Equivalent Consumption Research Articles

Adaptive ECMS based on speed forecasting for the control of a heavy-duty fuel cell vehicle for real-world driving

Aiming at reducing pollutant emissions, hydrogen and fuel cell hybrid electric vehicles (FCVs) represent a promising technological solution. In this scenario, this paper proposes an adaptive energy management strategy (A-EMS) based on speed forecasting for a heavy-duty FCV, in order to achieve stable battery charge sustenance in realistic driving conditions. A validated and optimized fuel cell system model has been integrated into a complete vehicle model developed in the GT-Suite environment. A short-term velocity prediction layer based on a long short term memory (LSTM) neural network has been built in the A-EMS framework. The network has been trained and tested with realistic driving data simulated by GT-Real Drive for routes of the Trans-European Transport Network. The vehicle speed prevision has been realized over different forecasting horizons (5, 10, and 20 s). The adaptive equivalent consumption minimization strategy (A-ECMS) combined with short-term vehicle speed prediction is the A-EMS core algorithm of the presented work. Its results are here compared with the standard ECMS (S-ECMS) for four different driving cycles, including both standardized (HDDT) and realistic driving profiles. Three different European routes, with varying characteristics and from different countries, have been selected to test the proposed strategy in various conditions. The short-term prediction layer achieves satisfactory forecasting accuracy, with a RMSE ranging from 1.76 km/h to 13.37 km/h. The A-ECMS provides an improved by an order of magnitude battery charge sustenance, evaluated in terms of maximum battery state of charge (SoC) variation and fluctuation degree, with a hydrogen consumption increase ranging from 3.76% to 11.40% compared to the S-ECMS, for which the driving cycle is supposed to be known beforehand. As an example, in the HDDT cycle, the absolute maximum SoC variation and its fluctuation degree are lowered by about 76% and 79%, respectively. In conclusion, the proposed A-ECMS demonstrated that it is applicable for real driving conditions without prior knowledge of the driving cycle while improving battery charge sustaining for a FCV.

Pre-operative sciatic nerve block vs postoperative surgeon-placed perineural stump catheter for prevention of phantom limb pain after below-knee amputation.

Pre-operative sciatic nerve block vs postoperative surgeon-placed perineural stump catheter for prevention of phantom limb pain after below-knee amputation.

Efficacy of prolonged intravenous lidocaine infusion for postoperative movement-evoked pain following hepatectomy: a double-blinded, randomised, placebo-controlled trial

BackgroundThe analgesic effect of intravenous lidocaine varies with the duration of lidocaine infusion and surgery type. We tested the hypothesis that prolonged lidocaine infusion alleviates postoperative pain in patients recovering from hepatectomy over the first 3 postoperative days. MethodsPatients undergoing elective hepatectomy were randomly assigned to receive prolonged i.v. lidocaine treatment or placebo. The primary outcome was incidence of moderate-to-severe movement-evoked pain at 24 h postoperatively. The secondary outcomes included incidence of moderate-to-severe pain during movement and at rest throughout the first 3 postoperative days, postoperative opioid consumption, and pulmonary complications. Plasma lidocaine concentration was also monitored. ResultsWe enrolled 260 subjects. Intravenous lidocaine lowered the incidence of moderate-to-severe movement-evoked pain at 24 h and 48 h postoperatively (47.7% vs 67.7%, P=0.001; 38.5% vs 58.5%, P=0.001) and reduced movement-evoked pain scores (3.7 [1.7] vs 4.2 [1.6]; mean difference 0.5 [95% confidence interval {CI}: 0.1–0.9]; P=0.018) and morphine equivalent consumption (47.2 [16.7] mg vs 52.6 [19.2] mg; mean difference 5.4 mg [95% CI: 1.0–9.8]; P=0.016) at 24 h postoperatively. Lidocaine also lowered the incidence of postoperative pulmonary complications (23.1% vs 38.5%; P=0.007). Median plasma lidocaine concentrations were 1.5, 1.9, and 1.1 μg ml−1 (inter-quartile ranges: 1.1–2.1, 1.4–2.6, and 0.8–1.6, respectively) after bolus injection, at the end of the surgery, and 24 h postoperatively. ConclusionsProlonged intravenous lidocaine infusion reduced the incidence of moderate-to-severe movement-evoked pain for 48 h after hepatectomy. However, the reduction in pain scores and opioid consumption by lidocaine was below the minimal clinically important difference. Clinical trial registrationNCT04295330.

