Teleportation of an arbitrary multipartite state via photonic Faraday rotation

We propose a practical scheme for deterministically teleporting an arbitrary multipartite state, either product or entangled, using Faraday rotation of the photonic polarization. Our scheme, based on the input-output process of single-photon pulses regarding cavities, works in low-Q cavities and only involves virtual excitation of the atoms, which is insensitive to both cavity decay and atomic spontaneous emission. Besides, the Bell-state measurement is accomplished by the Faraday rotation plus product-state measurements, which could much relax the experimental difficulty to realize the Bell-state measurement by the CNOT operation.Comment: 11 pages, 2 figures

Optimization Research of Generation Investment Based on Linear Programming Model

AbstractLinear programming is an important branch of operational research and it is a mathematical method to assist the people to carry out scientific management. GAMS is an advanced simulation and optimization modeling language and it will combine a large number of complex mathematical programming, such as linear programming LP, nonlinear programming NLP, MIP and other mixed-integer programming with the system simulation. In this paper, based on the linear programming model, the optimized investment decision-making of generation is simulated and analyzed. At last, the optimal installed capacity of power plants and the final total cost are got, which provides the rational decision-making basis for optimized investments

Borrower’s Self-Disclosure of Social Media Information in P2P Lending

In peer-to-peer (P2P) lending, soft information, such as borrowers’ facial features, textual descriptions of loan applications and so on, are regarded as potential signals to screen borrowers. In this study, we examine the signaling effect of a new category of soft information- social media information. Leveraging a unique dataset that combines loan data from a large P2P lending company with social media presence data from a popular social media site, and two natural experiments, we find two forms of social media information that act as signals of borrowers’ creditworthiness. First, borrowers’ choice to self-disclose their social media account is a predictor of their default probability. Second, borrowers’ social media presence, such as their social network and social media engagement, are also predictors of default probability. This study proffers new insights for the screening process in P2P lending and novel usage of social media information

DC-Prophet: Predicting Catastrophic Machine Failures in DataCenters

When will a server fail catastrophically in an industrial datacenter? Is it possible to forecast these failures so preventive actions can be taken to increase the reliability of a datacenter? To answer these questions, we have studied what are probably the largest, publicly available datacenter traces, containing more than 104 million events from 12,500 machines. Among these samples, we observe and categorize three types of machine failures, all of which are catastrophic and may lead to information loss, or even worse, reliability degradation of a datacenter. We further propose a two-stage framework-DC-Prophet-based on One-Class Support Vector Machine and Random Forest. DC-Prophet extracts surprising patterns and accurately predicts the next failure of a machine. Experimental results show that DC-Prophet achieves an AUC of 0.93 in predicting the next machine failure, and a F3-score of 0.88 (out of 1). On average, DC-Prophet outperforms other classical machine learning methods by 39.45% in F3-score.Comment: 13 pages, 5 figures, accepted by 2017 ECML PKD

Sex differences in costly signaling in rural Western China

Costly rituals convey commitment to communities and advertise trustworthiness and cooperativeness to peers, which might explain why humans perform costly religious rituals. Here, we compare the efficacy of occasional public displays versus regular but less public acts for prestige enhancement. We collected data on religious behaviors ranging from daily low-cost practices to infrequent high-cost pilgrimages to distant locations among residents of an agricultural Tibetan village, as well as their reputational standings. We find that religious practices are mediated by demographic factors such as wealth, age and gender. Women perform more daily religious activities, but men engage more in distant pilgrimages. Participation in distant pilgrimages increases the perception of all prosocial characteristics. In contrast, daily practices are positively associated with nominations for devoutness but not for other qualities. Devoutness is sometimes negatively associated with other reputational qualities, suggesting that religiosity might be not only about signaling prosociality

Filler Word Detection and Classification: A Dataset and Benchmark

Filler words such as `uh' or `um' are sounds or words people use to signal they are pausing to think. Finding and removing filler words from recordings is a common and tedious task in media editing. Automatically detecting and classifying filler words could greatly aid in this task, but few studies have been published on this problem. A key reason is the absence of a dataset with annotated filler words for training and evaluation. In this work, we present a novel speech dataset, PodcastFillers, with 35K annotated filler words and 50K annotations of other sounds that commonly occur in podcasts such as breaths, laughter, and word repetitions. We propose a pipeline that leverages VAD and ASR to detect filler candidates and a classifier to distinguish between filler word types. We evaluate our proposed pipeline on PodcastFillers, compare to several baselines, and present a detailed ablation study. In particular, we evaluate the importance of using ASR and how it compares to a transcription-free approach resembling keyword spotting. We show that our pipeline obtains state-of-the-art results, and that leveraging ASR strongly outperforms a keyword spotting approach. We make PodcastFillers publicly available, and hope our work serves as a benchmark for future research.Comment: Submitted to Insterspeech 202

Monodispersed β‐Glycerophosphate‐Decorated Bioactive Glass Nanoparticles Reinforce Osteogenic Differentiation of Adipose Stem Cells and Bone Regeneration In Vivo

Design and development of highly bioactive nanoscale biomaterials with enhanced osteogenic differentiation on adipose stem cells is rather important for bone regeneration and attracting much attention. Herein, monodispersed glycerophosphate‐decorated bioactive glass nanoparticles (BGN@GP) are designed and their effect is investigated on the osteogenic differentiation of adipose mesenchymal stem cells (ADMSCs) and in vivo bone regeneration. The surface‐modified BGN@GP can be efficiently taken by ADMSCs and shows negligible cytotoxicity. The in vitro results reveal that BGN@GP significantly enhances the alkaline phosphatase activity and calcium biominerialization of ADMSCs either under normal or osteoinductive medium as compared to BGNs. Further studies find that the osteogenic genes and proteins including Runx2 and Bsp in ADMSCs are significantly improved by BGN@GP even under normal culture medium. The in vivo animal experiment confirms that BGN@GP significantly promotes the new bone formation in a rat skull defect model. This study suggests that bioactive small molecule decorating is an efficient strategy to improve the osteogenesis capacity of inorganic ceramics nanomaterials.This paper reports that beta‐glycerophosphate‐functionalized bioactive glass nanoparticles (BGN@GP) could efficiently enhance the uptake of adipose‐derived stem cells (ADSCs) and improve the osteogenic differentiation of ADSCs and reinforce the in vivo bone regeneration, suggesting that BGN@GP is a promising biomaterial for bone tissue repair and regeneration.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154977/1/ppsc201900462.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154977/2/ppsc201900462-sup-0001-SuppMat.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154977/3/ppsc201900462_am.pd

China's evolving regional security strategy - China and the ASEAN regional forum

Master'sMASTER OF SOCIAL SCIENCE