On Cotorsion pairs of chain complexes

In the paper we first construct a new cotorsion pair, in the category of chain complexes, from two given cotorsion pairs in the category of modules, and then we consider completeness of such pairs under certain conditions.Comment: 11 pages. arXiv admin note: text overlap with arXiv:1210.0196 by other author

Amplitude Relations in Non-linear Sigma Model

In this paper, we investigate tree-level scattering amplitude relations in $U(N)$ non-linear sigma model. We use Cayley parametrization. As was shown in the recent works [23,24] both on-shell amplitudes and off-shell currents with odd points have to vanish under Cayley parametrization. We prove the off-shell $U(1)$ identity and fundamental BCJ relation for even-point currents. By taking the on-shell limits of the off-shell relations, we show that the color-ordered tree amplitudes with even points satisfy $U(1)$-decoupling identity and fundamental BCJ relation, which have the same formations within Yang-Mills theory. We further state that all the on-shell general KK, BCJ relations as well as the minimal-basis expansion are also satisfied by color-ordered tree amplitudes. As a consequence of the relations among color-ordered amplitudes, the total $2m$-point tree amplitudes satisfy DDM form of color decomposition as well as KLT relation.Comment: 27 pages, 8 figures, 4 tables, JHEP style, improved versio

MetaLDA: a Topic Model that Efficiently Incorporates Meta information

Besides the text content, documents and their associated words usually come with rich sets of meta informa- tion, such as categories of documents and semantic/syntactic features of words, like those encoded in word embeddings. Incorporating such meta information directly into the generative process of topic models can improve modelling accuracy and topic quality, especially in the case where the word-occurrence information in the training data is insufficient. In this paper, we present a topic model, called MetaLDA, which is able to leverage either document or word meta information, or both of them jointly. With two data argumentation techniques, we can derive an efficient Gibbs sampling algorithm, which benefits from the fully local conjugacy of the model. Moreover, the algorithm is favoured by the sparsity of the meta information. Extensive experiments on several real world datasets demonstrate that our model achieves comparable or improved performance in terms of both perplexity and topic quality, particularly in handling sparse texts. In addition, compared with other models using meta information, our model runs significantly faster.Comment: To appear in ICDM 201

Dynamic simulation of steam generation system in solar tower power plant

Concentrated solar power (CSP) plant with thermal energy storage can be operated as a peak load regulation plant. The steam generation system (SGS) is the central hub between the heat transfer fluid and the working fluid, of which the dynamic characteristics need to be further investigated. The SGS of Solar Two power tower plant was selected as the object. The mathematical model with lumped parameter method was developed and verified to analyze its dynamic characteristics. Five simulation tests were carried out under the disturbances that the solar tower power plant may encounter under various solar irradiations and output electrical loads. Both dynamic and static characteristics of SGS were analyzed with the response curves of the system state parameters. The dynamic response and time constants of the working fluids out of SGS was obtained when the step disturbances are imposed. It was indicated that the disturbances imposed to both working fluids lead to heat load reassignment to the preheater, evaporator and superheater. The proposed step-by-step disturbance method could reduce the fluid temperature and pressure fluctuations by 1.5 °C and 0.03 MPa, respectively. The results could be references for control strategies as well as the safe operation of and SGS.Peer reviewe

A Sarcoplasmic Reticulum Localized Protein Phosphatase Regulates Phospholamban Phosphorylation and Promotes Ischemia Reperfusion Injury in the Heart.

Phospholamban (PLN) is a key regulator of sarcolemma calcium uptake in cardiomyocyte, its inhibitory activity to SERCA is regulated by phosphorylation. PLN hypophosphorylation is a common molecular feature in failing heart. The current study provided evidence at molecular, cellular and whole heart levels to implicate a sarcolemma membrane targeted protein phosphatase, PP2Ce, as a specific and potent PLN phosphatase. PP2Ce expression was elevated in failing human heart and induced acutely at protein level by β -adrenergic stimulation or oxidative stress in cardiomyocytes. PP2Ce expression in mouse heart blunted β-adrenergic response and exacerbated ischemia/reperfusion injury. Therefore, PP2Ce is a new regulator for cardiac function and pathogenesis

Reconsideration of the QCD corrections to the ηc\eta_c decays into light hadrons using the principle of maximum conformality

In the paper, we analyze the $\eta_c$ decays into light hadrons at the next-to-leading order QCD corrections by applying the principle of maximum conformality (PMC). The relativistic correction at the ${\cal{O}}(\alpha_s v^2)$-order level has been included in the discussion, which gives about $10\%$ contribution to the ratio $R$. The PMC, which satisfies the renormalization group invariance, is designed to obtain a scale-fixed and scheme-independent prediction at any fixed order. To avoid the confusion of treating $n_f$-terms, we transform the usual $\overline{\rm MS}$ pQCD series into the one under the minimal momentum space subtraction scheme. To compare with the prediction under conventional scale setting, $R_{\rm{Conv,mMOM}-r}= \left(4.12^{+0.30}_{-0.28}\right)\times10^3$, after applying the PMC, we obtain $R_{\rm PMC,mMOM-r}=\left(6.09^{+0.62}_{-0.55}\right) \times10^3$, where the errors are squared averages of the ones caused by $m_c$ and $\Lambda_{\rm mMOM}$. The PMC prediction agrees with the recent PDG value within errors, i.e. $R^{\rm exp}=\left(6.3\pm0.5\right)\times10^3$. Thus we think the mismatching of the prediction under conventional scale-setting with the data is due to improper choice of scale, which however can be solved by using the PMC.Comment: 5 pages, 2 figure

Identifying vital edges in Chinese air route network via memetic algorithm

Due to its rapid development in the past decade, air transportation system has attracted considerable research attention from diverse communities. While most of the previous studies focused on airline networks, here we systematically explore the robustness of the Chinese air route network, and identify the vital edges which form the backbone of Chinese air transportation system. Specifically, we employ a memetic algorithm to minimize the network robustness after removing certain edges hence the solution of this model is the set of vital edges. Counterintuitively, our results show that the most vital edges are not necessarily the edges of highest topological importance, for which we provide an extensive explanation from the microscope of view. Our findings also offer new insights to understanding and optimizing other real-world network systems