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Fulltext Measuring the motives of informal entrepreneurs

Othman NS, Marthandan G, Ab Aziz K

F1000Res, 2022;11:56.
PMID: 36545376 DOI: 10.12688/f1000research.73706.2

Background - Handling non-observed activities pose major challenges to the governments and other stakeholders. Non-observed activities refer to underground activities, illegal activities, informal sector and any other activities that result in goods or services consumed by the household. The impact of these non-observed activities shows that the volume of people involved in the informal sector will rapidly increase. Informal economic activities are technically illegal yet are not intended as antisocial, thereby remaining acceptable to many individuals within the society. This research aimed to identify the factors that lead to entrepreneurial necessity and opportunity. Methods - The data of 51 respondents who were employed as informal entrepreneurs in Klang Valley areas in Malaysia was collected with the use of a questionnaire and convenient and proportionate sampling techniques. The data were analysed using SPSS software. Results - The two primary drivers of informal entrepreneurial activity were necessity and opportunity. The inability to find a formal job was an example of being driven by necessity. Meanwhile, individuals that are driven by opportunity chose to work independently in these informal sectors. Between necessity and engagement, refinement acted as a mediator. Often, necessity and opportunity do not automatically translate into successful entrepreneurship; further refinement is required in terms of market potential, technology usage, location preferences, and capital requirements. Improved refinement results in increased entrepreneurial engagement. Conclusions - The role and contribution of the informal sector entrepreneurship in economic development need to be evaluated and not just observed as an opportunity for individuals who choose this type of career. Therefore, further research is required in a wider variety of contexts to evaluate whether the same remains true in different populations. The results of this study can be useful for the government to set policies to encourage the transition of informal to formal entrepreneurships in Malaysia.
Numerical model for enhancing stimulated Brillouin scattering in optical microfibers

Yeap SH, Emami SD, Abdul-Rashid HA

F1000Res, 2021;10:521.
PMID: 37745939 DOI: 10.12688/f1000research.51029.2

Stimulated Brillouin scattering (SBS) is useful, among others for generating slow light, sensing and amplification. SBS was previously viewed as a poor method due to the limitation on optical power in high-powered photonic applications. However, considering the many possible applications using SBS, it is now of interest to enhance SBS in areas of Brillouin frequency shift together with Brillouin Gain. A numerical model, using a fully vectorial approach, by employing the finite element method, was developed to investigate methods for enhancing SBS in optical fiber. This paper describes the method related to the numerical model and discusses the analysis between the interactions of longitudinal, shear and hybrid acoustic modes; and optical modes in optical fiber. Two case studies were used to demonstrate this. Based on this numerical model, we report the influence of core radius, clad radius and effective refractive index on the Brillouin frequency shift and gain. We observe the difference of Brillouin shift frequency between a normal silica optical fiber and that of a microfiber - a uniformed silica fiber of a much smaller core and cladding dimensions where nonlinearities are higher. Also observed, the different core radii used and their respective Brillouin shift. For future work, the COMSOL model can also be used for the following areas of research, including simulating "surface Brillouin shift" and also to provide in-sights to the Brillouin shift frequency vB of various structures of waveguides, e.g circular, and triangular, and also to examine specialty fibers, e.g. Thulium and Chalcogenide doped fibers, and their effects on Brillouin shift frequency.
Fulltext Optimised deep neural network model to predict asthma exacerbation based on personalised weather triggers

