Browse publications by year: 2024

  1. Jing H, Chen Y, Liang B, Tian Z, Song F, Chen M, et al.
    Geriatr Nurs, 2024 Nov 08.
    PMID: 39521661 DOI: 10.1016/j.gerinurse.2024.10.030
    BACKGROUND: Frailty is considered highly prevalent among the elderly, and falls are a severe adverse event that occurs at a significantly higher rate in frail elderly patients, leading to serious consequences. The pre-frailty stage represents a reversible transitional state between health and frailty, and targeted interventions for pre-frail older adults can effectively reduce the incidence of falls in this population. Existing studies have not definitely identified the risk factors for falls in pre-frail older adults. This paper explores the relevant risk factors for falls in pre-frail older adults.

    METHODS: PubMed, Embase, Web of Science, Cochrane Library, CBM, CNKI, Wan fang, and VIP databases were searched for studies published from inception to 2023, without language restrictions. Observational studies were included in this systematic review that analyzed risk factors for accidental falls in pre-frail older adults. The NOS scale was used to evaluate the quality of cohort studies and case-control studies, while the AHRQ scale was used to evaluate the quality of the cross-sectional study. We utilized odds ratios (OR) and their corresponding 95 % confidence intervals (CI) to describe the statistical indicators. OR and 95 % CI values were directly extracted and organized in Excel. In cases where OR and CI values were not directly available, we extracted β and p values, calculated Exp using functions, and subsequently derived OR and 95 % CI using formulas. Finally, data pertaining to each risk factor were incorporated into RevMan 5.4 software for statistical analysis and effect size synthesis. We performed tests for heterogeneity and evaluated publication bias.

    RESULTS: A total of 14,370 studies were initially identified, and 26 studies were included in the systematic review. Among these studies, 14 were of high quality, while the remaining 12 were of moderate quality. A total of 16 risk factors were identified as potential risk factors for falls in pre-frail older adults. Significant risk factors were peripheral neuropathy(OR = 3.18, 95 %CI:3.02-3.35), decreased gait speed(OR = 1.90, 95 %CI:1.60-2.27), decreased ability to perform activities of daily living(OR = 1.57, 95 % CI:1.42-1.75), grip strength decreases(OR = 1.53, 95 % CI:1.17-2.00), gender (female)(OR = 1.51, 95 % CI:1.39-1.64), pain(OR = 1.47, 95 %CI:1.41-1.54), history of falls(OR = 1.20, 95 %CI:1.13-1.28) and age(OR = 1.10, 95 %CI:1.07-1.14).

    CONCLUSIONS: The occurrence of falls in pre-frail older adults is associated with multiple risk factors. These risk factors can provide clinical nursing staff with specific focal points for monitoring this population and devising targeted fall prevention measures, with the aim of reducing the incidence of falls in pre-frail older adults.

    REGISTRATION: The systematic review was registered on the International Prospective Register of Systematic Review (CRD42023450670).

