Displaying publications 61 - 80 of 331 in total

Abstract:
Sort:
  1. Yaseen ZM, Ali M, Sharafati A, Al-Ansari N, Shahid S
    Sci Rep, 2021 Feb 09;11(1):3435.
    PMID: 33564055 DOI: 10.1038/s41598-021-82977-9
    A noticeable increase in drought frequency and severity has been observed across the globe due to climate change, which attracted scientists in development of drought prediction models for mitigation of impacts. Droughts are usually monitored using drought indices (DIs), most of which are probabilistic and therefore, highly stochastic and non-linear. The current research investigated the capability of different versions of relatively well-explored machine learning (ML) models including random forest (RF), minimum probability machine regression (MPMR), M5 Tree (M5tree), extreme learning machine (ELM) and online sequential-ELM (OSELM) in predicting the most widely used DI known as standardized precipitation index (SPI) at multiple month horizons (i.e., 1, 3, 6 and 12). Models were developed using monthly rainfall data for the period of 1949-2013 at four meteorological stations namely, Barisal, Bogra, Faridpur and Mymensingh, each representing a geographical region of Bangladesh which frequently experiences droughts. The model inputs were decided based on correlation statistics and the prediction capability was evaluated using several statistical metrics including mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), correlation coefficient (R), Willmott's Index of agreement (WI), Nash Sutcliffe efficiency (NSE), and Legates and McCabe Index (LM). The results revealed that the proposed models are reliable and robust in predicting droughts in the region. Comparison of the models revealed ELM as the best model in forecasting droughts with minimal RMSE in the range of 0.07-0.85, 0.08-0.76, 0.062-0.80 and 0.042-0.605 for Barisal, Bogra, Faridpur and Mymensingh, respectively for all the SPI scales except one-month SPI for which the RF showed the best performance with minimal RMSE of 0.57, 0.45, 0.59 and 0.42, respectively.
  2. Mohd Ali M, Hashim N, Abd Aziz S, Lasekan O
    Food Res Int, 2020 11;137:109675.
    PMID: 33233252 DOI: 10.1016/j.foodres.2020.109675
    Pineapple (Ananas comosus) is a tropical fruit that is highly relished for its unique aroma and sweet taste. It is renowned as a flavourful fruit since it contains a number of volatile compounds in small amounts and complex mixtures. Pineapple is also a rich source of minerals and vitamins that offer a number of health benefits. Ranked third behind banana and citrus, the demand for pineapple has greatly increased within the international market. The growth of the pineapple industry in the utilisation of pineapple food-based processing products as well as waste processing has progressed rapidly worldwide. This review discusses the nutritional values, physicochemical composition and volatile compounds, as well as health benefits of pineapples. Pineapple contains considerable amounts of bioactive compounds, dietary fiber, minerals, and nutrients. In addition, pineapple has been proven to have various health benefits including anti-inflammatory, antioxidant activity, monitoring nervous system function, and healing bowel movement. The potential of food products and waste processing of pineapples are also highlighted. The future perspectives and challenges with regard to the potential uses of pineapple are critically addressed. From the review, it is proven that pineapples have various health benefits and are a potential breakthrough in the agricultural and food industries.
  3. Alamaary MS, Haron AW, Hiew MWH, Ali M
    Vet Med Sci, 2020 11;6(4):666-672.
    PMID: 32602662 DOI: 10.1002/vms3.315
    Present study aimed to investigate the effect of adding antioxidants, cysteine and ascorbic acid on the levels of glutamic oxaloacetic transaminase (GOT), glutamic-pyruvate (GPT), alkaline phosphatase (ALP), lactate dehydrogenase (LDH) and γ-glutamyl transpeptidase (GGT) enzymes of post-thawed stallion sperm. Ten ejaculates were collected each from four healthy stallions and cryopreserved using HF-20 freezing extender containing either 0 mg/ml cysteine or ascorbic acid, 0.5 mg/ml cysteine and 0.5 mg/ml ascorbic acid. All samples in freezing extender containing cysteine or ascorbic acid or none of them were assessed for sperm motility, viability, plasma membrane integrity, morphology and enzymes concentration. The ALP, LDH and GGT were significantly higher in 0-group compared with cysteine and ascorbic acid groups. The sperm motility of frozen-thawed semen with 0-group was significantly better compared with cysteine and ascorbic acid groups. The variation on viability, sperm membrane integrity and morphology were insignificant between all treated groups. Therefore, these enzymes were reduced when using antioxidants in the freezing extender. Results of the present study suggest that concentration of ALP, LDH and GGT enzymes could be used as parameters for prediction of frozen-thawed stallion semen.
  4. Ali MA, Islam MA, Othman NH, Noor AM, Ibrahim M
    Acta Sci Pol Technol Aliment, 2020 1 14;18(4):427-438.
    PMID: 31930793 DOI: 10.17306/J.AFS.0694
    BACKGROUND: Rice bran oil (RBO) contains significant amounts of micronutrients (oryzanol, tocotrienol, tocopherol, phytosterols etc.) that impart a high resistance to thermal oxidation of the oil. The high oxidative stability of RBO can make it a preferred oil to improve the oxidative and flavor stabilities of other oils rich in PUFAs. In this study, the changes in the oxidative status and fatty acid composition in soybean oil (SO) blended with RBO under extreme thermal conditions were evaluated.

