Operational Support Research Articles

Existing operational standards for field deployments of rapid response mobile laboratories: a scoping review

IntroductionRapid response mobile laboratories (RRML) play an important role in responding to emergencies such as outbreaks and humanitarian crises, working in coordination with national authorities. This scoping review aims to provide evidence to support the development of minimum operational standards for the deployment of RRMLs across the five key workstreams: operational support and logistics, biosafety and biosecurity, laboratory information management system, quality management systems and interoperability and coordination.MethodsWe searched PubMed, MEDLINE, EMBASE and the grey literature focusing on RRML deployment missions. Study characteristics such as year, country, objectives, methods, and findings were extracted and summarized to identify common themes, gaps, and patterns. The results were presented in a narrative format. We ensured methodological rigor by following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines throughout the review process.ResultsOut of 163 full-text studies assessed for eligibility, 46 met the inclusion criteria and were analyzed. Six studies addressed the five RRML workstreams. Operational support and logistics are most commonly addressed during pre-deployment phases with a focus on personnel, transport and cold chain management. The application of biosafety and biosecurity protocols is most addressed during the mission execution phase, particularly in the use of personal protective equipment and the implementation of decontamination and disinfection procedures. The laboratory information management system procedures most frequently reported include sample identification and result dissemination protocols. The quality management system workstream overlaps significantly with the other four workstreams, with a strong emphasis on internal and external quality assurance measures. Coordination and interoperability aspects involve maintaining multiple collaborations, ranging from coordinating with local authorities to establishing international partnerships. Common field challenges included interrupted data transfer in areas characterized by poor connectivity and difficulties caused by extreme weather conditions.DiscussionThis review highlights RRML deployment procedures and addresses some critical challenges concerning their deployment. It suggests the provision of a pre-deployment logistics checklist, the use of a pre-determined standardized dataset for inputs to reduce data entry errors and the application of standardized internal and external quality assurance measures.

THE PRIMARY ISSUES WITH THE DEVELOPMENT OF ENTREPRENEURIAL ACTIVITIES IN THE RA SERVICES SECTOR

Maintenance services play a significant part in the RA economy and come in third place in terms of GDP formation, after industry and agriculture. Additionally, the country has seen an unparalleled expansion in service delivery in recent years, which creates significant difficulties for the management of commercial operations in the sector. In this context, it is critical to draw attention to the current issues with business operations pertaining to service delivery and offer solutions, which have been discussed in the article. Particularly noteworthy are the insightful remarks made in the essay regarding RA-served solutions to issues pertaining to the sustainable development of services. Proposals were also made for the creation of high-caliber human resources and the innovative support of company operations, which creates prospects for the provision of services that meet international competitive standards.

Legal regulation of state and international aid in Ukraine during marital state: challenges for the economy and military production

