Qualitative Simulation Research Articles

Qualitative and quantitative simulation of best management practices (BMPs) for contaminated megasite remediation using the SiteWise™ tool

Remediation activities, particularly in megasites, may induce substantial secondary environmental impacts that must be addressed for green and sustainable remediation (GSR) practices. Only limited studies are available quantitatively assessing the environmental footprint and environmental benefits of implementing Best Management Practices (BMPs) in megasite remediation. This study used the SiteWise™ tool, a quantitative environmental footprint assessment for scenario simulation and benefit quantification of BMPs, on a contaminated megasite in Hebei Province, China. We observed a considerable environmental footprint and energy from the remediation. Taking the final implementation alternative (Alt 1) as an example, which is characterized by combining multiple remediation techniques, the greenhouse gas (GHG) emissions reached 113,474 t, the energy used was 2,082,841 million metric British thermal units (MMBTU), and other air pollutant emissions (NOx, SOx, and PM10) amounted to 856 t. Further BMP analyses highlighted the benefits of substituting the conventional solidification/stabilization agent with willow woodchip-based biochar, which could reduce GHG emissions by 50,806 t and energy used by 926,648 MMBTU. The overall environmental benefits of implementing all applicable BMPs in the remediation were significant, with a 66.85%, 50.15%, and 56.05% reduction in GHG emissions, energy used, and other air pollutants, respectively. Our study provides insights into quantifying the environmental footprint and exploring emission reduction pathways for contaminated megasite remediation. It also offers a feasible path for quantifying the environmental benefits of BMPs, promoting the development of GSR of contaminated sites.

A qualitative simulation checking approach of programmed grounded theory and its application in workers’ involvement: extending Corbin and Struss’ grounded theory checking mechanism

A qualitative simulation checking approach of programmed grounded theory and its application in workers’ involvement: extending Corbin and Struss’ grounded theory checking mechanism

Navigating climate change complexity and deep uncertainty: approach for building socio-ecological resilience using qualitative dynamic simulation

The consequences of climate change on different sectors of society are interrelated. The threats posed by rising global temperatures, intensifying extreme weather events, and shifting climatic patterns are becoming increasingly evident all around the world. Policymakers face the daunting task of assessing climate change risks, encompassing impacts and response strategies, to guide sustainability transformations. In this study, we introduce a four-step qualitative Decision Making Under Deep Uncertainty (DMDU) approach in the context of Climate Change Impact Assessments (CCIA). Our goal is to enhance the integration of CCIA into spatial planning, particularly in the Global South, using qualitative system dynamics simulation. Emphasizing the value of qualitative DMDU, we explore vulnerability and resilience through a lens of multi-sectoral and multi-scalar socio-ecological processes. We exemplify our approach by applying CCIA to the coastal zone of Yucatán, Mexico, accounting for social and environmental heterogeneity across the four Regions in which it is administered. Results identify the optimal allocation of climate change mitigation and adaptation policies to address specified resilience in each Region, all of which are required to achieve the overall resilience of the coastal zone. We argue that our qualitative DMDU approach provides an analytical platform to address the trade-offs inherent in the ranking of multiple vulnerabilities related to achieving general resilience.

A Wave-corrected Assessment of the Local Midplane

As the number of known Galactic structures mounts thanks to the Gaia Space Telescope, it is now pertinent to study methods for disentangling structures occupying the same regions of the Milky Way. Indeed, understanding the precise form of each individual structure and the interactions between structures may aid in understanding their origins and chronology. Moreover, accounting for known structures allows one to probe still finer Galactic structure. In order to demonstrate this, we have developed an odd low-pass filter (OLPF), which removes smaller, odd-parity structures like the vertical waves, and use the filtered data to examine the location of the Galaxy’s midplane. We find that the radial wave identified by Xu et al. continues inward to at least the Sun’s location, with an amplitude that decreases toward the inner, denser parts of the disk, consistent with a simple, qualitative simulation. Additionally, we employ the OLPF results to determine the solar offset, z ⊙, with smaller structures filtered out. We find that z ⊙ = 34.2 ± 0.3 pc.