Haque R, Ho SB, Chai I, Abdullah A

F1000Res, 2021;10:911.
PMID: 34745565 DOI: 10.12688/f1000research.73026.1

Background - Recently, there have been attempts to develop mHealth applications for asthma self-management. However, there is a lack of applications that can offer accurate predictions of asthma exacerbation using the weather triggers and demographic characteristics to give tailored response to users. This paper proposes an optimised Deep Neural Network Regression (DNNR) model to predict asthma exacerbation based on personalised weather triggers. Methods - With the aim of integrating weather, demography, and asthma tracking, an mHealth application was developed where users conduct the Asthma Control Test (ACT) to identify the chances of their asthma exacerbation. The asthma dataset consists of panel data from 10 users that includes 1010 ACT scores as the target output. Moreover, the dataset contains 10 input features which include five weather features (temperature, humidity, air-pressure, UV-index, wind-speed) and five demography features (age, gender, outdoor-job, outdoor-activities, location). Results - Using the DNNR model on the asthma dataset, a score of 0.83 was achieved with Mean Absolute Error (MAE)=1.44 and Mean Squared Error (MSE)=3.62. It was recognised that, for effective asthma self-management, the prediction errors must be in the acceptable loss range (error<0.5). Therefore, an optimisation process was proposed to reduce the error rates and increase the accuracy by applying standardisation and fragmented-grid-search. Consequently, the optimised-DNNR model (with 2 hidden-layers and 50 hidden-nodes) using the Adam optimiser achieved a 94% accuracy with MAE=0.20 and MSE=0.09. Conclusions - This study is the first of its kind that recognises the potentials of DNNR to identify the correlation patterns among asthma, weather, and demographic variables. The optimised-DNNR model provides predictions with a significantly higher accuracy rate than the existing predictive models and using less computing time. Thus, the optimisation process is useful to build an enhanced model that can be integrated into the asthma self-management for mHealth application.
Fulltext Relationship and career challenges faced by people infected with HIV in Malaysia

Tuan Abdullah TN, Mat Min R, Hossain M, Abdullah SS

F1000Res, 2019;8:1994.
PMID: 33214871 DOI: 10.12688/f1000research.21079.3

Background: In Malaysia, there are still lack of studies related to the challenges of people infected with HIV (PIWH). Therefore, this study was conducted to explore the experiences of PIWH and how they cope with HIV. Methods: This qualitative study was based on a social constructivist and grounded theory approach. A total of 12 PIWH were selected by purposive sampling, all of whom participated in semi-structured and audio-recorded interviews, which were supported with non-participant observations and diary entries on three occasions for each participant. The interviews and diaries were transcribed and analysed using the grounded theory approach, which was assisted by utilizing NVIVO-8 to identify the themes related to the experiences of the participants. Results: PIWH experienced challenges related to their career and relationships with family and others. These challenges led to difficulties in gaining employment and career development, as well as feelings of denial, being uncomfortable, rejection, and labelling. They found that their lives were totally and dramatically changed after being tested positive for HIV. Conclusions: Among PIWH, HIV impacted relationships with significant others and career development. The absence of support and acceptance from significant others affected the ability of PIWH to cope with their daily challenges. The results of this study have implications for policymakers in terms of gaining sufficient knowledge and awareness to provide prevention programmes for HIV/AIDS.
Fulltext Ocimum basilicum (kemangi) intervention on powder and microencapsulated Spirulina platensis and its bioactive molecules

Yuliani Y, Riyadi PH, Dewi EN, Jaswir I, Agustini TW

F1000Res, 2021;10:485.
PMID: 35083034 DOI: 10.12688/f1000research.52394.2

Background: Spirulina platensis contains several bioactive molecules such as phenol, flavonoid and phycocyanin pigments. This study unveils total phenol, flavonoid, antioxidant activity, phycocyanin content and evaluated encapsulation efficiency from Ocimum basilicum intervention on S. platensis. O. basilicum intervention aims to reduce unpleasant odors from S. platensis that will increase consumption and increase bioactive compounds. Methods: The intervention was carried out by soaking a S. platensis control sample (SP) in O. basilicum with a ratio of 1:4 (w/v) and it was then dried (DSB) and microencapsulated by freeze drying methods (MSB) using a combination of maltodextrin and gelatin. Total flavonoid and phenolic analysis with curve fitting analysis used a linear regression approach. Antioxidant activity of samples was analysed with the 2,2'-azino-bis-3-3thylbenzthiazoline-6-sulphonic acid (ABTS) method. Data were analysed using ANOVA at significance level (p < 0.05) followed by Tukey test models using SPSS v.22. Results: The result of this study indicated that O. basilicum intervention treatment (DSB) has the potential to increase bioactive compounds such as total phenol, antioxidant activity and phycocyanin, and flavonoid content. Intervention of O. basilicum on S. platensis (DSB) significantly increases total phenol by 49.5% and phycocyanin by 40.7%. This is due to the phenol and azulene compounds in O. basilicum which have a synergistic effect on phenol and phycocyanin in S. platensis. Microencapsulation using a maltodexrin and gelatin coating is effective in phycocyanin protection and antioxidant activity with an encapsulation efficiency value of 71.58% and 80.5%. Conclusion: The intervention of O. basilicum on S. platensis improved the total phenol and phycocyanin content and there is potential for a pharmaceutical product for a functional food and pharmaceutical product.
Fulltext COVID-19 impact: Customised economic stimulus package recommender system using machine learning techniques

