Solutions and memory effect of fractional-order chaotic system: A review (Interdisciplinary Physics)

Fractional calculus is a 300 years topic, which has been introduced to real physics systems modeling and engineering applications. In the last few decades, fractional-order nonlinear chaotic systems have been widely investigated. Firstly, the most used methods to solve fractional-order chaotic systems are reviewed. Characteristics and memory effect in those method are summarized. Then we discussed the memory effect in the fractional-order chaotic systems through the fractional-order calculus and numerical solution algorithms. It shows that the integer-order derivative has full memory effect, while the fractional-order derivative has nonideal memory effect due to the kernel function. Memory lose and short memory are discussed. Finally, applications of the fractional-order chaotic systems regarding the memory effects are investigated. The work summarized in this manuscript provides reference value for the applied scientists and engineering community of fractional-order nonlinear chaotic systems.

Basins Analysis and Petroleum Systems Modeling of Western Black Sea, Ukrainian Sector

The Ukrainian sector of the Western Black Sea (WBS) is one of the last remaining exploration frontiers in Europe. This area, which includes shelf to deepwater environments, is underexplored with no drilling of targets in water depths exceeding 100 meters. That is why, the Ukrainian sector of the WBS is attractive for exploration, especially in the context of new play types and targets such as biogenic gas. These hydrocarbon formations have been proven by neighboring Romania and Turkey in the areas adjacent to Ukrainian waters. Therefore, a rigorous Basin Analysis program has been initiated to assess the petroleum systems and play risks in the entire Ukrainian sector of the WBS. The goals of this program are: 1) to establish a regional geoscience foundation following best industrial practices in exploration; 2) to enable establishing more accurate risking and ranking procedures for an exploration portfolio and 3) to provide critical support for the analysis of a new generation of seismic data that is currently being acquired. In this paper the initial scope of work is presented.

Rapid-cycle systems modeling to support evidence-informed decision-making during system-wide implementation

Background To “model and simulate change” is an accepted strategy to support implementation at scale. Much like a power analysis can inform decisions about study design, simulation models offer an analytic strategy to synthesize evidence that informs decisions regarding implementation of evidence-based interventions. However, simulation modeling is under-utilized in implementation science. To realize the potential of simulation modeling as an implementation strategy, additional methods are required to assist stakeholders to use models to examine underlying assumptions, consider alternative strategies, and anticipate downstream consequences of implementation. To this end, we propose Rapid-cycle Systems Modeling (RCSM)—a form of group modeling designed to promote engagement with evidence to support implementation. To demonstrate its utility, we provide an illustrative case study with mid-level administrators developing system-wide interventions that aim to identify and treat trauma among children entering foster care. Methods RCSM is an iterative method that includes three steps per cycle: (1) identify and prioritize stakeholder questions, (2) develop or refine a simulation model, and (3) engage in dialogue regarding model relevance, insights, and utility for implementation. For the case study, 31 key informants were engaged in step 1, a prior simulation model was adapted for step 2, and six member-checking group interviews (n = 16) were conducted for step 3. Results Step 1 engaged qualitative methods to identify and prioritize stakeholder questions, specifically identifying a set of inter-related decisions to promote implementing trauma-informed screening. In step 2, the research team created a presentation to communicate key findings from the simulation model that addressed decisions about programmatic reach, optimal screening thresholds to balance demand for treatment with supply, capacity to start-up and sustain screening, and availability of downstream capacity to provide treatment for those with indicated need. In step 3, member-checking group interviews with stakeholders documented the relevance of the model results to implementation decisions, insight regarding opportunities to improve system performance, and potential to inform conversations regarding anticipated implications of implementation choices. Conclusions By embedding simulation modeling in a process of stakeholder engagement, RCSM offers guidance to realize the potential of modeling not only as an analytic strategy, but also as an implementation strategy.