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  1. Fulltext New marketing strategy model of E-commerce enterprises in the era of digital economy
    Ma X, Gu X
    Heliyon, 2024 Apr 30;10(8):e29038.
    PMID: 38628774 DOI: 10.1016/j.heliyon.2024.e29038
    With the continuous development of technology, traditional marketing methods no longer meet the needs of the main forces of social consumption, and people urgently need more innovative and personalized marketing strategies. E-commerce companies must develop a comprehensive customer-oriented marketing strategy based on big data and multi-channel to achieve their long-term healthy development. This paper first investigated the impact of the digital economy on e-commerce enterprises, focused on the transformation of the digital economy on the marketing model, expounded the development analysis of e-commerce in the digital economy era, and described the development trend of e-commerce marketing in the digital economy era. Then, this paper expounded the current problems faced by e-commerce enterprises, and discussed the lack of integrity, homogeneity, large-scale marketing strategies, and the lack of analysis and application of big data. After that, this paper put forward the marketing strategy of e-commerce enterprises in the digital economy era, and studied it from three aspects, namely, building a reasonable product management structure, marketing strategy based on customized marketing content, and social media marketing strategy based on information sharing. Then this paper proposed to use genetic algorithm to strengthen the marketing strategy of e-commerce enterprises. Finally, based on experiments and surveys, this paper used genetic algorithms to strengthen the construction of e-commerce enterprise marketing strategy in the digital economy, and concluded that the new e-commerce enterprise marketing strategy was 21% more satisfactory than the traditional new e-commerce enterprise marketing strategy. Through comparison, it can see that the integrity of the marketing plan of the new e-commerce enterprise's marketing strategy was 0.33 higher than that of the traditional e-commerce enterprise's marketing strategy, and the integrity of the promotion strategy was 0.34 higher than that of the traditional e-commerce enterprise's marketing strategy. After using the new e-commerce enterprise marketing strategy, the improved management structure was 0.29 higher than that of the traditional monitoring system, and the high quality of products was 0.18 higher than that of the traditional system.
  2. Fulltext Extended TAM based acceptance of AI-Powered ChatGPT for supporting metacognitive self-regulated learning in education: A mixed-methods study
    Dahri NA, Yahaya N, Al-Rahmi WM, Aldraiweesh A, Alturki U, Almutairy S, et al.
    Heliyon, 2024 Apr 30;10(8):e29317.
    PMID: 38628736 DOI: 10.1016/j.heliyon.2024.e29317
    This mixed-method study explores the acceptance of ChatGPT as a tool for Metacognitive Self-Regulated Learning (MSRL) among academics. Despite the growing attention towards ChatGPT as a metacognitive learning tool, there is a need for a comprehensive understanding of the factors influencing its acceptance in academic settings. Engaging 300 preservice teachers through a ChatGPT-based scenario learning activity and utilizing convenience sampling, this study administered a questionnaire based on the proposed Technology Acceptance Model at UTM University's School of Education. Structural equation modelling was applied to analyze participants' perspectives on ChatGPT, considering factors like MSRL's impact on usage intention. Post-reflection sessions, semi-structured interviews, and record analysis were conducted to gather results. Findings indicate a high acceptance of ChatGPT, significantly influenced by personal competency, social influence, perceived AI usefulness, enjoyment, trust, AI intelligence, positive attitude, and metacognitive self-regulated learning. Interviews and record analysis suggest that academics view ChatGPT positively as an educational tool, seeing it as a solution to challenges in teaching and learning processes. The study highlights ChatGPT's potential to enhance MSRL and holds implications for teacher education and AI integration in educational settings.
  3. Fulltext A comprehensive review of mycotoxins: Toxicology, detection, and effective mitigation approaches
    Khan R, Anwar F, Ghazali FM
    Heliyon, 2024 Apr 30;10(8):e28361.
