Search Results (13,033)

Against the backdrop of accelerating urbanization and population aging, urban parks have emerged as significant venues for enhancing the physical and mental well-being of older adults. The age-friendly quality of these spaces is directly linked to health equity and urban inclusiveness. Using the high-density historic district of Beilin in Xi’an as a case study, we developed an innovative assessment tool to evaluate the age-friendliness of park walking environments. Guided by the Health Impact Assessment (HIA) framework, this tool integrates subjective perceptions and objective data to diagnose environmental strengths and weaknesses across four dimensions: accessibility, safety, comfort, and health-related interactivity. Based on multi-source data and quantitative analysis, the study revealed key variations in the age-friendly attributes of different parks. Our field assessment focused on three representative park types: urban comprehensive, historic–cultural, and community leisure parks. The key findings are: (1) Safety was perceived by experts as the most critical dimension for older adults’ health experience, with a weight of 0.49, accounting for nearly half of the total. However, significant variations exist in safety quality across different types of parks. (2) Age-friendly performance differed profoundly among park types. Benefiting from systematic management, the urban comprehensive park achieved balanced performance and a total score of 84.87. In contrast, the historic–cultural park, constrained by its linear morphology and historical functions, scored the lowest at 66.03, exhibiting notable deficits in safety and comfort. The community leisure park, while vibrant in community activity, attained an intermediate score of 74.76 due to insufficient attention to safety details. (3) The assessment outcomes highlight the association of park typology, site selection, and design sophistication with the lived experience and potential health benefits for older adults. This study provides a refined evaluation tool and tailored optimization strategies for the age-friendly renovation of diverse park types. Full article

Soils in industrially influenced areas are often exposed to elevated nickel (Ni) levels due to metallurgical and alumina production activities. In this context, this study evaluated bauxite residue (BR) as an amendment to mitigate Ni availability and mobility in five agricultural soils from the Attica region, Greece, selected according to their pH values. Apart from the pH, soil properties were greatly varied. A very small amount of 1% BR (w/w) was incorporated into soils and batch adsorption experiments with eight Ni concentrations ranging between 1 and 90 mg Ni L⁻¹ were performed, followed by the direct application of the Tessier sequential fractionation scheme. BR addition increased the Ni adsorption capacity of soils, particularly those of low and neutral pH. BR increased the pH of acid soils, thus increasing the negatively charged sites on soil colloids. The Langmuir b_L constant provided indications of advanced Ni surface precipitation in the presence of BR. However, the desorption results suggested that, in addition to pH, Fe-Mn free oxides, noticeably those of amorphous form, controlled Ni fractionation in the studied soils. The mobility factor (MF) showed that the availability of Ni was restricted in all soil–BR mixtures. Yet, the distribution of Ni among the chemically active phases was different depending mainly on Fe-Mn free oxide content. Due to its high content in iron oxides, BR assisted the retention of Ni in soils with low Fe-Mn oxide concentration and increased significantly the Ni proportion extracted from the reducible phase. However, in soils richer in Fe-Mn oxides, BR incorporation resulted in enhanced oxidizable and residual fractions, suggesting stronger Ni binding. The results demonstrate that even a low BR application effectively enhances Ni immobilization by increasing adsorption capacity, shifting Ni toward more stable geochemical fractions, and significantly reducing its mobility, highlighting its potential as a sustainable soil amendment for Ni-contaminated soils. Full article