New method of equivalent energy consumption for evaluating thermal performance of energy-saving materials in passive buildings

To simplify the evaluation of the energy-saving performance of materials in passive buildings, a new method of equivalent energy consumption is proposed. The principle is to integrate the difference between the surface temperature of envelopes and the ideal temperature. This method quantifies the difference between the actual and ideal situation, without the need to combine the results of multiple indices for comprehensive evaluation. The reliability and efficiency of this new method are analysed by taking the top floor room with phase change materials used in Guangzhou as an example. The important parameters including phase change temperature, thermal conductivity, and latent heat, are selected and compared with the optimization results obtained by other traditional indices using the method of equivalent energy consumption. The optimization results of multiple indices are found to be the phase transition temperature of 35 ℃, thermal conductivity of 0.2 W·m-1K-1, and latent heat of 300 kJ·kg-1. The method of equivalent energy consumption is consistent with it in many examples, which proves its reliability. Taking the case of traversing the phase transition temperature as an example, it only takes 7.2 min to obtain the equivalent energy consumption and optimization results. However, when using other traditional methods to optimize the parameters of the same case, approximately 7 h of extra time is needed to process and analyse the data until the conclusion is obtained, excluding the calculation time. Therefore, this accurate new method makes it convenient and efficient to evaluate the energy-saving performance of materials in passive buildings. Moreover, the new method is suitable for different regions, climates, and architectural backgrounds, and researchers can use it according to their own needs.

Adaptive Equivalent Consumption Minimization Strategy for Fuel Cell Buses Based on Driving Style Recognition

Driving style has a significant effect on the operating economy of fuel cell buses (FCBs). To reduce hydrogen consumption and prolong the fuel cell life of FCBs, this paper proposes an online adaptive equivalent consumption minimum strategy (A-ECMS) based on driving style recognition. Firstly, driving data from various drivers is collected, and a standard driving cycle is created. Neural networks are then used to identify driving conditions, and three fuzzy logic recognizers are developed to identify driving styles for different driving conditions. The driving style factor is associated with the equivalent factor using an optimization algorithm that incorporates hydrogen consumption cost and fuel cell degradation cost into the objective function. Simulation results demonstrate that the proposed A-ECMS can reduce equivalent hydrogen consumption, prolong fuel cell life, and result in a 6.2% reduction in total operating cost compared to the traditional method.

An ECMS Based on Model Prediction Control for Series Hybrid Electric Mine Trucks

This paper presents an equivalent consumption minimization strategy (ECMS) based on model predictive control for series hybrid electric mine trucks (SHE-MTs), the objective of which is to minimize fuel consumption. Two critical works are presented to achieve the goal. Firstly, to gain the real-time speed trajectory on-line, a speed prediction model is established by utilizing a recurrent neural network (RNN). Specifically, a hybrid optimization algorithm based on the genetic algorithm (GA) and the particle swarm optimization algorithm (PSOA) is used to enhance the prediction precision of the speed prediction model. Then, on this basis, an ECMS based on MPC (ECMS-MPC) is proposed. In this process, to improve the real-time and working condition adaptability of the ECMS-MPC, the power-optimal fuel consumption mapping model of the range extender is established, and the equivalent factor (EF) is real-time adjusted by means of the PSOA. Finally, taking a cement mining road as the research object, the proposed strategy is simulated with the collected actual vehicle data. The experimental results indicate that the prediction precision of the proposed speed prediction model is over 98%, realizing on-line speed prediction effectively. Furthermore, compared to the existing real-time EMSs, its fuel-saving rate had an increase of more than 13%. This indicates that the designed ECMS-MPC is able to offer a novel and effective method for the on-line energy management of the SHE-MTs.

