Sufficient Conditions on the Exponential Stability of Neutral Stochastic Differential Equations with Time-Varying Delays

The exponential stability is investigated for neutral stochastic differential equations with time-varying delays. Based on the Lyapunov stability theory and linear matrix inequalities (LMIs) technique, some delay-dependent criteria are established to guarantee the exponential stability in almost sure sense. Finally a numerical example is provided to illustrate the feasibility of the result

Downside and upside risk spillovers from commercial banks into China’s financial system:A new copula quantile regression-based CoVaR model

In this paper, we investigate the downside and upside risk spillovers from three kinds of commercial banks (state-owned commercial banks (SOCBs), joint-stock commercial banks (JSCBs) and city commercial banks (CCBs)) to China’s financial system by proposing a new copula quantile regression-based CoVaR model. We find that (i) the dynamic risk spillovers show heterogeneity over time, specifically that its downward trend is significant after the stock market disaster in 2015; (ii) JSCBs display the largest risk spillovers, indicating that JSCBs are the main contributors to systemic risk in China’s financial system; and (iii) the risk spillovers are not symmetrical, as the upside risk spillovers are smaller than the downside risk spillovers. Our results have crucial implications for financial regulators and investors who want to measure and prevent systemic financial risk and optimise their investment strategies

Development of an UAS for Earthquake Emergency Response and Its Application in Two Disastrous Earthquakes

To support humanitarian action after a disaster, we require reliable data like high-resolution satellite images for analyses aimed to define the damages of facilities and/or infrastructures. However, we cannot obtain satellite images in few days after an event. Thus, in situ surveys are preferred. Advances in unmanned aircraft system (UAS) have promoted them to become precious tools for capturing and assessing the extents and volume of damages. Safety, flexibility, low cost, and ease of operation make UAS suitable for disaster assessment. In this chapter, we developed an example of UAS for swiftly acquiring disaster information. With the selected fixed-wing UAS, we successfully performed data acquisition at specified scales. For the image analysis, we applied a photogrammetric workflow to deal with the very high resolution of the images obtained without ground control points. The results obtained from two destructive earthquakes demonstrated that the presented system plays a key role on the processes of investigating and gathering information about a disaster in the earthquake epicentral areas, like road detection, structural damage survey, secondary disaster investigation, and quick disaster assessment. It can effectively provide disaster information in hardly entered areas to salvation headquarters for rapidly developing the relief measures

Network Pharmacology Based Research on the Combination Mechanism Between Escin and Low Dose Glucocorticoids in Anti-rheumatoid Arthritis

Rheumatoid arthritis (RA) is characterized by chronic progressive symmetrical synovitis and destruction of multiple joints. Glucocorticoids (GCs) are widely used in the treatment of RA. However, their adverse effects can be serious. Escin, which is isolated from Aesculus hippocastanum L., has been reported to have anti-inflammatory effects. We investigated the anti-RA effect of Escin combined with low dose GCs (dexamethasone, Dex) and the underlying mechanism. Adjuvant-induced RA rats and lipopolysaccharides (LPS)-injured RAW264.7 cells were used to investigate the anti-RA effects of Escin combined with low dose Dex in vivo and in vitro. The results showed that Escin combined with low-dose Dex significantly decreased arthritic index, serum IL-6 and TNF-α levels, reduced paw swelling, and ameliorated the joint pathology and immune organ pathology. Gene chip results revealed that Nr3c1 (GR) expression was significantly altered, and that GR was activated by Escin and low dose Dex in vivo and in vitro. Additionally, Escin combined with low dose Dex also significantly increased GR mRNA expression. However, when GR expression was suppressed by its specific inhibitor, the anti-RA effect of Escin combined with low-dose Dex was abolished. The data in this study demonstrated that Escin combined with Dex reduced the dose of Dex, and exerted significant anti-RA effects, which could also reduce the adverse effects of Dex. This combination might result from GR activation. This study might provide a new combination of drugs for the treatment of RA

Relational Governance and Opportunism in Logistics Outsourcing Relationships: Empirical Evidence From China

Logistics outsourcing is prevalent in today\u27s business world as a strategy to obtain competitive advantages. As in other relational exchanges, it is imperative to understand how to alleviate opportunistic behaviour in logistics outsourcing relationships. Using China\u27s burgeoning logistics industry as a backdrop, and drawing on social exchange and transaction cost theories, this study examines how relational norms and trust mitigate opportunistic behaviour and how environmental uncertainty moderates the effects of norms and trust from logistics users\u27 perspective. Employing data collected from 119 manufacturing and service firms in China, we empirically test the proposed model and find that trust and norms are effective safeguards in reducing the opportunistic behaviour of logistics service providers, particularly in highly uncertain environments

