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ijp-162
Porous silicon prepared by photo electrochemical etching assisted by laser
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Porous silicon (PS) layers are prepared by anodization for
different etching current densities. The samples are then
characterized the nanocrystalline porous silicon layer by X-Ray
Diffraction (XRD), Atomic Force Microscopy (AFM), Fourier
Transform Infrared (FTIR). PS layers were formed on n-type Si
wafer. Anodized electrically with a 20, 30, 40, 50 and 60 mA/cm2
current density for fixed 10 min etching times. XRD confirms the
formation of porous silicon, the crystal size is reduced toward
nanometric scale of the face centered cubic structure, and peak
becomes a broader with increasing the current density. The AFM
investigation shows the sponge like structure of PS at the lower
current density porous begin to form on the crystalline silicon, when
the current density increases, pores with maximum diameter are
formed as observed all over the surface. FTIR spectroscopy shows a
high density of silicon bonds, it is very sensitive to the surrounding
ambient air, and it is possible to oxidation spontaneously.

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Estimating concentration of toxic ions Arsenic in water by using Photonic Crystal Fiber based on Surface Plasmon Resonance (SPR)
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In this work, an enhanced Photonic Crystal Fiber (PCF) based on Surface Plasmon Resonance (SPR) sensor using a sided polished structure for the detection of toxic ions Arsenic in water was designed and implemented. The SPR curve can be obtained by polishing the side of the PCF after coating the Au film on the side of the polished area, the SPR curve can be obtained. The proposed sensor has a clear SPR effect, according to the findings of the experiments. The estimated signal to Noise Ratio (SNR), sensitivity (S), resolution (R), and Figures of merit (FOM) are approaching; the SNR is 0.0125, S is 11.11 μm/RIU, the resolution is 1.8x〖10〗^(-4), and the FOM is 13.88 for Single-mode Fiber- Photonic Crystal Fiber- single mode Fiber (SMF-P

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Publication Date
Mon May 01 2017
Journal Name
The Journal Of Immunology
Protective effects of Δ9-Tetrahydrocannabinol (THC) results from alteration in lung dysbiosis mediated by SEB-induced acute lung injury
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Abstract<p>Inhalation of Staphylococcal Enterotoxin B (SEB) is known to induce acute lung injury (ALI) and studies from our laboratory have shown that THC, a psychoactive ingredient found in Cannabis sativa, can attenuate the ALI. In the current study, we investigated the role played by lung microbiota in ALI with or without THC treatment. A dual-dose of SEB was given to C3H/HeJ mice, which were then treated either with vehicle or THC. SEB-administration caused ALI and 100% mortality while all THC-treated mice survived and suppressed the inflammation in the lungs. Furthermore, lung microbiota was collected and 16S rRNA sequencing was performed. The data were analyzed to determine the alpha and b</p> ... Show More
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Publication Date
Mon Mar 02 2026
Journal Name
Mustansiriyah University
Inhibition the Expression of fimC, fimD, fimH Genes in Uropathogenic E. coli Using TiO2 Nanoparticles Biosynthesized by Probiotics Bacteria
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المستودع الرقمي العراقي. مركز المعلومات الرقمية التابع لمكتبة العتبة العباسية المقدسة

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Publication Date
Wed Jan 01 2020
Journal Name
Annals Of Tropical Medicine And Public Health
The use of eggplant peel powder in the treatment of hyperlipidemia caused by antibiotics administration in male local rabbits
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Publication Date
Mon Jun 29 2015
Journal Name
Separation Science And Technology
An acidic injection well technique for enhancement of the removal of copper from contaminated soil by electrokinetic remediation process
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Publication Date
Sat Jun 30 2012
Journal Name
Al-kindy College Medical Journal
The Effect of Leptin Level in Pregnancy Complicated by Intrauterine Growth Restriction on Neonatal Outcome, in an Iraqi Center
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Background: Fifteen percent of small for gestational age are small as a result of fetal growth restriction, which could be due to maternal, placental or fetal factors. It is an important clinical problem associated with increase perinatal mortality and morbidity. Leptin is a protein that produced by many tissues including the placenta (syncytiotropholoast). Dysregulation of leptin metabolism may be implicated in preeclampsia and IUGR pathogenesis.
Aim of the study: To study the trend of leptin level alteration in maternal serum and cord blood in pregnancies complicated by fetal growth restriction and its relation with fetal outcome.
Methods: An Analytic, cross- sectional study conducted in Al-Elwyia Maternity Teaching Hospital and

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Publication Date
Mon Jan 01 2024
Journal Name
Results In Nonlinear Analysis
Numerical solutions for the time fractional Black-Scholes model governing European option by using double integral transform decomposition method
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Publication Date
Tue Mar 19 2024
Journal Name
Jordan Journal Of Pharmaceutical Sciences
MMP-1 and MMP-7 Expression is Influenced by Ginsenosides in Mice Exposed to Aflatoxin B1: in vivo Study
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Panax ginseng (PG), one of the most widely used herbal medicines, has demonstrated various beneficial effects such as anti-inflammatory, antioxidant, and anticancer impacts. Naturally occurring ginsenosides in the ginseng plant inhibit cell proliferation and significantly reduce liver damage induced by certain chemicals. Aflatoxin B1 (AFB1) is a primary mycotoxin due to its hepatotoxic, immunotoxic, and oncogenic effects in animal models and humans. In this study, we examined the effects of assorted doses of PG aqueous crude extract on the expression of matrix metalloproteinase 1 and 7 (MMP-1 and MMP-7) in the kidney, spleen, and liver of experimental AFB1-exposed mice, using immunohistochemistry (IHC). Mice were orally administered

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Publication Date
Sat Apr 01 2023
Journal Name
Biochemical Engineering Journal
Immobilization of mixed cells by Flaxseeds (Linum usitatissimum) extract as new nonconventional biocarrier for biodegradation of sodium dodecyl sulfate
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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