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How are core social phenomena to be understood as modes of being? This book offers an alternative approach to social ontology. Recent interest in social ontology on the part of mainstream philosophy and the social sciences presupposes from the outset that the human being can be cast as a conscious subject whose intentionality can be collective. By contrast, the present study insistently poses the crucial question of who the human being is and how they sociate as whos. Such whoness is a clean-cut departure from the venerable tradition of questioning whatness (quidditas, essence) in philosophical thinking. Casting human being hermeneutically as whoness opens up new insights into how human beings sociate in interplays of mutual estimation that are simultaneously social power plays. Hitherto, the ontology of social power in all its various guises, has only ever been implicit. This book makes it explicit. The kind of social power prevalent in capitalist societies is that of the reified value embodied in commodities, money, capital, & co. Reified value itself is constituted through an interplay of mutual estimation among things that reflects back on the power interplay among whos. In this way a new critique of capitalism becomes possible.

In order to make design decisions, engineers may seek to identify regions of the design domain that are acceptable in a computationally efficient manner. A design is typically considered acceptable if its reliability with respect to parametric uncertainty exceeds the designer’s desired level of confidence. Despite major advancements in reliability estimation and in design classification via decision boundary estimation, the current literature still lacks a design classification strategy that incorporates parametric uncertainty and desired design confidence. To address this gap, this works offers a novel interpretation of the acceptance region by defining the decision boundary as the hypersurface which isolates the designs that exceed a user-defined level of confidence given parametric uncertainty. This work addresses the construction of this novel decision boundary using computationally efficient algorithms that were developed for reliability analysis and decision boundary estimation. The proposed approach is verified on two physical examples from structural and thermal analysis using Support Vector Machines and Efficient Global Optimization-based contour estimation.

Accurate simulation of the quasi‐biennial oscillation (QBO) is challenging due to uncertainties in representing convectively generated gravity waves. We develop an end‐to‐end uncertainty quantification workflow that calibrates these gravity wave processes in E3SM for a realistic QBO. Central to our approach is a domain knowledge‐informed, compressed representation of high‐dimensional spatio‐temporal wind fields. By employing a parsimonious statistical model that learns the fundamental frequency from complex observations, we extract interpretable and physically meaningful quantities capturing key attributes. Building on this, we train a probabilistic surrogate model that approximates the fundamental characteristics of the QBO as functions of critical physics parameters governing gravity wave generation. Leveraging the Karhunen–Loève decomposition, our surrogate efficiently represents these characteristics as a set of orthogonal features, capturing cross‐correlations among multiple physics quantities evaluated at different pressure levels and enabling rapid surrogate‐based inference at a fraction of the computational cost of full‐scale simulations. Finally, we analyze the inverse problem using a multi‐objective approach. Our study reveals a tension between amplitude and period that constrains the QBO representation, precluding a single optimal solution. To navigate this, we quantify the bi‐criteria trade‐off and generate a set of Pareto optimal parameter values that balance the conflicting objectives. This integrated workflow improves the fidelity of QBO simulations and offers a versatile template for uncertainty quantification in complex geophysical models. Plain Language Summary Simulating the quasi‐biennial oscillation (QBO), a regular pattern of alternating winds high in the atmosphere, remains a major challenge for climate models. We developed an end‐to‐end workflow to calibrate gravity wave processes in the Energy Exascale Earth System Model, leading to more realistic simulations. We began by compressing complex spatio‐temporal data into a few key, physically meaningful quantities, such as the oscillation's amplitude and period. This data reduction allowed us to isolate the QBO signal from noise and other atmospheric phenomena. Next, we built a fast statistical model that predicts QBO behavior based on critical physics parameters. This surrogate efficiently captures relationships among various atmospheric features, reducing the need for computationally expensive full‐scale simulations. Our analysis revealed a trade‐off between QBO amplitude and period, meaning that improving one aspect often worsened the other. Rather than finding a single perfect solution, we identified a range of balanced settings that offer the best compromise. This integrated approach not only leads to more realistic QBO simulation but also provides a practical framework for tuning other complex atmospheric phenomena. Key Points We developed an end‐to‐end workflow that calibrates gravity wave generation in E3SMv3, improving quasi‐biennial oscillation (QBO) realism The fundamental frequency model compressed wind field data into physically interpretable quantities, isolated the QBO signal, and reduced dimensionality while retaining key QBO variability Our workflow reveals no single optimal configuration for QBO realism, but a frontier of best‐compromise solutions

Freedom, value, power, justice, government, legitimacy are major themes of the present inquiry. It explores the ontological structure of human beings associating with one another, the basic phenomenon of society. We human beings strive to become who we are in an ongoing power interplay with each other. Thinkers called as witnesses include Plato, Aristotle, Anaximander, Protagoras, Hobbes, Locke, Adam Smith, Hegel, Marx, Schopenhauer, Heidegger, Schumpeter, Hayek, Schmitt, Ernst Jünger, et al.