    PMID: 38628751 DOI: 10.1016/j.heliyon.2024.e28361
    Mycotoxins, harmful compounds produced by fungal pathogens, pose a severe threat to food safety and consumer health. Some commonly produced mycotoxins such as aflatoxins, ochratoxin A, fumonisins, trichothecenes, zearalenone, and patulin have serious health implications in humans and animals. Mycotoxin contamination is particularly concerning in regions heavily reliant on staple foods like grains, cereals, and nuts. Preventing mycotoxin contamination is crucial for a sustainable food supply. Chromatographic methods like thin layer chromatography (TLC), gas chromatography (GC), high-performance liquid chromatography (HPLC), and liquid chromatography coupled with a mass spectrometer (LC/MS), are commonly used to detect mycotoxins; however, there is a need for on-site, rapid, and cost-effective detection methods. Currently, enzyme-linked immunosorbent assays (ELISA), lateral flow assays (LFAs), and biosensors are becoming popular analytical tools for rapid detection. Meanwhile, preventing mycotoxin contamination is crucial for food safety and a sustainable food supply. Physical, chemical, and biological approaches have been used to inhibit fungal growth and mycotoxin production. However, new strains resistant to conventional methods have led to the exploration of novel strategies like cold atmospheric plasma (CAP) technology, polyphenols and flavonoids, magnetic materials and nanoparticles, and natural essential oils (NEOs). This paper reviews recent scientific research on mycotoxin toxicity, explores advancements in detecting mycotoxins in various foods, and evaluates the effectiveness of innovative mitigation strategies for controlling and detoxifying mycotoxins.
  4. Fulltext Experimental investigation and analytical verification of buckling of functionally graded carbon nanotube-reinforced sandwich beams
    Madenci E, Özkılıç YO, Bahrami A, Aksoylu C, Asyraf MRM, Hakeem IY, et al.
    Heliyon, 2024 Apr 30;10(8):e28388.
    PMID: 38638992 DOI: 10.1016/j.heliyon.2024.e28388
    Carbon nanotube (CNT) reinforcement can lead to a new way to enhance the properties of composites by transforming the reinforcement phases into nanoscale fillers. In this study, the buckling response of functionally graded CNT-reinforced composite (FG-CNTRC) sandwich beams was investigated experimentally and analytically. The top and bottom plates of the sandwich beams were composed of carbon fiber laminated composite layers and hard core. The hard core was made of a pultruded glass fiber-reinforced polymer (GFRP) profile. The layers of FG-CNTRC surfaces were reinforced with different proportions of CNT. The reference sample was made of only a pultruded GFRP profile. In the study, the reference sample and four samples with CNT were tested under compression. The largest buckling load difference between the reference sample and the sample with CNT was 37.7%. The difference between the analytical calculation results and experimental results was obtained with an approximation of 0.49%-4.92%. Finally, the buckling, debonding, interlaminar cracks, and fiber breakage were observed in the samples.
  5. Fulltext Network pharmacology-based approach to elucidate the pharmacologic mechanisms of natural compounds from Dictyostelium discoideum for Alzheimer's disease treatment
    Patil N, Dhariwal R, Mohammed A, Wei LS, Jain M
    Heliyon, 2024 Apr 30;10(8):e28852.
    PMID: 38644825 DOI: 10.1016/j.heliyon.2024.e28852
    Alzheimer's disease (AD) is increasingly becoming a major public health concern in our society. While many studies have explored the use of natural polyketides, alkaloids, and other chemical components in AD treatment, there is an urgent need to clarify the concept of multi-target treatment for AD. This study focuses on using network pharmacology approach to elucidate how secondary metabolites from Dictyostelium discoideum affect AD through multi-target or indirect mechanisms. The secondary metabolites produced by D. discoideum during their development were obtained from literature sources and PubChem. Disease targets were selected using GeneCards, DisGeNET, and CTD databases, while compound-based targets were identified through Swiss target prediction and Venn diagrams were used to find intersections between these targets. A network depicting the interplay among disease, drugs, active ingredients, and key target proteins (PPI network) was formed utilizing the STRING (Protein-Protein Interaction Networks Functional Enrichment Analysis) database. To anticipate the function and mechanism of the screened compounds, GO and KEGG enrichment analyses were conducted and visually presented using graphs and bubble charts. After the screening phase, the top interacting targets in the PPI network and the compound with the most active target were chosen for subsequent molecular docking and molecular dynamic simulation studies. This study identified nearly 50 potential targeting genes for each of the screened compounds and revealed multiple signaling pathways. Among these pathways, the inflammatory pathway stood out. COX-2, a receptor associated with neuroinflammation, showed differential expression in various stages of AD, particularly in pyramidal neurons during the early stages of the disease. This increase in COX-2 expression is likely induce by higher levels of IL-1, which is associated with neuritic plaques and microglial cells in AD. Molecular docking investigations demonstrated a strong binding interaction between the terpene compound PQA-11 and the neuroinflammatory receptor COX2, with a substantial binding affinity of -8.4 kcal/mol. Subsequently, a thorough analysis of the docked complex (COX2-PQA11) through Molecular Dynamics Simulation showed lower RMSD, minimal RMSF fluctuations, and a reduced total energy of -291.35 kJ/mol compared to the standard drug. These findings suggest that the therapeutic effect of PQA-11 operates through the inflammatory pathway, laying the groundwork for further in-depth research into the role of secondary metabolites in AD treatment.