  2. Alrasheedi AF, Rani P, Mishra AR, Alshamrani AM, Cavallaro F
    Sci Rep, 2024 Nov 09;14(1):27373.
    PMID: 39521811 DOI: 10.1038/s41598-024-78284-8
    The present work proposes a new decision support tool for assessing the sustainable suppliers in the healthcare supply chain. For this purpose, the classical Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) model is integrated with the Sugeno-Weber weighted averaging operators, modified symmetry point of criterion (SPC) model, rank sum (RS) tool and Fermatean fuzzy sets (FFSs), and named as the 'FF-SPC-RS-MARCOS' framework. The developed model firstly determines the decision experts' weights through RS model. Second, novel Sugeno-Weber weighted operators are introduced to combine the experts' opinions. Third, a unified weighting procedure is presented based on the combination of modified SPC approach for objective weight and RS method for subjective weight of attributes. To this aim, a novel distance measure is introduced for FFSs and further applied to compute the distance between aggregated Fermatean fuzzy numbers and symmetry point value of an attribute in the modified SPC approach. Further, a hybrid FF-SPC-RS-MARCOS approach is proposed to tackle the decision-making problems on FFSs setting. To elucidate the efficacy of the developed method, it is applied to a case study of sustainable supplier selection problem in the healthcare supply chain. The paper further conducts sensitivity investigation and comparison with existent approaches to test the stability and robustness of the ranking outcomes. This study shows how the proposed MARCOS method in combination with SPC and RS models can be used to prioritize the alternative suppliers in the healthcare supply chain. The introduced work provides a new methodology, which can help the practitioners and academics to evaluate suppliers with uncertain information and can also be employed to other areas facing similar types of decision-making problems.
  3. Bian X, Mohd Sukor MS
    Sci Rep, 2024 Nov 09;14(1):27421.
    PMID: 39521919 DOI: 10.1038/s41598-024-79322-1
    The study aims to explore whether work-life balance mediates the impact of work-family conflict and its dimensions on psychological well-being. Using a survey method, data were collected from a sample of 258 working women in Hebei province in China. The analysis was carried out using IBM SPSS and the PROCESS macro in order to test the mediation model. The findings show that work-family conflict has an indirect effect on psychological well-being through work-life balance. In the case of work-to-family conflict, a suppression effect is detected in which the mediator shows an underlying relationship between the work-to-family conflict and psychological well-being. On the other hand, family-to-work conflict is fully moderated by work-life balance. Based on these results, it can be concluded that enhancing the quality of work-life balance may help to reduce the negative impact of work-family conflict on psychological health. The findings of this study can be beneficial to organizations and policy makers to formulate policies that would enhance the mental health and work productivity of women professionals in China.
    MeSH terms: Adult; China/epidemiology; Conflict (Psychology); Family/psychology; Female; Humans; Mental Health*; Middle Aged; Surveys and Questionnaires; Young Adult; Work-Life Balance*
  4. Ehigiamusoe KU, Dogan E, Ramakrishnan S, Binsaeed RH
    J Environ Manage, 2024 Dec;371:123229.
    PMID: 39522189 DOI: 10.1016/j.jenvman.2024.123229
    The objective of this study is to unravel the linear impacts of economic growth, technological innovation, natural resource rents and trade openness on carbon emissions in Malaysia during 1980-2021. It also unveils the moderating role of technological innovation on the impacts of economic growth, natural resource rents and trade openness on carbon emissions. It further analyses the nonlinear relationship between technological innovation and carbon emissions. It estimates the parameters with the Autoregressive Distributed Lag model technique. The results of the linear model reveal that economic growth, natural resource rents and trade openness contributes to carbon emissions while technological innovation mitigates carbon emissions. The disaggregated analysis of natural resource rents indicates that oil rents, natural gas rents and coal rents intensify carbon emissions while mineral rents and forest rents do not contribute to carbon emissions. The disaggregated analysis of trade openness shows that exports worsen carbon emissions while imports have tenuous effect. The disaggregated analysis of technological innovation indicates that innovation by non-residents mitigate carbon emissions while innovation by residents do not alleviate carbon emissions. Moreover, evidence from the interaction model reveals that technological innovation can favourably mitigate the adverse impacts of economic growth and trade openness on carbon emissions albeit it cannot alleviate the impact of natural resource rents on carbon emissions. Besides, the nonlinear model indicates a U-shaped relationship between technological innovation and carbon emissions. Unlike previous studies that typically focused on the direct impacts of these variables, this study unravels the impacts of the disaggregated components as well as provides insights into the moderating and nonlinear effects of technological innovation on carbon emissions. The implication of this study is that efforts to achieve a carbon-neutral economy should consider the direct and indirect impacts of economic growth, technological innovation, natural resource rents and trade openness. It is recommended for Malaysia to encourage technological innovation in her quest to abate the adverse environmental impacts of economic activities.
    MeSH terms: Natural Resources*; Carbon; Commerce; Conservation of Natural Resources; Environment; Malaysia; Economic Development*; Inventions
  5. Abas Mohamed Y, Ee Khoo B, Shahrimie Mohd Asaari M, Ezane Aziz M, Rahiman Ghazali F
    Int J Med Inform, 2024 Nov 04;193:105689.
    PMID: 39522406 DOI: 10.1016/j.ijmedinf.2024.105689
    OBJECTIVE: Explainable Artificial Intelligence (XAI) is increasingly recognized as a crucial tool in cancer care, with significant potential to enhance diagnosis, prognosis, and treatment planning. However, the holistic integration of XAI across all stages of cancer care remains underexplored. This review addresses this gap by systematically evaluating the role of XAI in these critical areas, identifying key challenges and emerging trends.

