Displaying all 18 publications

Abstract:
Sort:
  1. Optimisation of n-channel trench power MOSFET using 2k factorial design method
    Nur Syakimah Ismail, Ibrahim Ahmad, Hafizah Husain
    Sains Malaysiana, 2009;38.
    The main objective of this research is to optimize the trench depth, trench width, epitaxial resistivity and epitaxial thickness in trench power MOSFET so as to obtain high breakdown voltage but low on-resistance. Optimisation of these parameters are based on 2k factorial design method for achieving specific on-resistance 0.1 mΩcm2 and blocking voltage higher than 30 V. ATHENA and ATLAS software from Silvaco Int. were used for fabrication simulation and device electrical characterisation. The results obtained were, the optimisation value for trench width was 1.25 μm, trench depth was 1.25 μm, epitaxial thickness was 4.75 μm and epitaxial resistivity was 0.32 Ωcm. The predictive value of breakdown voltage was 39.41 V and significant to factors trench depth, epitaxial thickness and epitaxial resistivity. The predictive value for on-resistance was 0.105 mΩcm2 with significant to factors trench depth, epitaxial thickness and epitaxial resistivity. In conclusion, 2k factorial design method is successfully utilised in optimizing n-channel trench power MOSFET.
  2. Performance characterization of schottky tunneling graphene field effect transistor at 60 nm gate length
    Noor Faizah Zainul Abidin, Ibrahim Ahmad, Pin JK, Menon PS
    Sains Malaysiana, 2017;46:1089-1095.
    A planar Graphene Field-Effect Transistor GFET performance with 60 nm gate length was evaluated in discovering new material to meet the relentless demand for higher performance-power saving features. The ATHENA and ATLAS modules of SILVACO TCAD simulation tool was employed to virtually design and assess the electrical performance of GFET. The developed model was benchmarked with the established results obtained from the DESSIS simulator model by using the same graphene channel’s parameters and simulated at fixed threshold voltage of 0.4V. The GFET was also analyzed and ranked its performance for four different gate oxides which includes HfO2, Al2O3, TiO2, and Ta2O5. Compared to the benchmarked device, our GFET shows a competitive performance although it possesses a lower drive current (ION). However, the leakage current (IOFF), subthreshold swing (SS) and the device’s switching capability (ION/IOFF) are more superior than those of the benchmarked device, with an improvement of 99%, 48.3% and 99.36%, respectively. The with different gate dielectrics were also proven to possess a lower IOFF, competitive ION, smaller SS and better switching capability compared to the established DESSISS model. The graphene parameters in this experiment can be utilized for further optimization of GFET with smaller gate lengths.
  3. Kesan teknik pengaktifan bermangkin berbeza terhadap prestasi terma penyebar haba cip balikan
    Lim V, Nowshad Amin, Foong C, Ibrahim Ahmad, Azami Zaharim, Rozaidi Rasid, et al.
    Sains Malaysiana, 2011;40.
    Kertas ini membentangkan kesan dua teknik pengaktifan bermangkin yang berbeza terhadap prestasi terma bagi penyebar haba cip balikan. Penyaduran nikel tanpa elektrik digunakan sebagai salah satu teknik saduran kerana ia boleh membentuk satu lapisan nikel yang ketebalannya seragam ke atas substrat kuprum. Proses pengaktifan bermangkin perlu dilakukan dahulu untuk mengenapkan sesetengah atom nikel ke atas substrat kuprum, supaya enapan nikel mampu untuk memangkinkan proses penurunan yang seterusnya. Dua jenis teknik pengakitfan telah dikaji, iaitu pemulaan galvani dan penyaduran nipis nikel-kuprum. Ujian simpanan suhu tinggi telah dijalankan untuk mengkaji takat resapan antara logam bagi lapisan nikel and kuprum. Kemeresapan terma bagi penyebar haba telah dikaji dengan menggunakan peralatan Nano-flash. Keputusan yang diperolehi menunjukkan bahawa penyebar haba yang diproses dengan penyaduran nipis nikel-kuprum mempunyai nilai kemeresapan terma (35-65 mm2 s-1) yang lebih rendah berbanding dengan penyebar haba yang diproses dengan teknik pemulaan galvani (60-85 mm2 s-1). Selain daripada itu, kajian ini juga menemui ketebalan lapisan antara logam nikel-kuprum dalam penyebar haba ini bertambah daripada 0.2 μm pada keadaan asal kepada 0.55 μm selepas 168 jam simpanan suhu tinggi. Lapisan antara logam nikel-kuprum mempunyai kekonduksian terma yang lebih rendah berbanding dengan kuprum tulen, ini telah merendahkan kemeresapan terma bagi penyebar haba. Kesimpulannya, teknik pemulaan galvani meyediakan prestasi terma yang lebih baik untuk penyebar haba yang digunakan dalam pembungkusan semikonduktor.
