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475 results for “income”
In-home Obesity Prevention to Reach Low-income Infants
ClinicalTrials.gov study NCT03529695. IPD Sharing: YES. Countries: 1. Publications: 1.
The multiomic landscape of epidemiological factors contributing to preterm birth in low- and middle-income countries
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Association between family income to poverty ratio and nocturia in adults aged 20 years and older
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HEartS Professional Survey: Charting the effects of COVID-19 lockdown 1.0 on working patterns, income, and wellbeing among performing arts professionals in the United Kingdom (April–June 2020)
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Data from: Association between night-shift work, sleep quality, and health-related quality of life : a cross-sectional study among manufacturing workers in a middle-income setting
<p>Objectives: Night-shift work may adversely affect health. This study aimed to determine the impact of night-shift work on health-related quality of life (HRQoL), and assess whether sleep quality was a mediating factor.</p> <p>Design: Cross-sectional study.</p> <p>Setting: 11 manufacturing factories in Malaysia.</p> <p>Participants: 177 night-shift workers aged 40 to 65 years old were compared with 317 non-night-shift work.</p> <p>Primary and secondary outcomes: Participants completed a self-administered questionnaire on socio-demography and lifestyle factors, short Form-12v2 Health Survey (SF-12), and the Pittsburgh Sleep Quality Index (PSQI). Baron and Kenny's method, Sobel test and multiple mediation model with bootstrapping were used to determine whether PSQI score or its components mediated the association between night-shift work and HRQoL.</p> <p>Results: Night-shift work was associated with sleep impairment and HRQoL. Night-shift workers had significantly lower mean scores in all the eight SF-12 domains (p<0.001). Compared to non-night shift workers, night-shift workers were significantly more likely to report poorer sleep quality, longer sleep latency, shorter sleep duration, sleep disturbances, and daytime dysfunction (p<0.001). Mediation analyses showed that PSQI global score mediated the association between night-shift work and HRQoL. "Subjective sleep quality" (indirect effect=-0.24, standard error [SE]=0.14, bias corrected 95%Confidence Interval [BC 95%CI]: -0.58 to -0.01) and "sleep disturbances" (indirect effect=-0.79, SE=0.22, BC 95%CI: -1.30 to -0.42) were mediators for the association between night-shift work and physical wellbeing, whereas "sleep latency" (indirect effect=-0.51, SE=0.21, BC 95%CI: -1.02 to -0.16) and "daytime dysfunction" (indirect effect=-1.11, SE=0.32, BC 95%CI: -1.86 to -0.58) were mediators with respect to mental wellbeing.</p> <p>Conclusion: Sleep quality partially explains the association between night-shift work and poorer HRQoL. Organisations should treat the sleep quality of night-shift workers as a top priority area for action in order to improve their employees' overall wellbeing.</p>
Data from: The effects of food supply on reproductive hormones and timing of reproduction in an income-breeding seabird
<p class="CxSpFirst">Current food supply is a major driver of timing of breeding in income-breeding animals, likely because increased net energy balance directly increases reproductive hormones and advances breeding. In capital breeders, increased net energy balance increases energy reserves, which eventually leads to improved reproductive readiness and earlier breeding. To test the hypothesis that phenology of income-breeding birds is independent of energy reserves, we conducted an experiment on food-supplemented ("fed") and control female black-legged kittiwakes (<em>Rissa tridactyla</em>). We temporarily increased energy costs (via weight handicap) in a 2 × 2 design (fed/unfed; handicapped/unhandicapped) during the pre-laying period and observed movement via GPS-accelerometry. We measured body mass, baseline hormones (corticosterone; luteinising hormone) before and after handicap manipulation, and conducted a gonadotropin-releasing hormone challenge. Females from all treatment groups foraged in similar areas, implying that individuals could adjust time spent foraging, but had low flexibility to adjust foraging distance. Consistent with the idea that income breeders do not accumulate reserves in response to increased food supply, fed birds remained within an energy ceiling by reducing time foraging instead of increasing energy reserves. Moreover, body mass remained constant until the onset of follicle development 20 days prior to laying regardless of feeding or handicap, implying that females were using a 'lean and fit' approach to body mass rather than accumulating lipid reserves for breeding. Increased food supply advanced endocrine and laying phenology and altered interactions between the hypothalamic-pituitary-adrenal axis and the hypothalamic-pituitary-gonadal axis, but higher energy costs (handicap) had little effect. Consistent with our hypothesis, increased food supply (but not net energy balance) advanced endocrine and laying phenology in income-breeding birds without any impact on energy reserves.</p>
