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Characterization and antifouling activity analysis of extracellular polymeric substances produced by an epibiotic bacterial strain Kocuria flava associated with the green macroalga Ulva lactuca

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Acta Oceanologica Sinica 2021年第4期40卷 107-115页

作者： Mohammad abdulaziz ba-akdah Sathianeson Satheesh Department of Marine Biology Faculty of Marine SciencesKing Abdulaziz UniversityJeddah 21589Saudi Arabia

Extracellular polymeric substances(EPS)are present externally to the microorganisms and play an important role in attachment and biofilm *** polymers possess antibacterial and antifouling *** this study,the antifouling activity of EPS produced by an epibiotic bacterium associated with macroalga Ulva lactuca was assessed against fouling bacteria and barnacle *** indicate that the EPS isolated from the epibiotic bacterium inhibits the biofilm formation of the bacteria without much antibacterial ***,the EPS reduced the settlement of barnacle larvae on the hard substrate under laboratory *** epibiotic bacterium was identified as Kocuria flava based on 16 S rRNA gene *** EPS was further analysed using Fourier transform infrared(FT-IR),nuclear magnetic resonance(NMR)and X-ray diffraction(XRD)to understand the biochemical *** analysis revealed the presence of polysaccharides,proteins,acetyl amine and succinyl *** electron microscope analysis indicated that the EPS consisted of aggregated and irregular sphere-shaped particles.

关键词： biofouling antifouling Kocuria flava exopolymers antibiofilm activity Red Sea

Chemical Defense of Soft Coral Sinularia polydactyla from the Red Sea Against Marine Biofilm-Forming bacteria

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Journal of Ocean University of China 2018年第6期17卷 1451-1457页

作者： ESKandER Rehab AL-SOFYANI Abdulmohsin A. EL-SHERBINY Mohsen M.O. ba-AKDAH Mohammad abdulaziz SATHEESH Sathianeson Department of Marine Biology Faculty of Marine Sciences King Abdulaziz University

Soft corals are an important group of organisms that live in reef ecosystems. In this study, the chemical defense of soft coral Sinularia polydactyla against biofilm-forming bacteria was assessed. The soft coral S. polydactyla was collected from the Obhur creek of the Red Sea and the bioactive compounds were extracted under different conditions using methanol and hexane as solvents. Results revealed that the bioactive compounds produced by the soft coral S. polydactyla were active against the growth, hydrophobicity and extracellular polymeric substances production of the biofilm-forming bacteria. However, the damage or injury in soft coral tissue caused a decrease in the activity against biofilm-forming bacteria. GC-MS analysis revealed that sesquiterpenes were abundant in normal coral sample extract while cembranoids were abundant in damaged coral sample extracts. In general, the results indicated that the soft corals either under stress or with damage may not have a strong chemical defense against the colonizing marine organisms and competitors.

关键词： chemical ecology antifouling antibiofilm activity bioactive compound coral tissue damage

Exact Traveling Wave Solutions to Phi-4 Equation and Joseph-Egri (TRLW) Equation and Calogro-Degasperis (CD) Equation by Modified (G'/G²)-Expansion Method

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Journal of Applied Mathematics and Physics 2023年第7期11卷 2103-2120页

作者： Maha Al-Harbi Waleed Al-hamdan Luwai Wazzan Department of Mathematics King Abdulaziz University Jeddah Saudi Arabia

In this study, we will introduce the modified (G'/G2)-expansion method to explore some of the exact traveling wave solutions of some nonlinear partial differential equations namely, Phi-4 equation, Joseph-Egri (TRLW) equation, and Calogro-Degasperis (CD) equation. As a result, we have obtained solutions for the equations expressed in terms of trigonometric, hyperbolic and rational functions. Moreover, some selected solutions are plotted using some specific values for the parameters.