The article analyzes the legal regulation of state and international aid in Ukraine under martial law starting from March 2022. During the Russian aggression against Ukraine, the system of state and international aid underwent significant transformations. In the conditions of military aggression, compliance with the standard rules for the provision of aid has become almost impossible. Immediately after the start of active hostilities, the Antimonopoly Committee of Ukraine decided to suspend the implementation of the rules regulating state aid. This decision was formalized on 03/07/2022 and provided for the temporary suspension of consideration of new aid notifications, changes to already existing programs, as well as complaints and applications related to state aid. On March 15, 2022, the Verkhovna Rada of Ukraine, in turn, adopted legislative changes that effectively abolished the system of control over state aid during martial law. This decision made it possible to quickly respond to economic challenges without waiting for lengthy administrative procedures. Assistance provided during martial law is automatically considered compatible with applicable law, and providers are exempt from reporting such programs. However, it is important to note that these are temporary measures that were adopted to provide operational support to the economy. The European Union has also adapted its aid rules to support economic sectors affected by the war in Ukraine. The European Commission made changes to the Temporary Crisis Framework, which simplified the provision of aid in the member states of the European Union. Ukraine aims to meet these standards in the future, which has become a key part of its European integration aspirations. While the suspension of aid poses potential risks to the long-term development of the economy, it also opens up opportunities for reform. As early as June 2022, the Ukrainian government adopted a plan to improve aid mechanisms aimed at adapting to European standards. This is an important step on the way to full integration of Ukraine into the legal system of the European Union. To date, the Government of Ukraine and the Antimonopoly Committee of Ukraine continue to work on improving the legislative framework in the field of state and international aid. The new plan, approved by the government, provides for the creation of criteria for assessing the compatibility of state and international aid, monitoring of existing programs and measures to improve aid control. Special attention is paid to the harmonization of legislation with the norms of the European Union, which is provided for by the Association Agreement. Gaps in the current legislation, discovered during martial law, should be used as an incentive to build a sustainable system that will meet European requirements. Despite the difficult circumstances of the war, Ukraine continues to move towards the implementation of European standards in the field of aid, which is an important part of preparations for joining the European Union. The task of the Government of Ukraine and the Antimonopoly Committee of Ukraine is to achieve significant results in this direction by 2025. This will give Ukraine the opportunity not only to restore the economy after the war, but also to ensure the stability of the state support system in the future.

Research on Closed-Loop Control of Screen-Based Guidance Operations in High-Speed Railway Passenger Stations Based on Visual Detection Model

Due to adjustments to the operation plan of guided trains at high-speed railway stations, a large amount of information is inevitably displayed, sometimes with delays, omissions, and misalignments. The effective management of guidance information can provide important support for the personnel flow operation of high-speed railway stations. Aiming to meet the requirements of high real-time and high accuracy of guided job control, a closed-loop control method based on a guided job is proposed, which provides enhanced text detection and recognition in a target area. Firstly, using the introduction of the triplet attention mechanism in YOLOv5 and the addition of fusion modules, the feature pyramid network is used to enhance the effective feature and feature interactions between the modules to improve the detection speed of the display. Then, the text on the guide screen is recognized and extracted in combination with the PaddleOCR model, and then, the results are proofread against the original plan to adjust the screen information. Finally, the effectiveness and feasibility of the method are verified by experimental data, with the accuracy of the improved model reaching 90.6% and the speed reaching 1 ms, which meets the requirement of real-time closed-loop control of Screen-Based Guidance Operations.

Forecasts of Video Game Sales based on the ARIMA Model

Abstract. With the rapid development of the digital age, video games have become an important component of the cultural industry, and their sales forecasting has become a focus of industry attention. This article aims to predict the sales of video games based on the ARIMA model and explore effective methods to improve prediction accuracy. Through in-depth research, this article found that the ARIMA model performs well in capturing the time series characteristics of sales data and can accurately predict future sales trends. The ARIMA model provides a systematic and scientific method for predicting the future market performance of video games by comprehensively considering the trends, seasonality, and random changes in historical sales data. This research achievement not only provides strong decision support for game developers, publishers, and platform operators but also promotes the optimization of resource allocation and market risk avoidance in the video games industry, which is of great significance for promoting the healthy and sustainable development of the industry.

Operation of Photoeelectron Spectrometers for Non-Invasive Photon Diagnostics at the European X-Ray Free Electron Laser

Angle-resolved photoelectron spectrometers with microchannel plate detectors and fast digitizer electronics are versatile and powerful devices for providing non-invasive single-shot photon diagnostics at a MHz repetition rate X-ray free-electron lasers. In this contribution, we demonstrate and characterize the performance of our two operational photoelectron spectrometers for the application of hard X-rays and soft X-rays as well as new automation tools and online data analysis that enable continuous support for machine operators and instrument scientists. Customized software has been developed for the real-time monitoring of photon beam polarization and spectral distribution both in single-color and two-color operation. Hard X-ray operation imposes specific design challenges due to poor photoionization cross-sections and very high photoelectron velocities. Furthermore, recent advancements in machine learning enable resolution enhancement by training the photoelectron spectrometer together with an invasive high-resolution spectrometer, which generates a response function model.