  6. Fulltext Unmasking the challenges in ideological and political education in China: A thematic review
    Ouyang S, Zhang W, Xu J, Mat Rashid A, How SP, Bin Hassan A
    Heliyon, 2024 Apr 30;10(8):e29176.
    PMID: 38644869 DOI: 10.1016/j.heliyon.2024.e29176
    China's distinctive educational approach, particularly its emphasis on ideological and political education, has garnered considerable academic attention for its impact on shaping individual values, fostering citizenship, and maintaining social stability. Despite the Chinese government's prioritization of ideological and political education, academic research in this field appears constrained, with existing studies predominantly focusing on normative and descriptive aspects. Normative research delineates how ideological and political education should be executed, while descriptive research illustrates its practical implementation. The effectiveness of these approaches is significantly diminished if they are not adequately interconnected-when only the current reality is explained without providing tools for improvement or when prescribed steps for improvement lack a basis in specific contexts. This paper conducts a comprehensive review of research on ideological and political education using ATLAS. ti 9 for thematic analysis. The review aims to unveil the intricate landscape of current research in China and address key questions: What are the primary trends in the literature on ideological and political education between 2021 and July 2023? What challenges does ideological and political education face? Through a direct exploration of these issues, this paper seeks to optimize the ideological and political education system, elevate its adaptability and effectiveness, and open avenues for research, fostering a more dynamic, inclusive, and resilient development of ideological and political education.
  7. Fulltext Influence of Maqian essential oil on gut microbiota and immunoresponses in type 1 diabetes: In silico study
    Dahab M, Idris H, Zhang P, Aladhadh M, Alatawi EA, Ming LC, et al.
    Heliyon, 2024 Apr 30;10(8):e29490.
    PMID: 38655301 DOI: 10.1016/j.heliyon.2024.e29490
    Diversity and homeostasis of gut bacterial composition is highly associated with the pathogenesis of insulin dysfunction and type 1 diabetes melittus (T1D), hence emerged in parallel with the activation of autoimmunity. We aimed to study the bioactive potential of essential oil from Zanthoxylum myriacanthum var. pubescens Huang (Maqian) through computational approaches. Twelve chemical constituents derived from Maqian essential oil were docked with selected proteins (i.e., 3pig, 1kho, 7dmq, 4m4d, 2z65, 4glp, and 3fxi) in which are involved in gut microbiota modulation in T1D. Subsequently, the prediction of bioavailability properties of the small molecules were evaluated. Among all chemical constituents, the post-docking interaction analysis demonstrated that α-phellandrene exhibits the strongest binding affinity and induces gut microbiota modulation with β-fructofuranosidase from Bifidobacterium longum. The current result revealed the potential of 3-Carene and α-Pinene in inducing specific changes in gut microbiota downregulating Clostridium perfringens and quenching Leptotrichia shahii respectively. β-Pinene possess exceptionally strong binding affinity that effectively disrupt the interaction between lipopolysaccharide and its cognate receptors, while α-Phellandrene was exhibited the uppermost binding affinity with TLR4/MD2 and could likely target TLR4 stimulating lipopolysaccharide. Our results are the first to report on the gut microbiota modulation effects of α-Phellandrene and β-Phellandrene via actions on LPS binding to CD14 and the TLR4 co-receptor signaling. In conclusion, our findings based on computational approaches, small molecules from Maqian present as promising agents which could regulate inflammatory response and modulate gut microbiota in type 1 diabetes mellitus.