A GM-Based Energy Management Strategy of Hybrid Power System for Hydrogen Fuel Cell Buses

Hydrogen energy is a clean, carbon-free, flexible, efficient, and widely used secondary energy source, which is an ideal alternative to promote the clean and efficient use of traditional fossil fuels. Hydrogen fuel cell bus has the advantages of a high-energy conversion rate, absolute pollution-free, sufficient raw materials, and convenient filling. The hybrid power system, composed of fuel cell and auxiliary energy source, is one of the key technologies to promote the development of hydrogen fuel cell vehicle. This study aims to propose an energy management strategy by analyzing the output characteristics and power allocation of fuel cell and power battery in the hybrid power mode with fuel cell as the main and battery as the auxiliary. A GM (1, N) power prediction strategy was proposed and compared with other strategies as an on-off control strategy and logical threshold value strategy in this study. The variation curves of the battery SOC and fuel cell output power under two working conditions of CCBC and real vehicle conditions were analyzed by using these three strategies, when the initial SOC of power battery is 30%, 70%, and 90%, respectively. Results showed that the power prediction strategy based on GM (1, N) has a better performance in output efficiency and fuel economy when compared to the other two strategies by analyzing the aspects of the battery in the SOC variation and equivalent hydrogen consumption and the fuel cell in the output power variation and hydrogen consumption. This research can be helpful to provide the suggested solution for energy management of the hybrid power system for hydrogen fuel cell buses.

Modeling, Simulation and Control Strategy Optimization of Fuel Cell Hybrid Electric Vehicle

This work represents the development of a Fuel Cell Hybrid Electric Vehicle (FCHEV) model, its validation, and the comparison of different control strategies based on the Toyota Mirai (1st generation) vehicle and its subsystems. The main investigated parameters are hydrogen consumption, and the variation of the state of charge, current, and voltage of the battery. The FCHEV model, which is made up of multiple subsystems, is developed and simulated in MATLAB® Simulink environment using a rule-based control strategy derived from the real system. The results of the model were validated using the experimental data obtained from the open-source Argonne National Laboratory (ANL) database. In the second part, the equivalent consumption minimization strategy is implemented into the controller logic to optimize the existing control strategy and investigate the difference in hydrogen consumption. It was found that the ECMS control strategy outperforms the rule-based one in all drive cycles by 0.4–15.6%. On the other hand, when compared to the real controller, ECMS performs worse for certain considered driving cycles and outperforms others.

Retrospective Study of the Safety and Efficacy of Intraoperative Methadone for Pain Management in Patients Undergoing Elective Intracranial Surgery

Patients undergoing intracranial surgery experience significant perioperative pain and are typically treated with short-acting opioids. Methadone, with its prolonged half-life and multimodal central nervous system effects, presents a promising option for managing postcraniotomy pain. Despite its proven efficacy in other types of surgeries, the use of methadone in patients undergoing craniotomy has not yet been explored. A retrospective chart review was conducted for 60 adult patients ranging in age from 18 to 81 years who received methadone during intracranial surgeries. The primary outcome of interest was the total opioid consumption in oral morphine milligram equivalents (MMEs) and patient-reported pain scores within 24 hours and up to 72 hours postoperatively. The methadone dosage varied from 5 to 20 mg. In the infratentorial group, the median total MME on postoperative day 1, 2, and 3 was 30.5, 17, and 0.8, respectively, with mean pain scores of 3.56, 3.91, and 2.71. In the supratentorial group, the median total MME on postoperative day 1, 2, and 3 was 17.85, 15.4, and 1.2, with mean pain scores of 2.31, 1.68, and 2.21, respectively. Patients who were chronic opioid users had significantly higher pain scores and average opioid use (P < 0.05). None of the patients required administration of naloxone or airway interventions. Comparison with the historical control showed that our study patients had lower pain scores and MME. The single intraoperative dose of methadone is well tolerated by adult patients undergoing various types of intracranial surgeries, with minimal side effects, including elderly patients aged 65 years or older.

Analgesic effects of intrathecal morphine and bupivacaine during robotic-assisted surgery: A prospective randomized controlled study.

