Difficulties In Control Research Articles

Economic Design of Quality control by Using Triangular Fuzzy Number with Alpha Cut

Manufacturers today prioritize increasing output quality while reducing per-unit costs to remain competitive. Statistical Process Control (SPC) is a useful tool for boosting quality and output. However, decision-makers in industries face difficulties in cost and quality control due to uncertainty in data. Fuzziness can be applied to uncertain data to manage the economic design of a control chart, allowing for better control over the control chart's economic design. This study seeks to enhance the economic design of X control charts by using fuzzy set theory, specifically utilizing triangular fuzzy numbers for cost parameters and the signed distance approach for defuzzification. The objective is to enhance the adaptability of these charts in unpredictable situations. The proposed model enables the incorporation of cost parameters inside a fuzzy framework, with the objective of minimizing the control chart while adhering to the permissible limit. The applicability and improved accuracy of the model in optimizing control chart parameters for a glass bottle production process are exemplified by an effective illustration. This study highlights the need of integrating fuzzy logic into SPC. It suggests a technique that improves the cost-effectiveness and operational effectiveness of control charts in situations when data is uncertain and imprecise. . KEYWORDS :Statistical quality control, Economic quality control, Triangular fuzzy number, Signed-distance, Alpha cut.

RNA sequencing analysis uncovers the role of aldehyde oxidase TcAOX2 in regulating toxic substance susceptibility in the red flour beetle, Tribolium castaneum

Aldehyde oxidase (AOX) is a class of metabolic enzymes, which can make T. castaneum resistant to aldehyde insecticides and thus increase the difficulty of control. In this study, we first examined the killing effect of benzaldehyde, one of the main active components of mugwort essential oil, to T. castaneum and demonstrated the involvement of TcAOX2 in regulating the sensitivity of T. castaneum to benzaldehyde. Subsequently, we identified a total of 105 differentially expressed genes relative to controls by RNA sequencing (RNA-Seq) analysis of T. castaneum late larvae injected with dsTcAOX2, including 67 up-regulated and 38 down-regulated expressed genes. Analysis and functional annotation of differentially expressed genes using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The results showed that the expression of apolipoprotein D, carboxypeptidase A, serine protease P40, pancreatic triacylglycerol lipase, and other genes related to immunity and metabolism, their expression also decreased with the decrease of TcAOX2 expression. The down-regulation of the expression of these genes may make T. castaneum less immune and less able to cope with stressful environments. This suggests that changes in TcAOX2 gene expression may affect the expression of these metabolism- or immunity-related genes, which in turn affects T. castaneum sensitivity to external toxicants. In conclusion, our results provide a theoretical basis for exploring the detoxification mechanism of aldehyde oxidase in T. castaneum and for screening target genes in response to external stimuli.

Isolated microgrid frequency stabilization through nonlinear model predictive control of a gas engine generator set

Gas engine generator sets are applied in microgrids due to their capability to provide reliable, responsive and efficient distributed power generation, enhancing grid resilience and enabling the integration of renewable energy sources. This article proposes a methodology for stabilizing the frequency of an isolated microgrid subjected to a measurable disturbance by controlling the power of a premixed turbocharged natural gas engine. Control difficulties of this task include strongly nonlinear dynamics, time delay in the air-fuel path and constrained operating conditions. Conventional control methods like proportional-integral control have difficulties solving these problems, and require extensive tuning efforts and gain scheduling to deliver acceptable performance, prompting adoption of advanced control strategies. The presented approach utilizes a cascaded control architecture with a nonlinear model predictive controller (NMPC) for high level control and engine specific low-level controllers for controlling the intake manifold pressure and air-fuel ratio. The NMPC captures the inherent nonlinear dynamics, accounts for an input delay and handles state-dependent constraints. The cascaded control architecture enables the usage of a comparably simple model for the NMPC design, reducing the computational cost and the parametrization effort. This additionally enables application of the high level controller for different gas engine types and allows design of the controller in a simple simulation environment prior to the experiments on the real engine. Experimental results highlight the NMPC’s ability to control the engine at its physical limits over the entire load range without inducing frequency oscillations using just one parameter set. This emphasizes the robustness of the presented approach, making it a promising solution for real-world applications.

Synergistic photobiocatalysis for enantioselective triple radical sorting.