Evacuation modelling for rapid multi-hazard tabletop exercise deployment

To prepare for large-scale emergencies and crisis affecting communities, authorities, and emergency commanders use several types of training methods ranging from seminars to full-scale exercises. Within this continuum of exercise types, tabletop exercises (TTXs) are habitually used to familiarise participants with mitigation strategies, population management and evacuation procedures conducted as a response to natural or technological hazards. Commonly, TTXs are paper-based, and if computerised, use basic electronic maps, tend to be scripted and have a linear nature. Information flow is unidirectional as the script dictates how the exercise unfolds. These exercises have little capacity for producing qualitative or quantitative feedback related to the impact that the received scenario injects (i.e., incoming messages including scripted events and hazard locations), the authorities’ decisions, and the impact of hazards have on the wellbeing of the community and the evacuation process. While informative during training, this type of feedback may prove vital in assessing the likely impact of real incident. In this work an evacuation simulation model is proposed to augment the TTX experience in real time, offering feedback and insights on the impact that such injects, decisions and hazards have on the simulated community.The proposed methodology is utilised in an actual TTX co-organised and executed by the Municipality of Rhodes, Greece, where the evacuation model is used to (a) develop the standard, non-incident specific evacuation procedures for the Medieval City of Rhodes (MCR), (b) to adapt these procedures based on the injects (generated on-site or telecommunicated, emulating receipt from the field), producing the TTX scenario and (c) to provide information on the impact that the TTX hazards have on the evacuation process. The integration of evacuation modelling into the TTX process demonstrated that it is possible to gain a deeper understanding of the complexities related to route choices in response to path closures, the assembly and evacuation performance, as well as the management of the simulated incident by analysing qualitative and quantitative simulation results.

Semantically triggered qualitative simulation of a geological process

The field of geology has been the subject of a range of research efforts aiming to formalize geological domain knowledge, notably through geological domain ontologies. The main focus of existing geological ontologies primarily lies in describing static geological objects and their properties, paying less attention to the knowledge concerning geological processes and events. Meanwhile, the geological process modeling and simulation predominantly rely on quantitative numerical approaches that necessitate comprehensive and abundant data as input. However, many geological processes took place on a million-year time scale with insufficient data and non-direct observations. Given the inherent incompleteness of geological data, geologists still rely on qualitative reasoning to validate their interpretations. There is currently a dearth of applicable methods to facilitate qualitative reasoning and simulate geological processes based on domain knowledge.We propose to model the effects of a geological process through an object-oriented program, while keeping an ontological representation of the situation at each instant. To combine the two models, we propose using semantically defined ‘process triggers.’ These process triggers are defined as part of the ontology, in accordance with the Basic Formal Ontology. They enable geologists to describe the precise moment when a geological process is triggered and initiated. On the computational program side, we employ the ‘Semantic Micro Object Language’ to embody the knowledge and rules provided by geologists, facilitating the simulation of geological processes. Through an evaluation experiment, our proposed approach demonstrates promising results within a reasonable timeframe. As proof of concept, we have applied our method to a real-world scenario of petroleum thermal maturation in Ekofisk Field and got a promising result. Our approach provides a formalism that allows a powerful code to interact with domain ontologies, which paves the path for future knowledge reasoning.

Qualitative Cusp Catastrophe Multi-Agent Simulation Model to Explore Abrupt Changes in Online Impulsive Buying Behavior

We develop a qualitative catastrophe (a nonlinear sudden violent change) multi-agent simulation model to investigate the evolution of group behavior, specifically abrupt changes in online impulsive buying (OIB) behavior. Studies have rarely investigated the mechanism of abrupt changes in OIB at the group level. To address the research gaps and advance this area of research, we employed a sequential multiple-methods approach. First, we designed a questionnaire to obtain and analyze consumer data to identify OIB drivers. Second, we built a qualitative catastrophe model based on empirical findings to describe sudden changes in the OIB behavior of individuals by merging catastrophe theory (CT) and qualitative simulation (QSIM). Finally, grounded in the qualitative catastrophe model, we constructed an agent-based model (ABM) to simulate group-level OIB behavior. The empirical findings revealed the following. (1) Sudden changes in group-level OIB occur as consumers’ sense of quantified self increases when self-control is low. (2) The greater the number of consumers with a proving preference (who prefer to prove their competence and performance to others) in the group, the higher the possibility of catastrophe; the scale of catastrophe increases significantly with the enhancement of product information features. (3) We identify optimal gamification for sudden increases in group-level OIB; the larger the degree of social networking is, the higher the likelihood of catastrophe behavior. Our proposed combination of a survey study, QSIM, and an ABM is a plausible solution for behavioral research on consumers, and the integration paradigm could help maintain market stability and promote products.

