Search Results (10,129)

Propolis, a resinous substance biosynthesized by honeybees from plant exudates and beeswax, has been valued for centuries in traditional medicine and is now increasingly recognized as a promising natural bioactive compound for functional food applications. Its complex phytochemical profile, mainly comprising flavonoids, phenolic acids, and terpenoids, confers potent antioxidant, antimicrobial, and anti-inflammatory properties that position it as a compelling candidate for use as a natural food preservative and bioactive additive. Despite this considerable potential, the widespread incorporation of propolis into food systems remains largely constrained by two main physicochemical limitations: its intense characteristic aroma, attributable to volatile terpenes and phenolic esters, which adversely affects sensory acceptance, and its inherent hydrophobicity, which prevents uniform dispersion in aqueous food matrices. This review critically examines three major technological strategies developed to overcome these barriers: (i) microencapsulation employing biopolymer wall materials, including alginate, chitosan, whey protein, and arabic gum, to mask organoleptic properties and enable controlled release; (ii) nanoemulsification to enhance water dispersibility and improve oral bioavailability; and (iii) the formulation of water-soluble propolis extracts through polyethylene glycol-based solvents or cyclodextrin complexation. In addition, this review provides a comprehensive assessment of the global chemical diversity of propolis and its bioactive properties as they relate to food preservation efficacy. Notwithstanding recent technological advances, critical research gaps persist regarding optimal effective concentrations, validated delivery systems, and scalable formulation strategies necessary for commercial food-grade applications. Addressing these gaps is essential for propolis to fulfill its considerable potential as a safe, widely accepted, and commercially viable natural food additive in next-generation functional food systems. Full article

Voltage source converters (VSCs), together with their inner current and outer power/voltage control loops, are fundamental building blocks in the modern, converter-dominated power systems, particularly within high-voltage DC (HVDC) frameworks. Selecting effective control methods for VSCs is essential to ensure the stability, power quality, and dynamic performance of HVDC grids. This paper seeks to advance the current body of research by delivering an in-depth, consistent, unified framework and systematic examination of VSC control architectures within HVDC networks. It thoroughly explores various control strategies for VSCs interfacing with HVDC grids, such as grid-following and grid-forming strategies, with particular emphasis on both stationary ($\alpha \beta$) and synchronous (dq) reference frames. Moreover, the paper provides a comprehensive analysis of the theoretical underpinnings and decoupled control strategies, like the feedforward decoupling of the d- and q-axis currents in the dq frame and the inherently decoupled structure of the αβ frame. Additionally, advanced filtering techniques, including Moving Average Filter (MAF), Cascaded Delayed Signal Cancellation (DSC), and LCL filters, are analyzed. In addition, harmonic mitigation strategies, like parallel/multiple resonant (PR) terms in the αβ frame and cascaded notch filters in the dq frame, are presented. Furthermore, precise power control approaches and synchronization methods are discussed in detail. Also, this paper presents a detailed comparison of the performance characteristics of phase-locked loop (PLL) and frequency-locked loop (FLL) in response to grid frequency variations. Moreover, this paper proposes circuit representations and VSC models in both synchronous and stationary reference frames. The simulation results corroborate the theoretical insights discussed in the paper under various operational conditions, including initial responses, grid disturbances, three-phase-to-ground temporary fault scenarios, harmonic distortions, and load imbalances, in terms of overshoot, settling time, active- and reactive-power fluctuation reduction, voltage unbalance factor, total harmonic distortion, and post-fault convergence time, all evaluated in accordance with the limits defined in EN-50160. This comprehensive comparison of the presented control strategies facilitates researchers in identifying the most appropriate controller depending on their specific application requirements. Full article

Hidden hunger and grassland degradation represent interconnected governance challenges in northern China’s pastoral areas. Nutrition-sensitive agriculture (NSA) has been conceptualised largely around crop-based systems, with limited attention to grassland grazing systems, where nutritional value is shaped by ecology, feeding practices, seasonality, local knowledge, and market institutions. Drawing on five rounds of fieldwork (2019–2025) across meadow, typical, and desert steppes in Inner Mongolia, this study employs a multi-case comparative design involving 92 semi-structured interviews, 58 policy documents, and long-term observations. Using reflexive thematic analysis, we develop an ecology–nutrition synergy framework to explain local practices and institutional constraints in nutrition-sensitive livestock farming. Three pathways are identified: grass–livestock nutritional balancing, scientific valorisation of native forage, and market experimentation linking ecological origin to nutritional quality. These pathways operate through three mechanisms: ecological mediation of nutritional quality, endogenous quality fluctuation as an inherent feature, and scientific codification of traditional pastoral knowledge. Four structural dilemmas constrain scaling: incompatibility between natural quality fluctuation and industrial standardisation; absence of institutional trust in nutritional premiums; short-term trade-offs between stocking control and nutritional enhancement; and fragmented cross-sectoral governance. The study extends NSA to grassland systems and offers a framework for integrating ecological protection, livestock quality, and nutrition-oriented governance in arid and semi-arid rangelands. Three theoretical contributions are advanced: (i) extending NSA’s conceptual boundary from cropping systems to natural grassland pastoral systems; (ii) embedding a nutrition-output dimension within Ostrom’s SES framework, thereby creating a triple-nested ecology–nutrition synergy framework; and (iii) specifying three grazing-system-specific mechanisms that distinguish grassland livestock systems from both crop-based and confined animal production systems. Full article

