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23 results for “water access”
16S rRNA gene sequence accessions from discrete water column samples collected from lakes in the McMurdo Dry Valleys, Antarctica (2013-2023, ongoing)
An important component of the McMurdo Dry Valleys Long Term Ecological Research (MCM LTER) project is monitoring spatial and temporal patterns in the biological composition of perennially ice-covered lakes in Antarctica’s McMurdo Dry Valleys. This data package contributes to this core research area by providing a curated table linking 16S rRNA gene sequence accession numbers archived in NCBI to MCM LTER limnological sampling campaigns conducted at specific depths along the water column of Lakes Fryxell, Hoare, Bonney, and Miers. These data enable integration of microbial community data with co-collected biological, chemical, and physical measurements.
Online Appendix for Networks of Inequality: Access to Water in Roman Pompeii
<p><strong>Online Appendix for Networks of Inequality: Access to Water in Roman Pompeii (Samuli Simelius)</strong></p><p>in Journal of Computer Applications in Archaeology "A Bridge too Far – Historical, Archaeological and Criminal Network Research"(eds. M. De Bernardin, M. Lorenzon, L. Tambs & A. Traviglia)<br><br>Figure 1: The locations of the dwelling entrances used in the study, as well as the entrances to the unexcavated area.<br>Figure 2: The polyline layer representing the street network.</p><p>Table 1: The dwellings which I have interpreted differently from Matthew Notarian's interpretation – including their new water collection values.</p><p>Table 2: The population estimations of the dwellings and their new water collection values (seconds).<br>Table 3: The distances (minutes and meters) from dwellings to baths. </p>
Everyday risks and access to water and sanitation in Lilongwe urban and peri-urban areas
<p>The household survey INHAbIT Cities - UNHIDE (Investigating Natural, Historical and Institutional Transformations in Cities and Uncovering Hidden Dynamics in Slum Environments) focuses on urban risks and sanitation in Lilongwe. The aim was to assess access to basic services and risks perception of urban dwellers living in areas characterised by different conditions of access to water and sanitation and other basic services. Lilongwe was a small town of less than 20,000 inhabitants in 1966 and only started growing after it became the capital in 1975. Its population has reached approximately 1 million inhabitants, living in 58 administrative units, called areas. Infrastructures and service provision is concentrated in the central areas – where parliament, ministries, government offices, embassies, hotels and the commercial area were located - while low income areas suffer the most from infrastructure and basic services deficits. To illustrate, while some areas access water through in-house connections, others are served through water kiosks, characterised (in some areas) by high rates of discontinuity. Similarly, everyday risks are unevenly distributed across urban spaces: as shown in the survey perception of risks varies drastically from neighbourhood to neighbourhood and depending on the quality and availability of services provided. Data for this survey were collected between February and April 2015 by a team of local researchers, who administered the questionnaire in local language.</p> <p>Publications linked to this survey are:</p> <p>Rusca M., Alda Vidal C., Hordijk M., Kral N., (2017) Bathing without water, and other stories of everyday hygiene practices and risk perception in urban low-income areas: the case of Lilongwe, Malawi, Environment and Urbanisation Vol 29, Issue 2, pp. 533 – 550. </p> <p>Tiwale S., Rusca M<strong>.</strong>, Zwarteveen M., The power of pipes: mapping urban water inequities through the material properties of networked water infrastructures. The case of Lilongwe, Malawi, Water Alternatives, Water Alternatives 11(2): 314-335.</p> <p>Rusca M. (2018): Visualising urban inequalities: the ethics of videography and documentary filmmaking in water research, <em>Wires Water</em>, <a href="https://doi.org/10.1002/wat2.1292">https://doi.org/10.1002/wat2.1292</a></p>
Figure. The phylogenetic tree showing the relationship among Brevibacillus parabrevis strains SA2.2 and TJ2.3, Bacillus licheniformis MG4.2, and their phylogenetically closest type strains. The GenBank accession numbers of the type strains and studied strains are shown following species names. Distance matrix was calculated by Kimura's 2-parameter model. The scale bar indicates 0.02 substitutions per nucleotide position. Alicyclobacillus pohliae AJ564766 served as an out-group. in Distribution of extracellular enzyme-producing bacteria in the digestive tracts of 4 brackish water fish species
Figure. The phylogenetic tree showing the relationship among Brevibacillus parabrevis strains SA2.2 and TJ2.3, Bacillus licheniformis MG4.2, and their phylogenetically closest type strains. The GenBank accession numbers of the type strains and studied strains are shown following species names. Distance matrix was calculated by Kimura's 2-parameter model. The scale bar indicates 0.02 substitutions per nucleotide position. Alicyclobacillus pohliae AJ564766 served as an out-group.