Peptidyl arginine deiminase 4 (PAD4) is a Ca²⁺-dependent enzyme that catalyzes histone citrullination and plays a central role in chromatin decondensation during neutrophil extracellular trap (NET) formation. Dysregulated PAD4-mediated NETosis contributes to the pathogenesis of diverse inflammatory and immune-related diseases, including autoimmune disorders, cancer, and thrombosis. Although several synthetic PAD4 inhibitors have been developed, their therapeutic application has been limited by issues related to selectivity, irreversible covalent reactivity, and suboptimal pharmacokinetic properties, prompting growing interest in natural products as alternative modulators of PAD4 activity and NETosis. This article presents a structural and mechanistic overview of natural products that target PAD4 and regulate NETosis. Based on enzyme kinetics, structural analyses, and functional validation, natural PAD4 modulators are classified into four categories: (i) active-site-directed inhibitors that bind within the U-shaped substrate tunnel, (ii) mixed and active-site-adjacent inhibitors that engage surface pockets flanking the catalytic site, (iii) allosteric and hybrid modulators that bind to regulatory regions distinct from the active site, and (iv) functionally validated PAD4 binders supported by biophysical and cellular evidence. Integration of structural, biochemical, and cellular data highlights that indirect or noncanonical modes of PAD4 regulation represent biologically coherent strategies for controlling pathological NETosis. Full article

To address the challenges posed by strong environmental disturbance during field observations of dust dispersion at highway construction sites, this study investigates the transport and diffusion patterns of construction dust (PM₁₀) by integrating numerical simulation with on-site measurements. Based on particle sampling parameters and wind conditions obtained from the target project, a construction PM₁₀ dispersion model was established using computational fluid dynamics (CFD). The wind direction that best matched the measured field data was selected as the reference condition, and the dispersion behavior of construction dust was simulated under different wind speeds and particle mass flow rates. The results indicate that larger wind-direction angles facilitate vertical dispersion of particulate matter, and higher wind speeds enhance long-distance transport while reducing near-source concentrations. Dust-suppression performance increases with barrier height, and under a low wind speed of 2 m·s⁻¹, a 3 m barrier achieves a PM₁₀ suppression efficiency of 73.6%. These findings provide quantitative evidence and technical support for PM₁₀ control in highway construction environments. Full article

Background: The H1N1 influenza A virus evades host immunity through continuous antigenic drift, posing a significant challenge to broad-spectrum neutralizing antibody therapies. This study aims to systematically evaluate the neutralizing capacity of the broad-spectrum antibody C12H5 against H1N1 strains from different eras and identify key immune escape mutation sites. Methods: Three representative H1N1 virus strains from 2009, 2018, and 2023 were selected. An antigen–antibody binding prediction model based on the ESM-2 large language model was constructed by integrating 48,762 GISAID sequence data and deep mutation scanning data from the Bloom laboratory. Candidate escape sites were screened using SHAP (SHapley Additive exPlanations) value analysis. Mutant viruses were constructed via reverse genetics, and their neutralizing capacity and replication fitness were validated through hemagglutination inhibition assays, microneutralization assays, and viral growth kinetics analysis. Results: Machine learning scoring identified five potential escape sites, with K147 exhibiting the highest overall score (0.92). SHAP analysis revealed that the K147 site within the HA protein’s 130-loop region received the highest importance score (0.28), significantly surpassing other candidate sites. Experimental validation revealed that the K147N mutation reduced neutralizing potency against C12H5 by 8-fold (from 1:1024 to 1:128) and approximately 6-fold in microneutralization assays (from 8.3 log₂ to 5.7 log₂), while exhibiting a replication advantage in MDCK cells. Microneutralization assays further confirmed an approximately 6-fold reduction in neutralization sensitivity. Structural analysis indicated that K147 is located at the periphery of the HA receptor-binding domain, immediately adjacent to the receptor-binding site. Conclusions: K147N is identified as the critical mutation mediating C12H5 immune escape, and this mutation has emerged in 2023 circulating strains. This study provides important molecular targets and early warning mechanisms for broad-spectrum antibody optimization and influenza vaccine updates. Full article

