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INTRODUCTION: Fluoroscopic guided procedures are a mainstay for Interventional Radiology (IR) procedures. Practice is needed for the novice to interpret fluoroscopic images and simultaneously perform the procedure hands-on as well as control the foot pedal to screen. We describe the development of a training simulation model which simulates the human kidney, ureter and bladder. METHOD: Stereolithography (SLA) 3D Print technology using SLA resin and Anycubic SLA printer were employed. A plastic tubing was used to connect the 3D printed kidney and bladder as the ureter. This simulation model permits fluoroscopic guided filling of "pelvicalyceal system" with contrast as well as ureteric stenting, guidewire and drainage catheter manipulation. Effectiveness of the model to attain skills for nephrostomy exchange and ureteric stenting was obtained via questionnaire from trainees prior to and after utilising the model. RESULT: The 3D printing simulation model of the kidney, ureter and bladder system enable trainees to perform nephrostomy exchange, nephrostogram and antegrade stenting. Participants felt more confident to perform the procedures as they were more familiar with the procedure. Besides that, participants felt their wire and catheter manipulation skills have improved after using the simulation model. CONCLUSION: Neph-ex simulation model is safe and effective for hands-on training in improving proficiency of fluoroscopy-guided nephrostomy exchange and antegrade ureteric stenting.

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INTRODUCTION: Chemical mass casualty incidents (MCIs) pose a substantial threat to public health and safety, with the capacity to overwhelm healthcare infrastructure and create societal disorder. Computer simulation systems are becoming an established mechanism to validate these plans due to their versatility, cost-effectiveness and lower susceptibility to ethical problems. METHODS: We created a computer simulation model of an urban subway sarin attack analogous to the 1995 Tokyo sarin incident. We created and combined evacuation, dispersion and victim models with the SIMEDIS computer simulator. We analyzed the effect of several possible approaches such as evacuation policy ('Scoop and Run' vs. 'Stay and Play'), three strategies (on-site decontamination and stabilization, off-site decontamination and stabilization, and on-site stabilization with off-site decontamination), preliminary triage, victim distribution methods, transport supervision skill level, and the effect of search and rescue capacity. RESULTS: Only evacuation policy, strategy and preliminary triage show significant effects on mortality. The total average mortality ranges from 14.7 deaths in the combination of off-site decontamination and Scoop and Run policy with pretriage, to 24 in the combination of onsite decontamination with the Stay and Play and no pretriage. CONCLUSION: Our findings suggest that in a simulated urban chemical MCI, a Stay and Play approach with on-site decontamination will lead to worse outcomes than a Scoop and Run approach with hospital-based decontamination. Quick transport of victims in combination with on-site antidote administration has the potential to save the most lives, due to faster hospital arrival for definitive care.

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Assessing the concentrations of various chemicals in river water is critical for ensuring global environmental sustainability. There is an increasing need to assess water risks in southeast Asia due to the increasing chemical pollution associated with the rapid economic growth and abnormal weather. Although AIST-SHANEL, a model for analyzing chemical concentrations in river water based on the characteristics of individual rivers and meteorological conditions, is useful for assessing the water risks, this model currently only applies to Japanese rivers due to the lack of global data. To facilitate the high-spatio-temporal-resolution exposure assessment for aquatic organisms systems in southeast Asia, we built a Global-SHANEL Asia model (expanded model of the AIST-SHANEL) by collecting and processing open geospatial and meteorological data in Asia. Estimated river flow rates and concentrations of linear alkyl benzenesulfonic acid (LAS) were compared to measured values. Our model precisely estimated the seasonal variation of flow rates related to weather changes and predicted LAS concentrations at a practical level (within one order of magnitude). The model visualizes the overall distribution of LAS concentrations in southeast Asia and identifies hotspots where chemical concentrations could increase. The model visualizes the chemical distribution across countries to facilitate risk assessments for chemical pollution in future climate change and population projections. The model identifies chemical pollution and aids decision-making to promote environmental sustainability.

