Operational Control Research Articles

Risk‐Aware SDN Defense Framework Against Anti‐Honeypot Attacks Using Safe Reinforcement Learning

ABSTRACTThe development of multiple attack methods by external attackers in recent years poses a huge challenge to the security and efficient operation of software‐defined networks (SDN), which are the core of operational controllers and data storage. Therefore, it is critical to ensure that the normal process of network interaction between SDN servers and users is protected from external attacks. In this paper, we propose a risk‐aware SDN defense framework based on safe reinforcement learning (SRL) to counter multiple attack actions. Specifically, the defender uses SRL to maximize the utility by choosing to provide a honeypot service or pseudo‐honeypot service within predefined security constraints, while the external attacker maximizes the utility by choosing an anti‐honeypot attack or masquerade attack. To describe the system risk in detail, we introduce the risk level function to model the simultaneous dynamic attack and defense processes. Simulation results demonstrate that our proposed risk‐aware scheme improves the defense utility by 17.5% and 142.4% and reduces the system risk by 42.7% and 59.6% compared to the QLearning scheme and the Random scheme, respectively.

Research progress on operation control and optimal scheduling of irrigation canal systems

AbstractOpen canals are a common water transfer method used in water transfer projects and agricultural irrigation and drainage projects. With the emergence of drawbacks in traditional canal control models and the increasingly severe shortage of water resources, accurate transport and distribution of water in the canal system of the irrigation district, rational allocation of water resources, reduction in water loss, improvement in the efficiency and benefit of water resource utilization, and satisfaction of the water demand of different water users are needed. Many scholars have conducted extensive research on canal operation control and optimal scheduling. This paper systematically reviews and summarizes the relevant research progress, including the theory of unsteady flow in open canals, the operation mode of the canal system, the operation control model and algorithm of canal systems, and the optimization of water distribution in canal systems. By summarizing the research progress already achieved, the existing problems and future development directions are identified according to actual needs, providing a reference for the ongoing modernization of irrigation districts and the research and application of digital twin irrigation district technology.

The Role of Financial Innovations in the Relationship between Open Market Operations and Access to Credit by Small and Medium Enterprises in Kisumu County, Kenya

Purpose: This study investigated the role of financial innovations in the relationship between open market operations and access to credit by small and medium enterprises in Kisumu County. The specific objectives were to assess the effect of open market operations on access to credit by small and medium enterprises and to investigate the role of financial innovations in the relationship between open market operations and access to credit by small and medium enterprises in Kisumu County. The study was guided by Milton Friedman's Monetarism Theory. Methodology: The study adopted a descriptive research design with a target population of 1,472 SME owners/finance officers in Kisumu County. A sample of 420 was obtained, and a closed-ended questionnaire was used to collect primary data. Data was analyzed using descriptive, correlation and regression analyses. Results: Results showed that open market operations had a statistically significant effect on SMEs' access to credit in Kisumu County. Further, financial innovations statistically and significantly moderated the effect on the relationship between open market operations and access to credit by small and medium enterprises. The study concluded that SMEs' access to credit depended on the direct and indirect effects of open market operations and also that financial innovations moderated these effects. Contribution to theory, practice and policy: The implication is that open market operations should be used to gradually and in a predictive manner increase the quantity of money until an equilibrium rate of interest is attained. SMEs will also be able to access credit if the supply is adequate and the interest rate is at the desired level for the clients. The results of the independent variable of this study showed that even though OMO had a significant effect on access to credit, its contribution was minimal. This may imply that the instruments used in the open market operations may not be accessible by small traders due to the minimum amount required for investment. The players of the financial markets could, therefore, think of innovative ways to customize products for the small traders in the open market operations to ensure optimum access to credit by SMEs. This study found that financial innovations increased the effect of open market operations on SMEs' access to credit by increasing the variation of access to credit. The use of financial innovations should, therefore, be encouraged as a bridge that would enhance SMEs' access to credit. This is a major contribution to knowledge, as no study has established this fact. Policies that would ensure implementation and control of the open market operations should be formulated. Mechanisms for firm checks should be crafted to ensure efficient and effective implementation of the same. These policies should be reviewed regularly to ensure they are current and offer proper guidance. Their implementation could ensure optimum utilization of the investment channels, hence ensuring the growth and stability of the economy.