  8. Fulltext A CMIP6 multi-model based analysis of potential climate change effects on watershed runoff using SWAT model: A case study of kunhar river basin, Pakistan
    Waheed A, Jamal MH, Javed MF, Idlan Muhammad K
    Heliyon, 2024 Apr 30;10(8):e28951.
    PMID: 38655367 DOI: 10.1016/j.heliyon.2024.e28951
    The hydrological regimes of watersheds might be drastically altered by climate change, a majority of Pakistan's watersheds are experiencing problems with water quality and quantity as a result precipitation changes and temperature, necessitating evaluation and alterations to management strategies. In this study, the regional water security in northern Pakistan is examined about anthropogenic climate change on runoff in the Kunhar River Basin (KRB), a typical river in northern Pakistan using Soil and Water Assessment tool (SWAT) and flow durarion curve (FDC). Nine general circulation models (GCMs) were successfully utilized following bias correction under two latest IPCC shared socioeconomic pathways (SSPs) emission scenarios. Correlation coefficients (R2), Nash-Sutcliffe efficiency coefficients (NSE), and the Percent Bias (PBIAS) are all above 0.75. The conclusions demonstrate that the SWAT model precisely simulates the runoff process in the KRB on monthly and daily timescales. For the two emission scenarios of SSP2-4.5 and SSP5-8.5, the mean annual precipitation is predicted to rise by 3.08 % and 5.86 %, respectively, compared to the 1980-2015 baseline. The forecasted rise in mean daily high temperatures is expected to range from 2.08 °C to 3.07 °C, while the anticipated increase in mean daily low temperatures is projected to fall within the range of 2.09 °C-3.39 °C, spanning the years 2020-2099. Under the two SSPs scenarios, annual runoff is estimated to increase by 5.47 % and 7.60 % due to climate change during the same period. Future socioeconomic growth will be supported by a sufficient water supply made possible by the rise in runoff. However, because of climate change, there is a greater possibility of flooding because of increases in both rainfall and runoff. As a result, flood control and development plans for KRB must consider the climate change's possible effects. There is a chance that the peak flow will move backwards relative to the baseline.
  9. Fulltext Improved accuracy in IoT-Based water quality monitoring for aquaculture tanks using low-cost sensors: Asian seabass fish farming
    Mohd Jais NA, Abdullah AF, Mohd Kassim MS, Abd Karim MM, M A, Muhadi N'
    Heliyon, 2024 Apr 30;10(8):e29022.
    PMID: 38655304 DOI: 10.1016/j.heliyon.2024.e29022
    Traditional approaches to monitoring water quality in aquaculture tanks present numerous limitations, including the inability to provide real-time data, which can lead to improper feeding practices, reduced productivity, and potential environmental risks. To address these challenges, this study aimed to create an accurate water quality monitoring system for Asian seabass fish farming in aquaculture tanks. This was achieved by enhancing the accuracy of low-cost sensors using simple linear regression and validating the IoT system data with YSI Professional Pro. The system's development and validation were conducted over three months, employing professional devices for accuracy assessment. The accuracy of low-cost sensors was significantly improved through simple linear regression. The results demonstrated impressive accuracy levels ranging from 76% to 97%. The relative error values which range from 0.27% to 4% demonstrate a smaller range compared to the values obtained from the YSI probe during the validation process, signifying the enhanced accuracy and reliability of the IoT sensor by using simple linear regression. The system's enhanced accuracy facilitates convenient and reliable real-time water quality monitoring for aquafarmers. Real-time data visualization was achieved through a microcontroller, Thingspeak, Virtuino application, and ESP 8266 Wi-Fi module, providing comprehensive insights into water quality conditions. Overall, this adaptable tool holds promise for accurate water quality management in diverse aquatic farming practices, ultimately leading to improved yields and sustainability.
  10. Fulltext Digital transformation as the driving force for sustainable business performance: A moderated mediation model of market-driven business model innovation and digital leadership capabilities
    Chen A, Li L, Shahid W
    Heliyon, 2024 Apr 30;10(8):e29509.
