Implicit Simulations using Messaging Protocols

A novel algorithm for performing parallel, distributed computer simulations on the Internet using IP control messages is introduced. The algorithm employs carefully constructed ICMP packets which enable the required computations to be completed as part of the standard IP communication protocol. After providing a detailed description of the algorithm, experimental applications in the areas of stochastic neural networks and deterministic cellular automata are discussed. As an example of the algorithms potential power, a simulation of a deterministic cellular automaton involving 10^5 Internet connected devices was performed.Comment: 14 pages, 3 figure

The Relative Power of Employment-to-Employment Reallocation and Unemployment Exits in Predicting Wage Growth

We study the cyclical comovement nominal wage growth (either monthly earnings or hourly wage rate) and labor market flows. We use microdata from the Survey of Income and Program Participation over 1996-2013 to purge composition effects in worker and job characteristics and to isolate the reallocative effect of Employer-to-Employer (EE) transitions. We find an "EE wage Phillips curve": wage inflation comoves positively with EE as strongly as with the employment rate. This correlation holds for job stayers; we interpret the EE rate as a measure of labor demand. We find no analogous evidence for the job-finding rate from unemployment

Wage Posting and Business Cycles

The canonical framework of Burdett and Mortensen (1998) derives wage dispersion as the unique equilibrium outcome in a stationary environment with meeting frictions and random search. Firms derive monopsony power from search frictions and commit to wage offers. Workers earn rents: wages are not compressed to the opportunity cost of work, owing to the ability of employed workers to receive additional offers and quit directly from one job into another, without experiencing unemployment. In previous work (Moscarini and Postel-Vinay 2016), we explored the implications of this job ladder for the aggregate dynamics of unemployment, wages, and the firm size distribution at business cycle frequencies. The model establishes a natural connection between the average wage growth in the economy and the pace of Employer-to-Employer (EE) transitions, through two channels. First, a composition effect: workers typically quit a job when they receive a better offer, hence the faster these transitions the higher the pace of reallocation toward high wages, and the higher average wage growth. Second, a strategic effect: the more opportunities workers have to quit, the more aggressive are their employers with their wage responses, to try and retain them. The first effect benefits only job movers, the second both movers and stayers. Therefore, we expect wage growth to be positively related to the pace of EE reallocation for all workers, but especially for movers. We verify this empirically with longitudinal micro data from the Survey of Income and Program Participation (SIPP)

River Restoration in the Twenty-First Century: Data and Experiential Knowledge to Inform Future Efforts

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71999/1/j.1526-100X.2007.00243.x.pd

Adherence to Blended or Face-to-Face Smoking Cessation Treatment and Predictors of Adherence:Randomized Controlled Trial

Background: Blended face-to-face and web-based treatment is a promising way to deliver smoking cessation treatment. Since adherence has been shown to be an indicator of treatment acceptability and a determinant for effectiveness, we explored and compared adherence and predictors of adherence to blended and face-to-face alone smoking cessation treatments with similar content and intensity. Objective: The objectives of this study were (1) to compare adherence to a blended smoking cessation treatment with adherence to a face-to-face treatment; (2) to compare adherence within the blended treatment to its face-to-face mode and web mode; and (3) to determine baseline predictors of adherence to both treatments as well as (4) the predictors to both modes of the blended treatment. Methods: We calculated the total duration of treatment exposure for patients (N=292) of a Dutch outpatient smoking cessation clinic who were randomly assigned either to the blended smoking cessation treatment (n=130) or to a face-to-face treatment with identical components (n=162). For both treatments (blended and face-to-face) and for the two modes of delivery within the blended treatment (face-to-face vs web mode), adherence levels (ie, treatment time) were compared and the predictors of adherence were identified within 33 demographic, smoking-related, and health-related patient characteristics. Results: We found no significant difference in adherence between the blended and the face-to-face treatments. Participants in the blended treatment group spent an average of 246 minutes in treatment (median 106.7% of intended treatment time, IQR 150%-355%) and participants in the face-to-face group spent 238 minutes (median 103.3% of intended treatment time, IQR 150%-330%). Within the blended group, adherence to the face-to-face mode was twice as high as that to the web mode. Participants in the blended group spent an average of 198 minutes (SD 120) in face-to-face mode (152% of the intended treatment time) and 75 minutes (SD 53) in web mode (75% of the intended treatment time). Higher age was the only characteristic consistently found to uniquely predict higher adherence in both the blended and face-to-face groups. For the face-to-face group, more social support for smoking cessation was also predictive of higher adherence. The variability in adherence explained by these predictors was rather low (blended R-2 =0.049; face-to-face R-2 =0.076). Within the blended group, living without children predicted higher adherence to the face-to-face mode (R-2 =0.034), independent of age. Higher adherence to the web mode of the blended treatment was predicted by a combination of an extrinsic motivation to quit, a less negative attitude toward quitting, and less health complaints (R-2 =0.164). Conclusions: This study represents one of the first attempts to thoroughly compare adherence and predictors of adherence of a blended smoking cessation treatment to an equivalent face-to-face treatment. Interestingly, although the overall adherence to both treatments appeared to be high, adherence within the blended treatment was much higher for the face-to-face mode than for the web mode. This supports the idea that in blended treatment, one mode of delivery can compensate for the weaknesses of the other. Higher age was found to be a common predictor of adherence to the treatments. The low variance in adherence predicted by the characteristics examined in this study suggests that other variables such as provider-related health system factors and time-varying patient characteristics should be explored in future research

Comparative analysis of tunisian sheep-like virus, bungowannah virus and border disease virus infection in the porcine host