Enterprise risk management in supply chain operation: a fuzzy risk prioritization approach

PurposeTraditional risk prioritization methods in Enterprise Risk Management (ERM) rely on precise data, which is often not available in real-world contexts. This study addresses the need for a robust model that can handle uncertain and imprecise information for more accurate risk assessment.Design/methodology/approachWe propose a group decision-making approach using fuzzy numbers to represent risk attributes and preferences. These are converted into fuzzy risk scores through defuzzification, providing a reliable method for risk ranking.FindingsThe proposed fuzzy risk prioritization framework improves decision-making and risk awareness in businesses. It offers a more accurate and robust ranking of enterprise risks, enhancing control and performance in supply chain operations by effectively representing uncertainty and accommodating multiple decision-makers.Practical implicationsThe adoption of this fuzzy risk prioritization framework can lead to significant improvements in enterprise risk management across various industries. By accommodating uncertainty and multiple decision-makers, organizations can achieve more reliable risk assessments, ultimately enhancing operational efficiency and strategic decision-making. This model serves as a guide for firms seeking to refine their risk management processes under conditions of imprecise information.Originality/valueThis study introduces a novel weighted fuzzy Risk Priority Number method validated in the risk management process of an integrated steel plant. It is the first to apply this fuzzy approach in the steel industry, demonstrating its practical effectiveness under imprecise information. The results contribute significantly to risk assessment literature and provide a benchmarking tool for improving ERM practices.

Appraising the Role of Strategic Control in Financial Performance: The Mediating Effect of the Resource Allocation Process—The Case of the Ministry of Finance–North Lebanon

This paper aims to appraise the influence of strategic control tactics on financial performance. The goal is to examine the mediating effect of the resource allocation process on the relationship between financial performance and five strategic control tactics. A quantitative hypothetico-deductive methodology was used in this study. A basic random sample of the Ministry of Finance–North Lebanon’s workforce was used to conduct an electronic questionnaire. A total of 232 valid responses were collected. Two statistical analysis methods, an exploratory and a confirmatory factor analysis, were implemented. The sample adequacy was confirmed by a KMO value higher than 0.7 before instigating the principal component analysis (PCA). The latter kept more than 60% of the initial data while structuring the data. The findings of the KMO and Barlett tests supported the adoption of PCA. The correlation matrix confirmed a statistically significant relationship between resource allocation, financial success, and strategic control techniques. The structural equation model (SEM) validated the linear correlations and statistical significance between the variables. The hypotheses were examined. Results confirmed that the model satisfactorily fits the data. The RMSEA is below the 0.05 threshold. The incremental indices are higher than 0.9. Results confirmed that the resource allocation process mediates the relationship between preventive control, operational control, special alert control, implementation control, and financial performance.

A novel component separation method for deformation monitoring of rockfill dams

High dams are constructed in mountain valley areas with extremely complex geomorphologies, geologies, and operating environments. The dam body and foundation are subjected to large hydraulic loadings and high stress levels, where many factors affect the structural deformation of the dam, making dam safety monitoring and risk assessment difficult. Since dam deformation is critical for evaluating safe operation, a novel dam deformation monitoring model based on the component separation method is proposed, which can provide scientific significance and high application value for operational safety control. The deformation monitoring data include deformation caused by the water level, the temperature, and the time effect. The homologous monitoring sequence points are selected, and a safety monitoring model is proposed based on the physical causes and the independent component signal decomposition technology. First, the aging component can be extracted by using the correlation consistency of a specific measurement point, where the environment is almost the same at the same time of year, such as the temperature and the water level. Then, fast independent component analysis algorithm is applied to further extract the dam deformation induced by the water level and the temperature via correlation analysis. Finally, a deformation monitoring model based on the component separation can be successfully constructed by combining models of the three components. The proposed dam deformation model can overcome problems of large covariance of deformation component, large collinear interference of periodic component separation, and unstable separation. It is further applied to a high face rockfill dam, and the results shows that the multiple correlation coefficient is greater than 0.995 and the mean absolute percentage error is less than 1.37%, demonstrating the high accuracy and stable separation of the components produced by using this model.

