Search Results (3,029)

The detection of trace chemicals at low and ultra-low concentrations is critical for applications in environmental monitoring, medical diagnostics, food safety and other fields. Conventional detection techniques often lack the required sensitivity, specificity, or cost-effectiveness, making real-time, in situ analysis challenging. Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical tool, offering improved sensitivity through the enhancement of Raman scattering by plasmonic nanostructures. While noble metals such as Ag and Au are currently the reference choices for SERS substrates, fabrication methods should balance enhancement efficiency, reproducibility and scalability. In this study, we propose a novel approach for SERS substrate fabrication using reactive Aerosol Jet Printing (r-AJP) as an innovative additive manufacturing technique. The r-AJP process enables in-flight Ag seed reduction and nucleation of Ag nanoparticles (NPs) by mixing silver nitrate and ascorbic acid aerosols before deposition, as suggested by computational fluid dynamics (CFD) simulations. The resulting coatings were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) analyses, revealing the formation of nanoporous crystalline Ag agglomerates partially covered by residual matter. The as-prepared SERS substrates exhibited remarkable SERS activity, demonstrating a high enhancement factor (10⁶) for rhodamine (R6G) detection. Our findings highlight the potential of r-AJP as a scalable and cost-effective fabrication strategy for next-generation SERS sensors, paving the way for the development of a new additive manufacturing tool for noble metal material deposition. Full article

Rice seed storage proteins (SSPs) play a critical role in determining the nutritional quality, cooking properties, and digestibility of rice. To enhance seed quality, CRISPR/Cas9 genome editing was applied to modify SSP composition by targeting genes encoding 13 kDa prolamins and type A glutelins. Three CRISPR/Cas9 constructs were designed: one specific to the 13 kDa prolamin subfamily and two targeting conserved GluA glutelin regions. Edited T₀ and T₁ lines were generated and analyzed using InDel analysis, SDS-PAGE, Bradford assay, and RP-HPLC. Insertions were more frequent than deletions, accounting for 56% and 74% of mutations in prolamin and glutelin genes, respectively. Editing efficiency varied between sgRNAs. All lines with altered protein profiles contained InDels in target genes. SDS-PAGE confirmed the absence or reduction in bands corresponding to 13 kDa prolamins or GluA subunits, showing consistent profiles among lines carrying the same construct. Quantification revealed significant shifts in SSP composition, including increased albumin and globulin content. Prolamin-deficient lines showed reduced prolamins, while GluA-deficient lines exhibited increased prolamins. Total protein content was significantly elevated in all edited lines, suggesting enrichment in lysine-rich fractions. These findings demonstrate that CRISPR/Cas9-mediated editing of SSP genes can effectively reconfigure the rice protein profile and enhance its nutritional value. Full article

The olive oil industry, a key component of Southern Europe’s agricultural sector, generates large amounts of by-products during processing, including olive leaves, branches, stones, and seeds. In the context of growing environmental concerns and limited natural resources—particularly in the Mediterranean regions—there is increasing interest in circular economy approaches that promote the valorization of agricultural residues. These by-products are rich in bioactive compounds, particularly phenolics such as oleuropein and hydroxytyrosol, which are well known for their antioxidant and anti-inflammatory activities. This study aimed to evaluate the phenolic content and antioxidant capacity of by-products from three olive cultivars using high-performance liquid chromatography with photodiode array detection (HPLC–PDA) and mass spectrometry (MS). The leaves and seeds, particularly from the “Cobrança” and a non-identified variety, presented the highest antioxidant activity, as well as the highest concentration of phenolic compounds, demonstrating once again the direct relationship between these two parameters. The identification of the compounds present demonstrated that the leaves and branches have a high diversity of phenolic compounds, particularly secoiridoids, flavonoids, phenylpropanoids, phenylethanoids, and lignans. An inverse relationship was observed between the chlorophyll and carotenoid content and the antioxidant activity, suggesting that phenolic compounds, rather than pigments, are the major contributors to antioxidant properties. Therefore, the by-products of the olive oil industry are a valuable source of sustainable bioactive compounds for distinct industrial sectors, such as the food, nutraceutical, and pharmaceutical industries, aligning with the European strategies for resource efficiency and waste reduction in the agri-food industries. Full article

