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Biomechanical Evaluation of Nano-Zirconia Coatings on Ti-6Al-7Nb Implant Screws in Rabbit Tibias

Current Medical Science 2018年第3期38卷 530-537页

作者： Thekra I. Hamad Abdalbseet A Fatalla amer subhi waheed Zena G. M. Azzawi Ying-guang CAO Ke SONG Department of Prosthodontics College of Dentistry University of Baghdad Baghdad 1417 Iraq MSc Ministry of Health Baghdad 1417 Iraq Department of Prosthodontics and lmplantology Tongjj Medical Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan 430030 China

The clinical success of dental implants can be improved by achieving optimum implant properties, such as their biomechanical and surface characteristics. Nano-structured coatings can play an important role in improving the implant surface. The purpose of the present study was to determine the most appropriate conditions for electrophoretic deposition （EPD） of nano-zirconia coatings on Ti-6A1-7Nb substrates and to evaluate the structural and biomechanical characteristics of these deposited coatings on the dental implants. EPD was used with different applied voltages and time periods to obtain a uniform layer of nano-zirconia on Ti-6A1-7Nb samples. The coated samples were weighed and the thickness of the product layer was measured. Surface analysis was performed by using optical microscopical examination, scanning electron microscope and X-ray diffraction phase analysis. For in vivo examination, 48 screw-designed implants （24 uncoated and 24 nano-zirconia coated） were implanted in both tibiae of 12 white New Zealand rabbits and evaluated biomechanically after 4- and 12-week healing intervals. Results revealed that the use of different conditions for EPD affected the final coating film properties. Increasing the applied voltage and coating time period increased the deposited nano-zirconia film thickness and weight. By selecting the appropriate coating conditions, and analyzing scanning electron microscopical examination and XRD patterns, this technique could produce a thin and continuous nano-zirconia layer with a uniform thickness of the Ti-6A1-7Nb samples. Mechanically, the nano-zirconia-coated implants showed a highly statistically significant difference in removal torque values, while histologically these coated implants enhanced and promoted osseointegration after 4 and 12 weeks of healing, compared with the uncoated ones. In conclusion, EPD is an effective technique for providing a high quality nano-zirconia coating film on dental implant surfaces. Moreover, the

关键词： dental implants electrophoretic deposition nano-zirconia surface characterization

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Characterization of Unsaturated Polyester Filled with Waste Coconut Shells, Walnut Shells, and Carbon Fibers

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Fluid Dynamics & Materials Processing 2023年第10期19卷 2449-2469页

作者： Marwah subhi Attallah Reem Alaa Mohammed Ruaa Haitham Abdel-Rahim Department of Materials Engineering University of Technology-IraqBaghdadIraq

This study aims to evaluate the erosion behavior and the hardness of hybrid composites made of varying amounts of coconut shells,walnut shells,and carbonﬁbers dispersed in a polyester ***(L16)Taguchi experiments were used to determine the optimal combination of *** particular,an erosion device con-sisting of a motor with a constantﬂow rate of 45 L/min,a pump with a diameter of 40 mm,a nozzle with a dia-meter of 5 mm,and a tank made of“perspex glass”55 cm long,30 cm tall,and 25 cm wide was *** tests were conducted by varying the sample-to-nozzle distance,the pattern angle,and the sand particle *** results have revealed that the presence of 7.5%by weight of waste coconut shell,for conditions corresponding to 90°angle,sand size 425μm,stand distance 30 cm,gives the best wear resistance(3.04×10^(-5) g/g).Theﬁller content and sand particle size affect the erosive rate,with the angle playing a secondary *** distance between the sample and the nozzle has a weaker effect on erosive *** hardness results show that the models(UP-5%carbonﬁber-2.5-3.5-4.5-5.5-6.5-7.5 wt.%waste coconut shell)give the best values for prayer compared to the samples(UP-5 wt.%carbonﬁber-2.5-3.5-4.5-5.5-6.5-7.5 wt.%waste walnut shell).

关键词： Unsaturated polyester resin carbonﬁber waste coconut shell walnut shell erosive behavior Taguchi’s method L16

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Modified Wild Horse Optimization with Deep Learning Enabled Symmetric Human Activity Recognition Model

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Computers, Materials & Continua 2023年第5期75卷 4009-4024页