Quantifying capital vs. income breeding: new promise with stable isotope measurements of individual amino acids
<p>1. Capital breeders accumulate nutrients prior to egg development, then use these stores to support offspring. In contrast, income breeders rely on local nutrients consumed contemporaneously with offspring development. Understanding such nutrient allocations is critical to assessing wildlife reliance on different habitats.</p> <p>2. Despite the contrast between these strategies, it remains challenging to trace nutrients from endogenous stores or exogenous food intake into offspring. Here, we tested a new solution to this problem.</p> <p>3. Using tissue samples collected opportunistically from wild emperor penguins (<i>Aptenodytes forsteri</i>), which exemplify capital breeding, we hypothesized that the stable carbon (δ<sup>13</sup>C) and nitrogen (δ<sup>15</sup>N) isotope values of individual amino acids (AA) in endogenous stores (e.g., muscle) and in egg yolk and albumen reflect the nutrient sourcing that distinguishes capital versus income breeding. Unlike other methods, this approach does not require untested assumptions or diet sampling.</p> <p>4. We found that over half of essential AA had δ<sup>13</sup>C values that did not differ between muscle and yolk or albumen, suggesting that most of these AA were directly routed from muscle into eggs. In contrast, almost all non-essential AA differed in δ<sup>13</sup>C values between muscle and yolk or between muscle and albumen, suggesting <i>de novo</i> synthesis. Over half of AA that have labile nitrogen atoms (i.e., "trophic" AA) had higher δ<sup>15</sup>N values in yolk and albumen than in muscle, suggesting that they were transaminated during their routing into egg tissue. This effect was smaller for AA with less labile nitrogen atoms (i.e., "source" AA).</p> <p>5. Our results indicate that the δ<sup>15</sup>N offset between trophic-source AA (Δ<sup>15</sup>N<sub>trophic-source</sub>) may provide an index of the extent of capital breeding. The value of emperor penguin Δ<sup>15</sup>N<sub>Pro-Phe</sub> was higher in yolk and albumen than in muscle, reflecting the mobilization of endogenous stores; in comparison, the value of Δ<sup>15</sup>N<sub>Pro-Phe</sub> was similar across muscle and egg tissue in previously-published data for income-breeding herring gulls (<i>Larus argentatus smithsonianus</i>). Our results provide a quantitative basis for using AA δ<sup>13</sup>C and δ<sup>15</sup>N, and isotopic offsets among AA (e.g., Δ<sup>15</sup>N<sub>Pro-Phe</sub>), to explore the allocation of endogenous versus exogenous nutrients across the capital versus income spectrum of avian reproduction.</p>
Data from: Models of community-based primary care for epilepsy in low and middle income countries
Objective: To review systematically community-based primary care interventions for epilepsy in low and middle income countries to rationalize approaches and outcome parameters in relation to epilepsy care in these countries. Methods: A systematic search of PubMed, EMBASE, Global Index Medicus, CINAHL and Web of Science was undertaken to identify trials and implementation of provision of anti-seizure medications, adherence reinforcement and/or healthcare provider or community education in community-based samples of epilepsy. Data on populations addressed, interventions and outcomes were extracted from eligible articles. Results: Twenty-four reports were identified, mostly care programs addressing active convulsive epilepsy. Phenobarbital has been used most frequently though other conventional antiseizure medications have also been used but none of the newer. Tolerability rates in these studies are high but overall, attrition is considerable. Other approaches have included updating primary health care providers, reinforcing treatment adherence in clinics and raising community awareness. The coverage of existing treatment gap in the community, epilepsy-related mortality and comorbidity burden are fleetingly addressed in these programs. Conclusions: The cost-free provision, mostly of phenobarbital has resulted in short-term seizure freedom in roughly half of the people with epilepsy in LMICs. Future programs should include a range of antiseizure medications. These should cover apart from seizure control and treatment adherence, primary healthcare provider education, raising community awareness and referral protocols for specialist care. The programs should ensure sustainability and impact assessment at a community level.
