Optical coherence microscopy and focal modulation microscopy for Real-time Deep Tissue imaging

Ph.DDOCTOR OF PHILOSOPH

Positive and unlabeled learning for user behavior analysis based on mobile internet traffic data

With the rapid development of wireless communication and mobile Internet, mobile phone becomes ubiquitous and functions as a versatile and smart system, on which people frequently interact with various mobile applications (Apps). Understanding human behaviors using mobile phone is significant for mobile system developers, for human-centered system optimization and better service provisioning. In this paper, we focus on mobile user behavior analysis and prediction based on mobile Internet traffic data. Real traffic flow data is collected from the public network of Internet Service Providers (ISPs), by high-performance network traffic monitors.We construct User-App bipartite network to represent the traffic interaction pattern between users and App servers. After mining the explicit and implicit features from User-App bipartite network, we propose two positive and unlabeled learning (PU learning) methods, including Spy-based PU learning and K-means-based PU learning, for App usage prediction and mobile video traffic identification. We firstly use the traffic flow data of QQ, a very famous messaging and social media application possessing high market share in China, as the experimental dataset for App usage prediction task. Then we use the traffic flow data from six popular Apps, including video intensive Apps (Youku, Baofeng, LeTV, Tudou) and other Apps (Meituan, Apple), as the experimental dataset for mobile video traffic identification task. Experimental results show that our proposed PU learning methods perform well in both tasks

Feasibility of using Y₂Ti₂O₇ nanoparticles to fabricate high strength oxide dispersion strengthened Fe-Cr-Al steels

Addition of Al can improve the corrosion resistance of oxide dispersion strengthened (ODS) steels. However, Al reacts with Y2O3 to form large Y-Al-O particles in the steels and deteriorates their mechanical properties. Herein, we successfully prepared Y2Ti2O7 nanoparticles (NPs) by the combination of hydrogen plasma-metal reaction (HPMR) and annealing. Y2Ti2O7 NPs with contents of 0.2 or 0.6 wt.% were then added into the Fe-14Cr-3Al-2W-0.35Ti (wt.%) steel to substitute the conventional Y2O3 NPs by mechanical alloying (MA). The Y2Ti2O7 NPs transformed into amorphous-like structure after 96 h MA. They crystallized with a fine size of 7.4±3.7 nm and shared a semi-coherent interface with the matrix after hot isostatic pressing (HIP) of the ODS steel with 0.6 wt.% Y2Ti2O7. With the increasing Y2Ti2O7 content from 0.2 to 0.6 wt.%, the tensile strength of the ODS steel increased from 1238 to 1296 MPa, which was much higher than that (949 MPa) of the ODS steel added with Y2O3. The remarkably improved mechanical properties of the Al-containing ODS steels were attributed to the increasing number density of Y2Ti2O7 nanoprecipitates. Our work demonstrates a novel route to fabricate high performance ODS steels with both high mechanical strength and good corrosion resistance

Feasibility of the Assessment of Cholesterol Crystals in Human Macrophages Using Micro Optical Coherence Tomography

The presence of cholesterol crystals is a hallmark of atherosclerosis, but until recently, such crystals have been considered to be passive components of necrotic plaque cores. Recent studies have demonstrated that phagocytosis of cholesterol crystals by macrophages may actively precipitate plaque progression via an inflammatory pathway, emphasizing the need for methods to study the interaction between macrophages and crystalline cholesterol. In this study, we demonstrate the feasibility of detecting cholesterol in macrophages in situ using Micro-Optical Coherence Tomography (µOCT), an imaging modality we have recently developed with 1-µm resolution. Macrophages containing cholesterol crystals frequently demonstrated highly scattering constituents in their cytoplasm on µOCT imaging, and µOCT was able to evaluate cholesterol crystals in cultured macrophage cells. Our results suggest that µOCT may be useful for the detection and characterization of inflammatory activity associated with cholesterol crystals in the coronary artery