Search Results (48,383)

This study investigates the influence of color representation, preprocessing, and thresholding strategies on unsupervised retinal vessel segmentation using computationally efficient classical image processing techniques. Nineteen image channels derived from RGB, HSV, HSL, YUV, YCrCb, CIELAB, and grayscale representations were evaluated in combination with five thresholding algorithms on the DRIVE dataset. The results demonstrate that luminance-dominant channels consistently outperform chrominance-based representations. The Moments (Tsai) thresholding algorithm provided the most robust performance across image representations, while contrast enhancement using CLAHE and white top-hat filtering significantly improved segmentation quality. In addition, the weighted combination of RGB channels was characterized by a dominant green-channel contribution (w_G ≈ 0.88–0.90) and a minimal blue-channel contribution (w_B ≈ 0–0.02), reflecting the spectral properties of retinal vasculature. The study highlights the central role of luminance information and demonstrates that task-specific optimization of color representations improves both segmentation accuracy and reliability. Although deep learning methods currently achieve state-of-the-art performance in retinal vessel segmentation, the results show that substantial optimization remains possible using classical, interpretable, and computationally efficient approaches. Full article

Material selection is crucial to hard tissue regeneration, and matching scaffold properties to those of the target tissue can improve clinical outcomes. This study compared the physicochemical, mechanical, and biological performance of fibrous scaffolds fabricated from polycaprolactone (PCL), polydioxanone (PDO), and gelatin methacryloyl (GelMA) for hard tissue regeneration. Polymeric fibers were produced by electrospinning, and their morphological, physical, and mechanical properties were characterized by scanning electron microscopy (SEM, n = 2), swelling and degradation analyses (n = 8), water contact angle measurements (n = 16), and tensile testing (n = 8). In addition, periodontal ligament stem cells (PDLSCs), alveolar bone marrow stem cells (aBMSCs), and dental pulp stem cells (DPSCs) were seeded onto the scaffolds to evaluate cell spreading (n = 4), viability (n = 8), and mineralized matrix formation (n = 6). Data were analyzed using one- or two-way ANOVA followed by appropriate post hoc tests (α = 5%). All polymers formed homogeneous fibrous scaffolds, with diameters within the nanoscale range. PDO and GelMA showed higher swelling than PCL, while PCL retained approximately 95% of its initial mass after three months. PCL and PDO showed higher elongation at break, tensile strength, and Young’s modulus than GelMA. Both PDO and GelMA displayed contact angles below 90°, with GelMA showing the lowest values. In vitro, all polymers were cytocompatible: PDO and GelMA enhanced DPSC viability at 7 days, whereas GelMA produced the highest viability for PDLSCs and aBMSCs at that time point. GelMA also promoted the highest mineralized matrix formation for DPSCs and PDLSCs, with no significant differences among polymers for aBMSCs. Overall, GelMA scaffolds promoted greater cell viability and mineralized matrix formation, while PCL and PDO provided superior mechanical properties, highlighting the importance of balancing biological and mechanical requirements when designing scaffolds for hard tissue regeneration. Full article

Glucagon-like peptide-1 (GLP-1) analogues are a major class of peptide therapeutics used to treat metabolic diseases. GLP-1-derived peptides are characterized by dynamic conformational ensembles in which folding, intermolecular assembly, and aggregation are strictly coupled processes. This study focused on the effects of sequence modifications, such as helix-promoting residues and backbone constraints on the helix-coil equilibrium, as well as lipidation, which creates competing equilibria among monomeric, oligomeric, and albumin-bound forms. These coupled equilibria simultaneously enhance pharmacokinetic properties and modulate conformational stability. We also explored how environmental conditions such as ionic concentration and temperature affect conformation, and emphasize how manufacturing processes act as external perturbations that could impact structural integrity. Moreover, we focus on the increasingly emerging new multi-agonist peptides, noting that their increased sequence complexity broadens conformational diversity and poses challenges to existing design methods. Despite significant experimental progress, predictive models capable of mapping the intricate interconnections among peptide sequences, lipidation patterns, and aggregation pathways remain critically limited. This highlights the importance of integrating biophysics, computation, and process science. The review points out that designing effective GLP-1 therapeutics rationally depends on managing conformational distributions across complex energy landscapes, not just stabilizing individual structures, in order to offer a new framework for developing the next generation of peptide drugs. Full article

