Search Results (17,897)

This paper introduces a robust and imperceptible video watermarking framework designed for blind extraction in dynamic video environments. The proposed method operates in the spatial domain and combines multiscale perceptual analysis, adaptive Just Noticeable Difference (JND)-based quantization, and temporal redundancy via multiframe embedding. Watermark bits are embedded selectively in blocks with high perceptual masking using a QIM strategy, and the corresponding DCT coefficients are estimated directly from the spatial domain to reduce complexity. To enhance resilience, each bit is redundantly inserted across multiple keyframes selected based on scene transitions. Extensive simulations over 21 benchmark videos (CIF, 4CIF, HD) validate that the method achieves superior performance in robustness and perceptual quality, with an average Bit Error Rate (BER) of 1.03%, PSNR of 50.1 dB, SSIM of 0.996, and VMAF of 97.3 under compression, noise, cropping, and temporal desynchronization. The system outperforms several recent state-of-the-art techniques in both quality and speed, requiring no access to the original video during extraction. These results confirm the method’s viability for practical applications such as copyright protection and secure video streaming. Full article

Streptococcus iniae (S. iniae) is a globally significant aquatic pathogen responsible for severe economic losses in aquaculture. While the S. iniae infection often exhibits distinct seasonal patterns strongly correlated with water temperature, there is limited knowledge regarding the temperature-dependent immune evasion strategies of S. iniae. Our results demonstrated a striking temperature-dependent virulence phenotype, with significantly higher A. latus mortality rates observed at high temperature (HT, 33 °C) compared to low temperature (LT, 23 °C). Proteomic analysis revealed temperature-dependent upregulation of key virulence factors, including streptolysin S-related proteins (SagG, SagH), antioxidant-related proteins (SodA), and multiple capsular polysaccharide (cps) synthesis proteins (cpsD, cpsH, cpsL, cpsY). Flow cytometry analysis showed that HT infection significantly reduced the percentage of lymphocyte and myeloid cell populations in the head kidney leukocytes of A. latus, which was associated with elevated caspase-3/7 expression and increased apoptosis. In addition, HT infection significantly inhibited the release of reactive oxygen species (ROS) but not nitric oxide (NO) production. Using S. iniae cps-deficient mutant, Δcps, we demonstrated that the cps is essential for temperature-dependent phagocytosis resistance in S. iniae, as phagocytic activity against Δcps remained unchanged across temperatures, while NS-1 showed significantly reduced uptake at HT. These findings provide new insights into the immune evasion of S. iniae under thermal regulation, deepening our understanding of the thermal adaptation of aquatic bacterial pathogens. Full article

Urban tourism has evolved into a complex adaptive system, where unregulated expansion disrupts the ecological balance and intensifies resource stress. Understanding the dynamic evolution and resilience mechanisms of the tourism ecological health network (TEHN) is essential for supporting sustainable urban tourism as a coupled human–natural system. Using Shanghai as a case study, we applied the "vigor–organization–resilience–services" (VORS) framework to evaluate ecosystem health, which served as a constraint for constructing the TEHN, using the minimum cumulative resistance (MCR) model for the period from 2001 to 2023. A resilience framework integrating structural and functional dimensions was further developed to assess spatiotemporal evolution and guide targeted enhancement strategies. The results indicated that as ecosystem health degraded, particularly in peripheral areas, the urban TEHN in Shanghai shifted from a dispersed to a centralized structure, with limited connectivity in the periphery. The resilience of the TEHN continued to grow, with structural resilience remaining at a high level, while functional resilience still required enhancement. Specifically, the low integration and limited choice between the tourism network and the transportation system hindered tourists from selecting routes with higher ecosystem health indices. Enhancing functional resilience, while sustaining structural resilience, is essential for transforming the TEHN into a multi-centered, multi-level system that promotes efficient connectivity, ecological sustainability, and long-term adaptability. The results contribute to a systems-level understanding of tourism–ecology interactions and support the development of adaptive strategies for balancing network efficiency and environmental integrity. Full article

