Election Verifiability for Helios under Weaker Trust Assumptions

Most electronic voting schemes aim at providing verifiability: voters should trust the result without having to rely on some authorities. Actually, even a prominent voting system like Helios cannot fully achieve verifiability since a dishonest bulletin board may add ballots. This problem is called ballot stuffing. In this paper we give a definition of verifiability in the computational model to account for a malicious bulletin board that may add ballots. Next, we provide a generic construction that transforms a voting scheme that is verifiable against an honest bulletin board and an honest registration authority (weak verifiability) into a verifiable voting scheme under the weaker trust assumption that the registration authority and the bulletin board are not simultaneously dishonest (strong verifiability). This construction simply adds a registration authority that sends private credentials to the voters, and publishes the corresponding public credentials. We further provide simple and natural criteria that imply weak verifiability. As an application of these criteria, we formally prove the latest variant of Helios by Bernhard, Pereira and Warinschi weakly verifiable. By applying our generic construction we obtain a Helios-like scheme that has ballot privacy and strong verifiability (and thus prevents ballot stuffing). The resulting voting scheme, Helios-C, retains the simplicity of Helios and has been implemented and tested

Vortex Plastic Flow, B(x,y,H(t)),M(H(t)),Jc(B(t))B(x,y,H(t)), M(H(t)), J_c(B(t)), Deep in the Bose Glass and Mott-Insulator Regimes

We present simulations of flux-gradient-driven superconducting vortices interacting with strong columnar pinning defects as an external field $H(t)$ is quasi-statically swept from zero through a matching field $B_{\phi}$. We analyze several measurable quantities, including the local flux density $B(x,y,H(t))$, magnetization $M(H(t))$, critical current $J_{c}(B(t))$, and the individual vortex flow paths. We find a significant change in the behavior of these quantities as the local flux density crosses $B_{\phi}$, and quantify it for many microscopic pinning parameters. Further, we find that for a given pin density $J_c(B)$ can be enhanced by maximizing the distance between the pins for $B < B_{\phi}$.Comment: 4 pages, 4 PostScript Figure

Exposure Assessment Techniques Applied to the Highly Censored Deepwater Horizon Gulf Oil Spill Personal Measurements

The GuLF Long-term Follow-up Study (GuLF STUDY) is investigating potential adverse health effects of workers involved in the Deepwater Horizon (DWH) oil spill response and cleanup (OSRC). Over 93% of the 160 000 personal air measurements taken on OSRC workers were below the limit of detection (LOD), as reported by the analytic labs. At this high level of censoring, our ability to develop exposure estimates was limited. The primary objective here was to reduce the number of measurements below the labs' reported LODs to reflect the analytic methods' true LODs, thereby facilitating the use of a relatively unbiased and precise Bayesian method to develop exposure estimates for study exposure groups (EGs). The estimates informed a job-exposure matrix to characterize exposure of study participants. A second objective was to develop descriptive statistics for relevant EGs that did not meet the Bayesian criteria of sample size ≥5 and censoring ≤80% to achieve the aforementioned level of bias and precision. One of the analytic labs recalculated the measurements using the analytic method's LOD; the second lab provided raw analytical data, allowing us to recalculate the data values that fell between the originally reported LOD and the analytical method's LOD. We developed rules for developing Bayesian estimates for EGs with >80% censoring. The remaining EGs were 100% censored. An order-based statistical method (OBSM) was developed to estimate exposures that considered the number of measurements, geometric standard deviation, and average LOD of the censored samples for N ≥ 20. For N 80% but enough non-censored measurements to apply Bayesian methods. We used the OBSM for 3% of the estimates and the simple substitution method for 11%. The methods presented here substantially reduced the degree of censoring in the dataset and increased the number of EGs meeting our Bayesian method's desired performance goal. The OBSM allowed for a systematic and consistent approach impacting only the lowest of the exposure estimates. This approach should be considered when dealing with highly censored datasets

Modeled Air Pollution from In Situ Burning and Flaring of Oil and Gas Released Following the Deepwater Horizon Disaster

