text:
- Research article
- Open Access
Dynamics of the quorum sensing switch: stochastic and non-stationary effects
- Marc Weber1 and
- Javier Buceta1Email author
© Weber and Buceta; licensee BioMed Central Ltd. 2013
- Received: 4 July 2012
- Accepted: 7 January 2013
- Published: 16 January 2013
A wide range of bacteria species are known to communicate through the so called quorum sensing (QS) mechanism by means of which they produce a small molecule that can freely diffuse in the environment and in the cells. Upon reaching a threshold concentration, the signalling molecule activates the QS-controlled genes that promote phenotypic changes. This mechanism, for its simplicity, has become the model system for studying the emergence of a global response in prokaryotic cells. Yet, how cells precisely measure the signal concentration and act coordinately, despite the presence of fluctuations that unavoidably affects cell regulation and signalling, remains unclear.
We propose a model for the QS signalling mechanism in Vibrio fischeri based on the synthetic strains lux01 and lux02. Our approach takes into account the key regulatory interactions between LuxR and LuxI, the autoinducer transport, the cellular growth and the division dynamics. By using both deterministic and stochastic models, we analyze the response and dynamics at the single-cell level and compare them to the global response at the population level. Our results show how fluctuations interfere with the synchronization of the cell activation and lead to a bimodal phenotypic distribution. In this context, we introduce the concept of precision in order to characterize the reliability of the QS communication process in the colony. We show that increasing the noise in the expression of LuxR helps cells to get activated at lower autoinducer concentrations but, at the same time, slows down the global response. The precision of the QS switch under non-stationary conditions decreases with noise, while at steady-state it is independent of the noise value.
Our in silico experiments show that the response of the LuxR/LuxI system depends on the interplay between non-stationary and stochastic effects and that the burst size of the transcription/translation noise at the level of LuxR controls the phenotypic variability of the population. These results, together with recent experimental evidences on LuxR regulation in wild-type species, suggest that bacteria have evolved mechanisms to regulate the intensity of those fluctuations.
- Quorum sensing
- Noise
- Stochastic modeling
- Vibrio fischeri
- Autoinducer
- Synchronization
Bacteria, long thought having a solitary existence, were found to communicate with one another by sending and receiving chemical messages [1]. Their communication mechanism results in the ability to synchronize the activity of the colony as a whole. The latter leads to a coordinated behaviour that in some cases resembles that of multicellular organisms, e.g. the so-called community effect during development [2]. Thus, by means of the quorum sensing (QS) mechanism, cells produce, export, and import signalling molecules (autoinducer). As the colony grows, more cells produce and export autoinducer, leading to an increasing concentration of the signalling molecule in the environment and in the cells. Upon reaching a concentration threshold, the autoinducer activates the expression of QS-controlled genes therefore coordinating the cells in a density-dependent manner. Importantly, QS controls a number of relevant phenotypic changes in bacteria as for example the virulence in S. aureus[3]. In addition, it has become a model system for studying the emergence of coordinated behaviour in communicating cells. All in all, QS has opened a research field with promising technological applications [4], as for example, the environmentally controlled invasion of cancer cells [5].
The QS systems in gram-negative bacteria share a core network architecture. In this regard, a characteristic model system is the LuxR/LuxI regulatory network in Vibrio fischeri[6]. LuxR protein is an autoinducer-dependent activator of the lux operon that drives the autocatalytic expression of luxR and of the autoinducer synthase, luxI, together with that of the genes responsible for the production of bioluminescence. The up-regulation of luxI increases the production of autoinducer molecules that in turn activates further gene expression. The resulting positive feedback loop leads to a bistable switch-like behaviour depending on the concentration of the autoinducer as shown by in silico[7–9] and in vivo experiments [10, 11]. Such switch-like behaviour has been observed at the population level by measuring the average gene expression level. However, how individual cells behave remains puzzling. In fact, as observed in Vibrio harveyi[12], Vibrio fischeri[13], Pseudomonas aeruginosa[14], and luxI/luxR-GFP strains of E. coli[15], the cellular response to QS signals seems to be highly heterogeneous at the level of the distribution of both the population phenotype and the response times of individual cells.
A number of studies have shown that noise plays an important role in bistable systems [16–18]. Therefore, the aforementioned heterogeneity may be caused by the random fluctuations that unavoidably affect cell regulation and signalling. This poses the intriguing question of how cells achieve a coordinated response in the presence of noise. Indeed, the QS mechanism may produce a robust and synchronized behaviour at the level of the population both experimentally [19] and theoretically [20]. However, how this behaviour at the collective level arises from the stochastic dynamics of individual cells is still an open question. At the end, in the framework of QS, a collective response means a precise information exchange in the colony. Consequently, how can a bacterial population estimate its number of constituents precisely if such information is fuzzy at the single cell level? Herein, we shed light on this problem and investigate how noise affects the QS transition both at the level of individual cells and at the level of the cell population.
In the context of QS modelling, most research has focused on the understanding of the intracellular circuit [7–11, 21–24], i.e. single cell studies, while few of them have considered an ensemble of communicating cells [25–28]. Yet, so far no study has taken into account the coupling of the signalling mechanism at the single cell and collective levels by stochastic means together with realistic dynamics of the proliferation process. In this work, we model the QS mechanism by using both deterministic and stochastic approaches and taking into account the key regulatory interactions between LuxR and LuxI, the autoinducer transport, the cellular growth and the division dynamics. Our results indicate that the cell response is highly heterogeneous and that noise in the gene expression of luxR is the main factor that determines this variability. Moreover, we show that the transition of the QS switch near the critical concentration of autoinducer is very slow compared to other characteristic temporal scales of the process and that, as a consequence, the non-stationary effects are crucial for setting a precise switch. As we show further below, the dilution due to cell growth and division is a key element required for an in-depth understanding of the QS response dynamics. In addition, we demonstrate that noise, depending on the cell density, can either prevent or promote phenotypic changes indicating a beneficial role played by stochasticity. Altogether, we find that the precision of the QS switch for determining the number of cells in the colony is highly dynamic and context dependent, which in turn favors adaptability.
Modelling of the LuxI/LuxR gene regulatory network
As revealed by the set of reactions (1), we assume that the regulatory complex (luxR·A)2 activates the transcription of luxI and luxR in opposite directions upon binding to the DNA. These reactions account for the main regulatory interactions of both lux01 and lux02 constructs. Since lux01 lacks the luxI gene the autoinducer, A, cannot be synthesized, i.e. k A =0, and an exogenous supply of the signalling molecule is required to induce the system. The expression rates of luxI and luxR depend on the initiation rate of transcription, the speed of elongation, the length of the transcript, and the rate of translation and postmodification into functional proteins. We take into account the differences due to these intermediate processes in an effective manner by using different transcription/translation rates for the luxR and luxI::gfp genes. Note that we assume that there are basal transcriptional rates, α R k R and α I k I , even though the regulatory complex (luxR·A)2 is not bound to the promoter region of the DNA. Still, since α R ,α I ≪1 (see parameter values below), the maximum transcriptional rates take place when the activator complex is bound.
Deterministic and stochastic approaches: cell growth and division
We notice that our in silico experiments span up to 100 hours of cell culture growth in some cases (simulated experimental time, not computational time). Thus, regardless of the description, and in addition to the dynamics of the regulatory network, we also need to take into account the effects of cell growth. If cells are maintained in the exponential phase with doubling time τ then the dynamics of the volume of the cell is Vc,tot(t)=V0,tot2t/τ. Where V0,tot=N V0, N being the number of cells in the colony and V0the volume of a single cell at the beginning of the cell cycle. As a consequence, the cellular growth introduces dilution terms, , in the r.h.s. of the ODEs of all species, with the exception of the autoinducer in the medium A ext . On the other hand, cell division events lead to the duplication of the genetic material. The latter is taken into account by adding the term to the ODE that describes the concentration of DNA. This term compensates exactly for the cell growth dilution such that , i.e. the total concentration of DNA, is kept constant.
In our simulations, as in the experiments we aim to reproduce, the cell density is kept constant. This can be achieved by means of an external dilution protocol (see below) that compensates for cell proliferation. We then keep the volume Vc,tot constant and define the external volume, V ext , such that the total volume of the cell culture reads V tot =V ext + Vc,tot. Accordingly, the parameter r, see equations (1), reads r=Vc,tot/V ext . We assume that molecules are homogeneously distributed inside both the cytoplasm and the external volume (i.e. spatial effects are disregarded). Finally, the resulting ODEs are numerically integrated.
