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Evaluating climate-related financial policies' impact on decarbonization with machine learning methods.
Sci Rep
January 2025
Joint Lab Artificial Intelligence and Data Science, Osnabrück University, 49074, Osnabrück, Germany.
This study examines how Climate-Related Financial Policies (CRFPs) support decarbonization and renewable energy transitions across 87 countries from 2000 to 2023. Using the Policy Sequencing Score (PSS) and a bindingness-weighted adoption indicator, it explores the relationships between CRFPs, CO2 emissions, and Renewable Energy Production (REP) across diverse economic and institutional contexts. Findings reveal significant variation in outcomes.
View Article and Find Full Text PDFConfigurable Multi-Layer Perceptron-Based Soft Sensors on Embedded Field Programmable Gate Arrays: Targeting Diverse Deployment Goals in Fluid Flow Estimation.
Sensors (Basel)
December 2024
Intelligent Embedded Systems of Computer Science, University of Duisburg-Essen, 47057 Duisburg, Germany.
This study presents a comprehensive workflow for developing and deploying Multi-Layer Perceptron (MLP)-based soft sensors on embedded FPGAs, addressing diverse deployment objectives. The proposed workflow extends our prior research by introducing greater model adaptability. It supports various configurations-spanning layer counts, neuron counts, and quantization bitwidths-to accommodate the constraints and capabilities of different FPGA platforms.
View Article and Find Full Text PDFIntegrating climate and physical constraints into assessments of net capture from direct air capture facilities.
Proc Natl Acad Sci U S A
January 2025
Department of Mechanical and Aerospace Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada.
Limiting climate change to targets enshrined in the Paris Agreement will require both deep decarbonization of the energy system and the deployment of carbon dioxide removal at potentially large scale (gigatons of annual removal). Nations are pursuing direct air capture to compensate for inertia in the expansion of low-carbon energy systems, decarbonize hard-to-abate sectors, and address legacy emissions. Global assessments of this technology have failed to integrate factors that affect net capture and removal cost, including ambient conditions like temperature and humidity, as well as emission factors of electricity and natural gas systems.
View Article and Find Full Text PDFClustered warming tolerances and the nonlinear risks of biodiversity loss on a warming planet.
Philos Trans R Soc Lond B Biol Sci
January 2025
Department of Genetics, Evolution and Environment, University College London, London WC1E 6BT, UK.
Anthropogenic climate change is projected to become a major driver of biodiversity loss, destabilizing the ecosystems on which human society depends. As the planet rapidly warms, the disruption of ecological interactions among populations, species and their environment, will likely drive positive feedback loops, accelerating the pace and magnitude of biodiversity losses. We propose that, even without invoking such amplifying feedback, biodiversity loss should increase nonlinearly with warming because of the non-uniform distribution of biodiversity.
View Article and Find Full Text PDFThermal Plasticity and Evolutionary Constraints in : Implications for Climate Change Adaptation.
Biology (Basel)
December 2024
Departamento de Ingeniería Genética, Unidad Irapuato, Cinvestav 36824, Mexico.
The ongoing rise in global temperatures poses significant challenges to ecosystems, particularly impacting bacterial communities that are central to biogeochemical cycles. The resilience of wild mesophilic bacteria to temperature increases of 2-4 °C remains poorly understood. In this study, we conducted experimental evolution on six wild strains from two lineages ( and ) to examine their thermal adaptation strategies.
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