Limited data exist concerning the management of postoperative pain after robotic-assisted surgery. The present study was performed to investigate the efficacy of intrathecal morphine and bupivacaine to treat postoperative pain in adult women undergoing robot-assisted laparoscopic hysterectomy. The primary outcomes of this study were opioid consumption and pain scores during and after robotic surgery. 96 patients were prospectively enrolled and randomized to a nonspinal group (n = 48) and a spinal group (n = 48). The intrathecal regimen consisted of 100 μg morphine and 15 mg of bupivacaine. The numeric rating scale scores (NRS) were assessed every 15 min in the postoperative care unit (PACU) and pain was treated with iv fentanyl or morphine when NRS was above 5 and orally oxycodone when NRS was 3-5. Cumulative iv opioid-consumption and NRS scores were compared. Intrathecal morphine and bupivacaine resulted in a significantly lower cumulative total iv opioid (morphine equivalents) consumption (9.4 ± 3.9 vs. 22.8 ± 6.1 mg equivalents). Highest recorded NRS scores in the PACU were also significantly lower in the spinal group (2.0 ± 2.6 vs. 5.3 ± 3.2). Intrathecal morphine and bupivacaine to treat postoperative pain after robotic-assisted laparoscopic hysterectomy decrease total opioid consumption and NRS pain scores. This might be of great importance to diminish the rate of other serious disadvantages related to opioids.

Performance enhancement of a nanofluid filtered solar membrane distillation system using heat pump for electricity/water cogeneration

Membrane distillation (MD) assisted by heat pump exhibits a favorable energy performance in water production, but it consumes huge precious electricity. In this work, a nanofluid filtered concentrating photovoltaic/thermal (CPV/T) technology is proposed to integrate with heat pump membrane distillation (HPMD) system for electricity/water cogeneration. Solar energy cascade utilization is considered in the system where electricity generated by CPV/T powers heat pump for MD heat recovery, and the collected thermal energy is used to heat seawater. A comprehensive study is carried out by establishing models of the receiver, direct contact membrane distillation (DCMD) and heat pump to investigate the performance of the nanofluid filtered solar membrane distillation system using heat pump. Results show that the seawater of 350.3 K is fed to the DCMD module while the electrical efficiency is above 12.2%. MD parametric analysis and equivalent specific thermal energy consumption (eSTEC) optimization are performed. We found that HPMD operates at the lowest eSTEC of 607.8 kWh·m−3 at heating temperature of 338 K and feed flow rate of 0.04 kg s−1. An overall system efficiency of 61% is obtained, and the comparison of permeate flux and energy consumption demonstrates advantages of the proposed system over other hybrid MD technologies.

A predictive control strategy based on A-ECMS to handle Zero-Emission Zones: Performance assessment and testing using an HiL equipped with vehicular connectivity

Recently, several metropolitan cities introduced Zero-Emissions Zones where the use of the Internal Combustion Engine is forbidden to reduce localized pollutants emissions. This is particularly problematic for Plug-in Hybrid Electric Vehicles, which usually work in depleting mode. So, the risk of not having enough energy stored to carry out the driving mission and then paying a fee is substantial. This work presents a viable solution by exploiting vehicular connectivity to retrieve navigation data of the urban event along a selected route. The battery energy needed, in the form of a minimum State of Charge (SoC), is calculated by a Speed Profile Prediction algorithm and a Backward Vehicle Model. That value is then fed to both a Rule-Based Strategy, developed specifically for this application, and an Adaptive Equivalent Consumption Minimization Strategy (A-ECMS). The effectiveness of this approach has been tested with a Connected Hardware-in-the-Loop (C-HiL) on a driving cycle measured on-road, stimulating the predictions with multiple re-routings. The tests have been conducted with different initial SoC values for each strategy, showing a maximum error in the SoC prediction of 2.4% and up to 26.1% of CO2 saving with the A-ECMS.

Efficacy of erector spinae nerve block for pain control after lumbar spinal surgeries: a systematic review and meta-analysis.

