Search Results (11,044)

Amid continuous urban population growth and urbanization’s environmental and social challenges, livable cities have become a key priority for governments. Among the various factors influencing urban livability, architectural design integrating natural elements plays a critical role. Melbourne consistently ranks as one of the world’s most livable cities, with its Central Business District (CBD) serving as its core. Since a previous study has highlighted a research gap concerning the role of architecture in livable cities and indicated that the characteristics of biophilic architecture remain unclear, this study addresses the following question: What are the attributes of biophilic architecture in the CBD of the livable city of Melbourne? Subsequently, buildings exhibiting characteristics of Biophilic architecture were surveyed, and photographs capturing the most representative aspects of each building were documented. These characteristics were then coded and analyzed using statistics. The study found that Biophilic architecture is extremely rare in Melbourne’s CBD, with only four of 6375 properties (0.06%) identified as such. The most prominent attributes include connection to nature, natural color tones, and light modulation shaped by the city’s grid layout and strong sunlight. However, the dominance of concrete structures and heritage regulations constrains formal diversity. While Melbourne may not provide abundant examples, its context offers valuable insight into how urban form and policy shape biophilic expression. Future studies should extend this comparative approach to other cities to better understand context-specific adaptations of biophilic design. Full article

Aging is a major risk factor for neurodegenerative diseases in which microglia-driven neuroinflammation plays a critical role in neuronal dysfunction and disease progression. In this study, we sought to isolate bioactive metabolites from Quercus acuta Thunb. fruits—which have traditionally been used in oriental medicine but are chemically and pharmacologically underexplored—and evaluate their anti-neuroinflammatory potential. A total of 14 compounds were isolated from an ethanol extract of Q. acuta fruits through bioactivity-guided isolation, and their structures were identified by NMR spectroscopy. Notably, this study is the first to demonstrate that 3,5,7,2′,6′-pentahydroxyflavanone and 2,5-dihydroxybenzaldehyde, among the compounds isolated from Q. acuta fruits, exhibit significant anti-neuroinflammatory activities. Both compounds reduced the production of proinflammatory mediators, including IL-6 and TNF-α, while inhibiting the expression of iNOS and COX-2. Moreover, they significantly inhibited NF-κB activation in lipopolysaccharide-induced BV2 microglia. Collectively, these findings indicate that Q. acuta fruits contain bioactive constituents with previously unreported anti-neuroinflammatory properties, supporting their potential as a natural source for the development of therapeutic agents targeting age-related neuroinflammation. Full article

Under the dual pressures of urbanization and climate change, vertical greening plays a crucial role in compensating for limited urban green space and in enhancing both landscape quality and ecological functions. To improve plant selection strategies for vertical greening, this study quantified the photosynthetic adaptability of ten green wall species across light gradients on all four building facades. Over three years of in situ monitoring, combined with analyses of photosynthetic parameter variation (P_max, LCP, and LSP) and biomass, we evaluated the physiological and ecological response mechanisms of plants with different growth forms at multiple scales (“trait–species–community”). The main findings are as follows: (1) Photosynthetically active radiation intensity had the order of south wall > east wall > west wall > north wall, with differences of 3–5 fold. (2) Cluster analysis of photosynthetic traits revealed a sensitivity hierarchy: monocotyledonous herbs > dicotyledonous herbs and vines > woody species. Woody plants such as Ligustrum sinense, Ligustrum japonicum, and Rhododendron spp. showed significantly lower variability in photosynthetic parameters (45.8–64.5%) than herbaceous species, thereby maintaining strong stability under light gradients. Muehlenbeckia complexa (Mc) adapted to intense south-facing light, while Acorus gramineus ‘Ogon’ (Ag) preferred the weaker light of north-facing walls. In contrast, Farfugium japonicum (Fj), Carex oshimensis (Co), Trachelospermum jasminoides (Tj), and Vinca major (Vm) displayed substantial physiological fluctuations. (3) Based on three years of monitoring data, we developed a quantitative model of light adaptation driven by the coefficient of variation (CV) of photosynthetic parameters. Together with PCA-based clustering, we proposed a “growth form–orientation” synergistic configuration framework. Woody plants with high photosynthetic stability are recommended as the structural backbone for cost-efficient green walls, supplemented by vine/herbaceous species selected according to wall orientation. This study not only provides a scientific basis for accurate plant selection and low-maintenance design of green walls but also provides technical strategies for integrating multifunctional green infrastructure with low-carbon urban development. Furthermore, the proposed approach can be standardized as a Nature-Based Solutions (NbS) pathway for widespread application to building facades in high-density cities worldwide. Full article

