Displaying publications 81 - 100 of 116 in total

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  1. Fulltext Performance Analysis of Linearly Arranged Concentric Circular Antenna Array with Low Sidelobe Level and Beamwidth Using Robust Tapering Technique
    Rahaman I, Haque MA, Singh NSS, Jafor MS, Sarkar PK, Rahman MA, et al.
    Micromachines (Basel), 2022 Nov 11;13(11).
    PMID: 36422388 DOI: 10.3390/mi13111959
    In this research, a novel antenna array named Linearly arranged Concentric Circular Antenna Array (LCCAA) is proposed, concerning lower beamwidth, lower sidelobe level, sharp ability to detect false signals, and impressive SINR performance. The performance of the proposed LCCAA beamformer is compared with geometrically identical existing beamformers using the conventional technique where the LCCAA beamformer shows the lowest beamwidth and sidelobe level (SLL) of 12.50° and -15.17 dB with equal elements accordingly. However, the performance is degraded due to look direction error, for which robust techniques, fixed diagonal loading (FDL), optimal diagonal loading (ODL), and variable diagonal loading (VDL), are applied to all the potential arrays to minimize this problem. Furthermore, the LCCAA beamformer is further simulated to reduce the sidelobe applying tapering techniques where the Hamming window shows the best performance having 17.097 dB less sidelobe level compared to the uniform window. The proposed structure is also analyzed under a robust tapered (VDL-Hamming) method which reduces around 69.92 dB and 48.39 dB more sidelobe level compared to conventional and robust techniques. Analyzing all the performances, it is clear that the proposed LCCAA beamformer is superior and provides the best performance with the proposed robust tapered (VDL-Hamming) technique.
  2. Nanomedicine-driven therapeutic interventions of autophagy and stem cells in the management of Alzheimer's disease
    Alhodieb FS, Rahman MA, Barkat MA, Alanezi AA, Barkat HA, Hadi HA, et al.
    Nanomedicine (Lond), 2023 Mar 20.
    PMID: 36938800 DOI: 10.2217/nnm-2022-0108
    Drug-loaded, brain-targeted nanocarriers could be a promising tool in overcoming the challenges associated with Alzheimer's disease therapy. These nanocargoes are enormously flexible to functionalize and facilitate the delivery of drugs to brain cells by bridging the blood-brain barrier and into brain cells. To date, modifications have included nanoparticles (NPs) coating with tunable surfactants/phospholipids, covalently attaching polyethylene glycol chains (PEGylation), and tethering different targeting ligands to cell-penetrating peptides in a manner that facilitates their entry across the BBB and downregulates various pathological hallmarks as well as intra- and extracellular signaling pathways. This review provides a brief update on drug-loaded, multifunctional nanocarriers and the therapeutic intervention of autophagy and stem cells in the management of Alzheimer's disease.
  3. Fulltext Stability and Reproducibility of Radiomic Features Based on Various Segmentation Techniques on Cervical Cancer DWI-MRI
    Ramli Z, Karim MKA, Effendy N, Abd Rahman MA, Kechik MMA, Ibahim MJ, et al.
    Diagnostics (Basel), 2022 Dec 12;12(12).
    PMID: 36553132 DOI: 10.3390/diagnostics12123125
    Cervical cancer is the most common cancer and ranked as 4th in morbidity and mortality among Malaysian women. Currently, Magnetic Resonance Imaging (MRI) is considered as the gold standard imaging modality for tumours with a stage higher than IB2, due to its superiority in diagnostic assessment of tumour infiltration with excellent soft-tissue contrast. In this research, the robustness of semi-automatic segmentation has been evaluated using a flood-fill algorithm for quantitative feature extraction, using 30 diffusion weighted MRI images (DWI-MRI) of cervical cancer patients. The relevant features were extracted from DWI-MRI segmented images of cervical cancer. First order statistics, shape features, and textural features were extracted and analysed. The intra-class relation coefficient (ICC) was used to compare 662 radiomic features extracted from manual and semi-automatic segmentations. Notably, the features extracted from the semi-automatic segmentation and flood filling algorithm (average ICC = 0.952 0.009, p > 0.05) were significantly higher than the manual extracted features (average ICC = 0.897 0.011, p > 0.05). Henceforth, we demonstrate that the semi-automatic segmentation is slightly expanded to manual segmentation as it produces more robust and reproducible radiomic features.
