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Fulltext Microalgal metabolites as anti-cancer/anti-oxidant agents reduce cytotoxicity of elevated silver nanoparticle levels against non-cancerous vero cells

Hussein HA, Maulidiani M, Abdullah MA

Heliyon, 2020 Oct;6(10):e05263.
PMID: 33102866 DOI: 10.1016/j.heliyon.2020.e05263

Heavy metal pollution has become a major concern globally as it contaminates eco-system, water networks and as finely suspended particles in air. In this study, the effects of elevated silver nanoparticle (AgNPs) levels as a model system of heavy metals, in the presence of microalgal crude extracts (MCEs) at different ratios, were evaluated against the non-cancerous Vero cells, and the cancerous MCF-7 and 4T1 cells. The MCEs were developed from water (W) and ethanol (ETH) as green solvents. The AgNPs-MCEs-W at the 4:1 and 5:1 ratios (v/v) after 48 and 72 h treatment, respectively, showed the IC50 values of 83.17-95.49 and 70.79-91.20 μg/ml on Vero cells, 13.18-28.18 and 12.58-25.7 μg/ml on MCF-7; and 16.21-33.88 and 14.79-26.91 μg/ml on 4T1 cells. In comparison, the AgNPs-MCEs-ETH formulation achieved the IC50 values of 56.23-89.12 and 63.09-91.2 μg/ml on Vero cells, 10.47-19.95 and 13.48-26.61 μg/ml on MCF-7; 14.12-50.11 and 15.13-58.88 μg/ml on 4T1 cells, respectively. After 48 and 72 h treatment, the AgNPs-MCE-CHL at the 4:1 and 5:1 ratios exhibited the IC50 of 51.28-75.85 and 48.97-69.18 μg/ml on Vero cells, and higher cytotoxicity at 10.47-16.98 and 6.19-14.45 μg/ml against MCF-7 cells, and 15.84-31.62 and 12.58-24.54 μg/ml on 4T1 cells, respectively. The AgNPs-MCEs-W and ETH resulted in low apoptotic events in the Vero cells after 24 h, but very high early and late apoptotic events in the cancerous cells. The Liquid Chromatography-Mass Spectrometry-Electrospray Ionization (LC-MS-ESI) metabolite profiling of the MCEs exhibited 64 metabolites in negative ion and 56 metabolites in positive ion mode, belonging to different classes. The microalgal metabolites, principally the anti-oxidative components, could have reduced the toxicity of the AgNPs against Vero cells, whilst retaining the cytotoxicity against the cancerous cells.
Fulltext Assessing the sustainability of the homestay industry for the East Coast of Malaysia using the Delphi approach

Zamzuki FA, Lola MS, Aruchunan E, Muthuvalu MS, Jubilee RVW, Zainuddin NH, et al.

Heliyon, 2023 Nov;9(11):e21433.
PMID: 38027815 DOI: 10.1016/j.heliyon.2023.e21433

Homestay ecotourism in Malaysia has been extensively examined in terms of its concepts, approaches, activities, and community engagement. However, a comprehensive assessment of the sustainability factors pertaining to host families remains a critical area awaiting exploration. This is paramount for ensuring the long-term viability of homestays and fostering economic benefits within rural communities. The present study seeks to establish direct subjective measurements for evaluating the interplay between local communities, tourism, and resources in safeguarding sustainable homestays. Utilizing the Delphi approach, this research conducted interviews with 51 experts who were actively involved in six homestays located on the East Coast of Peninsular Malaysia. The objective was to identify key evaluation indicators pertinent to the homestay industry. The findings underscored the pivotal roles played by community resources and tourism in the sustainability of homestays. Additionally, environmental, economic, and social factors emerged as crucial components for maintaining the industry's sustainability. This innovative assessment methodology offers a valuable instrument for enhancing the sustainability of the homestay sector, especially in the wake of the COVID-19 pandemic. By embracing this approach, homestay operators can fortify their sustainable management practices and prepare themselves for future pandemics. This study represents a significant contribution to the field of homestay ecotourism, emphasizing the imperative for continued research in this dynamic domain.
Fulltext Scientific mapping of research on English as a foreign language (EFL) reading instruction: A thirty-year perspective

