Search Results (443)

Sports non-fungible tokens (NFTs) have rapidly emerged as tradable digital goods within platform-mediated marketplaces, reshaping how sports organizations, athletes, and brands design fan experiences and monetize digital assets. To consolidate fragmented scholarship and clarify the concept space, this study conducts a systematic quantitative literature review combined with thematic analysis, following PRISMA 2020 and a SPIDER-guided review logic. Searches across six major databases (Web of Science, Scopus, ScienceDirect, PubMed, IEEE Xplore, ProQuest) plus Google Scholar (2017–March 2025) yielded 40 peer-reviewed studies that met predefined inclusion criteria and passed quality appraisal. Results show a sharp growth of sports-NFT research from 2021 to 2024, with strong inter-disciplinary convergence spanning sports marketing, information systems, computer science, and law. Integrating findings through a consumer-value lens, we inductively propose a five-type taxonomy—collectible, empowerment, identity/authentication, physical-asset linked, and virtual-interaction NFTs—each associated with distinct value mechanisms and e-commerce functionalities. The thematic synthesis further identifies four dominant research streams (industry digitalization, consumer psychology/behavior, legal–regulatory issues, and digital marketing), while revealing gaps in theory operationalization, method diversity (e.g., limited experiments/longitudinal designs), cross-context generalizability, and governance/sustainability. The study contributes to marketing and management scholarship by positioning sports NFTs as emerging technologies that reorganize customer engagement, brand-community building, and governance in platform-mediated sport markets, and it offers a research agenda for measuring consumer, brand, and organizational effects. Full article

In vertical farming systems, defining suitable lighting strategies is essential for improving crop productivity and product quality under controlled environmental conditions. This study evaluated the effects of four LED lighting configurations differing in spectral composition and lamp-to-canopy distance on the growth and selected quality traits of arugula (Eruca sativa Mill.) grown in a vertical nutrient film technique (NFT) system. Two light spectra were tested: white LED light and a red–blue LED combination, each applied at two distances from the crop canopy (20 and 40 cm). Two experiments were conducted in 2025 in a climate-controlled cultivation unit, and agronomic and quality-related variables were assessed at harvest, including fresh biomass, leaf development, total polyphenols, antioxidant capacity, chlorophyll index, and nitrate concentration. The LW20 treatment, representing a specific combination of white LED lighting, lamp-to-canopy distance, PPFD, and DLI, was associated with the highest fresh biomass, reaching 42.6 g plant⁻¹ in Experiment 1 and 70.9 g plant⁻¹ in Experiment 2, and with the highest total polyphenol content (38.4 mg GAE 100 g⁻¹ FW). In contrast, the red–blue treatments were associated with lower biomass production, while the RB20 treatment showed the lowest polyphenol concentration (26.2 mg GAE 100 g⁻¹ FW). Among the evaluated quality-related parameters, total polyphenols showed the clearest response to lighting conditions, whereas antioxidant capacity, chlorophyll index, and nitrate concentration were not significantly affected. Under the evaluated conditions, LW20 was the most favorable among the four tested lighting configurations for fresh biomass production and total polyphenol accumulation. However, this response should not be interpreted as evidence of white light superiority alone, because spectral composition, lamp-to-canopy distance, PPFD, and DLI were not independently controlled. Full article

Social media platforms such as X (formerly Twitter) increasingly shape attention formation, market visibility, and value signaling in electronic commerce, particularly in emerging digital asset markets such as Non-Fungible Tokens (NFTs). Prior work shows that social engagement correlates with NFT prices, suggesting its potential for valuation support. However, open social platforms exhibit heterogeneous user credibility, automated activity, and coordinated promotion, which can distort engagement-based inference. To address these challenges, we propose NFT-TRUST, a trust-aware social signal modeling framework that transforms raw engagement into credibility- and integrity-aware indicators for robust valuation support under manipulation-prone conditions. The framework integrates three components: (i) Credibility-Weighted Social Signal Aggregation (CW-SSA), (ii) Engagement Disproportionality Detection (EDD), and (iii) Integrity-Aware Signal Attenuation (IASA), which jointly reduce the influence of unreliable or manipulated signals while preserving informative engagement. Rather than estimating intrinsic NFT value from social signals alone, NFT-TRUST evaluates the reliability of social attention and converts it into trust-aware features. An XGBoost-based model is used to capture non-linear interactions among these features. Robustness is assessed through stress testing with RL-TweetGen-ST, a reinforcement learning–based synthetic tweet generator that simulates controlled engagement inflation. Experimental results show that NFT-TRUST achieves competitive predictive performance while demonstrating improved stability under simulated manipulation. Ablation analysis indicates that credibility and integrity components are complementary and jointly enhance the reliability of social-signal-based inference. Overall, this work advances trust-aware analytics in electronic commerce and supports more reliable social-driven valuation in emerging digital markets. Full article

