Rn Models Research Articles

3D finite element analysis of stress distribution on the shape of resected root-end or with/without bone graft of a maxillary premolar during endodontic microsurgery

Background/purposeApical root resection pattern affects the stress distribution behavior in the apical region of the resected tooth. The purpose of the study was to compare the biomechanical responses of resected teeth between endodontic microsurgery (horizontal resection) and targeted endodontic microsurgery (round resection). Materials and methodsFive different models were developed. The basic model without resection (NR) was regarded as the control model, and the others involved: horizontal resection without bone grafting (HN), horizontal resection with bone grafting (HG), round resection without bone grafting (RN), and round resection with bone grafting (RG) models. A static load of 100 N was applied to the buccal and palatal cusps of all the teeth in a 30° oblique direction. The maximum von-Mises stress and tooth displacement values were analyzed and compared. ResultsBoth the HN and RN models exhibited lower stress distribution values on bone compared with the NR (control) model. Regarding maximum stress distribution at the root apex, the stress value of the RN model was slightly higher compared to the HN model, whereas the RG model displayed a slightly lower stress value in comparison with the HG model. For maximum tooth displacement value, there were no significant differences between the HN and RN models, as well as the HG and RG models. ConclusionThe round resection pattern had comparable stress distribution behaviors at the root apex and tooth displacement values with the horizontal resection pattern. Targeted endodontic microsurgery might provide better biomechanical response of the resected tooth after root-end resection.

Assessment of three models for estimating daily net radiation in southern Africa

Accurate quantification of net radiation flux (Rn) is of paramount importance for the estimation of reference evapotranspiration (ET0) rate, which is used to estimate crop water use. A widely recommended Penman-Monteith procedure outlined in the Food and Agriculture Organization (FAO) Irrigation and Drainage Paper No. 56 for estimation of Rn (FAO56- Rn) is often used to estimate Rn. However, the FAO56- Rn model is data-intensive and also requires site-specific calibrations of coefficients to attain a high level of accuracy of Rn estimates. These coefficients are often used without site-specific calibrations as a result of' the lack of large and representative radiative flux measurements in data-scarce regions such as southern Africa and Rn estimates are therefore considered questionable. Assessment of different models in-situ measurements of Rn is critical to identify an alternative approach that could be used for accurate estimation of Rn with minimal data input and without any site-specific calibrations in this region. In this study, two new Rn models, which differ only in the procedures used to compute atmospheric emissivity were proposed. The first model requires measurements of solar irradiance (Rs) maximum and minimum air temperatures (Tair min and Tair max) while the second model requires additional measurements of relative humidity (RHmin and RHmax) for estimation of the actual vapour pressure (eair). Two new Rn models and a widely recommended FAO56- Rn model were evaluated using daily Rn measurements acquired from five sites which represent different climatic and land cover conditions of southern Africa. The results showed that the first model performed better than all the evaluated models at four sites, with regression coefficient (r2) values greater than 0.90 and index of agreement ( d) values greater than 0.97. These findings suggest that the first model presented here is the most promising and suitable to estimate Rn with minimum input data in southern Africa without any site-specific calibrations. The findings of this study can be used to inform the decision on selecting a model to be used for reliable estimates of Rn for improved estimation of crop water requirement in climatic conditions similar to this region.

Evaluation of Some Net Radiation Models for Improving Daily Reference Evapotranspiration Estimation in Iran

AbstractNet radiation (Rn) is one of the effective inputs for controlling soil heat flux, thermal convection, moisture flux exchange, and reference crop evapotranspiration (ET0) rate. In this research, the accuracy of some empirical and semiempirical Rn models is examined for different climates of Iran versus the recommended net radiation model as proposed in the Penman–Monteith Food and Agricultural Organization of the United Nations 56 standard (FAO 56) model for the period 1980–2007. For estimating daily net radiation, various net radiation models [Wright, basic regression model (BRM), Linacre, Berliand, Irmak, and Monteith] were examined. Model evaluations were implemented for four climate types. On regional averages, the linear BRM had the superior performance in generating the most accurate daily ET0. Results showed that for 70% of the study sites, the linear Rn models can be reliable candidates instead of sophisticated nonlinear Rn models, which are proposed in the reference FAO 56 model. For some ...

