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Fulltext LAVRF: Sign language recognition via Lightweight Attentive VGG16 with Random Forest

Ewe ELR, Lee CP, Lim KM, Kwek LC, Alqahtani A

PLoS One, 2024;19(4):e0298699.
PMID: 38574042 DOI: 10.1371/journal.pone.0298699

Sign language recognition presents significant challenges due to the intricate nature of hand gestures and the necessity to capture fine-grained details. In response to these challenges, a novel approach is proposed-Lightweight Attentive VGG16 with Random Forest (LAVRF) model. LAVRF introduces a refined adaptation of the VGG16 model integrated with attention modules, complemented by a Random Forest classifier. By streamlining the VGG16 architecture, the Lightweight Attentive VGG16 effectively manages complexity while incorporating attention mechanisms that dynamically concentrate on pertinent regions within input images, resulting in enhanced representation learning. Leveraging the Random Forest classifier provides notable benefits, including proficient handling of high-dimensional feature representations, reduction of variance and overfitting concerns, and resilience against noisy and incomplete data. Additionally, the model performance is further optimized through hyperparameter optimization, utilizing the Optuna in conjunction with hill climbing, which efficiently explores the hyperparameter space to discover optimal configurations. The proposed LAVRF model demonstrates outstanding accuracy on three datasets, achieving remarkable results of 99.98%, 99.90%, and 100% on the American Sign Language, American Sign Language with Digits, and NUS Hand Posture datasets, respectively.
Fulltext Does structural social capital lead to proactive green innovation? a three-part serial mediation model

Gao X

PLoS One, 2024;19(4):e0301286.
PMID: 38578793 DOI: 10.1371/journal.pone.0301286

Enhancing green innovation for business sustainability represents a pressing global challenge. In the context of the manufacturing industry, the relationship between proactive green innovation (PGI) and structural social capital (SSC) remains a profoundly under-researched area. Drawing upon the theories of social capital and dynamic capability (DC), this study investigated the relationship between SSC and PGI within manufacturing enterprises via three individual and sequential mediating factors, namely cognitive social capital (CSC), relational social capital (RSC), and DC. Adopting a cross-sectional quantitative design, this study collected survey data from 485 manufacturing sector employees in China using purposive sampling. Structural equation modeling analysis of the data revealed no significant direct impact of SSC on PGI, but a strong indirect impact through the sequential mediating influences of CSC, RSC, and DC. The findings suggests that PGI within manufacturing enterprises is not wholly shaped by SSC; rather, firm-level dynamic capabilities, characterized by a sequential mechanism, plays a crucial role in achieving PGI within these enterprises. This paper offers both theoretical and practical contributions and provides recommendations for future research based on its limitations.
Fulltext Genetic diversity and phylogeographic patterns of the peacock jewel-damselfly, Rhinocypha fenestrella (Rambur, 1842)

Noorhidayah M, Azrizal-Wahid N, Low VL, Yusoff NR

PLoS One, 2024;19(4):e0301392.
PMID: 38578719 DOI: 10.1371/journal.pone.0301392

Despite is known to have widespread distribution and the most active species of the family Chlorocyphidae, the molecular data of Rhinocypha fenestrella (Rambur, 1842) are relatively scarce. The present study is the first that examined the genetic diversity and phylogeographic pattern of the peacock jewel-damselfly R. fenestrella by sequencing the cytochrome C oxidase I (cox1) and 16S rRNA gene regions from 147 individuals representing eight populations in Malaysia. A total of 26 and 10 unique haplotypes were revealed by the cox1 and 16S rRNA genes, respectively, and 32 haplotypes were recovered by the concatenated sequences of cox1+16S. Analyses indicated that haplotype AB2 was the most frequent and the most widespread haplotype in Malaysia while haplotype AB1 was suggested as the common ancestor haplotype of the R. fenestrella that may arose from the Negeri Sembilan as discovered from cox1+16S haplotype network analysis. Overall haplotype and nucleotide diversities of the concatenated sequences were Hd = 0.8937 and Pi = 0.0028, respectively, with great genetic differentiation (FST = 0.6387) and low gene flow (Nm = 0.14). Population from Pahang presented the highest genetic diversity (Hd = 0.8889, Pi = 0.0022, Nh = 9), whereas Kedah population demonstrated the lowest diversity (Hd = 0.2842, Pi = 0.0003, Nh = 4). The concatenated sequences of cox1+16S showed genetic divergence ranging from 0.09% to 0.97%, whereas the genetic divergence for cox1 and 16S rRNA genes were 0.16% to 1.63% and 0.01% to 0.75% respectively. This study provides for the first-time insights on the intraspecific genetic diversity, phylogeographic pattern and ancestral haplotype of Rhinocypha fenestrella. The understanding of molecular data especially phylogeographic pattern can enhance the knowledge about insect origin, their diversity, and capability to disperse in particular environments.
Fulltext Qualitative assessment of knowledge, attitude and practice of oncologists about precision medicine in cancer patients- study from Lahore, Pakistan