We live today surrounded by countless digital gadgets and navigate through cyberspace as if it were the most natural thing in the world. This digital cast of being, however, comes from a long history of philosophical and mathematical thinking in which the Western will to productive power over movement has attained its consummation. This study traces the digital dissolution of beings from the Pythagoreans, Plato and Aristotle's ontology via Cartesian mathematical science through to our digitized economy and telecommunications. With an appendix reinterpreting quantum mechanical indeterminacy phenomenologically.

The first aim is to provide well-articulated concepts by thinking through elementary phenomena of today's world, focusing on privacy and the digital, to clarify who we are in the cyberworld — hence a phenomenology of digital whoness. The second aim is to engage critically, hermeneutically with older and current literature on privacy, including in today's emerging cyberworld. Phenomenological results include concepts of i) self-identity through interplay with the world, ii) personal privacy in contradistinction to the privacy of private property, iii) the cyberworld as an artificial, digital dimension in order to discuss iv) what freedom in the cyberworld can mean, whilst not neglecting v) intercultural aspects and vi) the EU context.

This paper describes the atmospheric component of the US Department of Energy's Energy Exascale Earth System Model (E3SM) version 3. Significant updates have been made to the atmospheric physics compared to earlier versions. Specifically, interactive gas chemistry has been implemented, along with improved representations of aerosols and dust emissions. A new stratiform cloud microphysics scheme more physically treats ice processes and aerosol‐cloud interactions. The deep convection parameterization has been largely improved with sophisticated microphysics for convective clouds, making model convection sensitive to large‐scale dynamics, and incorporating the dynamical and physical effects of organized mesoscale convection. Improvements in aerosol wet removal processes and parameter re‐tuning of key aerosol and cloud processes have improved model aerosol radiative forcing. The model's vertical resolution has increased from 72 to 80 layers with the extra eight layers added in the lower stratosphere to better simulate the Quasi‐Biennial Oscillation. These improvements have enhanced E3SM's capability to couple aerosol, chemistry, and biogeochemistry and reduced some long‐standing biases in simulating tropical variability. Compared to its predecessors, the model shows a much stronger signal for the Madden‐Julian Oscillation, Kelvin waves, mixed Rossby‐gravity waves, and eastward inertia‐gravity waves. Aerosol radiative forcing has been considerably reduced and is now better aligned with community best estimates, leading to significantly improved skill in simulating historical temperature records. Its simulated mean‐state climate is largely comparable to E3SMv2, but with some notable degradation in shortwave cloud radiative effect, precipitable water, and surface wind stress, which will be addressed in future updates. Plain Language Summary This study is part of a series describing the newly released version 3 of the US Department of Energy's Energy Exascale Earth System Model (E3SMv3), focusing on updates to its atmospheric component model (EAMv3). Substantial improvements have been made in representing atmospheric chemistry, aerosols, clouds, convective processes, and their interactions in the model. The model's vertical resolution in the lower stratosphere has increased to better simulate the Quasi‐Biennial Oscillation. These updates strengthen E3SM's ability to model aerosol, chemistry, and biogeochemistry, and reduce biases in tropical variability. The model now shows stronger signals for phenomena like the Madden‐Julian Oscillation and Kelvin waves. Aerosol radiative forcing is better aligned with community estimates, improving the model's skill in simulating historical temperatures. The model's simulated mean‐state climate is largely comparable to its predecessor model EAMv2. Key Points Significant updates were made to Earth System Model version 3 atmospheric physics, including gas phase chemistry, aerosols, clouds, and convection Improved cloud, convection, and vertical resolution largely improved tropical variability simulation in troposphere and stratosphere Improved aerosol representation and aerosol‐cloud interactions have led to a much‐reduced and realistic aerosol radiative forcing