Displaying publications 41 - 60 of 2380 in total

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  1. Bostan Ali W, Olayinka JA, Alam MM, Immelman A
    PLoS One, 2024;19(2):e0294890.
    PMID: 38349933 DOI: 10.1371/journal.pone.0294890
    Micro, Small, and Medium-sized Enterprises (MSMEs) in Thailand were assessed in this study to determine the short-term and long-term economic effects of post-COVID- 19 -, with the goal of developing policy guidelines that focus on the methods and strategies that will further develop and help recover these sectors. MSMEs are the most vulnerable and require assistants to combat the pandemic. This study assesses the perspectives of stakeholders on the development of mechanisms and the strategies applied to support vulnerable groups in Thailand, which mostly consist of women and children. The main data collection was gathered through online questionnaires that were distributed to various stakeholder groups. The tools used for analysis were advanced quantitative analysis tools that aid in achieving this research study's objectives, and data was examined primarily through the usage of path modeling, structural equation modeling (SEM), and descriptive analysis was among the methods used. The findings reveal that in the short term, MSMEs' ability to respond to COVID-19 implications has a significant impact on both financial and non-financial performance. Non-financial performance, on the other hand, is more affected by adaptability than financial performance. Demand shock from lockdowns and other COVID-19 cautionary interventions has a negative and significant impact on MSMEs' adaptability, financial performance, and non-financial performance. The demand shocks increased the vulnerability of MSMEs significantly but it was found that proper management of demand shock has helped stabilized and improve MSMEs' financial and non-financial performances, as well as helped decrease their vulnerability. When it comes to government policy, the focus is usually on enhancing the flexibility and financial performance of MSMEs. The government's legislative actions have little impact on MSMEs' non-financial performance and vulnerability. This could be because the majority of the programs are more focused on providing financial assistance to businesses or their consumers. COVID-19's supply and demand shock only hindered MSMEs' ability to respond to the changes and challenges caused by the pandemic, according to vendors. The vulnerability of MSMEs caused by COVID-19 creates grave effects on their financial performance. The findings of this research paper will assist policymakers in identifying the most vulnerable aspects of MSMEs, as well as their expectations- and determine the forms of support that will be required to combat the current and future pandemic situations that may occur in Thailand. In addition, it will aid policymakers in the establishment of procedures and supporting strategies for MSMEs to reduce the unemployment rate and stimulate the Thai economy, among other factors of improvement.
  2. Brady SM, Salway R, Mariapun J, Millard L, Ramadas A, Rizal H, et al.
    PLoS One, 2024;19(2):e0297102.
    PMID: 38377079 DOI: 10.1371/journal.pone.0297102
    BACKGROUND: Quantifying movement behaviours over 24-hours enables the combined effects of and inter-relations between sleep, sedentary time and physical activity (PA) to be understood. This is the first study describing 24-hour movement behaviours in school-aged children and adolescents in South-East Asia. Further aims were to investigate between-participant differences in movement behaviours by demographic characteristics and timing of data collection during Ramadan and COVID-19 restrictions.

    METHODS: Data came from the South-East Asia Community Observatory health surveillance cohort, 2021-2022. Children aged 7-18 years within selected households in Segamat, Malaysia wore an Axivity AX6 accelerometer on their wrist for 24 hours/day over 7 days, completed the PAQ-C questionnaire, and demographic information was obtained. Accelerometer data was processed using GGIR to determine time spent asleep, inactive, in light-intensity PA (LPA) and moderate-to-vigorous PA (MVPA). Differences in accelerometer-measured PA by demographic characteristics (sex, age, ethnicity, socioeconomic group) were explored using univariate linear regression. Differences between data collected during vs outside Ramadan or during vs after COVID-19 restrictions, were investigated through univariate and multiple linear regressions, adjusted for age, sex and ethnicity.

    RESULTS: The 491 participants providing accelerometer data spent 8.2 (95% confidence interval (CI) = 7.9-8.4) hours/day asleep, 12.4 (95% CI = 12.2-12.7) hours/day inactive, 2.8 (95% CI = 2.7-2.9) hours/day in LPA, and 33.0 (95% CI = 31.0-35.1) minutes/day in MVPA. Greater PA and less time inactive were observed in boys vs girls, children vs adolescents, Indian and Chinese vs Malay children and higher income vs lower income households. Data collection during Ramadan or during COVID-19 restrictions were not associated with MVPA engagement after adjustment for demographic characteristics.