Chen F, Abdullah R

Heliyon, 2024 Feb 15;10(3):e25217.
PMID: 38327399 DOI: 10.1016/j.heliyon.2024.e25217

In recent years, English as a foreign language (EFL) reading instruction has emerged as a prominent and recurring research theme in the realm of education. Despite this growing interest, prior studies have not outlined the research status of EFL reading instruction from a bibliometric lens. Addressing this gap, the present study aims to provide valuable insights into the research landscape of EFL reading instruction by using scientific mapping analysis on documents sourced from the Web of Science Database between 1994 and 2023. The study found that: 1) The analysis of publication trends suggests that the field of EFL reading instruction continues to evolve, with a foreseeable ongoing increase in research output. 2) Asian countries, specifically Iran, China, and Saudi Arabia emerge as leading contributors and collaborators in terms of research on EFL reading instruction. 3) Authors mainly from Asian countries demonstrate the highest levels of productivity and citation impact. 4) The most productive and cited journals primarily originate from developed countries, notably the United Kingdom and the United States. 5) The research foci identified cover various aspects such as "technology-based instruction," "critical thinking," and "literacy skills." However, there is an emerging shift in research focus towards themes "English proficiency," "Covid-19," "technology," "blended learning" and "mobile-assisted language learning (MALL)." By shedding light on the significant concepts and trends of the research field, this study adds to the burgeoning body of literature and provides valuable guidance to new scholars seeking to enrich their knowledge and perspectives on this particular topic.
Fulltext Bioaugmentation of Vibrio alginolyticus in phytoremediation of aluminium-contaminated soil using Scirpus grossus and Thypa angustifolia

Purwanti IF, Obenu A, Tangahu BV, Kurniawan SB, Imron MF, Abdullah SRS

Heliyon, 2020 Sep;6(9):e05004.
PMID: 33005804 DOI: 10.1016/j.heliyon.2020.e05004

This research analyses the performance of bacteria-assisted phytoremediation of aluminium (Al)-contaminated soil using native Indonesian plants namely, Scirpus grossus and Thypa angustifolia. A range finding test (RFT) was carried out for 14 days to obtain the tolerable Al concentration for both plants. A total of 2% and 5% (v/v) of Vibrio alginolyticus were bioaugmented during the 28-day phytoremediation test to enhance the overall Al removal. Result of the RFT showed that both plants can tolerate up to 500 mg/kg Al concentration. The addition of V. alginolyticus to the reactors resulted in a significant increment of Al removal from the contaminated soil (p < 0.05). Such addition of V. alginolyticus increased the Al removal by up to 14.0% compared with that without-bacteria addition. The highest Al removal was obtained for S. grossus with 5% V. alginolyticus with an efficiency of 35.1% from 500 mg/kg initial concertation. T. angustifolia with 500 mg/kg initial concentration showed the highest removal of 26.2% by the addition of 5% V. alginolyticus. The increase of Al removal by the bioaugmentation of V. alginolyticus was due to the interaction in the plant's rhizosphere. Exudates of both plants provided a good environment for bacteria to live in the root area. Meanwhile, the bacteria increased the bioavailability of Al to be further extracted by plants. Certain mechanisms, such as rhizostabilisation, phytostimulation and phytoextraction, were considered to be the main processes that occurred during the treatment. S. grossus and T. angustifolia displayed promising ability to act as Al hyperaccumulators with bioaccumulation factor values up to 5.308 and 3.068, respectively. Development of the design of the ex-situ soil phytoremediation reactors is suggested as a future research direction because it can significantly enhance the current obtained finding.
Fulltext A call to action: Unpacking the challenges to implementing social sustainability initiatives in a developing country city

