Results 101 to 110 of about 204,625 (305)

Hearing voices: mental illness and cultural recognition [PDF]

open access: yes, 2002
Popular misconceptions about the danger of madness have undermined mentally ill people’s struggle for social inclusion. Consequently, efforts to think through how we might belong together must take account of mental patients’ right to a public voice ...
Cross, S, Lockyer, S
core  

Macrophage Phenotype Detection Methodology on Textured Surfaces via Nuclear Morphology Using Machine Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
A novel machine learning approach classifies macrophage phenotypes with up to 98% accuracy using only nuclear morphology from DAPI‐stained images. Bypassing traditional surface markers, the method proves robust even on complex textured biomaterial surfaces. It offers a simpler, faster alternative for studying macrophage behavior in various experimental
Oleh Mezhenskyi   +5 more
wiley   +1 more source

Can Madness be Utopic? Analyzing Utopias through Madness as Political Praxis

open access: yesHumana.Mente: Journal of Philosophical Studies
The paper contends that madness can be used as a way to engage with theories of utopia. The author draws upon their own autoethnographic experiences of madness and analyzes them through a Nietzschean perspective.
Riley Clare Valentine
doaj  

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

open access: yesAdvanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas   +4 more
wiley   +1 more source

Précis of Madness: A Philosophical Exploration

open access: yesEuropean Journal of Analytic Philosophy
The following is a short synopsis of the book Madness: A Philosophical Exploration. It provides an overview of the book’s core distinction between madness-as-dysfunction and madness-as-strategy, and enumerates four benefits of relying on this conceptual ...
Justin Garson
doaj  

Divine Madness

open access: yesAmerican Journal of Islam and Society, 1995
This book is a welcome addition to the few book-length biographies of important African historical figures. The study, which consists of an introduction and six chapters, offers a fresh and balanced perspective on one of Africa's most controversial ...
Alusine Jalloh
doaj   +1 more source

MTCA‐Net: Multi‐Task Cascade Analysis Network for Real‐Time Sperm Quality Analysis

open access: yesAdvanced Intelligent Systems, EarlyView.
This article proposes MTCA‐Net, a multi‐task cascaded analysis network for real‐time sperm quality assessment in intracytoplasmic sperm injection. The framework integrates detection, tracking, and segmentation modules to jointly analyze sperm morphology and motility.
Jiajin Li   +10 more
wiley   +1 more source

European madness 1910–1980: lessons for today from Alastair Morgan's Continental Philosophy of Psychiatry: The Lure of Madness

open access: yesBJPsych Bulletin
In Continental Philosophy of Psychiatry: The Lure of Madness Alastair Morgan surveys the contributions of a loosely conceived school of psychiatrists, philosophers and social theorists to understanding and responding to madness during the years 1910–1980.
George Ikkos
doaj   +1 more source

Method or Madness? Textual analysis in media studies [PDF]

open access: yes, 1999
Scholarly analyses of media have tended to view the media text (e.g. film / programme / article) as the logical site of enquiry. However, this focus on the text has often resulted in a privileging of the text as the locus of meaning.
Havemann, Leo
core   +1 more source

Comparing the Latent Features of Universal Machine‐Learning Interatomic Potentials

open access: yesAdvanced Intelligent Systems, EarlyView.
This study quantitatively assesses how universal machine‐learning interatomic potentials encode the chemical space into latent features, showing unique model‐specific representations with high cross‐model reconstruction errors. It explores how training datasets, protocols, and targets affect these encodings.
Sofiia Chorna   +5 more
wiley   +1 more source

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