68 research outputs found

    Graphene, Transition Metal Dichalcogenides, and Perovskite Photodetectors

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    Recent years have witnessed a tremendous progress in 2D materials photodetector. Their unique properties including wide photoresponse wavelength, passivated surfaces, strong interaction with incident light, and high mobility enable dramatical superiority in photodetector application. The photophysics, device structure, working mechanism, and performance of three kinds of 2D materials photodetectors including graphene, transition metal dichalcogenides (TMDs), and halide perovskite are discussed in detail to give a profound understanding for the readers. In addition, we highlight the challenges and opportunities faced in studying 2D materials photodetector, and various strategies are summarized to help on the development of photodetection research and find ways to approach major problems

    Assessing Income-Related Inequality on Health Service Utilization among Chinese Rural Migrant Workers with New Co-Operative Medical Scheme: A Multilevel Approach

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    Background: Eliminating inequality in health service utilization is an explicit goal of China's health system. Rural migrant workers with New Rural Cooperative Medical Insurance (NCMS) still face the dilemma of limited health service; however, there is a lack of analysis or measurement on the income-related inequality of health service utilization. Method: The nationally representative data of the China Labor-Force Dynamic Survey in 2016 were used for analysis. Multilevel regressions were used to obtain robust estimates and to account for various covariates associated with health service utilization of rural migrant workers with NCMS. The concentration index and its decomposition method were applied to quantify the income-related inequality of health service utilization of rural migrant workers. Result: The multilevel model analysis indicated that influencing factors of health service utilization were diversified, including gender, city service quality index, type of industry, the per capita annual income, marital status, health self-assessment, the community health index and the number of friends. The concentration indices of the total cost of inpatient and OOP cost of inpatient were 0.102 (95%CI: 0.031, 0.149), and the CI of OOP cost of inpatient was 0.094 (95%CI: 0.007, 0.119), respectively. The horizontal inequality indices of the total cost of inpatient and OOP cost of inpatient were 0.051 and 0.009, respectively. Conclusion: Our study presented a unique opportunity to examine the potential influence factors of health service utilization of rural migrant workers with NCMS, and highlighted that unequal health service utilization is evident among rural migrant workers with NCMS. This study provides important corroborative evidence to take full account of the contribution of each determinant to the inequality and health service needs among rural migrant workers with NCMS, in order to improve the basic medical insurance and social security systems-particularly for some marginal groups in China

    Socio-economic inequalities in health service utilization among Chinese rural migrant workers with New Cooperative Medical Scheme: a multilevel regression approach

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    BackgroundWhile reducing inequity in health service utilization is an important goal of China's health system, it has been widely acknowledged that a huge number of rural migrant workers cannot be effectually protected against risks with the New Rural Cooperative Medical Insurance (NCMS).MethodData of the 2016 China Labor-force Dynamic Survey and the Chinese Urban Statistical Yearbook were used. The multilevel regression approach was implemented with a nationally representative sample of rural migrant workers with NCMS. Our study adopted the concentration index and its decomposition method to quantify the inequality of their health service utilization.ResultThe multilevel model analysis indicated that impact variables for health service utilization were not concentrated, especially the contextual and individual characteristics. The concentration indices of the probability of two weeks outpatient and the probability of inpatient were -0.168 (95%CI:-0.236,-0.092) and -0.072 (95%CI:-1.085,-0.060), respectively. The horizontal inequality indices for the probability of two-week outpatient and the probability of inpatient were -0.012 and 0.053, respectively.ConclusionThe health service utilization of rural migrant workers with NCMS is insufficient. Our study highlighted that substantial inequalities in their health service utilization did exist. In addition, their need of health service utilization increased the pro-poor inequality. Based on the findings, our study offered notable implications on compensation policies and benefit packages to improve the equality among rural migrant workers with NCMS

    Reversible transformation between CsPbBr3 nanowires and nanoparticles

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    We show that CsPbBr3 nanowires (NWs) are formed by the hierarchical arrangement of individual nanoparticles (NPs), and reversible transformation from NWs to NPs is also achieved by anion exchange

    Transcriptome analysis of stem development in the tumourous stem mustard Brassica juncea var. tumida Tsen et Lee by RNA sequencing