    PMID: 38655293 DOI: 10.1016/j.heliyon.2024.e29509
    Global organizations are still facing challenges in achieving sustainable performance despite the surge in digital technologies. It is imperative that firms invest in digital capabilities to secure sustainable market performance in the face of a barrage of novel inventions. Today, ensuring a resilient future demands business to focus on digital ambidexterity capabilities (i.e., exploitation and exploration), digitalized strategy adoption, and digital transformation. This study investigates the intricate dynamics between digital capabilities and digitalization strategies and their impact on sustainable business performance. The research employed a questionnaire-driven methodology to gather data from managerial personnel within industries. Results show that digital exploitation and exploration capabilities significantly enhance sustainable business performance. The research also establishes the beneficial effect of adopting a digitalization strategy on business performance and innovation. Market-driven business model innovation emerges as a critical factor, not only driving sustainable performance but also serving as a mediating link between various digital strategies and business success. Moreover, the study highlights the importance of digital leadership capabilities, further strengthening the relationship between innovative business models and sustainable performance. The findings underscore the synergistic effect of digital competencies and strategic digitalization in promoting sustainable and innovative practices in today's digital-driven business landscape.
  11. Mixed cations tin-germanium perovskite: A promising approach for enhanced solar cell applications
    Adli Azizman MS, Azhari AW, Ibrahim N, Che Halin DS, Sepeai S, Ludin NA, et al.
    Heliyon, 2024 Apr 30;10(8):e29676.
    PMID: 38665575 DOI: 10.1016/j.heliyon.2024.e29676
    Significant progress has been made over the years to improve the stability and efficiency of rapidly evolving tin-based perovskite solar cells (PSCs). One powerful approach to enhance the performance of these PSCs is through compositional engineering techniques, specifically by incorporating a mixed cation system at the A-site and B-site structure of the tin perovskite. These approaches will pave the way for unlocking the full potential of tin-based PSCs. Therefore, in this study, a theoretical investigation of mixed A-cations (FA, MA, EA, Cs) with a tin-germanium-based PSC was presented. The crystal structure distortion and optoelectronic properties were estimated. SCAPS 1-D simulations were employed to predict the photovoltaic performance of the optimized tin-germanium material using different electron transport layers (ETLs), hole transport layers (HTLs), active layer thicknesses, and cell temperatures. Our findings reveal that EA0.5Cs0.5Sn0.5Ge0.5I3 has a nearly cubic structure (t = 0.99) and a theoretical bandgap within the maximum Shockley-Queisser limit (1.34 eV). The overall cell performance is also improved by optimizing the perovskite layer thickness to 1200 nm, and it exhibits remarkable stability as the temperature increases. The short-circuit current density (Jsc) remains consistent around 33.7 mA/cm2, and the open-circuit voltage (Voc) is well-maintained above 1 V by utilizing FTO as the conductive layer, ZnO as the ETL, Cu2O as the HTL, and Au as the metal back contact. This configuration also achieves a high fill factor ranging from 87 % to 88 %, with the highest power conversion efficiency (PCE) of 31.49 % at 293 K. This research contributes to the advancement of tin-germanium perovskite materials for a wide range of optoelectronic applications.
  12. Artificial intelligence and social media on academic performance and mental well-being: Student perceptions of positive impact in the age of smart learning
    Shahzad MF, Xu S, Lim WM, Yang X, Khan QR
    Heliyon, 2024 Apr 30;10(8):e29523.
    PMID: 38665566 DOI: 10.1016/j.heliyon.2024.e29523
    The advancement of artificial intelligence (AI) and the ubiquity of social media have become transformative agents in contemporary educational ecosystems. The spotlight of this inquiry focuses on the nexus between AI and social media usage in relation to academic performance and mental well-being, and the role of smart learning in facilitating these relationships. Using partial least squares-structural equation modeling (PLS-SEM) on a sample of 401 Chinese university students. The study results reveal that both AI and social media have a positive impact on academic performance and mental well-being among university students. Furthermore, smart learning serves as a positive mediating variable, amplifying the beneficial effects of AI and social media on both academic performance and mental well-being. These revelations contribute to the discourse on technology-enhanced education, showing that embracing AI and social media can have a positive impact on student performance and well-being.