This paper proposes a high-precision theoretical and computational neurorehabilitation framework for Mild Cognitive Impairment (MCI), connecting computational neuroscience and clinical practice through qEEG-guided neurofeedback training (NFT). By employing sLORETA to identify putative pathological nodes within the Default Mode Network (DMN)—specifically the Precuneus and the Posterior Cingulate—the model utilizes spectral decomposition to isolate the aperiodic 1/f component, reducing background noise bias and allowing the calculation of a pure individual alpha frequency (IAF) to inform recalibration of Weber’s Cognitive Threshold. The core architecture uses Bayesian algorithms and stochastic modeling to drive a Dynamic Weight Change mechanism. To support Long-Term Potentiation (LTP) and Hebbian learning, reward thresholds are modulated in real time to target a 70% success rate, as a strategic rationale to anticipate neural fatigue while maintaining the Reward Prediction Error required for synaptic strengthening. As a prospective validation pathway, future studies may assess clinical value through changes in MoCA and RAVLT scores, as well as by examining normalization of cortical coherence in the Default Mode Network (DMN). By merging computational neuroscience with biological models of synaptic plasticity, this work outlines how individual biology can be mapped into an explicit mathematical model. The proposed framework may inform an individualized protocol that provides an objective model-based measure of cognitive recovery, suggesting a replicable and robust strategy for neurorehabilitation during the prodromal phase of dementia, and providing a new approach to neuroscience-based cognitive rehabilitation. This work is intended as a theoretical and computational framework; no complete empirical dataset is reported in the present manuscript. Full article

Agricultural greenhouse gas (GHG) fluxes are often measured using chamber-based methods. However, comparisons among chamber-based methods are limited. This study compared the effects of chamber type and GHG concentration measurement method on GHG fluxes, emissions, global warming potential (GWP), and reduced two-gas GWP (GWP*) in conventionally tilled soybean (Glycine max L. [Merr]) on a silt-loam soil (Aeric Epiaqualfs) in southeast Arkansas. Carbon dioxide (CO₂) fluxes measured by optical feedback-cavity enhanced absorption spectroscopy (OF-CEAS, FT-LICOR) were greater (p < 0.01) than from the non-steady-state, non-flow-through, static, closed-chamber method analyzed by gas chromatography (NFT-GC), while methane (CH₄) and nitrous oxide (N₂O) fluxes were greater (p < 0.01) from the NFT-GC than the FT-LICOR method. Cumulative season-long CO₂ emissions were 36.2, 31.6, and 13.7 times greater (p < 0.01) from the FT-LICOR than the NFT-GC method for 0–15, 0–30, and 0–60 min gas sampling intervals, respectively. Methane N₂O emissions and GWP* did not differ (p > 0.05) between FT-LICOR and NFT-GC methods for the 0–15, 0–30, and 0–60 min intervals. Results suggest that differences in GHG flux, emissions, and GWP estimates reflect the combined influence of measurement methods rather than individual system components (i.e., chamber design, analyzer type, or closure time), which should be considered when designing and executing field studies. Full article

