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Currently, nonalcoholic fatty liver disease (NAFLD) is the main cause of chronic liver disease and liver-related mortality worldwide. Hepatocellular carcinoma (HCC) is a fatal complication in patients with NAFLD. However, whether statins can reduce the risk of HCC in patients with NAFLD remains controversial. We aimed to determine the relationship between statin use and HCC occurrence among patients with NAFLD. We independently retrieved related studies from PubMed, EMBASE, Cochrane Library, Web of Science, and ClinicalTrial.gov (from 1 January 2000 to 27 February 2022). The main outcome was the development of HCC. A fixed-effects model was used to merge odds ratio (OR) in the meta-analysis. Five studies involving 684 363 patients were included. The results of the meta-analysis suggested a significantly lower risk of HCC among statin users with NAFLD [OR = 0.59; 95% confidence interval (CI), 0.39–0.89; I2= 87.90%]. Additionally, a lower risk of HCC was observed among patients with NAFLD aged less than 65 years (OR = 0.59; 95% CI, 0.46–0.77; I2= 20.50%). Statins can reduce the risk of HCC in patients aged less than 65 years with NAFLD.

Fresh water is a vital resource of the modern civilization but comprises less than 3% of the world’s water. It is recognized that the next decades are likely to see a considerable rise of world population and as a result, the water supply will need to increase, thus raising concerns of an imminent shortage. Water conservation methods, such as the recycling and reuse of water, can improve the water quality and reduce both the stress on water supplies and the human impact on the freshwater ecosystems. This paper provides a comprehensive analysis of the water recycling process applied to the Jiangsu Province by the use of representative simulations. Each model considers different processes of wastewater treatment along with various requisites for improving water quality and cost of facility. A case scenario of recycled water indicates that this advanced model is cost-effective and could play a leading role in Jiangsu Province. Furthermore, we believe that our model might be useful for solving the water scarcity of other urban developments.

Electrical safety is a major threat to public safety worldwide, with fires and explosions causing damage to property and loss of life. Detection and monitoring of the occurrence of destructive current spikes can provide valuable insights into system health and inform preventative maintenance. Current sensors based on the Magnetoelectric (ME) effect have been regarded as optimal solutions because of the low power consumption and high sensitivity of ME devices compared to conventional current sensors (current transformers, Hall-effect current sensors, etc.). However, none of the conventional sensing techniques can provide ex-situ recording or a means for a human-readable signal output. Development of a current sensor that can sense, visualize, and record a current level remains a challenge. Here, we report an electric current visualization sensor that uses a coupled magnetoelectric/electrochromic effect to transform environmental current energy into electrical signals, and subsequently to a color change readily interpreted by a human observer. The current visualization sensor uses a PZT piezoelectric microfiber composite (MFC) / FeSiB alloy (Metglas) laminate combined with a Prussian blue-based electrochromic device (ECD). Such a current sensor demonstrates high efficiency self-powered current sensing and non-volatile signal recording.

Real-time scheduling methods are essential and critical to complex product flexible shop-floor due to the dynamic events in the production process, such as new job insertions, machine breakdowns and frequent rework. Recently, digital twin (DT) technology can help identify disturbances by continuously comparing physical space with virtual space, which enables real-time scheduling and greatly reduces the deviation between pre-schedule and actual schedule. However, the conventional scheduling models and algorithms cannot satisfy the adaptiveness and timeliness requirements of optimization in DT enabled shop-floor (DTS). To address above challenges, an overall framework of DT enabled real-time scheduling (DTE-RS) for complex product shop-floor is proposed to effectively reduce adverse impacts of the dynamic disturbances and minimize the makespan. Firstly, complex product flexible job shop scheduling problem (CPFJSP) is formulated as Markov Decision Process (MDP), taking into account machine breakdown and new job insertions. Then, deep Q-network (DQN) based solution is developed to achieve optimal task dispatching according to real-time production state. Finally, the case study for aircraft overhaul shop-floor is conducted to demonstrate effectiveness and feasibility of the proposed real-time scheduling method. Through experimental comparison, it is indicated that the proposed method could effectively respond to dynamic disturbances and outperform the dynamic scheduling method in terms of makespan.