Critical Systems Research Articles

Enhancing collaborative advantage through critical systems thinking: An augmented viable system model intervention in a cross‐sector partnership social policy context

AbstractCross‐sector partnerships are essential for addressing wicked problems but are typically ineffective because of messy human and organisational dynamics. Systemic approaches are needed to re‐design collaborations for a collaborative advantage. While the Viable System Model (VSM) is suited to this task, little guidance is provided on managing multiple perspectives or marginalisation in VSM interventions. Hence, we trial and evaluate the utility of a novel multimethodology approach combining the VSM with Team Syntegrity (TS), which is a workshop protocol for supporting fair dialogue and stakeholder pluralism. Our findings show this combination supports joined‐up thinking about improvements for viability and synergies from combining these methodologies. We propose that before a VSM diagnosis, an understanding of ‘what a system does’ and existence of VSM functions is established to ensure more meaningful selection of intervention participants and consideration of the VSM's insights. We also identify four avenues for marginalisation that need careful consideration in critical systems interventions.

Blockchain Integration in Critical Systems Enhancing Transparency, Efficiency, and Real-Time Data Security in Agile Project Management, Decentralized Finance (DeFi), and Cold Chain Management

Blockchain technology has garnered significant attention for its potential to revolutionize critical systems by enhancing transparency, efficiency, and data security. This review examines the integration of blockchain in three essential domains: Agile Project Management, Decentralized Finance (DeFi), and Cold Chain Management. By leveraging decentralized ledgers and smart contracts, blockchain provides a robust framework for real-time tracking, data integrity, and automated compliance, addressing long-standing challenges across these sectors. In Agile Project Management, blockchain fosters seamless collaboration and transparent decision-making, minimizing bottlenecks and improving accountability. In DeFi, blockchain strengthens security for digital transactions and identity verification while offering financial autonomy and mitigating fraud risks. Within Cold Chain Management, blockchain ensures traceability, reduces data tampering risks, and enhances visibility throughout supply chain processes, safeguarding temperature-sensitive goods. This paper evaluates existing blockchain-based applications and frameworks, identifies current limitations, and discusses future opportunities for optimizing critical systems through blockchain. The findings highlight blockchain's transformative role in driving operational efficiency, security, and data transparency across diverse applications, providing a roadmap for industries to harness its full potential in critical environments.

Robustness Analysis of Multilayer Infrastructure Networks Based on Incomplete Information Stackelberg Game: Considering Cascading Failures

The growing importance of critical infrastructure systems (CIS) makes maintaining their normal operation against deliberate attacks such as terrorism a significant challenge. Combining game theory and complex network theory provides a framework for analyzing CIS robustness in adversarial scenarios. Most existing studies focus on single-layer networks, while CIS are better modeled as multilayer networks. Research on multilayer network games is limited, lacking methods for constructing incomplete information through link hiding and neglecting the impact of cascading failures. We propose a multilayer network Stackelberg game model with incomplete information considering cascading failures (MSGM-IICF). First, we describe the multilayer network model and define the multilayer node-weighted degree. Then, we present link hiding rules and a cascading failure model. Finally, we construct MSGM-IICF, providing methods for calculating payoff functions from the different perspectives of attackers and defenders. Experiments on synthetic and real-world networks demonstrate that link hiding improves network robustness without considering cascading failures. However, when cascading failures are considered, they become the primary factor determining network robustness. Dynamic capacity allocation enhances network robustness, while changes in dynamic costs make the network more vulnerable. The proposed method provides a new way of analyzing the robustness of diverse CIS, supporting resilient CIS design.

