Tool For Analysis Of Systems Research Articles

Spatio-temporal dynamics of an acoustically forced cryogenic coaxial jet injector

This study focuses on the application of dynamical systems theory to characterize the local susceptibility of a nonreacting, cryogenic, coaxial-jet, rocket injector to transverse acoustics. This is achieved using trajectories of the phase space obtained from high-speed imaging data, which reveal the underlying dynamical states of the system. Recurrence analysis is then used to obtain regular patterns in low-dimensional sub-space plots and provide a measure of the local response through recurrence quantification analysis. Of particular interest is quantification of the spatio-temporal coupling of the jet with the external acoustics as a function of the relative momentum flux ratio between the outer and inner jets. At lower outer-to-inner jet momentum flux ratios (J < 1), the jets have a relatively strong local response to acoustic coupling in the near field. This is followed by a sharp drop in this response further downstream where a broad range of instabilities indicates turbulent breakdown of the acoustic mode. This is in contrast to higher outer-to-inner jet momentum flux ratios (J > 1), for which the jets are intermittently coupled to the acoustic mode throughout the entire axial domain due to the presence of a second harmonic or natural instability mode. These dynamical systems analysis tools are used in conjunction with wavelet filtering to improve the utility of high-speed backlit images and are qualitatively consistent with wavelet analysis of the acoustic mode within the flow. The utility of these methods for quantifying the local susceptibility of turbulent coaxial jets to acoustic perturbations can provide powerful insight for the design and optimization of passive or active control systems for bipropellant rocket injectors and other potential propulsion applications.

Molecular analysis of the type III interferon complex and its applications in protein engineering

Type III interferons (IFNλs) are cytokines with critical roles in the immune system and are attractive therapeutic candidates due to their tissue-specific activity. Despite entering several clinical trials, results have demonstrated limited efficacy and potency, partially attributed to low-affinity protein-protein interactions (PPIs) responsible for receptor complex formation. Subsequently, structural studies of the native IFNλ signaling complexes remain inaccessible. While protein engineering can overcome affinity limitations, tools to investigate low-affinity systems like these remain limited. To provide insights into previous efforts to strengthen the PPIs within this complex, we perform a molecular analysis of the extracellular ternary complexes of IFNλ3 using both computational and experimental approaches. We first use molecular simulations and modeling to quantify differences in PPIs and residue strain fluctuations, generate detailed free energy landscapes, and reveal structural differences between an engineered, high-affinity complex, and a model of the wild-type, low-affinity complex. This analysis illuminates distinct behaviors of these ligands, yielding mechanistic insights into IFNλ complex formation. We then apply these computational techniques in protein engineering and design by utilizing simulation data to identify hotspots of interaction to rationally engineer the native cytokine-receptor complex for increased stability. These simulations are then validated by experimental techniques, showing that a single mutation at a computationally predicted site of interaction between the two receptors increases PPIs and improves complex formation for all IFNλs. This study highlights the power of molecular dynamics simulations for protein engineering and design as applied to the IFNλ family but also presents a potential tool for analysis and engineering of other systems with low-affinity PPIs.

The shift toward autonomous European inland waterway shipping: Identifying the gaps in the emerging socio-technical system

The introduction of automated solutions for inland waterways shipping supports the European vision for a sustainable and greener shift within maritime management and logistics. Despite increasing investments, impressive technological advancements, and active discussion to solve the regulatory and business model barriers, socio-technical aspects are still less studied in the preparation for the future of autonomous shipping. This study examines stakeholder and technology roles to map the gaps and challenges created in this emerging space using a system theory approach, specifically a recently developed work design system analysis tool named Change Agent Infrastructure (CHAI) analysis [1]. This framework was chosen to better understand the likely changes of the system with the introduction of automated technology and higher degrees of automation and digitalization in the European inland waterways. The analysis identifies that there are multiple receivers of the change and regulatory bodies will also be actors with considerable responsibilities to direct these changes.