Experimental simulation study on influencing factors of liquid production capacity in heterogeneous water drive reservoirs

Oilfield development involves a complex, dynamic flow process of oil and water, with reservoir characteristics and environmental conditions continually evolving as the field evolves. Particularly when a waterflooding reservoir reaches a stage of ultra-high water cut, prolonged waterflooding intensifies challenges in reservoir development: the exacerbation of reservoir heterogeneity and development behaviors disrupts the initial understanding of the reservoir's liquid production capacity from current development conditions. Thus, it becomes imperative to adjust the productivity prediction methods for oil wells in heterogeneous waterflooding reservoirs. Leveraging the flow simulation of reservoir micro channel networks, and integrating features such as the geometric characteristics of the reservoir percolation field, micro channel characteristics, interlayer differences of mixed layers, degree of plane heterogeneity, production pressure differentials, and fluid properties, a visual sand filling experimental model is established that adheres to specific similarity criteria. Using this sand filling experimental model, we simulate the percolation characteristics of oil–water two-phase flow during the waterflooding process, and uncover the diverse influencing factors and their varying degrees of impact on the oil-phase flow during this waterflooding phase. Qualitative and semi-quantitative percolation simulation experiments are employed to intuitively demonstrate the interlayer interference, degree of plane heterogeneity, and oil–water distribution in heterogeneous reservoirs, which influence the change in oil well productivity during waterflooding. This lays bare the microscopic percolation mechanisms behind the productivity changes in heterogeneous waterflooding reservoirs. The simulation experiment results show that the higher the permeability, the stronger the micro-heterogeneity, and the smaller the overall mobility increase after flooding, the smaller the JLDmax obtained by testing or calculation. At the same permeability, the greater the driving pressure difference, the greater the microscopic sweep coefficient within the pore network, and the greater the mobility increase after flooding, the greater the JLDmax. There is interlayer interference in commingled mining, and the higher the permeability of the high-permeability layer (the greater the interlayer difference), the higher the initial productivity of the commingled well. However, due to the high permeability layer being prone to flooding, resulting in ineffective water circulation, the low-permeability tube is difficult to completely flood, resulting in a small increase in overall mobility, and therefore, JLDmax is small. Water drive preferentially breaks through the high permeability zone on the plane, and the shape of the water drive sweep zone is controlled by the planar permeability gradient, the width of the high permeability zone, and the displacement pressure difference.

Using Visual Patient to Show Vital Sign Predictions, a Computer-Based Mixed Quantitative and Qualitative Simulation Study.

Machine learning can analyze vast amounts of data and make predictions for events in the future. Our group created machine learning models for vital sign predictions. To transport the information of these predictions without numbers and numerical values and make them easily usable for human caregivers, we aimed to integrate them into the Philips Visual-Patient-avatar, an avatar-based visualization of patient monitoring. We conducted a computer-based simulation study with 70 participants in 3 European university hospitals. We validated the vital sign prediction visualizations by testing their identification by anesthesiologists and intensivists. Each prediction visualization consisted of a condition (e.g., low blood pressure) and an urgency (a visual indication of the timespan in which the condition is expected to occur). To obtain qualitative user feedback, we also conducted standardized interviews and derived statements that participants later rated in an online survey. The mixed logistic regression model showed 77.9% (95% CI 73.2-82.0%) correct identification of prediction visualizations (i.e., condition and urgency both correctly identified) and 93.8% (95% CI 93.7-93.8%) for conditions only (i.e., without considering urgencies). A total of 49 out of 70 participants completed the online survey. The online survey participants agreed that the prediction visualizations were fun to use (32/49, 65.3%), and that they could imagine working with them in the future (30/49, 61.2%). They also agreed that identifying the urgencies was difficult (32/49, 65.3%). This study found that care providers correctly identified >90% of the conditions (i.e., without considering urgencies). The accuracy of identification decreased when considering urgencies in addition to conditions. Therefore, in future development of the technology, we will focus on either only displaying conditions (without urgencies) or improving the visualizations of urgency to enhance usability for human users.

