对"联邦滤波器信息分配系数的优选算法"一文的商榷

介绍了联邦滤波算法和信息分配原理，指出《中国惯性技术学报》第11卷第6期“联邦滤波器信息分配系数的优选算法”一中存在一些问题，说明使用该优选算法进行信息分配，可能使主滤波器方差阵失去正定性；将联邦滤波用于GPS姿态测量，实验表明动态选择信息分配因子，相对于固定信息分配因子的算法并没有明显优势。     

完全与不完全叉形分岔实验

介绍一种可演示完全与不完全叉形分彷的实验装置，并分析其机理。本文对非线性动力学实验设计有一定启示作用。     

Upper bound limit analysis of active earth pressure with different fracture surface and nonlinear yield criterion

Conventional calculations of static and seismic active earth pressures of soils on a retaining wall are formulated assuming the soils obeying a linear Mohr–Coulomb yield criterion. However, experimental evidences show that the strength envelopes of almost all geomaterials are nonlinear in nature over a wide range of normal stresses. In this paper, the strength envelope of the backfill behind a retaining wall is considered to follow a nonlinear yield criterion. A simple method is proposed for calculating the static and seismic active earth pressures acting against a retaining wall using a nonlinear yield criterion. This method is based on the upper bound theorem of limit analysis. Both translational and rotational fracture surfaces are employed in the formulation for calculating active earth pressures. Quasi-static representation of earthquake effects using a seismic coefficient concept is adopted for seismic active earth pressure calculations. Instead of using directly the actual nonlinear yield criterion, a linear Mohr–Coulomb yield criterion, which is tangential to the nonlinear yield criterion, is used to formulate the active earth pressure problem as a classical nonlinear programming problem. A nonlinear sequential quadratic programming algorithm is used to search for the maximum solution. In order to assess the validity of the proposed method, values of active earth pressures for different values of seismic coefficients and nonlinear parameters in the yield criterion are calculated and compared with solutions obtained using an extended Rankine’s active earth pressure theory. For the case of static active earth pressure, the upper bound solutions using the present method with a translational fracture surface are equal to the extended Rankine’s theoretical solutions and are slightly smaller than those obtained using the present method with a rotational fracture surface. For the case of seismic active earth pressure, numerical results obtained using the present method with a rotational fracture surface is very close to the extended Rankine’s theoretical solutions. A study is conducted to investigate the effects of the parameters in the nonlinear yield criterion on the active earth pressures.     

Natural Dietary Compound Xanthohumol Regulates the Gut Microbiota and Its Metabolic Profile in a Mouse Model of Alzheimer’s Disease

Discovering new and effective drugs for the treatment of Alzheimer’s disease (AD) is a major clinical challenge. This study focuses on chemical modulation of the gut microbiome in an established murine AD model. We used the 16S rDNA sequencing technique to investigate the effect of xanthohumol (Xn) on the diversity of intestinal microflora in 2-month- and 6-month-old APP/PS1 mice, respectively. APP/PS1 and wild-type mice were treated by gavage with corn oil with or without Xn every other day for 90 days. Prior to and following treatment, animals were tested for spatial learning, cognitive and memory function. We found Xn reduced cognitive dysfunction in APP/PS1 mice and significantly regulated the composition and abundance of gut microbiota both in prevention experiments (with younger mice) and therapeutic experiments (with older mice). Differential microflora Gammaproteobacteria were significantly enriched in APP/PS1 mice treated with Xn. Nodosilineaceae and Rikenellaceae may be the specific microflora modulated by Xn. The penicillin and cephalosporin biosynthesis pathway and the atrazine degradation pathway may be the principal modulation pathways. Taken together, oral treatment with Xn may have a neuroprotective role by regulating the composition of intestinal microflora, a result that contributes to the scientific basis for a novel prophylactic and therapeutic approach to AD.     

Rapid Screening of Lipase Inhibitors from Ophiopogonis Radix Using High-Performance Thin Layer Chromatography by Two Step Gradient Elution Combined with Bioautographic Method

In this study, a high-performance thin layer chromatography (HPTLC) method by two step gradient elution with two mobile phases was developed for the simultaneous analysis of seven constituents in Ophiopogonis Radix. The chromatography was performed on silica gel 60 F₂₅₄ plate with dichloromethane-methanol-ethyl acetate-water (70:25:12:3, v/v/v/v) and dichloromethane-methanol (300:1, v/v) as the mobile phase for two step gradient elution. Then, the HPTLC profiles were observed after derivatization with 10% sulfuric acid in ethanol solution. The obtained HPTLC images were further analyzed by chemometric approaches and the samples could be clustered based on regions and/or growth years, which were two important factors affecting the constituents in Ophiopogonis Radix. Furthermore, five compounds including ophiopogonin D, ophiopojaponin C, ophiopogonin D’, ophiopogonin C’ and methylophiopogonanone B were screened as potential lipase inhibitors from Ophiopogonis Radix by the HPTLC-bioautographic method. The binding modes and interactions between the five compounds and lipase were further explored by molecular docking analysis. The developed HPTLC method could be used for quality control of Ophiopogonis Radix and screening of the potential lipase inhibitors.     

