Vol. 6 No. 3 (2026): Researchers Journal of Science and Technology

Published: 2026-04-08

Articles

Effects of Zinc Oxide Nanoparticle Spiking on Physicochemical Parameters and Substrate-Induced Respiration in Ultisols

N. U. Nkantion

1 - 10
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Prevalence of Intestinal Parasites and the Therapeutic Potential of Andrographis Paniculata Leaf Extract in Managing Coccidiosis and Enhancing Growth Performance in Broiler Chickens

N. N. George, L. P. Usip, K. N. Opara, N. D. Ekpo

11 - 31
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Integrated Qualitative and Quantitative Evaluation of Depositional Environment and Hydrocarbon Prospectivity of the QX Field in Southeastern Niger Delta

N. Justina Ekiliwo, Anietie E. Ekot

32 - 62
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Optimized Stacking Ensemble of Random Forest and XGBoost for Heart Disease Prediction

U. Sani, A. A. Abubakar, D. G. Lazarus, A. A. Babajo

63 - 78
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        <title locale="en_US">Estimation of aquifer geohydrodynamic properties using the Inverse Slope method</title>
        <abstract locale="en_US">&lt;p&gt;This study is aimed at estimating aquifer geohydrodynamic properties of the hinterland aquifers of Obot Akara Local Government area for groundwater development in the area. A total of 12 Vertical Electrical Soundings (VES) was conducted in the area with the use of the Schlumberger electrode configuration with maximum current electrode separation of 600. The acquired data were interpreted using the modified Inverse Slope Method (ISM) to obtain the primary geoelectric parameters of the various lithological and hydrogeological units penetrated by the current in the area. The areais shown to comprise 3 to 4 geoelectric layers, with the third layer constituting the economical exploitable aquifer.&amp;nbsp; The thickness of this layer varies from 54.4 to 129.5 m with an average value of 86.7 m while its bulk resistivity varies from 396.0 to 3333.3&#x2126;m with an average value of 1425.5 &#x2126;m. These two primary aquifer parameters were&amp;nbsp;used in conjunction with empirical relations in&amp;nbsp;literature to estimate the geohydrodynamic&amp;nbsp;properties of the hinterland aquifers in the area. The estimated properties are pointers to the fact that aquifers in the area are very productive.&lt;/p&gt;</abstract>
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            <givenname locale="en_US">Aniekan</givenname>
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            <affiliation locale="en_US">Department of Physics, Geophysics Research&#xA0;Group (GRG), Akwa Ibom State University, Ikot&#xA0;Akpaden, Mkpat Enin, Nigeria</affiliation>
            <country>NG</country>
            <email>anny4mart@yahoo.com</email>
            <biography locale="en_US">&lt;p&gt;aniekanekanem@aksu.edu.ng&lt;/p&gt;</biography>
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    <article xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" locale="en_US" date_submitted="2022-08-13" status="3" submission_progress="0" current_publication_id="8" stage="production">
      <id type="internal" advice="ignore">8</id>
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        <name locale="en_US">ETESIN et al REJOST 2021.pdf</name>
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      <publication xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" locale="en_US" version="1" status="3" primary_contact_id="14" url_path="" seq="6" date_published="2021-12-01" section_ref="ART" access_status="0" xsi:schemaLocation="http://pkp.sfu.ca native.xsd">
        <id type="internal" advice="ignore">8</id>
        <title locale="en_US">Assessment of the Quality of water samples from Private Boreholes in Eket Local Government Area, Akwa Ibom State, Nigeria</title>
        <abstract locale="en_US">&lt;p&gt;Th&lt;strong&gt;e &lt;/strong&gt;major source of drinking water in our local communities is private boreholes, in which the quality of water becomes a public health concern.In an attempt to ascertain the health risk that thepeople are exposed to, this study was conducted to assess the quality of water from private boreholes in Eket Local Government Area. Water samples from the boreholes were subjected to analyses forphysico-chemical characteristics. For this purpose, water samples were collected from ten private boreholes for analyses and compared with the World Health Organization (WHO) permissible guidelines for potable water. Some of the parameters analyzed for by the standard test methods for the examination of water and wastewater were: pH, conductivity, dissolved&amp;nbsp; oxygen, redox potentials, nutrients, trace metals, iron, total hardness, calcium, magnesium, total alkalinity, bicarbonate alkalinity, carbonate, hydroxide and alkalinity. pH values of the water samples gave values that were below the permissible range of 6.5 to 8.5 for potable water, whereas, values for dissolved oxygen, redox potential, total dissolved solids, total hardness, calcium content, magnesium content, sulphate, phosphate, nitrate and sulphide were below the permissible limits for potable water. Alkalinity determination indicated that the water samples from boreholes have predominantly bicarbonate alkalinity, with negligible carbonate and hydroxide alkalinity. Though, the total alkalinity was below the permissible limit, the water samples are likely to form scales in boilers and heaters. The total hardness of the considered samples indicated the hardness classification range of 17.5&amp;nbsp; g/l to 59.5 mg/l, which is slightly hard and may require minor treatment for drinking and other domestic purposes. Notwithstanding the fact that the exploited aquifer in Eket has shallow depths of between 16.0 m to 30.4 m, values for lead, cadmium, copper, zinc, iron and manganese were below the permissible limits, except in station 1, in which the water has enhanced iron content above the permissible limit of 0.3 mg/l. The water samples had mean salinity of 0.01 %,&amp;nbsp;indicating that there is no salt water intrusion even though Eket is a coastal area. The mean pollution index calculated for all the sample parameters gave values that were below the critical value of&amp;nbsp;one, indicating no contamination of the aquifer by anthropogenic activities.&amp;nbsp;&lt;/p&gt;</abstract>
