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16 pages, 517 KB  
Entry
Storytelling in Advertising
by Elsa Simões
Encyclopedia 2026, 6(9), 191; https://doi.org/10.3390/encyclopedia6090191 (registering DOI) - 1 Sep 2026
Definition
Storytelling in advertising is an organising principle through which narrative meaning can be constructed at different but interconnected levels, from individual advertisements to campaigns and more enduring brand narratives across changing media environments. It provides the narrative logic through which individual advertisements can [...] Read more.
Storytelling in advertising is an organising principle through which narrative meaning can be constructed at different but interconnected levels, from individual advertisements to campaigns and more enduring brand narratives across changing media environments. It provides the narrative logic through which individual advertisements can function as narratives in their own right while also contributing to broader narrative structures, allowing audiences to interpret them within wider cultural frameworks. Although its forms have evolved with successive developments in advertising media, storytelling continues to rely on the narrative processes through which meaning is constructed. The distinction between the narrative content (tale) and its modes of expression (telling) explains how similar stories may be communicated differently as advertising adapts to new media. Storytelling therefore encompasses a wide range of narrative strategies while preserving its underlying narrative function. The emergence of generative artificial intelligence marks the latest stage in this historical development. Narrative production is increasingly distributed across human creators and computational systems. The construction of narrative meaning nevertheless continues to depend on human judgement, which remains central to advertising storytelling. Full article
(This article belongs to the Section Social Sciences)
68 pages, 4397 KB  
Article
Plant-Derived Aqueous Extracts as Bio-Based Modulators of Dunaliella salina Growth for Sustainable Cultivation
by Évellin do Espirito Santo, Ana Carolini Fernandes Mota, Rafael Boffo, Agatha Gonçalves Araújo, Julia Bolognesi Andrade, Stephanie França Carneiro, Aline Kirie Gohara-Beirigo, Maria Clara Arco e Flexa Fortuna, Aline Mello Carvalho, Daniel Pecoraro Demarque, Livia Seno Ferreira-Camargo and João Carlos Monteiro de Carvalho
Fermentation 2026, 12(9), 416; https://doi.org/10.3390/fermentation12090416 (registering DOI) - 1 Sep 2026
Abstract
This study assessed the effects of aqueous extracts from turmeric (Curcuma longa), mint (Mentha sp.), grape peel (Vitis sp.), and mango peel (Mangifera indica) on the growth and total carotenoid content of the microalga Dunaliella salina. [...] Read more.
This study assessed the effects of aqueous extracts from turmeric (Curcuma longa), mint (Mentha sp.), grape peel (Vitis sp.), and mango peel (Mangifera indica) on the growth and total carotenoid content of the microalga Dunaliella salina. A two-stage cultivation strategy was employed, in which aqueous extracts prepared by decoction were added at 0.5% (v/v) either at the inoculation or after the exponential growth phase. Microalgal growth was monitored by direct cell counting, and total carotenoid content was determined spectrophotometrically in the harvested biomass. The chemical profiles of the extracts were characterised by HPLC-MS/MS, enabling the annotation of key phenolic and flavonoid compounds. Specific orange turmeric and mint formulations enhanced microalgal cell proliferation by up to 31.88% and 28.95%, respectively, compared to the control. However, despite the higher biomass, the total carotenoid content did not increase correspondingly; orange turmeric extract even led to reductions of 90.84 to 92.86% in carotenoid content. These findings suggest that exogenous antioxidants may suppress the oxidative stress signals required to trigger carotenoid biosynthesis in D. salina. Additionally, grape peel extracts prepared at higher temperatures promoted better algal growth than those obtained at lower temperatures. These findings highlight the dual role of plant extracts in modulating microalgal growth and secondary metabolism, demonstrating that antioxidant-rich extracts may be used to enhance biomass accumulation before the subsequent induction of stress-mediated carotenogenesis, thereby potentially improving biotechnological yields. Full article
(This article belongs to the Section Microbial Metabolism, Physiology & Genetics)
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15 pages, 1267 KB  
Article
Effects of Daphnia magna on the Concentration and Size Distribution of Suspended Particles
by Xiaoyan Zhang, Feng Ge, Lichao Tan, Fukai Tang, Keke Xu, Xiaorong Wu, Mingzhu Zhang and Peiyong Guo
Ecologies 2026, 7(3), 92; https://doi.org/10.3390/ecologies7030092 (registering DOI) - 1 Sep 2026
Abstract
Suspended particles are key components of aquatic ecosystems that modulate the biogeochemical processes of natural waters. The filter feeder Daphnia magna can alter suspended particle characteristics and aquatic habitats, while habitat variations in turn affect its growth and reproduction. This study primarily investigated [...] Read more.