    METHODS: The blends were prepared in a volume ratio of 10:90, 20:80, 40:60, and 60:40 (RBO:SO). The changes in the oxidative parameters and fatty acid composition of the samples during heating at frying temperature (170°C) were determined using analytical and instrumental methods. Oxidative alteration was also monitored by recording FTIR spectra of oil samples.

    RESULTS: The increase in oxidative parameters (free fatty acid, color, specific extinctions, peroxide value, p-anisidine value, and thiobarbituric acid value) was greater in pure SO as compared to RBO or blend oils during heating. This indicates that the SO samples incorporated with RBO have the least degradation, while pure SO has the highest. Blending resulted in a lower level of polyunsaturated fatty acids (PUFA)  with       a higher level of saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA). During heating, the relative content of PUFA decreased and that of SFA increased. However, the presence of RBO in SO slowed down the oxidative deterioration of PUFA. In FTIR, the peak intensities in SO were markedly changed in comparison with blend oils during heating. The reduction in the formation of oxidative products in SO during thermal treatment increased as the concentration of the RBO in SO increased; however, the levels of the protective effect of RBO did not increase steadily with an increase in its concentration.

    CONCLUSIONS: During thermal treatment, the generation of hydroperoxides, their degradation and formation of secondary oxidative products as evaluated by oxidative indices, fatty acids and IR absorbances were lower in blend oils compared to pure SO. In conclusion, RBO can significantly retard the process of lipid peroxidation in SO during heating at frying temperature.

