Comparison of Soil Greenhouse Gas Fluxes during the Spring Freeze–Thaw Period and the Growing Season in a Temperate Broadleaved Korean Pine Forest, Changbai Mountains, China

Soils in mid-high latitudes are under the great impact of freeze–thaw cycling. However, insufficient research on soil CO2, CH4, and N2O fluxes during the spring freeze–thaw (SFT) period has led to great uncertainties in estimating soil greenhouse gas (GHG) fluxes. The present study was conducted in a temperate broad-leaved Korean pine mixed forest in Northeastern China, where soils experience an apparent freeze–thaw effect in spring. The temporal variations and impact factors of soil GHG fluxes were measured during the SFT period and growing season (GS) using the static-chamber method. The results show that the soil acted as a source of atmospheric CO2 and N2O and a sink of atmospheric CH4 during the whole observation period. Soil CO2 emission and CH4 uptake were lower during the SFT period than those during the GS, whereas N2O emissions were more than six times higher during the SFT period than that during the GS. The responses of soil GHG fluxes to soil temperature (Ts) and soil moisture during the SFT and GS periods differed. During the SFT period, soil CO2 and CH4 fluxes were mainly affected by the volumetric water content (VWC) and Ts, respectively, whereas soil N2O flux was influenced jointly by Ts and VWC. The dominant controlling factor for CO2 was Ts during the GS, whereas CH4 and N2O were mainly regulated by VWC. Soil CO2 and N2O fluxes accounted for 97.3% and 3.1% of the total 100-year global warming potential (GWP100) respectively, with CH4 flux offsetting 0.4% of the total GWP100. The results highlight the importance of environmental variations to soil N2O pulse during the SFT period and the difference of soil GHG fluxes between the SFT and GS periods, which contribute to predicting the forest soil GHG fluxes and their global warming potential under global climate change

Improving Massive Open Online Course Quality in Higher Education by Addressing Student Needs Using Quality Function Deployment

Massive Open Online Courses (MOOCs) are playing an increasingly important role in higher education. However, some MOOCs still suffer from low quality, which hinders the sustainable development of higher education. Course characteristics reflect students’ needs for online learning and have a significant impact on the quality of MOOCs. In the course improvement process, existing research has neither improved the MOOC quality from the perspective of student needs nor has it considered resource constraints. Therefore, to deal with this situation, we propose a student-needs-driven MOOC quality improvement framework. In this framework, we first map students’ differentiated needs for MOOCs into quality characteristics based on quality function deployment (QFD). Then, we formulate a mixed-integer linear programming model to produce MOOC quality improvement policies. The effectiveness of the proposed framework is verified by real-world data from China’s higher education MOOCs. We also investigate the impacts of budget, cost, and student needs on student satisfaction. Our results revealed that to significantly improve student satisfaction, the course budget needs to be increased by a small amount or the course cost needs to be greatly reduced. Our research provides an effective decision-making reference for MOOC educators to improve course quality

Computational drug repositioning for ischemic stroke: neuroprotective drug discovery.

Background: A comprehensive approach to drug repositioning will be required to overcome translational hurdles and identify more neuroprotective drugs. Results & methods: Gene Set Enrichment Analysis was applied to identify related pathways and enriched genes. Candidate genes were optimized using ToppGene, ToppGenet and pBRIT. From the perspective of the local structures, gene-domain-substructure-drug relationships were constructed. Using the MCODE algorithm and K-means clustering, 31 functional subnetworks were obtained, and 252 drugs with proposed neuroprotective function were identified. Using computational analysis, 72 substructures with different scores were found to correspond to neuroprotective functions. The protective effects of benidipine and barnidipine were confirmed in vitro. Conclusion: The authors' research has great potential to discover more neuroprotective drugs and obtain more information regarding mechanisms of action and functional substructures

Responses of photosynthetic parameters to drought in subtropical forest ecosystem of China