  4. Removal of nickel from aqueous solution using supported zeolite-Y hollow fiber membranes
    Muhamad N, Abdullah N, Rahman MA, Abas KH, Aziz AA, Othman MHD, et al.
    Environ Sci Pollut Res Int, 2018 Jul;25(19):19054-19064.
    PMID: 29721796 DOI: 10.1007/s11356-018-2074-3
    This work describes the development of supported zeolite-Y membranes, prepared using the hydrothermal method, for the removal of nickel from an aqueous solution. Alumina hollow fibers prepared using the phase inversion and sintering technique were used as an inert support. The supported zeolite-Y membranes were characterized using the field emission scanning electron microscope (FESEM), X-ray diffraction (XRD), and the water permeation and rejection test. The performance of the supported zeolite-Y membranes for heavy metal removal using batch adsorption and filtration test was studied using the atomic absorption spectroscopy (AAS). The adsorption study shows that the removal of nickel was pH-dependent but affected by the presence of α-alumina. The seeded zeolite-Y membrane gave the highest adsorption capacity which was 126.2 mg g-1. This enabled the membrane to remove 63% of nickel ions from the aqueous solution within 180 min of contact time. The adsorption mechanism of nickel onto the zeolite-Y membrane was best fitted to the Freundlich isotherm. The kinetic study concluded that the adsorption was best fitted to pseudo-second-order model with higher correlation coefficient (R2 = 0.9996). The filtration study proved that the zeolite-Y membrane enabled to reduce the concentration of heavy metal at parts per billion level.
  5. Contemporary evidence of workplace violence against the primary healthcare workforce worldwide: a systematic review
    Yusoff HM, Ahmad H, Ismail H, Reffin N, Chan D, Kusnin F, et al.
    Hum Resour Health, 2023 Oct 13;21(1):82.
    PMID: 37833727 DOI: 10.1186/s12960-023-00868-8
    Violence against healthcare workers recently became a growing public health concern and has been intensively investigated, particularly in the tertiary setting. Nevertheless, little is known of workplace violence against healthcare workers in the primary setting. Given the nature of primary healthcare, which delivers essential healthcare services to the community, many primary healthcare workers are vulnerable to violent events. Since the Alma-Ata Declaration of 1978, the number of epidemiological studies on workplace violence against primary healthcare workers has increased globally. Nevertheless, a comprehensive review summarising the significant results from previous studies has not been published. Thus, this systematic review was conducted to collect and analyse recent evidence from previous workplace violence studies in primary healthcare settings. Eligible articles published in 2013-2023 were searched from the Web of Science, Scopus, and PubMed literature databases. Of 23 included studies, 16 were quantitative, four were qualitative, and three were mixed method. The extracted information was analysed and grouped into four main themes: prevalence and typology, predisposing factors, implications, and coping mechanisms or preventive measures. The prevalence of violence ranged from 45.6% to 90%. The most commonly reported form of violence was verbal abuse (46.9-90.3%), while the least commonly reported was sexual assault (2-17%). Most primary healthcare workers were at higher risk of patient- and family-perpetrated violence (Type II). Three sub-themes of predisposing factors were identified: individual factors (victims' and perpetrators' characteristics), community or geographical factors, and workplace factors. There were considerable negative consequences of violence on both the victims and organisations. Under-reporting remained the key issue, which was mainly due to the negative perception of the effectiveness of existing workplace policies for managing violence. Workplace violence is a complex issue that indicates a need for more serious consideration of a resolution on par with that in other healthcare settings. Several research gaps and limitations require additional rigorous analytical and interventional research. Information pertaining to violent events must be comprehensively collected to delineate the complete scope of the issue and formulate prevention strategies based on potentially modifiable risk factors to minimise the negative implications caused by workplace violence.
  6. Fulltext Dual Regime Mode-Locked and Q-Switched Erbium-Doped Fiber Laser by Employing Graphene Filament-Chitin Film-Based Passive Saturable Absorber
    Zuikafly SNF, Ahmad H, Ismail MF, Abdul Rahman MA, Yahya WJ, Abu Husain N, et al.
    Micromachines (Basel), 2023 May 14;14(5).