Suspended particles are key components of aquatic ecosystems that modulate the biogeochemical processes of natural waters. The filter feeder Daphnia magna can alter suspended particle characteristics and aquatic habitats, while habitat variations in turn affect its growth and reproduction. This study primarily investigated the impacts of D. magna on the concentration and size distribution of suspended particles, and explored its particle size selectivity. Three particle types, namely kaolinite (KN), montmorillonite (MN) and natural particles (NP), were adopted for experiments, and natural particles were further divided into three size fractions (<150 μm, <96 μm, <75 μm). The results demonstrated that D. magna significantly reduced suspended particle concentrations via ingestion, with the most prominent effect observed within the initial three hours of experimentation, verifying its practical value for wastewater remediation. Though classified as a non-selective filter feeder, D. magna exhibited distinct particle size selectivity for identical substances. Fine particles (<8 μm) presented higher bioavailability and were preferentially ingested by D. magna. Additionally, the regulatory effects of D. magna on particle size distribution were closely associated with its particle digestion process, which depended on inherent particle properties, including composition and organic matter content. Full article
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22 pages, 7357 KB  
Article
Post-Repair Lifetime of Wind Turbine Blades: Multiscale Modelling of Local Blade Deformation and Role of Defects
by Ruben I. Erives, Antonios Tempelis, Philipp Ulrich Haselbach and Leon Mishnaevsky
J. Compos. Sci. 2026, 10(9), 470; https://doi.org/10.3390/jcs10090470 (registering DOI) - 1 Sep 2026
Abstract
A multiscale computational framework is presented to assess the effect of voids that may arise from a scarf repair and its influence on the post-repair lifetime of wind turbine blades. The approach links a full scale blade model with a detailed repair region [...] Read more.
A multiscale computational framework is presented to assess the effect of voids that may arise from a scarf repair and its influence on the post-repair lifetime of wind turbine blades. The approach links a full scale blade model with a detailed repair region model and a microscale representation of polymer adhesives containing voids. Boundary conditions from the global blade model are transferred to the scarf repair model, which subsequently provides input to a microscale representative volume element (RVE) of the adhesive containing voids using the submodelling technique. This RVE is combined with a continuum damage mechanics formulation to simulate high-cycle fatigue and estimate the lifetime for different void contents. The effect of void content resulting from scarf repair is evaluated under both quasi-static and high-cycle fatigue loading, enabling lifetime predictions. In the simulations, it was demonstrated that the lifetime of repaired blade is 4 times lower for the repair with 4% void content as compared with the repair with 1% void content. Full article
(This article belongs to the Section Composites Applications)
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16 pages, 23849 KB  
Article
Porous Polymer Nanocomposites from Ethyleneamine–Poly(ethylene glycol) Diacrylate and Metal Oxide Nanoparticles: Morphology and Property Control
by Naofumi Naga, Yuta Umino and Tamaki Nakano
Appl. Nano 2026, 7(3), 29; https://doi.org/10.3390/applnano7030029 (registering DOI) - 1 Sep 2026
Abstract
Porous polymer nanocomposites incorporating metal oxide nanoparticles (SiO2, ZrO2, and TiO2) were synthesized via the aza–Michael addition reaction of ethyleneamines with poly(ethylene glycol) diacrylate (PEGDA) under polymerization-induced phase-separation conditions. The resulting nanocomposites exhibited interconnected particulate morphologies with [...] Read more.