  13. Fulltext Understanding consumers' continuous-use intention of crowdsourcing logistics services: Empirical evidence from China
    Liu Y, Shang M, Jia C, Lim XJ, Ye Y
    Heliyon, 2024 Apr 30;10(8):e29819.
    PMID: 38681650 DOI: 10.1016/j.heliyon.2024.e29819
    Crowdsourcing logistics-based O2O (online to offline) has been increasingly implemented to help individuals or merchants tackle down the problem of intra city instant delivery in China. However, since insufficient control is imposed on free couriers, consumers are subjected to certain risks generated by the uneven service quality provided by free couriers, such that the continuous-use intention to adopt crowdsourcing logistics may be affected in an unexpected manner. A sampling survey was carried out in China's first- and second-tier cities, with 292 valid questionnaires collected. On that basis, the corresponding hypotheses were tested using the partial least squares (PLS) method. The findings of this study revealed that trust, perceived value, and satisfaction positively contributed to continuous-use intention, where trust contributed the most. Perceived risk exerted a significant negative effect on continuous use intention. Trust is capable of notably reducing perceived risk. Crowdsourcing logistics service quality is the critical driving variable of perceived value and satisfaction. Perceived risk has a negative moderating effect on satisfaction-continuous-use intention relationship, showing that the higher the perceived risk, the weaker the effect of satisfaction on continuous-use intention. Given perceived risk, a conceptual model was built by integrating e-CSI model (e-Customer Satisfaction Index Model) and PAM-ISC model (Post-acceptance Model of IS Continuance Model). From the integration, the findings of this study are expected to provide decision-making basis for crowdsourcing logistics platforms to help solve the "last mile" delivery problem.
  14. Fulltext Viral etiology of severe lower respiratory tract infections in SARS-CoV-2 negative hospitalized patients during the COVID-19 pandemic in Kuwait
    Altawalah H, Alfouzan W, Al-Fadalah T, Zalzala MA, Ezzikouri S
    Heliyon, 2024 Apr 30;10(8):e29855.
    PMID: 38681623 DOI: 10.1016/j.heliyon.2024.e29855
    BACKGROUND: The prevalence of respiratory infections is largely underexplored in Kuwait. The aim of our study is to determine the etiology of infections from patients who are SARS-CoV-2 negative hospitalized with severe lower respiratory tract infections (LRTIs) in Kuwait during the coronavirus disease 2019 (COVID-19) pandemic.

    METHODS: We conducted an observational cross-sectional study among severe LRTI patients between September 2021 and March 2022. Respiratory samples from 545 non-COVID-19 severe LRTIs patients were prospectively evaluated with FTD Respiratory 21 Plus® real-time PCR, targeting 20 different viruses and 1 atypical bacterial pathogen.

    RESULTS: Among all 545 hospitalized cases, 411 (75.4 %) tested positive for at least one respiratory pathogen. The most common were rhinovirus (HRV) (32.7 %), respiratory syncytial virus (RSV) (20.9 %), metapneumovirus (HMPV) (14.1 %), bocavirus (13.2 %), and influenza A (12.7 %). The proportion of pathogens detected was highest in the under-5 age group, while HKU1 (44.4 %) predominated in the elderly (>50 years).

    CONCLUSION: Our study reveals a high prevalence of respiratory viruses in severe acute lower respiratory tract infections among non-COVID-19 hospitalized patients in Kuwait. HRV remains the main etiology affecting the country, particularly in infants. These results underscore the necessity of employing multiplex PCR for accurate diagnosis and describing the epidemiology of infections among severe lower respiratory tract infections. This will facilitate the use of specific antiviral therapy and help avoid excessive or inappropriate antibiotic therapy.

  15. Fulltext Nutrition, phytochemical profiling, in vitro biological activities, and in silico studies of South Chinese white pitaya (Hylocereus undatus)
    Asghar A, Shahid M, Gang P, Khan NA, Fang Q, Xinzheng L
    Heliyon, 2024 Apr 30;10(8):e29491.
