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| 1 | 脆壁克鲁维酵母乳糖酶提取物性质研究显示文摘研究了脆壁克鲁维酵母菌乳糖酶的性质 ,该酶作用最适 pH在 6 5~ 7 0 ,最适温度为 37℃ ,5 0℃保温 15min残留酶活为 84 0 2 % ,该酶在 pH 5 8~ 7 3范围内比较稳定 ,以ONPG和乳糖为底物的米氏常数为1 16mmol/L和 5 6 3mmol/L ,Mn2 + ,Mg2 + ,Na+ ,K+ 及微量Ca2 + | 谭树华 Hadeel Amalek A Majid 高向东 吴梧桐 | 2000 | 药物生物技术2000，7，3： | 14 |
| 2 | 遥感和GIS技术应用于伊拉克南部Basrah省土地利用/覆盖变化及城市扩张研究(英文)显示文摘In recent years, land use/cover dynamic change has become a key subject that needs to be dealt with in the study of global environmental change. In this paper, remote sensing and geographic information systems (GIS) are integrated to monitor, map, and quantify the land use/cover change in the southern part of Iraq (Basrah Province was taken as a case) by using a 1:250 000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation, sand, urban area, unused land, and water bodies. Supervised classification and normalized difference build-up index (NDBI) were used respectively to retrieve its urban boundary. An accuracy assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify and illustrate the various LULC conversions that took place over the 13-year span of time. Results showed that the urban area had increased by the rate of 1.2% per year, with area expansion from 3 299.1 km2 in 1990 to 3 794.9 km2 in 2003. Large vegetation area in the north and southeast were converted into urban construction land. The land use/cover changes of Basrah Province were mainly caused by rapid development of the urban economy and population immigration from the countryside. In addition, the former government policy of 'returning farmland to transportation and huge expansion in military camps' was the major driving force for vegetation land change. The paper concludes that remote sensing and GIS can be used to create LULC maps. It also notes that the maps generated can be used to delineate the changes that take place over time. | Hadeel A.S. Mushtak T.Jabbar 陈晓玲 | 2009 | Geo-Spatial Information Science2009，12，2： | 2 |
| 3 | Topical aqueous extract of Ephedra alata can improve wound healing in an animal model显示文摘PurposeEphedra alata (E。alata ) 是在巴勒斯坦和其它区域成长的长期的坚韧的灌木植物。它为各种各样的疾病的治疗在人们药经常被使用。在这个工程, E。alata 摘录为它改进创伤和灼伤 healing.MethodsAn 的能力被测试 E 的水的摘录。alata 为 phytochemical 混合物的主要的班的存在被准备并且经历几 phytochemical 分析。在那以后,聚乙烯包含 E 的摘录的基于乙二醇的软膏。alata 被准备,它的创伤和灼伤愈合活动是用为深创伤和完整的厚度皮灼伤的一个动物模型的测试 in-vivo。效果对安慰剂软膏被比较。皮肤活体检视被使失明的临床的组织病理学说评估,除了分析表明了的数字 analysis.ResultsPhytochemical phytochemical 的主要的班的存在包括 flavonoids,碱, phytosteroids,酉分的混合物,不稳定的油和丹宁在准备摘录加重。作为与安慰剂软膏相比, E。alata 软膏显著地改进了创伤溃疡愈合,而它没在灼伤 ulcers.ConclusionE 愈合的质量上显示出优点。alata 摘录富于 phytochemical 混合物并且能改善当谈论地适用时,愈合弯屈。 | Naim Kittana Hanood Abu-Rass Ruba Sabra Lama Manasra Hadeel Hanany Nidal Jaradat Fatima Hussein Abdel Naser Zaid | 2017 | Chinese Journal of Traumatology2017，20，2： | 2 |
| 4 | Together We Stand-Analyzing Schooling Behavior in Naive Newborn Guppies through Biorobotic Predators显示文摘A major advantage of animal aggregations concerns cooperative antipredator strategies.Schooling behavior emerges earlier in many fish species,especially in those cannibalizing their offspring.Experience is fundamental for developing schooling behavior.However,the cognitive ability of naive newborn fish to aggregate remains unclear.Herein,Poecilia reticulata,was selected as model organism to investigate how combinations of biomimetic robotic agents and adult conspecific olfactory cues affect collective responses in newborns.The role of white and brown backgrounds in evoking aggregations was also assessed.Olfactory cues were sufficient for triggering aggregations in P.reticulata newborns,although robotic agents had a higher influence on the group coalescence.The combination of robotic agents and olfactory cues increased schooling behavior duration.Notably,schooling was longer in the escape compartment when robotic agents were presented,except for the combination of the male-mimicking robotic fish plus adult guppy olfactory cues,with longer schooling behavior in the exploring compartment.Regardless of the tested cues,newborn fish aggregated preferentially on the brown areas of the arena.Overall,this research provides novel insights on the early collective cognitive ability of newborn fish,paving the way to the use of biomimetic robots in behavioral ecology experiments,as substitutes for real predators. | Donato Romano Hadeel Elayan Giovanni Benelli Cesare Stefanini | 2020 | Journal of Bionic Engineering2020，17，1： | 1 |
