A Subdomain Method for Mapping the Heterogeneous Mechanical Properties of the Human Posterior Sclera

Although strongly correlated with elevated intraocular pressure, primary open-angle glaucoma (POAG) occurs in normotensive eyes. Mechanical properties of the sclera around the optic nerve head (ONH) may play a role in this disparity. The purpose of this study is to present an automated inverse mechanics based approach to determine the distribution of heterogeneous mechanical properties of the human sclera as derived from its surface deformations arising from pressure inflation experiments. The scleral shell of a 78 year old European Descent male donor eye was utilized to demonstrate the method; the sclera was coated with a speckle pattern on the outer surface and was subjected to inflation pressures of 5, 15, 30, and 45 mmHg. The speckle pattern was imaged at each pressure, and a displacement field was calculated for each pressure step using a previously described sequential digital image correlation (S-DIC) technique. The fiber splay and fiber orientation of the sclera collagen were determined experimentally, and the thickness across the scleral globe was determined using micro CT images. The displacement field from the inflation test was used to calculate the strain and also used as an input for inverse mechanics to determine the heterogeneity of material properties. The scleral geometry was divided into subdomains using the first principal strain. The Holzapfel anisotropic material parameters of matrix and fiber stiffness were estimated within each individual subdomain using an inverse mechanics approach by minimizing the sum of the square of the residuals between the computational and experimental displacement fields. The mean and maximum error in displacement across all subdomains were 8.9 ± 3.0 μm and 13.2 μm, respectively. The full pressure-inflation forward mechanics experiment was done using subdomain-specific mechanical properties on the entire scleral surface. The proposed approach is effective in determining the distribution of heterogeneous mechanical properties of the human sclera in a user-independent manner. Our research group is currently utilizing this approach to better elucidate how scleral stiffness influences those at high risk for POAG

A novel methodology to create generative statistical models of interconnects

This paper addresses the problem of constructing a generative statistical model for an interconnect starting from a limited set of S-parameter samples, which are obtained by simulating or measuring the interconnect for a few random realizations of its stochastic physical properties. These original samples are first converted into a pole-residue representation with common poles. The corresponding residues are modeled as a correlated stochastic process by means of principal component analysis and kernel density estimation. The obtained model allows generating new samples with similar statistics as the original data. A passivity check is performed over the generated samples to retain only passive data. The proposed approach is applied to a representative coupled microstrip line example

SBC2008-193100 ANALYTICAL SOLUTIONS TO AXISYMMETRIC PLANE STRAIN POROUS MEDIA- TRANSPORT MODELS IN LARGE ARTERIES

INTRODUCTION Theoretical and numerical finite element models (FEMs) have been developed for analysis of coupled structural-fluid-species transport in soft tissues Based on experimental observations [4], osmotic pressure and partial Onsager coupling of species transport can be neglected for large mobile species in rabbit carotid arteries. These analytical solutions provide a starting point for development of solutions to more complex problems and allow verification of the associated FEMs under development in our laboratory. The analytical solutions will allow comparison of elastic and poroelastic-species transport for axisymmetric, plane strain in thick-walled arteries including expressions for displacement, strain, stress, pore fluid pressure, and concentration fields,. The initial models considered here will be steady state (SS) solutions for compressible, linear, isotropic materials undergoing small strains

A novel generative stochastic model for high-speed interconnection links

In this paper we introduce a new modeling approach to create a generative model for stochastic link responses. The proposed scheme starts from a limited set of simulated or measured ‘training samples’, which are first represented by a rational model using vector fitting with common poles. Next, the generative model is built, leveraging the residues' stochastic distribution, via a principal component analysis and kernel density estimation. Then, in a post-processing phase, non-passive samples are discarded. The novel method is applied to a commercial connector footprint, a multi-conductor transmission line, and a complete link composed of the cascade connection of the former components

A Subdomain Method for Mapping the Heterogeneous Mechanical Properties of the Human Posterior Sclera

