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Expression levels ofβcatenin and galectin-3 in meningioma and their effect on brain invasion and recurrence:a tissue microarray study

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Cancer Biology & Medicine 2017年第3期14卷 319-326页

作者： Rehab Allah ahmed abdelhadi M Shebl Hany Onsy Habashy Department of Pathology Mansoura UniversityFaculty of MedicineMansoura DK 35516Egypt

Objective:Meningiomas are neoplasms that arise from the meninges of the central nervous system(CNS).They constitute about25.6%of CNS tumors diagnosed in *** morphological variants of meningiomas display aggressive behavior,leading to brain-invasive growth *** meningiomas are usually treated by complete surgical excision,the risk of postoperative recurrence ***,additional biomarkers for predicting aggressive behavior must be *** study aims to explore the clinical and biological relevance of the protein expression levels ofβ-catenin and galectine-3 in meningioma and to understand the pathobiology of this ***:This retrospective study was carried out on 153 cases of meningioma by using tissue microarrays and immunohistochemistry forβ-catenin and ***:Highβ-catenin expression was significantly associated with transitional and meningiotheliomatous meningiomas,low tumor grade,low recurrence rate,and low incidence of brain ***,high galectin-3 expression was associated with brain invasion,recurrence,high tumor grade,and tumor *** regression analysis indicated that among all variables included in the model,β-catenin and galactin-3 expression levels were significant predictors of tumor recurrence(P<0.001).Conclusions:Galectin-3 andβ-catenin are involved in meningioma recurrence but not in brain *** molecules could be important potential therapeutic targets and predictors for meningiomas.

关键词： Immunohistochemistry meningioma recurrence brain invasion galectin-3 and β-catenin

Classification COVID-19 Based on Enhancement X-Ray Images and Low Complexity Model

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Computers, Materials & Continua 2022年第7期72卷 561-576页

作者： Aymen saad Israa SKamil ahmed Alsayat ahmed Elaraby Department of Information Technology Technical College of ManagementKufaAl Furat Alawsat UniversityIraq Department of Medical Laboratory Techniques Al-Mustaqbal University CollegeHillaIraq Department of Computer Science College of Computer and Information SciencesJouf UniversitySaudi Arabia Department of Computer Science Faculty of Computers and InformationSouth Valley UniversityQenaEgypt

COVID-19 has been considered one of the recent epidemics that occurred at the last of 2019 and the beginning of 2020 that world *** spread of COVID-19 requires a fast technique for diagnosis to make the appropriate decision for the treatment.X-ray images are one of the most classifiable images that are used widely in diagnosing patients’data depending on radiographs due to their structures and tissues that could be *** Neural Networks(CNN)is the most accurate classification technique used to diagnose COVID-19 because of the ability to use a different number of convolutional layers and its high classification *** using CNNs techniques requires a large number of images to learn and obtain satisfactory *** this paper,we used SqueezNet with a modified output layer to classify X-ray images into three groups:COVID-19,normal,and *** this study,we propose a deep learning method with enhance the features of X-ray images collected from Kaggle,Figshare to distinguish between COVID-19,Normal,and Pneumonia *** this regard,several techniques were used on the selected image samples which are Unsharp filter,Histogram equal,and Complement image to produce another view of the *** Squeeze Net CNN model has been tested in two scenarios using the 13,437 X-ray images that include 4479 for each type(COVID-19,Normal and Pneumonia).In the first scenario,the model has been tested without any enhancement on the *** achieved an accuracy of 91%.But,in the second scenario,the model was tested using the same previous images after being improved by several techniques and the performance was high at approximately 95%.The conclusion of this study is the used model gives higher accuracy results for enhanced images compared with the accuracy results for the original images.A comparison of the outcomes demonstrated the effectiveness of ourDLmethod for classifying COVID-19 based on enhanced X-ray images.