| 5 | Envi- ronmental change monitoring in the arid and semi arid re gions:a case study A1-Basrah Province, Iraq 显示文摘 | HADEEL A S MUSHTAK T JABBAR CHEN X L | 2010 | Environ- mental Monitoring and Assessment2010，167，14： | 1 |
| 6 | Intravenous dexmedetomidine infusion for labour analgesia in patient with preeclampsia显示文摘 | Sami A Abu-Halaweh Abdel-Kareem S Al Oweidi Hadeel Abu-Malooh Majd Zabalawi Fawaz Alkazaleh Hamdi Abu-Ali Michael AE Ramsay | 2009 | European Journal of Anaesthesiology2009，，1： | 1 |
| 7 | High-throughput computational screening for twodimensional magnetic materials based on experimental databases of three-dimensional compounds显示文摘We perform a computational screening for two-dimensional(2D)magnetic materials based on experimental bulk compounds present in the Inorganic Crystal Structure Database and Crystallography Open Database.A recently proposed geometric descriptor is used to extract materials that are exfoliable into 2D derivatives and we find 85 ferromagnetic and 61 antiferromagnetic materials for which we obtain magnetic exchange and anisotropy parameters using density functional theory.For the easy-axis ferromagnetic insulators we calculate the Curie temperature based on a fit to classical Monte Carlo simulations of anisotropic Heisenberg models.We find good agreement with the experimentally reported Curie temperatures of known 2D ferromagnets and identify 10 potentially exfoliable 2D ferromagnets that have not been reported previously.In addition,we find 18 easy-axis antiferromagnetic insulators with several compounds exhibiting very strong exchange coupling and magnetic anisotropy. | Daniele Torelli Hadeel Moustafa Karsten W.Jacobsen Thomas Olsen | 2020 | npj Computational Materials2020，，1： | 1 |
| 8 | The efficacy of caudal dexmedetomidine on stress response and postoperative pain in pediatric cardiac surgery显示文摘 | Dalia Nasr Hadeel Abdelhamid | 2013 | Annals of Cardiac Anaesthesia2013，，2： | 1 |
| 9 | Accuracy of International Guidelines for Identifying Significant Fibrosis in Hepatitis B e Antigen-Negative Patients with Chronic Hepatitis显示文摘 | Faisal M. Sanai Mohammed A. Babatin Khalid I. Bzeizi Fahad AlSuhaibani Waleed Al-Hamoudi Khaled S. Alsaad Hadeel AlMana Fayaz A. Handoo Hamad Al-Ashgar Hamdan AlGhamdi Abeer Ibrahim Abdulrahman Aljumah Abduljaleel Alalwan Ibrahim H. AlTraif Hussa Al-Hussa | 2013 | Clinical Gastroenterology and Hepatology2013，，： | 1 |
| 10 | Accuracy of International Guidelines for Identifying Significant Fibrosis in Hepatitis B e Antigen-Negative Patients with Chronic Hepatitis显示文摘 | Faisal M. Sanai Mohammed A. Babatin Khalid I. Bzeizi Fahad AlSuhaibani Waleed Al-Hamoudi Khaled S. Alsaad Hadeel AlMana Fayaz A. Handoo Hamad Al-Ashgar Hamdan AlGhamdi Abeer Ibrahim Abdulrahman Aljumah Abduljaleel Alalwan Ibrahim H. AlTraif Hussa Al-Hussa | 2013 | Clinical Gastroenterology and Hepatology2013，，： | 1 |
| 11 | Hybrid meta-heuristic methods for the multi-resource leveling problem with activity splitting显示文摘 | Hadeel Alsayegh Moncer Hariga | 2012 | Automation in Construction2012，，： | 1 |
| 12 | Synthesis of new ammonium chitosan derivatives and their application for dye removal from aqueous media显示文摘 | Khalid Z. Elwakeel M.A. Abd El-Ghaffar Salah M. El-kousy Hadeel G. El-Shorbagy | 2012 | Chemical Engineering Journal2012，，： | 1 |
| 13 | Artificial Intelligence Based Optimal Functional Link Neural Network for Financial Data Science显示文摘In present digital era,data science techniques exploit artificial intelligence(AI)techniques who start and run small and medium-sized enterprises(SMEs)to have an impact and develop their businesses.Data science integrates the conventions of econometrics with the technological elements of data science.It make use of machine learning(ML),predictive and prescriptive analytics to effectively understand financial data and solve related problems.Smart technologies for SMEs enable allows the firm to get smarter with their processes and offers efficient operations.At the same time,it is needed to develop an effective tool which can assist small to medium sized enterprises to forecast business failure as well as financial crisis.AI becomes a familiar tool for several businesses due to the fact that it concentrates on the design of intelligent decision making tools to solve particular real time problems.With this motivation,this paper presents a new AI based optimal functional