Search Results (9,693)

The genus Quercus is an ecological keystone and economically vital component of Northern Hemisphere forests. While genomic studies have advanced our understanding of its nuclear and chloroplast genomes, the mitochondrial genomes of oaks remain less explored due to their complex evolutionary dynamics, which include extreme size variation, frequent rearrangements, and recurrent horizontal gene transfer. This study presents the assembly, annotation, and comparative analysis of mitogenomes from three closely related Asian oaks—Q. engleriana, Q. kongshanensis, and Q. tungmaiensis—using PacBio HiFi sequencing. The assemblies revealed distinct structural organizations: the Q. engleriana and Q. kongshanensis mitogenomes each comprised one circular contig and one linear contig, whereas the Q. tungmaiensis mitogenome comprised one circular contig and two linear contigs. Comparative analyses revealed variations in codon usage bias, simple sequence repeats, and predicted RNA editing sites. Notably, RNA editing in rps12 was uniquely observed in Q. kongshanensis. Mitochondrial targeting of plastid transcripts constituted 1.39%, 1.79%, and 2.24% of the mitogenomes, respectively. Phylogenetic reconstruction based on mitochondrial PCGs robustly resolved Q. kongshanensis and Q. tungmaiensis as sister species, with all three forming a distinct clade separate from other Quercus species. This study provides comprehensive mitogenomic resources essential for elucidating Quercus evolutionary biology and supporting germplasm development. Full article

Understanding adsorption and interfacial properties of surface-active agents at interfaces is crucial to the formation and stability of colloidal systems such as emulsions and foams. In this work, interfacial tension and viscoelasticity of saponin at the β-pinene/water interface were studied using drop tensiometry and dilational rheology measurement. For comparison, saponin at the air/water interface was also evaluated. Both saponin and β-pinene are bio-based, eco-friendly, and abundant in plants, trees, and agricultural wastes. Results showed that dynamic interfacial tensions σ(t) of saponin adsorbed at β-pinene/water and air/water interfaces could be well described by the Ward and Tordai model, suggesting that the saponin adsorption kinetics at both interfaces are controlled by a kinetically limited mechanism. The equilibrium interfacial pressure π_e data prior to critical micelle concentration (cmc) were adequately fitted by the Gibbs adsorption isotherm. At the β-pinene/water interface, a higher cmc and a larger area per molecule, but a lower π_e, were observed compared to the air/water interface. Interestingly, the dilational moduli of saponin at β-pinene/water increased with increasing oscillating frequency, but with less significant frequency dependence than their counterparts at the air/water interface. The dilational moduli of saponin at β-pinene/water passed through a minimum with increasing saponin bulk concentration, while the air/water interface exhibited a strikingly different trend in terms of concentration dependence and a higher magnitude for the dilational moduli. The correlation between adsorption behaviors and dilational properties of saponin at the two interfaces is discussed. Fundamental knowledge gained from this study will be beneficial for the rational development of new biocompatible emulsions and foam products for more sustainable applications. Full article

Microplastic pollution represents a significant environmental challenge, as microplastics accumulate in effluents and soils, causing serious risks to ecosystems and human health. Efficient removal of these contaminants is essential to mitigate their potential adverse effects. This review summarizes and critically analyses current methods for the removal of microplastics from effluents and soils, focusing on their effectiveness, advantages, and limitations. Conventional techniques—including filtration, flotation, chemical coagulation, flocculation, and adsorption—are discussed in the context of wastewater treatment and soil remediation. Emerging approaches, such as flocculation processes with special focus on the application of bio-based flocculants, are also highlighted as promising solutions. Key challenges in microplastic removal, including the diversity of microplastic types, their small size, and the complexity of environmental matrices, are addressed. This work intends to contribute to the urgent need for further research to develop more efficient and sustainable strategies for microplastic removal from environmental systems. Full article

