Oxygen Transport Kinetics in Solid Oxide Fuel Cell Cathode

Solid oxide fuel cells (SOFCs) are energy conversion devices that produce electricity by electrochemically combining a fuel and an oxidant across an ionic conducting oxide electrolyte. As it is regarded as the most efficient and versatile power generation system, SOFCs have attracted more substantial interest in recent years. Oxygen reduction at the cathode is considered as the main rate limiting factor to the performance of the whole system. In this work, experimental study of oxygen transport in single phase and infiltrated cathode materials using electrical conductivity relaxation (ECR) technique are combined with physical modeling to benefit SOFCs cathode improvement.;The conductivity relaxation technique involves measurement of time variation of the electrical conductivity of a sample after a stepwise change in the ambient oxygen partial pressure. Oxygen surface exchange (k) and bulk diffusion coefficients (D) can be obtained based on the correlation between a mean conductivity and the corresponding mean non-stoichiometry. Although the ECR technique has been widely used in various applications, reliability and accuracy of fitted results have been rarely discussed. Indeed, non-unique local fitting error minimums exist when fitting a single relaxation data set. Enhanced accuracy of D and k are obtained by fitting two sets of data and plotting the error intersection.;Oxygen surface exchange and bulk diffusion coefficients of the widely used cathode material La0.6Sr0.4Co0.2Fe 0.8O3-delta (LSCF) were obtained by applying the improved fitting method. The results indicated that the oxygen surface exchange coefficient depends on the final oxygen partial pressure following the P1/2O2 law. On the other hand, the oxygen bulk diffusion coefficient was considered to be influenced by the oxygen vacancy concentration and the ordering degree.;Electrical conductivity relaxation was further developed to investigate infiltrated cathode materials in this work. Ce0.8Sm0.2O 1.9 (SDC) and La0.6Sr0.4CoO3-delta (LSC) were chosen as the infiltrated materials. The oxygen exchange coefficient at the infiltrate/cathode backbone interface was deduced from the testing results. Both of the two infiltrated materials promoted the oxygen transport rate in LSCF. Under high oxygen partial pressure, the SDC spin coated LSCF sample showed a greater improvement than the LSC spin coated sample.;In addition, a model was built up to understand SOFCs infiltrated cathode. Infiltrate/cathode backbone interface and the corresponding 3PB region distinguished infiltrated SOFCs cathode from single phase cathode. Simulation results are more plausible by including the experimentally obtained oxygen interface exchange coefficient. Over-potential effects and infiltrated material optimization were included in the discussion

Deep Learning for Identifying Breast Cancer

Medical images are playing an increasingly important role in the prevention and diagnosis of diseases. Medical images often contain massive amounts of data. Professional interpretation usually requires a long time of professional study and experience accumulation by doctors. Therefore, the use of super storage and computing power in deep learning as a basis can effectively process a large amount of medical data. Breast cancer brings great harm to female patients, and early diagnosis is the most effective prevention and treatment method, so this project will create a new optimized breast cancer auxiliary diagnosis model based on ResNet. Analyze and process, realize medical aided diagnosis, and provide scientific diagnosis for breast cancer patients

Sulforaphane protects against ethanol-induced apoptosis and teratogenesis through epigenetic modulation of anti-apoptotic genes.

