Search Results (45,086)

This study examines the relationship between employee empowerment and sustainable competitiveness in the food and beverage manufacturing industry through the lenses of the Resource-Based View (RBV) and Dynamic Capability perspectives. Although employee empowerment has been widely associated with organisational success, comparatively limited attention has been devoted to its relationship with operational dimensions of competitiveness in manufacturing firms within emerging economies. Using cross-sectional survey data collected from 277 employees of the five largest food and beverage manufacturing companies in Southwest Nigeria, the study investigates employee empowerment as a multidimensional construct comprising structural and psychological components. Sustainable competitiveness is operationalised through cost leadership, product quality, on-time delivery, and flexibility. Data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings indicate that employee empowerment is positively associated with all four dimensions of competitiveness. The strongest associations were with flexibility, followed by product quality and on-time delivery. The association with cost leadership was relatively weaker. These findings indicate that employee empowerment might be particularly relevant to adaptability-oriented capabilities in manufacturing environments. The study contributes to the literature by integrating Resource-Based View and Dynamic Capability perspectives and provides insights into the importance of workforce-related capabilities in aiding operational competitiveness in manufacturing firms operating under resource-constrained conditions. Full article

Modern terrain rendering frameworks often struggle with the inherent trade-off between geometric continuity and hardware utilization. State-of-the-art watertight tessellation methods typically rely on explicit adjacency management and multi-pass synchronization, which severely restrict GPU parallelism and induce significant performance spikes during rapid camera transitions. In this paper, we propose a high-throughput, decoupled terrain rendering architecture that ensures visual continuity without the need for horizontal dependency tracking. Our framework leverages a linearized binary tree maintained within a 1D Unordered Access View (UAV), enabling each GPU thread to perform refinement and geometric reconstruction in total isolation. To resolve T-junction artifacts, we introduce an adjacency-blind directional stitching mechanism that utilizes localized hierarchical flags and per-edge error metrics to perform deterministic geometric repair in a single execution pass. Experimental results demonstrate that the proposed method achieves a stable rendering throughput of over 170 FPS on a large-scale $8192\times 8192$ dataset. Notably, our approach provides a 14% improvement in frame-rate stability during instantaneous camera teleportation compared to existing watertight frameworks, while simultaneously reducing the average triangle count by 21% through optimized boundary repair. These results confirm that our decoupled pipeline offers a robust and scalable solution for real-time spatial computing and high-performance simulation environments. Full article

Arbuscular mycorrhizal fungi (AMF) are crucial symbiotic microorganisms in terrestrial ecosystems, playing a vital role in maintaining orchard soil health and productivity. However, how organic–and Ca, Mg, Zn fertilizers co-application affect vertical stratification and ecological functions of arbuscular mycorrhizal fungi (AMF) in perennial fruit orchards remains unclear. Based on a five-year in situ peach trial, we established three fertilization regimes: low- (LWF), medium- (MWF), and high-input (HWF) regimes. We systematically analyzed the AMF community structure, diversity, and their correlations with soil physicochemical properties, as well as peach tree physiology, fruit yield, and quality across two soil depths: 0–20 cm (topsoil) and 20–40 cm (subsoil). HWF significantly inhibited AMF root colonization rates and spore density (p < 0.05), while reducing community α-diversity AMF α-diversity (p < 0.05), characterized by the enrichment of genera such as Glomus and a decrease in the relative abundance of Rhizoglomus. Redundancy analysis (RDA) identified available Zn (AZn) and Mg (WMg) as key drivers of this restructuring. Integrating RDA results into depth-specific partial least squares structural equation models (PLS-SEM), we found that subsoil AZn/WMg indirectly boosted yield by reshaping AMF composition (β = 0.34, p = 0.006), mediated via improved canopy status (NDVI, PRI). Total effect analysis confirmed the dominant role of subsoil pathways. These findings challenge the prevailing topsoil-centric view of soil microbial ecology and underscore the importance of considering the full soil profile when evaluating the impacts of agricultural practices on beneficial symbionts. We conclude that sustainable management strategies should account for depth-dependent AMF responses to maintain both productivity and belowground biodiversity across the entire rooting zone. Full article