Assessment of aerosol radioactivity in the atmospheric air of populated areas

Introduction. Due to the tense situation in the world, which may lead to deliberate emergencies at radiation-hazardous facilities as a result of terrorist or sabotage actions, the availability of methods for operational control of radioactive aerosols in the atmospheric air, as well as knowledge of background levels of α- and β-activity of aerosols in the locations of nuclear power facilities, mining and processing facilities The aim of the study was to assess the radioactivity of aerosols in the atmospheric air according to the indices of α- and β-activity (using the example of the cities of Voronezh, Novovoronezh, Pavlovsk, Lipetsk, Stary Oskol). Materials and methods. Atmospheric air sampling was carried out using a flow meter-sampler of PU-5 aerosol mixtures. The α- and β-activity of the surface of the AFA-RSP-20 filters was measured with the MKS-AT1117M dosimeter-radiometer with interchangeable detection units BDPA-01 and BDPB-01. Results. The results of measurements of aerosols α- and β-activity in the atmospheric air in all control points in the territories of populated places established the α-activity of the aerosols to vary from 1.10 • 10–3 to 6.75 • 10–3 Bq/m3, total (total) β-activity – from 3. 49 • 10–3 to 2.12 • 10–2 Bq/m3. The maximum indices values took place at control points near the open-pit mining of the Shkurlatovsky granite deposit (near Pavlovsk, Voronezh region). Limitations. The limitations of the study are related to possible errors of the proposed and tested methodology, single (one-time) measurements, variable meteorological conditions affecting a specific result. Conclusion. The maximum values of aerosols α- and β-activity in the atmospheric air of populated areas are determined by the results of one-time measurements (6.75 • 10–3 Bq/m3 and 2.12 • 10–2 Bq/m3) do not cause concerns for the health of the living population.

Simulation Model of a Steelmaking-Continuous Casting Process Based on Dynamic-Operation Rules.

The steelmaking-continuous casting process (SCCP) is a complex manufacturing process which exhibits the distinct features of process manufacturing. The SCCP involves a variety of production elements, such as multiple process routes, a wide array of smelting and auxiliary devices, and a variety of raw and auxiliary materials. The production-simulation of SCCP holds a natural advantage in being able to accurately depict the intricate production behavior involved, and this serves as a crucial tool for optimizing the production operation of the SCCP. This paper thoroughly considers the various production elements involved in the SCCP, such as the fluctuation of the converter smelting cycle, fluctuation of heat weight, and ladle operation. Based on the Plant Simulation software platform, a dynamic simulation model of the SCCP is established and detailed descriptions are provided regarding the design of an SCCP using dynamic-operation rules. Additionally, a dynamic operational control program for the SCCP is developed using the SimTalk language, one which ensures the continuous operation of the caster in the SCCP, using the discrete simulation platform. The effectiveness of the proposed dynamic simulation model is verified by the total completion time of the production plan, the transfer time of the heat among the different processes, and the frequency of ladle turnover. The simulation's results indicate that the dynamic simulation model has a satisfactory effect in simulating the actual production process. On this basis, the application effects of different schedules are compared and analyzed. Compared with a heuristic schedule, the optimized schedule based on the "furnace-machine coordinating" mode reduces the weighted value of total completion time by 8.7 min, reduces the weighted value of transfer waiting time by 45.5 min, and the number of rescheduling times is also reduced, demonstrating a better application effect and verifying the optimizing effect of the "furnace-machine coordinating" mode on the schedule.

A smooth switching strategy for steady-state operation control and fault transient control of doubly fed induction generator

Abstract As the proportion of wind power generation systems in power systems continues to rise, their dynamic response during system malfunctions has gained significant importance. As the grid short-circuit ratio continues to decrease, traditional fault ride-through algorithms for wind power generators may no longer be applicable. This is evidenced by voltage oscillations under significant disturbances and overvoltage issues during low-voltage ride-through, which are further aggravated during asymmetric fault conditions. Therefore, this paper focuses on the low-voltage ride-through issues of doubly fed induction wind power generators in weak power grids. It investigates the steady-state operation and transient control schemes and proposes a smooth transition strategy for steady-state and fault transient operations of doubly fed wind power generators. This approach guarantees the synchronization of active and reactive power, mitigates steady-state reactive power imbalance, and prevents voltage fluctuations triggered by recurring low-voltage ride-through occurrences. Furthermore, during fault recovery, a ramped active power restoration approach is employed to mitigate the coupling of active and reactive power introduced by the phase-locked loop, enabling rapid and stable restoration of active and reactive power outputs. As a result, superior dynamic performance is achieved during both symmetric and asymmetric fault processes. Finally, the superiority of the proposed smooth transition strategy under different fault scenarios is validated through simulations with the RTLAB platform.