Lignin is one of the most abundant natural biopolymers and plays a crucial role in the development of safe and sustainable alternatives for healthcare products. In this study, we employed molecular dynamics simulations and free energy calculations to investigate lignin derivatives’ interactions with skin-like membranes. Specifically, we designed a small lignin derivative composed of syringyl and guaiacyl subunits. Our results reveal that molecular size, concentration, and thermal conditions critically influence the insertion, interaction dynamics, and localization behavior of lignin derivatives. Notably, variations in these parameters induce distinct behaviors, including rapid membrane insertion, hydrogen bonding, clustering, and surface adhesion. The findings provide insights into the molecular mechanisms governing lignin derivatives’ interactions with skin-like membranes, with implications for developing bio-based skincare formulations and transdermal delivery systems. Our results highlight the importance of molecular size and concentration in optimizing lignin-derived compounds for dermatological and therapeutic applications. Full article

High energy consumption in Chinese rural residential buildings, caused by rudimentary construction methods and the poor thermal performance of building envelopes, poses a significant challenge to national sustainability and “dual carbon” goals. To address this, this study proposes a comprehensive modeling and analysis framework integrating an improved Bio-inspired Black-winged Kite Optimization Algorithm (IBKA) with Support Vector Regression (SVR). Firstly, to address the limitations of the original B-inspired BKA, such as premature convergence and low efficiency, the proposed IBKA incorporates diversification strategies, global information exchange, stochastic behavior selection, and an NGO-based random operator to enhance exploration and convergence. The improved algorithm is benchmarked against BKA and six other optimization methods. An orthogonal experimental design was employed to generate a dataset by systematically sampling combinations of influencing factors. Subsequently, the IBKA-SVR model was developed for energy consumption prediction and analysis. The model’s predictive accuracy and stability were validated by benchmarking it against six competing models, including GA-SVR, PSO-SVR, and the baseline SVR and so forth. Finally, to elucidate the model’s internal decision-making mechanism, the SHAP (SHapley Additive exPlanations) interpretability framework was employed to quantify the independent and interactive effects of each influencing factor on energy consumption. The results indicate that: (1) The IBKA demonstrates superior convergence accuracy and global search performance compared with BKA and other algorithms. (2) The proposed IBKA-SVR model exhibits exceptional predictive accuracy. Relative to the baseline SVR, the model reduces key error metrics by 37–40% and improves the R² to 0.9792. Furthermore, in a comparative analysis against models tuned by other metaheuristic algorithms such as GA and PSO, the IBKA-SVR consistently maintained optimal performance. (3) The SHAP analysis reveals a clear hierarchy in the impact of the design features. The Insulation Thickness in Outer Wall and Insulation Thickness in Roof Covering are the dominant factors, followed by the Window-wall Ratios of various orientations and the Sun space Depth. Key features predominantly exhibit a negative impact, and a significant non-linear relationship exists between the dominant factors (e.g., insulation layers) and the predicted values. (4) Interaction analysis reveals a distinct hierarchy of interaction strengths among the building design variables. Strong synergistic effects are observed among the Sun space Depth, Insulation Thickness in Roof Covering, and the Window-wall Ratios in the East, West, and North. In contrast, the interaction effects between the Window-wall Ratio in the South and other variables are generally weak, indicating that its influence is approximately independent and linear. Therefore, the proposed bio-inspired framework, integrating the improved IBKA with SVR, effectively predicts and analyzes residential building energy consumption, thereby providing a robust decision-support tool for the data-driven optimization of building design and retrofitting strategies to advance energy efficiency and sustainability in rural housing. Full article

