We use a set of hydrodynamical and dark matter-only (DMonly) simulations to calibrate the halo mass function (HMF). We explore the impact of baryons, propose an improved parametrization for spherical ...overdensity masses, and identify differences between our DMonly HMF and previously published HMFs. We use the Magneticum simulations, which are well suited because of their accurate treatment of baryons, high resolution, and large cosmological volumes of up to (3818 Mpc)3. Baryonic effects globally decrease the masses of galaxy clusters, which, at a given mass, results in a decrease of their number density. This effect vanishes at high redshift z ∼ 2 and for high masses M
200 m ≳ 1014 M⊙. We perform cosmological analyses of three idealized approximations to the cluster surveys by the South Pole Telescope (SPT), Planck, and eROSITA. We pursue two main questions. (1) What is the impact of baryons? – for the SPT-like and the Planck-like samples, the impact of baryons on cosmological results is negligible. In the eROSITA-like case, however, neglecting the baryonic impact leads to an underestimate of Ωm by about 0.01, which is comparable to the expected uncertainty from eROSITA. (2) How does our DMonly HMF compare with previous work? – for the Planck-like sample, results obtained using our DMonly HMF are shifted by Δ(σ8) ≃ Δ(σ8(Ωm/0.27)0.3) ≃ 0.02 with respect to results obtained using the Tinker et al. fit. This suggests that using our HMF would shift results from Planck clusters towards better agreement with cosmic-microwave-background anisotropy measurements. Finally, we discuss biases that can be introduced through inadequate HMF parametrizations that introduce false cosmological sensitivity.
Product innovation is a key to organizational renewal and success. Relative to other forms of innovation, radical product innovations offer unprecedented customer benefits, substantial cost ...reductions, or the ability to create new businesses, any of which should lead to superior organizational performance. In other words, a radical product innovation capability is a dynamic capability, one that enables the organization to maintain alignment with rapidly evolving customer needs in high‐velocity environments. Extensive research has been conducted on the antecedents to an incremental/general product innovation capability, and meta‐analyses have been conducted to integrate the results from the various studies. However, whether and how a radical product innovation capability differs from an incremental product innovation capability is also critical. The purpose of this work is to develop a testable model of the antecedents to radical product innovation success. Based on an extensive literature review, a comprehensive set of organizational components that comprise a firm's radical product innovation capability is identified. These organizational components include senior leadership, organizational culture, organizational architecture, the radical product innovation development process, and the product launch strategy. Of course, each of these components has subcomponents that provide even more texture. This review highlights how the components of a radical innovation capability function differently from those for an incremental capability. In addition, this review strongly suggests that the direct effects models that dominate this literature underestimate the complexity of the interplay of components that comprise a radical product innovation capability. Thus, a model to demonstrate this interplay of these organizational components is provided. Illustrative research propositions are offered to provide guidance to researchers. Suggestions for executives and managers who are involved in the product development process and for scholars who seek to advance the state of knowledge in this area are offered in the conclusion.
Given an uncountable and compact metric space
E
, the one-dimensional lattice system is the space
Ω
=
E
N
with an a priori measure
p
on the state space
E
. Given a potential
f
:
Ω
→
R
one can ask: ...among the invariant probabilities which one is the equilibrium probability
μ
for the interaction described by
f
? As usual the equilibrium probability for
f
is the one maximizing pressure. We will present here the case of the product type potential on the one-dimensional lattice system and in this setting we can show the explicit expression of the equilibrium probability. We will also consider questions about Ergodic Optimization, maximizing probabilities, subactions and we will show selection of a maximizing probability, when temperature goes to zero. Finally we show a large deviation principle when temperature goes to zero and we present an explicit expression for the deviation function.
The ancient Greeks used the term karotides for the great arteries in the neck, compression of which could plunge the victim into karoun: deep sleep or stupor. The artery name aside, studies of the ...patterns of brain infarction and their clinical severity have been an unbroken chain of growing sophistication in the past 150 years. Two main patterns emerged: perfusion failure with high-convexity infarction from hemodynamically important ipsilateral carotid stenosis or embolism from nonstenosing carotid plaque.
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