Exposure to crude oil chemicals and burning-related PM2.5 among Deepwater Horizon oil spill workers and incident coronary heart disease

No study to date has examined exposure to individual crude oil chemicals or fine particulate matter (PM2.5) from burning of crude oil/natural gas in relation to coronary heart disease (CHD) among oil spill workers. During the 2010 Deepwater Horizon (DWH) disaster, oil spill response and cleanup (OSRC) workers were exposed to toxic volatile components of crude oil and increased PM2.5 levels from burning of oil/gas.In aim 1, we investigated the association of exposure to total petroleum hydrocarbons (THC) and several crude oil chemicals (benzene, toluene, ethylbenzene, xylene, n-hexane, i.e. BTEX-H) with incident CHD events among 22,655 DWH OSRC workers. In aim 2, we assessed burning-related PM2.5 exposure in relation to CHD risk among 9,091 DWH water workers.Exposures to THC, BTEX-H, and burning-related PM2.5 were estimated via job-exposure matrices that linked air concentration data to self-reported OSRC work histories. We identified incident CHD events that occurred after each worker ended OSRC work from self-report and death certificates. We estimated hazard ratios (HR) and 95% confidence intervals (95%CI) for CHD associated with exposure to BTEX-H/THC (quintiles (Q)) and PM2.5. We applied inverse probability weights to account for bias due to confounding and loss to follow-up. We also assessed the joint effect of the BTEX-H mixture using quantile g-computation.Workers in the highest cumulative exposure category of each crude oil agent had modest increases in CHD risk compared to the referent group (Q1) of that agent (range of HR: 1.14-1.44), although most associations were non-significant. No apparent association was observed for the overall effect of the BTEX-H mixture. Compared to workers not involved in or near the burning (ref), workers with in the highest average PM2.5 exposure category had significantly elevated risk of CHD (HR=2.11, 95%CI: 1.08, 4.12). We also observed a monotonic, but non-significant, trend among workers with higher cumulative PM2.5 exposure (low: HR=1.19, 95%CI: 0.68, 2.08; medium: HR=1.38, 95%CI: 0.88, 2.16; high: HR=1.44, 95%CI: 0.96, 2.14). Higher exposures to volatile components of crude oil and PM2.5 from burning of oil/gas were associated with a modest increase in risk of CHD among oil spill workers.Doctor of Philosoph

Single channel based interference-free and self-powered human-machine interactive interface using eigenfrequency-dominant mechanism

The recent development of wearable devices is revolutionizing the way of human-machine interaction (HMI). Nowadays, an interactive interface that carries more embedded information is desired to fulfil the increasing demand in era of Internet of Things. However, present approach normally relies on sensor arrays for memory expansion, which inevitably brings the concern of wiring complexity, signal differentiation, power consumption, and miniaturization. Herein, a one-channel based self-powered HMI interface, which uses the eigenfrequency of magnetized micropillar (MMP) as identification mechanism, is reported. When manually vibrated, the inherent recovery of the MMP caused a damped oscillation that generates current signals because of Faraday's Law of induction. The time-to-frequency conversion explores the MMP-related eigenfrequency, which provides a specific solution to allocate diverse commands in an interference-free behavior even with one electric channel. A cylindrical cantilever model was built to regulate the MMP eigenfrequencies via precisely designing the dimensional parameters and material properties. We show that using one device and two electrodes, high-capacity HMI interface can be realized when the MMPs with different eigenfrequencies have been integrated. This study provides the reference value to design the future HMI system especially for situations that require a more intuitive and intelligent communication experience with high-memory demand.Comment: 35 pages, 6 figure

Distributed Movement Control for Building a Ring in Mobile Wireless Sensor Networks

Many applications in wireless sensor networks require some sensors to form a ring or multiring-based shape in the target area, such as intrusion detection, border surveillance, routing overlay formation, and network full coverage. In this paper, we study the problem of sensor redistribution to build a ring-based shape for mobile sensor networks. We first give the theoretical analysis on what is optimal sensor movement with the given random deployment. Then, we propose a fully distributed movement control algorithm to achieve ring-based shape for mobile sensor networks. We formally prove that our algorithm can achieve a ring-based distribution within finite time. We also present the procedures of applying our algorithm to form multiring-based distribution. Finally, we present extensive simulations to verify that our approach outperforms other schemes in terms of both the moving distance and convergence time

