Search Results (35,070)

Chitosan-based active films containing microwave-extracted Terminalia catappa leaf extract (TE) and hydrothermally synthesised zinc oxide were developed and characterised. The selected extraction condition (440 W, 20 min, followed by freeze drying) gave 29.5% extract recovery and a total phenolic content of 639.5 mg GAE/g extract. Structural analyses showed that the original crystalline ZnO phase was no longer detectable after film formation under acidic casting conditions, whereas zinc remained present in the film matrix, indicating acid-mediated dissolution and/or structural transformation during casting. Zinc-containing films exhibited higher tensile strength (up to 36.0 MPa), increased glass transition temperature (up to 122.9 °C), and reduced moisture content and water vapour transmission. TE contributed antioxidant activity and light-shielding properties, with antioxidant capacity reaching 22.1 mg Trolox/g film. Films containing ≥0.2% initial ZnO also showed disc-diffusion antimicrobial activity against Escherichia coli (up to 22.7 mm) and Staphylococcus aureus (up to 20.7 mm). A preliminary 7-day banana-wrapping study further suggested that intermediate formulations containing 0.1–0.2% TE and 0.2–0.3% initial ZnO provided a useful balance among mechanical performance, optical properties, antimicrobial activity, and visual preservation. Overall, zinc–polyphenol–chitosan interactions played an important role in governing film structure and functionality. Full article

Epidermal Growth Factor (EGF) plays an important role in skin regeneration and repair by promoting cell proliferation and collagen synthesis. However, its topical application is limited by low stability, susceptibility to degradation, and poor penetration through the stratum corneum due to its hydrophilic nature and relatively large molecular size. Microencapsulation offers a strategy to protect sensitive bioactives and improve their delivery in cosmetic formulations. In this study, EGF was encapsulated in Arabic gum/gelatine A (AG/GE) coacervate microcapsules and incorporated into a hydrating cream. The work extends previous studies using the same microcapsule composition for lipophilic compounds, demonstrating its applicability for a hydrophilic bioactive and highlighting the versatility of the encapsulation platform. The resulting microcapsules exhibited spherical, multinucleated morphology with an encapsulation efficiency of 78.8 + 1.0%. Although diffusion of microencapsulated EGF in the cream could not be directly determined, the formulation showed trends towards improvement in several skin parameters during the volunteer evaluation, including reduction in surface spots (31%), brown spots (21%) and pore visibility (10%), and improved texture (22%). A 25% decrease in transepidermal water loss and a 33% increase in elasticity suggested improved skin barrier function. Volunteers reported high acceptance regarding non-irritancy, texture, and sensory experience. Full article

Background/Objectives: Diabetic small fiber neuropathy and related sensory and epidermal problems affect up to 70% of all patients with diabetes. Long-term hyperglycemia disrupts cytoskeletal organization and axonal transport; however, molecular changes within human diabetic epidermis remain understudied. Diaph1 and its cytoskeletal ligands, including β-Actin and Profilin, are key regulators of cytoskeletal dynamics and may be associated with diabetes-related alterations in skin structure and innervation. Methods: Sixteen patients with type 2 diabetes, aged 43.3 ± 9.6 years (disease duration 18.9 ± 8.7 years), and twelve non-diabetic controls, aged 43.9 ± 8.9 years, were enrolled in the study. All participants provided informed consent. Skin punch biopsies were obtained under local anesthesia and processed for staining of PGP 9.5, Diaph1, β-Actin, and Profilin. Quantitative image analysis was performed to assess stained area fraction, signal intensity, and intraepidermal nerve fiber density. Statistical comparisons and Spearman’s rank correlation analyses were used to evaluate group differences and associations between staining parameters. Results: Diabetic skin samples exhibited a significant reduction in PGP 9.5-positive intraepidermal nerve fibers, indicating reduced cutaneous innervation. In contrast, Diaph1 and Profilin showed broader and more diffuse epidermal staining, while β-Actin displayed altered staining patterns and intensity. Significant correlations between Diaph1- and β-Actin-related staining measures indicated an association consistent with altered cytoskeletal organization under chronic hyperglycemic conditions. Conclusions: Long-standing type 2 diabetes was associated with reduced PGP 9.5-positive intraepidermal nerve fibers, together with altered epidermal staining patterns of Diaph1, Profilin and β-Actin. These findings indicate coexisting cutaneous denervation and cytoskeletal alterations in diabetic skin. Full article

