Search Results (9,612)

Hybrid fiber-reinforced concrete (HFRC), renowned for its significantly enhanced mechanical properties and structural integrity, is widely used in infrastructure construction and has become a key avenue of modern high-performance concrete development. The hybrid application of basalt fiber (BF) and polypropylene fiber (PPF) at optimized ratios generates synergistic effects, improving both mechanical performance and material service reliability. To explore and evaluate the synergistic mechanism of BF-PPF hybrid fibers on concrete’s mechanical properties and performance, this study employs an orthogonal experimental design and mechanical testing methods, measuring the materials’ static compressive strength (loading rate: 0.6 mm/min), splitting tensile strength (loading rate: 0.12-0.14 MPa/s), dynamic elastic modulus (measured by the ultrasonic method), and dynamic compressive strength (loading rates: 0.6 mm/min, 6 mm/min, and 60 mm/min). For these tests, we prepared 100 mm × 100 mm × 100 mm cubic specimens (for static compressive, dynamic compressive, and splitting tensile tests) and 400 mm × 100 mm × 100 mm prismatic specimens (for dynamic elastic modulus tests), with three parallel specimens in each test group. In addition, the microstructure was characterized by scanning electron microscopy (SEM) to observe the fiber-matrix interaction. The results show that when the BF/PPF volume ratio is 1:2 (BF0.05PPF0.1), the concrete’s compressive strength, splitting tensile strength, and elastic modulus increase by 13.7%, 76.3%, and 116.0%, respectively, with corresponding synergistic effect indices (Q) of 0.057, 0.213, and 0.241, indicating obvious positive synergy. Under dynamic loading, hybrid combinations with higher PPF content (e.g., BF0.05PPF0.1) exhibit strain-rate-dependent enhancements in compressive strength and better impact resistance. SEM analysis reveals that fibers inhibit microcrack propagation through fiber bridging, network distribution, and pull-out resistance, while also improving the interfacial transition zone’s structure. These findings provide theoretical support for the engineering application of composite fiber-reinforced concrete materials. Full article

Scaffold architecture is a key determinant of cell behavior and tissue regeneration in bone tissue engineering, yet the influence of pore size under dynamic culture conditions remains incompletely understood. This study aimed to evaluate the effects of scaffold pore size on osteogenic differentiation of porcine bone marrow-derived mesenchymal stem cells (pBMSCs) cultured in a rotational oxygen-permeable bioreactor system (ROBS). Three-dimensionally (3D) printed beta-tricalcium phosphate (β-TCP) scaffolds with pore sizes of 500 µm and 1000 µm were seeded with pBMSC and cultured for 7 and 14 days under dynamic perfusion conditions. Gene expression analysis revealed significantly higher levels of osteogenic markers (Runx2, BMP-2, ALP, Osx, Col1A1) in the 1000 µm group, particularly at the early time point, with the later-stage marker Osteocalcin (Ocl) rising faster and higher in the 1000 µm group, after a lower expression at 7 days. ALP activity assays corroborated these findings. Despite having lower mechanical strength, the 1000 µm scaffolds supported a homogeneous cell distribution and high viability across all regions. These results suggest that larger pore sizes enhance early osteogenic commitment by improving nutrient transport and fluid flow in dynamic culture. These findings also support the use of larger-pore scaffolds in bioreactor-based preconditioning strategies and underscore the clinical importance of promoting early osteogenic differentiation to reduce in vitro culture time, an essential consideration for the timely preparation of implantable grafts in bone tissue engineering. Full article

