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FIGURE 1 in Foraminifera biostratigraphy and paleoenvironment of Well 5, OML 34, Niger Delta, Nigeria
FIGURE 1. Location of studied well (modified after Odemerho; Urhobo Historical Society, 2008).
Table 2 in Morphometrical characterization of the Atlantic mudskipper species (Periophthalmus barbarus) (Linnaeus, 1766) (Perciformes; Gobiiae) from Abonema in Port Harcourt, Rivers State, Nigeria
<p><b>Table 2:</b> Minimum, maximum, means and standard deviation of Morphometrical measurements.</p><table><tbody><tr><th><b>Character</b></th><th><b>Minimum</b></th><th><b>Maximum Mean</b></th><th><b>Standard deviation</b></th></tr></tbody><tbody><tr><th>SL/TL</th><td>0.39</td><td>0.96</td><td>0.83</td><td>0.05</td></tr><tr><th>HL/TL</th><td>0.13</td><td>0.70</td><td>0.26</td><td>0.06</td></tr><tr><th>HW/HL</th><td>0.17</td><td>1.29</td><td>0.49</td><td>0.13</td></tr><tr><th>HD/HL</th><td>0.20</td><td>1.05</td><td>0.59</td><td>0.12</td></tr><tr><th>SNL/HL</th><td>0.03</td><td>0.65</td><td>0.32</td><td>0.10</td></tr><tr><th>ED/HL</th><td>0.01</td><td>0.50</td><td>0.24</td><td>0.07</td></tr><tr><th>PDL/TL</th><td>0.07</td><td>0.36</td><td>0.29</td><td>0.04</td></tr><tr><th>BD/TL</th><td>0.06</td><td>1.03</td><td>0.14</td><td>0.10</td></tr><tr><th>D1L/TL</th><td>0.03</td><td>0.19</td><td>0.13</td><td>0.04</td></tr><tr><th>D2L/TL</th><td>0.09</td><td>0.23</td><td>0.17</td><td>0.03</td></tr><tr><th>PFL/TL</th><td>0.06</td><td>0.27</td><td>0.17</td><td>0.05</td></tr><tr><th>AFL/TL</th><td>0.01</td><td>0.14</td><td>0.09</td><td>0.02</td></tr><tr><th>CFL/TL</th><td>0.07</td><td>0.24</td><td>0.16</td><td>0.03</td></tr><tr><th>CPL/TL</th><td>0.09</td><td>0.25</td><td>0.17</td><td>0.03</td></tr></tbody></table>
Table 3 in Morphometrical characterization of the Atlantic mudskipper species (Periophthalmus barbarus) (Linnaeus, 1766) (Perciformes; Gobiiae) from Abonema in Port Harcourt, Rivers State, Nigeria
<p><b>Table 3:</b> The linear measurements, Eigenvalue and the percentage variance.</p><table><tbody><tr><th><b>PC</b></th><th><b>Eigenvalue</b></th><th><b>% variance</b></th></tr></tbody><tbody><tr><th>1</th><td>0.0402861</td><td>55.892</td></tr><tr><th>2</th><td>0.00907681</td><td>12.593</td></tr><tr><th>3</th><td>0.00525164</td><td>7.286</td></tr><tr><th>4</th><td>0.0044251</td><td>6.1393</td></tr><tr><th>5</th><td>0.00371241</td><td>5.1505</td></tr><tr><th>6</th><td>0.00292212</td><td>4.0541</td></tr><tr><th>7</th><td>0.00193359</td><td>2.6826</td></tr><tr><th>8</th><td>0.000979485</td><td>1.3589</td></tr><tr><th>9</th><td>0.000803069</td><td>1.1142</td></tr><tr><th>10</th><td>0.000724781</td><td>1.0055</td></tr><tr><th>11</th><td>0.000611192</td><td>0.84796</td></tr><tr><th>12</th><td>0.000581671</td><td>0.807</td></tr><tr><th>13</th><td>0.000536577</td><td>0.74444</td></tr><tr><th>14</th><td>0.000233605</td><td>0.3241</td></tr></tbody></table>
Table 1 in Morphometrical characterization of the Atlantic mudskipper species (Periophthalmus barbarus) (Linnaeus, 1766) (Perciformes; Gobiiae) from Abonema in Port Harcourt, Rivers State, Nigeria
<p><b>Table 1:</b> Range (cm), mean and standard deviation of morphometric characters of <i>Periophthalmus barbarus</i> (n=100).</p><table><tbody><tr><th><b>Character</b></th><th><b>Minimum Maximum (cm) (cm)</b></th><th><b>Mean (cm)</b></th><th><b>Standard deviation</b></th></tr></tbody><tbody><tr><th>TL</th><td>9.28</td><td>14.86</td><td>11.41</td><td>1.15</td></tr><tr><th>SL</th><td>3.9</td><td>12.19</td><td>9.48</td><td>1.11</td></tr><tr><th>HL</th><td>1.47</td><td>7.5</td><td>3.01</td><td>0.69</td></tr><tr><th>HW</th><td>0.39</td><td>2.29</td><td>1.43</td><td>0.31</td></tr><tr><th>HD</th><td>0.91</td><td>2.66</td><td>1.74</td><td>0.34</td></tr><tr><th>SNL</th><td>0.1</td><td>1.9</td><td>0.95</td><td>0.31</td></tr><tr><th>PDL</th><td>0.71</td><td>4.64</td><td>3.29</td><td>0.53</td></tr><tr><th>ED</th><td>0.03</td><td>1.42</td><td>0.71</td><td>0.24</td></tr><tr><th>BD</th><td>0.57</td><td>11.58</td><td>1.59</td><td>1.13</td></tr><tr><th>D1L</th><td>0.36</td><td>2.8</td><td>1.46</td><td>0.50</td></tr><tr><th>D2L</th><td>1.08</td><td>3.13</td><td>1.90</td><td>0.38</td></tr><tr><th>PFL</th><td>0.57</td><td>3.35</td><td>1.96</td><td>0.68</td></tr><tr><th>AFL</th><td>0.13</td><td>1.83</td><td>1.03</td><td>0.25</td></tr><tr><th>CFL</th><td>0.7</td><td>3.1</td><td>1.80</td><td>0.45</td></tr><tr><th>CPL</th><td>0.84</td><td>2.83</td><td>1.95</td><td>0.41</td></tr></tbody></table>
