Self-trapping of Bose-Einstein condensates in optical lattices

The self-trapping phenomenon of Bose-Einstein condensates (BECs) in optical lattices is studied extensively by numerically solving the Gross-Pitaevskii equation. Our numerical results not only reproduce the phenomenon that was observed in a recent experiment [Anker {\it et al.}, Phys. Rev. Lett. {\bf 94} (2005)020403], but also find that the self-trapping breaks down at long evolution times, that is, the self-trapping in optical lattices is only temporary. The analysis of our numerical results shows that the self-trapping in optical lattices is related to the self-trapping of BECs in a double-well potential. A possible mechanism of the formation of steep edges in the wave packet evolution is explored in terms of the dynamics of relative phases between neighboring wells.Comment: 8 pages, 15 figure

Sensitive frequency-dependence of the carrier-envelope phase effect on bound-bound transition: an interference perspective

We investigate numerically with Hylleraas coordinates the frequency dependence of the carrier-envelope phase (CEP) effect on bound-bound transitions of helium induced by an ultrashort laser pulse of few cycles. We find that the CEP effect is very sensitive to the carrier frequency of the laser pulse, occurring regularly even at far-off resonance frequencies. By analyzing a two-level model, we find that the CEP effect can be attributed to the quantum interference between neighboring multi-photon transition pathways, which is made possible by the broadened spectrum of the ultrashort laser pulse. A general picture is developed along this line to understand the sensitivity of the CEP effect to laser's carrier frequency. Multi-level influence on the CEP effect is also discussed

Improving Stock Trading Decisions Based on Pattern Recognition Using Machine Learning Technology

PRML, a novel candlestick pattern recognition model using machine learning methods, is proposed to improve stock trading decisions. Four popular machine learning methods and 11 different features types are applied to all possible combinations of daily patterns to start the pattern recognition schedule. Different time windows from one to ten days are used to detect the prediction effect at different periods. An investment strategy is constructed according to the identified candlestick patterns and suitable time window. We deploy PRML for the forecast of all Chinese market stocks from Jan 1, 2000 until Oct 30, 2020. Among them, the data from Jan 1, 2000 to Dec 31, 2014 is used as the training data set, and the data set from Jan 1, 2015 to Oct 30, 2020 is used to verify the forecasting effect. Empirical results show that the two-day candlestick patterns after filtering have the best prediction effect when forecasting one day ahead; these patterns obtain an average annual return, an annual Sharpe ratio, and an information ratio as high as 36.73%, 0.81, and 2.37, respectively. After screening, three-day candlestick patterns also present a beneficial effect when forecasting one day ahead in that these patterns show stable characteristics. Two other popular machine learning methods, multilayer perceptron network and long short-term memory neural networks, are applied to the pattern recognition framework to evaluate the dependency of the prediction model. A transaction cost of 0.2% is considered on the two-day patterns predicting one day ahead, thus confirming the profitability. Empirical results show that applying different machine learning methods to two-day and three-day patterns for one-day-ahead forecasts can be profitable

Operation strategies of capital-constrained small and medium-sized enterprises based on blockchain technology

Introduction: In reality, due to the low credit rating of small and medium-sized enterprises (SMEs), it is difficult for them to obtain sufficient financing from a single financier. This paper considers a dual-channel supply chain consisting of a capital-constrained manufacturer, an e-commerce platform (ECP), a third-party logistics company (3PL) and consumers. There are two innovations in this paper: the manufacturer obtains sufficient production funds through hybrid financing of the ECP and 3PL, and consumers want to know product information and compare prices. The contributions of this paper are to investigate new applications of blockchain in both hybrid financing and meeting consumer information search needs.Methodology: We discuss the operation and pricing decisions of supply chain in two scenarios. These two scenarios are without adopting blockchain (N) and with adopting blockchain (B). Then, we compare the equilibrium decisions in two scenarios.Results: The results show that the supply chain will adopt blockchain when certain conditions are met. The initial adoption of blockchain is bad for the ECP and 3PL. Further, we find that with the increase of financing ratio, the optimal financing interest rate of the ECP decreases, while the optimal financing interest rate of the 3PL increases.Discussion: The numerical analysis shows that the adoption of blockchain can be more profitable when the cost of information search is high.Management insights: In order to achieve supply chain coordination, the manufacturer should give subsidies the ECP and 3PL

