Person Transfer GAN to Bridge Domain Gap for Person Re-Identification

Although the performance of person Re-Identification (ReID) has been significantly boosted, many challenging issues in real scenarios have not been fully investigated, e.g., the complex scenes and lighting variations, viewpoint and pose changes, and the large number of identities in a camera network. To facilitate the research towards conquering those issues, this paper contributes a new dataset called MSMT17 with many important features, e.g., 1) the raw videos are taken by an 15-camera network deployed in both indoor and outdoor scenes, 2) the videos cover a long period of time and present complex lighting variations, and 3) it contains currently the largest number of annotated identities, i.e., 4,101 identities and 126,441 bounding boxes. We also observe that, domain gap commonly exists between datasets, which essentially causes severe performance drop when training and testing on different datasets. This results in that available training data cannot be effectively leveraged for new testing domains. To relieve the expensive costs of annotating new training samples, we propose a Person Transfer Generative Adversarial Network (PTGAN) to bridge the domain gap. Comprehensive experiments show that the domain gap could be substantially narrowed-down by the PTGAN.Comment: 10 pages, 9 figures; accepted in CVPR 201

Protein engineering using azurin as the scaffold: capturing and studying novel metal-sulfenate and metal-NO species

Metalloproteins account for nearly half of all proteins in nature. Metal ions play important roles in catalyzing numerous important biological processes that necessary to sustain life on the planet, such as photosynthesis, respiration and nitrogen fixation. Much effort has been made to understand the relationship between structures and functions of metalloproteins. Although significant progresses have been made to obtain the knowledge of how metalloproteins work, the ultimate test is to use this knowledge to design new metallproteins that reproduce the structures and functions of native proteins. Protein redesign strategy is one of the most effective approaches in the design and engineering of artificial metalloenzymes. The advantage of a protein redesign strategy is that it can bypass the problem of developing a stable protein fold because many native proteins have remarkable adaptability for changes. The use of small, stable, easy-to-make, and well-characterized blue copper protein azurin as scaffold to design novel metal binding sites has been proven to be a promising way for protein redesign. Not only can its reduction potential be rationally tuned beyond the nature range via secondary coordination sphere engineering, but also the CuA and redox-active nonheme iron sites have been successfully engineered in azurin. Metal-sulfenate centers are known to play important roles in biology and yet only limited examples are known due to their instability and high reactivity. In Chapter 2, the first copper-sulfenate was characterized in a protein environment, formed at the active site of a cavity mutant of an electron transfer protein, type 1, blue copper azurin. Reaction of hydrogen peroxide with Cu(I)-Met121Gly azurin resulted in a new species with strong visible absorptions at 350 and 452 nm and a relatively low electron paramagnetic resonance gz value of 2.169 in comparison to other normal type 2 copper centers. The presence of a side-on copper-sulfenate species is supported by resonance Raman spectroscopy, electrospray mass spectrometry using isotopically enriched hydrogen peroxide, and density functional theory calculations correlated to the experimental data. In contrast, the reaction with Cu(II)-Met121Gly or Zn(II)-Met121Gly azurin under the same conditions did not result in Cys oxidation or copper-sulfenate formation. Structural and computational studies strongly suggest that the secondary coordination sphere non-covalent interactions are critical in stabilizing this highly reactive species, which can further react with oxygen to form a sulfinate and then a sulfonate species, as demonstrated by mass spectrometry. Engineering the electron transfer protein azurin into an active copper enzyme that forms a copper-sulfenate center and demonstrating the importance of non-covalent secondary sphere interactions in stabilizing it constitute important contributions toward the understanding of metal sulfenate species in biological systems. S-nitrosothiols are known reagents for NO storage and transportation in vivo and regulating factors in many physiological processes. While the S-nitrosylation catalyzed by heme proteins is well known, no direct evidence of S-nitrosylation of Cu(II)-bound cysteine by NO has been reported. In Chapter 3, the blue copper center in WTAz was converted into a red copper center that closely mimics that in nitrosocyanin by rational design of the primary coordination sphere (M121H/H46E) first, and then by tuning its reduction potential via deleting a hydrogen bond in the secondary coordination sphere (F114P). The engineered red copper protein exhibits a significantly longer Cu-S(Cys) bond distance (~2.28 Å), lower reduction potential (~107 mV at pH 8) and larger hyperfine splitting in the parallel region (~160×10-4 cm-1) as compared to blue copper proteins, and the electronic properties of the engineered protein are comparable to those of the red copper center in nitrosocyanin. Stoichiometric titration of NO to Cu(II)-M121H/H46E/F114PAz yields nearly quantitative S-nitrosylation product with concomitant reduction of the metal center with a second order rate constant of ~ 105 M-1s-1. The resulting S(Cys)-SNO containing protein shows a strong absorbance at 334 nm and a weak absorbance around 540 nm, similar to other reported RSNO species. Reduction of the Cu(II) site to Cu(I) during S-nitrosylation process is confirmed by a loss of over 90% of Cu(II) signal in EPR spectrum and a shift of the Cu K-edge to lower energy in XANES. Further EXAFS fitting reveals that the Cu-S distance increases from 2.18 Å in the reduced engineered red copper protein to 3.98 Å in the S-nitrosylation species, indicating Cu(I) interacts with N rather than S atom. DFT calculations have identified the most plausible mechanism for S(Cys)-NO