Vegetable oils are essential for human nutrition and industrial applications. With growing global demand, increasing oil content in oilseed crops has become a top priority. This review synthesizes recent progress in understanding the genetic, environmental, and molecular mechanisms regulating oil content, and presents biotechnological strategies to enhance oil accumulation in major oilseed crops. Oil biosynthesis is governed by intricate genetic–environmental interactions. Environmental factors and agronomic practices significantly impact oil accumulation dynamics. Quantitative trait loci (QTL) mapping and genome-wide association studies (GWAS) have identified key loci and candidate genes involved in lipid biosynthesis pathways. Transcription factors and epigenetic regulators further fine-tune oil accumulation. Biotechnological approaches, including marker-assisted selection (MAS) and CRISPR/Cas9-mediated genome editing, have successfully generated high-oil-content variants. Future research should integrate multi-omics data, leverage AI-based predictive breeding, and apply precision genome editing to optimize oil yield while maintaining seed quality. This review provides critical references for the genetic improvement and breeding of high- and ultra-high-oil-content varieties in oilseed crops. Full article

Compiler optimization is a critical component for improving program performance. However, the Rustc optimization process may introduce vulnerabilities due to algorithmic flaws or issues arising from component interactions. Existing testing methods face several challenges, including high randomness in test cases, inadequate targeting of vulnerability-prone regions, and low-quality initial fuzzing seeds. This paper proposes a test case generation method based on large language models (LLMs), which utilizes prompt templates and optimization algorithms to generate a code relevant to specific optimization passes, especially for real-time control logic and safety-critical modules unique to the industrial control field. A vulnerability screening approach based on static analysis and rule matching is designed to locate potential risk points in the optimization regions of both the MIR and LLVM IR layers, as well as in unsafe code sections. Furthermore, the targeted fuzzing strategy is enhanced by designing seed queues and selection algorithms that consider the correlation between optimization areas. The implemented system, RustOptFuzz, has been evaluated on both custom datasets and real-world programs. Compared with state-of-the-art tools, RustOptFuzz improves vulnerability discovery capabilities by 16%–50% and significantly reduces vulnerability reproduction time, thereby enhancing the overall efficiency of detecting optimization-related vulnerabilities in Rustc, providing key technical support for the reliability of industrial control systems. Full article

Climate change is jeopardizing global food security, with at least 713 million people facing hunger. To face this challenge, legumes as common beans could offer a nature-based solution, sourcing nutrients and dietary fiber, especially for rural communities in Latin America and Africa. However, since common beans are generally heat and drought susceptible, it is imperative to speed up their molecular introgressive adaptive breeding so that they can be cultivated in regions affected by extreme weather. Therefore, this study aimed to couple an advanced panel of common bean (Phaseolus vulgaris L.) × tolerant Tepary bean (P. acutifolius A. Gray) interspecific lines with Bayesian regression algorithms to forecast adaptation to the humid and dry sub-regions at the Caribbean coast of Colombia, where the common bean typically exhibits maladaptation to extreme heat waves. A total of 87 advanced lines with hybrid ancestries were successfully bred, surpassing the interspecific incompatibilities. This hybrid panel was genotyped by sequencing (GBS), leading to the discovery of 15,645 single-nucleotide polymorphism (SNP) markers. Three yield components (yield per plant, and number of seeds and pods) and two biomass variables (vegetative and seed biomass) were recorded for each genotype and inputted in several Bayesian regression models to identify the top genotypes with the best genetic breeding values across three localities on the Colombian coast. We comparatively analyzed several regression approaches, and the model with the best performance for all traits and localities was BayesC. Also, we compared the utilization of all markers and only those determined as associated by a priori genome-wide association studies (GWAS) models. Better prediction ability with the complete SNP set was indicative of missing heritability as part of GWAS reconstructions. Furthermore, optimal SNP sets per trait and locality were determined as per the top 500 most explicative markers according to their β regression effects. These 500 SNPs, on average, overlapped in 5.24% across localities, which reinforced the locality-dependent nature of polygenic adaptation. Finally, we retrieved the genomic estimated breeding values (GEBVs) and selected the top 10 genotypes for each trait and locality as part of a recommendation scheme targeting narrow adaption in the Caribbean. After validation in field conditions and for screening stability, candidate genotypes and SNPs may be used in further introgressive breeding cycles for adaptation. Full article

