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A mouse model of weight-drop closed head injury:emphasis on cognitive and neurological deficiency

Neural Regeneration Research 2016年第4期11卷 630-635页

作者： Igor Khalin Nor Laili Azua Jamari Nadiawati Bt Abdul Razak Zubaidah Bt Hasain Mohd Asri bin Mohd Nor Mohd Hakimi bin ahmad Zainudin Ainsah Bt Omar Renad Alyautdin Faculty of Medicine and Defence Health National Defence University of MalaysiaKem Sungai BesiKuala LumpurMalaysia Chemistry Department Centre for Defence Foundation StudiesNational Defence University of MalaysiaKem Sungai BesiKuala LumpurMalaysia Department of Civil Engineering Faculty of EngineeringNational Defence University of MalaysiaKem Sungai BesiKuala LumpurMalaysia Centre for Research and Innovation Management National Defence University of MalaysiaKem Sungai BesiKuala LumpurMalaysia Scientific Centre for Expertise of Medical Application Products Petrovsky BlvdMoscowRussia

Traumatic brain injury（TBI） is a leading cause of death and disability in individuals *** a clinically relevant TBI model in small-sized animals remains fairly *** good screening of potential therapeutics,which are effective in the treatment of TBI,animal models of TBI should be established and *** this study,we established mouse models of closed head injury using the Shohami weight-drop method with some modifications concerning cognitive deficiency assessment and provided a detailed description of the severe TBI animal *** found that 250 g falling weight from 2 cm height produced severe closed head injury in C57BL/6 male *** disorders in mice with severe closed head injury could be detected using passive avoidance test on day 7 after *** from this study indicate that weight-drop injury animal models are suitable for further screening of brain neuroprotectants and potentially are similar to those seen in human TBI.

关键词： nerve regeneration traumatic brain injury neurological severity score passive avoidance weightdrop injury model C57BL/6 mice neural regeneration

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KOH@NaX酸碱性调控及对甲苯甲醇侧链烷基化性能的影响

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石油学报（石油加工） 2022年第4期38卷 771-780页

作者：刘钰华王斌温月丽 ahmad Faraz 刘文龙黄伟太原理工大学省部共建煤基能源清洁高效利用国家重点实验室山西太原030024 太原理工大学环境科学工程学院山西太原030024 太原理工大学山西太原理工煤转化技术工程有限公司山西太原030024

通过固-液连续混加法制备了KOH改性的NaX系列催化剂,并采用X射线衍射(XRD)、N_(2)物理吸附-脱附、傅里叶红外光谱(FT-IR)、扫描电子显微镜(SEM)、X射线能谱(SEM-EDS-Mapping)、CO_(2)-TPD、NH_(3)-TPD等表征手段对其进行分析,考察KOH改... 详细信息

通过固-液连续混加法制备了KOH改性的NaX系列催化剂,并采用X射线衍射(XRD)、N_(2)物理吸附-脱附、傅里叶红外光谱(FT-IR)、扫描电子显微镜(SEM)、X射线能谱(SEM-EDS-Mapping)、CO_(2)-TPD、NH_(3)-TPD等表征手段对其进行分析,考察KOH改性的NaX系列催化剂在甲苯甲醇侧链烷基化反应中的催化性能。结果表明:KOH的均匀负载有利于增加NaX分子筛上强碱性位,同时抑制了中强酸性位;显著提高了甲醇转化率和苯乙烯与乙苯的总选择性,同时降低了甲烷和二甲苯的总选择性。在常压、425℃、质量空速1.0 h^(-1)、甲苯/甲醇摩尔比为5的条件下,当KOH的负载质量分数为7%时,甲醇转化率、苯乙烯和乙苯的总收率分别为99.81%和97.82%。通过对甲苯甲醇侧链烷基化反应机理的研究发现,甲醇在强碱性位和中强酸性位上存在一对竞争反应:甲醇在强碱性位上脱氢生成甲醛,进而与被活化的甲苯上的甲基反应生成苯乙烯和乙苯;而在中强酸性位上甲醇既可以加氢生成甲烷,也可以与甲苯发生苯环烷基化反应生成二甲苯。