Movement Characteristics of Droplet Deposition in Flat Spray Nozzle for Agricultural UAVs

At present, research on aerial spraying operations with UAVs mainly focuses on the deposition outcomes of droplets, with insufficient depth in the exploration of the movement process of droplet deposition. The movement characteristics of droplet deposition as the most fundamental factors affecting the effectiveness of pesticide application by UAVs are of great significance for improving droplet deposition. This study takes flat spray nozzles as the research object, uses the Particle Image Velocimetry (PIV) technique to obtain movement data of water droplet deposition under the influence of rotor flow fields, and investigates the variation characteristics of droplet deposition speed under different influencing factors. The results show that the deposition speed and the distribution area of high-speed (>12 m/s) particles increase with the increase of rotor speed, spraying pressure, and nozzle size. When the rotor speed increases from 0 r/min to 1800 r/min, the average increase in maximum droplet deposition speed for nozzle models LU120-02, LU120-03 and LU120-04 is 33.26%, 19.02%, and 7.62%, respectively. The rotor flow field significantly increases the number of high-speed droplets, making the dispersed droplet velocity distribution more concentrated. When the rotor speed is 0, 1000, 1500, and 1800 r/min, the average decay rates of droplet deposition speed are 36.72%, 20.00%, 15.47%, and 13.21%, respectively, indicating that the rotor flow field helps to reduce the decrease in droplet deposition speed, enabling droplets to deposit on the target area at a higher speed, reducing drift risk and evaporation loss. This study’s results are beneficial for revealing the mechanism of droplet deposition movement in aerial spraying by plant protection UAVs, improving the understanding of droplet movement, and providing data support and guidance for precise spraying operations.

Construction of a Joint Newmark–Runout Model for Seismic Landslide Risk Identification: A Case Study in the Eastern Tibetan Plateau

The key to seismic landslide risk identification resides in the accurate evaluation of seismic landslide hazards. The traditional evaluation models for seismic landslide hazard seldom consider the landslide dynamic runout process, leading to an underestimation of seismic landslide hazard. Therefore, a joint Newmark–Runout model based on landslide dynamic runout is proposed. According to the evaluation results of static seismic landslide hazard, the landslide source points can be extracted, and the landslide dynamic runout process is simulated to obtain the dynamic seismic landslide hazard. Finally, the static and dynamic seismic landslide hazards are fused to obtain an optimized seismic landslide hazard. In September 2022, a strong Ms6.8 earthquake occurred in the eastern Tibetan Plateau, triggering thousands of landslides. Taking the 2022 Luding earthquake-induced landslide as a sample, the function relationship between seismic slope displacement and landslide occurrence probability is statistically modeled, which partly improves the traditional Newmark model. The optimized seismic landslide hazard evaluation of the Luding earthquake area is conducted, and then, the seismic landslide risk identification is completed by taking roads and buildings as hazard-affected bodies. The results show that the length of the roads facing very high and high seismic landslide risks are 3.36 km and 15.66 km, respectively, and the buildings on the Moxi platform near the epicenter are less vulnerable to seismic landslides. The research findings can furnish critical scientific and technological support for swift earthquake relief operations.