    PMID: 37241671 DOI: 10.3390/mi14051048
    We investigate the dynamics of high energy dual regime unidirectional Erbium-doped fiber laser in ring cavity, which is passively Q-switched and mode-locked through the use of an environmentally friendly graphene filament-chitin film-based saturable absorber. The graphene-chitin passive saturable absorber allows the option for different operating regimes of the laser by simple adjustment of the input pump power, yielding, simultaneously, highly stable and high energy Q-switched pulses at 82.08 nJ and 1.08 ps mode-locked pulses. The finding can have applications in a multitude of fields due to its versatility and the regime of operation that is on demand.
  7. CT Reconstruction Algorithm and Low Contrast Detectability of Phantom Study: A Systematic Review and Meta-Analysis
    Adibah Yusof NA, Abdul Karim MK, Asikin NM, Paiman S, Awang Kechik MM, Abdul Rahman MA, et al.
    Curr Med Imaging, 2023;19(10):1105-1113.
    PMID: 35975862 DOI: 10.2174/1573405618666220816160544
    BACKGROUND: For almost three decades, computed tomography (CT) has been extensively used in medical diagnosis, which led researchers to conduct linking of CT dose exposure with image quality.

    METHODS: In this study, a systematic review and a meta-analysis study were conducted on CT phantom for resolution study especially based on the low contrast detectability (LCD). Furthermore, the association between the CT parameter such as tube voltage and the type of reconstruction algorithm, the amount of phantom scanning affecting the image quality and the exposure dose were also investigated in this study. We utilize PubMed, ScienceDirect, Google Scholar and Scopus databases to search related published articles from the year 2011 until 2020. The notable keywords comprise "computed tomography", "CT phantom", and "low contrast detectability". Of 52 articles, 20 articles are within the inclusion criteria in this systematic review.

    RESULTS: The dichotomous outcomes were chosen to represent the results in terms of risk ratio as per meta-analysis study. Notably, the noise in iterative reconstruction (IR) reduced by 24%, 33% and 36% with the use of smooth, medium and sharp filters, respectively. Furthermore, adaptive iterative dose reduction (AIDR 3D) improved image quality and the visibility of smaller less dense objects compared to filtered back-projection. Most of the researchers used 120 kVp tube voltage to scan phantom for quality assurance study.

    CONCLUSION: Hence, optimizing primary factors such as tube potential reduces the dose exposure significantly, and the optimized IR technique could substantially reduce the radiation dose while maintaining the image quality.

  8. Fulltext Role of neurotoxicants in the pathogenesis of Alzheimer's disease: a mechanistic insight
    Nisa FY, Rahman MA, Hossen MA, Khan MF, Khan MAN, Majid M, et al.
    Ann Med, 2021 Dec;53(1):1476-1501.
    PMID: 34433343 DOI: 10.1080/07853890.2021.1966088
    Alzheimer's disease (AD) is the most conspicuous chronic neurodegenerative syndrome, which has become a significant challenge for the global healthcare system. Multiple studies have corroborated a clear association of neurotoxicants with AD pathogenicity, such as Amyloid beta (Aβ) proteins and neurofibrillary tangles (NFTs), signalling pathway modifications, cellular stress, cognitive dysfunctions, neuronal apoptosis, neuroinflammation, epigenetic modification, and so on. This review, therefore, aimed to address several essential mechanisms and signalling cascades, including Wnt (wingless and int.) signalling pathway, autophagy, mammalian target of rapamycin (mTOR), protein kinase C (PKC) signalling cascades, cellular redox status, energy metabolism, glutamatergic neurotransmissions, immune cell stimulations (e.g. microglia, astrocytes) as well as an amyloid precursor protein (APP), presenilin-1 (PSEN1), presenilin-2 (PSEN2) and other AD-related gene expressions that have been pretentious and modulated by the various neurotoxicants. This review concluded that neurotoxicants play a momentous role in developing AD through modulating various signalling cascades. Nevertheless, comprehension of this risk agent-induced neurotoxicity is far too little. More in-depth epidemiological and systematic investigations are needed to understand the potential mechanisms better to address these neurotoxicants and improve approaches to their risk exposure that aid in AD pathogenesis.Key messagesInevitable cascade mechanisms of how Alzheimer's Disease-related (AD-related) gene expressions are modulated by neurotoxicants have been discussed.Involvement of the neurotoxicants-induced pathways caused an extended risk of AD is explicited.Integration of cell culture, animals and population-based analysis on the clinical severity of AD is addressed.
