MyMedR

Displaying publications 61 - 69 of 69 in total

Abstract:

Sort:

Fulltext An improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration

Ehteram M, Singh VP, Ferdowsi A, Mousavi SF, Farzin S, Karami H, et al.

PLoS One, 2019;14(5):e0217499.
PMID: 31150443 DOI: 10.1371/journal.pone.0217499

Reference evapotranspiration (ET0) plays a fundamental role in irrigated agriculture. The objective of this study is to simulate monthly ET0 at a meteorological station in India using a new method, an improved support vector machine (SVM) based on the cuckoo algorithm (CA), which is known as SVM-CA. Maximum temperature, minimum temperature, relative humidity, wind speed and sunshine hours were selected as inputs for the models used in the simulation. The results of the simulation using SVM-CA were compared with those from experimental models, genetic programming (GP), model tree (M5T) and the adaptive neuro-fuzzy inference system (ANFIS). The achieved results demonstrate that the proposed SVM-CA model is able to simulate ET0 more accurately than the GP, M5T and ANFIS models. Two major indicators, namely, root mean square error (RMSE) and mean absolute error (MAE), indicated that the SVM-CA outperformed the other methods with respective reductions of 5-15% and 5-17% compared with the GP model, 12-21% and 10-22% compared with the M5T model, and 7-15% and 5-18% compared with the ANFIS model, respectively. Therefore, the proposed SVM-CA model has high potential for accurate simulation of monthly ET0 values compared with the other models.
Fulltext Microwave radiation-induced grafting of 2-methacryloyloxyethyl trimethyl ammonium chloride onto lentil extract (LE-g-DMC) as an emerging high-performance plant-based grafted coagulant

Chua SC, Chong FK, Ul Mustafa MR, Mohamed Kutty SR, Sujarwo W, Abdul Malek M, et al.

Sci Rep, 2020 03 03;10(1):3959.
PMID: 32127558 DOI: 10.1038/s41598-020-60119-x

The importance of graft copolymerization in the field of polymer science is analogous to the importance of alloying in the field of metals. This is attribute to the ability of the grafting method to regulate the properties of polymer 'tailor-made' according to specific needs. This paper described a novel plant-based coagulant, LE-g-DMC that synthesized through grafting of 2-methacryloyloxyethyl trimethyl ammonium chloride (DMC) onto the backbone of the lentil extract. The grafting process was optimized through the response surface methodology (RSM) using three-level Box-Behnken Design (BBD). Under optimum conditions, a promising grafting percentage of 120% was achieved. Besides, characterization study including SEM, zeta potential, TGA, FTIR and EDX were used to confirm the grafting of the DMC monomer chain onto the backbone of lentil extract. The grafted coagulant, LE-g-DMC outperformed lentil extract and alum in turbidity reduction and effective across a wide range of pH from pH 4 to pH 10. Besides, the use of LE-g-DMC as coagulant produced flocs with excellent settling ability (5.09 mL/g) and produced the least amount of sludge. Therefore, from an application and economic point of views, LE-g-DMC was superior to native lentil extract coagulant and commercial chemical coagulant, alum.
Fulltext Glutathione (GSH) improves sperm quality and testicular morphology in streptozotocin-induced diabetic mice

Abdullah F, Khan Nor-Ashikin MN, Agarwal R, Kamsani YS, Abd Malek M, Bakar NS, et al.

Asian J Androl, 2021 1 22;23(3):281-287.
PMID: 33473013 DOI: 10.4103/aja.aja_81_20

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.
Sustainable management of water demand using fuzzy inference system: a case study of Kenyir Lake, Malaysia

Mohd Azlan NNI, Abdul Malek M, Zolkepli M, Mohd Salim J, Ahmed AN

Environ Sci Pollut Res Int, 2021 Apr;28(16):20261-20272.
PMID: 33405154 DOI: 10.1007/s11356-020-11908-4

Sustainable water demand management has become a necessity to the world since the immensely growing population and development have caused water deficit and groundwater depletion. This study aims to overcome water deficit by analyzing water demand at Kenyir Lake, Terengganu, using a fuzzy inference system (FIS). The analysis is widened by comparing FIS with the multiple linear regression (MLR) method. FIS applied as an analysis tool provides good generalization capability for optimum solutions and utilizes human behavior influenced by expert knowledge in water resources management for fuzzy rules specified in the system, whereas MLR can simultaneously adjust and compare several variables as per the needs of the study. The water demand dataset of Kenyir Lake was analyzed using FIS and MLR, resulting in total forecasted water consumptions at Kenyir Lake of 2314.38 m3 and 1358.22 m3, respectively. It is confirmed that both techniques converge close to the actual water consumption of 1249.98 m3. MLR showed the accuracy of the water demand values with smaller forecasted errors to be higher than FIS did. To attain sustainable water demand management, the techniques used can be examined extensively by researchers, educators, and learners by adding more variables, which will provide more anticipated outcomes.
Fulltext PM2.5 forecasting for an urban area based on deep learning and decomposition method

