Search Results (1,759)

The increasing demand for clean-label meat products has accelerated interest in natural bioactive compounds, including essential oils, plant polyphenols, and bacteriocins, as alternatives to synthetic preservatives. These compounds have the potential to enhance product safety and shelf life while meeting consumer expectations. Many natural bioactives exhibit antioxidant and antimicrobial activities, enabling them to reduce lipid oxidation and inhibit the growth of spoilage and pathogenic microorganisms in meat systems. Despite these benefits, their practical application remains limited by instability, volatility, poor solubility, and undesirable sensory effects. Encapsulation technologies have emerged as effective approaches to overcome these limitations by enhancing stability, controlling release behavior, and improving compatibility with complex meat matrices. This review synthesizes evidence from 154 studies published between 2010 and 2026 on the application of encapsulation technologies, including microencapsulation, nanoemulsions, liposomes, and cyclodextrin-based systems, for natural bioactives in meat systems. Encapsulated bioactive delivery systems are evaluated by integrating spoilage mechanisms, delivery system design, and application strategies. Encapsulation approaches are discussed in terms of structure–function relationships, release behavior, and interactions with meat components. Application strategies, including direct incorporation, edible coatings, and active packaging, are comparatively analyzed based on their functional performance in meat systems. Overall, nanoscale delivery systems are particularly effective in improving the dispersion, stability, and functional performance of hydrophobic bioactives, while controlled-release systems offer prolonged protection but often exhibit reduced predictability when translated from model systems to real meat matrices. Current challenges related to scalability, cost, regulatory constraints, sensory impact, industrial implementation, and the safe design of sustained-release antimicrobial systems are also addressed, thereby providing a framework for the rational development and implementation of effective clean-label preservation strategies in meat systems. Full article

Brain–computer interface (BCI) technology has shown potential for future rehabilitation-related and assistive control applications. Nevertheless, single-modality electroencephalography-based motor imagery (EEG-MI) signals are susceptible to interference, whereas existing algorithmic models suffer from limited classification accuracy and insufficient actionable control commands for interactive devices, thereby impeding their practical deployment. To tackle these limitations, this study presents a multimodal human–computer interaction control scheme that integrates eye-movement command encoding with EEG motor imagery decoding. Self-collected EEG-MI and eye-movement datasets were established to support the proposed multimodal control framework. In this framework, eye movements are not used merely as auxiliary inputs, but are encoded as discrete commands for start, stop, grasp, and release, thereby reducing the command burden of EEG-MI decoding. The EEG-TransNet model is enhanced by integrating a time–frequency feature branch and replacing the original convolutional encoder with an adaptive multi-branch EEG feature gating module, strengthening the representation and fusion of multi-domain features. The model yields average classification accuracies of 86.96% and 88.73% on the BCI IV-2a dataset and the self-collected EEG dataset, respectively. Four independent SVM binary classifiers are adopted to identify four eye movement patterns. The EEG and eye movement classification results are binary-encoded to generate hardware-compatible control commands. Robotic-arm grasping experiments with healthy trained participants showed an average task completion time of 17 s, and the repeated grasping success-rate results further provide preliminary evidence for the real-time feasibility of the multimodal control framework under controlled laboratory conditions. Full article

Autonomous AI agents capable of holding digital assets, signing transactions, and executing smart contracts on public blockchain networks have moved from research prototypes to active deployment over the past two years. Despite this pace of adoption, no systematic treatment of their architecture, coordination protocols, and governance structures exists that spans the full design space. This survey addresses that gap through a systematic review of the literature from 2019 to 2026, covering 177 peer-reviewed publications and 14 system documentation sources, identified through a structured search of IEEE Xplore, the ACM Digital Library, Scopus, and arXiv. We classify deployed and proposed systems along four architectural dimensions: on-chain execution, off-chain agents with on-chain settlement, verifiable off-chain computation, and multi-agent on-chain interaction. Then, we examine the coordination mechanisms through which agents reach collective decisions, covering auction-based protocols, cooperative multi-agent reinforcement learning, token-incentive structures, and gossip-based peer-to-peer coordination. Governance is treated as a distinct dimension, analysed through a technical lens, covering on-chain parameter control, dispute resolution, and DAO structures, and an organizational one, covering accountability, incentive alignment, principal–agent dynamics, and regulatory compatibility). We survey applications across decentralized finance, supply chain, IoT, and agent marketplace domains, and identify six open research problems whose resolution is a prerequisite for broader deployment. The convergence of mechanism design and multi-agent reinforcement learning in asynchronous blockchain environments is identified as the direction of greatest near-term research value. Full article