Razia S, Abu Bakar Ah SH

Heliyon, 2023 Aug;9(8):e19085.
PMID: 37636356 DOI: 10.1016/j.heliyon.2023.e19085

With cities sprawling and populations booming in developing regions, ensuring social sustainability in urban areas has become more urgent. This study investigates the challenges of implementing social sustainability initiatives for cities in developing countries, focusing on Dhaka as a representative city. A mixed-method approach involving structured questionnaire surveys and key informant interviews was used to collect quantitative and qualitative data. The study identified eighteen challenges to implementing social sustainability initiatives in Dhaka city, including a lack of poor urban governance, an inefficient city management system, a lack of political stability, a long delay in the planning approval process, etc. Additionally, experts identified additional challenges that require attention. The study offers empirical evidence to assist government officials, policymakers, and urban planners overcome these challenges and implement social sustainability effectively. To address the identified challenges, the study recommends revisiting the Structure Plan, Urban Area Plan, Detailed Area Plan, and Urban Sector Policy-2011. It highlights the crucial role of community social workers in mitigating specific issues in socially sustainable urban development. Eventually, the study will contribute to the implementation of SDG-11 in the 2030 Agenda for Sustainable Development by bridging the gap between urbanization and socially sustainable cities.
Fulltext Chemical constituents, usage and pharmacological activity of Cassia alata

Fatmawati S, Yuliana, Purnomo AS, Abu Bakar MF

Heliyon, 2020 Jul;6(7):e04396.
PMID: 32685725 DOI: 10.1016/j.heliyon.2020.e04396

Cassia alata or locally known as Ketepeng Cina (Indonesia) and Gelenggang (Malaysia) has been used as a traditional medicine to treat various diseases, especially skin diseases. In addition, C. alata has been reported to have potential anti allergic, anti inflammatory, antioxidant, anticancer, antidiabetic, and antifungal. Metabolite compounds that have been isolated from C. alata include flavones, flavonols, flavonoids glycosides, alatinon, alanonal and β-sitosterol-β-D-glucoside. The compounds have been isolated mainly from the leaves. Further identification is needed to discover the secondary metabolites from other parts of the plant such as seed, flower and bark which are reported to have potent antibacterial and antifungal activity. Therefore, this article highlights the secondary metabolites and biological activity of this plant which has been shown to have pharmacological properties against selected diseases.
Fulltext Identification and analysis of hoisting safety risk factors for IBS construction based on the AcciMap and cases study

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

Heliyon, 2024 Jan 15;10(1):e23587.
PMID: 38192814 DOI: 10.1016/j.heliyon.2023.e23587

Hoisting is an essential aspect of Industrial Building System (IBS) construction. Although research on hoisting safety in China has made strides to focus on "worker," "data," "task," "site," and "accident," there still needs to be more approaches based on multi-dimensional social system thinking. Therefore, the paper aims to fill this gap. We investigated 105 hoisting accidents in China and found that hoisting accidents occurred most frequently in China's southeast coastal region; truck-mounted cranes and tower cranes were the most common types of machinery involved in accidents; hoisting load off, capsizing of crane machinery, and workers falling from height are the three most common accident types; the average impact of a single hoisting accident is approximately RMB 2.43 million direct economic loss, 1.543 deaths and 0.829 injured. This study used three algorithms (Rindge regression, Lasson regression, and partial least squares regression) to explore the impact of deaths and injuries on direct economic losses. By combining Rasmussen's risk framework with the characteristics of hoisting construction, six risk domains and thirty-six safety risk factors were identified. Finally, we used AcciMap technology to construct a qualitative IBS hoisting management model, which exhaustively presents the systematic levels and propagation paths of the influencing factors by the PDCA method. The research helps academics explore strategies to improve the safety of hoisting construction in IBS. Moreover, the study outcomes can inform the policy-making process towards promoting healthy and sustainable construction development.
Fulltext Sustainability risk management: Are Malaysian companies ready?

