Cluster Management Research Articles

Dynamic mathematical model for resource management and scheduling in cloud computing environments

The object of the research is resource management and scheduling in Kubernetes clusters, in particular, data centers. It was determined that in many publications dedicated to optimization models of scheduling for Kubernetes, mathematical models either do not include constraints at all, or only have the constraints determined on the high level only. The purpose of the research is the creation of a dynamic low-level mathematical optimization model for resource management and scheduling in cloud computing environments that utilize Kubernetes. Examples of such environments include the data centers where the customers can rent both dedicated servers and resources of shared hosting servers that are allocated on demand. The suggested model was created using the principles of creation of mathematical models of discrete (combinatorial) optimization, and was given the name “dynamic” because it takes the time parameter into account. The model receives data about individual servers in the cluster and individual pods that should be launched as an input. The model aims to regulate not only individual assignments of pods to nodes, but also turning on and off the servers. The model has objectives of: minimization of the average number of shared hosting servers running; maximization of the average resource utilization coefficient on such servers; minimization of the number of occasions when the servers are turned on and off; minimization of resource utilization by the pods that are running on shared hosting servers but created by the customers renting the dedicated servers. The model considers resource constraints, among other limitations.

To get through to survive: Exploring the symptom cluster management process during oncological treatment from the perspective of patients with lung cancer - A grounded theory study.

To explore the symptom cluster management process from the perspective of patients with lung cancer within the oncological care context. We used a constructivist grounded theory methodology to collect and analyze rich data from 15 patients with lung cancer via individual interviews and a two-dimensional symptom assessment scale. A situational theoretical model describes the symptom cluster management process through the main category 'To get through to survive', with the category 'Handling symptom clusters' together with six sub-categories concerning the patients' management strategies and the category 'Living with symptom clusters,' together with two sub-categories describing the outcome in their daily life. Impacting conditions are incorporated in the model. Patients often feel left to their own devices to deal with symptom clusters and may not understand or foresee problematic circumstances as they manage their situations on a day-to-day basis. When symptoms are normalized and accepted, patients do not ask for support, or support is not being offered to them. Healthcare professionals should consider the peril of normalizing symptoms and the patients' altered time perspective that stems from their approach of living one day at a time, in further development of nursing interventions and person-centered care for this population.

Integrating Lean Six Sigma and Industry 4.0 for advancing the circular economy: A holistic research study

ABSTRACT The value of Industry 4.0 (I4.0) production is often assessed without considering sustainability, leading to incomplete evaluations. The disconnect between quality management and circular economy principles hinders efforts to enhance resource efficiency. Additionally, the absence of holistic methodologies constrains the exploration of complex connections between quality elements and sustainability factors. This research proposes an integrated approach to measure the value of I4.0 production, emphasizing sustainability. It integrates circular economy principles into quality management to boost resource efficiency and reduce waste. The study uses Lean Six Sigma and the Delphi technique to identify and refine quality elements, which are then mapped alongside sustainability factors and indices using adapted interpretive structural modeling (AISM). The approach provides cluster managers with insights to enhance quality, resource efficiency, waste reduction, and sustainable practices, fostering a paradigm shift toward sustainability in manufacturing ecosystems.

Factors influencing the entry of logistics service providers (LSPs) into the logistics clusters: a case study of Casablanca city

PurposeIn recent years, the concept of logistics cluster has attracted the attention of several researchers and practitioners. It is an agglomeration of different types of companies and operations: notably, those providing logistics services, such as supply chain organization, storage and distribution. The paper focuses on this concept by examining the factors influencing logistics service providers (LSPs) to enter the logistics clusters.Design/methodology/approachAn exploratory qualitative study based on semi-structured interviews was conducted. Regarding the sample size, the author interviewed 31 professionals belonging to logistics clusters located in the Moroccan economic metropolis: Casablanca.FindingsThe results show that the cost reduction, the reputation of the cluster, the learning from other LSP, the communal services, the geographical proximity, and the role of public authorities are the main factors impacting the entry of LSPs into these clusters.Practical implicationsThe findings of this study provide several practical insights for LSPs, government authorities, and cluster managers. For LSPs, understanding the key factors influencing their entry into logistics clusters—such as cost reduction, proximity and the role of public authorities—enables them to make strategic decisions that optimize their operations and enhance competitiveness. For cluster managers, the study highlights the importance of maintaining a strong cluster reputation and fostering collaboration between LSPs to attract new entrants. Finally, public authorities can leverage the insights to design policies that incentivize LSPs to join clusters by providing infrastructure, financial support and governance structures that align with industry needs.Originality/valueThis theme has never been investigated. Therefore, this research expands the literature review and tries to examine this gap of literature by studying the factors that can affect the adhesion of LSPs to these clusters.