Multi-objective optimization and multi-attribute decision-making support for optimal operation of multi stakeholder integrated energy systems

To efficiently tackle the optimal operation problem of multi-stakeholder integrated energy systems (IESs), this paper develops a multi-objective optimization and multi-attribute decision-making support method. Mathematically, The optimal operation of IESs interconnected with distributed district heating and cooling units (DHCs) via the power grid and gas network, can be formulated as a multi-objective optimization problem considering both economic, reliability and environment-friendly objectives with numerous constraints of each energy stakeholder. Firstly, a multi-objective group search optimizer with probabilistic operator and chaotic local search (MPGSO) is proposed to balance global and local optimality during the random search iteration. The MPGSO utilizes a crowding probabilistic operator to select producers to explore areas with higher potential but less crowding and reduce the number of fitness function calculations. Moreover, a new parameter selection strategy based on chaotic sequences with limited computational complexity is adopted to escape the local optimal solutions. Consequently, a set of superior Pareto-optimal fronts could be obtained by the MPGSO. Subsequently, a multi-attribute decision-making support method based on the interval evidential reasoning (IER) approach is used to determine a final optimal solution from the Pareto-optimal solutions, taking multiple attributes of each stakeholder into consideration. To verify the effectiveness of the MPGSO, the DTLZ suite of benchmark problems are tested compared with the original GSOMP, NSGA-II and SPEA2. Additionally, simulation studies are conducted on a modified IEEE 30-bus system connected with distributed DHCs and a 15-node gas network to verify the proposed approch. The quality of the obtained Pareto-optimal solutions is assessed using a set of criteria, including hypervolume (HV), generational distance (GD), and Spacing index, among others. Simulation results show that the number of Pareto-optimal solutions (NPS) of MPGSO are higher by about 32.6 %-62.1%, computation time (CT) are lower by about 2.94 %-46.1 % compared with other algorithms. Besides, to further evaluate the performance of the proposed approach in addressing larger-scale issues, the study employs the modified IEEE 118-bus system of greater magnitude. The proposed MPGSO algorithm effectively handles multi-objective and non-convex optimization problems with Pareto sets in terms of better convergence and distributivity.

Short-term inbound passenger flow prediction at high-speed railway stations considering the departure passenger arrival pattern

Accurate prediction of short-term inbound passenger flow at high-speed railway stations is of great significance for the refined operation of stations, the formulation of emergency plans, and the provision of intelligent services. The arrival of passengers traveling on the same train at the same station shows a similar pattern, which is called the departure passenger arrival pattern (DPAP). The short-term inbound passenger flow at the station is composed of the short-term inbound passenger flow of all waiting trains within the same period. Inspired by this, this paper develops an ensemble prediction model based on the time series decomposition modeling strategy to introduce the DPAP to the short-term inbound passenger flow prediction at stations. Firstly, we propose a new framework for studying the DPAP to calculate the fitted station short-term inbound passenger flow, which is only affected by the DPAP. During this process, we find that 7minutes is the optimal time granularity. Secondly, based on the singular spectrum analysis, we prove that the DPAP is the determining factor affecting the station short-term inbound passenger flow. Finally, we propose an ensemble prediction model that considers the DPAP to achieve short-term inbound passenger flow prediction at stations. The model consists of two parts: the deterministic and stochastic components prediction, where the former is predicted by the fitted station short-term inbound passenger flow, and the latter is achieved by the combination of historical stochastic components and weather type with the help of the Seq2Seq model based on time attention mechanism. Using real inbound passenger flow data, we compare the proposed model with 13 benchmark models and the results show that under different training and prediction steps, our model achieves optimal prediction performance, whether in all-day period and the busiest period of the station. Through further ablation experiments, it has been proven that the introduction of the DPAP effectively improves the prediction accuracy. Our model can provide scientific support for the intelligent operation of stations and the refined management of passenger flow.

Refined transmission line ice-cover prediction model and optimization study

Abstract This study aims to develop a fine-grained transmission line ice-cover prediction model and conduct an optimization study. Ice cover is one of the important factors leading to transmission line accidents, so accurately predicting the ice cover of transmission lines is crucial to ensure the safe operation of power grids. In this paper, an efficient ice-cover prediction model is constructed based on advanced machine learning algorithms and optimization methods and is validated and optimized with a large amount of experimental data. The results show that the proposed model has high accuracy and prediction capability in ice cover prediction, which provides important support for the safe operation of transmission lines.

