Results 211 to 220 of about 562,901 (310)

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

From Hurricane Irma to the Grindavík eruptions: volatility premiums in disaster governance. [PDF]

Disasters
Björnsson T.
europepmc   +1 more source

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

Advanced 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, Miguel Hernández‐del‐Valle, Christina Schenk, De‐Yi Wang, Maciej Haranczyk   +4 more
wiley   +1 more source

Learning asset-based community development in the rural Tanzania

, 2021
Nzali, Agnes, Porkka, Jouko
openaire   +2 more sources

Teaching Deaf learners in multi-grade classes: Perceptions from a rural Mpumalanga special school. [PDF]

Afr J Disabil
Chauke M, Ledwaba RG, Motitswe JM.
europepmc   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Investigating pathways to environmental civic engagement for diverse communities. [PDF]

Environ Manage
Hamaneh AB, Dayer AA, Drape TA, Chaves WA.   +3 more
europepmc   +1 more source

The Challenge of Handling Structured Missingness in Integrated Data Sources

Advanced Intelligent Discovery, EarlyView.
As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson, Marius Hofert, Eleni‐Rosalina Andrinopoulou, Niels Hagenbuch, Sarah McGough, Chris Harbron, Robin Mitra   +6 more
wiley   +1 more source

Mobilizing community assets to address health equity: Evaluation of the Communities Organizing to Promote Equity (COPE) project in Kansas. [PDF]

Public Health Pract (Oxf)
Bridges KM, Fitzgerald Wolff S, Finocchario-Kessler S, Knapp KE, Pacheco CM, Ablah E, Greiner KA, LeMaster JW, Chen Y, Collie-Akers V, Ramírez M, Miras Neira A, Scott A, Sykes KJ, Parente DJ, Corriveau E, Woodward J, Morrow E, Ellerbeck EF, COPE Team.   +19 more
europepmc   +1 more source