Numerical Simulation of Nanoparticle Transportation and Deposition in Pulmonary Vasculature

Nanoparticle holds significant promise as the next generation of drug carrier that can realize targeted therapy with minimal toxicity. To improve the delivery efficiency of nanoparticles, it is important to study their transport and deposition in blood flow. Many factors, like particle size, vessel geometry and blood flow rate, have significant influence on the particle transport, thus on the deposition fraction and distribution.In this thesis, computational fluid dynamics (CFD) simulations of blood flow and drug particle deposition were conducted in four models representing the human lung vasculature: artificial artery geometry, artificial vein geometry, original geometry and over-smoothed original geometry. Flow conditions used included both steady-state inlet flow and pulsatile inlet flow. Parabolic flow pattern and lumped mathematic model were used for inlet and outlet boundary conditions respectively. Blood flow was treated as laminar and Newtonian. Particle trajectories were calculated in each of these models by solving the integrated force balance on the particle, and adding a stochastic Brownian term at each step. A receptor-ligand model was integrated to simulate the particle binding probability. The results indicate the following: (i) Pulsatile flow can accelerate the particle binding activity and improve the particle deposition fraction on bifurcation areas; (ii) Unlike drug delivery in lung respiratory system, particle diffusion is very weak in blood flow, no clear relationship between the particle size and deposition area was found in our four-generation lung vascular model; and (iii) Surface imperfections have the dominant effect on particle deposition fraction over a wide range of particle sizes. Ideal artificial geometry is not sufficient to predict drug deposition, and an accurate image based geometry is required

Multi-area perimeter sensing system based on optical fiber wavelength division multiplexing technology

A new multi-area perimeter sensing system based on optical fiber wavelength division multiplexing (WDM) technology is proposed and demonstrated. The traditional single channel system with broadband mirror is improved by introducing fiber Bragg grating (FBG) as the mirror, and the number of the monitoring areas is expanded by using the FBG with different reflecting wavelengths matching the demodulation channels of a WDM apparatus. The WDM and FBG technology employed in the system makes the measurement in each channel independent, simultaneous, no mutual-interfering between channels sharing the same interference device. The experimental results show that the proposed perimeter sensing system is able to detect and recognize the perturbation localization simultaneously in each area or channel. The response time of the system is less than 1 ms, and crosstalk between channels is less than -20 dB

Substrate Structured Bournonite CuPbSbS₃ Thin Film Solar Cells

CuPbSbS3 has excellent photoelectric properties, such as high element abundance and optical absorption coefficient, and a suitable band gap, which is a material with the potential for absorbing layers of high-quality thin film solar cells. In addition, CuPbSbS3 is a material with a three-dimensional structure, which can guide the carrier to transport in all directions, so its performance can be regulated in multiple dimensions. At present, the substrate structure is often used in efficient solar cells since this structure does not affect other functional layers when the absorption layer is subjected to harsh annealing conditions. However, there have been no reports of the substrate structure of CuPbSbS3 solar cells so far. Therefore, in this work, CuPbSbS3 films deposited on a stable substrate of molybdenum (Mo) were prepared with butyldithiocarbamic acid (BDCA) solution, and the preparation process of reaction mechanism was described in detail. It was found that the band gap of the CuPbSbS3 thin film was 2.0 eV and the absorption coefficient was up to 105 cm−1, which is expected to be applied to the top absorption layer material in laminated cells. Thus, we first built a Glass/Mo/CuPbSbS3/CdS/ZnO/ITO substrate structured solar cell. From this, a photoelectric conversion efficiency of 0.094% was achieved. This work provides a tentative exploration for the future development of substrate structured CuPbSbS3 solar cells

TLFND: A Multimodal Fusion Model Based on Three-Level Feature Matching Distance for Fake News Detection

In the rapidly evolving information era, the dissemination of information has become swifter and more extensive. Fake news, in particular, spreads more rapidly and is produced at a lower cost compared to genuine news. While researchers have developed various methods for the automated detection of fake news, challenges such as the presence of multimodal information in news articles or insufficient multimodal data have hindered their detection efficacy. To address these challenges, we introduce a novel multimodal fusion model (TLFND) based on a three-level feature matching distance approach for fake news detection. TLFND comprises four core components: a two-level text feature extraction module, an image extraction and fusion module, a three-level feature matching score module, and a multimodal integrated recognition module. This model seamlessly combines two levels of text information (headline and body) and image data (multi-image fusion) within news articles. Notably, we introduce the Chebyshev distance metric for the first time to calculate matching scores among these three modalities. Additionally, we design an adaptive evolutionary algorithm for computing the loss functions of the four model components. Our comprehensive experiments on three real-world publicly available datasets validate the effectiveness of our proposed model, with remarkable improvements demonstrated across all four evaluation metrics for the PolitiFact, GossipCop, and Twitter datasets, resulting in an F1 score increase of 6.6%, 2.9%, and 2.3%, respectively