Search Results (232)

This study investigates how university students adopt large language models (LLMs) for online consumption of sustainable products, integrating perceived value theory with the technology acceptance model (TAM). Cross-sectional survey data were analyzed using structural equation modeling (SEM) and artificial neural networks (ANNs). SEM results reveal partial mediation. Performance expectancy value (PEV) and information quality value (IQV) directly shape continue using intention (CUI). They also influence CUI indirectly through perceived ease of use (PEU) and perceived usefulness (PU). Green self-identity value (GSV) influences CUI both directly and via PEU, while trust transfer value (TTV) and green perceived value (GPV) affect CUI only via PEU. ANN findings confirm this hierarchy, as PU (86.7%) and PEU (85.7%) are the strongest predictors of CUI, followed by GSV (73.7%). Convergent evidence from both methods indicates that instrumental utility, effortless interaction, and sustainability identity congruence drive sustained LLM use in the context of online consumption of green products, whereas credibility cues and sustainability incentives play secondary roles. This study extends TAM by incorporating multidimensional value constructs and offers design recommendations for engaging and high-utility AI shopping platforms. Full article

This study examines how memorable tourism experiences (MTEs) influence tourists’ intention to recommend coastal tourism destinations. Using a quantitative approach of PLS-SEM analysis and a disjoint two-stage approach, this study examines MTE as a higher-order construct (HOC) with its seven dimensions and the moderating role of coastal destination competitiveness (CDC) in structural relationships. Data were collected through purposive sampling from 339 tourists who had visited Likupang, one of the priority tourism destinations in Indonesia. The results show that MTE plays a crucial role in increasing perceived economic value (PEV) and place attachment (PLA), and it is directly related to the intention to recommend the destination (ITRD). In addition to the prominent mediation role of PEV, these findings reveal that the CDC can strengthen or weaken the influence of these factors on tourists’ intention to provide recommendations. Specifically, the CDC can strengthen PLA influence towards intention to recommend, whereas, in contrast, it weakens the PEV in driving these intentions. The findings of this study expand the horizon of managing coastal tourism with an understanding of tourist behavior, particularly through a focus on improving MTE from the dynamics of its seven dimensions in encouraging promotion through tourist recommendations while optimizing the natural competitiveness elements of Likupang. Full article

This study reports a successful selective waste collection initiative led by UFSC’s Araranguá campus in a municipality without a recycling system. The initiative, named “Recicla UFSC Ara”, was structured around three main components: (i) the installation of color-coded bins for recyclable waste (including paper, plastic, metals, and polystyrene) and non-recyclable waste in indoor and common areas; (ii) the establishment of a Voluntary Delivery Point (PEV) to gather specific recyclable materials, such as glass, electronics waste, plastic bottles, writing instruments, and bottle caps; and (iii) the execution of periodic educational community-focused campaigns aimed at encouraging participation from both the university and the broader local community. Recyclables were manually sorted and weighed during regular collection rounds, and contamination rates were calculated. Quantitative data collected from 2022 to 2025 were analyzed using descriptive statistics and one-way ANOVA to assess waste generation and contamination trends. Gathered recyclables were directed to appropriate partner institutions, including local “Ecoponto”, non-profit organizations, and corporate recycling programs. The study also conducted a literature review of similar university-led waste management programs to identify standard practices and regional specificities, providing a comparative analysis that highlights both shared elements and distinctive contributions of the UFSC model. Results demonstrate a significant volume of waste diverted from landfills and a gradual improvement in waste disposal practices among the university community. Targeted communication and operational changes mitigated key challenges, improper disposal, and logistical issues. This case underscores the role of universities as agents of environmental education and local sustainable development. Full article

In the context of emergency management, individual or household decisions to engage in risk mitigation behaviors are widely recognized to be influenced by a benefit–cost perception (perceived applied value (PAV) vs. perceived economic value (PEV), respectively). To better understand how such decisions are made, we conducted a mail survey (N = 211) of households living in the Red River of the North Basin, North Dakota, in 2018. The survey is aimed at understanding the overall experience of households with flooding and their behavior toward advanced protective strategies against future floods by analyzing household PEV—their willingness to pay for the National Aeronautics and Space Administration’s (NASA) Satellite Enhanced Snowmelt Flood Prediction system. This paper presents a mediation model in which various predictors (flood risk, experience, flood knowledge, flood risk perception, flood preparedness, flood mitigation, and flood insurance) are analyzed in relation to the PAV of the new Satellite Enhanced Snowmelt Flood Predictions in the Red River of the North Basin, which, in turn, may shape the PEV of this product. We discuss the potential implications for both the emergency management research community and professionals regarding the application of advanced risk mitigation technologies to help protect and sustain communities across the country from floods and other natural disasters. This paper provides a greater understanding of the economic and social aspects of sustainability in the context of emergency management and community development. Full article

