SYNTHESES AND CHARACTERIZATION OF LINEARLY EXTENDED TROPYLIUM SALTS AS N-TYPE ORGANIC SEMICONDUCTORS

Organic semiconductors have been of interest to scientists since the 1970s. However, while much attention was focused on p-type organic semiconductors, n-type organic semiconductors were seldom reported. In this thesis, a series of linearly extended tropylium salts (LETS) were synthesized as n-type organic semiconductors and characterized by 1H NMR, 13C NMR spectroscopy, MALDI-TOF-Mass spectrometry and UV-Vis spectroscopy. The proposed synthetic strategy has proven highly suitable to synthesize LETS compounds. UV-Vis spectra of LETS in solution have been studied as well as their stability. Linear extension of the backbones has been found to be an effective way to improve the optical properties. With each addition of one benzene ring to the backbone, the UV-Vis absorption can be red-shifted by about 170 nm and the HOMO-LUMO gap can be narrowed by approximate 0.7±0.2 eV. While linear extension of the LETS compounds improves their optical properties, it also reduces their stability, limiting their potential applications. LETS compounds with low HOMO-LUMO gaps are short-life species in solution. A detailed decomposition mechanism has not been studied, but nucleophilic attack by residual water in the solution appears to be involved. Fortunately, all LETS compounds were found to be stable in the solid state. In sealed vials stored in desiccators, they can be stored for years with very little decomposition. Their potential use in solid-state, sealed device is worth pursuing

Development of Computational Techniques for Regulatory DNA Motif Identification Based on Big Biological Data

Accurate regulatory DNA motif (or motif) identification plays a fundamental role in the elucidation of transcriptional regulatory mechanisms in a cell and can strongly support the regulatory network construction for both prokaryotic and eukaryotic organisms. Next-generation sequencing techniques generate a huge amount of biological data for motif identification. Specifically, Chromatin Immunoprecipitation followed by high throughput DNA sequencing (ChIP-seq) enables researchers to identify motifs on a genome scale. Recently, technological improvements have allowed for DNA structural information to be obtained in a high-throughput manner, which can provide four DNA shape features. The DNA shape has been found as a complementary factor to genomic sequences in terms of transcription factor (TF)-DNA binding specificity prediction based on traditional machine learning models. Recent studies have demonstrated that deep learning (DL), especially the convolutional neural network (CNN), enables identification of motifs from DNA sequence directly. Although numerous algorithms and tools have been proposed and developed in this field, (1) the lack of intuitive and integrative web servers impedes the progress of making effective use of emerging algorithms and tools; (2) DNA shape has not been integrated with DL; and (3) existing DL models still suffer high false positive and false negative issues in motif identification. This thesis focuses on developing an integrated web server for motif identification based on DNA sequences either from users or built-in databases. This web server allows further motif-related analysis and Cytoscape-like network interpretation and visualization. We then proposed a DL framework for both sequence and shape motif identification from ChIP-seq data using a binomial distribution strategy. This framework can accept as input the different combinations of DNA sequence and DNA shape. Finally, we developed a gated convolutional neural network (GCNN) for capturing motif dependencies among long DNA sequences. Results show that our developed web server enables providing comprehensive motif analysis functionalities compared with existing web servers. The DL framework can identify motifs using an optimized threshold and disclose the strong predictive power of DNA shape in TF-DNA binding specificity. The identified sequence and shape motifs can contribute to TF-DNA binding mechanism interpretation. Additionally, GCNN can improve TF-DNA binding specificity prediction than CNN on most of the datasets

ANN-based robust DC fault protection algorithm for MMC high-voltage direct current grids

