Subtraction method for NLO corrections in Monte-Carlo event generators for Z boson production

We use a subtraction method to construct NLO corrections in a Monte-Carlo event generator for the case of vector boson production in Drell-Yan processes. Our calculations are carried out both for the Bengtsson-Sjostrand-van Zijl (BSZ) algorithm and for a modified algorithm proposed by Collins. In the case of the modified algorithm, we compute the relation between the parton distribution functions and the ones in the MSbar scheme; this relation is the same as the corresponding relation for DIS. For the BSZ algorithm, we show that there is no simple relation.Comment: 16 pages, 4 figures, JHEP class. Misprints correcte

Semantics-Space-Time Cube. A Conceptual Framework for Systematic Analysis of Texts in Space and Time

We propose an approach to analyzing data in which texts are associated with spatial and temporal references with the aim to understand how the text semantics vary over space and time. To represent the semantics, we apply probabilistic topic modeling. After extracting a set of topics and representing the texts by vectors of topic weights, we aggregate the data into a data cube with the dimensions corresponding to the set of topics, the set of spatial locations (e.g., regions), and the time divided into suitable intervals according to the scale of the planned analysis. Each cube cell corresponds to a combination (topic, location, time interval) and contains aggregate measures characterizing the subset of the texts concerning this topic and having the spatial and temporal references within these location and interval. Based on this structure, we systematically describe the space of analysis tasks on exploring the interrelationships among the three heterogeneous information facets, semantics, space, and time. We introduce the operations of projecting and slicing the cube, which are used to decompose complex tasks into simpler subtasks. We then present a design of a visual analytics system intended to support these subtasks. To reduce the complexity of the user interface, we apply the principles of structural, visual, and operational uniformity while respecting the specific properties of each facet. The aggregated data are represented in three parallel views corresponding to the three facets and providing different complementary perspectives on the data. The views have similar look-and-feel to the extent allowed by the facet specifics. Uniform interactive operations applicable to any view support establishing links between the facets. The uniformity principle is also applied in supporting the projecting and slicing operations on the data cube. We evaluate the feasibility and utility of the approach by applying it in two analysis scenarios using geolocated social media data for studying people's reactions to social and natural events of different spatial and temporal scales

Frontiers of parasitology research in the People's Republic of China : infection, diagnosis, protection and surveillance

ABSTRACT: Control and eventual elimination of human parasitic diseases in the People's Republic of China (P.R. China) requires novel approaches, particularly in the areas of diagnostics, mathematical modelling, monitoring, evaluation, surveillance and public health response. A comprehensive effort, involving the collaboration of 188 scientists (<85% from P.R. China) from 48 different institutions and universities (80% from P.R. China), covers this collection of 29 articles published in Parasites & Vectors. The research mainly stems from a research project entitled 'Surveillance and diagnostic tools for major parasitic diseases in P.R. China' (grant no. 2008ZX10004-011) and highlights the frontiers of research in parasitology. The majority of articles in this thematic series deals with the most important parasitic diseases in P.R. China, emphasizing Schistosoma japonicum, Plasmodium vivax and Clonorchis sinensis plus some parasites of emerging importance such as Angiostrongylus cantonensis. Significant achievements have been made through the collaborative research programme in the following three fields: (i) development of control strategies for the national control programme; (ii) updating the surveillance data of parasitic infections both in human and animals; and (iii) improvement of existing, and development of novel, diagnostic tools to detect parasitic infections. The progress is considerable and warrants broad validation efforts. Combined with the development of improved tools for diagnosis and surveillance, integrated and multi-pronged control strategies now pave the way for elimination of parasitic diseases in P.R. China. Experiences and lessons learned can stimulate control and elimination efforts of parasitic diseases in other parts of the world

Isolated cold plasma regions: Observations and their relation to possible production mechanisms

Regions of enhanced cold plasma, isolated from the main plasmasphere along the Explorer 45 orbit on the equatorial plane, are reported using the sheath induced potentials seen by the electric field experiment. The occurrence of these regions has a strong correlation with negative enhancements of Dst, and their locations are primarily in the noon-dusk quadrant. The data support the concept that changes in large scale convection play a dominant role in the formation of these regions. Plasmatails that are predicted from enhancements of large scale convection electric fields in general define where these regions may be found. More localized processes are necessary to account for the exact configuration and structure seen in these regions and may eventually result in detachment from the main plasmasphere

Reynolds stress models of homogeneous turbulence

Existing and new models for the rapid and the return terms in the Reynolds stress equations were tested in two ways. One, by direct comparison of the model with simulation data. The other, by simulating the flows using the models and comparing the predicted Reynolds stresses with the data. It was found that existing linear models can be improved and that nonlinear models are in better agreement with the simulation data for a wide variety of flows

Scalable Methods for Adaptively Seeding a Social Network

In recent years, social networking platforms have developed into extraordinary channels for spreading and consuming information. Along with the rise of such infrastructure, there is continuous progress on techniques for spreading information effectively through influential users. In many applications, one is restricted to select influencers from a set of users who engaged with the topic being promoted, and due to the structure of social networks, these users often rank low in terms of their influence potential. An alternative approach one can consider is an adaptive method which selects users in a manner which targets their influential neighbors. The advantage of such an approach is that it leverages the friendship paradox in social networks: while users are often not influential, they often know someone who is. Despite the various complexities in such optimization problems, we show that scalable adaptive seeding is achievable. In particular, we develop algorithms for linear influence models with provable approximation guarantees that can be gracefully parallelized. To show the effectiveness of our methods we collected data from various verticals social network users follow. For each vertical, we collected data on the users who responded to a certain post as well as their neighbors, and applied our methods on this data. Our experiments show that adaptive seeding is scalable, and importantly, that it obtains dramatic improvements over standard approaches of information dissemination.Comment: Full version of the paper appearing in WWW 201