Search Results (367)

Salinity is a critical environmental stressor that inhibits seed germination and seedling growth globally. This study aimed to determine the optimal priming conditions for hot pepper (Capsicum annuum L.) seeds to alleviate salt stress-induced germination and growth reductions. Priming treatments included hydro-priming, chemical-priming (24-epibrassinolide (EBL), sodium nitroprusside (SNP), and polyamines), halo-priming (KNO₃), and modified drum-priming. Following treatment, germination characteristics, total polyphenol content (TPC), ABTS⁺ radical scavenging activity, and seedling growth traits were evaluated under 100 mM NaCl stress. Optimal conditions were identified as hydro-priming (50 h), chemical-priming (10⁻⁶ M EBL, 10⁻⁴ M SNP, 50 mM putrescine), halo-priming (300 mM KNO₃), and drum-priming (20 h hydration and 60 h incubation). Although NaCl treatment significantly reduced all germination traits, priming effectively mitigated these declines. A modified drum-priming method resulted in the shortest mean germination time (MGT) of 4.0 days, the highest germination rate (GR) of 25.2%·day⁻¹, and a 94% healthy seedling percentage (HSP), whereas the results for the untreated control were recorded as 6.6 days, 15.2%·day⁻¹, and 66%, respectively, under stress conditions. EBL and drum-priming showed the highest TPC and ABTS⁺ radical scavenging activity. Furthermore, priming prevented salt-induced reductions in seedling growth. EBL and drum-priming treatments resulted in the highest vitality index (VI). These results indicate that drum-priming and EBL priming are highly effective strategies for enhancing salt tolerance and ensuring uniform stand establishment in pepper seeds. Full article

Super oxidized water is a disinfectant generated by electrolysis whose effectiveness depends mainly on oxidation–reduction potential and pH. In this study, a 2² factorial Design of Experiments was applied to evaluate the influence of applied potential (8.2–12.2 V) and NaCl concentration (0.05–0.25 wt.%) on the redox properties of SOW, aiming to produce solutions with targeted disinfection profiles. The obtained models showed excellent predictive capacity (R² > 0.99), identifying NaCl concentration as the most influential factor affecting both oxidation–reduction potential and pH. The system enabled the controlled generation of SOW with ORP values ranging from approximately 950 to 1100 mV and pH between ~3.8 and 5.0, with experimental errors below 1.5%. Stability tests demonstrated that oxidation–reduction potential and pH remained within ±25 mV and ±0.15 units, respectively, over 24 weeks of storage. Microbiological evaluation revealed effective antimicrobial activity against Escherichia coli, Staphylococcus aureus, methicillin-resistant Staphylococcus aureus, and Candida albicans, with inhibition halos of up to ~5 mm depending on ORP and microorganism. The results demonstrate that Design of Experiments enables precise adjustment of SOW redox properties, allowing optimization of antimicrobial performance for specific applications. This positions super oxidized water as a flexible, stable, and scalable disinfection technology for industrial and clinical use. Full article

Despite decades of methodological sophistication, research on sustainable food behavior remains critically limited in predicting actual purchases. This study aims to examine how methodological fragmentation across psychometric, econometric, and behavioral approaches affects the predictive validity of sustainable food choice and purchasing behavior. This integrative systematic review of 62 empirical studies across psychometric validation, discrete choice experiments (DCEs), trust and cognitive biases, and objective behavioral measurement diagnoses the structural disarticulation between these traditions as the primary cause of limited predictive validity. Findings reveal a pronounced inversion of the evidence hierarchy: while self-report studies report moderate attitude–behavior correlations (β ≈ 0.40–0.50, self-report), the only long-term study using objective scanner data demonstrates that this relationship collapses to a virtually null effect (β = 0.022), representing a 95.6% decay in predictive capacity. Psychometric instruments demonstrate strong structural validity but lack ecological validation against actual purchases. DCEs have evolved econometrically (from MNL to GMNL models), yet remain isolated from psychological theory and real-world validation. Critically, no reviewed study integrated validated scales, a DCE, and objective behavioral data within a single design. Key moderators—skepticism, halo effects, and affective heuristics—are systematically underoperationalized. To overcome this impasse, we propose Hybrid Choice Models (HCM) as the central tool to formally articulate latent attitudes, stated preferences, and observed behavior, enabling cumulative evidence to inform policy and market strategies with greater predictive accuracy. These findings indicate that predictive advances depend on integrating measurement paradigms to achieve ecologically valid and policy-relevant models of sustainable consumer behavior. Full article

