Search

Your search keyword '"Li, Jinhui"' showing total 1,186 results
Start Over Author "Li, Jinhui" Search Limiters Available in Library Collection
1,186 results on '"Li, Jinhui"'

1. Ambient air pollution and urological cancer risk: A systematic review and meta-analysis of epidemiological evidence.

Author

Li, Jinhui, Deng, Zhengyi, Soerensen, Simon, Kachuri, Linda, Cardenas, Andres, Graff, Rebecca, Leppert, John, Langston, Marvin, and Chung, Benjamin

Subjects
Humans, Air Pollution, Urologic Neoplasms, Particulate Matter, Male, Air Pollutants, Environmental Exposure, Risk Factors, Urinary Bladder Neoplasms, Kidney Neoplasms, Prostatic Neoplasms, Female
Abstract

Exposure to ambient air pollution has significant adverse health effects; however, whether air pollution is associated with urological cancer is largely unknown. We conduct a systematic review and meta-analysis with epidemiological studies, showing that a 5 μg/m3 increase in PM2.5 exposure is associated with a 6%, 7%, and 9%, increased risk of overall urological, bladder, and kidney cancer, respectively; and a 10 μg/m3 increase in NO2 is linked to a 3%, 4%, and 4% higher risk of overall urological, bladder, and prostate cancer, respectively. Were these associations to reflect causal relationships, lowering PM2.5 levels to 5.8 μg/m3 could reduce the age-standardized rate of urological cancer by 1.5 ~ 27/100,000 across the 15 countries with the highest PM2.5 level from the top 30 countries with the highest urological cancer burden. Implementing global health policies that can improve air quality could potentially reduce the risk of urologic cancer and alleviate its burden.

Published
2024

2. MTRGL:Effective Temporal Correlation Discerning through Multi-modal Temporal Relational Graph Learning

Author

Su, Junwei, Wu, Shan, and Li, Jinhui

Subjects
Computer Science - Machine Learning, Economics - General Economics, Quantitative Finance - Trading and Market Microstructure
Abstract

In this study, we explore the synergy of deep learning and financial market applications, focusing on pair trading. This market-neutral strategy is integral to quantitative finance and is apt for advanced deep-learning techniques. A pivotal challenge in pair trading is discerning temporal correlations among entities, necessitating the integration of diverse data modalities. Addressing this, we introduce a novel framework, Multi-modal Temporal Relation Graph Learning (MTRGL). MTRGL combines time series data and discrete features into a temporal graph and employs a memory-based temporal graph neural network. This approach reframes temporal correlation identification as a temporal graph link prediction task, which has shown empirical success. Our experiments on real-world datasets confirm the superior performance of MTRGL, emphasizing its promise in refining automated pair trading strategies.

Published
2024

5. Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle

Author

Yang, Xu, Yang, Xiao, Liu, Weiqing, Li, Jinhui, Yu, Peng, Ye, Zeqi, and Bian, Jiang

Subjects
Computer Science - Artificial Intelligence, Quantitative Finance - General Finance
Abstract

In the wake of relentless digital transformation, data-driven solutions are emerging as powerful tools to address multifarious industrial tasks such as forecasting, anomaly detection, planning, and even complex decision-making. Although data-centric R&D has been pivotal in harnessing these solutions, it often comes with significant costs in terms of human, computational, and time resources. This paper delves into the potential of large language models (LLMs) to expedite the evolution cycle of data-centric R&D. Assessing the foundational elements of data-centric R&D, including heterogeneous task-related data, multi-facet domain knowledge, and diverse computing-functional tools, we explore how well LLMs can understand domain-specific requirements, generate professional ideas, utilize domain-specific tools to conduct experiments, interpret results, and incorporate knowledge from past endeavors to tackle new challenges. We take quantitative investment research as a typical example of industrial data-centric R&D scenario and verified our proposed framework upon our full-stack open-sourced quantitative research platform Qlib and obtained promising results which shed light on our vision of automatic evolving of industrial data-centric R&D cycle., Comment: 29 pages, 11 figures

Published
2023

7. Supply of Key Metals for China’s New Energy Industries under the Carbon Peaking and Carbon Neutrality Goals

Author

Liang Yangyang, Liu Lili, He Kebin, Huang Fei, Moisés Gómez, and Li Jinhui

Subjects
emerging solid waste, wind turbines, photovoltaic modules, key metal, supply risk, Engineering (General). Civil engineering (General), TA1-2040
Abstract