Background. Ethanol-induced excessive apoptosis in neural crest cells (NCCs), a multipotent progenitor cell population, is one of the major mechanisms underlying the pathogenesis of Fetal Alcohol Spectrum Disorders (FASD). However, the molecular mechanisms underlying FASD that results from maternal alcohol exposure during pregnancy are poorly understood. The overall goals of this study are to examine the mechanisms by which ethanol induces apoptosis and malformations in vitro and in vivo, and to develop a nutritional-based approach by using SFN and SFN-rich BSE to prevent FASD through epigenetic modulation. Results. This study demonstrates that ethanol exposure resulted in a significant increase in the DNMT activity and the expression of DNMT3a in human neural crest cells. SFN can significantly diminish ethanol-induced increases in DNMT activity and the expression of DNMT3a. We have also found that ethanol-induced up-regulation of DNMT3a and an increase in DNMT activity resulted in hypermethylation at the promoters of the selected anti-apoptotic genes and that SFN can diminish ethanol-induced hypermethylation at the promoters of the anti-apoptotic genes by preventing ethanol-induced up-regulation of DNMT3a and increase in DNMT activity. In addition, the knockdown of DNMT3a or treatment with SFN significantly diminished ethanol-induced decreases in the mRNA and protein expression of NAIP and XIAP and prevented ethanol-induced apoptosis in human neural crest cells. The knockdown of DNMT3a also enhanced the effects of SFN on the mRNA and protein expression of NAIP and XIAP and the protective effects of SFN on ethanol-induced apoptosis. This study also shows that ethanol exposure can increase HDAC activity and the expression of HDAC2 in human neural crest cells. SFN treatment significantly diminished ethanol-induced increase in HDAC activity and the up-regulation of HDAC2. We have also found that ethanol-induced increase in HDAC activity and up-regulation of HDAC2 resulted in the reduction of H3 acetylation at the promoters of AKT1, BIRC6 and XIAP and that SFN diminished ethanol-induced reduction of H3 acetylation at the promoters of anti-apoptotic genes by inhibiting HDAC activity and reducing ethanol-induced up-regulation of HDAC2. In addition, SFN treatment or knockdown of HDAC2 significantly diminished ethanol-induced decreases in the mRNA and protein expression of AKT1, BIRC6 and XIAP and prevented ethanol-induced apoptosis in human neural crest cells. The knockdown of HDAC2 also enhanced the effects of SFN on the mRNA and protein expression of AKT1, BIRC6 and XIAP and the protection against ethanol-induced apoptosis. In addition, our studies have shown that ethanol exposure can inhibit EMT through the down-regulation of Snail1 by decreasing H3K4me3 enrichment at the promoter regions of Snail1 and increase apoptosis in neural crest cells. SFN treatment can reverse the ethanol-induced reduction of the H3K4me3 enrichment at the promoter regions of Snail1, restore the expression of Snail1 and EMT in neural crest cells exposed to ethanol and diminished ethanol-induced apoptosis. These findings demonstrate that the disruption of EMT contributes to ethanol-induced apoptosis in neural crest cells and that SFN can prevent ethanol-induced apoptosis by restoring EMT through epigenetically regulating the expression of EMT-related genes, suggesting that elucidation of Snail1’s role in EMT and ethanol-induced apoptosis in neural crest cells may provide critical insight into the pathogenesis of FASD. Moreover, this study has demonstrated that SFN-rich BSE can attenuate ethanol-induced teratogenesis through epigenetically up-regulating the anti-apoptotic genes. Conclusions. The findings from work presented in this dissertation provide critical insight into the pathogenesis of FASD. In addition, the potency of SFN in preventing ethanol-induced apoptosis illustrates the potential of a practical and promising therapeutic strategy for FASD

Numerical algorithm based on Adomian decomposition for fractional differential equations

AbstractIn this paper, a novel algorithm based on Adomian decomposition for fractional differential equations is proposed. Comparing the present method with the fractional Adams method, we use this derived computational method to find a smaller “efficient dimension” such that the fractional Lorenz equation is chaotic. We also apply this new method to the time-fractional Burgers equation with initial and boundary value conditions. Numerical results and computer graphics show that the constructed numerical is efficient

Image Description using Radial Associated Laguerre Moments

This study proposes a new set of moment functions for describing gray-level and color images based on the associated Laguerre polynomials, which are orthogonal over the whole right-half plane. Moreover, the mathematical frameworks of radial associated Laguerre moments (RALMs) and associated rotation invariants are introduced. The proposed radial Laguerre invariants retain the basic form of disc-based moments, such as Zernike moments (ZMs), pseudo-Zernike moments (PZMs), Fourier-Mellin moments (OFMMs), and so on. Therefore, the rotation invariants of RALMs can be easily obtained. In addition, the study extends the proposed moments and invariants defined in a gray-level image to a color image using the algebra of quaternion to avoid losing some significant color information. Finally, the paper verifies the feature description capacities of the proposed moment function in terms of image reconstruction and invariant pattern recognition accuracy. Experimental results confirmed that the associated Laguerre moments (ALMs) perform better than orthogonal OFMMs in both noise-free and noisy conditions