2,583 research outputs found
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
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
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 -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 -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 decays into light hadrons using the principle of maximum conformality
In the paper, we analyze the 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 -order level has been included in the discussion, which gives about
contribution to the ratio . 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 -terms,
we transform the usual pQCD series into the one under the
minimal momentum space subtraction scheme. To compare with the prediction under
conventional scale setting, , after applying the PMC, we obtain
, where the
errors are squared averages of the ones caused by and . The PMC prediction agrees with the recent PDG value within errors, i.e.
. 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
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