Multicomponent reactions - those where three or more substrates combine into a product - have been highly useful in rapidly building chemical building blocks of increased complexity4, but achieving this enzymatically has remained rare.5 This limitation primarily arises because an enzyme's active site is not typically set up to address multiple substrates, especially in cases involving multiple radical intermediates6. Recently, chemical catalytic radical sorting has emerged as an enabling strategy for a variety of useful reactions7,8. However, making such processes enantioselective is highly challenging due to the inherent difficulty in the stereochemical control of radicals9. Here, we repurpose a thiamine-dependent enzyme10,11 through directed evolution, combine it with photoredox catalysis, to achieve a photobiocatalytic enantioselective three-component radical cross-coupling. This approach combines three readily available starting materials - aldehydes, α-bromo-carbonyls and alkenes - to give access to enantioenriched ketone products. Mechanistic investigations provide insights into how this dual photo-/enzyme system precisely directs the three distinct radicals involved in the transformation, unlocking new enzyme reactivity. Our approach has achieved exceptional stereoselectivity, with 25 out of 33 examples achieving ≥97% enantiomeric excess.

A Framework for Evaluating the Reasonable Internal Force State of the Cable-Stayed Bridge Without Backstays

The synchronous construction of the pylon and cables of a cable-stayed bridge without backstays has the characteristics of a short construction period and reduced support costs. However, it also increases the difficulty of construction control, making the reasonable completion state of the bridge more complex. To investigate the impact of various load parameters on the structural state of a cable-stayed bridge without backstays during the synchronous construction process, and to ensure a rational final bridge state, this study proposes an assessment framework for evaluating the internal forces of the bridge. The framework initially uses the response surface method to establish explicit equations relating the control indicators of the bridge’s final state to various load parameters. Subsequently, through sensitivity analysis, the degree of influence of each load parameter on the structural response of the cable-stayed bridge without backstays is examined. The most sensitive factors are identified to create a bridge parameter influence library, which helps reduce computational costs. Based on this, a method for controlling construction errors and predicting cable forces is proposed. This method utilizes the pre-established bridge parameter influence library, combined with the internal force state of the bridge at the current construction stage, to accurately predict the tension force of the stay cables in the subsequent stage, thereby ensuring a rational final bridge state. The framework is ultimately validated through a case study of the Longgun River Bridge to assess its rationality and effectiveness.

Event‐Triggered Adaptive Neural Network Control for 4WS4WD Wheeled Mobile Robot

ABSTRACTIn this article, an event‐triggered adaptive neural network controller based on threshold band is designed for a four wheels independently steered and four wheels independently driven (4WS4WD) mobile robot. The 4WS4WD mobile robot is attracting attention for its excellent motion performance such as manipulation versatility and posture flexibility. However, its control difficulty is increased due to its characteristics of being controlled by eight motors for steering and driving respectively. Also, since the robot itself has limited computing and communication resources, real‐time control cannot be guaranteed. To copy with that, the kinematic and dynamics models are first introduced for the 4WS4WD mobile robot. Second, an adaptive neural network controller with low‐frequency learning rate is utilized to control the mobile robot since there are unknown perturbations in the model. It can maintain system stability while handing unidentified model perturbations. The stability of the controller is demonstrated by Lyapunov stability analysis. An event‐triggered based on threshold band is suggested to lessen the amount of computation in the control process. Finally, the simulation outcomes further demonstrate how the suggested approach can greatly lessen the computational and communication cost while maintaining control performance.

A Neural Network-Based State-Constrained Control Strategy for Underactuated Aerial Transportation Systems Within Narrow Workspace

The aerial transportation system belongs to a symmetrical system and has recently garnered increasing attention from researchers due to its broad application range and convenient operation. The control difficulty of the aerial transportation system lies in the fact that the load is not directly actuated, posing a significant challenge for state-constrained control. Taking the motion of an unmanned aerial vehicle (UAV) suspension transportation system within complex pipelines as an example, this paper employs the the swept volume signed distance field (SVSDF) method to search for state boundaries, which is an aspect not considered or elaborated in many state-constrained control approaches. Furthermore, adaptive state-constrained control based on the radial basis function (RBF) neural network is utilized for the case of experiencing unknown air resistance. The convergence of the proposed method for underactuated and actuated state variables is theoretically demonstrated based on the Lyapunov technique. Compared with existing methods, the error integral index demonstrates that the proposed method displays better convergence capability in the simulation section when considering state constraints under disturbance and air resistance.

