Structural Changes and Regional Disparity in China's Inflation

The inflation problem in China has attracted a great deal of international attention in recent years. This paper examines the time series properties of China's CPI series. It is found that the overall inflation series and the inflation of food, tobacco, clothes, urban transport and urban housing are not persistent. Structural breaks in inflation are found in 2003 and 2004. The degree of rural-urban inflation disparity in China is also investigated. We find evidence that rural residents experience higher inflation than their urban counterparts.Structural Break, Unit Root, ADF Test, Rural and Urban Inflation.

The legacy of shamans? Structural and cognitive perspectives of prehistoric symbolism in the Bering Strait region

This research explores the meanings of prehistoric artistic artifacts discovered in the Bering Strait region. The research focuses on the prehistoric period between AD 100 and 1700, including Okvik culture, Old Bering Sea culture, Punuk Culture, Birnirk Culture, Thule culture, and Ipiutak Culture. My archaeological data in this research were collected from the archaeological collections of the Okvik site on Punuk Islands, the Kukulik site on St. Lawrence Island, and the Nukleet site at Cape Denbigh at the University of Alaska Museum of the North. Based on abundant ethnographic records from the Bering Strait region, this research relies on ethnographic analysis as methodology to approach prehistoric symbolism. Applying ethnographic analysis results in diverse interpretations of the archaeological artifacts, which bear potential spiritual or secular meanings. Theoretically, the research provides an assessment of contemporary archaeological theories such as cognitive archaeology, structural archaeology, and shamanism theory (general shamanism theory and the neuropsychological model) in order to examine the reliability of these theories in the study of prehistoric art. Due to the problems of cognitive, structural, and shamanism theories, the conclusion of this research builds on practice theory and animist ontology to interpret the variants of art productivity, cosmological structures, and relationship between humans and materials.Chapter 1: Introduction -- Chapter 2: Cognitive archaeology, structural archaeology, and the archaeology of shamanism -- Chapter 3: An archaeological review of prehistoric art in the Bering Strait Region -- Chapter 4: Art symbolism and practices in ethnographic records -- Chapter 5: Ethnographic perspectives of archaeological artifacts -- Chapter 6: Structural and cognitive perspectives -- Chapter 7: Summary and conclusions -- References

ELECTROMYOGRAPHIC ACTIVITY OF ELITE 100M ATHLETE BEFORE AND AFTER BREAKING RECORD – A CASE STUDY

The purpose of this study was through the fractal dimension analysis of an elite 100M ahtlete EMG signals before and after the competition. Results showed that the fractal dimension of athlete’s EMG signals were apparently different at different training states. In addition the fractal dimension of athlete’s EMG signals were identical at the different training loads. The fractal dimension of EMG signals from different muscle groups of the same athlete accomplishing the same movement were relatively stable. However the fractal dimension of EMG signals at different contractile states of muscles were apparently different at the same training phase

CHAOTIC CHARACTER OF SPRINTER'S MYOELECTRIC SIGNAL

There are different myoelectric reactions during muscle's motion when athletes are at different training stage. This study analyzed the myoelectric signal at different training stage of athletes according to chaotic theory and found that there were differences in the spectrum character of myoelectric signal and embedding dimension at different training stage of athletes. The results show that the myoelectric signal spectrum at relaxed status of the muscles mainly presents random noisy spectrum character, but the myoelectric signal spectrum at concentric contraction of the muscles presents divided modality spectrum character. The embedding dimension of myoelectric signal is obviously less at contracted status than at relaxed status. The relative value of embedding dimension of myoelectric signal is far larger during the preparation before tournament than during the transition stage

Deep Learning Predicts Stress–Strain Relations of Granular Materials Based on Triaxial Testing Data

This study presents an AI-based constitutive modelling framework wherein the prediction model directly learns from triaxial testing data by combining discrete element modelling (DEM) and deep learning. A constitutive learning strategy is proposed based on the generally accepted frame-indifference assumption in constructing material constitutive models. The low-dimensional principal stress-strain sequence pairs, measured from discrete element modelling of triaxial testing, are used to train recurrent neural networks, and then the predicted principal stress sequence is augmented to other high-dimensional or general stress tensor via coordinate transformation. Through detailed hyperparameter investigations, it is found that long short-term memory (LSTM) and gated recurrent unit (GRU) networks have similar prediction performance in constitutive modelling problems, and both satisfactorily predict the stress responses of granular materials subjected to a given unseen strain path. Furthermore, the unique merits and ongoing challenges of data-driven constitutive models for granular materials are discussed