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With the growing interest to harness cancer metabolism and energy reprogramming, this mini review aimed to explain the metabolic programming revealing the mechanisms regarding the treatment resistance. This mini review summarized the prominent cancer metabolic reprogramming on macromolecules. In addition, metabolic reprogramming explaining immune response and treatment resistance as well as energy reprogramming mechanisms are briefly discussed. Finally, some prospects in MR for reversing cancer drug resistance are highlighted.

Abstract Sintering of active metal species often happens during catalytic reactions, which requires redispersion in a reactive atmosphere at elevated temperatures to recover the activity. Herein, we report a simple method to redisperse sintered Cu catalysts via O2-H2O treatment at room temperature. In-situ spectroscopic characterizations reveal that H2O induces the formation of hydroxylated Cu species in humid O2, pushing surface diffusion of Cu atoms at room temperature. Further, surface OH groups formed on most hydroxylable support surfaces such as γ-Al2O3, SiO2, and CeO2 in the humid atmosphere help to pull the mobile Cu species and enhance Cu redispersion. Both pushing and pulling effects of gaseous H2O promote the structural transformation of Cu aggregates into highly dispersed Cu species at room temperature, which exhibit enhanced activity in reverse water gas shift and preferential oxidation of carbon monoxide reactions. These findings highlight the important role of H2O in the dynamic structure evolution of supported metal nanocatalysts and lay the foundation for the regeneration of sintered catalysts under mild conditions.

BackgroundYinChen WuLing Powder (YCWLP) has been recommended by consensus for the treatment of non-alcoholic steatohepatitis (NASH); nevertheless, its specific pharmacological mechanisms remain to be elucidated. This study aims to dissect the mechanisms underlying the therapeutic effects of YCWLP on NASH using a hybrid approach that encompasses network pharmacology, molecular docking, and in vitro experimental validation.MethodsWe compiled the chemical constituents of YCWLP from the Traditional Chinese Medicine System Pharmacological Database and Analysis Platform (TCMSP), while potential targets were predicted using the SwissTargetPrediction database. To identify NASH-related candidate targets, comprehensive retrieval was carried out using five authoritative databases. Protein-Protein Interaction (PPI) networks of direct targets of YCWLP in NASH treatment were then constructed using the String database, and functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, were conducted through the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. Core targets were discerned using the Molecular Complex Detection (MCODE) and cytoHubba algorithms. Subsequently, molecular docking of key compounds to core targets was conducted using AutoDock software. Moreover, we established a free fatty acid-induced HepG2 cell model to simulate NASH in vitro, with YCWLP medicated serum intervention employed to corroborate the network pharmacology-derived hypotheses. Furthermore, a combination of enzyme-linked immunosorbent assay (ELISA), and Western blotting analyses was employed to investigate the lipid, hepatic enzyme, SHP2/PI3K/NLRP3 signaling pathway and associated cytokine levels.ResultsThe network pharmacology analysis furnished a list of 54 compounds from YCWLP and 167 intersecting targets associated with NASH. Through analytic integration with multiple algorithms, PTPN11 (also known as SHP2) emerged as a core target of YCWLP in mitigating NASH. The in vitro experiments validated that 10% YCWLP medicated serum could remarkably attenuate levels of total cholesterol (TC, 1.25 vs. 3.32) and triglyceride (TG, 0.23 vs. 0.57) while ameliorating alanine aminotransferase (ALT, 7.79 vs. 14.78) and aspartate aminotransferase (AST, 4.64 vs. 8.68) leakage in NASH-afflicted cells. In addition, YCWLP significantly enhanced the phosphorylation of SHP2 (0.55 vs. 0.20) and downregulated the expression of molecules within the SHP2/PI3K/NLRP3 signaling axis, including p-PI3K (0.42 vs. 1.02), NLRP3 (0.47 vs. 0.93), along with downstream effectors-cleaved Caspase-1 (0.21 vs. 0.49), GSDMD-NT (0.24 vs. 0.71), mature interleukin-1β (IL-1β, 0.17 vs. 0.48), pro-IL-1β (0.49 vs. 0.89), mature interleukin-18 (IL-18, 0.15 vs. 0.36), and pro-IL-18 (0.48 vs. 0.95).ConclusionOur research reveals that YCWLP exerts therapeutic effects against NASH by inhibiting lipid accumulation and inflammation, which involves the attenuation of pyroptosis via the SHP2/PI3K/NLRP3 pathway.