Porous polymer nanocomposites incorporating metal oxide nanoparticles (SiO2, ZrO2, and TiO2) were synthesized via the aza–Michael addition reaction of ethyleneamines with poly(ethylene glycol) diacrylate (PEGDA) under polymerization-induced phase-separation conditions. The resulting nanocomposites exhibited interconnected particulate morphologies with particle diameters ranging from less than 0.5 to 5.0 μm. Increasing the nanoparticle content led to a significant reduction in particle size, indicating that the nanoparticles influenced the phase-separation process and the development of the porous structure. Energy-dispersive X-ray spectroscopy confirmed the homogeneous distribution of nanoparticles throughout the polymer matrix. The refinement of the porous morphology increased the bulk density and consequently enhanced the Young’s modulus of the nanocomposites. In addition, porous nanocomposites containing SiO2 nanoparticles exhibited distinct coloration when immersed in toluene owing to the Christiansen filter effect. The transmission wavelength shifted toward longer wavelengths with increasing SiO2 content, which was attributed to a decrease in the effective refractive index of the porous nanocomposites. These results demonstrate that the incorporation of metal oxide nanoparticles provides an effective strategy for controlling the morphology, mechanical properties, and optical functionality of porous polymer nanocomposites. Full article
(This article belongs to the Collection Feature Papers for Applied Nano)
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31 pages, 9415 KB  
Article
Valorization of Wheat Straw Cellulose into Biodegradable Packaging Films for Fresh Produce Preservation
by Sharad Bhattarai and Srinivas Janaswamy
Foods 2026, 15(17), 3111; https://doi.org/10.3390/foods15173111 - 1 Sep 2026
Abstract
The growing environmental impact of petroleum-based plastic packaging has accelerated the development of biodegradable materials from renewable resources. In this study, cellulose extracted from wheat straw was regenerated into biodegradable films using calcium-ion crosslinking and glycerol plasticization. A Box–Behnken experimental design optimized cellulose [...] Read more.
The growing environmental impact of petroleum-based plastic packaging has accelerated the development of biodegradable materials from renewable resources. In this study, cellulose extracted from wheat straw was regenerated into biodegradable films using calcium-ion crosslinking and glycerol plasticization. A Box–Behnken experimental design optimized cellulose content (0.35–0.5 g), calcium chloride concentration (200–800 nm), and glycerol concentration (0.5–1.5%) to produce films with balanced mechanical and barrier properties. The optimized film was characterized for its physicochemical, mechanical, optical, antioxidant, and biodegradation properties and evaluated for fresh grape packaging. The film exhibited favorable mechanical strength of 30.82 ± 4.70 MPa, controlled water vapor permeability of 0.59 ± 0.06 10−10 gm−1 s−1 Pa−1, elongation at break of 4.36 ± 0.35%, moderate transparency of 22.95 ± 0.65% mm−1 at 600 nm, and ultraviolet light-blocking capability, allowing only 9.57 ± 1.44% of UV-B at 300 nm, and an IC50 value of 0.33, indicating moderate antioxidant potential, with 35% biodegradation after 37 days at a soil moisture of 24%. During ambient storage, grapes packaged with the film reached 15% weight loss by 13 days, while slowing changes in total soluble solids, pH, titratable acidity, total phenolic content, and vitamin C, and delaying visible quality deterioration. Compared with the uncovered control, packaged grapes maintained acceptable quality for approximately six additional days, reaching 15 days of storage. Unlike conventional polystyrene film, which promoted excessive gas accumulation and fruit cracking, the wheat straw cellulose film provided a semipermeable barrier that balanced moisture and gas exchange. The systematic optimization of these formulations, followed by comprehensive characterization of the optimized films, demonstrates the potential of wheat straw cellulose as a functional material for developing cellulose films as sustainable, biodegradable packaging materials for extending the postharvest quality of fresh produce. Full article
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25 pages, 8116 KB  
Article
Leakage-Controlled and Information-Bounded Evaluation of Multi-Task Learning for Crumb–Rubber Modified Asphalt: What Twenty Mix Designs Can and Cannot Support
by He Huang, Yingli Gao, Bin Tian and Zhuo Yang
Materials 2026, 19(17), 3727; https://doi.org/10.3390/ma19173727 - 1 Sep 2026
Abstract
Data-driven prediction of crumb–rubber modified asphalt (CRMA) binder properties is usually reported on datasets in which a small number of mix-designs is swept across several test temperatures, so that the row count greatly exceeds the number of independent experiments. This study asks what [...] Read more.