    CONCLUSIONS: Demographic characteristics remained the strongest correlates of accelerometer-measured 24-hour movement behaviours in Malaysian children and adolescents. Future studies should seek to understand why predominantly girls, adolescents and children from Malay ethnicities have particularly low movement behaviours within Malaysia.

  3. He Y, Tom Abdul Wahab NE, Muhamad H, Liu D
    PLoS One, 2024;19(2):e0296910.
    PMID: 38381720 DOI: 10.1371/journal.pone.0296910
    BACKGROUND: With the evolution of China's social structure and values, there has been a shift in attitudes towards marriage and fertility, with an increasing number of women holding diverse perspectives on these matters. In order to better comprehend the fundamental reasons behind these attitude changes and to provide a basis for targeted policymaking, this study employs natural language processing techniques to analyze the discourse of Chinese women.

    METHODS: The study focused on analyzing 3,200 comments from Weibo, concentrating on six prominent topics linked to women's marriage and fertility. These topics were treated as research cases. The research employed natural language processing techniques, such as sentiment orientation analysis, Word2Vec, and TextRank.

    RESULTS: Firstly, the overall sentiment orientation of Chinese women toward marriage and fertility was largely pessimistic. Secondly, the factors contributing to this negative sentiment were categorized into four dimensions: social policies and rights protection, concerns related to parenting, values and beliefs associated with marriage and fertility, and family and societal culture.

    CONCLUSION: Based on these outcomes, the study proposed a range of mechanisms and pathways to enhance women's sentiment orientation towards marriage and fertility. These mechanisms encompass safeguarding women and children's rights, promoting parenting education, providing positive guidance on social media, and cultivating a diverse and inclusive social and cultural environment. The objective is to offer precise and comprehensive reference points for the formulation of policies that align more effectively with practical needs.