Galactic cosmic rays (GCRs), composed of protons and atomic nuclei, are accelerated in sources such as supernova remnants and pulsar wind nebulae, reaching energies up to the PeV range. As they propagate through the interstellar medium, their interactions with dense regions like molecular clouds produce secondary particles, including gamma-rays and neutrinos. In this study, we use the Geant4 Monte Carlo toolkit to simulate secondary particle production from GCR interactions within the Perseus molecular cloud, a nearby star-forming region. Our model incorporates realistic cloud composition, a wide range of incidence angles, and both hadronic and electromagnetic processes across a broad energy spectrum. The results highlight molecular clouds as significant sites of multi-messenger emissions and contribute to understanding the propagation of GCRs and the origin of diffuse gamma-ray and neutrino backgrounds in the Galaxy. Full article

Lorentz invariance is such a basic principle in fundamental physics that it must be constantly tested and any proposal of its violation and breakdown of CPT symmetry that might characterize some approaches to quantum gravity should be treated with care. In this review, we examine, among other scenarios, such instances in supercritical (Liouville) string theory, particularly in some brane models for “quantum foam”. Using the phenomenological formalism introduced here, we analyze the observational hints of Lorentz violation in time-of-flight lags of cosmic photons and neutrinos which fit excellently stringy space–time foam scenarios. We further demonstrate how stringent constraints from other astrophysical data, including the recent first detections of multi-TeV events in $\gamma$-ray burst 221009A and PeV cosmic photons by the Large High Altitude Air Shower Observatory (LHAASO), are satisfied in this context. Such models thus provide a unified framework for all currently observed phenomenologies of space–time symmetry breaking at Planckian scales. Full article

Thrombosis is a common complication in cancer patients, with a substantial impact on morbidity and mortality. Diffuse large B-cell lymphoma (DLBCL) and other aggressive lymphomas carry a high venous thromboembolism (VTE) risk. Extracellular vesicles (EVs) have gained attention in recent research as a new potential biomarker for VTE development. To determine the profile and association of EVs with VTE in patients with DLBCL, we conducted a prospective cohort study on 62 patients diagnosed with DLBCL. A total of 11 patients (17.7%) developed VTE. The concentrations of platelet-derived EVs (PEVs), E-selectin+ EVs, P-selectin+ EVs, tissue factor (TF)-positive/CD20+ EVs, TF−/CD19+ EVs, TF−/CD45+ EVs, and TF−/CD20+ EVs were significantly higher in DLBCL patients compared to healthy controls. In contrast, the concentration of TF− PEVs was significantly lower in DLBCL patients compared to healthy controls. No statistically significant differences were observed in the concentrations of the EV profiles among the DLBCL patients with and without VTE. Using Cox regression analysis, we found that none of the observed EV populations demonstrated an association with overall survival (OS). In conclusion, patients with DLBCL have elevated concentrations of distinct EV populations—in particular, PEVs, E-selectin EVs, P-selectin EVs, TF+/CD20+ EVs, and TF− DLBCL/B-cell EVs (CD19, CD20, CD45)—compared to healthy controls. DLBCL patients exhibit a specific EV profile, which is not significantly related to the risk of VTE and OS outcomes. Our data provide an intriguing insight into EV profiles in patients with DLBCL. Additional research is needed to elucidate these findings further. Full article

Bovine pestiviruses, namely bovine viral diarrhea virus (BVDV) and HoBi-like pestiviruses (HoBiPevs), are endemic viruses in Latin America, and the disease causes significant losses in the agricultural sector. The present review aims to perform a systematic assessment and meta-analysis of the prevalence of bovine pestiviruses in Latin America and their risk factors. Notable heterogeneity was observed in the analyzed groups, with significant prevalence variations based on age and country. However, no differences were found between temporal trends, production systems, or models. Identified risk factors included age, breed, location, reproductive practices, animal purchase, farm management, and biosecurity measures. This systematic review and meta-analysis of BVDV in Latin America provides critical insights to inform decision-making and strategic actions for disease control in the region. The high serological prevalence of bovine pestivirus across Latin America underscores the urgent need for standardized surveillance programs, biosecurity reinforcement, and targeted vaccination strategies. The presence of HoBiPev further complicates current diagnostic and control measures. Future research should focus on disease transmission dynamics, economic impact assessments, and the effectiveness of intervention programs tailored to the region’s diverse livestock production systems. Full article