Copper-containing steel is widely used in ship plates and other marine engineering fields due to its excellent mechanical properties and good weldability. However, in hydrogen-containing media environments, ship plate steel is prone to hydrogen embrittlement during service. Existing research primarily focuses on steel grades with copper content below 3 wt.%, while the diffusion and trapping behavior of hydrogen in ultra-high-copper steel with copper content exceeding 3 wt.% remains unclear. Therefore, this study designed an ultra-high-copper-content steel with a copper content of 6.01% and investigated the diffusion behavior of hydrogen in the test steel under different hydrogen charging current densities through microstructure characterization, slow strain rate tensile testing, electrochemical hydrogen permeation, and internal friction tests. The results indicate that with an increase in hydrogen charging current density, accompanied by a slight degradation in mechanical properties, the irreversible hydrogen trap density increases by 50.7%. A large number of microstructures, such as phase boundaries, grain boundaries, and dislocations, have formed inside the material, which have reversible trapping effects on hydrogen, effectively suppressing the migration of hydrogen in the crystal structure and reducing the embrittlement phenomenon caused by hydrogen. This study expands the application potential of copper-containing steel in the field of ocean engineering, providing an important reference for the future development of high-strength, hydrogen embrittlement-resistant copper steel with ultra-high copper content. Full article

ZnFe₂O₄ is a promising anode material for lithium-ion batteries (LIBs) due to its high theoretical capacity, but its practical use is limited by poor conductivity and large volume changes during cycling. To address these issues, a ZnFe₂O₄-reduced graphene oxide (Z-F-rGO) composite was fabricated via solvothermal synthesis and calcination, with Z-F nanoparticles in situ anchored on rGO sheets. Characterizations (XRD, Raman, XPS, SEM, TEM) confirm the formation of highly crystalline spinel Z-F with good interfacial contact with rGO. The Z-F-rGO electrode shows excellent electrochemical performance, maintaining a reversible capacity of 985.4 mA h g⁻¹ after 100 cycles at 0.5 A g⁻¹, significantly higher than the 498.2 mA h g⁻¹ of the Z-F. At 1.0 A g⁻¹, the Z-F-rGO electrode retains 959.4 mA h g⁻¹ after 300 cycles, while the Z-F electrode shows a capacity of 441.3 mA h g⁻¹. CV analysis indicates good reversibility, while EIS and GITT reveal reduced charge-transfer resistance and enhanced Li⁺ diffusion. This work provides an efficient strategy for scalable Z-F-rGO composites, offering a promising approach for high-performance LIB anodes. Full article

Background/Objectives: Fungal keratitis remains a vision-threatening infection, and current amphotericin B (AmphB) eye drops suffer from low corneal residence time, poor aqueous solubility, and the need for frequent dosing. This study develops electrospun nanofiber-based ophthalmic inserts combining polyvinyl alcohol (PVA), gamma-cyclodextrin (γ-CD), and sodium taurocholate (STC) to enhance AmphB solubility and provide a non-invasive, rapidly dissolving ophthalmic dosage form. Methods: γ-CD and STC-enhanced AmphB-loaded PVA nanofiber-based ophthalmic inserts with varying γ-CD and STC concentrations were prepared by electrospinning and characterized by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). Drug content, in vitro release (Weibull modeling), antifungal activity against Candida albicans, Fusarium solani, and Aspergillus fumigatus, ocular cytocompatibility using the Hen’s Egg Test on Chorioallantoic Membrane (HET-CAM), and accelerated stability (40 ± 2 °C, 75 ± 5% relative humidity, 4 weeks) were evaluated. Results: Bead-free nanofibers with mean diameters between 216 ± 33 nm and 310 ± 35 nm were obtained, and XRD confirmed complete amorphization of AmphB within the PVA nanofiber matrix, forming an amorphous solid dispersion. All formulations showed rapid and nearly complete AmphB release (≈100% within 60 min), with Weibull β values < 0.75, indicating Fickian diffusion-controlled release. AmphB-loaded PVA nanofiber-based ophthalmic inserts produced inhibition zones and broth susceptibility profiles comparable to AmphB in dimethyl sulfoxide (DMSO), demonstrating preserved antifungal activity. HET-CAM scores (0–0.9) classified the inserts as practically non-irritant, and SEM/FTIR after accelerated storage showed no relevant morphological or physicochemical changes. Conclusions: These γ-CD and STC-enhanced AmphB-loaded PVA nanofiber-based ophthalmic inserts provide a non-invasive, rapidly dissolving ophthalmic dosage form that combines amorphous AmphB, immediate drug availability, and good ocular tolerance, supporting their further development as a patient-friendly treatment option for fungal keratitis. Full article