Zaini N, Ean LW, Ahmed AN, Abdul Malek M, Chow MF

Sci Rep, 2022 Oct 20;12(1):17565.
PMID: 36266317 DOI: 10.1038/s41598-022-21769-1

Rapid growth in industrialization and urbanization have resulted in high concentration of air pollutants in the environment and thus causing severe air pollution. Excessive emission of particulate matter to ambient air has negatively impacted the health and well-being of human society. Therefore, accurate forecasting of air pollutant concentration is crucial to mitigate the associated health risk. This study aims to predict the hourly PM2.5 concentration for an urban area in Malaysia using a hybrid deep learning model. Ensemble empirical mode decomposition (EEMD) was employed to decompose the original sequence data of particulate matter into several subseries. Long short-term memory (LSTM) was used to individually forecast the decomposed subseries considering the influence of air pollutant parameters for 1-h ahead forecasting. Then, the outputs of each forecast were aggregated to obtain the final forecasting of PM2.5 concentration. This study utilized two air quality datasets from two monitoring stations to validate the performance of proposed hybrid EEMD-LSTM model based on various data distributions. The spatial and temporal correlation for the proposed dataset were analysed to determine the significant input parameters for the forecasting model. The LSTM architecture consists of two LSTM layers and the data decomposition method is added in the data pre-processing stage to improve the forecasting accuracy. Finally, a comparison analysis was conducted to compare the performance of the proposed model with other deep learning models. The results illustrated that EEMD-LSTM yielded the highest accuracy results among other deep learning models, and the hybrid forecasting model was proved to have superior performance as compared to individual models.
Fulltext Exogenous L-Glutathione Improves Vitrification Outcomes in Murine Preimplantation Embryos

Abdul Rahman NS, Mohamed Noor Khan NA, Eshak Z, Sarbandi MS, Mohammad Kamal AA, Abd Malek M, et al.

Antioxidants (Basel), 2022 Oct 25;11(11).
PMID: 36358471 DOI: 10.3390/antiox11112100

Vitrification is an important tool to store surplus embryos in assisted reproductive technology (ART). However, vitrification increases oxidative damage and results in decreased viability. Studies have reported that L-glutathione (GSH) supplementation improves the preimplantation development of murine embryos. Glutathione constitutes the major non-protein sulphydryl compound in mammalian cells, which confers protection against oxidative damage. However, the effect of GSH supplementation on embryonic vitrification outcomes has yet to be reported. This study aims to determine whether GSH supplementation in culture media improves in vitro culture and vitrification outcomes, as observed through embryo morphology and preimplantation development. Female BALB/c mice aged 6−8 weeks were superovulated through an intraperitoneal injection of 10 IU of pregnant mare serum gonadotrophin (PMSG), followed by 10 IU of human chorionic gonadotrophin (hCG) 48 h later. The mated mice were euthanized by cervical dislocation 48 h after hCG to harvest embryos. Two-cell embryos were randomly assigned to be cultured in either Group 1 (GSH-free medium), Group 2 (GSH-free medium with vitrification), Group 3 (0.01 mM GSH-supplemented medium), or Group 4 (0.01 mM GSH-supplemented medium with vitrification). Non-vitrified (Groups 1 and 3) and vitrified (Groups 2 and 4) embryos were observed for morphological quality and preimplantation development at 24, 48, 72, and 96 h. In the non-vitrified groups, there were significant increases in the number of Grade-1 blastocysts in GSH cultures (p < 0.05). Similarly, in the vitrified groups, GSH supplementation was also seen to significantly increase blastocyst formation. Exogenous GSH supplementation resulted in a significant increase in intracellular GSH, a release of cytochrome c from mitochondria, and a parallel decrease in intracellular reactive oxygen species (ROS) levels in vitrified eight-cell embryos (p < 0.05). GSH supplementation was shown to upregulate Bcl2 expression and downregulate Bax expression in the vitrified preimplantation embryo group. The action of exogenous GSH was concomitant with an increase in the relative abundance of Gpx1 and Sod1. In conclusion, our study demonstrated the novel use and practical applicability of GSH supplementation for improving embryonic cryotolerance via a decrease in ROS levels and the inhibition of apoptotic events by improvement in oxidative status.
Fulltext Increased yield performance of mutation induced Soybean genotypes at varied agro-ecological conditions

