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| 1 | Glutathione (GSH) improves sperm quality and testicular morphology in streptozotocin-induced diabetic mice显示文摘Diabetes mellitus(DM)is known to cause reproductive impairment.In men,it has been linked to altered sperm quality and testicular damage.Oxidative stress(OS)plays a pivotal role in the development of DM complications.Glutathione(GSH)is a part of a nonenzymatic antioxidant defense system that protects lipid,protein,and nucleic acids from oxidative damage.However,the protective effects of exogenous GSH on the male reproductive system have not been comprehensively examined.This study determined the impact of GSH supplementation in ameliorating the adverse effect of type 1 DM on sperm quality and the seminiferous tubules of diabetic C57BL/6NTac mice.GSH at the doses of 15 mg kg^(-1)and 30 mg kg^(-1)was given intraperitoneally to mice weekly for 6 consecutive weeks.The mice were then weighed,euthanized,and had their reproductive organs excised.The diabetic(D Group)showed significant impairment of sperm quality and testicular histology compared with the nondiabetic(ND Group).Diameters of the seminiferous lumen in diabetic mice treated with 15 mg kg^(-1) GSH(DGSH15)were decreased compared with the D Group.Sperm motility was also significantly increased in the DGSH15 Group.Improvement in testicular morphology might be an early indication of the protective roles played by the exogenous GSH in protecting sperm quality from effects of untreated type 1 DM or diabetic complications.Further investigation using different doses and different routes of GSH is necessary to confirm this suggestion. | Fathiah Abdullah Mohamed Noor Khan Nor-Ashikin Renu Agarwal Yuhaniza Shafinie Kamsani Mastura Abd Malek Nor Salmah Bakar Aqila-Akmal Mohammad Kamal Mimi-Sophia Sarbandi Nor-Shahida Abdul Rahman Nurul Huda Musa | 2021 | Asian Journal of Andrology2021，23，3： | 3 |
| 2 | Smart-Fragile Authentication Scheme for Robust Detecting of Tampering Attacks on English Text显示文摘Content authentication,integrity verification,and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication technology.In this paper,a text zero-watermarking approach known as Smart-Fragile Approach based on Soft Computing and Digital Watermarking(SFASCDW)is proposed for content authentication and tampering detection of English text.A first-level order of alphanumeric mechanism,based on hidden Markov model,is integrated with digital zero-watermarking techniques to improve the watermark robustness of the proposed approach.The researcher uses the first-level order and alphanumeric mechanism of Markov model as a soft computing technique to analyze English text.Moreover,he extracts the features of the interrelationship among the contexts of the text,utilizes the extracted features as watermark information,and validates it later with the studied English text to detect any tampering.SFASCDW has been implemented using PHP with VS code IDE.The robustness,effectiveness,and applicability of SFASCDW are proved with experiments involving four datasets of various lengths in random locations using the three common attacks,namely insertion,reorder,and deletion.The SFASCDW was found to be effective and could be applicable in detecting any possible tampering. | Mohammad Alamgeer Fahd N.Al-Wesabi Huda G.Iskandar Imran Khan Nadhem Nemri Mohammad Medani Mohammed Abdullah Al-Hagery Ali Mohammed Al-Sharafi | 2022 | Computers, Materials & Continua2022，，5： | 0 |
| 3 | IoMT-Enabled Fusion-Based Model to Predict Posture for Smart Healthcare Systems显示文摘Smart healthcare applications depend on data from wearable sensors(WSs)mounted on a patient’s body for frequent monitoring information.Healthcare systems depend on multi-level data for detecting illnesses and consequently delivering correct diagnostic measures.The collection of WS data and integration of that data for diagnostic purposes is a difficult task.This paper proposes an Errorless Data Fusion(EDF)approach to increase posture recognition accuracy.The research is based on a case study in a health organization.With the rise in smart healthcare systems,WS data fusion necessitates careful attention to provide sensitive analysis of the recognized illness.As a result,it is dependent on WS inputs and performs group analysis at a similar rate to improve diagnostic efficiency.Sensor breakdowns,the constant time factor,aggregation,and analysis results all cause errors,resulting in rejected or incorrect suggestions.This paper resolves this problem by using EDF,which is related to patient situational discovery through healthcare surveillance systems.Features of WS data are examined extensively using active