Reimagining Shenzhen Urbanism: Villages-in-the-City, Architecture Biennales, and Modern City-Building

This dissertation tells an alternative story of Shenzhen’s emergence of one of the world’s great manufacturing cities by focusing on the transformation of over one thousand former farming and fishing villages within the Shenzhen Special Economic Zone into Villages-in-the-City [ViC] that today house about 10 million out of Shenzhen SEZ’s 14 million people. Instead of showing these villages as places of scarcity, precarity, and conflict, I approach them as critical sites of production and supply, providing sites for small-scale manufacturing, local retail, and above all affordable housing for newly arrived migrants. Yet, these ViCs are not only visually concealed between hypermodern urban structures but also omitted in the dominant narrative of Shenzhen’s model-city building process. With historical materials and ethnographic observations, I identify three prominent sets of actors: (1) urban planners (concretizing central plans and visions); (2) architects (representing the global imagination); and (3) local villagers (as bottom-up forces), in shaping the ViCs’ spatial evolution and their relationship to the larger urban transformation. As I show, this complex top-down/bottom-up formation of the ViC’s is very different from the more familiar model of informal settlements in the global South. My analysis of a maps, planning atlases, government reports, and photographs reveals that the spatial transformation of ViCs was not outside of planning. Instead, from the 1950’s socialist ideal of perpetuating villages as cooperative production sites through the 1980’s and 1990’s development strategy of supporting village manufacturing industries and affordable rental housing for migrant workers, planning played a guiding role in the process. My participation in an urban renewal project/event (architecture biennale) targeting ViCs further unveils the expanding agency of the architectural imagination during China’s on-going modernization process. Global architects operating mostly through the Shenzhen Biennales turned creative power into political and market power through their partnerships with local architects and with the local government. In addition, through extensive interviewing and other fieldwork in a selected ViC, I reveal a growing gap between the original local villagers and their descendants who collectively own the ViC land and the migrant workers who constitute the majority of ViC occupants. Local villagers’ collective land ownership allows them to partner with the local government in attracting foreign investment for rapid growth and increased rents. While the original villagers have profited greatly from Shenzhen’s rise, the migrant workers who provided the labor-power to build the new city have nevertheless become a vulnerable group subject to displacement in Shenzhen’s on-going effort to build a modern, progressive, and innovative global image. This study of Shenzhen’s ViCs sheds light on the evolving process of city-building in China, which adds local complexities to current debates in globalization and urbanization studies.PHDArchitectureUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/168112/1/jayqwang_1.pd

RIPK2: a promising target for cancer treatment

As an essential mediator of inflammation and innate immunity, the receptor-interacting serine/threonine-protein kinase-2 (RIPK2) is responsible for transducing signaling downstream of the intracellular peptidoglycan sensors nucleotide oligomerization domain (NOD)-like receptors 1 and 2 (NOD1/2), which will further activate nuclear factor kappa-B (NF-κB) and mitogen-activated protein kinase (MAPK) pathways, leading to the transcription activation of pro-inflammatory cytokines and productive inflammatory response. Thus, the NOD2-RIPK2 signaling pathway has attracted extensive attention due to its significant role in numerous autoimmune diseases, making pharmacologic RIPK2 inhibition a promising strategy, but little is known about its role outside the immune system. Recently, RIPK2 has been related to tumorigenesis and malignant progression for which there is an urgent need for targeted therapies. Herein, we would like to evaluate the feasibility of RIPK2 being the anti-tumor drug target and summarize the research progress of RIPK2 inhibitors. More importantly, following the above contents, we will analyze the possibility of applying small molecule RIPK2 inhibitors to anti-tumor therapy

Visual Analytics Law Enforcement Toolkit

VALET, visual analytics law enforcement toolkit, is an interactive toolkit developed for law enforcement agencies to explore concerned crime information and make police resource allocation strategies. As a visual analytics toolkit, VALET is coupled with data collection, data analytics and data prediction. The objective of VALET is to assist law enforcement agencies to reduce crime rate by wisely allocating police resource based on the analytics of historical crime records. The program incorporates three steps to generate police patrol route and policeman allocation. The first step is to generate crime hotspots and crime contours of collected crime data. The next step is to analyze historical crime information and predict potential defects. Finally, the program is to compute police patrol routes and allocate police resource based on schedule and specialty. The results from the program allow us to generate risky area for different type of crimes, and evaluate policemen’s performance in dealing with different type of crimes. Thus, police department is able to assign police officers to designed patrol routes that suggested by prediction tool based on policemen’s specialty. This would take advantage of crime prediction and decrease the time of handling criminal activities. With VALET, law enforcement agencies are able to explore concerned crime information intelligently. At the same time, police department is prompted to allocate police resource wisely

