Search Results (6,493)

Wet cracks caused by leakage often exhibit visual and structural distortions due to surface contamination, salt crystallization, and corrosion byproducts. These factors significantly degrade the performance of sensor- and vision-based crack detection systems. In moist environments, the initiation and propagation of cracks tend to be highly nonlinear and irregular, making it challenging to distinguish crack regions from the background—especially under visual noise such as reflections, stains, and low contrast. To address these challenges, this study proposes a segmentation framework that integrates a dedicated preprocessing pipeline aimed at suppressing noise and enhancing feature clarity, all without altering the underlying segmentation architecture. The pipeline begins with adaptive thresholding to perform initial binarization under varying lighting conditions. This is followed by morphological operations and connected component analysis to eliminate micro-level noise and restore structural continuity of crack patterns. Subsequently, both local and global contrast are enhanced using histogram stretching and contrast limited adaptive histogram equalization. Finally, a background fusion step is applied to emphasize crack features while preserving the original surface texture. Experimental results demonstrate that the proposed method significantly improves segmentation performance under adverse conditions. Notably, it achieves a precision of 97.5% and exhibits strong robustness against noise introduced by moisture, reflections, and surface irregularities. These findings confirm that targeted preprocessing can substantially enhance the accuracy and reliability of crack detection systems deployed in real-world infrastructure inspection scenarios. Full article

In specific altitude ranges, biotic and abiotic factors can impact vector mosquitoes’ adaptation capacity, affecting their population differentiation. This study analyses if there exist morphological and genetic differences in four Anopheles (Kerteszia) populations in specific altitude ranges from the Colombian pacific coast to the premontane humid forests in Valle del Cauca, Colombia. Likewise, it is compared if the vector mosquito groups analyzed were genetically similar to the ones available in the region. Traditional and geometric morphometric analysis and the molecular marker CO-I were used. The research found that vector mosquitoes’ littoral populations differentiated morphologically according to their cross veins wing shapes compared to the other three groups in higher altitudes. Their genetic distances fluctuate between 4.95% and 6.84%, indicating that vector mosquitoes’ littoral populations belong to Anopheles neivai s.s. while the ones of higher altitudes are related to An. neivai 8—a lineage previously proposed based solely on molecular data. The study concludes that vector mosquitoes at the pacific Colombian coast from the littoral area in lower altitudes maintain a vast genetic variability with uniform populations; however, in higher altitudes, vector mosquitoes acquire molecular and morphological differences that may include the settlement of other lineages. Full article

The use of human stem cell-based embryo models (hSCBEM) in implantation research is developing rapidly. This raises regulatory and ethical issues as these models become more complex and get closer to morphological and functional identity with human embryos. This paper provides an analysis of two possible approaches to resolving the regulatory issues. The first approach is to try to achieve consistency with current regulation of embryo research, and the second approach is to elaborate the regulation of hSCBEMs based on their developmental potential. It is shown that both approaches are problematic. The consistency approach is problematic because the current regulation of embryo research is best understood as being the result of a historical, political compromise in most jurisdictions. And the approach based on assessment of developmental potential is problematic because of unavoidable epistemic uncertainty about the potential of a new hSCBEM, and because of problems in determining what constitutes a particular model, and what changes to a model makes it into a different model. Full article

Heat source parameters are critical input variables in welding thermal analysis, directly and significantly affecting the accuracy of the temperature field distribution, welding distortion, and residual stress prediction. This is particularly important in safety-critical welded structures, where high-precision heat source parameter identification is essential for ensuring the thermal simulation accuracy and mechanical performance reliability. Traditional parameter identification methods based on finite element simulations or experiments have limitations in adapting to complex working conditions and variable environments. To address this, this paper proposes the Heat Source Parameter Identification Network (HSPINet) model based on a residual convolutional neural network (ResNet) architecture with an attention mechanism capable of extracting key features from the weld morphology of T-joint structures, while accounting for the influence of process parameters and joint dimensions to achieve efficient and accurate identification of heat source parameters. This study not only enhances the intelligence level of heat source parameter identification but also provides a practical, intelligent tool for welding simulation and thermal field evaluation in complex industrial applications, demonstrating significant theoretical value and broad applicability in laser processing and manufacturing scenarios. Full article

