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High throughput screening of rooting depth in rice using buried herbicide
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Abstract<p>Root research requires high throughput phenotyping methods that provide meaningful information on root depth if the full potential of the genomic revolution is to be translated into strategies that maximise the capture of water deep in soils by crops. A very simple, low cost method of assessing root depth of seedlings using a layer of herbicide (<styled-content style="fixed-case">TRIK</styled-content> or diuron) buried 25 or 30 cm deep in soil‐filled boxes of varying size is described that is suitable for screening hundreds or thousands of rice accessions in controlled environment conditions. Variation in cultivar sensitivity to the herbicide when injected into pots was detected but considered small in relation to the variation detected when the herbicide was buried. Using 32 rice cultivars previously characterised for root traits in rhizotron and hydroponic systems, 80% of variation in herbicide score at 35 days was explained by cultivar and herbicide score correlated strongly with rooting depth traits. Using 139 genotypes of the Bala × Azucena mapping population, heritability for herbicide symptoms reached 55% and quantitative trait loci were detected which match those previously reported in this population. In repeated experiments using different soils, the method did not always perform to its maximum potential (in terms of speed of symptom development or discrimination between cultivars). This was not due to degradation or reduced bio‐availability of the herbicide in the soil but is believed to be due to the soil water content and water release characteristics as it relates to plant water use. Therefore, when using this technique, thorough preliminary experiments to determine the best water application regime for the particular combination of soil and environmental conditions are required. The method should be applicable to seedling stage screening of rice and other crops.</p>
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Publication Date
Thu Nov 25 2021
Journal Name
Engineering And Technology Journal
Pentacene Based Organic Field Effect Transistor Using Different Gate Dielectric
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This paper presents the electrical behavior of the top contact/ bottom gate of an organic field-effect transistor (OFET) utilizing Pentacene as a semiconductor layer with two distinctive gate dielectric materials Polyvinylpyrrolidone (PVP) and Zirconium oxide (ZrO2) were chosen. The influence of the monolayer and bilayer gates insulator on OFET performance was investigated. MATLAB software was used to simulate and determine the electrical characteristics of a device. The output and transfer characteristics were studied for ZrO2, PVP and ZrO2/PVP as an organic gate insulator layer. Both characteristics show a high drain current at the gate dielectric ZrO2/PVP equal to -0.0031A and -0.0015A for output and transfer characteristics respectively

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Publication Date
Thu Jan 23 2020
Journal Name
Iraqi Journal Of Laser
Spider Veins Treatment using 1064 nm Long-Pulse Nd:YAG Laser
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spider veins are clusters of Ectatic venules & are common finding on the lower limbs generally believed to be caused by multiple factors, including genetic predisposition, hormonal factors, gravity, occupation, pregnancy, becoming increasingly apparent with age, and trauma. Therapeutic options include sclerotherapy, surgical procedures, and treatment with different laser systems.

 Objectives: The purpose of the study was to evaluate the efficacy and safety of long pulsed (Nd:YAG) laser emitting at 1064nm in the treatment of spider veins.

Patients, Materials and Methods: This prospective study was done in the laser medicine research clinics of the Institute of las

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Publication Date
Thu May 05 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Classification SINGLE-LEAD ECG by using conventional neural network algorithm
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Publication Date
Tue Dec 28 2021
Journal Name
2021 2nd Information Technology To Enhance E-learning And Other Application (it-ela)
Pedestrian and Objects Detection by Using Learning Complexity-Aware Cascades
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Publication Date
Sun Jul 01 2012
Journal Name
Journal Of Computer Science
Peer-to-Peer Video Conferencing Using Hybrid Content Distribution Model
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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Thu Dec 01 2022
Journal Name
Neuroscience Informatics
Epileptic EEG activity detection for children using entropy-based biomarkers
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Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Bartholin Gland Cyst Treatment using Carbon Dioxide Laser (10600 nm)
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The Bartholin gland cyst is a condition that occurs in approximately 2% of women, most of whom are of reproductive age. Although benign pathology, it is associated with significant patient discomfort. This disorder is caused by the obstruction and consequent dilation of the cyst duct. Definitive treatment involves the surgical removal of the entire cyst. Other alternative treatments include Marsupialization, Word catheter, and the use of CO2 laser. CO2 laser can be used either to vaporize or to excise the Bartholin gland cyst. The Objectives: The purpose of the study was to evaluate the efficacy and safety of (10600nm) CO2 laser in the treatment of Bartholin gland cyst. Patients, Materials & Methods: This study was done in laser medi

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Publication Date
Wed Jan 01 2025
Journal Name
Fusion: Practice And Applications
Enhanced EEG Signal Classification Using Machine Learning and Optimization Algorithm
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This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

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Publication Date
Tue Sep 16 2025
Journal Name
Baghdad Science Journal
Mesoporous SBA-15 Synthesis and Characterization Using Various Dispersing Agents
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A successful synthesis of SBA-15 with semi-spherical morphology and suitable texture properties was achieved using hydrothermal technique. Sodium silicate, derived from silica sand from Iraq, was used as a silica precursor, and Pluronic p123 triblock copolymer was used as a template with a strong acid media (pH < 1). The effect of adding (1–3) g of either polyvinyl alcohol (PVA), Polyvinyl pyrrolidone (PVP -k30), or Sodium dodecyl sulfate (SDS) dispersant agents on the texture properties of the synthesized SBA-15 was studied. The SBA-15 sample underwent various characterization techniques, including X-ray diffraction (XRD), Fourier transform infrared (FTIR), atomic force microscopy (AFM), nitrogen adsorption-desorption using Br

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