Enhancing infrared emission of mercury telluride (HgTe) quantum dots by plasmonic structures

The coupling of HgTe quantum dots to a gold nanobump plasmonic array can enhance the spontaneous infrared emission by a factor of five and reduce the influence of nonradiative decay channels

Mass spectrometric investigation of biomedically important glycosylation

Glycobiology is the comprehensive study of the structure, biosynthesis, function and evolution of saccharides which are also named sugars or glycans. Glycosylation is a type of modification in which sugars are added to another molecule, such as a protein molecule or a ceramide. Abnormal glycosylation is frequently associated with diseases such as cancer and immune responses. Defining glycan structures is therefore important for understanding glycan function in health and disease. In addition, identification of glycan populations can provide essential information for further research on glycoproteins and glycolipids. In this thesis, glycomic experimental approaches were employed to characterize the structures and populations of glycans of glycoconjugates from HeLa cells, normal human dermal fibroblast (NHDF) cells, myoblasts, myotubes and trophoblasts. These approaches include sample preparation methodologies which were followed by the application of highly sensitive mass spectrometry, particularly MALDI-TOF MS, MALDI-TOF/TOF MS/MS and GC-MS. Ribosome inactivating proteins (RIPs) and lectins from elderberry are more toxic to HeLa cells than to NHDF cells. The difference in the cytotoxicity was hypothesized to be caused by the difference in the glycome patterns of HeLa and NHDF cells. To test the hypothesis, glycome patterns on both glycoproteins and glycolipids of HeLa and NHDF cells were investigated. Glycomic results have revealed that glycome patterns in HeLa cells and NHDF are different, and this gives a possible explanation for the difference observed in the cytotoxicity assay. Glutamine-fructose-6-phosphate transaminase 1 (GFPT1) is the first enzyme of the hexosamine biosynthetic pathway which yields uridine diphosphate N-acetylglucosamine (UDP-GlcNAc), an essential substrate for protein glycosylation. N-glycan branching is especially sensitive to alterations in the concentration of this sugar nucleotide. Mutations in the gene GFPT1 can result in “limb-girdle CMS with tubular aggregates” which is a subtype of congenital myasthenic syndromes (CMS). To investigate whether protein glycosylation at the neuromuscular junction might be involved in this impairment, the N-glycomes of myoblasts and myotubes derived from healthy controls and patients were investigated. My result showed that global glycosylation is not significantly impaired in the muscle cells from the CMS patients caused by GFPT1 mutations. The human fetoembryonic defense system hypothesis (hu-FEDS) is a hypothetical model depicting a way via which the human immune system is able to recognize foreign substances as "own species" as has been observed with maternal immune tolerance in pregnancy. The fundamental idea of this hypothesis is that glycoproteins existing in the reproductive system and exposed on gametes can either inhibit immune responses or prevent rejection of the foetus. This model has not been tested in human trophoblasts. My glycomic analyses of three trophoblast populations (CTB, STB and evCTB) revealed that functional glycan structures that are present on human gametes are also expressed on trophoblasts, and this provides further evidence for the hu-FEDS hypothesis.Open Acces

An Obstacle Avoidance Method of Soccer Robot Based on Evolutionary Artificial Potential Field

AbstractIn order to solve the problems that local minimum, path planning in obstacles, and optimizing global obstacle avoidance path, the paper proposed a new obstacle avoidance method. In this method, used the grid method to describe the information of obstacles environment, utilized the evolutionary artificial potential field method to optimize obstacle avoidance path. The simulation results show that the proposed method is feasible and effective

Enhancing infrared emission of mercury telluride (HgTe) quantum dots by plasmonic structures

The coupling of HgTe quantum dots to a gold nanobump plasmonic array can enhance the spontaneous infrared emission by a factor of five and reduce the influence of nonradiative decay channels

Modeling the hydro-mechanical responses of strip and circular punch loadings on water-saturated collapsible geomaterials

A stabilized enhanced strain finite element procedure for poromechanics is fully integrated with an elasto-plastic cap model to simulate the hydro-mechanical interactions of fluid-infiltrating porous rocks with associative and non-associative plastic flow. We present a quantitative analysis on how macroscopic plastic volumetric response caused by pore collapse and grain rearrangement affects the seepage of pore fluid, and vice versa. Results of finite element simulations imply that the dissipation of excess pore pressure may significantly affect the stress path and thus alter the volumetric plastic responses

Wav2code: Restore Clean Speech Representations via Codebook Lookup for Noise-Robust ASR

Automatic speech recognition (ASR) has gained a remarkable success thanks to recent advances of deep learning, but it usually degrades significantly under real-world noisy conditions. Recent works introduce speech enhancement (SE) as front-end to improve speech quality, which is proved effective but may not be optimal for downstream ASR due to speech distortion problem. Based on that, latest works combine SE and currently popular self-supervised learning (SSL) to alleviate distortion and improve noise robustness. Despite the effectiveness, the speech distortion caused by conventional SE still cannot be completely eliminated. In this paper, we propose a self-supervised framework named Wav2code to implement a generalized SE without distortions for noise-robust ASR. First, in pre-training stage the clean speech representations from SSL model are sent to lookup a discrete codebook via nearest-neighbor feature matching, the resulted code sequence are then exploited to reconstruct the original clean representations, in order to store them in codebook as prior. Second, during finetuning we propose a Transformer-based code predictor to accurately predict clean codes by modeling the global dependency of input noisy representations, which enables discovery and restoration of high-quality clean representations without distortions. Furthermore, we propose an interactive feature fusion network to combine original noisy and the restored clean representations to consider both fidelity and quality, resulting in even more informative features for downstream ASR. Finally, experiments on both synthetic and real noisy datasets demonstrate that Wav2code can solve the speech distortion and improve ASR performance under various noisy conditions, resulting in stronger robustness.Comment: 12 pages, 7 figures, Submitted to IEEE/ACM TASL

Noise-aware Speech Enhancement using Diffusion Probabilistic Model

5 pages, 2 figuresPreprin