Our paper investigates how emotions and cognitive biases shape small investors’ decisions in a bearish market or are perceived as such. Using semi-structured interviews and a focus group, we analyze the behavior of eight management science students engaged in a three-day trading simulation with virtual portfolios. Our findings show that emotions are active forces influencing judgment. Fear, often escalating into anxiety, was pervasive in response to losses and uncertainty, while frustration and powerlessness frequently led to decision paralysis. Early successes sometimes generated happiness and pride but also resulted in overconfidence and excessive risk-taking. These emotional dynamics contributed to the emergence of cognitive biases such as loss aversion, anchoring, confirmation bias, overconfidence, familiarity bias and herd behavior. Emotions often acted as precursors to biases, which then translated into specific decisions—such as holding losing positions, impulsive “revenge” trades or persisting with unsuitable financial strategies. In some cases, strong emotions bypassed cognitive biases and directly drove behavior. Social comparison through portfolio rankings also moderated responses, offering both comfort and additional pressure. By applying a qualitative perspective—not commonly used in behavioral finance—our study highlights the dynamic chain of emotions → biases → decisions and the role of social context. While limited by sample size and the short simulation period, this research provides empirical insights into how psychological mechanisms shape investment behavior under stress, offering avenues for future quantitative studies. Full article

MPs are pervasive pollutants in marine ecosystems, posing risks to aquatic organisms due to their small size and bioaccumulation potential. This study investigated the intestinal toxicity of MP particles extracted from mangrove sediments in zebrafish, comparing the effects before and after microbial degradation. Zebrafish were exposed to either undegraded MPs or microbially degraded MP extracts at concentrations of 0 (control), 2, 10, and 50 mg/L for 21 days in 10 L tanks (stocking density: 10 fish/L), with three replicate tanks per concentration. MPs were dispersed ultrasonically before addition to the water. Intestinal samples were collected on 7, 14, and 21 days for the analysis of immune response (tumor necrosis factor-alpha, TNF-α; interleukin-1 beta, IL-1β; interleukin-6, IL-6; interleukin-8, IL-8) and antioxidant activity (superoxide dismutase, SOD; catalase, CAT). Histopathological analysis revealed intestinal wall thinning, villus damage, and epithelial cell detachment in zebrafish exposed to both undegraded and degraded MP extracts; however, undegraded MPs induced more severe intestinal damage. Results indicated dynamic changes in cytokine expression: TNF-α decreased initially before increasing, while IL-1β and IL-8 first rose then declined. IL-6 peaked on day 7, dropped by day 14, and increased again on day 21. CAT expression decreased, whereas SOD increased only in the pre-degradation group. Microbial degradation reduced intestinal damage severity, with effects intensifying at higher MP exposure levels. These findings demonstrate that MPs can impair zebrafish digestive systems, but microbial degradation mitigates their toxicity. This study underscores the importance of biodegradation as a potential environmental remediation strategy and provides experimental evidence on MPs’ impact on aquatic organisms. Full article

Efficient navigation of Automated Guided Vehicles (AGVs) in dynamic warehouse environments requires real-time and accurate path segmentation algorithms. However, traditional semantic segmentation models suffer from excessive parameters and high computational costs, limiting their deployment on resource-constrained embedded platforms. A lightweight image segmentation algorithm is proposed, built on an improved ESPNet-C architecture, combining Spatial Group-wise Enhance (SGE) and Efficient Channel Attention (ECA) with a dual-branch upsampling decoder. On our custom warehouse dataset, the model attains 90.5% Miou with 0.425 M parameters and runs at ~160 FPS, reducing parameters by ×116–×136 and computational costs by 70–92% in comparison with DeepLabV3+. The proposed model improves boundary coherence by 22% under uneven lighting and achieves 90.2% Miou on the public BDD100K benchmark, demonstrating strong generalization beyond warehouse data. These results highlight its suitability as a real-time visual perception module for AGV navigation in resource-constrained environments and offer practical guidance for designing lightweight semantic segmentation models for embedded applications. Full article

For unmanned ground vehicles in squad mission support systems (SMSS-UGVs), tracking the entire squad as a group, rather than focusing on individual members, can effectively mitigate issues such as target loss caused by occlusion and environmental interference. However, most existing group target tracking methods are designed for extended targets, which typically assume a rigid and unchanging shape. In contrast, pedestrian groups in SMSS-UGV scenarios exhibit inconsistent motions among members, resulting in continuous changes in the overall group shape. To address this challenge, this paper proposes a group target tracking method specifically tailored for SMSS-UGVs in pedestrian tracking scenarios. We introduce a tracking framework that incorporates a data selection mechanism based solely on positional information, enabling robust handling of dynamic group composition through adaptive shape modeling. Furthermore, a novel group target tracking method based on multi-ellipse shape modeling (ME-CGT-UGV) is presented, which effectively captures complex and evolving group formations. The experimental results show that the proposed method reduces orientation error by 86.13% compared to single-target tracking and by 54.79% compared to shapeless modeling methods. It also maintains strong performance under challenging conditions, including occlusions, environmental disturbances, sharp turns, and formation changes. These findings indicate that the proposed approach significantly enhances the effectiveness and operational reliability of SMSS-UGVs in real-world applications. Full article

