Combinatorial proofs of some properties of tangent and Genocchi numbers

The tangent number $T_{2n+1}$ is equal to the number of increasing labelled complete binary trees with $2n+1$ vertices. This combinatorial interpretation immediately proves that $T_{2n+1}$ is divisible by $2^n$. However, a stronger divisibility property is known in the studies of Bernoulli and Genocchi numbers, namely, the divisibility of $(n+1)T_{2n+1}$ by $2^{2n}$. The traditional proofs of this fact need significant calculations. In the present paper, we provide a combinatorial proof of the latter divisibility by using the hook length formula for trees. Furthermore, our method is extended to $k$-ary trees, leading to a new generalization of the Genocchi numbers

Correcting for the solar wind in pulsar timing observations: the role of simultaneous a nd l ow-frequency observations

The primary goal of the pulsar timing array projects is to detect ultra-low-frequency gravitational waves. The pulsar data sets are affected by numerous noise processes including varying dispersive delays in the interstellar medium and from the solar wind. The solar wind can lead to rapidly changing variations that, with existing telescopes, can be hard to measure and then remove. In this paper we study the possibility of using a low frequency telescope to aid in such correction for the Parkes Pulsar Timing Array (PPTA) and also discuss whether the ultra-wide-bandwidth receiver for the FAST telescope is sufficient to model the solar wind variations. Our key result is that a single wide-bandwidth receiver can be used to model and remove the effect of the solar wind. However, for pulsars that pass close to the Sun such as PSR J1022+1022, the solar wind is so variable that observations at two telescopes separated by a day are insufficient to correct the solar wind effect.Comment: accepted by RA

Cross-Domain Labeled LDA for Cross-Domain Text Classification

Cross-domain text classification aims at building a classifier for a target domain which leverages data from both source and target domain. One promising idea is to minimize the feature distribution differences of the two domains. Most existing studies explicitly minimize such differences by an exact alignment mechanism (aligning features by one-to-one feature alignment, projection matrix etc.). Such exact alignment, however, will restrict models' learning ability and will further impair models' performance on classification tasks when the semantic distributions of different domains are very different. To address this problem, we propose a novel group alignment which aligns the semantics at group level. In addition, to help the model learn better semantic groups and semantics within these groups, we also propose a partial supervision for model's learning in source domain. To this end, we embed the group alignment and a partial supervision into a cross-domain topic model, and propose a Cross-Domain Labeled LDA (CDL-LDA). On the standard 20Newsgroup and Reuters dataset, extensive quantitative (classification, perplexity etc.) and qualitative (topic detection) experiments are conducted to show the effectiveness of the proposed group alignment and partial supervision.Comment: ICDM 201

Evaluation on Integrated Innovation Capability of Regions Based on Principal Component Analysis

The main carriers of national innovation capacity are the regions which gather the technology, economy, and culture, and the strength of regional innovation capacity indicates the strength of the national innovation capability, so the key to the improvement of the national innovation capacity is to enhance the innovation capacity of every region. Using statistics and statistical software SPSS V17.0 Statistics for principal component analysis, and to analyze and sort the innovation capability for our country’s 15 provinces and municipalities, evaluate the results and put forward policy recommendations related, to provide better ideas for economic development of every region.Key words: comprehensive evaluation; innovation capability of regions; integrated innovation capability; principal component analysis The title, abstract and keywords are being translated into French at present and the French version will be added into the paper later

Developing a Soil Column System to Measure Hydrogeophysical Properties of Unconsolidated Sediment

