Transcriptome Analysis and Physiological Responses of Economic Macroalga Gracilariopsis lemaneiformis under Sulfate Deficiency

Sulfur is an essential macronutrient for the growth of all photosynthetic organisms and plays important roles in different metabolic pathways.However,sulfur metabolism and its related research on macroalgae with important ecological value is rather limited.In this study,marine ecological valued macroalga Gracilariopsis lemaneiformis was used to study the general physiological responses and transcriptome profiling under the sulfate deficiency.The relative growth rate of algae under sulfate deficiency was statistically significantly lower than that of control after 6 days.However,no significant differences were observed in the pigments content and Fv/Fm value,indicating that the photosynthesis was not obviously affected under the sulfate deficiency.Furthermore,the significantly increased soluble protein and carbohydrate contents,and indistinctively differentially expressed sulfate transporter/permease(ST)and ATP sulfurylase(ATPS)genes suggesting that G.lemaneiformis cells did not use sulfur from internal protein and carbohydrate pools but utilize stored sulfur from vacuole to satisfy their nutritional requirements during the sulfate deficiency.Transcriptome data showed that most annotated differentially expressed genes(DEGs)were down-regulated under the sulfate deficiency,including a large proportion of genes involved in the pathway of sulfur metabolism.Therefore,it was concluded that the pathway of sulfur metabolism was suppressed under the sulfate deficiency in G.lemaneiformis.The results and analysis in this study provide a comprehensive understanding for the physiological and molecular response of G.lemaneiformis to sulfate deficiency.

Research on the Electric Energy Metering Data Sharing Method in Smart Grid Based on Blockchain

Enabling data sharing among smart grid power suppliers is a pressing challenge due to technical hurdles in verifying,storing,and synchronizing energy metering data.Access and sharing limitations are stringent for users,power companies,and researchers,demanding significant resources and time for permissions and verification.This paper proposes a blockchain-based architecture for secure and efficient sharing of electric energy metering data.Further,we propose a data sharing model based on evolutionary game theory.Based on the Lyapunov stability theory,the model’s evolutionary stable strategy(ESS)is analyzed.Numerical results verify the correctness and practicability of the scheme proposed in this paper,and provide a new method for realizing convenient,safe and fast data sharing.

Modeling and Analyzing Web Application with Aspect-Oriented Hierarchical Coloured Petri Nets

Aspect-oriented modeling can uncover potential design faults, yet most existing work fails to achieve both separation and composition in a natural and succinct way. This study presents an aspect-oriented modeling and analysis approach with hierarchical Coloured Petri Nets(HCPN). HCPN has sub-models and well-defined semantics combining a set of submodels. These two characteristics of HCPN are nicely integrated into aspect oriented modeling. Submodels are used to model aspects while the combination mechanism contributes to aspects weaving. Furthermore, the woven aspect oriented HCPN model can be simulated and analyzed by the CPN Tools. A systematic web application case study is conducted. The results show the system original properties are satisfied after weaving aspects and all design flaws are revealed. As such, the approach can support web application design and analysis in an aspect-oriented fashion concisely and effectively.