Naaem R, Hashmi FK, Yaqub S, Mohamed Noor DA

PLoS One, 2024;19(4):e0299010.
PMID: 38578776 DOI: 10.1371/journal.pone.0299010

BACKGROUND: Precision medicine (PM) is in great progressive stages in the West and allows healthcare practitioners (HCPs) to give treatment according to the patient's genetic findings, physiological and environmental characteristics. PM is a relatively new treatment approach in Pakistan Therefore, it is important to investigate the level of awareness, attitude, and challenges faced by oncology physicians while practicing PM for various therapies, especially cancer treatment.
OBJECTIVES: The present study aims to explore the level of awareness, attitude, and practice of PM in Pakistan along with the challenges faced by the oncologists for the treatment of cancer using the PM approach.
METHODS: Phenomenology-based qualitative approach was used. Face-to-face in-depth interviews were conducted using the purposive sampling approach among oncologists in Lahore, Pakistan. The data were analyzed using thematic content analysis to identify themes and sub-themes.
RESULTS: Out of 14 physicians interviewed 11 were aware of PM. They were keen on training to hone their skills and agreed on providing PM. Oncologists believed PM was expensive and given to affluent patients only. Other impeding factors include cost, lack of knowledge, and drug unavailability.
CONCLUSIONS: Despite basic knowledge and will to practice, resource and cost constraints were marked as significant barriers. Additional training programs and inclusion into the curriculum may help to pave the way to PM implementation in the future. In addition, health authorities and policymakers need to ensure a cheaper PM treatment can be made available for all cancer patients.
Fulltext Validation of key components in designing a social skills training content using virtual reality for high functioning autism youth-A Fuzzy Delphi method

Ahmad Basri MAF, Wan Ismail WS, Kamal Nor N, Mohd Tohit N, Ahmad MN, Mohamad Aun NS, et al.

PLoS One, 2024;19(4):e0301517.
PMID: 38574084 DOI: 10.1371/journal.pone.0301517

The use of virtual reality in social skills training for high functioning autism spectrum disorder (HFASD) youth has been found to be engaging and enjoyable. Despite the promising results, previous literature indicates that there has been no consensus on the social skills target in the training content. There is also limited research on how evidence-based strategies like cognitive and behaviour techniques are instantiated into the VR environment to teach social skills. The aim of this study is to determine the key components to design a social skills training content using virtual reality for youths with HFASD. The Fuzzy Delphi method (FDM) was used to obtain expert consensus on social skills difficulties and cognitive behavioral techniques included in the content in three phases. In phase 1, a questionnaire was developed from in-depth interviews and scientific literature review. The in-depth interviews were conducted with 13 HFASD youth, 7 parents and 6 experts. In phase 2, 3 experts rated the relevance of the items in the questionnaire using an item-level content validity index (I-CVI) assessment. In phase 3, the questionnaire was distributed to 10 experts to rate their level of agreement on each component using a 7-point Likert scale. Components that received a value above 75%, threshold value (d) ≤ 0.2, fuzzy score (A) ≥ α - cut value = 0.5 and higher rank based on defuzzification score were prioritized to be included in the content. Items that received higher expert consensus on social skills difficulties included assessing non-verbal responses, initiating, maintaining, and leaving conversations, emotional difficulties and difficulties in perspective taking. Cognitive and behavioral techniques that received higher expert consensus were psychoeducation, modelling, relaxation techniques, reinforcements, and perspective-taking questions. These key components can be used as a framework for the development of virtual learning content for social skills training in future studies.
Fulltext Motivators and barriers to the acceptability of a human milk bank among Malaysians