  4. Fulltext Lung Ultrasonography for COVID-19 Patients in Out of Hospital Settings
    Abd Wahab M, Eddie EA, Ibrahim Ahmad UQA, Shafie H, Shaikh Abd Karim SB, Abdull Wahab SF
    J Ultrasound, 2022 Jan 15.
    PMID: 35032294 DOI: 10.1007/s40477-021-00609-4
    PURPOSE: The portability of a hand-held ultrasound allows the health care worker to conduct lung ultrasound in out-of-hospital setting. It is used as a tool to conduct staging and triaging for COVID-19 patients. This study evaluated the utilization of lung ultrasound in an out-of-hospital setting versus chest x-rays in detecting and staging of COVID-19 patients with pneumonia.

    METHODS: The study was conducted among COVID-19 subjects at an out-of-hospital setting whereby lung ultrasound was done and subsequently chest x-rays were taken after being admitted to the health care facilities. Lung ultrasound findings were reviewed by emergency physicians, while the chest x-rays were reviewed by radiologists. Radiologists were blinded by the patients' lung ultrasound findings and clinical conditions. The analysis of the agreement between the lung ultrasound findings and chest x-rays was conducted.

    RESULTS: A total of 261 subjects were recruited. LUS detected pulmonary infiltrative changes in more stage 3 COVID-19 subjects in comparison to chest x-rays. Multiple B-lines were the predominant findings at the right lower anterior, posterior and lateral zones. Interstitial consolidations and ground glass opacities were the predominant descriptive findings in chest x-rays. However, there was no agreement between lung ultrasound and chest x-ray findings in detecting COVID-19 pneumonia as the Cohen's Kappa coefficient was 0.08 (95% CI 0.06-0.22, p = 0.16).

    CONCLUSION: The diagnostic imaging and staging of COVID-19 patients using lung ultrasound in out-of-hospital settings showed LUS detected lung pleural disease more often than CXR for stage 3 COVID-19 patients.

  5. Fulltext Optimal battery sizing in photovoltaic based distributed generation using enhanced opposition-based firefly algorithm for voltage rise mitigation
    Wong LA, Shareef H, Mohamed A, Ibrahim AA
    ScientificWorldJournal, 2014;2014:752096.
    PMID: 25054184 DOI: 10.1155/2014/752096
    This paper presents the application of enhanced opposition-based firefly algorithm in obtaining the optimal battery energy storage systems (BESS) sizing in photovoltaic generation integrated radial distribution network in order to mitigate the voltage rise problem. Initially, the performance of the original firefly algorithm is enhanced by utilizing the opposition-based learning and introducing inertia weight. After evaluating the performance of the enhanced opposition-based firefly algorithm (EOFA) with fifteen benchmark functions, it is then adopted to determine the optimal size for BESS. Two optimization processes are conducted where the first optimization aims to obtain the optimal battery output power on hourly basis and the second optimization aims to obtain the optimal BESS capacity by considering the state of charge constraint of BESS. The effectiveness of the proposed method is validated by applying the algorithm to the 69-bus distribution system and by comparing the performance of EOFA with conventional firefly algorithm and gravitational search algorithm. Results show that EOFA has the best performance comparatively in terms of mitigating the voltage rise problem.
  6. The relationship between the demographic, personal, and social factors of Malaysian motorcyclists and risk taking behavior at signalized intersections
    Borhan MN, Ibrahim ANH, Aziz A, Yazid MRM
    Accid Anal Prev, 2018 Dec;121:94-100.
