Do public employment services affect the self-rated health of migrant workers in China?

Migrant workers greatly contributing to China's industrialization and urbanization are confronted with increasing health risks. This study empirically investigates the effects of public employment services on the self-rated health of migrant workers in Shanghai China, by using data from the National Bureau of Statistics from 2015 to 2020. The estimation results under the Ordered Probit model illustrate that public employment services significantly improve the self-rated health of migrant workers, and vocational training, job development and other related services show an apparently positive correlation with the self-rated health. The marginal effect analysis reveals that public employment services obviously reduce the probability of health satisfaction as "average", "relatively satisfied" and "relatively dissatisfied", which translate into a significant increase in the probability of "very satisfied". The mechanism analysis verifies that public employment services enhance the self-rated health by increasing the proportion of medical insurance and injury insurance of migrant workers. The results are still reliable by adopting the methods of subsample regression, Propensity Score Matching and variable substitution to conduct robustness checks. This study further enriches the literature on public employment services and the health status of migrant workers, and provides policy implications on improving the health status of migrant workers and the public employment service system of China under the impact of the COVID-19 pandemic

Method for the measurement of triboelectric charge transfer at solid–liquid interface

Abstract Triboelectrification between a liquid and a solid is a common phenomenon in our daily life and industry. Triboelectric charges generated at liquid/solid interfaces have effects on energy harvesting, triboelectrification-based sensing, interfacial corrosion, wear, lubrication, etc. Knowing the amount of triboelectric charge transfer is very useful for studying the mechanism and controlling these phenomena, in which an accurate method is absolutely necessary to measure the triboelectric charge generated at the solid—liquid interface. Herein, we established a method for measuring the charge transfer between different solids and liquids. An equipment based on the Faraday cup measurement was developed, and the leakage ratio (r l) was quantified through simulation based on an electrostatic field model. Typical experiments were conducted to validate the reliability of the method. This work provides an effective method for charge measurement in triboelectrification research

A Regional Maize Yield Hierarchical Linear Model Combining Landsat 8 Vegetative Indices and Meteorological Data: Case Study in Jilin Province

The use of satellite remote sensing could effectively predict maize yield. However, many statistical prediction models using remote sensing data cannot extend to the regional scale without considering the regional climate. This paper first introduced the hierarchical linear modeling (HLM) method to solve maize-yield prediction problems over years and regions. The normalized difference vegetation index (NDVI), calculated by the spectrum of the Landsat 8 operational land imager (OLI), and meteorological data were introduced as input parameters in the maize-yield prediction model proposed in this paper. We built models using 100 samples from 10 areas, and used 101 other samples from 34 areas to evaluate the model’s performance in Jilin province. HLM provided higher accuracy with an adjusted determination coefficient equal to 0.75, root mean square error (RMSEV) equal to 0.94 t/ha, and normalized RMSEV equal to 9.79%. Results showed that the HLM approach outperformed linear regression (LR) and multiple LR (MLR) methods. The HLM method based on the Landsat 8 OLI NDVI and meteorological data could flexibly adjust in different regional climatic conditions. They had higher spatiotemporal expansibility than that of widely used yield estimation models (e.g., LR and MLR). This is helpful for the accurate management of maize fields

A Regional Maize Yield Hierarchical Linear Model Combining Landsat 8 Vegetative Indices and Meteorological Data: Case Study in Jilin Province

The use of satellite remote sensing could effectively predict maize yield. However, many statistical prediction models using remote sensing data cannot extend to the regional scale without considering the regional climate. This paper first introduced the hierarchical linear modeling (HLM) method to solve maize-yield prediction problems over years and regions. The normalized difference vegetation index (NDVI), calculated by the spectrum of the Landsat 8 operational land imager (OLI), and meteorological data were introduced as input parameters in the maize-yield prediction model proposed in this paper. We built models using 100 samples from 10 areas, and used 101 other samples from 34 areas to evaluate the model’s performance in Jilin province. HLM provided higher accuracy with an adjusted determination coefficient equal to 0.75, root mean square error (RMSEV) equal to 0.94 t/ha, and normalized RMSEV equal to 9.79%. Results showed that the HLM approach outperformed linear regression (LR) and multiple LR (MLR) methods. The HLM method based on the Landsat 8 OLI NDVI and meteorological data could flexibly adjust in different regional climatic conditions. They had higher spatiotemporal expansibility than that of widely used yield estimation models (e.g., LR and MLR). This is helpful for the accurate management of maize fields

Hierarchical Co3O4@NiMoO4 core-shell nanowires for chemiresistive sensing of xylene vapor

Hierarchical Co3O4@NiMoO4 core-shell nanowires for chemiresistive sensing of xylene vapo

Genome-Wide Identification and Characterization of Members of the ACS Gene Family in Cucurbita maxima and Their Transcriptional Responses to the Specific Treatments

Ethylene biosynthesis and signal transduction play critical roles in plant sex differentiation. ACS (1-aminocyclopropane-1-carboxylic acid synthase) is a rate-limiting enzyme in ethylene biosynthesis. However, the understanding of the ACS gene family in Cucurbita maxima is limited. Here, we identified and characterized 13 ACS genes in the C. maxima genome. All ACS genes could be divided into three groups according to a conserved serine residue at the C-terminus. Thirteen CmaACS genes were found to be randomly distributed on 10 of the 20 chromosomes of C. maxima. The ACS gene exhibits different tissue-specific expression patterns in pumpkin, and four ACS genes (CmaACS1, CmaACS4, CmaACS7, and CmaACS9) were expressed specifically in both the female and male flowers of C. maxima. In addition, the expression levels of CmaACS4 and CmaACS7 were upregulated after ethephon and IAA treatments, which ultimately increased the number of female flowers, decreased the position of the first female flower and decreased the number of bisexual flowers per plant. These results provide relevant information for determining the function of the ACS genes in C. maxima, especially for regulating the function of ethylene in sex determination

An acetone gas sensor based on nanosized Pt-loaded Fe2O3 nanocubes

An acetone gas sensor based on nanosized Pt-loaded Fe2O3 nanocube

The delivery of sensitive food bioactive ingredients : Absorption mechanisms, influencing factors, encapsulation techniques and evaluation models

Food-sourced bioactive compounds have drawn much attention due to their health benefits such as anti-oxidant, anti-cancer, anti-diabetes and cardiovascular disease-preventing functions. However, the poor solubility, low stability and limited bioavailability of sensitive bioactive compounds greatly limited their application in food industry. Therefore, numbers of carriers were developed for improving their dispersibility, stability and bioavailability. This review addresses the digestion and absorption mechanisms of bioactive compounds in epithelial cells based on several well-known in vitro and in vivo models. Factors such as environmental stimuli, stomach conditions and mucus barrier influencing the utilization efficacy of the bioactive compounds are discussed. Delivery systems with enhanced utilization efficacy, such as complex coacervates, cross-linked polysaccharides, self-assembled micro−/nano-particles and Pickering emulsions are compared. It is a comprehensive multidisciplinary review which provides useful guidelines for application of bioactive compounds in food industry.</p