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The purpose of this paper is to develop an integrity monitoring method using ERAIM (Extended Receiver Autonomous Integrity Monitoring) for the integrated GNSS/Inertial (Global Navigation Satellite System and inertial navigation system) of general aviation aircraft.

First the tightly integrated GNSS with Strapdown Inertial Navigation System (GNSS/SINS) and the Kalman filter is designed. Then the processing of ERAIM is presented, in which the least‐squares theory is used to calculate the best estimators by integrating the predicted states with measurement states of Kalman filter. Based on the new measurement model, the integrity monitoring for GNSS/inertial system is carried out, including the fault detection, identification, reliability and separability. Lastly, the simulation and analysis for ERAIM vs RAIM are performed to validate the proposed method.

Simulation results show that the ERAIM method is able to detect and identify effectively any type of failure including step failure and ramp failure. Compared to the RAIM method for only GNSS, the ERAIM increases the redundant information and reduces the correlation of test statistics, as well as enhancing the reliability and thus can significantly improve the performance of integrity monitoring.

In safety critical sectors such as aviation, stringent integrity performance requirements must be met. The ERAIM method cannot only be used in integrity monitoring for the integrated GNSS/Inertial system, but also can be applied to only GNSS or other integrated navigation systems for general aviation aircraft.

The paper presents a new integrity monitoring method of ERAIM, which is able to improve the fault detection and identification capabilities significantly by extending GNSS‐used RAIM method into the GNSS/Inertial integrated system.

The selection of purchasing channels by wine consumers indirectly affects buying experience and satisfaction, therefore, it is of great practical significance to study consumers' preference on channel selection. The purpose of this study is to investigate the current state of consumer selection for purchasing channel and the corresponding influencing factors.

A total of 2,976 valid questionnaires were collected by convenience sampling from 34 provinces, municipalities and autonomous regions of China in 2020 via the Internet, yielding a response rate of 82.2%. A categorical statistical approach was used to understand consumer's selection for each channel. Besides, binary logistic regression model was used to analyze the factors affecting consumers' channel selection.

The results show that Chinese wine consumers' main purchasing channels are as follows: supermarket/mall, wine specialty stores, comprehensive e-business flagship stores, comprehensive e-business individual stores, restaurants and short video and live streaming platforms. Estimation results showed that among the 12 influencing factors in 4 categories, consumers' education and some other factors significantly influenced consumers' decision on wine purchasing channels.

Limited by time and experimental conditions, this study did not analyze the trend of wine consumers' purchasing channel selection. Future work would concentrate on multi-year data and conduct longitudinal comparative analysis.

This study innovatively subdivides the currently popular wine sales channels in Chinese market and conducts research related to consumer channel selection. The results of the study can provide reference for wine producers and distributors to update their strategic layout and also help various channels to understand the characteristics of their customer groups for targeted marketing.

Piston ring dynamic problem plays an important role in the lubricant characteristics of a reciprocating engine, which lead to engine wear and the increased consumption of lubricating oil. A cavitation analysis of the piston ring lubrication with two-dimensional Reynolds equation has rarely been reported owing to the complex working condition. The purpose of this study is to establish a precise model that can provide guidance for the design of the piston ring.

In this paper, a cavitation model and its effect on the piston ring lubrication was studied in a simulation program based on the mass-conserving theory which is solved by means of the Newton–Raphson method. In this study, some models such as mixed lubrication, asperity contact, blow-by/blow-back flow and cavitation have been coupled with the lubrication model.

The established model has been compared with the traditional model that deals with cavitation by using the Reynolds boundary condition algorithm. The cavitation zone, pressure distribution and density distribution between the piston ring and the cylinder have also been predicted. Studies of the changing trend for the pressure distribution and the cavitation zone at few typical crank angles have been listed to illustrate the cavitation changing rule. The analysis of the results indicates that the developed simulation model can adequately illustrate the lubrication problem of the piston ring system. All the analyses will provide guidance for the oil film rupture and the reformation process.

A two-dimensional cavitation model based on the mass-conserving theory has been built. The cavitation-forming and -developing process for the piston ring–liner lubrication has been studied. Non-cavitation occurs in the vicinity of top dead center and bottom dead center. The non-cavitation period will be longer in the vicinity of 360° of crank angle. The density distribution in the cavitation zone can be obtained.

The purpose of this paper is to provide reference for researchers by reviewing the research advances and trend of agricultural product price forecasting methods in recent years.

This paper reviews the main research methods and their application of forecasting of agricultural product prices, summarizes the application examples of common forecasting methods, and prospects the future research directions.

1) It is the trend to use hybrid models to predict agricultural products prices in the future research; 2) the application of the prediction model based on price influencing factors should be further expanded in the future research; 3) the performance of the model should be evaluated based on DS rather than just error-based metrics in the future research; 4) seasonal adjustment models can be applied to the difficult seasonal forecasting tasks in the agriculture product prices in the future research; 5) hybrid optimization algorithm can be used to improve the prediction performance of the model in the future research.

The methods from this paper can provide reference for researchers, and the research trends proposed at the end of this paper can provide solutions or new research directions for relevant researchers.

The purpose of this study comes from the need of defining improved durability values and the realization of a good traceability management for selected vegan cheeses has suggested the comparison between a processed cheese and its analogous version without animal-origin raw materials. The durability should be studied at a well-defined temperature, probably agreed among the food producer and the food processor. In addition, the traceability system should consider many components and related suppliers.

A supply chain risk assessment analysis has been carried out with relation to two different products: an analogue cheese and a vegan cheese-like preparation. Raw materials and ingredients have been evaluated (production method and origin; geographical identification), with the aim of identifying simplified food.

An assessment of food supply networks has been carried out. In the first situation (analogue cheeses), the ingredient “cheeses” shows an important complexity: five suppliers with a related six-interconnection hub. On the other side, vegan cheeses are obtained from 11 ingredients (a challenging hub); four of them may be produced from 2–5 components of different origin (five total hubs). Tested processed cheeses are represented by means of a linear food supply network with two hubs (cheeses and “arrival” show degrees 6 and 9, respectively). Networks concerning vegan cheeses include five different hubs: four complex raw materials (degree: 2, 3, 4 and 5) and the “arrival” step (degree: 12).

The information load of vegan cheeses (two hubs, degrees >> average degree) appears high if compared with processed cheeses (two hubs), although the complexity of networks appears similar. Vegan cheeses may seem technologically simpler than processed cheeses and be sometimes questioned because of important traceability issues. Adequate traceability countermeasures in terms of preventive monitoring actions should be recommended when speaking of vegan cheeses. Anyway, a centralized manager would be always required.

The purpose of this study is to comprehend and determine the impact of the COVID-19 pandemic on business organizations and society, together with its relationship to entrepreneurship, innovation, digitization or digital transformation, by means of analysis of the Spanish Internet domains registration data set.

Following existing literature regarding time series analysis, the authors have designed a SARIMA methodology involving the forecasting of a non-COVID-19 data set from the available data and compared it to the existing COVID-19 data set in order to validate the formulated hypothesis.

The COVID-19 pandemic was found to be an unfortunate accelerator, regarding entrepreneurship and innovation as a digitization and digital transformation lever, with the results of the Internet domain registration analysis as a reliable indicator.

This research confirms the existence of new non-invasive approaches to complementary information, such as Internet domain registration analysis, that could serve as an early and quick indicator of innovation and entrepreneurship initiatives within business activities.