The modification of lignocellulosic fibers through controlled swelling and impregnation plays a decisive role in tailoring their structure and reactivity for use in sustainable composite materials. In this study, holocellulose fibers were swollen in various solvents (sodium hydroxide at 2 and 4 wt% and ethanol–water mixtures at 0, 50, 70, and 100 wt%) to evaluate their impact on swelling and fiber characteristics. The pulp was produced with peracetic acid at 90 °C for 120 min from spruce wood chips and used for the swelling treatment. The fibers underwent swelling for 4 h in the different solvents, both without and with solubilized lignin at concentrations of 10 and 30 g/L, to investigate the impregnation ability of the fibers for lignin as a natural binder. Fiber morphology, lignocellulosic composition, and liquid retention values were analyzed to assess the effects of solvent–binder interactions on fiber swelling and lignin uptake. The results revealed significant differences in fiber characteristics influenced by both solvent choice and lignin presence, demonstrating the feasibility and optimization potential of a single-step swelling-impregnation process. These findings highlight key factors that can improve the uptake of natural binders in wood fibers, offering insights for effective fiber preconditioning in composite production. Full article

The digital economy plays a transformative role in enhancing energy efficiency and promoting sustainable development globally. As a key manifestation of digital governance, e-government has emerged as a vital instrument for accelerating the digital transformation of public administration and modernizing governance systems. This study examines the impact of digital governance on urban energy efficiency by analyzing China’s E-Government Pilot City (EPC) policy as a quasi-natural experiment. Using a Difference-in-Differences (DID) approach and balanced panel data from 282 prefecture-level cities (2006–2020), we find that the EPC policy significantly improves total factor energy efficiency (TFEE) by an average of 2.60%. Mechanism analyses reveal that digital governance enhances energy efficiency through industrial structure upgrading, green technology innovation, and foreign direct investment attraction. Heterogeneity analyses indicate that the policy’s benefits are more pronounced in larger, non-resource-based, and non-old industrial base cities, as well as in regions with stronger institutional environments and advanced digital infrastructure. However, spatial spillover effects suggest that while the EPC policy boosts local energy efficiency, it may inadvertently reduce efficiency in neighboring areas due to competitive dynamics and industrial relocation. These findings underscore the importance of tailored and coordinated policy designs to maximize the energy efficiency benefits of digital governance. Full article

Natural enemies play a vital role in pest suppression and ecological balance within agricultural ecosystems. However, conventional vision-based recognition methods are highly susceptible to illumination variation, occlusion, and background noise in complex field environments, making it difficult to accurately distinguish morphologically similar species. To address these challenges, a multimodal natural enemy recognition and ecological interpretation framework, termed MAVC-XAI, is proposed to enhance recognition accuracy and ecological interpretability in real-world agricultural scenarios. The framework employs a dual-branch spatiotemporal feature extraction network for deep modeling of both visual and acoustic signals, introduces a cross-modal sampling attention mechanism for dynamic inter-modality alignment, and incorporates cross-species contrastive learning to optimize inter-class feature boundaries. Additionally, an explainable generation module is designed to provide ecological visualizations of the model’s decision-making process in both visual and acoustic domains. Experiments conducted on multimodal datasets collected across multiple agricultural regions confirm the effectiveness of the proposed approach. The MAVC-XAI framework achieves an accuracy of 0.938, a precision of 0.932, a recall of 0.927, an F1-score of 0.929, an mAP@50 of 0.872, and a Top-5 recognition rate of 97.8%, all significantly surpassing unimodal models such as ResNet, Swin-T, and VGGish, as well as multimodal baselines including MMBT and ViLT. Ablation experiments further validate the critical contributions of the cross-modal sampling attention and contrastive learning modules to performance enhancement. The proposed framework not only enables high-precision natural enemy identification under complex ecological conditions but also provides an interpretable and intelligent foundation for AI-driven ecological pest management and food security monitoring. Full article

