Akaike Information Criterion Test Research Articles

Effectiveness of Genetic Parameter Estimation in a Small Flock of Merino Sheep with Shallow Pedigree

In this study, the genetic and non-genetic parameters were estimated for growth traits of Karacabey merino sheep. Growth performance data refer to 1863 lambs born between 2016 and 2018. Analyses were carried out by restricted maximum likelihood fitting animal models and disregarding or including maternal genetic or maternal permanent environmental effect. Six different animal model were fitted for all traits, and the most suitable model for each trait was chosen after Akaike information criterion test (AIC). Year of birth, age of dam, type of birth and lamb sex were significant sources of variation on birth weight (BW), average daily gain (ADG), Kleiber ratio (KR), weaning weight (WW) and six month weight (6MW). Direct heritability (h^2) for BW, ADG and 6MW were 0.12, 0.02 and 0.04, respectively, however, for KR and WW were 0.00 model 6 (which the best). The estimates of maternal heritability (m^2) for ADG, KR and WW were 0.12, 0.04 and 0.04, respectively in model 5, also maternal heritability were low for BW and 6MW. Maternal permanent environmental effects (c^2) have high contribution to the explanation growth traits and were estimated between 0.19 and 0.75 for these traits. These results showed that selecting for improved maternal and/or direct effects for Karacabey merino in the herd would generate very slow genetic improvement in growth traits.

Dose-Response of TLD-100 in the Dose Range Useful for Hypofractionated Radiotherapy.

Purpose:The aim of the study was to exploit the feasibility of thermoluminescent dosimeters (TLDs) in radiation therapy techniques in which high dose per fraction is involved.Methods:Dose–response of TLD-100 (LiF: Mg, Ti) was investigated in both 6-MV photon and 6-MeV electron beams. The element correction factor (ECF) generation method was applied to check the variability of the TLDs response. Two batches of 50 TLDs were divided into groups and exposed in the dose range 0 to 30 Gy. Regression analysis was performed with both linear and quadratic models. For each irradiation beam, the calibration curves were obtained in 3 dose range 0 to 8 Gy, 0 to 10 Gy, and 0 to 30 Gy. The best-fitting model was assessed by the Akaike Information Criterion test.Results:The ECF process resulted a useful tool to reduce the coefficients of variation from original values higher than 5% to about 3.5%, for all the batches exposed. The results confirm the linearity of dose–response curve below the dose level of 10 Gy for photon and electron beam and the supralinear trend above.Conclusion:The TLDs are suitable dosimeters for dose monitoring and verification in radiation treatment involving dose up to 30 Gy in a single fraction.

Analysis of the Behavior of Daily Maximum Rainfall within the Department of Atlántico, Colombia

In the Colombian Caribbean region, there are few studies that evaluated the behavior of one of the most commonly used variables in hydrological analyses: the maximum daily rainfall (Pmax-24h). In this study, multiannual Pmax-24h time series from 19 rain gauges, located within the department of Atlántico, were analyzed to (a) determine possible increasing/decreasing trends over time, (b) identify regions with homogeneous behavior of Pmax-24h, (c) assess whether the time series are better suited under either a stationary or non-stationary frequency analysis, (d) generate isohyetal maps under stationary, non-stationary, and mixed conditions, and (e) evaluate the isohyetal maps by means of the calculation of areal rainfall (Pareal) in nine watersheds. In spite of the presence of both increasing and decreasing trends, only the Puerto Giraldo rain gauge showed a significant decreasing trend. Also, three regions (east, central, and west) with similar Pmax-24h behavior were identified. According to the Akaike information criterion test, 79% of the rain gauges showed better fit under stationary conditions. Finally, statistical analysis revealed that, under stationary conditions, the errors in the calculation of Pareal were more frequent, while the magnitude of the errors was larger under non-stationary conditions, especially in the central–south region.

