Search Results (2,282)

Kiwifruit (Actinidia spp.) is a globally important economic fruit with high nutritional value. Fruit peelability, defined as the mechanical ease of separating the peel from the fruit flesh, is a critical quality trait influencing consumer experience and market competitiveness and has emerged as a critical breeding target in fruit crop improvement programs. The present review systematically synthesized existing studies on kiwifruit peelability, and focused on its evolutionary trajectory, genotypic divergence, quantitative evaluation, possible underlying mechanisms, and artificial manipulation strategies. Kiwifruit peelability research has advanced from early exploratory studies in New Zealand (2010s) to systematic investigations in China (2020s), with milestones including the development of evaluation metrics and the identification of genetic resources. Genotypic variation exists among kiwifruit genera. Several Actinidia eriantha accessions and the novel Actinidia longicarpa cultivar ‘Guifei’ exhibit superior peelability, whereas most commercial Actinidia chinensis and Actinidia deliciosa cultivars exhibit poor peelability. Quantitative evaluation highlights the need for standardized metrics, with “skin-flesh adhesion force” and “peel toughness” proposed as robust, instrument-quantifiable indicators to minimize operational variability. Mechanistically, peelability is speculated to be governed by cell wall polysaccharide metabolism and phytohormone signaling networks. Pectin degradation and differential distribution during fruit development form critical “peeling zones”, whereas ethylene, abscisic acid, and indoleacetic acid may regulate cell wall remodeling and softening, collectively influencing skin-flesh adhesion. Owing to the scarcity of easy-to-peel kiwifruit cultivars, artificial manipulation methods, including manual peeling benchmarking, lye treatment, and thermal peeling, can be employed to further optimize kiwifruit peelability. Currently, shortcomings include incomplete genotype-phenotype characterization, limited availability of easy-peeling germplasms, and a fragmented understanding of the underlying mechanisms. Future research should focus on methodological innovation, germplasm development, and the elucidation of relevant mechanisms. Full article

Objective: Considering the absence of research testing the entire sequence of passion, behavioral regulation, and subjective well-being (SWB), this study aimed to analyze the hypothetical causal relationships between the variables of a model that integrates the Dualistic Passion Model (DMP) and Self-Determination Theory (SDT) in order to understand the impact of harmonious passion (HP) and obsessive passion (OP) and the regulation of motivation on the SWB of elite athletes with disability. Method: This study includes 143 elite athletes from national adapted sports (36 female; 107 male) aged between 15 and 59 (M = 29.21; SD = 10.45). Weekly training sessions ranged from 1 to 12 (M = 4.52; SD = 2.71), and the years of competitive practice ranged from 1 to 28 (M = 5.55; SD = 6.98). Data were collected using valid and reliable questionnaires for the study population and analyzed using structural equation analysis. The following results were identified: a positive and a significant effect between OP and self-determination motivation (SDM); a positive but not a significant effect between OP and non-self-determination motivation (NSDM); a significant effect between SDM and SWL and SDM and positive affect (PA); and, finally, a positive but non-significant effect between SDM and negative affect (NA). In contrast, there is a positive and significant effect between HP and SDM; a negative and significant effect between HP and NSDM; a positive but non-significant effect between NSDM and SWL; a negative and significant effect between NSDM and PA; and, finally, a positive and significant effect between NSDM and NA. Conclusions: The perception of passion regarding sport can be a positive predictor of SDM, which, in turn, can influence levels of SWB, both from a cognitive point of view (SWL) and from an emotional point of view (PA). This reinforces the positive effect of the self-determination behavior in adapted sport on SWB and its contribution to health and quality of life in people with disabilities. Full article

This paper presents the multi-triangular ring and self-routing protocol (MTRSRP), which is a new decentralized strategy designed to boost throughput and network efficiency in multiring scatternets. MTRSRP comprises two primary phases: leader election and scatternet formation, which collaborate to establish an effective multi-triangular ring topology. In the leader election phase, nodes exchange broadcast messages to gather neighbor information and elect coordinators through a competitive process. The scatternet formation phase determines the optimal number of rings based on the coordinator’s collected node information and predefined rules. The master nodes then send unicast connection requests to establish piconets within the scatternet, following a predefined role table. Intra- and inter-bridge nodes were activated to interconnect the piconets, creating a cohesive multi-triangular ring scatternet. Additionally, MTRSRP incorporates a self-routing addressing scheme within the triangular ring architecture, optimizing packet transmission paths and reducing overhead by utilizing master/slave relationships established during scatternet formation. Simulation results indicate that MTRSRP with dual-bridge connectivity outperforms the cluster-based on-demand routing protocol and Bluetooth low-energy mesh schemes in key network transmission performance metrics such as the transmission rate, packet delay, and delivery ratio. In summary, MTRSRP significantly enhances throughput, optimizes routing paths, and improves network efficiency in multi-ring scatternets through its multi-triangular ring topology and self-routing capabilities. Full article