Acoustic cavities play a role in many technological applications in civil, naval, and aerospace engineering. This study examines the vibroacoustic performance of a forced oscillating top membrane of a cylindrical container fully filled with a compressible and nonviscous fluid. For the case of harmonic motion and using Helmholtz’s equation, the velocity potential is deduced, and the acoustic pressure is obtained using Bernoulli’s linearized equation. Taking into account the dynamic equation for the membrane with the interacting fluid with the different terms expanded in a modal series and after an integration procedure over the membrane surface, a simple analytical quadratic equation is deduced, and the coupled natural frequencies of the membrane are obtained. For the case of forced vibrations, a transfer function is obtained for calculating the frequency spectrum response of the fluid–membrane interacting system. In particular, the membrane deformation spectrum and the acoustic cavity pressure spectrum are obtained for different location points. Moreover, the spectrum of the mean quadratic values of the membrane deflexion and acoustic pressure are deduced, along with its variation with different parameters such as drum height, membrane radius, fluid density, load position, sound speed, and membrane tension. The variation in sensitivity with frequency and other different parameters is also analysed. The results are contrasted with those obtained by other authors to validate the present work. Full article

Immobilization of yeast cells represents a significant advance in alcoholic fermentation. Compared to traditional methods that rely on the use of free cells, immobilized systems enable higher cell density, easier separation and reuse of biocatalysts, and improved fermentation control, all while maintaining cellular activity. The choice of immobilization material plays a key role in performance. Natural polymers such as alginate provide biocompatibility, but the main drawback is their insufficient mechanical strength. On the other hand, synthetic polymers offer greater durability but raise concerns regarding food safety and cost. Three-dimensional (3D) bioprinting is emerging as a promising solution, enabling the design of structural, customizable matrices with precise cell positioning and tunable physical properties. Traditional materials are undergoing reengineering as bioinks, while new synthetic and hybrid materials are being developed to overcome the limitations of conventional carriers. These innovations combine biocompatibility with mechanical stability and functional adaptability for industrial use. Although the application of 3D bioprinting to produce such carriers has shown promising progress, challenges remain in scalability, process integration, and long-term stability under industrial fermentation conditions. For these reasons, continued interdisciplinary research is necessary to further develop advanced techniques for immobilizing yeast cells for use in alcoholic fermentation. Full article

Background and Clinical Significance: The paper investigates the use of the Histolog^® Scanner, a confocal microscopy–based device, as a potential tool for intraoperative neuropathological diagnosis of brain tumors. Traditional intraoperative diagnosis, relying on frozen sections and squash preparations, can introduce artifacts and consume valuable tissue. The Histolog^® Scanner offers a plug-and-play solution capable of acquiring high-resolution images of fresh tissue surfaces in minutes while preserving tissue for further histological or molecular analyses. Cases Presentation: Three clinical cases—two women and one-man, mean age 57.3 years—undergoing neurosurgery for distinct brain lesions were included. Tissue samples were immersed in fluorescent dye, rinsed, and immediately analyzed with the Histolog^® Scanner before standard intraoperative histopathology. In the first case, a glioblastoma wild-type, traditional methods struggled to define tumor margins, whereas the device provided rapid, detailed imaging to guide resection. In the second case, a meningioma, the scanner confirmed lesion identity quickly, eliminating the need for a cryostat and reducing artifacts. In the third case, a brain metastasis, integration with cytological apposition allowed simultaneous assessment of lesion margins and nature without freezing the tissue. Conclusions: The Histolog^® Scanner demonstrated multiple advantages: rapid intraoperative use, clear margin visualization, preservation of tissue for subsequent analyses, reduce unnecessary resection, thereby helping to lower the risk of recurrence. This device may complement standard intraoperative methods, enhancing diagnostic accuracy and influencing postoperative treatment planning. Overall, the Histolog^® Scanner represents an innovative tool combining speed, precision, and tissue preservation, suggesting a promising role in establishing a new standard for intraoperative neurosurgical diagnosis. Full article