Diverse biological effects of glycosyltransferase genes from Tartary buckwheat

Background: Tartary buckwheat (Fagopyrum tataricum) is an edible cereal crop whose sprouts have been marketed and commercialized for their higher levels of anti-oxidants, including rutin and anthocyanin. UDP-glucose flavonoid glycosyltransferases (UFGTs) play an important role in the biosynthesis of flavonoids in plants. So far, few studies are available on UFGT genes that may play a role in tartary buckwheat flavonoids biosynthesis. Here, we report on the identification and functional characterization of seven UFGTs from tartary buckwheat that are potentially involved in flavonoid biosynthesis (and have varying effects on plant growth and development when overexpressed in Arabidopsis thaliana.) Results: Phylogenetic analysis indicated that the potential function of the seven FtUFGT proteins, FtUFGT6, FtUFGT7, FtUFGT8, FtUFGT9, FtUFGT15, FtUFGT40, and FtUFGT41, could be divided into three Arabidopsis thaliana functional subgroups that are involved in flavonoid biosynthesis of and anthocyanin accumulation. A significant positive correlation between FtUFGT8 and FtUFGT15 expression and anthocyanin accumulation capacity was observed in the tartary buckwheat seedlings after cold stress. Overexpression in Arabidopsis thaliana showed that FtUFGT8, FtUFGT15, and FtUFGT41 significantly increased the anthocyanin content in transgenic plants. Unexpectedly, overexpression of FtUFGT6, while not leading to enhanced anthocyanin accumulation, significantly enhanced the growth yield of transgenic plants. When wild-type plants have only cotyledons, most of the transgenic plants of FtUFGT6 had grown true leaves. Moreover, the growth speed of the oxFtUFGT6 transgenic plant root was also significantly faster than that of the wild type. At later growth, FtUFGT6 transgenic plants showed larger leaves, earlier twitching times and more tillers than wild type, whereas FtUFGT15 showed opposite results. Conclusions: Seven FtUFGTs were isolated from tartary buckwheat. FtUFGT8, FtUFGT15, and FtUFGT41 can significantly increase the accumulation of total anthocyanins in transgenic plants. Furthermore, overexpression of FtUFGT6 increased the overall yield of Arabidopsis transgenic plants at all growth stages. However, FtUFGT15 shows the opposite trend at later growth stage and delays the growth speed of plants. These results suggested that the biological function of FtUFGT genes in tartary buckwheat is diverse

Effect of amber powder on endometrial ultrastructure and MAPK pathway in endometriosis model rats

Purpose: To explore the therapeutic role of amber powder in endometriosis by investigating its effect on endometrial ultrastructure, ERK1/2, p38MAPK, and NF-κB mRNA pathways and CSRC/EFR/ERK1/2 proteins. Methods: Sprague Dawley (SD) rats were randomly divided into blank group, disease model group (untreated), amber powder high-dose group, amber powder medium-dose group, amber powder lowdose group and danazol group. Morphological changes in endometrial cells were studied using transmission electron microscopy. The expression of ERK1/2, p38MAPK, and NF-κB mRNA in endometrial tissues of each group was determined using quantitative real-time polymerase chain reaction (qRT-PCR). Immunohistochemistry was utilized for the measurement of C-SRC/EFR/ERK1/2 pathway protein expression. Results: The endometriosis rats treated with a high-, medium- and low-dose amber powder showed a decrease in the volume of ectopic lesions, compared with the untreated disease model group. The expressions of ERK1/2, p38MAPK, NF-κB mRNA, and C-SRC/EFR/ERK1/2 protein were higher in the eutopic and ectopic endometrial tissues in untreated disease group than those in normal control group. Moreover, treatment of endometriosis rats with amber powder revealed a reduction in the expressions of ERK1/2, p38MAPK, NF-κB mRNA and C-SRC/EFR/ERK1/2 proteins in eutopic and ectopic endometrium tissues. Conclusion: Amber powder reduces ectopic lesions and slows down the development of endometriosis, probably via inhibition of MAPK pathway genes in eutopic and ectopic endometrial tissues

Deglacial release of petrogenic and permafrost carbon from the Canadian Arctic impacting the carbon cycle

AbstractThe changes in atmospheric pCO2 provide evidence for the release of large amounts of ancient carbon during the last deglaciation. However, the sources and mechanisms that contributed to this process remain unresolved. Here, we present evidence for substantial ancient terrestrial carbon remobilization in the Canadian Arctic following the Laurentide Ice Sheet retreat. Glacial-retreat-induced physical erosion of bedrock has mobilized petrogenic carbon, as revealed by sedimentary records of radiocarbon dates and thermal maturity of organic carbon from the Canadian Beaufort Sea. Additionally, coastal erosion during the meltwater pulses 1a and 1b has remobilized pre-aged carbon from permafrost. Assuming extensive petrogenic organic carbon oxidation during the glacial retreat, a model-based assessment suggests that the combined processes have contributed 12 ppm to the deglacial CO2 rise. Our findings suggest potentially positive climate feedback of ice-sheet retreat by accelerating terrestrial organic carbon remobilization and subsequent oxidation during the glacial-interglacial transition.</jats:p