Introduction: Three-dimensional (3D) bioprinting is a promising approach for endodontic tissue engineering, enabling scaffolds with controlled architecture and bioactivity to support pulp regeneration. Objectives: This systematic review assessed the following: “What 3D bioprinting applications are reported in endodontics-related studies?” Materials and Methods: Following PRISMA 2020 guidelines, PubMed/MEDLINE, Scopus, Embase, Cochrane Library, Web of Science, SciELO, LILACS, and Google Scholar were searched up to January 2026 with no date or language limits. Two reviewers independently screened studies; risk of bias in in vitro studies was assessed with the QUIN tool. As only one study reported complete antimicrobial outcomes, an intra-study quantitative comparison (MD, 95% CI) of inhibition halos was performed (not a meta-analysis). Results: From 518 records, nine studies were included. Outcomes mainly addressed physicochemical properties (n = 9), cell viability (n = 7), biocompatibility (n = 5), and cell differentiation (n = 5); antimicrobial activity was evaluated in two studies. Most used hDPSCs and extrusion-based printing, testing calcium silicate composites, alginate hydrogels, functionalized PCL, and modified PLA. Modified PLA scaffolds showed greater antimicrobial activity, strongest with naringin and nHA formulations. Overall risk of bias was moderate (58.33%), largely due to limited reporting of randomization, blinding, and sampling. Conclusion: 3D-bioprinted scaffolds/bioinks generally improved cellular responses and bioactivity, especially with MTA, Biodentine, nHA, or naringin; antimicrobial effects were most evident in functionalized PLA (PLA/NAR and PLA/nHA/NAR). Full article

The electric fields generated by lightning discharges propagate upward and couple with the lower ionosphere, triggering various mesospheric optical emissions. The potential role of local terrain in modulating the lightning-generated electric fields in the lower ionosphere remains poorly understood. To investigate the effect of mountain terrain on the lightning-generated electric fields at high altitudes (70–85 km), a two-dimensional (2D) finite-difference time-domain (FDTD) simulation model was developed. The simplified mountain is parameterized by its height, width, and horizontal distance from the lightning channel. Simulation results show that mountain terrain significantly influences the lightning-driven electric field waveforms in the initiation region of sprite halos. Increased mountain height leads to greater attenuation of the high-altitude electric field amplitudes, thereby suppressing sprite halos initiation. The shielding effect of mountain width on the electric fields is less pronounced than that of mountain height, and it stabilizes when the width exceeds 40 km. When the horizontal distance between the mountain and lightning channel is less than 40 km, the electric field attenuation increases significantly with decreasing distance. The attenuation effect gradually weakens beyond a distance of 40 km, yet the electric field waveforms exhibit considerable fluctuations due to the reflection process. Full article

Drunken horse grass (Achnatherum inebrians) plays a vital role in ecological restoration and grassland sustainability in Northwest China, but its ecological functions are increasingly threatened by emerging fungal diseases. In 2024, a leaf spot disease characterized by brown lesions with yellow halos was observed on drunken horse grass in Gansu Province, China. The causal pathogens were identified as Alternaria alternata and Alternaria infectoria based on morphological characterization, pathogenicity tests, and multi-locus phylogenetic analysis (ITS, TEF, GPD, RPB2, Alt a 1, endoPG, and OPA10-2). Preliminary fungicide sensitivity assays revealed that tetramycin and difenoconazole had the strongest inhibitory effects against mycelial growth in vitro. The EC₅₀ values for tetramycin were 0.0755 mg/L (A. alternata) and 0.2175 mg/L (A. infectoria), while for difenoconazole, they were 0.1023 mg/L (A. alternata) and 0.0599 mg/L (A. infectoria). To our knowledge, this is the first report of Alternaria species infecting the host plant, drunken horse grass, providing an essential basis for the effective management of this disease and the protection of grassland ecosystems. Full article

