Nanocapsule-Based Prodrugs for Targeted Treatment of AIDS-Associated Non-Hodgkin Lymphoma

IABSTRACT OF THE DISSERTATION Non-Hodgkin lymphoma (NHL) is the most prevalent hematopoietic malignancy in the United States; notably, NHL patients with congenital and acquired immunodeficiencies (AIDS) are at elevated risk of brain metastases. Currently, there have been numerous treatments, particularly in the field of antibody-based immunotherapy and immune-modulation therapy, developed to tackle this problem. However, low delivery efficiency, short half-life and non- specific toxicity of the drugs pose significant setbacks to the efficacy of said treatments. To address these challenges, we propose a novel nanocapsule based platform that encapsulates the native drugs using various monomers and crosslinkers through free radical polymerization, which modifies the surface property of the drugs and allows high penetration into deeper tumor tissue and across the blood brain barrier (BBB) while improving the stability of the drugs in vivo. Notably, the inclusion of metalloproteinase-2 (MMP-2) degradable crosslinker serves as a controlled release mechanism which can be used to target MMP-rich tumor microenvironment, reducing the overall side-effects of the drugs across the system

Maximizing Revenue With Adaptive Modulation and Multiple FECs in Flexible Optical Networks

Flexible optical networks (FONs) are being adopted to accommodate the increasingly heterogeneous traffic in today's Internet. However, in presence of high traffic load, not all offered traffic can be satisfied at all time. As carried traffic load brings revenues to operators, traffic blocking due to limited spectrum resource leads to revenue losses. In this study, given a set of traffic requests to be provisioned, we consider the problem of maximizing operator's revenue, subject to limited spectrum resource and physical layer impairments (PLIs), namely amplified spontaneous emission noise (ASE), self-channel interference (SCI), cross-channel interference (XCI), and node crosstalk. In FONs, adaptive modulation, multiple FEC, and the tuning of power spectrum density (PSD) can be effectively employed to mitigate the impact of PLIs. Hence, in our study, we propose a universal bandwidth-related impairment evaluation model based on channel bandwidth, which allows a performance analysis for different PSD, FEC and modulations. Leveraging this PLI model and a piecewise linear fitting function, we succeed to formulate the revenue maximization problem as a mixed integer linear program. Then, to solve the problem on larger network instances, a fast two-phase heuristic algorithm is also proposed, which is shown to be near-optimal for revenue maximization. Through simulations, we demonstrate that using adaptive modulation enables to significantly increase revenues in the scenario of high signal-to-noise ratio (SNR), where the revenue can even be doubled for high traffic load, while using multiple FECs is more profitable for scenarios with low SNR

Throughput Maximization Leveraging Just-Enough SNR Margin and Channel Spacing Optimization

Flexible optical network is a promising technology to accommodate high-capacity demands in next-generation networks. To ensure uninterrupted communication, existing lightpath provisioning schemes are mainly done with the assumption of worst-case resource under-provisioning and fixed channel spacing, which preserves an excessive signal-to-noise ratio (SNR) margin. However, under a resource over-provisioning scenario, the excessive SNR margin restricts the transmission bit-rate or transmission reach, leading to physical layer resource waste and stranded transmission capacity. To tackle this challenging problem, we leverage an iterative feedback tuning algorithm to provide a just-enough SNR margin, so as to maximize the network throughput. Specifically, the proposed algorithm is implemented in three steps. First, starting from the high SNR margin setup, we establish an integer linear programming model as well as a heuristic algorithm to maximize the network throughput by solving the problem of routing, modulation format, forward error correction, baud-rate selection, and spectrum assignment. Second, we optimize the channel spacing of the lightpaths obtained from the previous step, thereby increasing the available physical layer resources. Finally, we iteratively reduce the SNR margin of each lightpath until the network throughput cannot be increased. Through numerical simulations, we confirm the throughput improvement in different networks and with different baud-rates. In particular, we find that our algorithm enables over 20\% relative gain when network resource is over-provisioned, compared to the traditional method preserving an excessive SNR margin.Comment: submitted to IEEE JLT, Jul. 17th, 2021. 14 pages, 8 figure

On 4n4n-dimensional neither pointed nor semisimple Hopf algebras and the associated weak Hopf algebras

For a class of neither pointed nor semisimple Hopf algebras $H_{4n}$ of dimension $4n$, it is shown that they are quasi-triangular, which universal $R$-matrices are described. The corresponding weak Hopf algebras $\mathfrak{w}H_{4n}$ and their representations are constructed. Finally, their duality and their Green rings are established by generators and relations explicitly. It turns out that the Green rings of the associated weak Hopf algebras are not commutative even if the Green rings of $H_{4n}$ are commutative.Comment: 18 page

Throughput Maximization in Multi-Band Optical Networks with Column Generation

Multi-band transmission is a promising technical direction for spectrum and capacity expansion of existing optical networks. Due to the increase in the number of usable wavelengths in multi-band optical networks, the complexity of resource allocation problems becomes a major concern. Moreover, the transmission performance, spectrum width, and cost constraint across optical bands may be heterogeneous. Assuming a worst-case transmission margin in U, L, and C-bands, this paper investigates the problem of throughput maximization in multi-band optical networks, including the optimization of route, wavelength, and band assignment. We propose a low-complexity decomposition approach based on Column Generation (CG) to address the scalability issue faced by traditional methodologies. We numerically compare the results obtained by our CG-based approach to an integer linear programming model, confirming the near-optimal network throughput. Our results also demonstrate the scalability of the CG-based approach when the number of wavelengths increases, with the computation time in the magnitude order of 10 s for cases varying from 75 to 1200 wavelength channels per link in a 14-node network.Comment: 6 pages, 4 figures, submitted to IEEE International Conference on Communications 2024 (ICC2024). (Note on arXiv: for beginners in the area of column generation, please refer to the example computation in the file . I have uploaded it to this arXiv project along with other source files.

Mapping the potential distribution of high artemisinin-yielding Artemisia annua L. (Qinghao) in China with a geographic information system

<p>Abstract</p> <p>Background</p> <p><it>Artemisia annua </it>L. is an important source for artemisinin, a potent drug for treating malaria. This study aims to map and predict the potential geographic distribution of <it>A. annua </it>L. in China.</p> <p>Methods</p> <p>The Geographic Information System for traditional Chinese medicine (TCM-GIS) was developed and used to map the potential geographic distribution of <it>A. annua </it>L.</p> <p>Results</p> <p>Climatic, edaphic and topographic characteristics of <it>A. annua </it>L. microhabitats in Youyang County were mapped to find distribution patterns. The maps identified that certain habitats in the Chongqing region and some potential regions, especially in Guizhou Province, possess similarity indices of ≥98%. In particular, high quality microhabitats <it>A. annua </it>L. were found in the Wuling mountains region.</p> <p>Conclusion</p> <p>The present study demonstrates a GIS approach to predict potential habitats for <it>A. annua </it>L. TCM-GIS is a powerful tool for assessing bioclimatic suitability for medicinal plants.</p