Background/Objectives: Global warming and rising CO₂ concentrations pose significant challenges to plant systems. Amid these pressures, this study contributes to understanding how tropical species respond by simultaneously evaluating reproductive and genetic traits. It specifically investigates the effects of maternal exposure to warming and elevated CO₂ on progeny physiology, genetic diversity, and population structure in Stylosanthes capitata, a resilient forage legume native to Brazil. Methods: Maternal plants were cultivated under controlled treatments, including ambient conditions (control), elevated CO₂ at 600 ppm (eCO₂), elevated temperature at +2 °C (eTE), and their combined exposure (eTEeCO₂), within a Trop-T-FACE field facility (Temperature Free-Air Controlled Enhancement and Free-Air Carbon Dioxide Enrichment). Seed traits (seeds per inflorescence, hundred-seed mass, abortion, non-viable seeds, coat color, germination at 32, 40, 71 weeks) and abnormal seedling rates were quantified. Genetic diversity metrics included the average (A) and effective (Ae) number of alleles, observed (Ho) and expected (He) heterozygosity, and inbreeding coefficient (Fis). Population structure was assessed using Principal Coordinates Analysis (PCoA), Analysis of Molecular Variance (AMOVA), number of migrants per generation (Nm), and genetic differentiation index (Fst). Two- and three-way Analysis of Variance (ANOVA) were used to evaluate factor effects. Results: Compared to control conditions, warming increased seeds per inflorescence (+46%), reduced abortion (−42.9%), non-viable seeds (−57%), and altered coat color. The germination speed index (GSI +23.5%) and germination rate (Gr +11%) improved with warming; combined treatments decreased germination time (GT −9.6%). Storage preserved germination traits, with warming enhancing performance over time and reducing abnormal seedlings (−54.5%). Conversely, elevated CO₂ shortened GSI in late stages, impairing germination efficiency. Warming reduced Ae (−35%), He (−20%), and raised Fis (maternal 0.50, progeny 0.58), consistent with the species’ mixed mating system; A and Ho were unaffected. Allele frequency shifts suggested selective pressure under eTE. Warming induced slight structure in PCoA, and AMOVA detected 1% (maternal) and 9% (progeny) variation. Fst = 0.06 and Nm = 3.8 imply environmental influence without isolation. Conclusions: Warming significantly shapes seed quality, reproductive success, and genetic diversity in S. capitata. Improved reproduction and germination suggest adaptive advantages, but higher inbreeding and reduced diversity may constrain long-term resilience. The findings underscore the need for genetic monitoring and broader genetic bases in cultivars confronting environmental stressors. Full article

Tomato processing waste (TPW) represents a valuable but underutilized by-product of the food industry with potential for valorization within bioeconomy models. This study investigated the chemical composition, antioxidant profile, and sanitary safety of TPW, analyzing the whole TPW; its fractions (peels and seeds) and oil are obtained from TPW seeds. All samples showed contaminant levels within regulatory limits, confirming their safety for further applications. Various drying methods (air-drying at 70 °C and at 50 °C, lyophilization and vacuum drying) and grinding intensities were evaluated to determine their impact on TPW bioactive compounds retention and organoleptic characteristics. TPW exhibited valuable nutritional properties, particularly high protein and dietary fiber content while TPW oil was characterized with high monounsaturated fatty acid content. Results demonstrated that drying method and particle size significantly influenced the yield of bioactive compound and organoleptic properties, with either lyophilization or vacuum drying and finer milling generally enhancing the recovery of polyphenols, β-carotene, and lycopene and improving color intensity. This research provides the first characterization of the TPW obtained from Croatian indigenous tomato varieties, establishing a scientific foundation for its sustainable valorization and, in broader terms, supporting circular economy objectives and contributing to more resource-efficient food systems. Full article