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BACKGROUND: Junior OB/GYN residents lack opportunities for fundamental surgical skills training of cesarean section, and most OB/GYN residents lack the experience of cervical laceration suturing due to its low incidence. METHODS: A porcine stomach simulation model was designed for obstetrics surgical training. The surface of the stomach simulated the uterus, and the pylorus and cardia simulated the cervical canal. EXPERIENCE: Materials are available from the nearby market. The total cost of the model isï¿¥41. This model can be used in the training in uterus incision and repair of cesarean section and training in cervical laceration suturing. CONCLUSION: The porcine stomach simulation model is pragmatic and realistic. They can be applied in the OB/GYN skill courses to introduce the fundamental obstetrics process to medical students and residents.

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The operation of modern wastewater treatment facilities is a balancing act in which a multitude of variables are controlled to achieve a wide range of objectives, many of which are conflicting. This is especially true within secondary activated sludge systems, where significant research and industry effort has been devoted to advance control optimization strategies, both domain-driven and data-driven. Among data-driven control strategies, reinforcement learning (RL) stands out for its ability to achieve better than human performance in complex environments. While RL has been applied to activated sludge process optimization in existing literature, these applications are typically limited in scope, and never for the control of more than three actions. Expanding the scope of RL control has the potential to increase the optimization potential while concurrently reducing the number of control systems that must be tuned and maintained by operations staff. This study examined several facets of the implementation of multi-action, multi-objective RL agents, namely how many actions a single agent could successfully control and what extent of environment data was necessary to train such agents. This study observed improved control optimization with increasing action scope, though control of waste activated sludge remains a challenge. Furthermore, agents were able to maintain a high level of performance under decreased observation scope, up to a point. When compared to baseline control of the Benchmark Simulation Model No. 1 (BSM1), an RL agent controlling seven individual actions improved the average BSM1 performance metric by 8.3 %, equivalent to an annual cost savings of $40,200 after accounting for the cost of additional sensors.

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Contamination of fresh produce with Listeria monocytogenes can occur throughout the supply chain, including at retail, where Listeria spp., including L. monocytogenes, may be introduced and spread via various routes. However, limited tools are available for retailers to assess practices that can enhance control of Listeria transmission to fresh produce. Therefore, we developed an agent-based model that can simulate Listeria transmission in retail produce sections to optimize environmental sampling programs and evaluate control strategies. A single retail store was used as a model environment, in which various routes of Listeria introduction into and transmission between environmental surfaces were modeled. Model prediction (i.e., Listeria prevalence) was validated using a published longitudinal study for all surfaces that were included in both the model and the validation data. Sensitivity analysis using the Partial Rank Correlation Coefficient showed that (i) initial Listeria concentration from incoming produce, (ii) transfer coefficient from produce to employee's hands, and (iii) transfer coefficient from consumer to produce were the top three parameters that were significantly (p < 0.0018) associated with the mean Listeria prevalence across all agents, suggesting that the accuracy of these parameters are important for prediction of overall Listeria prevalence at retail. Cluster analysis grouped agents with similar contamination patterns into six unique clusters; this information can be used to optimize the sampling plans for retail environments. Scenario analysis suggested that (i) more stringent supplier control as well as (ii) practices reducing Listeria transmission via consumer's hands may have the largest impact on reducing finished product contamination. Overall, we show that an agent-based model can serve as a foundational tool to help with decision-making on Listeria control strategies at retail.

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INTRODUCTION: Cost-effectiveness analyses typically ignore healthcare system resource constraints. Ophthalmology is affected by resource constraints because of increasing disease prevalence and the use of resource-intensive treatments. This study evaluated the impact of resource constraints on the cost-effectiveness of faricimab 6 mg, compared with aflibercept 2 mg and ranibizumab biosimilar 0.5 mg, for treating wet age-related macular degeneration (wAMD) or diabetic macular oedema (DMO) over a 5-year horizon. METHODS: A microsimulation model estimated the impact of resource constraints on patients visits, delays, costs and quality-adjusted life-year (QALY) losses due to treatment delays at a typical UK National Health Service eye hospital treating 1500 patients with wAMD and 500 patients with DMO. Patient characteristics, treatment regimens and treatment intervals were informed using published literature and expert opinion. Resource constraint was represented by limiting the number of available intravitreal injection appointments per week, with growing demand caused by rising disease prevalence. The model compared outcomes across three scenarios; each scenario involved treating all patients with one of the three treatments. RESULTS: Over 5 years, in a resource-constrained hospital, compared with aflibercept, faricimab use resulted in the avoidance of 12,596 delays, saved GBP/£15,108,609 in cost and avoided the loss of 60.06 QALYs. Compared with ranibizumab biosimilar, faricimab use resulted in the avoidance of 18,910 delays, incurred £2,069,088 extra cost and avoided the loss of 105.70 QALYs, resulting in an incremental cost-effectiveness ratio of £19,574/QALY. CONCLUSIONS: Accounting for resource constraints in health economic evaluation is crucial. Emerging therapies that are more durable and require less frequent clinic visits can reduce treatment delays, leading to improved QALY outcomes and reduced burden on healthcare systems. Faricimab reduced the number of delayed injections, leading to improved QALY outcomes for patients in a healthcare system with resource constraints. Faricimab is cost-saving when compared with aflibercept and cost-effective when compared with ranibizumab biosimilar.