The review aimed to examine the evidence on the efficacy of erector spinae nerve block (ESPB) for pain control after lumbar spinal surgeries. PubMed, CENTRAL, Embase, and Web of Science were examined for published randomized controlled trials (RCTs) assessing ESPB with control for lumbar spinal surgery patients. The primary review outcome was 24-hour total opioid consumption in morphine equivalents. The secondary review outcomes were pain at rest at 4-6 hours, 8-12 hours, 24 hours and 48 hours, first rescue analgesic timing, needing rescue analgesics number, and postoperative nausea and vomiting (PONV). 16 trials were eligible. Total opioid consumption was significantly lower with ESPB as compared to controls (MD: -12.68 95% CI: -18.09, -7.28 I2=99% p<0.00001). Pain scores at 4-6 hours (MD: -1.37 95% CI: -1.98, -0.76 I2=95% p<0.0001), 8-12 hours (MD: -1.18 95% CI:-1.84, -0.52 I2=98% p=0.0004), 24 hours (MD: -0.53 95% CI:-1.03, -0.04 I2=96% p=0.04) and 48 hours (MD: -0.36 95% CI:-0.84, 0.13 I2=88% p=0.15) were significantly lower in the ESPB group. The meta-analysis found that the ESPB group required a significantly longer time for the first analgesic request (MD: 5.26 95% CI: 2.53, 7.99 I2=100% p=0.002), had lower demand for rescue analgesics (OR: 0.12 95% CI: 0.07, 0.21 I2=2% p<0.00001) and fewer incidence of PONV (OR: 0.27 95% CI: 0.15, 0.49 I2=51% p<0.0001). ESPB can be highly efficacious for postoperative analgesia in lumbar surgery patients. The block has the capability of reducing opioid consumption in the first 24 hours and pain scores up to 48 hours along with a significant reduction in the need for rescue analgesics and PONV.

Peripheral Nerve Block Utilization is Associated With Decreased Postoperative Opioid Consumption and Shorter Length of Stay Following Total Knee Arthroplasty.

This study aims to examine differences in postoperative complications and opioid consumption associated with perioperative peripheral nerve block (PNB) utilization during primary total knee arthroplasty (TKA). The Premier Healthcare Database was queried for adult patients who underwent primary, elective TKA from 2015 to 2020. Patients who received a femoral or adductor canal PNB were compared to patients who did not. PNB utilization was trended from 2015 to 2020. Univariate and multivariate regression analyses were performed to assess differences in the 90-day risk of postoperative complications between groups. The average inpatient opioid consumption in morphine milligram equivalents was assessed as a function of length of stay. Overall, 609,991 patients were included. PNB utilization increased from 9.29% in 2015 to 30.3% in 2020. After controlling for confounders, the PNB cohort was more likely to have same-day discharge (adjusted odds ratio [aOR] 1.88) and had a decreased risk of periprosthetic joint infection (aOR 0.87), pulmonary embolism (aOR 0.81), and respiratory failure (aOR 0.78). However, there was an increased risk of seroma (aOR 1.75) and hematoma (aOR 1.22) associated with PNB utilization. Lower average overall opioid exposure was seen in the PNB cohort vs no-PNB cohort (82.1 ± 194.7 vs 89.4 ± 214.1 morphine milligram equivalents, P < .001). PNB utilization during primary TKA is associated with a shorter length of stay and decreased risk of multiple postoperative complications, as well as reduced postoperative opioid consumption. These data provide evidence in support of the safety and efficacy of this emerging practice. However, the clinical relevance of an increased risk of seroma and hematoma formation may warrant further investigation.

Analgaesic efficacy of single-injection serratus anterior plane block for breast surgery: A systematic review, meta-analysis and trial sequential analysis of randomised controlled trials.

There is conflicting evidence regarding the analgaesic efficacy of single-shot serratus anterior plane block (SAP) for breast surgery. This meta-analysis aimed to evaluate the analgaesic efficacy of SAP compared with non-block care (NBC) and other regional blocks, i.e. paravertebral block (PVB) and modified pectoral nerve block (PECS block) for breast surgery. PubMed, Embase, Scopus, the Cochrane Central Register of Controlled Trials and ClinicalTrials.gov were searched. We included randomized controlled trials reporting the use of the SAP block in adult breast surgery. The primary outcome was postoperative oral morphine equivalent (OME) consumption for up to 24 hours. Random-effects models were used to pool results and mean difference (MD), and odds ratio (OR) was calculated for continuous and dichotomous outcomes, respectively. GRADE guidelines were used to evaluate the strength of evidence, and trial sequential analysis (TSA) was performed to provide certainty to the conclusion. Twenty-four trials enrolling 1789 patients were included. Moderate strength evidence suggested that SAP provided a significant reduction in 24-hour OME compared with NBC [MD - 24.9 mg (95% CI - 41.54, -8.25; P < 0.001, I2 = 99.68%)]. TSA ruled out the possibility of false-positive results. Subgroup analysis for the SAP demonstrated that the superficial plane approach was more effective in reducing opioid consumption than the deep approach. The odds of developing PONV were significantly lower in SAP compared to NBC. Compared with PVB and PECS, SAP block was not statistically different for 24-hour OME and time to first rescue analgaesia. Single-shot SAP reduced opioid consumption, prolonged analgaesia duration, lowered pain scores, and decreased the incidence of PONV compared to NBC. There was no statistically significant difference in the studied endpoints between SAP, PVB, and PECS blocks.