作者： Bareen Shamsaldeen Tahir Zainab Salih Ageed Sheren Sadiq Hasan subhi R.M.Zeebaree Accounting Department College of Administration and EconomicsUniversity of DuhokDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq ITM Department Technical College of AdministrativeDuhok Polytechnic UniversityDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Traditional indoor human activity recognition(HAR)is a timeseries data classification problem and needs feature ***,considerable attention has been given to the domain ofHARdue to the enormous amount of its real-time uses in real-time applications,namely surveillance by authorities,biometric user identification,and health monitoring of older *** extensive usage of the Internet of Things(IoT)and wearable sensor devices has made the topic of HAR a vital subject in ubiquitous and mobile *** more commonly utilized inference and problemsolving technique in the HAR system have recently been deep learning(DL).The study develops aModifiedWild Horse Optimization withDLAided Symmetric Human Activity Recognition(MWHODL-SHAR)*** major intention of the MWHODL-SHAR model lies in recognition of symmetric activities,namely jogging,walking,standing,sitting,*** the presented MWHODL-SHAR technique,the human activities data is pre-processed in various stages to make it compatible for further processing.A convolution neural network with an attention-based long short-term memory(CNNALSTM)model is applied for activity *** MWHO algorithm is utilized as a hyperparameter tuning strategy to improve the detection rate of the CNN-ALSTM *** experimental validation of the MWHODL-SHAR technique is simulated using a benchmark *** extensive comparison study revealed the betterment of theMWHODL-SHAR technique over other recent approaches.

关键词： Human activity recognition symmetry deep learning machine learning pattern recognition time series classification

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Parameter Tuned Deep Learning Based Traffic Critical Prediction Model on Remote Sensing Imaging

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Computers, Materials & Continua 2023年第5期75卷 3993-4008页

作者： Sarkar Hasan Ahmed Adel Al-Zebari Rizgar R.Zebari subhi R.M.Zeebaree Computer Networks Department Sulaimani Polytechnic UniversitySulaimaniIraq Information Technology Department Technical College of Informatics-AkreDuhok Polytechnic UniversityIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Remote sensing(RS)presents laser scanning measurements,aerial photos,and high-resolution satellite images,which are utilized for extracting a range of traffic-related and road-related *** has a weakness,such as traffic fluctuations on small time scales that could distort the accuracy of predicted road and traffic *** article introduces an Optimal Deep Learning for Traffic Critical Prediction Model on High-Resolution Remote Sensing Images(ODLTCP-HRRSI)to resolve these *** presented ODLTCP-HRRSI technique majorly aims to forecast the critical traffic in smart *** attain this,the presented ODLTCP-HRRSI model performs two major *** the initial stage,the ODLTCP-HRRSI technique employs a convolutional neural network with an auto-encoder(CNN-AE)model for productive and accurate traffic ***,the hyperparameter adjustment of the CNN-AE model is performed via the Bayesian adaptive direct search optimization(BADSO)*** experimental outcomes demonstrate the enhanced performance of the ODLTCP-HRRSI technique over recent approaches with maximum accuracy of 98.23%.

关键词： Remote sensing images traffic prediction deep learning smart cities intelligent transportation systems

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Improved Transient Search Optimization with Machine Learning Based Behavior Recognition on Body Sensor Data

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Computers, Materials & Continua 2023年第5期75卷 4593-4609页

作者： Baraa Wasfi Salim Bzar Khidir Hussan Zainab Salih Ageed subhi R.M.Zeebaree ITM Department Technical College of AdministrationDuhok Polytechnic UniversityDuhokIraq Information System Engineering Department Erbil Technical Engineering CollegeErbil Polytechnic UniversityErbilIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Recently,human healthcare from body sensor data has gained considerable interest from a wide variety of human-computer communication and pattern analysis research owing to their real-time applications namely smart healthcare *** though there are various forms of utilizing distributed sensors to monitor the behavior of people and vital signs,physical human action recognition(HAR)through body sensors gives useful information about the lifestyle and functionality of an *** article concentrates on the design of an Improved Transient Search Optimization with Machine Learning based BehaviorRecognition(ITSOMLBR)technique using body sensor *** presented ITSOML-BR technique collects data from different body sensors namely electrocardiography(ECG),accelerometer,and *** addition,the ITSOML-BR technique extract features like variance,mean,skewness,and standard ***,the presented ITSOML-BR technique executes a micro neural network(MNN)which can be employed for long term healthcare monitoring and ***,the parameters related to the MNN model are optimally selected via the ITSO *** experimental result analysis of the ITSOML-BR technique is tested on the MHEALTH *** comprehensive comparison study reported a higher result for the ITSOMLBR approach over other existing approaches with maximum accuracy of 99.60%.