    PMID: 30237047 DOI: 10.1016/j.aap.2018.09.004
    In the context of road safety, risk-taking is undoubtedly one of the main contributory factors in road accidents. The actual forces which influence individuals to take such risks, nevertheless, are still not fully understood. To address this, this study was therefore conducted to investigate the relationship of the demographic, personal, and social factors of motorcyclists, with a specific focus on their risk-taking behavior at signalized intersections in Malaysia. This study adopted the quantitative method using cross-sectional questionnaire surveys and involved 251 respondents. The demographic factors were analyzed using the t-test and an ANOVA Scheffe Post-Hoc test, while the motorcyclists' personal and social characteristics were analyzed with multiple linear regression. The findings indicate that the individuals who were greater risk takers at signalized intersections were teenage motorcyclists (16-25 years old) who had finished their education before taking their high school diploma, and who also received a lower than average monthly income from private sector firms. The actual experience of accidents was also shown to be positively related to this risk-taking behavior. In addition, in term of personal and social factors, results showed that, for these individuals, there was a significant difference between the strength of peer influence and that of parental and spouse guidance. However, there was no significant difference in the risk-taking behavior of Malaysian motorcyclists riding at signalized intersections for the following factors: between genders, in terms of accident involvement, in terms of enforcement of traffic regulations, and prevention steps and confidence level after being involved in an accident.
  7. Fulltext Optimal Training Configurations of a CNN-LSTM-Based Tracker for a Fall Frame Detection System
    Mohamed NA, Zulkifley MA, Ibrahim AA, Aouache M
    Sensors (Basel), 2021 Sep 28;21(19).
    PMID: 34640803 DOI: 10.3390/s21196485
    In recent years, there has been an immense amount of research into fall event detection. Generally, a fall event is defined as a situation in which a person unintentionally drops down onto a lower surface. It is crucial to detect the occurrence of fall events as early as possible so that any severe fall consequences can be minimized. Nonetheless, a fall event is a sporadic incidence that occurs seldomly that is falsely detected due to a wide range of fall conditions and situations. Therefore, an automated fall frame detection system, which is referred to as the SmartConvFall is proposed to detect the exact fall frame in a video sequence. It is crucial to know the exact fall frame as it dictates the response time of the system to administer an early treatment to reduce the fall's negative consequences and related injuries. Henceforth, searching for the optimal training configurations is imperative to ensure the main goal of the SmartConvFall is achieved. The proposed SmartConvFall consists of two parts, which are object tracking and instantaneous fall frame detection modules that rely on deep learning representations. The first stage will track the object of interest using a fully convolutional neural network (CNN) tracker. Various training configurations such as optimizer, learning rate, mini-batch size, number of training samples, and region of interest are individually evaluated to determine the best configuration to produce the best tracker model. Meanwhile, the second module goal is to determine the exact instantaneous fall frame by modeling the continuous object trajectories using the Long Short-Term Memory (LSTM) network. Similarly, the LSTM model will undergo various training configurations that cover different types of features selection and the number of stacked layers. The exact instantaneous fall frame is determined using an assumption that a large movement difference with respect to the ground level along the vertical axis can be observed if a fall incident happened. The proposed SmartConvFall is a novel technique as most of the existing methods still relying on detection rather than the tracking module. The SmartConvFall outperforms the state-of-the-art trackers, namely TCNN and MDNET-N trackers, with the highest expected average overlap, robustness, and reliability metrics of 0.1619, 0.6323, and 0.7958, respectively. The SmartConvFall also managed to produce the lowest number of tracking failures with only 43 occasions. Moreover, a three-stack LSTM delivers the lowest mean error with approximately one second delay time in locating the exact instantaneous fall frame. Therefore, the proposed SmartConvFall has demonstrated its potential and suitability to be implemented for a real-time application that could help to avoid any crucial fall consequences such as death and internal bleeding if the early treatment can be administered.
  8. Fulltext Spatial distribution of malaria in Peninsular Malaysia from 2000 to 2009
    Alias H, Surin J, Mahmud R, Shafie A, Mohd Zin J, Mohamad Nor M, et al.
    Parasit Vectors, 2014;7:186.
    PMID: 24735583 DOI: 10.1186/1756-3305-7-186
    Malaria is still an endemic disease of public health importance in Malaysia. Populations at risk of contracting malaria includes indigenous people, traditional villagers, mobile ethnic groups and land scheme settlers, immigrants from malaria endemic countries as well as jungle workers and loggers. The predominant species are Plasmodium falciparum and P. vivax. An increasing number of P. knowlesi infections have also been encountered. The principal vectors in Peninsular Malaysia are Anopheles maculatus and An. cracens. This study aims to determine the changes in spatial distribution of malaria in Peninsular Malaysia from year 2000-2009.