This study focuses on the spatial variation in seed germination characteristics of Picea glauca and P. mariana, prominent and widespread species within the Canadian boreal forest. The main objective was to determine seed germination requirements of geographically distinct seed collections of P. glauca and P. mariana. A total of 73 collections of P. glauca and 62 collections of P. mariana were selected across Canada and tested for germination under various temperatures. Base temperature (T_b) and thermal time required to reach 50% germination (TH₅₀) were derived from thermal model parameters for all seed collections. Correlation analyses between seed germination traits, geographic, and climatic variables were conducted. Base temperatures for germination of P. glauca ranged from 5.2 to 11.9 °C while P. mariana had base temperatures ranging from 6.2 to 12.8 °C, indicating a broader temperature range for the former to initiate germination. Optimal germination temperatures ranged from 15 to 20 °C for P. glauca and from 17.5 to 30 °C for P. mariana. Thermal time requirements for 50% germination were higher for P. glauca than for P. mariana, indicating that the former takes longer to germinate under the same temperature conditions. Latitudinal-related variables such as temperature of sites had a stronger influence on germination relative to precipitation or potential evaporation and affected seed viability, final germination and germination capacity of all seed sources. Seed viability was lower in northern seed collections and germination capacity was diminished at lower temperatures for both species. The results from this study can be built into models predicting shifts in boreal forest species under climate change. Full article

Background/Objectives: Transverse maxillary deficiency in growing patients can be treated using rapid maxillary expansion (RME) or slow maxillary expansion (SME) with spring-based appliances, such as the Leaf Expander (LE), but their comparative dentoskeletal effects remain debated. This study evaluated the transverse dentoskeletal outcomes of LE-based SME versus conventional RME. Methods: A systematic review was conducted in accordance with PRISMA 2020 guidelines and registered in PROSPERO. Electronic searches were performed in PubMed, Scopus, Embase, Web of Science, and Cochrane Library up to 9 January 2026. Randomized controlled trials (RCTs) comparing LE-based SME and RME in skeletally immature patients were included. Primary outcomes were transverse maxillary change; secondary outcomes included dentoalveolar side effects. Risk of bias was assessed using the RoB 2 tool, and certainty of evidence was evaluated using the GRADE framework. When possible, a meta-analysis was performed using standardized mean differences and a random-effects model. Results: Four RCTs met the inclusion criteria. Both SME and RME achieved significant transverse expansion. Meta-analysis showed no statistically significant differences between protocols for inter-canine distance, inter-second deciduous molar distance, inter-first permanent molar distance, or basal maxillary width. Intergroup differences varied by anatomical site and measurement method: RME showed greater anterior dental and skeletal transverse gains, whereas SME achieved comparable intermolar expansion with greater molar distorotation. Three-dimensional analyses indicated similar morphological enlargement. Risk of bias ranged from low to high; the certainty of evidence was low to very low for most transverse parameters and moderate only for molar distorotation. Conclusions: Both LE-based SME and RME effectively correct transverse maxillary deficiency. Quantitative synthesis showed comparable overall transverse expansion, with differences mainly related to the distribution and biomechanical pattern of dentoskeletal effects rather than the absolute amount of expansion achieved. Appliance selection should be guided by biomechanical features and individual treatment objectives. Further high-quality RCTs with standardized three-dimensional protocols and longer follow-up are needed. Full article

Zebrafish, as an emerging model organism, are widely used in in vivo pharmacodynamic and pharmacokinetic studies. Unlike direct chemical analyses that require no sample preparation, most biological samples must undergo preprocessing steps—procedures that profoundly affect analytical outcomes. This paper systematically summarizes the main methods and types of zebrafish sample pretreatment currently in use, aiming to provide a reference for future research in zebrafish sample analysis and preparation. A systematic search was conducted across PubMed, Web of Science, and CNKI for studies published between 2014 and 2024 focusing on liquid–liquid extraction (LLE), solid phase extraction (SPE), and related techniques for zebrafish drug analysis. The results indicate that traditional methods, including LLE and protein precipitation, remain prevalent due to their operational simplicity, but are limited by low enrichment efficiency and pronounced matrix effects (MEs). In contrast, advanced SPE techniques, particularly solid phase microextraction (SPME), are increasingly favored for complex biological sample processing, with key trends including technique hyphenation (e.g., SPME–high-performance liquid chromatography (SPME-HPLC), and micro-SPE–mass spectrometry (µSPE-MS)) and the development of novel sorbents. Despite these advances, current challenges persist, such as immature rapid on-site pretreatment protocols, the difficulty of balancing analytical efficiency with operational simplicity, and the lack of standardized procedures across studies. Overall, zebrafish sample pretreatment techniques are evolving toward higher efficiency, selectivity, and automation. Future research efforts should prioritize the development of intelligent, eco-friendly pretreatment methods and the establishment of unified standards to enhance the reproducibility and comparability of zebrafish-based pharmacological studies. Full article