The introduction of mobile banking is essential in today’s financial sector, where technological innovation plays a critical role. To remain competitive in the current market, businesses must analyze client attitudes and perspectives, as these influence long-term demand and overall profitability. While previous studies have explored general adoption behaviors, limited research has examined how individual factors such as social influence, lifestyle compatibility, financial technology self-efficacy, and perceived usage cost affect mobile banking adoption among specific generational cohorts. This study addresses that gap by offering insights into these variables, contributing to the growing literature on mobile banking adoption, and presenting actionable recommendations for financial institutions targeting younger market segments. Using a structured questionnaire survey, data were collected from both users and non-users of mobile banking among the Gen Z population in the United States. The regression model significantly predicts mobile banking adoption, with an intercept of $-0.548$ ($p < 0.001$). Among the independent variables, perceived cost of usage has the strongest positive effect on adoption ($B=0.857$, $\beta =0.722$, $p < 0.001$), suggesting that adoption increases when mobile banking is perceived as more affordable. Social influence also has a significant positive impact ($B=0.642$, $\beta =0.643$, $p < 0.001$), indicating that peer influence is a central driver of adoption decisions. However, self-efficacy shows a significant negative relationship ($B=-0.343$, $\beta =-0.339$, $p < 0.001$), and lifestyle compatibility was found to be statistically insignificant ($p=0.615$). These findings suggest that reducing perceived costs, through lower fees, data bundling, or clearer communication about affordability, can directly enhance adoption among Gen Z consumers. Furthermore, leveraging peer influence via referral rewards, Partnerships with influencers, and in-app social features can increase user adoption. Since digital self-efficacy presents a barrier for some, banks should prioritize simplifying user interfaces and offering guided assistance, such as tutorials or chat-based support. Future research may employ longitudinal designs or analyze real-life transaction data for a more objective understanding of behavior. Additional variables like trust, perceived risk, and regulatory policies, not included in this study, should be integrated into future models to offer a more comprehensive analysis. Full article

E-commerce growth has reshaped consumer behavior and retail services, driving parcel demand and challenging last-mile logistics. Existing research predominantly relies on survey data and global regression models that overlook intra-urban spatial heterogeneity in shopping behaviors. This study bridges this gap by analyzing e-commerce demand’s spatial distribution from a retail service perspective, identifying key drivers, and evaluating implications for omnichannel strategies and logistics. Utilizing waybill big data, spatial analysis, and multiscale geographically weighted regression, we reveal: (1) High-density e-commerce demand areas are predominantly located in central districts, whereas peripheral regions exhibit statistically lower volumes. The spatial distribution pattern of e-commerce demand aligns with the urban development spatial structure. (2) Factors such as population density and education levels significantly influence e-commerce demand. (3) Convenience stores play a dual role as retail service providers and parcel collection points, reinforcing their importance in shaping consumer accessibility and service efficiency, particularly in underserved urban areas. (4) Supermarkets exert a substitution effect on online shopping by offering immediate product availability, highlighting their role in shaping consumer purchasing preferences and retail service strategies. These findings contribute to retail and consumer services research by demonstrating how spatial e-commerce demand patterns reflect consumer shopping preferences, the role of omnichannel retail strategies, and the competitive dynamics between e-commerce and physical retail formats. Full article

