Displaying publications 1 - 20 of 99 in total

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  1. Abdul Razak SF, Yogarayan S, Azman A, Abdullah MFA, Muhamad Amin AH, Salleh M
    F1000Res, 2021;10:1265.
    PMID: 36852011 DOI: 10.12688/f1000research.73398.2
    Background: V2V (Vehicle-to-Vehicle) is a booming research field with a diverse set of services and applications. Most researchers rely on vehicular simulation tools to model traffic and road conditions and evaluate the performance of network protocols. We conducted a scoping review to consider simulators that have been reported in the literature based on successful implementation of V2V systems, tutorials, documentation, examples, and/or discussion groups. Methods: Simulators that have limited information were not included. The selected simulators are described individually and compared based on their requirements and features, i.e., origin, traffic model, scalability, and traffic features. This scoping review was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The review considered only research published in English (in journals and conference papers) completed after 2015. Further, three reviewers initiated the data extraction phase to retrieve information from the published papers. Results: Most simulators can simulate system behaviour by modelling the events according to pre-defined scenarios. However, the main challenge faced is integrating the three components to simulate a road environment in either microscopic, macroscopic or mesoscopic models. These components include mobility generators, VANET simulators and network simulators. These simulators require the integration and synchronisation of the transportation domain and the communication domain. Simulation modelling can be run using a different types of simulators that are cost-effective and scalable for evaluating the performance of V2V systems in urban environments. In addition, we also considered the ability of the vehicular simulation tools to support wireless sensors. Conclusions: The outcome of this study may reduce the time required for other researchers to work on other applications involving V2V systems and as a reference for the study and development of new traffic simulators.
  2. Abdullah AH, Neo TK, Low JH
    F1000Res, 2021;10:1076.
    PMID: 35035894 DOI: 10.12688/f1000research.73210.2
    Background: Studies have acknowledged that social media enables students to connect with and learn from experts from different ties available in the students' personal learning environment (PLE). Incorporating experts into formal learning activities such as scaffolding problem-solving tasks through social media, allows students to understand how experts solve real-world problems. However, studies that evaluate experts' problem-solving styles on social media in relation to the tie strength of the experts with the students are scarce in the extant literature. This study aimed to explore the problem-solving styles that the experts portrayed based on their ties with the students in problem-based learning (PBL) on Facebook. Methods: This study employed a simultaneous within-subject experimental design which was conducted in three closed Facebook groups with 12 final year management students, six business experts, and one instructor as the participants. The experts were invited by the students from the weak and strong ties in their PLE. Hinging on the Strength of Weak Ties Theory (Granovetter, 1973) and problem-solving styles (Selby et al., 2004), this study employed thematic analysis using the ATLAS.ti qualitative data analysis software to map the experts' comments on Facebook. Results:  The experts from strong and weak ties who had a prior relationship with the students showed people preference style by being more sensitive to the students' learning needs and demonstrating firmer scaffolding compared to the weak ties' experts who had no prior relationship with the students. Regardless of the types of ties, all experts applied all manner of processing information and orientation to change but the degree of its applications are correlated with the working experience of the experts. Conclusion: The use of weak or strong ties benefited the students as it expedited their problem-solving tasks since the experts have unique expertise to offer depending on the problem-solving styles that they exhibited.
  3. Abdullah MFA, Yogarayan S, Abdul Razak SF, Azman A, Muhamad Amin AH, Salleh M
    F1000Res, 2021;10:1104.
    PMID: 38595984 DOI: 10.12688/f1000research.73269.4
    Vehicle to Everything (V2X) communications and services have sparked considerable interest as a potential component of future Intelligent Transportation Systems. V2X serves to organise communication and interaction between vehicle to vehicle (V2V), vehicle to infrastructure (V2I), vehicle to pedestrians (V2P), and vehicle to networks (V2N). However, having multiple communication channels can generate a vast amount of data for processing and distribution. In addition, V2X services may be subject to performance requirements relating to dynamic handover and low latency communication channels. Good throughput, lower delay, and reliable packet delivery are the core requirements for V2X services.  Edge Computing (EC) may be a feasible option to address the challenge of dynamic handover and low latency to allow V2X information to be transmitted across vehicles. Currently, existing comparative studies do not cover the applicability of EC for V2X. This review explores EC approaches to determine the relevance for V2X communication and services. EC allows devices to carry out part or all of the data processing at the point where data is collected. The emphasis of this review is on several methods identified in the literature for implementing effective EC. We describe each method individually and compare them according to their applicability. The findings of this work indicate that most methods can simulate the EC positioning under predefined scenarios. These include the use of Mobile Edge Computing, Cloudlet, and Fog Computing. However, since most studies are carried out using simulation tools, there is a potential limitation in that crucial data in the search for EC positioning may be overlooked and ignored for bandwidth reduction. The EC approaches considered in this work are limited to the literature on the successful implementation of V2X communication and services. The outcome of this work could considerably help other researchers better characterise EC applicability for V2X communications and services.
  4. Akbar R, Jusoh SA
    F1000Res, 2013;2:64.
    PMID: 24555044 DOI: 10.12688/f1000research.2-64.v2
    Envelope glycoproteins of Hepatitis C Virus (HCV) play an important role in the virus assembly and initial entry into host cells. Conserved charged residues of the E2 transmembrane (TM) domain were shown to be responsible for the heterodimerization with envelope glycoprotein E1. Despite intensive research on both envelope glycoproteins, the structural information is still not fully understood. Recent findings have revealed that the stem (ST) region of E2 also functions in the initial stage of the viral life cycle. We have previously shown the effect of the conserved charged residues on the TM helix monomer of E2. Here, we extended the model of the TM domain by adding the adjacent ST segment. Explicit molecular dynamics simulations were performed for the E2 amphiphilic segment of the ST region connected to the putative TM domain (residues 683-746). Structural conformation and behavior are studied and compared with the nuclear magnetic resonance (NMR)-derived segment of E2 ( 2KQZ.pdb). We observed that the central helix of the ST region (residues 689 - 703) remained stable as a helix in-plane to the lipid bilayer. Furthermore, the TM domain appeared to provide minimal contribution to the structural stability of the amphipathic region. This study also provides insight into the orientation and positional preferences of the ST segment with respect to the membrane lipid-water interface.
  5. Allinjawi K, Sharanjeet-Kaur SK, Akhir SM, Mutalib HA
    F1000Res, 2016;5:2742.
    PMID: 28163898 DOI: 10.12688/f1000research.9971.1
    Aim: The purpose of this study was to compare the changes in relative peripheral refractive error produced by two different designs of progressive soft contact lenses in myopic schoolchildren. Methods: Twenty-seven myopic schoolchildren age between 13 to 15 years were included in this study. The measurements of central and peripheral refraction were made using a Grand-Seiko WR-5100K open-field autorefractometer without correction (baseline), and two different designs of progressive contact lenses (PCLs) (Multistage from SEED & Proclear from Cooper Vision) with an addition power of +1.50 D. Refractive power was measured at center and at eccentricities between 35º temporal to 35º nasal visual field (in 5º steps). Results: Both PCLs showed a reduction in hyperopic defocus at periphery. However, this reduction was only significant for the Multistage PCL (p= 0.015), (Proclear PCL p= 0.830).  Conclusion: Multistage PCLs showed greater reduction in peripheral retinal hyperopic defocus among myopic schoolchildren in comparison to Proclear PCLs.
  6. Alvarez MF, Bolívar-Mejía A, Rodriguez-Morales AJ, Ramirez-Vallejo E
    F1000Res, 2017;6:390.
    PMID: 28503297 DOI: 10.12688/f1000research.11078.2
    BACKGROUND: In the last three years, chikungunya virus disease has been spreading, affecting particularly the Americas, producing more than two million cases. In this setting, not only new disease-related epidemiological patterns have been found, but also new clinical findings have been reported by different research groups. These include findings on the cardiovascular system, including clinical, electrocardiographic and echocardiographic alterations. No previous systemic reviews have been found in major databases about it.

