Simulation Scenarios Research Articles

Adaptive MPC path-tracking controller based on reinforcement learning and preview-based PID controller

Path-tracking control is a crucial process for autonomous vehicles, ensuring that the vehicle drives safely along the reference path, and the suitable controller parameters ensure the accuracy and stability of this process. To enhance the adaptability of traditional path-tracking controller parameters, this paper proposes an adaptive model predictive control (MPC) controller based on a preview-based PID controller and deep deterministic policy gradient (DDPG) algorithm to achieve adaptive tuning of the controller parameters. Starting with the design of the dynamics tracking error model of the vehicle and the MPC controller. Based on the actor-critic reinforcement learning architecture, the DDPG agent is designed to tune the prediction horizon and weight matrix of the MPC controller. A preview-based PID controller is proposed to improve the efficiency and stability of reinforcement learning and compensate for the error in vehicle modeling. The improved algorithm performance is verified through the simulation scenarios of high-speed lane changing and accelerated overtaking scenarios constructed by MATLAB/Simulink. The results show that the improved algorithm significantly improves the adaptive ability of the traditional MPC controller to time-varying conditions and achieves higher tracking accuracy and stability.

A Computer Modeling-Based Target Zone for Transposition Osteotomy of the Acetabulum in Patients with Hip Dysplasia.

This study aimed to determine the acetabular position to optimize hip biomechanics after transposition osteotomy of the acetabulum (TOA), a specific form of periacetabular osteotomy, in patients with hip dysplasia. We created patient-specific finite-element models of 46 patients with hip dysplasia to simulate 12 virtual TOA scenarios: lateral rotation to achieve a lateral center-edge angle (LCEA) of 30°, 35°, and 40° combined with anterior rotation of 0°, 5°, 10°, and 15°. Joint contact pressure (CP) on the acetabular cartilage during a single-leg stance and simulated hip range of motion without osseous impingement were calculated. The optimal acetabular position was defined as satisfying both normal joint CP and the required range of motion for activities of daily living. Multivariable logistic regression analysis was used to identify preoperative morphological predictors of osseous impingement after virtual TOA with adequate acetabular correction. The prevalence of hips in the optimal position was highest (65.2%) at an LCEA of 30°, regardless of the amount of anterior rotation. While the acetabular position minimizing peak CP varied among patients, approximately 80% exhibited normalized peak CP at an LCEA of 30° and 35° with 15° of anterior rotation, which were the 2 most favorable configurations among the 12 simulated scenarios. In this context, the preoperative head-neck offset ratio (HNOR) at the 1:30 clock position (p = 0.018) was an independent predictor of postoperative osseous impingement within the required range of motion. Specifically, an HNOR of <0.14 at the 1:30 clock position predicted limitation of required range of motion after virtual TOA (sensitivity, 57%; specificity, 81%; and area under the receiver operating characteristic curve, 0.70). Acetabular reorientation to an LCEA of between 30° and 35° with an additional 15° of anterior rotation may serve as a biomechanics-based target zone for surgeons performing TOA in most patients with hip dysplasia. However, patients with a reduced HNOR at the 1:30 clock position may experience limited range of motion in activities of daily living postoperatively. This study provides a biomechanics-based target for refining acetabular reorientation strategies during TOA while considering morphological factors that may limit the required range of motion.

Teamwork in Rural Emergency Health Care: A Simulation-Based Cross-over Study of Co-located and Distributed Teams.

Despite the increasing use of distributed healthcare teams, performance evaluation is largely lacking. This study examined rural emergency health care in Sweden to determine the effect of teams being either co-located or distributed with remote physicians accessible via telemedicine. In this crossover study, 17 three-person teams were video recorded during co-located and distributed simulated scenarios. Team performance in the video recordings was evaluated using the TEAM instrument. Co-located scenarios had significantly higher Total ratings for the instrument (items 1-11), in the teamwork domain (items 3-9), and in overall performance (item 12) compared with distributed scenarios (P < 0.005). Item-level analysis revealed that co-located teams were better at completing tasks on time (item 4) and showed greater adaptability to changing situations (item 7). The higher rating of the performance of co-located teams underscores the challenges facing distributed teams. Given that distributed healthcare teams are a reality in rural areas in northern Sweden, education and training must be adapted to address these challenges. This adaptation is crucial for ensuring high-quality patient care by distributed teams.