A Frequency Estimation Scheme Based on Gaussian Average Filtering Decomposition and Hilbert Transform: With Estimation of Respiratory Rate as an Example

Frequency estimation plays a critical role in vital sign monitoring. Methods based on Fourier transform and eigen-analysis are commonly adopted techniques for frequency estimation. Because of the nonstationary and time-varying characteristics of physiological processes, time-frequency analysis (TFA) is a feasible way to perform biomedical signal analysis. Among miscellaneous approaches, Hilbert–Huang transform (HHT) has been demonstrated to be a potential tool in biomedical applications. However, the problems of mode mixing, unnecessary redundant decomposition and boundary effect are the common deficits that occur during the procedure of empirical mode decomposition (EMD) or ensemble empirical mode decomposition (EEMD). The Gaussian average filtering decomposition (GAFD) technique has been shown to be appropriate in several biomedical scenarios and can be an alternative to EMD and EEMD. This research proposes the combination of GAFD and Hilbert transform that is termed the Hilbert–Gauss transform (HGT) to overcome the conventional drawbacks of HHT in TFA and frequency estimation. This new method is verified to be effective for the estimation of respiratory rate (RR) in finger photoplethysmography (PPG), wrist PPG and seismocardiogram (SCG). Compared with the ground truth values, the estimated RRs are evaluated to be of excellent reliability by intraclass correlation coefficient (ICC) and to be of high agreement by Bland–Altman analysis

Design of Meter-Scale Antenna and Signal Detection System for Underground Magnetic Resonance Sounding in Mines

Magnetic resonance sounding (MRS) is a novel geophysical method to detect groundwater directly. By applying this method to underground projects in mines and tunnels, warning information can be provided on water bodies that are hidden in front prior to excavation and thus reduce the risk of casualties and accidents. However, unlike its application to ground surfaces, the application of MRS to underground environments is constrained by the narrow space, quite weak MRS signal, and complex electromagnetic interferences with high intensities in mines. Focusing on the special requirements of underground MRS (UMRS) detection, this study proposes the use of an antenna with different turn numbers, which employs a separated transmitter and receiver. We designed a stationary coil with stable performance parameters and with a side length of 2 m, a matching circuit based on a Q-switch and a multi-stage broad/narrowband mixed filter that can cancel out most electromagnetic noise. In addition, noises in the pass-band are further eliminated by adopting statistical criteria and harmonic modeling and stacking, all of which together allow weak UMRS signals to be reliably detected. Finally, we conducted a field case study of the UMRS measurement in the Wujiagou Mine in Shanxi Province, China, with known water bodies. Our results show that the method proposed in this study can be used to obtain UMRS signals in narrow mine environments, and the inverted hydrological information generally agrees with the actual situation. Thus, we conclude that the UMRS method proposed in this study can be used for predicting hazardous water bodies at a distance of 7–9 m in front of the wall for underground mining projects

Research on De-Noising Method of Grounded Electrical Source Airborne Transient Electromagnetic Data Based on Singular Spectrum Analysis

The grounded electrical source airborne transient electromagnetic (GREATEM) system is widely used in groundwater resources detection, geothermal resource detection, geological structure detection, and other fields due to its wide detection range, high detection efficiency, and high resolution. The field data received by the GREATEM system is easily affected by various noises, such as instrument system noise, power frequency noise, sferics noise, and other noise, which reduce the data signal-to-noise ratio (SNR) and affects the data interpretation accuracy. This paper proposes a singular spectrum analysis (SSA) for the GREATEM data de-noising in response to this problem. First, we calculate the electromagnetic response of a uniform half-space using a GREATEM system with an electrical source to verify the effectiveness of the SSA algorithm for GREATEM data de-noising. To determine the appropriate parameters for SSA, we propose a particle swarm optimization algorithm to choose the window length. Later, SSA is used to decompose a synthetic quasi-two-dimensional earth model of GREATEM data. After SSA, the SNR of the reconstructed signal increased by 36 dB, and the RMSE does not exceed 4.9 × 10−6, which verifies the feasibility of the SSA for de-noising GREATEM data. Finally, through field measurement data processing, the effectiveness of the method is further confirmed