Temporal similarity metrics for latent network reconstruction: The role of time-lag decay

When investigating the spreading of a piece of information or the diffusion of an innovation, we often lack information on the underlying propagation network. Reconstructing the hidden propagation paths based on the observed diffusion process is a challenging problem which has recently attracted attention from diverse research fields. To address this reconstruction problem, based on static similarity metrics commonly used in the link prediction literature, we introduce new node-node temporal similarity metrics. The new metrics take as input the time-series of multiple independent spreading processes, based on the hypothesis that two nodes are more likely to be connected if they were often infected at similar points in time. This hypothesis is implemented by introducing a time-lag function which penalizes distant infection times. We find that the choice of this time-lag strongly affects the metrics' reconstruction accuracy, depending on the network's clustering coefficient and we provide an extensive comparative analysis of static and temporal similarity metrics for network reconstruction. Our findings shed new light on the notion of similarity between pairs of nodes in complex networks

Like-sign Di-lepton Signals in Higgsless Models at the LHC

We study the potential LHC discovery of the Z1 KK gauge boson unitarizing longitudinal W+W- scattering amplitude. In particular, we explore the decay mode Z1->t tbar along with Z1-> W+W- without specifying the branching fractions. We propose to exploit the associated production pp-> W Z1, and select the final state of like-sign dileptons plus multijets and large missing energy. We conclude that it is possible to observe the Z1 resonance at a 5 sigma level with an integrated luminosity of 100 inverse fb at the LHC upto 650 GeV for a dominant WW channel, and 560 GeV for a dominant ttbar channel.Comment: 13 pages, 7 figure

Single-pixel imaging with origami pattern construction

Single-pixel compressive imaging can recover images from a small amount of measurements, offering many benefits especially for the scenes where the array detection is unavailable. However, the widely used random patterns fail to explore internal relations between the patterns and the image reconstruction. Here we propose a single-pixel imaging method based on origami pattern construction with a better imaging quality, but with less uncertainty of the pattern sequence. It can decrease the sampling ratio even to 0.5\%, really realizing super sub-Nyquist sampling. The experimental realization of this approach is a big step forward toward the real-time compressive video applications.Comment: 12 pages, 6 figure

Pulse shape discrimination based on the Tempotron: a powerful classifier on GPU

This study introduces the Tempotron, a powerful classifier based on a third-generation neural network model, for pulse shape discrimination. By eliminating the need for manual feature extraction, the Tempotron model can process pulse signals directly, generating discrimination results based on learned prior knowledge. The study performed experiments using GPU acceleration, resulting in over a 500 times speedup compared to the CPU-based model, and investigated the impact of noise augmentation on the Tempotron's performance. Experimental results showed that the Tempotron is a potent classifier capable of achieving high discrimination accuracy. Furthermore, analyzing the neural activity of Tempotron during training shed light on its learning characteristics and aided in selecting the Tempotron's hyperparameters. The dataset used in this study and the source code of the GPU-based Tempotron are publicly available on GitHub at https://github.com/HaoranLiu507/TempotronGPU.Comment: 14 pages,7 figure

Frost Durability and Strength of Concrete Prepared with Crushed Sand of Different Characteristics

The influences of fines content, methylene blue (MB) value, and lithology of crushed sand (CS) on frost durability and strength of concrete were investigated, and the frost durability and strength of crushed sand concrete (CSC) and river sand concrete (RSC) were compared. The results show that inclusion of fines improves CSC compressive strength and reduces frost durability of C30 CSC when fines content reaches 10%, whereas it has little negative influence on frost durability of C60 CSC. Increasing MB value does not negatively affect compressive strength of C30 CSC but decreases compressive strength of C60 CSC and frost durability of CSC, and the reduction is more pronounced when MB value exceeds 1.0. Lithology has no prominent influence on frost durability and compressive strength of CSC within the lithologies (dolomite, limestone, granite, basalt, and quartz) studied. Though compressive strength of CSC is a little higher than RSC under equal water to cement ratio, frost durability of CSC is no better than RSC especially for C30 CSC, and air-entraining agent is suggested for enhancing frost durability of C30 CSC exposed to freezing environment