Кластерне управління проєктами: підходи, виклики та перспективи

The article examines cluster project management as a modern innovative approach to organizing and coordinating projects. It establishes that cluster management is based on the consolidation of interrelated projects into clusters for the joint use of resources, enhancing the efficiency of innovative potential utilization, and stimulating innovation. Cluster management allows for resource optimization, improved communication, the development of synergy between projects, and decision-making flexibility. The article analyzes the main types of clusters, including geographical, sectoral, vertical, and horizontal, and their impact on the success of project management and the productivity of individual projects. It also discusses the key advantages of cluster management, including resource optimization, improved coordination among participants, increased overall productivity, and flexibility. The study reveals that the cluster approach helps reduce costs, avoid duplication of efforts, promotes rapid market response, and allows organizations to effectively adapt to market challenges. In addition to the advantages, the article highlights the challenges organizations face when applying the cluster approach. These include the need to adapt to external changes, competition among cluster participants, and intellectual property protection, which can pose a threat to innovation. A new approach to cluster project management is proposed, which integrates vertical and horizontal clusters with modern digital technologies, such as monitoring and management tools. This approach enhances the effectiveness, resilience, and innovativeness of projects in the context of globalization and digitalization. The article also explores successful examples of clusters, such as the Silicon Valley technology cluster and the California wine cluster, which illustrate the benefits of collaboration within a cluster system. The article emphasizes the importance of flexibility and continuous updating of management methodologies to ensure the success of clusters in today's competitive environment.

Guidelines for peri-discharge management and follow-up of acute exacerbations of chronic obstructive pulmonary disease(2024 edition)

Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are important events in the course of chronic obstructive pulmonary disease(COPD), and its diagnosis, treatment and prevention are the focus of disease management. Optimizing the peri-discharge management of AECOPD will help to improve continuity of care, prevent recurrence of acute events in the short time, and improve long-term prognosis. In recent years, evidence on the peri-discharge period and the cluster management of AECOPD has accumulated, and confirming the benefit of early follow-up and management after discharge. By reviewing the available evidence, this guideline aims to standardize discharge management and follow-up pathways for AECOPD patients. This guideline is intended for physicians and nursing staff involved in the clinical practice of COPD.

СПЕЦИФИКИ В УПРАВЛЕНИЕТО НА КЛЪСТЕРИТЕ В СРАВНЕНИЕ С ТОВА НА ИНДИВИДУАЛНИТЕ ОРГАНИЗАЦИИ

The report presents the particularities in the management of clusters compared to individual companies. It examines three important aspects in which the approach to leadership differs. A comparative analysis is made of the specifics of the management of cluster organizations, compared to that of individual companies in nine main directions. Attention is paid to their structure, focus, activity, influence and impact. It is concluded that the distinction between the management of a cluster and that of a company is crucial, as they represent different operational units with different objectives and dynamics.

Full-scale simulation of a 372 kW/372 kWh whole-cluster immersion cooling lithium-ion battery cluster and battery thermal management system design

The battery thermal management system (BTMS) is a necessary consideration to ensure the efficiency, safety, and reliability of battery energy storage systems (BESS). Immersion cooling, with its high heat transfer efficiency and uniform heat distribution, is emerging as the trend in BTMS. This study investigated a 372 kW/372 kWh BESS utilizing the immersion cooling technique, where the entire cluster of batteries is immersed in a coolant. The large-full-scale simulation model is established to analyze the flow and temperature performance. 3 types of immersion coolant are compared, which are 10# transformer oil (DF1), silicone oil-5cSt (DF2), and natural ester RAPO (DF3). The conclusion shows that DF2 is the optimal immersion liquid for the battery cluster, for the lowest average temperatures, which are 26.30 °C and 36.91 °C during 0.5 P and 1 P discharge, respectively. Based on the temperature uniformity index (UTave,s), DF1 represents the best temperature uniformity, with the value of 0.034 and 0.047 during 0.5P and 1P discharge, respectively. Because of the high viscosity of DF3, it achieves the highest system pressure drop and the worst temperature uniformity, which shows that DF3 are not suitable to be selected as immersion coolant.