Research and development in the field of glass-based laser additive manufacturing continues to receive significant interest within scientific and industrial contexts. In particular, powder bed fusion by laser radiation (PBF-LB) enables the additive manufacturing of porous and vitrified, complex three-dimensional components. The present study investigates the glass morphology that can be achieved using PBF-LB for components made from alkali borosilicate glass. The investigations focus on the comprehensive analysis of the entire process window, including the characterisation of porous and molten glass morphology. In particular, the influence of different laser-beam diameters, which are achieved through defocusing, and the variation in volume energy density are examined in detail and compared with conventional shaping. It was determined that the process of mechanically stable shaping is constrained to temperatures above the softening temperature and relative component densities within the range of ρrel = 37.8…94.2%. Furthermore, it has been demonstrated that the process-related line-like energy input results in the formation of characteristic vitrification strands. This research contributes to the overall understanding of the producible glass morphology and the process limitations of the PBF-LB process. In addition, the entire range of glass morphologies, ranging from open-pored to closed-melt configurations, could be analysed for the first time. Full article

Lithium-ion batteries (LIBs) have become the dominant energy storage technology due to their versatility and superior performance across diverse applications. Silicon (Si) stands out as a particularly promising high-capacity anode material for next-generation LIBs, offering a theoretical capacity nearly ten times greater than conventional graphite anodes. However, its practical implementation faces a critical challenge: the material undergoes a ~300% volume expansion during lithiation/delithiation, which causes severe mechanical stress, electrode pulverization, and rapid capacity decay. In addressing these limitations, advanced polymer binders serve as essential components for preserving the structural integrity of Si-based anodes. Notably, self-healing polymeric binders have emerged as a groundbreaking solution, capable of autonomously repairing cycle-induced damage and significantly enhancing electrode durability. The evaluation of self-healing performance is generally based on mechanical characterization methods while morphological observations by scanning electron microscopy provide direct evidence of crack closure; for electrochemically active materials, electrochemical techniques including GCD, EIS, and CV are employed to monitor recovery of functionality. In this study, a novel self-healing copolymer (PHX-23) was synthesized for Si anodes using a combination of octadecyl acrylate (ODA), methacrylic acid (MA), 2-hydroxyethyl methacrylate (HEMA), and polyethylene glycol methyl ether methacrylate (PEGMA). The copolymer was thoroughly characterized using NMR, FTIR, TGA, SEM, and EDX to confirm its chemical structure, thermal stability, and morphology. Electrochemical evaluation revealed that the PHX-23 binder markedly improves cycling stability, sustaining a reversible capacity of 427 mAh g⁻¹ after 1000 cycles at 1C. During long-term cycling, the Coulombic efficiency of the PHX-23 polymer is 99.7%, and similar functional binders in the literature have shown similar results at lower C-rates. Comparative analysis with conventional binders (e.g., PVDF and CMC/SBR) demonstrated PHX-23’s exceptional performance, exhibiting higher capacity retention and improved rate capability. These results position PHX-23 as a transformative binder for silicon anodes in next-generation lithium-ion batteries. Full article