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CO2 laser machining is a cost effective and time saving solution for fabricating microchannels on polymethylmethacrylate (PMMA). Due to the lack of research on the incubation effect and ablation behavior of PMMA under high-power laser irradiation, predictions of the microchannel profile are limited. In this study, the ablation process and mechanism of a continuous CO2 laser machining process on microchannel production in PMMA in single-pass and multi-pass laser scan modes are investigated. It is found that a higher laser energy density of a single pass causes a lower ablation threshold. The ablated surface can be divided into three regions: the ablation zone, the incubation zone, and the virgin zone. The PMMA ablation process is mainly attributed to the thermal decomposition reactions and the splashing of molten polymer. The depth, width, aspect ratio, volume ablation rate, and mass ablation rate of the channel increase as the laser scanning speed decreases and the number of laser scans increases. The differences in ablation results obtained under the same total laser energy density using different scan modes are attributed to the incubation effect, which is caused by the thermal deposition of laser energy in the polymer. Finally, an optimized simulation model that is used to solve the problem of a channel width greater than spot diameter is proposed. The error percentage between the experimental and simulation results varies from 0.44% to 5.9%.

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BACKGROUND: Injection-equipment-sharing networks play an important role in hepatitis C virus (HCV) transmission among people who inject drugs (PWID). Direct-acting antiviral (DAA) treatments for HCV infection and interventions to prevent HCV transmission are critical components of an overall hepatitis C elimination strategy, but how they contribute to the elimination outcomes in different PWID network settings are unclear. METHODS: We developed an agent-based network model of HCV transmission through the sharing of injection equipment among PWID and parameterized and calibrated the model with rural PWID data in the United States. We modeled curative and preventive interventions at annual coverage levels of 12.5 %, 25 %, or 37.5 % (cumulative percentage of eligible individuals engaged), and two allocation approaches: random vs targeting PWID with more injection partners (hereafter 'degree-based'). We compared the impact of these intervention strategies on prevalence and incidence of HCV infections. We conducted sensitivity analysis on key parameters governing the effects of curative and preventive interventions and PWID network characteristics. RESULTS: Combining curative and preventive interventions at 37.5 % annual coverage with degree-based allocation decreased prevalence and incidence of HCV infection by 67 % and 70 % over two years, respectively. Curative interventions decreased prevalence by six to 12 times more than preventive interventions, while curative and preventive interventions had comparable effectiveness on reducing incidence. Intervention impact increased with coverage almost linearly across all intervention strategies, and degree-based allocation was always more effective than random allocation, especially for preventive interventions. Results were sensitive to parameter values defining intervention effects and network mean degree. CONCLUSION: DAA treatments are effective in reducing both prevalence and incidence of HCV infection in PWID, but preventive interventions play a significant role in reducing incidence when intervention coverage is low. Increasing coverage, including efforts in reaching individuals with the most injection partners, preventing reinfection, and improving compliance and retention in preventive services can substantially improve the outcomes. PWID network characteristics should be considered when designing hepatitis C elimination programs.

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Risk index tools have the potential to assist farmers in making strategic decisions regarding their farm design to manage losses of nutrients. Such tools require a vulnerability framework, and these are often based on scores or rankings. These frameworks struggle to take account of interactions between elements of the physical environment. Process-based simulation models inherently take account of interactions and may be a viable alternative to score-based methods. We describe the method to populate a database of transport factors that covers the agricultural lands of New Zealand that is designed for usage as the susceptibility framework within a risk index tool. The method gives both leaching and runoff transport factors and gives values by month. The simulation model used had already been validated for simulating water and nitrogen balances and the generated spatial patterns of the transport factors was validated via expert assessment. These features allow good representation of the risks posed across a wide range of farming activities.•Use of a simulation model to quantify transport factors.•Captures the interactions between soil and weather factors in the physical environment.•Produces a country-wide database intended as a susceptibility framework for a risk index tool.