  4. Ledger MJ, Sowter A, Morrison K, Evans CD, Large DJ, Athab A, et al.
    PLoS One, 2024;19(2):e0298939.
    PMID: 38394278 DOI: 10.1371/journal.pone.0298939
    Tropical peatland across Southeast Asia is drained extensively for production of pulpwood, palm oil and other food crops. Associated increases in peat decomposition have led to widespread subsidence, deterioration of peat condition and CO2 emissions. However, quantification of subsidence and peat condition from these processes is challenging due to the scale and inaccessibility of dense tropical peat swamp forests. The development of satellite interferometric synthetic aperture radar (InSAR) has the potential to solve this problem. The Advanced Pixel System using Intermittent Baseline Subset (APSIS, formerly ISBAS) modelling technique provides improved coverage across almost all land surfaces irrespective of ground cover, enabling derivation of a time series of tropical peatland surface oscillations across whole catchments. This study aimed to establish the extent to which APSIS-InSAR can monitor seasonal patterns of tropical peat surface oscillations at North Selangor Peat Swamp Forest, Peninsular Malaysia. Results showed that C-band SAR could penetrate the forest canopy over tropical peat swamp forests intermittently and was applicable to a range of land covers. Therefore the APSIS technique has the potential for monitoring peat surface oscillations under tropical forest canopy using regularly acquired C-band Sentinel-1 InSAR data, enabling continuous monitoring of tropical peatland surface motion at a spatial resolution of 20 m.
  5. Adeleke AO, Royahu CO, Ahmad A, Dele-Afolabi TT, Alshammari MB, Imteaz M
    PLoS One, 2024;19(2):e0294286.
    PMID: 38386950 DOI: 10.1371/journal.pone.0294286
    This study highlights the effectiveness of oyster shell biocomposite for the biosorption of Cd(II) and Pb(II) ions from an aqueous solution. The aim of this work was to modify a novel biocomposite derived from oyster shell for the adsorption of Cd(II) and Pb(II) ions from aqueous solution. The studied revealed the specific surface BET surface area was 9.1476 m2/g. The elemental dispersive x-ray analysis (EDS) indicated that C, O, Ag, Ca were the predominant elements on the surface of the biocomposite after which metals ions of Cd and Pb were noticed after adsorption. The Fourier transform Irradiation (FT-IR) revealed the presence of carboxyl and hydroxyl groups on the surface. The effect of process variables on the adsorption capacity of the modified biocomposite was examined using the central composite design (CCD) of the response surface methodology (RSM). The process variables which include pH, adsorbent dose, the initial concentration and temperature were the most effective parameters influencing the uptake capacity. The optimal process conditions of these parameters were found to be pH, 5.57, adsorbent dose, 2.53 g/L, initial concentration, 46.76 mg/L and temperature 28.48°C for the biosorption of Cd(II) and Pb(II) ions from aqueous solution at a desirability coefficient of 1. The analysis of variance (ANOVA) revealed a high coefficient of determination (R2 > 0.91) and low probability coefficients for the responses (P < 0.05) which indicated the validity and aptness of the model for the biosorption of the metal ions. Experimental isotherm data fitted better to the Langmuir model and the kinetic data fitted better to the pseudo-second-order model. Maximun Cd(II) and Pb(II) adsorption capacities of the oyster shell biocomposite were 97.54 and 78.99 mg/g respectively and was obtained at pH 5.56 and 28.48°C. This investigation has provided the possibility of the utilization of alternative biocomposite as a sustainable approach for the biosorption of heavy metal ions from the wastewater stream.
  6. Posos-Parra O, Mota-Sanchez D, Pittendrigh BR, Wise JC, DiFonzo CD, Patterson E
    PLoS One, 2024;19(2):e0295928.
    PMID: 38394153 DOI: 10.1371/journal.pone.0295928
    The fall armyworm (Spodoptera frugiperda) is one of the most destructive pests of corn. New infestations have been reported in the East Hemisphere, reaching India, China, Malaysia, and Australia, causing severe destruction to corn and other crops. In Puerto Rico, practical resistance to different mode of action compounds has been reported in cornfields. In this study, we characterized the inheritance of resistance to chlorantraniliprole and flubendiamide and identified the possible cross-resistance to cyantraniliprole and cyclaniliprole. The Puerto Rican (PR) strain showed high levels of resistance to flubendiamide (RR50 = 2,762-fold) and chlorantraniliprole (RR50 = 96-fold). The inheritance of resistance showed an autosomal inheritance for chlorantraniliprole and an X-linked inheritance for flubendiamide. The trend of the dominance of resistance demonstrated an incompletely recessive trait for H1 (♂ SUS × ♀ PR) × and an incompletely dominant trait for H2 (♀ SUS × ♂ PR) × for flubendiamide and chlorantraniliprole. The PR strain showed no significant presence of detoxification enzymes (using synergists: PBO, DEF, DEM, and VER) to chlorantraniliprole; however, for flubendiamide the SR = 2.7 (DEM), SR = 3.2 (DEF) and SR = 7.6 (VER) indicated the role of esterases, glutathione S- transferases and ABC transporters in the metabolism of flubendiamide. The PR strain showed high and low cross-resistance to cyantraniliprole (74-fold) and cyclaniliprole (11-fold), respectively. Incomplete recessiveness might lead to the survival of heterozygous individuals when the decay of diamide residue occurs in plant tissues. These results highlight the importance of adopting diverse pest management strategies, including insecticide rotating to manage FAW populations in Puerto Rico and other continents.
  7. Bahari NI, Sutan R, Abdullah Mahdy Z
    PLoS One, 2024;19(2):e0297563.
    PMID: 38394134 DOI: 10.1371/journal.pone.0297563
    INTRODUCTION: The COVID-19 pandemic has exerted devastating effects on healthcare delivery systems, specifically those for pregnant women. The aim of this review was to determine the maternal perception of antenatal health care services during the COVID-19 pandemic critical phase.

    METHODS: Scopus, Web of Science, SAGE, and Ovid were systematically searched using the keywords "maternal", "COVID-19 pandemic", "maternal health service", and "maternal perception". Articles were eligible for inclusion if they were original articles, written in English, and published between January 1, 2020, and December 12, 2022. This review was performed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Eligible articles were assessed using the Mixed Methods Appraisal Tool. Thematic analysis was used for data synthesis.

    RESULTS: Of 2683 articles identified, 13 fulfilled the inclusion criteria and were included in the narrative synthesis. Five themes emerged regarding the determinants of maternal perception of antenatal healthcare services during the COVID-19 pandemic critical phase: lack of psychosocial support, poor maternal healthcare quality, poor opinion of virtual consultation, health structure adaptation failure to meet women's needs, and satisfaction with maternal health services.

    CONCLUSION: Maternal perception, specifically pregnant women's psychosocial and maternal health needs, should be focused on the continuation of maternal care during the COVID-19 pandemic. It is critical to identify the maternal perception of maternal health services during the pandemic to ensure health service equity in the "new normal" future.

