Search Results (7,896)

In this study, free vibration analysis of three-layer sandwich panels with cores based on a triply periodic minimum surface (TPMS) and graphene platelet-reinforced composite (GPLRC) faces is performed. Four different geometries including cylindrical, spherical, saddle and flat panels were investigated and the governing equations were solved using higher-order shear deformation theory (HSDT) extracted from Hamilton’s principle. The accuracy and precision of the presented analytical method is verified by comparing the dimensionless natural frequencies with reference studies. Then, the effect of various parameters including panel geometry, core topology type and graphene weight percentage on the vibration response was investigated. The results show that adding graphene to the face layers significantly increases the natural frequencies and improves the overall stiffness of the structure. In addition, the frequencies of the panel may be controlled through different patterns and topologies. Also, double-curved panels, especially spherical geometries, present the highest fundamental natural frequency. The findings of this research could play an important role in the design and performance evaluation of advanced structures with TPMS cores and nanoscale reinforcement. Full article

Manual data storage methods on various mobile devices, IoT devices, and traditional computing platforms still lack sufficient security governance due to the absence of a unified security framework. Unlike application controlled environments, manual storage locations such as file systems, removable media, and IoT devices are highly susceptible to unauthorized access, misuse, and exfiltration. To address this problem, the paper proposes a security framework for manual storage systems using metadata, and the proposed framework includes three different algorithms, namely MARShield, ThreshGuard, and SentinelScheduler. These three algorithms operate together to ensure security for manual storage systems. MARShield is used for enforcing immutable metadata, multi-access rights based on tokens, and persistent source tracking by cryptographically securing provenance logs. ThreshGuard, on the other hand, enables the use of adaptive threshold-based misuse regulation and bottleneck-controlled serialized execution. SentinelScheduler optimizes the use of cryptography by incorporating trust-based application profiling and idle-time scheduling for heavy security operations. The proposed methodology is evaluated using a hybrid approach combining real-world datasets (CIC-IoT2023, TON-IoT, Bot-IoT and ISCX VPN non-VPN) and dataset-driven synthetic access pattern generation. Real datasets are used to model realistic IoT traffic behaviors, while additional synthetic scenarios are introduced to evaluate adaptability against evolving and previously unseen attack patterns. Network level features from these datasets are systematically transformed into storage-level access behaviors to evaluate metadata-driven access control. The experimental results indicate improved detection accuracy (94.6%), reduced false positive rate (4.3%), improved misuse control efficiency (92%) and scalability (94%). The proposed methodology for securing manual storage domains is scalable, adaptive, and portable, extending the security of applications and their associated domains. Full article

Artificial intelligence (AI) is increasingly influencing nanopharmaceutical development by supporting the transition from empirical formulation screening toward predictive, data-driven, and translationally oriented design. Nanocarrier-based therapeutics are governed by nonlinear relationships among material composition, physicochemical attributes, manufacturing parameters, biological identity, pharmacokinetics, toxicity, and therapeutic performance. In this review, we examine how AI can contribute to nanopharmaceutical development from predictive formulation design to clinical translation. We synthesize current applications of machine learning, deep learning, physics-informed modeling, hybrid mechanistic–AI approaches, and automated optimization workflows, with emphasis on critical quality attribute modeling, multi-objective optimization, design of experiments, quality-by-design, process analytical technology, digital twins, and continuous manufacturing. We also discuss applications involving nano–bio interactions, pharmacokinetics, toxicity, immunogenicity, and precision nanomedicine. AI-based approaches can support rational nanocarrier design, identify nonlinear formulation–property relationships, guide optimization, improve process understanding, and integrate heterogeneous experimental, biological, and manufacturing datasets across diverse nanopharmaceutical platforms. These methods are particularly relevant for modeling protein corona formation, cellular uptake, intracellular trafficking, biodistribution, pharmacokinetics, toxicity, immunogenicity, and patient-specific responses. However, translational implementation remains limited by fragmented datasets, inconsistent reporting standards, limited interpretability, insufficient external validation, uncertain predictions, poorly defined applicability domains, and evolving regulatory expectations for adaptive computational models. Overall, AI should be viewed not only as an optimization tool, but also as a translational framework connecting formulation science, biological prediction, manufacturing control, and clinical implementation. Future progress will depend on standardized data infrastructures, explainable and externally validated models, uncertainty quantification, applicability-domain definition, hybrid mechanistic–AI frameworks, regulatory-ready documentation, and clinically relevant case studies. Full article