Small Area Estimation of Household Economic Indicators under Unit-Level Generalized Additive Models for Location, Scale and Shape

Abstract We propose a small area estimation model based on Generalized Additive Models for Location, Scale and Shape (SAE-GAMLSS) for the estimation of household economic indicators. SAE-GAMLSS relax the exponential family distributional assumption and allow each distributional parameter to depend on covariates. A bootstrap approach to estimate the MSE is proposed. The SAE-GAMLSS estimator shows a largely better performance than the well-known Empirical Best Linear Unbiased Predictor (EBLUP) under various simulated scenarios. Per-capita consumption of Italian and foreign households in Italian regions, in urban and rural areas, is estimated using SAE-GAMLSS. Results show that the well-known Italian North–South divide does not hold for foreigners.

Research on the Carbon Emission Prediction and Reduction Strategies for the Civil Aviation Industry in China: A System Dynamics Approach

With the continuous growth in the volume of global air transportation, the carbon emissions of the civil aviation industry have received increasing attention. Carbon emission reduction in civil aviation is an inevitable requirement for achieving sustainable social development. This article aims to use system dynamics (SD) methods to establish a carbon emission model for the civil aviation industry that includes economic, demographic, technological, policy, and behavioral factors; analyze the key factors that affect carbon emissions; and explore effective emission reduction strategies. Researchers have found that SD-based carbon emission prediction has a high accuracy and is suitable for predicting carbon emissions in civil aviation. Through different scenario simulations, it has been found that any single emission reduction measure will struggle to effectively contribute to the expected carbon reductions in China’s civil aviation. Simultaneously adopting measures such as improving fuel efficiency, adopting clean energy, and using new-power aircraft is an effective way to reduce carbon emissions from civil aviation. In addition, policy intervention and technological innovation are equally crucial for achieving long-term emission reduction goals. The research results not only provide a scientific basis for the sustainable development of the aviation industry but also provide a reference for policymakers to formulate comprehensive emission reduction strategies.

Transformation and development of simulation-based education and child first aid skills training

Background: Simulation-based medical education is a complex learning methodology in different fields. Exposing children to this teaching method is uncommon as it is designed for adult learning. This study aimed to develop and implement simulation-based education in first aid training of children and investigate the emotions of children in post-simulation scenarios that replicate emergency situations. Methods: This was a phenomenological qualitative research study. The participants attended the modified “Little Doctor” course that aims to train children in first aid and, subsequently, completed simulation scenarios. The children attended focus groups and were asked about their experiences of the course and how they felt during the simulation scenarios. Results: 12 children (Age 8–11 years old) attended the course, and 10 completed the simulation scenarios and focus groups. The major theme derived from was the simulation experience’s effect, which was divided into two subthemes: the emotion caused by—and the behavioral response to—the simulation. The analysis revealed shock and surprise toward the environment of the simulation event and the victim. The behaviors expressed during the simulation scenarios ranged from skill application and empathy to recall and teamwork. Conclusions: Simulation scenarios were successfully implemented during the first-aid training course. Although participants reported mixed feelings regarding the experience, they expressed confidence in their ability to perform real-life skills.

Stimulating ambulance specialist nurse students' ethical reflections by high-fidelity simulation.

