Search Results (448)

Caffeoyl hexapeptide-9 (CH-9) is a novel cosmetic peptide designed by conjugating hexapeptide-9 (H-9), a known collagen-mimetic peptide with established skin anti-aging activity, with caffeic acid (CA) via an amide bond, leveraging peptide-drug conjugate (PDC) design principles. In ultraviolet (UV)-irradiated cellular and skin models, CH-9 outperformed H-9 in preserving cell viability, restoring collagen types I, III, and IV, and suppressing interleukin-6 and -8 secretion. Additionally, its direct antioxidant activity, absent in H-9, was demonstrated in vitro by scavenging of hydroxyl and peroxyl radicals. Molecular docking indicated CH-9 interacted with the catalytic domain of matrix metalloproteinase 2 (MMP2), a key enzyme in collagen degradation during photoaging, suggesting a potential inhibition of its activity. Molecular dynamics (MD) simulations revealed an improved insertion of CH-9 into a stratum corneum (SC) lipid bilayer compared to H-9, consistent with enhanced skin permeation in vivo. Moreover, CH-9 exhibited improved aqueous and cosmetic serum stability over CA. In a 28-day clinical study, topical application of CH-9 significantly improved skin elasticity and firmness compared to H-9. This work demonstrates that the PDC-based conjugate CH-9 combines enhanced anti-photoaging efficacy with improved transdermal permeation and stability, highlighting a promising strategy for the development of advanced cosmetic ingredients. Full article

The steel-plate–concrete composite reinforcement method is derived from the bonded steel plate and increased-section techniques. It is employed to enhance the strength of concrete structures that require a substantial increase in load-bearing capacity. To develop a flexural deformation calculation theory that accounts for slip effects in general reinforced cross-sections with bilateral symmetry, interfacial slip and deflection equations are formulated based on the relationship between interlayer slip and the rotational angle of beams in the plane, as well as the principle of force equilibrium. A numerical method, established based on this theoretical framework, is proposed to facilitate the analytical solution and is verified to be consistent with analytical results. Furthermore, the accuracy of the calculation theory is validated through bending experiments. Finally, the influence of key parameters affecting slip on the flexural stiffness of the reinforced beam is evaluated by determining the stiffness reduction coefficient according to the theory. The results indicate that the flexural stiffness of reinforced beams is governed by three non-dimensional parameters: the boundary condition parameter (μ), composite action parameter (shear connector stiffness (βl)), and relative bending stiffness parameter (G_∞/G₀). The loading mode does not affect the flexural stiffness of the reinforced beams. As βl approaches 100 and G_∞/G₀ approaches 1, η approaches 100%. In cases where high stiffness is required, reducing interfacial slip can minimize the loss of flexural stiffness in composite structures. Conservative calculations indicate that satisfying the conditions βl ≥ 8 and G_∞/G₀ ≤ 1.6 during design can ensure that the reduction in flexural stiffness of the reinforced beam remains above 90%. Full article

The continuous degradation of mangrove ecosystems, considered among the most vulnerable worldwide, reveals multiple threats driven by human activities and climate change. In the Peruvian context, particularly in the Tumbes Mangrove ecosystem, these pressures are intensified by the absence of integrated spatial and educational infrastructures capable of supporting conservation efforts while engaging local communities. In response, this research proposes a Sustainable Interpretation Center for Conservation and Environmental Education in Ecologically Sensitive Areas of the Tumbes Mangrove, Peru. The methodology includes climate data analysis, identification of local flora and fauna, and site topography characterization, supported by digital tools such as Google Earth, AutoCAD 2025, Revit 2025, and 3D Sun Path. The results are reflected in an architectural proposal that incorporates sustainable materials compatible with sensitive ecosystems, including eco-friendly structural solutions based on algarrobo timber, together with resilient strategies addressing climatic variability, such as lightweight structures, elevated platforms, and passive environmental solutions that minimize impact on the mangrove. Furthermore, the proposal integrates a photovoltaic energy system consisting of 12 solar panels with a unit capacity of 450 W, providing a total installed capacity of 5.4 kWp, complemented by a 48 V LiFePO₄ battery storage system designed to ensure energy autonomy during periods of low solar availability. In conclusion, the proposal adheres to principles of sustainability and energy efficiency and aligns with the Sustainable Development Goals (SDGs) 7, 8, 12, 14, and 15, reinforcing the use of clean energy, responsible tourism, sustainable resource management, and the conservation of marine and terrestrial ecosystems. Full article