        <licenseUrl>https://creativecommons.org/licenses/by-nc-nd/4.0</licenseUrl>
        <copyrightYear>2022</copyrightYear>
        <keywords locale="en_US">
          <keyword>Water Quality Index</keyword>
          <keyword>Pollution Index</keyword>
          <keyword>Boreholes</keyword>
          <keyword>Potable Water</keyword>
          <keyword>Aquifer</keyword>
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</embed>
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    <article xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" locale="en_US" date_submitted="2022-08-13" status="3" submission_progress="0" current_publication_id="7" stage="production">
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        <name locale="en_US">JEWEL _REJOST 2021.pdf</name>
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      <publication xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" locale="en_US" version="1" status="3" primary_contact_id="13" url_path="" seq="3" date_published="2021-12-01" section_ref="ART" access_status="0" xsi:schemaLocation="http://pkp.sfu.ca native.xsd">
        <id type="internal" advice="ignore">7</id>
        <title locale="en_US">Lithosphere-Atmosphere-Ionosphere Coupling Processes for Pre-, Co-, and Post Earthquakes: A case study of Northern Mariana, U.S.A. Earthquake of 31st October, 2007</title>
        <abstract locale="en_US">&lt;p&gt;Using the Plasma analyzer (IAP)and Langmuir Probe (ISL) experiments of the (Detection of Electromagnetic Emissions Transmitted from Earthquake Regions (DEMETER) and Total Electron Content (TEC) from GPS data, lithospheric-atmospheric - ionospheric coupling has been observed before, during and after the magnitude 7.2 Northern Mariana, U.S.A. Earthquake of 31st October, 2007. Both sets of data recorded perturbations within the investigative period. The study revealed pre &#x2013; ionospheric variations on -17 day in the TEC with a value of 3.57 Total electron content unit (TECU) at 8:00 UTC while the IAP and ISL (Electron density) sensors of the DEMETER had 2.83 cm3 and 3.95 cm3 respectively on - 4 days. All pre -ionospheric perturbations were recorded in the morning. A co - ionospheric perturbation was revealed by the Electron Density with a value of -2.04 cm3 during&amp;nbsp;the night time reading on the earthquake day (day 0). Four post - seismic day perturbations were&amp;nbsp;recorded on day 2 (2.35 K and day 3 (2.15 K)&amp;nbsp;from Electron temperature of the ISL experiment&amp;nbsp;and 2.18 cm3 and 3.98 cm3 on days 5 and 7&amp;nbsp;respectively from the IAP sensor. The observed&amp;nbsp;anomalies were screened for false alarm using the&amp;nbsp;geomagnetic indices of Kernnifzer digit (Kp) and&amp;nbsp;disturbance storm time (Dst.) It was however&amp;nbsp;realized that the state of the ionosphere was&amp;nbsp;geomagnetically quiet on these days; hence the&amp;nbsp;observed variations were seismogenic.&amp;nbsp;&lt;/p&gt;</abstract>
        <licenseUrl>https://creativecommons.org/licenses/by-nc-nd/4.0</licenseUrl>
        <copyrightYear>2022</copyrightYear>
        <keywords locale="en_US">
          <keyword>Earthquake</keyword>
          <keyword>DEMETER</keyword>
          <keyword>TEC</keyword>
          <keyword>Perturbations</keyword>
          <keyword>Seismogenic</keyword>
        </keywords>
        <authors xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://pkp.sfu.ca native.xsd">
          <author include_in_browse="true" user_group_ref="Author" seq="3" id="13">
            <givenname locale="en_US">Jewel</givenname>
            <familyname locale="en_US">Thomas</familyname>
            <affiliation locale="en_US">Department of Physics, Geophysics Research Group&#xA0;(GRG), Akwa Ibom State University, Ikot Akpaden,&#xA0;Mkpat Enin, Nigeria</affiliation>
            <country>NG</country>
            <email>jewelemem@gmail.com</email>
          </author>
        </authors>
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        <name locale="en_US">Nyong et al _ REJOST 2021.pdf</name>
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      <publication xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" locale="en_US" version="1" status="3" primary_contact_id="9" url_path="" seq="5" date_published="2021-12-01" section_ref="ART" access_status="0" xsi:schemaLocation="http://pkp.sfu.ca native.xsd">
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        <title locale="en_US">Self- Cleaning Materials: Review of Recent Progress and Innovations</title>
        <abstract locale="en_US">&lt;p&gt;This paper is a review of some of the trends in the theoretical conception and development of&amp;nbsp;self-cleaning materials for various applications.&amp;nbsp;This review is significant as it highlights briefly&amp;nbsp;the various research activities in the area of self-cleaning materials. Beyond the Wenzel, Cassie-Baxter and Young's Models that are used in theoretically examining the concept of self-cleaning, there is advancement of modelling and simulation of contact angles behaviour to include the effect of gravitational forces. Furthermore, research trends in three (3)&amp;nbsp;different areas, namely; self-cleaning glasses,&amp;nbsp;self-cleaning fabrics and self-cleaning cements&amp;nbsp;have been discussed in some details. It has been&amp;nbsp;noted that researches have focused on the use of photocatalyst, mainly TiO2 and SiO2, to generate self-cleaning surfaces that are capable of photodegrading organic matter. These photo-catalysts are added &lt;em&gt;in-situ &lt;/em&gt;to the materials or&amp;nbsp;coated on to the materials' surfaces. Different&amp;nbsp;methods of coating of these photocatalysts on to&amp;nbsp;the surfaces of the materials have been developed. Some of these coating methods that&amp;nbsp;have seen great interest recently are the pad-dry&amp;nbsp;cure and sol-gel coating methods&lt;/p&gt;</abstract>
