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Sacrificial piles as a countermeasure against local scour around underwater pipelines

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Water Science and Engineering 2024年第2期17卷 187-196页

作者： Forough Raeisi Seyed mohammad ali Zomorodiann Masih Zolghadr Hazi mohammad Azamathulla Department of Water Engineering Shiraz UniversityShiraz ***Iran Department of Water Sciences Engineering Jahrom UniversityJahrom ***Iran Department of Civil and Environmental Engineering The University of the West IndiesSt.Augustine CampusTrinidad 331310Republic of Trinidad and Tobago

Local scour around pipelines crossing rivers or in marine environments is a significant concern.It can lead to failure of the pipelines resulting in environmental side effects and economic losses.This study developed an experimental method to reduce local scour around pipelines with a steady flow of clear water by installing cylindrical and cubical sacrificial piles.Three sizes of sacrificial piles were examined in a linear arrangement.Sacrificial piles were installed on the upstream side of the pipeline at three distances.Maximum scour depth reduction rates below the pipeline were computed.The results showed that sacrificial piles could protect a pipeline from local scour.A portion of scoured sediment around the sacrificial piles was deposited beneath the pipeline.This sediment accumulation reduced the scour depth beneath the pipeline.Analysis of the experimental results demonstrated that the size of piles(d),the spacing between piles,and the distance between the pipe and piles(Xp)were the variables that reduced the maximum scour beneath the pipeline with a diameter of D.For the piles with d=0.40D and 0.64D,X_(p)=4OD was the optimal distance to install a group of piles,and cubical piles could mitigate scour more effectively than cylindrical piles under similar conditions.For the piles with d=D,the greatest reduction in scour depth was achieved at X_(p)=50D with any desired spacings between piles,and cylindrical piles in this dimension could protect the pipeline against scour more effectively than cubical piles.

关键词： Clear water River crossing pipeline Local scour Self-burial process Sediment transport

Green tea catechins inhibit microglial activation which prevents the development of neurological disorders

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Neural Regeneration Research 2020年第10期15卷 1792-1798页

作者： Tahereh Farkhondeh ali mohammad pourbagher-shahri Milad Ashrafizadeh Silvia Llorens Folgado ali Rajabpour-Sanati mohammad Reza Khazdair Saeed Samarghandian Cardiovascular Diseases Research Center Birjand University of Medical SciencesBirjandIran Faculty of Medicine Birjand University of Medical SciencesBirjandIran Department of Basic Science Faculty of Veterinary MedicineUniversity of TabrizTabrizIran Department of Medical Sciences Faculty of Medicine of AlbaceteCentro Regional de Investigaciones Biomedicas(CRIB)University of Castilla-La ManchaAlbaceteSpain Healthy Ageing Research Center Neyshabur University of Medical SciencesNeyshaburIran Department of Basic Medical Sciences Neyshabur University of Medical SciencesNeyshaburIran

The over-activated microglial cells induce neuroinflammation which has the main role in neurological disorders.The over-activated microglia can disturb neuronal function by releasing inflammatory mediators leading to neuronal dysfunctions and death.Thus,inhibition of over-activated microglia may be an effective therapeutic approach for modulating neuroinflammation.Experimental studies have indicated anti-neuroinflammatory effects of flavonoids such as green tea catechins.The current research was aimed to review the effect of green tea catechins in inhibiting microglial cells,inflammatory cascades,and subsequent neurological diseases.

关键词： catechins green tea microglia neuroinflammation neurological disease

An Improved Binary Quantum-based Avian Navigation Optimizer Algorithm to Select Effective Feature Subset from Medical Data:A COVID-19 Case Study

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Journal of Bionic Engineering 2024年第1期21卷 426-446页

作者： ali Fatahi mohammad H.Nadimi-Shahraki Hoda Zamani Faculty of Computer Engineering Najafabad BranchIslamic Azad UniversityNajafabad ***Iran Big Data Research Center Najafabad BranchIslamic Azad UniversityNajafabad ***Iran