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    <p>Abstract</p> <p>Background</p> <p>Tumourous stem mustard (<it>Brassica juncea </it>var. <it>tumida </it>Tsen et Lee) is an economically and nutritionally important vegetable crop of the <it>Cruciferae </it>family that also provides the raw material for <it>Fuling </it>mustard. The genetics breeding, physiology, biochemistry and classification of mustards have been extensively studied, but little information is available on tumourous stem mustard at the molecular level. To gain greater insight into the molecular mechanisms underlying stem swelling in this vegetable and to provide additional information for molecular research and breeding, we sequenced the transcriptome of tumourous stem mustard at various stem developmental stages and compared it with that of a mutant variety lacking swollen stems.</p> <p>Results</p> <p>Using Illumina short-read technology with a tag-based digital gene expression (DGE) system, we performed <it>de novo </it>transcriptome assembly and gene expression analysis. In our analysis, we assembled genetic information for tumourous stem mustard at various stem developmental stages. In addition, we constructed five DGE libraries, which covered the strains <it>Yong'an </it>and <it>Dayejie </it>at various development stages. Illumina sequencing identified 146,265 unigenes, including 11,245 clusters and 135,020 singletons. The unigenes were subjected to a BLAST search and annotated using the GO and KO databases. We also compared the gene expression profiles of three swollen stem samples with those of two non-swollen stem samples. A total of 1,042 genes with significantly different expression levels occurring simultaneously in the six comparison groups were screened out. Finally, the altered expression levels of a number of randomly selected genes were confirmed by quantitative real-time PCR.</p> <p>Conclusions</p> <p>Our data provide comprehensive gene expression information at the transcriptional level and the first insight into the understanding of the molecular mechanisms and regulatory pathways of stem swelling and development in this plant, and will help define new mechanisms of stem development in non-model plant organisms.</p

    Implementation and first-year screening results of an ocular telehealth system for diabetic retinopathy in China

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    <p>Abstract</p> <p>Background</p> <p>To describe implementation and first-year screening results of the first Chinese telehealth system for diabetic retinopathy (DR) - the Beixinjing Community Diabetic Retinopathy Telehealth system (BCDRT).</p> <p>Methods</p> <p>BCDRT implementation was based on the acquisition of adequate digital retinographs, secure digital transmission, storage and retrieval of participants' data and reader-generated medical reports. Local diabetic residents meeting inclusion criteria were enrolled into the BCDRT system beginning in 2009. Participants recommended for further in-person examination with ophthalmologists were followed, and the consistencies in diagnoses between BCDRT and ophthalmologists for DR or macular edema were calculated.</p> <p>Results</p> <p>A total of 471 diabetic residents participated in BCDRT screening in 2009. The proportions of total DR, proliferative DR, and diabetic macular edema were 24.42% (115 patients), 2.12% (10 patients) and 6.47% (24 patients), respectively: 56 patients consulted ophthalmologists for further in-person retinal examination with funduscopy after pupil dilation. High rates of consistency between BCDRT screening and ophthalmologists were observed for macular edema (Kappa = 0.81), moderate or severe non-proliferative DR grade (Kappa = 0.92), and other DR grades (Kappa = 1). A total of 456 (96.82%) patients were willing to participate in the next BCDRT screening.</p> <p>Conclusions</p> <p>BCDRT was a reliable and valid system for DR screening, and offers the potential to increase DR annual screening rates in local residents.</p

    Genomic prediction of drought tolerance during seedling stage in maize using low-cost molecular markers

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    Drought tolerance in maize is a complex and polygenic trait, especially in the seedling stage. In plant breeding, complex genetic traits can be improved by genomic selection (GS), which has become a practical and effective breeding tool. In the present study, a natural maize population named Northeast China core population (NCCP) consisting of 379 inbred lines were genotyped with diversity arrays technology (DArT) and genotyping-by-sequencing (GBS) platforms. Target traits of seedling emergence rate (ER), seedling plant height (SPH), and grain yield (GY) were evaluated under two natural drought stress environments in northeast China. Adequate genetic variations were observed for all the target traits, but they were divergent across environments. Similarly, the heritability of the target trait also varied across years and environments, the heritabilities in 2019 (0.88, 0.82, 0.85 for ER, SPH, GY) were higher than those in 2020 (0.65, 0.53, 0.33) and cross-2-years (0.32, 0.26, 0.33). In total, three marker datasets, 11,865 SilicoDArT markers obtained from the DArT-seq platform, 7837 SNPs obtained from the DArT-seq platform, and 91,003 SNPs obtained from the GBS platform, were used for GS analysis after quality control. The results of phylogenetic trees showed that broad genetic diversity existed in the NCCP population. Genomic prediction results showed that the average prediction accuracies estimated using the DArT SNP dataset under the two-fold cross-validation scheme were 0.27, 0.19, and 0.33, for ER, SPH, and GY, respectively. The result of SilicoDArT is close to the SNPs from DArT-seq, those were 0.26, 0.22, and 0.33. For the trait with lower heritability, the prediction accuracy can be improved using the dataset filtered by linkage disequilibrium. For the same trait, the prediction accuracies estimated with two DArT marker datasets were consistently higher than that estimated with the GBS SNP dataset under the same genotyping cost. The prediction accuracy was improved by controlling population structure and marker quality, even though the marker density was reduced. The prediction accuracies were improved by more than 30% using the significant-associated SNPs. Due to the complexity of drought tolerance under the natural stress environments, multiple years of data need to be accumulated to improve prediction accuracy by reducing genotype-by-environment interaction. Modeling genotype-by-environment interaction into genomic prediction needs to be further developed for improving drought tolerance in maize. The results obtained from the present study provides valuable pathway for improving drought tolerance in maize using GS
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