Abdul Razak SE, Mustapha M, Mohammed Shah S, Abu Kasim NA

Heliyon, 2024 Feb 15;10(3):e24681.
PMID: 38317937 DOI: 10.1016/j.heliyon.2024.e24681

The sustainability issues resulting from Malaysian palm oil production have garnered much interest in the palm oil industry. Consequently, Malaysian palm oil industry is indirectly exposed to sustainability risks, including boycott and reputational and regulatory risks. Hence, the industry encounters intense pressure from numerous stakeholders to address sustainability issues. Prior studies propounded that sustainability risk management (SRM) could minimise the adverse impact of sustainability risks by addressing sustainability issues. Nevertheless, the implementation of sustainability risk management in Malaysia remains low as numerous companies are not ready for it. Drawing on contingency theory, the objective of this study is to investigate the influence of contextual factors that can influence companies' readiness in implementing sustainability risk management. Data was collected through the distribution of questionnaires between July and December 2020. A total of 407 questionnaires were distributed, with a response rate of 29 %. Resultantly, sustainability strategy, business size, top management support, and regulatory pressure positively and significantly influenced sustainability risk management implementation. The findings also expanded the current theoretical knowledge with valuable insights for policymakers regarding the factors influencing to companies' readiness in implementing SRM.
Fulltext Implementation of machine learning in DNA barcoding for determining the plant family taxonomy

Riza LS, Zain MI, Izzuddin A, Prasetyo Y, Hidayat T, Abu Samah KAF

Heliyon, 2023 Oct;9(10):e20161.
PMID: 37767518 DOI: 10.1016/j.heliyon.2023.e20161

The DNA barcoding approach has been used extensively in taxonomy and phylogenetics. The differences in certain DNA sequences are able to differentiate and help classify organisms into taxa. It has been used in cases of taxonomic disputes where morphology by itself is insufficient. This research aimed to utilize hierarchical clustering, an unsupervised machine learning method, to determine and resolve disputes in plant family taxonomy. We take a case study of Leguminosae that historically some classify into three families (Fabaceae, Caesalpiniaceae, and Mimosaceae) but others classify into one family (Leguminosae). This study is divided into several phases, which are: (i) data collection, (ii) data preprocessing, (iii) finding the best distance method, and (iv) determining disputed family. The data used are collected from several sources, including National Center for Biotechnology Information (NCBI), journals, and websites. The data for validation of the methods were collected from NCBI. This was used to determine the best distance method for differentiating families or genera. The data for the case study in the Leguminosae group was collected from journals and a website. From the experiment that we have conducted, we found that the Pearson method is the best distance method to do clustering ITS sequence of plants, both in accuracy and computational cost. We use the Pearson method to determine the disputed family between Leguminosae. We found that the case study of Leguminosae should be grouped into one family based on our research.
Flux model development and synthesis optimization for an enhanced GO embedded nanocomposite membrane through FFD and RSM approach

Abdul Wahab MS, Abd Rahman S, Abu Samah R

Heliyon, 2020 Nov;6(11):e05610.
PMID: 33305039 DOI: 10.1016/j.heliyon.2020.e05610

A two-level full factorial design was used to analyze several factors involved in PSF-GO-Pebax thin film nanocomposite membranes development. Permeate flux was chosen as a single response for four possible factors: Pebax selective layer concentration, amount of GO load to Pebax selective layer, Pebax-GO selective layer thickness, and amount of GO load to PSF substrate. The study is aimed at factors interaction and contribution towards the highest permeation flux via FFD and RSM approach. R2 obtained from the ANOVA is 0.9937 with Pebax concentration as the highest contributing factor. Pebax concentration-amount of GO load to PSF substrate is the only interaction contributing to the highest flux. A regression analysis concluded the study with model development and an optimized condition for the membrane design.
Fulltext Development and validation of an instrument to assess the knowledge and perceptions of predatory journals

Marar S, Hamza MA, Ayyash M, Abu-Shaheen A

Heliyon, 2023 Nov;9(11):e22270.
PMID: 38045152 DOI: 10.1016/j.heliyon.2023.e22270