Data-driven prediction of crumb–rubber modified asphalt (CRMA) binder properties is usually reported on datasets in which a small number of mix-designs is swept across several test temperatures, so that the row count greatly exceeds the number of independent experiments. This study asks what such a dataset can actually support. Using 221 laboratory measurements drawn from 20 independent CRMA mix designs, we evaluate a task-adaptive mixture-of-experts multi-task network (TA-MoE-MTL), a locked Huber-anchored hybrid extension, and fourteen deep and classical reference models for the joint prediction of penetration, softening point, ductility and rutting factor. Three methodological elements are introduced. First, model selection is made strictly nested and group-aware: the stopping epoch is chosen on an inner split of the training designs and the held-out designs are used once. Second, we bound what the recorded inputs can explain before any model is fitted: because the consistency targets are constant within a mix design and because eight designs share identical input vectors while their rutting factors differ, the attainable coefficient of determination for the rutting factor is 0.790 rather than unity. Third, performance is reported with each mix design weighted equally, so that high replication designs cannot dominate. The locked hybrid assigns 90% weight to a Huber-anchored robust expert branch and 10% to a freshly trained TA-MoE-MTL branch. It attains pooled out-of-fold coefficients of determination of 0.613/0.594/0.878/0.685 and ranks first of 16 models at a mean pooled R2 0.693, exceeding MLP–sklearn (0.656) by 0.037. Across three seeds, seeds 42/43/44 give mean pooled R2 values of 0.693/0.689/0.693 (mean 0.691 ± 0.002), and all three runs remain above the frozen MLP sklearn reference. A learning curve over the number of training designs is still rising at the largest size the data allow. The contribution of this work is an evaluation protocol for replicated mix design datasets, a way of bounding their information content, and a robust hybrid that exposes rather than hides the value of a simple small-sample anchor. Full article
(This article belongs to the Section Materials Simulation and Design)
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18 pages, 16287 KB  
Article
Optimal Placement of Meters in a Physical Electrical Network for Real-Time Harmonic State Estimation Assessment
by Ruben Rodríguez-Flores, Aurelio Medina-Rios, Rafael Cisneros-Magaña, Juan Manuel Verduzco-Durán and Julio Cesar Godinez-Delgado
Energies 2026, 19(17), 4127; https://doi.org/10.3390/en19174127 - 1 Sep 2026
Abstract
This contribution presents a methodology for optimal placement (OP) of meters in power systems, using the state-space reference frame. The goal is to minimize the state estimation error, specifically, the mean squared error (MSE), through OP of a limited number of measurement devices [...] Read more.
This contribution presents a methodology for optimal placement (OP) of meters in power systems, using the state-space reference frame. The goal is to minimize the state estimation error, specifically, the mean squared error (MSE), through OP of a limited number of measurement devices and keep the total observability of the system. The measurement set is applied to the time-domain state estimation based on the Kalman filter (KF) to obtain voltage and current waveforms in real time, and the harmonic content is evaluated through the application of the Fast Fourier Transform (FFT). The effectiveness of harmonic state estimation (HSE) is demonstrated in case studies considering different operating points in a test electrical network, particularly in estimating the dynamic behavior of nonlinear electrical loads. The HSE method is implemented in physical tests using Lab-Volt® equipment to monitor the system in real time using MATLAB/Simulink® software through the RL-LAB® platform; the real-time experimental tests (RTE) allow validation of the real-time digital simulation (RTS). Full article
(This article belongs to the Section F: Electrical Engineering)
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22 pages, 1842 KB  
Article
Bioprocess and Stoichiometric Modeling of Pleurotus djamor Cultivation in Wheat Stubble Solid-State Fermentation
by Vicente Peña-Caballero, Pablo Antonio López-Pérez, María José Enríquez-Arredondo, Elizabeth Quintana-Rodríguez, Adán Topiltzin Morales-Vargas and José Luis Zárate-Castrejón
Fermentation 2026, 12(9), 414; https://doi.org/10.3390/fermentation12090414 - 1 Sep 2026
Abstract
A formal framework of bioprocesses enables accurate prediction of reaction outcomes, thereby optimizing resource allocation and reducing production costs. This study aimed to establish an approximate stoichiometric equation and determine the bioenergetics growth parameters of the pink oyster mushroom (Pleurotus djamor) [...] Read more.