Abstract Liver metastasis is the major reason for most of colorectal cancer (CRC) related deaths. Accumulating evidence indicates that CRC patients with non-alcoholic fatty liver disease (NAFLD) are at a greater risk of developing liver metastasis. With the growing prevalence of NAFLD, a better understanding of the molecular mechanism in NAFLD-driven CRC liver metastasis is needed. In this study, we demonstrated that NAFLD facilitated CRC liver metastasis as a metabolic disorder and promoted the stemness of metastatic CRC cells for their colonization and outgrowth in hepatic niches. Metabolically, the lipid-rich microenvironment in NAFLD activated de novo palmitate biosynthesis in metastatic CRC cells via upregulating fatty acid synthase (FASN). Moreover, increased intracellular palmitate bioavailability promoted EGFR palmitoylation to enhance its protein stability and plasma membrane localization. Furthermore, we demonstrated that the FDA-approved FASN inhibitor orlistat could reduce NAFLD-activated endogenous palmitate production, thus inhibiting palmitoylation of EGFR to suppress CRC cell stemness and restrict liver metastasis in synergy with conventional chemotherapy. These findings reveal that the NAFLD metabolic microenvironment boosts endogenous palmitate biosynthesis in metastatic CRC cells and promotes cell stemness via EGFR palmitoylation, and FASN inhibitor orlistat could be a candidate adjuvant drug to suppress liver metastasis in CRC patients with NAFLD.

Abstract Radiotherapy (RT) is one of the important treatment modalities for non-small cell lung cancer (NSCLC). However, the maximum radiation dose that NSCLC patient can receive varies little. Therefore, the exploitation of novel RT sensitization approaches is a critical need for the clinical treatment. RT resistance in NSCLC is linked to tumor microenvironment (TME) hypoxia, cell cycle arrest and associated genetic alterations. Here, we designed a novel method for targeted delivery of quercetin (QT) and CeO2 to enhance RT sensitivity. We loaded QT into CeO2@ZIF-8-HA nanoparticles to prevent its degradation in the circulatory system and successfully delivered QT and CeO2 targeted to NSCLC tumors. Under the protection and targeted delivery of Zeolitic Imidazolate Framework-8 (ZIF-8), the nanocomplexes exhibited excellent catalytic mimetic activity in decomposing H2O2 into O2, thus significantly reversing the hypoxia of TME, while the radiosensitizer QT caused DNA damage directly after RT. In a subcutaneous tumor model, CeO2@ZIF-8-HA overcame radiation resistance and enhanced therapeutic efficacy. This multiple sensitization strategy combining delivery of QT and CeO2@ZIF-8-HA nanozymes opens a promising approach for RT of NSCLC.

Abstract Random jump of network communication topology challenges the tracking accuracy of linear switched reluctance motor (LSRM) system. This paper studies the pilot‐following consensus control of the multiple direct‐drive motion system (MDDMS) with semi‐Markov jump topology. The mathematical model of LSRM is constructed and the multi‐phase excitation strategy is studied. The directed graph is used to model the information transmission among the leaders and follower, and a new mechanism consensus based on previous states is provided. A consensus system based on semi‐Markov jump topology is constructed and the problem of consensus is shifted into a problem of stability analysis. A sufficient condition for consensus problem is obtained by using semi‐Markov switching system theory and graph theory. The MDDMS achieves consensus in the form of exponential convergence under the designed consensus controller. Several groups of simulation results verify the effectiveness of the proposed consensus control method.