关键词： COVID-19 X-ray image enhancement classification CNN SqueezNet model

Oilfield produced water treatment in internal-loop airlift reactor using electrocoagulation/flotation technique

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Chinese Journal of Chemical Engineering 2018年第4期26卷 879-885页

作者： saad H.Ammar ahmed S.Akbar Department of Chemical engineering AL-Nahrain University

Oilfield produced water is large quantities of salty water trapped in underground formations and subsisted under high temperatures and pressures that are brought to the surface along with oil during production. Produced water(PW) contains a lot of pollutants such as hydrocarbons and metals, this water must be treated before disposal. Therefore, different techniques are being used to treat produced water. Electrocoagulation is an efficient treatment technique involving the dissolution of anodes and formation of electro-coagulants, while the simultaneous generation of H_2 bubbles at the cathode leads to the pollutant removal by flotation. Electrocoagulation(EC)method is one of the most promising and widely used processes to treat oilfield produced water. In the present work, a conventional internal-loop(draught tube) airlift reactor was utilized as electrocoagulation/flotation cell for PW treatment by inserting two aluminum electrodes in the riser section of the airlift reactor. The EC airlift reactor was operated in a batch mode for the liquid phase. Different experimental parameters were studied on the oil and turbidity removal efficiencies such as current density, initial pH, electrocoagulation time, and air *** experimental results showed that mixing of the oil droplets in the PW was accomplished using only the liquid recirculation resulted by H_2 microbubbles generated by EC process which enhanced the oil removal. The experimental results further showed that the EC time required achieving ≥ 90% oil removal efficiency decreases from 46 to 15 min when operating current density increases from 6.8 to 45.5 mA·cm^(-2). This reactor type was found to be highly efficient and less energy consuming compared to conventional existing electrochemical cells which used mechanical agitation.

关键词： Produced water Wastewater treatment Electrocoagulation/flotation Internal loop Airlift reactor

Nature-inspired Hybrid Optimization Algorithms for Load Flow Analysis of Islanded Microgrids

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Journal of Modern Power Systems and Clean Energy 2020年第6期8卷 1250-1258页

作者： saad Mohammad Abdullah Ashik ahmed Quazi Nafees Ul Islam the Department of Electrical and Electronic Engineering Islamic University of TechnologyBoard BazarGazipur 1704Bangladesh

Load flow analysis is a significant tool for proper planning,operation,and dynamic analysis of a power system that provides the steady-state values of voltage magnitudes and angles at the fundamental ***,due to the absence of a slack bus in an islanded microgrid,modified load flow algorithms should be adopted considering the system frequency as one of the solution *** paper proposes the application of nature-inspired hybrid optimization algorithms for solving the load flow problem of islanded *** nature-inspired algorithms such as genetic algorithm(GA),differential evolution(DE),flower pollination algorithm(FPA),and grasshopper optimization algorithm(GOA)are separately merged with imperialistic competitive algorithm(ICA)to form four hybrid algorithms named as ICGA,ICDE,ICFPA,and *** of these algorithms are tested on the 6-bus test system and the modified IEEE 37-bus test system.A comparison among the proposed algorithms is carried out in terms of statistical analysis conducted using SPSS statistics *** the statistical analysis,it is identified that on an average,ICDE takes less number of iterations and consequently needs less execution time compared with other algorithms in solving the load flow problem of islanded microgrids.

关键词： Nature-inspired hybrid algorithm global optimization islanded microgrid load flow analysis

Improving the Transmission Security of Vein Images Using a Bezier Curve and Long Short-Term Memory

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Computers, Materials & Continua 2024年第6期79卷 4825-4844页

作者： ahmed H.Alhadethi Ikram Smaoui ahmed Fakhfakh saad M.Darwish Computer Science and School of Electronics and Telecommunications University of SfaxSfax3029Tunisia LETI Laboratory University of SfaxSfax3029Tunisia Digital Research Center of Sfax Technopark of SfaxSfax3029Tunisia Department of Information Technology Institute of Graduate Studies and ResearchAlexandria UniversityAlexandriaEgypt

