Topological Design of Multi-Material Compliant Mechanisms with Global Stress Constraints

This paper presents an approach for the topological design of multi-material compliant mechanisms with global stress constraints. The element stacking method and the separable stress interpolation scheme are applied to calculate the element stiffness and element stress of multi-material structures. The output displacement of multi-material compliant mechanisms is maximized under the constraints of the maximum stress and the structural volume of each material. The modified P-norm method is applied to aggregate the local von Mises stress constraints for all the finite elements to a global stress constraint. The sensitivities are calculated by the adjoint method, and the method of moving asymptotes is utilized to update the optimization problem. Several numerical examples are presented to demonstrate the effectiveness of the proposed method. The appearance of the de facto hinges in the optimal mechanisms can be suppressed effectively by using the topology optimization model with global stress constraints, and the stress constraints for each material can be met.

Alterations of structural connectivity and structural co-variance network in focal cortical dysplasia

Background The aim of this study was to investigate alterations in structural connectivity and structural co-variance network in patients with focal cortical dysplasia (FCD). Methods We enrolled 37 patients with FCD and 35 healthy controls. All subjects underwent brain MRI with the same scanner and with the same protocol, which included diffusion tensor imaging (DTI) and T1-weighted imaging. We analyzed the structural connectivity based on DTI, and structural co-variance network based on the structural volume with T1-weighted imaging. We created a connectivity matrix and obtained network measures from the matrix using the graph theory. We tested the difference in network measure between patients with FCD and healthy controls. Results In the structural connectivity analysis, we found that the local efficiency in patients with FCD was significantly lower than in healthy controls (2.390 vs. 2.578, p = 0.031). Structural co-variance network analysis revealed that the mean clustering coefficient, global efficiency, local efficiency, and transitivity were significantly decreased in patients with FCD compared to those in healthy controls (0.527 vs. 0.635, p = 0.036; 0.545 vs. 0.648, p = 0.026; 2.699 vs. 3.801, p = 0.019; 0.791 vs. 0.954, p = 0.026, respectively). Conclusions We demonstrate that there are significant alterations in structural connectivity, based on DTI, and structural co-variance network, based on the structural volume, in patients with FCD compared to healthy controls. These findings suggest that focal lesions with FCD could affect the whole-brain network and that FCD is a network disease.

LayOpt: an educational web-app for truss layout optimization

A new interactive truss layout optimization web-app has been developed for educational use. This has been designed to be used on a range of devices, from mobile phones to desktop PCs. Truss designs are first generated via numerical layout optimization and then rationalized via geometry optimization. It is then shown that these designs can be simplified using a computationally inexpensive process that allows the user to control the trade-off between complexity and structural volume. The process involves the use of smooth Heaviside representations of member existence variables, with nodal slack forces employed that allow unstable intermediate truss structures. Full details of the web-app are provided in this contribution, from underlying formulation to cloud computing implementation. A range of numerical examples are used to demonstrate the efficacy of the web-app, and to show how it can potentially be used in educational and practical engineering settings.

Are there network differences between the ipsilateral and contralateral hemispheres of pain in patients with migraine?

Background The present study aimed to investigate differences in the structural co-variance network based on structural volume and differences in the functional network based on cerebral blood flow between the ipsilateral and contralateral hemispheres of pain in patients with migraine. Methods We prospectively enrolled 27 patients with migraine without aura, all of whom had unilateral migraine pain that always occurred on the same side. We defined the ipsilateral hemisphere as the side of migraine pain, whereas we defined the contralateral hemisphere as that contralateral to the side of migraine pain. We obtained structural volumes using three-dimensional T1-weighted images and cerebral blood flow measurements using arterial spin labeling MRI. We then analyzed structural co-variance networks based on structural volumes and functional networks based on cerebral blood flow using graph theory. Results There were no significant differences in structural volume or cerebral blood flow between the ipsilateral and contralateral hemispheres. However, there were significant differences in the structural co-variance network and functional network. In the structural co-variance network, the betweenness centrality of the thalamus was lower in the ipsilateral hemisphere than in the contralateral hemisphere. In the functional network, the betweenness centrality of the anterior cingulate and paracingulate gyrus was lower, while that of the opercular part of the inferior frontal gyrus was higher, in the ipsilateral hemisphere than in the contralateral hemisphere. Conclusion The present findings successfully demonstrate that there are significant differences in the structural co-variance network and functional network between the ipsilateral and contralateral hemispheres of pain in patients with migraine. Such findings may be related to the pathogenesis of pain in these patients.

CerebrA: Accurate registration and manual label correction of Mindboggle-101 atlas for MNI-ICBM152 template

Accurate anatomical atlases are recognized as important tools in brain-imaging research. They are widely used to estimate disease-specific changes and therefore, are of great relevance in extracting regional information on volumetric variations in clinical cohorts in comparison to healthy populations. The use of high spatial resolution magnetic resonance imaging and the improvement in data preprocessing methods have enabled the study of structural volume changes on a wide range of disorders, particularly in neurodegenerative diseases where different brain morphometry analyses are being broadly used in an effort to improve diagnostic biomarkers.In the present dataset, we introduce the Cerebrum Atlas (CerebrA) along with the MNI-ICBM2009c average template. MNI-ICBM2009c is the most recent version of the MNI-ICBM152 brain average, providing a higher level of anatomical details. Cerebra is based on an accurate non-linear registration of cortical and subcortical labelling from Mindboggle 101 to the symmetric MNI-ICBM2009c atlas, followed by manual editing.

Electric field causes volumetric changes in the human brain

Recent longitudinal neuroimaging studies in patients with electroconvulsive therapy (ECT) suggest local effects of electric stimulation (lateralized) occur in tandem with global seizure activity (generalized). We used electric field (EF) modeling in 151 ECT treated patients with depression to determine the regional relationships between EF, unbiased longitudinal volume change, and antidepressant response across 85 brain regions. The majority of regional volumes increased significantly, and volumetric changes correlated with regional electric field (t = 3.77, df = 83, r = 0.38, p=0.0003). After controlling for nuisance variables (age, treatment number, and study site), we identified two regions (left amygdala and left hippocampus) with a strong relationship between EF and volume change (FDR corrected p<0.01). However, neither structural volume changes nor electric field was associated with antidepressant response. In summary, we showed that high electrical fields are strongly associated with robust volume changes in a dose-dependent fashion.

Energy-Based Robustness Measure for Deteriorating Structures

<p>An approach to robustness assessment of structural systems undergoing continuous damage is presented. Damage is described by means of a dimensionless index associated with prescribed patterns of cross-sectional deterioration and computed through a weighted average over the structural volume based on strain energy. The variation of a performance indicator associated with deformation modes and load participation factors is related to the amount of damage to obtain a dimensionless measure of structural robustness. The proposed approach is applied to structural robustness assessment of an arch bridge under continuous deterioration.</p>