This study explores applying big data technology in vocational colleges and universities’ innovation and entrepreneurship education model to improve the teaching effect and promote students’ ...innovation ability and employment competitiveness. The study includes theoretical analysis and empirical research to analyze the teaching mode, evaluation system, and its impact on the educational effect. The academic model using big data technology significantly improved students’ theoretical knowledge, professional research ability, innovation, and practice ability. This teaching model resulted in an average score of 90 points for innovative practice ability in classes, compared to the traditional education model, which was 27 points higher. The model also significantly improved students’ moral character, motivation, and learning behavior. The innovation and entrepreneurship education model of vocational colleges supported by big data technology can effectively enhance students’ comprehensive quality and innovation ability, which is significant to education reform and talent cultivation.
•Desert-oasis thermal environmental change threats to eco-sustainability and habitat quality.•Accurate identify the “cold island zone” and “heat island zone” in arid zones.•LULC and urbanization ...development are closely linked to the thermal environment.•Spatial heterogeneity of natural and human factors in land use types.
As a typical geographic landscape unit in the arid zone of northwest China, the distribution of the thermal environment in the substratum of the desert-oasis is of great significance to the monitoring of the ecological environment and the quality of human habitat in the region. The purpose of this research is to reveal the spatial–temporal evolution pattern of the thermal environment of the desert–oasis in the Turpan–Hami region from 2005 to 2020 and its trend changes, and to investigate the relationship between natural and human factors and the thermal environment and to conduct a long time series analysis. Firstly, the accuracy of MODIS land surface temperature (LST) data combined with site data was verified. Secondly, the mean-standard deviation method is used to identify desert heat island and oasis cold island zones. Again, the spatial–temporal distribution and change trends of thermal environment are explored by using standard deviation ellipse and spatial autocorrelation combined with land use/land cover (LULC) types. Finally, based on the multi-source remote sensing data, the natural factors and human factors are selected to explore their correlation with the thermal environment using Pearson correlation analysis. The results show that (1) the desert heat island zones are distributed in the desert areas on the periphery of urban built-up areas in Gaochang District, Shanshan County and Yizhou District of Hami Region. The oasis cold island zones are concentrated in the urban built-up areas of Gaochang District and Yizhou District, mainly because the vegetation coverage of urban built-up areas is higher than that of the peripheral desert areas. (2) The spatial development characteristics of the extremely high temperature (EHT) zone and the high temperature (HT)zone from 2005 to 2020 are “southeast-northeast-northwest” and “southeast-northwest” respectively, and the area of construction land 16a increased by 0.31%. This indicates that the spatial evolution of the thermal environment is closely related to the LULC and the degree of urbanization development. (3) From a four–period image with P < 0.001 and Z > 2.58, the thermal environment displays a high positive spatial correlation with Moran's I values of 0.45, 0.54, 0.47, and 0.45. (4) Temperature (Tem), downward longwave radiation (LWdown), and nighttime light intensity (NPP) all exhibited positive correlations with the LST and are significant in the desert region (p < 0.05); The albedo exhibited negative correlations with the LST and is significant in the grassland and woodland regions (p < 0.05).
Improving the understanding of mechanisms involved in a low miscible displacement efficiency is significant for a wide spectrum of applications in subsurface from environment such as groundwater ...remediation and CO2 sequestration to energy extraction such as enhanced oil recovery and geothermal recovery. Two key limiting factors to the efficiency are viscous fingering (VF) instability and dead‐end pores in porous media. Previous research on VF simply assumes all pores are well connected and fluids can be mobilized by convection. However, fluids trapped in dead‐end pores, such as nonaqueous phase liquids (NAPLs) in groundwater remediation, are inaccessible to convection, resulting in even less efficient displacements. Instead of the classic convection‐diffusion/dispersion equation, in this work, we use a fundamentally different capacitance model to incorporate the mass transfer between two pore types in miscible displacements. The hybrid pseudospectral and high‐order finite difference methods are employed to solve the governing equations in a fixed reference frame for simulating the flow dynamics. We found that the viscous fingering instabilities in well‐connected pore network led to an unstable, nonuniform distribution of trapped NAPLs in dead‐end pores network. Different with a traditional view that NAPLs are easily cleaned up, our study indicates the existence of dead‐end pores results in an inefficient cleanup of NAPLs in swept area because of the slow mass transfer of trapped NAPLs between two pore types. A simple model is developed to accurately predict the NAPL concentration behind finger trailing front, which has not been previously examined. Six flow regimes, four of which are new, are then identified.