    PMID: 38681612 DOI: 10.1016/j.heliyon.2024.e29491
    BACKGROUND: White pitaya, a popular tropical fruit, is known for its high nutritional value. It is commercially cultivated worldwide for its potential use in the food and pharmaceutical industries. This study aims to assess the nutritional and phytochemical contents and biological potential of the South Chinese White Pitaya (SCWP) peel, flesh, and seed extracts.

    METHODS: Extract fractions with increasing polarity (ethyl acetate 

  16. Investigation of flow behaviour in the nozzle of a Pelton wheel: Effects and analysis of influencing parameters
    Geeri S, Kolakoti A, Samuel OD, Abbas M, Aigba PA, Ajimotokan HA, et al.
    Heliyon, 2024 Apr 30;10(8):e28986.
    PMID: 38681544 DOI: 10.1016/j.heliyon.2024.e28986
    The performance of a Pelton wheel is influenced by the jet created by the nozzle. Therefore, a Computational Fluid Dynamics (CFD) simulation was proposed. In this study, the significant output parameters (outlet velocity, outlet pressure, and tangential force component) and input parameters (different pressure and spear locations) were examined. In addition, the influencing parameters and their contributing percentages to the performance of the Pelton wheel were calculated using different optimisation techniques such as Taguchi Design of Experiments (DoE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Grey Relational Analysis (GRA) and Criteria Importance Through Intercriteria Correlation (CRITIC). The effect of input factors on the output response was examined with DoE, and the results show that the inlet pressure had the most significant impact (97.38%, 99.18%, and 97.38%, respectively, for all different spear sites with a 99% confidence level). In terms of preference values, the TOPSIS and GRA results are comparable (best ranks for simulation runs #24 and #25 and least ranks for simulations #2 and #3, respectively). The CRITIC results for the pressure parameter are in good agreement with the Taguchi ANOVA analysis. The last spear location (5 mm after the nozzle outlet), with an inlet pressure of 413685 Pa generated the best result when employing the TOPSIS and GRA techniques. The outlet pressure of the nozzle was found to have a significant impact on the flow pattern of the Pelton Wheel based on the analysis of the CRITIC, Taguchi, and CFD results.
  17. Fulltext Tetraalkylammonium salts (TAS) in solar energy applications - A review on in vitro and in vivo toxicity
    Mustafa NM, Jumaah FN, Ludin NA, Akhtaruzzaman M, Hassan NH, Ahmad A, et al.
    Heliyon, 2024 Apr 15;10(7):e27381.
    PMID: 38560257 DOI: 10.1016/j.heliyon.2024.e27381
    Tetraalkylammonium salt (TAS) is an organic salt widely employed as a precursor, additive or electrolyte in solar cell applications, such as perovskite or dye-sensitized solar cells. Notably, Perovskite solar cells (PSCs) have garnered acclaim for their exceptional efficiency. However, PSCs have been associated with environmental and health concerns due to the presence of lead (Pb) content, the use of hazardous solvents, and the incorporation of TAS in their fabrication processes, which significantly contributes to environmental and human health toxicity. As a response, there is a growing trend towards transitioning to safer and biobased materials in PSC fabrication to address these concerns. However, the potential health hazards associated with TAS necessitate a thorough evaluation, considering the widespread use of this substance. Nevertheless, the overexploitation of TAS could potentially increase the disposal of TAS in the ecosystem, thus, posing a major health risk and severe pollution. Therefore, this review article presents a comprehensive discussion on the in vitro and in vivo toxicity assays of TAS as a potential material in solar energy applications, including cytotoxicity, genotoxicity, in vivo dermal, and systemic toxicity. In addition, this review emphasizes the toxicity of TAS compounds, particularly the linear tetraalkyl chain structures, and summarizes essential findings from past studies as a point of reference for the development of non-toxic and environmentally friendly TAS derivatives in future studies. The effects of the TAS alkyl chain length, polar head and hydrophobicity, cation and anion, and other properties are also included in this review.
  18. Fulltext Comparative analysis of growth and health of juvenile African catfish (Clarias gariepinus) fed with different starch diets
    Seong Wei L, Rahim MSAA, Yeu Hooi K, Khoo MI, Mohamad Nor A, Wee W
    Heliyon, 2024 Apr 15;10(7):e28224.