This study explores how university students experience conversational artificial intelligence (AI) in the era of generative AI from the perspectives of algorithmic intimacy, social connection, well-being, and autonomy, and identifies their subjective meaning structures. Specifically, it examines how university students perceive conversational AI in relation to emotional regulation, self-understanding, relational boundaries, and autonomy, and how these perceptions relate to intimacy and well-being. Unlike previous studies focused primarily on AI use and acceptance, this study analyses how students interpret their experiences with conversational AI and negotiate relational boundaries. Using Q methodology, we developed 40 Q statements from literature review and in-depth interviews. Fifty-six university students in South Korea with experience using conversational AI completed the Q-sorting process. A four-factor solution explained 55% of the total variance and yielded four distinct types: (1) Relationship-Negating Instrumentalists, (2) Selective Emotional Utilizers, (3) Reflective Distancers, and (4) Autonomy Defenders. Although none of the groups viewed AI as a complete substitute for human relationships, they differed in their acceptance of algorithmic intimacy, use of AI for emotional support and regulation, concerns about dependence, and efforts to protect autonomy. These findings suggest that conversational AI experiences involve negotiating intimacy and boundaries rather than producing uniformly positive or negative outcomes. This study complements variable-centred approaches by identifying distinct subjective meaning structures in university students’ human–AI relationship experiences. Full article

Background: Technological innovation in logistics (TIL), logistics capability (LC), and lean logistics (LL) are receiving wider attention in logistics and supply chain research. They are often examined in separate models and less often in relation to both business performance (BP) and market performance (MP). Their joint effects on organizational performance remain insufficiently examined in previous research. Methods: This study examined the effects of TIL, LC, and LL on BP and MP through a quantitative survey conducted among enterprises in Serbia, a transition economy with limited empirical evidence on these relationships. Data from 129 valid responses were analyzed through descriptive statistics, correlation analysis, linear regression analysis, and multicollinearity diagnostics. Results: The findings show that LC has a positive and significant effect on both BP and MP. LL has a positive and significant effect on BP, while TIL has a positive and significant effect on MP. The model explains a larger share of variance in BP than in MP. Conclusions: The results support a differentiated view of logistics transformation and indicate that BP and MP should be examined as related but distinct outcome dimensions. The study integrates TIL, LC, and LL within a unified performance framework. Full article

Soft tissue sarcomas are rare, biologically diverse mesenchymal malignancies in which pharmacologic resistance cannot be explained by a single unifying mechanism. In this narrative review, resistance is conceptualized as a dynamic, multilayered process shaped by histologic subtype, genomic architecture, transcriptional plasticity, the tumor microenvironment, and treatment-driven selective pressure. Resistance to conventional chemotherapy arises through both intrinsic and acquired mechanisms, including altered drug transport and metabolism, enhanced DNA damage responses, impaired apoptotic signaling, clonal selection, and the emergence of therapy-persistent cellular states. By contrast, resistance to targeted and epigenetic therapies more often reflects adaptive bypass signaling, lineage reprogramming, and incomplete identification of subtype-specific dependencies than secondary on-target alterations alone. The tumor microenvironment further contributes to therapeutic failure through hypoxia, extracellular matrix-mediated barriers, abnormal vascularization, myeloid-dominant immunosuppression, and immune exclusion, thereby helping explain the modest and histology-dependent activity of immune checkpoint inhibitors in soft tissue sarcoma. This review also differentiates baseline predictive biomarkers from dynamic resistance-monitoring tools, underscoring the potential—despite still limited clinical maturity—of pharmacogenomic markers, immune signatures, tertiary lymphoid structures, circulating tumor DNA, and circulating methylation-based approaches. Finally, emerging strategies to overcome resistance are examined, including mechanism-based combinations, biomarker-guided treatment selection, synthetic lethality, functional precision platforms, and adaptive histology-specific trial designs. Collectively, these observations support a view of resistance in soft tissue sarcoma as a context-dependent biological process that demands integrated, subtype-aware, and translationally grounded therapeutic strategies. Full article

Astrocytes are increasingly recognized as key regulators of multiple sclerosis (MS) pathogenesis, known to actively influence neuroinflammation, blood–brain barrier integrity, leukocyte recruitment, glial scar formation, and tissue repair. Evidence from both MS and its animal models demonstrates substantial astrocyte heterogeneity, exerting either pathogenic or neuroprotective functions depending on the local microenvironment. In this review, we discuss the diverse roles of astrocytes in MS, with particular focus on signaling pathways that govern astrocyte responses during chronic neuroinflammation. We further explore the growing evidence that astrocytes within chronic active lesion cores are not merely passive structural cells, but instead may be involved in immune regulation, survival signaling, and tissue maintenance. Collectively, these findings support a revised view of astrocytes as regulators of lesion dynamics and CNS homeostasis during MS. A deeper understanding of astrocyte heterogeneity and the signaling networks that control astrocyte function may reveal novel therapeutic opportunities to limit neurodegeneration and disease progression. Full article

