A rapid and automated computational approach to the design of multistable soft actuators

We develop an automated computational modeling framework for rapid gradient-based design of multistable soft mechanical structures composed of non-identical bistable unit cells with appropriate geometric parameterization. This framework includes a custom isogeometric analysis-based continuum mechanics solver that is robust and end-to-end differentiable, which enables geometric and material optimization to achieve a desired multistability pattern. We apply this numerical modeling approach in two dimensions to design a variety of multistable structures, accounting for various geometric and material constraints. Our framework demonstrates consistent agreement with experimental results, and robust performance in designing for multistability, which facilities soft actuator design with high precision and reliability

A coupled SPH-DEM model for fluid-structure interaction problems with free-surface flow and structural failure

An integrated particle model is developed to study fluid-structure interaction (FSI) problems with fracture in the structure induced by the free surface flow of the fluid. In this model, the Smoothed Particle Hydrodynamics (SPH) based on the kernel approximation and particle approximation is used to model the fluid domain in accordance with Navier-Stokes equations and the Discrete Element Method (DEM) with a parallel bond model is used to represent the real solid structure through a hexagonal packing of bonded particles. Validation tests have been carried out for the DEM model of the structure with deformation and fracture failure, the SPH model of the fluid and the coupled SPH-DEM model of FSI without fracture, all showing very good agreement with analytical solutions and/or published experimental and numerical results. The simulation results of FSI with fracture indicate that the SPH-DEM model developed is capable of capturing the entire FSI process from structural deformation to structural failure and eventually to post-failure deformable body movement

Reduced Order Modeling of Blood Flow and Applications

Cardiovascular disease (CVD) is the leading cause of death worldwide. Image-based computational fluid dynamic (CFD) simulations have been widely used to characterize patient-specific blood flow features in the cardiovascular system. The simulation results provide high spatiotemporal resolution of functional indicators of CVD not revealed through imaging. Moreover, computational modeling provides the ability to virtually test interventions or devices. Despite this upside, patient-specific simulations remain computationally expensive, prone to numerical instabilities, and can be sensitive to method parameters, all of which have limited their clinical use. These limitations have also been prohibitive in research applications requiring parametric analyses such as uncertainty quantification, data assimilation, optimization, parameter tuning, etc. These factors motivate the need for reduced-order modeling (ROM) of blood flow to be used in place of, or in conjunction with, fully-resolved CFD modeling.As such, this dissertation focuses on developing ROMs to efficiently compute blood flow in cardiovascular domains that can enable timely decision support, and applications requiring ensembles of numerical simulations. Through fundamental understanding of physics and physiology, we developed a novel physics-based ROM strategy, that not only calculates blood flow and pressure at a fraction of the computational cost compared to the current standard CFD, but can do so much more accurately than other existing ROM methods. The proposed method demonstrated consistent agreement with CFD simulations in terms of flow rate and pressure distribution over a broad range of hemodynamic conditions and vascular geometries. To evaluate the utility of this ROM methodology, we applied this framework to several translational and research applications

A Distributed Lumped Parameter Model of Blood Flow

We propose a distributed lumped parameter (DLP) modeling framework to efficiently compute blood flow and pressure in vascular domains. This is achieved by developing analytical expressions describing expected energy losses along vascular segments, including from viscous dissipation, unsteadiness, flow separation, vessel curvature and vessel bifurcations. We apply this methodology to solve for unsteady blood flow and pressure in a variety of complex 3D image-based vascular geometries, which are typically approached using computational fluid dynamics (CFD) simulations. The proposed DLP framework demonstrated consistent agreement with CFD simulations in terms of flow rate and pressure distribution, with mean errors less than 7% over a broad range of hemodynamic conditions and vascular geometries. The computational cost of the DLP framework is orders of magnitude lower than the computational cost of CFD, which opens new possibilities for hemodynamics modeling in timely decision support scenarios, and a multitude of applications of imaged-based modeling that require ensembles of numerical simulations