This study presents a comprehensive digital workflow for the archaeological investigation and heritage enhancement of the Coëby megalithic necropolis (Brittany, France). Dating to the Middle Neolithic, between the 4th and 3rd millennia BC, this chronology is established through stratigraphy, material culture, and radiocarbon dating. Focusing on cairns TRED 8 and TRED 9, which are two excavation units, we combined field archaeology, photogrammetry, and topographic data with open-source 3D geometric modeling to reconstruct the monuments’ original volumes and test construction hypotheses. The methodology leveraged the free software Blender (version 3.0.1) and its Bagapie extension for the procedural simulation of lithic block distribution within the tumular masses, ensuring both metric accuracy and realistic texturing. Beyond static reconstruction, the research explores innovative dynamic and narrative visualization techniques. We employed the FILM model for smooth video interpolation of the construction sequences and utilized the Wan 2.1 AI model to generate immersive video scenes of Neolithic life based on archaeologically informed prompts. The entire process, from data acquisition to final visualization, was conducted using free and open-source tools, guaranteeing full methodological reproducibility and alignment with open science principles. Our results include detailed 3D reconstructions that elucidate the complex architectural sequences of the cairns, as well as dynamic visualizations that enhance the understanding of their construction logic. This study demonstrates the analytical potential of open-source 3D modelling and AI-based visualisation for megalithic archaeology. Full article

Background/Objectives: Autism spectrum disorder (ASD) exhibits remarkable genetic heterogeneity involving hundreds of risk genes; however, the mechanism by which these genes organize within biological networks to contribute to disease pathogenesis remains incompletely understood. This study aims to elucidate these organizational principles and identify critical network bottlenecks using a novel integrative computational framework. Methods: We analyzed 893 SFARI genes using a three-pronged computational approach: (1) a Machine Learning Dynamic Perturbation Propagation algorithm; (2) a hypergraph construction method explicitly modeling multi-gene complexes by integrating protein–protein interactions, co-expression modules, and curated pathways; and (3) Hypergraph Neural Network embeddings for gene clustering. Validation was performed using hub-independent features to address potential circularity, followed by a druggability assessment to prioritize therapeutic targets. Results: The hypergraph construction captured 3847 multi-way relationships, representing a 45% increase in biological relationships compared to pairwise networks. The perturbation algorithm achieved a 51% higher correlation with TADA genetic evidence than random walk methods. Analysis revealed a hierarchical organization where 179 hub genes exhibited a 3.22-fold increase in degree centrality and a 4.71-fold increase in perturbation scores relative to non-hub genes. Hypergraph Neural Network clustering identified five distinct gene clusters, including a “super-hub” cluster of 10 genes enriched in synaptic signaling (4.2-fold) and chromatin remodeling (3.9-fold). Validation confirmed that 8 of these 10 genes co-cluster even without topological information. Finally, we identified high-priority therapeutic targets, including ARID1A, POLR2A, and CACNB1. Conclusions: These findings establish hierarchical network organization principles in ASD, demonstrating that hub genes maintain substantially elevated perturbation states. The identification of critical network bottlenecks and pharmacologically tractable targets provides a foundation for understanding autism pathogenesis and developing precision medicine approaches. Full article

The worldwide population is anticipated to reach 10.12 billion by the year 2100, thereby amplifying the necessity for sustainable agricultural methodologies to secure food availability while reducing ecological consequences. Conventional synthetic pesticides, while capable of increasing crop yields by as much as 50%, present considerable hazards such as toxicity, the emergence of resistance, and environmental pollution. This review examines biopesticides, originating from microbial (e.g., Bacillus thuringiensis, Trichoderma spp.), plant, or animal sources, as environmentally sustainable alternatives which address pest control through mechanisms including antibiosis, hyperparasitism, and competition. Biopesticides provide advantages such as biodegradability, minimal toxicity to non-target organisms, and a lower likelihood of resistance development. The global market for biopesticides is projected to be valued between USD 8 and 10 billion by 2025, accounting for 3–4% of the overall pesticide sector, and is expected to grow at a compound annual growth rate (CAGR) of 12–16%. To mitigate production costs, agro-industrial byproducts such as rice husk and starch wastewater can be utilized as economical substrates in both solid-state and submerged fermentation processes, which may lead to a reduction in expenses ranging from 35% to 59%. Strategies for process intensification, such as the implementation of intensified bioreactors, continuous cultivation methods, and artificial intelligence (AI)-driven monitoring systems, significantly improve the upstream stages (including strain development and fermentation), downstream processes (such as purification and drying), and formulation phases. These advancements result in enhanced productivity, reduced energy consumption, and greater product stability. Patent activity, exemplified by 2371 documents from 1982 to 2021, highlights advancements in formulations and microbial strains. The integration of circular economy principles in biopesticide production through process intensification enhances the safety, quality, and sustainability of food systems. Projections suggest that by the 2040s to 2050s, biopesticides may achieve market parity with synthetic alternatives. Obstacles encompass the alignment of regulations and the ability to scale in order to completely achieve these benefits. Full article