Essential oils are multicomponent natural products with potential neurobehavioral activity, but integrated comparative studies remain limited. This study compared the essential oils of Satureja brevicalyx, Peperomia dolabriformis, and Rosmarinus officinalis in relation to their chemical profiles, predicted target interactions, preliminary acute oral safety, anxiolytic-like and antidepressant-like effects, antagonist-sensitive behavioral patterns, and exploratory serum biomarkers. Oils were characterized by GC-MS, and their constituents were screened by molecular docking against anxiety-, depression-, sleep-, and stress-related targets. Independent cohorts of male BALB/c mice received oral essential oils (25–100 mg/kg) and were assessed in anxiety-related, depression-related, and locomotor behavioral paradigms, including the elevated plus maze, light–dark box, marble burying, tail suspension, forced swim, and open field tests. Flumazenil and WAY-100635 were used to examine whether the behavioral responses were sensitive to γ-aminobutyric acid type A (GABA-A)/benzodiazepine- and serotonin 1A (5-HT1A)-related pharmacological modulation, respectively. In a preliminary 24-h acute oral toxicity screen, no mortality was observed up to 5000 mg/kg. The three oils produced anxiolytic-like and antidepressant-like effects without reducing spontaneous locomotor activity. Within its experimental block, S. brevicalyx showed the most consistent flumazenil-sensitive anxiolytic-like pattern and FDR-significant reductions in corticosterone and TNF-α, together with increased IL-4. P. dolabriformis showed a broader predicted multitarget docking profile and antagonist-sensitive behavioral attenuation compatible with mixed pathway participation. R. officinalis produced significant but more moderate behavioral effects. WAY-100635 partially attenuated the antidepressant-like effects of all three oils. These findings support differentiated but convergent functional neurobehavioral profiles among the oils. The docking, antagonist, and biomarker results should be interpreted as hypothesis-generating evidence of possible pathway involvement, supporting further validation in chronic stress models, receptor-specific assays, pharmacokinetic studies, and expanded safety evaluations. Full article

Polyhydroxyalkanoates (PHAs) are a family of microbial polyesters distinguished by their excellent biocompatibility and tunable degradation profiles. However, systematic evaluation of the interaction effect between their chemical structure, material properties, and biological performance remains limited, particularly in veterinary medicine applications. In this study, we conducted comprehensive in vitro and in vivo evaluations of five commercially available PHA (co)polymers: poly(3-hydroxybutyrate) (PHB); poly(3-hydroxybutyrate-co-4-hydroxybutyrate) containing 5 mol% or 15 mol% 4-hydroxybutyrate monomer (P34HB 5%, P34HB 15%); and poly(3-hydroxybutyrate-co-3-hydroxyvalerate) containing 5 mol% or 15 mol% 3-hydroxyvalerate monomer (PHBV 5%, PHBV 15%). Material characterization confirmed that the introduction of proper comonomers effectively reduced crystallinity and accelerated the degradation process. Biological assays demonstrated quite excellent cytocompatibility and hemocompatibility among all tested PHA materials. Notably, P34HB 5% nanoparticles promoted human umbilical vein endothelial cell (HUVEC) migration. In a 12-week murine subcutaneous implantation model, the PHBV 15% group exhibited the thinnest fibrous capsule formation and the mildest inflammatory response. Furthermore, intramuscular injection of nanoparticles revealed favorable muscle tissue compatibility in all groups. These results provided a co-polymer ratio-based justification for PHA selection, thus providing support for the application of these biomaterials in veterinary drug delivery platforms, wound dressings, and biodegradable implants. Full article