    MATERIALS AND METHODS: Following the PRISMA guidelines, a comprehensive literature search was conducted across Scopus and Web of Science, focusing on publications from January 2020 to May 2024. After rigorous screening and quality assessment, 69 studies were selected for in-depth analysis.

    RESULTS: The review identified critical gaps in the application of XAI within cancer care, notably the exclusion of clinicians in 83% of studies, which raises concerns about real-world applicability and may lead to explanations that are technically sound but clinically irrelevant. Additionally, 87% of studies lacked rigorous evaluation of XAI explanations, compromising their reliability in clinical practice. The dominance of post-hoc visual methods like SHAP, LIME and Grad-CAM reflects a trend toward explanations that may be inherently flawed due to specific input perturbations and simplifying assumptions. The lack of formal evaluation metrics and standardization constrains broader XAI adoption in clinical settings, creating a disconnect between AI development and clinical integration. Moreover, translating XAI insights into actionable clinical decisions remains challenging due to the absence of clear guidelines for integrating these tools into clinical workflows.

    CONCLUSION: This review highlights the need for greater clinician involvement, standardized XAI evaluation metrics, clinician-centric interfaces, context-aware XAI systems, and frameworks for integrating XAI into clinical workflows for informed clinical decision-making and improved outcomes in cancer care.

  6. Mongkhonmath N, Olson PS, Puttarak P, Chaiyakunapruk N, Sawangjit R
    PMID: 39522823 DOI: 10.1016/j.japh.2024.102293
    BACKGROUND: Pharmacovigilance is essential for patient safety, but underreporting adverse drug reactions (ADRs) is a global challenge.

    OBJECTIVES: This review evaluated the effectiveness of strategies for enhancing ADR reporting by healthcare professionals (HCPs).

    METHODS: This systematic review was conducted following the Cochrane and the PRISMA guidelines. Five international databases were searched from inception to December 2023 and updated search to September 2024. Randomized clinical controlled trials (RCTs) and non-RCTs on enhancing ADR reporting were included. The primary outcomes were the number of overall ADR and high-quality ADR reports. Study quality was assessed using the EPOC risk of bias (ROB), and ROBIN-I for RCT, and non-RCT. All data were evaluated using a random-effects model, and heterogeneity was assessed using I2 statistic and chi-squared tests.

    RESULTS: From 1,672 studies, 13 studies (10 RCTs, and 3 non-RCTs) with 28,116 participants were included. Two of 10 RCTs had low ROB while the remaining were judged as unclear and moderate ROB. Most studies were in high-income countries, and the main strategy was educating HCPs through workshops. Meta-analysis showed significant increases in overall ADR reporting through educating HCPs with a rate ratio (RR) of 5.09 (95%CI: 3.36-7.71, I2=84.5%, low certainty), and in high-quality reporting with 1.31 (95%CI:1.09-1.58, I2=0.0%, moderate certainty). Subgroup analysis indicated that educating HCPs through face-to-face workshops combined with the Tawai app (RR:10.5, 95%CI:8.74-12.61), a face-to-face workshop alone (RR:6.69, 95%CI:5.43-8.25, I2=0.0%), and repeated telephone (RR:2.59, 95%CI:1.75-3.84, I2=8.8%) significantly increased the overall number of ADR reports with moderate certainty. Email or letter communications showed no significant effect.

    CONCLUSION: Educating HCPs via interactive strategies like face-to-face workshops with or without a mobile app and repeated phone calls improved ADR reporting. However, long-term, high-quality studies are needed to confirm these findings before recommending widespread implementation in clinical practice, especially in LMICs.

