Meteorological observations and weather forecasting services of the CHINARE

By 2018, China had conducted 34 scientific explorations in Antarctica spearheaded by the Chinese National Antarctic Research Expedition (CHINARE). Since the first CHINARE over 30 years ago, considerable work has been undertaken to promote the development of techniques for the observation of surface and upper-air meteorological elements, and satellite image and data reception systems at Chinese Antarctic stations and onboard Chinese icebreakers have played critical roles in this endeavor. The upgrade of in situ and remote sensing measurement methods and the improvement of weather forecasting skill have enabled forecasters to achieve reliable on-site weather forecasting for the CHINARE. Nowadays, the routing of icebreakers, navigation of aircraft, and activities at Chinese Antarctic stations all benefit from the accurate weather forecasting service. In this paper, a review of the conventional meteorological measurement and operational weather forecasting services of the CHINARE is presented

Prediction Method of the Moisture Content of Black Tea during Processing Based on the Miniaturized Near-Infrared Spectrometer

The moisture content of black tea is an important factor affecting its suitability for processing and forming the unique flavor. At present, the research on the moisture content of black tea mainly focuses on a single withering step, but the research on the rapid detection method of moisture content of black tea applicable to the entire processing stage is ignored. This study is based on a miniaturized near-infrared spectrometer(micro−NIRS) and establishes the prediction models for black tea moisture content through machine learning algorithms. We use micro−NIRS for spectroscopic data acquisition of samples. Linear partial least squares (PLS) and nonlinear support vector regression (SVR) were combined with four spectral pre−processing methods, and principal component analysis (PCA) was applied to establish the predictive models. In addition, we combine the gray wolf optimization algorithm (GWO) with SVR for the prediction of moisture content, aiming to establish the best prediction model of black tea moisture content by optimizing the selection of key parameters (c and g) of the kernel function in SVR. The results show that SNV, as a method to correct the error of the spectrum due to scattering, can effectively extract spectral features after combining with PCA and is better than other pre−processing methods. In contrast, the nonlinear SVR model outperforms the PLS model, and the established mixed model SNV−PCA−GWO−SVR achieves the best prediction effect. The correlation coefficient of the prediction set and the root mean square error of the prediction set are 0.9892 and 0.0362, respectively, and the relative deviation is 6.5001. Experimental data show that the moisture content of black tea can be accurately and effectively determined by micro-near-infrared spectroscopy

Prediction Method of the Moisture Content of Black Tea during Processing Based on the Miniaturized Near-Infrared Spectrometer

The moisture content of black tea is an important factor affecting its suitability for processing and forming the unique flavor. At present, the research on the moisture content of black tea mainly focuses on a single withering step, but the research on the rapid detection method of moisture content of black tea applicable to the entire processing stage is ignored. This study is based on a miniaturized near-infrared spectrometer(micro−NIRS) and establishes the prediction models for black tea moisture content through machine learning algorithms. We use micro−NIRS for spectroscopic data acquisition of samples. Linear partial least squares (PLS) and nonlinear support vector regression (SVR) were combined with four spectral pre−processing methods, and principal component analysis (PCA) was applied to establish the predictive models. In addition, we combine the gray wolf optimization algorithm (GWO) with SVR for the prediction of moisture content, aiming to establish the best prediction model of black tea moisture content by optimizing the selection of key parameters (c and g) of the kernel function in SVR. The results show that SNV, as a method to correct the error of the spectrum due to scattering, can effectively extract spectral features after combining with PCA and is better than other pre−processing methods. In contrast, the nonlinear SVR model outperforms the PLS model, and the established mixed model SNV−PCA−GWO−SVR achieves the best prediction effect. The correlation coefficient of the prediction set and the root mean square error of the prediction set are 0.9892 and 0.0362, respectively, and the relative deviation is 6.5001. Experimental data show that the moisture content of black tea can be accurately and effectively determined by micro-near-infrared spectroscopy

Uptake of Di(2-ethylhexyl) Phthalate (DEHP) by the Plant Benincasa hispida and Its Use for Lowering DEHP Content of Intercropped Vegetables

Uptake of di­(2-ethylhexyl) phthalate (DEHP) by the plant Benincasa hispida and its use for topical phytoremediation were investigated by cultivation of plants in DEHP-contaminated environments. The results showed that major plant organs of B. hispida, including leaves, stems, and fruits, readily absorbed DEHP from the air. The amount of DEHP that accumulated in leaves, stems, and fruits was mainly dependent upon exposure time, and most DEHP accumulated in their inner tissues. A single plant of B. hispida with a gourd was able to absorb more than 700 mg of DEHP when it was exposed to DEHP-contaminated air for 6 week. B. hispida reduced air DEHP concentration by 65–76% as the air DEHP concentration ranged from 2351 to 3955 μg/m³ (high DEHP level) and 85–92% as the air DEHP concentration ranged from 35.1 to 65.3 μg/m³ (low DEHP level) in greenhouse experiments. When intercropping of B. hispida and Brassica chinensis or Brassica campestris, B. hispida reduced more than 87% of DEHP accumulation in the latter, which indicates that B. hispida has excellent use potential for lowering the DEHP content of intercropped vegetables

The variability of surface radiation fluxes over landfast sea ice near Zhongshan station, east Antarctica during austral spring

Surface radiative fluxes over landfast sea ice off Zhongshan station have been measured in austral spring for five springs between 2010 and 2015. Downward and upward solar radiation vary diurnally with maximum amplitudes of 473 and 290 W m−2, respectively. The maximum and minimum long-wave radiation values of the mean diurnal cycle are 218 and 210 W m−2 for downward radiation, 277 and 259 W m−2 for upward radiation and 125 and −52 W m−2 for net radiation. The albedo has a U-shaped mean diurnal cycle with a minimum of 0.64 at noon. Sea ice thickness is in the growth phase for most spring days, but can be disturbed by synoptic processes. The surface temperature largely determines the occurrence of ice melting. Surface downward and upward long-wave radiation show synoptic oscillations with a 5–8 day period and intraseasonal variability with a 12–45 day period. The amplitudes of the diurnal, synoptic and intraseasonal variability show some differences during the five austral springs considered here. The intraseasonal and synoptic variability of downward and upward long-wave radiation are associated with the variability of cloud cover and surface temperature induced by the atmospheric circulation

Divergent Carry-Over Effects of Hypoxia during the Early Development of Abalone

After being exposed to environmental stimuli during early developmental stages, some organisms may gain or weaken physiological regulating abilities, which would have long-lasting effects on their performance. Environmental hypoxia events can have significant effects on marine organisms, but for breeding programs and other practical applications, it is important to further explore the long-term physiological effects of early hypoxia exposure in economically significant species. In this study, the Pacific abalone Haliotis discus hannai was exposed to moderate hypoxia (∼4 mg/L) from zygote to trochophora, and the assessments of hypoxia tolerance were conducted on the grow-out stage. The results revealed that juvenile abalones exposed to hypoxia at the early development stages were more hypoxia-tolerant but with slower weight growth, a phenomenon called the trade-off between growth and survival. These phenotypic effects driven by the hypoxia exposure were explained by strong selection of genes involved in signal transduction, autophagy, apoptosis, and hormone regulation. Moreover, long non-coding RNA regulation plays an important role modulating carry-over effects by controlling DNA replication and repair, signal transduction, myocardial activity, and hormone regulation. This study revealed that the ability to create favorable phenotypic differentiation through genetic selection and/or epigenetic regulation is important for the survival and development of aquatic animals in the face of rapidly changing environmental conditions