关键词：酸碱性调控甲苯甲醇侧链烷基化 KOH@NaX催化剂乙苯选择性

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A Component Selection Framework of Cohesion and Coupling Metrics

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Computer Systems Science & Engineering 2023年第1期44卷 351-365页

作者： M.Iyyappan Arvind Kumar Sultan ahmad Sudan Jha Bader Alouffi Abdullah Alharbi Department of Computer Science and Engineering SRM UniversityDelhi-NCRSonepat131029India Department of Computer Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharj11942Saudi Arabia School of Sciences Christ(Deemed to be University)Delhi-NCRGhaziabad201003India Department of Computer Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

Component-based software engineering is concerned with the develop-ment of software that can satisfy the customer prerequisites through reuse or inde-pendent *** and cohesion measurements are primarily used to analyse the better software design quality,increase the reliability and reduced system software *** complexity measurement of cohesion and coupling component to analyze the relationship between the component *** this paper,proposed the component selection framework of Hexa-oval optimization algorithm for selecting the suitable components from the *** measures the interface density modules of coupling and cohesion in a modular software *** cohesion measurement has been taken into two parameters for analyz-ing the result of complexity,with the help of low cohesion and high *** coupling measures between the component of inside parameters and outside *** process of coupling and cohesion,the measured values were used for the average calculation of components *** paper measures the complexity of direct and indirect interaction among the component as well as the proposed algorithm selecting the optimal component for the *** better result is observed for high cohesion and low coupling in compo-nent-based software engineering.

关键词： Component-based software system coupling metric cohesion metric complexity component interface module density

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Chest Radiographs Based Pneumothorax Detection Using Federated Learning

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Computer Systems Science & Engineering 2023年第11期47卷 1775-1791页

作者： ahmad Almadhor Arfat ahmad Khan Chitapong Wechtaisong Iqra Yousaf Natalia Kryvinska Usman Tariq Haithem Ben Chikha Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakaka72388Saudi Arabia Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand School of Telecommunication Engineering Suranaree University of TechnologyNakhon Ratchasima30000Thailand Department of Computer Science and Software Engineering International Islamic UniversityIslamabadPakistan Information Systems Department Faculty of ManagementComenius University in BratislavaOdbojárovBratislava440Slovakia Prince Sattam bin Abdulaziz University AlKharjSaudi Arabia

Pneumothorax is a thoracic condition that occurs when a person’s lungs collapse,causing air to enter the pleural cavity,the area close to the lungs and chest *** most persistent disease,as well as one that necessitates particular patient care and the privacy of their health *** radiologists find it challenging to diagnose pneumothorax due to the variations in *** learning-based techniques are commonly employed to solve image categorization and segmentation ***,it is challenging to employ it in the medical field due to privacy issues and a lack of *** address this issue,a federated learning framework based on an Xception neural network model is proposed in this *** pneumothorax medical image dataset is obtained from the Kaggle *** preprocessing is performed on the used dataset to convert unstructured data into structured information to improve the model’s ***-max normalization technique is used to normalize the data,and the features are extracted from chest Xray *** dataset converts into two windows to make two clients for local model *** neural network model is trained on the dataset individually and aggregates model updates from two clients on the server *** decrease the over-fitting effect,every client analyses the results three *** 1 performed better in round 2 with a 79.0%accuracy,and client 2 performed better in round 2 with a 77.0%*** experimental result shows the effectiveness of the federated learning-based technique on a deep neural network,reaching a 79.28%accuracy while also providing privacy to the patient’s data.

