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The extraction of parallel minor components algorithm in directional convergence in signal feature extraction was studied.By comparing the unweighted projection approximation subspace tracking (PAST) algorithm with the weighted PAST parallel minor component extraction algorithm,the evolution method of the minor component extraction algorithm was analyzed.Theorical analysis illustrated that the weighted rule was able to guide the angle evolution between the vectors of the state matrix and minor components.Finally,Matlab simulation verifies the validity of the proposed theory.

In the present work, based on the generalized principal component analysis, we propose a new approach to decompose the subspace of fault deviations, which is used for reconstruction-based fault diagnosis through principal component analysis (PCA) monitoring system. The proposed method is advanced since it lightens the computational burden by eliminating the irrelavant information and simplifying the fault subspace. The fault effects are extracted through analyzing the generalized principal components of the normal operating data and the fault data. The significant fault deviations that cause the alarming monitoring statistic are calculated. This is achieved by designing a two-part feature decomposition procedure. In the first part, the normal operating subspace is extracted through analyzing the generalized principal components of both the historical normal data and fault data. The fault-free part of the data is eliminated by projecting the data into the normal operating subspace. In the second part, principal component analysis is performed on the remaining part of the data, where the largest fault deviation directions are decomposed in order. By the two-part decomposition, an integrated fault subspace for all monitoring statistic indices is obtained, which separates the measurement data into two different parts for fault reconstruction. One part is related to the normal operating subspace, which is deemed to follow normal rules, and thus insignificant to remove alarming monitoring statistics. The other is related to the fault subspace, which contributes to the out-of-control signals. Theoretical support is constructed and the related statistical characteristics are analyzed. Its feasibility and performance are illustrated with the data from the Tennessee Eastman (TE) benchmark process.

Aiming at the lack of information criterion functions of sub subspace,a novel criterion function was proposed by adding a penalty term to the Rayleigh quotient.Through analyzing the properties of all the stable points,it was proven that the criterion function exhibited the global maximum attained if and only if the weight matrices span the minor subspace.A minor subspace tracking algorithm was derived by gradient ascending method and its global convergence analysis was also accomplished.Numerical simulations and real application verifies the correctness of the criterion function and derived algorithm.

SRAM-based field programmable gate arrays (FPGAs) are widely used in mission-critical applications, such as aerospace and avionics. Due to the increasing working frequency and technology scaling of ultra-nanometer technology, single event transients (SETs) are becoming a major source of errors for these devices. In this paper, we propose a workflow for evaluating the behavior of SETs in SRAM-based FPGAs. The method is able to compute the propagation-induced pulse broadening (PIPB) effect introduced by the logic resources traversed by transient pulses. Besides, we developed an accurate look-up table (LUT) layout model able to effectively predict the kinds of the SETs induced by radiation-particle and to accurately mimic the phenomena of the SET generation and propagation. The proposed methodology is applicable to any recent technology to provide the SET analysis, necessary for an efficient mitigation technology. The experimental results achieved from a set of benchmark circuits mapped on a 28-nm SRAM-based FPGA and compared with the fault injection experiments demonstrate the effectiveness of our technique.

Generalized minor component analysis (GMCA) is of great use in modern signal processing. The GMCA algorithms can be simplified to extract the minor generalized eigenvector of the autocorrelation input matrices pencil. In contrast to batching methods, the Hebbian-rule-based algorithm can extract the minor generalized eigenvector online. Few Hebbian-rule-based GMCA algorithms have been reported in the literature, and most of them are not self-stabilizing. Thus, a novel algorithm for GMCA, which is advantageous in terms of good convergence speed, self-stabilizing property, and multiple generalized minor component extraction in sequence, is proposed in this paper. A theoretical analysis verifies these properties via matrix theory and the deterministic discrete-time method. Numerical simulations are conducted to further demonstrate the advantages of the proposed algorithm.

The partial least squares (PLS) method has been widely used in quality-related industrial process monitoring because of its ability to extract quality-related information. Generally, online quality monitoring data cannot be obtained in real time, and in this case, updating the online monitoring model is a serious challenge. In this paper, an online monitoring dynamic PLS (OMD-PLS) model that uses the relation between time-delay process data and time-delay quality data is proposed. To accurately monitor the quality-related and process-related fault data, we also propose an online monitoring dynamic concurrent PLS (OMDC-PLS) model based on OMD-PLS, which has the ability to detect slight deviations. Furthermore, an alarm-parameter alarm method based on the OMDC-PLS model is proposed and effectively reduces the false alarm rate. Finally, numerical simulations and the Tennessee Eastman process are used to illustrate the effectiveness of the proposed methods.