Schizophrenia remains a debilitating global health challenge where pharmacologic treatment has been stagnant for over seventy years, relying almost exclusively on the blockade of dopamine receptors. While this mechanism controls positive psychosis, it frequently fails to address negative symptoms or cognitive impairment and carries a significant burden of metabolic and motor adverse effects. This review evaluates the scientific and clinical validation of xanomeline–trospium (Cobenfy^®; investigational name KarXT), the first approved antipsychotic with a completely non-dopaminergic mechanism of action. We synthesize data ranging from the unique structural biology of the bitopic M1/M4 muscarinic receptor agonist xanomeline to the pharmacokinetic innovation of using the peripheral antagonist trospium chloride to mitigate systemic toxicity. Comprehensive analyses of the EMERGENT clinical trial program demonstrate that this combination significantly reduces heterogeneous schizophrenia symptoms with a safety profile distinct from current standards of care, specifically avoiding weight gain and extrapyramidal movement disorders. Furthermore, we contrast this success with the recent failures of other novel mechanisms and explore the potential for precision medicine through the identification of muscarinic receptor deficit biotypes. We conclude that M1/M4 muscarinic receptor agonism represents an important advance toward circuit-based therapeutics that may help overcome some of the limitations inherent to dopamine-centered pharmacotherapy. Full article

This study critically addresses the challenge of selecting optimal insulation materials for contemporary, energy-efficient building envelopes, a decision with profound environmental, structural, and occupational health consequences. The paper responds to the growing demand for sustainable, resilient solutions by comparing wool, a bio-based, regenerative material, and expanded polystyrene (EPS), a synthetic polymer widely implemented in the construction industry, and advanced laboratory testing (thermal conductivity, moisture buffering, freeze–thaw resistance) is discussed in a comprehensive synthesis of the recent literature. Also, field evaluations from European retrofits and pilot projects (UK, Denmark, Finland, Iceland, Norway, Sweden, Germany and France) further contextualize performance outcomes, and life cycle impacts are considered. Recent results reveal that wool insulation achieves a moisture buffering value (MBV) between 1.8 and 2.7 (g/m²) % RH, minimal vapor resistance (mvr = 1–2), and preserves functional and structural integrity through more than 100 freeze–thaw cycles, leading to significant stabilization of the interior microclimate and enhanced durability. In contrast, EPS delivers lower thermal conductivity (0.032–0.037 (W/mK), critical for reducing heating/cooling demand, but exhibits limited vapor permeability (lvp = 60–150 MN·s/(g·m)), increased risk of condensation and mold, and reduced compressive strength (<22% after 30 cycles), especially when ventilation details are inadequate. Hybrid envelope systems leveraging both EPS and wool are demonstrated to optimize energy efficiency (up to 23% seasonal savings) and reduce interior humidity fluctuations, while lifecycle and recycling assessments show wool panels to be markedly superior in carbon footprint reduction and circularity. The stratification of insulation layers incorporating wool for vapor and moisture control, and EPS for pure thermal resistance is emerging as best practice in sustainable retrofit and new-build projects. Recommendations highlight the necessity for rigorous laboratory validation, international standards alignment, and integrated material design for robust hygrothermal comfort and environmental performance. The review also covers wool- and EPS-based hybrid composites, showing how natural fibers can improve key mechanical properties without compromising thermal insulation performance or environmental benefits. Full article

