Application and Research Progress of Heat Pipe in Thermal Management of Lithium-Ion Battery

Lithium-ion batteries have the advantages of high energy density, high average output voltage, long service life, and environmental protection, and are widely used in the power system of new energy vehicles. However, during the working process of the battery, the working temperature is too high or too low, which will affect the charging and discharging performance, battery capacity and battery safety. As a result, a battery thermal management system (BTMS) is essential to maintain the proper ambient temperature of the working battery. Thermal management of power batteries is a key technology to ensure maximum battery safety and efficiency. This paper discusses the significance of thermal management technology in the development of new energy vehicles, introduces the main technical means of thermal management of lithium-ion batteries for vehicle, and focuses on the current state of research on the use of various types of heat pipes in lithium-ion batteries. Finally, the use of heat pipes in the thermal control of lithium-ion batteries is promising.Citation: Ning, Y., Tao, R., Luo, J., and Hu, Q. (2022). Application and Research Progress of Heat Pipe in Thermal Management of Lithium-Ion Battery. Trends in Renewable Energy, 8, 130-144. DOI: 10.17737/tre.2022.8.2.0014

A roadmap to fair and trustworthy prediction model validation in healthcare

A prediction model is most useful if it generalizes beyond the development data with external validations, but to what extent should it generalize remains unclear. In practice, prediction models are externally validated using data from very different settings, including populations from other health systems or countries, with predictably poor results. This may not be a fair reflection of the performance of the model which was designed for a specific target population or setting, and may be stretching the expected model generalizability. To address this, we suggest to externally validate a model using new data from the target population to ensure clear implications of validation performance on model reliability, whereas model generalizability to broader settings should be carefully investigated during model development instead of explored post-hoc. Based on this perspective, we propose a roadmap that facilitates the development and application of reliable, fair, and trustworthy artificial intelligence prediction models.Comment: 12 pages, 2 figure

Hepatitis E Virus Genotype Diversity in Eastern China

We studied 47 hepatitis E virus (HEV) isolates from hospitalized patients in Nanjing and Taizhou, eastern China. Genotypes 1, 3, and 4 were prevalent; genotype 3 and subgenotype 4b showed a close relationship with the swine strains in eastern China, thus indicating that HEV genotype 3 had infected humans in China

Federated and distributed learning applications for electronic health records and structured medical data: A scoping review

Federated learning (FL) has gained popularity in clinical research in recent years to facilitate privacy-preserving collaboration. Structured data, one of the most prevalent forms of clinical data, has experienced significant growth in volume concurrently, notably with the widespread adoption of electronic health records in clinical practice. This review examines FL applications on structured medical data, identifies contemporary limitations and discusses potential innovations. We searched five databases, SCOPUS, MEDLINE, Web of Science, Embase, and CINAHL, to identify articles that applied FL to structured medical data and reported results following the PRISMA guidelines. Each selected publication was evaluated from three primary perspectives, including data quality, modeling strategies, and FL frameworks. Out of the 1160 papers screened, 34 met the inclusion criteria, with each article consisting of one or more studies that used FL to handle structured clinical/medical data. Of these, 24 utilized data acquired from electronic health records, with clinical predictions and association studies being the most common clinical research tasks that FL was applied to. Only one article exclusively explored the vertical FL setting, while the remaining 33 explored the horizontal FL setting, with only 14 discussing comparisons between single-site (local) and FL (global) analysis. The existing FL applications on structured medical data lack sufficient evaluations of clinically meaningful benefits, particularly when compared to single-site analyses. Therefore, it is crucial for future FL applications to prioritize clinical motivations and develop designs and methodologies that can effectively support and aid clinical practice and research

Associations between early-life screen viewing and 24 hour movement behaviours : findings from a longitudinal birth cohort study

Background Screen viewing is a sedentary behaviour reported to interfere with sleep and physical activity. However, few longitudinal studies have assessed such associations in children of preschool age (0-6 years) and none have accounted for the compositional nature of these behaviours. We aimed to investigate the associations between total and device-specific screen viewing time at age 2-3 years and accelerometer-measured 24 h movement behaviours, including sleep, sedentary behaviour, light physical activity, and moderate-to-vigorous physical activity (MVPA) at age 5.5 years. Methods The Growing Up in Singapore Towards healthy Outcomes (GUSTO) study is an ongoing longitudinal birth cohort study in Singapore, which began in June 2009. We recruited pregnant women during their first ultrasound scan visit at two major public maternity units in Singapore. At clinic visits done at age 2-3 years, we collected parent-reported information about children's daily total and device-specific screen viewing time (television, handheld devices, and computers). At 5.5 years, children's movement behaviours for 7 consecutive days were measured using wrist-worn accelerometers. We assessed the associations between screen viewing time and movement behaviours (sedentary behaviour, light physical activity, MVPA, and sleep) using Dirichlet regression, which accounts for the compositional nature of such behaviours. This study is active but not recruiting and is registered with ClinicalTrials.gov, NCT01174875. Findings Between June 1, 2009, and Oct 12, 2010, 1247 pregnant women enrolled and 1171 singleton births were enrolled. 987 children had parent-reported screen data at either 2 or 3 years, of whom 840 attended the clinic visit at age 5.5 years, and 577 wore an accelerometer. 552 children had at least 3 days of accelerometer data and were included in the analysis. Total screen viewing time at age 2-3 years had a significant negative association with sleep (p=0.008), light physical activity (p= 3 h screen viewing time]), and less light physical activity (384.6 vs 356.2 mins per day), and MVPA (76.2 vs 63.4 mins per day) at age 5.5 years. No significant differences in time spent sleeping were observed between the groups (539.5 vs 540.4 mins per day). Similar trends were observed for television viewing and handheld device viewing. Interpretation Longer screen viewing time in children aged 2-3 years was associated with more time spent engaged in sedentary behaviour and shorter time engaged in light physical activity and MVPA in later childhood. Our findings indicate that screen viewing might displace physical activity during early childhood, and suggest that reducing screen viewing time in early childhood might promote healthier behaviours and associated outcomes later in life. Copyright (C) 2020 Elsevier Ltd. All rights reserved.Peer reviewe