Ultrasonic-assisted synthesis of highly stable RuPd bimetallic catalysts supported on MgAl-layered double hydroxide for N-ethylcarbazole hydrogenation

Environmental Science and Pollution Research - N-Ethylcarbazole (NEC), as a promising liquid organic hydrogen carrier (LOHC), can store and release hydrogen through a reversible catalytic...     

N,P-codoped carbon quantum dots-decorated TiO2 nanowires as nanosized heterojunction photocatalyst with improved photocatalytic performance for methyl blue degradation

Environmental Science and Pollution Research - N,P-doped carbon quantum dots (N,P-CQDs) are deemed as a promising candidate to environmentally friendly materials owing to the inexpensive,...     

The effect and its critical window for ambient temperature and humidity in pregnancy on term low birth weight

Environmental Science and Pollution Research - As common meteorological factors in daily life, there is limited evidence for the effect of ambient temperature and humidity during pregnancy on the...     

A new method for broad-scale modeling and projection of plant assemblages under climatic,biotic, and environmental cofiltering

There is increasing interestin broad-scale analysis, modeling, and prediction of the distribution and composition of plant species assemblages under climatic, environmental, and biotic change, particularly for conservation purposes. We devised a method to reliably predict the impact of climate change on large assemblages of plant communities, while also considering competing biotic and environmental factors. To this purpose, we first used multilabel algorithms in order to convert the task of explaining a large assemblage of plant communities into a classification framework able to capture with high cross-validated accuracy the pattern of species distributions under a composite set of biotic and abiotic factors. We applied our model to a large set of plant communities in the Swiss Alps. Our model explained presences and absences of 175 plant species in 608 plots with >87% cross-validated accuracy, predicted decreases in α, β, and γ diversity by 2040 under both moderate and extreme climate scenarios, and identified likely advantaged and disadvantaged plant species under climate change. Multilabel variable selection revealed the overriding importance of topography, soils, and temperature extremes (rather than averages) in determining the distribution of plant species in the study area and their response to climate change. Our method addressed a number of challenging research problems, such as scaling to large numbers of species, considering species relationships and rarity, and addressing an overwhelming proportion of absences in presence–absence matrices. By handling hundreds to thousands of plants and plots simultaneously over large areas, our method can inform broad-scale conservation of plant species under climate change because it allows species that require urgent conservation action (assisted migration, seed conservation, and ex situ conservation) to be detected and prioritized. Our method also increases the practicality of assisted colonization of plant species by helping to prevent ill-advised introduction of plant species with limited future survival probability.     

根表铁膜的形成和添加硒对水稻吸收转运无机汞和甲基汞的影响

为了研究根表铁膜和硒对水稻吸收、转运不同形态的汞的影响,用Fe2+溶液诱导根表形成铁膜后,将水稻植株分别暴露于无机汞(Hg Cl2)、甲基汞(Me Hg Cl)、无机汞和亚硒酸钠(Hg Cl2+Na2Se O3)混合溶液、甲基汞和亚硒酸钠(Me Hg Cl+Na2Se O3)混合溶液的培养液中继续培养72 h。用DCB(dithionite-citrate-bicarbonate)提取根表铁膜,并用电感耦合等离子体质谱(ICP-MS)测定DCB溶液中Fe、Hg含量及水稻根、茎叶中Hg含量。结果表明:水稻根表铁膜对Me Hg Cl和Hg Cl2均有吸附,对Me Hg Cl的吸附作用高于Hg Cl2。根表铁膜的形成显著降低了汞暴露水稻根、茎叶中汞的含量;铁膜的形成也显著降低了Hg Cl2和Me Hg Cl从水稻根部到茎叶部分的转运效率。硒的存在可增加铁膜对Hg Cl2和Me Hg Cl的吸附,降低水稻对Hg Cl2和Me Hg Cl的吸收和转运。研究结果表明:根表铁膜和硒单独或联合作用能显著抑制水稻对无机汞和甲基汞的吸收和转运,进而可以减少汞在稻米中的蓄积。研究的开展对于提高汞污染区稻米的质量和保证粮食安全具有一定的现实意义。     

Effects of cotton straw amendment on soil fertility and microbial communities

Maintaining soil fertility, while controlling pollution from excessive chemical fertilizer application is important for keeping soil productivity of sustainable agriculture. Variety of straws have been used and proven to be good soil amendments for increasing soil organic matter (OM) and a range of additional soil nutrients. However, little is known about the utilization of cotton straw for soil amendment. To better understand the mechanism behind cotton straw soil amendments, investigations were performed upon cucumber seedlings, where changes to soil nutrients and microbial communities were investigated. The results revealed that the cotton straw application promoted the cucumber seedling growth by significantly increasing the soil OM, available nitrogen, available phosphorus, and available potassium. The concentration of cotton straw was positively correlated to both the number of the culturable microorganisms and also the total microbial biomass within soil. Furthermore, assessment of cotton straw application using Biolog metabolic profiling and phospholipid fatty acid analysis revealed that such application increased the microbial community metabolic activity, and markedly changed the structure of microbial community. 16S rRNA gene clone library construction and phylogenetic analysis of soil bacteria revealed γ- Proteobacteria sequences dominated the cotton straw amendment soil, comprising 27.8% of the total number of analyzed sequences, while they were less represented in control soil (13.4%). On the contrary, the Sphingobacteria (7.8%) and Verrucomicrobia (2.4%) in the cotton straw amendment soil decreased after application when compared to the control soil 15.2% and 15.2%.     

应对自然灾害国际救援制服标识意义与应用思考

本文分析了当前国内应急救援服装存在服装种类不统一、结构设计较欠缺、综合功能单一等一些问题,提出了坚持产品配套、注重材料选择、突出功能综合、重视人体功效的适合多种救援任务的救援服装设计思路。     

奇迹是怎样诞生的?

2004年秋天,对于四川省华蓥市天池镇打锣湾村和观音溪镇李子垭村的杨瑞春、杨瑞国等217户计830位村民来说,是值得高兴的日子,因为他们在党和政府的关怀下,从此脱离了地质灾害的威胁,生命和财产有了保障。     

健身房里问题多

如今的都市人在紧张的工作之余,首选健身已是一种时尚。然而,由于都市地皮紧张,各类健身房基本设在了楼房里,且多数安营扎寨于地下室中。这样,问题也就出现了。     

A comparison of two models with Landsat data for estimating above ground grassland biomass in Inner Mongolia,China

Two models, artificial neural network (ANN) and multiple linear regression (MLR), were developed to estimate typical grassland aboveground dry biomass in Xilingol River Basin, Inner Mongolia, China. The normalized difference vegetation index (NDVI) and topographic variables (elevation, aspect, and slope) were combined with atmospherically corrected reflectance from the Landsat ETM+ reflective bands as the candidate input variables for building both models. Seven variables (NDVI, aspect, and bands 1, 3, 4, 5 and 7) were selected by the ANN model (implemented in Statistica 6.0 neural network module), while six (elevation, NDVI, and bands 1, 3, 5 and 7) were picked to fit the MLR function after a stepwise analysis was executed between the candidate input variables and the above ground dry biomass. Both models achieved reasonable results with RMSEs ranging from 39.88% to 50.08%. The ANN model provided a more accurate estimation (RMSE_r = 39.88% for the training set, and RMSE_r = 42.36% for the testing set) than MLR (RMSE_r = 49.51% for the training, and RMSE_r = 53.20% for the testing). The final above ground dry biomass maps of the research area were produced based on the ANN and MLR models, generating the estimated mean values of 121 and 147 g/m², respectively.