formation as the direct radical reaction of NO with Cu(II)-coordinated S(Cys) enabled by the high covalency of the Cu(II)-S(Cys) bond. Our results provide the first direct evidence of S-nitrosylation of copper-bound cysteine in a protein, and show that such a reaction can modulate solution NO concentration under physiologically relevant conditions to prevent NO inhibition of cytochrome oxidase activity. Cupredoxins are known to contain a type 1 copper (T1Cu) center that is coordinately saturated and performs exclusively electron transfer function. Nitrosocyanin has been shown to contain an open-binding site, with water as a ligand, but spectroscopic and X-ray crystallographic studies indicate that it contains a type 2 copper (T2Cu) center. In Chapter 4, a novel cupredoxin isolated from Nitrosopumilus maritimus, called Nmar_1307, was recombinantly expressed in E. coli and characterized with different spectroscopic methods. The protein displays a strong purple color due to strong absorptions around 413 nm (1450 M-1cm-1) and 558 nm (1770 M-1cm-1) in the UV-vis electronic spectrum and a small hyperfine coupling constant (A|| < 100x10-4 cm-1) in the EPR spectrum, typical of T1Cu center. X-ray crystal structure at 1.6 Å resolution con-firms that it contains T1Cu center with a Cu atom coordinated by two His and one Cys in a trigonal place and a short Cu(II)-SCys bond (2.25 Å). In contrast to the coordinately saturated T1Cu center observed in other cupredoxins, the Nmar_1307 contains a unique T1Cu center with an open-binding site containing water. Both UV-vis absorption and EPR spectroscopy studies suggest that the Nmar_1307 can oxidase NO to nitrite, whose activity is attributable to the unusually high reduction potential (484±9 mV vs. SHE) of the copper site. These results suggest T1Cu cupredoxins can have a wide range of structural features, including an open-binding site containing water, making this class of proteins even more versatile. Mononuclear nitrosyl iron complexes – mononitrosyl iron {FeNO}7, dinitrosyl iron {Fe(NO)2}8 and {Fe(NO)2}9 – are key intermediates in the nitrosylation of nonheme iron proteins in biology. It has been difficult to capture all three species in identical host complexes for both native enzymes and synthetic analogs, which is necessary to elucidate changes to the structure of the iron center during nitrosylation and the factors that control their chemical reactivities. More importantly, to the best of our knowledge, the {Fe(NO)2}8 species which is proposed as an intermediate in cis-FeB mechanism of nitric oxide reductases (NORs) has never been unambiguously characterized and thus the one-electron reduction process from {Fe(NO)2}8 to {Fe(NO)2}9 is not fully understood. In Chapter 5, a stepwise nitrosylation process of an engineered non heme iron site in blue copper azurin was captured and characterized. All {FeNO}7, {Fe(NO)2}8 and {Fe(NO)2}9 species are successfully isolated by controlling the amount of nitric oxide added and reaction time. The {Fe(NO)2}8 species can be reduced to {Fe(NO)2}9 with either dithionite or excess NO. Structural information of the {FeNO}7, {Fe(NO)2}8 and {Fe(NO)2}9 species are gained by combining the results of electron nuclear double resonance (ENDOR), hyperfine sub-level correlation (HYSCORE) and nuclear resonance vibrational spectroscopy (NRVS) techniques. The entire pathway of engineered non heme iron protein nitrosylation process from reduced form to {FeNO}7, then to {Fe(NO)2}8 and {Fe(NO)2}9 is discovered. These results not only enhance our understanding of the pathological and physiological roles of nitric oxide in non heme iron proteins’ regulation but also shed light on the mechanism of NORs. Compared to other virus presented in drinking water, adenoviruses show high resistance to monochloramine and low pressure ultraviolet light but significantly disinfected by free chlorine. A systematic understanding of adenovirus inactivation by free chlorine would potentially direct the development and optimization of water treatments and strengthen our understanding of virus inactivation mechanism. Previous study suggests that genome damage and loss of the interaction between fiber and CAR receptors are not the cause of disinfection but the disruption of penton or hexon protein structure may play an important role in adenovirus inactivation by free chlorine. In Chapter 6, adenovirus penton and hexon with 6×His-tag at C-terminal was first time expressed in E. coli. This novel method enable us to produce all three major capsid proteins of human adenovirus serotype 2 in a fast and high quality way. Around 90% sequence coverages are achieved after trypsin digestion – MS/MS studies. This approach allowed us to detect modifications at amino acid sidechains and provide insight into the mechanism of Ad2 inactivation by free chlorine. In summary, this thesis details in capture and characterization of novel copper-sulfenate, copper-SNO and dinitrosyl iron species in engineered azurin with different spectroscopic methods and DFT calculation

Incorporating Class-based Language Model for Named Entity Recognition in Factorized Neural Transducer

In spite of the excellent strides made by end-to-end (E2E) models in speech recognition in recent years, named entity recognition is still challenging but critical for semantic understanding. In order to enhance the ability to recognize named entities in E2E models, previous studies mainly focus on various rule-based or attention-based contextual biasing algorithms. However, their performance might be sensitive to the biasing weight or degraded by excessive attention to the named entity list, along with a risk of false triggering. Inspired by the success of the class-based language model (LM) in named entity recognition in conventional hybrid systems and the effective decoupling of acoustic and linguistic information in the factorized neural Transducer (FNT), we propose a novel E2E model to incorporate class-based LMs into FNT, which is referred as C-FNT. In C-FNT, the language model score of named entities can be associated with the name class instead of its surface form. The experimental results show that our proposed C-FNT presents significant error reduction in named entities without hurting performance in general word recognition