Generalization of Friedberg-Lee Symmetry

We study the possible origin of Friedberg-Lee symmetry. First, we propose the generalized Friedberg-Lee symmetry in the potential by including the scalar fields in the field transformations, which can be broken down to the FL symmetry spontaneously. We show that the generalized Friedberg-Lee symmetry allows a typical form of Yukawa couplings, and the realistic neutrino masses and mixings can be generated via see-saw mechanism. If the right-handed neutrinos transform non-trivially under the generalized Friedberg-Lee symmetry, we can have the testable TeV scale see-saw mechanism. Second, we present two models with the $SO(3)\times U(1)$ global flavour symmetry in the lepton sector. After the flavour symmetry breaking, we can obtain the charged lepton masses, and explain the neutrino masses and mixings via see-saw mechanism. Interestingly, the complete neutrino mass matrices are similar to those of the above models with generalized Friedberg-Lee symmetry. So the Friedberg-Lee symmetry is the residual symmetry in the neutrino mass matrix after the $SO(3)\times U(1)$ flavour symmetry breaking.Comment: 16 pages, no figure, version published in PR

Understanding the DsJ+(2317)D^+_{sJ}(2317) and DsJ+(2460)D^+_{sJ}(2460) with Sum Rules in HQET

In the framework of heavy quark effective theory we use QCD sum rules to calculate the masses of the $\bar c s$ $(0^+, 1^+)$ and $(1^+, 2^+)$ excited states. The results are consistent with that the states $D_{sJ}(2317)$ and $D_{sJ}(2460)$ observed by BABAR and CLEO are the $0^+$ and $1^+$ states in the $j_l={1\over 2}^+$ doublet

Effective and Efficient Similarity Index for Link Prediction of Complex Networks

Predictions of missing links of incomplete networks like protein-protein interaction networks or very likely but not yet existent links in evolutionary networks like friendship networks in web society can be considered as a guideline for further experiments or valuable information for web users. In this paper, we introduce a local path index to estimate the likelihood of the existence of a link between two nodes. We propose a network model with controllable density and noise strength in generating links, as well as collect data of six real networks. Extensive numerical simulations on both modeled networks and real networks demonstrated the high effectiveness and efficiency of the local path index compared with two well-known and widely used indices, the common neighbors and the Katz index. Indeed, the local path index provides competitively accurate predictions as the Katz index while requires much less CPU time and memory space, which is therefore a strong candidate for potential practical applications in data mining of huge-size networks.Comment: 8 pages, 5 figures, 3 table

Adaptive Honeypot Engagement through Reinforcement Learning of Semi-Markov Decision Processes

A honeynet is a promising active cyber defense mechanism. It reveals the fundamental Indicators of Compromise (IoCs) by luring attackers to conduct adversarial behaviors in a controlled and monitored environment. The active interaction at the honeynet brings a high reward but also introduces high implementation costs and risks of adversarial honeynet exploitation. In this work, we apply infinite-horizon Semi-Markov Decision Process (SMDP) to characterize a stochastic transition and sojourn time of attackers in the honeynet and quantify the reward-risk trade-off. In particular, we design adaptive long-term engagement policies shown to be risk-averse, cost-effective, and time-efficient. Numerical results have demonstrated that our adaptive engagement policies can quickly attract attackers to the target honeypot and engage them for a sufficiently long period to obtain worthy threat information. Meanwhile, the penetration probability is kept at a low level. The results show that the expected utility is robust against attackers of a large range of persistence and intelligence. Finally, we apply reinforcement learning to the SMDP to solve the curse of modeling. Under a prudent choice of the learning rate and exploration policy, we achieve a quick and robust convergence of the optimal policy and value.Comment: The presentation can be found at https://youtu.be/GPKT3uJtXqk. arXiv admin note: text overlap with arXiv:1907.0139

Exclusive semileptonic rare decays B−>(B ->_ (K,K^*) \ell^+ \ell^- in supersymmetric theories

The invariant mass spectrum, forward-backward asymmetry, and lepton polarizations of the exclusive processes $B\to K(K^*)\ell^+ \ell^-, \ell=\mu, \tau$ are analyzed under supersymmetric context. Special attention is paid to the effects of neutral Higgs bosons (NHBs). Our analysis shows that the branching ratio of the process \bkm can be quite largely modified by the effects of neutral Higgs bosons and the forward-backward asymmetry would not vanish. For the process \bksm, the lepton transverse polarization is quite sensitive to the effects of NHBs, while the invariant mass spectrum, forward-backward asymmetry, and lepton longitudinal polarization are not. For both \bkt and \bkst, the effects of NHBs are quite significant. The partial decay widths of these processes are also analyzed, and our analysis manifest that even taking into account the theoretical uncertainties in calculating weak form factors, the effects of NHBs could make SUSY shown up.Comment: Several references are added, typo are correcte

Genetic diversity of the 2013–14 human isolates of influenza H7N9 in China

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Back reaction, covariant anomaly and effective action

In the presence of back reaction, we first produce the one-loop corrections for the event horizon and Hawking temperature of the Reissner-Nordstr\"om black hole. Then, based on the covariant anomaly cancelation method and the effective action technique, the modified expressions for the fluxes of gauge current and energy momentum tensor, due to the effect of back reaction, are obtained. The results are consistent with the Hawking fluxes of a (1+1)-dimensional blackbody at the temperature with quantum corrections, thus confirming the robustness of the covariant anomaly cancelation method and the effective action technique for black holes with back reaction.Comment: 17 page

Open-Retrieval Conversational Question Answering

Conversational search is one of the ultimate goals of information retrieval. Recent research approaches conversational search by simplified settings of response ranking and conversational question answering, where an answer is either selected from a given candidate set or extracted from a given passage. These simplifications neglect the fundamental role of retrieval in conversational search. To address this limitation, we introduce an open-retrieval conversational question answering (ORConvQA) setting, where we learn to retrieve evidence from a large collection before extracting answers, as a further step towards building functional conversational search systems. We create a dataset, OR-QuAC, to facilitate research on ORConvQA. We build an end-to-end system for ORConvQA, featuring a retriever, a reranker, and a reader that are all based on Transformers. Our extensive experiments on OR-QuAC demonstrate that a learnable retriever is crucial for ORConvQA. We further show that our system can make a substantial improvement when we enable history modeling in all system components. Moreover, we show that the reranker component contributes to the model performance by providing a regularization effect. Finally, further in-depth analyses are performed to provide new insights into ORConvQA.Comment: Accepted to SIGIR'2