Selecting statistical models to study the relationship between soybean yield and soil physical properties

Statistical models allow the representation of data sets and the estimation and/or prediction of the behavior of a given variable through its interaction with the other variables involved in a phenomenon. Among other different statistical models, are the autoregressive state-space models (ARSS) and the linear regression models (LR), which allow the quantification of the relationships among soil-plant-atmosphere system variables. To compare the quality of the ARSS and LR models for the modeling of the relationships between soybean yield and soil physical properties, Akaike's Information Criterion, which provides a coefficient for the selection of the best model, was used in this study. The data sets were sampled in a Rhodic Acrudox soil, along a spatial transect with 84 points spaced 3 m apart. At each sampling point, soybean samples were collected for yield quantification. At the same site, soil penetration resistance was also measured and soil samples were collected to measure soil bulk density in the 0-0.10 m and 0.10-0.20 m layers. Results showed autocorrelation and a cross correlation structure of soybean yield and soil penetration resistance data. Soil bulk density data, however, were only autocorrelated in the 0-0.10 m layer and not cross correlated with soybean yield. The results showed the higher efficiency of the autoregressive space-state models in relation to the equivalent simple and multiple linear regression models using Akaike's Information Criterion. The resulting values were comparatively lower than the values obtained by the regression models, for all combinations of explanatory variables.

Predicting the growth response to thinning for Scots pine stands using individual-tree growth models

Summary

Effect of grade on disease-free survival and overall survival in FIGO stage I adenocarcinoma of the endometrium.

OBJECTIVE: To analyse the effect of differentiation on disease-free survival (DFS) and overall survival (OS) in patients with stage I adenocarcinoma of the endometrium. PATIENTS AND METHODS: From 1979 to 1995, 350 patients with FIGO stage IA-IC with well (G1), moderately (G2) or poorly (G3) differentiated tumors were treated with surgery and high dose-rate brachytherapy with or without external radiation. Median age was 65 years (39-86 years). RESULTS: The 5-year DFS was 88+/-3% for the G1 tumors, 77+/-4% for the G2 tumors, and 67+/-7% for the G3 tumors (P=0.0049). With regard to the events contributing to DFS, the 5-year cumulative percentage of local relapse was 4.6% for the G1 tumors, 9.0% for the G2 tumors, and 4.6% (P=0.027) for the G3 tumors. Cumulative percentage of metastasis was 1.4, 6.3 and 7.2% (P<0.001), respectively, whereas percentages of death were 6.0, 7.9 and 20.7% (P<0.001). The 5-year OS was 91+/-3, 83+/-4 and 76+/-7%, respectively (P=0.0018). In terms of multivariate hazard ratios (HR), the relative differences between the three differentiation groups correspond to an increase of 77% of the risk of occurrence of either of the three events considered for the DFS (HR=1.77, 95% CI [0.94-3.33]), (P=0.078) for the G2 tumors and of 163% (HR=2.63, 95% CI [1.27-5.43]), (P=0.009) for the G3 tumors with respect to the G1 tumors. The estimated relative hazards for OS are, respectively, in line with those for DFS: HR=1.51 (P=0.282) for the G2 tumors; and HR=3.37 (P=0.003) for the G3 tumors. CONCLUSION: Patients with grade 1 tumors are those least exposed to either local relapse, metastasis, or death. In contrast patients with grade 2 tumors seem to be at higher risk of metastasis, whereas patients with grade 3 tumors appear at higher risk of death. Since we have looked at the first of three competing events (local relapse, metastasis and death), this suggests that patients with grade 3 tumors probably progress to death so fast that local relapse, if any, cannot be observed.

Calibration of the century, apsim and ndicea models of decomposition and n mineralization of plant residues in the humid tropics

The aim of this study was to calibrate the CENTURY, APSIM and NDICEA simulation models for estimating decomposition and N mineralization rates of plant organic materials (Arachis pintoi, Calopogonium mucunoides, Stizolobium aterrimum, Stylosanthes guyanensis) for 360 days in the Atlantic rainforest bioma of Brazil. The models´ default settings overestimated the decomposition and N-mineralization of plant residues, underlining the fact that the models must be calibrated for use under tropical conditions. For example, the APSIM model simulated the decomposition of the Stizolobium aterrimum and Calopogonium mucunoides residues with an error rate of 37.62 and 48.23 %, respectively, by comparison with the observed data, and was the least accurate model in the absence of calibration. At the default settings, the NDICEA model produced an error rate of 10.46 and 14.46 % and the CENTURY model, 21.42 and 31.84 %, respectively, for Stizolobium aterrimum and Calopogonium mucunoides residue decomposition. After calibration, the models showed a high level of accuracy in estimating decomposition and N- mineralization, with an error rate of less than 20 %. The calibrated NDICEA model showed the highest level of accuracy, followed by the APSIM and CENTURY. All models performed poorly in the first few months of decomposition and N-mineralization, indicating the need of an additional parameter for initial microorganism growth on the residues that would take the effect of leaching due to rainfall into account.