OBJECTIVE: The main aim of this study is to develop a valid and reliable instrument to assess levels of knowledge and perceptions of predatory journals.
METHODS: The current study employed successive methods framework including (1) item generation through a literature review and theoretical framework development, (2) validity testing in terms of face, content, and construct validity for perceptions construct as well as item analysis for knowledge scale, and (3) reliability testing in terms of Cronbach's alpha, Kuder-Richardson (KR-20), item-to-total correlations, corrected item-to-total correlations, Cronbach's alpha if item deleted, and test-retest reliability. A total of 304 participants were recruited from King Fahad Medical City (KFMC) in Riyadh, Saudi Arabia to evaluate its construct validity and reliability. This was established using exploratory factor analysis (EFA) with principal axis factoring (PFA) and varimax rotation as well as confirmatory factor analysis (CFA) for perception construct.
RESULTS: An instrument was developed from this study called the "Predatory Journals KP Assessment Questionnaire". The results of EFA and CFA confirmed the construct validity of the perception construct. Item analysis confirmed the construct validity of the knowledge scale. The internal consistency and test-retest reliability were achieved for the knowledge scale items, consisting of 13 items. The results of EFA confirmed the measured constructs of perceptions toward predatory journals. The results of EFA and CFA for perception construct resulted in only one factor with 9 items.
CONCLUSION: This study has successfully developed a valid and reliable questionnaire to measure knowledge and perceptions of predatory journals among researchers in the clinical and health disciplines. This instrument serves as a valuable guide for future studies that aim to assess researcher's knowledge and perceptions about predatory journals and examine the differences in these measured constructs according to their demographic and professional characteristics.
Fulltext Optimizing brushless direct current motor design: An application of the multi-objective generalized normal distribution optimization

Pandya SB, Jangir P, Mahdal M, Kalita K, Chohan JS, Abualigah L

Heliyon, 2024 Feb 29;10(4):e26369.
PMID: 38404848 DOI: 10.1016/j.heliyon.2024.e26369

In this study, we tackle the challenge of optimizing the design of a Brushless Direct Current (BLDC) motor. Utilizing an established analytical model, we introduced the Multi-Objective Generalized Normal Distribution Optimization (MOGNDO) method, a biomimetic approach based on Pareto optimality, dominance, and external archiving. We initially tested MOGNDO on standard multi-objective benchmark functions, where it showed strong performance. When applied to the BLDC motor design with the objectives of either maximizing operational efficiency or minimizing motor mass, the MOGNDO algorithm consistently outperformed other techniques like Ant Lion Optimizer (ALO), Ion Motion Optimization (IMO), and Sine Cosine Algorithm (SCA). Specifically, MOGNDO yielded the most optimal values across efficiency and mass metrics, providing practical solutions for real-world BLDC motor design. The MOGNDO source code is available at: https://github.com/kanak02/MOGNDO.
Fulltext Multi-objective liver cancer algorithm: A novel algorithm for solving engineering design problems

Kalita K, Naga Ramesh JV, Čep R, Pandya SB, Jangir P, Abualigah L

Heliyon, 2024 Mar 15;10(5):e26665.
PMID: 38486727 DOI: 10.1016/j.heliyon.2024.e26665

This research introduces the Multi-Objective Liver Cancer Algorithm (MOLCA), a novel approach inspired by the growth and proliferation patterns of liver tumors. MOLCA emulates the evolutionary tendencies of liver tumors, leveraging their expansion dynamics as a model for solving multi-objective optimization problems in engineering design. The algorithm uniquely combines genetic operators with the Random Opposition-Based Learning (ROBL) strategy, optimizing both local and global search capabilities. Further enhancement is achieved through the integration of elitist non-dominated sorting (NDS), information feedback mechanism (IFM) and Crowding Distance (CD) selection method, which collectively aim to efficiently identify the Pareto optimal front. The performance of MOLCA is rigorously assessed using a comprehensive set of standard multi-objective test benchmarks, including ZDT, DTLZ and various Constraint (CONSTR, TNK, SRN, BNH, OSY and KITA) and real-world engineering design problems like Brushless DC wheel motor, Safety isolating transformer, Helical spring, Two-bar truss and Welded beam. Its efficacy is benchmarked against prominent algorithms such as the non-dominated sorting grey wolf optimizer (NSGWO), multiobjective multi-verse optimization (MOMVO), non-dominated sorting genetic algorithm (NSGA-II), decomposition-based multiobjective evolutionary algorithm (MOEA/D) and multiobjective marine predator algorithm (MOMPA). Quantitative analysis is conducted using GD, IGD, SP, SD, HV and RT metrics to represent convergence and distribution, while qualitative aspects are presented through graphical representations of the Pareto fronts. The MOLCA source code is available at: https://github.com/kanak02/MOLCA.
Fulltext The mediating effect of interpersonal distrust on the relationship between perceived organizational politics and workplace ostracism in higher education institutions

