The Numerical Invariant Measure of Stochastic Differential Equations With Markovian Switching

The existence and uniqueness of the numerical invariant measure of the backward Euler-Maruyama method for stochastic differential equations with Markovian switching is yielded, and it is revealed that the numerical invariant measure converges to the underlying invariant measure in the Wasserstein metric. Under the polynomial growth condition of drift term the convergence rate is estimated. The global Lipschitz condition on the drift coefficients required by Bao et al., 2016 and Yuan et al., 2005 is released. Several examples and numerical experiments are given to verify our theory.Comment: 25 pages, 4 figure

Diagnostic performance and clinical impact of blood metagenomic next-generation sequencing in ICU patients suspected monomicrobial and polymicrobial bloodstream infections

IntroductionEarly and effective application of antimicrobial medication has been evidenced to improve outcomes of patients with bloodstream infection (BSI). However, conventional microbiological tests (CMTs) have a number of limitations that hamper a rapid diagnosis.MethodsWe retrospectively collected 162 cases suspected BSI from intensive care unit with blood metagenomics next-generation sequencing (mNGS) results, to comparatively evaluate the diagnostic performance and the clinical impact on antibiotics usage of mNGS.Results and discussionResults showed that compared with blood culture, mNGS detected a greater number of pathogens, especially for Aspergillus spp, and yielded a significantly higher positive rate. With the final clinical diagnosis as the standard, the sensitivity of mNGS (excluding viruses) was 58.06%, significantly higher than that of blood culture (34.68%, P<0.001). Combing blood mNGS and culture results, the sensitivity improved to 72.58%. Forty-six patients had infected by mixed pathogens, among which Klebsiella pneumoniae and Acinetobacter baumannii contributed most. Compared to monomicrobial, cases with polymicrobial BSI exhibited dramatically higher level of SOFA, AST, hospitalized mortality and 90-day mortality (P<0.05). A total of 101 patients underwent antibiotics adjustment, among which 85 were adjusted according to microbiological results, including 45 cases based on the mNGS results (40 cases escalation and 5 cases de-escalation) and 32 cases on blood culture. Collectively, for patients suspected BSI in critical condition, mNGS results can provide valuable diagnostic information and contribute to the optimizing of antibiotic treatment. Combining conventional tests with mNGS may significantly improve the detection rate for pathogens and optimize antibiotic treatment in critically ill patients with BSI

Adaptive Backlash Compensation Method Based on Touch State Observation for a Solid Ducted Rocket

A hysteresis model was built to describe the backlash of the flow regulator in a solid ducted rocket, and its influence on the engine control was also analyzed in this study. An adaptive backlash compensation method was proposed under two challenges: limited information and backlash state variation caused by the harsh environment in the gas generator. The touch state is designed and its observation is used to get the state of backlash, and a compensation control method using the existing information was carried out combined with the motion intention. This method greatly shortened the time during the transition and reduced the hysteresis effect on the control system. Furthermore, the compensation method is improved and acquires a self-learning ability, the compensation parameter changes adaptively during the process of flow regulation, and it is able to meet the challenge of an unknown and variable state of backlash. Finally, the validation of the compensation method was carried out with two simulations

Whole head quantitative susceptibility mapping using a least-norm direct dipole inversion method

A new dipole field inversion method for whole head quantitative susceptibility mapping (QSM) is proposed. Instead of performing background field removal and local field inversion sequentially, the proposed method performs dipole field inversion directly on the total field map in a single step. To aid this under-determined and ill-posed inversion process and obtain robust QSM images, Tikhonov regularization is implemented to seek the local susceptibility solution with the least-norm (LN) using the L-curve criterion. The proposed LN-QSM does not require brain edge erosion, thereby preserving the cerebral cortex in the final images. This should improve its applicability for QSM-based cortical grey matter measurement, functional imaging and venography of full brain. Furthermore, LN-QSM also enables susceptibility mapping of the entire head without the need for brain extraction, which makes QSM reconstruction more automated and less dependent on intermediate pre-processing methods and their associated parameters. It is shown that the proposed LN-QSM method reduced errors in a numerical phantom simulation, improved accuracy in a gadolinium phantom experiment, and suppressed artefacts in nine subjects, as compared to two-step and other single-step QSM methods. Measurements of deep grey matter and skull susceptibilities from LN-QSM are consistent with established reconstruction methods