Abstract Aim The aim of the study was to investigate the correlation between fear of COVID‐19 and mental health of nurses and the effects of psychological capital and burnout in this relation. Design A cross‐sectional study. Methods The online surveys were conducted among mainland Chinese nurses. Participants (n = 445; average age 32.89 ± 6.76 years) completed an online‐questionnaire based on the Fear of COVID‐19 Scale, the Psychological Capital Scale, Maslach Burnout Inventory Human Services Survey for Medical Professionals Scale and the 12‐Item Short Form Health Survey. Data analysis was conducted by Pearson's correlation analysis, Harman single‐factor test and the bootstrap method for mediating effect testing. Results (1) The study demonstrated a significant direct effect of fear of COVID‐19 on nurses' mental health, as well as on mediating factors such as burnout and psychological capital. (2) Regression analyses confirmed that while psychological capital bolstered mental health, burnout undermined it, with fear of COVID‐19 further imposing a negative influence. (3) Fear of COVID‐19 exerted an effect on the mental health of nurses by the independent and chain intermediary functions of psychological capital and burnout, resulting in a total mediating effect of −0.233.

Abstract Background During the tumourigenesis and development of colorectal cancer (CRC), the inactivation of tumour suppressor genes is closely involved, although detailed molecular mechanisms remain elusive. Accumulating studies, including ours, have demonstrated that basic leucine zipper transcription factor ATF (activating transcription factor)‐like 2 (BATF2) is a capable tumour suppressor that localises in the nucleus. However, its different subcellular localisation, potential functions and underlying mechanisms are unclear. Methods The translocation of BATF2 and its clinical relevance were detected using CRC samples, cell lines and xenograft nude mice. Candidate BATF2‐binding proteins were screened using co‐immunoprecipitation, quantitative label‐free liquid chromatography–tandem mass spectrometry proteomic analysis, Western blotting and immunofluorescence. Recombinant plasmids, point mutations and siRNAs were applied to clarify the binding sites between BATF2 and chromosome region maintenance 1 (CRM1). Results The present study found that BATF2 was mainly localised in the cytoplasm, rather than nucleus, of CRC cells in vitro and in vivo, while cytoplasmic BATF2 expression was inversely correlated with the prognosis of CRC patients. Furthermore, we identified the nuclear export and subsequent ubiquitin‐mediated degradation of BATF2 in CRC cells. Mechanistically, a functional nuclear export sequence (any amino acid) was characterised in BATF2 protein, through which BATF2 bound to CRM1 and translocated out of nucleus, ultimately enhancing CRC growth via inducing activator protein 1 (AP‐1)/cyclin D1/phosphorylated retinoblastoma protein (pRb) signalling pathway. Additionally, nuclear export of BATF2 can be retarded by the mutation of NES in BATF2 or the knockdown of CRM1, whereas CRM1 expression was negatively associated with nuclear BATF2 expression and the prognosis of CRC patients. Conclusion These findings revealed the biological effects and underlying mechanisms of cytoplasmic localisation of BATF2. Furthermore, suppressing nuclear export of BATF2 via mutating its NES region or inhibiting CRM1 expression may serve as a promising therapeutic strategy against CRC.

This study reveals an unrecognized role of ABHD5 in regulating colon cancer stemness via controlling YAP methylation and nuclear localization, further explaining the molecular mechanism through which ABHD5 functions as a tumour suppressor gene in colon cancer.

