Magnetic nanocatalysts for oxidative decomposition of persistent organic pollutants (POPs) in contaminated water

The thesis reports the synthesis of magnetic Mn-based nanocatalysts by different hydrothermal methods and their application in the oxidative reaction of aqueous phenol solutions for wastewater treatment. It was found that all the catalysts present high activity in peroxymonosulfate (PMS, Oxone) activation for the decomposition of phenol and good magnetic performance in separation. This research makes good contributions to materials synthesis and catalytic oxidation of organic pollutants in water

Functional and Structural Studies of Cytochromes P450 by Resonance Raman Spectroscopy

Cytochrome P450 is a broad class of heme monooxygenase enzymes which catalyze various oxidative transformations. There are two main kinds of mammalian P450s: steroidogenic and drug metabolizing P450s. The first project involves a steroidogenic P450, CYP17A1, occupying a central role in the biosynthesis of steroid hormones. It catalyzes hydroxylation reaction on pregnenolone and progesterone, generating 17OH-pregnenolone and 17OH-progesterone, presumably utilizing a “Compound I” species. However, these hydroxylated products can be further processed in a second oxidative cycle to cleave the C17–C20 bond to form dehydroepiandrosterone or androstenedione, respectively, a crucial step in androgen production. Interestingly, it is well known that cytochrome b5 is a key regulator of androgen synthesis, by a mechanism that is still not well understood. As the enzymes involved here are both membrane-bound, resonance Raman (rR) studies are performed on unique nanodisc-based dyads to investigate their interaction, including characterization of their ferric state and unstable dioxygen intermediates, the essential results supporting an electron transfer role of cyt b5. The second project is focused on a fusion enzyme called P450BM3, which possesses a covalently linked cytochrome P450 reductase. This fusion enzyme is clearly a good target for biotechnologically application. In the present work, rR studies focus on several biotechnologically important mutants of P450BM3, which have altered substrate selectivity, allowing metabolism of the human proton pump inhibitor, omeprazole, producing metabolites that precisely match those generated by human CYP2C19, thereby providing an inexpensive source of these precious materials that are needed for drug metabolism studies. Specifically, it is shown that binding of omeprazole to these BM3 mutants leads to differing degrees of high spin state conversion of the heme iron. Furthermore, the ferrous CO adduct were acquired to interrogate the effect of substrate binding on the distal pocket architecture. The third project involves the biotechnologically important peroxygenases. Specifically, rR studies are applied to CYP152L1 and CYP152L2 enzymes, which are able to convert fatty acids into industrially valuable terminal alkenes without requiring a complex reductase system. Herein, using chemical strategies to trap and isolate key reaction intermediates, rR spectroscopy is being employed to probe their structure and reactivity

Understanding and Predicting Delay in Reciprocal Relations

Reciprocity in directed networks points to user's willingness to return favors in building mutual interactions. High reciprocity has been widely observed in many directed social media networks such as following relations in Twitter and Tumblr. Therefore, reciprocal relations between users are often regarded as a basic mechanism to create stable social ties and play a crucial role in the formation and evolution of networks. Each reciprocity relation is formed by two parasocial links in a back-and-forth manner with a time delay. Hence, understanding the delay can help us gain better insights into the underlying mechanisms of network dynamics. Meanwhile, the accurate prediction of delay has practical implications in advancing a variety of real-world applications such as friend recommendation and marketing campaign. For example, by knowing when will users follow back, service providers can focus on the users with a potential long reciprocal delay for effective targeted marketing. This paper presents the initial investigation of the time delay in reciprocal relations. Our study is based on a large-scale directed network from Tumblr that consists of 62.8 million users and 3.1 billion user following relations with a timespan of multiple years (from 31 Oct 2007 to 24 Jul 2013). We reveal a number of interesting patterns about the delay that motivate the development of a principled learning model to predict the delay in reciprocal relations. Experimental results on the above mentioned dynamic networks corroborate the effectiveness of the proposed delay prediction model.Comment: 10 page

Secure Pick Up: Implicit Authentication When You Start Using the Smartphone

We propose Secure Pick Up (SPU), a convenient, lightweight, in-device, non-intrusive and automatic-learning system for smartphone user authentication. Operating in the background, our system implicitly observes users' phone pick-up movements, the way they bend their arms when they pick up a smartphone to interact with the device, to authenticate the users. Our SPU outperforms the state-of-the-art implicit authentication mechanisms in three main aspects: 1) SPU automatically learns the user's behavioral pattern without requiring a large amount of training data (especially those of other users) as previous methods did, making it more deployable. Towards this end, we propose a weighted multi-dimensional Dynamic Time Warping (DTW) algorithm to effectively quantify similarities between users' pick-up movements; 2) SPU does not rely on a remote server for providing further computational power, making SPU efficient and usable even without network access; and 3) our system can adaptively update a user's authentication model to accommodate user's behavioral drift over time with negligible overhead. Through extensive experiments on real world datasets, we demonstrate that SPU can achieve authentication accuracy up to 96.3% with a very low latency of 2.4 milliseconds. It reduces the number of times a user has to do explicit authentication by 32.9%, while effectively defending against various attacks.Comment: Published on ACM Symposium on Access Control Models and Technologies (SACMAT) 201

UrbanScene3D: A Large Scale Urban Scene Dataset and Simulator

The ability to perceive the environments in different ways is essential to robotic research. This involves the analysis of both 2D and 3D data sources. We present a large scale urban scene dataset associated with a handy simulator based on Unreal Engine 4 and AirSim, which consists of both man-made and real-world reconstruction scenes in different scales, referred to as UrbanScene3D. Unlike previous works that purely based on 2D information or man-made 3D CAD models, UrbanScene3D contains both compact man-made models and detailed real-world models reconstructed by aerial images. Each building has been manually extracted from the entire scene model and then has been assigned with a unique label, forming an instance segmentation map. The provided 3D ground-truth textured models with instance segmentation labels in UrbanScene3D allow users to obtain all kinds of data they would like to have: instance segmentation map, depth map in arbitrary resolution, 3D point cloud/mesh in both visible and invisible places, etc. In addition, with the help of AirSim, users can also simulate the robots (cars/drones)to test a variety of autonomous tasks in the proposed city environment. Please refer to our paper and website(https://vcc.tech/UrbanScene3D/) for further details and applications.Comment: Project page: https://vcc.tech/UrbanScene3D

The Transformation of Major Power Generation Channels and Comparative Analysis of Policies in China and the United States in the Context of Carbon Neutrality

The primary contributor to global warming is human emissions of greenhouse gases. In order to prevent the continued warming of the global climate, the realization of carbon neutrality is a necessary way to achieve this goal. Although both China and the United States have made corresponding strategic deployments to achieve carbon neutrality, the difficulties faced by the two countries to attain the goal still need to be analyzed and resolved. This article compares the primary power generation methods and the differences in policies between the two countries over the years. It analyzes the changes and difficulties China and the United States faced in achieving carbon neutrality. Preliminary analysis shows that China and the United States generate electricity mainly through thermal power. Due to the difference in resources between the two countries, the United States uses natural gas as a raw material. In contrast, coal is the primary raw material for China's thermal power generation. China and the United States have developed ambitious policy plans to meet their respective carbon neutrality objectives. However, in contrast to China's more stable policies, the US strategy needs equivalent stability