关键词： Privacy preserving pneumothorax disease federated learning chest x-ray images healthcare machine learning deep learning

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Exact Analysis of Non-Linear Fractionalized Jeffrey Fluid.A Novel Approach of Atangana-Baleanu Fractional Model

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Computers, Materials & Continua 2020年第12期65卷 2033-2047页

作者： Saqib Murtaza Farhad Ali Aamina Nadeem ahmad Sheikh Ilyas Khan Kottakkaran Sooppy Nisar Department of Mathematics City University of Science and Information TechnologyPeshawarKhyber PakhtnkhwaPakistan Computational Analysis Research Group Ton Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Mathematics and Statistics Ton Duc Thang UniversityHo Chi Minh CityVietnam Department of Mathematics College of Science Al-ZulfiMajmah UniversityAl-Majmah11952Saudi Arabia Department of Mathematics College of Arts and SciencesPrince Sattam Bin Abdulaziz UniversityWadi AldawaserSaudi Arabia

It is a very difficult task for the researchers to find the exact solutions to mathematical problems that contain non-linear terms in the ***,this article aims to investigate the viscous dissipation(VD)effect on the fractional model of Jeffrey fluid over a heated vertical flat plate that suddenly moves in its own *** on the Atangana-Baleanu operator,the fractional model is developed from the fractional constitutive *** is responsible for the non-linear behavior in the *** taking the Laplace and Fourier sine transforms,exact expressions have been obtained for momentum and energy *** influence of relative parameters on fluid flow and temperature distribution is shown *** special cases,and for the sake of correctness,the corresponding results for second-grade fluid and Newtonian viscous fluid are also *** is interesting to note that fractional parameterαprovides more than one line as compared to the classical *** effect represents the memory effect in the fluid which is not possible to elaborate by the classical *** is also worth noting that the temperature profile of the generalized Jeffrey fluid rises for higher values of Eckert number which is due to the enthalpy difference of the boundary layer.

关键词： Viscous dissipation atangana-baleanu fractional derivative laplace transform fourier sine transform

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Longtail Tuna (Thunnus tonggol) Consumption Frequency in Terengganu, Malaysia

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Open Journal of Marine Science 2020年第3期10卷 141-148页

作者： Norhazirah Abdul Aziz Adiana Ghazali Kamaruzzaman bin Yunus Zurahanim Fasha Annual Ali ahmad Ong Meng Chuan Faculty of Science and Marine Environment Universiti Malaysia Terengganu Kuala Nerus Malaysia Kulliyyah of Science International Islamic University Malaysia Kuantan Malaysia Environmental Health Research Centre Institute for Medical Research Kuala Lumpur Malaysia Marine Fishery Resources Development and Management Department Southeast Asian Fisheries Development Center (SEAFDEC) Chendering Malaysia Institute of Oceanography and Environment Universiti Malaysia Terengganu Kuala Nerus Malaysia Ocean Pollution and Ecotoxicology (OPEC) Research Group Universiti Malaysia Terengganu Kuala Nerus Malaysia

In Terengganu, Longtail tuna or Thunnus tonggol is one of the most popular marine fishes landed by fishermen and has a high demand among customers. This species often served with a unique local delicacy called Nasi Dagang and Ikan Singgang, one of the favourite meals during breakfast by local communities. Since people have always consumed this species, therefore this study aims to identify the consumption rate of this species among Terengganu people. Specifically, this survey data obtained from 124 respondents, ages ranged from 15 to 60 years old from five districts in Terengganu, including Besut, Kuala Nerus, Kuala Terengganu, Hulu Terengganu, and Kemaman. Generally, the estimated amount of this species consumption is 239.7 g per person and 1.83 times per week. From the formula calculated, the amount of this species consumed by one person is 437.4 g/person/week. This value can use to calculate the permissible tolerable weekly intake (PTWI) to estimate the intake of pollutants, such as heavy metals in the human body.