Background/Objectives: Nipple-sparing mastectomy (NSM) is a surgical procedure that significantly improves postoperative cosmetic outcomes and quality of life (QOL) while ensuring oncological safety. However, ischemic necrosis of the nipple–areolar complex (NAC), resulting from impaired blood flow, remains a serious complication, particularly in patients with risk factors. To mitigate this ischemic risk, the Nipple Delay (ND) procedure, which applies the principle of surgical delay, has been proposed. The objective of this study was to retrospectively review cases in which the ND procedure was performed prior to NSM with immediate autologous breast reconstruction and to evaluate the safety and clinical utility of this technique in preventing NAC necrosis. Methods: This study included 30 breasts from 30 patients who underwent the ND procedure prior to NSM with autologous reconstruction at our institution. ND was performed under local anesthesia two weeks before NSM. The skin around the NAC was dissected from the underlying breast tissue. Results: The median age of the patients was 49 years, and the mean BMI was 22.7 kg/m². Risk factors for NAC necrosis included periareolar incision in 24 patients (80.0%), a BMI of 25 kg/m² or higher in 7 patients (23.3%), and a history of smoking in 8 patients (26.7%). No cases of full-thickness necrosis requiring NAC excision were observed (0%). Partial-thickness necrosis, which healed with conservative treatment, was observed in 6 patients (20.0%). No malignant involvement was detected in subareolar specimens. Conclusions: A staged approach using the ND procedure before NSM suggests effectiveness for preventing serious ischemic complications and safely expanding the indications for NSM, even in patients at high risk of NAC necrosis. Full article

Precise control over defect structures is essential for tuning the functional properties of lithium niobate (LiNbO₃) crystals. Although the threshold effect of Hf⁴⁺ doping is well recognized, its underlying atomic-scale mechanism, especially in systems co-doped with luminescent rare earth ions, remains unclear. In this study, we combine experimental and theoretical approaches to elucidate the Hf⁴⁺ concentration-driven threshold behavior in Dy: LiNbO₃ crystals. A series of crystals with Hf⁴⁺ concentrations of 2, 4, 6, and 8 mol% were grown using the Czochralski method. Characterization through XRD and IR spectroscopy identified a threshold near 4 mol%, evidenced by an inflection in lattice constants and a pronounced blue shift of the OH⁻ absorption peak. UV–Vis–NIR absorption spectra revealed a systematic enhancement of Dy³⁺f–f transition intensities, linking the global defect structure to the local crystal field of the optical activator. First-principles calculations showed that Hf⁴⁺ ions preferentially occupy Li sites, repairing antisite Nb defects ($\mathrm{N}{\mathrm{b}}_{\mathrm{Li}}^{4+}$) below the threshold, and incorporate into Nb sites beyond it, inducing structural reorganization. Electron Localization Function analysis visualized strengthened Hf-O covalent bonding in the post-threshold regime. This work establishes a complete atomic-scale picture connecting dopant site preference, chemical bonding, and macroscopic properties, providing a foundational framework for the rational design of advanced LiNbO₃-based materials. Full article

Ultra-shallow prefabricated underpass tunnel technology has been widely adopted in urban transportation construction owing to its advantages of rapid construction and minimal environmental impact. However, the deformation behavior of tunnel joints under long-term vehicular dynamic loads remains unclear, which constrains the reliability and durability of this technology. To address this, this study focuses on a large cross-section tunnel with five bidirectional lanes. A combined methodology of “refined numerical simulation + long-term cyclic loading model tests” was employed to systematically investigate the dynamic response and cumulative deformation patterns of tunnel joints under different burial depths (3 m, 5 m, and 8 m) and prestress levels (0–0.5 MPa). First, based on the analysis of structural bending moment distribution, various division principles such as zero-moment points and maximum-moment points were compared, leading to the determination of a joint layout scheme primarily adopting a two-segment division. On this basis, a refined numerical model integrating pavement excitation and vehicle dynamic coupling was established, supplemented by a model test with 2 million loading cycles, to reveal the deformation mechanism of joints under both moving vehicle loads and long-term loading. The results indicate the following: (1) burial depth is the decisive factor controlling overall joint deformation—increasing the depth from 3 m to 8 m can reduce the maximum joint opening and slip by approximately 60%; (2) prestress serves as a key measure for restraining joint opening and ensuring waterproofing performance, with its effect being particularly pronounced under shallow burial conditions; (3) based on the dynamic attenuation coefficient, the concept of “sensitive burial depth” (approximately 3.7 m) is proposed, providing a quantitative criterion for identifying tunnels susceptible to surface traffic loads; (4) the recommended two-segment structural division scheme effectively controls deformation while considering construction convenience and waterproofing reliability. The methodological framework of “numerical simulation + model testing” established in this study can provide theoretical support and engineering reference for the long-term performance design and assessment of ultra-shallow prefabricated tunnels. Full article