Selection strategies to introgress water deficit tolerance derived from Solanum galapagense accession LA1141 into cultivated tomato (datasets)
<p>This dataset includes best linear unbiased predictors (BLUPs) used for composite interval mapping in the LA1141 × OH8245 BC<sub>2</sub>S<sub>3</sub> families (tab - BC2S3_BLUP_data_for_CIM), greenhouse data corresponding to the BC<sub>2</sub>S<sub>5</sub> advanced lines (tab - BC2S5_GH_trial), and field performance data corresponding to the BC<sub>2</sub>S<sub>5</sub> advanced lines (tab - BC2S5_Field_Trial).</p>
Survey on Understanding the Challenges of Accessing Water in Metro Manila
<p>Conducted in 2020, the results of the household survey (n=800) describe the challenges of accessing water by urban poor communities living in informal and resettlement sites in and around Metro Manila. Responses provide information on experiences related to price and availability of water, perceptions about the performance of water providers, coping strategies during water shortages, housing and sanitation conditions, and perceptions about the role and influence of state and non-state players related to water provision.</p>
SWDA Inequalities Dataset: Safe Water Drinking Water Access Indicator and Inequalities Indexes of Brazilian Municipalities
<p>The SWDA Inequalities Dataset consist on results of Safe Drinking Water Access - SDWA indicators and inequalities indexes obtained by an adapted Lorenz Curve approach calculated for all Brazilian municipalities.The main datasource is the Brazillian 2010 Demographic Census, which is the last Population Census data publicaly available. The SDWA indicators are weighted by the SDWA values corresponding to census tracts considering permanent private household residents (Eq. 2). The safe drinking water sources are: (i) general water distribution network; (ii) well or spring located on the property; (iii) rainwater stored in a cistern, cement box, etc.; (iv) or well or spring outside the property, tank car, rainwater stored otherwise, river, dam, lake or stream, or another form of water supply. Considering that these drinking water sources differ in terms of accessibility, availability and water quality, the AHP Method was applied to obtain different weights for each form of water access (Eq. 1).</p> <p>The Gini Index (G_water), Concentration Coefficient (C_water) and Dissimilarity Index (D_water), were adapted to analyze inequalities in SDWA. The Safe Drinking Water Concentration Index is obtained from the Lorenz Curve, with the percentage of residents in permanent households accumulated and ordered by <em>per capita income</em> in the abscissa of the graph (Eq. 3). The <em>per capita income</em> is obtained by the ratio between the total nominal monthly income and the number of residents of the permanent households of each census tract. The Safe Drinking Water Gini Index was similarly adapted, with the residents accumulated and ordered by the safe drinking water rate in the abscissa of the graph (Eq. 4). The ratios between Upper and Lower Quintiles (R_8020) were obtained for each municipality, that is, the relationship between the rates of SDWA for permanent private households that represent 20% of the residents with the highest average <em>per capita</em> income (4th quintile represented by <em>Q<sub>4</sub></em>) and the most economically unfavorable 20% (1st quintile represented by <em>Q<sub>1</sub></em>) (Eq. 5). The Safe Drinking Water Dissimilarity Index is calculated by the weighted average of the absolute difference of the SDWA indicator of each quintile of the average <em>per capita income</em> and the average rate (Eq. 6). The inequalities indexes are also presented as normalized values (G_water_norm, C_water_norm, R_8020_norm, D_water_norm).