  7. Maslub MG, Daud NAA, Radwan MA, Sha'aban A, Ibrahim AG
    Eur J Med Res, 2024 Nov 10;29(1):539.
    PMID: 39523378 DOI: 10.1186/s40001-024-02109-7
    BACKGROUND: A single nucleotide polymorphism (SNP) is a variation in the DNA sequence that results from the alteration of a single nucleotide in the genome. Atorvastatin is used to treat hypercholesterolemia. It belongs to a class of drugs called statins, which lower elevated levels of total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C). Research findings on the associations between the response to atorvastatin and genetic polymorphisms in CYP3A4 and CYP3A5 are inconclusive. The effects of CYP3A4*1B (rs2740574 C/T) and CYP3A5*3 (rs776746 T/C) on atorvastatin therapy have not been previously studied among Egyptians.

    OBJECTIVE: This research aimed to investigate the effects of the genetic polymorphisms CYP3A4*1B and CYP3A5*3 on atorvastatin treatment in Egyptians.

    METHODS: In this prospective cohort study, 100 subjects were genotyped for these SNPs. All participants were screened for serum lipid profiles, liver enzymes, total bilirubin (TB), and creatine kinase (CK) before and after 40 mg postatorvastatin therapy. Atorvastatin plasma levels were assessed posttreatment; atorvastatin pharmacokinetics were evaluated in five carriers of the CYP3A4*1B (T/T) and CYP3A5*3 (C/C) genotypes.

    RESULTS: The allele frequencies of the CYP3A4*1B and CYP3A5*3 SNPs were 86% and 83%, respectively. The CYP3A4*1B (T/T) and CYP3A5*3 (C/C) genotypes significantly improved the serum triglyceride (TG) level (P 

    MeSH terms: Adult; Egypt; Female; Genotype; Humans; Hypercholesterolemia/blood; Hypercholesterolemia/drug therapy; Hypercholesterolemia/genetics; Male; Middle Aged; Prospective Studies; Polymorphism, Single Nucleotide*
  8. Wan Mohd Zin RM, Jalaludin MY, Md Zain F, Hong JYH, Ahmad Kamil NZI, Mokhtar AH, et al.
    Diabetol Metab Syndr, 2024 Nov 11;16(1):268.
    PMID: 39523406 DOI: 10.1186/s13098-024-01493-8
    BACKGROUND: In recent years, there has been a surge of interest in the metabolic phenotype among children with obesity characterized by the absence of associated cardiometabolic risk factors (CRFs), known as metabolically healthy obesity (MHO), as opposed to those with metabolically unhealthy obesity (MUO). This study investigated the effect of lifestyle intervention on CRFs among children with MHO and MUO.

    METHODS: A total of 102 school-aged children with obesity (54 girls and 48 boys) aged 8-16 years completed a 16-week school-based lifestyle modification intervention program, MyBFF@school Phase I. The intervention consisted of physical activity, healthy eating promotion, and psychological empowerment. MHO and MUO statuses were defined based on the 2018 consensus-based criteria. Fasting venous blood collection, body composition measurement, clinical assessment and physical fitness testing were conducted at baseline and at the end of week 16.

    RESULTS: After the intervention, the CRFs of the children with MUO improved with significant decreases in systolic (p 