A new fuzzy approach and bankruptcy theory in risk estimation in Waste Load Allocation.

In this paper, we developed a simulator-optimizer model based on risk analysis to determine Waste Load Allocation (WLA). A new Fuzzy index as Fuzzy Risk Index (FRI) was linked with multi-objective optimization to minimize FRI for the environmental stakeholder and the total cost of sewage treatment for the polluting industries as the other collective stakeholder. Afterwards, the conflict was resolved with the help of Nash bargaining and bankruptcy approach (Constrained Equal Awards Rule). The model was run using quantitative/qualitative data for the KhoramAbad River. To check the efficiency of FRI, the process followed for WLA was reimplemented by the Monte Carlo simulation (MCS). A comparison between the two approaches revealed that the outcomes derived from Fuzzy arithmetic across all aspects, encompassing river qualitative simulation, nondominated curve, Nash bargaining's agreed point, and bankruptcy output, closely mirrored the results of MCS. The notable distinction lies in the drastic reduction of the model's execution time by a factor of 450.

Dynamics of a nonlinear epidemic transmission model incorporating a class of hospitalized individuals: a qualitative analysis and simulation

This study aims to develop a novel mathematical epidemic compartmental model that includes a compartment or class for individuals who become infected and experience severe illness due to the infection. These individuals require hospitalization and the use of specialized medical equipment, such as ventilators, ICU beds, etc, during an outbreak. This compartment is referred to as the ‘hospitalized population compartment’ throughout this study. Additionally, the model incorporates a saturated incidence rate for new infection cases and the hospitalization rate for individuals severely affected by the infection, intending to create a more realistic scenario of the dynamics of disease transmission. The model is developed by integrating a compartment for hospitalized individuals into the standard susceptible-infected-recovered compartmental model and is subsequently mathematically analyzed for qualitative behavior. In this model, the saturated hospitalization rate reflects that the number of severely infected individuals who can be hospitalized is limited at any given time due to constraints in sufficient hospital infrastructure availability. The incidence rate of susceptibles becoming infected is modeled using the Holling Type II functional form, which incorporates inhibitory effects observed within the population. The study analyzes the mathematical model for two types of equilibria: the disease-free equilibrium (DFE) and the endemic equilibrium (EE). To investigate the stability of both equilibria, the basic reproduction number, , is calculated using the next-generation matrix method. The findings indicate that when , the DFE is locally asymptotically stable. Conversely, when , the DFE becomes unstable, leading to the emergence of a positive EE. Additionally, the study explores the occurrence of forward and backward transcritical bifurcations under specific conditions when . Furthermore, the study delves into both the local and global stability behaviors of the EE. Numerical simulations of the model are also performed to support the theoretical findings.

Temperature dependence of surface microstructure of 316 L stainless steel exposed to low-energy hydrogen ion irradiation

The austenitic 316 L stainless steel (316LSS) is an important metal for nuclear installations due to its high strength, good plastic toughness and excellent corrosion resistance, and is commonly used as the plasma-facing and structural material. In this study, 316LSS samples are irradiated with low-energy hydrogen ions (35 eV) at the temperature of 400–1300 K to investigate the surface microstructure evolution. The experimental results show that the surface of 316LSS samples remains relatively smooth at 400 K and 600 K after irradiation. Significant surface roughening including spherical protrusions is formed on the surface at 800 K and 1100 K, and step-like streaks are observed at 1300 K. However, no drastic change in the surface morphology is observed in the separate annealing experiments at 800–1300 K. It has been shown that hydrogen ion irradiation mainly causes the surface microstructure evolution of 316LSS samples. After hydrogen plasma exposure, a large number of adatoms are first formed on the surface of 316LSS because of bubble growth. The adatoms then preferentially reach the defects by diffusion at certain temperatures, and aggregate into spherical protrusions with low surface energy. The qualitative simulation results show that the irradiation temperature affects the diffusion and aggregation of adatoms on the surface, and the radius of the spherical protrusions gradually increases due to the decrease of the surface binding energy and the increase of the irradiation fluence.