BackgroundMild cognitive impairment (MCI) is a common neurological disorder. Moxibustion has been shown to be effective in treating MCI, but its therapeutic mechanisms still remain unclear. This study mainly aimed to investigate the modulation effect of moxibustion treatment for patients with MCI by functional magnetic resonance imaging (fMRI).MethodsA total of 47 patients with MCI and 30 healthy controls (HCs) participated in resting-state fMRI imaging (rs-fMRI) scans. Patients with MCI were randomly divided into true moxibustion group (TRUE, n = 30) and sham moxibustion group (SHAM, n = 17). The degree centrality (DC) approach was applied to distinguish altered brain functions. Correlation analysis was then performed to examine the relationships between the neuroimaging findings and clinical symptoms.ResultsCompared with HCs, patients with MCI mainly showed decreased DC in the left middle frontal cortex (MFC) and bilateral middle cingulate cortex (MCC). After moxibustion treatment, the SHAM group had no significant DC findings, while TRUE group mainly showed significant increased DC in the bilateral MFC and MCC, as well as decreased DC in the left middle occipital cortex (MOC). Repeated measures analysis of variance (ANOVA) showed significant interactions between the two groups of patients with MCI. In addition, the higher Mini-Mental State Examination (MMSE) score was significantly positively correlated with increased DC in the right MFC and left MCC after moxibustion treatment.ConclusionOur findings demonstrate that the potential value of moxibustion treatment on MCI, which adds new insights into the popular view that moxibustion treatment may slow cognitive decline in patients with MCI.

ObjectiveThis study aimed to develop an effective support vector machine (SVM) classifier based on the multi-modal data for detecting the main brain networks involved in group separation of premature ejaculation (PE).MethodsA total of fifty-two patients with lifelong PE and 36 matched healthy controls were enrolled in this study. Structural MRI data, functional MRI data, and diffusion tensor imaging (DTI) data were used to process SPM12, DPABI4.5, and PANDA, respectively. A total of 12,735 features were reduced by the Mann–Whitney U test. The resilience nets method was further used to select features.ResultsFinally, 36 features (3 structural MRI, 7 functional MRI, and 26 DTI) were chosen in the training dataset. We got the best SVM model with an accuracy of 97.5% and an area under the curve (AUC) of 0.986 in the training dataset as well as an accuracy of 91.4% and an AUC of 0.966 in the testing dataset.ConclusionOur findings showed that the majority of the brain abnormalities for the classification was located within or across several networks. This study may contribute to the neural mechanisms of PE and provide new insights into the pathophysiology of patients with lifelong PE.

In nuclear power plants, due to the special working environment, the status of the fuel rods will be changed by the influence of radiation. And these changes, such as diameter expansion, will cause damage to the fuel rods and even affect the safe operation of nuclear power plants. Therefore, it is necessary to accurate diameter measurement for nuclear fuel rods. This paper aims to solve the measurement problem of fuel rods, and proposes a measurement technique based on image processing. In the proposed scheme, based on Zhang's method, tangential distortion is considered to be an affecting factor at first to improve the accuracy of camera calibration. Then, a particle swarm algorithm with all-parameter adaptive mutation method is proposed for the optimization of camera parameters. Finally, a simple and convenient method to calculate pixel equivalent is designed by considering the feature extraction of corner coordinates of subpixel to accurately obtain pixel equivalents. The effectiveness of this measurement scheme is highlighted on a measuring platform. The relative error of the proposed method reaches 0.041%, and RMSE reaches 4.16 μm. Experimental results demonstrate that this approach is efficient for high-accuracy diameter measurement of fuel rods.