Analysis of cooling and heating characteristics of thermal management system for fuel cell bus

Vehicle thermal management system (VTMS) is an important part of the safe operation of fuel cell vehicles (FCVs). In this work, an integrated thermal management system was proposed for a fuel cell bus, with 80 kW fuel cell and 105 kWh battery. Liquid cooling is adopted for fuel cell, battery and motor. The model of VTMS was based on AMESim software. Two modes, including cooling and heating, were simulated for VTMS under different ambient conditions. The simulation is performed under a modified New European Driving Cycle (MNEDC), in which the running time is 1180 s and the distance is 10437 m. Results show that the VTMS could fulfill the temperature requirement for both modes. In cooling mode, ambient temperature of 34 °C, 37 °C and 40 °C are considered. The equivalent hydrogen consumption (EHC) is 505.68 g, 522.93 g and 539.48 g respectively. In heating mode, the ambient temperature is set to be −10 °C, −5 °C, 0 °C, and the corresponding EHC is 840.16 g, 783.64 g and 707.53 g, respectively. Besides, EHC at different heating target temperature for the fuel cell and battery was investigated. Results show that reducing the target heating temperature of fuel cell by 10 °C consumes less hydrogen than reducing the target heating temperature of battery by 5 °C. It is hoped that the results of this work will play a positive role in extending driving range.

Driving-Behavior-Aware Optimal Energy Management Strategy for Multi-Source Fuel Cell Hybrid Electric Vehicles Based on Adaptive Soft Deep-Reinforcement Learning

The majority of existing energy management strategies (EMSs), merely considering external driving conditions, often allocate demand power in an irrational way, resulting in a waste of energy and a short service life of power sources. Therefore, it is necessary to integrate driving behavior in EMS to reduce the fuel consumption and improve the lifespan of power sources. In this paper, a driving-behavior-aware adaptive deep-reinforcement-learning (DRL) based EMS is proposed for a three-power-source fuel cell hybrid electric vehicle (FCHEV). To fully utilize each power source, a hierarchical power splitting method is adopted by an adaptive fuzzy filter. Then, a high-performance driving behavior recognizer is employed, and Pontryagin’s minimum principle (PMP) method is used to compute the optimal equivalent factor (EF) of each driving behavior. To realize a trade-off between global learning and real-time implementation, an improved multi-learning-space DRL-based algorithm, applying driving-behavior-aware adaptive equivalent consumption minimization strategy (A-ECMS) and soft learning mechanism, is proposed and verified by a series of simulations. Simulation results show that, compared with the benchmark method ECMS, the proposed P-DQL method can reduce the hydrogen consumption by 49.9% on average, and the total cost to use by 31.4%, showing a promising ability to increase fuel economy and reduce hydrogen consumption and the total cost to use of FCHEV.

Ultrasound-Guided Quadratus Lumborum Block at the Lateral Supra-Arcuate Ligament versus Subcostal Transversus Abdominis Plane Block for Postoperative Analgesia Following Open Hepatectomy: A Randomized Controlled Trial.