Dendritic cells (DCs) are key antigen-presenting cells essential for the initiation of immune responses. Their migration is tightly regulated by adhesive structures, including podosomes and focal adhesions (FAs), allowing for interactions with the extracellular matrix (ECM) for coordinated cell movement. The organization and dynamics of these structures are controlled by actin and microtubule cytoskeletons; however, the mechanisms governing their balance in distinct DC subsets are not completely understood. In this study, we investigated cytoskeletal regulation of the interplay between podosomes and FAs in GM-CSF-derived inflammatory-like DCs (GM-BMDCs) and Flt3L-derived conventional DCs (FL-BMDCs). GM-BMDCs showed a higher capacity to form podosomes compared with FL-BMDCs, which exhibited fewer and less prominent structures. Actin depolymerization resulted in the complete loss of podosomes, whereas disruption of microtubules induced podosome reorganization and altered the structure of FAs. Importantly, cytoskeletal perturbation in both DC subsets led to podosome dissolution, highlighting the requirement of cytoskeletal integrity for their maintenance. Furthermore, actin integrity was essential for podosome-mediated ECM degradation and efficient migration of GM-BMDCs, while microtubules fine-tuned the balance between podosome and focal adhesion dynamics, thereby regulating DC motility. Full article

Introduction: Elasmobranchs play a vital role in marine food webs through top-down control and the structuring of ecosystem stability, yet more than one-third of species face extinction. The Maldives, a recognised Indian Ocean hotspot for shark and batoid diversity, designated its EEZ as a shark sanctuary in 2010, but multispecies elasmobranch occurrence patterns and environmental drivers remain poorly characterised in Lhaviyani Atoll in the central Maldives, which hosts two Important Shark and Ray Areas (ISRAs). Recreational SCUBA networks can turn routine dive activity into long-term conservation evidence, already informing nearly 10% of the western Indian Ocean ISRAs. Objective: To characterise spatiotemporal patterns of elasmobranch assemblages in Lhaviyani Atoll (2017–2024), quantify how environmental and geomorphic drivers shape relative abundance, diversity, and hotspots, and provide evidence for targeted elasmobranch conservation. Methodology: A seven-year opportunistic dive-log dataset of 12,732 SCUBA surveys and 142,994 elasmobranch records across 94 dive sites was analysed. Effort-standardised relative abundance and community metrics (Shannon diversity, Pielou’s evenness) were modelled against sea surface temperature (SST), salinity, dissolved oxygen, chlorophyll-a, zonal current velocity, substrate type, and reef geomorphology using generalised additive models (GAMs). Spatial analyses identified persistent northern-rim aggregation areas aligned with ISRAs. Results: Twenty-eight species (14 sharks, 14 batoids) were recorded, including 23 threatened on the IUCN Red List (4 Critically Endangered, 12 Endangered, 7 Vulnerable). Relative abundance and diversity peaked during the late southwest monsoon (August–September) and declined during the northeast monsoon (December–March). After 2021, diversity and evenness increased while overall abundance declined. Relative abundance was primarily driven by SST, salinity, and current velocity; for sharks, dissolved oxygen and chlorophyll-a were additionally significant, whereas batoid abundance was driven mainly by temperature, oxygen, and current velocity. Four persistent hotspots along the northern atoll rim were identified, with sharks concentrated along exposed slopes and channels, and batoids distributed broadly within lagoonal habitats. Conclusions: Long-term citizen science dive-log monitoring is cost-effective for elasmobranch conservation in remote tropical seascapes. These results show how dive-industry partnerships can inform conservation governance over a decade after sanctuary designation, supporting targeted, habitat-focused management as shark and batoid conservation frameworks continue to evolve. Full article