Regulatory Role of PFC Corticotropin-Releasing Factor System in Stress-Associated Depression Disorders: A Systematic Review

Stress has a substantial role in formation of psychiatric disorders especially depression. Meanwhile, impairment of the prefrontal cortex (PFC) is connected to the executive and cognitive deficits induced by the stress. Given the involvement of the corticotropin-releasing factor (CRF) in stress-related processes and knowing the fact that PFC hosts a lot of CRF receptors and CRF neurotransmissions, it can worth to look at the CRF as a potential treatment for the regulation of depression disorders induced by stress within PFC region. Here, for the first time we aimed to systematically review the effectiveness of intra-PFC CRF system in the modulation of depression dysfunction caused by the stress in clinical and preclinical models/studies. Qualified researches were combined utilizing a comprehensive search of six databases including Scopus, Pubmed, Web of Science, Sciencedirect, APA PsycNet, and Embase in April 2021 and were evaluated through proper methodological quality assessment tools. Results indicate that PFC has a remarkable role in the modulation for stress-induced depression and intra-PFC CRF receptors agonist and antagonist are very considerable for regulating these types of impairments. Specifically, elevation of both CRF immunoreactivity and gene expression were observed in human studies. In the animal studies, mostly immunoreactivity or excitatory/inhibitory currents of CRF within the PFC regulated depression dysfunction. In conclusion, reviewed studies show a positive attitude toward the CRF system in regulation of the stress-induced depression; however, obviously further investigations are required to get closer to the best treatment

Endocannabinoids and addiction memory: Relevance to methamphetamine/morphine abuse

Aim This review aims to summarise the role of endocannabinoid system (ECS), incluing cannabinoid receptors and their endogenous lipid ligands in the modulation of methamphetamine (METH)/morphine-induced memory impairments. Methods Here, we utilized the results from researches which have investigated regulatory role of ECS (including cannabinoid receptor agonists and antagonists) on METH/morphine-induced memory impairments. Results Among the neurotransmitters, glutamate and dopamine seem to play a critical role in association with the ECS to heal the drug-induced memory damages. Also, the amygdala, hippocampus, and prefrontal cortex are three important brain regions that participate in both drug addiction and memory task processes, and endocannabinoid neurotransmission have been investigated. Conclusion ECS can be regarded as a treatment for the side effects of METH and morphine, and their memory-impairing effects

Intra-hippocampal administration of orexin receptor antagonists dose-dependently attenuates reinstatement of morphine seeking behavior in extinguished rats

It has been shown that the hippocampus plays an essential role in the regulation of reward and memory as indicated by the conditioned place preference (CPP) paradigm. Morphine-induced CPP is a common method to consider motivational properties of morphine in animals. Recently, this model has been used in many laboratories to investigate neuronal mechanisms underlying reinstatement of morphine seeking induced by drug reexposure. Our previous studies indicate that the hippocampus especially CA1 region is involved in reinstatement of drug-seeking behaviors. Also, several studies have shown that orexin attenuates key functional and behavioral effects of its co-transmitter dynorphin. The present study evaluates the role of orexinergic receptors within the CA1 region of the hippocampus in the reinstatement of morphine-induced CPP. Therefore, after the extinction period, the different doses (SB 334867; 0.3, 3, and 30 nM/0.5 mu l DMSO) of either orexin-1 or -2 receptor antagonists were bilaterally microinjected into the CA1, 15 min before receiving an effective priming dose of morphine (1 mg/kg). The results revealed that administration of both SB 334867 and TCS OX2 29 prior to injection of the priming dose of morphine significantly reduced the reinstatement of morphine-induced CPP without altering the animal's locomotor activity. Also, the 50% effective dose value of SB 334867 on the reinstatement of morphine seeking behavior was close three times more than that in TCS OX2 29 treatment group. Therefore, the consequences suggested that both orexin receptors in the CA1 play a considerable role in the reinstatement of morphine-induced CPP