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Purpose. This systematic review aims to consolidate key findings regarding the efficacy of pain relief medications administered prior to pan‐retinal photocoagulation (PRP) for diabetic retinopathy (DR). Methods. A comprehensive search of major databases from 1993 to 2023 was conducted. Clinical trials comparing pain relief drugs before PRP in patients diagnosed with DR requiring PRP treatment were eligible for inclusion. The assessment of pain scores involved the use of various scales, such as the visual analog scale (VAS), numerical rating scale (NRS), verbal rating scale (VRS), and other ordinal pain scales. In addition, laser parameters were taken into consideration during the analysis. Results. Twenty‐two clinical trials from initial 150 studies were included in the review. Nine studies evaluated the pain relief effects of nonsteroidal anti‐inflammatories NSAIDs (selective NSAID and nonselective NSAID), two studies compared the effects of opioids (conventional opioids and atypical opioids), and eleven studies investigated the effects of benzodiazepines, lidocaine, and other sedatives. Conclusion. This review synthesizes findings from multiple studies reporting pain as an adverse outcome of PRP in patients with advanced DR. Based on the evidence from reviewed clinical trials, the administration of lidocaine 2% via transconjunctival, retrobulbar, or peribulbar block along with specific NSAIDs, such as topical ketorolac administrated 24 hours before treatment or oral diclofenac potassium (50 mg) prior to PRP, demonstrated beneficial effects among patients with DR. [ABSTRACT FROM AUTHOR]

Antilock braking systems (ABSs) have been developed to improve vehicle control during sudden braking, especially on slippery road surfaces. The objective of such control is to increase wheel traction force in the desired direction while maintaining adequate vehicle stability and steerability and reducing the vehicle stopping distance. In this paper, an optimized fuzzy controller is proposed for ABSs. The objective function is defined to maintain the wheel slip to a desired level so that maximum wheel traction force and maximum vehicle deceleration are obtained. All the components of a fuzzy system are optimized using genetic algorithms. The error-based global optimization approach is used for fast convergence near the optimum point. Simulation results show fast convergence and good performance of the controller for different road conditions. Index Terms--Antilock braking system (ABS), error-based optimization, genetic-fuzzy controller, hybrid controller.

Adjustable speed motor drives are among the most representative types of non-linear systems which can exhibit rich varieties of complex dynamic behaviours. This study presents the investigation of chaotic phenomena in the switched reluctance (SR) motor drive employing digital speed regulator and hysteresis current controller. For conducting stability analysis, a small signal discrete-time model of the SR drive has been derived and analysed for a range of control parameters. The simulation results of time-domain and frequency-domain analysis and phase portraits of the SR drive system are also demonstrated and discussed. Two influencing factors for chaotic behaviour in the SR drive system are identified and examined in detail: the feedback delay of the speed regulator and measurement imperfection from a rotary incremental encoder. For verification, an 8/6 pole 2.3 kW SR drive is employed in experimental tests. The bifurcation diagrams of the reference signal, waveforms of phase current, and the corresponding frequency spectra are recorded and illustrated for both normal and chaotic operations, which reveal the pattern of chaos exhibited from this type of electric drive system. [ABSTRACT FROM AUTHOR]

The electric power transformer is a vital apparatus in power systems, and failure prognostics is significant for the protection of this asset. In addition to the asset damage, its unexpected failure would interrupt power delivery and jeopardize the stability of the system. There are several fault diagnosis methods introduced for the detection of this kind of fault; however, their functionality is for the postfault condition when the asset is already damaged, and the operation of the system is interrupted. Electric insulation deteriorations make the transformers susceptive to faults due to thermal and electrical stresses. In this article, the impact of early stages insulation deteriorations on the temperature inside the transformer is studied using a finite-element electromagnetic–thermofluid method and based on the observations an online sensor-based decision-making predictive fault diagnosis approach is proposed. Finally, the results are experimentally verified. [ABSTRACT FROM AUTHOR]