Third-wave cognitive-behavioral therapies (CBT3) have progressively shifted the focus of psychotherapy from symptom reduction to process-based and transdiagnostic mechanisms of change, emphasizing self-identification as a core dimension. Within this evolution, the Self-Identification Program (SIP) represents a conceptual and clinical advancement particularly relevant to mood disorders, where maladaptive self-identification, rumination, and self-judgment play central roles. SIP directly targets dysfunctional self-identification—the reification of transient and maladaptive mental contents as defining features of a self—through a framework integrating the three levels of CBT3: mindfulness (CBT3.1), loving/kindness and compassion (CBT3.2), and deconstructive insight into the nature of a self (CBT3.3). Theoretically, SIP aligns with dimensional psychiatry (AMPD, HiTOP, RDoC) and recent advances in behavioral linguistics (Relational Frame Theory) and psychotherapy (Process-Based Behavioral Therapy). By integrating linguistic, affective, and neuroscientific perspectives, SIP bridges contextual behavioral science and contemplative practice, offering a unified, process-based model of identity transformation. Clinically, SIP extends CBT3 beyond mindfulness and loving/kindness and/or compassion training to specifically address the mechanism by which self-identification becomes a source of suffering—namely, the mistaken identification with an independent and permanent self. In doing so, SIP provides a novel, mechanistically grounded pathway toward enduring change in depressive and bipolar spectrum disorders. Full article

Missionary periodicals during the late Qing dynasty played a crucial role in introducing, translating, and systematizing Western scientific knowledge, thereby facilitating China’s transition from the traditional epistemic frameworks of “Lixue” to modern academic disciplines. Situated within a framework of knowledge transmission and disciplinary formation mediated by Chinese Christianity, this study moves beyond prior scholarship that mainly focused on individual missionary figures such as Young John Allen or specific publications like The Church News. Instead, it adopts a broader perspective, employing an integrated quantitative and qualitative analysis to examine their collective role in scientific modernization and disciplinization. The research argues that translational activities in these publications fundamentally reshaped China’s knowledge landscape. It specifically traces the semantic evolution of “Gezhi” (格致) and the transformation of “Lixue” from a moral-philosophical tradition toward the modern natural sciences. By reconstructing this process, the paper illuminates how Chinese Christianity contributed to knowledge structuring and academic modernization, highlighting its significant impact on contemporary disciplines such as Translation Studies. The findings underscore the multifaceted interactions among religious media, knowledge production, and social change. Full article

Ulex europaeus L. has been introduced into many countries as an ornamental and hedgerow plant, and it often escapes its intended location, establishing dense, feral thickets. These thickets threaten the structure and function of native flora and fauna in areas where the plant has been introduced. Because of its invasive nature, U. europaeus is considered one of the world’s 100 worst alien invasive species. It exhibits rapid growth, and high biomass accumulation with a high nitrogen fixation ability. Its flowering phenology depends on local conditions and population. It produces a large number of viable seeds and establishes extensive seed banks. These seeds remain viable for a long time due to physical dormancy. Ulex europaeus produces elaiosomes on the seed surface that are likely used solely for seed dispersal by ants. Ulex europaeus has a high level of genetic diversity due to its allohexaploid chromosome sets. This allows the plant to adapt to different habitats and tolerate various climate conditions. It can survive in areas with limited sunlight beneath tall plant canopies. Its shade tolerance surpasses that of other shrub species. Ulex europaeus produces several compounds, including quinolizidine alkaloids, monoterpenes, flavonoids, and cinnamic acid derivatives. These compounds play a role in defensive responses to biotic stressors, including pathogen infections, herbivorous insects, and neighboring plants competing for resources. These life history traits and defensive abilities may contribute to the expansion of U. europaeus populations into new habitats, enabling the plant to thrive as an invasive species. This is the first study to examine the invasiveness of U. europaeus in terms of its growth, reproduction, ability to adapt to different conditions, and defensive responses to biotic stressors. Full article