The increasing implementation of drift-reduction regulations in agriculture has driven the widespread adoption of drift-reducing spray nozzles. However, concerns remain about their impact on the biological efficacy of foliar-applied herbicides, particularly at early weed growth stages. This study evaluated the bio-efficiency of various drift-reducing flat-fan nozzles across three weed species (Chenopodium album, Solanum nigrum, and Echinochloa crus-galli), two growth stages, and six herbicides differing in mode of action and formulation properties. Dose–response bioassays were conducted using eight nozzle–pressure combinations under controlled greenhouse conditions. Spray characteristics, including droplet size distribution, coverage, contact angle, and surface tension, were quantified to elucidate interactions affecting herbicide efficacy. The results showed that nozzle effects were more pronounced for high-surface-tension formulations and poorly wettable weed targets. Several coarser droplet drift-reducing nozzles (e.g., ID3, APTJ) showed inferior performance in controlling small C. album and S. nigrum targets with bentazon and erectophile E. crus-galli targets with cycloxydim. At the same time, nozzle choice was less critical for tembotrione and nicosulfuron spray solutions, which have low surface tension. Across weed species, growth stages, and herbicides, nozzles producing finer, slower droplets demonstrated superior and more consistent performance compared to those producing larger, faster droplets. These findings offer science-based guidance for selecting nozzle types that balance drift mitigation with effective weed control under current and future regulatory constraints. Full article

Background: The treatment of cavitated lesions has evolved with minimally invasive dentistry (MID), whereby we can leave demineralized enamel that could potentially be remineralizable with the use of materials such as resin-modified glass ionomer cements (RMGICs) that allow these lesions to be repaired and remineralized while removing less tooth tissue. The aim of our study was to compare the influence of aging on adhesion to sound enamel, demineralized enamel, and the healthy dentin of five RMGICs (Vitremer^®, ACTIVA BioACTIVE Restorative, Riva LC, Ionolux^®, and GC Fuji II LC) and fluoride release. There are currently no studies on adhesion in demineralized enamel. Method: A total of 1035 bovine incisors were analyzed in 45 groups of 23 teeth each. The groups were established based on three factors: time (24 h, 1 month, and 3 months); substrate (sound enamel, demineralized enamel, and healthy dentin); and type of material. In each group, 20 samples underwent shear bond strength (SBS) and fracture type analysis. Adhesive interfaces were observed in three samples from each group using field emission scanning electron microscopy (FESEM). Daily and cumulative fluoride release rates were calculated. Results: Adhesion improved over time on both demineralized and sound enamel. ACTIVA BioACTIVE Restorative had the highest SBS values (33.63 ± 10.69 MPa), and Vitremer^® had the lowest (4.10 ± 4.63). Most fractures were adhesive. Vitremer^® and Ionolux^® showed the highest daily and cumulative fluoride release rates (Vitremer daily (24 h): 225.30 ± 26.28 ppm/g; Vitremer cumulative (30 days): 635.99 ± 305.38 ppm/g; Ionolux daily (24 h): 207.59 ± 48.43 ppm/g; Ionolux cumulative (30 days): 501.21 ± 138.71 ppm/g) and ACTIVA BioACTIVE Restorative showed the lowest (ACTIVA daily (24 h): 10.50 ± 0.85; ACTIVA cumulative (30 days): 39.10 ± 2.16). Conclusions: ACTIVA BioACTIVE Restorative was the material with the best adhesion values on all substrates and at all times, but it showed the lowest fluoride release rates. Full article

The increasing capabilities of Unmanned Aerial Vehicles (UAVs) or drones are opening up diverse business opportunities. Innovations in drones, U-space, and UTM systems are driving the rapid development of new air mobility applications, often outpacing current regulatory frameworks. These applications now span multiple sectors, from infrastructure monitoring to urban parcel delivery, resulting in a projected increase in drone traffic within shared airspace. This growth introduces significant safety concerns, particularly in managing the separation between drones and manned aircraft. Although various research efforts have addressed this deconfliction challenge, a critical need remains for improved automated solutions at both strategic and tactical levels. In response, our SESAR-funded initiative, AI4HyDrop, investigates the application of machine learning to develop an intelligent system for UAV deconfliction. As part of this effort, we conducted a comprehensive literature review to assess the application of Artificial Intelligence (AI) in this domain. The AI algorithms used in drone deconfliction can be categorized into three types: deep learning, reinforcement learning, and bio-inspired learning. The findings lay a foundation for identifying the key requirements of an AI-based deconfliction system for UAVs. Full article