New energy industries, such as wind and photovoltaic (PV) power generation, are key to supporting the carbon peaking and carbon neutrality goals of China. The installed capacity of wind and PV power in China is the largest worldwide; therefore, it is necessary to secure the supply of key metal materials and conduct a more accurate management of emerging solid wastes. This study sets different development scenarios based on the historical data and planning objectives of wind and PV power industries of China. It assesses the demand, waste, and supply of key metals in China’s new energy industry using a life distribution model of wind and PV power generation equipment, and focuses on identifying the supply pressure of silver, copper, gallium, silver, steel, and neodymium,thereby providing a basic support for realizing the green and low-carbon development of the energy industry by 2060. In the baseline scenario, the decommissioned volume of the wind and PV power generation industries will reach 4.6 GW and 28.3 GW in 2035,respectively; and the total decommissioned volume (by mass) of both wind and PV power generation equipment will reach 2.54 ×106 t and 1.048 ×107 t in 2035 and 2060, respectively. In terms of the supply of key metals for the new energy industry during 2030‒2060,iron and steel have a low supply risk (≤5%), neodymium has a medium-high supply risk (25%‒50%), copper and silver have a high supply risk (50%‒100%), and the supply of gallium and indium are at an extremely high risk owing to their excessive peak demand.To improve the security and diversity of the supply chain of the new energy industry, it is necessary to ensure the sustainable supply of metal mineral resources and promote material recycling and efficient use. Furthermore, we propose the following recommendations:(1) treating decommissioned equipment for wind and PV power generation as waste electrical and electronic products, (2) incorporating wind and PV power generation enterprises into the Catalogue of Classified Management of Pollutant Discharge Permits for Stationary Pollution Sources, (3) improving the distributed new-energy solid-waste recycling system, and (4) developing recycling technologies for emerging solid wastes.

Published
2024
Full Text
View/download PDF

9. Macro carbon price prediction with support vector regression and Paris accord targets

Author

Li, Jinhui

Subjects
Quantitative Finance - General Finance, Economics - General Economics, Statistics - Applications
Abstract

Carbon neutralization is an urgent task in society because of the global warming threat. And carbon trading is an essential market mechanics to solve carbon reduction targets. Macro carbon price prediction is vital in the useful management and decision-making of the carbon market. We focus on the EU carbon market and we choose oil price, coal price, gas price, and DAX index to be the four market factors in predicting carbon price, and also we select carbon emission targets from Paris Accord as the political factor in the carbon market in terms of the macro view of the carbon price prediction. Thus we use these five factors as inputs to predict the future carbon yearly price in 2030 with the support vector regression models. We use grid search and cross validation to guarantee the prediction performance of our models. We believe this model will have great applications in the macro carbon price prediction.

Published
2022

11. Reshaping global policies for circular economy

Author

Zeng, Xianlai, Ogunseitan, Oladele A, Nakamura, Shinichiro, Suh, Sangwon, Kral, Ulrich, Li, Jinhui, and Geng, Yong

Subjects
Responsible Consumption and Production
Published
2022

20. Effect of citric acid on properties of (3-mercaptopropyl)trimethoxysilane modified xylan/polyvinyl alcohol composite film

Author

LI Jinhui, WANG Yining, YANG Sixia, WANG Haisong, and LYU Yanna

Subjects
citric acid, xylan, polyvinyl alcohol, crosslinking agent, composite film, Materials of engineering and construction. Mechanics of materials, TA401-492
Abstract

In order to improved the defects of xylan-based films such as strong hygroscopicity and low mechanical strength, a collaborative modification protocol of citric acid (CA) and MPTMS-modified xylan (MSMX) was proposed. Xylan from sugarcane bagasse was firstly modified by (3-mercaptopropyl)trimethoxysilane (MPTMS), and then citric acid was used as crosslinking agent or plasticizer. The MSMX/PVA/CA films were prepared by casting method and the effects of citric acid content on the structure and packaging performance of the composite film were studied. The results show that with the increase of CA content, the cross-linking degree of MSMX/PVA/CA films increases and the internal structure becomes more dense, which lead to the significant enhancement of mechanical properties and water vapor barrier performance. Meanwhile, the hydrophobicity of the MSMX/PVA/CA films is improved with the decrease of hydrophilice groups. When CA content is 20% (mass fraction), the tensile strength of MSMX/PVA/CA film is 41.8 MPa, water contact angle is 82°, and the water vapor transmittance reaches 2.79×10-13 g·cm·cm-2·s-1·Pa-1, which is 37.79% lower than that of film without CA. The addition of CA improves the moisture barrier properties and mechanical strength of xylan composite films, which makes it have a potential application in the field of food and drug packaging.

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results