In order to study the role of noise in a population of cells communicating by QS, we build also a stochastic model of a population of bacteria. In this case, each bacterium is described as a single cell carrying a copy of the regulatory network. The ensemble of all the chemical reactions in all cells, including the diffusion reaction, are treated as one global system. We apply the Gillespie algorithm [32] to compute the time of the next reaction, choose the reaction channel from the list of all possible reactions and update the number of molecules according to the reaction stoichiometry. We model the system of cells as a global stochastic system in order to simulate as exactly as possible the stochastic dynamics of all chemical species, in particular that of autoinducer molecules. The noise in the signalling molecule originates from different sources: randomness in its synthesis by LuxI, fluctuations at the level of the number of molecules of LuxI, and randomness in the diffusion reaction of the autoinducer. The latter is particularly important since it leads to correlations between cells as follows. An autoinducer molecule can diffuse out of the cytoplasm of one cell into the medium, thereby increasing the number of molecules in the external volume by one; this increase in the level of A ext changes the probabilities of an autoinducer molecule to diffuse into any other cell. Thus, all the cells are coupled through the diffusion reaction. We note that while a possible optimization of the algorithm relies on parallelizing the code such that each cell evolves independently [25], this approximation is prone to introduce errors in the dynamics of the signalling molecule because the aforementioned correlations are neglected.
In this way, we allow variability from cell to cell in regards of the duration of the cell cycle, yet setting a minimum cell cycle duration, λτ. According to these definitions, the average duration and standard deviation of the cell cycle are τ and (1−λ)τ respectively.
Finally, we notice that in principle the Gillespie algorithm needs to be adapted in order to take into account the time-dependent cell volume. The propensity of a second-order reaction at cell i at time t scales as p i (t)=p0V0/Vc,i(t), where p0 stands for propensity of the reaction at division time when Vc,i(0)=V0. The propensity p0are derived from the corresponding reaction rate, k, by dividing the latter by the initial cell volume, p0=k/V0. In addition to the change in the propensities of the reaction channels, the algorithm would also need to be adapted to compute the time till next reaction [35]. However, in our case, since all reactions rates are faster than the rate of variation of the cell volume, ∼1/τ, (see parameter values below) then the volume increase is negligible during the time interval until the next reaction takes place. Consequently, we can adiabatically eliminate the volume growth dynamics and safely assume that the volume-dependent propensities remain constant until the next reaction occurs. Summarizing, at a given time t we compute, as described above, the time-dependent propensities based on the volume of the cell at that time and, according to those, we determine the time at which the next reaction takes place, t + △t, following the standard Gillespie algorithm.
Gene expression noise: burst size
During translation mRNA molecules are translated into proteins following a bursting dynamics [36–38]. The so-called burst size, b X , is defined as the ratio between the protein X production rate and the mRNA X degradation rate. It has been shown that b X is directly related to the intensity of gene expression noise [36, 39]. Thus, for the same average protein concentration, the larger b X is, the more fluctuating expression dynamics is displayed by protein X. In our stochastic simulations we use the burst size b X as a parameter to tune the noise intensity at the level of luxI and luxR and study its effects. Unless explicitly indicated otherwise, the bursting size in the stochastic simulations is b R =b I =20.
External dilution protocol
In controlled experimental setups it is advantageous to keep the cell density constant. This is carried out by means of an external dilution protocol that compensates for cell growth. Experimentally, this is usually achieved by periodic dilutions of the cell culture [10] or by a continuous flow of liquid medium in a chemostat or in a microfluidic device [40]. This procedure allows to measure the stationary concentration of the signalling molecule at a given cell density and/or to estimate the threshold of the QS collective response of a cell culture. Moreover, the external dilution is also important in order to maintain cells in the exponential growth phase and prevent depletion of nutrients in the medium. Additionally, the levels of the autoinducer can be controlled by adding/removing exogenous signalling molecules in/from the culture buffer. We implement those in our simulations as follows.
In the deterministic model, as shown in Figure 2, we assume a unique cell with volume Vc,tot. Cell density is controlled by a continuous efflux that removes cytoplasm and culture medium at a rate that compensates exactly for the cell growth, such that the volume Vc,totremains constant. Concurrently, a continuous influx of equal and opposite rate brings fresh medium to the cell culture. In our in silico stochastic experiments, the efflux is reproduced by removing molecules, A ext , from the medium and washing away cells by "deleting" a cell picked at random in the population each time a new cell is born.
where γ=ln(2)/τ. That is, an efflux removes autoinducer molecules from the external volume at a rate γ and an influx introduces signalling molecules in the external volume at a rate . In the deterministic description, the last equation leads to an additional term at the r.h.s. of the ODE for the concentration of A ext :. We notice that in our simulations, as in experiments, V tot /V ext ≃1. In the absence of synthesis (e.g. lux01) and taking into account that the degradation is slower than the diffusion and the influx rate, it is easy to see that the concentration of autoinducer, both inside and outside the cell, tends to : the desired control value of the autoinducer concentration (see Additional file 3: Figure S1).
Parameters used in the deterministic and stochastic simulations
K d 1
dissociation constant of LuxR to A
100 nM
unbinding rate of LuxR to A
10 mi n−1
K d 2
dissociation constant of LuxR·AI dimerization
20 nM
dissociation rate of dimer (LuxR·AI)2
1 mi n−1
k A
synthesis rate of A by LuxI
0.04 mi n−1
K dlux
dissociation constant of (LuxR·AI)2 to the lux promoter
200 nM
dissociation rate of (LuxR·AI)2 to the lux promoter
10 mi n−1
burst size
k R
transcription rate of luxR
200/b mi n−1
k I
transcription rate of luxI
50/b mi n−1
p R
translation rate of luxR mRNA
b d mR mi n −1
p I
translation rate of luxI mRNA
b d mI mi n −1
α R
ratio between unactivated and activated rate of expression of luxR
α I
ratio between unactivated and activated rate of expression of luxI
d A
degradation rate of A (same inside and outside the cell)
0.001 mi n−1
degradation rate of (LuxR·AI)2
0.002 mi n−1
d C
degradation rate of LuxR·AI
0.002 mi n−1
d R
degradation rate of LuxR
0.002 mi n−1
d I
degradation rate of LuxI
0.01 mi n−1
d mR
degradation rate of luxR mRNA
0.347 mi n−1
d mI
degradation rate of luxI mRNA
0.347 mi n−1
effective diffusion rate of A through the cell membrane
10 mi n−1
cell cycle duration (doubling time) in RM/succinate at 30 C
45 min
relative weight between the det./sto. components of the cell cycle
cell volume at the beginning of cell cycle
1.5 μ m3
V tot
total cell culture volume
First passage time analysis
The mean first passage time at a given autoinducer concentration quantifies the average time that a cell takes to get activated or deactivated. For computing the first passage time in transitions, from low (high) to high (low) state, we take a single cell at the low (high) state and follow its dynamics until the GFP expression level reaches the high (low) state. We point out that the maximum GFP concentration refers to that of the deterministic simulations. In order to get enough statistics, we repeat this procedure, departing from the same initial condition, 103 times for each concentration of autoinducer.
The deterministic model reproduces the experimental observations at the population level
The chemical kinetics formalism leads to a set of ODEs that describes the population average dynamics in terms of the concentration of the different species considered in our model (see Additional file 1: Text S1). As in some experiments [10], we assume that the cell culture grows in an environment where the concentration of the external autoinducer in the medium, , is kept fixed and under well-stirred conditions. In addition, we implement a dilution protocol that compensates for cell growth and maintains the cell density constant (see Methods). We notice that in some experimental setups, e.g. [10], a periodic dilution protocol is applied for keeping the cell density constant; in our model, we keep the cell density constant by means of a continuous influx and efflux of culture medium, as in a chemostat or microfluidic device.