Data from: Developing and applying a macroinvertebrate‐based multimetric index for urban rivers in the Niger Delta, Nigeria
<p class="MsoCommentText">Urban pollution of riverine ecosystem is a serious concern in the Niger Delta region of Nigeria. No biomonitoring tool exists for the routine monitoring of effects of urban pollution on riverine systems within the region. Therefore, the aim of this study was to develop and apply a macroinvertebrate-based multimetric index for assessing water quality condition of impacted urban river systems in the Niger Delta area of Nigeria. Macroinvertebrate and physico-chemical samples were collected from 11 stations in eight river systems. Based on the physico-chemical variables, the stations were categorised into three impact categories namely; least impacted stations (LIS), moderately impacted stations (MIS) and heavily impacted stations (HIS). Seventy seven (77) candidate metrics were tested and only five: Hemiptera abundance, %Coleoptera+Hemiptera, %Chironomidae+Oligochaeta, Evenness index and Logarithm of relative abundance of very large body size (>40-80 mm) were retained and integrated into the final Niger Delta urban multimetric index (MINDU). The validation data set showed a correspondence of 83.3% between the index result and the physico-chemically-based classification for the LIS and a 75% correspondence for the MIS. A performance of 22.2% was recorded for the HIS. The newly developed MINDU proved useful as a biomonitoring tool in the Niger Delta region of Nigeria, and can thus be used by environmental managers and government officials for routine monitoring of rivers and streams subjected to urban pollution.</p>
Image 1 in Ecological studies on Aerangis biloba (Lindl.) Schltr. (Orchidaceae) in NACGRAB field gene bank, southwestern Nigeria
Image 1. Map of Nigeria showing the location of study area
Image 3 in Ecological studies on Aerangis biloba (Lindl.) Schltr. (Orchidaceae) in NACGRAB field gene bank, southwestern Nigeria
Image 3. Aerangis biloba with whitish flowers
FPCA - From mobile app-based crowdsourcing to crowd-trusted food price estimates in Nigeria: pre-processing and post-sampling strategy for optimal statistical inference
<p>Timely and reliable monitoring of commodity food prices is an essential requirement for the assessment of market and food security risks and the establishment of early warning systems, especially in developing economies. However, data from regional or national systems for tracking changes of food prices in sub-Saharan Africa lacks the temporal or spatial richness and is often insufficient to inform targeted interventions. In addition to limited opportunity for [near-]real-time assessment of food prices, various stages in the commodity supply chain are mostly unrepresented, thereby limiting insights on stage-related price evolution. Yet, governments and market stakeholders rely on commodity price data to make decisions on appropriate interventions or commodity-focused investments. Recent rapid technological development indicates that digital devices and connectivity services are becoming affordable for many, including in remote areas of developing economies. This offers a great opportunity both for the harvesting of price data (via new data collection methodologies, such as crowdsourcing/crowdsensing — i.e. citizen-generated data — using mobile apps/devices), and for disseminating it (via web dashboards or other means) to provide real-time data that can support decisions at various levels and related policy-making processes. However, market information that aims at improving the functioning of markets and supply chains requires a continuous data flow as well as quality, accessibility