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Foreign exchange is the largest financial market in the world, and it is also one of the most volatile markets. Technical analysis plays an important role in the forex market and trading algorithms are designed utilizing machine learning techniques. Most literature used historical price information and technical indicators for training. However, the noisy nature of the market affects the consistency and profitability of the algorithms. To address this problem, we designed trading rule features that are derived from technical indicators and trading rules. The parameters of technical indicators are optimized to maximize trading performance. We also proposed a novel cost function that computes the risk-adjusted return, Sharpe and Sterling Ratio (SSR), in an effort to reduce the variance and the magnitude of drawdowns. An automatic robotic trading (RoboTrading) strategy is designed with the proposed Genetic Algorithm Maximizing Sharpe and Sterling Ratio model (GA-MSSR) model. The experiment was conducted on intraday data of 6 major currency pairs from 2018 to 2019. The results consistently showed significant positive returns and the performance of the trading system is superior using the optimized rule-based features. The highest return obtained was 320% annually using 5-minute AUDUSD currency pair. Besides, the proposed model achieves the best performance on risk factors, including maximum drawdowns and variance in return, comparing to benchmark models. The code can be accessed at https://github.com/zzzac/rule-based-forextrading-system

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6 Li and 7 Li, with excellent nuclear properties, are important raw materials in the development of the nuclear industry. In the current work, a mercury-free extraction and lithium isotopic separation system with benzo-15-crown-5 (B15C5) ether as the extractant, ionic liquid as the co-extractant, and anisole as the diluent was constructed. In addition, a novel method for extracting lithium ions with B15C5 and multistage cross-flow separation of lithium isotopes by the organic liquid film were introduced. After 20 stages of cross-flow extraction, the abundance of 6 Li increased from 7.498 to 9.654% and the abundance of 7 Li increased from 92.502 to 93.561%. It was demonstrated that the B15C5 system not only can enrich 6 Li but also can serve to enrich 7 Li. The reason for the enrichment of lithium isotopes by this method was explored. Moreover, this study predicted the number of theoretical cross-flow stages of the abundance of 6 Li and 7 Li which can be used as a nuclear material.

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Benign prostatic hyperplasia (BPH) is a common urological disease in older males. Existing pharmacotherapy shows several side effects, and the exploration of new therapeutic strategies is of high significance. Tonglong Qibi (TQ) decoction was proved to ameliorate BPH, while the underlying mechanisms are still unclear. In the current study, we explored the anti-BPH effects of TQ in vivo and identified its main therapeutic component and the underlying mechanisms in vitro. We demonstrated that TQ mitigated BPH in rats and showed no toxicity to the liver and reproductive system. Network pharmacology identified quercetin as the main component in TQ treating BPH. Quercetin reduced proliferation, oxidative stress, and increased Nrf2 expression in hyperplastic prostate epithelial cells. These findings indicate that quercetin in TQ alleviates BPH via inhibiting oxidative stress and activating the Nrf2 signalling pathway.