Search Results (3,003)

Due to the severe hazard of aflatoxins (AFs) to humans, it is of great significance to detect the key aflatoxins, aflatoxin B₁ (AFB₁) and aflatoxin G₁ (AFG₁), in food and feed in simple, rapid, and semi-quantitative ways. The hybridoma clone 3A1 was prepared in this study, and anti-AFB₁ monoclonal antibody (mAb) with high specificity and affinity (9.38 × 10⁸ L/mol) from 3A1 was purified. The indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) demonstrated that the linear detection range for AFB₁ was 0.029–1.526 ng/mL with a limits of determination (LOD) of 0.023 ng/mL. A latex microsphere-based immunochromatographic test strip (LM-ICTS) was constructed based on 3A1, which showed that the strip could detect AFB₁ (LOD: lower than 1.79 ng/mL) and AFG₁ (LOD: lower than 8.08 ng/mL), and the linear detection ranges for AFB₁ and AFG₁ are 1.79–48.46 ng/mL and 8.08–107.40 ng/mL, respectively. The average recoveries of intra-assay and inter-assay for peanuts were (98.4 ± 4.7)% and (92.6 ± 7.6)%, and the average coefficient of variation (CVs) were 4.38% and 8.15%, respectively. For sunflower seeds, the intra-assay and inter-assay recoveries were (94.4 ± 7.2)% and (89.2 ± 4.3)%, and the average CVs were 6.6% and 4.9%, respectively. In summary, the developed LM-ICTS exhibited excellent sensitivity and specificity, which provided a rapidly stable on-site detection choice for AFB₁ and AFG₁ to contaminated agricultural samples, including grain and feed. Full article

This study explores graph-based methods to model and analyze the semantic interplay between editorial taxonomies and user-generated folksonomies on the PornHub platform, using a dataset of over 97,000 videos (2015–2024). We construct and examine a graph of user-assigned tags and platform-defined categories, applying the Leiden community detection algorithm to uncover latent semantic groupings. To enrich the graph structure, we embed textual metadata using state-of-the-art language models (Qwen3-Embedding-4B and all-MiniLM-L6-v2), enabling the integration of natural language processing within graph-based learning. Our analysis reveals that folksonomies partially align with taxonomies through synonymous structures but also diverge by capturing nuanced attributes such as body features and aesthetic styles. These asymmetries highlight how folksonomies introduce higher-resolution semantic layers absent from fixed-category systems. By fusing graph mining, NLP-driven embeddings, and network-based clustering, this work contributes a hybrid methodology for semantic knowledge extraction in large-scale, user-generated content. It offers implications for graph-based recommendation, content moderation, and metadata enrichment—demonstrating the utility of graph-centric AI techniques in real-world multimedia data settings. Full article

To reduce reflective cracking in asphalt pavements, gravel base layers are commonly employed to disperse stress and delay structural damage. However, the loose nature of gravel bases results in complex interlayer contact conditions, typically involving interlocking between gravel particles in the base and aggregates in the asphalt surface course. In order to accurately simulate this interaction and to improve the interlayer shear performance, a mesoscale finite element model was developed and combined with macroscopic tests. Effects due to the type and amount of binder material, type of asphalt surface layer, and external loading on shear strength were systematically analyzed. The results indicate that SBS (Styrene–Butadiene–Styrene)-modified asphalt provides the highest interlayer strength, followed by SBR (Styrene–Butadiene Rubber)-modified emulsified asphalt and unmodified base bitumen. SBS (Styrene–Butadiene–Styrene)-modified asphalt achieves optimal interlaminar shear strength at a coating rate of 0.9 L/m². Additionally, shear strength increases with applied load but decreases with increasing void ratio and the nominal maximum aggregate size of the surface course in the analyzed spectra. Based on simulation and experimental data, an equivalent macro–meso predictive model relating shear strength to key influencing factors was established. This model effectively bridges mesoscale mechanisms and practical engineering applications, providing theoretical support for the design and performance optimization of asphalt pavements with gravel bases. Full article

The development of renewable fuel-based energy, as well as waste disposal and advanced chemical processes, makes it necessary to use materials with favorable corrosion resistance, especially in high temperature conditions. In such conditions, alloys are subject to degradation, and the rate of the processes depends directly on the state of the material at the beginning of operation and the operating environment conditions. Hence, the 800HT material was selected for the tests, which was subjected to long-term operation in variable ambient conditions. This work aims to reveal the possibility of microstructure recovery in the alloy after long-term operation and subjected to detailed LM and SEM microscopic analysis and corrosion tests in simulated environments. The tests revealed that in long-term operation conditions, periods of temperature exceedance may occur and, as a consequence, unfavorable phases affecting the plasticity of the material, such as σ-phase or M23C6, may be released. In turn, the presence of these phases, mainly at grain boundaries, does not significantly reduce corrosion resistance in nitrogen-rich environments, but causes intensive processes induced by chlorides and sulfates at high temperatures. Full article