Ramachandran K, Dahlui M, Nik Farid ND

PLoS One, 2024;19(3):e0299308.
PMID: 38437241 DOI: 10.1371/journal.pone.0299308

The World Health Organisation (WHO) recommends that all babies be exclusively breastfed, stating that donor milk is the next best alternative in the absence of the mother's own milk. Milk sharing takes many forms, namely wet nursing, co-feeding, cross-feeding, and a human milk bank (HMB). However, the establishment of a human milk bank is still not widely accepted and is a debatable topic because of religious concerns in Malaysia. The aim of this study is to determine the facilitators and barriers among Malaysians towards the acceptance of an HMB. A cross-sectional study with 367 participants was conducted; the participants answered an online-validated, self-administered questionnaire. Data on sociodemographic, knowledge on breastfeeding benefits, knowledge and attitude on HMB-specific issues were analysed in terms of frequency before proceeded with multiple logistic regression. The majority of the respondents were Muslim (73.3%), had completed their tertiary education (82.8%), and were employed (70.8%). Only 55.9% of respondents had heard of HMB, stating the internet as their main source of information, but many respondents were agreeable to its establishment (67.8%). Most respondents had a good score on knowledge of breastfeeding benefits and on HMB-specific issues (70% and 54.2%, respectively), while 63.8% had a positive attitude towards HMB. In the multivariate analysis, mothers with a good score on general knowledge of breastfeeding (AOR: 1.715; 95% CI 1.047-2.808) were more likely to accept the establishment of HMB, while being a Muslim was negatively associated with its establishment (AOR = 0.113, 95% CI 0.050-0.253). The study found a high prevalence of mothers who were willing to accept the establishment of HMB. By educating mothers on the benefits of breastfeeding, as well as addressing their religious concerns, the establishment of a religiously abiding HMB in Malaysia may be accepted without compromising their beliefs or the health benefit of donor milk.
Fulltext Study protocol for a mixed methods approach to optimize colorectal cancer screening in Malaysia: Integrating stakeholders insights and knowledge-to-action framework

Chong DW, Jayaraj VJ, Ab Rahim FI, Syed Soffian SS, Azmi MF, Mohd Yusri MY, et al.

PLoS One, 2024;19(4):e0299659.
PMID: 38593177 DOI: 10.1371/journal.pone.0299659

INTRODUCTION: Colorectal cancer is a growing global health concern and the number of reported cases has increased over the years. Early detection through screening is critical to improve outcomes for patients with colorectal cancer. In Malaysia, there is an urgent need to optimize the colorectal cancer screening program as uptake is limited by multiple challenges. This study aims to systematically identify and address gaps in screening service delivery to optimize the Malaysian colorectal cancer screening program.
METHODS: This study uses a mixed methods design. It focuses primarily on qualitative data to understand processes and strategies and to identify specific areas that can be improved through stakeholder engagement in the screening program. Quantitative data play a dual role in supporting the selection of participants for the qualitative study based on program monitoring data and assessing inequalities in screening and program implementation in healthcare facilities in Malaysia. Meanwhile, literature review identifies existing strategies to improve colorectal cancer screening. Additionally, the knowledge-to-action framework is integrated to ensure that the research findings lead to practical improvements to the colorectal cancer screening program.
DISCUSSION: Through this complex mix of qualitative and quantitative methods, this study will explore the complex interplay of population- and systems-level factors that influence screening rates. It involves identifying barriers to effective colorectal cancer screening in Malaysia, comparing current strategies with international best practices, and providing evidence-based recommendations to improve the local screening program.
Fulltext KCO: Balancing class distribution in just-in-time software defect prediction using kernel crossover oversampling