  9. Fulltext Antioxidant, anticancer, apoptosis properties and chemical composition of black truffle Terfezia claveryi
    Dahham SS, Al-Rawi SS, Ibrahim AH, Abdul Majid AS, Abdul Majid AMS
    Saudi J Biol Sci, 2018 Dec;25(8):1524-1534.
    PMID: 30591773 DOI: 10.1016/j.sjbs.2016.01.031
    Desert truffles are seasonal and important edible fungi that grow wild in many countries around the world. Truffles are natural food sources that have significant compositions. In this work, the antioxidant, chemical composition, anticancer, and antiangiogenesis properties of the Terfezia claveryi truffle were investigated. Solvent extractions of the T. claveryi were evaluated for antioxidant activities using (DPPH, FRAP and ABTS methods). The extracts cytotoxicity on the cancer cell lines (HT29, MCF-7, PC3 and U-87 MG) was determined by MTT assay, while the anti-angiogenic efficacy was tested using ex-vivo assay. All extracts showed moderate anticancer activities against all cancer cells (p 
  10. Data mining of the essential causes of different types of fatal construction accidents
    Rafindadi AD, Shafiq N, Othman I, Ibrahim A, Aliyu MM, Mikić M, et al.
    Heliyon, 2023 Feb;9(2):e13389.
    PMID: 36761825 DOI: 10.1016/j.heliyon.2023.e13389
    Accident analysis is used to discover the causes of workplace injuries and devise methods for preventing them in the future. There has been little discussion in the previous studies of the specific elements contributing to deadly construction accidents. In contrast to previous studies, this study focuses on the causes of fatal construction accidents based on management factors, unsafe site conditions, and workers' unsafe actions. The association rule mining technique identifies the hidden patterns or knowledge between the root causes of fatal construction accidents, and one hundred meaningful association rules were extracted from the two hundred and fifty-three rules generated. It was discovered that many fatal construction accidents were caused by management factors, unsafe site circumstances, and risky worker behaviors. These analyses can be used to demonstrate plausible cause-and-effect correlations, assisting in building a safer working environment in the construction sector. The study findings can be used more efficiently to design effective inspection procedures and occupational safety initiatives. Finally, the proposed method should be tested in a broader range of construction situations and scenarios to ensure that it is as accurate as possible.
  11. Fulltext Automated Glaucoma Screening and Diagnosis Based on Retinal Fundus Images Using Deep Learning Approaches: A Comprehensive Review
    Zedan MJM, Zulkifley MA, Ibrahim AA, Moubark AM, Kamari NAM, Abdani SR
    Diagnostics (Basel), 2023 Jun 26;13(13).
    PMID: 37443574 DOI: 10.3390/diagnostics13132180
    Glaucoma is a chronic eye disease that may lead to permanent vision loss if it is not diagnosed and treated at an early stage. The disease originates from an irregular behavior in the drainage flow of the eye that eventually leads to an increase in intraocular pressure, which in the severe stage of the disease deteriorates the optic nerve head and leads to vision loss. Medical follow-ups to observe the retinal area are needed periodically by ophthalmologists, who require an extensive degree of skill and experience to interpret the results appropriately. To improve on this issue, algorithms based on deep learning techniques have been designed to screen and diagnose glaucoma based on retinal fundus image input and to analyze images of the optic nerve and retinal structures. Therefore, the objective of this paper is to provide a systematic analysis of 52 state-of-the-art relevant studies on the screening and diagnosis of glaucoma, which include a particular dataset used in the development of the algorithms, performance metrics, and modalities employed in each article. Furthermore, this review analyzes and evaluates the used methods and compares their strengths and weaknesses in an organized manner. It also explored a wide range of diagnostic procedures, such as image pre-processing, localization, classification, and segmentation. In conclusion, automated glaucoma diagnosis has shown considerable promise when deep learning algorithms are applied. Such algorithms could increase the accuracy and efficiency of glaucoma diagnosis in a better and faster manner.
  12. Fulltext Intelligent Bone Age Assessment: An Automated System to Detect a Bone Growth Problem Using Convolutional Neural Networks with Attention Mechanism
    Zulkifley MA, Mohamed NA, Abdani SR, Kamari NAM, Moubark AM, Ibrahim AA
    Diagnostics (Basel), 2021 Apr 24;11(5).