Electronic health records (EHRs) are typically stored in relational databases, making them difficult to query for nontechnical users, especially under privacy constraints. We evaluate two practical clinical NLP workflows, natural language to SQL (NL2SQL) for EHR querying and retrieval-augmented generation for clinical question answering (RAG-QA), with a focus on privacy-preserving deployment. We benchmark nine large language models, spanning open-weight options (DeepSeek V3/V3.1, Llama-3.3-70B, Qwen2.5-32B, Mixtral-8 × 22B, BioMistral-7B, and GPT-OSS-20B) and proprietary APIs (GPT-4o and GPT-5). The models were chosen to represent a diverse cross-section spanning sparse MoE, dense general-purpose, domain-adapted, and proprietary LLMs. On MIMICSQL (27,000 generations; nine models × three runs), the best NL2SQL execution accuracy (EX) is 66.1% (GPT-4o), followed by 64.6% (GPT-5). Among open-weight models, DeepSeek V3.1 reaches 59.8% EX, while DeepSeek V3 reaches 58.8%, with Llama-3.3-70B at 54.5% and BioMistral-7B achieving only 11.8%, underscoring a persistent gap relative to general-domain benchmarks. We introduce SQL-EC, a deterministic SQL error-classification framework with adjudication, revealing string mismatches as the dominant failure (86.3%), followed by query-join misinterpretations (49.7%), while incorrect aggregation-function usage accounts for only 6.7%. This highlights lexical/ontology grounding as the key bottleneck for NL2SQL in the biomedical domain. For RAG-QA, evaluated on 100 synthetic patient records across 20 questions (54,000 reference–generation pairs; three runs), BLEU and ROUGE-L fluctuate more strongly across models, whereas BERTScore remains high on most, with DeepSeek V3.1 and GPT-4o among the top performers; pairwise t-tests confirm that significant differences were observed among the LLMs. Cost–performance analysis based on measured token usage shows per-query costs ranging from USD 0.000285 (GPT-OSS-20B) to USD 0.005918 (GPT-4o); DeepSeek V3.1 offers the best open-weight cost–accuracy trade-off, and GPT-5 provides a balanced API alternative. Overall, the privacy-conscious RAG-QA attains strong semantic fidelity, whereas the clinical NL2SQL remains brittle under lexical variation. SQL-EC pinpoints actionable failure modes, motivating ontology-aware normalization and schema-linked prompting for robust clinical querying. Full article

This study examined the impact of different bio-based and biodegradable mulching films (TSCs) and soil conditioners (SCs) on plant productivity and fruit quality in a tomato cultivation trial under non-irrigated conditions. In particular, different TSCs were developed based on xanthan gum (XG) or gelatine (GEL) mixed with wood fibres (WFs), while SCs were produced using XG and cellulose fibres. A total of 72 plants of Solanum lycopersicum var. cerasiforme were planted. The yield and number of fruits were measured at harvest, followed by physico-chemical analyses, while plant root systems were examined at the end of the experimental period. The results highlighted that the GEL-based TSCs improved the total fruit yield compared to the control (+50% on average). Furthermore, improved fruit yield was also observed for the XG-based SCs when applied in the soil with a higher organic content. Overall, no significant differences in fruit quality (i.e., Brix degree, carotenoids, lutein and potassium content) and plant root system parameters were found for all the treatments applied. At the end of the test, it was noticed that GEL-based films substantially retained their consistency due to their greater density and thickness, while XG-based films were more disintegrated, indicating higher biodegradation. Full article