Ismail AM, Ab Hamid SH, Abdul Sani A, Mohd Daud NN

PLoS One, 2024;19(4):e0299585.
PMID: 38603718 DOI: 10.1371/journal.pone.0299585

The performance of the defect prediction model by using balanced and imbalanced datasets makes a big impact on the discovery of future defects. Current resampling techniques only address the imbalanced datasets without taking into consideration redundancy and noise inherent to the imbalanced datasets. To address the imbalance issue, we propose Kernel Crossover Oversampling (KCO), an oversampling technique based on kernel analysis and crossover interpolation. Specifically, the proposed technique aims to generate balanced datasets by increasing data diversity in order to reduce redundancy and noise. KCO first represents multidimensional features into two-dimensional features by employing Kernel Principal Component Analysis (KPCA). KCO then divides the plotted data distribution by deploying spectral clustering to select the best region for interpolation. Lastly, KCO generates the new defect data by interpolating different data templates within the selected data clusters. According to the prediction evaluation conducted, KCO consistently produced F-scores ranging from 21% to 63% across six datasets, on average. According to the experimental results presented in this study, KCO provides more effective prediction performance than other baseline techniques. The experimental results show that KCO within project and cross project predictions especially consistently achieve higher performance of F-score results.
Fulltext Research on an innovative design and evaluation method of Chinese tea sets based on GT-AHP-FCE

Zhao Y, Hamat B, Wang T, Wang S, Pang LLL

PLoS One, 2024;19(4):e0302005.
PMID: 38603676 DOI: 10.1371/journal.pone.0302005

AIMS: In order to explore new consumer demands for Chinese tea set products, propose an innovative tea set product design and evaluation method to improve the user experience and satisfaction of the produced tea sets, thereby promoting the development of the tea set market and the promotion of tea culture.
METHODS: Firstly, grounded theory (GT) was used to analyze interview data to extract consumer demand indicators and construct a design evaluation hierarchical model. Secondly, the Analytical Hierarchy Process (AHP) was used to calculate the weights of the indicators, determine their priority of importance, and obtain several indicators that have a greater impact on the tea set design to guide innovative design practice. Lastly, the tea set design schemes were evaluated using the fuzzy comprehensive evaluation method to select the optimal design scheme and also to act as a guideline for further design optimization.
CONCLUSION: This study explores the innovative design and evaluation method for tea set products based on GT-AHP-FCE and validates the feasibility of this approach through a practical example of tea set design inspired by "The Classic of Mountains and Seas.". It provides innovative theoretical and practical guidance for designers of subsequent tea set products and also provides a new path for the inheritance and innovation of traditional culture.
Fulltext The effects of the COVID-19 pandemic period on stock market return and volatility. Evidence from the Pakistan Stock Exchange

Wang B, Waris M, Adamiak K, Adnan M, Hamad HA, Bhatti SM

PLoS One, 2024;19(4):e0295853.
PMID: 38625885 DOI: 10.1371/journal.pone.0295853

The COVID-19 pandemic has emerged as a significant event of the current century, introducing substantial transformations in economic and social activities worldwide. The primary objective of this study is to investigate the relationship between daily COVID-19 cases and Pakistan stock market (PSX) return volatility. To assess the relationship between daily COVID-19 cases and the PSX return volatility, we collected secondary data from the World Health Organization (WHO) and the PSX website, specifically focusing on the PSX 100 index, spanning from March 15, 2020, to March 31, 2021. We used the GARCH family models for measuring the volatility and the COVID-19 impact on the stock market performance. Our E-GARCH findings show that there is long-term persistence in the return volatility of the stock market of Pakistan in the period of the COVID-19 timeline because ARCH alpha (ω1) and GARCH beta (ω2) are significant. Moreover, is asymmetrical effect is found in the stock market of Pakistan during the COVID-19 period due to Gamma (ѱ) being significant for PSX. Our DCC-GARCH results show that the COVID-19 active cases have a long-term spillover impact on the Pakistan stock market. Therefore, the need of strong planning and alternative platform should be needed in the distress period to promote the stock market and investor should advised to make diversified international portfolio by investing in high and low volatility stock market to save their income. This study advocated the implications for investors to invest in low volatility stock especially during the period of pandemics to protect their return on investment. Moreover, policy makers and the regulators can make effective policies to maintain financial stability during pandemics that is very important for the country's economic development.
Fulltext The effects of dance interventions on physical function and quality of life among middle-aged and older adults: A systematic review