In this paper, through the application of 3D design technology in the construction of 220kV Miluoxi substation, the main aspects of the application of 3D design technology in the construction are summarized, including inter discipline verification, collision inspection, real scene modeling, equipment 3D installation details, 4D construction simulation, VR technology application and mobile application solutions. This paper also summarizes the economic, management and social benefits of three-dimensional application, which can be used as a reference for the following projects.

Abstract Background Several previous studies have identified a potential role that the gut microbiome can play in autism spectrum disorder (ASD) in children, but little is known about how variations in the virome may be involved in ASD. We aimed to understand the changes in the gut DNA virome of children with ASD. Methods A case–control study was presented, in which 13 two-children families were observed while considering the age, mode of birth, history of antibiotic use, and vaccination history to minimize the influence of confounding factors. DNA viral metagenomic sequencing was successfully performed on stool samples from 11 children with ASD and 12 healthy non-ASD children. The basic composition and gene function of the participants' fecal DNA virome were detected and analyzed. Finally, the abundance and diversity of the DNA virome of children with ASD and their healthy siblings were compared. Results The gut DNA virome in children aged 3–11 years was found to be dominated by the Siphoviridae family of Caudovirales. The proteins encoded by the DNA genes mainly carry out the functions of genetic information transmission and metabolism. Compared the gut DNA virome of ASD and healthy non-ASD children, their abundance of Caudovirales and Petitvirales both showed a significant negative correlation (r = -0.902, P

ObjectivePrevious cohort trials have shown that skipping breakfast increases the risk of obesity or overweight in children. However, this finding remains controversial. Through a meta-analysis, this study systematically evaluated the effect of skipping breakfast on the prevalence of obesity or overweight in children.MethodsWe performed a literature search for studies published until March 19, 2023. using the Cochrane, PubMed, and Embase databases. Based on the inclusion and exclusion criteria, observational studies on the relationship between skipping breakfast and overweight/obesity in children and adolescents were analyzed. Three investigators independently screened the relevant literature, extracted the data, and assessed the risk of bias. The quality of the included studies was assessed using the Newcastle-Ottawa Scale (NOS). A random-effects model was used. The odds ratio (OR) with its 95% confidence interval (CI) was used to indicate the effect size.ResultsA total of 40 retrospective studies with 323,244 children ranging in age from 2 to 20 years were included in this study. The results of this meta-analysis showed that children and adolescents who skipped breakfast had a significantly higher prevalence of obesity or overweight than those who ate breakfast (OR, 1.59; 95% CI, 1.33–1.90; P < 0.001). Skipping breakfast was positively associated with overweight in children and adolescents (OR, 1.37; 95% CI, 1.23–1.54; P < 0.001). Similarly, skipping breakfast was positively associated with obesity in children and adolescents (OR, 1.51; 95% CI, 1.30–1.76; P < 0.001). The effect was also different by sex, with girls being the most affected (OR, 1.47; 95% CI, 1.23–1.76; P < 0.001). There was also a correlation between skipping breakfast and abdominal obesity in children (OR, 0.65; 95% CI, 0.55–0.77; P < 0.001).ConclusionThis meta-analysis suggested that skipping breakfast is associated with an increased risk of overweight/obesity in children and adolescents. The findings provide support for a possible protective role of breakfast against excessive weight gain in children and adolescents. However, more rigorous study designs with validated and standardized measures of relevant variables are needed.