  5. Aniza I, Jamsiah M, Amin SA, Ali M, Munizam AM
    MyJurnal
    Introduction : Family Health Development Division is one of the earliest divisions in Public Health Department, Ministry of Health Malaysia. The division has progressed each year with the extension and expansion of the scopes of services since the establishment of Maternal and Child Health Unit in 1956. The services currently include school children, adolescent, adult and elderly health and also known as life-course perspective: from womb to tomb.
    Objectives : The objective is to elaborate and explain the reformation of primary health care services implemented in the past and present.
    Methods : The methodology applied is compilation, data review and comparison from annual report, action plan report, articles, speeches, specialists and stake holder view.
    Results : The focus of Primary Health Care Service is covering health promotion, disease prevention, early detection and treatment, acute disease care, disease limitation and rehabilitation, clinical support services and teleprimary care. The reformation is caused by factors such as globalization, modernization, growth of health market, emergence and re-emergence of diseases, and development of medical technology. Three health fields that have underwent and under going reformation are concept and wellness practise in primary healthcare, primary healthcare clinical support services development and primary healthcare informatics development. The outcome of these reformations is the increment of service quality and outstanding services for patients and health staffs.
    Conclusion : Health reformation in primary healthcare is greatly needed to give excellent services for primary health care for today and future.
  6. Mohd Ali M, Hashim N, Bejo SK, Shamsudin R
    J Food Sci Technol, 2017 Oct;54(11):3650-3657.
    PMID: 29051660 DOI: 10.1007/s13197-017-2826-y
    The potential of laser light backscattering imaging was investigated for monitoring color parameters of seeded and seedless watermelons during storage. Two watermelon cultivars were harvested and stored for 3 weeks with seven measuring storage days (0, 4, 8, 12, 15, 18, and 21). The color parameters of watermelons were monitored using the conventional colorimetric methods (L*, a*, b*, C*, H*, and ∆E*) and laser light backscattering imaging system. A laser diode emitting at 658 nm and 30 mW power was used as a light source to obtain the backscattering image. The backscattering images were evaluated by the extraction of backscattering parameters based on the mean pixel values. The results showed that a good color prediction was achieved by the seedless watermelon with the R2 are all above 0.900. Thus, the application of the laser light backscattering imaging can be used for evaluating the color parameters of watermelons during the storage period.
  7. Abbas Ali M, Anowarul Islam M, Othman NH, Noor AM
    J Food Sci Technol, 2017 Dec;54(13):4335-4343.
    PMID: 29184239 DOI: 10.1007/s13197-017-2904-1
    The oxidative stability and fatty acid composition of groundnut seed oil (GSO) exposed to microwaves were evaluated during heating at 170 °C. During heating, the oxidative indices such as free fatty acid, peroxide value, p-anisidine value, TOTOX, thiobarbituric acid value, specific extinctions, and color value were increased. The increments were found to be higher in unroasted seed oils compared to roasted ones indicating lower release of lipid oxidation products in roasted GSO. After 9 h heating, the relative content of polyunsaturated fatty acid (PUFA) decreased to 89.53% and that of saturated fatty acid (SFA) increased to 117.46% in unroasted sample. The relative content of PUFA decreased to 92.05% and that of SFA increased to 105.76% in 7.5 min roasted sample after 9 h of heating. However, the roasting process slowed down the oxidative deterioration of PUFA. With increased heating times, an appreciable loss was more apparent in the triacylglycerol species OLL and OOL in unroasted samples compared to roasted ones. In FTIR, the peak intensities in unroasted samples were markedly changed in comparison with roasted samples during heating. The roasting of groundnut seed prior to the oil extraction reduced the oxidative degradation of oil samples; thereby increasing heat stability.
  8. Ali M, Ullah S, Ahmad MS, Cheok MY, Alenezi H
    Environ Sci Pollut Res Int, 2023 Feb;30(9):23335-23347.
    PMID: 36322356 DOI: 10.1007/s11356-022-23811-1
    Social media is playing a vital role in the promotion of green products by reshaping the millennial green purchasing intention and green consumption behaviors, resulting in progressive growth toward sustainable environment and lower carbon emission. Non-organic consumption among humans has increased the carbon emission in contrary risked environment; therefore, consumption behavior and purchasing intention are required to change for better sustainable environment. This study's goal is to determine the effects of social media in molding the consumption behaviors while considering eco-labeling, eco-branding, social norms, and purchase intensions among millennials to promote green consumption and lower carbon emission. It was decided to use a cross-sectional questionnaire survey to get information from the students of different faculties including social sciences, engineering, and bio-sciences. SPSS.V.22 and Smart-PLS were used to analyzed the data. Results indicated that social media has a profoundly good impact on molding and impacting youth behaviors regarding the green consumption, resulting in increasing intention toward sustainable environment which results in lower carbon emission. The results are in line with the predictions and contextual analysis, as the whole world is coming back toward natural life and is working for environmental protection and sustainability specially to lower the carbon emission. Therefore, students are molding themselves toward green consumption. The study recommends that future research may be conducted to study more contextual variables, who has influence on the green consumption among the general public regarding green consumptions and lowering carbon emission and stepping toward the sustainable environment.
  9. Ji D, Sibt-E-Ali M, Amin A, Ayub B
    Environ Sci Pollut Res Int, 2023 Oct;30(46):103198-103211.
    PMID: 37682436 DOI: 10.1007/s11356-023-29719-8
    Belt and Road Initiative (BRI) countries have benefited greatly from the intelligent growth of the green economy made possible by the widespread adoption of internet and mobile phone technologies. In addition, renewable energy consumption endorses sustainable development. Therefore, the purpose of this research is to determine if the use of information and communication technology (ICT) and renewable energy consumption has an effect on sustainable development in BRI countries, while using the augmented mean group (AMG) model, AMG robustness test, and panel Dumitrescu-Hurlin causality test to get robust results. According to the results of the study, the information and communication technology, renewable consumption, human capital, and urbanization reduces the emission of carbon dioxide emission in BRI countries while economic growth enhances the CO2 emission. Therefore, it is recommended that BRI countries increase their inter-regional cooperation in order to boost investment in renewable energy, effectively use the spillover effect of technology and knowledge, and end the resource curse in environmental policy. Based on the results, the authors of this paper propose a number of important steps toward environmental sustainability.
  10. Aziz N, Aznida FAA, Ali MF, Aris JH
    Med J Malaysia, 2023 Mar;78(2):225-233.
    PMID: 36988535
    INTRODUCTION: Dementia is a global challenge for healthcare systems, including Malaysia. Despite evidence-based Clinical Practice Guidelines (CPG) for dementia management in primary care, detection is poor. Improving detection rates requires understanding current practice and influencing factors. This study aims to assess the practice of cognitive evaluation among primary care practitioners (PCPs) and its associated factors, as well as its correlation with their knowledge and attitudes towards early dementia diagnosis.

