Dataset Information

Gravity surveys using a mobile atom interferometer.

ABSTRACT: Mobile gravimetry is important in metrology, navigation, geodesy, and geophysics. Atomic gravimeters could be among the most accurate mobile gravimeters but are currently constrained by being complex and fragile. Here, we demonstrate a mobile atomic gravimeter, measuring tidal gravity variations in the laboratory and surveying gravity in the field. The tidal gravity measurements achieve a sensitivity of 37 ?Gal/ Hz (1 ?Gal = 10 nm/s²) and a long-term stability of better than 2 ?Gal, revealing ocean tidal loading effects and recording several distant earthquakes. We survey gravity in the Berkeley Hills with an uncertainty of around 0.04 mGal and determine the density of the subsurface rocks from the vertical gravity gradient. With simplicity and sensitivity, our instrument paves the way for bringing atomic gravimeters to field applications.

SUBMITTER: Wu X

PROVIDER: S-EPMC6731071 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Gravity surveys using a mobile atom interferometer.

Wu Xuejian X Pagel Zachary Z Malek Bola S BS Nguyen Timothy H TH Zi Fei F Scheirer Daniel S DS Müller Holger H

Science advances 20190906 9

Mobile gravimetry is important in metrology, navigation, geodesy, and geophysics. Atomic gravimeters could be among the most accurate mobile gravimeters but are currently constrained by being complex and fragile. Here, we demonstrate a mobile atomic gravimeter, measuring tidal gravity variations in the laboratory and surveying gravity in the field. The tidal gravity measurements achieve a sensitivity of 37 μGal/ Hz (1 μGal = 10 nm/s<sup>2</sup>) and a long-term stability of better than 2 μG ...[more]

PMID: 31523711

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Project description:BackgroundThe monitoring and evaluation of public health programs based on traditional face-to-face interviews in hard-to-reach and unstable regions present many challenges. Mobile phone-based methods are considered to be an effective alternative, but the validity of mobile phone-based data for assessing implementation strength has not been sufficiently studied yet. Nested within an evaluation project for an integrated community case management (iCCM) and family planning program in Mali, this study aimed to assess the validity of a mobile phone-based health provider survey to measure the implementation strength of this program.MethodsFrom July to August 2018, a cross-sectional survey was conducted among the community health workers (ASCs) from six rural districts working with the iCCM and family planning program. ASCs were first reached to complete the mobile phone-based survey; within a week, ASCs were visited in their communities to complete the in-person survey. Both surveys used identical implementation strength tools to collect data on program activities related to iCCM and family planning. Sensitivity and specificity were calculated for each implementation strength indicator collected from the phone-based survey, with the in-person survey as the gold standard. A threshold of ≥ 80% for sensitivity and specificity was considered adequate for evaluation purposes.ResultsOf the 157 ASCs interviewed by mobile phone, 115 (73.2%) were reached in person. Most of the training (2/2 indicators), supervision (2/3), treatment/modern contraceptive supply (9/9), and reporting (3/3) indicators reached the 80% threshold for sensitivity, while only one supervision indicator and one supply indicator reached 80% for specificity. In contrast, most of the stock-out indicators (8/9) reached 80% for specificity, while only two indicators reached the threshold for sensitivity.ConclusionsThe validity of mobile phone-based data was adequate for general training, supervision, and supply indicators for iCCM and family planning. With sufficient mobile phone coverage and reliable mobile network connection, mobile phone-based surveys are useful as an alternative for data collection to assess the implementation strength of general activities in hard-to-reach areas.

Project description:BackgroundeCohort studies offer an efficient approach for data collection. However, eCohort studies are challenged by volunteer bias and low adherence. We designed an eCohort embedded in the Framingham Heart Study (eFHS) to address these challenges and to compare the digital data to traditional data collection.ObjectiveThe aim of this study was to evaluate adherence of the eFHS app-based surveys deployed at baseline (time of enrollment in the eCohort) and every 3 months up to 1 year, and to compare baseline digital surveys with surveys collected at the research center.MethodsWe defined adherence rates as the proportion of participants who completed at least one survey at a given 3-month period and computed adherence rates for each 3-month period. To evaluate agreement, we compared several baseline measures obtained in the eFHS app survey to those obtained at the in-person research center exam using the concordance correlation coefficient (CCC).ResultsAmong the 1948 eFHS participants (mean age 53, SD 9 years; 57% women), we found high adherence to baseline surveys (89%) and a decrease in adherence over time (58% at 3 months, 52% at 6 months, 41% at 9 months, and 40% at 12 months). eFHS participants who returned surveys were more likely to be women (adjusted odds ratio [aOR] 1.58, 95% CI 1.18-2.11) and less likely to be smokers (aOR 0.53, 95% CI 0.32-0.90). Compared to in-person exam data, we observed moderate agreement for baseline app-based surveys of the Physical Activity Index (mean difference 2.27, CCC=0.56), and high agreement for average drinks per week (mean difference 0.54, CCC=0.82) and depressive symptoms scores (mean difference 0.03, CCC=0.77).ConclusionsWe observed that eFHS participants had a high survey return at baseline and each 3-month survey period over the 12 months of follow up. We observed moderate to high agreement between digital and research center measures for several types of surveys, including physical activity, depressive symptoms, and alcohol use. Thus, this digital data collection mechanism is a promising tool to collect data related to cardiovascular disease and its risk factors.

Project description:BackgroundThis is the first study to examine the costs of conducting a mobile phone survey (MPS) through interactive voice response (IVR) to collect information on risk factors for noncommunicable diseases (NCD) in three low- and middle-income countries (LMIC); Bangladesh, Colombia, and Uganda.MethodsThis is a micro-costing study conducted from the perspective of the payer/funder with a 1-year horizon. The study evaluates the fixed costs and variable costs of implementing one nationally representative MPS for NCD risk factors of the adult population. In this costing study, we estimated the sample size of calls required to achieve a population-representative survey and associated incentives. Cost inputs were obtained from direct economic costs incurred by a central study team, from country-specific collaborators, and from platform developers who participated in the deployment of these MPS during 2017. Costs were reported in US dollars (USD). A sensitivity analysis was conducted assessing different scenarios of pricing and incentive strategies. Also, costs were calculated for a survey deployed targeting only adults younger than 45 years.ResultsWe estimated the fixed costs ranging between $47,000 USD and $74,000 USD. Variable costs were found to be between $32,000 USD and $129,000 USD per nationally representative survey. The main cost driver was the number of calls required to meet the sample size, and its variability largely depends on the extent of mobile phone coverage and access in the country. Therefore, a larger number of calls were estimated to survey specific harder-to-reach sub-populations.ConclusionMobile phone surveys have the potential to be a relatively less expensive and timely method of collecting survey information than face-to-face surveys, allowing decision-makers to deploy survey-based monitoring or evaluation programs more frequently than it would be possible having only face-to-face contact. The main driver of variable costs is survey time, and most of the variability across countries is attributable to the sampling differences associated to reaching out to population subgroups with low mobile phone ownership or access.

Dataset Information

Gravity surveys using a mobile atom interferometer.

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Gravity surveys using a mobile atom interferometer.

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