Background The poor immunogenicity of solid tumors limits the efficacy ofanti-programmed cell death protein 1 (anti-PD1)-based immune checkpoint blockade (ICB); thus, less than 30% of patients with cancer exhibit a response. Currently, there is still a lack of effective strategies for improving tumor immunogenicity.Methods The antitumor effect of ultrasound-stimulated nanobubbles (USNBs) alone and in combination with an anti-PD1 antibody was evaluated in RM1 (prostate cancer), MC38 (colon cancer) and B16 (melanoma) xenograft mouse models. The phenotypes of antigen-presenting cells and CD8+ T cells were evaluated by flow cytometry. Damage-associated molecular pattern (DAMP) release, antigen release and tumor cell necrosis were assessed via western blot, flow cytometry, transmission electron microscopy and confocal microscopy.Results USNB promoted the infiltration and antitumor activity of CD8+ T cells. The combination of USNB and anti-PD1 blockade improved systemic antitumor immunity and resulted in an abscopal effect and long-term immune memory protection after complete tumor remission. Mechanistically, tumor-targeting USNB induced tumor cell necrosis through an ultrasound-mediated cavitation effect, which significantly increased DAMP release and tumor antigen presentation, consequently sensitizing tumors to ICB treatment.Conclusion The administration of USNB increased tumor immunogenicity by remodeling the tumor-immune microenvironment, providing a promising strategy for sensitizing poorly immunogenic solid tumors to immunotherapy in the clinic.

In many-objective optimization, maintaining a good balance between convergence and diversity have turned out to be a considerable challenge for classical evolutionary algorithms. The large scale solution set required to describe the entire Pareto optimal front hinder the decision makers from finding the most satisfactory solution, whereas he/she is only interested in a limited part of the objective space. The dilemma can be handled by incorporating the preference information in the search process. In this paper, an evolutionary algorithm based on region preference is proposed for many-objective optimization. The preference model is constructed in combination of the target region and reference points. To focus the search on the preference region while maintaining well convergence and diversity within the region, a tri-level ranking criterion is introduced into the proposed algorithm, and different rank works at different phase of the search process. A fuzzy theory-based interactive approach is proposed to guide more individuals to further search into the objective space with higher preference degree and help the decision maker choose the most interested solution. The proposed algorithm has been extensively compared with other state-of-the-art preference-based algorithms on DTLZ1~ DTLZ4 test problems having 3-10 objectives. The experimental results indicate that the proposed algorithm can achieve competitive and better performance. Moreover, we extend the algorithm to handle multiple target regions.

Establishing a symmetrical model of surrounding vehicles and accurately obtaining the driving state of the surrounding vehicles in the driving environment can improve the safety of driving, which is an important issue that needs to be considered in the automatic driving system or auxiliary driving system. Therefore, we propose an adaptive unscented Kalman filter algorithm based on Interacting Multiple Model (IMM) theory to estimate the state of target vehicle in the high-speed driving environment. To be specific, we use the Constant Turn Rate and Acceleration (CTRA) theory to establish the target vehicle kinematics model, simultaneously, in order to overcome the problem of estimator failure when the yaw rate is close to zero, a simplified version of the CTRA model is also introduced into the estimation process. In addition, the parameter adaptation strategy is added, so the proposed estimator can overcome the uncertainty of the noise model and improve its accuracy. Finally, the effectiveness of proposed state estimation algorithm is verified on the Carsim and Simulink co-simulation platform. The results of simulations and experiments show that the accuracy and stability of IMM-based algorithm is better than the single-model algorithm in different scenarios, and the parameter adaptation strategy brings performance improvement.

To address the problems of mismatch, poor flexibility and low accuracy of ordinary manipulators in the complex special deflagration work process, this paper proposes a new five-degree-of-freedom (5-DOF) folding deflagration manipulator. Firstly, the overall structure of the explosion-expulsion manipulator is introduced. The redundant degrees of freedom are formed by the parallel joint axes of the shoulder joint, elbow joint and wrist pitching joint, which increase the flexibility of the mechanism. Aiming at a complex system with multiple degrees of freedom and strong coupling of the manipulator, the virtual joint is introduced, the corresponding forward kinematics model is established by D–H method, and the inverse kinematics solution of the manipulator is derived by analytical method. In the MATLAB platform, the workspace of the manipulator is analyzed by Monte Carlo pseudo-random number method. The quintic polynomial interpolation method is used to simulate the deflagration task in joint space. Finally, the actual prototype experiment is carried out using the data obtained by simulation. The trajectory planning using the quintic polynomial interpolation method can ensure the smooth movement of the manipulator and high accuracy of operation. Furthermore, the trajectory is basically consistent with the simulation trajectory, which can realize the work requirements of putting the object into the explosion-proof tank. The new 5-DOF folding deflagration manipulator designed in this paper has stable motion and strong robustness, which can be used for deflagration during the COVID-19 epidemic.