Bhuiyan MSH, Malek MA, Emon RM, Khatun MK, Khandaker MM, Alam MA

Braz J Biol, 2022;84:e255235.
PMID: 35019108 DOI: 10.1590/1519-6984.255235

In soybean breeding program, continuous selection pressure on traits response to yield created a genetic bottleneck for improvements of soybean through hybridization breeding technique. Therefore an initiative was taken to developed high yielding soybean variety applying mutation breeding techniques at Plant Breeding Division, Bangladesh Institute of Nuclear Agriculture (BINA), Bangladesh. Locally available popular cultivar BARI Soybean-5 was used as a parent material and subjected to five different doses of Gamma ray using Co60. In respect to seed yield and yield attributing characters, twelve true breed mutants were selected from M4 generation. High values of heritability and genetic advance with high genotypic coefficient of variance (GCV) for plant height, branch number and pod number were considered as favorable attributes for soybean improvement that ensure expected yield. The mutant SBM-18 obtained from 250Gy provided stable yield performance at diversified environments. It provided maximum seed yield of 3056 kg ha-1 with highest number of pods plant-1 (56). The National Seed Board of Bangladesh (NSB) eventually approved SBM-18 and registered it as a new soybean variety named 'Binasoybean-5' for large-scale planting because of its superior stability in various agro-ecological zones and consistent yield performance.
Exploring machine learning algorithms for accurate water level forecasting in Muda river, Malaysia

Adli Zakaria MN, Ahmed AN, Abdul Malek M, Birima AH, Hayet Khan MM, Sherif M, et al.

Heliyon, 2023 Jul;9(7):e17689.
PMID: 37456046 DOI: 10.1016/j.heliyon.2023.e17689

Accurate water level prediction for both lake and river is essential for flood warning and freshwater resource management. In this study, three machine learning algorithms: multi-layer perceptron neural network (MLP-NN), long short-term memory neural network (LSTM) and extreme gradient boosting XGBoost were applied to develop water level forecasting models in Muda River, Malaysia. The models were developed using limited amount of daily water level and meteorological data from 2016 to 2018. Different input scenarios were tested to investigate the performance of the models. The results of the evaluation showed that the MLP model outperformed both the LSTM and the XGBoost models in predicting water levels, with an overall accuracy score of 0.871 compared to 0.865 for LSTM and 0.831 for XGBoost. No noticeable improvement has been achieved after incorporating meteorological data into the models. Even though the lowest reported performance was reported by the XGBoost, it is the faster of the three algorithms due to its advanced parallel processing capabilities and distributed computing architecture. In terms of different time horizons, the LSTM model was found to be more accurate than the MLP and XGBoost model when predicting 7 days ahead, demonstrating its superiority in capturing long-term dependencies. Therefore, it can be concluded that each ML model has its own merits and weaknesses, and the performance of different ML models differs on each case because these models depends largely on the quantity and quality of data available for the model training.
Clinical, Radiological, and Microbiologic Characteristics of Patients with Noncystic Fibrosis Bronchiectasis in a Tertiary Center at Jordan

Albtoosh AS, Altarawneh T, Toubasi AA, Malek M, Albulbol DM, Alnugaimshi SF, et al.

Curr Med Imaging, 2024;20:1-8.
PMID: 38389348 DOI: 10.2174/0115734056255925231108052743

BACKGROUND: Only a small number of the investigations that were carried out in the Middle East attempted to characterize patients with NCFB. In order to characterize patients with NCFB, as well as their etiologies, microbiological profiles, and outcomes, we therefore carried out this investigation.
METHODS: This retrospective cohort study was carried out at the Jordan University Hospital (JUH), a tertiary facility located in Amman, Jordan. Non-cystic Fibrosis Bronchiectasis (NCFB) was defined as an HRCT scan typical for bronchiectasis along with a negative sweat chloride test to rule out cystic fibrosis. Patients' data were collected by the use of Electronic Medical Records (EMR) at our institution. Frequent exacerbation was defined as more than 2 exacerbations in 1 year of the onset of the diagnosis.
RESULTS: A total of 79 patients were included, and 54.4% of them were female. The mean and standard deviation of the patient's age was 48.61 ± 19.62. The etiologies of bronchiectasis were evident in 79.7% of the sample. Asthma, Chronic Obstructive Pulmonary Diseases (COPD), and Kartagener syndrome were the most prevalent etiologies, accounting for related illnesses in 21.8%, 21.5%, and 13.9% of the patients, respectively. The most frequent bacteria cultured in our cohort were Pseudomonas and Candida Species. Moreover, 43 patients of the study cohort were frequent exacerbators, and 5 patients died.
CONCLUSION: Our study supports the need to identify several bronchiectasis phenotypes linked to various causes. These findings provide information to clinicians for the early detection and treatment of bronchiectasis in Jordan.