Although strongly correlated with elevated intraocular pressure, primary open-angle glaucoma (POAG) occurs in normotensive eyes. Mechanical properties of the sclera around the optic nerve head (ONH) may play a role in this disparity. The purpose of this study is to present an automated inverse mechanics based approach to determine the distribution of heterogeneous mechanical properties of the human sclera as derived from its surface deformations arising from pressure in fl ation experiments. The scleral shell of a 78 year old European Descent male donor eye was utilized to demonstrate the method; the sclera was coated with a speckle pattern on the outer surface and was subjected to in fl ation pressures of 5, 15, 30, and 45 mmHg. The speckle pattern was imaged at each pressure, and a displacement fi eld was calculated for each pressure step using a previously described sequential digital image correlation(S-DIC) technique. The fiber splay and fiber orientation of the sclera collagen were determined experimentally, and the thickness across the scleral globe was determined using micro CT images. The displacement fi eld from the in fl ation test was used to calculate the strain and also used as an input for inverse mechanics to determine the heterogeneity of material properties. The scleral geometry was divided into subdomains using the first principal strain. The Holzapfel anisotropic material parameters of matrix and fiber stiffness were estimated within each individual subdomain using an inverse mechanics approach by minimizing the sum of the square of the residuals between the computational and experimental displacement fields. The mean and maximum error in displacement across all subdomains were 8.9 +/- 3.0 mu m and 13.2 mu m, respectively. The full pressure-inflation forwardmechanics experiment was done using subdomain-specific mechanical properties on the entire scleral surface. The proposed approach is effective in determining the distribution of heterogeneous mechanical properties of the human sclera in a user-independent manner. Our research group is currently utilizing this approach to better elucidate how scleral stiffness influences those at high risk for POAG.National Eye Institute of the National Institutes of Health (NIH) [R01EY020890, R01FD006582]; University of Pittsburgh Center for Research Computing (CRC); Pittsburgh Supercomputer Center through NSF-XSEDE award [TG-ENG160035]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

A generative modeling framework for statistical link analysis based on sparse data

This paper proposes a novel strategy for creating generative models of stochastic link responses starting from limited available data. Whereas state-of-the-art techniques, e.g., based on generalized polynomial chaos expansions, require a considerable amount of (expensive) input data, here we start from a small set of "training" responses. These responses are obtained either from simulations or measurements to construct a comprehensive stochastic model. Using this model, new response samples can be generated with a distribution as similar as possible to the real data distribution, for use in Monte Carlo-like analyses. The methodology first uses the standard Vector Fitting algorithm to fit the S-parameter data with rational functions having common poles. Then, a generative model for the residues is created by means of principal component analysis and kernel density estimation. An a posteriori selection of passive samples is performed on the generated data to ensure the new samples are physically consistent. The proposed modeling approach is applied to a commercial connector and to a set of differential striplines. Both are concatenated to produce the stochastic analysis of a complete link. Comparisons on the prediction of time-domain responses are also provided

SBC2008-193021 COMPUTATIONAL SIMULATION OF A MEMS-BASED MICROACTUATOR FOR TISSUE ENGINEERING APPLICATIONS

INTRODUCTION The relationship between the 3D microstructure of tissueengineered constructs (TECs) and their resulting mechanical and biological function is critical in providing TECs with clinically meaningful mechanical properties in reasonable incubation times. We hypothesize that the next generation of TECs must incorporate a controllable and optimized microstructure (and resulting mechanical properties) if they are to mechanically and biologically mimic tissue function. While the development of a robustly engineered tissue replacement will undoubtedly require simultaneous biochemical and biomechanical stimulation, this paper will focus on the development of a device to impose localized micro-mechanical stimulation. In this paper a MEMS-based device is introduced that can differentially stimulate the mechanical microenvironment of TECs using a noninvasive magnetic actuation mechanism. The device consists of a bed of micro-flaps (MFs) that are doped with a para/ferromagnetic material. Since the fabrication of such a device can be costly, the purpose of the current work is to develop a computational tool that can aid in device design. Finite element models (FEMs) are introduced to determine the relationship between MF/magnet size/properties and horizontal MF deflection. Towards this end, a 2D magneto-structural model was created to guide the development of a microdevice with a desired MF deflection