Portfolio practices in the principal evaluation process: A qualitative case study

BackgroundThe portfolio is a vital component of the evaluation of principals and serves as a repository of evidence of achievements, skills, and capabilities. It facilitates the meticulous recording and documentation of experiences undertaken. Furthermore, the portfolio is instrumental in the refinement of conceptual ideas over time, while simultaneously offering a panoramic vista of a school's operational ethos and its alignment with professional benchmarks. ObjectiveThis study delves into the practices surrounding the principal portfolio and the formative and summative evaluation of principals by their evaluating supervisors. It aims to uncover principals’ perceptions regarding the obligatory nature of portfolios and other evaluative methodologies throughout both assessments. In light of the pivotal role that portfolios occupy in the realm of professional development and evaluation for school principals, the Abu Dhabi Education Council has mandated the compilation of principal portfolios within public schools. This mandate requires a detailed accounting of principals' proficiencies, achievements, and developmental trajectories. Markedly, this exploration stands as one of a scant number of inquiries probing the application of portfolios by school principals, with a particular focus on the context of the United Arab Emirates. It is poised to enrich the discourse on the utility of portfolios as instrumental tools for fostering leadership acumen and evaluative competency within the spheres of educator and principal preparation over the preceding two decades. The critical examination of these practices is vital for a nuanced understanding of their operational dynamics, the efficacy and challenges of e-portfolios, the array of opportunities they unveil, the identities of the involved stakeholders, and their ultimate objectives. MethodsThis study adopted a qualitative research approach to gather and analyze non-numerical data in the form of concepts, opinions, and experiences presented by principals and their supervisors within the Al-Ain School District (overseen by the Abu Dhabi Education Council)). The cohort of participants comprised nine individuals endowed with extensive portfolio experience, six principals and three cluster managers. All worked in public educational institutions and were meticulously selected based on predefined criteria. This study relied on several data collection methods to obtain participants’ perspectives on their experiences with portfolio practices, including face-to-face interviews and documents from their portfolios. ResultsA thematic analysis of the participant data yielded five salient themes reflecting the experiences of the principals: (1) inconsistent expectations for portfolio evidence; (2) portfolios summoned in response to rising tensions at the summative evaluation; (3) portfolios promoting reflective practices in formative evaluation; (4) portfolios susceptible to manipulation or falsification; and (5) excessive time spent building and developing portfolios. In order to maximize the utility of portfolios, this result invites school principals to unleash the latent potential inherent in their actions by leveraging portfolios as mirrors for reflective leadership and ongoing self-assessment. ConclusionsThis research delineates both practical and theoretical ramifications for the application of professional portfolios. It elucidates the nature of evidence principals ought to incorporate within their portfolios. Furthermore, it endeavors to better inform principals of the evidence collection process, including what artifacts and documentation to gather and how to do so.

A two-layer strategy for sustainable energy management of microgrid clusters with embedded energy storage system and demand-side flexibility provision

The intermittent nature of renewable energy generation and the fluctuating demands pose persistent challenges in microgrid operations. In response, stakeholders and operators have turned to clustering the geographically adjacent microgrids as a solution. In this context, this paper introduces a novel two-layer energy management strategy for microgrid clusters, utilizing demand-side flexibility and the capabilities of shared battery energy storage (SBES) to minimize operational costs and emissions, while ensuring a spinning reserve within individual microgrids to prevent load-shedding. In the lower layer, the proposed approach devises optimal day-ahead operation policies, while the upper layer employs a cooperative strategy to further optimize the operational efficiency across the entire cluster. The energy management problem is accurately formulated as a mixed integer quadratic programming (MIQP) optimization, which incorporates linear terms in the problem's constraints. The formulation accounts for operational costs associated with SBES including expenses of charging/discharging and changes in operating states (CiOS). Real-world case studies with a cluster of three microgrids in Australia validate the effectiveness of this approach. Results show a reduction in operational costs for the base case scenario by 6.96 % compared to conventional microgrid management strategies. Sensitivity analyses further demonstrate the economic benefits of varying SBES capacity and flexibility pricing, with savings ranging from 6.5 % to 8.1 %. The proposed strategy also reduces CO2 emissions by up to 11.6 %, while improving system reliability. This strategy holds promise for integration into distributed energy systems with high renewable penetration and clustered local grids, offering significant advantages for utility operators and end-users through improved energy efficiency and reduced emissions.