    PMID: 33923215 DOI: 10.3390/diagnostics11050765
    Skeletal bone age assessment using X-ray images is a standard clinical procedure to detect any anomaly in bone growth among kids and babies. The assessed bone age indicates the actual level of growth, whereby a large discrepancy between the assessed and chronological age might point to a growth disorder. Hence, skeletal bone age assessment is used to screen the possibility of growth abnormalities, genetic problems, and endocrine disorders. Usually, the manual screening is assessed through X-ray images of the non-dominant hand using the Greulich-Pyle (GP) or Tanner-Whitehouse (TW) approach. The GP uses a standard hand atlas, which will be the reference point to predict the bone age of a patient, while the TW uses a scoring mechanism to assess the bone age using several regions of interest information. However, both approaches are heavily dependent on individual domain knowledge and expertise, which is prone to high bias in inter and intra-observer results. Hence, an automated bone age assessment system, which is referred to as Attention-Xception Network (AXNet) is proposed to automatically predict the bone age accurately. The proposed AXNet consists of two parts, which are image normalization and bone age regression modules. The image normalization module will transform each X-ray image into a standardized form so that the regressor network can be trained using better input images. This module will first extract the hand region from the background, which is then rotated to an upright position using the angle calculated from the four key-points of interest. Then, the masked and rotated hand image will be aligned such that it will be positioned in the middle of the image. Both of the masked and rotated images will be obtained through existing state-of-the-art deep learning methods. The last module will then predict the bone age through the Attention-Xception network that incorporates multiple layers of spatial-attention mechanism to emphasize the important features for more accurate bone age prediction. From the experimental results, the proposed AXNet achieves the lowest mean absolute error and mean squared error of 7.699 months and 108.869 months2, respectively. Therefore, the proposed AXNet has demonstrated its potential for practical clinical use with an error of less than one year to assist the experts or radiologists in evaluating the bone age objectively.
  13. Fulltext Estimation of soil erodibility in Peninsular Malaysia: A case study using multiple linear regression and artificial neural networks
    Rehman MA, Abd Rahman N, Ibrahim ANH, Kamal NA, Ahmad A
    Heliyon, 2024 Apr 15;10(7):e28854.
    PMID: 38576554 DOI: 10.1016/j.heliyon.2024.e28854
    Soil erodibility (K) is an essential component in estimating soil loss indicating the soil's susceptibility to detach and transport. Data Computing and processing methods, such as artificial neural networks (ANNs) and multiple linear regression (MLR), have proven to be helpful in the development of predictive models for natural hazards. The present case study aims to assess the efficiency of MLR and ANN models to forecast soil erodibility in Peninsular Malaysia. A total of 103 samples were collected from various sites and K values were calculated using the Tew equation developed for Malaysian soil. From several extracted parameters, the outcomes of correlation and principal component analysis (PCA) revealed the influencing factors to be used in the development of ANN and MLR models. Based on the correlation and PCA results, two sets of influencing factors were employed to develop predictive models. Two MLR (MLR-1 and MLR-2) models and four neural networks (NN-1, NN-2, NN-3, and NN-4) optimized using Levenberg-Marquardt (LM) and scaled conjugate gradient (SCG) were developed and evaluated. The model performance validation was conducted using the coefficient of determination (R2), mean squared error (MSE), root mean squared error (RMSE), and Nash-Sutcliffe efficiency coefficient (NSE). The analysis showed that ANN models outperformed MLR models. The R2 values of 0.446 (MLR-1), 0.430 (MLR-2), 0.894 (NN-1), 0.855 (NN-2), 0.940 (NN-3), and 0.826 (NN-4); MSE values of 0.0000306 (MLR-1), 0.0000315 (MLR-2), 0.0000158 (NN-1), 0.0000261 (NN-2), 0.0000318 (NN-3), and 0.0000216 (NN-4) suggested the higher accuracy and lower modelling error of ANN models as compared with MLR. This study could provide an empirical basis and methodological support for K factor estimation in the region.
  14. Micro-anatomical changes in major blood vessel caused by dengue virus (serotype 2) infection
    Priya SP, Sakinah S, Ling MP, Chee HY, Higuchi A, Hamat RA, et al.
    Acta Trop, 2017 Jul;171:213-219.
