Effect of land use patterns on stability and distributions of organic carbon in the hilly region of Western Sichuan, China

Soil aggregation is important for the resistance of land surfaces to erosion, and it influences the ability of soils to remain productive. At the same time, it is also an important process of carbon sequestration. The objectives of this study were to elucidate the effects of different land use patterns on soil aggregate stability and the distribution of organic carbon in different aggregate fractions in order to prove that the different land use patterns enhance soil aggregate stability. Five kinds of soil samples were collected from the hilly area of western Sichuan under different land use patterns, such as abandoned farmlands, eucalyptus plantations, Chinese fir plantations, tea plantations and loquat orchards. The results demonstrated that the five land use patterns had high proportions of aggregates at the size of >2 mm after dry sieving, and had high proportions of aggregates at the size of < 0.5 mm after wet sieving. The aggregation abilities of the soils were significantly different depending on land use patterns. Waterstable aggregate stability was highest in the Chinese fir plantations, followed by eucalyptus plantations and tea plantations. Water-stable aggregate stability was the lowest in loquat  orchards and abandoned farmlands. Except for coarse particle, soil particle contents of the same size were affected according to the different land use patterns. As the size of aggregates decreased, the organic carbon content of the soil aggregates in tea plantations increased after a decrease, and then reduced again. However, the organic carbon contents of soil aggregates in other land uses increased continuously with the decreasing size of aggregates. Organic carbon content of the soil aggregates was strongly increased in land areas that had been converted from abandoned farmland to Chinese fir plantations, tea plantations and loquat orchards, while it was decreased when abandoned farmland was converted to eucalyptus plantations. The results provided the basis of implementation of returning farmland to forest and the process of carbon sequestration in the study areas.Key words: Soil aggregate, soil aggregate fractions, soil aggregate stability, organic carbon content of the soil aggregates, land uses

Gamma-Ray Burst Afterglows with Energy Injection: Homogeneous Versus Wind External Media

Assuming an adiabatic evolution of a gamma-ray burst (GRB) fireball interacting with an external medium, we calculate the hydrodynamics of the fireball with energy injection from a strongly magnetic millisecond pulsar through magnetic dipole radiation, and obtain the light curve of the optical afterglow from the fireball by synchrotron radiation. Results are given both for a homogeneous external medium and for a wind ejected by GRB progenitor. Our calculations are also available in both ultra-relativistic and non-relativistic phases. Furthermore, the observed R-band light curve of GRB{000301C} can be well fitted in our model, which might provide a probe of the properties of GRB progenitors.Comment: revised version for publication in Chin. Phys. Let

GeV antiproton/gamma-ray excesses and the WW-boson mass anomaly: three faces of ∼60−70\sim 60-70 GeV dark matter particle?

For the newly discovered $W$-boson mass anomaly, one of the simplest dark matter (DM) models that can account for the anomaly without violating other astrophysical/experimental constraints is the inert two Higgs doublet model, in which the DM mass ($m_{S}$) is found to be within $\sim 54-74$ GeV. In this model, the annihilation of DM via $SS\to b\bar{b}$ and $SS\to WW^{*}$ would produce antiprotons and gamma rays, and may account for the excesses identified previously in both particles. Motivated by this, we re-analyze the AMS-02 antiproton and Fermi-LAT Galactic center gamma-ray data. For the antiproton analysis, the novel treatment is the inclusion of the charge-sign-dependent three-dimensional solar modulation model as constrained by the time-dependent proton data. We find that the excess of antiprotons is more distinct than previous results based on the force-field solar modulation model. The interpretation of this excess as the annihilation of $SS\to WW^{*}$ ($SS\to b\bar{b}$) requires a DM mass of $\sim 40-80$ ($40-60$) GeV and a velocity-averaged cross section of $O(10^{-26})~{\rm cm^3~s^{-1}}$. As for the $\gamma$-ray data analysis, rather than adopting the widely-used spatial template fitting, we employ an orthogonal approach with a data-driven spectral template analysis. The fitting to the GeV $\gamma$-ray excess yields DM model parameters overlapped with those to fit the antiproton excess via the $WW^{*}$ channel. The consistency of the DM particle properties required to account for the $W$-boson mass anomaly, the GeV antiproton excess, and the GeV $\gamma$-ray excess suggest a common origin of them.Comment: 8 page