The rapid growth of electric vehicles and electrified systems has increased the risk of bearing failures due to combined mechanical and electrical stresses. This study investigated the performance of hexagonal boron nitride nanoparticle-enhanced lithium grease under electrified conditions. Experiments based on a Taguchi L9 orthogonal array were conducted on deep groove ball bearings using a full-scale test rig at 1200 rpm with varying loads (100–300 N), currents (6–10 A), and hBN concentrations (0.1–1 wt.%). The tribo-electrical performance of nano-enhanced grease was compared with the base grease and commercial grease. It was observed that the base grease exhibited superior performance with a lower current flow, reduced vibration, and minimal surface degradation. In contrast, the hBN-enhanced grease exhibited inferior tribo-performance, with high vibrations and surface damage in electrified conditions. The surface analysis revealed features morphologically similar to white etching areas and micro-pitting. The FTIR results indicated grease degradation, while ICP-OES confirmed higher wear debris generation in the commercial and hBN-added greases. The present work indicates that additives like hBN nanoparticles do not necessarily improve performance under electrified conditions, making it important to consider the type of additives to be added during lubricant formulation. Thus, the findings emphasize the importance of lubricant formulation for controlling electrically induced bearing failures and provide insights for developing advanced greases for electric machinery applications. Full article

Early identification of anatomically significant coronary artery disease (CAD) remains a major clinical challenge despite advances in cardiovascular diagnostics. Novel circulating biomarkers may improve risk stratification and diagnostic discrimination beyond conventional parameters. We investigated the diagnostic utility of four emerging biomarkers—Phoenixin-14, Syntenin-1, Alamandine, and Cerebellin-1—for the assessment of CAD severity. In this prospective observational study, 90 participants undergoing coronary angiography were categorized into three groups: severe CAD (≥70% stenosis; n = 30), non-obstructive/non-critical CAD (<70% stenosis; n = 30), and angiographically normal controls (n = 30). Patients with acute coronary syndrome, diabetes mellitus, prior coronary revascularization, cardiomyopathy, or significant systemic disease were excluded. Circulating biomarker concentrations were quantified using the enzyme-linked immunosorbent assay. Comparative analyses, correlation testing, and receiver operating characteristic (ROC) analyses were performed to evaluate discriminatory performance. Circulating Phoenixin-14 concentrations progressively declined across the control, non-critical CAD, and severe CAD groups [40.1 (29.0–49.7) vs. 24.4 (18.5–30.1) vs. 16.7 (13.4–19.0) pg/mL, respectively; p < 0.001]. Phoenixin-14 demonstrated outstanding discrimination for severe CAD, achieving an area under the ROC curve (AUC) of 0.969 (95% CI, 0.888–0.997), with 86.7% sensitivity and 96.7% specificity at a threshold of ≤20.2 pg/mL. Diagnostic performance was substantially lower for Syntenin-1 (AUC, 0.795), Alamandine (AUC, 0.661), and Cerebellin-1 (AUC, 0.597). Phoenixin-14 also showed robust discrimination for non-critical CAD (AUC, 0.832). Biomarker concentrations exhibited correlations with metabolic indices while remaining largely independent of traditional cardiovascular risk factors. Among the evaluated novel circulating biomarkers, Phoenixin-14 demonstrated superior diagnostic performance for both obstructive and non-obstructive CAD, markedly outperforming Syntenin-1, Alamandine, and Cerebellin-1. These findings identify Phoenixin-14 as a promising candidate biomarker for CAD severity assessment and clinical risk stratification. Larger multicenter studies are warranted to validate these exploratory findings and determine their incremental value in contemporary cardiovascular practice. Full article

Offshore wind farms are increasingly and rapidly expanding due to their ability to harness strong and consistent wind energy resources. Large offshore wind farms are connected to mainland grids through High-Voltage Direct Current (HVDC) technology. However, offshore wind farms can often experience disturbances related to sudden wind changes, voltage drops/dips, faults related to converter switching, and unbalanced grid conditions which affect both the HVDC operation and wind turbine output. As a result, there is a growing need for more advanced and reliable modeling and monitoring tools. Moreover, traditional proportional-integral (PI) controllers are widely applied in wind turbines and HVDC systems due to their simple structure, easy implementation, and reliability. However, PI controllers perform poorly under non-linear and abnormal/fast-changing conditions, especially during sudden drops in wind power and grid faults. With this background, this paper first develops a digital twin model of an offshore wind farm that enables remote operation and monitoring of individual wind turbines. Also, an artificial intelligence (AI)-based controller, namely a fuzzy logic controller (FLC), is proposed to maintain transient stability of a full digital twin-based offshore wind farm connected to the HVDC grid under fault conditions. The effectiveness of the proposed FLC is demonstrated by considering a digital twin-enabled 700 MW offshore wind farm. The performance of the proposed FLC has been compared with that of the PI controller. Simulations performed by the MATLAB/Simulink software show that during the moderate voltage dip at 15 s, the PI controller experienced a 29.8% power reduction with a recovery time of approximately 9 s, whereas the FLC reduced the power drop to 23.1% and recovered within 6 s. During the severe converter disturbance at 15 s, the PI controller recorded a 36.9% power reduction compared to 23.4% for the FLC. Similarly, during the short-duration turbulence at 15 s, the PI controller exhibited a 36.73% power drop and recovered in approximately 7 s, while the FLC limited the power reduction to 19.17% and recovered within 5s. Overall, the FLC provided improved voltage stability, faster recovery, reduced oscillations, and superior fault ride-through capability compared with the conventional PI controller, demonstrating its effectiveness for digital twin-enabled offshore wind farm application. Full article