Kannan R, Wang IZW, Ong HB, Ramakrishnan K, Alamsyah A

F1000Res, 2021 09 16;10:932.
PMID: 34925768 DOI: 10.12688/f1000research.72976.2

Background: The Malaysian government reacted to the pandemic's economic effect with the Prihatin Rakyat Economic Stimulus Package (ESP) to cushion the novel coronavirus 2019 (COVID-19) impact on households. The ESP consists of cash assistance, utility discount, moratorium, Employee Provident Fund (EPF) cash withdrawals, credit guarantee scheme and wage subsidies. A survey carried out by the Department of Statistics Malaysia (DOSM) shows that households prefer different types of financial assistance. These preferences forge the need to effectively customise ESPs to manage the economic burden among low-income households. In this study, a recommender system for such ESPs was designed by leveraging data analytics and machine learning techniques. Methods: This study used a dataset from DOSM titled "Effects of COVID-19 on the Economy and Individual - Round 2," collected from April 10 to April 24, 2020. Cross-Industry Standard Process for Data Mining was followed to develop machine learning models to classify ESP receivers according to their preferred subsidies types. Four machine learning techniques-Decision Tree, Gradient Boosted Tree, Random Forest and Naïve Bayes-were used to build the predictive models for each moratorium, utility discount and EPF and Private Remuneration Scheme (PRS) cash withdrawals subsidies. The best predictive model was selected based on F-score metrics. Results: Among the four machine learning techniques, Gradient Boosted Tree outperformed the rest. This technique predicted the following: moratorium preferences with 93.8% sensitivity, 82.1% precision and 87.6% F-score; utilities discount with 86% sensitivity, 82.1% precision and 84% F-score; and EPF and PRS with 83.6% sensitivity, 81.2% precision and 82.4% F-score. Households that prefer moratorium subsidies did not favour other financial aids except for cash assistance. Conclusion: Findings present machine learning models that can predict individual household preferences from ESP. These models can be used to design customised ESPs that can effectively manage the financial burden of low-income households.
Fulltext Molecular characterization and genetic diversity of four undescribed novel oleaginous Mortierella alpina strains from Libya

Muftah Eltariki FE, Tiwari K, Alhoot MA

F1000Res, 2021;10:895.
PMID: 34745563 DOI: 10.12688/f1000research.70644.1

Background: A large number of undiscovered fungal species still exist on earth, which can be useful for bioprospecting, particularly for single cell oil (SCO) production. Mortierella is one of the significant genera in this field and contains about hundred species. Moreover, M. alpina is the main single cell oil producer at commercial scale under this genus. Methods: Soil samples from four unique locations of North-East Libya were collected for the isolation of oleaginous Mortierella alpina strains by a serial dilution method. Morphological identification was carried out using light microscopy (Olympus, Japan) and genetic diversity of the isolated Mortierella alpina strains was assessed using conserved internal transcribed spacer (ITS) gene sequences available on the NCBI GenBank database for the confirmation of novelty. The nucleotide sequences reported in this study have been deposited at GenBank (accession no. MZ298831:MZ298835). The MultAlin program was used to align the sequences of closely related strains. The DNA sequences were analyzed for phylogenetic relationships by molecular evolutionary genetic analysis using MEGA X software consisting of Clustal_X v.2.1 for multiple sequence alignment. The neighbour-joining tree was constructed using the Kimura 2-parameter substitution model. Results: The present research study confirms four oleaginous fungal isolates from Libyan soil. These isolates (barcoded as MSU-101, MSU-201, MSU-401 and MSU-501) were discovered and reported for the first time from diverse soil samples of district Aljabal Al-Akhdar in North-East Libya and fall in the class: Zygomycetes; order: Mortierellales. Conclusions: Four oleaginous fungal isolates barcoded as MSU-101, MSU-201, MSU-401 and MSU-501 were identified and confirmed by morphological and molecular analysis. These fungal isolates showed highest similarity with Mortierella alpina species and can be potentialistic single cell oil producers. Thus, the present research study provides insight to the unseen fungal diversity and contributes to more comprehensive Mortierella alpina reference collections worldwide.
Factors influencing COVID-19 vaccine acceptance in Indonesia: an adoption of Technology Acceptance Model