Introduction: Ethical competence in professional practice can be considered essential among nurses and nurses in ambulance care encounter ethical dilemmas frequently. To enhance ethical competence among students in the ambulance specialist nursing program, high-fidelity simulation scenarios including ethical dilemmas were introduced as a learning activity. Research aim: The research aim was to investigate the usefulness of high-fidelity simulation in ambulance specialist nurse education to teach ethical reasoning when caring for children. Research design: This study was conducted as a qualitative interview study, complemented with observations and using field notes and qualitative interviews for data collection. Data was analysed using deductive qualitative content analysis based on a care ethical model. Participants and research context: Participants (n = 35) were recruited from an ambulance nurse educational program at a Swedish university. Data was collected after the students took part in two high-fidelity simulations involving children in an ambulance care setting. Ethical considerations: The study has been vetted and approved by the ethical council at the University of Borås, Sweden. The study follows the Helsinki Declaration's advice on ethical principles. Results: The results showed that most of the students expressed some form of ethical reasoning during the simulation sessions, which were elaborated and reflected upon during the debriefing part of the sessions. The simulation design seemed to have a great impact on the outcome of the student's ethical reasoning, where increased immersion led to deeper emotional engagement among the students which increased awareness of their personal preconceptions. Conclusions: This study aimed to investigate whether high-fidelity simulations could be useful to stimulate ethical reflections and contribute to increased ethical competence among students. In conclusion, a well-designed high-fidelity simulation can be useful as an educational tool to learn and enhance ethical competence among specialist ambulance nursing students.

Numerical simulation on exhaled aerosol transmission based on realistic oral-nasal structures and temperature distribution

ABSTRACT Respiratory infections are currently understood to be caused by pathogens released through the nose or mouth of an infected individual, and subsequently transmitted to susceptible hosts. These pathogens are enclosed in liquid particles that are aerosolized from the respiratory tract during activities such as breathing, speaking, sneezing, and coughing. These particles vary widely in size, ranging from submicron to several microns. While past research has largely overlooked the human respiratory system, recent analysis has revealed that the actual structure of the nasal cavity significantly influences the prediction of aerosol transmission during exhalation. In this study, computational fluid dynamics (CFD) simulations were conducted to analyze the aerosol transmission generated during exhalation from the nasal and oral cavities. Realistic nasal and oral cavity structures were taken into account, and authentic temperature distributions were applied to the surfaces. Additionally, inhalation conditions for susceptible individuals were established to evaluate the risk of inhalation-generated exposure. Through various simulation scenarios, we separately discussed the impact of environmental wind speed, separation distance, and exhalation flow rate. The simulation results indicate that environmental wind amplifies the complexity of the flow field and the transmission and deposition of particles between two individuals. Under ambient wind velocities of 0.5 m/s and 1 m/s, it was observed that over 80% of the particles with a diameter of 1 µm inhaled through the nasal cavity accounted for the total deposition on the infected individual. Furthermore, high exhalation flow rates exhibited higher deposition ratios at close distances, in line with our expectations. Therefore, it is advisable to minimize close contact as much as possible during periods of frequent respiratory infections, and to wear masks in order to reduce the risk of inhalation exposure. Implications: During the activities such as breathing, speaking, sneezing, and coughing, liquid particles containing pathogens are aerosolized from the respiratory tract and are released from nose or mouth through the nebulization. In this study, we investigated the transmission of aerosols from human exhalation in the outdoor environment, innovatively taking the real oral-nasal structure and the active inhalation of vulnerable people into consideration, and explored the human-to-human transmission of respiratory viruses. The results are beneficial for public health assessment and policy development.

Optimization of Multitask Scheduling for Swarm UAV System with Charging Platform

Swarm UAV technology have potential application in a wide range because of its ability to utilize large number, low cost and unified scheduled UAVs. Unified scheduling is tasks and resources allocation through UAV scheduling optimization, which is the key problem for swarm UAV research. Existing scheduling research mainly focuses on scheduling analysis for small-scale, short-time tasks of swarm UAVs, and rarely consider the application of charging platform. Scheduling optimization must consider the influence of charging and other factors for future UAV multi-task and long-time applications . An improved swarm UAV task scheduling method based on a unified scheduling model and improved genetic algorithms was proposed. First, the wireless charging platform resources are incorporated into the UAV working environment, and the working scenario is modeled systematically. Then, the genetic algorithm is used to optimize the task and charging platform resource assignment. Finally, the proposed method is tested and validated using simulated scenarios. Test results show that the proposed method can better adapt to changes in tasks, environment and resources, and still shows good results with relatively large swarms.