The GuLF STUDY, initiated by the National Institute of Environmental Health Sciences, is investigating the health effects among workers involved in the oil spill response and clean-up (OSRC) after the Deepwater Horizon (DWH) explosion in April 2010 in the Gulf of Mexico. Clean-up included in situ burning of oil on the water surface and flaring of gas and oil captured near the seabed and brought to the surface. We estimated emissions of PM2.5 and related pollutants resulting from these activities, as well as from engines of vessels working on the OSRC. PM2.5 emissions ranged from 30 to 1.33e6 kg per day and were generally uniform over time for the flares but highly episodic for the in situ burns. Hourly emissions from each source on every burn/flare day were used as inputs to the AERMOD model to develop average and maximum concentrations for 1-, 12-, and 24-h time periods. The highest predicted 24-h average concentrations sometimes exceeded 5000 μg m-3 in the first 500 m downwind of flaring and reached 71 μg m-3 within a kilometer of some in situ burns. Beyond 40 km from the DWH site, plumes appeared to be well mixed, and the predicted 24-h average concentrations from the flares and in situ burns were similar, usually below 10 μg m-3. Structured averaging of model output gave potential PM2.5 exposure estimates for OSRC workers located in various areas across the Gulf. Workers located nearest the wellhead (hot zone/source workers) were estimated to have a potential maximum 12-h exposure of 97 μg m-3 over the 2-month flaring period. The potential maximum 12-h exposure for workers who participated in in situ burns was estimated at 10 μg m-3 over the ~3-month burn period. The results suggest that burning of oil and gas during the DWH clean-up may have resulted in PM2.5 concentrations substantially above the U.S. National Ambient Air Quality Standard for PM2.5 (24-h average = 35 μg m-3). These results are being used to investigate possible adverse health effects in the GuLF STUDY epidemiologic analysis of PM2.5 exposures

Using Real-Time Area VOC Measurements to Estimate Total Hydrocarbons Exposures to Workers Involved in the Deepwater Horizon Oil Spill

Even though the Deepwater Horizon oil spill response and clean-up (OSRC) had one of the largest exposure monitoring efforts of any oil spill, a number of exposure groups did not have sufficient personal data available or there were gaps in days measured to adequately characterize exposures for the GuLF STUDY, an epidemiologic study investigating the health of the OSRC workers. Area measurements were available from real-time air monitoring instruments and used to supplement the personal exposure measurements. Objectives: The objective was to present a method that used real-time volatile organic compounds (VOCs) area measurements transformed to daily total hydrocarbons (THC) time-weighted averages (TWAs) to supplement THC personal full-shift measurements collected using passive charcoal badges. A second objective was to develop exposure statistics using these data for workers on vessels piloting remotely operated vehicle (ROV) vessels and other marine vessels (MVs) not at the job title level, but at the vessel level. Methods: From hourly vessel averages derived from ~26 million real-time VOC measurements, we estimated full-shift VOC TWAs. Then, we determined the relationship between these TWAs and corresponding full-shift THC personal measurements taken on the same vessel-day. We used this relationship to convert the full-shift VOC measurements to full-shift 'THC' TWA estimates when no personal THC measurements existed on a vessel-day. We then calculated arithmetic means (AMs) and other statistics of THC exposures for each vessel. Results: The VOC-derived estimates substantially supplemented the THC personal measurements, with the number of vessel-days for which we have exposure estimates increasing by ~60%. The estimates of the AMs are some of the highest observed in the GuLF STUDY. As expected, the AMs decreased over time, consistent with our findings on other vessels. Conclusions: Despite the inherent limitations of using real-time area measurements, we were able to develop additional daily observations of personal THC exposures for workers on the ROV vessels and other MVs over time. The estimates likely resulted in more representative estimates of the AMs in the GuLF STUDY. The method used here can be applied in other occupational settings and industries for personal exposure estimation where large amounts of area measurements and more limited numbers of personal measurements are available

Methods for the Analysis of 26 Million VOC Area Measurements during the Deepwater Horizon Oil Spill Clean-up

The NIEHS GuLF STUDY is an epidemiologic study of the health of workers who participated in the 2010 Deepwater Horizon oil spill response and clean-up effort. Even with a large database of approximately 28 000 personal samples that were analyzed for total hydrocarbons (THCs) and other oil-related chemicals, resulting in nearly 160 000 full-shift personal measurements, there were still exposure scenarios where the number of measurements was too limited to rigorously assess exposures. Also available were over 26 million volatile organic compounds (VOCs) area air measurements of approximately 1-min duration, collected from direct-reading instruments on 38 large vessels generally located near the leaking well. This paper presents a strategy for converting the VOC database into hourly average air concentrations by vessel as the first step of a larger process designed to use these data to supplement full-shift THC personal exposure measurements. We applied a Bayesian method to account for measurements with values below the analytic instrument's limit of detection while processing the large database into average instrument-hour concentrations and then hourly concentrations across instruments on each day of measurement on each of the vessels. To illustrate this process, we present results on the drilling rig ship, the Discoverer Enterprise. The methods reduced the 26 million measurements to 21 900 hourly averages, which later contributed to the development of additional full-shift THC observations. The approach used here can be applied by occupational health professionals with large datasets of direct-reading instruments to better understand workplace exposures

Development of a total hydrocarbon ordinal job-exposure matrix for workers responding to the Deepwater Horizon disaster: The GuLF STUDY