Analysis of a macrophage carbamylated proteome reveals a function in post-translational modification crosstalk

BackgroundLysine carbamylation is a biomarker of rheumatoid arthritis and kidney diseases. However, its cellular function is understudied due to the lack of tools for systematic analysis of this post-translational modification (PTM).MethodsWe adapted a method to analyze carbamylated peptides by co-affinity purification with acetylated peptides based on the cross-reactivity of anti-acetyllysine antibodies. We also performed immobilized-metal affinity chromatography to enrich for phosphopeptides, which allowed us to obtain multi-PTM information from the same samples.ResultsBy testing the pipeline with RAW 264.7 macrophages treated with bacterial lipopolysaccharide, 7,299, 8,923 and 47,637 acetylated, carbamylated, and phosphorylated peptides were identified, respectively. Our analysis showed that carbamylation occurs on proteins from a variety of functions on sites with similar as well as distinct motifs compared to acetylation. To investigate possible PTM crosstalk, we integrated the carbamylation data with acetylation and phosphorylation data, leading to the identification 1,183 proteins that were modified by all 3 PTMs. Among these proteins, 54 had all 3 PTMs regulated by lipopolysaccharide and were enriched in immune signaling pathways, and in particular, the ubiquitin-proteasome pathway. We found that carbamylation of linear diubiquitin blocks the activity of the anti-inflammatory deubiquitinase OTULIN.ConclusionsOverall, our data show that anti-acetyllysine antibodies can be used for effective enrichment of carbamylated peptides. Moreover, carbamylation may play a role in PTM crosstalk with acetylation and phosphorylation, and that it is involved in regulating ubiquitination in vitro.Graphical 9DSWmM7hoJm8b3LaxSLrsCVideo

On the dynamics of a new memristive diode emulator-based Chua’s circuit

The study of nonlinear systems has been the subject of numerous publications. When controlling the symmetry of chaotic oscillators, it has been observed that the symmetrical structure of the diode-bridge memristive emulators is continuously modified to break the symmetry of its current–voltage characteristic. This allows the nature of the symmetry of the oscillator in which they are incorporated to be influenced. In this paper, we present a simple memristive emulator based on simple electronic elements. This new emulator enables a simplified symmetry control method. By varying a control resistor, we modify the symmetry of the current–voltage characteristic of the memristor emulator and thus the symmetry of Chua oscillator in which it is incorporated as nonlinear component. Using dynamical systems analysis tools such as bifurcation diagrams and Lyapunov spectra, we describe how by simply varying a control parameter the symmetry is gradually broken. We highlight striking dynamic properties such as the coexistence of multiple symmetric and asymmetric oscillations and antimonotone bifurcations as well. Laboratory experimental studies are carried out to support the theoretically obtained results.

Site suitability analysis for locating construction and demolition waste transfer station: an Indian case study.

Construction and Demolition Waste Management (CDWM) includes collecting, transporting, processing, and disposing construction and demolition (C&D) waste, where collection and transportation of bulky and voluminous C&D waste contribute significantly to economic and environmental impacts. Transfer station (TS) being a link between various waste management (WM) facilities plays a significant role in collection and transportation of waste. Thus, locating TS at suitable site can help in reducing the overall impacts. Employment of Geographic Information System (GIS) analysis tools in CDWM is a powerful strategy for site suitability study. A case study in Coimbatore, India, is presented in this study using GIS-based multi-criteria analysis for locating C&D waste TS. The criteria for site suitability analysis are chosen based on literature review, regulations, and experts' opinions. Weights of the chosen criteria are estimated using analytic hierarchy process (AHP), and the final suitability map is created by weighted overlay analysis (WOA) in GIS environment. Results provide first-hand information for local decision makers to locate C&D waste transfer station in the chosen study region and report that 12% of the entire area is "highly suitable" for transfer station location.

Beyond sector coupling: Utilizing energy grids in sector coupling to improve the European energy transition

Sector coupling and system integration are key concepts in the energy transition from fossil fuels to fully decarbonized energy systems based on renewable energy. An intelligent use of sector coupling – such as that expressed in the concept of a smart energy system –accommodates for the identification of a more energy-efficient and affordable green transition. However, these benefits are often not fully identified in scenario modelling for the simple reason that not all energy systems analysis tools are equipped to do so. Here, we use the EnergyPLAN tool to replicate the EU Baseline and 1.5 TECH scenarios of the report “A Clean Planet for All”, which we then compare to a smart energy systems scenario for Europe. Due to its focus on sector coupling, we show how such a smart energy Europe scenario can be more energy efficient and affordable than the other scenarios.