Biomass–plastic co-pyrolysis has emerged as a promising thermochemical route for the valorization of mixed biomass and plastic waste streams, addressing growing challenges in waste management and resource efficiency. This review summarizes current knowledge on feedstock interactions, reactor technologies, operating conditions, and resulting product distributions. The literature indicates that co-processing biomass with plastics can enhance process performance compared to single-feedstock pyrolysis. Improvements are mainly observed in liquid product quality, increased energy content of gaseous fractions, and modified char properties, although outcomes strongly depend on feedstock composition and process conditions. Beyond technical aspects, the review highlights the relevance of co-pyrolysis within circular economy systems. Oil can be considered a secondary feedstock for the refining and chemical industries, process gas can support internal energy integration, and char may be utilized in material or environmental applications, contributing to partial closure of carbon and resource loops. Despite these advantages, the transition from laboratory-scale studies to large-scale implementation remains the major challenge for biomass–plastic co-pyrolysis. This limitation is associated with feedstock heterogeneity, contamination issues, scale-up difficulties, regulatory uncertainty, and the need for downstream upgrading of products. Overall, biomass–plastic co-pyrolysis represents a promising pathway toward circular waste valorization, but its practical relevance depends on successful system-level integration rather than laboratory-scale performance alone. Full article

Iron (Fe) and selenium (Se) deficiencies are global health concerns associated with adverse health outcomes. Plants constitute a dietary source of these elements, particularly for individuals following plant-based diets. However, plant Fe availability is limited by soil processes that reduce Fe mobility and uptake, whereas Se accumulation is constrained by the low abundance of Se in soils. Increasing Fe and Se concentrations in edible plant parts through biofortification represents a sustainable strategy to alleviate micronutrient deficiency. This review examines the mechanisms governing Fe and Se uptake, translocation, metabolism, and genetic regulation, and discusses current biofortification strategies, including agronomic practices, natural and microbial-based approaches, conventional breeding and marker-assisted selection, transgenic technologies, and nanoparticles. While cereals remain the principal targets of large-scale biofortification programs, recent advances in horticultural crops are also highlighted because of their growing nutritional and commercial importance. Current evidence indicates that integrated agronomic and genetic approaches are more effective than single interventions, although simultaneous Fe and Se biofortification remains largely underexplored. Successful biofortification is also strongly influenced by soil properties, nutrient interactions, and crop genotype. Emerging tools, including plant–microbe interactions and synthetic biology, offer promising opportunities to enhance micronutrient accumulation and bioavailability. Further research should optimize integrated Fe–Se biofortification strategies while addressing agronomic and socioeconomic constraints to support their large-scale adoption and contribute to sustainable food systems. Full article