Modeling and Control for Alkaline Water Electrolyzers Operating in Wide Range

Modeling and Control for Alkaline Water Electrolyzers Operating in Wide Range

Risk factors affecting the food safety risk in food business operations for risk-based inspection: A systematic review.

Foodborne illnesses result in a high disease burden worldwide, making food safety control of food business operations (FBOs) an urgent issue. With public agencies and FBOs facing challenges in monitoring the complex food supply chain with limited resources, scientific and objective insights into those factors that are related to food safety at FBOs are needed. These factors can be used as input for risk-based inspection. We conducted a systematic review to identify and analyze risk factors affecting the FBOs' food safety risk. We used a set of predefined search strings in Scopus and Web of Science to search for scientific manuscripts published in the English language between January 1 2003 and February 1 2023. The review identified 53 relevant studies and 43 risk factors. The presence of certified personnel turned out to be the most cited factor. Nearly half of the extracted factors had only been investigated in one study. Additional challenges were identified for developing a universal ready-to-use list of factors for the building of a risk-based inspection method, such as the limitation in the applicability of identified factors in different types of FBOs, and the variability in conclusions between publications for certain factors (e.g., FBO location and inspection history), stressing the need for additional research. Future studies should also prioritize standardizing definitions and measurements, particularly regarding compliance factors. In general, the current list of factors brought forward in our review lays the groundwork for building a transparent, objective, and risk-based method for food safety inspections of FBOs.

Meta-Reinforcement Learning for Spacecraft Proximity Operations Guidance and Control in Cislunar Space

Innovative lightweight and model-free guidance algorithms are essential to achieve full autonomy of spacecraft and address future space exploration challenges. In the near future, this type of technology will be essential for cislunar space proximity operations, such as NASA’s Artemis program and its Lunar Gateway project. In this scenario, a meta-reinforcement learning algorithm is employed to address the real-time optimal guidance problem of a spacecraft in the cislunar environment. Non-Keplerian orbits pose complex dynamics, where classic control theory may be less adaptable and more computationally expensive compared to machine learning approaches. Meta-RL stands out for its ability to learn how to learn through experience, training on various tasks to enhance efficiency, and effectiveness in tackling new ones. By modeling a stochastic optimal control problem within the circular restricted three-body problem framework as a Markov decision process, an LSTM-based network agent is trained using proximal policy optimization, considering operational constraints and stochastic effects for safety and robustness evaluation. Additionally, an MLP-based agent and an optimal control pseudo-spectral solution are assessed for comparison. The resulting tool autonomously guides spacecraft in cislunar proximity operations, approximating the optimal control solution with a versatile algorithmic framework. This ensures both robustness and computational efficiency.

Scenario Planning in Pam Jaya For 2030 in Dealing with Future Uncertainties

Access to clean and safe drinking water is a fundamental human right and a cornerstone of public health and sustainable urban development. PAM JAYA has taken full operational control, assuming responsibility for providing and distributing clean water to DKI Jakarta. To meet its targets by 2030 and navigate future uncertainties for PAM JAYA, this research employs scenario planning to better identify driving forces, develop scenarios, and formulate strategies. This research addresses the key focal issue and research objectives regarding the extensive strategies PAM JAYA should adopt over the next six years to achieve its business targets. A qualitative research approach, utilizing semi-structured interviews, predicts multiple future scenarios. Seventeen driving forces were identified, leading to two critical uncertainties: Law Enforcement and Tariff Adjustment. Four scenarios emerged: Harmony Era, Strict Era, Lax Prosperity Era, and Injustice Era. Exploring the implications and strategic options for each scenario equips PAM JAYA to manage future uncertainties. Early warning signals are produced for each scenario, serving as leading indicators to guide PAM JAYA’s direction.

