Results 141 to 150 of about 3,753,697 (367)

AI‐Powered Framework for Evaluating Drug Efficacy for Three‐Dimensional In Vitro Cancer Models in Robot‐Assisted Production

open access: yesAdvanced Robotics Research, EarlyView.
An AI‐powered, robot‐assisted framework automatically produces, images, and analyzes 3D tumor spheroids to evaluate drug efficacy. Integrated modules handle spheroid formation, live/dead staining, brightfield imaging, and automated image analysis, including spheroid segmentation, viability and metrics to assess the drug treatment efficacy. The workflow
Dalia Mahdy   +13 more
wiley   +1 more source

Factors Driving Battery and Solar Purchase Decision of Residents: a Behavioural Choice Experiment Using a Hybrid Discrete Choice and Latent Variable Model

open access: yesAdvanced Sustainable Systems, EarlyView.
This article explores what drives households to adopt solar PV and battery systems in South East Queensland. Using hybrid discrete choice experiments, it reveals distinct adopter profiles and highlights cost, system size, and energy independence as key motivators.
Mohammad Alipour   +3 more
wiley   +1 more source

Racial differences in the income–well-being gradient

open access: yesJudgment and Decision Making
Existing research documents a log-linear relationship between income and subjective well-being, known as the income–well-being gradient. Using data from millions of Americans, mainly from the Gallup Daily Poll, we find significant racial differences in ...
Bouke Klein Teeselink   +2 more
doaj   +1 more source

Urbanization and Subjective Well-Being

open access: yes, 2019
This chapter proposes a review of the most recent works developed by the authors on the association between urbanization and subjective well-being. While most previous studies point out a strong dichotomy between urban and rural areas, the latter being characterized by higher levels of well-being than the former, the research program presented here ...
C. Lenzi, G. Perucca
openaire   +2 more sources

Multi‐Site Transfer Classification of Major Depressive Disorder: An fMRI Study in 3335 Subjects

open access: yesAdvanced Science, EarlyView.
The study proposes graph convolution network with sparse pooling to learn the hierarchical features of brain graph for MDD classification. Experiment is done on multi‐site fMRI samples (3335 subjects, the largest functional dataset of MDD to date) and transfer learning is applied, achieving an average accuracy of 70.14%.
Jianpo Su   +14 more
wiley   +1 more source

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