Facial attribute segmentation is challenging because facial regions differ in size, shape, texture, and visibility, especially under non-frontal viewing conditions. This study evaluates the segmentation of four facial attribute classes: hair, eyebrows, mustache, and beard. A dataset of 5000 manually annotated FFHQ facial images was used to train and compare approaches within the same evaluation framework: YOLO segmentation, YOLO detection combined with SAM2 segmentation, and U-Net. The methods were evaluated on annotated test set, per facial attribute, and on an additional controlled phantom-based dataset acquired at five viewing angles. The hybrid YOLO detection and SAM2 segmentation pipeline achieved the best overall performance, with micro IoU of 0.820 and a micro Dice score of 0.893 on the annotated test set. Hair and beard are segmented more reliably than eyebrows and mustache, while segmentation accuracy decreased as the viewing angle increased. These results show that facial attribute segmentation performance depends on the selected method, target class, and acquisition viewpoint. The findings provide a basis for selecting and further improving segmentation methods for future registration and medical robotic applications. Full article

Identifying the spatio-temporal evolutionary patterns and driving mechanisms of rural tourism network attention is essential for predicting the development trends of the rural tourism industry and delivering refined industrial governance. Taking 356 prefecture-level cities in China from 2015 to 2024 as basic research units, this paper constructs a comprehensive evaluation system for rural tourism network attention based on multi-source data. Furthermore, its spatio-temporal evolution characteristics and internal influencing factors are systematically investigated by means of spatial autocorrelation analysis and geographically weighted regression. The results indicate that the overall level of rural tourism network attention in China shows an obvious fluctuating growth trend, which can be divided into three successive stages, namely steady growth (from 0.8530 in 2015 to 1.2028 in 2019), explosive growth (from 1.9563 in 2020 to 3.7471 in 2021) and high-level fluctuation (maintained in the high range of 2.4–3.4). In addition, with the continuous iteration of internet communication media, the guiding influence of traditional search platforms has gradually weakened, while emerging social media and short-video platforms have become the core carriers of online tourism traffic. Correspondingly, media innovation persistently reshapes the spatial distribution pattern of rural tourism network attention. In terms of spatial characteristics, rural tourism network attention has undergone a significant transformation from geographical gradient polarization to overall regional equilibrium. Specifically, from 2015 to 2024, the overall Moran’s I index remained positive, with values ranging from 0.0116 to 0.1358, indicating an overall trend of gradual decline. High-attention areas are predominantly concentrated in economically developed urban agglomerations, whereas remote and economically underdeveloped regions exhibit contiguous low-value aggregation characteristics, which reveals a remarkable trend of balanced development nationwide. In view of driving mechanisms, highway network density, tourism income, rural tourism resource and enrollment of university students are identified as the core driving factors dominating the spatio-temporal evolution of rural tourism network attention. Moreover, the intensity of the influence of each factor presents distinct spatial heterogeneity. This study further reveals that the spatial heterogeneity of rural tourism network attention calculated using multi-source fused data shows a remarkable convergent characteristic, which can reflect the actual distribution of the rural tourism market more objectively and accurately. Meanwhile, rural tourism network attention is typically characterized by scale-dependent with the spatial distribution at the macro-scale being more balanced than that at the meso- and micro-scales. Full article

This overview paper highlights the idea that the polytopic approach is more than a modeling technique. It proposes a unified perspective in which polytopic representations constitute a conceptual bridge between complex system dynamics and convex analysis. From modeling to control, the polytope is not only limited to a geometric interpretation but is used as a methodological principle—an intelligent sensor system for structuring uncertainty, representing a nonlinear behaviors, and enabling decision-making, even for critical safety systems. Indeed, the polytopic approach should not be viewed merely as a convexification tool, but as a way of thinking about complexity, i.e., a structured methodology linking representation, uncertainty management, and control synthesis. For this purpose, this work focuses on safety-critical systems, i.e., cyber-physical systems operating under malicious cyber-attacks, where ensuring resilience has become a major challenge. The review highlights recent developments that extend classical polytopic approaches beyond robust control and toward cyber-resilient estimation and control, including false-data injection attack modeling, simultaneous state and attack estimation, resilient observer-based control, and event-triggered control under communication constraints. The paper also discusses how these developments position the polytopic framework with respect to recent advances in cyber-physical security and resilient control. Overall, the proposed perspective illustrates how polytopic representations have evolved into a unifying paradigm for addressing nonlinear dynamics, cyber-attacks, uncertainties, and network-induced constraints while enhancing the resilience, reliability, and operational safety of safety-critical cyber-physical systems. Full article

