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Aims Methods Results Conclusions We explored whether esketamine anesthesia during hysteroscopic surgery can reduce intraoperative hemodynamic fluctuations and improve patient benefit.A total of 170 patients undergoing hysteroscopic surgery were enrolled, and 151 patients were finally included in the analysis, among which 19 used vasoactive drugs during surgery. Patients were randomly assigned to either the esketamine anesthesia group (E group) or the sufentanil anesthesia group (S group). The primary outcomes were blood pressure and heart rate during the surgery. Secondary outcomes included resistance to laryngeal mask insertion, demand for propofol and remifentanil, nausea and vomiting, Richmond Agitation and Sedation Scale (RASS), dizziness and pain intensity after resuscitation, vasoactive medication treatment, hospitalization time and expenses.E group had a more stable heart rate, systolic blood pressure, diastolic blood pressure and mean blood pressure than the S group (p < 0.001). Patients in E group had a higher demand for propofol (p < 0.001) but better RASS scores (p < 0.001) after resuscitation. The incidence of intraoperative vasoactive medication use was higher in the S group (18.4% vs. 6.7%, p = 0.029). There were no statistically significant differences in terms of resistance to laryngeal mask insertion, remifentanil demand, time required for resuscitation, postoperative pain, dizziness, nausea or vomiting.Compared with sufentanil, esketamine‐induced anesthesia during hysteroscopic surgery can reduce intraoperative hemodynamic fluctuations and the incidence of intraoperative vasoactive medication. Although esketamine‐induced anesthesia may increase the demand for propofol during surgery, it does not affect the anesthesia recovery time and the quality of patient recovery is better. [ABSTRACT FROM AUTHOR]

For the detection and identification problems of common faults in the use of gearbox,considering the nonlinear,non-stationary properties of the gearbox vibration response signal,a method for the gearbox fault diagnosis based on local mean decomposition（ LMD） approximate entropy and PSO-ELM is proposed.Firstly,the LMD decomposition method is used for gearbox vibration signal,with correlation coefficient method extracted the first four PF components which contain the main fault information. By using the approximate entropy to describe quantitatively,and the feature vector is formed. Finally,the input weights of ELM and the threshold value of the hidden layer neurons are optimized by the particle swarm optimization algorithm,the model of PSO-ELM is established,and the approximate entropy values are input into the ELM and PSO-ELM models to recognize and classify the fault types of the gearbox of different conditions. The results show that based on LMD approximate entropy and PSO-ELM has the higher classification accuracy,the feasibility of this method is verified.

Aiming at the non-stationary and nonlinear of gearbox vibration signals,a fault diagnosis method based on the multi-fractal and particle swarm optimization support vector machine（PSO-SVM）is put forward.Firstly,the fractal filter with short-time fractal dimension as fuzzy control parameters is used to filtering noise reduction the gearbox vibration signals with bigger background noises.Secondly,the multi-fractal spectrum algorithm is applied to analyze the signal after filtering,the results show that the characteristic parameters:Δa（q）、f（a（q））maxand box dimensions Dbcan give a good presentation for gearbox working condition.Finally,the particle swarm optimization（PSO）is applied to optimize the parameters of support vector machine（SVM）.Taking the multi-fractal characteristic vectors as input parameters of PSO-SVM and SVM to recognize the fault types of the gearbox.The results show that SVM based on particle swarm optimization can improve the classification accuracy.Meanwhile,the validity of gearbox fault diagnosis based on muti-fractal and PSO-SVM is proved.

Targeting the non-stationary characteristics of short and transient impulse vibration signals of high speed automaton, a new method based on empirical mode decomposition (EMD) and close degree to diagnose fault for high speed automaton is proposed in this paper. Firstly, original acceleration vibration signals are decomposed into a finite number of stationary intrinsic mode functions (IMFs), and then the EMD energy of each IMF is calculated. The correlation analysis is applied and the results show that the first three IMFs contained the most dominant fault information; therefore, the energy feature extracted from the first three IMFs that could serve as a feature vector for fault patterns recognition of automaton. Finally close degree evaluation method was used to diagnose the automaton fault. The experimental results indicate that the proposed approach put forward in this paper can effectively identify automaton fault patterns and it has a great application potential in condition monitoring and fault diagnosis of automaton.