and trust. More data does not necessarily translate into better information. Citizen-based data-generation systems are often confronted by challenges related to data quality and citizen participation, which may be further complicated by the volume of data generated compared to traditional approaches. Following the food price hikes during the first noughties of the 21st century, the European Commission's Joint Research Centre (JRC) started working on innovative methodologies for real-time food price data collection and analysis in developing countries. The work carried out so far includes a pilot initiative to crowdsource data from selected markets across several African countries, two workshops (with relevant stakeholders and experts), and the development of a spatial statistical quality methodology to facilitate the best possible exploitation of geo-located data. Based on the latter, the JRC designed the Food Price Crowdsourcing Africa (FPCA) project and implemented it within two states in Northern Nigeria. The FPCA is a credible methodology, based on the voluntary provision of data by a crowd (people living in urban, suburban, and rural areas) using a mobile app, leveraging monetary and non-monetary incentives to enhance contribution, which makes it possible to collect, analyse and validate, and disseminate staple food price data in real time across market segments. The granularity and high frequency of the crowdsourcing data open the door to real-time space-time analysis, which can be essential for policy and decision making and rapid response on specific geographic regions. <a href="https://datam.jrc.ec.europa.eu/datam/perm/news/870?rdr=1666109837893">Link to the project</a></p>
Floristic composition, structure and diversity of riparian forests in southwestern Nigeria: Conservation is inevitable
<p>The Nigerian riparian forest ecosystems had declined in extent and distribution and this had been attributed mainly to land use change. This study intended to provide an understanding of the links between plant diversity, composition, structures, and disturbances both anthropogenic and natural processes inducing the vegetation dynamics. Nine study sites were used for this study, within each site, five (5) plots (0.25 ha in size) were marked out and placed systematically at an interval of 10 m along the transect. A complete enumeration of plant species was carried out and identified at the species level. Diversity indices and structural parameters were determined and anthropogenic activities were ranked. A total number of 233 plant species were identified, belonging to 80 families; out of which, Euphorbiaceae and Apocynaceae were dominant families The density and basal area ranged from 2,200-6,000 ha<sup>-1</sup> and 2.59-17.58 m<sup>2</sup> ha<sup>-1</sup> respectively across the study sites. <em>Pterocarpus santalinoides</em>, <em>Alchornea cordiflora</em>, <em>Chassalia kolly</em>, <em>Tetracera</em> spp,<em> Fimbristylis</em>, <em>Bambusa vulgaris</em> and <em>Cyrtosperma senegalense</em> were the dominant species. The Shannon diversity index ranged from (1.38-3.49), Simpson (0.66-0.97), and Evenness diversity (0.43-0.84). Fisher alpha (10.03-30.21) and Whittaker beta diversity (0.36-0.89) values were highest in Ipetumodu (site VIII) and lowest in Ilesha (site II). Seventy-three (73%) of the species in this study had a low important value index (IVI). The dominance of some lianas and herbaceous species in the riparian forest sites showed disturbances, stages of ecological succession, and regeneration of the vegetation. Conservation is inevitable towards maintaining and protecting species diversity, ecosystem roles, and services of these forests in Nigeria.</p>
Fig. 28 in Terrestrial mollusc species richness and diversity in Omo Forest Reserve, Ogun State, Nigeria
Fig. 28. Dendrogram of Bray-Curtis similarity between plots in sites I and II.
Fig. 2 in Terrestrial mollusc species richness and diversity in Omo Forest Reserve, Ogun State, Nigeria
Fig. 2. Rank abundance curve for terrestrial snails from Omo Forest Reserve in Ogun State, Nigeria.
