Modeling an Industrial Revolution: How to Manage Large-Scale, Complex IoT Ecosystems?

Advancements around the modern digital industry gave birth to a number of closely interrelated concepts: in the age of the Internet of Things (IoT), System of Systems (SoS), Cyber-Physical Systems (CPS), Digital Twins and the fourth industrial revolution, everything revolves around the issue of designing well-understood, sound and secure complex systems while providing maximum flexibility, autonomy and dynamics.The aim of the paper is to present a concise overview of a comprehensive conceptual framework for integrated modeling and management of industrial IoT architectures, supported by actual evidence from the Arrowhead Tools project; in particular, we adopt a three-dimensional projection of our complex engineering space, from modeling the engineering process to SoS design and deployment.In particular, we start from modeling principles of the the engineering process itself. Then, we present a design-time SoS representation along with a toolchain concept aiding SoS design and deployment. This brings us to reasoning about what potential workflows are thinkable for specifying comprehensive toolchains along with their data exchange interfaces. We also discuss the potential of aligning our vision with RAMI4.0, as well as the utilization perspectives for real-life engineering use-cases

Photometry of the Didymos System across the DART Impact Apparition

On 2022 September 26, the Double Asteroid Redirection Test (DART) spacecraft impacted Dimorphos, the satellite of binary near-Earth asteroid (65803) Didymos. This demonstrated the efficacy of a kinetic impactor for planetary defense by changing the orbital period of Dimorphos by 33 minutes. Measuring the period change relied heavily on a coordinated campaign of lightcurve photometry designed to detect mutual events (occultations and eclipses) as a direct probe of the satellite’s orbital period. A total of 28 telescopes contributed 224 individual lightcurves during the impact apparition from 2022 July to 2023 February. We focus here on decomposable lightcurves, i.e., those from which mutual events could be extracted. We describe our process of lightcurve decomposition and use that to release the full data set for future analysis. We leverage these data to place constraints on the postimpact evolution of ejecta. The measured depths of mutual events relative to models showed that the ejecta became optically thin within the first ∼1 day after impact and then faded with a decay time of about 25 days. The bulk magnitude of the system showed that ejecta no longer contributed measurable brightness enhancement after about 20 days postimpact. This bulk photometric behavior was not well represented by an HG photometric model. An HG 1 G 2 model did fit the data well across a wide range of phase angles. Lastly, we note the presence of an ejecta tail through at least 2023 March. Its persistence implied ongoing escape of ejecta from the system many months after DART impact

Dynamic Execution of Engineering Processes in Cyber-Physical Systems of Systems Toolchains

Engineering tools support the process of creating, operating, maintaining, and evolving systems throughout their lifecycle. Toolchains are sequences of tools that build on each others’ output during this procedure. The complete chain of tools itself may not even be recognized by the humans who utilize them, people may just recognize the right tool being used at the right place in time. Modern engineering processes, however, do not value such ad-hoc choice of tooling, because of their uncontrolled nature. Building upon the Extended Automation Engineering Model defined by the IEC 81346 standard, this paper proposes to automate the toolchain building and execution process for Cyber-Physical System of Systems (CPSoS), utilizing key principles of the Eclipse Arrowhead framework. The proposed toolchain automation solution addresses issues such as tool interoperability, interaction, automation, and dynamic choreography. The feasibility of this set of integrated concepts is validated through an Arrowhead-based toolchain choreography demonstration. Note to Practitioners —The paper discusses approaches to the automated execution of various industry-related processes. As the processes are becoming more complex and involve numerous systems which have to be orchestrated, a simple and preprogrammed workflow is not enough anymore. Therefore, building on top of the principles of the Eclipse Arrowhead framework, an adequate model of toolchains, allowing for their automated execution, is proposed. Different approaches to supervision of toolchain execution are discussed showing the benefits of reaching higher automation levels. Further, four adoption levels are introduced, which are a measure of the toolchain automation progress. Finally, a simplified demonstrator is shown and steps to elevate it to higher adoption levels are highlighted. To ensure that the approach is industry-oriented, several examples of how the proposed methodology can be used in the industrial context are discussed

Modeling an Industrial Revolution: How to Manage Large-Scale, Complex IoT Ecosystems?

Advancements around the modern digital industry gave birth to a number of closely interrelated concepts: in the age of the Internet of Things (IoT), System of Systems (SoS), Cyber-Physical Systems (CPS), Digital Twins and the fourth industrial revolution, everything revolves around the issue of designing well-understood, sound and secure complex systems while providing maximum flexibility, autonomy and dynamics.The aim of the paper is to present a concise overview of a comprehensive conceptual framework for integrated modeling and management of industrial IoT architectures, supported by actual evidence from the Arrowhead Tools project; in particular, we adopt a three-dimensional projection of our complex engineering space, from modeling the engineering process to SoS design and deployment.In particular, we start from modeling principles of the the engineering process itself. Then, we present a design-time SoS representation along with a toolchain concept aiding SoS design and deployment. This brings us to reasoning about what potential workflows are thinkable for specifying comprehensive toolchains along with their data exchange interfaces. We also discuss the potential of aligning our vision with RAMI4.0, as well as the utilization perspectives for real-life engineering use-cases

Metabolic syndrome is associated with similar long-term prognosis in non-obese and obese patients. An analysis of 45 615 patients from the nationwide LIPIDOGRAM 2004-2015 cohort studies

Aims We aimed to evaluate the association between metabolic syndrome (MetS) and long-term all-cause mortality. Methods The LIPIDOGRAM studies were carried out in the primary care in Poland in 2004, 2006 and 2015. MetS was diagnosed based on the National Cholesterol Education Program, Adult Treatment Panel III (NCEP/ATP III) and Joint Interim Statement (JIS) criteria. The cohort was divided into four groups: non-obese patients without MetS, obese patients without MetS, non-obese patients with MetS and obese patients with MetS. Differences in all-cause mortality was analyzed using Kaplan-Meier and Cox regression analyses. Results 45,615 participants were enrolled (mean age 56.3, standard deviation: 11.8 years; 61.7% female). MetS was diagnosed in 14,202 (31%) by NCEP/ATP III criteria, and 17,216 (37.7%) by JIS criteria. Follow-up was available for 44,620 (97.8%, median duration 15.3 years) patients. MetS was associated with increased mortality risk among the obese (hazard ratio, HR: 1.88 [95% CI, 1.79-1.99] and HR: 1.93 [95% CI 1.82-2.04], according to NCEP/ATP III and JIS criteria, respectively) and non-obese individuals (HR: 2.11 [95% CI 1.85-2.40] and 1.7 [95% CI, 1.56-1.85] according to NCEP/ATP III and JIS criteria respectively). Obese patients without MetS had a higher mortality risk than non-obese patients without MetS (HR: 1.16 [95% CI 1.10-1.23] and HR: 1.22 [95%CI 1.15-1.30], respectively in subgroups with NCEP/ATP III and JIS criteria applied). Conclusions MetS is associated with increased all-cause mortality risk in non-obese and obese patients. In patients without MetS obesity remains significantly associated with mortality. The concept of metabolically healthy obesity should be revised