Search Results (6,182)

Phoebe bournei is an important economic tree species in China, its large-scale propagation is limited by the difficulty of adventitious root (AR) formation in cuttings. In this study, morphological, physiological, and transcriptomic analyses were conducted to investigate the process of AR formation in P. bournei. The results showed that ARs mainly originated from callus tissue. During AR formation, soluble sugar and soluble protein contents changed significantly. Malondialdehyde (MDA) and oxygen free radicals (OFRs) peaked at first sampling stage (PB0), while the activities of polyphenol oxidase (PPO) and indoleacetic acid oxidase (IAAO) exhibited similar patterns. Lignin content increased during callus induction stage, whereas phenolic content continuously declined throughout rooting. Endogenous hormone levels also changed markedly, and Orthogonal partial least squares discriminant analysis (OPLS-DA) analysis indicated that indole-3-acetic acid (IAA) and abscisic acid (ABA) played dominant roles in this process. KEGG enrichment analysis revealed significant enrichment of the phenylpropanoid biosynthesis pathway in all three comparison groups. A total of 48 differentially expressed genes (DEGs) were enriched in plant hormone signal transduction pathways, with 22 and 14 genes associated with IAA and ABA signaling, respectively. Weighted gene co-expression network analysis (WGCNA) further identified two hub modules related to IAA and ABA contents, including eight hub genes such as D6PKL1 and ISTL1. Correlation analysis revealed that the hub genes D6PKL1 and HSP were significantly positively correlated with IAA4 in the IAA signaling pathway. Overall, this study provides new insights into the mechanisms underlying AR formation in P. bournei cuttings and offers a theoretical basis for optimizing its clonal propagation system. Full article

The construction sector is a major contributor to climate change, with embodied carbon emissions from building materials representing a critical share of its environmental footprint. Selecting zero-carbon materials is therefore essential for reducing life-cycle emissions while advancing global climate goals. This study investigates six decision-making factors, including cost-effectiveness, durability, buildability, embodied carbon, availability, and aesthetics, and evaluates four alternative materials (wood, hemp, rammed earth, and straw bale) in the New Zealand context. A survey of 203 industry professionals was analysed using descriptive statistics, one-sample t-tests, and structural equation modelling (SEM). Using a 5-point Likert scale, the survey assessed six factors affecting material choice: cost-effectiveness, durability, buildability, embodied carbon, aesthetics, and material availability. Descriptive and inferential analyses were performed using SEM via Partial Least Squares analysis. The results revealed that embodied carbon and material availability were the most influential factors shaping zero-carbon material selection. Among the available alternatives, hemp emerged as the most preferred material, while cost-effectiveness and wood showed moderate impacts, and aesthetic considerations had the least influence. These findings highlight that environmental performance and practical accessibility are central drivers of decision-making when adopting zero-carbon materials. This study contributes to developing effective strategies for promoting the widespread adoption of zero-carbon materials, thereby supporting New Zealand’s progress toward achieving the Sustainable Development Goals and the 2030 Agenda for reducing greenhouse gas emissions. Full article

Human–Robot Collaboration (HRC) in construction projects promises enhanced productivity, safety, and quality, yet realizing these benefits requires understanding the multifaceted human and robotic factors that influence team performance. This study develops and validates a multidimensional framework that links key human abilities (operational skill, decision-making ability, and learning ability) and robot capacities (functionality and operability) to HRC team performance, with task complexity considered as contextual influence. A field survey of construction practitioners (n = 548) was analyzed using partial least squares structural equation modeling (PLS-SEM) to test direct effects and human–robot synergies. Results reveal that all five main effects are positive and significant, indicating that both human abilities and robot capacities have significant contribution. Moreover, every hypothesized two-way interaction is supported, evidencing strong interaction effects. Three-way moderation analyses further reveal that task complexity significantly strengthened the interactions of human abilities with robot functionality, whereas its interactions with robot operability were not significant. The study contributes an integrated and theory-driven model of HRC team performance that accounts for human abilities and robot capacities under varying task complexity, and validated constructs that can be used to diagnose and predict performance. The findings offer actionable guidance for project managers by recommending that they prioritize user-friendly robot operability to translate worker expertise into performance across a wide range of tasks, invest in training to strengthen operators’ skills and decision-making, and, for complex tasks, pair highly skilled workers with high-functionality robots to maximize performance gains. Full article

