Search Results (25,396)

This work contributes to advancing sustainable energy and waste management strategies by investigating the thermochemical conversion of food-based biomass through pyrolysis, highlighting the role of artificial intelligence (AI) in enhancing process modelling accuracy and optimization efficiency. The main objective is to explore the potential of underutilized biomass resources like spent coffee grounds (SCGs) and DSs (date seeds) for sustainable hydrogen production. Specifically, it aims to optimize the pyrolysis process while evaluating the performance of these resources both individually and as blends. Proximate, ultimate, fibre, TGA/DTG, kinetic, thermodynamic, and Py-Micro-GC analyses were conducted for pure DS, SCG, and blends (75% DS-25% SCG, 50%DS-50%SCG, 25%DS–75%SCG). Blend 3 offered superior hydrogen yield potential but had the highest activation energy (Ea: 313.24 kJ/mol), while Blend 1 exhibited the best activation energy value (Ea: 161.75 kJ/mol). The kinetic modelling based on isoconversional methods (KAS, FWO, and Friedman) identified KAS as the most accurate. These approaches work together to provide a detailed understanding of the pyrolysis process with a particular emphasis on the integration of artificial intelligence (AI). An LSTM model trained with lignocellulosic data predicted TGA curves with exceptional accuracy (R²: 0.9996–0.9998). Full article

The global edible oil market is consistently at risk of economically motivated adulteration, underscoring the necessity of robust analytical methods essential for authentication. Among various phytochemicals, phytosterols have emerged as powerful diagnostic markers and compositional indicators for verifying the botanical origin, purity, and quality of edible oils. This review summarizes recent advancements in phytosterol analysis, highlighting its application in detecting adulteration in high-value oils such as olive oil, tea seed oil, and sesame oil. We discuss the approaches of multiple chromatographic and mass spectrometry techniques (GC-MS, LC-MS) with chemometric analysis of novel markers like fatty acyl sterol esters and sterol degradation products. Furthermore, we discuss significant challenges, including the need for comprehensive databases, the identification of complex sterol compositional profiles, and the limitations of current standardized methods. The advancement of phytosterol-based authentication increasingly depends on the development of rapid, high-throughput, and non-targeted sterol profiling approaches, supported by artificial intelligence and bioinformatics, to ensure vegetable oil authenticity and safeguard market integrity. Full article

Soybean (Glycine max L. Merr.) is a globally significant oilseed crop. The number of four-seeded pods in the lower part (FSPL) serves as a critical yield component under high-density planting. To date, numerous crop-specific traits have been investigated in multiple breeding studies of soybean; however, little attention has been paid to studies on FSPL. Hence, in this study, we investigated the genetic basis of FSPL using a recombinant inbred line population (RIL3613) across four environments. The segregated genetic mapping population was cultivated during the field experiments, and the collected phenotypic dataset of FSPL exhibited quantitative genetics and high broad-sense heritability (0.724), indicating stable genetic control. Further, we performed quantitative trait locus (QTL) mapping using raw means in each environment and identified 10 QTL, explaining phenotypic variations (PVE) ranging from 0.10% to 2.94%. Among the identified environmentally stable QTL, qFSPL-15-1 was consistently detected across all environments. Two candidate genes [Glyma.15G034100 (encoding lysophosphatidic acid acyltransferase 2) and Glyma.15G034200 (encoding an RNA-binding protein)] were predicted within the flanking genomic interval. The allele frequencies of haplotype combinations of Hap1: Pro2 + CDS1 for Glyma.15G034100 and Hap3: Pro3 + CDS1 for Glyma.15G034200 in wild soybeans (26.6–30.0%) were larger than improved cultivars (52.6–53.4%). We believe that our current findings elucidate the molecular mechanisms regulating lower-pod formation and provide precise genetic targets for marker-assisted selection in high-yield soybean breeding. Full article

