745 research outputs found
CHEMICAL CHARACTERIZATION AND ANTIMICROBIAL ACTIVITY OF JORDANIAN PROPOLIS AND NIGELLA SATIVA SEED OIL AGAINST CLINICALLY ISOLATED MICROORGANISMS
Objective: Increasing use of medicinal plants in the treatment of infectious diseases are due to the development of multi-antibiotics resistant microorganisms, and had alerted our interest in the examination of some natural products. This study was carried out to investigate the antimicrobial activity of Jordanian propolis, black seed oil (Nigella sativa) extract, alone or in combination against clinically isolated microorganisms (bacteria and fungi).Methods: Jordanian propolis samples were collected. Aqueous and alcoholic extractions were done; black seed oil was extracted from Nigella sativa seeds. Seven clinical isolated microorganisms namely: Micrococcus luteus, Bacillus pumilus, Bordetella bronchisptica, Enterococcus fecalis, Bacillus subtilis, and Staphylococcus aureus, and one yeast strain namely Candida albicans were used. The antimicrobial activity was investigated by agar diffusion technique and microplate dilution to determine the MIC.Results: The results indicated that the alcoholic propolis extract showed higher antimicrobial activity than the aqueous propolis extract. The antimicrobial activity of black seed oil was significantly higher than that of the propolis. Mixing propolis with black seed oil showed synergism effects against some microorganisms as Enterococcus fecalis (24±1.1), Bordetella bronchisptica (20±0.9) and Candida albicans (40±2.3), and additive with others as Bacillus subtilis (28±1.8).Conclusion: Black seed oil and propolis might be used as a potential source of safe and effective natural antimicrobial in pharmaceutical and food industries
OXIDANTS AND ANTIOXIDANTS AS RISK FACTORS IN YOUNG ARABIAN MALE PATIENTS WITH ACUTE MYOCARDIAL INFARCTION
Objective: This study aim to investigate the levels of oxidative stress, antioxidants besides uric acid, C-reactive protein (CRP), lipid profile and cardiac biomarker enzymes in young men admitted to the hospital for the first time with acute myocardial infarction (AMI), to investigate any Relationship between them.Methods: 135 young men age Ë‚ 40 y old, admitted to the cardiology unit with suspected MI and 130 age and sex matched healthy controls were included in this study. Blood samples were collected from the patients and the control group. The blood samples were collected from the patients on the day of admission and on the day of discharge.Results: The levels of xanthine oxidase (XO), malondialdehyde (MDA), CRP, uric acid, total cholesterol (TC), total triglyceride (TG), low-density lipoprotein (LDL-C), apoprotein-B 100 (Apo B), and cardiac biomarker enzymes were significantly high, whereas catalase, vitamin C, high-density lipoprotein (HDL-C) and apoprotein-A1 (Apo A1) were significantly low on the day of admission (Time A) and slightly higher on the day of discharge (Time B), but both were still lower than the controls. There was a decrease in XO and MDA activity and an increase in catalase activity and vitamin C level.Conclusion: These results may indicate possible relationships between these parameters and AMI.Keywords: Acute myocardial infarction, Xanthine oxidase, Malondialdehyde, Antioxidants, Lipid profil
Carbon Nanoparticles-Decorated Carbon Nanotubes
© 2020, The Author(s). Multi walled carbon nanotubes (MWCNTs) were decorated by activated carbon nanoparticles of resorcinol-formaldehyde aerogels. Carbon nanospheres and MWCNTs were mixed by equal mass ratios for different durations. The products were characterized by Raman spectroscopy, thermal gravimetric analysis, nanoscanning electron microscopy, transmission electron microscopy and x-ray diffraction. The results indicated that a significant decoration with carbon nanoparticles occurred onto the MWCNTs.This publication was made possible by the NPRP award (NPRP 08-014-2-003) from the Qatar National Research Fund (a member of The Qatar Foundation). The statements made herein are solely the responsibility of the authors. Technical support from the Department of Chemical Engineering, the Central Laboratories Unit (CLU) and Gas Processing Centre (GPC) at Qatar University is also acknowledged. The publication of this article was funded by the Qatar National Library
Influence of chitosan addition on resorcinol-formaldehyde xerogel structure