    METHODS: We performed a systematic review looking for reports about cardiovascular compromise during chikungunya disease. Cardiac compromise is not so common in isolated episodes; but countries where chikungunya virus is an epidemic should be well informed about this condition. We used 6 bibliographical databases as resources: Medline/Pubmed, Embase, ScienceDirect, ClinicalKey, Ovid and SciELO. Dengue reports on cardiovascular compromise were included as well, to compare both arbovirus' organic compromises. Articles that delved mainly into the rheumatic articular and cutaneous complications were not considered, as they were not in line with the purpose of this study. The type of articles included were reviews, meta-analyses, case-controls, cohort studies, case reports and case series. This systematic review does not reach or performed a meta-analysis.

    RESULTS: Originally based on 737 articles, our reviewed selected 40 articles with 54.2% at least mentioning CHIKV cardiovascular compromise within the systemic compromise. Cardiovascular manifestations can be considered common and have been reported in France, India, Sri Lanka, Malaysia, Colombia, Venezuela and USA, including mainly, but no limited to: hypotension, shock and circulatory collapse, Raynaud phenomenon, arrhythmias, murmurs, myocarditis, dilated cardiomyopathy, congestive insufficiency, heart failure and altered function profile (Troponins, CPK).

    CONCLUSIONS: Physicians should be encouraged to keep divulgating reports on the cardiovascular involvement of chikungunya virus disease, to raise awareness and ultimately encourage suitable diagnosis and intervention worldwide. More research about cardiovascular involvement and manifestations of systemic Chikungunya virus infection is urgently needed.