    MATERIALS AND METHODS: A cross-sectional study conducted online, using Google FormTM recruited 207 Medical Officers from 14 public primary health centres, with a response rate of 74%. The Knowledge, Attitude and Practice Questionnaire for Family Physicians (KAPQFP) was used to assess PCPs' knowledge, attitude and practice in dementia care. Items in each domain were scored on a 4-point Likert scale, with scores ranging from 1 to 4. Each domain's mean score was divided by 4 and converted to a scale of 100, with higher scores indicating better knowledge, attitude and practice. Bivariate analyses were conducted to determine the factors associated with cognitive evaluation practice.

    RESULTS: The overall mean practice score was 3.53±0.52 (88.3%), which is substantially higher than the mean score for perceived competency and knowledge of 2.46±0.51 (61.5%). The mean score for attitude towards dementia and collaboration with nurses and other healthcare professionals was 3.36±0.49 (84.0%) and 3.43±0.71 (85.8%), respectively. PCPs with prior dementia training showed better practice (p=0.006), as did PCPs with longer primary care work experience (p=0.038). A significant positive association was found between knowledge-practice ((rs=0.207, p=0.003), attitude towards dementia practice ((rs=0.478, p<0.001), and attitude towards collaboration with other healthcare professionals-practice (rs= 0.427, p<0.001). Limited time and inadequate knowledge regarding dementia diagnosis and cognitive evaluation tools were among the reasons cognitive evaluations were not performed.

    CONCLUSION: PCPs demonstrated better practice of cognitive evaluation, as compared to their knowledge and attitude. Given that their perceived competency and knowledge on dementia diagnosis is low and is positively associated with their practice, it is crucial to implement a comprehensive dementia training to enhance their knowledge and confidence on early detection of cognitive decline and cognitive evaluation in order to achieve better dementia detection in primary care.

  11. Benjamin TWC, Aznida FAA, Ali MF
    Med J Malaysia, 2023 May;78(3):301-307.
    PMID: 37271839
    INTRODUCTION: Depression in the elderly constitutes 7.3% of the total Malaysian national prevalence of depression. However, depression is commonly underdiagnosed by primary care physicians, which may impact coexisting comorbid conditions and general well-being. As depression in the elderly increases with age, its prevalence is expected to become even more significant due to the increased life expectancy and isolation during the pandemic. This study aims to determine the perceptions, views and barriers encountered among primary care physicians on screening for depression among the elderly.