Gels are usually not environment-friendly due to their difficult biodegradability. Therefore, the addition of chitosan, even in small amounts, will make such gels biodegradable and thus can be useful in many applications that require environment-friendly materials. The addition of small quantities of chitosan to the reacting solution resorcinol-formaldehyde xerogel was investigated. Different hybrid resorcinol-formaldehyde-chitosan xerogels were characterized by dierent techniques, including Raman spectra, FTIR, XRD, TGA, SEM, surface area and porosity analyzer, and CHNS/O microanalyzer. It was seen that the addition of chitosan, even in a minor quantity, has a significant influence on the structural features of the resulting xerogels. The lattice order and crystallinity, chemical functions, thermal stability, morphology, elemental ratio, pore structure, and appearance were changed by adding chitosan into the xerogel structure. - 2019 by the authors. Licensee MDPI, Basel, Switzerland.This publication was made possible by the NPRP award (NPRP 08-014-2-003) from the Qatar National Research Fund (a member of Qatar Foundation). Statements made herein are the sole responsibility of the authors. Technical support from the Department of Chemical Engineering, Central Laboratory Unit (CLU) and Gas Processing Centre (GPC) at Qatar University is also acknowledged. Further, the publication of this article was funded by the Qatar National Library.Scopu
Arabic Handwriting Synthesis
Training and testing data for optical character recognition are cumbersome to obtain. If large amounts of data can be produced from small amounts, much time and effort can be saved. This paper presents an approach to synthesize Arabic handwriting. We segment word images into labeled characters and then use these in synthesizing arbitrary words. The synthesized text should look natural; hence, we define some criteria to decide on what is acceptable as natural-looking.
The text that is synthesized by using the natural-looking constrain is compared to text that is synthesized without using the natural-looking constrain for evaluation
ACETYLENIC DIMERIZATION UNDER BASIC CONDITIONS
Objective: The lack of information concerning the pharmacological activity of amino acetylenic amide derivatives in which the cyclic amine is aziridine or azetidine promoted our interest to synthesize N-[4-(1-azeridinyl)-2-butynyl] pyrrolide-1,3-dione 4, N-[4-(1-azetidinyl)-2-butynyl] pyrrolidine-1,3-dione 5 and N-[4-(1-pyrrolidnyl)-2-butynyl]pyrrolide-1,3-dione 6.Methods: Melting points, IR, 1H-NMR 13CNMRspectra were measured.Results: Dimerization of 2-(prop-2-yn-1-yl) pyrrolidine-1,3-dione was generated rather than Mannich product, while using pyrrolidine as base in Mannich reaction generated the expected Mannich product. Rationalization for the mechanism of dimerization and Mannich adduct are discussed.Conclusion: Mannich reaction may afford the dimerization product of the acetylenic compounds rather than Mannich adduct.Â
Building a Tensegrity-Based Computational Model to Understand Endothelial Alignment Under Flow
Indiana University-Purdue University Indianapolis (IUPUI)Endothelial cells form the lining of the walls of blood vessels and are continuously subjected to mechanical stimuli from the blood flow. Microtubule-organizing center (MTOC), also known as centrosome is a structure found in eukaryotic cells close to the nucleus. MTOC relocates relative to the nucleus when endothelial cells are exposed to shear stress which determines their polarization, thus it plays a critical role in cell migration and wound healing. The nuclear lamina, a mesh-like network that lies underneath the nuclear membrane, is composed of lamins, type V intermediate filament proteins. Mutations in LMNA gene that encodes A-type lamins cause the production of a mutant form of lamin A called progerin and leads to a rare premature aging disease known as Hutchinson-Gilford Progeria Syndrome (HGPS). The goal of this study is to investigate how fluid flow affects the cytoskeleton of endothelial cells.
This thesis consists of two main sections; computational mechanical modeling and laboratory experimental work. The mechanical model was implemented using Ansys Workbench software as a tensegrity-based cellular model in order to simulate the state of an endothelial cell under the effects of induced shear stress from the blood fluid flow. This tensegrity-based cellular model - composed of a plasma membrane, cytoplasm, nucleus, microtubules, and actin filaments - aims to understand the effects of the fluid flow on the mechanics of the cytoskeleton. In addition, the laboratory experiments conducted in this study examined the MTOC-nuclear orientation of endothelial cells under shear stress with the presence of wound healing. Wild-type lamin A and progerin-expressing BAECs were studied under static and sheared conditions.