An Exploration of Context and the Use of Evidence‐Based Nonpharmacological Practices in Emergency Departments

The uptake of evidence in practice remains a challenge for healthcare professionals including nurses and providers. Increased use of evidence-based practices (EBPs) in healthcare settings may improve patient conditions such as pain and decrease the cost of health care. The relationship between context in the practice environment and uptake of EBP remains an understudied area. This study explored the relationships of context including the elements of individual, unit, and hospital and the use of evidence-based nonpharmacological pediatric pain management practices (EBNPPs) using an existing data set of RNs and providers, defined as doctors of medicine and osteopathy, nurse practitioners, and physician assistants caring for children in the emergency department. A secondary data analysis was conducted using correlation and regression. Initial analysis identified several significant positive correlations with individual, unit, and hospital context elements and EBNPP. A significant correlation was not found between evaluation and EBNPP and magnet status and EBNPP for RNs or providers. RN regression analyses found that knowledge and continuing education were significant predictors of EBNPP. Overall context was a significant predictor of EBNPP for both the RN and provider models. A pooled regression analysis with RNs and providers found that RNs had a significant increased use of EBNPP when compared to providers. Regression analyses found that overall context significantly predicted the use of EBPPM for RNs and providers although no one element-individual, unit, or hospital-was identified as more important. The effect of context on EBNPP did not differ by profession in this sample. Future research should focus on the overall influence of context on EBP and consider other factors that may play a role in the uptake of EBP.

Evaluating the Impact of Daily Net Radiation Models on Grass and Alfalfa-Reference Evapotranspiration Using the Penman-Monteith Equation in a Subhumid and Semiarid Climate

Net radiation Rn is the main driving force of evapotranspiration ET and is a key input variable to the Penman-type combination and energy balance equations. However, Rn is not commonly measured. This paper analyzes the impact of 19 net radiation models that differ in model structure and intricacy on estimated grass and alfalfa-reference ET ETo and ETr, respectively and investi- gates how climate, season and cloud cover influence the impact of the Rn models on ETo and ETr. Datasets from two locations Clay Center, Nebraska, subhumid; and Davis, California, a Mediterranean-type semiarid climate were used. Rn values computed from the 19 models were used in the standardized ASCE-EWRI Penman-Monteith equation to estimate ETo and ETr on a daily time step. The influence of seasons on the estimation of Rn and on estimated ETo and ETr was investigated in winter November-March and summer May-September months. To analyze the influence of clouds on the impact of Rn models, relative shortwave radiation Rrs was used as a means to express the cloudiness of the days as: 0 Rrs0.35 for completely cloudy days; 0.35 Rrs0.70 for partially cloudy days; and 0.70 Rrs1.0 for clear sky days. The performances of Rn models showed variations at the same location and between the locations for the same model based on methods used to calculate various model parameters. The most significant impact of Rn on estimated ETo and ETr was related to the methods used to calculate atmospheric emissivity rather than methods used to calculate clear sky solar radiation Rso or cloud adjustment factor f. Rn models that used average air temperature to compute and an estimated f resulted in good performances at both locations. Empirical models that assumed f=1.0 showed poor to average performances at both locations. While model performances varied based on methods used to calculate Rso, f, and , there were significant seasonal variations in performances of models that calculated as a function of actual vapor pressure of the air ea. The seasonal variations in performances of these models were greater under subhumid climate at Clay Center than in semiarid climate at Davis, Calif. The models that calculated as a function of ea performed better under completely cloudy days than on other days, more so at Clay Center. Methods used to calculate have a significant impact on the Rn model performance, especially in unstable climatic conditions such as at Clay Center where there are frequent and rapid changes in climatic variables in a given day and throughout the year. The results of this study can be used as a reference tool to provide practical information on which method to select based on the data availability for reliable estimates of daily Rn relative to the ASCE-EWRI Rn method in subhumid and semiarid climates similar to Clay Center, Neb. and Davis, Calif.

Net Radiation Dynamics: Performance of 20 Daily Net Radiation Models as Related to Model Structure and Intricacy in Two Climates