Pyrolysis characteristics and kinetic analysis of rice husk

In this work, the thermo-gravimetric and differential thermo-gravimetric curves of rice husk at different heating rates (20, 40, 60, 80 and 100 °C min−1) were obtained using a thermo-gravimetric analyzer under nitrogen atmosphere. The pyrolysis characteristics of rice husk were analyzed. The fitted Gaussian function peaks showed that the pyrolysis mass loss of rice husk can be characterized by three independent reactions. The devolatilization index D was calculated, and the effect of different experimental statuses on the pyrolysis of rice husk was discussed. The kinetic parameters of rice husk were calculated using iso-conversional models and distributed activation energy models (DAEMs). The kinetic parameters obtained by differential Friedman method and integral Ozawa method were found to be 224.85 kJ mol−1 and 220.06 kJ mol−1, respectively. The apparent activation energies for pyrolysis were not fixed value and continuously fluctuated with the increase in conversion rate. The kinetic parameters, obtained using the Kissinger method, were relatively simple and could not represent the variation trends of variables. Six different probability density functions for DAEMs were used to compute the pyrolysis kinetic parameters. The energy compensation effect existed between the activation energy and the frequency factors. It can be concluded from a comprehensive F test and the amount criterion test (Akaike information criterion test) that the Weibull model is more appropriate to study the pyrolysis of rice husk. Finally, the apparent activation energy, calculated using the Weibull model, was calculated to be 131.97 kJ mol−1, whereas the reaction order was 3.2.

Crossover from plasmonic analogue of Fano resonance to Autler–Townes splitting in a double guide mode resonances system

The plasmonic analogy from Fano resonance to Autler–Townes splitting (ATS) in mid-infrared spectral range is observed assisted by a dual parallel graphene-coated grating structure. The analytical derivation exhibits a height-dependent resonance which is crucial for discerning Fano resonance from ATS. The mechanism of generating a transparency window seeks a trade-off between Fano resonance and ATS at threshold height. While within the critical height, Fano resonance dominates. The Akaike Information Criterion test is used to discern these two effects quantitatively. Moreover, the device pronounces a good tunability accompanied with a slowing light application. Our ideas open up a new insight view of designing or constructing highly integrated, multi-functional graphene-based metamaterials in nanoscale.

New Approach for Managing Pavement Friction and Reducing Road Crashes

Evaluation of crash count data as a function of roadway characteristics allows departments of transportation (DOTs) to predict expected average crash risks to assist in identifying segments that could benefit from various treatments. Crash risk is modeled using negative binomial regression, as a function of annual average daily traffic (AADT) and other variables. For this paper, a crash study was carried out for the Interstate, primary, and secondary routes in the Salem District of Virginia. The data used in the study included the following information obtained from Virginia DOT records: 2010 to 2012 crash data, 2010 to 2012 AADT, and horizontal radius of curvature. In addition, tire–pavement friction, or skid resistance, was measured with a continuous friction measurement, fixed-slip device called a GripTester. Negative binomial regression was used to relate the crash data to the AADT, skid resistance, and horizontal radius of curvature. To determine which of the variables to include in the final models, researchers performed the Akaike information criterion test. By mathematically combining the information acquired from the negative binomial regression models and the information contained in the crash counts, researchers empirically estimated the parameters of each network’s true average crash risks with the empirical Bayes approach. The new estimated average crash risks were then used to rank segments according to their empirically estimated crash risk and to prioritize segments according to their expected crash reduction if a friction treatment were applied.

Double point source W-phase inversion: Real-time implementation and automated model selection

Rapid and accurate characterization of an earthquake source is an extremely important and ever evolving field of research. Within this field, source inversion of the W-phase has recently been shown to be an effective technique, which can be efficiently implemented in real-time. An extension to the W-phase source inversion is presented in which two point sources are derived to better characterize complex earthquakes. A single source inversion followed by a double point source inversion with centroid locations fixed at the single source solution location can be efficiently run as part of earthquake monitoring network operational procedures. In order to determine the most appropriate solution, i.e., whether an earthquake is most appropriately described by a single source or a double source, an Akaike information criterion (AIC) test is performed. Analyses of all earthquakes of magnitude 7.5 and greater occurring since January 2000 were performed with extended analyses of the September 29, 2009 magnitude 8.1 Samoa earthquake and the April 19, 2014 magnitude 7.5 Papua New Guinea earthquake. The AIC test is shown to be able to accurately select the most appropriate model and the selected W-phase inversion is shown to yield reliable solutions that match published analyses of the same events.

A critical assessment of the use of a surface reaction rate equation to correlate biosorption kinetics

A critical assessment of the use of a variable-order, power-law type surface reaction rate equation to correlate biosorption kinetics is presented. The general nth order rate equation with three adjustable parameters was fit to the kinetic data of lead uptake by inactivated cells of Rhodotorula glutinis using a genetic algorithm search method. The uptake process was fast, with apparent equilibrium reached in approximately 30 min. According to the Akaike information criterion test, the three-parameter nth order equation was superior to the much used pseudo second order equation with two fitting parameters. However, the strong fit of the former equation resulted in unrealistic parameter estimates. Parametric sensitivity analysis indicated that the available kinetic data with only limited information content did not allow simultaneous identification of three unknown parameters. As a result, the three-parameter nth order equation was found to be overparameterized with highly correlated parameters. It was, however, possible to retrieve meaningful parameter estimates from the kinetic data when the number of fitting parameters was reduced from 3 to 2.

