Results 201 to 210 of about 1,643,554 (351)

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

Challenges and Future Directions in Assessing the Quality and Completeness of Advanced Materials Safety Data for Re‐Usability: A Position Paper From the Nanosafety Community

open access: yesAdvanced Sustainable Systems, EarlyView.
Nanosafety data provide a guiding example for establishing best practices in data management, aligning with FAIR principles and quality criteria. This review explores existing quality assessment approaches for reliability, relevance, and completeness, emphasizing the need for harmonization and adaptation to nanomaterials and advanced materials. The aim
Verónica I. Dumit   +43 more
wiley   +1 more source

A Comparative Study of Formal and Informal Specifications through an Industrial Case Study [PDF]

open access: green, 2001
Manoranjan Satpathy   +3 more
openalex  

Data‐Driven Multi‐Objective Optimization of Large‐Diameter Si Floating‐Zone Crystal Growth

open access: yesAdvanced Theory and Simulations, EarlyView.
This study presents a surrogate‐based Multi‐Objective Optimization framework for Floating Zone silicon crystal growth. An ensemble of Neural Networks is trained on simulation data and combined with Genetic Algorithms to explore trade‐offs in process parameters.
Lucas Vieira   +3 more
wiley   +1 more source

Aspects of zone-like identity and holotomographic tracking of human stem cell-derived liver sinusoidal endothelial cells. [PDF]

open access: yesFront Cell Dev Biol
Amirola-Martinez M   +8 more
europepmc   +1 more source

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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