VLC performance in underground vehicular tunnels

In recent years, the integration of intelligent transportation systems (ITS) has gained popularity as a means of enhancing the safety of roadways and underground tunnels and reducing traffic congestion. Given the fact that conventional radio frequency (RF) communication systems are vulnerable to significant limitations as a result of a variety of factors, including signal attenuation and interference, which affect their application, the emerging visible light communication (VLC) technology is an exciting potential candidate for facilitating wireless access in such environments. This study investigates the deployment of VLC systems in underground vehicular tunnels involving a handover strategy based on the software-defined network (SDN) approach, with the objective of addressing the fundamental challenges faced by communication systems in such scenarios. The Optisystem software is used to simulate and investigate the performance of the proposed system, which is based on orthogonal frequency division multiplexing (OFDM) technology in both line-of-sight (LOS) and non-line-of-sight (NLOS) conditions. The simulated scenario is capable of achieving a data rate of 10 Gbps within a link range of 3 meters in the LOS approach. In the NLOS propagation model, a data rate of 2 Gbps can be attained without any error. The simulation results reveal a particular perspective on the viability of VLC systems in improving the communication infrastructure in underground vehicular tunnels and promoting efficient tunnel operations. The evaluation of the simulated system is conducted based on bit error rate (BER), signal-to-noise ratio (SNR), and the constellation diagram.

Deep Learning Transient Electromagnetic Inversion for Seawater Intrusion

Abstract To enhance the capability of transient electromagnetic method(TEM) in detecting seawater intrusion and delineating the boundaries in coastal areas, we developed a deep learning inversion method for TEM data based on the Swin Transformer model in this study. First many standardized resistivity models were designed and generated to describe t the subsurface resistivity structures associated with seawater intrusion in coastal areas .Then, TEM forward modelling was performed to compute the corresponding TEM responses, thereby constructing a seawater intrusion-oriented training dataset. Then, the robust Swin Transformer model was employed as the backbone network to build a deep learning inversion model, named SITEMNet, to derive a direct nonlinear transformation that maps TEM responses to subsurface resistivity models. The proposed SITEMNet inversion technique was validated using simulated data scenarios and actual field TEM measurements, showing great promise in accurately identifying seawater intrusion interface and geological formations.

Leadership Lingo: Developing a Shared Language of Leadership Behaviors to Enrich Debriefing Conversations.

Leadership in medical emergencies is variable and frequently suboptimal, contributing to poor patient care and outcomes. Simulation training can improve leadership in both simulated practice and real clinical emergencies. Thoughtful debriefing is essential. However, unclear language around leadership limits facilitators' capacity for transformative reflective discussion. Internal medicine trainees participated in simulated medical emergency scenarios. Video recordings of consenting participants were analyzed using template analysis. A priori codes from existing literature formed an initial coding template. This was modified with inductive codes from the observed behaviors to develop a taxonomy of leadership behaviors in simulated medical emergencies. The taxonomy was then transformed into an infographic, to be used as a leadership debriefing tool. The taxonomy of leadership behaviors consisted of the following 4 themes: Structuring, Decision making, Supporting, and Communicating. Structuring behaviors shaped the team, ensuring that the right people were in the right place at the right time. Decision-making behaviors steered the team, setting a direction and course of action. Communicating behaviors connected the team, sharing valuable information. Supporting behaviors nurtured the team, guiding team members to perform at their optimum level. Debriefing-as-imagined is not always debriefing-as-done. A shared language of leadership can connect educators and learners, advancing critical debriefing conversations and enabling facilitators to drive meaningful reflective discussion. The use of infographics in simulation offers an opportunity to support educators in facilitating complex debriefing conversations.

Three-Dimensional Internal Voids and Marginal Adaptation in Deep Margin Elevation Technique: Efficiency of Highly Filled Flowable Composites.

