Formulation of an innovative model for the bioeconomy.

PLoS One

Postgraduate in Agri-Food Science and Technology, Autonomous University of Chapingo, National Council of Science and Technology, Texcoco, Mexico.

Published: November 2024

Background: The bioeconomy, an evolving concept promoting sustainable use of renewable biological resources, confronts the challenge of balancing growth and sustainability across sectors like biotechnology, agriculture, and forestry. This study aims to elucidate the bioeconomy's dynamic nature, constructing a comprehensive theoretical model addressing these complexities.

Methodology: Through an extensive literature review, foundational elements for this model were identified: defining the core concept, delineating relevant variables, specifying assumptions and parameters, and depicting relationships through equations or diagrams. Special attention was given to integrating Georgescu-Roegen's insights, emphasizing causal links, state variables, measurement scales, and validation plans.

Results: The model incorporates Georgescu-Roegen's insights, highlighting the importance of clearly defining the bioeconomy for a comprehensive understanding. The proposed model leverages variables, assumptions, and equations within Georgescu-Roegen's framework, serving as a crucial tool for researchers, policymakers, and industry stakeholders. This approach facilitates research structuring, informed decision-making, and interdisciplinary collaboration.

Conclusion: By addressing the bioeconomy's evolution, and cross-sectional boundaries, and adopting a broader perspective, this study contributes to policy development for a more sustainable and integrated bioeconomy. Based on empirical knowledge, this model provides not only a solid theoretical framework but also practical guidelines for advancing toward a balanced and resilient bioeconomy.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11534262PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0309358PLOS

Publication Analysis

Top Keywords

variables assumptions
8
georgescu-roegen's insights
8
model
6
bioeconomy
5
formulation innovative
4
innovative model
4
model bioeconomy
4
bioeconomy background
4
background bioeconomy
4
bioeconomy evolving
4

Similar Publications

Inference of Correlations Among Testlet Effects: A Latent Variable Selection Method.

Appl Psychol Meas

December 2024

Collaborative Innovation Center of Assessment Toward Basic Education Quality, Beijing Normal University, Beijing, China.

In psychological and educational measurement, a testlet-based test is a common and popular format, especially in some large-scale assessments. In modeling testlet effects, a standard bifactor model, as a common strategy, assumes different testlet effects and the main effect to be fully independently distributed. However, it is difficult to establish perfectly independent clusters as this assumption.

View Article and Find Full Text PDF

Investigation of bidirectional causal association between temporomandibular disorders and five mental disorders.

Arch Oral Biol

December 2024

College & Hospital of Stomatology, Anhui Medical University, Key Lab. of Oral Diseases Research of Anhui Province, Hefei 230032, China. Electronic address:

Objective: This study utilized two-sample Mendelian randomization (TSMR) to investigate the bidirectional causal associations between temporomandibular disorders (TMD) and five mental disorders.

Methods: Single-nucleotide polymorphisms (SNPs) linked to TMD were extracted from the Genome-Wide Association Studies (GWAS) database. The SNPs selected as instrumental variables (IVs) were required to have strong associations with the exposure phenotype and to meet the assumptions of Mendelian randomization (MR) analysis.

View Article and Find Full Text PDF

Healthcare-associated infections (HAIs) represent a major threat in Europe. Infection prevention and control (IPC) measures are crucial to lower their occurrence, as well as antimicrobial stewardship to ensure appropriate use of antibiotics. Starting from Italian national data, this study aimed at: (i) describing IPC indicators, prevalence of HAIs, antimicrobial use and appropriateness of antibiotic use in Italy; (ii) estimating effects of IPC variables on HAI prevalence and on the proportion of antibiotics without specific reason.

View Article and Find Full Text PDF

Classification and regression problems can be challenging when the relevant input features are diluted in noisy datasets, in particular when the sample size is limited. Traditional Feature Selection (FS) methods address this issue by relying on some assumptions such as the linear or additive relationship between features. Recently, a proliferation of Deep Learning (DL) models has emerged to tackle both FS and prediction at the same time, allowing non-linear modeling of the selected features.

View Article and Find Full Text PDF

Control charts are commonly used for process monitoring under the assumption that the variable of interest follows a normal distribution. However, this assumption is frequently violated in real-world applications. In this study, we develop an adaptive control chart based on the exponentially weighted moving average (EWMA) statistic to monitor irregular variations in the mean of the Truncated Transmuted Burr-II (TTB-II) distribution, employing Hastings approximation for normalization.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!