Adversarial attacks in Natural Language Processing (NLP) present a critical challenge, particularly in sentiment analysis, where subtle input modifications can significantly alter model predictions. In search of more robust defenses against adversarial attacks on sentimental analysis, this research work introduces two novel defense mechanisms: the Lexicon-Based Random Substitute Model (LRSM) and the Word-Variant Voting Model (WVVM). LRSM employs randomized substitutions from a dataset-specific lexicon to generate diverse input variations, disrupting adversarial strategies by introducing unpredictability. Unlike traditional defenses requiring synonym dictionaries or precomputed semantic relationships, LRSM directly substitutes words with random lexicon alternatives, reducing overhead while maintaining robustness. Notably, LRSM not only neutralizes adversarial perturbations but occasionally surpasses the original accuracy by correcting inherent model misclassifications. Building on LRSM, WVVM integrates LRSM, Frequency-Guided Word Substitution (FGWS), and Synonym Random Substitution and Voting (RS&V) in an ensemble framework that adaptively combines their outputs. Logistic Regression (LR) emerged as the optimal ensemble configuration, leveraging its regularization parameters to balance the contributions of individual defenses. WVVM consistently outperformed standalone defenses, demonstrating superior restored accuracy and F1 scores across adversarial scenarios. The proposed defenses were evaluated on two well-known sentiment analysis benchmarks: the IMDB Sentiment Dataset and the Yelp Polarity Dataset. The IMDB dataset, comprising 50,000 labeled movie reviews, and the Yelp Polarity dataset, containing labeled business reviews, provided diverse linguistic challenges for assessing adversarial robustness. Both datasets were tested using 4000 adversarial examples generated by established attacks, including Probability Weighted Word Saliency, TextFooler, and BERT-based Adversarial Examples. WVVM and LRSM demonstrated superior performance in restoring accuracy and F1 scores across both datasets, with WVVM excelling through its ensemble learning framework. LRSM improved restored accuracy from 75.66% to 83.7% when compared to the second-best individual model, RS&V, while the Support Vector Classifier WVVM variation further improved restored accuracy to 93.17%. Logistic Regression WVVM achieved an F1 score of 86.26% compared to 76.80% for RS&V. These findings establish LRSM and WVVM as robust frameworks for defending against adversarial text attacks in sentiment analysis. Full article

This paper introduces a novel fractional-order model using the Caputo derivative operator to investigate the virus dynamics of adaptive immune responses. Two infection routes, namely cell-to-cell and virus-to-cell transmissions, are incorporated into the dynamics. Our research establishes the existence and uniqueness of positive and bounded solutions through the application of the generalized mean-value theorem and Banach fixed-point theory methods. The fractional-order model is shown to be Ulam–Hyers stable, ensuring the model’s resilience to small errors. By employing the normalized forward sensitivity method, we identify critical parameters that profoundly influence the transmission dynamics of the fractional-order virus model. Additionally, the framework of optimal control theory is used to explore the characterization of optimal adaptive immune responses, encompassing antibodies and cytotoxic T lymphocytes (CTL). To assess the influence of memory effects, we utilize the generalized forward–backward sweep technique to simulate the fractional-order virus dynamics. This study contributes to the existing body of knowledge by providing insights into how the interaction between virus-to-cell and cell-to-cell dynamics within the host is affected by memory effects in the presence of optimal control, reinforcing the invaluable synergy between fractional calculus and optimal control theory in modeling within-host virus dynamics, and paving the way for potential control strategies rooted in adaptive immunity and fractional-order modeling. Full article

Research highlights a growing demand for active, experiential learning methods in higher education, especially in teacher education. While the benefits of parental involvement (PI) are well-documented, Hungary lacks tools to effectively prepare teacher trainees for fostering family–school cooperation. This study addresses this gap by introducing a custom-designed board game as an innovative teaching tool. The game simulates real-world challenges in PI through a cooperative, scenario-based framework. Exercises are grounded in international and national research, ensuring their relevance and evidence-based design. Tested with 110 students, the game’s educational value was assessed via post-gameplay questionnaires. Participants emphasized the strengths of its cooperative structure, realistic scenarios, and integration of humor. Many reported gaining new insights into parental roles and strategies for effective home–school partnerships. Practical applications include integrating the game into teacher education curricula and adapting it for other educational contexts. This study demonstrates how board games can bridge theory and practice, offering an engaging, effective medium to prepare future teachers for the challenges of PI. Full article