The Hydraulic and Boundary Characteristics of a Dike Breach Based on Cluster Analysis

It is important to determine the hydraulic boundary eigenvalues of typical embankment breaches before carrying out research on their occurrence mechanisms and assessing their repair technology. However, it is difficult to obtain the hydraulic boundary conditions of the typical levee breaches accurately with minor or incomplete measured data due to the complexity and instability of the levee breach. Based on more than 100 groups of domestic and foreign test data of embankment/earth dam failures, the correlation between the hydraulic boundary eigenvalues of a breach was established based on the cluster analysis approach. Additionally, the missing values were imputed after correlating and fitting. Meanwhile, the hydraulic boundary parameters and the related equations of a generalized typical breach were obtained through the statistical analysis of the probability density of the dimensionless eigenvalues of the breach. The analysis showed that the width of the breach mainly ranges in 20~100 m, while the water head of the breach is 4~12 m, and the velocity of the breach is 2~8 m/s. The distribution probabilities of all them are about 64~71%. The probability density of the width-to-depth ratio and the Froude number of the breach are both subject to normal distribution characteristics. The distribution frequency of the width-to-depth ratio of 3~8 is approximately 55%, and the Froude number of 0.4~0.8 is approximately 60%. These methods and findings might provide valuable support for the statistical research of the boundary and hydraulic characteristics of the breach, and the closure technology of breach

Multi-scale MRI reconstruction via dilated ensemble networks

As aliasing artefacts are highly structural and non-local, many MRI reconstruction networks use pooling to enlarge filter coverage and incorporate global context. However, this inadvertently impedes fine detail recovery as downsampling creates a resolution bottleneck. Moreover, real and imaginary features are commonly split into separate channels, discarding phase information particularly important to high frequency textures. In this work, we introduce an efficient multi-scale reconstruction network using dilated convolutions to preserve resolution and experiment with a complex-valued version using complex convolutions. Inspired by parallel dilated filters, multiple receptive fields are processed simultaneously with branches that see both large structural artefacts and fine local features. We also adopt dense residual connections for feature aggregation to efficiently increase scale and the deep cascade global architecture to reduce overfitting. The real-valued version of this model outperformed common reconstruction architectures as well as a state-of-the-art multi-scale network whilst being three times more efficient. The complex-valued network yielded better qualitative results when more phase information was present

Cerebral OEF quantification: a comparison study between quantitative susceptibility mapping and dual‐gas calibrated BOLD imaging

To compare regional oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen consumption (CMRO ) quantified from the microvascular quantitative susceptibility mapping (QSM) using a hypercapnic gas challenge with those measured by the dual-gas calibrated BOLD imaging (DGC-BOLD) in healthy subjects.Ten healthy subjects were scanned using a 3T MR system. The QSM data were acquired with a multi-echo gradient-echo sequence at baseline and hypercapnia. Cerebral blood flow data were acquired using the pseudo-continuous arterial spin labeling technique. Baseline OEF and CMRO were calculated using QSM and cerebral blood flow measurements. The DGC-BOLD data were also collected under a hypercapnic and a hyperoxic condition to yield baseline OEF and CMRO . The QSM-OEF and CMRO maps were compared with DGC-BOLD OEF and CMRO maps using region of interest (vascular territories) analysis and Bland-Altman plots.Hypercapnia is a robust stimulus for mapping OEF in combination with QSM. Average OEF in 16 vascular territory regions of interest across 10 subjects was 0.40 ± 0.04 by QSM-OEF and 0.38 ± 0.09 by DGC-BOLD. The average CMRO was 176 ± 35 and 167 ± 53 μmol O /min/100g by QSM-OEF and DGC-BOLD, respectively. A Bland-Altman plot of regional OEF and CMRO in regions of interest revealed a statistically significant but small difference (OEF difference = 0.02, CMRO difference = 9 μmol O /min/100g, p < .05) between the 2 methods for the 10 healthy subjects.Hypercapnic challenge-assisted QSM-OEF is a feasible approach to quantify regional brain OEF and CMRO . Compared with DGC-BOLD, hypercapnia QSM-OEF results in smaller intersubject variability and requires only 1 gas challenge

The Demand Supply Steady-State Process-Based Multi-Level Spare Parts Optimization