We compared daily net radiation (Rn) estimates from 19 methods with the ASCE-EWRI Rn estimates in two climates: Clay Center, Nebraska (sub-humid) and Davis, California (semi-arid) for the calendar year. The performances of all 20 methods, including the ASCE-EWRI Rn method, were then evaluated against Rn data measured over a non-stressed maize canopy during two growing seasons in 2005 and 2006 at Clay Center. Methods differ in terms of inputs, structure, and equation intricacy. Most methods differ in estimating the cloudiness factor, emissivity (e), and calculating net longwave radiation (Rnl). All methods use albedo (a) of 0.23 for a reference grass/alfalfa surface. When comparing the performance of all 20 Rn methods with measured Rn, we hypothesized that the a values for grass/alfalfa and non-stressed maize canopy were similar enough to only cause minor differences in Rn and grass- and alfalfa-reference evapotranspiration (ETo and ETr) estimates. The measured seasonal average a for the maize canopy was 0.19 in both years. Using a = 0.19 instead of a = 0.23 resulted in 6% overestimation of Rn. Using a = 0.19 instead of a = 0.23 for ETo and ETr estimations, the 6% difference in Rn translated to only 4% and 3% differences in ETo and ETr, respectively, supporting the validity of our hypothesis. Most methods had good correlations with the ASCE-EWRI Rn (r2 > 0.95). The root mean square difference (RMSD) was less than 2 MJ m-2 d-1 between 12 methods and the ASCE-EWRI Rn at Clay Center and between 14 methods and the ASCE-EWRI Rn at Davis. The performance of some methods showed variations between the two climates. In general, r2 values were higher for the semi-arid climate than for the sub-humid climate. Methods that use dynamic e as a function of mean air temperature performed better in both climates than those that calculate e using actual vapor pressure. The ASCE-EWRI-estimated Rn values had one of the best agreements with the measured Rn (r2 = 0.93, RMSD = 1.44 MJ m-2 d-1), and estimates were within 7% of the measured Rn. The Rn estimates from six methods, including the ASCE-EWRI, were not significantly different from measured Rn. Most methods underestimated measured Rn by 6% to 23%. Some of the differences between measured and estimated Rn were attributed to the poor estimation of Rnl. We conducted sensitivity analyses to evaluate the effect of Rnl on Rn, ETo, and ETr. The Rnl effect on Rn was linear and strong, but its effect on ETo and ETr was subsidiary. Results suggest that the Rn data measured over green vegetation (e.g., irrigated maize canopy) can be an alternative Rn data source for ET estimations when measured Rn data over the reference surface are not available. In the absence of measured Rn, another alternative would be using one of the Rn models that we analyzed when all the input variables are not available to solve the ASCE-EWRI Rn equation. Our results can be used to provide practical information on which method to select based on data availability for reliable estimates of daily Rn in climates similar to Clay Center and Davis.

POWER-LAWS f(R) THEORIES ARE COSMOLOGICALLY UNACCEPTABLE

In a recent paper,1 we have shown that f(R) = R + μRn modified gravity dark energy models are not cosmologically viable because during the matter era that precedes the accelerated stage the cosmic expansion is given by a ~ t1/2 rather than a ~ t2/3, where a is a scale factor and t is the cosmic time. A recent work by Capozziello et al.2 criticized our results presenting some apparent counter-examples to our claim in f(R) = μRn models. We show here that those particular Rn models can produce an expansion as a ~ t2/3 but this does not connect to a late-time acceleration. Hence, though acceptable f(R) dark energy models might exist, the Rn models presented in Capozziello et al. are not cosmologically viable, confirming our previous results in Ref. 1.

Subgeometric ergodicity of strong Markov processes

We derive sufficient conditions for subgeometric f-ergodicity of strongly Markovian processes. We first propose a criterion based on modulated moment of some delayed return-time to a petite set. We then formulate a criterion for polynomial f-ergodicity in terms of a drift condition on the generator. Applications to specific processes are considered, including Langevin tempered diffusions on ℝn and storage models.

Kinetics of the thermal decomposition of [Co(NH3)6]2(C2O4)3·4H2O

The thermal decomposition of [Co(NH3)6]2(C2O4)3·4H2O was studied under isothermal conditions in flowing air and argon. Dissociation of the above complex occurs in three stages. The kinetics of the particular stages thermal decomposition have been evaluated. The RN and/or AM models were selected as those best fitting the experimental TG curves. The activation energies,E, and lnA were calculated with a conventional procedure and by a new method suggested by Kogaet al. [10, 11]. Comparison of the results have showed that the Arrhenius parameters values estimated by the use of both methods are very close. The calculated activation energies were in air: 96 kJ mol−1 (R1.575, stage I); 101 kJ mol−1 (Ain1.725 stage II); 185 kJ mol−1 (A 2.9, stage III) and in argon: 66 kJ mol−1 (A 1.25, stage I); 87 kJ mol−1 (A 1.825, stage II); 133 kJ mol−1 (A 2.525, stage III).