A geographically and temporally weighted autoregressive model with application to housing prices

Spatiotemporal autocorrelation and nonstationarity are two important issues in the modeling of geographical data. Built upon the geographically weighted regression (GWR) model and the geographically and temporally weighted regression (GTWR) model, this article develops a geographically and temporally weighted autoregressive model (GTWAR) to account for both nonstationary and auto-correlated effects simultaneously and formulates a two-stage least squares framework to estimate this model. Compared with the maximum likelihood estimation method, the proposed algorithm that does not require a prespecified distribution can effectively reduce the computation complexity. To demonstrate the efficacy of our model and algorithm, a case study on housing prices in the city of Shenzhen, China, from year 2004 to 2008 is carried out. The results demonstrate that there are substantial benefits in modeling both spatiotemporal nonstationarity and autocorrelation effects simultaneously on housing prices in terms of R2 and Akaike Information Criterion (AIC). The proposed model reduces the absolute errors by 31.8% and 67.7% relative to the GTWR and GWR models, respectively, in the Shenzhen data set. Moreover, the GTWAR model improves the goodness-of-fit of the ordinary least squares model and the GTWR model from 0.617 and 0.875 to 0.914 in terms of R2. The AIC test corroborates that the improvements made by GTWAR over the GWR and the GTWR models are statistically significant.

Rural wind farm development: Social, environmental and economic features important to local residents

The research problem was to examine residents' perceptions of personal costs and benefits in terms of social, environmental or economic features that influence support of or resistance to wind farm development in four rural communities in eastern Michigan. Data were collected from residents using a mail questionnaire, which included twenty-one Likert-style questions inquiring about perceived impact statements of wind farm development in the community. The analysis indicated that there were both differences and similarities in the perception of wind farm impacts on the rural communities. More specifically, the results of the Akaike information criterion test indicated that there was substantial support for nine of the twenty-one variables in support of wind farm development. The contribution of this study recognizes the importance of noneconomic perspectives of wind farm development where turbine construction had not yet been fully exploited. In particular, the data lend support for the use of Social Exchange Theory and further exploration of its applicability in renewable energy investigations.

Novel Population Pharmacokinetic Modeling of Arabinosyl Cytosine Triphosphate: Insights On Potential Preferential Formation of Ara-CTP Directly From Elacytarabine As Well As From Ara-C

