TEQUILA: Temporal Question Answering over Knowledge Bases

Question answering over knowledge bases (KB-QA) poses challenges in handling complex questions that need to be decomposed into sub-questions. An important case, addressed here, is that of temporal questions, where cues for temporal relations need to be discovered and handled. We present TEQUILA, an enabler method for temporal QA that can run on top of any KB-QA engine. TEQUILA has four stages. It detects if a question has temporal intent. It decomposes and rewrites the question into non-temporal sub-questions and temporal constraints. Answers to sub-questions are then retrieved from the underlying KB-QA engine. Finally, TEQUILA uses constraint reasoning on temporal intervals to compute final answers to the full question. Comparisons against state-of-the-art baselines show the viability of our method

U(1)-decoupling, KK and BCJ relations in N=4\mathcal{N}=4 SYM

We proved the color reflection relation, U(1)-decoupling, Kleiss-Kuijf and Bern-Carrasco-Johansson relation for color-ordered $\mathcal{N}=4$ Super Yang-Mills theory using $\mathcal{N}=4$ SYM version BCFW recursion relation, which depends only on the general properties of super-amplitudes. This verified the conjectured matter fields BCJ relation. We also show that color reflection relation and U(1)-decoupling relation are special cases of KK relation, if we consider the KK relation as a general relation, then the former two relations come out naturally as the special cases.Comment: 17 page

Deprojection technique for galaxy cluster considering point spread function

We present a new method for the analysis of Abell 1835 observed by XMM-Newton. The method is a combination of the Direct Demodulation technique and deprojection. We eliminate the effects of the point spread function (PSF) with the Direct Demodulation technique. We then use a traditional depro-jection technique to study the properties of Abell 1835. Compared to that of deprojection method only, the central electron density derived from this method increases by 30%, while the temperature profile is similar.Comment: accepted for publication in Sciences in China -- G, the Black Hole special issu

Low-Temperature Rapid Synthesis and Superconductivity of Fe-Based Oxypnictide Superconductors

we were able to develop a novel method to synthesize Fe-based oxypnictide superconductors. By using LnAs and FeO as the starting materials and a ball-milling process prior to solid-state sintering, Tc as high as 50.7 K was obtained with the sample of Sm 0.85Nd0.15FeAsO0.85F0.15 prepared by sintering at temperatures as low as 1173 K for times as short as 20 min.Comment: 2 pages,2 figures, 1 tabl

Relaxed 2-D Principal Component Analysis by LpL_p Norm for Face Recognition

A relaxed two dimensional principal component analysis (R2DPCA) approach is proposed for face recognition. Different to the 2DPCA, 2DPCA-$L_1$ and G2DPCA, the R2DPCA utilizes the label information (if known) of training samples to calculate a relaxation vector and presents a weight to each subset of training data. A new relaxed scatter matrix is defined and the computed projection axes are able to increase the accuracy of face recognition. The optimal $L_p$-norms are selected in a reasonable range. Numerical experiments on practical face databased indicate that the R2DPCA has high generalization ability and can achieve a higher recognition rate than state-of-the-art methods.Comment: 19 pages, 11 figure

Coulomb Screening of 2D Massive Dirac Fermions

A model of 2D massive Dirac fermions, interacting with a instantaneous $1/r$ Coulomb interaction, is presented to mimic the physics of gapped graphene. The static polarization function is calculated explicitly to analyze screening effect at the finite temperature and density. Results are compared with the massless case . We also show that various other works can be reproduced within our model in a straightforward and unified manner

Gunrock: A High-Performance Graph Processing Library on the GPU

For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and the complexity of programming GPUs have been two significant challenges for developing a programmable high-performance graph library. "Gunrock", our graph-processing system designed specifically for the GPU, uses a high-level, bulk-synchronous, data-centric abstraction focused on operations on a vertex or edge frontier. Gunrock achieves a balance between performance and expressiveness by coupling high performance GPU computing primitives and optimization strategies with a high-level programming model that allows programmers to quickly develop new graph primitives with small code size and minimal GPU programming knowledge. We evaluate Gunrock on five key graph primitives and show that Gunrock has on average at least an order of magnitude speedup over Boost and PowerGraph, comparable performance to the fastest GPU hardwired primitives, and better performance than any other GPU high-level graph library.Comment: 14 pages, accepted by PPoPP'16 (removed the text repetition in the previous version v5