Social media creates an interactive information communication platform for disaster preparedness, mitigation, response, and recovery. Recent research has analyzed the participation of social media in natural disasters, such as the Haiti Earthquake in 2010, Queensland floods from 2010 to 2011, Hurricane Sandy in 2012, and Colorado flood in 2013, but little research has paid attention to drought risk management. In this study, the strengths, weaknesses, opportunities, and threats analysis method is used to evaluate the social media sites of governmental agencies that were directly involved in California's Drought Task Force in the historic drought in 2014. The results show that state governmental agencies have used the popular social media platforms (Facebook, YouTube, and Twitter) as communication channels with professional stakeholders and the general public. The major functions of social media in the California drought risk management process included one-way information sharing, two-way information sharing, situational awareness, rumor control, reconnection, and decision making. However, social media was not active in donation solicitation and volunteer management. The two-way communication still stayed in relatively surficial levels with limited comments and inadequate conversations. A gap existed to reconnect public social media domain and personal social networks, even though drought risk was closely related to everyone's daily life. During the California drought in 2014, Facebook worked actively in two-way information sharing for drought risk information and water conservation strategies; YouTube was a robust platform that attracted large number of views on drought videos; and Twitter played an effective role in reconnection of social networks to expedite drought risk information dissemination.

Purpose: Ispinesib (SB-715992) is a potent inhibitor of kinesin spindle protein, a kinesin motor protein essential for the formation of a bipolar mitotic spindle and cell cycle progression through mitosis. Clinical studies of ispinesib have shown a 9% response rate in patients with locally advanced or metastatic breast cancer and a favorable safety profile without significant neurotoxicities, gastrointestinal toxicities, or hair loss. To better understand the potential of ispinesib in the treatment of breast cancer, we explored the activity of ispinesib alone and in combination with several therapies approved for the treatment of breast cancer.Experimental Design: We measured the ispinesib sensitivity and pharmacodynamic response of breast cancer cell lines representative of various subtypes in vitro and as xenografts in vivo and tested the ability of ispinesib to enhance the antitumor activity of approved therapies.Results: In vitro, ispinesib displayed broad antiproliferative activity against a panel of 53 breast cell lines. In vivo, ispinesib produced regressions in each of five breast cancer models and tumor-free survivors in three of these models. The effects of ispinesib treatment on pharmacodynamic markers of mitosis and apoptosis were examined in vitro and in vivo, revealing a greater increase in both mitotic and apoptotic markers in the MDA-MB-468 model than in the less sensitive BT-474 model. In vivo, ispinesib enhanced the antitumor activity of trastuzumab, lapatinib, doxorubicin, and capecitabine and exhibited activity comparable with paclitaxel and ixabepilone.Conclusions: These findings support further clinical exploration of kinesin spindle protein inhibitors for the treatment of breast cancer. Clin Cancer Res; 16(2); 566-76. ©2010 AACR.

Facial Expression Recognition (FER) is a challenging task that improves natural humancomputer interaction. This paper focuses on automatic FER on a single in-the-wild (ITW) image. ITW images suffer real problems of pose, direction, and input resolution. In this study, we propose a pyramid with super-resolution (PSR) network architecture to solve the ITW FER task. We also introduce a prior distribution label smoothing (PDLS) loss function that applies the additional prior knowledge of the confusion about each expression in the FER task. Experiments on the three most popular ITW FER datasets showed that our approach outperforms all the state-of-the-art methods.

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