Entropy Measures in Machine Fault Diagnosis: Insights and Applications

Entropy, as a complexity measure, has been widely applied for time series analysis. One preeminent example is the design of machine condition monitoring and industrial fault diagnostic systems. The occurrence of failures in a machine will typically lead to non-linear characteristics in the measurements, caused by instantaneous variations, which can increase the complexity in the system response. Entropy measures are suitable to quantify such dynamic changes in the underlying process, distinguishing between different system conditions. However, notions of entropy are defined differently in various contexts (e.g., information theory and dynamical systems theory), which may confound researchers in the applied sciences. In this paper, we have systematically reviewed the theoretical development of some fundamental entropy measures and clarified the relations among them. Then, typical entropy-based applications of machine fault diagnostic systems are summarized. Further, insights into possible applications of the entropy measures are explained, as to where and how these measures can be useful towards future data-driven fault diagnosis methodologies. Finally, potential research trends in this area are discussed, with the intent of improving online entropy estimation and expanding its applicability to a wider range of intelligent fault diagnostic systems

A Polyadenylation Factor Subunit Implicated in Regulating Oxidative Signaling in Arabidopsis thaliana

BACKGROUND: Plants respond to many unfavorable environmental conditions via signaling mediated by altered levels of various reactive oxygen species (ROS). To gain additional insight into oxidative signaling responses, Arabidopsis mutants that exhibited tolerance to oxidative stress were isolated. We describe herein the isolation and characterization of one such mutant, oxt6. METHODOLOGY/PRINCIPAL FINDINGS: The oxt6 mutation is due to the disruption of a complex gene (At1g30460) that encodes the Arabidopsis ortholog of the 30-kD subunit of the cleavage and polyadenylation specificity factor (CPSF30) as well as a larger, related 65-kD protein. Expression of mRNAs encoding Arabidopsis CPSF30 alone was able to restore wild-type growth and stress susceptibility to the oxt6 mutant. Transcriptional profiling and single gene expression studies show elevated constitutive expression of a subset of genes that encode proteins containing thioredoxin- and glutaredoxin-related domains in the oxt6 mutant, suggesting that stress can be ameliorated by these gene classes. Bulk poly(A) tail length was not seemingly affected in the oxt6 mutant, but poly(A) site selection was different, indicating a subtle effect on polyadenylation in the mutant. CONCLUSIONS/SIGNIFICANCE: These results implicate the Arabidopsis CPSF30 protein in the posttranscriptional control of the responses of plants to stress, and in particular to the expression of a set of genes that suffices to confer tolerance to oxidative stress

Stochastic simulation of a model for circadian rhythms in plants

Circadian clocks allow living organisms to anticipate and adapt to the daily variations of the environment. The interlocked feedback loops of the transcription factors network in the plant clock generate oscillations with expression peaks at specific times of the day. In this work, we explore the effect of molecular noise on the behavior of the plant circadian clock through numerical simulations. The influence of system size, photoperiod, and mutations of clock genes on the robustness of the oscillations are discussed. Our simulations show that the oscillations remain robust when the mRNA and protein levels are in the range of a few hundreds molecules. Entrainment by light–dark cycles enhances the robustness compared to constant conditions. Multiple light inputs and inter-cellular coupling also contribute to the robustness of the oscillations. The comparison between deterministic and stochastic simulations of single and double mutants shows that stochasticity does not qualitatively affect the behaviour of mutants but that they do not have the same robustness to noise. Finally, the model shows that noise can induce transitions between two limit cycles in a birhythmic clock mutant.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Exponentially Fitted Two-Derivative Runge-Kutta Methods for Simulation of Oscillatory Genetic Regulatory Systems

Oscillation is one of the most important phenomena in the chemical reaction systems in living cells. The general purpose simulation algorithms fail to take into account this special character and produce unsatisfying results. In order to enhance the accuracy of the integrator, the second-order derivative is incorporated in the scheme. The oscillatory feature of the solution is captured by the integrators with an exponential fitting property. Three practical exponentially fitted TDRK (EFTDRK) methods are derived. To test the effectiveness of the new EFTDRK methods, the two-gene system with cross-regulation and the circadian oscillation of the period protein in Drosophila are simulated. Each EFTDRK method has the best fitting frequency which minimizes the global error. The numerical results show that the new EFTDRK methods are more accurate and more efficient than their prototype TDRK methods or RK methods of the same order and the traditional exponentially fitted RK method in the literature

Performance enhancement of ensemble empirical mode decomposition

Ensemble empirical mode decomposition (EEMD) is a newly developed method aimed at eliminating mode mixing present in the original empirical mode decomposition (EMD). To evaluate the performance of this new method, this paper investigates the effect of two parameters pertinent to EEMD: the amplitude of added white noise and the number of ensemble trials. A test signal with mode mixing that mimics realistic bearing vibration signals measured on a bearing test bed was developed to enable quantitative evaluation of the EEMD and provide guidance on how to choose the two parameters appropriately for bearing signal decomposition. Subsequently, a modified EEMD (MEEMD) method is proposed to reduce the computational cost of the original EEMD method as well as improving its performance. Numerical evaluation and systematic study using vibration data measured on an experimental bearing test bed verified the effectiveness and computational efficiency of the proposed MEEMD method for bearing defect diagnosis

Effect of modified opioid sparing anaesthesia on postoperative quality of recovery in patients undergoing laparoscopic bariatric surgery: protocol for a monocentre, double-blind randomised controlled trial – the MOSA study

Introduction Obesity patients undergoing laparoscopic bariatric surgery (LBS) are frequently encountered perioperative adverse events related to opioids-based anaesthesia (OBA) or opioids-free anaesthesia (OFA). While modified opioid-sparing anaesthesia (MOSA) has been shown to lower the occurrence of adverse events related to OBA and OFA. This study is to assess the efficacy of MOSA in enhancing the recovery quality among individuals undergoing LBS.Methods and analysis A single-centre, prospective, double-blind, randomised controlled trial is conducted at a tertiary hospital. A total of 74 eligible participants undergoing elective LBS will be recruited and randomly allocated. Patients in the MOSA group will receive a combination of low-dose opioids, minimal dexmedetomidine, esketamine and lidocaine, while in the OBA group will receive standard general anaesthesia with opioids. Patients in both groups will receive standard perioperative care. The primary outcome is the quality of recovery-15 score assessed at 24 hours after surgery. Secondary outcomes include pain levels, anxiety and depression assessments, gastrointestinal function recovery, perioperative complication rates, opioid consumption and length of hospital stay.Ethics and dissemination Ethical approval has been provided by the Ethical Committee of Yan’an Hospital of Kunming City (approval No. 2023-240-01). Eligible patients will provide written informed consent to the investigator. The outcomes of this trial will be disseminated in a peer-reviewed scholarly journal.Trial registration number The study protocol is registered at https://www.chictr.org.cn/ on 19 December 2023. (identifier: ChiCTR2300078806). The trial was conducted using V.1.0

A Computational Model for the Cold Response Pathway in Plants

info:eu-repo/semantics/publishe

Steady-State-Preserving Simulation of Genetic Regulatory Systems

A novel family of exponential Runge-Kutta (expRK) methods are designed incorporating the stable steady-state structure of genetic regulatory systems. A natural and convenient approach to constructing new expRK methods on the base of traditional RK methods is provided. In the numerical integration of the one-gene, two-gene, and p53-mdm2 regulatory systems, the new expRK methods are shown to be more accurate than their prototype RK methods. Moreover, for nonstiff genetic regulatory systems, the expRK methods are more efficient than some traditional exponential RK integrators in the scientific literature