On the Nature of X(4260)

We study the property of $X(4260)$ resonance by re-analyzing all experimental data available, especially the $e^+e^- \rightarrow J/\psi\,\pi^+\pi^-,\,\,\,\omega\chi_{c0}$ cross section data. The final state interactions of the $\pi\pi$, $K\bar K$ couple channel system are also taken into account. A sizable coupling between the $X(4260)$ and $\omega\chi_{c0}$ is found. The inclusion of the $\omega\chi_{c0}$ data indicates a small value of $\Gamma_{e^+e^-}=23.30\pm 3.55$eV.Comment: Refined analysis with new experimental data included. 13 page

Berry phase in a composite system

The Berry phase in a composite system with only one subsystem being driven has been studied in this Letter. We choose two spin-$\frac 1 2$ systems with spin-spin couplings as the composite system, one of the subsystems is driven by a time-dependent magnetic field. We show how the Berry phases depend on the coupling between the two subsystems, and what is the relation between these Berry phases of the whole system and those of the subsystems.Comment: 4 pages, 6 figure

A Gaussian Bayesian model to identify spatio-temporal causalities for air pollution based on urban big data

Identifying the causalities for air pollutants and answering questions, such as, where do Beijing's air pollutants come from, are crucial to inform government decision-making. In this paper, we identify the spatio-temporal (ST) causalities among air pollutants at different locations by mining the urban big data. This is challenging for two reasons: 1) since air pollutants can be generated locally or dispersed from the neighborhood, we need to discover the causes in the ST space from many candidate locations with time efficiency; 2) the cause-and-effect relations between air pollutants are further affected by confounding variables like meteorology. To tackle these problems, we propose a coupled Gaussian Bayesian model with two components: 1) a Gaussian Bayesian Network (GBN) to represent the cause-and-effect relations among air pollutants, with an entropy-based algorithm to efficiently locate the causes in the ST space; 2) a coupled model that combines cause-and-effect relations with meteorology to better learn the parameters while eliminating the impact of confounding. The proposed model is verified using air quality and meteorological data from 52 cities over the period Jun 1st 2013 to May 1st 2015. Results show superiority of our model beyond baseline causality learning methods, in both time efficiency and prediction accuracy. © 2016 IEEE.postprintLink_to_subscribed_fulltex

Comparison of reactive magnesia- and carbide slag-activated ground granulated blastfurnace slag and Portland cement for stabilisation of a natural soil

In this study, reactive magnesia (MgO)- and carbide slag (CS)-activated ground granulated blastfurnace slag (GGBS) were used to stabilise a natural soil in comparison to Portland cement (PC). X-ray diffraction (XRD), scanning electron microscopy (SEM) and unconfined compressive strength (UCS) test were employed to investigate the microstructural and mechanical properties of stabilised soils. The results indicated that the main hydration products of CS-GGBS stabilised soil included calcium silicate hydrates (CSH), calcium aluminate hydrates (CAH) and ettringite. For MgO-GGBS stabilised soils, CSH was the only hydration product detected. These hydration products had different microstructure and binding ablility, affecting the strength of stabilised soils. There was an optimum MgO or CS content, in a range of 10-20%, for yielding the highest UCS of MG-GGBS or CS-GGBS stabilised soil at the same age. The 90-day UCS of the optimum MgO-GGBS and CS-GGBS stabilised soils was 3.0-3.2 and 2.4-3.2 times that of the PC stabilised soil, respectively.The authors appreciate the funding provided by National Natural Science Foundation of China (41330641) and Jiangsu Province (BY2014120).This is the accepted manuscript. The final version is available at http://www.sciencedirect.com/science/article/pii/S0169131715001325

Scheme for sharing classical information via tripartite entangled states

We investigate schemes for quantum secret sharing and quantum dense coding via tripartite entangled states. We present a scheme for sharing classical information via entanglement swapping using two tripartite entangled GHZ states. In order to throw light upon the security affairs of the quantum dense coding protocol, we also suggest a secure quantum dense coding scheme via W state in analogy with the theory of sharing information among involved users.Comment: 4 pages, no figure. A complete rewrritten vession, accepted for publication in Chinese Physic

Volatile components of fruits of Ligustrum lucidum Ait. stimulate proliferation and differentiation of rat calvarial osteoblasts

The fruits of Ligustrum lucidum Ait., (FLL), which contain rich volatile components, are commonly used as tonic for kidney and liver in the  traditional Chinese medicine prescriptions. This study aimed to investigate the effects of volatile components of FLL on the proliferation and   differentiation of rat calvarial osteoblasts by the MTT method and  measuring the activity of alkaline phosphatase (ALP). Results showed that volatile components (1 to 100 μg/mL) of FLL significantly (p<0.01) stimulated the proliferation and increased the ALP activity of rat calvarial osteoblasts which indicated that volatile components of FLL played an important role in osteoblastic bone formation just as non-volatile  components in FLL. Such finding accredited the FLL as a potential  candidate that might be useful in bone engineering and in treating bone defects including osteoporosis. The volatile components were analyzed by GC-MS. A total of 67 compounds were identified and the main components included (Z,Z)- 9,12-octadecadienoic acid (33.47%), n-hexadecanoic acid (15.02%), (E)-9-octadecenoic acid (9.03%), α-cadinol (6.51%), 4-hexyl-2,5-dihydro-2,5-dioxo-3-furanacetic acid (4.93%) and (E)-8-octadecenoic acid methyl ester (2.69%).Key words: Ligustrum lucidum, volatile components, rat calvarial osteoblasts

Entanglement distillation using particle statistics

We extend the idea of entanglement concentration for pure states(Phys. Rev. Lett. {\bf 88}, 187903) to the case of mixed states. The scheme works only with particle statistics and local operations, without the need of any other interactions. We show that the maximally entangled state can be distilled out when the initial state is pure, otherwise the entanglement of the final state is less than one. The distillation efficiency is a product of the diagonal elements of the initial state, it takes the maximum 50%, the same as the case for pure states.Comment: 3 pages, 1 figur

Two-photon excited hemoglobin fluorescence

We discovered that hemoglobin emits high energy Soret fluorescence when two-photon excited by the visible femtosecond light sources. The unique spectral and temporal characteristics of hemoglobin fluorescence were measured by using a time-resolved spectroscopic detection system. The high energy Soret fluorescence of hemoglobin shows the spectral peak at 438 nm with extremely short lifetime. This discovery enables two-photon excitation fluorescence microscopy to become a potentially powerful tool for in vivo label-free imaging of blood cells and vessels