A Method to Transit the Rotor-to-Stator Rubbing to Normal Motion Using the Phase Characteristic

A method is proposed to transit the rotor-to-stator rubbing to no-rub motion through active auxiliary bearing. The key point of this technique is to express the attractive domain of no-rub motion based on the phase characteristic and to represent the desired status. The feedback actuation is applied by an active auxiliary bearing to drive the rotor approaching the desired status. After that, the control actuation is turned off. Although the desired status is still in rubbing, it is in the attractive domain of no-rub motion, and the response of the rotor is automatically attracted to no-rub motion

Impulsive Control of the Rotor-Stator Rub Based on Phase Characteristic

An impulsive control method is proposed to eliminate the rotor-stator rubbing based on the phase characteristic. The relation between the vibration energy and the phase difference suggests the starting point for controlling the rotor-stator rubbing by implementing impulse. When the contact between the rotor and the stator occurs, the impulse is implemented in x-direction and y-direction several times to avoid the rotor-stator rubbing. The practical feasibility of this approach is investigated by numerical simulations

Fault location in CNC system software based on the architecture expansion

Trenutno ne postoje odgovarajuće metode kojima bi se pronašla greška u softveru CNC sustava i otklonile skrivene opasnosti. U svrhu poboljšanja pouzdanosti CNC sustava, u radu je predložena metoda lokacije greške u softveru CNC sustava zasnovana na širenju arhitekture. Analizirana je greška u softveru CNC sustava, predložena je metoda širenja arhitekture softvera CNC sustava i ustanovljena je komponenta širenja. Pratili su se i bilježili izvršna putanja i informacije o morfologiji podataka softvera, dobivena je putanja greške i prihvaćen algoritam slične putanje kako bi se generirala putanja slična putanji greške. Postavljen je model zasnovan na potpori vektora najmanjim kvadratima (Least Square Support Vector Machine - LS-SVM) kako bi se odredila naredba za grešku, eliminirale greške i greška softvera stavila u strukturu CNC sustava. Eksperimentiranje s lokacijom greške provedeno je u kartici za nadzor višeosnog gibanja PCI-7344. Rezultat eksperimenta pokazuje da se predloženom metodom izbjeglo ponovljeno testiranje i otklanjanje grešaka od strane programera. Neograničena umjetnim faktorima i nivoima, to je pouzdana metoda za lociranje greške u softveru CNC sustava.There are currently no appropriate methods to find CNC system software defects and eliminate hidden dangers. In order to improve CNC system reliability, the architecture expansion-based fault location method in CNC system software was proposed in this paper. The failure of CNC system software was 619 analysed, the expansion method of CNC system software architecture was proposed and the expansion component was established. The software data morphology information and running path were monitored and recorded, the failure pathway was obtained and a similar path set algorithm was adopted to generate the similar pathway set of the fault path. A least squares SVM-based suspicion model was established to determine the fault statement, eliminate faults and position the software fault in the level of the CNC system structure. Fault location experimentation was conducted in the multi-axis movement control card PCI-7344. The experiment’s result shows that the method proposed avoided the repeated testing and debugging by programmers. Without being limited by artificial factors and levels, it is a reliable method of CNC system software fault location

ChemRL-GEM: Geometry Enhanced Molecular Representation Learning for Property Prediction

Effective molecular representation learning is of great importance to facilitate molecular property prediction, which is a fundamental task for the drug and material industry. Recent advances in graph neural networks (GNNs) have shown great promise in applying GNNs for molecular representation learning. Moreover, a few recent studies have also demonstrated successful applications of self-supervised learning methods to pre-train the GNNs to overcome the problem of insufficient labeled molecules. However, existing GNNs and pre-training strategies usually treat molecules as topological graph data without fully utilizing the molecular geometry information. Whereas, the three-dimensional (3D) spatial structure of a molecule, a.k.a molecular geometry, is one of the most critical factors for determining molecular physical, chemical, and biological properties. To this end, we propose a novel Geometry Enhanced Molecular representation learning method (GEM) for Chemical Representation Learning (ChemRL). At first, we design a geometry-based GNN architecture that simultaneously models atoms, bonds, and bond angles in a molecule. To be specific, we devised double graphs for a molecule: The first one encodes the atom-bond relations; The second one encodes bond-angle relations. Moreover, on top of the devised GNN architecture, we propose several novel geometry-level self-supervised learning strategies to learn spatial knowledge by utilizing the local and global molecular 3D structures. We compare ChemRL-GEM with various state-of-the-art (SOTA) baselines on different molecular benchmarks and exhibit that ChemRL-GEM can significantly outperform all baselines in both regression and classification tasks. For example, the experimental results show an overall improvement of 8.8% on average compared to SOTA baselines on the regression tasks, demonstrating the superiority of the proposed method