Search Results (36,167)

Blockchain technology (BCT) is often discussed as digital support for timber traceability in the context of the EU Deforestation-Free Products Regulation (EUDR), which requires operators and traders to demonstrate legality, deforestation-free production, geolocation at the forest parcel level, and verifiable supply chain documentation from 30 December 2026, with an extended timeline for micro, small, and medium-sized enterprises (SMEs) until 30 June 2027. This study assesses where BCT can realistically add value in timber supply chains under operational forestry conditions and identifies the necessary technical, organizational, and legal prerequisites. A combination of a targeted literature review and empirical input from experts in the forestry and timber industry, including guided expert web-conferencing interviews (n = 41), an online survey (n = 69 completed responses), and a transdisciplinary workshop (n = 18) was utilized to obtain a comprehensive overview of industry perspectives. Qualitative data from interviews and workshop sessions were analyzed using structured qualitative content analysis, while survey data were evaluated using descriptive statistics. The expected benefits are associated with the introduction of tamper-proof timber harvesting practices and cross-organizational verification mechanisms. To address the discrepancy between biological uncertainty and digital rigidity, the study proposes a dynamic allocation model adapted from the energy sector that distinguishes between fixed and variable wood capacities to automate logistical planning via smart contracts. However, respondents emphasize that practical obstacles, such as limited digital maturity in forestry, fragmented data infrastructures across the supply chain, and unresolved issues of data sovereignty hinder the implementation of BCT. BCT alone is unable to resolve the problem of weak physical-digital identity continuity, a phenomenon widely known as the oracle problem; however, coupling the ledger with physical or biological anchors (e.g., photo-optical, automated inkjet marking identification) can re-establish this physical–digital continuity and thereby resolve the oracle problem. The results demonstrate that blockchain acts most plausibly as a supporting component within hybrid traceability architectures that prioritize event-based authentication, off-chain data processing where appropriate, and integration with existing certification systems. The study highlights the necessity of defining distinct organizational roles and responsibilities while integrating user-centric digital solutions tailored specifically to small and medium-sized enterprises (SMEs). Full article

Background: Lactiplantibacillus plantarum is a widely studied probiotic species; however, probiotic characteristics and safety profiles are strain-specific, requiring independent evaluation. This study characterized Lactiplantibacillus plantarum ATA-LPC98052 as a candidate probiotic raw material. Methods: ATA-LPC98052 was evaluated for hemolysis, acid/bile tolerance, Caco-2 adhesion, cytotoxicity, and storage stability. Subacute oral safety was assessed in Wistar rats by gavage for 28 days at 1.2 × 10¹¹ CFU/kg/day; the study design incorporated selected principles of OECD Test Guideline 407. Clinical, hematological, biochemical, organ-weight, and macroscopic endpoints were evaluated. Fecal microbiota was analyzed by 16S rRNA sequencing; WGS was used for taxonomic confirmation and genomic safety screening. Results: ATA-LPC98052 was γ-hemolytic and maintained 60% viability at pH 1.5 and 96% at pH 5.0, while viability ranged from 74% to 82% across 0.1–0.5% bile salt concentrations. Caco-2 cell viability was 99%, adhesion exceeded 90%, and the lyophilized preparation remained stable for 15 months, maintaining 9.6 log₁₀ CFU/g. Repeated oral administration caused no mortality or consistent treatment-related toxicological pattern. Longitudinal microbiota analysis showed no significant treatment × time effects on alpha diversity or Bray–Curtis community structure, and no genus-level MaAsLin2 association was FDR-significant. WGS confirmed L. plantarum identity and no contamination; ResFinder detected no acquired antimicrobial resistance determinants meeting specified thresholds, whereas CARD/RGI identified low-identity qacJ and vanY homologs requiring cautious interpretation. Conclusion: ATA-LPC98052 demonstrated favorable in vitro probiotic characteristics, technological stability, gut microbiota-modulating potential, and a favorable subacute safety profile under the tested conditions; however, microbiota findings were exploratory, and phenotypic MIC testing remains warranted. Full article