关键词： Thunnus tonggol Consumption South China Sea PTWI

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Using Capsule Networks for Android Malware Detection Through Orientation-Based Features

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Computers, Materials & Continua 2022年第3期70卷 5345-5362页

作者： Sohail Khan Mohammad Nauman Suleiman Ali Alsaif Toqeer Ali Syed Hassan ahmad Eleraky Deanship of Preparatory Year and Supporting Studies Computer Science DepartmentImam Abdulrahman Bin Faisal UniversityDammamSaudi Arabia National University of Computer and Emerging Sciences Pakistan Department of Computer Science Islamic University of MedinaMedinaSaudi Arabia

Mobile phones are an essential part of modern *** two popular mobile phone platforms,Android and iPhone Operating System(iOS),have an immense impact on the lives of millions of *** these two,Android currently boasts more than 84%market ***,any personal data put on it are at great risk if not properly *** the other hand,more than a million pieces of malware have been reported on Android in just 2021 till *** and mitigating all this malware is extremely difficult for any set of human *** to this reason,machine learning-and specifically deep learning-has been utilized in the recent past to resolve this ***,deep learning models have primarily been designed for image *** this line of research has shown promising results,it has been difficult to really understand what the features extracted by deep learning models are in the domain of ***,due to the translation invariance property of popular models based on ConvolutionalNeural Network(CNN),the true potential of deep learning for malware analysis is yet to be *** resolve this issue,we envision the use of Capsule Networks(CapsNets),a state-of-the-art model in deep *** argue that since CapsNets are orientation-based in terms of images,they can potentially be used to capture spatial relationships between different features at different locations within a sequence of *** design a deep learning-based architecture that efficiently and effectively handles very large scale malware datasets to detect Androidmalware without resorting to very deep *** leads tomuch faster detection as well as increased *** achieve state-of-the-art F1 score of 0.987 with an FPR of just 0.002 for three very large,real-world malware *** code is made available as open source and can be used to further enhance our work with minimal effort.

关键词： Malware security Android deep learning capsule networks

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A Novel Capability of Object Identification and Recognition Based on Integrated mWMM

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Computers, Materials & Continua 2023年第4期75卷 959-976页

作者： MZeeshan Sarwar Mohammed Hamad Alatiyyah ahmad Jalal Mohammad Shorfuzzaman Nawal Alsufyani Jeongmin Park Department of Computer Science Air UniversityIslamabadPakistan Department of Computer Science College of Sciences and Humanities in AflajPrince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-siGyeonggi-do15073Korea

In the last decade,there has been remarkable progress in the areas of object detection and recognition due to high-quality color images along with their depth maps provided by RGB-D *** enable artificially intelligent machines to easily detect and recognize objects and make real-time decisions according to the given *** cues can improve the quality of object detection and *** main purpose of this research study to find an optimized way of object detection and identification we propose techniques of object detection using two RGB-D *** proposed methodology extracts image normally from depth maps and then performs clustering using the Modified Watson Mixture Model(mWMM).mWMM is challenging to handle when the quality of the image is not ***,the proposed RGB-D-based system uses depth cues for segmentation with the help of *** it extracts multiple features from the segmented *** selected features are fed to the Artificial Neural Network(ANN)and Convolutional Neural Network(CNN)for detecting *** achieved 92.13%of mean accuracy over NYUv1 dataset and 90.00%of mean accuracy for the Redweb_v1 ***,their results are compared and the proposed model with CNN outperforms other state-of-the-art *** proposed architecture can be used in autonomous cars,traffic monitoring,and sports scenes.

关键词： Artificial intelligence convolutional neural network depth images interactive-object detection machine learning

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First United Arab Emirates consensus on diagnosis and management of inflammatory bowel diseases:A 2020 Delphi consensus

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World Journal of Gastroenterology 2020年第43期26卷 6710-6769页