Lu J, Abd Rahman NA, Wyon M, Shaharudin S

PLoS One, 2024;19(4):e0301236.
PMID: 38640093 DOI: 10.1371/journal.pone.0301236

BACKGROUND: Fundamental physical functions such as postural control and balance are vital in preserving everyday life, affecting an individual's quality of life. Dance is a physical activity that offers health advantages across various life stages. Nevertheless, the effects of dance interventions on physical function, postural control, and quality of life among older adults have remained underexplored. The review aimed to examine the strength of evidence for dance interventions on physical function and quality of life among middle-aged and older adults.
METHODS: A systematic review was conducted across four databases (PubMed, Cochrane Library, Web of Science, and Medline), focusing on studies involving more than four weeks of dance interventions. MeSH terms [dance or dance intervention or dance rehabilitation or dance movement] and [motor function or functional capacity or postural control or functional mobility or mobility or postural balance or balance or flexibility or gait] and [well-being or quality of life or life satisfaction] were utilized in the search. This review was registered in the PROSPERO database (CRD42023422857). Included studies were assessed using the Cochrane Risk of Bias.
RESULTS: The search revealed 885 studies, and 16 met the inclusion criteria. The effects of various dance genres on physical functions and quality of life were compared. Most studies showed that dance intervention improved physical function, balance, postural control and quality of life. Dance intervention showed a high level of adherence compared to physiotherapy, self-care, conventional therapy, and aerobic and resistance exercise.
CONCLUSION: In terms of improving physical function and quality of life, structured dance is a safe and relatively effective alternative to exercise. Note the effect of movement selection and intensity in the dance interventions. Dance with music may increase participants' interest, encouraging more physical activity among middle-aged and older adults.
Impact of the Russia-Ukraine conflict on the quality and quantity of Malaysia's palm oil production: A time series analysis

Mat Enh A, Mustafa H, Ahmed F, Wahab A

PLoS One, 2024;19(5):e0302405.
PMID: 38709775 DOI: 10.1371/journal.pone.0302405

This study investigates the effects of the Russia-Ukraine conflict on the quality and quantity of Malaysia's palm oil production through a time series analysis. The study uses three primary factors to evaluate palm oil production: the Monthly Oil Extraction Rate (OER), the Monthly Fresh Fruit Bunch (FFB) Yield, and the Monthly Oil Exports. The results indicate that the Russia-Ukraine conflict significantly impacted the quality and quantity of palm oil production in Malaysia. Marginal declines in both the quality and quantity of palm oil produced at the onset of the conflict indicate a slight but significant decline in palm oil production during the next four-year period.
Developing a risk framework for assembly construction based on stakeholder theory and structural equation modelling

Junjia Y, Xiaoxiang Q, Alias AH, Haron NA, Abu Bakar N

PLoS One, 2024;19(5):e0301370.
PMID: 38709752 DOI: 10.1371/journal.pone.0301370

Occupational injuries in the construction industry have plagued many countries, and many cases have shown that accidents often occur because of a combination of project participants. Assembled construction (AC) projects have received extensive attention from Chinese scholars as a future trend, but few studies have explored the interrelationships and potential risks of various stakeholders in depth. This study fills this research gap by proposing a multi-stakeholder AC risk framework. The study surveyed 396 stakeholders, then analyzed the collected data and created a risk framework based on Structural Equation Modelling (SEM) and the CRITIC weighting method. The results revealed that factors like "regular supervision is a formality," "blindly approving the wrong safety measures," and "failure to organize effective safety education and training." are vital risks in AC of China. Finally, the study validates the risk factors and the framework with 180 real-life cases, which shows that the proposed framework is theoretically grounded and realistic. The study also suggests multi-level strategies such as introducing AI-based automated risk monitoring, improving the adaptability of normative provisions to technological advances, and advancing the culture of project communities of interest to ensure AC's safe practices.
Fulltext Comparative stability analysis of Indonesian banks: Markov Switching-Dynamic Regression for Islamic and conventional sectors

Mawardi I, Al Mustofa MU, Widiastuti T, Fanani S, Bakri MH, Hanafi Z, et al.