Lung cancer is currently the most frequently diagnosed malignancy worldwide, accounting for approximately 12.4% of all cancers and, despite major advances in molecularly targeted therapies and immunotherapy, represents the leading cause of cancer-related mortality, In recent years, antibody–drug conjugates (ADCs) have emerged as a novel therapeutic strategy, combining the specificity of monoclonal antibodies with the potent cytotoxic activity of highly active payloads to selectively target tumor cells while limiting systemic toxicity. This narrative review summarizes the current role of ADCs in lung cancer, with particular focus on their structural components, mechanisms of action, and the biological features that determine treatment efficacy. We discuss the rationale for targeting established and emerging antigens in non-small cell and small cell lung cancer, including HER2, TROP2, c-MET, HER3, CEACAM5, DLL3, and other promising targets currently under clinical investigation. The principal mechanisms of primary and acquired resistance are also reviewed, including antigen modulation, altered intracellular trafficking, lysosomal dysfunction, drug efflux, tumor microenvironment-mediated immune suppression, and intratumor heterogeneity. In addition, we provide an overview of the safety profile of ADCs, highlighting the most clinically relevant adverse events and their underlying biological mechanisms. We also examine the evolving landscape of predictive biomarkers beyond antigen expression, including genomic, transcriptomic, proteomic, and liquid biopsy-based approaches, together with emerging spatial and single-cell technologies that may improve patient selection. Finally, we discuss future directions in the field, including novel payloads, next-generation linker technologies, bispecific ADCs, combination strategies, and personalized ADC development. Overall, ADCs are rapidly reshaping the therapeutic landscape of lung cancer. Continued optimization of drug design, biomarker-driven patient selection, and a deeper understanding of resistance mechanisms will be essential to fully realize their clinical potential. Full article

Mpox has emerged as a global public health concern, highlighting the limitations of traditional vaccinia-based vaccination strategies and the urgent need for precision vaccinology approaches. Advances in structural virology and immunoinformatics have enabled the identification of conserved immunodominant antigens from both mature virion and extracellular virion forms, supporting the development of multivalent antigen combinations capable of inducing broad neutralizing antibody (nAb) responses. Emerging delivery technologies including mRNA-lipid nanoparticles, viral vectors, and self-assembling protein nanoparticles offer rapid scalability, enhanced immunogenicity, and improved safety compared with conventional live-attenuated vaccines. Addressing antigenic evolution, vaccine supply limitations, and population-specific immune variability will be crucial for optimizing vaccine effectiveness. This review synthesizes current evidence on antigen design, vaccine delivery platforms, and immunological correlates of protection to outline a framework for next-generation mpox vaccines. Precision vaccinology therefore represents a transformative strategy for developing durable, clade-specific mpox vaccines and strengthening preparedness against future orthopoxvirus outbreaks worldwide. Full article

Sodium-ion batteries (SIBs) have emerged as a highly promising candidate for large-scale energy storage and low-temperature (LT) applications, featuring abundant raw materials, low cost and working mechanisms analogous to lithium-ion batteries (LIBs). Although the ionic radius of Na⁺ is slightly larger than that of Li⁺, their smaller Stokes radius and lower desolvation energy barrier endow SIBs with unique thermodynamic advantages in LT environments. However, under extremely LT conditions, issues such as a sharp increase in electrolyte viscosity, sluggish desolvation kinetics, lattice distortion and detrimental phase transitions in electrode materials, as well as instability at the electrode–electrolyte interface, collectively constrain the LT electrochemical performance of SIBs. Most existing literature merely conduct fragmented and decoupled summaries focusing on a single component (electrolyte, cathode or anode), lacking systematic elucidation of the multi-factor coupled degradation mechanism under LT conditions and holistic evaluation of multi-dimensional modification strategies. To fill this research gap, this work systematically elaborates the intrinsic LT degradation mechanism of SIBs driven by multi-physical-field coupling. From four core perspectives, including electrolyte engineering, cathode modification, anode structural construction and precise interface regulation, we comprehensively summarize mainstream technical systems for LT performance enhancement at the current stage, and thoroughly analyze the working principle, technical merits and inherent limitations of various modification approaches. Finally, the future development directions of SIBs are prospected on the basis of previous research, aiming to provide systematic and scientific theoretical guidance for in-depth mechanism exploration and industrial technological upgrading of wide-temperature-range, high-performance SIBs. Full article

