Ooid growth: Uniqueness of time-invariant, smooth shapes in 2D

Evolution of planar curves under a nonlocal geometric equation is investigated. It models the simultaneous contraction and growth of carbonate particles called ooids in geosciences. Using classical ODE results and a bijective mapping, we demonstrate that the steady parameters associated with the physical environment determine a unique, time-invariant, compact shape among smooth, convex curves embedded in ℝ2. It is also revealed that any time-invariant solution possesses D2 symmetry. The model predictions remarkably agree with ooid shapes observed in nature.

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How the development of executive function influences our moment-by-moment interactions with the real-world environment

10.31234/osf.io/p2qb8 ◽

2021 ◽

Author(s):

Sam Wass

Keyword(s):

Executive Function ◽

Physical Environment ◽

Different Types ◽

The Face ◽

Social And Physical Environment ◽

New Research ◽

Mental Constructs ◽

Time Invariant ◽

Invariant Properties ◽

World Environment

Historically, the study of executive function (EF) development has relied on using experimental paradigms to assess EFs as abstract, time-invariant properties of individual brains. Here, we discuss new research that moves away from studying EFs purely as internal mental constructs, towards an approach that aims to understand how EFs are expressed through the inter-relationship between an individual’s brain and the world around them. We offer three illustrative examples of this approach. The first looks at how we learn to make predictions and anticipations based on different types of regularity in our early social and physical environment. The second looks at how we learn to correct, moment-by-moment, for changes in the outside world to maintain stability in the face of change. The third looks at how we allocate our attention on a moment-by-moment basis, in naturalistic settings. We discuss potential new therapeutic avenues for improving EFs arising from this research.

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On the Role of Equilibrium Reactions in Bore-Hole Waters in the Skellefte-Field, Northern Sweden

Hydrology Research ◽

10.2166/nh.1983.0015 ◽

1983 ◽

Vol 14 (3) ◽

pp. 179-192

Author(s):

Jan Lidén ◽

Staffan Sjöberg

Keyword(s):

Rock Type ◽

Invariant Solution ◽

Solution Composition ◽

Ph Values ◽

Equilibrium Reactions ◽

Computerized Simulation ◽

Main Components ◽

Time Invariant

In a series of bore holes in an acid-intermediate volcanite rock type measurements of pH and pe (in situ), main ionic constituents, silicic acid and aluminium were made. The bore holes covered the pH interval 6.5-8.6, each with a time invariant solution composition. Field data were used as an experimental test of computerized simulation of weathering reactions by means of equilibrium models. The results suggest that a criterion for an undisturbed groundwater system is a high pH and a low pe where the dissolved main components reach a saturation concentration close to that experimentally found. For lower pH values, however, only the subsystem H+ - Si(OH)4 - Al3+ corresponded to an equilibrium behaviour.

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Using Particle Filters to Analyse the Credibility in Model Predictions

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.807.218 ◽

2015 ◽

Vol 807 ◽

pp. 218-225

Author(s):

Peter Lewis Green

Keyword(s):

Bayesian Approach ◽

Particle Filters ◽

Parameter Estimates ◽

Model Predictions ◽

Bayesian Tracking ◽

Time Invariant

Models are often used to make predictions far from the region where they were trained and validated. In this paper attempts are made to analyse the credibility that can be placed in such predictions. The proposed approach involves treating a model’s parameters as time-variant (even if it is believed that this is not the case), before utilising Bayesian tracking techniques to realise parameter estimates. An example is used to demonstrate that, relative to a Bayesian approach where the parameters are assumed to be time-invariant, treating the parameters as time-variant can reveal important flaws in the model and raise questions about its ability to make credible predictions.

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An Application of the HFACS Method to Aviation Accidents in Africa

Aviation Psychology and Applied Human Factors ◽

10.1027/2192-0923/a000093 ◽

2016 ◽

Vol 6 (1) ◽

pp. 33-38 ◽

Cited By ~ 4

Author(s):

Isaac Munene

Keyword(s):

Human Factors ◽

Physical Environment ◽

Human Factor ◽

Flight Training ◽

African Countries ◽

Causal Factors ◽

Aviation Accidents ◽

Factors Analysis ◽

Adverse Weather ◽

Decision Errors

Abstract. The Human Factors Analysis and Classification System (HFACS) methodology was applied to accident reports from three African countries: Kenya, Nigeria, and South Africa. In all, 55 of 72 finalized reports for accidents occurring between 2000 and 2014 were analyzed. In most of the accidents, one or more human factors contributed to the accident. Skill-based errors (56.4%), the physical environment (36.4%), and violations (20%) were the most common causal factors in the accidents. Decision errors comprised 18.2%, while perceptual errors and crew resource management accounted for 10.9%. The results were consistent with previous industry observations: Over 70% of aviation accidents have human factor causes. Adverse weather was seen to be a common secondary casual factor. Changes in flight training and risk management methods may alleviate the high number of accidents in Africa.

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