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Improving the quality of fuel represents an effective solution to address the long-standing issue of engine emissions. This study adopts CeO2 and carbon nanotubes as additives, which are blended with neat diesel using a physicochemical method to produce nanofuel. The research investigated the combustion and emission performance of a high-pressure common rail four-cylinder engine under various operating conditions, utilizing different types of nanomaterials, nanoparticle sizes, and biofuel substitutes as variables. The outcomes of the study indicate superior performance of the nanofuel compared with neat diesel across all evaluated aspects. Notably, the size of the added particles directly influenced the beneficial enhancements achieved in diesel fuel. Additionally, the nanofuel containing carbon nanotubes demonstrated a greater improvement effect than the one incorporating CeO2. Furthermore, when compared with neat diesel, the combustion of carbon nanotubes (CNT) nanofuel at 100% load resulted in a notable 4.0% increase in brake thermal efficiency, coupled with reductions of 3.0% in brake specific fuel consumption and 8.8%, 4.4%, 4.9%, and 9.6% reductions, respectively, for carbon monoxide (CO), hydrocarbons (HC), nitrogen oxides (NOx), and smoke emissions. It is noteworthy that the incorporation of biofuel alternatives, such as biodiesel and ethanol, into nanofuels exhibited even further enhanced effects in terms of promoting combustion and reducing emissions. The findings of this study serve as an important reference for selecting suitable nanofuels tailored to meet diverse operational demands of engines. [ABSTRACT FROM AUTHOR]

Background: The rapid growth of web-based medical services has highlighted the significance of smart triage systems in helping patients find the most appropriate physicians. However, traditional triage methods often rely on department recommendations and are insufficient to accurately match patients' textual questions with physicians' specialties. Therefore, there is an urgent need to develop algorithms for recommending physicians., Objective: This study aims to develop and validate a patient-physician hybrid recommendation (PPHR) model with response metrics for better triage performance., Methods: A total of 646,383 web-based medical consultation records from the Internet Hospital of the First Affiliated Hospital of Xiamen University were collected. Semantic features representing patients and physicians were developed to identify the set of most similar questions and semantically expand the pool of recommended physician candidates, respectively. The physicians' response rate feature was designed to improve candidate rankings. These 3 characteristics combine to create the PPHR model. Overall, 5 physicians participated in the evaluation of the efficiency of the PPHR model through multiple metrics and questionnaires as well as the performance of Sentence Bidirectional Encoder Representations from Transformers and Doc2Vec in text embedding., Results: The PPHR model reaches the best recommendation performance when the number of recommended physicians is 14. At this point, the model has an F 1 -score of 76.25%, a proportion of high-quality services of 41.05%, and a rating of 3.90. After removing physicians' characteristics and response rates from the PPHR model, the F 1 -score decreased by 12.05%, the proportion of high-quality services fell by 10.87%, the average hit ratio dropped by 1.06%, and the rating declined by 11.43%. According to whether those 5 physicians were recommended by the PPHR model, Sentence Bidirectional Encoder Representations from Transformers achieved an average hit ratio of 88.6%, while Doc2Vec achieved an average hit ratio of 53.4%., Conclusions: The PPHR model uses semantic features and response metrics to enable patients to accurately find the physician who best suits their needs., (©Yingbin Zheng, Yunping Cai, Yiwei Yan, Sai Chen, Kai Gong. Originally published in JMIR Human Factors (https://humanfactors.jmir.org), 15.08.2024.)

Background: After the implementation of 2- and 3-child policies, the rising proportion of high-age and high-risk pregnancies put enormous pressure on maternal and child health (MCH) services for China. This populous nation with an increasing population flow imperatively required the support of large-scale information systems for management. Municipal MCH information systems were commonly applied in developed cities of eastern provinces in China. However, implementation of provincial MCH information systems in relatively low-income areas is lacking. In 2020, the implementation of a regional maternal and child information system (RMCIS) in Inner Mongolia filled this gap., Objective: This paper aimed to demonstrate the construction process and evaluate the implementation effect of an RMCIS in improving the regional MCH in Inner Mongolia., Methods: We conducted a descriptive study for the implementation of an RMCIS in Inner Mongolia. Based on the role analysis and information reporting process, the system architecture design had 10 modules, supporting basic health care services, special case management, health support, and administration and supervision. Five-color management was applied for pregnancy risk stratification. We collected data on the construction cost, key characteristics of patients, and use count of the main services from January 1, 2020, to October 31, 2022, in Inner Mongolia. Descriptive analysis was used to demonstrate the implementation effects of the RMCIS., Results: The construction and implementation of the RMCIS cost CNY 8 million (US $1.1 million), with a duration of 13 months. Between 2020 and 2022, the system recorded 221,772 registered pregnant women, with a 44.75% early pregnancy registry rate and 147,264 newborns, covering 278 hospitals and 225 community health care centers in 12 cities. Five-color management of high-risk pregnancies resulted in 76,975 (45.45%) pregnancies stratified as yellow (general risk), 36,627 (21.63%) as orange (relatively high risk), 156 (0.09%) as red (high risk), and 3888 (2.30%) as purple (infectious disease). A scarred uterus (n=28,159, 36.58%), BMI≥28 (n=14,164, 38.67%), aggressive placenta praevia (n=32, 20.51%), and viral hepatitis (n=1787, 45.96%) were the top factors of high-risk pregnancies (yellow, orange, red, and purple). In addition, 132,079 pregnancies, including 65,018 (49.23%) high-risk pregnancies, were registered in 2022 compared to 32,466 pregnancies, including 21,849 (67.30%) high-risk pregnancies, registered in 2020., Conclusions: The implementation of an RMCIS in Inner Mongolia achieved the provincial MCH data interconnection for basic services and obtained both social and economic benefits, which could provide valuable experience to medical administration departments, practitioners, and medical informatics constructors worldwide., (©Yiwei Yan, Congyan Xing, Jian Chen, Yingbin Zheng, Xiaobin Li, Yirong Liu, Zhanxiang Wang, Kai Gong. Originally published in JMIR Pediatrics and Parenting (https://pediatrics.jmir.org), 25.03.2024.)