Artificial intelligence (AI) is increasingly integrated into higher education; however, limited empirical evidence explains how technology-acceptance perceptions are linked to sustainable learning outcomes through Creative Learning, AI Literacy, and Ethical Awareness, particularly in military higher education. This study examines the relationships among AI Perceived Usefulness, Perceived Ease of Use, AI System Quality, Creative Learning, AI Literacy, Ethical Awareness, and Sustainable Learning Outcomes by integrating the Technology Acceptance Model, Constructivist Learning Theory, and the Sustainable Education Framework. A cross-sectional survey was conducted among 250 undergraduate cadets at the Lithuanian Military Academy. The proposed model was evaluated using covariance-based structural equation modelling, bootstrap mediation analysis, moderation analysis, and one-way analysis of variance. The results provide substantial support for the proposed relationships. AI Perceived Usefulness and Perceived Ease of Use were positively related to Creative Learning, while AI System Quality was positively related to AI Literacy. Creative Learning and AI Literacy, in turn, showed significant positive relationships with Sustainable Learning Outcomes. Creative Learning partially mediated the relationship between AI Perceived Usefulness and Sustainable Learning Outcomes, whereas AI Literacy mediated the relationship between AI System Quality and Sustainable Learning Outcomes. Ethical Awareness showed both a significant direct relationship with Sustainable Learning Outcomes and a moderating effect on the Creative Learning–Sustainable Learning Outcomes relationship. Significant differences were also observed across academic-year cohorts. Overall, the findings extend technology-acceptance research by showing how pedagogical, competency-related, and ethical dimensions are jointly related to Sustainable Learning Outcomes in military higher education. Full article

Retrieval-augmented generation has emerged as a core technological paradigm for addressing the bottlenecks of hallucinations and knowledge lag in large language models. However, many existing reviews focus on a single technical branch or vertical application scenario, making only scattered references to hardware, evaluation methods, and cross-industry empirical evidence, and lacking a systematic, end-to-end integration. This paper conducts research based on a total of 115 papers, comprising foundational literature from 1998–2019 and core RAG literature from 2020–2026, systematically cataloging end-to-end technologies and supporting solutions, establishing a quantitative hardware comparison table and comparing 11 categories of open-source and commercial APIs, constructing a two-tier, four-level standardized evaluation framework, and compiling empirical evidence and implementation challenges across eight industries from 2024 to 2026. Based on this, the paper identifies four major structural contradictions—the retrieval–creation trade-off, the geometric–semantic misalignment as a symmetry problem between representation space and semantic structure, the autonomy–reliability paradox, and evaluation blind spots—as a unified analytical framework for the five major technological strands. Finally, this paper proposes four research directions for practical implementation—differentiable joint optimization, hybrid geometric space learning, interpretable causal reasoning, and multidimensional diagnostic evaluation—providing a systematic reference for both theoretical research on RAG and its deployment in the private sector. Full article

Collagen functional fragments retain selected activities of parent collagens while allowing greater flexibility in sequence design and precision fermentation. Although recent reviews have covered recombinant collagen production technologies, expression platforms, purification strategies, quality control, and biomedical applications, fragment selection, host–process matching, production, and characterization have received less integrated attention. This review focuses primarily on collagen-derived functional fragments, while collagen-mimetic peptides and collagen-like proteins are discussed as related design systems. The biological basis for fragmentation includes receptor-recognition motifs, matrikines and matricryptins, and basement membrane-derived fragments. The review further examines how motif context, Gly-X-Y organization, stabilizing sequence features, protease susceptibility, post-translational modification requirements, and host compatibility influence fragment stability, expression performance, production feasibility, and product integrity. Microbial production using Escherichia coli, Komagataella phaffii, and Saccharomyces cerevisiae is discussed from the perspectives of construct–host matching, secretory or intracellular production, prolyl 4-hydroxylase configuration, fermentation optimization and scale-up, and product characterization. Finally, we discuss AI-assisted, quality-guided design-build-test-learn workflows that integrate computational prediction, curated structural, extracellular-matrix, interaction, and protease resources, two-tier candidate evaluation, and format-appropriate experimental testing to support iterative sequence, host, and process optimization. The development of collagen functional fragments therefore depends on coordinated optimization of biological function, molecular design, microbial host performance, fermentation processes, and product characterization. Full article

This perspective consolidates recent advances that position plasma and metamaterials as a unified metasystem for next-generation space micropropulsion systems. The need for new approaches arises because advanced small form-factor satellites and propulsion systems face physical and technological limits of conventional methods, including restricted scalability, limited electromagnetic control, and insufficient efficiency for complex and long-duration missions. These causes motivate the implementation of concepts based on metamaterials, plasma-based subsystems used in unconventional ways, and engineered ionized media. The paper integrates three complementary domains: plasma-enabled fabrication of complex metamaterials, engineered plasma–metamaterial interaction for controlled electromagnetic environments, and structured plasmas functioning as metamaterials with tunable effective properties. Emerging examples include metasurface-assisted waveguides for compact plasma sources, plasma-induced transparency platforms, machine learning-optimized metamaterial absorbers, and inverse-designed plasma metamaterials. Advances in plasma-based additive manufacturing and hierarchical material synthesis further expand the design space for multifunctional architectures, enabling adaptive, efficient and miniaturized propulsion concepts for CubeSat-class and small-satellite systems. Full article

