Interaction between gender and post resuscitation interventions on neurological outcome in an asphyxial rat model of cardiac arrest

Purpose Previous clinical studies have suggested an effect of gender on outcome after out-of-hospital cardiac arrest, but the results are conflicting and there is no uniform agreement regarding gender differences in survival and prognosis. The present study was aimed to investigate the interaction between gender and post resuscitation interventions on neurological outcome in an asphyxial rat model of cardiac arrest. Methods Asphyxia was induced by blocking the endotracheal tube in 120 adult Sprague–Dawley rats (60 males and 60 females) at the same age. Cardiopulmonary resuscitation (CPR) was started after 5 min of untreated cardiac arrest. Animals were randomized into one of the three post resuscitation care intervention groups (n = 40, 20 males) immediately after resuscitation: (1) normothermic control (NC): ventilated with 2% N2/98% O2 for 1 h under normothermia; (2) targeted temperature management (TTM): ventilated with 2% N2/98% O2 for 1 h under hypothermia; (3) hydrogen inhalation (HI): ventilated with 2% H2/98% O2 for 1 h under normothermia. Physiological variables were recorded during the 5 h post resuscitation monitoring period. Neurological deficit score (NDS) and accumulative survival were used to assess 96 h outcomes. Mutual independence analysis and Mantel–Haenszel stratified analysis were used to explore the associations among gender, intervention and survival. Results The body weights of female rats were significantly lighter than males, but CPR characteristics did not differ between genders. Compared with male rats, females had significantly lower mean arterial pressure, longer onset time of the electroencephalogram (EEG) burst and time to normal EEG trace (TTNT) in the NC group; relatively longer TTNT in the TTM group; and substantially longer TTNT, lower NDSs, and higher survival in the HI group. Mutual independence analysis revealed that both gender and intervention were associated with neurological outcome. Mantel–Haenszel stratified analysis demonstrated that female rats had significantly higher survival rate than males when adjusted for the confounder intervention. Conclusion In this rat model cardiac arrest and CPR, gender did not affect resuscitation but associated with neurological outcome. The superiority of female rats in neurological recovery was affected by post resuscitation interventions and female rats were more likely to benefit from hydrogen therapy.

Multi-Stage Convolutional Broad Learning with Block Diagonal Constraint for Hyperspectral Image Classification

By combining the broad learning and a convolutional neural network (CNN), a block-diagonal constrained multi-stage convolutional broad learning (MSCBL-BD) method is proposed for hyperspectral image (HSI) classification. Firstly, as the linear sparse feature extracted by the conventional broad learning method cannot fully characterize the complex spatial-spectral features of HSIs, we replace the linear sparse features in the mapped feature (MF) with the features extracted by the CNN to achieve more complex nonlinear mapping. Then, in the multi-layer mapping process of the CNN, information loss occurs to a certain degree. To this end, the multi-stage convolutional features (MSCFs) extracted by the CNN are expanded to obtain the multi-stage broad features (MSBFs). MSCFs and MSBFs are further spliced to obtain multi-stage convolutional broad features (MSCBFs). Additionally, in order to enhance the mutual independence between MSCBFs, a block diagonal constraint is introduced, and MSCBFs are mapped by a block diagonal matrix, so that each feature is represented linearly only by features of the same stage. Finally, the output layer weights of MSCBL-BD and the desired block-diagonal matrix are solved by the alternating direction method of multipliers. Experimental results on three popular HSI datasets demonstrate the superiority of MSCBL-BD.

Water Hammer Simulation Method in Pressurized Pipeline with a Moving Isolation Device

Smart isolation devices (SIDs) are commonly used in pressurized subsea pipelines that need to be maintained or repaired. The sudden stoppage of the SID may cause large water hammer pressures, which may threaten both the pipeline and the SID. This paper proposes a simulation method by using a coupled dynamic mesh technique to simulate water hammer pressures in the pipeline. Unlike other water hammer simulations, this method is the first to be used in the simulation in pipelines with a moving object. The implicit method is applied to model the moving SID since it has the mutual independence between the space step and the time step. The movement of the SID is achieved by updating the size of the computational meshes close to the SID at each time step. To improve the efficiency of the simulation and the ability of handling complex boundary conditions, the pipe sections far away from the SID can also be simulated by using the explicit Method of Characteristics (MOC). Verifications were conducted using the simulated results from the Computational Fluid Dynamics (CFD) numerical simulation. Two scenarios have been studied and the comparisons between the simulated results by using the dynamic meshes in 1D methods and those by the CFD simulation show a high correlation, thus validating the new method proposed in this paper.

