Simulation Studies of Pulsed Voltage Effects on Cells

This dissertation research focuses on the new field of pulsed electric field interactions with biological cells. In particular, Intracellular Electromanipulation which has important biomedical applications, is probed. Among the various aspects studied, nanosecond, high-intensity pulse induced electroporation is one phenomena. It is simulated based on a coupled scheme involving the current continuity and Smoluchowski equations. A dynamic pore model can be achieved by including a dependence on the pore population density and a variable membrane tension. These changes make the pore formation energy E(r) self-adjusting and dynamic in response to pore formation. Additionally, molecular dynamics (MD) simulations are also discussed as a more accurate, though computationally intensive, alternative. Besides inducing pores in cells, external voltages could also be used, in principle, to modulate action potential generation in nerves. The electric-field induced poration could block action potential propagation. This aspect has been studied by modifying the traditional cable model for nerves, by accounting for the increased membrane conductance and the altered membrane capacitance. This conduction block in nerves due to an electroporation related local short-circuit would be similar in concept to stopping the propagation of an air-pressure wave down a leaky pipe. This study also focuses on threshold process in cellular apoptosis induced by nanosecond, high-intensity electric pulses. In particular, the pulse number dependent cell survival trends are quantified based on a biophysical model of the cellular apoptotic processes. Time-dependent evolution of the caspase concentrations and the various molecular species are simulated. The numerical evaluations provide qualitative predictions of pulse number cell survival, the relative assessment of extrinsic and intrinsic pathways, and rough predictions of the time duration over which irreversible activation at the molecular level could be initiated by the electric pulses. Time dependent kinetics of the caspases as well as the various molecular species within the apoptotic pathway, were simulated using the rate equation model originally proposed by Bagci et al. Finally, an asymmetric electroporation model is presented. Electric pulsing pore energy and mechanical pore energy are studied. This has relevance to the flow of ions in and out of cells

Tourists’ green behavior: Co-creation and emotional experience

Based on the theory of inseparability nature of service, service dominant logic, and SOR model, this study examined the interactive relationships among tourists’ co-creation of experience, self-esteem, satisfaction with travel experience, quality of life, and green behavior. Using data collected from 493 tourists in China, the results indicated that co-creation of experience directly influenced their self-esteem, satisfaction with travel experience, and green behavior. Besides, the findings found that emotional experience (satisfaction with travel experience, self-esteem, quality of life) partially mediated the relationships between co-creation experience and green behavior. Finally, co-creation affected tourists’ green behavior through the chain mediating role of self-esteem, satisfaction with travel experience, and quality of life. Theoretical and practical implications were discussed as well

Viscous effect on interaction between shock wave and cylindrical bubble: based on the discrete Boltzmann method

The viscous effects on the interaction between a shock wave and a two-dimensional cylindrical bubble are investigated based on the discrete Boltzmann method (DBM). Besides some interesting Hydrodynamic Non-Equilibrium (HNE) behaviors, some relevant Thermodynamic Non-Equilibrium (TNE) behaviors are carefully studied. It is found that the viscosity contributes little effect on the dynamic processes in the shock compression stage but significantly influences them in the post-shock stage. A bubble with a smaller viscosity coefficient displays a stouter jet structure, can be compressed more easily, and reaches its minimum characteristic scales slower. The viscosity accelerates the average motion of the bubble, reduces the vorticity strength (circulation), and restrains the material mixing between the ambient gas and the bubble. The viscous effects on different TNE quantities/perspectives show interesting differences. These differences indicate the complexity of TNE behaviors, which still requires further understanding. The viscous effects on entropy production are also investigated. It is found that the entropy production caused by the non-organized momentum flux (NOMF) is larger than that caused by the non-organized energy flux (NOEF). As the Prandtl number increases, the entropy production $S_{\rm{NOMF}}$ increases. But the $S_{\rm{NOEF}}$ first decreases and then approaches a saturation value

