Results 61 to 70 of about 83,599 (303)

MERCHANTRY VS NOBILITY: KHARKIV ELITE IN THE SECOND HALF OF XIX – THE EARLY XX CENTURY

open access: yesМісто: історія, культура, суспільство, 2017
The article attempts to trace the effect of the Pareto elite circulation law on the example of the Kharkiv city elite in the second half of the 19th - early 20th centuries. The author investigates the involvement of the nobility and the merchants in the
Anastasiya Bozhenko
doaj   +1 more source

Graph‐based imitation and reinforcement learning for efficient Benders decomposition

open access: yesAIChE Journal, EarlyView.
Abstract This work introduces an end‐to‐end graph‐based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural network, which takes as input a bipartite graph representation of the master problem and proposes a candidate solution.
Bernard T. Agyeman   +3 more
wiley   +1 more source

Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites

open access: yesAdvanced Intelligent Discovery, EarlyView.
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir   +4 more
wiley   +1 more source

The Pareto Argument for Inequality Revisited [PDF]

open access: yes
One of the more obscure arguments for Rawls’ difference principle dubbed ‘the Pareto argument for inequality’ has been criticised by G. A. Cohen (1995, 2008) as being inconsistent.
Fisher, A. R. J., McClennen, Edward F.
core  

Loss-Avoidance and Forward Induction in Experimental Coordination Games [PDF]

open access: yes, 1995
We report experiments on how players select among multiple Pareto-ranked equilibria in a coordination game. Subjects initially choose inefficient equilibria.
Cachon, Gérard P., Camerer, Colin F.
core   +2 more sources

Deep Learning‐Assisted Design of Mechanical Metamaterials

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong   +5 more
wiley   +1 more source

On the Possibility of Continuous, Paretian and Egalitarian Evaluation of Infinite Utility Streams [PDF]

open access: yes
There exists a utilitarian tradition à la Sidgwick of treating equal generations equally in the form of anonymity. Diamond showed that no social evaluation ordering over infinite utility streams satisfying the Pareto principle, Sidgwick's equity ...
Hara, Chiaki   +3 more
core  

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

open access: yesAdvanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova   +4 more
wiley   +1 more source

The Problematics of the Pareto Principle [PDF]

open access: yesSSRN Electronic Journal, 2003
The Pareto principle is often considered self-evident, particularly by economists. On close examination, however, it is much more problematic than is commonly believed. Preference satisfaction is only imperfectly related to values such as individual welfare and autonomy. Moreover, preferences can change during transactions or because of shifts in legal
openaire   +2 more sources

Harnessing Machine Learning to Understand and Design Disordered Solids

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

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