  9. Fulltext A hybrid multi objective cellular spotted hyena optimizer for wellbore trajectory optimization
    Biswas K, Nazir A, Rahman MT, Khandaker MU, Idris AM, Islam J, et al.
    PLoS One, 2022;17(1):e0261427.
    PMID: 35085239 DOI: 10.1371/journal.pone.0261427
    Cost and safety are critical factors in the oil and gas industry for optimizing wellbore trajectory, which is a constrained and nonlinear optimization problem. In this work, the wellbore trajectory is optimized using the true measured depth, well profile energy, and torque. Numerous metaheuristic algorithms were employed to optimize these objectives by tuning 17 constrained variables, with notable drawbacks including decreased exploitation/exploration capability, local optima trapping, non-uniform distribution of non-dominated solutions, and inability to track isolated minima. The purpose of this work is to propose a modified multi-objective cellular spotted hyena algorithm (MOCSHOPSO) for optimizing true measured depth, well profile energy, and torque. To overcome the aforementioned difficulties, the modification incorporates cellular automata (CA) and particle swarm optimization (PSO). By adding CA, the SHO's exploration phase is enhanced, and the SHO's hunting mechanisms are modified with PSO's velocity update property. Several geophysical and operational constraints have been utilized during trajectory optimization and data has been collected from the Gulf of Suez oil field. The proposed algorithm was compared with the standard methods (MOCPSO, MOSHO, MOCGWO) and observed significant improvements in terms of better distribution of non-dominated solutions, better-searching capability, a minimum number of isolated minima, and better Pareto optimal front. These significant improvements were validated by analysing the algorithms in terms of some statistical analysis, such as IGD, MS, SP, and ER. The proposed algorithm has obtained the lowest values in IGD, SP and ER, on the other side highest values in MS. Finally, an adaptive neighbourhood mechanism has been proposed which showed better performance than the fixed neighbourhood topology such as L5, L9, C9, C13, C21, and C25. Hopefully, this newly proposed modified algorithm will pave the way for better wellbore trajectory optimization.
  10. Fulltext Machine learning-based technique for gain and resonance prediction of mid band 5G Yagi antenna
    Haque MA, Rahman MA, Al-Bawri SS, Yusoff Z, Sharker AH, Abdulkawi WM, et al.
    Sci Rep, 2023 Aug 03;13(1):12590.
    PMID: 37537201 DOI: 10.1038/s41598-023-39730-1
    In this study, we present our findings from investigating the use of a machine learning (ML) technique to improve the performance of Quasi-Yagi-Uda antennas operating in the n78 band for 5G applications. This research study investigates several techniques, such as simulation, measurement, and an RLC equivalent circuit model, to evaluate the performance of an antenna. In this investigation, the CST modelling tools are used to develop a high-gain, low-return-loss Yagi-Uda antenna for the 5G communication system. When considering the antenna's operating frequency, its dimensions are [Formula: see text]. The antenna has an operating frequency of 3.5 GHz, a return loss of [Formula: see text] dB, a bandwidth of 520 MHz, a maximum gain of 6.57 dB, and an efficiency of almost 97%. The impedance analysis tools in CST Studio's simulation and circuit design tools in Agilent ADS software are used to derive the antenna's equivalent circuit (RLC). We use supervised regression ML method to create an accurate prediction of the frequency and gain of the antenna. Machine learning models can be evaluated using a variety of measures, including variance score, R square, mean square error, mean absolute error, root mean square error, and mean squared logarithmic error. Among the nine ML models, the prediction result of Linear Regression is superior to other ML models for resonant frequency prediction, and Gaussian Process Regression shows an extraordinary performance for gain prediction. R-square and var score represents the accuracy of the prediction, which is close to 99% for both frequency and gain prediction. Considering these factors, the antenna can be deemed an excellent choice for the n78 band of a 5G communication system.
  11. Mechanistic insight into immunomodulatory effects of food-functioned plant secondary metabolites
    Ali Reza ASM, Nasrin MS, Hossen MA, Rahman MA, Jantan I, Haque MA, et al.
    Crit Rev Food Sci Nutr, 2023;63(22):5546-5576.