Data annotation serves as a critical foundation for artificial intelligence (AI) and machine learning (ML). Recently, AI agents powered by large language models (LLMs) have emerged as effective solutions to longstanding challenges in data annotation, such as scalability, consistency, cost, and limitations in domain expertise. These agents facilitate intelligent automation and adaptive decision-making, thereby enhancing the efficiency and reliability of annotation workflows across various fields. Despite the growing interest in this area, a systematic understanding of the role and capabilities of AI agents in annotation is still underexplored. This paper seeks to fill that gap by providing a comprehensive review of how LLM-driven agents support advanced reasoning strategies, adaptive learning, and collaborative annotation efforts. We analyze agent architectures, integration patterns within workflows, and evaluation methods, along with real-world applications in sectors such as healthcare, finance, technology, and media. Furthermore, we evaluate current tools and platforms that support agent-based annotation, addressing key challenges such as quality assurance, bias mitigation, transparency, and scalability. Lastly, we outline future research directions, highlighting the importance of federated learning, cross-modal reasoning, and responsible system design to advance the development of next-generation annotation ecosystems. Full article

Hydrogels, characterized by their high water content, tunable mechanical properties, and excellent biocompatibility, have emerged as a promising material platform for the preservation of cultural heritage. Their unique physicochemical features enable non-invasive and adaptable solutions for environmental regulation, structural stabilization, and antifungal protection. This review provides a comprehensive overview of recent progress in hydrogel-based strategies specifically developed for the conservation of cultural relics, with a particular focus on antifungal performance—an essential factor in preventing biodeterioration. Current hydrogel systems, composed of natural or synthetic polymer networks integrated with antifungal agents, demonstrate the ability to suppress fungal growth, regulate humidity, alleviate mechanical stress, and ensure minimal damage to artifacts during application. This review also highlights future research directions, such as the application prospects of novel materials, including stimuli-responsive hydrogels and self-dissolving hydrogels. As an early exploration of the use of hydrogels in antifungal protection and broader cultural heritage conservation, this work is expected to promote the wider application of this emerging technology, contributing to the effective preservation and long-term transmission of cultural heritage worldwide. Full article

Rapid urbanization and demographic shifts present significant challenges to spatial justice in green space provision. Traditional static assessments have become increasingly inadequate for guiding park planning, which now requires a dynamic, future-oriented analytical approach. To address this gap, this study incorporates population dynamics into urban park planning by developing a dynamic evaluation framework for park accessibility. Building on the Gaussian-based two-step floating catchment area (Ga2SFCA) method, we propose the human-population-projection-Ga2SFCA (HPP-Ga2SFCA) model, which integrates population forecasts to assess park service efficiency under future demographic pressures. Using neighborhood-committee-level census data from 2000 to 2020 and detailed park spatial data, we identified five types of population change and forecast demographic distributions for both short- and long-term scenarios. Our findings indicate population decline in the urban core and outer suburbs, with growth concentrated in the transitional inner-suburban zones. Long-term projections suggest that 66% of communities will experience population growth, whereas short-term forecasts indicate a decline in 52%. Static models overestimate park accessibility by approximately 40%. In contrast, our dynamic model reveals that accessibility is overestimated in 71% and underestimated in 7% of the city, highlighting a potential mismatch between future population demand and current park supply. This study offers a forward-looking planning framework that enhances the responsiveness of park systems to demographic change and supports the development of more equitable, adaptive green space strategies. Full article