link neural network(FLNN)based financial crisis prediction(FCP)model forSMEs.The proposed model involves preprocessing,feature selection,classification,and parameter tuning.At the initial stage,the financial data of the enterprises are collected and are preprocessed to enhance the quality of the data.Besides,a novel chaotic grasshopper optimization algorithm(CGOA)based feature selection technique is applied for the optimal selection of features.Moreover,functional link neural network(FLNN)model is employed for the classification of the feature reduced data.Finally,the efficiency of theFLNNmodel can be improvised by the use of cat swarm optimizer(CSO)algorithm.A detailed experimental validation process takes place on Polish dataset to ensure the performance of the presented model.The experimental studies demonstrated that the CGOA-FLNN-CSO model has accomplished maximum prediction accuracy of 98.830%,92.100%,and 95.220%on the applied Polish dataset Year I-III respectively. | Anwer Mustafa Hilal Hadeel Alsolai Fahd NAl-Wesabi Mohammed Abdullah Al-Hagery Manar Ahmed Hamza Mesfer Al Duhayyim | 2022 | Computers, Materials & Continua2022，，3： | 1 |
| 14 | The value of bedside Lung Ultrasonography in diagnosis of neonatal pneumonia 显示文摘 | Hadeel M Seif E1 Dien Dalia AK | 2013 | The Egyptian Journal of Radiology and Nu-clear Medicine2013，4，19： | 1 |
| 15 | Environmental change monitoring in the arid and semi-arid regions: a case study A1-Basrah Province, Iraq显示文摘 | Hadeel A S Mushtak T Jabbar Chen Xiao-ling | 2010 | Environmental Monitoring and As- sessment2010，167，14： | 1 |
| 16 | Opinions and attitudes toward targeted temperature management in the emergency department and intensive care unit in a developing country: a survey study显示文摘INTRODUCTION The past two decades have witnessed one of the most contentious scientific debates in the field of temperature management after cardiac arrest in adults.It started in 2002,following the publication of two groundbreaking trials showing lower mortality rates and improved neurologic recovery with the use of active cooling.[1,2]International recommendations advocate active cooling in the range of 32–34℃for comatose survivors of out-of-hospital cardiac arrest (OHCA).[3,4]The year2013 marked the tipping point with the release of the TTM 1 trial. | Abdullah Bakhsh Hadeel Alotaibi Sara Alothman Abdulrahman Alothman Rahaf Alothman Abdulrahman Alsulami Malak Alamoudi Ali Alothman Ali Al-Shareef | 2023 | World Journal of Emergency Medicine2023，14，2： | 1 |
| 17 | Self-Reported Hair Loss Following COVID-19: An Observational Study显示文摘Objective: COVID-19 has been significantly associated with both psychosocial stress and physiologic stress, both of which are known to trigger telogen effluvium. This study was performed to estimate the prevalence of hair loss among patients with COVID-19 and to determine the correlation of the severity of COVID-19 with the severity of hair loss.Methods: Data were collected through a self-administered electronic questionnaire that was distributed among social media platforms. Participants were invited to complete the survey using a convenience sampling technique. A multiple response dichotomies analysis and chi-square test of independence were used to analyze data.Results: Among 420 participants who reported a positive PCR result of SARS-CoV-2, 77.6% reported hair loss after COVID-19 development. Notably, the onset of hair loss was within 3 weeks of COVID-19 development in 29% of participants. Most of the participants reported that the duration of hair loss was up to 6 months, and hair regrowth was noticed within 1 year after COVID-19 development. Patients who were admitted to the hospital, who experienced respiratory difficulties, who had lost weight due to COVID-19, and who experienced symptoms for longer than 10 days were significantly more prone to experience severe hair loss following COVID-19 (P < 0.001).Conclusion: This study demonstrated a high frequency of self-reported hair loss after the development of COVID-19. Interestingly, even patients with mild COVID-19 symptoms were significantly more prone to experience moderate hair loss. Unique to COVID-19 infection, the onset of hair loss following the development of COVID-19 was within 3 weeks in one-third of the participants. | Abdulmajeed Alajlan Rema Aldihan Lyan Almana Rahaf Althnayan Hadeel Awartani Sami Alsuwaidan | 2023 | International Journal of Dermatology and Venereology2023，6，1： | 0 |