Biophilic design has gained increasing importance in contemporary architecture due to its potential to enhance human well-being, environmental quality, and the integration of nature within built environments. While a growing body of literature exists, there remains a limited understanding of how biophilic architecture is visually expressed in diverse regional contexts. As the exterior of a building constitutes its most immediate expression, examining these characteristics is essential. This research gap raises the question of how exterior biophilic design characteristics are articulated in architectural practice within different geographic settings. To address this gap, this study examines the exterior architectural characteristics of biophilic design through selected case studies from Asia, Europe, and Australia, focusing on how these characteristics are manifested in each regional context. The research adopts a three-step methodological approach. First, on-site photographic documentation was conducted. Second, the collected photographs were systematically coded. Third, descriptive analysis was employed to examine the distribution of biophilic design characteristics in diverse regional contexts. Across all regions, biophilic attributes are most prominently manifested with natural colors, natural materials, and biomorphic or natural forms. In contrast, spatial attributes appear less consistently documented in photographs. This study is limited by its reliance on photographic analysis and a relatively small sample size. Future research should integrate multimethod approaches and expanded case studies to capture experiential and environmental dimensions of biophilic design beyond visual attributes. Full article

Linear alkylbenzene (LAB) is the main raw material used to make biodegradable detergents, and its production process is based on aromatic alkylation. HY zeolites that have undergone controlled dealumination and desilication have led industrial standards amongst solid acid catalysts because of their controllable acidity and hierarchical pore structure. Coke formation in such systems can assume a dual role, which is dependent on its condition. Though the over-deposition is known to cause deactivation by blocking the micropores, Bronsted acid-site masking, and diffusion collapse, the low-level deposition could also be done to increase the monoalkylate selectivity by the pore mouth catalysis, steric modulation, and selective suppression of secondary alkylation pathways. The critical review is done on the structural-kinetic interaction that determines the coke evolution in HY-based catalysts. In order to moderate the acid-site density and enhance hydrothermal stability, dealumination (Si/Al optimization of about 2.5 to 30–100) occurs, but to reduce deep-pore coke formation, desilication (interconnected mesopores) is created. The bimodal porosity and regulated acidity are found to be synergistic, as hierarchical HY zeolites produced through successive cycles of steam and alkaline treatments not only show LAB selectivity in excess of 90% but also exhibit much longer catalyst lifetimes. Quantitative research on the beneficial coke regime revealed that it was composed of about 36 wt% hydrogen-rich species, which were localized at the pore mouths, hence enhancing monoalkylation selectivity by 15–40%. Beyond a critical transition window (e.g., 8–12 wt.%), coke formation to condensed polyaromatic and graphitic products leads to fast deactivated coke formation, which is due to percolation limits and transport-controlled kinetics. More advanced techniques of characterization of the coke, e.g., temperature-programmed oxidation (TPO), ²⁷Al MAAS NMR, and UV-Raman spectroscopy, indicate how the coke is changed to highly structured graphitic deposits of high oxidation activation energy. Activity recovery of 85–98% is obtained in regeneration processes, including controlled oxidative calcination, microwave-based and plasma-based processes, and thermal management protocols, and it would be determined by the chemistry of the coke, its spatial distribution, and the regeneration protocols. This paper has developed a mechanistic coke control system by cross-tuning the acidity and development of an effective pore network, which led to a sustainable aromatic alkylation reaction with minimal activity loss, high selectivity, and long life. Full article