The existing ultrasonic obstacle avoidance robot only uses an ultrasonic sensor in the process of obstacle avoidance, which can only be avoided according to the fixed obstacle avoidance route. Obstacle avoidance cannot follow additional information. At the same time, existing robots rarely involve the obstacle avoidance strategy of avoiding pits. In this study, on the basis of ultrasonic sensor obstacle avoidance, visual information is added so the robot in the process of obstacle avoidance can refer to the direction indicated by road signs to avoid obstacles, at the same time, the study added an infrared ranging sensor, so the robot can avoid potholes. Aiming at this situation, this paper proposes an intelligent obstacle avoidance design of an autonomous mobile robot based on a multi-sensor in a multi-obstruction environment. A CascadeClassifier is used to train positive and negative samples for road signs with similar color and shape. A multi-sensor information fusion is used for path planning and the obstacle avoidance logic of the intelligent robot is designed to realize autonomous obstacle avoidance. The infrared sensor is used to obtain the environmental information of the ground depression on the wheel path, the ultrasonic sensor is used to obtain the distance information of the surrounding obstacles and road signs, and the information of the road signs obtained by the camera is processed by the computer and transmitted to the main controller. The environment information obtained is processed by the microprocessor and the control command is output to the execution unit. The feasibility of the design is verified by analyzing the distance acquired by the ultrasonic sensor, infrared distance measuring sensors, and the model obtained by training the sample of the road sign, as well as by experiments in the complex environment constructed manually.

Aiming at the crossing problem of complex terrain, to further improve the ability of obstacles crossing, this paper designs and develops an all-terrain wheel-legged hybrid robot (WLHR) with strong adaptability to the environment. According to the operation requirements in different road conditions, the robot adopts a wheel and leg compound structure, which can realize the transformation of wheel movement and leg movement to adjust its motion state. The straight and turning process of the robot is analyzed theoretically, the kinematics model is established and solved, and obstacle crossing analysis is carried out by establishing the mathematical model of front wheel obstacle crossing when the robot meets obstacles. To verify the analysis results, ADAMS software is used to simulate and analyze the process of robot running on the complex road surface and obstacles-crossing. Finally, a theoretical prototype is made to verify its feasibility. Theoretical analysis and experimental results show that the designed WLHR is feasible and has the stability of the wheeled mechanism and the higher obstacle crossing ability of the legged mechanism so that the robot can adapt to a variety of complex road conditions.

Objective: This investigation examined the effect of velvet antler (VA) on endothelial progenitor cells (EPCs) and the associated effects to promote angiogenesis and repair vascular endothelial injury in rats with myocardial infarction (MI).Methods: VA was analyzed by liquid chromatography-mass spectrometry. Male Sprague Dawley rats were randomly divided into four groups: sham, MI, VA, and VA + DAPT (gamma-secretase inhibitor IX, a specific blocker of the Notch signaling pathway) group. The rats underwent ligation of the left anterior descending coronary artery for the establishment of MI. Sham-operated rats were used as controls. Blood was taken from the orbital plexus on the first and third days after the operation, and all rats were euthanized on the 7th day after surgery. The blood samples were used to detect the contents of circulating endothelial progenitor cells (CEPCs) and vascular endothelial growth factor (VEGF). Echocardiography was used to test the cardiac function. Cardiac tissue was used for immunohistochemistry and electron microscope, and the marginal zone of the MI tissue was used for western blot and reverse transcription-quantitative polymerase chain reaction.Results: The number of basically qualitative metabolites is 445. Among them, there are 74 substances with relative content greater than 0.05%. VA increased the concentration of CEPCs and VEGF in serum, CD133 content and microvessel density (MVD), and protected the morphology of microvascular endothelial cells in the marginal area of MI at 7 days post-MI surgery. CEPCs and MVD in the VA +DAPT group were lower than those of VA group. VA increased the protein expressions of Jagged-1, Notch1, NICD and HES1, and the mRNA expressions of Hes1 and Hey2, while some of the effects could be suppressed by DAPT.Conclusion: These results suggest that VA promotes the mobilization of EPCs to promote angiogenesis and repair vascular endothelial cell damage in post-MI rats, and these effects may be due to activation of the Notch signal pathway.