As economically important sympatric species in the Northwest Pacific, the Japanese sardine (Sardinops melanostictus) and Chub mackerel (Scomber japonicus) exhibit significant biological interactions. Understanding the impact of interspecies competition on their habitat dynamics can provide crucial insights for the sustainable development and management of these interconnected species resources. This study utilizes fisheries data of S. melanostictus and S. japonicus from the Northwest Pacific, collected from June to November between 2017 and 2020. We integrated various environmental parameters, including temperature at different depths (0, 50, 100, 150, and 200 m), eddy kinetic energy (EKE), sea surface height (SSH), chlorophyll-a concentration (Chl-a), and the oceanic Niño index (ONI), to construct interspecific competition species distribution model (icSDM) for both species. We validated these models by overlaying the predicted habitats with fisheries data from 2021 and performing cross-validation to assess the models’ reliability. Furthermore, we conducted correlation analyses of the habitats of these two species to evaluate the impact of interspecies relationships on their habitat dynamics. The results indicate that, compared to single-species habitat models, the interspecific competition species distribution model (icSDM) for these two species exhibit a significantly higher explanatory power, with R² values increasing by up to 0.29; interspecific competition significantly influences the habitat dynamics of S. melanostictus and S. japonicus, strengthening the correlation between their habitat changes. This relationship exhibits a positive correlation at specific stages, with the highest correlations observed in June, July, and October, at 0.81, 0.80, and 0.88, respectively; interspecific competition also demonstrates stage-specific differences in its impact on the habitat dynamics of S. melanostictus and S. japonicus, with the most pronounced differences occurring in August and November. Compared to S. melanostictus, interspecific competition is more beneficial for the expansion of the optimal habitat (HIS ≥ 0.6) for S. japonicus and, to some extent, inhibits the habitat expansion of S. melanostictus. The variation in migratory routes and predatory interactions (with larger individuals of S. japonicus preying on smaller individuals of S. melanostictus) likely constitutes the primary factors contributing to these observed differences. Full article

Research has widely validated three-band spectral index as a simple, valid, and highly accurate method of estimating the copper content of soil. However, selecting the best band combination from hundreds of thousands, even millions of candidate combinations in hyperspectral data, is a very complicated problem. To address this issue, this study collected a total of 170 soil samples from the Aktas copper-gold mining area in Fuyun County, Xinjiang, China. Then, two algorithms including Competitive Weighted Resampling (CARS) and Stepwise Regression Analysis (STE) were applied to pick the bands from the original and first-order derivative spectra, respectively. A three-band index model was developed using the selected feature bands to estimate soil copper content. Results showed the first-order derivative spectrum transforms the spectral curve into a sharper one, with more peaks and valleys, which is beneficial for increasing the correlation between bands and copper content compared with the original spectrum. Moreover, integrating first-order derivative spectroscopy with CARS makes it possible to precisely identify key spectral bands and outperforms the dimensionality-reduction capabilities compared with the integration of STE. This strategy drastically reduces the time spent screening and is proven to have similar model accuracy, as compared to the individual group lifting method. Specifically, it reduces the duration of an 8 h task down to a mere 2 s. An intelligent screening of three-band indices is proposed in this study as a method of rapidly estimating copper content in soil. Full article

Background: Automated surgical navigation can be separated into three stages: (1) organ identification and localization, (2) identification of the organs requiring further surgery, and (3) automated planning of the operation path and steps. With its ideal visual and operating system, the da Vinci surgical system provides a promising platform for automated surgical navigation. This study focuses on the first step in automated surgical navigation by identifying organs in gynecological surgery. Methods: Due to the difficulty of collecting da Vinci gynecological endoscopy data, we propose DeepVinci, a novel end-to-end high-performance encoder–decoder network based on convolutional neural networks (CNNs) for pixel-level organ semantic segmentation. Specifically, to overcome the drawback of a limited field of view, we incorporate a densely multi-scale pyramid module and feature fusion module, which can also enhance the global context information. In addition, the system integrates an edge supervision network to refine the segmented results on the decoding side. Results: Experimental results show that DeepVinci can achieve state-of-the-art accuracy, obtaining dice similarity coefficient and mean pixel accuracy values of 0.684 and 0.700, respectively. Conclusions: The proposed DeepVinci network presents a practical and competitive semantic segmentation solution for da Vinci gynecological surgery. Full article

Employee creativity is essential for navigating digital disruption and maintaining organizational competitiveness; however, the mechanisms through which digital leadership fosters creativity remain underexplored. This study investigates the psychological and social processes through which digital leadership influences workplace creativity. Grounded in social cognitive and social exchange theories, the proposed model incorporates innovation self-efficacy and knowledge sharing as mediators and technology readiness as a moderator. Data were collected using a three-wave, time-lagged, multi-source survey design from 234 matched respondents, including employees and supervisors, across 20 business units in seven regional branches of a large Chinese organization undergoing digital transformation. The findings indicate that digital leadership significantly enhances employee creativity through the partial mediation of both innovation self-efficacy and knowledge sharing. Notably, the indirect effect through knowledge sharing was stronger, underscoring the critical role of collaborative processes in driving creativity. Furthermore, technology readiness positively moderates the effects of digital leadership on both mediators and amplifies the indirect effects on creativity. These findings provide valuable insights into how organizations can leverage digital leadership more effectively by aligning leadership strategies with employees’ psychological readiness and fostering a digitally supportive work environment. Full article