Chaos-based coverage path planning framework for mobile robots and its digital signal processing implementation

Abstract For special coverage path planning, chaos-based mobile robots present a promising solution. The robot can cover the area of interest rapidly with unpredictable trajectories. However, this unpredictability causes difficulties in trajectory control and the robot often makes sharp turns, affecting motion stability. To address these challenges, this paper proposes a universal chaos-based path planning framework for mobile robots. Firstly, a chaotic system that can generate multi-scroll and multi-wing attractors is designed to verify the effectiveness of the framework. Secondly, an integrated system consisting of mobile robots and chaos is proposed to generate chaotic trajectories. By the control parameters in the integrated system, the formation mechanism of continuous chaotic trajectories is shown, which makes the chaotic trajectory have the advantages of scaling, rotating, straightening, and bending, and the path planning no longer relies on the chaotic system only. Then, a regional path planning strategy is proposed to control the angular velocity and workspace of the robot, making its motion smooth and reducing trajectory redundancy. Experiments conducted under this framework have demonstrated its university, with various chaotic systems capable of generating efficient robot trajectories with high coverage rate. Compared with the state-of-the-art similar memoryless algorithms, the coverage task can be accomplished quickly and efficiently by our approach. Finally, the robot trajectory tracking control verifies the controllability of chaotic trajectories, and the implementation of chaotic trajectories with digital signal processing techniques further validates the feasibility of path planning frameworks.

Associations between preschooler screen time trajectories and executive function

ObjectivesTo examine associations between preschooler screen time trajectories and executive functions and effortful control at age 5. MethodsProspective, community-based convenience sample of 315 parents of preschoolers (54% male), studied at the ages of 3.5 (2020), 4.5 (2021), and 5.5 (2022). Parent-reported screen use at the ages of 3.5, 4.5, and 5.5 was used to estimate preschooler screen use trajectories. Using latent growth modeling, we identified low (mean=.9 hrs/day, 23%), medium (mean=3.0 hrs/day, 56%), and high (mean=6.38 hrs/day, 21%) screen time groups.Children completed assessments of inhibitory control and cognitive flexibility at age 5.5. Both tasks are from the NIH Toolbox. Parents reported child effortful control at the age of 3.5 and 5.5 using the Children’s Behavior Questionnaire, educational attainment, and parenting stress. ResultsChildren in the average (b =-5.24) and high (b=.9.30) screen time trajectories scored significantly lower on inhibitory control than those in the low screen time group. Children in the average and high screen time groups also scored higher than children in the low screen time group on cognitive flexibility (b =-4.50) and (b=-10.12), respectively. Finally, children in the average and high screen time groups scored lower than children in the low screen time groups on effortful control (b =-.41) and (b=-.61), respectively. ConclusionsThe present study shows that stability in high levels of screen use is common among preschoolers and may forecast higher risk of cognitive difficulty and lower levels of cognitive control by the time of school entry. SummaryHigh levels of preschooler screen use were associated with lower scores on assessments of inhibitory control, cognitive flexibility, and effortful control.

Effect of severe periodontitis of maxillary molars on the maxillary sinus and the treatment principles of periodontitis related maxillary sinusitis

Maxillary sinus is located in the maxilla bone with the largest volume in all sinuses and is closest to the roots of maxillary posterior teeth, especially the mesiobuccal root of the maxillary second molar. The thickness of the normal maxillary sinus mucosa is about 1 mm. When stimulated or infected, it shows thickening of the mucosa. Periodontitis is one of the most common oral diseases in human beings, and the complex root anatomy of the maxillary molars aggravates the difficulty of inflammation control. Severe periodontitis of maxillary molars without effective treatment can affect the maxillary sinus, increasing the possibility of the mucosa thickening, and is also one of the reasons for the occurrence of odontogenic maxillary sinusitis (OMS). There are many different schemes for the treatment of OMS caused by severe periodontitis of maxillary molars. Extraction of teeth with severe periodontal disease without retention value or successful periodontal treatment can significantly reduce the thickness of maxillary sinus mucosa. For the patients with uncontrollable sinusitis by using drug treatment and eliminating odontogenic causes, or ones with severe symptoms, periodontal treatment and endoscopic sinus surgery can be combined to effectively control the periodontitis related maxillary sinusitis.

