Search Results (9,503)

Adaptive learning environments and large language models (LLMs) are increasingly combined, yet most LLM-based tutoring work addresses feedback generation in isolation rather than its integration into a controlled, auditable learning loop. This paper presents a design study of a provider-independent LLM architecture for adaptive Oracle SQL tutoring. We report the system at the design stage—specifying the underlying adaptive learning platform, a provider-independent service layer that abstracts interchangeable model back-ends behind a single auditable interface, the SQL-specific extension (a reference-based evaluator demonstrated as a proof-of-concept on an in-memory SQLite fixture of the fixed Oracle HR schema; Oracle-specific execution, the live sandbox, and course-wide evaluation remain planned), and a concrete validation pathway—without claiming empirical effectiveness. The design pairs cognitive adaptivity, realised as mastery-based task selection under configurable parameters, with motivational design grounded in Keller’s ARCS model. Following a design-based research orientation, the adaptation logic is expressed as testable design conjectures. We contribute (a) a modular, provider-independent architecture for LLM-supported SQL learning; (b) a formalised adaptation logic linking learner states, adaptive responses, and conjectures; (c) an illustrative prompt template with a three-level quality-control workflow for AI-generated feedback; and (d) a proposed estimation-oriented feasibility pilot protocol—a validation pathway rather than an empirical contribution of this article—to be preregistered before data collection, with up to 50 undergraduate participants. Implemented capabilities, planned SQL-specific functions, and hypothesised outcomes are kept explicitly distinct throughout. Full article

Hydrogel-and-nanomaterial-integrated wearable biosensor networks are promising platforms for real-time biomedical monitoring because they combine soft biointerfaces, sensitive signal transduction, and wireless data connectivity. Hydrogels provide tissue-like softness, hydration, adhesion, permeability, and biocompatibility, whereas nanomaterials such as graphene, carbon nanotubes, MXenes, metallic nanoparticles, and conductive polymers enhance conductivity, electrochemical activity, optical responsiveness, mechanical durability, and signal amplification. This review summarizes recent advances in hydrogel-and-nanomaterial-integrated wearable biosensors, ranging from soft material interfaces and stand-alone sensing devices to wireless wearable nodes, IoT-connected platforms, and emerging closed-loop sensor–actuator systems. Because these platforms differ substantially in their level of integration and validation, this review distinguishes enabling material and device concepts from fully connected or closed-loop systems. The distinctive contribution of this review is a materials-to-systems, evidence-graded framework that links hydrogel and nanomaterial interface design with sensing mechanisms, wearable sensor-node integration, wireless and IoT connectivity, and closed-loop actuation while distinguishing device-level proof of concept from clinically validated performance. We discuss functional hydrogel design, nanomaterial-based conductive networks, hybrid hydrogel–nanomaterial structures, and key requirements for skin compatibility, adhesion, stretchability, and long-term stability. Major sensing mechanisms and biomedical targets are reviewed, including electrochemical and optical biosensing, mechanical and physiological signal sensing, and sweat biomarker monitoring. We further highlight system-level integration strategies involving wearable sensor nodes, wireless communication, smartphone and cloud connectivity, data processing, power management, security, and reliability. Representative biomedical applications are summarized, including sweat-based metabolic monitoring, smart wound monitoring, hydrogel-based wound dressings, cardiovascular and respiratory monitoring, and motion sensing. Finally, current technical and translational challenges are discussed with emphasis on the distinction between analytical sensing performance, physiological correlation, and clinical validation. Disease-management and closed-loop healthcare applications are discussed as emerging directions that require appropriate human studies, reference-method comparison, agreement analysis, long-term monitoring, and safety validation before clinical implementation. Full article

This study examines how environmental, social and governance (ESG) pressures are translated into verifiable governance practices in European banking and asks why this translation remains uneven in the Western Balkans. Drawing on institutional theory, Europeanisation and the evolving architecture of the Corporate Sustainability Reporting Directive (CSRD), European Sustainability Reporting Standards (ESRS), prudential ESG risk governance and sustainability assurance, the article distinguishes between ESG pressure and ESG measure. The empirical analysis uses an original, manually coded dataset of 55 banks across eleven European countries. A governance-oriented maturity framework captures the progression from CSR-dominant disclosure to formal reporting standards, board-level integration and external assurance. Descriptive statistics and group comparison tests reveal a pronounced institutional divide: EU-core and Croatian banks occupy the highest maturity category, while banks in selected Western Balkan systems remain concentrated around partial integration and lack local assurance. A robustness comparison using ESG_core, which excludes reporting standards and assurance, confirms that the regional divide persists beyond those mechanically related components. A double-coded subsample of 17 banks further demonstrates substantial-to-perfect inter-coder reliability across the principal coded dimensions. The article then develops a complementary policy architecture for a permissioned, blockchain-enabled ESG data platform based on standardized application programming interfaces, off-chain data storage, on-chain hashes and shared attestations. The proposed design links triple-entry accounting principles with regulatory supervision and independent assurance while explicitly addressing data protection, interoperability and the oracle problem. The article contributes by integrating comparative evidence on ESG governance maturity with a technologically realistic pathway for reducing data and assurance gaps in transition economies. Full article