Extension of a low-tech Model Predictive Control (MPC) algorithm for grid-supportive heat pump operation

This paper presents the further development of a low-tech Model Predictive Control (MPC) for the grid-friendly operation of heat pumps. The developed algorithm is already available in the literature [1] and successfully implemented in multiple buildings. The overall goal is, to predictively optimize comfort parameters taking into account weather forecast data for 48 h. A simple mathematical building model and an optimization function are used to calculate the heating (or cooling) requirement and determine the optimum heating (cooling) output curve over time.Based on the initial results, the algorithm is extended to include an energy price forecast. This modification enables the simultaneous optimization of comfort and heat supply costs. This forecast-based cost & comfort function is designed for the use of heat pumps in buildings with thermally activated components (TAB). The extension enables the MPC to process day-ahead electricity prices or other price signals in addition to weather forecast data. This means that the operation of heat pumps can be shifted to periods that are beneficial to the grid.The algorithm is analysed and validated in a Matlab/Simulink building simulation for a heating period of one sample month. A case study with different price scenarios is the main part of this paper. Depending on the assumed price fluctuation, the simulation leads to cost savings between 6.65 % and 12.5 % for the observation period of one month. The simulation results thus show that heat generation can be shifted to times with lower electricity prices, which leads to a significant reduction in heating costs without any significant loss of comfort. In conclusion, the developed low-tech MPC enables grid-supportive operation of heat pumps.

Методичні аспекти формування облікової політики товарів у системі управління підприємством

The article studies methodological aspects of accounting and controlling goods in enterprises to form an informational foundation for managerial decision-making. The study’s relevance is associated with the widespread nature of trade operations in enterprises across various sectors of economic activity. The statistical data analysis has proven that the volume of trade operations is increasing, and such operations are conducted across different economic sectors. The development of trade activities enhances the importance of goods in enterprise operations, thus underscoring the need to develop theoretical and methodological provisions for accounting and controlling goods. The purpose of the article is to systematize the theoretical and methodological foundations of goods accounting and control and to determine the role of these processes in an enterprise’s operations and overall management system. The role of accounting and control of goods in the management system of an enterprise’s activities is substantiated. It is determined that the quality development of such a system will facilitate the collection of timely and accurate information on inventory and serve as a tool for ensuring the enterprise’s financial stability. The existing methodological foundations of this process have been systematized to enable the development of a goods accounting system for enterprises. Regulatory acts governing the accounting and control of goods operations are summarized in two directions: external and internal. The main aspects of goods accounting regulated by the examined documents are characterized. The main elements of goods accounting policy, which serve as the foundation for forming information support for managerial decisions, are highlighted; thus, enterprise management must develop and coordinate them. The system of accounts for recording transactions involving enterprise goods is specified, along with the correspondence of accounts for reflecting such operations, including the documentary support for their representation. The necessity of goods control is substantiated, and the primary methods for its implementation are specified. The research results can be applied in the practical activities of enterprises to organize a system of accounting and control of goods. Keywords: information support, control, accounting, regulation, goods, managerial decisions.

Development of a fuzzy logic-based model for assessing the reliability of relay protection systems

This article presents a reliability assessment model for relay protection devices using fuzzy logic. It introduces an algorithm for simulating these devices, employing the Mamdani model with an "if-then" rule base. Inputs include the percentage of correct operation and the frequency of correct and incorrect operations. Implemented in Matlab with 21 rules, the fuzzy logic model uses triangular membership functions for input and output variables, with defuzzification via the center of gravity method. The model was tested using statistical data from SIEMENS SIPROTEC terminals, specifically distance protection and differential protection devices for transformers and autotransformers. The assessment considers operation frequencies for 1 to 3 devices, combining statistical and simulation data for a comprehensive analysis. Results show that including operation frequencies improves evaluation accuracy. The proposed model not only assesses current reliability but also predicts future behavior, aiding in the planning and optimization of relay protection systems. This model is valuable for professionals in generating companies, grid organizations, and operational dispatch control entities, helping them analyze relay protection performance and develop strategies to ensure reliable operation. The research focuses on the reliability of relay protection devices in power systems, addressing the need for a more accurate and comprehensive evaluation method. Traditional methods may not fully account for the complexities in modern microprocessor-based protections. This study aims to enhance reliability assessments through a model that integrates statistical data and simulation techniques, ultimately supporting better planning and optimization of relay protection systems

An approach to Molten Salt Reactor operation and control and its application to the ARAMIS actinide burner

