Hasil untuk "Competition"

Thorsten Beck, O. D. Jonghe, G. Schepens

Gerard Hoberg, G. Phillips

F. Maestre, R. Callaway, F. Valladares et al.

Y. Hautier, P. Niklaus, A. Hector

Allen N. Berger, L. Klapper, Rima Turk-Ariss

Arnoud Boot, A. Thakor

Tim Besley, Tim Besley, Tim Besley et al.

P. Klemperer

R. Sanchez

E. Chamberlin

T. Bresnahan, P. Reiss

Joseph Farrell, P. Klemperer, P. Klemperer

Subrata Biswas

J. Connell

Kenneth F. Scheve, M. Slaughter

C. Flammer

N. Bloom, C. Propper, Stephan Seiler et al.

C. Fernandez, Y. Monnier, M. Santonja et al.

In contrast to plant-animal interactions, the conceptual framework regarding the impact of secondary metabolites in mediating plant-plant interference is currently less well defined. Here, we address hypotheses about the role of chemically-mediated plant-plant interference (i.e., allelopathy) as a driver of Mediterranean forest dynamics. Growth and defense abilities of a pioneer (Pinus halepensis) and a late-successional (Quercus pubescens) Mediterranean forest species were evaluated under three different plant interference conditions: (i) allelopathy simulated by application of aqueous needle extracts of Pinus, (ii) resource competition created by the physical presence of a neighboring species (Pinus or Quercus), and (iii) a combination of both allelopathy and competition. After 24 months of experimentation in simulated field conditions, Quercus was more affected by plant interference treatments than was Pinus, and a hierarchical response to biotic interference (allelopathy < competition < allelopathy + competition) was observed in terms of relative impact on growth and plant defense. Both species modulated their respective metabolic profiles according to plant interference treatment and thus their inherent chemical defense status, resulting in a physiological trade-off between plant growth and production of defense metabolites. For Quercus, an increase in secondary metabolite production and a decrease in plant growth were observed in all treatments. In contrast, this trade-off in Pinus was only observed in competition and allelopathy + competition treatments. Although Pinus and Quercus expressed differential responses when subjected to a single interference condition, either allelopathy or competition, species responses were similar or positively correlated when strong interference conditions (allelopathy + competition) were imposed.

Tyler J. Richards, Adam E. Flanders, Errol Colak et al.

The Radiological Society of North America (RSNA) Lumbar Degenerative Imaging Spine Classification (LumbarDISC) dataset is the largest publicly available dataset of adult MRI lumbar spine examinations annotated for degenerative changes. The dataset includes 2,697 patients with a total of 8,593 image series from 8 institutions across 6 countries and 5 continents. The dataset is available for free for non-commercial use via Kaggle and RSNA Medical Imaging Resource of AI (MIRA). The dataset was created for the RSNA 2024 Lumbar Spine Degenerative Classification competition where competitors developed deep learning models to grade degenerative changes in the lumbar spine. The degree of spinal canal, subarticular recess, and neural foraminal stenosis was graded at each intervertebral disc level in the lumbar spine. The images were annotated by expert volunteer neuroradiologists and musculoskeletal radiologists from the RSNA, American Society of Neuroradiology, and the American Society of Spine Radiology. This dataset aims to facilitate research and development in machine learning and lumbar spine imaging to lead to improved patient care and clinical efficiency.

Alireza Azarberahman, Mahmoodreza Mohammadnejadi Modi

PurposeThis research examines the structure of financial markets by integrating game theory and fuzzy logic. The objective is to develop a differential game model that analyzes competition among financial firms within a specific industry.Design/methodology/approachThis study employs a differential game model, where players set service prices, dynamically influencing market shares and profits over time. The model incorporates two fuzzy criteria—market power (price-variable cost ratio) and product differentiation (Herfindahl-Hirschman index)—to assess market structure. These criteria are applied to data from Tehran Stock Exchange (TSE) industries, specifically banking, insurance, and e-commerce, to evaluate their respective market structures.FindingsThe results indicate that financial industries tend to be closer to perfect competition compared to other market structures. Additionally, a comparative analysis of the status of these industries in relation to each other reveals that the banking and the e-commerce industries exhibit characteristics of monopolistic competition, whereas the insurance industry aligns more closely with perfect competition. This study provides useful insights into player behavior and its implications for financial policy, aiding in market analysis and forecasting.Originality/valueThis research offers a novel approach by integrating game theory and fuzzy logic to analyze the structure of financial markets.