        <licenseUrl>https://creativecommons.org/licenses/by-nc-nd/4.0</licenseUrl>
        <copyrightYear>2022</copyrightYear>
        <keywords locale="en_US">
          <keyword>Self-cleaning</keyword>
          <keyword>Photocatalyst</keyword>
          <keyword>Superhydrophobic</keyword>
        </keywords>
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        <title locale="en_US">Intelligent Surveillance and Facial Recognition System for Efficient Border Monitoring and Threats Prediction Using Machine Learning Approach</title>
        <abstract locale="en_US">&lt;p&gt;Border authenticate an integral portion in a&amp;nbsp;country's security, but borders are extremely prone and vulnerable to unauthorized&amp;nbsp;migration, illegal smuggling of goods and drugs, human trafficking and assaults by the extremists as well as intrusion and cohesion between several parties. Border surveillance is&amp;nbsp;the most central task in the area of national&amp;nbsp;security and defense. Basically, borders need to be secured and kept under close monitoring and control for effective surveillance at different border points, which are stretched across&amp;nbsp;hundreds of miles and have extreme terrain as&amp;nbsp;well as climatic conditions. Hence, the need of&amp;nbsp;the moment is to develop an automated border&amp;nbsp;surveillance system which can perform the&amp;nbsp;surveillance task without requiring any human&amp;nbsp;intervention.&amp;nbsp;The proposed system uses Internet Protocol&amp;nbsp;(IP) camera or thermal imaging (TI) camera for&amp;nbsp;detection of various objects and infiltrators. The&amp;nbsp;Camera is assigned an IP address and&amp;nbsp;connected through local network to the control&amp;nbsp;center. Software code captures video and subsequently the intrusion detection.&amp;nbsp;Machine Learning &lt;strong&gt;(ML) &lt;/strong&gt;approach with&amp;nbsp;Principal Component Analysis &lt;strong&gt;(PCA) &lt;/strong&gt;and Viola Jones Algorithm was adopted for the intelligence recognition and facial detection of persons from list of images captured based on the surveillance IP camera. Consequently, the data sets were segmented into training set and test set of 300 images and 100 images respectively. Furthermore, we subjected our PCA model to an accuracy test and selected&amp;nbsp; out&amp;nbsp;different individual faces. These faces were all&amp;nbsp;tested with our face recognition system and&amp;nbsp;data was further computed in confusion matrix&amp;nbsp;for performance evaluation and system&amp;nbsp;accuracy. The confusion matrix demonstrated&amp;nbsp;an overall accuracy of 83%, which indicates a&amp;nbsp;good outcome of the Viola Jones Algorithm in&amp;nbsp;&amp;nbsp;our intelligent border surveillance system&amp;nbsp;(IBSS).&amp;nbsp;&amp;nbsp;&lt;/p&gt;</abstract>
        <licenseUrl>https://creativecommons.org/licenses/by-nc-nd/4.0</licenseUrl>
        <copyrightYear>2022</copyrightYear>
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          <keyword>Intelligent Border Surveillance System(IBSS)</keyword>
          <keyword>Machine Learning (ML)</keyword>
          <keyword>Thermal Imaging (TI) camera</keyword>
          <keyword>Principal Component Analysis (PCA)</keyword>
          <keyword>Viola Jones Algorithm</keyword>
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            <givenname locale="en_US">Imeh</givenname>
            <familyname locale="en_US">Umoren</familyname>
            <affiliation locale="en_US">Department of Computer Science, Akwa Ibom&#xA0;State University, Mkpat Enin, Akwa Ibom State,&#xA0;Nigeria</affiliation>
            <country>NG</country>
            <email>imehumoren@aksu.edu.ng</email>
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            <givenname locale="en_US">Saviour</givenname>
            <familyname locale="en_US">Inyang</familyname>
            <affiliation locale="en_US">Department of Computer Science, Akwa Ibom&#xA0;State University, Mkpat Enin, Akwa Ibom State,&#xA0;Nigeria</affiliation>
            <country>NG</country>
            <email>imehumoren@aksu.edu.ng</email>
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        <title locale="en_US">Modeling and Evaluation of Soft Handoff in Wireless Communication Networks for Effective Performance Based on Traffic Indicators</title>
        <abstract locale="en_US">&lt;p&gt;The ever growing provision of highly developed services in Mobile networks required operators to offer severe Quality of Service (QoS) assurance. This goal can be accomplished by applying several optimization measures. One of the most significant indexes for QoS evaluation is the call admission and drop-call probability. Consequently, these core indexes in networks service performance have not deeply been studied in well-established mobile network environments. Indeed, these requirements, judging from an accurate statistical analysis on realistic data call for a proposed model for optimizing soft handoff of the call admission and subsequent drop call occurrences in Code Division Multiple Access (CDMA) Networks. Performance analysis on statistical field data validates the efficiency of the model already available theoretically, considering handoff&amp;nbsp;failure as the main reason of drop calls, which offer a minor contribution for service optimization in an established cellular network. Basically, many other incidents indicate more relevant factor in influencing the call admission and call dropping. Nonetheless, the proposed model relates the drop-call probability with call&amp;nbsp;admission parameters. The level of its effectiveness has been demonstrated and&amp;nbsp;authenticated by experimental procedures.&amp;nbsp;Essentially, results reveal how each traffic&amp;nbsp;parameter affects cellular network performance&amp;nbsp;and QoS provisioning. Consequently, network&amp;nbsp;performance considered response time&amp;nbsp;indicating how fast a packet can be sent or how quickly a document can be retrieved. The&amp;nbsp;outcome of this work demonstrates how the&amp;nbsp;network performance can be affected by traffic&amp;nbsp;metrics; types of network traffic, the number of&amp;nbsp;devices connected on the network, network&amp;nbsp;latency, number of transmission errors and the&amp;nbsp;bandwidth of the transmission medium.&amp;nbsp;&amp;nbsp;&lt;/p&gt;</abstract>