Molten salt reactors (MSRs) are Generation IV nuclear reactor concepts gaining significant research interest worldwide. The present work proposes a methodology for the definition and optimization of the MSR operating conditions and control strategy. The proposed methodology employs a novel 0D steady-state model, the multi-physics system-scale MOSAICS (MOlten SAlt Incompressible Calculation System) model and a Global Sensitivity Analysis (GSA) method based on Hilbert-Schmidt Independence Criterion indices. The methodology was then applied to the ARAMIS (Advanced Reactor for Actinides Management in Salt) fast-spectrum chloride-salt burner reactor. Two alternative control strategies are proposed in order to achieve target margins to the salt freezing and structure material limit temperatures during normal operation, plus a 20 % power variation per minute load-following objective. The performance of the control strategies was assessed through comparison with the natural behavior during a load-increasing transient, as well as during Unprotected Transient Over-Power (UTOP) and Station Blackout (SBO) accidents. Controlled load variation transients are observed to reduce overall temperature variation rates throughout the salt circuits, while the inclusion of a variable fuel flow from the reactor commands can further limit these fluctuations. However, the selected operating conditions exhibited insufficient margins to freezing or the materials limit temperature under unprotected accident conditions. GSA enabled the derivation of correlations to characterize the dynamic response of MSRs to the accidents. Based on the observed reactor response to the various transients, potential modifications to the ARAMIS design and control strategies are proposed.

Implementation of a mathematical component in the device development for operational control of the dump truck

Implementation of a mathematical component in the device development for operational control of the dump truck

Highly sensitive protection scheme considering the PV operation control models

The integration of distributed generation (DG) based on inverters into power systems has increased significantly, necessitating a thorough understanding of its impact on fault analysis and the performance of distribution networks' protection mechanisms. This study addresses this issue by examining how various inverter management modes influence protective relay systems within IEEE 9-bus redial and mesh networks, CIGRE and IEEE 33-bus networks featuring Photovoltaic (PV) farms and Battery Energy Storage Systems (BESS), by IEEE1547–2018 and German grid code standards. By analyzing grid-connected scenarios with five distinct PV control modes, the research introduces a novel protection methodology termed the Photovoltaic Overcurrent Relay (PVOCR). This method introduces a current-voltage characteristic to optimally coordinate Overcurrent Relays (OCRs), aiming to reduce their operational time and eliminate mis-coordination events. The proposed PVOCR is evaluated against standard inverse time, SOCR, and modern adaptive voltage, VOCR, relay schemes across various fault scenarios differing in type and location. Furthermore, the PVOCR scheme effectively operates across all PV inverter modes without experiencing miscoordination events, whereas the SOCR and VOCR schemes encountered such issues during the operation of Control 4. These results underscore the potential utility of the PVOCR methodology in enhancing the reliability and efficiency of protection systems in inverter-based DG networks.

The effects of Cd2+ and Cu2+ on characteristics of soluble microbial products from activated sludge via altering expression of cellular metabolism pathways

The effect of heavy metals on soluble microbial products (SMPs) have been widely studied in the activated sludge system. However, their impact on the biofunctions of SMPs remain unclear, which could reflect state of cellular metabolism. In present work, we investigated toxic impact of Cd2+ and Cu2+ on properties of soluble microbial products (SMPs) and cellular metabolism activities via proteomics analysis and genotoxicity. The results indicated all sized fractions in SMPs have been increased by addition of Cd2+ or Cu2+ through altering several cellular metabolic pathways; especially for the appearance of Cu2+. The toxicity of Cd2+ impacted cellular substrate consumption, energy generation, and electron transport activities via changing metabolism and/or degradation of amino acid, while the addition of Cu2+ threated transfer of genetic information and cellular signals, energy generation and storage, and activity of enzymes via affecting metabolic activities of ribonucleic acid, purine, and pyrimidine. Meanwhile, ribosomes played essential roles in toxic resistance under Cd2+ shock, ATP-binding cassette (ABC) transporters functioned in toxic resistance under Cu2+ shock. In addition, the expression of functional genes grpE, dnaJ, ibpB, and ytfE were specially regulated by Cd2+ shock, and the expression of functional genes grxA, grxB, gst, ahpF, marC, dacB, and pbpG are particularly sensitive to the Cu2+ stress; which confirmed differences in cellular response activities under stressful conditions of toxic Cd2+ and Cu2+. Those findings provided key insights into how toxic metals change cellular metabolism at the molecular level, which would be meaningful to operational control and optimization of biological wastewater treatment.