Societal Impact of Test Automation: Reducing Human Error in Critical Systems

This article explores the profound societal impact of test automation across critical sectors such as healthcare, finance, transportation, and energy. It examines how automated testing processes significantly reduce human error, enhance system reliability, and improve service quality. The article presents compelling evidence from various studies and reports, demonstrating substantial improvements in medical diagnostics, financial fraud detection, transportation safety, and energy distribution efficiency. Beyond error reduction, the article discusses broader societal benefits, including enhanced accuracy in data processing, faster emergency response times, improved service quality, and strategic resource allocation. The article underscores the crucial role of test automation in addressing the challenges posed by increasingly complex technological systems and its far-reaching implications for public safety, economic stability, and overall quality of life.

Fast Identification of Critical Nodes in Complex Network Based on Improved Greedy Algorithm

Abstract Over the past decades, many critical and complex systems, such as power grid, transportation network, and information network, have been effectively modeled using complex network. However, these networks are susceptible to cascading failure, triggered by minor failure, leading to partial or total collapse. Preventing cascading failure necessitates the protection of critical nodes within the network, making the identification of these nodes particularly crucial. In this paper, we introduce an Improved Greedy Algorithm (IGA), inspired by the traditional greedy algorithm and the relationship between the propagation mechanism of cascading failure and N-K failure. This algorithm gets rid of the shortcomings of traditional recognition algorithms for dealing with large-scale networks with long time and low accuracy, and evaluates the critical degree of nodes based on network connectivity and overload rate. The simulation is carried out in Barabsi-Albert (BA) network and IEEE 39-, 118-bus systems, and make comparisons with other different algorithms. The results show that IGA not only has low computational complexity, but also has high accuracy in identifying critical nodes in complex networks.

Case Study of an Integrated Design and Technical Concept for a Scalable Hyperloop System

This paper presents the design process and resulting technical concept for an integrated hyperloop system, aimed at realizing efficient high-speed ground transportation. This study integrates various functions into a coherent and technically feasible solution, with key design decisions that optimize performance and cost-efficiency. An iterative design process with domain-specific experts, regular reviews, and a dataset with a single source of truth were employed to ensure continuous and collective progress. The proposed hyperloop system features a maximum speed of 600 kmh and a capacity of 21 passengers per pod (vehicle). It employs air docks for efficient boarding, electromagnetic suspension (EMS) combined with electrodynamic suspension (EDS) for high-speed lane switching, and short stator motor technology for propulsion. Cooling is managed through water evaporation at an operating pressure of 10 mbar, while a 300 kW inductive power supply (IPS) provides onboard power. The design includes a safety system that avoids emergency exits along the track and utilizes separated safety-critical and high-bandwidth communication. With prefabricated concrete parts used for the tube, construction costs can be reduced and scalability improved. A dimensioned cross-sectional drawing, as well as a preliminary pod mass budget and station layout, are provided, highlighting critical technical systems and their interactions. Calculations of energy consumption per passenger kilometer, accounting for all functions, demonstrate a distinct advantage over existing modes of transportation, achieving greater efficiency even at high speeds and with smaller vehicle sizes. This work demonstrates the potential of a well-integrated hyperloop system to significantly enhance transportation efficiency and sustainability, positioning it as a promising extension to existing modes of travel. The findings offer a solid framework for future hyperloop development, encouraging further research, standardization efforts, and public dissemination for continued advancements.

Feasibility and Safety of Targeted Temperature Management During Interhospital Transport of Post-Cardiac Arrest Patients

Objectives Early initiation of targeted temperature management (TTM) is crucial for post-resuscitation care. Although TTM is initiated prior to transport and continued during interhospital transport (IHT), its feasibility and safety during IHT for cardiac arrest patients have not been thoroughly assessed. This study aims to evaluate the feasibility and safety of interhospital TTM for post-resuscitation patients. Methods A retrospective analysis of post-cardiac arrest patients transported by a dedicated critical care transport team between January 2016 and April 2023 was conducted. Adult patients resuscitated from cardiac arrest without mental recovery were enrolled. The study population was divided into those who received TTM during IHT (IHT-TTM group) and those who did not (non-IHT-TTM group). The primary outcome was body temperature drop during transport, with hypotension, or desaturation during transport considered as secondary outcomes. Multivariable conditional logistic regression analysis was performed after frequency matching. Results Among 593 post-cardiac arrest patients, 332 were included in the analysis after exclusions. Of these, 44 (13.3%) received TTM during IHT. Conditional logistic regression analysis showed significantly higher likelihood for a drop in body temperature during IHT for the IHT-TTM group, with an odds ratio (OR) of 12.91 (95%CI: 5.28–31.53). No significant association was found for hypotension (OR (95%CI): 0.72 (0.13–3.97)), or desaturation during IHT (0.65 (0.15–2.82)). Conclusions Administration of TTM during IHT for post-cardiac arrest patients appears to be feasible and safe. These findings support the implementation of dedicated critical care transport systems capable of providing TTM during IHT for post-cardiac arrest patients.