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PURPOSE: To study the published literature for various models used for simulation and training in the field of pediatric colorectal surgery. METHOD: A PubMed search was conducted for studies of simulation models in anorectal malformation on 24 March 2024 with the search words 'simulation pediatric colorectal surgery' followed by another search on 'simulation AND anorectal malformation' that gave 22 and 14 results, respectively (total 36). After removing 4 duplicate publications, 12 were found relevant to simulation and training in colorectal diseases. One publication relevant to the topic was added from literature, thirteen articles were studied. RESULTS: Of these, 5; 1; 4; and 3 were on inanimate models; animate model; 3D reconstructions; and training, respectively. Simulation models are available for posterior sagittal anorectoplasty. The same inanimate model was used in five articles. The animate model was based on a chicken cadaver. 3D models have been made for personalized preoperative assessment and to understand the imaging in anorectal malformation. One 3D model was made by regeneration of organoid epithelium. Training modules were made to evaluate surgical dissection, standardize surgical techniques, and improve proficiency. CONCLUSION: Simulation models are an important tool for teaching the steps of surgery and discussing the nuances of operative complications among mentors and peers. With advances in this field, the development of high-fidelity models, more training modules, and consensus on surgical techniques will benefit surgical training.

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With recent outbreaks of foot-and-mouth disease (FMD) in Indonesia and Bali, industry, government and public concern for its incursion into Australia is increasing. The potential impact of an outbreak on the agricultural industry and national economy could be devastating. To date, research conducted in relation to FMD in Australia predominantly concerns simulations and models performed to predict various outcomes. This project critically appraises the current literature regarding the simulated use of vaccination and its effectiveness for controlling the spread of FMD in Australia in the event of an outbreak. Findings from 10 modelling studies suggest that vaccination is effective at controlling the size and duration of an outbreak (under certain conditions), however, there is less clarity about cost-effectiveness.

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Climate change, with warming and drying weather conditions, is reducing the growth, seed production, and survival of fire-adapted plants in fire-prone regions such as Mediterranean-type ecosystems. These effects of climate change on local plant demographics have recently been shown to reduce the persistence time of local populations of the fire-killed shrub Banksia hookeriana dramatically. In principle, extinctions of local populations may be partly compensated by recolonization events through long-distance dispersal mechanisms of seeds, such as post-fire wind and bird-mediated dispersal, facilitating persistence in spatially structured metapopulations. However, to what degree and under which assumptions metapopulation dynamics might compensate for the drastically increased local extinction risk remains to be explored. Given the long timespans involved and the complexity of interwoven local and regional processes, mechanistic, process-based models are one of the most suitable approaches to systematically explore the potential role of metapopulation dynamics and its underlying ecological assumptions for fire-prone ecosystems. Here we extend a recent mechanistic, process-based, spatially implicit population model for the well-studied fire-killed and serotinous shrub species B. hookeriana to a spatially explicit metapopulation model. We systematically tested the effects of different ecological processes and assumptions on metapopulation dynamics under past (1988-2002) and current (2003-2017) climatic conditions, including (i) effects of different spatio-temporal fires, (ii) effects of (likely) reduced intraspecific plant competition under current conditions and (iii) effects of variation in plant performance among and within patches. In general, metapopulation dynamics had the potential to increase the overall regional persistence of B. hookeriana. However, increased population persistence only occurred under specific optimistic assumptions. In both climate scenarios, the highest persistence occurred with larger fires and intermediate to long inter-fire intervals. The assumption of lower intraspecific plant competition caused by lower densities under current conditions alone was not sufficient to increase persistence significantly. To achieve long-term persistence (defined as >400 years) it was necessary to additionally consider empirically observed variation in plant performance among and within patches, that is, improved habitat quality in some large habitat patches (≥7) that could function as source patches and a higher survival rate and seed production for a subset of plants, specifically the top 25% of flower producers based on current climate conditions monitoring data. Our model results demonstrate that the impacts of ongoing climate change on plant demographics are so severe that even under optimistic assumptions, the existing metapopulation dynamics shift to an unstable source-sink dynamic state. Based on our findings, we recommend increased research efforts to understand the consequences of intraspecific trait variation on plant demographics, emphasizing the variation of individual traits both among and within populations. From a conservation perspective, we encourage fire and land managers to revise their prescribed fire plans, which are typically short interval, small fires, as they conflict with the ecologically appropriate spatio-temporal fire regime for B. hookeriana, and likely as well for many other fire-killed species.

