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Parallel factor analysis (PARAFAC) coupled with support-vector machine (SVM) was carried out to identify and discriminate between the fluorescence spectroscopies of coconut water brands.

PARAFAC was applied to reduce three-dimensional data of excitation emission matrix (EEM) to two-dimensional data. SVM was applied to discriminate between six commercial coconut water brands in this study. The three largest variation data from fluorescence spectroscopy were extracted using the PARAFAC method as the input data of SVM classifiers.

The discrimination results of the six commercial coconut water brands were achieved by three SVM methods (Ga-SVM, PSO-SVM and Grid-SVM). The best classification accuracies were 100.00%, 96.43% and 94.64% for the training set, test set and CV accuracy.

The above results indicate that fluorescence spectroscopy combined with PARAFAC and SVM methods proved to be a simple and rapid detection method for coconut water and perhaps other beverages.

Synthesizing the unique Confucian cultural values and the common characteristics of emerging markets, the purpose of this paper is to examine how face drives consumers’ attitudes toward global consumer culture positioning (GCCP) as well as the moderating roles of social aggrandizement and susceptibility to normative influence (SNI).

The authors adopt the total effect moderation model to test the hypotheses using data collected from China.

The results show that face positively affects consumers’ attitudes toward GCCP through enhancing their pursuit for global myth. In addition, social aggrandizement positively moderates the influence of face on pursuit for global myth. SNI positively moderates the influence of pursuit for global myth on attitudes toward GCCP.

The findings of this study highlight the need to utilize local powers to promote brands globally and provide guidelines for “Think Globally, Act Locally” in Confucian societies.

This study represents an important step in the global branding literature regarding the advancement of culturally driven attitudes toward GCCP by taking root in the Confucian culture.

The purpose of this paper is to assess the serious corrosion problems of the water injection system on the offshore oil field and to study the type, and effect factors and mechanisms of corrosion on the offshore oil field in order to develop an effective corrosion inhibitor for the sea water injection system.

The corrosion of metal in a water injection system was studied by weight‐loss and electrochemical methods.The effect factors and mechanisms of corrosion on the offshore oil field were proposed from the trend of corrosion.

FeCO₃ is the main corrosion product in the water injection system of the Chengdao Offshore Oil Field. The corrosion rate of coupons in sea water injection systems reaches a maximum peak at a temperature of 50‐60°C. The corrosion rate of coupons exposed in all three water samples increased with an increase in the dissolved oxygen concentration. When the mixed ratio of sea water and produced water and well water is 1:3:1 or 1:2:2, the corrosion rate of carbon steel is lower than is the case in pure water. The electrochemical mechanism of corrosion indicates that corrosion in the well water, produced water, and sea water samples were all controlled by the oxygen absorption process, which controlled the cathodic reaction. The corrosion rate of coupons followed the ranking order: well water; produced water; sea water.

This paper provides the main corrosion product in the water injection system of the Chengdao Offshore Oil Field, and provides new information on the effect factors and mechanisms of corrosion on the offshore oil field.

The purpose of this paper is to argue that current ways school systems have addressed social mobility is misguided at best and, at worst, hurts social mobility. Instead, we call for a focus on investment in teachers' professional capital as a primary lever for enhancing the likelihood they can effectively prepare and develop all children to lead successful lives after school. These arguments have become even more pertinent with the COVID-19 pandemic.

Using contemporary research, and grounded in our collective decades of research in these areas, we define social mobility and document how the aim of improving it has become a central tenet of our governments' stated ambitions and the yardstick by which school systems' success is measured. We then show how the application of market-based approaches to schools and teachers' work has hindered social mobility and offer a new path forward.

After 50 years of neoliberal policies incentivising individualistic and competitive behaviours, it is time to move towards policies that enhance professional capital and promote high quality collaboration between teachers. We call for a new path forward: a re-orientation to invest in teachers' capacity to realise the potential of education to improve the life prospects for all children, irrespective of their background.

As with so many issues, the COVID-19 pandemic has shone an intense light on the role of educators in society. There are credible concerns that economic and educational inequalities resulting from the crisis have the potential to trigger a fall in future social mobility levels. Yet this should also be seen as a new dawn for renewed thinking in which we seriously consider a shift away from neoliberal to professional capital policies to create an education system that nurtures teaching professionals, promotes collective behaviour and helps rather than hinders efforts to improve social mobility.

This paper aims to present an alternative airspeed computation method based on artificial neural networks (ANN) without requiring pitot-static system measurements.

The data set used to train proposed neural model is obtained from the Digital Flight Data Acquisition Unit records of a Boeing 737 type commercial aircraft for real flight routes. The proposed method uses the flight parameters as inputs of the ANN. The Levenberg–Marquardt training algorithm was used to train the neural model.

The predicted airspeed values obtained with ANN are in good agreement with the measured airspeed values. The proposed neural model can be used as an alternative airspeed computation method.

The proposed alternative airspeed computation method can be used when the air data computer or pitot-static system has failed.

The proposed method uses flight parameters as inputs for the ANN. As such, airspeed is calculated using flight parameters instead of the pitot-static system measurements.