Pesticide contamination in urban runoff, stormwater, and peri-urban drainage networks is an increasing concern because of the persistence, mobility, and ecological toxicity of many pesticide residues and their transformation products. Nature-based solutions (NBSs), including constructed wetlands, bioretention systems, biofilters, and permeable reactive bio-barriers, provide low-energy and ecologically compatible platforms for urban water treatment; however, their performance is often constrained by limited sorption capacity, substrate saturation, variable hydraulic loading, and incomplete degradation of persistent pesticides. Biochar offers a multifunctional amendment for strengthening these systems because its tunable porosity, surface functionality, mineral composition, redox activity, and microbial habitat-forming capacity can support pesticide adsorption, catalytic transformation, and biodegradation. This review critically evaluates biochar-integrated NBSs for pesticide-contaminated urban water systems by linking biochar production and modification strategies with pesticide removal mechanisms, biochar–microbe interactions, engineered treatment configurations, and field-scale applicability. A comparative synthesis is provided across material-level mechanisms, system-level performance, machine learning-assisted prediction, techno-economic feasibility, life-cycle impacts, and environmental risk considerations. By integrating material properties, removal mechanisms, NBS configurations, predictive modeling, sustainability assessment, and risk considerations, this review provides a broader comparative basis than previous studies focused mainly on individual aspects of biochar-based pesticide remediation. Future priorities include standardized biochar production, long-term field validation, spent-biochar management, ecotoxicological assessment, and data-driven optimization of biochar-assisted NBSs. Full article

Nucleic acids exhibit structured electromagnetic features shaped by classical electronegativity (EN) patterns. Mapping Pauling EN values across DNA and RNA reveals a largely invariant, high-EN phosphodiester backbone that provides a consistent electrostatic scaffold, while nucleobases introduce sequence-specific electron density shifts that generate tunable recognition fields. Together, these features create a dual-system framework in which a stable electrostatic background supports sequence-dependent informational cues. Within this environment, short-timescale vibronic interactions may arise from patterned vibrational and electronic behavior, producing modest “quantum overlay” effects compatible with known decoherence constraints. These structured, anisotropic electrostatic features may help explain differences in stability between DNA and RNA, the functional outcomes of nucleoside modifications such as N¹-methylpseudouridine (m¹Ψ), and the sensitivity of translational fidelity to small architectural perturbations. The framework yields experimentally testable predictions involving vibrational relaxation, dipole reorientation, and charge-transfer behavior, offering a classical-to-quantum interpretive bridge that may inform the design of next-generation therapeutic mRNAs. Full article

Text entry remains a bottleneck for productivity-oriented Virtual Reality (VR), especially in scenarios where optical hand tracking is unstable because of self-occlusion, poor lighting, or out-of-view interaction. We present SlideRing, a dual-thumb wearable text-entry method that senses thumb-to-finger micro-gestures with two miniature Inertial Measurement Units (IMUs). SlideRing defines a 30-command interaction space from two hands, three target fingers, and five gesture types, then maps these commands to a full alphabetic keyboard through two complementary strategies: an ergonomic layout optimized for low movement cost and a QWERTY-compatible layout optimized for learnability. To decode subtle inertial signals, we design a dual-stream recognition model with a Statistical Feature Encoder, a Temporal Feature Encoder, and a context-aware gating module for joint finger–action classification. In offline evaluation, the model reaches 96.5% target-finger accuracy and 94.2% action-type accuracy. In a five-day text-entry study, the ergonomic layout improves from 7.43 to 15.75 words per minute (WPM), while the QWERTY-compatible layout improves from 10.55 to 15.25 WPM. The ergonomic layout reduces physical demand, whereas the QWERTY-compatible layout lowers initial mental load. These results suggest that IMU-based thumb-to-finger input has the potential to provide robust, low-visual-demand text entry for constrained VR environments. Full article

