Evaluating the utility of gravity gradient tensor components

Geophysics ◽  
2014 ◽  
Vol 79 (1) ◽  
pp. G1-G14 ◽  
Author(s):  
Mark Pilkington
Keyword(s):  
Gravity Gradient ◽  
Directional Sensitivity ◽  
Model Parameters ◽  
Data Sets ◽  
Model Errors ◽  
Gravity Response ◽  
Quantitative Rating ◽  
Text Ranking ◽  
Body Shapes ◽  
The Relationship

Gravity gradiometry allows individual components and combinations of components to be used in interpretation. Knowledge of the information content of different components and their combinations is therefore crucial to their effectiveness, and a quantitative rating of information level is needed to guide the choice. To this end, I use linear inverse theory to examine the relationship between the different tensor components and combinations thereof and the model parameters to be determined. The model used is a rectangular prism, characterized by seven parameters: the prism location [Formula: see text], [Formula: see text]; its width [Formula: see text] and breadth [Formula: see text]; the density [Formula: see text]; the depth to top [Formula: see text]; and thickness [Formula: see text]. Varying these values allows a variety of body shapes, e.g., blocks, plates, dykes, and rods, to be considered. The Jacobian matrix, which relates parameters and their associated gravity response, clarifies the importance and stability of model parameters in the presence of data errors. In general, for single tensor components and combinations, the progression from well to poorly determined parameters follows the trend of [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], to [Formula: see text]. Ranking the estimated model errors from a range of models showed that data sets consisting of concatenated components produced the smallest parameter errors. For data sets comprising combined tensor components, the invariants of the tensor produced the smallest parameter errors. Of the single tensor components, [Formula: see text] gave the best performance overall, but those single components with strong directional sensitivity can produce some individual parameters with smaller estimated errors (e.g., [Formula: see text] and [Formula: see text] estimated from [Formula: see text]).

scholarly journals Peach Rusty Spot Epidemics: Management with Fungicide, Effect on Fruit Growth, and the Incidence-Lesion Density Relationship

Plant Disease ◽  
2003 ◽  
Vol 87 (12) ◽  
pp. 1477-1486 ◽  
Author(s):  
Laura A. Furman ◽  
Norman Lalancette ◽  
James F. White
Keyword(s):  
Disease Incidence ◽  
Exponential Model ◽  
Rapid Decline ◽  
Model Parameters ◽  
Data Sets ◽  
Progress Curve ◽  
Significant Seasonal Variation ◽  
Density Relationship ◽  
Parameter Values ◽  
The Relationship

Different numbers of consecutive fungicide applications, beginning at petal fall and continuing into the summer, were examined for their effect on rusty spot epidemics. Disease progressions for each fungicide level were quantified by fitting either the logistic or monomolecular model. When the weighted absolute infection rate (ρ) and maximum disease level (Kmax) parameters were expressed as functions of the number of applications, the logistic decline model provided the best fit for five of six data sets. This model described a gradual decrease in ρ and Kmax in response to the initial fungicide application, a rapid decline in parameter values with the addition of one or two applications, and a diminished parameter response as fungicide applications continued toward the end of the epidemic. Based on examination of model behavior across all 3 years of the study, adequate management was achieved with a total of three to five fungicide applications. Additional analyses of area under the disease progress curve and final disease intensity at harvest supported these results and indicated that further reduction in fungicide usage may be possible. Unlike earlier findings, rusty spot did not significantly decrease fruit volume or weight at midseason or at harvest; as lesion density increased, fruit volume remained constant. The relationship between disease incidence and lesion density within any given year was best explained by the zero-intercept version of the exponential model. However, comparison of model parameters across years revealed significant seasonal variation. Nevertheless, the incidence-lesion density relationships were fairly uniform across years at incidence values below 0.5, where lesion density increased gradually and in a near-linear fashion.

scholarly journals GRS1915+105: a comparison of the plateau state to the canonical hard state

2010 ◽  
Vol 6 (S275) ◽  
pp. 294-298 ◽  
Author(s):  
Pieter van Oers ◽  
Sera Markoff
Keyword(s):  
Black Hole ◽  
Near Infrared ◽  
Model Parameters ◽  
Data Sets ◽  
X Ray ◽  
Black Hole Binaries ◽  
Hard State ◽  
Multi Wavelength ◽  
Plateau State ◽  
The Relationship