ZnO/Ni3ZnC0.7/x% CNT (x = 0, 2, 5, 10) urchin-like structures have been synthesized using a facile method based on metal-organic frameworks (MOFs) and applied as the electromagnetic absorber. The results of the experiments demonstrate that the content of multi-wall carbon nanotubes (MWCNT) has a great influence on the absorbing performance of the hybrid material. Conduction loss, interfacial polarization and ferromagnetic resonance all contribute to the electromagnetic absorption. The urchin-like ZnO/Ni3ZnC0.7/5% CNT composite presents excellent absorbing properties. When the filler loading of ZnO/Ni3ZnC0.7/5% CNT composite in paraffin matrix is only 10 wt.%, a minimum reflection loss of −33.2 dB is achieved at a layer thickness of 4.9 mm.

A fiber ring resonator (FRR) constructed using a Panda polarization-maintaining fiber does not effectively solve the problem of temperature-related polarization fluctuation, which considerably limits the detection accuracy of the resonant fiber optic gyro. The polarization-maintaining photonic crystal fiber (PM-PCF) can improve the thermal stability of the FRR. In this study, a structure that can simultaneously detect the polarization fluctuation of two FRRs is designed. We analyzed and verified the polarization phase shift errors of these two types of fibers, which are caused by the thermally induced birefringence changes. Theoretical simulation and experimental results confirm that a PM-PCF can be used to optimize the FRR, which can effectively suppress the polarization fluctuation.

The radiation effects of three Er3+-doped superfluorescent fiber sources (SFSs), which are based on three segments of Er-doped fibers with different lengths, are studied experimentally. We observed that the radiation-induced attenuation of the signal light of the 1530 nm band for an SFS is less than that of the 1560 nm band. Thus, the trimming technique of the Gauss-like spectra is investigated to reduce the mean wavelength drift. A filter was customized and used in superfluorescent fiber sources. To further reduce output power loss, the method with feedback control of pump power was adopted in the SFS. Then, the trimming spectral SFS with pump feedback control was tested under irradiation environment at the dose rate of 2.988 Gy/h. The experimental results demonstrate that the mean wavelength drift is

This experiment demonstrated the resonance asymmetry phenomenon in the resonant fiber optic gyro. The asymmetry of resonant curve affects the system open-loop bias and its stability, which directly affects the accuracy of angular velocity measurement. In this paper, a new mathematic model is established. The influence of the coupler normal mode loss difference (the phase difference between the coupler cross port output optical field and direct port is less than the ideal π/2) on the symmetry of resonant curve, the resonant signal modulated by the triangular wave, and the demodulation curve are analyzed. Moreover, the asymmetry of the resonant curve leads to the asymmetry of the resonant signal, as modulated by the triangular wave and the demodulation curve from the theoretical simulation and the experiment.

This paper focuses on the stability issue of discrete-time networked control systems with random Markovian delays and uncertain transition probabilities, wherein the random time delays exist in the sensor-to-controller and controller-to-actuator. The resulting closed-loop system is modeled as a discrete-time Markovian delays system governed by two Markov chains. Using Lyapunov stability theory, a result is established on the Markovian structure and ensured that the closed-loop system is stochastically stable. A simulation example illustrates the validity and feasibility of the results.