The Operation Strategy of the MIDC Systems for Optimizing Renewable Energy Integration of Jeju Power System

The power system on Jeju Island currently faces challenges due to an imbalance between power supply and demand owing to increasing renewable energy (RE) generation. Consequently, the multi-infeed high-voltage direct-current (MIDC) systems are expected to play an important role in reducing RE curtailment and increasing RE penetration. However, despite the balance between power supply and demand, transmission line (TL) overloads on Jeju Island, which has a low permissible rating, may lead to RE curtailment. We propose an operational strategy for the MIDC systems to mitigate TL overloading and RE curtailment. This strategy was aimed at managing the possible congestion of TLs, maintaining a power supply–demand balance, and increasing the penetration level of RE. In this paper, we present a scheme for calculating the operating points of the MIDC systems and allocating RE curtailment using optimization with security constraints to mitigate TL overloading. The proposed optimization model simplifies solving the mathematical equations involved by employing a sensitivity factor called the power transfer distribution factor (PTDF), using which linear programming (LP) optimization can be performed. To verify the feasibility of the operational strategy, case studies are conducted using an actual Jeju Island power system with a power system analysis tool—Power System Simulator for Engineering (PSS/E). The optimization problem was solved using MATLAB.

Framework for global stability analysis of dynamical systems.

Dynamical systems that are used to model power grids, the brain, and other physical systems can exhibit coexisting stable states known as attractors. A powerful tool to understand such systems, as well as to better predict when they may "tip" from one stable state to the other, is global stability analysis. It involves identifying the initial conditions that converge to each attractor, known as the basins of attraction, measuring the relative volume of these basins in state space, and quantifying how these fractions change as a system parameter evolves. By improving existing approaches, we present a comprehensive framework that allows for global stability analysis of dynamical systems. Notably, our framework enables the analysis to be made efficiently and conveniently over a parameter range. As such, it becomes an essential tool for stability analysis of dynamical systems that goes beyond local stability analysis offered by alternative frameworks. We demonstrate the effectiveness of our approach on a variety of models, including climate, power grids, ecosystems, and more. Our framework is available as simple-to-use open-source code as part of the DynamicalSystems.jl library.

Decomposing the Institutional Structure of Interstate River Basins Using Institutional Grammar and Institutional Analysis and Development Framework

Rules play a core role in building a water management institution. However, the rules for water resource regulation in subnational interstate river basins remain inadequately explored. Furthermore, a lack of tools for detailed and systematic analysis of these rules hinders water managers from developing better water management strategies. Accordingly, in this paper, we combine institutional grammar and the institutional analysis and development framework’s rule typology to identify the formal rules regulating the water resources of Australia’s Murray-Darling Basin (MDB) and generate insights regarding the characteristics and key actors in the MDB’s institutional structure. Specifically, we study the position, boundary, choice, aggregation, information, scope, and payoff rules that regulate water in different MDB contexts. Overall, the MDB’s institutional structure emphasizes the choice and information rules that control actors’ actions and the availability of information. Aggregation rules, which regulate collective action, are found in every context. Nevertheless, the composition of the identified rules differs across the basin’s contexts, indicating that the focus of the basin’s institutional instrument differs across situations. We further analyze choice and aggregation rules to investigate the basin actors’ roles and interdependencies. The results reveal that decisions concerning administration, water distribution, monitoring, and infrastructure development are made collectively, except with respect to basin plan development, where decision-making is the responsibility of a single actor. Our proposed approach can therefore be used to thoroughly analyze any complex interstate institutional water structure. Overall, our findings foster a comprehensive understanding of the structure of interstate water institutions while facilitating the development of a systematic water institution analysis tool.

A Study on Petri Net Supporting Tools for System Modeling and Analysis

Within this work we analyze and compare ten Petri net supporting tools for systemmodeling and analysis. A short summary of several available overviews of Petri nettools is performed before the tools analysis itself to evaluate the current state in thisfield. Principal parts of the paper are focused on analysis and evaluation of the selectedtools. We provide detailed and practical description of selection of up to date tools,their evaluation based on various criteria, and recommendations for several use cases.

