Doctor of Philosophy

dissertationIn the era of big data, many applications generate continuous online data from distributed locations, scattering devices, etc. Examples include data from social media, financial services, and sensor networks, etc. Meanwhile, large volumes of data can be archived or stored offline in distributed locations for further data analysis. Challenges from data uncertainty, large-scale data size, and distributed data sources motivate us to revisit several classic problems for both online and offline data explorations. The problem of continuous threshold monitoring for distributed data is commonly encountered in many real-world applications. We study this problem for distributed probabilistic data. We show how to prune expensive threshold queries using various tail bounds and combine tail-bound techniques with adaptive algorithms for monitoring distributed deterministic data. We also show how to approximate threshold queries based on sampling techniques. Threshold monitoring problems can only tell a monitoring function is above or below a threshold constraint but not how far away from it. This motivates us to study the problem of continuous tracking functions over distributed data. We first investigate the tracking problem on a chain topology. Then we show how to solve tracking problems on a distributed setting using solutions for the chain model. We studied online tracking of the max function on ""broom"" tree and general tree topologies in this work. Finally, we examine building scalable histograms for distributed probabilistic data. We show how to build approximate histograms based on a partition-and-merge principle on a centralized machine. Then, we show how to extend our solutions to distributed and parallel settings to further mitigate scalability bottlenecks and deal with distributed data

Ranking Large Temporal Data

Ranking temporal data has not been studied until recently, even though ranking is an important operator (being promoted as a firstclass citizen) in database systems. However, only the instant top-k queries on temporal data were studied in, where objects with the k highest scores at a query time instance t are to be retrieved. The instant top-k definition clearly comes with limitations (sensitive to outliers, difficult to choose a meaningful query time t). A more flexible and general ranking operation is to rank objects based on the aggregation of their scores in a query interval, which we dub the aggregate top-k query on temporal data. For example, return the top-10 weather stations having the highest average temperature from 10/01/2010 to 10/07/2010; find the top-20 stocks having the largest total transaction volumes from 02/05/2011 to 02/07/2011. This work presents a comprehensive study to this problem by designing both exact and approximate methods (with approximation quality guarantees). We also provide theoretical analysis on the construction cost, the index size, the update and the query costs of each approach. Extensive experiments on large real datasets clearly demonstrate the efficiency, the effectiveness, and the scalability of our methods compared to the baseline methods.Comment: VLDB201

State-of-the-art self-luminescence: a win-win situation

Self-luminescence, which eliminates the real-time external optical excitation, can effectively avoid background autofluorescence in photoluminescence, endowing with ultrahigh signal-to-noise ratio and sensitivity in bioassay. Furthermore, in situ generated and emitted photons have been applied to develop excitation-free diagnostics and therapeutic agents against deeply seated diseases. "Enhanced" self-luminescence, referring to the aggregation-induced emission (AIE)-integrated self-luminescence systems, is endowed with not only the above merits but also other superiorities including stronger luminous brightness and longer half-life compared with "traditional" self-luminescence platforms. As an emerging and booming hotspot, the "enhanced" self-luminescence facilitated by the win-win cooperation of the aggregation-induced emission and self-luminescent techniques has become a powerful tool for interdisciplinary research. This tutorial review summarizes the advancements of AIE-assisted self-luminescence including chemiluminescence and afterglow imaging, starting from the discussion on the design and working principles, luminescent mechanisms of self-luminescence fuels, versatile integrated approaches and advantages, and a broad range of representative examples in biosensors and oncotherapy. Finally, the current challenges and perspectives are discussed to further actuate the development of "enhanced" self-luminescence agents for biomedical diagnosis and treatment.Agency for Science, Technology and Research (A*STAR)Ministry of Education (MOE)This work was partially supported by the National Natural Science Foundation of China Grant (21788102), the Research Grants Council of Hong Kong (16305518, 16307020, C6014- 20W, C6009-17G and 16305618), the Innovation and Technology Commission (ITC-CNERC14SC01), and the Material Science Foundation of Guangdong Province (2019B121205012); J. F. thanks National Science Foundation of China 21925802, 21878039; K. P. thanks Singapore Ministry of Education, Academic Research Fund Tier 1 (2019-T1-002-045, RG125/19, RT05/ 20), Academic Research Fund Tier 2 (MOE2018-T2-2-042), and A*STAR SERC AME Programmatic Fund (SERC A18A8b0059) for the financial support

Early characteristics of the COVID-19 outbreak predict the subsequent epidemic scope

OBJECTIVES: The mostly-resolved first wave of the COVID-19 epidemic in China provided a unique opportunity to investigate how the initial characteristics of the COVID-19 outbreak predict its subsequent magnitude. METHODS: We collected publicly available COVID-19 epidemiological data from 436 Chinese cities from 16th January-15th March 2020. Based on 45 cities that reported >100 confirmed cases, we examined the correlation between early-stage epidemic characteristics and subsequent epidemic magnitude. RESULTS: We identified a transition point from a slow- to a fast-growing phase for COVID-19 at 5.5 (95% CI, 4.6-6.4) days after the first report, and 30 confirmed cases marked a critical threshold for this transition. The average time for the number of confirmed cases to increase from 30 to 100 (time from 30-to-100) was 6.6 (5.3-7.9) days, and the average case-fatality rate in the first 100 confirmed cases (CFR-100) was 0.8% (0.2-1.4%). The subsequent epidemic size per million population was significantly associated with both of these indicators. We predicted a ranking of epidemic size in the cities based on these two indicators and found it highly correlated with the actual classification of epidemic size. CONCLUSIONS: Early epidemic characteristics are important indicators for the size of the entire epidemic

FoxH1 Represses the Promoter Activity of <i>cyp19a1a</i> in the Ricefield Eel (<i>Monopterus albus</i>)

Forkhead box H1 (FoxH1) is a sexually dimorphic gene in Oreochromis niloticus, Oplegnathus fasciatus, and Acanthopagrus latus, indicating that it is essential for gonadal development. In the present study, the molecular characteristics and potential function of FoxH1 and the activation of the cyp19a1a promoter in vitro were evaluated in Monopterus albus. The levels of foxh1 in the ovaries were three times higher than those in the testes and were regulated by gonadotropins (Follicle-Stimulating Hormone and Human Chorionic Gonadotropin). FoxH1 colocalized with Cyp19a1a in the oocytes and granulosa cells of middle and late vitellogenic follicles. In addition, three FoxH1 binding sites were identified in the proximal promoter of cyp19a1a, namely, FH1 (−871/−860), FH2 (−535/−524), and FH3 (−218/−207). FoxH1 overexpression significantly attenuated the activity of the cyp19a1a promoter in CHO cells, and FH1/2 mutation increased promoter activity. Taken together, these results suggest that FoxH1 may act as an important regulator in the ovarian development of M. albus by repressing cyp19a1a promoter activity, which provides a foundation for the study of FoxH1 function in bony fish reproductive processes