K0−Kˉ0K^0-\bar{K}^0 mixing in the minimal flavor-violating two-Higgs-doublet models

The two-Higgs-doublet model (2HDM), as one of the simplest extensions of the Standard Model (SM), is obtained by adding another scalar doublet to the SM, and is featured by a pair of charged scalars, which could affect many low-energy processes. In the "Higgs basis" for a generic 2HDM, only one scalar doublet gets a nonzero vacuum expectation value and, under the criterion of minimal flavor violation, the other one is fixed to be either color-singlet or color-octet, which are named as the type-III and the type-C 2HDM, respectively. In this paper, we study the charged-scalar effects of these two models on the $K^0-\bar{K}^0$ mixing, an ideal process to probe New Physics (NP) beyond the SM. Firstly, we perform a complete one-loop computation of the box diagrams relevant to the $K^0-\bar{K}^0$ mixing, keeping the mass and momentum of the external strange quark up to the second order. Together with the up-to-date theoretical inputs, we then give a detailed phenomenological analysis, in the cases of both real and complex Yukawa couplings of the charged scalars to quarks. The parameter spaces allowed by the current experimental data on the mass difference $\Delta m_K$ and the CP-violating parameter $\epsilon_K$ are obtained and the differences between these two 2HDMs are investigated, which are helpful to distinguish them from each other from a phenomenological point of view.Comment: 30 pages,10 figures, 2 table

Dynamic structure of stock communities: A comparative study between stock returns and turnover rates

The detection of community structure in stock market is of theoretical and practical significance for the study of financial dynamics and portfolio risk estimation. We here study the community structures in Chinese stock markets from the aspects of both price returns and turnover rates, by using a combination of the PMFG and infomap methods based on a distance matrix. We find that a few of the largest communities are composed of certain specific industry or conceptional sectors and the correlation inside a sector is generally larger than the correlation between different sectors. In comparison with returns, the community structure for turnover rates is more complex and the sector effect is relatively weaker. The financial dynamics is further studied by analyzing the community structures over five sub-periods. Sectors like banks, real estate, health care and New Shanghai take turns to compose a few of the largest communities for both returns and turnover rates in different sub-periods. Several specific sectors appear in the communities with different rank orders for the two time series even in the same sub-period. A comparison between the evolution of prices and turnover rates of stocks from these sectors is conducted to better understand their differences. We find that stock prices only had large changes around some important events while turnover rates surged after each of these events relevant to specific sectors, which may offer a possible explanation for the complexity of stock communities for turnover rates

Exploiting Emotions in Social Interactions to Detect Online Social Communities

The rapid development of Web 2.0 allows people to be involved in online interactions more easily than before and facilitates the formation of virtual communities. Online communities exert influence on their members’ online and offline behaviors. Therefore, they are of increasing interest to researchers and business managers. Most virtual community studies consider subjects in the same Web application belong to one community. This boundary-defining method neglects subtle opinion differences among participants with similar interests. It is necessary to unveil the community structure of online participants to overcome this limitation. Previous community detection studies usually account for the structural factor of social networks to build their models. Based on the affect theory of social exchange, this research argues that emotions involved in social interactions should be considered in the community detection process. We propose a framework to extract social interactions and interaction emotions from user-generated contents and a GN-H co-training algorithm to utilize the two types of information in community detection. We show the benefit of including emotion information in community detection using simulated data. We also conduct a case study on a real-world Web forum dataset to exemplify the utility of the framework in identifying communities to support further analysis

Optimizing production scheduling of steel plate hot rolling for economic load dispatch under time-of-use electricity pricing

Time-of-Use (TOU) electricity pricing provides an opportunity for industrial users to cut electricity costs. Although many methods for Economic Load Dispatch (ELD) under TOU pricing in continuous industrial processing have been proposed, there are still difficulties in batch-type processing since power load units are not directly adjustable and nonlinearly depend on production planning and scheduling. In this paper, for hot rolling, a typical batch-type and energy intensive process in steel industry, a production scheduling optimization model for ELD is proposed under TOU pricing, in which the objective is to minimize electricity costs while considering penalties caused by jumps between adjacent slabs. A NSGA-II based multi-objective production scheduling algorithm is developed to obtain Pareto-optimal solutions, and then TOPSIS based multi-criteria decision-making is performed to recommend an optimal solution to facilitate filed operation. Experimental results and analyses show that the proposed method cuts electricity costs in production, especially in case of allowance for penalty score increase in a certain range. Further analyses show that the proposed method has effect on peak load regulation of power grid.Comment: 13 pages, 6 figures, 4 table

plantsUPS: a database of plants' Ubiquitin Proteasome System

<p>Abstract</p> <p>Background</p> <p>The ubiquitin 26S/proteasome system (UPS), a serial cascade process of protein ubiquitination and degradation, is the last step for most cellular proteins. There are many genes involved in this system, but are not identified in many species. The accumulating availability of genomic sequence data is generating more demands in data management and analysis. Genomics data of plants such as <it>Populus trichocarpa</it>, <it>Medicago truncatula</it>, <it>Glycine max </it>and others are now publicly accessible. It is time to integrate information on classes of genes for complex protein systems such as UPS.</p> <p>Results</p> <p>We developed a database of higher plants' UPS, named 'plantsUPS'. Both automated search and manual curation were performed in identifying candidate genes. Extensive annotations referring to each gene were generated, including basic gene characterization, protein features, GO (gene ontology) assignment, microarray probe set annotation and expression data, as well as cross-links among different organisms. A chromosome distribution map, multi-sequence alignment, and phylogenetic trees for each species or gene family were also created. A user-friendly web interface and regular updates make plantsUPS valuable to researchers in related fields.</p> <p>Conclusion</p> <p>The plantsUPS enables the exploration and comparative analysis of UPS in higher plants. It now archives > 8000 genes from seven plant species distributed in 11 UPS-involved gene families. The plantsUPS is freely available now to all users at <url>http://bioinformatics.cau.edu.cn/plantsUPS</url>.</p