The Tree–Seed Algorithm (TSA) is a symmetry-driven metaheuristic algorithm that shows potential for complex optimization problems, but it suffers from local optimum entrapment and slow convergence. To address these limitations, we propose the ADTSA algorithm. First, ADTSA adopts a symmetry-driven dual-layer framework for seed generation, which promotes effective information exchange between subpopulations and accelerates convergence speed. In later iterations, ADTSA enhances the population’s exploitation ability through a population fusion mechanism, further improving the convergence speed. Moreover, we propose a historical optimal solution archiving and replacement mechanism, along with a t-distribution perturbation mechanism, to enhance the algorithm’s ability to escape local optima. ADTSA also strengthens population diversity and avoids local optima through convex lens symmetric reverse generation based on the optimal solution. With these mechanisms, ADTSA converges more effectively to the global optimum during the evolutionary process. Tests on the IEEE CEC 2014 benchmark functions showed that ADTSA outperformed several top-performing algorithms, such as LSHADE, JADE, LSHADE-RSP, and the latest TSA variants, and it also excelled in comparison with other optimization algorithms, including GWO, PSO, BOA, GA, and RSA, underscoring its robust performance across diverse testing scenarios. The proposed ADTSA’s applicability in solving complex constrained problems was also validated, with the results showing that ADTSA achieved the best solutions for these complex problems. Full article

Stipagrostis pennata is an important plant in desert ecosystems. Its seed-endophytic bacteria may play a critical role in plant growth and environmental adaptation processes. This study systematically analyzed the community composition and potential plant growth-promoting (PGP) functions of seed-endophytic bacteria associated with S. pennata. The results showed that while the overall diversity of bacterial communities from different sampling sites was similar, significant differences were observed in specific functional genes and species abundances. Nine endophytic bacterial strains were isolated from the seeds, among which Bacillus altitudinis strain L7 exhibited phosphorus solubilizing capabilities, nitrogen fixing, IAA production, siderophore generation, and multi-hydrolytic enzyme activities. Additionally, the genomic sequencing of L7 revealed the key genes involved in plant growth promotion and environmental adaptation, including Na⁺ efflux systems, K⁺ transport systems, compatible solute synthesis genes, and the gene clusters associated with nitrogen metabolism, IAA synthesis, phosphate solubilization, and siderophore synthesis. Strain L7 exhibits salt and osmotic stress tolerance while promoting plant growth, providing a promising candidate for desert microbial resource utilization and plant biostimulant development. Full article

A typical seed of rice (Oryza sativa L.) gives rise to a single seedling. In contrast, seeds from multiple embryos may develop into two or more seedlings, one of which is generated via sexual reproduction, while the others are likely to originate through apomictic pathways. Therefore, the occurrence of multiple embryos is often considered a hallmark of apomixis in rice. Apomixis refers to an asexual reproductive strategy wherein unreduced gametes form through modified meiosis (apomeiosis) without fertilization, thereby generating clonal offspring generally genetically identical to the maternal plant. This process is of great relevance in fixing heterosis in hybrid rice breeding. This review discusses the origin, frequency, genetic regulation, and candidate genes related to multiple embryos in rice and provides a systematic summary of the latest research advances in rice apomixis. The insights presented in this study provide a theoretical foundation for the application of apomixis in rice breeding. Full article

Seed germination and early seedling growth are pivotal stages that define crop establishment and yield potential. Conventional agrochemicals used to improve these processes often raise environmental concerns, highlighting the need for sustainable alternatives. In this study, we demonstrated that water treated with cylindrical dielectric barrier discharge (c-DBD) plasma, enriched with nitric oxide (NO) and reactive nitrogen species (RNS), markedly enhanced onion (Allium cepa) seed germination and seedling vigor. The plasma-treated water (PTW) promoted rapid imbibition, broke dormancy, and accelerated germination rates beyond 98%. Seedlings irrigated with PTW exhibited significantly increased biomass, root and shoot length, chlorophyll content, and antioxidant enzyme activities, accompanied by reduced lipid peroxidation. Transcriptomic profiling revealed that PTW orchestrated a multifaceted regulatory network by upregulating gibberellin biosynthesis genes (GA3OX1/2), suppressing abscisic acid signaling components (ABI5), and activating phenylpropanoid metabolic pathways (PAL, 4CL) and antioxidant defense genes (RBOH1, SOD). These molecular changes coincided with elevated NO₂⁻ and NO₃⁻ levels and finely tuned hydrogen peroxide dynamics, underpinning redox signaling crucial for seed activation and stress resilience. Our findings establish plasma-generated NO-enriched water as an innovative, eco-friendly technology that leverages redox and hormone crosstalk to stimulate germination and early growth, offering promising applications in sustainable agriculture. Full article