  8. Husnain AU, Mokhtar N, Mohamed Shah NB, Dahari MB, Azmi AA, Iwahashi M
    PLoS One, 2024;19(2):e0296969.
    PMID: 38394180 DOI: 10.1371/journal.pone.0296969
    There are three primary objectives of this work; first: to establish a gas concentration map; second: to estimate the point of emission of the gas; and third: to generate a path from any location to the point of emission for UAVs or UGVs. A mountable array of MOX sensors was developed so that the angles and distances among the sensors, alongside sensors data, were utilized to identify the influx of gas plumes. Gas dispersion experiments under indoor conditions were conducted to train machine learning algorithms to collect data at numerous locations and angles. Taguchi's orthogonal arrays for experiment design were used to identify the gas dispersion locations. For the second objective, the data collected after pre-processing was used to train an off-policy, model-free reinforcement learning agent with a Q-learning policy. After finishing the training from the training data set, Q-learning produces a table called the Q-table. The Q-table contains state-action pairs that generate an autonomous path from any point to the source from the testing dataset. The entire process is carried out in an obstacle-free environment, and the whole scheme is designed to be conducted in three modes: search, track, and localize. The hyperparameter combinations of the RL agent were evaluated through trial-and-error technique and it was found that ε = 0.9, γ = 0.9 and α = 0.9 was the fastest path generating combination that took 1258.88 seconds for training and 6.2 milliseconds for path generation. Out of 31 unseen scenarios, the trained RL agent generated successful paths for all the 31 scenarios, however, the UAV was able to reach successfully on the gas source in 23 scenarios, producing a success rate of 74.19%. The results paved the way for using reinforcement learning techniques to be used as autonomous path generation of unmanned systems alongside the need to explore and improve the accuracy of the reported results as future works.
  9. T A, G G, P AMD, Assaad M
    PLoS One, 2024;19(3):e0299653.
    PMID: 38478485 DOI: 10.1371/journal.pone.0299653
    Mechanical ventilation techniques are vital for preserving individuals with a serious condition lives in the prolonged hospitalization unit. Nevertheless, an imbalance amid the hospitalized people demands and the respiratory structure could cause to inconsistencies in the patient's inhalation. To tackle this problem, this study presents an Iterative Learning PID Controller (ILC-PID), a unique current cycle feedback type controller that helps in gaining the correct pressure and volume. The paper also offers a clear and complete examination of the primarily efficient neural approach for generating optimal inhalation strategies. Moreover, machine learning-based classifiers are used to evaluate the precision and performance of the ILC-PID controller. These classifiers able to forecast and choose the perfect type for various inhalation modes, eliminating the likelihood that patients will require mechanical ventilation. In pressure control, the suggested accurate neural categorization exhibited an average accuracy rate of 88.2% in continuous positive airway pressure (CPAP) mode and 91.7% in proportional assist ventilation (PAV) mode while comparing with the other classifiers like ensemble classifier has reduced accuracy rate of 69.5% in CPAP mode and also 71.7% in PAV mode. An average accuracy of 78.9% rate in other classifiers compared to neutral network in CPAP. The neural model had an typical range of 81.6% in CPAP mode and 84.59% in PAV mode for 20 cm H2O of volume created by the neural network classifier in the volume investigation. Compared to the other classifiers, an average of 72.17% was in CPAP mode, and 77.83% was in PAV mode in volume control. Different approaches, such as decision trees, optimizable Bayes trees, naive Bayes trees, nearest neighbour trees, and an ensemble of trees, were also evaluated regarding the accuracy by confusion matrix concept, training duration, specificity, sensitivity, and F1 score.
  10. Rosli NA, Al-Maleki AR, Loke MF, Tay ST, Rofiee MS, Teh LK, et al.
    PLoS One, 2024;19(3):e0298434.
    PMID: 38446753 DOI: 10.1371/journal.pone.0298434
    In H. pylori infection, antibiotic-resistance is one of the most common causes of treatment failure. Bacterial metabolic activities, such as energy production, bacterial growth, cell wall construction, and cell-cell communication, all play important roles in antimicrobial resistance mechanisms. Identification of microbial metabolites may result in the discovery of novel antimicrobial therapeutic targets and treatments. The purpose of this work is to assess H. pylori metabolomic reprogramming in order to reveal the underlying mechanisms associated with the development of clarithromycin resistance. Previously, four H. pylori isolates were induced to become resistant to clarithromycin in vitro by incrementally increasing the concentrations of clarithromycin. Bacterial metabolites were extracted using the Bligh and Dyer technique and analyzed using metabolomic fingerprinting based on Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry (LC-Q-ToF-MS). The data was processed and analyzed using the MassHunter Qualitative Analysis and Mass Profiler Professional software. In parental sensitivity (S), breakpoint isolates (B), and induced resistance isolates (R) H. pylori isolates, 982 metabolites were found. Furthermore, based on accurate mass, isotope ratios, abundances, and spacing, 292 metabolites matched the metabolites in the Agilent METLIN precise Mass-Personal Metabolite Database and Library (AM-PCDL). Several metabolites associated with bacterial virulence, pathogenicity, survival, and proliferation (L-leucine, Pyridoxone [Vitamine B6], D-Mannitol, Sphingolipids, Indoleacrylic acid, Dulcitol, and D-Proline) were found to be elevated in generated resistant H. pylori isolates when compared to parental sensitive isolates. The elevated metabolites could be part of antibiotics resistance mechanisms. Understanding the fundamental metabolome changes in the course of progressing from clarithromycin-sensitive to breakpoint to resistant in H. pylori clinical isolates may be a promising strategy for discovering novel alternatives therapeutic targets.
  11. Lim SK, Lee SWH
    PLoS One, 2024;19(3):e0296067.
    PMID: 38446815 DOI: 10.1371/journal.pone.0296067
    INTRODUCTION: Chronic kidney disease (CKD) is a global health concern which results in significant economic burden. Despite this, treatment options are limited. Recently, dapagliflozin has been reported have benefits in people with CKD. This study aimed to evaluate the cost-effectiveness of dapagliflozin as an add-on to standard of care (SoC) in people with CKD in Malaysia.