        <licenseUrl>https://creativecommons.org/licenses/by-nc-nd/4.0</licenseUrl>
        <copyrightYear>2022</copyrightYear>
        <keywords locale="en_US">
          <keyword>QoS assurance</keyword>
          <keyword>call admission</keyword>
          <keyword>drop-call&#xA0;probability</keyword>
          <keyword>handoff failure</keyword>
          <keyword>Code Division Multiple Access (CDMA)</keyword>
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        <title locale="en_US">Assessment of heavy metals concentration in sediments of Utibete River, Eastern Obolo, Southeastern Nigeria using particle induced X-ray emission (PIXE) technique</title>
        <abstract locale="en_US">&lt;p&gt;The contamination of heavy metals constituent&amp;nbsp;of sediments in Utibete River in Eastern Obolo, Akwa Ibom, Nigeria was assessed. In application of PIXE techniques, ten heavy&amp;nbsp;metals, Ti, Cr, Mn, Fe, Cu, Zn, Rb, Sr, Zr and Pb, were determined from each of the sediment&amp;nbsp;samples obtained at 6 sampling sites. The concentration of Fe was the highest in all the sampling sites ranged 11371.6 &#x2013; 45095.9 ppm Pollution indices such as enrichment factor (EF),&amp;nbsp;geo-accumulation index (Igeo) and contamination factor (CF) were employed to assess the toxicity threat posed on that part of the ecosystem by the investigated heavy metals. The results of the three pollutions indices were&amp;nbsp;similar, indicating that that part of that River was highly polluted with Cr, Rb, Zr, Zn, and Mn, Pb&amp;nbsp;at some point. Pollution lead index (PLI)&amp;nbsp;employed for contamination assessment showed 5 of the sampling sites of Utibete River were contaminated with heavy metals determined with the exception of site 2 where there is low contamination of those heavy metals. These high inputs of the heavy metals might be due to&amp;nbsp;pronounced anthropogenic influences around the&amp;nbsp;studied areas. Analysis of multivariate statistics&amp;nbsp;such as Pearson&#x2019;s Correlation coefficient and&amp;nbsp;cluster analysis were also applied to ascertain the&amp;nbsp;relationship and sources of investigated heavy&amp;nbsp;metals. Both positive and negative correlations&amp;nbsp;were observed among some heavy metals while&amp;nbsp;the cluster analysis revealed four main clusters.&amp;nbsp;&amp;nbsp;&lt;/p&gt;</abstract>
        <licenseUrl>https://creativecommons.org/licenses/by-nc-nd/4.0</licenseUrl>
        <copyrightYear>2022</copyrightYear>
        <keywords locale="en_US">
          <keyword>Heavy metals</keyword>
          <keyword>sediments</keyword>
          <keyword>Particle&#xA0;induced emission technique (PIXE)</keyword>
          <keyword>enrichments factor (EF)</keyword>
          <keyword>geo-accumulation index (Igeo)</keyword>
          <keyword>Contamination factor (CF)</keyword>
          <keyword>pollution load&#xA0;index (PLI)</keyword>
        </keywords>
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            <givenname locale="en_US">Okwet</givenname>
            <familyname locale="en_US">Yawo</familyname>
            <affiliation locale="en_US">Department of Physics, Akwa Ibom State University, Ikot&#xA0;Akpaden, Nigeria</affiliation>
            <country>NG</country>
            <email>okwetyawo33@gmail.com</email>
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            <givenname locale="en_US">Ita</givenname>
            <familyname locale="en_US">Akpan</familyname>
            <affiliation locale="en_US">Department of Physics, University of Calabar, Calabar,&#xA0;Nigeria</affiliation>
            <country>NG</country>
            <email>itayenakpan@yahoo.com</email>
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        <title locale="en_US">Analysis of ionospheric response to Earthquake using GPS data: a case study of Chignik, North America and Southern-Sandwich, South America Earthquakes</title>
        <abstract locale="en_US">&lt;p&gt;In this study, GPS-derived total electron&amp;nbsp;content (TEC) data were utilized to monitor&amp;nbsp;ionospheric behaviour 20 days before and 5days after two significant earthquakes that&amp;nbsp;occurred in Chignik, North America and Southern-Sandwich, South America on 10th November 2021 and 8th December 2021 respectively. Data were collected from GPS stations within the seismogenic zone. The sunspot number (SSN) and F10.7 indices were used to track solar activity during the events, while the planetary geomagnetic activity index (kp) and disturbance storm-time (Dst) indices were used to check geomagnetic activity. Results from the analysis revealed that TEC data contain both negative and positive&amp;nbsp;ionospheric anomalies during the investigative period using a statistical analysis technique that&amp;nbsp;involved moving median. Geomagnetic and&amp;nbsp;solar indices indicated relative stillness during 88% of the anomalous days isolated for the earthquakes, hence anomalies were considered seismogenic. The result further suggests that a significantamount of disturbances is caused by seismogenic processes. As earthquake-induced anomalies were found within 20 days of the studied cases, it was also shown by the&amp;nbsp;discovery of earthquake-induced TEC anomalies through temporal analysis that ionospheric fluctuations are crucial for earthquake forecasting. Therefore, this study suggests that there could be a connection between TEC anomalies in the ionospheric&amp;nbsp;space and the occurrence of significant earthquakes. Thus, it is advised that TEC monitoring be seriously taken into account for short-term earthquake event forecasting, particularly in regions with unreliable seismic measurements.&lt;/p&gt;</abstract>
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            <affiliation locale="en_US">Department of Physics, Faculty of Physical&#xA0;Sciences, Akwa Ibom State University, Ikot&#xA0;Akpaden, Mkpat Enin</affiliation>