To evaluate interfacial three-dimensional adaptation and internal voids of different flowable materials before and after cyclic fatigue in a simulated deep-margin elevation scenario. Eighty (n &#61; 80) extracted premolars were selected and two Class II cavities were prepared. The mesial one with cervical margin 1 mm above the cementum-enamel junction (CEJ) and the distal one with cervical margin 1 mm below the CEJ. After performing adhesive procedures, specimens were divided into four groups according to the employed materials for 2 mm horizontal deep-margin relocation: nanohybrid composite (Clearfil ES2, Kuraray); conventional viscosity flowable composite (Tetric Flow, Ivoclar); medium viscosity flowable composite (Majesty ES2 Low Flow, Kuraray); high viscosity flowable composite (Majesty ES2 Super Low Flow, Kuraray). All restorations were finalized by oblique layering with nanohybrid composite (Clearfil ES2, Kuraray). To reveal interfacial and internal gap progression, specimens were scanned with a micro-CT (SkyScan 1172), before and after 500,000 cycles of mechanical chewing simulation (50 N, 1 Hz). Data were imported into Mimics software after smoothing and region growing. Only the 2 mm margin relocation volumes were considered. Obtained masks were analyzed for noise removal and volume calculation. At baseline, interfacial gap progression and internal voids, expressed in mm3, were collected and statistically analyzed with two-way ANOVA (α 0.05) for the variables substrate and restorative materials followed by Tukey post-hoc test. An additional two-way ANOVA test, followed by Tukey post-hoc test, was performed to evaluate variation in interfacial gap progression after mechanical aging. At baseline, the ANOVA test showed a significant difference for the variable restorative materials (p &#61; 0.01). More specifically, the Tukey post-hoc test revealed that the highly filled medium viscosity composite performed better than the conventional viscosity composite at baseline for the interfacial gap. The internal voids ANOVA test at baseline reported no significant differences for the variable tested. Analysis of variance for internal gap progression after thermocycling showed no differences for both substrate and restorative material employed. Highly filled medium viscosity composite performed significantly better than the conventional viscosity flowable composite for what concern baseline interfacial gaps. Artificial aging with a chewing simulator and thermocycling did not affect interfacial gap progression on enamel and dentin. The tested restorative materials performed equally after aging.

Adaptive output feedback control of a bidirectional AC/DC totem‐pole PFC converter for wireless charging of electric vehicles

AbstractThis paper deals with the control problem of a single‐phase bidirectional alternating current/direct current (AC/DC) totem‐pole power factor correction (PFC) converter intended to be used in wireless power transfer (WPT) chargers for electric vehicles (EVs). The converter is operating as a bridgeless boost rectifier with the PFC functionality during grid to vehicle (G2V) mode and as a PFC inverter during vehicle to grid (V2G) mode. Firstly, the operating principle is presented. Secondly, an overall mathematical model governing all the operating modes of the converter is elaborated. Thirdly, due to the nonlinearity of the studied system, a nonlinear controller–based Lyapunov technique is designed to achieve the following control objectives: (i) unity power factor (UPF) during both power transfer modes G2V and V2G, (ii) regulation of the DC‐link voltage, and (iii) asymptotic stability of the closed‐loop system. Further, as the developed control law requires the measurement of all voltages and currents, an adaptive observer–based Kalman‐like technique is designed to estimate all the required signals and parameters. The performances of the proposed output feedback control technique are validated through several simulation scenarios showing that all control objectives are achieved. It should be noted that the use of the Kalman observer reduces the complexity of the systems as it requires only two measurements (grid voltage and current) making it an advantageous solution over existing solutions where three measurements are generally used. Furthermore, due to the low‐pass filtering behavior of the observer and its susceptibility to estimate the converter's parameters, the robustness of the controller and its insensitivity to the parameter uncertainties are greatly improved.

Land Use Changes and Future Land Use Scenario Simulations of the China–Pakistan Economic Corridor under the Belt and Road Initiative

The China–Pakistan Economic Corridor (CPEC), as an important part of the Belt and Road Initiative, is of great significance for the promotion of sustainable development in the region through the study of land use change and the simulation of future multi-scenarios. Based on the multi-period land use data of the CPEC, this study firstly analyzed the spatial and temporal land use changes in the CPEC from 2000 to 2020 by using GIS technology, and, secondly, simulated the land use patterns of the CPEC under four scenarios, namely, natural development, investment priority, ecological protection, and harmonious development, in 2040 by using the Markov-FLUS model with comprehensive consideration of natural, socio-economic, and other driving factors. The results show the following: (1) The urban land, forest land, and grassland in the CPEC from 2000 to 2020 show an increasing trend, while the farmland, unutilized land, and water area categories show a decreasing trend. In terms of land use transfer changes, the most frequently transferred out is the conversion of unutilized land to grassland. (2) The FLUS model has high accuracy in simulating the land use pattern of the CPEC, and its applicability in the CPEC area is strong and can be used to simulate the future land use pattern of the CPEC. (3) Among the four different land use scenarios, the harmonious development scenario strikes a better balance between infrastructure construction, economic development, and ecological protection, and can provide a scientific basis for future land management in the CPEC, in order to highlight the importance of promoting economic growth and ecological protection and ultimately realize sustainable development.

