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Abstract Discrete event systems (DESs) are powerful abstract representations for large human-made physical systems in a wide variety of industries. Safety control issues on DESs have been extensively studied based on the logical specifications of the systems in various literature. However, when facing the DESs under uncertain environment which brings into the implicit specifications, the classical supervisory control approach may not be capable of achieving the performance. So in this research, we propose a new approach for optimal control of DESs under uncertain environment based on supervisory control theory (SCT) and reinforcement learning (RL). Firstly, we use SCT to gather deliberative planning algorithms with the aim to safe control. Then we convert the supervised system to Markov Decision Process simulation environments that is suitable for optimal algorithm training. Furthermore, a SCT-based RL algorithm is designed to maximize performance of the system based on the probabilistic attributes of the state transitions. Finally, a case study on the autonomous navigation task of a delivery robot is provided to corroborate the proposed method by multiple simulation experiments. The result shows the proposed approach owning 8.27 $$\%$$ % performance improvement compared with the non-intelligent methods. This research will contribute to further studying the optimal control of human-made physical systems in a wide variety of industries.

Recently, the application of two–dimensional (2D) piezoelectric materials has been seriously hindered because most of them possess only in–plane piezoelectricity but lack out–of–plane piezoelectricity. In this work, using first–principles calculation, by atomic substitution of penta–graphene (PG) with tiny out–of–plane piezoelectricity, we design and predict stable 2D X–PG (X = Si or Ge) semiconductors with excellent in–plane and out–of–plane piezoelectricity and extremely high in–plane hole mobility. Among them, Ge–PG exhibits better performance in all aspects with an in–plane strain piezoelectric coefficient d11 = 8.43 pm/V, an out–of–plane strain piezoelectric coefficient d33 = −3.63 pm/V, and in–plane hole mobility μh = 57.33 × 103 cm2 V−1 s−1. By doping Si and Ge atoms, the negative Poisson’s ratio of PG approaches zero and reaches a positive value, which is due to the gradual weakening of the structure’s mechanical strength. The bandgaps of Si–PG (0.78 eV) and Ge–PG (0.89 eV) are much smaller than that of PG (2.20 eV), by 2.82 and 2.47 times, respectively. This indicates that the substitution of X atoms can regulate the bandgap of PG. Importantly, the physical mechanism of the out–of–plane piezoelectricity of these monolayers is revealed. The super–dipole–moment effect proposed in the previous work is proved to exist in PG and X–PG, i.e., it is proved that their out–of–plane piezoelectric stress coefficient e33 increases with the super–dipole–moment. The e33–induced polarization direction is also consistent with the super–dipole–moment direction. X–PG is predicted to have prominent potential for nanodevices applied as electromechanical coupling systems: wearable, ultra–thin devices; high–speed electronic transmission devices; and so on.

The equipment investment is large and the annual operating cost is high in oversized open-pit mines. The rationality of the truck-shovel selection and matching has a more prominent influence on the economic benefit of mines. Therefore, we set up an optimization method of truck-shovel selection for oversized open-pit mines, and developed a software system of truck-shovel matching to solve the problem of truck-shovel selection and matching for oversized open-pit mines. First, based on the likelihood statistics method to decide the reasonable quantity range of shovels in the oversized open-pit mine, the selection and matching of shovels under different production scales are realized according to the production ability equation of shovels. Then, according to the principal of deciding the truck by shovel, and by deciding the shovel equipment, the truck-shovel efficiency model is constructed, the proper bucket-to-capacity ratio is obtained in the oversized open-pit mine, and the economic range of truck matching under different shovel specifications is determined by the bucket-to-ability ratio. Finally, using this method, the software system of truck-shovel matching is developed by using C# language, which can automatically calculate the quantity of equipment and the material consumption. The results show that the reasonable number of shovels for the oversized open-pit mine should be 4~7, and the bucket-to-capacity ratio should be 4~5:1. When the annual excavation quantity of the mine is 80~150 million tons, the 35~55 m3 shovels should be the mainstream specification. The research results were applied to a new oversized open-pit mine in Tibet, China, and the problem of equipment selection was solved.

Antibiotics are widely detected in the water environment, posing a serious threat to the health of humans and animals. The effect of levofloxacin (LOFL) on pollutant removal and the difference in the influence mechanisms at normal and low temperatures in constructed wetlands are worth discussing. A hydroponic culture experiment was designed with Iris pseudacorus L. at low and normal temperatures. LOFL (0–100 µg/L) was added to the systems. The results indicated that the removal of pollutants was affected most by temperature, followed by LOFL concentration. At the same concentration of LOFL, the pollutant removal rate was significantly higher at normal temperature than at low temperature. Low concentrations of LOFL promoted the degradation of pollutants except TN under normal-temperature conditions. Compared with the results at low temperature, the bacterial community richness was higher and the diversity of bacterial communities was lower under normal-temperature conditions. The genera and the function of bacteria were greatly affected by antibiotic concentration, temperature and test time. A series of microorganisms resistant to antibiotics and low temperature were identified in this study. The results will provide valuable information and a reference for our understanding of the ecological effects of LOFL.

In this manuscript, we have developed an efficient spraying method to successfully fabricate a series of flower-like coordination polymers (CP) microparticles, including Co/BDC (1,4-benzenedicarboxylate) metal organic frameworks (MOF) and infinite coordination polymers (ICP) microparticles, as well as Ni-Co/BDC MOF and Zn/DOBDC (2,5-dioxido-1,4-benzenedicarboxylate) MOF. The spraying method has shown high efficiency and universality in synthesizing the flower-like CP. The crystalline structure can be adjusted by varying the solvent composition in the spraying process. SEM observation demonstrated the MOF and ICP microparticles possess the similar flower-like structure, which is composed of nanoflakes with smooth surface, and the flower-like microparticles could be monodisperse with as low as 5% polydispersity. Moreover, the fabrication of the flower-like CP microparticles by spraying has a wide operation window, because there is no need to precisely control the experiment conditions, like solvents, concentration, and spray order. Due to the practicality of spray technique, this work would pave the way for the manufacture of the flower-like materials and have great potential in applications of catalysis, sensor, energy storage, and so on.

Diverse dietary constituents, encompassing both macro- and micronutrient intakes, have established connections with various cancers, though their specific roles in cervical cancer remain unclear. This study explores dietary intake correlations among women aged 30 yrs and above diagnosed with cervical cancer (n=215), contrasted with women without (n=860). These populations were selected from the 1999–2018cycle of the National Health and Nutrition Examination Survey. The research implemented the univariate analysis and the least absolute shrinkage and selection operator (LASSO) regression to estimate the association of 29 variables with cervical cancer, subsequently identifying the most pertinent variables linked to cervical cancer. Six covariates emerged as significantly associated with cervical cancer in univariate analyses (age, race, fiber, magnesium, caffeine, vitamin C) (p<0.05). In LASSO regression, with the escalating penalty factor (λ), it was discerned that specific covariates, including age, race, fiber, and Vitamin C, consistently remained in the model. Univariate analysis and logistic LASSO regression findings suggested that diets deficient in fiber and vitamin C were related to cervical cancer. [ABSTRACT FROM AUTHOR]