    MATERIALS AND METHODS: This qualitative study involved five public healthcare clinics in the Kuching district with indepth interviews (IDI) conducted on 14 primary care doctors (PCDs). Semi-structured interviews and in-depth discussions were conducted via videoconferencing. One representative was selected from each clinic at initiation, followed by snowball method for subsequent subject selection until saturation of themes. Interviews were transcribed verbatim, and analysis based on framework analysis principles via NVivo software. Themes were analysed deductively according to study objectives and evidence from literature.

    RESULTS: Three main themes emerged from the IDI: (1) The perception of depression in elderly patients, (2) The perceived barriers to screening, and (3) The screening processes. Majority of the PCDs perceived depression as part of ageing process. Time constraints, lack of privacy in consultation rooms, dominant caregivers and failure to recognise recurrent somatic symptoms as part of depression influenced PCDs decision to screen. Screening was technically challenging for PCDs to use the DASS-21, which was not socio-culturally validated for local native population. Only 21.4% of respondents (3/14) reported screening at least three out 10 elderly patients seen over 1- month period. During the covid pandemic, due to the same human resource support and practices, most participants thought their screening for depression in elderlies had not changed.

    CONCLUSION: Awareness of depression among PCDs needs to be re-enforced via continuous medical education programs to use appropriate screening tools, address infrastructure related barriers to optimise screening practices. The use of appropriate locally validated and socio-culturally adapted tool is vital to correctly interpret the screening test for patients.