Retinal vessel segmentation is crucial for analyzing medical images, where symmetry in vascular structures plays a fundamental role in diagnostic accuracy. In recent years, the rapid advancements in deep learning have provided robust tools for predicting detailed images. However, within many scenarios of medical image analysis, the task of data annotation remains costly and challenging to acquire. By leveraging symmetry-aware semi-supervised learning frameworks, our approach requires only a small portion of annotated data to achieve remarkable segmentation outcomes, significantly diminishing the costs associated with data labeling. At present, most semi-supervised approaches rely on pseudo-label update strategies. Nonetheless, while these methods generate high-quality pseudo-label images, they inevitably contain minor prediction errors in a few pixels, which can accumulate during iterative training, ultimately impacting learner performance. To address these challenges, we propose an enhanced semi-supervised vessel semantic segmentation approach that employs a symmetry-preserving pixel-level filtering strategy. This method retains highly reliable pixels in pseudo labels while eliminating those with low reliability, ensuring spatial symmetry coherence without altering the intrinsic spatial information of the images. The filtering strategy integrates various techniques, including probability-based filtering, edge detection, image filtering, mathematical morphology methods, and adaptive thresholding strategies. Each technique plays a unique role in refining the pseudo labels. Extensive experimental results demonstrate the superiority of our proposed method, showing that each filtering strategy contributes to enhancing learner performance through symmetry-constrained optimization. Full article

Psathyrostachys huashanica (2n = 2x = 14, NsNs) and Leymus mollis (2n = 4x = 28, NsNsXmXm) are important wild relatives of common wheat. The Ns chromosomes from two species have been successfully introgressed into wheat through distant hybridization. To compare the genetic effects and evolutionary relationship of Ns chromosomes from different genera in a wheat background, wheat-P. huashanica derivative WH15 and wheat-L. mollis derivative WM14-2 were selected. Sequential FISH-GISH showed that both WH15 and WM14-2 contained 40 wheat chromosomes (with 2D deletion) and two Ns chromosomes with different FISH karyotypes. Molecular markers and SNP array analysis revealed that the two lines both introduced 2Ns chromosomes. However, the P. huashanica 2Ns and L. mollis 2Ns had distinct sequence compositions, and the different SNPs between the two species 2Ns chromosomes were primarily clustered on the short arm. WH15 and WM14-2 exhibited significant differences in spike-related morphologies but shared leaf rust resistance and susceptibility to powdery mildew and Fusarium head blight. Cytogenetic analysis confirmed stable meiotic inheritance of the introduced 2Ns chromosomes. We further developed universal diagnostic markers for 2Ns chromosomes based on SLAF-seq. Therefore, substantial divergence likely exists between the Ns genomes of P. huashanica and L. mollis, and P. huashanica is probably not the direct Ns genome donor for Leymus. Our research-developed derivatives provide unique resources for comparative studies of the structural and functional evolution of homoeologous Ns chromosomes across genera, while offering valuable alleles for wheat improvement. Full article

Aeolian sand is the primary geological material for construction in desert regions, and its stabilization with industrial solid wastes-based geopolymer (ISWG) provides an eco-friendly treatment replacing cement. This study comparatively investigated the enhancement effects of chemical activators and expansive agents on compressive strength of aeolian sand stabilized by ISWG (ASIG). Three chemical activators—NaOH, Ca(OH)₂, and CaCl₂—along with two expansive agents—desulfurized gypsum and bentonite—were considered. Through X-ray diffraction, thermogravimetric analysis, scanning electron microscopy, mercury intrusion porosimetry and pH values tests, the enhancement mechanisms of the additives on ASIG were elucidated. Results demonstrate that the expansive agent exhibits significantly superior strengthening effects on ASIG compared to the widely applied chemical activators. Chemical activators promoted ISWs dissolution and hydration product synthesis, thereby densifying the hydration product matrix but concurrently enlarged interparticle pores. Desulfurized gypsum incorporation induced morphological changes in ettringite, and excessive desulfurized gypsum generated substantial ettringite that disrupted gel matrix. In contrast, bentonite demonstrated superior pore-filling efficacy while densifying gel matrix through a compaction effect. These findings highlight bentonite superior compatibility with the unique microstructure of aeolian sand compared to conventional alkaline activators or expansive agents, and better effectiveness in enhancing the strength of ASIG. Full article