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        <title locale="en_US">Assessment of Heavy Metals Concentration in Soil of Champion Breweries Plc, Aka Offot, Uyo, Southern Nigeria Using X-Ray Fluorescence Technique</title>
        <abstract locale="en_US">&lt;p&gt;The contamination of heavy metals present in soil of Champion Breweries Plc, Aka Offot, Uyo, in Southern Nigeria was assessed. In application of XRF techniques, seventeen (17) heavy metals, namely potassium (K), calcium(Ca), titanium (Ti), vanadium (V), chromium (Cr), manganese (Mn), iron (Fe), nickel (Ni), copper (Cu), zinc (Zn), gallium (Ga), arsenic (As), bromine (Br), rubidium (Rb), strontium (Sr), yttrium(Y), and zirconium (Zr), were determined from each of the soil samples obtained at four (4) sampling sites. Fe&amp;nbsp; had the highest concentration in all the sampling sites&amp;nbsp;&amp;nbsp;in the range of 17320.0 &#x2013; 29380.0 ppm and Ga had the lowest concentration in all the four-sampling site, ranging from 8.16 &#x2013; 62.713 ppm. Co was only detected in one sampling site. The Enrichment factor (EF), geo-accumulation index (Igeo) and contamination factor (CF) were used as pollution indices to assess the toxicity threat posed on that part of the ecosystem by the investigated heavy metals. The results of the three pollutions indices were similar, indicating that the part of the industry was highly polluted with Cr, Rb, Zr, Zn, and Mn, Pb at some point. These high inputs of the heavy metals might be due to pronounced anthropogenic influences around the studied area. Analysis of multivariate statistics such as Pearson&#x2019;s Correlation coefficient and cluster analysis were also applied to ascertain the relationship and sources of investigated heavy metals. Both positive and negative correlations were observed among some heavy metals. Rb was observed to have a strong positive correlation with As, Ga, Zn. Ti has a strong&amp;nbsp; negative correlation with Cr, Br, Rb and a strong positive value with Fe and Zr which suggest that these elements are from the same origin. Low correlation between Ca -As, Ga - Zr, Mn &#x2013; Rb, etc suggest that they come from different sources. Cluster analysis revealed two main clusters, this shows that elements in each of the cluster can specifically be said to come&amp;nbsp;from the same source.&amp;nbsp;&lt;/p&gt;</abstract>
        <licenseUrl>https://creativecommons.org/licenses/by-nc-nd/4.0</licenseUrl>
        <copyrightYear>2022</copyrightYear>
        <keywords locale="en_US">
          <keyword>X-Ray Fluorescence (XRF)&#xA0;technique</keyword>
          <keyword>heavy metals</keyword>
          <keyword>soil pollution</keyword>
          <keyword>enrichment factor (EF)</keyword>
          <keyword>geo-accumulation&#xA0;index (Igeo)</keyword>
          <keyword>contamination factor (CF)</keyword>
        </keywords>
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            <givenname locale="en_US">Ambrose</givenname>
            <familyname locale="en_US">Dominic</familyname>
            <affiliation locale="en_US">Department of Physics, Akwa Ibom State University,&#xA0;Ikot Akpaden, Nigeria</affiliation>
            <country>NG</country>
            <email>prosperlly@gmail.com</email>
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            <givenname locale="en_US">Ita</givenname>
            <familyname locale="en_US">Akpan</familyname>
            <affiliation locale="en_US">Department of Physics, University of Calabar, Calabar,&#xA0;Nigeria</affiliation>
            <country>NG</country>
            <email>itayenakpan@yahoo.com</email>
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            <givenname locale="en_US">Okwet</givenname>
            <familyname locale="en_US">Yawo</familyname>
            <affiliation locale="en_US">Department of Physics, Akwa Ibom State University,&#xA0;Ikot Akpaden, Nigeria</affiliation>
            <country>NG</country>
            <email>okwetyawo33@gmail.com</email>
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        <title locale="en_US">Assessment of Contamination Status of Heavy Metals in Sediment due to Gas Flaring at Esit Eket, South Eastern Nigeria</title>
        <abstract locale="en_US">&lt;p&gt;This study assessed the contamination status of heavy metals in sediment of Esit Eket, south eastern Nigeria due to gas flaring. Six sediment samples were collected into well labeled polyethene bags with the use of a hand trowel at a depth of 10cm during the dry season in the month of February precisely in the intertidal zone at extremely low tide randomly from the flare point to a distance of about 250m away from the flare site. These samples were refrigerated for two days before transported to the laboratory to analyze for heavy metals concentration using a particle induced x-ray emission (PIXE) technique. Heavy metals such as Titanium (Ti), Chromium (Cr), Manganese (Mn), Iron (Fe), Copper (Cu), Zinc (Zn), Rubidium ( Zirconium (Zr) and Lead (Pb) were Rb), Strontium (Sr),analyzed.The meanconcentration values of these metals were4739.73, 83.94, 1782.28, 37519.54, 24.36, 134.68, 56.33, 112.80, 118.60 and 31.85 ppm respectively. The three pollution indices {enrichment factor (EF), geo-accumulation index (Igeo) and contamination factor (CF)} employed to assess the contamination status of heavy metals in sediment samples of the study area revealed the elemental trend to be in descending order in each area of this study Mn&amp;gt;Zn&amp;gt;Pb&amp;gt;Cu&amp;gt;Fe&amp;gt;Sr&amp;gt;Rb&amp;gt;Cr&amp;gt;Ti&amp;gt; Zr. Analysis of multi-variate statistics such as Pearson&#x2019;s Correlation coefficient and cluster analysis were also applied to ascertain the relationship and sources of&amp;nbsp; investigated heavy metals. Both positive and negative correlations were observed among some heavy metals but at 0.05 levels, while the cluster&amp;nbsp;analysis revealed three main clusters. The study concluded that the ecosystems in the flared sites region are vulnerable to bioaccumulation of&amp;nbsp;heavy metals in the soil. The concentrations of Iron (Fe) in sediments are higher at the study area than every other elements but Manganese (Mn)&amp;nbsp;poses more negative effects than others.&amp;nbsp;&lt;/p&gt;</abstract>
