Anisotropic but nodeless superconducting gap in the presence of spin density wave in iron-pnictide superconductor NaFe1-xCoxAs

The coexisting regime of spin density wave (SDW) and superconductivity in the iron pnictides represents a novel ground state. We have performed high resolution angle-resolved photoemission measurements on NaFe1-xCoxAs (x = 0.0175) in this regime and revealed its distinctive electronic structure, which provides some microscopic understandings of its behavior. The SDW signature and the superconducting gap are observed on the same bands, illustrating the intrinsic nature of the coexistence. However, because the SDW and superconductivity are manifested in different parts of the band structure, their competition is non-exclusive. Particularly, we found that the gap distribution is anisotropic and nodeless, in contrast to the isotropic superconducting gap observed in an SDW-free NaFe1-xCoxAs (x=0.045), which puts strong constraints on theory.Comment: 5 pages, 4 figures + supplementary informatio

Centrality, system size and energy dependences of charged-particle pseudo-rapidity distribution

Utilizing the three-fireball picture within the quark combination model, we study systematically the charged particle pseudorapidity distributions in both Au+Au and Cu+Cu collision systems as a function of collision centrality and energy, $\sqrt{s_{NN}}=$ 19.6, 62.4, 130 and 200 GeV, in full pseudorapidity range. We find that: (i)the contribution from leading particles to $dN_{ch}/d\eta$ distributions increases with the decrease of the collision centrality and energy respectively; (ii)the number of the leading particles is almost independent of the collision energy, but it does depend on the nucleon participants $N_{part}$; (iii)if Cu+Cu and Au+Au collisions at the same collision energy are selected to have the same $N_{part}$, the resulting of charged particle $dN/d\eta$ distributions are nearly identical, both in the mid-rapidity particle density and the width of the distribution. This is true for both 62.4 GeV and 200 GeV data. (iv)the limiting fragmentation phenomenon is reproduced. (iiv) we predict the total multiplicity and pseudorapidity distribution for the charged particles in Pb+Pb collisions at $\sqrt{s_{NN}}= 5.5$ TeV. Finally, we give a qualitative analysis of the $N_{ch}/$ and $dN_{ch}/d\eta/|_{\eta\approx0}$ as function of $\sqrt{s_{NN}}$ and $N_{part}$ from RHIC to LHC.Comment: 12 pages, 8 figure

Enabling the Possibility of creating a New Smart Resilient City in the Post-Pandemic Period

Beginning in early 2020, the COVID-19 pandemic sweeps across the globe. Despite the full lockdowns are being released deliberately and gradually in most parts of the world, social distancing is still needed in short-term and medium-term to mitigate the spread of coronavirus. These disruptive changes of life and work landscape bring the needs to reset the way how we use our cities and the opportunities to reshape the way how we manage our cities, which directly impact on the wellbeing during the post-pandemic period. For previous developed smart cities, it remains to be checked whether the historical data and the existing solutions during pre-pandemic still works in the post-pandemic situations. Faced with the post-pandemic situation that we have never seen before, the effectiveness of developed smart city solutions along with the applicability of adopted historical data must be re-evaluated and re-verified timely. This paper aims at providing a start point of enabling a future of resilient cities from the pre-pandemic to post-pandemic. Firstly, behaviour changes will be discussed. Then, the framework of the bidirectional interaction between human and cities will be established in this paper, and the mitigation measures based on digital innovation will be further provided that could guarantee the smart cities from the insufficient post-pandemic data. Future works and challenges will also be discussed. With the pervasive digital transformation of cities, the possibility of creating a more robust and smart resilient city is provided to maximally unleash the value of data, historical or recent, under a people-focused view

Co-training an improved recurrent neural network with probability statistic models for named entity recognition

© Springer International Publishing AG 2017. Named Entity Recognition (NER) is a subtask of information extraction in Natural Language Processing (NLP) field and thus being wildly studied. Currently Recurrent Neural Network (RNN) has become a popular way to do NER task, but it needs a lot of train data. The lack of labeled train data is one of the hard problems and traditional co-training strategy is a way to alleviate it. In this paper, we consider this situation and focus on doing NER with co-training using RNN and two probability statistic models i.e. Hidden Markov Model (HMM) and Conditional Random Field (CRF). We proposed a modified RNN model by redefining its activation function. Compared to traditional sigmoid function, our new function avoids saturation to some degree and makes its output scope very close to [0, 1], thus improving recognition accuracy. Our experiments are conducted ATIS benchmark. First, supervised learning using those models are compared when using different train data size. The experimental results show that it is not necessary to use whole data, even small part of train data can also get good performance. Then, we compare the results of our modified RNN with original RNN. 0.5% improvement is obtained. Last, we compare the co-training results. HMM and CRF get higher improvement than RNN after co-training. Moreover, using our modified RNN in co-training, their performances are improved further

The Digital Silicon Photomultiplier

The Silicon Photomultipliers (SiPMs) are the new step in the development of the modern detection structures in the area of low photon flux detection with a unique capability of detection up to the single photons. The Silicon Photomultiplier intrinsically represents a digital signal source on the elementary cell level. The materials and technology of SiPMs are consistent with the modern electronics technology. We present the realization and implementation of a fully digital Silicon Photomultiplier Imager with an enclosed readout and processing on the basis of modern 3D technology