Latent heat thermal energy storage (LHTES) based on phase change materials (PCMs) is receiving increasing interest since it offers high energy storage density while enabling the integration of variable renewable energies, hence boosting the transition towards a climate-neutral future. Despite the advantages that PCMs offer in providing a nearly isothermal solid–liquid phase transition, they still face some challenges that limit their deployment in real applications such as low thermal conductivity, phase separation, and supercooling, which affect charging and discharging rates. X-ray computed tomography (XCT) is a non-destructive imaging technique widely used in materials science for both qualitative and quantitative analysis of material microstructures and their evolution. Recent advances in laboratory-XCT instrumentation enabled short acquisition times on the order of tens of seconds which allows the investigation of dynamic processes in situ by time-lapse XCT measurements. These advances open new opportunities for revealing information on the morphology of solid–liquid PCMs. Despite the fact that XCT imaging has significant potential for energy research, its application in the field of PCMs is fairly new. A key enabler of applications of XCT to PCMs is the density difference between solid and liquid PCMs, which was found to be higher than 7% for all investigated PCMs. This enabled solid and liquid phases to be distinguished one from the other and properly quantified over time. The present work reviews the principles of laboratory-based XCT and the recent applications of XCT technology in the characterisation of PCMs, with emphasis on the study of the solid–liquid phase transition and validation of numerical PCM models by addressing the potentialities and challenges of XCT in PCM research. Full article

The development of advanced wound dressing materials with enhanced antibacterial properties is critical for improving patient outcomes and reducing infection risks. This study introduces a novel bio-based aerogel composed of copper-crosslinked alginate and hyaluronic acid, synthesized using supercritical gel drying techniques. Alginate and hyaluronic acid polymers are widely used in the pharmaceutical and medical industries because of their nontoxicity, biodegradability, and biocompatibility. This study aimed to create an aerogel that could be used as a potential wound dressing material by crosslinking hyaluronic acid and alginate with copper. The bio-based aerogel was prepared by ionic gelation and supercritical gel drying. The prepared materials were characterized using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), BET surface area analysis, and energy-dispersive X-ray fluorescence (XRF). Moreover, the aerogel wound dressing properties were evaluated in terms of fluid uptake and antibacterial activity against S. aureus and E. coli. The physicochemical characterization of the prepared aerogels revealed their unique structural and morphological features, which are influenced by copper ion concentration and crosslinking time. Regarding their wound dressing evaluation, both aerogel and hydrogel were found to have antibacterial properties when tested on S. aureus with inhibition zones of (36 mm, 23 mm) and E. coli (31.6 mm, 21 mm) for hydrogel and aerogel, respectively. Also, excellent fluid uptake was found to reach up to 743%. These findings underscore the potential of copper-crosslinked alginate–hyaluronic acid aerogels as innovative wound dressing materials that combine superior antibacterial efficacy with excellent fluid management, paving the way for improved wound healing solutions. Full article

In this study, a full factorial experiment was conducted to investigate the interactive effects of different red-to-blue light ratios (with R–B ratios of 0.6, 1.2, and 2.4) and photosynthetic photon flux densities (PPFDs of 200, 250, 300, and 350 μmol·m⁻²·s⁻¹) on the growth, biomass accumulation, and nutritional quality of spinach (Spinacia oleracea L.) in a plant factory using substrate cultivation. The results demonstrated that both LED light quality and light intensity had significant regulatory effects on spinach’s morphological development, pigment biosynthesis, photosynthetic activity, and nutritional quality. The treatment combining an R–B ratio of 1.2 with a PPFD of 300 μmol·m⁻²·s⁻¹ produced the most favorable outcomes, resulting in the largest leaf area (98.3 cm²), the highest net photosynthetic rate (16.4 μmol·m⁻²·s⁻¹), and the greatest shoot fresh mass (48.7 g·plant⁻¹). Moreover, this treatment also led to the highest vitamin C content in the leaves and a notable reduction in nitrate accumulation. Correlation analysis revealed significant positive relationships (r ≥ 0.70) between leaf number and shoot fresh mass, chlorophyll content, and vitamin C content. Principal component analysis further indicated that PC1 and PC2 jointly accounted for 83.4% of the total variance, with growth-related and quality-related traits contributing primarily to PC1 and PC2, respectively. Among all treatment combinations, the R–B ratio of 1.2 and 300 μmol·m⁻²·s⁻¹ condition achieved the highest comprehensive performance score. These findings underscore the critical role of finely tuned LED light environments in optimizing spinach productivity and nutritional quality in a controlled environment. Based on the results, an R–B ratio of 1.2 combined with a PPFD of 300 μmol·m⁻²·s⁻¹ is recommended as the optimal lighting strategy for spinach cultivation in plant factories. Full article