    PMID: 34955042 DOI: 10.1080/10408398.2021.2021138
    Medicinally important plant-foods offer a balanced immune function, which is essential for protecting the body against antigenic invasion, mainly by microorganisms. Immunomodulators play pivotal roles in supporting immune function either suppressing or stimulating the immune system's response to invading pathogens. Among different immunomodulators, plant-based secondary metabolites have emerged as high potential not only for immune defense but also for cellular immunoresponsiveness. These natural immunomodulators can be developed into safer alternatives to the clinically used immunosuppressants and immunostimulant cytotoxic drugs which possess serious side effects. Many plants of different species have been reported to possess strong immunomodulating properties. The immunomodulatory effects of plant extracts and their bioactive metabolites have been suggested due to their diverse mechanisms of modulation of the complex immune system and their multifarious molecular targets. Phytochemicals such as alkaloids, flavonoids, terpenoids, carbohydrates and polyphenols have been reported as responsible for the immunomodulatory effects of several medicinal plants. This review illustrates the potent immunomodulatory effects of 65 plant secondary metabolites, including dietary compounds and their underlying mechanisms of action on cellular and humoral immune functions in in vitro and in vivo studies. The clinical potential of some of the compounds to be used for various immune-related disorders is highlighted.
  12. Fulltext Mechanical versus manual cardiopulmonary resuscitation (CPR): an umbrella review of contemporary systematic reviews and more
    El-Menyar A, Naduvilekandy M, Rizoli S, Di Somma S, Cander B, Galwankar S, et al.
    Crit Care, 2024 Jul 30;28(1):259.
    PMID: 39080740 DOI: 10.1186/s13054-024-05037-4
    BACKGROUND: High-quality cardiopulmonary resuscitation (CPR) can restore spontaneous circulation (ROSC) and neurological function and save lives. We conducted an umbrella review, including previously published systematic reviews (SRs), that compared mechanical and manual CPR; after that, we performed a new SR of the original studies that were not included after the last published SR to provide a panoramic view of the existing evidence on the effectiveness of CPR methods.

    METHODS: PubMed, EMBASE, and Medline were searched, including English in-hospital (IHCA) and out-of-hospital cardiac arrest (OHCA) SRs, and comparing mechanical versus manual CPR. A Measurement Tool to Assess Systematic Reviews (AMSTAR-2) and GRADE were used to assess the quality of included SRs/studies. We included both IHCA and OHCA, which compared mechanical and manual CPR. We analyzed at least one of the outcomes of interest, including ROSC, survival to hospital admission, survival to hospital discharge, 30-day survival, and survival to hospital discharge with good neurological function. Furthermore, subgroup analyses were performed for age, gender, initial rhythm, arrest location, and type of CPR devices.

    RESULTS: We identified 249 potentially relevant records, of which 238 were excluded. Eleven SRs were analyzed in the Umbrella review (January 2014-March 2022). Furthermore, for a new, additional SR, we identified eight eligible studies (not included in any prior SR) for an in-depth analysis between April 1, 2021, and February 15, 2024. The higher chances of using mechanical CPR for male patients were significantly observed in three studies. Two studies showed that younger patients received more mechanical treatment than older patients. However, studies did not comment on the outcomes based on the patient's gender or age. Most SRs and studies were of low to moderate quality. The pooled findings did not show the superiority of mechanical compared to manual CPR except in a few selected subgroups.

    CONCLUSIONS: Given the significant heterogeneity and methodological limitations of the included studies and SRs, our findings do not provide definitive evidence to support the superiority of mechanical CPR over manual CPR. However, mechanical CPR can serve better where high-quality manual CPR cannot be performed in selected situations.

  13. Arsenic adsorption mechanism on palm oil fuel ash (POFA) powder suspension
    Yusof MSM, Othman MHD, Wahab RA, Jumbri K, Razak FIA, Kurniawan TA, et al.
    J Hazard Mater, 2020 02 05;383:121214.