Directed grey-box fuzzers focus on testing specific target code. They have been utilized in various security applications, such as reproducing known crashes and identifying vulnerabilities resulting from incomplete patches. Distance-guided directed fuzzers calculate the distance to the target node for each node in a CFG or CG, which has always been the mainstream in this field. However, the distance can only reflect the relationship between the current node and the target node, and it does not consider the impact of the reaching sequence before the target node. To mitigate this problem, we analyzed the properties of the instrumented function’s call graph after selective instrumentation, and the complexity of reaching the target function sequence was estimated. Assisted by the sequence complexity, we proposed a two-stage function call sequence-based seed-scheduling strategy. The first stage is to select seeds with a higher probability of generating test cases that reach the target function. The second stage is to select seeds that can generate test cases that meet the conditions for triggering the vulnerability as much as possible. We implemented our approach in SEZZ based on SelectFuzz and compare it with related works. We found that SEZZ outperformed AFLGo, Beacon, WindRanger, and SelectFuzz by achieving an average improvement of 13.7×, 1.50×, 9.78×, and 2.04× faster on vulnerability exposure, respectively. Moreover, SEZZ triggered three more vulnerabilities than the other compared tools. Full article

Fall detection is a critical task in healthcare monitoring systems, especially for elderly populations, for whom timely intervention can significantly reduce morbidity and mortality. This study proposes a privacy-preserving and scalable fall-detection framework that integrates federated learning (FL) with transfer learning (TL) to train deep learning models across decentralized data sources without compromising user privacy. The pipeline begins with data acquisition, in which annotated video-based fall-detection datasets formatted in YOLO are used to extract image crops of human subjects. These images are then preprocessed, resized, normalized, and relabeled into binary classes (fall vs. non-fall). A stratified 80/10/10 split ensures balanced training, validation, and testing. To simulate real-world federated environments, the training data is partitioned across multiple clients, each performing local training using pretrained CNN models including MobileNetV2, VGG16, EfficientNetB0, and ResNet50. Two FL topologies are implemented: a centralized server-coordinated scheme and a ring-based decentralized topology. During each round, only model weights are shared, and federated averaging (FedAvg) is applied for global aggregation. The models were trained using three random seeds to ensure result robustness and stability across varying data partitions. Among all configurations, decentralized MobileNetV2 achieved the best results, with a mean test accuracy of 0.9927, F1-score of 0.9917, and average training time of 111.17 s per round. These findings highlight the model’s strong generalization, low computational burden, and suitability for edge deployment. Future work will extend evaluation to external datasets and address issues such as client drift and adversarial robustness in federated environments. Full article

Isatis tinctoria L. (Brassicaceae), also known as woad or dyer’s woad, is an ancient plant with a rosy future ahead. Most of the knowledge about woad is related to indigo dye production and its medicinal applications, especially its leaves. The general interest in woad has decreased with the rise of petroleum-based products. However, nowadays this plant is attracting interest again with industries reintroducing natural dyes. To meet the market demand in a sustainable manner, recent studies have focused specifically on woad seeds, leading to a valorization of the whole woad plant. This review provides an overview of the botanical, phytochemical composition, and properties of woad seeds, primarily supporting their cosmetic and pharmaceutical potential. From a chemical point of view, woad seeds mainly contain fatty acids, amino acids, phytosterols and glucosinolates. These compounds have been investigated through their extraction and analytical methods, as well as their properties and industrial applications. Full article