Performance and operational economics estimates for a coal gasification combined-cycle cogeneration powerplant

A performance and operational economics analysis is presented for an integrated-gasifier, combined-cycle (IGCC) system to meet the steam and baseload electrical requirements. The effect of time variations in steam and electrial requirements is included. The amount and timing of electricity purchases from sales to the electric utility are determined. The resulting expenses for purchased electricity and revenues from electricity sales are estimated by using an assumed utility rate structure model. Cogeneration results for a range of potential IGCC cogeneration system sizes are compared with the fuel consumption and costs of natural gas and electricity to meet requirements without cogeneration. The results indicate that an IGCC cogeneration system could save about 10 percent of the total fuel energy presently required to supply steam and electrical requirements without cogeneration. Also for the assumed future fuel and electricity prices, an annual operating cost savings of 21 percent to 26 percent could be achieved with such a cogeneration system. An analysis of the effects of electricity price, fuel price, and system availability indicates that the IGCC cogeneration system has a good potential for economical operation over a wide range in these assumptions

Social Ranking Techniques for the Web

The proliferation of social media has the potential for changing the structure and organization of the web. In the past, scientists have looked at the web as a large connected component to understand how the topology of hyperlinks correlates with the quality of information contained in the page and they proposed techniques to rank information contained in web pages. We argue that information from web pages and network data on social relationships can be combined to create a personalized and socially connected web. In this paper, we look at the web as a composition of two networks, one consisting of information in web pages and the other of personal data shared on social media web sites. Together, they allow us to analyze how social media tunnels the flow of information from person to person and how to use the structure of the social network to rank, deliver, and organize information specifically for each individual user. We validate our social ranking concepts through a ranking experiment conducted on web pages that users shared on Google Buzz and Twitter.Comment: 7 pages, ASONAM 201

Improved memory loading techniques for the TSRV display system

A recent upgrade of the TSRV research flight system at NASA Langley Research Center retained the original monochrome display system. However, the display memory loading equipment was replaced requiring design and development of new methods of performing this task. This paper describes the new techniques developed to load memory in the display system. An outdated paper tape method for loading the BOOTSTRAP control program was replaced by EPROM storage of the characters contained on the tape. Rather than move a tape past an optical reader, a counter was implemented which steps sequentially through EPROM addresses and presents the same data to the loader circuitry. A cumbersome cassette tape method for loading the applications software was replaced with a floppy disk method using a microprocessor terminal installed as part of the upgrade. The cassette memory image was transferred to disk and a specific software loader was written for the terminal which duplicates the function of the cassette loader

Voter model with non-Poissonian interevent intervals

Recent analysis of social communications among humans has revealed that the interval between interactions for a pair of individuals and for an individual often follows a long-tail distribution. We investigate the effect of such a non-Poissonian nature of human behavior on dynamics of opinion formation. We use a variant of the voter model and numerically compare the time to consensus of all the voters with different distributions of interevent intervals and different networks. Compared with the exponential distribution of interevent intervals (i.e., the standard voter model), the power-law distribution of interevent intervals slows down consensus on the ring. This is because of the memory effect; in the power-law case, the expected time until the next update event on a link is large if the link has not had an update event for a long time. On the complete graph, the consensus time in the power-law case is close to that in the exponential case. Regular graphs bridge these two results such that the slowing down of the consensus in the power-law case as compared to the exponential case is less pronounced as the degree increases.Comment: 18 pages, 8 figure

Optimal restoration of noisy 3D X-ray data via shearlet

decomposition

Covariate-Adjusted Constrained Bayes Predictions of Random Intercepts and Slopes. Sujit Ghosh is a

Constrained Bayes methodology represents an alternative to the posterior mean (empirical Bayes) method commonly used to produce random effect predictions under mixed linear models. The general constrained Bayes methodology of Ghosh (1992) is compared to a direct implementation of constraints, and it is suggested that the former approach could feasibly be incorporated into commercial mixed model software. Simulation studies and a real-data example illustrate the main points and support the conclusions