Poly(organo)phosphazenes (PPZs) are increasingly recognized as versatile biomaterials for drug delivery applications in nanomedicine. Their unique hybrid structure—featuring an inorganic backbone and highly tunable organic side chains—confers exceptional biocompatibility and adaptability. Through precise synthetic methodologies, PPZs can be engineered to exhibit a wide spectrum of functional properties, including the formation of multifunctional nanostructures tailored for specific therapeutic needs. These attributes enable PPZs to address several critical challenges associated with conventional drug delivery systems, such as poor pharmacokinetics and pharmacodynamics. By modulating solubility profiles, enhancing drug stability, enabling targeted delivery, and supporting controlled release, PPZs offer a robust platform for improving therapeutic efficacy and patient outcomes. This review explores the fundamental chemistry, biopharmaceutical characteristics, and biomedical applications of PPZs, particularly emphasizing their role in zero-dimensional nanotherapeutic systems, including various nanoparticle formulations. PPZ-based nanotherapeutics are further examined based on their drug-loading mechanisms, which include electrostatic complexation in polyelectrolytic systems, self-assembly in amphiphilic constructs, and covalent conjugation with active pharmaceutical agents. Together, these strategies underscore the potential of PPZs as a next-generation material for advanced drug delivery platforms. Full article

Soil phosphorus (P) availability is an important determinant of productivity in Pinus massoniana (Masson pine) forests. The mechanistic bases governing the physiological and growth responses of Masson pine to varying soil P conditions remain insufficiently characterized. This study aims to decipher the adaptive strategies of Masson pine to different soil P levels, focusing on root morphological–architectural plasticity and the allocation dynamics of nutrient elements and photosynthetic assimilates. One-year-old potted Masson pine seedlings were exposed to four P addition treatments for one year: P0 (0 mg kg⁻¹), P1 (25 mg kg⁻¹), P2 (50 mg·kg⁻¹), and P3 (100 mg kg⁻¹). In July and December, measurements were conducted on seedling organ biomass, root morphological indices [root length (RL), root surface area (RSA), root diameter (RD), specific root length (SRL), and root length ratio (RLR) for each diameter grade], root architectural indices [number of root tips (RTs), fractal dimension (FD), root branching angle (RBA), and root topological index (TI)], as well as the content of nitrogen (N), phosphorus (P), carbon (C), and non-structural carbohydrates (NSCs) in roots, stems, and leaves. Compared with the P0 treatment, P2 and P3 significantly increased root biomass, root–shoot ratio, RL, RSA, RTs, RLR of finer roots (diameter ≤ 0.4 mm), nutrient accumulation ratio in roots, and starch (ST) content in roots, stems and leaves. Meanwhile, they decreased soluble sugar (SS) content, SS/ST ratio, C and N content, and N/P and C/P ratios in stems and leaves, as well as nutrient accumulation ratio in leaves. The P3 treatment significantly reduced RBA and increased FD and SRL. Our results indicated that Masson pine adapts to low P by developing shallower roots with a reduced branching intensity and promoting the conversion of ST to SS. P’s addition effectively alleviates growth limitations imposed by low P, stimulating root growth, branching, and gravitropism. Although a sole P addition promotes short-term growth and P uptake, it triggers a substantial consumption of N, C, and SS, leading to significant decreases in N/P and C/P ratios and exacerbating N’s limitation, which is detrimental to long-term growth. Under high-P conditions, Masson pine strategically prioritizes allocating limited N and SS to roots, facilitating the formation of thinner roots with low C costs. Full article

European pig farmers are challenged by increasingly stringent EU regulations to protect the environment from pollution, to meet animal welfare standards and to make pig farming more sustainable. Economic sustainability is defined as the ability to achieve higher profits by respecting social and natural resources. This study is focused on the analysis of the economic resilience of intensive and extensive farming systems, based on data collected from 56 farms located in Denmark, Poland, Italy and Spain. Productive and economic performances of these farms are analyzed, and economic resilience is assessed through a survey including a selection of indicators, belonging to different themes: [i] resilience of resources, [ii] entrepreneurship, [iii] propensity to extensification. The qualitative data from the questionnaire allow for an exploration of how production systems relate to the three dimensions of resilience. Different levels of resilience were found and discussed for intensive and extensive farms. The findings suggest that intensive farms benefit from high standards and greater bargaining power within the supply chain. Extensive systems can achieve profitability through value-added strategies and generally display good resilience. Policies that support investment and risk reduction are essential for enhancing farm resilience and robustness, while strengthening farmer networks can improve adaptability. Full article