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To address the requirements of sonar imaging, such as high receiving sensitivity, a wide bandwidth, and a wide receiving angle, an AlN PMUT with an optimized ratio of 0.6 for the piezoelectric layer diameter to backside cavity diameter is proposed in this paper. A sample AlN PMUT is designed and fabricated with the SOI substrate-based bulk MEMS process. The characterization test result of the sample demonstrates a -6 dB bandwidth of approximately 500 kHz and a measured receiving sensitivity per unit area of 1.37 V/µPa/mm2, which significantly surpasses the performance of previously reported PMUTs. The -6 dB horizontal angles of the AlN PMUT at 300 kHz and 500 kHz are measured as 68.30° and 54.24°, respectively. To achieve an accurate prediction of its characteristics when being packaged and assembled in a receive array, numerical simulations with the consideration of film stress are conducted. The numerical result shows a maximum deviation of ±7% in the underwater receiving sensitivity across the frequency range of 200 kHz to 1000 kHz and a deviation of about 0.33% in the peak of underwater receiving sensitivity compared to the experimental data. By such good agreement, the simulation method reveals its capability of providing theoretical foundation for enhancing the uniformity of AlN PMUTs in future studies.

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Since conventional PID (Proportional-Integral-Derivative) controllers hardly control the robot to stabilize for constant force grinding under changing environmental conditions, it is necessary to add a compensation term to conventional PID controllers. An optimal parameter finding algorithm based on SAC (Soft-Actor-Critic) is proposed to solve the problem that the compensation term parameters are difficult to obtain, including training state action and normalization preprocessing, reward function design, and targeted deep neural network design. The algorithm is used to find the optimal controller compensation term parameters and applied to the PID controller to complete the compensation through the inverse kinematics of the robot to achieve constant force grinding control. To verify the algorithm's feasibility, a simulation model of a grinding robot with sensible force information is established, and the simulation results show that the controller trained with the algorithm can achieve constant force grinding of the robot. Finally, the robot constant force grinding experimental system platform is built for testing, which verifies the control effect of the optimal parameter finding algorithm on the robot constant force grinding and has specific environmental adaptability.

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Temperature and light are the key factors affecting the formation of tomato fruit quality in greenhouse cultivation. However, there are few simulation models that examine the relationship between tomato fruit quality formation and temperature and light. In this study, a model was established that investigated the relationships between soluble sugar (SSC), organic acid content (OAC), and SSC/OAC and the cumulative product of thermal effectiveness and photosynthetically active radiation (TEP) during the fruit-ripening period in a solar greenhouse. The root mean square error (RMSE) values were calculated to compare the consistency between the simulated and measured values, and the RMSE values for SSC, OAC, and SSC/OAC were 0.09%, 0.14%, and 0.358, respectively. The combined weights of quality indicators were obtained using the analytic hierarchy process (AHP) and entropy weighting method, ranking as SSC > OAC > SSC/OAC > CI > lycopene > Vc > fruit firmness. The comprehensive fruit quality evaluation value was obtained using the TOPSIS method (Technique for Order Preference by Similarity to an Ideal Solution) and a simulation model between comprehensive tomato fruit quality and TEP was explored. This study could accurately simulate and quantify the accumulation of tomato fruit quality during fruit ripening in response to environmental conditions in a solar greenhouse.

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To effectively reduce residual stresses in GH4169 workpieces, thus enhancing fatigue strength and operational lifespan, this study investigates the influence of spray cooling parameters on surface residual stresses during GH4169 turning in spray cooling conditions, utilizing both simulation and experimental approaches. A simulation model of residual stresses was established using finite element analysis when GH4169 was cut in spray cooling. The effects of spray pressure and flow rate on residual tensile stresses were analyzed. The analysis reveals that with increasing spray pressure, residual tensile stresses show a decreasing trend, gradually stabilizing. Conversely, with an increasing spray flow rate, residual tensile stresses initially decrease and then increase. The turning experiments of GH4169 were conducted under different spray parameters. After the experiment, the workpiece was sectioned and analyzed for residual stresses using X-ray diffraction instrumentation. The value residual stress measured closely matched those of simulation, with a relative error within 6%, validating the accuracy of the simulation model and confirming the appropriateness of parameter settings. These results contribute to the further promotion of spray cooling technology and facilitate the rational selection of spray parameters.