Performance of vibration and current signals in the fault diagnosis of induction motors using deep learning and machine learning techniques

Induction motors (IMs) play a pivotal role in various industrial applications, powering critical systems such as pumps, compressors, fans, blowers, and refrigeration and air conditioning systems. Monitoring the health of these IMs is essential for ensuring reliable operation. Numerous sensors, including vibration, current, temperature, acoustic, and power sensors, can be employed for their health monitoring. This article conducts a comprehensive comparative analysis of two widely used sensors—vibration and current, for classifying different health states of IMs, such as a healthy condition, bearing fault, and misalignment. The study employed deep learning techniques, specifically 1D and 2D convolutional neural networks, trained on raw data. Additionally, machine learning techniques, including random forest and XGBoost, were utilized and trained on features derived from preprocessed signals using fast Fourier transform and discrete wavelet decomposition. Comparative results indicated that vibration signals achieved remarkably high accuracy, nearly 100%, in detecting the investigated mechanical faults, while current signals, after signal processing and manual feature extraction, achieved an accuracy of 87.41%. These results demonstrate that, though current sensors are a viable alternative to vibration sensors, their performance can be affected by the type and degree of the considered faults. This study also highlights the attributes of vibration and current signals in the health monitoring of rotating machinery such as IMs.

Why health systems cannot fix problems caused by food systems: a call to integrate accountability for obesity into food systems policy.

Overweight and obesity now impact one-third of the entire adult population globally, and play a role in the development of 3 of the 4 more common causes of death. Accountability systems for obesity prevention centring on food environment policies and health system strengthening have been vital for raising awareness to the lack of progress in prevention. However, health systems have struggled to prevent and treat obesity - in part because critical food systems reforms largely lay outside the mandate of health sectors and with government agencies for agriculture, industry, infrastructure, trade and investment, and finance. In this commentary we highlight aspects of food systems that are driving poor diets and obesity, and demonstrate a powerful but largely overlooked opportunity for accountability mechanisms for obesity that better address food systems as a main driver. We draw on lessons generated in the Pacific Islands Region where they have demonstrated remarkable commitment to obesity prevention through food system reforms, and the adoption of accountability systems that bring leaders to account on these. We make recommendations for accountability mechanisms that facilitate greater cooperation of food systems sectors on obesity and NCD prevention.

Quantum steering ellipsoids and quantum obesity in critical systems

Abstract Quantum obesity (QO) is a novel function introduced to quantify quantum correlations that go beyond traditional measures like entanglement, while also functioning as an entanglement witness. One of the key strengths of QO lies in its analyticity for arbitrary states of bipartite systems, making it a more accessible and versatile tool compared to other measures of quantum correlations, such as quantum discord. In this work, we highlight the importance of QO as a fundamental quantity for identifying signatures of quantum phase transitions, which are critical changes in the ground state of quantum systems driven by quantum fluctuations. We introduce a mechanism based on local filtering operations designed to enhance the critical behavior of QO near phase transition points, providing a deeper understanding of these phenomena. Furthermore, we present a theorem that characterizes how QO transforms under local quantum operations and classical communications (LOCC), which broadens its applicability to a wider range of quantum systems. This opens new avenues for exploring quantum criticality and other novel quantum phenomena by leveraging the analytically computable, pairwise QO, thus offering both theoretical insights and practical applications in quantum information science.