PLoS One, 2024;19(4):e0301398.
PMID: 38635825 DOI: 10.1371/journal.pone.0301398

The banking industry necessitates implementing an early warning system to effectively identify the factors that impact bank managers and enable them to make informed decisions, thereby mitigating systemic risk. Identifying factors that influence banks in times of stability and crisis is crucial, as it ultimately contributes to developing an improved early warning system. This study undertakes a comparative analysis of the stability of Indonesian Islamic and conventional banking across distinct economic regimes-crisis and stability. We analyze monthly banking data from December 2007 to November 2022 using the Markov Switching Dynamic Regression technique. The study focuses on conducting a comparative analysis between Islamic banks, represented by Islamic Commercial Bank (ICB) and Islamic Rural Bank (IRB), and conventional banks, represented by the Conventional Commercial Bank (CCB) and Conventional Rural Bank (CRB). The findings reveal that both Islamic and conventional banks exhibit a higher probability of being in a stable regime than a crisis regime. Notably, Islamic banks demonstrate a greater propensity to remain in a stable regime than their conventional counterparts. However, in a crisis regime, the likelihood of recovery for Sharia-compliant institutions is lower than for conventional banks. Furthermore, our analysis indicates that larger banks exhibit higher stability than their smaller counterparts regarding assets and size. This study pioneers a comprehensive comparison of the Z-score, employed as a proxy for stability, between two distinct classifications of Indonesian banks: Sharia (ICB and IRB) and conventional (CCB and CRB). The result is expected to improve our awareness of the elements that affect the stability of Islamic and conventional banking in Indonesia, leading to a deeper comprehension of their dynamics.
Fulltext Advancing e-commerce user purchase prediction: Integration of time-series attention with event-based timestamp encoding and Graph Neural Network-Enhanced user profiling

Zhou S, Hudin NS

PLoS One, 2024;19(4):e0299087.
PMID: 38635519 DOI: 10.1371/journal.pone.0299087

In recent years, the global e-commerce landscape has witnessed rapid growth, with sales reaching a new peak in the past year and expected to rise further in the coming years. Amid this e-commerce boom, accurately predicting user purchase behavior has become crucial for commercial success. We introduce a novel framework integrating three innovative approaches to enhance the prediction model's effectiveness. First, we integrate an event-based timestamp encoding within a time-series attention model, effectively capturing the dynamic and temporal aspects of user behavior. This aspect is often neglected in traditional user purchase prediction methods, leading to suboptimal accuracy. Second, we incorporate Graph Neural Networks (GNNs) to analyze user behavior. By modeling users and their actions as nodes and edges within a graph structure, we capture complex relationships and patterns in user behavior more effectively than current models, offering a nuanced and comprehensive analysis. Lastly, our framework transcends traditional learning strategies by implementing advanced meta-learning techniques. This enables the model to autonomously adjust learning parameters, including the learning rate, in response to new and evolving data environments, thereby significantly enhancing its adaptability and learning efficiency. Through extensive experiments on diverse real-world e-commerce datasets, our model demonstrates superior performance, particularly in accuracy and adaptability in large-scale data scenarios. This study not only overcomes the existing challenges in analyzing e-commerce user behavior but also sets a foundation for future exploration in this dynamic field. We believe our contributions provide significant insights and tools for e-commerce platforms to better understand and cater to their users, ultimately driving sales and improving user experiences.
Fulltext What factors affecting investment decision? The moderating role of fintech self-efficacy