Drought stress during germination impairs seed germination and seedling development in wheat. Seed germination depends on embryo lipid mobilization for energy supply; however, the molecular mechanisms underlying lipid mobilization in drought stress germination remain unclear. Two wheat cultivars with significant differences in drought resistance, Shannong 28 (SN28) and Xinmai 296 (XM296), were subjected to integrated transcriptomic, metabolomic, and lipidomic analyses to reveal molecular response differences. SN28 exhibited increased root length (RL), while XM296 showed significant decreases in germination energy (GE), vigor index (VI), and single seedling dry weight (SSDW). Multi-omics integration revealed that SN28 maintained efficient lipid mobilization under drought through a distinctive regulatory strategy: suppressing jasmonic acid synthesis to prevent excessive growth inhibition, activating α-DOX1 signaling to maintain defense function, and coordinating these with low expression of ABA signaling factors MYB96 and ABI4 to relieve lipid mobilization suppression. Upregulated lipase and nsLTP genes (TaLTPIe.1, TaLTPIg.1) promoted lipid mobilization, while coordinated activation of arginine–proline metabolism, zeatin biosynthesis, and antioxidant defense pathways provided metabolic support. In contrast, XM296’s extensive inhibition of lipoxygenase enzymes and insufficient lipid mobilization capacity directly underlies its drought susceptibility. These findings indicate that cultivar-specific lipid metabolism patterns are key determinants of germination-stage drought resistance, providing candidate genes for wheat breeding. Full article

Background: As the body’s first line of defense against environmental stressors, the skin is highly susceptible to UVB-induced damage, which triggers inflammation and impairs barrier function. This study investigates the protective effects of safflower seed oil (SSO) and fermented Artemisia annua oil (FAAO) against UVB-induced skin injury. Methods: The protective effects of SSO and FAO against UVB irradiation was first tested in HaCaT keratinocyte. Subsequently, a UVB-irradiated SKH-1 mouse model was established to evaluate these two oils. RNA-seq analysis was employed to investigate the potential molecular mechanisms by which SSO and FAO repair the skin barrier. Results: In vitro experiments demonstrated that SSO (0.25%) and FAAO (0.1%) significantly enhanced HaCaT keratinocyte viability following UVB exposure while selectively modulating pro-inflammatory cytokine production. In a UVB-irradiated SKH-1 mouse model, standalone SSO or FAAO treatment partially ameliorated epidermal hyperplasia and restored UV-reduced collagen content, while the 1:1 SSO/FAAO combination exhibited superior efficacy in restoring skin architecture, reducing erythema and edema, and suppressing immune cell infiltration. Transcriptomic profiling revealed that the combined treatment promoted structural repair by attenuating inflammatory responses and preserving extracellular matrix homeostasis. Conclusions: Together, these findings underscore the potential of SSO/FAAO as a multifunctional botanical intervention for mitigating UVB-induced cutaneous damage. Full article

Resource allocation in sixth-generation (6G) networks must meet throughput, latency, and reliability targets while network conditions keep changing. At the same time, the telemetry needed to train good models is distributed across many devices and edge nodes, so sending it to a central server can violate privacy or data-sharing constraints. Federated learning (FL) helps, but two practical concerns usually determine whether it works in practice: how much communication is needed to achieve strong performance, and whether weaker (tail) clients benefit-not only the average client. In this study, we run large-scale FL on 6G telemetry with 200 clients and quantify the communication fairness trade-off. We evaluate FedAvg and FedProx under multiple settings and benchmark them against a strong centralized model and a local-only baseline. Results are reported as mean ± 95% confidence intervals over five random seeds. We measure the accuracy, macro-F1, AUC, and AP, and we also focus on tail behavior using the worst eligible client accuracy, p10 client accuracy, and fairness gap. By plotting the accuracy/macro-F1 against cumulative communication (bytes), we show that some configurations match the average performance while transmitting far fewer data. Finally, we find that the worst client performance improves early and then stabilizes, and a sensitivity study suggests that FedProx’s $\mu$ has a limited impact in this setup. These findings offer actionable guidance for 6G operators and system designers by quantifying how participation and dropout policies translate into concrete communication budgets and tail client behavior. Full article