Further simulations to check if the dynamics of our model is compatible with the experimental data refer to the behaviour of the system under non-stationary induction conditions and to the serial dilution protocol of the external medium [10]. As for the first, when cells are induced for 10 h, we observe that the bistability region increases (see Figure 3). As for the second, cells are partially induced at a fixed autoinducer concentration for 2 hours and afterwards the external medium is changed hourly to decrease the concentration of the autoinducer. In this case, the transient response of the cells (Figure 3, green curves) also reproduces the experimental observations. That is, from the point of view of the population average, the deterministic model is not only capable of reproducing the steady-state of the network but also its dynamics. Moreover, in agreement with experiments (see Figure S6 in [10]) our simulations reveal that the temporal scale for reaching a steady-state is much larger than the cell cycle duration. In order to clarify how noise and the induction time modifies the timing for the transition at the single cell level we then perform stochastic simulations.
The stochastic simulations reveal the interplay between non-stationary effects and noise
Cells are subjected to intrinsic noise at the level of the mRNAs, regulatory proteins, i.e. LuxR and LuxI, and at the level of signalling molecules. In order to analyze the behaviour of individual cells and reveal how noise affects the QS switch, we perform stochastic simulations of a population of growing and dividing cells as described in the Methods section (see Additional file 2: Video S1). The transition of an individual cell from the low to the high state, and the other way around, is intrinsically random and depends, among others, on the levels of autoinducer. Thus, inside a population some cells will jump while others remain in their current state leading to a bimodal phenotypic distribution. We compute the proportion of cells that are below and above a threshold of GFP equal to half-maximum GFP concentration. We consider the distribution of cells to be bimodal when the proportion of cells in either the low or the high state is below 90% and according to this we define the range of autoinducer concentration for which there is bimodality. For low concentrations of autoinducer, , the collective response of the cell population is unactivated, and for high concentrations, , such response activates most of the cells leading to a global response of the colony. On the other hand, within the bimodality range, the response is distributed between two subpopulations, thus failing to achieve a global coordination in the colony. In order to characterize this behaviour, we introduce the concept of precision in the QS switch as the inverse of the concentration range for which the cells response distribution (phenotypes), during an induction experiment, is bimodal. That is, the larger the bimodal range, the less precise the switch is in order to generate a global response in the colony. In this regard, we point out that the precision of the switch in a noise-free situation is infinite since all cells achieve global coordination simultaneously.
As expected the intrinsic noise decreases the precision of the QS switch with respect to the deterministic case. Still, noise helps cells to become activated before the critical concentration of a fluctuations-free system under all induction conditions. Moreover, in steady-state conditions the high state is globally achieved before the critical deterministic concentration. This phenomenon is recapitulated in Figure 4 (bottom) where we plot the population average response for the induction and dilution experiments at steady-state (100 h induction) for both the deterministic and stochastic models. Notice that the dilution curves of the stochastic model are similar to that of the deterministic model; however, the average transition to the high state occurs at a lower autoinducer concentration due to intrinsic fluctuations.
The features of the QS switch depends on the transcriptional noise of LuxR
The response of bacterial colonies driven by the QS signalling mechanism under noisy conditions has been addressed, in a broad sense, by different authors. In particular, the characterization of the collective response as a synchronization phenomenon where the phenotypic variations can be generically predicted has been proposed [47]. However, this approach requires gene regulatory interactions controlling the QS switch that do not induce bistability and lead to a monostable behaviour, e.g. negative feedback loops [48]. Our study focus on strains that display, as the wild-type LuxI/LuxR system do, bistability and, consequently, an alternative method to quantify the phenotypic variability induced by noise was needed, i.e. the precision concept. Moreover, previous works assume stationary conditions and disregard the role of the cell cycle duration. Herein, in agreement with experimental results, we have shown that the time for reaching a steady expression rate is much larger than the cell cycle duration (see [10]). As a result, we have revealed that the interplay between non-stationary and stochastic effects is key for understanding the global response of the colony and the phenotypic variability. Finally, we have shown that the intrinsic noise is able to stabilize a particular phenotypic state. This effect, namely the fluctuations inducing a slowing down in the activation of the cells, emerges because noise extends the bistable region compared to the deterministic system. While such a noise-induced phenomenon has been characterized in population models [49] and, more recently, in theoretical studies on bistable switches [18], to the best of our knowledge, this is the first time that is reported in the context of QS systems. All in all, from the viewpoint of the comprehension of how noisy inputs may condition phenotypic variability in bacterial colonies, our study introduces a number of advances.
Herein, we have characterized how the precision of the QS switch depends on the stochasticity levels and, importantly, elucidated which noisy component of the LuxI/LuxR regulatory network drives the observed phenomenology. Thus, we have found that under non-stationary conditions, LuxR controls the phenotypic variability and that changing the noise intensity at the level of LuxI has no effect on the precision of the switch. A plausible explanation for this reads as follows. The fluctuations at the level of LuxI are transmitted to the autoinducer. However, the diffusion mechanism rapidly averages out the stochasticity levels of the latter. This is not possible for LuxR which is kept within the cell. As a consequence the amount of activation complex, that is ultimately the responsible for the activation, is driven by the fluctuations of LuxR but not by those of LuxI.
Recent experimental work has measured the bioluminescence levels of individual V. fischeri cells at fixed autoinducer concentration [13]. In agreement with our results, the authors observed that cells differed widely in terms of their activation time and luminescence distribution. Interestingly, other experiments have revealed the presence of additional regulatory interactions for controlling the LuxR noise levels. For example, C8HSL molecules, a second QS signal in V. fischeri, has been suggested to reduce the noise in bioluminescence output of the cells at low autoinducer concentrations [50]. In the same direction, in V. harveyi, the number of LuxR dimers is tightly regulated indicating a control over LuxR intrinsic noise [51]. In fact, wild-type V. harveyi strains have two negative feedback loops that repress the production of LuxR [52] and this kind of regulatory circuit is known to reduce noise levels [53]. In this context, our results provide a feasible explanation for the network structure in wild-type strains: since noise in LuxR controls the phenotypic variability of the LuxR/LuxI QS systems, bacteria have evolved mechanisms to control its noise levels. An additional argument in this regard arises from our results about the deactivation of cells: once they are fully induced we do not observe reversibility of the phenotype (FPT larger than 100 h). First, these results are in agreement with other switching systems as the gallactose signalling network in yeast [54] and with theoretical results that explain the asymmetric switching dynamics due to stochastic effects [18]. Second, they reveal the importance of additional interactions that regulate negatively luxR in wild-type strains and indicates that synthetic strains as lux01 and lux02 summarize many features of the wild-type operon during the activation process but fail to capture some of dynamical aspects of the deactivation phenomenon.
Herein we have introduced deterministic and stochastic modelling approaches for describing the core functionality of the LuxI/LuxR regulatory network in quorum sensing systems. We have focused on synthetic constructs, lux01 and lux02, that reproduce the behaviour of the wild-type system and allow for controlled experiments that have provided quantification of the activation process [10]. The deterministic approach has allowed us to estimate different parameters of the model and reproduce the switch-like behaviour of the QS network. Thus, our simulations reveal that the interplay between non-stationary and stochastic effects are key and that, for an extended range of autoinducer concentrations, a bimodal phenotypic variability develops such that cells fail to produce a global response. In this context we have introduced the concept of precision of the QS switch, as the inverse of the width of the bimodal phenotypic region.
By computing the statistics of the activation dynamics of cells, we have shown that the QS precision depends on the gene expression noise at the level of LuxR and is independent from that of LuxI. Our results, together with the experimental evidences on LuxR regulation in wild-type species, suggest that the noise at the level of LuxR controls the phenotypic variability of the LuxR/LuxI QS systems and that bacteria have evolved to control its intensity. In addition, the robust stabilization of the phenotype once is fully induced indicates that, albeit synthetic strains as lux01 and lux02 summarize many features of the wild-type operon during the activation process, they fail to capture crucial aspects of the deactivation phenomenon.
Most insight in regards of the effect of LuxR noise on the dynamics of cell activation is given by the study of the mean first passage time (MFPT). In terms of the timing of activation, we have observed two opposite effects depending on the control parameter : for nM, the larger the noise in LuxR, the quicker the cells become activated, while for nM, we observe the opposite effect and noise slows down cell activation. We suggest that this effect can be explained by the stochastic stabilization of the low state. Moreover, the calculation of additional properties of the statistics of the first passage time have allowed us to relate the concept of precision of the switch with the variability of the FPT by estimating the 10% and 90% quantiles.