    METHODS: A Markov model was adapted to estimate the economic and clinical benefits of dapagliflozin in people with Stage 2 to 5 CKD. The cost-effectiveness was performed based upon data from the Dapagliflozin and Prevention of Adverse Outcomes in Chronic Kidney Disease (DAPA-CKD) trial supplemented with local costs and utility data whenever possible.

    RESULTS: In Malaysia, dapagliflozin in combination with SoC was the dominant intervention compared to SoC alone (RM 81,814 versus RM 85,464; USD19,762 vs USD20,644). Adding dapagliflozin to SoC in people with CKD increased life expectancy by 0.46 years and increased quality-adjusted life years (QALY) by 0.41 in comparison with SoC alone (10.01 vs. 9.55 years, 8.76 vs. 8.35 QALYs). This translates to a saving of RM8,894 (USD2,148) with every QALY gained. The benefits were due to the delay in CKD progression, resulting in lower costs of dialysis and renal transplantation. Results were robust to variations in assumptions over disease management costs as well as subgroup of population that would be treated and below the accepted willingness-to-pay thresholds of RM 46,000/QALY.

    CONCLUSION: The use of dapagliflozin was projected to improved life expectancy and quality of life among people with CKD, with a saving RM8,894 (USD2,148) for every quality-adjusted life-year gained and RM7,898 (USD1,908) saving for every life year gained.