Background: Three-dimensional (3D) printing and bioprinting have emerged as transformative technologies in tissue engineering and regenerative medicine. Conventional 3D printing enables the fabrication of complex, customizable scaffolds that mimic the native extracellular matrix (ECM), providing mechanical support essential for cell adhesion, proliferation, and differentiation. In contrast, 3D bioprinting integrates biomaterials, growth factors, and living cells into bioinks, allowing the precise layer-by-layer construction of tissue-like structures. Objective: This review aims to highlight recent advances and applications of both conventional 3D printing and 3D bioprinting in regenerative medicine, with a specific focus on craniofacial tissue regeneration. Particular emphasis is placed on the distinct roles of scaffold-based and cell-laden approaches. Methods: A comprehensive analysis of the current literature was conducted to examine both conventional 3D printing and bioprinting approaches used in craniofacial tissue engineering. Emphasis was placed on printing techniques, bioink composition and selection, scaffold design, and cell sources, as well as their applications across multiple tissue types. Results: Recent developments demonstrate that conventional 3D printing enables the fabrication of customizable scaffolds, whereas 3D bioprinting enables the generation of highly organized, cell-laden constructs that closely resemble native tissue architecture. These technologies have shown promising outcomes in developing patient-specific disease models and regenerative implants for craniofacial tissues, including bone, dental, tracheal, ocular, muscle, and neural tissues. Conclusions: 3D printing and bioprinting offer powerful platforms for craniofacial regenerative medicine. Ongoing advancements in bioink formulation, printing precision, and biological integration are expected to further enhance their translational and clinical potential. Full article

Vehicle-to-Grid (V2G) enables energy and information exchange between electric vehicles (EVs) and the power grid. Large amounts of distributed data are generated in V2G systems. The charging data of EVs connected to charging piles (CPs) are aggregated by charging stations (CSs), charging service operators (COs), and load aggregation platforms. The aggregated results support grid regulation and electricity market trading. However, some CPs within a station are idle or offline due to hardware failures or communication disruptions, preventing their data from being aggregated in time. Consequently, traditional schemes that rely on full-pile participation result in incomplete ciphertext aggregation results due to the absence of data contributions from some CPs, making correct decryption unreliable. In addition, most existing data aggregation schemes only provide a single result. They cannot satisfy the differentiated data access demands of V2G business entities. To address these challenges, a user-driven differentiated fault-tolerant data aggregation scheme for V2G interaction is proposed. First, the EC-ElGamal encryption scheme is employed to preserve data confidentiality, while the ECDSA batch signature verification mechanism is adopted to ensure data integrity. Second, a mask compensation mechanism is designed to restore the completeness of the aggregated ciphertext under the failures of some CPs. Finally, on-demand differential de-aggregation and controlled authorized decryption are designed based on Shamir’s secret sharing scheme. Data users (DUs) are allowed to access target ciphertexts on demand, only upon obtaining sufficient authorization from CPs. Security and performance analyses demonstrate that the proposed scheme effectively resists chosen-plaintext and key-collusion attacks with practical efficiency. The proposed scheme provides a secure and reliable solution for V2G data aggregation. Full article

Background/Objectives: Digital pathology is transforming diagnostic workflows through whole-slide imaging (WSI), digital archiving, artificial intelligence (AI)-assisted analysis, and remote consultation. The existing literature only partly addresses patient access to pathology records and cross-institutional sharing within a holistic governance framework. This study proposes a Self-Sovereign Identity (SSI)-based conceptual governance model that treats digital pathology archives as components of long-term clinical memory. Here, clinical memory refers to a pathology-specific information layer that preserves record context, provenance, integrity, and longitudinal links across time and institutions while supporting governed reuse and legally bounded patient-managed access. Methods: Eighty publicly available complaints from the Şikayetvar platform were examined using codebook-based thematic content analysis. Aggregated National Health Service (NHS) Written Complaints data were used to provide an illustrative external governance context. These data were not used for cross-country prevalence comparison or corroboration. Results: The main complaint themes were absent or inaccessible pathology results (66.3%) and records that remained unavailable despite notifications that the results were ready (55.0%). Complaint themes, the literature, regulatory sources, technical standards, and internal clinical review were synthesized while preserving different analytical functions, and 11 governance requirements were identified. Conclusions: Developed through Design Science Research, the model integrates verifiable credentials (VCs), a patient digital wallet, purpose- and time-limited authorization, dynamic consent and access revocation, secure off-chain storage, and blockchain-based integrity and auditing. The model was examined through an internal requirement-coverage assessment and a supplementary post hoc benchmark-oriented assessment. These analyses indicate conceptual consistency rather than independent validation. Real-world technical, clinical, usability, security, and equity validation remains necessary. Full article