A Resource Nexus Analysis Methodology for Quantifying Synergies and Trade-Offs in the Agricultural Sector and Revealing Implications of a Legume Production Paradigm Shift

Resource management in the sustainability context has increasingly been a key object that makes the application of holistic approaches an imperative need. The water–energy–food nexus concept offers tools for such system analysis in an integrated manner, through the identification and quantification of synergies and trade-offs. The agricultural sector often constitutes one of the main resource depletion hotspots. In this article, a nexus assessment methodological approach is developed for an agricultural context. Water, energy, food, land uses, and greenhouse gas emissions are perceived as nexus components. The methodology considers resource uses within and outside the biogeographical system boundaries, interpreting them as direct and indirect interlinkages. The methodology is validated on an actual case study, in Thessaly, Central Greece. Four nexus indicators are introduced to assess the impact of different land use planning scenarios. Legume production, which has been considered as a relatively beneficial land use among other crop choices, is tested against the four nexus indicators. Multiple advantages of such a land use paradigm shift are revealed, specific to the directions of food security, energy security, and economic sustainability.

Dynamical analysis of nonlinear fractional order Lorenz system with a novel design of intelligent solution predictive radial base networks

In this research work, the convective flow of Lorenz attractor in the fractional domain is modeled with a nonlinear flexible structure of radial basis neural network (RBNN). The physical parameters of the complex fractional-order system are initially computed with fractional order Runge–Kutta solver for different stochastic scenarios of control constraints and designed its parametric model with RBFN under various initial conditions of the chaotic Lorenz system. Multiple chaos of the Lorenz system with the dynamical neural network structure are computed for different fractional order solutions to analyze the sensitivity of chaotic behavior by means of Lyapunov exponents. Phase diagrams of the chaotic pattern show the fractional-order Lorenz system has compact dynamical behavior and has the potential for the design application of a real dynamical system. Embedded dimension and time delay of the fractional Lorenz system are computed using the average mutual information (AMI) technique to evaluate the suitability of the time delay chaotic pattern in the fractional domain, which is affected by the numerical algorithm and fluctuated on minute time step size. The proposed design of RBFN has been confirmed as an exceptionally high-performance tool for soft computing and dynamics analysis of chaotic systems in the fractional order domain.

Uncertainty quantification in the techno-economic analysis of emission reduction technologies: a tutorial case study on CO2 mineralization

The pathways toward net-zero greenhouse gas emissions by 2050 should be designed based on solid scientific evidence. Ex ante system analysis tools, such as techno-economic assessments (TEAs), are key instruments to guide decision-makers. As ex ante TEAs of CO2 mitigation technologies embody a high level of uncertainty, the informed use of uncertainty analysis becomes crucial for meaningful interpretation and communication of TEA outputs. To foster enhanced appreciation and the use of uncertainty analysis, we compare multiple uncertainty analysis methods for ex ante TEAs, using a case study on CO2 mineralization in the cement industry. We show that local sensitivity analysis tools such as one-way analysis, which are most often used by TEA practitioners, may not suffice for deriving reliable conclusions and provide guidance on how to apply global sensitivity analysis methods, such as variance-based indicators for TEAs in this field.

Linear controller design approach for nonlinear systems by integrating gap metric and stability margin

In the past few years and in many applications, linear feedback control has proved to be adequate for the control of various nonlinear systems. Therefore, before attempting the controller design phase, it is natural to ask, “When is a linear controller adequate for a nonlinear system?” This article provides a new nonlinearity analysis method based on the gap metric and the stability margin that is able to quantify the nonlinearity degree of a system once it has an internal model control controller. The internal model control strategy is used since it provides a direct measure of the discrepancy between outputs from the nonlinear system and its internal model when both are subject to the same controller. It is shown that a feedback loop may exhibit much lower nonlinearity than an open-loop nonlinear system by a careful design of a single linear internal model control controller via the gap metric and stability margin, used as model-based analysis tools for linear time-invariant systems. Both simulations and an experimental validation on a semibatch reactor prove the effectiveness of the proposed method.