As cities densify and lifestyles become increasingly individualized, older adults face heightened risks of isolation and reduced wellbeing. Yet in historic Chinese neighborhoods, everyday socio-cultural practices—square dancing, Mahjong, community gardening and street markets—continue to foster social cohesion and spatial familiarity. This study employs Christopher Alexander’s pattern-language framework to examine how these practices are spatially embedded across six traditional neighborhoods in Chengdu. Drawing on systematic field observation, photographic surveys and typological mapping, it identifies recurring spatial configurations that support older adults’ participation and cultural continuity. While many canonical patterns remain relevant, the analysis shows how several require contextual reinterpretation to reflect Chinese collectivism, threshold sociability and informal public-space use. Synthesizing these insights, the paper develops a pattern-based design toolkit for culturally sensitive urban regeneration, contributing to age-friendly planning grounded in lived spatial practices. Although centered on six historic neighborhoods in Chengdu, the findings are intended primarily for Chinese heritage-led regeneration and—where comparable high-density morphologies, edge conditions and management regimes exist—are cautiously transferable to heritage districts elsewhere. Full article

Populus species are highly susceptible to wetwood formation, which adversely affects tree growth, timber quality, and wood processing. In this study, 28 aerobic and 7 anaerobic bacterial strains were isolated and purified from I-69 poplar trees infected with wetwood using tissue-based pathogen isolation techniques. Preliminary screening identified three highly pathogenic isolates, including two aerobic strains (AB4 and AB14) and one anaerobic strain (ANAB1), all of which induced wetwood symptoms in 100% of inoculated seedlings with pronounced severity. Through comprehensive characterization, including morphological analysis, physiological–biochemical profiling, and 16S rRNA gene sequencing, these strains were taxonomically classified as Pantoea agglomerans (AB4), Escherichia fergusonii (AB14), and Enterobacter hormaechei (ANAB1). These 35 strains were subsequently inoculated into one-year-old healthy poplar seedlings through three distinct methods, including stem injection, root infection, and leaf infection. Experimental results demonstrated that only stem injection successfully induced wetwood symptoms, while root and leaf infection failed to produce pathological manifestations. For stem-inoculated specimens, pathogenicity was evaluated based on three diagnostic parameters, including heartwood discoloration length, pigmentation intensity, and affected tissue area ratio. Significant variability in symptom severity was observed among different bacterial strains. These findings expand the known diversity of bacterial species associated with wetwood development and provide valuable insights for understanding its etiology and for guiding future disease management strategies. Full article

In this paper, we use molecular phylogenetics, micro-CT scanning, and morphological analyses to describe a new species of goby, Pascua marecoralliensis, and demonstrate that the genus Pascua is distinct from Hetereleotris, as supported by five diagnostic characters, including modified basicaudal scales and reduced sensory papillae patterns. Phylogenetic analysis places Pascua as sister to the Gobiodon group, while Hetereleotris forms a separate clade. The new species, P. marecoralliensis, differs from congeners in fin ray counts, cephalic pore patterns, and head morphology and exhibits unique live colouration. Additionally, we reclassify Hetereleotris readerae and H. sticta as Pascua readerae and P. sticta based on shared genus-specific traits. The distribution of Pascua spans the southern Pacific, suggesting a relict lineage or undiscovered diversity in the genus. This work underscores the importance of integrative taxonomic approaches for resolving cryptic diversity in gobioid fishes and highlights the need for further sampling in understudied regions. Full article