In summary, our results indicate that in bacterial colonies driven by the QS mechanism there is a trade-off between the activation onset and a global response due to non-stationary and stochastic effects. On one hand, large levels of noise at the level of LuxR imply that cells require smaller autoinducer levels for achieving an activation onset but, at the same time, a global response requires a substantial autoinducer concentration. On the other hand, if the LuxR noise levels are small, the activation onset is shifted toward larger values of the autoinducer concentration but the global response is achieved for smaller concentration values. Our study could be useful for Synthetic Biology approaches that exploit the QS mechanism. The fact that some important features of the QS mechanism, e.g. precision, rely on the burst size of one component, opens the door to modifications of the LuxI/LuxR operon for regulating the response depending on the problem under consideration. Finally, further research is needed about the general validity and applicability on the noise-induced stabilization phenomenon of particular phenotypic states in other gene regulatory systems beyond the QS mechanism. Work in that direction is in progress.
We thank Oriol Canela Xandri and Nico Geisel for fruitful comments. Financial support was provided by MICINN under grant BFU2010-21847-C02-01/BMC, and by DURSI through project 2009-SGR/01055. We also acknowledge support from the European Science Foundation through the FuncDyn programme. M.W. acknowledges the support of the Spanish MICINN through a doctoral fellowship (FPU AP2008-03272).
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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


text: Pictured: Daniela Ruah (Special Agent Kensi Blye). A former defendant of Deeks is targeted for discovering information that could dismantle a lucrative car shipping operation with links to a global terrorist ring. Meanwhile, the NCIS: LA team tackles the large-scale stolen car operation from the inside when Kensi goes undercover in an auto body shop. Photo: Monty BrintonCBS ©2012 CBS Broadcasting, Inc. All Rights Reserved.

subset: commoncrawl


text:
Thier View | America is vulnerable to a lack of financial rules
The following editorial appeared in the Pittsburgh Post-Gazette on Wednesday:
Six years since the financial industry had to be resuscitated by the federal government, the American economy still remains at risk from another catastrophic episode of over-speculation and bailouts.
It's been four years since the passage of the Dodd-Frank Act, which promised to overhaul the financial sector.
But many of the law's regulations on proprietary trading, opaque derivatives and the health of America's banks have been delayed or watered down by slow-moving agencies within the Obama administration.
Namely, that's the Securities and Exchange Commission and the Commodity Futures Trading Commission.
As of July 1, only 208 of the 398 rules required by the Dodd-Frank Act had been finalized, according to Davis, Polk and Wardwell LLP, a law firm that tracks the law's progress.
About 45 percent of the deadlines for making rules have been missed.
The heart of the legislation, the Volcker Rule, was supposed to go into effect in July 2012.
That has been delayed to 2015.
The Volcker Rule bans proprietary trading, where banks make risky investments with clients' money instead of their own. It also limits investment in hedge funds and private equity.
At the same time, large banks seem to have resumed the bad behavior that contributed to the Great Recession.
JP Morgan trader Bruno Iksil, known as the London Whale, lost billions after gambling on credit default swaps, the same messy instruments that almost killed AIG.
Citibank faces a lawsuit over its handling of mortgage securities and failed its Federal Reserve stress test in June, meaning that the company's risky balance sheet could imperil the broader economy.
While Congress has been predictably unhelpful on financial regulation since Republicans took control of the House of Representatives in 2010, the Obama administration deserves most of the blame.
It should not take five years to implement the key-stone of any law, no matter how complex.
The revolving door between financial regulators and big banks might explain the foot-dragging.
Last month, the SEC approved a rule with a clear loophole letting international affiliates of U.S. banks evade derivatives trading regulations.
Until the executive branch moves more seriously toward faithfully executing the law, American consumers will remain exposed to the excesses of unregulated markets.


text:
Thursday, June 14, 2007
"Atlantis here! Atlantis there! Atlantis Everywhere"
17 comments:
Excellent! I have really enjoyed your first six podcasts.
Maybe you could do one on Gurdjieff and symbolist Egypt?
- June 15, 2007 at 9:21 AM
Great presentation. I look forward to your continued research.
- July 7, 2007 at 3:00 PM
Well, how soon?
- July 18, 2007 at 3:09 AM
- theseus said...
Hello John Anthony...
It has been too long. Exciting news and vindication of you in the recently published findings at Qurta:
Etchings 15,000 years old indeed!
I blogged about it and mentioned you.
- July 29, 2007 at 12:34 AM
Some interesting discussion on the topic here, take some 'with a grain of salt' however:
Author Dorothy Cora Moore discuss her contemporary novel, "The Atlanteans" and explain how the mythical land of Atlantis raises fascinating implications in today's uncertain climate, both socially and globally.
- August 9, 2007 at 10:35 PM
An update on "The ARE's Search for Atlantis", with some new Bimini discoveries. [TDG]
Part Two of Three - Discoveries at Bimini: Columns, Marble Building Ruins, and Possible Building Foundations in 100-Feet of Water - By Dr. Greg Little:
- August 11, 2007 at 2:44 AM
"Too often I read descriptions of how the Great Pyramid was built or how the ancient builders managed the megalithic stones in Peru that gloss right over the magnitude of these accomplishments. Cutting right to the chase, a modern locomotive engine weighs 200 tons."
- Will Hart
- August 11, 2007 at 5:48 PM
Something is Wrong with this Picture!
"Egyptian scholar's claim that it was built in 23 years with stone hammers, cooper chisels, wooden sledges, ramps and manpower. But is this possible? Let's look at the facts and statistics first. The Great Pyramid is estimated to be composed of 2.3 million blocks of stone having a combined mass of 6 million tons. The stone blocks weigh from 1 to 70 tons and the average is about 2.5 tons."
- Will Hart
- August 11, 2007 at 5:54 PM
Egyptologists: It is Time to Prove Your Claims
by Will Hart
Egyptologists are displaying irrational and unscientific fixations by stubbornly clinging to ideas that have already been discredited. Mr. Lerhner and Mr. Hawass use every public forum to repeat their unproven speculations about how the ancient (Egyptian) builders quarried, transported, lifted, dressed and precisely positioned blocks of stone weighing from 50 to 200 tons.
The problem is that they have not proven that the primitive tools and methods that they assert the builders used are equal to the task. In fact, several well-documented attempts over the past 30 years have actually failed to replicate what the builders achieved. In the 1970s a Japanese team funded by Nissan tried to build a one-third, scale model of the Great Pyramid using the methods Egyptologists claim the ancient engineers employed. They could not duplicate a single step of the process.
- Will Hart
- August 11, 2007 at 5:56 PM
VIDEO - Dr. Robert Shoch
Dr. Robert Shoch is a geologist well known for his research on the Great Sphinx, as well as for his studies of the underwater structure off the coast of Yonaguni Island, Japan, and other ancient sites and studies. He is currently a tenured faculty member at Boston University's College of General Studies where he has taught since 1984. Dr. Schoch completed his graduate work at Yale University, earning a Ph.D. (1983) in geology and geophysics...
Conscious Media Network
- August 11, 2007 at 6:02 PM
VIDEO - John Anthony West
We caught up with John at the 2006 CPAK Conference, hosted by Walter Cruttenden, in University of California Irvine where he gave us a spirited interview full of his personal and somewhat candid viewpoints. He makes ancient Egypt so much fun that you wish you could go with him on his next trip.
Conscious Media Network
- August 11, 2007 at 6:04 PM
A.R.E.'s Atlantis Search Findings
For some years A.R.E. members and the organization itself have conducted expeditions in search of ruins or any remains of the lost continent of Atlantis.
The newest expeditions have been to Andros. Eight expeditions have been to Andros.
Information / photos / videos:
- August 11, 2007 at 10:40 PM
C2CAM Archive:
Atlantis Connections
Journalist and author Will Hart shared his insights into uncovering our cosmic ancestry and connections to Atlantis. The focus should not be on finding Atlantis on the bottom of the ocean, but rather in tracing its influence which is spread out across a number of civilizations, he said. Egypt, in particular, he believes shows signs of Atlantean heritage. The pyramids were built between 10 and 20,000 years ago, he estimated, and once had outer casings on them. They were placed at prime energy points and were used in a kind of technology that interfaced with human consciousness, Hart said.
The Olmecs of Mexico, who mysteriously disappeared, were another civilization that he connected with Atlantis. Some of their artifacts such as highly polished obsidian mirrors may have had paranormal or supernatural uses, he suggested.
He also theorized that the Basque culture of Europe, and the Berbers of Africa have roots in Atlantis. Both groups, live near the Atlantic ocean and have unique physical characteristics that set them apart from their neighbors.