    PMID: 31546216 DOI: 10.1016/j.jhazmat.2019.121214
    The contribution of palm oil fuel ash (POFA), an agricultural waste as a low cost adsorbent for the removal of arsenite (As(III)) and arsenate (As(V)) was explored. Investigation on the adsorbency characteristics of POFA suspension revealed that the surface area, particle size, composition, and crystallinity of the SiO2 rich mullite structure were the crucial factors in ensuring a high adsorption capacity of the ions. Maximum adsorption capacities of As(III) and As(V) at 91.2 and 99.4 mg g-1, respectively, were obtained when POFA of 30 μm particle size was employed at pH 3 with the highest calcination temperature at 1150 °C. An optimum dosage of 1.0 g of dried POFA powder successfully removed 48.7% and 50.2% of As(III) and As(V), respectively. Molecular modeling using the density functional theory consequently identified the energy for the proposed reaction routes between the SiO- and As+ species. The high stability of the POFA suspension in water in conjunction with good adsorption capacity of As(III) and As(V) seen in this study, thus envisages its feasibility as a potential alternative absorbent for the remediation of water polluted with heavy metals.
  14. Anti-diarrheal activities of phytol along with its possible mechanism of action through in-vivo and in-silico models
    Islam MT, Rahman MA, Saeed M, Ul-Haq Z, Alam MJ, Mondal M, et al.
    Cell Mol Biol (Noisy-le-grand), 2020 Jun 25;66(4):243-249.
    PMID: 32583783
    Phytol (PHY), a chlorophyll-derived diterpenoid, exhibits numerous pharmacological properties, including antioxidant, antimicrobial, and anticancer activities. This study evaluates the anti-diarrheal effect of phytol (PHY) along with its possible mechanism of action through in-vivo and in-silico models. The effect of PHY was investigated on castor oil-induced diarrhea in Swiss mice by using prazosin, propranolol, loperamide, and nifedipine as standards with or without PHY. PHY at 50 mg/kg (p.o.) and all other standards exhibit significant (p < 0.05) anti-diarrheal effect in mice. The effect was prominent in the loperamide and propranolol groups. PHY co-treated with prazosin and propranolol was found to increase in latent periods along with a significant reduction in diarrheal section during the observation period than other individual or combined groups. Furthermore, molecular docking studies also suggested that PHY showed better interactions with the α- and β-adrenergic receptors, especially with α-ADR1a and β-ADR1. In the former case, PHY showed interaction with hydroxyl group of Ser192 at a distance of 2.91Å, while in the latter it showed hydrogen bond interactions with Thr170 and Lys297 with a distance of 2.65 and 2.72Å, respectively. PHY exerted significant anti-diarrheal effect in Swiss mice, possibly through blocking α- and β-adrenergic receptors.
  15. Fulltext Psychological distress, fear and coping among Malaysians during the COVID-19 pandemic
    Bahar Moni AS, Abdullah S, Bin Abdullah MFIL, Kabir MS, Alif SM, Sultana F, et al.
    PLoS One, 2021;16(9):e0257304.
    PMID: 34506576 DOI: 10.1371/journal.pone.0257304
    INTRODUCTION: The COVID-19 pandemic has enormously affected the psychological well-being, social and working life of millions of people across the world. This study aimed to investigate the psychological distress, fear and coping strategies as a result of the COVID-19 pandemic and its associated factors among Malaysian residents.

    METHODS: Participants were invited to an online cross-sectional survey from Aug-Sep 2020. The study assessed psychological distress using the Kessler Psychological Distress Scale, level of fear using the Fear of COVID-19 Scale, and coping strategies using the Brief Resilient Coping Scale. Univariate and multivariate logistic regression analyses were conducted to adjust for potential confounders.

    RESULTS: The mean age (±SD) of the participants (N = 720) was 31.7 (±11.5) years, and most of them were females (67.1%). Half of the participants had an income source, while 216 (30%) identified themselves as frontline health or essential service workers. People whose financial situation was impacted due to COVID-19 (AOR 2.16, 95% CIs 1.54-3.03), people who drank alcohol in the last four weeks (3.43, 1.45-8.10), people who were a patient (2.02, 1.39-2.93), and had higher levels of fear of COVID-19 (2.55, 1.70-3.80) were more likely to have higher levels of psychological distress. Participants who self-isolated due to exposure to COVID-19 (3.12, 1.04-9.32) and who had moderate to very high levels of psychological distress (2.56, 1.71-3.83) had higher levels of fear. Participants who provided care to a family member/patient with a suspected case of COVID-19 were more likely to be moderately to highly resilient compared to those who did not.