  7. Alvi Q, Baloch GM, Chinna K, Dabbagh A
    F1000Res, 2020;9:901.
    PMID: 32802322 DOI: 10.12688/f1000research.24866.1
    Ovarian cancer is a fatal gynaecological cancer and eighth most common cancer in women globally. Lifestyle, reproductive and sociodemographic factors are among the influential parameters that may significantly affect the risk of ovarian cancer and its mortality rate. However, the epidemiological investigations have shown that the risk of ovarian cancers associated with these factors is different in varied geographical distributions. Lifestyle and reproductive factors have not been investigated thoroughly across a wide cultural diversity. The objective of this study is to investigate the association of these factors with ovarian cancer in Pakistan. This investigation will focus on the lifestyle effects of fat intake, intake of tea, habitual exercise, use of talc, personal hygiene, habit of holding urine for long time, obesity on ovarian cancer among Pakistani women.  Reproductive variables will include age at menarche, natural menopausal age, parity, nulliparity (miscarriages, abortion, stillbirths), infertility, fertility treatment, tubal ligation, oral contraceptive use, and family history of breast or ovarian cancer. Sociodemographic variables will include effect of age, income, education, and geographical location. A case-control study will be conducted in the major cancer hospitals of Pakistan and the patients will also be interviewed. The controls will be recruited outside the hospital. For controls the same age limit and residency requirements will be applied. The information gained from this research will be an important contribution to develop programs for health promotion, with a focus on ovarian cancer prevention and women's health. The findings could be used for health policies and planning to prevent ovarian cancer. The research will pave the way for a public policy and interventions to reduce the burden of ovarian cancer in Pakistan.
  8. Anbananthen KSM, Subbiah S, Chelliah D, Sivakumar P, Somasundaram V, Velshankar KH, et al.
    F1000Res, 2021;10:1143.
    PMID: 34987773 DOI: 10.12688/f1000research.73009.1
    Background: In recent times, digitization is gaining importance in different domains of knowledge such as agriculture, medicine, recommendation platforms, the Internet of Things (IoT), and weather forecasting. In agriculture, crop yield estimation is essential for improving productivity and decision-making processes such as financial market forecasting, and addressing food security issues. The main objective of the article is to predict and improve the accuracy of crop yield forecasting using hybrid machine learning (ML) algorithms. Methods: This article proposes hybrid ML algorithms that use specialized ensembling methods such as stacked generalization, gradient boosting, random forest, and least absolute shrinkage and selection operator (LASSO) regression. Stacked generalization is a new model which learns how to best combine the predictions from two or more models trained on the dataset. To demonstrate the applications of the proposed algorithm, aerial-intel datasets from the github data science repository are used. Results: Based on the experimental results done on the agricultural data, the following observations have been made. The performance of the individual algorithm and hybrid ML algorithms are compared using cross-validation to identify the most promising performers for the agricultural dataset.  The accuracy of random forest regressor, gradient boosted tree regression, and stacked generalization ensemble methods are 87.71%, 86.98%, and 88.89% respectively. Conclusions: The proposed stacked generalization ML algorithm statistically outperforms with an accuracy of 88.89% and hence demonstrates that the proposed approach is an effective algorithm for predicting crop yield. The system also gives fast and accurate responses to the farmers.
  9. Andoy-Galvan JA, Sriram S, Kiat TJ, Xin LZ, Shin WJ, Chinna K
    F1000Res, 2023;12:550.
    PMID: 37868299 DOI: 10.12688/f1000research.125203.1
    Background: Doctors with a normal BMI and healthy living habits have shown to be more confident and effective in providing realistic guidance and obesity management to their patients. This study investigated obesogenic tendencies of medical students as they progress in their medical studies. Methods: A cohort of forty-nine medical students enrolled in a five-year cohort study and was followed up after one year. At the initiation of the cohort, socio-demography and information on anthropometry, accommodation, eating behavior, stress and sleeping habits of the students had been recorded. Follow-up data was collected using a standardized self-administered questionnaire. Results: Thirty-seven percent of the students in the cohort are either obese or overweight in the one-year period.. A year of follow-up suggests that there is an increase in BMI among the male students (P=0.008) and the changes are associated with changes in accommodation (P=0.016), stress levels (P=0.021), and sleeping habits (P=0.011). Conclusion: Medical education system should seriously consider evaluating this aspect in the curriculum development to help our future medical practitioners practice a healthy lifestyle and be the initiator of change in the worsening prevalence of obesity worldwide.
