77 research outputs found
GW26-e1303 Correlation between serum cholesterol and PCI-related myocardial infarction: Is HDL-C good or bad?
GW26-e1305 Platelet aggregation influenced by the loading-dose of multiple anti-platelet therapy in patients with acute myocardial infarction
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Multi-functional anodes boost the transient power and durability of proton exchange membrane fuel cells.
Proton exchange membrane fuel cells have been regarded as the most promising candidate for fuel cell vehicles and tools. Their broader adaption, however, has been impeded by cost and lifetime. By integrating a thin layer of tungsten oxide within the anode, which serves as a rapid-response hydrogen reservoir, oxygen scavenger, sensor for power demand, and regulator for hydrogen-disassociation reaction, we herein report proton exchange membrane fuel cells with significantly enhanced power performance for transient operation and low humidified conditions, as well as improved durability against adverse operating conditions. Meanwhile, the enhanced power performance minimizes the use of auxiliary energy-storage systems and reduces costs. Scale fabrication of such devices can be readily achieved based on the current fabrication techniques with negligible extra expense. This work provides proton exchange membrane fuel cells with enhanced power performance, improved durability, prolonged lifetime, and reduced cost for automotive and other applications
GW26-e4543 Hyperhomocysteinemia and contrast-induced nephropathy in diabetic patients with renal dysfunction who underwent percutaneous coronary intervention
GW26-e1576 The Association between Frequent Premature Ventricular Contractions and the Left Ventricular Function of Late Pregnant Women
The art of defense: letting networks fool the attacker
Some deep neural networks are invariant to some input transformations, such
as Pointnet is permutation invariant to the input point cloud. In this paper,
we demonstrated this property could be powerful in defense of gradient-based
attacks. Specifically, we apply random input transformation which is invariant
to the networks we want to defend. Extensive experiments demonstrate that the
proposed scheme defeats various gradient-based attackers in the targeted attack
setting, and breaking the attack accuracy into nearly zero. Our code is
available at: {\footnotesize{\url{https://github.com/cuge1995/IT-Defense}}}
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