and iterative learning to identify errors in specific postures.This technology improves position detection accuracy,analysis duration,and error rate,regardless of user movements.Wearable devices play a critical role in the management and treatment of patients.They can ensure that patients are provided with a unique treatment for their medical needs.This paper discusses the EDF technique for optimizing posture identification accuracy through multi-feature analysis.At first,the patients’walking patterns are tracked at various time intervals.The characteristics are then evaluated in relation to the stored data using a random forest classifier. | Taher M.Ghazal Mohammad Kamrul Hasan Siti Norul Huda Abdullah Khairul Azmi Abubakkar Mohammed A.M.Afifi | 2022 | Computers, Materials & Continua2022，，5： | 0 |
| 4 | A Parallel Hybrid Testing Technique for Tri-Programming Model-Based Software Systems显示文摘Recently,researchers have shown increasing interest in combining more than one programming model into systems running on high performance computing systems(HPCs)to achieve exascale by applying parallelism at multiple levels.Combining different programming paradigms,such as Message Passing Interface(MPI),Open Multiple Processing(OpenMP),and Open Accelerators(OpenACC),can increase computation speed and improve performance.During the integration of multiple models,the probability of runtime errors increases,making their detection difficult,especially in the absence of testing techniques that can detect these errors.Numerous studies have been conducted to identify these errors,but no technique exists for detecting errors in three-level programming models.Despite the increasing research that integrates the three programming models,MPI,OpenMP,and OpenACC,a testing technology to detect runtime errors,such as deadlocks and race conditions,which can arise from this integration has not been developed.Therefore,this paper begins with a definition and explanation of runtime errors that result fromintegrating the three programming models that compilers cannot detect.For the first time,this paper presents a classification of operational errors that can result from the integration of the three models.This paper also proposes a parallel hybrid testing technique for detecting runtime errors in systems built in the C++programming language that uses the triple programming models MPI,OpenMP,and OpenACC.This hybrid technology combines static technology and dynamic technology,given that some errors can be detected using static techniques,whereas others can be detected using dynamic technology.The hybrid technique can detect more errors because it combines two distinct technologies.The proposed static technology detects a wide range of error types in less time,whereas a portion of the potential errors that may or may not occur depending on the 4502 CMC,2023,vol.74,no.2 operating environment are left to the dynamic technology,which completes the validation. | Huda Basloom Mohamed Dahab Abdullah Saad AL-Ghamdi Fathy Eassa Ahmed Mohammed Alghamdi Seif Haridi | 2023 | Computers, Materials & Continua2023，，2： | 0 |
| 5 | Optimized synthesis and photovoltaic performance of TiO_2 nanoparticles for dye-sensitized solar cell显示文摘This paper presents response surface methodology(RSM) as an efficient approach for modeling and optimizingTiO_2 nanoparticles preparation via co-precipitation for dye-sensitized solar cell(DSSC) performance.Titanium(Ⅳ) bis-(acetylacetonate) di-isopropoxide(DIPBAT).isopropanol and water were used as precursor,solvent and co-solvent,respectively.Molar ratio of water,aging temperature and calcination temperature as preparation factors with main and interaction effects on particle characteristics and performances were investigated.Particle characteristics in terms of primary and secondary sizes,crystal orientation and morphology were determined by X-ray diffractometry(XRD) and scanning electron microscopy(SEM).Band gap energy and power conversion efficiency of DSSCs were used for performance studies.According to analysis of variance(ANOVA) in response surface methodology(RSM),all three independent parameters were statistically significant and the final model was accurate.The model predicted maximum power conversion efficiency(0.14%) under the optimal condition of molar ratio of DIPBAT-to-isopropanol-to-water of 1:10:500,aging temperature of 36℃ and calcination temperature of400℃.A second set of data was adopted to validate the model at optimal conditions and was found to be0.14±0.015%,which was very close to the predicted value.This study proves the reliability of the model in identifying the optimal condition for maximum performance. | Siti Nur Fadhilah Zainudin Masturah Markom Huda Abdullah Renata Adami Siti Masrinda Tasirin | 2013 | Particuology2013，11，6： | 0 |