  12. Dodo Y, Arif K, Alyami M, Ali M, Najeh T, Gamil Y
    Sci Rep, 2024 Feb 26;14(1):4598.
    PMID: 38409333 DOI: 10.1038/s41598-024-54513-y
    Geo-polymer concrete has a significant influence on the environmental condition and thus its use in the civil industry leads to a decrease in carbon dioxide (CO2) emission. However, problems lie with its mixed design and casting in the field. This study utilizes supervised artificial-based machine learning algorithms (MLAs) to anticipate the mechanical characteristic of fly ash/slag-based geopolymer concrete (FASBGPC) by utilizing AdaBoost and Bagging on MLPNN to make an ensemble model with 156 data points. The data consist of GGBS (kg/m3), Alkaline activator (kg/m3), Fly ash (kg/m3), SP dosage (kg/m3), NaOH Molarity, Aggregate (kg/m3), Temperature (°C) and compressive strength as output parameter. Python programming is utilized in Anaconda Navigator using Spyder version 5.0 to predict the mechanical response. Statistical measures and validation of data are done by splitting the dataset into 80/20 percent and K-Fold CV is employed to check the accurateness of the model by using MAE, RMSE, and R2. Statistical analysis relies on errors, and tests against external indicators help determine how well models function in terms of robustness. The most important factor in compressive strength measurements is examined using permutation characteristics. The result reveals that ANN with AdaBoost is outclassed by giving maximum enhancement with R2 = 0.914 and shows the least error with statistical and external validations. Shapley analysis shows that GGBS, NaOH Molarity, and temperature are the most influential parameter that has significant content in making FASBGPC. Thus, ensemble methods are suitable for constructing prediction models because of their strong and reliable performance. Furthermore, the graphical user interface (GUI) is generated through the process of training a model that forecasts the desired outcome values when the corresponding inputs are provided. It streamlines the process and provides a useful tool for applying the model's abilities in the field of civil engineering.
  13. İlbasmış M, Çitil M, Demirtaş F, Ali M, Barut A, Mohsin M
    Environ Sci Pollut Res Int, 2023 Aug;30(38):89726-89739.
    PMID: 37460882 DOI: 10.1007/s11356-023-28544-3
    The aim of this study is to examine the effect of green investments on air quality for developed and developing European countries. In this context, the short- and long-term effects of green investments on air quality were examined by panel generalized method of moments (GMM) and panel causality method. As a result of the GMM analysis, it has been determined that green investments negatively affect the air quality for both developed European countries and developing European countries in the short term, but this effect turns positive in developed countries in the long term. As a result of the panel causality analysis, two-way causality was determined between air quality and green investments.
  14. Asghar R, Javed MF, Ali M, Najeh T, Gamil Y
    Sci Rep, 2024 May 02;14(1):10135.
    PMID: 38697995 DOI: 10.1038/s41598-024-59345-4
    This article presents a numerical and artificial intelligence (AI) based investigation on the web crippling performance of pultruded glass fiber reinforced polymers' (GFRP) rectangular hollow section (RHS) profiles subjected to interior-one-flange (IOF) loading conditions. To achieve the desired research objectives, a finite element based computational model was developed using one of the popular simulating software ABAQUS CAE. This model was then validated by utilizing the results reported in experimental investigation-based article of Chen and Wang. Once the finite element model was validated, an extensive parametric study was conducted to investigate the aforementioned phenomenon on the basis of which a comprehensive, universal, and coherent database was assembled. This database was then used to formulate the design guidelines for the web crippling design of pultruded GFRP RHS profiles by employing AI based gene expression programming (GEP). Based on the findings of numerical investigation, the web crippling capacity of abovementioned structural profiles subjected to IOF loading conditions was found to be directly related to that of section thickness and bearing length whereas inversely related to that of section width, section height, section's corner radii, and profile length. On the basis of the findings of AI based investigation, the modified design rules proposed by this research were found to be accurately predicting the web crippling capacity of aforesaid structural profiles. This research is a significant contribution to the literature on the development of design guidelines for pultruded GFRP RHS profiles subjected to web crippling, however, there is still a lot to be done in this regard before getting to the ultimate conclusions.
  15. Umer A, Ali M, Jehangiri AI, Bilal M, Shuja J
    Sensors (Basel), 2024 Apr 09;24(8).
    PMID: 38675998 DOI: 10.3390/s24082381
    IoT-based smart transportation monitors vehicles, cargo, and driver statuses for safe movement. Due to the limited computational capabilities of the sensors, the IoT devices require powerful remote servers to execute their tasks, and this phenomenon is called task offloading. Researchers have developed efficient task offloading and scheduling mechanisms for IoT devices to reduce energy consumption and response time. However, most research has not considered fault-tolerance-based job allocation for IoT logistics trucks, task and data-aware scheduling, priority-based task offloading, or multiple-parameter-based fog node selection. To overcome the limitations, we proposed a Multi-Objective Task-Aware Offloading and Scheduling Framework for IoT Logistics (MT-OSF). The proposed model prioritizes the tasks into delay-sensitive and computation-intensive tasks using a priority-based offloader and forwards the two lists to the Task-Aware Scheduler (TAS) for further processing on fog and cloud nodes. The Task-Aware Scheduler (TAS) uses a multi-criterion decision-making process, i.e., the analytical hierarchy process (AHP), to calculate the fog nodes' priority for task allocation and scheduling. The AHP decides the fog nodes' priority based on node energy, bandwidth, RAM, and MIPS power. Similarly, the TAS also calculates the shortest distance between the IoT-enabled vehicle and the fog node to which the IoT tasks are assigned for execution. A task-aware scheduler schedules delay-sensitive tasks on nearby fog nodes while allocating computation-intensive tasks to cloud data centers using the FCFS algorithm. Fault-tolerant manager is used to check task failure; if any task fails, the proposed system re-executes the tasks, and if any fog node fails, the proposed system allocates the tasks to another fog node to reduce the task failure ratio. The proposed model is simulated in iFogSim2 and demonstrates a 7% reduction in response time, 16% reduction in energy consumption, and 22% reduction in task failure ratio in comparison to Ant Colony Optimization and Round Robin.
  16. Ali M, Wahab IBA, Huri HZ, Yusoff MS
    Syst Rev, 2024 Apr 02;13(1):99.
    PMID: 38566190 DOI: 10.1186/s13643-024-02478-4
    BACKGROUND: Personalised learning, an educational approach that tailors teaching and learning to individual needs and preferences, has gained attention in recent years, particularly in higher education. Advances in educational technology have facilitated the implementation of personalised learning in various contexts. Despite its potential benefits, the literature on personalised learning in health sciences higher education remains scattered and heterogeneous. This scoping review aims to identify and map the current literature on personalised learning in health sciences higher education and its definition, implementation strategies, benefits, and limitations.

