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bsj-3509
Radiological Impact Assessment of Farm Soils and Ofada rice (Oryza sativa japonica) from Three Areas in Nigeria
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Oryza sativa japonica (ofada rice) is largely grown in Aramoko, Abakaliki and Ofada are communities and consumed by both the poor and rich in Nigeria. A total of twenty ofada rice farmlands were identified in each study area and rice samples were randomly collected, thoroughly mixed to make a representative sample from each farmland. Soil samples were collected in each farm to a depth of 5-15cm from at least eight different points and thoroughly mixed together to form a representative sample. The samples were thereafter taken to the laboratory for preparation and spectroscopic analysis. A well-calibrated NaI(Tl) gamma-ray detector was used in spectrometric analysis of the samples and descriptive statistics was used to analyze the results.

The respective mean 40K, 238U and 232Th activity concentrations in the rice were 261.8±52.5Bq/kg, 9.6±1.2Bq/kg and 8.7±1.0Bq/kg (Ofada); 257.3±39.0Bq/kg, 9.3±1.1Bq/kg and 7.8±1.8Bq/kg (Abakaliki); and 248.2±54.8Bq/kg, 9.3±0.9Bq/kg and 7.6±1.5Bq/kg (Aramoko). The respective mean 40K, 238U and 232Th activity concentrations in the soils were 333.9±62.8Bq/kg, 11.1±1.1Bq/kg and 11.0±1.4Bq/kg (Ofada); 306.8±36.0Bq/kg, 10.7±0.8Bq/kg and 9.4±1.8 Bq/kg (Abakaliki) and 321.8±42.4Bq/kg, 10.9±0.5Bq/kg and 9.5±0.6Bq/kg (Aramoko). The highest mean ingestion dose of 106.0±8.0µSv/y and outdoor effective dose of 32.4±3.40µSv/y were recorded in Ofada community. The highest mean ingestion cancer risk of (0.33±0.004) x10-3was recorded in Aramoko. The results indicated significantly lower radionuclide ingestion dose than the world limit value of 290µSv/y and lower cancer risks than the UNSCEAR recommended limit of 0.29x10-3, therefore consumption of ofada rice from the areas may not pose any serious health impact.

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Publication Date
Thu Oct 01 2020
Journal Name
Engineering Science And Technology, An International Journal
Thermal performance improvement based on the hybrid design of a heat sink
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Publication Date
Mon Sep 23 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Buckling analysis of reinforced composite plates with a multiwall carbon nanotube (MWCNT)
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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Science
The Dynamics of Sokol-Howell Prey-Predator Model Involving Strong Allee Effect
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In this paper,  a Sokol-Howell prey-predator model involving strong Allee effect is proposed and analyzed. The existence, uniqueness, and boundedness are studied. All the five possible equilibria have been are obtained and their local stability conditions are established. Using Sotomayor's theorem, the conditions of local saddle-node and transcritical and pitchfork bifurcation are derived and drawn. Numerical simulations are performed to clarify the analytical results

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Publication Date
Fri Jul 01 2022
Journal Name
Ieee Transactions On Systems, Man, And Cybernetics: Systems
Design of Robust Terminal Sliding Mode Control for Underactuated Flexible Joint Robot
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Flexible joint robot (FJR) manipulators can offer many attractive features over rigid manipulators, including light weight, safe operation, and high power efficiency. However, the tracking control of the FJR is challenging due to its inherent problems, such as underactuation, coupling, nonlinearities, uncertainties, and unknown external disturbances. In this article, a terminal sliding mode control (TSMC) is proposed for the FJR system to guarantee the finite-time convergence of the systems output, and to achieve the total robustness against the lumped disturbance and estimation error. By using two coordinate transformations, the FJR dynamics is turned into a canonical form. A cascaded finite-time sliding mode observer (CFTSMO) is construct

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Proposition of New Ensemble Data-Intelligence Models for Surface Water Quality Prediction
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Publication Date
Thu May 07 2015
Journal Name
Journal Of Infrared, Millimeter, And Terahertz Waves
Distinguishing Gasoline Engine Oils of Different Viscosities Using Terahertz Time-Domain Spectroscopy
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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Surgery Open
Does preoperative magnetic resonant cholangiopancreatography (MRCP), improve the safety of laparoscopic cholecystectomy?
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<bold>ABSTRACT</bold> <sec> <title>Background:

Magnetic resonance cholangiopancreatography (MRCP) is a non-invasive imaging test with excellent overall sensitivity and specificity for demonstrating the level and the presence of a biliary obstruction. MRCP has emerged as an accurate, diagnostic modality for investigating the biliary and pancreatic duct. In some cases, it has been recommended that preoperative MRCP is a good choice for the detection of CBD stones.

Aim:

The aim of the s

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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Sun Oct 01 2023
Journal Name
Nanostructures
Effect of Selenium Nanoparticles with Cress Extract on Polycystic Ovary Syndrome (PCOS)
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Selenium is naturally present in the human body, animals, and plants, and is one of the important elements in their growth and maintenance. Recently, the nanoform of selenium has attracted attention due to its low toxicity and a high degree of adsorption compared to its organic and inorganic forms. The current study aimed to examine the effect of Cress leaves (Lepidium sativum L.) extract in combination with selenium nanoparticles in alleviating polycystic ovary syndrome in letrozole-induced PCOS in adult female rats. Nonthermal or cold plasma was used in the synthesis of selenium nanoparticles. Subsequently, the produced nanoparticles were identified, the 30 rats were divided into 6 equal groups, the first group was healthy (negative contr

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