Monitoring thermal effluent is critical for assessing aquatic ecosystem health, yet traditional satellite remote sensing and in situ point measurements often fail to capture fine-scale thermal dynamics in narrow streams and complex coastal areas due to spatiotemporal resolution limitations. This study establishes a high-precision surface water temperature mapping protocol using a low-cost Unmanned Aerial Vehicle (UAV) equipped with an uncooled thermal infrared sensor (FLIR Vue Pro R) to overcome these observational gaps. We investigated two distinct hydrological environments—an inland stream and a coastal sea—to provide initial evidence for the applicability of an in situ-based linear regression calibration model across contrasting aquatic settings. The initial uncalibrated radiometric temperatures exhibited significant bias errors reaching up to 9.2 °C in the stream and 9.4 °C in the coastal area, primarily driven by atmospheric attenuation and environmental factors. However, the proposed calibration method dramatically reduced these discrepancies, achieving Root Mean Square Errors (RMSE) of 0.43 °C and 0.42 °C, respectively, with high determination coefficients (R² > 0.87). The derived high-resolution thermal maps successfully visualized the detailed diffusion patterns of thermal plumes, revealing a steep temperature gradient of approximately 13 °C in the stream discharge zone and a distinct 5 °C elevation in the coastal effluent area relative to the ambient water. These findings demonstrate that UAV-based thermal remote sensing, when coupled with a rigorous radiometric calibration strategy, can serve as a cost-effective and reliable tool for environmental monitoring, bridging the critical scale gap between local point measurements and regional satellite observations. Full article

Background/Objectives: Central Nervous System (CNS) relapse represents a severe and often fatal complication of Diffuse Large B-Cell Lymphoma (DLBCL). This study aimed to evaluate clinical, biological, and treatment-related factors associated with progression-free survival (PFS) until CNS relapse in patients with DLBCL. Methods: A retrospective cohort study was conducted using clinical data from adult DLBCL patients evaluated and treated at the Regional Institute of Oncology, Iași, Romania, between 2015 and 2023. Associations between clinical, biological, and treatment-related variables and CNS relapse were evaluated using univariate and multivariable Cox proportional hazards models, Fine–Gray competing-risk analyses, and propensity score-based methods to address confounding by indication for CNS prophylaxis. Results: Twenty-six CNS relapse events (6.3%) and 72 deaths without prior CNS relapse occurred over a median follow-up of 12 months. In the prespecified reduced multivariable Cox model, non-R-CHOP regimens (HR 4.57, 95% CI 1.67–12.52; p = 0.003) and high CNS-IPI scores (HR 4.70, 95% CI 1.14–19.46; p = 0.033) were independently associated with CNS relapse. The 20-month cumulative incidence of CNS relapse was 7.0% in the R-CHOP-like group versus 35.2% in the non-R-CHOP group (Gray’s test p < 0.001). Fine–Gray modeling confirmed the association for non-R-CHOP regimens (SHR 3.38, 95% CI 1.21–9.45; p = 0.02). Cell-of-origin subtype, double-expressor phenotype, and Ki-67 were not significantly associated with CNS relapse. Conclusions: High CNS-IPI and treatment with non-R-CHOP regimens independently predicted earlier CNS relapse. Future multicenter studies with molecular profiling are needed to refine CNS risk stratification. Full article