    METHODS: A comprehensive search of electronic databases, PubMed, Scopus, Google Scholar, Educational Research Complete, and Journal Storage (JSTOR), will be conducted to identify relevant articles. The search will be limited to articles published in the English language between 2000 and 2023. The search strategy will be designed and adapted for each database using a combination of keywords and subject headings related to personalised learning and health sciences higher education. Eligibility criteria will be applied to screen and select articles. Data extraction and quality assessment will be performed, and thematic synthesis will be used to analyse the extracted data.

    DISCUSSION: The results of the scoping review will present a comprehensive and coherent overview of the literature on personalised learning in health sciences higher education. Key themes and topics related to personalised learning, its definitions, models, implementation strategies, benefits, and limitations, will be identified. The geographical and temporal distribution of research on personalised learning in health sciences higher education will also be described. This scoping review will provide a structured synthesis of the available evidence on personalised learning in health sciences higher education, highlighting potential gaps and areas for future research. The findings will contribute to ongoing scholarly and policy debates on personalised learning in higher education, informing the development of best practices, guidelines, and future research agendas.

  17. Sha An Ali M, Mohd Nazir NA, Manaf ZA
    Malays J Med Sci, 2020 Mar;27(2):101-111.
    PMID: 32788846 MyJurnal DOI: 10.21315/mjms2020.27.2.11
    Background: The low consumption of fruits and vegetables among children is a global challenge. Foods recognition, nutrition knowledge and attitude are factors that influence children's dietary practices. This study aims to assess the preference, attitude, recognition and knowledge of fruits and vegetables intake among Malay children.

    Methods: A cross-sectional study was conducted among Malay children from five primary schools in Kuala Lumpur using self-administered questionnaires.

    Results: A total of 134 Malay children (70 males and 64 females) with a mean (SD) age of 10.3 (1.0) years were recruited. Majority of the children had a father (61.9%) and a mother (56.0%) with secondary school education and earned below RM3,900 (70.9%) per month. The most preferred fruits and vegetable were bananas (91.9%) and carrots (71.4%), while the most recognised was oranges (100.0%) and tomatoes (96.3%). The children demonstrated an overall moderate level of attitude, recognition and knowledge with mean (SD) scores of 70.3 (19.9), 76.8 (18.1) and 73.6 (17.5), respectively, towards fruits and vegetables intake. Majority of the children (53.0%) were not aware of the daily recommended servings of fruits and vegetables, while 40.0% of children expressed a low attitude towards eating a variety of fruits and vegetables. The willingness to try a new type of vegetables and consume more vegetables was lower (68.7%) compared to fruits (75.4%).

    Conclusion: The preferences and recognition of fruits were higher compared to vegetables among the children. The children demonstrated a moderate level of attitude, recognition and knowledge towards fruits and vegetables consumption. Efforts to educate children on the recommended number of servings per day and improve their acceptability of vegetables should be implemented to promote the increase in fruits and vegetables consumption among children.