Data Sets: An Assessment of Water Trusts: Drinking Water Quality and Provision in Six Low-income, Peri-urban Communities of Lusaka, Zambia
<p>Data set associated with the manuscript published in GeoHealth titled An Assessment of Water Trusts: Drinking Water Quality and Provision in Six Low-income, Peri-urban Communities of Lusaka, Zambia. This includes bacterial, nitrate, specific conductance, and Water Trust survey data collected from Lusaka, Zambia in 2013, 2014, 2016, an 2019.</p>
Data on the Impact of Consumption Taxes on Income Inequality
<p>This data is part of a research project on the impact of consumption taxes on inequality by Julien Blasco, Elvire Guillaud and Michaël Zemmour.</p> <p>Our project is currently published in the LIS Working Paper Series. You may cite it as:</p> <blockquote> <p>Blasco J., Guillaud E., Zemmour M. (2020) <a href="http://www.lisdatacenter.org/wps/liswps/785.pdf">“Consumption Taxes and Income Inequality: An International Perspective with Microsimulation”</a>, <em>LIS Working Paper Series</em>, No. 785.</p> </blockquote> <p>You are free to use the datasets we provide here, but please cite them as:</p> <blockquote> <p>Blasco J., Guillaud E., Zemmour M., Data on the Impact of Consumption Taxes on Income Inequality, <a href="https://doi.org/10.5281/zenodo.4291984"><em>https://doi.org/</em>10.5281/zenodo.4291984</a>, October 2020.</p> </blockquote> <p>For detailed information on the method used, please refer to <a href="https://www.lisdatacenter.org/wps/liswps/785.pdf">Blasco, Guillaud and Zemmour (2020)</a>. In particular, the appendices describe the imputation models used for consumption. All the coefficients are given, which allows for a replication of this imputation method in other datasets.</p> <p>The code used is available at <a href="https://github.com/JulienBlasco/consumption-taxes">https://github.com/JulienBlasco/consumption-taxes</a>.</p> <p>Our data is base on surveys on income and consumption, harmonized by the <a href="https://www.lisdatacenter.org">Luxembourg Income Study</a>. We used <a href="https://stats.oecd.org">OECD Statistics</a> for National Accounts data on income, consumption and consumption tax revenue.</p> <p> </p> <p><strong>Description of the data</strong></p> <p>The data is constituted of five tables.</p> <ul> <li>Two datasets are aggregated indicators at the country-year level, such as Gini coefficients for different concepts of income, global consumption tax-to-income ratios, anti-redistributive effect of consumption taxes: <ul> <li>For the core model (82 country-years): ConsumptionTaxes_indicators_coremodel.dta</li> <li>For the lighter model (126 country-years): ConsumptionTaxes_indicators_xtnddmodel</li> </ul> </li> <li>Two datasets are variables broken down by percentiles of disposable income, within each country-year. Please note that these data are mainly for graphing purposes, not detailed analysis at the percentile level: <ul> <li>Core model (82 country-years): ConsumptionTaxes_percentiles_coremodel</li> <li>Lighter model (126 country-years): ConsumptionTaxes_percentiles_xtnddmodel</li> </ul> </li> <li>One dataset that contains the implicit effective tax rates on consumption, computed with National Accounts data: 18-07-27 OECD_itrcs.dta</li> </ul>
DCC RDM2014 Survey Responses by Institutional Research Income
<p>Responses downloaded from Bristol Online Survey, with analysis in Excel. Responses have been anonymised.</p>
Georeferenced datas of mean income of North-West Lausanne villages.
