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Chinese folk orchestral music is the product of the combination of thousands of years of Chinese instrumental ensemble culture and the excellent orchestral experience of the West. In the past hundred years, Chinese folk orchestra has gone through the process of "from learning and imitation to integration and innovation" twice. Since the New Era, Chinese folk orchestras have been developing rapidly, the number of outstanding composers has been increasing, the compositional style has been diversified, and the creative space has been active. This paper analyzes the creation of folk orchestras in the New era, and then gives the path and suggestions to promote the development of folk orchestras.

This paper aims to fulfil the methodological gaps that are prevalent within mobile banking (m-banking) practices in the government-to-person (G2P) payment sector in developing countries. By drawing upon the interpretive and social constructionist stance that underpins the theoretical framework, it highlights how the case study methodology guides a qualitative approach for data collection in the study. Hence, an interpretive case study of the Benazir Support Programme in Pakistan, provides a holistic view of m-banking practices from both programme designers as well as women user's perspective. We discuss how an interpretive methodology 'constructs' social realities around mobile banking for individually 'enabling' and 'constraining' G2P payments, and its impact on financial inclusion for socio-economic change within households. To conclude, we argue why financial education, and training is important for 'capabilities development' in the financial inclusion agenda to eradicate poverty in Pakistan.

This paper considers the scenario that all data entries in a confidentialised unit record file were masked by multiplicative noises, regardless of whether unit records are sensitive or not and regardless of whether the masked variables are dependent or independent variables in the underlying regression analysis. A technique is introduced in this paper to show how to estimate parameters in a regression model, which is originally fitted by unmasked data, based on masked data. Several simulation studies and a real-life data application are presented.

We discuss alternative approaches for estimating from cross-sectional categorical data in the presence of
misclassification. Two parameterisations of the misclassification model are reviewed. The first employs misclassification
probabilities and leads to moment-based inference. The second employs calibration probabilities and leads to maximum likelihood inference. We show that maximum likelihood estimation can be alternatively performed by employing misclassification probabilities and a missing data specification. As an alternative to maximum likelihood estimation we propose a quasi-likelihood parameterisation of the misclassification model. In this context an explicit definition of the likelihood function is avoided and a different way of resolving a missing data problem is provided.
Variance estimation for the alternative point estimators is considered. The different approaches are illustrated using real data from the UK Labour Force Survey and simulated data.