The development of FLASH particle therapy, especially proton therapy, characterized by ultra-high dose rates (>40 Gy/s), presents significant challenges for dosimetry and beam monitoring. For example, ionization chambers (ICs) exhibit charge recombination effects leading to saturation, and other passive detectors cannot be used for real-time monitoring. This paper presents the idea, simulations and the preliminary prototype of a scintillating-fibers SiPM-based dosimeter for both high-flux and conventional dose-rate proton beam therapy. The prototype is based on 1 mm diameter plastic scintillating fibers, coupled to Silicon Photomultipliers (SiPMs). We estimated the interactions and the produced light signal within the fibers by the protons and towards the photodetectors using a semi-analytical model combining SRIM and analytical calculations. We estimated a light signal reaching the SiPMs in the range of 10⁷–10¹¹ photons (in a 50 ms beam pulse), for proton energies in the range 70–228 MeV, between the minimum and maximum beam current levels for conventional and FLASH conditions. Results highlight the very large dynamic range needed to be compatible with conventional and FLASH regimes. We also evaluated the linearity limits of the SiPMs and of the scintillating fibers. Finally, we preliminarily validated a reduced prototype version with a proton beam, demonstrating a good linearity of the system. Full article

Background: Diabetic cardiomyopathy (DCM) is characterized by metabolic dysfunction, inflammation, extracellular matrix (ECM) remodeling, and myocardial fibrosis. Increasing evidence suggests that ferroptosis-associated oxidative injury may contribute to cardiac remodeling; however, the interaction between ferroptosis-related pathways and fibrosis-associated molecular networks remains incompletely understood. This study explored the ferroptosis–fibrosis axis using an integrative transcriptomic and systems pharmacology framework. Methods: Differentially expressed genes were identified from the GSE5406 myocardial transcriptomic dataset comparing nonfailing donor hearts with ischemic and idiopathic cardiomyopathy samples and analyzed using functional enrichment, protein–protein interaction, and disease-association approaches. Cross-dataset comparison and exploratory sample-level external evaluation were performed using the independent GSE263297 DCM-related dataset. Candidate genes were further evaluated by receiver operating characteristic (ROC) analysis and machine learning-based feature selection using least absolute shrinkage and selection operator (LASSO), random forest, and support vector machine-recursive feature elimination (SVM-RFE). Representative compounds associated with fibrosis-, oxidative stress-, inflammation-, and ferroptosis-related pathways were subsequently assessed by molecular docking against TGFBR1, STAT3, GPX4, AKT1, SMAD3, and ACSL4. Results: Transcriptomic analyses highlighted ECM organization, collagen-containing ECM, and fibrosis-related pathways as dominant biological themes. Cross-dataset comparison showed partial preservation of transcriptional patterns between independent myocardial cohorts, with 20 of 51 evaluated genes demonstrating concordant expression direction across datasets. ROC analysis identified LUM and ASPN as having the highest area under the curve (AUC) values among candidate genes, whereas COL1A1, COL1A2, and COL3A1 also showed elevated AUC values. Machine learning analyses identified FCN3, HOPX, CNN1, and GLUL as the core signature consistently prioritized across all three algorithms, whereas LUM was additionally identified by two of three algorithms. Internal validation yielded a cross-validated AUC of 0.934 (95% CI: 0.820–1.000), and exploratory sample-level external evaluation of the four-gene signature in GSE263297 yielded an AUC of 0.673 (95% CI: 0.380–0.967). Exploratory docking analyses suggested potential structural compatibility between several candidate compounds and fibrosis-, inflammation-, and ferroptosis-associated targets, with comparatively lower predicted binding-energy values observed for selected ligand–target combinations. Conclusions: The findings are consistent with a fibrosis-dominant remodeling signature and suggest potential network-level links between ferroptosis-associated processes and cardiac fibrosis. These observations should be regarded as exploratory and hypothesis-generating and require validation in independent cohorts and experimental studies. Full article