BackgroundRecent studies reported the association between the changes in gut microbiota and sepsis, but there is unclear for the gut microbes on aged sepsis is associated acute lung injury (SALI), and metformin treatment for the change in gut microbiota. This study aimed to investigate the effect of metformin on gut microbiota and SALI in aged rats with sepsis. It also explored the therapeutic mechanism and the effect of metformin on aged rats with SALI.MethodsAged 20-21 months SD rats were categorized into three groups: sham-operated rats (AgS group), rats with cecal ligation and puncture (CLP)-induced sepsis (AgCLP group), and rats treated with metformin (100 mg/kg) orally 1 h after CLP treatment (AgMET group). We collected feces from rats and analyzed them by 16S rRNA sequencing. Further, the lung samples were collected for histological analysis and quantitative real-time PCR (qPCR) assay and so on.ResultsThis study showed that some pathological changes occurring in the lungs of aged rats, such as hemorrhage, edema, and inflammation, improved after metformin treatment; the number of hepatocyte death increased in the AgCLP group, and decreased in the AgMET group. Moreover, metformin relieved SALI inflammation and damage. Importantly, the gut microbiota composition among the three groups in aged SALI rats was different. In particular, the proportion of E. coli and K. pneumoniae was higher in AgCLP group rats than AgS group rats and AgMET group rats; while metformin could increase the proportion of Firmicutes, Lactobacillus, Ruminococcus_1 and Lactobacillus_johnsonii in aged SALI rats. Moreover, Prevotella_9, Klebsiella and Escherichia_Shigella were correlated positively with the inflammatory factor IL-1 in the lung tissues; Firmicutes was correlated negatively with the inflammatory factor IL-1 and IL-6 in the lung tissues.ConclusionsOur findings suggested that metformin could improve SALI and gut microbiota in aged rats, which could provide a potential therapeutic treatment for SALI in aged sepsis.

Cerebral palsy (CP) is a group of permanent, but not unchanging, disorders of movement and/or posture and motor function. Since the major brain injury associated with CP is white matter injury (WMI), especially, in preterm infants, we established a “multi-hit” rat model to mimic human WMI in symptomatology and at a histological level. In our WMI model, pups suffering from limb paresis, incoordination, and direction difficulties fit the performance of CP. Histologically, they present with fewer neural cells, inordinate fibers, and more inflammatory cell infiltration, compared to the control group. From the electron microscopy results, we spotted neuronal apoptosis, glial activation, and myelination delay. Besides, the abundant appearance of IBA1-labeled microglia also implied that microglia play a role during neuronal cell injury. After activation, microglia shift between the pro-inflammatory M1 type and the anti-inflammatory M2 type. The results showed that LPS/infection stimulated IBA1 + (marked activated microglia) expression, downregulated CD11c + (marked M1 phenotype), and upregulated Arg 1 + (marked M2 phenotype) protein expression. It indicated an M1 to M2 transition after multiple infections. In summary, we established a “multi-hit” WMI-induced CP rat model and demonstrated that the microglial activation correlates tightly with CP formation, which may become a potential target for future studies.

The robust H∞ consensus control problem of high-order discrete-time multi-agent systems with parameter uncertainties and external disturbances is studied, and a linear distributed consensus protocol is designed in this paper. Firstly, the robust H∞ consensus control problem of high-order discrete-time multi-agent systems with parameter uncertainties and external disturbances is transformed to a robust H∞ control problem of a set of independent uncertain systems. Secondly, a suffcient linear matrix inequality (LMI) condition is derived to insure that high-order discrete-time multi-agent systems with parameter uncertainties and external disturbances achieve robust consensus with a H∞ performance level γ. Thirdly, convergence results are given as final consensus values of high-order discrete-time linear multi-agent systems with parameter uncertainties and without external disturbances. Finally, a contrast numerical experiment with and without parameter uncertainties is provided to demonstrate the correctness and effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

The robust guaranteed cost consensus problem of high-order discrete-time linear multi-agent systems (MASs) with parameter uncertainties and time-varying delays is studied, and a linear consensus protocol of it is designed. Norm-bounded uncertainties and polytopic uncertainties are considered. First, the idea of robust guaranteed cost control is introduced into consensus problems for the MASs, where a cost function is defined based on state errors among neighbouring agents and control inputs of all the agents. Second, by constructing suitable Lyapunov functions and using the stability theory of discrete-time linear systems, two sufficient linear matrix inequality conditions are derived to insure that high-order discrete-time linear MASs with the two types of parameter uncertainties and time-varying delays reach robust guaranteed cost consensus. At the same time, two upper bounds of the guaranteed cost function are also given. Third, convergence results are given as final consensus values of the MASs with parameter uncertainties and time-varying delays. Finally, two numerical comparisons are given to illustrate the correctness and availability of the theoretical results. [ABSTRACT FROM AUTHOR]