  10. Andoy-Galvan JA, Lugova H, Patil SS, Wong YH, Baloch GM, Suleiman A, et al.
    F1000Res, 2020;9:160.
    PMID: 32399203 DOI: 10.12688/f1000research.22236.1
    Background: Recent studies have shown that higher income is associated with a higher risk for subsequent obesity in low- and middle-income countries, while in high-income countries there is a reversal of the association - higher-income individuals have a lower risk of obesity. The concept of being able to afford to overeat is no longer a predictor of obesity in developed countries. In Malaysia, a trend has been observed that the prevalence of obesity increases with an increase in income among the low-income (B40) group. This trend, however, was not further investigated. Therefore, this study was performed to investigate the association of income and other sociodemographic factors with obesity among residents within the B40 income group in an urban community.  Methods: This cross-sectional study used a systematic sampling technique to recruit participants residing in a Program Perumahan Rakyat (PPR), Kuala Lumpur, Malaysia. The sociodemographic characteristics were investigated through face-to-face interviews. Weight and height were measured, and body mass index (BMI) was calculated and coded as underweight, normal, overweight and obese according to the cut-off points for the Asian population. A chi-squared test was used to compare the prevalence of obesity in this study with the national prevalence. A generalized linear model was introduced to identify BMI predictors. Results: Among the 341 participants, 25 (7.3%) were underweight, 94 (27.6%) had normal weight, 87 (25.5%) were overweight, and 135 (39.6%) were obese. The proportion of obese adults (45.8%) was significantly higher than the national prevalence of 30.6% (p<0.001). Among all the tested variables, only income was significantly associated with BMI (p=0.046). Conclusion: The proportion of obesity in this urban poor community was higher compared with the national average. BMI increased as the average monthly household income decreased.
  11. Angers-Loustau A, Petrillo M, Bengtsson-Palme J, Berendonk T, Blais B, Chan KG, et al.
    F1000Res, 2018;7.
    PMID: 30026930 DOI: 10.12688/f1000research.14509.2
    Next-Generation Sequencing (NGS) technologies are expected to play a crucial role in the surveillance of infectious diseases, with their unprecedented capabilities for the characterisation of genetic information underlying the virulence and antimicrobial resistance (AMR) properties of microorganisms.  In the implementation of any novel technology for regulatory purposes, important considerations such as harmonisation, validation and quality assurance need to be addressed.  NGS technologies pose unique challenges in these regards, in part due to their reliance on bioinformatics for the processing and proper interpretation of the data produced.  Well-designed benchmark resources are thus needed to evaluate, validate and ensure continued quality control over the bioinformatics component of the process.  This concept was explored as part of a workshop on "Next-generation sequencing technologies and antimicrobial resistance" held October 4-5 2017.   Challenges involved in the development of such a benchmark resource, with a specific focus on identifying the molecular determinants of AMR, were identified. For each of the challenges, sets of unsolved questions that will need to be tackled for them to be properly addressed were compiled. These take into consideration the requirement for monitoring of AMR bacteria in humans, animals, food and the environment, which is aligned with the principles of a "One Health" approach.
  12. Anggraini L, Marlida Y, Wizna W, Jamsari J, Mirzah M, Adzitey F, et al.
    F1000Res, 2018 10 19;7:1663.
    PMID: 32201563 DOI: 10.12688/f1000research.16224.3
    Background: Dadih (fermented buffalo milk) is a traditional Indonesian food originating from West Sumatra province. The fermentation process is carried out by lactic acid bacteria (LAB), which are naturally present in buffalo milk.  Lactic acid bacteria have been reported as one of potential producers of γ-aminobutyric acid (GABA). GABA acts as a neurotransmitter inhibitor of the central nervous system. Methods: In this study, molecular identification and phylogenetic analysis of GABA producing LAB isolated from indigenous dadih of West Sumatera were determined. Identification of the GABA-producing LAB DS15 was based on conventional polymerase chain reaction. 16S rRNA gene sequence analysis was used to identify LAB DS15. Results: PCR of the 16S rRNA gene sequence of LAB DS15 gave an approximately 1400 bp amplicon.  Phylogenetic analysis showed that LAB DS15 was Pediococcusacidilactici, with high similarity of 99% at 100% query coverage to Pediococcusacidilactici strain DSM 20284. Conclusions: It can be concluded that GABA producing LAB isolated from indigenous dadih was Pediococcus acidilactici.
  13. Bachtiar E, Bachtiar BM, Kusumaningrum A, Sunarto H, Soeroso Y, Sulijaya B, et al.
    F1000Res, 2023;12:419.
    PMID: 38269064 DOI: 10.12688/f1000research.130995.3
    BACKGROUND: The available evidence suggests that inflammatory responses, in both systemic and oral tissue, contribute to the pathology of COVID-19 disease. Hence, studies of inflammation biomarkers in oral fluids, such as saliva, might be useful to better specify COVID-19 features.