HSV-2 is the main pathogen causing genital herpes, and its infection increases the infection and transmission of HIV-1. Currently, there are no vaccines to prevent HSV-2 infection or treatment that can fully cure it. Mining key host factors that regulate HSV-2 replication and elucidating their specific regulatory mechanisms are crucial for understanding virus–host interactions and discovering new antiviral targets. In the current study, we identified DDX43 as a cellular factor involved in the suppression of HSV-2 replication through comparative transcriptomic analyses of HSV-2-infected epithelial cells, followed by experimental validation. Comprehensive transcriptomic profiling revealed distinct host cellular gene expression patterns in HeLa and ARPE-19 cell lines post HSV-2 infection. Subsequent orthogonal partial least-squares discriminant analysis (OPLS-DA) pinpointed DDX43 as one of the principal mediators distinguishing the host response between HSV-2-infected HeLa and ARPE-19 cells. Furthermore, overexpression of DDX43 inhibited HSV-2 replication, whereas knockdown of endogenous DDX43 enhanced HSV-2 replication. Additional experiments revealed that human DDX43 inhibits HSV-2 replication in an interferon-independent manner. This study demonstrates that DDX43 serves as a host regulator against HSV-2 infection, underscoring the power of comparative transcriptomics in identifying novel host proteins that modulate viral replications. Full article

Farmers’ perceptions of environmental change are a key trigger for livelihood behaviors. However, it remains unclear how these perceptions become specific livelihood strategies through internal psychological processes. To address this, this study constructs an analytical framework. It integrates multidimensional environmental perceptions, risk aversion, and livelihood strategies. Particular focus is given to the mediating role of risk aversion in the link between perception of environmental change and livelihood strategy. The proposed mechanism is tested using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings indicate that farmers pursue both adaptive and defensive livelihood strategies. They balance security with development opportunities. Perceptions of ecological transition and market volatility significantly affect both adaptive and defensive strategies. Perception of social dynamics mainly influences adaptive strategies. The perception of policy adjustment has no significant effect. Risk aversion mediates these relationships. It strengthens defensive behaviors while promoting adaptive actions, showing its dual function in risk management and proactive adaptation. These findings underscore the complexity of decision-making in rural areas. They elucidate how environmental perceptions shape risk awareness and responses to livelihoods. This offers insights for policies aimed at enhancing rural resilience. Full article

The current study aims to address the research gap regarding inconsistent findings on the effect of environmental knowledge (EK) in enhancing green purchase intention (GPI) by incorporating pro-environmental behavior (PEB) and environmental concern (EC) as factors to leverage green purchase intention. Five hypotheses were developed and tested using a sample of 300 respondents in Indonesia. Survey data from 300 respondents were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings demonstrate the pivotal role of pro-environmental behavior in two ways. First, pro-environmental behavior mediates the relationship between environmental knowledge and green purchase intention. Second, while pro-environmental behavior enhances environmental concern, it is insufficient to fully strengthen green purchase intention; additional factors, such as the activation of ethical values of concern, are needed to reinforce this intention further. However, the limitations include reliance on quantitative cross-sectional data and focus on Bali, suggesting a need for longitudinal and cross-cultural studies. Practical recommendations include incorporating local communities in eco-tourism programs to ensure social acceptance and sustainability. In general, the results contribute theoretically by integrating knowledge, concern, and behavior into a cohesive model explaining green consumer intentions in tourism. This comprehensive approach supports efforts to transform individual values and behavior, which are critical alongside systemic or policy changes in advancing sustainable tourism. Full article