Landslides are a common geological hazard in mountainous areas, causing significant damage to ecosystems and production activities. Near-natural ecological restoration is considered an effective strategy for post-landslide recovery. To investigate the impact of near-natural restoration strategies on the recovery of plant communities and soil in landslide-affected areas, we selected landslide plots in Lantian County at 1, 6, and 11 years post-landslide as study sites, surveyed plots undergoing near-natural restoration and adjacent undisturbed control plots (CK), and collected and analyzed data on plant communities and soil properties. The results indicate that vegetation succession followed a path from “human intervention to natural competition”: species richness peaked at 1 year post-landslide (D_m = 4.2). By 11 years, dominant species prevailed, with tree species decreasing to 4.1 ± 0.3, while herbaceous diversity increased by 200% (from 4 to 12 species). Soil recovery showed significant temporal effects: total nitrogen (TN) and dehydrogenase activity (DHA) exhibited the greatest increases after 1 year post-landslide (132% and 232%, respectively), and by 11 years, the available nitrogen (AN) in restored plots recovered to 98% of the CK levels. Correlations between plant and soil characteristics strengthened over time: at 1 year, only 6–9 pairs showed significant correlations (p < 0.05), increasing to 21–23 pairs at 11 years. Near-natural restoration drives system recovery through the “selection of native species via competition and activation of microbial functional groups”. The 6–11-year period post-landslide is a critical window for structural optimization, and we recommend phased dynamic regulation to balance biodiversity and ecological functions. Full article

In the increasingly competitive landscape of higher education, student satisfaction and loyalty are recognized as essential components for institutional sustainability and long-term success. This study aims to examine the interrelationships between service quality, technological innovation, student satisfaction, and student loyalty within higher education institutions in the Turkish Republic of Northern Cyprus (TRNC). Grounded in relationship marketing theory and the expectancy–disconfirmation paradigm, the research develops and tests a structural model that investigates the impact of perceived service quality on technological innovation, student satisfaction, and loyalty. The data were collected from 448 undergraduate students studying in the faculties of education at five leading private universities in TRNC, selected based on their international academic rankings. The analysis, conducted using structural equation modelling (SEM), reveals that service quality significantly and directly influences technological innovation, student satisfaction, and student loyalty. Additionally, technological innovation has a positive but comparatively weaker effect on student loyalty. Among the variables, student satisfaction emerges as the strongest determinant of loyalty, serving as a key mediator in the relationship between service quality and loyalty. This research contributes to the higher education literature by extending the traditional service quality–loyalty framework with the inclusion of technological innovation. The findings offer practical insights for university administrators, emphasizing the importance of delivering high-quality educational services combined with continuous digital innovation to enhance the student experience and foster long-term student commitment. Full article

To investigate the characteristics of rhizosphere soil microbial communities associated with Schisandra sphenanthera across different altitudinal gradients and to reveal the driving factors of microbial community dynamics, this study collected rhizosphere soil samples at four elevations: 900 m (HB1), 1100 m (HB2), 1300 m (HB3), and 1500 m (HB4). High-throughput sequencing and molecular ecological network analysis were employed to analyze the microbial community composition and species interactions. A null model was applied to elucidate community assembly mechanisms. The results demonstrated that bacterial communities were dominated by Proteobacteria, Acidobacteriota, Actinobacteriota, and Chloroflexi. The relative abundance of Proteobacteria increased with elevation, while that of Acidobacteriota and Actinobacteriota declined. Fungal communities were primarily composed of Ascomycota and Basidiomycota, with both showing elevated relative abundances at higher altitudes. Diversity indices revealed that HB2 exhibited the highest bacterial Chao, Ace, and Shannon indices but the lowest Simpson index. For fungi, HB3 displayed the highest Chao and Ace indices, whereas HB4 showed the highest Shannon index and the lowest Simpson index. Ecological network analysis indicated stronger bacterial competition at lower elevations and enhanced cooperation at higher elevations, contrasting with fungal communities that exhibited increased competition at higher altitudes. Altitude and soil nutrients were negatively correlated with soil carbon content, while plant nutrients and fungal diversity positively correlated with soil carbon. Null model analysis suggested that deterministic processes dominated bacterial community assembly, whereas stochastic processes governed fungal assembly. These findings highlight significant altitudinal shifts in the microbial community structure and assembly mechanisms in S. sphenanthera rhizosphere soils, driven by the synergistic effects of soil nutrients, plant growth, and fungal diversity. This study provides critical insights into microbial ecology and carbon cycling in alpine ecosystems, offering a scientific basis for ecosystem management and conservation. Full article