Comparison and Analysis of Electromagnetic Characteristics of Basic Structure of Wireless Power Coil for Permanent Magnet Motors in Electric Vehicles

The purpose of this paper is to compare and analyze the electromagnetic characteristics of the basic structure of the coil in the electromagnetic coupling mechanism for the wireless power supply of permanent magnet motors in electric vehicles. The electromagnetic coupling mechanism is one of the key technologies for wireless power transmission and the coil structure plays a key role in the transmission performance of the coupling mechanism, and different structures can achieve different performances. The central objective of coil structure studies is to investigate how the coupling coefficient can be increased to achieve greater transmitted power and higher efficiency. In this paper, we investigate two basic coil configurations, circular and square, by studying their flux density variations when used as transmitting coils and their electromagnetic coupling characteristics when used as receiving coils. Three couplers consisting of circular and square coils are also analyzed in simulations and experiments are carried out on couplings containing circular and square coils of the same area. The results of the study show that the qualitative analysis, simulation analysis and experimental results are in high agreement. The results of this paper are an important reference for the design and optimization of wireless power coils for permanent magnet motors in electric vehicles.

A study on the simulation of psychological and behavioral dynamics in the unsafe state of coal mine workers

The coal mine production safety hazards are large, and the situation is difficult, and coal mine workers are affected psychologically, producing unsafe psychological states and triggering unsafe behavior. This paper firstly studies the interactive influence process of the unsafe psychological state of coal mine workers and reveals the emergence process of unsafe psychology and behavior of coal mine workers. According to the characteristics of qualitative simulation of safety behavior, safety psychology and unsafe state of coal mine personnel, 23 simulation schemes are designed, and simulation analysis is carried out using QSIM simulation software platform. According to the simulation results of 23 schemes, the dynamic emergence process of safety behavior, safety psychology, and unsafe state of coal mine workers was sorted out from the aspects of different states and the intensity of different management measures, and the law of the effect of coal mine workers' safety psychology on safety behavior and safety state was obtained , revealing the interactive influence of coal mine workers' psychology on the unsafe state and the internal evolution mechanism of the emergent process. It is of great theoretical and practical significance for coal mine safety management to study the interaction of hazardous psychological states of coal mine workers and the dynamic generation mechanism of the emergence process of unsafe behaviors.

The Performance of Sensitivity-Maps Method in Reconstructing Low Contrast and Multi-Contrast Objects for Microwave Imaging Applications

The microwave imaging system for breast tumor/cancer detection requires high sensitivity to detect abnormal tissue that has little contrast in high-density breasts. This paper proposes a qualitative microwave imaging system simulation based on inverse scattering using the sensitivity-maps method. This method utilizes two measurement types for system calibration: a reference object as a scatterer-free background and a calibration object to obtain the system's impulse response. The object under test (OUT) consists of an object with low dielectric contrast and a phantom with multiple low dielectric contrasts (multi-contrast). Reconstruction is carried out on three types of S-parameter measurement data, namely S_11,〖 S〗_21, and a combination of both. S-parameters are measured at several frequencies, which are 3, 10, 14, 15, 16, 20 GHz, and the combination of all those frequencies (multifrequency). Reconstructed images show that the system is capable of reconstructing dielectric objects accurately. Quantitatively, the results show that the multifrequency S_21 measurement yields the best image quality with relative root mean squared error (RRMSE) values of 0.1272 and structural similarity index (SSIM) of 0.9076. The designed imaging system also successfully reconstructs multi-contrast phantom accurately with RRMSE of 0.1434 and SSIM of 0.4609.