Che Hassan N, Abdul-Rahman A, Ab Hamid SN, Mohd Amin SI

PLoS One, 2024;19(4):e0299004.
PMID: 38635510 DOI: 10.1371/journal.pone.0299004

This study aims to determine, from the perspective of investors, the factors that predict Islamic unit trust (IUT) investment intentions. Additionally, this paper examines the moderating effect of fintech self-efficacy (FSE) on the relationship between attitude and investment intention. A total of 392 data were collected from IUT investors in Malaysia and analyzed using partial least squares structural equation modeling. The findings reveal that subjective norms have the highest impact on investment intention, followed by attitude and FSE, while religiosity is not significantly associated with investment intention in Islamic unit trust funds. Attitude significantly mediates religiosity-intention and Islamic financial literacy-intention relationships. FSE significantly moderates the attitude-intention relationship. The results shed light on the key factors that increase investing behavior and have direct managerial implications with regard to marketing strategies and target markets. These findings suggest that IUT service providers should take the lead in attracting customers through effective and targeted marketing initiatives, particularly by enhancing customers' FSE and capabilities. This study provides empirical evidence on the interrelationships between Islamic financial literacy, religiosity, and FSE in examining investors' behavior using the Theory of Planned Behavior framework. The study explores the moderating role of FSE on the relationship between attitude and investment intention.
Fulltext Prevalence and predictors of post-acute COVID syndrome among infected healthcare workers at University Malaya Medical Centre

Lim SH, Lim YC, Zaki RA, Johari BM, Chang CY, Omar SFS, et al.

PLoS One, 2024;19(4):e0298376.
PMID: 38626017 DOI: 10.1371/journal.pone.0298376

BACKGROUND: Post Acute COVID Syndrome (PACS), a complex and poorly understood condition characterised by persistent symptoms following the acute phase of COVID-19 infection, has emerged as a significant global health concern. Healthcare workers who had been at the forefront of the pandemic response are at heightened risk of contracting the virus and subsequently developing PACS. Therefore, we aim to determine the prevalence and risk factors for PACS among healthcare workers infected with COVID-19.
METHODS: A cross-sectional study was conducted between October 2022 and August 2023 using an online REDCap electronic data capture tool questionnaire. PACS was defined as new or persistent symptoms lasting more than 28 days after a positive SARS-CoV-2 polymerase chain reaction or rapid test kit antigen test. Multivariable logistic regression was performed to determine predictors associated with PACS.
RESULTS: Among 609 infected healthcare workers, they were predominantly female (71.8%), Malays (84.6%), and aged 18-39 years (70.1%). 50.7% of infected healthcare workers experienced PACS. The most common PACS symptoms experienced were fatigue (27.9%), cough (25.1%), decreased physical strength (20.5%), and musculoskeletal pain (19.2%). Those who are more likely to develop PACS were females, underlying asthma, and COVID-19 severity category 3. On the other hand, those who received booster vaccinations were less likely to develop PACS.
CONCLUSION: PACS is prevalent among healthcare workers with COVID-19 at the University Malaya Medical Centre. These findings emphasise the critical need for those with higher risk to receive regular health monitoring and checkups to detect any early signs of PACS. It underscores the need for continuous support and healthcare interventions to mitigate the impacts of PACS and ensure the physical and mental well-being of healthcare workers.
Fulltext Machine learning in internet financial risk management: A systematic literature review

Tian X, Tian Z, Khatib SFA, Wang Y

PLoS One, 2024;19(4):e0300195.
PMID: 38625972 DOI: 10.1371/journal.pone.0300195

Internet finance has permeated into myriad households, bringing about lifestyle convenience alongside potential risks. Presently, internet finance enterprises are progressively adopting machine learning and other artificial intelligence methods for risk alertness. What is the current status of the application of various machine learning models and algorithms across different institutions? Is there an optimal machine learning algorithm suited for the majority of internet finance platforms and application scenarios? Scholars have embarked on a series of studies addressing these questions; however, the focus predominantly lies in comparing different algorithms within specific platforms and contexts, lacking a comprehensive discourse and summary on the utilization of machine learning in this domain. Thus, based on the data from Web of Science and Scopus databases, this paper conducts a systematic literature review on all aspects of machine learning in internet finance risk in recent years, based on publications trends, geographical distribution, literature focus, machine learning models and algorithms, and evaluations. The research reveals that machine learning, as a nascent technology, whether through basic algorithms or intricate algorithmic combinations, has made significant strides compared to traditional credit scoring methods in predicting accuracy, time efficiency, and robustness in internet finance risk management. Nonetheless, there exist noticeable disparities among different algorithms, and factors such as model structure, sample data, and parameter settings also influence prediction accuracy, although generally, updated algorithms tend to achieve higher accuracy. Consequently, there is no one-size-fits-all approach applicable to all platforms; each platform should enhance its machine learning models and algorithms based on its unique characteristics, data, and the development of AI technology, starting from key evaluation indicators to mitigate internet finance risks.
Fulltext Assessment of coastal river water quality in Bangladesh: Implications for drinking and irrigation purposes

Uddin MR, Khandaker MU, Ahmed S, Abedin MJ, Hossain SMM, Al Mansur MA, et al.