This paper presents the kinematic design and experimental validation of a two-degree-of-freedom ankle mechanism based on stepper motor actuation and ball-screw transmission. The proposed system employs a hybrid architecture, combining actively controlled motion in the sagittal plane with passively compliant motion in the frontal plane. Experimental evaluation under no-load laboratory conditions demonstrated a strong linear relationship between motor steps and joint angle within an operating range of approximately ±22°, with coefficients of determination exceeding 0.97. The results confirm the predictability and repeatability of the kinematic transformation while revealing minor hysteresis effects associated with mechanical transmission. The proposed mechanism is intended as a validation platform for studying motion transformation in multi-DoF (degree-of-freedom) ankle systems, providing a basis for future work on load analysis, torque modeling, and closed-loop control. Full article

To address the limited endurance of unmanned underwater vehicles (UUVs) during long-duration missions, this study proposes a foldable and retractable wave energy converter (WEC) conformally integrated with the UUV hull. A two-degrees-of-freedom heave-coupled dynamic model of the float–UUV system is established, and parameter-matching relationships are derived using complex dynamic stiffness and impedance-matching theory. A bidirectionally coupled STAR-CCM+-AMESim co-simulation framework resolves the nonlinear viscous flow field, relative motion, and PTO dynamic response in closed loop. Under regular wave conditions defined based on a representative Bohai Sea state, the effects of the transmission ratio and spring stiffness on the coupled motion and equivalent resistive load power output are systematically investigated. Under the specified wave condition, average electrical power varies unimodally with both parameters, reaching 70.8 W at a transmission ratio of 15 and a spring stiffness of 4642 N/m; the corresponding peak power is 161.2 W. The system is more sensitive to increases than decreases in transmission ratio, suggesting a value slightly below the theoretical optimum for engineering design. The instantaneous power shows an asymmetric double-peak pattern, indicating a shift in dominance between direct float-driven generation and spring-mediated energy release. Agreement between theory and co-simulation provides numerical cross-validation and offers a theoretical basis and numerical methodology for designing and optimizing WECs on mobile UUV platforms. Full article

Volatile fluorinated compounds (VFCs) are indispensable to modern industry, yet their potent greenhouse effects pose critical environmental challenges. Functional porous materials, ranging from zeolites and semiconductor oxides to metal–organic frameworks (MOFs), covalent organic frameworks (COFs), and other advanced porous materials, have emerged as versatile platforms for VFC sensing and capture, leveraging their structural tunability, ultrahigh surface areas, and designable pore chemistry. This review provides a systematic summary of recent advances in porous materials for VFC management. For sensing, we examine transduction mechanisms (chemiresistive, optical, and gravimetric approaches) with emphasis on structure–signal relationships. For capture, we evaluate adsorptive performance across VFC subclasses, highlighting design principles that govern selectivity and capacity. Based on recent achievements, we assess persistent gaps between laboratory-scale achievements and practical deployment. Possible pathways toward integrated sense-and-capture systems are also explored. By bridging fundamental materials science, this review highlights cross-cutting design strategies that may accelerate the development of next-generation VFC management platforms. Full article