Background/Objectives: This study aimed to evaluate and compare the clinical characteristics and outcomes of patients with methicillin-susceptible Staphylococcus aureus (MSSA) and streptococcal native joint septic arthritis (NJSA). Methods: This retrospective multicenter study included adult patients with NJSA from three tertiary care hospitals between 2004 and 2023. Patients were categorized into three groups based on bacterial virulence and differences among streptococcal species: MSSA, non-viridans streptococci, and viridans streptococci. Results: A total of 213 NJSA cases were identified, comprising 164 MSSA, 35 non-viridans streptococcal, and 14 viridans streptococcal cases. Non-viridans streptococcal NJSA exhibited significantly more acute clinical features associated with systemic inflammation, including frequent fever, leukocytosis, thrombocytopenia, elevated C-reactive protein levels, higher total bilirubin levels, and acute kidney injury, compared to MSSA and viridans streptococcal NJSA. The clinical presentations were similar between the MSSA and viridans streptococcal groups. The non-viridans streptococcal group showed a higher incidence of concomitant bacteremia, but a lower proportion of positive joint culture results. Treatment approaches were consistent across the groups, except for a shorter duration of antibiotic therapy in the viridans group. Treatment failure rates were comparable: 9.8% for MSSA, 14.3% for non-viridans streptococci, and 21.4% for viridans streptococci. Conclusions: This study highlights the heterogeneous nature of streptococcal NJSA, with non-viridans streptococci presenting more aggressive clinical manifestations despite similar treatment responses across groups. These findings challenge conventional views on streptococci as a less virulent pathogen than MSSA and emphasize the need for diagnostic and management strategies tailored to the unique pathogenic traits of these bacteria. Full article

Background and objectives: Optimal oxygen administration during delivery room resuscitation remains a major challenge in very preterm infants. While both hypoxemia and excessive oxygen exposure have been associated with adverse outcomes, the prognostic value of early oxygenation parameters remains unclear. This study aimed to evaluate the association between preductal SpO₂ at 5 min of life and early respiratory and neurological outcomes in preterm infants born at or below 32 weeks of gestation. Materialsandmethods: This retrospective single-centre study included 31 preterm infants born at ≤32 weeks of gestation, identified from 34 consecutive eligible births. Demographic, delivery room, respiratory, laboratory, and neuroimaging data were collected from medical records. The primary outcome was intraventricular hemorrhage (IVH), graded by the Papile classification, during the first week of life. Secondary outcomes included respiratory support requirements, surfactant administration, and capillary blood gas parameters at two hours of life. Associations were evaluated using Spearman rank correlation; because SpO₂@5 and delivery room FiO₂ were strongly related to gestational age, partial correlations controlling for gestational age were additionally performed, together with a group comparison for IVH. Exact two-sided p values are reported. Results: The median gestational age was 28 weeks + 4 days (range: 22 weeks + 1 day to 31 weeks + 5 days), and the median birth weight was 1120 g. IVH of any grade occurred in 20 infants (64.5%), including severe (grade III–IV) IVH in 10 (32.3%). Median delivery room FiO₂ was 35% (IQR 30–50%), and median SpO₂ at 5 min of life was 83% (IQR 75–90%). Lower SpO₂ at 5 min of life was associated with an increased number of surfactant doses (rs = −0.46, p = 0.010), lower capillary pH at two hours of life (rs = 0.39, p = 0.032), and a higher grade of IVH (rs = −0.39, p = 0.030); median SpO₂@5 was 80% in infants with IVH versus 90% in those without (p = 0.057). Higher delivery room FiO₂ was associated with increased use of DuoPAP (rs = 0.36, p = 0.045), mechanical ventilation (rs = 0.41, p = 0.021), and surfactant administration (rs = 0.56, p < 0.001), as well as lower pH (rs = −0.55, p = 0.002) and higher lactate levels (rs = 0.37, p = 0.044) at two hours of life. Because SpO₂@5 and FiO₂ were both strongly correlated with gestational age (rs = 0.54 and −0.76, respectively), all associations were re-examined controlling for gestational age. The associations of SpO₂@5 with IVH grade (partial rs = −0.22, p = 0.247), surfactant doses (partial rs = −0.08, p = 0.678) and 2 h pH (partial rs = 0.19, p = 0.335) were attenuated and no longer significant, as were those of FiO₂ with mechanical ventilation (partial rs = −0.04, p = 0.817) and surfactant doses (partial rs = −0.01, p = 0.945); only the association between FiO₂ and 2 h pH persisted (partial rs = −0.37, p = 0.048). Conclusions: In preterm infants born at or below 32 weeks of gestation, lower SpO₂ at 5 min and higher delivery room oxygen requirements were associated with less favorable respiratory and metabolic outcomes, as well as with IVH. However, apart from the association between FiO₂ and 2 h pH, none of these associations remained statistically significant after adjustment for gestational age, and these findings, from a small and heterogeneous single-centre cohort, should be considered hypothesis-generating. Early oxygenation parameters are best viewed as simple bedside markers of cardiopulmonary adaptation and overall illness severity in very preterm infants, rather than as independent predictors of clinical outcomes. Further prospective studies are needed to confirm these associations and define clinically relevant threshold values. Full article