<p>Georeferenced datas of mean income of North-West Lausanne villages.</p>
Deep Learning with Satellite Images Enables High-Resolution Income Estimation: a Case Study of Buenos Aires
<p>This repository contains the datasets required for replicating the results in Abbate et al (forthcoming). The datasets also include per capita income estimates at a 50x50 meter resolution for the years 2013, 2018, and 2022, using satellite images from the Metropolitan Area of Buenos Aires (Argentina) and 2010 census+survey data. The model, based on the EfficientnetV2 architecture, achieved high accuracy in predicting household incomes (R2=0.878), surpassing existing methods in spatial resolution and performance. </p> <p>Inside the Replication Package folder, the user can replicate the main results from the paper. This includes:</p> <ol> <li> <p><strong>Small Area Estimation (SAE) Replication:</strong></p> <ul> <li> <p><strong>Argentina Household Survey Data (EPH):</strong> Processed microdata for 2010, 2013, 2018, and 2022 (ARG_*_EPHC-S2_*.dta).</p> </li> <li> <p><strong>Argentina Census Microdata:</strong> Raw 2010 census microdata (censo2010_fullraw_p.dta).</p> </li> <li> <p><strong>Census Tract Map:</strong> Shapefile of 2010 census tracts (radios_eph_with_link.shp).</p> </li> <li> <p><strong>SAE Output:</strong> The final small_area_estimates.parquet file containing census tract-level population and estimated income, which serves as labels for the CNN model.</p> </li> </ul> </li> <li> <p><strong>CNN-based Income Prediction Replication (Paper Results):</strong></p> <ul> <li> <p><strong>CNN Model Income Predictions:</strong> Gridded 50x50m income estimates for Buenos Aires for 2013, 2018, and 2022 (income_estimates_*.shp).</p> </li> <li> <p><strong>Normalization Scalars:</strong> A CSV file (scalars_ln_pred_inc_mean_trimTrue.csv) to convert the model's log-scale outputs into real income values (2010 PPP-adjusted Argentinian pesos).</p> </li> <li> <p><strong>World Settlement Footprint (WSF):</strong> Satellite-based data (WSF2015_v2_-60_-36.tif) used to mask predictions in uninhabited areas.</p> </li> </ul> </li> </ol> <p>Key prediction datasets are published in shapefile format, while input data for SAE and other auxiliary files are in formats like .dta, .parquet, .csv, and .tif.</p> <p>Results can be replicated by connecting these datasets with the scripts available at the GitHub repo linked below.</p> <p>For researchers who wish to replicate the full analysis pipeline starting from the original source imagery, the data must be acquired commercially. The proprietary Pleiades and Pleiades NEO satellite imagery is owned by Airbus and can be purchased through their data portal: https://space-solutions.airbus.com/imagery/. To facilitate this process, we provide the unique product identifiers for each scene used in this study. These identifiers can be used to query the Airbus archive and purchase the exact scenes.</p> <ul> <li><strong>Pléiades</strong>: for 2013 imagery the IDs are DS_PHR1A_201302051411520_FR1_PX_W059S35_0807_03124, DS_PHR1A_201302071357305_FR1_PX_W059S35_0410_06105 and DS_PHR1A_201302071357509_FR1_PX_W059S35_0609_05426, and for 2018, DS_PHR1A_201803251356358_FR1_PX_W059S35_0909_03875, DS_PHR1A_201808021356574_FR1_PX_W059S35_0509_06938 and DS_PHR1A_201808021357186_FR1_PX_W059S35_0706_06104.</li> <li><strong>Pleiades NEO</strong>: for 2022 imagery the IDs used are 000047717_1_22_STD_A, 000047717_1_24_STD_A, 000047717_1_25_STD_A, 000047717_1_26_STD_A, 000058605_1_3_STD_A, 000058605_1_4_STD_A, 000058605_1_7_STD_A, and 000058608_1_2_STD_A.</li> </ul> <p><strong>Important Usage Note:</strong> Since the predictions for each 50x50m cell individually present some random variation, we recommend that the results are used by averaging out the estimations for each area of interest (e.g., municipalities, neighborhoods, sections, or census tracts) and not at an individual cell level. As detailed throughout the paper, the aggregated results, even in small areas such as census tracts, predict household incomes with precision.</p> <p>Furthermore, inside this repository, it is possible to access and use the model’s trained parameters to make predictions about different satellite images.</p> <p>Data can be visualized by accessing: <a href="https://ingresoamba.netlify.app">https://ingresoamba.netlify.app</a></p> <p> </p> <p> </p>
Data for: Reproductive tactics, birth timing and the risk-resource trade-off in an income breeder