Web applications increasingly handle sensitive data in diverse use cases, but conventional encryption implementations apply a uniform level of cryptographic protection to all traffic, regardless of the associated risk. This static approach results in either excessive computational overhead when applying maximum encryption universally, or inadequate protection when using lightweight encryption to preserve performance. This paper proposes an Adaptive Encryption Framework (AEF) designed to bridge the gap between performance and security in web applications. Rather than relying on a static protocol, AEF dynamically adjusts encryption algorithms based on a real-time composite risk score (0–100). This score is derived from six weighted variables: network risk (25%), authentication strength (20%), behavioral risk (20%), device trust (15%), data sensitivity (15%), and temporal risk (5%). Depending on the calculated risk, the system automatically transitions between three distinct security tiers: GREEN (utilizing ChaCha20-Poly1305), YELLOW (AES-256-GCM), or RED (AES-256-GCM with per-request HKDF key derivation for key isolation). All three profiles use exclusively standardized cryptographic primitives. The proposed weighting distribution was evaluated through sensitivity analysis on 27 framework-executed scenarios and further calibrated using 40,000 labeled application requests. Within these experimental conditions, it achieved complete agreement with the expected scenario classifications, and no alternative weight configuration produced better held-out performance. Additional validation on 61,065 HTTP requests from the CSIC 2010 dataset yielded an area under the ROC curve (ROC AUC) of 0.860, with no attack request assigned to the lightweight profile under the evaluated operating conditions. Across three hardware platforms and four payload sizes, all encryption profiles maintained sub-millisecond latency. Extended load testing showed that a four-worker Node.js cluster sustained 4948 requests per second at 2000 concurrent connections, a 7.1-fold improvement over a single process. When hardware cryptographic acceleration was disabled, ChaCha20-Poly1305 became up to 9.1 times faster than AES-256-GCM, supporting its use as the lightweight profile. The framework proposed in this paper operationalizes the qualitative risk assessment guidelines from NIST SP 800-30 and SP 800-63 into a quantitative, automated encryption selection mechanism for web applications, evaluated under the hardware platforms, concurrency levels and traffic assumptions described in this study. Full article

Online commercial sex platforms have become key environments in which potential indicators relevant to technology-facilitated sexual exploitation (TFSE) and technology-facilitated gender-based violence (TFGBV) may be observed. Current language models and computational approaches to identifying potential exploitation often assume that behavioural indicators (e.g., geographical mobility, pricing, and other linguistic markers) are easily accessible and comparable across online spaces and jurisdictions. This study challenges this assumption by showing that platform design largely shapes the variables and indicators that can be observed in these spaces. Drawing on a large-scale dataset of 1.9 million profiles (after cleaning) from two major online commercial-sex platforms, AdultWork (United Kingdom) and CallEscort (United States), the research examines how potential exploitation-related indicators may be identified and interpreted across platform architectures. Through cross-platform mapping, significant misalignments in data visibility and comparability were highlighted for demographic characteristics, mobility data, and services offered. To address comparability challenges, the study introduces a platform-mediated visibility framework to explain how platform design shapes the visibility, interpretation, and comparability of potential indicators relevant to TFSE and TFGBV. The framework provides a methodological basis for interpreting exploitation-related indicators across different platform architectures and underscores the value of platform-aware approaches to safeguarding and prevention. In collaboration with US and UK law enforcement and Non-Governmental Oranization (NGO) partners, the study advocates for proactive and tailored prevention strategies that account for platform architecture while recognising that coordinated activity and potential indicators do not, in isolation, establish exploitation, trafficking or criminal behaviour. Full article

Widespread use of organophosphate pesticides (OPPs) raises environmental, food safety, and public health concerns, and drives demand for rapid, sensitive, portable analytical technologies. We reviewed conductive polymer composite (CPC)-based electrochemical OPP sensors, focusing on the structure–performance relationships of representative polymers, polyaniline (PANI), polypyrrole (PPy), polythiophene (PTh), and poly(3,4-ethylenedioxythiophene) (PEDOT), and their hybrids with carbon nanomaterials, metal nanoparticles, metal oxides, MXenes, and metal–organic frameworks. We provided a critical comparison of conductive polymer systems, composite architectures, and enzymatic, molecularly imprinted polymer-based, and direct electrocatalytic sensing strategies, highlighting how material selection influences performance and applicability. Reported CPC-based sensors achieved limits of detection from micro- to femtomolar and successful application in real environmental and food samples; however, these results illustrate the capabilities achieved by selected high-performing reported platforms rather than the overall performance of CPC-based sensors. Despite these advances, reproducibility, long-term operational stability, matrix effects, sensor variability, and field implementation still limit deployment. We discussed future directions to address these challenges, including AI-assisted data analysis, standardised validation, portable field platforms, and sustainable fabrication. Rather than identifying a universally superior platform, this review emphasises rational material selection and composite design to guide CPC sensor development and translation for environmental monitoring and food safety applications. Full article