Stable silicon isotope fractionation reflects the routing of water through a mesoscale hillslope

Concentration - isotope Ratio - Discharge (C-R-Q) relationships offer a promising means of disentangling the underlying hydrologic, geochemical, and ecological factors that produce variations in stream solute chemistry across a variety of critical zone systems. However, natural environments are both temporally and spatially complex, and prevailing interpretations of these C-R-Q patterns remain difficult to validate. Here we employ three replicate artificially constructed hillslopes at the Landscape Evolution Observatory (LEO) in Tucson, Arizona as simplified analogs to natural catchments. LEO allows us to record silicon stable isotope (δ30Si) signatures of fluid discharge under a controlled irrigation schedule in a system devoid of vegetation. This unique meso‑scale experiment enables, for the first time, evaluation of metalloid stable isotope signatures at the scale of natural hillslopes constrained to known fluid transit time distributions (TTDs) and limited to fractionation in association with secondary mineral formation. We report δ30Si in discharge samples collected over three randomized storm events of varying intensity. The data reflect consistent enrichment in the fluid phase between +1.00 and +2.07 ‰ across the three hillslopes, despite highly variable irrigation scenarios, reflecting substantial loss of SiO2 from solution due to secondary mineral precipitation. We compare results from an isotope-enabled Reactive Transport Model (RTM) and the discharge measurements from LEO to constrain the contributions of both characteristic watershed TTDs and fractionation pathways in emergent δ30Si signatures. Our study confirms and expands upon recent work in natural systems attributing intra-site variability in silicon stable isotope signatures to the routing of fluid through catchments.

SPIKE-Dx

Diagnostic systems are important for many aerospace systems, which are severly limited in available power, like cubesats or UAVs. Therefore, traditional diagnostics systems cannot be used due to their substantial footprint and constraints. In this paper, we present our very low power diagnostic tool SPIKE-Dx. to monitor critical systems with constrained computational and energy resources. This is made possible through spiking neural networks (SNNs), which are executable within optimized simulation environments and further implemented on on cutting-edge neuromorphic hardware. Based upon FMEA (Failure Mode and Effect Analysis) framework, Diagnostic Bayesian Networks (DBNs) can be constructed that provide powerful means for diagnostic reasoning. In this paper, we describe such DBNs and a method to automatically translate the DBN into highly structured networks of spiking neurons for execution in SPIKE-Dx.

Efficient quantum circuits based on the quantum natural gradient

Efficient preparation of arbitrary entangled quantum states is crucial for quantum computation. This is particularly important for noisy intermediate-scale quantum simulators relying on variational hybrid quantum-classical algorithms. To that end, we propose symmetry-conserving modified quantum approximate optimization algorithm (SCom-QAOA) circuits. The depths of these circuits depend not only on the desired fidelity to the target state but also on the amount of entanglement the state contains. The parameters of the SCom-QAOA circuits are optimized using the quantum natural gradient method based on the Fubini-Study metric. The SCom-QAOA circuit transforms an unentangled state into a ground state of a gapped one-dimensional Hamiltonian with a circuit depth that depends not on the system size but rather on the finite correlation length. In contrast, the circuit depth grows proportionally to the system size for preparing low-lying states of critical one-dimensional systems. Even in the latter case, SCom-QAOA circuits with depth less than the system size were sufficient to generate states with fidelity in excess of 99%, which is relevant for near-term applications. The proposed scheme enlarges the set of the initial states accessible for variational quantum algorithms and widens the scope of investigation of nonequilibrium phenomena in quantum simulators. Published by the American Physical Society 2024

Recruitment and Retention in the National Diabetes Prevention Program Lifestyle Change Program in Two Federally Qualified Health Centers in Rural Hawai'i.