Karim DN, Abdul Majid AH, Omar K, Aburumman OJ

Heliyon, 2021 Jun;7(6):e07280.
PMID: 34258449 DOI: 10.1016/j.heliyon.2021.e07280

Despite a widespread consensus towards the implications of workplace ostracism to employees, little research attention has been paid to exploring its determinants, especially in the educational sector. In the context of higher education institutions, workplace ostracism can lead to a number of undesired outcomes, such as deviant workplace behavior, turnover, and decreased job performance. Thus, this study aims to explore the role of perceived organizational politics in promoting workplace ostracism. Drawing on the social exchange theory, the study also attempts to identify the mediating role of interpersonal distrust in the relationship between perceived organizational politics and workplace ostracism in higher education institutions. Data were conveniently collected from 154 full-time faculty members serving in five public universities in Bangladesh. To test the research hypotheses, the study employed partial least squares path modeling. The findings revealed that there is a significant positive association between perceived organizational politics and workplace ostracism and that interpersonal distrust plays an intervening role in the relationship. These results highlight the role of perceived organizational politics and interpersonal distrust in shaping academics' workplace ostracism. Based on the findings, the study suggests both practical and theoretical implications with directions for future research.
Fulltext Clinical and genetic profile in index patients with spinocerebellar ataxia type 3 in Indonesia: case report

Aminah S, Huda F, Gamayani U, Pusparini I, Mochyadin MFA, Sribudiani Y, et al.

Heliyon, 2021 Jul;7(7):e07519.
PMID: 34345727 DOI: 10.1016/j.heliyon.2021.e07519

Spinocerebellar ataxia (SCA) is an autosomal dominant hereditary disease with progressive course, and no causal therapy. Diagnostics are still challenging, due to facility and protocols, and so as in Indonesia. As a national referral center, Dr. Hasan Sadikin Central General Hospital has received a lot of patients from all over Indonesia, particularly from Western Java. Study related to SCA (including clinical and genetic profile) is still limited in Indonesia. We identified index patients from three families with ataxia, hence intend to determine their clinical and genetic pattern. The hereditary pattern is autosomal dominant. Scale for the assessment and rating of ataxia (SARA) shows mild and moderate ataxia. Inventory of non-ataxia signs (INAS) scores of the patients were 3, 5 and 6. Montreal cognitive assessment-Indonesian version (MOCA-INA) shows only one patient has mild cognitive impairment, despite young age. Barthel index shows 1 subject has moderate dependency. Mutation in Ataxin3 polyQ repeats shows pathologically long CAG repeats, 72,10; 72,10; and 72,23 respectively in mutant and wild type allele. We diagnosed the index patients with spinocerebellar ataxia type 3. This study is the first case series study in Indonesia. The hereditary pattern is clearly shown as an autosomal dominant ataxia. The clinical and genetic profile was varied, and the symptom is progressive and deteriorates overtime, including wide based gait, speech problem, motor and sensor complaint, and cognitive decline complaint. Despite the same polyQ stretch length, the onset and clinical characteristics of patients are diverse.
Fulltext Impact of intrapersonal and interpersonal emotional intelligence and self-directed learning on academic performance among pre-university science students