关键词： Behavior recognition transient search optimization machine learning healthcare sensors wearables

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Automated Colonic Polyp Detection and Classification Enabled Northern Goshawk Optimization with Deep Learning

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Computers, Materials & Continua 2023年第5期75卷 3677-3693页

作者： Mohammed Jasim Mohammed Jasim Bzar Khidir Hussan subhi R.M.Zeebaree Zainab Salih Ageed Engineering College Al-Kitab UniversityKirkukIraq Information System Engineering Department Erbil Technical Engineering CollegeErbil Polytechnic UniversityErbilIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq

The major mortality factor relevant to the intestinal tract is the growth of tumorous cells(polyps)in various *** specifically,colonic polyps have a high rate and are recognized as a precursor of colon cancer *** is the conventional technique for detecting colon polyps,and considerable research has proved that automated diagnosis of image regions that might have polyps within the colon might be used to help experts for decreasing the polyp miss *** automated diagnosis of polyps in a computer-aided diagnosis(CAD)method is implemented using statistical ***,Deep Learning,particularly throughConvolution Neural networks(CNN),is broadly employed to allowthe extraction of representative *** manuscript devises a new Northern Goshawk Optimization with Transfer Learning Model for Colonic Polyp Detection and Classification(NGOTL-CPDC)*** NGOTL-CPDC technique aims to investigate endoscopic images for automated colonic polyp *** accomplish this,the NGOTL-CPDC technique comprises of adaptive bilateral filtering(ABF)technique as a noise removal process and image pre-processing ***,the NGOTL-CPDC model applies the Faster SqueezeNet model for feature extraction purposes in which the hyperparameter tuning process is performed using the NGO ***,the fuzzy Hopfield neural network(FHNN)method can be employed for colonic poly detection and classification.A widespread simulation analysis is carried out to ensure the improved outcomes of the NGOTL-CPDC *** comparison study demonstrates the enhancements of the NGOTL-CPDC model on the colonic polyp classification process on medical test images.

关键词： Biomedical imaging artificial intelligence colonic polyp classification medical image classification computer-aided diagnosis

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Solar Radiation Prediction Using Satin Bowerbird Optimization with Modified Deep Learning

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Computer Systems Science & Engineering 2023年第9期46卷 3225-3238页

作者： Sheren Sadiq Hasan Zainab Salih Agee Bareen Shamsaldeen Tahir subhi R.M.Zeebaree ITM Department Technical College of AdministrativeDuhok Polytechnic UniversityDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq Accounting Department College of Adminstration and EconomicsUniversity of DuhokDuhokIraq Energy Eng.Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Solar energy will be a great alternative to fossil fuels since it is clean and *** photovoltaic(PV)mechanism produces sunbeams’green energy without noise or *** PV mechanism seems simple,seldom malfunctioning,and easy to *** energy productivity significantly contributes to smart grids through many small PV *** solar radiation(SR)prediction could substantially reduce the impact and cost relating to the advancement of solar *** recent times,several SR predictive mechanism was formulated,namely artificial neural network(ANN),autoregressive moving average,and support vector machine(SVM).Therefore,this article develops an optimal Modified Bidirectional Gated Recurrent Unit Driven Solar Radiation Prediction(OMBGRU-SRP)for energy *** presented OMBGRU-SRP technique mainly aims to accomplish an accurate and time SR prediction *** accomplish this,the presented OMBGRU-SRP technique performs data preprocessing to normalize the solar ***,the MBGRU model is derived using BGRU with an attention mechanism and skip *** last,the hyperparameter tuning of the MBGRU model is carried out using the satin bowerbird optimization(SBO)algorithm to attain maximum prediction with minimum error *** SBO algorithm is an intelligent optimization algorithm that simulates the breeding behavior of an adult male Satin Bowerbird in the *** experiments were conducted to demonstrate the enhanced SR prediction *** experimental values highlighted the supremacy of the OMBGRU-SRP algorithm over other existing models.

关键词： Solar radiation prediction deep learning parameter optimization energy management sustainability

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Application of advanced platelet-rich fibrin for through-and-through bony defect during endodontic surgery:Three case reports and review of the literature

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World Journal of Clinical Cases 2023年第17期11卷 4168-4178页

作者： Fahda N Algahtani Rahaf Almohareb Manar Aljamie Nouf Alkhunaini Shatha subhi ALHarthi Reem Barakat Department of Clinical Dental Sciences College of DentistryPrincess Nourah Bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Department of Endodontics Vision Colleges of Dentistry and NursingRiyadh 11671Saudi Arabia Department of Dental Specialized Medical Center HospitalsRiyadh 11671Saudi Arabia Department of Preventive Dental Sciences College of DentistryPrincess Nourah Bint Abdulrahman UniversityRiyadh 11671Saudi Arabia

BACKGROUND The use of advanced platelet-rich fibrin(A-PRF)membranes for guided bone and tissue regeneration in through-and-through defects after endodontic surgery was explored in three *** SUMMARY Herein,three patients presented to the endodontic clinic suffering from apical periodontitis,associated with large bone resorption and related to previously endodontically treated *** surgery was indicated in these cases and the osteotomy site was covered by A-PRF ***-beam computed tomography(CBCT)was used to assess the cases before and after the *** Four months post-surgery,the recall CBCT scan showed complete obliteration of the osteotomy with newly formed bone.A-PRF membrane showed promising results and was an advantageous addition to surgical endodontic treatment.