An important recent development in the field of linguistics is the use of small language models to investigate language acquisition. Following this line of research, we investigate the mysterious appearance of ‘negative concord’ (e.g., I didn’t do nothing) in the speech of children whose environment offers no exposure to patterns of this sort. Drawing on a 10-million-word version of the BabyLM corpus, we show that the preference for negative concord over patterns involving a single negative (e.g., I did nothing) can be traced to a cognitive force known as biuniqueness, whose effects will be examined with the help of data from both natural speech and a language model. Full article

Quartz is a widely used mineral in dosimetric and geochronological applications due to its stable luminescence properties under ionizing radiation. This study presents an artificial neural network (ANN)-based approach to predict the optically stimulated luminescence (OSL) decay curves of quartz extracted from Mediterranean beach sand samples in Turkey. Experimental OSL signals were obtained from quartz samples irradiated with beta doses ranging from 0.1 Gy to 1034.9 Gy. The dataset was used to train ANN models with three different learning algorithms: Levenberg–Marquardt (LM), Bayesian Regularization (BR), and Scaled Conjugate Gradient (SCG). Forty-seven decay curves were used for training and three for testing. The ANN models were evaluated based on regression accuracy, training–validation–test performance, and their predictive capability for low, medium, and high doses (1 Gy, 72.4 Gy, 465.7 Gy). The results showed that BR achieved the highest overall regression (R = 0.99994) followed by LM (R = 0.99964) and SCG (R = 0.99820), confirming the superior generalization and fits across all dose ranges. LM performs optimally at low-to-moderate doses, and SCG delivers balanced yet slightly noisier predictions. The proposed ANN-based method offers a robust and effective alternative to conventional kinetic modeling approaches for analyzing OSL decay behavior and holds considerable potential for advancing luminescence-based retrospective dosimetry and OSL dating applications. Full article

Education 4.0 promotes active, personalized, and competency-based learning aligned with the Sustainable Development Goals (SDGs), yet most current platforms rely on centralized architectures that restrict access, agency, and adaptability. To address this problem, Web3 technologies—including blockchain, decentralized identifiers (DIDs), peer-to-peer storage, and smart contracts—enable the creation of platforms that uphold equity, data sovereignty, and pedagogical flexibility. This paper investigates how the convergence of Education 4.0 and Web3 technologies can drive the development of sustainable, inclusive, and learner-centered digital education systems. We examine two decentralized education platforms, EtherLearn and DeLMS, to assess their design affordances and limitations. Building on these insights, we propose a layered architectural framework grounded in sustainability principles. Our analysis shows that decentralized infrastructures can expand access in underserved regions, increase credential portability, empower learners with greater autonomy, and foster participatory governance through decentralized voting, token-based incentives, and community moderation. Despite these advantages, significant challenges remain around usability, energy efficiency, and regulatory compliance. We conclude by identifying key research priorities at the intersection of sustainable educational technology, digital equity, and decentralized system design. Full article

Background: With growing evidence regarding long-term clinical results of left main angioplasty, it has become clear that the gap between percutaneous coronary interventions (PCIs) and bypass surgery can be narrowed only by improving the PCI technique. While intravascular ultrasound (IVUS) has become routinely used for this subset of lesions, there is still insufficient data regarding the role of optical coherence tomography (OCT) in left main PCI. Aims: The aim of this study was to investigate the long-term results of OCT-guided PCI in comparison to angiographical guidance alone. Material and methods: We conducted a retrospective single-center high-volume analysis of patients with left main disease treated by PCI. The primary endpoint was all-cause death. Results and discussion: Between January 2013 and January 2024, we enrolled 221 eligible patients with unprotected left main coronary artery disease treated by PCI; among these, 13.1% were treated by OCT-guided PCI and 86.9% by angiographic-guided PCI. At a median follow up of 30.16 months (interquartile range: 14.3–60 months), Kaplan–Meier survival analysis revealed a significantly higher survival probability in the OCT group compared to the non-OCT group (log-rank p = 0.034), with no significant differences between the groups regarding procedural success rate. In the multivariable Cox proportional hazards model, adjusting for other relevant covariates, OCT was borderline non-significantly independently associated with a 63% reduction in mortality (HR = 0.37, p = 0.063). Conclusions: In our study, OCT-guided PCI was associated with early procedural distinctions and a trend toward improved unadjusted survival in LM PCI. The findings highlight the potential procedural advantages of OCT, as well as the need for larger prospective studies to establish its long-term clinical benefits in left main interventions. Full article