Aquatic ecosystems are increasingly affected by anthropogenic pollution, highlighting the need for efficient and advanced water treatment technologies. Poly(vinyl alcohol-co-vinyl acetate) copolymer (PVA-co-PVAc), a partially hydrolyzed copolymer derived from poly(vinyl acetate), has received limited attention for surface water remediation. To address this gap, PVA-co-PVAc was prepared and evaluated as an alternative material for surface water treatment. The polymer identity was inferred from the synthesis route and degree-of-hydrolysis measurements; comprehensive structural characterization was beyond the scope of the present application-focused study. Physico-chemical and microbiological characterization of water samples collected from six locations in Joumine Dam revealed the highest contamination levels at the dam inlet, indicating a substantial pollution load entering the reservoir. Consequently, water from this site was selected to evaluate the treatment performance of the copolymer. Among the tested copolymer concentrations (0.1%, 0.2%, 0.5%, and 1% w/v), the best performance was achieved at 1% (w/v), resulting in a 93% reduction in total cell density determined by direct microscopic counting, together with significant decreases in turbidity and organic matter and an apparent decrease in fluoride concentration, requiring independent analytical confirmation. These findings demonstrate the potential of PVA-co-PVAc to improve selected surface-water quality parameters under laboratory treatment conditions and support further investigation of this material using natural water matrices. Full article

Climate risk increasingly threatens regional industrial chain resilience, while artificial intelligence (AI) offers new tools for mitigating its effects. Using panel data for 167 Chinese prefecture-level cities from 2008 to 2023, this study examines the impact of climate risk on regional industrial chain resilience and the moderating role of AI. Climate risk significantly weakens resilience, whereas AI mitigates this adverse effect. Both effects are significant in eastern, northeastern, and coastal regions and in large and industrial cities. AI’s moderating role is more pronounced in cities with lower AI development, while heat and drought cause greater damage. The mechanism analysis shows that climate risk significantly inhibits industrial structure upgrading, total factor productivity, and industrial co-agglomeration. AI can alleviate these negative effects. Climate risk also generates negative cross-regional spillovers, whereas AI produces positive moderating spillovers. Both effects are concentrated within the first three years after a shock. These findings clarify how climate risk propagates through industrial chains and demonstrate AI’s value in risk governance, highlighting the need for timely and context-specific deployment of intelligent technologies. Full article

In recent decades, the digital transformation has increasingly influenced structures and practices in community social services in Spain and other European countries. The progressive integration of telecare systems, home automation, mobile applications, and digital tools into the community sphere has enabled the optimisation of certain interventions, but it has also generated ethical dilemmas and new forms of inequality. This article examines how technologies are incorporated into community social services and home care practices in Spain within a context marked by gender, class, and age inequalities. Drawing on qualitative research involving thirty-two interviews with care recipients, carers, and representatives of social organisations, we analyse the socio-technological networks that mediate care, their impact on self-determination, and the limits and resistance to digitalisation. Our findings indicate that, within the community sphere, technologies can only contribute effectively to greater well-being when they are integrated into an ethical framework that prioritises human accompaniment, social co-responsibility, and the recognition of care as a right. We further discuss the tensions faced by cooperative and community organisations in providing sustained inclusive and dignified services within a precarious socio-economic context that highlights shared responsibility. Finally, we offer reflections on technological innovation, advocating for interdisciplinary collaboration that strengthens community networks and advances social justice. Full article

Precision livestock farming (PLF) integrates sensing technologies, data acquisition (DAQ) systems, and machine learning (ML) frameworks to continuously monitor individual animals and support welfare assessment through physiological and behavioral observations. Advances in infrared thermography, radar sensing, vision-based systems, acoustic monitoring, and wearable technologies have substantially expanded the ability to collect high-resolution data describing animal responses to internal and external stimuli. However, despite considerable technological progress, a persistent gap remains between sensing performance demonstrated under controlled experimental conditions and reliable deployment within commercial livestock environments. This gap is characterized by environmental variability, unrestricted animal movement, and operational constraints within commercial environments. Using a structured review methodology, this review examines sensing modalities, embedded DAQ architectures, communication strategies, ML methodologies, data privacy, farmer adoption, and an illustrative engineering workflow through the lens of welfare-relevant physiological characteristics. Emphasis placed on the distinction between direct sensor measurements and the biological processes they represent. Sensor outputs do not directly quantify welfare, stressors, or management outcomes; rather, they provide measurements of physiological and behavioral responses that require appropriate biological context for meaningful interpretation. As a result, welfare assessment does not depend solely on the ability to acquire data, but also on the ability to accurately relate those data to underlying physiological mechanisms. Within this framework, ML serves as a critical bridge between measurement and interpretation by enabling the analysis of complex, multimodal datasets. Future advancement of welfare-oriented PLF systems will require stronger alignment among sensing methodologies, physiological understanding, and practical deployment realities to generate meaningful, scalable, and biologically grounded welfare assessments. Full article

