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Background China has one of the fastest paces of the growing aging population, High-level policymakers have recently recognized the aging population presents significant challenges to the Chinese healthcare system. In this context, the healthcare-seeking behaviors of the elderly population have become an essential field of study. It is necessary to understand their access to health services and to improve their quality of life, as well as to help policymakers to formulate healthcare policy. The study empirically investigates the factors influencing the elderly population’s healthcare-seeking behaviors in Shanghai, China, especially in choosing the quality of healthcare facilities to visit. Methods We designed a cross-sectional study. The data of this study were derived from the “Shanghai elderly medical demand characteristics questionnaire” in the middle of November to early December 2017. A total of 625 individuals were included in the final sample. Logistic regression was adopted to investigate the differences in healthcare-seeking behaviors between elderly people when suffer from mild illness, severe illness and follow-up treatment. Next, the differences in gender were also discussed. Results Factors affecting the healthcare-seeking behaviors of the elderly differ in mild illness and severe illness situations. For mild illness, demographic factors (gender and age) and socioeconomic factors (income and employment) play an important role in elderly healthcare choices. Female and older elderlies are more likely to choose local, lower-quality facilities, whereas those with high income and private employment are more likely to choose higher-quality facilities. For severe illness, socioeconomic factors (income and employment) are important. Furthermore, individuals with basic medical insurance are more likely to choose lower-quality facilities. Conclusion This study has shown that the affordability of public health services should be addressed. Medical policy support may be an important way to reduce the gap in access to medical services. We should pay attention to the gender differences in the elderly’s choice of medical treatment behavior, consider the differences in the needs of male and female elderly. our findings are only for elderly Chinese participants in the greater Shanghai area.

Photovoltaic panels are the core components of photovoltaic power generation systems, and their quality directly affects power generation efficiency and circuit safety. To address the shortcomings of existing photovoltaic defect detection technologies, such as high labor costs, large workloads, high sensor failure rates, low reliability, high false alarm rates, high network demands, and slow detection speeds of traditional algorithms, we propose an algorithm named ST-YOLO specifically for photovoltaic module defect detection. This algorithm is based on YOLOv8s. First, it introduces the C2f-SCconv convolution module, which is based on SCconv convolution. This module reduces the computational burden of model parameters and improves detection speed through lightweight design. Additionally, the Triplet Attention mechanism is incorporated, significantly enhancing detection accuracy without substantially increasing model parameter computations. Experiments on a self-built photovoltaic array infrared defect image dataset show that ST-YOLO, compared to the baseline YOLOv8s, achieves a 15% reduction in model weight, a 2.9% improvement in Precision, and a 1.4% increase in mAP@0.5. Compared to YOLOv7-Tiny and YOLOv5s, ST-YOLO also demonstrates superior detection performance and advantages. This indicates that ST-YOLO has significant application value in photovoltaic defect detection.

Under the challenge of global energy transition, coal-fired cogeneration systems are undergoing a technical revolution towards enhanced efficiency, heating capacity, and flexibility. In this paper, four schemes using a steam ejector integrated into a cogeneration system are designed. Considering operational safety, integrated locations are selected at the front and back of high- and medium-pressure turbines. Subsequently, the thermodynamic and operational characteristics under both design and off-design conditions are analyzed based on a model built in EBSILON Professional. Finally, a sensitivity analysis of the heating process is conducted. The results show that the integration of steam ejectors can increase the waste heat recovery ratio of exhaust steam by 18.42–45.61% under design conditions. The largest waste heat recovery ratio is obtained in System 4, resulting in the power generation efficiency (ηg) and gross energy utilization efficiency (ηp) of 81.95% and 65.53%, respectively. Meanwhile, the steam ejector can expand the power-load regulation range of the cogeneration system, and System 4 has the lowest lower power limit among all the systems. The ηp values of Systems 1–4 reach extreme values at different mixed steam pressures of the ejector. Increasing the pinch point temperature difference reduces the power load ηg and ηp of Systems 1–4. The results provide technical solutions for improving the heating capacity and efficient and flexible operation of cogeneration systems.

