Hefei National Research Center for Physical Sciences at the Microscale, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Department of Materials Science and Engineering, CAS Key Laboratory of Materials for Energy Conversion, University of Science and Technology of China, Hefei, Anhui 230026, China
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Huijuan Huang
Hefei National Research Center for Physical Sciences at the Microscale, iChEM (Collaborative Innovation Center of Chemistry for Energy Materials), Department of Materials Science and Engineering, CAS Key Laboratory of Materials for Energy Conversion, University of Science and Technology of China, Hefei, Anhui 230026, China
Ovarian hyperstimulation syndrome (OHSS) is almost exclusively associated with ovulation induction with gonadotropins or, occasionally, clomiphene citrate. Severe ovarian hyperstimulation after delivery has never been reported previously. Herein, a case of OHSS after Cesarean operation is presented. The left ovary was subjected to wedge section and three-quarters of the tissue was removed. Cysts on the right ovary were enucleated and fluid within the cysts was sucked away. The patient was treated by intravenous albumin infusion.
Location-based services (LBS) have gained huge popularity because of the easy availability of modern mobile devices and the fast development of geographical information science (GIS). However, the lack of protection for private user positions might give rise to privacy concerns. This kind of problem is especially serious in mobile application environment because many mobile applications tend to use LBS. In this paper, we propose a new privacy preserving approach using customized robust cloaked region (RCR), depending on a peer-to-peer structure and the premise that users do not trust each other when sharing their geographical locations. Two algorithms are used to generate the RCR with high user density. The area of the RCR is controlled by the user’s demanded degree of protection. To enhance the resistance to regional background knowledge attack, we incorporate a location semantic value into each unit of the user map. According to extensive simulations, our method can effectively obfuscate a user’s geographical location into a highly indistinguishable region because of the disturbance of nearby users and different equally possible locations.