关键词： Exact Solutions Modified (G'/G2)-Expansion Method Phi-4 Equation Joseph-Egri (TRLW) Equation Calogro-Degasperis (CD) Equation

Numerical Methods for Solving Logarithmic Nonlinear Schrödinger’s Equation

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Journal of Applied Mathematics and Physics 2022年第12期10卷 3635-3648页

作者： Anees Al-Harbi Waleed Al-hamdan Luwai Wazzan Department of Mathematics King Abdulaziz University Jeddah Saudi Arabia

In this study, we will construct numerical techniques for tackling the logarithmic Schrödinger’s nonlinear equation utilizing the explicit scheme and the Crank-Nicolson scheme of the finite difference method. These schemes will be subjected to accuracy and stability tests before being used. Efficacy and robustness of the techniques under consideration will be demonstrated using an exact solution, one-Gausson, as well as conserved quantities. Interaction of two-soliton will be conducted. The numerical findings revealed, the interplay behavior is flexible.

关键词： Explicit Scheme Implicit Scheme Exact Solutions Bounded Domain Stability One Soliton Soliton Interaction Gaussons

A Deep-CNN Crowd Counting Model for Enforcing Social Distancing during COVID19 Pandemic: Application to Saudi Arabia’s Public Places

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Computers, Materials & Continua 2021年第2期66卷 1315-1328页

作者： Salma Kammoun Jarraya Maha hamdan Alotibi Manar Salamah Ali Department of Computer Science FCITKing Abdulaziz UniversityJeddahSaudi Arabia MIRACL-Laboratory Sfax UniversitySfaxTunisia Department of Computer Science King Khalid UniversityAbhaSaudi Arabia

With the emergence of the COVID19 virus in late 2019 and the declaration that the virus is a worldwide pandemic,health organizations and governments have begun to implement severe health precautions to reduce the spread of the virus and preserve human *** enforcement of social distancing at work environments and public areas is one of these obligatory *** management is one of the effective measures for social *** reducing the social contacts of individuals,the spread of the disease will be immensely *** this paper,a model for crowd counting in public places of high and low densities is *** model works under various scene conditions and with no prior knowledge.A Deep CNN model(DCNN)is built based on convolutional neural network(CNN)structure with small kernel size and two *** increase the efficiency of the model,a convolutional neural network(CNN)as the front-end and a multi-column layer with Dilated Convolution as the back-end were ***,the proposed method accepts images of arbitrary sizes/scales as inputs from different *** evaluate the proposed model,a dataset was created from images of Saudi people with traditional and non-traditional Saudi *** model was also trained and tested on some existing *** to current counting methods,the results show that the proposed model has significantly improved efficiency and reduced the error *** achieve the lowest MAE by 67%,32%.and 15.63%and lowest MSE by around 47%,15%and 8.1%than M-CNN,Cascaded-MTL,and CSRNet respectively.

关键词： CNN crowd counting COVID19

Prevalence and Correlates of Dyslipidemia among Adults in Saudi Arabia: Results from a National Survey

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Open Journal of Endocrine and Metabolic Diseases 2012年第4期2卷 89-97页

作者： abdulaziz F. Al-Kaabba Nasser A. Al-hamdan Ahmed El Tahir Abdelshakour M. Abdalla Abdalla A. Saeed Muaawia A. Hamza Faculty of Medicine King Fahad Medical City King Saud Bin AbdulAziz University for Health Sciences Riyadh Saudi Arabi Faculty of Medicine King Fahad Medical City King Saud Bin AbdulAziz University for Health Sciences Riyadh Saudi Arabia

Data were collected and analyzed from a cross-sectional study using the World Health Organization’s STEPwise approach, to estimate the prevalence of various types of dyslipidemia and determine their associated factors among adults in Kingdom of Saudi Arabia. The study population included 4490 Saudi adults aged 15 years and older who were selected by a stratified, multistage, cluster random sampling technique. Lipid profile was determined by spectrophotometrically by biochemical methods, high total cholesterol (TC) was defined as TC of 5.2 mmol/L or more, hypertriglyceridemia as serum triglycerides level 1.7 mmol/L or more and. low high-density lipoprotein cholesterol (HDL-C) as serum HDL-C 0.9 mmol/L or less, LDL-C 3.35 mmol/L or more and TC/HDL ratio 5 or more. Of the 4490 subjects (94.4 % of total sample) included in the final analysis, 51% were females, 23% of study subjects were less than 25years and 11% were 55 or more years of age. The overall prevalence of dyslipidemia ranged from about 20% to 40%. The highest prevalence was for triglycerides where about 44% of all subjects were affected. About a fifth of the subjects had high level of total cholesterol. Males had significantly higher prevalence of all types of dyslipidemia than female except LDL-C and TC. Higher dyslipidemia prevalence of total cholesterol and triglycerides were significantly found in older subjects, illiterates and housekeepers. Lower prevalence rates for HDL-C was significantly observed in retired and youngest subjects. There were significant regional variations and significantly higher prevalence of dyslipidemia among hypertensives, diabetics, obese/overweight, smokers and physically inactive subjects. There were no significant differences according to income or fruits and vegetable consumption. Logistic regression analysis revealed that obesity/overweight, gender, age, diabetes were the most important significant predictors of dyslipidemia. The findings of this study suggest that the pre