        <licenseUrl>https://creativecommons.org/licenses/by-nc-nd/4.0</licenseUrl>
        <copyrightYear>2022</copyrightYear>
        <keywords locale="en_US">
          <keyword>Gas flare</keyword>
          <keyword>Bioaccumulation</keyword>
          <keyword>Intertidal</keyword>
          <keyword>Enrichment&#xA0;factor (Ef)</keyword>
          <keyword>geo-accumulation index (Igeo)</keyword>
          <keyword>contamination factor&#xA0;(Cf)</keyword>
          <keyword>Vegetation</keyword>
        </keywords>
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            <givenname locale="en_US">Simeon</givenname>
            <familyname locale="en_US">Ubulom</familyname>
            <affiliation locale="en_US">Department of Marine Biology, Faculty of&#xA0;Biological Sciences, Akwa Ibom State University, Ikot Akpaden, Nigeria</affiliation>
            <country>NG</country>
            <email>ubulomsimeon@gmail.com</email>
          </author>
          <author include_in_browse="true" user_group_ref="Author" seq="4" id="29">
            <givenname locale="en_US">Mary</givenname>
            <familyname locale="en_US">Ekanim</familyname>
            <affiliation locale="en_US">Department of Marine Biology, Faculty of&#xA0;Biological Sciences, Akwa Ibom State University, Ikot Akpaden, Nigeria</affiliation>
            <country>NG</country>
            <email>ubulomsimeon@gmail.com</email>
          </author>
          <author include_in_browse="true" user_group_ref="Author" seq="4" id="30">
            <givenname locale="en_US">Ini-Ibehe</givenname>
            <familyname locale="en_US">Etim</familyname>
            <affiliation locale="en_US">Marine Chemistry and Corrosion Research Group, Department of Marine Biology, Akwa Ibom State University, P.M.B. 1167, Nigeria&#xA0;</affiliation>
            <country>NG</country>
            <email>ubulomsimeon@gmail.com</email>
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          <author include_in_browse="true" user_group_ref="Author" seq="4" id="31">
            <givenname locale="en_US">Okwet</givenname>
            <familyname locale="en_US">Yawo</familyname>
            <affiliation locale="en_US">Department of Marine Biology, Faculty of&#xA0;Biological Sciences, Akwa Ibom State University, Ikot Akpaden, Nigeria</affiliation>
            <country>NG</country>
            <email>ubulomsimeon@gmail.com</email>
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            <givenname locale="en_US">Ita</givenname>
            <familyname locale="en_US">Ewa-Oboho</familyname>
            <affiliation locale="en_US">Department of Marine Biology, Faculty of&#xA0;Biological Sciences, Akwa Ibom State University, Ikot Akpaden, Nigeria</affiliation>
            <country>NG</country>
            <email>ubulomsimeon@gmail.com</email>
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    <article xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" locale="en_US" date_submitted="2022-08-16" status="3" submission_progress="0" current_publication_id="13" stage="production">
      <id type="internal" advice="ignore">13</id>
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        <name locale="en_US">4 FATIMAH et al.pdf</name>
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      <publication xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" locale="en_US" version="1" status="3" primary_contact_id="24" url_path="" seq="3" date_published="2022-06-01" section_ref="ART" access_status="0" xsi:schemaLocation="http://pkp.sfu.ca native.xsd">
        <id type="internal" advice="ignore">13</id>
        <title locale="en_US">Gas chromatography - mass spectrometry characterization and antibacterial activity of stem-bark extracts of Dacryodes edulis (African pear)</title>
        <abstract locale="en_US">&lt;p&gt;This study investigates the antibacterial&amp;nbsp;activities of the stem bark extract of &lt;em&gt;Dacryodes &lt;/em&gt;&lt;em&gt;edulis. &lt;/em&gt;The aim of the study was to deduce the potency of the crude extracts and their metabolites from stem-barks of &lt;em&gt;Dacryodes &lt;/em&gt;&lt;em&gt;edulis &lt;/em&gt;on drug-resistant microbial pathogen(s). The stem bark of the plant was extracted with five solvents of different polarities. While extraction with hexane, dichloromethane, ethyl acetate, and methanol were done using a soxhlet extractor, aqueous extract was obtained by soaking 250 g of powdered&amp;nbsp; samples in 200ml of distilled water for 18 hours&amp;nbsp;The five plant extracts were subjected to phytochemical screening that revealed the&amp;nbsp;presence&amp;nbsp;of alkaloids, flavonoids,&amp;nbsp;carbohydrates, tannins, saponin, steroids, and&amp;nbsp;triterpenes. The bioactivity of the extracts at&amp;nbsp;varying concentrations of 250 mg/mL, 200mg/mL, 150 mg/mL, 100 mg/mL, 50 mg/mL&amp;nbsp;and 25 mg/mL were determined. Based on the result of the bioassay, the most active extracts&amp;nbsp;were partitioned into acidic, basic, and neutral metabolites and the bioactivity tests were&amp;nbsp;repeated on the metabolites. The extracts&amp;nbsp;elicited antibacterial activity against all the strains tested zones of inhibition ranging&amp;nbsp;between 1 mm to 36 mm. The bactericidal&amp;nbsp;effects of the extracts on all the microorganisms&amp;nbsp;tested were positive at 250 mg/mL and 200&amp;nbsp;mg/mL. Also, the acidic, basic, and neutral metabolites of the Methanol and the Ethylacetate extracts exhibited bactericidal effects at 250 mg/mL. At 200 mg/mL, all the six samples except the neutral metabolite of the methanol extract (which was only effective against&amp;nbsp;&lt;em&gt;Staphylococcus Aureus, Salmonella typhi, &lt;/em&gt;and&amp;nbsp;&lt;em&gt;Salmonella Paratyphli&lt;/em&gt;) exhibited antibacterial activity. The gas chromatography-mass spectrometry (gc-ms) spectra revealed 4-dehydroxy-N-(4,5-methylenedioxy-2-nitrobenzylidene) tyramine and1,2{bis(2-methyl propyl)} benzene dicarboxylateas the&amp;nbsp;most abundant compound in the basic metabolites of ethyl acetate and methanol&amp;nbsp;extracts respectively. The most active metabolites were basic metabolites of ethyl acetate and methanol extracts. While the basic&amp;nbsp;metabolites of ethyl acetate contain mostly alkaloids; the basic metabolites of methanol contain mostly terpenoids. These active metabolites possess antibacterial activity against &lt;em&gt;Staphylococcus aureus &lt;/em&gt;and other&amp;nbsp;pathogens tested.&lt;/p&gt;</abstract>