Background: Rosacea is a chronic inflammatory dermatosis characterized by vascular dysregulation, immune dysfunction, neurovascular alterations, and microbial involvement. Recent advances in understanding its pathophysiology have led to the development of targeted therapeutic strategies addressing multiple disease mechanisms. This systematic review aimed to evaluate contemporary evidence regarding emerging and established treatment approaches for rosacea. Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. PubMed, Scopus, and Web of Science were searched for studies published between 2016 and 2025. Original human studies evaluating therapeutic interventions for rosacea were included. Study selection, data extraction, and risk-of-bias assessment were performed independently by two reviewers. Methodological quality was assessed using Joanna Briggs Institute (JBI) critical appraisal tools appropriate for each study design. Results: Fifteen studies involving 537 patients with rosacea and 77 controls (614 participants in total) met the eligibility criteria. Evaluated interventions included vascular-targeted therapies, topical anti-inflammatory agents, systemic and immunomodulatory treatments, and microbiome-oriented approaches. Oxymetazoline, pulsed-dye laser, platelet-rich plasma, ivermectin, azelaic acid, dapsone, sulfur preparations, and metronidazole demonstrated clinical benefits in reducing erythema, inflammatory lesions, or overall disease severity. Emerging therapies, including tofacitinib and oral ivermectin, showed promising results in refractory disease. Microbiome-related interventions, particularly Demodex-targeted therapies and Helicobacter pylori eradication, were also associated with clinical improvement. Risk-of-bias assessment identified two studies with low risk of bias, twelve with moderate risk of bias, and one study with high risk of bias. Conclusions: Current evidence supports a multimodal and mechanism-based approach to rosacea management, integrating vascular, inflammatory, immunological, and microbiological targets. However, the available evidence remains limited by small sample sizes, heterogeneous methodologies, short follow-up periods, and a predominance of non-randomized study designs. Large, well-designed randomized controlled trials are needed to establish optimal evidence-based treatment strategies and define the long-term efficacy and safety of emerging therapies. Full article

In the field of urban traffic management, optimizing traffic signals at intersections is crucial for enhancing traffic flow efficiency. Despite advances in intelligent traffic signal control strategies through deep reinforcement learning (DRL), practical deployment challenges persist, such as abrupt changes in signal phases and significant hardware costs. This paper proposes a novel Traffic Characteristics-Guided Progressive optimization (TCGP) method that builds on classical fixed-time traffic signals. It is based on the classic fixed-time and quickly optimizes the green time ratio of intersection traffic lights by integrating the relationship between green light duration and traffic flow. Then, it efficiently explores the traffic signal cycle duration of a single intersection. Using a progressive optimization strategy, TCGP addresses the “curse of dimensionality” problem caused by a large number of intersections. TCGP ensures compatibility with traditional control methods and offers performance comparable to state-of-the-art DRL approaches, with competitive stability and computational efficiency. Evaluations with public datasets and real traffic data from Zhengzhou, Henan, China, confirm TCGP’s competitive performance and adaptability. This contributes fresh perspectives to the modernization of urban traffic systems. Full article

The growing demand for effective delivery of active ingredients in cosmetic formulations has stimulated the development of advanced carrier systems. This study evaluates the potential of the dicephalic di-N-oxide surfactant N,N-bis [3,3-(dimethylamino)-propyl]dodecylamide (C₁₂-(DAPANO)₂) as a stabilizer for aqueous dispersions of solid lipid nanoparticles (SLNs) and nanostructured lipid carriers (NLCs). Lipid nanoparticles were prepared using three classes of solid lipids—cetyl palmitate, glyceryl behenate, and stearic acid—through high-speed homogenization followed by ultrasonication. Their physicochemical properties were characterized using DLS, TEM, AFM, DSC, and TGA. All formulations exhibited particle sizes below 300 nm and a low polydispersity index (<0.30), indicating good uniformity. High absolute zeta potential values and stability studies confirmed excellent physical stability, with all dispersions remaining stable for at least 90 days at room temperature. Compared with bulk lipids, nanoparticles showed lower melting temperatures and reduced crystallinity. NLCs exhibited lower crystallization and melting temperatures than SLNs and displayed a more spherical morphology. Cytotoxicity assessment using J774.E macrophages revealed no adverse effects. These findings highlight the surfactant’s potential as a stabilizing agent for lipid-based cosmetic nanocarriers, supporting the development of stable systems with improved active ingredient loading and controlled release properties. Full article