  9. Anggraeni AR, Lim LW, Takeuchi T
    J Sep Sci, 2024 Nov;47(21):e70017.
    PMID: 39523539 DOI: 10.1002/jssc.70017
    A chiral monolith stationary phase was fabricated by modifying the monolith surface using L-cysteine through a thiol-epoxy click reaction. L-cysteine-bonded polymer monolith was characterized by scanning electron microscopy/energy-dispersive X-ray and attenuated total reflectance Fourier-transformed infrared. The monomer content and modification temperature were carefully optimized to create a polymer monolith with excellent mechanical stability and permeability. Our findings revealed that the column morphology depended significantly on the porogen concentration and modification temperature for its morphology and efficiency. Adequate pores and binding sites were formed with the optimal porogen content, while a higher modification temperature improved the modification yield, enhancing peak shapes and increasing separation efficiency. The column demonstrated its capability for enantioseparation of dansyl glutamic acid, dansyl aspartic acid, dansyl methionine, and dansyl phenylalanine using a 60 mM ammonium acetate buffer solution and acetonitrile in a 20:80 v/v ratio. It maintained good mechanical stability and repeatability with no relative standard deviation exceeding 7%. These results indicated that the L-cysteine-bonded polymer monolith has excellent potential as a chiral stationary phase.
  10. Omran S, Leong SL, Blebil A, Mohan D, Ang WC, Teoh SL
    Clin Transl Sci, 2024 Nov;17(11):e70057.
    PMID: 39523855 DOI: 10.1111/cts.70057
    Lack of pharmacogenomics knowledge among healthcare professionals is the most significant cited barrier to implementing pharmacogenomics in clinical settings. Despite the growth in research initiatives and awareness of pharmacogenomics, healthcare professionals continue to report a lack of knowledge and confidence in practicing pharmacogenomics. This study aims to assess the current pharmacogenomics knowledge gaps and learning needs of healthcare professionals in Malaysia. A modified Delphi with a multidisciplinary expert panel was conducted, and a purposive sampling method was used with predefined selection criteria. Fourteen study sites in Malaysia were included. The cut-off value to approach consensus was predefined as a threshold of 60% or higher, and a quantitative descriptive statistical analysis was performed. The study demonstrated that all experts rated the suggested educational content components as essential/important to be included in the educational intervention. Additionally, experts highlighted the significant barriers and gaps to adopting and practicing pharmacogenomics. To conclude, this multisite Delphi study enabled the development of a tailored, effective, evidence-based, competency-based educational intervention in pharmacogenomics for healthcare professionals in Malaysia. To keep up with the rapid evolution of the pharmacogenomics field, healthcare professionals should be equipped with the necessary competencies required to practice pharmacogenomics for better health outcomes. Future research is needed to determine the feasibility of the proposed educational intervention.
    MeSH terms: Adult; Delphi Technique*; Female; Humans; Health Knowledge, Attitudes, Practice*; Malaysia; Male; Middle Aged; Needs Assessment
  11. Yong JL, Roberts G
    Clin Teach, 2024 Nov 11.
    PMID: 39523937 DOI: 10.1111/tct.13833
    INTRODUCTION: Clinical skills are fundamental to medical school curriculums and typically introduced within the preclinical years. In their experiential learning, students' self-efficacy, or the belief in their ability to succeed, is an important factor in influencing clinical skill mastery. Reflection is thought to affect self-efficacy; however, its exact impacts remain largely unexplored within published literature. This mixed methods study investigated whether preclinical students' engagement with reflection affected self-efficacy for clinical skills.

    METHODS: Two hundred seventy-three of the 289 preclinical medical students who were invited to participate responded to this 2022 study. We used validated questionnaires to measure engagement with reflection and perceived self-efficacy for clinical skills, conducting hierarchical multiple linear regression for analysis. Thirteen students participated in semi-structured interviews and focus groups, which were analysed via thematic analysis.

    RESULTS: While statistical analysis showed no significant effects of engaging with reflection on clinical skill self-efficacy, thematic analysis suggested that students perceived the opposite. The themes through which reflection affected self-efficacy were by 'evaluation of performances' against expected outcomes, 'familiarisation and understanding of skills', by 'transforming personal mindsets' and allowing students to 'connect to their emotions'.

    CONCLUSION: This study suggests that engaging with reflection can positively or negatively affect self-efficacy for clinical skills, depending on students' attitudes towards reflective practice. Solely engaging with reflection is insufficient to alter self-efficacy beliefs and should be considered alongside personal factors including the individual's mindset and perceived need for reflection. The medical educator's role in facilitating reflection is important, enabling students to reap the benefits of this practice.

