Laplacian Features for Learning with Hyperbolic Space

Due to its geometric properties, hyperbolic space can support high-fidelity embeddings of tree- and graph-structured data. As a result, various hyperbolic networks have been developed which outperform Euclidean networks on many tasks: e.g. hyperbolic graph convolutional networks (GCN) can outperform vanilla GCN on some graph learning tasks. However, most existing hyperbolic networks are complicated, computationally expensive, and numerically unstable -- and they cannot scale to large graphs due to these shortcomings. With more and more hyperbolic networks proposed, it is becoming less and less clear what key component is necessary to make the model behave. In this paper, we propose HyLa, a simple and minimal approach to using hyperbolic space in networks: HyLa maps once from a hyperbolic-space embedding to Euclidean space via the eigenfunctions of the Laplacian operator in the hyperbolic space. We evaluate HyLa on graph learning tasks including node classification and text classification, where HyLa can be used together with any graph neural networks. When used with a linear model, HyLa shows significant improvements over hyperbolic networks and other baselines

Systematic study of elliptic flow parameter in the relativistic nuclear collisions at RHIC and LHC energies

We employed the new issue of a parton and hadron cascade model PACIAE 2.1 to systematically investigate the charged particle elliptic flow parameter $v_2$ in the relativistic nuclear collisions at RHIC and LHC energies. With randomly sampling the transverse momentum $x$ and $y$ components of the particles generated in string fragmentation on the circumference of an ellipse instead of circle originally, the calculated charged particle $v_2(\eta)$ and $v_2(p_T)$ fairly reproduce the corresponding experimental data in the Au+Au/Pb+Pb collisions at $\sqrt{s_{NN}}$=0.2/2.76 TeV. In addition, the charged particle $v_2(\eta)$ and $v_2(p_T)$ in the p+p collisions at $\sqrt s$=7 TeV as well as in the p+Au/p+Pb collisions at $\sqrt{s_{NN}}$=0.2/5.02 TeV are predicted.Comment: 7 pages, 5 figure

Higher moment singularities explored by the net proton non-statistical fluctuations

We use the non-statistical fluctuation instead of the full one to explore the higher moment singularities of net proton event distributions in the relativistic Au+Au collisions at $\sqrt{s_{NN}}$ from 11.5 to 200 GeV calculated by the parton and hadron cascade model PACIAE. The PACIAE results of mean ($M$), variance ($\sigma^2$), skewness ($S$), and kurtosis ($\kappa$) are consistent with the corresponding STAR data. Non-statistical moments are calculated as the difference between the moments derived from real events and the ones from mixed events, which are constructed by combining particles randomly selected from different real events. An evidence of singularity at $\sqrt{s_{NN}}\sim$ 60 GeV is first seen in the energy dependent non-statistical $S$ and $S\sigma$.Comment: 5 pages,5 figure

A minK-HERG complex regulates the cardiac potassium current I(Kr).

MinK is a widely expressed protein of relative molecular mass approximately 15K that forms potassium channels by aggregation with other membrane proteins. MinK governs ion channel activation, regulation by second messengers, and the function and structure of the ion conduction pathway. Association of minK with a channel protein known as KvLQT1 produces a voltage-gated outward K+ current (I[sK]) resembling the slow cardiac repolarization current (I[Ks]). HERG, a human homologue of the ether-a-go-go gene of the fruitfly Drosophila melanogaster, encodes a protein that produces the rapidly activating cardiac delayed rectifier (I[Kr]). These two potassium currents, I(Ks) and I(Kr), provide the principal repolarizing currents in cardiac myocytes for the termination of action potentials. Although heterologously expressed HERG channels are largely indistinguishable from native cardiac I(Kr), a role for minK in this current is suggested by the diminished I(Kr) in an atrial tumour line subjected to minK antisense suppression. Here we show that HERG and minK form a stable complex, and that this heteromultimerization regulates I(Kr) activity. MinK, through the formation of heteromeric channel complexes, is thus central to the control of the heart rate and rhythm

PACIAE 2.0: An updated parton and hadron cascade model (program) for the relativistic nuclear collisions

We have updated the parton and hadron cascade model PACIAE for the relativistic nuclear collisions, from based on JETSET 6.4 and PYTHIA 5.7 to based on PYTHIA 6.4, and renamed as PACIAE 2.0. The main physics concerning the stages of the parton initiation, parton rescattering, hadronization, and hadron rescattering were discussed. The structures of the programs were briefly explained. In addition, some calculated examples were compared with the experimental data. It turns out that this model (program) works well.Comment: 23 pages, 7 figure

Model Identification and Control for a Quarter Car Test Rig of Series Active Variable Geometry Suspension

In this paper, a quarter car test rig is utilized to perform an experimental study of the singlelink variant of the Series Active Variable Geometry Suspension (SAVGS). A nonlinear model of the test rig is identified with the use of a theoretical quarter car model and the rig’s experimental frequency response. A linear equivalent modeling method that compensates the geometric nonlinearity is also adopted to synthesize an H-infinity control scheme. The controller actively adjusts the single-link velocity in the SAVGS to improve the suspension performance. Experiments are performed to evaluate the SAVGS practical feasibility, the performance improvement, the accuracy of the nonlinear model and the controller’s robustness