The act of transmitting photos via the Internet has become a routine and significant *** the security measures to safeguard these images from counterfeiting and modifications is a critical domain that can still be further *** study presents a system that employs a range of approaches and algorithms to ensure the security of transmitted venous *** main goal of this work is to create a very effective system for compressing individual biometrics in order to improve the overall accuracy and security of digital photographs by means of image *** paper introduces a content-based image authentication mechanism that is suitable for usage across an untrusted network and resistant to data loss during *** employing scale attributes and a key-dependent parametric Long Short-Term Memory(LSTM),it is feasible to improve the resilience of digital signatures against image deterioration and strengthen their security against malicious ***,the successful implementation of transmitting biometric data in a compressed format over a wireless network has been *** applications involving the transmission and sharing of images across a *** suggested technique utilizes the scalability of a structural digital signature to attain a satisfactory equilibrium between security and picture *** effective adaptive compression strategy was created to lengthen the overall lifetime of the network by sharing the processing of *** scheme ensures a large reduction in computational and energy requirements while minimizing image quality *** approach employs multi-scale characteristics to improve the resistance of signatures against image *** proposed system attained a Gaussian noise value of 98%and a rotation accuracy surpassing 99%.

关键词： Image transmission image compression text hiding Bezier curve Histogram of Oriented Gradients(HOG) LSTM image enhancement Gaussian noise rotation

Dynamical analysis and anti-synchronization of a new 6D model with self-excited attractors

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Applied Mathematics(A Journal of Chinese Universities) 2023年第1期38卷 27-43页

作者： saad Fawzi Al-Azzawi ahmed S.Al-Obeidi Department of Mathematics College of Computer Science and MathematicsUniversity of MosulMosul 41002Iraq

A novel 6D dissipative model with an unstable equilibrium point is introduced *** of the dynamic characteristics of the proposed model were explored via analyses and numerical simulations including critical points,stability,Lyapunov exponents,time phase portraits,and circuit ***,anti-synchronization phenomena were implemented on the new ***,the error dynamics is ***,four different controllers are adopted to stabilize this error relying on the nonlinear control technique with two main ways:linearization and Lyapunov stability *** comparison with previous works,the present controllers realize anti-synchronization based on another method/linearization ***,a comparison between the two ways was *** simulation results show the effectiveness and accuracy of the first analytical strategy.

关键词： 6D hyperchaotic system self-excited attractor anti-synchronization Lyapunov stability theory

Fusarium pseudograminearum and *** affect the root system architecture of bread wheat

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The Crop Journal 2023年第1期11卷 316-321页

作者： ahmed saad Jack Christopher Anke Martin Stephen McDonald Cassandra Percy Centre for Crop Health University of Southern QueenslandToowoombaQLD 4350Australia University of Queensland Queensland Alliance for Agriculture and Food Innovation(QAAFI)Leslie Research FacilityToowoombaQLD 4350Australia

Yield losses of bread wheat due to crown rot can be more severe when drought conditions occur during the grain-filling *** architecture characteristics are important for soil exploration and belowground resource acquisition and are essential for adaptation to water-limited *** such as root angle,length and density have been strongly associated with acquisition efficiency and contribute to yield stability of the *** impact of crown rot pathogens on wheat root architecture is poorly *** examined differences in root angle,length and number,as well as dry root weight of the crown rot-susceptible bread wheat cultivar,Livingston inoculated with one of two crown rot pathogens Fusarium culmorum or Fusarium pseudograminearum in a transparent-sided root observation *** adverse impacts on plant health and growth were revealed by visual discolouration of the leaf sheaths;fresh and dry shoot weight;leaf area of the oldest and the youngest fully expanded leaf and leaf *** of most recorded root system measurements were reduced when inoculated with either *** or *** contrast,root angle was increased in the presence of *** but was not significantly changed by *** development of whiteheads and grain losses in bread wheat caused by crown rot have previously been associated with blockages of the vascular *** method employed here was able to identify differences in the pathogen impacts on roots,which were not detected using previous *** research indicates that in the presence of *** and *** infection,not only reductions in the size and biomass of the shoot system but also changes in the length,biomass and architecture of the root system could play an important role in yield loss.