AbstractGRS 1915+105 is a very peculiar black hole binary that exhibits accretion-related states that are not observed in any other stellar-mass black hole system. One of these states, however – referred to as the plateau state – may be related to the canonical hard state of black hole X-ray binaries. Both the plateau and hard state are associated with steady, relatively lower X-ray emission and flat/inverted radio emission, that is sometimes resolved into compact, self-absorbed jets. To investigate the relationship between the plateau and the hard state, we fit two multi-wavelength observations using a steady-state outflow-dominated model, developed for hard state black hole binaries. The data sets consist of quasi-simultaneous observations in radio, near-infrared and X-ray bands. Interestingly, we find both significant differences between the two plateau states, as well as between the best-fit model parameters and those representative of the hard state. We discuss our interpretation of these results, and the possible implications for GRS 1915+105's relationship to canonical black hole candidates.

scholarly journals Population Pharmacodynamic Modeling Using the Sigmoid Emax Model: Influence of Inter-individual Variability on the Steepness of the Concentration–Effect Relationship. a Simulation Study

2020 ◽  
Vol 23 (1) ◽  
Author(s):  
Johannes H. Proost ◽  
Douglas J. Eleveld ◽  
Michel M. R. F. Struys
Keyword(s):  
Binary Data ◽  
Drug Effect ◽  
Individual Variability ◽  
Concentration Effect ◽  
Pharmacodynamic Modeling ◽  
Model Parameters ◽  
Data Sets ◽  
Effect Relationship ◽  
Multiple Data Sets ◽  
The Relationship

AbstractThe relationship between the concentration of a drug and its pharmacological effect is often described by empirical mathematical models. We investigated the relationship between the steepness of the concentration–effect relationship and inter-individual variability (IIV) of the parameters of the sigmoid Emax model, using the similarity between the sigmoid Emax model and the cumulative log-normal distribution. In addition, it is investigated whether IIV in the model parameters can be estimated accurately by population modeling. Multiple data sets, consisting of 40 individuals with 4 binary observations in each individual, were simulated with varying values for the model parameters and their IIV. The data sets were analyzed using Excel Solver and NONMEM. An empirical equation (Eq. (11)) was derived describing the steepness of the population-predicted concentration–effect profile (γ*) as a function of γ and IIV in C50 and γ, and was validated for both binary and continuous data. The tested study design is not suited to estimate the IIV in C50 and γ with reasonable precision. Using a naive pooling procedure, the population estimates γ* are significantly lower than the value of γ used for simulation. The steepness of the population-predicted concentration–effect relationship (γ*) is less than that of the individuals (γ). Using γ*, the population-predicted drug effect represents the drug effect, for binary data the probability of drug effect, at a given concentration for an arbitrary individual.

The visual arrays task…visual storage capacity or attention control?

2019 ◽  
Author(s):  
Jessie Martin ◽  
Jason S. Tsukahara ◽  
Christopher Draheim ◽  
Zach Shipstead ◽  
Cody Mashburn ◽  
...  
Keyword(s):  
Working Memory ◽  
Storage Capacity ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Data Sets ◽  
Independent Data ◽  
Visual Storage ◽  
Design Selection ◽  
The Relationship

**The uploaded manuscript is still in preparation** In this study, we tested the relationship between visual arrays tasks and working memory capacity and attention control. Specifically, we tested whether task design (selection or non-selection demands) impacted the relationship between visual arrays measures and constructs of working memory capacity and attention control. Using analyses from 4 independent data sets we showed that the degree to which visual arrays measures rely on selection influences the degree to which they reflect domain-general attention control.