作者： Maryam Alkhatry ahmad Al-Rifai Vito Annese Filippos Georgopoulos ahmad N Jazzar Ahmed M Khassouan Zaher Koutoubi Rahul Nathwani Mazen S Taha Jimmy K Limdi Gastroenterology and Endoscopy Department Ibrahim Bin Hamad Obaid Allah HospitalMinistry of Health and PreventionRas Al KhaimanUnited Arab Emirates Department of Gastroenterology Sheikh Shakbout Medical CityAbu DhabiUnited Arab Emirates Department of Gastroenterology Valiant ClinicDubaiUnited Arab Emirates Department of Gastroenterology and Endoscopy American HospitalDubaiUnited Arab Emirates Gastroenterology and Endoscopy Unit Al Zahra HospitalDubaiUnited Arab Emirates Gastroenterology Division Sheikh Khalifa Medical CityAbu DhabiUnited Arab Emirates Digestive Disease Unit Rashid HospitalDubaiUnited Arab Emirates Digestive Disease Institute Cleveland ClinicAbu DhabiUnited Arab Emirates Department of Gastroenterology Mediclinic City HospitalDubaiUnited Arab Emirates Gastroenterology and Hepatology Tawam HospitalAl AinUnited Arab Emirates Department of Gastroenterology The Pennine Acute Hospitals NHS TrustManchester Academic Health SciencesUniversity of ManchesterManchester M85RBUnited Kingdom

Ulcerative colitis and Crohn’s disease are the main entities of inflammatory bowel disease characterized by chronic remittent inflammation of the gastrointestinal *** incidence and prevalence are on the rise worldwide,and the heterogeneity between patients and within individuals over time is *** progressive advance in our understanding of the etiopathogenesis coupled with an unprecedented increase in therapeutic options have changed the management towards evidence-based interventions by clinicians with *** guideline was stimulated and supported by the Emirates Gastroenterology and Hepatology Society following a systematic review and a Delphi consensus process that provided evidence-and expert opinion-based *** up-to-date guidance is provided regarding diagnosis,evaluation of disease severity,appropriate and timely use of different investigations,choice of appropriate therapy for induction and remission phase according to disease severity,and management of main complications.

关键词： Ulcerative colitis Crohn’s disease Infliximab Adalimumab Vedolizumab Ustekinumab Tofacitinib

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CD-FL:Cataract Images Based Disease Detection Using Federated Learning

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Computer Systems Science & Engineering 2023年第11期47卷 1733-1750页

作者： Arfat ahmad Khan Shtwai Alsubai Chitapong Wechtaisong ahmad Almadhor Natalia Kryvinska Abdullah Al Hejaili Uzma Ghulam Mohammad Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia School of Telecommunication Engineering Suranaree University of TechnologyNakhon Ratchasima30000Thailand Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakaka72388Saudi Arabia Information Systems Department Faculty of ManagementComenius University in BratislavaOdbojárovBratislava440Slovakia Faculty of Computers&Information Technology Computer Science DepartmentUniversity of TabukTabuk71491Saudi Arabia Department of Computer Science and Software Engineering International Islamic UniversityIslamabad44000Pakistan

A cataract is one of the most significant eye problems worldwide that does not immediately impair vision and progressively worsens over *** cataract prediction based on various imaging technologies has been addressed recently,such as smartphone apps used for remote health monitoring and eye *** recent years,advances in diagnosis,prediction,and clinical decision support using Artificial Intelligence(AI)in medicine and ophthalmology have been *** to privacy concerns,a lack of data makes applying artificial intelligence models in the medical field *** address this issue,a federated learning framework named CDFL based on a VGG16 deep neural network model is proposed in this *** study collects data from the Ocular Disease Intelligent Recognition(ODIR)database containing 5,000 patient *** significant features are extracted and normalized using the min-max normalization *** the federated learning-based technique,the VGG16 model is trained on the dataset individually after receiving model updates from two *** transferring the attributes to the global model,the suggested method trains the local *** global model subsequently improves the technique after integrating the new *** client analyses the results in three rounds to decrease the over-fitting *** experimental result shows the effectiveness of the federated learning-based technique on a Deep Neural Network(DNN),reaching a 95.28%accuracy while also providing privacy to the patient’s *** experiment demonstrated that the suggested federated learning model outperforms other traditional methods,achieving client 1 accuracy of 95.0%and client 2 accuracy of 96.0%.

关键词： Privacy-preserving cataract disease federated learning fundus images healthcare smartphone applications machine learning

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