<p><span>In variable environments, habitats that are rich in resources often carry a higher risk of predation. As a result, natural selection should favour individuals that balance allocation of time to foraging versus avoiding predation through an optimal decision-making process that maximises fitness. The behavioural trade-off between resource acquisition and risk avoidance is expected to be particularly acute during gestation and lactation when the energetic demands of reproduction peak</span><span>.</span><span> Here, we investigated how reproductive female roe deer adjust their foraging activity and habitat use during the birth period to manage this trade-off compared to non-reproductive juveniles, and how parturition date constrains individual tactics of risk-resource management. Activity of reproductive females more than doubled immediately following parturition, when energy demand is highest. Furthermore, compared to non-reproductive juveniles, they increased their exposure to risk by using open habitat more during daytime and ranging closer to roads. However, these post-partum modifications in behaviour were particularly pronounced in late-parturient females who adopted a more risk-prone tactic, presumably to compensate for the growth handicap of their late-born offspring. In income breeders, individuals that give birth late may be constrained to trade risk avoidance for foraging during peak allocation to reproduction, with probable consequences for individual fitness.</span></p>
HEartS Professional Survey: Charting the effects of COVID-19 on working patterns, income, and wellbeing among performing arts professionals in the United Kingdom (April-May 2021)
<p>These data were collected using the <em>HEartS Professional Survey II</em> from performing arts workers in the United Kingdom in April–May 2021. <em>HEartS Professional II </em>is an adaptation of the <em>HEartS Professional I</em> survey which was used in April–June 2020 (<a href="https://doi.org/10.5061/dryad.s7h44j14z">https://doi.org/10.5061/dryad.s7h44j14z</a>). Both surveys were designed as multi-strategy data collection tools with two main purposes: (1) to chart working patterns, income, sources of support, and indicators of mental and social well-being in order to identify trends in the effects of the lockdown at the time and (2) to explore the individual work and wellbeing experiences of performing arts professionals in their own words, in order to identify the subjective effects of lockdown in terms of challenges and opportunities. The survey covers six areas: (1) demographics; (2) information on illness or self-isolation related to COVID-19; (3) work profiles and income; (4) changes to work profiles and income as a result of the pandemic, as well as sources of support; (5) open-response questions about work and wellbeing experiences of lockdown including challenges and opportunities; and (6) validated measures of health, wellbeing, and social connectedness.<span> The <em>HEartS Professional</em> surveys are adaptations of the Depression, loneliness, online survey, pandemic, performing arts professionals, Social Isolation, UK adult sample, well-being, Work </span>which charts the Health, Economic, and Social impacts of the ARTs (<a href="https://doi.org/10.5061/dryad.3r2280gdj">https://doi.org/10.5061/dryad.3r2280gdj</a>). </p>
Data from: Building functional and sustainable pharmacovigilance systems - an analysis of pharmacovigilance development across high-, middle- and low-income countries
<p>Background</p> <p>Pharmacovigilance (PV) is an essential component of health systems. Functional PV systems protect and promote public health by supporting the safe and effective use of medicinal products through the prevention and mitigation of harm. With increased simultaneous introduction of innovative products in high-, middle- and low-income countries, e.g., COVID-19 vaccines, or solely in low- and middle-income countries (LMIC), e.g., malaria vaccines, PV systems in LMIC must be able to detect safety signals and ensure adequate safety surveillance. This research aims to analyse the development of PV systems across high-, middle- and low-income countries and to carve out essential elements for implementing functional and sustainable PV systems in LMIC.</p> <p>Methods</p> <p>A convergent parallel mixed-methods design, consisting of qualitative and quantitative methods was used. Qualitative research consisted of semi-structured interviews. To expand the breadth and range of the study, a quantitative survey was conducted, focusing on the same thematic questions as the semi-structured interviews.