Feature Subset Selection(FSS)is an NP-hard problem to remove redundant and irrelevant features particularly from medical data,and it can be effectively addressed by metaheuristic algorithms.However,existing binary versions of metaheuristic algorithms have issues with convergence and lack an effective binarization method,resulting in suboptimal solutions that hinder diagnosis and prediction accuracy.This paper aims to propose an Improved Binary Quantum-based Avian Navigation Optimizer Algorithm(IBQANA)for FSS in medical data preprocessing to address the suboptimal solutions arising from binary versions of metaheuristic algorithms.The proposed IBQANA’s contributions include the Hybrid Binary Operator(HBO)and the Distance-based Binary Search Strategy(DBSS).HBO is designed to convert continuous values into binary solutions,even for values outside the[0,1]range,ensuring accurate binary mapping.On the other hand,DBSS is a two-phase search strategy that enhances the performance of inferior search agents and accelerates convergence.By combining exploration and exploitation phases based on an adaptive probability function,DBSS effectively avoids local optima.The effectiveness of applying HBO is compared with five transfer function families and thresholding on 12 medical datasets,with feature numbers ranging from 8 to 10,509.IBQANA's effectiveness is evaluated regarding the accuracy,fitness,and selected features and compared with seven binary metaheuristic algorithms.Furthermore,IBQANA is utilized to detect COVID-19.The results reveal that the proposed IBQANA outperforms all comparative algorithms on COVID-19 and 11 other medical datasets.The proposed method presents a promising solution to the FSS problem in medical data preprocessing.

关键词： Feature subset selection Optimization Binary metaheuristic algorithms Bioinspired Machine learning Medical datasets

Development of anti-corrosive coating on AZ31 Mg alloy modified by MOF/LDH/PEO hybrids

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Journal of Magnesium and Alloys 2024年第2期12卷 586-607页

作者： Muhammad ali Khan Ananda Repycha Safira mohammad Aadil Mosab Kaseem Corrosion and Electrochemistry Laboratory Department of Nanotechnology and Advanced Materials EngineeringSejong UniversitySeoul 05006Republic of Korea

The self-assembly of hybrid inorganic-organic materials on stationary platforms plays a critical role in improving their structural stability and wide usability.In this work,a novel two-step hydrothermal approach is proposed for synthesizing stable and advanced hybrid coatings on metal-oxide platforms through the surface modification of layered double hydroxide(LDH)films using novel metal-organic frameworks(MOFs).Initially,Mg-Al LDH nanocontainers,grown on a magnesium oxide layer produced through plasma electrolytic oxidation(PEO)of AZ31 Mg alloy substrate,were intercalated with cobalt via an oxidation route,providing the metallic coordination center for the MOF formation.In the subsequent step,a pioneering technique is introduced,utilizing tryptophan as the organic linker for the first time at a pH of 10.The self-assembly of cobalt-tryptophan complex,driven by the strong bonding between electrophilic sites of monomers and nucleophilic sites,facilitated the formation of a MOF network having a cloud-like structure on the surface of MgAl LDH's film.The resulting MOF-LDH encapsulation containers demonstrate exceptional electrochemical stability when exposed to a 3.5 wt.%NaCl solution,surpassing the performance of PEO and pure LDH coatings.This enhanced stability is attributed to the development of a dense top layer and a stable composition within the self-assembled MOF,effectively sealing flaws and preventing the infiltration of corrosive ions into the underlying metallic substrate.The formation mechanism of MOFs on LDH galleries is investigated using density functional theory calculations.

关键词： Mg alloy Layered double hydroxide Metal-organic frameworks Corrosion DFT

Stratigraphy of the Alveolina elliptica group from the Middle Eocene of Iran:Calibration with calcareous nannofossils biozones and description of Alveolina ozcani n. sp.

