paper-with-me

홈 › Papers

Quantifying firm-level risks from nature deterioration

2025-01-24 · Ricardo Crisostomo

We estimate the loss of value that companies might suffer from nature overexploitation. We find that global equities shed 26.8% in a scenario of unabated nature decline, while the worst-performing firms lose ~75% of their value. Our risk framework considers five environmental hazards: biodiversity loss, land degradation, climate change, human population and nature capital. We also introduce two metrics to assess nature-related risks: a Country Degradation Index that tracks the damage caused by environmental hazards in specific territories, including nonlinear dynamics and tipping points; and a Nature Risk Score that summarizes the risk that companies face due to the decline of nature and its services.

📄 PDF Abstract BibTeX arXiv:2501.14391

Code (0)

등록된 구현이 없습니다.

Similar Papers 제목 키워드 기반

OpenIPDM: A Probabilistic Framework for Estimating the Deterioration and Effect of Interventions on Bridges

2022-01-20 · Zachary Hamida, Blanche Laurent, James-A. Goulet

This paper describes OpenIPDM software for modelling the deterioration process of infrastructures using network-scale visual inspection data. In addition to the deterioration state estimates, OpenIPDM provides functions …

EmoAgent: Assessing and Safeguarding Human-AI Interaction for Mental Health Safety

2025-04-13 · Jiahao Qiu, Yinghui He, Xinzhe Juan, Yimin Wang 외

The rise of LLM-driven AI characters raises safety concerns, particularly for vulnerable human users with psychological disorders. To address these risks, we propose EmoAgent, a multi-agent AI framework designed to evalu…

Quantifying Health Inequalities Induced by Data and AI Models

2022-04-24 · Honghan Wu, Minhong Wang, Aneeta Sylolypavan, Sarah Wild

AI technologies are being increasingly tested and applied in critical environments including healthcare. Without an effective way to detect and mitigate AI induced inequalities, AI might do more harm than good, potential…

Prognosis

Frequency-Scale Saliency for Spectral Descriptor Analysis in 3D Shape Retrieval

2026-06-05 · Jianru Shen arxiv

Classical spectral descriptors such as the Heat Kernel Signature and Wave Kernel Signature are widely used for non-rigid 3D shape retrieval, yet their failure modes remain poorly understood. We present a frequency-scale …

Are You Sure? Challenging LLMs Leads to Performance Drops in The FlipFlop Experiment

2023-11-14 · Philippe Laban, Lidiya Murakhovs'ka, Caiming Xiong, Chien-Sheng Wu

The interactive nature of Large Language Models (LLMs) theoretically allows models to refine and improve their answers, yet systematic analysis of the multi-turn behavior of LLMs remains limited. In this paper, we propos…