    METHODS: In the current study, we performed quantitative real-time PCR to measure salivary levels of C-reactive protein (CRP) and interleukin-6 (IL-6) in saliva obtained from patients diagnosed with mild COVID-19, in a diabetic group (DG; n = 10) and a non-diabetic group (NDG; n = 13). All participants were diagnosed with periodontitis, while six participants with periodontitis but not diagnosed with COVID-19 were included as controls.

    RESULTS: We found increases in salivary total protein levels in both the DG and NDG compared to control patients. In both groups, salivary CRP and IL-6 levels were comparable. Additionally, the levels of salivary CRP were significantly correlated with total proteins, in which a strong and moderate positive correlation was found between DG and NDG, respectively. A linear positive correlation was also noted in the relationship between salivary IL-6 level and total proteins, but the correlation was not significant. Interestingly, the association between salivary CRP and IL-6 levels was positive. However, a moderately significant correlation was only found in COVID-19 patients with diabetes, through which the association was validated by a receiver operating curve.

    CONCLUSIONS: These finding suggest that salivary CRP and IL-6 are particularly relevant as potential non-invasive biomarker for predicting diabetes risk in mild cases of COVID-19 accompanied with periodontitis.

  14. Bhuiyan MR, Abdullah DJ, Hashim DN, Farid FA, Uddin DJ, Abdullah N, et al.
    F1000Res, 2021;10:1190.
    PMID: 35136582 DOI: 10.12688/f1000research.73156.2
    BACKGROUND: This paper focuses on advances in crowd control study with an emphasis on high-density crowds, particularly Hajj crowds. Video analysis and visual surveillance have been of increasing importance in order to enhance the safety and security of pilgrimages in Makkah, Saudi Arabia. Hajj is considered to be a particularly distinctive event, with hundreds of thousands of people gathering in a small space, which does not allow a precise analysis of video footage using advanced video and computer vision algorithms. This research proposes an algorithm based on a Convolutional Neural Networks model specifically for Hajj applications. Additionally, the work introduces a system for counting and then estimating the crowd density.

    METHODS: The model adopts an architecture which detects each person in the crowd, spots head location with a bounding box and does the counting in our own novel dataset (HAJJ-Crowd).

    RESULTS: Our algorithm outperforms the state-of-the-art method, and attains a remarkable Mean Absolute Error result of 200 (average of 82.0 improvement) and Mean Square Error of 240 (average of 135.54 improvement).

    CONCLUSIONS: In our new HAJJ-Crowd dataset for evaluation and testing, we have a density map and prediction results of some standard methods.