Faturohman T, Kengsiswoyo GAN, Harapan H, Zailani S, Rahadi RA, Arief NN

F1000Res, 2021;10:476.
PMID: 34621508 DOI: 10.12688/f1000research.53506.2

Background: It is critical to understand the factors that could affect the acceptance of the coronavirus disease 2019 (COVID-19) vaccine in the community. The aim of this study was to determine factors that could possibly affect the acceptance of Indonesian citizens of COVID-19 vaccination using a Technology Acceptance Model (TAM), a model how users come to accept and use a technology. Methods: An online survey was conducted between the first and fifth of November, 2020. Participants were asked to respond to questions on acceptance, perceived usefulness, perceived ease of use, perceived religiosity towards, and amount of information about COVID-19. This study used the Technology Acceptance Model (TAM) as the framework to decide factors that affect vaccine acceptance. Structural Equation Model was employed to assess the correlation between all explanatory variables and vaccine acceptance. Mann-Whitney test and Kruskal-Wallis rank were employed to assess demographic factors associated with acceptance. Results: In total, 311 responses were included for analysis. Our TAM model suggested that high perceived usefulness significantly increased COVID-19 vaccine acceptance and high perceived ease of use significantly increased the perceived usefulness. Perceived religiosity did not substantially affect vaccine acceptance. The amount of information on COVID-19 also did not significantly affect vaccine acceptance. Our data suggested that vaccine acceptance was associated with age, type of occupation, marital status and monthly income to some degree. Conclusion: Since perceived usefulness affects vaccine acceptance, the government should focus on the usefulness of the vaccine when promoting the COVID-19 vaccine to Indonesian citizens. In addition, since perceived ease of use significantly affects users' acceptance to COVID-19 vaccine, the easier to acquire the vaccine in the community, the higher chance that the citizens are willing to be vaccinated.
Fulltext Kyasanur forest disease virus: viremia and challenge studies in monkeys with evidence of cross-protection by Langat virus infection

Shah KV, Dandawate CN, Bhatt PN

F1000Res, 2012;1:61.
PMID: 24627765 DOI: 10.12688/f1000research.1-61.v1

Kyasanur Forest Disease Virus (KFDV), discovered in 1957, is a member of the tick-borne encephalitis virus (TBEV) complex. Diseases caused by members of the TBEV complex occur in many parts of the world. KFDV produces a hemorrhagic fever in humans in South India and fatal illnesses in both species of monkeys in the area, the black faced langur (Presbytis entellus) and the bonnet macaque (Macaca radiata). Experimental infection of the langur and the bonnet macaque with early mouse passage KFDV strain P9605 resulted in a viremia of up to 11 days duration, peak viremia titers as high as 10 (9), and death in 82 = 100% of the animals. Prolonged passage of the KFDV strain P9605 in monkey kidney tissue culture resulted in a markedly reduced virulence of the virus for both species; peak viremia titers in monkeys decreased by 2.5 to 4.0 log LD 50 (p= 0.001), and the mortality decreased to 10% (p= 0.001). In challenge experiments, monkeys previously infected with tissue-culture-adapted KFDV, or with the related Langat virus from Malaysia, were fully protected against virulent KFDV. These studies in non-human primates lend support to the idea that a live virus vaccine from a member of the TBEV complex may be broadly protective against infections by other members of the TBEV complex.
Fulltext Lightning Behaviour during the COVID-19 Pandemic

Yusfiandika F, Lim SC, Gomes C, Chockalingam A, Cheng Pay L

F1000Res, 2021 09 09;10:906.
PMID: 34804502 DOI: 10.12688/f1000research.70650.2

Background COVID-19 has drastically dampened human activities since early 2020. Studies have shown that this has resulted in changes in air temperature and humidity. Since lightning activities are dependent on air temperature and humidity, this study is conducted to evaluate the correlation between the intensity of lightning activities with the atmospheric changes, and investigates the changes, in lightning activities due to atmospheric changes during the COVID-19 pandemic. Methods The hypothesis was tested through a t-test and Pearson's correlation study. The variation trend of lightning strikes count (LSC) in Europe and Oceania during the five months COVID-19 lockdown period (March - July) compared to the same period in the previous five years from 2015 to 2019 is investigated. Results Statistical analysis shows the LSC in Europe and Oceania during the lockdown period dropped significantly by more than 50% and 44% respectively compared to the same period in previous five years. Furthermore, LSC was found to be positively correlated with air temperature and relative humidity in Europe. However, in Oceania, LSC seems to be only positively correlated with air temperature but negatively correlated with relative humidity. Conclusions This study seems to suggest that lightning activities have significantly changed during this pandemic due to reduction in human activities.
Fulltext Formulation and characterisation of alginate hydrocolloid film dressing loaded with gallic acid for potential chronic wound healing