Early detection of agricultural fires with Unmanned Aerial Vehicles (UAVs) is important for environmental safety, yet it remains difficult because ignition cues are extremely small, smoke patterns vary widely, and farmland scenes often contain strong background interference such as specular reflections. Model development is further constrained by the scarcity of data from the early ignition stage. To address these challenges, we propose a joint data and model optimization framework. We first build a hybrid dataset through an ROI-guided synthesis pipeline, in which latent diffusion models are used to insert high-fidelity, carefully screened fire samples into real farmland backgrounds. We then introduce EF-YOLO, a detector designed for high sensitivity to small targets. The network uses SPD-Conv to reduce feature loss during spatial downsampling and includes a high-resolution P2 head to improve the detection of minute objects. To reduce background clutter, a Dual-Path Frequency–Spatial Enhancement (DP-FSE) module serves as a lightweight statistical surrogate that extracts global contextual cues and local salient features in parallel, thereby suppressing high-frequency noise. Experimental results show that EF-YOLO achieves an AP_s of 40.2% on sub-pixel targets, exceeding the YOLOv8s baseline by 15.4 percentage points. With a recall of 88.7% and a real-time inference speed of 78 FPS, the proposed framework offers a strong balance between detection performance and efficiency, making it well suited for edge-deployed agricultural fire early-warning systems. Full article

Non-typhoidal Salmonella (NTS) is an important poultry-associated pathogen with major One Health and economic impacts, but data on its epidemiology and antimicrobial resistance in Nigeria remain limited. This study investigated the prevalence, serovar distribution, clonal relatedness, and antimicrobial resistance of NTS along the poultry production chain in Enugu State, southeastern Nigeria. A total of 2400 samples were collected, comprising feces (cecal content)/cloacal swabs from chickens (n = 1100), eggs (n = 400), chicken meat (n = 600), and stool samples from poultry workers (n = 300). Isolation and identification were performed using standard bacteriological methods, with confirmation by serotyping and polymerase chain reaction (PCR) targeting the invA gene. Genetic relatedness was assessed using enterobacterial repetitive intergenic consensus (ERIC)-PCR, and antimicrobial susceptibility was determined by the disk diffusion method. Overall, 47 (2.0%) Salmonella enterica isolates were recovered from 2400 samples, with the highest prevalence observed in eggs (3.5%), followed by human stool (3.3%), chicken meat (1.8%), and chicken feces (1.1%). Only 35 (11.8%) of the 297 sampled farms were positive for Salmonella, and recovery rates differed significantly (p = 0.0065) among sample sources. Five serotypes were identified, dominated by S. Typhimurium (57.4%), followed by S. Enteritidis (14.9%), S. Anatum (12.8%), S. Stanley (8.5%), and S. Agona (6.3%). ERIC-PCR revealed multiple clonal clusters, many containing isolates from mixed sources, indicating circulation of related strains between poultry and humans. All isolates were resistant to ampicillin, with high resistance to tetracycline (76.6%), sulphamethoxazole–trimethoprim (51.1%), and fluoroquinolones. Overall, 80.9% of isolates were multidrug-resistant, with a mean Multiple Antibiotic Resistance Index of 0.29, highest among isolates from chicken feces. Although the prevalence of NTS was low, the presence of genetically related multidrug-resistant strains across the production chain underscores the role of poultry as a reservoir for zoonotic transmission and highlights the need for coordinated One Health surveillance and antimicrobial stewardship strategies in Nigeria. Full article

This study addresses a two-dimensional anomalous solute transport process within a two-zone fractal porous medium. A mathematical formulation is developed to characterise transport phenomena in a non-homogeneous porous domain. The medium consists of two interacting regions: one containing mobile fluid and the other containing immobile fluid, between which mass transfer occurs. In the mobile-fluid region, solute transport is governed by the convection–diffusion equation. In contrast, the immobile-fluid region is described using a first-order kinetic model. The problem of solute injection through a designated boundary point is formulated and numerically implemented. The effects of anomalous transport behaviour on solute migration and filtration characteristics are examined. The study further evaluates the pressure field, filtration velocity distribution, and solute concentration in both zones. Full article