As vital repositories of Beijing’s cultural heritage, Qing Dynasty Qinwang (Prince of the First Rank) mansions offer profound insights into the era’s architectural evolution. Despite its significance, systematic architectural analysis of Prince Jingjin’s Mansion is lacking, with existing research primarily focusing on historical events. To address this gap, the present study focuses on Prince Jingjin’s Mansion as its research subject, utilizing historical document analysis, historical map comparison, field investigation, and space syntax analysis. This study investigates the succession of ownership, historical development, and architectural regulations, and outlines the complete construction process shaped by the evolution of early Qing princely mansion regulations as well as the functional transformation during the late Qing period. Furthermore, the architectural features of the mansion are explored from five perspectives: site selection, functionality, spatial layout, individual buildings, and gardens. The objective of this study is to elucidate the unique characteristics and significance of Prince Jingjin’s Mansion, thereby offering theoretical support for the development of Beijing as a renowned historical and cultural city and for the preservation and adaptive reuse of architectural heritage structures. Full article

The earthquake doublet on 6 February 2023 served as an important test in Türkiye. It helped assess the vulnerability of Türkiye’s building stock under different seismic loading conditions across a large region. The widespread destruction and casualties observed in heavily damaged cities following the 6 February 2023 earthquakes served as a warning. This urged a re-evaluation of the seismic performance assessment framework and risk mitigation strategies. Seismic isolation technology is considered the best method for earthquake-resilient design. Passive control systems are primarily preferred for use in critical facilities, such as healthcare complexes and data centers. Properly designed seismically isolated hospital buildings exhibited superior performance during the 6 February 2023 earthquakes compared to fixed-base counterparts. However, their use in residential buildings in Türkiye is still limited due to impediments such as stringent code requirements and peer review processes. This study evaluates the effectiveness of the ELF procedure in the Turkish Seismic Design Code-2018, incorporating two site-specific studies and earthquake record scaling in Antakya city center. Moreover, it examines the influence of considering directivity effects for using seismic isolation systems in regions with high seismicity. An effective and rapid evaluation procedure is employed for the inelastic response of seismically isolated residential buildings in accordance with the TSDC-2018 without needing any particular academic or commercial software. A suite of differential equations using the design parameters is arranged to represent the overall dynamics of seismically isolated buildings. Disregarding the directivity effects in site-specific studies for the selected construction site in Antakya city center can result in large earthquake demands and careful attention should be given to reconstruction studies for urban planning and more detailed studies should be carried out including other complex mechanisms experienced during the 6 February 2023 Türkiye earthquake doublet. Full article

Cross-site transfer learning is a promising approach to address data scarcity at newly deployed photovoltaic (PV) stations by leveraging knowledge from data-rich source sites. However, existing domain adaptation methods align feature representations without distinguishing physically meaningful causal relationships from site-specific spurious correlations, leading to negative transfer when local environmental conditions differ substantially between stations. This paper proposes CausalTransPV, a causal invariant representation learning framework that integrates explicit temporal causal discovery with selective domain alignment for cross-site PV power forecasting. The framework comprises three synergistic modules: (i) a multi-station temporal causal discovery module that jointly learns shared and station-specific causal graphs through differentiable acyclicity-constrained optimization with a cross-station invariance regularizer; (ii) a causal-guided disentangled encoder that decomposes representations into causal-invariant and site-specific subspaces using the discovered causal graph as a structural prior; and (iii) a causal-subspace transfer and prediction module that performs maximum mean discrepancy (MMD)-based domain alignment exclusively on the causal subspace. Experiments on the Desert Knowledge Australia Solar Centre (DKASC) multi-station dataset under varying target label ratios (0–50%) demonstrate that CausalTransPV achieves relative mean absolute error (MAE) reductions of 6.9–9.9% over the strongest baseline. Ablation studies, causal graph analysis, feature space visualization, and weather-conditioned case studies further validate the contribution of each component. These results suggest that causal-guided selective transfer offers an effective paradigm for reliable PV forecasting under data-scarce cross-site scenarios. Full article