关键词： Dyslipidemia Prevalence Risk Factors Adults Saudi Arabia

Investigating Physical Exercise among Jordanians with Diabetes Mellitus

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Health 2016年第2期8卷 181-189页

作者： Muhammad W. Darawad Sultan Mosleh Amani A. Khalil Mahmoud Maharmeh Ayman M. hamdan-Mansour Osama A. Samarkandi Faculty of Nursing The University of Jordan Amman Jordan Faculty of Nursing University of Mutah Karak Jordan Prince Sultan bin abdulaziz College for Emergency Medical Services King Saud University Riyadh Saudi Arabia

This study is aimed to investigate exercise behaviors (frequency and duration) among Jordanian diabetic patients, and their correlation with their physical characteristics and perceived exercise benefits and barriers, exercise self efficacy, and exercise planning. An exploratory descriptive design was utilized using the cross-sectional survey with self-reported questionnaires (Demographics, Charlson Comorbidity Index, Exercise Self-Efficacy Scale, Exercise Benefits and barriers Scale, and Commitment to a Plan for Exercise Scale). A convenience sample of 115 Jordanians with diabetes mellitus was recruited from diabetes outpatient clinics. Participants reported an average number of 3.2 physical activities per week (average of 2.9 hours), with walking being the most common activity. Participant’s body mass index, comorbidity index, and exercise self-efficacy were correlated with both frequency and duration of exercise (r = -0.393, -0.286, 0.219 and -0.272, 0.383, 0.260, respectively). A predictive model of five predictors (age, BMI, CCI, exercise self efficacy, and perceived exercise barriers) that significantly predicted exercise duration (R2 = 0.34, F = 9.14, P < 0.000) was found. Diabetic patients were found to exercise less than optimum. Illness itself was not a cause of not exercising compared to lack of time and desire. Factors that can enhance or inhibit participants’ engagement in exercise should be included in designing tailored exercise educational programs.

关键词： Physical Exercise Benefits and barriers Self-Efficacy Diabetes Jordan

A Short Review of Classification Algorithms Accuracy for Data Prediction in Data Mining Applications

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Journal of Data Analysis and Information Processing 2021年第3期9卷 162-174页

作者： Ibrahim ba’abbad Thamer Althubiti Abdulmohsen Alharbi Khalid Alfarsi Saim Rasheed Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah KSA

Many business applications rely on their historical data to predict their business future. The marketing products process is one of the core processes for the business. Customer needs give a useful piece of information that helps to market the appropriate products at the appropriate time. Moreover, services are considered recently as products. The development of education and health services is depending on historical data. For the more, reducing online social media networks problems and crimes need a significant source of information. Data analysts need to use an efficient classification algorithm to predict the future of such businesses. However, dealing with a huge quantity of data requires great time to process. Data mining involves many useful techniques that are used to predict statistical data in a variety of business applications. The classification technique is one of the most widely used with a variety of algorithms. In this paper, various classification algorithms are revised in terms of accuracy in different areas of data mining applications. A comprehensive analysis is made after delegated reading of 20 papers in the literature. This paper aims to help data analysts to choose the most suitable classification algorithm for different business applications including business in general, online social media networks, agriculture, health, and education. Results show FFBPN is the most accurate algorithm in the business domain. The Random Forest algorithm is the most accurate in classifying online social networks (OSN) activities. Naïve bayes algorithm is the most accurate to classify agriculture datasets. OneR is the most accurate algorithm to classify instances withi

关键词： Data Prediction Techniques Accuracy Classification Algorithms Data Mining Applications