Identifying influential nodes in complex contagion mechanism

Identifying influential nodes in complex networks is one of the most important and challenging problems to help optimize the network structure, control the spread of the epidemic and accelerate the spread of information. In a complex network, the node with the strongest propagation capacity is known as the most influential node from the perspective of propagation. In recent years, identifying the key nodes in complex networks has received increasing attention. However, it is still a challenge to design a metric that has low computational complexity but can accurately identify important network nodes. Currently, many centrality metrics used to evaluate the influence capability of nodes cannot balance between high accuracy and low time complexity. Local centrality suffers from accuracy problems, while global metrics require higher time complexity, which is inefficient for large scale networks. In contrast, semi-local metrics are with higher accuracy and lower time cost. In this paper, we propose a new semi-local centrality measure for identifying influential nodes under complex contagion mechanisms. It uses the higher-order structure within the first and second-order neighborhoods of nodes to define the importance of nodes with near linear time complexity, which can be applied to large-scale networks. To verify the accuracy of the proposed metric, we simulated the disease propagation process in four real and two artificial networks using the SI model under complex propagation. The simulation results show that the proposed method can identify the nodes with the strongest propagation ability more effectively and accurately than other current node importance metrics

ThumbNet: One Thumbnail Image Contains All You Need for Recognition

Although deep convolutional neural networks (CNNs) have achieved great success in computer vision tasks, its real-world application is still impeded by its voracious demand of computational resources. Current works mostly seek to compress the network by reducing its parameters or parameter-incurred computation, neglecting the influence of the input image on the system complexity. Based on the fact that input images of a CNN contain substantial redundancy, in this paper, we propose a unified framework, dubbed as ThumbNet, to simultaneously accelerate and compress CNN models by enabling them to infer on one thumbnail image. We provide three effective strategies to train ThumbNet. In doing so, ThumbNet learns an inference network that performs equally well on small images as the original-input network on large images. With ThumbNet, not only do we obtain the thumbnail-input inference network that can drastically reduce computation and memory requirements, but also we obtain an image downscaler that can generate thumbnail images for generic classification tasks. Extensive experiments show the effectiveness of ThumbNet, and demonstrate that the thumbnail-input inference network learned by ThumbNet can adequately retain the accuracy of the original-input network even when the input images are downscaled 16 times

Dietary exposure level of to perfluorinated compounds and its relationship with perinatal adverse events in pregnant women in Xuhui District of Shanghai

BackgroundPerfluorinated compounds (PFCs) are persistent organic pollutants. Dietary exposure to PFCs among pregnant women may lead to elevated risks of adverse events during pregnancy and postpartum depression. ObjectiveTo estimate potential risk of dietary exposure to PFCs among pregnant women in Xuhui District, Shanghai, and the relationship between dietary PFCs exposure and risks of adverse events during pregnancy and postpartum depression. MethodsThis study was a small cohort study which recruited women residing in Xuhui District from July 2017 to September 2018. All information was collected through questionnaires by trained investigators. Basic information and dietary information were collected at the time of inclusion, where the dietary information was obtained through the Food Frequency Questionnaire (FFQ). A follow-up visit was conducted within 42 d after delivery to collect the occurrence of adverse events during pregnancy and postpartum depression. According to the results of dietary survey, sampling and PFCs level testing were conducted on commercially available staple foods, poultry and livestock meat, aquatic products, vegetables, milk and dairy products, eggs, etc. The food sampling points covered all subdistricts in Xuhui District, including farmers' markets, supermarkets, convenience stores, and shops. Daily exposure level and hazard ratio (HR) of PFCs per capita were calculated according to the dietary survey and laboratory testing. Logistic regression was used to estimate the relationship between PFCs exposure and the risks of adverse events during pregnancy and postpartum depression. The levels of PFCs exposure were further divided into 4 groups according to interquartile range, and OR and Ptrend value were calculated respectively. ResultsA total of 345 pregnant women were recruited in this study, whose average age was (29.61±4.92) years. Among them, 26.37% subjects reported at least one adverse event during pregnancy, and 30.14% subjects reported an Edinburgh Postnatal Depression Scale (EPDS) score ≥12. A total of 132 food samples were collected and tested, and PFCs were positive mainly in milk and dairy products, poultry meat, livestock meat, eggs, fresh water products, and sea water products. The PFCs positive rate in fresh water products was the highest, reaching 100%. The average concentration of PFCs in the positive samples was 0.018-2.10 μg·kg−1. The HR of PFCs was 4.44. A higher risk of postpartum depression was found along with a higher perfluorooctane sulfonate (PFOS) exposure level (Ptrend=0.02). ConclusionDietary PFCs exposure may pose a health risk to pregnant women. The study findings suggest that decreasing the intake of freshwater products might help reduce the risk of PFCs exposure among pregnant women in Xuhui district, Shanghai