The impact of pine wilt disease on the endophytic microbial communities structure of Pinus koraiensis.

Pine Wilt Disease (PWD) is a devastating pine tree disease characterized by rapid onset, high mortality rate, quick spread, and difficulty in control. Plant microbiome plays a significant role in the development of PWD. However, the endophytic microbial communities of Pinus koraiensis infected by pine wood nematode (PWN) Bursaphelenchus xylophilus remain largely unexplored. In this study, we analyzed the structural changes of endophytic communities of P. koraiensis after infection by the PWN using high-throughput sequencing technology. The results showed that the community structure underwent significant changes as the degree of PWN infection intensified. The diversity and abundance of endophytic fungi in P. koraiensis increased, while those of endophytic bacteria in P. koraiensis decreased during the infection process. Meanwhile, the abundance of some dominant microorganisms has also changed, including species such as Graphilbum and Pseudoalteromonas. Functional prediction analysis showed that the functional composition of endophytic fungi in P. koraiensis was significantly different across the development of PWD, while the composition of endophytic bacteria remained essentially similar. The results indicated that PWN infection had a significant impact on the structure, diversity, abundance, and functional gene composition of endophytic microbial communities in P. koraiensis, and most of the main endophytic microbial groups tended to coordinate with each other. This work provides a better understanding of the changes in endophytic community structure and function caused by PWD infection of P. koraiensis, which may benefit the exploration of potential endophytes for PWN biocontrol.

Opportunities and Challenges on Natural Farming

Natural Farming, an ecological and sustainable agricultural practice, emphasizes minimal human intervention and the use of natural resources for crop cultivation. Unlike conventional farming, which relies heavily on chemical inputs, Natural Farming integrates practices such as minimal tillage and organic inputs like cow dung and plant-based preparations. This case study explores Natural Farming practices among farmers in Tamil Nadu, focusing on their experiences, opportunities, and challenges. The study includes detailed case studies of three farmers in Coimbatore District and each farmer employing different natural farming techniques and facing unique obstacles. The findings reveal that Natural Farming offers significant benefits, including reduced farming costs, improved soil health, and enhanced market opportunities for organic produce. Farmers reported that these practices lead to better crop resilience and higher-quality produce, often fetching premium prices. However, challenges persist, including difficulties in weed control, pest and disease management, labor shortages, and delay in certification, which can affect market access and profitability. The study underscores the potential of Natural Farming to transform agricultural practices by promoting sustainability and reducing dependence on chemical inputs. It also highlights the need for supportive interventions, such as enhanced market access, comprehensive farmer training, and government support to address the identified challenges and maximize the benefits of Natural Farming. This study contributes to a deeper understanding of Natural Farming's role in sustainable agriculture and its implications for farmers in Tamil Nadu.

The Daydream Spectrum: The Role of Emotional Dysregulation, Internalized Stigma and Self-Esteem in Maladaptive Daydreaming Among Adults With ADHD, ASD, and Double Diagnosis.

Maladaptive daydreaming (MD) is characterized by vivid, excessive fantasy activity that becomes prioritized over other activities and may result in avoidant coping strategies. Little is known about the relationship between MD and internalized stigma in the neurodivergent sample. The current study aimed to examine emotional dysregulation, escapism and self-perception (self-esteem and internalized stigma) as potential determinants of MD in three groups: adults on the autism spectrum, with ADHD, and both diagnoses ("AuDHD"), including their neurodivergent symptoms (autistic traits, empathizing, ADHD symptoms). A sample of 293 persons (139 with ADHD, 74 on the autism spectrum, and 80 with both diagnoses) completed self-report scales concerning ADHD symptoms, autism spectrum symptoms, empathizing, self-esteem, daydreaming as escapism, emotional dysregulation, maladaptive daydreaming, and internalized stigma. A correlation analysis was implemented. Additionally, a group comparison and quantile regression for the 25th, 50th, and 75th percentile of maladaptive daydreaming in the three groups were executed. The results showed that internalized stigma, emotional dysregulation, escapism, and self-esteem have significant associations with MD in the neurodiverse sample. The ADHD group achieved the lowest scores in emotional dysregulation, discrimination experience, and social withdrawal. The groups did not vary in MD rates, stereotype endorsement, stigma resistance, nonacceptance of emotional responses, and impulse control difficulties. The AuDHD group achieved higher results than the ASD group only in the ADHD symptoms. Quantile regression revealed differences in the predictors of maladaptive daydreaming in the three groups. ADHD symptoms and self-suppression escapism were significant predictors for the higher levels of MD in persons with singular autism or ADHD diagnosis. The results showed no differences in MD rates, although there were significant variations in predictive features among the three samples. The role of internalized stigma and self-esteem was highlighted in the results as significant associates of MD prevalence. These outcomes expand the current knowledge in the context of maladaptive daydreaming, internalized stigma, self-esteem and emotional dysregulation in a neurodiverse sample and allow for proposing clinical applications and further research directions.

