scholarly journals Amplitude, Latency, and Peak Velocity in Accommodation and Disaccommodation Dynamics

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Antonio J. Del Águila-Carrasco ◽  
José J. Esteve-Taboada ◽  
Eleni Papadatou ◽  
Teresa Ferrer-Blasco ◽  
Robert Montés-Micó
Keyword(s):  
Experimental Data ◽  
Exponential Function ◽  
Peak Velocity ◽  
Data Fitting ◽  
Mean Difference ◽  
Sigmoid Function ◽  
Analysis Strategies ◽  
Analysis Strategy ◽  
Experimental Data Fitting ◽  
Adequate Analysis

The aim of this work was to ascertain whether there are differences in amplitude, latency, and peak velocity of accommodation and disaccommodation responses when different analysis strategies are used to compute them, such as fitting different functions to the responses or for smoothing them prior to computing the parameters. Accommodation and disaccommodation responses from four subjects to pulse changes in demand were recorded by means of aberrometry. Three different strategies were followed to analyze such responses: fitting an exponential function to the experimental data; fitting a Boltzmann sigmoid function to the data; and smoothing the data. Amplitude, latency, and peak velocity of the responses were extracted. Significant differences were found between the peak velocity in accommodation computed by fitting an exponential function and smoothing the experimental data (mean difference 2.36 D/s). Regarding disaccommodation, significant differences were found between latency and peak velocity, calculated with the two same strategies (mean difference of 0.15 s and −3.56 D/s, resp.). The strategy used to analyze accommodation and disaccommodation responses seems to affect the parameters that describe accommodation and disaccommodation dynamics. These results highlight the importance of choosing the most adequate analysis strategy in each individual to obtain the parameters that characterize accommodation and disaccommodation dynamics.

scholarly journals Confronting theoretical predictions with experimental data; fitting strategy for multi-dimensional distributions

2015 ◽  
Vol 16 (1) ◽  
pp. 17 ◽  
Author(s):  
Przecinski Tomasz ◽  
Roig Pablo ◽  
Shekhovtsova Olga ◽  
Was Zbigniew ◽  
Zaremba Jakub
Keyword(s):  
Experimental Data ◽  
Data Fitting ◽  
Theoretical Predictions ◽  
Experimental Data Fitting

Mass Loss and Nose Shape Change on Ogive-nose Steel Projectiles During Concrete Penetration

2012 ◽  
Vol 13 (3-4) ◽  
Author(s):  
Hai-Jun Wu ◽  
Feng-Lei Huang ◽  
Yi-Nan Wang ◽  
Zhou-Ping Duan ◽  
Yu Shan
Keyword(s):  
Experimental Data ◽  
Mass Loss ◽  
High Speed ◽  
Shape Change ◽  
Data Fitting ◽  
Nose Shape ◽  
Semi Empirical ◽  
The Impact ◽  
Steel Projectiles ◽  
Experimental Data Fitting

AbstractThe mass loss of the nose of projectile is an obvious phenomenon in high-speed penetration into concrete target. The mass loss percentage depends linearly on the impact velocities of projectile according to experimental data fitting results. A semi-empirical model, which can calculate the ogive-nose shape change due to mass loss, is developed in this paper. The modified penetration model shows that the penetration depth is influenced by nose erosion.

scholarly journals Correlation between Paris function parameters to crack velocity for Alumina ceramics

2011 ◽  
Vol 8 (2) ◽  
pp. 326-332
Author(s):  
Baghdad Science Journal
Keyword(s):  
Experimental Data ◽  
Crack Growth ◽  
Exponential Function ◽  
Crack Velocity ◽  
Alumina Ceramic ◽  
Velocity Versus ◽  
Rate Theory ◽  
Alumina Ceramics ◽  
Region I ◽  
Different Grain Size

The question about the existence of correlation between the parameters A and m of the Paris function is re-examined theoretically for brittle material such as alumina ceramic (Al2O3) with different grain size. Investigation about existence of the exponential function which fit a good approximation to the majority of experimental data of crack velocity versus stress intensity factor diagram. The rate theory of crack growth was applied for data of alumina ceramics samples in region I and making use of the values of the exponential function parameters the crack growth rate theory parameters were estimated.

scholarly journals Influence of image analysis strategy, cooling rate, and sample volume on apparent protein cloud-point temperature determination

2020 ◽  
Author(s):  
Marieke E. Klijn ◽  
Jürgen Hubbuch
Keyword(s):  
Image Analysis ◽  
Cooling Rate ◽  
Cloud Point ◽  
Detection Method ◽  
Sample Volume ◽  
Point Temperature ◽  
Analysis Strategies ◽  
Experimental Parameters ◽  
Analysis Strategy ◽  
Cloud Point Temperature