PLoS One, 2024;19(4):e0300878.
PMID: 38635835 DOI: 10.1371/journal.pone.0300878

Saltwater intrusion in the coastal areas of Bangladesh is a prevalent phenomenon. However, it is not conducive to activities such as irrigation, navigation, fish spawning and shelter, and industrial usage. The present study analyzed 45 water samples collected from 15 locations in coastal areas during three seasons: monsoon, pre-monsoon, and post-monsoon. The aim was to comprehend the seasonal variation in physicochemical parameters, including water temperature, pH, electrical conductivity (EC), salinity, total dissolved solids (TDS), hardness, and concentrations of Na+, K+, Mg2+, Ca2+, Fe2+, HCO3-, PO43-, SO42-, and Cl-. Additionally, parameters essential for agriculture, such as soluble sodium percentage (SSP), sodium absorption ratio (SAR), magnesium absorption ratio (MAR), residual sodium carbonate (RSC), Kelly's ratio (KR), and permeability index (PI), were examined. Their respective values were found to be 63%, 16.83 mg/L, 34.92 mg/L, 145.44 mg/L, 1.28 mg/L, and 89.29%. The integrated water quality index was determined using entropy theory and principal component analysis (PCA). The resulting entropy water quality index (EWQI) and SAR of 49.56% and 63%, respectively, indicated that the samples are suitable for drinking but unsuitable for irrigation. These findings can assist policymakers in implementing the Bangladesh Deltaplan-2100, focusing on sustainable land management, fish cultivation, agricultural production, environmental preservation, water resource management, and environmental protection in the deltaic areas of Bangladesh. This research contributes to a deeper understanding of seasonal variations in the hydrochemistry and water quality of coastal rivers, aiding in the comprehension of salinity intrusion origins, mechanisms, and causes.
Fulltext Effects of poly(3-hydroxybutyrate) [P(3HB)] coating on the bacterial communities of artificial structures

Chai YJ, Syauqi TA, Sudesh K, Ee TL, Ban CC, Kar Mun AC, et al.

PLoS One, 2024;19(4):e0300929.
PMID: 38635673 DOI: 10.1371/journal.pone.0300929

The expanding urbanization of coastal areas has led to increased ocean sprawl, which has had both physical and chemical adverse effects on marine and coastal ecosystems. To maintain the health and functionality of these ecosystems, it is imperative to develop effective solutions. One such solution involves the use of biodegradable polymers as bioactive coatings to enhance the bioreceptivity of marine and coastal infrastructures. Our study aimed to explore two main objectives: (1) investigate PHA-degrading bacteria on polymer-coated surfaces and in surrounding seawater, and (2) comparing biofilm colonization between surfaces with and without the polymer coating. We applied poly(3-hydroxybutyrate) [P(3HB)) coatings on concrete surfaces at concentrations of 1% and 6% w/v, with varying numbers of coating cycles (1, 3, and 6). Our findings revealed that the addition of P(3HB) indeed promoted accelerated biofilm growth on the coated surfaces, resulting in an occupied area approximately 50% to 100% larger than that observed in the negative control. This indicates a remarkable enhancement, with the biofilm expanding at a rate roughly 1.5 to 2 times faster than the untreated surfaces. We observed noteworthy distinctions in biofilm growth patterns based on varying concentration and number of coating cycles. Interestingly, treatments with low concentration and high coating cycles exhibited comparable biofilm enhancements to those with high concentrations and low coating cycles. Further investigation into the bacterial communities responsible for the degradation of P(3HB) coatings identified mostly common and widespread strains but found no relation between the concentration and coating cycles. Nevertheless, this microbial degradation process was found to be highly efficient, manifesting noticeable effects within a single month. While these initial findings are promising, it's essential to conduct tests under natural conditions to validate the applicability of this approach. Nonetheless, our study represents a novel and bio-based ecological engineering strategy for enhancing the bioreceptivity of marine and coastal structures.

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