  12. Zeng J, Liu W
    PLoS One, 2024;19(3):e0293156.
    PMID: 38446752 DOI: 10.1371/journal.pone.0293156
    Professional identity has become a central topic in teacher education research and a crucial factor in shaping teachers' self-perception and perspectives on various aspects of their profession, including teacher roles, scholarly research, curriculum design, classroom instruction, instructional methods, and strategies, as well as their interactions within the educational context. Despite the considerable scholarly interest in teacher identity development, relatively few studies have considered how to measure teacher professional identity. This study developed and validated a new measurement of professional identity among Chinese pre-service teachers from an English language education program. A total of 560 pre-service teachers majoring in English language education were invited to participate in a survey and 542 questionnaires were deemed valid and subjected to analysis. Through this analysis, a scale with 17 items was developed, focusing on three different dimensions: professional self-efficacy, career commitment, and professional knowledge. After excluding items with a relatively poor correlation with factor loading, the final scale consisted of 13 items. The results showed that the developed scale has relatively good reliability (α = 0.939) and structural validity (χ2/df = 2.46, p < .001, CFI = 0.978, TLI = 0.971, SRMR = 0.033, RMSEA (90% CI) = 0.071 0.054, 0.089). This study may provide a quantitative instrument for future research to measure professional identity among pre-service teachers, both in Chinese and other contexts.
  13. Haddad A, Habaebi MH, Elsheikh EAA, Islam MR, Zabidi SA, Suliman FEM
    PLoS One, 2024;19(4):e0301371.
    PMID: 38557695 DOI: 10.1371/journal.pone.0301371
    To secure sensitive medical records in the healthcare clouds, this paper proposes an End-to-End Encryption (E2EE) to enhance a patient-centric blockchain-based system for electronic health record (EHR) management. The suggested system with a focus on the patient enables individuals to oversee their medical records within various involved parties by authorizing or withdrawing permission for access to their records. Utilizing the inter-planetary file system (IPFS) for record storage is chosen due to its decentralized nature and its ability to guarantee the unchangeability of records. Then an E2EE enhancement maintains the medical data integrity using dual level-Hybrid encryption: symmetric Advanced Encryption Standard (AES) and asymmetric Elliptic Curve Cryptography (ECC) cryptographic techniques. The proposed system is implemented using the Ethereum blockchain system for EHR data sharing and integration utilizing a web-based interface for the patient and all users to initiate the EHR sharing transactions over the IPFS cloud. The proposed system performance is evaluated in a working system prototype. For different file sizes between 512 KB to 100 MB, the performance metrics used to evaluate the proposed system were the time consumed for generating key, encryption, and decryption. The results demonstrate the proposed system's superiority over other cutting-edge systems and its practical ability to share secure health data in cloud environments.
  14. Zhao X, Wider W, Zhang X, Fauzi MA, Wong CH, Jiang L, et al.
    PLoS One, 2024;19(3):e0297791.
    PMID: 38536845 DOI: 10.1371/journal.pone.0297791
    This cross-sectional study investigated the effects of value-based leadership and growth mindset on the intrinsic work motivation of Chinese lecturers. In addition, this study used age as a categorical moderator to investigate generational differences between the effects of Millennials and their predecessors. A sample of 518 lecturers from various Chinese universities was used to collect data, and SEM-PLS was used to analyse the data. The results showed that value-based leadership and growth mindset had a significant positive impact on both younger and older lecturers' intrinsic work motivation, with the effect of value-based leadership on younger lecturers' intrinsic motivation being significantly stronger than on older lecturers' intrinsic motivation, whereas the effect of growth mindset on intrinsic work motivation did not differ significantly between the younger and older groups. This study contributes to the existing research literature by contrasting the value-based leadership and growth mindset in relation to lecturers' intrinsic work motivation across younger and older groups in Chinese higher education settings, where greater heterogeneity between age groups was identified. The findings also provided university administrators with recommendations for boosting the intrinsic work motivation of lecturers, influencing future education policy.
  15. Bay SS, Kamaruzaman L, Mohd R, Azhar Shah S
    PLoS One, 2024;19(3):e0297378.
    PMID: 38536785 DOI: 10.1371/journal.pone.0297378
    INTRODUCTION: Chronic kidney disease (CKD) is a major public health issue with significant socioeconomic impacts. In Malaysia, the prevalence of CKD in 2018 was 15%. Complications of CKD such as anaemia, mineral bone disease, and infections led to frequent hospitalizations resulting in work disability and unemployment. To date, there is no data of employment status of CKD patients in Malaysia.

    METHODS: A cross-sectional study of patients with advanced CKD (stage 4 and 5 non-dialysis) treated in our centre. We interviewed those aged 18 to 60 years old who were selected based on random sampling of their employment status and associated factors. Work disabilities and quality of life were assessed using work productivity and activity impairment (WPAI-GH) questionnaire and kidney disease and quality of life (KDQOL-36) questionnaire. These questionnaires were assisted by the main investigators to aid participants in facilitating their response process.