Prediabetes disproportionately affects racial and ethnic minority groups in Hawai'i. The National Diabetes Prevention Program lifestyle change program (National DPP LCP) decreases the risk of developing diabetes. However, enrolling and retaining participants is a challenge for program providers. This evaluation aimed to understand factors that influence racial and ethnic minority groups in Hawai'i to enroll in and complete the program. From 2018 through 2023, two federally qualified health centers (FQHCs) in rural Hawai'i administered 6 year-long cohorts. Trained lifestyle coaches, who were FQHC staff members, recruited participants and facilitated the evidence-based curriculum. In 2023, the evaluation team conducted semistructured interviews with 14 of the 40 enrolled participants (35%), all of whom were women aged 25 to 74 years. Six participants identified as Native Hawaiian or Other Pacific Islander and 3 as Filipino. Eight participants reported completing the program. We used qualitative methodology to analyze transcripts. We identified themes around motivators, barriers, facilitators, and suggestions for improvement. Recruitment by trusted individuals in their communities motivated participants to enroll. Caregiving and work obligations were attendance barriers for early withdrawers and graduates. Social support from lifestyle coaches and enrolled friends and family were facilitators for program completion. Suggestions included improving class availability and incorporating culturally relevant recipes. Barriers experienced by Native Hawaiian or Other Pacific Islander and Filipino participants were similar to those reported by racial and ethnic groups in other studies. Program providers in rural communities should use trusted individuals as lifestyle coaches and recruit family and friends, regardless of National DPP LCP eligibility, to reduce caregiving barriers and engage critical support systems to facilitate completion.

Exactly solvable non-unitary time evolution in quantum critical systems I: effect of complex spacetime metrics

Abstract In this series of works, we study exactly solvable non-unitary time evolutions in one-dimensional quantum critical systems ranging from quantum quenches to time-dependent drivings. In this part I, we are motivated by the recent works of Kontsevich and Segal (2021 arXiv:2105.10161) and Witten (2021 arXiv:2111.06514) on allowable complex spacetime metrics in quantum field theories. In general, such complex spacetime metrics will lead to non-unitary time evolutions. In this work, we study the universal features of such non-unitary time evolutions based on exactly solvable setups. Various physical quantities including the entanglement Hamiltonian and entanglement spectrum, entanglement entropy, and energy density at an arbitrary time can be exactly solved. Due to the damping effect introduced by the complex time, the excitations in the initial state are gradually damped out in time. The non-equilibrium dynamics exhibit universal features that are qualitatively different from the case of real-time evolutions. For instance, for an infinite system after a global quench, the entanglement entropy of the semi-infinite subsystem will grow logarithmically in time, in contrast to the linear growth in a real-time evolution. Moreover, we study numerically the time-dependent driven quantum critical systems with allowable complex spacetime metrics. It is found that the competition between driving and damping leads to a steady state with an interesting entanglement structure.

Pragmatic ontology—Enhancing the philosophical foundation for critical systems thinking/practice

AbstractA sound theoretical foundation for multimethodology should be consistent across the main branches of philosophy: ontological heterogeneity, epistemological plurality and methodological multiplicity. In this light, I posit that (1) Jackson's recent embracement of pragmatism lacks a critical element: a well‐formulated ontology; (2) to overcome this shortcoming, it is necessary to bring ontology back into critical systems thinking/practice; and (3) such an urgent task has further to overcome the current indifference in systems thinking toward ontology. I shall draw intellectual insights from Quine's ‘ontological commitment’, Habermas's ‘ontological presupposition’, Xu Changfu's ‘theory of heterogeneity’, Husserl's ‘ontology layers’, Gadamer's hermeneutic notions ‘prejudice’ and ‘tradition’, as well as ‘ontology building’ practice across the natural and social sciences. I shall also use a multimethodology approach wuli–shili–renli (WSR) as an example to illustrate the working and evolving of pragmatic ontology.

