Zhejiang University

About: Zhejiang University is a education organization based out in Hangzhou, Zhejiang, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 161257 authors who have published 183264 publications receiving 3417592 citations. The organization is also known as: Chekiang University & Zheda.

Self-Assembly of Single-Layer CoAl-Layered Double Hydroxide Nanosheets on 3D Graphene Network Used as Highly Efficient Electrocatalyst for Oxygen Evolution Reaction

Abstract: A non-noble metal based 3D porous electrocatalyst is prepared by self-assembly of the liquid-exfoliated single-layer CoAl-layered double hydroxide nanosheets (CoAl-NSs) onto 3D graphene network, which exhibits higher catalytic activity and better stability for electrochemical oxygen evolution reaction compared to the commercial IrO2 nanoparticle-based 3D porous electrocatalyst.

Long-term fluorescent cellular tracing by the aggregates of AIE bioconjugates.

Abstract: There is a great demand for long-term cellular tracers because of their great importance in monitoring biological processes, pathological pathways, therapeutic effects, etc. Herein we report a new type of fluorescence “turn-on” probe for tracing live cells over a long period of time. We synthesized the fluorogenic probe by attaching a large number of tetraphenylethene (TPE) labels to a chitosan (CS) chain. The resultant TPE–CS bioconjugate shows a unique aggregation-induced emission (AIE) behavior. It is nonfluorescent when dissolved but becomes highly emissive when its molecules are aggregated. The AIE aggregates can be readily internalized by HeLa cells. The cellular staining by the TPE–CS aggregates is so indelible that it enables cell tracing for as long as 15 passages. The internalized AIE aggregates are kept inside the cellular compartments and do not contaminate other cell lines in the coculture systems, permitting the differentiation of specific cancerous cells from normal healthy cells.

Latency Optimization for Resource Allocation in Mobile-Edge Computation Offloading

Abstract: By offloading intensive computation tasks to the edge cloud located at the cellular base stations, mobile-edge computation offloading (MECO) has been regarded as a promising means to accomplish the ambitious millisecond-scale end-to-end latency requirement of fifth-generation networks. In this paper, we investigate the latency-minimization problem in a multi-user time-division multiple access MECO system with joint communication and computation resource allocation. Three different computation models are studied, i.e., local compression, edge cloud compression, and partial compression offloading. First, closed-form expressions of optimal resource allocation and minimum system delay for both local and edge cloud compression models are derived. Then, for the partial compression offloading model, we formulate a piecewise optimization problem and prove that the optimal data segmentation strategy has a piecewise structure. Based on this result, an optimal joint communication and computation resource allocation algorithm is developed. To gain more insights, we also analyze a specific scenario where communication resource is adequate while computation resource is limited. In this special case, the closed-form solution of the piecewise optimization problem can be derived. Our proposed algorithms are finally verified by numerical results, which show that the novel partial compression offloading model can significantly reduce the end-to-end latency.