    PMID: 38560210 DOI: 10.1016/j.heliyon.2024.e28224
    This study evaluated the effects of potato, wheat, rice, and corn starch on growth performance, blood parameters, digestive enzyme activity, antioxidative response, and gut microbiota of African catfish, Clarias gariepinus. A control diet (a commercial fish diet) and four different starch (potato, PO; wheat, WH; corn, CO; rice, RC) formulations were fed to African catfish with average weight of 10.5g (n = 30) for eight weeks. The experiment was conducted in triplicates. At the end of the feeding trial, the growth performance of African catfish fed with potato starch (PO) was significantly higher than other treatment groups. Furthermore, this group recorded significant and lowest feed conversion ratio (FCR) compared to other groups. Meanwhile, there were no significant differences in all tested hematological parameters and antioxidative response between the groups. Digestive enzyme activities in the fish intestines, including amylase, lipase, and protease, were significantly higher in African catfish fed with the PO diet. In addition, this group demonstrated substantially lower viscerosomatic index (VSI) and hepatosomatic index (HSI) than other groups, indicating that the fish has more meat on its body. The PO diet group also recorded significantly higher Akkermansia muciniphila, a good gut microbiota. Therefore, the PO diet potentially improves African catfish's growth performance and health status.
  19. Fulltext Impulse buying behavior during livestreaming: Moderating effects of scarcity persuasion and price perception
    Feng Z, Al Mamun A, Masukujjaman M, Wu M, Yang Q
    Heliyon, 2024 Apr 15;10(7):e28347.
    PMID: 38560201 DOI: 10.1016/j.heliyon.2024.e28347
    This research aimed to identify the factors that influence impulse buying behavior during livestreaming and advance the existing literature based on a proposed conceptual framework grounded in the stimulus-organism-response (S-O-R) model. We also tested the moderating effects of price perception and scarcity persuasion. An online self-administered questionnaire was used to collect data from 837 Chinese participants aged over 18 years. The data were analyzed using partial least squares structural equation modeling using Smart-PLS version 4.0. The findings showed that susceptibility to social influence, impulse buying tendency, cognitive reactions, affective reactions, and the urge to buy impulsively are statistically significant predictors of impulse buying during livestreaming, with price perception and scarcity persuasion as moderators. The study expands the S-O-R model for livestreaming impulse buying in e-commerce context, highlighting its multifaceted nature and revealing the mediating role of Urge to Buy Impulsively in translating cognitive and emotional factors into impulse buying behavior. These insights offer practical guidance for marketers to design tailored strategies that leverage psychological triggers and external cues to enhance consumer engagement and encourage desired behaviors, ultimately leading to more effective marketing campaigns and improved consumer experiences.
  20. Fulltext Real-time driver identification in IoV: A deep learning and cloud integration approach
    Gheni HM, AbdulRahaim LA, Abdellatif A
    Heliyon, 2024 Apr 15;10(7):e28109.
    PMID: 38560228 DOI: 10.1016/j.heliyon.2024.e28109
    The Internet of Vehicles (IoV) emerges as a pivotal extension of the Internet of Things (IoT), specifically geared towards transforming the automotive landscape. In this evolving ecosystem, the demand for a seamless end-to-end system becomes paramount for enhancing operational efficiency and safety. Hence, this study introduces an innovative method for real-time driver identification by integrating cloud computing with deep learning. Utilizing the integrated capabilities of Google Cloud, Thingsboard, and Apache Kafka, the developed solution tailored for IoV technology is adept at managing real-time data collection, processing, prediction, and visualization, with resilience against sensor data anomalies. Also, this research suggests an appropriate method for driver identification by utilizing a combination of Convolutional Neural Networks (CNN) and multi-head self-attention in the proposed approach. The proposed model is validated on two datasets: Security and collected. Moreover, the results show that the proposed model surpassed the previous works by achieving an accuracy and F1 score of 99.95%. Even when challenged with data anomalies, this model maintains a high accuracy of 96.2%. By achieving accurate driver identification results, the proposed end-to-end IoV system can aid in optimizing fleet management, vehicle security, personalized driving experiences, insurance, and risk assessment. This emphasizes its potential for road safety and managing transportation more effectively.
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