How do the frameworks of religion and spirituality influence perceptions of what it means to be a Black man and a family man? This study explores how increases in religiosity and spirituality influence Black masculinity and fatherhood among 33 Black Christian couples (n = 66). Qualitative interviews and analysis examine how religious beliefs and practices may facilitate shifts from independence-centered views of masculinity to family-oriented, spiritually grounded ideals. Participants described how deepened religiosity and spirituality were perceived as assisting with greater marital fidelity, fatherly involvement, and relational commitment, regardless of denominational affiliation, socioeconomic status, or education. Key mechanisms included (1) personal crises and faith community engagement, (2) divine interventions, (3) scripture study, and (4) recovering traditional religious masculinity roles. Findings suggest that religion and spirituality may provide an alternative framework for Black masculinity, one that emphasizes relationality, moral integrity, and family leadership. These processes are interpreted through Ryff’s six-factor model of eudaimonic well-being and mapped onto positive psychology constructs such as resilience, meaning-making, and the sanctification of family roles. Full article

Growing evidence suggests that urban greenery is associated with improved mental health, yet how eye-level exposure functions within specific socio-environmental contexts remains underexplored. This study presents an exploratory case study utilizing semantic segmentation of street-view imagery to quantify eye-level greenery (“open greenery”) across two contrasting community contexts: a densely developed area (Region 1) and a less developed area (Region 2) in Korea. Using interaction models reinforced by 5000-iteration bootstrap analyses, we identified the moderating role of greenery in the relationship between mental health (depression and cognitive function) and life satisfaction. Our findings indicate that the psychological benefits of greenery are highly contingent upon the interplay between individual vulnerability and regional context. Specifically, in Region 1, greenery moderated well-being for the low-cognitive function subgroup, while in Region 2, the moderating effect was most pronounced among individuals with depressive symptoms. Despite the inherent limitations of small subgroup samples, the stability of these patterns across repeated bootstrap iterations highlights meaningful “spatial intersections” where greenery plays a role in shaping psychological well-being. By adopting a case-centric approach, this study highlights that the benefits of street-view greenery are not uniform but context-dependent. These results underscore the necessity of context-aware green infrastructure strategies tailored to the specific environmental needs of vulnerable populations in diverse community settings. Full article

Modern autonomous systems rely on heterogeneous sensing modalities—including vision sensors, millimeter-wave radar, and LiDAR—yet each individual sensor exhibits characteristic failure modes in challenging real-world conditions. While LiDAR-vision co-processing has received extensive attention, the synergistic potential of 4D radar paired with monocular optics remains comparatively unexplored. To fill this gap, we develop a graph-enhanced multi-modal architecture that jointly leverages sparse 4D radar returns and high-resolution camera imagery for scene-level 3D perception. The proposed system is organized around four tightly coupled processing stages: (i) an image-guided point densification scheme (SAA) that augments sparse radar clouds with camera-derived pseudo measurements; (ii) a pose-invariant cross-modal fusion layer that harmonizes enriched radar features with image descriptors and object saliency maps; (iii) a dynamic hypergraph assembly stage that captures higher-order inter-object and cross-sensor dependencies; and (iv) a HyperGCN inference module that regresses 3D bounding parameters and class labels on the resulting relational graph. Integrating the temporal velocity cues native to radar with the rich appearance information from cameras, the system delivers reliable perception under diverse environmental conditions. On the View-of-Delft (VOD) evaluation suite, the proposed model records an mAP of 69.3 and mAOS of 59.8. A systematic ablation further quantifies how geometric invariance—across translation, rotation, and scale transformations—individually affects end-to-end detection fidelity. Full article