  12. Liang Z, Fang X, Liang Z, Xiong J, Deng F, Nyamasvisva TE
    iScience, 2024 Nov 15;27(11):111037.
    PMID: 39524329 DOI: 10.1016/j.isci.2024.111037
    Urban flooding significantly impacts city planning and resident safety. Traditional flood risk models, divided into physical and data-driven types, face challenges like data requirements and limited scalability. To overcome these, this study developed a model combining graph convolutional network (GCN) and spiking neural network (SNN), enabling the extraction of both spatial and temporal features from diverse data sources. We built a comprehensive flood risk dataset by integrating social media reports with weather and geographical data from six Chinese cities. The proposed Graph SNN model demonstrated superior performance compared to GCN and LSTM models, achieving high accuracy (85.3%), precision (0.811), recall (0.832), and F1 score (0.821). It also exhibited higher energy efficiency, making it scalable for real-time flood prediction in various urban environments. This research advances flood risk assessment by efficiently processing heterogeneous data while reducing energy consumption, offering a sustainable solution for urban flood management.
  13. Abdalla S, Aroua MK, Gew LT
    ACS Omega, 2024 Nov 05;9(44):44019-44032.
    PMID: 39524627 DOI: 10.1021/acsomega.4c04277
    Plant-based oils, such as coconut, olive, argan, and jojoba, are abundant in natural emollients and vital fatty acids that hydrate and moisturize the skin. They shield the surface, stop moisture loss, and maintain suppleness of, the skin. They are rich in vitamins, nutrients, and antioxidants that nourish the skin. Virgin coconut oil (VCO) is used as a functional food due to its tremendous health benefits, and olive oil is well-known for its cosmetic and culinary applications. Argan oil contains many antioxidants, vital fatty acids, and vitamin E, while jojoba oil is an excellent moisturizer and conditioner. Plant-based oils can be extracted using various techniques including conventional and chemical extraction methods, and each will affect the yield and quality. Traditional methods like mechanical pressing are less efficient, whereas extraction methods such as pressurized liquid and supercritical fluid extraction may give higher yields and better quality. The chemical composition of olive oil primarily consists of saturated fatty acids (SFAs), polyunsaturated fatty acids (PUFAs), and monounsaturated fatty acids (MUFAs). Argan oil is rich in tocopherols, containing between 60 and 90 mg per 100 g, with only 19 g/100 g of argan oil's fatty acids saturated. Jojoba oil is liquid wax comprising over 98% triglyceride esters, pure waxes, vitamins, and sterols. This review focuses on the chemical and biological properties, production processes, and applications of natural cosmetic oils (virgin coconut oil, olive oil, argan oil, and jojoba oil), emphasizing their usage in skin care and cosmeceutical products.
  14. Rusly SNA, Jamal SH, Samsuri A, Mohd Noor SA, Abdul Rahim KS
    Heliyon, 2024 Nov 15;10(21):e39631.
    PMID: 39524708 DOI: 10.1016/j.heliyon.2024.e39631
    The field of propellants has recently witnessed dynamic shift, including advancements in propulsion technology and a growing emphasis on the development of environmentally friendly propellants. Nitrate ester (NE) are extensively used in solid propellants, exhibiting chemical instability as they undergo decomposition reactions. Stabilization is a crucial aspect in propellant, ensuring the safety and reliable performance of energetic materials. Stabilizer plays a vital role in inhibiting or slowing down the autocatalytic decomposition reaction of propellants. In response to grow health and environmental concerns, there is a continuous effort to explore and evaluate green stabilizers designed to replace traditional stabilizers, which have been associated with adverse environmental impacts. Therefore, this study aimed to provide an overview of the current research carried out in the field of NE-based propellants, emphasizing the most significant work undertaken on green stabilizer materials for NE-based propellants. A comprehensive review of various environmentally friendly and low-toxicity stabilizers employed in propellants are presented, and their effects on the stability and shelf-life performance of NE-based propellants are discussed. Furthermore, this paper delves into the stabilization mechanisms of green stabilizers to mitigate decomposition reactions, thereby preventing unwanted side effects and ensuring long-term storage stability. Through a comprehensive review of recent developments, the manuscript highlights the successes and challenges associated with the incorporation of green stabilizers in NE-based propellants formulations. Finally, the review concludes by outlining future research directions and opportunities for innovation in sustainable and green stabilizers as well as key issues that need to be addressed and resolved. The comprehensive review and insights provided in this study contribute to the ongoing efforts in developing safer and more sustainable propellant technologies.
  15. Maity R, Sudhakar K, Razak AA
    Heliyon, 2024 Nov 15;10(21):e39604.
    PMID: 39524726 DOI: 10.1016/j.heliyon.2024.e39604
