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Transformations in mathematics alter the position or orientation of a function’s graph while preserving its fundamental shape. One important type of transformation is the horizontal shift, which involves modifying the input variable within a function’s equation. This operation affects where outputs occur along the horizontal axis but does not alter the function’s overall structure.A horizontal shift is achieved by replacing the input variable x with either x + c or x - c,...
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The shape of a suspension bridge cable hanging under its own weight is described by a catenary curve, which is modeled using the hyperbolic cosine function. This mathematical model accurately captures the balance between gravity and tension acting along the cable. When a particular vertical position on the cable is known, the corresponding horizontal position can be determined using the inverse hyperbolic cosine function, allowing for a detailed analysis of the cable's geometry.Inverse...
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A function's graph can be modified by changing its position or size without altering its overall shape. These transformations allow the graph to be moved across the coordinate plane while preserving its pattern and structure. One of the most common transformations is shifting, which repositions the graph without distorting it.When the output of a function is adjusted by adding or subtracting a constant, the graph shifts vertically. A positive value moves the graph upward, while a negative value...
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Transformations modify the graphical representation of a function without changing its fundamental form. One common transformation is reflection, which flips the graph across a designated axis. When the vertical coordinates of all points are multiplied by the negative one, the entire graph is mirrored over the horizontal axis. This transformation reverses the vertical orientation of peaks and troughs, akin to signal inversion in electrical systems, where a waveform is flipped, but the timing of...
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Derivatives quantify the rate of change of a function and can be interpreted geometrically as the slope of a straight line or the slope of a tangent line to a curve at a given point. In the context of a roller coaster, the derivative of the function describing the track’s horizontal position provides a mathematical description of how steep the path is at any location along the ride.Constant and Linear PathsA horizontal segment of a roller coaster can be modeled by a constant function,...
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Updated: Jan 18, 2026

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
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Equivariant valuations on convex functions.

Georg C Hofstätter1, Jonas Knoerr1

  • 1Institute of Discrete Mathematics and Geometry, TU Wien, 1040 Vienna, Austria.

Calculus of Variations and Partial Differential Equations
|September 11, 2025
PubMed
Summary

Researchers classified continuous valuations on convex functions, identifying analogues of the difference body map. They proved no generalization of the projection body map exists in this setting for convex functions.

Keywords:
26B2552A4152B45

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Area of Science:

  • Convex Geometry
  • Functional Analysis
  • Geometric Measure Theory

Background:

  • Valuations are fundamental tools in integral geometry and convex geometry.
  • Continuous valuations on spaces of convex functions have been extensively studied.
  • Understanding their behavior under geometric transformations is crucial.

Purpose of the Study:

  • To classify continuous valuations on finite convex functions.
  • To investigate their properties under volume-preserving linear maps.
  • To determine the existence of analogues for difference body and projection body maps.

Main Methods:

  • Classification of continuous valuations using properties of dual epi-translation-invariance and equi-/contravariance.
  • Analysis of the behavior of these valuations under linear transformations.
  • Demonstration of non-existence results through rigorous mathematical proof.

Main Results:

  • Identification of valuation-theoretic functional analogues of the difference body map.
  • Proof of the non-existence of a generalized projection body map in this context.
  • Extension of the non-existence result to valuations on convex functions finite near the origin.

Conclusions:

  • The study provides a complete classification of specific continuous valuations.
  • It highlights fundamental differences between difference body and projection body maps in this setting.
  • The findings contribute to a deeper understanding of geometric valuations and their limitations.