This article presents a critical review of the development of window systems used in civil engineering, interpreting them not as discrete construction products, but as complex technical and material systems whose actual value emerges from the interdependence of structural configuration, material composition, thermal performance, durability, and manufacturing and implementation constraints. The review discusses the evolution of windows from simple envelope elements providing daylight, ventilation, and weather protection into advanced building-envelope systems associated with energy efficiency, occupant comfort, in-service durability, and environmental responsibility. Particular attention is given to the principal families of window systems, including PVC-U, aluminium, timber, steel, façade, hybrid, and composite-based solutions. The analysis shows that improving the thermal insulation of a single component is not, in itself, a sufficient criterion for evaluating system quality. Declared performance may be constrained by thermal bridges at the installation interface, ageing of sealing systems, imperfections in joining processes, material deformation, and difficulties related to repair, disassembly, and recycling. From the perspective of sustainable construction, window systems should therefore be assessed across their whole life cycle, taking into account energy effectiveness, in-service stability, technological feasibility, renovation potential, and the possibility of closing material loops. The review also identifies the need for further research into integrated assessment methods, the long-term durability of advanced frame systems, the role of the window-to-wall interface, and verifiable strategies for circularity. Full article

Confronted with severe global challenges, including water scarcity, excessive use of chemical fertilizers and pesticides, and heavy metal contamination in soils, conventional agricultural technologies exhibit marked limitations in integrated water–fertilizer management and non-point source pollution control. Leveraging their excellent water retention capacity, intelligent sustained-release properties, and environmental responsiveness, hydrogels offer innovative solutions to advance sustainable agricultural development. This review comprehensively outlines the fundamental types, crosslinking mechanisms, and key functional properties of hydrogels, with a focused discussion on their agricultural deployment as high-efficiency soil conditioners, fertilizer vectors, and pesticide carriers; it deciphers the microscopic water-holding mechanisms under the tristate water model, delineates the divergent water-uptake and retention behaviors between ionic and non-ionic hydrogels, and clarifies the cyclic water-holding and release mechanisms of hydrogels during soil amelioration. Thise paper further synthesizes hydrogel-enabled environmental remediation applications, in which heavy metals and pesticide residues in soils and aquatic systems are removed via functional-group coordination adsorption or photocatalytic degradation; concurrently, hydrogels have been shown to activate plant systemic immunity through calcium-signaling pathways, thereby inducing broad-spectrum antiviral defense responses. Moreover, hydrogels can be integrated into precision agriculture frameworks to enable real-time monitoring of crop physiological status and to support targeted irrigation and fertilization management. This work also evaluates the role of hydrogels in promoting seed germination, root system development, crop metabolic regulation, and stress resilience, while introducing tailored application strategies across distinct plant growth stages. Their documented economic advantages include water conservation, enhanced crop yields, reduced dependence on synthetic fertilizers, and lower labor costs. Nevertheless, the large-scale implementation of hydrogels continues to face multifaceted challenges—particularly poor degradability and latent ecological risks, as conventional polyacrylamide (PAM)-based gels resist soil mineralization and retain potentially neurotoxic monomers, leaving a critical gap in multi-annual field data concerning their non-target interference with native soil aggregate evolution, pore distribution, and rhizospheric carbon–nitrogen footprints. Mechanistically, many hydrogels with tensile strengths below 1 MPa are highly susceptible to three-dimensional network collapse under high-salinity osmotic shock and tillage mechanical stress, exhibiting a precipitous drop in water retention after more than three wet–dry cycles due to deficient long-term structural stability. Compounding these technical gaps are elevated production costs and low farmer adoption, driven by the absence of texture-specific performance thresholds—such as an available water increment ≥ 40% for sandy soils—and the lack of established life-cycle cost models and farmer incentive mechanisms for bio-based hydrogels. Moving forward, hydrogel technology should pivot toward materials innovation and cost-reduction engineering to broaden its applicability, employ ≥3-year, multi-habitat regional trials to delineate ecological benefit–risk boundaries, and ultimately position hydrogels as pivotal enablers of sustainable, green agricultural paradigms. Full article