- August 11, 2007 at 10:43 PM
Early- To Mid-Pleistocene-Age Rocks Found At Shallow
Depth Represent A "Record In The Rocks" Of
The Once Great Continent
Background to the Discovery of a Significant Geological Disconformity at Bimini
Investigating the possible existence of Atlantis can be exhilarating. Especially so when retrieving rock cores from the deck of a drilling barge positioned in the sparkling waters of the Bimini Inlet.
This is the story of a geological investigation conducted by William Hutton and Jonathan Eagle, of The Hutton Commentaries, in March, 2007. The article also covers certain follow-on activities required to document our encounter with a completely unexpected geological disconformity, there in the carbonate-rock and sediment strata beneath the Bimini Islands. Fossil coral ages and a C-14 date lend credence to a statement made in an Edgar Cayce psychic reading which indicates that evidence of Atlantis may be found in Bimini...
Hutton Commentaries website:
- August 16, 2007 at 8:27 PM
In the year 2000, Andrew Collins published Gateway to Atlantis, proposing that the impact of a comet over the North America resulted in the end of the ice age 10,900 years ago, and destroyed Atlantis, an island empire in the Atlantic, in a single night.
Now, incredibly, corroboration has come from a group of scientists who have published in established scientific journals and written a book saying that the very disaster Andrew identified 7 years ago did indeed happen! Of course, they don't address the issue of Atlantis, but they have proved that the catastrophe involved was very real.
Listen as Andrew Collins tells William Henry the enthralling story of what really happened in the distant past--and proves where Atlantis must have been.
Dreamland podcast:
- August 18, 2007 at 12:54 AM
So, has the show stopped for good?
- September 9, 2007 at 10:38 AM
- JOHN ANTHONY WEST said...
Apologies to all who have been waiting for PhoenixFire 7. I have been extremely busy lately, but we aim to record it next week.
Thanks for your patience.
- September 12, 2007 at 8:01 AM


text:
Yann Martel's Man Booker-winning Life of Pi is one of my favourite novels of all-time, and so I was both excited and apprehensive when I heard that it was finally released as a movie more than 10 years after it was originally published.
One of the reasons why the film took so long to adapt from the 2001 novel is because filmmakers deemed it unadaptable and unfilmable, which was certainly the way I felt when I finished reading it. But if anyone could pull it off, it would be Oscar winner Ang Lee, one of the most skilled directors of his generation.
And so I'm glad to say that the film version of Life of Pi is a huge success. While it doesn't quite make me believe in God, as the story's protagonist suggests, it is probably as good as it could have ever been given the inherent difficulties in bringing this wonderful tale to life.
The adapted screenplay by Oscar nominee David Magee (Finding Neverland) turned out to be surprisingly faithful to the novel (as far as I can remember anyway). Told through the voice of the titular character, it tells the story of a young Indian boy who becomes stranded on a life boat in the middle of the Pacific Ocean with a Bengal tiger.
The first problem, of course, is making the situation believable within its own context. The second is employing special effects that support authenticity. And the third, and possibly biggest obstacle, is to make a 2-hour film interesting when most of it is dominated by a single human character and a mostly-CGI animal incapable of dialogue.
To Lee's credit, he overcomes all three problems with ease, or at least it feels that way. Lee's Life of Pi comes across as a kind of surreal fable recounted by a skilled storyteller, enabling it to feel both genuine and fantastical. The special effects are seamless (Lee says his experience on the underrated Hulk made it possible) and I certainly could not tell when the tiger was real or animated. As for keeping the story interesting, Lee does so by lengthening the on-land introduction (though not unnecessarily so — it sets up the characters and the remainder of the film nicely) and by changing things up constantly so there is not a lot of repetition when they are at sea.
The performance of Suraj Sharma as the teenage Pi is remarkable, especially considering that it's the teenage student's first film. He didn't have to do it alone but he carries the film through its toughest stretches and remained convincing all the way until the very end.
Some have criticised the film's preachiness about god/religion and its ending, but both of these things come straight from the novel. Personally, the ending was one thing about the novel that I truly loved, and I'm glad Lee decided to keep it in, though I question his decision to rely on strictly verbal storytelling as opposed to utilizing the visual. I can't say much more without giving things away so I'll stop there.
Granted, there are times when the film felt a little like a prettier version of Castaway (the one with a skinny Tom Hanks and "Wilsoooooon!") and the story occasionally felt trapped in that little lifeboat, but on the whole Life of Pi is an enchanting, poetic and visually stunning experience that's also unexpectedly moving and thought-provoking — even for someone who has read the book. Going in, I thought I'd appreciate the film's aesthetics and technical achievements more than anything else, but I was pleasantly surprised by the emotive storytelling and engrossing drama.
4.25 stars out of 5
PS: That said, I'm still not sold on the 3D, which despite my numerous vows I ended up paying extra for again — I thought only the introductory sequence with the animals, and maybe a few of the underwater scenes, were really enhanced by the 3D; the rest seemed perfectly fine in 2D to me. The extra large screen and superior sound from IMAX, on the other hand, was probably worth it.
PPS: I wonder what kind of film it would have been had M Night Shyamalan adapted and directed it, as rumoured earlier. That's not bagging Mr Airbender — I'm genuinely wondering.


text:
Vampire Music
Click Below
Amy Mah is a snarky, sarcastic and cynical author who writes of her life as a modern Vampire and whose books can be seen at: www.FangsRule.com or on Amazon her first book is self help guide called: Fangs Rule a girls guide to being a vampire from Reardon Publishing and is available as full colour paperback, Kindle; E Book. Amy also written VAMPIRE where you read of her problems of living her life as a blood chilling denizen of the night. Later this year her book on sexy Demons will be published


text:
Interior designer Jillian Harris can't resist at least one design tip casting back to her days as the star of TV's The Bachelorette. She advises a personal approach to finding pieces worth restoring.
"When you are looking for a salvage piece, it's much like trying to find a guy in a bar or a club," says the 31-year-old. "You'll just be attracted to him, and you'll know - you'll know. You'll also know if he's shady or if he's a good, solid guy. I think it's the same thing with a piece (of furniture)."
Harris is headlining the 2011 Calgary Home + Design Show, Sept. 22 to 25 at BMO Centre. She will be on the Design Stage, hosted by HGTV, presenting ideas and examples of how homeowners can transform their space while bringing out their personality. Harris is a design expert on Extreme Makeover: Home Edition and host of HGTV's new series Canada's Handyman Challenge, slated to run in January and February.
What Harris recognizes, and what makes her designs so strong, is that an old chest, painting or chair are more than just functional objects. They tie us to our memories.
"I'm attracted to pieces because of the warm fuzzies they give me inside. I'm really connected to my past and I love things that bring me happy memories," she says.
Harris surveys her small Vancouver condo for examples. A Moroccan-style stool with a herringbone, flamestitch effect reminds her of her first trips to Mexico. A stunning sketch
of a bull she bought from a Spanish street vendor while on her way to a date with Kiptyn Locke on The Bachelorette is a piece rich in memories.
Framed and matted in black for $100, it now looks like a $5,000 gallery piece.
Harris, who grew up Peace River and lived in Calgary, says we need to be brave enough to recognize who we are to make our spaces personal. And it doesn't have to cost a lot to make something look high style.
Start by judging how much effort and money a piece may take to restore.
"When you're salvaging, your piece has to have good bones," Harris says.
"If a leg is falling off, or the back is falling off, typically it's not worth the money to try to fix it. You may be able to find a different purpose for it, though."
She mentions a 1930s Louis-style cane-back chair she owns. She bartered the price for the battered and worn brown upholstered chair down to $25.
"My mom and my cousin and my aunt, who are all professional salvagers, walked right by it without batting an eye. I immediately had a vision for it." Her father helped her spray paint the frame white and
she had the seat reupholstered in a luxurious chartreuse Schumacher fabric for about $1,000. It reminds her of her grandparents.
Whether Harris is salvaging for herself or for clients, she searches for the inner beauty of a piece.
"I really do appreciate fine antiques, but what I really love is searching for something that looks like it's on the way to the dump and making it look beautiful."
Is it worth it?
Jillian Harris shares her tips for choosing decor items to restore.
- Is it worth salvaging?
Do you have the budget to do what needs to be done? Ripped fabric can be cheap to replace; refoaming and repadding a couch is expensive.