Gan JE, Chin CY

F1000Res, 2021;10:451.
PMID: 34249341 DOI: 10.12688/f1000research.52528.1

Background: A dramatic growth in the prevalence of chronic wounds due to diabetes has represented serious global health care and economic issues. Hence, there is an imperative need to develop an effective and affordable wound dressing for chronic wounds. Recent research has featured the potential of bioactive compound gallic acid (GA) in the context of wound recovery due to their safety and comparatively low cost. However, there is a scarcity of research that focuses on formulating GA into a stable and functional hydrocolloid film dressing. Thus, this present study aimed to formulate and characterise GA-loaded alginate-based hydrocolloid film dressing which is potentially used as low to medium suppurating chronic wound treatment. Methods: The hydrocolloid composite films were pre-formulated by blending sodium alginate (SA) with different combinations of polymers. The hydrocolloid films were developed using solvent-casting method and the most satisfactory film formulation was further incorporated with various GA concentrations (0.1%, 0.5% and 1%). The drug-loaded films were then characterised for their physicochemical properties to assess their potential use as drug delivery systems for chronic wound treatment. Results: In the pre-formulation studies, sodium alginate-pectin (SA-PC) based hydrocolloid film was found to be the most satisfactory, for being homogenous and retaining smoothness on surface along with satisfactory film flexibility. The SA-PC film was chosen for further loading with GA in 0.1%, 0.5% and 1%. The characterisation studies revealed that all GA-loaded films possess superior wound dressing properties of acidic pH range (3.97-4.04), moderate viscosity (1600 mPa-s-3198 mPa-s), optimal moisture vapor transmission rate (1195 g/m 2/day, 1237g/m 2/day and 1112 g/m 2/day), slower moisture absorption and film expansion rate and no chemical interaction between the GA and polymers under FTIR analysis. Conclusion: An SA-PC hydrocolloid film incorporated with gallic acid as a potentially applicable wound dressing for low to medium suppurating chronic wounds was successfully developed.
Obesogenic Environment in the medical field: First year findings from a five-year cohort study

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.
Fulltext Income and obesity in an urban poor community: a cross-sectional study

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.
Fulltext Lifestyle and reproductive health: the aetiology of ovarian cancer in Pakistan

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.
Fulltext Parents' perceptions on policies of early childhood care and education programmes in selected states of Malaysia

Tang D, Peng Chew F, Abdul Rahman M, Dhamotharan M

F1000Res, 2022;11:938.
PMID: 36226043 DOI: 10.12688/f1000research.122443.2

BACKGROUND: The 2030 agenda for sustainable development proposed global equitable quality education and lifelong learning opportunities for all children . The quality of early childhood care and education (ECCE) programs helps shape children's minds, attitudes and behaviors, and has short and long-term effects on a child, a family and a country. In Malaysia, the government has formulated some policies and laws to protect children's rights. However, ECCE is facing some challenges. The purpose of this study is to investigate parents' perceptions of the quality of ECCE programs implemented by Malaysian government.
METHODS: A mixed method was used to collect data on parents' perceptions of ECCE policies in selected states in Malaysia. The questionnaires, (P1/POL) from the research project "Development of a Comprehensive and Integrated Model of Quality Malaysian ECCE", were distributed among 629 respondents who have a child in a preschool, and 22 participants were randomly selected to take part in five focus group interviews Results: The key findings of the study revealed 68% parents were not familiar with ECCE Malaysian government policy, however 84.3% stressed it is important for the government to educate them about ECCE. Thus findings indicated that the majority of parents lack awareness of the ECCE policies and quality of early childhood care and education programs related to the policies remain the issue. While interviewing the focus group ,most of them were not aware of ECCE and pointed out parents are stressing children's academic learning in particular preschools.
CONCLUSIONS: It is concluded that parents' awareness regarding the ECCE program must be part of the policies and needs to improve. It is recommended that the government of Malaysia should supply more information on ECCE policies to parents and focus on policy implementation. Moreover, the quality of ECCE programs should be improved based on the parents' perceptions.
Fulltext Post-pandemic e-learning: a pre-protocol to assess the impact of mobile VR on learner motivation and engagement for VARK learning styles