</p> <p><span class="math-tex">\(t_{water} = 0.376*t_{piped} + 0.309*t_{well} + 0.274*t_{cistern} + 0.041*t_{others} \;\;\;\;\;\;\;\;\;\; (Eq. 1) \)</span></p> <p><span class="math-tex">\(0.041 \leq t_{water} \leq 0.368\)</span></p> <p><span class="math-tex">\(t_{piped} + t_{well} + t_{cistern} + t_{others} = 1\)</span></p> <p><em>t </em>is the relationship between residents in permanent private households with access (piped, well, cistern and/or other) and the total number of residents in permanent private households.</p> <p><span class="math-tex">\(SDWA = \frac{\sum_{i=1}^{n} (t_{water_{norm_i}}*p_i)}{\sum_{i=1}^{n}(p_i)} \;\;\;\;\;\;\;\;\;\; (Eq. 2)\)</span></p> <p>considering the percentage of residents in permanent private households of each sector (<em>p<sub>i</sub></em>) and the number of census tracts (<em>n</em>).</p> <p><span class="math-tex">\(C_{water} = (p_{r_i}*t_{water_{norm_{i+1}}} - p_{r_{i+1}}*t_{water_{norm_{i}}}) + ... + (p_{r_{i-1}}*t_{water_{norm_{i}}} - p_{r_i}*t_{water_{norm_{i-1}}}) \;\;\;\;\;\;\;\;\;\; (Eq. 3)\)</span></p> <p>where <span class="math-tex">\(p_{r_i}\)</span> stand for a percentage of residents in permanent private households ordered by average income <em>per capita</em>, with <em>C<sub>water</sub></em><sub> </sub>ranging between -1 and 1.</p> <p><span class="math-tex">\(G_{water} = 1 - {\sum_{i=1}^{n}(p_{w_i}-p_{w_{i-1}})*(t_{water_{norm_i}} + t_{water_{norm_{i-1}}}}) \;\;\;\;\;\;\;\;\;\; (Eq. 4)\)</span></p> <p>where <span class="math-tex">\(p_{w_i}\)</span> is the percentage of residents in permanent private households ordered by the weighted water access rate ( <span class="math-tex">\(t_{water_{norm}}\)</span>), and <em>G<sub>water</sub></em> ranging between 0 and 1.</p> <p><span class="math-tex">\(R_{80/20} = \frac{t_{water_{norm_{Q_4}}}}{t_{water_{norm_{Q_1}}}} \;\;\;\;\;\;\;\;\;\; (Eq. 5)\)</span></p> <p>with <em>R<sub>80/20</sub></em><sub> </sub>ranging between 0 and ∞.</p> <p><span class="math-tex">\(D_{water} = \frac{1}{2\overline t_{water_{norm}}} \times \sum_{i=1}^{n}\beta_i |t_{water_{norm_i}} - \overline t_{water_{norm}}| \{ \sum \beta_i = 1 \;\;\;\;\;\;\;\;\;\; (Eq. 6)\)</span></p> <p>with <em>β<sub>i</sub></em> standing for the proportion of group <em>i</em> in the sample, <span class="math-tex">\(\overline t_{water_{norm}}\)</span> the normalized mean safe drinking water access rate of the municipality, <span class="math-tex">\(t_{water_{norm_i}}\)</span> the normalized safe drinking water access rate of group <em>i</em>, with a value between 0 and 1; and <em>n</em> the number of groups (<em>n</em>= 5); with <em>D<sub>water</sub> </em>presenting values between 0 and 1.</p>
The Safety and Efficacy of an Extravascular, Water-Soluble Sealant for Venous Access-Site Closure
ClinicalTrials.gov study NCT02438475. IPD Sharing: Not stated. Countries: 1. Publications: 5.
School Water Access, Food and Beverage Intake, and Obesity
ClinicalTrials.gov study NCT03181971. IPD Sharing: NO. Countries: 1. Publications: 3.