Sea Clutter Covariance Matrix Estimation and Its Application to Whitening Filter

The accurate estimation of clutter covariance matrix (CCM) is essential in designing a radar detector/filter to suppress sea clutter. This estimation might not be easily accomplished because of the scarcity of valid training vectors adjacent to the range cell under test (CUT). We propose a new CCM estimation algorithm that is derived by modeling time-series clutter returns into a clutter Doppler spectrum in the frequency domain and exploiting mutual independence among spectral components. To justify its excellence over the conventional sample covariance matrix (SCM) algorithm, we design two filters—a maximum signal-to-interference-plus-noise ratio (SINR)-based filter and a whitening filter—that use the estimated CCMs and compare their performance in a numerically simulated sea clutter scenario. Comparisons are made by showing the eigenvector spectra of the estimated CCMs and the frequency responses and outputs of the filters. Moreover, SINRs at the target Doppler bin are examined and compared with a theoretical, analytically derived SINR.

mixIndependR: a R package for statistical independence testing of loci in database of multi-locus genotypes

Background Multi-locus genotype data are widely used in population genetics and disease studies. In evaluating the utility of multi-locus data, the independence of markers is commonly considered in many genomic assessments. Generally, pairwise non-random associations are tested by linkage disequilibrium; however, the dependence of one panel might be triplet, quartet, or other. Therefore, a compatible and user-friendly software is necessary for testing and assessing the global linkage disequilibrium among mixed genetic data. Results This study describes a software package for testing the mutual independence of mixed genetic datasets. Mutual independence is defined as no non-random associations among all subsets of the tested panel. The new R package “mixIndependR” calculates basic genetic parameters like allele frequency, genotype frequency, heterozygosity, Hardy–Weinberg equilibrium, and linkage disequilibrium (LD) by mutual independence from population data, regardless of the type of markers, such as simple nucleotide polymorphisms, short tandem repeats, insertions and deletions, and any other genetic markers. A novel method of assessing the dependence of mixed genetic panels is developed in this study and functionally analyzed in the software package. By comparing the observed distribution of two common summary statistics (the number of heterozygous loci [K] and the number of share alleles [X]) with their expected distributions under the assumption of mutual independence, the overall independence is tested. Conclusion The package “mixIndependR” is compatible to all categories of genetic markers and detects the overall non-random associations. Compared to pairwise disequilibrium, the approach described herein tends to have higher power, especially when number of markers is large. With this package, more multi-functional or stronger genetic panels can be developed, like mixed panels with different kinds of markers. In population genetics, the package “mixIndependR” makes it possible to discover more about admixture of populations, natural selection, genetic drift, and population demographics, as a more powerful method of detecting LD. Moreover, this new approach can optimize variants selection in disease studies and contribute to panel combination for treatments in multimorbidity. Application of this approach in real data is expected in the future, and this might bring a leap in the field of genetic technology. Availability The R package mixIndependR, is available on the Comprehensive R Archive Network (CRAN) at: https://cran.r-project.org/web/packages/mixIndependR/index.html.

Research on accounting information sharing mechanism from the perspective of national governance

Accounting information sharing plays an important role in giving full play to the resource allocation effect of accounting information and promoting the modernization of national governance. It is one of the main tasks of the 13th five year plan for accounting reform and development of the Ministry of finance to establish a public service platform for social accounting information based on the disclosure of financial report data. In view of a series of problems brought about by the current accounting information multi submission, different caliber, mutual independence and non sharing, this paper discusses the mechanism and implementation path of accounting information sharing from the perspective of national governance, and puts forward a vertical through, horizontal interaction, internal integration and national unified accounting information sharing service system. Through the establishment of accounting information platform, accounting information can be “Count one, share resources”.

Reconstruction of falsified election results using Shpilkin integral method

I propose a simple and formal method to reconstruct falsified election results, based on the hypothesis of the mutual independence of the overall turnout and the result of power. This method is a development of the classical method of S.A. Shpilkin, however, it does not require additional assumptions and has no free parameters. In addition, it uniformly reconstructs all key values and uses a simpler and clearer mathematical procedure. Comparison of official and true results of federal elections allows to perform a political science analysis of the development of the institution of electoral frauds in Russia in the 20th century and its impact on the political system.