The Total Synthesis of () 7-HDHA

Fatty acid () 7-HDHA was recently identified as an endogenous ligand for PPAR/ receptors by one of our collaborators Dr. Henry Krause group. While this discovery is promising in understanding PPARs mechanism of effects and related diseases (Alzheimers disease, cerebral ischemia, retina inflammation, etc.), the study of 7-HDHA in relation to PPARs has been hampered by the high cost and limited supply of 7-HDHA. The total synthesis of 7-HDHA was attempted using four different strategies, and finally achieved in 11 steps in the longest reaction sequence, starting from commercially available (triisopropylsilyl)acetylene and 2-pentyn-1-ol. The overall yield of this synthesis was 12%. This concise route mainly relies on the one-step generation of three Z-double bonds with the semi-hydrogenation catalyst P2-Nickel, and a late-stage semi-hydrogenation with Zn(Cu/Ag) reagent. The completion of this synthesis will now provide large quantities of 7-HDHA quickly, and thus enable extensive studies of PPAR 7-HDHA interaction

Managerial Perception of Supply Chain Quality Risk: Risk Analysis and Decision Analysis

Due to increased supply chain complexity, ensuring the quality of supply materials or products from upstream suppliers has become a challenge for firms. A great deal has been written on possible solutions and strategies to deal with supply chain quality risk (SCQR) in recent years. However, the manager’s decision-making process in relation to SCQR has not been fully researched. To close this gap, the aims of this study were to scrutinise managers’ perceptions of SCQR, as well as the antecedents of and decision-making related to perceived SCQR. The relevant literature was comprehensively reviewed in order to build a foundation for the conceptualisation of perceived SCQR. This study proposed that the managerial perception of SCQR was a multi-dimensional concept with four representations. A rigorous scale development process was adopted to develop a set of reliable instruments to measure perceived SCQR. With a sample of 316 Chinese manufacturers, the validity and reliability of the measurement scales for the representations of SCQR perception were assessed. Based on the risky-decision making model, a theoretical framework of the managerial decision-making process in relation to perceived SCQR was proposed. Furthermore, the agency theory and resource dependence theory were drawn on to identify factors related to the supply chain relationship and supply chain quality barriers that might have effects on three of the representations of SCQR. Based on the resource dependence theory, it was found that buyer and supplier dependence affect the representations of SCQR differently. The empirical results indicate that the inability to test and inability to trace are significant drivers of the perception of SCQR. The representation of SCQR impact on the intention of adopting two oriented quality management practices was also examined. The result reveals that when managers face increasing SCQR, they tend to be conservative in applying the quality management practices

Towards Robust Neural Networks via Random Self-ensemble

Recent studies have revealed the vulnerability of deep neural networks: A small adversarial perturbation that is imperceptible to human can easily make a well-trained deep neural network misclassify. This makes it unsafe to apply neural networks in security-critical applications. In this paper, we propose a new defense algorithm called Random Self-Ensemble (RSE) by combining two important concepts: {\bf randomness} and {\bf ensemble}. To protect a targeted model, RSE adds random noise layers to the neural network to prevent the strong gradient-based attacks, and ensembles the prediction over random noises to stabilize the performance. We show that our algorithm is equivalent to ensemble an infinite number of noisy models $f_\epsilon$ without any additional memory overhead, and the proposed training procedure based on noisy stochastic gradient descent can ensure the ensemble model has a good predictive capability. Our algorithm significantly outperforms previous defense techniques on real data sets. For instance, on CIFAR-10 with VGG network (which has 92\% accuracy without any attack), under the strong C\&W attack within a certain distortion tolerance, the accuracy of unprotected model drops to less than 10\%, the best previous defense technique has $48\%$ accuracy, while our method still has $86\%$ prediction accuracy under the same level of attack. Finally, our method is simple and easy to integrate into any neural network.Comment: ECCV 2018 camera read

City acupuncture: the sustainable development of the balanced city in post-industrial age

After the Franco dictatorship, a new chapter occurred in Barcelona’s Democracy. As having fully understood the spirit of Cerda’s planning, the participants in Barcelona urban planning creatively started to use a treatment called acupuncture in the city, which has the same spirit as traditional Chinese medical science, and revived the ruined city, gradually gain back the balanced and sustainable management of the city. The thesis introduces the problems Barcelona met in the post-industrial age and the corresponding solutions, mainly focuses on Barcelona city renewal in the 80s, and tries to explain the relationship between traditional Chinese medical science and city acupuncture, which will be the clue of the thesis. The thesis will be described in three chapters, human body and city under the view of traditional Chinese medical science, acupuncture therapy and the Barcelona model and sustainable development of the balanced city.Peer Reviewe