Data from: Wild chimpanzees (Pan troglodytes schweinfurthii) use tools to access out of reach water
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Data from: Barriers to access improved water and sanitation in poor peri-urban settlements of Abidjan, Côte d'Ivoire
Achieving access to safe water and sanitation still pose major challenges in urban areas of sub-Saharan Africa countries, despite all the progress achieved in the last decade. This study assessed the ability of populations living in poor peri-urban settlements to access improved water and sanitation and identified factors influencing this access, in order to guide sustainable mitigating solutions to address associated health and environmental risks. We conducted a cross-sectional study in six poor peri-urban settlements of Yopougon, the largest municipality of Abidjan. A total of 556 randomly selected households were included. The factors associated with access to improved water and sanitation were identified through explanatory models using multivariate logistic regression. A proportion of 25% of all households assessed did not have access to clean water and 57% lacked improved sanitation. Socioeconomic status and settlement characteristics appear as the main indicators of poor access to reliable water and sanitation in peri-urban settlements. The presence of the household head's wife at home was associated with greater access to clean water (OR = 3.57; 95% CI: 1.74, 7.31), thus highlighting the important role of women in ensuring access to clean water in these specific environments. Household size, education and religion were not significantly associated with the two considered outcomes. Women therefore should be involved at all levels of programming in water promotion in these settlements to improve the population's well-being. While religion does not appear to play an important role in access to water and sanitation, successful interventions should involve religious communities because of their large representation.
Unravelling the genetic diversity of water yam (Dioscorea alata L.) accessions from Tanzania using simple sequence repeat (SSR) markers
<p><span>Water yam</span><span> (<em>Dioscorea alata</em></span><span> L.) is among the most cultivated species used as a source of food and income for small-scale farmers in Tanzania. However, little is documented about <em>Dioscorea</em> species available in Tanzania, including their genetic diversity. This study used ten polymorphic microsatellite markers to determine the genetic diversity and relationship of 63 <em>D. alata</em> accessions from six major producing regions. Results revealed a polymorphic information content (PIC) of 0.63, while the number of alleles per locus ranged from 4 to 12 with a mean of 7.60. The expected heterozygosity ranged from 0.17 to 0.74, with a mean of 0.49, which suggests moderate genetic diversity of <em>D. alata</em> accessions. Kagera region had the highest mean number of (1.5) private alleles. Analysis of molecular variance revealed that 91% of the variation was attributed to within-population while among-population contributed 9% of the total variation. The highest Nei's genetic distance (0.65) was for accessions sampled from Arusha and Mtwara regions. Principal coordinate analysis and cluster analysis using Unweighted Paired Group Method using Arithmetic (UPGMA) grouped <em>D. alata</em> accessions into two major clusters regardless of geographical origin and local names. The Bayesian structure analysis confirmed the two clusters obtained in UPGMA and revealed an admixture of <em>D. alata</em> accessions in all six regions suggesting farmers' extensive exchange of planting materials. These results are helpful in the selection of <em>D. alata</em> accessions for breeding programs in Tanzania.</span></p>
Increasing Water Access and Appeal in Community Recreation Centers
ClinicalTrials.gov study NCT03637465. IPD Sharing: NO. Countries: 1. Publications: 2.
Data from: Barriers to access improved water and sanitation in poor peri-urban settlements of Abidjan, Côte d’Ivoire
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Data from: Interspecific interference competition at the resource patch scale: do large herbivores spatially avoid elephants while accessing water?
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Unravelling the genetic diversity of water yam (Dioscorea alata L.) accessions from Tanzania using simple sequence repeat (SSR) markers
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Data from: Elevated [CO2] mitigates the effect of surface drought by stimulating root growth to access sub-soil water
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Evaluation of the Impact of Water Access and Promotion in Parks on Beverage Intake
ClinicalTrials.gov study NCT03889561. IPD Sharing: NO. Countries: 1. Publications: 0.
Expanding Access to Safe Water in Nigeria
ClinicalTrials.gov study NCT07246824. IPD Sharing: NO. Countries: 1. Publications: 0.
Multi-omics profiling of 5 Arabidopsis accessions in response to combined water and nitrogen deficiencies
GEO Series GSE206890. Arabidopsis thaliana. 119 samples. Type: Expression profiling by high throughput sequencing.
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