Standard Retinex-based algorithms typically rely on gradient constraints to decompose an image, assuming that illumination is spatially smooth while reflectance contains sharp details. However, strictly gradient-based priors frequently produce halo artifacts or over-smoothing because they are unable to differentiate between intrinsic structural edges and high-frequency noise. In this paper, we propose a novel Similarity Image-Guided Retinex (SIMRET) model that fundamentally diverges from traditional derivative-based regularization. We present a color-based pixel-level similarity analysis to build a global guidance matrix rather than merely depending on local gradients. This Similarity Image functions as a reliable weight map during the decomposition process by mathematically encoding the chromatic relationships and spatial coherence between pixels. The model strictly maintains consistency across structural boundaries to avoid halo effects while adaptively enforcing smoothness in homogeneous regions to suppress noise by incorporating this similarity guidance into the optimization objective. We solve the proposed SIMRET model using an alternating optimization framework, where the similarity constraints effectively regularize the ill-posed decomposition problem. Extensive tests on various low-light datasets show that the suggested model successfully overcomes the trade-off between noise reduction and detail preservation, achieving better visual naturalness and signal fidelity than state-of-the-art techniques. Full article

Chryseobacterium indologenes MA9 is a causative agent of root rot disease in Panax notoginseng (P. notoginseng), with its high incidence being a major manifestation of continuous cropping barriers, severely hindering the sustainable development of the P. notoginseng industry. In this study, a novel lytic bacteriophage, MA9V-3, was isolated from wastewater, targeting C. indologenes MA9. The phage produced clear plaques, ranging from 1 to 3 mm in diameter, with a surrounding halo. Phage MA9V-3 achieved an adsorption rate of up to 80% after 30 min of contact with C. indologenes MA9, a latent period of approximately 40 min, and an average burst-size if 160 PFU/cell. Transmission electron microscopy revealed that phage MA9V-3 possesses an icosahedral head and a contractile tail, exhibiting a typical myovirus-like morphology. According to the latest ICTV taxonomy, MA9V-3 belongs to the class Caudoviricetes, and the phage’s biocontrol efficacy and inhibitory capacity were evaluated at different multiplicity of infection (MOI s). The results showed that the highest titer recorded at 1.6 × 10¹⁰ PFU/mL. Whole-genome sequencing revealed that MA9V-3 is a double-stranded circular DNA virus, with a genome length of 103,203 bp, GC content of 34.29%, and 150 open reading frames (ORFs), one of which is related to tRNA. Only 13 of these ORFs encode known functional sequences, likely due to the limited available gene data for such phages in the database, with additional details on hypothetical proteins yet to be uncovered. Comparative database analysis confirmed that the phage genome contains no antibiotic resistance or toxin-related genes. Phage therapy experiments were performed using MA9V-3 and two other phages screened in our laboratory. The experimental results showed that phage MA9V-3 may be a potential candidate for effectively controlling the infection of Panax notoginseng by C. indologenes MA9, and offering valuable insights into the potential application of phage therapy for managing bacterial plant diseases. Full article

Background/Objectives: The aim of the current study was to investigate the mechanistic hepatoprotective efficacy of selenium (SE) and chitosan-coated selenium nanoparticles (CS-SENPs) using a rat model induced by lipopolysaccharide (LPS). Methods: CS-SENP was prepared and characterized for particle size, polydispersity index (PDI), zeta potential, transmission electron microscope (TEM), and Fourier transform infrared spectroscopy (FTIR). Male albino rats (n = 40) were divided into four groups: control, LPS, SE, and CS-SENP. SE and CS-SENPs (5 mg/kg orally for 14 days) were given before LPS injection. Tissue architecture was assessed using histopathological analysis. HSP-47 and STEAP-3 protein expression levels were measured using ELISA, and oxidative stress markers were quantitatively evaluated. The expression of HO-1, TLR-4, STAT-3, TRAF-6, and IL-17A was measured using immunohistochemical analysis. Furthermore, HSP-90 expression was evaluated by immunofluorescence labeling. Results: CS-SENP characterization revealed uniform (PDI = 0.125 ± 0.04) nanoparticle size (108.54 ± 2.24 nm), with high zeta potential (+63.92 ± 6.287 mV), attributed to the CS layer, which was confirmed by FTIR and TEM as an electron-lucent halo enveloping the individual SENP cores. CS-SENPs significantly reduced lipid peroxidation (MDA) and restored glutathione (GSH) more effectively than SE. CS-SENPs improved redox (upregulated HO-1) and iron balance (downregulated STEAP-3), and also increased the anti-inflammatory effect (suppressed TLR-4, IL-17A, TRAF-6, and STAT-3). CS-SENPs showed superior antifibrotic efficacy (suppresses stress proteins, HSP-47 and HSP-90). Rats treated with CS-SENPs had nearly normal liver structure. Conclusions: The results concluded that CS-SENPs had superior and multi-targeted hepatoprotection against LPS-induced liver damage. Full article

