@article{marquez_barrios_vera_mendez_tolosa_zambrano_li_2023, title={A Perspective on The Synergistic Potential of Artificial Intelligence and Product-Based Learning Strategies in Biobased Materials Education}, volume={44}, ISSN={1749-7728}, url={http://dx.doi.org/10.1016/j.ece.2023.05.005}, DOI={10.1016/j.ece.2023.05.005}, abstractNote={The integration of product-based learning strategies in Materials in Chemical Engineering education is crucial for students to gain the skills and competencies required to thrive in the emerging circular bioeconomy. Traditional materials engineering education has often relied on a transmission teaching approach, in which students are expected to passively receive information from instructors. However, this approach has shown to be inadequate under the current circumstances, in which information is readily available and innovative tools such as artificial intelligence and virtual reality environments are becoming widespread (e.g., metaverse). Instead, we consider that a critical goal of education should be to develop aptitudes and abilities that enable students to generate solutions and products that address societal demands. In this work, we propose innovative strategies, such as product-based learning methods and GPT (Generative Pre-trained Transformer) artificial intelligence text generation models, to modify the focus of a Materials in Chemical Engineering course from non-sustainable materials to sustainable ones, aiming to address the critical challenges of our society. This approach aims to achieve two objectives: first to enable students to actively engage with raw materials and solve real-world challenges, and second, to foster creativity and entrepreneurship skills by providing them with the necessary tools to conduct brainstorming sessions and develop procedures following scientific methods. The incorporation of circular bioeconomy concepts, such as renewable resources, waste reduction, and resource efficiency into the curriculum provides a framework for students to understand the environmental, social, and economic implications in Chemical Engineering. It also allows them to make informed decisions within the circular bioeconomy framework, benefiting society by promoting the development and adoption of sustainable technologies and practices.}, journal={Education for Chemical Engineers}, publisher={Elsevier BV}, author={Marquez, Ronald and Barrios, Nelson and Vera, Ramon and Mendez, Maria E. and Tolosa, Laura and Zambrano, Franklin and Li, Yali}, year={2023}, month={May}, pages={164–180} }
 @article{li_huang_2022, title={Assessing the impact of public transfer payments on the vulnerability of rural households to healthcare poverty in China}, volume={22}, ISSN={["1472-6963"]}, DOI={10.1186/s12913-022-07604-3}, abstractNote={Abstract}, number={1}, journal={BMC HEALTH SERVICES RESEARCH}, author={Li, Yali and Huang, Lei}, year={2022}, month={Feb} }
 @article{li_zambrano_wang_marquez_2022, title={How China's Foreign Waste Ban Will Reshape the US Recycling Supply Chain: Economic and Environmental Considerations towards a Circular Economy Oriented Paper Recycling Industry}, volume={17}, ISSN={["1930-2126"]}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85134501507&partnerID=MN8TOARS}, DOI={10.15376/biores.17.2.3178-3201}, abstractNote={Until recently, China was the largest scrap and unsorted waste importer in the world. Chinese industries sorted the imported wastes and recovered plastic, paper, textiles, and metals, using them as raw materials for manufacturing processes. Since 2013, the Chinese government has imposed measures to ban the import of wastes, the latest one being the “National Sword” policy (fully deployed in January 2021), banning the import of unsorted and recycled wastes. As a result, collecting wastes and recyclables and sending them to China is no longer an option; this has drastically affected the recycling industry supply chain with considerable consequences. This study analyzed the development of Chinese foreign policies on the export of paper waste materials from the U.S. and their specific impact on the recovered paper recycling industry. The economic and environmental consequences of the policy on the U.S. paper recycling industry were analyzed using three scenarios: landfilling (as a baseline), incineration, and recycling. The CO2 emissions were estimated and then compared. It was found that recycling would result in the largest reduction in greenhouse gases. Although recycling was the best evaluated scenario, it has the greatest costs; therefore, possible solutions towards adding value to paper wastes were analyzed.}, number={2}, journal={BIORESOURCES}, author={Li, Yali and Zambrano, Franklin and Wang, Yuhan and Marquez, Ronald}, year={2022}, month={May}, pages={3178–3201} }
 @article{li_xiao_2020, title={Environmental Efficiency Assessment of the US Pulp and Paper Industry Using an SBM-DEA Model}, volume={15}, ISSN={["1930-2126"]}, DOI={10.15376/biores.15.4.7796-7814}, abstractNote={The pulp and paper industry contributes to the economic development of the U.S., producing goods that meet primary needs. However, this sector must operate in a balance with the environment to ensure ecological preservation. Proposing a non-radial slacks-based measure – data envelopment analysis (SBM-DEA) approach, this study assessed the environmental efficiency of the pulp and paper industry in the U.S. from 2015 to 2018. External environmental impacts and random interferences on efficiency assessment were explored by using a stochastic frontier approach (SFA) regression. This study revealed that the U.S. pulp and paper industry was highly non-eco-efficient in the period evaluated, presenting an average environmental efficiency value of 0.509. Also, it is suggested that a total of 2.967 million metric tons of CO2eq emissions were in excess of those that were estimated based on an assumption of perfect environmental efficiency from 2015 to 2018 in the U.S. pulp and paper Industry. Based on the analysis of input and output slacks and the external environmental factors which reflect the environmental features of each decision-making unit (DMU), these facilities should substantially reduce CO2eq emissions and enhance the resources-allocation efficiency for improving the environmental efficiency of the U.S. PPI.}, number={4}, journal={BIORESOURCES}, author={Li, Yali and Xiao, Jianhua}, year={2020}, month={Nov}, pages={7796–7814} }