Key Points
A fundamentally different porous medium with non‐negligible dead‐end pore volume is incorporated in unstable miscible displacements
The interactions of fluids in well‐connected and dead‐end pores and the impacts on viscous fingering and cleanup of non‐aqueous phase liquids are characterized
Six flow regimes, four of which are new, are identified in the full “life cycle” displacements in porous media with dead‐end pores
The accurate inversion of actual evapotranspiration (ETa) at a regional scale is crucial for understanding water circulation, climate change, and drought monitoring. In this study, we produced a 1 km ...monthly ETa dataset for Turpan and Hami, two typical arid cities in northwest China, using multi-source remote sensing data, reanalysis information, and the ETMonitor model from 1980 to 2021. We analyzed the spatiotemporal variation of ETa using various statistical approaches and discussed the impact of climate and land use and cover changes (LUCC) on ETa. The results show the following: (1) the estimation results correlate well with ETa products on monthly scales (coefficient of determination (R2) > 0.85, root mean square error (RMSE) < 15 mm/month) with high reliability. (2) The ETa values were spatially distributed similarly to precipitation and LUCC, with the multi-year (1980–2021) average of 66.31 mm and a slightly fluctuating downward trend (−0.19 mm/a). (3) During the 42-year period, 63.16% of the study area exhibited an insignificant decrease in ETa, while 86.85% experienced pronounced fluctuations (coefficient of variation (CV) > 0.20), and 78.83% will show an upward trend in the future. (4) ETa was significantly positively correlated with precipitation (94.17%) and insignificantly positively correlated with temperature (55.81%). The impact of human activities showed an insignificant decreasing trend (85.41%). Additionally, the intensity of ETa varied considerably among land types, with the largest for cropland (424.12 mm/a). The results of the study have implications for promoting the rational allocation of regional water resources and improving water use efficiency in arid zones.
Background. LIM and SH3 domain protein 1 (LASP1), highly expressed in a variety of tumors, is considered as a novel tumor metastasis biomarker. However, it is unknown which signaling pathway works ...and how the signal transduces into cell nucleus to drive tumor progression by LASP1. The aim of this study is to explore the essential role of LASP1 in TGF-β1-induced epithelial-mesenchymal transition (EMT) in lung cancer cells. Methods. The gene and protein levels of LASP-1 were successfully silenced or overexpressed by LASP-1 shRNA lentivirus or pcDNA in TGF-β1-treated lung cancer cell lines, respectively. Then, the cells were developed EMT by TGF-β1. The cell abilities of invasion, migration, and proliferation were measured using Transwell invasion assay, wound healing assay, and MTT assay, respectively. Western blotting was used to observe the protein levels of EMT-associated molecules, including N-cadherin, vimentin, and E-cadherin, and the key molecules in the TGF-β1/Smad/Snail signaling pathway, including pSmad2 and Smad2, pSmad3 and Smad3, and Smad7 in cell lysates, as well as Snail1, pSmad2, and pSmad3 in the nucleus. Results. TGF-β1 induced higher LASP1 expression. LASP1 silence and overexpression blunted or promoted cell invasion, migration, and proliferation upon TGF-β1 stimulation. LASP1 also regulated the expression of vimentin, N-cadherin, and E-cadherin in TGF-β1-treated cells. Activity of key Smad proteins (pSmad2 and pSmad3) and protein level of Smad7 were markedly regulated through LASP1. Furthermore, LASP1 affected the nuclear localizations of pSmad2, pSmad3, and Snail1. Conclusion. This study reveals that LASP1 regulates the TGF-β1/Smad/Snail signaling pathway and EMT markers and features, involving in key signal molecules and their nuclear levels. Therefore, LASP1 might be a drug target in lung cancer.
Exploring the future trends of land use/land cover (LULC) changes is significant for the sustainable development of a region. The simulation and prediction of LULC in a large-scale basin in an arid ...zone can help the future land management planning and rational allocation of resources in this ecologically fragile region. Using the whole Ili-Balkhash Basin as the study area, the patch-generating land use simulation (PLUS) model and a combination of PLUS and Markov predictions (PLUS–Markov) were used to simulate and predict land use in 2020 based on the assessment of the accuracy of LULC classification in the global dataset. The accuracy of simulations and predictions using the model were measured for LULC data covering different time periods. Model settings with better simulation results were selected for simulating and predicting possible future land use conditions in the basin. The future predictions for 2025 and 2030, which are based on historical land change characteristics, indicate that the overall future spatial pattern of LULC in the basin remains relatively stable in general without the influence of other external factors. Over the time scale of the future five years, the expansion of croplands and barren areas in the basin primarily stems from the loss of grasslands. Approximately 48% of the converted grassland areas are transformed into croplands, while around 40% are converted into barren areas. In the longer time scale of the future decade, the conversion of grasslands to croplands in the basin is also evident. However, the expansion phenomenon of urban and built-up lands at the expense of croplands is more significant, with approximately 774.2 km2 of croplands developing into urban and built-up lands. This work provides an effective new approach for simulating and predicting LULC in data-deficient basins at a large scale in arid regions, thereby establishing a foundation for future research on the impact of human activities on basin hydrology and related studies.
