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Rhizosphere microbiomes can regulate plant drought tolerance

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Pedosphere 2022年第1期32卷 61-74页

作者： Mehtab Muhammad ASLAM Eyalira JOKal aisha Lawan IDRIS Zhang QIAN Weifeng XU Joseph K.KARANJA Shabir HWANI Wei YUAN College of Agriculture Yangzhou UniversityYangzhou 225009China Joint International Research Laboratory of Water and Nutrient in Crops and College of Life Sciences Center for Plant Water-Use and Nutrition Regulation and College of Resources and EnvironmentFujian Agriculture and Forestry UniversityFuzhou 350002China Juncao Research Center College of Life SciencesFujian Agriculture and Forestry UniversityFuzhou 350002China State Key Laboratory of Ecological Pest Control for Fujian and Taiwan Crops&Key Laboratory of Biopesticide and Chemical Biology of Ministry of Education College of Life SciencesFujian Agriculture and Forestry UniversityFuzhou 350002China Mountain Research Centre for Field Crops Khudwani Sher-e-Kashmir University of Agricultural Sciences and TechnologyKashmir 192102India

Beneficial root-associated rhizospheric microbes play a key role in maintaining host plant growth and can potentially allow drought-resilient crop production. The complex interaction of root-associated microbes mainly depends on soil type, plant genotype, and soil moisture. However, drought is the most devastating environmental stress that strongly reduces soil biota and can restrict plant growth and yield. In this review, we discussed our mechanistic understanding of drought and microbial response traits. Additionally, we highlighted the role of beneficial microbes and plant-derived metabolites in alleviating drought stress and improving crop growth. We proposed that future research might focus on evaluating the dynamics of root-beneficial microbes under field drought conditions. The integrative use of ecology, microbial, and molecular approaches may serve as a promising strategy to produce more drought-resilient and sustainable crops.

关键词： biota drought stress metabolites phytohormone plant growth root-microbe association

Water Wave Optimization with Deep Learning Driven Smart Grid Stability Prediction

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Computers, Materials & Continua 2022年第12期73卷 6019-6035页

作者： Anwer Mustafa Hilal aisha Hassan Abdalla Hashim Heba G.Mohamed Mohammad alamgeer Mohamed K.Nour Anas Abdelrahman Abdelwahed Motwakel Department of Electrical and Computer Engineering International Islamic University MalaysiaKuala Lumpur53100Malaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science and Bioinformatics Singhania UniversityPacheri BariJhnujhunuRajasthanIndia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Mechanical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11835Egypt

Smart Grid(SG)technologies enable the acquisition of huge volumes of high dimension and multi-class data related to electric power grid operations through the integration of advanced metering infrastructures,control systems,and communication *** SGs,user demand data is gathered and examined over the present supply criteria whereas the expenses are then informed to the clients so that they can decide about electricity *** the entire procedure is valued on the basis of time,it is essential to perform adaptive estimation of the SG’s *** advancements inMachine Learning(ML)andDeep Learning(DL)models enable the designing of effective stability prediction models in *** this background,the current study introduces a novel Water Wave Optimization with Optimal Deep Learning Driven Smart Grid Stability Prediction(WWOODL-SGSP)*** aim of the presented WWOODL-SGSP model is to predict the stability level of SGs in a proficient *** attain this,the proposed WWOODL-SGSP model initially applies normalization process to scale the data to a uniform ***,WWO algorithm is applied to choose an optimal subset of features from the pre-processed ***,Deep Belief Network(DBN)model is followed to predict the stability level of ***,Slime Mold algorithm(SMA)is exploited to fine tune the hyperparameters involved in DBN *** order to validate the enhanced performance of the proposedWWOODL-SGSP model,a wide range of experimental analyses was *** simulation results confirmthe enhanced predictive results of WWOODL-SGSP model over other recent approaches.

关键词： Smart grid stability prediction deep learning energy systems machine learning metaheursitics

高效、可重复使用的多相催化剂SiO_2-NaHSO_4用于水中三组分一锅法合成八氢喹唑啉-2,5-二酮(英文)

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催化学报 2012年第4期33卷 677-680页

作者： Sadeq Hamood Saleh AZZAM aisha SIDDEKHA Aatika NIZAM Mohamed Afzal PASHA Department of Studies in Chemistry Central College CampusBangalore UniversityBengaluru-560001India Department of Chemistry Smt.V.H.D.Central Institute of Home ScienceBangalore-560001India

An environmentally benign method for the synthesis of octahydro-quinazolin-2,5-diones by the reaction of aromatic aldehydes,dimedone,and urea in the presence of SiO2-NaHSO4 is ***2-NaHSO4 acts as an efficient,mild,and... 详细信息