АУДИТ ВПРОВАДЖЕННЯ РИНКОВОЇ ІНФРАСТРУКТУРИ В УПРАВЛІННІ КЛАСТЕРАМИ

The article discusses the issue of the audit of the implementation of market infrastructure in the management of clusters, which is a key factor for increasing the efficiency and competitiveness of modern economic systems. Special attention is paid to the analysis of the role of market infrastructure in the development of cluster formations, which contributes to the synergistic effect, the unification of enterprises, scientific institutions and other business entities to achieve common economic goals. The purpose of the study is to carry out a comprehensive analysis of the implementation of market infrastructure in the management of clusters and determine its impact on the effectiveness of the functioning of cluster formations in Kyrgyzstan. The main attention is paid to the assessment of infrastructural components, such as logistics, financial services, information technology and institutional support, which ensure the competitiveness and sustainable development of clusters in the conditions of the modern economy. The object of the study is auditing methods and approaches used to assess the effectiveness and risks of innovative processes of introducing market infrastructure during cluster management. Research methods: logical and meaningful method, methods of comparison, systematization, induction and deduction, analysis and synthesis, coefficient method. The main hypothesis of the follow-up. Effective implementation of market infrastructure in the management of clusters has a positive effect on their competitiveness and ability to adapt to changes in the economic environment. The lack of proper infrastructure or its shortcomings can significantly limit the potential of clusters in achieving a synergistic effect and ensuring economic growth. Present of the main material. The authors highlight methodological approaches to the audit of market infrastructure, including the analysis of key indicators such as logistics and information networks, financial and credit institutions, as well as government support mechanisms. The importance of conducting an audit to identify problematic aspects that prevent the efficient functioning of clusters and to develop recommendations for their elimination is substantiated. Originality and practical significance. The study also presents the results of the analysis of the impact of the introduction of market infrastructure on the competitiveness of clusters and their ability to adapt to changes in the global economic environment. The issue of integration of cluster strategies with regional and national economic plans was separately considered. On the basis of empirical data, conclusions are drawn regarding the effectiveness of infrastructure changes and practical recommendations for improving cluster management are offered. Conclusions and prospects for further research. The results of the audit show that the market infrastructure is a key element that contributes to the development of clusters, ensuring effective interaction between the participants of the cluster association, improving their productivity and competitive advantages. Implementation of infrastructure components, such as modern information and communication technologies, financial institutions and logistics networks, is crucial for improving the efficiency of cluster management.

Surviving Sepsis Campaign guideline update:problems and progress

Sepsis is a clinical syndrome, the core of which is the disorder of the host's response to infection. Sepsis progresses to septic shock, which can lead to increased mortality, so early identification and standardized management are particularly important. Over the past 30 years, the definition of septic shock has gradually changed, with efforts to improve the identification and screening of early septic shock, and to emphasize the importance of organ dysfunction in patients with septic shock. The birth of the rescue systemic infection movement has played an important role in the management of septic shock patients. Although the cluster management of septic shock patients has reduced the overall mortality of septic shock patients, the management still faces many challenges. How to provide personalized treatment to patients, especially some controversial treatments, is still a major area for us to consider and explore.

CN90 “To get through to survive”: Exploring the symptom cluster management process during oncological treatment from the perspective of patients with lung cancer

CN90 “To get through to survive”: Exploring the symptom cluster management process during oncological treatment from the perspective of patients with lung cancer

Exploring spatio-temporal dynamics for enhanced wind turbine condition monitoring

Efficient wind power cluster management and sustainable industry development require an optimized maintenance approach integrating condition monitoring. However, the intricate spatiotemporal correlations and non-stationarity of the data continue to pose significant challenges in extracting valuable insights from the supervisory control and data acquisition (SCADA) system. Hence, this paper proposes a novel approach for Dynamically Fusing Spatio-Temporal information with Difference Excitation (DFST-DE) in wind power systems’ condition monitoring. First, it extracts spatial dependencies by integrating sparse graph structures with Gumbel Softmax regularization and incorporates temporal information using a hybrid adaptive self-attention mechanism. This combined approach effectively captures comprehensive spatiotemporal correlations. Second, it proposes a Spatio-Temporal Difference Excitation module to mitigate non-stationarity in time series data by smoothing trend changes. The proposed DFST-DE approach achieves superior performance by effectively fusing spatial, temporal and excitation information. Finally, it optimizes anomaly detection accuracy and efficiency by dynamically adjusting the threshold based on anomaly score statistics. Experimental results on real-world wind farm datasets demonstrate that the proposed approach outperforms other established methods in detecting early abnormal conditions in wind turbines.