Spare parts are one of the important components of the equipment comprehensive support system. Spare parts management plays a decisive role in achieving the desired availability with the minimum cost. With the equipment complexity increasing, the price of spare parts has risen sharply. The traditional spare parts management makes the contradiction between fund shortage and spare parts shortage increasingly prominent. Based on the analysis of the multi-echelon and multi-indenture spare parts support model VARI-METRIC (vary multi-echelon technology for recoverable item control, VARI-METRIC), which is widely used by troops and enterprises in various countries, the model is mainly used in high system availability scenarios. However, in the case of low equipment system availability, the accuracy and cost of model inventory prediction are not ideal. This paper proposed the multi-level spare parts optimization model, which is based on the demand-supply steady-state process. It is an analytical model, which is used to solve the low accuracy problem of the VARI-METRIC model in the low equipment system availability. The analytical model is based on the multi-level spare parts support process. The article deduces methods for solving demand rate, demand–supply rate, equipment system availability, and support system availability. The marginal analysis method is used in the model to analyze the spare parts inventory allocation strategy’s current based cost and availability optimal value. Finally, a simulation model is established to evaluate and verify the model. Then, the simulation results show that, when the low availability of equipment systems are 0.4, 0.6, the relative errors of the analytical model are 3.54%, 3.86%, and its costs are 0.52, 1.795 million ¥ RMB. The experiment proves that the inventory prediction accuracy of the analytical model is significantly higher than that of the VARI-METRIC model in low equipment system availability. Finally, the conclusion and future research directions are discussed

Quantification of brain oxygen extraction fraction using QSM and a hyperoxic challenge

To use hyperoxia in combination with QSM to quantify microvascular oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO ) in healthy subjects and to cross-validate results with those from hypercapnia QSM-OEF.Ten healthy subjects were scanned on a 3T MRI scanner. At baseline normoxia and during hyperoxia (PetO = +300 mmHg), QSM data were acquired using a multi-echo gradient-echo (GRE) sequence, and cerebral blood flow data were acquired using a pseudocontinuous arterial spin labeling sequence. The OEF and CMRO maps were computed and compared with those from hypercapnia QSM-OEF, acquired in the same subjects, using correlation and Bland-Altman analysis in 16 vascular territories.Hyperoxia QSM-OEF produced physiologically reasonable OEF and CMRO values in all subjects (gray-matter region of interest average OEF = 0.42 ± 0.04, average CMRO = 181 ± 34 μmol O /min/100\ua0g). When compared with hypercapnia QSM-OEF, Bland-Altman plots revealed small deviations (mean OEF difference = 0.015, mean CMRO difference = 4.9\ua0μmol O /min/100\ua0g, P < .05). Good and excellent correlations of regional OEF and CMRO were found for the two methods. In addition, hyperoxia had minimal impact on cerebral blood flow (average gray-matter cerebral blood flow was reduced by 7.5 ± 5.4%).Hyperoxia in combination with QSM is a robust approach to measure OEF. Compared with hypercapnia, hyperoxia is more comfortable and has minimal impact on cerebral blood flow

LncRNA H19 promotes the differentiation of bovine skeletal muscle satellite cells by suppressing Sirt1/FoxO1

Abstract Background H19 is a well-characterized Long noncoding RNA (lncRNA) that has been proven to promote myoblast differentiation in humans and mice. However, its mechanism of action is still not fully interpreted. Methods Using RT-qPCR, we examined H19 RNA levels in various tissues from 1-week, 1-month, 6-month and 36-month old male cattle (i.e., newborn, infant, young and adult). The protein and mRNA levels of MyoG, MyHC, Sirt1 and FoxO1 in the satellite and C2C12 cells with an H19 silencing or overexpression vector were respectively detected using western blot and real-time qPCR. Results H19 was highly expressed in skeletal muscle at all the studied ages. High expression of H19 was required for the differentiation of bovine satellite cells. Knockdown of H19 caused a remarkable increase in the myoblast-inhibitory genes Sirt1/FoxO1, suggesting that H19 suppresses Sirt1/FoxO1 expression during myogenesis. Western blotting analysis of co-transfection of Sirt1 or FoxO1 expression vectors with pcDNA-H19 indicated that Sirt1/FoxO1 overexpression neutralized the promotion of myoblast differentiation through transfection of pcDNA-H19. Conclusion H19 promoted the differentiation of bovine skeletal muscle satellite cells by suppressing Sirt1/FoxO1