Manzoor SR, Mohd-Isa WN, Dollmat KS

F1000Res, 2021;10:1106.
PMID: 35646326 DOI: 10.12688/f1000research.73311.2

Background: The Covid-19 pandemic has resulted in an abrupt but accelerated shift to e-learning worldwide. Education in a post-pandemic world has to amalgamate the advantages of e-learning with important pedagogical goals associated with in-person teaching. Although various advanced technologies are present at our fingertips today, we are still unable to use their full potential in teaching and learning. In this regard, mobile VR technology is both cost-efficient, versatile and engaging for students. Developing countries have more smartphone users than developed countries, implying that developing countries, like Malaysia, should utilize mobile or cellphones more significantly. With that in mind, we propose here a pre-protocol to investigate learner motivation and levels of engagement for e-learning with smartphone-integrated VR, based on their VARK (Visual, Auditory, Read/Write, Kinesthetic) learning styles. Proposed methodology: This study intends to look into students from the same age group under the K-12 (particularly grade 9-12) belonging to STEM curriculum. The Google Cardboard VR set will be used as the prime technology for its affordability, easy build feature and variety of available vendors. A mixed-method (survey and activity log/tracking) for data collection is suggested to find the degree of engagement and motivation of the learners' learning in the mobile VR-assisted e-learning context. The students will be taught a topic using the mobile VR and then be assessed through simple classroom quizzes to assess how well they grasped the concept. The data collected through activity logs (while teaching the topic in mobile VR) and questionnaires will be mapped to each individual learner and organized in a data repository. Further visualization, analysis and investigation will be performed using Smart PLS, Python or R language. Conclusions: The study aims to provide context for smartphone and software companies to develop technologies that could facilitate learner motivation and engagement during the post-pandemic state.
Fulltext Development of species-specific SCAR markers for identification and authentication of three rare Peninsular Malaysian endemic Coelogyne (Orchidaceae) orchids

Kok Hon Y, Yong CS, Abdullah JO, Go R

F1000Res, 2020;9:1161.
PMID: 33299554 DOI: 10.12688/f1000research.26170.2

Background:Coelogyne kaliana, Coelogyne stenochila and Coelogyne tiomanensis are three valuable rare orchid species endemic to Peninsular Malaysia, currently rampantly traded illegally via the internet and through local nurseries, which label them as hybrids to avoid enforcement detection. Drastic measures to ensure the continued existence of their populations in the wild should be introduced as they are rapidly diminishing into extinction, including the development of rapid and accurate species-specific identification tools. These three orchid species are highly similar morphologically and currently it is impossible to distinguish among them without their reproductive structures. Methods: RAPD-based species-specific SCAR markers were developed to distinguish and authenticate the identity of these three endemic Peninsular Malaysian Coelogyne species. Results: Three SCAR markers were successfully developed in this study. SCAR marker primer pair , CKL_f / CKL_r was specific to C. kaliana as it produced a unique single band of 271 bp but not in C. stenochila and C. tiomanensis. SCAR marker primer pair CST_f / CST_r amplified a single band of 854 bp in C. stenochila and two bands of different sizes (372 bp and 858 bp) in C. tiomanensis, but no amplification in C. kaliana. The third SCAR marker primer pair, CTI_f / CTI_r produced a single band (about 500 bp) for both C. stenochila and C. tiomanensis, but showed no amplification in C. kaliana. Conclusions: Although not all these SCAR markers were species amplification specific, they could be used to discriminate among the three Coelogyne species effectively. Accurate species identification is one of the most important steps to allow a proper management plan to be established in the effort to conserve these three endangered orchid species of Peninsular Malaysia. Besides, it could effectively put a stop to the illegal trading of these rare endangered orchid species worldwide.
Fulltext Lightning safety awareness level in Malaysia