Educational information systems have evolved into highly interconnected digital landscapes that support learning management platforms, student information systems, institutional repositories, and online assessment environments. As these systems increasingly operate across cloud infrastructures and mobile devices, ensuring the confidentiality, integrity, and availability (CIA Triad) of educational data is critical for safeguarding institutional operations and maintaining trust in digital education services. This paper investigates how next-generation security protocols, such as adaptive multi-factor authentication and advanced access control and data protection mechanisms, can reinforce ISO/IEC 27001:2022 requirements within contemporary educational information systems. The analysis maps emerging protocol capabilities to relevant new ISO/IEC 27001:2022 control domains, illustrating how they mitigate threats associated with unauthorized access, data manipulation, and service disruption. The proposed framework is further supported by an implementation-oriented mapping and an illustrative operational architecture that demonstrates the feasibility of translating prioritized security determinants into practical mechanisms. The FAHP analysis identifies access control mechanisms, backup and recovery, and data validation as the three highest-weighted determinants, with aggregate weights of 0.061, 0.059, and 0.057, respectively. These determinants are translated into a determinant-driven Security Operationalization Matrix that connects ISO/IEC 27001:2022 control domains, CIA dimensions, and technology recommendations, and is complemented by implementation feasibility considerations tailored to the budgetary, infrastructural, and resource constraints characteristic of educational institutions. Based on the prioritization results and conceptual operationalization, the proposed integrative approach provides a structured and progressively adoptable foundation for CIA-oriented security governance in digital educational environments. Full article

Cultural heritage is a critical pillar of identity, social cohesion and continuity within ethnocultural communities. However, the preservation of cultural heritage across Southern Africa is largely constrained by fragmented colonial policy implementation, and limited community engagement. This study critically examines the application of the Evidence-Based Policy and Practice (EBPP) model as a decolonizing framework for sustainable management of cultural heritage. The study conducts a structured scoping review of literature to explore the integration of EBPP with the principles of Collective Benefit, Authority to Control, Responsibility, Ethics (CARE), and the principles of Findable, Accessible, Interoperable, Reusable (FAIR) to support inclusive and ethical governance. The findings of the study reveal that sustainable management of cultural heritage is dependent upon community-led governance, alignment between research, policy, and practice, and strengthening of intellectual property protections. The study identifies persistent gaps in the operationalization of indigenous knowledge policies and highlighted the need for participatory approaches to ensure the long-term sustainability of cultural heritage. The study argues that the integration of EBPP, alongside the principles of CARE and FAIR, significantly enhances accountability, fosters data sovereignty, and supports the decolonization of knowledge systems. Thus, the study makes a significant contribution to the growing global discourse on sustainable development by positioning cultural heritage as a dynamic resource for social transformation. Full article

Flexible casing piles can form locally enlarged sections by expanding flexible casings during concrete casting, thereby filling karst cavities and improving the adaptability and bearing capacity of pile foundations in karst areas. However, the damage evolution and failure mechanism of the enlarged section under vertical loading remain insufficiently understood. In this study, a three-dimensional finite element model of a flexible casing pile was established using the Concrete Damaged Plasticity (CDP) model. The stress transfer, plastic strain development, and tensile–compressive damage evolution of the enlarged section under vertical static loading were investigated. The effects of karst cavity spacing, cavity number, and cavity diameter on the vertical bearing behavior were further analyzed. The results show that damage localization is governed by the transition zone between the pile shaft and the enlarged section, where plastic strain, tensile damage localization, and compressive damage accumulation develop in a coupled manner. Increasing the number and diameter of enlarged sections improves the ultimate bearing capacity, whereas cavity spacing mainly controls the interaction and synchronization of damage zones between adjacent enlarged sections. These findings establish a damage-based interpretation for identifying the failure-control region of flexible casing piles in karst cavities and provide a basis for bearing-capacity assessment and structural optimization. Full article

This study examines how digitalization discourse is mobilized in public carbon reporting under institutional complexity and how it varies across different carbon-accountability structures in an emerging-market context within the Global South. A longitudinal comparative discourse analysis was conducted on 70 annual and sustainability reports (2015–2024) from seven Vietnamese listed firms, contrasting firms with internal carbon accountability against those with supply-chain-mediated accountability. The 2015–2024 timeframe was deliberately selected to capture a critical decade of regulatory evolution, marked by the aftermath of the Paris Agreement and the escalating enforcement of net-zero and environmental, social, and governance (ESG) disclosure mandates. Findings reveal that digitalization functions as an ambivalent rhetorical resource rather than a uniformly substantive sustainability enabler. Firms with operationally visible emissions utilize digitalization for “temporal buffering,” deferring immediate physical abatement by framing technology as a future transition pathway. Conversely, firms with supply-chain-mediated emissions employ “boundary displacement,” framing accountability as contingent on fragmented supplier data. These patterned responses constitute “digital institutional camouflage”. We conclude that digital reporting sophistication should not be conflated with substantive decarbonization; effective oversight requires cross-validating digital infrastructures with concrete emission-reduction measures. Ultimately, this study empirically specifies institutional decoupling theory by demonstrating how emissions visibility and organizational control shape distinct pathways of discursive decoupling. Full article