Fast and reliable protection is a significant technical challenge in modular multilevel converter (MMC) based DC grids. The existing fault detection methods suffer from the difficulty in setting protective thresholds, incomplete function, insensitivity to high resistance faults and vulnerable to noise. This paper proposes an artificial neural network (ANN) based method to enable DC bus protection and DC line protection for DC grids. The transient characteristics of DC voltages are analysed during DC faults. Based on the analysis, the discrete wavelet transform (DWT) is used as an extractor of distinctive features at the input of the ANN. Both frequency-domain and time-domain components are selected as input vectors. A large number of offline data considering the impact of noise is employed to train the ANN. The outputs of the ANN are used to trigger the DC line and DC bus protections and select the faulted poles. The proposed method is tested in a four-terminal MMC based DC grid under PSCAD/EMTDC. The simulation results verify the effectiveness of the proposed method in fault identification and the selection of the faulty pole. The intelligent algorithm based protection scheme has good performance concerning selectivity, reliability, robustness to noise and fast action

Resveratrol protects the retina from I/R injury by inhibiting RGCS apoptosis, glial activation and expression of inflammatory factors

Purpose: To study the protective effect of resveratrol against retinal injury induced by ischemiareperfusion (I/R), and the underlying mechanism  action.Methods: Retinal I/R injury was established in 72 healthy male SD rats. The rats were assigned to 3 groups: control, model and resveratrol groups, with 24 rats in each group. Pathological changes in retina were determined using H&E staining. Retinal ganglion cells (RGCs) were counted usingfluorescence gold retrograde staining. Western blotting was used to assay the expressions of caspase- 3, Bax, Bcl-2, GFAP, COX-2 and iNOS. The expressions of COX-2 and iNOS were measured by immunofluorescence.Results: The retina in the control group was dense and ordered, and its morphology was normal. In contrast, the retina in the model group was thinner, with loose cells and disordered structure. In the resveratrol group, the retina was thicker, the structure was orderly, and the cells were dense. Relative to control, the population of RGCs in model rat retina was significantly reduced, and the expressions of Bcl-2, Bax, caspase-3, GFAP, COX-2 and iNOS were significantly upregulated (p < 0.05). In the resveratrol group, the number of RGCs in the retina was markedly elevated, relative to model rats, and the expressions of Bcl-2, Bax, caspase-3, GFAP, COX-2 and iNOS were significantly decreased (p < 0.05).Conclusion: Resveratrol protects the retina from I/R injury in rats by inhibiting RGCs apoptosis, glial activation and expressions of inflammatory factors. Thus, this compound may be potentially suitable for the management of retina damage. Keywords: Resveratrol, RGCs apoptosis, Glial activation, Inflammatory factors, I/R injur

An improved DC fault protection scheme independent of boundary components for MMC based HVDC grids

For Modular Multilevel Converter (MMC) based DC grids, current-limiting reactors (CLRs) are mainly employed to suppress the fault current and provide boundary effects to detect internal faults. Thus, most existing protection schemes are highly dependent on the larger CLRs to guarantee high selectivity. However, in existing MMC based HVDC projects, the size of CLRs is restrained by the cost, weight and system stability under normal state. Thus, boundary protections may fail to detect high-resistance faults and pole-to-ground faults. To overcome these shortcomings, this paper proposes a fast and selective DC fault detection algorithm independent of boundary components. The propagation characteristics of line-mode backward traveling-waves (TW) are analyzed to identify external and internal faults. The polarities of zero-mode backward TWs are employed to select faulted poles. To detect remote faults, a pilot protection scheme based on the directional overcurrent is adopted as the complementary criterion. The detection speed of the proposed protection is fast, with a delay less than 1.1ms. Besides, it is robust to fault resistance and immune to noise. Various simulation results in PSCAD/EMTDC demonstrate that the proposed method is not affected by AC faults, fault distances and fault type

Scheme of Overloaded Truck Control on a Rural Highway

A new working mode of overloaded traffic control for rural highways is presented, and a location-routing model is built to optimize the check base distribution and the control vehicles’ routing schemes. Then, for the location-routing model with a large set of location alternatives and an unknown settable number of check bases, a multiple ant colony optimization algorithm is designed to solve the model. Furthermore, actual data from Guiyang rural highways are used to perform a numerical analysis. The results indicate that the model can be used to obtain the optimal base location-vehicle routing scheme to verify the feasibility of the model and the algorithm. The model and algorithm can help managers to make decisions on locating the check bases and routing the control vehicles