This study examines how educational attainment and creative-class identity influence public library use among Black homeowners in Ward 8, Washington, D.C., a historically disinvested, yet resilient, Black community. Using an adapted theoretical framework (Chatman’s Small World Theory, Florida’s creative class theory, and Crenshaw’s intersectionality), the research investigates how symbolic capital informs institutional engagement in a racially homogeneous but economically stratified setting. A survey of 56 Black homeowners examined the relationships among education, income, creative-class identity, and library use. Logistic regression analysis revealed that higher educational attainment was a significant predictor of identification with the Black Creative Class^TM. However, neither income nor creative-class identity significantly predicted public library use. These findings challenge the assumption that middle-class status or creative-class affiliation ensures participation in educational or cultural institutions. Instead, they suggest that deeper dynamics, such as cultural relevance, perceived alignment, and trust, may shape engagement with public libraries. The study advances knowledge in library and information science (LIS) and urban studies by demonstrating how spatial context and class distinctions within Black communities shape library engagement. The results underscore the need for culturally responsive library strategies that recognize class-based variation within racial groups, moving beyond monolithic models of community outreach. Full article

Targeting the classification and evaluation of chemical flooding well groups in medium-thick sandstone reservoirs (single-layer thickness: 5–15 m), this study proposes a multi-level classification model based on decision trees. Through the comprehensive analysis of key static factors influencing chemical flooding efficiency, a four-tier classification index system was established, comprising: interlayer/baffle development frequency (Level 1), thickness-weighted permeability rush coefficient (Level 2), reservoir rhythm characteristics (Level 3), and pore-throat radius-based reservoir connectivity quality (Level 4) as its core components. The model innovatively transforms common reservoir physical parameters (porosity and permeability) into pore-throat radius parameters to enhance guidance for polymer molecular weight design, while employing a thickness-weighted permeability rush coefficient to simultaneously characterize heterogeneity impacts from both permeability and thickness variations. Unlike existing classification methods primarily designed for thin-interbedded reservoirs—which consider only connectivity or apply fuzzy mathematics-based normalization—this model specifically addresses medium-thick reservoirs’ unique challenges of interlayer development and intra-layer heterogeneity. Furthermore, its decision tree architecture clarifies classification logic and significantly reduces data preprocessing complexity. In terms of engineering practicality, the classification results are directly linked to well-group development bottlenecks, as validated in the J16 field application. By implementing customized chemical flooding formulations tailored to the study area, the production performance in the expansion zone achieved comprehensive improvement: daily oil output dropped from 332 tons to 243 tons, then recovered to 316 tons with sustained stabilization. Concurrently, recognizing that interlayer barriers were underdeveloped in certain well groups during production layer realignment, coupled with strong vertical heterogeneity posing polymer channeling risks, targeted profile modification and zonal injection were implemented prior to flooding conversion. This intervention elevated industrial replacement flooding production in the study area from 69 tons to 145 tons daily post-conversion. This framework provides a theoretical foundation for optimizing chemical flooding pilot well-group selection, scheme design, and dynamic adjustments, offering significant implications for enhancing oil recovery in medium-thick sandstone reservoirs through chemical flooding. Full article