Non-Fungible Tokens (NFTs) are unique digital assets stored on a blockchain that certify ownership of an item, giving rise to NFT art, where digital creations are tokenized to provide verifiable scarcity and provenance. To clarify the polarized debate surrounding this phenomenon, this paper conducts a systematic literature review of 18 academic articles (2020–2025) to synthesize the current state of research on its aesthetics. The review first maps the field’s methodological and typological landscape, and then presents three core thematic findings: the reconfiguration of value from intrinsic visual merit to social factors like community and identity; the evolution of the artist’s role from creator to system designer and community manager; and the adaptation of traditional art world frameworks. The study’s primary contribution is the articulation of a new theoretical framework, “decentralized aesthetics,” which posits that the value of NFT art is derived from the holistic, participatory experience it generates across perceptual, cognitive, emotional, and socio-cultural dimensions, rather than from its isolated visual properties. Finally, the paper identifies critical research gaps, such as a lack of longitudinal and cross-cultural studies, and proposes an agenda for future inquiry into digital creativity and ownership. Full article

This paper develops a tractable theoretical framework to study how network participation shapes the boom–bust dynamics of non-fungible token (NFT) prices. We model NFT pricing under network effects and heterogeneous consumers, and show that prices and participation are jointly determined in equilibrium. The model implies a critical participation threshold that separates expansion from contraction regimes: above this threshold, positive feedback between participation and valuation generates self-reinforcing growth, while below it, weakening network benefits lead to contraction. We provide empirical evidence using data from the aggregate NFT market and prominent collections including Bored Ape Yacht Club (BAYC) and CryptoPunks. Reduced-form regressions show a positive association between prices and network participation, with stronger effects at the collection level than in the aggregate market. Threshold estimation further provides evidence consistent with regime-dependent dynamics, with clearer tipping behaviour in well-defined NFT communities than in the aggregate market. These findings suggest that NFT valuation is closely tied to network structure and participation dynamics. More broadly, this paper contributes a unified framework that links participation, price formation, and threshold behaviour in NFT markets. Full article

The incorporation of the Internet of Things (IoT) in indoor agricultural systems has become an essential tool for monitoring and analyzing environmental variables, contributing to more efficient decision-making. This article presents the design and implementation of an IoT-based digital agriculture system applied to a Plant Factory (PF) for hydroponic vegetable cultivation using the Nutrient Film Technique (NFT). The objective of this study was to develop a system capable of effectively monitoring and controlling the environmental variables that directly influence the microclimate of a closed agricultural environment. The proposed system integrates a four-layer IoT architecture based on a MODBUS RS-485 communication bus, which allows for continuous data acquisition and the operation of multiple sensors and controlled devices. Additionally, user-oriented tools such as a human–machine interface (HMI), a web application, a mobile application and an automatic alert module were incorporated, enhancing accessibility and remote supervision. Experimental results showed stable control performance of ambient temperature (TA), relative humidity (RH), photoperiod, and photosynthetic photon flux density (PPFD), along with continuous monitoring of CO₂ concentration. A 30-day validation experiment using Swiss chard (Beta vulgaris L. var. cicla) under controlled conditions was conducted. The results showed progressive plant development, with leaf area increasing from 15.17 cm² to 690.39 cm², plant height from 7 cm to 31 cm, fresh weight from 23 g to 171 g, and the number of leaves from 9 to 20. These results support the functional validity of the proposed system as a reliable platform for environmental monitoring and control in controlled-environment agriculture. Full article

Excessive nitrate accumulation in leafy vegetables presents significant health risks, requiring sustainable strategies to optimize yield while minimizing nitrogen-related anti-nutritional factors in controlled environments. This study investigated the effects of varying LED light intensities 236.9 µmol·m⁻²·s⁻¹ (high), 189.8 µmol·m⁻²·s⁻¹ (medium), and 117.6 µmol·m⁻²·s⁻¹ (low) on nitrates (NO₃⁻) dynamics, growth, and biochemical composition in two Lollo Rossa lettuce cultivars, Carmesi and Carnelian, grown in NFT hydroponic systems. Conducted under constant temperature (20/18 °C day/night) and CO₂ (625 µmol·mol⁻¹) to isolate light’s influence, the experiment used a replicated design with three replicates per treatment, each including two cultivars. Morphological traits (plant height, rosette diameter, leaf number, biomass, root development) and biochemical parameters (nitrate and sugar contents) were assessed via mean comparisons, trends, and correlations. Results demonstrated that higher light intensity significantly suppressed nitrate accumulation in lettuce through enhanced assimilation and dilution effects linked to increased growth. Nitrate levels dropped to 2091.67 mg kg⁻¹ from 2443.33 mg kg⁻¹ in Carmesi and 2013.33 mg kg⁻¹ from 2515.00 mg kg⁻¹ in Carnelian. Negative correlations were observed between nitrate content and growth parameters: nitrates vs. fresh biomass (r = −0.89); nitrates vs. plant height (r = −0.79). Concurrently, it boosted carbohydrate content (Carmesi: 3.03 °Brix; Carnelian: 3.08 °Brix) and promoted vigorous growth, with Carmesi achieving superior metrics under high light (height: 22.12 cm, rosette diameter: 29.87 cm, fresh biomass: 206.88 g, root biomass: 19.58 g) compared to low light (17.45 cm height, 183.42 g biomass). Carnelian exhibited similar trends but prioritized root elongation. These findings underscore light’s role in regulating nitrate transporters and assimilation enzymes (e.g., nitrate reductase), offering a low-cost approach to reduce nitrate risks, enhance nutritional quality, and improve yield in controlled horticultural systems (CHS). Full article

