Stock market trading volumes and economic uncertainty dependence: before and during Sino-U.S. trade friction

This article mainly studies the interaction between the economic uncertainty and stock market trading volumes changes before and during Sino-U.S. trade friction using multifractal detrended fluctuation analysis (M.F.-D.F.A.) and multifractal detrended crosscorrelation analysis (M.F.-D.C.C.A.). Our research aims to reveal whether the economic uncertainty increased by Sino-U.S. trade friction affects stock market trading volume more susceptible, as well as how policymaker strengthen risk management and maintain financial stability. The results show that the dynamic volatility linkages between economic uncertainty and stock market trading volumes changes are multifractal, and the cross-correlation of volatility linkages are anti-persistent. Through the rolling-windows analysis, we also find that the economic uncertainty and trading volumes are anti-persistent dynamic cross-correlated. This means that while economic uncertainty increases, trading volume decreases. Besides, Sino-U.S. trade friction has impact on the cross-correlated behaviour significantly, suggesting that stock markets’ risks are relatively large and trading volumes changes are more susceptible by economic uncertainty during Sino-U.S. trade friction in the U.S. Our study complements existing literature about the stock markets trading volumes and economic uncertainty dependence relationship by multifractal theory’s methods. The overall findings imply that the increased economic uncertainty caused by Sino-U.S. trade friction exacerbates financial risks, which are useful for policymakers and investors

The structure of kagome superconductors CsV3_3Sb5_5 in the charge density wave states

The structure of charge density wave states in AV$_3$Sb$_5$ (A = K, Rb, Cs) kagome superconductors remains elusive, with three possible $2a\times2a\times2c$ candidates: tri-hexagonal, star-of-David, and their mixture. In this study, we conducted a systematic first-principles investigation of the nuclear quadrupole resonance (NQR) and nuclear magnetic resonance (NMR) spectra for the $2a\times2a\times2c$ CsV$_3$Sb$_5$ structures. By comparing our simulations with experimental data, we have concluded that the NQR spectrum indicates the tri-hexagonal structure as the proper structure for CsV$_3$Sb$_5$ after its charge density wave phase transition. The NMR calculation results obtained from the tri-hexagonal structure are also consistent with the experimental data.Comment: 8 pages, 3 figures and appendi

A three-stage criterion method for extracting local vibration modes of tensioned cables in beam string structures

As light and efficient large-span space structures, beam string structures have been widely used since the 1980s. Within them, cables are the main force-bearing component; their level of tension determines the overall stiffness, performance and structural safety of the beam string structures. Real-time monitoring of the cable force during the construction and service periods is an important and effective measure to ensure the safety of the cable structure. At present, the vibration method is widely used in nearly all common engineering practices for cable force identification/monitoring because of its simplicity and efficiency. However, the vibration of the cable segment will be affected by the whole structure, so the cable force-frequency relationship based on the simple single cable model cannot meet the accuracy requirement of cable force identification of the beam string structure. Therefore, in this paper, through finite element simulation and theoretical analysis, a three-stage criterion is proposed to develop a new method for obtaining the local modal information of the tensioned cable segment where the influence of the overall structure is considered. The new method’s performance was compared with the results obtained by the vibration method according to the single-cable model assumption, and the design values of the cable forces. The magnitude of the error in the identification of the tension force of the beam string structure according to the single-cable model was studied to provide a correction method, so that the single-cable model assumption can be used to improve the measuring efficiency and ensure the solution accuracy. The numerical results show the effectiveness of the proposed method. The work of this paper provides a new approach for improving the identification accuracy of the vibration method of a complex cable system such as the beam string structure and is a useful discussion on the vibration method of complex cable systems

Siliceous foam material and its application in post-combustion carbon capture for NGCC plants: effects of aging conditions

In an effort to reduce the overall energy penalty and capital expenditure associated with carbon capture technologies, a variety of porous solid adsorbents have been developed. The limitations of solid sorbent in large-scale process are related to its CO2 uptake, physicochemical stability, lifecycle, regenerability and operation condition. In this paper, siliceous foam materials were synthesized via a modified microemulsion templating method and functionalized with branched polyethylenimine (PEI). The physical characteristics of synthesized silica adsorbents under different aging conditions were analysed via N2 sorption analysis and Scanned Electron Microscopy (SEM) morphological analysis. CO2 uptake was evaluated by thermogravimetric analyser (TGA). The results show that CO2 uptake is desirable even under low CO2 partial pressure and is predictable with multiple linear regression (MLR) model in the range of examined materials

Poor Sleep Quality Is Associated with Dawn Phenomenon and Impaired Circadian Clock Gene Expression in Subjects with Type 2 Diabetes Mellitus

Aims. We investigated whether poor sleep quality is associated with both dawn phenomenon and impaired circadian clock gene expression in subjects with diabetes. Methods. 81 subjects with diabetes on continuous glucose monitoring were divided into two groups according to the Pittsburgh Sleep Quality Index. The magnitude of dawn phenomenon was quantified by its increment from nocturnal nadir to prebreakfast. Peripheral leucocytes were sampled from 81 subjects with diabetes and 28 normal controls at 09:00. Transcript levels of circadian clock genes (BMAL1, PER1, PER2, and PER3) were determined by real-time quantitative polymerase chain reaction. Results. The levels of HbA1c and fasting glucose and the magnitude of dawn phenomenon were significantly higher in the diabetes group with poor sleep quality than that with good sleep quality. Peripheral leucocytes from subjects with poor sleep quality expressed significantly lower transcript levels of BMAL1 and PER1 compared with those with good sleep quality. Poor sleep quality was significantly correlated with magnitude of dawn phenomenon. Multiple linear regression showed that sleep quality and PER1 were significantly independently correlated with dawn phenomenon. Conclusions. Dawn phenomenon is associated with sleep quality. Furthermore, mRNA expression of circadian clock genes is dampened in peripheral leucocytes of subjects with poor sleep quality

Model-agnostic meta-learning for fault diagnosis of industrial robots

The success of deep learning in the field of fault diagnosis depends on a large number of training data, but it is a challenge to achieve fault diagnosis of multi-axis industrial robots in the case of few-shot. To address this issue, this paper proposes a method called Model-Agnostic Meta-Learning (MAML) for fault diagnosis of industrial robots. Its goal is to train an effective industrial robot fault classifier using minimal training data. Additionally, it can learn to recognize faults in new scenarios with high accuracy based on the training data. Experimental results based on a six-axis industrial robot dataset show that the proposed method is superior to traditional convolutional neural network (CNN) and transfer learning, and that the diagnostic results with the same amount of data in few-shot cases are better than existing intelligent fault diagnosis methods