Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective

The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model\u27s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the development and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee\u27s multidisciplinary membership, followed by a large stakeholder community survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing implementations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare

Twenty years of stereotype threat research: A review of psychological mediators

This systematic literature review appraises critically the mediating variables of stereotype threat. A bibliographic search was conducted across electronic databases between 1995 and 2015. The search identified 45 experiments from 38 articles and 17 unique proposed mediators that were categorized into affective/subjective (n = 6), cognitive (n = 7) and motivational mechanisms (n = 4). Empirical support was accrued for mediators such as anxiety, negative thinking, and mind-wandering, which are suggested to co-opt working memory resources under stereotype threat. Other research points to the assertion that stereotype threatened individuals may be motivated to disconfirm negative stereotypes, which can have a paradoxical effect of hampering performance. However, stereotype threat appears to affect diverse social groups in different ways, with no one mediator providing unequivocal empirical support. Underpinned by the multi-threat framework, the discussion postulates that different forms of stereotype threat may be mediated by distinct mechanisms

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)

Utilization of Copper Alloys for Marine Applications

Utilization of copper alloy components in systems deployed in marine environment presents potential improvements by reducing maintenance costs, prolonging service life, and increasing reliability. However, integration of these materials faces technological challenges, which are discussed and addressed in this work, including characterization of material performance in seawater environment, hydrodynamics of copper alloy components, and design procedures for systems with copper alloys. To characterize the hydrodynamic behavior of copper alloy nets, mesh geometry of the major types of copper nets currently used in the marine aquaculture are analyzed and formulae for the solidity and strand length are proposed. Experimental studies of drag forces on copper alloy net panels are described. Based on these studies, empirical values for normal drag coefficients are proposed for various types of copper netting. These findings are compared to the previously published data on polymer nets. It is shown that copper nets exhibit significantly lower resistance to normal currents, which corresponds to lower values of normal drag coefficient. The seawater performance (corrosion and biofouling) of copper alloys is studied through the field trials of tensioned and untensioned specimens in a one-year deployment in the North Atlantic Ocean. The corrosion behavior is characterized by weight loss, optical microscopy, and SEM/EDX analyses. The biofouling performance is quantified in terms of the biomass accumulation. To estimate the effects of stray electrical currents on the seawater corrosion measurements, a low cost three-axis stray electric current monitoring device is designed and tested both in the lab and in the 30-day field deployment. The system consists of a remotely operated PC with a set of pseudo-electrodes and a digital compass. The collected data is processed to determine magnitudes of AC and DC components of electric field and dominant AC frequencies. Mechanical behavior of copper alloys is investigated through a series of uniaxial tension tests on virgin and weathered (after one-year deployment in the ocean) specimens. The changes in mechanical properties are quantified in terms of differences in Young\u27s modulus, Poisson\u27s ratio, ultimate strength, and ultimate strain. The obtained stress-strain data is used for numerical modeling of the mechanical behavior of chain-link nets. The simulations are compared with the experimental data on stiffness and strength of the nets. The available information on seawater performance of copper alloys (corrosion, biofouling, mechanics) and copper alloy nets (hydrodynamics) is used to develop engineering procedures for marine aquaculture fish cage systems with copper alloy netting. The design, analysis, and fabrication procedures are illustrated on a commercial size gravity-type offshore fish cage deployed in the Pacific Ocean near Isla Italia (Patagonia, Chile). The funding for this work was provided by the International Copper Association. This work was also supported through two UNH Fellowships: CEPS UNH Graduate Fellowship to Outstanding PhD Program Applicants and Dissertation Year Fellowship.

Prediction of the effective elastic moduli of materials with irregularly-shaped pores based on the pore projected areas

AbstractStatistical modeling is used to correlate geometric parameters of pores with their contributions to the overall Young’s moduli of linearly elastic solids. The statistical model is based on individual pore contribution parameters evaluated by finite element simulations for a small pore subset selected using the design of experiments approach, so there is no need to solve the elasticity problem for all pores in the material. A polynomial relating pore geometric parameters to the contribution parameters is then fitted to the results of the simulations. We found a good correlation between normalized projected areas of the pores on three coordinate planes and their contributions to the corresponding effective Young’s moduli. The model is applied and validated for two large sets of pore geometries obtained by X-ray microcomputed tomography of a carbon/carbon and a 3D woven carbon/epoxy composite specimens

Effect of the bending stiffness on the volumetric stability of fish cages with copper alloy netting

It has been well established that aquaculture will supply an increasing share of the world’s se food demand in the future. Most finfish are raised in marine fish cages consisting of a floating superstructure, polymer net chamber and a sinker weight(s). These systems are susceptible to large deformations, which can lead to reduction of the cage’s volume and severely impact the health of the fish stock. Net chamber deformation could be mitigated with the use of stiffer netting, such as copper alloy mesh. However, little is known regarding the bending characteristics of copper alloy nets and their relationship to the volumetric deformation of a fish cage. In this study, numerical modeling tools and techniques are developed and used to predict the dynamic structural behavior of gravity fish cages with copper alloy. An analytical model is validated by experimental testing to obtain an equivalent flexural rigidity. The model is used for finite element studies of the effect of bending resistance on the volume loss of fish cages with copper alloy netting. The contribution of the copper alloy’s bending resistance to the volumetric stability is found to be minimal for the tested configurations. Thus, the traditional numerical modeling techniques (i.e. using truss elements) are sufficient for analyzing copper alloy cage configurations

Dataset for: A Comprehensive Pipeline for Multi-Resolution Modeling of the Mitral Valve: Validation, Computational Efficiency, and Predictive Capability

Multiple studies have demonstrated that the pathological geometries unique to each patient can affect the durability of mitral valve (MV) repairs. While computational modeling of the MV is a promising approach to improve the surgical outcomes, the complex MV geometry precludes use of simplified models. Moreover, the lack of complete in-vivo geometric information presents significant challenges in the development of patient-specific computational models. There is thus a need to determine the level of detail necessary for predictive MV models. To address this issue, we developed a novel pipeline for building attribute-rich computational models of MV with varying fidelity directly from the in-vitro imaging data. The approach combines high-resolution geometric information from loaded and unloaded states to achieve a high level of anatomic detail, followed by mapping and parametric embedding of tissue attributes to build a high resolution, attribute-rich computational models. Subsequent lower resolution models were then developed, and evaluated by comparing the displacements and surface strains to those extracted from the imaging data. We then identified the critical levels of fidelity for building predictive MV models in the dilated and repaired states. We demonstrated that a model with a feature size of ~5 mm and mesh size of ~1 mm was sufficient to predict the overall MV shape, stress, and strain distributions with high accuracy. However, we also noted that more detailed models were found to be needed to simulate microstructural events. We conclude that the developed pipeline enables sufficiently complex models for biomechanical simulations of MV in different state