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Microplastics toxicity: Classification, sources, exposure routes, and experiments
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Microplastics (MPs), including polymers such as polyethylene, polyvinyl chloride (PVC), and polystyrene (PS), are widespread environmental contaminants detected in air, water, soil, and food. These particles originate from the breakdown of larger plastics and from direct industrial and consumer sources, including packaging, textiles, and personal care products. MPs enter the human body primarily through ingestion, inhalation, and dermal contact, with food, water, and air serving as major exposure pathways. Once internalized, MPs have been found in various human tissues and biological fluids, indicating their capacity for bioaccumulation. Toxicological studies in experimental models and occupational settings link MP exposure to oxidative stress, inflammation, cellular dysfunction, and potential organ toxicity, including effects on the gastrointestinal, respiratory, immune, reproductive, and nervous systems. PVC microplastics, in particular, are associated with liver toxicity and increased cancer risk in occupationally exposed populations. MPs can also act as vectors for environmental pollutants and plastic-associated chemicals, further amplifying health risks. This review summarizes the classification, major sources, exposure routes, and toxicological activity of MPs. A comprehensive understanding of MP properties is essential for developing effective strategies to mitigate their persistent harmful effects on public health and the environment. Copyright © 2025. Published by Elsevier Inc.

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Publication Date
Mon Aug 26 2024
Journal Name
Jbpml
Studying The Changes in Motility and Morphology on Human sperm after exposure to low doses of x-rays
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the energy that a radiation source emits as light (photons), electromagnetic waves, or particles is known as radiation. X-ray is one type of ionizing radiation that falls within the electromagnetic wave category of short wavelengths. Because of their short wavelength. X-ray is a type of ionizing radiation that is used in a constantly growing number of diagnostic procedures. X-ray diagnostic imaging has been employed in the medical field for more than a century(Hariyoto et al., 2020). Radiation has advantages for human health, but there is also a risk. the impacts of Radiation on Fertility it is an oligospermia, or a reduction in the number of sperm cells, which is already possible after radiation exposure of 0.15 mGy. It Leads to impede

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Publication Date
Thu Dec 01 2022
Journal Name
Tropical Journal Of Natural Product Research
Alterations in Biochemical Parameters and Antioxidant Enzymes in Male Mice as Biomarkers of Exposure to Pollution with Cadmium
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There is currently a significantly larger concentration of toxins in our environment than there was in the past. This is mostly attributable to the expansion of modern industry. This investigation was conducted in order to investigate various haematological and biochemical changes in order to determine the effects of Cd on the liver and kidney. Because of its long biological half-life, it is considered hazardous to human health. The effect of sub-lethal doses (40, 80 and 120 mg\Kg) of Cadmium (Cd) on male mice were evaluated for 4 weeks, and analysis was done to estimate their biochemical parameters and antioxidant enzymes. The results showed that Cd-treated mice had considerably lower packed cell volume, red blood cells, and haemoglobin. W

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Publication Date
Wed Jan 01 2025
Journal Name
Advances In Animal And Veterinary Sciences
Exposure to Environmental Perfluorooctanoic Acid (PFOA) Induced Hepatocellular Apoptosis and Alteration in Serum Biomarkers in Diabetic Guinea Pigs
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Publication Date
Thu Sep 08 2022
Journal Name
Al-khwarizmi Engineering Journal
Assessment of Ornamental Plants Tolerance for Acute Exposure of Acetaminophen and Methylparaben in Constructed Wetlands- a Preliminary Study
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The study aims to select suitable ornamental plant species that can survive relatively with high concentrations of acetaminophen and methylparaben in constructed wetlands. Alternanthera spp, Asparagus aethiopicus and Chlorophytum comosum are examined to withstand three initial concentrations, 20, 100 and 200 mg/L of acetaminophen and methylparaben. A total of 21 plastic pails with each 3 L capacity consisting of nine pails are used for each pharmaceutical and personal care products (PPCPs) compounds (acetaminophen and methylparaben) for three ornamental plants (Alternanthera spp, Asparagus aethiopicus and Chlorophytum comosum), with three pails as plant controls. The results reveales

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Sun Apr 23 2017
Journal Name
International Conference Of Reliable Information And Communication Technology
Classification of Arabic Writer Based on Clustering Techniques
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Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

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Publication Date
Mon Dec 01 2025
Journal Name
Journal Of Physics: Conference Series
Advanced Machine Learning Models for Banana Sweetness Classification
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It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Self-Localization of Guide Robots Through Image Classification
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The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Classification of fetal abnormalities based on CTG signal
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The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was t

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Publication Date
Fri Jan 01 2016
Journal Name
Middle-east Journal Of Scientific Research
Question Classification Using Different Approach: A Whole Review
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