| 6 | Text Extraction with Optimal Bi-LSTM显示文摘Text extraction from images using the traditional techniques of image collecting,and pattern recognition using machine learning consume time due to the amount of extracted features from the images.Deep Neural Networks introduce effective solutions to extract text features from images using a few techniques and the ability to train large datasets of images with significant results.This study proposes using Dual Maxpooling and concatenating convolution Neural Networks(CNN)layers with the activation functions Relu and the Optimized Leaky Relu(OLRelu).The proposed method works by dividing the word image into slices that contain characters.Then pass them to deep learning layers to extract feature maps and reform the predicted words.Bidirectional Short Memory(BiLSTM)layers extractmore compelling features and link the time sequence fromforward and backward directions during the training phase.The Connectionist Temporal Classification(CTC)function calcifies the training and validation loss rates.In addition to decoding the extracted feature to reform characters again and linking them according to their time sequence.The proposed model performance is evaluated using training and validation loss errors on the Mjsynth and Integrated Argument Mining Tasks(IAM)datasets.The result of IAM was 2.09%for the average loss errors with the proposed dualMaxpooling and OLRelu.In the Mjsynth dataset,the best validation loss rate shrunk to 2.2%by applying concatenating CNN layers,and Relu. | Bahera H.Nayef Siti Norul Huda Sheikh Abdullah Rossilawati Sulaiman Ashwaq Mukred Saeed | 2023 | Computers, Materials & Continua2023，76，9： | 0 |
| 7 | Novel Adaptive Binarization Method for Degraded Document Images显示文摘Achieving a good recognition rate for degraded document images is difficult as degraded document images suffer from low contrast,bleedthrough,and nonuniform illumination effects.Unlike the existing baseline thresholding techniques that use fixed thresholds and windows,the proposed method introduces a concept for obtaining dynamic windows according to the image content to achieve better binarization.To enhance a low-contrast image,we proposed a new mean histogram stretching method for suppressing noisy pixels in the background and,simultaneously,increasing pixel contrast at edges or near edges,which results in an enhanced image.For the enhanced image,we propose a new method for deriving adaptive local thresholds for dynamic windows.The dynamic window is derived by exploiting the advantage of Otsu thresholding.To assess the performance of the proposed method,we have used standard databases,namely,document image binarization contest(DIBCO),for experimentation.The comparative study on well-known existing methods indicates that the proposed method outperforms the existing methods in terms of quality and recognition rate. | Siti Norul Huda Sheikh Abdullah Saad M.Ismail Mohammad Kamrul Hasan Palaiahnakote Shivakumara | 2021 | Computers, Materials & Continua2021，，6： | 0 |
| 8 | Review:Development of lanthanum strontium cobalt ferrite composite cathodes for intermediate-to low-temperature solid oxide fuel cells显示文摘Solid oxide fuel cells(SOFCs) offer high energy conversion,low noise,low pollutant emission,and low processing cost.Despite many advantages,SOFCs face a major challenge in competing with other types of fuel cells because of their high operating temperature.The necessity to reduce the operational temperature of SOFCs has led to the development of research into the materials and fabrication technology of fuel cells.The use of composite cathodes significantly reduces the cathode polarization resistance and expands the triple phase boundary area available for oxygen reduction.Powder preparation and composite cathode fabrication also affect the overall performance of composite cathodes and fuel cells.Among many types of cathode materials,lanthanum-based materials such as lanthanum strontium cobalt ferrite(La1-xSrxCo1-yFeyO3- have recently been discovered to offer great compatibility with ceria-based electrolytes in performing as composite cathode materials for intermediate-to low-temperature SOFCs(IT-LTSOFCs).This paper reviews various ceria-based composite cathodes for IT-LTSOFCs and focuses on the aspects of progress and challenges in materials technology. | Nurul Akidah BAHARUDDIN Hamimah Abd RAHMAN Andanastuti MUCHTAR Abu Bakar SULONG Huda ABDULLAH | 2013 | Journal of Zhejiang University-Science A(Applied Physics & Engineering)2013，14，1： | 0 |
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