GNSS interference detection: Methodology utilising ADS-B NACp indicator and GPS almanac data

Abstract The threat of GNSS interference poses a great danger to many critical infrastructure systems including air navigation. With a focus on mitigating this threat, this paper proposes a methodology for detecting GNSS interference. The methodology utilises the quality indicator NACp transmitted in ADS-B messages and GPS almanac data for interference detection. The NACp indicator enables estimation of the position error derived from GPS, which is compared with the HDOP value of the GPS satellite constellation. Based on this comparison, the developed detection algorithm determines whether the aircraft is affected by jamming. The detection methodology is evaluated on datasets obtained during deliberate experiments with GPS jamming. The proposed methodology provides a way to detect GNSS interference, facilitating mitigation of its impact on air traffic operation.

Infrastructure first principles for the Anthropocene

Abstract There appears to be a growing decoupling between the conditions that infrastructures were designed for and today’s rapidly changing environments. Infrastructures today are largely predicated on the technologies, goals, and governance structures from a century ago. While infrastructures continue to deliver untold value, there is growing evidence that these critical, basic, and lifeline systems appear ill-equipped to confront the volatility, uncertainty, accelerating conditions, and complexity that define them and their changing environments. Innovative and disruptive first principles are needed to guide infrastructures in the Anthropocene. Drawing from emerging infrastructure research and disciplines that appear better able to confront disruption and change, a novel set of first principles are identified: (1) Plan for complex conditions and surprise; (2) Recouple with agility and flexibility; (3) Govern for exploration and instability; (4) Build consensus as control decentralizes; (5) Restructure to engage with porous boundaries; and, (6) Cyberthreat planning is now mission critical. These principles should guide infrastructure planning recognizing the changing nature and increasingly obsolete boundaries that have defined engineered systems in the modern era.

Life cycle sustainability assessments of critical civil infrastructure systems: additional guidance for future research and practical application

ABSTRACT Sustainable development of critical civil infrastructure systems should include economic, environmental, and social considerations, as well as considerations that are of high value to stakeholders and decision-makers. Life cycle economic and environmental impacts of critical civil infrastructure systems are commonly quantified by well-established methodologies such as life cycle assessment and life cycle costing. However, social and other related impacts of critical civil infrastructure systems can be difficult to quantify and are therefore less commonly and thoroughly addressed. A mini-literature review was conducted to explore how sustainability is currently evaluated for critical civil infrastructure systems. The review found that, while there are life cycle assessment frameworks available, there is vague guidance available for addressing factors that are not directly related to environmental, economic, or social (i.e., difficult to quantify) impacts. In response, the authors build upon currently available methodologies by discussing a supplemental approach for collecting additional data for critical civil infrastructure systems, which includes the use of stakeholder discussions and semistructured interviews. Including a range of factors early on in life cycle sustainability assessments of critical civil infrastructure can improve study robustness and allow for further integration of decision-making factors in life cycle sustainability assessments.

Critical systems thinking for managing complexity of food security

AbstractReductionist approaches, conventionally used to address the complexities of food security, successfully addressed production challenges throughout the 20th century. However, this approach met its limitations when addressing broader issues encompassing socio‐economic and sustainability. Additionally, this approach tends to equip us with reactive methods rather than prescriptive, while decision‐makers today are encouraged to take anticipatory plans and act quickly in any situation. This paper tries to manage the complexity of food security using critical system thinking to assist decision‐makers in choosing a system approach relevant to the issue. It started by presenting the evolution of food security complexity by documenting significant historical milestones in the global journey of global food security. Furthermore, we associate the outcomes of each milestone, in this case, the World Food Conference/Summit, in shaping the direction of the global research theme. We also interview stakeholders from government, businesses and NGOs to identify the complexity of food practices based on their perspectives. Lastly, we categorize food security issues into six types of complexity by referring to Jackson. We show how system of systems methodology (SOSM) can enable us to frame the complexity of food security into relevant categories equipped with suggested methods, thereby enabling the allocation of resources and time more effectively and efficiently.