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Journal of Palaeogeography 2024年第1期13卷 54-79页

作者： Mehdi Hadi Lorenzo Consorti ali Bahrami mohammad Parandavar Saeed Khorramdel Department of Geology Faculty of SciencesUniversity of IsfahanIsfahanIran Institute of Marine Sciences(ISMAR-CNR) Area Science ParkBasovizza34149 TriesteItaly National Iranian Oil Company Exploration DirectorateSheikh Bahaei SquareTehranIran Department of Geology Faculty of ScienceFerdowsi University of MashhadMashhadIran

Precise taxonomy and the chronostratigraphic calibration of the Middle Eocene Alveolina from Central Iran is here undertaken from the Chah-Talkh section of the southern Sabzevar region(Central Iran). We have identified Alveolina kieli, Alveolina stercusmuris and Alveolina nuttalli along with the new species Alveolina ozcani n. sp. that we include into the Alveolina elliptica group. We have also found Nummulites uroniensis, Nummulites obesus and Nummulites cf. verneuili and associated calcareous nannofossils that look reliable to make thoughtful correlations with the Shallow Benthic Zones(SBZ). The foraminiferal biostratigraphy suggests an assignment to the upper part of the lower Lutetian-lower part of the middle Lutetian,SBZ13(Middle Eocene), further strengthened through the identification of the calcareous nannofossil NP14b-NP15b or CNE8-CNE10 biozones, providing a solid correlation with the global stratigraphic standards.

关键词： Alveolina Calcareous nannofossil Central neo-tethys Central Iran Middle Eocene Biostratigraphy

MoBShield:A Novel XML Approach for Securing Mobile Banking

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Computers, Materials & Continua 2024年第5期79卷 2123-2149页

作者： Saeed Seraj ali Safaa Sadiq OmprakashKaiwartya mohammad Aljaidi Alexandros Konios Mohammed ali Mohammed Abazeed Department of Computer Science Nottingham Trent UniversityClifton LaneNottinghamNG118NSUK Department of Computer Science Faculty of Information TechnologyZarqa UniversityZarqa13110Jordan Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Mobile banking security has witnessed significant R&D attention from both financial institutions and academia.This is due to the growing number of mobile baking applications and their reachability and usefulness to society.However,these applications are also attractive prey for cybercriminals,who use a variety of malware to steal personal banking information.Related literature in mobile banking security requiresmany permissions that are not necessary for the application’s intended security functionality.In this context,this paper presents a novel efficient permission identification approach for securing mobile banking(MoBShield)to detect and prevent malware.A permission-based dataset is generated for mobile banking malware detection that consists large number of malicious adware apps and benign apps to use as training datasets.The dataset is generated from 1650 malicious banking apps of the Canadian Institute of Cybersecurity,University of New Brunswick and benign apps from Google Play.A machine learning algorithm is used to determine whether amobile banking application ismalicious based on its permission requests.Further,an eXplainable machine learning(XML)approach is developed to improve trust by explaining the reasoning behind the algorithm’s behaviour.Performance evaluation tests that the approach can effectively and practically identify mobile banking malware with high precision and reduced false positives.Specifically,the adapted artificial neural networks(ANN),convolutional neural networks(CNN)and XML approaches achieve a higher accuracy of 99.7%and the adapted deep neural networks(DNN)approach achieves 99.6%accuracy in comparison with the state-of-the-art approaches.These promising results position the proposed approach as a potential tool for real-world scenarios,offering a robustmeans of identifying and thwarting malware inmobile-based banking applications.Consequently,MoBShield has the potential to significantly enhance the security and trustworthiness of mobile banking platforms,mitigating the risks p

关键词： Security malware detection deep learning convolutional neural networks deep neural networks

Robust design of sliding mode control for airship trajectory tracking with uncertainty and disturbance estimation

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Journal of Systems Engineering and Electronics 2024年第1期35卷 242-258页

作者： WASIM Muhammad ali Ahsan CHOUDHRY mohammad Ahmad SHAIKH Inam Ul Hasan SALEEM Faisal Department of Aeronautics and Astronautics Engineering Institute of Space TechnologyIslamabad 44000Pakistan Department of Electrical Engineering University of Engineering and TechnologyTaxila 47080Pakistan Department of Measurements and Control Systems Silesian University of TechnologyGliwice 44-101Poland The Joint Doctoral School Silesian University of TechnologyGliwice 44-100Poland

