Originator or propagator? Incorporating social role theory into topic models for twitter content analysis

A large number of studies have been devoted to modeling the contents and interactions between users on Twitter. In this paper, we propose a method inspired from Social Role Theory (SRT), which assumes that a user behaves differently in different roles in the generation process of Twitter content. We consider the two most distinctive social roles on Twitter: originator and propagator, who respectively posts original messages and retweets or forwards the messages from others. In addition, we also consider role-specific social interactions, especially implicit interactions between users who share some common interests. All the above elements are integrated into a novel regularized topic model. We evaluate the proposed method on real Twitter data. The results show that our method is more effective than the existing ones which do not distinguish social roles. Copyright 2013 ACM.

Density forecasts of crude-oil prices using option-implied and ARCH-type models

The predictive accuracy of competing crude-oil price forecast densities is investigated for the 1994–2006 period. Moving beyond standard ARCH type models that rely exclusively on past returns, we examine the benefits of utilizing the forward-looking information that is embedded in the prices of derivative contracts. Risk-neutral densities, obtained from panels of crude-oil option prices, are adjusted to reflect real-world risks using either a parametric or a non-parametric calibration approach. The relative performance of the models is evaluated for the entire support of the density, as well as for regions and intervals that are of special interest for the economic agent. We find that non-parametric adjustments of risk-neutral density forecasts perform significantly better than their parametric counterparts. Goodness-of-fit tests and out-of-sample likelihood comparisons favor forecast densities obtained by option prices and non-parametric calibration methods over those constructed using historical returns and simulated ARCH processes. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:727–754, 2011

Metastable de-excitation spectroscopy and density functional theory study of the selective oxidation of crotyl alcohol over Pd(111)

The extremely surface sensitive technique of metastable de-excitation spectroscopy (MDS) has been utilized to probe the bonding and reactivity of crotyl alcohol over Pd(111) and provide insight into the selective oxidation pathway to crotonaldehyde. Auger de-excitation (AD) of metastable He (23S) atoms reveals distinct features associated with the molecular orbitals of the adsorbed alcohol, corresponding to emission from the hydrocarbon skeleton, the O n nonbonding, and C═C π states. The O n and C═C π states of the alcohol are reversed when compared to those of the aldehyde. Density functional theory (DFT) calculations of the alcohol show that an adsorption mode with both C═C and O bonds aligned somewhat parallel to the surface is energetically favored at a substrate temperature below 200 K. Density of states calculations for such configurations are in excellent agreement with experimental MDS measurements. MDS revealed oxidative dehydrogenation of crotyl alcohol to crotonaldehyde between 200 and 250 K, resulting in small peak shifts to higher binding energy. Intramolecular changes lead to the opposite assignment of the first two MOs in the alcohol versus the aldehyde, in accordance with DFT and UPS studies of the free molecules. Subsequent crotonaldehyde decarbonylation and associated propylidyne formation above 260 K could also be identified by MDS and complementary theoretical calculations as the origin of deactivation and selectivity loss. Combining MDS and DFT in this way represents a novel approach to elucidating surface catalyzed reaction pathways associated with a “real-world” practical chemical transformation, namely the selective oxidation of alcohols to aldehydes.

24-Karat or fool’s gold? Consequences of real team and co-acting group membership in healthcare organizations

Although theory on team membership is emerging, limited empirical attention has been paid to the effects of different types of team membership on outcomes. We propose that an important but overlooked distinction is that between membership of real teams and membership of co-acting groups, with the former being characterized by members who report that their teams have shared objectives, and structural interdependence and engage in team reflexivity. We hypothesize that real team membership will be associated with more positive individual- and organizational-level outcomes. These predictions were tested in the English National Health Service, using data from 62,733 respondents from 147 acute hospitals. The results revealed that individuals reporting the characteristics of real team membership, in comparison with those reporting the characteristics of co-acting group membership, witnessed fewer errors and incidents, experienced fewer work related injuries and illness, were less likely to be victims of violence and harassment, and were less likely to intend to leave their current employment. At the organizational level, hospitals with higher proportions of staff reporting the characteristics of real team membership had lower levels of patient mortality and sickness absence. The results suggest the need to clearly delineate real team membership in order to advance scientific understanding of the processes and outcomes of organizational teamwork.

Credibility theory-based available transfer capability assessment

Since the development of large scale power grid interconnections and power markets, research on available transfer capability (ATC) has attracted great attention. The challenges for accurate assessment of ATC originate from the numerous uncertainties in electricity generation, transmission, distribution and utilization sectors. Power system uncertainties can be mainly described as two types: randomness and fuzziness. However, the traditional transmission reliability margin (TRM) approach only considers randomness. Based on credibility theory, this paper firstly built models of generators, transmission lines and loads according to their features of both randomness and fuzziness. Then a random fuzzy simulation is applied, along with a novel method proposed for ATC assessment, in which both randomness and fuzziness are considered. The bootstrap method and multi-core parallel computing technique are introduced to enhance the processing speed. By implementing simulation for the IEEE-30-bus system and a real-life system located in Northwest China, the viability of the models and the proposed method is verified.

True real-time change data capture with web service database encapsulation

This research is investigating the claim that Change Data Capture (CDC) technologies capture data changes in real-time. Based on theory, our hypothesis states that real-time CDC is not achievable with traditional approaches (log scanning, triggers and timestamps). Traditional approaches to CDC require a resource to be polled, which prevents true real-time CDC. We propose an approach to CDC that encapsulates the data source with a set of web services. These web services will propagate the changes to the targets and eliminate the need for polling. Additionally we propose a framework for CDC technologies that allow changes to flow from source to target. This paper discusses current CDC technologies and presents the theory about why they are unable to deliver changes in real-time. Following, we discuss our web service approach to CDC and accompanying framework, explaining how they can produce real-time CDC. The paper concludes with a discussion on the research required to investigate the real-time capabilities of CDC technologies. © 2010 IEEE.