To address the technical bottleneck of the coordinated improvement of high-temperature rutting resistance, low-temperature cracking resistance and environmental protection performance of road asphalt, and to address the existing problems in the research of sepiolite modified asphalt, such as the ambiguous microscopic mechanism of action, the lack of quantitative relationship between dosage and performance, and the unclear adaptability of modification processes, this study employed high-purity sepiolite as a modifier. After optimizing its microstructure through organic and surface modification, the sepiolite with the best compatibility with asphalt was selected. Four dosage gradients of 2%, 4%, 6%, and 8% were designed. Rheological tests were conducted to investigate the effects of sepiolite on the rutting resistance at high temperature, the cracking resistance at low temperature, and the fatigue durability of asphalt. Gas chromatography–mass spectrometry (GC–MS) was used to analyze changes in the organic components of asphalt fumes, while Fourier-transform infrared spectroscopy (FTIR) and gel permeation chromatography (GPC) were applied to reveal the microscopic interaction mechanisms and smoke-suppression principles. Results show that pristine sepiolite exhibits the best compatibility with asphalt. Although modified sepiolite shows a 43–45% increase in specific surface area, the overall high–low temperature coordination of the modified asphalt decreases by 10–15%. The sepiolite dosage has a significant influence on asphalt performance: when the dosage is 4–6%, the rutting factor of asphalt increases by 25–30%, indicating the best high-temperature deformation resistance; at 4%, the asphalt creep stiffness decreases by over 15%, minimizing the low-temperature cracking risk; and at 2–4%, the fatigue life extends by 9–13%, with the most notable improvement at 2%. In terms of smoke suppression, the porous structure of sepiolite adsorbs 3–5% of the light volatile components in asphalt, while its metal oxides inhibit the release of aliphatic and aromatic hydrocarbons, reducing toxic fume emissions by 12–18%. Microscopically, the interaction between sepiolite and asphalt is dominated by physical adsorption without chemical functional group recombination. The fibrous network of sepiolite enhances the structural stability of asphalt, while the adsorption of small and medium molecular components optimizes the molecular weight distribution, achieving a dual effect of performance enhancement and smoke suppression. Full article

Leuconostoc mesenteroides is a key microorganism in food biotechnology, valued for its production of flavor-forming metabolites and exopolysaccharides, and its inclusion in starter cultures and biocatalytic systems. However, the application of advanced genetic tools to L. mesenteroides remains hindered by multiple barriers, including inefficient DNA transfer, elevated endogenous nuclease activity, and restriction–modification systems sensitive to plasmid methylation patterns. As a result, even widely accepted electroporation methodologies often yield inconsistent or irreproducible transformation results, limiting the strain’s amenability to metabolic engineering and synthetic biology applications. In this study, a reproducible electroporation protocol for the L. mesenteroides strain H32-02 Ksu is developed and experimentally validated. The protocol concept relies on the sequential optimization of key process steps: targeted weakening of the cell wall followed by osmotic protection, the development of a gentle electrical stimulus that ensures membrane permeability without critical damage, and the creation of recovery conditions that minimize loss of viability and degradation of incoming DNA. Matching plasmid methylation to the recipient’s restriction profile proved critical: choosing a source for plasmid DNA production with a compatible methylation pattern dramatically increased the likelihood of successful transformation. In our case, the selection of an E. coli strain with a more suitable methylation profile increased the yield of transformants by 3.5 times. It was also shown that reducing the pulse voltage increase transformant number by 3 times. The combined optimization resulted in an approximately 40-fold increase in transformation efficiency compared to the baseline level and, for the first time, provided consistently reproducible access to transformants of this strain. The highest transformation efficiency was achieved: 8 × 10² CFU µg⁻¹ DNA. The presented approach highlights the strain-specificity of barriers in Leuconostoc and forms a technological basis for constructing strains with desired properties, expressing heterologous enzymes, and subsequently scaling up bioprocesses in food and related industries. The methodological principles embodied in the protocol are potentially transferable to other lactic acid bacteria with similar limitations. Full article