| 18 | Automated Deep Learning Driven Crop Classification on Hyperspectral Remote Sensing Images显示文摘Hyperspectral remote sensing/imaging spectroscopy is a novel approach to reaching a spectrum from all the places of a huge array of spatial places so that several spectral wavelengths are utilized for making coherent images.Hyperspectral remote sensing contains acquisition of digital images from several narrow,contiguous spectral bands throughout the visible,Thermal Infrared(TIR),Near Infrared(NIR),and Mid-Infrared(MIR)regions of the electromagnetic spectrum.In order to the application of agricultural regions,remote sensing approaches are studied and executed to their benefit of continuous and quantitativemonitoring.Particularly,hyperspectral images(HSI)are considered the precise for agriculture as they can offer chemical and physical data on vegetation.With this motivation,this article presents a novel Hurricane Optimization Algorithm with Deep Transfer Learning Driven Crop Classification(HOADTL-CC)model onHyperspectralRemote Sensing Images.The presentedHOADTL-CC model focuses on the identification and categorization of crops on hyperspectral remote sensing images.To accomplish this,the presentedHOADTL-CC model involves the design ofHOAwith capsule network(CapsNet)model for generating a set of useful feature vectors.Besides,Elman neural network(ENN)model is applied to allot proper class labels into the input HSI.Finally,glowworm swarm optimization(GSO)algorithm is exploited to fine tune the ENNparameters involved in this article.The experimental result scrutiny of the HOADTL-CC method can be tested with the help of benchmark dataset and the results are assessed under distinct aspects.Extensive comparative studies stated the enhanced performance of the HOADTL-CC model over recent approaches with maximum accuracy of 99.51%. | Mesfer Al Duhayyim Hadeel Alsolai Siwar Ben Haj Hassine Jaber SAlzahrani Ahmed SSalama Abdelwahed Motwakel Ishfaq Yaseen Abu Sarwar Zamani | 2023 | Computers, Materials & Continua2023，，2： | 0 |
| 19 | Machine Learning Based Depression,Anxiety,and Stress Predictive Model During COVID-19 Crisis显示文摘Corona Virus Disease-2019(COVID-19)was reported at first in Wuhan city,China by December 2019.World Health Organization(WHO)declared COVID-19 as a pandemic i.e.,global health crisis onMarch 11,2020.The outbreak of COVID-19 pandemic and subsequent lockdowns to curb the spread,not only affected the economic status of a number of countries,but it also resulted in increased levels of Depression,Anxiety,and Stress(DAS)among people.Therefore,there is a need exists to comprehend the relationship among psycho-social factors in a country that is hypothetically affected by high levels of stress and fear;with tremendously-limitingmeasures of social distancing and lockdown in force;and with high rates of new cases and mortalities.With this motivation,the current study aims at investigating theDAS levels among college students during COVID-19 lockdown since they are identified as a highly-susceptible population.The current study proposes to develop Intelligent Feature Subset Selection withMachine Learning-based DAS predictive(IFSSML-DAS)model.The presented IFSSML-DAS model involves data preprocessing,Feature Subset Selection(FSS),classification,and parameter tuning.Besides,IFSSML-DAS model uses Group Gray Wolf Optimization based FSS(GGWO-FSS)technique to reduce the curse of dimensionality.In addition,Beetle Swarm Optimization based Least Square Support Vector Machine(BSO-LSSVM)model is also employed for classification in which the weight and bias parameters of the LSSVM model are optimally adjusted using BSO algorithm.The performance of the proposed IFSSML-DAS model was tested using a benchmark DASS-21 dataset and the results were investigated under different measures.The outcome of the study suggests the development of specialized programs to handleDAS among population so as to overcome COVID-19 crisis. | Fahd N.Al-Wesabi Hadeel Alsolai Anwer Mustafa Hilal Manar Ahmed Hamza Mesfer Al Duhayyim Noha Negm | 2022 | Computers, Materials & Continua2022，，3： | 0 |
| 20 | In Vitro Study on Virulence Potentials of Burkholderia pseudomallei Isolated from Immunocompromised Patients显示文摘 | Hadeel Tawfiq Al-Hadithi Rana Muhammad Abdulnabi | 2012 | Journal of Life Sciences2012，6，10： | 0 |
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