Collaboration is essential in today’s technology-driven world, where IT professionals work in teams to solve complex problems. To mirror industry practices, universities have increasingly adopted project-based learning approaches, requiring students to work collaboratively on tasks such as software development. However, while considerable research has examined group project outcomes, little is known about the decision-making processes students use to select their partners, particularly in software development. This study, therefore, explores the factors influencing IT students’ choices of group project partners and how these choices reflect broader learning priorities. A qualitative approach was employed, collecting open-ended responses from 103 software development students through individual interviews conducted via MS Teams. Thematic analysis was used to identify recurring patterns in the data. Five main themes emerged: Personal Relationships & Familiarity, Work Ethic & Dedication, Communication & Teamwork, Reliability & Accountability, and Technical Skills & Competence. The findings indicate that students prioritise interpersonal trust, reliability, and communication skills over technical ability when selecting partners. This suggests that students view effective collaboration as grounded more in work ethic and relational qualities than in coding proficiency alone. Full article

(±)-tiaprofenic acid (TA), marketed as (Surgam^®), belongs to the family of NSAIDs, with the peculiarity of a reduced incidence of ulcer induction in rats compared with parent drugs. However, some adverse effects were observed, and better knowledge of its interaction with biologic substrates is needed. Unfortunately, unlike most commercial NSAIDs, suitable single crystals for an X-ray diffraction study could not be obtained. To fill the gap, the crystal structure of TA was solved by X-ray powder diffraction, and the molecular interactions stabilizing the structure were analyzed by Hirshfeld surface and energy framework analysis. TA crystallizes in the $P{2}_1/c$ space group, with its two enantiomers in the asymmetric unit, further confirming the peculiarity of the crystal structure and the difficulty of solving it. TA packing is characterized by alternating enantiomers connected through hydrogen bonds, forming chains, arranged in layers, stabilized by $\pi$-stacking. First principle modeling revealed several stable conformations within 4 $\mathrm{k}$$\mathrm{J}$/$\mathrm{mol}$ of the global minimum and the relaxed potential energy scans revealed modest (8 $\mathrm{k}$$\mathrm{J}$/$\mathrm{mol}$–15 $\mathrm{k}$$\mathrm{J}$/$\mathrm{mol}$) energy barriers. Such flat energy landscape suggests flexible and dynamic behavior of tiaprofenic acid in solution and in vivo conditions, with multiple suitable docking sites. Full article

Background/Objectives: The prognosis of patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) is significantly affected by inflammatory state and immune dysregulation. The systemic inflammatory response index (SIRI), which reflects neutrophil, monocyte, and lymphocyte dynamics, has emerged as a potential marker of immune-inflammatory status. However, its role in predicting HBV-ACLF outcomes remains unclear. This research aims to elucidate the prognostic value of SIRI and its dynamic changes combined with disease severity scores in predicting the outcomes of HBV-ACLF. Methods: The study included HBV-ACLF patients enrolled in a multicenter clinical study between July 2019 and April 2024. Based on 90-day outcomes, the participants were categorized into survival and death groups. Clinical data and SIRI values were collected on days 0 (baseline), 3, 7, and 14. Independent prognostic factors were identified using Cox regression and least absolute shrinkage and selection operator (LASSO) analysis. The predictive value of dynamic SIRI changes combined with disease severity scores was evaluated using receiver operating characteristic (ROC) curves. Results: A total of 153 patients with HBV-ACLF were analyzed, including 104 in the survival group and 49 in the death group. SIRI values were significantly lower in the survival group than in the death group across all time points. Multivariate Cox regression analysis identified that an increased ΔSIRI at day 3 (ΔSIRI3), a higher MELD score, and a lower albumin level were independently associated with increased 90-day mortality. The combination of SIRI on day three (SIRI3) and MELD-Na score on day three (MELD-Na3) demonstrated the highest predictive performance, with an AUC of 0.817 (95% CI: 0.750–0.883). Conclusions: The combination of the SIRI and MELD-Na score on day three provides a strong predictive value for the short-term prognosis of HBV-ACLF, highlighting its potential utility in early prognostic evaluation. Full article