The aim of this research was to experimentally analyze the influence of drying method, temperature, and drying time on moisture content (MC), elemental composition (percentages of C, H, N, S, and O), and protein and fat content in sunflower seeds, as well as to apply and compare different existing machine learning regression models for moisture content prediction. The study was conducted on three sunflower hybrids (Sumiko, Pioneer, and Agromatic Lidea) using conduction, vacuum, and fluidized bed drying at temperatures from 50 to 80 °C and durations from 15 to 60 min. The results showed that temperature and time are the main controllable parameters of drying, while drying methods and hybrid also significantly influence the process. In moisture content modelling, artificial neural networks (ANN) achieved the best predictive performance (R² = 0.97; RMSE = 0.46), while SVR models showed slightly weaker but still high accuracy. The results indicate that machine learning models can be useful tools for predicting moisture content based on drying parameters and may support improved monitoring and management of the sunflower seed drying process. Full article

The regeneration and repair of scarless skin tissue remain a significant challenge for full-thickness wounds. Traditional wound management approaches, particularly passive healing through scabbing and conventional mechanical debridement, are frequently associated with significant pain, high infection risks, and abnormal scar formation, often failing to support the regeneration of skin appendages like hair follicles. In recent years, collagen-based scaffolds have been widely adopted in tissue-engineered skin substitutes owing to their favorable biocompatibility. However, their simplistic, single-component architecture inherently lacks the dynamic, cell-instructive microenvironment found in native skin, which not only compromises the long-term survival and functional integration of seeded cells but also directly leads to insufficient reconstruction of the dermo-epidermal junction, thereby impairing skin barrier function and ultimately limiting overall regenerative efficacy. In this study, we propose a biomimetic multilayer composite scaffold system in which decellularized amniotic membrane matrix (AM) is combined with fibroblast-laden collagen gel (FCG) and seeded with epidermal stem cells (EpiSCs). This bionic skin (denoted as AM-FCG-EpiSCs) is designed to achieve hierarchical regeneration of full-thickness skin defects. Compared with injured skin treated with Moropicin ointment, the injured skin treated with AM-FCG-EpiSCs healed more quickly and regenerated appendages like hair follicles without scarring. The results show that the biomimetic structure of AM-FCG-EpiSCs can mediate dynamic cell–cell interactions and regulate the microenvironment. This breakthrough overcomes the dual challenges of scar suppression and functional restoration in full-thickness skin regeneration, offering an innovative solution for translational medicine. Full article

The purpose of this work is to investigate the binding state of inorganic elements to flavonoid components in aqueous extract of Silybum marianum (SM) seeds, as well as the antioxidant activity of the extract. This study employed reversed-phase high-performance liquid chromatography (RP-HPLC) to separate silymarin flavonoids in boiling water decoction of SM seeds, and collected the post-column effluent in the segments according to the retention time of seven main silymarin flavonoid components. Inductively coupled plasma mass spectrometry (ICP-MS) was subsequently utilized to quantify nine inorganic elements (As, Cd, Co, Cr, Cu, Fe, Mn, Mo, Zn) in the collected HPLC fractions of the decoction. Meanwhile, electron paramagnetic resonance spectroscopy (EPR) was employed to assess the free radical scavenging activity of aqueous extract of SM seeds, using the signal intensity changes of 2,2-diphenyl-1-picrylhydrazyl (DPPH) and DMPO-OH• adducts as quantitative metrics. The results showed that essential trace elements (Cu, Fe, Mn, Zn) mainly existed as inorganic ions or strong polar forms in the tea-like infusion, with weak binding to flavonoid compounds. On the other hand, the aqueous extract exhibited significant •OH scavenging capacity, with a scavenging rate of 95% against •OH generated by continuous 5 min ultraviolet irradiation of H₂O₂ aqueous solution. This study provides experimental evidence for the development of SM as a food–medicine dual-purpose resource, proposing that consumption of SM seed tea represents a facile and effective approach to supplement trace elements and intake silymarin for enhancing endogenous antioxidant defense. Full article