Objective: To determine the effects of robotic-assisted gait training on cardiopulmonary fitness and exercise capacity for people with incomplete spinal cord injury. Methods: PubMed, Embase, Web of Science, PEDro, CENTRAL and CINAHL were searched from inception until September 4, 2022. Randomized controlled trials that evaluated the effects of robotic-assisted gait training on cardiopulmonary fitness and exercise capacity for individuals with incomplete spinal cord injury were selected. Mean differences (MD) with 95% confidence interval (CI) were calculated. The methodological quality was evaluated by the Cochrane Risk of Bias 2.0 tool. Subgroup analyses were conducted according to the time since injury. Results: In total 19 studies involving 770 patients were eligible for analysis. Individuals with acute incomplete spinal cord injury in robotic-assisted gait training groups showed significantly greater improvements in 6-minute walking test (MD 53.32; 95% CI 33.49 to 73.15; P < 0.001), lower extremity motor scale (MD 5.22; 95% CI 3.63 to 6.80; P < 0.001) and walking index for spinal cord injury II (MD 3.18; 95% CI 1.34 to 5.02; P < 0.001). Robotic-assisted gait training improved peak oxygen consumption to a greater degree for chronic incomplete spinal cord injury patients (MD 4.90; 95% CI 0.96 to 8.84; P = 0.01). Conclusion: Robot-assisted gait training may be a feasible and effective intervention in terms of cardiopulmonary fitness and exercise capacity for individuals with incomplete spinal cord injury. [ABSTRACT FROM AUTHOR]

Most conventional post-stroke rehabilitation treatments do not involve imposed constraints of the unaffected limb. In contrast, Constraint-Induced Movement Therapy (CIMT) is comprised of massed task practice with the affected limb and constraint of the unaffected limb. CIMT is a promising rehabilitation technique used for motor recovery of affected limbs after stroke, but its effectiveness and mechanism are not fully understood. We compared the effects of the two exercise modes on limb function post-stroke in animal models and human subjects, and investigated whether oxidative stress response was involved in regulating the effects. We first conducted a randomized controlled trial (RCT), in which 84 subjects with cerebral infarction were assigned to dose-matched constraint-induced movement therapy (CIMT), or unconstraint exercise (UE), or conventional rehabilitation treatment. Motor functions of the limb are primary outcomes of the RCT measured using Brief Fugl–Meyer upper extremity score (FMA-UE), Ashworth score, and Barthel scale. Psychological influence of CIMT and UE was also examined using Self-Rating Depression Scale (SDS). Next, we investigated the effects of CIMT and UE in rats undergoing middle cerebral artery occlusion and reperfusion (MCAO/R). Motor function, infarct volume, and pathohistological changes were investigated by mNSS, MRI, and histological studies. The role of Keap1-Nrf2-ARE was investigated using qRT-PCR, Western blot, immunochemistry, immunofluorescence, and ELISA experiments. In RCT, patients taking CIMT had a higher score in FMA-UE, Barthel index, and SDS, and a lower score in modified Ashworth, compared to those taking UE. In rats receiving CIMT, motor function was increased, and infarct volume was decreased compared to those receiving UE. The expression of Keap1 protein and mRNA in the peri-infarct tissue was decreased, and Nrf2 and ARE protein and mRNA were increased in rats receiving CIMT compared with UE. Nrf2 agonist t-BHQ increased the benefits of CIMT. In conclusion, CIMT is more effective than UE in improving upper limb motor function, reducing muscle spasm in patients with cerebral infarction compared to UE, but patients receiving CIMT may feel depressed. Moreover, both CIMT and UE are beneficial to limb function recovery and limit the infarct expansion in MCAO/R rats, but CIMT was more effective than UE. Oxidative stress reaction has an essential role in regulating the CIMT induced benefits. [ABSTRACT FROM AUTHOR]

As a high-energy insensitive explosive which is expected to replace 2,4,6-trinitrotoluene (TNT), it is necessary to evaluate the thermal risk of 2,4-dinitroanisole (DNAN). In this article, the thermal performance of DNAN was tested using differential scanning calorimeter (DSC) and accelerating rate calorimeter (ARC). According to the test results, the decomposition activation energy (E), the pre-exponential constant (A), activation entropy (ΔS≠), activation enthalpy (ΔH≠), activation Gibbs free energy (ΔG≠) at TP0 of the reaction and the critical temperature of thermal explosion (Tb) were obtained. The kinetic model under adiabatic conditions was established. The thermal hazard assessment of DNAN was carried out according to the thermodynamic parameters, and the assessment results are of great significance to the application of DNAN. [ABSTRACT FROM AUTHOR]