    Agrivoltaics is an innovative approach where solar energy, water, land and biodiversity are integrated into the same area to maximize resource utilization for sustainable development, also known as Agrivoltaism. The combination of solar water pumping and agri-solar has led to the development of a new generation of irrigation systems that are highly sustainable and efficient. Agri-solar water pumping can irrigate crops, feed livestock, clean solar modules, cool the PV system, generate energy, store water, and provide community drinking water. This paper addresses the basic design and capacity requirements of solar water pumping systems for irrigating a 0.5-ha Agrivoltaics system in Kuala Lumpur. The SISIFO tool has been used to simulate the Agri-solar water pumping performance for tropical humid climatic conditions. The various parameters like site details, climate data, type of PV modules, DC pump -motor and converters are used as input data to evaluate the energy yield parameters (output energy in DC and AC form), hydraulic parameters (volume of water pumped), loss parameters (capture and system losses) and efficiency parameters (performance of the system). Lettuce was chosen as it is fast growing with good yield per hectare. Based on the result, a detailed analysis of the agrivoltaic lettuce plant is performed. A detailed analysis of the solar resource assessment, system design, Key performance indicators, loss analysis and environmental analysis of the Agri-solar water pumping has been carried out. Considering their specific climatic conditions, this can significantly assist policymakers in selecting the optimal solar pumping station for agrivoltaic plants. The importance of considering various factors when choosing a solar pumping station for agrivoltaics is also highlighted.
  16. Wang L, Pertheban TRAL, Li T, Zhao L
    Heliyon, 2024 Nov 15;10(21):e38768.
    PMID: 39524730 DOI: 10.1016/j.heliyon.2024.e38768
    With the vigorous development of e-commerce, more and more goods are sold online. The electronic platform not only brings convenience to people's lives but also gives more people the opportunity of employment and entrepreneurship, which contributes to the promotion of economic value and the creation of wealth. With the gradual maturity of network technology represented by Big Data, it has also led to the further development of e-commerce. In the past, e-commerce mostly used business intelligence systems for data analysis. However, as the data becomes more and more complex, the innovation ability and data analysis ability of traditional business intelligence systems are relatively conservative, so it is of great significance to update and strengthen business intelligence to analyze its role in e-commerce data. Therefore, this paper proposed the application of business intelligence based on Big Data in e-commerce data analysis. By combining Big Data and a business intelligence system and taking the e-commerce data of a certain brand of beverage as the research object, the Days-Times-Money (DTM) model was established, and the data mining technology was used to classify the brand consumers. The data results showed that among the three consumption attributes, the highest consumption density of consumption days, consumption times, and consumption amount was 68.63 %, 67.99 %, and 69.72 % respectively. These were not more than 70 %, which indicated that the consumption of this brand of beverages had a high space for growth. According to the consumption density, the users of this brand of beverage were divided into four consumer groups. According to the classification results, it provided feasible marketing reference opinions for the brand beverage and could provide direction for brand value-added by mining the hidden data of the brand beverage. This paper hoped to use the brand beverage as a case to provide reference and reality for the development of e-commerce enterprises and provide a reference for the application and promotion of business intelligence based on Big Data in e-commerce data analysis.
  17. Yang Y, Adnan HM, Alivi MA
    Heliyon, 2024 Nov 15;10(21):e39092.
    PMID: 39524767 DOI: 10.1016/j.heliyon.2024.e39092
    TikTok has become increasingly popular among young people in China and there is growing number of young people who start to pay great attention to their health through this platform. Wuhan is a significant location for this study, since it was the initial epicenter of COVID-19. However, little is known about the extent to which university students in Wuhan, China, rely on TikTok for health-related information and how this affects their preventive health actions in the post-COVID-19 era. Therefore, it is crucial to look into the direct effects of TikTok users' search for health information and their actions to protect their health, as well as the mediating functions of e-health literacy and COVID-19 risk perception. The impact of TikTok as a social media platform on the health-related behaviors of university students was examined using the Media Dependency Theory which explains how media use can have significant effects on individuals' attitudes, beliefs, and behaviors. 426 questionnaires were gathered by cluster sampling from a sample of Wuhan university students. Mplus8 was used to perform structural equation modelling, which looked at the relationships between these variables. The results showed a positive correlation between users' TikTok health information seeking and their health preventive behavior (β = 0.303, p 
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