Analytical Solution Of Microbes Interacting With Surfaces

Nowadays, there is a rising interest in studying the behavior of microbes and their interactions with flow and surfaces. In order to explore the velocity field, pressure and forces around the microbes, the solution of Stokes equations, which is called a Stokeslet, is used. This solution represents a singular velocity field due to a concentrated external force acting on fluid at a single point. This singularity could cause the expression of velocity not integrable. We use the Regularized Stokeslet Method and Method of Images to deal with this problem. The expression of force is replaced by a radially symmetric function, which distributes the force on a certain area rather than at a single point. We perform different numerical simulations to validate the code against analytical solution for flow around a sphere and a swimmer. The numerical results match well with the exact solutions. It can be concluded that the analytical solutions of microbes interacting with surfaces can be well simulated using the method of Regularized Stokeslet

Mathematical Modeling of Eddy-Current Loss for a New Induction Heating Device

A new induction heating device is presented in this paper. This device can convert mechanical energy into heat energy by utilizing eddy currents, which are induced by rotating permanent magnets. A mathematical model is established for estimating eddy-current loss of the device. The distribution of induced currents and the resultant magnetic field intensity are considered in the process of modeling the eddy-current loss and so is the mutual influence of the electric field between neighborhood pole projection areas. Particularly, the skin effect is considered by correcting the numerical integral domain of eddy current density, which has great effect on the calculating results. Based on specific examples, the effectiveness and correctness of proposed model are proved by finite element analysis. The results show that the mathematical model can provide important reference for design and structure optimization of the device

CT Image Quality Assessment: From Phantom Development to Human Observer Studies

Purpose: To assess the Computed Tomography (CT) image quality by: first, developing custom phantoms with variable, controllable and repeatable texture features for the assessment of high-resolution CT scanners; second, applying the dynamic Fluence Field Modulation (FFM) technique and validating its efficacy by conducting a human observer study. Methods: Procedural routines for texture generation were developed based on constrained sphere packing within specified volumes. Repeatability in phantom production was investigated by printing ensembles phantoms of the same design. They were scanned and registered for assessment of measures across different prints, permitting computation of standard deviation volumes and various radiomic measures to quantify variability. Tissue contrast control was achieved by immersing these phantoms in potassium phosphate solutions with varying concentrations. Dynamic FFM was achieved by combining view-dependent Tube Current Modulation (TCM) and spatially modulating the X-ray beam through the Moiré patterns produced by the relative motion of Multiple Aperture Devices (MADs). Three different FFM imaging protocols were designed, and a 9 Alternative Forced Choice (9AFC) human observer study was to be conducted to evaluate their imaging performances. Results: All texture inserts being developed exhibited great similarity with respect to the corresponding anatomical textures. The textures further depended on the 3D printer nozzle size: smaller nozzle resulted in higher printing quality and precision but with higher variability. Although biased from the ground truth, the low standard deviations of the radiomics and the standard deviation maps indicated high repeatability of the texture features. Results for the assessment of different FFM imaging protocols via the human observer study are ongoing pending Institutional Review Board (IRB) review. Conclusion: The 3D printed texture phantoms offer a highly repeatable and flexible method to probe the ability of high-resolution CT to reproduce textures in reconstructed images. With increasing focus on task-based image quality and radiomics, such custom phantoms have the potential to play an increasing role in imaging performance assessments. The observer study with different FFM strategies helps to evaluate the detectability of certain texture features in CT scans. In summary, both the procedural phantom generation and the human observer study are effective methods for probing CT image quality

Temporal-spatial analysis of a foot-and-mouth disease model with spatial diffusion and vaccination

Foot-and-mouth disease is an acute, highly infectious, and economically significant transboundary animal disease. Vaccination is an efficient and cost-effective measure to prevent the transmission of this disease. The primary way that foot-and-mouth disease spreads is through direct contact with infected animals, although it can also spread through contact with contaminated environments. This paper uses a diffuse foot-and-mouth disease model to account for the efficacy of vaccination in managing the disease. First, we transform an age-space structured foot-and-mouth disease into a diffusive epidemic model with nonlocal infection coupling the latent period and the latent diffusive rate. The basic reproduction number, which determines the outbreak of the disease, is then explicitly formulated. Finally, numerical simulations demonstrate that increasing vaccine efficacy has a remarkable effect than increasing vaccine coverage

An Algorithm for Computing the Radix-2n Fast Fourier Transform

In digital signal processing, the Fast Fourier Transform (FFT) is a kind of high efficient method to calculate the discrete Fourier transform (DFT). It cuts the discrete signal sequence which the length is N for different radix sequences to operate using the way of handing back and partition. Currently, the radix-2 FFT algorithm is a popular approach to do the transform work. However, its computation is still big. This paper seeks for a more efficient algorithm to better reduce computational complexity and it starts the study from the radix-2 and the radix-4 fast Fourier transform, then explores more efficient and faster radix-8 FFT algorithm and finally extends to radix any power of 2. Experiments evidence that the radix-8 FFT algorithm outperform the radix-2 in all in circumstances, therefore prove the feasibility and efficiency of the radix-2n

GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combination

Recent progress in deep learning is revolutionizing the healthcare domain including providing solutions to medication recommendations, especially recommending medication combination for patients with complex health conditions. Existing approaches either do not customize based on patient health history, or ignore existing knowledge on drug-drug interactions (DDI) that might lead to adverse outcomes. To fill this gap, we propose the Graph Augmented Memory Networks (GAMENet), which integrates the drug-drug interactions knowledge graph by a memory module implemented as a graph convolutional networks, and models longitudinal patient records as the query. It is trained end-to-end to provide safe and personalized recommendation of medication combination. We demonstrate the effectiveness and safety of GAMENet by comparing with several state-of-the-art methods on real EHR data. GAMENet outperformed all baselines in all effectiveness measures, and also achieved 3.60% DDI rate reduction from existing EHR data.Comment: AAAI 2019; change the template and fix some typo