关键词：化学催化高压高温

Prevalence and Factors Associated with Postpartum Depression during the COVID-19 Pandemic among Women in Jeddah, Saudi Arabia: A Cross-Sectional Study

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Open Journal of Obstetrics and Gynecology 2020年第11期10卷 1644-1657页

作者： aisha Ibrahim Tarabay Dalal Boogis Aysha Tariq Tabbakh Raghad Akram Kemawi Layan Abduljalil Boogis Abdulrahman Tariq Tabbakh Maha Mohsen al-Hadrami Manal Mohsen al-Hadrami Obstetrics and Gynecology Consultant King Abdulaziz Hospital Jeddah KSA Medical Intern IbnSina College Jeddah KSA Medical Student Battarje Medical College Jeddah KSA Medical Student IbnSina National College Jeddah KSA

Background: Postpartum depression is the most common psychological health problem among females;it begins after the birth of the child and can occur at any time during the first year of delivery. The COVID-19 pandemic is a novel virus that is highly infectious and has several negative psychological impacts on individuals globally. Aim: Coronavirus disease 2019 (COVID-19) has been reported to increase the incidence rate of depression. We investigated the prevalence rate and associated factors of postpartum depression (PPD) among women in Jeddah, Saudi Arabia, during the COVID-19 period, thereby attempting to determine whether and how COVID-19 affected PPD. Methods: This is a cross-sectional study that was conducted on women at one week to six months postpartum using an online questionnaire. SPSS program was used for analyzing data. Results: This study included 150 participated women;49.3% were in the age range of 25 - 34 years old. There were 30.7% reported being primigravida. Regarding the level of depression, there were 60.7% reported the presence of depression;the depression was affected by some demographics of females such as the education level (P = 0.021) and other factors related to the COVID-19 pandemic such as visiting the doctor during

关键词： PPD COVID-19 Prevalence Associated Factors

Explainable Classification Model for Android Malware Analysis Using API and Permission-Based Features

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Computers, Materials & Continua 2023年第9期76卷 3167-3188页

作者： Nida Aslam Irfan Ullah Khan Salma Abdulrahman Bader aisha alansari Lama Abdullah alaqeel Razan Mohammed Khormy Zahra Abdultawab alKubaish Tariq Hussain SAUDI ARAMCO Cybersecurity Chair Department of Computer ScienceCollege of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Computer Engineering Department College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia School of Computer Science and Technology Zhejiang Gongshang UniversityHangzhouChina

One of the most widely used smartphone operating systems,Android,is vulnerable to cutting-edge malware that employs sophisticated *** malware attacks could lead to the execution of unauthorized acts on the victims’devices,stealing personal information and causing hardware *** previous studies,machine learning(ML)has shown its efficacy in detecting malware events and classifying their ***,attackers are continuously developing more sophisticated methods to bypass ***,up-to-date datasets must be utilized to implement proactive models for detecting malware events in Android mobile ***,this study employed ML algorithms to classify Android applications into malware or goodware using permission and application programming interface(API)-based features from a recent *** overcome the dataset imbalance issue,RandomOverSampler,synthetic minority oversampling with tomek links(SMOTETomek),and RandomUnderSampler were applied to the Dataset in different *** results indicated that the extra tree(ET)classifier achieved the highest accuracy of 99.53%within an elapsed time of 0.0198 s in the experiment that utilized the RandomOverSampler ***,the explainable Artificial Intelligence(EAI)technique has been applied to add transparency to the high-performance ET *** global explanation using the Shapely values indicated that the top three features contributing to the goodware class are:Ljava/net/URL;->openConnection,Landroid/location/LocationManager;->getLastKgoodwarewnLocation,and *** the other hand,the top three features contributing to themalware class are Receive_Boot_Completed,Get_Tasks,and Kill_Background_*** is believed that the proposedmodel can contribute to proactively detectingmalware events in Android devices to reduce the number of victims and increase users’trust.

关键词： Android malware machine learning malware detection explainable artificial intelligence cyber security

Phenolic Contents and Antioxidant Activities of Green Tea with and without Lemon

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Natural Science 2016年第6期8卷 247-255页

作者： Ayat B. al-Ghafari Ayat M. Shorbaji Lamya A. al-Sarori Eman O. Baduwailan aisha A. Basaar Huda A. al Doghaither Hala F. al-Marzouki Ulfat M. Omar Department of Biochemistry Faculty of Science King Abdulaziz University Jeddah KSA

Tea is the most widely consumed beverage throughout the world, after water and is considered as a good antioxidant nutrient against free radical reactions. Lemons are citrus fruits that are very common in many parts of the world and are well known for their health benefits. In this study, different assays were used to evaluate total phenolic content and antioxidant activities of green tea with and without lemon. Our results showed that green tea with lemon has higher phenolic content, stronger reducing power than green tea without lemon;and exhibits a significant inhibition of 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and hydrogen peroxide (H2O2). However, both samples exhibited high ferrous chelating activity with no significant difference among each other indicating a good antioxidant potential for both. This is a comparative study between green tea and green tea supplemented with lemon. The study contributes to a better understanding about how the addition of supplements like lemon might influence the antioxidant activity of tea.

