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An insight into nanocellulose as soft condensed matter: Challenge and future prospective toward environmental sustainability

Tan K, Heo S, Foo M, Chew IM, Yoo C

Sci Total Environ, 2019 Feb 10;650(Pt 1):1309-1326.
PMID: 30308818 DOI: 10.1016/j.scitotenv.2018.08.402

Nanocellulose, a structural polysaccharide that has caught tremendous interests nowadays due to its renewability, inherent biocompatibility and biodegradability, abundance in resource, and environmental friendly nature. They are promising green nanomaterials derived from cellulosic biomass that can be disintegrated into cellulose nanofibrils (CNF) or cellulose nanocrystals (CNC), relying on their sensitivity to hydrolysis at the axial spacing of disordered domains. Owing to their unique mesoscopic characteristics at nanoscale, nanocellulose has been widely researched and incorporated as a reinforcement material in composite materials. The world has been consuming the natural resources at a much higher speed than the environment could regenerate. Today, as an uprising candidate in soft condensed matter physics, a growing interest was received owing to its unique self-assembly behaviour and quantum size effect in the formation of three-dimensional nanostructured material, could be utilised to address an increasing concern over global warming and environmental conservation. In spite of an emerging pool of knowledge on the nanocellulose downstream application, that was lacking of cross-disciplinary study of its role as a soft condensed matter for food, water and energy applications toward environmental sustainability. Here we aim to provide an insight for the latest development of cellulose nanotechnology arises from its fascinating physical and chemical characteristic for the interest of different technology holders.
Smart solutions for clean air: An AI-guided approach to sustainable industrial pollution control in coal-fired power plant

Lim JY, Teng SY, How BS, Loy ACM, Heo S, Jansen J, et al.

Environ Pollut, 2023 Oct 15;335:122335.
PMID: 37558197 DOI: 10.1016/j.envpol.2023.122335

Conventional fossil fuels are relied on heavily to meet the ever-increasing demand for energy required by human activities. However, their usage generates significant air pollutant emissions, such as NOx, SOx, and particulate matter. As a result, a complete air pollutant control system is necessary. However, the intensive operation of such systems is expected to cause deterioration and reduce their efficiency. Therefore, this study evaluates the current air pollutant control configuration of a coal-powered plant and proposes an upgraded system. Using a year-long dataset of air pollutants collected at 30-min intervals from the plant's telemonitoring system, untreated flue gas was reconstructed with a variational autoencoder. Subsequently, a superstructure model with various technology options for treating NOx, SOx, and particulate matter was developed. The most sustainable configuration, which included reburning, desulfurization with seawater, and dry electrostatic precipitator, was identified using an artificial intelligence (AI) model to meet economic, environmental, and reliability targets. Finally, the proposed system was evaluated using a Monte Carlo simulation to assess various scenarios with tightened discharge limits. The untreated flue gas was then evaluated using the most sustainable air pollutant control configuration, which demonstrated a total annual cost, environmental quality index, and reliability indices of 44.1 × 106 USD/year, 0.67, and 0.87, respectively.
Fulltext Development and Asian-wide validation of the Grade for Interpretable Field Triage (GIFT) for predicting mortality in pre-hospital patients using the Pan-Asian Trauma Outcomes Study (PATOS)

Yu JY, Heo S, Xie F, Liu N, Yoon SY, Chang HS, et al.

Lancet Reg Health West Pac, 2023 May;34:100733.
PMID: 37283981 DOI: 10.1016/j.lanwpc.2023.100733

BACKGROUND: Field triage is critical in injury patients as the appropriate transport of patients to trauma centers is directly associated with clinical outcomes. Several prehospital triage scores have been developed in Western and European cohorts; however, their validity and applicability in Asia remains unclear. Therefore, we aimed to develop and validate an interpretable field triage scoring systems based on a multinational trauma registry in Asia.
METHODS: This retrospective and multinational cohort study included all adult transferred injury patients from Korea, Malaysia, Vietnam, and Taiwan between 2016 and 2018. The outcome of interest was a death in the emergency department (ED) after the patients' ED visit. Using these results, we developed the interpretable field triage score with the Korea registry using an interpretable machine learning framework and validated the score externally. The performance of each country's score was assessed using the area under the receiver operating characteristic curve (AUROC). Furthermore, a website for real-world application was developed using R Shiny.
FINDINGS: The study population included 26,294, 9404, 673 and 826 transferred injury patients between 2016 and 2018 from Korea, Malaysia, Vietnam, and Taiwan, respectively. The corresponding rates of a death in the ED were 0.30%, 0.60%, 4.0%, and 4.6% respectively. Age and vital sign were found to be the significant variables for predicting mortality. External validation showed the accuracy of the model with an AUROC of 0.756-0.850.
INTERPRETATION: The Grade for Interpretable Field Triage (GIFT) score is an interpretable and practical tool to predict mortality in field triage for trauma.
FUNDING: This research was supported by a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (Grant Number: HI19C1328).

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