  
Network Model ◽  
Operating Conditions ◽  
Transmembrane Pressure ◽  
Feed Water ◽  
Permeate Flux ◽  
Artificial Neural

This paper describes the prediction of flux behavior in an ultrafiltration (UF) membrane system using a Kalman neuro training (KNT) network model. The experimental data was obtained from operating a pilot plant of hollow fiber UF membrane with groundwater for 7 months. The network was trained using operating conditions such as inlet pressure, filtration duration, and feed water quality parameters including turbidity, temperature and UV254. Pre-processing of raw data allowed the normalized input data to be used in sigmoid activation functions. A neural network architecture was structured by modifying the number of hidden layers, neurons and learning iterations. The structure of KNT-neural network with 3 layers and 5 neurons allowed a good prediction of permeate flux by 0.997 of correlation coefficient during the learning phase. Also the validity of the designed model was evaluated with other experimental data not used during the training phase and nonlinear flux behavior was accurately estimated with 0.999 of correlation coefficient and a lower error of prediction in the testing phase. This good flux prediction can provide preliminary criteria in membrane design and set up the proper cleaning cycle in membrane operation. The KNT-artificial neural network is also expected to predict the variation of transmembrane pressure during filtration cycles and can be applied to automation and control of full scale treatment plants.

The crystal structure of ethyl-Z-3-amino-2-benzoyl-2-butenoate and measurement of the barrier to E,Z-isomerization

1980 ◽  
Vol 58 (17) ◽  
pp. 1821-1828 ◽  
Author(s):  
Gary D. Fallon ◽  
Bryan M. Gatehouse ◽  
Allan Pring ◽  
Ian D. Rae ◽  
Josephine A. Weigold
Keyword(s):  
Crystal Structure ◽  
Nuclear Magnetic Resonance ◽  
Hydrogen Bond ◽  
Free Energy ◽  
Magnetic Resonance ◽  
Energy Of Activation ◽  
X Ray ◽  
X Ray Crystallography ◽  
Free Energy Of Activation ◽  
Nuclear Magnetic

Ethyl-3-amino-2-benzoyl-2-butenoate crystallizes from pentane as either the E (mp 82–84 °C) or the Z-isomer (mp 95.5–96.5 °C). The E isomer is less stable, and changes spontaneously into the Z, which bas been identified by X-ray crystallography. The structure is characterised by an N–H/ester CO hydrogen bond and a very long C2—C3 bond (1.39 Å). Nuclear magnetic resonance methods have been used to measure the rate of [Formula: see text] isomerization at several temperatures, leading to the estimate that the free energy of activation at 268 K is 56 ± 8 kJ.

Experimental and Analytical Characterization of Alternative Aviation Fuel Sprays Under Realistic Operating Conditions

2018 ◽  
Author(s):  
Andrew Corber ◽  
Nader Rizk ◽  
Wajid Ali Chishty
Keyword(s):  
Experimental Data ◽  
Alternative Fuels ◽  
Laser Sheet ◽  
National Research Council ◽  
Diagnostic System ◽  
Operating Conditions ◽  
Aviation Fuel ◽  
Injection System ◽  
Test Time

The National Jet Fuel Combustion Program (NJFCP) is an initiative, currently being led by the Office of Environment & Energy at the FAA, to streamline the ASTM jet fuels certification process for alternative aviation fuels. In order to accomplish this objective, the program has identified specific applied research tasks in several areas. The National Research Council of Canada (NRC) is contributing to the NJFCP in the areas of sprays and atomization and high altitude engine performance. This paper describes work pertaining to atomization tests using a reference injection system. The work involves characterization of the injection nozzle, comparison of sprays and atomization quality of various conventional and alternative fuels, as well as use of the experimental data to validate spray correlations. The paper also briefly explores the application viability of a new spray diagnostic system that has potential to reduce test time in characterizing sprays. Measurements were made from ambient up to 10 bar pressures in NRC’s High Pressure Spray Facility using optical diagnostics including laser diffraction, phase Doppler anemometry (PDA), LIF/Mie Imaging and laser sheet imaging to assess differences in the atomization characteristics of the test fuels. A total of nine test fluids including six NJFCP fuels and three calibration fluids were used. The experimental data was then used to validate semi-empirical models, developed through years of experience by engine OEMs and modified under NJFCP, for predicting droplet size and distribution. The work offers effective tools for developing advanced fuel injectors, and generating data that can be used to significantly enhance multi-dimensional combustor simulation capabilities.

Sign in / Sign up

Export Citation Format

Share Document