  15. Bin Jamal Mohd Lokman EH, Goh VT, Yap TTV, Ng H
    F1000Res, 2022;11:57.
    PMID: 37082303 DOI: 10.12688/f1000research.73134.1
    Background: The lack of real-time monitoring is one of the reasons for the lack of awareness among drivers of their dangerous driving behavior. This work aims to develop a driver profiling system where a smartphone's built-in sensors are used alongside machine learning algorithms to classify different driving behaviors. Methods: We attempt to determine the optimal combination of smartphone sensors such as accelerometer, gyroscope, and GPS in order to develop an accurate machine learning algorithm capable of identifying different driving events (e.g. turning, accelerating, or braking). Results: In our preliminary studies, we encountered some difficulties in obtaining consistent driving events, which had the potential to add "noise" to the observations, thus reducing the accuracy of the classification. However, after some pre-processing, which included manual elimination of extraneous and erroneous events, and with the use of the Convolutional Neural Networks (CNN), we have been able to distinguish different driving events with an accuracy of about 95%. Conclusions: Based on the results of preliminary studies, we have determined that proposed approach is effective in classifying different driving events, which in turn will allow us to determine driver's driving behavior.
  16. Bramantoro T, Zulfiana AA, Amir MS, Irmalia WR, Mohd Nor NA, Nugraha AP, et al.
    F1000Res, 2022;11:924.
    PMID: 36313542 DOI: 10.12688/f1000research.124547.3
    Background: Drinking coffee is known to have both positive and negative aftermath on periodontal health. The current study is aiming to systematically review the impact of coffee consumption on periodontal health status. Methods: An article search was carried out in two electronic databases (PUBMED and Web of Sciences). All type of experimental and observational studies were included. The assessment of the included articles were conducted using Joanna Briggs Institute (JBI) critical appraisal tool. Data were analyzed qualitatively. Result: A total of 10 articles were included in this study. Most (5) of the studies discovered a negative correlation between coffee intake and periodontal health, while 4 other studies found the protective effect of daily coffee consumption against alveolar bone loss. Last, only one study found that coffee intake did not relate with periodontitis. Conclusion: The effect of coffee consumption on periodontal health was fragmented since coffee has complex components that may give either beneficial effects or negative impact on periodontal health.
  17. Cheng KM, Koo AC, Mohd Nasir JS, Wong SY
    F1000Res, 2021;10:890.
    PMID: 35035889 DOI: 10.12688/f1000research.72761.2
    Background: Gamification is an innovative approach to engaging in activities that people believe as less interesting. Recycling has been an issue not taken aware by the people in environmental sustainability. There are substantial studies on recycling intention due to the continual growth of unethical and unsustainable waste disposal. Creative approaches to recycling awareness activities should be made to fulfil youths' increasing interest in and demand for recycling. The main objective of this study is to explore the factors related to youths' recycling intentions after experiencing a gamified online recycling learning activity, Edcraft Gamified Learning (EGL). Gamified recycling education is believed to be a practical and engaging approach for youths. Methods: 100 students participated in EGL, consisting of two levels of plastic crafting and recycling activities. They experienced online EGL at home between May and September in 2020, during the COVID-19 pandemic total lockdown in Malaysia, namely, Movement Control Order (MCO). 29 participants were selected to participate in five focus group discussions (FGDs) with five to eight participants per session to explore their opinions towards gamified learning, motivation and recycling intention. Results: This paper reports the findings of the FGDs. A codebook was developed based on the codes from the FGD feedback. The codes were rated by two raters, followed by an assessment of inter-rater reliability and thematic analysis. The findings emerged and were confirmed with four themes as factors that influence recycling intention. They are gameful experience, social influence, intrinsic motivation, and extrinsic motivation. Conclusion: The dependent variable, recycling intention, was connected to the four themes to verify the conceptual framework. One limitation of the study was the design of the EGL activity, which was only carried out over two days with two levels of gamified recycling education, as students had concurrent academic online classes during that period.
  18. Chengappa S K, Rao A, K S A, Jodalli PS, Shenoy Kudpi R
    F1000Res, 2023;12:390.
    PMID: 37521767 DOI: 10.12688/f1000research.132035.1