Epidemiological Evidence that Maternal Influenza Contributes to the Aetiology of Schizophrenia

1993 ◽  
Vol 163 (4) ◽  
pp. 522-534 ◽  
Author(s):  
W. Adams ◽  
R. E. Kendell ◽  
E. H. Hare ◽  
P. Munk-Jørgensen
Keyword(s):  
Data Sets ◽  
Time Lags ◽  
Epidemiological Evidence ◽  
Intrauterine Development ◽  
Increased Risk ◽  
Schizophrenic Patients ◽  
The Relationship ◽  
Monthly Incidence ◽  
Maternal Influenza

The epidemiological evidence that the offspring of women exposed to influenza in pregnancy are at increased risk of schizophrenia is conflicting. In an attempt to clarify the issue we explored the relationship between the monthly incidence of influenza (and measles) in the general population and the distribution of birth dates of three large series of schizophrenic patients - 16 960 Scottish patients born in 1932–60; 22 021 English patients born in 1921–60; and 18 723 Danish patients born in 1911–65. Exposure to the 1957 epidemic of A2 influenza in midpregnancy was associated with an increased incidence of schizophrenia, at least in females, in all three data sets. We also confirmed the previous report of a statistically significant long-term relationship between patients' birth dates and outbreaks of influenza in the English series, with time lags of - 2 and - 3 months (the sixth and seventh months of pregnancy). Despite several other negative studies by ourselves and others we conclude that these relationships are probably both genuine and causal; and that maternal influenza during the middle third of intrauterine development, or something closely associated with it, is implicated in the aetiology of some cases of schizophrenia.

PSVI-8 Meta-regression Analysis to Determine the Relationship Between Growing Pig Body Weight and Variation

2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  
Keyword(s):  
Body Weight ◽  
Regression Analysis ◽  
Sample Size ◽  
Polynomial Regression ◽  
Data Sets ◽  
Regression Equations ◽  
Prediction Equations ◽  
Data Set ◽  
Rate Of Increase ◽  
The Relationship

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.

scholarly journals Dampness and student-reported social climate: two multilevel mediation models

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Eerika Finell ◽  
Asko Tolvanen ◽  
Juha Pekkanen ◽  
Timo Ståhl ◽  
Pauliina Luopa
Keyword(s):  
Indoor Air ◽  
Social Climate ◽  
School Level ◽  
Data Sets ◽  
Student Relationships ◽  
Teacher Student Relationships ◽  
Teacher Student ◽  
Mediational Models ◽  
The Relationship ◽  
Perceptions Of School

Abstract Background Little previous research has analysed the relationship between schools’ indoor air problems and schools’ social climate. In this study, we analysed a) whether observed mould and dampness in a school building relates to students’ perceptions of school climate (i.e. teacher-student relationships and class spirit) and b) whether reported subjective indoor air quality (IAQ) at the school level mediates this relationship. Methods The data analysed was created by merging two nationwide data sets: survey data from students, including information on subjective IAQ (N = 25,101 students), and data from schools, including information on mould and dampness in school buildings (N = 222). The data was analysed using multilevel mediational models. Results After the background variables were adjusted, schools’ observed mould and dampness was not significantly related to neither student-perceived teacher-student relationships nor class spirit. However, our mediational models showed that there were significant indirect effects from schools’ observed mould and dampness to outcome variables via school-level subjective IAQ: a) in schools with mould and dampness, students reported significantly poorer subjective IAQ (standardised β = 0.34, p < 0.001) than in schools without; b) the worse the subjective IAQ at school level, the worse the student-reported teacher-student relationships (β = 0.31, p = 0.001) and class spirit (β = 0.25, p = 0.006). Conclusions Problems in a school’s indoor environment may impair the school’s social climate to the degree that such problems decrease the school’s perceived IAQ.

Sicker and Poorer—The Consequences of Being Uninsured: A Review of the Research on the Relationship between Health Insurance, Medical Care Use, Health, Work, and Income

2003 ◽  
Vol 60 (2_suppl) ◽  
pp. 3S-75S ◽  
Author(s):  
Jack Hadley
Keyword(s):  
Health Insurance ◽  
Medical Care ◽  
Data Sets ◽  
Work Effort ◽  
Services Research ◽  
The Past ◽  
Medical Care Use ◽  
Process Studies ◽  
Annual Earnings ◽  
The Relationship