Nazri K, Lim SC, Gomes C

F1000Res, 2021;10:921.
PMID: 34909192 DOI: 10.12688/f1000research.73064.2

Introduction: Malaysia is one of the countries with the highest lightning flash density globally. While sufficiency of lightning protection system is crucial to ensure human safety against lightning strikes, the public awareness towards lightning safety is also equally important in Malaysia. Hence, this study was conducted to understand the current lightning safety awareness level of the Malaysian population. Methods: An online questionnaire survey which consists of 22 scientific statements of lightning was first developed in Malay and English. The questionnaire allows the respondent to also check their own score upon completion of the questionnaire. It was then distributed to the public for data collection. The sample size comprised of both genders, all layers of society from various educational level and social background. Results: Overall, the awareness on lightning safety amongst Malaysian is at moderate level with an average score of slightly above 50%. Urbanites scored marginally better than their rural counterparts. One's education level does not dictate their awareness level of lightning safety. Discussion: In conclusion, the public in Malaysia needs to be better educated on lightning safety. Similar studies should be replicated in other countries experiencing similar levels of lightning activity to better understand the public's perception on lightning.
Practice and knowledge of dietary supplement consumption among Indonesian adults post-delta wave of the COVID-19 pandemic

d'Arqom A, Nasution MZ, Kadir SZSA, Yusof J, Govindaraju K

F1000Res, 2023;12:3.
PMID: 37469719 DOI: 10.12688/f1000research.129045.2

Background: Increasing dietary supplement (DS) consumption was observed during the COVID-19 pandemic, including during the post-Delta wave period. This study aimed to measure the practice of DS consumption and respondents' knowledge of DS. Methods: An internet-based survey was distributed from October-December 2021 and obtained 541 valid and completed responses. Descriptive analysis was performed to present the practice of DS consumption, including frequency, duration, aim, preferable dosage form etc. Level of knowledge on DS principles, side effects and regulation were also measured. Inferential analyses were conducted to determine the predictors of the respondents' DS practice and level of knowledge. Results: Data from 541 valid responses showed that 77.63% of respondents consumed DS in the last 3 months, with only 59.52% reporting also consuming DS before the COVID-19 pandemic. One half of the respondents had good knowledge about DS; however, some knowledge regarding side effects and possible drug-supplement interaction needed improvement. Their DS consumption practice was affected by their economic status and history of contracting COVID-19. Nevertheless, the level of knowledge was not affected by the sociodemographic factors and DS supplement experience. Conclusions: Taken together, the practice of self-consumption of DS in Indonesia is increasing; hence, knowledge of DS is necessary to avoid detrimental effects that might occur in the future. Increasing access to information on better labelling and educating consumers about DS are important actions to consider.
Fulltext Machine learning methods to predict particulate matter PM 2.5

Palanichamy N, Haw SC, S S, Murugan R, Govindasamy K

F1000Res, 2022;11:406.
PMID: 36531254 DOI: 10.12688/f1000research.73166.1

Introduction Pollution of air in urban cities across the world has been steadily increasing in recent years. An increasing trend in particulate matter, PM 2.5, is a threat because it can lead to uncontrollable consequences like worsening of asthma and cardiovascular disease. The metric used to measure air quality is the air pollutant index (API). In Malaysia, machine learning (ML) techniques for PM 2.5 have received less attention as the concentration is on predicting other air pollutants. To fill the research gap, this study focuses on correctly predicting PM 2.5 concentrations in the smart cities of Malaysia by comparing supervised ML techniques, which helps to mitigate its adverse effects. Methods In this paper, ML models for forecasting PM 2.5 concentrations were investigated on Malaysian air quality data sets from 2017 to 2018. The dataset was preprocessed by data cleaning and a normalization process. Next, it was reduced into an informative dataset with location and time factors in the feature extraction process. The dataset was fed into three supervised ML classifiers, which include random forest (RF), artificial neural network (ANN) and long short-term memory (LSTM). Finally, their output was evaluated using the confusion matrix and compared to identify the best model for the accurate prediction of PM 2.5. Results Overall, the experimental result shows an accuracy of 97.7% was obtained by the RF model in comparison with the accuracy of ANN (61.14%) and LSTM (61.77%) in predicting PM 2.5. Discussion RF performed well when compared with ANN and LSTM for the given data with minimum features. RF was able to reach good accuracy as the model learns from the random samples by using decision tree with the maximum vote on the predictions.

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