Analysis of Information Technology Governance in the Transportation Agency using the Cobit 4.1 Framework

Information technology plays a role in supporting the goals of companies and government agencies by providing a fast, easy and accurate information and communication platform, increasing the effectiveness and efficiency of the planning process, and supporting innovation in companies and government agencies to develop. The existence of Information Technology has experienced development and the relationship between its operational roles in running an organization, where it is not only as a support for operations. Research was conducted at the Transportation Agency which concluded that the old system used was ineffective because the process carried out took time and space, making employee performance less efficient. After searching for data at the Transportation Agency by collecting data, it can be concluded that the information system used is still not optimal. Therefore, a system design was carried out. The results of the analysis were applied to a cobit system application program. After the research was conducted, the results of the calculation of the maturity model level obtained an average index of 3.16 ( Level 3). This means that the system. The new information system designed is expected to improve the quality of information and performance in the future

Comparison Performance Analysis of HDD, SSD and NVME for OLTP Database Server

Databases are an essential component of life in modern society. The database has become an online Transaction Processing (OLTP) operational support company. This study discusses the storage configuration in a virtual server database for OLTP Database with a benchmark against three storage configurations for four databases: SQL Server, MySQL, PostgreSQL, and MariaDB for Windows Server virtualization. Benchmarks using TPC-C to get the best performance from all three configurations have been tested. The results of this study show that the storage configuration of HDD as a virtual disk drive OS and NVME as a virtual disk drive database get better performance as online transaction processing (OLTP) compared to HDD as a virtual disk drive OS and HDD or SSD as a virtual disk drive database. Using the TPC-C benchmark, the study tested the performance of four databases (SQL Server, MySQL, PostgreSQL, and MariaDB) in various virtual storage configurations. The results of 36 experiments involving different numbers of virtual users (10, 50, and 100) showed that a hybrid configuration that used HDDs for the operating system and NVME for database storage provided the best performance. On SQL Server, SSD configurations show better results for smaller user loads. The results suggest that the combination of HDD and NVME is the optimal configuration for most databases in OLTP tasks, and it provides useful guidance in efficient storage investment decision-making. Further research is expected to be able to conduct tests.

Inisiasi Pengolahan Air Embung dengan Teknologi Multimedia Filter (MMF) sebagai Solusi Air Bersih di Kabupaten Bojonegoro

Clean water and proper sanitation are fundamental human needs. Nganti Village, located in Ngraho Subdistrict, Bojonegoro Regency, faces significant drought and clean water shortages, particularly during the dry season. The water quality remains subpar despite the presence of springs and water reservoirs. Consequently, processing raw water from the village's reservoir can offer a viable solution. This service activity aims to harness water reservoirs as a clean water source through multimedia filter (MMF) technology. The activities, conducted from 2022 to the end of 2023, encompass four stages: socializing the program plans, constructing multimedia filters (MMF), installing the water treatment unit on-site, and evaluating water quality, followed by necessary follow-ups. The primary activities involve installing water treatment units with MMF technology in collaboration with village officials and the community. The treated water is then tested for quality at the IPB University laboratory. Test results indicate that MMF technology significantly improves water quality, reducing parameters such as Magnesium, Manganese, Calcium, Iron, and Phosphate by 25.8‒97.8%, thus meeting quality standards. However, some parameters, such as TSS, COD, and Zinc, still exceed quality standards, necessitating further processing. This advanced water treatment requires involvement from the local government, particularly in funding through community empowerment programs, to install advanced treatment units and provide operational support for these units.