Conventional general relativity supplies the notion of a vacuum tension and thus a maximum force $F_{\max }=c^4/\left(4G\right)\simeq 3·{10}^{43}$ N that is realized for a black hole. In conjunction with the Wilson area rule, we are thus led to the surface confinement of the mass of a black hole analogous to the surface confinement of quarks. The central result of our paper is that PeV scale protons can be generated on the surface of a Kerr black hole. This result is in concert with the presence at the galactic center of that Pevatron accelerating mechanism first suggested by the H.E.S.S. Collaboration and further confirmed by the HAWC Observatory. Full article

Full dependence on the main electrical grid carries risks, including high electricity costs and increased power losses due to the distance between power plants and consumers. An energy community consists of distributed generation resources and consumers within a localized area, aiming to produce electricity economically and sustainably while minimizing long-distance power transfers and promoting renewable energy integration. In this paper, a method for the optimal and sustainable operation of energy communities organized in interconnected microgrids is developed. The microgrids examined in this work consist of residential buildings, plug-in electric vehicles (PEVs), renewable energy sources (RESs), and local generators. The primary objective of this study is to minimize the operational costs of the energy community resulting from the electricity exchange with the main grid and the power production of local generators. To achieve this, microgrids efficiently share electric power, regulate local generator production, and leverage energy storage in PEVs for power management, reducing the need for traditional energy storage installation. Additionally, this work aims to achieve net-zero energy exchange with the main grid, reduce greenhouse gas (GHG) emissions, and decrease power losses in the distribution lines connecting microgrids, while adhering to numerous technical and operational constraints. Detailed simulations were conducted to prove the effectiveness of the proposed approach. Full article

Platelet extracellular vesicles (PEVs) are emerging as key biomarkers in diabetes mellitus (DM), reflecting altered platelet function and coagulation pathways. This study compares two proteomic techniques—nanoLC-MALDI-MS/MS and nanoLC-TIMS-MS/MS—for analyzing PEVs in diabetic patients, to assess their potential for biomarker discovery. PEVs were isolated from platelet-rich plasma and characterized using tunable resistive pulse sensing (TRPS), Fourier-transform infrared (FTIR) spectroscopy, and transmission electron microscopy (TEM). Proteomic analyses identified significant differences in protein expression between diabetic and non-diabetic individuals, with nanoLC-TIMS-MS/MS demonstrating superior sensitivity by detecting 97% more unique proteins than nanoLC-MALDI-MS/MS. Key differentially expressed proteins included apolipoproteins and oxidative stress markers, which may contribute to platelet dysfunction and cardiovascular complications in DM. Sex-specific variations in protein expression were also observed, highlighting potential differences in disease progression between male and female patients. The integration of advanced proteomic methodologies provides novel insights into the role of PEVs in diabetes pathophysiology, underscoring their diagnostic and therapeutic potential. These findings pave the way for improved biomarker-based strategies for early detection and monitoring of diabetic complications. Full article

The question of at which energy the transition from galactic to extra-galactic cosmic rays takes place has been a long-standing conundrum in cosmic ray physics. The sun stands out as the closest and clearest astrophysical accelerator of cosmic rays, while other objects within and beyond the galaxy remain enigmatic. It is probable that the cosmic ray spectrum and mass components from these celestial sources share similarities, offering a novel approach to study their origin. In this study, we perform joint analysis of spectra and mass in the energy range from MeV to 10 EeV, and find the following: (1) $⟨\mathrm{lnA}⟩$ demonstrates three clear peaks, tagging component transition; (2) a critical variable $\Delta$ is adopted to define the location of the transition; (3) for protons, the knee is located at ∼1.8 PeV, and the boundary between the galaxy and extra-galaxy occurs at ∼60 PeV, marked by a spectral dip; and (4) the all-particle spectrum exhibits hardening at ∼60 PeV due to the contribution of nearby galaxies, and the extra-galaxy dominates ∼0.8 EeV. We hope the LHAASO experiment can perform spectral measurements of individual species to validate these specific observations. Full article