Present-day artificial intelligence systems (AI), virtual assistants, and devices connected to the Internet of Things (IoT) are playing an increasingly important role in decision-making processes in the everyday lives of individuals and daily operations of organizations. In this respect, the users’ trust is a key factor determining their acceptance and effective use. In contemporary digital ecosystems, this trust increasingly becomes a component of sustainable digital marketing, in which transparent data practices and responsible communication shape long-term consumer–technology relationships. This paper analyzes the halo effect as a psychological mechanism affecting the perception of competences, reliability, and ethics in the case of technologies based on AI. Based on the literature on behavioral economics, it was shown how positive associations with the interface, brand, or previous experience of the user may lead to excessive trust in technology. Such mechanisms also play a significant role in shaping sustainable consumption patterns, as users—guided by cognitive shortcuts—can adopt technologies in ways that either strengthen or weaken responsible digital behaviors. Moreover, the potential risks associated with this phenomenon were also indicated. The aim of this paper was to present how the utilization of the halo effect influences the generation of trust in smart systems and the formulation of implication for management practices and technology design. These implications are increasingly important in the context of sustainable digital marketing policy, where organizations must align persuasive communication with ethical standards and with rising expectations regarding sustainable digital transformation. Relationships between variables were analyzed using structural equation modeling (SEM), making it possible to verify complex dependencies between the perceived image of technology, the halo effect, and the users’ trust. This study tested three core hypotheses regarding the halo effect’s role, the foundational importance of security, and the mediating function of trust in technology adoption. The results of these analyses indicate that the halo effect significantly affects the level of trust in each of the investigated areas, with the strongest effect observed in the case of virtual assistants, where perception of the human-like characteristics of the interface considerably strengthened trust in the competences and reliability of the system. This finding has particular relevance for AI-driven personalization mechanisms, which increasingly guide consumer decision-making and shape their long-term behavioral patterns in online environments, with direct implications for sustainable consumption. This paper provides contribution to innovation management and technical marketing, stressing the importance of cognitive and emotional factors in the acceptance of new technologies. At the same time, it highlights the theoretical need to integrate responsible AI design with sustainable digital marketing strategies The findings suggest that ensuring trust, once established, has the potential to support not only technological innovation but broader societal goals related to responsible consumption, environmental stewardship, and long-term digital well-being aligned with sustainable development principles. However, this study stops short of empirically measuring sustainable consumption behaviors, offering instead a conceptual link that requires further empirical validation. Full article

Accurate identification of fire smoke is a key link in realizing early fire prevention and control. Traditional intelligent video and image processing technologies are significantly restricted by environmental factors, with weak anti-interference capabilities and limitations in distinguishing fire smoke, leading to a high false alarm rate of fires. To address this problem, this paper proposes an unconventional visual field smoke detection method based on image enhancement. The method innovatively improves the Retinex algorithm by integrating improved guided filtering, adaptive brightness correction, and CLAHE-WWGIF joint processing, which realizes targeted optimization for the unique interference factors of under-construction nuclear power plants such as water mist, low illumination, and equipment occlusion. First, an improved Retinex algorithm is used to process the image to improve the image brightness and contrast, retain edge details while avoiding halo artifacts, reduce the impact of noise, and optimize visual features. Then, the sample data set is integrated, and the YOLOv11 target detection algorithm is used to achieve accurate identification and positioning of smoke targets. Experimental data shows that the fire identification method achieves an accuracy rate of 93.6% and 92.3% for fire smoke identification in interference-prone scenarios such as dark nights and water mist, respectively, and the response time to fire smoke is only 1.8 s and 2.1 s. In practical on-site applications at nuclear power plant construction sites, the method is integrated into an “edge computing + distributed deployment” hardware system, which realizes real-time smoke detection in core areas such as nuclear islands and conventional islands with a false alarm rate of less than 5% and a detection delay of ≤300 ms, meeting the ultra-strict safety monitoring requirements of nuclear power projects. Experiments show that this method can be effectively applied to smoke detection scenarios under unconventional visual fields, accurately identify smoke, provide reliable technical support for fire smoke identification under unconventional visual fields, significantly reduce the false alarm rate of fire detection, and provide technical support for the safety of under-construction nuclear power plants. Full article