Understanding the social relationships and behaviours of pet rats is important, particularly because they are comparatively understudied compared to their laboratory and wild counterparts, and little is known about their welfare. Here, open-ended interviews, with a particular focus on rat social relationships and behaviours, were conducted with 23 pet rat owners in the United Kingdom and a reflective thematic analysis was conducted on the resulting, transcribed dataset. Seven main themes were generated: Social Behaviours, Social Life and Group Dynamics, Introducing New Rats and Repairing Social Bonds, Owner Practices, Participant and Rat Contextual Background, Owner Narratives and Shared Understandings, and Owner Research Interests. Owners described rat social relationships and behaviours with a high level of consistency and reported the techniques they employ to manage the social dynamics of their rat groups, including the first scientific report of rat introductions. We propose that these qualitative findings can inform future research, including observational studies of captive (pet and non-pet) rat management and welfare. Full article

Young people under the care of child protection agencies are at increased risk of entering the criminal justice system. Residential youth organisations support young people who are unable to reside with their families or in foster care. Youth workers in these environments ensure the safety and wellbeing of young people in their care, consequently supporting the wellbeing of the overall community. This research explored the views and experiences of Queensland residential youth workers via a focus group interview. The data captured a thick description of service delivery practices. Constructivist Grounded Theory was used to conceptualise a theoretical framework based on the various empirical realities of participants. The findings highlight occasions where complex power dynamics had damaging consequences for youth workers and young people. Participants explored systemic constraints and structural inequalities, thus detailing the implications of top-down organisational structures on their service delivery, safety, and outcomes for young people. Participants were concerned about the implications of interrupted attachment and young people’s progression into crime. Practice recommendations centre around improving the disconnection between front-line realities and systemic hierarchies. Residential out-of-home care service delivery should focus on building community connection and belonging; mental, emotional and physical safety; collaborative care; and support. Full article

Marine shelled organisms exhibit diverse growth strategies shaped by species-specific traits and environmental conditions that critically influence their ecological roles, particularly within Marine Animal Forests (MAF), which are structurally complex habitats and biodiversity-rich habitats. This review compiles and compares empirical growth data for 16 bivalve and gastropod species across seven families, classified as full MAF contributors (Pinna nobilis, Flexopecten glaber, Pecten maximus, and Placopecten magellanicus), partial MAF contributors (Cerastoderma edule, C. glaucum, Chamelea gallina, Ruditapes philippinarum, Mercenaria mercenaria, Panopea generosa, Anadara kagoshimensis, A. inaequivalvis, and Tegillarca granosa), and ecologically relevant non-MAF species (Buccinum undatum, Hexaplex trunculus, and Rapana venosa). Age estimation methods included direct techniques, such as shell growth ring and opercular annulus analysis, alongside indirect approaches, such as length-frequency analysis, stable isotope profiling, and mark–recapture studies. Growth trajectories were modelled using von Bertalanffy growth function (VBGF) parameters to estimate the shell size from ages 1 to 4. Based on these estimates, species were categorised into slow, moderate, fast, and exceptional growth groups. These classifications were further explored through hierarchical clustering that grouped species according to their VBGF-derived growth values, revealing consistent and contrasting life history strategies. This comparative analysis should enhance the understanding of molluscan growth dynamics and support the conservation and management of MAF-associated ecosystems by informing restoration planning, guiding species selection, and contributing to evidence-based policy development. Full article

To evaluate the stability dynamics of typical forest plant communities in Northeast China, 57 forest plots were surveyed in 2009 and surveyed again in 2014. By adapting temporary stability (TS) as the community stability indicator, all plots were divided into three groups of low, moderate, and high stability, and the community initial state and state changes in different groups were analyzed. Results showed that the first dominant species in 15.8% (3/19) of plots was replaced by the second dominant species from 2009 to 2014 in the low stability group, but no such changes occurred in the moderate and high stability groups. The TS change amplitude was obvious in the low stability group, while that was slight in the high stability group. The relative basal area of the top two species was close in the low stability group in both 2009 and 2014, while the first dominant species was prominent in the high stability group. Communities in the high stability group had lower tree diversity, and those in the low stability group had more trees in 2009. Furthermore, tree size increased significantly in the low and moderate stability groups, and tree number decreased significantly in the moderate stability group from 2009 to 2014. The TS indicator is feasible in describing the stability state and change processes of forest plant communities on a time scale. Full article