    PMID: 28427958 DOI: 10.1016/j.actatropica.2017.04.010
    Dengue virus (DENV) has emerged as a major economic concern in developing countries, with 2.5 billion people believed to be at risk. Vascular endothelial cells (ECs) lining the circulatory system from heart to end vessels perform crucial functions in the human body, by aiding gas exchange in lungs, gaseous, nutritional and its waste exchange in all tissues, including the blood brain barrier, filtration of fluid in the glomeruli, neutrophil recruitment, hormone trafficking, as well as maintenance of blood vessel tone and hemostasis. These functions can be deregulated during DENV infection. In this study, BALB/c mice infected with DENV serotype 2 were analyzed histologically for changes in major blood vessels in response to DENV infection. In the uninfected mouse model, blood vessels showed normal architecture with intact endothelial monolayer, tunica media, and tunica adventitia. In the infected mouse model, DENV distorted the endothelium lining and disturbed the smooth muscle, elastic laminae and their supporting tissues causing vascular structural disarrangement. This may explain the severe pathological illness in DENV-infected individuals. The overall DENV-induced damages on the endothelial and it's supporting tissues and the dysregulated immune reactions initiated by the host were discussed.
  15. Angiogenic and wound healing potency of fermented virgin coconut oil: in vitro and in vivo studies
    Ibrahim AH, Li H, Al-Rawi SS, Majid ASA, Al-Habib OA, Xia X, et al.
    Am J Transl Res, 2017;9(11):4936-4944.
    PMID: 29218091
    OBJECTIVE: The process of wound healing involves activation of keratinocytes, fibroblasts, endothelial cells, etc. Angiogenesis is crucial during the process of wound healing. Virgin coconut oil is widely utilized in South Asia for various purposes including food, medicinal and industrial applications. This study aimed to evaluate the potency of fermented virgin coconut oil (FVCO) in angiogenesis and wound healing via both in vitro and in vivo assays.

    METHODS: Human umbilical vein endothelial (HUVEC), fibroblast (CCD-18) and retinal ganglion (RGC-5) cells were cultured in medium containing different concentrations of FVCO. The proliferation, migration and morphological changes of cells were determined. The angiogenic effect of FVCO was evaluated by rat aortic assay. The therapeutic effect of FVCO on wound healing was further assessed in a wound excision model in Sprague Dawley rats. The expression of phospho-VEGFR2 (vascular endothelial growth factor receptor 2) in HUVECs was detected by Western blot.

    RESULTS: FVCO (6 and 12 µg/mL) significantly improved the proliferation of HUVEC, CCD-18 and RGC-5 cells (P < 0.05 or 0.01). FVCO (25 µg/mL) markedly increased the migration ability of CCD-18 and RGC-5 cells (P < 0.05). FVCO did not affect cell morphology as indicated by fluorescein diacetate (FDA), rhodamine 123 and Hoechst staining. FVCO (25, 50 and 100 µg/mL) significantly stimulated the ex vivo blood vessel formation as compared with negative control (P < 0.05). Rats in FVCO group had significantly smaller wound size, higher wound healing percentage, and shorter wound closure time when compared with control group since day 8 (P < 0.05), suggesting that oral FVCO administration notably promoted the wound healing process. FVCO treatment (6 and 12 µg/mL) significantly enhanced the phospho-VEGFR2 expression in HUVECs (P = 0.006 and 0.000, respectively).

    CONCLUSION: Our study confirms a high angiogenic and wound healing potency of FVCO that might be mediated by the regulation of VEGF signing pathway.

  16. Fulltext Ethnopharmacology, Biological Evaluation, and Chemical Composition of Ziziphus spina-christi (L.) Desf.: A Review
    Abdulrahman MD, Zakariya AM, Hama HA, Hamad SW, Al-Rawi SS, Bradosty SW, et al.
    Adv Pharmacol Pharm Sci, 2022;2022:4495688.