Mini-LED local dimming systems commonly suffer from luminance discontinuity, halo artifacts, and temporal instability in dynamic scenes. Traditional heuristic-based methods and standard convolutional neural networks often fail to capture long-range spatial dependencies and struggle to balance spatial smoothness, content fidelity, and real-time performance under hardware constraints. To address these challenges, this paper proposes SwinLightNet, an efficient adaptive backlight optimization network tailored for Mini-LED displays. Built upon a Swin Transformer framework tailored for Mini-LED backlight optimization, SwinLightNet integrates five hardware-aware design strategies: (i) a lightweight Swin variant (window size = 8, MLP ratio = 2.0) for efficient global context modeling; (ii) CNN encoder–decoder integration for multi-scale feature extraction; (iii) a partition-level alignment module ensuring spatial consistency; (iv) a backlight constraint module enforcing local luminance consistency and contrast preservation; (v) a change-aware temporal decision framework stabilizing dynamic sequences. These components synergistically resolve core limitations: global modeling suppresses halo artifacts while preserving content fidelity; alignment and constraint modules eliminate luminance discontinuity without compromising contrast; and the temporal framework guarantees flicker-free output under motion. Evaluated on DIV2K (static images) and a custom 2K-resolution video dataset (dynamic scenes), SwinLightNet demonstrates robust reconstruction quality while maintaining only 1.18 million parameters and 0.088 GFLOPs (Computational Cost). The results confirm SwinLightNet’s effectiveness in holistically addressing spatial, temporal, and hardware constraints, demonstrating strong potential for practical deployment in resource-constrained Mini-LED backlight control systems. Full article

We present an ab initio study on the one-neutron halo nucleus ¹¹Be using nuclear lattice effective field theory with high-fidelity chiral interactions at N3LO. By employing the wavefunction matching method to mitigate the sign problem and the pinhole algorithm to sample many-body correlations, we successfully reproduce the ground-state parity inversion and the extended matter radius characteristic of the halo structure. We analyze the intrinsic density distributions and geometric shapes of ¹¹Be in comparison with the core nucleus ¹⁰Be. Our results reveal a prominent two-cluster structure in both nuclei and the occupation of the $\sigma$ molecular orbital by the valence neutron in ¹¹Be. It enhances the prolate deformation as well as the diffuse neutron tail, distinct from the $\pi$-orbital occupation observed in the ¹⁰Be ground state. Full article

We investigate the dynamical stability of circular orbits around a Kerr black hole embedded in a Dehnen-type dark matter halo. The effective spacetime metric of the combined system is constructed using the Newman–Janis algorithm, and the effective potential for test-particle motion in the equatorial plane is derived. The stability of circular orbits is analyzed through the Hessian matrix of the effective potential, while the stability strength and restoring-force distribution are employed to quantify the orbital response to small perturbations. Our results show that the presence of the dark matter halo significantly alters the spatial structure of stable circular orbits, leading to non-continuous stable regions whose location and extent depend sensitively on the halo’s characteristic density, scale radius, and the black hole spin. The innermost stable circular orbit (ISCO) is shifted relative to the vacuum Kerr case, with its position determined by the combined effects of the spin and halo parameters. Two-dimensional heatmaps, parameter scans, and three-dimensional visualizations systematically illustrate how the black hole spin and dark matter halo properties influence the ISCO and the distribution of stable orbits. Finally, we analyze the influence of the dark matter halo on the structure of the black hole event horizon. These results provide a detailed theoretical investigation of orbital dynamics around rotating black holes in dark-matter-rich environments. Full article

Background: The Glycemic Index (GI) serves as a critical indicator of carbohydrate quality linked to postprandial glycemic response. As “Low-GI” claims proliferate on front-of-pack labels, it remains unclear how consumers value this complex signal. This study quantifies willingness to pay (WTP) for Low-GI labeling and tests a “motivation–capability” mechanism, positing that health orientation motivates label use, while objective Low-GI knowledge facilitates targeted evaluation across nutritional contexts. Methods: A discrete choice experiment was conducted in China using plain yogurt (N = 910). Mixed logit models analyzed how the valuation of the Low-GI claim is moderated by carbohydrate context, health orientation, and objective knowledge. Results: Results indicate a significant average premium for Low-GI labeling, with health orientation acting as a consistent motivational amplifier. Objective knowledge functions as a critical moderator interacting with carbohydrate context, driving label valuation only in specific low- or high-carbohydrate profiles while triggering skepticism in regular carbohydrate ones. Conclusions: These findings suggest that the public health effectiveness of emerging physiological claims depends jointly on consumer motivation and label-specific literacy. Consequently, policy interventions should combine label standardization with targeted education, equipping consumers with the capability to decode the claim’s physiological meaning rather than relying on a generalized health halo. Full article