Long-Lasting Nanotherapeutics for the Treatment of Eye Diseases

Blindness represents a substantial burden to the healthcare system. However, delivering therapeutics to the eye is a challenge on multiple levels. Rapid clearance of medications in eye drops requires that they be applied frequently, but patient compliance with eye drop regimens is poor (e.g., glaucoma patients only take roughly one-half of their doses correctly). In addition, drug penetration to the back of the eye following topical administration is limited due to multiple ocular barriers. On the other hand, the blood-retinal barrier limits the delivery of drugs into the eye following systemic administration. In this talk, I will present a long-lasting polymeric drug delivery system engineered to enhance ocular therapeutic activity through prolonging drug half-life, releasing drugs in a controlled fashion, and eliminating toxic side effects for improved treatment of eye diseases

3D Body Tracking using Deep Learning

This thesis introduces a 3D body tracking system based on neutral networks and 3D geometry, which can robustly estimate body poses and accurate body joints. This system takes RGB-D data as input. Body poses and joints are firstly extracted from color image using deep learning approach. The estimated joints and skeletons are further translated to 3D space by using camera calibration information. This system is running at the rate of 3 4 frames per second. It can be used to any RGB-D sensors, such as Kinect, Intel RealSense [14] or any customized system with color depth calibrated. Comparing to the sate-of-art 3D body tracking system, this system is more robust, and can get much more accurate joints locations, which will benefits projects require precise joints, such as virtual try-on, body measure, real-time avatar driven

Effect of corticosteroid therapy in acute pain edema caused by Herpes Zoster

Purpose: To evaluate the curative effect of corticosteroids in the treatment of acute pain, local edema, and skin lesions caused by herpes zoster, and to develop some pertinent therapeutic guidelines.Methods: A total of 48 cases of patients diagnosed with herpes zoster from 2010 to 2011 in the dermatology clinic of Shan Dong Traffic Hospital were selected and all received the same therapy of antiviral, pain-relieving and nerve nutrition. They were divided into a corticosteroid application group, with 24 patients treated with corticosteroids, and a control group of 24 patients without corticosteroids. Local swelling subsided in the corticosteroid group. The differences observed in pain relief and days needed for blisters to dry and scab between the two patient groups were analyzed to determine significance and, thus, assess the curative effect of corticosteroids in treatment of herpes zoster.Results: Patients in the glucocorticosteroid application group relieved pain faster than patients in the control group (2.38 ± 1.41 days vs 5.50 ± 3.19 days), and the difference was significant (p < 0.05). Skin lesions of patients in the glucocorticosteroid application group healed quicker than that of patients in control group (2.83 ± 0.87 days vs 3.54 ± 1.02 days), and the difference was remarkable (p < 0.05). Local swelling of patients in the glucocorticosteroid application group recovered rapidly after treatment. .Conclusion: Treatment of herpes zoster with appropriate corticosteroid isodose application can effectively relieve acute pain and local swelling, and speed up scabbing and healing of skin lesions.Keywords: Herpes zoster, Corticosteroids, Local edema, Scab, Skin lesions, Acute pain, Blisters, Therapeutic guideline

An efficient iterative method for dynamical Ginzburg-Landau equations

In this paper, we propose a new finite element approach to simulate the time-dependent Ginzburg-Landau equations under the temporal gauge, and design an efficient preconditioner for the Newton iteration of the resulting discrete system. The new approach solves the magnetic potential in H(curl) space by the lowest order of the second kind Nedelec element. This approach offers a simple way to deal with the boundary condition, and leads to a stable and reliable performance when dealing with the superconductor with reentrant corners. The comparison in numerical simulations verifies the efficiency of the proposed preconditioner, which can significantly speed up the simulation in large-scale computations

A Priori Analysis of Stable Neural Network Solutions to Numerical PDEs

Methods for solving PDEs using neural networks have recently become a very important topic. We provide an a priori error analysis for such methods which is based on the $\mathcal{K}_1(\mathbb{D})$-norm of the solution. We show that the resulting constrained optimization problem can be efficiently solved using a greedy algorithm, which replaces stochastic gradient descent. Following this, we show that the error arising from discretizing the energy integrals is bounded both in the deterministic case, i.e. when using numerical quadrature, and also in the stochastic case, i.e. when sampling points to approximate the integrals. In the later case, we use a Rademacher complexity analysis, and in the former we use standard numerical quadrature bounds. This extends existing results to methods which use a general dictionary of functions to learn solutions to PDEs and importantly gives a consistent analysis which incorporates the optimization, approximation, and generalization aspects of the problem. In addition, the Rademacher complexity analysis is simplified and generalized, which enables application to a wide range of problems.Comment: This paper has been merged with arXiv:2107.0446