Assessment of Situational Complexities and Vehicle Control Difficulties for Profiling Driving Skills

Assessment of Situational Complexities and Vehicle Control Difficulties for Profiling Driving Skills

Coherence Programming for Efficient Linearly Polarized Perovskite Light-Emitting Diodes.

Although quasi-two-dimensional (quasi-2D) perovskites are ideal material platforms for highly efficient linearly polarized electroluminescence owing to their anisotropic crystal structures, so far, there has been no practical implementation of these materials for the demonstration of linearly polarized perovskite light-emitting diodes (LP-PeLEDs). This scarcity is due to difficulty in orientation and phase distribution control of the quasi-2D perovskites while minimizing the defects, all of which are required to manifest aligned transition dipole moments (TDMs). To achieve this multifaceted goal, herein, we introduce a synergistic strategy to quasi-2D perovskites by incorporating both a trimethylolpropane triacrylate anchoring layer and 18-Crown-6 molecular passivator into the film fabrication process. It is found that the interfacial anchoring layer guides the oriented growth of perovskites along the (110) plane, whereas the molecular passivator reduces the number of defects and homogenizes the crystal phase. As a result, a quasi-2D perovskite film with macroscopically aligned TDM that renders high radiative recombination and the degree of linear polarization (DoLP) is constructed. This "coherence-programmed emission layer" demonstrates highly efficient LP-PeLEDs, not only achieving a maximum external quantum efficiency of ∼23.7%, a brightness of ∼36,142 cd/m2, and a DoLP of ∼38%, but also significantly improving the signal-to-interference-and-noise ratio in a multi-cell visible light communication system.

Weld Pool Flow Characteristics in Double-Wire Arc Welding of Aluminum Alloys: Research by Numerical Simulations

Double-wire arc welding involves simultaneously feeding two wires into a molten pool, improving the efficiency and flexibility of traditional welding techniques. However, the interactions between the two wires and the molten pools are complex, which increases the difficulties in process and composition control. This work focuses on the weld pool flow characteristics in double-wire TIG arc welding. A CFD model incorporating a liquid bridge transfer model was developed to simulate the fluid flow phenomenon. Results show that the bead-forming appearances and flow characteristics of double-wire arc welding show no significant differences from single-wire arc welding. Welding current and welding speed have significant effects on the weld bead dimensions, while only welding current has effects on the flow characteristics. Wire feed XOZ angles show no significant influences on weld bead forming appearances and molten pool flow characteristics. Wire feed XOY angles influence the symmetry of the weld bead and the fluid flow. In 5B71/7055 heterogeneous double-wire arc welding, achieving a uniform distribution of alloy elements is difficult due to the complex convection patterns within the molten pool.

Research Progress and Challenges of Hydrogen-Ammonia Hybrid Fuel Engines

In this paper, we review the research status of hydrogen and ammonia engines, and discuss the potential of the two fuels as clean energy sources and their challenges. Hydrogen fuel has attracted attention due to its high energy density and zero-emission characteristics, but hydrogen fuel engines have problems such as increased nitrogen oxide emissions, tempering and early ignition. Ammonia fuel, as a carbon-free alternative fuel, has the advantage of being easy to store, but it is inferior to traditional fuels in combustion performance. This paper further analyzes the research progress of hydrogen/ammonia hybrid fuel engines, highlighting specific challenges such as optimizing the fuel mixture ratio, addressing safety concerns related to hydrogen's flammability and ammonia's toxicity, and overcoming technical difficulties in combustion control, points out the combustion support effect of hydrogen and the influence of ammonia on combustion rate, and discusses the advantages of hybrid fuel engines in emission control. Finally, this paper summarizes the current development trend of hydrogen/ammonia fuel engine technology and puts forward suggestions for future research directions.