Apart from the established pestivirus species Pestivirus A to Pestivirus K novel species emerged. Pigs represent not only hosts for porcine pestiviruses, but are also susceptible to bovine viral diarrhea virus, border disease virus (BDV) and other ruminant pestiviruses. The present study focused on the characterization of the ovine Tunisian sheep-like virus (TSV) as well as Bungowannah virus (BuPV) and BDV strain Frijters, which were isolated from pigs. For this purpose, we performed genetic characterization based on complete coding sequences, studies on virus replication in cell culture and in domestic pigs, and cross-neutralization assays using experimentally derived sera. TSV forms a distinct phylogenetic group more closely related to Pestivirus C (classical swine fever virus, CSFV) than to Pestivirus D (BDV). In contrast to BDV and BuPV, TSV replicates by far more efficiently on ovine than on porcine cells. Nevertheless, pigs were susceptible to TSV. As a consequence of close antigenic relatedness of TSV to CSFV, cross-reactivity was detected in CSFV-specific antibody assays. In conclusion, TSV is genetically closely related to CSFV and can replicate in domestic pigs. Due to close antigenic relatedness, field infections of pigs with TSV and other ruminant pestiviruses can interfere with serological diagnosis of classical swine fever

Web-based intensive therapeutic contact for eating disorders

Contains fulltext : 121984.pdf (publisher's version ) (Open Access)Although many people suffer from eating disorders, which have high mortality and severe morbidity, only a small number of affected people in the Netherlands are treated by mental health professionals. Eating disorders are often not recognized. Many patients do not ask for help because of shame, a lack of awareness, or denial of the disorder. Even when the disorder is recognized, it is difficult to motivate patients to seek help. As a result, many patients are in urgent need of help.1 p

Adherence to Blended or Face-to-Face Smoking Cessation Treatment and Predictors of Adherence:Randomized Controlled Trial

Background: Blended face-to-face and web-based treatment is a promising way to deliver smoking cessation treatment. Since adherence has been shown to be an indicator of treatment acceptability and a determinant for effectiveness, we explored and compared adherence and predictors of adherence to blended and face-to-face alone smoking cessation treatments with similar content and intensity.Objective: The objectives of this study were (1) to compare adherence to a blended smoking cessation treatment with adherence to a face-to-face treatment; (2) to compare adherence within the blended treatment to its face-to-face mode and web mode; and (3) to determine baseline predictors of adherence to both treatments as well as (4) the predictors to both modes of the blended treatment.Methods: We calculated the total duration of treatment exposure for patients (N=292) of a Dutch outpatient smoking cessation clinic who were randomly assigned either to the blended smoking cessation treatment (n=130) or to a face-to-face treatment with identical components (n=162). For both treatments (blended and face-to-face) and for the two modes of delivery within the blended treatment (face-to-face vs web mode), adherence levels (ie, treatment time) were compared and the predictors of adherence were identified within 33 demographic, smoking-related, and health-related patient characteristics.Results: We found no significant difference in adherence between the blended and the face-to-face treatments. Participants in the blended treatment group spent an average of 246 minutes in treatment (median 106.7% of intended treatment time, IQR 150%-355%) and participants in the face-to-face group spent 238 minutes (median 103.3% of intended treatment time, IQR 150%-330%). Within the blended group, adherence to the face-to-face mode was twice as high as that to the web mode. Participants in the blended group spent an average of 198 minutes (SD 120) in face-to-face mode (152% of the intended treatment time) and 75 minutes (SD 53) in web mode (75% of the intended treatment time). Higher age was the only characteristic consistently found to uniquely predict higher adherence in both the blended and face-to-face groups. For the face-to-face group, more social support for smoking cessation was also predictive of higher adherence. The variability in adherence explained by these predictors was rather low (blended R2=0.049; face-to-face R2=0.076). Within the blended group, living without children predicted higher adherence to the face-to-face mode (R2=0.034), independent of age. Higher adherence to the web mode of the blended treatment was predicted by a combination of an extrinsic motivation to quit, a less negative attitude toward quitting, and less health complaints (R2=0.164).Conclusions: This study represents one of the first attempts to thoroughly compare adherence and predictors of adherence of a blended smoking cessation treatment to an equivalent face-to-face treatment. Interestingly, although the overall adherence to both treatments appeared to be high, adherence within the blended treatment was much higher for the face-to-face mode than for the web mode. This supports the idea that in blended treatment, one mode of delivery can compensate for the weaknesses of the other. Higher age was found to be a common predictor of adherence to the treatments. The low variance in adherence predicted by the characteristics examined in this study suggests that other variables such as provider-related health system factors and time-varying patient characteristics should be explored in future research

Stellar models and isochrones from low-mass to massive stars including pre-main sequence phase with accretion

Grids of stellar models are useful tools to derive the properties of stellar clusters, in particular young clusters hosting massive stars, and to provide information on the star formation process in various mass ranges. Because of their short evolutionary timescale, massive stars end their life while their low-mass siblings are still on the pre-main sequence (pre-MS) phase. Thus the study of young clusters requires consistent consideration of all the phases of stellar evolution. But despite the large number of grids that are available in the literature, a grid accounting for the evolution from the pre-MS accretion phase to the post-MS phase in the whole stellar mass range is still lacking. We build a grid of stellar models at solar metallicity with masses from 0.8 $M_\odot$ to 120 $M_\odot$, including pre-MS phase with accretion. We use the {\sc genec} code to run stellar models on this mass range. The accretion law is chosen to match the observations of pre-MS objects on the Hertzsprung-Russell diagram. We describe the evolutionary tracks and isochrones of our models. The grid is connected to previous MS and post-MS grids computed with the same numerical method and physical assumptions, which provides the widest grid in mass and age to date. Numerical tables of our models and corresponding isochrones are available online