Hardware, such as knobs or hinges for a dresser or an armoire, is easily replaced.
Pass on wobbly structure, unless you are going to repurpose the piece, such as replacing a dresser's broken drawers with baskets or using drawers from a broken chest as storage units.
"If there's a reason you love it, think about what else you could do with it," Harris says.
- Knobs and other hardware
Harris's favourite source for hardware is Anthropologie.
"They have the most stunning knobs, but they are not cheap," she says. "I did a dresser last spring in Chicago that was featured on oprah.com. I did the desk for $20 and bought it for $50." But the hardware rang in at $150.
She suggests using expensive hardware on pieces you have professionally refinished. For more reasonably priced hardware, Harris turns to Target, which is opening stores in Canada and Calgary in 2013.
Sometimes it's just the details that make a piece pop. By changing out the wooden knobs to crystal knobs from Home Depot, Harris transformed an IKEA chest of drawers into a restoration hardwood piece.
You can also salvage hardware, though it's harder to find matching sets or pieces.


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Resist the urge to let anyone — even a relative — use your emery board. This tool is a porous germ-trapper. Keep yours to yourself, and replace it often.
Are you cramming your feet into too-small or too-pointy shoes? If so, your toenails may grow into the surrounding skin — causing the dreaded ingrown nail, which can lead to pain, swelling, and infection. When nails are too long, tight shoes can cause even more damage, says Mitchel P. Goldman, M.D., an associate clinical professor of dermatology at the University of California, San Diego. "If your toes hit the front of your shoe, nails can crack or turn black-and-blue. Or nails may lift, which can lead to infection."
Nails need to be hydrated, since most problems crop up when they're parched. "Dry nails can crack, peel, and become brittle. Plus, dehydrated cuticles not only look ragged but also can turn into painful and infected hangnails," says Audrey Kunin, M.D., a Kansas City, Missouri, dermatologist. The best moisturizers are thick — even greasy. Try Elizabeth Arden Eight Hour Hand Cream.
Keep your shoes on while at public places (swimming pools, locker rooms, shoe stores) — if you don't, we won't be responsible for your toenail health. Why worry? "Warm, damp environments are a breeding ground for fungi and viruses," explains Phoebe Rich, M.D., a nail disorders expert and a clinical associate professor of dermatology at Oregon Health & Science University in Portland. Tip: If hose isn't offered when you're shoe shopping, ask for it.
TLC to help nails grow
"Everyone has an individual rate at which her nails increase in length, and that can't be changed," says Paul Kechijian, M.D., a nail specialist and a former clinical associate professor of dermatology at New York University. On average, nails gain about one eighth of an inch per month. Their growth can be influenced by hormones (which is why pregnant women's nails grow like crazy) and temperature (more growth in summer than in winter). While most experts agree that there's no single food or pill that will speed nail growth, it's well-known that poor nutrition, infections, and aging can all slow it. "To keep nails healthy, hydrate them and minimize the use of harsh chemicals and tools," says Marsha Gordon, M.D., associate clinical professor of dermatology and vice chairman of the dermatology department at Mount Sinai School of Medicine. Help prevent breakage with a hardener like OPI Nail Envy
These infections can settle in without your even realizing it. To be on the safe side, says Dr. Rich of Oregon Health & Science University, you should periodically remove any polish and inspect your fingers and toes. "Fungus is contagious and can spread from one nail to another — and even from nails to skin," she explains. "These infections aren't dangerous, but they can be painful and unsightly." What to know:
Humid places are fungus favorites, which helps explain why sweaty shoes and socks make toes more susceptible than fingers. Fungal nail infections account for about 50 percent of all nail disorders, according to the American Academy of Dermatology. Untreated athlete's foot and nail injuries can also make you prone to infection.
Warning Signs
Your nail is thickening, yellowing, crumbling, or lifting from its bed (as if it's about to fall off).
The bad news: "Since the infection occurs under the nail plate or in the nail bed, successful treatment will take several months or more," says Dr. Rich, who suggests trying prescription oral medication (like Lamisil). For new or mild cases, a topical medication may help.
Wash and dry your feet thoroughly. Keep your shoes on in public places. If your feet sweat a lot, change your socks often.
"As you get older, nails grow more slowly, become more brittle, and can also develop vertical ridges," says Dr. Gordon of Mount Sinai School of Medicine. One product that helps: Sally Hansen Age Correct Strength Treatment, left, which reduces breakage by fortifying the nail; it also fills in the ridges, making them less obvious. Buffing can also smooth the surface, but be gentle so you don't thin the nail and leave it even weaker.
Can I prevent peeling, breaking and splitting?
Exposure to water is most often the culprit here — surprisingly, the more you soak, the drier the nail becomes, weakening over time. Detergents in soaps, household cleansers, and some nail polish removers can also have adverse effects. Prevent further damage by wearing rubber gloves during chores (see page 70 for winners of a GH Institute glove test). After hand-washing, apply a rich moisturizer to nails to replace the natural oils that water washes away. Using a polish (even clear) or a cuticle oil (like Creative Nail Design SolarOil) will provide a protective shield.
What's the best way to manicure my nails?
File in one direction only — sawing back and forth can cause splitting. Nails are strongest when you shape them into an oval, says Dr. Kunin of Kansas City. The pointier you make them, the likelier they are to break.
What do those tiny white marks mean?
It's a myth that these flecks indicate a vitamin deficiency. More likely, they're the result of a minor injury and will disappear as the nail grows. But watch out for dark marks. If you recently hurt your hand (say, in a car door), don't worry. But if not, and you see a black, brown, or purple band on your nail, it could be a sign of skin cancer. See a doctor right away.


text:
Major Section: OTHER
Example: ACL2 !>:good-byeNote: Your entire session will disappear forever when you type
The command
:good-bye quits not only out of the ACL2 command loop,
but in fact quits entirely out of the underlying Lisp. Thus, there
is no going back! You will not be able to re-enter the command loop
after typing
:good-bye! All your work will be lost!!!
This command may not work in some underlying Common Lisp implementations. But we don't expect there to be any harm in trying. It does work in GCL and Allegro CL, at least as of this writing.
In some systems, typing
control-d at the top-level ACL2 prompt
control-c control-d if inside emacs) will call this function.
If you merely want to exit the ACL2 command loop, use
q instead
(see q).


text:
/ Paintball Hoppers / Dye Rotor Loader (16)
When you need a loader that is both fast and reliable the Dye Rotor is the loader for you. The Dye Rotor is a hard shell loader that is designed to withstand any form of punishment in any weather condition while able to feed paintballs at 50 balls per second (BPS) consistently into your gun. Pick up a Dye Rotor for your gun and it'll be the last loader you will ever need for Paintball.


text:
Statement of Beatrice Disman
Regional Commissioner of Social Security
New York Region
Chair of the Social Security Administration
Medicare Planning and Implementation Task Force
January 31, 2007
Mr. Chairman and Members of the Committee:
Thank you for inviting me to discuss the Social Security Administration's (SSA 's) ongoing efforts under the Medicare Prescription Drug Program to sign-up eligible Medicare beneficiaries for the low-income subsidy (LIS) program, or "extra help" as it is commonly called. I am Bea Disman, and I have served for over a decade as Regional Commissioner of the New York Region. I have also spent the past 3 years at the helm of SSA 's Medicare Planning and Implementation Task Force. In this role I have seen the truly tireless and dedicated efforts of so many SSA employees, and partners within and outside government, as they have reached out to those individuals who could benefit from the low-income subsidy. It has been a remarkable experience for me, and it is with great pride that I am here to share their story with you.
In the past year, SSA has continued its intensive efforts to locate low-income Medicare beneficiaries, and provide them with an opportunity to apply for this important benefit. We have used targeted mailings, phone calls, computer data matches, community forums, partnerships with State agencies and non-profit organizations, public information fact sheets, word-of-mouth – in short, any and all means at our disposal – to reach those eligible to receive assistance with out-of-pocket costs associated with the new Medicare prescription drug coverage. Today's testimony will describe many of these efforts.
To begin, it may be helpful to recap Social Security's role and responsibilities regarding the new Medicare prescription drug coverage. This provides the context to further describe SSA's activities in getting low-income people the "extra help" intended by Congress.