Glioblastoma (GBM) remains one of the most aggressive and treatment-resistant brain tumors, largely due to its profound intratumoral heterogeneity and immunosuppressive microenvironment. Various classifications of GBM subtypes were created based on transcriptional and methylation profiles. This effort, followed by the development of new technology such as single-nuclei sequencing (snRNAseq) and spatial transcriptomics, led to a better understanding of the glioma cells’ plasticity and their ability to transition between diverse cellular states. GBM cells can mimic neurodevelopmental programs to resemble oligodendrocyte or neural progenitor behavior and hitchhike the local neuronal network to support their growth. The tumor microenvironment, especially under hypoxic conditions, drives the tumor cell clonal selection, which then reshapes the immune cells’ functions. These adaptations contribute to immune evasion by progressively disabling T cell and myeloid cell functions, ultimately establishing a highly immunosuppressive tumor milieu. This complex and metabolically constrained environment poses a major barrier to effective antitumor immunity and limits the success of conventional therapies. Understanding the dynamic interactions between glioma cells and their microenvironment is essential for the development of more effective immunotherapies and rational combination strategies aimed at overcoming resistance and improving patient outcomes. Full article

Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disorder characterized by the destruction of insulin-producing pancreatic beta cells, resulting in lifelong insulin dependence. While genetic susceptibility—particularly human leukocyte antigen (HLA) class II alleles—is a major risk factor, accumulating evidence implicates viral infections as potential environmental triggers in disease onset and progression. This narrative review synthesizes current findings on the role of viral pathogens in T1DM pathogenesis. Enteroviruses, especially Coxsackie B strains, are the most extensively studied and show strong epidemiological and mechanistic associations with beta-cell autoimmunity. Large prospective studies—including Diabetes Virus Detection (DiViD), The environmental determinans of diabetes in the young (TEDDY), Miljøfaktorer i utvikling av type 1 diabetes (MIDIA), and Diabetes Autoimmunity Study in the Young (DAISY)—consistently demonstrate correlations between enteroviral presence and the initiation or acceleration of islet autoimmunity. Other viruses—such as mumps, rubella, rotavirus, influenza A (H1N1), and SARS-CoV-2—have been investigated for their potential involvement through direct cytotoxic effects, immune activation, or molecular mimicry. Interestingly, certain viruses like varicella-zoster virus (VZV) and cytomegalovirus (CMV) may exert modulatory or even protective influences on disease progression. Proposed mechanisms include direct beta-cell infection, molecular mimicry, bystander immune activation, and dysregulation of innate and adaptive immunity. Although definitive causality remains unconfirmed, the complex interplay between genetic predisposition, immune responses, and viral exposure underscores the need for further mechanistic research. Elucidating these pathways may inform future strategies for targeted prevention, early detection, and vaccine or antiviral development in at-risk populations. Full article

To further enhance the economic performance of fuel cell vehicles (FCVs), this study develops a model-adaptive model predictive control (MPC) strategy. This strategy leverages the dynamic relationship between proton exchange membrane fuel cell (PEMFC) output characteristics and temperature to track its optimal operating temperature (OOT), addressing challenges of temperature control accuracy and high energy consumption in the PEMFC thermal management system (TMS). First, PEMFC and TMS models were developed and experimentally validated. Subsequently, the PEMFC power–temperature coupling curve was experimentally determined under multiple operating conditions to serve as the reference trajectory for TMS multi-objective optimization. For MPC controller design, the TMS model was linearized and discretized, yielding a predictive model adaptable to different load demands for stack temperature across the full operating range. A multi-constrained quadratic cost function was formulated, aiming to minimize the deviation of the PEMFC operating temperature from the OOT while accounting for TMS parasitic power consumption. Finally, simulations under Worldwide Harmonized Light Vehicles Test Cycle (WLTC) conditions evaluated the OOT tracking performance of both PID and MPC control strategies, as well as their impact on stack efficiency and TMS energy consumption at different ambient temperatures. The results indicate that, compared to PID control, MPC reduces temperature tracking error by 33%, decreases fan and pump speed fluctuations by over 24%, and lowers TMS energy consumption by 10%. These improvements enhance PEMFC operational stability and improve FCV energy efficiency. Full article