Okwuduba EN, Nwosu KC, Okigbo EC, Samuel NN, Achugbu C

Heliyon, 2021 Mar;7(3):e06611.
PMID: 33869848 DOI: 10.1016/j.heliyon.2021.e06611

Provision of equitable access to university education is the primary goal of pre-university education. Academically weak students stand to benefit more from pre-university program. However, available literature on effectiveness of the program revealed that high percentage of students still fail pre-university courses. Although the role of psycho-emotional factors on student academic performance has been highlighted, mechanism through which psycho-emotional factors impact on academic performance of pre-university science students is still not clear to offer adequate insights for proper intervention program. Therefore, we examined the pre-university students' academic performance in sciences in relation to Emotional Intelligence (EI) (Interpersonal EI and Intrapersonal EI) and Self-directed Learning (SDL). Specifically, a correlational study design was conducted to measure and gauge the level of relationships amongst Interpersonal EI, Intrapersonal EI, SDL and academic performance of pre-university students. The participants were 443 Nigerian students enrolled in pre-university science program. Students' self-report on EI and SDL were gathered and analyzed using SPSS 26 and AMOS 24. Exploratory and confirmatory factor analysis were performed to determine cross-cultural validity of the instruments in the Nigerian context. After controlling for gender and age, the hierarchical regression analysis reveals that student academic performance was positively predicted by perceived Interpersonal and Intrapersonal EI, whereas self-directed learning has an inconsistent predictive impact at different steps in the model. Overall, the predictor variables were able to explain substantial proportion of students' academic performance in pre-university program. Insightful suggestions were made.
Fulltext Prediction of methyl orange dye (MO) adsorption using activated carbon with an artificial neural network optimization modeling

Alardhi SM, Fiyadh SS, Salman AD, Adelikhah M

Heliyon, 2023 Jan;9(1):e12888.
PMID: 36699265 DOI: 10.1016/j.heliyon.2023.e12888

In this study, methyl orange (MO) dye removal by adsorption utilizing activated carbon made from date seeds (DPAC) was modeled using an artificial neural network (ANN) technique. Instrumental investigations such as X-ray diffraction (XRD), scanning electron microscopy (SEM), and Brunauer-Emmett-Teller (BET) analysis were used to assess the physicochemical parameters of adsorbent. By changing operational parameters including adsorbent dosage (0.01-0.03 g), solution pH 3-8, initial dye concentration (5-20 mg/L), and contact time (2-60 min), the viability of date seeds for the adsorptive removal of methyl orange dye from aqueous solution was assessed in a batch procedure. The system followed the pseudo 2nd order kinetic model for DPAC adsorbent, according to the kinetic study (R2 = 0.9973). The mean square error (MSE), relative root mean square error (RRMSE), root mean square error (RMSE), mean absolute percentage error (MAPE), relative error (RE), and correlation coefficient (R2) were used to measure the ANN model performance. The maximum RE was 8.24% for the ANN model. Two isotherm models, Langmuir and Freundlich, were studied to fit the equilibrium data. Compared with the Freundlich isotherm model (R2 = 0.72), the Langmuir model functioned better as an adsorption isotherm with R2 of 0.9902. Thus, this study demonstrates that the dye removal process can be predicted using an ANN technique, and it also suggests that adsorption onto DPAC may be employed as a main treatment for dye removal from wastewater.
Fulltext Estimating sediment yield at Kaduna watershed, Nigeria using soil and water assessment tool (SWAT) model

Daramola J, Ekhwan TM, Mokhtar J, Lam KC, Adeogun GA

Heliyon, 2019 Jul;5(7):e02106.
PMID: 31372557 DOI: 10.1016/j.heliyon.2019.e02106

Over the years, sedimentation has posed a great danger to the storage capacity of hydropower reservoirs. Good understanding of the transport system and hydrological processes in the dam is very crucial to its sustainability. Under optimal functionality, the Shiroro dam in Northern Nigeria can generate ∼600 MW, which is ideally sufficient to power about 404,000 household. Unfortunately, there have not been reliable monitoring measures to assess yield in the upstream, where sediments are sourced into the dam. In this study, we applied the Soil and Water Assessment Tool (SWAT) to predict the hydrological processes, the sediment transport mechanism and sediment yield between 1990 and 2018 in Kaduna watershed (32,124 km2) located upstream of the dam. The model was calibrated and validated using observed flow and suspended sediment concentration (SSC) data. Performance evaluation of the model was achieved statistically using Nash-Sutcliffe (NS), coefficient of determination (r2) and percentage of observed data (p-factor). SWAT model evaluation using NS (0.71), r2 (0.80) and p-factors of 0.86 suggests that the model performed satisfactorily for streamflow and sediment yield predictions. The model identified the threshold depth of water (GWQMN.gw) and base flow (ALPHA_BF.gw) as the most sensitive parameters for streamflow and sediment yield estimation in the watershed. Our finding showed that an estimated suspended sediment yield of about 84.1 t/ha/yr was deposited within the period under study. Basins 67, 71 and 62 have erosion prone area with the highest sediment values of 79.4, 75.1 and 73.8 t/h respectively. Best management practice is highly recommended for the dam sustainability, because of the proximity of erosion-prone basins to the dam.
Capital structure determinants across sectors: Comparison of observed evidences from the use of time series and panel data estimators

