Results 81 to 90 of about 141,957 (262)

Estimating Climate Risk Exposure in the U.S. Insurance Sector Using Factor Model and EVT

Mathematics
This study examines the exposure of the U.S. insurance sector to climate-related risks using a two-step approach combining factor modeling and Extreme Value Theory. The analysis first constructs a climate risk factor from transition-sensitive sectors and
Olanrewaju Oluwadamilare Olaniyan
doaj   +1 more source

ChicGrasp: Imitation‐Learning‐Based Customized Dual‐Jaw Gripper Control for Manipulation of Delicate, Irregular Bio‐Products

Advanced Robotics Research, EarlyView.
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar, Zhengtong Xu, Siavash Mahmoudi, Pouya Sohrabipour, Chaitanya Pallerla, Yu She, Wan Shou, Philip Glen Crandall, Dongyi Wang   +8 more
wiley   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

Advanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source

Cross‐Scale Hierarchical Targeted Delivery System Based on Small‐Scale Magnetic Robots

Advanced Robotics Research, EarlyView.
This article reviews a cross‐scale hierarchical targeted delivery system that integrates magnetic continuum robots and magnetic microrobots. By combining rapid long‐range navigation with precise microscale targeting, the system overcomes key limitations of single‐scale approaches.
Junjian Zhou, Zhiqiang Chen, Yuanbiao Ma, Zhiqiang Tang, Qianqian Wang   +4 more
wiley   +1 more source

On multivariate extensions of the conditional Value-at-Risk measure

Insurance: Mathematics and Economics, 2015
CoVaR is a systemic risk measure proposed by Adrian and Brunnermeier (2011) able to measure a financial institution’s contribution to systemic risk and its contribution to the risk of other financial institutions. CoVaR stands for conditional Value-at-Risk, i.e. it indicates the Value at Risk for a financial institution that is conditional on a certain
Di Bernardino, Elena, Fernández Ponce, E., Palacios Rodríguez, Fátima, Rodríguez Griñolo, María del Rosario   +3 more
openaire   +3 more sources

DRIVE‐SAFE: Data‐Driven Robustness and Informed Validation for Evolving Specifications via Formal Evaluation

Advanced Robotics Research, EarlyView.
DRIVE‐SAFE evaluates learning‐based, black‐box autonomous driving policies against evolving temporal safety requirements using Signal Temporal Logic robustness metrics. It aggregates distributional robustness measures with domain‐informed weights to guide iterative retraining.
Kristy Sakano, Jianyu An, Dinesh Manocha, Huan Xu   +3 more
wiley   +1 more source

Value-at-Risk da Carteira do Ibovespa: uma análise com o uso de modelos de memória longa Value-at-Risk for Ibovespa: an analysis using long memory models

Gestão & Produção, 2012
O presente estudo propõe uma análise comparativa de dez modelos de volatilidade para o cálculo do Value-at-Risk (VaR) para carteira teórica do Ibovespa, considerando a presença de memória longa na série temporal dos seus retornos diários.
Luiz Eduardo Gaio, Tabajara Pimenta Júnior   +1 more
doaj   +1 more source

Robust conditional variance estimation and value-at-risk

The Journal of Risk, 2001
A common approach to estimating the conditional volatility of short horizon asset returns is to use an exponentially weighted moving average (EWMA) of squared past returns. The EWMA estimator is based on the maximum likelihood estimator of the variance of the normal distribution, and is thus optimal when returns are conditionally normal. However, there
Harris, Richard D F, Guermat, Cherif
openaire   +2 more sources

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Inhibition of IGFBP4 in Granulosa Cells Improves Reproductive Performance and Maintains Fertility With Age via YAP Signaling

Advanced Science, EarlyView.
IGFBP4 is upregulated in granulosa cells of aged ovaries across monkeys, mice, and humans. It inhibits YAP signaling, thereby suppressing cell proliferation and contributing to follicular dysfunction. Deletion of Igfbp4 in granulosa cells enhances ovulatory output, improves hormone profiles, and reproductive performance in aged female mice, suggesting ...
Qianhui Hu, Ajun Geng, Ziyuan Li, Fanghao Guo, Jingqiang Wang, Xinyi Chen, Meiling Zhang, Yi Arial Zeng, Wen Li   +8 more
wiley   +1 more source