Exploring the regional cooling efficiency of urban residential vegetation using scenario simulation

The study of the cooling efficiency of vegetation in urban residential areas at a micro-scale is important for improving the thermal environment of those areas. The quantitative analysis of the effect of the layout of different building patterns on the cooling efficiency of green space is particularly crucial. This study takes a typical residential area with a row-column arrangement in Jiangning District, Nanjing City, Jiangsu Province, China, as the research object. Using the ENVI-MET model used for numerical simulation, 15 simulation scenarios were designed based on building orientation, height, and density. The research proposes the methodology of the regional cooling efficiency (RCE) of urban residential vegetation, reveals the daily variation characteristics of the RCE of vegetation in a residential area, and analyzes the factors influencing of regional cooling efficiency. The results showed that the daily variation in RCE for vegetation in the residential area exhibited a single-peak trend. The minimum and maximum RCE values appeared at 6:00 and 14:00, respectively. The average air temperature and building density in the residential area had a significant positive correlation with RCE, while average relative humidity had a negative correlation. Average wind speed, average building height, and average sky view factor showed nonlinear correlations with RCE, and the importance ranking of each factor's effect on RCE was air temperature > relative humidity > building density > wind speed > building height > sky view factor. This study will provide theoretical support for improving the thermal environment in urban residential areas during the urban planning process.

Large scale multi-GPU based parallel traffic simulation for accelerated traffic assignment and propagation

Traffic simulation is a critical tool for congestion analysis, travel time estimation, and route optimization in urban planning, benefiting navigation apps, transportation network companies, and state agencies. Traditionally, traffic micro-simulation frameworks are based on road segments and can only support a limited number of main roads. Efficient traffic simulation on a regional scale remains a significant challenge due to the complexity of urban mobility and the large scale of spatiotemporal data. This paper introduces a Large Scale Multi-GPU Parallel Computing based Regional Scale Traffic Simulation Framework (LPSim), which leverages graphical processing unit (GPU) parallel computing to address these challenges. LPSim utilizes a multi-GPU architecture to simulate extensive and dynamic traffic networks with high fidelity and reduced computation time. Using the parallel processing capabilities of GPUs, LPSim can perform tens of millions of individual vehicle dynamics simulations simultaneously, significantly outperforming traditional CPU-based approaches. The framework is designed to be scalable and can easily accommodate the increasing complexity of traffic simulations. We present the theory behind GPU-based traffic simulation, the architecture of single- and multi-GPU based simulations, and the graph partition strategies that enhance computation resource load balance. Our experimental results demonstrate the effectiveness of LPSim in simulating large-scale traffic scenarios. LPSim is capable of completing simulations of 2.82 million trips in just 6.28 min on a single GPU machine equipped with 5120 CUDA cores (Tesla V100-SXM2). Furthermore, utilizing a Google Cloud instance with two NVIDIA V100 GPUs, which collectively offer 10240 CUDA cores, LPSim successfully simulates 9.01 million trips within 21.16 min. We further tested our simulator with the same demand on dual NVIDIA A100-PCIE-40GB GPUs, which finished the simulation in 0.0398 h, approximately 113 times faster than the same simulation scenario running on an Intel(R) Xeon(R) Gold 6326 CPU @ 2.90 GHz, which takes 4.49 h to complete. This performance not only demonstrates its speed and scalability advantages over traditional simulation techniques but also highlights LPSim’s unique position as the first traffic simulation framework that is scalable for both single- and multiple-GPU configurations. Consequently, LPSim provides an invaluable tool for individuals and extensive research teams alike, enabling the acquisition of large-scale traffic simulation results in a time-efficient manner. LPSim code is available at: https://github.com/Xuan-1998/LPSim