Do impulse control difficulties moderate the relationship between intermittent fasting and disordered eating?

BackgroundRecent findings suggest positive associations between intermittent fasting (IF, i.e., an eating pattern that consists of alternating between consuming and abstaining calories over specified periods of time) and disordered eating (DE), including binge eating, laxative use, and self-induced vomiting. However, as not all individuals who engage in IF present with DE, the current study aimed to investigate whether 1) IF was associated with elevated DE, and 2) impulse control difficulties differentially predict DE in intermittent fasters compared to non-intermittent fasters. MethodsParticipants included 929 undergraduates (M = 19.8, SD = 2.97) from a university in the United States. IF was assessed with a single item question, “Do you intentionally engage in intermittent fasting in order to lose/maintain your weight or due to health-related motivations?” The Eating Disorder Examination Questionnaire was used to measure DE (i.e., global score, restraint, eating, shape, and weight concerns). One subscale from the Difficulties in Emotional Regulation Scale was used to measure impulse control difficulties. Hierarchal regressions examined whether impulse control difficulties moderated the relationship between IF and DE while controlling for age, gender, race, and ethnicity. ResultsIF was significantly associated with all DE outcomes. Adjusted analyses indicated that impulse control difficulties moderated the relationship between IF and two DE outcomes (i.e., global score (b = 0.038, se = 0.017, t = 2.17, p < 0.05) and restraint (b = 0.042, se = 0.019, t = 2.22, p < 0.05)). DiscussionThese results support previous literature that suggests an association between IF and elevated DE. Further, individuals engaging in IF with impulse control difficulties may experience more feelings of restraint towards eating and increased overall DE though effects were small. Future research delineating who is at highest risk for DE when engaging in IF is needed.

Spatially distributed low-cross talk vector beams.

A spatially distributed low-cross talk vector beam refers to a vector beam that exhibits different intensities, phases, and polarization states along the propagation direction. This type of vector beam features low-cross talk between beams on different planes and finds extensive applications in optical communications and related fields. However, current technologies face challenges such as intensity interference at different imaging planes and difficulties in the precise control of phases and polarization states, which affect beam quality. In this study, we investigated the beam propagation process and employed a global optimization strategy to precisely control the intensity and phase distribution of the beam fields. This approach ensures that the beam forms the desired complex amplitude distribution in the target region while effectively suppressing cross talk in non-target regions. We utilized the method to generate two beams with complementary intensities and phases. Subsequently, through an interference optical path, we separated these two beams and converted them into orthogonal polarization states. Finally, by superimposing these two beams, we obtained a spatially varying low-cross talk vector beam. We experimentally validated the beam's different optical characteristics and low-cross talk properties on three planes. Our work opens up new prospects, to the best of our knowledge, for holographic technology with capabilities for ultra-fine depth control and polarization multiplexing.

Revealing the coupled evolution process of construction risks in mega hydropower engineering through textual semantics

Mega hydropower engineering (MHE) involves complex construction processes, harsh environments, and highly mobile personnel, equipment, and other resources, resulting in a high incidence of construction risks and significant difficulties in safety control. Previous studies extensively explored the identification and governance of risks in MHE. However, these studies did not adequately utilize accident report case texts, and the coupled evolutionary law of construction risks remains unclear. To address this gap, this study developed a Bert-based Global Pointer Network for Named Entity-Relation Joint Extraction (Bert-GPLinker) to extract risk factors and their relationships. Second, the extracted risk factors and their relationships were employed to construct a knowledge graph, integrating text matching and path inference algorithms to propose a coupled evolutionary path reasoning method for construction risks. Finally, the coupled interactions among the risk factors were considered, and the interaction matrix principle was utilized to quantitatively assess the importance of each risk factor in the knowledge graph. The results showed that (1) the F1 value of Bert-GPLinker on the self-built dataset was 91.90%, indicating better model performance; (2) the coupled evolutionary reasoning system can quickly deduce the evolutionary path with the highest probability of any risk node and the types of accidents that may result; and (3) among the top 25 risk factors in terms of importance, those in the management system category accounted for 52%, with higher importance mainly concentrated in inspection, supervision, and training.