Flax (Linum usitatissimum L.) is among the earliest domesticated crops and remains agronomically and economically important due to its dual use for fibre and seed (oil) production. In recent years, renewed interest in flax has emerged from its role in diversified and sustainable agriculture, human nutrition, and bio-based industrial applications. This review provides a comprehensive agronomic synthesis of global flax production, integrating worldwide production trends, genetic resource availability, and the main agronomic drivers governing crop establishment, growth, yield, and quality. Particular emphasis is placed on climatic requirements, soil and nutrient management, crop management practices, and water use, as well as on the contrasting requirements of fibre flax and seed flax. Despite growing research efforts, agronomic knowledge on flax remains fragmented across environments, production purposes, and management strategies, limiting the translation of experimental findings into robust, environment-specific crop management recommendations. Sustainable intensification of flax production will therefore depend on integrating optimized agronomic practices with breeding strategies that exploit existing genetic diversity to improve yield stability, quality, and resilience under increasing climatic variability. Full article

Pea (Pisum sativum L.) is an important source of food and feed and contributes to soil improvement through its association with nitrogen-fixing bacteria. By enabling higher yields and selection of tolerant genotypes, controlled environment agriculture (CEA) could meet increasing nutritional needs despite adverse conditions. The main objective of this study was to investigate the effects of drought stress on the development of vegetable pea genotypes under controlled vertical farming conditions. Plants were grown in CEA and exposed to drought stress at different developmental stages, after flowering and after pod formation. Drought significantly reduced pod and seed numbers, showing a stronger effect than genotype. For example, genotype Favorit produced 7.67 and 9.00 seeds per plant under control conditions, compared with only 2.00 and 2.67 seeds per plant under drought treatments. Pod length, seed number, and seed weight were also lower under stress, highlighting the importance of water availability during seed setting and filling. Fresh and dry biomass were mainly influenced by genotype, indicating differences in stress adaptability. The results also demonstrate that CEA can be used for reproducible abiotic stress experiments relevant to plant breeding and crop production. Full article

Soil-borne diseases have become increasingly serious due to continuous planting. Soil fumigation may be inadequate because of the persistence of soil-borne pathogens on ginger seed rhizome. A combined strategy of soil fumigation and seed rhizome disinfection would be necessary to achieve synergistic control. In this study, the approach of soil fumigation with chloropicrin (CP) coupled with seed rhizome disinfection (Copper, Cu) was first adopted to evaluate the synergistic effects on soil physicochemical properties, enzyme activities and microbial communities, and therefore reveal mechanisms for soil microecological health and crop yield promotion. The results showed the comprehensive strategy could reduce NO₃⁻-N content, and the activities of soil enzymes, while increased NH₄⁺-N content, EX-Cu, and OXI-Cu content, which were positively correlated with ginger yield but negatively correlated with soil-borne pathogens and plant mortality. On the other hand, there was a reduction in bacterial diversity and richness, which was positively correlated with the abundance of soil-borne pathogens. Moreover, some beneficial soil microorganisms’ relative abundance (such as Firmicutes, Actinobacteria, Bacillus, and Sphingomonas.) was increased. The strategy decreased the abundance of Fusarium spp. and Phytophthora spp. by 49.41–90.07% and 43.34–89.21%, respectively. Compared with other treatments, the combination decreased the ginger mortality by 5.70–57.02% and increased the growth of ginger plants and yield by 3.58–139.96%, and 13.11–399.74%, respectively. This study highlights a prospect to promote ginger growth and yield by blocking the transmission of primary infection pathogens in ginger cultivation and improving soil ecological environment. Full article