Rehan R, Abdul Hadi AR, Hussain HI, Adnan Hye QM

Heliyon, 2023 Sep;9(9):e19618.
PMID: 37810001 DOI: 10.1016/j.heliyon.2023.e19618

This comparative study is an attempt to explore the determinants of capital structure for Malaysian firms listed in various sectors level. Within the framework of traditional and moderate dynamic capital structure theories, the key determinants such as fixed assets, current assets, return on equity, size, earning per share and total assets are tested in relation to the debt-equity ratio. The large-scale study entails data collected from 551 listed firms of Bursa Malaysia main market over 12 years period i.e. 2005-2016. Notably, this study combines Time Series econometrics with Panel Data analysis to enhance methodological robustness. Moreover, the comparative analysis approach is designated to recognize the most persistent capital structure determinants. In the first place, the Multiple Regression analysis (MRA) is selected as a baseline estimation method. Subsequently, the Auto Regression Distributed Lag model (ARDL), the Panel Data Static models, and Dynamic model via the Generalized Method of Moments (GMM) are employed to identify the capital structure determinants for the firms listed at Bursa Malaysia. The outcomes are surprising and indicate that the entire market is primarily controlled by the studied determinant total assets, which is significant in both construction and property sectors through MRA, ARDL, and GMM analysis. Technically, the significant role of tangibility and the existence of speed of adjustment across sectors imply that the Dynamic Capital Structure is the most prominent among all, followed by the Dynamic Trade-off theory.
Fulltext Estimation of soil erodibility in Peninsular Malaysia: A case study using multiple linear regression and artificial neural networks

Rehman MA, Abd Rahman N, Ibrahim ANH, Kamal NA, Ahmad A

Heliyon, 2024 Apr 15;10(7):e28854.
PMID: 38576554 DOI: 10.1016/j.heliyon.2024.e28854

Soil erodibility (K) is an essential component in estimating soil loss indicating the soil's susceptibility to detach and transport. Data Computing and processing methods, such as artificial neural networks (ANNs) and multiple linear regression (MLR), have proven to be helpful in the development of predictive models for natural hazards. The present case study aims to assess the efficiency of MLR and ANN models to forecast soil erodibility in Peninsular Malaysia. A total of 103 samples were collected from various sites and K values were calculated using the Tew equation developed for Malaysian soil. From several extracted parameters, the outcomes of correlation and principal component analysis (PCA) revealed the influencing factors to be used in the development of ANN and MLR models. Based on the correlation and PCA results, two sets of influencing factors were employed to develop predictive models. Two MLR (MLR-1 and MLR-2) models and four neural networks (NN-1, NN-2, NN-3, and NN-4) optimized using Levenberg-Marquardt (LM) and scaled conjugate gradient (SCG) were developed and evaluated. The model performance validation was conducted using the coefficient of determination (R2), mean squared error (MSE), root mean squared error (RMSE), and Nash-Sutcliffe efficiency coefficient (NSE). The analysis showed that ANN models outperformed MLR models. The R2 values of 0.446 (MLR-1), 0.430 (MLR-2), 0.894 (NN-1), 0.855 (NN-2), 0.940 (NN-3), and 0.826 (NN-4); MSE values of 0.0000306 (MLR-1), 0.0000315 (MLR-2), 0.0000158 (NN-1), 0.0000261 (NN-2), 0.0000318 (NN-3), and 0.0000216 (NN-4) suggested the higher accuracy and lower modelling error of ANN models as compared with MLR. This study could provide an empirical basis and methodological support for K factor estimation in the region.

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