Nuclear curvature energy in relativistic models

The difficulties arising in the calculation of the nuclear curvature energy are analyzed in detail, especially with reference to relativistic models. It is underlined that the implicit dependence on curvature of the quantal wave functions is directly accessible only in a semiclassical framework. It is shown that also in the relativistic models quantal and semiclassical calculations of the curvature energy are in good agreement.

Nonideal particle distributions from kinetic freeze-out models

In fluid dynamical models the freeze-out of particles across a three-dimensional space-time hypersurface is discussed. The calculation of final momentum distribution of emitted particles is described for freeze-out surfaces, with both spacelike and timelike normals, taking into account conservation laws across the freeze-out discontinuity.

Freeze-out in hydrodynamical models

We study the effects of strict conservation laws and the problem of negative contributions to final momentum distribution during the freeze-out through 3-dimensional hypersurfaces with spacelike normal. We study some suggested solutions for this problem, and demonstrate it in one example.

Radiation therapy duration influences overall survival in patients with cervical carcinoma.

OBJECTIVE: This article analyses the influence of treatment duration on survival in patients with invasive carcinoma of the cervix treated by radical radiation therapy. METHOD: Three hundred and sixty patients with FIGO stage IB-IIIB carcinoma of the cervix were treated in Lausanne (Switzerland) with external radiation and brachytherapy as first line therapy. Median therapy duration was 45 days. Patients were classified according to the duration of the therapies, taking 60 days (the 75th percentile) as an arbitrary cut-off. RESULTS: The 5-year survival was 61% (S.E. = 3%) for the therapy duration group of less than 60 days and 53% (S.E. = 7%) for the group of more than 60 days. In terms of univariate hazard ratio (HR), the relative difference between the two groups corresponds to a 50% increase of deaths (HR = 1.53, 95% CI = 1.03-2.28) for the longer therapy duration group (P = 0.044). In a multivariate analysis, the magnitude of estimated relative hazards for the longer therapies are confirmed though significance was reduced (HR = 1.52, 95% CI = 0.94-2.45, P = 0.084). CONCLUSION: These findings suggest that short treatment duration is a factor associated with longer survival in carcinoma of the cervix.

Classical motions from pseudoclassical spin-1/2 particle models

The classical trajectory and spin precessions of Bargmann, Michel, and Telegdi are deduced from a pseudoclassical model of a relativistic spin-(1/2) particle. The corresponding deduction from a non- relativistic model is also given.

Do habitat suitability models reliably predict the recovery areas of threatened species?

1. Identifying those areas suitable for recolonization by threatened species is essential to support efficient conservation policies. Habitat suitability models (HSM) predict species' potential distributions, but the quality of their predictions should be carefully assessed when the species-environment equilibrium assumption is violated.2. We studied the Eurasian otter Lutra lutra, whose numbers are recovering in southern Italy. To produce widely applicable results, we chose standard HSM procedures and looked for the models' capacities in predicting the suitability of a recolonization area. We used two fieldwork datasets: presence-only data, used in the Ecological Niche Factor Analyses (ENFA), and presence-absence data, used in a Generalized Linear Model (GLM). In addition to cross-validation, we independently evaluated the models with data from a recolonization event, providing presences on a previously unoccupied river.3. Three of the models successfully predicted the suitability of the recolonization area, but the GLM built with data before the recolonization disagreed with these predictions, missing the recolonized river's suitability and badly describing the otter's niche. Our results highlighted three points of relevance to modelling practices: (1) absences may prevent the models from correctly identifying areas suitable for a species spread; (2) the selection of variables may lead to randomness in the predictions; and (3) the Area Under Curve (AUC), a commonly used validation index, was not well suited to the evaluation of model quality, whereas the Boyce Index (CBI), based on presence data only, better highlighted the models' fit to the recolonization observations.4. For species with unstable spatial distributions, presence-only models may work better than presence-absence methods in making reliable predictions of suitable areas for expansion. An iterative modelling process, using new occurrences from each step of the species spread, may also help in progressively reducing errors.5. Synthesis and applications. Conservation plans depend on reliable models of the species' suitable habitats. In non-equilibrium situations, such as the case for threatened or invasive species, models could be affected negatively by the inclusion of absence data when predicting the areas of potential expansion. Presence-only methods will here provide a better basis for productive conservation management practices.

Influence of disorder strength on phase-field models of interfacial growth

We study the influence of disorder strength on the interface roughening process in a phase-field model with locally conserved dynamics. We consider two cases where the mobility coefficient multiplying the locally conserved current is either constant throughout the system (the two-sided model) or becomes zero in the phase into which the interface advances (one-sided model). In the limit of weak disorder, both models are completely equivalent and can reproduce the physical process of a fluid diffusively invading a porous media, where super-rough scaling of the interface fluctuations occurs. On the other hand, increasing disorder causes the scaling properties to change to intrinsic anomalous scaling. In the limit of strong disorder this behavior prevails for the one-sided model, whereas for the two-sided case, nucleation of domains in front of the invading front are observed.