Demographics and the Political Sustainability of Pay-as-you-go Social Security

The net present value of costs and benefits from a pay-as-you-go social security system are negative for young people and positive for the elderly. If people all vote their financial self-interest, there will be a pivotal age such that those who are younger favor smaller social security benefits and those who are older will favor larger benefits. For persons of each age and sex, we estimate the expected present value gained or lost from a small permanent increase in the amount of benefits, where the cost of these benefits is divided equally among the population of working age. Assuming that everyone votes his or her long run financial self-interest, and calculating the number of voters in the population of each age and sex, we can determine whether there is majority support for an increase or a decrease in social security benefits. We use statistics on the age distribution and mortality rates for the United States to explore the sensitivity of political support for social security to alternative assumptions about the discount rate, excess burden in taxation, voter participation rates, and birth, death, and migration rates. We find that a once-and-for-all decrease in benefits would be defeated by a majority of selfish voters under a wide range of parameters. We also study the predicted majority outcomes of votes on changing the retirement age.

Electromagnetic energy transfer and switching in nanoparticle chain arrays below the diffraction limit

Electromagnetic energy transfer in plasmon wires consisting of chains of closely spaced metal nanoparticles can occur below the diffraction limit by means of coupled plasmon modes. Coherent propagation with group velocities that exceed 0.1 c is possible in straight wires and around sharp corners (bending radius much less than wavelength of visible light). Energy transmission through chain networks is possible at high efficiencies and is a strong function of the frequency and polarization direction of the plasmon mode. Although these structures exhibit transmission losses due to heating of about 3 dB/500 nm, they have optical functionality that cannot be obtained in other ways at a length scale ≪1 μm

Organizational Image Repair Tactics and Crisis Type: Implications for Crisis Response Strategy Effectiveness

Existing models of organizational crisis response effectiveness provide useful insights but are limited in terms of offering a guide for practitioners dealing with actual crisis situations. This analysis examines the relative effectiveness of image repair tactics based on differences in root causes of crisis events. Results suggest that certain image repair tactics are seen as the most and the least effective regardless of crisis type. At the same time, there were some differences across crisis types that could guide practitioner tactic choices. Limited results here and in past research raise questions about whether image repair tactic effectiveness can be usefully mapped to situational variables, such as audience or crisis type. This article concludes with discussion on this matter and suggestions for future research

Global analysis of phase locking in gene expression during cell cycle: the potential in network modeling

<p>Abstract</p> <p>Background</p> <p>In nonlinear dynamic systems, synchrony through oscillation and frequency modulation is a general control strategy to coordinate multiple modules in response to external signals. Conversely, the synchrony information can be utilized to infer interaction. Increasing evidence suggests that frequency modulation is also common in transcription regulation.</p> <p>Results</p> <p>In this study, we investigate the potential of phase locking analysis, a technique to study the synchrony patterns, in the transcription network modeling of time course gene expression data. Using the yeast cell cycle data, we show that significant phase locking exists between transcription factors and their targets, between gene pairs with prior evidence of physical or genetic interactions, and among cell cycle genes. When compared with simple correlation we found that the phase locking metric can identify gene pairs that interact with each other more efficiently. In addition, it can automatically address issues of arbitrary time lags or different dynamic time scales in different genes, without the need for alignment. Interestingly, many of the phase locked gene pairs exhibit higher order than 1:1 locking, and significant phase lags with respect to each other. Based on these findings we propose a new phase locking metric for network reconstruction using time course gene expression data. We show that it is efficient at identifying network modules of focused biological themes that are important to cell cycle regulation.</p> <p>Conclusions</p> <p>Our result demonstrates the potential of phase locking analysis in transcription network modeling. It also suggests the importance of understanding the dynamics underlying the gene expression patterns.</p

Accurate, precise modeling of cell proliferation kinetics from time-lapse imaging and automated image analysis of agar yeast culture arrays

BACKGROUND: Genome-wide mutant strain collections have increased demand for high throughput cellular phenotyping (HTCP). For example, investigators use HTCP to investigate interactions between gene deletion mutations and additional chemical or genetic perturbations by assessing differences in cell proliferation among the collection of 5000 S. cerevisiae gene deletion strains. Such studies have thus far been predominantly qualitative, using agar cell arrays to subjectively score growth differences. Quantitative systems level analysis of gene interactions would be enabled by more precise HTCP methods, such as kinetic analysis of cell proliferation in liquid culture by optical density. However, requirements for processing liquid cultures make them relatively cumbersome and low throughput compared to agar. To improve HTCP performance and advance capabilities for quantifying interactions, YeastXtract software was developed for automated analysis of cell array images. RESULTS: YeastXtract software was developed for kinetic growth curve analysis of spotted agar cultures. The accuracy and precision for image analysis of agar culture arrays was comparable to OD measurements of liquid cultures. Using YeastXtract, image intensity vs. biomass of spot cultures was linearly correlated over two orders of magnitude. Thus cell proliferation could be measured over about seven generations, including four to five generations of relatively constant exponential phase growth. Spot area normalization reduced the variation in measurements of total growth efficiency. A growth model, based on the logistic function, increased precision and accuracy of maximum specific rate measurements, compared to empirical methods. The logistic function model was also more robust against data sparseness, meaning that less data was required to obtain accurate, precise, quantitative growth phenotypes. CONCLUSION: Microbial cultures spotted onto agar media are widely used for genotype-phenotype analysis, however quantitative HTCP methods capable of measuring kinetic growth rates have not been available previously. YeastXtract provides objective, automated, quantitative, image analysis of agar cell culture arrays. Fitting the resulting data to a logistic equation-based growth model yields robust, accurate growth rate information. These methods allow the incorporation of imaging and automated image analysis of cell arrays, grown on solid agar media, into HTCP-driven experimental approaches, such as global, quantitative analysis of gene interaction networks