AbstractThe protein cloud-point temperature (TCloud) is a known representative of protein–protein interaction strength and provides valuable information during the development and characterization of protein-based products, such as biopharmaceutics. A high-throughput low volume TCloud detection method was introduced in preceding work, where it was concluded that the extracted value is an apparent TCloud (TCloud,app). As an understanding of the apparent nature is imperative to facilitate inter-study data comparability, the current work was performed to systematically evaluate the influence of 3 image analysis strategies and 2 experimental parameters (sample volume and cooling rate) on TCloud,app detection of lysozyme. Different image analysis strategies showed that TCloud,app is detectable by means of total pixel intensity difference and the total number of white pixels, but the latter is also able to extract the ice nucleation temperature. Experimental parameter variation showed a TCloud,app depression for increasing cooling rates (0.1–0.5 °C/min), and larger sample volumes (5–24 μL). Exploratory thermographic data indicated this resulted from a temperature discrepancy between the measured temperature by the cryogenic device and the actual sample temperature. Literature validation confirmed that the discrepancy does not affect the relative inter-study comparability of the samples, regardless of the image analysis strategy or experimental parameters. Additionally, high measurement precision was demonstrated, as TCloud,app changes were detectable down to a sample volume of only 5 μL and for 0.1 °C/min cooling rate increments. This work explains the apparent nature of the TCloud detection method, showcases its detection precision, and broadens the applicability of the experimental setup.

A Soil Water Characteristic Curve Model Considering Urea Concentration

2013 ◽  
Vol 798-799 ◽  
pp. 157-160
Author(s):  
You Le Wang ◽  
Dong Fang Tian ◽  
Gai Qing Dai ◽  
Yao Ruan ◽  
Lang Tian
Keyword(s):  
Experimental Data ◽  
Water Content ◽  
Soil Water ◽  
Exponential Function ◽  
Characteristic Curve ◽  
Urea Concentration ◽  
Exponential Functions ◽  
Valuable Data ◽  
Soil Water Characteristic Curve ◽  
Curve Model

A new soil water characteristic curve (SWCC) model considering urea concentration is presented in the paper. Two assumptions are used to obtain the model. One is SWCC which could be described by exponential functions in the experiments. Another is relationship between the parameters of exponential functions and urea concentration which is linear based on experimental data. In the research, we have carried out some experiments of SWCC and obtained some valuable data which could affect urea concentration. By using linear fitting, an exponential function between water content and suction and urea concentration is established.

scholarly journals CONCEPT ANALYSIS STRATEGIES FOR THE DEVELOPMENT OF MIDDLE-RANGE NURSING THEORIES

2019 ◽  
Vol 28 ◽  
Author(s):  
Marcos Antônio Gomes Brandão ◽  
Claudia Angélica Mainenti Ferreira Mercês ◽  
Rafael Oliveira Pitta Lopes ◽  
Jaqueline Santos de Andrade Martins ◽  
Priscilla Alfradique de Souza ◽  
...  
Keyword(s):  
Concept Analysis ◽  
Research And Practice ◽  
Philosophical Foundations ◽  
Middle Range ◽  
Analysis Strategies ◽  
Analysis Strategy ◽  
Analytical Procedures ◽  
Interactive Theory

ABSTRACT Objective: to reflect on strengths and limitations of the concept analysis strategies as resources for the development of middle-range nursing theories. Method: a reflection study of metatheoretical nature. Results: strategies for concept analysis for the development of middle-range nursing theories are presented. The philosophical foundations of concepts and their interface with the analytical procedures were presented. It has been found that Nursing uses three approaches for concept analysis: adapted Wilsonian, evolutionary and pragmatic utility. The concept analysis strategy was illustrated by the Interactive Theory of Breastfeeding. Conclusion: concept analysis strategies have been employed in nursing to develop theories and to refine the concepts and terminologies used in research and practice. Despite their widespread use, there is still great diversity of methods used and some uncertainties that hinder their implementation.

Particle Identification Using Light Scattering

2009 ◽  
pp. 143-160
Author(s):  
M. C. Bartholomew-Biggs ◽  
Z. Ulanowski ◽  
S. Zakovic
Keyword(s):  
Experimental Data ◽  
Global Optimization ◽  
Light Scattering ◽  
Least Squares ◽  
Scattering Problem ◽  
Data Fitting ◽  
Particle Identification ◽  
Identification Procedure ◽  
Robust Identification ◽  
Actual Particle

We discuss some experience of solving an inverse light scattering problem for single, spherical, homogeneous particles using least squares global optimization. If there is significant noise in the data, the particle corresponding to the “best” solution may not correspond well to the “actual” particle. One way of overcoming this difficulty involves the use of peak positions in the experimental data as a means of distinguishing genuine from spurious solutions. We introduce two composite approaches which combine conventional data fitting with peak-matching and show that they lead to a more robust identification procedure.

Sign in / Sign up

Export Citation Format

Share Document