High-speed planar laser-induced fluorescence investigation of nitric oxide generated by hypersonic Mach reflections for computational fluid dynamics validation

In this article, the authors present an experimental investigation of the thermochemical relaxation regions downstream of symmetric Mach reflections generated in Mach 8.5 flows with stagnation enthalpies from 7 to 10 MJ/kg. The experiment was performed in the Hypervelocity Expansion Tunnel at the National Aerothermochemistry and Hypersonics Laboratory of Texas A&M University. The investigation focused on studying the nitric oxide morphology in the vicinity of a strong normal shock wave and shear layers. Experimental planar laser-induced fluorescence measurements at 250 kHz repetition rate with a quasi-simultaneous natural emission photography demonstrate a sufficient rejection of natural emission and reveal intricate flow structures in the shock vicinity. Steady computational fluid dynamics (CFD) flow solutions obtained with the US3D software were used to simulate laser-induced fluorescence signal levels for quantitative comparison against the experimentally acquired data. The investigation accomplished four objectives: complex flowfield visualization in the vicinity of the Mach stem with 4 μs temporal resolution, evaluation of the level of high-temperature chemistry effects introduced to the freestream by the expansion tunnel, both qualitative and quantitative CFD simulation validation, and cross-checking or introduction of fundamental properties of nitric oxide laser-induced fluorescence including absorption cross section for vibrationally excited states of nitric oxide and a collisional quenching cross section of nitric oxide by atomic nitrogen.

The neighborhood as an energy-generating community: the case of the El Banafseg residential neighborhood, East Cairo

Nowadays, energy consumption is a global challenge due to the shortage of some energy sources and, consequently, their increasing prices. This paper argues that by using an integrative approach for using various energy harvesting techniques, a typical residential neighborhood can be operated as a self-generator of some or all of its needed energy. The paper follows mixed qualitative, experimental, and numerical simulation approaches to examine the practicality of the hypothesis. It uses Space syntax modeling theory (socio-spatial software) to analyze the pedestrian flow to indicate potential locations of kinetic energy harvesting piezoelectric tiles in the selected residential neighborhood. In addition, the possibility of installing photovoltaic electrical cells on rooftops of the neighborhood residential blocks is studied. The numerical simulation quantifies the capacity of the harvested energy to achieve a model of a green neighborhood. The paper measures the percentage of the residences’ energy needs that can be harvested using renewable energy resources. It reveals that 30% of the energy consumed in the residential blocks can be generated from photovoltaic electrical cells, and 38% of the energy consumed by street lighting of the entire neighborhood could be generated using the kinetic energy harvested by piezoelectric tiles.

Architectonics of individual taxation system

Transformation of national economies caused by globalization and digitalization of business processes leads to changes in the whole chain of relationships at the levels of "state-individual", "employee-employer", "tax authority-taxpayer". The following research goal is to develop a unified construct of the taxation system, taking into account modern transformation processes and system economy principles. The research applies a comprehensive approach, which includes three main analysis methods: qualitative comparative analysis, simulation modeling, and interpretative qualitative research. Qualitative comparative analysis was used to identify the elements of individual taxation. Simulation modeling was used to visualize taxation main parameters and limitations. Interpretative research was used to describe the interaction of the system elements. The scientific novelty of the research is the presented architectonics of individual taxation system, which develops the theory of system economy of Kleiner and includes 4 elements (subsystems), classified by the criterion of definiteness of time and space. First, objects – exist in the uncertainty of time and the certainty of space. Second, projects - exist in limited time and defined space. Third, environments – exist in the indefiniteness of time and the uncertainty of space. Fourth, processes - exist in limited time and uncertainty of space. The elements of the objective subsystem include taxpayers individuals and individual entrepreneurs, tax authorities, tax agents, other participants of tax legal relations, and the territory. The project subsystem includes tools and mechanisms of tax regulation, which are experimental and temporary in nature. Tax functions implementation was visualized in the context of the presented system.

