Advancements in Polymer-Assisted Layer-by-Layer Fabrication of Wearable Sensors for Health Monitoring.

Recent advancements in polymer-assisted layer-by-layer (LbL) fabrication have revolutionized the development of wearable sensors for health monitoring. LbL self-assembly has emerged as a powerful and versatile technique for creating conformal, flexible, and multi-functional films on various substrates, making it particularly suitable for fabricating wearable sensors. The incorporation of polymers, both natural and synthetic, has played a crucial role in enhancing the performance, stability, and biocompatibility of these sensors. This review provides a comprehensive overview of the principles of LbL self-assembly, the role of polymers in sensor fabrication, and the various types of LbL-fabricated wearable sensors for physical, chemical, and biological sensing. The applications of these sensors in continuous health monitoring, disease diagnosis, and management are discussed in detail, highlighting their potential to revolutionize personalized healthcare. Despite significant progress, challenges related to long-term stability, biocompatibility, data acquisition, and large-scale manufacturing are still to be addressed, providing insights into future research directions. With continued advancements in polymer-assisted LbL fabrication and related fields, wearable sensors are poised to improve the quality of life for individuals worldwide.

Geographic and gender disparities in global education achievement during the COVID-19 pandemic.

School closures induced by the COVID-19 pandemic have negatively impacted on 1.7 billion children, resulting in losses of learning time and a decline of learning scores. However, the learning losses of students exposed to the COVID-19 pandemic at the country level have been quantitatively unaddressed. Here we model the global learning losses of students due to the COVID-19 in 2020. Our results reveal a global average Harmonized Test Scores (HTS) loss of 2.26 points. Learning continuity measures reduce the global average HTS loss by 1.64 points. South Asia and Sub-Saharan Africa have high HTS losses (5.82 and 2.94 points), while Europe & Central Asia and North America have low HTS losses (0.85 and 0.93 points). Compared with South Asia and Sub-Saharan Africa, North America and Europe & Central Asia implement more effective learning continuity measures. HTS losses in low-income and lower-middle-income countries are higher (3.35 and 3.13 points) than those in high-income and upper-middle-income countries (0.99 and 2.31 points). Learning losses of global female students are higher than their male counterparts, and there is significant heterogeneity across national regions. Our results reveal both global learning losses and gender inequality in learning scores due to the COVID-19 pandemic. Global disparities highlight the importance of the need to mitigate education inequality.

Low-cost smartphone-based LIBS combined with deep learning image processing for accurate lithology recognition.

A low-cost and multi-channel smartphone-based spectrometer was developed for LIBS. As the CMOS detector is two-dimensional, simultaneous multichannel detection was achieved by coupling a linear array of fibres for light collection. Thus, besides the atomic information, the spectral images containing the propagation and spatial distribution characters of a laser induced plasma plume could be recorded. With these additional features, accurate rock type prediction was achieved by processing the raw data directly through a deep learning model.

Performance evaluation of medical service for breast cancer patients based on diagnosis related groups.

BACKGROUND: To evaluate the performance of medical service for patients with breast cancer in Henan Province, China, using diagnosis related groups (DRGs) indicators and to provide data to inform practices and policies for the prevention and control of breast cancer. METHODS: The data were collected from the front pages of medical records (FPMR) of all hospitals above class II that admitted breast cancer patients in Henan Province between 2016 and 2019. Breast cancer patients were the subjects in our study. China DRGs (CN-DRGs) was used as a risk adjustment tool. Three indicators, including the case mix index (CMI), number of DRGs, and total weight, were used to evaluate the range of available services for patients with breast cancer, while indicators including the charge efficiency index (CEI), time efficiency index (TEI) and inpatient mortality of low-risk group cases (IMLRG) were used to evaluate medical service efficiency and medical safety. RESULTS: Between 2016 and 2019, there were 103,760 patients with breast cancer. The total weight increased over the study period at an average annual rate of 21.71%. The TEI decreased over the study period by 15.60%. The CEI exhibited an increasing trend, but the average annual rate of increase was small (2.94%). The IMLRP was 0.02, 0, 0 and 0.01% in 2016, 2017, 2018 and 2019, respectively. CONCLUSION: The performance of medical service improved between 2016 and 2019 for breast cancer patients discharged from study hospitals in Henan Province. The main area of improvement was in the range of available services, but medical institutions must still make efforts to improve the efficiency of medical services and ensure medical safety. DRGs is an effective evaluation tool.

Standardization of Type 2 Diabetes Outpatient Expenditure with Bundled Payment Method in China.

BACKGROUND: In recent years, the prevalence of type 2 diabetes among Chinese population has been increasing by years, directly leading to an average annual growth rate of 19.90% of medical expenditure. Therefore, it is urgent to work on strategies to control the growth of medical expenditure on type 2 diabetes on the basis of the reality of China. Therefore, in this study, we explored the feasibility of implementing bundled payment in China through analyzing bundled payment standards of type 2 diabetes outpatient services. METHODS: This study analyzed the outpatient expenditure on type 2 diabetes with Beijing Urban Employee's Basic Medical Insurance from 2010 to 2012. Based on the analysis of outpatient expenditure and its influential factors, we adopted decision tree approach to conduct a case-mix analysis. In the end, we built a case-mix model to calculate the standard expenditure and the upper limit of each combination. RESULTS: We found that age, job status, and whether with complication were significant factors that influence outpatient expenditure for type 2 diabetes. Through the analysis of the decision tree, we used six variables (complication, age, diabetic foot, diabetic nephropathy, cardiac-cerebrovascular disease, and neuropathy) to group the cases, and obtained 11 case-mix groups. CONCLUSIONS: We argued that it is feasible to implement bundled payment on type 2 diabetes outpatient services. Bundled payment is effective to control the increase of outpatient expenditure. Further improvements are needed for the implementation of bundled payment reimbursement standards, together with relevant policies and measures.