Moreover, a custom MATLAB code was utilized to measure the MTOC-nuclear orientation angle and classification. Results demonstrate that shear stress leads to different responses of the MTOC orientation between the wild-type and progerin-expressing cells
around the vertical wound edge. Future directions for this study involve additional experimental work together with the improved simulation results to confirm the MTOC orientation relative to the nucleus under shear stress
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Arabic text recognition of printed manuscripts. Efficient recognition of off-line printed Arabic text using Hidden Markov Models, Bigram Statistical Language Model, and post-processing.
Arabic text recognition was not researched as thoroughly as other natural languages. The need for automatic Arabic text recognition is clear. In addition to the traditional applications like postal address reading, check verification in banks, and office automation, there is a large interest in searching scanned documents that are available on the internet and for searching handwritten manuscripts. Other possible applications are building digital libraries, recognizing text on digitized maps, recognizing vehicle license plates, using it as first phase in text readers for visually impaired people and understanding filled forms.
This research work aims to contribute to the current research in the field of optical character recognition (OCR) of printed Arabic text by developing novel techniques and schemes to advance the performance of the state of the art Arabic OCR systems.
Statistical and analytical analysis for Arabic Text was carried out to estimate the probabilities of occurrences of Arabic character for use with Hidden Markov models (HMM) and other techniques.
Since there is no publicly available dataset for printed Arabic text for recognition purposes it was decided to create one. In addition, a minimal Arabic script is proposed. The proposed script contains all basic shapes of Arabic letters. The script provides efficient representation for Arabic text in terms of effort and time.
Based on the success of using HMM for speech and text recognition, the use of HMM for the automatic recognition of Arabic text was investigated. The HMM technique adapts to noise and font variations and does not require word or character segmentation of Arabic line images.
In the feature extraction phase, experiments were conducted with a number of different features to investigate their suitability for HMM. Finally, a novel set of features, which resulted in high recognition rates for different fonts, was selected.
The developed techniques do not need word or character segmentation before the classification phase as segmentation is a byproduct of recognition. This seems to be the most advantageous feature of using HMM for Arabic text as segmentation tends to produce errors which are usually propagated to the classification phase.
Eight different Arabic fonts were used in the classification phase. The recognition rates were in the range from 98% to 99.9% depending on the used fonts. As far as we know, these are new results in their context. Moreover, the proposed technique could be used for other languages. A proof-of-concept experiment was conducted on English characters with a recognition rate of 98.9% using the same HMM setup. The same techniques where conducted on Bangla characters with a recognition rate above 95%.
Moreover, the recognition of printed Arabic text with multi-fonts was also conducted using the same technique. Fonts were categorized into different groups. New high recognition results were achieved.
To enhance the recognition rate further, a post-processing module was developed to correct the OCR output through character level post-processing and word level post-processing. The use of this module increased the accuracy of the recognition rate by more than 1%.King Fahd University of Petroleum and Minerals (KFUPM
GARDNet: Robust Multi-View Network for Glaucoma Classification in Color Fundus Images
Glaucoma is one of the most severe eye diseases, characterized by rapid
progression and leading to irreversible blindness. It is often the case that
diagnostics is carried out when one's sight has already significantly degraded
due to the lack of noticeable symptoms at early stage of the disease. Regular
glaucoma screenings of the population shall improve early-stage detection,
however the desirable frequency of etymological checkups is often not feasible
due to the excessive load imposed by manual diagnostics on limited number of
specialists. Considering the basic methodology to detect glaucoma is to analyze
fundus images for the optic-disc-to-optic-cup ratio, Machine Learning
algorithms can offer sophisticated methods for image processing and
classification. In our work, we propose an advanced image pre-processing
technique combined with a multi-view network of deep classification models to
categorize glaucoma. Our Glaucoma Automated Retinal Detection Network (GARDNet)
has been successfully tested on Rotterdam EyePACS AIROGS dataset with an AUC of
0.92, and then additionally fine-tuned and tested on RIM-ONE DL dataset with an
AUC of 0.9308 outperforming the state-of-the-art of 0.9272. Our code is
available on https://github.com/ahmed1996said/gardnetComment: Keywords: Glaucoma Classification, Color Fundus Images. Computer
Aided Diagnosis. Deep Learnin
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