As you know, the Medicare Modernization Act, or MMA, enacted in December 2003, established the new Medicare prescription drug benefit. The new Medicare prescription drug coverage was designed to allow all people with Medicare an opportunity to voluntarily enroll in prescription drug coverage. MMA also provided an additional level of assistance, or "extra help," for people with Medicare who have limited incomes and resources in helping to pay for the monthly premiums and cost-sharing that are required by the new Medicare prescription drug coverage.
The responsibility for enrolling individuals for the prescription drug coverage is a joint effort between the Department of Health and Human Services (HHS) and private insurance companies, which establish Prescription Drug Plans (PDPs) for that purpose. HHS automatically enrolled individuals who were already eligible for Medicare and full Medicaid benefits in a PDP plan and the subsidy in November 2005. This process was intended to ensure a smooth transition for these "full-benefit dual eligibles" from Medicaid drug coverage to the new Part D, and this population also had opportunities to switch to a different PDP provider than the one in which they were automatically enrolled. Additional low-income beneficiaries who also received Supplemental Security Income (SSI) or participated in certain Medicare Savings Programs (MSPs) were automatically eligible for a subsidy and enrolled into a PDP plan (if they had not already selected a plan) during May 2006.
SSA was given the responsibility by Congress to take "extra help" applications and to make eligibility determinations for individuals who were not automatically eligible. In order to be eligible for "extra help," individuals must have incomes below 150 percent of the poverty level applicable to their corresponding household size. In 2007 this is $15,315 for an individual and $20,535 for a couple. Resources must be less than $11,710 for single individuals or $23,410 for a married couple. It should be noted that both the income and resource limits adjust annually, based on the Federal Poverty Guidelines (for income) and the Consumer Price Index (for resources).
Individuals with incomes between 135 percent and 150 percent of poverty are eligible for a subsidy amount based on a sliding scale depending on their resources. Individuals with incomes below 135 percent would be eligible to receive the highest subsidies.
SSA was given these responsibilities because of its network of nearly 1,300 offices with 35,000 employees across the country, and because of its already existing role in administering some parts of the Medicare program. Over the past 70 years, SSA has gained a reputation for helping citizens in the communities where they live, and Congress realized that SSA's presence "on the ground" would be vital in the launch of the Medicare "extra help" program. Also, the low-income subsidy was designed with many similarities to SSI, a means-tested assistance program for low-income aged, blind and disabled individuals, which SSA has administered for more than 30 years.
Development of "Extra Help" Application
Upon passage of MMA, SSA immediately began planning for the implementation of the limited-income subsidy. We recognized from the onset that development of a simplified application for the "extra help" was essential for successful implementation. Thus, our goals were to develop an application that elderly and disabled Medicare beneficiaries, their caregivers, or other third party assistance providers would be able to understand and easily complete and not have to travel to a Social Security field office. SSA also wanted to maximize the use of automation, not only to process these forms efficiently, but also to process them as quickly as possible.
To accomplish these goals, SSA conducted substantial testing of the "extra help" application form. The paper application went through many drafts before being finalized. Social Security, in collaboration with the Centers for Medicare & Medicaid Services (CMS), conducted focus groups with current Medicare beneficiaries to test potential applicants' understanding of the application, conducted special cognitive testing of the application and had design engineers review the layout of the applications. We also discussed various draft versions of the application with national and local advocacy groups and with State Medicaid Directors, as well as with Congressional staffs.
Our Office of Systems staff contributed to the design of the application as well to make sure that the information on the form could be electronically scanned into our computers, thereby reducing errors and minimizing the number of employees needed to process incoming applications.
Realizing the need to reach our beneficiaries in new ways, SSA worked to develop alternatives to the traditional paper-based application. In July 2005, we unveiled the Internet version of the application located at www.socialsecurity.gov, allowing people to apply online for help with Medicare Prescription Drug Plan costs. The online application has been a tremendous success, receiving one of the highest scores ever given to a public or private sector organization by the American Customer Satisfaction Index (ACSI).
The percentage of "extra help" applications we receive through Internet filing continues to rise. Over the last 4 months, about 20 percent of new applications are Internet filings. This means that, as a percentage of applications received, the online "extra help" application has even exceeded the success of SSA's online Application for Retirement benefits.
Telephone inquiries were also part of our efforts to make the "extra help" application process as simple as possible. We provided extensive training to assist our teleservice representatives in answering subsidy-related questions. These teleservice representatives can refer callers directly to specialized claims-taking employees who could then take applications by phone. This process allows individuals calling our 1-800 number to immediately file for the "extra help."
Social Security developed a computer matching process with the Internal Revenue Service (IRS) regarding the validation of certain income and resource information provided by applicants. This process was designed to reduce one of the barriers often cited as to why individuals do not file for means-testing programs. Using this computer match allowed SSA to build an application process that would not require applicants to submit proof of resources and income, as long as the applicant's statement on the application was in substantial agreement with the computer records.
In summary, although subsidy eligibility determinations are by their very nature complex, we believe that we have created a simple application process, which allows individuals to apply for the "extra help" as quickly and easily as possible, while also taking advantage of current technology.
I would also note that efforts to improve the "extra help" application are ongoing. In recent months, for example, we have added fields to the paper application that allow the applicant to enter the amount of his or her Social Security benefit. Of course SSA already knows this information, and the original application instructions stated that the applicant did not need to supply Social Security benefit amounts. But our analysis of applications received showed that applicants were trying to enter the information anyway, and this was frequently leading to inaccurate application entries and inaccurate eligibility determinations. In another update, for example, we simplified the question about filing as a couple and changed the resource amounts to reflect the 2007 resource limits.
Outreach Efforts
I would now like to turn to the efforts SSA has undertaken to inform beneficiaries about the "extra help" available for prescription drugs. Efforts to educate the public about the new, "extra help" program began almost immediately after passage of MMA, and this outreach continues today. SSA has worked with CMS and other Federal agencies, community based organizations, advocacy groups, and State entities in order to spread the word about the available "extra help."
During the past two years, SSA has held more than 76,000 Medicare outreach events. We were in the communities – in senior citizen centers, pharmacies, public housing, churches – any place in which we thought senior citizens or the disabled were likely to be found. Targeted application-taking events were held in Social Security offices throughout the country, and personal invitations to these events were mailed to beneficiaries who had not yet applied for the "extra help," but had been identified as being potentially eligible for the program.
We also continue to work with States that have their own pharmaceutical assistance programs, State Health Insurance Programs, Area Agencies on Aging, local housing authorities, community health clinics, PDPs, and others to identify people with limited income and resources who may be eligible for the "extra help."
Throughout these efforts, SSA 's goal has been to reach every potentially eligible Medicare beneficiary multiple times, in a variety of ways: for example, by targeted mailings and events, and follow-up phone calls. And while we are confident we have taken appropriate steps to reach out to those who may be eligible for the "extra help," our outreach efforts are continuing. Because there is no enrollment period for the "extra help," a Medicare beneficiary can apply at any time. This means there is no inappropriate time to reach out to our lower-income beneficiaries, and there is no wrong time for these individuals to complete an application.
As you know, many estimates have been made as to the size of the eligible population. But whether there are 300 or 3 million people, SSA 's job is the same – find them. Find them where they live, find them in the communities where they work, find them in any way we can. Our message is simple: if you could possibly benefit from this program, SSA will help you apply.
Mailing of Subsidy Applications and Targeted Outreach
To further explain how this outreach philosophy has translated into action, I would now like to describe some of the specific routes SSA has taken to reach our lower-income Medicare beneficiaries.
Although the new Medicare prescription drug coverage did not begin until January 2006, SSA began mailing applications to individuals who were potentially eligible for "extra help" in May 2005. During the following three months, we mailed almost 19 million applications. Our goal was to have as many potentially eligible limited income Medicare beneficiaries as possible file for the "extra help" before the Medicare prescription drug program started in January 2006.
We also intended to cast the widest net possible in our efforts to reach the public. Thus, we sent the 19 million applications to potentially eligible individuals, even though we knew that not all of this group would meet the income and resource requirements. Social Security was only able to use certain data bases to screen the Medicare population to identify potential eligible individuals who had income below 150% of the Federal poverty level. This initial effort allowed us to begin making eligibility determinations for the "extra help" as early as July 2005.