    RESULT: A total of 318 patients recruited, 53.5% were males, with a mean age of 49.0 ± 9.0 years old. The main cause of CKD was diabetes (67.0%) followed by hypertension (11.3%). Majority of them were obese (55.3%) with a mean body mass index of 28.81 ± 6.3 kg/m2. The mean household income was RM 4669.50 ± 3034.75 (USD1006.27 ± 653.99). The employment rate was 50% (n = 159). 86% of the unemployed patients were in B40 income category. Multiple Logistic Regression was performed on the significant factors affecting employment status showed one year increase in age increased 6.5% odds to be unemployed. Female and dyslipidaemia had 2.24- and 2.58-times higher odds respectively to be unemployed. Meanwhile, patients with tertiary level of education were 81% less odds to be unemployed. Patients with advanced CKD had a mean percentage of 24.35 ± 15.23 work impairment and 13.36 ± 32.34 mean percentages of face absenteeism due to the disease burden. Furthermore, patients who were unemployed had significant perceived symptoms and problem lists, effects, and burden of kidney disease (p<0.01) and showed poor mental and physical composites (p<0.01) as compared with those who were employed.

    CONCLUSION: The employment rate of advanced CKD patients was low with half of patients lost their jobs due to the disease burden and had poor mental and physical composites of quality of life. This raises the concern for financial support for long term renal replacement therapy.

  16. Tariq MU, Ismail SB
    PLoS One, 2024;19(3):e0294289.
    PMID: 38483948 DOI: 10.1371/journal.pone.0294289
    The COVID-19 pandemic has had a significant impact on both the United Arab Emirates (UAE) and Malaysia, emphasizing the importance of developing accurate and reliable forecasting mechanisms to guide public health responses and policies. In this study, we compared several cutting-edge deep learning models, including Long Short-Term Memory (LSTM), bidirectional LSTM, Convolutional Neural Networks (CNN), hybrid CNN-LSTM, Multilayer Perceptron's, and Recurrent Neural Networks (RNN), to project COVID-19 cases in the aforementioned regions. These models were calibrated and evaluated using a comprehensive dataset that includes confirmed case counts, demographic data, and relevant socioeconomic factors. To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. The findings indicate that the selected deep learning algorithms were proficient in forecasting COVID-19 cases, although their efficacy varied across different models. After a thorough evaluation, the model architectures most suitable for the specific conditions in the UAE and Malaysia were identified. Our study contributes significantly to the ongoing efforts to combat the COVID-19 pandemic, providing crucial insights into the application of sophisticated deep learning algorithms for the precise and timely forecasting of COVID-19 cases. These insights hold substantial value for shaping public health strategies, enabling authorities to develop targeted and evidence-based interventions to manage the virus spread and its impact on the populations of the UAE and Malaysia. The study confirms the usefulness of deep learning methodologies in efficiently processing complex datasets and generating reliable projections, a skill of great importance in healthcare and professional settings.
  17. Yang L, Lei Y, Chu D, Jiang J, Li Z, Tang Y, et al.
    PLoS One, 2024;19(3):e0300040.
    PMID: 38483916 DOI: 10.1371/journal.pone.0300040
    INTRODUCTION: High levels of burnout are prevalent among Emergency Department staff due to chronic exposure to job stress. There is a lack of knowledge about anteceding factors and outcomes of burnout in this population.

    AIMS: To provide a comprehensive overview of burnout and identify its workplace antecedents and outcomes among Emergency Department staff.

    METHODS: The scoping study will follow the methodology outlined by the Joanna Briggs Institute. PubMed, Scopus, Web of Science, APA PsycInfo, and CINAHL databases will be searched using predefined strategies. Two reviewers will screen the title, abstract and full text separately based on the eligibility criteria. Data will be charted, coded, and narratively synthesized based on the job demands-resources model.

    CONCLUSION: The results will provide insights into the underlying work-related factors contributing to burnout and its implications for individuals, healthcare organizations, and patient care.

  18. Luu MN, Imoto A, Matsuo Y, Huy NT, Qarawi A, Alhady STM, et al.
    PLoS One, 2024;19(3):e0280144.
    PMID: 38489310 DOI: 10.1371/journal.pone.0280144
    INTRODUCTION: In the context of collective efforts taken in Japan to control the spread of COVID-19, the state of emergency and social distancing have caused a negative impact on the mental health of all residents, including foreign communities in Japan. This study aimed to evaluate the level of anxiety and its associated factors among non-Japanese residents residing in Japan during the COVID-19 pandemic.

    METHODS: A web-based survey in 13 languages was conducted among non-Japanese residents living in Japan during the COVID-19 situation. The State-Trait Anxiety Inventory assessed the level of anxiety-State (STAI-S) scores prorated from its six-item version. The multivariable logistic regression using the Akaike Information Criterion (AIC) method was performed to identify the associated factors of anxiety among participants.