    CONCLUSION: Vulnerable groups of individuals such as patients and those impacted financially during COVID-19 should be supported for their mental wellbeing. Behavioural interventions should be targeted to reduce the impact of alcohol drinking during such crisis period.

  16. Photocatalytic degradation of oilfield produced water using graphitic carbon nitride embedded in electrospun polyacrylonitrile nanofibers
    Alias NH, Jaafar J, Samitsu S, Yusof N, Othman MHD, Rahman MA, et al.
    Chemosphere, 2018 Aug;204:79-86.
    PMID: 29653325 DOI: 10.1016/j.chemosphere.2018.04.033
    Separation and purification of oilfield produced water (OPW) is a major environmental challenge due to the co-production of the OPW during petroleum exploration and production operations. Effective capture of oil contaminant and its in-situ photodegradation is one of the promising methods to purify the OPW. Based on the photocatalytic capability of graphitic carbon nitride (GCN) which was recently rediscovered, photodegradation capability of GCN for OPW was investigated in this study. GCN was synthesized by calcination of urea and further exfoliated into nanosheets. The GCNs were incorporated into polyacrylonitrile nanofibers using electrospinning, which gave a liquid-permeable self-supporting photocatalytic nanofiber mat that can be handled by hand. The photocatalytic nanofiber demonstrated 85.4% degradation of OPW under visible light irradiation, and improved the degradation to 96.6% under UV light. Effective photodegradation of the photocatalytic nanofiber for OPW originates from synergetic effects of oil adsorption by PAN nanofibers and oil photodegradation by GCNs. This study provides an insight for industrial application on purification of OPW through photocatalytic degradation under solar irradiation.
  17. Psychological Impact of COVID-19 Pandemic in Bangladesh: Analysis of a Cross-Sectional Survey
    Abir T, Osuagwu UL, Kalimullah NA, Yazdani DMN, Husain T, Basak P, et al.
    Health Secur, 2021 08 03;19(5):468-478.
    PMID: 34348050 DOI: 10.1089/hs.2020.0205
    The COVID-19 pandemic has generated fear, panic, distress, anxiety, and depression among many people in Bangladesh. In this cross-sectional study, we examined factors associated with different levels of psychological impact as a result of COVID-19 in Bangladesh. From April 1 to 30, 2020, we used a self-administered online questionnaire to collect data from 10,609 respondents. Using the Impact of Event Scale-Revised to assess the psychological impact of the COVID-19 pandemic on respondents, we categorized the levels of impact as normal, mild, moderate, or severe. Ordinal logistic regression was used to examine the associated factors. The prevalence of mild, moderate, and severe psychological impact was 10.2%, 4.8%, and 45.5%, respectively. Multivariate analysis revealed that the odds of reporting normal vs mild, moderate, or severe psychological impact were 5.9 times higher for people living in the Chittagong Division, 1.7 times higher for women with lower education levels, 3.0 times higher among those who were divorced or separated, 1.8 times higher for those working full time, and 2.4 times higher for those living in shared apartments. The odds of reporting a psychological impact were also higher among people who did not enforce protective measures inside the home, those in self-quarantine, those who did not wear face masks, and those who did not comply with World Health Organization precautionary measures. Increased psychological health risks due to COVID-19 were significantly higher among people who experienced chills, headache, cough, breathing difficulties, dizziness, and sore throat before data collection. Our results showed that 1 in 2 respondents experienced a significant psychological impact as a result of the COVID-19 pandemic. Public health researchers should consider these factors when targeting interventions that would have a protective effect on the individual's psychological health during a pandemic or future disease outbreak.
  18. Oilfield-produced water treatment using conventional and membrane-based technologies for beneficial reuse: A critical review
    Samuel O, Othman MHD, Kamaludin R, Sinsamphanh O, Abdullah H, Puteh MH, et al.
    J Environ Manage, 2022 Feb 03;308:114556.