The Influence of Intense Tai Chi Training on Physical Performance and Hemodynamic Outcomes in Transitionally Frail, Older Adults

Background. Few data exist to evaluate whether Tai Chi (TC) training improves physical performance and hemodynamic outcomes more than a wellness education (WE) program does among older fallers transitioning to frailty. Methods. This 48-week randomized clinical trial was provided at 10 matched pairs of congregate living facilities in the Atlanta metropolitan area to 291 women and 20 men, who were transitionally frail, ≥70 years old, and had fallen at least once within the past year. Pairs of facilities were randomized to either TC exercise (n = 158) or WE (control) interventions (n = 153) over 48 weeks. Physical performance (freely chosen gait speed, reach, chair-rises, 360° turn, picking up an object from the floor, and single limb support) and hemodynamic outcomes (heart rate and blood pressure) were obtained at baseline and after 4, 8, and 12 months. Results. Mean percent change (baseline to 1 year) for gait speed increased similarly in both cohorts (TC: 9.1% and WE: 8.2%; p =.78). However, time to complete three chair-rises decreased 12.3% for TC and increased 13.7% for WE (p =.006). Baseline to 1 year mean percent change decreased among TC and increased within WE cohorts for: body mass index (-2.3% vs 1.8%; p <.0001), systolic blood pressure (-3.4% vs 1.7%; p =.02), and resting heart rate (-5.9% vs 4.6%; p <.0001). Conclusions. TC significantly improved chair-rise and cardiovascular performance. Because TC training reduced fall occurrences in this cohort, factors influencing functional and cardiovascular improvements may also favorably impact fall event

Multiple agency perspective, family control, and private information abuse in an emerging economy

Using a comprehensive sample of listed companies in Hong Kong this paper investigates how family control affects private information abuses and firm performance in emerging economies. We combine research on stock market microstructure with more recent studies of multiple agency perspectives and argue that family ownership and control over the board increases the risk of private information abuse. This, in turn, has a negative impact on stock market performance. Family control is associated with an incentive to distort information disclosure to minority shareholders and obtain private benefits of control. However, the multiple agency roles of controlling families may have different governance properties in terms of investors’ perceptions of private information abuse. These findings contribute to our understanding of the conflicting evidence on the governance role of family control within a multiple agency perspectiv

Reconstructing dynamical networks via feature ranking

Empirical data on real complex systems are becoming increasingly available. Parallel to this is the need for new methods of reconstructing (inferring) the topology of networks from time-resolved observations of their node-dynamics. The methods based on physical insights often rely on strong assumptions about the properties and dynamics of the scrutinized network. Here, we use the insights from machine learning to design a new method of network reconstruction that essentially makes no such assumptions. Specifically, we interpret the available trajectories (data) as features, and use two independent feature ranking approaches -- Random forest and RReliefF -- to rank the importance of each node for predicting the value of each other node, which yields the reconstructed adjacency matrix. We show that our method is fairly robust to coupling strength, system size, trajectory length and noise. We also find that the reconstruction quality strongly depends on the dynamical regime

Size-Dependent Surface Plasmon Dynamics in Metal Nanoparticles

We study the effect of Coulomb correlations on the ultrafast optical dynamics of small metal particles. We demonstrate that a surface-induced dynamical screening of the electron-electron interactions leads to quasiparticle scattering with collective surface excitations. In noble-metal nanoparticles, it results in an interband resonant scattering of d-holes with surface plasmons. We show that this size-dependent many-body effect manifests itself in the differential absorption dynamics for frequencies close to the surface plasmon resonance. In particular, our self-consistent calculations reveal a strong frequency dependence of the relaxation, in agreement with recent femtosecond pump-probe experiments.Comment: 8 pages + 4 figures, final version accepted to PR