Monetary Theory from a Chinese Historical Perspective

We discuss monetary thought in ancient China from the perspective of Western monetary theory. It sets out the structure of economic activity in the various dynasties of ancient China and emphasizes the differences in monetary structure from Europe (and later North America). Imperial China was a politically integrated structure with regional segmentation of economic activities and hence with regional money. Monetary policy was one body conducted at regional level, but overseen naturally politically before national integration under the Ming dynasty (14th century). In various regions different forms of money circulated, with gold, silver, copper, and paper all present at various times. Monetary policy was guided by monetary thought, such as later in Europe. Basic concepts such as monetary function, the velocity of circulation, inflation, interest rate parity and the quantity theory were all present. The economics of Imperial China witnessed boom and bust, inflation and deflation and monetary control much like Europe to follow. Monetary thought thus seemingly preceded Western thought, and had remarkable similarities. Whether much of this thought travelled down the silk road remains unknown, but the possibility is intriguing.

Investigation into the Water Exit Behavior of a Cavity

Launching-type ship lifts are commonly used in navigational mountain rivers to realize river channelization and communicate different water systems. However, the complicated water–gas–solid coupling process incurred during the water exit of cavities beneath a ship chamber can strongly affect the stability of the chamber and even affect the ship lift operation. In this study, the water exit behavior of a generalized cavity model was investigated using an experimental–numerical approach. Both the air pressure and flow patterns during the water exit process were analyzed. The results demonstrate three different types of air pressure process in cavity exits. Based on the results, a series of relationships are proposed to predict the maximum negative pressure incurred in the water exit process. Moreover, a method was developed to determine the optimum ported area of the cavity regarding the absence of additional hydrodynamic loads. Furthermore, a classification system to typify the flow patterns manifesting in the cavity is proposed. It was found that the transition from a slug flow to a drop flow could be determined as a transition coefficient K equal to 1

Design method for throttle holes area of telescopic shock absorber tric Vehicles

Abstrac

Does right hemisphere compensate for the left in school-age children with large left middle fossa arachnoid cysts?

Abstract Background To assess the cognitive function changes and brain network neuroplasticity in school-age children having large (diameter > 5 cm) left middle fossa arachnoid cyst (MFACs). Methods Eleven patients and 22 normal controls (NC) between 6 and 14 years of age were included. The CNS Vital Signs (CNS VS) were administered for cognitive assessment. The differences of cognitive data and functional connectivity (FC) in resting-state functional magnetic resonance imaging (rs-fMRI) were compared between the patient group and the NC group. The correlations between the altered FC and cognitive data in the patient group were assessed. Results Patient group had significantly poorer attention (including Complex Attention, Sustained Attention, Simple Attention, Cognitive Flexibility, and Executive Function) and memory function (Visual Memory and Working Memory) than the NC group (uncorrected p-value, p-unc < 0.05). Whole-brain local correlation (LCOR) analysis showed an extensively lower LCOR in the patient group (voxel threshold p-unc < 0.001, cluster-size threshold of false discovery rate adjusted p (p-FDR) < 0.001). Functional connectivity (FC) analysis showed that bilateral frontal and temporal lobes connectivity in the patient group was significantly lower than the NC group (p-FDR < 0.05). Seed-based FC analysis indicated that there was altered FC between the right temporal lobe and the left temporal-parietal/temporal-occipital area (p-FDR < 0.05). In the patient group, most of the altered FC had a negative correlation to the cognitive score, while the FC in the right temporal lobe-left temporal-occipital area positively correlated to Verbal/Visual Memory (r = 0.41–0.60, p-FDR < 0.05). In correlation analysis between clinical data and cognitive score, the only significant result was a low correlation between cyst size and Reaction Time (-0.30–-0.36, P-FDR < 0.05). Conclusions School-aged children with large left MFAC showed significantly lower cognitive performance primarily in attention and memory domains. Distinct from neuroplasticity in a unilateral brain lesion, compensation in the healthy hemisphere in MFAC patients was sparse

Efficient Open-Set Recognition for Interference Signals Based on Convolutional Prototype Learning

Interference classification plays an important role in anti-jamming communication. Although the existing interference signal recognition methods based on deep learning have a higher accuracy than traditional methods, these have poor robustness while rejecting interference signals of unknown classes in interference open-set recognition (OSR). To ensure the classification accuracy of the known classes and the rejection rate of the unknown classes in interference OSR, we propose a new hollow convolution prototype learning (HCPL) in which the inner-dot-based cross-entropy loss (ICE) and the center loss are used to update prototypes to the periphery of the feature space so that the internal space is left for the unknown class samples, and the radius loss is used to reduce the impact of the prototype norm on the rejection rate of unknown classes. Then, a hybrid attention and feature reuse net (HAFRNet) for interference signal classification was designed, which contains a feature reuse structure and hybrid domain attention module (HDAM). A feature reuse structure is a simple DenseNet structure without a transition layer. An HDAM can recalibrate both time-wise and channel-wise feature responses by constructing a global attention matrix automatically. We also carried out simulation experiments on nine interference types, which include single-tone jamming, multitone jamming, periodic Gaussian pulse jamming, frequency hopping jamming, linear sweeping frequency jamming, second sweeping frequency jamming, BPSK modulation jamming, noise frequency modulation jamming and QPSK modulation jamming. The simulation results show that the proposed method has considerable classification accuracy of the known classes and rejection performance of the unknown classes. When the JNR is −10 dB, the classification accuracy of the known classes of the proposed method is 2–7% higher than other algorithms under different openness. When the openness is 0.030, the unknown class rejection performance plateau of the proposed method reaches 0.9883, while GCPL is 0.9403 and CG-Encoder is 0.9869; when the openness is 0.397, the proposed method is more than 0.89, while GCPL is 0.8102 and CG-Encoder is 0.9088. However, the rejection performance of unknown classes of CG-Encoder is much worse than that of the proposed method under low JNR. In addition, the proposed method requires less storage resources and has a lower computational complexity than CG-Encoder