Modeling and optimization are essential tasks that arise in the analysis and design of supply chains (SCs). SC models are essential for understanding emergent behavior such as transactions between participants, inherent value of products exchanged, as well as impact of externalities (e.g., policy and climate) and of constraints. Unfortunately, most users of SC models have limited expertise in mathematical optimization, and this hinders the adoption of advanced decision-making tools. In this work, we present ADAM, a web platform that enables the modeling and optimization of SCs. ADAM facilitates modeling by leveraging intuitive and compact graph-based abstractions that allow the user to express dependencies between locations, products, and participants. ADAM model objects serve as repositories of experimental, technology, and socio-economic data; moreover, the graph abstractions facilitate the organization and exchange of models and provides a natural framework for education and outreach. Here, we discuss the graph abstractions and software design principles behind ADAM, its key functional features and workflows, and application examples.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9610445 | PMC |
http://dx.doi.org/10.1016/j.compchemeng.2022.107911 | DOI Listing |
J Occup Environ Med
November 2024
University of Connecticut, Storrs, Connecticut, USA.
Objective: The purpose of study was to explore family caregiver perspectives on work-life balance while caring for adults with Parkinson's Disease.
Methods: The study was performed using a convergent mixed methods design and a revised adaptation of the Work-Life Conflict model. Caregivers completed surveys followed by semi-structured interviews (N = 40).
J Occup Environ Hyg
January 2025
Center for Environmental Solutions and Emergency Response, United States Environmental Protection Agency, Cincinnati, Ohio.
Chemical release data are essential for performing chemical risk assessments to understand the potential exposures arising from industrial processes. Often, these data are unknown or unavailable and must be estimated. A case study of volatile organic compound releases during extrusion-based additive manufacturing is used here to explore the viability of various regression methods for predicting chemical releases to inform chemical assessments.
View Article and Find Full Text PDFIntegr Environ Assess Manag
January 2025
División de Estudios de Posgrado e Investigación, Tecnológico Nacional de México/IT de Culiacán, Culiacán, Sinaloa, México.
Eutrophication is one of the most relevant concerns due to the risk to water supply and food security. Nitrogen and phosphorus chemical species concentrations determined the risk and magnitude of eutrophication. These analyses are even more relevant in basins with intensive agriculture due to agrochemical discharges.
View Article and Find Full Text PDFAngew Chem Int Ed Engl
January 2025
Emory University, Chemistry, 1515 Dickey Dr., 30322, Atlanta, UNITED STATES OF AMERICA.
Genetically encoded tension sensors (GETSs) allow for quantifying forces experienced by intracellular proteins involved in mechanotransduction. The vast majority of GETSs are comprised of a FRET pair flanking an elastic "spring-like" domain that gradually extends in response to force. Because of ensemble averaging, the FRET signal generated by such analog sensors conceals forces that deviate from the average, and hence it is unknown if a subset of proteins experience greater magnitudes of force.
View Article and Find Full Text PDFACS Nano
January 2025
Department of Physics and Astronomy, University of Manitoba, Winnipeg R3T 2N2, Canada.
Theory and simulations are used to demonstrate implementation of a variational Bayes algorithm called "active inference" in interacting arrays of nanomagnetic elements. The algorithm requires stochastic elements, and a simplified model based on a magnetic artificial spin ice geometry is used to illustrate how nanomagnets can generate the required random dynamics. Examples of tracking and PID control are demonstrated and shown to be consistent with the original stochastic differential equation formulation of active inference.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!