    PMID: 35124308 DOI: 10.1016/j.jenvman.2022.114556
    Oilfield produced water (OPW) is one of the most important by-products, resulting from oil and gas exploration. The water contains a complex mixture of organic and inorganic compounds such as grease, dissolved salt, heavy metals as well as dissolved and dispersed oils, which can be toxic to the environment and public health. This article critically reviews the complex properties of OPW and various technologies for its treatment. They include the physico-chemical treatment process, biological treatment process, and physical treatment process. Their technological strengths and bottlenecks as well as strategies to mitigate their bottlenecks are elaborated. A particular focus is placed on membrane technologies. Finally, further research direction, challenges, and perspectives of treatment technologies for OPW are discussed. It is conclusively evident from 262 published studies (1965-2021) that no single treatment method is highly effective for OPW treatment as a stand-alone process however, conventional membrane-based technologies are frequently used for the treatment of OPW with the ultrafiltration (UF) process being the most used for oil rejection form OPW and oily waste water. After membrane treatment, treated effluents of the OPW could be reused for irrigation, habitant and wildlife watering, microalgae production, and livestock watering. Overall, this implies that target pollutants in the OPW samples could be removed efficiently for subsequent use, despite its complex properties. In general, it is however important to note that feed quality, desired quality of effluent, cost-effectiveness, simplicity of process are key determinants in choosing the most suitable treatment process for OPW treatment.
  19. Fulltext Optimization of a High-Performance Poly(diallyl dimethylammonium chloride)-alumina-perfluorooctanoate Intercalated Ultrafiltration Membrane for Treating Emulsified Oily Wastewater via Response Surface Methodology Approach
    Raji YO, Othman MHD, Nordin NAHSM, Adam MR, Said KAM, Abdulyekeen KA, et al.
    Membranes (Basel), 2021 Dec 01;11(12).
    PMID: 34940457 DOI: 10.3390/membranes11120956
    This research aimed to investigate the ultrafiltration of water from emulsified oily wastewater through the application of surface-functionalized ceramic membrane to enhance its water permeability based on optimized parameters using a cross-flow filtration system. The interactive effects of feed concentration (10-1000 ppm), pH (4-10), and pressure (0-3 bar) on the water flux and oil rejection were investigated. Central composite design (CCD) from response surface methodology (RSM) was employed for statistical analysis, modeling, and optimization of operating conditions. The analysis of variance (ANOVA) results showed that the oil rejection and water flux models were significant with p-values of 0.0001 and 0.0075, respectively. In addition, good correlation coefficients of 0.997 and 0.863 were obtained for the oil rejection and water flux models, respectively. The optimum conditions for pressure, pH, and feed concentration were found to be 1.5 bar, pH 8.97, and 10 ppm, respectively with water flux and oil rejection maintained at 152 L/m2·h and 98.72%, respectively. Hence, the functionalized ultrafiltration ceramic membrane enables the separation efficiency of the emulsified oil in water to be achieved.
  20. Fulltext Optimized Intelligent Classifier for Early Breast Cancer Detection Using Ultra-Wide Band Transceiver
    Halim AAA, Andrew AM, Mustafa WA, Mohd Yasin MN, Jusoh M, Veeraperumal V, et al.
    Diagnostics (Basel), 2022 Nov 19;12(11).
    PMID: 36428930 DOI: 10.3390/diagnostics12112870
    Breast cancer is the most common cancer diagnosed in women and the leading cause of cancer-related deaths among women worldwide. The death rate is high because of the lack of early signs. Due to the absence of a cure, immediate treatment is necessary to remove the cancerous cells and prolong life. For early breast cancer detection, it is crucial to propose a robust intelligent classifier with statistical feature analysis that considers parameter existence, size, and location. This paper proposes a novel Multi-Stage Feature Selection with Binary Particle Swarm Optimization (MSFS-BPSO) using Ultra-Wideband (UWB). A collection of 39,000 data samples from non-tumor and with tumor sizes ranging from 2 to 7 mm was created using realistic tissue-like dielectric materials. Subsequently, the tumor models were inserted into the heterogeneous breast phantom. The breast phantom with tumors was imaged and represented in both time and frequency domains using the UWB signal. Consequently, the dataset was fed into the MSFS-BPSO framework and started with feature normalization before it was reduced using feature dimension reduction. Then, the feature selection (based on time/frequency domain) using seven different classifiers selected the frequency domain compared to the time domain and continued to perform feature extraction. Feature selection using Analysis of Variance (ANOVA) is able to distinguish between class-correlated data. Finally, the optimum feature subset was selected using a Probabilistic Neural Network (PNN) classifier with the Binary Particle Swarm Optimization (BPSO) method. The research findings found that the MSFS-BPSO method has increased classification accuracy up to 96.3% and given good dependability even when employing an enormous data sample.
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