关键词： Antioxidant Activity Green Tea Lemon Metal Chelation Phenolic Compounds Radical Scavenging Component

Restricted Three-Body Problem in Cylindrical Coordinates System

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Applied Mathematics 2012年第8期3卷 907-909页

作者： Mohammed Sharaf aisha alshaery Department of Astronomy Faculty of Science King Abdul Aziz University Jeddah Saudi Arabia Department of Mathematics Faculty of Science King Abdul Aziz University Jeddah Saudi Arabia

In this paper, the equations of motion for spatial restricted circular three body problem will be established using the cylindrical coordinates. Initial value procedure that can be used to compute both the cylindrical... 详细信息

关键词： Spatial Restricted Circular Three Body Problem Regularization

Melting heat transfer with radiative effects and homogeneous–heterogeneous reaction in thermally stratified stagnation flow embedded in porous medium

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Journal of Central South University 2018年第11期25卷 2701-2711页

作者： M.JAVED M.FAROOQ S.AHMAD aisha ANJUM Department of Mathematics Riphah International UniversityIslamabad 44000Pakistan

The present article deals with thermally stratified stagnation-point flow saturated in porous medium on surface of variable thickness along with more convincing and reliable surface condition termed as melting heat ***–heterogeneous reaction and radiative effects have been further taken into account to reconnoiterproperties of heat *** heat transfer and phenomenon of homogeneous–heterogeneous reaction have engrossed widespread utilization in purification of metals,welding process,electroslag melting,biochemical systems,catalysis and several industrial *** transformations are utilized to attain a scheme of ordinary differential equations possessing exceedingly nonlinear *** process is employed to develop convergent solutions of the resulting *** regarding velocity,thermal field and concentration distribution for several involved parameters is pivotal *** behaviors of skin friction coefficient and Nusselt number are also *** of the reactants is found to depreciate as a result of strength of both heterogeneous and homogeneous reaction *** existence of melting phenomenon,declining attitude of fluid temperature is observed for higher radiation parameter.

关键词： melting heat transfer porous medium stagnation point variable sheet thickness homogeneous– heterogeneous reaction

Sensory Evaluation of Flavored Soy Milk-Based Yogurt： A Comparison between Jordanian and Malaysian Consumers

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Journal of Food Science and Engineering 2014年第1期4卷 27-35页

作者： Anas AI-Nabulsi Reyad Shaker Tareq Osaili Mahmoud al-Taani Amin Olaimat Saddam Awaisheh aisha Abushelaibi Richard Holley Department of Nutrition and Food Technology Faculty of Agriculture Jordan University of Science and Technology Irbid 22110Jordan Department of Food Science Collage of Food and Agriculture United Arab Emirates University Al-Ain 15551 UAE Department of Clinical Nutrition and Dietetics College of Health Sciences University of Sharjah Sharjah 27272 UAE Department of Food Science Faculty of Agriculture and Food Sciences University of Manitoba Winnipeg MB R3T 2N2 Canada Department of Nutrition and Food Technology A l-Balqa Applied University Al-Salt 19117 Jordan

Soy yogurt has gained significant popularity due to its nutritional health benefits. The objectives of this study were to develop flavored yogurt from soybean milk with reduced soy aftertaste by the addition of 30% （wt/wt） strawberry or orange jam in conjunction with a lactic acid fermentation. Soy milk-based yogurt products were assessed for microbial quality and for acceptability by a panel of Jordanian and Malaysian consumers. Sixty-one individuals, of whom 75.4% （n = 46） were Jordanian and 24.6% （n = 15） were Malaysian, evaluated the plain and flavored soy milk-based yogurt. The overall acceptability of orange and strawberry soy yogurt was rated significantly higher than plain soy yogurt. In general, the orange and strawberry soy yogurt received higher sensory ratings from Malaysian than Jordanian consumers. In addition, formulations with orange jam received higher scores than those flavored with strawberry. Shelf life tests showed that soy yogurt was acceptable for at least 8 d without perceptible spoilage. Therefore, the approach used yielded flavored products with better acceptability and improved sensory attributes, including decreased intensity of off flavor, with suitable shelf life at 4 ℃.

关键词： Soy milk sensory evaluation flavored yogurt shelf life functional food.