The mechanism underlying the effect of drought on the photosynthetic traits of leaves in forest ecosystems in subtropical regions is unclear. In this study, three limiting processes (stomatal, mesophyll and biochemical limitations) that control the photosynthetic capacity and three resource use efficiencies (intrinsic water use efficiency (iWUE), nitrogen use efficiency (NUE) and light use efficiency (LUE)), which were characterized as the interactions between photosynthesis and environmental resources, were estimated in two species (Schima superba and Pinus massoniana) under drought conditions. A quantitative limitation analysis demonstrated that the drought-induced limitation of photosynthesis in Schima superba was primarily due to stomatal limitation, whereas for Pinus massoniana, both stomatal and non-stomatal limitations generally exhibited similar magnitudes. Although the mesophyll limitation represented only 1% of the total limitation in Schima superba, it accounted for 24% of the total limitations for Pinus massoniana. Furthermore, a positive relationship between the LUE and NUE and a marginally negative relationship or trade-off between the NUE and iWUE were observed in the control plots. However, drought disrupted the relationships between the resource use efficiencies. Our findings may have important implications for reducing the uncertainties in model simulations and advancing the understanding of the interactions between ecosystem functions and climate change

Student demands extracted from MOOC review data.

Higher vocational education is the core component of China’s national education system and shoulders the mission of cultivating high-skilled and applied talents. The wide application of Massive Open Online Courses (MOOCs) has effectively improved the curriculum system of China’s higher vocational education. In the meantime, some MOOCs suffer from poor course quality. Therefore, from the perspective of sustainable course quality improvement, we propose a data-driven framework for mining and analyzing student reviews in China’s higher vocational education MOOCs. In our framework, we first mine multi-level student demands hidden in MOOC reviews by combining web crawlers and text mining. Then we use an artificial neural network and the KANO model to classify the extracted student demands, thereby designing effective and sustainable MOOC quality improvement strategies. Based on the real data from China’s higher vocational education MOOCs, we validate the effectiveness of the proposed data-driven framework.</div

Inorganic and organic nitrogen acquisition by a fern Dicranopteris dichotoma in a subtropical forest in South China.

The fern Dicranopteris dichotoma is an important pioneer species of the understory in Masson pine (Pinus massoniana) forests growing on acidic soils in the subtropical and tropical China. To improve our understanding of the role of D. dichotoma in nitrogen (N) uptake of these forests, a short-term (15)N experiment was conducted at mountain ridge (MR, with low N level) and mountain foot (MF, with high N level). We injected (15)N tracers as (15)NH4, (15)NO3 or (15)N-glycine into the soil surrounding each plant at both MR and MF sites. Three hours after tracer injection, the fern D. dichotoma took up 15NH4+ significantly faster at MF than at MR, but it showed significantly slower uptake of (15)NO3- at MF than at MR. Consequently, (15)NO3- made greater contribution to the total N uptake (50% to the total N uptake) at MR than at MF, but (15)N-glycine only contributed around 11% at both sites. Twenty-four hours after tracer injection, D. dichotoma preferred (15)NH4+ (63%) at MR, whereas it preferred (15)NO3- (47%) at MF. We concluded that the D. dichotoma responds distinctly in its uptake pattern for three available N species over temporal and spatial scales, but mainly relies on inorganic N species in the subtropical forest. This suggests that the fern employs different strategies to acquire available N which depends on N levels and time

The sentiment polarity of student demands in MOOC reviews.

The sentiment polarity of student demands in MOOC reviews.</p

The accuracy as the training of the neural network.

The accuracy as the training of the neural network.</p

Self-assembled graphene oxide microcapsules in Pickering emulsions for self-healing waterborne polyurethane coatings

A self-assembly process was employed to prepare the graphene oxide microcapsules (GOMCs), containing linseed oil as the healing agent. The nanometer-thick shells of GOMCs were built by the liquid crystalline assembling of graphene oxide (GO) sheets, forming at liquid liquid interface in Pickering emulsions. The GOMCs were embedded into waterborne polyurethane matrix, enabling the facile fabrication of self-healing composite coatings on hot-dip galvanized steel surfaces. The inclusion of GOMCs in the composite coatings not only imparted self-healing properties to the coatings, but also improved their anticorrosion properties because of the physical barrier of the GO shell, leading to much better survival to the weather/marine environment and surface wear. (C) 2017 Elsevier Ltd. All rights reserved