Aiming at the problem that the multi-scale feature interaction ability of the traditional deep learning-based line selection algorithm is insufficient, resulting in the decline of line selection accuracy, a multi-scale feature fusion line selection method based on transfer learning is proposed, abbreviated as TLM-Net. Firstly, to address the issue of the insufficient generalization ability of the line selection network in small-sample scenarios, a simulation data pre-training framework is constructed, and a robust feature representation basis is established through a cross-domain knowledge transfer mechanism. Secondly, aiming at the problem of insufficient extraction of feature information by traditional algorithms, a multi-scale feature fusion network (MFFN) is designed to integrate global context information and local detail features, achieving cross-level semantic complementarity and spatial alignment optimization. Then, to enhance the representation ability of weak fault feature information, an EKA mechanism integrating variable kernel convolution is designed. The background interference is reduced through adaptive multi-region feature focusing, and the edge recognition accuracy of the model for irregular targets is improved. Finally, the pre-trained model is transferred to the target domain by adopting the transfer learning strategy, and the network parameters are fine-tuned in combination with the on-site data to achieve cross-domain adaptation of the feature space. The experimental results show that the TLM-Net algorithm’s mAP@0.5 reaches 98.5%, the accuracy rate and recall rate reach 98.3% and 96.5%, respectively, and the accuracy is improved by 37.5% compared with the original model. Full article

Objectives: This study evaluated the test–retest repeatability of semi-quantitative and volumetric features derived from artificial intelligence (AI)-assisted lesion segmentation on ¹⁸F-DCFPyL Prostate Specific Membrane Antigen (PSMA)-PET/CT imaging of patients with prostate cancer (PCa). Specifically, we assessed the reliability of maximum, minimum and total standardized uptake values (SUV_max, SUV_mean, SUV_total) and lesion volume measurements across varying lesion sizes and explored the implications of variability for clinical decision-making. Methods: We analyzed ¹⁸F-DCFPyL PSMA-PET/CT images from 22 patients with metastatic PCa. Lesion segmentation was performed using the AI-guided TRAQinform IQ technology, followed by a manual review to eliminate potential false-positive sites of uptake. Lesion-level test–retest repeatability was evaluated using 95% limits of agreement (LOA), intra-class correlation coefficient (ICC), within-subject coefficient of variation (wCOV) and Bland–Altman analysis for SUV and volumetric parameters. Lesions were stratified by size (>1 cm³ and >1.5 cm³) to assess the impact of lesion volume cut-offs on measurement variability. Results: A total of 297 lesions were analyzed, including 191 lesions > 1 cm³ and 161 lesions > 1.5 cm³. Test–retest variability was higher in smaller lesions, with narrower LOA and lower wCOV for larger lesions. SUV_max and SUV_mean exhibited lower variability than SUV_total and lesion volume. The 95% LOA for SUV_max ranged from −33.81% to +38.02% for all lesions, improving to −31.82% to +31.01% for lesions > 1.5 cm³. Similar trends were observed for SUV_mean, SUV_total, and volume. Bland–Altman plots confirmed reduced variability in larger lesions, with no significant systematic bias. Conclusions: The test–retest repeatability of AI-assisted PSMA-PET/CT features varies by feature type, with semi-quantitative features demonstrating improved repeatability relative to volumetric features. Additionally, repeatability is influenced by lesion size, with larger lesions exhibiting greater reliability. These findings highlight the importance of lesion size-dependent thresholds in response assessment and variability-aware feature selection in prognostic models. Current algorithms may be better optimized for larger lesions and higher volumes of disease, with limitations remaining in the robust detection and segmentation of smaller/more subtle lesions. Full article