Cytosolic escape of mitochondrial DNA triggers cGAS-STING-NLRP3 axis-dependent nucleus pulposus cell pyroptosis

Low back pain (LBP) is a major musculoskeletal disorder and the socioeconomic problem with a high prevalence that mainly involves intervertebral disc (IVD) degeneration, characterized by progressive nucleus pulposus (NP) cell death and the development of an inflammatory microenvironment in NP tissue. Excessively accumulated cytosolic DNA acts as a damage-associated molecular pattern (DAMP) that is monitored by the cGAS-STING axis to trigger the immune response in many degenerative diseases. NLRP3 inflammasome-dependent pyroptosis is a type of inflammatory programmed death that promotes a chronic inflammatory response and tissue degeneration. However, the relationship between the cGAS-STING axis and NLRP3 inflammasome-induced pyroptosis in the pathogenesis of IVD degeneration remains unclear. Here, we used magnetic resonance imaging (MRI) and histopathology to demonstrate that cGAS, STING, and NLRP3 are associated with the degree of IVD degeneration. Oxidative stress induced cGAS-STING axis activation and NLRP3 inflammasome-mediated pyroptosis in a STING-dependent manner in human NP cells. Interestingly, the canonical morphological and functional characteristics of mitochondrial permeability transition pore (mPTP) opening with the cytosolic escape of mitochondrial DNA (mtDNA) were observed in human NP cells under oxidative stress. Furthermore, the administration of a specific pharmacological inhibitor of mPTP and self-mtDNA cytosolic leakage effectively reduced NLRP3 inflammasome-mediated pyroptotic NP cell death and microenvironmental inflammation in vitro and degenerative progression in a rat disc needle puncture model. Collectively, these data highlight the critical roles of the cGAS-STING-NLRP3 axis and pyroptosis in the progression of IVD degeneration and provide promising therapeutic approaches for discogenic LBP.Subject terms: Cell death, Diseases     

Saprophytic Bacillus Accelerates the Release of Effective Components in Agarwood by Degrading Cellulose

The value of Agarwood increases with time due to the gradual release of its major components, but the mechanism behind this remains unclear. Herein we reveal that the potential driving force of this process is the degradation of cellulose in Agarwood by its saprophytic Bacillus subtilis. We selected 10-year-old Agarwood from different places and then isolated the saprophytic bacteria. We confirmed these bacteria from different sources are all Bacillus and confirmed they can degrade cellulose, and the highest cellulase activity reached 0.22 U/mL. By co-cultivation of the bacterium and Agarwood powder, we found that three of the strains could release the effective components of Agarwood, while they had little effect in increasing the same components in living Aquilaria sinensis. Finally, we demonstrated that these saprophytic Bacillus subtilis have similar effects on Zanthoxylum bungeanum Maxim and Dalbergiaod orifera T. Chen, but not on Illicium verum Hook. f, Cinnamomum cassia Presl and Phellodendron chinense Schneid. In conclusion, our experiment revealed that the saprophytic Bacillus release the effective components of Agarwood by degrading cellulose, and we provide a promising way to accelerate this process by using this bacterial agent.     

Multi-Sensor Vibration Signal Based Three-Stage Fault Prediction for Rotating Mechanical Equipment

In order to reduce maintenance costs and avoid safety accidents, it is of great significance to carry out fault prediction to reasonably arrange maintenance plans for rotating mechanical equipment. At present, the relevant research mainly focuses on fault diagnosis and remaining useful life (RUL) predictions, which cannot provide information on the specific health condition and fault types of rotating mechanical equipment in advance. In this paper, a novel three-stage fault prediction method is presented to realize the identification of the degradation period and the type of failure simultaneously. Firstly, based on the vibration signals from multiple sensors, a convolutional neural network (CNN) and long short-term memory (LSTM) network are combined to extract the spatiotemporal features of the degradation period and fault type by means of the cross-entropy loss function. Then, to predict the degradation trend and the type of failure, the attention-bidirectional (Bi)-LSTM network is used as the regression model to predict the future trend of features. Furthermore, the predicted features are given to the support vector classification (SVC) model to identify the specific degradation period and fault type, which can eventually realize a comprehensive fault prediction. Finally, the NSF I/UCR Center for Intelligent Maintenance Systems (IMS) dataset is used to verify the feasibility and efficiency of the proposed fault prediction method.     

An Enhanced Full-Form Model-Free Adaptive Controller for SISO Discrete-Time Nonlinear Systems

This study focuses on the full-form model-free adaptive controller (FFMFAC) for SISO discrete-time nonlinear systems, and proposes enhanced FFMFAC. The proposed technique design incorporates long short-term memory neural networks (LSTMs) and fuzzy neural networks (FNNs). To be more precise, LSTMs are utilized to adjust vital parameters of the FFMFAC online. Additionally, due to the high nonlinear approximation capabilities of FNNs, pseudo gradient (PG) values of the controller are estimated online. EFFMFAC is characterized by utilizing the measured I/O data for the online training of all introduced neural networks and does not involve offline training and specific models of the controlled system. Finally, the rationality and superiority are verified by two simulations and a supporting ablation analysis. Five individual performance indices are given, and the experimental findings show that EFFMFAC outperforms all other methods. Especially compared with the FFMFAC, EFFMFAC reduces the RMSE by 21.69% and 11.21%, respectively, proving it to be applicable for SISO discrete-time nonlinear systems.