</p> <p>Results</p> <p>Twelve key informants from nine countries were interviewed and 52 respondents from 36 countries completed an online questionnaire. Four major themes consisting of 12 categories emerged from the data. Based on these, the following elements essential for building functional and sustainable pharmacovigilance systems in LMIC were identified: understanding the drivers of PV development; adequately resolving core system challenges; implementing an efficient organisational structure and procedures for PV; investing in activities beyond reporting of adverse drug reactions; identifying alternate sources of financing; having a national strategy with a vision and mission for PV; adequately leveraging the health system; and effectively integrating the pharmaceutical sector in the national PV system.</p> <p>Conclusions</p> <p>Findings from this research revealed progress in PV systems in LMIC in the last decade, though significant efforts are still needed to develop these systems to meet global standards. Developing the different areas emerging from this research, which necessitates implementing functional PV structures and processes, adequately leveraging the health system and effectively engaging the pharmaceutical sector, through the mechanisms proposed, would enable a comprehensive progression from basic to stable, functional and thus sustainable PV systems in LMIC.</p>
Randomised trials in maternal and perinatal health in low- and middle-income countries from 2010 to 2019: A systematic scoping review
<p><strong>Objectives: </strong>To identify and map all trials in maternal health conducted in low- and middle-income countries (LMIC) over the 10-year period 2010-2019, to identify geographical and thematic trends, as well as compare to global causes of maternal death and pre-identified priority areas.</p> <p><strong>Design: </strong>Systematic scoping review.</p> <p><strong>Primary and secondary outcome measures: </strong>Extracted data included location, study characteristics and whether trials corresponded to causes of mortality and identified research priority topics.</p> <p><strong>Results: </strong>Our search identified 7,269 articles, 874 of which were included for analysis. Between 2010 and 2019, maternal health trials conducted in LMICs more than doubled (50 to 114). Trials were conducted in 61 countries – 231 trials (26.4%) were conducted in Iran. Only 225 trials (25.7%) were aligned with a cause of maternal mortality. Within these trials, pre-existing medical conditions, embolism, obstructed labour, and sepsis were all under-represented when compared with number of maternal deaths globally. Large numbers of studies were conducted on priority topics such as labour and delivery, obstetric haemorrhage, and antenatal care. Hypertensive disorders of pregnancy, diabetes, and health systems and policy – despite being high-priority topics – had relatively few trials.</p> <p><strong>Conclusion: </strong>Despite trials conducted in LMICs increasing from 2010 to 2019, there were significant gaps in geographical distribution, alignment with causes of maternal mortality, and known research priority topics. The research gaps identified provide guidance and insight for future research conducted in low-resource settings.</p>
Low-fold seismic reflection data acquired across the Northern Hikurangi subduction margin and incoming Hikurangi Plateau, New Zealand
<p>Two-dimensional seismic reflection data were acquired on two surveys of the Northern Hikurangi subduction margin, New Zealand in 2011 and 2015. The survey data were collected to support research of tectonic structure, slow slip processes, stratigraphic architecture, and thermal state of the subduction margin and incoming plate, as well as to support ocean-floor drilling associated with IODP Expeditions 372 and 375. The surveys include (1) R/V <em>Tangaroa</em> NIWA voyage TAN1114 undertaken in 2011 by the National Institute of Water and Atmospheric Research (NIWA) and GNS Science, as part of the <em>OS2020 Northern Hikurangi Margin Geohazards</em> survey; and (2) R/V <em>Rodger Revelle</em> cruise RR1508 undertaken in 2015 by Oregon State University as part of the <em>Subduction Thrust Investigation of New Zealand using Geothermics and Seismics (STINGS)</em> project (see Figure 1). TAN1114 voyage was funded by the New Zealand Government Oceans 2020 Programme, and core research programme funding by NIWA and GNS Science. Cruise RR1508 was funded by NSF grants OCE-1355878 and OCE-1355870.