The GuLF STUDY is a cohort study investigating the health of workers who responded to the Deepwater Horizon oil spill in the Gulf of Mexico in 2010. The objective of this effort was to develop an ordinal job-exposure matrix (JEM) of airborne total hydrocarbons (THC), dispersants, and particulates to estimate study participants' exposures. Information was collected on participants' spill-related tasks. A JEM of exposure groups (EGs) was developed from tasks and THC air measurements taken during and after the spill using relevant exposure determinants. THC arithmetic means were developed for the EGs, assigned ordinal values, and linked to the participants using determinants from the questionnaire. Different approaches were taken for combining exposures across EGs. EGs for dispersants and particulates were based on questionnaire responses. Considerable differences in THC exposure levels were found among EGs. Based on the maximum THC level participants experienced across any job held, 1/414% of the subjects were identified in the highest exposure category. Approximately 10% of the cohort was exposed to dispersants or particulates. Considerable exposure differences were found across the various EGs, facilitating investigation of exposure-response relationships. The JEM is flexible to allow for different assumptions about several possibly relevant exposure metrics

Exposure Group Development in Support of the NIEHS GuLF Study

In the GuLF Study, a study investigating possible adverse health effects associated with work on the oil spill response and clean-up (OSRC) following the Deepwater Horizon disaster in the Gulf of Mexico, we used a job-exposure matrix (JEM) approach to estimate exposures. The JEM linked interview responses of study participants to measurement data through exposure groups (EGs). Here we describe a systematic process used to develop transparent and precise EGs that allowed characterization of exposure levels among the large number of OSRC activities performed across the Gulf of Mexico over time and space. EGs were identified by exposure determinants available to us in our measurement database, from a substantial body of other spill-related information, and from responses provided by study participants in a detailed interview. These determinants included: job/activity/task, vessel and type of vessel, weathering of the released oil, area of the Gulf of Mexico, Gulf coast state, and time period. Over 3000 EGs were developed for inhalation exposure and applied to each of 6 JEMs of oil-related substances (total hydrocarbons, benzene, toluene, ethylbenzene, total xylene, and n-hexane). Subsets of those EGs were used for characterization of exposures to dispersants, particulate matter, and oil mist. The EGs allowed assignment to study participants of exposure estimates developed from measurement data or from estimation models through linkage in the JEM for the investigation of exposure-response relationships

Estimates of Inhalation Exposures to Oil-Related Components on the Supporting Vessels During the Deepwater Horizon Oil Spill

The Deepwater Horizon oil spill response and clean-up (OSRC) involved over 9000 large and small vessels deployed in waters of the Gulf of Mexico across four states (Alabama, Florida, Louisiana, and Mississippi). For the GuLF STUDY, we developed exposure estimates of oil-related components for many work groups to capture a wide range of OSRC operations on these vessels, such as supporting the four rig vessels charged with stopping the spill at the wellhead; skimming oil; in situ burning of oil; absorbing and containing oil by boom; and environmental monitoring. Work groups were developed by: (i) vessel activity; (ii) location (area of the Gulf or state); and (iii) time period. Using Bayesian methods, we computed exposure estimates for these groups for: total hydrocarbons measured as total petroleum hydrocarbons (THC), benzene, toluene, ethylbenzene, xylene, and n-hexane (BTEX-H). Estimates of the arithmetic means for THC ranged from 0.10 ppm [95% credible interval (CI) 0.04, 0.38 ppm] in time periods 2 and 3 (16 July-30 September 2010) to 15.06 ppm (95% CI 10.74, 22.41 ppm) in time period 1a (22 April-15 May 2010). BTEX-H estimates were substantially lower (in the parts per billion range). Exposure levels generally fell over time and differed statistically by activity, location, and time for some groups. These exposure estimates have been used to develop job-exposure matrices for the GuLF STUDY

Estimates of Inhalation Exposures among Land Workers during the Deepwater Horizon Oil Spill Clean-up Operations

Following the Deepwater Horizon oil spill disaster, thousands of workers and volunteers cleaned the shoreline across four coastal states of the Gulf of Mexico. For the GuLF STUDY, we developed quantitative estimates of oil-related chemical exposures [total petroleum hydrocarbons (THC), benzene, toluene, ethylbenzene, xylene, and n-hexane (BTEX-H)] from personal measurements on workers performing various spill clean-up operations on land. These operations included decontamination of vessels, equipment, booms, and personnel; handling of oily booms; hazardous waste management; beach, marsh, and jetty clean-up; aerial missions; wildlife rescue and rehabilitation; and administrative support activities. Exposure estimates were developed for unique groups of workers by (i) activity, (ii) state, and (iii) time period. Estimates of the arithmetic means (AMs) for THC ranged from 0.04 to 3.67 ppm. BTEX-H estimates were substantially lower than THC (in the parts per billion range). Both THC and BTEX-H estimates were substantially lower than their respective occupational exposure limits. The work group, 'Fueled engines' consistently was one of the higher exposed groups to THC and BTEX-H. Notable differences in the AM exposures were observed by activity, time and, to a lesser degree, by state. These exposure estimates were used to develop job-exposure matrices for the GuLF STUDY