Many studies confirmed that several approaches of quadratus lumborum block (QLB) were superior to transversus abdominis plane block (TAPB) in reducing opioid consumption during postoperative period. As a new QLB approach at the lateral supra-arcuate ligament (QLB-LSAL), the analgesic efficacy and safety in patients undergoing open hepatectomy are still unknown. This study aims to compare postoperative analgesia between the blocks in open hepatectomy. Sixty-two patients undergoing open hepatectomy were enrolled and randomly allocated into the QLB-LSAL group (group Q) and the subcostal TAPB group (group T). Preoperatively, patients received ultrasound-guided bilateral QLB-LSAL or subcostal TAPB with injection of 0.5% ropivacaine (a total volume of 40 mL). The primary outcome was cumulative total morphine equivalent consumption in the first postoperative 24 h. Other outcomes included numerical rating scale (NRS) scores at rest and coughing, cumulative total morphine equivalent consumption at 2, 6, 12, 48 h, Quality of Recovery-15 (QoR-15) scores, time to first patient-controlled intravenous analgesia (PCIA) request, time to first ambulation and adverse effects. The cumulative total morphine equivalent consumption in group Q was decreased significantly at all postoperative time points (P < 0.01). The postoperative NRS scores at rest and coughing in group Q were lower than those in group T at all postoperative time points except 48 h (P < 0.05). A significant increase was also observed in the QoR-15 scores among patients in group Q. Time to first PCIA request was significantly prolonged in group Q than in group T, and time to first ambulation was shortened. Adverse effects showed no statistical significance between the two groups. Compared with subcostal TAPB, preoperative bilateral QLB-LSAL provided superior analgesic properties and promoted early postoperative recovery quality in patients undergoing open hepatectomy. China Clinical Trials Registration Center (http://www.chictr.org.cn) ChiCTR2200063291, 3/9/2022.

Rectus sheath block versus local anesthetic infiltration in pediatric laparoscopic inguinal hernia repair: a randomized controlled trial.

Rectus sheath block (RSB) and local anesthetic infiltration (LAI) are used for postoperative analgesia in pediatric laparoscopic inguinal hernia repair. However, whether the analgesic effect of RSB is superior to LAI remains unclear. We hypothesized that RSB would reduce opioid consumption in patients. Patients aged 3-14 years scheduled for laparoscopic inguinal hernia repair were randomly allocated to the RSB, local anesthetic infiltration high concentration (LAIHC), local anesthetic infiltration low concentration (LAILC), or control groups. Preoperatively, they received 0.4mL/kg of 0.25% ropivacaine (RSB), 0.4mL/kg of 0.25% ropivacaine( LAILC), or 0.2mL/kg of 0.5% ropivacaine(LAIHC), and 0.2mL/kg of normal saline(control). The primary outcome was equivalent morphine consumption. We analyzed 136 patients (RSB, 33; LAIHC, 34; LAILC, 35; control, 34). Intraoperative morphine equivalent consumption was lower in the RSB group (0.115 [0.107-0.123]) than in the LAIHC (0.144 [0.137-0.151]), LAILC (0.141 [0.134-0.149]), and control (0.160 [0.151-0.170]) groups (P<0.001). In the post-anesthesia care unit, morphine equivalent consumption differed between the RSB (0.018 [0.010-0.027]), LAIHC (0.038 [0.028-0.049]), LAILC (0.056 [0.044-0.067]), and control (0.074 [0.063-0.084]) groups (P<0.001). The rescue morphine equivalent consumption did not differ significantly between the RSB (0.015 [0.007-0.023]) and LAIHC (0.019 [0.010-0.029]) groups, which were lower than that in the control group (0.037 [0.029-0.045]) (P=0.001). RSB can provide effective analgesia for pediatric laparoscopic inguinal hernia repair, with better effectiveness than that of LAI at the same dose.

A decision-making approach for the health-aware energy management of ship hybrid power plants

Although autonomous shipping has attracted increasing interest, its further development requires innovative solutions to operate autonomous ships without the direct intervention of human operators. This study aims to develop a health-aware energy management (HAEM) approach for ship hybrid power plants, integrating the health monitoring information from reliability tools with the energy management tools. This approach employs the equivalent consumption minimisation strategy (ECMS) along with a Dynamic Bayesian network (DBN), as well as the utopia decision-making method and a model for the ship hybrid power plant. The HAEM approach is demonstrated for a parallel hybrid power plant of a pilot boat considering realistic operating profiles. The results demonstrate that by employing HAEM approach for the investigated ship power plant operating for 300 h reduces its failure rate almost fourfold at the cost of fuel consumption increase of around 1.5%, compared to the respective operation with the ECMS. This study is expected to contribute towards the development of supervisory control of autonomous power plants.