Anchoring Bias in Online Voting

Voting online with explicit ratings could largely reflect people's preferences and objects' qualities, but ratings are always irrational, because they may be affected by many unpredictable factors like mood, weather, as well as other people's votes. By analyzing two real systems, this paper reveals a systematic bias embedding in the individual decision-making processes, namely people tend to give a low rating after a low rating, as well as a high rating following a high rating. This so-called \emph{anchoring bias} is validated via extensive comparisons with null models, and numerically speaking, the extent of bias decays with interval voting number in a logarithmic form. Our findings could be applied in the design of recommender systems and considered as important complementary materials to previous knowledge about anchoring effects on financial trades, performance judgements, auctions, and so on.Comment: 5 pages, 4 tables, 5 figure

Performance investigation of hybrid excited switched flux permanent magnet machines using frozen permeability method

This study investigates the electromagnetic performance of a hybrid excited switched flux permanent magnet (SFPM) machine using the frozen permeability (FP) method. The flux components due to PMs, field excitation windings and armature windings have been separated using the FP method. It has been used to separate the torque components due to the PMs and excitations, providing a powerful insight into the torque generation mechanism of hybrid excited SFPM machines. It also allows the accurate calculation of d- and q-axis inductances, which will then be used to calculate the torque, power and power factor against rotor speed to compare the relative merits of hybrid excited SFPM machines with different types of PMs (i.e. NdFeB, SmCo and Ferrite). This offers the possibility of choosing appropriate PMs for different applications (maximum torque or maximum speed). Although only one type of hybrid excited PM machine has been employed to carry out the investigations, the method used in this study can also be extended to other hybrid excited PM machines. The predicted results have been validated by tests

RKappa: Statistical sampling suite for Kappa models

We present RKappa, a framework for the development and analysis of rule-based models within a mature, statistically empowered R environment. The infrastructure allows model editing, modification, parameter sampling, simulation, statistical analysis and visualisation without leaving the R environment. We demonstrate its effectiveness through its application to Global Sensitivity Analysis, exploring it in "parallel" and "concurrent" implementations. The pipeline was designed for high performance computing platforms and aims to facilitate analysis of the behaviour of large-scale systems with limited knowledge of exact mechanisms and respectively sparse availability of parameter values, and is illustrated here with two biological examples. The package is available on github: https://github.com/lptolik/R4KappaComment: Hybrid Systems and Biology 2014, Vienn

Tag-Aware Recommender Systems: A State-of-the-art Survey

In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related works and future challenges of tag-aware recommendation algorithms.Comment: 19 pages, 3 figure

Emergence of scale-free leadership structure in social recommender systems

The study of the organization of social networks is important for understanding of opinion formation, rumor spreading, and the emergence of trends and fashion. This paper reports empirical analysis of networks extracted from four leading sites with social functionality (Delicious, Flickr, Twitter and YouTube) and shows that they all display a scale-free leadership structure. To reproduce this feature, we propose an adaptive network model driven by social recommending. Artificial agent-based simulations of this model highlight a "good get richer" mechanism where users with broad interests and good judgments are likely to become popular leaders for the others. Simulations also indicate that the studied social recommendation mechanism can gradually improve the user experience by adapting to tastes of its users. Finally we outline implications for real online resource-sharing systems

Pairing symmetry and properties of iron-based high temperature superconductors

Pairing symmetry is important to indentify the pairing mechanism. The analysis becomes particularly timely and important for the newly discovered iron-based multi-orbital superconductors. From group theory point of view we classified all pairing matrices (in the orbital space) that carry irreducible representations of the system. The quasiparticle gap falls into three categories: full, nodal and gapless. The nodal-gap states show conventional Volovik effect even for on-site pairing. The gapless states are odd in orbital space, have a negative superfluid density and are therefore unstable. In connection to experiments we proposed possible pairing states and implications for the pairing mechanism.Comment: 4 pages, 1 table, 2 figures, polished versio