Purpose: Evaluate long-term immunogenicity and its association with the number of vaccines and breakthrough infections in patients with hematologic malignancies compared to a healthy cohort. Methods: This study is an amendment of a multicenter study (DRKS00027372) which described the upsurge of anti-spike-IgGs on day 120 from a blunted day-35 response in patients with hematologic neoplasms. In this amendment, 191 individuals from the original study (patients with myeloid and lymphoid neoplasms and controls) were followed beyond month 12 after first SARS-CoV-2-vaccination. The long-term humoral and cellular responses and their correlation with the number of vaccines were studied. Results: After a median follow-up of 18 months, a median of three vaccinations (range 1–5) were given. Antibody levels did not correlate with the number of vaccinations (≤2 versus ≥3) (p = 0.3). With a median of 5274 U/mL anti-spike-IgGs, the inferior day-120 antibody response in patients with lymphoid neoplasms was no longer detected. Breakthrough SARS-CoV-2-infections, mostly mild, occurred in 67% of controls and 46% of patients. Patients with lymphoid neoplasms with two vaccinations did not have more infections compared to patients with more doses (p = 0.4). There was a significant decline in the spike-specific T-cell response for CovCD4⁺ and CovCD8⁺ (p < 0.001). On last assessment, 33% of individuals lost their day-120 CovCD4⁺-positive response (p < 0.001). There was no correlation between the number of vaccinations and cellular immune response in patients and controls (p = 0.3). Conclusions: In this study, breakthrough infections were high despite repeated boosting, which by itself does not lead to an upsurge in the cellular immune response in the majority of patients. Full article

As a core component of industrial robots, the transmission accuracy life (TAL) of rotary vector (RV) reducers constitutes a primary factor determining the high-precision operation of robotic systems. However, current life evaluation methods for RV reducers predominantly rely on conventional bearing strength life calculations, while neglecting its transmission accuracy degradation during operation. To address this limitation, a static analysis model of RV reducers is established, through which a calculation method for transmission accuracy and TAL is presented. Simultaneously, tooth surface and bearing wear models are developed based on Archard’s wear theory. Through coupled analysis of the aforementioned models, the transmission accuracy degradation law of RV reducers is revealed. The results show that during the operation of the RV reducer, the transmission error (TE) maintains relative stability over time, whereas the lost motion (LM) exhibits a continuous increase. Based on this observation, LM is defined as the evaluation metric for TAL, and a novel TAL estimation model is proposed. The feasibility of the developed TAL estimation model is ultimately validated through accelerated transmission accuracy degradation tests on RV reducers. The error between the predicted and experimental results is 11.06%. The proposed TAL estimation model refines the life evaluation methodology for RV reducers, establishing a solid foundation for real-time transmission accuracy compensation in reducer operation. Full article

Retrieval-Augmented Generation (RAG) combined with Large Language Models (LLMs) introduces a new paradigm for clinical-trial data analysis that is both real-time and knowledge-traceable. This study targets a multi-site, real-world data environment. It builds a hierarchical RAG pipeline spanning an electronic health record (EHR), National Health Insurance (NHI) billing codes, and image-vector indices. The LLM is optimized through lightweight LoRA/QLoRA fine-tuning and reinforcement-learning-based alignment. The system first retrieves key textual and imaging evidence from heterogeneous data repositories and then fuses these artifacts into the contextual window for clinical report generation. Experimental results show marked improvements over traditional manual statistics and prompt-only models in retrieval accuracy, textual coherence, and response latency while reducing human error and workload. In evaluation, the proposed multimodal RAG-LLM workflow achieved statistically significant gains in three core metrics—recall, factual consistency, and expert ratings—and substantially shortened overall report-generation time, demonstrating clear efficiency advantages versus conventional manual processes. However, LLMs alone often face challenges such as limited real-world grounding, hallucination risks, and restricted context windows. Similarly, RAG systems, while improving factual consistency, depend heavily on retrieval quality and may yield incoherent synthesis if evidence is misaligned. These limitations underline the complementary nature of integrating RAG and LLM architectures in a clinical reporting context. Quantitatively, the proposed system achieved a Composite Quality Index (CQI) of 78.3, outperforming strong baselines such as Med-PaLM 2 (72.6) and PMC-LLaMA (74.3), and reducing the report drafting time by over 75% (p < 0.01). These findings confirm the practical feasibility of the framework to support fully automated clinical reporting. Full article