A formal framework of bioprocesses enables accurate prediction of reaction outcomes, thereby optimizing resource allocation and reducing production costs. This study aimed to establish an approximate stoichiometric equation and determine the bioenergetics growth parameters of the pink oyster mushroom (Pleurotus djamor) using a “black box” modeling approach. A commercial strain was cultivated in polypropylene bags at 28 °C and 75% relative humidity. The harvested mushroom biomass was dried and analyzed for C, H, and N content, with O determined by difference. The resulting empirical formulas were CH1.33O0.36N0.02 for the dry wheat straw substrate and CH1.81O0.41N0.09 for the fungal biomass. The bioprocess exhibited a primordia initiation period of 20.5 days, a total harvest window of 50.0 days, a maximum biological efficiency of 16.77%, a model yield (Y) of 0.90%, and a productivity of 20.5 g/100 g substrate. In conclusion, this biotechnological framework provides a robust predictive tool for industrial scaling, enabling mass and energy balance optimization in real time without reliance on costly intracellular measurements. Thus, it establishes a reliable and sustainable pathway to convert low-cost agricultural residues into high-value bioproducts, supporting the goals of a circular economy. Full article
26 pages, 20234 KB  
Article
Deep Learning-Based Quantitative Precipitation Estimation Using Ground-Based Microwave Radiometer and Micro-Rain Radar Observations
by Jingyang Li and Jieying He
Remote Sens. 2026, 18(17), 2941; https://doi.org/10.3390/rs18172941 - 1 Sep 2026
Abstract
This study utilizes the 89 GHz dual-polarization channel of the Ground-Based Multi-Frequency and Dual-Polarization Microwave Radiometer (GMD-MR) to overcome the challenges posed by the insensitivity of low-frequency microwave channels to cloud ice particles. By integrating data from Micro-Rain Radars (MRRs), we developed and [...] Read more.
This study utilizes the 89 GHz dual-polarization channel of the Ground-Based Multi-Frequency and Dual-Polarization Microwave Radiometer (GMD-MR) to overcome the challenges posed by the insensitivity of low-frequency microwave channels to cloud ice particles. By integrating data from Micro-Rain Radars (MRRs), we developed and implemented advanced convolutional and deep learning models. These models leverage brightness temperature, polarization differences, and constraints from cloud and precipitation data to quantitatively estimate cloud ice content, cloud water content profiles, rainwater content profiles, and precipitation rates, achieving correlation coefficients of 0.6, 0.7, 0.84, and 0.84, respectively. Our analysis of the spatiotemporal dynamics of ice water, cloud liquid water, and rain liquid water paths during precipitation events highlights their predictive value for precipitation occurrence. With a prediction accuracy of 97% and a temporal correlation coefficient of 0.9, our findings affirm the effectiveness of ground-based radiometers and micro-rain radars in precipitation detection. This study demonstrates the capability of multi-instrument joint retrieval for various meteorological parameters, highlighting the significant potential of multi-source microwave data fusion in quantitative precipitation estimation. It establishes and reinforces the foundation for future investigations into the physical processes of precipitation evolution. Full article
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54 pages, 5992 KB  
Article
Environmental Policy Sequencing for Sustainability: Mandatory Regulation and Multidimensional Corporate Disclosure in China
by Zijuan Zhang and Yuanyuan Wang
Sustainability 2026, 18(17), 8964; https://doi.org/10.3390/su18178964 - 1 Sep 2026
Abstract
Environmental policy evaluation for sustainability requires attention not only to the effects of individual instruments but also to how prior policy exposure shapes corporate responses to subsequent regulation. Using China’s revised Environmental Protection Law as the institutional setting, this study examines whether firms [...] Read more.
Environmental policy evaluation for sustainability requires attention not only to the effects of individual instruments but also to how prior policy exposure shapes corporate responses to subsequent regulation. Using China’s revised Environmental Protection Law as the institutional setting, this study examines whether firms facing historically greater regulatory exposure experienced differential post-2015 changes in corporate environmental disclosure and whether pre-policy environmental subsidy exposure is associated with the magnitude of those responses. Corporate disclosure is conceptualized as a multidimensional policy response comprising aggregate disclosure-based transparency, outcome-oriented content, process-oriented content, and structural balance. Using Chinese A-share listed firms from 2008 to 2023, the analysis combines entropy balancing with a difference-in-differences design and industry-level inference. Historically, pollution-intensive firms exhibit a larger post-2015 increase in aggregate disclosure-based transparency than comparison firms (β = 0.2221), wild-bootstrap (p = 0.0005). Both outcome- and process-oriented disclosure increase, with a significantly larger response in outcome-oriented content, whereas content imbalance does not decline significantly. Greater pre-policy subsidy exposure is associated with a smaller incremental response (β = −0.0542), wild-bootstrap (p = 0.0238), although this relationship is distributionally sensitive and noncausal. The findings indicate that corporate responses to mandatory regulation are multidimensional and may vary with prior policy exposure, highlighting the relevance of policy sequencing to sustainability governance. Because later environmental policies overlap with the post-2015 period, the estimates reflect differential responses to the broader regulatory environment rather than the isolated effect of a single law. The disclosure measures capture reported information rather than verified environmental performance. Full article
(This article belongs to the Section Economic and Business Aspects of Sustainability)
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27 pages, 1250 KB  
Systematic Review
Emotional Dependency and Parasocial Grief Following the Alteration or Loss of Companion Artificial Intelligences: A Systematic Review
by Johanna Lilibeth Alcívar Ponce, Wilson Alexander Zambrano Vélez, Gioryi Sornoza Zavala, José Manuel Peñafiel Mejillones and Julio César Rivera Ruiz
Behav. Sci. 2026, 16(9), 1548; https://doi.org/10.3390/bs16091548 - 1 Sep 2026
Abstract
With the advance of large language models, companion AI agents have evolved to simulate complex relational dynamics, responding to the need for affection and emotional support. This systematic review aimed to analyze the available empirical evidence on the manifestations of emotional dependency and [...] Read more.