High-performance and low-power field-effect transistors (FETs) are the basis of integrated circuit fields, which undoubtedly require researchers to find better film channel layer materials and improve device structure technology. MoS2 has recently shown a special two-dimensional (2D) structure and superior photoelectric performance, and it has shown new potential for next-generation electronics. However, the natural atomic layer thickness and large specific surface area of MoS2 make the contact interface and dielectric interface have a great influence on the performance of MoS2 FET. Thus, we focus on its main performance improvement strategies, including optimizing the contact behavior, regulating the conductive channel, and rationalizing the dielectric layer. On this basis, we summarize the applications of 2D MoS2 FETs in key and emerging fields, specifically involving logic, RF circuits, optoelectronic devices, biosensors, piezoelectric devices, and synaptic transistors. As a whole, we discuss the state-of-the-art, key merits, and limitations of each of these 2D MoS2-based FET systems, and prospects in the future.

Key message RsMYB1a was the crucial MYB, and RsbHLH4 is the essential partner in regulating the anthocyanin biosynthesis in radish. There are four color types of radish according to whether or not the anthocyanin accumulates in the skin and flesh of taproot. Red radishes accumulate a substantial amount of anthocyanins in both the skin and flesh. It is well known that the MYB-bHLH-WD40 transcription factor(s) complex regulates the biosynthesis of anthocyanin in plants. Here in, four candidate MYB and bHLH genes, RsMYB1a , RsMYB1b , RsbHLH2 and RsbHLH4 , were isolated from red radish ‘Hongxin 1’. The expression of RsbHLH4 and the two structural genes RsANS and RsUFGT was significantly positively correlated with anthocyanin contents. The expression of RsMYB1a was also highly correlated with anthocyanin accumulation, particularly when the white flesh sample of ‘Hongxin 1-1’ was excluded. The transient expression of RsMYB1a in the radish cotyledon and leaf induced anthocyanin accumulation with even stronger promoting role when expression in combination with RsbHLH4 . These results suggested that RsMYB1a was the crucial MYB, and that RsbHLH4 is an essential partner in regulating the biosynthesis of anthocyanins in radish. The low or undetectable RsbHLH4 expression paralleled the lack of anthocyanin accumulation in the white flesh of ‘Hongxin 1-1’ and ‘Shaguan 1’. Assays demonstrated that RsMYB1a interacted with RsbHLH4 and activated the expression of RsbHLH4 . Notably, all the dark red radish cultivars have a longer RsMYB1a genomic DNA sequence, while the short and nonfunctional RsMYB1a is present in non-red cultivars. The length of the first intron and the presence of an early stop codon of RsMYB1 might underlie the differential anthocyanin accumulation in the radish taproot.

Mn-doped perovskite CsPb(Cl/Br)3 nanocrystals (NCs) have been widely explored due to their unique dual-color emission characteristics, which could reduce the usage of toxic Pb and introduce the exciton emission in blue region and the stable Mn2+ emission peak in orange-red region via energy transfer from exciton to Mn2+ emission. Although doping high concentration Mn2+ could increase the Mn2+ emission, excess Mn2+ ions would be expelled from the host perovskite lattice. Doping secondary metal Ni into the NCs as an efficient method is always used to improve the Mn2+ emission. We adopted a one-pot halogen injection into Cs-precursor under ambient environment method to prepare (Mn, Ni): CsPbCl3 and (Mn, Ni): CsPb(Cl/Br)3 NCs, which introduces NiCl2 in the Mn: CsPb(Cl/Br)3 NCs to supply enough halide ions and to passivate defect states or traps in the perovskite NCs so as to enhance Mn2+ emission. Density Functional Theory (DFT) calculations were also conducted to explain our experimental results, which revealed that Ni2+ doping could eliminate the in-gap deep defects of the CsPb(Cl/Br)3 nanocrystals. In addition, the passivated lattice defects help to improve the stability of the perovskite NCs, preventing from electron beam irradiation.