Highway ramp merging requires autonomous vehicles to make safe and efficient decisions in dense mixed traffic, where strong vehicle interactions and rapidly changing acceptable gaps make the task particularly challenging. Existing reinforcement learning methods are often unimodal and overly conservative, while diffusion-based policies, despite their ability to generate multimodal actions, usually suffer from high inference latency and safety risks caused by unconstrained sampling. To address these issues, this paper proposes AM-DIMPO, an action-mask-guided safe diffusion-implicit policy optimization framework for ramp-merging tasks. The proposed method combines DDIM-based implicit sampling with a state-dependent continuous action mask to improve multimodal action generation efficiency while enhancing action feasibility. In addition, the mask correction signal is incorporated into policy learning to encourage the policy to generate actions closer to the safe feasible region. Experiments are conducted in a Gym-based ramp-merging simulator under both light-traffic and dense-traffic scenarios, where the proposed method is compared with classical reinforcement learning baselines, diffusion reinforcement learning baselines, and a safety-aware PPO baseline. The results show that, in dense traffic, AM-DIMPO achieves a merging success rate of 97.3%, an average speed of 16.27 m/s, and an inference latency of 68 ms; in light traffic, the success rate reaches 98.1%. Moreover, the proposed method maintains robust performance under the tested noisy-observation and reduced-visibility settings. Overall, AM-DIMPO achieves a favorable balance among empirical safety, traffic efficiency, robustness, and real-time inference performance in dense highway ramp-merging tasks. Full article

This paper formulates the “Minimum Vertex Cut with Reachable Set” (MVCRS) problem as an optimization framework to suppress botnet propagation in networked systems, and clarifies its computational complexity and algorithmic solutions. Building a firewall to minimize damage is essential for addressing botnet propagation in Internet of Things (IoT) networks. We define the basic MVCRS problem as minimizing the sum of the weight of the deployed resources and the resulting propagation scope. While we demonstrate that the constrained version of the problem is NP-complete, we show that the fundamental trade-off optimization model can be solved in polynomial time by reducing it to the maximum flow–minimum cut problem. This provides a theoretical baseline for optimal resource allocation in cybersecurity. Experimental evaluations reveal the limitations of conventional heuristics. In community-structured networks, the degree-based greedy algorithm overlooks critical bridge nodes, yielding an optimality gap of up to 72.6% above the theoretical minimum cost. Conversely, our exact algorithm consistently guarantees the optimal minimum cost (a 0% gap) with high statistical stability across diverse topologies. Furthermore, it scales efficiently to solve 100,000-node IoT networks within practical time limits, proving to be a reliable and efficient foundation for botnet suppression in complex real-world systems. Full article

Water exhibits unique interfacial properties that arise from the collective organization of its hydrogen-bond network. Establishing clear links between molecular-scale interactions and macroscopic observables remains a central challenge in understanding the behavior of liquid water. In this work, we combine experimental measurements of the contact angle of sessile water drops with quantum-chemical modeling of small water clusters (H₂O)_n (n = 2–6) to explore multiscale effects of hydrogen-bond cooperativity. The cluster calculations reveal a nonlinear, saturating evolution of hydrogen-bond geometries with increasing cluster size, reflecting the onset of cooperative many-body effects. Experimentally, the evolution of the apparent contact angle during evaporation is quantified using both conventional geometry and a non-invasive geometrical-optical method based on analysis of the dark refractive ring, which provides independent validation against conventional goniometric measurements. The evaporation dynamics are further interpreted within the diffusion-limited framework of the Popov model, indicating that the temporal evolution of the apparent contact angle is primarily consistent with geometry-controlled mass loss under diffusion-limited conditions, rather than requiring variations in intrinsic surface energy. By combining macroscopic contact-angle measurements with molecular-level cluster analysis, this study offers a qualitative multiscale perspective in which minimal cooperative hydrogen-bond motifs provide molecular context for interpreting interfacial behavior, without implying direct quantitative prediction of macroscopic interfacial observables. Full article

This empirical study examines how FinTech innovation is adopted, scaled, and sustained in a small and highly regulated market, such as Latvia. The triangulated analytical framework is applied in this study, integrating Rogers’ Innovation Diffusion Theory (IDT), De Meyer’s Innovation Ecosystem framework, and Value Chain Theory. This framework analyses the relationship between innovation characteristics, ecosystem relationships, and restructuring in the value chain. The data was collected from FinTech leaders, conventional financial institutions (banks), regulators, and associations, and was analysed thematically. Based on interviews with stakeholders, the relative advantage of Latvian FinTech lies in its flexibility, speed, and trialability; however, barriers to adoption result in complex regulation, an uneven distribution of technology in infrastructure, and differences in institutional readiness. The authors found strong collaboration among the ecosystem’s players but limited proactive regulatory engagement. This research provides a replicable model for cross-border or cross-sector analysis to assess the progress of innovation in regulatory and Environmental, Social and Governance (ESG) integration. Full article