What if Dark Matter Gamma-Ray Lines come with Gluon Lines?

In dark matter (DM) models, the production of a gamma line (or of a "box-shaped" gamma-ray spectrum) from DM annihilation proceeds in general from a loop diagram involving a heavy charged particle. If the charged particle in the loop carries also a color charge, this leads inevitably to DM annihilation to gluons, with a naturally larger rate. We consider a scenario in which DM candidates annihilate dominantly into gluon pairs, and determine (as far as possible, model-independent) constraints from a variety of observables: a) the dark matter relic density, b) the production of anti-protons, c) DM direct detection and d) gluon-gluon fusion processes at LHC. Among other things, we show that this scenario together with the recent claim for a possible gamma line from the Galactic center in the Fermi-LAT data, leads to a relic abundance of DM that may be naturally close to the cosmological observations.Comment: 6 figures, 10 page

Classification Structures in the Changing Environment of Active Commercial Websites: the Case of eBay.com . In Beeghtol, Clare, Howarth Lynne C., and Williamson, Nancy J. (eds.) Dynamism and Stability in Knowledge Organization.

This paper reports on a portion of a larger ongoing project. We address the issues of information organization and retrieval in large, active commercial websites. More specifically, we address the use of classification for providing access to the contents of such sites. We approach this analysis by describing the functionality and structure of the classification scheme of one such representative, large, active, commercial websites: eBay.com, a web-based auction site for millions of users and items. We compare eBay’s classification scheme with the Art & Architecture thesaurus, which is a tool for describing and providing access to material culture

Physiological responses of Scaevola aemula seedlings under high temperature stress

Global climate change is expected to result in a relative high frequency of a short period of extreme high temperature (HT) on plant ecosystems and can have an adverse impact on plant growth and development, yet the response of plants to such damage is not fully understood. In this study, physiological responses of Scaevola aemula seedlings to a short-term(a 3-day period) HT stress were investigated in order to examine the adaptation of S. aemula to the thermal environment. The S. aemula seedlings were cultivated under four temperature treatments of 25/20, 35/27, 40/30, 46/35 °C (day/night). The HT stress-induced injure symptoms in leaves were recorded and several selected important physiological variables were measured. The results showed that the leave injuries were not apparent under HT (35/27 °C), but serious damages were observed at days two and three post-treatment under severe HT (40/30 and 46/35 °C). For adapting the thermic environments, S. aemula seedlings exhibited a rapid increase of photosynthetic pigments, soluble sugar contents, and superoxide dismutase activity, and simultaneously a decrease of soluble protein contents, proline contents and catalase activity. The HT tolerance of S. aemula species depends upon both the elevated temperature and the period of time under the increased temperature. Our study suggests that S. aemula could grow well under 35/27 °C. The results provide evidence for the introduction and resource assessment of S. aemula species

Impacts of fast food and food retail environment on overweight and obesity in China: a multilevel latent class cluster approach

Objective To simultaneously identify consumer segments based on individual-level consumption and community-level food retail environment data and to investigate whether the segments are associated with BMI and dietary knowledge in China. Design A multilevel latent class cluster model was applied to identify consumer segments based not only on their individual preferences for fast food, salty snack foods, and soft drinks and sugared fruit drinks, but also on the food retail environment at the community level. Setting The data came from the China Health and Nutrition Survey (CHNS) conducted in 2006 and two questionnaires for adults and communities were used. Subjects A total sample of 9788 adults living in 218 communities participated in the CHNS. Results We successfully identified four consumer segments. These four segments were embedded in two types of food retail environment: the saturated food retail environment and the deprived food retail environment. A three-factor solution was found for consumers’ dietary knowledge. The four consumer segments were highly associated with consumers’ dietary knowledge and a number of sociodemographic variables. Conclusions The widespread discussion about the relationships between fast-food consumption and overweight/obesity is irrelevant for Chinese segments that do not have access to fast food. Factors that are most associated with segments with a higher BMI are consumers’ (incorrect) dietary knowledge, the food retail environment and sociodemographics. The results provide valuable insight for policy interventions on reducing overweight/obesity in China. This study also indicates that despite the breathtaking changes in modern China, the impact of ‘obesogenic’ environments should not be assessed too strictly from a ‘Western’ perspective

The DEK oncoprotein is a critical component of the EKLF/KLF1 enhancer in erythroid cells

Understanding how transcriptional regulators are themselves controlled is important in attaining a complete picture of the intracellular effects that follow signaling cascades during early development and cell-restricted differentiation. We have addressed this issue by focusing on the regulation of EKLF/KLF1, a zinc finger transcription factor that plays a necessary role in the global regulation of erythroid gene expression. Using biochemical affinity purification, we have identified the DEK oncoprotein as a critical factor that interacts with an essential upstream enhancer element of the EKLF promoter and exerts a positive effect on EKLF levels. This element also binds a core set of erythroid transcription factors, suggesting that DEK is part of a tissue-restricted enhanceosome that contains BMP4-dependent and -independent components. Together with local enrichment of properly coded histones and an open chromatin domain, optimal transcriptional activation of the EKLF locus can be established

Inferring Disease-Associated MicroRNAs Using Semi-supervised Multi-Label Graph Convolutional Networks