Background/Objectives: Healthcare organizations worldwide face challenges in retaining talented employees, with the phenomenon of quiet quitting increasingly recognized as a contemporary issue. Rather than leaving their jobs, employees remain at work but exert minimal effort and exhibit reduced engagement, which can ultimately undermine the performance of healthcare organizations. The aim of this research was to examine the impact of servant leadership on work engagement within healthcare organizations, to determine whether this leadership style can help mitigate the effects of quiet quitting. Methods: The study employed a quantitative approach, utilizing validated instruments to measure servant leadership and work engagement. A cross-sectional study design was utilized, employing a convenience sampling method. A total of 362 valid surveys were collected from healthcare professionals in Serbia participating in the study from January to March 2025. The partial least squares structural equation modeling (PLS-SEM) method was used to examine the relationship between servant leadership and work engagement among healthcare professionals. Results: The results indicate that servant leadership has a positive and statistically significant impact on all dimensions of engagement: vigor, dedication, and absorption. Conclusions: Based on these findings, it is concluded that servant leadership can serve as an effective strategy for enhancing work engagement and reducing negative employee behaviors, such as quiet quitting, which may, in turn, improve organizational efficiency in the healthcare industry. Full article

AI-based assistive technologies (AIATs) are increasingly recognised as essential tools to enhance accessibility, independence, and inclusion for visually impaired students in higher education. However, limited evidence exists regarding the determinants of their acceptance and use, particularly in terms of psychosocial factors. This study aimed to extend the Unified Theory of Acceptance and Use of Technology (UTAUT) by incorporating physical self-esteem (PSE) as a moderator and behavioural intention (BI) as a mediator within a single model. Data were collected through a validated questionnaire administered to 395 visually impaired undergraduates across five Saudi universities. Constructs included effort expectancy (EE), performance expectancy (PE), facilitating conditions (FCs), social influence (SI), BI, and PSE. Partial Least Squares Structural Equation Modelling (PLS-SEM) was used for analysis. Results showed that PE and SI significantly predicted both BI and adoption, while EE strongly predicted BI but not AIAT adoption; FC had no significant influence on either outcome. BI positively affected AIAT adoption and mediated the effects of PE, EE, and SI, but not FC. Moderation analysis indicated that PSE strengthened the influence of PE, EE, and SI on BI and adoption. These findings underscore the significance of psychological factors, particularly self-esteem, in promoting the adoption of AIAT and offer guidance for developing inclusive educational strategies. Full article

Mobile learning (m-learning) technologies are gaining popularity in universities but not uniformly across institutions because of cognitive, affective, and behavior obstacles. This research tested and applied an expansion of the Technology Acceptance Model (TAM) with technostress (TECH) and resistance to change (RTC) as affective obstacles, as well as the core predictors of perceived usefulness (PU), perceived ease of use (PE), and perceived risk (PR). By employing a cross-sectional survey of Greek university students (N = 608) and partial least squares structural equation modeling (PLS-SEM), we tested direct and indirect impacts on behavioral intention (BI) to apply m-learning applications. The results affirm that PU and PE are direct predictors of BI, while PR has no direct impact on BI but acts indirectly through TECH and RTC. Mediation is partial in terms of PE and PU and indirect-only (complete) in terms of PR with respect to the impact of affective states on adoption. Multi-group comparisons found differences in terms of gender, age, confidence, and years of use but not frequency of use, implying that psychological and experiential characteristics have a greater impact on intention than habitual patterns. These results offer theory-driven and segment-specific guidelines for psychologically aware, user-focused m-learning adoption in higher education. Full article