To address the inherent limitations of the standard Sine Cosine Algorithm (SCA) in multi-threshold image segmentation, this paper proposes an enhanced algorithm named the Reinforcement Learning–Thermal Conduction–Sine Cosine Algorithm (RLTC-SCA), with symmetry as a core guiding principle. Symmetry, a fundamental property in nature and image processing, refers to the invariance or regularity of grayscale distributions, texture patterns, and structural features across image regions; this characteristic is widely exploited to improve segmentation accuracy by leveraging consistent spatial or intensity relationships. In multi-threshold segmentation, symmetry manifests in the balanced distribution of optimal thresholds within the grayscale space, as well as the symmetric response of segmentation metrics (e.g., PSNR, SSIM) to threshold adjustments. To evaluate the optimization performance of RLTC-SCA, comprehensive numerical experiments were conducted on the CEC2020 and CEC2022 benchmark test suites. The proposed algorithm was compared with several mainstream metaheuristic algorithms. An ablation study was designed to analyze the individual contribution and synergistic effects of the three enhancement strategies. The convergence behavior was characterized using indicators such as average fitness value, search trajectory, and convergence curve. Moreover, statistical stability was assessed using the Wilcoxon rank-sum test (at a significance level of $p = 0.05$) and the Friedman test. Experimental results demonstrate that RLTC-SCA outperforms all comparison algorithms in terms of average fitness, convergence speed, and stability, ranking first on both benchmark test suites. Furthermore, RLTC-SCA was applied to multi-threshold image segmentation tasks, where the Otsu method was adopted as the objective function. Segmentation performance was evaluated on multiple benchmark images under four threshold levels (2, 4, 6, and 8) using PSNR, FSIM, and SSIM as evaluation metrics. The results indicate that RLTC-SCA can efficiently obtain optimal segmentation thresholds, with PSNR, FSIM, and SSIM values consistently higher than those of competing algorithms—demonstrating superior segmentation accuracy and robustness. This study provides a reliable solution for improving the efficiency and precision of multi-threshold image segmentation and enriches the application of intelligent optimization algorithms in the field of image processing. Full article

One of the problems of suburbanization is the occupation of agricultural land. When defining newly built areas, the suitability of the land should be considered. The paper tries to verify, on the example of 8 selected Czech municipalities, whether the suburban-type built-up areas they define in their territories respect this principle and what proportion of these areas is located on land belonging to the highest three soil quality classes. Full article

Fibre Bragg grating (FBG) grid sensors are an underexplored technology with potential to benefit nuclear thermal hydraulics experiments. This paper presents a new FBG grid sensor consisting of 38 FBGs across 8 flow-crossing chords. Using this sensor, experiments determined for the first time that an FBG grid can detect large air bubbles rising in standing liquids—demonstrated in both columns of water and 20W50 automotive oil. The instrument’s sensitivity was quantified by comparing its measurements to high-speed camera recordings. Analysis of Bragg wavelength shift timings on each chord enabled the surface of a bubble to be reconstructed using the air–oil data. Finally, the increase in Bragg wavelength when bubbles interact with the FBG grid suggests a variant sensing principle different from that reported in the literature for FBG grids in flowing liquids. Full article

As a core component of MEMS LiDAR, the 2D MEMS mirror, with high-precision optical angle detection, is a key technology for radar scanning and imaging. Existing piezoresistive detection schemes of mirrors suffer from high fabrication complexity, high temperature sensitivity, and a limited accuracy of only 0.08°, failing to meet the requirements for vehicular and airborne scanning applications. This study focuses on a two-dimensional electromagnetic MEMS mirror. Based on the reflection principles of geometric optics, angle detection schemes with photodiode (PD) arrays are analyzed. A novel four-quadrant optical measurement sensor featuring a 16-PD array is proposed. This design replaces conventional large-area PDs with a compact PD array, effectively mitigating nonlinearity and low accuracy issues caused by oversized PD trenches and edge dimensions. High-precision detection of the mirror’s deflection angle is achieved by measuring the current variations induced by the reflected spot position on the PDs in each quadrant. The experimental results demonstrate that the 16-PD array optical angle sensor achieves an accuracy between 0.03° and 0.036° over a detection range of ±8°. Full article