Profitable dairy farming requires continuous appraisal and adaptation of production systems in response to changing market and agricultural policy conditions. Geopolitical and climate events have exemplified the exposure of farm incomes to the increased volatility associated with often-global market factors. In this context, bio-economic models can be a useful tool for researchers seeking to understand the financial resilience of different production systems to these changing circumstances. The AFBI Dairy Systems Model is presented and used to simulate the impacts of alternative price scenarios for Northern Ireland-based dairy systems. The whole farm model consists of four interdependent components, comprising farm system, animal nutrition, feed supply and financial sub models. The model is used to evaluate how fluctuations in milk, concentrate, fertiliser, contractor, and electricity prices, as well as interest rate changes, affect three distinct production systems. The financial performance of all systems was sensitive to variations in milk and concentrate prices but relatively insensitive to variations in fertiliser, contractor, and electricity prices and interest rate changes. The profitability of a low-output system was less exposed to variations in prices. In contrast, a high-output system was more exposed to price variations. However, a medium-input system was the most profitable across the majority of price scenarios investigated. Full article

This study proposes a Personalized Deep Learning-Based Sleep Recommendation System Using Lifelog Data (PDSRS-LD). Traditional sleep research primarily relies on bio signals such as EEG and ECG recorded during sleep but often fails to sufficiently reflect the influence of daily activities on sleep quality. To address this limitation, we collect lifelog data such as stress levels, fatigue, and sleep satisfaction via wearable devices and use them to construct individual user profiles. Subsequently, real sleep data obtained from an AI-powered motion bed are incorporated for secondary training to enhance recommendation performance. PDSRS-LD considers comprehensive user data, including gender, age, and physical activity, to analyze the relationships among sleep quality, stress, and fatigue. Based on this analysis, the system provides personalized sleep improvement strategies. Experimental results demonstrate that the proposed system outperforms existing models in terms of F1 score and Average Precision (mAP). These results suggest that PDSRS-LD is effective for real-time, user-centric sleep management and holds significant potential for integration into future smart healthcare systems. Full article

For centuries, artisans have resolved intricate engineering conundrums with intuitive ingenuity, bequeathing a legacy of design wisdom that remains largely untapped in contemporary biomimetics. This “anthro-creative” form of biomimicry, deeply embedded within traditional crafts such as Chaozhou woodcarving, is predominantly tacit and qualitative, which has traditionally eluded systematic interpretation. To address this, we propose the Hierarchical Biomimetics-Based Evaluation System (HBBES), a transdisciplinary framework that couples expert-defined hierarchies through the Analytic Hierarchy Process (AHP) with perceptual assessments from one hundred public evaluators via Fuzzy Comprehensive Evaluation (FCE). Applied to canonical works—including the Lobster and Crab Basket (overall score: 4.36/5.00)—the HBBES revealed a striking finding: both expert and public valuations are anchored not in structural hierarchy, but in aesthetic resonance, particularly the craft’s lifelike morphological analogy and nuanced modulation of light. Beyond offering a replicable pathway for translating artisanal intuition into operative design principles, this study proposes a culture-driven paradigm for biomimetics, bridging intangible heritage with technological innovation. Full article

This research presents the study of utilizing the cocoa husk biomass waste to obtain active carbon through carbonization method, followed by chemical–thermal activation. The activated carbon (CH) was characterized using BET, SEM–EDX, XPS, and Raman techniques. The obtained material showed a high specific surface area of 1661 m²·g⁻¹, and XPS confirmed the presence of oxygen-containing surface functionalities. The adsorption of reactive dye Drimaren Red K-7B by CH was studied to assess the impact of the initial concentration in water solution, temperature, and contact time. The adsorbent achieved over 90% removal within three minutes at 40 °C. The experimental data for the adsorption of Drimaren Red K-7B using CH showed a good fit with the Dubinin–Radushkevich isotherm and a pseudo-second-order kinetic model. This research offers a promising approach for advancing the circular economy through the obtaining of eco-friendly adsorbents derived from biomass waste, exhibiting high initial adsorption efficiency and rapid uptake kinetics towards reactive dye. Full article