Improving the nutritional quality of food through advanced and sustainable agricultural practices has become a key objective of modern vegetable crop production. Emphasis is placed on increasing the content of health-promoting bioactive compounds, such as vitamins and polyphenols, particularly flavonoids whose accumulation is strongly affected by various biotic and abiotic stress factors. To mitigate stress-induced limitations and enhance plant performance, biostimulants are increasingly applied. Among them, Trichoderma spp. are widely recognized for their ability to promote plant growth and resilience, primarily through enzymatic activity and the production of bioactive metabolites. The aim of this study was to evaluate the potential of the native Trichoderma sp. strain STP8 to enhance the production of bioactive compounds through seed and soil applications at planting and 26 days after planting (DAP), applied individually or in combination. A spore suspension (4 × 10⁶ spores mL⁻¹) was used. The experiment was arranged in a randomized complete block design with five replicates. At harvest (43 DAP), dry matter, ascorbic acid, chlorophyll, and carotenoid contents were determined. Additionally, flavonoids and non-flavonoids, total phenolics, individual phenolic compounds, and antioxidant capacity were analyzed. Achieved results demonstrate that the effects of the native Trichoderma sp. strain STP8 on lettuce secondary metabolism and antioxidant properties are strongly dependent on the developmental stage at which inoculation is performed, providing further insight into the stage-specific interactions between plans and Trichoderma. Practically, a single application at planting proved to be the most effective strategy for enhancing the accumulation of bioactive compounds, indicating that optimized application timing may improve the efficacy of Trichoderma-based biostimulants, while avoiding unnecessary repeated applications. These findings support the potential use of native Trichoderma strains as sustainable tools for improving the nutritional and functional quality of lettuce. Further research integrating physiological, biochemical, and molecular analyses is required to elucidate the mechanisms by which the native Trichoderma sp. strain STP8 regulates the biosynthesis of bioactive compounds in lettuce. Full article

Terahertz (THz) radiation generated through ultrafast transient photocurrent mechanisms has become a cornerstone of modern THz photonics, enabling broadband coherent emission with sub-picosecond temporal resolution. This review provides a comprehensive and mechanism-driven analysis of THz pulse generation via photo-Dember diffusion currents, surface depletion field acceleration, and biased photoconductive antenna architectures. We present a comprehensive comparative analysis of wide- and low-bandgap material platforms, including III–V, II–VI, and group IV semiconductors, as well as two-dimensional materials, topological insulators, and Weyl semimetals, highlighting how their intrinsic properties, such as band structure, carrier mobility, recombination dynamics, doping, and dielectric response, govern their THz emission efficiency, bandwidth, and spectral tunability. Special emphasis is placed on germanium (Ge), which has re-emerged as a highly promising THz source material owing to its high carrier mobility, long diffusion lengths, strain-tunable band structure, and CMOS compatibility. We highlight the roles of doping, strain-induced direct transitions, and several fabrication techniques in controlling the nonlinear photoexcited charge-carrier dynamics in Ge, thereby unlocking enhanced broadband THz performance. Finally, we explore the emerging application prospects of THz radiation, ranging from non-invasive security screening to biochemical sensing and archeological preservation. By bridging fundamental material science with scalable device architectures, this review outlines current challenges, highlights evolving opportunities in novel materials, and charts future directions towards integrated THz technologies. Full article

Polyetheretherketone (PEEK) has emerged as a promising biomaterial for orthopedic and craniofacial implants due to its favorable mechanical properties and fatigue resistance; however, its inherent chemical inertness limits effective osseointegration. In this study, femtosecond laser surface modification is explored as a strategy to enhance the bioactivity of PEEK. Based on a previously performed parametric study, controlled micro- and nanoscale surface textures were fabricated using femtosecond laser processing, enabling precise tuning of surface roughness and wettability without the need for additional chemical treatment. The modified surfaces were systematically characterized in terms of morphology, composition, and topography using scanning electron microscopy (SEM), 3D profilometry, and water contact angle measurements. Four optimized femtosecond laser-generated surface architectures were selected for the present investigation and comprehensively characterized, followed by in vitro evaluation of dental pulp stem cell adhesion, morphology, and proliferation. The results indicate that laser-induced micro/nanostructuring enhances the surface properties of PEEK, while supporting cellular attachment and favorable cell–surface interaction. Differences in the biological response were observed among the optimized laser-textured surfaces. These findings highlight the feasibility of femtosecond laser texturing as a clean, reproducible, and scalable approach for the development of next-generation, personalized orthopedic implants. Full article