AbstractAbstract 3547 Objectives:Elacytarabine (CP-4055) is an elaidic acid ester of arabinosyl cytosine (Ara-C), administered as a liposomal formulation, that is being developed to treat hematologic malignancies. CP-4055 is metabolized to Ara-C, which is transformed intracellularly to active arabinosyl cytosine triphosphate (Ara-CTP) and inactive deaminated metabolite arabinosyl uracil (Ara-U). The present analysis aimed to elucidate the pharmacokinetics (PK) of Ara-CTP and identify its relationship with CP-4055, Ara-C, Ara-U and various blood parameters measured in the target patient population. Methods:Patients suffering from hematologic malignancies, including refractory/relapsing acute myeloid leukemia (AML), who participated in Phase I or II CP-4055 trials, were included in this analysis. CP-4055 monotherapy was given as an intravenous infusion over 2 h/day for 5 days, 4 h/day for 5 days or continuously over 120 hours at doses ranging from 200 to 2500 mg/m2/day. Blood samples were collected at various time-points (until 168 hours post-dose) and plasma was assayed for CP-4055, Ara-C, and Ara-U using a validated LC-MS/MS method. Ara-CTP was measured by HPLC in isolated leukemic blast cells from AML patients. Cholesterol levels were also measured. Population PK analyses were conducted using the iterative two-stage method in ADAPT 5®. First, a model was determined for cholesterol, which was incorporated into a PK model for CP-4055, Ara-C and Ara-U. Individual PK parameters from this model were fixed and then used for the analysis of Ara-CTP. For Ara-CTP modeling, 1-compartment (cpt) models were tested with various routes of formation. For all models, model discrimination was performed using standard criteria (residual variability, quality of fit graphs, Akaike information criterion test). Results:In the cholesterol analysis, 13 patients (57 concentrations) were included while 43 patients (around 27 concentrations per patient) were included in the modeling of CP-4055, Ara-C and Ara-U. A subset of 17 patients (46 concentrations) was part of the Ara-CTP analysis. Cholesterol was described by an indirect model with a rate of elimination and a rate of formation that was increased by phospholipids infused along with CP-4055. CP-4055 PK was best described by a 2-cpt model, where the central cpt was partitioned into 2 sub-cpts. The first sub-cpt represented a lipid depot cpt where liposomal-bound CP-4055 was infused, and which transferred CP-4055 into the other sub-cpt, which represented CP-4055 released from liposomes. The transfer of CP-4055 from the liposomes was unidirectional and saturable, and cholesterol level influenced the size of the second sub-cpt. Ara-CTP appeared to be formed from unbound CP-4055, presumably within cancer cells, and was also formed as expected from Ara-C which was best described by a 2-cpt model, while Ara-U followed a 1-cpt model with an elimination that was dependent upon creatinine clearance. The proposed model is depicted below. [Display omitted] Based on the model, terminal elimination half-life values for CP-4055, Ara-C, Ara-U and Ara-CTP were around 9, 68, 5 and 3 hours, respectively, and were independent of dose and infusion time. Residual variabilities for cholesterol, CP-4055, Ara-C, Ara-U and Ara-CTP were 21.0%, 34.0%, 39.4%, 12.5% and 29.2%, respectively. Conclusions:For the first time, a population PK approach was used to describe the PK of a triphosphate metabolite in relation to a parent drug as well as other metabolites. Indeed, the novel multi-cpt model developed herein simultaneously described and explained the PK of cholesterol, elacytarabine, Ara-C, Ara-U and Ara-CTP. The inclusion of cholesterol levels in the model improved the overall quality of fit, especially for administered liposomal-elacytarabine. The proposed PK model describing Ara-CTP disposition suggests that Ara-CTP is formed not only from Ara-C but also from elacytarabine, presumably within cancer cells, although the exact mechanism is unknown. Disclosures:Seng Yue:Learn and Confirm: Employment; Clavis Pharma: Consultancy. Gandhi:Clavis Pharma: Research Funding. O'Brien:Clavis Pharma: Research Funding. Ravandi:Clavis Pharma: Research Funding. Jacobsen:Clavis Pharma: Employment, Equity Ownership. Dirven:Clavis Pharma: Employment. Hagen:Clavis Pharma: Employment, Equity Ownership. Hals:Clavis Pharma: Employment. Ducharme:Learn and Confirm: Employment, Equity Ownership; Clavis Pharma: Consultancy.

Modelling of Annual Stream Flows by Autoregressive Models

The main aim of the present study was to develop a autoregressive model for annual streamflow of Godavari river. Autoregressive models of order 1,2.3.4 and 5 were tried. AR (I) model was found suitable based on Box- Pierce Portmonteau test and Akaike Information Criterion test. The mean and skewness of generated series were found close to historical values. The mean forecast error. mean relative error and integral square error indicates a high degree of model fitness to the observed data series.

Diagnosis of enzyme inhibition based on the degree of inhibition.

In this work, a method for the diagnosis of kinetic inhibition, based on the dependence of the degree of inhibition (epsilon(i)) on the inhibitor concentration [I] and on the substrate concentration [S], is presented. Because the degree of inhibition is a ratio between rates, kinetic data are normalized by the introduction of an internal control-the rate of the uninhibited reaction. Therefore, the error associated with the kinetic measurements decreases and less experimental measurements are necessary to achieve the diagnosis. The process described, which uses graphical and/or non-linear fitting procedures, allows distinguishing between 20 different kinds of inhibition, including not only linear and hyperbolic, but also parabolic and rational 2,2 inhibitions. Rational 2,2 indicates a new type of inhibition corresponding to an incomplete parabolic inhibition, i.e. mechanistically it corresponds to an inhibitor that binds to two inhibition sites producing enzymatic complexes that are still active. In spite of its comprehensiveness, the diagnosis process is greatly facilitated by the division of the diagnosis of the inhibition in a step-by-step procedure, where only two rival models are evaluated in each step. In the non-linear fittings, the choice between rival models uses a test based on information statistics theory, the Akaike information criterion test, in order to penalize complex models that tend to be favoured in fittings. Finally, equations that allow the determination of inhibition kinetic constants were also deduced. The formalism presented was tested by examining inhibition of acid phosphatase by phosphate (a linear competitive inhibitor).

A population pharmacokinetic model for vancomycin in pediatric patients and its predictive value in a naive population.