Non-fungible tokens (NFTs) are transforming the commercialisation of digital art by establishing unique blockchain identifiers that ensure authenticity and certify subsequent transactions. However, the transfer of control over an NFT does not automatically include the transfer of the associated copyrights, thereby creating legal uncertainty as to what rights are actually acquired. This interdisciplinary project between engineering and law proposes the design of a smart contract, based on the ERC-721 standard, to manage the transfer of property rights linked to digital artworks represented as NFTs. The accompanying legal contract incorporates essential clauses covering the identification of the parties, a description of the artwork and its link to the token, pricing, royalties, and the terms of rights transfer. The proposal seeks to integrate blockchain technology with existing legal frameworks, offering an innovative solution that strengthens legal certainty in the transfer of copyright within digital environments. Full article

Existing approaches mainly characterize connectedness in four dimensions: node size, direction, spillover magnitude between nodes, and time variation. However, the sign of spillovers has not been explicitly incorporated into the analysis. To address this limitation, this paper introduces sign as a fifth dimension and constructs a five-dimensional signed network-topology framework based on BVAR historical decomposition. The framework is used to examine the evolution of spillover signs and to explore the multidimensional spillover effects among the cryptocurrency, NFT, and foreign exchange markets. The results show that the signed spillovers across these three markets vary over time during the sample period. On average, DXY exerts negative spillover effects on the cryptocurrency market, while ETH exerts more pronounced negative spillover effects on the NFT market. Furthermore, during the COVID-19 pandemic and the cryptocurrency crash period, BTC shifted from a net receiver of risk spillovers to a net transmitter. In terms of sign, spillover magnitudes vary relatively little across periods, whereas sign reversals occur more frequently. Full article

Controlled environment agriculture (CEA) relies on hydroponic systems to achieve high yields, yet optimizing plant performance remains a challenge. Beneficial endophytic bacteria offer a sustainable solution by promoting growth and nutrient uptake. Here, we investigated the mechanistic basis of growth enhancement in lettuce (Lactuca sativa) inoculated with Pseudomonas psychrotolerans IALR632 in a nutrient film technique (NFT) system. Growth measurements showed significant increases in shoot and root biomass and leaf greenness. RNA-seq profiling at 4, 10, and 15 days after transplanting revealed dynamic transcriptional reprogramming, with 38, 796, and 7642 differentially expressed genes, respectively. MapMan and GO analyses indicated up-regulation of pathways related to cell wall remodeling, lipid metabolism, nitrogen assimilation, and stress adaptation, alongside modulation of ethylene signaling. Root bacterial microbiome through 16S metabarcoding sequencing demonstrated distinct community shifts, confirmed by analysis of similarity (ANOSIM) (R = 1, p = 0.028), with enrichment of genera linked to nutrient cycling and plant growth promotion. These findings provide integrated molecular and ecological evidence that IALR632 enhances lettuce growth by coordinating host gene expression and rhizobiome restructuring, offering a mechanistic framework for microbial inoculant strategies in hydroponic horticulture. Full article