Constipation is a prevalent gastrointestinal disorder with limited effective therapeutic options. Probiotics have emerged as promising microecological interventions, yet marked strain-specific efficacy and incomplete mechanistic understanding hinder clinical translation. This review systematically synthesizes evidence from human randomized controlled trials, animal studies, and mechanistic investigations on probiotic interventions for constipation. We catalog major anti-constipation strains across Bifidobacterium, Lactobacillus, Bacillus, and other genera, and summarize key findings from published meta-analyses indicating that B. coagulans improves stool consistency by 52.8%, L. paracasei demonstrates 86.3% effectiveness for incomplete defecation severity and 87.6% for PAC-SYM, while L. reuteri achieves 99.9% effectiveness on PAC-QoL. Mechanistically, probiotics act through four synergistic pathways: gut microbiota modulation, metabolite-mediated actions centered on SCFAs and 5-HT—with strains harboring the abfA gene cluster exhibiting enhanced arabinan utilization for sustained metabolite production—gut–brain axis neuro regulation, and dynamic mucosal barrier restoration. Finally, we propose a systematic four-stage screening pipeline integrating genomic pre-screening, probiotic property evaluation, in vitro functional prediction, and in vivo multi-tiered validation. This review provides a comprehensive framework for evidence-based strain selection and personalized probiotic therapy in constipation management. Full article

Climate change has been associated with an increasing occurrence of extreme wind phenomena, including hurricanes, tornadoes, and downbursts, with noticeable rises in both their frequency and severity. These events have heightened concerns regarding their devastating impacts on structures, infrastructure, and economies. To provide a comprehensive and reliable review, a large number of previous studies and scientific references were collected and carefully screened. The selection process focused primarily on studies directly related to structural engineering applications, wind-induced structural responses, tornado and hurricane loading mechanisms, and simulation techniques used in wind engineering research. References unrelated to structural behavior, engineering analysis, or wind-resistant design were excluded to maintain the technical relevance and consistency of the review. This review explores parameters influencing wind loads, focusing on tornado flow field characteristics such as swirl ratio, ground roughness, translation speed, and topography. It also examines structural properties such as geometry, material, orientation, and proximity to the tornado path that govern a building’s ability to withstand wind-induced forces. The review evaluates experimental techniques, including wind tunnel tests, tornado simulators, and numerical simulations using Computational Fluid Dynamics (CFD) to improve understanding and resilience. These approaches are compared for effectiveness in replicating real-world scenarios and enhancing predictive accuracy. Furthermore, key engineering standards, such as ASCE 7-22 and FEMA guidelines, are highlighted, showing their role in improving structural design, identifying gaps in research, and advocating for future studies. It emphasizes integrating emerging computational technologies, including machine learning, to enhance structural design efficiency and disaster response performance. This review aims to guide researchers and engineers toward developing resilient structures capable of mitigating the impacts of extreme wind events. Full article