The impact of antenatal cluster management on maternal delivery and postpartum rehabilitation

ObjectivePregnancy care can improve maternal pregnancy outcomes. Cluster nursing, an evidence-based, patient-centered model, enhances pregnancy care, can provide patients with high-quality nursing services, has been widely used in clinical practice in recent years. However, most previous studies evaluated cluster nursing program only for a single clinical scenario. In this study, we developed and implemented a antenatal cluster care program for various prenatal issues faced by puerpera to analyze its application effect.MethodsThis is a historical before and after control study. 89 expectant mothers who had their prenatal information files registered in the outpatient department of a grade III, level A hospital from June 2020 to September 2021 were finally enrolled in observation group, and received prenatal cluster management. Another set of 89 expectant mothers from January 2019 to December 2019 were included in the control group and received traditional routine prenatal management. The effect of cluster nursing management on maternal delivery and postpartum rehabilitation was evaluated and compared between the two groups.ResultsCompared with the control group, the observation group had a significantly higher natural delivery rate, better neonatal prognosis, higher rates of exclusive breastfeeding, lower incidence of postpartum complications, shorter postpartum hospital stay, better postpartum health status, and higher satisfaction with nursing services. Compared with before intervention, the SAS and SDS scores of the observation group showed significant improvement after intervention.ConclusionAntenatal cluster care is beneficial to improve maternal and neonatal outcomes, and can have positive effects on natural pregnancy and breastfeeding, while improving the multimedia health education ability of medical care and emphasizing the importance of social support.

On the Optimization of Kubernetes toward the Enhancement of Cloud Computing

With the vigorous development of big data and cloud computing, containers are becoming the main platform for running applications due to their flexible and lightweight features. Using a container cluster management system can more effectively manage multiocean containers on multiple machine nodes, and Kubernetes has become a leader in container cluster management systems, with its powerful container orchestration capabilities. However, the current default Kubernetes components and settings have appeared to have a performance bottleneck and are not adaptable to complex usage environments. In particular, the issues are data distribution latency, inefficient cluster backup and restore leading to poor disaster recovery, poor rolling update leading to downtime, inefficiency in load balancing and handling requests, poor autoscaling and scheduling strategy leading to quality of service (QoS) violations and insufficient resource usage, and many others. Aiming at the insufficient performance of the default Kubernetes platform, this paper focuses on reducing the data distribution latency, improving the cluster backup and restore strategies toward better disaster recovery, optimizing zero-downtime rolling updates, incorporating better strategies for load balancing and handling requests, optimizing autoscaling, introducing better scheduling strategy, and so on. At the same time, the relevant experimental analysis is carried out. The experiment results show that compared with the default settings, the optimized Kubernetes platform can handle more than 2000 concurrent requests, reduce the CPU overhead by more than 1.5%, reduce the memory by more than 0.6%, reduce the average request time by an average of 7.6%, and reduce the number of request failures by at least 32.4%, achieving the expected effect.

P2P power trading based on reinforcement learning for nanogrid clusters

In this paper, a novel peer-to-peer (P2P) power trading for power management of nanogrid clusters with renewable energy sources is presented. Unlike power management of smart grids in megawatt power scale, power management of nanogrids in kilowatt power scale requires individual control of electric appliances. P2P trading is characterized by complex elements such as decentralized architecture, participant behaviors, and distributed energy resources. To this end, multi-objective optimization providing Pareto-optimal solutions is applied to the power management of nanogrid clusters capable of P2P trading. The P2P power trading aims at maximizing the profit as well as minimizing the grid power consumption. However, due to the conventional rule for P2P trading and trade-off property of Pareto-optimal solution, the result of P2P trading is not optimal. To improve the performance of P2P trading in terms of total electricity cost, reinforcement learning (RL) algorithms are introduced. For RL, deep neural networks are applied to P2P power trading. The RL agent of each nanogrid cluster learns the behavior of P2P trading and then fulfills P2P trading. In the proposed RL technique, graph convolutional network is employed for analyzing graph-structured data, and bidirectional long short-term memory network is utilized for data prediction, enhancing the performance of P2P trading. It is found from simulations of power management for nanogrid clusters that the electricity cost with the proposed RL technique is the lowest among the RL algorithms considered for benchmark test. The electricity cost is reduced by 36.7%, averaged over ten nanogrid clusters, as compared to the electricity cost obtained from power management without RL algorithms.