Smart Mobility plays a key role in Smart Cities, given its ability to support the rollout of intelligent transport systems, allowing for more sustainable urban transportation and greater interoperability across diverse mobility modes. Furthermore, Smart Mobility is essential to maximize the quality of life for the community while advancing principles of sustainability, economic development, technological innovation, and collaborative governance. Real-Time Traffic Management (RTTM) emerges as a vital technology for optimizing traffic management in Smart Mobility. Using the PRISMA framework, the proposed systematic literature review examines 165 peer-reviewed publications related to RTTM research work published between 2019 and 2025. This review identified eleven application domains, with Urban Traffic Management Systems (36.97%) and Artificial Intelligence (AI) and Predictive Analytics (12.73%) representing the most prominent areas. A retrospective analysis of the literature on control architecture used in closed-loop feedback systems indicates that most studies (89%) have adopted a more dynamic control model, while 7.8% adopted a Digital Twin (DT)-based approach. However, several implementation barriers persist, including limited integration of online optimization and learning loops into RTTM systems, gaps in performance comparisons between simulation and reality, scalability issues due to heterogeneous environments, inconsistent data quality caused by various sensor types, and difficulties integrating sensors into a control system. In addition, this paper proposes a taxonomy of RTTM applications and control architectures, while outlining key practical barriers to implementation and charting future research directions for advancing Smart Mobility through robust RTTM. Full article

With the digital economy advancing at a fast pace, digital transformation plays a pivotal role in reinforcing firms’ innovation capability and promoting high-quality development. This study analyzes Chinese non-financial publicly listed firms on the A-share market over the period 2009–2023. Based on text mining of annual reports, this study constructs an index capturing digital transformation and empirically evaluate its impact on innovation output with firm and year fixed effects. The estimates suggest that digital transformation meaningfully increases firms’ innovation output; the inference is unchanged when applying instrumental-variable approaches and conducting extensive robustness checks. Mechanism analysis reveals two parallel channels: (1) the R&D investment mechanism, characterized by improvements in R&D intensity, capitalization rate, per capita efficiency, and investment growth; (2) the governance environment mechanism, reflected in enhanced internal control, improved information disclosure quality, and strengthened audit supervision. Once firms are stratified by characteristics, the estimated positive effect of digital transformation is most pronounced for firms with low financial constraints, large size, eastern locations, and state ownership. This study identifies both direct and indirect mechanisms linking digital transformation to innovation and highlights how firm- and region-specific features condition the magnitude of this effect, thereby offering empirical implications for corporate digitalization strategies and policy design. Full article

Earth-based materials are promising candidates for balancing thermal performance, hygrothermal regulation, and environmental sustainability. The objective of this study is to evaluate and compare the hygrothermal behavior of two earthen materials, structural cob and lightweight insulating earth, against conventional reference concrete, taking into account not only their insulating properties but also their ability to regulate coupled heat and moisture transfers. Experimental tests show a significantly higher hygroscopic buffering capacity for earth-based materials, with an MBV of 2.23 g/(m²∙%RH) for the structural material and 1.21 g/(m²∙%RH) for the insulation material, compared to less than 0.5 g/(m²∙%RH) for concrete. The sorption isotherms confirm distinct water storage behaviors, with an average sensitivity to relative humidity of 10.47% for the insulation material, compared to 3.8% for concrete and 2.25% for the structural material, in addition to an average reduction of 26% in the adsorption capacity between 23 °C and 45 °C for both earthen materials. Coupled heat–moisture simulations in COMSOL quantitatively demonstrate the hygrothermal superiority of bio-based materials over conventional concrete, as concrete promotes interstitial moisture accumulation due to its low vapor permeability. The parametric sensitivity analysis highlights the effect of hygrothermal properties, where diffusivity controls transport kinetics and sorption governs water storage, while thermal conductivity modulates the spatial redistribution of thermo-hygric fields. The next and final step made it possible to link the phenomena observed at the material scale to the actual energy performance of the building, confirming the potential of the double-wall cob + lightweight earth system to reduce heating and cooling requirements and maintain stable indoor comfort, where the annual heating demand is reduced by approximately 24% compared to the conventional prototype. Full article