Glyphosate is the most widely used herbicide worldwide and in Mexico; however, its effects on soil microbiota in traditional agroecosystems remain unclear. We evaluated bacterial, archaeal, and fungal responses to commercial glyphosate in three representative karst soils of the Yucatán Peninsula (black Leptosol, red Leptosol, and red Cambisol) historically associated with the Mayan milpa system. The high-throughput sequencing of the 16S rRNA V4 and ITS1 regions was used to assess diversity patterns and differential abundance. Glyphosate application did not significantly alter alpha or beta diversity; however, fifteen taxa classified at the genus level exhibited shifts in relative abundance. Most bacterial taxa were depauperated in treated soils, whereas others, such as Arthrobacter, were enriched after application, indicating the presence of tolerant or resistant bacteria that may play a role in glyphosate degradation. Cordyceps, an entomopathogenic fungus, was depleted, indicating potential for natural pest control. The similarity of the core microbiota between samples with and without glyphosate application indicates that these communities are resilient. Overall, under short-term exposure, glyphosate induced compositional shifts in specific taxa without major effects on community structure but with potential implications for soil functionality and resilience in the Mayan milpa. Full article

Traffic anomaly detection plays a crucial role in improving road safety and enabling timely responses to abnormal events. Recent research has explored generative and predictive models to enhance detection accuracy; however, the dynamic and complex nature of traffic scenes often introduces noise and uncertainty, reducing reliability. This work presents TGU-Net, a Temporal Generative U-Net framework designed for real-time traffic anomaly detection in urban environments. The proposed model integrates two key innovations: (1) a temporal modeling component that captures dependencies across consecutive frames, and (2) contextual scene enrichment that enhances the distinction between normal and anomalous behaviors. These additions mitigate reconstruction noise and improve detection robustness without compromising computational efficiency. Experimental evaluations on a synthetically generated CARLA-based dataset demonstrate that TGU-Net achieves strong performance in precision, recall, and early anomaly detection, confirming its potential as a scalable and reliable framework for real-world traffic monitoring systems. Full article

Common Weakness Enumerations (CWEs) and Common Vulnerabilities and Exposures (CVEs) are open knowledge bases that provide definitions, descriptions, and samples of code vulnerabilities. The combination of Large Language Models (LLMs) with vulnerability knowledge bases helps to enhance and automate code vulnerability repair. Several key factors come into play in this setting, including (1) the retrieval of the most relevant context to a specific vulnerable code snippet; (2) augmenting LLM prompts with the retrieved context; and (3) the generated artifact form, such as a code repair with natural language explanations or a code repair only. Artifacts produced by these factors often lack transparency and explainability regarding the rationale behind the repair. In this paper, we propose an LLM-enabled framework for explainable recommendation of vulnerable code repairs with techniques addressing each factor. Our method is data-driven, which means the data characteristics of the selected CWE and CVE datasets and the knowledge base determine the best retrieval strategies. Across 100 experiments, we observe the inadequacy of the SOTA metrics to differentiate between low-quality and irrelevant repairs. To address this limitation, we design the LLM-as-a-Judge framework to enhance the robustness of recommendation assessments. Compared to baselines from prior works, as well as using static code analysis and LLMs in zero-shot, our findings highlight that multifaceted LLMs guided by retrieval context produce explainable and reliable recommendations under a small to mild level of self-alignment bias. Our work is developed on open-source knowledge bases and models, which makes it reproducible and extensible to new datasets and retrieval strategies. Full article