Results 181 to 190 of about 35,606 (249)
ABSTRACT Objectives This scoping review characterizes the scope, methods, and framing of empirical research evaluating the Field Sanitation Standard (FSS) and Worker Protection Standard (WPS) of the U.S. Environmental Protection Agency and the U.S. Department of Labor respectively.
Kaitlyn Alvarez Noli +3 more
wiley +1 more source
A framework for a national cancer imaging repository in Nigeria. [PDF]
Adegoke-Elijah A +5 more
europepmc +1 more source
FAIR4prep: FAIR clinical informatics data preprocessing in artificial intelligence applications. [PDF]
Cobo M +3 more
europepmc +1 more source
Documentation on metadata standards for inclusion of resources in data portalLead beneficiary is TAUFSD an affiliated entity of CESSDA ...
openaire +1 more source
A framework for reproducibly managing coupled research software and data assets based on shared transformation functions. [PDF]
Kuckertz P +11 more
europepmc +1 more source
Sustainable Manufacturing Platforms for Closed‐Cycle Bioeconomy Applications
ABSTRACT The transition to a circular bioeconomy requires innovative production platforms that prioritize sustainability, resource efficiency, and waste minimization. Organic waste from agriculture, aquaculture, and food production represents an underutilized feedstock for biomanufacturing, contributing to a circular economy.
Yelizaveta Chernysh +2 more
wiley +1 more source
Opportunities and obstacles in harnessing intraoperative data. [PDF]
Hernandez A, Marwaha J.
europepmc +1 more source
Turning a new leaf: PhenoVision provides leaf phenology data at the global scale
Abstract Premise Plant phenology dictates many aspects of community function and ecosystem dynamics. Yet, global phenology data are still limited, especially in areas lacking monitoring programs. Here we present a new data resource, PhenoVision–Leaf, which extends a computer vision pipeline utilizing iNaturalist digital image vouchers to produce global‐
Erin L. Grady +6 more
wiley +1 more source
TrainTracks - federated learning for reproducible research on sensitive medical data. [PDF]
Elwes M +5 more
europepmc +1 more source