Cementitious sand and gravel (CSG) is commonly used in construction engineering; however, its mix proportion design is complex, and traditional physical experiments face limitations such as long cycles, high costs, and susceptibility to external factors when obtaining high-quality sample data. In this study, a foundational dataset was first acquired through physical experiments: 100 sets of CSG specimens with different mix proportions (cement content 40, 50, 60, 70 kg/m³; water-to-binder ratio 1.0, 1.2, 1.4; sand ratio 0.1, 0.2, 0.3, 0.4; fly ash content 20, 30, 40, 50 kg/m³) were prepared. After 28 days of standard curing, compressive strength and splitting tensile strength tests were conducted using a WAW-1000 electro-hydraulic servo universal testing machine, yielding 100 sets of real mechanical property data. The coefficients of variation for all test groups were below 10%, confirming the reliability and repeatability of the experimental data. On this basis, a data augmentation method based on Conditional Tabular Generative Adversarial Networks (CTGAN) is proposed. Through adversarial training between the generator and the discriminator, the model learns the multi-dimensional distribution characteristics of the original CSG data and generates 100 synthetic samples, which are then merged with the original data to expand the dataset to 200 samples. The quality of the synthetic data is evaluated using Wasserstein distance and correlation matrix heatmaps. Furthermore, a hybrid XGBoost–LSTM prediction model is proposed—XGBoost is used for feature construction to capture nonlinear interactions among mix proportion variables, and the constructed features are then fed into an LSTM network for sequential learning and regression prediction. The results show that the CTGAN-generated data are highly consistent with the original data in terms of kernel density distributions and variable correlations, with Wasserstein distance significantly superior to four comparative methods: Bootstrap, SMOTE, GaussianCopula, and TVAE. After augmentation, the XGBoost–LSTM model achieves a coefficient of determination (R²) of 0.9897 for compressive strength prediction (vs. 0.9793 before augmentation) and 0.9801 for splitting tensile strength (vs. 0.9882 before augmentation, a slight decrease). The mean absolute percentage errors (MAPE) are 4.49% and 4.11%, and the root mean square errors (RMSE) are 0.201 and 0.049, respectively; both error metrics are reduced compared with those before augmentation. Compared with baseline models including XGBoost, LSTM, Random Forest (RF), and Support Vector Regression (SVR), the XGBoost–LSTM model exhibits the best performance across all evaluation metrics, and Wilcoxon signed-rank tests confirm that the performance differences are statistically significant (p < 0.05). The proposed method of CTGAN-based data augmentation combined with the XGBoost-LSTM hybrid model provides an effective solution to the problem of insufficient CSG sample data and offers a reference for data enhancement and performance prediction of other small-sample materials. Full article

Biological aerosols represent a significant challenge for modern CBRN defense due to their potential for long-range dispersion and the need for rapid threat assessment. Current stand-off detection systems are effective in recognizing anomalous aerosol clouds but often lack the molecular specificity required for reliable agent identification. This review examines the role of mid-infrared (MIR) spectroscopy as an emerging approach for chemically resolved stand-off bioaerosol sensing. The physical principles of MIR detection are discussed, including molecular vibrational fingerprints, differential scattering (DISC), and circular intensity differential scattering (CIDS), together with their relationship to aerosol optical properties and Mie resonance effects. Existing and emerging sensing architectures are reviewed, ranging from operational CO₂ laser-based DISC systems to semiconductor-based platforms utilizing tunable differential absorption lidar (DIAL), Quantum Cascade Lasers (QCLs), and dual-comb spectroscopy. The analysis highlights the ability of MIR sensing to access biomolecular signatures associated with proteins, lipids, nucleic acids, and bacterial spores, while also addressing challenges related to atmospheric attenuation, biological variability, and signal interpretation. The reviewed literature indicates that MIR spectroscopy offers a promising pathway toward improved stand-off identification of hazardous bioaerosols, supporting early threat detection and enhanced situational awareness in applications including CBRN defense, critical infrastructure protection, environmental monitoring, public health surveillance, and emergency response. Full article

This study was conducted to determine the optimal mineralization enhancement period for recycled aggregates, and to elucidate the mechanisms underlying the mineralization enhancement of recycled aggregates and the self-healing of concrete cracks. Microbial-induced calcium carbonate precipitation enables the self-healing of concrete cracks: microbial carriers can effectively increase the survival rate of microorganisms within the concrete matrix, thereby enhancing the self-healing performance of the concrete. However, current carriers suffer from poor mechanical properties, poor compatibility with cement-based materials, and high costs. This study proposed a crack-self-healing concrete based on a mixed culture of microorganisms immobilized in recycled aggregate, and investigated the effects of the time of recycled aggregate incorporation on the concrete’s compressive strength and self-healing performance. The results showed that the optimal adsorption and incubation times for the recycled aggregates were 15 min and 9 days, respectively. Following mineralization and reinforcement, the water absorption and crushing index of the recycled aggregates was 11.4% and 20.4%, respectively. Moreover, the precipitates at the concrete cracks were in the form of regular cubes and clusters, and the crystals were calcite and aragonite. Small amounts of phosphorus were detected, originating from extracellular polymers produced by microbial metabolism, indicating that the organic matrix was involved in the crystal nucleation and growth processes. The compressive strength of the concrete increased by 35%. After repair and curing, the crack healing rate of the concrete reinforced with microorganisms immobilized on the recycled aggregates reached 70%. Full article

