Observation of the TeV gamma-ray source MGRO J1908+06 with ARGO-YBJ

The extended gamma ray source MGRO J1908+06, discovered by the Milagro air shower detector in 2007, has been observed for about 4 years by the ARGO-YBJ experiment at TeV energies, with a statistical significance of 6.2 standard deviations. The peak of the signal is found at a position consistent with the pulsar PSR J1907+0602. Parametrizing the source shape with a two-dimensional Gauss function we estimate an extension \sigma = 0.49 \pm 0.22 degrees, consistent with a previous measurement by the Cherenkov Array H.E.S.S.. The observed energy spectrum is dN/dE = 6.1 \pm 1.4 \times 10^-13 (E/4 TeV)^{-2.54 \pm 0.36} photons cm^-2 s^-1 TeV^-1, in the energy range 1-20 TeV. The measured gamma ray flux is consistent with the results of the Milagro detector, but is 2-3 times larger than the flux previously derived by H.E.S.S. at energies of a few TeV. The continuity of the Milagro and ARGO-YBJ observations and the stable excess rate observed by ARGO-YBJ along 4 years of data taking support the identification of MGRO J1908+06 as the steady powerful TeV pulsar wind nebula of PSR J1907+0602, with an integrated luminosity above 1 TeV about 1.8 times the Crab Nebula luminosity.Comment: 6 pages, accepted for pubblication by ApJ. Replaced to correct the author lis

Long-term Monitoring on Mrk 501 for Its VHE gamma Emission and a Flare in October 2011

As one of the brightest active blazars in both X-ray and very high energy $\gamma$-ray bands, Mrk 501 is very useful for physics associated with jets from AGNs. The ARGO-YBJ experiment is monitoring it for $\gamma$-rays above 0.3 TeV since November 2007. Starting from October 2011 the largest flare since 2005 is observed, which lasts to about April 2012. In this paper, a detailed analysis is reported. During the brightest $\gamma$-rays flaring episodes from October 17 to November 22, 2011, an excess of the event rate over 6 $\sigma$ is detected by ARGO-YBJ in the direction of Mrk 501, corresponding to an increase of the $\gamma$-ray flux above 1 TeV by a factor of 6.6$\pm$2.2 from its steady emission. In particular, the $\gamma$-ray flux above 8 TeV is detected with a significance better than 4 $\sigma$. Based on time-dependent synchrotron self-Compton (SSC) processes, the broad-band energy spectrum is interpreted as the emission from an electron energy distribution parameterized with a single power-law function with an exponential cutoff at its high energy end. The average spectral energy distribution for the steady emission is well described by this simple one-zone SSC model. However, the detection of $\gamma$-rays above 8 TeV during the flare challenges this model due to the hardness of the spectra. Correlations between X-rays and $\gamma$-rays are also investigated.Comment: have been accepted for publication at Ap

Dataset about Port Research

After detemining that there is no direct connection to the port in the network diagram, get the direct connection distance between ports through the port.sol.com.cn、SeaRates.com and McDistance shipping calculation tool. If there is a big difference between the three query data, the average value method is used for optimization, get the table Port Distance.Using the Floyd algorithm, the path between two ports in the port network graph is solved on the basis of the table Port Distance, there maybe multiple shortest paths between two ports, but this situation is not considered here, the only result will be the result of Python simulation, get the table Port Shortest Path.After get the Port Shortest Path, calculate the value of the shortest path between two ports, get the table Port Shortest Path Value.According to the shortest path between two ports, count the number of routes for each port, then use the K-Medoids, construting the model of strategic importance of ports, get the table The number of ports is crossed by the shortest path.According to the principle of the Betweenness Centrality model, the Betweenness Centrality of each port in the whole network is obtained by the table Port Shortest Path, and then use the K-Medoids, get the table Port Betweenness Centrality.The values and contents of the table The number of ports is crossed by the shortest path and the table Betweenness Centrality Group are combined together to get the table Total Group to facilitate data search.</div

Dataset about Port Research

在确定网络图中端口之间没有直接连接后，请通过port.sol.com.cn，SeaRates.com和McDistance运输计算工具获得端口之间的直接连接距离。如果三个查询数据之间有较大差异，则使用平均值法进行优化，获得表端口距离。Using the Floyd algorithm, the path between two ports in the port network graph is solved on the basis of the table Port Distance, there maybe multiple shortest paths between two ports, but this situation is not considered here, the only result will be the result of Python simulation, get the table Port Shortest Path.After get the Port Shortest Path, calculate the value of the shortest path between two ports, get the table Port Shortest Path Value.According to the shortest path between two ports, count the number of routes for each port, then use the K-Medoids, construting the model of strategic importance of ports, get the table Number of ports are crossed by the shortest path.根据“中间性中心性”模型的原理，通过“端口最短路径”表获得整个网络中每个端口的“中间性中心性”，然后使用K-Medoids来获得“端口中间性中心性”表。表“端口通过次数组”和“中间性组”表的值和内容组合在一起，得到表“总组”，以方便数据搜索。</div

Resting-state BOLD signal variability is associated with individual differences in metacontrol

This dataset includes the computer codes, data analysis steps, analysed data to investigate ⁠the association between resting-state BOLD signal variability and individual differences in metacontrol policies