Abstract P6-05-15: Standard of Care for HR+/HER2- Breast Cancer: Integrating The “Yale Model Shared Decision-Making Multidisciplinary Team Solution” into the Practice Setting

Abstract Background: Breast cancer patients are faced with treatment choices that can involve complex preference-sensitive decisions. The National Quality Forum initiated a “Call to Action” to integrate shared decision-making (SDM) processes into practice where clinicians and patients work together to make healthcare decisions that align with what matters most to patients. Projects In Knowledge, @Point of Care, Dartmouth and Yale collaborated to develop a pilot educational initiative to address and improve patient-centered care and SDM processes in the institutional cancer care setting. Methods: Training materials co-developed for the Yale Breast Cancer multidisciplinary team (N=11: oncologists, nurses/NPs, pharmacist) address SDM, CDK4/6 Inhibitor treatment of metastatic HR+ HER2- breast cancer, and clinician-patient role play methods implementing SDM in treatment discussions/decisions with patients. Reinforcement training, based on interim interview and case role play assessments, was customized to meet specific needs of the team. Qualitative semi-structured interviews and simulation case role play observational methods, using a two-rater system, were used to assess improved SDM performance. Baseline pre-intervention interviews and case role play assessments were compared to interim post-intervention and end of pilot (EOP) post-reinforcement training intervention interviews and case role play assessments (using a Likert scale 0-4 rating score: 0=0%; 1=25%, 2=50%; 3=75%; 4=100%). Following the training and assessments, a focus group of team members provided insights into the performance of the group, assessed the acceptability, feasibility, and repeatability of the program, and informed future education. Results: Semi-structured interview findings revealed that clinicians learned about nuances of CDK 4/6 inhibitors, crystallized their understanding of SDM through reinforcement training (customized in real time), and felt they were better able to implement SDM as a result of their case role play assessments. Training empowered the Yale Breast Cancer team to show pre- to post-education improvement in SDM case role play scenarios, ranging from 16% to 39%. Areas of greatest improvement: 1) determining decision style preference (+36%); 2) determining patients’ risk/burden tolerance (+32%); 3) determining patients’ activation, engagement, and self-efficacy (+34%), 4) determining trade-off decisions with patients (+39%), and 5) determining patients’ readiness to make a decision (+32%). Future research should explore how best to integrate SDM into the real world time restricted clinical practice. Conclusions: Educational training improved SDM skills for the multidisciplinary Yale Breast Cancer team, which can lead to improved clinician-patient decision-making and patient-centric care. The training process also facilitated team building and encouraged ongoing participation in SDM. Overall Yale Breast Cancer SDM Pilot Case Study Role-Play Assessments (Data reflect findings for 11 participants who completed their case role play) Citation Format: Elaine Rudell, Tarjani Agrawal, Patty Peterson, Michele Fallon Ingram, Brant Oliver, Kerin Adelson. Standard of Care for HR+/HER2- Breast Cancer: Integrating The “Yale Model Shared Decision-Making Multidisciplinary Team Solution” into the Practice Setting [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-05-15.

Chemical and mechanical analysis of field and laboratory aged bitumen

To predict the performance of bituminous products during their service life, an accurate simulation of the aging behaviour is required. Several laboratory methods are available, yet the correlation to field aging is mostly missing. In this study, an unmodified bitumen was exposed to laboratory aging with the Pressure Aging Vessel (PAV) using one to five aging cycles and the Viennese Binder Aging (VBA) method, followed by a comparison to a field sample of the same base binder. Measurements with the dynamic shear rheometer (DSR) and Fourier-transform-infrared (FTIR) spectroscopy showed that the field aging level could not be reached neither with VBA nor with multiple PAV cycles, but a better approximation compared to the standard aging procedure was achieved. The FTIR spectra displayed a high degree of correlation between the VBA and field aged sample, especially regarding carbonyl formation in the aromatic fraction and the intensity of the sulphoxide band in the resin and asphaltene fractions. Additionally, the VBA sample showed more similarities to the field sample regarding fluorescence excitation–emission maps. Although both laboratory aging methods are an improvement to the standard procedure, the VBA method allowed for a better qualitative simulation of the chemical properties of the investigated field sample.