Genetic adaptation of skin pigmentation in highland Tibetans.

Strong ultraviolet (UV) radiation at high altitude imposes a serious selective pressure, which may induce skin pigmentation adaptation of indigenous populations. We conducted skin pigmentation phenotyping and genome-wide analysis of Tibetans in order to understand the underlying mechanism of adaptation to UV radiation. We observe that Tibetans have darker baseline skin color compared with lowland Han Chinese, as well as an improved tanning ability, suggesting a two-level adaptation to boost their melanin production. A genome-wide search for the responsible genes identifies GNPAT showing strong signals of positive selection in Tibetans. An enhancer mutation (rs75356281) located in GNPAT intron 2 is enriched in Tibetans (58%) but rare in other world populations (0 to 18%). The adaptive allele of rs75356281 is associated with darker skin in Tibetans and, under UVB treatment, it displays higher enhancer activities compared with the wild-type allele in in vitro luciferase assays. Transcriptome analyses of gene-edited cells clearly show that with UVB treatment, the adaptive variant of GNPAT promotes melanin synthesis, likely through the interactions of CAT and ACAA1 in peroxisomes with other pigmentation genes, and they act synergistically, leading to an improved tanning ability in Tibetans for UV protection.

Numerical study on dynamic behavior of entrapped air in a partially filled pipe.

Rapid filling in horizontal partially filled pipes with entrapped air may result in extreme pressure transients. This study advanced the current understanding of dynamic behavior of entrapped air above tailwater (the initial water column with a free surface in a partially filled pipe) through rigid-column modeling and sensitivity analysis of system parameters. Water and air were considered as incompressible fluid and ideal gas, respectively, and the continuity and momentum equations for water and a thermodynamic equation for air were solved by using the fourth order Runge-Kutta method. The effects of system parameters were examined in detail, including tailwater depth, entrapped air volume, driving head, pipe friction, and relative length of entrapped air and pipe. The results indicate that the presence of tailwater can mitigate the peak pressure when with identical initial volumes of entrapped air, as it can be considered to reflect a certain amount of loss of the net driving head. However, the peak pressure can increase as much as about 45% for the cases with fixed pipe length, due to the reduction in the initial entrapped air volume. The rise time for the first peak pressure was closely related to pipe friction, whereas the oscillation period (defined as the time duration between the first and second peaks) was virtually irrelevant. The applicability of the rigid-column model was discussed, and a time scale relevant indicator was proposed. When the indicator is larger than 20, the relative difference between the peak pressure estimation and experimental measurements is generally below 5%.

[Analysis on Spatial-temporal Characteristics and Driving Factors of PM2.5 in Henan Province from 2015 to 2019].

PM2.5 is the main component of haze, and Henan Province has become one of the key areas of PM2.5 pollution control. Based on the PM2.5 concentration data of Henan Province from 2015 to 2019, spatial autocorrelation, spatial hot spot detection, and other methods were used to analyze its temporal and spatial characteristics, and the geodetector method was introduced to analyze the interpretation strength of meteorological factors, air quality factors, and social factors on PM2.5 concentration. The results showed that:from 2015 to 2019, the concentration of PM2.5 in Henan Province showed an overall downward trend, the days of high pollution decreased, the days of low pollution increased, and the high pollution gradually transformed into medium pollution. The concentration of PM2.5 had obvious characteristics of spatial aggregation. The five-year global spatial autocorrelation index first dropped and then rose, and the spatial hot spots were concentrated in northern Henan (Anyang, Hebi, Xinxiang, and Jiaozuo); the spatial cold spots were concentrated in western Henan (Sanmenxia, Luoyang, and Nanyang). The shift in space center of gravity showed a trend of going north. Single-factor detection showed that among the nine influencing factors, land use type (0.511), precipitation (0.312), and NO2(0.277) were the most obvious factors affecting PM2.5 concentration, and the other factors were PM10(0.255), temperature (0.209), wind speed (0.183), O3(0.121), GDP(0.073), and population (0.046). Interaction detection showed that the combined effect of multiple factors was more significant than that of single factors. These results can provide theoretical support for the control of air pollution in Henan Province.

Research on a Novel Hybrid Decomposition-Ensemble Learning Paradigm Based on VMD and IWOA for PM2.5 Forecasting.

The non-stationarity, nonlinearity and complexity of the PM2.5 series have caused difficulties in PM2.5 prediction. To improve prediction accuracy, many forecasting methods have been developed. However, these methods usually do not consider the importance of data preprocessing and have limitations only using a single forecasting model. Therefore, this paper proposed a new hybrid decomposition-ensemble learning paradigm based on variation mode decomposition (VMD) and improved whale-optimization algorithm (IWOA) to address complex nonlinear environmental data. First, the VMD is employed to decompose the PM2.5 sequences into a set of variational modes (VMs) with different frequencies. Then, an ensemble method based on four individual forecasting approaches is applied to forecast all the VMs. With regard to ensemble weight coefficients, the IWOA is applied to optimize the weight coefficients, and the final forecasting results were obtained by reconstructing the refined sequences. To verify and validate the proposed learning paradigm, four daily PM2.5 datasets collected from the Jing-Jin-Ji area of China are chosen as the test cases to conduct the empirical research. The experimental results indicated that the proposed learning paradigm has the best results in all cases and metrics.