Laser shock peening (LSP) is an advanced surface modification technique that significantly enhances the fatigue resistance of metallic components through the synergistic implantation of deep compressive residual stresses (CRSs) and gradient microstructural refinement. Existing investigations have shown that LSP can generate strengthening layers extending from several hundred micrometers to approximately 1 mm in depth, with affected zones reaching 5–6 times the depth typically achieved by conventional shot peening in representative titanium alloys. In specific cases, LSP has increased the fatigue limit from 483.2 MPa to 593.6 MPa, corresponding to an improvement of approximately 22.8%, while optimized treatment of Ti-17 compressor blades has extended fatigue life by more than two orders of magnitude. This review systematically elucidates the anti-fatigue strengthening mechanisms of LSP across a range of metallic systems, with emphasis on three key aspects: (i) the mechanistic retardation of fatigue crack initiation and propagation, mediated by CRS-induced reductions in the stress intensity factor and enhanced crack closure effects; (ii) the parametric sensitivity of surface integrity and stress field homogeneity to laser energy density, spot overlap ratio, and multiple-impact sequencing; and (iii) the process-specific characteristics of emerging LSP variants, including laser peening without coating, warm laser shock peening, and cryogenic laser shock peening. Furthermore, we critically evaluate the role of multiscale numerical simulations—encompassing macroscopic finite element analysis, mesoscopic crystal plasticity modeling, and molecular dynamics—in optimizing process parameters and predicting fatigue life. By integrating experimental, computational, and theoretical perspectives, this review establishes a coherent process–structure–property framework to guide the rational design of LSP protocols for targeted fatigue performance enhancement. Full article

This review comparatively analyzed MWCNT-reinforced thermoplastic polyester nanocomposites based on petroleum-derived (PET, PBT) and bio-based (PLA, PBS) matrices, focusing on processing methods, mechanical performance, thermal stability, electrical behavior, and recyclability. Optimal MWCNT loadings typically ranged from 0.3 to 3 wt.%; higher loadings induced nanotube agglomeration and deteriorated properties due to poor dispersion and stress concentration. Melt mixing, solution blending, direct compounding, and in situ polymerization were evaluated, and their influence on dispersion quality, interfacial bonding, and scalable manufacturability was discussed. PET exhibited the largest improvements in mechanical and thermal performance (tensile strength and modulus increases >300% in optimized systems); acid or compatibilizer functionalization of MWCNT improved PET thermal stability by approximately 20–50 °C and promoted heterogeneous nucleation. PBT reached optimal reinforcement at 0.3–1 wt.% MWCNT, yielding tensile strength increases up to ~57% alongside increased crystallinity and faster crystallization kinetics. PLA generally showed reduced tensile strength after MWCNT addition unless compatibilized (e.g., via plasticizers or grafting), whereas PBS consistently gained strength, modulus, and crystallinity but experienced reductions in ductility. Electrical percolation thresholds varied widely (0.25–14 wt.%), demonstrating that dispersion quality, nanotube functionalization, and processing route governed conductivity and percolation behavior more than matrix chemistry. Recyclability and circular economy aspects were assessed: while PET/MWCNT systems showed promise for mechanical recycling and property recovery, data on repeated reprocessing, CNT structural integrity, and long-term electrical performance were scarce; PBT recycling studies were limited, and PBS/PLA recycling with retained conductive networks remained underexplored. Based on the comparative analysis, key limitations, critical research gaps, and practical recommendations for processing, compatibilization, and end-of-life evaluation were identified to guide future work aimed at enhancing both performance and sustainability of polyester/MWCNT nanocomposites. Full article