</p> <p> </p> <p><strong>R/V <em>Tangaroa</em> TAN1114 Seismic Data</strong></p> <p><strong>Data Acquisition:</strong> The seismic system used on R/V <em>Tangaroa</em> during the 2011 National Institute of Water and Atmospheric Research (NIWA) survey TAN1114 included a source comprising two Sodera 45/105 GI guns operated in true GI mode. The guns were deployed 35 m behind the vessel RV <em>Tangaroa</em> at 5 m water depth. Lines TAN1114-01 to -13, and part of line 14 were acquired with a shot interval of 10.8 seconds (~25 m sailing at 4.5 knots), providing a nominal coverage of 12-fold data. Part of line TAN1114-14 and lines 15-23 were acquired with a shot interval of 21.6 seconds (~50 m sailing at 4.5 knots), providing a nominal 6-fold coverage. Data were recorded on a Geometrics GeoEel 48-channel seismic streamer with 6 X 100 m active sections, and a group interval of 12.5 m. The streamer was deployed at a depth of 7.5 m, apart from line TAN1114-01 where it was towed at 5 m depth. Depth control was maintained with a CSMX depth control system including three DigiCourse 5011 compass birds. The record length was 8 s and the sample rate 2 ms. Differential GPS was used for positioning. Table 1 summarises TAN1114 recording parameters and Table 2 lists TAN1114 lines acquired and processed. TAN1114 line coordinates are detailed in Table 3.</p> <p><strong>Data Processing:</strong> A total of 29 seismic lines were processed providing 1350 km of multichannel seismic reflection data. The lines were processed to post-stack time-migrated SEGY sections, using GNS Science GLOBE CLARITAS. With allowance for overlap of line segments the data were grouped into 51167 shot-point locations. Raw data were written to disk as IBM standard SEG-Y files. IBM Claritas Extended SEG-Y data were written to disk after geometry was added, after stack, and after migration. Shots were CDP sorted from disk during the stacking process to avoid creating large and unnecessary separate CDP sorted files. </p> <p>Post-stack migration (finite difference migration) has been applied to the stacked sections to produce a dip-true image, this results in clearer resolution of structural features such as faults and folds, and of detailed sedimentary features such as on-lapping and truncated reflections. Sea-floor multiple reflections disturb structural imaging especially in water depths less than 500 m. All seismic data are written to disk as processed sections in SEG-Y format. Line TAN1114-A is a composite splice including parts of lines TAN1114-4A, -6A and 7A. Details of the TAN1114 processing parameters are given in Table 4 and SEG-Y trace headers in Table 5.</p> <p> </p> <p><strong>R/V <em>Rodger Revelle</em> RR1508 Seismic Data</strong></p> <p><strong>Data Acquisition:</strong> The 2015 R/V <em>Rodger Revelle</em> survey RR1508 used a seismic system operated by Scripps Institute of Oceanography. Of two sub-regions surveyed during this cruise, only data from the northern Hikurangi margin are presented here. The seismic system used was similar to that on <em>Tangaroa</em> TAN1114, including a source comprising two Sodera 45/105 GI guns operated in true GI mode. The guns were deployed at a depth of 3.5 m and the shot spacing was 25 m. Data were recorded on a Geometrics GeoEel 48-channel seismic streamer with 6 X 100 m active sections, and a group interval of 12.5 m. The streamer was deployed at a depth of 3.5 m. During acquisition of the HKS01 lines, only the nearest 40 data channels were recorded. The record length was 8 s and the sample rate 1 ms. Differential GPS was used for positioning. Table 6 summarises RR1508 recording parameters and Table 7 lists RR1508 lines acquired and processed.</p> <p><strong>Data Processing: </strong>A total of 13 HKS01 seismic lines were processed to post-stack time-migrated SEGY sections, using GNS Science GLOBE CLARITAS. Data processing included application of geometry, sorting, trace editing, normal moveout correction, stack, filtering and finite difference migration. All seismic data are written to disk as processed sections in SEG-Y format. Details of the RR1508 processing parameters are given in Table 8 and SEG-Y trace headers in Table 9.</p> <p> </p> <p><strong>List of files</strong></p> <p>Figure 1. TAN1114 and RR1508 seismic line locations on the northern Hikurangi margin.</p> <p>Table 1. Summary of TAN1114 recording parameters.</p> <p>Table 2. Summary of TAN1114 lines acquired and processed.</p> <p>Table 3. Summary of TAN1114 line coordinates.</p> <p>Table 4. Summary of TAN1114 seismic processing sequence.</p> <p>Table 5. Summary of TAN1114 SEG-Y trace headers.</p> <p>Table 6. Summary of RR1508 recording parameters.</p> <p>Table 7. Summary of RR1508 lines acquired and processed.</p> <p>Table 8. Summary of RR1508 seismic processing sequence.</p> <p>Table 9. Summary of RR1508 SEG-Y trace headers.