This paper advances pump energy optimization by shifting the analytical focus from nominal efficiency to energy-optimal operating areas derived directly from in-field measurements. A structured experimental methodology is presented for reconstructing pump performance under real hydraulic and electrical conditions using existing systems and variable frequency drives. High-resolution datasets obtained from in-field testing are densified and normalized to map the operational area of pumps across flow, head, and rotational speed. The Best Electricity Use Point (BEUP) is identified as an energy-optimal area rather than a single operating point, accounting for system-level losses. Application to a municipal water supply pumping station on Kos Island (Greece) demonstrates that real operating behavior deviates substantially from manufacturer specifications and that BEUP-oriented control enables systematic reductions in energy consumption while improving hydraulic stability and mechanical stress conditions. The proposed framework supports a transition from static efficiency concepts to adaptive, measurement-driven pump operation. Full article

Building energy consumption accounts for 30% of global energy use, making building management pivotal to achieving global sustainability. Occupants have profound impacts on the building environment. Incorporating occupant-related factors into the environmental control process is essential for optimizing the efficiency of building management systems (BMSs), which thus gives rise to the concept of occupant-centric control (OCC). Conventional methods rely on simplified models and fixed schedules that fail to satisfy environmental control and occupant requirements, while constructing credible models places strict requirements on the dataset. In this paper, we propose a Model-Aware Predictive Control (MAPC) framework that can construct credible models with limited data and provide room-level control strategies to optimize the trade-off between occupant comfort and energy consumption. The technological innovations of this research are twofold. On the one hand, we design a model construction and fine-tuning method that combines data-driven subspace projection approach with physical priors that can construct credible thermal dynamic models with limited data. On the other hand, to balance the potential conflicts between enhancing occupant comfort and saving energy, we present a hierarchical decision-making mechanism that enables adaptive multi-objective room-level control considering dynamic occupant comfort requirements and energy usage. The experimental results obtained on an EnergyPlus-based simulation dataset and a publicly available dataset demonstrate that MAPC can provide room-level control strategies based on dynamic occupant requirements and user preferences and achieve superior trade-offs between occupant comfort and energy consumption. The ablation experiments also demonstrated the superiority of MAPC in constructing reliable models on limited datasets. MAPC provides pivotal support for the advancement of the intelligent buildings and sustainable indoor environment. Full article

Theranostics is a novel approach that integrates diagnostic and therapeutic efficacy on a single platform, holding great promise for precision medicine by enabling real-time monitoring of disease progression and therapeutic response. Despite significant advances, the successful development and delivery of theranostic systems are critically limited by multiple biological barriers present at systemic, tissue, cellular, anatomical, and immunological levels. These barriers restrict bioavailability, target accessibility, and therapeutic efficacy, while often increasing off-target accumulation and adverse effects. This review provides a comprehensive overview of the major biological barriers encountered in theranostic development, including physiological barriers such as plasma protein binding, renal clearance, and hepatic metabolism; anatomical barriers like endothelial linings, the blood–brain barrier (BBB), and the tumor microenvironment; cellular barriers involving membrane permeability, intracellular trafficking, and endo-lysosomal entrapment; and immunological barriers such as immune recognition, inflammatory responses, and complement activation. Special emphasis is placed on the BBB, highlighting its structural complexity, transport mechanisms, and strategies such as molecular Trojan-horse technology, receptor-mediated and adsorptive-mediated transcytosis, and nanocarrier-based approaches to enhance central nervous system delivery. The review further discusses targeted delivery challenges, including receptor heterogeneity and multidrug resistance, and critically evaluates current strategies to overcome these barriers through surface functionalization, stimuli-responsive systems, biomimetic carriers, and controlled-release mechanisms. Finally, recent advances, clinical challenges, and future perspectives—including personalized theranostics, artificial intelligence—assisted design, and next-generation barrier-penetrating systems—are explored. Overall, this review aims to provide a structured understanding of biological barriers in theranostics and highlight innovative approaches to improve their translational potential. Full article