Sustainable groundwater regulation in typical irrigation areas of inland river basins based on ecological indicators and the MIKE-SHE hydrological model

Study regionThe study area is located in the Nukus irrigation area on the lower reaches of the Amudarya River in Uzbekistan. Study focusThe extensive agricultural land development has introduced a substantial amount of water resources into the irrigation area, leading to a significant rise in regional groundwater levels. Quantifying regional groundwater resource issues and achieving sustainable groundwater management under conditions of high spatiotemporal heterogeneity are key scientific issues for regional ecological protection. Thus, this study used the concept of ecological water level to quantify groundwater issues, used the MIKE-SHE hydrological model to conduct scenario simulations, formulated and subsequently evaluated a groundwater regulation plan with spatiotemporal attributes. New hydrological insights for the regionRegional sustainable development groundwater level should be within the range of 1.78–2.78 m. During the irrigation and non-irrigation periods, the groundwater levels in approximately 84.3 % and 72.2 % of the study area respectively exceeded the upper and lower ecological water level limits. Under the background of gradually increasing groundwater fluctuations, it will pose a serious threat to regional ecology. Therefore, this paper established a monthly-scale groundwater zoning control plan, which can make the area of regional groundwater within the ecological water level reach 87.53 %. All research not only contributes to the protection of the local ecological environment but also provides valuable insights for water resources management in other regions.

Evaluation of the effect of CYP2D6 and OCT1 polymorphisms on the pharmacokinetics of tramadol: Implications for clinical safety and dose rationale in paediatric chronic pain.

Our investigation aimed to assess the dose rationale of tramadol in paediatric patients considering the effect of CYP2D6/OCT1 polymorphisms on systemic exposure. Recommendations were made for the oral dose of tramadol to be used in a prospective study in children (3months to < 18 years old) with chronic pain. Intravenous pharmacokinetic and genotype data from neonatal patients (n = 46) were available for this analysis. The time course of tramadol and O-desmethyltramadol (M1) concentrations was characterized using a nonlinear mixed effects approach in conjunction with extrapolation principles. Clinical trial simulations were then implemented to explore the effects of polymorphism, maturation and developmental growth on the disposition of tramadol and M1. Reported efficacious exposure range in adult subjects were used as reference. The pharmacokinetics of tramadol and M1 was characterized by a two-compartment model. The total clearance of tramadol (CLPP) comprised CYP2D6-mediated metabolism (CLPM) and other pathways (CLPO). Age-related changes in CLPM, CLPO and M1 clearance (CLMO) were described by a sigmoid function, with CYP2D6 as a covariate on CLPP and CLPM, and OCT1 on CLMO. Simulation scenarios includingdifferent CYP2D6/OCT1 combinations revealed that steady-state concentrations are above the putative ranges for analgesia in >15% and >70% of subjects after doses of 3 and 8mg/kg, respectively. In the absence of genotyping, reference exposure ranges can be used to define the dose rationale for tramadol in paediatric chronic pain. However, a starting dose of 0.5mg/kg/day should be considered, followed by stepwise titration to the desired analgesic response.

Online Unmanned Ground Vehicle Path Planning Based on Multi-Attribute Intelligent Reinforcement Learning for Mine Search and Rescue

Aiming to improve the efficiency of the online process in path planning, a novel searching method is proposed based on environmental information analysis. Firstly, a search and rescue (SAR) environmental model and an unmanned ground vehicle (UGV) motion model are established according to the characteristics of a mining environment. Secondly, an online search area path-planning method is proposed based on the gray system theory and the reinforcement learning theory to handle multiple constraints. By adopting the multi-attribute intelligent (MAI) gray decision process, the action selection decision can be dynamically adjusted based on the current environment, ensuring the stable convergence of the model. Finally, experimental verification is conducted in different small-scale mine SAR simulation scenarios. The experimental results show that the proposed search planning method can capture the target in the search area with a smoother convergence effect and a shorter path length than other path-planning algorithms.