Health services research conducted over the past 25 years makes a compelling case that having health insurance or using more medical care would improve the health of the uninsured. The literature's broad range of conditions, populations, and methods makes it difficult to derive a precise quantitative estimate of the effect of having health insurance on the uninsured's health. Some mortality studies imply that a 4% to 5% reduction in the uninsured's mortality is a lower bound; other studies suggest that the reductions could be as high as 20% to 25%. Although all of the studies reviewed suffer from methodological flaws of varying degrees, there is substantial qualitative consistency across studies of different medical conditions conducted at different times and using different data sets and statistical methods. Corroborating process studies find that the uninsured receive fewer preventive and diagnostic services, tend to be more severely ill when diagnosed, and receive less therapeutic care. Other literature suggests that improving health status from fair or poor to very good or excellent would increase both work effort and annual earnings by approximately 15% to 20%.

scholarly journals Theory and Applications of the Unit Gamma/Gompertz Distribution

Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1850
Author(s):  
Rashad A. R. Bantan ◽  
Farrukh Jamal ◽  
Christophe Chesneau ◽  
Mohammed Elgarhy
Keyword(s):  
Stochastic Ordering ◽  
Real Data ◽  
Rate Function ◽  
The Other ◽  
Likelihood Method ◽  
Model Parameters ◽  
Data Sets ◽  
Gompertz Distribution ◽  
Probability And Statistics ◽  
Analytical Behavior

Unit distributions are commonly used in probability and statistics to describe useful quantities with values between 0 and 1, such as proportions, probabilities, and percentages. Some unit distributions are defined in a natural analytical manner, and the others are derived through the transformation of an existing distribution defined in a greater domain. In this article, we introduce the unit gamma/Gompertz distribution, founded on the inverse-exponential scheme and the gamma/Gompertz distribution. The gamma/Gompertz distribution is known to be a very flexible three-parameter lifetime distribution, and we aim to transpose this flexibility to the unit interval. First, we check this aspect with the analytical behavior of the primary functions. It is shown that the probability density function can be increasing, decreasing, “increasing-decreasing” and “decreasing-increasing”, with pliant asymmetric properties. On the other hand, the hazard rate function has monotonically increasing, decreasing, or constant shapes. We complete the theoretical part with some propositions on stochastic ordering, moments, quantiles, and the reliability coefficient. Practically, to estimate the model parameters from unit data, the maximum likelihood method is used. We present some simulation results to evaluate this method. Two applications using real data sets, one on trade shares and the other on flood levels, demonstrate the importance of the new model when compared to other unit models.

scholarly journals Neural network-based modeling of the number of microbubbles generated with four circulation factors in cardiopulmonary bypass

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Satoshi Miyamoto ◽  
Zu Soh ◽  
Shigeyuki Okahara ◽  
Akira Furui ◽  
Taiichi Takasaki ◽  
...  
Keyword(s):  
Cardiopulmonary Bypass ◽  
Flow Rate ◽  
Neurological Complications ◽  
Estimation Accuracy ◽  
Model Parameters ◽  
Perfusion Flow ◽  
Postsurgical Complication ◽  
Tenfold Cross Validation ◽  
Suction Flow ◽  
The Relationship

AbstractThe need for the estimation of the number of microbubbles (MBs) in cardiopulmonary bypass surgery has been recognized among surgeons to avoid postoperative neurological complications. MBs that exceed the diameter of human capillaries may cause endothelial disruption as well as microvascular obstructions that block posterior capillary blood flow. In this paper, we analyzed the relationship between the number of microbubbles generated and four circulation factors, i.e., intraoperative suction flow rate, venous reservoir level, continuous blood viscosity and perfusion flow rate in cardiopulmonary bypass, and proposed a neural-networked model to estimate the number of microbubbles with the factors. Model parameters were determined in a machine-learning manner using experimental data with bovine blood as the perfusate. The estimation accuracy of the model, assessed by tenfold cross-validation, demonstrated that the number of MBs can be estimated with a determinant coefficient R2 = 0.9328 (p < 0.001). A significant increase in the residual error was found when each of four factors was excluded from the contributory variables. The study demonstrated the importance of four circulation factors in the prediction of the number of MBs and its capacity to eliminate potential postsurgical complication risks.

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