Stability analysis tool for discrete-time systems in control education

Stability analysis tool for discrete-time systems in control education

Developing a reflection and analysis tool (We-ReAlyse) for readmissions to the intensive care unit: A quality improvement project

BackgroundReadmissions to the intensive care unit are associated with poorer patient outcomes and health prognoses, alongside increased lengths of stay and mortality risk. To improve quality of care and patients’ safety, it is essential to understand influencing factors relevant to specific patient populations and settings. A standardized tool for systematic retrospective analysis of readmissions would help healthcare professionals understand risks and reasons affecting readmissions; however, no such tool exists. PurposeThis study’s purpose was to develop a tool (We-ReAlyse) to analyze readmissions to the intensive care unit from general units by reflecting on affected patients’ pathways from intensive care discharge to readmission. The results will highlight case-specific causes of readmission and potential areas for departmental- and institutional-level improvements. MethodA root cause analysis approach guided this quality improvement project. The tool’s iterative development process included a literature search, a clinical expert panel, and a testing in January and February 2021. ResultsThe We-ReAlyse tool guides healthcare professionals to identify areas for quality improvement by reflecting the patient's pathway from the initial intensive care stay to readmission. Ten readmissions were analyzed by using the We-ReAlyse tool, resulting in key insights about possible root causes like the handover process, patient's care needs, the resources on the general unit and the use of different electronic healthcare record systems. ConclusionsThe We-ReAlyse tool provides a visualization/objectification of issues related to intensive care readmissions, gathering data upon which to base quality improvement interventions. Based on the information on how multi-level risk profiles and knowledge deficits contribute to readmission rates, nurses can target specific quality improvements to reduce those rates. Implications for clinical practice and researchWith the We-ReAlyse tool, we have the opportunity to collect detailed information about ICU readmissions for an in-depth analysis. This will allow health professionals in all involved departments to discuss and either correct or cope with the identified issues. In the long term, this will allow continuous, concerted efforts to reduce and prevent ICU readmissions. To obtain more data for analysis and to further refine and simplify the tool, it may be applied to larger samples of ICU readmissions. Furthermore, to test its generalizability, the tool should be applied to patients from other departments and other hospitals. Adapting it to an electronic version would facilitate the timely and comprehensive collection of necessary information. Finally, the tool’s emphasis comprises reflecting on and analyzing ICU readmissions, allowing clinicians to develop interventions targeting the identified problems. Therefore, future research in this area will require the development and evaluation of potential interventions.

A self-evolving network-based artificial society model for the experiment analysis of complex social system

Powered by advanced information technology, more and more complex social systems are exhibiting characteristics of complex networks. In consideration of the cost, legal and institutional constraints on the study of social systems in real world, the computational experiment method has emerged as a novel and powerful computational theory and tool for the quantitative analysis of complex social systems. However, how to map the dynamic network features of the real world into artificial society models is an urgent issue confronting the computational experiments method. In this paper, based on the theory of complex networks and complex adaptive systems, we propose a dynamic self-evolving network-based artificial society modeling method to achieve the autonomous evolution of the whole social network. The method abstracts the artificial society into an individual node model and a global network model: the individual model evolves autonomously through individual behavior rules, which continuously changes the topology of the global network model, and then presents the emergent phenomenon of the artificial society system. And then, the validity of the model is demonstrated by using the world trade network as the case study. The experiment results show that the self-evolving network-based artificial society modeling method proposed in this paper provides a new perspective and tool for studying the network evolution characteristics of complex social systems.

Ellipsoidal approximations of the minimal robust positively invariant set

An optimization algorithm is presented in this paper for the minimal robust positively invariant (mRPI) set approximations via sums-of-squares (SOS) optimization. The mRPI set is an effective tool for robust analysis of uncertain systems under bounded disturbances. The approximation of the mRPI set is always characterized by a polyhedron computed after finite time iterations. In this paper, an mRPI set is characterized by an ellipsoidal set while bounded parametric uncertainties act on states. The proposed algorithm optimizes the shape matrix of the ellipsoidal set approximation by minimizing the volume of the ellipsoidal set. The algorithm is designed for discrete-time and continuous-time nonlinear systems respectively. The algorithm has the ability to further minimize the mRPI set by optimizing the state-feedback control law. Examples are employed to validate the effectiveness of the proposed algorithms.

Mapping CPAT I/O Data to CIM and Setting the Multiplicity of Attributes and Associations

This study demonstrates the mapping of input/output (I/O) data of Central Research Institute of Electric Power Industry's Power System Analysis Tool (CPAT) with the Common Information Model (CIM) and the setting of the multiplicity of attributes and associations. The mapping describes which CIM classes defined in IEC 61970‐301 Edition 7.0 and IEC 61970‐302 Edition 1.0 correspond to which I/O data of CPAT. In addition, the multiplicity of their attributes and associations is determined by requirements of the I/O data of CPAT. © 2023 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.