    PMID: 35677711 DOI: 10.1155/2022/4495688
    Medicinal plants are the primary raw materials used in the production of medicinal products all over the world. As a result, more study on plants with therapeutic potential is required. The tropical tree Ziziphus spina belongs to the Rhamnaceae family. Biological reports and traditional applications including management of diabetes and treatment of malaria, digestive issues, typhoid, liver complaints, weakness, skin infections, urinary disorders, obesity, diarrhoea, and sleeplessness have all been treated with different parts of Z. spina all over the globe. The plant is identified as a rich source of diverse chemical compounds. This study is a comprehensive yet detailed review of Z. spina based on major findings from around the world regarding ethnopharmacology, biological evaluation, and chemical composition. Scopus, Web of Science, BioMed Central, ScienceDirect, PubMed, Springer Link, and Google Scholar were searched to find published articles. From the 186 research articles reviewed, we revealed the leaf extract to be significant against free radicals, microbes, parasites, inflammation-related cases, obesity, and cancer. Chemically, polyphenols/flavonoids were the most reported compounds with a composition of 66 compounds out of the total 193 compounds reported from different parts of the plant. However, the safety and efficacy of Z. spina have not been wholly assessed in humans, and further well-designed clinical trials are needed to corroborate preclinical findings. The mechanism of action of the leaf extract should be examined. The standard dose and safety of the leaf should be established.
  17. Safety assessment of widely used fermented virgin coconut oil (Cocos nucifera) in Malaysia: Chronic toxicity studies and SAR analysis of the active components
    Ibrahim AH, Khan MS, Al-Rawi SS, Ahamed MB, Majid AS, Al-Suede FS, et al.
    Regul Toxicol Pharmacol, 2016 Nov;81:457-467.
    PMID: 27756558 DOI: 10.1016/j.yrtph.2016.10.004
    Fermented Virgin Coconut Oil (FVCO) is widely used in the Southeast Asia as food and traditional medicine. The objective of the present study is the evaluation of chronic safety of the commercialized FVCO of Malaysia and other Southeast Asian countries. A single dose of 5000 mg/kg of FVCO was administered orally in rats (each group, n = 5) for the acute toxicity study and 175, 550 and 2000 mg/kg for sub-chronic and chronic studies (each group, n = 10), respectively. The behavior, mortality, and body weight of the rats were assessed to determine the toxic effects of FVCO. The haematology, biochemistry and histopathology of the treated rats were evaluated. The treated rats were safe with the dose of 5000 mg/kg in acute, sub-chronic and chronic indication. Abnormal clinical signs and morphology (gross necroscopy), changes of organ weight, anomalous haematology and biochemistry indexes were not found in comparison with the control (p > 0.05). In general, food and water intake were higher in the treated rats related to control. It was concluded that the presence of the antioxidant active compounds of FVCO might be the reason of safety. The structure activity relationship (SAR) provides a comprehensive mechanism to determine the safety that is the presence of the electron donating phenolic groups, carbonyl groups, and carboxylic acid in the ortho and meta position of the aromatic rings. The SAR showed the antioxidant properties of myristic acid and lauric acid determined by GC-MS analysis. This result suggests the safety of FVCO for chronic use, nutritional activity that FVCO formulation complies the requirements of regulatory agencies.
  18. Fulltext Investigating the Mechanical Properties and Durability of Asphalt Mixture Modified with Epoxidized Natural Rubber (ENR) under Short and Long-Term Aging Conditions
    Safaeldeen GI, Al-Mansob RA, Al-Sabaeei AM, Yusoff NIM, Ismail A, Tey WY, et al.
    Polymers (Basel), 2022 Nov 04;14(21).
    PMID: 36365719 DOI: 10.3390/polym14214726
    Modifiers such as fibers, fillers, natural and synthetic polymer extenders, oxidants and anti-oxidants, and anti-stripping agents are added to produce modified asphalt. However, polymers are the most widely utilized modifiers to enhance the function of asphalt mixtures. The objective of this research was to evaluate the mechanical properties and durability of epoxidized natural rubber (ENR)-modified asphalt mix under short- and long-term aging conditions. The physical and rheological characteristics of the base asphalt and ENR-modified asphalt (ENRMA) were tested. In order to evaluate the mechanical properties and durability of the modified mixtures, the resilient modulus of the ENR-asphalt mixtures under unaged, and short- and long-term aging conditions at various temperatures and frequencies was obtained. Furthermore, the resistance to moisture damage of asphalt mixtures was investigated. The findings showed that the stiffness of the ENR-asphalt mixes increased because of the mutual influence of short- and long-term aging on the mixes. In addition, ENR reduced the susceptibility to moisture damage. The stiffness of the mixes was influenced by the temperature and frequencies. By using mathematical modelling via the multivariable power least squares method, it was found that temperature was the dominant factor among all other factors. The results suggested that the durability of asphalt pavements is improved by using ENR.
Related Terms
    Try searching for something
Filters
Contact Us

Please provide feedback to Administrator (afdal@afpm.org.my)

External Links