The accelerating contamination of global ecosystems by heavy metal ions, per- and polyfluoroalkyl substances (PFASs), microplastics and nanoplastics (MNPs), and emerging contaminants demands sensing technologies that are rapid, sensitive, selective, and field-deployable. Quantum dots (QDs) have emerged as leading candidates for environmental sensing; however, their performance is often interpreted empirically rather than through a unified understanding of the underlying excitonic physics. This narrative review presents a mechanistically integrated framework for QD-based environmental sensing, establishing the exciton, the spatially confined electron–hole quasiparticle, as the primary signal carrier in the most analytically powerful QD sensing modalities. A critical distinction is drawn between three categories of signal-generating processes: genuine excitonic transduction (photoinduced electron transfer, trap-state modulation, FRET, charge-transfer exciton formation, and binding energy modulation); non-excitonic optical phenomena, including the inner filter effect and light scattering, which are frequently misattributed as excitonic responses; and partially excitonic processes such as certain electrochemiluminescence pathways. Exciton fundamentals, confinement effects, and the influence of defects, dopants, and surface states are examined across carbon, chalcogenide, perovskite, and III–V QD families. A Defect–Exciton Energy Map is introduced as a rational design tool linking defect characteristics to excitonic response regime and sensing modality. Application of the mechanistic framework to heavy metal ions, PFASs, microplastics, and emerging contaminants demonstrates that sensing performance differences are mechanistically predictable from excitonic parameters rather than being arbitrary outcomes of materials choice. Benchmarking against competing platforms identifies conditions under which QD sensors offer genuine advantages. The roles of density functional theory, molecular dynamics, and machine learning in enabling rational sensor design are assessed. Key challenges, including stability, real-sample validation, standardisation, and toxicity, and future directions, including QD/two-dimensional material heterostructures and circular economy carbon QD platforms, are identified. Full article

Laboratories play a critical role in engineering education by bridging the gap between theoretical knowledge and practical applications. Dedicated laboratory stands serve as essential platforms for experiential learning, enabling students to interact directly with real or simulated systems. These stands enable a deeper understanding of complex engineering concepts and, at the same time, support the creation of essential skills such as problem-solving, critical thinking, and system integration. While physical laboratory stands provide a rich learning experience, their large-scale implementation can be both technically and financially challenging. In this context, virtual laboratory environments based on virtual prototypes offer a valuable complementary approach by improving access to practical learning while providing greater flexibility and reducing implementation costs. This paper presents the development of a virtual laboratory stand implemented using Simscape and designed for use in the teaching process in mechatronics engineering. The developed virtual prototype materializes a Segway-type self-balancing mobile robot and is used as a teaching tool in the lab activity of the control systems course. The educational effectiveness of the proposed virtual laboratory stand was evaluated by comparing students’ perceptions with those of a conventional analytical-model-based laboratory activity. The collected questionnaire data were analyzed using descriptive statistics and the Mann–Whitney U test. Students using the virtual laboratory reported consistently higher ratings than those using the analytical model, with statistically significant differences observed in three questionnaire items. These findings suggest that the proposed virtual laboratory stand enhances students’ learning experience and provides a valuable complementary approach for teaching control system design in mechatronics. Full article

Background/Objectives: Repurposing existing drugs may represent a promising strategy for effective cancer therapy. This study was the first to investigate the augmented antitumor therapeutic effect achieved by co-incorporating the NSAID Niflumic acid (NIF) with ceramides into PEGylated cerosomes (NIF-loaded PEG-CERs) in a novel platform that targets specifically the MAPK-ERK signaling pathway and miR-21-5p modulation. Methods: The prepared formulae were statistically optimized utilizing a full factorial design and the optimal formula (C5) was further incorporated into a topical gel and evaluated for ex vivo rat skin permeation, and tested in vivo in a subcutaneous solid Ehrlich carcinoma (SEC) mice model. Results: The optimal formula (C5) showed tubular elongated morphology with higher EE% (96.71 ± 0.0), lower vesicular size (VS) and PDI values, 292.95 ± 0.78 nm and 0.47 ± 0.0 respectively. A high ZP value (−37.5 ± 0.57 mV) was in accordance with stability results showing good stability of the optimal formula (C5). Permeability studies exhibited 2.02-fold higher skin permeation compared to pure NIF gel. A significant decrease in tumor volume and marked improvement in survival rate in SEC mice were confirmed by downregulation of EGFR, ERK1, ERK2, and miR-21-5p expression. Furthermore, an increase in total antioxidant capacity and caspase-3 levels was observed, accompanied by significant suppression in cyclin D1, MMP-2, COX-2, and MDA levels. Finally, histopathological analysis revealed the superior antitumor effect of C5 gel together with immunohistochemical assay showing the lowest BCL-2-positive staining, indicating the restoration of physiological apoptotic balance. Conclusions: Based on the previous findings, NIF-loaded PEG-CERs offer augmented therapeutic potential for efficient topical skin cancer management in an SEC mice model. Full article