Just as important as the initial mailing of applications was follow-up contacts with those individuals who did not return them. We contracted with a vendor to remind individuals of the availability of the "extra help" program and to ask if they needed assistance. Of the 9.1 million people who were called by the vendor, 800,000 asked that we resend applications, and nearly 400,000 requested assistance and were referred to SSA. In addition, 5 million follow-up notices were sent because the vendor could not locate a phone number for the individual (for example, an individual who was displaced by Hurricane Katrina).
We continue to use Agency mailings to inform the public. For example, the cost of living adjustment notice sent in November 2005 and again in November 2006 to over 50 million Social Security beneficiaries, each time, contained information about the new drug program and the availability of "extra help." In May 2006, our annual notice to individuals potentially eligible for Medicare Savings Programs provided "extra help" information to 5.7 million beneficiaries.
Also, SSA identified approximately 1.5 million disability beneficiaries who received an "extra help" application mailer, but did not file an application. We mailed a special follow-up notice to these beneficiaries between March 16 and April 11, 2006, explaining to beneficiaries that they may be eligible for the subsidy, and assuring them that this would not have an adverse effect on their disability benefits.
In addition, we personally called over 300,000 beneficiaries, who did not respond to an "extra help" application mailer, but had previously applied for and received the $600 assistance under the Medicare drug discount card, to offer help in completing the "extra help" application.
Targeted advertising efforts have been coordinated with national organizations, such as AARP, and targeted outreach events have been conducted with state organizations such as the Elderly Pharmaceutical Insurance Coverage (EPIC) program in New York .
In additional efforts to reach specific communities, SSA has undertaken targeted mailings to beneficiaries with representative payees, beneficiaries who speak Spanish, Asian-American and African-American households, and beneficiaries age 79 and older who lived in zip codes with a high percentage of low income households. During the period of June through August, 2006, 2.5 million "extra help" applications were mailed to these individuals.
SSA has also made a special effort to reach and reenroll those "extra help" recipients who have lost "deemed" or automatically eligible status. As I previously described, some individuals received the subsidy automatically, by virtue of Medicaid, SSI or MSP eligibility. In some cases, however, these individuals lose eligibility to these other programs, and thus their deemed status. Working with the CMS, in September 2006, SSA mailed more than 600,000 applications with notices to Medicare beneficiaries who were no longer automatically eligible for "extra help." To date, more than 230,000 of these people have reapplied. This is in addition to a number of individuals who have regained automatic eligibility through reentitlement to certain State programs. Social Security has just started a pilot to personally call 10,000 of these individuals who have lost their deemed status and have not filed for "extra help." The results of the pilot will guide our approach in following up with the rest of this population.
In addition to the many specific outreach activities SSA has performed in the past year, the agency also provides educational outreach to Medicare attainers – those current Social Security beneficiaries who turn 65 or reach the 25 th month of their disability. If our records indicate an attainer may potentially be eligible for "extra help," SSA sends an application. This means between 120,000 – 130,000 beneficiaries receive LIS applications every month. Similarly, many individuals call our 800 number or visit our field offices to conduct traditional Social Security business. We educate these individuals about the "extra help," and we will take the application if it is appropriate.
Continuing Success
As of mid January 2007, SSA has received applications from almost 6.1 million beneficiaries, of which almost 1 million were unnecessary, because either the applicants were automatically eligible or because they had filed more than one application. We have made over 5.9 million determinations on the eligibility for "extra help" and have now found more than 2.3 million of these individuals eligible.
Generally, SSA continues to receive between 30,000 – 40,000 applications for "extra help" every week – almost 600 thousand since the beginning of the fiscal year. This continued level of interest from beneficiaries – this unexpectedly high amount of applications received more than one year beyond the program's launch – tells us our outreach campaign is working.
While SSA has no direct role in assisting individuals in either selecting or enrolling in PDPs, we have provided instructions to the field offices on how to make sure those with questions on the new Medicare prescription drug coverage are directed to the resources they need. In some cases this means our employees will simply refer the questioner to 1-800-MEDICARE, or to the beneficiary's PDP provider, but in other cases it means making a personal call to state coordinators, reprinting and faxing award notices, and even making emergency calls to CMS Regional Offices.
SSA employees across the country are continuing to promote this valuable benefit. Our job is not completed, and we continue to look for more ways to reach those eligible for the "extra help" program.
In conclusion, I want to express my personal thanks, to this Committee for your continuing support for the Agency. As you know, SSA is operating under a continuing resolution, with funding levels significantly below the President's request. Moreover, the separate funding pool that the Congress authorized under MMA during the prescription drug program's start-up period no longer exists.
This situation means that "extra help" outreach has to be handled along with all of SSA's other vital workloads – such as the taking of retirement and disability claims. However, I can tell you from my own experience, that the dedicated employees of SSA will continue to do our very best, not only in administering the low-income subsidy and premium withholding for the Medicare prescription drug program, but also in providing our very important traditional services to the American public.
We look forward to our continued dialogue with organizations, advocacy groups, and of course, this Committee, as we progress with "extra help" program efforts.
Thank you and I will be glad to answer any questions you may have.


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Displaying pictures of your children makes your house feel like a home. At Rooms To Go, we know that a good picture needs to be encapsulated in a quality frame. We offer a selection of picture frames that will delightfully display your fond memories and add a little flair to the room.
The right style frame can magnify a photo's mood and personality. With a number of styles, our inventory offers kids picture frames that can match the mood of a photo or a room's decor. Many of our kids picture frames feature classic designs and muted blues, greens, and reds. For baby pictures, we offer picture frames that come in pastel blues and pinks and feature elegant, tasteful designs. Some of our more extravagant picture frames include wild, multi-color prints or stark black and white designs. For Disney lovers, we offer picture frames that feature your favorite animated characters.
Frame your photos in style with our kids picture frames. Whether you want flashy picture frames for kids artwork, bright and cheerful frames for lively snapshots, or simple, tasteful frames for your most prized memories, we have the right frame for you at Rooms To Go. Browse through our selection and find children's picture frames that are perfect for your memories.


text:
Characterizing quality for science data products
Characterizing quality for a science data product is hard. We have been working on this issue in our Multi-Sensor Data Synergy Advisor (MDSA) project with Greg Leptoukh and Chris Lynnes from the NASA Goddard Space Flight Center (GSFC). The following is my opinion on what product quality means and how it can be characterized. This work was presented as a poster at the AGU FM 2011 meeting.
Science product quality is hard to define, characterize, and act upon. Product quality reflects a comparison against standard products of a similiar kind, but it is also reflective of the fitness-for-use of the product for the end-user. Users weigh quality characteristics (e.g. accuracy, completeness, coverage, consistency, representativeness) based on their intended use for the data, and therefore quality of a product can be different based on different users' needs and interests. Despite the subjective nature of quality assertions, and their sensitivity to users fitness-for-use, most quality information is provided by the product producer and the subjective criteria used to determine quality is opaque, if available at all.
If users are given product quality information at all, this information usually comes in one of two forms:
- tech reports where extensive statistical analysis is reported on very specific characteristics of the product
- in the form of subjective and unexplained statements such as 'good', 'marginal', 'bad'.
This is either information overload that is not easy for the user to quickly assess or a near lack of the type of information that a user needs to make their own subjective quality assessment.
Is there a smilar scenario in common-day life where users are presented with quality information that they can readily understand and act upon?
There is, and you see it every day in the supermarket.
Nutrition Facts labels provide nutrition per serving information (e.g. amount of Total Fat, Total Carbohydrates, Protein) and how the the listed amounts per serving compare to a perspective daily diet.
The comparison to a standard 2,000 calorie diet provides the user with a simple assessment tool for the usefulness of food item in their unique diet. Quality assertions, such as whether this food is 'good', or 'bad' for the consumer's diet are left to the consumer – but are relatively easy to make with the available information.
A 'quality facts' label for a scientific data product, showing computed values for community-recognized quality indicators, would go a long way towards enabling a nutrition label-like presentation of quality that is easy for science users to consume and act upon.
We have begun working on mockups of what such a presentation of quality could look like, and have constructed a basic quality model that would allow us to express in RDF the information that would be used to construct a quality facts label.
Our quality model primer presents our high-level quality model and its application to an aerosol satellite data product in detail.
Our poster presentation was a hit at AGU, where we received a great deal of positive feedback on it. This nutrition label-like presentation is immediately familiar, and supports the metaphor of science users 'shopping' for the best data product to fit their needs.
We still have a long way to go on developing our presentation, but the feedback from discussions at AGU tells me that our message resonated with our intended audience.