        <licenseUrl>https://creativecommons.org/licenses/by-nc-nd/4.0</licenseUrl>
        <copyrightYear>2022</copyrightYear>
        <keywords locale="en_US">
          <keyword>Antibacterial activity</keyword>
          <keyword>Dacryodes edulis</keyword>
          <keyword>metabolites</keyword>
          <keyword>Phytochemicals</keyword>
        </keywords>
        <authors xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://pkp.sfu.ca native.xsd">
          <author include_in_browse="true" user_group_ref="Author" seq="3" id="24">
            <givenname locale="en_US">Fatimah</givenname>
            <familyname locale="en_US">Oladejobi</familyname>
            <affiliation locale="en_US">Department of Pure and Industrial Chemistry,&#xA0;University of Port Harcourt, P.M.B. 5323, Port&#xA0;Harcourt, Rivers State, Nigeria.</affiliation>
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        <title locale="en_US">Supervised Machine Learning Model For Effective Classification Of Patients With Covid-19 Symptoms Based On Bayesian Belief Network</title>
        <abstract locale="en_US">&lt;p&gt;Covid-19 is a contagious infection and should&lt;/p&gt;&#xD;
&lt;p&gt;be managed properly. If it is identified early&lt;/p&gt;&#xD;
&lt;p&gt;enough, the chances of survival are high.&lt;/p&gt;&#xD;
&lt;p&gt;Symptoms presentations may be confusing to&lt;/p&gt;&#xD;
&lt;p&gt;health practitioners since they are similar to&lt;/p&gt;&#xD;
&lt;p&gt;other diseases and the number of health&lt;/p&gt;&#xD;
&lt;p&gt;professionals are mostly insufficient,&lt;/p&gt;&#xD;
&lt;p&gt;especially in developing countries, hence a&lt;/p&gt;&#xD;
&lt;p&gt;correct and timely diagnoses based on&lt;/p&gt;&#xD;
&lt;p&gt;symptoms&#x2019; presentations can prove difficult.&lt;/p&gt;&#xD;
&lt;p&gt;So far, efforts to take address these needs are&lt;/p&gt;&#xD;
&lt;p&gt;still not adequate. In this paper, we leverage on&lt;/p&gt;&#xD;
&lt;p&gt;the efficacy of machine learning algorithms to&lt;/p&gt;&#xD;
&lt;p&gt;present a machine learning approach,&lt;/p&gt;&#xD;
&lt;p&gt;Bayesian Belief Network, that aims at ensuring&lt;/p&gt;&#xD;
&lt;p&gt;that the symptoms&#x2019; set are correctly and&lt;/p&gt;&#xD;
&lt;p&gt;timeously classified as either Covid-19+ or&lt;/p&gt;&#xD;
&lt;p&gt;Covid-19- .&lt;/p&gt;&#xD;
&lt;p&gt;A dataset is gathered from observed symptoms&lt;/p&gt;&#xD;
&lt;p&gt;of confirmed Covid-19 patients by healthcare&lt;/p&gt;&#xD;
&lt;p&gt;practitioners. The dataset is trained so as to be&lt;/p&gt;&#xD;
&lt;p&gt;able to classify, based on this prior knowledge,&lt;/p&gt;&#xD;
&lt;p&gt;any supplied symptom set. This has been able to&lt;/p&gt;&#xD;
&lt;p&gt;effectively handle the problem of wrong or&lt;/p&gt;&#xD;
&lt;p&gt;delayed diagnoses with its attendant negative&lt;/p&gt;&#xD;
&lt;p&gt;consequences. Our model yields 98% accuracy,&lt;/p&gt;&#xD;
&lt;p&gt;showing a significant classification accuracy of&lt;/p&gt;&#xD;
&lt;p&gt;patients with Covid-19 symptoms.&lt;/p&gt;&#xD;
&lt;p&gt;&amp;nbsp;&lt;/p&gt;</abstract>
        <licenseUrl>https://creativecommons.org/licenses/by-nc-nd/4.0</licenseUrl>
        <copyrightYear>2022</copyrightYear>
        <keywords locale="en_US">
          <keyword>Bio-inspired computing</keyword>
          <keyword>Computer&#xA0;aided diagnosis</keyword>
          <keyword>Bayesian Network</keyword>
          <keyword>Machine&#xA0;learning</keyword>
          <keyword>Covid-19</keyword>
        </keywords>
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          <author include_in_browse="true" user_group_ref="Author" seq="2" id="23">
            <givenname locale="en_US">Anietie</givenname>
            <familyname locale="en_US">Ekong&#xA0;</familyname>
            <affiliation locale="en_US">Department of Computer Science, Akwa&#xA0;Ibom State University, Mkpat Enin, Akwa&#xA0;Ibom State, Nigeria.</affiliation>
            <country>NG</country>
            <email>anietieekong@aksu.edu.ng</email>
            <biography locale="en_US">&lt;p&gt;&amp;nbsp;&lt;/p&gt;&#xD;
&lt;p&gt;&amp;nbsp;&lt;/p&gt;</biography>
          </author>
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        <title locale="en_US">Preliminary Assessment of Radiometric Survey over a Dumpsite in eket Urban, South-Eastern</title>
        <abstract locale="en_US">&lt;p&gt;A radiometric survey was conducted at a&amp;nbsp;dumpsite in Eket Urban, south-eastern Nigeria, with the aim of monitoring low&amp;nbsp;of radioactive contamination . The dumpsite is located behind the defunct Qua Steel Complex&amp;nbsp;in Eket Urban, Akwa Ibom State, Nigeria. The&amp;nbsp;Study area is located between latitude 04&#xB0; 37&#x2032; 07.7&#x2033; and 04&#xB0; 37&#x2032; 00.4&#x2033;N&amp;nbsp;and&amp;nbsp;longitudes&amp;nbsp;007&#xB0; 56&#x2032; 11.4&#x2033; and 007&#xB0; 56&#x2032; 23.5&#xB0;E,&amp;nbsp;in Benin&amp;nbsp;Formation. The dump contains mixed waste of different materials like kitchen and other household wastes, industrial, agricultural&amp;nbsp;wastes, etc. A portable radiation survey scanner&amp;nbsp;REED R8008 was used to quantify the&amp;nbsp;exposure levels in the dump.Gamma radiation exposure rates in counts per minute (cpm) were obtained from two profiles which were oriented at N 80&#xB0; E and N 90&#xB0; W of the dump at&amp;nbsp;increasing distance of 5m from the reference&amp;nbsp;points.&amp;nbsp;A plot of exposure rate in counts per minute&amp;nbsp;versus distance reveals that Profile 1 has almost uniform amplitude with a range of 29 to 37 cpm, the highest amplitude recorded at an&amp;nbsp;interval of 90m Profile 2 shows higher&amp;nbsp;amplitudes of gamma ray levels ranging&amp;nbsp;from&amp;nbsp;3.2 to 42.6 cpm, with&amp;nbsp;the relatively higher&amp;nbsp;amplitudes of 40.1 to 42.6&amp;nbsp;cpm within the&amp;nbsp;dumpsite. A gradual drop towards the adjoining&amp;nbsp;farmland was noticed.&amp;nbsp;The results therefore reveal higher gamma radiation in the dumpsite compared to gamma radiation of 3.2, 3.8, and 3.2 cpm respectively at the three control points.&amp;nbsp;The gamma radiation emission levels from the dump in the range of 20.4 to 42.6&amp;nbsp;cpm (0.12 to&amp;nbsp;0.24 Sv/hr) could be accumulated and&amp;nbsp;become&amp;nbsp;hazardous if not properly managed, to forestall&amp;nbsp;the exceeding of 1mSv/year&amp;nbsp;set by the&amp;nbsp;International Commission on Radiological&amp;nbsp;Protection (ICRP) for the environment and general population.&amp;nbsp;&lt;/p&gt;</abstract>