Fast and precise monitoring of soil organic matter (SOM) during maize growth periods is crucial for real-time assessment of soil quality. However, the big challenge we usually face is that many agricultural soils are covered by crops or snow, and the bare soil period is short, which makes reliable SOM prediction complex and difficult. In this study, an unmanned aerial vehicle (UAV) was utilized to acquire multi-temporal hyperspectral images of maize across the key growth stages at the field scale. The auxiliary predictors, such as spectral indices (I), field management (F), plant characteristics (V), and soil properties (S), were also introduced. We used stepwise multiple linear regression, partial least squares regression (PLSR), random forest (RF) regression, and XGBoost regression models for SOM prediction, and the results show the following: (1) Multi-temporal remote sensing information combined with multi-source predictors and their combinations can accurately estimate SOM content across the key growth periods. The best-fitting model depended on the types of models and predictors selected. With the I + F + V + S predictor combination, the best SOM prediction was achieved by using the XGBoost model (R² = 0.72, RMSE = 0.27%, nRMSE = 0.16%) in the R3 stage. (2) The relative importance of soil properties, spectral indices, plant characteristics, and field management was 55.36%, 26.09%, 9.69%, and 8.86%, respectively, for the multiple periods combination. Here, this approach can overcome the impact of the crop cover condition by using multi-temporal UAV hyperspectral images combined with valuable auxiliary variables. This study can also improve the field-scale farmland soil properties assessment and mapping accuracy, which will aid in soil carbon sequestration and soil management. Full article

This study developed a rapid, non-destructive method for the quantitative detection of protein in cottonseed by integrating near-infrared (NIR) fiber spectroscopy with chemometric machine learning. The establishment of this method holds significant importance for the rational and efficient utilization of cottonseed resources, advancing research on the genetic improvement of cottonseed nutritional quality, and promoting the development of equipment for raw cottonseed protein detection. Fuzzy cottonseed samples from three varieties were collected, and their NIR fiber-optic spectra were acquired. Reference protein contents were measured using the Kjeldahl method. Spectra were denoised through preprocessing, after which informative wavelengths were selected by combining Uninformative Variable Elimination (UVE) with Competitive Adaptive Reweighted Sampling (CARS) and the Random Frog (RF) algorithm. Partial least squares regression (PLSR), least-squares support vector machine (LSSVM), and support vector regression (SVR) models were then constructed to predict protein content. Model performance was assessed using the coefficient of determination (R²), root-mean-square error (RMSE), residual predictive deviation (RPD), and range error ratio (RER). The results indicate that the standard normal variate (SNV) is the most effective preprocessing step. The best performance was achieved by the LSSVM model coupled with UVE + CARS, yielding R² = 0.8571, RMSE = 0.0033, RPD = 2.7078, and RER = 10.72, outperforming the PLSR and SVR counterparts. These findings provide technical support for the rapid detection of fuzzy cottonseed protein and lay the groundwork for the development of related detection equipment. Full article

This study investigates the role of Modern Management Accounting (MMA)—which integrates Strategic Management Accounting (SMA) and Strategic Customer Knowledge (SCK)—in driving Sustainable Competitive Advantage (SCA) and Business Sustainability (BS) in Thai green hotels. Business Sustainability is conceptualized as the achievement of balanced outcomes across economic performance, social responsibility, and environmental stewardship. It addresses a theoretical debate by testing two competing SCA models: a disaggregated model (which separates SCA into Customer Experience Advantage (CEA) and Operational Efficiency Advantage (OEA)) and a holistic model (which treats SCA as a unified construct). Data from 115 certified green hotels were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results revealed a critical distinction between the models. In the disaggregated model, SMA and SCK contributed to both CEA and OEA, but only OEA directly enhanced BS and served as a partial mediator in the relationships from both SMA and SCK to BS, whereas CEA showed no significant mediating effects. Conversely, the holistic model demonstrated that overall SCA served as a partial mediator in the relationships from both SMA and SCK to BS, while also exerting a strong direct effect on BS. The study concludes that achieving business sustainability requires a holistic SCA that integrates both operational efficiency and customer experience, offering a comprehensive framework for strategic management in the hotel industry. These findings underscore the strategic imperative for hotel managers to cultivate an integrated competitive advantage, where superior customer experiences and operational excellence are synergistically managed, to ensure long-term business sustainability. Full article