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PURPOSE OF THE STUDY: To elucidate the design and fabrication methodologies employed in creating a personalized cleft lip simulation model, primarily intended for enhancing surgical training and diverse applications. The study further sought to assess the viability of integrating this simulation model into undergraduate oral experiments and instructional settings. STUDY DESIGN: Facial data from individuals with cleft lip conditions were acquired using a scanner. Subsequent stages involved reverse engineering and the utilization of 3D printing technology to generate a cleft lip silicone simulation model. The molding process entailed injecting silicone into a polylactic acid mold. The study enrolled 53 undergraduate students majoring in dentistry, who were randomly assigned to either a control or experimental group. A dedicated instructor guided each group independently, employing a combination of multiple-choice tests and surveys to gauge real-time evaluations and discern inter-group disparities. RESULTS AND CONCLUSIONS: We successfully designed and produced a personalized cleft lip simulation model, demonstrating notable efficacy in the context of cleft lip experimental teaching. Statistical analysis revealed a significant difference (P < 0.05) in the scores of the experimental group students on multiple-choice questions pertaining to cleft lip surgical procedures. Survey outcomes indicated that the experimental group students exhibited higher confidence levels in cleft lip surgery, as reflected from their responses to relevant questions, compared to the traditional group students. These differences were statistically significant (P < 0.05). The simulation model developed in this study emerges as a reliable and cost-effective training and teaching tool for cleft lip surgery.

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An increasing number of countries are investigating options to stop the spread of the emerging zoonotic infection Salmonella Dublin (S. Dublin), which mainly spreads among bovines and with cattle manure. Detailed surveillance and cattle movement data from an 11-yr period in Denmark provided an opportunity to gain new knowledge for mitigation options through a combined social network and simulation modeling approach. The analysis revealed similar network trends for noninfected and infected cattle farms despite stringent cattle movement restrictions imposed on infected farms in the national control program. The strongest predictive factor for farms becoming infected was their cattle movement activities in the previous month, with twice the effect of local transmission. The simulation model indicated an endemic S. Dublin occurrence, with peaks in outbreak probabilities and sizes around observed cattle movement activities. Therefore, pre- and postmovement measures within a 1-mo time window may help reduce S. Dublin spread.

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BACKGROUND AND OBJECTIVE: Magnetic particle imaging (MPI) is an emerging imaging technology in medical tomography that utilizes the nonlinear magnetization response of superparamagnetic iron oxide (SPIO) particles to determine the in vivo spatial distribution of nanoparticle contrast agents. The reconstruction image quality of MPI is determined by the characteristics of magnetic particles, the setting of the MPI scanner parameters, and the hardware interference of MPI systems. We explore a feasible method to systematically and quickly analyze the impact of these factors on MPI reconstruction image quality. METHODS: We propose a systematic 3-D MPI simulation model. The MPI simulation model has the capability of quickly producing the simulated reconstruction images of a scanned phantom, and quantitative analysis of MPI reconstruction image quality can be achieved by comparing the differences between the input image and output image. These factors are mainly classified as imaging parameters and interference parameters in our model. In order to reduce the computational time of the simulation model, we introduce GPU parallel programming to accelerate the processing of large complex matrix data. For ease of use, we also construct a reliable, high-performance, and open-source 3-D MPI simulation software tool based on our model. The efficiency of our model is evaluated by using OpenMPIData. To demonstrate the capabilities of our model, we conduct simulation experiments using parameters consistent with a real MPI scanner for improving MPI image quality. RESULTS: The experimental results show that our simulation model can systematically and quickly evaluate the impact of imaging parameters and interference parameters on MPI reconstruction image quality. CONCLUSIONS: We developed an easy-to-use and open-source 3-D MPI simulation software tool based on our simulation model incorporating all the stages of MPI formation, from signal acquisition to image reconstruction. In the future, our simulation model has potential guiding significance to practical MPI images.

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