    Background: Microplastic particles are used as ingredients in personal care products such as face washes, shower gels and toothpastes and form one of the main sources of microplastic pollution, especially in the marine environment. In addition to being a potential pollutant to the environment, the transfer of microplastics to humans can become a severe threat to public health. This systematic review was conceptualized to identify evidence for the presence of and characteristics of microplastics in toothpaste formulations. Methods: The PICOS Criteria was used for including studies for the review. Electronic databases of Scopus, Embase, Springer Link, PubMed, Web of Science and Google Scholar were searched, as well as hand and reference searching of the articles was carried out. The articles were screened using the software application, Covidence® and data was extracted. Results: This systematic review showed that toothpastes from China, Vietnam, Myanmar and the UAE, reported no evidence of microplastics and those from Malaysia, Turkey and India reported the presence of microplastics. The shape of the microplastics present in these toothpastes were found to be granular, irregular with opaque appearance and also in the form of fragments and fibers and the percentage weight in grams ranged from 0.2 to 7.24%. Malaysia releases 0.199 trillion microbeads annually from personal care products into the environment and toothpastes in Turkey release an average of 871 million grams of microplastics annually. Similarly, in India, it has been reported that 1.4 billion grams of microplastic particles are emitted annually from toothpaste. Conclusions: The findings of this systematic review provide evidence that toothpastes, at least in some parts of the world, do contain microplastics and that there is a great risk of increase in the addition of microplastics to the environment by the use of toothpaste.
  19. Chew LJ, Haw SC, Subramaniam S
    F1000Res, 2021;10:937.
    PMID: 34868563 DOI: 10.12688/f1000research.73060.1
    Background: A recommender system captures the user preferences and behaviour to provide a relevant recommendation to the user. In a hybrid model-based recommender system, it requires a pre-trained data model to generate recommendations for a user. Ontology helps to represent the semantic information and relationships to model the expressivity and linkage among the data. Methods: We enhanced the matrix factorization model accuracy by utilizing ontology to enrich the information of the user-item matrix by integrating the item-based and user-based collaborative filtering techniques. In particular, the combination of enriched data, which consists of semantic similarity together with rating pattern, will help to reduce the cold start problem in the model-based recommender system. When the new user or item first coming into the system, we have the user demographic or item profile that linked to our ontology. Thus, semantic similarity can be calculated during the item-based and user-based collaborating filtering process. The item-based and user-based filtering process are used to predict the unknown rating of the original matrix. Results: Experimental evaluations have been carried out on the MovieLens 100k dataset to demonstrate the accuracy rate of our proposed approach as compared to the baseline method using (i) Singular Value Decomposition (SVD) and (ii) combination of item-based collaborative filtering technique with SVD. Experimental results demonstrated that our proposed method has reduced the data sparsity from 0.9542% to 0.8435%. In addition, it also indicated that our proposed method has achieved better accuracy with Root Mean Square Error (RMSE) of 0.9298, as compared to the baseline method (RMSE: 0.9642) and the existing method (RMSE: 0.9492). Conclusions: Our proposed method enhanced the dataset information by integrating user-based and item-based collaborative filtering techniques. The experiment results shows that our system has reduced the data sparsity and has better accuracy as compared to baseline method and existing method.
  20. Chia J, Chin JJ, Yip SC
    F1000Res, 2021;10:931.
    PMID: 36798451 DOI: 10.12688/f1000research.72910.1
    Digital signature schemes (DSS) are ubiquitously used for public authentication in the infrastructure of the internet, in addition to their use as a cryptographic tool to construct even more sophisticated schemes such as those that are identity-based. The security of DSS is analyzed through the existential unforgeability under chosen message attack (EUF-CMA) experiment which promises unforgeability of signatures on new messages even when the attacker has access to an arbitrary set of messages and their corresponding signatures. However, the EUF-CMA model does not account for attacks such as an attacker forging a different signature on an existing message, even though the attack could be devastating in the real world and constitutes a severe breach of the security system. Nonetheless, most of the DSS are not analyzed in this security model, which possibly makes them vulnerable to such an attack. In contrast, a better security notion known as strong EUF-CMA (sEUF-CMA) is designed to be resistant to such attacks. This review aims to identify DSS in the literature that are secure in the sEUF-CMA model. In addition, the article discusses the challenges and future directions of DSS. In our review, we consider the security of existing DSS that fit our criterion in the sEUF-CMA model; our criterion is simple as we only require the DSS to be at least secure against the minimum of existential forgery. Our findings are categorized into two classes: the direct and indirect classes of sEUF-CMA. The former is inherently sEUF-CMA without any modification while the latter requires some transformation. Our comprehensive  review contributes to the security and cryptographic research community by discussing the efficiency and security of DSS that are sEUF-CMA, which aids in selecting robust DSS in future design considerations.
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