Towards an Optimal Energy Consumption for Unattended Mobile Sensor Networks through Autonomous Sensor Redeployment

Energy hole is an inherent problem caused by heavier traffic loads of sensor nodes nearer the sink because of more frequent data transmission, which is strongly dependent on the topology induced by the sensor deployment. In this paper, we propose an autonomous sensor redeployment algorithm to balance energy consumption and mitigate energy hole for unattended mobile sensor networks. First, with the target area divided into several equal width coronas, we present a mathematical problem modeling sensor node layout as well as transmission pattern to maximize network coverage and reduce communication cost. And then, by calculating the optimal node density for each corona to avoid energy hole, a fully distributed movement algorithm is proposed, which can achieve an optimal distribution quickly only by pushing or pulling its one-hop neighbors. The simulation results demonstrate that our algorithm achieves a much smaller average moving distance and a much longer network lifetime than existing algorithms and can eliminate the energy hole problem effectively

Bicriteria Optimization in Wireless Sensor Networks: Link Scheduling and Energy Consumption

Link scheduling is important for reliable data communication in wireless sensor networks. Previous works mainly focus on how to find the minimum scheduling length but ignore the impact of energy consumption. In this paper, we integrate them together and solve them by multiobjective genetic algorithms. As a contribution, by jointly modeling the route selection and interference-free link scheduling problem, we give a systematical analysis on the relationship between link scheduling and energy consumption. Considering the specific many-to-one communication nature of WSNs, we propose a novel link scheduling scheme based on NSGA-II (Non-dominated Sorting Genetic Algorithm II). Our approach aims to search the optimal routing tree which satisfies the minimum scheduling length and energy consumption for wireless sensor networks. To achieve this goal, the solution representation based on the routing tree, the genetic operations including tree based recombination and mutation, and the fitness evaluation based on heuristic link scheduling algorithm are well designed. Extensive simulations demonstrate that our algorithm can quickly converge to the Pareto optimal solution between the two performance metrics

Distinguishing Linkage Position and Anomeric Configuration of Glucose–Glucose Disaccharides by Water Adduction to Lithiated Molecules

A method was developed to distinguish both the linkage position and the anomericity of all reducing and two nonreducing glucopyransosyl–glucose disaccharides using only electrospray ionization–mass spectrometry/mass spectrometry (ESI–MS/MS). Carbohydrates are well-known to form complexes with metal cations during electrospray ionization. Addition of a lithium salt to a solution containing a disaccharide, M, results in [M + Li]⁺ after ESI. Collision-induced dissociation of these ions creates product ions at <i>m</i>/<i>z</i> 187 and <i>m</i>/<i>z</i> 169 from cleavage of the glycosidic bond and are present for all disaccharides studied. Both of these product ions were found to adduct water after their formation in a quadrupole ion trap. The kinetics of this water adduction can be measured by isolating either of the product ions and waiting a short time (<1 s) before mass analysis. Additionally, for both product ions, only a fraction of the ions were able to adduct water. This unreactive fraction was measured along with the reaction rate, and the combination of these two values was found to be unique for each disaccharide. Additionally, after CID, a 1000 ms delay can be added, and the ratios of the resulting products ions of <i>m</i>/<i>z</i> 169, 187, and 205 can be used to distinguish linkage position and anomericity with a single tandem mass spectrometry experiment

Distinguishing Biologically Relevant Hexoses by Water Adduction to the Lithium-Cationized Molecule

A method to distinguish the four most common biologically relevant underivatized hexoses, d-glucose, d-galactose, d-mannose, and d-fructose, using only mass spectrometry with no prior separation/derivatization step has been developed. Electrospray of a solution containing hexose and a lithium salt generates [Hexose+Li]⁺. The lithium-cationized hexoses adduct water in a quadrupole ion trap. The rate of this water adduction reaction can be used to distinguish the four hexoses. Additionally, for each hexose, multiple lithiation sites are possible, allowing for multiple structures of [Hexose+Li]⁺. Electrospray produces at least one structure that reacts with water and at least one that does not. The ratio of unreactive lithium-cationized hexose to total lithium-cationized hexose is unique for the four hexoses studied, providing a second method for distinguishing the isomers. Use of the water adduction reaction rate or the unreactive ratio provides two separate methods for confidently (<i>p</i> ≤ 0.02) distinguishing the most common biologically relevant hexoses using only femtomoles of hexose. Additionally, binary mixtures of glucose and fructose were studied. A calibration curve was created by measuring the reaction rate of various samples with different ratios of fructose and glucose. The calibration curve was used to accurately measure the percentage of fructose in three samples of high fructose corn syrup (<4% error)