Geophysical methods have been increasingly used to characterize the Earth\u27s critical zone (CZ) and monitor hydrological processes occurring within it. For a quantitative interpretation, geophysical studies of CZ materials are necessary, and thus require more sophisticated laboratory setups. In this study, we develop a hydrogeophysical soil column system to measure key hydraulic and electrical properties of regolith in CZs. The developed soil column system consists of two components: (a) a novel hydrogeophysical probe that measures pore water pressure and electrical potential in soils and (b) a cylindrical cell to hold soil samples. The system can be arranged to perform both saturated flow and drainage tests. The saturated flow test is similar to the traditional constant head experiment for determining the hydraulic conductivity and streaming potential coupling coefficient. The drainage tests can produce transient responses of cumulative overflow, pore water pressure, and streaming potential. These transient data can be used to estimate the sample\u27s electrical and hydraulic properties with the coupled, stochastic hydrogeophysical inversion. A sand sample is used to demonstrate the procedures of applying this new system. The measured saturated hydraulic conductivity and streaming potential coupling coefficient of the sand are within the typical ranges of sands reported in the literature. The inversion-estimated soil parameters can well reproduce the measured transient responses during the drainage test of the sample. Moreover, the inversion-estimated saturated properties are in good agreement with those independently measured in the saturated flow test, showing the robustness of the developed system

Research on the Construction of New Energy Automotive Industry Innovation System based on Low-carbon Economy

Abstract: The development of new energy automotive industry meets new opportunity and challenge with the emergence of low-carbon economy. The low-carbon economy not only has provided the development direction for the new energy automotive industry ， but may also changed the fundamental nature of it simultaneously. What is more, it even can evoke deep-seated revolution of the automotive industry. The article has elaborated the elements, structure model and operation mechanism of the new energy automotive industry based on the low-carbon economy development pattern. Indeed, it provided a brand-new thought for our new energy automotive industry development. Key words: Low-carbon economy; New energy automotive; Industrial innovation syste

Noise Folding in Completely Perturbed Compressed Sensing

This paper first presents a new generally perturbed compressed sensing (CS) model y=(A+E)(x+u)+e, which incorporated a general nonzero perturbation E into sensing matrix A and a noise u into signal x simultaneously based on the standard CS model y=Ax+e and is called noise folding in completely perturbed CS model. Our construction mainly will whiten the new proposed CS model and explore in restricted isometry property (RIP) and coherence of the new CS model under some conditions. Finally, we use OMP to give a numerical simulation which shows that our model is feasible although the recovered value of signal is not exact compared with original signal because of measurement noise e, signal noise u, and perturbation E involved

Study on the Conceptual Model of E-Government standards Adoption Based on Institutional Theory

The purpose of this study is to investigate the forces that promote national e-government standards adoption and diffusion by government agencies. By using institutional theory as a theoretical basis, a conceptual model is set up and the hypotheses are proposed. Three forces of improving national e-government standards adoption are discussed. They are coercive forces, mimetic forces and normative forces. The survey questionnaire has been developed which will be used to test the theoretical model. All the data will be expectedly collected by the end of May, 2013 and then the structural equation model will be analyzed with PLS. From a theoretical perspective, the research model may be informative for researchers investigating the adoption of other technological standards. From the practical perspective, the research results may give some advice to government officials to promote the diffusion national e-government standards

Coupled Inversion of Hydraulic and Self-Potential Data from Transient Outflow Experiments to Estimate Soil Petrophysical Properties

Hydraulicproperties of soils could play an important role in affecting the partitioning of precipitation in the critical zone. In addition to traditional approaches, in the last two decades, many geophysical methods have been used to aid the hydrologic characterization and measurement of geological materials. In particular, the self-potential (SP) method shows great potential in these hydrogeophysical applications. The objective of this study is to evaluate whether the addition of SP data can improve the estimation of hydraulic properties of soils in an outflow experiment. A stochastic, coupled hydrogeophysical inversion was developed, in which the governing equations were solved using the finite volume method and the parameter estimation was conducted using a Bayesian approach associated with the Markov chain Monte Carlo technique. The results show that the addition of SP data in the inversion could reduce the uncertainty related to the estimated hydraulic parameters of soils and the length of the associated 95% confidence interval can be shortened by ∼1/3. It is also shown that the electrical properties of soils at saturated and unsaturated conditions may also be estimated from the outflow experiment when SP data are available. Compared with hydraulic parameters, the accuracy of the estimated electrical properties is slightly lower. Among them, the saturated streaming potential coupling coefficient Csat has the highest accuracy and lowest uncertainty since Csat directly influences the magnitude of SP signals. The accuracy of other electrical parameters is lower than that of Csat (and hydraulic parameters), and the associated uncertainty can be one order of magnitude larger