The efficient removal of tenacious oxide scales from hot-rolled steel surfaces represents a persistent challenge in advanced manufacturing, as traditional manual grinding methods exhibit poor efficiency and environmental compatibility. This investigation develops an innovative methodology, i.e., a “coarse-to-fine” hierarchical cleaning paradigm consisting of dual-stepwise laser cleaning with variable parameters that successfully addresses the restrictive process window inherent to conventional single-parameter techniques. Through a strategically designed sequential treatment protocol—employing initial low-frequency (20 kHz), high-energy-density (200 mm/s) laser irradiation for primary oxide ablation, succeeded by high-frequency (60 kHz), low-energy-density (4000 mm/s) processing for residual scale elimination—we demonstrate an optimal synergy between ablative and thermomechanical vibration mechanisms. Rigorous multi-modal characterization incorporating SEM-EDS microscopy, oxygen content quantification, and metallographic analysis confirms exceptional performance metrics, including 98.7% oxide removal efficiency and 43.2% reduction in substrate surface roughness relative to standard methods. The developed protocol achieves a 2.8-fold expansion of the operational parameter space while establishing a novel “coarse-to-fine” hierarchical cleaning paradigm. These findings offer fundamental insights into laser–matter interactions while delivering a transferable technological framework for high-value manufacturing sectors, particularly in automotive and aerospace component production. Full article

Two-dimensional (2D) group-IV materials are promising for spintronics due to their silicon compatibility and tunable properties. In this work, we investigate the structural, electronic, magnetic, and optical properties of semi-hydrogenated 2D SiGe random alloys—where hydrogen atoms saturate only one side of the atomic plane—using density functional theory and many-body perturbation theory ($G{W}_0$). Substitutional disorder is modeled via representative high-symmetry configurations introduced by Baldereschi and co-workers to enable quasiparticle and optical simulations in large supercells. We demonstrate that these semi-hydrogenated alloys possess an intrinsic magnetic semiconducting ground state, arising from the electronic structure of the system, with an integer magnetic moment of $1{\mathsf{\mu }}_{\mathrm{B}}$ per primitive cell. The spin-resolved electronic structure features nearly flat frontier bands and a finite energy gap, which is significantly renormalized by quasiparticle corrections while maintaining robust spin polarization. These properties remain remarkably stable across different realizations of chemical disorder and over a wide range of alloy compositions considered in this work. Optical spectra calculated within the random phase approximation reveal a composition-dependent red-shift of the low-energy onset in the imaginary part of the dielectric function, consistent with the evolution of the quasiparticle electronic structure and the persistence of flat spin-polarized frontier bands. Our findings establish semi-hydrogenated 2D SiGe random alloys as a resilient model platform to explore interaction-driven magnetism in disordered two-dimensional systems, while simultaneously offering realistic prospects for spintronic and magneto-optoelectronic applications in the presence of chemical disorder. Full article

The development of fully biodegradable poly(3-hydroxybutyrate) (PHB)-based materials with improved mechanical performance remains a major challenge due to the limited ductility and processability of this highly crystalline polymer. Blending and plasticisation are viable strategies to enhance PHB toughness; however, the interactions governing polymer–plasticiser compatibility and their impact on structure–property relationships remain not fully understood. In this work, the compatibility and plasticisation mechanisms of two citrate-based plasticisers, tributyl citrate (TBC) and acetyl tributyl citrate (ATBC), were systematically investigated in biodegradable blends based on PHB, polylactic acid (PLA), and poly(butylene adipate-co-terephthalate) (PBAT). Polymer–plasticiser affinity was evaluated through Hansen Solubility Parameters and interaction radius, which indicated good compatibility of PHB with both plasticisers and a stronger affinity for ATBC. Differential scanning calorimetry showed that citrate plasticisers reduced the glass transition temperature, modified crystallisation kinetics, and altered the crystalline morphology of the blends. Dynamic mechanical analysis confirmed the reduction in the glass transition temperature of PHB–PLA systems, which is in agreement with the DSC results. Migration experiments showed equilibrium after approximately 72 h, with PHB–PLA blends exhibiting better plasticiser retention than PHB–PBAT systems. TBC consistently showed higher migration than ATBC, in line with its lower molecular weight and higher volatility. Mechanical testing demonstrated that plasticisation efficiency strongly depended on blend composition: TBC was more effective in enhancing ductility in PHB–PLA blends, whereas ATBC performed better in PHB–PBAT systems. It was also highlighted that the plasticisers had a remarkable ability to substantially increase the ductility of the blends compared with their unplasticised counterparts, as reflected by the pronounced decrease in stiffness and the marked increase in elongation at break. SEM analysis of tensile fracture surfaces evidenced a brittle failure mode for PHB–PLA blends, whereas PHB–PBAT systems exhibited a ductile fracture mode with fibrillar features and clear signs of phase separation. Finally, thermogravimetric analysis showed no appreciable thermal degradation within the processing temperature window used for mixing and hot pressing, confirming the thermal stability of the materials under the selected conditions. These findings establish clear correlations between thermodynamic compatibility, migration behaviour, thermal properties, fracture mechanisms, and mechanical performance, providing useful guidelines for the design of citrate-plasticised PHB-based biodegradable materials. Full article

