Results 111 to 120 of about 498,756 (298)

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

open access: yesAdvanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee   +3 more
wiley   +1 more source

Ruptures and Continuities

open access: yesManazir Journal
The paper examines the development of art galleries and exhibition spaces in Lebanon since the beginning of the civil war in 1975 and throughout the 1980s, with a particular interest in the shifts and changes that occurred as a result of the hostilities.
Monique Bellan
doaj   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia   +1 more
wiley   +1 more source

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

open access: yesAdvanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan   +3 more
wiley   +1 more source

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

KI-basierte Wissensvermittlung in der Schule

open access: yesMedienimpulse
Der Beitrag analysiert das Verhältnis von Digitalem Kapitalismus, staatlichen Schulen und den Möglichkeiten einer evidenzbasierten Medienpädagogik.
Markus Pohlmann   +2 more
doaj   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

open access: yesAdvanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser   +6 more
wiley   +1 more source

Pluralism without Illusions [PDF]

open access: yes, 2005
Much of contemporary Anglo-American Liberal political theory is still living under the shadow of Max Weber. In particular, it seems to accept the idea of disenchantment and has more recently discovered the problem value pluralism. Max Weber’s idea of the
Lassman, Peter
core   +1 more source

Legitimidad, dominación y derecho en la teoría sociológica del Estado de Max Weber

open access: yesRevista Estudios Socio-Jurídicos, 2010
En este artículo se analizan de forma conceptual y crítica las relaciones entre legitimidad, dominación y derecho en el complejo aparato conceptual de la sociológica de Max Weber.
Hernán Martínez-Ferro
doaj  

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

open access: yesAdvanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu   +11 more
wiley   +1 more source

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