Development Gateway shisha study qualitative data: Understanding factors influencing Shisha smoking in Nigeria
<p>79 qualitative transcripts from semi-structured interviews conducted across 13 states in Nigeria with either six (for Adamawa, Anambra, Ebonyi, Edo, FCT, Gombe, Kaduna, Kogi, Lagos, Oyo, Plateau and Rivers) or seven (Kano) qualitative transcripts per state. The transcripts are from a study exploring the following questions:</p> <ol> <li>What factors (demographic, social, cultural, behavioural, etc.) are associated with the use of shisha in Nigeria?</li> <li>What are the shisha use patterns and behaviours among those who use shisha in Nigeria?</li> </ol> <p>Respondents were self-reported current shisha users identified from public places that are known to provide spaces for use of shisha such as social clubs, night clubs, bars, pubs, cafes, and restaurants. Study participants had to be at least 18 years old to participate in the study.</p> <p>Topics covered in the interviews include respondent’s history of shisha smoking, perceived benefits from smoking shisha, awareness of health implications of smoking shisha, perceptions towards selected health risks of shisha smoking, use of sundry substances and other risky behaviours, and regulations Laws on shisha use in Nigeria.</p> <p>The data was collected between December 2021 and January 2022</p> <p>Also included with the dataset is the interview guide.</p> <p> </p>
LEVELS OF POLYCYCLIC AROMATIC HYDROCARBON IN THE SOIL AROUND TYPICAL AUTOMOBILE REPAIR WORKSHOPS IN NIGERIA
<p>the data was obtained for the levels of Polycyclic Aromatic Hydrocarbon in the soil around typical automobile repair workshops in Nigeria. </p>
The Constitutionality or Otherwise of the 2017 Guidelines on the Implementation of Treasury Single Account (TSA)/E-Collection in Nigeria
<p>By now, it is trite that Sections 80 (1) and 162 (1) of the Constitution of the Federal Republic of Nigeria, 1999 (the Constitution), provide for the Treasury Single Account (TSA) and Federation Account (FA); which sections also exempt certain receipts from the TSA and FA. This paper therefore considers the 2017 Guidelines on the Implementation of Treasury Single Account (TSA)/e-Collection (the Guidelines), which the Office of the Accountant General of the Federation empowered to monitor and manage the Treasury Single Account and the Federation Account has issued. This Guidelines directs all federal government Ministries, Departments and Agencies to remit their revenue to the TSA, TSA Sub-Accounts or FA, whilst only exempting Federal Government equity funded enterprises which are still required to pay dividends into the TSA. This sweeping directive is claimed to have been released to ensure total compliance with sections 80 (1) and 162 (1) of the Constitution. It is against the backdrop of the foregoing that this paper x-rays the provisions of the Constitution, and as a corollary, various Acts of the National Assembly, to the end of determining the conformity or otherwise of the Guidelines, to their provisions.</p>
Data set for fossil Co2 emission in Nigeria
<p>Here is a dataset that captures fossil Co2 emission in Nigeria. </p>
Hydrological dataset of Selected Rivers in South Eastern Nigeria
<p>The dataset was obtained from NASA/MERRA-2, which spans from 1981-2019. The hydrological properties are relative humidity (H), atmospheric pressure (P), wind speed (S), rainfall (F), radiation (R), air temperature (Ta), earth-skin temperature (Ts), and discharge (Q).</p>
Youth Power Action Feasibility Study of Online Support Group Intervention Among Adolescents Living With HIV in Nigeria
ClinicalTrials.gov study NCT03076996. IPD Sharing: NO. Countries: 1. Publications: 1.
HIV Self-Testing and Long-Acting Injectables for HIV Treatment and Prevention Among Commercial Minibus Drivers (I-TEST LAIs) in Nigeria
ClinicalTrials.gov study NCT07000513. IPD Sharing: NO. Countries: 1. Publications: 2.
Tablet-based Mobile Health Ultrasound for Point-of-care Breast Cancer Diagnosis in Nigeria
ClinicalTrials.gov study NCT04501419. IPD Sharing: YES. Countries: 1. Publications: 1.
Management of Severe Acute Malnutrition in SCD, in Northern Nigeria
ClinicalTrials.gov study NCT03634488. IPD Sharing: NO. Countries: 2. Publications: 5.
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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.