The robotic airship can provide a promising aerostatic platform for many potential applications.These applications require a precise autonomous trajectory tracking control for airship.Airship has a nonlinear and uncertain dynamics.It is prone to wind disturbances that offer a challenge for a trajectory tracking control design.This paper addresses the airship trajectory tracking problem having time varying reference path.A lumped parameter estimation approach under model uncertainties and wind disturbances is opted against distributed parameters.It uses extended Kalman filter(EKF)for uncertainty and disturbance estimation.The estimated parameters are used by sliding mode controller(SMC)for ultimate control of airship trajectory tracking.This comprehensive algorithm,EKF based SMC(ESMC),is used as a robust solution to track airship trajectory.The proposed estimator provides the estimates of wind disturbances as well as model uncertainty due to the mass matrix variations and aerodynamic model inaccuracies.The stability and convergence of the proposed method are investigated using the Lyapunov stability analysis.The simulation results show that the proposed method efficiently tracks the desired trajectory.The method solves the stability,convergence,and chattering problem of SMC under model uncertainties and wind disturbances.

关键词： airship chattering extended Kalman filter(EKF) model uncertainties estimation sliding mode controller(SMC)

Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1167-1202页

作者： Samina Amin Muhammad ali Zeb Hani Alshahrani Mohammed Hamdi mohammad Alsulami Asadullah Shaikh Institute of Computing Kohat University of Science and TechnologyKohat26000Pakistan Department of Computer Science College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Information System College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic outbreaks.This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance.Since,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by SM.This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic outbreaks.DL has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation results.In recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM analysis.This paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM analysis.Finally,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

关键词： Social media epidemic machine learning deep learning health informatics pandemic

The global,prevalence,and risk factors of postoperative fever after percutaneous nephrolithotomy:A systematic review and meta-analysis

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Asian Journal of Urology 2024年第2期11卷 253-260页

作者： Reza Falahatkar Siavash Falahatkar mohammad Amin Khajavi Gaskarei Masoomeh Afzalipoor ali Mojtahedi Neda aligolighasemabadi Ahmad Deilami Samaneh Mirzaei Dahka mohammad-Hossein Keivanlou alireza Jafari Urology Research Center Guilan University of Medical SciencesGuilanRashtIran Department of Surgery University of SaskatchewanSaskatoonCanada Microbiology Department School of MedicineGuilan University of Medical SciencesRashtIran Department of Internal Medicine School of MedicineGuilan University of Medical SiencesRashtIran School of Nursing and Midwifery Guilan University of Medical SciencesGuilanRashtIran

Objective:This study aimed to explore the global,prevalence,and risk factors of fever after percutaneous nephrolithotomy(PCNL)by conducting a systematic review and meta-analysis.Methods:The high-sensitivity searching was conducted without time limitation until December 30,2020 in Web of Sciences,Scopus,and PubMed based on inclusion and exclusion criteria.Results:The prevalence rates of fever and sepsis among patient undergoing PCNL were estimated 9.5%(95%confidence interval[CI]:9.3%-9.7%),and 4.5%(95%CI:4.2%-4.8%),respectively.Nephrostomy tube was used in 9.96%(95%CI:9.94%-9.97%)of patients.The mean preoperative white blood cells of patients were 6.401×109/L;18.3%and 4.55%of patients were considered as the positive urinary culture and pyuria,respectively.About 20.4%of patients suffered from residual stones.The odds ratios(ORs)of fever in patients who suffering from diabetes mellitus,hydronephrosis,staghorn stones,and blood transfusion were 4.62(95%CI:2.95-7.26),1.04(95%CI:0.81-1.34),2.57(95%CI:0.93-7.11),and 2.65(95%CI:1.62-4.35),respectively.Patients who underwent PCNL in prone position were more likely to develop fever(OR:1.23;95%CI:0.75-2.00)than patients in supine position.Conclusion:The current study showed that patients who suffer from diabetes mellitus,hydronephrosis,staghorn stones,nephrostomy tube or double-J stent,blood transfusion,and also patients who underwent PCNL in prone position surgery are more likely to develop a postoperative fever after PCNL.

关键词： Percutaneous nephrolithotomy Fever Hydronephrosis Diabetes Meta-analysis