The objectives of this study were to (i) construct a population pharmacokinetic (PK) model able to describe vancomycin (VAN) concentrations in serum in pediatric patients, (ii) determine VAN PK parameters in this population, and (iii) validate the predictive ability of this model in a naive pediatric population. Data used in this study were obtained from 78 pediatric patients (under 18 years old). PK analyses were performed using compartmental methods. The most appropriate model was chosen based on the evaluation of pertinent graphics and calculation of the Akaike information criterion test. The population PK analysis was performed using an iterative two-stage method. A two-compartment PK model using age, sex, weight, and serum creatinine as covariates was determined to be the most appropriate one to describe serum VAN concentrations. The quality of fit was very good, and the distribution of weighted residuals was found to be homoscedastic (Wilcoxon signed rank test). Fitted population PK parameters (mean +/- standard deviation) were as follows: central clearance (0.1 +/- 0.05 liter/h/kg), central volume of distribution (0.27 +/- 0.07 liter/kg), peripheral volume of distribution (0.16 +/- 0.07 liter/kg), and distributional clearance (0.16 +/- 0.07 liter/kg). The predictive ability of the developed model (including the above-mentioned covariates) was evaluated in a naive population of 19 pediatric patients. The predictability was very good. Precision (+/-95% confidence interval [CI]) (peak, 4.1 [+/-1.4], and trough, 2.2 [+/-0.7]) and bias (+/-95% CI) (peak, -0.58 [+/-2.2], and trough, 0.63 [+/-1.1] mg/liter) were significantly (P < 0.05) superior to those obtained using a conventional method (precision [+/-95% CI]: peak, 8.03 [+/-2. 46], and trough, 2.7 [+/-0.74]; bias: peak, -7.1 [+/-2.9], and trough, -1.35 [+/-1.2] mg/liter). We propose the use of this population PK model to optimize VAN clinical therapies in our institution and others with similar patient population characteristics.he object

Species Scaling of Propafenone Disposition and Concentration–Time Relationships among Eight Mammalian Species

Usually, smaller mammals have higher clearances per unit body mass than do larger mammalian species.When clearance and other pharmacokinetic parameters are correlated with internal physiological processes, species tend to dispose of drugs at a similar pace.The first application of this concept is pharmacokinetic time, expressed with different units: Kaliynochron, Apolysichron, Dienetichron, and Syndesi- chron.The present work describes pharmacokinetic time in these units from data obtained with propafenone in eight animal species: mouse, rat, rabbit, dog, sheep, human, cow, and horse.Additionally, volume of distribution (Vdss = 6.5B0 94) and clearance (CL = 0.17B086) were correlated to body weight (B). Different units of pharmacokinetic time were evaluated with an Akaike Information Criterion test, and the Syndesichron was the unit that provided the best superimposition for the concentration-time plot for all animal species.It can be inferred that all mammalian species eliminated half of the dose from their bodies in 4759 Syndesichrons.

EZ-FIT: A practical curve-fitting microcomputer program for the analysis of enzyme kinetic data on IBM-PC compatible computers

EZ-FIT, an interactive microcomputer software package, has been developed for the analysis of enzyme kinetic and equilibrium binding data. EZ-FIT was designed as a user-friendly menudriven package that has the facility for data entry, editing, and filing. Data input permits the conversion of cpm, dpm, or optical density to molar per minute per milligram protein. Data can be fit to any of 14 model equations including Michaelis-Menten, Hill, isoenzyme, inhibition, dual substrate, agonist, antagonist, and modified integrated Michaelis-Menten. The program uses the Nelder-Mead simplex and Marquardt nonlinear regression algorithms sequentially. A report of the results includes the parameter estimates with standard errors, a Student t test to determine the accuracy of the parameter values, a Runs statistic test of the residuals, identification of outlying data, an Akaike information criterion test for goodness-of-fit, and, when the experimental variance is included, a χ 2 statistic test for goodness-of-fit. Several different graphs can be displayed: an X- Y, a Scatchard, an Eadie-Hofstee, a Lineweaver-Burk, a semilograithmic, and a residual plot. A data analysis report and graphs are designed to evaluate the goodness-of-fit of the data to a particular model.

Technological change and economies of scale in Canadian financial institutions: A selection from competing hypotheses

This study isolates economies of scale from technological change in Canadian financial institutions. By employing the most general translog cost function and by using a sequential Akaike's information criterion test, we select the most appropriate model from 127 possible hypotheses. The results suggest that there exist increasing returns to scale and that technological change is not Hicks-neutral. In fact, technological change has resulted in greater relative expenditures on physical capital. These results suggest that further integration, centralization, and sharing of technology would be benificial in the Canadian financial industry.