Transcriptomic and Physiological Variations of Three Arabidopsis Ecotypes in Response to Salt Stress.

Salt stress is one of the major abiotic stresses in agriculture worldwide. Analysis of natural genetic variation in Arabidopsis is an effective approach to characterize candidate salt responsive genes. Differences in salt tolerance of three Arabidopsis ecotypes were compared in this study based on their responses to salt treatments at two developmental stages: seed germination and later growth. The Sha ecotype had higher germination rates, longer roots and less accumulation of superoxide radical and hydrogen peroxide than the Ler and Col ecotypes after short term salt treatment. With long term salt treatment, Sha exhibited higher survival rates and lower electrolyte leakage. Transcriptome analysis revealed that many genes involved in cell wall, photosynthesis, and redox were mainly down-regulated by salinity effects, while transposable element genes, microRNA and biotic stress related genes were significantly changed in comparisons of Sha vs. Ler and Sha vs. Col. Several pathways involved in tricarboxylic acid cycle, hormone metabolism and development, and the Gene Ontology terms involved in response to stress and defense response were enriched after salt treatment, and between Sha and other two ecotypes. Collectively, these results suggest that the Sha ecotype is preconditioned to withstand abiotic stress. Further studies about detailed gene function are needed. These comparative transcriptomic and analytical results also provide insight into the complexity of salt stress tolerance mechanisms

A big-data approach for investigating destination image gap in Sanya City: When will the online and the offline goes parted?

Tourism destination images in terms of the gaps between the projected and perceived images are of great significance in the development of destinations. Additionally, the use of big-data in tourism studies remains under-utilized despite the boom in big-data applications and the increasing number of electronic User Generated Contents (UGC). Aiming to take advantage of tourism UGC to fully understand the destination image gap between official promotion materials and tourist perception of Sanya City in China, this study innovatively employed a big-data analysis technique, Tourism Sentiment Evaluation (TSE) model and proposed a new analysis framework integrating the “cognitive-affective” model with the gap analysis of projected and perceived destination image to explore the destination image gap of Sanya. It is found that Sanya’s perceptive destination image is overall consistent with its official positioning; however, there also exist image gaps between the two groups in terms of the impact of festival events and tourists’ attitude towards core scenic spots amongst others. This study’s findings are discussed in light of their methodological, theoretical, and practical implications for destination positioning, marketing, and management

A Cost Function Approach to the Prediction of Passenger Distribution at the Subway Platform

This paper proposes a cost function approach to predict the passenger distribution at the platform, which is contributed to provide services to the passenger safety and convenience and also an efficient use of the subway platform. According to the limited observation and field data collection of Beijing Xuanwumen subway station, passenger behaviors and basic attributes at the platform are analyzed. Based on the analysis and investigation, factors including the distance to the waiting area, the passenger density in the visual field, and the length of the waiting area occupied by passengers are put forward as important factors to affect the choice of the waiting area. The determination of the real-time choice defined by these factors is applied to model the passengers’ waiting area choice behaviors. Simulation experiments are run for the model calibration and validation combining with the collected field data. The results show that the passenger distribution which arises from the model is capable of keeping consistent with the actual distribution in the rough. The model is helpful for controlling how heavy carriages are congested and providing suggestions to optimize the layout of platform facilities

A Young Seedling Stripe2 phenotype in rice is caused by mutation of a chloroplast-localized nucleoside diphosphate kinase 2 required for chloroplast biogenesis

Abstract Chloroplast development and chlorophyll (Chl) biosynthesis in plants are regulated by many genes, but the underlying molecular mechanisms remain largely elusive. We isolated a rice mutant named yss2 (young seedling stripe2) with a striated seedling phenotype beginning from leaf 2 of delayed plant growth. The mutant developed normal green leaves from leaf 5, but reduced tillering and chlorotic leaves and panicles appeared later. Chlorotic yss2 seedlings have decreased pigment contents and impaired chloroplast development. Genetic analysis showed that the mutant phenotype was due to a single recessive gene. Positional cloning and sequence analysis identified a single nucleotide substitution in YSS2 gene causing an amino acid change from Gly to Asp. The YSS2 allele encodes a NDPK2 (nucleoside diphosphate kinase 2) protein showing high similarity to other types of NDPKs. Real-time RT-PCR analysis demonstrated that YSS2 transcripts accumulated highly in L4 sections at the early leaf development stage. Expression levels of genes associated with Chl biosynthesis and photosynthesis in yss2 were mostly decreased, but genes involved in chloroplast biogenesis were up-regulated compared to the wild type. The YSS2 protein was associated with punctate structures in the chloroplasts of rice protoplasts. Our overall data suggest that YSS2 has important roles in chloroplast biogenesis

Big Data in the Big D

Presentation paper for the 2017 International Conference on Knowledge Management. This paper introduces the study and practice of design knowledge management and knowledge transfer across the design of a newly built nuclear power plant in China