Electrospun sulfonated polyketone (PK) nanofiber membranes were prepared to investigate the sulfonation-time-dependent structure–property relationships of hydrocarbon-based polymer electrolyte membranes for PEMFC (Polymer Electrolyte Membrane Fuel Cell) applications. NaCl addition to the electrospinning solution increased solution conductivity and enabled the formation of uniform PK nanofibers with an average diameter of approximately 270 nm. Subsequent sulfonation introduced sulfonic-acid-related groups into the PK nanofiber framework, and the resulting membrane properties were strongly governed by sulfonation time. Among the tested membranes, PK-NC16 exhibited the highest proton conductivity of 0.107 ± 0.031 S cm⁻¹ and an ion exchange capacity of 2.82 m_eq g⁻¹, exceeding or comparable to those of Nafion 115 under the tested conditions. FTIR-based analysis indicated that the relative sulfonation index increased up to 16 h, whereas extended sulfonation for 24 h generated additional sulfone/sulfonate-related bands, suggesting possible side reactions or structural changes under prolonged acid treatment. The high water uptake of PK-NC16 enhanced proton transport but also revealed a hydration-sensitive polymer network, as reflected by a voltage degradation rate of approximately −590 μV h⁻¹ during a 100 h short-term stability constant-current test. These results demonstrate that sulfonation time is a key parameter controlling the balance among ionic functionality, hydration, mechanical response, proton conductivity, and PEMFC-relevant single-cell performance in electrospun PK nanofiber membranes. Full article

This research analyzes the wavy, axisymmetric flow of a Ree–Eyring non-Newtonian nanofluid, infused with motile microorganisms, within a porous, tapered cylindrical channel under a transverse magnetic field. This investigation presents a theoretical framework that may inform the improvement of energy efficiency and thermal management in biomedical engineering applications, such as drug delivery systems and microfluidic biosensors. The work provides an extended insight by a contribution to the evaluation of entropy generation, explicitly considering the influence of motile microorganisms, thereby bridging a gap in the existing literature. The comprehensive physical model further incorporates the combined effects of Joule heating, viscous dissipation, nonlinear thermal radiation, and chemical reactions. Methodologically, the governing nonlinear equations of the system were rendered tractable under long-wavelength and low-Reynolds-number assumptions and subsequently solved using the numerical Runge–Kutta–Fehlberg technique. The key conclusion is that, based on the present numerical model, careful selection of magnetic field strength and microorganism motility parameters may reduce irreversible energy losses, potentially improving the net usable work in advanced nanofluid transport systems for biomedical applications, subject to experimental validation. The most significant finding reveals that the magnetic field serves as a dual-purpose control parameter: increasing its strength boosts total entropy generation by 20–30% while simultaneously raising the Bejan number, confirming heat transfer as the dominant irreversibility mechanism in the system. Additionally, nanoparticle concentration diminishes substantially with elevated chemical reaction rates and Schmidt numbers, while microorganism density is highly sensitive to the Péclet number, which causes flow disruptions. Full article

Controversy persists on a global scale regarding the trade-offs between greenhouse gas (GHG) emissions, yield, the global warming potential (GWP), and GHG intensity (GHGI) following organic fertilizer substitution within vegetable cropping systems. This study aimed to quantify these effects under diverse conditions and elucidate the direct and indirect drivers governing these outcomes through a meta-analysis and structural equation modeling (SEM). We synthesized 655 paired observations from 69 published studies using random-effects meta-analysis, finding that organic fertilizer substitution significantly increased CH₄ emissions and GWP compared to inorganic fertilizer controls. Although this was the general trend, organic fertilizer could reduce GWP under specific climatic and soil conditions by reducing N₂O emissions, such as mean annual precipitation <400 mm or soil total nitrogen ≥3 g kg⁻¹. These conditions were also associated with substantially higher yield and lower GHGI. Furthermore, SEM demonstrated that field management practices exerted significant direct effects on N₂O emissions, GWP, and GHGI. Reductions in N₂O emissions, GWP, and GHGI could be achieved with fertilizer application duration ≥10 years, total N application rate ≥300 kg ha⁻¹, and field cultivation or plowing. GHGI was also reduced through yield enhancement under a moderate organic substitution rate (33–66%) or irrigation ≥300 mm. Our study provides a scientific basis for moving beyond universal recommendations towards precision organic management, which is essential for optimizing fertilization strategies to mitigate agricultural GHG emissions. Full article