In this study, we propose a structured valuation framework for non-fungible tokens (NFTs), a distinct class of digital assets whose pricing mechanisms remain insufficiently understood. Based on previous empirical studies and illustrative case analyses of three major NFT collections, we synthesize insights from non-cash-flow asset theory, market microstructure, and behavioral finance to construct a four-layer valuation framework consisting of the Asset, Market, Technology, and Ecosystem layers. We identify three NFT-specific mechanisms—verified digital scarcity, pseudonymous signaling, and on-chain herding—that modify or extend traditional valuation paradigms. Empirical evidence from the literature suggests that rarity-driven asset features and social-influence dynamics are dominant price determinants, while wash trading, fragmented liquidity, and platform incentive structures generate persistent distortions in price discovery. Case analyses of CryptoPunks, Bored Ape Yacht Club, and Pudgy Penguins demonstrate how differing risk exposures across the four layers translate into distinct valuation trajectories. With this framework, we obtain a basis for improved risk assessment, regulatory oversight, and business model design in NFT markets. Full article

Mastitis in dairy cows, caused by pathogens such as Staphylococcus aureus, Escherichia coli, and Candida albicans, leads to substantial economic losses and contributes to antimicrobial resistance, emphasizing the need for natural alternatives. This study assessed the phytochemical composition, antioxidant activity, and in vitro antimicrobial effects of ethanol extracts from ten medicinal plants, including Populus balsamifera buds, Syzygium aromaticum, and Humulus lupulus, as well as two multi-component plant mixtures and commercial products against reference strains and field isolates of mastitis pathogens. Extracts exhibited total phenolic contents ranging from 2.5 to 43.0 mg GE/g, with Populus balsamifera and Syzygium aromaticum demonstrating the strongest DPPH radical scavenging activity (IC₅₀ 1.89–2.9 mg/g extract). Disc diffusion assays demonstrated broad-spectrum inhibition, particularly for Populus balsamifera (15.1–19.1 mm inhibition zones) and Humulus lupulus (9.0–18.4 mm) against key pathogens; phenolic and flavonoid contents positively correlated with antimicrobial activity (r = 0.63–0.99, p < 0.001). Multi-component mixtures provided consistent broad-spectrum effects (12.6–17.2 mm). These phenolic-rich plant extracts represent promising alternatives to reduce antibiotic use in dairy mastitis management. Full article

To address the engineering problems of high cement content, high brittleness, and weak frost resistance of cement-improved loess in the seasonal frozen soil area of Northwest China, F1 ion curing agent (F1) and cement composite improved loess (FCIL) were used in this paper. Through unconfined compressive (UC) strength tests, consolidated undrained (CU) triaxial shear tests, and microscopic pore characteristics analysis, the mechanical properties, freeze–thaw cycle deterioration law, and microscopic pore structure of FCIL were studied. The effects of cement content (C_c), F1 dosage (C_F), number of freeze–thaw cycles (N_F-T), and confining pressure (σ₃) on the strength, deformation behavior, and pore characteristics of FCIL were analyzed. The synergistic improvement mechanism of FCIL, as well as the freeze–thaw damage mechanism, was elucidated. The results show that C_c is the primary factor controlling the strength of improved loess. The incorporation of F1 can further increase UCS and markedly enhance the failure strain (ε_f), thereby achieving simultaneous improvements in strength and ductility. An appropriate mix proportion was identified as C_F = 0.2 L/m³ and C_c = 6%. After 7 d curing, FCIL exhibited a UCS of 1.35 MPa, a cohesion (c) of 205 kPa, an internal friction angle (φ) of 36.2°, and ε_f 1.8 times that of loess improved with C_c = 6% cement alone. CU triaxial shear tests indicate that, under all tested conditions, the stress–strain responses of FCIL exhibit σ3-sensitive strain-softening behavior. As C_c and σ₃ increase, triaxial peak strength (q_max) and secant modulus (E₅₀) increase significantly. Compared with natural loess (NL), FCIL shows a markedly lower porosity (n), a substantial increase in the proportion of micropores, and reductions in medium and small pores. After multiple freeze–thaw cycles, the evolution of the pore structure is effectively restrained. This indicates that the combined use of F1 and cement promotes the formation of a dense layered stacking structure, significantly improves the microscopic pore-size distribution, and enhances the mechanical performance of loess under freeze–thaw environments. Full article