Among numerous atmospheric-pressure plasma jets (APPJs), high industrial acceptability has been reached for the ones based on high-voltage, low-current, vortex-stabilized arc, typically operated with kHz DC-pulses. This review explores the interrelations between the “process” in a chemical–physical sense and “process”, or to better differentiate, “processing” in the sense of technological treatment, with respect to such APPJs. The mutual dependence of the processing requirements (e.g., high processing speed, compatibility with robotic processing, low total cost of ownership, reliability, and long service intervals) and the physical and chemical processes in the plasma jet are analyzed. The focus is on the hybrid character of the produced plasma, comprising a non-equilibrium arc and a diffuse plasma. Different operation modes of the gliding arc discharge (GAD) are discussed. The reviewed chemical processes are the generation of reactive oxygen–nitrogen species (RONS), oxidation and reduction reactions, and interactions with vapors, solids, and liquids. The considered processing examples are established applications, such as surface activation, cleaning, oxide reduction, film removal, and coating, as well as emerging applications for sterilization and plasma-activated water (PAW) production. Full article

Sustainable EV charging infrastructure is fragmented by proprietary applications, vendor lock-in, and weakly time-differentiated pricing, blunting its contribution to urban-mobility decarbonisation. This paper asks whether an open-protocol, super-app-mediated photovoltaic–storage charging architecture can jointly resolve these three fragmentations under deployed field conditions and what its sustainability profile then looks like. We report a campus photovoltaic–storage microgrid integrating heterogeneous EV chargers under an open, vendor-neutral charging-control protocol with super-app authentication and payment replacing dedicated charging applications and a time-differentiated tariff aligned at the meter-interval level with the underlying utility wholesale rate; the deployment is exercised through a researcher-scheduled commissioning campaign of 13 sessions designed to establish functional correctness across the operating envelope rather than to measure user behaviour. Three results emerge across cross-vendor compatibility, onboarding friction, and grid alignment. First, basic message-level OCPP compatibility is sustained across two charger vendors under a single cloud management system—in sequential single-vendor sessions—including the full charging profile up to near-rated DC peak power. Second, the super-app-mediated workflow, which requires no charging-specific application installation and no new charger-operator account, structurally eliminates the dedicated application installation and the email/SMS/credit-card verification round-trips of conventional onboarding, compressing measured first-use end-to-end interaction to 31 s; relative to reconstructed commercial-operator baselines, this is, to the best of the authors’ knowledge, an order-of-magnitude reduction rather than a controlled benchmark. Third, mid-day energy delivery aligns incidentally with the utility off-peak window, not user-driven demand shifting, while PV-displacement and BESS-discharge contributions to charging are bracketed by scenario rather than being separately metered. The paper’s contribution is therefore a replicable, policy-embedded sustainable charging architecture validated at field scale within the New Taipei Net-Zero Carbon Demonstration Site Programme, with no claim of global novelty; the same architecture is structurally positioned to convert the observed incidental grid-friendliness into a deliberate, user-facing benefit via a hardware-free mid-day-discount redesign. Full article