In light of escalating global environmental deterioration, studies on pro-environmental intention and behaviour with the ultimate goal of identifying contributing factors to minimise environmental issues are common. Theory of Planned Behaviour (TPB) is widely used to study environmental intentions and behaviours. However, how quality of life (QoL) influences these intentions and interactions among TPB’s own variables within a single research framework has not been thoroughly explored. Therefore, this study extends TPB by incorporating the four dimensions of QoL, as measured by the Control, Autonomy, Self-Realisation, and Pleasure (CASP-19) scale, to understand pro-environmental intentions from Malaysian viewpoints. In this study, quantitative approach was applied, and the data were collected from Malaysians aged 18 and above (N = 182) in Klang Valley, Malaysia. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), a two-step approach was employed to assess the measurement and structural models. The findings confirmed Theory of Planned Behaviour (TPB) is a robust model for environmental studies showing that subjective norm and perceived behavioural control significantly influence attitudes toward pro-environmental behaviour, ultimately leading to pro-environmental intention. Interestingly, this study found no relationship between QoL dimensions and pro-environmental intention. Lastly, both theoretical and managerial implications were discussed, and research limitations and suggestions for future research directions were put forward. Full article

This study examines the descriptive trajectories through which service innovation is associated with customer exit dynamics after service failures, drawing on a three-wave panel of 532 online travel agency users and employing partial least squares structural equation modeling with predictive assessment. We analyze how innovation is associated with switching intentions via brand hate and brand distrust over time. Results reveal distinct temporal patterns: service innovation is linked to consistent reductions in both hate and distrust, yet only hate emerges as a salient mediator whose marginal association with switching intensifies over time. In contrast, distrust, although mitigated by innovation, remains relatively stable and behaviorally inert. Rather than asserting a causal explanation, we document temporal associations—labelled here as a “dilution effect”—to indicate that innovation coincides with weakening negative emotions but only partial attenuation of their behavioral correlates. By distinguishing between the fading but influential role of hate and the persistent yet inert nature of distrust, this study clarifies differentiated pathways through which negative states coincide with customer exit. For managers, the results highlight the need for staged innovation strategies to dissipate hate, complemented by long-term trust-repair initiatives to address enduring distrust and reduce customer churn. Full article

Potatoes are the most extensively cultivated vegetable crop in Canada and rank as the fifth largest primary agricultural commodity. Given their diverse end uses and significant market value, particularly in processed forms, ensuring consistent quality from harvest to consumption is of critical importance. Total glycoalkaloids (TGA) are nitrogen-containing secondary metabolites that are known to accumulate in the tuber as an effect of greening in-field or elsewhere in the supply chain. In this study, 210 Yukon Gold (YG) potatoes were exposed to a constant light source to green over a period of 14 days and sampled in 7-day intervals. The samples were scanned using a short-wave infrared (SWIR) hyperspectral imaging camera in the 900–2500 nm wavelength range. Once individually scanned, pixel-wise spectral data was extracted and averaged for each tuber and matched with its respective ground truth TGA values which were obtained using a High-Performance Liquid Chromatography (HPLC) system. Prediction models using the partial least squares regression technique were developed from the extracted hyperspectral data and reference TGA values. Wavelength selection techniques such as competitive adaptive re-weighted sampling (CARS) and backward elimination (BE) were deployed to reduce the number of contributing wavelengths for practical applications. The best model resulted in a correlation coefficient of cross-validation (R²_cv) of 0.72 with a root mean square error of cross-validation (RMSE_cv) of 51.50 ppm. Full article