Background/Objectives: Emotion classification based on eye-movement features has become a widely adopted approach due to the simplicity of data acquisition and the strong association between ocular responses and emotional states. However, several challenges remain with regard to existing emotion recognition methods, including the relatively weak correlation between eye-movement features and emotional labels and the fact that the key features are not prominently presented. Methods: To address abovelimitations, this study proposes an improved CNN-transformer combined with enhanced deep canonical correlation analysis network (ICTD). The proposed method first performs preprocessing and reconstruction of raw eye-movement signals to extract informative features. Subsequently, convolutional neural networks (CNNs) and transformer architectures are employed to capture local and global feature, respectively. In addition, an incremental feature feedforward network is incorporated to enhance the transformer, enabling the model to assign higher importance to salient feature information. Finally, the extracted representations are processed through deep canonical correlation analysis based on cosine similarity in order to generate classification outcomes. Results: Experiments conducted on the SEED-IV, SEED-V, and eSEE-d datasets demonstrate that the proposed ICTD framework consistently outperforms baseline approaches and attains optimal classification results. (1) On the eSEE-d dataset, the results of three-category arousal and valence classification reach 81.8% and 85.2%, respectively; (2) on the SEED-IV dataset, the emotion four-category classification result reaches 91.2%; (3) finally, on the SEED-V dataset, the emotion five-category classification result reaches 85.1%. Conclusions: The proposed ICTD framework effectively improves feature representation and classification performance, showing strong potential for practical emotion recognition and physiological signal analysis. Full article

Spiny lobster aquaculture in Southeast Asia represents one of the most economically valuable and socially important forms of small-scale coastal aquaculture globally. Unlike most aquaculture sectors, production in Vietnam, Indonesia, and the Philippines has developed almost entirely on the basis of wild-caught pueruli (postlarval lobsters) rather than hatchery-produced seed. This reliance on wild seed has generated persistent debate regarding biological sustainability, environmental risk, and compatibility with responsible aquaculture principles. Here, we synthesise more than two decades of regional production data, fisheries observations, larval biology research, population genetics, and oceanographic modelling to evaluate the sustainability of puerulus fishing in Southeast Asia. Evidence indicates that many major settlement areas function as recruitment sinks, characterised by extremely high natural mortality and weak coupling between local settlement and local adult spawning biomass. Under these conditions, harvesting pueruli prior to inevitable natural mortality is unlikely to reduce adult lobster stocks when spatially targeted and appropriately regulated. We further demonstrate that puerulus fisheries exhibit exceptionally low environmental impact while underpinning substantial livelihood benefits for coastal communities. We conclude that wild seed fisheries, when embedded within effective governance frameworks, represent a legitimate and sustainable foundation for crustacean aquaculture during the transition toward commercial hatchery technologies. Full article

Cadmium (Cd) contamination severely threatens crop productivity and food safety, particularly in maize (Zea mays L.), which exhibits relatively high capacities for metal uptake and translocation. Metal tolerance proteins (MTPs) play essential roles in metal homeostasis and detoxification; however, the functions of maize MTP under Cd stress remain poorly understood. In this study, a comprehensive expression analysis of the maize MTP gene family revealed that two Zn-CDF members, ZmMTP1-1 and ZmMTP1-2, displayed the strongest and most consistent transcriptional induction in response to Cd stress, especially in roots. Phylogenetic and structural analyses confirmed that both genes are closely related to MTP1 homologs from other plant species, while exhibiting distinct gene structures and regulatory features. Functional characterization in transgenic Arabidopsis thaliana demonstrated that overexpression of ZmMTP1-1 or ZmMTP1-2 significantly enhanced tolerance to Cd and Zn stress, as reflected by improved seed germination, root growth, survival, and biomass accumulation. Enhanced metal tolerance was associated with elevated antioxidant enzyme activities, reduced oxidative damage, and coordinated upregulation of endogenous metal transporter genes. Moreover, heterologous expression of ZmMTP1-1 in yeast further supported its conserved role in Cd tolerance. Collectively, these findings indicate that ZmMTP1-1 and ZmMTP1-2 contribute to Cd detoxification through coordinated metal transport and stress-response pathways, providing potential genetic resources for improving heavy metal tolerance in maize. Full article