    RESULTS: From January to March 2021, we collected 392 responses. A total of 357 valid responses were analyzed. 54.6% of participants suffered from clinically significant anxiety (CSA). In multivariable logistic model analysis, the CSA status or the high level of anxiety was associated with three factors, including having troubles/difficulties in learning or working, decreased sleep duration, and decreased overall physical health (p<0.05).

    CONCLUSION: Our study suggests several possible risk factors of anxiety among non-Japanese residents living in Japan undergoing the COVID-19 pandemic, including the troubles or difficulties in learning or working, the decrease in sleep duration, and the decrease in overall physical health.

  19. Huq AKMM, Roney M, Dubey A, Nasir MH, Tufail A, Aluwi MFFM, et al.
    PLoS One, 2024;19(3):e0299238.
    PMID: 38483871 DOI: 10.1371/journal.pone.0299238
    BACKGROUND: Currently, there is no antiviral medication for dengue, a potentially fatal tropical infectious illness spread by two mosquito species, Aedes aegypti and Aedes albopictus. The RdRp protease of dengue virus is a potential therapeutic target. This study focused on the in silico drug discovery of RdRp protease inhibitors.

    METHODS: To assess the potential inhibitory activity of 29 phenolic acids from Theobroma cacao L. against DENV3-NS5 RdRp, a range of computational methods were employed. These included docking, drug-likeness analysis, ADMET prediction, density functional theory (DFT) calculations, and molecular dynamics (MD) simulations. The aim of these studies was to confirm the stability of the ligand-protein complex and the binding pose identified during the docking experiment.

    RESULTS: Twenty-one compounds were found to have possible inhibitory activities against DENV according to the docking data, and they had a binding affinity of ≥-37.417 kcal/mol for DENV3- enzyme as compared to the reference compound panduratin A. Additionally, the drug-likeness investigation produced four hit compounds that were subjected to ADMET screening to obtain the lead compound, catechin. Based on ELUMO, EHOMO, and band energy gap, the DFT calculations showed strong electronegetivity, favouravle global softness and chemical reactivity with considerable intra-molecular charge transfer between electron-donor to electron-acceptor groups for catechin. The MD simulation result also demonstrated favourable RMSD, RMSF, SASA and H-bonds in at the binding pocket of DENV3-NS5 RdRp for catechin as compared to panduratin A.

    CONCLUSION: According to the present findings, catechin showed high binding affinity and sufficient drug-like properties with the appropriate ADMET profiles. Moreover, DFT and MD studies further supported the drug-like action of catechin as a potential therapeutic candidate. Therefore, further in vitro and in vivo research on cocoa and its phytochemical catechin should be taken into consideration to develop as a potential DENV inhibitor.

  20. Altharan YM, Shamsudin S, Lajis MA, Al-Alimi S, Yusuf NK, Alduais NAM, et al.
    PLoS One, 2024;19(3):e0300504.
    PMID: 38484005 DOI: 10.1371/journal.pone.0300504
    Direct recycling of aluminum waste is crucial in sustainable manufacturing to mitigate environmental impact and conserve resources. This work was carried out to study the application of hot press forging (HPF) in recycling AA6061 aluminum chip waste, aiming to optimize operating factors using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Genetic algorithm (GA) strategy to maximize the strength of recycled parts. The experimental runs were designed using Full factorial and RSM via Minitab 21 software. RSM-ANN models were employed to examine the effect of factors and their interactions on response and to predict output, while GA-RSM and GA-ANN were used for optimization. The chips of different morphology were cold compressed into billet form and then hot forged. The effect of varying forging temperature (Tp, 450-550°C), holding time (HT, 60-120 minutes), and chip surface area to volume ratio (AS:V, 15.4-52.6 mm2/mm3) on ultimate tensile strength (UTS) was examined. Maximum UTS (237.4 MPa) was achieved at 550°C, 120 minutes and 15.4 mm2/mm3 of chip's AS: V. The Tp had the largest contributing effect ratio on the UTS, followed by HT and AS:V according to ANOVA analysis. The proposed optimization process suggested 550°C, 60 minutes, and 15.4 mm2 as the optimal condition yielding the maximum UTS. The developed models' evaluation results showed that ANN (with MSE = 1.48%) outperformed RSM model. Overall, the study promotes sustainable production by demonstrating the potential of integrating RSM and ML to optimize complex manufacturing processes and improve product quality.
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