关键词： Crown rot Root characteristics Livingston Wheat

A Review on Primary and Secondary Controls of Inverter-interfaced Microgrid

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Journal of Modern Power Systems and Clean Energy 2021年第5期9卷 969-985页

作者： Kafeel ahmed Mehdi Seyedmahmoudian saad Mekhilef N.M.Mubarak Alex Stojcevski School of Software and Electrical Engineering Swinburne University of TechnologyVIC 3122VictoriaAustralia Power Electronics and Renewable Energy Research Laboratory Department of Electrical EngineeringUniversity of Malaya50603 Kuala LumpurMalaysia Department of Chemical Engineering Faculty of Engineering and ScienceCurtin University of Technology98009 SarawakMalaysia

The demand of electricity and environmental issues associated with conventional power generation plants are increasing *** technology has transformed the conventional power system through the integration of distributed generation(DG).With the help of modern power electronic technology,the conventional power system is able to support the integration of DGs based on renewable energy sources(RESs).The systematic combination of DGs with energy storage system forms a microgrid(MG),which can operate in islanded mode or grid-connected *** intermittent nature of RES and varying load pose substantial obstacles such as voltage and frequency instability,and the unreliability of *** feeder impedances and non-linear loads are considered as present challenges in MG *** control has been useful in undertaking solutions to these *** paper covers the deep insight of different control methods applied at the primary and secondary control levels in hierarchical *** primary control,the classification based on droop and non-droop controls is *** virtual synchronization machine(VSM)based control method is *** and frequency restoration control and economical operations at decentralized and centralized secondary control are analyzed in *** on the existing literature,critical discussion on MG control and future trends are also presented to provide future research perspectives.

关键词： Distributed generation(DG) hierarchical control droop control non-droop control inverter

Real and Altered Fingerprint Classification Based on Various Features and Classifiers

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Computers, Materials & Continua 2023年第1期74卷 327-340页

作者： Saif saad Hameed Ismail Taha ahmed Omar Munthir Al Okashi College of Computer Sciences and Information Technology University of AnbarAnbarIraq

Biometric recognition refers to the identification of individuals through their unique behavioral features(e.g.,fingerprint,face,and iris).We need distinguishing characteristics to identify people,such as fingerprints,which are world-renowned as the most reliablemethod to identify *** recognition of fingerprints has become a standard procedure in forensics,and different techniques are available for this *** current techniques lack interest in image enhancement and rely on high-dimensional features to generate classification ***,we proposed an effective fingerprint classification method for classifying the fingerprint image as authentic or altered since criminals and hackers routinely change their fingerprints to generate fake *** order to improve fingerprint classification accuracy,our proposed method used the most effective texture features and *** Analysis(DCA)and Gaussian Discriminant Analysis(GDA)are employed as classifiers,along with Histogram of Oriented Gradient(HOG)and Segmentation-based Feature Texture Analysis(SFTA)feature vectors as *** performance of the classifiers is determined by assessing a range of feature sets,and the most accurate results are *** proposed method is tested using a Sokoto Coventry Fingerprint Dataset(SOCOFing).The SOCOFing project includes 6,000 fingerprint images collected from 600 African people whose fingerprints were taken ten *** distinct degrees of obliteration,central rotation,and z-cut have been performed to obtain synthetically altered replicas of the genuine *** proposal achieved massive success with a classification accuracy reaching 99%.The experimental results indicate that the proposed method for fingerprint classification is feasible and *** experiments also showed that the proposed SFTA-based GDA method outperformed state-of-art approaches in feature dimension and classification accuracy.

关键词： Fingerprint classification HOG SFTA discriminant analysis(DCA)classifier gaussian discriminant analysis(GDA)classifier SOCOFing