Background/Objectives: Urinary incontinence (UI), defined as the involuntary loss of urine, is common among female athletes. As more women engage in competitive sports, numerous studies have explored UI in young, nulliparous, and physically active women. The objectives of this study were (i) to analyze the prevalence, severity, and characteristics of UI in professional nulliparous female soccer players and (ii) to compare the status of the pelvic floor muscles (PFMs) between professional soccer players and physically active young women. Methods: This descriptive cross-sectional study included professional soccer players (n = 18) and physically active women (n = 14). UI was assessed using the ICIQ-SF questionnaire, and PFM function was evaluated through intracavitary examination using the PERFECT method. Additional data were collected on body composition and on urinary, bowel, and sexual health. Results: UI affected 35.7% of physically active women and 50% of professional soccer players. Stress urinary incontinence (SUI) was the most common type, present in 100% of affected soccer players and 60% of affected active women. The severity of UI was mostly mild, with no significant differences between groups. PFM assessment revealed deficiencies in control, relaxation, endurance, and rapid contractions, as well as difficulties performing an effective perineal locking (PL) maneuver during increased intra-abdominal pressure. Conclusions: These findings highlight the need for targeted programs focused on strengthening and educating athletes about their PFMs, aiming to prevent UI and improve both performance and quality of life. The study reinforces the importance of preventive strategies for pelvic floor health in sports. Full article

Background: Brazilian Jiu-Jitsu (BJJ) is a physically demanding sport associated with a notable risk of musculoskeletal injuries. Understanding injury patterns, rehabilitation approaches, and psychological readiness to return to sport (RTS) is essential for prevention and management strategies. This study aimed to investigate injury characteristics among Italian BJJ athletes, assess their rehabilitation processes and psychological recovery, and identify key risk factors such as belt level, body mass index (BMI), and training load. Methods: A cross-sectional survey was conducted among members of the Italian BJJ community, including amateur and competitive athletes. A total of 360 participants completed a 36-item online questionnaire. Data collected included injury history, rehabilitation strategies, RTS timelines, and responses to the Injury-Psychological Readiness to Return to Sport (I-PRRS) scale. A Random Forest machine learning algorithm was used to identify and rank potential injury risk factors. Results: Of the 360 respondents, 331 (92%) reported at least one injury, predominantly occurring during training sessions. The knee was the most frequently injured joint, and the action “attempting to pass guard” was the most reported mechanism. Most athletes (65%) returned to training within one month. BMI and age emerged as the most significant predictors of injury risk. Psychological readiness scores indicated moderate confidence, with the lowest levels associated with playing without pain. Conclusions: Injuries in BJJ are common, particularly affecting the knee. Psychological readiness, especially confidence in training without pain, plays a critical role in RTS outcomes. Machine learning models may aid in identifying individual risk factors and guiding injury prevention strategies. Full article

In the current era of a dynamic environment, organizations need to continuously innovate and transform to remain competitive. Digital transformation is an essential driver across organizations, including small and medium-sized enterprises (SMEs), reshaping organizational agility. This research examines the interconnection among knowledge sharing, digital transformation, open innovation, organizational agility, and transformational leadership. A quantitative research design was employed, using an online survey with data collected from 543 participants selected through a stratified random sampling from SMEs in China. Data were analyzed by utilizing partial least squares structural equation modeling. The results include a significant impact of knowledge sharing on digital transformation, digital transformation on open innovation, and open innovation on organizational agility. Additionally, digital transformation and open innovation were found to significantly mediate the relationship between knowledge sharing and open innovation and organizational agility. Moreover, transformational leadership significantly moderated the impact of digital transformation on open innovation. The model explained 67.7% of the variation in organizational agility. The research provides a holistic model for SMEs aiming to leverage information sharing, technological integration, and leadership practice to improve flexible and innovative systems, contributing to theoretical understanding and practical solutions to sustainable resilience. Full article