Distinguishing Biologically Relevant Hexoses by Water Adduction to the Lithium-Cationized Molecule

A method to distinguish the four most common biologically relevant underivatized hexoses, d-glucose, d-galactose, d-mannose, and d-fructose, using only mass spectrometry with no prior separation/derivatization step has been developed. Electrospray of a solution containing hexose and a lithium salt generates [Hexose+Li]⁺. The lithium-cationized hexoses adduct water in a quadrupole ion trap. The rate of this water adduction reaction can be used to distinguish the four hexoses. Additionally, for each hexose, multiple lithiation sites are possible, allowing for multiple structures of [Hexose+Li]⁺. Electrospray produces at least one structure that reacts with water and at least one that does not. The ratio of unreactive lithium-cationized hexose to total lithium-cationized hexose is unique for the four hexoses studied, providing a second method for distinguishing the isomers. Use of the water adduction reaction rate or the unreactive ratio provides two separate methods for confidently (<i>p</i> ≤ 0.02) distinguishing the most common biologically relevant hexoses using only femtomoles of hexose. Additionally, binary mixtures of glucose and fructose were studied. A calibration curve was created by measuring the reaction rate of various samples with different ratios of fructose and glucose. The calibration curve was used to accurately measure the percentage of fructose in three samples of high fructose corn syrup (<4% error)

Fine particulate matter and incident coronary heart disease events up to 10 years of follow-up among Deepwater Horizon oil spill workers.

BACKGROUND: During the 2010 Deepwater Horizon (DWH) disaster, in-situ burning and flaring were conducted to remove oil from the water. Workers near combustion sites were potentially exposed to burning-related fine particulate matter (PM2.5). Exposure to PM2.5 has been linked to increased risk of coronary heart disease (CHD), but no study has examined the relationship among oil spill workers. OBJECTIVES: To investigate the association between estimated PM2.5 from burning/flaring of oil/gas and CHD risk among the DWH oil spill workers. METHODS: We included workers who participated in response and cleanup activities on the water during the DWH disaster (N&nbsp;=&nbsp;9091). PM2.5 exposures were estimated using a job-exposure matrix that linked modelled PM2.5 concentrations to detailed DWH spill work histories provided by participants. We ascertained CHD events as the first self-reported physician-diagnosed CHD or a fatal CHD event that occurred after each workers last day of burning exposure. We estimated hazard ratios (HR) and 95% confidence intervals (95%CI) for the associations between categories of average or cumulative daily maximum PM2.5 exposure (versus a referent category of water workers not near controlled burning) and subsequent CHD. We assessed exposure-response trends by examining continuous exposure parameters in models. RESULTS: We observed increased CHD hazard among workers with higher levels of average daily maximum exposure (low vs. referent: HR&nbsp;=&nbsp;1.26, 95% CI: 0.93, 1.70; high vs. referent: HR&nbsp;=&nbsp;2.11, 95% CI: 1.08, 4.12; per 10&nbsp;μg/m3 increase: HR&nbsp;=&nbsp;1.10, 95% CI: 1.02, 1.19). We also observed suggestively elevated HRs among workers with higher cumulative daily maximum exposure (low vs. referent: HR&nbsp;=&nbsp;1.19, 95% CI: 0.68, 2.08; medium vs. referent: HR&nbsp;=&nbsp;1.38, 95% CI: 0.88, 2.16; high vs. referent: HR&nbsp;=&nbsp;1.44, 95% CI: 0.96, 2.14; per 100 μg/m3-d increase: HR&nbsp;=&nbsp;1.03, 95% CI: 1.00, 1.05). CONCLUSIONS: Among oil spill workers, exposure to PM2.5 from flaring/burning of oil/gas was associated with increased risk of CHD