</p> <p> </p> <p>Processed SEGY seismic data</p> <p>TAN1114-01.sgy</p> <p>TAN1114-02.sgy</p> <p>TAN1114-03.sgy</p> <p>TAN1114-04.sgy</p> <p>TAN1114-04A.sgy</p> <p>TAN1114-05.sgy</p> <p>TAN1114-06.sgy</p> <p>TAN1114-06A.sgy</p> <p>TAN1114-07.sgy</p> <p>TAN1114-07A.sgy</p> <p>TAN1114-08.sgy</p> <p>TAN1114-09.sgy</p> <p>TAN1114-10.sgy</p> <p>TAN1114-10B.sgy</p> <p>TAN1114-11.sgy</p> <p>TAN1114-12.sgy</p> <p>TAN1114-12T.sgy</p> <p>TAN1114-13.sgy</p> <p>TAN1114-14.sgy</p> <p>TAN1114-15.sgy</p> <p>TAN1114-16.sgy</p> <p>TAN1114-17.sgy</p> <p>TAN1114-18.sgy</p> <p>TAN1114-19.sgy</p> <p>TAN1114-20.sgy</p> <p>TAN1114-21.sgy</p> <p>TAN1114-22.sgy</p> <p>TAN1114-23.sgy</p> <p>TAN1114-A.sgy</p> <p>RR1508-HKS01_01.sgy</p> <p>RR1508-HKS01_02.sgy</p> <p>RR1508-HKS01_02A.sgy</p> <p>RR1508-HKS01_03.sgy</p> <p>RR1508-HKS01_04.sgy</p> <p>RR1508-HKS01_05.sgy</p> <p>RR1508-HKS01_05A.sgy</p> <p>RR1508-HKS01_06.sgy</p> <p>RR1508-HKS01_07.sgy</p> <p>RR1508-HKS01_08.sgy</p> <p>RR1508-HKS01_09.sgy</p> <p>RR1508-HKS01_09A.sgy</p> <p>RR1508-HKS01_10.sgy</p>
Data for: Improving routine childhood immunisation outcomes in low- and middle-income countries: An evidence gap map
<p><strong>Objective</strong>: To support evidence-informed decision-making, we created an evidence gap map (EGM) to characterise the evidence base on the effectiveness of interventions in improving routine childhood immunisation outcomes in low- and middle-income countries (LMICs).</p> <p><strong>Methods</strong>: We developed an intervention-outcome matrix with 38 interventions and 43 outcomes. We searched academic databases and grey literature sources for relevant impact evaluations (IEs) and systematic reviews (SRs). Search results were screened on title/abstract. Those included in the title/abstract were retrieved for a full review. Studies meeting the eligibility criteria were included and data were extracted for each included study. All screening and data extraction was done by two independent reviewers. We analysed these data to identify trends in the geographic distribution of evidence, the concentration of evidence across intervention and outcome categories, and attention to vulnerable populations in the literature.</p> <p><strong>Results: </strong>We identified 309 studies, comprising 226 completed IEs, 58 completed SRs, 24 ongoing IEs, and 1 ongoing SR. Evidence from IEs is heavily concentrated in a handful of countries in Sub- Saharan Africa and South Asia. Among interventions, the most frequently evaluated are those related to education and material incentives for caregivers or health workers. There are gaps in the study of non-material incentives and outreach to vulnerable populations. Among outcomes, those related to vaccine coverage and health are well covered. However, evidence on intermediate outcomes related to health system capacity or barriers faced by caregivers is much more limited.</p> <p><strong>Conclusions:</strong> There is valuable evidence available to decision-makers for use in identifying and deploying effective strategies to increase routine immunisation in LMICs. However, additional research is needed to address gaps in the evidence base.</p>
HEartS Professional Survey: Charting the effects of COVID-19 on working patterns, income, and well-being among arts professionals in China (October 2020, August 2021)
<p>These data were collected using the HEartS Professional China survey from performing arts workers in China in October 2020 and August 2021. HEartS Professional China is an adaptation of the HEartS Professional surveys which were used in 2020-2021. All the surveys were designed as multi-strategy data collection tools with two main purposes: (1) to chart working patterns, income, sources of support, and indicators of mental and social well-being to identify trends in the effects of the lockdown at the time and (2) to explore the individual work and wellbeing experiences of performing arts professionals in their own words, to identify the subjective effects of lockdown in terms of challenges and opportunities. The survey covers six areas: 1) demographics; (2) information on illness or self-isolation related to COVID-19; (3) work profiles and income; (4) changes to work profiles and income as a result of the pandemic, as well as sources of support; (5) open-response questions about work and wellbeing experiences of lockdown including challenges and opportunities; and (6) validated measures of health, wellbeing, and social connectedness. The HEartS Professional surveys are adaptations of the HEartS Survey which charts the Health, Economic, and Social impacts of the ARTs (<a href="https://doi.org/10.5061/dryad.3r2280gdj">https://doi.org/10.5061/dryad.3r2280gdj</a>).</p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.