Management and Control of Scalable and Resilient Next-Generation Optical Networks

Two research topics in next-generation optical networks with wavelength-division multiplexing (WDM) technologies were investigated: (1) scalability of network management and control, and (2) resilience/reliability of networks upon faults and attacks. In scalable network management, the scalability of management information for inter-domain light-path assessment was studied. The light-path assessment was formulated as a decision problem based on decision theory and probabilistic graphical models. It was found that partial information available can provide the desired performance, i.e., a small percentage of erroneous decisions can be traded off to achieve a large saving in the amount of management information. In network resilience under malicious attacks, the resilience of all-optical networks under in-band crosstalk attacks was investigated with probabilistic graphical models. Graphical models provide an explicit view of the spatial dependencies in attack propagation, as well as computationally efficient approaches, e.g., sum-product algorithm, for studying network resilience. With the proposed cross-layer model of attack propagation, key factors that affect the resilience of the network from the physical layer and the network layer were identified. In addition, analytical results on network resilience were obtained for typical topologies including ring, star, and mesh-torus networks. In network performance upon failures, traffic-based network reliability was systematically studied. First a uniform deterministic traffic at the network layer was adopted to analyze the impacts of network topology, failure dependency, and failure protection on network reliability. Then a random network layer traffic model with Poisson arrivals was applied to further investigate the effect of network layer traffic distributions on network reliability. Finally, asymptotic results of network reliability metrics with respect to arrival rate were obtained for typical network topologies under heavy load regime. The main contributions of the thesis include: (1) fundamental understandings of scalable management and resilience of next-generation optical networks with WDM technologies; and (2) the innovative application of probabilistic graphical models, an emerging approach in machine learning, to the research of communication networks.Ph.D.Committee Chair: Ji, Chuanyi; Committee Member: Chang, Gee-Kung; Committee Member: McLaughlin, Steven; Committee Member: Ralph, Stephen; Committee Member: Zegura, Elle

Supervisor Narcissism and Time Theft: Investigating the Mediating Roles of Emotional Exhaustion and the Moderating Roles of Attachment Style

Although some studies have begun to explore the factors influencing employees’ time theft, it has not been uncommon to link employee time theft to leader personality traits. Based on the conservation of resources theory, this paper examines the influence of supervisor narcissism on employee time theft. It is found that supervisor narcissism positively affects employee time theft via the emotional exhaustion of employees. Further, employee’s attachment styles moderate the mediation effect of emotional exhaustion between supervisor narcissism and employee time theft. This study adds important insights into employee time theft, leader negative traits and the theory and practice of organizational management

Advances in CRISPR/Cas gene therapy for inborn errors of immunity

Inborn errors of immunity (IEIs) are a group of inherited disorders caused by mutations in the protein-coding genes involved in innate and/or adaptive immunity. Hematopoietic stem cell transplantation (HSCT) is a mainstay definitive therapy for many severe IEIs. However, the lack of HLA-matched donors increases the risk of developing severe immunological complications. Gene therapy provides long-term clinical benefits and could be an attractive therapeutic strategy for IEIs. In this review, we describe the development and evolution of clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated proteins (Cas) gene-editing systems, including double-strand break (DSB)-based gene editing and DSB-free base editing or prime editing systems. Here, we discuss the advances in and issues associated with CRISPR/Cas gene editing tools and their potential as therapeutic alternatives for IEIs. We also highlight the progress of preclinical studies for the treatment of human genetic diseases, including IEIs, using CRISR/Cas and ongoing clinical trials based on this versatile technology

CPIA Dataset: A Comprehensive Pathological Image Analysis Dataset for Self-supervised Learning Pre-training

Pathological image analysis is a crucial field in computer-aided diagnosis, where deep learning is widely applied. Transfer learning using pre-trained models initialized on natural images has effectively improved the downstream pathological performance. However, the lack of sophisticated domain-specific pathological initialization hinders their potential. Self-supervised learning (SSL) enables pre-training without sample-level labels, which has great potential to overcome the challenge of expensive annotations. Thus, studies focusing on pathological SSL pre-training call for a comprehensive and standardized dataset, similar to the ImageNet in computer vision. This paper presents the comprehensive pathological image analysis (CPIA) dataset, a large-scale SSL pre-training dataset combining 103 open-source datasets with extensive standardization. The CPIA dataset contains 21,427,877 standardized images, covering over 48 organs/tissues and about 100 kinds of diseases, which includes two main data types: whole slide images (WSIs) and characteristic regions of interest (ROIs). A four-scale WSI standardization process is proposed based on the uniform resolution in microns per pixel (MPP), while the ROIs are divided into three scales artificially. This multi-scale dataset is built with the diagnosis habits under the supervision of experienced senior pathologists. The CPIA dataset facilitates a comprehensive pathological understanding and enables pattern discovery explorations. Additionally, to launch the CPIA dataset, several state-of-the-art (SOTA) baselines of SSL pre-training and downstream evaluation are specially conducted. The CPIA dataset along with baselines is available at https://github.com/zhanglab2021/CPIA_Dataset

