Robust creation of entanglement between remote memory qubits

In this Letter we propose a robust quantum repeater architecture building on the original DLCZ protocol [L.M. Duan \textit{et al.}, Nature \textbf{414}, 413 (2001)]. The architecture is based on two-photon Hong-Ou-Mandel-type interference which relaxes the long distance stability requirements by about 7 orders of magnitude, from sub wavelength for the single photon interference required by DLCZ to the coherence length of the photons. Our proposal provides an exciting possibility for robust and realistic long distance quantum communication.Comment: Comments are welcome, to appear in Phys. Rev. Lett., accepted versio

Reading Scene Text in Deep Convolutional Sequences

We develop a Deep-Text Recurrent Network (DTRN) that regards scene text reading as a sequence labelling problem. We leverage recent advances of deep convolutional neural networks to generate an ordered high-level sequence from a whole word image, avoiding the difficult character segmentation problem. Then a deep recurrent model, building on long short-term memory (LSTM), is developed to robustly recognize the generated CNN sequences, departing from most existing approaches recognising each character independently. Our model has a number of appealing properties in comparison to existing scene text recognition methods: (i) It can recognise highly ambiguous words by leveraging meaningful context information, allowing it to work reliably without either pre- or post-processing; (ii) the deep CNN feature is robust to various image distortions; (iii) it retains the explicit order information in word image, which is essential to discriminate word strings; (iv) the model does not depend on pre-defined dictionary, and it can process unknown words and arbitrary strings. Codes for the DTRN will be available.Comment: To appear in the 13th AAAI Conference on Artificial Intelligence (AAAI-16), 201

Mindfulness-Based Intervention For Nurses In AIDS Care In China: A Pilot Study.

Background/purpose:Workplace stress among nurses providing care for people living with human immunodeficiency virus is a serious problem in China that may increase rates of job burnout and affect quality of care. Mindfulness-based intervention has been shown to be effective in relieving stress and burnout in nurses. Therefore, we designed a mixed-method pilot study to evaluate a mindfulness-based intervention for nurses providing care for people living with human immunodeficiency virus. Methods:Twenty nurses caring for people living with human immunodeficiency virus in the First Hospital of Changsha, China participated in a mindfulness-based intervention for 2 hr sessions weekly for 6 weeks. The Perceived Stress Scale, Maslach Burnout Inventory, Five Facets Mindfulness Questionnaire, State-Trait Anxiety Inventory, and the Beck Depression Inventory were used to collect data before and after the mindfulness-based intervention. Participants were invited to attend an in-depth interview 1 week after the end of the mindfulness-based intervention to give feedback. Results:The quantitative analyses revealed a significant change in Five Facets Mindfulness Questionnaire scores. There were no significant differences between pre- and post-intervention measures of any other variables. Qualitative results showed nurses experienced a decrease in work and daily life pressures; improvements in communications with patients, colleagues and families, with better regulation of negative emotions, and acceptance of other people and attention. Conclusion:This study supports the acceptability and potential benefits of the mindfulness-based intervention in helping nurses caring for people living with human immunodeficiency virus to manage stress and emotions, and improve their acceptance of others and attention. A larger study with a randomized controlled trial design is warranted to confirm the effectiveness of this mindfulness-based intervention