Disease; Gene Network; Biocomputational Method; Computer ModelingMicroRNAs (miRNAs) play crucial roles in biological processes involved in diseases. The associations between diseases and protein-coding genes (PCGs) have been well investigated, and miRNAs interact with PCGs to trigger them to be functional. We present a computational method, DimiG, to infer miRNA-associated diseases using a semi-supervised Graph Convolutional Network model (GCN). DimiG uses a multi-label framework to integrate PCG-PCG interactions, PCG-miRNA interactions, PCG-disease associations, and tissue expression profiles. DimiG is trained on disease-PCG associations and an interaction network using a GCN, which is further used to score associations between diseases and miRNAs. We evaluate DimiG on a benchmark set from verified disease-miRNA associations. Our results demonstrate that DimiG outperforms the best unsupervised method and is comparable to two supervised methods. Three case studies of prostate cancer, lung cancer, and inflammatory bowel disease further demonstrate the efficacy of DimiG, where top miRNAs predicted by DimiG are supported by literature

Temporal update dynamics under blind sampling

Abstract—Network applications commonly maintain local copies of remote data sources in order to provide caching, indexing, and data-mining services to their clients. Modeling performance of these systems and predicting future updates usually requires knowledge of the inter-update distribution at the source, which can only be estimated through blind sampling – periodic downloads and comparison against previous copies. In this paper, we first introduce a stochastic modeling framework for this problem, where the update and sampling processes are both renewal. We then show that all previous approaches are biased unless the observation rate tends to infinity or the update process is Poisson. To overcome these issues, we propose four new algorithms that achieve various levels of consistency, which depend on the amount of temporal information revealed by the source and capabilities of the download process. I

On sample-path staleness in lazy data replication

We analyze synchronization issues arising between two stochastic point processes, one of which models data churn at an information source and the other periodic downloads from its replica (e.g., search engine, web cache, distributed database). Due to lazy (pull-based) synchronization, the replica experiences recurrent staleness, which translates into some form of penalty stemming from its reduced ability to perform consistent compu-tation and/or provide up-to-date responses to customer requests. We model this system under non-Poisson update/refresh processes and obtain sample-path averages of various metrics of staleness cost, generalizing previous results and exposing novel problems in this field

Unraveling the importance of forest structure and composition driving soil microbial and enzymatic responses in the subtropical forest soils

As the responsive soil properties, soil microbial fractions and enzymatic activities are often recommended for assessing soil environment. Different flora, silvicultural practices, and anthropogenic activities regulate essential ecosystem processes. They could substantially affect biological properties, nutrient budgets, and biogeochemical cycles at local and regional scales. This study examined how different forest compositions influenced by various anthropogenic activities (land use change, over-exploitation, species translocation) affect soil microbial properties and enzymatic activities, as well as the effects of soil chemical properties on these patterns in important sub-tropical forest ecosystems in Southern China. The research was conducted at Lutou forest research station, located in Yueyang, Hunan Province, China. Soil samples were collected at 0–10, 10–20, and 20–40 cm depths from natural broadleaved forest (NBF), coniferous monoculture plantations (CPF), and mixed forest stand. CPF stands are directly affected by human interference and frequent harvesting practices, whereas mixed forest and NBF stands are naturally grown forests with minimal human interference. Enzymes continually play a positive role in preserving soil health. The results showed that the interaction effect of forest type and soil depth significantly influenced urease, sucrase, and protease activity (all p < 0.001); however, no clear patterns were observed. Soil microbial carbon (MBC) and soil microbial nitrogen (MBN) were remarkably higher in 0–10 cm in mixed forest and NBF stand compared to CPF stand. For the upper soil layer, soil organic carbon (SOC) was higher in mixed forest, whereas, for the remaining two layers, it was observed to be highest in NBF. Moreover, the microbial quotient (MBC/SOC) was considerably higher in NBF forest in all soil layers than in mixed forest and CPF stand. Soil organic carbon (SOC) and soil total nitrogen (TN) had a strong positive relationship with MBC compared to MBN. Our study contributes toward an enhanced understanding of soil enzymatic responses and microbial soil dynamics’ biological patterns, controls, and activities in different rural forest ecosystems

Relations among neutrino observables in the light of a large theta_13 angle

The recent T2K and MINOS indications for a "large" theta_13 neutrino mixing angle can be accommodated in principle by an infinite number of Yukawa flavour structures in the seesaw model. Without considering any explicit flavour symmetry, there is an instructive exercise one can do: to determine the simplest flavour structures which can account for the data with a minimum number of parameters, simply assuming these parameters to be uncorrelated. This approach points towards a limited number of simple structures which show the minimum complexity a neutrino mass model must generally involve to account for the data. These basic structures essentially lead to only 4 relations between the neutrino observables. We emphasize that 2 of these relations, |sin theta_13|=(tan theta_23/cos delta)*(1-tan theta_12)/(1+tan theta_12) and |sin theta_13| = sin theta_12 R^1/4, with R= Delta m^2_21/Delta m^2_32, have several distinctive properties. First, they hold not only with a minimum number of parameters, but also for complete classes of more general models. Second, any value of theta_13 within the T2K and MINOS ranges can be obtained from these relations by taking into account small perturbations. Third, they turn out to be the pivot relations of models with approximate conservation of lepton number, which allow the seesaw interactions to induce observable flavour violating processes, such as mu -> e gamma and tau -> mu gamma. Finally, in specific cases of this kind, these structures have the rather unique property to allow a full reconstruction of the seesaw Lagrangian from low energy data.Comment: 13 pages, 3 figure