With the advance of large language models, companion AI agents have evolved to simulate complex relational dynamics, responding to the need for affection and emotional support. This systematic review aimed to analyze the available empirical evidence on the manifestations of emotional dependency and parasocial grief experienced by users in response to the algorithmic alteration or loss of these companion AI agents. Following the guidelines of the PRISMA 2020 statement and with a protocol registered on OSF, an exhaustive search was conducted across the Web of Science, Scopus, PubMed, and APA PsycINFO databases. After applying inclusion criteria via the PICOS framework and evaluating methodological quality using the MMAT tool, 14 empirical studies were selected and included. The synthesized results suggest that technical disruptions (updates, content filters, or server shutdowns) are associated with disruptions in the agent’s identity continuity, which users frequently described as coinciding with separation distress, depressive symptoms, perceived isolation, and parasocial grief expressed through anthropomorphic metaphors. It is preliminarily concluded that the loss or modification of companion AI agents may be linked to a psychosocial impact that presents descriptive similarities to interpersonal breakups or disenfranchised grief. Full article
(This article belongs to the Special Issue Digital Technologies, Mental Health and Well-Being)
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18 pages, 4821 KB  
Article
Genome-Wide Identification of the R2R3-MYB Gene Family in Solanum americanum and Functional Analysis of Its Role in Fruit Coloration
by Yanbo Yang, Zhiying Gong, Yanwen Wang, Hang Li, Jiahong Li, Qihang Cai, Zuming Luo, Zhenghai Sun and Liping Li
Biology 2026, 15(17), 1480; https://doi.org/10.3390/biology15171480 - 1 Sep 2026
Abstract
Anthocyanins are key secondary metabolites responsible for fruit coloration in plants, and their biosynthesis is largely regulated by R2R3-MYB transcription factors. However, the R2R3-MYB regulators controlling fruit anthocyanin accumulation in wild Solanum species remain poorly understood. Here, Solanum americanum was used to identify [...] Read more.
Anthocyanins are key secondary metabolites responsible for fruit coloration in plants, and their biosynthesis is largely regulated by R2R3-MYB transcription factors. However, the R2R3-MYB regulators controlling fruit anthocyanin accumulation in wild Solanum species remain poorly understood. Here, Solanum americanum was used to identify candidate R2R3-MYB genes associated with fruit coloration through genome-wide identification, phylogenetic analysis, synteny analysis, expression profiling, and virus-induced gene silencing (VIGS). A total of 122 SaMYB genes were identified, and phylogenetic analysis revealed that SaMYB proteins clustered with Arabidopsis thaliana R2R3-MYB members in conserved subgroups, suggesting evolutionary conservation of this family. Synteny analysis identified 37 syntenic gene pairs among SaMYB genes, and the Ka/Ks values of all analyzable gene pairs were below 1, indicating that these duplicated genes are subject to functional constraint. Integrated analysis of phylogenetic relationships, protein structures, promoter cis-elements, and fruit developmental expression patterns identified SaMYB59 and SaMYB106 as candidate regulators of anthocyanin accumulation. VIGS analysis demonstrated that silencing SaMYB106 reduced purple coloration, decreased anthocyanin content, and downregulated the expression of the structural gene DFR. These results indicate that SaMYB106 functions as a positive regulator of fruit anthocyanin accumulation in S. americanum. This study provides insights into the molecular basis of fruit coloration in wild Solanum species. Full article
(This article belongs to the Special Issue Advances in Plant Genomics and Genome Editing)
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21 pages, 598 KB  
Article
Solid-State Fermentation with Saccharomyces cerevisae: A Strategy to Modulate the Properties of Faba Bean Flours
by Nerea Sarasa-Gil, Sandra Horvitz, María José Beriain, Paloma Vírseda, Francisco C. Ibañez and Débora Villaño
Foods 2026, 15(17), 3110; https://doi.org/10.3390/foods15173110 - 1 Sep 2026
Abstract
Faba bean (Vicia faba L.) is a high-protein legume limited by its sensory profile and antinutritional factors like RFOs (Raffinose Family Oligosaccharides). The impact of solid-state fermentation (SSF) with Saccharomyces cerevisiae on properties of starch-(SF) and protein-rich (PF) faba bean flours was [...] Read more.