Li Yinhe (born 1952) is a nationally and internationally-known sociologist and sexologist in China and a prominent LGBTQ rights activist. The material for this article is drawn from an interview with ...Dr. Li conducted in Beijing on OCtober 9, 2018.
Bioinformatics and RT-PCR analysis of RNA from four Lentinula edodes samples identified 22 different virus-like contigs comprising 15 novel and 3 previously reported viruses. We further investigated ...the Lentinula edodes negative-stranded RNA virus 1 (LeNSRV1) isolated from a symptomatic sample, whose virion is a filamentous particle with a diameter of ~15 nm and a length of ~1200 nm. RT-PCR analysis detected LeNSRV1 in 10 of the 56 Chinese L. edodes core collection strains and 6 of the 22 monokaryotic strains from the L. edodes strain HNZMD. Genetic variation analysis showed that the sequences encoding the nucleocapsid protein (ORF2) from all the aforementioned LeNSRV1 positive strains are very conservative. The results presented here may enrich our understanding of L. edodes virus diversity and the characteristics of LeNSRV1, and will promote further research on virus-host interaction in L. edodes.
•( (1) Identification of 22 different virus-like contigs comprising 15 novel viruses in L. edodes.•Firstly exhibit the viral particles of a negative-strand RNA mymonavirus LeNSRV1.•Firstly exhibit of the occurrence and genetic variation of LeNSRV1 in Chinese Lentinula edodes core collection and sexual basidiospores.
Automatic road extraction from remote sensing images has an important impact on road maintenance and land management. While significant deep-learning-based approaches have been developed in recent ...years, achieving a suitable trade-off between extraction accuracy, inference speed and model size remains a fundamental and challenging issue for real-time road extraction applications, especially for rural roads. For this purpose, we developed a lightweight dynamic addition network (LDANet) to exploit rural road extraction. Specifically, considering the narrow, complex and diverse nature of rural roads, we introduce an improved Asymmetric Convolution Block (ACB)-based Inception structure to extend the low-level features in the feature extraction layer. In the deep feature association module, the depth-wise separable convolution (DSC) is introduced to reduce the computational complexity of the model, and an adaptation-weighted overlay is designed to capture the salient features. Moreover, we utilize a dynamic weighted combined loss, which can better solve the sample imbalance and boosts segmentation accuracy. In addition, we constructed a typical remote sensing dataset of rural roads based on the Deep Globe Land Cover Classification Challenge dataset. Our experiments demonstrate that LDANet performs well in road extraction with fewer model parameters (<1 MB) and that the accuracy and the mean Intersection over Union reach 98.74% and 76.21% on the test dataset, respectively. Therefore, LDANet has potential to rapidly extract and monitor rural roads from remote sensing images.
Extreme climate events have a significant impact both on the ecological environment and human society, and it is crucial to analyze the spatial–temporal evolutionary trends of extreme climate. Based ...on the RClimDex model, this study used trend analysis, probability density function, and wavelet coherence analysis to analyze the spatiotemporal variation characteristics of extreme climate indices and their response mechanisms to teleconnection patterns. The results of the study show that: (1) All the extreme precipitation indices, except max 1-day precipitation amount, max 5-day precipitation amount, and extremely wet days increased, with no significant abrupt changes. The extreme warm indices increased and extreme cold indices decreased. The years with abrupt changes were mainly distributed between 1988 and 1997. (2) Spatially, the extreme precipitation indices of most meteorological stations decreased, except for the simple daily intensity index and the number of very heavy precipitation days. The extreme warm indices of most meteorological stations increased, and the extreme cold indices decreased. (3) Except for consecutive dry days, the frequency of extreme precipitation indices increased significantly, the severity and frequency of high-temperature events increased, while the frequency of low-temperature events increased, but the severity decreased. The results of rescaled range (R/S) analysis indicated that the climate in the Beijing–Tianjin–Hebei region will further tend to be warm and humid in the future. (4) The Polar/Eurasia Pattern, the East Atlantic Pattern, the Arctic Oscillation, and the East Atlantic/West Russian Pattern were most closely associated with extreme climate events in the Beijing–Tianjin–Hebei region. The multi-factor combination greatly enhanced the explanatory power of the teleconnection pattern for extreme climates.
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