Modeling and optimization of costs associated with the development of clustered organizational management structures in construction companies

The article aims to examine models and methods of cost optimization associated with the development of clustered organizational structures in construction companies. The research methodology involved an analysis of existing approaches, simulation modeling, and econometric equation analysis. As a result, different approaches to cost estimation and optimization applied in the construction sphere are presented. Particular attention is paid to the development of complex models and their optimization under the conditions of uncertainty through simulation modeling of various scenarios of cluster organizational structures in construction companies. The analysis also includes an assessment of the advantages and disadvantages of econometric semi-linear dynamic equations and the feasibility of their application. The discussion section emphasizes the importance of integrating different optimization methods to achieve the most optimal outcome in the management of construction companies. Further research directions are outlined. The results can be relevant when formulating development strategies and making investment decisions in the construction sphere. The research conclusions confirm the significance of applying modern cost optimization methods to improve the management efficiency of construction companies and their competitiveness in the market of construction services.

Graph Theoretical Models for Enhancing Highway Connectivity and Safety in Vehicular Networks

Vehicular networks play a crucial role in modern transportation systems, significantly impacting connectivity and safety on highways. This paper explores the application of graph theoretical models to enhance both connectivity and safety in vehicular networks. Graph theory, a branch of discrete mathematics, provides a robust framework for modeling and analyzing complex networks, including those formed by vehicles on highways. Our study begins by defining the vehicular network as a graph where nodes represent vehicles, and edges denote communication links between them. We employ various graph theoretical concepts such as connectivity, centrality, and network flow to evaluate and improve the network's performance. Key metrics, including the degree of nodes, clustering coefficients, and shortest path lengths, are utilized to quantify network connectivity and identify critical nodes and edges that influence overall network efficiency. One of the primary objectives is to ensure uninterrupted connectivity in the presence of dynamic and often unpredictable vehicular movement. To this end, we analyze the network's resilience to node failures and propose strategies to enhance robustness using redundancy and alternative routing paths. By incorporating concepts like k-connectivity and network diameter, we develop models that maintain high levels of connectivity despite the removal or failure of multiple nodes or edges. Safety is addressed through the lens of network stability and reliability. We investigate the impact of vehicular density, speed, and communication range on the network's ability to sustain reliable communication channels. Techniques such as dynamic topology management and adaptive power control are proposed to mitigate the risks associated with network fragmentation and communication delays. Furthermore, we introduce optimization algorithms that leverage graph partitioning and community detection to improve the management of vehicular clusters, facilitating efficient data dissemination and reducing the likelihood of congestion-related incidents. The proposed models are validated through simulations that mimic real-world highway conditions, demonstrating significant improvements in both connectivity and safety metrics. In conclusion, the application of graph theoretical models offers a promising approach to enhancing highway connectivity and safety in vehicular networks

Outpatient management of prolonged seizures and seizure clusters to prevent progression to a higher-level emergency: Consensus recommendations of an expert working group.

The management of prolonged seizures (PS) and seizure clusters (SC) is impeded by the lack of international, evidence-based guidance. We aimed to develop expert recommendations regarding consensus definitions of PS, SC, and treatment goals to prevent progression to higher-level emergencies such as status epilepticus (SE). An expert working group, comprising 12 epileptologists, neurologists, and pharmacologists from Europe and North America, used a modified Delphi consensus methodology to develop and anonymously vote on statements. Consensus was defined as ≥75% voting "Agree"/"Strongly agree." All group members strongly agreed that termination of an ongoing seizure in as short a time as possible is the primary goal of rapid and early seizure termination (REST) and that an ideal medication for REST would start to act within 2 min of administration to terminate ongoing seizure activity. Consensus was reached on the terminology defining PS (with proposed thresholds of 5 min for prolonged focal seizures and 2 min for prolonged absence seizures and the convulsive phase of bilateral tonic-clonic seizures) and SC (an abnormal increase in seizure frequency compared with the individual patient's usual seizure pattern). All group members strongly agreed or agreed that patients who have experienced a PS should be offered a REST medication, and all patients who have experienced a SC should be offered an acute cluster treatment (ACT). Further, when prescribing a REST medication or ACT, a seizure action plan should be agreed upon in consultation with the patient and caregiver. The expert working group had a high level of agreement on the recommendations for defining and managing PS and SC. These recommendations will complement the existing guidance for the management of acute seizures, with the possibility of treating them earlier to potentially avoid progression to more severe seizures, including SE.