This paper presents a blockchain-enabled Multi-Agent System (MAS) for real-time power management in Virtual Prosumer (VP) Networks, integrating Plug-in Electric Vehicles (PEVs) and Renewable Energy Sources (RESs). The proposed framework addresses critical challenges related to scalability, security, and operational efficiency by developing a hierarchical MAS architecture that optimizes the scheduling and coordination of geographically distributed PEVs and RESs. Unlike conventional business management systems, this study integrates a blockchain-based security mechanism within the MAS framework, leveraging Proof of Authority (PoA) consensus to enhance transaction security while addressing scalability and energy consumption concerns. The system further employs advanced Particle Swarm Optimization (PSO) to dynamically compute optimal power set-points, enabling adaptive and efficient energy distribution. Additionally, hierarchical aggregation of transactions at lower MAS layers enhances computational efficiency and system resilience under high-traffic and partial network failure conditions. The proposed framework is validated through large-scale simulations spanning four major cities in Greece, demonstrating its scalability, reliability, and efficiency under diverse operational scenarios. Results confirm that the system effectively balances energy supply and demand while maintaining secure and transparent transactions. Despite these advancements, practical deployment challenges remain, including synchronization delays in geographically distributed agents, legacy system integration, and blockchain energy consumption. Future research directions include investigating more advanced consensus mechanisms (e.g., Proof of Task), machine learning-driven predictive optimization, real-world large-scale testing, and federated learning models for decentralized decision-making. The proposed framework offers a scalable, secure, and efficient solution for decentralized real-time energy management in Virtual Prosumer Networks. Full article

Eosinophilic esophagitis (EoE) is a chronic inflammatory esophageal disorder. The lack of non-invasive biomarkers currently results in dependency on endoscopy with biopsies for its diagnosis and monitoring. We aimed to identify potential non-invasive biomarkers using microRNAs (miRNAs) in plasma-derived extracellular vesicles (pEVs). This was a prospective single-center observational study of a discovery cohort of EoE patients (n = 26) with active disease (EoE.Basal) and after anti-inflammatory treatment (EoE.Post.tx) and control subjects (n = 16). Small-RNA-seq was performed to identify differentially regulated small RNAs (sRNAs). Candidate miRNAs were validated in an independent cohort (EoE patients, n = 33; controls, n = 14). The pEVs-sRNA cargo differed among conditions. Compared with controls, Ser_Comb_22, Leu_Comb_5, miR-10b-5p, and miR-125a-5p were upregulated in EoE.Basal, and miR-224-5p, miR-221-3p, let-7d-5p, and miR-191-5p were downregulated. The combination of miR-221-3p and miR-10b-5p showed the best diagnostic performance. Comparing paired EoE samples, miR-374a-5p and miR-30a-3p were upregulated in EoE.Basal, while miR-15a-5p and let-7d-5p were downregulated. Combined miR-30a-3p and miR-15a-5p showed the best AUC values, and miR-30a-3p alone was best as a monitoring biomarker (p = 0.001). In conclusion, pEVs-sRNA changed upon inflammation in EoE patients, and miR-30a-3p was proposed as a potential biomarker for monitoring the treatment. This study was the first to explore the use of pEVs as a non-invasive biomarker for EoE. Full article

The global energy crisis and the pursuit of carbon neutrality have introduced significant challenges to the optimal dispatch of power systems. Despite advancements in optimization techniques, existing methods often struggle to efficiently handle the uncertainties introduced by renewable energy sources and the dynamic behavior of plug-in electric vehicles (PEVs). This study presents a multi-energy collaborative optimization approach based on a dynamic opposite level-based learning optimization swarm algorithm (DO3LSO). The methodology explores the impact of integrating PEVs and renewable energy sources, including photovoltaic and wind power, on unit commitment (UC) problems. By incorporating the bidirectional charging and discharging capabilities of PEVs and addressing the volatility of renewable energy, the proposed method demonstrates the ability to reduce reliance on traditional fossil fuel power generation, decrease carbon emissions, stabilize power output, and achieve a 7.01% reduction in costs. Comparative analysis with other optimization algorithms highlights the effectiveness of DO3LSO in achieving rapid convergence and precise optimization through hierarchical learning and dynamic opposite strategies, showcasing superior adaptability in complex load scenarios. The findings underscore the importance of multi-energy collaborative optimization as a pivotal solution for addressing the energy crisis, facilitating low-carbon transitions, and providing essential support for the development of intelligent and sustainable power systems. Full article