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The existing coal mine equipment digital twin modeling method mainly focuses on single equipment modeling. It lacks three machine coupling collaborative relationship analysis. In order to solve the above problems, the paper puts forward three machine digital twin and collaborative modeling method for fully mechanized working face. By adopting an intelligent modeling method, the method constructs agent-based models of a coal mining machine, a hydraulic support and a scraper conveyor which comprise a sensing unit, a control unit and an execution unit. The method constructs corresponding visual models according to a three-dimensional modeling process. The method drives the three-dimensional models to move by the intelligent models. The combination of the two forms a digital twin model of three machines. A discrete event modeling method is used to construct a collaborative process model covering the interaction process of the three machine digital twin model. The three machine mining process is sorted out according to the time sequence to form a three machine collaborative process time sequence table. The digital twin model is used to describe the state and behavior of the three machines in fully mechanized mining and to simulate the calculation at the individual level. The collaborative process model is used to represent the sequential action transformation between digital twin models and realize the deduction of the whole three machine collaborative process. The simulation of rocker lifting and lowering for the digital twin model of the shearer is carried out. The simulation results show that compared with the measured data of real equipment, the model error is small, an average error of rocker arm dip angle is 2.3°. The simulation of continuous column lifting action for the digital twin model of hydraulic support is carried out. The simulation results show good consistency between the model and real equipment. Compared with the measured data of the real equipment, the average angle error is 0.14° and the average stroke error is 6.3 mm. Combined with the actual production log of the coal mine, the virtual and real simulation experiment of the three machine collaborative model is carried out. The results show that the three machine digital twin model of the fully mechanized working face and real equipment realize mutual mapping. The simulation results are close to the real records. The three machine collaborative model can accurately reflect the collaborative mining process. The method of three machine digital twin and collaborative modeling for fully mechanized working face provides a new idea for the digital twin modeling of fully mechanized coal mining equipment and its collaborative relationship.

A liquid chromatography–tandem mass spectrometry method with vonoprazan fumarate‐d4 as a stable isotope‐labeled internal standard was developed and validated aiming at quantification of vonoprazan fumarate in human plasma for a bioequivalence study. Chromatographic separation was achieved by acetonitrile one‐step protein precipitation using a gradient elution of 0.1% formic acid aqueous solution and acetonitrile with a run time of 3.65 min. Detection was carried out on a tandem mass spectrometer in multiple reaction monitoring mode via a positive electrospray ionization interface. The multiple reaction monitoring mode of precursor–product ion transitions for vonoprazan fumarate and vonoprazan fumarate‐d4 were m/z 346.0 → 315.1 and 350.0 → 316.0, respectively. The linear range was 0.150–60.000 ng/ml. This method was fully validated with acceptable results in terms of selectivity, carryover, lower limit of quantification, calibration curve, accuracy, precision, dilution effect, matrix effect, stability, recovery and incurred sample reanalysis. A successful application of this method was realized in the bioequivalence study of vonoprazan fumarate tablet (20 mg) among healthy Chinese volunteers. [ABSTRACT FROM AUTHOR]

Meat and meat products are highly susceptible to contamination by microorganisms and foodborne pathogens, which cause serious economic losses and health hazards. The large consumption and waste of meat and meat products means that there is a need for safe and effective preservation methods. Furthermore, toxicological aspects of chemical preservation techniques related to major health problems have sparked controversies and have prompted consumers and producers to turn to natural preservatives. Consequently, natural preservatives are being increasingly used to ensure the safety and quality of meat products as a result of customer preferences and biological efficacy. However, information on the current status of these preservatives is scattered and a comprehensive review is lacking. Here, we review current knowledge on the classification, mechanisms of natural preservatives and their applications in the preservation of meat and meat products, and also discuss the potential of natural preservatives to improve the safety of meat and meat products. The current status and the current research gaps in the extraction, application and controlled‐release of natural antibacterial agents for meat preservation are also discussed in detail. This review may be useful to the development of efficient food preservation techniques in the meat industry. © 2024 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

The Blasingame method is a valuable tool for analysing the diminishing production challenge in the presence of variable bottomhole pressure and diverse production conditions. It is essential to highlight that the Blasingame method views the closed reservoir as the outer boundary condition for its model. This paper introduces the concept of the equivalent well control radius and formulates the Blasingame method based on the fluid flow characteristics inherent in twin-well production, taking into account the influence of inter- well interference. This study provides an in-depth analysis of production variations in reservoirs with inter-well interference by examining Blasingame type-curve definitions of the dimensionless parameters. Additionally, it investigates key factors impacting production, including neighbouring wells' production, distance, and opening time: variations in all three parameters lead to different levels of interference between wells, which manifests itself in the regularised production integral derivative curve with different lengths and heights of convexity. Numerical simulations employing orthogonality are conducted to validate the reliability of this method. The results of these simulations offer theoretical support for the precise evaluation of reservoirs facing similar challenges. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) with non-orthogonal multiple access (NOMA) has been anticipated to offer diverse real-time applications, wherein the crux is to guarantee the age of information (AoI) for dynamic traffic. However, the traffic temporal variation provokes the interdependence between queue status and interference, in which context the AoI performance remains to be further explored. In this paper, an analytical framework is established to characterize the AoI performance in NOMA-IoT networks with random Bernoulli and deterministic periodic arrivals. Particularly, a numerical algorithm is devised to obtain the queue service rate, and tractable expressions for AoI violation probability and average AoI under both the first-come first-served (FCFS) and the preemptive last-come first-served (LCFS-PR) service disciplines are derived. Simulations are conducted to validate the proposed analysis. The results unveil that LCFS-PR conduces to better AoI performance than FCFS, and yet the gain diverges for each device with different traffic arrival configurations. In addition, the result shows that with sporadic traffic arrival, the periodic pattern outperforms the Bernoulli pattern, whereas this advantage gradually diminishes with more frequent packet arrival. [ABSTRACT FROM AUTHOR]