A finite element model for mixed porohyperelasticity with transport, swelling, and growth

The purpose of this manuscript is to establish a unified theory of porohyperelasticity with transport and growth and to demonstrate the capability of this theory using a finite element model developed in MATLAB. We combine the theories of volumetric growth and mixed porohyperelasticity with transport and swelling (MPHETS) to derive a new method that models growth of biological soft tissues. The conservation equations and constitutive equations are developed for both solid-only growth and solid/fluid growth. An axisymmetric finite element framework is introduced for the new theory of growing MPHETS (GMPHETS). To illustrate the capabilities of this model, several example finite element test problems are considered using model geometry and material parameters based on experimental data from a porcine coronary artery. Multiple growth laws are considered, including time-driven, concentrationdriven, and stress-driven growth. Time-driven growth is compared against an exact analytical solution to validate the model. For concentration-dependent growth, changing the diffusivity (representing a change in drug) fundamentally changes growth behavior. We further demonstrate that for stress-dependent, solid-only growth of an artery, growth of an MPHETS model results in a more uniform hoop stress than growth in a hyperelastic model for the same amount of growth time using the same growth law. This may have implications in the context of developing residual stresses in soft tissues under intraluminal pressure. To our knowledge, this manuscript provides the first full description of an MPHETS model with growth. The developed computational framework can be used in concert with novel in-vitro and in-vivo experimental approaches to identify the governing growth laws for various soft tissues

Development and performance of the c4c national clinical trial networks for optimizing pediatric trial facilitation

Introduction:The high failure rate of industry-driven pediatric clinical trials leads to insufficient timely labeling of drugs in children and a lack of scientific evidence, resulting in the persistently high off-label drug use. National clinical trial networks can facilitate collaboration between sites, investigators, and experts, increasing the likelihood of successful trials. Within the conect4children (c4c) network, an Innovative Medicines Initiative 2-funded project, National Hubs hosted by National Clinical Trials Networks were set up across 21 European countries to facilitate the setup and execution of pediatric clinical trials. In this paper, we aim to present the performance metrics of the trial feasibility process as well as learnings and challenges encountered by the Belgian and Dutch Networks in working within the European c4c project.Method:The c4c National Hubs streamline pediatric clinical trials by initiating early country outreach, identifying overlapping studies, recommending quality trial sites, and supporting trial budgeting for both industry and academic settings. To show the impact of Pedmed-NL and Belgian Pediatric Clinical Research Network (BPCRN), internal metrics were collected from 2019 to 2022 on four industry-sponsored and three academic trials performed within the c4c network. Timelines and outcomes of the site identification were collected and analyzed for industry trials. A qualitative analysis was conducted through c4c platforms, sponsor interactions, and stakeholder engagement to evaluate the added value of a research network.Results:In industry-sponsored trials, full feasibility questionnaires were completed within 2 weeks (n = 48), and inclusion rates were up to 80% of clinical sites. Before committing to c4c, 14% of sites were contacted by industry, leading to communication burdens. Utilizing national infrastructure knowledge and therapeutic environment insights helped optimize trial timelines and address feasibility challenges. In addition, national adaptations, such as bilingual staff and site development, played a role in streamlining trial operations in both academic and industry settings. Performance and experiences were similar for both networks.Conclusion:The early-facilitation examples from the c4c trials demonstrated promising metrics for two National Hubs, including optimized start-up timelines and aiding site selection quality. The learnings and challenges of the Belgian and Dutch Networks provided insights for the development of clinical research networks