An improved YOLOv8n-IRP model for natural rubber tree tapping surface detection and tapping key point positioning

Aiming at the problem that lightweight algorithm models are difficult to accurately detect and locate tapping surfaces and tapping key points in complex rubber forest environments, this paper proposes an improved YOLOv8n-IRP model based on the YOLOv8n-Pose. First, the receptive field attention mechanism is introduced into the backbone network to enhance the feature extraction ability of the tapping surface. Secondly, the AFPN structure is used to reduce the loss and degradation of the low-level and high-level feature information. Finally, this paper designs a dual-branch key point detection head to improve the screening ability of key point features in the tapping surface. In the detection performance comparison experiment, the YOLOv8n-IRP improves the D_mAP50 and P_mAP50 by 1.4% and 2.3%, respectively, over the original model while achieving an average detection success rate of 87% in the variable illumination test, which demonstrates enhanced robustness. In the positioning performance comparison experiment, the YOLOv8n-IRP achieves an overall better localization performance than YOLOv8n-Pose and YOLOv5n-Pose, realizing an average Euclidean distance error of less than 40 pixels. In summary, YOLOv8n-IRP shows excellent detection and positioning performance, which not only provides a new method for the key point localization of the rubber-tapping robot but also provides technical support for the unmanned rubber-tapping operation of the intelligent rubber-tapping robot.

Modeling and Energy Flow Calculation of Integrated Energy System Based on Partial Differential Equation Model

This paper discusses the modeling and energy flow calculation method of integrated energy system based on partial differential equation model. By constructing a model that integrates power, heat, and natural gas networks, we analyze in detail the process of energy transmission, conversion, and storage in the system. In the process of modeling, the influence of compressor in constant compression ratio, constant outlet pressure and constant natural gas flow is specially considered, and the accuracy of the model is verified by specific data. In terms of energy flow calculation methods, we compare the performance of the unified solution method and the decomposition solution method. Data analysis shows that the non-gradient descent iterative method, gradient descent iterative method and decomposition solution method show consistency in calculation accuracy, that is, the calculation results of the three methods are the same. However, in terms of computational efficiency, the gradient descent iterative method shows significant advantages. Specifically, under identical computing conditions, our analysis reveals that the gradient descent iterative method exhibits a convergence rate approximately 30% faster than the decomposition solution method, resulting in a notable reduction of around 25% in computational time. This pivotal observation serves as a solid foundation for selecting a more computationally efficient approach in practical applications. To further enhance the computational efficiency, we have delved into deriving the Jacobian matrix of the model and subsequently proposed an advanced gradient descent iterative calculation technique. Through the actual test, this method not only improves the calculation speed, but also ensures the stability and accuracy of the calculation. The research in this paper not only provides a strong theoretical support for the optimal operation of the integrated energy system, but also provides a valuable reference for future research in related fields. Through specific data analysis, we prove the effectiveness and practicability of the proposed method, laying a solid foundation for the sustainable development of integrated energy systems.

Optimizing DG Handling: Designing an Immersive MRsafe Training Program

The rapid growth of e-commerce has significantly increased demands on logistics providers, particularly in the areas of product handling and shipment. One of the most challenging and critical aspects of this process is the handling of dangerous goods (DG). This is a complex and time-intensive operation that requires safety measures and proper packaging and labelling, because mishandling DG can lead to severe injuries, property loss, and legal liability. This puts additional pressure on logistics providers to efficiently manage DG while maintaining speed and safety in the context of e-commerce. To meet this challenge, there is an urgent need to advance training programs and enhance the operational efficiency for DG handling. The use of mixed reality (MR) technology offers a promising solution. By seamlessly integrating virtual elements with real-world environments, MR has the potential to greatly improve the effectiveness and efficiency of the training of DG handling. Earlier research has examined MR in various fields, while there is still a research gap in applying MR specifically to the training of DG handling. This paper seeks to address the current research gap by presenting a novel MR model, named “MRSafe,” for a training program on the safe handling of DG. The model offers users virtual experiences and comprehensive guidance to provide operational decision support.