Comparative study of Al2O3, SiO2 and TiO2-coated LiNi0.6Co0.2Mn0.2O2 electrode prepared by hydrolysis coating technology

In this work, Al, Si and Ti oxides are used to modify the surface of LiNi0.6Co0.2Mn0.2O2 (NCM622) electrode through the hydrolysis coating technology. SEM and TEM results revealed that three prepared oxide layers have different uniformity and morphology. Also, charge-discharge results showed different initial discharge capacity and cycle ability of three different oxide coatings. It is shown that when the temperature is increased from 25 to 50 °C, the capacity retention of Al2O3-coated NCM622 is reduced by only 4 %, what demonstrated the best ability of this oxide to restrain cycle deterioration. Additionally, when the charge cutoff voltage is increased to 4.6 V, Al2O3-coated NCM622 showed 74 % of capacity retention. As the number of charge-discharge cycles increases, the dissolution of some transition metal ions may be restrained by Al2O3 layer. Generally, the enhanced electrochemical performance of Al2O3-coated NCM622 could be ascribed to the suppression of mutual reaction between electrode and electrolyte and improvement of structural stability of the material by Al2O3 coating

Immobilization of lipase on chitosan beads for removal of pitch particles from whitewater during papermaking

Pitch deposits originating from alkaline peroxide bleaching of mechanical pulps can seriously decrease the runnability of the paper machine when efforts have been made to increase the reuse of process water. In order to degrade pitch particles present in whitewater, lipase was immobilized on chitosan beads using a binary method. The operational stability of the immobilized lipase and its efficacy for treating whitewater were also preliminary studied. The results showed that the highest activity of immobilized lipase was achieved by using 0.5% 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC) for activation and 0.0025% glutaraldehyde for cross-linking chitosan. The immobilized lipase also exhibited very good operational stability, and the pitch particles present in whitewater could be reduced by 66.8% after treatment with the immobilized lipase

Detection of genome-wide structural variations in the Shanghai Holstein cattle population using next-generation sequencing

Objective The Shanghai Holstein cattle breed is susceptible to severe mastitis and other diseases due to the hot weather and long-term humidity in Shanghai, which is the main distribution centre for providing Holstein semen to various farms throughout China. Our objective was to determine the genetic mechanisms influencing economically important traits, especially diseases that have huge impact on the yield and quality of milk as well as reproduction. Methods In our study, we detected the structural variations of 1,092 Shanghai Holstein cows by using next-generation sequencing. We used the DELLY software to identify deletions and insertions, cn.MOPS to identify copy-number variants (CNVs). Furthermore, we annotated these structural variations using different bioinformatics tools, such as gene ontology, cattle quantitative trait locus (QTL) database and ingenuity pathway analysis (IPA). Results The average number of high-quality reads was 3,046,279. After filtering, a total of 16,831 deletions, 12,735 insertions and 490 CNVs were identified. The annotation results showed that these mapped genes were significantly enriched for specific biological functions, such as disease and reproduction. In addition, the enrichment results based on the cattle QTL database showed that the number of variants related to milk and reproduction was higher than the number of variants related to other traits. IPA core analysis found that the structural variations were related to reproduction, lipid metabolism, and inflammation. According to the functional analysis, structural variations were important factors affecting the variation of different traits in Shanghai Holstein cattle. Our results provide meaningful information about structural variations, which may be useful in future assessments of the associations between variations and important phenotypes in Shanghai Holstein cattle. Conclusion Structural variations identified in this study were extremely different from those of previous studies. Many structural variations were found to be associated with mastitis and reproductive system diseases; these results are in accordance with the characteristics of the environment that Shanghai Holstein cattle experience