This study investigates the use of a local fiber, specifically milkweed that grows in Quebec, Canada, for nonwoven building applications. Milkweed is a natural fiber with an ultra-lightweight hollow structure that provides excellent acoustic and thermal insulation properties. To provide three-dimensional stability to nonwovens, milkweed fibers were blended with a low-melt fiber composed of a polyethylene terephthalate core and a polyolefin sheath (LM 2.2), and polylactic acid (PLA) fibers. Several nonwovens with different fiber contents were manufactured using an air-laid Spike process. The nonwovens were compared with a commercially available thermal insulation material made of 100% hemp. The thermal conductivity and thermal resistance were measured at different temperatures. The sound absorption coefficient of the nonwovens was determined both using an impedance tube and the Johnson–Champoux–Allard (JCA) acoustic model. The results showed that all nonwovens exhibit thermal conductivity values below 70 mW/m·K at temperatures ranging from −4 °C to 24 °C, which are lower than many materials commonly used in building applications. A sample presented a thermal resistance that is 8%, 10%, and 45% higher than those of rock wool, polyisocyanurate (PIR), and fiberglass, respectively. Full article

This work presents an 80 Gbps photonics-aided millimeter-wave (mm Wave) wireless communication system employing 16-Quadrature Amplitude Modulation (16-QAM) and a 1 × 2 single-input multiple-output (SIMO) architecture with maximum ratio combining (MRC) to achieve robust 87.5 GHz transmission over 4.6 km. By utilizing polarization-diverse optical heterodyne generation and spatial diversity reception, the system enhances spectral efficiency while addressing the low signal-to-noise ratio (SNR) and channel distortions inherent in long-haul links. A blind equalization scheme combining the constant modulus algorithm (CMA) and decision-directed least mean squares (DD-LMS) filtering enables rapid convergence and suppresses residual inter-symbol interference, effectively mitigating polarization drift and phase noise. The experimental results demonstrate an SNR gain of approximately 3 dB and a significant bit error rate (BER) reduction with MRC compared to single-antenna reception, along with improved SNR performance in multi-antenna configurations. The synergy of photonic mm Wave generation, adaptive spatial diversity, and pilot-free digital signal processing (DSP) establishes a robust framework for high-capacity wireless fronthaul, overcoming atmospheric attenuation and dynamic impairments. This approach highlights the viability of 16-QAM in next-generation ultra-high-speed networks (6G/7G), balancing high data rates with resilient performance under channel degradation. Full article

Due to insufficient absolute positioning accuracy, industrial robots frequently face challenges in efficiently performing drilling and riveting operations during the assembly of aircraft and other large-scale workpieces. To enhance the absolute positioning accuracy of industrial robots, this paper proposes a novel kinematic calibration method for industrial robots based on the Improved Grey Wolf Optimization (IGWO) algorithm. Specifically, the method employs an enhanced selection and update strategy to avoid convergence stagnation and local optimum traps. The proposed method features a novel boundary search strategy, which leverages the Dimension-oriented Learning (DL) search strategy to enhance search speed and stability. Through parameter identification and calibration experiments, the effectiveness of the method was validated using an ABB IRB4600 industrial robot and a Leica laser tracker. Additionally, compared with the Levenberg–Marquardt (LM) algorithm, Particle Swarm Optimization (PSO), and Genetic Algorithm (GA), the IGWO algorithm demonstrates faster convergence and superior optimization performance. According to the calibration experimental results, by applying the IGWO algorithm, the absolute positioning accuracy of the industrial robot is ultimately improved from 1.918 mm to 0.475 mm and the absolute positioning accuracy is improved by 75.2%. Full article

Nepenthes L. species (tropical pitcher plants) are a classic example of carnivorous plants. The Nepenthes traps are highly specialized pitchers with a zoned structure. On the outer surface of the pitcher, there are nectaries and various types of trichomes, including glandular trichomes. The main aim of our study was to examine these glandular trichome structures and check the distribution of the homogalacturonans (HGs) and hemicelluloses in the cell wall of trichome cells. The structure of Nepenthes bicalcarata Hook. f. and Nepenthes albomarginata T.Lobb ex Lindl. trichomes was analyzed using light and electron microscopy. The antibodies were used against the wall components [anti-pectic homogalacturonans (HGs): JIM5 (low methylesterified HGs), LM19 (low methylesterified HGs), CCRC-M38 (a fully de-esterified HGs), JIM7 (highly esterified HGs), LM20 (esterified HGs), LM5 (galactan) and anti-hemicelluloses: LM25 (xyloglucan), LM15 (galactoxyloglucan), CCRC-M138 (xylan), and LM10 antibody (xylan)]. The localization of the examined compounds was determined using immunohistochemistry techniques. The presence of endodermal and transfer cells supports the idea that peltate trichomes actively transport solutes. Also, the presence of pectic homogalacturonans and hydrophilic hemicelluloses indicates that water or aqueous solutions are transported through the trichomes’ cell walls. Our study supports the idea that these trichomes may act as hydathodes or hydropotes. Full article