关键词： Cone-beam computed tomography Endodontic Periapical disease Plateletrich fibrin Surgery Tunnel defect Alveolar bone loss Case report

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Prevalence of Charles Bonnet syndrome in low vision:a systematic review and meta-analysis

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Annals of Eye Science 2022年第2期7卷 80-92页

作者： Yousif subhi Mads Assenholt Nielsen Daniel Andrew Richard Scott Lars Morten Holm Amardeep Singh Department of Ophthalmology RigshospitaletGlostrupDenmark Department of Clinical Research University of Southern DenmarkOdenseDenmark Faculty of Health and Medical Sciences University of CopenhagenKøbenhavnDenmark Department of Ophthalmology Waikato District Health BoardHamiltonNew Zealand

Background:Charles Bonnet syndrome(CBS)is characterized by vivid lifelike visual hallucinations and is typically seen in individuals with visual *** this systematic review,we summarize current knowledge on the prevalence of CBS in patients with low ***:We searched 11 literature databases on 21 April 2021 for studies on the prevalence of CBS in low vision *** protocol was registered in the PROSPERO database(***42021255021).Eligible studies were defined as those on a population of low vision patients wherein the prevalence of CBS was evaluated(without any further restriction on the method for diagnosis of CBS).No restriction was enforced on study design,but we expected observational cross-sectional studies due to the nature of our research *** authors independently extracted data and evaluated risk of bias of individual studies using the Agency for Healthcare Research and Quality checklist for cross-sectional *** underwent qualitative review in the text and quantitatively in a prevalence meta-analysis using the random-effects *** analysis was made to evaluate the robustness of the summary ***:We identified 11 studies,which summarized data on 4,521 individuals with visual *** of CBS was based on screening questions or interviews,which in positive cases often was explored in more detail with follow-up questions or *** studies either had normal mental state as a participant eligibility criterion or as a part of the diagnosis of *** pooled prevalence of CBS in low vision patients aged≥40 years was 19.7%(95%CI:13.8%to 26.4%).The sensitivity analysis showed certain robustness in the summary prevalence estimate wherein prevalence estimates ranged from 16.9%to 22.5%.Conclusions:CBS is a prevalent condition in patients with low vision at a rate of approximately one in five *** that an estimated 239 million individuals have moderate visual im

关键词： Charles Bonnet syndrome(CBS) visual hallucinations low vision

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Spotted Hyena Optimizer Driven Deep Learning-Based Drug-Drug Interaction Prediction in Big Data Environment

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Computer Systems Science & Engineering 2023年第9期46卷 3831-3845页

作者： Mohammed Jasim Mohammed Jasim Shakir Fattah Kak Zainab Salih Ageed subhi R.M.Zeebaree Engineering College Al-Kitab UniversityKirkukIraq Information Technology Department Technical College of Informatics-AkreDuhok Polytechnic UniversityDuhokIraq Computer Science Department College of ScienceNawroz UniversityDuhokIraq Energy Engineering Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq

Nowadays,smart healthcare and biomedical research have marked a substantial growth rate in terms of their presence in the literature,computational approaches,and discoveries,owing to which a massive quantity of experimental datasets was published and generated(Big Data)for describing and validating such ***-drug interaction(DDI)significantly contributed to drug administration and *** continues as the main obstacle in offering inexpensive and safe *** normally happens for patients with extensive medication,leading them to take many drugs *** may cause side effects,either mild or severe health *** reduced victims’quality of life and increased hospital healthcare expenses by increasing their recovery *** efforts were made to formulate new methods for DDI prediction to overcome this *** this aspect,this study designs a new Spotted Hyena Optimizer Driven Deep Learning based Drug-Drug Interaction Prediction(SHODL-DDIP)model in a big data *** the presented SHODL-DDIP technique,the relativity and characteristics of the drugs can be identified from different sources for *** input data is preprocessed at the primary level to improve its ***,the salp swarm optimization algorithm(SSO)is used to select *** this study,the deep belief network(DBN)model is exploited to predict the DDI *** SHO algorithm is involved in improvising the DBN model’s predictive outcomes,showing the novelty of the *** experimental result analysis of the SHODL-DDIP technique is tested using drug databases,and the results signified the improvements of the SHODLDDIP technique over other recent models in terms of different performance measures.

关键词： Drug-drug interaction deep learning spotted hyena optimization feature selection classification

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