What are the health system impacts of engaging with global health activity? A qualitative study

Abstract Background Global health partnerships between high-income health systems and low- and middle-income countries (LMICs) are becoming more common as there is an appreciation of the need for collaboration to solve global health issues through knowledge and skill exchange. However, partnership evaluations largely focus on the benefits to individual participants and recipient systems, with little evidence of the impacts on the high-income system. Therefore, the aim of this study was to explore the health system-wide impacts of engaging with global health activity and consider the arguments for and against adopting these partnerships. Methods We carried out semi-structured interviews with individuals from three UK health systems that engage with global health activity to explore their motivations to in doing so. Transcripts were thematically analysed. Results We found that engagement in global health activity can contribute to workforce recruitment, retention, development, and upskilling, benefiting the system. Examples were also given of system-wide clinical, reputational, and economic benefits. However, this activity impacts short term staffing and can cause personal emotional issues that systems need to support. We also explored facilitators of engaging in global health work which included operational support, supporting healthcare staff to engage, and system acceptance. Barriers included lack of senior buy-in, opportunity access inequities, operational challenges, and the current UK health system challenges. Conclusions This study demonstrated the potentially significant system-level benefits of engaging in global health activity. These focused on improved workforce, which is a major public health issue worldwide. We have also identified system characteristics, such as buy-in and operational support, which influence success. We hope this work provides a building block demonstrating there are benefits to be had for donor health systems, but barriers must be overcome. Key messages • The potential benefits and drawbacks that may arise from high-income health systems engaging in global health, as well as facilitators and barriers, are explored. • This study creates a foundation to understand donor-system benefits and encourages further research, particularly in systems who do not engage with global health activity to understand why this is.

Developing Excel VBA Functions for the Mathematical Modeling of Three-Dimensional Vectors

The current computer support for operations involving three-dimensional vectors is insufficient, even in widely used programs like Excel. These programs lack customised features specifically designed for vector operations. However, this limitation can be overcome by using the options provided by Visual Basic for Applications. By creating user functions, we can effectively calculate various results related to the mathematical application of vectors. These functions include determining the magnitude and absolute value of a vector, calculating the angle between two vectors or the cosine of that angle, finding the scalar product and vector product of two vectors, and evaluating the mixed product of three vectors. By incorporating these custom functions into the spreadsheet program, users can easily perform mathematical calculations pertaining to three-dimensional vectors.

Long-term outcomes and operators' experience in primary percutaneous coronary intervention for ST-segment elevation myocardial infarction.

Primary percutaneous coronary intervention (pPCI) for ST-segment elevation myocardial infarction (STEMI) is typically performed by experienced operators. Therefore, the safety of pPCI for STEMI performed by less experienced operators with the support of experienced operators remains unknown. We aimed to investigate the long-term outcomes of pPCI for STEMI performed by less experienced operators with the support of experienced operators. In total, 775 STEMI patients were enrolled and divided into groups according to operator experience in PCI: less experienced (n = 384) and experienced (n = 391) operator groups. Experienced operators were defined as those who had performed > 50 elective PCI procedures per year as the first operator or instructional assistant, whereas less experienced operators were defined as others. When less experienced operators performed the pPCI, experienced operators supported them. The primary endpoint was any cardiovascular event, defined as a composite of cardiovascular death, nonfatal myocardial infarction, and unplanned hospitalization for heart failure. In the propensity score-matched analysis, 324 patients were included in each group. The cumulative incidence of the primary endpoint over a median of 5years in the less experienced operator group was similar to that in the experienced operator group (15% vs. 18%, P = 0.209). In the multivariate Cox proportional hazards model, there was no excess risk for patients operated upon by less experienced operators for the primary endpoint (adjusted hazard ratio, 0.85; 95% confidence interval, 0.58-1.25; P = 0.417). pPCI for STEMI by less experienced operators did not increase the risk of in-hospital mortality or 5-year long-term cardiovascular events if supported by experienced operators.