Faba bean (Vicia faba L.) is a high-protein legume limited by its sensory profile and antinutritional factors like RFOs (Raffinose Family Oligosaccharides). The impact of solid-state fermentation (SSF) with Saccharomyces cerevisiae on properties of starch-(SF) and protein-rich (PF) faba bean flours was investigated. Proximate composition, amino acid profile, digestible carbohydrates, organic acid contents, and techno-functional properties were determined. Sensory properties of SF- and PF-based crepes were also assessed. SSF reduced digestible carbohydrates by 10% (SF) and 22% (PF). RFOs concentration decreased by 39% in SF after SSF. Malic and acetic acids increased in both fractions. In PF, glutamic and aspartic acids increased (14.09 and 8.41%, respectively), whereas lysine decreased, suggesting protein structural modifications without compromising nutritional quality. Water absorption capacity rose by 12.41% (SF) and 6.7% (PF), while oil absorption capacity improved only in SF (22.63%). Water solubility decreased by 43.78% and 23.76% in SF and PF. Finally, compared to crepes made with unfermented flour, those prepared with fermented PF received a global acceptance 48.50% more favorable. These findings highlight SSF with S. cerevisiae as a promising strategy to improve sensory properties and expand the application of faba bean flour fractions as functional ingredients in plant-based food products. Full article
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31 pages, 5634 KB  
Article
Conceptualizing and Measuring Mindfulness in School Settings: A Mixed Methods Study and Development of Mindfulness in School Scale
by Ziyaeddin Halid İpek and Ferudun Sezgin
J. Intell. 2026, 14(9), 210; https://doi.org/10.3390/jintelligence14090210 - 1 Sep 2026
Abstract
This study aimed to explore how mindfulness is perceived and experienced by teachers and to develop and validate the Mindfulness in School Scale (MSS) for use in school settings. An exploratory sequential mixed methods design was employed. In the qualitative phase, phenomenological interviews [...] Read more.
This study aimed to explore how mindfulness is perceived and experienced by teachers and to develop and validate the Mindfulness in School Scale (MSS) for use in school settings. An exploratory sequential mixed methods design was employed. In the qualitative phase, phenomenological interviews were conducted with 23 teachers selected through purposive maximum variation sampling. Content analysis identified six themes: Self-Observation, Environmental Observation, Self-Awareness, Environmental Awareness, Acceptance, and Reactive Control. These findings informed the development of the MSS. In the quantitative phase, the scale was administered to 663 teachers. Exploratory and Confirmatory Factor Analyses supported a five-dimensional structure comprising Self-Observation, Environmental Observation, Self-Awareness, Environmental Awareness, and Acceptance, explaining 51.46% of the total variance. Standardized CFA factor loadings ranged from 0.50 to 0.90, and the measurement model demonstrated satisfactory fit (χ2/df = 1.20, RMSEA = 0.028, CFI = 0.984, TLI = 0.981). The five dimensions also demonstrated satisfactory internal consistency, with Cronbach’s alpha coefficients ranging from 0.80 to 0.93. Correlations among the dimensions were generally low to moderate, indicating that the MSS captures related but distinct aspects of mindfulness in school settings rather than a single underlying construct. The findings further suggest that mindfulness in schools is shaped by both intrapersonal and interpersonal processes, with environmental awareness emerging as a contextually salient dimension. Overall, the MSS provides initial evidence for the validity and reliability of its five dimensions as a multidimensional instrument for assessing mindfulness among teachers in school settings while offering a context-specific framework for future research examining the relationship between mindfulness and emotional intelligence. Full article
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