The distinct problems of physical inconsistency and of multivariate bias potentially involved in the statistical adjustment of climate simulations

Bias adjustment of numerical climate model simulations involves several technical and epistemological arguments wherein the notion of physical inconsistency is often referred to, either for rejecting the legitimacy of bias adjustment in general or for justifying the necessity of sophisticated multivariate techniques. However, this notion is often mishandled, in part because the literature generally proceeds without defining it. In this context, the central objective of this study is to clarify and illustrate the distinction between physical inconsistency and multivariate bias, by investigating the effect of bias adjustment on two different kinds of inter-variable relationships, namely a physical constraint expected to hold at every step of a time series and statistical properties that emerge with potential bias over a climatic time scale. The study involves the application of 18 alternative bias adjustment techniques on 10 climate simulations and over 12 sites across North America. Adjusted variables are temperature, pressure, relative humidity and specific humidity, linked by a thermodynamic constraint. The analysis suggests on the one hand that a clear instance of potential physical inconsistency can be avoided with either a univariate or a multivariate technique, if and only if the bias adjustment strategy explicitly considers the physical constraint to be preserved. On the other hand, it also suggests that sophisticated multivariate techniques alone aren’t complete adjustment strategies in presence of a physical constraint, as they cannot replace its explicit consideration. As a supplementary objective, this study relates common optional adjustment procedures with likely effects on diverse basic statistical properties, as an effort to guide climate information users in the determination of adequate bias adjustment strategies for their research purposes.

Physical Constraint in Pediatric Dentistry: The Lived Experience of Parents

Background: The use of physical constraint in pediatric dentistry is highly controversial. Papoose boards in particular, which envelop and immobilize children during treatment procedures, have been described as barbaric devices even though their goal is to protect the patient. In this debate, the voice of parents is important but still missing in the scientific literature. Aim: To understand how parents or caregivers experienced physical constraint and the use of the papoose board on their children during regular dental treatment. Design: We conducted qualitative research rooted in interpretive phenomenology. Accordingly, we performed in-depth individual interviews with a purposive sample of 7 parents or caregivers. The interviews took place in Montréal, Canada, after the children had been treated with a papoose board for nonemergency dental treatments. The discussions were audio recorded, transcribed, and thematically analyzed. Results: Two perspectives emerged among participants. Some explained that the papoose board calmed their children, helped the dentist to complete the procedures, and made their experience less stressful. For others, the papoose board was a horrible and traumatizing experience, leading to feelings of guilt toward their children. They expressed anger toward the dentists for not allowing them enough time to decide and for imposing use of the device. Conclusion Our study raises serious ethical concerns about this practice. We believe that using a papoose board should remain an extraordinary measure and, more generally, that dental professionals should reflect on the place of children and their families in clinical encounters. Knowledge Transfer Statement: The findings of this study should encourage policy makers, dental professionals and ethicists to consider the following points: 1) the traumatizing experiences described by parents raise serious ethical concerns about the use of papoose boards; 2) the dental profession should reflect on the place of children and their families in the clinical encounter and grapple with the importance of consent and how to ensure consent in encounters involving children and their parents.

Study on the spectral characteristics and analytical performance of pulverized coal using laser-induced breakdown spectroscopy under a fast physical constraint

Using a new sample preparation device to improve the online analysis capability of LIBS for pulverized coal.

A constraint-based optimization technique for estimating physical parameters of Jiles – Atherton hysteresis model

Purpose Improperly fitted parameters for the Jiles–Atherton (JA) hysteresis model can lead to non-physical hysteresis loops when ferromagnetic materials are simulated. This can be remedied by including a proper physical constraint in the parameter-fitting optimization algorithm. This paper aims to implement the constraint in the meta-heuristic simulated annealing (SA) optimization and Nelder–Mead simplex (NMS) algorithms to find JA model parameters that yield a physical hysteresis loop. The quasi-static B(H)-characteristics of a non-oriented (NO) silicon steel sheet are simulated, using existing measurements from a single sheet tester. Hysteresis loops received from the JA model under modified logistic function and piecewise cubic spline fitted to the average M(H) curve are compared against the measured minor and major hysteresis loops. Design/methodology/approach A physical constraint takes into account the anhysteretic susceptibility at the origin. This helps in the optimization decision-making, whether to accept or reject randomly generated parameters at a given iteration step. A combination of global and local heuristic optimization methods is used to determine the parameters of the JA hysteresis model. First, the SA method is applied and after that the NMS method is used in the process. Findings The implementation of a physical constraint improves the robustness of the parameter fitting and leads to more physical hysteresis loops. Modeling the anhysteretic magnetization by a spline fitted to the average of a measured major hysteresis loop provides a significantly better fit with the data than using analytical functions for the purpose. The results show that a modified logistic function can be considered a suitable anhysteretic (analytical) function for the NO silicon steel used in this paper. At high magnitude excitations, the average M(H) curve yields the proper fitting with the measured hysteresis loop. However, the parameters valid for the major hysteresis loop do not produce proper fitting for minor hysteresis loops. Originality/value The physical constraint is added in the SA and NMS optimization algorithms. The optimization algorithms are taken from the GNU Scientific Library, which is available from the GNU project. The methods described in this paper can be applied to estimate the physical parameters of the JA hysteresis model, particularly for the unidirectional alternating B(H) characteristics of NO silicon steel.

Three-Dimensional Modeling of Mineral/Elemental Compositions for Shale Reservoirs

Summary Mineral compositional analysis of rocks is important for developing shale resources because the relationships between mineral compositions and petrophysical properties are critical for resource evaluation and completion optimization. Elementary properties are now routinely analyzed at wells in evaluating shale reservoirs. However, these properties have not been modeled in the three-dimensional (3D) reservoir. This is because an elemental composition has a physical constraint that is relatively easily adhered to in data analysis for wells but not in 3D modeling of reservoirs. A critical condition of elemental composition is that the sum of its components is equal to 100% to honor the mass-preservation principle. Traditional modeling methods do not satisfy this physical condition, sometimes producing nonphysical values, such as negative porosity values and fluid-saturation values greater than 100%. To date, only the compositional-modeling methods using a log-ratio transform can consistently satisfy this physical constraint. This paper presents modeling methods using additive log-ratio transform for modeling mineral compositions.