  18. Ben Hadda T, Berredjem M, Almalki FA, Rastija V, Jamalis J, Emran TB, et al.
    J Biomol Struct Dyn, 2022;40(19):9429-9442.
    PMID: 34033727 DOI: 10.1080/07391102.2021.1930161
    Remdesivir and hydroxychloroquine derivatives form two important classes of heterocyclic compounds. They are known for their anti-malarial biological activity. This research aims to analyze the physicochemical properties of remdesivir and hydroxychloroquine compounds by the computational approach. DFT, docking, and POM analyses also identify antiviral pharmacophore sites of both compounds. The antiviral activity of hydroxychloroquine compound's in the presence of zinc sulfate and azithromycin is evaluated through its capacity to coordinate transition metals (M = Cu, Ni, Zn, Co, Ru, Pt). The obtained bioinformatic results showed the potent antiviral/antibacterial activity of the prepared mixture (Hydroxychloroquine/Azithromycin/Zinc sulfate) for all the opportunistic Gram-positive, Gram-negative in the presence of coronavirus compared with the complexes Polypyridine-Ruthenium-di-aquo. The postulated zinc(II) complex of hydroxychloroquine derivatives are indeed an effective antibacterial and antiviral agent against coronavirus and should be extended to other pathogens. The combination of a pharmacophore site with a redox [Metal(OH2)2] moiety is of crucial role to fight against viruses and bacteria strains. [Formula: see text]Communicated by Ramaswamy H. Sarma.
  19. Suleiman MK, Dixon K, Commander L, Nevill P, Quoreshi AM, Bhat NR, et al.
    Front Microbiol, 2019;10:63.
    PMID: 30766519 DOI: 10.3389/fmicb.2019.00063
    This research examined the general soil fungi and AM fungal communities associated with a Lonely Tree species (Vachellia pachyceras) existing in the Sabah Al-Ahmad Natural Reserve located at the Kuwait desert. The goals of the study were to describe the general fungal and AM fungal communities present in the rhizospheric, non-rhizospheric soils and roots of V. pachyceras, respectively, as well as local and non-local V. pachyceras seedlings when grown under standard nursery growing environments. Soil and root samples were analyzed for an array of characteristics including soil physicochemical composition, and culture-independent method termed PCR-cloning, intermediate variable region of rDNA, the large subunit (LSU) and internal transcribed spacer (ITS) region sequence identifications. The results reveal that the fungal phylotypes were classified in four major fungal phyla namely Ascomycota, Basidiomycota, Chytridiomycota, and Zygomycota. The largest assemblage of fungal analyses showed communities dominated by members of the phylum Ascomycota. The assays also revealed a wealth of incertae sedis fungi, mostly affiliated to uncultured fungi from diverse environmental conditions. Striking difference between rhizosphere and bulk soils communities, with more fungal diversities and Operational Taxonomic Units (OTUs) richness associated with both the field and nursery rhizosphere soils. In contrast, a less diverse fungal community was found in the bulk soil samples. The characterization of AM fungi from the root system demonstrated that the most abundant and diversified group belongs to the family Glomeraceae, with the common genus Rhizophagus (5 phylotypes) and another unclassified taxonomic group (5 phylotypes). Despite the harsh climate that prevails in the Kuwait desert, studied roots displayed the existence of considerable number of AM fungal biota. The present work thus provides a baseline of the fungal and mycorrhizal community associated with rhizosphere and non-rhizosphere soils and roots of only surviving V. pachyceras tree from the Kuwaiti desert and seedlings under nursery growing environments.
  20. Tao H, Al-Hilali AA, Ahmed AM, Mussa ZH, Falah MW, Abed SA, et al.
    Chemosphere, 2023 Mar;317:137914.
    PMID: 36682637 DOI: 10.1016/j.chemosphere.2023.137914
    Heavy metals (HMs) are a vital elements for investigating the pollutant level of sediments and water bodies. The Murray-Darling river basin area located in Australia is experiencing severe damage to increased crop productivity, loss of soil fertility, and pollution levels within the vicinity of the river system. This basin is the most effective primary production area in Australia where agricultural productivity is increased the gross domastic product in the entire mainland. In this study, HMs contaminations are examined for eight study sites selected for the Murray-Darling river basin where the inverse Distance Weighting interpolation method is used to identify the distribution of HMs. To pursue this, four different pollution indices namely the Geo-accumulation index (Igeo), Contamination factor (CF), Pollution load index (PLI), single-factor pollution index (SPLI), and the heavy metal pollution index (HPI) are computed. Following this, the Pearson correlation matrix is used to identify the relationships among the two HM parameters. The results indicate that the conductivity and N (%) are relatively high in respect to using Igeo and PLI indexes for study sites 4, 6, and 7 with 2.93, 3.20, and 1.38, respectively. The average HPI is 216.9071 that also indicates higher level pollution in the Murray-Darling river basin and the highest HPI value is noted in sample site 1 (353.5817). The study also shows that the levels of Co, P, Conductivity, Al, and Mn are mostly affected by HMs and that these indices indicate the maximum HM pollution level in the Murray-Darling river basin. Finally, the results show that the high HM contamination level appears to influence human health and local environmental conditions.
Filters
Contact Us

Please provide feedback to Administrator ([email protected])

External Links