Nodeless superconductivity in Ca3Ir4Sn13: evidence from quasiparticle heat transport

We report resistivity $\rho$ and thermal conductivity $\kappa$ measurements on Ca$_3$Ir$_4$Sn$_{13}$ single crystals, in which superconductivity with $T_c \approx 7$ K was claimed to coexist with ferromagnetic spin-fluctuations. Among three crystals, only one crystal shows a small hump in resistivity near 20 K, which was previously attributed to the ferromagnetic spin-fluctuations. Other two crystals show the $\rho \sim T^2$ Fermi-liquid behavior at low temperature. For both single crystals with and without the resistivity anomaly, the residual linear term $\kappa_0/T$ is negligible in zero magnetic field. In low fields, $\kappa_0(H)/T$ shows a slow field dependence. These results demonstrate that the superconducting gap of Ca$_3$Ir$_4$Sn$_{13}$ is nodeless, thus rule out nodal gap caused by ferromagnetic spin-fluctuations.Comment: 5 pages, 4 figure

Possible DDˉD\bar{D} and BBˉB\bar{B} Molecular states in a chiral quark model

We perform a systematic study of the bound state problem of $D\bar{D}$ and $B\bar{B}$ systems by using effective interaction in our chiral quark model. Our results show that both the interactions of $D\bar{D}$ and $B\bar{B}$ states are attractive, which consequently result in $I^G(J^{PC})=0^+(0^{++})$ $D\bar{D}$ and $B\bar{B}$ bound states.Comment: arXiv admin note: substantial text overlap with arXiv:1204.395

Differential Effect of Anaerobic Digestion on Gaseous Products from Sequential Pyrolysis of Three Organic Solid Wastes

Studies have shown that anaerobic digestion (AD) has an effect on the liquid and solid product property of sequential pyrolysis, but its influence on the gaseous products is lacking. In this study, syngas produced by pyrolysis from three raw organic solid wastes and the corresponding digestates, i.e., food waste, vinasse, and cow manure were investigated. AD causes a decrease in the contents of volatile solid, fixed carbon, C, H, and N and an increase in the S content. The weight loss of the wastes mainly occurs at 200–550 °C during the pyrolysis and the loss of the food waste and vinasse is higher than that of cow manure. In the carbon (C)-containing gas, AD leads to a decrease in the CH4 content of the syngas, implying that the heat values of the digestates are lower than that of the raw substrates. After AD, the total amount of nitrogen (N)-containing gas from the vinasse increases by 40.1%, while that from cow manure decreases by 14.1%. On the contrary, the total amount of sulfur (S)-containing groups in the syngas from vinasse drop by 22.0%, while that from cow manure increases by 9.1%. In addition, slight changes in the C-, N-, and S-containing gases are found from food waste. The results indicate that AD has a different effect on the N- and S- containing gaseous groups from different organic solid wastes, and the mechanisms deserve further investigation. The findings supply a theoretical foundation for environmental-friendly application of syngas from the digestates

On the discovery of continuous truth: a semi-supervised approach with partial ground truths

In many applications, the information regarding to the same object can be collected from multiple sources. However, these multi-source data are not reported consistently. In the light of this challenge, truth discovery is emerged to identify truth for each object from multi-source data. Most existing truth discovery methods assume that ground truths are completely unknown, and they focus on the exploration of unsupervised approaches to jointly estimate object truths and source reliabilities. However, in many real world applications, a set of ground truths could be partially available. In this paper, we propose a semi-supervised truth discovery framework to estimate continuous object truths. With the help of ground truths, even a small amount, the accuracy of truth discovery can be improved. We formulate the semi-supervised truth discovery problem as an optimization task where object truths and source reliabilities are modeled as variables. The ground truths are modeled as a regularization term and its contribution to the source weight estimation can be controlled by a parameter. The experiments show that the proposed method is more accurate and efficient than the existing truth discovery methods