        <licenseUrl>https://creativecommons.org/licenses/by-nc-nd/4.0</licenseUrl>
        <copyrightYear>2022</copyrightYear>
        <keywords locale="en_US">
          <keyword>Radiometric anomalies</keyword>
          <keyword>dumpsite</keyword>
          <keyword>Gamma radiation</keyword>
          <keyword>Benin Formation</keyword>
          <keyword>Geiger counter</keyword>
        </keywords>
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            <givenname locale="en_US">Nsikak</givenname>
            <familyname locale="en_US">Bassey</familyname>
            <affiliation locale="en_US">Department of Geology, Faculty of Physical&#xA0;Sciences, Akwa Ibom State University, Mkpat&#xA0;Enin- Nigeria</affiliation>
            <country>NG</country>
            <email>abrahamudoh@aksu.edu.ng</email>
          </author>
          <author include_in_browse="true" user_group_ref="Author" seq="1" id="22">
            <givenname locale="en_US">Abraham</givenname>
            <familyname locale="en_US">Udoh</familyname>
            <affiliation locale="en_US">Department of Geology, Faculty of Physical&#xA0;Sciences, Akwa Ibom State University, Mkpat&#xA0;Enin- Nigeria</affiliation>
            <country>NG</country>
            <email>abrahamudoh@aksu.edu.ng</email>
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        <title locale="en_US">Application of pollution indices in estimating the toxicity of heavy metals in sediments of Okoro River in Eastern Obolo, Southeastern Nigeria</title>
        <abstract locale="en_US">&lt;p&gt;The sediments of Okoro River were studied to&amp;nbsp;assess the contamination status of the heavy metals present. Particle induced X-ray emission&amp;nbsp;(PIXE) technique employed revealed the present of Ti, Cr, Mn, Fe, Cu, Zn, Rb, Sr, Zr, and Pb. The results revealed that the&amp;nbsp;concentrations ranged from 1942.2-6299.3&amp;nbsp;mg/kg for Ti, 55.5 - 171.7 mg/kg for Cr, 71.7 to&amp;nbsp;374.2 mg/kg for Mn, 6881.5 - 66477.0 mg/kg&amp;nbsp;for Fe, 5.9 - 37.6 mg/kg for Cu, 8.6 - 84.5 mg/kg for Zn, 0.0 - 226.4 mg/kg for Rb, 0.0 -&amp;nbsp;107.0 mg/kg for Sr, 59.7 - 1333.2 for Zr and 0.0&amp;nbsp;-51.7 mg/kg for Pb. Pollution indices such as&amp;nbsp;enrichment factor (EF), geoaccumulation index (Igeo), contamination factor (CF) and pollution load index (PLI) were employed to assess the levels of pollution of the sediments of the&amp;nbsp;River.&amp;nbsp;The results revealed that the sediments were&amp;nbsp;polluted with the present of these heavy metals detected as confirmed from the mean value of PLI greater than 1 (i.e. mean value of PLI = 1.13). This pollution is as a result of external influences on the River. The concentrations&amp;nbsp;were also subjected to multivariate statistical&amp;nbsp;analysis such as Pearson correlation coefficient and cluster analysis, which revealed only positive coefficient of some heavy metals and that, signified artificial similar sources of the heavy metals to the aquatic bodies in the river.&lt;/p&gt;</abstract>
        <licenseUrl>https://creativecommons.org/licenses/by-nc-nd/4.0</licenseUrl>
        <copyrightYear>2022</copyrightYear>
        <keywords locale="en_US">
          <keyword>sediments</keyword>
          <keyword>heavy metals</keyword>
          <keyword>enrichment factor (EF)</keyword>
          <keyword>geo-accumulation&#xA0;index (Igeo)</keyword>
          <keyword>contamination factor (CF)</keyword>
          <keyword>pollution load index (PLI)</keyword>
        </keywords>
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            <givenname locale="en_US">Okwet</givenname>
            <familyname locale="en_US">Yawo</familyname>
            <affiliation locale="en_US">Department of Physics, Akwa Ibom State University,&#xA0;Ikot Akpaden, Nigeria</affiliation>
            <country>NG</country>
            <email>okwetyawo33@gmail.com</email>
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            <givenname locale="en_US">Ephraim</givenname>
            <familyname locale="en_US">Inyang</familyname>
            <affiliation locale="en_US">Department of Physics, University of Calabar, Calabar,&#xA0;Nigeria</affiliation>
            <country>NG</country>
            <email>inyang.ephraim@gmail.com</email>
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            <givenname locale="en_US">Ita</givenname>
            <familyname locale="en_US">Akpan</familyname>
            <affiliation locale="en_US">Department of Physics, University of Calabar, Calabar,&#xA0;Nigeria</affiliation>
            <country>NG</country>
            <email>itayenakpan@yahoo.com</email>
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        </covers>
      </publication>
    </article>
  </articles>
</issue>

Vol. 6 No. 3 (2026): Researchers Journal of Science and Technology

Articles

Effects of Zinc Oxide Nanoparticle Spiking on Physicochemical Parameters and Substrate-Induced Respiration in Ultisols

Prevalence of Intestinal Parasites and the Therapeutic Potential of Andrographis Paniculata Leaf Extract in Managing Coccidiosis and Enhancing Growth Performance in Broiler Chickens

Integrated Qualitative and Quantitative Evaluation of Depositional Environment and Hydrocarbon Prospectivity of the QX Field in Southeastern Niger Delta

Optimized Stacking Ensemble of Random Forest and XGBoost for Heart Disease Prediction

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