Pathological myopia is a major cause of blindness among people under 50 years old and can result in severe vision loss in extreme cases. Currently, its detection primarily relies on manual methods, which are slow and heavily dependent on the expertise of physicians, making them impractical for large-scale screening. To tackle these challenges, we propose SMLS-YOLO, an instance segmentation method based on YOLOv8n-seg. Designed for efficiency in large-scale screenings, SMLS-YOLO employs an extremely lightweight model. First, StarNet is introduced as the backbone of SMLS-YOLO to extract image features. Subsequently, the StarBlock from StarNet is utilized to enhance the C2f, resulting in the creation of the C2f-Star feature extraction module. Furthermore, shared convolution and scale reduction strategies are employed to optimize the segmentation head for a more lightweight design. Lastly, the model incorporates the Multi-Head Self-Attention (MHSA) mechanism following the backbone to further refine the feature extraction process. Experimental results on the pathological myopia dataset demonstrate that SMLS-YOLO outperforms the baseline YOLOv8n-seg by reducing model parameters by 46.9%, increasing Box mAP@0.5 by 2.4%, and enhancing Mask mAP@0.5 by 4%. Furthermore, when compared to other advanced instance segmentation and semantic segmentation algorithms, SMLS-YOLO also maintains a leading position, suggesting that SMLS-YOLO has promising applications in the segmentation of pathological myopia images.

The aim of this study was to establish a method for discriminating Dendrobium officinale from four of its close relatives Den- drobium chrysanthum, Dendrobium erystallinum, Dendrobium aphyllum and Dendrobium devonianum based on chemical composition analysis. We analyzed 62 samples of 24 Dendrobium species. High performance liquid chromatography analysis confirmed that the four low molecular weight compounds 4＇,5,7-trihydroxyflavanone （naringenin）, 3,4-dihydroxy-4＇,5-dime- tboxybibenzyl （DDB~2）, 3＇,4-dihydroxy-3,5＇-dimethoxybibenzyl （gigantol）, and 4,4＇-dihydroxy-3,3＇,5-trimethoxybibenzyl （moscatilin）, were common in the genus. The phenol-sulfuric acid method was used to quantify polysaccharides, and the mon- osaccharide composition of the polysaccharides was determined by gas chromatography. Stepwise discriminant analysis was used to differentiate among the five closely related species based on the chemical composition analysis. This proved to be a simple and accurate approach for discriminating among these species. The results also showed that the polysaccharide content, the amounts of the four low molecular weight compounds, and the mannose to glucose ratio, were important factors for species discriminaut. Therefore, we propose that a chemical analysis based on quantification of naringenin, bibenzyl, and polysaccha- rides is effective for identifying D. officinale.

Human pluripotent stem cell (hPSC)-derived cardiomyocytes (CMs) hold great promise for the repair of the injured heart, but optimal cell production in a fully chemically defined and cost-effective system is essential for the efficacy and safety of cell transplantation therapies. In this study, we provided a simple and efficient strategy for cardiac differentiation from hPSCs and performed functional evaluation in a rat model of myocardial infarction. Using a chemically defined medium including four components, recombinant human albumin, ascorbic acid, human transferrin, and RPMI 1640, we developed a manageable and cost-effective protocol for robust generation of CMs from hPSCs. Interestingly, the addition of transferrin helped hPSCs to transit from TeSR-E8 medium to the simple cardiac differentiation medium and successfully initiated mesoderm differentiation without significant cell death. The CM generation efficiency was up to 85% based on cTnT expression. We performed transcriptome profiling from differentiation day 0 to 35, and characterized interesting dynamic change of cardiac genes. CMs derived from transferrin-supplemented simple medium have similar transcriptome and the maturation level compared to those generated in B27 minus insulin medium as well as their in vivo counterparts. Importantly, after transplantation, hPSC-derived CMs survived in the infarcted rat heart, significantly improved the physiological function and reduced fibrosis. Our study offers an easy-to-use and cost-effective method for cardiac differentiation and facilitates the translational application of hPSC-derived CMs for heart repair.